Miracle-dz/UniFAR-FTUs huggingface dataset:
Network Analysis Reveals a Common Host–Pathogen Interaction Pattern in Arabidopsis Immune Responses

Many plant pathogens secrete virulence effectors into host cells to target important proteins in host cellular network. However, the dynamic interactions between effectors and host cellular network have not been fully understood. Here, an integrative network analysis was conducted by combining Arabidopsis thaliana protein–protein interaction network, known targets of Pseudomonas syringae and Hyaloperonospora arabidopsidis effectors, and gene expression profiles in the immune response. In particular, we focused on the characteristic network topology of the effector targets and differentially expressed genes (DEGs). We found that effectors tended to manipulate key network positions with higher betweenness centrality. The effector targets, especially those that are common targets of an individual effector, tended to be clustered together in the network. Moreover, the distances between the effector targets and DEGs increased over time during infection. In line with this observation, pathogen-susceptible mutants tended to have more DEGs surrounding the effector targets compared with resistant mutants. Our results suggest a common plant–pathogen interaction pattern at the cellular network level, where pathogens employ potent local impact mode to interfere with key positions in the host network, and plant organizes an in-depth defense by sequentially activating genes distal to the effector targets.
Chaotic Adaptive Control of Non-Binary TTCM Decoding Algorithm

This paper presents a non-binary Turbo Trellis Coded Modulation (TTCM) decoder-based multidimensional 3-D (Maximum A Posteriori) MAP algorithm. The proposed system deals with Non-binary error control coding of the TTCM scheme for transmissions over the AWGN channel. The idea of Non-binary codes has been extended for symbols defined over rings of integers, which outperform binary codes with only a small increase in decoding complexity. This paper employs chaos technique at the decoding stage of the Nonbinary TTCM decoder, since the turbo decoding algorithm can be viewed as a high-dimensional dynamical nonlinear system. A simple technique to control transient chaos of turbo decoding algorithm is devised. The analysis of non-linear discrete deterministic Non-binary TTCM decoder used the Binary (0-1) test for chaos to distinguish between regular and chaotic dynamics. The most powerful aspect of the method is that it is independent of the nature of the vector field (or data) under consideration. The simulation results show that the performance of the non-binary TTCM decoding algorithmbased chaos technique outperforms the binary and non-binary decoding methods.
Coordinating Multiple Disparity Proposals for Stereo Computation

While great progress has been made in stereo computation over the last decades, large textureless regions remain challenging. Segment-based methods can tackle this problem properly, but their performances are sensitive to the segmentation results. In this paper, we alleviate the sensitivity by generating multiple proposals on absolute and relative disparities from multi-segmentations. These proposals supply rich descriptions of surface structures. Especially, the relative disparity between distant pixels can encode the large structure, which is critical to handle the large textureless regions. The proposals are coordinated by point-wise competition and pairwise collaboration within a MRF model. During inference, a dynamic programming is performed in different directions with various step sizes, so the long-range connections are better preserved. In the experiments, we carefully analyzed the effectiveness of the major components. Results on the 2014 Middlebury and KITTI 2015 stereo benchmark show that our method is comparable to state-of-the-art.
The Electoral Origins of Polarized Politics

Data from the 2010 Cooperative Congressional Election Study are examined to determine the extent to which partisan polarization is a popular as well as an elite phenomenon. The evidence indicates that ordinary Americans as well as political elites divide consistently along party lines over a broad range of issues and legislative preferences. Partisan ideological divisions are not confined to the political class; they extend downward into the citizenry to the degree that people are actively involved in politics. The coincidence of partisan differences across issues results in a bimodal distribution of aggregate preferences among voters, showing that partisan sorting can by itself polarize the electorate even if sorted partisans do not adopt extreme positions on individual issues. The distribution of partisan preferences is even more sharply bimodal and polarized when the electoral constituencies of the congressional parties are compared, so the electoral process sustains elite polarization. Primary electoral constituencies tend to be even more extreme, particularly on the Republican side, deterring departures from party orthodoxy and thus movement toward the median voter.
The Endothelial Cell Protein C Receptor

