Miracle-dz/UniFAR-FTUs huggingface dataset:
Construction of infrastructure index for Indonesia

Purpose The purpose of this paper is to construct indices on Indonesia’s economic infrastructure. The components of infrastructure include transportation, communications and electricity. In constructing the indices, the authors use the longest available data covering the period 1970-2015. The indices of each component of infrastructure are aggregated linearly with the weights calculated using principal component analysis (PCA). The infrastructure index for Indonesia has had a positive increasing trend since 1970, particularly supported by the increase in the infrastructure indices of electricity and telecommunication. Meanwhile, the infrastructure index of transportation has been relatively stable. The infrastructure index constructed shows positive relation with Indonesia’s GDP growth and GDP per capita. Design/methodology/approach In constructing the indices, the authors use the longest available data covering the period 1970-2015. The indices of each components of infrastructure are aggregated linearly with the weights calculated using PCA. Findings The infrastructure index for Indonesia has a positive increasing trend since 1970, particularly supported by the increase in the infrastructure indices of electricity and telecommunication. Meanwhile, the infrastructure index of transportation has been relatively stable. The infrastructure index constructed shows positive relation with Indonesia’s GDP growth and GDP per capita. Originality/value The novelty of this research is a construction of the infrastructure index for Indonesia. The infrastructure index is important to benchmark the level of infrastructure development and to understand its connection to economic growth. It is also an important barometer used by policymakers for infrastructure investment and planning purposes.
Compliance with School-Based Management Standards: An Assessment for Policy Formulation

Basic education is challenged to be responsive to the current demands ofquality education through the efficient delivery of educational servicesand the translation of knowledge, skills, and attitudes that enable thelearners to attain mandated learning outcomes. Over the past decades,many initiatives and reform efforts have been implemented to realizethe thrusts of Basic Education Reform Agenda. One key response of thenational government is the implementation of the standard principles ofthe School-Based Management (SBM). Two elementary schools in theDivision of San Carlos City in Negros Occidental, Philippines, implementSBM with an ultimate goal of achieving learning outcomes. This studyaimed to assess the level of compliance with the standard principles ofSBM and its implication to the quality of life among the learners beyondbasic education using a descriptive-comparative research design. Theparticipants were internal and external assessors identified througha predetermined criterion. The data were collected through SBMstandardized survey form with the necessary supporting documentsincluding focus group discussion (FGD) relative to the compliance withSBM standards. The findings revealed that the two central schools areon Level 2 and are categorized as maturing schools, wherein, most ofthe standard principles of SBM are complied with and implemented forcontinuous improvement. Both schools are prepared for National SBMlevel 3 accreditation relative to the SBM principles.
Who Pays Attention to SEC Form 8-K?

The SEC requires public companies to disclose material information on Form 8-K within four days of a triggering event. We show that, on 8-K event and filing dates, there is significant abnormal attention on Bloomberg terminals, which are a source of information for institutional investors, while traditional media attention tends to be higher on filing days. Significant price discovery occurs on the event date and on the days between that day and the filing date. The traditional media coverage on the filing day appears to attract the attention of retail investors and leads to further price changes in the direction of the pre-filing day price change. Institutional investors exploit this price pressure via opportunistic liquidity provision. Overall, our evidence suggests that the Form 8-K filing may have little direct informational benefit, particularly to retail investors.
Using Twitter to observe election incidents in the United States

Individuals’ observations about election administration can be valuable to improve election performance, to help assess how well election forensics methods work, to address interesting behavioral questions and possibly to help establish the legitimacy of an election. In the United States such observations cannot be gathered through official channels. We use Twitter to extract observations of election incidents by individuals all across the United States throughout the 2016 election, including primaries, caucuses and the general election. To classify Tweets for relevance and by type of election incident, we use automated machine classification methods in an active learning framework. We demonstrate that for primary election day in one state (California), the distribution of types of incidents revealed by data developed from Twitter roughly matches the distribution of complaints called in to a hotline run on that day by the state. For the general election we develop hundreds of thousands of incident observations that occur at varying rates in different states, that vary over time and by type and that depend on state election and demographic conditions. Thousands of observations concern long lines, but even more celebrate successful performance of the election process—testimonies that ”I voted! ” proliferate.
Identifying an appropriate science curriculum for undergraduate nursing in New Zealand

