Miracle-dz/UniFAR-FTUs huggingface dataset:
Pseudo Descriptions for Meta-Data Retrieval

Search in meta-data is challenging due to the sparsity of the available textual information. To alleviate the sparsity problem, the paper in hand evolves from the existing document expansion paradigm and proposes pseudo-descriptions as a new paradigm. Instead of encoding paradigmatic term relations implicitly in an expansion vector, we generate an explicit cohesive text field for meta-data records that describes the entity associated with the record. In contrast to document expansions, pseudo-descriptions allow to reveal why a certain document is considered relevant although the original meta-data does not contain the query terms. Moreover, they are easier to operationalize and facilitate the use of sophisticated retrieval features such as phrase search and query term proximity. To generate pseudo-descriptions, we propose a relevance dependent strategy that depends on the search engine result pages obtained from issuing the meta-data as a search query to a designated reference search engine. To demonstrate the validity of the pseudo-description paradigm, we experiment with different TREC collections where we withhold the content information to simulate a meta-data retrieval scenario. Though retrieval with full content information remains superior, our approach achieves retrieval performance improvements en par with document expansion.
Universal method for robust detection of circadian state from gene expression

Significance Determining the state of an individual’s internal physiological clock has important implications for precision medicine, from diagnosing neurological disorders to optimizing drug delivery. To be useful, such a test must be accurate, minimally burdensome to the patient, and robust to differences in patient protocols, sample collection, and assay technologies. TimeSignature is a machine-learning approach to predict physiological time based on gene expression in human blood. A powerful feature is TimeSignature’s generalizability, enabling it to be applied to samples from disparate studies and yield highly accurate results despite systematic differences between the studies. This quality is unique among expression-based predictors and addresses a major challenge in the development of reliable and clinically useful biomarker tests. Circadian clocks play a key role in regulating a vast array of biological processes, with significant implications for human health. Accurate assessment of physiological time using transcriptional biomarkers found in human blood can significantly improve diagnosis of circadian disorders and optimize the delivery time of therapeutic treatments. To be useful, such a test must be accurate, minimally burdensome to the patient, and readily generalizable to new data. A major obstacle in development of gene expression biomarker tests is the diversity of measurement platforms and the inherent variability of the data, often resulting in predictors that perform well in the original datasets but cannot be universally applied to new samples collected in other settings. Here, we introduce TimeSignature, an algorithm that robustly infers circadian time from gene expression. We demonstrate its application in data from three independent studies using distinct microarrays and further validate it against a new set of samples profiled by RNA-sequencing. Our results show that TimeSignature is more accurate and efficient than competing methods, estimating circadian time to within 2 h for the majority of samples. Importantly, we demonstrate that once trained on data from a single study, the resulting predictor can be universally applied to yield highly accurate results in new data from other studies independent of differences in study population, patient protocol, or assay platform without renormalizing the data or retraining. This feature is unique among expression-based predictors and addresses a major challenge in the development of generalizable, clinically useful tests.
Cross-cultural invariances in the architecture of shame

Significance This set of experiments shows that in 15 traditional small-scale societies there is an extraordinarily close correspondence between (i) the intensity of shame felt if one exhibited specific acts or traits and (ii) the magnitude of devaluation expressed in response to those acts or traits by local audiences, and even foreign audiences. Three important and widely acknowledged sources of cultural variation between communities—geographic proximity, linguistic similarity, and religious similarity—all failed to account for the strength of between-community correlations in the shame–devaluation link. This supplies a parallel line of evidence that shame is a universal system, part of our species’ cooperative biology, rather than a product of cultural evolution. Human foragers are obligately group-living, and their high dependence on mutual aid is believed to have characterized our species’ social evolution. It was therefore a central adaptive problem for our ancestors to avoid damaging the willingness of other group members to render them assistance. Cognitively, this requires a predictive map of the degree to which others would devalue the individual based on each of various possible acts. With such a map, an individual can avoid socially costly behaviors by anticipating how much audience devaluation a potential action (e.g., stealing) would cause and weigh this against the action’s direct payoff (e.g., acquiring). The shame system manifests all of the functional properties required to solve this adaptive problem, with the aversive intensity of shame encoding the social cost. Previous data from three Western(ized) societies indicated that the shame evoked when the individual anticipates committing various acts closely tracks the magnitude of devaluation expressed by audiences in response to those acts. Here we report data supporting the broader claim that shame is a basic part of human biology. We conducted an experiment among 899 participants in 15 small-scale communities scattered around the world. Despite widely varying languages, cultures, and subsistence modes, shame in each community closely tracked the devaluation of local audiences (mean r = +0.84). The fact that the same pattern is encountered in such mutually remote communities suggests that shame’s match to audience devaluation is a design feature crafted by selection and not a product of cultural contact or convergent cultural evolution.
Immunotherapy for Cat Allergies: A Potential Strategy to Scratch Back

