Miracle-dz/UniFAR-FTUs huggingface dataset:
An Arthropod Enzyme, Dfurin 1, and a Vertebrate Furin Homolog Display Distinct Cleavage Site Sequence Preferences for a Shared Viral Proprotein Substrate

Abstract Alphaviruses replicate in vertebrate and arthropod cells and utilize a cellular enzyme called furin to process the PE2 glycoprotein precursor during virus replication in both cell types. Furin cleaves PE2 at a site immediately following a highly conserved four residue cleavage signal. Prior studies demonstrated that the amino acid immediately adjacent to the cleavage site influenced PE2 cleavage differently in vertebrate and mosquito cells (HW Heidner et al. 1996. Journal of Virology 70: 2069–2073.). This finding was tentatively attributed to potential differences in the substrate specificities of the vertebrate and arthropod furin enzymes or to differences in the carbohydrate processing phenotypes of arthropod and vertebrate cells. To further address this issue, we evaluated Sindbis virus replication and PE2 cleavage in the Chinese hamster, Cricetulus griseus Milne-Edwards (Rodentia: Cricetidae) ovary cells (CHO-K1) and in a CHO-K1-derived furin-negative cell line (RPE.40) engineered to stably express the Dfurin1 enzyme of Drosophila melanogaster Meigen (Diptera: Drosophilidae). Expression of Dfurin1 enhanced Sindbis virus titers in RPE.40 cells by a factor of 102 – 103, and this increase correlated with efficient cleavage of PE2. The PE2-cleavage phenotypes of viruses containing different amino acid substitutions adjacent to the furin cleavage site were compared in mosquito (C6/36), CHO-K1, and Dfurin1-expressing RPE.40 cells. This analysis confirmed that the substrate specificities of Dfurin1 and the putative mosquito furin homolog present in C6/36 cells are similar and suggested that the alternative PE2 cleavage phenotypes observed in vertebrate and arthropod cells were due to differences in substrate specificity between the arthropod and vertebrate furin enzymes and not to differences in host cell glycoprotein processing pathways.
Why don't you stick to them? Understanding factors influencing and counter-measures to combat deviant behavior towards organizational IT standards

Organizational information technology (IT) standards have become increasingly important for companies. However, insights from practice indicate that employees tend to violate these standards, generating a need for govern- ance and management mechanisms with which to successfully implement them in the organization. The literature reveals a lack of research on organizational IT standards' governance. Drawing on this finding, our research aims at identi- fying the factors that influence an employee's deviant behavior towards organi- zational IT standards. We therefore derive a conceptual model deductively from the literature, which we supplement with an interview study. Future research could use quantitative methods to validate this model. Our work enriches IS re- search and practitioner bodies of knowledge. We do so by first extending our knowledge of an employee's deviant behavior towards organizational IT stand- ards. Second, we provide valuable insights for organizations by providing start- ing points to improve their standardization efforts.
Application and evaluation of chinese version of zarit caregiver burden interview

Objective To evaluate the applicability and modified effect of the Chinese version of Zarit Caregiver Burden Interview(ZBI) in Chinese population.Methods ZBI scale was used to measure the caregivers' burden,the modified effect was evaluated through the reliability and validity analysis and the logistic regression that analysised risk factors of caregivers' burden.Results Caregivers' culture degree,the patient ADL score and the number of caregiver were the main risk factors of caregivers' burden,the Chinese version of ZBI reached the technology demand level of the scale.Conclusion Adding the number of caregiver can reduce caregivers' burden.Enlarging the survey population extent in can enhance the Chinese ZBI applicability.
Action Recognition Using Local Consistent Group Sparse Coding with Spatio-Temporal Structure

This paper presents a novel and efficient framework for human action recognition through integrating the local consistent group sparse representation with spatio-temporal structure of each video sequence. We firstly propose a sparse encoding scheme named local consistent group sparse coding (LCGSC) to generate the sparse representation of each video sequence. The novel encoding scheme takes global structural information of features belonging to one group into consideration as well as the local correlations between similar features. In order to incorporate the spatio-temporal structures, an average location (AL) model is proposed to describe the distribution of each visual word along the spatio-temporal coordinates on the basis of the obtained sparse codes. Eventually, each video sequence is jointly represented by the sparse representation and the spatio-temporal layouts which fully model its motion, appearance and spatio-temporal information. Our framework is computationally efficient and achieves comparable performance on the challenging datasets with state-of-the-art methods.
Interroom radiative couplings through windows and large openings in buildings: Proposal of a simplified model

