Miracle-dz/UniFAR-FTUs huggingface dataset:
RESIDENTS’ FACILITIES SATISFACTION IN HOUSING PROJECT DELIVERED BY PUBLIC PRIVATE PARTNERSHIP (PPP) IN OGUN STATE, NIGERIA

Public-private partnership in housing development provide conducive housing environment through provision of services, good and quality facilities, easy access to social amenities, good security arrangement among others. It is on this basis that this study examined residents’ satisfaction of facilities in housing projects delivered by public private partnership. A field survey was conducted in three existing housing estates delivered through PPP within the study area. The information gathered from both the secondary and primary data were used to analyze occupant’s satisfaction of facilities available in housing project delivered by PPP. Questionnaires were distributed through systematic sampling method to 224 respondents in the three existing housing estates in the study area. Result showed that Year of tenure, size of house hold, provision of facilities, security of life and properties, location of resident, space allocation, proximity to work place were some of the factors significantly contributed to occupier satisfaction of facilities available in a PPP driven housing estate . The study recommended that for successful implementation of the PPP housing project to meet the desired satisfaction of any occupier, the government should ensure that all the necessary infrastructural facilities and services like good road, electricity, school, health centre etc. be provided first before building production commence on the estate. Moreover, recreational facilities lacking in most of the estates should be provided so that residents of the estate would not need to travel miles to access these facilities.
Characterizing and predicting essential habitat features for juvenile coastal sharks

The successful management of shark populations requires juvenile recruitment success. Thus, conservation initiatives now strive to include the protection of areas used by pre-adult sharks in order to promote juvenile survivorship. Many shark species use inshore areas for early life stages; however, species often segregate within sites to reduce competition. Using a fisheries-independent gillnet survey from the Northern Gulf of Mexico (2000–2010) we describe distribution patterns and preferred habitat features of the juveniles of six shark species. Our results suggest that multiple shark species concurrently use the area for early life stages and although they overlap, they exhibit distinct habitat preferences characterized by physical variables. Habitat suitability models suggest that temperature, depth, and salinity are the important factors driving juvenile shark occurrence. Within each site, across the sampled range of physical characteristics, blacktip shark (Carcharhinus limbatus) preferred higher temperature (>30 °C) and mid-depth (~5.5 m); bonnethead shark (Sphyrna tiburo) preferred higher temperature (>30 °C) and mid-salinity (30–35 PSU), finetooth shark (Carcharhinus isodon) preferred low salinity ( 30 °C) and salinity (>35 PSU), Atlantic sharpnose shark (Rhizoprionodon terraenovae) preferred high temperature (>30 °C) and deep water (>6 m), and spinner shark (Carcharhinus brevipinna) preferred deep water (>8 m) and high temperature (>30 °C). The other investigated factors, including year, month, latitude, longitude, bottom type, inlet distance, coastline and human coast were not influential for any species. Combining habitat preferences with the sampled environmental characteristics, we predicted habitat suitability throughout the four sites for which physical characteristics were sampled. Habitat suitability surfaces highlight the differences in habitat use between and within sites. This work provides important insight into the habitat ecology of juvenile shark populations, which can be used to better manage these species and protect critical habitat.
A character-recognition system for Hangeul

This work presents a rule-based character-recognition system for the Korean script, Hangeul. An input raster image representing one Korean character (Hangeul syllable) is thinned down to a skeleton, and the individual lines extracted. The lines, along with information on how they are interconnected, are translated into a set of hierarchical graphs, which can be easily traversed and compared with a set of reference structures represented in the same way. Hangeul consists of consonant and vowel graphemes, which are combined into blocks representing syllables. Each reference structure describes one possible variant of such a grapheme. The reference structures that best match the structures found in the input are combined to form a full Hangeul syllable. Testing all of the 11 172 possible characters, each rendered as a 200-pixel-squared raster image using the gothic font AppleGothic Regular, had a recognition accuracy of 80.6 percent. No separation logic exists to be able to handle characters whose graphemes are overlapping or conjoined; with such characters removed from the set, thereby reducing the total number of characters to 9 352, an accuracy of 96.3 percent was reached. Hand-written characters were also recognised, to a certain degree. The work shows that it is possible to create a workable character-recognition system with reasonably simple means.
Quantifying magnitudes and distributions of CO sources

