Miracle-dz/UniFAR-FTUs huggingface dataset:
Automatic generation of application specific processors

An application-specific instruction-set processor (ASIP) is ideally suited for embedded applications that have demanding performance, size, and power requirements that cannot be satisfied by a general purpose processor. ASIPs also have time-to-market and programmability advantages when compared to custom ASICs. The AutoTIE system simplifies the creation of ASIPs by automatically enhancing a base processor with application specific instruction set architecture (ISA) extensions, including instructions, operations, and register files. The new instructions, operations, and register files are automatically recognized and exploited by the entire software tool chain, including the C/C++ compiler. Thus, taking advantage of the generated ASIP does not require any changes to the application or any assembly language coding. AutoTIE uses the C/C++ compiler to analyze an application, and based on the analysis generates thousands, or even millions, of possible ISA extensions for the application. AutoTIE then uses performance and hardware estimation techniques to combine the ISA extensions into a large number of potential ASIPs, and for a range of hardware costs, chooses the ASIP that provides the maximum performance improvement. For example, for an application performing a radix-4 FFT, AutoTIE considers over 34,000 potential sets of ISA extensions. For hardware costs ranging from 7800 gates to 128,000 gates, AutoTIE combines these extensions to form 31 ASIPs, which provide performance improvements ranging from a factor of 1.12 to a factor of 11.3 compared to a general-purpose processor.
Availability of Ectomycorrhizal Fungi to Black Spruce above the Present Treeline in Eastern Labrador

Ectomycorrhizal fungi (ECMF) are an important biotic factor in the survival of conifer seedlings under stressful conditions and therefore have the potential to facilitate conifer establishment into alpine and tundra habitats. In order to assess patterns of ectomycorrhizal availability and community structure above treeline, we conducted soil bioassays in which Picea mariana (black spruce) seedlings were grown in field-collected soils under controlled conditions. Soils were collected from distinct alpine habitats, each dominated by a different ectomycorrhizal host shrub: Betula glandulosa, Arctostaphylos alpina or Salix herbacaea. Within each habitat, half of the soils collected contained roots of ectomycorrhizal shrubs (host+) and the other half were free of host plants (host−). Forest and glacial moraine soils were also included for comparison. Fungi forming ectomycorrhizae during the bioassays were identified by DNA sequencing. Our results indicate that ECMF capable of colonizing black spruce are widespread above the current tree line in Eastern Labrador and that the level of available inoculum has a significant influence on the growth of seedlings under controlled conditions. Many of the host− soils possessed appreciable levels of ectomycorrhizal inoculum, likely in the form of spore banks. Inoculum levels in these soils may be influenced by spore production from neighboring soils where ectomycorrhizal shrubs are present. Under predicted temperature increases, ectomycorrhizal inoculum in soils with host shrubs as well as in nearby soils without host shrubs have the potential to facilitate conifer establishment above the present tree line.
The Effect of Positive Psychology Interventions in Clinical Samples with Psychiatric Disorders on Well-Being and Psychiatric Symptoms: A Systematic Literature Review

Background: Research on positive psychological interventions [PPIs] suggests significant but small to medium effects on mental health in non-clinical samples, yet data is inconclusive whether PPIs are beneficial for clinical samples. The aim of this systematic literature review is to describe the effects of PPIs in clinical samples with psychiatric disorders on well-being and psychiatric symptoms (depression, anxiety, stress). Methods: A systematic literature review was performed following PRISMA guidelines. The study quality was assessed using the Jadad scale and the Cochrane Collaboration’s tool for assessing risk of bias. The PPIs were recoded into the five elements from Seligman’s well-being theory (PERMA). Lastly, Pearson’s bivariate correlation coefficients were calculated and tested for statistical significance between the sum of the PERMA elements and the effect sizes. Results: The included 15 studies (N = 950) displayed different psychiatric disorders (depression being most frequent), sample groups (489 in PPIs, 461 in control), ages (M = 40.29, range = [18; 68]) and PPI components. For increasing well-being 14 of the 15 studies reported small to large effect sizes (range = [0.15; 1.81]), 13 of the 15 for reducing symptoms of depression (range = [0.12; 2.13]), 8 out of 8 for anxiety (range = [0.30; 2.53]) and 4 out of 5 for stress (range = [0.38; 1.40]). The sum of the PERMA elements was not associated with the effect size of any outcome measure (well-being, depression, anxiety, stress). All used studies were of low or medium quality. Conclusion: PPIs seem to be innovative and for many patients with psychiatric disorders effective. The patients benefit in increased well-being and reduced pathological symptoms. Further, the applicability of the PERMA model appears to be a fitting paradigm to describe well-being but is not a necessity for the function of PPIs in clinical samples. It may be time to explore the applicability of PPIs as complementary programs to psychotherapy by practitioners to garner more practical insights and further the scientific efforts.
Stringent V beta requirement for the development of NK1.1+ T cell receptor-alpha/beta+ cells in mouse liver

