Miracle-dz/UniFAR-FTUs huggingface dataset:
Staying Alive: Social Studies in Elementary Schools.

It’s a crisis. Social studies, particularly in the elementary grades, has been pushed to the back burner in schools.1 Time is the biggest nemesis. Increased attention to math and language arts under the federal No Child Left Behind law is squeezing out social studies. Many states have standards in social studies so teachers are expected to cover the topic, but without being attached to a high-stakes test, the subject has lost ground. Some states, such as Illinois, are even dropping state social studies tests. What little social studies is taught usually consists of “laundry lists”—vocabulary words, dates and people’s names, educators say, which is just plain boring. Money is another rare commodity to buy proper books, to find quality teachers, and even to create standardized tests to ensure the subject is being taught. Most educators find the decreased attention to social studies a travesty. Even though many students learn social studies in middle or high school, they lack the basic knowledge needed for the subject. Many middle and high school teachers are squeezed for time and can’t teach it all. In the end, educators fear youngsters are growing up with little or no knowledge of their own and their neighbors’ histories, ironically when the nation is debating many foreign policy issues. “What has happened with No Child Left Behind is that someone made a political decision that reading and writing and arithmetic are the core subjects that we need to spend a considerable amount of time and money on in grades three through eight. And it put social studies on the back burner,” says Jesus Garcia, president of National Council for the Social Studies. “That doesn’t make sense. We should maintain the core subjects at the forefront and allow the kind of funding to teach that well. ” The 2004 report from Council for Basic Education, Academic Atrophy: The Condition of the Liberal Arts in America’s Public Schools, reveals that social studies is suffering, particularly in high minority schools.2 The good news, the report states, is more emphasis is placed on math, reading, writing, science and secondary social studies. But the bad news is the reduced commitment to the arts, foreign language and elementary social studies. Syd Golston, dean of students at El Hambra High School in Phoenix Union High School District, says education author Alfie Kohn3 is right when he says learning for the joy of learning should guide education, but it doesn’t. While districts nationwide may test social studies, there is little, if any, time for mock trials, role playing or immersion learning, Golston says, which really inspires children and makes learning fun. “There is no time to do the things that are personal and process-oriented,” he adds.
A Report on the 2017 Native Language Identification Shared Task

Native Language Identification (NLI) is the task of automatically identifying the native language (L1) of an individual based on their language production in a learned language. It is typically framed as a classification task where the set of L1s is known a priori. Two previous shared tasks on NLI have been organized where the aim was to identify the L1 of learners of English based on essays (2013) and spoken responses (2016) they provided during a standardized assessment of academic English proficiency. The 2017 shared task combines the inputs from the two prior tasks for the first time. There are three tracks: NLI on the essay only, NLI on the spoken response only (based on a transcription of the response and i-vector acoustic features), and NLI using both responses. We believe this makes for a more interesting shared task while building on the methods and results from the previous two shared tasks. In this paper, we report the results of the shared task. A total of 19 teams competed across the three different sub-tasks. The fusion track showed that combining the written and spoken responses provides a large boost in prediction accuracy. Multiple classifier systems (e.g. ensembles and meta-classifiers) were the most effective in all tasks, with most based on traditional classifiers (e.g. SVMs) with lexical/syntactic features.
Ethanol concentrations in antemortem blood samples under controlled conditions.

AIM The change of antemortem blood alcohol concentration (BAC) in inadequately processed samples was examined. METHODS The study was performed on nine healthy, sober volunteers after overnight fasting. Blood samples were divided into groups and stored, with or without NaF, for varying time periods (12, 24 and 48 h) and at different temperatures (4 degrees C and 20 degrees C). BAC analysis was performed by the gas-chromatography method. RESULT All groups showed very low values of BAC. CONCLUSION Surprisingly, this study showed no ethanol production in improperly processed antemortem blood samples in healthy and sober individuals who were subjected to overnight fasting.
Crystal structure of human cyclophilin D in complex with its inhibitor, cyclosporin A at 0.96‐Å resolution

Crystal structure of human cyclophilin D in complex with its inhibitor, cyclosporin A at 0.96-Å resolution Kenji Kajitani, Masahiro Fujihashi, Yukiko Kobayashi, Shigeomi Shimizu, Yoshihide Tsujimoto, and Kunio Miki* 1Department of Chemistry, Graduate School of Science, Kyoto University, Sakyo-Ku, Kyoto 606-8502, Japan 2 Laboratory of Molecular Genetics, Department of Medical Genetics, Osaka University Medical School and SORST of JST, Suita, Osaka 565-0871, Japan
Comparative Analysis of Adaptive Vessel Segmentation—Cerebral Arteriovenous Malformation

