Miracle-dz/UniFAR-FTUs huggingface dataset:
Stabilizing Inputs to Approximated Nonlinear Functions for Inference with Homomorphic Encryption in Deep Neural Networks

Leveled Homomorphic Encryption (LHE) offers a potential solution that could allow sectors with sensitive data to utilize the cloud and securely deploy their models for remote inference with Deep Neural Networks (DNN). However, this application faces several obstacles due to the limitations of LHE. One of the main problems is the incompatibility of commonly used nonlinear functions in DNN with the operations supported by LHE, i.e. addition and multiplication. As common in LHE approaches, we train a model with a nonlinear function, and replace it with a low-degree polynomial approximation at inference time on private data. While this typically leads to approximation errors and loss in prediction accuracy, we propose a method that reduces this loss to small values or eliminates it entirely, depending on simple hyper-parameters. This is achieved by the introduction of a novel and elegantly simple Min-Max normalization scheme, which scales inputs to nonlinear functions into ranges with low approximation error. While being intuitive in its concept and trivial to implement, we empirically show that it offers a stable and effective approximation solution to nonlinear functions in DNN. In return, this can enable deeper networks with LHE, and facilitate the development of security- and privacy-aware analytics applications.
Situational Grounding within Multimodal Simulations

In this paper, we argue that simulation platforms enable a novel type of embodied spatial reasoning, one facilitated by a formal model of object and event semantics that renders the continuous quantitative search space of an open-world, real-time environment tractable. We provide examples for how a semantically-informed AI system can exploit the precise, numerical information provided by a game engine to perform qualitative reasoning about objects and events, facilitate learning novel concepts from data, and communicate with a human to improve its models and demonstrate its understanding. We argue that simulation environments, and game engines in particular, bring together many different notions of "simulation" and many different technologies to provide a highly-effective platform for developing both AI systems and tools to experiment in both machine and human intelligence.
Parallel Contextual Bandits in Wireless Handover Optimization

As cellular networks become denser, a scalable and dynamic tuning of wireless base station parameters can only be achieved through automated optimization. Although the contextual bandit framework arises as a natural candidate for such a task, its extension to a parallel setting is not straightforward: one needs to carefully adapt existing methods to fully leverage the multi-agent structure of this problem. We propose two approaches: one derived from a deterministic UCB-like method and the other relying on Thompson sampling. Thanks to its Bayesian nature, the latter is intuited to better preserve the exploration-exploitation balance in the bandit batch. This is verified on toy experiments, where Thompson sampling shows robustness to the variability of the contexts. Finally, we apply both methods on a real base station network dataset and evidence that Thompson sampling outperforms both manual tuning and contextual UCB.
A Convergence Analysis of Nonlinearly Constrained ADMM in Deep Learning

Efficient training of deep neural networks (DNNs) is a challenge due to the associated highly nonconvex optimization. The alternating direction method of multipliers (ADMM) has attracted rising attention in deep learning for its potential of distributed computing. However, it remains an open problem to establish the convergence of ADMM in DNN training due to the nonlinear constraints involved. In this paper, we provide an answer to this problem by establishing the convergence of some nonlinearly constrained ADMM for DNNs with smooth activations. To be specific, we establish the global convergence to a Karush-Kuhn-Tucker (KKT) point at a ${\cal O}(1/k)$ rate. To achieve this goal, the key development lies in a new local linear approximation technique which enables us to overcome the hurdle of nonlinear constraints in ADMM for DNNs.
Fearless Concurrency? Understanding Concurrent Programming Safety in Real-World Rust Software

Rust is a popular programming language in building various low-level software in recent years. It aims to provide safe concurrency when implementing multi-threaded software through a suite of compiler checking rules. Unfortunately, there is limited understanding of how the checking rules influence the safety of concurrent programming in Rust applications. In this paper, we perform a preliminary study on Rust's concurrency safety from two aspects: concurrency usage and concurrency bugs. Our study can provide better understanding on Rust's concurrency and can guide future researchers and practitioners in writing better, more reliable Rust software and in developing debugging and bug detection tools for Rust.
Combinação de classificadores em diferentes espaços de características para classificação de documentos