The liver of C57BL/6 mice contains a major subset of CD4+8- and CD4-8- T cell receptor (TCR)-alpha/beta+ cells expressing the polymorphic natural killer NK1.1 surface marker. Liver NK1.1+TCR-alpha/beta+ (NK1+ T) cells require interaction with beta2-microglobulin-associated, major histocompatibility complex I-like molecules on hematopoietic cells for their development and have a TCR repertoire that is highly skewed to Vbeta8.2, Vbeta7, and Vbeta2. We show here that congenic C57BL/6.Vbeta(a) mice, which lack Vbeta8- expressing T cells owing to a genomic deletion at the Vbeta locus, maintain normal levels of liver NK1+ T cells owing to a dramatic increase in the proportion of cells expressing Vbeta7 and Vbeta2 (but not other Vbetas). Moreover, in C57BL/6 congenic TCR-V Vbeta3 and -Vbeta8.1 transgenic mice (which in theory should not express other Vbeta, owing to allelic exclusion at the TCR-beta locus), endogenous TCR-Vbeta8.2, Vbeta7, and Vbeta2 (but not other Vbetas) are frequently expressed on liver NK1+T cells but absent on lymph node T cells. Finally, when endogenous V beta expression is prevented in TCR-Vbeta3 and Vbeta8.1 transgenic mice (by introduction of a null allele at the C beta locus), the development of liver NK1+T cells is totally abrogated. Collectively, our data indicate that liver NK1+T cells have a stringent requirement for expression of TCR-Vbeta8.2, Vbeta7, or Vbeta2 for their development.
Genome scan methods against more complex models: when and how much should we trust them?

The recent availability of next‐generation sequencing (NGS) has made possible the use of dense genetic markers to identify regions of the genome that may be under the influence of selection. Several statistical methods have been developed recently for this purpose. Here, we present the results of an individual‐based simulation study investigating the power and error rate of popular or recent genome scan methods: linear regression, Bayescan, BayEnv and LFMM. Contrary to previous studies, we focus on complex, hierarchical population structure and on polygenic selection. Additionally, we use a false discovery rate (FDR)‐based framework, which provides an unified testing framework across frequentist and Bayesian methods. Finally, we investigate the influence of population allele frequencies versus individual genotype data specification for LFMM and the linear regression. The relative ranking between the methods is impacted by the consideration of polygenic selection, compared to a monogenic scenario. For strongly hierarchical scenarios with confounding effects between demography and environmental variables, the power of the methods can be very low. Except for one scenario, Bayescan exhibited moderate power and error rate. BayEnv performance was good under nonhierarchical scenarios, while LFMM provided the best compromise between power and error rate across scenarios. We found that it is possible to greatly reduce error rates by considering the results of all three methods when identifying outlier loci.
Latent Confusion Analysis by Normalized Gamma Construction

We developed a flexible framework for modeling the annotation and judgment processes of humans, which we called "normalized gamma construction of a confusion matrix. " This framework enabled us to model three properties: (1) the abilities of humans, (2) a confusion matrix with labeling, and (3) the difficulty with which items are correctly annotated. We also provided the concept of "latent confusion analysis (LCA)," whose main purpose was to analyze the principal confusions behind human annotations and judgments. It is assumed in LCA that confusion matrices are shared between persons, which we called "latent confusions", in tribute to the "latent topics" of topic modeling. We aim at summarizing the workers' confusion matrices with the small number of latent principal confusion matrices because many personal confusion matrices is difficult to analyze. We used LCA to analyze latent confusions regarding the effects of radioactivity on fish and shellfish following the Fukushima Daiichi nuclear disaster in 2011.
) , 000 – 000 Van der Corput Sequences Towards General ( 0 , 1 ) – Sequences in Base b par

As a result of recent studies on unidimensional low discrepancy sequences, we can assert that the original van der Corput sequences are the worst distributed with respect to various measures of irregularities of distribution among two large families of (0, 1)–sequences, and even among all (0, 1)–sequences for the star discrepancy D∗. We show in the present paper that it is not the case for the extreme discrepancy D by producing two kinds of sequences which are the worst distributed among all (0, 1)–sequences, with a discrepancy D essentially twice greater. In addition, we give an unified presentation for the two generalizations presently known of van der Corput sequences.
Load demand Sharing using multiple distributed generation units for the operation of microgrids to realize satisfied power sharing

