Miracle-dz/UniFAR-FTUs huggingface dataset:
Investigating the Neurophysiological Effect of Thermal Environment on Individuals’ Performance Using Electroencephalogram

The thermal environment has a great influence on individuals’ performance; however, factors such as one’s motivation to perform well under experimental conditions cause difficulties in assessing how room temperature affect subjects’ performance. One approach to overcome this problem is to understand the changes in individuals’ neurophysiological conditions. This paper reports on the results of an experiment where electroencephalogram (EEG) data were collected from 5 subjects while they performed four computerized cognitive tasks. Power spectral density of EEG signals in three different thermal environments, slightly cool, neutral, and slightly warm, was compared within-subjects. In most cases, significant differences in PSD of the frontal theta (4-8Hz) activity are observed, indicating individuals’ mental effort varies with room temperature. In the long run, the increased mental workload will reduce individuals’ performance and be detrimental to their productivity. The study indicates that the proposed method could be implemented on a larger scale for further studies.
Block Motion Model for Optical Flow with Smoothness Prior Function

An explicit constraint is introduced into the Lucas-Kanade gradient based block motion model. This constraint helps the estimation process to consider surrounding motion vectors during its calculation. Consequently a better motion field can be produced than that by the original block motion model. Further, a discontinuity adaptive function is introduced into the Lucas-Kanade equation, which helps to preserve the discontinuities of motion fields
Cows Need Both C 16 and C 18 Fatty Acids

During the past decade, fatty acid (FA) research has been focused on discovering the optimal combination of FA to feed to lactating cows for the purpose of improving milk yield (MY) and milk components. Most long chain fatty acid (LCFA) supplements contain either combinations of palmitic (C16:0) and oleic acids (C18:1), highly enriched C16:0 (>80%), or C16:0, stearic acid (C18:0), and C18:1. These supplement categories have substantial published research trials over the past 30 years. Nutritionists, researchers, and dairymen are continuing to search for the most optimal combination of these three LCFA. New information continues to enhance our knowledge of the metabolism and utilization of these LCFA for the purpose of improving MY, milk fat (MF), milk protein (MP), and reproduction by improving energy balance (EB) in early lactation. These LCFA are intimately involved in the metabolism of the lactating cow and have specific functions in the production of milk and milk components. Palmitic acid has been shown to improve milk fat % and yield. However, supplementing C16:0 has no effect on MY, body weight gain or body condition score (BCS). Stearic acid has been observed to have a positive influence on dry matter intake (DMI) and the yield of milk, MF, MP, and milk lactose. Combinations of C16:0 and C18:0 have been shown to improve MY, milk components, and improve EB in early lactation. Thus, the importance in discovering the proper ratio and feeding rates of these LCFA to improve performance is of interest.
Affine-Invariant Image Retrieval Based on Wavelet Interest Points

This paper presents an affine-in variant image retrieval approach based on wavelet-based detector, which uses the space-tree property of the transform coefficients to estimate the interest points. Meanwhile, in order to retrieve images compressed by wavelet algorithm such as JPEG2000, the detector only uses the partial bit-planes of the wavelet coefficients to detect the interest points. To provide affine-invariant image matching, annular color histogram, annular texture histogram and spatial cohesion based on interest points are presented to describe image features. A series of experiments based on an image database consisting of 1000 images are performed to confirm the effectiveness of our method
Posterior maxillary (PM) plane and anterior cranial architecture in primates

This study tests several hypotheses of integration between the cranial base and face in primates. After reviewing the definition and anatomical basis for the posterior maxillary (PM) plane, which demarcates the back of the midface at its junction with the sphenoid, we demonstrate how the PM plane can be identified accurately on radiographs, and confirm that it maintains a 90° angle relative to the Neutral Horizontal Axis of the orbits in all primates. In addition, we use the PM plane to test Dabelow's ( 1929 ) hypothesis that the orbits and anterior cranial base are more highly integrated in anthropoids than in strepsirrhines, and we test the hypothesis that the midline anterior cranial base (planum sphenoideum) and anterior cranial floor (planum sphenoideum plus cribriform plate) in primates are highly correlated with each other relative to the PM plane. The mean angle between the anterior cranial base and the PM plane does not differ significantly from 90° in anthropoids, but differs significantly in strepsirrhines. The anterior cranial base and anterior cranial floor, however, correlate well with each other relative to the PM plane in both suborders of primates, independent of orbital orientation and configuration. The PM plane, anterior cranial base, and anterior cranial floor, therefore, form an integrated structural complex, a “facial block,” whose orientation relative to the posterior cranial base influences craniofacial shape among anthropoids in which orbital orientation influences the orientation of the anterior cranial base. One such effect is that increases in cranial base flexion shorten the antero‐posterior length of the nasopharynx. Anat Rec 264:247–260, 2001. © 2001 Wiley‐Liss, Inc.
Hereditary bladder cancer

