Miracle-dz/UniFAR-FTUs huggingface dataset:
Ab initio determination of the phonon deformation potentials of graphene

The elastic properties of graphene have become of renewed interest recently with the focus of research on carbon nanotubes. These tubes, being wrapped-up graphite sheets, have vibrational and elastic properties similar to those of graphite, and many analogies have been made. Experimentally, the vibrational in-plane frequencies are similar ~e.g., 1592 cm 21 for nanotubes 1 and 1580 cm 21 for graphite 2 ! , and for the purposes of calculating many physical properties to first order the effect of curvature may be neglected. 3 On the other hand, there have been ab initio calculations of the vibrational eigenfrequencies, 4 which allowed the estimate of curvature-induced effects on the frequencies, and of the phonon eigenvectors which gave substantial new insight into the actual vibrations of chiral tubes. 5 Recently, pressure-dependent Raman experiments gave rise to at first sight surprising results concerning the pressure derivatives. The low-energy radial-breathing mode around 200 cm 21 exhibited a many times larger logarithmic pressure derivative than the high-energy modes. This was understood in terms of a substantial contribution of van der Waals forces between neighboring tubes in a bundle. 6,7 The high
Schulter-Arm-Schmerzen

Schulterschmerzen gehören zu den häufigsten Gelenkbeschwerden. Da in der Schulter auf engstem Raum viele Muskeln, Bänder, Sehnen, Schleimbeutel und Knochen zusammenarbeiten, können die Beschwerden verschiedene Gründe haben. Die genaue Ursache herauszufinden, gelingt nicht immer. Die Dauer der Erkrankung liegt zwischen 3 Monaten und 1 Jahr. Die Ursachen für das Auftreten und die Dauer der Erkrankung sind vielfältig und mithilfe der ganzheitlichen Sichtweise der osteopathischen Medizin gut zu erfassen und zu behandeln. Der Erfolg ist abhängig von der Schwere der Schädigung, der Auswahl von adäquaten Behandlungsmethoden und von der Compliance des Patienten.
Statins may increase diabetes, but benefit still outweighs risk

Data have been accumulating on the risk of developing type 2 diabetes in patients receiving statins and on the potential adverse effects of these drugs on glycemic control in patients who already have type 2 diabetes. This article reviews data linking statin use and new-onset diabetes mellitus, the effects of statins on glycemic control in type 2 diabetes, the benefit-risk considerations of statin use and type 2 diabetes, and how these factors affect patient management. The weight of the evidence suggests that statin use is associated with an increased risk of new-onset diabetes mellitus, but the magnitude of the effect has varied across studies.
Song popularity prediction model based on multi-modal feature fusion and LightGBM

Since the task of hit song prediction was proposed, many experts and technicians have done a lot of research and achieved good results, but there are still some problems such as limited song feature types, lack of feature importance, and insufficient prediction accuracy. This paper proposes a song popularity prediction model based on multi-modal feature fusion and LightGBM. In our proposed model, there is a multi-modal feature extraction structure, a LightGBM structure and a logistic regression structure. First, in order to solve the problem of limited song feature types, we fuse metadata, audio features and other relevant important features into multi-modal features. Then, in order to improve the accuracy of prediction, we introduce LightGBM algorithm to preprocess the dataset and train the model, so as to obtain the predicted value of song popularity. At the same time, we introduce a logistic regression model to research the influence of each feature on whether a song is popular from the perspective of binary classification, so that we can further study the importance of song features, and obtain the response coefficient of each feature, namely, the coefficient of response mean. Finally, we compare the prediction results of our model with the existing models, and the experiments show that the prediction results of our model have higher accuracy.
LCS : Alleviating Total Cold Start Latency in Serverless Applications with LRU Warm Container Approach

