Miracle-dz/UniFAR-FTUs huggingface dataset:
A multi-institutional double-blind phase II study evaluating response and surrogate biomarkers to carboplatin and nab-paclitaxel (CP) with or without vorinostat as preoperative systemic therapy (PST) in HER2-negative primary operable breast cancer (TBCRC008).

TPS111 Background: Traditionally, systemic treatment recommendations for women with breast cancer have been based on clinicopathologic factors following definitive surgery. PST allows for improved surgical outcomes and assessment of response without compromising long- term outcomes. Chemotherapy is currently the most effective treatment for women with triple-negative (ER-, PR-, HER2-) or luminal type B breast cancers. Many women suffer recurrence and death despite optimal chemotherapy, emphasizing the need for new strategies. Epigenetic modifiers may sensitize tumors to chemotherapy and enhance outcomes. We hypothesized that preoperative CP combined with the histone deacetylase inhibitor vorinostat is a better option than CP alone in women with triple-negative or luminal type B breast cancer who are candidates for PST. Methods: This study includes both a run-in phase to investigate the safety of 12 weekly doses of C (AUC 2) and P (100 mg/m2) with vorinostat 400mg po daily (first 3 out of every 7 days) in .
Psychological problem self-measurement in serviceman

Objective:To analyze the characteristics of psychological problem and its influence factors in serviceman.Methods:A total of 362 serviceman were measured with SCL 90, and the state of body,cognition,emotion and social function, etc . were analyzed.Results:(1) The grand mean,positive items,positive symptom mean,partial factorial score of serviceman were higher than that of normal Chinese;(2) The factors influencing psychological health of serviceman included education,only child,environment,single family and so on. (3)There were obvious correlation between single parent family and somatization,interpersonal relations and anxiety,between growing environment and anancasm,interpersonal relation, and between only child and interpersonal relation,phobia.Conclusion:The psychological problems of serviceman are cognition,emotion and interpersonal relations,this may be correlated with their psychological characteristics and army particularity.
Stemming and its effects on TFIDF ranking.

High precision IR is often hard for a variety of reasons; one of these is the large number of morphological variants for any given term. To address some of the issues arising from a mismatch between different word forms used in the queries and the relevant documents, researchers have long proposed the use of various stemming algorithms to reduce terms to a common base form. Stemming, in general, has not been an unmitigated success in improving IR. This poster argues that stemming can help in certain contexts and that an empirical investigation of the relationship between stemming performance and retrieval performance can be valuable. We extend previously reported work on stemming and IR (e.g., [2, 4, 5]) by using a novel, dictionary based “perfect” stemmer, which can be parametrized for different accuracy and coverage levels. This allows us to measure changes in IR performance for any given change in stemming performance on a given data set. To place this work in context, we discuss an empirical evaluation of stemming accuracy for three stemming algorithms – including the widely used Porter algorithm [9]. Section 2 briefly discusses the three variants of stemming, and presents experimental evidence for their relative coverage and accuracy. Section 3 discusses the use of these stemmers for IR and presents some of our findings. Finally, Section 4 concludes with a discussion of our results and possible future directions.
Multi-stage programming (poster)

The concept of a multi-stage computation has recently been the focus of a number of studies [2, 1]. A computational stage roughly corresponds to the “running” of a program on some input. Practical interest in models of mult i-st age computations stems from their significant potential for enabling meamng-preservmg optimization whenever the inputs to a program are available at “different times”.
LUSTRE: A declarative language for programming synchronous systems*

This paper presents the language LUSTRE, whose main application field is the programming of automatic control and signal processing systems. In this field, design is tra- ditionally driven by means of two types of tools. First, specifications are often systems of equations (differential or finite difference equations, boolean equations, . . .). Second, implementations are often nets of operators connected with wires (switches, gates, analog diagrams). Such tools present several ad&tag- as a basis for
Strongly Typed Flow-Directed Representation Transformations

We present a new framework for transforming data representations in a strongly typed intermediate language. Our method allows both value producers (sources) and value consumers (sinks) to support multiple representations, automatically inserting any required code. Specialized representations can be easily chosen for particular source/sink pairs. The framework is based on these techniques: 1. Flow annotated types encode the “flows-from” (source) and “flows-to” (sink) information of a flow graph. 2. Intersection and union types support (a) encoding precise flow information, (b) separating flow information so that transformations can be well typed, (c) automatically reorganizing flow paths to enable multiple representations. As an instance of our framework, we provide a function representation transformation that encompasses both closure conversion and inlining. Our framework is adaptable to data other than functions.
Answering queries using templates with binding patterns (extended abstract)

When integrating heterogeneous information resources, it is often the case that the source is rather limited in the kinds of queries it can answer. If a query is asked of the entire system, we have a new kind of optimization problem, in which we must try to express the given query in terms of the limited query templates that this source can answer. For the case of conjunctive queries, we show how to decide with a nondeterministic polynomial-time algorithm whether the given query can be answered. We then extend our results to allow arithmetic comparisons in the given query and in the templates.
Web-scale Topic Models in Spark: An Asynchronous Parameter Server.

