Miracle-dz/UniFAR-FTUs huggingface dataset:
Constraining scalar fields with stellar kinematics and collisional dark matter

The existence and detection of scalar fields could provide solutions to long- standing puzzles about the nature of dark matter, the dark compact objects at the centre of most galaxies, and other phenomena. Yet, self-interacting scalar fields are very poorly constrained by astronomical observations, leading to great uncertainties in estimates of the mass mand the self-interacting coupling constantof these fields. To counter this, we have systematically employed available astronomical observations to develop new constraints, con- siderably restricting this parameter space. In particular, by exploiting precise observations of stellar dynamics at the centre of our Galaxy and assuming that these dynamics can be explained by a single boson star, we determine an upper limit for the boson star compactness and impose significant limits on the values of the properties of possible scalar fields. Requir- ing the scalar field particle to follow a collisional dark matter model further narrows these constraints. Most importantly, we find that if a scalar dark matter particle does exist, then it cannot account for both the dark-matter halos and the existence of dark compact objects in galactic nuclei.
BRein memory: A 13-layer 4.2 K neuron/0.8 M synapse binary/ternary reconfigurable in-memory deep neural network accelerator in 65 nm CMOS

A versatile reconfigurable accelerator for binary/ternary deep neural networks (DNNs) is presented. It features a massively parallel in-memory processing architecture and stores varieties of binary/ternary DNNs with a maximum of 13 layers, 4.2 K neurons, and 0.8 M synapses on chip. The 0.6 W, 1.4 TOPS chip achieves performance and energy efficiency that is 10–10<sup>2</sup> and 10<sup>2</sup>–10<sup>4</sup> times better than a CPU/GPU/FPGA.
Association of antibodies blocking HIV‐1 gp160‐sCD4 attachment with virus neutralizing activity in human sera

Sera, from HIV‐1 and HIV‐2 seropositive individuals, were tested for the presence of antibodies able to inhibit the binding (BI) of HIV‐IIIB gp160 (produced in mammalian cells using a vaccinia expression system) to the extracellular portion of the CD4 receptor. A competition enzyme immunoassay (EIA) with scluble CD4 (sCD4) was used. BI antibodies were highly prevalent among HIV‐1 seropositives but not in HIV‐2 infected individuals. Attempts to localize the binding site for these BI antibodies on the primary sequence of gp120 by using synthetic peptides encompassing the putative CD4 binding site on gp120 (aa 397–439) were not successful. This study did not reveal a significant correlation between the presence of BI antibodies and disease evolution. BI antibody titres correlated less well with anti‐gp160 titres (r=0.51, P⩽0.011) than with neutralizing antibody (NA) titres using either the isolates HIV‐SF2 (SF2) (r=0.77, P⩽0.000) and HIV‐MN (MN) (r=0.61, P⩽0.002) or the isolate HIV‐IIIB (HX10) (r=0.89, P⩽0.000) of which the gp160 for the assays was derived. An HIV‐IIIB neutralizing serum, elicited in a rabbit by immunization with a 17‐mer synthetic peptide derived from the third variable domain (V3) of gp120, did bind gp160 without inhibiting the subsequent attachment of sCD4 to gp160. These results indicate that (conformational) epitopes on gp160 recognized by antibodies that inhibit the attachment to CD4 may be identical or closely linked to the binding sites (not in the V3 domain) for HIV‐1 (group‐specific) neutralizing antibodies.
The ubiquitin E1 enzyme Ube1 mediates NEDD8 activation under diverse stress conditions

