Miracle-dz/UniFAR-FTUs huggingface dataset:
Broadly Neutralizing Antibody PGT121 Allosterically Modulates CD4 Binding via Recognition of the HIV-1 gp120 V3 Base and Multiple Surrounding Glycans

New broad and potent neutralizing HIV-1 antibodies have recently been described that are largely dependent on the gp120 N332 glycan for Env recognition. Members of the PGT121 family of antibodies, isolated from an African donor, neutralize ∼70% of circulating isolates with a median IC50 less than 0.05 µg ml−1. Here, we show that three family members, PGT121, PGT122 and PGT123, have very similar crystal structures. A long 24-residue HCDR3 divides the antibody binding site into two functional surfaces, consisting of an open face, formed by the heavy chain CDRs, and an elongated face, formed by LCDR1, LCDR3 and the tip of the HCDR3. Alanine scanning mutagenesis of the antibody paratope reveals a crucial role in neutralization for residues on the elongated face, whereas the open face, which accommodates a complex biantennary glycan in the PGT121 structure, appears to play a more secondary role. Negative-stain EM reconstructions of an engineered recombinant Env gp140 trimer (SOSIP.664) reveal that PGT122 interacts with the gp120 outer domain at a more vertical angle with respect to the top surface of the spike than the previously characterized antibody PGT128, which is also dependent on the N332 glycan. We then used ITC and FACS to demonstrate that the PGT121 antibodies inhibit CD4 binding to gp120 despite the epitope being distal from the CD4 binding site. Together, these structural, functional and biophysical results suggest that the PGT121 antibodies may interfere with Env receptor engagement by an allosteric mechanism in which key structural elements, such as the V3 base, the N332 oligomannose glycan and surrounding glycans, including a putative V1/V2 complex biantennary glycan, are conformationally constrained.
Word valence and its effects

words tend, on the whole, to have more affective associations than concrete words, and the greater the affective associations, the earlier those abstract words are acquired (especially for positive words, Kousta et al. 2009). Thus, affect may play a critical role in allowing the learning, or bootstrapping of abstract knowledge. Of course it is the case that not all abstract words are affectively loaded. Affect, nonetheless, could have an important role in allowing for knowledge that cannot be grounded to the external world to begin developing. Once the system is set in place, other abstract concepts can be learned based on linguistic information only. (Meteyard et al. 2012: 800) We will pay a little bit more attention to phylogeny, taking as a point of departure the discussion in Jablonka et al. (2012). For hominids, the whole body, including positioning in relation to others (proxemics), was available for communication. The signals were strongly emotive and at the same time strongly context-bound (iconic and deictic). Jablonka et al. point out that early humans distinguished themselves from the other hominids through strong inner group interaction, in which cooperation was important (see Tomasello and Vaish 2013: 237f), for example in the form of alloparenting (taking care of each other’s offspring). This required control of emotions, in particular the suppression of aggression. In other words, self-domestication was a useful evolutionary step. This context was favorable for the development of communicative tools which were free from too much emotional involvement. Every small venture in that direction was awarded by evolutionary forces, first as a social practice, then co-evolutionary incorporated in the genes, because individuals who were good at this type of signals (“symbols”) had an advantage. An important part of self-domestication has to do with the control of emotions. With the help of a non-emotional communicative instrument, communication can take place in a more neutral, objective way than with body language; see Jablonka et al. (2012: 2157):
State estimation with nonlinear inequality constraints based on unscented transformation

The state of some practical dynamic systems satisfies constraints, which can be utilized to improve the performance of state estimation. State estimation with nonlinear inequality constraints is a challenging problem. Projection methods are widely used to solve this problem. In this paper, a projection method is formulated as a special nonlinear function. Based on this formulation, unconstrained estimated states can be easily projected into the feasible constraint region through unscented transformation (UT), and both the constrained mean and co-variance can be obtained. An approach is proposed to reduce the complexity of this projection process and a closed-form solution is derived for one-dimensional constraints. To solve the problem that the constrained covariance may be ill-conditioned in UT-based approaches, a modification of the covariance is also proposed to account for necessary uncertainties. Two illustrative scenarios for ground moving target tracking are simulated to demonstrate the effectiveness and the efficiency of the proposed approaches.
Triggering parental involvement for parents of different language backgrounds: the role of types of partnership activities and preschool characteristics

Home and educational institutions are children's most important external influences and a positive partnership between the two can positively affect children's cognitive and non-cognitive development. Quality of family–preschool partnership (FPP) can depend on preschool and family characteristics. For Germany, studies show that immigrant parents perceive a lack of positive FPP. The present study addresses the following research questions: (1) How do parents and teachers in Germany rate FPP? (2) Do ratings of FPP differ between parents who do or do not speak German at home? (3) Is there a relation between the structural quality of the centre and ratings of FPP for teachers and parents? Results reflect positive ratings of FPP (1). Mean comparisons confirmed differences between parent groups (2). Multilevel regression analyses indicate that percentage of children who do not speak German at home is positively associated with parents’ ratings of FPP, but negatively with teachers’ satisfaction about FPP (3).
Modeling transcription programs: inferring binding site activity and dose-response model optimization

