Miracle-dz/UniFAR-FTUs huggingface dataset:
Two Kinds of High-Level Probability

According to influential views the probabilities in classical statistical mechanics and other special sciences are objective chances, although the underlying mechanical theory is deterministic, since the deterministic low level is inadmissible or unavailable from the high level. Here two intuitions pull in opposite directions: One intuition is that if the world is deterministic, probability can only express subjective ignorance. The other intuition is that probability of high-level phenomena, especially thermodynamic ones, is dictated by the state of affairs in the world. We argue in support of this second intuition and we show that in fact there are two different ways in which high-level probability describes matters of fact, even if the underlying microscopic reality is deterministic. Our analysis is novel, but supports approaches by, e.g., Loewer, Albert, Frigg and Hoefer, List and Pivato. In particular, the reductive view we propose here can be seen as a naturalization of the above approaches. We consider consequences of our result for nonreductive physicalist approaches, such as functionalism, that admit multiple realization of the kinds that appear in the special sciences by physical kinds. We show that nonreductive physicalism implies the existence of nonphysical matters of fact.
Classification of Encrypted Texts using Deep Learning

The most widely used cryptographic systems can identify cryptographic algorithms and identify encryption keys. Statistical methods and learning a variety of machines have been used to identify cryptographic algorithms, each of which has its own advantages and disadvantages. This paper seeks to provide a method for identifying the algorithm used for encrypted texts in text files. Since the volume of this kind of data is very big and increases at any given moment, then the accuracy is calculated by voting of these classifiers. The process of identifying the encryption algorithm is also known from the encrypted texts as the classification of text. So, three methods of encryption AES, RC5, BLOWFISH have been used to evaluate system performance. A three class’s classifier is needed, for this purpose, k-nearest neighbor’s algorithm has been used. This article is based on a deep learning approach, provides a new method for identifying the pattern in cryptographic texts and learning them by methods of representing features. The proposed method, consists of four parts of the preprocessing, feature learning, data classification and voting. The proposed system's efficiency in algorithm classification is 99.1%.
Semântica denotacional escalável de linguagens imperativas

Este trabalho de dissertacao aborda uma nova solucao para o problema de escalabilidade da Semântica Denotacional, intitulada Semântica Denotacional Baseada em Componentes. Essa tecnica utiliza uma biblioteca de componentes de semântica denotacionalque encapsulam conceitos fundamentais e recorrentes de linguagens de programacao imperativas. Uma das principais funcoes da biblioteca e remover das equacoes semânticas a dependencia aparente de contexto das construcoes. Dessa forma, as definicoes semânticassao definidas pelo mapeamento direto entre as construcoes da sintaxe abstrata de uma linguagem e as combinacoes de componentes que modelam sua semântica. O fluxo de informacoes de contexto e encapsulado pelos componentes. Como principais contribuicoes do trabalho, podem-se citar: definicao de uma nova metodologia baseada em componentes para obtencao de escalabilidade e reuso em definicoes de semântica denotacional; a implementacao de um ambiente de desenvolvimento para a metodologia, o qual permite a escrita de prototipos de interpretadores para linguagens definidas; identificacao e organizacao dos conceitos fundamentais e recorrentesdas linguagens de programacao imperativas em uma biblioteca de componentes de definicao semântica; abstracao do contexto em equacoes semânticas denotacionais.
Peak-Load Management in Commercial Systems With Electric Vehicles

Electric vehicles (EVs) are getting popular as one of the effective solutions for increased energy efficiency in commercial systems. This paper proposes an improved algorithm for commercial peak-load management using EVs, battery-energy-storage systems, and photovoltaic units. It uses the bidirectional vehicle-to-grid technique to utilize the energy from EVs in a parking lot. The proposed system has been tested in a real power distribution network in realistic load and weather conditions. The financial benefit of the system is also investigated, and it is found that the industrial peak load can be reduced by 50%, and the energy cost can be reduced by up to 27.3%. It also enhances the load factor by 9%. The performance of the proposed control algorithm is compared with that of an artificial-neural-network-based technique and tested in a laboratory prototype. From simulated and experimental results, it is found that the proposed approach provides substantial savings, while reducing the peak demand of the existing grids.
ESE Framework Verification by MBSE

