Miracle-dz/UniFAR-FTUs huggingface dataset:
An ASP Approach for Reasoning on Neural Networks under a Finitely Many-Valued Semantics for Weighted Conditional Knowledge Bases

Abstract Weighted knowledge bases for description logics with typicality have been recently considered under a “concept-wise” multipreference semantics (in both the two-valued and fuzzy case), as the basis of a logical semantics of multilayer perceptrons (MLPs). In this paper we consider weighted conditional $\mathcal{ALC}$ knowledge bases with typicality in the finitely many-valued case, through three different semantic constructions. For the boolean fragment $\mathcal{LC}$ of $\mathcal{ALC}$ we exploit answer set programming and asprin for reasoning with the concept-wise multipreference entailment under a $\varphi$ -coherent semantics, suitable to characterize the stationary states of MLPs. As a proof of concept, we experiment the proposed approach for checking properties of trained MLPs.
CTMSTOU driven markets: simulated environment for regime-awareness in trading policies

Market regimes is a popular topic in quantitative finance even though there is little consensus on the details of how they should be defined. They arise as a feature both in financial market prediction problems and financial market task performing problems. In this work we use discrete event time multi-agent market simulation to freely experiment in a reproducible and understandable environment where regimes can be explicitly switched and enforced. We introduce a novel stochastic process to model the fundamental value perceived by market participants: Continuous-Time Markov Switching Trending Ornstein-Uhlenbeck (CTMSTOU), which facilitates the study of trading policies in regime switching markets. We define the notion of regime-awareness for a trading agent as well and illustrate its importance through the study of different order placement strategies in the context of order execution problems.
Distributional Reinforcement Learning via Sinkhorn Iterations

Distributional reinforcement learning (RL) is a class of state-of-the-art algorithms that estimate the entire distribution of the total return rather than only its expectation. The empirical success of distributional RL is determined by the representation of return distributions and the choice of distribution divergence. In this paper, we propose a new class of Sinkhorn distributional RL (SinkhornDRL) algorithm that learns a ﬁnite set of statistics, i.e., deterministic samples, from each return distribution and then uses Sinkhorn iterations to evaluate the Sinkhorn distance between the current and target Bellmen distributions. Sinkhorn divergence fea-tures as the interpolation between the Wasserstein distance and Maximum Mean Discrepancy (MMD). SinkhornDRL ﬁnds a sweet spot by taking advantage of the geometry of optimal transport-based distance and the unbiased gradient estimate property of MMD. Finally, compared to state-of-the-art algorithms, SinkhornDRL’s competitive performance is demonstrated on the suit of 55 Atari games. In this paper, a novel family of distributional RL algorithms based on Sinkhorn Divergence is proposed that accomplishes a competitive performance compared with the-state-of-the-art distributional RL algorithms on 55 Atari games. Theoretical analysis about the convergence and moment matching behavior is provided along with a rigorous empirical veriﬁcation. Albeit being associated with MMD algorithm, distributional RL with Sinkhorn divergence is complementary to previous algorithms, leading to an important contribution among the research community.
Survival regression with proper scoring rules and monotonic neural networks

We consider frequently used scoring rules for right-censored survival regression models such as time-dependent concordance, survival-CRPS, integrated Brier score and integrated binomial log-likelihood, and prove that neither of them is a proper scoring rule. This means that the true survival distribution may be scored worse than incorrect distributions, leading to inaccurate estimation. We prove that, in contrast to these scores, the right-censored log-likelihood is a proper scoring rule, i.e., the highest expected score is achieved by the true distribution. Despite this, modern feed-forward neural-network-based survival regression models are unable to train and validate directly on the right-censored log-likelihood, due to its intractability, and resort to the aforementioned alternatives, i.e., non-proper scoring rules. We therefore propose a simple novel survival regression method capable of directly optimizing log-likelihood using a monotonic restriction on the time-dependent weights, coined SurvivalMonotonic-net (SuMo-net). SuMo-net achieves state-of-the-art log-likelihood scores across several datasets with 20--100$\times$ computational speedup on inference over existing state-of-the-art neural methods, and is readily applicable to datasets with several million observations.
Bypass of Dfi1 Regulation of Candida albicans Invasive Filamentation by Iron Limitation

