Miracle-dz/UniFAR-FTUs huggingface dataset:
Motor and Sensory Deficits in the teetering Mice Result from Mutation of the ESCRT Component HGS

Neurons are particularly vulnerable to perturbations in endo-lysosomal transport, as several neurological disorders are caused by a primary deficit in this pathway. In this report, we used positional cloning to show that the spontaneously occurring neurological mutation teetering (tn) is a single nucleotide substitution in hepatocyte growth factor-regulated tyrosine kinase substrate (Hgs/Hrs), a component of the endosomal sorting complex required for transport (ESCRT). The tn mice exhibit hypokenesis, muscle weakness, reduced muscle size and early perinatal lethality by 5-weeks of age. Although HGS has been suggested to be essential for the sorting of ubiquitinated membrane proteins to the lysosome, there were no alterations in receptor tyrosine kinase levels in the central nervous system, and only a modest decrease in tropomyosin receptor kinase B (TrkB) in the sciatic nerves of the tn mice. Instead, loss of HGS resulted in structural alterations at the neuromuscular junction (NMJ), including swellings and ultra-terminal sprouting at motor axon terminals and an increase in the number of endosomes and multivesicular bodies. These structural changes were accompanied by a reduction in spontaneous and evoked release of acetylcholine, indicating a deficit in neurotransmitter release at the NMJ. These deficits in synaptic transmission were associated with elevated levels of ubiquitinated proteins in the synaptosome fraction. In addition to the deficits in neuronal function, mutation of Hgs resulted in both hypermyelinated and dysmyelinated axons in the tn mice, which supports a growing body of evidence that ESCRTs are required for proper myelination of peripheral nerves. Our results indicate that HGS has multiple roles in the nervous system and demonstrate a previously unanticipated requirement for ESCRTs in the maintenance of synaptic transmission.
Scalable malware forensics using phylogenetic analysis

Malware forensics analysts confront one of our biggest homeland security challenges - a continuing flood of new malware variants released by adaptable adversaries seeking new targets in cyberspace, exploiting new technologies, and bypassing existing security mechanisms. Reverse engineering new samples, understanding their capabilities, and ascertaining provenance is time-intensive and requires considerable human expertise. We present DECODE, a prototype malware forensics analysis system developed under DARPA's Cyber Genome program. DECODE increases the actionable forensics derivable from large repositories of collected malware by quickly identifying a new malware sample as a variant of other malware samples, without relying on pre-existing anti-virus signatures. DECODE also accelerates reverse engineering efforts by quickly identifying parts of the malware that have already been seen in other samples and characterizing the new and different capabilities. DECODE can also reconstruct the evolution of malware variants over time. DECODE applies phylogenetic analysis to provide these advantages. Phylogenetic analysis is the study of similarities and differences in program structure to find relationships within groups of software programs, providing insights about new malware variants not available from signature-based malware detection.
A Voronoi-based hybrid motion planner

We present a hybrid path planning algorithm for rigid and articulated bodies translating and rotating in a 3D workspace. Our approach generates a Voronoi roadmap in the workspace and combines it with "bridges" computed by a randomized path planner with Voronoi-biased sampling. The Voronoi roadmap is computed from a discrete approximation to the generalized Voronoi diagram (GVD) of the workspace, which is generated using graphics hardware. By using this GVD, portions of the path can be generated without random sampling, substantially reducing the number of random samples needed for the full query. The planner has been implemented and tested on a number of benchmarks. Some preliminary comparisons with a randomized motion planner indicate that our planner performs more than an order of magnitude faster in several challenging scenarios.
Final-state constrained optimal control via a projection operator approach

In this paper we develop a numerical method to solve nonlinear optimal control problems with final-state constraints. Specifically, we extend the PRojection Operator based Netwon's method for Trajectory Optimization (PRONTO), which was proposed by Hauser for unconstrained optimal control problems. While in the standard method final-state constraints can be only approximately handled by means of a terminal penalty, in this work we propose a methodology to meet the constraints exactly. Moreover, our method guarantees recursive feasibility of the final-state constraint. This is an appealing property especially in realtime applications in which one would like to be able to stop the computation even if the desired tolerance has not been reached, but still satisfy the constraints. Following the same conceptual idea of PRONTO, the proposed strategy is based on two main steps which (differently from the standard scheme) preserve the feasibility of the final-state constraints: (i) solve a quadratic approximation of the nonlinear problem to find a descent direction, and (ii) get a (feasible) trajectory by means of a feedback law (which turns out to be a nonlinear projection operator). To find the (feasible) descent direction we take advantage of final-state constrained Linear Quadratic optimal control methods, while the second step is performed by suitably designing a constrained version of the trajectory tracking projection operator. The effectiveness of the proposed strategy is tested on the optimal state transfer of an inverted pendulum.
Statistics and characteristics of MgII absorbers along GRB lines of sight observed with VLT-UVES

