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The study of security and privacy in vehicular ad hoc networks (VANETs) has become a hot topic that is wide open to discussion. As the quintessence of this aspect, authentication schemes deployed in VANETs play a substantial role in providing secure communication among vehicles and the surrounding infrastructures. Many researchers have proposed a variety of schemes related to information verification and computation efficiency in VANETs. In 2018, Kazemi et al. proposed an evaluation and improvement work towards Azees et al.’s efficient anonymous authentication with conditional privacy-preserving (EAAP) scheme for VANETs. They claimed that the EAAP suffered from replaying attacks, impersonation attacks, modification attacks, and cannot provide unlinkability. However, we also found out if Kazemi et al.’s scheme suffered from the unlinkability issue that leads to a forgery attack. An adversary can link two or more messages sent by the same user by applying Euclid’s algorithm and derives the user’s authentication key. To remedy the issue, in this paper, we proposed an improvement by encrypting the message using a shared secret key between sender and receiver and apply a Nonce in the final message to guarantee the unlinkability between disseminated messages.

In the era of big data, data-driven services (DDS) have become critical competitive strategies for digital platform-based enterprises. This paper considers two operational modes of e-commerce platforms, which are self-operated and third-party modes, respectively, and they each lead a platform system. The Hotelling model is adopted to describe the competitive market of both platforms. We characterize their system performance functions. The optimization models are built using game theory to discuss the DDS and price decisions. We obtain the implementation conditions of DDS strategies for both platforms and the dominant situations of their respective DDS levels. We find that a platform adopting the price reduction strategy can improve the performance of its platform system while reducing the competitor’s system performance. From the system performance perspective, continuous improvement of the DDS level may appear “harming others may not benefit oneself”; that is, continuously improving the DDS level leads to a decrease in the competitor’s system performance but not necessarily an increase in its system performance. Further, consumer welfare within both platform systems shows the law of “as one falls then another rises”. As the big data industry matures, self-operated platforms would demonstrate the advantages of service level, profit, and system performance. In contrast, third-party platforms would have an advantage in consumer welfare. These conclusions have important implications for e-commerce platforms developing data-driven operations-based strategies.

The development of computational models for simulating tumor growth and response to treatment has gained significant momentum during the last few decades. At the dawn of the era of personalized medicine, providing insight into complex mechanisms involved in cancer and contributing to patient-specific therapy optimization constitute particularly inspiring pursuits. The in silico oncology community is facing the great challenge of effectively translating simulation models into clinical practice, which presupposes a thorough sensitivity analysis, adaptation and validation process based on real clinical data. In this paper, the behavior of a clinically-oriented, multiscale model of solid tumor response to chemotherapy is investigated, using the paradigm of nephroblastoma response to preoperative chemotherapy in the context of the SIOP/GPOH clinical trial. A sorting of the model's parameters according to the magnitude of their effect on the output has unveiled the relative importance of the corresponding biological mechanisms; major impact on the result of therapy is credited to the oxygenation and nutrient availability status of the tumor and the balance between the symmetric and asymmetric modes of stem cell division. The effect of a number of parameter combinations on the extent of chemotherapy-induced tumor shrinkage and on the tumor's growth rate are discussed. A real clinical case of nephroblastoma has served as a proof of principle study case, demonstrating the basics of an ongoing clinical adaptation and validation process. By using clinical data in conjunction with plausible values of model parameters, an excellent fit of the model to the available medical data of the selected nephroblastoma case has been achieved, in terms of both volume reduction and histological constitution of the tumor. In this context, the exploitation of multiscale clinical data drastically narrows the window of possible solutions to the clinical adaptation problem.

Knowledge of contagion among economies is a relevant issue in economics. The canonical model of contagion is an alternative in this case. Given the existence of endogenous variables in the model, instrumental variables can be used to decrease the bias of the OLS estimator. In the presence of heteroskedastic disturbances this paper proposes the use of conditional volatilities as instruments. Simulation is used to show that the homoscedastic and heteroskedastic estimators which use them as instruments have small bias. These estimators are preferable in comparison with the OLS estimator and their asymptotic distribution can be used to construct confidence intervals.