Modification of proteins with ubiquitin and ubiquitin-like molecules is involved in the regulation of almost every biological process. Historically, each conjugation pathway has its unique set of E1, E2 and E3 enzymes that lead to activation and conjugation of their cognate molecules. Here, we present the unexpected finding that under stress conditions, the ubiquitin E1 enzyme Ube1 mediates conjugation of the ubiquitin-like molecule NEDD8. Inhibition of the 26S proteasome, heat shock and oxidative stress cause a global increase in NEDDylation. Surprisingly, this does not depend on the NEDD8 E1-activating enzyme, but rather on Ube1. A common event in the tested stress conditions is the depletion of “free” ubiquitin. A decrease in “free” ubiquitin levels in the absence of additional stress is sufficient to stimulate NEDDylation through Ube1. Further analysis on the NEDD8 proteome shows that the modified NEDDylated proteins are simultaneously ubiquitinated. Mass spectrometry on the complex proteome under stress reveals the existence of mixed chains between NEDD8 and ubiquitin. We further show that NEDDylation of the p53 tumor suppressor upon stress is mediated mainly through Ube1. Our studies reveal an unprecedented interplay between NEDD8 and ubiquitin pathways operating in diverse cellular stress conditions.
No 53 Competition in the Workplace : An Experimental Investigation

We analyze competition between workers in a gift-exchange experiment where two workers are hired by the same employer. In the competition treatment the two employees simultaneously choose their e ort whereas in the baseline treatment competition cannot occur since there is only one employee per employer. We nd that in the competition treatment employers implicitly set tournament incentives by rewarding employees who choose higher e ort levels than their co-workers. Here, employees' e ort levels increase signi cantly faster, which can be explained by imitation learning. Furthermore we nd that employers decrease their wage payments per unit of e ort exerted over time when employing two workers. JEL Classi cation numbers: C91, J41, L22, M52.
The role of ice stream dynamics in deglaciation

Since the mid‐Pleistocene transition, deglaciation has occurred only after ice sheets have grown large while experiencing several precession and obliquity cycles, indicating that large ice sheets are more sensitive to Milankovitch forcing than small ice sheets are. Observations and model simulations suggest that the development of ice streams in the Laurentide Ice Sheet played an as yet unknown role in deglaciations. In this study, we propose a mechanism by which ice streams may enhance deglaciation and render large ice sheets more sensitive to Milankovitch forcing. We use an idealized configuration of the Parallel Ice Sheet Model that permits the formation of ice streams. When the ice sheet is large and ice streams are sufficiently developed, an upward shift in equilibrium line altitude, commensurate with Milankovitch forcing, results in rapid deglaciation, while the same shift applied to an ice sheet without fully formed ice streams results in continued ice sheet growth or slower deglaciation. Rapid deglaciation in ice sheets with significant streaming behavior is caused by ice stream acceleration and the attendant enhancement of calving and surface melting at low elevations. Ice stream acceleration is ultimately the result of steepening of the ice surface and increased driving stresses in ice stream onset zones, which come about due to the dependence of surface mass balance on elevation. These ice sheet simulations match the broad features of geomorphological observations and add ice stream dynamics that are missing from previous model studies of deglaciation.
Combining binary-SVM and pairwise label constraints for multi-label classification

Multi-label classification is an extension of traditional classification problem in which each instance is associated with a set of labels. Recent research has shown that the ranking approach is an effective way to solve this problem. In the multi-labeled sets, classes are often related to each other. Some implicit constraint rules are existed among the labels. So we present a novel multi-label ranking algorithm inspired by the pairwise constraint rules mined from the training set to enhance the existing method. In this method, one-against-all decomposition technique is used firstly to divide a multi-label problem into binary class sub-problems. A rank list is generated by combining the probabilistic outputs of each binary Support Vector Machine (SVM) classifier. Label constraint rules are learned by minimizing the ranking loss. Experimental performance evaluation on well-known multi-label benchmark datasets show that our method improves the classification accuracy efficiently, compared with some existed methods.
Convolution particle filtering for parameter estimation in general state-space models

The state-space modeling of partially observed dynamic systems generally requires estimates of unknown parameters. From a practical point of view, it is relevant in such filtering contexts to simultaneously estimate the unknown states and parameters. Efficient simulation-based methods using convolution particle filters are proposed. The regularization properties of these filters is well suited, given the context of parameter estimation. Firstly the usual non Bayesian statistical estimates are considered: the conditional least squares estimate (CLSE) and the maximum likelihood estimate (MLE). Secondly, in a Bayesian context, a Monte Carlo type method is presented. Finally we present a simulated case study
Preventive start-time optimisation of open shortest path first link weights for hose model

