Miracle-dz/UniFAR-FTUs huggingface dataset:
High-order theta harmonics account for the detection of slow gamma

ABSTRACTLocal field potential (LFP) oscillations are the superposition of excitatory/inhibitory postsynaptic potentials. In the hippocampus, the 20-55 Hz range (‘slow gamma’) is proposed to support cognition independent of other frequencies. However, this band overlaps with theta harmonics. We aimed to dissociate the generators of slow gamma versus theta harmonics with current source density and different LFP decompositions. Hippocampal theta harmonic and slow gamma generators were not dissociable. Moreover, comparison of wavelet, ensemble empirical-mode (EEMD), and Fourier decompositions produced distinct outcomes with wavelet and EEMD failing to resolve high-order theta harmonics well defined by Fourier analysis. The varying sizes of the time-frequency atoms used by wavelet distributed the higher-order harmonics over a broader range giving the impression of a low frequency burst (“slow gamma”). The absence of detectable slow gamma refutes a multiplexed model of cognition in favor of the energy cascade hypothesis in which dependency across oscillatory frequencies exists.
Visible Spectra Conjugated Dyes: Integrating Quantum Chemical Concepts with Experimental Data

The visible spectra of the conjugated dyes pinacyanol chloride, 1-1'-diethyl-2,2'-cyanine iodide, and 1-1'-diethyl-2,2'-dicarbocyanine iodide are measured. Molar absorptivities and integrated absor.
New trends in the state‐to‐state photodissociation dynamics of H2O(Ã)

The water molecule, rotationally state selected in the third and fourth OH stretching overtone (‖04〉−, ‖05〉−) and stretch–bend combination (‖04−2〉) levels, has been photodissociated via the A state at λ≂282 nm. The photofragment rotational state distributions, determined by OH(A–X) laser induced fluorescence (LIF), differ from those reported previously by Andresen and co‐workers, in which water was initially prepared in the ‖01〉− level and photodissociated at 193 nm, and from those by Crim and co‐workers, in which H2O was photodissociated via the ‖04〉− level at wavelengths shorter than 282 nm. These differences become more pronounced with increasing angular momentum in the parent water molecule and with an increasing number of quanta in the intermediate OH stretching overtone state. The Franck–Condon theory of Balint‐Kurti, previously employed successfully to account for the product state distributions arising from the 193 nm photodissociation of H2O‖01〉−, qualitatively reproduces the trends observed in .
Nanofiltration for the Recovery of Low Molecular Weight Polysaccharides and Polyphenols from Winery Effluents

A wide range of nanofiltration membranes are investigated for the fractionation of a winery effluent and recovery of the polysaccharides of low molecular weight and of the polyphenols. Permeation experiments were carried out with three laboratory-made cellulose acetate membranes and two commercial membranes: NF270 membrane supplied by Filmtec Corp., Minneapolis, MN (USA) and ETNA01PP membrane supplied by Alfa Laval, Nakskov, Denmark. The five membranes were characterized by the rejection coefficients to a set of reference solutes and evaluated in terms of the rejection coefficients to polysaccharides, polyphenols, conductivity and total organic carbon. The rejection coefficients to polyphenols were overall lower than the ones to polysaccharides, meaning that the polyphenols permeate preferentially through all the membranes. Among these membranes, the NF270 membrane displayed the highest rejection coefficients for all parameters evaluated, with rejections in the order of 93.8% and 99% for polyphenols and polysaccharides, respectively. On the other hand, the ETNA01PP membrane presented the lowest rejection coefficients: around 27% to polyphenols and 72% to polysaccharides.
Dynamic representations of faces in the human ventral visual stream link visual features to behaviour

Humans can rapidly extract information from faces even in challenging viewing conditions, yet the neural representations supporting this ability are still not well understood. Here, we manipulated the presentation duration of backward-masked facial expressions and used magnetoencephalography (MEG) to investigate the computations underpinning rapid face processing. Multivariate analyses revealed two stages in face perception, with the ventral visual stream encoding facial features prior to facial configuration. When presentation time was reduced, the emergence of sustained featural and configural representations was delayed. Importantly, these representations explained behaviour during an expression recognition task. Together, these results describe the adaptable system linking visual features, brain and behaviour during face perception.
Exploratory neuroimmune profiling identifies CNS-specific alterations in COVID-19 patients with neurological involvement