Medical studies have shown that the condition of human retinal vessels may reveal the physiological structure of the relationship between age-related macular degeneration, glaucoma, atherosclerosis, cataracts, diabetic retinopathy, and other ophthalmic diseases and systemic diseases, and their abnormal changes often serve as a diagnostic basis for the severity of the condition. In this paper, we design and implement a deep learning-based algorithm for automatic segmentation of retinal vessel (CSP_UNet). It mainly adopts a U-shaped structure composed of an encoder and a decoder and utilizes a cross-stage local connectivity mechanism, attention mechanism, and multi-scale fusion, which can obtain better segmentation results with limited data set capacity. The experimental results show that compared with several existing classical algorithms, the proposed algorithm has the highest blood vessel intersection ratio on the dataset composed of four retinal fundus images, reaching 0.6674. Then, based on the CSP_UNet and introducing hard parameter sharing in multi-task learning, we innovatively propose a combined diagnosis algorithm vessel segmentation and diabetic retinopathy for retinal images (MTNet). The experiments show that the diagnostic accuracy of the MTNet algorithm is higher than that of the single task, with 0.4% higher vessel segmentation IoU and 5.2% higher diagnostic accuracy of diabetic retinopathy classification.

Patent Citation Analysis has been gaining considerable traction over the past few decades. In this paper, we collect extensive information on patents and citations and provide a perspective of citation network analysis of patents from a statistical viewpoint. We identify and analyze the most cited patents, the most innovative and the highly cited companies along with the structural properties of the network by providing in-depth descriptive analysis. Furthermore, we employ Exponential Random Graph Models (ERGMs) to analyze the citation networks. ERGMs enables understanding the social perspectives of a patent citation network which has not been studied earlier. We demonstrate that social properties such as homophily (the inclination to cite patents from the same country or in the same language) and transitivity (the inclination to cite references’ references) together with the technicalities of the patents (e.g., language, categories), has a significant effect on citations. We also provide an in-depth analysis of citations for sectors in patents and how it is affected by the size of the same. Overall, our paper delves into European patents with the aim of providing new insights and serves as an account for fitting ERGMs on large networks and analyzing them. ERGMs help us model network mechanisms directly, instead of acting as a proxy for unspecified dependence and relationships among the observations.

Objective This case study examined implementation of the National Health Services Standards (NHSSs) as a continuous quality improvement (CQI) process at three church-based health facilities in Papua New Guinea. This process was designed to improve quality of care and accredit the level three health centers to level four as district hospitals to provide a higher level of care. The aims of the paper are to critically examine driving and restraining forces in CQI implementation and analyses how power influences agenda setting for change. Methods Semi-structured interviews were conducted with nine managers and eight health workers as well as three focus group discussions with health workers from three rural church-based health facilities in Morobe and Madang provinces. They included senior, mid-level and frontline managers and medical doctors, health extension officers, nursing officers and community health workers. Thematic analysis was used as an inductive and deductive process in which applied force field analysis, leadership-member exchange (LMX) theory and agenda setting was applied. Results Qualitative analysis showed how internal and external factors created urgency for change. The CQI process was designed as a collective process. Power relations operated at and between various levels: the facilities, which supported or undermined the change process; between management whereby the national management supported the quality improvement agenda, but the regional management exercised positional power in form of inaction. Theoretical analysis identified the ‘missing bit in the middle’ shaped by policy actors who exercise power over policy formulation and constrained financial and technical resources. Analysis revealed how to reduce restraining forces and build on driving forces to establish a new equilibrium. Conclusion Multiple theories contributed to the analysis showing how to resolve problematic power relations by building high-quality, effective communication of senior leadership with mid-level management and reactivated broad collaborative processes at the health facilities. Addressing the ‘missing bit in the middle’ by agenda setting can improve implementation of the NHSSs as a quality improvement process. The paper concludes with learning for policy makers, managers and health workers by highlighting to pay close attention to institutional power dynamics and practices.

Nitrotyrosine is one of the post-translational modifications (PTMs) in proteins that occurs when their tyrosine residue is nitrated. Compared with healthy people, a remarkably increased level of nitrotyrosine is detected in those suffering from rheumatoid arthritis, septic shock, and coeliac disease. Given an uncharacterized protein sequence that contains many tyrosine residues, which one of them can be nitrated and which one cannot? This is a challenging problem, not only directly related to in-depth understanding the PTM's mechanism but also to the nitrotyrosine-based drug development. Particularly, with the avalanche of protein sequences generated in the postgenomic age, it is highly desired to develop a high throughput tool in this regard. Here, a new predictor called "iNitro-Tyr" was developed by incorporating the position-specific dipeptide propensity into the general pseudo amino acid composition for discriminating the nitrotyrosine sites from non-nitrotyrosine sites in proteins. It was demonstrated via the rigorous jackknife tests that the new predictor not only can yield higher success rate but also is much more stable and less noisy. A web-server for iNitro-Tyr is accessible to the public at http://app.aporc.org/iNitro-Tyr/. For the convenience of most experimental scientists, we have further provided a protocol of step-by-step guide, by which users can easily get their desired results without the need to follow the complicated mathematics that were presented in this paper just for the integrity of its development process. It has not escaped our notice that the approach presented here can be also used to deal with the other PTM sites in proteins.

