Miracle-dz/UniFAR-FTUs huggingface dataset:
Media startups as examples of innovation in Spanish media market. A study of cases

Introduction: The media industry is undergoing a process of constant change. News organisations must adapt to new technologies and consumption patterns. However, the large infrastructures and rigid processes and mentalities of most media complicate this adaptation and leave room for new innovative and flexible actors: the startups. Methods: The study is based on the case study of four startups in Spain: Politibot, Cuonda, Datadista and Newskid. Information is collected from the founders of these initiatives through a questionnaire interview, while documentary research is used to examine the features of these projects. Results and discussion: These startups are committed to exploring new formats, distribution channels and revenue streams through the use of technology and focus their efforts on specific niches. The results highlight the importance of flexibility, open mindedness and multidisciplinary teamwork in the new media market.
THE COLLECTION OF INFORMATION CONTROL CENTER

Consider the option of building the last miles to telecom operators, in accordance with the requirements for the construction of the last miles of control centers in the power industry. A variant is proposed for constructing a typical network node of the last miles of the control center, taking into account all the necessary interfaces for the transmission of dispatch telephone communication channels, telemetry information transmission channels, as well as service communication channels and information exchange between electric power entities and dispatch centers. A variant of the construction and topology of the last miles of the control center, methods of reservation of channels to access nodes are described. All types and types of interfaces that are necessary to use for the organization of dispatch communication channels and the transmission of telemetric information in the dispatch centers of the regional level have been determined. The use of various types of interfaces for service purposes is described in detail. Separate types of interfaces are used for voice transmission and for dispatch communication channels with objects. The variants of using analog interfaces for transmitting telemetry information via corresponding communication channels, which are used for cent equipment with analog outputs, are described. There are several types of redundancy of communication channels to ensure uninterrupted operation of the control center and to exclude the possibility of disabling the main and backup channels at the same time when working with a particular object. The redundancy of the hardware is carried out by installing additional cards in the equipment of the nodes in the cold reserve. Power redundancy is carried out due to the presence of at least two power supply units of the equipment for connection from two different sources of the uninterruptible power supply system. There is a reserve for the optical fibers of the last miles to the access nodes, which in turn allows you to change the transport transmission line in case of failure of the current one.
Homogeneous Regions for Image Segmentation Based on Fuzzy Logic

This paper mainly replicates the idea of Fuzzy logic for homogeneous edge cutting algorithm for image segmentations. Soft Computing is an emerging field that consists of complementary elements of fuzzy logic, neural computing and evolutionary computation. Soft computing techniques have found wide applications. One of the most important applications is edge detection specifically at homogeneous regions for image segmentation based on Fuzzy logic. The process of partitioning a digital image into multiple regions or sets of pixels is called image segmentation [3]. Edge is a boundary between two homogeneous regions. Edge detection refers to the process of identifying and locating sharp discontinuities in an image.
Effects of Dietary Zinc Levels on the Growth Performance , Organ Zinc Content , and Zinc Retention in Broiler Chickens

The objective of this study was to investigate the optimal zinc (Zn) requirement of broiler chickens based on Zn retention. On the day of hatch, 350 male Ross 308 broilers were randomly assigned to seven treatments with five replicates of ten birds each. Zinc was supplemented as ZnSO4·7H2O at 0, 20, 40, 60, 80, 100, or 120 mg/ kg in the starter diet (fed from 1 to 21 d of age) and at 0, 16, 32, 48, 64, 80, or 96 mg/kg in the grower diet (fed from 22 to 42 d of age). The analyzed Zn levels were 34.98 and 27.57 mg/kg in the basal starter and grower diets, respectively. Supplemental Zn levels did not influence body weight gain, feed intake, feed conversion ratio, or liver Zn content of broilers at 21 and 42 d of age (p>0.05). Tibia ash Zn content of 21-d-old broilers increased when Zn supplementation level increased from 0 to 40 mg/kg Zn in (p<0.05). The highest breast muscle Zn content in 42-d-old broilers was observed when 100 and 80 mg Zn/ kg was supplemented in the starter and grower diets, respectively. Fecal Zn content, Zn intake, Zn excretion, and Zn retention of 31to 33-d-old broilers linearly increased with supplemental Zn levels (p<0.05). Zinc retention values, calculated as the difference between Zn intake and Zn excretion, were negative, about zero, and positive when starter/grower diets were supplemented with 0/0 and 20/16, 40/32, and 60/48 and 120/96 mg/kg, respectively. These results indicate that supplementing 40 and 32 mg Zn/kg in starter and grower diets, respectively, promote the growth performance of broiler chickens, while reduce Zn excretion in the environment.
Consumers' Acceptance of Internet Shopping