The important task for the operation of autonomous micro grids, is to share the load demand using multiple distributed generation units. In this paper to realize satisfied power sharing without the communication between DG units, the voltage droop control and its different variations have been proposed. Generally, in a low- voltage micro grids, due to the effects of feeder impedance, the droop control is subject to the real and reactive power coupling and steady-state reactive power sharing errors. The complex micro grid configurations often make the reactive power sharing more challenging. To improve the reactive power sharing accuracy an enhanced control strategy that estimates the reactive power control error through injecting small real power disturbances, which is activated by the low-bandwidth synchronization signals from the central controller The proposed compensation method achieves accurate reactive power sharing at the steady state. Simulation and experimental results validate the feasibility of the proposed method.
Method comparison of automated matching software-assisted cone-beam CT and stereoscopic kilovoltage x-ray positional verification image-guided radiation therapy for head and neck cancer: a prospective analysis

We sought to characterize interchangeability and agreement between cone-beam computed tomography (CBCT) and digital stereoscopic kV x-ray (KVX) acquisition, two methods of isocenter positional verification currently used for IGRT of head and neck cancers (HNC). A cohort of 33 patients were near-simultaneously imaged by in-room KVX and CBCT. KVX and CBCT shifts were suggested using manufacturer software for the lateral (X), vertical (Y) and longitudinal (Z) dimensions. Intra-method repeatability, systematic and random error components were calculated for each imaging modality, as were recipe-based PTV expansion margins. Inter-method agreement in each axis was compared using limits of agreement (LOA) methodology, concordance analysis and orthogonal regression. 100 daily positional assessments were performed before daily therapy in 33 patients with head and neck cancer. Systematic error was greater for CBCT in all axes, with larger random error components in the Y- and Z-axis. Repeatability ranged from 9 to 14 mm for all axes, with CBCT showing greater repeatability in 2/3 axes. LOA showed paired shifts to agree 95% of the time within ±11.3 mm in the X-axis, ±9.4 mm in the Y-axis and ±5.5 mm in the Z-axis. Concordance ranged from ‘mediocre’ to ‘satisfactory’. Proportional bias was noted between paired X- and Z-axis measures, with a constant bias component in the Z-axis. Our data suggest non-negligible differences in software-derived CBCT and KVX image-guided directional shifts using formal method comparison statistics. A correction was made to the first line of page 7404 of this article on 26 November 2009. The corrected electronic version is identical to the print version.
Video Summarization with SOMs

Video summarization is a process where a long video file is converted to a considerably shorter form. The video summary can then be used to facilitate efficient searching and browsing of video files in large video collec- tions. The aim of successful automatic summarization is to preserve as much as possible from the essential content of each video. What is essential is subjective and dependent on the use of the videos and the overall content of the col- lection. In this paper we present an overview of the SOM- based methodology we have used for video summarization. The method uses temporal trajectories of the best-matching units of frame-wise feature vectors for shot boundary de- tection and shot similarity assessment. The video mate- rial we have used in our experiments comes from NIST's annual TRECVID evaluation for content-based video re- trieval systems.
The Minimal Persuasive Effects of Campaign Contact in General Elections: Evidence from 49 Field Experiments

Significant theories of democratic accountability hinge on how political campaigns affect Americans’ candidate choices. We argue that the best estimate of the effects of campaign contact and advertising on Americans’ candidates choices in general elections is zero. First, a systematic meta-analysis of 40 field experiments estimates an average effect of zero in general elections. Second, we present nine original field experiments that increase the statistical evidence in the literature about the persuasive effects of personal contact tenfold. These experiments’ average effect is also zero. In both existing and our original experiments, persuasive effects only appear to emerge in two rare circumstances. First, when candidates take unusually unpopular positions and campaigns invest unusually heavily in identifying persuadable voters. Second, when campaigns contact voters long before election day and measure effects immediately—although this early persuasion decays. These findings contribute to ongoing debates about how political elites influence citizens’ judgments.
Boundary conditions in charge conjugate sl(N) WZW theories

We compute the representations (``nimreps'') of the fusion algebra of affine sl(N), which determine the boundary conditions of sl(N) WZW theories twisted by the charge conjugation. This is done following two procedures, one of general validity, the other specific to the problem at hand. The problem is related to the classical problem of decomposition of the fundamental representations of sl(N) onto representations of $B_l=so(2l+1)$ or $C_l =sp(2l)$ algebras. The relevant nimreps and their diagonalisation matrix are thus expressed in terms of modular data of the affine B or C algebras
The effect of destination image, event image, and satisfaction in determining behavioral intention

