Miracle-dz/UniFAR-FTUs huggingface dataset:
Activation of Ca2+‐activated Cl− channel ANO1 by localized Ca2+ signals

Ca2+‐activated chloride channels (CaCCs) regulate numerous physiological processes including epithelial transport, smooth muscle contraction and sensory processing. Anoctamin‐1 (ANO1, TMEM16A) is a principal CaCC subunit in many cell types, yet our understanding of the mechanisms of ANO1 activation and regulation are only beginning to emerge. Ca2+ sensitivity of ANO1 is rather low and at negative membrane potentials the channel requires several micromoles of intracellular Ca2+ for activation. However, global Ca2+ levels in cells rarely reach such levels and, therefore, there must be mechanisms that focus intracellular Ca2+ transients towards the ANO1 channels. Recent findings indeed indicate that ANO1 channels often co‐localize with sources of intracellular Ca2+ signals. Interestingly, it appears that in many cell types ANO1 is particularly tightly coupled to the Ca2+ release sites of the intracellular Ca2+ stores. Such preferential coupling may represent a general mechanism of ANO1 activation in native tissues.
Quasilinear algorithm for the component tree

The level sets of a map are the sets of points with level above a given threshold. The connected components of the level sets, thanks to the inclusion relation, can be organized in a tree structure, that is called the component tree. This tree, under several variations, has been used in numerous applications. Various algorithms have been proposed in the literature for computing the component tree. The fastest ones have been proved to run in 0(nln(n)) complexity. In this paper, we propose a simple to implement quasi-linear algorithm for computing the component tree on symmetric graphs, based on Tarjan’s union-find principle.
Testing for Jumps in a Discretely Observed Process

We propose a new test to determine whether jumps are present in asset returns or other discretelly sampled processses. As the sampling interval tends to 0, our test statistic converges to 1 if there are jumps, and to another deterministic and known value (such as 2) if there are no jumps. The test is valid for all Ito semimartingales, depends neither on the law of the process nor on the coefficients of the equation which it solves, does not require a preliminary estimation of these coefficients, and when there are jumps the test is applicable whether jumps have finite or infinite activity and for an arbitrary Blumenthal-Getoor index. We finally implement the test on simulations and asset returns data.
Local Morphine Withdrawal Increases c-fos Gene, Fos Protein, and Oxytocin Gene Expression in Hypothalamic Magnocellular Neurosecretory Cells

We measured stimulation of c-fos and oxytocin gene expression during excitation of oxytocin cells induced by systemic or local morphine withdrawal. Female rats were made morphine-dependent by intracerebroventricular morphine infusion over 5 d. Morphine withdrawal, induced by systemic injection of the opioid antagonist naloxone (5 mg/kg) in conscious or anesthetized rats, increased the density of c-fos messenger RNA and of oxytocin heterogeneous nuclear RNA in supraoptic nucleus cells compared with those of nonwithdrawn rats; c-fos messenger RNA was also increased in the magnocellular and parvocellular paraventricular nuclei of withdrawn rats. Morphine withdrawal increased the number of Fos-immunoreactive cells in the supraoptic and magnocellular paraventricular nuclei of conscious or pentobarbitone-anesthetized rats. Morphine withdrawal also increased Fos-immunoreactive cell numbers in the parvocellular paraventricular nucleus of conscious but not anesthetized rats. Central administration of the α1-adrenoreceptor antagonist benoxathian (5 μg/min) did not prevent morphine withdrawal-induced increases in the numbers of Fos-immunoreactive neurons in the supraoptic or magnocellular paraventricular nucleus. Unilateral microdialysis administration of naloxone (10−5m) into the supraoptic nucleus of anesthetized morphine-dependent rats increased Fos-immunoreactive cell numbers compared with the contralateral nucleus. Finally, we investigated whether dependence could be induced by chronic unilateral infusion of morphine into a supraoptic nucleus; systemic naloxone (5 mg/kg) increased Fos-immunoreactive cell numbers in the morphine-infused nucleus compared with the contralateral nucleus. Thus, morphine withdrawal excitation increases c-fos and oxytocin gene expression in supraoptic nucleus neurons. This occurs independently from excitation of their ascending noradrenergic inputs, and both dependence and withdrawal can be induced within the supraoptic nucleus.
Pervasive and Persistent Redundancy among Duplicated Genes in Yeast

