Miracle-dz/UniFAR-FTUs huggingface dataset:
Hepatoprotective Effect of Herb Formula KIOM2012H against Nonalcoholic Fatty Liver Disease

Nonalcoholic fatty liver disease (NAFLD) is a hepatic ailment with a rapidly increasing incidence due to dietary hypernutrition and subsequent obesity. Fatty liver disease can lead to steatohepatitis, fibrosis, cirrhosis, and even cancer, which is associated with various complications. Discovering effective natural materials and herbs can provide alternative and complementary medical treatments to current chemical pharmaceuticals. To develop an effective natural agent for NAFLD, we formulated a combination of four herb mixtures (KIOM2012H) and observed lipid-lowering efficacy. The inhibitory effects of KIOM2012H on free fatty acid-induced lipid accumulation, triglyceride contents, and gene expressions were analyzed in HepG2 cells. Using high fat diet-fed mice, body weight changes, gross liver appearances, hepatic triglyceride contents, and gene expressions were evaluated. KIOM2012H dose-dependently inhibited lipid accumulation and gene expressions involved in lipogenesis and related regulators. Experimental animals also showed a decrease in body weight changes and lipid-associated physiological parameters. This study shows that KIOM2012H has an alleviating effect on fatty acid and lipid accumulation, and therefore can be applied for development of new therapeutic pharmaceuticals for treatment of NAFLD using natural products and herbs.
Multilingual Part-of-Speech Tagging: Two Unsupervised Approaches

We demonstrate the effectiveness of multilingual learning for unsupervised part-of-speech tagging. The central assumption of our work is that by combining cues from multiple languages, the structure of each becomes more apparent. We consider two ways of applying this intuition to the problem of unsupervised part-of-speech tagging: a model that directly merges tag structures for a pair of languages into a single sequence and a second model which instead incorporates multilingual context using latent variables. Both approaches are formulated as hierarchical Bayesian models, using Markov Chain Monte Carlo sampling techniques for inference. Our results demonstrate that by incorporating multilingual evidence we can achieve impressive performance gains across a range of scenarios. We also found that performance improves steadily as the number of available languages increases.
Data Selection and Procurement

Data Selection and Procurement In this note I overview the data selection and procurement process for structural models. Data selection for structural models presents unique challenges because it is imperative to consider the information that identifies causal effects of interest and because the institutional context has substantial ramification for the structure of the model. I discuss three types of field data upon which to build empirical models; data that are proprietary to firms and public data that can come from the public domain or be purchased from private research firms and the benefits and limits of each. I then detail a process for obtaining proprietary data and the potential pitfalls inherent in the process. “Now we really do have essentially free and ubiquitous data. So the complimentary scarce factor is the ability to understand that data and extract value from it. ” Varian (2009)
A multiprocessor DSP system using PADDI-2

We have integrated an image processing system built around PADDI-2, a custom 48 node MIMD parallel DSP. The system includes image processing algorithms, a graphical SFG tool, a simulator, routing tools, compilers, hardware configuration and debugging tools, application development libraries, and software implementations for hardware verification. The system board, connected to a SPARCstation via a custom Sbus controller, contains 384 processors in 8 VLSI chips. The software environment supports a multiprocessor system under development (VGI-1). The software tools and libraries are modular, with implementation dependencies isolated in layered encapsulations.
Patient-Specific Induced Pluripotent Stem Cells for SOD1-Associated Amyotrophic Lateral Sclerosis Pathogenesis Studies

The genetic reprogramming technology allows one to generate pluripotent stem cells for individual patients. These cells, called induced pluripotent stem cells (iPSCs), can be an unlimited source of specialized cell types for the body. Thus, autologous somatic cell replacement therapy becomes possible, as well as the generation of in vitro cell models for studying the mechanisms of disease pathogenesis and drug discovery. Amyotrophic lateral sclerosis (ALS) is an incurable neurodegenerative disorder that leads to a loss of upper and lower motor neurons. About 10% of cases are genetically inherited, and the most common familial form of ALS is associated with mutations in the SOD1 gene. We used the reprogramming technology to generate induced pluripotent stem cells with patients with familial ALS. Patient-specific iPS cells were obtained by both integration and transgene-free delivery methods of reprogramming transcription factors. These iPS cells have the properties of pluripotent cells and are capable of direct differentiation into motor neurons.
Online and Offline Social Participation and Social Poverty Traps: Can Social Networks Save Human Relations?