The rapid growth of Internet has created a new medium for shopping, that is Internet shopping. Instead of going to departmental stores, people can easily purchase the goods or services they need through this media. This medium also provides services 24 hours per day, and seven days a week. Consequently, this phenomenon has created huge opportunities for merchants in doing business. In designing the right way of doing business over the Internet, merchants need to understand their customers’ characteristics. The objective of this study is to investigate the individual differences such as prior Web experience, shopping orientation and demographic factors that will influence intention to shop on the Web, mediated by the perceived usefulness and perceived ease of use. The model of this study adapt the refined of Davis’ (1989) TAM model that is proposed by Venkatesh (1996) and individual differences factors that is proposed by Crisp et al. (1997).
Who Is More Collectivistic? Hong Kong Chinese or Australian Chinese

This study investigated the relative importance of self-esteem and collective self-esteem (CSE) in predicting subjective wellbeing (SWB) for the Hong Kong Chinese and Australian Chinese, with the latter group comprising the first generation and second generation immigrants. By embedding in the homeostatic model of SWB, both self-esteem and CSE predicted SWB variance for all Chinese respondents, though it was intriguing that CSE made stronger prediction for the Australian Chinese than Hong Kong Chinese and that the amount of SWB variance contributed by CSE was the highest for the Australian second generation Chinese immigrants. These results were consistent with the higher level of collectivism measured in the Australian Chinese. Explanations are in the context of migrant status.
Acousto-electric tomography with total variation regularization

We study the numerical reconstruction problem in acousto-electric tomography of recovering the conductivity distribution in a bounded domain from interior power density data. We propose a numerical method for recovering discontinuous conductivity distributions, by reformulating it as an optimization problem with L1 fitting and total variation penalty subject to PDE constraints. We establish continuity and differentiability results for the forward map, and the well-posedness of the optimization problem, and present an easy-to-implement and robust numerical method based on successive linearization, smoothing and iterative reweighting. Extensive numerical experiments are presented to illustrate the feasibility of the proposed approach.
MEC 2017: Multimodal Emotion Recognition Challenge

This paper introduces baselines for the Multimodal Emotion Recognition Challenge (MEC) 2017, which is a part of the first Asian Conference on Affective Computing and Intelligent Interaction (ACII Asia) 2018. The aim of MEC 2017 is to improve the performance of emotion recognition in real-world conditions. The Chinese Natural Audio-Visual Emotion Database (CHEAVD) 2.0 is utilized as the challenge database, which is an extension of CHEAVD as released in MEC 2016. MEC 2017 has three sub-challenges and 31 teams participate in either all or part of them. 27 teams, 16 teams and 17 teams participate in audio (only), video (only) and multimodal emotion recognition sub-challenges, respectively. Baseline scores of the audio (only) and the video (only) sub-challenges are generated from Support Vector Machines (SVM) where audio features and video features are considered separately. In the multimodal sub-challenge, feature-level fusion and decision-level fusion are both utilized. The baselines of the audio (only), the video (only) and the multimodal sub-challenges are 39.2%, 21.7% and 35.7% in macro average precision.
Reconfigurable Sensor Analog Front-End Using Low-Noise Chopper-Stabilized Delta-Sigma Capacitance-to-Digital Converter