In this paper, we train a Latent Dirichlet Allocation (LDA) topic model on the ClueWeb12 data set, a 27-terabyte Web crawl. We extend Spark, a popular framework for performing large-scale data analysis, with an asynchronous parameter server. Such a parameter server provides a distributed and concurrently accessed parameter space for the model. A Metropolis-Hastings based collapsed Gibbs sampler is implemented using this parameter server achieving an amortized O(1) sampling complexity. We compare our implementation to the default Spark implementations and show that it is significantly faster and more scalable without sacrificing model quality. A topic model with 1,000 topics is trained on the full ClueWeb12 data set, uncovering some of the prevalent themes that appear on the Web.
A GSM MODULATOR USING A AI: FREQUENCY DISCRIMINATOR BASED SYNTHESIZER

This paper describes a new transmitter architecture suitable for GSM modulation. The technique is based on direct modulation of a high resolution AZ frequency discriminator based synthesizer to produce the modulated RF signal without any up-conversion. The advantage of this architecture is that it does not require mixers or D/A converters to generate the In-phase and Quadrature signals as in conventional GSM transmitters. This eliminates many of the analog problems associated with mixing and filtering and results in an architecture suitable for monolithic integration.
Cognitive Dysfunction in Patients with Type 2 Diabetes

Among the chronic complications of diabetes,particularly in elderly patients,there is a higher prevalence of cognitive dysfunction. Mild cognitive impairment can increase the risk for progression to dementia after a few years. Hyperglycemia,insulin-resistant states,vascular,genetic factors may be correlated with cognitive dysfunction of type 2 diabetes patients,which is also influenced by brain-derived neurotrophic factor and exercise. In recent years,knowledge on type 2 diabetes cognitive dysfunction has been deepening,and here is to make a review of the pathogenesis,screening and assessment,and treatment and management of type 2 diabetes mellitus cognitive dysfunction.
Knowledge-as-Theory-and-Elements

Knowledge-as-Theory-and-Elements Alexander Munson This dissertation will examine the Knowledge-as-Theory-and-Elements perspective on knowledge structure. The dissertation creates a set of theoretical criteria given within a template by which lesson plans can be designed to teach mathematics and the physical sciences. The dissertation also will test the Knowledge-as-Theory-and-Elements theoretical perspective by designing lesson plans to teach a branch of mathematics, graph theory, by using the new template. The dissertation will include a comparative study investigating the effectiveness of the lesson plans conforming to the new template and the lesson plans designed by the traditional theoretical perspective Knowledge-as-Elements.
THE INDIAN VETERINARY JOURNAL

Seroprevalence of peste des petits ruminants in organised and unorganised sectors in Karnataka – A.K. Santhosh, Raveendra Hegde, S. Isloor, R. Amitha Gomes, D. Rathnamma, S.M. Byregowda, K. Prabhudas and C. Renukaprasad . 659 Comparative efficacy of alum precipitated and aluminium hydroxide gel adsorbed enterotoxaemia vaccines in sheep – T. Pavan Kumar, G. Sunitha, A.V. Krishna Mohan and G. Hanumanth Reddy . 661 Evaluation of R mutant Escherichia coli J5 bacterin vaccine against coliform mastitis in cows – Hasan Solmaz, Ziya Ilhan, Ibrahim Tasal and Abdulbaki Aksakal . 663 Effect of electrolyte supplementation on feed and water intake in heat stressed buffalo calves – G. Krishnan, G. Singh and D.C. Shukla . 665 Serodiagnosis of canine ehrlichiosis by enzyme linked immunosorbent assays T.J. Harikrishnan, D.J. Chellappa, N. Pazhanivel and G. Rajavelu . 668 Prevalence of skin and subcutaneous tissue neoplasms in dogs T.S. Dayananda, Suguna Rao, S.M. Byregowda, M.L. Satyanarayana, K.C. Jayachandra and V.T. Shilpa . 671 Efficacy of abamectin against sarcoptic mange in adult buffaloes M.S. Bal, V. Mahajan, Ashuma, Paramjit Kaur, S. Sharma, Renu and S.S. Rath . 674 Studies on haematology and serum biochemistry profile in canine demodecosis Pritam Sarkar, A. Chakraborti and Debaki Ghosh . 676 Follicular dynamics during estrous cycle in crossbred cows Manjusha Patil, K.P. Khillare, S.K. Sahatpure and M.D. Meshram . 679 Sperm morphological abnormalities and freezability of semen in bulls D.K. Mandal, S. Tyagi and M. Kumar . 681 Efficacy of Tes-tris semen extender on freezability of dog semen T. Sathiamoorthy, S.A. Asokan, C. Veerapandian and J. Kalatharan . 685 Genetic parameters and breeding values of milk yield of Holstein cows S. Dikmen and H. Baspinar . 687 Performance of crossbred pigs on different feeding regimes D. Medhi, K.K. Baruah and H. Baishya . 691 Effect of kitchen waste on growth and carcass characteristics of indigenous pigs – S. Kumar, A.P. Sinha, S.K. Singh, R.N. Singh, R.Kumar and H. Kumar . 695 Serum mineral profile of crossbred calves supplemented with zinc sulphate and zinc propionate – G.P. Mandal and R.S. Dass . 700 Effect of sodium butyrate vis-a-vis virginiamycin on liveweight gain and feed conversion ratio in broiler chickens M.T. Bhutia, B. Roy and S. Pal . 703 Effect of dietary protein with fish meal or amino acids on the growth performance of pigs M.V. A.N. Suryanarayana, K. Anand Rao and D. Srinivasa Rao . 705 A study on the lipase producing psychrotrophic bacteria isolated from milk and dairy products – B. Murugan and G. Kumaresan . 708 Pre-weaning morpho-metric measurements and body wegiths of Beetal kids – Maroof Ahmad, P.K. Singh, D.K. Sadana, Gurmej Singh, S. Alam and D. Chahal . 710
Efficient tree pattern matching (extended abstract): an aid to code generation

