Miracle-dz/UniFAR-FTUs huggingface dataset:
The Impact of High-Tech Industry Agglomeration on Green Economy Efficiency—Evidence from the Yangtze River Economic Belt

Development is the eternal theme of the times. However, the transformation of the development mode is imminent, and we should abandon the extensive economic development mode and turn to the efficient development of an intensive mode. The high-tech industry will be the decisive force in future industrial development. The agglomeration of the industry will help form economies of scale, thereby improving the effective allocation of resources and promoting productivity. The increase in green economy efficiency is a key factor in achieving green development and an important indicator of achieving the coordinated development of economic development and environmental protection. Therefore, in this study, we try to improve the efficiency of the green economy through industrial agglomeration to achieve green development. In order to solve this problem, we took the Yangtze River Economic Belt as the research object, used Super Slacks-based Measure (SBM) data envelopment analysis (DEA) and general algebraic modeling system (GAMS) to study the green economy efficiency, and then used the system generalized moment method (SGMM) to study the impact of high-tech industry agglomeration on green economy efficiency. According to the empirical test, we found that (1) the green economy efficiency of the Yangtze River Economic Belt shows a volatile upward trend, (2) the green economy efficiency of the Yangtze River Economic Belt differs with time and by region, (3) the agglomeration of the high-tech industry has a lagging effect on the improvement of green economy efficiency, and (4) the regression coefficients of economic development and foreign direct investment are positive and those of environmental regulation and urbanization are negative. Finally, in this paper, we provide corresponding policy recommendations to promote the agglomeration of high-tech industries, thereby improving the efficiency of the green economy.
Analyse des risques portant sur le circuit de la nutrition parentérale en réanimation néonatale

Le circuit de la nutrition parenterale (NP) pediatrique a la carte est un processus a risque car il comporte de nombreuses etapes impliquant elles-memes de nombreux intervenants. Suite au rapport de l’IGAS (Inspection generale des affaires sociales) de janvier 2015, le CHU d’Amiens Picardie a mis en place une Evaluation des pratiques professionnelles sur le circuit de la NP. L’objectif etant d’identifier les risques auxquels sont confrontes les differents acteurs du circuit, de les prioriser pour proposer des axes d’amelioration et d’evaluer leur mise en place. Pour y repondre, deux outils sont utilises : l’audit de processus et l’Analyse des modes de defaillance, de leurs effets et de leur criticite (AMDEC). Le processus a ete decoupe en trois sous-processus : prescription, fabrication et administration. Le premier tour d’audit a permis de faire un etat des lieux du circuit et la methode AMDEC a permis d’identifier et de hierarchiser les modes de defaillance du circuit. Sept groupes de travail pluridisciplinaires ont ete mis en place pour proposer des axes d’amelioration : actions de formation, redaction et mise a jour de protocoles, modification des pratiques, etc. Le second tour d’audit a permis d’evaluer l’impact de ces mesures correctives. Ce travail a abouti a la securisation de nombreux elements du circuit de la NP. L’informatisation du circuit dans sa globalite fait partie des prochaines etapes.
#FeesMustFall: Lessons from the Post‑colonial Global South

The protests that engulfed South African universities in 2015 and 2016 revealed a dissatisfaction by students with regard to higher education fees. The current study looks at some of the lessons that could assist South Africa in understanding the role of universal fee‑free higher education or fee‑free higher education for the poor. Most countries in the post‑colonial global South indicate a shift into cost sharing as mounting financial pressures on state budgets make universal free education unsustainable. The current study shows that the cost sharing model in South Africa has not resonated with students and may also be exclusionary to poor students. The lessons from the post‑colonial global South show that the trend in higher education is that the poor are often left out of most fee structures – including dual track, universal fee‑free, and cost-sharing models. The current study explores some implications and considerations of the current means test model that has been introduced by the current South African president, while using the global South as reference point for the implications of this fee structure, particularly in relation to poor and working-class students.
Containing Large-Scale Criminal Violence through Internationalized Prosecution: How the CICIG Contributed to the Reduction of Guatemala's Murder Rate

This article explores whether and how internationalized prosecution contributes to the reduction of criminal violence. Internationalized prosecution is a strategy of cooperation between international organizations and domestic institutions to investigate and prosecute state security agents and criminals who collude to dominate illicit markets. We focus on the International Commission Against Impunity in Guatemala (CICIG), a UN-backed institution in which international investigators collaborated with Guatemala’s public prosecutors and the police to dismantle criminal structures that emerged during the country’s civil war. Results from a Synthetic Control Model show that had Guatemala not adopted the CICIG in 2008, the country’s homicide rate would have doubled in 2016. Substantively, the CICIG contributed to prevent over 18,000 murders. We argue that the training and protection the CICIG provided to Guatemalan prosecutors empowered them to reduce murder rates by preventing murder-for-hire operations, reducing criminal competition, deterring state-criminal collusion, restricting iron-fist policies, and discouraging private violence.
What Constitutes an 'Actionable Insight' in Learning Analytics?

