Miracle-dz/UniFAR-FTUs huggingface dataset:
Future Tourists' Characteristics and Decisions: The Use of Genetic Algorithms as a Forecasting Method

This paper applies genetic algorithms to tourism forecasting. To date, genetic algorithms have normally been used as an optimization method. Their application to forecasting with real-world data has not been studied extensively. The paper illustrates how genetic algorithms can be used for this purpose and the new kind of forecast that is obtained. Specifically, the algorithms are applied to a real tourist population, and the characteristics and decisions of each future tourist are forecast. The results suggest that tourism forecasting based on genetic algorithms could reduce the risk of decision making in tourism planning.
Research on Computational Complexity Optimization for Intra and Inter Prediction in Video Compression

Due to the popularization of digital image capturing devices, video content is growing in volume every year. To compress the huge amount of data to much smaller capacity so that it can be manipulated with low cost for video conference, broadcasting, online video-on-demand and surveillance system, video coding technology has been developed since 1989. H.264/AVC is the latest international standard which provides high compression efficiency while introducing heavy computational load and high power consumption. As video content is also growing in resolution and 4k2k content becomes the mainstream, since 2010, a successor to H.264/AVC called High Efficiency Video Coding (HEVC) for next generation video coding is under standardization. HEVC can provide doubled compression efficiency compared to H.264/AVC, while tremendous computational cost is required which leads to longer encoding time and higher power consumption. In both standards, the most effective while computationally intensive tool is Rate Distortion Optimization (RDO) based hybrid encoding, which reduces spatial and temporal redundancy by brutally trying a wide range of block types and prediction modes. In hybrid encoding, intra prediction reduces data redundancy in neighboring blocks, it is not that complexity consuming but affects throughput due to high data dependency; inter prediction estimates motions by finding a matching block in other several frames, consequently, large memory as well as high power consumption will be consumed. The problem becomes even critical in HEVC in that quadtree-structured coding block candidates for hybrid encoding have been increased by a factor of 2. Since II video-related entertainment applications require real-time transmission and portable devices suffer from short battery life and limited hardware resources, it is desirable and urgent to develop optimization techniques for video encoders. The target of this dissertation is to reduce the computational complexity in video encoder by half while keeping the compression performance in terms of both video quality and encoded bits, so that video data can be compressed efficiently within halt time or under lower power consumption. Firstly, a mode decision scheme is proposed and implemented in to H.264/AVC, in which both prediction modes in intra coding and block types in hybrid prediction is reduced largely by means of texture analysis. Proposed texture analysis achieves better accuracy than previous works and the proposed mode decision scheme is proved to be capable of reducing computational complexity of H.264/AVC encoder by 52.5% averagely, which outperforms Liu's method [IEEE Trans. of CSVT 2009] Secondly, a content adaptive hierarchical decision …
Please Scroll down for Article Journal of Human Development Poverty Reduction and Human Development in Africa Poverty Reduction and Human Development in Africa

This article may be used for research, teaching and private study purposes. Any substantial or systematic reproduction, redistribution , reselling , loan or sub-licensing, systematic supply or distribution in any form to anyone is expressly forbidden. The publisher does not give any warranty express or implied or make any representation that the contents will be complete or accurate or up to date. The accuracy of any instructions, formulae and drug doses should be independently verified with primary sources. The publisher shall not be liable for any loss, actions, claims, proceedings, demand or costs or damages whatsoever or howsoever caused arising directly or indirectly in connection with or arising out of the use of this material. Abstract This paper uses cross-national data to investigate the extent to which the adoption of human development strategies has resulted in a reduction of poverty in Africa. Inter-country variations in income and human poverty reinforce the established patterns of well-being within the continent, as countries in Northern and Southern Africa have the lowest levels of poverty. The empirical analysis reveals that inter-country differences in poverty levels can be accounted for by variables indicative of the different facets of human development. These include public expenditure on education, primary school enrolment, female educational enrolment, expenditure on health, and good governance. Other significant variables apart from those pertaining to human development are economic growth, high external debt, the prevalence of HIV/AIDS and the geographical disadvantage of being a landlocked country. The paper also shows that foreign aid has had a limited effect on poverty reduction in Africa.
Behavioral Tests for Evaluation of Information Processing and Cognitive Deficits in Rodent Animal Models of Neuropsychiatric Disorders