A simplified model of indoor short wave radiation couplings adapted to multi-zone simulations is proposed, thanks to a simplifying hypothesis and to the introduction of an indoor short wave exchange matrix. The specific properties of this matrix appear useful to quantify the thermal radiation exchanges between the zones separated by windows or large openings. Integrated in CODYRUN software, this module is detailed and compared to experimental measurements carried out on a real scale tropical building.
Modular Reactive Neurocontrol for Biologically Inspired Walking Machines

A neurocontroller is described which generates the basic locomotion and controls the sensor-driven behavior of a four-legged and a six-legged walking machine. The controller utilizes discrete-time neurodynamics, and is of modular structure. One module is for processing sensor signals, one is a neural oscillator network serving as a central pattern generator, and the third one is a so-called velocity regulating network. These modules are small and their structures and their functionalities are analyzable. In combination, they enable the machines to autonomously explore an unknown environment, to avoid obstacles, and to escape from corners or deadlock situations. The neurocontroller was developed and tested first using a physical simulation environment, and then it was successfully transferred to the physical walking machines. Locomotion is based on a gait where the diagonal legs are paired and move together, e.g. trot gait for the four-legged walking machine and tripod gait for the six-legged walking machine. The controller developed is universal in the sense that it can easily be adapted to different types of even-legged walking machines without changing the internal structure and its parameters.
A method for enhancing controllability with adding links in directed networks

In this paper a method to enhance controllability of directed network by adding links is proposed. The adding strategy is based on node degree ratio. Numerical simulation on two network models demonstrates that this method is more effective in enhancing controllability than random adding links method. The effectiveness of this method lies in reducing the degree heterogeneity of network, which is helpful to enhance the controllability of network. We expect our research provide an effective and practical method to enhance the controllability of directed networks.
Risk prediction of pulmonary tuberculosis using genetic and conventional risk factors in adult Korean population

A complex interplay among host, pathogen, and environmental factors is believed to contribute to the risk of developing pulmonary tuberculosis (PTB). The lack of replication of published genome-wide association study (GWAS) findings limits the clinical utility of reported single nucleotide polymorphisms (SNPs). We conducted a GWAS using 467 PTB cases and 1,313 healthy controls obtained from two community-based cohorts in Korea. We evaluated the performance of PTB risk models based on different combinations of genetic and nongenetic factors and validated the results in an independent Korean population comprised of 179 PTB cases and 500 healthy controls. We demonstrated the polygenic nature of PTB and nongenetic factors such as age, sex, and body mass index (BMI) were strongly associated with PTB risk. None of the SNPs achieved genome-wide significance; instead, we were able to replicate the associations between PTB and ten SNPs near or in the genes, CDCA7, GBE1, GADL1, SPATA16, C6orf118, KIAA1432, DMRT2, CTR9, CCDC67, and CDH13, which may play roles in the immune and inflammatory pathways. Among the replicated SNPs, an intergenic SNP, rs9365798, located downstream of the C6orf118 gene showed the most significant association under the dominant model (OR = 1.59, 95% CI 1.32–1.92, P = 2.1×10−6). The performance of a risk model combining the effects of ten replicated SNPs and six nongenetic factors (i.e., age, sex, BMI, cigarette smoking, systolic blood pressure, and hemoglobin) were validated in the replication set (AUC = 0.80, 95% CI 0.76–0.84). The strategy of combining genetic and nongenetic risk factors ultimately resulted in better risk prediction for PTB in the adult Korean population.
SUMIS: Near-Optimal Soft-In Soft-Out MIMO Detection With Low and Fixed Complexity

The fundamental problem of interest here is soft-input-soft-output multiple-input-multiple-output (MIMO) detection. We propose a method, referred to as subspace marginalization with interference suppression (SUMIS), that yields unprecedented performance at low and fixed (deterministic) complexity. Our method provides a well-defined tradeoff between computational complexity and performance. Apart from an initial sorting step consisting of selecting channel-matrix columns, the algorithm involves no searching nor algorithmic branching; hence the algorithm has a completely predictable run-time and allows for a highly parallel implementation. We numerically assess the performance of SUMIS in different practical settings: full/partial channel state information, sequential/iterative decoding, and low/high rate outer codes. We also comment on how the SUMIS method performs in systems with a large number of transmit antennas.
Measuring systematic long-term trajectories of school effectiveness improvement

ABSTRACT The objective of this study was to identify trajectories of school improvement experienced by Chilean elementary schools over the last decade. Using econometric analysis and controlling for potential confounding factors, we created an index of school performance combining outcome indicators focused on different school dimensions, and estimated the 2002/2010 evolution of school improvement for all Chilean schools with available data. Broadly, we estimated an average increase in the school performance of about 0.19 SD; nevertheless, while 41% of the schools increased their educational performance by at least 0.1 SD, 25% of the schools decreased it during the same period; we also found that improving school effectiveness was more probable among schools with lower student socioeconomic status (SES). Finally, we found that the observed school improvement trajectories tended to be non-linear; thus, we estimated that only 13.4% of the schools improved their performance in a systematic way during the entire decade.
Communication and medication refill adherence: the Diabetes Study of Northern California.

