Miracle-dz/UniFAR-FTUs huggingface dataset:
Loop homology of moment-angle complexes in the flag case

We develop a general homological approach to presentations of connected graded associative algebras, and apply it to loop homology of moment-angle complexes $Z_K$ that correspond to flag simplicial complexes $K$. For arbitrary coefficient ring, we describe generators of the Pontryagin algebra $H_*(\Omega Z_K)$ and defining relations between them. We prove that such moment-angle complexes are coformal over $\mathbb{Q},$ give a necessary condition for rational formality, and compute their homotopy groups in terms of homotopy groups of spheres.
Connecting Pressure‐Saturation and Relative Permeability Models to Fracture Properties: The Case of Capillary‐Dominated Flow of Supercritical CO2 and Brine

Fractures are potential pathways for subsurface fluids. In the context of geologic CO2 sequestration, fractures could threaten the security of reservoirs since they are pathways for leakage. However, the constitutive equations describing the pressure‐saturation and relative permeability‐saturation, key inputs for flow modeling and prediction, are poorly understood for two‐phase fracture flow at the field scale where each fracture might be an element of a complex fracture network or dual‐porosity domain. This knowledge is required for the safe storage of CO2 under potentially fractured caprocks. To address this, we numerically simulated two‐phase viscous flow through horizontal heterogeneous fractures across a broad range of roughness and aperture correlation length. The numerical experiments, which solved the modified local cubic law, showed a weak to strong phase interference during the drainage process; that is, supercritical CO2 displaces brine if the imposed pressure + local viscous force > local capillary force. The drainage process ended when no new brine cells can be further invaded by CO2. Afterward, we froze the saturation field for each individual phase and calculated the relative permeability by single‐phase flow modeling. Thousands of simulated pressure‐saturation and relative permeability curves enabled us to estimate and connect the parameters of the Van‐Genuchten model and of the generalized ν‐type model to fracture roughness and aperture correlation length. This empirical connection will be useful for assessing and predicting immiscible two‐phase flow in horizontal rough fractures at the large scale.
Endogenous Sphingolipid Signaling Pathway Implicated in the Action of Croton membranaceus on the Prostate Gland in BPH Patients

Background: Croton membranaceus extract has apoptotic effects on BPH-1 cells. This study determined if the apoptotic effects were created through the ceramide pathway. Methods: The study was a follow-up to a previous observational study of 30 histologically confirmed patients with benign prostatic hyperplasia (BPH) who were on C. membranaceus ethanolic extract at 20 mg t.i. d orally for 3 mo. Thereafter, total and free prostate-specific antigen (PSA), lipid profile plus Apo lipoprotein A and B, ceramide/Sphingophospho-kinase 1 (SphK1) and 2 (SphK2), sphingosine lyase (SPL), the cytotoxic adducts of oxidative stress 4-hydroxy-2-nonenal (4HNE) and malondialdehyde (MDA), were determined. Results: Total and free PSA were significantly (p < 0.05) different after treatment. Apo lipoprotein A was significantly different (p = 0.024). The SphK1/SphK2 ratio reduced significantly (p = 0.049). Furthermore, SPL, ceramide, and MDA increased significantly after treatment (p = 0.05, p = 0.004, and p = 0.007, respectively). A weak positive correlation was found between high-density lipoprotein (HDL) cholesterol and SphK1, and HDL and ceramide before treatment (p = 0.036, r = 0.3826; p = 0.018, r = 0.4286, respectively. Conclusions: C. membranaceus uses the ceramide pathway by modulating the SphK1/SphK2 ratio and increasing SPL to generate oxidative stress and consequently apoptosis.
Ieee Transactions on Information Theory Capacity and Delay Tradeoffs for Ad-hoc Mobile Networks

