Miracle-dz/UniFAR-FTUs huggingface dataset:
A stochastic phase model with reflective boundary and induced beating for the cardiac muscle cells

We consider the stochastic phase models for the community effect of cardiac muscle cells. The model is the extension of the stochastic integrate-and-fire model in which we incorporate the irreversibility after beating, induced beating and refractory. We focus on investigating the expectation and variance of (synchronized) beating interval. In particular, for the single-isolated cell, we obtain the closed-form expectation and variance of the beating interval, and we discover that the coefficient of variance (CV) has upper limit $\sqrt{2/3}$. For two-coupled cells, we derive the partial differential equations (PDEs) for the expected synchronized beating intervals and the distribution density of phase. Moreover, we also consider the conventional Kuramoto model for both two- and $N$-cells models, where we establish a new analysis using stochastic calculus to obtain the CV of the ''synchronized'' beating interval, and make some improvement to the literature work.
Tolerant Distribution Testing in the Conditional Sampling Model

Recently, there has been significant work studying distribution testing under the Conditional Sampling model. In this model, a query involves specifying a subset $S$ of the domain, and the output received is a sample drawn from the distribution conditioned on being in $S$. In this paper, we primarily study the \emph{tolerant} versions of the classic \emph{uniformity} and \emph{identity} testing problems, providing improved query complexity bounds in the conditional sampling model. In this paper, we prove that tolerant uniformity testing in the conditional sampling model can be solved using $\tilde{O}(\varepsilon^{-2})$ queries, which is known to be optimal and improves upon the $\tilde{O}(\varepsilon^{-20})$-query algorithm of [CRS15]. Our bound even holds under the Pair Conditional Sampling model, a restricted version of the conditional sampling model where every queried subset $S$ either must have exactly $2$ elements, or must be the entire domain of the distribution. We also prove that tolerant identity testing in the conditional sampling model can be solved in $\tilde{O}(\varepsilon^{-4})$ queries, which is the first known bound independent of the support size of the distribution for this problem. Finally, we study (non-tolerant) identity testing under the pair conditional sampling model, and provide a tight bound of $\tilde{\Theta}(\sqrt{\log n} \cdot \varepsilon^{-2})$ for the query complexity, improving upon both the known upper and lower bounds in [CRS15].
Origin of entropy of gravitationally produced dark matter: The entanglement entropy

We study the emergence of entropy in gravitational production of dark matter particles, ultra light scalars minimally coupled to gravity and heavier fermions, from inflation to radiation domination (RD). Initial conditions correspond to dark matter fields in their Bunch-Davies vacua during inflation. The "out" states are correlated particle-antiparticle pairs, and the distribution function is found in both cases. In the adiabatic regime the density matrix features rapid decoherence by dephasing from interference effects in the basis of "out" particle states, effectively reducing it to a diagonal form with a concomitant von Neumann entropy. We show that it is exactly the entanglement entropy obtained by tracing over one member of the correlated pairs. Remarkably, for both statistics the entanglement entropy is similar to the quantum kinetic entropy in terms of the distribution function with noteworthy differences stemming from pair correlations. The entropy and the kinetic fluid form of the energy momentum tensor all originate from decoherence of the density matrix. For ultra light scalar dark matter, the distribution function peaks at low momentum $\propto 1/k^3$ and the specific entropy is $\ll 1$. This is a hallmark of a \emph{condensed phase} but with vanishing field expectation value. For fermionic dark matter the distribution function is nearly thermal and the specific entropy is $\mathcal{O}(1)$ typical of a thermal species. We argue that the functional form of the entanglement entropy is quite general and applies to alternative production mechanisms such as parametric amplification during reheating.
Improving Memory Utilization in Convolutional Neural Network Accelerators

