Miracle-dz/UniFAR-FTUs huggingface dataset:
IDENTIFYING AND EVALUATING HOTSPOTS OF CLIMATE-RELATED INDICATORS IN THE SAHEL MAKING USE OF OBJECT-BASED REGIONALIZATION TECHNIQUES

The countries of the Sahel are among the countries most affected by global climate and/or environmental change. These changes in climate are likely to worsen the prevailing water scarcity in this region and will significantly affect livelihoods, biodiversity, food security and human health. Within a study carried out under the direction of the United Nations Environment Programme (UNEP), historical climate trends and their implications on food security and regional stability in the Sahel and western Africa were investigated. The implementation of an integrated object-based regionalization technique for multi-dimensional indicator spaces and the development of a spatial meta-indicator enabled us to highlight and assess hotpots, which are mainly affected by climatic changes. The observed trends and changes for the past 24 to 36 years were explored for a set of four climate change induced drivers: (1) temperature, (2) precipitation, (3) drought, and (4) major flood events. The identification and evaluation of the hotspots of climate-related indicators, as well as of migration and conflict patterns in the nine Sahelian countries, which form the Permanent Inter-State Committee for Drought Control in the Sahel (CILSS), relied on time-series of freely available global datasets. The resulting conceptual spatial entities, instances of geons, are homogenous in terms of their response to the climate-related spatial phenomena concerned. The presented approach enables the integration of indicators from different domains/sources and reveals a high potential for hotspot assessments of higher systemic properties across various scales, such as socio-economic/ecological vulnerability, while likewise delivering conditioned (policy-oriented) information.
Detection and Attribution of Wildfire Pollution in the Arctic and Northern Mid-latitudes using a Network of FTIR Spectrometers and GEOS-Chem

Abstract. We present a multi-year time series of column abundances of carbon monoxide (CO), hydrogen cyanide (HCN), and ethane (C2H6) measured using Fourier transform infrared (FTIR) spectrometers at ten sites affiliated with the Network for Detection of Atmospheric Composition Change (NDACC). Six are high-latitude sites: Eureka, Ny-Alesund, Thule, Kiruna, Poker Flat, and St. Petersburg , and four are mid-latitude sites: Zugspitze, Jungfraujoch, Toronto, and Rikubetsu. For each site, the inter-annual trends and seasonal variabilities of the CO time series are accounted for, allowing ambient concentrations to be determined. Enhancements above ambient levels were used to identify possible wildfire pollution events. Since the abundance of each trace gas emitted in a wildfire event is specific to the type of vegetation burned and the burning phase, correlations of CO to the long-lived wildfire tracers HCN and C2H6 allow for further confirmation of the detection of wildfire pollution, while complementary measurements of aerosol optical depth from nearby AERONET sites confirm the presence of wildfire smoke. A GEOS-Chem tagged CO simulation with Global Fire Assimilation System (GFAS) biomass burning emissions was used to determine the source attribution of CO concentrations at each site from 2003–2018. The influence of the various wildfire sources is found to differ between sites while North American and Asian boreal wildfires fires were found to be the greatest contributors to episodic CO enhancements in the summertime at all sites.
EFFECTIVENESS OF TRAINING & DEVELOPMENT IN MNC’S EMPLOYEES

Training is different form education; particularly formal education. The education is concerned mainly with enhancement of knowledge, but the aims of training are increasing knowledge while changing attitudes and competences in good manner. Basically the education is formulated within the framework and to syllabus, but the training is not formed in to the frame and as well as syllabus. It may differ from one employee to another, one group to another, even the group in the same class. The reason for that can be mentioned as difference of attitudes and skills from one person to another. Even the situation is that, after good training program, all different type skilled one group of employees can get in to similar capacity, similar skilled group. That is an advantage of the trainings. Employers should enable employees to pursue training and development in a direction that they choose and are interested in, not just in company-assigned directions. Companies should support learning, in general, and not just in support of knowledge needed for the employee's current or next anticipated job. It should be noted that the key factor is keeping the employee interested, attending, engaged, motivated and retained.Very often Training and Development are considered as synonyms. Practically speaking, there is a difference between the two.
Quantifying and Understanding Gender and Cross-Cultural Differences in Mental Health Expression via Social Media