First degree relatives of patients with bladder cancer have a two-fold increased risk of bladder cancer but high-risk bladder cancer families are extremely rare. There is no clear Mendelian inheritance pattern that can explain the increased familial risk. This makes classical linkage studies for the mapping of susceptibility genes impossible. The disease is probably caused by a combination of exposure to exogenous carcinogens and a large number of susceptibility genes with modest effects. Genome-wide association studies are better suited to identify these genes. Three such studies are currently underway and are expected to report their results in 2008.
Genetic Variation of Fatty Acid Oxidation and Obesity, A Literature Review

Modulation of fat metabolism is an important component of the etiology of obesity as well as individual response to weight loss program. The influence of lipolysis process had receives many attentions in recent decades. Compared to that, fatty acid oxidation which occurred after lipolysis seems to be less exposed. There are limited publications on how fatty acid oxidation influences predisposition to obesity, especially the importance of genetic variations of fatty acid oxidation proteins on development of obesity. The aim of this review is to provide recent knowledge on how polymorphism of genes related fatty acid oxidation is obtained. Studies in human as well as animal model showed that disturbance of genes related fatty acid oxidation process gave impact on body weight and risks to obesity. Several polymorphisms on CD36, CPT, ACS and FABP had been shown to be related to obesity either by regulating enzymatic activity or directly influence fatty acid oxidation process.
Improvisational change management in the pubic sector

This paper deals with the issue of how the use of a plan can improve change management when introducing groupware in the public sector, using an improvisational perspective. The research is based on an empirical study at a municipal administration investigating changes in the work situation after the implementation of groupware. When an improvisational model of change management was applied certain development possibilities of the model and it's use appeared. Firstly, the model does not acknowledge anticipated changes that do not occur in practice. Secondly, we argue that a more active utilization of a plan enables guidance of the process. Finally, we emphasize the necessity of translating a plan into a local context.
Outcomes of TB Treatment by HIV Status in National Recording Systems in Brazil, 2003–2008

Background Although the Brazilian national reporting system for tuberculosis cases (SINAN) has enormous potential to generate data for policy makers, formal assessments of treatment outcomes and other aspects of TB morbidity and mortality are not produced with enough depth and rigor. In particular, the effect of HIV status on these outcomes has not been fully explored, partly due to incomplete recording in the national database. Methodology/Principal Findings In a retrospective cohort study, we assessed TB treatment outcomes, including rates of cure, default, mortality, transfer and multidrug resistant TB (MDR-TB) among a purposively chosen sample of 161,481 new cases reported in SINAN between 2003 and 2008. The study population included all new cases reported in the six States with the highest level of completeness of the HIV status field in the system. These cases were mostly male (67%), white (62%), had pulmonary TB (79%) and a suspect chest X ray (83%). Treatment outcomes were best for those HIV negative cases and worst for those known HIV positive patients (cure rate of 85.7% and 55.7% respectively). In multivariate modeling, the risk of having an unfavorable outcome (all outcomes except cure) was 3.09 times higher for those HIV positive compared with those HIV negative (95% CI 3.02–3.16). The risk of death and default also increased with HIV positivity. The group without a known HIV status showed intermediate outcomes between the groups above, suggesting that this group includes some with HIV infection. Conclusions HIV status played an important role in TB treatment outcomes in the study period. The outcomes observed in those with known HIV were poor and need to be improved. Those in the group with unknown HIV status indicate the need for wider HIV testing among new TB cases.
Immune System Modulation of Germinal and Parenchymal Neural Progenitor Cells in Physiological and Pathological Conditions

Historically, the Central Nervous System (CNS) was considered as an immune privileged site (Billingham and Boswell, 1953), being viewed as a territory physiologically out of the competence of immune cells. This notion has developed on initial studies showing that: (i) CNS unrelated antigens (i.e. foreign grafts, bacteria, viruses) evade an immune recognition when delivered to the brain parenchyma (Galea et al., 2007); (ii) no infiltrating immune cells nor antigen presenting cells (APCs, i.e. dendritic cells, DCs, see Table 1) can be detected in the CNS parenchyma in physiological conditions (Engelhardt and Ransohoff, 2005); (iii) CNS cells do not constitutively express major histocompatibility complex (MHC)I and MHCII molecules (Fabry et al., 1994); (iv) neural cells express apoptosis inductors for immune cells (Bechmann et al., 1999); (v) the CNS does not possess lymphatic vessels (Engelhardt and Ransohoff, 2005). The segregation between nervous and immune cells appeared tightly preserved by the anatomical separations offered by the Blood Brain Barrier (BBB) and the blood-cerebrospinal fluid barrier (Choi and Benveniste, 2004). Over time, on the basis of the association between immune inflammation and neurodegeneration, the concept of immune privilege further acquired the connotation of a defence mechanism against the detrimental effects of immune activation within the CNS.
Diabetic Retinopathy, Its Progression, and Incident Cardiovascular Events in the ACCORD Trial