A subset of patients with COVID-19 display neurologic symptoms but it remains unknown whether SARS-CoV-2 damages the central nervous system (CNS) directly through neuroinvasion, or if neurological symptoms are due to secondary mechanisms, including immune-mediated effects. Here, we examined the immune milieu in the CNS through the analysis of cerebrospinal fluid (CSF) and in circulation through analysis of peripheral blood mononuclear cells (PBMCs) of COVID-19 patients with neurological symptoms. Single cell sequencing with paired repertoire sequencing of PBMCs and CSF cells show evidence for unique immune response to SARS-CoV-2 in the CNS. Strikingly, anti-SARS-CoV-2 antibodies are present in the CSF of all patients studied, but the antibody epitope specificity in the CSF and relative prevalence of B cell receptor sequences markedly differed when compared to those found in paired serum. Finally, using a mouse model of SARS-CoV-2 infection, we demonstrate that localized CNS immune responses occur following viral neuroinvasion, and that the CSF is a faithful surrogate for responses occurring uniquely in the CNS. These results illuminate CNS compartment-specific immune responses to SARS-CoV-2, forming the basis for informed treatment of neurological symptoms associated with COVID-19.
Infertility due to defective sperm flagella caused by an intronic deletion in DNAH17 that perturbs splicing.

Artificial insemination in pig (Sus scrofa domesticus) breeding involves the evaluation of the semen quality of breeding boars. Ejaculates that fulfill predefined quality requirements are processed, diluted and used for inseminations. Within short time, eight Swiss Large White boars producing immotile sperm that had multiple morphological abnormalities of the sperm flagella were noticed at a semen collection center. The eight boars were inbred on a common ancestor suggesting that the novel sperm flagella defect is a recessive trait. Transmission electron microscopy cross-sections revealed that the immotile sperm had disorganized flagellar axonemes. Haplotype-based association testing involving microarray-derived genotypes at 41,094 SNPs of six affected and 100 fertile boars yielded strong association (P = 4.22 × 10-15) at chromosome 12. Autozygosity mapping enabled us to pinpoint the causal mutation on a 1.11 Mb haplotype located between 3,473,632 and 4,587,759 bp. The haplotype carries an intronic 13-bp deletion (Chr12:3,556,401-3,556,414 bp) that is compatible with recessive inheritance. The 13-bp deletion excises the polypyrimidine tract upstream exon 56 of DNAH17 (XM_021066525.1: c.8510-17_8510-5del) encoding dynein axonemal heavy chain 17. Transcriptome analysis of the testis of two affected boars revealed that the loss of the polypyrimidine tract causes exon skipping which results in the in-frame loss of 89 amino acids from DNAH17. Disruption of DNAH17 impairs the assembly of the flagellar axoneme and manifests in multiple morphological abnormalities of the sperm flagella. Direct gene testing may now be implemented to monitor the defective allele in the Swiss Large White population and prevent the frequent manifestation of a sterilizing sperm tail disorder in breeding boars.
INTERNET FINANCIAL REPORTING, PENGUNGKAPAN INFORMASI WEBSITE, LUAS LINGKUP PELAPORAN INTERNET, DAN NILAI PERUSAHAAN

Penelitian ini bertujuan untuk menguji, (1) apakah ada perbedaan nilai perusahaan antara perusahaan yang menerapkan Internet Financial Reporting (IFR) dan perusahaan yang tidak menerapkan. (2) apakah ada pengaruh tingkat pengungkapan informasi website (TPIW) dan luas lingkup pengungkapan IFR (LPI) terhadap nilai perusahaan (Q). Untuk menguji kerobasan hasil, penelitian ini menggunakan variabel kontrol yaitu ukuran perusahaan (SIZE) dan profitabilitas (ROA). Jumlah sampel yang diteliti sebanyak 184 perusahaan non keuangan yang terdaftar di BEI selama tahun 2012. Hasil penelitian menunjukkan bahwa perusahaan yang melakukan IFR terbukti memiliki nilai perusahaan yang lebih tinggi dibandingkan dengan perusahaan yang tidak melakukan. Perbedaan ini secara statistik signifikan. Penelitian ini juga mendokumentasi bahwa TPIW, LPI, dan ROA berpengaruh positif terhadap nilai perusahaan, sementara SIZE berpengaruh negatif. Temuan penelitian ini mengimplikasi bahwa perusahaan yang melakukan IFR, melakukan pengungkapan informasi lewat website yang semakin banyak, dan memiliki lingkup pengungkapan informasi website yang luas dapat menjadi sinyal positif bagi investor sehingga dapat meningkatkan nilai perusahaan.
Within-host genomics of SARS-CoV-2

