Algorithms

Electrical Impedance Tomography (EIT) is an attractive method for clinically monitoring patients during mechanical ventilation, because it can provide a non-invasive continuous image of pulmonary impedance which indicates the distribution of ventilation. However, most clinical and physiological research in lung EIT is done using older and proprietary algorithms; this is an obstacle to interpretation of EIT images because the reconstructed images are not well characterized. To address this issue, we are developing a consensus linear reconstruction algorithm for lung EIT, called GREIT (Graz consensus Reconstruction algorithm for EIT). This paper describes the unified approach to linear image reconstruction developed for GREIT. The framework for the linear reconstruction algorithm consists of: 1) detailed finite element models of a representative adult and neonatal thorax; 2) consensus on the performance figures of merit for EIT image reconstruction; and 3) a systematic approach to optimize a linear reconstruction matrix to desired performance measures. Consensus figures of merit, in order of importance, are: a) uniform amplitude response, b) small and uniform position error, c) small ringing artefacts, d) uniform resolution, e) limited shape deformation, and f) high resolution. Such figures of merit must be attained while maintaining small noise amplification and small sensitivity to electrode and boundary movement. This approach represents the consensus of a large and representative group of experts in EIT algorithm design and clinical applications for pulmonary monitoring. All software and data to implement and test the algorithm has been made available under an open source license which allows free research and commercial use.

Visual P300 responses were recorded by using checkerboard-type stimuli. 1 High amplitude P300-delta responses Ž . Ž were visible even in single trial ERPs. 2 An algorithm for efficient selection of P300 single trials based on . Ž. evaluation of delta responses is introduced. 3 The 'universal' character of the P300-delta response demonstrated in this report may open new avenues for the understanding of functional ERP components.

Quality control machinery in the endoplasmic reticulum (ER) helps ensure that only properly folded and assembled proteins accumulate in the ER or continue along the secretory pathway. Aberrant proteins are retrotranslocated to the cytosol and degraded by the proteasome, a process called ER-associated degradation. Doa10, a transmembrane protein of the ER/nuclear envelope, is one of the primary ubiquitin ligases (E3s) participating in ER-associated degradation in Saccharomyces cerevisiae. Here we report the membrane organization of the 1319-residue Doa10 polypeptide. The topology was determined by fusing a dual-topology reporter after 16 different Doa10 fragments. Our results indicate that Doa10 contains 14 transmembrane helices (TMs). Based on protease digestion of yeast microsomes, both the N-terminal RING-CH domain and the C terminus face the cytosol. Notably, the experimentally derived topology was not predicted correctly by any of the generally available TM prediction algorithms. Bioinformatic analysis and in silico mutagenesis guided the topological studies through problematic regions. The conserved TD domain in Doa10 includes three TMs. These TMs might function in cofactor binding or substrate recognition, or they might be part of a retrotranslocation channel. The Derlins were previously proposed to provide such channels, but we show that the two yeast Derlins are not required for degradation of Doa10 membrane substrates, as was found before for the Sec61 translocon. Finally, we provide evidence that the likely human Doa10 ortholog, TEB4 (MARCH-VI), adopts a topology similar to that of Doa10.

Background: One of the limiting factors in achieving the best spatial resolution in positron emission tomography (PET), especially in smallanimal PET, is the positron range associated with the decay of nuclides, and usual PET image reconstruction algorithms do not provide a correction for the positron range. This work presents initial results obtained with the maximum a posteriori (MAP) algorithm, which has been developed to include an accurate model of the camera response, the Poisson distribution of coincidence data and the fundamental physics of positron decay including the positron range. Methods: Phantoms were imaged with three positron emitting isotopes of Cu ( 60 Cu, 61 Cu and 64 Cu), and mice and rats were imaged with two radiopharmaceuticals labeled with these isotopes in a microPET-R4 camera. These isotopes decay by positron emission with very different end-point energies resulting in wildly different spatial resolutions. Spatial resolution improvement and image quality offered by the MAP algorithm were studied with the line source phantom and a miniature Derenzo phantom. In addition, three mice and three rats were sequentially injected over a 48-h period with Cu-pyruvaldehyde bis(N 4 -methylthiosemicarbazone) (for blood flow to organs) and Cu-1,4,7,10-tetraazacyclododecane-1,4,7-tri(methanephosphonic acid) (for bone imaging) labeled with the said three isotopes of Cu. Results: The line source experiment showed that comparable spatial resolution is possible with all three isotopes when using the positron range correction in MAP. The in vivo images obtained from 60 Cu and 61 Cu and reconstructed with 2D filtered back projection algorithms provided by the camera manufacturer show reduced clarity due to degraded spatial resolution arising from the extended positron ranges as compared with 64 Cu. MAP reconstructions exhibited a higher resolution with clearer organ delineation. Conclusion: Inclusion of a positron range model in the MAP reconstruction algorithm may potentially result in significant resolution recovery for isotopes with larger positron ranges.

We propose a new method to render high dynamic range images that models global and local adaptation of the human visual system. Our method is based on the centersurround Retinex model. The novelties of our method is first to use an adaptive filter, whose shape follows the image high contrast edges, thus reducing halo artifacts common to other methods. Secondly, only the luminance channel is processed, which is defined by the first component of a principal component analysis. Principal component analysis provides orthogonality between channels and thus reduces the chromatic changes caused by the modification of luminance. We show that our method efficiently renders high dynamic range images and we compare our results with the current state of the art.