We use a simplified version of the GRANTOUR chemical tracer model to analyze emissions of CO from various sources. The GRANTOUR model has been simplified to include the eigenvalue chemistry solution method of Prather (1994). The analysis includes fossil fuel combustion, biomass burning, hydrocarbon oxidation, ocean, and terrestrial sources of CO. We also present a 1{degree} x 1{degree} emissions inventory of CO from fossil fuel combustion.
An Efficient K-SVD Algorithm of Dictionary Learning for HRRP Targets Recognition

Kun CHEN , Yuehua LI b and , Yilu MA c 1 School of Electronic and Optical Engineering, Nanjing University of Science and Technology, Nanjing, China 2 School of Electronic and Optical Engineering, Nanjing University of Science and Technology, Nanjing, China 3 School of Electronic and Optical Engineering, Nanjing University of Science and Technology, Nanjing, China kitchen2016@sina.cn, *nlglyh2013@sina.cn, mayilu@gmail.com
Adoption of Computer-Aided Technology (CAx) in Textile and Apparel Industries

The extended nature of industrial operations demanded the integration of information and communication technologies (ICT) and computer aided technology (CAx) in industrial processes. Although there are 130 textile and apparel industries in Ethiopia, the adoption of such technology is limited. Hence, this research studied factors affecting CAx adoption through the extension of the technology acceptance model of Davis (1989) by adding perceived competitive advantage, cost effectiveness, and perceived security. The finding revealed that perceived ease of use, perceived service, perceived competitive advantage, cost effectiveness, perceived security and perceived usefulness are significant predictors of intention to use CAx in textile and apparel industries. General Terms Information Systems, ICT Adoption, Technology Acceptance, Computer-Aided Technology.
The Politics of Precedent in International Law: A Social Network Application—ERRATUM

There is no formal binding precedent in international law. Yet, as this article demonstrates, countries nonetheless expend considerable resources in seeking to shape legal precedent. Looking at the international trade regime, I show that while some disputes are initiated to gain market access in response to domestic interests, others are filed primarily to build favorable precedent for future cases of greater commercial value. I construct an original dataset consisting of the network of all rulings spanning the WTO period, and the cases they cite. I analyze this network to provide systematic evidence for the existence of "test cases" in international law: countries initiate commercially unimportant disputes to shape legal precedent to their advantage. And wealthy countries with high legal capacity are significantly better able to do so. While the existence of binding precedent in international law remains a point of continuous debate, countries observably behave in a manner consistent with its existence.
Photosynthetic production of ethanol from carbon dioxide in genetically engineered cyanobacteria

The rapidly growing demand for energy and the environmental concerns about carbon dioxide emissions make the development of renewable biofuels more and more attractive. Tremendous academic and industrial efforts have been made to produce bioethanol, which is one major type of biofuel. The current production of bioethanol is limited for commercialization because of issues with food competition (from food-based biomass) or cost effectiveness (from lignocellulose-based biomass). In this report we applied a consolidated bioprocessing strategy to integrate photosynthetic biomass production and microbial conversion producing ethanol together into the photosynthetic bacterium, Synechocystis sp. PCC6803, which can directly convert carbon dioxide to ethanol in one single biological system. A Synechocystis sp. PCC6803 mutant strain with significantly higher ethanol-producing efficiency (5.50 g L−1, 212 mg L−1 day−1) compared to previous research was constructed by genetically introducing pyruvate decarboxylase from Zymomonas mobilis and overexpressing endogenous alcohol dehydrogenase through homologous recombination at two different sites of the chromosome, and disrupting the biosynthetic pathway of poly-β-hydroxybutyrate. In total, nine alcohol dehydrogenases from different cyanobacterial strains were cloned and expressed in E. coli to test ethanol-producing efficiency. The effects of different culturing conditions including tap water, metal ions, and anoxic aeration on ethanol production were evaluated.
Endocrine Active Compounds Actions during Neonatal Period: Effect on the Ovary