The depth and breadth of science knowledge that is required to educate registered nurses has been the subject of much debate, both nationally and internationally. Central to the debate is the lack of clarity on what science is required for nursing. Nursing students world-wide report anxieties and difficulties with learning science within nursing programmes. It has not been established if science is required for nursing, nor has it been established how science is used by nurses engaged in clinical practice. This research was aimed at examining the use of science in nursing practice and therefore identifying an appropriate undergraduate nursing science curriculum for New Zealand nursing schools. To achieve this aim, a mixed method, interpretive, naturalistic approach has been employed involving interviews, surveys, observation studies and document analysis. The research had four phases; interviews with nine nurse educators and lecturers, written surveys undertaken by 71 registered nurses, observation and indepth interviews with 17 registered nurses’ in practice across the central and lower North Island, and document analysis. Nurse educators and lecturers were interviewed to gain their perspectives of the role of science in nursing. A Science Attitude and Self-Efficacy (SASE) survey included sections that focused on nurses’ attitudes towards their nursing science courses, attitudes towards science in nursing, and probed their confidence in their own ability to use science in practice. Observations of nurses in their clinical practice were conducted over several hours and the nurses interviewed about their observed actions. The observed nursing actions and espoused science knowledge that were extracted from clinical practice were categorised into science and science-related topics which frame the breadth of content used in nursing practice, and the depth was ascertained by the level of complexity the nurse was able to articulate. Document analysis of curriculum information as well as Nursing Council of New Zealand standards for education, competencies and scopes of practice was also performed to ascertain the importance and relevance of science to nursing practice. Nursing Council documents state that science is important for all levels of nursing practice, from patient observation, to clinical decision-making. Science knowledge assists the nurse when conducting risk analyses and when performing
An Expectation–Maximization-Based IVA Algorithm for Speech Source Separation Using Student’s t Mixture Model Based Source Priors

The performance of the independent vector analysis (IVA) algorithm depends on the choice of the source prior to better model the speech signals as it employs a multivariate source prior to retain the dependency between frequency bins of each source. Identical source priors are frequently used for the IVA methods; however, different speech sources will generally have different statistical properties. In this work, instead of identical source priors, a novel Student’s t mixture model based source prior is introduced for the IVA algorithm that can adapt to the statistical properties of different speech sources and thereby enhance the separation performance of the IVA algorithm. The unknown parameters of the source prior and unmixing matrices are estimated together by deriving an efficient expectation maximization (EM) algorithm. Useful improvement in the separation performance in different realistic scenarios is confirmed by experimental studies on real datasets.
The knowledge, skills and competencies for effective public affairs practice: A mechanism to embed ethics

In the United Kingdom (UK) there has been concern and scepticism as to the role of public affairs in supporting the democratic process. At the heart of this debate are issues around the motives of those conducting public affairs. This chapter is based on a pilot study that explores the knowledge, skills and competencies for effective public affairs practice. It raises the possibility that by adopting a competency-based approach there can be a mechanism to embed ethics visibly into practice improving the quality of public affairs practice and demonstrating the positive impact that advocacy plays. It is based on synthesising scholarship from the fields of public affairs and human resource management, six pilot interviews and an exploratory analysis of professional competency frameworks. Early results suggest an appetite and an opportunity to create a framework that can add conceptual and practical value.
Firm specific determinants of markup ‐ the case of Slovenian manufacturing firms

Abstract Investigations of firms’ pricing decisions and performances have been twofold. While within the industrial organisation framework stress is placed on industry‐specific factors and the market power of firms within industries, various organisational theories emphasise the role of ‘soft’ factors in the determination of firms’ performance. The main thesis of our paper is that the size of a firm's markup can mostly be explained by the firm's productivity, capital and labour costs, as well as the firm's market power and organisational structure characteristics, when the external environment and industry membership is controlled for. Our objective is thus to explain firm‐level markups by a set of firm‐specific factors. The empirical analysis of markup determinants is based on a sample of Slovenian manufacturing firms (NACE 15–37) in the 1994–2003 period, applying panel data regression GLS model and ANOVA analyses. We find that, besides market share and cost factors, organisational structure change occur.
Research on the discovery of opinion leaders in social networks

Since entering the era of Wed 2.0, social networks have been an indispensable part of human life. At present, these social networks are the main source of information dissemination and alienation, and they play a key role in the process of dissemination and are the central users of social networks. Central users have an incredible ability to communicate in their community, and their knowledge and experience of things have a great impact on other users in the community. This research mainly uses the analysis method of social network to analyze the community and find the central users in the community. We use Louvain algorithm to identify the community structure in social networks, and on this basis we use PageRank algorithm to analyze the central users in each community.
Self-help groups in India: challenges and a roadmap for sustainability