The possibilities of Learning Analytics as a tool for empowering teachers and educators have created a steep interest in how to provide so-called actionable insights. However, the literature offers little in the way of defining or discussing what the term “actionable insight” means. This selective literature review provides a look into the use of the term in current literature. The review points to a dominant perspective in the literature that assumes the perspective of a rational actor, where actionable insights are treated as insights mined from data and subsequently acted upon. It also finds evidence of other perspectives and discusses the need for clarification of the term in order to establish a more precise and fruitful use of the term.
Populism and the Risks of Conceptual Overreach: A Case Study from Indonesia

ABSTRACT This paper examines the competing political styles of the two presidential candidates in the 2014 and 2019 Indonesian national elections: current Indonesian President Joko Widodo (better known as Jokowi) and his challenger Prabowo Subianto. While both have been described as populists, we draw on the most recent ideational approach to the concept of populism to argue that only one of these political figures (Prabowo) should be defined as a populist. Jokowi’s political style, on the other hand, is better understood by applying the concept of technocracy. In identifying the competition between Jokowi’s technocratic style and Prabowo’s populist style, we argue that this case study from Indonesia points to the potential for the concept of populism to be misapplied where other concepts such as technocracy are more appropriate.
Exploring Brand Awareness, Customer Loyalty and Perceived Quality: how they ensure Profitability and generate Purchase Intention: A study on cosmetic industry of Pakistan

The research looks at the reseller's view of the brand's reputation, quality and customer loyalty on the profitability and purchasing of the brand. In addition, the research focuses on clarifying the role of the purchasing power intermediary in the relationship between brand awareness and profitability, quality and profitability, brand awareness and profitability. The investigation was of a causal nature and data was collected from 200 retailers. The results showed the brand awareness and loyally meaningless impact, while the observed quality had a significant impact on profitability. In addition, the results revealed a significant impact on brand awareness, quality knowledge and loyalty for purchasing purposes. The conciliation Sobel test showed that procurement intensity only conveys the relationship between observed quality and profitability.
Hybrid Adaptive Educational Hypermedia Recommender Accommodating User’s Learning Style and Web Page Features

Personalized recommenders have proved to be of use as a solution to reduce the information overload ‎problem. Especially in Adaptive Hypermedia System, a recommender is the main module that delivers ‎suitable learning objects to learners. Recommenders suffer from the cold-start and the sparsity problems. ‎Furthermore, obtaining learner’s preferences is cumbersome. Most studies have only focused on similarity ‎between the interest profile of a user and those of others. However, it can lead to the gray-sheep problem, ‎in which users with consistently different opinions from the group do not benefit from this approach. On ‎this basis, matching the learner’s learning style with the web page features and mining specific attributes ‎is more desirable. The primary contribution of this research is to introduce a feature-based recommender ‎system that delivers educational web pages according to the user's individual learning style. We propose an ‎Educational Resource recommender system which interacts with the users based on their learning style ‎and cognitive traits. The learning style determination is based on Felder-Silverman theory. Furthermore, ‎we incorporate all explicit/implicit data features of a page and the elements contained in them that have an ‎influence on the quality of recommendation and help the system make more effective recommendations. ‎
Can changes in commodity prices help to predict inflation? : A Bayesian Approach

In this paper, steady-state Bayesian vector autoregressive models are used to examine if changes in commodity prices could help to improve the forecasts of CPI inflation in Sweden, a small open economy. An in-sample analysis is conducted in terms of impulse response functions and an out-of-sample forecast exercise is performed in order to examine the out-of-sample relation. The variables used in this paper are different types of commodity price indices, CPI inflat ion, unemployment rate and the three-month Treasury bill rate, where the last two variables are used as control variables. Monthly data are used and the sample period ranges from 1993M01 to 2019M01. The results from the impulse response functions show that a shock in either one of the commodity price indices have a significant positive effect on CPI inflation. The maximum effect of a shock in commodity price indices on CPI inflation is reached after 6-12 months, depending on model specification. The error measures for the out-of-sample forecasts show that models including commodities price indices tend to have, overall, smaller forecasting errors throughout the horizons. The Diebold-Mariano test indicates that a broad commodity price index does help to forecast CPI inflation in longer horizons. The test further shows that using different types of commodities could help to improve forecast performance on different horizons. The overall results from the DM test indicates that most of the significant differences in forecasting performance occurs in later horizons. Table of
Building an integrated conceptual model of competitive learning capability

