Miracle-dz/UniFAR-FTUs huggingface dataset:
Nodal and extranodal peripheral T/NK-cell neoplasms: Current aspects

Peripheral T/NK–cell lymphomas (PTCL) are rare, bizarre, and extremely diverse cancers. The disease is prone to relapse with a high level of chemorefractoriness leading to a poor outcome. Almost 70% of patients will experience relapse, with a median 5–year overall survival (OS) in approximately 30%. Upfront management of PTCL has been extrapolated from the treatment paradigm for aggressive B–NHL. However, universally accepted induction is rather palliative than curative. Regardless of the maximal reinforcement of upfront management, only event-free survival has been influenced but not the OS. All actual guidelines emphasize the importance of the autologous stem cell transplantation (auto–SCT) as a consolidation of first major response. The allogeneic SCT (allo–SCT) is not evidence–based part of upfront management. Nevertheless, its use is justified in the relapsed/refractory setting. Unfortunately, the vast majority of patients are not candidates for aggressive treatment modalities making the recommended paradigm as limited feasible. Regarding such a situation, novel compounds are warranted. Although presented data indicate ominous prognosis in PTCL, it is important to denote that there has been evidence – based improvement in the treatment paradigm by the introduction of L–Asparaginase and targeted therapy for CD30+ PTCL. In this sense, a considerable number of new compounds entered early phase trials and gave promising results. All lights have been focused on upcoming results given the fact that at the moment we have not much to offer to the patients who have relapsed or were primary refractory.
Training a Quantum Neural Network to Solve the Contextual Multi-Armed Bandit Problem

Artificial intelligence has permeated all aspects of our lives today. However, to make AI behave like real AI, the critical bottleneck lies in the speed of computing. Quantum computers employ the peculiar and unique properties of quantum states such as superposition, entanglement, and interference to process information in ways that classical computers cannot. As a new paradigm of computation, quantum computers are capable of performing tasks intractable for classical processors, thus providing a quantum leap in AI research and making the development of real AI a possibility. In this regard, quantum machine learning not only enhances the classical machine learning approach but more importantly it provides an avenue to explore new machine learning models that have no classical counterparts. The qubit-based quantum computers cannot naturally represent the continuous variables commonly used in machine learning, since the measurement outputs of qubit-based circuits are generally discrete. Therefore, a continuous-variable (CV) quantum architecture based on a photonic quantum computing model is selected for our study. In this work, we employ machine learning and optimization to create photonic quantum circuits that can solve the contextual multi-armed bandit problem, a problem in the domain of reinforcement learning, which demonstrates that quantum reinforcement learning algorithms can be learned by a quantum device.
Deep Transfer Learning with Apache Spark to Detect COVID-19 in chest X-ray Images

A chest X-ray test is one of the most important and recurrent medical imaging examinations It is the first imaging technique that represents a significant role in the diagnosis of SARS-CoV-2 disease Automatic classification of 2019-nCoV using X-ray images is a major request that can help doctors to make the best decisions In this paper, we adopted, developed, and validated a Deep Transfer Learning (DTL) method using Convolutional Neural Network (CNN) based models InceptionV3 and ResNet50 with Apache Spark framework for the classification of COVID-19 in chest X-ray images collected from Kaggle repository High accuracy was obtained by our model in the detection of COVID-19 X-ray images 99 01% by the pre-trained InceptionV3 model and 98 03% for the ResNet50 model
Biodiversity of phytoplankton cyst assemblages in surface sediments of the Black Sea based on metabarcoding