The multidrug resistance protein, MRP1, is a clinically important ATP-binding cassette transporter in which the three membrane-spanning domains (MSDs), which contain up to 17 transmembrane (TM) helices, and two nucleotide binding domains (NBDs) are configured MSD1-MSD2-NBD1-MSD3-NBD2. In tumor cells, MRP1 confers resistance to a broad spectrum of drugs, but in normal cells, it functions as a primary active transporter of organic anions such as leukotriene C4and 17β-estradiol 17β-(d-glucuronide). We have previously shown that mutation of TM17-Trp1246eliminates 17β-estradiol 17β-(d-glucuronide) transport and drug resistance conferred by MRP1 while leaving leukotriene C4transport intact. By mutating the 11 remaining Trp residues that are in predicted TM segments of MRP1, we have now determined that five of them are also major determinants of MRP1 function. Ala substitution of three of these residues, Trp445(TM8), Trp553(TM10), and Trp1198(TM16), eliminated or substantially reduced tran...

To address low contraceptive use in Tanzania, a pilot intervention using a mobile job aid was developed to guide community health workers (CHWs) to deliver integrated counseling on family planning, HIV, and other sexually transmitted infections (STIs). In this article, we describe the process of developing the family planning algorithms and implementation of the mobile job aid, discuss how the job aid supported collection of real-time data for decision making, and present the cost of the overall system based on an evaluation of the pilot. The family planning algorithm was developed, beginning in June 2011, in partnership with the Tanzania Ministry of Health and Social Welfare based on a combination of evidence-based tools such as the Balanced Counseling Strategy Plus Toolkit. The pilot intervention and study was implemented with 25 CHWs in 3 wards in Ilala district in Dar es Salaam between January 2013 and July 2013. A total of 710 family planning users (455 continuing users and 255...

Hepatitis E virus (HEV) is the major cause of epidemic and sporadic hepatitis globally. Outbreaks are associated with fecal contamination of drinking water, yet the environmental reservoir of HEV between epidemics remains unclear. In contrast to neighboring countries, where epidemics and sporadic disease co-occur, HEV-endemic communities in rural Bangladesh seldom report outbreaks; sporadic hepatitis E is reported from urban and rural areas of the country. Besides typical enteric risk factors, other routes for HEV infection and disease are unclear. We conducted monthly household surveillance of a southern Bangladeshi community of 23,500 people to find incident cases of acute hepatitis E over a 22 month period. An algorithm was used to capture 279 candidate cases, of which 46 were confirmed acute HEV infections. An exploratory casecontrol study was conducted to identify putative risk factors for disease. Nearly 70% of cases were over 15 years old. Female gender seemed protective (OR:0.34) against hepatitis E in this conservative setting, as was the use of sanitary latrines (OR:0.28). Socioeconomic status or animal exposures were not significant predictors of disease, although outdoor employment and recent urban travel were. Unexpectedly, recent contact with a ''jaundiced'' patient and a history of injection exposure in the 3 months prior to disease (OR:15.50) were significant. Susceptible individuals from ''endemic'' communities share similar enteric exposure risks to those commonly associated with tourists from non-endemic countries. This study also raises the novel possibility of parenteral and person-to-person transmission of HEV in non-epidemic, sporadic disease settings.

Information on forest biomass is required for several purposes, including estimation of forest bioenergy resources and forest carbon stocks. Airborne laser scanning is today considered the most accurate remote sensing method for forest inventory. The three-dimensional nature of laser scanning data enables estimation of the volumes of the tree canopies. The dimensions of the tree canopies show high correlation with the amount of forest biomass. Optical aerial photographs are often used to complement laser data, for improved distinction between tree species. The paper reports on a study testing the estimation of forest biomass variables in two study areas in Southern Finland. The biomass variables were derived on the basis of tree-level field measurements, with biomass models used for pine, spruce, and birch. The sample-plot-level biomass components were derived on the basis of tree-level data and used as reference data for airborne-laserand aerial-photograph-based estimation. Results...

In order to overcome the limitations of the linear-quadratic model and include synergistic effects of heat and radiation, a novel radiobiological model is proposed. The model is based on a chain of cell populations which are characterized by the number of radiation induced damages (hits). Cells can shift downward along the chain by collecting hits and upward by a repair process. The repair process is governed by a repair probability which depends upon state variables used for a simplistic description of the impact of heat and radiation upon repair proteins. Based on the parameters used, populations up to 4-5 hits are relevant for the calculation of the survival. The model describes intuitively the mathematical behaviour of apoptotic and nonapoptotic cell death. Linear-quadratic-linear behaviour of the logarithmic cell survival, fractionation, and (with one exception) the dose rate dependencies are described correctly. The model covers the time gap dependence of the synergistic cell ...

Streetscapes are basic urban elements which play a major role in the livability of a city. The visual complexity of streetscapes is known to influence how people behave in such built spaces. However, how and which characteristics of a visual scene influence our perception of complexity have yet to be fully understood. This study proposes a method to evaluate the complexity perceived in streetscapes based on the statistics of local contrast and spatial frequency. Here, 74 streetscape images from four cities, including daytime and nighttime scenes, were ranked for complexity by 40 participants. Image processing was then used to locally segment contrast and spatial frequency in the streetscapes. The statistics of these characteristics were extracted and later combined to form a single objective measure. The direct use of statistics revealed structural or morphological patterns in streetscapes related to the perception of complexity. Furthermore, in comparison to conventional measures of visual complexity, the proposed objective measure exhibits a higher correlation with the opinion of the participants. Also, the performance of this method is more robust regarding different time scenarios.