The Protein C Pathway before EPCR The protein C anticoagulant pathway is recognized as a major control mechanism of blood coagulation [reviewed in]. Defects in protein C, protein S and thrombomodulin have all been implicated as predisposing factors for the development of venous thrombosis (2-5) and, under some circumstances, contributing to arterial thrombosis (6-8). The pathway is initiated when thrombin binds to thrombomodulin (TM), an integral membrane receptor found primarily on endothelium, but also on a variety of other cells including monocytes. The thrombin-TM complex activates protein C rapidly and can also activate a procarboxypeptidase B, often referred to as TAFI, thrombin activatable fibrinolysis inhibitor. Once activated protein C (APC) is generated, it binds to protein S and can then inactivate either factor Va or factor VIIIa on the surface of negatively charged phospholipids or on the membranes of activated cells. The thrombin-TM complex is inhibited by either antithrombin or protein C inhibitor. The estimated half life of the complex at plasma levels of these inhibitors is only a few seconds. Since EPCR is among the newest proteins in the coagulation/anticoagulation area to be identified, I have included references to abstracts in this review that are yet to be published in full.
An historical framework for psychiatric nosology

This essay, which seeks to provide an historical framework for our efforts to develop a scientific psychiatric nosology, begins by reviewing the classificatory approaches that arose in the early history of biological taxonomy. Initial attempts at species definition used top-down approaches advocated by experts and based on a few essential features of the organism chosen a priori. This approach was subsequently rejected on both conceptual and practical grounds and replaced by bottom-up approaches making use of a much wider array of features. Multiple parallels exist between the beginnings of biological taxonomy and psychiatric nosology. Like biological taxonomy, psychiatric nosology largely began with ‘expert’ classifications, typically influenced by a few essential features, articulated by one or more great 19th-century diagnosticians. Like biology, psychiatry is struggling toward more soundly based bottom-up approaches using diverse illness characteristics. The underemphasized historically contingent nature of our current psychiatric classification is illustrated by recounting the history of how ‘Schneiderian’ symptoms of schizophrenia entered into DSM-III. Given these historical contingencies, it is vital that our psychiatric nosologic enterprise be cumulative. This can be best achieved through a process of epistemic iteration. If we can develop a stable consensus in our theoretical orientation toward psychiatric illness, we can apply this approach, which has one crucial virtue. Regardless of the starting point, if each iteration (or revision) improves the performance of the nosology, the eventual success of the nosologic process, to optimally reflect the complex reality of psychiatric illness, is assured.
Using a multiclass novelty classifier for face recognition

Face recognition, one of the most explored themes in biometry, is used in a wide range of applications: access control, forensic detection, surveillance and monitoring system, robotic and human machine interaction. In this paper, a new classifier is proposed for face recognition. The performance of this new classifier is compared with the performance of the KNN classifier. The face image database used was the ORL. For feature extractions the following methods were employed: PCA, 2DPCA and (2D)2PCA. The performance tests of both classifiers were done both in verification and identification mode. In identification mode, the recognition rate with the leave-one-out strategy is equal to 100% with PCA, 2DPCA and (2D)2PCA. In the verification mode, the recognition rate is 100% with PCA and 2DPCA and 97.5% for (2D)2PCA. For the half-half strategy, the best recognition rate in the identification mode was obtained with (2D)2PCA, 98.5%, and in the verification mode, with PCA, 88%.
Analysis of the anti‐allodynic effects of combination of a synthetic cannabinoid and a selective noradrenaline re‐uptake inhibitor in nerve injury‐induced neuropathic mice

Combining drugs not only reduces specific adverse effects of each of the drug at a higher dose but also may lead to enhanced efficacy. Tapentadol is a recently discovered analgesic possessing μ‐opioid receptor agonism and noradrenaline re‐uptake inhibition in a single molecule. Taking into consideration, the pharmacological similarities between opioids and cannabinoids, we assumed that combination of cannabinoids with noradrenaline re‐uptake inhibitors might also be effective. We therefore aimed to determine whether combining 1:1, 1:3 and 3:1 fixed ratios of the synthetic cannabinoid WIN 55,212‐2 and the selective noradrenaline re‐uptake inhibitor maprotiline exert anti‐allodynic synergy on nerve‐injured neuropathic mice.
Distribution of Chemokine Receptor CCR2 and CCR5 Genotypes and Their Relative Contribution to Human Immunodeficiency Virus Type 1 (HIV-1) Seroconversion, Early HIV-1 RNA Concentration in Plasma, and Later Disease Progression