Extensive global sampling and whole genome sequencing of the pandemic virus SARS-CoV-2 have enabled researchers to characterise its spread, and to identify mutations that may increase transmission or enable the virus to escape therapies or vaccines. Two important components of viral spread are how frequently variants arise within individuals, and how likely they are to be transmitted. Here, we characterise the within-host diversity of SARS-CoV-2, and the extent to which genetic diversity is transmitted, by quantifying variant frequencies in 1390 clinical samples from the UK, many from individuals in known epidemiological clusters. We show that SARS-CoV-2 infections are characterised by low levels of within-host diversity across the entire viral genome, with evidence of strong evolutionary constraint in Spike, a key target of vaccines and antibody-based therapies. Although within-host variants can be observed in multiple individuals in the same phylogenetic or epidemiological cluster, highly infectious individuals with high viral load carry only a limited repertoire of viral diversity. Most viral variants are either lost, or occasionally fixed, at the point of transmission, consistent with a narrow transmission bottleneck. These results suggest potential vaccine-escape mutations are likely to be rare in infectious individuals. Nonetheless, we identified Spike variants present in multiple individuals that may affect receptor binding or neutralisation by antibodies. Since the fitness advantage of escape mutations in highly-vaccinated populations is likely to be substantial, resulting in rapid spread if and when they do emerge, these findings underline the need for continued vigilance and monitoring.
FFAR1 and FFAR4 additively cooperate to control glucose tolerance and insulin secretion in male mice

The fatty-acid receptors FFAR1 (Gpr40) and FFAR4 (Gpr120) are implicated in the regulation of insulin secretion and insulin sensitivity, respectively. Although the properties of Gpr120 and Gpr40 converge on glucose homeostasis, few studies have addressed possible interactions between these two receptors in the control of β cell function. Here we generated mice deficient in Gpr120 or Gpr40, alone or in combination, and metabolically phenotyped male and female mice fed a normal chow or high-fat diet. We assessed insulin secretion in isolated mouse islets exposed to selective Gpr120 and Gpr40 agonists singly or in combination. Following normal chow feeding, body weight and energy intake were unaffected by deletion of either receptor, although fat mass increased in Gpr120 knockout (KO) females. Fasting blood glucose levels increased in Gpr120/40 double KO mice, and in a sex-dependent manner in Gpr120 KO and Gpr40 KO animals. Oral glucose tolerance was reduced in Gpr120/40 double KO male mice and in Gpr120 KO females, whereas insulin secretion and insulin sensitivity were unaffected. In hyperglycemic clamps, the glucose infusion rate and disposition index were lower in Gpr120/40 double KO. In contrast, we did not observe changes in glucose tolerance in either single or double KO animals under high-fat feeding. In isolated wild-type islets, the combination of selective Gpr120 and Gpr40 agonists additively increased insulin secretion compared to each agonist alone. We conclude that Gpr120 and Gpr40 cooperate in an additive manner to regulate glucose homeostasis and insulin secretion in male mice.
BERT Goes Shopping: Comparing Distributional Models for Product Representations

Word embeddings (e.g., word2vec) have been applied successfully to eCommerce products through prod2vec. Inspired by the recent performance improvements on several NLP tasks brought by contextualized embeddings, we propose to transfer BERT-like architectures to eCommerce: our model - Prod2BERT - is trained to generate representations of products through masked session modeling. Through extensive experiments over multiple shops, different tasks, and a range of design choices, we systematically compare the accuracy of Prod2BERT and prod2vec embeddings: while Prod2BERT is found to be superior in several scenarios, we highlight the importance of resources and hyperparameters in the best performing models. Finally, we provide guidelines to practitioners for training embeddings under a variety of computational and data constraints.
Speed of convergence of Chernoff approximations for two model examples: heat equation and transport equation