Purpose Self-help groups (SHGs) have widely been accepted by developing nations for their contribution to inclusive development. Despite its importance and the recognition of the same, SHGs and their members face several challenges. The purpose of this paper is to comprehensively investigate the inhibiting factors affecting the effectiveness of women SHGs. The paper also proposes a roadmap for all the self-help promoting institutions, such as banks, state and central government, and non-government organizations to address the challenges. Design/methodology/approach The study adopts an exploratory research design to undertake this applied research. It uses phenomenographic and interpretative approaches. Qualitative data have been collected from 24 members belonging to eight SHGs from the eastern Indian state of Odisha with the help of a semi-structured interview schedule. The result has been analyzed by using content analysis. Findings The study finds that SHG members in Odisha face several challenges in the form of financial bottlenecks, entrepreneurial obstacles, capacity-building impediments, mentor-ship challenges, socio-structural challenges and group dynamics. Research limitations/implications The study finds many unique and contextual inhibiting factors, which are valuable additions to the existing literature. At the same time, the result may not be applicable to other kinds of SHGs, such as Alcoholic Anonymous, as their nature, composition and deliverables are quite different from the SHG that the current study has taken into consideration. Practical implications The proposed roadmap would be useful to policymakers, non-government organizations and other agencies involved in the promotion and capacity building of SHGs operating in Odisha in particular and India in general. Originality/value The literature is mainly concerned with the impact evaluation of SHG programs. This study investigates the challenges faced by SHGs in a systematic way and provides a roadmap to address the same in a comprehensive way.
Evaluando el impacto de las medidas de desdolarización del crédito en el Perú

Este trabajo evalua el impacto de las medidas que el BCRP implemento entre 2013 y 2016. Nuestros resultados muestran que, a pesar de la existencia de una ligera tendencia a la baja en los indicadores de dolarizacion del credito antes de su implementacion, el ritmo de desdolarizacion se acelero luego de la adopcion de las medidas de politica anteriormente mencionadas, especialmente luego del anuncio a inicios de 2015. Se encuentra evidencia que senala que desde el anuncio del primer paquete de medidas, 6 de los 10 puntos porcentuales de reduccion en el grado de dolarizacion del credito esta asociado a la implementacion del Programa de Desdolarizacion. A diferencia del impacto homogeneo de las medidas de 2015 en adelante en todos los segmentos de credito, las medidas de 2013 afectaron principalmente ciertos segmentos tales como corporativos y empresas pequenas. Asimismo, se identifica un efecto heterogeneo por tamano del credito, donde los bancos prefirieron sustituir los prestamos de mayor tamano de moneda extranjera a moneda domestica.
From the Dynamic Lattice Liquid Algorithm to the Dedicated Parallel Computer – mDLL Machine

: The designing, production and testing of the mDLL machine led to the development of such a structure in which operational cells (e.g. KDLL) were located in the nodes of a three-dimensional torus network and the device was scalable. Thus, the future expansion of this device with additional Printed Circuit Boards (PCB) will not result in lengthened wire connections between Field-Programmable Gate Arrays (FPGA) or slow down the operation of the machine. The conducted tests conﬁrmed the correctness of the adopted design assumptions and showed that by using mDLL one can effectively perform molecular simulations. Despite some structural shortcomings, the mDLL machine was a prototype that has already been sufﬁciently tested to allow the technology used in it to be used to build a device with a number of 1 million to 5 million KDLL cells. Such a device would already be suitable for simulating multi-particle systems with unprecedented speed.
Is It Possible to Manage the Product Recovery Processes in an ERP? Analysis of Functional Needs

In today’s business environment, different factors make product return and product recovery increasingly more important in order to recover value and increase the company’s profitability. In such an environment, where sustainability concerns and awareness of environmental responsibility in industrial production has considerably grown, reverse logistics (RL) becomes more relevant and, thus, its correct management using suitable information systems (IS) is fundamental. Nevertheless, today’s IS in general, and in Enterprise Resources Planning (ERP) in particular, are developed based on conventional logistic processes that do not contemplate the specific characteristics of RL. The main objective of this work is to analyze the functional requirements of an IS to manage product recovery processes that serve as a guide to develop a suitable ERP for RL. The research methodology has been conducted with a qualitative approach, through which the main specific requirements that an IS must meet to manage RL have been stablished, and a data model for the development of solutions to the requirements identified in an ERP system has been proposed. For the development in the ERP it is recommended to start with the requirement of RBOM (Reverse Bill Of Materials) management, since it is the most complex development and has a greater relationship with the rest.
Osteoarthritis: the role and mechanisms of the chondroprotective peptide Urocortin I

