Miracle-dz/UniFAR-FTUs huggingface dataset:
MOJAVE: Monitoring of Jets in AGN with VLBA Experiments. IV. The Parent Luminosity Function of Radio-Loud Blazars

We use a complete sample of active galactic nuclei (AGN) selected on the basis of relativistically beamed 15 GHz radio flux density (MOJAVE: Monitoring of Jets in AGN with VLBA Experiments) to derive the parent radio luminosity function (RLF) of bright radio-selected blazar cores. We use a maximum likelihood method to fit a beamed RLF to the observed data and thereby recover the parameters of the intrinsic (unbeamed) RLF. We analyze two subsamples of the MOJAVE sample: the first contains only objects of known FR II class, with a total of 103 sources, and the second subsample adds 24 objects of uncertain FR class for a total of 127 sources. Both subsamples exclude four known FR I radio galaxies and two gigahertz-peaked spectrum sources. We obtain good fits to both subsamples using a single power law intrinsic RLF and a pure density evolution function of the form zmexp{−1/2[(z − z0)/σ]2}. We find that a previously reported break in the observed MOJAVE RLF actually arises from using incomplete bins (because of the luminosity cutoff) across a steep and strongly evolving RLF, and does not reflect a break in the intrinsic RLF. The derived space density of the parent population of the FR II sources from the MOJAVE sample (with L15 GHz ⩾ 1.3 × 1025 W Hz−1) is approximately 1.6 × 103 Gpc −3.
Conditionally Positive Definite Kernels for SVM Based Image Recognition

Kernel based methods such as support vector machine (SVM) has provided successful tools for solving many recognition problems. One of the reasons of this success is the use of kernels. Positive definiteness has to be checked for kernels to be suitable for most of these methods. For instance for SVM, the use of a positive definite kernel insures that the optimized problem is convex and thus the obtained solution is unique. Alternative class of kernels called conditionally positive definite have been studied for a long time from the theoretical point of view and have drawn attention from the community only in the last decade. We propose a new kernel, named log kernel, which seems particularly interesting for images. Moreover, we prove that this new kernel is a conditionally positive definite kernel as well as the power kernel. Finally, we show from experimentations that using conditionally positive definite kernels allows us to outperform classical positive definite kernels
Dynamic Critical Resistance: A Timing-Based Critical Resistance Model for Statistical Delay Testing of Nanometer ICs

As CMOS IC feature sizes shrink down to the nanometer regime, the need for more efficient test methods capable of dealing with new failure mechanisms increases. Advances in this domain require a detailed knowledge of these failure physical properties and the development of appropriated test methods. Several works have shown the relative increase of resistive defects (both opens and shorts), and that they mainly affect circuit timing rather than impacting its static DC behavior. Defect evolution, together with the increase of parameter variations, represents a serious challenge for traditional delay test methods based on fixed time delay limit setting. One alternative to deal with variation relies on adopting correlation where test limits for one parameter are settled based on its correspondence to other circuit variables. In particular, the correlation of circuit delay to reduced V DD has been proposed as a useful test method. In this work the authors investigate the merits of this technique for future technologies where variation is predicted to increase, analyzing the possibilities of detecting resistive shorts and opens
Inequivalence of Difference Sets: On a Remark of Baumert

An often cited statement of Baumert in his book Cyclic difference sets asserts that four well known families of cyclic $(4t-1,2t-1,t-1)$ difference sets are inequivalent, apart from a small number of exceptions with $t< 8$. We are not aware of a proof of this statement in the literature. Three of the families discussed by Baumert have analogous constructions in non-cyclic groups. We extend his inequivalence statement to a general inequivalence result, for which we provide a complete and self-contained proof. We preface our proof with a survey of the four families of difference sets, since there seems to be some confusion in the literature between the cyclic and non-cyclic cases.
Providing QoS with the Deficit Table Scheduler