Candida albicans is an opportunistic pathogen responsible for a larger proportion of candidiasis and candidemia cases than any other Candida species (CDC). The ability of C. albicans cells to invade and cause disease is linked to their ability to filament. Despite this, there are gaps in our knowledge of the environmental cues and intracellular signaling that triggers the switch from commensal organism to filamentous pathogen. ABSTRACT Candida albicans filamentation, the ability to convert from oval yeast cells to elongated hyphal cells, is a key factor in its pathogenesis. Previous work has shown that the integral membrane protein Dfi1 is required for filamentation in cells grown in contact with a semisolid surface. Investigations into the downstream targets of the Dfi1 pathway revealed potential links to two transcription factors, Sef1 and Czf1. Sef1 regulates iron uptake and iron utilization genes under low-iron conditions, leading us to hypothesize that there exists a link between iron availability and contact-dependent invasive filamentation. In this study, we showed that Sef1 was not required for contact-dependent filamentation, but it was required for wild-type (WT) expression levels of a number of genes during growth under contact conditions. Czf1 is required for contact-dependent filamentation and for WT levels of expression of several genes. Constitutive expression and activation of either Sef1 or Czf1 individually in a dfi1 null strain resulted in a complete rescue of the dfi1 null filamentation defect. Because Sef1 is normally activated in low-iron environments, we embedded WT and dfi1 null cells in iron-free agar medium supplemented with various concentrations of ferrous ammonium sulfate (FAS). dfi1 null cells embedded in media with a low concentration of iron (20 μM FAS) showed increased filamentation in comparison to mutant cells embedded in higher concentrations of iron (50 to 500 μM). WT cells produced filamentous colonies in all concentrations. Together, the data indicate that Dfi1, Czf1, Sef1, and environmental iron regulate C. albicans contact-dependent filamentation. IMPORTANCE Candida albicans is an opportunistic pathogen responsible for a larger proportion of candidiasis and candidemia cases than any other Candida species. The ability of C. albicans cells to invade and cause disease is linked to their ability to filament. Despite this, there are gaps in our knowledge of the environmental cues and intracellular signaling that triggers the switch from commensal organism to filamentous pathogen. In this study, we identified a link between contact-dependent filamentation and iron availability. Over the course of tissue invasion, C. albicans cells encounter a number of different iron microenvironments, from the iron-rich gut to iron-poor tissues. Increased expression of Sef1-dependent iron uptake genes as a result of contact-dependent signaling will promote the adaptation of C. albicans cells to a low-iron-availability environment.
Epidemiology of interleukin-6: the 30-year follow-up of the 1982 Pelotas (Brazil) birth cohort study

Abstract Background Cardiovascular diseases are the main cause of death globally. Interleukin-6 (IL-6) is a biomarker of cardiovascular risk. Aim To investigate factors associated with IL-6 concentration in serum, from early life up to 30 years of age. Subjects and methods In the 2012–2013 follow-up, IL-6 was measured in 2809 participants of the 1982 Pelotas Birth Cohort (1369 males). Multivariable linear regressions, stratified by sex, were performed to evaluate the associations of African ancestry, family income and maternal education at birth, monthly income and education at 30 years, smoking status, harmful alcohol intake, physical activity, and body composition with IL-6, considering a conceptual hierarchical framework. Results Males with low educational levels and current smokers had the highest mean IL-6. Among females, African ancestry and low monthly income were associated with the highest mean values for the outcome. Physical activity had an inverse association with IL-6 concentration among females. A direct relationship was observed between the measures of adiposity on IL-6, in both sexes. Conclusion Body composition was the main predictor for the outcome evaluated in males and females. Thus, the avoidance of overweight remains an important strategy for the prevention and control of cardiovascular risk and biomarkers associated with these diseases.
P2P Traffic Detection Technology and Analysis