We analyze the properties of Mg ii absorption systems detected along the sightlines toward GRBs using a sample of 10 GRB afterglow spectra obtained with VLT-UVES over the past six years. The signal-to-noise ratio is high enough that we can extend previous studies to smaller equivalent widths (typically Wr > 0.3 A). Over a pathlength of Δz ∼ 14, we detect 9 intervening Mg ii systems with Wr > 1 A and 9 weaker MgII systems (0.3 < Wr < 1.0 A) when about 4 and 7, respectively, are expected from observations of QSO sightlines. The number of weak absorbers is similar along GRB and QSO lines of sight, while the number of strong systems is higher along GRB lines of sight with a 2σ significance. Using intermediate and low-resolution observations reported in the literature, we increase the absorption length for strong systems to Δz = 31.5 (about twice the path length of previous studies) and find that the number density of strong Mg ii systems is a factor of 2.1 ± 0.6 higher (about 3σ significance) toward GRBs than towards QSOs, about twice less, however, than previously reported. We divide the sample into three redshift bins and find that the number density of strong Mg ii is greater in the low-redshift bins. We investigate in detail the properties of strong Mg ii systems observed with UVES, deriving an estimate of both the H i column density and the associated extinction. Both the estimated dust extinction in strong GRB Mg ii systems and the equivalent width distribution are consistent with what is observed for standard QSO systems. We also find that the number density of (sub)-DLAs per unit redshift in the UVES sample is probably twice more than what is expected from QSO sightlines, which confirms the peculiarity of GRB lines of sight. These results indicate that neither a dust extinction bias nor different beam sizes of the sources are viable explanations for the excess. It is still possible that the current sample of GRB lines of sight is biased by a subtle gravitational lensing effect. More data and larger samples are needed to test this hypothesis.
Factors manipulate ERP implementation: An experiential study from Pakistan

ERP (Enterprise Resource Planning) is a foremost improvement in the arena of organizational management and information system. ERP has the ability to integrate and assimilate the information in an efficient way. ERP is an utmost extensive business management system that presents real-time competences and flawless presentation of information for organizations and businesses. Nevertheless, not all the ERP implementation projects are successful. Implementation of ERP affects the overall processes of organizations. The organizations implementing ERP systems may face various challenges. The objective of this study is to identify the critical success factors of ERP implementation in Pakistani organizations using ERP systems. The study was conducted by developing a survey questionnaire. The questionnaires distributed among the ERP users of Pakistani organizations. For further analysis total 422 responded were. The study founds a significant association of technological, strategic, project management, people, top management support and communication factor with ERP implementation. The results of the study are beneficial to the ERP vendors and professionals to formulate particular strategies to overwhelm the misfit between ERP systems and organizations implementing ERP systems in developing countries like Pakistan. Additionally, the managers and organizations might increase their understanding regarding the complications essential in the ERP installation to evade hurdles and escalate the chances of ERP success.
Analysis of Heart Rate Variability by Applying Nonlinear Methods with Different Approaches for Graphical Representation of Results

There is an open discussion over nonlinear properties of the Heart Rate Variability (HRV) which takes place in most scientific studies nowadays. The HRV analysis is a non-invasive and effective tool that manages to reflect the autonomic nervous system regulation of the heart. The current study presents the results of HRV analysis based on 24-hour Holter ECG signals of healthy and unhealthy subjects. Analysis of heart intervals is performed with the use of original algorithms and software, developed by the authors, to quantify the irregularity of the heart rate. The main aim is the formation of the parametric estimate of patients’ health status, based on mathematical methods that are applied on cardiac physiology. The obtained results show that the analysis of Holter recordings by nonlinear methods may be appropriate for diagnostic, forecast and prevention of the pathological cardiac statuses. Different approaches of graphical representation and visualization of these results are used in order to verify this.
Study of Recent DDoS Attacks and Defense Evaluation Approaches

Distributed Denial of Service (DDoS) attacks is virulent, relatively new type of attacks on the availability of Internet services and resources. DDoS attackers infiltrate large number of computers by exploiting software vulnerabilities, to set up DDoS attack networks. DDoS attacks pose an immense threat to the Internet, therefore some defense systems are required to defend these attacks. In this paper, an overview of DDoS problem, brief detail of most recent DDoS incidents on online organizations is highlighted. Finally three approaches to evaluate DDoS defense systems i.e theory, simulation and emulation are discussed.
A 30.8-dBm Wideband CMOS Power Amplifier With Minimized Supply Fluctuation