Osteoarthritis (OA), a chronic degenerative condition of the diarthrodial joints is most predominant amongst the middle aged and elderly population, where it is associated with progressive disability and deformity of the joints. Whilst the exact mechanism of OA pathogenesis is currently unknown, chondrocyte death by apoptosis is seen as one of the main contributors to the disease process. It is increasingly recognised that the overproduction of mediators such as Nitric Oxide (NO) in Osteoarthritic cartilage contributes to the disease pathology partly by inducing chondrocyte apoptosis. Therefore, agents, which protect against NOinduced mitochondrial injury, may have therapeutic potential in Osteoarthritis. The CRF related peptide, Urocortin I (UCNI), has been shown to protect the human chondrocyte cell line, C-20/A4, from SNAP/NO induced apoptotic death, but little is yet known about its mechanism of action. Therefore the aim of this project is to investigate the potential mechanism through which UCNI exerts its observed protective effects. The studies documented here, have demonstrated the endogenous expression of this cytoprotective peptide, UCNI, by C-20/A4 chondrocytes and have shown that treatment of chondrocytes with SNAP (a NO donor) resulted in a significant increase in apoptosis which was abrogated by the addition of exogenous UCNI. Therefore, an investigation into the potential mechanism for UCNI mediated protection against apoptosis in chondrocytes (i.e. chondroprotection) detected the mRNA expression of both CRFR1 and CRFR2 receptors specifically the CRFR1? and CRFR2? splice variants by the C-20/A4 chondrocytes. However the CRFR antagonist, ? helical CRH failed to induce apoptosis or abrogate the protective effects of UCNI against SNAP/NO induced apoptosis. RT-PCR studies have also demonstrated C-20/A4 mRNA expression of the Kir6.1, Kir6.2, SUR1 and SUR2B subunits of the KATP channels suggesting that functional KATP channels are also present in these cells, which represent a further putative mechanism of action for UCNI. Quantitative PCR studies were performed to determine regulation of CRFR and Kir6.1 expression by UCNI. These studies showed that treatment of chondrocytes with UCNI and SNAP alone and concurrently resulted in no significant change in mRNA expression of either CRF receptors or kir6.1 (the pore forming subunit of the mitochondrial KATP channel). Treatment of chondrocytes with Diazoxide, a mitochondrial KATP channel opener, resulted in a reduction in SNAP induced apoptosis, mimicking that seen for UCNI, suggesting a similar protective role for these channels in chondrocytes, to that proposed in other cell types and supporting these channels as potential targets for UCNI in chondroprotection.
Semi empirical models for drying of agricultural products by used structured artificial neural network

We compared a semi empirical and an empirical model. The empirical model is a multilayer ANN. The semi empirical model is a custom multilayer ANN. It is a structured model, and we define the structure by hand before the training of the network. The influence of the neuron numbers on the accuracy of the models was also investigated by statistical approach. We found that the custom multilayer ANNs developed like this, are suitable for modelling the drying process of agricultural materials. They also provide the ability to improve the applicability of the empirical models. Furthermore, the semi empirical model has a higher sensitivity on neuron number applied. Keywords: drying; energetics; artificial neural network; semi-empirical model.
Asymmetrical relationship between oil price shocks and trade deficit: Evidence from Pakistan

This study investigates the asymmetric impact of oil price shocks on trade deficit for Pakistan economy, using NonLinear ARDL analysis, over the period of 1990QI-2016QIV. The estimation results confirm the presence of nonlinearity in the series. The bound testing approach also establishes the existence of asymmetric relationship between trade deficit and oil price movements. We find that increase (decrease) in oil prices and wholesale prices and decrease (increase) in industrial product results in a significant increase (decrease) in trade deficit. The adjustment pattern, using dynamic multipliers, reveals that the new long-run equilibrium for oil prices can be archived after 1 year and 2 months, wholesale prices by 3 years and 8 months and for industrial growth in 6 years and 6 months. This paper has important policy implications for Pakistani decision-makers.
Convolutional Support Vector Machines For Image Classification

The Convolutional Neural Network (CNN) is a machine learning model which excels in tasks that exhibit spatially local correlation of features, for example, image classification. However, as a model, it is susceptible to the issues caused by local minima, largely due to the fully-connected neural network which is typically used in the final layers for classification. This work investigates the effect of replacing the fully-connected neural network with a Support Vector Machine (SVM). It names the resulting model the Convolutional Support Vector Machine (CSVM) and proposes two methods for training. The first method uses a linear SVM and it is described in the primal. The second method can be used to learn a SVM with a non-linear kernel by casting the optimisation as a Multiple Kernel Learning problem. Both methods learn the convolutional filter weights in conjunction with the SVM parameters. The linear CSVM (L-CSVM) and kernelised CSVM (K-CSVM) in this work each use a single convolutional filter, however, approaches are described which may be used to extend the K-CSVM with multiple filters per layer and with multiple convolutional layers. The L-CSVM and K-CSVM show promising results on the MNIST and CIFAR-10 benchmark datasets.