Aim: Neurovascular abnormalities are extremely complex, due to the multitude of factors acting simultaneously on cerebral hemodynamics. Cerebral Arteriovenous Malformation (CAVM) hemo-dynamic in one of the vascular abnormality condition results changes in the vessels structures and hemodynamics in blood vessels. The challenge is segmenting accurate vessel region to measure hemodynamics of CAVM patients. The clinical procedure is in-vivo method to measure hemodynamics. The catheter-based procedure is difficult, as it is sometimes difficult to reach vessels sub-structures. Methods: In this paper, we have proposed adaptive vessel segmentation based on threshold technique for CAVM patients. We have compared different adaptive methods for vessel segmentation of CAVM structures. The sub-structures are modeled using lumped model to measure hemodynamics non-invasively. Results: Twenty-three CAVM patients with 150 different vessel locations of DSA datasets were studied as part of the adaptive segmentation. 30 simulated data has been evaluated for more than 150 vessels locations for sub-segmentation of vessels. The segmentation results are evaluated with accuracy of 93%. The computed p-value is smaller than the significance level 0.05. Conclusion: The adaptive segmentation using threshold based produces accurate vessel segmentation, results in better accuracy of hemodynamic measurements for DSA images for CAVM patients. The proposed adaptive segmentation helps clinicians to measure hemodynamic non-invasively for the segmented sub-structures of vessels.
Review of modern diagnostic techniques for assessing insulation condition in aged transformers

Cellulosic paper and oil insulation in a transformer degrade at higher operating temperatures. Degradation is accelerated in the presence of oxygen and moisture. Power transformers being expensive items need to be carefully monitored throughout their operation. Well established time-based maintenance and conservative replacement planning is not feasible in a current market driven electricity industry. Condition based maintenance and online monitoring are now gaining importance. Currently there are varieties of chemical and electrical diagnostic techniques available for insulation condition monitoring of power transformers. This paper presents a description of commonly used chemical diagnostics techniques along with their interpretation schemes. A number of new chemical techniques are also described in this paper. A number of electrical diagnostic techniques have gained exceptional importance to the utility professionals. Among these techniques polarisation/depolarisation current measurement, return voltage measurement and frequency domain dielectric spectroscopy at low frequencies are the most widely used. This paper describes analyses and interpretation of these techniques for transformer insulation condition assessment.
Matching Drivers and Transportation Requests in Crowdsourced Delivery Systems

While the sales volume of e-commerce transactions is growing rapidly, the traditional concept of packages delivery has been challenged by innovative approaches such as crowdsourced delivery. Using individuals, for example commuters, to deliver packages from senders to receivers can provide several economic and environmental benefits. This paper illustrates an algorithm that automates and optimizes the assignment of drivers to transportation requests by matching them based on transportation routes and time constraints. We evaluated our algorithm by using a simulated setting based on mobility data recorded in a major German city. This paper contributes to theory by giving guidance for future research on matching algorithms for crowdsourced delivery systems and to practice by illustrating an algorithm that can be adapted by existing and new crowdsourced delivery platforms.
Involvement of Vitronectin in Lipopolysaccaride-Induced Acute Lung Injury1

Vitronectin is present in large concentrations in serum and participates in regulation of humoral responses, including coagulation, fibrinolysis, and complement activation. Because alterations in coagulation and fibrinolysis are common in acute lung injury, we examined the role of vitronectin in LPS-induced pulmonary inflammation. Vitronectin concentrations were significantly increased in the lungs after LPS administration. Neutrophil numbers and proinflammatory cytokine levels, including IL-1β, MIP-2, KC, and IL-6, were significantly reduced in bronchoalveolar lavage fluid from vitronectin-deficient (vitronectin−/−) mice, as compared with vitronectin+/+ mice, after LPS exposure. Similarly, LPS induced increases in lung edema, myeloperoxidase-concentrations, and pulmonary proinflammatory cytokine concentrations were significantly lower in vitronectin−/− mice. Vitronectin−/− neutrophils demonstrated decreased KC-induced chemotaxis as compared with neutrophils from vitronectin+/+ mice, and incubation of vitronectin+/+ neutrophils with vitronectin was associated with increased chemotaxis. Vitronectin−/− neutrophils consistently produced more TNF-α, MIP-2, and IL-1β after LPS exposure than did vitronectin+/+ neutrophils and also showed greater degradation of IκB-α and increased LPS-induced nuclear accumulation of NF-κB compared with vitronectin+/+ neutrophils. These findings provide a novel vitronectin-dependent mechanism contributing to the development of acute lung injury.
Population proteomics: addressing protein diversity in humans