Global collaboration continues to grow as a share of all scientific cooperation, measured as coauthorships of peer-reviewed, published papers. The percent of all scientific papers that are internationally coauthored has more than doubled in 20 years, and they account for all the growth in output among the scientifically advanced countries. Emerging countries, particularly China, have increased their participation in global science, in part by doubling their spending on R&D; they are increasingly likely to appear as partners on internationally coauthored scientific papers. Given the growth of connections at the international level, it is helpful to examine the phenomenon as a communications network and to consider the network as a new organization on the world stage that adds to and complements national systems. When examined as interconnections across the globe over two decades, a global network has grown denser but not more clustered, meaning there are many more connections but they are not grouping into exclusive ‘cliques’. This suggests that power relationships are not reproducing those of the political system. The network has features an open system, attracting productive scientists to participate in international projects. National governments could gain efficiencies and influence by developing policies and strategies designed to maximize network benefits—a model different from those designed for national systems.

This paper focuses on determining the structural similarity of two molecules, i.e., the similarity of the interconnection of all the elementary cycles in the corresponding molecular graphs. In this paper, we propose and analyze an algorithmic approach based on the resolution of the Maximum Common Edge Subgraph (MCES) problem with graphs representing the interaction of cycles molecules. Using the ChEBI database, we compare the effectiveness of this approach in terms of structural similarity and computation time with two calculations of similarity of molecular graphs, one based on the MCES, the other on the use of different fingerprints (Daylight, ECFP4, ECFP6, FCFP4, FCFP6) to measure Tanimoto coefficient. We also analyze the obtained structural similarity results for a selected subset of molecules.

To balance the supply and demand in China's beef market, beef consumption must be scientifically and effectively forecasted. Beef consumption is affected by many factors and is characterized by gray uncertainty. Therefore, gray theory can be used to forecast the beef consumption, In this paper, the structural defects and unreasonable parameter design of the traditional gray model are analyzed. Then, a new gray model termed, EGM(1,1,r), is built, and the modeling conditions and error checking methods of EGM(1,1,r) are studied. Then, EGM(1,1,r) is used to simulate and forecast China's beef consumption. The results show that both the simulation and prediction precisions of the new model are better than those of other gray models. Finally, the new model is used to forecast China's beef consumption for the period from 2019-2025. The findings will serve as an important reference for the Chinese government in formulating policies to ensure the balance between the supply and demand for Chinese beef.

BackgroundOne approach considered for reducing health care spending is to narrow the gap in spending between high- and low-spending areas. The goal would be to reduce spending in the high areas to similar levels achieved in areas that use health care more efficiently. This paper examined the degree to which high-spending areas remain high-spending and which types of service lead to convergence or divergence in spending in New York State.MethodsThis analysis utilized publicly available data on county-level spending trends for the Medicare fee-for-service population from 2007 to 2016. The study applied methods previously used to evaluate changes in the regional variation of health care spending nationally to county-level data within New York.ResultsThe spread of health care spending converged slightly over the ten-year period analyzed. There was also evidence for regression to the mean-effects and changes in the relative rankings of spending across counties during this time. While there was strong evidence for convergence, many high-spending counties in 2007 remained high-spending in 2016. There were also differences in which services drove spending variation at the national level compared to within New York.ConclusionsThese findings point to counties with consistently high spending as a potential focus for health care cost-control efforts. Moreover, efforts to reduce unwarranted variation in spending may need to be tailored to the circumstances of particular regions as there are geographic differences in which services drive spending variation. Regression to the mean effects also have important implications for the specifications of alternative provider payment models, such as accountable care organizations, which promote convergence in spending by utilizing spending targets.

M2 channel, an influenza virus transmembrane protein, serves as an important target for antiviral drug design. There are still discordances concerning the role of some residues involved in proton transfer as well as the mechanism of inhibition by commercial drugs. The viral M2 proteins show high conservativity; about 3/4 of the positions are occupied by one residue in over 95%. Nine M2 proteins from the H3N2 strain and possibly two proteins from H2N2 strains make a phylogenic cluster closely related to 2RLF. The variability range is limited to 4 residues/position with one exception. The 2RLF protein stands out by the presence of 2 serines at the positions 19 and 50, which are in most other M2 proteins occupied by cysteines. The study of correlated mutations shows that there are several positions with significant mutational correlation that have not been described so far as functionally important. That there are 5 more residues potentially involved in the M2 mechanism of action. The original software used in this work (Consensus Constructor, SSSSg, Corm, Talana) is freely accessible as stand-alone offline applications upon request to the authors. The other software used in this work is freely available online for noncommercial purposes at public services on bioinformatics such as ExPASy or NCBI. The study on mutational variability, evolutionary relationship, and correlated mutation presented in this paper is a potential way to explain more completely the role of significant factors in proton channel action and to clarify the inhibition mechanism by specific drugs.

