Miracle-dz/UniFAR-FTUs huggingface dataset:
Work shift duration: a review comparing eight hour and 12 hour shift systems.

OBJECTIVES: Shiftwork is now a major feature of working life across a broad range of industries. The features of the shift systems operated can impact on the wellbeing, performance, and sleep of shiftworkers. This paper reviews the current state of knowledge on one major characteristic of shift rotas-namely, shift duration. Evidence comparing the relative effects of eight hour and 12 hour shifts on fatigue and job performance, safety, sleep, and physical and psychological health are considered. At the organisational level, factors such as the mode of system implementation, attitudes towards shift rotas, sickness absence and turnover, overtime, and moonlighting are discussed. METHODS: Manual and electronic searches of the shiftwork research literature were conducted to obtain information on comparisons between eight hour and 12 hour shifts. RESULTS: The research findings are largely equivocal. The bulk of the evidence suggests few differences between eight and 12 hour shifts in the way they affect people. There may even be advantages to 12 hour shifts in terms of lower stress levels, better physical and psychological wellbeing, improved durations and quality of off duty sleep as well as improvements in family relations. On the negative side, the main concerns are fatigue and safety. It is noted that a 12 hour shift does not equate with being active for only 12 hours. CONCLUSIONS: There can be considerable extension of the person's time awake either side of the shift. However, the effects of longer term exposure to extended work days have been relatively uncharted in any systematic way. Longitudinal comparative research into the chronic impact of the compressed working week is needed.
Artemis sheds new light on V(D)J recombination

Summary: V(D)J recombination represents one of the three mechanisms that contribute to the diversity of the immune repertoire of B lymphocytes and T lymphocytes. It also constitutes a major checkpoint during the development of the immune system. Indeed, any V(D)J recombination deficiency leads to a block of B‐cell and T‐cell maturation in humans and animal models, leading to severe combined immunodeficiency (T‐B‐SCID). Nine factors have been identified so far to participate in V(D)J recombination. The discovery of Artemis, mutated in a subset of T‐B‐SCID, provided some new information regarding one of the missing V(D)J recombinase activities: hairpin opening at coding ends prior to DNA repair of the recombination activating genes 1/2‐generated DNA double‐strand break. New conditions of immune deficiency in humans are now under investigations and should lead to the identification of additional V(D)J recombination/DNA repair factors.
Prostate Cancer in a Patient with Giant Prostatic Hyperplasia: The Robotic Approach to a Difficult Problem.

The robotic approach toward radical prostatectomy for prostate cancer has only recently become widespread. Two of the advantages of the robotic approach have been described to be the optical magnification afforded by camera and the ability to reach deep into the pelvis. These advantages are particularly salient in cases where the pelvis is particularly narrow or the prostate is particularly large. In this report, we describe the management of a patient with two simultaneous prostatic diseases: prostate cancer and a massive prostate weighing 560 g causing urinary retention and hematuria, who underwent robot-assisted radical prostatectomy for prostate removal. To the best of our knowledge, this is the largest prostate to be removed through the means of robot-assisted surgery.
Determining hybrid reflectance properties and shape reconstruction by using indirect diffuse illumination method

In this paper, we propose the estimating method of reflectance properties and the recovery of shape by using Normal Sampler and Indirect Diffuse Illumination Method(IDIM). Photometric Stereo Method(PSM) is generally based on the direct illumination. PSM in this paper is modified with indirect diffuse illumination(IDI) and then applied to hybrid reflectance model which consists of two main components; Lambertian and specular reflectance. Under the indirect diffuse illumination, the reflectance properties of natural objects can be determined by using Normal Sampler that has almost all the normal components in the observed direction. The estimated reflectance properties are used to construct reference table. Also, 3-D shape of an object can be recovered from intensity distribution of a pixel and a reference table. In this paper, the reference table is used to recover the 3-D shape of an object and IDI simplifies the limited conditions of reflectance analysis for prior studies without any loss in performance. The proposed method can be applied to various types of surfaces which can be defined by hybrid reflectance.
Repair Kinetics of Genomic Interstrand DNA Cross-Links: Evidence for DNA Double-Strand Break-Dependent Activation of the Fanconi Anemia/BRCA Pathway

