nils-herrmann/clean_scirepeval huggingface dataset:
DTACU: a global DVFS algorithm based on piece energy model
Year: 2016

Considering the exclusive policy and poor energy benefits for multicore processor by Ondemand algorithm, a global DVFS (Dynamic Voltage and Frequency Scaling) algorithm DTACU based on piece energy model is proposed. In order to translate multicore problems to single core problems, an equivalent energy model, called piece energy model, was set up. It divided the time into several periods in which no task arrive or finish in each core, hence the multicore processor can be seen as a single core processor. Based on theoretical research on energy consumption and current published papers, analytical expressions of equivalent single core energy consumption were deduced. DTACU was proposed through analyzing the source of energy consumption in expression and implemented based on Userspace. Taking the number of active cores and dynamic thresholds into account, DTACU only change CPU speed during one period to both reduce energy consumption and satisfy the demand of task deadline. The final result of experiments show that DTACU can achieve lower energy consumption without sacrificing system performance compared with Ondemand.  Nowadays, reducing the energy consumption is considered as one of the major research topics for computing system, especially for mobile computing system. Comparing with low power component design and manufacturing technology, processor low power design at system level is also meaningful. Dynamic Voltage and Frequency Scaling (DVFS) is one of feasible means of reducing energy consumption. It is a hardware technology used to dynamically scale up or down the frequency or voltage of processor according to the governor policy and the workload demand at the cost of an increased latency. For multicore processor, there are two main means of DVFS control, namely local DVFS and global DVFS. Local DVFS changes the clock frequency per core, while global DVFS makes these changes for the entire chip. Recently, clustered DVFS, which uses multiple of on chip regulators drive a set of DVFS domains, was proposed for multicore processors[1] Theoretically, local DVFS is the most effective way to reducing energy consumption. However, in practice global DVFS is the most common in processor design, since it is cheaper to implement, but there are still some issues on global DVFS, such as low energy benefits and complex algorithms. In this paper, we explore and propose a global DVFS algorithm DTACU (Dynamic Threshold and Active Cores based on Userspace) by analyzing the relationship between frequency and energy consumption based on piece energy model. Section 2 introduces the related works about global DVFS. After presenting the detailed process of setting up the piece energy model, the description and implementation of DTACU are presented in Section 4. The results of experiment are shown in section 5, and final conclusion is given in section 6.
Probiotika a jejich vliv na dyslipidemii a diabetes
Year: 2010

Probiotika drive marginalizovane a podcenovane tema se dostavaji v poslednich 10 15 letech do popredi zajmu vedcu i verejnosti. Ucinky na poruchy a choroby zazivaciho traktu jsou dobre znamy a postupne jsou odhalovany dalsi priznive efekty na zanetlive nemoci lokalizovane mimo strevo (urogenitalni trakt, klouby) na onemocneni autoimunitni i onkologicka. Pusobenim ve streve, ktere je povazovano za nejvetsi imunitni organ v tele, mohou vyznamne zlepsit imunitni reakce organizmu. Vzhledem k vlastnostem, ktere ovlivnuji zanet, se nove oteviraji moznosti pouziti i v oblastech chorob civilizacnich, jejichz spolecnym jmenovatelem je zanetliva reakce organizmu.
GPT 3: Its Nature, Scope, Limits, and Consequences
Venue: Minds Mach.
Year: 2020

In this commentary, we discuss the nature of reversible and irreversible questions, that is, questions that may enable one to identify the nature of the source of their answers. We then introduce GPT 3, a third generation, autoregressive language model that uses deep learning to produce human like texts, and use the previous distinction to analyse it. We expand the analysis to present three tests based on mathematical, semantic (that is, the Turing Test) and ethical questions and show that GPT 3 is not designed to pass any of them. This is a reminder that GPT 3 does not do what it is not supposed to do, and that any interpretation of GPT 3 as the beginning of the emergence of a general form of artificial intelligence is merely uninformed science fiction. We conclude by outlining some of the significant consequences of the industrialisation of automatic and cheap production of good, semantic artefacts.
Hybrid non isolated and non inverting Nx interleaved DC DC multilevel boost converter for renewable energy applications
Venue: 2016 IEEE 16th International Conference on Environment and Electrical Engineering (EEEIC)
Year: 2016