BACKGROUND Poor medication refill adherence contributes to poor cardiometabolic control and diabetes outcomes. Studies linking communication between patients and health care providers to adherence often use self-reported adherence and have not explored differences across communication domains or therapeutic indications. METHODS To investigate associations between patient communication ratings and cardiometabolic medication refill adherence, we conducted a cross-sectional analysis of 9377 patients in the Diabetes Study of Northern California (DISTANCE), a race-stratified, random sample of Kaiser Permanente survey respondents. Eligible participants received 1 or more oral hypoglycemic, lipid-lowering, or antihypertensive medication in the 12 months preceding the survey. Communication was measured with a 4-item Consumer Assessment of Healthcare Providers and Systems Survey (CAHPS) score and 4 items from the Trust in Physicians and Interpersonal Processes of Care instruments. Poor adherence was classified as greater than a 20% continuous medication gap for ongoing medication therapies. Using modified least squares regression, we calculated differences in poor adherence prevalence for a 10-point decrease in CAHPS score and compared higher vs lower communication ratings on other items, adjusting for necessary sociodemographic and medical confounders derived from a directed acyclic graph. RESULTS In this cohort, 30% had poor cardiometabolic medication refill adherence. For each 10-point decrease in CAHPS score, the adjusted prevalence of poor adherence increased by 0.9% (P=.01). Compared with patients offering higher ratings, patients who gave health care providers lower ratings for involving patients in decisions, understanding patients' problems with treatment, and eliciting confidence and trust were more likely to have poor adherence, with absolute differences of 4% (P=.04), 5% (P=.02), and 6% (P=.03), respectively. Associations between communication and adherence were somewhat larger for hypoglycemic medications than for other medications. CONCLUSIONS Poor communication ratings were independently associated with objectively measured inadequate cardiometabolic medication refill adherence, particularly for oral hypoglycemic medications. Future studies should investigate whether improving communication skills among clinicians with poorer patient communication ratings could improve their patients' cardiometabolic medication refill adherence and outcomes.
Knowledge Integration in Software Teams: An Assessment of Project Uncertainty and IT-Usage as Antecedents

Organizational knowledge resources typically exist in specialized pockets scattered across the firm. As distributed knowledge systems, firms’ capacity to manage their knowledge resources is linked with their ability to integrate these pockets of specialized knowledge. Firms are increasingly depending on teams to strategically consolidate their dispersed knowledge into productive outcomes. Teams integrate knowledge from external sources with internal knowledge such as skills, know-how, and expertise of their members to create project outcomes. The aim of this research will be to examine how knowledge integration in software teams is influenced by project uncertainty and IT-usage.
Multiple-Human Tracking by Iterative Data Association and Detection Update

Multiple-object tracking is an important task in automated video surveillance. In this paper, we present a multiple-human-tracking approach that takes the single-frame human detection results as input and associates them to form trajectories while improving the original detection results by making use of reliable temporal information in a closed-loop manner. It works by first forming tracklets, from which reliable temporal information is extracted, and then refining the detection responses inside the tracklets, which also improves the accuracy of tracklets' quantities. After this, local conservative tracklet association is performed and reliable temporal information is propagated across tracklets so that more detection responses can be refined. The global tracklet association is done last to resolve association ambiguities. Experimental results show that the proposed approach improves both the association and detection results. Comparison with several state-of-the-art approaches demonstrates the effectiveness of the proposed approach.
From Local Similarities to Global Coding: A Framework for Coding Applications

Feature coding has received great attention in recent years as a building block of many image processing algorithms. In particular, the importance of the locality assumption in coding approaches has been studied in many previous works. We review this assumption and claim that using the similarity of data points to a more global set of anchor points does not necessarily weaken the coding method, as long as the underlying structure of the anchor points is considered. We propose to capture the underlying structure by assuming a random walker over the anchor points. We also show that our method is a fast approximation to the diffusion map kernel. Experiments on various data sets show that with a knowledge of the underlying structure of anchor points, different state-of-the-art coding algorithms may boost their performance in different learning tasks by utilizing the proposed method.
Spatial and Spectral Analysis and Modeling of Transversal Chromatic Aberrations and their Compensation