Many female reproductive disorders observed during adulthood originate from the neonatal period, which is a critical stage toward the reproductive potency. Human and animal fertility are determined by the pool of primordial follicles that are established during fetal or neonatal life. The earliest stages of follicle development are under control of a variety of factors, including sex steroids. Neonatal period is a “critical devel- opmental window” in which organisms are susceptible to the environmental chemicals that may affect the reproductive health. Endocrine active compounds (EACs) are found abundantly in the environment and interfere with sex steroids (predominantly andro gens and estrogens) by either mimicking or blocking their functions. This review covers the current knowledge about the effects of selected EACs with androgenic (testoster one propionate), anti-androgenic (flutamide), estrogenic (diethylstilbestrol, bisphenol A, 4-tert-octylphenol, phtalates and genistein), anti-estrogenic (ICI 182,780 and parabens), or mixed activity (methoxychlor) on the ovary of neonates, focusing on their effects on the early stages of folliculogenesis. These chemicals have been shown to affect oocyte survival, follicle formation, and growth, as well as steroidogenic functions. The better cognition of mechanisms underlying the long-term consequences of the neonatal EACs exposure may in future lead to an understanding of human health risks and developing prevention strategies.
Using monolingual corpora for statistical machine translation: the METIS system

In this article the principles of the METIS Machine Translation system are presented. METIS employs an extensive tagged and lemmatised corpus of texts in the target language, coupled with bilingual lexica covering the desired pairs of source-target languages. To generate a high-quality translation, the METIS system is provided with statistical tools enabling it to extract linguistic knowledge from the annotated corpus of the target language. The advantage of this approach is that, although no grammars need to be provided explicitly, grammatical translations are retrieved from the corpus by using pattern matching techniques.
Automatic classification of attention-deficit/hyperactivity disorder using brain activation

Nowadays, there is an active fi eld of research in neuroscience trying to fi nd relations between neurofunctional abnormalities of brain structures and neurological disorders. Previous statistical studies on brain functional Magnetic Resonance Images (fMRI) have found Attention Defi cit Hyperactivity Disorder (ADHD) patients are characterized by reduced activity in the inferior frontal gyrus (IFG) during response inhibition tasks and in the Ventral Striatum (VStr) during reward anticipation tasks. Interpreting brain image experiments using fMRI requires analysis of complex data and diff erent univariate or multivariate approaches can be chosen. Recently, one analysis approach that has grown in popularity is the use of machine learning algorithms to train classifiers to discriminate abnormal behavior or other variables of interest from fMRI data. The purpose of this work is to apply machine learning techniques to perform fMRI group analysis in an adult population. We propose a multivariate classifi er using diff erent discriminative features. Furthermore, we show how temporal information of fMRI data can be taken into account to improve the discrimination. We demonstrate that our new approach is able to diagnose the ADHD characteristics based on the activation in the executive functions. Previous results on the response inhibition task did not find di fferences between activation responses. Opposite to these results, we achieve accurate classifi cation performance for this task. Moreover, in this case, we show that classi fication rates can be signi cantly improved by incorporating temporal information into the classi fier.
How fish habitat suitability does shape the 3 D spatial organisation of anchovy across scales ?