Neuropsychiatric disorders represent a serious medical and human issue. In general, these diseases are detrimental to the quality of life and sociability of afflicted patients. Moreover, they are an immense socio-economic burden. Brain disorders are sometimes denoted as graveyards of pharmaceutical enterprises , referring to relatively a large proportion of drugs for these diseases failing to prove efficient or safe in later phases of clinical trials. Our understanding of what really happens in the central nervous system (CNS) is very limited, especially in relation to normal and pathological behaviors. This limitation also effects the research of neuropsychiatric disorders. We do not know the exact pathogenic mechanisms of numerous diseases, such as Alzheimer's disease or schizophrenia, which prevents the causal treatment of many of them. The symptomatic-like treatment often yields an insufficient therapeutic outcome and in many cases, is accompanied by serious side-effects (as is the case for classical antipsychotics in refractory schizophrenic patients). In some areas of neuro-science research, we are often just beginning to understand brain-behavior relationships in health and disease.
Neural coding in barrel cortex during whisker-guided locomotion

Animals seek out relevant information by moving through a dynamic world, but sensory systems are usually studied under highly constrained and passive conditions that may not probe important dimensions of the neural code. Here, we explored neural coding in the barrel cortex of head-fixed mice that tracked walls with their whiskers in tactile virtual reality. Optogenetic manipulations revealed that barrel cortex plays a role in wall-tracking. Closed-loop optogenetic control of layer 4 neurons can substitute for whisker-object contact to guide behavior resembling wall tracking. We measured neural activity using two-photon calcium imaging and extracellular recordings. Neurons were tuned to the distance between the animal snout and the contralateral wall, with monotonic, unimodal, and multimodal tuning curves. This rich representation of object location in the barrel cortex could not be predicted based on simple stimulus-response relationships involving individual whiskers and likely emerges within cortical circuits. DOI: http://dx.doi. org/10.7554/eLife.12559. 001
Diabetic retinal exudates detection using machine learning techniques

Diabetic Retinopathy (DR) is an eye filled illness caused by the complication of polygenic disease and that is to be detected accurately for timely treatment. As polygenic disease progresses, the vision of a patient could begin to deteriorate and leads to blindness. In this proposed work, the presence or absence of retinal exudates are detected using machine learning (ML) techniques. To detect the presence of exudates features like Mean, Standard deviation, Centroid and Edge Strength are extracted from Luv color space after segmenting the Retinal image. A total of 100 images were used, out of which 80 images were used for training and 20 images were used for testing. The classification task carried out with classifiers like Naive bayes (NB), Multilayer Perceptron (MLP) and Extreme Learning Machine (ELM). Experimental results shows that the model built using Extreme Learning Machine outperforms other two models and effectively detects the presence of exudates in retinal images.
Study protocol for a randomized, controlled trial comparing the efficacy of two educational interventions to improve inhalation techniques in patients with chronic obstructive pulmonary disease (COPD): TIEPOC Study