ABSTRACT At the CC (β) chemokine receptor 2 (CCR2) and CCR5 loci, combinations of common single-nucleotide polymorphisms (SNPs) and a 32-bp deletion (Δ32) form nine stable haplotypes (designated A through G*2). The distribution of these CCR2-CCR5 haplotypes was examined among 703 participants in the Multicenter AIDS Cohort Study (MACS), the District of Columbia Gay (DCG) Study, and the San Francisco Men’s Health Study (SFMHS). Highly exposed and persistently seronegative (HEPS; n = 90) Caucasian men from MACS more frequently carried heterozygous G*2 (Δ32) genotypes (especially A/G*2) and less frequently carried the homozygous E/E genotype compared with 469 Caucasian seroconverters (SCs) from the same cohort (P = 0.004 to 0.042). Among 341 MACS Caucasian SCs with 6- to 12-month human immunodeficiency virus type 1 (HIV-1) seroconversion intervals and no potent antiretroviral therapy, mean plasma HIV-1 RNA level during the initial 42 months after seroconversion was higher in carriers of the E/E genotype and lower in those with the 64I-bearing haplotype F*2 or the Δ32-bearing haplotype G*2 (and especially genotypes A/G*2 and F*2/G*2). A multivariable model containing these CCR markers showed significant composite effects on HIV-1 RNA at each of four postconversion intervals (P = 0.0004 to 0.050). In other models using time to AIDS as the endpoint, the same markers showed more modest contributions (P = 0.08 to 0.24) to differential outcome during 11.5 years of follow-up. Broadly consistent findings in the larger MACS Caucasian SCs and the smaller groups of MACS African-American SCs and the DCG and SFMHS Caucasian SCs indicate that specific CCR2-CCR5 haplotypes or genotypes mediate initial acquisition of HIV-1 infection, early host-virus equilibration, and subsequent pathogenesis.
Personal Names and Cultural Change: A Study of the Naming Patterns of Italians and Jews in the United States in 1910

Although individual and personal, names take on their significance in social interaction. Since the context of social interaction changes with immigration, names can be expected to change as well. In this paper, we use information from the Public Use Sample of the 1910 U.S. census to compare the patterns of personal (given) names of first- and second-generation Italian and Jewish immigrants and native-born whites of native parentage, and to examine the association of naming patterns of immigrants with several measures indicating interaction with those outside the ethnic group. Because the information from the census is at a single point in time, we also draw on interviews with elderly Italian and Jewish women in order to provide more direct evidence of change and of the contexts in which this change occurred.
Between Teaching and Learning: Development of the Team Mainz Rolling Brains for the Simulation League of RoboCup 99

The development of our team for RoboCup ’99 is mainly oriented towards a transparent way of transferring explicit knowledge into the agent control and its combination with learning algorithms capable of fine-tuning the acquired skills. The explicit knowledge is formulated in terms of rules, the non-explicit knowledge is to be realized as a set of parameters adapted by hierarchical reinforcement learning and by rule evolution. The teaching process for the implicit learning is not determined by a simple fixed reinforcement return, but by a — possibly complex — agent that represents a human or an automated coach.
Parser Evaluation Using Derivation Trees: A Complement to evalb

This paper introduces a new technique for phrase-structure parser analysis, categorizing possible treebank structures by integrating regular expressions into derivation trees. We analyze the performance of the Berkeley parser on OntoNotes WSJ and the English Web Treebank. This provides some insight into the evalb scores, and the problem of domain adaptation with the web data. We also analyze a “test-ontrain” dataset, showing a wide variance in how the parser is generalizing from different structures in the training material.
Large-Scale Evaluation of a Vulnerability Analysis Framework

Ensuring that exploitable vulnerabilities do not exist in a piece of software written using type-unsafe languages (e.g., C/C++) is still a challenging, largely unsolved problem. Current commercial security tools are improving but still have shortcomings, including limited detection rates for certain vulnerability classes and high false-positive rates (which require a security expert's knowledge to analyze). To address this there is a great deal of ongoing research in software vulnerability detection and mitigation as well as in experimentation and evaluation of the associated software security tools. We present the second-generation prototype of the MINESTRONE architecture along with a large-scale evaluation conducted under the IARPA STONESOUP program. This second evaluation includes improvements in the scale and realism of the test suite with real-world test programs up to 200+KLOC. This paper presents three main contributions. First, we show that the MINESTRONE framework remains a useful tool for evaluating real-world software for security vulnerabilities. Second, we enhance the existing tools to provide detection of previously omitted vulnerabilities. Finally, we provide an analysis of the test corpus and give lessons learned from the test and evaluation.
Optimal Placement of Virtual Inertia in Power Grids

A major transition in the operation of electric power grids is the replacement of synchronous machines by distributed generation connected via power electronic converters. The accompanying “loss of rotational inertia” and the fluctuations by renewable sources jeopardize the system stability, as testified by the ever-growing number of frequency incidents. As a remedy, numerous studies demonstrate how virtual inertia can be emulated through various devices, but few of them address the question of “where” to place this inertia. It is, however, strongly believed that the placement of virtual inertia hugely impacts system efficiency, as demonstrated by recent case studies. In this paper, we carry out a comprehensive analysis in an attempt to address the optimal inertia placement problem. We consider a linear network-reduced power system model along with an $\mathscr {H}_2$ performance metric accounting for the network coherency. The optimal inertia placement problem turns out to be non-convex, yet we provide a set of closed-form global optimality results for particular problem instances as well as a computational approach resulting in locally optimal solutions. Further, we also consider the robust inertia allocation problem, wherein the optimization is carried out accounting for the worst-case disturbance location. We illustrate our results with a three-region power grid case study and compare our locally optimal solution with different placement heuristics in terms of different performance metrics.
Governance and Performance of Tunisian Banks