The purpose of the study is to examine the effect of subliminal priming in terms of the perception of images influenced by words with positive, negative, and neutral emotional content, through electroencephalograms (EEGs). Participants were instructed to rate how much they like the stimuli images, on a 7-point Likert scale, after being subliminally exposed to masked lexical prime words that exhibit positive, negative, and neutral connotations with respect to the images. Simultaneously, the EEGs were recorded. Statistical tests such as repeated measures ANOVAs and two-tailed paired-samples t-tests were performed to measure significant differences in the likability ratings among the three prime affect types; the results showed a strong shift in the likeness judgment for the images in the positively primed condition compared to the other two. The acquired EEGs were examined to assess the difference in brain activity associated with the three different conditions. The consistent results obtained confirmed the overall priming effect on participants' explicit ratings. In addition, machine learning algorithms such as support vector machines (SVMs), and AdaBoost classifiers were applied to infer the prime affect type from the ERPs. The highest classification rates of 95.0% and 70.0% obtained respectively for average-trial binary classifier and average-trial multi-class further emphasize that the ERPs encode information about the different kinds of primes.

Motivation: Predicting the secondary structure of a protein (alpha-helix, beta-sheet, coil) is an important step towards elucidating its three-dimensional structure, as well as its function. Presently, the best predictors are based on machine learning approaches, in particular neural network architectures with a fixed, and relatively short, input window of amino acids, centered at the prediction site. Although a fixed small window avoids overfitting problems, it does not permit capturing variable long-rang information. Results: We introduce a family of novel architectures which can learn to make predictions based on variable ranges of dependencies. These architectures extend recurrent neural networks, introducing non-causal bidirectional dynamics to capture both upstream and downstream information. The prediction algorithm is completed by the use of mixtures of estimators that leverage evolutionary information, expressed in terms of multiple alignments, both at the input and output levels. While our system currently achieves an overall performance close to 76% correct prediction -at least comparable to the best existing systems -the main emphasis here is on the development of new algorithmic ideas. Availability: The executable program for predicting protein secondary structure is available from the authors free of charge.

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We evaluated the role of automated quantitative computed tomography (CT) scan interpretation algorithm in detecting interstitial lung disease (ILD) and/or emphysema in a sample of elderly subjects with mild lung disease. We hypothesized that the quantification and distributions of CT attenuation values on lung CT, over a subset of Hounsfield units (HUs) range (-1000 HU, 0 HU), can differentiate early or mild disease from normal lung. We compared the results of quantitative spiral rapid end-exhalation (functional residual capacity, FRC) and end-inhalation (total lung capacity, TLC) CT scan analyses of 52 subjects with radiographic evidence of mild fibrotic lung disease to the results of 17 normal subjects. Several CT value distributions were explored, including (1) that from the peripheral lung taken at TLC (with peels at 15 or 65 mm), (2) the ratio of (1) to that from the core of lung, and (3) the ratio of (2) to its FRC counterpart. We developed a fused-lasso logistic regression mo...

We present a registration algorithm that can handle the discontinuity of deformation with an ultimate goal to investigate how pulmonary lobes deform to accommodate chest wall shape changes. We first show that discontinuities can exist in both normal and tangent directions. Such discontinuities are accounted for by a spatially varying diffusive regularization which restricts smoothing inside objects. Meanwhile, a distance term is combined with the sum of squared intensity differences (SSD) to explicitly match corresponding interfaces and intensity patterns. The capability of this new method is demonstrated using two-dimensional (2-D) synthetic examples with complete or incomplete "fissures" and threedimensional (3-D) computed tomography (CT) lung datasets.

Relationships between structural and functional variables in asthmatic lungs at local and global (or lobar) levels remain to be discovered. This study aims to investigate local alterations of structural variables (bifurcation angle θ, circularity Cr, airway wall thickness WT and hydraulic diameter Dh) in asthmatics, and their correlations with other imaging and pulmonary function tests (PFT) based global and lobar metrics including lung shape, air-trapping, regional volume change and more. 61 healthy subjects, 67 non-severe and 67 severe asthmatics were studied. The structural variables were derived from CT images at total lung capacity (TLC). Air-trapping was measured at functional residual capacity (FRC), and regional volume change (derived from image registration) was measured between FRC and TLC. The tracheal diameter and wall thickness predicted by 61 healthy subjects were used to normalize the Dh and WT. New normalization schemes allowed for the dissociation of luminal narrowi...

The explanation for prone and supine differences in tissue density and pleural pressure gradients in the healthy lung has been inferred from several studies as compression of dependent tissue by the heart in the supine posture; however, this hypothesis has not been directly confirmed. Differences could also arise from change in shape of the chest wall and diaphragm, and because of shape with respect to gravity. The contribution of this third mechanism is explored here. Tissue density and static elastic recoil were estimated in the supine and prone left human lung at functional residual capacity using a finite-element analysis. Supine model geometries were derived from multidetector row computed tomography imaging of two subjects: one normal ( subject 1), and one with small airway disease ( subject 2). For each subject, the prone model was the supine lung shape with gravity reversed; therefore, the prone model was isolated from the influence of displacement of the diaphragm, chest wa...