The development and application of P2P technology have increased the load of networks,and affected the performance of networks.Therefore,it is necessary to detect and control the P2P traffic.Based on the introduction of P2P traffic detection technology,several current P2P traffic identification technologies are compared and analyzed in the paper,the advantages and disadvantages of the various traffic detection technologies are pointed out,and the development direction of the detection technology is elaborated.An idea of combining different detection methods to meet the requirements of a certain accuracy and efficiency is proposed.
A Broad Survey of Gene Body and Repeat Methylation in Cnidaria Reveals a Complex Evolutionary History

Abstract DNA methylation, an important component of eukaryotic epigenetics, varies in pattern and function across Metazoa. Notably, bilaterian vertebrates and invertebrates differ dramatically in gene body methylation (GbM). Using the frequency of cytosine-phospho-guanines (CpGs), which are lost through mutation when methylated, we report the first broad survey of DNA methylation in Cnidaria, the ancient sister group to Bilateria. We find that: 1) GbM differentially relates to expression categories as it does in most bilaterian invertebrates, but distributions of GbM are less discretely bimodal. 2) Cnidarians generally have lower CpG frequencies on gene bodies than bilaterian invertebrates potentially suggesting a compensatory mechanism to replace CpG lost to mutation in Bilateria that is lacking in Cnidaria. 3) GbM patterns show some consistency within taxonomic groups such as the Scleractinian corals; however, GbM patterns variation across a range of taxonomic ranks in Cnidaria suggests active evolutionary change in GbM within Cnidaria. 4) Some but not all GbM variation is associated with life history change and genome expansion, whereas GbM loss is evident in endoparasitic cnidarians. 5) Cnidarian repetitive elements are less methylated than gene bodies, and methylation of both correlate with genome repeat content. 6) These observations reinforce claims that GbM evolved in stem Metazoa. Thus, this work supports overlap between DNA methylation processes in Cnidaria and Bilateria, provides a framework to compare methylation within and between Cnidaria and Bilateria, and demonstrates the previously unknown rapid evolution of cnidarian methylation.
Remote Assessment of Cardiovascular Risk Factors and Cognition in Middle-Aged and Older Adults: Proof-of-Concept Study

Background Adults with cardiovascular disease risk factors (CVRFs) are also at increased risk of developing cognitive decline and dementia. However, it is often difficult to study the relationships between CVRFs and cognitive function because cognitive assessment typically requires time-consuming in-person neuropsychological evaluations that may not be feasible for real-world situations. Objective We conducted a proof-of-concept study to determine if the association between CVRFs and cognitive function could be detected using web-based, self-administered cognitive tasks and CVRF assessment. Methods We recruited 239 participants aged ≥50 years (mean age 62.7 years, SD 8.8; 42.7% [n=102] female, 88.7% [n=212] White) who were enrolled in the Health eHeart Study, a web-based platform focused on cardiac disease. The participants self-reported CVRFs (hypertension, high cholesterol, diabetes, and atrial fibrillation) using web-based health surveys between August 2016 and July 2018. After an average of 3 years of follow-up, we remotely evaluated episodic memory, working memory, and executive function via the web-based Posit Science platform, BrainHQ. Raw data were normalized and averaged into 3 domain scores. We used linear regression models to examine the association between CVRFs and cognitive function. Results CVRF prevalence was 62.8% (n=150) for high cholesterol, 45.2% (n=108) for hypertension, 10.9% (n=26) for atrial fibrillation, and 7.5% (n=18) for diabetes. In multivariable models, atrial fibrillation was associated with worse working memory (β=-.51, 95% CI -0.91 to -0.11) and worse episodic memory (β=-.31, 95% CI -0.59 to -0.04); hypertension was associated with worse episodic memory (β=-.27, 95% CI -0.44 to -0.11). Diabetes and high cholesterol were not associated with cognitive performance. Conclusions Self-administered web-based tools can be used to detect both CVRFs and cognitive health. We observed that atrial fibrillation and hypertension were associated with worse cognitive function even in those in their 60s and 70s. The potential of mobile assessments to detect risk factors for cognitive aging merits further investigation.
An Innovative Approach In Nanotechnology-Based Delivery System For The Effective Management Of Psoriasis.

