Miracle-dz/UniFAR-FTUs huggingface dataset:
Population Growth and CO2 Emission in Nigeria: A Recursive ARDL Approach

Theoretically, population growth is believed to increase greenhouse gas emissions, particularly CO2 emissions through the increase in human activities. Accordingly, this study aimed to investigate this assertion in Nigeria using an autoregressive distributed lag model covering periods from 1971-2000, 1971-2005, and 1971-2010 recursively. The results indicated that population was not a determinant of CO2 emissions in all the three periods in the long run. However, economic growth was found to be the only long-run CO2 emissions determining factor within the studied periods. However, in the short run, virtually all the explanatory variables and their lags, that is, population growth, economic growth, and energy consumption, were significant in determining CO2 emissions. The findings suggested that population growth, which is the focal point of the study, could only determine CO2 emissions in the short run. Therefore, population checking measures could be a short-run effective measure to lower the emissions level. Also, further research should be conducted on how to effectively and efficiently manage the population growth–CO2 emissions relationship.
Intrinsic iron spread and a new metallicity scale for globular clusters

We have collected spectra of about 2000 red giant branch (RGB) stars in 19 Galactic globular clusters (GC) using FLAMES@VLT (about 100 stars with GIRAFFE and about 10 with UVES, respectively, in each GC). These observations provide an unprecedented, precise, and homogeneous data-set of Fe abundances in GCs. We use it to study the cosmic scatter of iron and find that, as far as Fe is concerned, most GCs can still be considered mono-metallic, since the upper limit to the scatter of iron is less than 0.05 dex, meaning that the degree of homogeneity is better than 12%. The scatter in Fe we find seems to have a dependence on luminosity, possibly due to the well-known inadequacies of stellar atmospheres for upper-RGB stars and/or to intrinsic variability. It also seems to be correlated with cluster properties, like the mass, indicating a larger scatter in more massive GCs which is likely a (small) true intrinsic scatter. The 19 GCs, covering the metallicity range of the bulk of Galactic GCs, define an accurate and updated metallicity scale. We provide transformation equations for a few existing scales. We also provide new values of [Fe/H], on our scale, for all GCs in the Harris catalogue.
Observations of M87 and Hydra A at 90 GHz

This paper presents new observations of the AGNs M87 and Hydra A at 90 GHz made with the MUSTANG bolometer array on the Green Bank Telescope at 8.5 ′′ resolution. A spectral analysis is performed combining this new data and archival VLA data on these objects at longer wavelengths. This analysis can detect variations in spectral index and curvature expected from energy losses in the radiating particles. M87 shows only weak evidence for steepening of the spectrum along the jet suggesting either re-acceleration of the relativistic particles in the jet or insufficient losses to affect the spectrum at 90 GHz. The jets inHydra A show strong steepening as they move from the nucleus suggesting unbalanced losses of the higher energy relativistic particles. The difference between these two sources may be accounted for by the different lengths over which the jets are observable, 2 kpc for M87 and 45 kpc for Hydra A.
Time Synchronous Chart Parsing of Speech Integrating Unification Grammars with Statistics

We present an active chart parser which parses left connected wordgraphs in a strictly time synchronous way. The parser performs a beam search on the possible paths through the word graph and on the possible derivations of the uni-cation grammar simultaneously. A metric is given to assign scores to edges, taking into account the whole left context thereby combining acoustic probabilities, n-gram probabilities and uniication grammar probabilities. A specialized model for the derivation of typed uniica-tion grammars is introduced. Diierent ways of coupling the parser with an LR beam decoder in an online time synchronous fashion are de-ned and several experimental results are presented. Two top down and one bottom up method are investigated. In bottom up mode, the decoder sends word hypotheses as they are found from left to right, while the parser keeps step. In verify mode, the decoder is always a frame ahead, while the parser veriies received hypotheses, providing language information to the decoder. In predict mode, the parser is a frame ahead, sending possible successor information to the decoder. The latter uses this information to restrict its search space. Finally a method to maximally reduce multiple paths in a left connected word graph produced by a beam decoder ist presented, which can be used in all of the three strategies.
Discriminative Local Sparse Representations for Robust Face Recognition