Rationale and Objectives. A previous scan-regularized reconstruction (PSRR) method was proposed to reduce radiation dose and applied to lung perfusion studies. Normal and ultra-low-dose lung computed tomographic perfusion studies were compared in terms of the estimation accuracy of pulmonary functional parameters. A sequence of sheep lung scans were performed in three prone, anesthetized sheep at normal and ultralow doses. A scan protocol was developed for the ultra-low-dose studies with electrocardiographic gating: time point 1 for a normal x-ray dose scan (100 kV, 150 mAs) and time points 2 to 21 for low-dose scans (80 kV, 17 mAs). A nonlinear diffusionbased post-filtering method was applied to the difference images between the low-dose images and the high-quality reference image. The final images at 20 time points were generated by fusing the reference image with the filtered difference images. Results. The power spectra of perfusion images and coherences in the normal scans showed a great improvement in image quality of the ultra-low-dose scans with PSRR relative to those without RSRR. The gamma variate fitting and the repeatability of the measurements of the mean transit time demonstrated that the key parameters of lung functions can be reliably accessed using PSRR. The variability of the ultra-low-dose scan results obtained using PSRR was not substantially different from that between two normal-dose scans. Conclusions. This study demonstrates that an approximate 90% reduction in radiation dose is achievable using PSRR without compromising quantitative computed tomographic measurements of regional lung function.

New approaches of empirical antifungal therapy (EAT) in selected hematological patients with persistent febrile neutropenia (PFN) have been proposed in recent years, but their cost-effectiveness has not been studied. The aim of this study was to compare the cost-effectiveness of two different approaches of EAT in hematological patients with PFN: the diagnosis-driven antifungal therapy (DDAT) approach versus the standard approach of EAT. A decision tree to assess the cost-effectiveness of both approaches was developed. Outcome probabilities and treatment pathways were extrapolated from two studies: a prospective cohort study following the DDAT approach and a randomized clinical trial following the standard approach. Uncertainty was undertaken through sensitivity analyses and Monte Carlo simulation. The average effectiveness and economic advantages in the DDAT approach compared to the standard approach were 2.6% and €5,879 (33%) per PFN episode, respectively. The DDAT was the dominant...

The accuracy in orientation tracking attainable by using inertial measurement units (IMU) when measuring human motion is still an open issue. This study presents a systematic quantification of the accuracy under static conditions and typical human dynamics, simulated by means of a robotic arm. Two sensor fusion algorithms, selected from the classes of the stochastic and complementary methods, are considered. The proposed protocol implements controlled and repeatable experimental conditions and validates accuracy for an extensive set of dynamic movements, that differ in frequency and amplitude of the movement. We found that dynamic performance of the tracking is only slightly dependent on the sensor fusion algorithm. Instead, it is dependent on the amplitude and frequency of the movement and a major contribution to the error derives from the orientation of the rotation axis w.r.t. the gravity vector. Absolute and relative errors upper bounds are found respectively in the range [0.7°Ä 8.2°] and [1.0°Ä 10.3°]. Alongside dynamic, static accuracy is thoroughly investigated, also with an emphasis on convergence behavior of the different algorithms. Reported results emphasize critical issues associated with the use of this technology and provide a baseline level of performance for the human motion related application.

The dose response of the BANG ® 3 polymer gel dosimeter ͑MGS Research Inc., Madison, CT͒ was studied using the OCTOPUS™ laser CT scanner ͑MGS Research Inc., Madison, CT͒. Six 17 cm diameter and 12 cm high Barex cylinders, and 18 small glass vials were used to house the gel. The gel phantoms were irradiated with 6 and 10 MV photons, as well as 12 and 16 MeV electrons using a Varian Clinac 2100EX. Three calibration methods were used to obtain the dose response curves: ͑a͒ Optical density measurements on the 18 glass vials irradiated with graded doses from 0 to 4 Gy using 6 or 10 MV large field irradiations; ͑b͒ optical-CT scanning of Barex cylinders irradiated with graded doses ͑0.5, 1, 1.5, and 2 Gy͒ from four adjacent 4 ϫ 4 cm 2 photon fields or 6 ϫ 6 cm 2 electron fields; and ͑c͒ percent depth dose ͑PDD͒ comparison of optical-CT scans with ion chamber measurements for 6 ϫ 6 cm 2 , 12 and 16 MeV electron fields. The dose response of the BANG ® 3 gel was found to be linear and energy independent within the uncertainties of the experimental methods ͑about 3%͒. The slopes of the linearly fitted dose response curves ͑dose sensitivities͒ from the four field irradiations ͑0.0752Ϯ 3%, 0.0756Ϯ 3%, 0.0767Ϯ 3%, and 0.0759Ϯ 3% cm -1 Gy -1 ͒ and the PDD matching methods ͑0.0768Ϯ 3% and 0.0761Ϯ 3% cm -1 Gy -1 ͒ agree within 2.2%, indicating a good reproducibility of the gel dose response within phantoms of the same geometry. The dose sensitivities from the glass vial approach are different from those of the cylindrical Barex phantoms by more than 30%, owing probably to the difference in temperature inside the two types of phantoms during gel formation and irradiation, and possible oxygen contamination of the glass vial walls. The dose response curve obtained from the PDD matching approach with 16 MeV electron field was used to calibrate the gel phantom irradiated with the 12 MeV, 6 ϫ 6 cm 2 electron field. Three-dimensional dose distributions from the gel measurement and the Eclipse planning system ͑Varian Corporation, Palo Alto, CA͒ were compared and evaluated using 3% dose difference and 2 mm distance-to-agreement criteria.

