Miracle-dz/UniFAR-FTUs huggingface dataset:
The Life of Pasteur

Pasteur, a tanner by trade, was drawn as a conscript in 1811, and wen through the Peninsular War in 1812, 1813. He was one of the bUUU men which formed the Leval division that fought at Bar-sur-Aube against an army of 40,000, and one of the 3rd Regiment spoken oi _ns " brave amongst the brave," of which Thiers writes in his " History ot n Consulate and the Empire," that " if Napoleon had none but sue i soldiers the result of that great struggle would certainly have een different. " In 1814 this conscript soldier was made a sergeant-major, and received the cross of the Legion of Honour. He retired from 16 army a couple of months later, when, on the fall of the Emperor, lis regiment received the name of the Regiment Dauphin. The following year, at the age of 26, having commenced work as a tanner, lie mariie( Jeanne Etiennette Roqui, and emigrated to Dole, there settling down in
Development of a Live Recombinant BCG Expressing Human Immunodeficiency Virus Type 1 (HIV-1) Gag Using a pMyong2 Vector System: Potential Use As a Novel HIV-1 Vaccine

Even though the rate of new human immunodeficiency virus type 1 (HIV-1) infections is gradually decreasing worldwide, an effective preventive vaccine for HIV-1 is still urgently needed. The recombinant Mycobacterium bovis BCG (rBCG) is promising for the development of an HIV-1 vaccine. Recently, we showed that a recombinant Mycobacterium smegmatis expressing HIV-1 gag in a pMyong2 vector system (rSmeg-pMyong2-p24) increased the efficacy of a vaccine against HIV-1 in mice. Here, we evaluated the potential of an rBCG expressing HIV-1 p24 antigen Gag in pMyong2 (rBCG-pMyong2-p24) in a vaccine application for HIV-1 infection. We found that rBCG-pMyong2-p24 elicited an enhanced HIV-1 p24 Gag expression in rBCG and infected antigen-presenting cells. We also found that compared to rBCG-pAL-p24 in a pAL5000 derived vector system, rBCG-pMyong2-p24 elicited enhanced p24-specific immune responses in vaccinated mice as evidenced by higher levels of HIV-1 Gag-specific CD4 and CD8 T lymphocyte proliferation, gamma interferon ELISPOT cell induction, antibody production, and cytotoxic T lymphocytes (CTL) responses. Furthermore, rBCG-pMyong2-p24 showed a higher level of p24-specific Ab production than rSmeg-pMyong2-p24 in the same pMyong2 vector system. In conclusion, our data indicated that a live recombinant BCG expressing HIV-1 Gag using a pMyong2 vector system, rBCG-pMyong2-p24 elicited an enhanced immune response against HIV-1 infections in a mouse model system. So, rBCG-pMyong2-p24 may have the potential as a prime vaccine in a heterologous prime-boost vaccine strategy for HIV-1 infection.
Scalable Training of Hierarchical Topic Models

Large-scale topic models serve as basic tools for feature extraction and dimensionality reduction in many practical applications. As a natural extension of flat topic models, hierarchical topic models (HTMs) are able to learn topics of different levels of abstraction, which lead to deeper understanding and better generalization than their flat counterparts. However, existing scalable systems for flat topic models cannot handle HTMs, due to their complicated data structures such as trees and concurrent dynamically growing matrices, as well as their susceptibility to local optima. In this paper, we study the hierarchical latent Dirichlet allocation (hLDA) model which is a powerful nonparametric Bayesian HTM. We propose an efficient partially collapsed Gibbs sampling algorithm for hLDA, as well as an initialization strategy to deal with local optima introduced by tree-structured models. We also identify new system challenges in building scalable systems for HTMs, and propose efficient data layout for vectorizing HTM as well as distributed data structures including dynamic matrices and trees. Empirical studies show that our system is 87 times more efficient than the previous open-source implementation for hLDA, and can scale to thousands of CPU cores. We demonstrate our scalability on a 131-million-document corpus with 28 billion tokens, which is 4--5 orders of magnitude larger than previously used corpus. Our distributed implementation can extract 1,722 topics from the corpus with 50 machines in just 7 hours.
The influence of massage on neonatal hyperbilirubinemia: a meta-analysis of randomized controlled trials