A key recent advance in face recognition models a test face image as a sparse linear combination of a set of training face images. The resulting sparse representations have been shown to possess robustness against a variety of distortions like random pixel corruption, occlusion and disguise. This approach however makes the restrictive (in many scenarios) assumption that test faces must be perfectly aligned (or registered) to the training data prior to classification. In this paper, we propose a simple yet robust local block-based sparsity model, using adaptively-constructed dictionaries from local features in the training data, to overcome this misalignment problem. Our approach is inspired by human perception: we analyze a series of local discriminative features and combine them to arrive at the final classification decision. We propose a probabilistic graphical model framework to explicitly mine the conditional dependencies between these distinct sparse local features. In particular, we learn discriminative graphs on sparse representations obtained from distinct local slices of a face. Conditional correlations between these sparse features are first discovered (in the training phase), and subsequently exploited to bring about significant improvements in recognition rates. Experimental results obtained on benchmark face databases demonstrate the effectiveness of the proposed algorithms in the presence of multiple registration errors (such as translation, rotation, and scaling) as well as under variations of pose and illumination.
Toward an interpersonal life-stress model of depression: The developmental context of stress generation

The validity of a developmentally based life-stress model of depression was evaluated in 88 clinic-referred youngsters. The model focused on (a) the role of child–environment transactions, (b) the specificity of stress–psychopathology relations, and (c) the consideration of both episodic and chronic stress. Semistructured diagnostic and life-stress interviews were administered to youngsters and their parents. As predicted, in the total sample child depression was associated with interpersonal episodic and chronic stress, whereas externalizing disorder was associated with noninterpersonal episodic and chronic stress. However, the pattern of results differed somewhat in boys and girls. Youngsters with comorbid depression and externalizing disorder tended to experience the highest stress levels. Support was obtained for a stress-generation model of depression, wherein children precipitate stressful events and circumstances. In fact, stress that was in part dependent on children's contribution distinguished best among diagnostic groups, whereas independent stress had little discriminative power. Results suggest that life-stress research may benefit from the application of transactional models of developmental psychopathology, which consider how children participate in the construction of stressful environments.
Sociometric Study of Intragroup Relations in a Work Group

The aim of this study is to explore intragroup relations in retail. The article conduct a sociometric analysis that takes into account labor and affective criteria, using the probability theory method and the UCINET program. In so doing the paper observe that the group, despite having been formally established for more than five years, does not display any solid indicators of high cohesion. The article observe that formal authority and informal leadership do not coincide and that there are two group factions in both criteria, which supports the finding of low cohesion. But despite these deficiencies in terms of cohesion, paper do not find any completely ignored or solitary individuals; as such, the group has established relations that can be improved. To this end, group cohesion should be promoted through a work design that facilitates interaction between individuals and rewards group results, all of which will serve to enhance the performance of this group.
Goh Yen Nee Determining Factors for ISO 14001 EMS Implementation among SMEs in Malaysia : A Resource Based View

This research aimed to find out the determining factors for ISO 14001 EMS implementation among SMEs in Malaysia from the Resource based view. A cross-sectional approach using survey was conducted. A research model been proposed which comprises of ISO 14001 EMS implementation as the criterion variable while physical capital resources (i.e. environmental performance tracking and organizational infrastructures), human capital resources (i.e. top management commitment and support, training and education, employee empowerment and teamwork) and organizational capital resources (i.e. recognition and reward, organizational culture and organizational communication) as the explanatory variables. The research findings show that only environmental performance tracking, top management commitment and support and organizational culture are found to be positively and significantly associated with ISO 14001 EMS implementation. It is expected that this research will shed new knowledge and provide a base for future studies about the role played by firm’s internal resources. Keywords—ISO 14001 Environmental Management System, Malaysia, Resource based view, SMEs
A multi-channel spectrum sensing scheme with filter bank realization for LTE signals