Community structure detection in complex networks is important since it can help better understand the network topology and how the network works. However, there is still not a clear and widely-accepted definition of community structure, and in practice, different models may give very different results of communities, making it hard to explain the results. In this paper, different from the traditional methodologies, we design an enhanced semi-supervised learning framework for community detection, which can effectively incorporate the available prior information to guide the detection process and can make the results more explainable. By logical inference, the prior information is more fully utilized. The experiments on both the synthetic and the real-world networks confirm the effectiveness of the framework. ommunity structure detection in complex networks is of critical importance for understanding not only the network topology, but also how the network works 1-3 . In many real applications, the revealed communities often correspond to functional modules of the network, such as pathways in metabolic networks, or a group of people that have common interest. These functional modules can be considered building blocks of networks. Furthermore, dynamics in the networks with communities can be very different from those without communities. However, it is very hard to give a general and widely-accepted definition of community structure due to the complexity of real problems, and most of the revealed communities are model-based, which makes the results hard to explain, or in other words, the correctness and meanings of the communities cannot be confirmed without the background information about the functions of the nodes. Hence if the background information can be effectively incorporated to guide the process of community structure detection, we will get much better results. In our previous work, we have proposed a semi-supervised learning framework to incorporate two types of background information into community detection: must-link and cannot link 4 . An interesting question is: How to make better use of the prior knowledge to do more with less? In this paper, based on our previous work 4 and logical inference, we propose an enhanced semi-supervised learning framework for community structure detection, which can incorporate the available prior information more effectively. The most important contribution of the framework is that it adds a logical inference step to more fully utilize the two types of prior information, must-link constraints and cannot-link constraints, and can more effectively combine the information with the topology structure of networks to guide the detecting process. The experimental results show that the proposed method can significantly improve the detection performance. We also evaluate which type of constraints is more useful, indicating that the constraints of must-link contribute much more than that of cannot-link. In this section, we empirically tested the effectiveness of the enhanced semi-supervised learning framework for community detection. To do this, we applied NMF, spectral clustering and InfoMap with the revised adjacency matrices to several well-studied networks. Data description. Both the synthetic and the real-world networks were used in our experiments. Details are as follows: 1) GN 1 : The GN network, also known as the ''four groups'' network, has 128 nodes which are divided into four equalized sized non-overlapping communities with 32 nodes each. On average, each node has Z in 1 Z out 5

This work reports a method based on correlation functions to convert EPID transit signals into in vivo dose values at the isocenter point, D iso , of dynamic IMRT beams supplied by Varian linac. Dose reconstruction for intensity-modulated beams required significant corrections of EPID response, due to the X-ray component transmitted through multileaf collimator. The algorithm was formulated using a set of simulated IMRT beams. The beams were parameterized by means of a fluence inhomogeneity index, FI, introduced to describe the degree of beam modulation with respect to open beams. This way, all dosimetric parameters involved in D iso reconstruction algorithm, such as the correlation functions, the correction factor for EPID to phantom distance and the modulated tissue maximum ratios, were determined as a function of the FI index. Clinical IMRT beams were used to irradiate a homogeneous phantom, and for each beam, the agreement between the reconstructed dose, D iso , and the dose computed by TPS, D iso,TPS , was well within 5 %. Moreover, the average ratios, R, between the D iso , and D iso,TPS , resulted equal to 1.002 ± 0.030. Thirty-five IMRT fields of 5 different patients undergoing radiotherapy for headneck tumors were tested and the results were displayed on a computer screen after 2 min from the end of the treatment. However, 350 in vivo tests supplied an average ratio R equal to 1.004 ± 0.040. The in vivo dosimetry procedure here presented is among the objectives of a National Project financially supported by the Istituto Nazionale di Fisica Nucleare for the development of in vivo dosimetry procedures (Piermattei et al. in Nucl Instrum Methods Phys Res B 274:42-50, 2012) connected to the Record-Verify system of the radiotherapy center.

Inside the 'cavernous sinus' or 'parasellar region' the human internal carotid artery takes the shape of a siphon that is twisted and torqued in three dimensions and surrounded by a network of veins. The parasellar section of the internal carotid artery is of broad biological and medical interest, as its peculiar shape is associated with temperature regulation in the brain and correlated with the occurrence of vascular pathologies. The present study aims to provide anatomical descriptions and objective mathematical characterizations of the shape of the parasellar section of the internal carotid artery in human infants and its modifications during ontogeny. Three-dimensional (3D) computer models of the parasellar section of the internal carotid artery of infants were generated with a state-of-the-art 3D reconstruction method and analysed using both traditional morphometric methods and novel mathematical algorithms. We show that four constant, demarcated bends can be described along the infant parasellar section of the internal carotid artery, and we provide measurements of their angles. We further provide calculations of the curvature and torsion energy, and the total complexity of the 3D skeleton of the parasellar section of the internal carotid artery, and compare the complexity of this in infants and adults. Finally, we examine the relationship between shape parameters of the parasellar section of the internal carotid artery in infants, and the occurrence of intima cushions, and evaluate the reliability of subjective angle measurements for characterizing the complexity of the parasellar section of the internal carotid artery in infants. The results can serve as objective reference data for comparative studies and for medical imaging diagnostics. They also form the basis for a new hypothesis that explains the mechanisms responsible for the ontogenetic transformation in the shape of the parasellar section of the internal carotid artery.

Correlated data gathering in body area networks calls for systems that perform efficient compression and reliable transmission of the measurements, while imposing a small computational burden at the sensors. Highly-efficient compression mechanisms, e.g., adaptive arithmetic entropy encoding, do not address the problem adequately, as they have high computational demands. In this paper, we propose a new distributed joint source-channel coding (DJSCC) solution for this problem. Following the principles of distributed source coding, our design allows for efficient compression and error-resilient transmission while exploiting the correlation amongst sensors' readings at energy-robust sink nodes. In this way, the computational complexity and in turn, the energy consumption at the sensor node is kept to a minimum. Our DJSCC design is based on a new non-systematic Slepian-Wolf Raptor code construction that achieves good performance at short code lengths, which are appropriate for low-rate data gathering within local or body area sensor networks. Experimental results using a WSN deployment for temperature monitoring reveal that, for lossless compression, the proposed system leads to a 30.08% rate reduction against a baseline system that performs adaptive arithmetic entropy encoding of the temperature readings. Moreover, under AWGN and Rayleigh fading channel losses, the proposed system leads to energy savings between 12.19% to 16.51% with respect to the baseline system.