Abstract Resting stages are common for the life cycle of some phytoplankton species, including blooming and potentially toxic species. The “seed bank” accumulated in the sediments can initiate blooms in the water column and could be an early warning signal of harmful algal blooms (HABs). In order to identify the phytoplankton cyst assemblages, thirteen surface sediment samples were collected from different sites in the Black Sea. The diversity of the resting stages was assessed using high-throughput sequencing metabarcoding (V7-9 hypervariable region of the 18S rDNA). One hundred and eighty microalgal species were identified with high level of similarity to the reference sequences. Dinoflagellates were dominated by Biecheleria, Gymnodinium and Karlodinium. Within diatoms, Skeletonema, Chaetoceros and Thalassiosira were the most abundant genera. Sixteen of the detected operational taxonomic units (OTUs) were assigned to harmful microalgae (12 dinoflagellates species, 1 diatom, 1 haptophyte and 2 raphidophytes). No pattern of microalgal sequences depth distribution was discriminated. The results show that DNA metabarcoding has a great potential for assessment of the phytoplankton diversity in environmental sediments.
Is PISA more important to school reforms than educational research? The selective use of authoritative references in media and in parliamentary debates

ABSTRACT Two separate data searches underlie this analysis of how references to educational research and to PISA are used in the Swedish education debate. The data consist of 380 newspaper articles from the eight largest print media outlets in Sweden and 200 protocols from parliamentary debates (2000 to 2016) that made explicit reference to ‘PISA’ and/or to ‘educational research’. Based on a content analysis of this material, in which notions of policy borrowing and de-/legitimization are central, we describe the result as a selective use of PISA data and of educational research in the education debate. PISA is used to legitimize selective (party political) solutions that are oriented towards problems of teaching. The analysis also shows that politics and the media debate concerning education seems disinterested in educational research in a broader sense and that PISA seems to offer sufficient and ‘neutral’ authoritative knowledge and support for policy and reforms. We argue that PISA is the first way to obtain legitimate support for educational reforms. In so doing, the kinds of problems that these reforms aim to solve have been narrowed down to teaching- or practice-oriented problems.
The Acceptability of Telemedicine Cabins by the Students

Telemedicine solutions are invading our daily lives, raising a major issue concerning the personalization of remote consultation and trust in the physician's Competence, Integrity and Benevolence (Trusting Beliefs). The aim of this study is to extend the existing Technology-Acceptance-Model (TAM) using the concept of Trusting Beliefs and Perceived Personalization. To test the model, a quantitative approach using existing scales has been selected. A survey was administered to students from several French business schools and the sample of 158 students was analysed using a Partial Least Approach. Findings highlight the key role of Trusting Beliefs in Perceived-Personalization. While two of the three dimensions (Benevolence and Integrity) of Trusting Beliefs theory have no influence on the Intention-to-Use, Competence has a direct, positive and significant impact on Intention-to-Use a Telemedicine Cabin. The relationship between the variables of the TAM is validated, except for Perceived-Ease-of-Use, which does not impact the Intention-to-Use a Telemedicine cabin.
Data-Driven Simulation Modeling of the Checkout Process in Supermarkets: Insights for Decision Support in Retail Operations

We build a realistic agent-based model for simulating customer decisions of picking a checkout line at a supermarket that is calibrated to actual point of sale (POS) data from a major European retail chain. It is implemented on the open-access NetLogo simulation platform and is freely available to academics and practitioners interested in testing how different checkout zone layouts, as well as queue management and feedback strategies impact the overall efficiency of the checkout process. In particular, we show that when customers pick a line by minimizing the expected waiting time, not only is this choice beneficial for the customers themselves, as it leads to shorter waiting times in queues, but also for the supermarket management, since it yields shorter working times of the cashiers. As such, we provide guidance as to the feedback that could be provided to customers entering the checkout zone.
Adaptation in Coding by Large Populations of Neurons in the Retina