For a long time, mental illness was treated as a gender and culture-neutral problem. However recent research shows that several social and psychological characteristics are unique to women [6], and hence there is a need to investigate in depth the causes and antecedents of emotional distress in women [49]. In developing countries, socio-political and economic issues such as poverty, inequalities in the workplace, societal and cultural expectations of women are often known to heighten women’s risk to distress and mental illness [54]. However, the gender and cultural dimensions of mental health, especially in countries of the majority world, are less understood1. The United Nations’ Millennium Development Goals2, established in 2000, notes that the majority of data we have on global burden of mental illnesses comes from massive data aggregation exercises conducted only once every few years [38]. This data often does not include gender information; and often different countries have different policies and practices in place in terms of how mental illnesses are assessed [48]. Overlooking gender or culture based differences can have drastic consequences. This includes, misdiagnosis, misappropriation of interventions, constrained help-seeking along stereotypical lines, and a “one-size-fits-all” approach to extend help to those who may have unique needs [49, 48]. With the lack of an adequate global surveillance system, and with the accelerating pace of economic and cultural change, more frequently updated information on mental disorders for different gender and cultural subgroups is needed [39, 41], especially from subgroups who may not necessarily appear in formal statistical surveys of health and well-being. In recent years, a new research direction has established social media data as a way to understand mental health challenges in people [16, 14, 26]. It has been found that these approaches can greatly supplement and complement traditional mental health assessments, such as the Behavioral Risk Factor Surveillance System (BFRSS) survey conducted by the Centers for Disease Control and Prevention (CDC) in the US [13, 12, 10, 18]. However, cultural and gendered expression of different subgroups may differ markedly from the “typical”, largely western populations, on which these current social media investigations of mental health are based [16, 14]. Per the perspective laid out by postcolonial computing, rarely are analytical insights and intervention mechanisms able to be transplanted without modification from one subgroup to another, and still provide the same value [29]. Therefore, identifying gender based and cross-cultural context is critical in the use of such passively sensed big data for making sense of mental health and well-being.
SERVICE-ORIENTED VISION : ACTION AND THINKING FOR THE FUTURE MOBILE LEARNING ENVIRONMENTS

With the rapid developments of Internet and mobile technologies (adaptive hypermedia, semantic web, seamless mobility are some), peoples (learners) are changing their way of living changing their behavior, becoming more active (mobility, personalization and simulation), and dynamically involving and engaging in the learning experiences (communities, collaboration, connectedness etc). Monolithic designs of the traditional E-Learning/Mobile Learning(hereafter will be called E-Learning) platforms, first(blackbox type and content based) and second(modular and learning object based) generations of LMS , are failing to keep pace with these changes. Social and collaborative learning experiences in a diversity of technologies, architectural flexibility, information interoperability, adaptive to need of the learners (learners wish their contextual needs fulfilled without bothering about underlying technologies) are some of challenging issues for the next-generation E-Learning environments [1]. E-Learning Framework (ELF) [2], Open Knowledge Initiative (OKI) [3] and IMS Abstract Framework (IAF) [4], Open Mobile Abstract Framework (OMAF) [5] are defining service-oriented based specifications and guidelines for the E-Learning platforms and frameworks, [5, 6] are some research initiatives in this area to address these challenges but most work is in its early stages. We in FABULA project [7], which is the part of multidisciplinary effort among IDI, ITEM and LIKT at NTNU Norway, will explore service-oriented vision with novel principles and technical solutions for the next generation of the E-Learning platforms emphasizing collaborative process of knowledge construction and sharing enabled by seamless mobile networks and location awareness within a city.
Identifying genetic markers for a range of phylogenetic utility#_#x2013;From species to family level

Resolving the phylogenetic relationships of closely related species using a small set of loci is challenging as sufficient information may not be captured from a limited sample of the genome. Relying on few loci can also be problematic when conflict between gene-trees arises from incomplete lineage sorting and/or ongoing hybridization, problems especially likely in recently diverged lineages. Here, we developed a method using limited genomic resources that allows identification of many low copy candidate loci from across the nuclear and chloroplast genomes, design probes for target capture and sequence the captured loci. To validate our method we present data from Eucalyptus and Melaleuca, two large and phylogenetically problematic genera within the Myrtaceae family. With one annotated genome, one transcriptome and two whole-genome shotgun sequences of one Eucalyptus and four Melaleuca species, respectively, we identified 212 loci representing 263 kbp for targeted sequence capture and sequencing. Of these, 209 were successfully tested from 47 samples across five related genera of Myrtaceae. The average percentage of reads mapped back to the reference was 57.6% with coverage of more than 20 reads per position across 83.5% of the data. The methods developed here should be applicable across a large range of taxa across all kingdoms. The core methods are very flexible, providing a platform for various genomic resource availabilities and are useful from shallow to deep phylogenies.
R&D-Intensity, Mispricing, and Stock Returns in the Taiwan Stock Market