Purpose The purpose of this paper is to provide insights into the overarching role of learning capabilities by presenting a framework to describe how learning capability development is captured by combining the three main elements of internal marketing orientation, exploratory capabilities and resource recombination. Design/methodology/approach This is a conceptual paper building upon the theoretical integration approach of Mayer and Sparrowe (2013) to establish competitive empowerment through learning capability development, effective internal response and resources recombination. Findings The competitive learning capability model provides a firm’s foundation for theorizing organizational competitive models from an internal perspective, by mastering learning capability development at the centre of the model. Research limitations/implications The paper emphasizes the competitive connotation of learning capabilities as a construct in strategic management. It shows the underlying role of learning across organizational processes; hence, its theoretical significance through the learning capabilities model. Practical implications This paper argues that learning is at the centre of organizational competitiveness. Firms can achieve more fruitful results by continuously implementing resource integration strategies built on their learned experiences. Originality/value The principal significance of this paper lies in the achievement of conceptualizing learning from a strategic management perspective. Insight in this area helps bridge organizational efforts in pursuit of competitive advantage by exploiting key core learning competencies embedded in a firm’s resources and capabilities.
Metrics and appraisal for noise reduction in holographic data processing

This paper discusses on noise reduction in holographic data processing. Especially, for phase data in speckle metrology, related to a wrapped modulo 2π phase map, post processing is required to reduce random fluctuations such as the speckle phase decorrelation. The choice of the filtering algorithm is a challenge since a large variety of filtering schemes are available in literature. In addition, the metric for evaluating algorithms has to be discussed, especially regarding the need, or not, for a reference image. In order to assess the evaluations of the available de-noising strategies, we have constituted databases with simulated phase data. Then, 34 de-noising algorithms were chosen considering their efficiency in image processing and digital holography, as stationary wavelet transform based algorithm with Daubechies, symlets wavelet, curvelets, contourlets, BM3D (block matching 3D) algorithm (state of the art in the image processing), NL-means (non local) algorithms, 2D windowed Fourier transform and SPADEDH ; in addition, we consider classical methods such as Wiener, median and Gauss filtering, anisotropic filtering and Frost filter which was widely used in SAR (synthtic aperture radar) imaging. These schemes were evaluated through rankings provided by pertinent quality metrics. But, the main problem with quality metrics is that they are not self-sufficient in the sense that they require a noise-free reference phase fringe pattern in order to be computed. In practical situations, one only has a set of measurements to be processed, and no exact phase is available to evaluate the quality of processing. In order to bypass this limitation, a noise-free reference metric was developed, that means a metric which is directly capable of providing information on how efficient the filtering is, without the help of any reference measurement and by only considering the measured available phase data. So, we present and discuss on the rankings which were obtained, and in addition, we present a reference free metric adapted to phase data filtering in speckle metrology.
Guiding SMT solvers with Monte Carlo Tree Search and neural networks

Monte Carlo Tree Search (MCTS) is a technique to guide search in a large decision space by taking random samples and evaluating their outcome. Frequently, MCTS is employed together with reward heuristics learnt by neural networks. The talk will propose a guidance mechanism for SMT solvers based on a combination of MCTS and neural networks. Machine learning methods gain importance in automated reasoning. A particularly strong trend are neural networks, having produced state-of-the-art results for premise selection [WTWD17, ISA + 16]. Outside of automated reasoning, neural networks have been combined with Monte Carlo Tree Search, treating problems as diverse as finding good strategies to play the game of Go [SHM + 16] and planning of chemical syntheses [SKTW17, SPW17]. In automated reasoning, Monte Carlo Tree Search (MCTS) has been applied to first-order automated theorem proving, using hand-crafted heuristics instead of neural networks [FKU17]. We propose a combination of Monte Carlo Tree Search and neural networks to guide the search performed by an SMT solver. We are exploring the idea of such guidance in the Psyche platform [GL13], which offers a modular architecture for theorem proving. It implements an adaptation, to automated reasoning in general and to SMT solving in particular, of the LCF architecture [Mil79, GMW79]. LCF is mostly used in Interactive Theorem Proving and is particualrly widely implemented in the proof assistants of the HOL family, such as the HOL system [HOL], Isabelle [Isa], etc. The LCF architecture allows theorem proving strategies to be programmable, while guaranteeing the correctness of any claim that a formula is provable. The architecture's kernel component offers an API whose primitives implement basic reasoning inferences, and strategies can be programmed on top of the kernel via the API. The claims of provability are then necessarily correct-by-construction, assuming the correctness of the kernel, but regardless of any potential defects in the design or in the implementation of strategies (or in the user's input, for the case of Interactive Theorem Proving). Psyche embraces this paradigm and, in the case of SMT solving, relates to a position paper by de Moura and Passmore, entitled "The strategy challenge in SMT solving" [dMP13], which promoted the programmability of strategies as compositions of basic reasoning tasks, explicitly referring to the LCF paradigm. This approach opens up the possibilities of extensively experimenting with various strategies, whether they be handcrafted or machine-learned, while never jeopardising the correctness of the solver's output. Guiding the search by techniques such as MCTS and neural networks can be envisaged more easily in provers whose architecture implements this approach. Psyche's architecture does so at a rather fine-grained level, separating the code that implements reasoning inferences from the code that implements search strategies.
STAFF: Automated Signature Generationfor Fine-Grained FunctionTraffic Identification