A key component for networks with Quality of Service (QoS) support is the egress link scheduling algorithm. An ideal scheduling algorithm implemented in a high-performance network with QoS support should satisfy two main properties: good end-to-end delay and implementation simplicity. Table-based schedulers try to offer a simple implementation and good latency bounds. Some of the latest proposals of network technologies, like Advanced Switching and InfiniBand, include in their specifications one of these schedulers. However, these table-based schedulers do not work properly with variable packet sizes, as is usually the case in current network technologies. We have proposed a new table-based scheduler, which we have called Deficit Table (DTable) scheduler, that works properly with variable packet sizes. Moreover, we have proposed a methodology to configure this table-based scheduler in such a way that it permits us to decouple the bounding between the bandwidth and latency assignments. In this paper, we thoroughly review the provision of QoS with the DTable scheduler and our configuration methodology, and evaluate the performance of our proposals in a multimedia scenario. Simulation results show that our proposals are able to provide a similar latency performance than more complex scheduling algorithms. Moreover, we show the advantages of our decoupling configuration methodology over the usual ways of configuring this kind of table-based schedulers.
Exploiting fast ethernet performance in multiplatform cluster environment

As the communication subsystem largely determines the overall performance and the characteristics of cluster systems, it must face diverging demands such as bandwidth, latency, quality of service and cost. In this paper we investigate the performance and improvement possibilities of a portable TCP/IP based communication subsystem that aims to integrate heterogeneous nodes. The cluster is built up from standard PCs connected with low-cost network, where nodes may have different processor speed, memory size and may even run different operating systems. We present and compare application level end-to-end latencies measured under different conditions varying the number of simultaneous connections, processing threads and the types of operating systems. Our experiments show that message latencies are overwhelmingly dominated by software overheads, which can be hidden or eliminated by different methods, thus PC clusters can take good advantage of the bandwidth of a Fast Ethernet connection even with smaller message sizes. Finally, based on the results, we draw the attention to a domain of inaccuracy of the standard communication models in PC cluster environment, and we suggest a new formula to describe the latency of concurrent message channels over the same medium.
VLSI architecture of HEVC intra prediction for 8K UHDTV applications

This paper presents an efficient VLSI architecture of intra prediction for 8K×4K HEVC decoder. It supports all 35 intra prediction modes and prediction sizes ranging from 4×4 to 64×64. This works proposed a Cyclic SRAM Banks based Parallel Reference Sample Fetching (CSB-PRSF), which guarantees enough reference samples for prediction and reduces the number of registers used for storing reference samples. To guarantee high throughput, 16 pixels are predicted by 4×4 Block Based Pipelining, and dependency between neighboring blocks is eliminated by Hybrid Data Forwarding and Block Reordering. This architecture is synthesized using 90nm technology and the maximum working frequency is 469 MHz, with 72.1K gates area. Running at 397MHz, the architecture can support 4320p@120fps HEVC intra decoding, with full modes and full sizes.
Fusing Multi-Stream Deep Networks for Video Classification

This paper studies deep network architectures to address the problem of video classification. A multi-stream framework is proposed to fully utilize the rich multimodal information in videos. Specifically, we first train three Convolutional Neural Networks to model spatial, short-term motion and audio clues respectively. Long Short Term Memory networks are then adopted to explore long-term temporal dynamics. With the outputs of the individual streams, we propose a simple and effective fusion method to generate the final predictions, where the optimal fusion weights are learned adaptively for each class, and the learning process is regularized by automatically estimated class relationships. Our contributions are two-fold. First, the proposed multi-stream framework is able to exploit multimodal features that are more comprehensive than those previously attempted. Second, we demonstrate that the adaptive fusion method using the class relationship as a regularizer outperforms traditional alternatives that estimate the weights in a "free" fashion. Our framework produces significantly better results than the state of the arts on two popular benchmarks, 92.2\% on UCF-101 (without using audio) and 84.9\% on Columbia Consumer Videos.
Comparative proteomics of inhaled silver nanoparticles in healthy and allergen provoked mice