Optimising link weights in an open shortest path first network is a challenging traffic engineering problem to reduce network congestion. Most of the previous studies have focused on the application of start-time optimisation (SO) and run-time optimisation on both pipe and hose models of link weight optimisation. In a more recent study, an efficient policy, preventive start-time optimisation (PSO), has been introduced for link weight optimisation. However, no studies have been reported on the application of PSO to the hose model where the exact traffic demand between each source and destination node pair does not need to be specified. A PSO policy for the hose model to optimise the link weights against link failures is proposed. The proposed scheme employs a heuristic algorithm to determine a suitable set of link weights to reduce worst-case congestion for any single link failure. It efficiently selects the worst-case performance traffic matrix and reduces the worst-case congestion ratio as compared with a brute-force scheme which is computationally expensive when searching the link weight space against all the possible traffic matrices and topologies created by single link failures. The numerical results show that the proposed scheme is more effective in the reduction of worst-case congestion ratio than the scheme utilising SO.
PHARMACOLOGICAL EVALUATION OF MEMBRANE‐MODERATED TRANSDERMAL SYSTEM OF GLIPIZIDE

1 Membrane‐moderated transdermal systems of glipizide were prepared using drug‐containing carbopol gel (drug reservoir) and ethyl cellulose, as well as Eudragit RS‐100, Eudragit RL‐100 (Rohm Pharma, Darmstadt, Germany) and ethylene vinyl acetate (EVA; 2, 9 and 19% vinyl acetate content) rate‐controlling membranes, and were subsequently evaluated in vitro (drug content and drug permeation studies) and in vivo (acute and long‐term hypoglycaemic activity, effect on glucose tolerance, biochemical and histopathological studies, skin irritation test and pharmacokinetic studies in mice). 2 The drug content of the systems was found to be more than 99%. Variations in drug permeation patterns were observed among the formulations containing different rate‐controlling membranes. 3 The system with the EVA (19% vinyl acetate) rate‐controlling membrane was selected for in vivo experiments. This transdermal system produced better improvement with respect to hypoglycaemic activity, glucose tolerance and tested biochemical, histopathological and pharmacokinetic parameters all compared with oral administration and exhibited negligible skin irritation. 4 The transdermal system successfully prevented severe hypoglycaemia in the initial hours and it was also effective for chronic application.
Learning of a multi-class classifier with rejection option using sparse Representation

This paper introduces a multi-class classification algorithm based on sparse representation which considers on rejection option to minimize risks caused by outliers. Here the outliers include signals that do not belong to any classes learned in a training step. To successfully reject the outliers, new rejection measure and corresponding dictionary learning algorithm are presented. Experimental results on an image set, Caltech 101 [1] and one sound data set, AUI dataset, show that the proposed algorithm has improvements in classifying result by rejecting outliers.
HLA-DR polymorphism in a Senegalese Mandenka population : DNA oligotyping and population genetics of DRB 1 specificities TIERCY

HLA class II loci are useful markers in human population genetics, because they are extremely variable and because new molecular techniques allow large-scale analysis of DNA allele frequencies. Direct DNA typing by hybridization with sequence-specific oligonucleotide probes (HLA oligotyping) after enzymatic in vitro PCR amplification detects HLA allelic polymorphisms for all class II loci. A detailed HLA-DR oligotyping analysis of 191 individuals from a geographically, culturally, and genetically well-defined western African population, the Mandenkalu, reveals a high degree of polymorphism, with at least 24 alleles and a heterozygosity level of.884 for the DRB1 locus. The allele DRB1*1304, defined by DNA sequencing of the DRB1 first-domain exon, is the most frequent allele (27.1%). It accounts for an unusually high DR13 frequency, which is nevertheless within the neutral frequency range. The next most frequent specificities are DR11, DR3, and DR8. Among DRB3-encoded alleles, DR52b (DRB3*02) represents as much as 80.7% of all DR52 haplotypes. A survey of HLA-DR specificities in populations from different continents shows a [. ] TIERCY, Jean-Marie, et al. HLA-DR polymorphism in a Senegalese Mandenka population : DNA oligotyping and population genetics of DRB1 specificities. American Journal of Human Genetics, 1992, vol. 51, no. 3, p. 592-608
Diverse uncultivated bacterial groups from soils of the arid southwestern United States that are present in many geographic regions