The modeling of transcription regulation programs is a major focus of today's biology. The challenge is to utilize diverse high-throughput data (gene expression, promoter binding site localization assays, protein expression) in order to infer the mechanistic models of transcription control. We propose a new model which integrates transcription factor-gene affinities, protein abundance and gene expression levels. Transcription factor binding site activity is represented by a dose-affinity-response function, and regulation is assumed to be a combinatorial function of the activities of the binding sites in the gene's promoter sites.We develop algorithms that infer the model given complete data and give a fast polynomial time algorithm under reasonable assumptions. We also show how to assess initial values of missing data (notably protein abundance) using a novel framework for active motif detection, which may be of independent interest. We test the various components of the framework on gene expression data related to carbohydrate metabolism in yeast. The results demonstrate the high specificity and sensitivity of the approach and its advantages over extant motif activity detection methods. We are also able to predict new active motifs in the galactose pathway.A key feature of our method is the global approach to transcription factor activity and to the relation between this activity and promoter signals. We use dozens of genes, with many different promoter signals and expression levels in order to draw conclusions on the function of a single transcription factor. This provides us the robustness necessary in order to overcome the considerable level of noise in the data.
ffi cient and Optimal Selling Mechanisms with Private Information Acquisition Costs ∗

In auctions with private information acquisition costs, we completely characterize efficient and optimal two-stage selling mechanisms, with the first stage being the pre-screening or entry right allocation mechanism, and the second stage being the traditional private good provision mechanism. Both efficiency and optimality require the second stage mechanism to be ex post efficient. For the first stage of entry allocation, both efficient and optimal mechanisms admit the most efficient bidders (the bidders with the least information acquisition costs), while the optimal mechanism admits fewer entrants. The efficient entry right allocation rule maximizes the expected total surplus, while the optimal entry right allocation rule maximizes the expected “virtual” total surplus, which is the total surplus adjusted for the information rent. We show that both efficient and optimal entry right allocation rules can be truthfully implemented in dominant strategies. We also demonstrate that the optimal entry right allocation mechanism can be implemented through an all-pay auction.
Detecting Eating Using a Wrist Mounted Device During Normal Daily Activities

The prevalence of obesity is a growing, worldwide health concern. Self-monitoring of eating consumptio n is widely recognized as a necessity for weight loss. In this paper we describe a novel method for automated monitoring of eating. Our method uses a single sensor that is worn on the wrist, similar in form to a watch. Wrist orientation was captured at a rate of 60 Hz for an entire day while four subjects conducted their natural daily routine. In our first experiment, we manually segmented the wrist motion data according to task logs kept by the subjects, and developed an algorithm to classify the tasks, achieving an accuracy of 91%. In our second experiment, we automatically segmented the wrist motion data in order to detect eating sessions, achieving a detection accuracy of 82%. Our methods will enable new opportunities in the study of dietetics, weight loss and management, nutrition, and health monitoring.
A Cost-Based Approach to Performance Analysis of Distributed Object Stores

Monitoring the performance of programs running on massively parallel computers or distributed systems is an extremely difficult problem because of the volume of information generated and the complexity of interactions between components of the program. This problem is made even more difficult by the new parallel programming paradigm provided by “distributed object stores”. This paper discusses the problems of analysing the performance of programs that use distributed object stores. A conceptual analysis framework that addresses many of these problems is then presented. This framework models the object store as a collection of resources, each of which has a state that can vary during execution. Operations performed by the program are modelled as requests to these resources, the cost of which can depend on the resource’s state. The performance of the program can then be analysed in terms of the states and costs of the object store resources that it accesses, providing a means of detecting various forms of contention between client processes. This approach allows the programmer of a system that uses a distributed object store to analyse performance problems without needing a detailed understanding of the implementation of the
Genome-Wide Linkage Analysis of Global Gene Expression in Loin Muscle Tissue Identifies Candidate Genes in Pigs