Generative AI is transforming state power, replacing transparent legal processes with opaque algorithmic systems. This commentary argues that this shift is not simply a technical upgrade but a qualitative break from previous forms of digital governance. Where earlier predictive systems classified and ranked citizens, generative AI constructs the informational environment within which citizens act. I argue that this shift operates along two axes: generative AI's layered opacity dissolves the chains of public answerability that link transparency to accountability, while its capacity for synthetic content generation fragments the shared factual ground that deliberation depends on. Regulatory responses such as the EU AI Act represent important but insufficient counterweights. The central challenge remains ensuring these technologies serve democratic governance rather than reduce citizens to objects of algorithmic management.

Purpose: To efficiently deliver respiratory-gated radiation during synchrotron-based pulsed heavy-ion radiotherapy, a novel respiratory guidance method combining a personalized audio-visual biofeedback (BFB) system, breath hold (BH), and synchrotron-based gating was designed to help patients synchronize their respiratory patterns with synchrotron pulses and to overcome typical limitations such as low efficiency, residual motion, and discomfort. Methods: In-house software was developed to acquire body surface marker positions and display BFB, gating signals, and real-time beam profiles on a LED screen. Patients were prompted to perform short BHs or short deep breath holds (SDBH) with the aid of BFB following a personalized standard BH/SDBH (stBH/stSDBH) guiding curve or their own representative BH/SDBH (reBH/reSDBH) guiding curve. A practical simulation was performed for a group of 15 volunteers to evaluate the feasibility and effectiveness of this method. Effective dose rates (EDRs), mean absolute errors between the guiding curves and the measured curves, and mean absolute deviations of the measured curves were obtained within 10%-50% duty cycles (DCs) that were synchronized with the synchrotron's flat-top phase. Results: All maneuvers for an individual volunteer took approximately half an hour, and no one experienced discomfort during the maneuvers. Using the respiratory guidance methods, the magnitude of residual motion was almost ten times less than during nongated irradiation, and increases in the average effective dose rate by factors of 2. 39-4.65, 2.39-4.59, 1.73-3.50, and 1.73-3.55 for the stBH, reBH, stSDBH, and reSDBH guiding maneuvers, respectively, were observed in contrast with conventional free breathing-based gated irradiation, depending on the respiratory-gated duty cycle settings. Conclusions: The proposed respiratory guidance method with personalized BFB was confirmed to be feasible in a group of volunteers. Increased effective dose rate and improved overall treatment precision were observed compared to conventional free breathing-based, respiratory-gated irradiation. Because breathing guidance curves could be established based on the respective average respiratory period and amplitude for each patient, it may be easier for patients to cooperate using this technique. C 2014 American Association of Physicists in Medicine.

To efficiently deliver respiratory-gated radiation during synchrotron-based pulsed heavy-ion radiotherapy, a novel respiratory guidance method combining a personalized audio-visual biofeedback (BFB) system, breath hold (BH), and synchrotron-based gating was designed to help patients synchronize their respiratory patterns with synchrotron pulses and to overcome typical limitations such as low efficiency, residual motion, and discomfort. In-house software was developed to acquire body surface marker positions and display BFB, gating signals, and real-time beam profiles on a LED screen. Patients were prompted to perform short BHs or short deep breath holds (SDBH) with the aid of BFB following a personalized standard BH/SDBH (stBH/stSDBH) guiding curve or their own representative BH/SDBH (reBH/reSDBH) guiding curve. A practical simulation was performed for a group of 15 volunteers to evaluate the feasibility and effectiveness of this method. Effective dose rates (EDRs), mean absolute er...

Using bovine serum albumin (BSA) as the model protein, normal Raman spectra of fluorescein isothiocyanate (FITC) conjugated protein were systematically studied for the first time using both solution and the drop coating deposition Raman (DCDR) sampling techniques. The FITC-BSA Raman spectra are dominated by the FITC Raman features that are strongly pH dependent. Current DCDR detection sensitivity obtained with a 10:1 FITC-BSA conjugate is 45 fmol in terms of total protein consumption and ∼15 attomol at laser probed volume. Unlike the FITC-BSA solution Raman spectra, where the FITC Raman features are photostable, concurrent FITC fluorescence and Raman photobleaching is observed in the DCDR spectra of FITC-BSA. While the FITC Raman photobleaching follows a single exponential decay function with a time constant independent of the FITC labeling ratio, the fluorescence background photobleaching is much more complicated and it depends strongly on the FITC labeling ratio and sample conditi...

Brushless direct current (BLDC) motors are widely utilized in industrial and traction applications, particularly in electric vehicles (EVs), due to their inherent advantages. In EVs, a very low steady-state error with rapid convergence responses is required for a smooth wheel acceleration. This article proposes a robust and fast speed controller for the BLDC-driven EV using optimized proportional-integral (PI) and fractional-order (FOPI) controllers tuned by a new bio-inspired optimization algorithm called the Giant Armadillo Optimization (GAO) algorithm. The main goal of this study is to improve the performance of the BLDC motor under different variations of the reference speed. The suggested system was designed and tested using the MATLAB/Simulink environment. In this study, three different case studies are applied, including no load, sudden decrease in speed, and random speed variations. Moreover, the achieved results are compared with the classical PI and particle swarm optimization (PSO-PI) controllers. The obtained results show that the suggested GAO-FOPI controllers significantly outperform the conventional controllers, obtaining a speed overshoot of 2.13%, compared to 8.4% with the classical PI method. Finally, the suggested controller decreases the rise time to 1.02 sec, achieving a 41% enhancement when compared with PSO-PI and PI techniques (1.64 sec and 1.72 sec).