In the past several years, proteomics and its subdiscipline clinical proteomics have been engaged in the discovery of the next generation protein of biomarkers. As the effort and the intensive debate it has sparked continue, it is becoming apparent that a paradigm shift is needed in proteomics in order to truly comprehend the complexity of the human proteome and assess its subtle variations among individuals. This review introduces the concept of population proteomics as a future direction in proteomics research. Population proteomics is the study of protein diversity in human populations. High-throughput, top-down mass spectrometric approaches are employed to investigate, define and understand protein diversity and modulations across and within populations. Population proteomics is a discovery-oriented endeavor with a goal of establishing the incidence of protein structural variations and quantitative regulation of these modifications. Assessing human protein variations among and within populations is viewed as a paramount undertaking that can facilitate clinical proteomics’ effort in discovery and validation of protein features that can be used as markers for early diagnosis of disease, monitoring of disease progression and assessment of therapy. This review outlines the growing need for analyzing individuals’ proteomes and describes the approaches that are likely to be applied in such a population proteomics endeavor.
Determinants of Increased Replicative Capacity of Serially Passaged Simian Immunodeficiency Virus with nef Deleted in Rhesus Monkeys

ABSTRACT Most rhesus macaques infected with simian immunodeficiency virus SIVmac239 with nef deleted (either Δnef or ΔnefΔvprΔUS [Δ3]) control viral replication and do not progress to AIDS. Some monkeys, however, develop moderate viral load set points and progress to AIDS. When simian immunodeficiency viruses (SIVs) recovered from two such animals (one Δnef and the other Δ3) were serially passaged in rhesus monkeys, the SIVs derived from both lineages were found to consistently induce moderate viral loads and disease progression. Analysis of viral sequences in the serially passaged derivatives revealed interesting changes in three regions: (i) an unusually high number of predicted amino acid changes (12 to 14) in the cytoplasmic domain of gp41, most of which were in regions that are usually conserved; these changes were observed in both lineages; (ii) an extreme shortening of nef sequences in the region of overlap with U3; these changes were observed in both lineages; and (iii) duplication of the NF-κB binding site in one lineage only. Neither the polymorphic gp41 changes alone nor the U3 deletion alone appeared to be responsible for increased replicative capacity because recombinant SIVmac239Δnef, engineered to contain either of these changes, induced moderate viral loads in only one of six monkeys. However, five of six monkeys infected with recombinant SIVmac239Δnef containing both TM and U3 changes did develop persisting moderate viral loads. These genetic changes did not increase lymphoid cell-activating properties in the monkey interleukin-2-dependent T-cell line 221, but the gp41 changes did increase the fusogenic activity of the SIV envelope two- to threefold. These results delineate sequence changes in SIV that can compensate for the loss of the nef gene to partially restore replicative and pathogenic potential in rhesus monkeys.
Effects of ibotenic acid-induced loss of neurons in the medial prefrontal cortex of rats on behavioral vigilance: evidence for executive dysfunction

Rats were trained in a previously validated task for the assessment of sustained attention, or vigilance. This task required the animals to discriminate between signals of variable lengths and non-signal events by making an appropriate lever press. The performance of sham-lesioned animals in this task was characterized by a signal-length dependent number of hits. Also, approximately 70 percent of the non-signals were correctly rejected. Ibotenic acid-induced lesions of the medial prefrontal cortex decreased the relative number of hits and correct rejections and, in essence, resulted in random lever selection. The lesion did not affect the number of omissions or side bias. Furthermore, the performance of lesioned animals was insensitive to the detrimental effects of distractors. The effects of the lesions do not support an interpretation in terms of sustained attention. Rather, the pattern of the lesioned animals' performance is speculated to reveal a fundamental disruption of decisional processes, reminiscent of the executive dysfunctions observed in patients with damage to ventromedial prefrontal areas or with schizophrenia.
An optical flow and inter-frame block-based histogram correlation method for moving object detection

Moving object detection is very important for video surveillance. In this paper, we present a new real time motion detection algorithm that is based on the integration of optical flow and inter-frame block-based histogram correlation method to achieve better performance. The optical flow method is used to detect any movement under the background and the inter-frame block-based histogram correlation method is used to eliminate the background information and separate the moving object from it. The biggest advantage of this algorithm is that it does not need to learn the background model from hundreds of images and can handle quick image variations without prior knowledge about the object size and shape. The algorithm has high capability of anti-interference and preserves high accurate rate detection at the same time. The effectiveness of the proposed algorithm for motion detection is demonstrated in a simulation environment and the evaluation results are reported in this paper.
Mechanism-based Pain Diagnosis: Issues for Analgesic Drug Development