The loss of functional redundancy is the key process in the evolution of duplicated genes. Here we systematically assess the extent of functional redundancy among a large set of duplicated genes in Saccharomyces cerevisiae. We quantify growth rate in rich medium for a large number of S. cerevisiae strains that carry single and double deletions of duplicated and singleton genes. We demonstrate that duplicated genes can maintain substantial redundancy for extensive periods of time following duplication (∼100 million years). We find high levels of redundancy among genes duplicated both via the whole genome duplication and via smaller scale duplications. Further, we see no evidence that two duplicated genes together contribute to fitness in rich medium substantially beyond that of their ancestral progenitor gene. We argue that duplicate genes do not often evolve to behave like singleton genes even after very long periods of time.
Closed-Form Critical Conditions of Subharmonic Oscillations for Buck Converters

Based on a general critical condition of subharmonic oscillation in terms of the loop gain, many closed-form critical conditions for various control schemes in terms of converter parameters are derived. Some previously known critical conditions become special cases in the generalized framework. Given an arbitrary control scheme, a systematic procedure is proposed to derive the critical condition for that control scheme. Different control schemes share similar forms of critical conditions. For example, both V2 control and proportional voltage mode control have the same form of critical condition. A peculiar phenomenon in average current mode control where subharmonic oscillation occurs in a window value of pole can be explained by the derived critical condition. A ripple amplitude index to predict subharmonic oscillation proposed in the past research has limited application and is shown invalid for a converter with a large pole comparable to the switching frequency.
On preservation of dissipation inequalities under sampling

We show that if we first design a controller for a continuous-time nonlinear plant with disturbances so that it achieves a certain dissipation inequality for the continuous-time closed-loop system and then implement it as a sampled-data controller using a sampler and zero order hold, then the dissipation inequality will be preserved for the exact discrete-time model of the sampled data closed-loop system in a semiglobal practical sense (the sampling period is the parameter that we can adjust). Moreover, a similar statement is proved for open-loop systems, where controls are considered as free variables. Two different forms of dissipation inequalities are considered for the exact discrete-time models: the "weak" form and the "strong" form.
Speed binning aware design methodology to improve profit under parameter variations

Designing high-performance systems with high yield under parameter variations has raised serious design challenges in nanometer technologies. In this paper, we propose a profit-aware yield model, based on which we present a statistical design methodology to improve profit of a design considering frequency binning and product price profile. A low-complexity sensitivity-based gate sizing algorithm is developed to improve the profitability of design over an initial yield-optimized design. We also propose an algorithm to determine optimal bin boundaries for maximizing profit with frequency binning. Finally, we present an integrated design methodology for simultaneous sizing and bin placement to enhance profit under an area constraint. Experiments on a set of ISCAS85 benchmarks show up to 26% (36%) improvement in profit for fixed bin (for simultaneous sizing and bin placement) with three frequency bins considering both leakage and delay bounds compared to a design optimized for 90% yield at iso-area
Statistical inferences for functional data

With modern technology development, functional data are being observed frequently in many scientific fields. A popular method for analyzing such functional data is ``smoothing first, then estimation. '' That is, statistical inference such as estimation and hypothesis testing about functional data is conducted based on the substitution of the underlying individual functions by their reconstructions obtained by one smoothing technique or another. However, little is known about this substitution effect on functional data analysis. In this paper this problem is investigated when the local polynomial kernel (LPK) smoothing technique is used for individual function reconstructions. We find that under some mild conditions, the substitution effect can be ignored asymptotically. Based on this, we construct LPK reconstruction-based estimators for the mean, covariance and noise variance functions of a functional data set and derive their asymptotics. We also propose a GCV rule for selecting good bandwidths for the LPK reconstructions. When the mean function also depends on some time-independent covariates, we consider a functional linear model where the mean function is linearly related to the covariates but the covariate effects are functions of time. The LPK reconstruction-based estimators for the covariate effects and the covariance function are also constructed and their asymptotics are derived. Moreover, we propose a $L^2$-norm-based global test statistic for a general hypothesis testing problem about the covariate effects and derive its asymptotic random expression. The effect of the bandwidths selected by the proposed GCV rule on the accuracy of the LPK reconstructions and the mean function estimator is investigated via a simulation study. The proposed methodologies are illustrated via an application to a real functional data set collected in climatology.
On the Sublinear Behavior of MIMO Channel Capacity at Low SNR

We consider wideband wireless communication over a multiple-input, multiple-output (MIMO) Rayleigh fading channel where the transmitter has no channel state information (CSI). We study the channel with perfect receiver CSI (coherent channel) versus the channel with no CSI at the receiver (non-coherent channel). A channel with partial CSI at the receiver has a capacity between the coherent and non-coherent channels and in this paper, we study the two extremes. The capacities of the coherent and non-coherent channels dier in their sublinear term and in [6], Verd u computed the sublinear term of the coherent channel and gave a lower bound for the sublinear term of the noncoherent channel. However, without an upper bound for this term, we cannot quantify the loss in capacity (or increase in bandwidth required) due to lack of receiver CSI. In this paper, we compute an upper bound for the sublinear term of the non-coherent MIMO channel and show that it is approximately O(SNR). We therefore quantify the maximum penalty for not having CSI at the receiver. For the i.i. d. Rayleigh fading channel, we study the eect of the number of receive antennas on the loss in capacity due to not having CSI at the receiver. We show that this loss increases monotonically with the number of receive antennas. Therefore, as the number of receive antennas increases, channel estimation becomes more and more important. This also shows that the capacity increase due to power gain from the additional receive antennas is more if we know the additional paths at the receiver.
Optimization of GMM training for speaker verification