Background The statistical analysis of protein structures requires datasets in which structural features can be considered independently distributed, i.e. not related through common ancestry, and that fulfil minimal requirements regarding the experimental quality of the structures it contains. However, non-redundant datasets based on sequence similarity invariably contain distantly related homologues. Here we provide a reference dataset of non-homologous protein domains, assuming that structural dissimilarity at the topology level is incompatible with recognizable common ancestry. The dataset is based on domains at the Topology level of the CATH database which hierarchically classifies all protein structures. It contains the best refined representatives of each Topology level, validates structural dissimilarity and removes internally duplicated fragments. The compilation of Nh3D is fully scripted. Results The current Nh3D list contains 570 domains with a total of 90780 residues. It ...

A hybrid standards-based approach has been adopted in Singapore to develop a Logical Information Model (LIM) for healthcare information exchange. The Singapore LIM uses a combination of international standards, including ISO13606-1 (a reference model for electronic health record communication), ISO21090 (healthcare datatypes), SNOMED CT (healthcare terminology) and HL7 v2 (healthcare messaging). This logic-based design approach also incorporates mechanisms for achieving bi-directional semantic interoperability.

A hybrid standards-based approach has been adopted in Singapore to develop a Logical Information Model (LIM) for healthcare information exchange. The Singapore LIM uses a combination of international standards, including ISO13606-1 (a reference model for electronic health record communication), ISO21090 (healthcare datatypes), SNOMED CT (healthcare terminology) and HL7 v2 (healthcare messaging). This logic-based design approach also incorporates mechanisms for achieving bi-directional semantic interoperability.

ȶ ſ ÿ -We consider computationally reconstructing gene regulatory networks on top of the binary abstraction of gene expression state information. Unlike previous Boolean network approaches, the proposed method does not handle noisy gene expression values directly. Instead, two-valued "hidden state" information is derived from gene expression profiles using a robust statistical technique, and a gene interaction network is inferred from this hidden state information. In particular, we exploit Espresso, a well-known 2-level Boolean logic optimizer in order to determine the core network structure. The resulting gene interaction networks can be viewed as dynamic Bayesian networks, which have key advantages over more conventional Bayesian networks in terms of biological phenomena that can be represented. The authors tested the proposed method with a time-course gene expression data set from microarray experiments on anti-cancer drugs doxorubicin and paclitaxel. A gene interaction network was produced by our method, and the identified genes were validated with a public annotation database. The experimental studies we conducted suggest that the proposed method inspired by engineering systems can be a very effective tool to decipher complex gene interactions in living systems.

In silico modeling of Gene Regulatory Networks has gained a lot of attention recently as it gives a very powerful tool to experimental biologists to gather the knowledge gained from different biological experiments and understand the dynamics of the overall system. One of the key dynamics that is often interesting is the steady states of the networks which biologically corresponds to the cellular states. In our previous paper, we gave an efficient method called GenYsis to compute these steady states in Boolean representation of Gene Regulatory Network. It has been observed that protein may be expressed at more then two level of expression. This may result in different cellular outcomes. To address this issue, we present here a multiple-level modeling methodology that allows us to be more accurate. In this paper we extend our software GenYsis to model gene regulatory networks where each node in the network may take multiple values.

Difficult airway has gained increasing interest due to a relatively high number of adverse effects following unsuccessful intubation. Besides traditional techniques, several alternative methods are available today. It is crucial for the anesthesiologists and intensive care physicians to maintain sufficient oxygenation and ventilation of the patient. Hypoxia is one of the most frequent causes of death or severe neurologic defects in anesthesia. Therefore, it is necessary to have an easy alternative to secure the airways in critical situations.

Difficult airway has gained increasing interest due to a relatively high number of adverse effects following unsuccessful intubation. Besides traditional techniques, several alternative methods are available today. It is crucial for the anesthesiologists and intensive care physicians to maintain sufficient oxygenation and ventilation of the patient. Hypoxia is one of the most frequent causes of death or severe neurologic defects in anesthesia. Therefore, it is necessary to have an easy alternative to secure the airways in critical situations.

Difficult airway has gained increasing interest due to a relatively high number of adverse effects following unsuccessful intubation. Besides traditional techniques, several alternative methods are available today. It is crucial for the anesthesiologists and intensive care physicians to maintain sufficient oxygenation and ventilation of the patient. Hypoxia is one of the most frequent causes of death or severe neurologic defects in anesthesia. Therefore, it is necessary to have an easy alternative to secure the airways in critical situations.

Transcription factors (TFs) are crucial for regulating cell differentiation during the development of the immune system. However, the key TFs for orchestrating the specification of distinct immune cells are not fully understood. Here, we integrated the transcriptomic and epigenomic measurements in 73 mouse and 61 human primary cell types, respectively, that span the immune cell differentiation pathways. We constructed the cell-type-specific transcriptional regulatory network and assessed the global importance of TFs based on the Taiji framework, which is a method we have previously developed that can infer the global impact of TFs using integrated transcriptomic and epigenetic data. Integrative analysis across cell types revealed putative driver TFs in cell lineage-specific differentiation in both mouse and human systems. We have also identified TF combinations that play important roles in specific developmental stages. Furthermore, we validated the functions of predicted novel TFs ...