Rule-based languages such as Kappa excel in their support for handling the combinatorial complexities prevalent in many biological systems, including signalling pathways. But Kappa provides little structure for organising rules, and large models can therefore be hard to read and maintain. This paper introduces a high-level, modular extension of Kappa called LBS-κ. We demonstrate the constructs of the language through examples and three case studies: a chemotaxis switch ring, a MAPK cascade, and an insulin signalling pathway. We then provide a formal definition of LBS-κ through an abstract syntax and a translation to plain Kappa. The translation is implemented in a compiler tool which is available as a web application. We finally demonstrate how to increase the expressivity of LBS-κ through embedded scripts in a general-purpose programming language, a technique which we view as generally applicable to other domain specific languages.

Introduction Queues are inherent to service encounters, as it is not always possible to provide service to all clients at the exact moment they request service. Queues involve waiting for a service in a specific place that might also be crowded, they obstruct the client's’ goal of receiving service, and at times lead clients to mistreat service providers and in extreme cases even attack them violently. We show, in a hospital setting, that perceived predicted future wait and load can buffer the causes of violence towards service staff. Methods We combine objective data on crowdedness, reports of violence, and durations of time people waited, with psychological measures of perceived load and perceived future wait, collected from 226 people in the Emergency Department (ED) of a large hospital. Visitors to the ED were recruited as they waited for service. They indicated their perceived load in the ED and their perceived remaining wait for service. This data was then triangulated with objective operational data regarding the actual number of people waiting for service (i.e., crowdedness) and objective data regarding staff calls to security to stop violent accounts. Results We find that with increased crowdedness, there are more calls to security reporting violence. However, this relationship is moderated by two factors: when people perceive the future wait to be short and when they perceive the load on the system to be high. Moreover, a three-way interaction shows that crowdedness is associated with more incidents of violence, however high perceived load and low perceived future wait are associated with fewer violent incidents. Conclusions This paper demonstrates the relationship between crowded queues and violence towards service staff, and suggests two psychological mechanisms for buffering such violence: reducing perceived future wait and elevating perceived load.

Rising migration numbers and the resulting increase in economic and sociocultural heterogeneity in societies all over the world are theorised to put pressure on the sustainable use of common-pool resources [CPRs]. Increased heterogeneity is argued to decrease trust and diversify interests between resource users, leading to overuse and decline of natural and man-made CPRs. The aim of this paper is to understand cooperative behaviour under economic and sociocultural heterogeneity in CPRs, through the analyses of experimental data including 344 subjects from the United Kingdom and the Netherlands, and 144 subjects from India. Multilevel regression, ordinal logistic regression, linear conditional-contribution profiles [LCPs] and agent-based models [ABMs] are used to analyse and replicate experimental outcomes on the micro- and macro-level. Results show that the combination of economic and sociocultural heterogeneity affects cooperation negatively when the decision-situation is perceived as unfair, but that neither economic nor sociocultural heterogeneity on themselves affect cooperation negatively. Economic heterogeneity is even found to affect cooperation positively relative to homogeneity. Player type classification based on LCP scores shows that experimental outcomes can be interpreted with player types, and ABM simulations validate the experimental results by replicating the main outcomes.

Generally, in a waveguide-based humidity sensors, increasing the relative humidity (RH) causes the cladding refractive index (RI) to increase due to cladding water absorption. However, if graphene oxide (GO) is used, a reverse phenomenon is seen due to a gap increase in graphene layers. In this paper, this interesting property is applied in order to fabricate differential humidity sensor using the difference between RI of reduced GO (rGO) and nano-anatase TiO2 in a chip. First, a new approach is proposed to prepare high quality nano-anatase TiO2 in solution form making the fabrication process simple and straightforward. Then, the resulted solutions (TiO2 and GO) are effortlessly drop casted and reduced on SU8 two channels waveguide and extensively examined against several humid conditions. Investigating the sensitivity and performance (response time) of the device, reveals a great linearity in a wide range of RH (35% to 98%) and a variation of more than 30 dB in transmitted optical power with a response time of only ~0.7 sec. The effect of coating concentration and UV treatment are studied on the performance and repeatability of the sensor and the attributed mechanisms explained. In addition, we report that using the current approach, devices with high sensitivity and very low response time of only 0.3 sec can be fabricated. Also, the proposed device was comprehensively compared with other state of the art proposed sensors in the literature and the results were promising. Since high sensitivity ~0.47dB/%RH and high dynamic performances were demonstrated, this sensor is a proper choice for biomedical applications.