We consider the throughput/delay tradeoffs for scheduling data transmissions in a mobile ad-hoc network. To reduce delays in the network, each user sends redundant packets along multiple paths to the destination. Assuming the network has a cell partitioned structure and users move according to a simplified i.i. d. mobility model, we compute the exact network capacity and the exact end-to-end queueing delay when no redundancy is used. The capacity achieving algorithm is a modified version of the Grossglauser-Tse 2-hop relay algorithm and provides O(N) delay (where N is the number of users). We then show that redundancy cannot increase capacity, but can significantly improve delay. The following necessary tradeoff is established: delay/rate ≥ O(N). Two protocols that use redundancy and operate near the boundary of this curve are developed, with delays of O(√ N) and O(log(N)), respectively. Networks with non-i.i. d. mobility are also considered and shown through simulation to closely match the performance of i.i. d. systems in the O(√ N) delay regime.
Theory and practice for measuring health care quality

As competition, cost control, and new modes of delivery emerge in health care, there is a need to reexamine both the traditional definitions of health care quality and the methods by which it is measured. Industries other than health care have much to teach regarding the methods for obtaining, analyzing, and displaying data; techniques for problem identification, problem solving, and reassessment; and ideas about organizational factors that produce a high quality product or service. The Quality-of-Care Measurement Department at the Harvard Community Health Plan has built a program that draws from a distinguished health care quality assurance tradition and incorporates techniques that have been successful in other industries.
Dysfunctional inflammasome in Schnitzler's syndrome.

OBJECTIVE IL-1beta plays a key role in the pathogenesis of Schnitzler's syndrome (SS). We have investigated inflammasome activity in peripheral blood mononuclear cells (PBMCs) from a patient affected by a variant type of SS. METHODS PBMCs were purified by Ficoll and examined for ability to secrete IL-1beta and -18, expression and function of the P2X(7) receptor and expression of apoptosis-associated speck-like protein containing a caspase recruitment domaine (ASC) and NOD-like receptor protein 3 (NLRP3) before and after the therapy with steroid. Furthermore, extracellular adenosine 5'-triphosphate (ATP) blood levels were determined by luciferase assay. Expression of inflammasome components was measured by real time PCR and western blotting. RESULTS PBMCs of patient with SS showed a high, spontaneous and lipopolysaccharide-stimulated, IL-1beta release but low response to stimulation with the P2X(7) agonist benzoyl ATP. P2X(7) expression was several fold increased, whereas ASC expression was dramatically decreased compared with PBMCs from healthy controls. NLRP3 expression was unchanged. Prednisone treatment induced remission of clinical symptoms and normalized IL-1beta secretion and P2X(7) and ASC expression. CONCLUSION These findings reveal the presence of an overall derangement of the inflammasome and IL-1beta processing and release in SS.
Antibacterial Activity of Essential Oils from Palmarosa, Evening Primrose, Lavender and Tuberose

Essential oils extracted from flower petals of palmarosa (Cymbopogon martini), evening primrose (Primula rosea), lavender (Lavandula angustifolia) and tuberose (Polianthus tuberosa) were tested for their antibacterial activities against gram-positive and gram-negative bacteria. Different concentrations of each essential oil ranging from 10-100% were tested. Both gram-positive and gram-negative bacteria were found susceptible to the studied flower essential oils. With increase in concentration of essential oil, increase in zone of inhibition was observed thus dose-dependent response was clear for each essential oil. Essential oil extracted from Cymbopogon martini showed the highest activity against both gram positive and gram negative bacteria among the tested essential oils.
Sedation for routine gastrointestinal endoscopic procedures: a review on efficacy, safety, efficiency, cost and satisfaction

