Miracle-dz/UniFAR-FTUs huggingface dataset:
The importance of experience replay database composition in deep reinforcement learning

Recent years have seen a growing interest in the use of deep neural networks as function approximators in reinforcement learning. This paper investigates the potential of the Deep Deterministic Policy Gradient method for a robot control problem both in simulation and in a real setup. The importance of the size and composition of the experience replay database is investigated and some requirements on the distribution over the state-action space of the experiences in the database are identified. Of particular interest is the importance of negative experiences that are not close to an optimal policy. It is shown how training with samples that are insufficiently spread over the state-action space can cause the method to fail, and how maintaining the distribution over the state-action space of the samples in the experience database can greatly benefit learning.
On the Spectral Efficiency of Noncoherent Doubly Selective Channels

This paper considers block transmissions over single-antenna doubly selective channels that obey a compl exexponential basis expansion model. We consider the noncohe rent case, when the channel fading coefficients are not known at bo th transmitter and receiver. We characterize the spectral efficiency of the channel when the inputs are chosen from continuous distributions. Then, we study several pilot aided transmisions (PAT) over the doubly selective channels. We establish that all the PAT schemes designed to minimize the channel estimation error variance are spectrally inefficient. We also design no vel spectrally efficient PAT schemes.
Ionospheric D region remote sensing using VLF radio atmospherics

Lightning discharges radiate the bulk of their electromagnetic energy in the very low frequency (VLF, 3–30 kHz) and extremely low frequency (ELF, 3–3000 Hz) bands. This energy, contained in impulse‐like signals called radio atmospherics or sferics, is guided for long distances by multiple reflections from the ground and lower ionosphere. This suggests that observed sferic waveforms radiated from lightning and received at long distances (>1000 km) from the source stroke contain information about the state of the ionosphere along the propagation path. The focus of this work is on the extraction of nighttime D region electron densities (in the altitude range of ∼70–95 km) from observed VLF sferics. In order to accurately interpret observed sferic characteristics, we develop a model of sferic propagation which is based on an existing frequency domain subionospheric VLF propagation code. The model shows that the spectral characteristics of VLF sferics depend primarily on the propagation path averaged ionospheric D region electron density profile, covering the range of electron densities from ∼100 to 103 cm−3. To infer the D region density from observed VLF sferics, we find the electron density profile that produces a modeled sferic spectrum that most closely matches an observed sferic spectrum. In most nighttime cases the quality of the agreement and the uncertainties involved allow the height of an exponentially varying electron density profile to be inferred with a precision of ∼0.2 km.
Correlation functions of twist operators applied to single self-avoiding loops

The O(n) spin model in two dimensions may equivalently be formulated as a loop model, and then mapped to a height model which is conjectured to flow under the renormalization group to a conformal field theory (CFT). At the critical point, the order n terms in the partition function and correlation functions describe single self-avoiding loops. We investigate the ensemble of these self-avoiding loops using twist operators, which count loops which wind non-trivially around them with a factor −1. These turn out to have level 2 null states and hence their correlators satisfy a set of partial differential equations. We show that partly connected parts of the four-point function count the expected number of loops which separate one pair of points from the other pair, and find an explicit expression for this. We argue that the differential equation satisfied by these expectation values should have an interpretation in terms of a stochastic(Schramm)–Loewner evolution (SLEκ) process with κ = 6. The two-point function in a simply connected domain satisfies a closely related set of equations. We solve these and hence calculate the expected number of single loops which separate both points from the boundary.
Involvement of CX3CL1/CX3CR1 axis in etanercept therapy for patients with active rheumatoid arthritis

Objective To examine the relationship between serum chemokine levels and patient responsiveness in rheumatoid arthritis (RA) patients to etanercept (ETN) and the influence of ETN administration on serum chemokine levels. Methods Serum levels of the chemokines CX3CL1, CXCL8, CXCL10, and CCL3 were quantified prior to (at baseline) and after 14 weeks of treatment with ETN in 20 patients using enzyme-linked immunosorbent assay. Disease status was assessed using the Disease Activity Score (DAS28). The response to ETN was classified according to the European League Against Rheumatism (EULAR) response criteria. Results By 14 weeks, ETN produced a significant overall reduction in DAS28 among the 20 patients with RA; eight patients achieved a good response, and 10 patients achieved a moderate response based on EULAR response criteria. A significant reduction in CX3CL1 was observed in the responsive group, although ETN treatment had no significant effect on the serum levels of the other three chemokines. In addition, the messenger ribonucleic acid expression of CX3CR1 in peripheral blood mononuclear cells and the cell-surface expression of CX3CR1 protein in peripheral blood CD8+CD3+ T cells were both decreased after ETN treatment. Conclusions Our results suggest that the CX3CL1 and CX3CR1 in patients with active RA may be sensitive to antitumor necrosis factor-α therapy and confirm that CX3CL1/CX3CR1 axis plays a crucial role in the pathogenesis of RA.
Childhood trauma and adolescent mental health: A transdisciplinary approach for social work research and practice