Enterprise system engineering (ESE) is a practice emerging in the last decades, aiming to support the enterprise systems engineers in generating and developing enterprise architecture and improving enterprise operational processes. However, ESE differs significantly from systems engineering (SE) due to the enterprise's unique property as a system of unsynchronized arrays of systems. This property might lead to severe issues, such as cross-enterprise failures, lack of decision-support information for cross-enterprise decisions, long delays in integration tests, and unexpected emergent behavior. Enterprise Processes Integrative Collaboration (EPIC) framework is an ESE framework, aims to address this property by generating better coordination between unsynchronized arrays of systems within the enterprise and even further across several enterprises. Previous research dealt with the validation of this framework by implementation in two large-scale enterprises from the aerospace and transportation disciplines. The objective of this study was to verify the EPIC framework completeness and integrity, as an example of ESE framework verification. A model-based SE methodology was used to encapsulate EPIC, defining the ESE activities, required resources, and products. This encapsulation allows tracing the engineering activities, verifying the model completeness, traceability, integrity, and interoperability of the ESE processes collaboration.
Bunsetsu-based Dependency Relation and Coordinate Structure Annotation on ‘Balanced Corpus of Contemporary Written Japanese’

This article presents syntactic annotation for ‘Balanced Corpus of Contemporary Written Japanese’. We propose a syntactic annotation schema wherein the bun-setsu dependency and coordinate structure are separated. In addition, we propose an annotation standard to determine the attachments beyond clause boundaries. Our annotation schema and standard have issues associated the hierarchical annotation processes. Furthermore, we present the basic statistics of the annotation data.
Isolation , Cloning , and SubCellular Localization of Transketolase from Amaranthus Tricolor L .

Transketolase ( TK) is one of the key enzymes that involved in the Oxidative Pentose Phosphate Pathway (OPPP), and produce erythrose-4phosphate which is the pre cursor for many secondary metabolites such as aroma tic amino acids, lignin and flavonoid. The OPPP is composed o f tw functionally-connected phases, the oxidative and nonoxidative phase. The complete OPPP is localized in cytosol of animal and prokaryotic. However, in pla nt, the first phase is localised in cytosol but the sub-cellular localization of the second phase of OPPP is still u nder debate. There is no study available on transketolase in Amaranthus tricolor till to day? Therefore, the objectives of study ar e to isolate TK gene from Amaranthus tricolor, to compare its iden tity with other plant species and to determine its subcellular localization. The full length of 2021bp nucleotide sequence of TK had been isolated from A. tricolor by RTPCR. ClustalW revealed that A. tricolor TK sequences showed high similarity (more than 81 %) w ithin plants’ other species. Subcellular localization by using TargetP 1.1 and ChloroP revealed that of A. tricolor TK was located in the plastid. Thus it can be concluded that the OPPP is incomplete in the cytosol.
Pre-proofs Is there an ‘ End of History Illusion ’ for Life Satisfaction ? Evidence from a Three-Wave Longitudinal Study

According to the ‘end of history illusion’ (EOHI) individuals underestimate the amount of future change they will experience. Using results from a three-wave longitudinal study of American adults (N = 2390, mean age = 55.31 years, 56% female), we examined ratings of recollected past (10 years prior), current, and anticipated future (10 years later) life satisfaction at Wave 2, as well as current life satisfaction at Wave 1 (nine years earlier) and at Wave 3 (nine years later). Younger adults typically underestimated their past and overestimate their future LS, whereas older adults tended to underestimate their future LS. Contrary to the EOHI, most individuals either were accurate or anticipated too much change into the future, rather than too little.
Recurrent Neural Network Architectures Toward Intrusion Detection