Paul Chernoff in 1968 proposed his approach to approximations of one-parameter operator semigroups while trying to give a rigorous mathematical meaning to Feynman's path integral formulation of quantum mechanics. In early 2000's Oleg Smolyanov noticed that Chernoff's theorem may be used to obtain approximations to solutions of initial-value problems for linear partial differential equations (LPDEs) of evolution type with variable coefficients, including parabolic equations, Schrodinger equation, and some other. Chernoff expressions are explicit formulas containing variable coefficients of LPDE and the initial condition, hence they can be used as a numerical method for solving LPDEs. However, the speed of convergence of such approximations at the present time is understudied which makes it risky to employ this class of numerical methods. In the present paper we take two equations with known solutions (heat equation and transport equation) and study both analytically and numerically the speed of decay of the norm of the difference between Chernoff approximations and exact solutions. We also provide graphical illustrations of convergence and its rate. These model examples, being relatively simple, allow to demonstrate general properties of Chernoff approximations. The observations obtained build a base for the future employment of the approach based on Chernoff's theorem to the problem of construction of new numerical methods for solving initial-value problem for parabolic LPDEs with variable coefficients.
Exploring axial symmetry in modified teleparallel gravity

Axially symmetric spacetimes play an important role in the relativistic description of rotating astrophysical objects like black holes, stars, etc. In gravitational theories that venture beyond the usual Riemannian geometry by allowing independent connection components, the notion of symmetry concerns, not just the metric, but also the connection. As discovered recently, in teleparallel geometry axial symmetry can be realised in two branches, while only one of these has a continuous spherically symmetric limit. In the current paper, we consider a very generic $f(T,B,\phi,X)$ family of teleparallel gravities, whose action depends on the torsion scalar $T$ and the boundary term $B$, as well as a scalar field $\phi$ with its the kinetic term $X$. As the field equations can be decomposed into symmetric and antisymmetric (spin connection) parts, we thoroughly analyse the antisymmetric equations and look for solutions of axial spacetimes which could be used as ans\"atze to tackle the symmetric part of the field equations. In particular, we find solutions corresponding to a generalisation of the Taub-NUT metric, and the slowly rotating Kerr spacetime. Since this work also concerns a wider issue of how to determine the spin connection in teleparallel gravity, we also show that the method of "turning off gravity" proposed in the literature, does not always produce a solution to the antisymmetric equations.
Limit of Weierstrass measure on stable curves

The goal of the paper is to study the limiting behavior of the Weierstrass measures on a smooth curve of genus $g\geqslant 2$ as the curve approaches a certain nodal stable curve represented by a point in the Deligne-Mumford compactification $\overline{\mathcal M}_g$ of the moduli $\mathcal{M}_g$, including irreducible ones or those of compact type. As a consequence, the Weierstrass measures on a stable rational curve at the boundary of $\mathcal{M}_g$ are completely determined. In the process, the asymptotic behavior of the Bergman measure is also studied.
ON FUNDAMENTAL FOURIER COEFFICIENTS OF SIEGEL CUSP FORMS OF DEGREE 2

Abstract Let F be a Siegel cusp form of degree $2$ , even weight $k \ge 2$ , and odd square-free level N. We undertake a detailed study of the analytic properties of Fourier coefficients $a(F,S)$ of F at fundamental matrices S (i.e., with $-4\det (S)$ equal to a fundamental discriminant). We prove that as S varies along the equivalence classes of fundamental matrices with $\det (S) \asymp X$ , the sequence $a(F,S)$ has at least $X^{1-\varepsilon }$ sign changes and takes at least $X^{1-\varepsilon }$ ‘large values’. Furthermore, assuming the generalized Riemann hypothesis as well as the refined Gan–Gross–Prasad conjecture, we prove the bound $\lvert a(F,S)\rvert \ll _{F, \varepsilon } \frac {\det (S)^{\frac {k}2 - \frac {1}{2}}}{ \left (\log \lvert \det (S)\rvert \right )^{\frac 18 - \varepsilon }}$ for fundamental matrices S.
Model-free and Bayesian Ensembling Model-based Deep Reinforcement Learning for Particle Accelerator Control Demonstrated on the FERMI FEL