INTRODUCTION Psoriasis is an ineradicable, non-contagious inflammatory autoimmune skin disorder exhibiting abnormal redness of the skin and flaky patches which affect the exposed body surface. It is caused by negative signals produced by the immune system, leading to excessive growth and differentiation of keratinocytes and other inflammatory reactions on the skin. The topical route is primarily preferred in treating skin disorders due to the smaller size of the drug molecule, which allows them to cross the outer layer of the skin, i.e., stratum corneum, and permeate into the deep layer, unlike transdermal and other routes. The conventional topical treatments used in the past, such as coal tar, and dithranol leads to meager patient compliance due to decreased potency, and imperfect aesthetic. In contrast, systemic therapy such as methotrexate, cyclosporine, and acitretin produce related side effects. At present, various novel carriers like liposomes, ethosomes, niosomes, nanostructured lipid carriers, etc., have shown promising results to treat psoriasis. Therefore, this review primarily concentrates on the current advancements in novel carriers for various drugs to treat psoriasis topically. Area covered: The objective of this review describes the detailed study such as pathophysiology, epidemiology, types, causes, diagnosis, and topical treatment options for psoriasis, as well as the role of the nanotechnology-based delivery system to manage psoriasis.
Naltrexone at low doses (LDN) and its relevance to cancer therapy

ABSTRACT Introduction Naltrexone was designed to inhibit opioid receptors without activating them and hence used to block the stimulatory effects of morphine and heroin. It was noted that in certain patients being treated with naltrexone for an opioid addiction many reported significant secondary benefit when being weaned off naltrexone. This group of patients had chronic inflammatory and autoimmune conditions and reported improvements whilst using the lower dosages of naltrexone. There have also been recent anecdotal reports of cancer resolution following the use of low doses of naltrexone (LDN). However, the mechanism of action is unclear. Areas covered We review three mechanisms through which LDN can influence cancer progression; namely, (a) antagonism of receptors to which LDN binds, which include toll-like receptors 7–9 that lead to IL-6 suppression b) modulation of immune function in patients; and c) direct inhibition of signaling pathways involved in cancer cell control, including the priming of pro-apoptotic pathways. Expert opinion Considering the increase in the number of anecdotal reports of activity, there will likely be a bigger drive toward using LDN in the oncological setting. These reports support clinical trials of LDN in cancer, especially when given in combination with certain chemotherapy.
The scientific potential and technological challenges of the High-Luminosity Large Hadron Collider program

We present an overview of the High-Luminosity (HL-LHC) program at the Large Hadron Collider (LHC), its scientific potential and technological challenges for both the accelerator and detectors. The HL-LHC program is expected to start circa 2027 and aims to increase the integrated luminosity delivered by the LHC by an order of magnitude at the collision energy of 14 TeV. This requires upgrades to the injector system, accelerator complex and luminosity levelling. The two experiments, ATLAS and CMS, require substantial upgrades to most of their systems in order to cope with the increased interaction rate, and much higher radiation levels than at the current LHC. We present selected examples based on novel ideas and technologies for applications at a hadron collider. Both experiments will replace their tracking systems. We describe the ATLAS pixel detector upgrade featuring novel tilted modules, and the CMS Outer Tracker upgrade with a new module design enabling use of tracks in the level-1 trigger system. CMS will also install state-of-the-art highly segmented calorimeter endcaps. Finally, we describe new picosecond precision timing detectors of both experiments. In addition, we discuss how the upgrades will enhance the physics performance of the experiments, and solve the computing challenges posed by the expected large data sets. The physics program of the HL-LHC is focused on precision measurements probing the limits of the Standard Model (SM) of particle physics and discovering new physics. We present a selection of studies that have been carried out to motivate the HL-LHC program. A central topic of exploration will be the characterization of the Higgs boson. The large HL-LHC data samples will extend the sensitivity of searches for new particles or new interactions whose existence has been hypothesized in order to explain shortcomings of the SM. Finally, we comment on the nature of large scientific collaborations.
A Bayesian Multi-Outcome Analysis of Fine Particulate Matter and Cardiorespiratory Hospitalizations

