Miracle-dz/UniFAR-FTUs huggingface dataset:
Stochastic reaction-diffusion models in biology

Every cell contains several millions of diffusing and reacting biological molecules. The interactions between these molecules ultimately manifest themselves in all aspects of life, from the smallest bacterium to the largest whale. One of the greatest open scientific challenges is to understand how the microscopic chemistry determines the macroscopic biology. Key to this challenge is the development of mathematical and computational models of biochemistry with molecule-level detail, but which are sufficiently coarse to enable the study of large systems at the cell or organism scale. Two such models are in common usage: the reaction-diffusion master equation, and Brownian dynamics. These models are utterly different in both their history and in their approaches to chemical reactions and diffusion, but they both seek to address the same reaction-diffusion question. Here we make an in-depth study into the physical validity of these models under various biological conditions, determining when they can reliably be used. Taking each model in turn, we propose modifications to the models to better model the realities of the cellular environment, and to enable more efficient computational implementations. We use the models to make predictions about how and why cells behave the way they do, from mechanisms of self-organisation to noise reduction. We conclude that both models are extremely powerful tools for clarifying the details of the mysterious relationship between chemistry and biology.
Genetic Diversity of Deformed Wing Virus From Apis mellifera carnica (Hymenoptera: Apidae) and Varroa Mite (Mesostigmata: Varroidae)

Abstract Deformed wing virus (DWV) is one of the most widespread viruses that infect honey bee colonies.The route of infection is directly through contaminated food, feces, and air, or indirectly through the varroa mite, which acts as a vector. Positive DWV samples were obtained from Carniolan honey bee (Apis mellifera carnica) colonies and of varroa mites from the whole territory of Slovenia during a survey between 2007 and 2014. Nucleotide sequences of 471 nucleotides for the L protein gene and 573 nucleotides for the helicase gene were compared. High genetic diversity was observed among these Slovenian Carniolan honey bee DWV field samples, as well as with almost all the strains previously found in other countries in Europe. Phylogenetic analyses in two regions of the viral genome show that several of the DWV strains obtained from honey bees and varroa are genetically very closely related, confirming the important role of varroa in the transmission of DWV. Identification of closely related sequences also confirmed that the same strains of DWV have been successfully transmitted between various honey bee colonies and apiaries. It has also been established that simultaneous infection, in one apiary, of honey bees with two or more different strains of DWV is quite frequent. This is phylogenetic study that compares honey bee and varroa DWV strains from Carniolan honeybees.
On the Representational Power of Restricted Boltzmann Machines for Symmetric Functions and Boolean Functions

Restricted Boltzmann machines (RBMs) are used to build deep-belief networks that are widely thought to be one of the first effective deep learning neural networks. This paper studies the ability of RBMs to represent distributions over <inline-formula> <tex-math notation="LaTeX">$\{0,1\}^{n}$ </tex-math></inline-formula> via softplus/hardplus RBM networks. It is shown that any distribution whose density depends on the number of 1’s in their input can be approximated with arbitrarily high accuracy by an RBM of size <inline-formula> <tex-math notation="LaTeX">$2n+1$ </tex-math></inline-formula>, which improves the result of a previous study by reducing the size from <inline-formula> <tex-math notation="LaTeX">$n^{2}$ </tex-math></inline-formula> to <inline-formula> <tex-math notation="LaTeX">$2n+1$ </tex-math></inline-formula>. A theorem for representing partially symmetric Boolean functions by softplus RBM networks is established. Accordingly, the representational power of RBMs for distributions whose mass represents the Boolean functions is investigated in comparison with that of threshold circuits and polynomial threshold functions. It is shown that a distribution over <inline-formula> <tex-math notation="LaTeX">$\{0,1\}^{n}$ </tex-math></inline-formula> whose mass represents a Boolean function can be computed with a given margin <inline-formula> <tex-math notation="LaTeX">$\delta$ </tex-math></inline-formula> by an RBM of size and parameters bounded by polynomials in <inline-formula> <tex-math notation="LaTeX">$n$ </tex-math></inline-formula>, if and only if it can be computed by a depth-2 threshold circuit with size and parameters bounded by polynomials in <inline-formula> <tex-math notation="LaTeX">$n$ </tex-math></inline-formula>.
Nonsaturating large magnetoresistance in semimetals