Applying stock return data in the Taiwan stock market from 07/1988 to 06/2002, we document in this paper, firstly, that R&D-intensive stocks tend to outperform stocks with little or no R&D. Secondly, the R&D-intensity effect cannot fully be attributed to firm size and seasonal effects. Thirdly, the mispricing of R&D stocks not only exists but also persists. The market apparently undervalues R&D-intensive firms and overvalues non-R&D-intensive firms. Firms with high (low) R&D-intensity earn on average positive (negative) abnormal returns in the subsequent three years. Fourthly, the R&D-intensity effect is more pronounced for firms in the electronics industry after 1996.
Understanding Each-Other: Engineering Challenges and Opportunities for Users and Systems in the Deep Learning Era

In this paper, we discuss the impact of Deep Learning (DL) techniques in the present and future of the interactive system engineering. On the one hand, the support for more complex vocabularies oﬀers opportunities in better shaping the communication between the user and the system. On the other hand, we identify challenges related to the lack of transparency and explainability in the trained models, which have a negative impact on system understanding for both developers and users.
Development and optimization of a miniaturized extrusion-spheronization process for the formation of pure substance pellets

Pharmaceutical pellets are often enclosed in capsules used as oral drug formulations. The pelletization technology, responsible for the formation of pellets, is seen as an agglomeration of drug particles and excipients. In this way the loose powder particles are converted into pellets. Drugs and plasticity increasing excipients are common formulation substances used to manufacture pellets characterized by a narrow size distribution, low friability and acceptable aspect ratio. Since the pellets in the present study were designed for use in single pellet dissolution studies, the friability was of no importance. In this work, the possibility to produce pure substance pellets i.e. without the inclusion of plasticizing excipients, using miniaturized extrusion-spheronization equipment, was tested. The exclusion of plasticizers is of importance since they influence drug release when dissolution is in progress. In all formulations, water was used as binding liquid. The primary particle size determines the available surface for interaction with the binding liquid, necessary for solid bridge formation between particles in the pelletization process. This explains why before extrusion and spheronization is done, the raw material has to be micronized in order to reduce primary particle size. For this reason also a grinding time analysis was performed. A clearly decrease in particle size was found during the first 5 minutes. Grinding more than 5 minutes, decreases the particle size slightly. Particle size and morphology were analysed by optical microscopy linked to an imaging analysis software. Also the influence of spheronization variables i.e. rotational speed, moisture content and spheronization time on the pellet size and shape was investigated. Theophylline pellets (~1014 μm) and ibuprofen pellets (~1155 μm) could be prepared with aspect ratios values beneath 1.2. Conventional pellet formulations containing theophylline, lactose and microcrystalline cellulose, were prepared in order to compare particle size and morphology with the new formulated pure substance pellets. Finally, an x-ray powder diffraction analysis was performed to define transformation in theophylline crystal state during the extrusion-spheronization process. It was found that the grinding process did not influence the crystallinity of the theophylline in contrast to the extrusion-spheronization process, in which the theophylline was converted to the monohydrate form.
Developing Logic-Based Fuzzy Neural Networks with the Aid of GA-RSL and Information Granulation

This study proposes a hybrid development of logic-based fuzzy neural networks. The networks are constructed with the aid of AND and OR fuzzy neurons. The fundamental architecture of the networks comprises a hidden layer formed by a collection of AND neurons that is followed by an output layer consisting of OR neurons. There are two main optimization mechanisms (hybrid optimization) applied in such networks: the structural binary development uses a genetic algorithm (GA) while a parametric refinement of the networks is realized through a random signal-based learning (RSL). A GA concentrates on a preliminary and rough binary optimization and in this way helps combat an eventual curse of dimensionality, that is, we can envision that only a small subset of features is essential and their reduction may help develop a compact network in highly dimensional spaces. This curse is inherent to high dimensional problems to which RSL is quite vulnerable. A numerical example serves as a detailed illustration of the development approach. c © 2004 IIT. All rights reserved.
The role of Ag+, Ca2+, Pb2+ and Al3+ adions in the SERS turn-on effect of anionic analytes

In our recent studies we highlighted the role of adsorbed ions (adions) in turning on the surface-enhanced Raman scattering (SERS) effect in a specific mode for anionic and cationic analytes. In this work, we emphasize the role of Ag+, Ca2+, Pb2+ and Al3+ adions in the specific adsorption of anionic analytes such as the citrate capping agent and three organic acids. Our results suggest an adion-specific adsorption mechanism: the adsorption of anionic analytes is facilitated by positively charged adions such as Ag+, Ca2+, Pb2+ or Al3+, which provide adsorption sites specific for the anionic analytes. The turn-on of the SERS effect is explained in the context of the chemical mechanism of SERS. The adions form SERS-active sites on the silver surface enabling a charge transfer between the adsorbate and the silver surface. High-intensity SERS spectra of uric acid, salicylic acid and fumaric acid could be recorded at a concentration of 50 µM only after activation of the colloidal silver nanoparticles by Ca2+, Pb2+ or Al3+ (50 µM). The chemisorption of the three anionic species to the silver surface occurs competitively and is enhanced with the anions of higher affinities to the silver surface as indicated by the SERS spectra of corresponding mixed solutions.
Diagnostic and Prognostic Value of Monocarboxylate Transporters Gene Expression in Patients with Prostate Cancer and Its Potential Use in Liquid Biopsies: A Preliminary Study