Serverless computing offers "Function-as-a-Service"(FaaS), which promotes an application in the form of independent granular components called functions. FaaS goes well as a widespread standard that facilitates the development of applications in cloud-based environments. Clients can solely focus on developing applications in a serverless ecosystem, passing the overburden of resource governance to the service providers. However, FaaS platforms have to bear the degradation in performance originating from the cold starts of executables i.e. serverless functions. The cold start reflects the delay in provisioning a runtime container that processes the functions. Each serverless platform is handling the problem of cold start with its own solution. In recent times, approaches to deal with cold starts have received the attention of many researchers. This paper comes up with an extensive solution to handle the cold start problem. We propose a scheduling approach to reduce the cold start occurrences by keeping the containers alive for a longer period of time using the Least Recently Used warm Container Selection (LCS ) approach on Affinity-based scheduling. Further, we carried out an evaluation and compared the obtained results with the MRU container selection approach. The proposed LCS approach outperforms by approximately 48% compared to the MRU approach.
Efficient Task Offloading in IoT-Fog Network

Applications using AI or augmented reality which are resource hungry and cannot be computed on the end user device are sent to the cloud for processing. But cloud may not be nearer to the edge device and hence time required to execute that application is more. This paper presents a brief introduction to offloading in IoT-Fog Network. Various aspects and problems present in this area are mentioned. We also performed an analytical analysis to calculate the values quality of service parameters(QOS) for an optimal mapping.
Analysis of Determinants of Audit Report Lag on Non-Financial Companies Listed on LQ-45 Index

Audit report lag has become a phenomenon in the business world. The financial statements of public companies that want to be published to shareholders and the general public must first be audited by a public accounting firm. The delay in the audit report has an impact on the delay in the publication of financial statements which makes financial statement users hampered in making decisions. The purpose of this research is to obtain empirical evidence whether firm size, audit committee size, and audit firm status affect audit report lag. This research is conducted on non-financial companies listed on the LQ45 Index of the Indonesia Stock Exchange. Based on the purposive sampling method, a total of 20 companies are selected as research samples. The data analysis is done using Microsoft Excel and SPSS 25 software. The research result showed that audit committee size significantly affects audit report lag. Meanwhile, the results for firm size and audit firm status do not influence audit report lag.
Multi-modal Variational Auto-Encoder Model for Micro-video Popularity Prediction

Popularity prediction of micro videos on multimedia is a hotly studied topic due to the widespread use of video upload sharing services. It’s also a challenging task because popular pattern is affected by multiple factors and is hard to be modeled. The goal of this paper is to use feature extraction techniques and variation auto-encoder (VAE) framework to predict the popularity of online micro-videos. First, we identify four declarable modalities that are important for adaptability and expansibility. Then, we design a multi-modal based VAE regression model (MASSL) to exploit the domestic and foreign information extracted from heterogeneous features. The model can be applied to large-scale multimedia platforms, even the modality absence scenarios. With extensive experiments conducted on the dataset, which was originally generated from the most popular video-sharing website in China, the result demonstrates the effectiveness of our proposed model by comparing with baseline approaches.
A bayesian analysis of the multinomial model for a dichotomous response with nonrespondents

This paper studies the mu1tinomial model 2x2 contingency table data with some cell counts missing . Various hypotheses of interest including row-column independence are tested by using Bayes factors which represent the ratio of the posterior odds to the prior odds for the null hypothesis. The Dirichlet-Beta family of prior distributions is considered for the multinomial parameters cond itional on the complement of the null hypothesis. The Bayes factor for the incomplete data is a mixture of the Bayes factors for different possibilities for the full data.
Evaluation of Antidepressant Activity of Aqueous Extract of Withania Somnifera [ Aswagandha ] Roots in Albino Mice