Background Silver nanoparticles (AgNPs) have been associated with the exacerbation of asthma; however, the immunological basis for the adjuvant effects of AgNPs is not well understood. Objective The aim of the study reported here was to investigate the allergic effects of AgNP inhalation using proteomic approaches. Methods Allergen provoked mice were exposed to 33 nm AgNPs at 3.3 mg/m3. Following this, bronchoalveolar lavage fluid (BALF) and plasma were collected to determine protein profiles. Results In total, 106 and 79 AgNP-unique proteins were identified in the BALF of control and allergic mice, respectively. Additionally, 40 and 26 AgNP-unique proteins were found in the plasma of control and allergic mice, respectively. The BALF and plasma protein profiles suggested that metabolic, cellular, and immune system processes were associated with pulmonary exposure to AgNPs. In addition, we observed 18 proteins associated with systemic lupus erythematosus that were commonly expressed in both control and allergic mice after AgNP exposure. Significant allergy responses were observed after AgNP exposure in control and allergic mice, as determined by ovalbumin-specific immunoglobulin E. Conclusion Inhaled AgNPs may regulate immune responses in the lungs of both control and allergic mice. Our results suggest that immunology is a vital response to AgNPs.
Callers’ Experiences of Contacting a National Suicide Prevention Helpline

Background: Helplines are a significant phenomenon in the mixed economy of health and social care. Given the often anonymous and fleeting nature of caller contact, it is difficult to obtain data about their impact and how users perceive their value. This paper reports findings from an online survey of callers contacting Samaritans emotional support services. Aims: To explore the (self-reported) characteristics of callers using a national suicide prevention helpline and their reasons given for contacting the service, and to present the users’ evaluations of the service they received. Methods: Online survey of a self-selected sample of callers. Results: 1,309 responses were received between May 2008 and May 2009. There were high incidences of expressed suicidality and mental health issues. Regular and ongoing use of the service was common. Respondents used the service for complex and varied reasons and often as part of a network of support. Conclusions: Respondents reported high levels of satisfaction with the service and perceived contact to be helpful. Although Samaritans aims to provide a crisis service, many callers do not access this in isolation or as a last resort, instead contacting the organization selectively and often in tandem with other types of support.
The Translation of Attitudes into Verdicts

Attitudes toward the death penalty are consistently predictive of jurors' verdicts in criminal trials. Two studies were conducted to find out why. In Study 1, eligible jurors viewed a videotape showing conflicting testimony by a prosecution and defense witness in an assault case. "Death-qualified" subjects (those permitted to serve on capital juries) interpreted testimony in a manner more favorable to the prosecution than "excludable" subjects (those excluded from serving on juries in capital cases due to their opposition to the death penalty), suggesting that differing interpretations of evidence may mediate the relationship between attitudes toward the death penalty and verdicts. In Study 2, the same jurors indicated their reactions to a number of hypothetical situations in which a jury had convicted an innocent defendant or acquitted a guilty one. ~ qualified" subjects expressed tess regret concerning erroneous convictions and more regret concerning erroneous acquittals than "excludable" subjects. Theoretical interpretations of this pattern of results suggest that "death qualified" subjects may have a lower threshold of conviction than "excludable" subjects; thus the relationship between attitudes toward the death penalty and verdicts may also be mediated by differing thresholds of conviction.
Ability of Density Feature in Low-Dose Computed Tomography for Evaluating Screened Lung Tumor