Recurrent Neural Networks (RNN) show a remarkable result in sequence learning, particularly in architectures with gated unit structures such as Long Short-term Memory (LSTM). In recent years, several permutations of LSTM architecture have been proposed mainly to overcome the computational complexity of LSTM. In this dissertation, a novel study is presented that will empirically investigate and evaluate LSTM architecture variants such as Gated Recurrent Unit (GRU), Bi-Directional LSTM, and Dynamic-RNN for LSTM and GRU specifically on detecting network intrusions. The investigation is designed to identify the learning time required for each architecture algorithm and to measure the intrusion prediction accuracy. RNN was evaluated on the DARPA/KDD Cup’99 intrusion detection dataset for each architecture. Feature selection mechanisms were also implemented to help in identifying and removing nonessential variables from data that do not affect the accuracy of the prediction models, in this case Principal Component Analysis (PCA) and the RandomForest (RF) algorithm. The results showed that RF captured more significant features over PCA when the accuracy for RF 97.86% for LSTM and 96.59% for GRU, were PCA 64.34% for LSTM and 67.97% for GRU. In terms of RNN architectures, prediction accuracy of each variant exhibited improvement at specific parameters, yet with a large dataset and a suitable time training, the standard vanilla LSTM tended to lead among all other RNN architectures which scored 99.48%. Although Dynamic RNN’s offered better performance with accuracy, Dynamic-RNN GRU scored 99.34%, however they tended to take a longer time to be trained with high training cycles, Dynamic-RNN LSTM needs 25284.03 seconds at 1000 training cycle. GRU architecture had one variant introduced to reduce LSTM complexity, which developed with fewer parameters resulting in a faster-trained model compared to LSTM needs 1903.09 seconds when LSTM required 2354.93 seconds for the same training cycle. It also showed equivalent performance with respect to the parameters such as hidden layers and time-step. BLSTM offered impressive training time as 190 seconds at 100 training cycle, though the accuracy was below that of the other RNN architectures which didn’t exceed 90%.
Variables Affecting Marketing Performance of Value Added Milk Product among Dealers in Abia State Nigeria

This study examined the variables affecting marketing performance of value added milk products among dealers in Abia State Nigeria. Data was collected through a random sampling technique with the use of well-structured questionnaire to elicit information from 60 value-added milk dealers from Aba and 30 from Umuahia to have a total of 90 respondents. Simple descriptive statistics and inferential statistics were employed in the data analysis. The result shows that taste contributed more to the sales of vita-milk than other milk products. Vita-milk wholesalers incurred the highest marketing cost followed by viju-milk wholesalers. In summary, the result holds that all the products are profitable and it can be concluded that value-added milk products wholesale marketing is a profitable enterprise. Advertising, price of close substitutes, and size diversification of the product were major factors affecting volume of sales and consumption of the value-added milk products in Abia state. It was recommended that producers of these products do well in improving the outlook of their products such as the tastes, packaging/labeling and advertising so as to increase the buy-back behaviour of the consumers and as such increase market share, profit and sales’ volume.
A brief positioning of ‘ interpersonal pragmatics ’ and ‘ relational work

The field of politeness studies has developed considerably within the last decades and today we are faced with discussions on how to best approach this topic theoretically and methodologically, what its scope of investigation should be and how to best combine it with insights from other research traditions within interpersonal pragmatics (for overviews see Locher, 2012, 2013). This has advanced the field but it has also brought about the need to clarify positions in light of insecurities over terminology and research angle/interest. In this brief statement, I will first position my own understanding of the study of the relational side of language – largely developed together with Richard J. Watts and Andreas Langlotz – and react to a number of issues that were raised in connection with the notion of ‘relational work’ in Spencer-Oatey’s contribution to this special issue.
ANTI α -GLUCOSIDASE, ANTITUMOUR, ANTIOXIDATIVE, ANTIMICROBIAL ACTIVITY, NUTRITIVE AND HEALTH PROTECTIVE POTENTIAL OF SOME SEAWEEDS FROM THE ADRIATIC COAST OF MONTENEGRO