In cognitive ratio (CR), spectrum sensing is a crucial technique aiming at exploiting spectrum white spaces. This sensing task is more difficult for multiple channels in wide bands. In this paper, we investigate spectrum sensing tasks for long-term evolution (LTE) networks in large frequency-bands. We propose an effective spectrum sensing scheme to detect LTE signals and classify the cell-identities transmitted in multi-channels in parallel. To prove the concept and validate the performance of the proposed scheme, a secondary LTE transmission in TV bands is modeled in our simulations. At the perspective of realistic scenarios, the identified information could be utilized for some functions such as the co-ordination among secondary networks or initial-cell-search procedures between secondary user-equipments and their serving base-stations in the secondary LTE transmission. The simulation results show that the detection and classification performance of the proposed scheme is close tightly to that in the case of a single channel. The scheme works well in multi-path fading environment with carrier frequency offset (CFO) and is tolerant to noise uncertainty.
The world through the computer: computer augmented interaction with real world environments

Current user interface techniques such as WIMP or the desk-top metaphor do not support real world tasks, because the focus of these user interfaces is only on human–computer interactions, not on human–real world interactions. In this paper, we propose a method of building computer augmented environments using a situation-aware portable device. This device, called NaviCam , has the ability to recognize the user’s situation by detecting color-code IDs in real world environments. It displays situation sensitive information by superim-posing messages on its video see-through screen. Combination of ID-awareness and portable video-see-through display solves several problems with current ubiquitous computers systems and augmented reality systems.
Zero temperature limit of holographic superconductors

We consider holographic superconductors whose bulk description consists of gravity minimally coupled to a Maxwell field and charged scalar field with general potential. We give an analytic argument that there is no ``hard gap'': the real part of the conductivity at low frequency remains nonzero (although typically exponentially small) even at zero temperature. We also numerically construct the gravitational dual of the ground state of some holographic superconductors. Depending on the charge and dimension of the condensate, the infrared theory can have emergent conformal or just Poincare symmetry. In all cases studied, the area of the horizon of the dual black hole goes to zero in the extremal limit, consistent with a nondegenerate ground state.
Comparative Transcriptome Analysis of Resistant and Susceptible Common Bean Genotypes in Response to Soybean Cyst Nematode Infection

Soybean cyst nematode (SCN; Heterodera glycines Ichinohe) reproduces on the roots of common bean (Phaseolus vulgaris L.) and can cause reductions in plant growth and seed yield. The molecular changes in common bean roots caused by SCN infection are unknown. Identification of genetic factors associated with SCN resistance could help in development of improved bean varieties with high SCN resistance. Gene expression profiling was conducted on common bean roots infected by SCN HG type 0 using next generation RNA sequencing technology. Two pinto bean genotypes, PI533561 and GTS-900, resistant and susceptible to SCN infection, respectively, were used as RNA sources eight days post inoculation. Total reads generated ranged between ~ 3.2 and 5.7 million per library and were mapped to the common bean reference genome. Approximately 70–90% of filtered RNA-seq reads uniquely mapped to the reference genome. In the inoculated roots of resistant genotype PI533561, a total of 353 genes were differentially expressed with 154 up-regulated genes and 199 down-regulated genes when compared to the transcriptome of non- inoculated roots. On the other hand, 990 genes were differentially expressed in SCN-inoculated roots of susceptible genotype GTS-900 with 406 up-regulated and 584 down-regulated genes when compared to non-inoculated roots. Genes encoding nucleotide-binding site leucine-rich repeat resistance (NLR) proteins, WRKY transcription factors, pathogenesis-related (PR) proteins and heat shock proteins involved in diverse biological processes were differentially expressed in both resistant and susceptible genotypes. Overall, suppression of the photosystem was observed in both the responses. Furthermore, RNA-seq results were validated through quantitative real time PCR. This is the first report describing genes/transcripts involved in SCN-common bean interaction and the results will have important implications for further characterization of SCN resistance genes in common bean.
Group Decision Making in Selection Hyper-heuristics