To explore the diagnostic value of density features in lung tumor screened from low dose computed tomography (LDCT) with thin section. A computer-aided diagnosis (CAD) system was established to assist in defining tumor and density features. Forty-eight surgically confirmed tumors in 38 patients screened by thin-section LDCT were retrospectively enrolled in consecutive manner to examine the performance of this system. The confirmed surgical results included 29 malignant and 19 benign tumors. The pathology of malignancy were adenocarcinoma (AdCa, n=17) and adenocarcinoma in situ (AdIs, n=12). The benignancy included atypical adenomatous hyperplasia (AAH, n=11) and benign non-AAH (n=8). Of density features, tumor Entropy provided the best power to differentiate malignancy from benignancy (p<;0.001), and further to classify the 4-type histopathology (p<;0.001). Feature Entropy has limitation in differentiating AdIs from benign non-AAH, which can be improved using feature of tumor disappearance rate (TDR) and Mean. Entropy and TDR were determined to be best decisive factors in constructing the CAD prediction model, which predicted tumors between malignancy and benignancy with an Az of 0.913. Density features defined using CAD is useful to differentiate malignancy from benignancy of lung tumors screened using thin-section multi-detector LDCT, and further to predict histopathology.
UPSTREAM VOLATILITY IN THE SUPPLY CHAIN: THE MACHINE TOOL INDUSTRY AS A CASE STUDY

Cyclicality is a well‐known and accepted fact of life in market‐driven economies. Less well known or understood, however, is the phenomenon of amplification as one looks “upstream” in the industrial supply chain. We examine the amplification phenomenon and its implications through the lens of one upstream industry that is notorious for the intensity of the business cycles it faces: the machine tool industry. Amplification of demand volatility in capital equipment supply chains, e. g. , machine tools, is particularly large relative to that seen in distribution and component parts supply chains. We present a system dynamics simulation model to capture demand volatility amplification in capital supply chains. We explore the lead‐time, inventory, production, productivity, and staffing implications of these dynamic forces. Several results stand out. First, volatility hurts productivity and lowers average worker experience. Second, even though machine tool builders can do little to reduce the volatility in their order streams through choice of forecast rule, a smoother forecasting policy will lead companies to retain more of their skilled work force. This retention of skilled employees is often cited as one of the advantages that European and Japanese companies have had relative to their U. S. competitors. Our results suggest some insights for supply chain design and management: downstream customers can do a great deal to reduce the volatility for upstream suppliers through their choice of order forecast rule. In particular, companies that use smoother forecasting policies tend to impose less of their own volatility upon their supply base and may consequently enjoy system‐wide cost reduction.
Glucocorticoid receptor gene inactivation in dopamine-innervated areas selectively decreases behavioral responses to amphetamine

The meso-cortico-limbic system, via dopamine release, encodes the rewarding and reinforcing properties of natural rewards. It is also activated in response to abused substances and is believed to support drug-related behaviors. Dysfunctions of this system lead to several psychiatric conditions including feeding disorders and drug addiction. These disorders are also largely influenced by environmental factors and in particular stress exposure. Stressors activate the corticotrope axis ultimately leading to glucocorticoid hormone (GCs) release. GCs bind the glucocorticoid receptor (GR) a transcription factor ubiquitously expressed including within the meso-cortico-limbic tract. While GR within dopamine-innervated areas drives cocaine's behavioral responses, its implication in responses to other psychostimulants such as amphetamine has never been clearly established. Moreover, while extensive work has been made to uncover the role of this receptor in addicted behaviors, its contribution to the rewarding and reinforcing properties of food has yet to be investigated. Using mouse models carrying GR gene inactivation in either dopamine neurons or in dopamine-innervated areas, we found that GR in dopamine responsive neurons is essential to properly build amphetamine-induced conditioned place preference and locomotor sensitization. c-Fos quantification in the nucleus accumbens further confirmed defective neuronal activation following amphetamine injection. These diminished neuronal and behavioral responses to amphetamine may involve alterations in glutamate transmission as suggested by the decreased MK801-elicited hyperlocomotion and by the hyporeactivity to glutamate of a subpopulation of medium spiny neurons. In contrast, GR inactivation did not affect rewarding and reinforcing properties of food suggesting that responding for natural reward under basal conditions is preserved in these mice.
On Critical Linguistics