We have performed a phylogenetic survey of microbial species present in two soils from northern Arizona. Microbial DNA was purified directly from soil samples and subjected to PCR amplification with primers specific for bacterial 16S rRNA gene sequences (rDNAs). Clone libraries from the two soils were constructed, and 60 clone inserts were partially sequenced. Phylogenetic analysis of these sequences revealed extensive diversity. Most of the analyzed sequences (64%) fell into five novel clusters having no known cultured members. Extensive analysis of 10 nearly full-length rDNAs from clones representative of the novel groups indicated that four of the five groups probably cluster into a large "supergroup" which is as distinct from currently recognized bacterial divisions as the latter are from each other. From this we postulate the existence of a major bacterial lineage, previously known only from a single cultured representative, whose diversity and ecology we are only beginning to explore. Analysis of our data and that from other rDNA sequence-based studies of soils from different geographic regions shows considerable overlap of sequence types. Taken together, these groups encompass most of the novel rDNA sequences recovered in each comparable analysis reported to date, despite large differences in soil types and geographic sources. Our results indicate that members of these new groups comprise a phylogenetically diverse, geographically widespread, and perhaps numerically important component of the soil microbiota.
Histone modifications as a platform for cancer therapy

Tumorigenesis and metastasis are a progression of events resulting from alterations in the processing of the genetic information. These alterations result from stable genetic changes (mutations) involving tumor suppressor genes and oncogenes (e.g., ras, BRAF) and potentially reversible epigenetic changes, which are modifications in gene function without a change in the DNA sequence. Mutations of genes coding for proteins that directly or indirectly influence epigenetic processes will alter the cell's gene expression program. Epigenetic mechanisms often altered in cancer cells are DNA methylation and histone modifications (acetylation, methylation, phosphorylation). This article will review the potential of these reversible epigenetic processes as targets for cancer therapies. © 2005 Wiley‐Liss, Inc.
Can Combined 18F-FDG-PET and Dynamic Contrast-Enhanced MRI Predict Behavior of Desmoid Tumors in Patients With Familial Adenomatous Polyposis?

BACKGROUND: Desmoid tumors associated with familial adenomatous polyposis show variable behavior; about 10% grow relentlessly, resulting in severe morbidity or mortality. Investigations that could identify the minority of desmoid tumors that behave aggressively would allow these tumors to be treated early and spare the majority of patients who have more benign disease from unnecessary intervention. OBJECTIVE: The aim of this study was to investigate whether imaging the tumor metabolic-vascular phenotype by modern methods predicts growth. DESIGN: This is a prospective case series study. SETTINGS: The study was conducted at a tertiary center specializing in familial adenomatous polyposis and desmoid disease. PATIENTS: Nine patients with familial adenomatous polyposis (4 male, mean age 39 years) with desmoid tumor underwent 18F-FDG-PET and dynamic contrast-enhanced MRI. Standard MRI was repeated a year later to assess tumor growth. MAIN OUTCOME MEASURES: The primary outcome measured was the correlation between 18F-FDG-PET and dynamic contrast-enhanced MRI parameters and subsequent desmoid growth. RESULTS: Failed intravenous access precluded dynamic contrast-enhanced MRI in 1 female patient. Thirteen desmoid tumors (4 intra-abdominal, 2 extra-abdominal, 7 abdominal wall; mean area, 68 cm2) were analyzed in the remaining 8 patients. Two patients died before follow-up MRI. Five tumors decreased in size, 3 increased in size, and 3 remained stable after a year. Significant correlation (Spearman rank correlation, significance at 5%) existed between maximum standardized uptake value and kep (r = −0.56, p = 0.04), but not with other vascular parameters (Ktrans (r = −0.47, p = 0.09); ve (r = −0.11, p = 0.72); integrated area under the gadolinium-time curve at 60 seconds (r = −0.47, p = 0.10)). There was no significant difference in the maximum standardized uptake value or dynamic contrast-enhanced MRI parameters (Ktrans, ve, kep, integrated area under the gadolinium-time curve at 60 seconds) between the tumors that grew or decreased in size or between the tumor sites. However, vascular metabolic ratio (maximum standardized uptake value/Ktrans) was significantly different for tumor site (p = 0.001) and size (p = 0.001, 1-way ANOVA). LIMITATIONS: This investigation is limited because of its exploratory nature and small patient numbers. CONCLUSIONS: Although not predictive for tumor behavior, some correlations existed between dynamic contrast-enhanced MRI and 18F-FDG-PET parameters. Vascular metabolic ratio may provide further information on tumor behavior; however, this needs to be evaluated with further larger studies.
Unemployment and drinking behaviour: some data from a general population survey of alcohol use.