Significance The intensive recent investigations of topological semimetals have revealed a large number of semimetal compounds that exhibit very large nonsaturating magnetoresistance. Multiple mechanisms for this magnetoresistance phenomenon have been theoretically proposed, but experimentally it is unclear how to identify which mechanism is responsible in a particular sample or how to make a clean connection between experimental observations and theoretical models. Our results show that the magnetic susceptibility and the tangent of the Hall angle successfully capture the fundamental differences in seemingly similar nonsaturating large magnetoresistance, where charge compensation, energy dispersion, and the roles of disorder are markedly distinct, and provide empirical templates to characterize the origins of the extraordinary magnetotransport properties in the newly discovered topological semimetals and beyond. The rapidly expanding class of quantum materials known as topological semimetals (TSMs) displays unique transport properties, including a striking dependence of resistivity on applied magnetic field, that are of great interest for both scientific and technological reasons. So far, many possible sources of extraordinarily large nonsaturating magnetoresistance have been proposed. However, experimental signatures that can identify or discern the dominant mechanism and connect to available theories are scarce. Here we present the magnetic susceptibility (χ), the tangent of the Hall angle (tan⁡θH), along with magnetoresistance in four different nonmagnetic semimetals with high mobilities, NbP, TaP, NbSb2, and TaSb2, all of which exhibit nonsaturating large magnetoresistance (MR). We find that the distinctly different temperature dependences, χ(T), and the values of tan⁡θH in phosphides and antimonates serve as empirical criteria to sort the MR from different origins: NbP and TaP are uncompensated semimetals with linear dispersion, in which the nonsaturating magnetoresistance arises due to guiding center motion, while NbSb2 and TaSb2 are compensated semimetals, with a magnetoresistance emerging from nearly perfect charge compensation of two quadratic bands. Our results illustrate how a combination of magnetotransport and susceptibility measurements may be used to categorize the increasingly ubiquitous nonsaturating large magnetoresistance in TSMs.
Perceptron Linear Activation Function Design with CMOS-Memristive Circuits

In the last decade, the interest to emulate of the functionality and structure of the human brain to solve the problems related to image processing and pattern recognition, especially using to Artificial Neural Network (ANN), has significantly increased. The capability of ANN to perform at highspeed has been proven to be very useful for various large scale problems. One of the simple ANN models is perceptron. Since the perceptron is the basic form of a neural network, the efficient implementation of an activation functions is required to build the neural network on hardware. As various works introduce the design of sigmoid and tangent activation functions, most of the other activation functions remain an open research problem. This paper describes the design of the perception circuit with the linear activation function based on operational amplifier for memristive crossbar based neural networks. Additionally, the variation of performance with temperature and noise noise analysis of the circuit are presented.
Maximum Entropy Low-Rank Matrix Recovery

We propose a novel, information-theoretic method, called <monospace>MaxEnt</monospace>, for efficient data acquisition for low-rank matrix recovery. This proposed method has important applications to a wide range of problems, including image processing and text document indexing. Fundamental to our design approach is the so-called maximum entropy principle, which states that the measurement masks that maximize the entropy of observations, also maximize the information gain on the unknown matrix <inline-formula><tex-math notation="LaTeX">$\mathbf {X}$</tex-math> </inline-formula>. Coupled with a low-rank stochastic model for <inline-formula><tex-math notation="LaTeX">$\mathbf {X}$</tex-math></inline-formula>, such a principle 1) reveals novel connections between information-theoretic sampling and subspace packings, and 2) yields efficient mask construction algorithms for matrix recovery, which significantly outperform random measurements. We illustrate the effectiveness of <monospace>MaxEnt</monospace> in simulation experiments, and demonstrate its usefulness in two real-world applications on image recovery and text document indexing.
Comparison of Bipolar and Unipolar Pulses in Cell Electrofusion: Simulation and Experimental Research

Objective: Unipolar pulses have been used in cell electrofusion over the last decades. However, the problem of high mortality with unipolar pulses has not been solved effectively. The cell fusion rate is restricted by cell mortality. By using the advantages of bipolar pulses which cause less cell damage, this paper attempts to use bipolar pulses to increase the cell fusion rate. Methods: the transmembrane voltage and pore density of cells subjected to unipolar/bipolar pulses were simulated in COMSOL software. In an experiment, two 40 μs unipolar and two 20–20 μs bipolar pulses with electric fields of 2, 2.5, and 3 kV/cm were applied to SP2/0 murine myeloma cells. To determine the cell fusion rate and cell mortality, cells were stained with Hoechst 33342 and propidium iodide. Results: the simulation in this paper showed that a high transmembrane voltage and a high pores density were concentrated only at the contact area of cells when bipolar pulses were used. The results of the cell staining experiment verified the simulation analysis. When bipolar pulses were applied, the cell mortality was significantly reduced. In addition, the cell fusion rate with bipolar pulses was almost two times higher than that with unipolar pulses. Conclusion: for cell electrofusion, compared with unipolar pulses, bipolar pulses can not only reduce the cell mortality remarkably but also improve the cell fusion rate obviously. Significance: this paper introduces a novel way to increase the fusion rate of cells.
Analysis of Pure Collective Aloha MAC Protocol with Multilevel Powers