While the accuracy of convolutional neural networks (CNNs) has achieved vast improvements by introducing larger and deeper network architectures, also the memory footprint for storing their parameters and activations has increased. This trend especially challenges power- and resource-limited accelerator designs, which are often restricted to store all network data in on-chip memory to avoid interfacing energy-hungry external memories. Maximizing the network size that fits on a given accelerator thus requires to maximize its memory utilization. While the traditionally used ping-pong buffering technique is mapping subsequent activation layers to disjunctive memory regions, we propose a mapping method that allows these regions to overlap and thus utilize the memory more efficiently. This letter presents the mathematical model to compute the maximum activations memory overlap and thus the lower bound of on-chip memory needed to perform layer-by-layer processing of CNNs on memory-limited accelerators. Our experiments with various real-world object detector networks show that the proposed mapping technique can decrease the activations memory by up to 32.9%, reducing the overall memory for the entire network by up to 23.9% compared to traditional ping-pong buffering. For higher resolution denoising networks, we achieve activation memory savings of 48.8%. Additionally, we implement a face detector network on a field-programmable gate array-based camera to validate these memory savings on a complete end-to-end system.
ALMA Deep Field in SSA22

Deep surveys with the Atacama Large Millimeter Array (ALMA) have uncovered a population of dusty star-forming galaxies which are faint or even undetected at optical to near-infrared wavelengths. Their faintness at short wavelengths makes the detailed characterization of the population challenging. Here we present a spectroscopic redshift identification and a characterization of one of these near-infrared-dark galaxies discovered by an ALMA deep survey. The detection of [C i](1–0) and CO(4–3) emission lines determines the precise redshift of the galaxy, ADF22.A2, to be z = 3.9913 ± 0.0008. On the basis of a multi-wavelength analysis, ADF22.A2 is found to be a massive, star-forming galaxy with a stellar mass of M∗ = 1.1 +1.3 −0.6 × 1011 M and SFR= 430+230 −150 M yr−1 . The molecular gas mass was derived to be M(H2) [CI] = (5.9 ± 1.5) × 1010 M, indicating a gas fraction of ≈35%, and the ratios of L[CI](1−0)/LIR and L[CI](1−0)/LCO(4−3) suggest that the nature of the interstellar medium in ADF22.A2 is in accordance with those of other bright submillimeter galaxies. The properties of ADF22.A2, including the redshift, star-formation rate, stellar mass, and depletion time scale (τdep ≈ 0.1−0.2 Gyr), also suggest that ADF22.A2 has the characteristics expected for the progenitors of quiescent galaxies at z & 3. Our results demonstrate the power of ALMA contiguous mapping and line scan, which help us to obtain an unbiased view of galaxy formation in the early Universe.
Learning to Play Cup-and-Ball with Noisy Camera Observations

Playing the cup-and-ball game is an intriguing task for robotics research since it abstracts important problem characteristics including system nonlinearity, contact forces and precise positioning as terminal goal. In this paper, we present a learning model based control strategy for the cup-and-ball game, where a Universal Robots UR5e manipulator arm learns to catch a ball in one of the cups on a Kendama. Our control problem is divided into two sub-tasks, namely (i) swinging the ball up in a constrained motion, and (ii) catching the free-falling ball. The swing-up trajectory is computed offline, and applied in open-loop to the arm. Subsequently, a convex optimization problem is solved online during the ball’s free-fall to control the manipulator and catch the ball. The controller utilizes noisy position feedback of the ball from an Intel RealSense D435 depth camera. We propose a novel iterative framework, where data is used to learn the support of the camera noise distribution iteratively in order to update the control policy. The probability of a catch with a fixed policy is computed empirically with a user specified number of roll-outs. Our design guarantees that probability of the catch increases in the limit, as the learned support nears the true support of the camera noise distribution. High-fidelity Mujoco simulations and preliminary experimental results support our theoretical analysis (video link– GitHub link).
Impact of Neuroprotection on Incidence of Alzheimer's Disease