Background Nearly 6,000 QTL have been reported for 588 different traits in pigs, more than in any other livestock species. However, this effort has translated into only a few confirmed causative variants. A powerful strategy for revealing candidate genes involves expression QTL (eQTL) mapping, where the mRNA abundance of a set of transcripts is used as the response variable for a QTL scan. Methodology/Principal Findings We utilized a whole genome expression microarray and an F2 pig resource population to conduct a global eQTL analysis in loin muscle tissue, and compared results to previously inferred phenotypic QTL (pQTL) from the same experimental cross. We found 62 unique eQTL (FDR <10%) and identified 3 gene networks enriched with genes subject to genetic control involved in lipid metabolism, DNA replication, and cell cycle regulation. We observed strong evidence of local regulation (40 out of 59 eQTL with known genomic position) and compared these eQTL to pQTL to help identify potential candidate genes. Among the interesting associations, we found aldo-keto reductase 7A2 (AKR7A2) and thioredoxin domain containing 12 (TXNDC12) eQTL that are part of a network associated with lipid metabolism and in turn overlap with pQTL regions for marbling, % intramuscular fat (% fat) and loin muscle area on Sus scrofa (SSC) chromosome 6. Additionally, we report 13 genomic regions with overlapping eQTL and pQTL involving 14 local eQTL. Conclusions/Significance Results of this analysis provide novel candidate genes for important complex pig phenotypes.
Divergent transcriptional regulation among expanding human immunodeficiency virus type 1 subtypes

The current AIDS pandemic represents the uneven spread of multiple genetically related subtypes (A to J) of human immunodeficiency virus type 1 (HIV-1). Notably, HIV-1 E in southeast Asia and HIV-1 C in sub-Saharan Africa are expanding faster and are likely of greater global significance than the HIV-1 B subtype prevalent in the United States and Europe. While many studies have focused on genetic variation among structural genes, we chose to conduct a comparative analysis of the long terminal repeats of HIV-1 E and HIV-1 C isolates and report subtype-specific differences in enhancer copy numbers and sequences, as well as divergent activation in response to the cellular transcriptional activators Rel-p65 and NFATc and viral Tat. This study is the first to identify functional distinctions in promoter architecture between HIV-1 subtypes and raises the possibility that regulatory divergence among the subtypes of HIV-1 has occurred. Divergent transcriptional regulation may explain some of the epidemiologically observed differences in transmission and pathogenesis and underscores the need for further comparative analysis of HIV-1 regulation.
A game-theoretical model for wireless information and power transfer in relay interference channels

In this paper, we consider simultaneous wireless information and power transfer (SWIPT) in relay interference channels, where multiple source-destination pairs communicate through their dedicated energy harvesting relays. Game theory is applied to design a distributed power splitting scheme for the considered system. Particularly, a non-cooperative game is formulated, in which each link is modeled as a strategic player who aims to maximize its own achievable rate. The existence and uniqueness of the Nash equilibrium (NE) for the formulated game is analyzed. A distributed algorithm is proposed based on the best response functions to achieve the NE. Numerical results show that the proposed game-theoretical approach can achieve a near-optimal network-wide performance.
Processing Motion Capture Data to Achieve Positional Accuracy

Abstract In animating an articulated entity with motion capture data, if the reconstruction is based on forward kinematics, there could be a large error in the end-effector position. The inaccuracy becomes conspicuous when the entity makes interactions with the environment or other entities. The frames at which the end-effector position needs to be accurate are designated as “keyframes” (e.g., the impact moment in a punch). We present an algorithm that processes the original joint angle data to produce a new motion in which the end-effector error is reduced to zero at keyframes. The new motion should not be too much different from the original motion. We formulated the problem as a constrained minimization problem so that the characteristics of the original joint angle data is optimally preserved during the enhancement steps. The algorithm was applied to several examples such as boxing, kicking, and catching motions. Experiments prove that our algorithm is a valuable tool to improve captured motion especially when the end-effector trajectory contains a special goal.
Tim-3+ T-bet+ Tumor-Specific Th1 Cells Colocalize with and Inhibit Development and Growth of Murine Neoplasms1

Although T cells infiltrate many types of murine and human neoplasms, in many instances tumor-specific cytotoxicity is not observed. Strategies to stimulate CTL-mediated antitumor immunity have included in vitro stimulation and/or genetic engineering of T cells, followed by adoptive transfer into tumor-bearing hosts. In this model of B cell lymphoma in SJL/J mice, we used Tim-3+ T-bet+ Th1 cells to facilitate the development of tumor-specific CTL. Tumor-specific Th1 cell lines were polarized with IL-12 during in vitro stimulation and long term maintenance. As few as 5 million Tim-3+ T-bet+ Th1 cells enabled recipients to resist growth of malignant transplantable cells. In addition, similar numbers of Th1 cells injected into 2- to 3-mo-old mice inhibited development of the spontaneous primary lymphomas, which normally arise in 90% of aging mice. CFSE+ Th1 cells colocalized with injected tumor cells in vivo and formed conjugates with the tumor cells within follicles, whereas in nontumor-challenged recipients the CFSE+ Th1 cells localized only within the T cell zones of the spleen. These results provide evidence that adoptive immunotherapy with Tim-3+ T-bet+ tumor-specific Th1 cells can be used to induce host cytotoxic responses that inhibit the development and growth of neoplastic cells.
Automatic Lane Detection in Image Sequences for Vision-based Navigation Purposes