ABSTRACT The detailed mechanisms of DNA interstrand cross-link (ICL) repair and the involvement of the Fanconi anemia (FA)/BRCA pathway in this process are not known. Present models suggest that recognition and repair of ICL in human cells occur primarily during the S phase. Here we provide evidence for a refined model in which ICLs are recognized and are rapidly incised by ERCC1/XPF independent of DNA replication. However, the incised ICLs are then processed further and DNA double-strand breaks (DSB) form exclusively in the S phase. FA cells are fully proficient in the sensing and incision of ICL as well as in the subsequent formation of DSB, suggesting a role of the FA/BRCA pathway downstream in ICL repair. In fact, activation of FANCD2 occurs slowly after ICL treatment and correlates with the appearance of DSB in the S phase. In contrast, activation is rapid after ionizing radiation, indicating that the FA/BRCA pathway is specifically activated upon DSB formation. Furthermore, the formation of FANCD2 foci is restricted to a subpopulation of cells, which can be labeled by bromodeoxyuridine incorporation. We therefore conclude that the FA/BRCA pathway, while being dispensable for the early events in ICL repair, is activated in S-phase cells after DSB have formed.
The prevalence of complications associated with lumbar and thoracic spinal deformity surgery in the elderly population: a meta-analysis.

Background The prevalence of spinal deformities increases with age, affecting between 30% and 68% of the elderly population (ages ≥65). The reported prevalence of complications associated with surgery for spinal deformities in this population ranges between 37% and 71%. Given the wide range of reported complication rates, the decision to perform surgery remains controversial. Methods A comprehensive search was conducted using PubMed, Embase, and Cochrane to identify studies reporting complications for spinal deformity surgery in the elderly population. Pooled prevalence estimates for individual complication types were calculated using the random-effects model. Results Of 5,586 articles, 14 met inclusion criteria. Fourteen complication types were reported, with at least 2 studies for each complication with the following pooled prevalence: reoperation (prevalence 19%; 95% CI, 9-36%; 107 patients); hardware failure (11%; 95% CI, 5-25%; 52 patients); infection (7%; 95% CI, 4-12%; 262 patients); pseudarthrosis (6%; 95% CI, 3-12%; 149 patients); radiculopathy (6%; 95% CI, 1-33%; 116 patients); cardiovascular event (5%; 95% CI, 1-32%; 121 patients); neurological deficit (5%; 95% CI, 2-15%; 248 patients); deep vein thrombosis (3%; 95% CI, 1-7%; 230 patients); pulmonary embolism (3%; 95% CI, 1-7%; 210 patients); pneumonia (3%; 95% CI, 1-11%; 210 patients); cerebrovascular or stroke event (2%; 95% CI, 0-9%; 85 patients); death (2%; 95% CI, 1-9%; 113 patients); myocardial infarction (2%; 95% CI, 1-6%; 210 patients); and postoperative hemorrhage (1%; 95% CI, 0-10%; 85 patients). Conclusions Most complication types following spinal deformity surgery in the elderly had prevalence point estimates of <6%, while all were at least ≤19%. Additional studies are needed to further explore composite prevalence estimates and prevalence associated with traditional surgical approaches as compared to minimally-invasive procedures in the elderly.
FC-MAC: Fine-grained cognitive MAC for wireless video streaming