Converging evidence suggests that high levels of education and intellectual activity increase the cognitive reserve and reduce the risk of dementia. However, little is known about the impact that different neuroprotective strategies may have on the incidence of Alzheimer's disease. Using a simple mathematical regression model, it is shown here that age-specific counts of basic cognitive units (surrogate of neurons or synapses) in the normal population can be estimated from Alzheimer's incidence rates. Hence, the model can be used to test the effect of neuroprotection on Alzheimer's incidence. It was found that the number of basic cognitive units decreases with age, but levels off in older people. There were no gender differences after correcting for survival. The model shows that even modest neuroprotective effects on basic cognitive units can lead to dramatic reductions in the number of Alzheimer's cases. Most remarkably, a 5% increase in the cognitive reserve would prevent one third of Alzheimer's cases. These results suggest that public health policies aimed at increasing the cognitive reserve in the general population (e.g., implementing higher levels of education) are likely the most effective strategy for preventing Alzheimer's disease.
INNATE IMMUNE SENSING OF A BACTERIAL PORE-FORMING TOXIN: THE ROLE OF THE NLRP3 INFLAMMASOME

Gram-positive bacterial infections have risen over recent years and current antibiotic treatments are not always sufficient to control these infections. Specifically, antibiotics target bacteria themselves, but not the bacterially secreted proteins that contribute to bacterial pathogenesis and host tissue damage (i.e. virulence factors). These virulence factors may linger after bacteria are eradicated, making their interaction with the host important to understand for the development of novel therapeutics to supplement antibiotics. One class of virulence factors studied in our laboratory is a large pore-forming toxin family known as the cholesterol-dependent cytolysins (CDC). These exotoxins are secreted by over twenty species of gram-positive bacteria and have been shown to contribute to the virulence of the bacteria that secrete them. We are interested in exploring the pathways initiated by CDC in host innate immune cells such as macrophages and dendritic cells. These cells would be expected to first encounter CDC after bacterial infection and therefore, pathways initiated in these cells by CDC could be targeted for the benefit of the host.We have characterized the mechanism of mature IL-1beta secretion induced by CDC tetanolysin O (TLO) from LPS-primed murine bone marrow-derived macrophages (BMDM). This process is dependent on TLO dose and relies on the caspase-1-containing NLRP3 inflammasome as well as associated signaling pathways, which include ion fluxes and iPLA2 and cathepsin B activities. Furthermore, TLO induces different cell death programs in BMDM that are dependent on TLO dose. High TLO doses induce conventional necrotic cell death while low TLO doses cause NLRP3 inflammasome-dependent and cathepsin B-dependent necrotic cell death that is characterized by lactate dehydrogenase (LDH) and high mobility group box 1 (HMGB1) release. Both IL-1beta and HMGB1 are pro-inflammatory cytokines that contribute to inflammation and may be useful therapeutic targets, in addition to the inflammasome. Finally, susceptibility to CDC-induced cell killing varies based on cell type. In order to determine pathways that might explain these differences, we created a variant murine dendritic cell line resistant to pore formation. Though this cell line has been characterized to some degree, future studies will be needed to pinpoint the pathways responsible for the phenotype observed.
Agarwood Alcohol Extract Ameliorates Isoproterenol-Induced Myocardial Ischemia by Inhibiting Oxidation and Apoptosis

Agarwood is a traditional medicine used for treating some diseases, including painful and ischemic diseases. This study was carried out to investigate the potential cardioprotective effect of the whole-tree agarwood-inducing technique-produced agarwood alcohol extract (WTAAE) on isoproterenol- (ISO-) induced myocardial ischemia (MI) in rats and explore the underlying molecular mechanisms. Compared to the MI group, WTAAE pretreatment significantly improved ST wave abnormal-elevation, mitigated myocardial histological damage; decreased creatinine kinase (CK), lactate dehydrogenase (LDH), alanine transaminase (ALT), and aspartate transaminase (AST) levels; reduced hydrogen peroxide (H2O2) and lipid peroxide (LPO) production; and increased total antioxidant capacity (T-AOC) and catalase (CAT) activities. Moreover, agarwood alcohol extracts (AAEs) markedly enhanced the mRNA levels of Nrf2-ARE pathway, and Bcl-2 reduced the apoptotic Bax family mRNA expressions. In addition, the effect of WTAAE was greater than that of wild agarwood alcohol extract (WAAE) and burning-chisel-drilling agarwood alcohol extract (FBAAE). All of these data indicate that WTAAE exerted the protective effects of MI, and its mechanism was associated with upregulating Nrf2-ARE and suppressing Bcl-2 pathways.
Antimicrobial Resistance Profile and Biofilm Production of Microorganisms Isolated from Oropharynx of Rupornis magnirostris (Gmelin, 1788) and Caracara plancus (Miller, 1777)