Cat allergies are a common and costly problem in the United States. Various drug and nondrug therapies exist to alleviate and control symptoms once allergic disease has developed. However, these therapies are often ineffective or do not address the underlying condition itself. Immunotherapy is an option for patients when symptoms are not adequately controlled by medications and/or avoidance measures, when adverse effects of medications are unacceptable, or when the patient wants to reduce their long-term use of medication. The purpose of this article is to describe the efficacy and safety of immunotherapy when used to prevent or treat cat allergies.
Physiology, activity and costs of parental care in birds

ABSTRACT Parental care is assumed to be costly in that it requires sustained, high-intensity activity sufficient to cause costs of reproduction (decreased survival and future fecundity of parents). Costs of reproduction are, in turn, thought to have a physiological basis where intense activity causes a decrease in parental condition. However, attempts to identify the physiological basis of costs of reproduction have produced mixed results. Here, I argue that in birds, the central idea that parental care represents sustained, high-intensity work might be incorrect. Specifically: (a) the duration of intense activity associated with chick-rearing might be quite limited; (b) flight, the most obvious sustained, high-intensity activity, might only represent a small component of an individual's overall activity budget; (c) some (high-quality) individuals might be able to tolerate costs of intense activity, either owing to their physiological state or because they have access to more resources, without perturbation of physiological homeostasis; and (d) individuals might utilise other mechanisms to modulate costs of activity, for example, mass loss, again avoiding more substantial physiological costs. Furthermore, I highlight the important fact that life-history theory predicts that reproductive trade-offs should only be expected under food stress. Most birds breed in spring and early summer precisely because of seasonal increases in food abundance, and so it is unclear how often parents are food stressed. Consequently, I argue that there are many reasons why costs of reproduction, and any physiological signature of these costs, might be quite rare, both temporally (in different years) and among individuals. Summary: Contrary to expectation, parental care might not involve sustained, high-intensity activity; that is, it might not be ‘hard work’ and, consequently, costs of reproduction and physiological signatures of costs might rarely be experienced.
An Approach to Designing Belief-Desire-Intention Based Virtual Agents for Travel Assistance

The aim of this research is to propose a Belief-Desire-Intention (BDI) architecture-based approach for a virtual agent design. The presented case of a chatbot assistant in a travel domain demonstrates the necessity of the BDI architecture modification. The approach is taken for multiple BDI agent instances with a shared external knowledge base. The architecture was presented using Views and Beyond approach. A decision view was added to the architecture description to show alternatives and emphasize required modifications of the BDI architecture in the presented case.
Non-Parametric Variational Inference with Graph Convolutional Networks for Gaussian Processes

Inference for GP models with non-Gaussian noises is computationally expensive when dealing with large datasets. Many recent inference methods approximate the posterior distribution with a simpler distribution defined on a small number of inducing points. The inference is accurate only when data points have strong correlation with these inducing points. In this paper, we consider the inference problem in a different direction: GP function values in the posterior are mostly correlated in short distance. We construct a variational distribution such that the inference for a data point considers only its neighborhood. With this construction, the variational lower bound is highly decomposible, hence we can run stochastic optimization with very small batches. We then train Graph Convolutional Networks as a reusable model to identify variational parameters for each data point. Model reuse greatly reduces the number of parameters and the number of iterations needed in optimization. The proposed method significantly speeds up the inference and often gets more accurate results than previous methods.
Mobile mathematical environments: current state and development prospects