Text Classification is a problem in which a natural language document is assigned to one of the pre-established classes. Text Classification, with feature vectors generated by Bagof-Words, has two notable difficulties: high dimensionality and sparse data matrix. Feature selection reduces these difficulties, but discards information in the process. An alternative is to perform transformations over the features, because by altering the features it is possible to work without discarding information, allowing improvement of recognition rates and, in some cases, reduction of dimensionality and sparseness. Among these transformations, two underused in literature are: Dissimilarity Representation (DR), where each document is represented by a vector composed of distances calculated relative to a set of reference documents; and Dichotomy Transformation (DT), where the original problem is transformed into a binary problem and each document is transformed into several vectors with features obtained by the absolute value of the difference for the documents of a subset of the original set. The use of DR can reduce both the high dimensionality and sparseness. Whereas the use of DT, despite not reducing dimensionality or sparseness, improves the recognition rates of the classifier, since it works with a larger amount of documents on a problem transformed into two classes. In this work, two multiple classifiers systems for Text Classification are proposed: Combined Dissimilarity Spaces (CoDiS) and Combined Dichotomy Transformations (CoDiT), each one based on the transformations mentioned above. The multiple classifiers benefits from the need to find a set for the transformations, because using different sets allows the creation of a diverse and robust system. Experiments were performed comparing the proposed architectures with literature methods using up to 47 public databases and the results show that the proposals achieve superior performance in most cases.
MENSAdb: a thorough structural analysis of membrane protein dimers

Abstract Membrane proteins (MPs) are key players in a variety of different cellular processes and constitute the target of around 60% of all Food and Drug Administration–approved drugs. Despite their importance, there is still a massive lack of relevant structural, biochemical and mechanistic information mainly due to their localization within the lipid bilayer. To help fulfil this gap, we developed the MEmbrane protein dimer Novel Structure Analyser database (MENSAdb). This interactive web application summarizes the evolutionary and physicochemical properties of dimeric MPs to expand the available knowledge on the fundamental principles underlying their formation. Currently, MENSAdb contains features of 167 unique MPs (63% homo- and 37% heterodimers) and brings insights into the conservation of residues, accessible solvent area descriptors, average B-factors, intermolecular contacts at 2.5 Å and 4.0 Å distance cut-offs, hydrophobic contacts, hydrogen bonds, salt bridges, π–π stacking, T-stacking and cation–π interactions. The regular update and organization of all these data into a unique platform will allow a broad community of researchers to collect and analyse a large number of features efficiently, thus facilitating their use in the development of prediction models associated with MPs. Database URL: http://www.moreiralab. com/resources/mensadb.
Explanation in Human-AI Systems: A Literature Meta-Review, Synopsis of Key Ideas and Publications, and Bibliography for Explainable AI

This is an integrative review that address the question, "What makes for a good explanation? " with reference to AI systems. Pertinent literatures are vast. Thus, this review is necessarily selective. That said, most of the key concepts and issues are expressed in this Report. The Report encapsulates the history of computer science efforts to create systems that explain and instruct (intelligent tutoring systems and expert systems). The Report expresses the explainability issues and challenges in modern AI, and presents capsule views of the leading psychological theories of explanation. Certain articles stand out by virtue of their particular relevance to XAI, and their methods, results, and key points are highlighted. It is recommended that AI/XAI researchers be encouraged to include in their research reports fuller details on their empirical or experimental methods, in the fashion of experimental psychology research reports: details on Participants, Instructions, Procedures, Tasks, Dependent Variables (operational definitions of the measures and metrics), Independent Variables (conditions), and Control Conditions.
Prevalence, Awareness, and Control of Hypertension in Greater Beirut Area, Lebanon

Background Hypertension (HTN) has been identified as the leading risk factor for mortality and the third cause of disability worldwide. Lebanon has witnessed a threefold increase in the prevalence of HTN in the past decade. The timely exploration and detection of the factors contributing to a higher prevalence of the disease among the Lebanese population is fundamental. The objectives of this study were to assess the prevalence, awareness, and control rates of HTN in Greater Beirut Area in Lebanon and to identify their respective predictors. Methods A representative sample of 501 participants aged 18-79 years residing in Greater Beirut Area was examined. Data collection form was filled up, through interviews, physical exams, and lab tests. The analysis was done for three defined outcomes: blood pressure status (normotensive, prehypertension, and hypertension), unaware HTN, and uncontrolled HTN. These were compared for the various associated predictors. Results The sample consisted of 64.3% women and mean age 45.4 ± 15 years and the subjects were predominantly from low educational income levels. The results showed that 36.4% of the study participants were hypertensive, 25.3% were prehypertensive, and 38.2% had optimal blood pressure, while the awareness rate was 65.4% and control rate was 61%. The independent predictors of HTN were age, gender, marital status, T2D, body fat, triglyceride (positive correlates), and income level (negative correlate). Moreover, unawareness of HTN was common among older age, men, single participants, and the obese. We could not identify any factor related to uncontrolled HTN. Conclusion The trend in the prevalence of HTN in Greater Beirut Area is found to be consistent and relatively high, yet there was an observed improvement in the awareness and control of the disease. Public health measures on a national level are urgently needed to curb the increasing prevalence of HTN, achieve primary prevention, and better control the disease.
Characterization and Regulation of Carrier Proteins of Mitochondrial Glutathione Uptake in Human Retinal Pigment Epithelium Cells