Background: An appropriate inhalation technique and adherence to treatment are both critical determinants of the success of chronic obstructive pulmonary disease (COPD) management. We have observed that up to 75% of patients do not use a successful inhalation technique. Knowledge evaluation and frequent reassessment of inhaler use, together with education of patients and healthcare professionals, can significantly improve the benefits that patients with COPD will derive from inhaler therapy. The objective of this study is to test the efficacy of two educational interventions to improve inhalation techniques in patients with COPD. Methods: Multicenter randomized controlled trial with 296 patients diagnosed with COPD selected by a non-probabilistic method of sampling from seven Spanish Primary Care Centers. The patients will be divided into three groups by block randomization. The three groups are: 1) control; 2) Intervention A; and 3) Intervention B. The control group will comprise patients with no explanations or written information; the Intervention A group will comprise patients to whom we give written information only; and the Intervention B group will comprise patients to whom we give written information plus instructor training. Every patient in each group will be visited four times during the year of the study at the health centers. Discussion: Our hypothesis is that the application of educational interventions (A or B) in patients with COPD who use inhaler therapy will increase the number of patients who perform a correct inhalation technique by at least 25%. We will evaluate the effectiveness of these interventions on patient inhalation technique improvement, where feasible within the context of clinical practice.
Not Necessarily In The Same Boat: Heterogeneous Risk Assessment Among East African Pastoralists

This paper studies variation in risk assessment by pastoralists in the arid and semi arid lands of southern Ethiopia and northern Kenya. Despite superficial homogeneity among east African pastoralists, we show that there exists considerable within-group heterogeneity in their assessment of various risks. We conceptualise risk as comprising of four distinct components: objective exposure, subjective perception, ex ante mitigation capacity, and ex post coping capacity. This conceptualisation provides an effective framework for understanding the observed heterogeneity as the natural consequence of (sometimes modest) structural differences in economic activity patterns, agroclimatic conditions, proximity to towns, wealth, and gender roles. It therefore provides a useful tool for drawing out the policy implications of subjects' expressed concerns about prospective livelihood hazards.
Showing shape with texture: two directions seem better than one

Studies have shown that observers' judgment of surface orientation and curvature is affected by the presence of surface texture pattern. However, the question of designing a texture pattern that does not hide the surace information nor does convey a misrepresentation of the surface remains unsolved. The answer to this question has important potential imapct across a wide range of visualization application. Molecular modeling and radiation therapy are among the many fields that are in need of accurately visualizing their data and could benefit from such methods. Over the past several years we have carried out a series of experiments to investigate the impact of various texture pattern characteristics on shape perception. In this paper we report the result of our most recent study. The task in this study was adjusting surface attitude probes under three different texture conditions and a control condition in which no texture was present. We later compare the performances of the subjects. The three texture conditions were: a doubly oriented texture in which approximately evenly spaced lines followed both of the principal directions, a singly oriented texture in which lines followed only the first principal direction, and a singly oriented line integral convolution. Over a series of 200 trials (4 texture conditions, 10 surface probe locations * five repeated measures) a total of five naive participants were asked to adjust a circular probe. The probes were randomly located on an arbitrary curved surface and its perpendicular extension appeared to be oriented in the direction of the surface normal. An analysis of the results showed that the performance was best in the two directional texture condition. Performances were further decreased in one directional and no texture conditions (in that order). The paper is organized as follows. In Section 1 we briefly describe the motivation for our work. In Section 2 we describe our experimental methods, including a brief summary of the process of the stimuli preparation and a detailed presentation of statistic analysis of our experimental results. In Section 3 we discuss the implications of our findings and in the last section we will talk about our future plans.
Information Disclosures, Default Risk, and Bank Value

This paper investigates the causal effects of voluntary information disclosures on a bank's expected default probability, enterprise risk, and value. I measure disclosure via a self-constructed index for the largest 80 U.S. bank holding companies for the period 1998-2011. I provide evidence that a bank's management responds to a plausibly exogenous deterioration in the supply of public information by increasing its voluntary disclosure, which in turn improves investors' assessment of the bank risk and value. This evidence suggests that disclosure may alleviate informational frictions and lead to a more efficient allocation of risk and return.
Income inequality in the United States, 1947-1985