Abstract Introduction: The efficacy of massage to treat neonatal hyperbilirubinemia remains controversial. We conducted a systematic review and meta-analysis to explore the influence of massage on the neonatal hyperbilirubinemia. Methods: We search PubMed, Embase, Web of science, EBSCO, and Cochrane Library databases through November 2017 for randomized controlled trials (RCTs) assessing the effect of massage on neonatal hyperbilirubinemia. This meta-analysis is performed using the random-effect model. Results: Six RCTs involving 357 patients are included in the meta-analysis. Overall, compared with the control group in neonatal hyperbilirubinemia, massage therapy is associated with substantially reduced serum bilirubin level within 4 d (mean difference (MD) = −2.31; 95% CI = −2.92 to −1.70; p < . 00001) and transcutaneous bilirubin level within 4 d for neonatal hyperbilirubinemia (MD = −1.97; 95% CI = −2.55 to −1.39; p < .00001), but results no remarkable impact on serum bilirubin level on 2 d (MD = −0.82; 95% CI = −2.16–0.52; p = .23), transcutaneous bilirubin level on 2 d (MD = −0.17; 95% CI = −1.34 to 1.00; p = .77), frequency of defecation daily on 2 d (MD = 0.57; 95% CI = −0.03 to 1.16; p = .06), and frequency of defecation daily within 4 d (MD = 0.83; 95% CI = −0.11 to 1.76; p = .08). Conclusions: Massage therapy can significantly reduce serum bilirubin level and transcutaneous bilirubin level within 4 d, but demonstrates no influence on serum bilirubin level and transcutaneous bilirubin level on 2 d, frequency of defecation daily on 2 and 4 d for neonatal hyperbilirubinemia.
Workload characterization of interactive cloud services on big and small server platforms

Key-value stores (e.g., Memcached) and web servers (e.g., NGINX) are widely used by cloud providers. As interactive services, they have strict service-level objectives, with typical 99th-percentile tail latencies on the order of a few milliseconds. Unlike average latency, tail latency is more sensitive to changes in usage load and traffic patterns, system configurations, and resource availability. Understanding the sensitivity of tail latency to application and system factors is critical to efficiently design and manage systems for these latency-critical services. We present a comprehensive study of the impact a diverse set of application, hardware, and isolation configurations have on tail latency for two representative interactive services, Memcached and NGINX. Examined factors include input load, thread-level parallelism, request size, virtualization, and resource partitioning. We conduct this study on two server platforms with significant differences in terms of architecture and price points: an Intel Xeon and an ARM-based Cavium ThunderX server. Experimental results show that latency on both platforms is subject to changes of several orders of magnitude depending on application and system settings, with Cavium ThunderX being more sensitive to configuration parameters.
Genomics-Enabled Next-Generation Breeding Approaches for Developing System-Specific Drought Tolerant Hybrids in Maize

Breeding science has immensely contributed to the global food security. Several varieties and hybrids in different food crops including maize have been released through conventional breeding. The ever growing population, decreasing agricultural land, lowering water table, changing climate, and other variables pose tremendous challenge to the researchers to improve the production and productivity of food crops. Drought is one of the major problems to sustain and improve the productivity of food crops including maize in tropical and subtropical production systems. With advent of novel genomics and breeding tools, the way of doing breeding has been tremendously changed in the last two decades. Drought tolerance is a combination of several component traits with a quantitative mode of inheritance. Rapid DNA and RNA sequencing tools and high-throughput SNP genotyping techniques, trait mapping, functional characterization, genomic selection, rapid generation advancement, and other tools are now available to understand the genetics of drought tolerance and to accelerate the breeding cycle. Informatics play complementary role by managing the big-data generated from the large-scale genomics and breeding experiments. Genome editing is the latest technique to alter specific genes to improve the trait expression. Integration of novel genomics, next-generation breeding, and informatics tools will accelerate the stress breeding process and increase the genetic gain under different production systems.
Automatic Package Coupling and Cycle Minimization