The purpose of this study was to expand knowledge of sport tourists’ behavioral intention at recurring small-scale event (i.e., marathons) by analyzing several important factors: destination image, event image, and satisfaction. Data were collected from 297 sport tourists (176 from the Mercedes-Benz Marathon Event, 121from the Publix Marathon Event). The results revealed that destination image, event image, and satisfaction positively influenced behavioral intention. The results also indicated that satisfaction partially mediated the relationship between two images (i.e., destination image and event image) and behavioral intention. Lastly, the results supported that previous visit experience only moderated the relationship between destination image and behavioral intention. The theoretical and practical implications of these findings are discussed, and suggestions for future direction are detailed. INDEX WORDS: Sport Tourism; Recurring Small-Scale Event; Destination Image; Event Image; Satisfaction; Behavioral Intention THE EFFECT OF DESTINATION IMAGE, EVENT IMAGE, AND SATISFACTION IN DETERMINING BEHAVIORAL INTENTION: RECURRING SMALL-SCALE EVENT
“The quickest transshipment problem”

A dynamic network consists of a graph with capacities and transit times on its edges. The quickest transshipment problem is defined by a dynamic network with several sources and sinks; each source has a specified supply and each sink has a specified demand. The problem is to send exactly the right amount of flow out of each source and into each sink in the minimum overall time. Variations of the quickest transshipment problem have been studied extensively; the special case of the problem with a single sink is commonly used to model building evacuation. Similar dynamic network flow problems have numerous other applications; in some of these, the capacities are small integers and it is important to find integral flows. There are no polynomial-time algorithms known for most of these problems. In this paper we give the first polynomial-time algorithm for the quickest transshipment problem. Our algorithm provides an integral optimum flow. Previously, the quickest transshipment problem could only be solved efficiently in the special case of a single source and single sink.
Stored Osteoarticular Allografts Clinical , Histologic , and Radiographic Outcomes of Distal Femoral Resurfacing With

1082 Full-thickness cartilage loss in the knee is a difficult clinical problem, especially in young patients. Defects involving loss of subchondral bone are particularly challenging to treat in this population. Osteochondral allograft transplantation is one option currently used to address these lesions (Figure 1). This study focuses on the clinical, radiographic, and histologic outcome of large osteoarticular allografts stored 4 to 6 weeks. Osteochondral allograft transplantation should be considered in the context of a comprehensive treatment algorithm for addressing chondral damage, as well as con-comitant lesions, in the injured knee. Treatment of the Background: Fresh osteoarticular allograft transplantation has a long history of clinical success. These grafts have typically been implanted less than 1 week from donor asystole.
Meta-Analysis of the SLCO1B1 c.521T>C Variant Reveals Slight Influence on the Lipid-Lowering Efficacy of Statins

Background Several studies have focused on the association between the lipid-lowering efficacy of statins and the SLCO1B1 c.521T>C polymorphism; however, the results are conflicting. The effects of statins show significant variability between individuals. This meta-analysis aimed to investigate the effects of the SLCO1B1 c.521T>C polymorphism on the lipid-lowering effects of statins. Methods We systematically searched PubMed and Web of Science to screen relevant studies. Meta-analysis was performed to identify the association between SLCO1B1 c.521 polymorphisms and the lipid-lowering effects of statinson the basis of the standard mean difference (SMD) and 95% confidence intervals (CIs). Additionally, we checked for heterogeneity (I2) among studies and evidence of publication bias. We obtained eight studies including 2,012 wild genotype (T/T) and 526 variant genotype (T/C and C/C) cases. Results No significant difference was observed in the lipid-lowering efficacy of statins between the wildand variant genotypes of SLCO1B1, with a pooled SMD of 0.03 (95% CI: -0.07-0.13). Furthermore, there was no significant effect in the meta-analyses of the variant heterozygote, homozygote, and Chinese populations. Subgroup meta-analysis indicated that the timerequired for the statin to take effectdid notsignificantly affect the association between lipid-lowering efficacy of statins and SLCO1B1 c.521T>C polymorphism. However, thewild genotype improved the lipid-lowering efficacy of simvastatin with a pooled SMD of -0.26 (95% CI: -0.47- -0.05). Conclusions No significant association was detected between the lipid-lowering efficacy of statins and the SLCO1B1 c.521T>C polymorphism, with the exception of simvastatin.
Towards feature selection in network

Traditional feature selection methods assume that the data are independent and identically distributed (i.i.d.). However, in real world, there are tremendous amount of data which are distributing in a network. Existing features selection methods are not suited for networked data because the i.i. d. assumption no longer holds. This motivates us to study feature selection in a network. In this paper, we present a supervised feature selection method based on Laplacian Regularized Least Squares (LapRLS) for networked data. In detail, we use linear regression to utilize the content information, and adopt graph regularization to consider the link information. The proposed feature selection method aims at selecting a subset of features such that the empirical error of LapRLS is minimized. The resultant optimization problem is a mixed integer programming, which is difficult to solve. It is relaxed into a $L_{2,1}$-norm constrained LapRLS problem and solved by accelerated proximal gradient descent algorithm. Experiments on benchmark networked data sets show that the proposed feature selection method outperforms traditional feature selection method and the state of the art learning in network approaches.