Recently, there is a massive growth in the amount of wireless video traffics. To increase the network efficiency and cater to the needs of Quality of Experience (QoE), researchers propose hybrid MAC schemes, with multiple MAC protocols anchored in a single MAC layer. Different MAC protocols are selected for diverse users' requirements. However, the existing hybrid MAC mainly combines various MAC protocols in time domain. Only one type of traffic can be satisfied at a time, and others have to endure poor QoE. Meanwhile, the channel resources are not fully utilized due to coarse usage in time domain. Motivated by this, we propose FC-MAC, a Fine-grained Cognitive MAC for video streaming in wireless networks. Instead of dividing channel time into slots, FC-MAC splits the channel frequency into fine-grained subchannels, and hybrid different MAC protocols in frequency domain. By dynamically adjusting the bandwidth and the MAC protocols according to the users' needs and channel condition, FC-MAC ensures the QoE at low cost and achieves high multiplexing gain. We conduct extensive simulations to verify the effectiveness of FC-MAC. Numerous results show that compared with time domain hybrid MAC, FC-MAC achieves 190% performance gain.
Detecting Attention Shift from Neural Response Based on Beat-frequency-modulated Musical Excerpts

This paper presents a new approach for detecting attention from auditory steady-state responses (ASSR) by using musical excerpts. The feature extraction process for electroencephalogram (EEG) signal is combined with a support vector machine as a binary discriminator. A novel modulation that emphasizes the beat timing of the excerpts has enhances the EEG response. Thanks to the beat-locked epoch extraction and additional information that signals the locked excerpt, the estimation errors are less than 8% using only ten seconds of data. Contrary to our expectations, a waveform-averaging method outperforms a harmonic filter bank and a bin-subtraction methods in the frequency domain for feature extraction. Overall, attention estimation from EEGs using musical excerpts as stimuli has been successfully achieved, which represents significant progress towards the development of a mass-EEG measurement system.
Effects of synthetic human pancreatic (tumor) GH releasing factor and somatostatin, triiodothyronine and dexamethasone on GH secretion in vitro.

The effects of synthetic human pancreatic (tumor) GH Releasing Factor, hpGRF, and a partially purified rat hypothalamic GRF, rhGRF, on secretion of GH by primary cultures of rat pituitary cells are reported to be inhibited noncompetitively by somatostatin. Dexamethasone and triiodothyronine pretreatment enhance the response to hpGRF.
JAVA SPEECH API

This document is an overview of the Java Speech API. Java Speech API is part of the Java Media APIs collection that provides an applications developer the means to implement multimedia applications. The document contains a brief introduction to speech synthesis and speech recognition in general and then proceeds to the design of the Java Speech API and its use in speech applications. The Java Speech Markup Language and Java Speech Grammar Format specifications are also covered.
Spiking Neural Networks Hardware Implementations and Challenges

Neuromorphic computing is henceforth a major research field for both academic and industrial actors. As opposed to Von Neumann machines, brain-inspired processors aim at bringing closer the memory and the computational elements to efficiently evaluate machine learning algorithms. Recently, spiking neural networks, a generation of cognitive algorithms employing computational primitives mimicking neuron and synapse operational principles, have become an important part of deep learning. They are expected to improve the computational performance and efficiency of neural networks, but they are best suited for hardware able to support their temporal dynamics. In this survey, we present the state of the art of hardware implementations of spiking neural networks and the current trends in algorithm elaboration from model selection to training mechanisms. The scope of existing solutions is extensive; we thus present the general framework and study on a case-by-case basis the relevant particularities. We describe the strategies employed to leverage the characteristics of these event-driven algorithms at the hardware level and discuss their related advantages and challenges.
Mécanismes impliqués dans le remodelage du tissu adipeux et dans l'amélioration de la lipémie par les agonistes PPAR-[gamma]