Purpose. This study examines the prevalence of trauma subtypes, polytraumatization, and perinatal depression in a diverse sample of adolescent mothers to help inform perinatal depression prevention, screening, and treatment efforts. Methods. We conducted a secondary analysis of a convenience sample of adolescent mothers (N=210) from a prospective longitudinal study of perinatal depression. Participants were recruited from a county-based, public health prenatal clinic and data was collected in the prenatal and postpartum periods. Results. In this sample, 81% of adolescent mothers reported at least one trauma experience; 75% reported lifetime experience of IPV. The most prevalent trauma types among adolescent mothers reporting perinatal depression were sexual trauma (11.4%), childhood loss (28.3%), emotional adversity (17.1%), and polytraumatization (43%). Conclusions. Trauma is alarmingly prevalent among adolescent mothers. Results suggest standards of care for adolescent mothers should include screening adolescent mothers for trauma history and provision of appropriate referrals for IPV. Findings support the need for trauma-informed treatment in perinatal public health clinics to decrease potential health risks to both mother and baby.
Functional Verification of RTL Designs driven by Mutation Testing metrics

The level of confidence in a VHDL description directly depends on the quality of its verification. This quality can be evaluated by mutation-based test, but the improvement of this quality requires tremendous efforts. In this paper, we propose a new approach that both qualifies and improves the functional verification process. First, we qualify test cases thanks to the mutation testing metrics: faults are injected in the design under verification (DUV) (making DUV's mutants) to check the capacity of test cases to detect theses mutants. Then, a heuristic is used to automatically improve IPs validation data. Experimental results obtained on RTL descriptions from ITC'99 benchmark show how efficient is our approach.
Information Sharing in a Supply Chain with a Common Retailer

We study the problem of information sharing in a supply chain with two competing manufacturers selling substitutable products through a common retailer. Our analysis shows that the retailer’s incentive to share information strongly depends on nonlinear production cost, competition intensity, and whether the retailer can offer a contract to charge a payment for the information. Without information contracting, the retailer has an incentive to share information for free when production economy is large but has no incentive to do so when there is production diseconomy. With information contracting, the retailer has an incentive to share information when either production diseconomy/economy is large or competition is intense. We characterize the conditions under which the retailer shares information with none, one, or both of the manufacturers. We also show that the retailer prefers to sell information sequentially rather than concurrently to the manufacturers, whereas the manufacturers’ preferences are reversed. This paper was accepted by Yossi Aviv, operations management.
An Adaptive Approach to Learn Overcomplete Dictionaries With Efficient Numbers of Elements

Dictionary learning for sparse representation has recently attracted attention among the signal processing society in a variety of applications such as denoising, classification, and compression. The number of elements in a learned dictionary is crucial since it governs specificity and optimality of sparse representation. Sparsity level, number of dictionary elements, and representation error are three correlated factors in which setting each pair of them results in a specific value of the third factor. An arbitrary selection of the number of dictionary elements affects either the sparsity level or/and the representation error. Despite recent advancements in training dictionaries, the number of dictionary elements is still heuristically set. To avoid the representation's suboptimality, a systematic approach to adapt the elements' number based on input datasets is essential. Some existing methods try to address this requirement such as enhanced K-SVD, sub-clustering K-SVD, and stage-wise K-SVD. However, it is not specified under which sparsity level and representation error criteria their learned dictionaries are size-optimized. We propose a new dictionary learning approach that automatically learns a dictionary with an efficient number of elements that provides both desired representation error and desired average sparsity level. In our proposed method, for any given representation error and average sparsity level, the number of elements in the learned dictionary varies based on content complexity of training datasets. The performance of the proposed method is demonstrated in image denoising. The proposed method is compared to state-of-the-art, and results confirm the superiority of the proposed approach.
A qualitative exploration into how male students with mental health problems experience stigma

"This study explored how male students with mental health problems experience stigma. An all-male sample was selected as previous literature has revealed their frequent inability to consult mental health services (Lindsey et al, 2010), their negative attitudes towards help- seeking behaviours (Chandra & Minkovitz, 2006), and their abundance of self-stigma endorsement (Judd et al, 2008). It is therefore suggested that males are the gender group that are the most affected by mental health stigma; this makes their personal experiences with stigma an important area to further explore. An awareness and understanding of these experiences may be key to stigma reduction for one of its most affected groups. Qualitative methods were employed within the research. Five male student’s experiences were explored utilising semi-structured interviews as the method of data collection, a thematic analysis was performed to analyse the data. This produced four overarching themes: 1) feelings of separation from society 2) self-stigmatising effects 3) gender identities 4) stigma experienced from society Each of the overarching themes allowed for insight into how the male students experience stigma, the most prominent theme that emerged across the data was gender identities. It is suggested that being male, and furthermore ideas about masculinity, have negative effects for males with mental health problems. The current study suggests this intensifies their experiences with stigma, and as a result, curative measures are suggested. "
Selective Coding Strategy for composite relay channels