The formation and development of the human person is most influenced by the environment in which it lives, studies, works. Therefore, the problem of the creation of such a high-tech information and communication educational and scientific environment, in which the student is on a daily basis during the whole period of study at univeristy, which should meet the needs of the information society, to the modern level, is an important and topical problem of both theoretical and practical nature, science, technology and world educational standards, and to promote the level of information and communication training and the formation of professional competencies. An example of such an information and communication educational and scientific environment for the teaching of mathematical subjects of university students is a web-oriented mathematical environment.
Off-line vs. On-line Evaluation of Recommender Systems in Small E-commerce

In this paper, we present our work towards comparing on-line and off-line evaluation metrics in the context of small e-commerce recommender systems. Recommending on small e-commerce enterprises is rather challenging due to the lower volume of interactions and low user loyalty, rarely extending beyond a single session. On the other hand, we usually have to deal with lower volumes of objects, which are easier to discover by users through various browsing/searching GUIs. The main goal of this paper is to determine applicability of off-line evaluation metrics in learning true usability of recommender systems (evaluated on-line in A/B testing). In total 800 variants of recommenders were evaluated off-line w.r. t. 18 metrics covering rating-based, ranking-based, novelty and diversity evaluation. The off-line results were afterwards compared with on-line evaluation of 12 selected recommender variants and based on the results, we tried to learn and utilize an off-line to on-line results prediction model. Off-line results shown a great variance in performance w.r. t. different metrics with the Pareto front covering 64% of the approaches. Furthermore, we observed that on-line results are considerably affected by the seniority of users. On-line metrics correlates positively with ranking-based metrics (AUC, MRR, nDCG) for novice users, while too high values of novelty had a negative impact on the on-line results for them.
Brillouin Dynamic Gratings—A Practical Form of Brillouin Enhanced Four Wave Mixing in Waveguides: The First Decade and Beyond

Brillouin-Enhanced Four-Wave-Mixing techniques, which couple four optical beams through Brillouin nonlinearity, have gained popularity in the 1980’s largely owing to their phase conjugation properties. Experiments were mainly conducted in liquid cells. The interest in Brillouin-Enhanced Four-Wave-Mixing has reawakened in the 2000’s, following the quest for dynamically reconfigurable gratings in optical fibers. Termed Brillouin Dynamic Grating this time around, it is, in fact, an acoustic wave, optically generated by stimulated Brillouin scattering process between two pump waves. The acoustic wave either carries the coherent information encoded by the pump beams, or in the case of sensing applications, its properties are determined by the environmental parameters. This information, in turn, is imparted to the third phase-matched optical probe wave through the elasto-optic effect. Over the last decade, this mechanism allowed for the realization of many all-optical signal processing functions and has proven instrumental in distributed sensing applications. This paper describes the basics, as well as the state of the art, of BDG-based applications in optical fibers. It also surveys the efforts being done to carry over these concepts to the photonic chip level.
Torchbearer: A Model Fitting Library for PyTorch

We introduce torchbearer, a model fitting library for pytorch aimed at researchers working on deep learning or differentiable programming. The torchbearer library provides a high level metric and callback API that can be used for a wide range of applications. We also include a series of built in callbacks that can be used for: model persistence, learning rate decay, logging, data visualization and more. The extensive documentation includes an example library for deep learning and dynamic programming problems and can be found at this http URL The code is licensed under the MIT License and available at https://github.com/ecs-vlc/torchbearer.
Scalable Metadata Management Techniques for Ultra-Large Distributed Storage Systems -- A Systematic Review

The provisioning of an efficient ultra-large scalable distributed storage system for expanding cloud applications has been a challenging job for researchers in academia and industry. In such an ultra-large-scale storage system, data are distributed on multiple storage nodes for performance, scalability, and availability. The access to this distributed data is through its metadata, maintained by multiple metadata servers. The metadata carries information about the physical address of data and access privileges. The efficiency of a storage system highly depends on effective metadata management. This research presents an extensive systematic literature analysis of metadata management techniques in storage systems. This research work will help researchers to find the significance of metadata management and important parameters of metadata management techniques for storage systems. Methodical examination of metadata management techniques developed by various industry and research groups is described. The different metadata distribution techniques lead to various taxonomies. Furthermore, the article investigates techniques based on distribution structures and key parameters of metadata management. It also presents strengths and weaknesses of individual existing techniques that will help researchers to select the most appropriate technique for specific applications. Finally, it discusses existing challenges and significant research directions in metadata management for researchers.
To save or degrade: balancing proteasome homeostasis to maximize cell survival