Functional relationships in marine ecosystems are complex as far as physical and biological parameters are involved. Improving our understanding of ecosystem functioning requires the ability to observe in situ the interactions between physical and biological features. In this context, the Peruvian anchovy (Engraulis ringens) is an interesting case study as this species supports the highest worldwide landings and is know to present very high populational, distributional and even biological dynamics at different spatio-temporal scales. A specific behavioural ecology survey was performed in November 2004 to study 3D occupation of space by anchovy in Peru. This study was based on an integrated approach. Indeed, using a series of observation tools (Niskin, CTD probes, zooplankton sampling, stomach content analysis, echo-sounder, multibeam sonar, birds and mammal observations) we assessed interactions between fish and most of the oceanographic and biotic environmental features possibly driving its behaviour. We could link levels of fish organisation (layer, school, shoal, cluster) to different oceanographic and biological features: upwelling plume, plankton patches, water masses fronts, predators and others, varying in space and in time, particularly according to the diel cycle. We adapted the basin model framework to propose a conceptual model of environment impact on fish space occupation. Indeed, the small and medium-scale habitat favourability shaped the fish 3D spatial organisation.
Best Practice for DSDL-based Validation

is paper proposes a best practice guide to apply Document Schema Definition Languages (DSDL) for validation of an arbitrary industry vocabulary. e research is based mainly on a practical case study of creating such an optimized set of DSDL validation artefacts for XLIFF 2, a complex industry vocabulary. Available schema languages have advanced functionality, enhanced expressivity and can be used in concert if needed. is advantage, on the other hand, makes the creation of a stable and robust set of validation artefacts hard, because there would usually be more than one way to describe the same Functional Dependencies or Integrity Constraints and various validation tasks can be solved by more than one schema language.
Effects of 2,4-DP- P (2,4-Dichlorophenoxypropionic Acid-P) Plant Growth Regulator on Fruit Size and Yield of Star Ruby Grapefruit (Citrus paradisi Osb.)

Star Ruby is the main grapefruit (Citrus paradisi) variety grown in Turkey; however, small fruit size is a common problem in ‘Star Ruby’ grapefruit. Fruit size is a decisive external quality parameter in citrus at the marketing of fresh citrus fruits. Fruit size can be enhanced by several techniques such as girdling and thinning. Various plant growth regulators are known to affect the growth and size of citrus fruit. The objective of the present study was to observe the effects of 2,4 dichlorophenoxypropionic acid-p (2,4-DP-P) on the fruit size, yield and quality of Star Ruby from 20-year-old trees budded on sour orange rootstock in Adana, Turkey in 2007. Four concentrations (50, 100, 150 and 300 ppm) of 2,4-DP-P were applied 8 weeks after anthesis during physiological fruit drop when the mean fruit diameter was 13-15 mm. The results indicated that the application of 2,4-DP-P increased the fruit size of Star Ruby grapefruit without reducing yield. The application had a significant effect on fruit yield except for trees treated with 50 ppm 2,4-DP-P. Compared with the control trees, applications of 2,4-DP-P increased the number of large, commercially valuable Star Ruby (>93 mm, 89-93 mm and 84-89 mm). No effects were determined on fruit internal quality parameters. Thus, the results of the present study revealed that 2,4-DP-P can be used to improve the fruit size of Star Ruby fruitlets during the June drop.
The Individual, the Group and Nature

In this article, the author proposes to consider the complexity of the interconnections between individual, group and nature. Is there a link between mental representations of nature and psychological well-being. If the child is not, and 'entity' separate from the mother, the individual can not be seen isolated from its physical world. The relationship with nature and fundamental emotional and psychological development. individuals and groups project on the natural world just as they do with the human world.
Dynamis review : An overview about applications of the Dynamis approach in cognitive psychology