Object-oriented (OO) software is usually organized into subsystems using the concepts of package or module.Such modular structure helps applications to evolve when facing new requirements.However, studies show that as software evolves to meet requirements and environment changes, modularization quality degrades. To help maintainers improve the quality of software modularization we have designed and implemented a heuristic search-based approach for automatically optimizing inter-package connectivity (i.e., dependencies). In this paper, we present our approach and its underlying techniques and algorithm.We show through a case study how it enables maintainers to optimize OO package structure of source code.Our optimization approach is based on Simulated Annealing technique.
Policy Gradient With Value Function Approximation For Collective Multiagent Planning

Decentralized (PO)MDPs provide an expressive framework for sequential decision making in a multiagent system. Given their computational complexity, recent research has focused on tractable yet practical subclasses of Dec-POMDPs. We address such a subclass called CDEC-POMDP where the collective behavior of a population of agents affects the joint-reward and environment dynamics. Our main contribution is an actor-critic (AC) reinforcement learning method for optimizing CDEC-POMDP policies. Vanilla AC has slow convergence for larger problems. To address this, we show how a particular decomposition of the approximate action-value function over agents leads to effective updates, and also derive a new way to train the critic based on local reward signals. Comparisons on a synthetic benchmark and a real-world taxi fleet optimization problem show that our new AC approach provides better quality solutions than previous best approaches.
Solution structure of a mini IGF‐1

Mini insulin‐like growth factor 1, an inactive insulin‐like growth factor 1 mutant lacking the C region, was studied by 2D NMR spectroscopy. Resonances were assigned for almost all protons of the 57 amino acid residues. The 3D structure of the protein was determined by distance geometry methods. Three helical segments; Ala 8‐Cys 18, Gly 42‐Phe 49, and Leu 54‐Cys 61, were identified, corresponding to those present in wild‐type insulin‐like growth factor 1 and in single‐chain insulin. Their relative orientation, however, was found to be changed. This change is connected with a displacement of the Phe 23‐Tyr 24‐Phe 25‐Asn 26 β‐strand‐like segment, i.e., of aromatic side chains known to be important for receptor binding. Thus, deletion of the C region of IGF‐1 results in a substantial tertiary structural rearrangement that accounts for the loss of receptor affinity.
Characterizing the Key Metabolic Pathways of the Neonatal Mouse Heart Using a Quantitative Combinatorial Omics Approach

The heart of a newborn mouse has an exceptional capacity to regenerate from myocardial injury that is lost within the first week of its life. In order to elucidate the molecular mechanisms taking place in the mouse heart during this critical period we applied an untargeted combinatory multiomics approach using large-scale mass spectrometry-based quantitative proteomics, metabolomics and mRNA sequencing on hearts from 1-day-old and 7-day-old mice. As a result, we quantified 1.937 proteins (366 differentially expressed), 612 metabolites (263 differentially regulated) and revealed 2.586 differentially expressed gene loci (2.175 annotated genes). The analyses pinpointed the fructose-induced glycolysis-pathway to be markedly active in 1-day-old neonatal mice. Integrated analysis of the data convincingly demonstrated cardiac metabolic reprogramming from glycolysis to oxidative phosphorylation in 7-days old mice, with increases of key enzymes and metabolites in fatty acid transport (acylcarnitines) and β-oxidation. An upsurge in the formation of reactive oxygen species and an increase in oxidative stress markers, e.g., lipid peroxidation, altered sphingolipid and plasmalogen metabolism were also evident in 7-days mice. In vitro maintenance of physiological fetal hypoxic conditions retained the proliferative capacity of cardiomyocytes isolated from newborn mice hearts. In summary, we provide here a holistic, multiomics view toward early postnatal changes associated with loss of a tissue regenerative capacity in the neonatal mouse heart. These results may provide insight into mechanisms of human cardiac diseases associated with tissue regenerative incapacity at the molecular level, and offer a prospect to discovery of novel therapeutic targets.
Long-Term Hyperphagia and Caloric Restriction Caused by Low- or High-Density Husbandry Have Differential Effects on Zebrafish Postembryonic Development, Somatic Growth, Fat Accumulation and Reproduction