Reinforcement learning holds tremendous promise in accelerator controls. The primary goal of this paper is to show how this approach can be utilised on an operational level on accelerator physics problems. Despite the success of model-free reinforcement learning in several domains, sample-efficiency still is a bottle-neck, which might be encompassed by model-based methods. We compare well-suited purely model-based to model-free reinforcement learning applied to the intensity optimisation on the FERMI FEL system. We find that the model-based approach demonstrates higher representational power and sample-efficiency, while the asymptotic performance of the model-free method is slightly superior. The model-based algorithm is implemented in a DYNA-style using an uncertainty aware model, and the model-free algorithm is based on tailored deep Q-learning. In both cases, the algorithms were implemented in a way, which presents increased noise robustness as omnipresent in accelerator control problems. Code is released in this https URL.
Smartphone Sensing for the Well-Being of Young Adults: A Review

Over the years, mobile phones have become versatile devices with a multitude of capabilities due to the plethora of embedded sensors that enable them to capture rich data unobtrusively. In a world where people are more conscious regarding their health and well-being, the pervasiveness of smartphones has enabled researchers to build apps that assist people to live healthier lifestyles, and to diagnose and monitor various health conditions. Motivated by the high smartphone coverage among young adults and the unique issues they face, in this review paper, we focus on studies that have used smartphone sensing for the well-being of young adults. We analyze existing work in the domain from two perspectives, namely Data Perspective and System Perspective. For both these perspectives, we propose taxonomies motivated from human science literature, which enable to identify important study areas. Furthermore, we emphasize the importance of diversity-awareness in smartphone sensing, and provide insights and future directions for researchers in ubiquitous and mobile computing, and especially to new researchers who want to understand the basics of smartphone sensing research targeting the well-being of young adults.
Rank-One Measurements of Low-Rank PSD Matrices Have Small Feasible Sets

We study the role of the constraint set in determining the solution to low-rank, positive semidefinite (PSD) matrix sensing problems. The setting we consider involves rank-one sensing matrices: In particular, given a set of rank-one projections of an approximately low-rank PSD matrix, we characterize the radius of the set of PSD matrices that satisfy the measurements. This result yields a sampling rate to guarantee singleton solution sets when the true matrix is exactly low-rank, such that the choice of the objective function or the algorithm to be used is inconsequential in its recovery. We discuss applications of this contribution and compare it to recent literature regarding implicit regularization for similar problems. We demonstrate practical implications of this result by applying conic projection methods for PSD matrix recovery without incorporating low-rank regularization.
Measuring Disentanglement: A Review of Metrics

Learning to disentangle and represent factors of variation in data is an important problem in artificial intelligence. While many advances have been made to learn these representations, it is still unclear how to quantify disentanglement. While several metrics exist, little is known on their implicit assumptions, what they truly measure, and their limits. In consequence, it is difficult to interpret results when comparing different representations. In this work, we survey supervised disentanglement metrics and thoroughly analyze them. We propose a new taxonomy in which all metrics fall into one of the three families: intervention-based, predictor-based, and information-based. We conduct extensive experiments in which we isolate properties of disentangled representations, allowing stratified comparison along several axes. From our experiment results and analysis, we provide insights on relations between disentangled representation properties. Finally, we share guidelines on how to measure disentanglement.
Who is the best coach of all time? A network-based assessment of the career performance of professional sports coaches

We consider two large datasets consisting of all games played among top-tier European soccer clubs in the last $60$ years, and among professional American basketball teams in the past $70$ years. We leverage game data to build networks of pairwise interactions between the head coaches of the teams and measure their career performance in terms of PageRank centrality. We identify Arsène Wenger, Sir Alex Ferguson, Jupp Heynckes, Carlo Ancelotti and José Mourinho as the top $5$ European soccer coaches of all time. In American basketball, the first $5$ positions of the all-time ranking are occupied by Red Auerbach, Gregg Popovich, Phil Jackson, Don Nelson and Lenny Wilkens. We further establish rankings by decade and season. We develop a simple methodology to monitor performance throughout a coach’s career, and to dynamically compare the performance of two or more coaches at a given time. The manuscript is accompanied by the website coachscore.luddy. indiana.edu where complete results of our analysis are accessible to the interested readers.