In this paper hybrid non isolated/ non inverting Nx interleaved DC DC multilevel Boost Converter for renewable energy applications is presented. The presented hybrid topology is derived from the conventional interleaved converter and the Nx Multilevel boost converter. In renewable energy applications, generated energy cannot be directly used at application end. In most of the cases it needs to be stepped up with DC DC converter at operating voltage levels as per the requirement of the application. Though conventional boost converter can theoretically be used for this purpose, but obtaining such high gain implies that boost converter should operate at it its maximum duty cycle, which is not feasible due to the great variations in the output voltage caused by small variations in the duty cycle, leading the boost converter to instability and also increases the voltage stress across switches. The advantages of presenting topology of DC DC converter are high voltage conversion, reduce ripple, low voltage stress, non inverting without utilizing the high duty and transformer. The main advantage of presented topology is more number of levels can be increased by adding capacitor and diode circuitry to increase the voltage gain without disturbing the main circuit. Moreover, the presented topology is compared with several recent high gain converters. The proposed topology is simulated in MATLAB/SIMULATION and results will verify the validity of the design and operation of the converter.
Charity institutions as networks of power: how Anzia Yezierska's characters resist philanthropic surveillance
Year: 2017

espanolA finales del siglo XIX, una serie de instituciones privadas norteamericanas se encargaron de difundir valores nacionales debido a la oleada masiva de inmigrantes provenientes de Europa del Este. Estas instituciones, especialmente las organizaciones de la caridad, apoyaban la integracion de las inmigrantes, sin embargo, desde una perspectiva clasista. Segun la autora polaco americana Anzia Yezierska (1885 1970) sus programas aparentemente inclusivos realmente obstaculizaban la satisfaccion del discurso del Sueno Americano, basado en la premisa de preservar las diferencias individuales. Al comparar estas instituciones caritativas con la prision panoptica de la que Michel Foucault hace referencia, este estudio pretende demostrar como las similitudes entre ambas estructuras ayudan a entender hasta que punto las benefactoras consiguieron eficazmente influir a las inmigrantes recien llegadas. La jerarquia de poder establecida entre ellas determinaria las dificultades de estas ultimas para alcanzar el reconocimiento de su individualidad desde su experiencia interseccional. La alternativa a la red de vigilancia, pues, aparece en el acto de solidaridad, un tipo de resistencia que permite a los personajes guetizados representar su distincion cultural fuera del proceso de americanizacion. EnglishAt the end of the nineteenth century, American private institutions took the charge of spreading national values due to the massive wave of eastern European immigration. These institutions, especially charitable organizations, supported the integration of immigrants, however, from a classist perspective. According to the Polish American author Anzia Yezierska (1885 1970) their apparently inclusive programs actually hindered the fulfilment of the discourse of the American Dream, which is based on the premise of preserving individual differences. By comparing those charitable institutions to Michel Foucault's panoptical prison, this research attempts to demonstrate how the similarities between both structures help understand up to what extent the benefactresses in charge accurately managed to influence the newly arrived immigrants. The hierarchy of power established between them would determine the latter's difficulties to achieve the recognition of their individualities from their intersectional experiences. The alternative to the monitoring network, thus, appears in the act of solidarity, a kind of resistance that allows ghettoized characters to perform their cultural distinctiveness away from Americanization.
Open problems in hash function security
Venue: Des. Codes Cryptogr.
Year: 2015

A cryptographic hash function compresses arbitrarily long messages to digests of a short and fixed length. Most of existing hash functions are designed to evaluate a compression function with a finite domain in a mode of operation, and the compression function itself is often designed from block ciphers or permutations. This modular design approach allows for a rigorous security analysis via means of both cryptanalysis and provable security. We present a survey on the state of the art in hash function security and modular design analysis. We focus on existing security models and definitions, as well as on the security aspects of designing secure compression functions (indirectly) from either block ciphers or permutations. In all of these directions, we identify open problems that, once solved, would allow for an increased confidence in the use of cryptographic hash functions.
The Effect of MUC1 rs4072037 Functional Polymorphism on Cancer Susceptibility: Evidence from Published Studies
Venue: PloS one
Year: 2014

Genome wide association studies have identified a susceptibility variation MUC1 rs4072037 for gastric cancer in Chinese population. Subsequent case control studies have reported this association in other populations. However, the results remain controversial and ambiguous. The aim of this study is to provide a precise quantification for the association between MUC1 rs4072037 variation and the risk of cancer. We performed pooled analysis of 10 case control designed studies including 4,220 cases and 6,384 controls. Odds ratios (OR) and 95% confidence interval (95%CI) were calculated to assess strength of association in overall studies and in subgroup analysis stratified by ethnicity and cancer types. All statistical analyses were performed by Manager 5.0 and Stata 12.0 software. Overall, the MUC1 rs4072037 polymorphism was associated with risk of cancer in all genetic models (G vs A: OR 0.71, 95%CI: 0.63 0.80, p<0.01; GA vs AA: OR 0.61, 95%CI:0.55 0.67, p<0.01; GG vs AA: OR 0.58, 95%CI: 0.47 0.71, p<0.01; AG+AA vs GG: OR 0.60, 95%CI: 0.55 0.60, p<0.01; GG vs AG+AA: OR 0.70, 95%CI: 0.58 0.85, p<0.01) Further, subgroup analysis based on ethnicity suggested MUC1 rs4072037 polymorphism had a subtly reduced cancer risk among Asian population, and stratified analysis by cancer types showed significantly decreased risk of gastric cancer in all genetic models. In conclusion, MUC1 rs4072037 polymorphism may be used as potential biomarker for cancer susceptibility particularly for gastric cancer and for Asian population.
Public response to news reports on the Mount Kusatsu Shirane volcanic eruption: A content analysis of online reader comments
Year: 2020