Most gastrointestinal endoscopic procedures are now performed with sedation. Moderate sedation using benzodiazepines and opioids continue to be widely used, but propofol sedation is becoming more popular because its unique pharmacokinetic properties make endoscopy almost painless, with a very predictable and rapid recovery process. There is controversy as to whether propofol should be administered only by anesthesia professionals (monitored anesthesia care) or whether properly trained non-anesthesia personnel can use propofol safely via the modalities of nurse-administered propofol sedation, computer-assisted propofol sedation or nurse-administered continuous propofol sedation. The deployment of non-anesthesia administered propofol sedation for low-risk procedures allows for optimal allocation of scarce anesthesia resources, which can be more appropriately used for more complex cases. This can address some of the current shortages in anesthesia provider supply, and can potentially reduce overall health care costs without sacrificing sedation quality. This review will discuss efficacy, safety, efficiency, cost and satisfaction issues with various modes of sedation for non-advanced, non-emergent endoscopic procedures, mainly esophagogastroduodenoscopy and colonoscopy.
The Neural Substrates of Biological Motion Perception: an fMRI Study

biological motion (4 T EPI; whole brain). In experiment 1, 10 subjects viewed biological motion (a human figure jumping up and down, composed of 21 dots), alternating with a control stimulus created by applying autoregressive models to the biological motion stimulus (such that the dots' speeds and amplitudes were preserved whereas their linking structure was not). The lengths of the stimulus bouts varied, and therefore the transitions between biological motion and control stimuli were unpredictable. Subjects had to indicate with a button press when each transition occurred. In a related biological motion task, subjects detected short (1 s) disturbances within these displays. We also examined the neural substrates of motion and shape perception, as well as motor imagery, to determine whether or not the cortical regions involved in these processes are also recruited during biological motion perception. Subjects viewed linear motion displays alternating with static dots and a series of common objects alternating with band-limited white noise patterns. Subjects also generated imagery of their own arm movements alternating with visual imagery of common objects. Biological motion specific BOLD signal was found within regions of the lingual gyrus at the cuneus border, showing little overlap with object recognition, linear motion or motion imagery areas. The lingual gyrus activation was replicated in a second experiment that also mapped retinotopic visual areas in three subjects. The results suggest that a region of the lingual gyrus within VP is involved in higher-order processing of motion information.
TransFusion: Contrastive Learning with Transformers

This paper proposes a novel framework, TransFusion, designed to make the process of contrastive learning more analytical and explainable. TransFusion consists of attention blocks whose softmax being replaced by ReLU, and its final block's weighted-sum operation is truncated to leave the adjacency matrix as the output. The model is trained by minimizing the Jensen-Shannon Divergence between its output and the target affinity matrix, which indicates whether each pair of samples belongs to the same or different classes. The main contribution of TransFusion lies in defining a theoretical limit for answering two fundamental questions in the field: the maximum level of data augmentation and the minimum batch size required for effective contrastive learning. Furthermore, experimental results indicate that TransFusion successfully extracts features that isolate clusters from complex real-world data, leading to improved classification accuracy in downstream tasks.
Inverse scattering on the line with incomplete scattering data

The Schroedinger equation is considered on the line when the potential is real valued, compactly supported, and square integrable. The nonuniqueness is analyzed in the recovery of such a potential from the data consisting of the ratio of a corresponding reflection coefficient to the transmission coefficient. It is shown that there are a discrete number of potentials corresponding to the data and that their L^2-norms are related to each other in a simple manner. All those potentials are identified, and it is shown how an additional estimate on the L^2-norm in the data can uniquely identify the corresponding potential. The recovery is illustrated with some explicit examples.
Journal Fü R Die Reine Und Angewandte Mathematik Prime Factors of Dynamical Sequences

Let fðtÞ A QðtÞ have degree d f 2. For a given rational number x 0 , define x nþ1 ¼ fðx n Þ for each n f 0. If this sequence is not eventually periodic, and if f does not lie in one of two explicitly determined a‰ne conjugacy classes of rational functions, then x nþ1 À x n has a primitive prime factor in its numerator for all su‰ciently large n. The same result holds for the exceptional maps provided that one looks for primitive prime factors in the denominator of x nþ1 À x n. Hence the result for each rational function f of degree at least 2 implies (a new proof) that there are infinitely many primes. The question of primitive prime factors of x nþD À x n is also discussed for D uniformly bounded.
An Economic Analysis of Strategies to Control Clostridium Difficile Transmission and Infection Using an Agent-Based Simulation Model