Purpose To characterize two mitochondrial membrane transporters 2-oxoglutarate (OGC) and dicarboxylate (DIC) in human RPE (hRPE) and to elucidate their role in the regulation of mitochondrial glutathione (mGSH) uptake and cell death in oxidative stress. Methods The localization of OGC and DIC proteins in confluent hRPE, polarized hRPE monolayers and mouse retina was assessed by immunoblotting and confocal microscopy. Time- and dose-dependent expression of the two carriers were determined after treatment of hRPE with H2O2, phenyl succinate (PS), and butyl malonate (BM), respectively, for 24 hours. The effect of inhibition of OGC and DIC on apoptosis (TUNEL), mGSH, and mtDNA was determined. Silencing of OGC by siRNA knockdown on RPE cell death was studied. Kinetics of caspase 3/7 activation with OGC and DIC inhibitors and effect of cotreatment with glutathione monoethyl ester (GSH-MEE) was determined using the IncuCyte live cell imaging. Results OGC and DIC are expressed in hRPE mitochondria and exhibited a time- and dose-dependent decrease with stress. Pharmacologic inhibition caused a decrease in OGC and DIC in mitochondria without changes in mtDNA and resulted in increased apoptosis and mGSH depletion. GSH-MEE prevented apoptosis through restoration of mGSH. OGC siRNA exacerbated apoptotic cell death in stressed RPE which was inhibited by increased mGSH from GSH-MEE cotreatment. Conclusions Characterization and mechanism of action of two carrier proteins of mGSH uptake in RPE are reported. Regulation of OGC and DIC will be of value in devising therapeutic strategies for retinal disorders such as AMD.
A single-center experience of post-transplant lymphomas involving the central nervous system with a review of current literature

Background Central Nervous System (CNS) lymphoma is a rare presentation of post-transplantation lymphoproliferative disorder (PTLD). Methods This single center retrospective study reviewed presentations, management and outcomes of CNS lymphomas in kidney transplant patients transplanted 1968 to 2015, and reviews relevant current literature. Results We identified 5773 adult kidney transplant recipients of who 90 had a PTLD diagnosis confirmed. CNS disease was diagnosed in 6/90 (7%). Median age at presentation was 60 years and time from transplant 4.5 years. Immunosuppression at diagnosis included mycophenolate mofetil and prednisolone without calcineurin inhibitor in 5/6 patients. Histological analysis diagnosed monomorphic disease in 5/6, and one polymorphic case with tissue positive for Epstein-barr virus (EBV) in 5/6 cases. Despite this 2/4 EBV positive cases had no detectable EBV in peripheral blood or CSF at diagnosis. Treatment strategies included reduction in immunosuppression in all, chemotherapy (n=5), radiotherapy (n=3), Cytotoxic T-Lymphocytes and Craniotomy (n=2). Patient survival was 40% at 1 year with CTL treated patients surviving beyond three years from diagnosis. Conclusion This study supports observational data suggesting MMF treated patients without CNI may have increased risk of disease. Peripheral blood screening for EBV DNAemia does not seem helpful in early identification of those at risk.
Knowledge and Awareness of Human Papillomavirus Among College Students in South Carolina

Despite the existence of a safe and effective vaccine, human papillomavirus (HPV) remains prevalent in the United States, with late adolescence and early adulthood being periods of increased risk. Thus, targeting college-aged individuals for HPV prevention and vaccination promotion is critical—particularly in regions such as the Deep South where vaccination rates remain low. This study sought to examine awareness and knowledge of HPV as well as experiences and attitudes regarding HPV vaccination among college students in the Deep South. Specifically, we completed a cross-sectional survey of 256 undergraduate students from a large public university in South Carolina. Although a majority of participants were aware of HPV, significant knowledge gaps existed, particularly regarding prevention, symptoms, and consequences of HPV infection. Participants were also largely unaware of men’s susceptibility for negative HPV outcomes. Multivariate regression modeling was used to identify predictors of HPV knowledge, with results indicating that participants who were female and white, as well as those who were vaccinated, had higher levels of HPV knowledge. Findings highlight the need for comprehensive HPV education on college campuses and offer insights to priority populations that may be appropriate focuses of efforts to increase HPV knowledge and vaccination rates.
An Analysis of Sports Specialization in NCAA Division I Collegiate Athletics