EM training of GMM often suffers from the existence of local maxima and singularities in the likelihood space. In this paper, we present a new Modified Split-and-Merge EM algorithm (MSMEM) for speaker verification tasks, which performs split-and-merge operations to escape from local maxima and reduce the chances of generating singularities. With two modified criteria to select split-and-merge candidates for speaker verification task, the overall likelihoods of both training and testing data are improved. Furthermore, modified adaptive variance flooring is introduced in the new EM procedure. Experiments on synthetic data show the advantages of MSMEM. Global threshold EER results on a speaker verification task using the TIMIT database confirm the improvement of the system performance.
Stress fibers in the splenic sinus endothelium in situ: molecular structure, relationship to the extracellular matrix, and contractility

In the present study, we investigated structural and functional aspects of stress fibers in a cell type in situ, i.e., the sinus endothelium of the human spleen. In this cell type, stress fibers extend underneath the basal plasma membrane and are arranged parallel to the cellular long axis. Ultrastructurally, the stress fibers were found to be composed of thin actin-like filaments (5-8 nm) and thick myosin-like filaments (10-15 nm X 300 nm). Actin filaments displayed changes in polarity (determined by S-1-myosin subfragment decoration), which may allow a sliding filament mechanism. At their plasmalemmal attachment sites, actin filaments exhibited uniform polarity with the S-1- arrowhead complexes pointing away from the plasma membrane. Fluorescence microscopy showed that the stress fibers have a high affinity for phalloidin and antibodies to actin, myosin, tropomyosin, and alpha-actinin. Vinculin was confined to the cytoplasmic aspect of the plasmalemmal termination sites of stress fibers, while laminin, fibronectin, and collagens were located at the extracellular aspect of these stress fiber-membrane associations. Western blot analysis revealed polypeptide bands that contained actin, myosin, and alpha- actinin to be major components of isolated cells. Exposure of permeabilized cells to MgATP results in prominent changes in cellular shape caused by stress fiber contraction. It is concluded that the stress fibers in situ anchored to cell-to-extracellular matrix contacts can create tension that might allow the endothelium to resist the fluid shear forces of blood flow.
Practical Investigations on Cobalt–Iron Laminations for Electrical Machines

The adoption of high-performance soft magnetic material can be considered a possible way to respect the challenging design specifications for aerospace and automotive electrical machines. This paper presents an accurate noninvasive investigation of magnetic and energetic properties of cobalt-iron stator cores. In particular, the focus lies on the annealing processes aimed to maximize the magnetic saturation and the mechanical strength. Three cobalt-iron stator core samples coming from different annealing processes have been analyzed, both from the BH characteristics and losses viewpoints. Stator slot effects on the magnetic measurements have been investigated by finite-element method. A fringing effect correction factor to be applied on the measured BH curves is as well reported. In order to complete the experimental campaign analysis, micrographic analysis of the material structure is presented, as well as the iron losses separation coefficients.
Association between Outdoor Ambient Illuminance and Elderly People’s Moods in a Care Home

Daylight has potential to stimulate individual’s sensations and feelings. Older people who live in care homes should have some sense of outdoor daylight that might influence their moods. This paper describes a pilot study that investigates the association between the outdoor ambient illuminance and elderly people’s mood changes in a care home environment while controlling other contributory factors, such as outdoor temperature, occupant age, gender and medical conditions (e.g. dementia and blindness). Real world field data was collected from an existing care home. Environmental data (outdoor illuminance and temperature) was collected by installing outdoor data loggers on the roof top of the care home. Demographic and physiological information of the occupants were collected from care home records. Care home staff rated occupants’ moods on a Likert-type scale composed of three quantifiable response modes: numerical rating scale (NRS), visual analogue scale (VAS) and faces rating scale (FRS). Ordered logit (OLOGIT) model, suitable to develop correlation between ordinal dependent variables (i.e. mood) and continuous data (i.e. illuminance) are used. The analysis shows, assuming all other explanatory variables remain constant, the probability of a better mood increases with the increase of outdoor illuminance (p-value=0.022). However, in a very hot/cold day the probability of a better mood could be decreased under the same outdoor daylight level.
Graph hashing and factorization for fast graph stream classification