ENORMOUS progress is currently being made by the exploitation of modern neurobiologic techniques in the elucidation of mechanisms that may contribute to the pathogenesis of pain. These indicate that pain can be generated in multiple ways at a number of different sites that may coexist between and across diverse disease states. Molecular biologic techniques are contributing to the analysis of pain mechanisms and are leading to the discovery of new targets, which are being used in high throughput screens by the pharmaceutical industry for the discovery of highly specific small molecules as potential novel analgesics. The discovery of targets specific to particular pain mechanisms will soon enable therapy to be targeted specifically at those mechanisms. This raises several problems: how to identify the mechanisms in an individual patient, how to test for the efficacy of a compound that may alter only one component of a complex syndrome that involves multiple mechanisms, and how to test for interaction between two different compounds targeted at two independent mechanisms. Clinical studies suggest that within conventional diagnostic groups of chronic pain patients, there are subgroups with differing responses to drug treatment, and yet the clinical development of new analgesic drugs has ignored this mechanistic heterogeneity. Trials that select patients based only on a disease may produce a false-negative result, with the nonresponders diluting out the benefit in the subgroup with the targeted mechanism. In this review, we sketch a research agenda that might move us toward a mechanism-based analgesic development. First, it is necessary to consider the following questions: To what degree can clinicians directly assess pain mechanisms in patients? What is the evidence from controlled clinical trials that variation in analgesic response between patients can be explained by disease or syndrome, tissue of pain origin, or symptom-based assessment of pain mechanisms? How should analgesic development pathways be revised to most efficiently demonstrate the spectrum of efficacy of a new drug? What types of collaborations between academic pain researchers, industry, government research funders, and regulators can hasten the potential clinical benefits of mechanism-based pain treatment?
evel set method with automatic selective local statistics for brain umor segmentation in MR images iran

The level set approach is a powerful tool for segmenting images. This paper proposes a method for segmenting brain tumor images from MR images. A new signed pressure function (SPF) that can efficiently stop the contours at weak or blurred edges is introduced. The local statistics of the different objects present in the MR images were calculated. Using local statistics, the tumor objects were identified among different objects. In this level set method, the calculation of the parameters is a challenging task. The calevel set method ctive contours eodesic active contours han–Vese model mage segmentation culations of different parameters for different types of images were automatic. The basic thresholding value was updated and adjusted automatically for different MR images. This thresholding value was used to calculate the different parameters in the proposed algorithm. The proposed algorithm was tested on the magnetic resonance images of the brain for tumor segmentation and its performance was evaluated visually and quantitatively. Numerical experiments on some brain tumor images highlighted the of th R images efficiency and robustness
Allergenicity prediction by protein sequence

Potential allergenicity of transgenic proteins for consumption must be investigated before their introduction into the food chain. A prerequisite is sequence analysis. We have critically reviewed the performance of the current guidelines proposed by the Food and Agriculture Organization (FAO) and the World Health Organization (WHO) for allergenicity prediction based on protein sequence and show that its precision is very low. To improve prediction, we propose a new strategy based on sequence motifs identified from a new allergen database. If tested on random test sequences and known allergens, both methods are apparently very sensitive. However, the precision of our motif‐based prediction (95.5%) is superior to the current method (36.6%). We conclude that the proposed motif‐based prediction is a superior alternative to the current method for use in the decision‐tree approach for allergenicity assessment.
The potential for abuse of genetics in militarily significant biological weapons

Concern has been expressed at successive Review Conferences of the Biological and Toxin Weapons Convention (BTWC) regarding the possible misuse of new biological knowledge; this article reviews some of these developments. Genetic manipulation, and genomics in particular, would modify existing pathogens and render previously harmless organisms pathogenic. Viruses could be modified as vectors to alter their pathogenicity in animals and man or act as carriers for genes or toxins. Plant pathogens, particularly fungi, could be modified as biological warfare agents against crops. An effective verification protocol for the BTWC is an essential part of the web of deterrence against these developments.
Real-time method for general road segmentation

Image road detection in unstructured environments is a crucial and challenging problem in the application of mobile robots and autonomous vehicles. In this paper, we present an effective and computationally efficient solution to segment the road region for structured and unstructured roads. We propose a new method that incorporates two different approaches: road detection based on the vanishing point and image segmentation using a seeded region growing (SRG) algorithm. First, a fast vanishing point detection algorithm is applied and used to find an estimation of the road boundaries. Subsequently, we segment the road area region executing a SRG algorithm based on the vanishing point and the road boundaries found previously. Evaluation of our method over different images datasets demonstrates that it is effective in challenging conditions such as dirt and curved roads.
FDTD analysis of a shorted and truncated microstrip antenna for mobile communications systems

In this paper, a shorted and truncated microstrip antenna suitable for mobile communications systems is presented. Full-wave analysis is performed using the finite-difference time-domain method. It has been found that the shorted and truncated microstrip antennas exhibit a very narrow band resonance around 850 MHz when the dimensions of the antenna are chosen properly.