This paper proposes a reconfigurable sensor analog front-end using low-noise chopper-stabilized delta-sigma capacitance-to-digital converter (CDC) for capacitive microsensors. The proposed reconfigurable sensor analog front-end can drive both capacitive microsensors and voltage signals by direct conversion without a front-end amplifier. The reconfigurable scheme of the front-end can be implemented in various multi-mode applications, where it is equipped with a fully integrated temperature sensor. A chopper stabilization technique is implemented here to achieve a low-noise characteristic by reducing unexpected low-frequency noises such as offsets and flicker noise. The prototype chip of the proposed sensor analog front-end is fabricated by a standard 0.18-μm 1-poly-6-metal (1P6M) complementary metal-oxide-semiconductor (CMOS) process. It occupies a total active area of 5.37 mm2 and achieves an effective resolution of 16.3-bit. The total power consumption is 0.843 mW with a 1.8 V power supply.
PREDICTION OF HEART DISEASE USING K-MEANS and ARTIFICIAL NEURAL NETWORK as HYBRID APPROACH to IMPROVE ACCURACY

— The heart is important organ of human body part. Life is completely dependent on efficient working of the heart. What if a heart undergoes a disorder, cardiovascular diseases are the most challenging disease for reducing patient count. According to survey conducted by WHO, about 17 million people die around the globe due to cardiovascular diseases i.e 29.20% among all caused death, mostly in developing countries. Thus there is a need of getting rid of the this complicated task CVD using advanced data mining techniques, in order to discover knowledge of Heart disease prediction. In this paper, we propose an efficient hybrid algorithmic approach for heart disease prediction . This paper serves efficient prediction technique to determine and extract the unknown knowledge of heart disease using hybrid combination of K-means clustering algorithm and artificial neural network. In our proposed model we considered 14 attribute out of 74 attributes of UCI Heart Disease Data Set [19]. This technique uses medical terms such as age, weight, gender, blood pressure and cholesterol rate etc for prediction. To perform grouping of various attributes it uses k-means algorithm and for predicting it uses Back propagation technique in neural networks. The main objective of this paper is to develop a prototype for predicting heart diseases with higher accuracy rate.
The Selective Inhibitor of Nuclear Export Compound, Selinexor, Inhibits NF-κB and Induces Anti-Non-Small Cell Lung Cancer Activity Regardless of p53 Status

Non-small cell lung cancer (NSCLC) has poor prognosis even with various treatment options. Unfortunately, resistance develops quickly and novel therapies are needed. Exportin-1 (XPO1) is a nuclear export protein upregulated in many types of cancers. Inhibition of XPO1 by selinexor (KPT-330), an oral Selective Inhibitor of Nuclear Export (SINE) compound, leads to nuclear accumulation of tumor suppressor proteins (TSPs), cell cycle arrest and cancer cell death. Selinexor is being evaluated in Phase I and II clinical trials in many different cancer indications (see clinicaltrials.gov for details) including lung cancer (NCT02351505). To date, selinexor has been given to >1400 patients and has shown good tolerability with manageable side effects. In this study the effects of selinexor on NSCLC cell growth and apoptosis were evaluated in vitro and in vivo. Selinexor inhibited tumor cell growth and clonogenic formation and induced cell cycle arrest and apoptosis in cell lines regardless of genetic background (EC50: 25-700 nM). The XPO1 cargo proteins p53, p21, IκB, E2F4, and survivin demonstrated strong nuclear localization after 4 to 24 hour treatment with selinexor followed by apoptosis (i.e. PARP, caspases-3 and -8 cleavage). Selinexor altered the localization of the NF-κB inhibitor IκB and functional evaluation of NF-κB in A549 and NCI-H1299 revealed transcriptional repression with EC50 values similar to the inhibition measured in cell proliferation assays. A549 xenografts in mice treated with selinexor showed markedly greater tumor growth inhibition (%TGI=81% at 20 mg/kg selinexor vs vehicle, p<0.0001) versus cisplatin-treated mice (%TGI=13% at 5 mg/kg cisplatin vs vehicle, p=0.06) when compared to vehicle. Using IHC on paraffin embedded tissue, treated tumors showed reduced cell proliferation (Ki67) while inducing nuclear accumulation of p53, p21, FOXO1, survivin, NF-κB and IκB. In NSCLC, selinexor forces nuclear retention of TSPs, inhibits tumor growth and NF-κB transcriptional activity, and induces cell death regardless of p53 status. These data demonstrate therapeutic potential for the treatment of NSCLC.
The Effect of Nature Education Program on the Level of Environmental Awareness of the Elementary School Students from Different Socioeconomic Status