Supplemental Digital Content is available in the text. Background: Short-term fine particulate matter (PM2.5) exposure is positively associated with acute cardiovascular and respiratory events. Understanding whether this association varies across specific cardiovascular and respiratory conditions has important biologic, clinical, and public health implications. Methods: We conducted a time-stratified case-crossover study of hospitalizations from 2000 through 2014 among United States Medicare beneficiaries aged 65+. The outcomes were hospitalizations with any of 57 cardiovascular and 32 respiratory discharge diagnoses. We estimated associations with two-day moving average PM2.5 as a piecewise linear term with a knot at PM2.5 = 25 g/m3. We used Multi-Outcome Regression with Tree-structured Shrinkage (MOReTreeS) to identify de novo groups of related diseases such that PM2.5 associations are: (1) similar within outcome groups; but (2) different between outcome groups. We adjusted for temperature, humidity, and individual-level characteristics. We introduce an R package, moretrees. Results: Our dataset included 16,007,293 cardiovascular and 8,690,837 respiratory hospitalizations. Of 57 cardiovascular diseases, 51 were grouped and positively associated with PM2.5. We observed a stronger positive association for heart failure, which formed a separate group. We observed negative associations for groups containing the outcomes other aneurysm and intracranial hemorrhage. Of 32 respiratory outcomes, 31 were grouped and were positively associated with PM2.5. Influenza formed a separate group with a negative association. Conclusions: We used a new statistical approach, MOReTreeS, to uncover variation in the association between short-term PM2.5 exposure and hospitalizations for cardiovascular and respiratory causes controlling for patient characteristics, time trends, and environmental confounders.
Low-power wireless remote terminal design based on GPRS/GSM

A low-power remote terminal unit (RTU) based on GPRS/GSM (general packet radio service/global system for mobile communication) hybrid communications was developed for data acquisition and transmission from distributed monitoring points in industrial environments. The RTU samples data at adjustable intervals and uploads the data to the remote monitoring centre. When the GPRS network is congested, the RTU switches to short message service (SMS) mode to resume data transmission with data guaranteed integrity. The RTU uses an MSP430 microprocessor, with its ultra-low power mode utilized during the idle cycle. Lab and field tests demonstrate that the RTU can reliably sample and transmit data. During a 48 h test, the GPRS loss rate was 6.94‰, with no losses with the hybrid communication system. The GPRS average transmission delay was 1.126~2.669 s. The power consumption during the working cycle was 200 mW and 0.2 mW during the low power mode.
Targeting the NANOG/HDAC1 axis reverses resistance to PD-1 blockade by reinvigorating the antitumor immunity cycle

Immune checkpoint blockade (ICB) therapy has shifted the paradigm for cancer treatment. However, the majority of patients lack effective responses because of the emergence of immune-refractory tumors that disrupt the amplification of antitumor immunity. Therefore, the identification of clinically available targets that restrict antitumor immunity is required to develop potential combination therapies. Here, using transcriptomic data on patients with cancer treated with programmed cell death protein 1 (PD-1) therapy and newly established mouse preclinical anti–PD-1 therapy–refractory models, we identified NANOG as a factor restricting the amplification of the antitumor immunity cycle, thereby contributing to the immune-refractory feature of the tumor microenvironment (TME). Mechanistically, NANOG induced insufficient T cell infiltration and resistance to CTL-mediated killing via the histone deacetylase 1–dependent (HDAC1-dependent) regulation of CXCL10 and MCL1, respectively. Importantly, HDAC1 inhibition using an actionable agent sensitized NANOGhi immune-refractory tumors to PD-1 blockade by reinvigorating the antitumor immunity cycle. Thus, our findings implicate the NANOG/HDAC1 axis as a central molecular target for controlling immune-refractory tumors and provide a rationale for combining HDAC inhibitors to reverse the refractoriness of tumors to ICB therapy.