The key contributions of this paper are the proposed Pure Collective Aloha (PCA) medium access control (MAC) protocol with multilevel powers and its closed-form theoretical analysis. The PCA MAC protocol collects a batch of packets before transmitting these packets sequentially in the channel. The key idea in the design of this PCA MAC protocol with multilevel powers is to spread out the arrivals of each batch of packets in a channel and the multilevel powers of the packets received at the receiver allow capture for the case of the strongest signal power packet among the overlapping lower signal power packets to be successfully received at the receiver. If it is the only received packet, it is successfully received, regardless of its received power level. The PCA MAC protocol with multilevel powers is analyzed theoretically. The explicit closed-form expressions for the optimal offered loads and the maximum throughputs of the Pure Aloha, the Slotted Aloha and the PCA MAC protocols with multilevel powers are presented. The numerical results show that the throughput of the asynchronous PCA MAC protocol with multilevel powers is about 90.5% better than that of the asynchronous Pure Aloha MAC protocol with multilevel powers and can approach the maximum throughput bound of the synchronous Slotted Aloha MAC protocol with multilevel powers, without the need of any synchronization mechanism to slot boundaries.
User's Perspective of Software Quality

In a decade ago software engineering exploration progressively focused on software quality improvement and assessment, however the major of these researchers focus on the internal/development perspective i.e. they did not consider users point of views. Nevertheless users mainly attention in the quality of performance intended functions efficiently without knowing how the software product is developed, how work form inside, or its internal quality. The achievement of software companies is totally relies upon the users satisfaction, which they choose to use a software product or not. Hence, in software development strong attention must given to users satisfactions. Software Quality research on users satisfaction help the developers to develop a software that meet users requirements and accepted by end users. In this article based on well known software quality models and the users of software product we intended to discuss the factors as well as sub factors of software quality that influence user's satisfactions.
Load Node – ESS-DG-PV Level II : MG Asset Dispatching Utility Agent MGCC Agent MG Equivalent Aggregate MG Models ( Controllable Loads ) Level I : Distribution System Control Utility Agent

This paper presents an approximate Reinforcement Learning (RL) methodology for data-driven power management of networked Microgrids (MG) in electric distribution systems. In practice, the system operator has limited or no knowledge of the MG asset behavior and models behind the Point of Common Coupling (PCC). This makes the distribution systems unobservable and impedes a conventional optimization approach for solving the power management problem while satisfying network constraints. To tackle this challenge, we have proposed a bilevel model-free machine learning framework in a retail market environment which functions exclusively based on the exchanged signals between different entities within the market. While at the lower level, each MG provides power-flow-constrained optimal response to price and voltage signals, at the higher level, the system operator performs function approximation to predict the behavior of market participants under incomplete information of MG parametric models. This function approximation scheme is then used within an adaptive RL framework to optimize the price signal and the substation voltage as the system load and solar generation change over time. Numerical experiments have been devised to verify the performance of the proposed learning model.
Development of loneliness in midlife and old age: Its nature and correlates.

Research has long demonstrated that loneliness is a key risk factor for poor health. However, less is known about the development and predictors of loneliness across later adulthood. We examined these questions using two-wave data obtained 5 years apart in the population-based Norwegian NorLAG study (N = 5,555; age 40-80 years; 51% women). We considered direct measures of loneliness (asking directly about feeling lonely) and indirect measures (avoiding the term loneliness) and linked them to self-report data on personality and contact with friends, and to register data on socioeconomic (education, income, unemployment), physical health (sick leave, lifetime history of disability), and social factors (children, marriage/cohabitation, lifetime history of divorce and widowhood). Results indicated that levels of loneliness increased steadily for women, whereas men's levels followed a U-shaped curve, with highest loneliness at ages 40 and 80. At age 40, loneliness declined between the two data waves, but with increasing age the decrease abated and turned into increases when loneliness was measured indirectly. Disability, no spouse/cohabiting partner, widowhood, and little contact with friends were each associated with more loneliness. Similarly, people high in emotional stability and extraversion reported less loneliness and experienced steeper loneliness declines on one or both loneliness measures. We take our results to illustrate the utility of combining self-report and register data and conclude that the development of loneliness across the second half of life is associated with both individual difference characteristics and aspects of social embedding. We discuss possible mechanisms underlying our findings and consider practical implications. (PsycINFO Database Record (c) 2018 APA, all rights reserved).
Prevalence and clinical correlates of depression in the acute phase of first episode schizophrenia