A comprehensive theory of neural computation requires an understanding of the statistical properties of the neural population code. The focus of this work is the experimental study and theoretical analysis of the statistical properties of neural activity in the tiger salamander retina. This is an accessible yet complex system, for which we control the visual input and record from a substantial portion greater than a half of the ganglion cell population generating the spiking output. Our experiments probe adaptation of the retina to visual statistics: a central feature of sensory systems which have to adjust their limited dynamic range to a far larger space of possible inputs. In Chapter 1 we place our work in context with a brief overview of the relevant background. In Chapter 2 we describe the experimental methodology of recording from 100+ ganglion cells in the tiger salamander retina. In Chapter 3 we first present the measurements of adaptation of individual cells to changes in stimulation statistics and then investigate whether pairwise correlations in fluctuations of ganglion cell activity change across different stimulation conditions. We then transition to a study of the population-level probability distribution of the retinal response captured with maximum-entropy models. Convergence of the model inference is presented in Chapter 4. In Chapter 5 we first test the empirical presence of a phase transition in such models fitting the retinal response to different experimental conditions, and then proceed to develop other characterizations which are sensitive to complexity in the interaction matrix. This includes an analysis of the dynamics of sampling at finite temperature, which demonstrates a range of subtle attractor-like properties in the energy landscape. These are largely conserved when ambient illumination is varied 10-fold, a result not necessarily apparent from the measured low-order statistics of the distribution. Our results form a consistent picture which is discussed at the end of Chapter 5. We conclude with a few future directions related to this thesis. iii
Effect of Exercise Program in Reducing Risk of Fall in Elderly People

Objective: To study the Effect of Exercise Program in reducing risk of fall in elderly subject. Materials and Method: Total 30 elderly subjects(10 males and 20 females) aged above 60 years were having problem with flexibility, balance and high risk of fall were selected for the assessment of their flexibility, gait and balance. Subjects who are bed ridden, having neurological conditions, Psychiatry condition and visual deficit were excluded from the study. Outcome measures used were Morse fall risk assessment tool, Timed up and go test, Functional reach test, Functional gait assessment. Conclusion: The present study provided evidence to conclude that the exercise programme was significantly effective in improving strength, flexibility and balance along with reducing risk of fall in elderly population.
Sub-Femtosecond Processes in Molecules Studied by Coincidence Spectroscopy

Studying dynamics in molecules occurring on the few-femtosecond to subfemtosecond timescale is a formidable challenge, due to the wealth of phenomena exhibited by molecular systems. Complex manifolds of electronic states featuring electron-nuclear and electron-electron correlations complicate the interpretation of experimental data. In order to improve the situation, it is desirable to perform experiments where as much information as possible is obtained about the processes under scrutiny. When ionization is involved, this amounts to the detection of the full momentum vectors of all charged particles created in a single event, i.e. electrons and ions, the latter of which may dissociate into smaller fragments. This can be accomplished in coincidence experiments using a reaction-microscope detector. In this thesis, a reaction microscope is employed with the aim of studying attosecond dynamics taking place in molecules. First, the polyatomic molecule 1,3-butadiene is investigated using intense femtosecond laser pulses. According to the well-known three-step model, an electron is released from the molecule via strong-field ionization and may subsequently return to and rescatter from its parent ion, all of which happens within a single laser cycle. A common phenomenon in the response of molecules to strong fields is ionization to multiple final electronic states of the cation. Here, the coincidence capabilities of the reaction microscope are exploited to demonstrate directly for the first time that the resulting multiple electron continua display differences in their rescattering behaviour. Using aligned molecules, it is furthermore shown that the probability for the electron to return to the core is dependent on the orientation of the molecule with respect to the laser polarization direction, since the returning electron wave packet retains structural information on the shape of its initial bound state. The other goal of the thesis is to take the step from experiments relying on the sub-cycle dynamics occurring in a femtosecond laser pulse to attosecond pump-probe coincidence spectroscopy. To this end, a beamline combining a reaction microscope with a two-colour, attosecond-stable interferometric setup based on high-harmonic generation is presented. The setup is designed to operate at a repetition rate of 100 kHz, which is an order of magnitude larger than other setups currently combining attosecond spectroscopy with coincidence detection and which affords shorter acquisition times for coincidence experiments. First test results, in particular the first full characterization of attosecond pulse trains driven by sub-8 fs pulses at a repetition rate of 100 kHz, permit an optimistic perspective that, in the near future, the beamline will be capable of providing attosecond and few-cycle femtosecond pulses for pumpprobe experiments on molecular targets, promising to uncover novel insights into the complex attosecond dynamics of polyatomic molecules.
Too Much of Two Good Things: Effects of Founders’ Educational Level and Heterogeneity on Start-Up Funds Raised