The Dynamis review has been designed to provide an overview about applications of the Dynamis approach in cognitive psychology. Since the development of computer-based scenarios Dynamis, based on linear structural equation systems, has become increasingly popular as a tool for analysing decision making and complex problem solving. Beginning with the role of system size, connectivity, and types of relations in a system (e. g, eigendynamics and side effects) it has been discussed how formal system characteristics may influence the process of complex problem solving. In a second part, essential task demands, i. e. knowledge acquisition and knowledge application, have been specified further with particular respect to their interdependency. Supporting influences as to effective presentation of information and task demands have been suggested in this context: graphical presentation, semantic embedding, structural diagrams and other tutorials, instructed strategies, specific goals, and hypotheses. Research on the impact of problem solvers’ habitual intellectual and strategic abilities as well as motivation completed the presentation of the extensive contexts in which Dynamis systems have been applied and possibly will be applied to in future research. Correspondence concerning this report should be addressed to Joachim Funke, Department of Psychology, Universität Heidelberg, Hauptstraße 47-51, D-69117 Heidelberg, Germany. E-mail: Joachim.Funke@psychologie.uni-heidelberg.de (http://funke.uni-hd.de)
Impedance Modelling and Parametric Sensitivity of a VSC-HVDC System: New Insights on Resonances and Interactions

Pervasiveness of power converters in the electric power system is expected in the future. Such large penetration will change the current power system dynamics leading to uncertain, unexpected, and potentially critical responses. This paper investigates the stability and resonance of a VSC-HVDC (Voltage Source Converter High Voltage Direct Current) link within an AC grid, whilst providing insights into resonances having a role on the grid. This is studied through the impedance-based modelling of the entire system (AC and DC grids), including controls of converters. Additionally, the impact of the different parameters of the hybrid AC-DC power system such as control systems and grid components on the system dynamics and stability is investigated. From this study, the impact of the system components and the controls of the converter on overall resonance response and stability is shown, including potential undesired sub-synchronous and harmonic resonances due to AC-DC system interactions. The analytical impedance-based models developed and obtained is validated through time-domain simulations, the physical model of the whole system is built in Simscape™ Power Systems™ and control systems in MATLAB/Simulink® (R2017b). This has demonstrated the validity of the model to deal with and detect such dynamics.
Fire in Your Hands: Understanding Thermal Behavior of Smartphones

Overheating smartphones could hamper user experiences. While there have been numerous reports on smartphone overheating, a systematic measurement and user experience study on the thermal aspect of smartphones is missing. Using thermal imaging cameras, we measure and analyze the temperatures of various smartphones running diverse application workloads such as voice calling, video recording, video chatting, and 3D online gaming. Our experiments show that running popular applications such as video chat, could raise the smartphone's surface temperature to over 50$^\circ$C in only 10 minutes, which could easily cause thermal pain to users. Recent ubiquitous scenarios such as augmented reality and mobile deep learning also have considerable thermal issues. We then perform a user study to examine when the users perceive heat discomfort from the smartphones and how they react to overheating. Most of our user study participants reported considerable thermal discomfort while playing a mobile game, and that overheating disrupted interaction flows. With this in mind, we devise a smartphone surface temperature prediction model, by using only system statistics and internal sensor values. Our evaluation showed high prediction accuracy with root-mean-square errors of less than 2$^\circ$C. We discuss several insights from our findings and recommendations for user experience, OS design, and developer support for better user-thermal interactions.
Quantitative assessments of geometric errors for rapid prototyping in medical applications

Purpose – In medical applications, it is crucial to evaluate the geometric accuracy of rapid prototyping (RP) models. Current research on evaluating geometric accuracy has focused on identifying two or more specific anatomical landmarks on the original structure and the RP model, and comparing their corresponding linear distances. Such kind of accuracy metrics is ambiguous and may induce misrepresentations of the actual errors. The purpose of this paper is to propose an alternative method and metrics to measure the accuracy of RP models.Design/methodology/approach – The authors propose an accuracy metric composed of two different approaches: a global accuracy evaluation using volumetric intersection indexes calculated over segmented Computed Tomography scans of the original object and the RP model. Second, a local error metric that is computed from the surfaces of the original object and the RP model. This local error is rendered in a 3D surface using a color code, that allow differentiating regions where.