The AIDS is a chronic disease and the researchers still exert their high efforts to reach the cure of HIV infection. The most common treatment is the antiretroviral therapy (cART) and the virus can be more effected if the patients stop using cART. The other problem is that the CD8+ T cells might be exhausted by persistent immune activation by cART. This paper introduces fractional-order into a mathematical model of HIV infection combining with stem cell therapy and control the infection by the immune system cells (CD8+ T cells). The paper introduced the numerical solutions for the mathematical model. The results show that the stem cell therapy with the activation of immune system cells might causes the cure for a HIV patient. This results are consistent with medical studies. Also, we proposed the effect of the fractional order (α) on the figures of the components.

Linear aggregation is present in some animals, such as the coordinated movement of ants and the migration of caterpillars and spinylobsters, but none has been reported on rotifers. The rotifers were collected and clone cultured in the laboratory at 25 ± 1°C, under natural light (light intensity ~130 lx, L:D = 14:10). The culture medium(pH = 7.3) was formulated as described by Suga et al., and rotifers were fed on the micro algae Scenedesmus obliquus grown in HB-4 medium to the exponential growth stage. When density was high (150 individuals ml-1), the behavior of rotifers was observed using a stereo microscope (Motic ES-18TZLED). In this paper, linear aggregation in Brachionus calyciflorus was found for the first time, and experiments were carried out to verify the correlation between linear aggregation and culture density of B. calyciflorus. With the increase of density, the number of aggregations increase, the number of individuals in the aggregation increased, and the maintenance time of the aggregation was also increased. Therefore, we speculate that the formation of aggregates is related to density and may be a behavioral signal of density increase, which may transmit information between density increase and formation of dormant eggs.

Image segmentation is an indispensable process in the visualization of human tissues, particularly during clinical analysis of brain magnetic resonance (MR) images. For many human experts, manual segmentation is a difficult and time consuming task, which makes an automated brain MR image segmentation method desirable. In this regard, this paper presents a new segmentation method for brain MR images, integrating judiciously the merits of rough-fuzzy computing and multiresolution image analysis technique. The proposed method assumes that the major brain tissues, namely, gray matter, white matter, and cerebrospinal fluid from the MR images are considered to have different textural properties. The dyadic wavelet analysis is used to extract the scale-space feature vector for each pixel, while the rough-fuzzy clustering is used to address the uncertainty problem of brain MR image segmentation. An unsupervised feature selection method is introduced, based on maximum relevance-maximum significance criterion, to select relevant and significant textural features for segmentation problem, while the mathematical morphology based skull stripping preprocessing step is proposed to remove the non-cerebral tissues like skull. The performance of the proposed method, along with a comparison with related approaches, is demonstrated on a set of synthetic and real brain MR images using standard validity indices.

The compartment model analysis using medical imaging data is the well-established but extremely time consuming technique for quantifying the changes in microvascular physiology of targeted organs in clinical patients after antivascular therapies. In this paper, we present a first graphics processing unit-accelerated method for compartmental modeling of medical imaging data. Using this approach, we performed the analysis of dynamic contrast-enhanced magnetic resonance imaging data from bevacizumab-treated glioblastoma patients in less than one minute per slice without losing accuracy. This approach reduced the computation time by more than 120-fold comparing to a central processing unit-based method that performed the analogous analysis steps in serial and more than 17-fold comparing to the algorithm that optimized for central processing unit computation. The method developed in this study could be of significant utility in reducing the computational times required to assess tumor physiology from dynamic contrast-enhanced magnetic resonance imaging data in preclinical and clinical development of antivascular therapies and related fields.