Preface Introduction Household Structure Changes: Income-Receiving Units Labor Demand Changes: Industrial and Occupational Employment Shifts Labor Supply Changes: Population Age Structure Labor Supply Changes: Female Labor Force Participation Government Redistribution Efforts: Cash Expenditures on Social Insurance White-Nonwhite Differences: Labor Demand, Labor Supply, Government, and Income-Receiving Unit Structure Summary of the Past and Predictions of the Future Conclusions and Policy Implications Appendix 1: Computations of Income Inequality and Distribution Appendix 2: Procedure to Calculate Projections Appendix 3: Data and Data Sources Appendix 4: Regression Results Bibliography Index
Analysis of Soil Water Retention Data Using Artificial Neural Networks

Many studies of water flow and solute transport in the vadose zone require estimates of the unsaturated soil hydraulic properties, including the soil water retention curve (WRC) describing the relationship between soil suction and water content. An artificial neural network (ANN) approach was developed to describe the WRC using observed data from several soils. The ANN approach was found to produce equally or more accurate descriptions of the retention data as compared to several analytical retention functions popularly used in the vadose zone hydrology literature. Given sufficient input data, the ANN approach was also found to closely describe the hysteretic behavior of a soil, including observed scanning wetting and drying curves.
How Do Blog Gardens Grow? Language Community Correlates with Network Diffusion and Adoption of Blogging Systems

Different language communities present in a multimedia blog and social network hosting system are contrasted. The disproportionate population of Chinese language speaking users is explored. Four stages of population growth and activity are examined: invitation, adoption, retention, and contribution. Using blog system logs we find that the Chinese language user population grew from just two invitations and demonstrates higher levels of invitation and retention which was highly correlated with contribution. Additional survey results confirm the difference between language communities on their attitudes and approaches to blogging systems. This suggests visible differences in the ways different cultures and language communities embrace and enact relationships through computer mediated publication.
STREPTOCOCCAL FIBRINOLYSIS: A PROTEOLYTIC REACTION DUE TO A SERUM ENZYME ACTIVATED BY STREPTOCOCCAL FIBRINOLYSIN

1. Methods for the preparation and partial purification of streptococcal fibrinolysin are described. 2. The lysis of fibrin clots in the presence of streptococcal fibrinolysin is associated with proteolysis of the fibrin. Digestion is due to an enzyme normally present in serum or plasma in an inactive state, which is activated by fibrinolysin. Fibrinolysin alone has no demonstrable proteolytic activity. 3. The lysin factor-fibrinolysin system brings about proteolysis of other proteins such as gelatin or casein, in addition to fibrin and fibrinogen. 4. It is suggested that lysin factor exists in serum or plasma as a zymogen, and that it is activated by fibrinolysin, a kinase, in a manner similar to the activation of trypsinogen by enterokinase or the mold kinase of Kunitz (1938).
Reducing fragmentation impact with forward knowledge in backup systems with deduplication

Deduplication of backups is very effective in saving storage, but may also cause significant restore slowdown. This problem is caused by data fragmentation, where logically continuous but duplicate data is not placed sequentially on the disk. Two types of fragmentation introduce high restore penalty: inter-version fragmentation, caused by duplicates present in multiple versions of the same backup, and internal fragmentation, caused by duplicates present in a single backup stream. This paper introduces Limited Forward Knowledge cache (LFK) reducing the internal fragmentation problem. The cache performs blocks eviction based on available limited forward knowledge. As keeping the full knowledge requires memory proportional to the size of a backup, we limit the forward knowledge to an 8GB window and show that such limitation does not impact the performance significantly. In order to further increase the LFK effectiveness in presence of inter-version fragmentation we combined this algorithm with already known solution called Context-Based Rewriting --- CBR (Kaczmarczyk et al. 2012). Our evaluation with real-world traces shows that data fragmentation results in an average 42% slowdown for backups stored on a single disk. LFK alone reduces this drop to 21%. CBR+LFK eliminates it completely so the restore speed is equal to reading non-duplicated data. In amulti-disk setup the standard approach suffers from 83% restore performance drop. The combined algorithms reduce this drop to 35%, assuring a 4 times better restore bandwidth.
Cell-surface residence of sphingosine 1-phosphate receptor 1 on lymphocytes determines lymphocyte egress kinetics