In this study, we develop an evolutionary game model to analyze how human relations evolve in a context characterized by declining face-to-face interactions and growing online social participation. Our results suggest that online networks may constitute a coping response allowing individuals to “defend” their social life from increasing busyness and a reduction in the time available for leisure. Internet-mediated interaction can play a positive role in preventing the disruption of ties and the weakening of community life documented by empirical studies. In this scenario, the digital divide is likely to become an increasingly relevant factor of social exclusion, which may exacerbate inequalities in well-being and capabilities.
VET leadership for the future – characteristics, contexts and capabilities

This paper examines leadership in Australia’s vocational education and training (VET) sector. VET leaders make a vital and growing contribution to learners, industry and society, yet research on their work is limited. This has direct implications for ensuring leadership is most effective, and for framing evidence-based capacity development. The current research draws together reviews of complex and often competing contexts, analyses of prior research, and results from a national survey of 327 practising VET leaders. Analysis of what VET leaders report doing in their jobs suggests that while they are attuned to the education-focused demands of their roles, they now need new capabilities to respond to internal and external developments. To identify the powerful forces which shape leadership, the study established criteria seen to mark out effective performance in each role. It highlighted a set of indicators identified by VET leaders as those most important in making judgements about the effective delivery of each role. Identifying indicators of effective performance is important, as it is these which, ideally, drive leaders’ aspirations and behaviours. The future capacity of VET in Australia will be underpinned by the capability and regeneration of its leadership. New programmes need to focus on concrete ‘change management’ skills, working through complex real-world problems and leading change in ambiguous environments. The more authentic and active modes of learning were advocated by VET leaders, who expressed an overwhelming preference for practice-based and self-managed, as opposed to formal, forms of professional learning.
An Algorithmic Introduction to Numerical Simulation of Stochastic Differential Equations

A practical and accessible introduction to numerical methods for stochastic differential equations is given. The reader is assumed to be familiar with Euler's method for deterministic differential equations and to have at least an intuitive feel for the concept of a random variable; however, no knowledge of advanced probability theory or stochastic processes is assumed. The article is built around $10$ MATLAB programs, and the topics covered include stochastic integration, the Euler--Maruyama method, Milstein's method, strong and weak convergence, linear stability, and the stochastic chain rule.
Chasing after Non-cyanobacterial Nitrogen Fixation in Marine Pelagic Environments

Traditionally, cyanobacterial activity in oceanic photic layers was considered responsible for the marine pelagic dinitrogen (N2) fixation. Other potentially N2-fixing bacteria and archaea have also been detected in the pelagic water column, however, the activity and importance of these non-cyanobacterial diazotrophs (NCDs) remain poorly constrained. In this perspective we summarize the N2 fixation rates from recently published studies on photic and aphotic layers that have been attributed to NCD activity via parallel molecular measurements, and discuss the status, challenges, and data gaps in estimating non-cyanobacterial N2 fixation NCNF in the ocean. Rates attributed to NCNF have generally been near the detection limit thus far (<1 nmol N L−1 d−1). Yet, if considering the large volume of the dark ocean, even low rates of NCNF could make a significant contribution to the new nitrogen input to the ocean. The synthesis here shows that nifH transcription data for NCDs have been reported in only a few studies where N2 fixation rates were detected in the absence of diazotrophic cyanobacteria. In addition, high apparent diversity and regional variability in the NCDs complicate investigations of these communities. Future studies should focus on further investigating impacts of environmental drivers including oxygen, dissolved organic matter, and dissolved inorganic nitrogen on NCNF. Describing the ecology of NCDs and accurately measuring NCNF rates, are critical for a future evaluation of the contribution of NCNF to the marine nitrogen budget.
Defining Surgical Therapy for Pseudomembranous Colitis With Toxic Megacolon