Abstract Background: Reported rates of depression in schizophrenia vary considerably. Objective: To measure the prevalence of depression in a first episode sample of people with schizophrenia. Methods: All referrals with a first episode of schizophrenia diagnosed using SCID interviews were assessed pre-discharge and again six months later. We used the Calgary Depression Scale for Schizophrenia (CDSS) and Positive and Negative Syndrome Scale (PANSS) to assess the severity of symptoms. Results: Pre-discharge, 10.4% of the sample met CDSS criteria for depression. According to the PANSS depression (PANSS -D) subscale, 3% of patients were depressed, with a mean score of 7.48 (SD = 2.97). Only 3% of patients pre-discharge were found to be depressed on both the CDSS and the PANSS-D. Six months later 6.5% were depressed according to the CDSS. However none reached depression criteria according to the PANSS-D. The CDSS correlated with PANSS-D both pre-discharge and at follow-up. Feelings of depression and self-deprecation were the most common symptoms at baseline and follow-up. The CDSS was unrelated to negative symptoms at both stages. A lifetime history of alcohol abuse increased the risk for depression. Conclusion: Rates of depression in this sample were low. The CDSS appears to discriminate between depression and negative symptoms. Like the general population, alcohol misuse is a risk factor for depression in first episode schizophrenia.
Naturalization Module in Neural Networks for Screen Content Image Quality Assessment

Deep learning approaches have demonstrated success in no-reference image quality assessment tasks. However, due to the specific properties of screen content images (SCIs), deep neural networks for SCI quality assessment are not as optimal as those designed for images depicting natural scenes. In order to tackle this discrepancy, a “naturalization” module composed of an upsampling layer and a convolutional layer is proposed to transform SCIs to have characteristics more similar to that of natural images. In addition, a new deep learning model architecture along with data augmentation techniques tailored to SCIs are implemented. The performance of the proposed approach is evaluated on the Screen Image Quality Assessment Database and Screen Content Image Database, and has shown to have superior performance to state-of-the-art methods in predicting the perceptual quality of SCIs.
Is callose required for silicification in plants?

The cell wall polymer callose catalyses the formation of silica in vitro and is heavily implicated in biological silicification in Equisetum (horsetail) and Arabidopsis (thale cress) in vivo. Callose, a β-1,3-glucan, is an ideal partner for silicification, because its amorphous structure and ephemeral nature provide suitable microenvironments to support the condensation of silicic acid into silica. Herein, using scanning electron microscopy, immunohistochemistry and fluorescence, we provide further evidence of the cooperative nature of callose and silica in biological silicification in rice, an important crop plant and known silica accumulator. These new data along with recently published research enable us to propose a model to describe the intracellular events that together determine callose-driven biological silicification.
Prescribing Variation in General Practices in England Following a Direct Healthcare Professional Communication on Mirabegron

Introduction: Pharmacovigilance may detect safety issues after marketing of medications, and this can result in regulatory action such as direct healthcare professional communications (DHPC). DHPC can be effective in changing prescribing behaviour, however the extent to which prescribers vary in their response to DHPC is unknown. This study aims to explore changes in prescribing and prescribing variation among general practitioner (GP) practices following a DHPC on the safety of mirabegron, a medication to treat overactive bladder (OAB). Methods: This is an interrupted time series study of English GP practices from 2014–2017. National Health Service (NHS) Digital provided monthly statistics on aggregate practice-level prescribing and practice characteristics (practice staff and registered patient profiles, Quality and Outcomes Framework indicators, and deprivation of the practice area). The primary outcome was monthly mirabegron prescriptions as a percentage of all OAB drug prescriptions and we assessed the change following a DHPC issued by the European Medicines Agency in September 2015. The DHPC stated mirabegron use was contraindicated with severe uncontrolled hypertension and cautioned with hypertension. Variation between practices in mirabegron prescribing before and after the DHPC was assessed using the systematic component of variation (SCV). Multilevel segmented regression with random effects quantified the change in level and trend of prescribing after the DHPC. Practice characteristics were assessed for their association with a reduction in prescribing following the DHPC. Results: This study included 7408 practices. During September 2015, 88.9% of practices prescribed mirabegron and mirabegron comprised a mean of 8.2% (SD 6.8) of OAB prescriptions. Variation between practices was classified as very high and the median SCV did not change significantly (p = 0.11) in the six months after the September 2015 DHPC (12.4) compared to before (11.6). Before the DHPC, the share of mirabegron over all OAB drug prescriptions increased by 0.294 (95% confidence interval (CI), 0.287, 0.301) percentage points per month. There was no significant change in the month immediately after the DHPC (−0.023, 95% CI −0.105 to 0.058), however there was a significant reduction in trend (−0.036, 95% CI −0.049 to −0.023). Higher numbers of registered patients, patients aged ≥65 years, and practice area deprivation were associated with having a significant decrease in level and slope of mirabegron prescribing post-DHPC. Conclusion: Variation in mirabegron prescribing was high over the study period and did not change substantively following the DHPC. There was no immediate prescribing change post-DHPC, although the monthly growth did slow. Knowledge of the degree of variation in and determinants of response to safety communications may allow those that do not change prescribing habits to be provided with additional support.