Prostate cancer (PCa) is the second most common type of tumor in men and the need to establish new biomarkers that may aid those already existing in the diagnosis and follow-up of the disease is becoming increasingly evident. In order to maintain the intracellular pH, the cancer cell regulates the production of monocarboxylate transporter proteins (MCTs). We aimed to evaluate the potential prognostic and diagnostic value of MCT1, MCT4 and CD147 gene expression in the blood of patients with PCa throughout the treatment. The difference in expression of the proposed markers between patients with PCa (n = 27) and healthy men (n = 26) was obtained by RT-qPCR and determined by the 2-ΔCq method. Patients with PCa and healthy donors differ in the expression of MCT1, MCT4 and CD147, and this difference can be detected in peripheral blood samples. MCT1 presented higher expression in patients with PCa than in healthy subjects, progressing in line with the severity of the disease. In the analysis of the ROC curve, MCT1 expression showed a high specificity. CD147 area under the curve, although lower than that obtained for MCT1, is simila0r to that described for % free PSA (0,64) and higher than that described for free PSA (0,615). Detection of MCT1 expression in peripheral blood samples could be a complementary diagnostic tool as well as a prognosis marker in prostate cancer.
End User Personalization of Social Humanoid Robots

In this position paper we present some research challenges for end user personalization of social humanoid robots. We introduce the motivations for addressing such challenges and the main features of the type of robots that we want to consider. We discuss some initial research efforts that have recently been put forward in this area, and the type of solutions that have been proposed in order to facilitate the development activities for people without programming experience. We then identify and discuss some research challenges that can be important to address in the near future in order to better exploit such emerging technologies.
Improving the fault-tolerance level within the GRID computing environment-integration with the low-level checkpointing packages

The advantages of utilizing the checkpointing functionality are obvious; how ever so far the Grid community has not developed a widely accepted standard that would allow the Grid env ironment to consciously utilize lowlevel checkpointing packages. Therefore, such a standard named G rid Checkpointing Architecture is being designed within the CoreGRID project. To define, validate, and prove the developed concepts, we utilize small proof-ofconcept implementations of checkpointing-aware Grid environments. Im ple entation, testing and examining these systems allow us to check the feasibility of the devised concepts and provide us with adequate experience. The paper describes the architecture and scenario of one of such proof-of-co ncept implementations. The presented integration of a low-level checkpointing package with the Grid environment allows the G rid Resource Broker to recover user’s jobs in case of failure.
Expression and Clinical Significance of Cytoskeleton Microtubule- Associated-Tau in Gastric Carcinoma

Background and Objectives: Microtubules, the main components of spindles in the mitotic phase, can provide the suitable conditions for unlimited proliferation of tumor cells. Cytoskeleton microtubule-associated-Tau accelerates the progress of malignant tumor through microtubules. Currently, the expression of Cytoskeleton microtubule-associated-Tau in gastric cancer and the relationship between clinical pathological factors research has not yet been reported, so the report aims to elucidate the features of Cytoskeleton microtubule-associated-Tau expression in normal gastric tissue and gastric carcinoma tissue. Materials and Methods: The expressions of Cytoskeleton microtubule-associated protein-Tau protein and Cytoskeleton microtubule-associated protein-Tau mRNA were investigated in 60 cases of gastric carcinoma (cases) and 10 cases of normal gastric tissues (controls). Immunohistochemistry and RT-PCR were respectively used to detect the expression of Cytoskeleton microtubule-associated protein-Tau protein and Tau mRNA in the normal and carcinomatous gastric tissues. Results: The expressions of both cytoskeleton microtubule-associated protein-Tau protein and Tau mRNA in the carcinomatous gastric tissue were higher than in the normal gastric tissue ( P<0.05 ). Likewise, both biomarkers were expressed significantly lower in the well-differentiated and moderately-differentiated gastric carcinoma was than in the poorly-differentiated one ( P<0.05 ). Moreover, their expressions in the gastric carcinoma without lymph node metastasis was lower than in the gastric carcinoma with lymph node metastasis ( P<0.05 ). Conclusion: The expressions of Cytoskeleton microtubule-associated-protein, Tau-protein and Cytoskeleton microtubule-associated-protein, Tau-mRNA were significantly different between the normal gastric tissue and the gastric carcinoma tissue, and were correlated with the degree differentiation and lymph node status. JCMS Nepal. 2015;11(3):6-11.