The aim of the present study was to reveal the potential biological activities of the dichlorometane:methanol (1:1) dry extract (DME) and the nutritional value of selected seaweeds: Cymodocea nodosa , Halimeda tuna, Cystoseira barbata and Codium bursa , collected from the Adriatic coast, Montenegro. We assessed the chemical composition and several biological activities such as: anti- α -glucosidase, antitumour, antimicrobial and antioxidative activity. H. tuna had the best cytotoxic activity against human colon carcinoma cell line, LS174 (IC 50 = 17.92 ± 1.54 µg/mL). C. nodosa demonstrated strong cytotoxicity against human adenocarcinoma cell line, HeLa (IC 50 = 13.28 ± 0.39 µg/mL) and human chronic myelogenous leukaemia cell line, K562 (IC 50 = 19.64 ± 1.55 µg/mL). C. barbata had the best anti α -glucosidase (IC 50 = 9.98 ± 3.34 µ g/mL) and antimicrobial activity (minimal inhibitory concentration of 100 µg/mL) for Staphylococcus aureus and Bacillus subtilis . C. bursa showed the highest nutritional value (490.4 kcal).
Value co-creation and purchase intention in social commerce : The enabling role of word-of-mouth and trust Full Paper

Social commerce combines commercial and social activities, and has managed in a very short period of time to attract the interest of researchers and practitioners. In this study we use theories of trust and value co-creation to understand how word-of-mouth (WOM) affects purchase intentions in social commerce settings. Drawing on a sample of 385 survey-based responses from users of social commerce platforms, we empirically examine a set of hypotheses by means of partial least squares analysis. The outcomes of the analysis demonstrate that WOM has a direct effect on purchase intentions, as well as an indirect one by developing a sense of trust to consumers. WOM and its impact on trust also has a positive effect on a consumers’ propensity to engage in value co-creation, which ultimately contributes to increased levels of purchase intentions. In closing, theoretical and practical implications are discussed, and limitations of the study are highlighted.
Genomic Applications on Cray supercomputers : Next Generation Sequencing Workflow

Recent progress in DNA sequencing technology has yielded a new class of devices that allow for the a n lysis of genetic material with unprecedented speed and effic iency. These advances, styled under the name Next-Generation Seq uencing (NGS), increasingly shift the burden from chemistry done in a laboratory to a string manipulation problem, well suited to HighPerformance Computing (HPC). By breaking up DNA into millions of small strands (20 to 1000 bases) and re ading them in parallel, the rate at which genetic material can be acquired has increased by several orders of magnitude at the exp ense of a new distinction between raw and processed genetic data. The technology that generates raw genomic data is becom ing increasingly fast and inexpensive when compared to the rate that this data can be analyzed. In general, assembling s mall reads into a useful form is done by either assembling individu al reads (de novo) or mapping these pieces against a reference (mapp ing). In this paper, we present our experience with Ray, a p arallel shortread de novo assembler code. We also present a configuration f or an NGS workflow based on Sonexion storage and Cray supercomputers. Keywords—Next-generation sequencing; assembler; DNA ; high-performance computing; parallel; genome
THE EFFECTIVENESS OF ACOUSTIC TRAINING ON TONE ACQUISITION BY HONG KONG LEARNERS OF MANDARIN