The wavelength-dependency of the refraction indices in optical systems involves chromatic aberrations: one object point is not projected on exactly one image point on the sensor plane, but dispersed depending on its wavelengths in a rainbow-like manner due to the wavelength-dependency. These distortions have already been analyzed for the three broadband color planes red, green and blue of an RGB camera for example. As far as the authors know, no analysis was performed yet for more than three narrow wavelength bands and each color plane was considered separately so far. In this paper, we describe the measurement of chromatic aberrations for multiple narrowband color channels and extend the models from the literature to characterize these distortions. We then link the parameters obtained for all color channels in order to include the wavelength-dependency into the models of the distortions. This leads to a more general model for the chromatic aberrations, calculating the distortions as a function of the wavelength and the image position. We then compensate the chromatic aberrations using these models and finally estimate their accuracy.
Good Fences Make Good Neighbors: Endogenous Property Rights in a Game of Conflict

This paper derives the conditions under which property rights can arise in an anarchy equilibrium. The creation of property rights requires that players devote part of their endowment to the public good of property rights protection. In the Nash equilibrium, players contribute zero to the protection of property rights. In contrast, a king who provides property rights protection paid for by a tax on endowments can completely eliminate conflict, but such a king has an incentive to take the surplus for himself. Thus players have an incentive to find a solution that keeps power in their own hands. In a social contract, players first credibly commit part of their endowments to providing property rights and then allocate the balance of their endowments between production and conflict. While property rights can arise under a social contract if the productivity of resources relative to the size of the population is sufficiently high, these property rights may be less than perfectly secure. Nevertheless, for sufficiently high productivity of resources relative to the size of the population, the social contract welfare dominates autocracy. Key Words:
T-Storm: Traffic-Aware Online Scheduling in Storm

Storm has emerged as a promising computation platform for stream data processing. In this paper, we first show inefficiencies of the current practice of Storm scheduling and challenges associated with applying traffic-aware online scheduling in Storm via experimental results and analysis. Motivated by our observations, we design and implement a new stream data processing system based on Storm, namely, T-Storm. Compared to Storm, T-Storm has the following desirable features: 1) based on runtime states, it accelerates data processing by leveraging effective traffic-aware scheduling for assigning/re-assigning tasks dynamically, which minimizes inter-node and inter-process traffic while ensuring no worker nodes are overloaded, 2) it enables fine-grained control over worker node consolidation such that T-Storm can achieve better performance with even fewer worker nodes, 3) it allows hot-swapping of scheduling algorithms and adjustment of scheduling parameters on the fly, and 4) it is transparent to Storm users (i.e., Storm applications can be ported to run on T-Storm without any changes). We conducted real experiments in a cluster using well-known data processing applications for performance evaluation. Extensive experimental results show that compared to Storm (with the default scheduler), T-Storm can achieve over 84% and 27% speedup on lightly and heavily loaded topologies respectively (in terms of average processing time) with 30% less number of worker nodes.
Market Impacts on Land-Use Change: An Agent-Based Experiment

Land-use change in a market economy, particularly at the urban–rural fringe in North America, is shaped through land and housing markets. Although market activities are at the core of economic studies of land-use change, many market elements are neglected by coupled human–environment models. We scrutinized the effects of the level of detail of market representation using an abstract, agent-based model of land-use change. This model includes agents representing land buyers and sellers and their respective market-based decision-making behaviors. Our results show that although incorporating key market elements, particularly budget constraints and competitive bidding, in land-use models generally alters projected land-use patterns, their impacts differ significantly depending on the level of detail of market representation. Consistent with theories of land change, our research confirms that budget constraints can considerably reduce the projected quantity of land-use change. The effects of competitive bidding, however, are more complex and depend on buyers’ budgets, their relative preferences for proximity versus open-space amenities, and the size of neighborhoods. Market competition might reduce or increase the quantity of land-use change and the degree of sprawl in the simulated landscapes. Because of the strong effects of market elements on resulting patterns, adequate representation of the structure of markets is important for capturing and characterizing the complexity inherent in coupled human–environment systems.
Boundary-induced wavelength selection in a one-dimensional pattern-forming system.

We have measured the stability boundary for steady electroconvection in thin, freely suspended smectic liquid crystal films. As the voltage across the film, or the film length, is varied, convective vortices are created or destroyed at the ends of the film to keep the pattern wave number within a stable range. The measured stability boundary lies substantially inside the Eckhaus boundary for this system. Our results are consistent with a mechanism for boundary-induced wavelength selection proposed by Cross et al. [Phys. Rev. Lett. 45, 898 (1980)].