Graph stream classification concerns building learning models from continuously growing graph data, in which an essential step is to explore subgraph features to represent graphs for effective learning and classification. When representing a graph using subgraph features, all existing methods employ coarse-grained feature representation, which only considers whether or not a subgraph feature appears in the graph. In this paper, we propose a fine-grained graph factorization approach for Fast Graph Stream Classification (FGSC). Our main idea is to find a set of cliques as feature base to represent each graph as a linear combination of the base cliques. To achieve this goal, we decompose each graph into a number of cliques and select discriminative cliques to generate a transfer matrix called Clique Set Matrix (M). By using M as the base for formulating graph factorization, each graph is represented in a vector space with each element denoting the degree of the corresponding subgraph feature related to the graph, so existing supervised learning algorithms can be applied to derive learning models for graph classification.
Education and Training Management Model and Incentive Mechanism based on Core Employees of Scientific and Technological Small and Micro Enterprises

The core employees are the key resources of gathering strength and innovating for scientific and technological small and micro enterprises (STSMEs). Aiming at the status quo of the education and training of core employees of STSMEs, as well as the solidification of the current incentive mechanism, the unreasonable salary system, the imperfect training mechanism and the lack of corporate culture, this study starts with the influence of core employees on STSMEs, and analyzes the problems existing in the education and training model and incentive mechanism of core employees of STSMEs. Combined with the characteristics of STSMEs, this study proposes specific measures to improve the incentive mechanism of core employees to stimulate the potentials of core employees, give full play to the value of core employees, and enhance the market competitiveness of STSMEs.
Battle and Fettle of Chronically Middle-Aged Adults: Basis for Eclectic Therapy

This study sought to examine the chronically middle-aged adults’ quality of life in terms of physical, psychological, level of independence, social relationship, environment and spirituality, religion and personal beliefs. It also explored on their feelings and experiences toward the illness. This study used a concurrent triangulation type of mixed method to thoroughly explore the perceptions, difficulties and coping of chronically middle aged adults. WHO Quality of Life was used in quantitative data and interview and observation was utilized for the qualitative part. Percentage, weighted mean and ranking was used to analyse the data. Results show that chronically ill middle-aged need physical assistance, psychological support, and they have ambivalent feelings towards level of independence. On the contrary, they have a satisfying social relationship, secure environment to live, and an enhanced level of spirituality. Experiences of chronically ill middle aged adults arise into different meaning as to loss of control over the body, deprived healthy identity, devalued self, cyclic sadness, period of hopelessness and struggles, impact of uncertainty, support that enhance positivity, spiritual intensification and moving toward self sufficiency. An eclectic therapy is devised to address the specific needs of chronically ill middle-aged adults. Thus, a LIFE therapy as an eclecticism approach is devised based on the result of the study.
Gravitational Thomas Precession and the Perihelion Advance of Mercury

Gravitational Thomas Precession (GTP) is the name given to Thomas Precession when the acceleration is caused by a gravitational force field. The GTP gives a negative contribution of 7.163 arcsec/century for the anomalous perihelion advance of Mercury's orbit. This effect seems to be of some concern for the General Relativity.
On data sparsification and a recursive algorithm for estimating a kernel-based measure of independence

Technological improvements have led to situations where data sets are sufficiently rich that in the interests of processing speed it is desirable to throw away samples that provide little additional information. This is referred to here as data sparsification. The first contribution is a study of a recently proposed data sparsification scheme; ideas from vector quantisation are used to assess its performance. Informed by this study, a modification of the data sparsification algorithm is proposed and applied to the problem of estimating a kernel-based measure of independence of two datasets. (Given i.i.d. observations from two random variables, x and y, the underlying problem is to determine whether or not x and y are independent of each other.) The second contribution of this paper is to make recursive an existing algorithm for measuring independence and able to operate on both raw data and on sparsified data generated by the aforementioned data sparsification algorithm. Compared with the original algorithm, the recursive algorithm is significantly faster due to its lower memory and computational requirements.
A Dual Space Representation for Geometric Data

Thie paper presents a representation echeme for polyhedral objects in arbitrary dimensions. Each object ie represented as the algebraic sum of convex polyhedra (cells). Each cell in turn ie represented ae the intereection of halfspacee and encoded in a vector. The notion of vertices is abandoned completely aa it ie not needed for the eet and eearch operators we intend to support. We ehow how thie approach allows UB to decompose set operations (such aa intersection) on polyhedral objecta into two atepe. The first step consists of a collection of vector operations; the second step is a garbage collection where vectors that represent empty celle are eliminated.