Pronunciation of Mandarin tone has become one of the most important elements in teaching Mandarin in Hong Kong schools with the implementation of Biliteracy and Trilingualism language policy. Nowadays, pitch contours of Mandarin tones can be visualized with help of acoustic phonetic software such as Praat. The tool can also be used as a tool to help learners improve their pronunciation accuracy. The main purpose of this study is to examine learners’ pronunciation of Mandarin tones before and after acoustic training. The study consisted of three inter-related parts: pre-test, tone visualization training, and post-test. Six female Hong Kong learners of Mandarin were invited to read and listen 24 monosyllabic words and 40 disyllabic words in tests. During the tone visualization training, the participants were involved in five on-campus training sessions and two online self-learning sessions using the acoustic phonetic software Praat. The graphical representations such as the duration, pitch height and pitch contour of each tone and permutation were instructed. Overall, the acoustic training improved the participants’ pronunciation of Mandarin tones. The findings can help develop an effective tone training scheme for L2 Mandarin learners.
A . Interfacing Auditory Models with Speech Models

For some time now, research on automatic speech recognition (ASR) has been largely concerned with what might be called the signal processing approach, in which the recognition of speech by machines was viewed as an information processing problem, quite distinct from the problem of how humans recognise speech. The signal-processing approach has had considerable success in the sense that it has produced a succession of special purpose devices that can recognise speech provided the vocabulary and the number of speakers is limited. It has not, however, led to the development of a general purpose ASR machine that can handle continuous speech from an arbitrary group of speakers using the vocabulary typical of normal conversation. It is also the case that the performance of current systems falls away rapidly when they are required to operate in noisy or reverberant environments. The question then arises as to how best to proceed in the pursuit of the general purpose ASR machine. Some speech scientists argue that we should continue with the signal processing approach; that the quickest and surest route to the general machine is to refine the existing techniques and algorithms. An excellent review of the signal processing approach is presented in Bristow (1986). Others argue that current systems
Pediatric Obesity / Nutrition The frequency of family meals and nutritional health in children : a meta-analysis

s, dissertations) in English or German. Second, we performed forward searches. Using Web of Science, we systematically searched for studies that cited key studies identified in the literature search. Third, we conducted backward searches, i.e. we manually examined the reference lists of reviews on family meals. These searches identified a total of 3,906 articles (see Fig. 1, for a PRISMA flow chart illustrating the study selection process). Inclusion/exclusion of the first 500 studies was determined independently by the first author and a second trained rater. Because the agreement rate (94%) was high (40), the remaining studies were screened by only one rater each. The eligibility criteria for inclusion in the meta-analysis were as follows: (i) a measure of family meal frequency; (ii) at least one indicator of nutritional health and (iii) a statistical association between family meal frequency and nutritional health. Measures of nutritional health considered were (i) BMI, (ii) healthy diet, (iii) unhealthy diet and (iv) overall diet quality. Studies were excluded if (i) children were not the target population; (ii) the study examined children with feeding problems (e.g. children with autism) or with diseases requiring a special diet (e.g. children with cystic fibrosis or diabetes) and (iii) the study reported insufficient statistics to calculate an effect size. Using these criteria, we arrived at a total of 57 studies (13–22,38,41–86).
Comparison of laboratory and in-flight performance of InfraRed Array Camera (IRAC) detector arrays on Spitzer Space Telescope

Judith L. Pipher*, Craig W. McMurtry, William J. Forrest, Craig R. McCreight, Mark E. McKelvey, Robert E. McMurray Jr., Roy R. Johnson, Giovanni G. Fazio, Joseph L. Hora, Lori E. Allen, Matthew L. N. Ashby, Pauline Barmby, Lynne K. Deutsch, Jiasheng Huang, Massimo Marengo, S. Thomas Megeath, Michael A. Pahre, Brian M. Patten, Zhong Wang, Steven P. Willner, William F. Hoffmann, S. Harvey Moseley, Richard G. Arendt, Danny J. Krebs, Peter Eisenhardt, Daniel Stern, Varoujan Gorjian, Bidushi Bhattacharya, William J. Glaccum, Mark Lacy, Patrick J. Lowrance, Sean J. Carey, Seppo Laine, John Stauffer, Jason A. Surace, William T. Reach, Gillian Wilson