This paper presents the software application ORION (All-sky camera geOmetry calibRation from star positIONs). This software has been developed with the aim of providing geometrical calibration to all-sky cameras, i.e. assess which sky coordinates (zenith and azimuth angles) correspond to each camera pixel. It is useful to locate bodies over the celestial vault, like stars and planets, in the camera images. The user needs to feed ORION with a set of cloud-free sky images captured at night-time for obtaining the calibration matrices. ORION searches the position of various stars in the sky images. This search can be automatic or manual. The sky coordinates of the stars and the corresponding pixel positions in the camera images are used together to determine the calibration matrices. The calibration is based on three parameters: the pixel position of the sky zenith in the image; the shift angle of the azimuth viewed by the camera with respect to the real North; and the relationship between the sky zenith angle and the pixel radial distance regards to the sky zenith in the image. In addition, ORION includes other features to facilitate its use, such as the check of the accuracy of the calibration. An example of ORION application is shown, obtaining the calibration matrices for a set of images and studying the accuracy of the calibration to predict a star position. Accuracy is about 9.0 arcmin for the analyzed example using a camera with average resolution of 5.4 arcmin/pixel (about 1.7 pixels).

This paper presents the first empirical investigation that compares Euler and linear diagrams when they are used to represent set cardinality. A common approach is to use area-proportional Euler diagrams but linear diagrams can exploit length-proportional straight-lines for the same purpose. Another common approach is to use numerical annotations. We first conducted two empirical studies, one on Euler diagrams and the other on linear diagrams. These suggest that area-proportional Euler diagrams with numerical annotations and length-proportional linear diagrams without numerical annotations support significantly better task performance. We then conducted a third study to investigate which of these two notations should be used in practice. This suggests that area-proportional Euler diagrams with numerical annotations most effectively supports task performance and so should be used to visualize set cardinalities. However, these studies focused on data that can be visualized reasonably accurately using circles and the results should be taken as valid within that context. Future work needs to determine whether the results generalize both to when circles cannot be used and for other ways of encoding cardinality information.

Background The prevalence of stunting in South Sulawesi and West Sulawesi Province is relatively high. Studies reveal various household, parental, and child factors are associated with stunting. This paper aimed to determine the determinants of stunting among children under five in South and West Sulawesi Province using the 2013 and 2018 Indonesia Basic Health Survey. Methods This study was a secondary data analysis using the 2013 and 2018 Indonesian Basic Health Surveys. The unit of analysis was children under five years, and the study obtained 3641 and 4423 children in South Sulawesi Province from the 2013 and 2018 Indonesia Basic Health Survey, respectively, and 804 and 1059 children from the 2013 and 2018 Indonesia Basic Health Survey in West Sulawesi Province, respectively. The multivariable poisson regression model was conducted to determine the determinants of stunting. Results The results showed that the mean age of children in South Sulawesi and West Sulawesi Province was 31.1 months and 30.8 months, respectively, on 2013 survey compare to 29.6 months and 29.1 months on the 2018 survey. The determinants of stunting in children under five in South Sulawesi Province in 2013 survey were household with two children under five (APR:1.24; 95% CI: 1.1–1.3; p-value = 0.006), maternal BMI (APR: 1.1; 95% CI: 1.03–1.1; p-value = Conclusions The determinants of stunting in children under five in South Sulawesi Province are number of children under five in the household, maternal education, maternal weight, maternal height, maternal BMI, child’s age, and birthweight. Meanwhile, the determinants of stunting in children under five in West Sulawesi were wealth, maternal education, maternal weight, maternal BMI,, child’s age, child’s sex, and history of acute respiratory infection. Hence, intervention on household and child levels as well as maternal sociodemographic factors need to be addressed.

This paper classifies the karst landscapes of the Petén Plateau and defines the Mirador-Calakmul Karst Basin by illustrating the distribution of its karst hydrologic features. Archaeological and spatial research of the Mirador-Calakmul area of Guatemala and Mexico has shown it to be a karst basin with geopolitical implications. Current research characterizes the karst landscapes of the Petén Plateau, maps the distribution of karst hydrologic features, and delineates the basin in geomorphological terms. To further this aim, multiple forms of remote sensing data including orthophotographs, a satellite Digital Elevation Model, satellite multispectral images, and Light Detection and Ranging (LiDAR) data have been integrated to interpret the karst features in the study area. Outcrop study and thin section analysis of the upper Buena Vista Formation document that the dominant lithologies are a shallow water algal boundstone interbedded with terrestrial caliche. Karst landforms have been mapped over the Petén Plateau and we identify five karst landscapes, the largest of which is a fluviokarst landscape dominated by karst valleys. We further map karst hydrologic features including seasonal swamps, dolines, intermittent lakes, intermittent streams, solution-enhanced fractures, and springs all of which are characteristic of drainage basins. Boundaries of the karst basin are mapped from multiple lines of evidence including distribution of the karst valleys, a line of springs along the western boundary of the fluviokarst landscape, and a surface drainage analysis. We capture and classify hydrologic data points and develop a regional groundwater map that indicates subsurface flow from east to west within the basin. A drainage map illustrates the extensive system of karst valleys, boundaries, and inferred groundwater flow paths of the Mirador-Calakmul Karst Basin. It was within this geomorphological setting that the ancient Maya developed an extensive civilization during the Middle and Late Preclassic periods (1000 BCE-150 CE).