Identifying a user operating application function can reﬂect the user behavior, or even can help to improve the user experience. It is the focus of the real application in big data analytics technology. Unlike Coarse-grained Trafﬁc Identiﬁcation (CTI) which only identify application/protocol that a packet is related to, Fine-grained Function Trafﬁc Identiﬁcation (FFTI) maps the trafﬁc packet to a meaningful user operation or an application function. In this paper, our focus is to identify the ﬁne-grained function signature. We propose an automatic and stable signature generation method, so-called STAFF, to identify different application functions. STAFF treats data packets as long strings. The aim of our method is to ﬁnd all the string fragments whose length is longer than a prescribed length and whose occurrence is higher than a prescribed frequency. The ﬁnal signature will be presented as pairs of string fragments and their corresponding occurrence frequency. The experimental results show that STAFF can automatically generate ﬁne-grained function signatures in different applications with average 93.65% identiﬁcation accuracy and the method is noise insensitive.
INTELLECTUAL PROPERTY RIGHTS and ECONOMIC GROWTH in EUROPE

Nowadays countries growth rates are determined by technology and innovation capacity therefore the protection and support of technological ideas are very crucial. From this viewpoint we investigate the impact of intellectual property rights (IPRs) and various related variables on economic growth for both developed countries in Europe and Turkey from 1995 to 2005. Using SUR technique (seemingly unrelated regressions), we try to put forward the impact various variables effects on economic growth. These variables are; GDP per adult worker, physical capital investment, human capital stock, market freedom index, research and development, intellectual property rights index. In this way, we can analyze the determinants of the growth for the countries which have different development degrees.
Re-examination of the standards for transit oriented development influence zones in India

Transit oriented development (TOD) is a land-use and transport integrated urban planning strategy that is highly acclaimed for promoting sustainable city development. This review aims to identify the problems regarding adoption of TOD standards or guidelines formulated by developed countries in developing countries, such as India, and the necessity of conducting adaptability studies on TOD influence areas. The existing studies show that the size of the influence area varies among different cities and travel modes. Accordingly, no single size influence zone is suitable for all cases. This review highlights the necessity of carefully considering the spatial extent of influence areas and modes other than walking as access or egress modes in the Indian context. Moreover, this review aims to provide insight on how to plan TOD in the context of developing countries, because the mobility patterns in these countries differ considerably from those in the developed world.
YOUTH ELECTORAL VIOLENCE AND THE SOCIO-ECONOMIC DEVELOPMENT OF THE TAMALE METROPOLIS OF GHANA

Since the onset of the Fourth Republic of Ghana, successful elections have been held to deependemocratic participation. Despite its democratic achievements, Ghana has had its own share ofelectoral violence. During electoral seasons, Ghanaian youth who form the bulk of mass base ofpolitical parties are often drawn into various tense situations that erupt in violence. This paperexamines the ways and extents of youth involvement in electoral violence in the TamaleMetropolis of Ghana. A cross-sectional survey research design involving the use of Questionnaire,Key Informant Interviews, Focus Group Discussions and literature review were used to generatedata. A total of 183 participants from among youth, state agencies and political parties wereengaged as respondents. Data generated are analysed and presented using qualitative andquantitative techniques. The analyses reveal that the key forms of electoral violence were insultsof opponents, physical attacks, clashes with security agencies and electoral officials, intentionallyobstructing the electoral process and the prevention from voting. The causes of the violence werefound to be difficulty in exercising franchise, long queues, delays in electoral process, suspicionof underage voting and destruction of paraphernalia. There were impacts such as living in a stateof emergency, loss of lives and property, stagnation of businesses, and creation of fear and panic.In conclusion, youth electoral violence affects the socio-economic activities of people andcommunities and thus contribute to stalling development. Multi-stakeholder dialogues and peaceeducation are recommended.