The aim of this preliminary study was to identify microorganisms with antimicrobial resistance profile and biofilm producers in oropharynx of Rupornis magnirostris and Caracara plancus. Six R. magnirostris and six C. plancus maintained in Triage Center for Wild Animals (CETAS) facilities were studied. Coagulase-positive staphylococci (CoPS), enterobacteria, and yeasts were identified by the biochemical analysis or MALDI-TOF mass spectrometry. The resistance profile of the microorganisms was analyzed according to CLSI. The biofilm production was evaluated by Congo red and violet crystal staining methods. Among the 12 birds, 10 presented strains of CoPS and/or enterobacteria with resistance profile, such as methicillin-resistant CoPS (MR-CoPS), vancomycin-resistant CoPS (VR-CoPS), extended-spectrum β-lactamase-producing Enterobacteriaceae (ESBL), and Klebsiella pneumoniae carbapenemase- (KPC-) producing bacteria. Regards the fungal analysis, Candida spp. , Cryptococcus spp. , Rhodotorula mucilaginosa, R. glutinis, and Trichosporon coremiiforme were identified. All the Trichosporon coremiiforme strains were resistant to amphotericin B, as well as all the Rhodotorula mucilaginosa exhibited resistance to fluconazole. Related to the biofilm production, among the 8 CoPS, 27 enterobacteria, and 10 yeasts isolates, 3, 16, and 7 strains were biofilm producers, respectively. Thus, the presence of these microorganisms in birds of prey is worrisome, highlighting its possible influence in the spread of infections in urban centers.
The PPAR Ω Pocket: Renewed Opportunities for Drug Development

The past decade of PPARγ research has dramatically improved our understanding of the structural and mechanistic bases for the diverging physiological effects of different classes of PPARγ ligands. The discoveries that lie at the heart of these developments have enabled the design of a new class of PPARγ ligands, capable of isolating central therapeutic effects of PPARγ modulation, while displaying markedly lower toxicities than previous generations of PPARγ ligands. This review examines the emerging framework around the design of these ligands and seeks to unite its principles with the development of new classes of ligands for PPARα and PPARβ/δ. The focus is on the relationships between the binding modes of ligands, their influence on PPAR posttranslational modifications, and gene expression patterns. Specifically, we encourage the design and study of ligands that primarily bind to the Ω pockets of PPARα and PPARβ/δ. In support of this development, we highlight already reported ligands that if studied in the context of this new framework may further our understanding of the gene programs regulated by PPARα and PPARβ/δ. Moreover, recently developed pharmacological tools that can be utilized in the search for ligands with new binding modes are also presented.
ESTIMATION OF SEX-SPECIFIC SURVIVAL FROM CAPTURE-RECAPTURE DATA WHEN SEX IS NOT ALWAYS KNOWN

Many animals lack obvious sexual dimorphism, making assignment of sex difficult even for observed or captured animals. For many such species it is possible to assign sex with certainty only at some occasions; for example, when they exhibit certain types of behavior. A common approach to handling this situation in capture–recapture studies has been to group capture histories into those of animals eventually identified as male and female and those for which sex was never known. Because group membership is dependent on the number of occasions at which an animal was caught or observed (known sex animals, on average, will have been observed at more occasions than unknown-sex animals), survival estimates for known-sex animals will be positively biased, and those for unknown animals will be negatively biased. In this paper, we develop capture–recapture models that incorporate sex ratio and sex assignment parameters that permit unbiased estimation in the face of this sampling problem. We demonstrate the magnitude.
Gradient models, gradient analysis, and hierarchical structure in plant communities