Background Pseudomembranous colitis has increased in incidence and severity over the past 10 years. Toxic megacolon is a rare but reported presentation of severe pseudomembranous colitis. This article reviews the reported cases of Clostridium difficile with toxic megacolon in the literature and introduces an additional case that underscores the importance of early diagnosis in guiding appropriate therapy. Methods A systematic review of the literature was performed to identify previous reports of pseudomembranous colitis presenting with toxic megacolon, and the outcomes of each of these cases was analyzed. The review was focused on atypical presentations in immunocompromised patients. Results Seventeen cases of C. difficile colitis presenting as toxic megacolon were identified. The overall mortality rate was 50% (9/18). Fifteen patients underwent surgery with an associated mortality rate of 50%. Thirteen patients had a subtotal colectomy. Seven of the patients (39%) were taking immunosuppressant medications, and 5 (28%) patients presented with atypical symptoms. Three (76%) of those were immunosuppressed. In several cases, failure to make an early diagnosis of C. difficile colitis resulted in a worse outcome because appropriate therapy was delayed. Conclusions Toxic megacolon is well-established as an unusual presentation of C. difficile colitis. These patients are less likely to present with typical symptoms such as diarrhea or typical risk factors like recent administration of antibiotics, so diagnosis can be a challenge. A patient presenting with toxic megacolon without a history of inflammatory bowel disease should be assumed to have C. difficile colitis until proven otherwise, and medical or surgical therapy administered accordingly.
Essentials of Nonverbal Assessment

Chapter 1. Overview: Assessing Diverse Populations with Nonverbal Tests of Intelligence Chapter 2. Unidimensional Nonverbal Tests. Chapter 3. Multidimensional Nonverbal Intelligence Tests: Administration, Scoring,and Interpretation of the UNIT. Chapter 4. Multidimensional Nonverbal Intelligence Tests: Strenghts and Weaknessesand Clinical Applications of the UNIT. Chapter 5. Multidimensional Nonverbal Intelligence Tests: Administration, Scoring,and Interpretation of the Leiter-R. Chapter 6. Multidimensional Nonverbal Intelligence Tests: Strenghts and Weaknessesand Clincial Applications of the Leiter-R.
The Juvenile Intervention Program: Results of the Process, Impact and Outcome Evaluations

Data were analyzed for a random sample of sixty-four juvenile participants who completed the program between January 1, 1977 and April, 1978 and a random sample of forty-seven juvenile participants who completed the program between May, 1978 and August, 1979. In order to assess program impact, all the juvenile participants are administered a pretest during the first JIP session and a posttest after the last session. Follow-up data on impact measures are collected six months after program completion. In addition, participants are asked to complete a one-page questionnaire assessing their participation at the completion of each of the seven JIP sessions. Analysis of the data indicates that the program positively affected family communication patterns, self-esteem levels and drug knowledge levels at follow-up. The follow-up data indicated that drug-related school system and drug-related criminal justice system contacts were significantly reduced. The data also indicated that there was a reduction in drug usage by regular users for selected drugs.
Cooperative Anomaly and Intrusion Detection for Alert Correlation in Networked Computing Systems