The success of early-stage start-ups is strongly dependent on founders’ education. Yet, while scholars maintain that investors should consider founders' education an important signal of start-ups' prospects, mixed empirical findings suggest that more education does not always trigger positive investor reactions. Scholars have thus urged the development of new theoretical insights that may explain why and when education is beneficial to start-ups' emergence. Based on cognitive and social psychology literature, in this article, we evidence that different configurations of founders' education affect the ability of founding teams to obtain funding. The empirical support that we obtained from a sample of 1078 start-ups helps reconcile the contradictory findings of past research through a joint examination of two dimensions of founders' education that were previously only investigated separately—the level of education and the heterogeneity of educational backgrounds. Our focus on the group dynamics founding teams advances our understanding of the contribution of founders’ education onto early-stage start-ups' fund raising. In greater detail, educational level and educational heterogeneity positively affect the amount of funds raised, but their joint presence negatively moderates such a relationship. In doing so, we also provide start-uppers and policymakers with important information regarding how cofounders should group together when launching a start-up.
The physiological effects of artificial light at night on the Australian black field cricket

I DECLARATION . III PREFACE . IV ACKNOWLEDGEMENTS.VI TABLE OF CONTENTS. VIII LIST OF TABLES . XI LIST OF FIGURES . XII CHAPTER 1: GENERAL INTRODUCTION . 1 ARTIFICIAL LIGHT AT NIGHT (ALAN) . 2 ALAN AND LIFE HISTORY TRAITS . 5 ALAN AND IMMUNE FUNCTION . 7 ALAN AND MELATONIN – A POTENTIAL MECHANISTIC LINK . 8 THE RESEARCH CHALLENGE . 13 THESIS OBJECTIVES AND AIMS . 15 CHAPTER 2: ARTIFICIAL LIGHT AT NIGHT PROLONGS JUVENILE DEVELOPMENT TIME IN THE BLACK FIELD CRICKET, TELEOGRYLLUS COMMODUS . 17 ABSTRACT . 18 INTRODUCTION . 19 METHODS . 21 Experimental ALAN treatments and rearing conditions. 21 Juvenile development and survival . 22 Adult morphology and survival . 23 Reproductive output . 23 Statistical analyses . 25 RESULTS . 26 Juvenile development and survival . 26 Adult morphology and survival . 27 Reproductive output . 28
Characteristics and Intracellular Life of Brucella Organism: A Review

Brucella is a Gram-negative, facultative intracellular bacteria that causes zoonotic brucellosis in humans and various animals. These pathogens are affecting domestic animals (cattle, goat, sheep, pig, dogs and camel), human and wild animals. Humans are accidental hosts of brucellosis acquiring the infection commonly from contact with infected animals, aborted materials and consumption raw milk. Brucella do not produce classical virulence factors, and their capacity to successfully replicate within a variety of host cells, to persist for prolonged periods within host cells and to evade the host immune response at the same time underlies their pathogenicity. The virulence factors of Brucella are involved in intracellular survival and replication within mononuclear phagocytic cells, preferentially macrophages in the host and hampers the intracellular trafficking and ability to prevent recognition by the host defense system. All these comprehensions of Brucella can inhabit inside the phagocytes of infected host to promote their survival, persistence and multiplication.
Chromatin maturation of the HIV-1 provirus in primary resting CD4+ T cells