Consider the composite relay channel (CRC) where the channel is randomly drawn from a set of conditional distributions with index θ ϵ Θ, which represents the vector of channel parameters. The specific draw θ is assumed to be unknown at the source, fully known at the destination and only partly known at the relay. In this setting, the coding would commonly be chosen regardless of the channel measurement at the relay end. This work introduces a novel coding which enables the relay to select-based on its channel measurement - the best coding strategy between Compress-and-Forward (CF) and Decode-and-Forward (DF). Indeed, provided that the channel source-to-relay is good enough for decoding the message, the relay decides on DF and otherwise it may switch to CF. The proposed Selective Coding Strategy (SCS) is based on superposition coding, DF and CF schemes, backward and joint decoding. We derive bounds on the asymptotic average error probability of the memoryless CRC. An application example to the fading Gaussian CRC is also investigated.
Praktis kepimpinan distributif dan komitmen terhadap organisasi berdasarkan kohort generasi guru

Praktis kepimpinan distributif merupakan keperluan dalam sistem pendidikan, kerana guru dan pemimpin sekolah dapat mewujudkan kerjasama dan interaksi bagi meningkatkan pencapaian pelajar. Kajian mengenai kepimpinan distibutif ini masih lagi di peringkat awal dan perlu diperbanyakkan. Kajian ini bertujuan untuk mengenal pasti hubungan antara kepimpinan distributif dengan komitmen guru berdasarkan kohort generasi di sekolah menengah kebangsaan. Kajian ini menggunakan seramai 298 responden yang terdiri daripada guru dan menggunakan pendekatan kuantitatif berbentuk tinjauan keratan rentas. Kajian ini telah menggunakan kerangka teoritikal kepimpinan distributif Spillane (2006) yang telah menghubungkan interaksi antara pemimpin, pengikut dan juga situasi. Kajian ini menggunakan instrumen Distributed Leadership Survey (DLS) oleh Davis (2009), dan juga instrumen Affective, Continuance and Normative Commitment Scales (ACNCS) yang telah dibangunkan oleh Meyer dan Allen (1997). Pemilihan responden adalah berdasarkan kepada pensampelan rawak berstrata tidak mengikut kadar dan juga persampelan bertujuan. Sebanyak tiga hipotesis telah dibina dan diuji dengan menggunakan kaedah statistik ujian korelasi Pearson, ujian-t sampel bebas dan ujian ANOVA menerusi SPSS versi 21. Dapatan kajian menunjukkan terdapat hubungan yang signifikan antara kepimpinan distributif dan komitmen guru terhadap organisasi. Dimensi kepimpinan pengetua dan dimensi visi sekolah didapati sangat kerap dipraktiskan di dalam kajian ini. Bagi komitmen terhadap organisasi, didapati dimensi komitmen normatif adalah yang paling tinggi. Tiada perbezaan yang signifikan dalam kepimpinan distributif dengan komitmen guru berdasarkan kohort generasi dan juga jantina guru. Berdasarkan kepada dapatan kajian ini, adalah dicadangkan agar pemimpin sekolah dapat menyebarluaskan kepimpinan kepada guru di samping berkongsi visi sekolah yang jelas dan mudah difahami oleh warga sekolah, tanpa mengira jantina dan kohort generasi.
Impact of Host IL28B rs12979860, rs8099917 in Interferon Responsiveness and Advanced Liver Disease in Chronic Genotype 3 Hepatitis C Patients

Background and Aims Genetic polymorphisms near interleukin 28B gene are associated with spontaneous and treatment induced clearance of hepatitis C virus (HCV). Our objective was to evaluate the impact of interleukin 28B single nucleotide polymorphism (rs12979860, rs8099917) variability in HCV genotype 3 infected populations. Methods 400 hepatitis C seroreactive patients from different population groups in Eastern and North Eastern part of India were assessed for host and viral genotypic analysis. 83 HCV genotype 3 infected patients were administered pegylated interferon- ribavirin therapy. Viral genotyping was performed using nested reverse transcriptase-PCR followed by direct sequencing methods. Host interleukin 28B genotyping was performed using real-time PCR based single nucleotide polymorphism analysis. Results Out of 400 hepatitis C seroreactive individuals, 73.25% were found to be RNA positive. HCV genotype 3 (65.87%) was found to be the major circulating strain in this region followed by genotype 1 (32.08%). rs12979860 CC genotype was significantly associated with sustained virological response in HCV genotype 3 infected population. In patients achieving rapid virological response, favourable CC/TT allele at rs12979860, rs8099917 was found to be predominant at both the alleles at 77%, 73.2% respectively; whereas in case of patients with relapsed HCV infection CT, TG alleles were found to be predominant. Additionally, CC genotypes at rs12979860 were found to be associated with sustained virological response in patients with high viral load (OR = 6.75, 0.05<p). HCV unfavourable rs12979860 TT, rs8099917 GG alleles were present in 34%, 27.6% patients with relapsed HCV infection respectively. Also unfavourable CT, TG genotypes were found to be predominant in patients with advanced stages of liver disease. Conclusion CC, TT the two favourable markers at SNPs rs12979860 and rs8099917 are strongly associated with sustained virological response in genotype 3 infected populations. This information will aid clinicians to effectively design response based treatment regimen.
Differentiating between patients with vasovagal syncope using the analysis of heart rate variability during head-up tilt test