A hyper-heuristic is a high level methodology which performs search over the space of heuristics each operating on the space of solutions to solve hard computational problems. This search process is based on either generation or selection of low level heuristics. The latter approach is used in selection hyper-heuristics. A generic selection hyper-heuristic has two main components which operate successively: heuristic selection and move acceptance methods. An initially generated solution is improved iteratively using these methods. At a given step, the most appropriate heuristic is selected from a fixed set of low level heuristics and applied to a candidate solution producing a new one. Then, a decision is made whether to accept or reject the new solution. This process is repeated until the termination criterion is satisfied. There is strong empirical evidence that the choice of selection hyper-heuristic influences its overall performance. This is one of the first studies to the best of our knowledge that suggests and explores the use of group decision making methods for move acceptance in selection hyper-heuristics. The acceptance decision for a move is performed by multiple methods instead of a single one. The performance of four such group decision making move acceptance methods are analysed within different hyper-heuristics over a set of benchmark functions. The experimental results show that the group decision making strategies have potential to improve the overall performance of selection hyper-heuristics.
Induction of p16INK4a Is the Major Barrier to Proliferation when Epstein-Barr Virus (EBV) Transforms Primary B Cells into Lymphoblastoid Cell Lines

To explore the role of p16INK4a as an intrinsic barrier to B cell transformation by EBV, we transformed primary B cells from an individual homozygous for a deletion in the CDKN2A locus encoding p16INK4a and p14ARF. Using recombinant EBV-BAC viruses expressing conditional EBNA3C (3CHT), we developed a system that allows inactivation of EBNA3C in lymphoblastoid cell lines (LCLs) lacking active p16INK4a protein but expressing a functional 14ARF-fusion protein (p14/p16). The INK4a locus is epigenetically repressed by EBNA3C – in cooperation with EBNA3A – despite the absence of functional p16INK4a. Although inactivation of EBNA3C in LCLs from normal B cells leads to an increase in p16INK4a and growth arrest, EBNA3C inactivation in the p16INK4a-null LCLs has no impact on the rate of proliferation, establishing that the repression of INK4a is a major function of EBNA3C in EBV-driven LCL proliferation. This conditional LCL system allowed us to use microarray analysis to identify and confirm genes regulated specifically by EBNA3C, independently of proliferation changes modulated by the p16INK4a-Rb-E2F axis. Infections of normal primary B cells with recombinant EBV-BAC virus from which EBNA3C is deleted or with 3CHT EBV in the absence of activating ligand 4-hydroxytamoxifen, revealed that EBNA3C is necessary to overcome an EBV-driven increase in p16INK4a expression and concomitant block to proliferation 2–4 weeks post-infection. If cells are p16INK4a-null, functional EBNA3C is dispensable for the outgrowth of LCLs.
G-Protein-Coupled Estrogen Receptor Agonist Suppresses Airway Inflammation in a Mouse Model of Asthma through IL-10