Anti-depressants play a major role in today’s life style. There are evidences of the ayurvedic formulation withania somnifera (roots) being effective in various neuropsychiatric conditions. The antidepressant activities of aqueous extract Withania somnifera roots (AEWS) were studied using Forced swim test (FST). Effect of different doses of AEWS (30,40,50 mg/kg), Imipramine (15mg/kg)were studied on behavioural despair tests induced immobility time . WS produced dose dependent decrease in immobility time in FST, maximum effect being observed with WS 50 mg/kg. The findings support the use of WS as potential adjuvant in depressive disorders.
Distributed feedback ridge waveguide lasers fabricated by nanoscale printing and molding on nonplanar substrates

This letter describes the use of printing and molding techniques to fabricate plastic photopumped laser that use distributed feedback resonators on ridge waveguides. The results indicate (i) potential optoelectronic applications of a set of emerging low cost lithographic techniques that can pattern a range of materials with submicron resolution on nonplanar substrates, (ii) a new type of plastic laser based on molded organic gain materials, and (iii) that thresholds of plastic distributed feedback ridge waveguide lasers are similar to their planar counterparts.
Genomics of the “tumorigenes” clade of the family Rhizobiaceae and description of Rhizobium rhododendri sp. nov

Tumorigenic members of the family Rhizobiaceae, known as agrobacteria, are responsible for crown and cane gall diseases of various agricultural crops worldwide. Tumorigenic agrobacteria are commonly found in the genera Agrobacterium, Allorhizobium, and Rhizobium. In this study, we analyzed a distinct “tumorigenes” clade of the genus Rhizobium, which includes the tumorigenic species Rhizobium tumorigenes, as well as strains causing crown gall disease on rhododendron. Here, high quality, closed genomes of representatives of the “tumorigenes” clade were generated, followed by comparative genomic and phylogenomic analyses. Additionally, phenotypic characteristics of representatives of the “tumorigenes” clade were analyzed. Our results showed that the tumorigenic strains isolated from rhododendron represent a novel species of the genus Rhizobium for which the name Rhizobium rhododendri sp. nov. is proposed. This species also includes additional strains originating from blueberry and Himalayan blackberry in USA, whose genome sequences were retrieved from GenBank. Both R. tumorigenes and R. rhododendri contain multipartite genomes, including a chromosome, putative chromids, and megaplasmids. Synteny and phylogenetic analyses indicated that a large putative chromid of R. rhododendri resulted from the cointegration of an ancestral megaplasmid and two putative chromids, following its divergence from R. tumorigenes. Moreover, gene clusters specific for both species of the “tumorigenes” clade were identified, and their biological functions and roles in ecological diversification of R. rhododendri and R. tumorigenes were predicted and discussed.
Regulation of replication origin licensing by ORC phosphorylation reveals a two-step mechanism for Mcm2–7 ring closing

Eukaryotic DNA replication must occur exactly once per cell cycle to maintain cell ploidy. This outcome is ensured by temporally separating replicative helicase loading (G1 phase) and activation (S phase). In budding yeast, helicase loading is prevented outside of G1 by cyclin-dependent kinase (CDK) phosphorylation of three helicase-loading proteins: Cdc6, the Mcm2-7 helicase, and the origin recognition complex (ORC). CDK inhibition of Cdc6 and Mcm2-7 are well understood. Here we use single-molecule assays for multiple events during origin licensing to determine how CDK phosphorylation of ORC suppresses helicase loading. We find that phosphorylated ORC recruits a first Mcm2-7 to origins but prevents second Mcm2-7 recruitment. Phosphorylation of the Orc6, but not of the Orc2 subunit, increases the fraction of first Mcm2-7 recruitment events that are unsuccessful due to the rapid and simultaneous release of the helicase and its associated Cdt1 helicase-loading protein. Real-time monitoring of first Mcm2-7 ring closing reveals that either Orc2 or Orc6 phosphorylation prevents Mcm2-7 from stably encircling origin DNA. Consequently, we assessed formation of the MO complex, an intermediate that requires the closed-ring form of Mcm2-7. We found that ORC phosphorylation fully inhibits MO-complex formation and provide evidence that this event is required for stable closing of the first Mcm2-7. Our studies show that multiple steps of helicase loading are impacted by ORC phosphorylation and reveal that closing of the first Mcm2-7 ring is a two-step process started by Cdt1 release and completed by MO-complex formation. Significance Statement Each time a eukaryotic cell divides (by mitosis) it must duplicate its chromosomal DNA exactly once to ensure that one full copy is passed to each resulting cell. Both under-replication or over-replication result in genome instability and disease or cell death. A key mechanism to prevent over-replication is the temporal separation of loading of the replicative DNA helicase at origins of replication and activation of these same helicases during the cell division cycle. Here we define the mechanism by which phosphorylation of the primary DNA binding protein involved in these events inhibits helicase loading. Our studies identify multiple steps of inhibition and provide new insights into the mechanism of helicase loading in the uninhibited condition.
Covariance estimation for multidimensional data using the EM algorithm