Peroxisome proliferator-activated receptor-y (PPAR-y) agonists are used clinically for the treatment of insulin résistance and type 2 diabètes. In addition to improving insulin sensitivity, thèse agonists induce profound changes in lipid metabolism. Indeed, PPAR-y agonists increase lipid accumulation in subcutaneous fat and reduce lipid déposition in viscéral fat. Concomitantly with thèse changes, PPAR-y agonism reduces circulating triglycérides (TG) and non-esterified free fatty acids (NEFA). The précise mechanisms involved in thèse effects are not known. The work presented in this thesis shows in rats that PPAR-y agonism increases lipid accumulation in subcutaneous fat by increasing adipocyte differentiation and the expression/activity of déterminants of lipid uptake and rétention. In viscéral fat, thèse déterminants were not strongly affected by the treatment. In this tissue, energy dissipation and lipid oxidation were preferentially increased, contributing to reduce fat accretion in viscéral dépôts. We show hère that PPAR-y agonists increased lipoprotein lipase (LPL) activity especially in subcutaneous and in brown adipose tissues and that this effect was strongly associated with the stimulation of fat accretion in thèse dépôts and with the réduction in circulating TG. This work underlies the major rôle of brown adipose tissue in the hypolipidemic effect of PPAR-y agonism in rodents. Although adipose tissue LPL is important for the réduction in circulating TG in PPAR-y agonist-treated animais, some observations indicate that LPL is not essential in this effect. In mice lacking LPL in fat and muscles, the stimulation of NEFA uptake and rétention in adipose tissue reduced lipid accumulation in the liver, TG sécrétion potential and triglyceridemia. The improvement of insulin's anti-lipolytic action and the stimulation of the expression of gènes involved in fatty acid esterification and recycling contributed to reduce circulating NEFA. This effect occurred even if PPAR-y agonism strongly increased the expression of the lipases involved in TG breakdown in adipose tissue.
Stein's method for comparison of univariate distributions

We propose a new general version of Stein's method for univariate distributions. In particular we propose a canonical definition of the Stein operator of a probability distribution {which is based on a linear difference or differential-type operator}. The resulting Stein identity highlights the unifying theme behind the literature on Stein's method (both for continuous and discrete distributions). Viewing the Stein operator as an operator acting on pairs of functions, we provide an extensive toolkit for distributional comparisons. Several abstract approximation theorems are provided. Our approach is illustrated for comparison of several pairs of distributions : normal vs normal, sums of independent Rademacher vs normal, normal vs Student, and maximum of random variables vs exponential, Frechet and Gumbel.
Dynamic User Modeling in a Web Store Shell

We describe a framework for the dynamic revision of user models in an adaptive Web store shell, which tailors the suggestion of goods, as well as the interaction style, to the characteristics and interests of the individual user. The behavior of the user is unobtrusively monitored, by segmenting it on the basis of the focus spaces explored in the browsing activity, and the actions performed by the user are summarized into abstract facts. These facts are used for revising the user model via the interpretation process performed by a Bayesian Network which relates user features to user behavior.
A survey of shadow algorithms

The various types of shadows are characterized. Most existing shadow algorithms are described, and their complexities, advantages, and shortcomings are discussed. Hard shadows, soft shadows, shadows of transparent objects, and shadows for complex modeling primitives are considered. For each type, shadow algorithms within various rendering techniques are examined. The aim is to provide readers with enough background and insight on the various methods to allow them to choose the algorithm best suited to their needs and to help identify the areas that need more research and point to possible solutions. <<ETX>>
A Survey of Deep Learning for Sentiment Analysis

—Deep learning has detonated in the public responsiveness, primarily as predictive and analytical products pervade our world, in the form of innumerable human-centered smart-world systems, including targeted advertisements, natural language assistants and interpreters, and mock-up self-driving vehicle systems. In contrast, researchers across disciplines have been including into their research to solve various natural language processing issues. In this paper we seek to provide a thorough exploration of Deep learning and its applications like sentimental analysis and natural language processing (NLP). Deep learning has an edge over the traditional machine learning algorithms, like support vector machine (SVM) and Naïve Bayes, for sentiment analysis because of its potential to overcome the challenges faced by sentiment analysis and handle the diversities involved, without the expensive demand for manual feature engineering. Deep learning models promise one thing - given sufficient amount of data and sufficient amount of training time, they can perform the task of sentiment classification on any text class with minimal restrictions and no task-specific or data-specific manual feature engineering. We hope this survey provides a valuable reference for new Deep learning practitioners, as well as those seeking to innovate in the application of deep learning.
The Cln3 cyclin is down‐regulated by translational repression and degradation during the G1 arrest caused by nitrogen deprivation in budding yeast