Human immunodeficiency virus type 1 (HIV-1) infection is a chronic condition, where viral DNA integrates into the genome. Latently infected cells form a persistent, heterogeneous reservoir. The reservoir that reinstates an active replication comprises only cells with intact provirus that can be reactivated. We confirmed that latently infected cells from patients exhibited active transcription throughout the provirus. To find transcriptional determinants, we characterized the establishment and maintenance of viral latency during proviral chromatin maturation in cultures of primary CD4+ T-cells for four months after ex vivo HIV-1 infection. As heterochromatin (marked with H3K9me3 or H3K27me3) gradually stabilized, the provirus became less accessible with reduced activation potential. In a subset of infected cells, active marks (i.e., H3K27ac) remained detectable, even after prolonged proviral silencing. After T-cell activation, the proviral activation occurred uniquely in cells with H3K27ac-marked proviruses. Our observations suggested that, after transient proviral activation, cells were actively returned to latency. Author Summary HIV infection is a devastating disease affecting 35 million people worldwide. Current anti-retroviral treatment is highly effective and has made the HIV infection chronic. However, a cure is far on the horizon. The problem for an HIV cure is that, even though the virus particles are eradicated, the infected cells maintain the information of remake the virus. This information is integrated in the host cell. The proviral chromatin switches between active and inactive states. Thereby, the infected cells evade both the immune system and death associated with massive viral production. Here we have characterized the composition of the proviral chromatin and how it connects with transcription and viral production. In resting primary CD4+ T-cells, we follow the fate of the provirus starting at infection until latency is firmly established. We found that only a fraction of the proviruses switched between the two chromatin states, and thus were able to remain undetectable but still produce new viruses. These proviruses were associated with a specific chromatin mark, allowing us to identify the activatable fraction of infected cells. Our study provides key insights as to detect the remaining HIV-infected cells capable of reseeding the infection and the mechanisms whereby these cells are maintained.
An Opinion Spam Detection Method Based on 
Multi-Filters Convolutional Neural Network

: With the continuous development of e-commerce, consumers show increasing interest in posting comments on consumption experience and quality of commodities. Meanwhile, people make purchasing decisions relying on other comments much more than ever before. So the reliability of commodity comments has a significant impact on ensuring consumers’ equity and building a fair internet-trade-environment. However, some unscrupulous online-sellers write fake praiseful reviews for themselves and malicious comments for their business counterparts to maximize their profits. Those improper ways of self-profiting have severely ruined the entire online shopping industry. Aiming to detect and prevent these deceptive comments effectively, we construct a model of Multi-Filters Convolutional Neural Network (MFCNN) for opinion spam detection. MFCNN is designed with a fixed-length sequence input and an improved activation function to avoid the gradient vanishing problem in spam opinion detection. Moreover, convolution filters with different widths are used in MFCNN to represent the sentences and documents. Our experimental results show that MFCNN outperforms current state-of-the-art methods on standard spam detection benchmarks.
Efficacy of Ca ionophore and 6-dimethylaminopurine on activation of prepubertal ovine oocytes

The present study was carried out to compare the different activation protocols for production of parthenogenetic embryos from prepubertal sheep ovarian oocytes and to compare the in vitro fertilization derived embryos. In vitro fertilization (IVF) embryos were produced by adopting IVFMC of oocytes collected from prepubertal sheep ovaries from local slaughter house, Ziaguda (Hyderabad). The overall cleavage rate was 57.5 ± 0.38, 53 ± 0.87 and 8 ± 0.24%, respectively in treatments I (10% ESS + 10 µg/ml FSH + 10 µg/ml LH + µg/ml estradiol + 50 µg/ml gentamicin + TCM 199 B), II (10 µg/ml FSH + 10 µg/ml LH + µg/ml estradiol + 50 µg/ml gentamicin + TCM 199 B) and III (50 µg/ml gentamicin + TCM 199 B), respectively. The cleaved cells attained 2-cell, 4-cell, 8-cell and Morula stage were 38.5 ± 0.28, 27.25 ± 0.28, 24.5 ± 0.23 and 14 ± 0.16%, 31 ± 0.71, 20 ± 0.60, 11 ± 0.51 and 2 ± 0.21%,, 3 ± 0.24, 1 ± 0.20, 0 and 0%, respectively in treatments I, II and III. Among the three treatments, Treatment I achieved significantly (P