We show that tree pattern matching has significant advantages in the specification and implementation of efficient code generators. We present a top-down tree-matching algorithm that is particularly well suited to code generation applications. Finally, we present a new back-end language that incorporates tree pattern matching with dynamic programming into a uniform framework for the specification and implementation of efficient code generators.
The knowledge complexity of interactive proof-systems

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Inside risks: the Trojan horse race

This year has been pivotal for malicious software (malware) such as viruses, worms, and Trojan horses. Although the problem is not new, Internet growth and weak system security have increased the risks. Viruses and worms survive by moving from computer to computer. Prior to the Internet, computers communicated slowly, mostly from floppy disks and bulletin boards. Initially, antivirus programs were fairly effective at blocking known types of malware entering PCs, especially when only a handful of viruses prevailed. But now there are over 10,000 virus types; with email and Internet connectivity, the opportunities and speed of propagation have increased dramatically. Things have changed. Like Melissa, the Worm.ExploreZip worm, and other inevitable variants, viruses arrive via email and use email software features to replicate themselves across the network. They mail themselves to people known to the infected host, enticing the recipients to open or run them. They propagate almost instantaneously. Antiviral software simply cannot keep up. And email runs over Internet connections that block everything else. Email tunnels through firewalls. Everyone uses it. Melissa uses features in Microsoft Word (with variants using Excel) to automatically email itself to others, and Melissa and Worm.ExploreZip make use of Microsoft Outlook's automatic mail features. Microsoft is certainly to blame for creating the powerful macro capabilities of Word and Excel, blurring the distinction between exe-cutable files (which can be dangerous) and data files (which at one time seemed safe). They will be blamed when Outlook 2000, which supports HTML, makes it possible for users to be attacked by HTML-based malware simply by opening email. DOS set the security state-of-the-art back 25 years, and Microsoft has continued that legacy to this day. Microsoft certainly has a lot to answer for, but the real cause is more subtle. It's easy to point fingers at virus creators or at the media for publicity begetting further malware. But a basic problem is the permissive nature of the Internet. As long as a program has the ability to do anything on the computer it runs on, malware will be incredibly dangerous. Just as fire-walls protect different computers on the same network, we're going to need something to protect different processes running on the same computer. Malware cannot be stopped at the firewall because email tunnels it through a firewall, popping up on the inside and causing its intended damage. Thus far, the examples have been mild, but they represent a …
USE OF ANTICOAGULANT AGENTS FOR STROKE PREVENTION

Anticoagulant therapy has been used for the treatment and prevention of stroke since the late 1950s. Since that time, intense basic and clinical research has addressed the development and demonstration of efficacy of diverse anticoagulant agents for prevention of cerebrovascular disease in a wide variety of clinical states and disease processes. Early investigators in the pre-computed tomography (CT) scan era recognized that the major complication of anticoagulant therapy is bleeding, both systemic and intracranial, which for the most part is dose related. The high risk of intracranial hemorrhage in these pre-CT scan era studies may have been related to the use of high intensities of anticoagulant therapy, unsuspected initial intracerebral hemorrhage, suboptimal control of hypertension, and initiation of therapy in the acute phase of stroke (Levine et al, 2004). Recent investigators have examined putative risk factors associated with bleeding during anticoagulation therapy with an eye toward optimizing the use of anticoagulant therapy. This chapter has several objectives: (1) to review the pharmacology of available and emerging anticoagulant therapies; (2) to illustrate the system for evaluating the quality of clinical evidence and grading therapeutic recommendations; (3) to present a detailed evidence-based review of the use of anticoagulants for specific disease processes, as well as during pregnancy, and when possible, to supplement the clinical trial data by high-quality observational epidemiological studies and expert opinion; and (4) to discuss the occurrence of and risk factors for intracranial hemorrhage with anticoagulant therapy.
Effectiveness Evaluation of Mass Media in Health Education