This paper reports on the real time public responses to the eruption disaster on Mt. Kusatsu Shirane in January 2018. This volcanic disaster attracted significant media coverage, with many people again acknowledging the risk of volcanic hazards from the many news reports. These days, as it has become increasingly common for people to express their opinions using online sites, online reader comments can be important sources of public opinion. This paper used a content analysis approach to analyze the comments posted in online news reports on the volcanic disaster to determine the public's perspective of the risks associated with volcanic disasters and volcanology. Applying an inductive category extraction strategy, the comments were sorted into six categories of comments (1) that made reference to volcanic risk perception, (2) on volcanology or volcanologists, (3) that had fatalistic perceptions of natural disasters as blameless misfortunes, (4) on eruption predictability, (5) on disaster risk reduction measures implemented by central/local governments and disaster management agencies, and (6) explaining the phreatic explosion mechanism. It was found that many comments tended to have a negative tone, and a prominent criticism was that modern science could not detect volcanic activities reliably. However, some commenters suggested that experts with a sophisticated knowledge of volcanology should be available to support local communities in a similar way to the "home doctor" Volcanologists need to disseminate information, such as the current state of geological and earth science education systems, volcanological knowledge, and application of the lessons learned from volcanic disasters.
Bebidas ricas em acucares de adicao e"sintomas de asma na infancia: analise nos primeiros 1000 dias de vida Coorte Brisa, Sao Luis
Year: 2018

O objetivo deste estudo foi analisar a associacao entre consumo de Bebidas Ricas em Acucares de Adicao (SSB) nos primeiros 1000 dias de vida e "sintomas de asma na infancia" explorando os caminhos diretos e indiretos dessa associacao via excesso de peso da crianca e via inflamacao alergica. Trata se de um estudo envolvendo variaveis em dois momentos da Coorte BRISA, Sao Luis, Brasil (n=1140) pre natal e segundo ano de vida das criancas. Um modelo teorico com variaveis coletadas no pre natal (socioeconomica e idade materna) e no segundo ano (amamentacao exclusiva, idade da crianca, z score do IMC e contagem de eosinofilos da crianca) foi construido para avaliar a associacao das SSB com "sintomas de asma na infancia" por meio de modelagem de equacoes estruturais. A variavel explanatoria principal foi o percentual de acucar consumido proveniente das SSB (bebidas lacteas e nao lacteas) em relacao as calorias totais. O desfecho "child asthma traits" foi uma variavel latente formada por quatro indicadores de asma: diagnostico medico de asma, chiado, emergencia medica por chiado intenso e rinite. O maior percentual do consumo de acucar proveniente de SSB, foi associado diretamente aos maiores valores de "sintomas de asma na infancia" (CP=0.123; P=0.043) Maiores valores de eosinofilos foram associados independentemente a "sintomas de asma na infancia" (CP=0.155; P=0.021) enquanto o aleitamento materno exclusivo foi protecao a esse desfecho (CP= 0.151; P=0.020) Nao foram observados efeitos diretos ou indiretos do excesso de peso da crianca nos valores dos "sintomas de asma na infancia" Esses resultados sugerem que o maior consumo de SSB contribui para o risco de "sintomas de asma na infancia" sendo essa associacao independente do excesso de peso da crianca e da inflamacao eosinofilica.
Application of Big Data and Technologies for Integrated Water Resources Management A Survey
Venue: 2019 Sixth International Conference on Social Networks Analysis, Management and Security (SNAMS)
Year: 2019

Problems related to water are of highest relevance, and their importance is likely to increase in future. Tools of Integrated Water Resources Management (IWRM) address those problems. New technological developments on various fronts, concerning measurement, data transfer and storage, as well as data processing, modeling and visualization enable the advanced use and application of IWRM tools. Mainly we provide an overview on the development in various fields of IWRM and briefly include information about an ongoing project that involves some of the new technologies, in particular the long range wide area network (LoRaWAN) for data transfer from hydrological sensors.
Computer Assisted Language Learning
Year: 2020

Information and communication technology, a diverse set of technological tools and resources used to communicate, create, remove, store and manage information. ICT includes radio, T.V. computer, internet, server, hardware, software, recording and processing system for sound, still and moving pictures. The extensive growth of the internet has made online communication a part of daily life. The progress of science and technology have brought innovative and effective trend for language learning. Computer Assisted Language Learning has made remarkable contribution in searching a solution and in the methodology of language teaching and learning. The advancement of technology has a vast share in the growth of English.
Stress Test Evaluation for Natural Language Inference
Venue: COLING
Year: 2018