Under a complex-Gaussian data model, a maximum likelihood method based on the iterative expectation-maximization algorithm is given to estimate structured covariance matrices for multidimensional data organized into column-vector form. The covariance structures of interest involve a hierarchy of subblocks within the covariance matrix, and include block-circulant and block Toeplitz matrices and their generalizations. These covariance matrices are elements of certain covariance constraint sets such that each element may be described as a matrix multiplication of a known matrix of Kronecker products and a nonnegative-definite, block-diagonal matrix. Several convergence properties of the estimation procedure are discussed, and an example of algorithm behavior is provided. <<ETX>>
Reduced blood to brain glucose transport as the cause for hyperglycemia in a model resolves multiple anomalies in type 2 diabetes

Classically type 2 diabetes is believed to be a result of insulin resistance and relative insulin deficiency. However, evidences have been accumulating against the insulin resistance centered models. Absence of fasting hyperglycemia by insulin receptor knockouts or insulin suppression, evidence for hyperinsulinemia preceding insulin resistance, the perplexing hyperinsulinemic normoglycemic state, reduced glucose transport to the brain preceding hyperglycemia, signs of vasculopathy preceding hyperglycemia, absent or poor correlation between fasting glucose and insulin, very strong positive correlation between indices of insulin resistance and β cell function in population data are some of the anomalous findings which glucose homeostasis models have not addressed so far. With increasing evidence for neuronal involvement in glucose regulation, we propose a refined model of glucose regulation that considers brain glucose and insulin levels as the ultimate target of homeostasis and combines central and peripheral mechanisms of regulation. A model considering reduced rate of blood to brain transportation of glucose and insulin as primary pathology explains most of the patterns, with or without insulin resistance. Apart from resolving multiple anomalies the model also accounts for the limited and inconsistent success of glucose normalization in effectively reducing diabetic complications and mortality.
Hydrogel as an advanced energy material for flexible batteries

ABSTRACT Flexible energy storage devices have risen to the top of the heap in contemporary era, by virtue of their novel characteristics such as virtuous flexibility, which allows them to maintain superior electrochemical performance even when stretched, and twisted. Synthetic polymers break down inflexibly, resulting in pollution of the environment, for this reason biodegradable hydrogels with benevolent properties are used as flexible battery materials to elucidate this issue. Herein, a hydrogel-based flexible battery, its privileges, applications, difficulties and adversities are symbolized and discussed with zeal to support the research for the rapidly evolving area. Graphical Abstract
Modeling and Learning From Variation and Covariation