Oikos 78: 23-30. Two general models of plant community structure, the community-unit and the continuum, have dominated the thinking of American community ecologists. Hy- potheses derived from these and other models of plant community structure rarely have been tested, however. Traditionally, analyses of gradient structure have focused primarily on whether or not the boundaries of species response curves are clustered, which does not provide a complete picture of gradient structure. In this study, we statistically analyzed three characteristics of plant community structure along gradi- ents (1) pattern of boundaries of species distributions, (2) pattern of modes of species response curves, and (3) whether or not species distributions exhibit hierarchical structure. In combination, these characteristics yield eight different models of vegeta- tion structure along gradients. To determine if vegetation corresponds to any of these models, we sampled species composition using belt transects of contiguous quadrats in a total of 42 wetland sites in Minnesota and the southern Great Plains, USA. Boundaries of species distributions were clustered in 10 of 42 cases, modes of species response curves were clustered in 19 of 42 cases, and species distributions exhibited hierarchical structure in all 42 cases. Results varied between sites. Overall, four models of community structure were supported. None of the sites sampled supported the models often associated with the continuum or the community-unit. These results confirmed the need to explore alternative models of gradient structure, and suggested that more than one model of vegetation structure may be needed to represent community structure along gradients. B. W. Hoagland and S. L. Collins, Dept of' Botany and Microbiology, Unic. of Oklahoma, Norman, OK 73019, USA (uresent address of B WH: Oklahoma ,Vatural Heritage Inventory, Unit. of' Oklahoma, 111
Alzheimer's disease drug development pipeline: 2020

Alzheimer's disease (AD) is a growing public health concern affecting millions of patients worldwide and costing billions of dollars annually. We review the pipeline of drugs and biologics in clinical trials for the treatment of AD. We use the Common Alzheimer's and Related Dementias Research Ontology (CADRO) to classify treatment targets and mechanisms of action. We review our annual pipeline reports for the past 5 years to provide longitudinal insight into clinical trials and drug development for AD.
Occurrence of Enteric Viruses in Surface Water and the Relationship with Changes in Season and Physical Water Quality Dynamics

Environmental water quality issues have dominated global discourse and studies over the past five decades. Significant parameters of environmental water quality include changes in biological and physical parameters. Some of the biological parameters of significance include occurrence of enteric viruses. Enteric viruses can affect both human and animal's health by causing diseases such as gastrointestinal and respiratory infections. In this study, the relationship between the occurrence of enteric viruses with reference to adenoviruses and enteroviruses and the physical water quality characteristics was assessed from water samples collected from Lake Victoria (LV) in Kenya. In order to understand the dynamics of season driven enteric viruses' contamination of the lake waters, we additionally analysed seasonal behavior of the lake's catchment area in terms of rainfall effects. Physical quality parameters were measured on-site while viral analysis was carried out by molecular methods using the nested polymerase chain reaction (nPCR). From 216 samples that were analysed for viral contamination, enteric viral genomes were discovered in 18 (8.3%) of the samples. Out of half of the samples (108) collected during the rainy season, enteric viral genomes were detected in 9.26% (10) while 8 (7.41%) samples tested positive from the other half of the samples (108) collected during the dry season. There was, however, no significant correlation noted between the physical water quality characteristics and the enteric viruses' occurrence. Neither wet season nor dry season was significantly associated with the prevalence of the viruses. In Lake Victoria waters, most of the samples had an average of physical water quality parameters that were within the range accepted by the World Health Organization (WHO) for surface waters with exemption of turbidity which was above the recommended 5 NTU as recorded from some sampling sites. Continuous and long-term surveillance of the lake water to accurately monitor the contaminants and possible correlation between chemical, physical, and biological characteristics is recommended. This would be important in continuous understanding of the hydrological characteristics changes of the lake for proper management of its quality with reference to the WHO standards. A multiple varied-sampling approach in different geographical regions during different seasons is recommended to establish the geographical distribution and relatedness to seasonal distribution patterns of the viruses. The data generated from this study will be useful in providing a basis for assessment of seasonally driven fecal pollution load of the lake and enteric virus contamination for proper management of the sanitary situation around the lake.