The aim of this paper is to improve the physiological understanding in order to differentiate between the two types of vasovagal syncope by performing a Head-up Tilt Test. The Head-up Tilt Test is a well known procedure to reproduce vasovagal syncope, patients who had syncope during the test show different orthostatic response depending on they are cardioinhibitory or vasodepressor patients which can be explain by different pathogeneses, although existing knowledge of the autonomic balance in patients with positive response is still not completely clear. The Electrocardiogram signal from 20 patients, 12 cardioinhibitory and 8 vasodepressor were analyzed with the validated software Segmenta (Laboratory of Signal and Image Processing, Rennes) to extract classical heart rate variability parameters then comparison were made within and between group for 5 minutes of resting, the first 5 minutes of the tilt test and the last 5 minutes before syncope. The Results show that Cardioinhibitory patients had higher low frequency parameter in the last 5 minutes before syncope than vasodepressor patients (p<;0.05), using Principal Component Analysis, differentiating between cardioinhibitor and vasodepressor group can be done in the 5 minutes of resting and the last 5 minutes before syncope. This study suggests a lack of sympatho-vagal balance activation in subjects with vasovagal syncope which can be explained by attenuation in cardiac rhythm regulation and predominance sympathetic activity for cardioinhibitory patients. In addition we demonstrated that by using one parameter (Low Frequency), we can distinguish between the two types before five minutes of syncope but by a combination of multiple parameters using principal component analysis we can differentiate the two groups from the five minutes of supine position.
Separation of Singing Voice Using Nonnegative Matrix Partial Co-Factorization for Singer Identification

In order to improve the performance of singer identification, we propose a system to separate singing voice from music accompaniment for monaural recordings. Our system consists of two key stages. The first stage exploits the nonnegative matrix partial co-factorization (NMPCF), which is a joint matrix decomposition integrating prior knowledge of singing voice and pure accompaniment to separate the mixture signal into singing voice portion and accompaniment portion. In the second stage, based on the separated singing voice obtained by the first stage, the pitches of singing voice are first estimated and then the harmonic components of singing voice can be distinguished. For a frame, the distinguished harmonic components are regarded as reliable while other frequency components unreliable, thus the spectrum is incomplete. With those harmonic components, the complete spectrums of singing voice can be reconstructed by a missing feature method, spectrum reconstruction, obtaining a refined signal with more clean singing voice. Experimental results demonstrate that, from the point view of source separation, the singing voice refinement can further improve ΔSNR in contrast with the singing voice separation using NMPCF, while for the point view of singer identification, the singing voice separated by NMPCF is more appropriate than the refined singing voice.
Conformally invariant powers of the Laplacian — A complete nonexistence theorem

Conformally invariant operators and the equations they determine play a central role in the study of manifolds with pseudo-Riemannian, Riemannian, conformai and related structures. This observation dates back to at least the very early part of the last century when it was shown that the equations of massless particles on curved space-time exhibit conformai invariance. In this setting a key operator is the con formally invariant wave operator which has leading term a pseudo-Laplacian. The Riemannian signature variant of this operator is a fundamental tool in the Yam abe problem on compact manifolds. Here one seeks to find a metric, from a given conformai class, that has constant scalar curvature. Recently it has become clear that higher order analogues of these operators, viz., conformally invariant operators on weighted functions (i.e., conformai densities) with leading term a power of the Laplacian, have a central role in generating and solving other curvature prescription problems as well as other problems in geometric spectral theory and mathematical physics [2, 5, 15]. In the flat setting, the existence of such operators dates back to [16], where it is shown that, on 4-dimensional Minkowski space, for k G N = {1,2,. }, the kth power of the flat wave operator Ak, acting on densities of the appropriate weight, is invariant under the action of the conformai group. More generally, if ? [w] denotes the space of conformai densities of weight uiGl, then on a flat conformai manifold of dimension n > 3 (and any signature) there exists, for each k E N, a unique conformally invariant operator