Background A number of strategies exist to reduce Clostridium difficile (C. difficile) transmission. We conducted an economic evaluation of “bundling” these strategies together. Methods We constructed an agent-based computer simulation of nosocomial C. difficile transmission and infection in a hospital setting. This model included the following components: interactions between patients and health care workers; room contamination via C. difficile shedding; C. difficile hand carriage and removal via hand hygiene; patient acquisition of C. difficile via contact with contaminated rooms or health care workers; and patient antimicrobial use. Six interventions were introduced alone and "bundled" together: (a) aggressive C. difficile testing; (b) empiric isolation and treatment of symptomatic patients; (c) improved adherence to hand hygiene and (d) contact precautions; (e) improved use of soap and water for hand hygiene; and (f) improved environmental cleaning. Our analysis compared these interventions using values representing 3 different scenarios: (1) base-case (BASE) values that reflect typical hospital practice, (2) intervention (INT) values that represent implementation of hospital-wide efforts to reduce C. diff transmission, and (3) optimal (OPT) values representing the highest expected results from strong adherence to the interventions. Cost parameters for each intervention were obtained from published literature. We performed our analyses assuming low, normal, and high C. difficile importation prevalence and transmissibility of C. difficile. Results INT levels of the “bundled” intervention were cost-effective at a willingness-to-pay threshold of $100,000/quality-adjusted life-year in all importation prevalence and transmissibility scenarios. OPT levels of intervention were cost-effective for normal and high importation prevalence and transmissibility scenarios. When analyzed separately, hand hygiene compliance, environmental decontamination, and empiric isolation and treatment were the interventions that had the greatest impact on both cost and effectiveness. Conclusions A combination of available interventions to prevent CDI is likely to be cost-effective but the cost-effectiveness varies for different levels of intensity of the interventions depending on epidemiological conditions such as C. difficile importation prevalence and transmissibility.
Improving subcellular localization prediction using text classification and the gene ontology

MOTIVATION Each protein performs its functions within some specific locations in a cell. This subcellular location is important for understanding protein function and for facilitating its purification. There are now many computational techniques for predicting location based on sequence analysis and database information from homologs. A few recent techniques use text from biological abstracts: our goal is to improve the prediction accuracy of such text-based techniques. We identify three techniques for improving text-based prediction: a rule for ambiguous abstract removal, a mechanism for using synonyms from the Gene Ontology (GO) and a mechanism for using the GO hierarchy to generalize terms. We show that these three techniques can significantly improve the accuracy of protein subcellular location predictors that use text extracted from PubMed abstracts whose references are recorded in Swiss-Prot.
Tighter Variational Representations of f-Divergences via Restriction to Probability Measures

We show that the variational representations for f-divergences currently used in the literature can be tightened. This has implications to a number of methods recently proposed based on this representation. As an example application we use our tighter representation to derive a general f-divergence estimator based on two i.i. d. samples and derive the dual program for this estimator that performs well empirically. We also point out a connection between our estimator and MMD.
Marine biofilms: cyanobacteria factories for the global oceans