Objective To evaluate the effect of mass media on increasing health knowledge and changing health behaviors of residents in Beijing.Methods A questionnaire survey was conducted among 1000 residents, 385 males and 565 females, aged 25 to 64, in the 8 urban districts of Beijing by cluster random sampling. The data was analyzed by using statistic software SPSS.Results 89 8% respondents got their heath knowledge from mass media including television program (64 6%), newspapers and magazines (62 7%), broadcast (43 5%), etc. 40%～70% respondents attributed their behavioral changes mainly to health education and attributed 50% of their behavioral changes to television programs, newspapers and magazines, and broadcast. 82 9% of their knowledge about sexually transmitted diseases came from mass media. The three most preferable mass media were TV, periodicals, and radio broadcast. Public service advertisement and big scale counseling activity had very little effect.Conclusion Mass media, especially TV, periodicals, and radio broadcast, are the main channels to acquire health education for the residents in Beijing.
A pattern-based analysis of clinical computer-interpretable guideline modeling languages.

OBJECTIVES Languages used to specify computer-interpretable guidelines (CIGs) differ in their approaches to addressing particular modeling challenges. The main goals of this article are: (1) to examine the expressive power of CIG modeling languages, and (2) to define the differences, from the control-flow perspective, between process languages in workflow management systems and modeling languages used to design clinical guidelines. DESIGN The pattern-based analysis was applied to guideline modeling languages Asbru, EON, GLIF, and PROforma. We focused on control-flow and left other perspectives out of consideration. MEASUREMENTS We evaluated the selected CIG modeling languages and identified their degree of support of 43 control-flow patterns. We used a set of explicitly defined evaluation criteria to determine whether each pattern is supported directly, indirectly, or not at all. RESULTS PROforma offers direct support for 22 of 43 patterns, Asbru 20, GLIF 17, and EON 11. All four directly support basic control-flow patterns, cancellation patterns, and some advance branching and synchronization patterns. None support multiple instances patterns. They offer varying levels of support for synchronizing merge patterns and state-based patterns. Some support a few scenarios not covered by the 43 control-flow patterns. CONCLUSION CIG modeling languages are remarkably close to traditional workflow languages from the control-flow perspective, but cover many fewer workflow patterns. CIG languages offer some flexibility that supports modeling of complex decisions and provide ways for modeling some decisions not covered by workflow management systems. Workflow management systems may be suitable for clinical guideline applications.
Finding Effective Geo-Social Group for Impromptu Activity with Multiple Demands

Geo-social group search aims to find a group of people proximate to a location while socially related. One of the driven applications for geo-social group search is organizing an impromptu activity. This is because the social cohesiveness of a found geo-social group ensures a good communication atmosphere and the spatial closeness of the geo-social group reduces the preparation time for the activity. Most existing works treat geo-social group search as a problem that finds a group satisfying a single social constraint while optimizing the spatial proximity. However, when an impromptu activity has additional demands on attendees, e.g., the activity requires that the attendees have certain set of skills, the existing works cannot find an effective geo-social group efficiently. In this paper, we study how to find a group that is most proximate to a query location while satisfying multiple constraints. Specifically, the multiple constraints on which we focus include social constraint, size constraint and keyword constraint. We propose a novel search framework which first effectively narrows down the search space with theoretical guarantees and then efficiently finds the optimum result. Although our model considers multiple constraints, novel techniques devised in this paper ensure that search cost is equivalent to parameterized constant times of one time social constraint checking on a vastly restricted search space. We conduct extensive experiments on both real and semi-synthetic datasets for demonstrating the efficiency of the proposed search algorithm. To evaluate the effectiveness, we conduct two case studies on real datasets, demonstrating the superiority of our proposed model.
Distilling Structured Knowledge into Embeddings for Explainable and Accurate Recommendation

Recently, the embedding-based recommendation models (e.g., matrix factorization and deep models) have been prevalent in both academia and industry due to their effectiveness and flexibility. However, they also have such intrinsic limitations as lacking explainability and suffering from data sparsity. In this paper, we propose an end-to-end joint learning framework to get around these limitations without introducing any extra overhead by distilling structured knowledge from a differentiable path-based recommendation model. Through extensive experiments, we show that our proposed framework can achieve state-of-the-art recommendation performance and meanwhile provide interpretable recommendation reasons.