Background Hepatitis C virus (HCV) infection is one of the most common bloodborne viral infections reported in Pakistan. Frequent dialysis treatment of hemodialysis patients exposes them to a high risk of HCV infection. The main purpose of this paper is to quantify the prevalence of HCV in hemodialysis patients through a systematic review and meta-analysis. Methods We systematically searched PubMed, Medline, EMBASE, Pakistani Journals Online and Web of Science to identify studies published between 1 January 1995 and 30 October 2019, reporting on the prevalence of HCV infection in hemodialysis patients. Meta-analysis was performed using a random-effects model to obtain pooled estimates. A funnel plot was used in conjunction with Egger’s regression test for asymmetry and to assess publication bias. Meta-regression and subgroup analyses were used to identify potential sources of heterogeneity among the included studies. This review was registered on PROSPERO (registration number CRD42019159345). Results Out of 248 potential studies, 19 studies involving 3446 hemodialysis patients were included in the meta-analysis. The pooled prevalence of HCV in hemodialysis patients in Pakistan was 32.33% (95% CI: 25.73–39.30; I2 = 94.3%, p < 0.01). The subgroup analysis showed that the prevalence of HCV among hemodialysis patients in Punjab was significantly higher (37.52%; 95% CI: 26.66–49.03; I2 = 94.5, p < 0.01) than 34.42% (95% CI: 14.95–57.05; I2 = 91.3%, p < 0.01) in Baluchistan, 27.11% (95% CI: 15.81–40.12; I2 = 94.5, p < 0.01) in Sindh and 22.61% (95% CI: 17.45–28.2; I2 = 78.6, p < 0.0117) in Khyber Pukhtoonkhuwa. Conclusions In this study, we found a high prevalence (32.33%) of HCV infection in hemodialysis patients in Pakistan. Clinically, hemodialysis patients require more attention and resources than the general population. Preventive interventions are urgently needed to decrease the high risk of HCV infection in hemodialysis patients in Pakistan.

Evaluation of brainstem pathways with diffusion tensor imaging (DTI) and tractography may provide insights into pathophysiologies associated with dysfunction of key brainstem circuits. However, identification of these tracts has been elusive, with relatively few in vivo human studies to date. In this paper we proposed an automated approach for reconstructing nine brainstem fiber trajectories of pathways that might be involved in pain modulation. We first performed native-space manual tractography of these fibers in a small normative cohort of participants and confirmed the anatomical precision of the results using existing anatomical literature. Second, region-of-interest pairs were manually defined at each extracted fiber’s termini and nonlinearly warped to a standard anatomical brain template to create an atlas of the region-of-interest pairs. The resulting atlas was then transformed non-linearly into the native space of 17 veteran patients’ brains for automated brainstem tractography. Lastly, we assessed the relationships between the integrity levels of the obtained fiber bundles and pain severity levels. Fractional anisotropy (FA) measures derived using automated tractography reflected the respective tracts’ FA levels obtained via manual tractography. A significant inverse relationship between FA and pain levels was detected within the automatically derived dorsal and medial longitudinal fasciculi of the brainstem. This study demonstrates the utility of DTI in exploring brainstem circuitries involved in pain processing. In this context, the described automated approach is a viable alternative to the time-consuming manual tractography. The physiological and functional relevance of the measures derived from automated tractography is evidenced by their relationships with individual pain severities.

Traffic congestion brings not only delay and inconvenience, but other associated national concerns, such as greenhouse gases, air pollutants, road safety issues and risks. Identification, measurement, tracking, and control of urban recurrent congestion are vital for building a livable and smart community. A considerable amount of works has made contributions to tackle the problem. Several methods, such as time-based approaches and level of service, can be effective for characterizing congestion on urban streets. However, studies with systemic perspectives have been minor in congestion quantification. Resilience, on the other hand, is an emerging concept that focuses on comprehensive systemic performance and characterizes the ability of a system to cope with disturbance and to recover its functionality. In this paper, we symbolized recurrent congestion as internal disturbance and proposed a modified metric inspired by the well-applied “R4” resilience-triangle framework. We constructed the metric with generic dimensions from both resilience engineering and transport science to quantify recurrent congestion based on spatial-temporal traffic patterns and made the comparison with other two approaches in freeway and signal-controlled arterial cases. Results showed that the metric can effectively capture congestion patterns in the study area and provides a quantitative benchmark for comparison. Also, it suggested not only a good comparative performance in measuring strength of proposed metric, but also its capability of considering the discharging process in congestion. The sensitivity tests showed that proposed metric possesses robustness against parameter perturbation in Robustness Range (RR), but the number of identified congestion patterns can be influenced by the existence of ϵ. In addition, the Elasticity Threshold (ET) and the spatial dimension of cell-based platform differ the congestion results significantly on both the detected number and intensity. By tackling this conventional problem with emerging concept, our metric provides a systemic alternative approach and enriches the toolbox for congestion assessment. Future work will be conducted on a larger scale with multiplex scenarios in various traffic conditions., PLoS ONE, 13 (1), ISSN:1932-6203