Developing banking standards is an important process for a country’s financial and economic well being. Their importance incites governments to insure the stability and the good performance of their banking systems. Accordingly, several researchers pay a particular attention to banking governance. Specifically, shareholders-managers’ convergence of interests and the possible repercussions of these on the performance of banks can be avoided only by implementing a solid system of governance. The main purpose of this article is to determine the impact of governance on the performance of banks, through an empirical study of a sample of 10 Tunisian banks during the period 1997-2007. Our empirical investigation shows a positive association between external administrators and performance. It is worth noting that a high number of administrators results in a negative effect on performance. The results also reveal that managers lack control while the board of directors seems to exert a lot of power. This state of affairs results from the fact of associating the role of the manager with that of the board of directors. Finally, our results reveal a negative association between the presence of a group of dominant shareholders and performance, a phenomenon which might be explained in terms of private appropriation of benefits.
DISTRIBUTED VIDEO CODING BASED ON SELECTIVE DATA PRUNING AND HIGH-ORDER EDGE-DIRECTED INTERPOLATION

In the current distributed video coding (DVC), a low resolution video sequence is generated with spatial and/or temporal downsampling at the encoder. At the decoder side, interpolation is performed and the interpolated pixels are further refined by using a error-correcting code such as Turbo codes or LDPC. In our previous work, we proposed a spatial domain DVC which uses a line-based downsampling method called selective data pruning (SDP). SDP is used for reducing the spatial frame size at the encoder. The obtained frames are then encoded and transmitted. Received frames are decoded and interpolated back to their original size by the single frame-based interpolation called the high-order edge-directed interpolation. However, artifacts are visible in the interpolated images because the positions of pruned lines are fixed for all GOP frames and the pixel continuity between frames are not sufficiently taken into account. In this paper, we focused on the image quality improvement of interpolated frames by using the multiframe-based interpolation. Experiments are performed to evaluate the quality of interpolated images and the rate distortion performance.
Assessment of volumetric bone mineral density of the femoral neck in postmenopausal women with and without vertebral fractures using quantitative multi-slice CT

ObjectiveTo demonstrate the validity and reliability of volumetric quantitative computed tomography (vQCT) with multi-slice computed tomography (MSCT) and dual energy X-ray absorptiometry (DXA) for hip bone mineral density (BMD) measurements, and to compare the differences between the two techniques in discriminating postmenopausal women with osteoporosis-related vertebral fractures from those without.MethodsNinety subjects were enrolled and divided into three groups based on the BMD values of the lumbar spine and/or the femoral neck by DXA. Groups 1 and 2 consisted of postmenopausal women with BMD changes <−2SD, with and without radiographically confirmed vertebral fracture (n=11 and 33, respectively). Group 3 comprised normal controls with BMD changes ≥−1SD (n=46). Post-MSCT (GE, LightSpeed16) scan reconstructed images of the abdominal-pelvic region, 1.25 mm thick per slice, were processed by OsteoCAD software to calculate the following parameters: volumetric BMD values of trabecular bone (TRAB), cortical bone (CORT), and integral bone (INTGL) of the left femoral neck, femoral neck axis length (NAL), and minimum cross-section area (mCSA). DXA BMD measurements of the lumbar spine (AP-SPINE) and the left femoral neck (NECK) also were performed for each subject.ResultsThe values of all seven parameters were significantly lower in subjects of Groups 1 and 2 than in normal postmenopausal women (P<0.05, respectively). Comparing Groups 1 and 2, 3D-TRAB and 3D-INTGL were significantly lower in postmenopausal women with vertebral fracture(s) [(109.8±9.61) and (243.3±33.0) mg/cm3, respectively] than in those without [(148.9±7.47) and (285.4±17.8) mg/cm3, respectively] (P<0.05, respectively), but no significant differences were evident in AP-SPINE or NECK BMD.Conclusionthe femoral neck-derived volumetric BMD parameters using vQCT appeared better than the DXA-derived ones in discriminating osteoporotic postmenopausal women with vertebral fractures from those without. vQCT might be useful to evaluate the effect of osteoporotic vertebral fracture status on changes in bone mass in the femoral neck.