OBJECTIVE Both the presence of diabetic retinopathy and its severity are significantly associated with future cardiovascular (CV) events. Whether its progression is also linked to incident CV outcomes hasn’t been assessed. RESEARCH DESIGN AND METHODS The relationship between retinopathy, its 4-year progression, and CV outcomes (CV death or nonfatal myocardial infarction or stroke) was analyzed in participants in the Action to Control Cardiovascular Risk in Diabetes (ACCORD) trial who also participated in the ACCORD Eye Study. Retinopathy was classified as either none, mild, moderate, or severe, and worsening was classified as a <2-step, 2–3-step, or >3-step change (that included incident laser therapy or vitrectomy). RESULTS Participants (n = 3,433) of mean age 61 years had baseline retinal photographs (seven stereoscopic fields). Compared with no retinopathy, the adjusted HRs (95% CI) for the CV outcome rose from 1.49 (1.12–1.97) for mild retinopathy to 2.35 (1.47–3.76) for severe retinopathy. A subset of 2,856 was evaluated for progression of diabetic retinopathy at 4 years. The hazard of the primary outcome increased by 38% (1.38 [1.10–1.74]) for every category of change in retinopathy severity. Additional adjustment for the baseline and follow-up levels of A1C, systolic blood pressure, and lipids either individually or together rendered the relationships between worsening and CV outcomes nonsignificant. CONCLUSIONS Both the severity of retinopathy and its progression are determinants of incident CV outcomes. The retina may provide an anatomical index of the effect of metabolic and hemodynamic factors on future CV outcomes.
Barrier variational generation of quasi‐isometric grids

A grid generation method based on the minimization of the discrete barrier functional with feasible set consisting of quasi‐isometric grids is suggested. The deviation from isometry for given grid connectivity and prescribed boundary conditions is minimized via the contraction of the feasible set into a small vicinity of the optimal grid. Formulation of functional with given metrics in both physical and logical spaces allows to consider the adaptive grid generation in terms of quasi‐isometric grids and cover many practical applications. A fast and reliable grid untangling procedure based on the penalty‐like reformulation of barrier functional and the continuation technique is described. Numerical experiments demonstrate that the suggested functional produces high‐quality grids with small global condition numbers. Copyright © 2001 John Wiley & Sons, Ltd.
Problems in Wireless Ad-hoc Sensor Networks

Wireless ad-hoc sensor networks have recently emerged as a premier research topic. They have great long term economic potential, ability to transform our lives, and pose many new system-building challenges. Sensor networks also pose a number of new conceptual and optimization problems. Some, such as location, deployment, and tracking, are fundamental issues, in that many applications rely on them for needed information. In this paper, we address one of the fundamental problems, namely coverage. Coverage in general, answers the questions about quality of service (surveillance) that can be provided by a particular sensor network. We first define the coverage problem from several points of view including deterministic, statistical, worst and best case, and present examples in each domain. By combining computational geometry and graph theoretic techniques, specifically the Voronoi diagram and graph search algorithms, we establish the main highlight of the paper-optimal polynomial time worst and average case algorithm for coverage calculation. We also present comprehensive experimental results and discuss future research directions related to coverage in sensor networks. I. Introduction As our personal computing era evolves into a ubiquitous computing one, there is a need for a world of fully connected devices with inexpensive wireless networks. Improvements in wireless network technology interfacing with emerging micro-sensor based on MEMs technology [2], is allowing sophisticated inexpensive sensing, storage, processing, and communication capabilities to be unobtrusively embedded into our everyday physical world. Moreover, embedded web servers [1, 3] can be used to connect the physical world of sensors and actuators to the virtual world of information utilities and services. Consequently, a flurry of research activity has recently commenced in the sensor network domain, especially in wireless ad-hoc sensor networks. Although many of the sensor technologies are not new, there are certain physical laws governing the energy requirements of performing wireless communications that have limited the feasibility of such devices in the past. Some of the benefits of the newer, more capable sensor nodes are the ability to: 1. Build large-scale networks; 2. Implement sophisticated protocols; 3. Reduce the amount of communication (wireless) required to perform tasks by distributed and/or local precomputations; 4. Implement complex power saving modes of operation depending on the environment and the state of the network. Due to the above-mentioned advances in sensor network technology, more and more practical applications of wireless sensor networks continue to emerge. As an example, consider the millions of acres that are lost around …
Analysis of Training Set Composition in Boosting for Object Category Recognition