Nutrients are among the most important trophic factors in all organisms. When deprived of essential nutrients, yeast cells use accumulated reserves to complete the current cycle and arrest in the following G1 phase. We show here that the Cln3 cyclin, which has a key role in the timely activation of SBF (Swi4–Swi6)‐ and MBF (Mbp1–Swi6)‐dependent promoters in late G1, is down‐regulated rapidly at a post‐transcriptional level in cells deprived of the nitrogen source. In addition to the fact that Cln3 is degraded faster by ubiquitin‐dependent mechanisms, we have found that translation of the CLN3 mRNA is repressed ∼8‐fold under nitrogen deprivation conditions. As a consequence, both SBF‐ and MBF‐dependent expression is strongly down‐regulated. Mainly because of their transcriptional dependence on SBF, and perhaps with the contribution of similar post‐transcriptional mechanisms to those found for Cln3, the G1 cyclins Cln1 and 2 become undetectable in starved cells. The complete loss of Cln cyclins and the sustained presence of the Clb–cyclin kinase inhibitor Sic1 in starved cells may provide the molecular basis for the G1 arrest caused by nitrogen deprivation.
Unidirectional and diffractionless surface plasmon polaritons on three-dimensional nonreciprocal plasmonic platforms

Light-matter interactions in conventional nanophotonic structures typically lack directionality. For example, different from microwave antenna systems, most optical emitters (excited atoms/molecules, quantum dots) exhibit quasi-isotropic dipolar radiation patterns with low directivity. Furthermore, surface waves supported by conventional material substrates do not usually have a preferential direction of propagation, and their wavefront tends to spread as it propagates along the surface, unless the surface or the excitation are properly engineered. In this article, we theoretically demonstrate the possibility of realizing truly unidirectional excitation and propagation of surface-plasmon-polariton modes on a nonreciprocal platform, namely, a gyrotropic magnetized plasma. Based on a Green function approach, we provide a comprehensive and systematic analysis of all the available physical mechanisms that may bestow the system with directionality, both in the sense of one-way excitation of surface waves, and directive diffractionless propagation. The considered mechanisms include the effect of strong and weak forms of nonreciprocity, the elliptic-like or hyperbolic-like topology of the modal dispersion surfaces, and the source polarization state, with the associated possibility of chiral surface-wave excitation governed by angular-momentum matching. By suitably combining all these mechanisms, we theoretically demonstrate, for the first time, truly unidirectional surface-plasmon-polariton modes, propagating as a single ultra-narrow diffractionless beam on a three-dimensional plasmonic platform. Our theoretical findings may enable a new generation of nanophotonic structures and devices with highly directional response, with important practical implications for sub-diffractive nano-optical interconnects, super-resolution imaging, and enhanced classical and quantum light-matter interactions.
Alternative Energy Vehicles Drive System: Control, Flux and Torque Estimation, and Efficiency Optimization

Indirect field-oriented control, direct field-oriented control, and direct torque control are the most widely used instantaneous torque control techniques for the drive system of alternative energy vehicles (AEVs). This paper evaluates three candidate alternating-current machines and investigates the suitability of different control techniques for the drive systems of battery-powered electric vehicles, hybrid electric vehicles, and integrated starter alternators. Accurate flux and torque estimation is the core of any opted control technique for all types of AEV drive systems. Therefore, an accurate closed-loop voltage model flux and torque estimator that is insensitive to stator resistance variation has been designed. This paper also analyzes loss model control and search control (SC) techniques for the drive system's efficiency optimization and proposes an offline SC efficiency optimization technique. Experimental results are presented to demonstrate the performance of the proposed flux and torque estimator and efficiency optimizer.
Spoken language translation using automatically transcribed text in training

In spoken language translation a machine translation system takes speech as input and translates it into another language. A standard machine translation system is trained on written language data and expects written language as input. In this paper we propose an approach to close the gap between the output of automatic speech recognition and the input of machine translation by training the translation system on automatically transcribed speech. In our experiments we show improvements of up to 0.9 BLEU points on the IWSLT 2012 English-to-French speech translation task.