The main purpose of this study is to examine the effect of the nature education program on the environmental awareness levels of the elementary school students from different socioeconomic status. The study is designed in a concurrent nested mixed method. Pretest-posttest quasi-experimental model for quantitative data and case study model for qualitative data were used in accord with this research design. The study group consists of 78 students determined by the proportional cluster sampling method among 4th grade students in the Konya province center during 2016-2017 education years that participated in the education class in Konya Tropical Butterfly Garden, and also voluntarily participated in the research. TURKSTAT data, teachers, student information forms and voluntary participation were taken into consideration while determining the study group. The data of the study were collected with the 35-item Elementary School Environment Awareness Scale developed for the research project. In the analysis of the quantitative data, significance tests were applied, and qualitative data were analyzed by content analysis.
Implementation and evaluation of coherent synthetic aperture radar processing for level measurements of bulk goods with an FMCW-system

Abstract. In industrial process measurement instrumentation, radar systems are well established for the measurement of filling levels of liquids in tanks. Level measurements of bulk goods in silos, on the other hand, are more challenging because the material is heaped up and its surface has typically a relatively complex shape. In this paper, the application of synthetic aperture radar (SAR) reconstruction with a frequency modulated continuous wave (FMCW) radar system for level measurements of bulk goods is evaluated. In the proposed monostatic setup, echo signals are acquired at discrete antenna positions on top of the silo. Spatially resolved information about the surface contour of a bulk good heap is reconstructed by coherent 'delay and sum' processing. The concept has been experimentally evaluated with a 24 to 26 GHz FMCW radar system mounted on a linear stepping motor positioning unit. Measurements on a thin metal wire at different range and on a curved test-object with a diffusely scattering surface have been performed to analyze the system's point spread function (PSF) and performance. Constant range and azimuth resolutions (−6 dB) of 15 cm and 8 cm, respectively, have been obtained up to a range of 6 m, and results of further evaluations show that the proposed concept allows more accurate and reliable level reconstructions of surface profiles compared to the conventional approach with measurements at a single antenna position.
Accounting for Excess Zeros and Sample Selection in Poisson and Negative Binomial Regression Models

We present several modifications of the Poisson and negative binomial models for count data to accommodate cases in which the number of zeros in the data exceed what would typically be predicted by either model. The excess zeros can masquerade as overdispersion. We present a new test procedure for distinguishing between zero inflation and overdispersion. We also develop a model for sample selection which is analogous to the Heckman style specification for continuous choice models. An application is presented to a data set on consumer loan behavior in which both of these phenomena are clearly present.
Increasing Teacher Awareness of STEM Careers

Teacher awareness of STEM careers impacts students as they consider career choices. Researchers examined the effects of teacher professional development and lesson implementation in integrated science, technology, engineering, and math (STEM) on teacher awareness of STEM careers. Study subjects were high school science and engineering/technology teachers participating in a ten-day, 70-hour summer professional development institute (PROJECT NAME) designed to educate teachers in adopting an integrated STEM education model. The study used a quasi-experimental nonequivalent control group design that incorporated an experimental group and an untreated control group with both pretest, posttest, and delayed posttest assessments of non-randomized participants. Researchers analyzed changes in scores on the T-STEM survey of STEM career awareness using cumulative link mixed models (CLMM). STEM career awareness increased for teachers participating in professional development and the degree of change varied by group and assessment time.
Exploratory and confirmatory factor validation and psychometric properties of the HR roles for HR managers in Malaysia

The effectiveness ofthe Human Role Assessment Survey Questionnaire, HRASQ. (Conner and Ulrich. 1996) was investigated with a sample of 108 Human Resource (HR) managers. The exploratory and confirmatoryfactor analyses showed that the 3-subscale structure ofthe HRASQ was valid. In addition, the results verified that the HRASQ had high internal reliability. These results indicated that the HRASQ and its subscales can be used in research related to role ofthe HR in Malaysia.
Analysis of unsupervised aspect term identification methods for Portuguese reviews