Marine biofilms were newly revealed as a giant microbial diversity pool for global oceans. However, the cyanobacterial diversity in marine biofilms within the upper seawater column and its ecological and evolutionary implications remains undetermined. Here, we reconstructed a full picture of modern marine cyanobacteria habitats by re-analysing 9.3 terabyte metagenomic datasets and 2648 metagenome-assembled genomes (MAGs). The abundance of cyanobacteria lineages exclusively detected in marine biofilms were up to 9-fold higher than those in seawater at similar sample size. Analyses revealed that cyanobacteria in marine biofilms are specialists with strong geographical and environmental constraints on their genome and functional adaption, which in stark contrast to the generalistic features of seawater-derived cyanobacteria. Molecular dating suggests the important diversifications in biofilm-forming cyanobacteria appear to coincide with the Great Oxidation Event (GOE), “boring billion” middle Proterozoic, and the Neoproterozoic Oxidation Event (NOE). These new insights suggest that marine biofilms are large and important cyanobacterial factories for the global oceans. Importance Cyanobacteria, highly diverse microbial organisms, play a crucial role in Earth’s oxygenation and biogeochemical cycling. However, their connection to these processes remains unclear, partly due to incomplete surveys of oceanic niches. Our study uncovered significant cyanobacterial diversity in marine biofilms, showing distinct niche differentiation compared to seawater counterparts. These patterns reflect three key stages of marine cyanobacterial diversification, coinciding with major geological events in Earth’s history. Thus, surface-associated biomass within oceanic niches emerges as a pivotal factor in Earth’s evolution.
Forecasting Irregularly Sampled Time Series using Graphs

Forecasting irregularly sampled time series with missing values is a crucial task for numerous real-world applications such as healthcare, astronomy, and climate sciences. State-of-the-art approaches to this problem rely on Ordinary Differential Equations (ODEs) which are known to be slow and often require additional features to handle missing values. To address this issue, we propose a novel model using Graphs for Forecasting Irregularly Sampled Time Series with missing values which we call GraFITi. GraFITi first converts the time series to a Sparsity Structure Graph which is a sparse bipartite graph, and then reformulates the forecasting problem as the edge weight prediction task in the graph. It uses the power of Graph Neural Networks to learn the graph and predict the target edge weights. GraFITi has been tested on 3 real-world and 1 synthetic irregularly sampled time series dataset with missing values and compared with various state-of-the-art models. The experimental results demonstrate that GraFITi improves the forecasting accuracy by up to 17% and reduces the run time up to 5 times compared to the state-of-the-art forecasting models.
A Korean experience with chronic actinic dermatitis during an 18‐year period: meteorological and photoimmunological aspects

Background and purpose: The authors noted that chronic actinic dermatitis (CAD) increased in connection with increased sun exposure and believed that there may be a correlation between the two. The purpose of this study was to determine the relationship between increased sun exposure and CAD. We also applied a clinical severity scoring system to determine the correlation with various laboratory parameters.
Pre-Deployment Testing, Augmentation and Calibration of Cross-Sensitive Sensors

Over the past few years, many low-cost pollution sensors have been integrated into measurement platforms for air quality monitoring. However, using these sensors is challenging: concentrations of toxic substances in ambient air often lie at sensors' sensitivity boundaries, environmental conditions affect the sensor measurements, and the sensors often suffer from poor selectivity, i.e. are cross-sensitive to multiple pollutants. Datasheet information on these effects is scarce or may not cover deployment conditions. Consequently the sensors need to undergo extensive pre-deployment testing to examine their feasibility for a given application and to find the optimal measurement setup that allows accurate data collection and calibration. In this work, we propose a novel method to conduct in-field testing of low-cost sensors. The algorithm proposed is based on multiple least-squares and leverages the physical variation of urban air pollution to quantify the amount of explained and unexplained sensor signal. We verify (i) whether a sensor is feasible for air quality monitoring in a given environment and underpin our analysis with positive and negative examples of sensors available on the market, (ii) model sensor cross-sensitivities to interfering gases and environmental effects and (iii) compute the optimal sensor array and its calibration parameters for stable and accurate sensor measurements over long time periods in a given environment. Finally, we provide an experimental evaluation of our approach using over 9 million measurements of various low-cost sensors collected in an urban area. Based on the results from our testing methodology we propose an optimized sensor array setup. Further, we show---compared to a state-of-the-art calibration technique---a significantly lower calibration error with better long-time stability of the calibration parameters.