The confusion in the alcohol‐unemployment literature may be partly explained by methodological considerations. A standard instrument for measuring alcohol consumption was used in this study which reports data drawn from a general population study. Results show that unemployed males were particularly likely to binge drink and to report adverse effects from consuming alcohol. It is suggested that (a) the choice of consumption variables may influence the outcome of research in this area, and (b) unemployed men may be exposed to greater risks from drinking alcohol. Copyright © 1987, Wiley Blackwell. All rights reserved
An Optimized Scheme of Energy Consumption in Wireless Sensor MAC Protocol

The primary goal for wireless sensor MAC protocol is energy conservation. S(sensor)-MAC based on sensor networks proposes schemes such as periodic sleep and overhearing avoidance for that goal. An analytic model of CAP is employed for our probability model of active period for minimizing energy consumption in a S(sensor)-MAC. We evaluate the time for one successful transmission so that nodes can go to sleep after one successful transmission for energy saving, since that per-node latency and fairness are less important in sensor networks. We validate the accuracy of the analytic model by comparing the analytic results with OPNET simulation results and result confirms that the model can save energy effectively
Distributed control of networked large-scale systems based on a scheduling middleware

This paper investigates event-triggered distributed control of networked large-scale systems under simultaneous consideration of network dynamics. Based on an information dispatching middleware, a framework of networked distributed large-scale systems is established. In terms of the middleware, the information selection module is developed to regulate the transmission of the sampled data by means of a novel event-triggered scheme. In the congestion avoidance module, a real-time scheduling strategy is proposed such that the released sampled output measurement data is transmitted within the allowable transmission network-induced delay. By employing Lyapunov-Krasovskii functional theory, sufficient conditions are derived such that the large-scale distributed system can achieve a prescribed H∞ performance. Then the suitable distributed controllers and network congestion controllers can be co-designed provided that a set of linear matrix inequalities is feasible. Finally, an example is given to illustrate the merits and effectiveness of the proposed method.
Socioeconomic status and hypertension: a meta-analysis

Background: The relationship between socioeconomic status (SES) and hypertension has been studied in a number of reviews. However, the impact of SES on hypertension has been reported in several studies with conflicting results. Methods: A systematic search was performed in PubMed, Proquest and Cochrane databases for observational studies on hypertension prevalence and SES, published in English, until March 2014. Hypertension was defined as a mean SBP of at least 140 mmHg or a DBP of at least 90 mmHg, or use of antihypertensive medication. The inverse variance method with a random-effects model was used to pool the risk estimates from the individual studies. Data abstraction was conducted independently by two authors. Results: Among the 2404 references, 51 studies fulfilled the inclusion criteria. An overall increased risk of hypertension among the lowest SES was found for all three indicators: income [pooled odds ratio (OR) 1.19, 95% confidence interval (CI) 0.96–1.48], occupation (pooled OR 1.31, 95% CI 1.04–1.64) and education (pooled OR 2.02, 95% CI 1.55–2.63). The associations were significant in high-income countries, and the increased risk of hypertension for the lowest categories of all SES indicators was most evident for women, whereas men revealed less consistent associations. Conclusion: Low SES is associated with higher blood pressure, and this association is particularly evident in the level of education. It is important to identify and monitor hypertension to reduce the risk of this disease among the most vulnerable groups in different countries and among different societies.