Intelligent Vehicles, as a main part of Intelligent Transportation Systems (ITS), will have great impact on transportation in near future. They would be able to understand their immediate environment and also communicate with other traffic participants such as other vehicles, infrastructures and traffic management centres. Intelligent vehicles could navigate autonomously in highway and urban scenarios using maps, GPS, video sensors and so on. To navigate autonomously or follow a road, intelligent vehicles need to detect lanes. It seems that the best cue for lane detection is to use the lane markings painted on roads and it should be noticed that among passive and active sensors, the video sensors are the best candidate for finding lane markings. In this paper we present a method for lane detection in image sequences of a camera mounted behind the windshield of a vehicle. The main idea is to find the features of the lane in consecutive frames which match a particular geometric model. The geometric model is a parabola, an approximation of a circular curve. By mapping this model in image space and calculation of gradient image using Sobel operator, the parameters of the lane can be calculated using a randomized Hough transform and a genetic algorithm. The proposed method is tested on different road images taken by a video camera from Ghazvin-Rasht road in Iran. Experimental results on different road scenes indicate the good performance of the proposed method.
Semantic labeling for improved vehicle detection in aerial imagery

Growing cities and increasing traffic densities result in an increased demand for applications such as traffic monitoring, traffic analysis, and support of rescue work. These applications share the need for accurate detection of relevant vehicles, e.g. in aerial imagery. Recently, the application of deep learning based detection frameworks like Faster R-CNN clearly outperformed conventional detection methods for vehicle detection in aerial images. In this paper, we propose a detection framework that fuses Faster R-CNN and semantic labeling to integrate contextual information. We achieve an improved detection performance by decreasing the number of false positive detections while the number of candidate regions to classify is reduced. To demonstrate the generalization of our approach, we evaluate our detection framework for various ground sampling distances on a publicly available dataset.
Complete Partite subgraphs in dense hypergraphs

For a given r ‐uniform hypergraph ${\cal F}$ we study the largest blow‐up of ${\cal F}$ which can be guaranteed in every large r ‐uniform hypergraph with many copies of ${\cal F}$. For graphs this problem was addressed by Nikiforov, who proved that every n ‐vertex graph that contains Ω(nℓ) copies of the complete graph Kℓ must contain a complete ℓ ‐partite graph with Ω(log n) vertices in each class. We give another proof of Nikiforov's result, make very small progress towards that problem for hypergraphs, and consider a Ramsey‐type problem related to a conjecture of Erdős and Hajnal. © 2012 Wiley Periodicals, Inc. Random Struct. Alg. , 2012
Muscle synergies evoked by microstimulation are preferentially encoded during behavior

Electrical microstimulation studies provide some of the most direct evidence for the neural representation of muscle synergies. These synergies, i.e., coordinated activations of groups of muscles, have been proposed as building blocks for the construction of motor behaviors by the nervous system. Intraspinal or intracortical microstimulation (ICMS) has been shown to evoke muscle patterns that can be resolved into a small set of synergies similar to those seen in natural behavior. However, questions remain about the validity of microstimulation as a probe of neural function, particularly given the relatively long trains of supratheshold stimuli used in these studies. Here, we examined whether muscle synergies evoked during ICMS in two rhesus macaques were similarly encoded by nearby motor cortical units during a purely voluntary behavior involving object reach, grasp, and carry movements. At each microstimulation site we identified the synergy most strongly evoked among those extracted from muscle patterns evoked over all microstimulation sites. For each cortical unit recorded at the same microstimulation site, we then identified the synergy most strongly encoded among those extracted from muscle patterns recorded during the voluntary behavior. We found that the synergy most strongly evoked at an ICMS site matched the synergy most strongly encoded by proximal units more often than expected by chance. These results suggest a common neural substrate for microstimulation-evoked motor responses and for the generation of muscle patterns during natural behaviors.
treatment failure in pneumonia Penicillin-resistant pneumococcus and risk of

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Distributed Software Development: Toward an Understanding of the Relationship Between Project Team, Users and Customers

The objective of this paper is to propose a typology for distributed software development comprising the relation between the three main stakeholders: project team (developers, analysts, managers, testers, system administrator, etc), customers and users. We propose a set of criteria to define geographically distributed environments. As a result, a model to define the distribution level for an organization in a Distributed Software Development (DSD) environment is presented. The model is applied to two exploratory case studies and its results discussed. These cases studies involve companies with headquarters in the United States and a development unit in Brazil. Advantages of this model as well as some aspects of the increasing distribution of software development particularly in a few Brazilian organizations are discussed.