A wideband design method for a twisted eight-shape transformer is introduced with the design guidelines. The supply modulation effect caused by the fluctuation of virtual ground is analyzed. To minimize the effect, the different matching capacitors are adopted at each port and an accurate virtual ground is positioned. For verification, a fully integrated linear CMOS power amplifier (PA) is implemented in a 0.18-μm standard 1P6M RF CMOS process for 2.3- and 2.6-GHz m-WiMAX (IEEE 802.16e standard) system. In continuous-wave measurements, the two-stage Class-AB PA delivers 30.8-dBm saturated power with a 30.6% power-added efficiency (PAE) and 22-dB gain across 900-MHz bandwidth (defined as 1-dB gain bandwidth). In 16 quadrature amplitude modulation m-WiMAX modulation signal measurements, the PA generates 26.2-dBm average power with a 20.5% PAE. The PA complies with the spectrum mask at a 21-dBm average power level and satisfies 3% error vector magnitude at 17-dBm average power.
Visual impairment in a visual medium: Perspectives of online learners with visual impairments

x Chapter 1: Introduction . 1 Overview . 1 Background . 1 Personal Disclosure . 4 Statement of the Problem . 5 Statement of the Purpose . 6 Research Question . 6 Methods Summary . 7 Significance of the Study . 8 Delimitations of the Study . 9 Definition of Terms. 10 Summary . 11 Chapter 2: Review of Literature . 12 Overview . 12 Online Distance Learning . 12 Learners with Disabilities . 18 Students with Visual Impairments and the Internet . 22 Conclusion . 25 Chapter 3: Methodology. 26 vi Overview . 26 Phenomenology. 26 Site and Sample Selection . 28 Data Collection Plan . 31 Validity and Rigor. 42 Data Analysis . 49 Timeline Summary . 51 Chapter 4: Findings . 53 Participant 1: Lydia . 62 Participant 2: Jane . 72 Participant 3: Moira . 81 Themes . 90 Summary . 106 Chapter 5: Implications and Discussion . 108 Introduction . 108 Summary of the Study . 108 How Findings Differ from Literature Review . 121 Delimitations and Limitations of the Study . 124 Implications. 125 Recommendations for Future Research . 144 Closing . 145 Appendix A: Documents in the Study . 158 Appendix B: Interview Guide . 162 Appendix C: Summary of Reviewer Experience . 165
Educational Data mining for Prediction of Student Performance Using Clustering Algorithms

: In recent years, the biggest challenges that educational institutions are facing the explosive growth of educational data and to use this data to improve the quality of managerial decisions. Educational institutions are playing an important role in our society and playing a vital role for growth and development of nation. Prediction of student’s performance in educational environments is also important as well. Student’s academic Education details & performance is based upon various factors like personal details, social, psychological etc. Educational database contain the useful information for predicting a students’ performance, rank factor & details. The data mining techniques are more helpful in classifying educational database. Educational data mining concerns with developing methods for discovering knowledge from data, that comes from educational institutions. The Data Mining prediction has allowed a decision making tool which can facilitate better resource utilization in terms of students performance. In our college, the student details have been taken for analysis and data mining methods have been employed to get vital information. The work aims to develop a trust model using data mining techniques which mines required information, so that the present education system may adopt this as a strategic management tool.
O R I G I N a L C O N T R I B U T I O N Open Access

The role of Ugandan District Hospital orthopedic units in the care of vulnerable road users: a cross-sectional study Abstract Background: Musculoskeletal injuries are a common cause of morbidity after road traffic injury (RTI) in motorizing countries. District hospitals provide front-line orthopedic care in Uganda and other sub-Saharan African nations. Improving care at the district hospital level is an important component of the World Health Organization's strategy for surgical and trauma systems strengthening, but the data necessary to inform RTI safety and care initiatives has previously been insufficient at the district hospital level. The objective of this study was to provide data on the patient population and patterns of musculoskeletal injury caused by RTI at Ugandan district hospitals. Methods: In this cross-sectional study, all patients with musculoskeletal injuries identified on x-ray presenting to three Ugandan district hospitals from October 2013 to January 2014 were interviewed and examined to obtain data on patient demographics and injury context by road user category. This manuscript is a subgroup analysis of RTI victims from a broader dataset of all musculoskeletal injuries.
Color Image Segmentation Using Soft Rough Fuzzy-c-means Clustering and Smo Support Vector Machine