Network-centric computing systems manifest as Grids, clusters, Intranets, LANs, or P2P networks, etc. These distributed systems are subject to security breaches in an open network environment. Conventional intrusion detection systems (IDS) use the misuse model at the packet level. An anomaly detection system (ADS) follows a normal-use model at Internet connection level. We integrate these two alert systems into a Cooperative Anomaly and Intrusion Detection System (CAIDS). This integrated system detects not only known attacks but also unknown anomalies. The system integration is enabled by Internet episode datamining, anomaly classification, alert correlation, and automated signature generation. We have tested the CAIDS performance at USC with an Internet trace of 23.35 millions of traffic packets, intermixed with 200 attacks from the Lincoln Lab IDS dataset. We achieved a combined detection rate up to 75% at a false alarm rate lower than 5%. These results are sharply improved from 38% in using the network IDS Snort and from 50% in using the ADS alone. Our system detects many novel attacks hidden in telnet, http, ftp, smtp, Email, pop3, and authentication services. The CAIDS offers correlated alerts to intrusions on distributed hosts or anomalies with disrupted connectivity in the component networks.
The DbpA catalytic core unwinds double-helix substrates by directly loading on them

DbpA is a DEAD-box RNA helicase implicated in the assembly of the large ribosomal subunit. Similar to all the members of the DEAD-box family, the DbpA protein has two N-terminal RecA-like domains, which perform the RNA unwinding. However, unlike other members of this family, the DbpA protein also possesses a structured C-terminal RNA-binding domain that mediates specific tethering of DbpA to hairpin 92 of the Escherichia coli 23S ribosomal RNA. Previous studies using model RNA molecules containing hairpin 92 show that the RNA molecules support the DbpA protein's double-helix unwinding activity, provided that the double helix has a 3′ single-stranded region. The 3′ single-stranded region was suggested to be the start site of the DbpA protein's catalytic unwinding activity. The data presented here demonstrate that the single-stranded region 3′ of the double-helix substrate is not required for the DbpA protein's unwinding activity and the DbpA protein unwinds the double-helix substrates by directly loading on them.
Graphs in compilation (poster)

Traditionally, inside compilers, expression trees are used as an internal representation of functional programs. A big disadvantage of trees is the w of explicit variable names in expressions. When expression trees are transformed to optimize a program [5], we end up doing a lot of administration on the variables. Aleo, substitution of variables is a costly and awkward operation. Variable names create an extra indirection we do not want, but still have to deal with.
Efficient Memoryless Cordic for FFT Computation

A new memoryless CORDIC algorithm for the FFT computation is proposed in this paper. This approach calculates the direction of the micro-rotations from the control counter of the FFT, so the area of the rotator hardly depends on the number of rotations, which is particularly suitable for the computation of FFTs of a high number of points. Moreover, the new CORDIC presents other advantages such as the simplification of the basic CORDIC processor used to calculate the micro-rotations, or an easy way to compensate the intrinsic gain of the CORDIC algorithm. Additionally, the VLSI implementation of the algorithm is a pipeline architecture with high performance in terms of speed, throughput and latency.
An X-ray selected sample of radio-loud quasars

We construct the first X-ray selected sample of broad line radio-loud AGN from the EMSS survey. In order to test unifying schemes for radio-loud objects, their spectral and statistical properties (both flat and steep spectrum objects) are examined and compared with those of other samples of blazars. The X-ray selection allows us to explore properties of radio-loud quasars 10-100 weaker in the radio band than classical samples. The most convincing interpretation of our results is that there are no radio-loud quasars whose synchrotron emission peak reaches the EUV-soft X-ray band at these (radio) flux levels. Moreover, due to the comparatively weak non-thermal emission, a quasi-thermal component appears to contribute at optical-UV energies. The detection of sources at low radio fluxes also reveals a large population of steep spectrum quasars and the lack of the predicted turnover in the quasar (radio) counts. The evolution of X-ray selected radio-loud quasars does not significantly differ from that of radio-selected ones, and flat spectrum and steep spectrum sources appear to behave quite similarly.
Interaction between the human nuclear cap-binding protein complex and hnRNP F