Critical linguistics, belonging to instrumental linguistics initiated by Halliday, uses linguistics theories, mainly utilizing Halliday' s systematic functional grammar, to analyzepublic text, to reveal the hidden ideology or power relationship, and to expound philosophy and linguistic foundation of critical linguistics, its view on language, text and context.
Risk Models of Operative Morbidities in 16,930 Critically Ill Surgical Patients Based on a Japanese Nationwide Database

Abstract The aim of the study was to evaluate preoperative variables predictive of lethal morbidities in critically ill surgical patients at a national level. There is no report of risk stratification for morbidities associated with mortality in critically ill patients with acute diffuse peritonitis (ADP). We examined data from 16,930 patients operated during 2011 and 2012 in 1546 different hospitals for ADP identified in the National Clinical Database of Japan. We analyzed morbidities significantly associated with operative mortality. Based on 80% of the population, we calculated independent predictors for these morbidities. The risk factors were validated using the remaining 20%. The operative mortality was 14.1%. Morbidity of any grade occurred in 40.2% of patients. Morbidities correlated with mortality, including septic shock, progressive renal insufficiency, prolonged ventilation >48 hours, systemic sepsis, central nervous system (CNS) morbidities, acute renal failure and pneumonia, and surgical site infection (SSI), were selected for risk models. A total of 18 to 29 preoperative variables were selected per morbidity and yielded excellent C-indices for each (septic shock: 0.851; progressive renal insufficiency: 0.878; prolonged ventilation >48 h: 0.849; systemic sepsis: 0.839; CNS morbidities: 0.848; acute renal failure: 0.868; pneumonia: 0.830; and SSI: 0.688). We report the first risk stratification study on lethal morbidities in critically ill patients with ADP using a nationwide surgical database. These risk models will contribute to patient counseling and help predict which patients require more aggressive surgical and novel pharmacological interventions.
Nature Genetics Advance Online Publication a N a Ly S I S the Support of Human Genetic Evidence for Approved Drug Indications

Over a quarter of drugs that enter clinical development fail because they are ineffective. Growing insight into genes that influence human disease may affect how drug targets and indications are selected. However, there is little guidance about how much weight should be given to genetic evidence in making these key decisions. To answer this question, we investigated how well the current archive of genetic evidence predicts drug mechanisms. We found that, among well-studied indications, the proportion of drug mechanisms with direct genetic support increases significantly across the drug development pipeline, from 2.0% at the preclinical stage to 8.2% among mechanisms for approved drugs, and varies dramatically among disease areas. We estimate that selecting genetically supported targets could double the success rate in clinical development. Therefore, using the growing wealth of human genetic data to select the best targets and indications should have a measurable impact on the successful development of new drugs. Attrition is a major challenge in drug discovery and development, with more than half of clinical studies failing because of lack of efficacy 1–4. The widespread failure of preclinical model systems to adequately predict efficacy in humans has led drug developers to look for other sources of evidence to inform decisions about which targets to pursue and for which indications (disease or reason for treatment for which a drug is approved). Since the completion of the Human Genome Project and the rise of genome-wide association studies (GWAS) and whole-genome and whole-exome sequencing studies, there has been rapid progress in identifying the genes that influence human health and disease 5. These genetic insights can potentially transform the process of selecting the best drug targets and indications 6 , the key decisions in drug discovery. There are several examples of genes associated with disease traits that have been proven to be effective drug targets. One canonical example is the target for statins, HMGCR, which has been associated with serum cholesterol levels 7. Several other examples were recently highlighted for rheumatoid arthritis 8. Such examples and the rapidly growing body of human genetic data led us to ask how much weight should be given to genetic associations when choosing which drug targets to pursue for a desired indication. RESULTS In this study, we go beyond previous work on drug repositioning 9 to investigate how well clinically successful drug mechanisms (the protein product modulated to elicit a clinical response) are predicted by …