Background: Youth sports specialization has become more prevalent despite consequences such as increased injury rates and burnout. Young athletes, coaches, and parents continue to have misconceptions about the necessity of sports specialization, giving athletes the encouragement to focus on a single sport at a younger age. Purpose: To characterize the motivations for specialization and determine when elite athletes in various individual and team sports made the decision to specialize. Study Design: Cross-sectional study; Level of evidence, 3. Methods: A Likert-style survey was developed and distributed to athletes from two National Collegiate Athletic Association (NCAA) Division I institutions. The survey’s Flesch-Kincaid grade level was 6.3. Statistical analysis was performed via the Student t test, where a P value less than . 05 was considered significant. Results: A total of 303 athletes with a mean ± SD age of 19.9 ± 1.52 years across 19 sports were surveyed; 94.7% of specialized athletes had previously played another organized sport prior to college, and 45% of athletes had played multiple sports up to age 16 years. The mean age of specialization was 14.9 years, with a significant difference between athletes competing in team (15.5 years) and individual (14.0 years) sports (P = .008). Males in individual sports specialized earlier than those in team sports (P ≤ .001). Nearly one-fifth (17.4%) of athletes reported specializing at age 12 years or earlier. Personal interest, skill level, time constraints, and potential scholarships were the most important reasons for specialization overall. For individual sports, the motivations for specialization were similar, but collegiate (P < .001) or professional (P < .001) ambitions were significantly larger contributing factors. Conclusion: Early sports specialization is uncommon among NCAA Division I athletes for most team sports, whereas individual sports tend to have athletes who specialize earlier and are more motivated by professional and collegiate goals. This study characterized the timing of specialization among elite athletes, providing a basis for understanding the motivations behind youth sports specialization. Physicians should be prepared to discuss the misconception that early sports specialization is necessary or common among most team-focused collegiate-level athletes. Knowing the motivations for sports specialization will guide clinicians in their discussions with youth athletes.
Strengthening Care Delivery in Primary Care Facilities: Perspectives of Facility Managers on the Immunization Program in Kenya

Background: Primary healthcare facility managers (PHFMs) occupy a unique position in the primary healthcare system, as the only cadre combining frontline clinical activities with managerial responsibilities. Often serving as ‘street-level bureaucrats,’ their perspectives can provide contextually relevant information about interventions for strengthening primary healthcare delivery, yet such perspectives are under-represented in the literature on primary healthcare strengthening. Our objective in this study was to explore perspectives of PHFMs in western Kenya regarding how to leverage human resource factors to improve immunization programs, in order to draw lessons for strengthening of primary healthcare delivery. Methods: We employed a sequential mixed methods approach. We conducted in-depth interviews with key informants in Kakamega County. Emergent themes guided questionnaire development for a cross-sectional survey. We randomly selected 94 facility managers for the survey which included questions about workload, effects of workload on immunization program, and appropriate measures to address workload effects. Participants provided self-assessment of their general motivation at work, their specific motivation to ensure that all children in their catchment areas were fully immunized, and recommendations to improve motivation. Participants were asked about frequency of supervisory visits, supervisor activities during those visits, and how to improve supervision. Results: The most frequently reported consequences of high workload were reduced accuracy of vaccination records (47%) and poor client counseling (47%). Hiring more clinical staff was identified as an effective remedy to high workload (69%). Few respondents (20%) felt highly motivated to ensure full immunization coverage and only 13% reported being very motivated to execute their role as a health worker generally. Increasing frequency of supervisory visits and acting on the feedback received during those visits were mostly perceived as important measures to improve program effectiveness. Conclusion: Besides increasing the number of staff providing clinical care, PHFMs endorsed introducing some financial incentives contingent on specified targets and making supervisory visits meaningful with action on feedback as strategies to increase program effectiveness in primary healthcare facilities in Kenya. Targeting health worker motivation and promoting supportive supervision may reduce missed opportunities and poor client counseling in primary healthcare facilities in Kenya.
Phytophthora betacei, a new species within Phytophthora clade 1c causing late blight on Solanum betaceum in Colombia

Over the past few years, symptoms akin to late blight disease have been reported on a variety of crop plants in South America. Despite the economic importance of these crops, the causal agents of the diseases belonging to the genus Phytophthora have not been completely characterized. In this study, a new Phytophthora species was described in Colombia from tree tomato (Solanum betaceum), a semi-domesticated fruit grown in northern South America. Comprehensive phylogenetic, morphological, population genetic analyses, and infection assays to characterize this new species, were conducted. All data support the description of the new species, Phytophthora betacei sp. nov. Phylogenetic analyses suggest that this new species belongs to clade 1c of the genus Phytophthora and is a close relative of the potato late blight pathogen, P. infestans. Furthermore, it appeared as the sister group of the P. andina strains collected from wild Solanaceae (clonal lineage EC-2). Analyses of morphological and physiological characters as well as host specificity showed high support for the differentiation of these species. Based on these results, a complete description of the new species is provided and the species boundaries within Phytophthora clade 1c in northern South America are discussed.