hnRNP F was identified in a screen for proteins that interact with human CBP80 and CBP20, the components of the nuclear cap-binding complex (CBC). In vitro interaction studies showed that hnRNP F can bind to both CBP20 and CBP80 individually. hnRNP F and CBC bind independently to RNA, but hnRNP F binds preferentially to CBC-RNA complexes rather than to naked RNA. The hnRNP H protein, which is 78% identical to hnRNP F and also interacts with both CBP80 and CBP20 in vitro, does not discriminate between naked RNA and CBC-RNA complexes, showing that this effect is specific. Depletion of hnRNP F from HeLa cell nuclear extract decreases the efficiency of pre-mRNA splicing, a defect which can be partially compensated by addition of recombinant hnRNP F. Thus, hnRNP F is required for efficient pre-mRNA splicing in vitro and may participate in the effect of CBC on pre-mRNA splicing.
MetaAnn: Um Gerador de Ferramentas para Anotação de Textos (MetaAnn: a Generator of Text Annotation Tools) [in Portuguese]

With the growing use of corpora in the field of Computational Linguistics, so increases the need for tools that are able to annotate these corpora. These tools, however, are generally aimed at the application of very specific annotation schemes, so that different schemes require the development of specific tools. The use of general tools, on the other hand, brings in extra complexity that is undesirable for the task. In this paper, this subject is approached by introducing the prototype of a meta-tool for generating the Java source code of ad hoc annotation tools, thereby retaining the advantages of a general tool, but without the cost in complexity that it brings to the task. Resumo. Com o crescimento do uso de corpora no campo da Linguı́stica Computacional, aumenta também a necessidade de haver ferramentas capazes de anotar esses corpora. Essas ferramentas, no entanto, em geral são construı́das para a aplicação de esquemas de anotação bem especı́ficos, fazendo com que diferentes esquemas exijam o desenvolvimento de diferentes ferramentas. O uso de ferramentas gerais, por outro lado, traz consigo uma complexidade extra que não é desejável à tarefa. Nesse artigo, essa questão é abordada através da apresentação do protótipo de uma meta-ferramenta capaz de gerar código-fonte Java de ferramentas de anotação ad hoc, mantendo assim as vantagens de uma ferramenta geral, mas sem o custo em complexidade que esta traz à tarefa.
Identification of brachyspina syndrome carriers in Chinese Holstein cattle

Brachyspina syndrome (BS) is a rare monogenic autosomal recessive hereditary disorder identified in the Holstein breed caused by a 3.3-kb deletion in the bovine Fanconi anemia complementation group I (FANCI) gene on chromosome 21. In previous reports, the BS mutant allele was identified in North American and European Holstein populations. Because frozen semen and embryos have been imported into China from such regions during the past few years, BS has potentially spread into the dairy cattle population in China. In the present study, 206 Holstein bulls and 136 Holstein cows were tested for BS, with 10 BS carrier bulls and 3 carrier cows identified. Pedigree analysis showed that all 10 BS carrier bulls could be traced back to a common ancestor, the U.S. Holstein sire Sweet Haven Tradition. It is recommended that effective selection and mating strategies should be carried out to gradually eliminate this recessive gene from the Chinese Holstein population.
The Value of Resource Flexibility in the Resource - Constrained Job Assignment Problem

We consider the problem of minimizing project duration in an environment where each project activity can be executed by a number of different flexible resources. The capabilities of the flexible resources are modeled using a binary activity-resource matrixA called theavailability matrix. Activity durations are known deterministically. We develop tight lower bounds and a variety of heuristics accompanied with extensive computational tests regarding their performance. It is shown that our algorithms consistently perform near optimally. Using these heuristics, we perform experiments on the effect of operating flexibility on project duration, where resource flexibility is measured by the number of resources available per activity, and the form of the availability matrixA. Our experiments lead to important managerial guidelines regarding the role of resource flexibility on project duration. For instance, it is found that when the flexible capabilities of the resources are evenly distributed across the activities, small improvements in resource flexibilities provide nearly the same benefits in project duration as a system of fully flexible resources.