The sphingosine 1-phosphate receptor 1 (S1P1) promotes lymphocyte egress from lymphoid organs. Previous work showed that agonist-induced internalization of this G protein–coupled receptor correlates with inhibition of lymphocyte egress and results in lymphopenia. However, it is unclear if S1P1 internalization is necessary for this effect. We characterize a knockin mouse (S1p1rS5A/S5A) in which the C-terminal serine-rich S1P1 motif, which is important for S1P1 internalization but dispensable for S1P1 signaling, is mutated. T cells expressing the mutant S1P1 showed delayed S1P1 internalization and defective desensitization after agonist stimulation. Mutant mice exhibited significantly delayed lymphopenia after S1P1 agonist administration or disruption of the vascular S1P gradient. Adoptive transfer experiments demonstrated that mutant S1P1 expression in lymphocytes, rather than endothelial cells, facilitated this delay in lymphopenia. Thus, cell-surface residency of S1P1 on T cells is a primary determinant of lymphocyte egress kinetics in vivo.
Whole CMV Proteome Pattern Recognition Analysis after HSCT Identifies Unique Epitope Targets Associated with the CMV Status

Cytomegalovirus (CMV) infection represents a vital complication after Hematopoietic Stem Cell Transplantation (HSCT). We screened the entire CMV proteome to visualize the humoral target epitope-focus profile in serum after HSCT. IgG profiling from four patient groups (donor and/or recipient +/− for CMV) was performed at 6, 12 and 24 months after HSCT using microarray slides containing 17174 of 15mer-peptides overlapping by 4 aa covering 214 proteins from CMV. Data were analyzed using maSigPro, PAM and the ‘exclusive recognition analysis (ERA)’ to identify unique CMV epitope responses for each patient group. The ‘exclusive recognition analysis’ of serum epitope patterns segregated best 12 months after HSCT for the D+/R+ group (versus D−/R−). Epitopes were derived from UL123 (IE1), UL99 (pp28), UL32 (pp150), this changed at 24 months to 2 strongly recognized peptides provided from UL123 and UL100. Strongly (IgG) recognized CMV targets elicited also robust cytokine production in T-cells from patients after HSCT defined by intracellular cytokine staining (IL-2, TNF, IFN and IL-17). High-content peptide microarrays allow epitope profiling of entire viral proteomes; this approach can be useful to map relevant targets for diagnostics and therapy in patients with well defined clinical endpoints. Peptide microarray analysis visualizes the breadth of B-cell immune reconstitution after HSCT and provides a useful tool to gauge immune reconstitution.
Corporate Governance and Firm Performance: Recent Evidence from Borsa Istanbul (BIST) Corporate Governance Index (XKURY)

As competition for foreign and domestic investment increases, firms look for new ways to remain competitive in today's complex business environment. Good corporate governance is rewarded with higher market valuation and companies with better corporate governance practices enjoy higher price-to-book ratios. Investors are actually ready to pay a premium for a company that is respectful to corporate governance practices. In this study, we aim to analyze the impact of several accounting ratios on the corporate governance scores of the selected companies from the Borsa Istanbul (BIST) Corporate Governance Index (XKURY). Our study covers the period of 2008 and 2014. To conduct our study, we selected three types of ratios : liquidity ratios, profitability ratios and operating efficiency ratios. Our results reveal the positive impacts between the liquidity ratios of Net Cash Flow by Operating Activities and Net Working Capital to Total Assets on the corporate governance rating scores. On the other hand, we could not obtain any significant associations between profitability ratios, operating efficiency ratios and corporate governance levels of the firms. Keywords : Corporate governance, firm performance, accounting ratios, liquidity ratios, Borsa Istanbul (BIST) Corporate Governance Index (XKURY)