A method for enhancing the reliability of implicit computational algorithms and decreasing their sensitivity to initial conditions without adversely impacting their efficiency is investigated. Efficient convergence is maintained by specifying a large global Courant (CFL) number while reliability is improved by limiting the local CFL number such that the solution change in any cell is less than a specified tolerance. The method requires control over two key issues: obtaining a reliable estimate of the magnitude of the solution change and defining a realistic limit for its allowable variation. The magnitude of the solution change is estimated from the calculated residual in a manner that requires negligible computational time. An upper limit on the local solution change is attained by a proper non-dimensionalization of variables in different flow regimes within a single problem or across different problems. The method precludes unphysical excursions in Newton-like iterations in highly non-linear regions where Jacobians are changing rapidly as well as non-physical results such as negative densities, temperatures or species mass fractions during the computation. The method is tested against a series of problems all starting from quiescent initial conditions to identify its characteristics and to verify the approach. The results reveal a substantial improvement in convergence reliability of implicit CFD applications that enables computations starting from simple initial conditions without user intervention.

The ability of gum kondagogu [Cochlospermum gossypium (L.) DC.], a natural carbohydrate biopolymer, was investigated for adsorptive removal of toxic metal ions Cd 2+ , Cu 2+ , Fe 2+ , Pb 2+ , Ni 2+ , Zn 2+ , Hg 2+ and total Cr present in industrial effluents. Various physico-chemical parameters, such as, pH, temperature, equilibrium contact time, % biosorption and adsorption capacity, were investigated. Metal biosorption (%) and adsorption capacity of the biopolymer was determined by ICP-MS. Gum kondagogu was capable of competitively biosorb 8 toxic metal ions from the samples of industrial effluents tested. The adsorption capacity was observed to be in the following order, Cd 2+ > Cu 2+ > Fe 2+ > Pb 2+ > Hg 2+ > total Cr > Ni 2+ > Zn 2+ . The maximum adsorption capacity of metals by gum kondagogu varied in the range of 31-37 mg g -1 for Fe 2+ and minimum of 5.5-9.3 mg g -1 for Hg 2+ in the effluent samples tested. The equilibrium adsorption data were fitted to Langmuir isotherm models for all the metal ions adsorbed. FT-IR studies were carried out to understand the type of functional groups in gum kondagogu responsible for metal biosorption process. Desorption studies on biosorbed metal ions showed that HCl was a good eluant for all metals tested. The re-adsorption capacity of the recycled gum kondagogu biopolymer sustained its biosorption property at 90% level, even after 3 cycle of desorption. Gum kondagogu biopolymer has the potential to be used as an effective, non-toxic, economical and an efficient biosorbent clean-up matrix for removal of toxic metals from industrial effluents.

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Multichannel recordings of the electromagnetic fields emerging from neural currents in the brain generate large amounts of data. Suitable feature extraction methods are, therefore, useful to facilitate the representation and interpretation of the data. Recently developed independent component analysis (ICA) has been shown to be an efficient tool for artifact identification and extraction from electroencephalographic (EEG) and magnetoencephalographic (MEG) recordings. In addition, ICA has been applied to the analysis of brain signals evoked by sensory stimuli. This paper reviews our recent results in this field.

Objective: To replicate, using the Greek version of the 15D instrument, the three-stage valuation procedure, using a sample of coronary artery disease patients; to assess on a preliminary basis the psychometric properties of the instrument in the Greek health-care environment; to evaluate the health-related quality of life of patients with coronary artery disease. Methods: The generic instrument 15D was translated and culturally adapted into the Greek language and setting. It was then administered during October 2005 to May 2006 to 420 coronary artery disease patients. The three-stage valuation procedure was employed and, with the use of elicited preference weights, a single health-related quality of life index score for the patients was derived. Scores were also calculated using the original Finnish valuation system and compared with the previously derived utilities. Sensitivity, reliability, and validity were assessed by examining response distributions, floor and ceiling effects, item-scale correlations, Cronbach's alpha coefficients, and hypothesized relationships between sociodemographic variables and health-related quality of life. Results: The Greek valuation systematically generated higher 15D utilities than the Finnish one. Nevertheless, the utilities derived with the original Finnish valuation algorithm differed significantly with respect to sex, age, and education, just as they did using the Greek valuation system. In most cases, the full range of possible responses has been used satisfactorily and floor and ceiling effects were generally moderate. In general, internal consistency reliability was also satisfactory. The valuation system generated results demonstrating satisfactory psychometric properties. Further research should validate the 15D in the general Greek population.

BACKGROUND: Stereoelectroencephalography (SEEG) methodology, originally developed by Talairach and Bancaud, is progressively gaining popularity for the presurgical invasive evaluation of drug-resistant epilepsies. OBJECTIVE: To describe recent SEEG methodological implementations carried out in our center, to evaluate safety, and to analyze in vivo application accuracy in a consecutive series of 500 procedures with a total of 6496 implanted electrodes. METHODS: Four hundred nineteen procedures were performed with the traditional 2-step surgical workflow, which was modified for the subsequent 81 procedures. The new workflow entailed acquisition of brain 3-dimensional angiography and magnetic resonance imaging in frameless and markerless conditions, advanced multimodal planning, and robot-assisted implantation. Quantitative analysis for in vivo entry point and target point localization error was performed on a sub-data set of 118 procedures (1567 electrodes). RESULTS: The methodology a...