Automatic term identification is a fundamental task for text mining and many other natural language processing applications. Based on the tradition of statistical and symbolic methods, whether adopting or not machine learning techniques, new hybrid proposals for term extraction have arisen. In this paper we investigate the above approaches in an unsupervised way to identify relevant terms in Portuguese, focusing on book reviews. Terms, in this context, usually represent opinion aspects, whose identification is a challenging and an equally important task. We show that current methods have varied performances, but that we may significantly improve their results by considering the distributional properties of words. Resumo. A identificação automática de termos é fundamental na mineração de textos e em aplicações de processamento de linguagem natural. Com base em métodos estatı́sticos e simbólicos, adotando ou não técnicas de aprendizado de máquina, surgiram novas propostas hı́bridas para extração de termos. Neste trabalho, investigamos essas abordagens de forma não supervisionada para identificar termos relevantes em Português, com foco em revisões de livros. Os termos, neste contexto, geralmente representam aspectos de opinião, cuja identificação é uma tarefa desafiadora e igualmente importante. Mostramos que métodos atuais têm desempenhos variados, mas que seus resultados podem ser melhorados considerando as propriedades distribucionais das palavras.
Measures of Adiposity in the Identification of Metabolic Abnormalities in Middle-aged and Older Korean Adults

† Corresponding Author: Hyeon Chang Kim, PhD Department of Preventive Medicine, Yonsei University College of Medicine, 50 Yonsei-ro, Seodaemun-gu, Seoul 120-752, Korea. Tel: +82-2-2228-1873 E-mail: hckim@yuhs.ac * This study was supported by grants from the Korean Health Technology R&D Project (HI13C0715). [접수일: 2014년 06월 11일, 수정일: 2014년 08월 12일, 게재확정일: 2014년 10월 06일] Abstract Ji Hye Park1), Hyeon Chang Kim2)†, Ju-Mi Lee2), Dong Phil Choi1), Bo Mi Song1),
Characterizing Information in Physical Systems: from Biology to Black Holes

In this thesis, we use classical and quantum information theory to probe fundamental questions about living and nonliving physical systems, including developing embryos, conformal field theories, black holes, and holographic dualities. We begin by analyzing how spatially varying concentrations of four proteins in the early stage fruit fly embryo are able to encode enough information to specify a precise body plan for the developed adult fly. We then transition to studying how information is tied to physics in nonliving systems, beginning with a conjecture on the structure of universal terms in the Rényi entropy in 3 + 1-d CFT. In the following pair of chapters, we use “topological” entanglement in AdS3/CFT2 duality as a springboard for developing a precise correspondence between Liouville theory and the topological sector of 2+1-d gravity. Then, in the final chapter, we study the “information flow” among energy scales in a 2-d field theory constructed as a CFT deformed by the irrelevant dimension-4 operator T T̄ . We do so by constructing an explicit manifestation of holographic RG. By identifying the T T̄ coupling with a hard cutoff in the bulk, we are able to exactly match the thermodynamics of a “black hole in a box” with the physics of an integrable field theory. Throughout, our goal is to demonstrate that studying uncertainty with information theory, entanglement, and renormalization group flow allows us to organize the unknowns and thus obtain new methods for constraining, characterizing, and dualizing the system at hand. In the process, we learn fundamental properties we might not have otherwise known to study.
Penggunaan BUKU dan Kepemilikan dalam Menganalisis Efisiensi Perbankan di Indonesia

In December 2016, there are 116 commercial banks in Indonesia. Those banks are divided into few categories. Two of them are commercial banks based on business activity (BUKU) and based on ownership. This research analyzes all commercial banks that operates between 2012 and 2016 and divide them into two categories mention before. The aim of the research is to find out efficiency score using SFA method based on those two categories. The result show that banks in BUKU 3 have the highest efficiency score, followed by BUKU 1, BUKU 4 and BUKU 2. Meanwhile, on ownership category, state owned enterprise banks have the highest score. It then followed by foreign banks, private . banks, municipal banks and the last one mix ownership banks