In recent years, the zebrafish (Danio rerio) has emerged as an alternative vertebrate model for energy homeostasis and metabolic diseases, including obesity and anorexia. It has been shown that diet-induced obesity (DIO) in zebrafish shares multiple pathophysiological features with obesity in mammals. However, a systematic and comprehensive analysis of the different pathways of energy expenditure in obese and starved fish had been missing thus far. Here, we carry out long-term ad libitum feeding (hyperphagia) and caloric restriction studies induced by low- or high-density husbandry, respectively, to investigate the impact of caloric intake on the timing of scale formation, a crucial step of postembryonic development and metamorphosis, and on somatic growth, body weight, fat storage and female reproduction. We show that all of them are positively affected by increased caloric intake, that middle-aged fish develop severe DIO, and that the body mass index (BMI) displays a strict linear correlation with whole-body triglyceride levels in adult zebrafish. Interestingly, juvenile fish are largely resistant to DIO, while BMI and triglyceride values drop in aged fish, pointing to aging-associated anorexic effects. Histological analyses further indicate that increased fat storage in white adipose tissue involves both hyperplasia and hypertrophy of adipocytes. Furthermore, in ovaries, caloric intake primarily affects the rate of oocyte growth, rather than total oocyte numbers. Finally, comparing the different pathways of energy expenditure with each other, we demonstrate that they are differentially affected by caloric restriction / high-density husbandry. In juvenile fish, scale formation is prioritized over somatic growth, while in sexually mature adults, female reproduction is prioritized over somatic growth, and somatic growth over fat storage. Our data will serve as a template for future functional studies to dissect the neuroendocrine regulators of energy homeostasis mediating differential energy allocation.
Multidimensional approach usefulness in early Alzheimer’s disease: advances in clinical practice

Background and aim: Improving quality of life of patients with early Alzheimer’s Disease (AD) is a primary concern of health professionals involved in dementia treatment. The aim of this study is to reveal associations among psychiatric symptoms and wellbeing aspects, dysfunctional lifestyles and stress-related behaviors, illness perception, personality traits, and life quality satisfaction, in order to offer a comprehensive evaluation of psychological and behavioral aspects characterizing patients with early AD. Methods: This is a cross-sectional study in which all the outpatients included were evaluated at the Dementia Clinic in Parma (Italy). 21 patients with probable AD were assessed by an overall cognitive screening (Milan Overall Dementia Assessment), the evaluation of personal and instrumental autonomy (Activities of Daily Living and Instrumental Activities of Daily Living), and of dementia severity (Clinical Dementia Rating Scale). After the neurocognitive assessment, a wide battery of clinical and psychological measures (Symptom Questionnaire, Pisa Stress Questionnaire, Illness Behavior Questionnaire, Sixteen Personality Factor Questionnaire and Satisfaction Profile) was administered to the patients. Spearman’s rho correlations between clinical and psychological measures were performed. Results: A tendency to deny anxiety, depressive and somatic symptoms might be present in patients with early AD. They also present with hypochondriasis, resulting in higher level of anxiety and depression. Reduced liveliness and self-reliance as personality traits may influence the intensity of such symptoms. Conclusions: A comprehensive assessment including psychological and clinical measures should be routinely integrated in clinical practice for the evaluation of patients with early AD. (www.actabiomedica.it)
Strategic role of nanotechnology for production of bioethanol and biodiesel