This project explores recognition and classification of objects in images using the popular and effective machine learning method, Boosting. Boosting provides a framework for developing robust object detection algorithms. Boosting itself involves the training of a series of increasingly discriminating simple classifiers, and then blending their outputs – further, it involves constructing a classifier as a sum of simple weak learners. By themselves, these weak learners do not contribute much to classification performance; however, the main ingredient for Boosting’s success is a method for incrementally selecting the weak learners. That said, Boosting has successfully been applied in computer vision in areas such as pedestrian and face detection. However, despite the method’s success, its performance may be heavily dependant on the quality and quantity of the data on which it is trained. In the present context, quality of training data could cover such properties as having images that cover a range of lighting conditions, poses of an object, and alignment characteristics of the object and image. Quantity of training data really means the number of positive and negative examples of the object to be classified. In this project, I propose to explore recognition and classification of objects in images using Boosting by selecting a couple of interesting, difficult object categories, and varying the training conditions for the Boosting solution. I will do this by examining different elements of quality and quantity of training data as described, and reporting the results via standard methods such as Receiver Operating Characteristic (ROC) curves to vividly describe the contributions of quality and quantity of training data to the final, Boosting solution. This work finds that increasing data set size improves correct classification rate, classifiers trained on misaligned images perform more poorly than classifiers trained on images tightly aligned to their respective object category, and suggests that an assembly of classifiers trained on component body parts of highly articulated, jointed figures may be a better strategy for their correct classification than a classifier trained on the single, large figure itself.
Variation-Aware Resource Allocation Evaluation for Cloud Workflows Using Statistical Model Checking

Aiming at minimizing service operating costs and SLA (Service Level Agreement) violations, various resource allocation strategies have been investigated to support Cloud service providers' decision making. However, due to the service execution time variation, traditional optimal resource allocation strategies cannot achieve the best performance in practice. To address this problem, we propose an automated variation-aware evaluation framework for resource allocation strategies based on statistical model checker UPPAAL-SMC. Our framework can systematically evaluate the performance of resource allocation strategies under variations, and conduct complex queries on the quality of service. The experimental results show that our framework can not only filter inferior solutions efficiently, but also can enable the tuning of requirement constraints. Since our approach can be fully automated, the human efforts in resource allocation strategy evaluation can be significantly reduced.
The Trichoderma reesei Cry1 Protein Is a Member of the Cryptochrome/Photolyase Family with 6–4 Photoproduct Repair Activity

DNA-photolyases use UV-visible light to repair DNA damage caused by UV radiation. The two major types of DNA damage are cyclobutane pyrimidine dimers (CPD) and 6–4 photoproducts (6-4PP), which are repaired under illumination by CPD and 6–4 photolyases, respectively. Cryptochromes are proteins related to DNA photolyases with strongly reduced or lost DNA repair activity, and have been shown to function as blue-light photoreceptors and to play important roles in circadian rhythms in plants and animals. Both photolyases and cryptochromes belong to the cryptochrome/photolyase family, and are widely distributed in all organisms. Here we describe the characterization of cry1, a member of the cryptochrome/photolyase protein family of the filamentous fungus Trichoderma reesei. We determined that cry1 transcript accumulates when the fungus is exposed to light, and that such accumulation depends on the photoreceptor Blr1 and is modulated by Envoy. Conidia of cry1 mutants show decreased photorepair capacity of DNA damage caused by UV light. In contrast, strains over-expressing Cry1 show increased repair, as compared to the parental strain even in the dark. These observations suggest that Cry1 may be stimulating other systems involved in DNA repair, such as the nucleotide excision repair system. We show that Cry1, heterologously expressed and purified from E. coli, is capable of binding to undamaged and 6-4PP damaged DNA. Photorepair assays in vitro clearly show that Cry1 repairs 6-4PP, but not CPD and Dewar DNA lesions.
An evaluation of evolved term-weighting schemes in information retrieval

This paper presents an evaluation of evolved term-weighting schemes on short, medium and long TREC queries. A previously evolved global (collection-wide) term-weighting scheme is evaluated on unseen TREC data and is shown to increase mean average precision over idf. A local (within-document) evolved term-weighting scheme is presented which is dependent on the best performing global scheme. The full evolved scheme (i.e. the combined local and global scheme) is compared to both the BM25 scheme and the Pivoted Normalisation scheme.Our results show that the local evolved solution does not perform well on some collections due to its document normalisation properties and we conclude that Okapi-tf can be tuned to interact effectively with the evolved global weighting scheme presented and increase mean average precision over the standard BM25 scheme.