We heartily thank editor Heping Zhang for according our article (McShane, Böckenholt, and Hansen 2022) discussion. We are extremely grateful for the opportunity to receive comments on our work from a set of distinguished discussants who possess a tremendous breadth and depth of knowledge and expertise, and we thank them profoundly for the great deal of time and effort they put into contemplating and responding to our article. We were delighted that De Boeck, DeKay, and Xu (2022; hereafter DDX) appreciated our contributions, namely (i) our proposal to quantify the variation and covariation in variates and effects at all levels and (ii) our multilevel multivariate modeling framework for doing so. We were gratified that they recognized that our proposal addresses not only replicability but also generalizability and integrability; found that our modeling framework was easily adapted to and proved useful for their reanalysis of the data from the second metastudy of DeKay et al. (2022); and discussed how our framework would prove useful for the analysis of the data from potential future integrative metastudies. Inspired by the discussion, we make five comments regarding modeling and learning from variation and covariation.
PHYSICAL PROPERTIES OF LARGE AND SMALL GRANULES IN SOLAR QUIET REGIONS

The normal mode observations of seven quiet regions obtained by the Hinode spacecraft are analyzed to study the physical properties of granules. An artificial intelligence technique is introduced to automatically find the spatial distribution of granules in feature spaces. In this work, we investigate the dependence of granular continuum intensity, mean Doppler velocity, and magnetic fields on granular diameter. We recognized 71,538 granules by an automatic segmentation technique and then extracted five properties: diameter, continuum intensity, Doppler velocity, and longitudinal and transverse magnetic flux density to describe the granules. To automatically explore the intrinsic structures of the granules in the five-dimensional parameter space, the X-means clustering algorithm and one-rule classifier are introduced to define the rules for classifying the granules. It is found that diameter is a dominating parameter in classifying the granules and two families of granules are derived: small granules with diameters smaller than 1. ″44, and large granules with diameters larger than 1. ″44. Based on statistical analysis of the detected granules, the following results are derived: (1) the averages of diameter, continuum intensity, and Doppler velocity in the upward direction of large granules are larger than those of small granules; (2) the averages of absolute longitudinal, transverse, and unsigned flux density of large granules are smaller than those of small granules; (3) for small granules, the average of continuum intensity increases with their diameters, while the averages of Doppler velocity, transverse, absolute longitudinal, and unsigned magnetic flux density decrease with their diameters. However, the mean properties of large granules are stable; (4) the intensity distributions of all granules and small granules do not satisfy Gaussian distribution, while that of large granules almost agrees with normal distribution with a peak at 1.04 I0.
Temperature dependence of the structural parameters of gold nanoparticles investigated with EXAFS

The ${L}_{3}$ edge of Au nanoparticles, having sizes ranging from $2.4\phantom{\rule{0.3em}{0ex}}\text{to}\phantom{\rule{0.3em}{0ex}}5.0\phantom{\rule{0.3em}{0ex}}\mathrm{nm}$, have been investigated by x-ray absorption fine structure spectroscopy in the temperature range of $20\char21{}300\phantom{\rule{0.3em}{0ex}}\mathrm{K}$. Data were recorded at the European Synchrotron Radiation Facility with a very good signal to noise ratio. To achieve a very high accuracy in the determination of the first shell distance, a very careful data analysis was performed also taking into account the presence of asymmetry effects. In all samples, the temperature dependence of the first neighbor distance results is different from that of the macrocrystalline counterpart. In the largest size samples, a reduction of the thermal expansion was found, whereas in the smallest ones, the presence of a crossover from an initial thermal expansion to a thermal contraction was observed. Calculations based on a simple model show that localization effects that increase as the nanoparticle size decreases can explain the reported thermal effects.
The XEUS hard x-ray camera

The high-energy response of XEUS will be of crucial importance for a number of astrophysical topics, e.g.: highly obscured AGNs, non-thermal emissions from SNRs, AGNs and clusters of galaxies, nuclear line emission from SNRs and hard X-ray emission in GRB afterglows. The XEUS telescope will achieve high-energy response (up to 90 keV) employing super mirror technology whereby the inner mirrors will be coated with graded multi layers. The detectors will be implemented as part of the Wide Field Imager which also has DEPFET and CCDs to cover the soft-X-ray survey science. Solutions for the associated focal plane Hard X-ray Imaging Camera have been investigated by the XEUS Instrument Working Group and will be discussed in the present contribution.