Abstract In spite of the limited sources of fossil fuels, energy demand has been considerably increased since the last century. The problems associated with global warming due to rising atmospheric greenhouse gas levels and scarcity of fossil fuels make it imperative to reduce our heavy dependency on fossil fuels. These reasons forced countries throughout the world to search for new fuel alternatives. Biofuel have gathered considerable attention due to their inherent benefits, like lower greenhouse gas emission, renewability, and sustainability. Commercially, biofuels are produced from vegetable oils, animal fats, and carbohydrates by using transesterification and fermentation. However, biofuel production suffers from high production costs and other technical barriers. Considering the environmental and economic issues, use of nanotechnology seems to be a viable solution. Nanoparticles have a number of interesting properties for the production of second-generation ethanol or transesterification of oils and fats to yield biodiesel. It is advantageous for recovery and reuse of catalysts. The present review discusses the role of nanotechnology in the production of bioethanol and biodiesel. Moreover, applications of nanoparticles for the production of biodiesel and second-generation ethanol with special reference to enzyme immobilization and chemical nano-catalysis have been described.
Affinity propagation: An exemplar‐based tool for clustering in psychological research

Affinity propagation is a message-passing-based clustering procedure that has received widespread attention in domains such as biological science, physics, and computer science. However, its implementation in psychology and related areas of social science is comparatively scant. In this paper, we describe the basic principles of affinity propagation, its relationship to other clustering problems, and the types of data for which it can be used for cluster analysis. More importantly, we identify the strengths and weaknesses of affinity propagation as a clustering tool in general and highlight potential opportunities for its use in psychological research. Numerical examples are provided to illustrate the method.
Notice of RetractionThe Effectiveness of Human Resource Management Practices on Independent Innovation: Dynamic Capabilities as a Mediator

Effective SHRM practices can lead to superior independent innovation. Nevertheless, the mechanism between these two has not been carefully identified. Using the survey data, the paper examines the relationship among SHRM practices, dynamic capabilities and independent innovation. The results from structural equation analysis indicate that the effective SHRM practices can increase the flexible organization, organizational learning, resources integration and environmental perception. Dynamic capabilities can enhance the independent innovation.
The Application of New Technology on De-burring and Polishing Machining for Precise Mechanical Parts

In the process of precise mechanical machining,how to improve and control the machining quality of precise mechanical parts effectively is a very important problem.The technology of de-burring and polishing in precise machining process also is a matter hard to overcome in automatic production of precise mechanical parts.In this article,some problems in the application of several new technologies on de-burring and polishing machining in precise mechanical parts manufacture are summarized.
Electromyographic Responses Across Different Pulse‐Widths of Sacral Neuromodulation in Sheep

In rodents, we reported that short pulse‐width (PW) neuromodulation might provide more efficient therapy delivery than traditional 0.21 msec PW. Using fully implanted, commercialized systems in the sheep, the goal of this study was to characterize the relationship of electromyographic (EMG) responses of the external anal sphincter (EAS) to different PWs of sacral neuromodulation (SNM).
Selecting Subexpressions to Materialize at Datacenter Scale

We observe significant overlaps in the computations performed by user jobs in modern shared analytics clusters. Naively computing the same subexpressions multiple times results in wasting cluster resources and longer execution times. Given that these shared cluster workloads consist of tens of thousands of jobs, identifying overlapping computations across jobs is of great interest to both cluster operators and users. Nevertheless, existing approaches support orders of magnitude smaller workloads or employ heuristics with limited effectiveness. In this paper, we focus on the problem of subexpression selection for large workloads, i.e., selecting common parts of job plans and materializing them to speed-up the evaluation of subsequent jobs. We provide an ILP-based formulation of our problem and map it to a bipartite graph labeling problem. Then, we introduce BigSubs, a vertex-centric graph algorithm to iteratively choose in parallel which subexpressions to materialize and which subexpressions to use for evaluating each job. We provide a distributed implementation of our approach using our internal SQL-like execution framework, SCOPE, and assess its effectiveness over production workloads. BigSubs supports workloads with tens of thousands of jobs, yielding savings of up to 40% in machine-hours. We are currently integrating our techniques with the SCOPE runtime in our production clusters.