In recent years, formalization and reasoning of topological relations have become a hot topic as a means to generate knowledge about the relations between spatial objects at the conceptual and geometrical levels. These mechanisms have been widely used in spatial data query, spatial data mining, evaluation of equivalence and similarity in a spatial scene, as well as for consistency assessment of the topological relations of multi-resolution spatial databases. The concept of computational fuzzy topological space is applied to simple fuzzy regions to efficiently and more accurately solve fuzzy topological relations. Thus, extending the existing research and improving upon the previous work, this paper presents a new method to describe fuzzy topological relations between simple spatial regions in Geographic Information Sciences (GIS) and Artificial Intelligence (AI). Firstly, we propose a new definition for simple fuzzy line segments and simple fuzzy regions based on the computational fuzzy topology. And then, based on the new definitions, we also propose a new combinational reasoning method to compute the topological relations between simple fuzzy regions, moreover, this study has discovered that there are (1) 23 different topological relations between a simple crisp region and a simple fuzzy region; (2) 152 different topological relations between two simple fuzzy regions. In the end, we have discussed some examples to demonstrate the validity of the new method, through comparisons with existing fuzzy models, we showed that the proposed method can compute more than the existing models, as it is more expressive than the existing fuzzy models.

PurposeThe aim of this experimental study was to investigate whether paper-and-pencil and computerized surveys administered in the school setting yield equivalent data quality indicators and risk behavior prevalence estimates.MethodsData were drawn from the European School Survey Project on Alcohol and Other Drugs (ESPAD®) carried out in Italy to monitor drug, alcohol, tobacco use and other risk-behaviors among Italian high school students aged 15-19 years. A sub-sample of schools was recruited for the study (1673 pupils). For each school, two entire randomly selected courses (from the first to the fifth grade) participated and were assigned randomly to the self-administered paper-and-pencil (N = 811) or computerized survey (N = 862). Differences in data quality were assessed using the following indicators: questionnaire completeness (missing gender and/or 50% of missing answers) and internal consistency (repetitive extreme response patterns). Separate logistic regression models were used to estimate the mode effect on the reporting of each risk behavior, controlling for gender and age. Finally, the prevalence estimates of the experimental study were compared to the results of the national ESPAD® study.ResultsThe computerized administration mode produced a higher proportion of invalid questionnaires, but the prevalence estimates generated from responses to the paper-and-pencil and computerized surveys were generally equivalent. Nevertheless, comparing these results with those of the national ESPAD® study, some differences in the prevalence rates were found.ConclusionsThe findings suggest that in a proctored school setting, the computerized survey mode yields almost the same results as the paper-and-pencil mode. However, because of the reliance on existing informatics facilities until when all schools in the country will be sufficiently equipped for the computerized data collection, they should be given the opportunity to choose between paper-and-pencil and computerized survey modes, in order to avoid a possible selection bias.

Even though mRNA expression levels are commonly used as a proxy for estimating functional differences that occur at the protein level, the relation between mRNA and protein expression is not well established. Further, no study to date has tested whether the evolutionary differences in mRNA expression observed between species reflect those observed in protein expression. Since a large proportion of mRNA expression differences observed between mammalian species appears to have no functional consequences for the phenotype, it is conceivable that many or most mRNA expression differences are not reflected at the protein level. If this is true, then differences in protein expression may largely reflect functional adaptations observed in species phenotypes. In this paper, we present the first direct comparison of mRNA and protein expression differences seen between humans and chimpanzees. We reproducibly find a significant positive correlation between mRNA expression and protein expression differences. This correlation is comparable in magnitude to that found between mRNA and protein expression changes at different developmental stages or in different physiological conditions within one species. Noticeably, this correlation is mainly due to genes with large expression differences between species. Our study opens the door to a new level of understanding of regulatory evolution and poses many new questions that remain to be answered.