Estrogen influences the disease severity and sexual dimorphism in asthma, which is caused by complex mechanisms. Besides classical nuclear estrogen receptors (ERαβ), G-protein-coupled estrogen receptor (GPER) was recently established as an estrogen receptor on the cell membrane. Although GPER is associated with immunoregulatory functions of estrogen, the pathophysiological role of GPER in allergic inflammatory lung disease has not been examined. We investigated the effect of GPER-specific agonist G-1 in asthmatic mice. GPER expression in asthmatic lung was confirmed by immunofluorescent staining. OVA-sensitized BALB/c and C57BL/6 mice were treated with G-1 by daily subcutaneous injections during an airway challenge phase, followed by histological and biochemical examination. Strikingly, administration of G-1 attenuated airway hyperresponsiveness, accumulation of inflammatory cells, and levels of Th2 cytokines (IL-5 and IL-13) in BAL fluid. G-1 treatment also decreased serum levels of anti-OVA IgE antibodies. The frequency of splenic Foxp3+CD4+ regulatory T cells and IL-10-producing GPER+CD4+ T cells was significantly increased in G-1-treated mice. Additionally, splenocytes isolated from G-1-treated mice showed greater IL-10 production. G-1-induced amelioration of airway inflammation and IgE production were abolished in IL-10-deficient mice. Taken together, these results indicate that extended GPER activation negatively regulates the acute asthmatic condition by altering the IL-10-producing lymphocyte population. The current results have potential importance for understanding the mechanistic aspects of function of estrogen in allergic inflammatory response.
Seasonal Pattern of Batrachochytrium dendrobatidis Infection and Mortality in Lithobates areolatus: Affirmation of Vredenburg's “10,000 Zoospore Rule”

To fully comprehend chytridiomycosis, the amphibian disease caused by the chytrid fungus Batrachochytrium dendrobatidis (Bd), it is essential to understand how Bd affects amphibians throughout their remarkable range of life histories. Crawfish Frogs (Lithobates areolatus) are a typical North American pond-breeding species that forms explosive spring breeding aggregations in seasonal and semipermanent wetlands. But unlike most species, when not breeding Crawfish Frogs usually live singly—in nearly total isolation from conspecifics—and obligately in burrows dug by crayfish. Crayfish burrows penetrate the water table, and therefore offer Crawfish Frogs a second, permanent aquatic habitat when not breeding. Over the course of two years we sampled for the presence of Bd in Crawfish Frog adults. Sampling was conducted seasonally, as animals moved from post-winter emergence through breeding migrations, then back into upland burrow habitats. During our study, 53% of Crawfish Frog breeding adults tested positive for Bd in at least one sample; 27% entered breeding wetlands Bd positive; 46% exited wetlands Bd positive. Five emigrating Crawfish Frogs (12%) developed chytridiomycosis and died. In contrast, all 25 adult frogs sampled while occupying upland crayfish burrows during the summer tested Bd negative. One percent of postmetamorphic juveniles sampled were Bd positive. Zoospore equivalents/swab ranged from 0.8 to 24,436; five out of eight frogs with zoospore equivalents near or >10,000 are known to have died. In summary, Bd infection rates in Crawfish Frog populations ratchet up from near zero during the summer to over 25% following overwintering; rates then nearly double again during and just after breeding—when mortality occurs—before the infection wanes during the summer. Bd-negative postmetamorphic juveniles may not be exposed again to this pathogen until they take up residence in crayfish burrows, or until their first breeding, some years later.
Online learning adaptation strategy for DASH clients

In this work, we propose an online adaptation logic for Dynamic Adaptive Streaming over HTTP (DASH) clients, where each client selects the representation that maximize the long term expected reward. The latter is defined as a combination of the decoded quality, the quality fluctuations and the rebuffering events experienced by the user during the playback. To solve this problem, we cast a Markov Decision Process (MDP) optimization for the selection of the optimal representations. System dynamics required in the MDP model are a priori unknown and are therefore learned through a Reinforcement Learning (RL) technique. The developed learning process exploits a parallel learning technique that improves the learning rate and limits sub-optimal choices, leading to a fast and yet accurate learning process that quickly converges to high and stable rewards. Therefore, the efficiency of our controller is not sacrificed for fast convergence. Simulation results show that our algorithm achieves a higher QoE than existing RL algorithms in the literature as well as heuristic solutions, as it is able to increase average QoE and reduce quality fluctuations.