ABSTRACT Autophagic degradation of proteasomes (termed proteaphagy) is a conserved mechanism by which cells eliminate excess or damaged particles. This clearance is induced rapidly when organisms are starved for nitrogen and, because proteasomes are highly abundant, their breakdown likely makes an important contribution to the amino acid pools necessary for survival. By contrast, our recent studies found that proteasomes are not degraded in response to carbon starvation, even though bulk macroautophagy is similarly activated. Instead, carbon starvation induces sequestration of proteasomes into membrane-less cytoplasmic condensates previously termed proteasome storage granules (PSGs), which protect proteasomes from autophagic degradation. Preserving proteasomes in PSGs enhances the ability of yeast cells to recover from a variety of stresses, implying that rapid remobilization of stored proteasomes when conditions improve is advantageous to cell fitness. Consequently, the choice of whether to save or degrade proteasomes can profoundly impact cell survival.
Use of Vasopressor Increases the Risk of Mortality in Traumatic Hemorrhagic Shock: A Nationwide Cohort Study in Japan

Objectives: To evaluate the possible association of vasopressor use with mortality in traumatic hemorrhagic shock patients. Design: Retrospective cohort study. Setting: Traumatic hemorrhagic shock patients at 260 emergency hospitals in Japan between 2004 and 2015. Patients: Three-thousand five-hundred fifty-one traumatic hemorrhagic shock patients who had systolic hypotension (< 90 mm Hg) on arrival at the emergency department and a blood transfusion received within the first 24 hours. Interventions: The use of vasopressor for traumatic hemorrhagic shock within the first 24 hours. Measurements and Main Results: Among 236,698 trauma patients, 3,551 were included in the study. Overall, 198 of 459 patients (43%) in the vasopressor+ group expired compared with 481 of 3,092 patients (16%) in the vasopressor– group. Use of vasopressor had an odds ratio of 2.172 (95% CI, 1.666–2.833) for in-hospital mortality adjusted for age, gender, year of onset, cause of injury, mechanism of injury, vital signs at the emergency department, Injury Severity Score, use of prehospital IV fluid, and volume of blood transfusion within the first 24 hours. In the propensity score-matched cohort and two subgroup analyses (massive transfusion and survivable injury models), use of vasopressor was associated with higher mortality (odds ratio, 2.168; 95% C, 1.442–3.320), (odds ratio, 2.029; 95% CI, 1.414–2.911; massive transfusion model), and (odds ratio, 1.959; 95% CI, 1.364–2.814; survivable injury model). Conclusions: Use of vasopressor for traumatic hemorrhagic shock was associated with mortality after controlling for biases (trauma severity; volume of fluid resuscitation).
Structure-specific DNA replication-fork recognition directs helicase and replication restart activities of the PriA helicase

Significance DNA replication complexes are often prematurely ejected from sites of DNA replication. Left unrepaired, this situation results in incomplete genome replication and cell death. All cells have therefore evolved “replication restart” mechanisms to reload the replicative machinery. This process is orchestrated by the PriA DNA helicase in bacteria. We describe the structural mechanism by which PriA recognizes and processes branched DNA replication forks. PriA binds to each arm of the replication fork and interaction with the parental DNA is shown to be particularly important for targeting PriA’s lagging strand-specific functions in vitro and in vivo. Our work provides mechanistic insights into how genome maintenance proteins recognize DNA replication forks and how they couple those interactions to strand-specific functions. DNA replication restart, the essential process that reinitiates prematurely terminated genome replication reactions, relies on exquisitely specific recognition of abandoned DNA replication-fork structures. The PriA DNA helicase mediates this process in bacteria through mechanisms that remain poorly defined. We report the crystal structure of a PriA/replication-fork complex, which resolves leading-strand duplex DNA bound to the protein. Interaction with PriA unpairs one end of the DNA and sequesters the 3′-most nucleotide from the nascent leading strand into a conserved protein pocket. Cross-linking studies reveal a surface on the winged-helix domain of PriA that binds to parental duplex DNA. Deleting the winged-helix domain alters PriA’s structure-specific DNA unwinding properties and impairs its activity in vivo. Our observations lead to a model in which coordinated parental-, leading-, and lagging-strand DNA binding provide PriA with the structural specificity needed to act on abandoned DNA replication forks.