Natural language inference (NLI) is the task of determining if a natural language hypothesis can be inferred from a given premise in a justifiable manner. NLI was proposed as a benchmark task for natural language understanding. Existing models perform well at standard datasets for NLI, achieving impressive results across different genres of text. However, the extent to which these models understand the semantic content of sentences is unclear. In this work, we propose an evaluation methodology consisting of automatically constructed "stress tests" that allow us to examine whether systems have the ability to make real inferential decisions. Our evaluation of six sentence encoder models on these stress tests reveals strengths and weaknesses of these models with respect to challenging linguistic phenomena, and suggests important directions for future work in this area.
Attention to Orthographic and Phonological Word Forms in Vocabulary Instruction for Kindergarten English Learners
Year: 2016

This study examined benefits of connecting meaning, speech, and print in vocabulary learning for kindergarten English learners. Students screened eligible with limited English proficiency were randomly assigned to two instruction conditions. Both groups received direct instruction in high frequency root words. One condition featured added attention to orthographic and phonological word features. Increased attention to the spoken and printed word forms was associated with significantly greater gains in general vocabulary and word reading, and in taught word spelling. Results suggest features of effective vocabulary instruction for young and English learner students.
Assigning function to protein protein interactions: a weakly supervised BioBERT based approach using PubMed abstracts
Venue: ArXiv
Year: 2020

Protein protein interactions (PPI) are critical to the function of proteins in both normal and diseased cells, and many critical protein functions are mediated by interactions.Knowledge of the nature of these interactions is important for the construction of networks to analyse biological data. However, only a small percentage of PPIs captured in protein interaction databases have annotations of function available, e.g. only 4% of PPI are functionally annotated in the IntAct database. Here, we aim to label the function type of PPIs by extracting relationships described in PubMed abstracts.  We create a weakly supervised dataset from the IntAct PPI database containing interacting protein pairs with annotated function and associated abstracts from the PubMed database. We apply a state of the art deep learning technique for biomedical natural language processing tasks, BioBERT, to build a model dubbed PPI BioBERT for identifying the function of PPIs. In order to extract high quality PPI functions at large scale, we use an ensemble of PPI BioBERT models to improve uncertainty estimation and apply an interaction type specific threshold to counteract the effects of variations in the number of training samples per interaction type.  We scan 18 million PubMed abstracts to automatically identify 3253 new typed PPIs, including phosphorylation and acetylation interactions, with an overall precision of 46% (87% for acetylation) based on a human reviewed sample. This work demonstrates that analysis of biomedical abstracts for PPI function extraction is a feasible approach to substantially increasing the number of interactions annotated with function captured in online databases.
Transfusion: Understanding Transfer Learning for Medical Imaging
Venue: NeurIPS
Year: 2019

Transfer learning from natural image datasets, particularly ImageNet, using standard large models and corresponding pretrained weights has become a de facto method for deep learning applications to medical imaging. However, there are fundamental differences in data sizes, features and task specifications between natural image classification and the target medical tasks, and there is little understanding of the effects of transfer. In this paper, we explore properties of transfer learning for medical imaging. A performance evaluation on two large scale medical imaging tasks shows that surprisingly, transfer offers little benefit to performance, and simple, lightweight models can perform comparably to ImageNet architectures. Investigating the learned representations and features, we find that some of the differences from transfer learning are due to the over parametrization of standard models rather than sophisticated feature reuse. We isolate where useful feature reuse occurs, and outline the implications for more efficient model exploration. We also explore feature independent benefits of transfer arising from weight scalings.
Local Algorithms for Hierarchical Dense Subgraph Discovery
Venue: Proc. VLDB Endow.
Year: 2018

Finding the dense regions of a graph and relations among them is a fundamental problem in network analysis. Core and truss decompositions reveal dense subgraphs with hierarchical relations. The incremental nature of algorithms for computing these decompositions and the need for global information at each step of the algorithm hinders scalable parallelization and approximations since the densest regions are not revealed until the end. In a previous work, Lu et al. proposed to iteratively compute the $h$ indices of neighbor vertex degrees to obtain the core numbers and prove that the convergence is obtained after a finite number of iterations. This work generalizes the iterative $h$ index computation for truss decomposition as well as nucleus decomposition which leverages higher order structures to generalize core and truss decompositions. In addition, we prove convergence bounds on the number of iterations. We present a framework of local algorithms to obtain the core, truss, and nucleus decompositions. Our algorithms are local, parallel, offer high scalability, and enable approximations to explore time and quality trade offs. Our shared memory implementation verifies the efficiency, scalability, and effectiveness of our local algorithms on real world networks.