Color Image segmentation splits an image into modules, with high correlation among objects contained in the image. Many color image segmentation algorithms in the literature, segment an image on the basis of color, texture and as a combination of both color and texture. In this paper, a color image segmentation algorithm is proposed by extracting both texture and color features and applying them to the Sequential Minimal Optimization-Support Vector Machine (SMO-SVM) classifier for segmentation. Gabor filter decomposition is used for extracting the textural features and homogeneity model is used for obtaining the color features. The SMO-SVM is trained using the samples obtained from Soft Rough Fuzzy-C-Means (SRFCM) clustering. Fuzzy set based membership functions efficiently handle the problem of overlapping clusters. The lower and upper approximation concepts of rough sets effectively deal with uncertainty, vagueness, and incompleteness in data. Parameterization tools are not necessary in defining Soft set theory. The goodness aspects of soft sets, rough sets and fuzzy sets are integrated in the proposed algorithm to achieve improved segmentation performance. The proposed algorithm is comparable and achieved better performance compared with the state of the art algorithms found in the literature.
Straight outta K-1: An autoethnographic analysis of a Black male teacher's experience employing Hip Hop in a kindergarten-first grade classroom

dfdgfgfdf Abstract This study analyzed the learning outcomes of a Black male kindergarten-first grade teacher's usage of Hip Hop as an instructional approach using autoethnography as a method. The primary research question that guided this work was, " What can I learn from an examination of the experiences of Black male kindergarten/first grade teacher and students from a retroactive examination of the use of Hip Hop Pedagogy in a kindergarten/first grade classroom of African American children? Data sources for this study included of artifacts (electronic classroom portfolios, videos of classroom instruction, archived teaching evaluations, parents' e-mails, student assessments, correspondence from administrators, lesson plans and reflective notes) amassed over the course of one full year (including summer school). Data were analyzed using open and thematic coding. Major themes were then used to create three vignettes which captured the findings of the study. I triangulated data (Patton, 2002) to enhance the fidelity and trustworthiness of my study using two kinds of data: (1) personal memories/self-observational/self-reflective data and (2) external data 1 (archived teaching evaluations, parents' emails). Findings showed that my conceptions of hip hop pedagogy evolved over the school year as I learned to position myself as a learner and to learn from students. I learned that I did not have to be the only person to perform hip hop and that students could lead the process, while also addressing learning outcomes of the curriculum. Culturally relevant pedagogical dimensions were evident in my use of hip hop pedagogy (e.g., conceptions of self and others, conceptions of knowledge, and social relations). Although educators can extrapolate from the body of literature in secondary settings and make adaptations for preschool and elementary school children, this research addressed the need to study K-3 classrooms that use Hip Hop pedagogy by examining the effectiveness, barriers, challenges, and insufficiencies of strategies and processes used to integrate Hip Hop pedagogy in a K-1 classroom. The findings of the study may be useful for: (a) understanding how Hip Hop and rap are defined in the context of k-3 classroom settings; (b) further understanding the literacies that children already possess from their communities; (c) acquiring more knowledge about young children's identities and its relationship to Hip Hop culture; (d) identifying the impact that Hip Hop culture (including mainstream aspects and music corporations) has on children that may emerge in the classroom; and (e) exploring the impact of teacher identity on instruction.
New dynamical models of lead-acid batteries

This paper documents the main results of studies that have been carried out, during a period of more than a decade, at University of Pisa in co-operation with other technical Italian institutions, about models of electrochemical batteries suitable for the use of the electrical engineer, in particular for the analysis of electrical systems with batteries. The problem of simulating electrochemical batteries by means of equivalent electric circuits is defined in a general way; then particular attention is then devoted to the problem of modeling of lead-acid batteries. For this kind of battery, a general model structure is defined from which specific models can be inferred, having different degrees of complexity and simulation quality. In particular, the implementation of the third-order model, that shows a good compromise between complexity and precision, is developed in detail. The behavior of the proposed models is compared with results obtained with extensive lab tests on different types of lead-acid batteries.
Current Concept of Stem Cell Therapy for Spinal Cord Injury: A Review

Spinal cord injury (SCI) is a catastrophic condition associated with significant neurological deficit, social, and financial burdens. Over the past decades, various treatments including medication, surgery, and rehabilitation therapy for SCI have been performed, but there were no definite treatment option to improve neurological function of patients with chronic SCI. Therefore, new treatment trials with stem cells have been studied to regenerate injured spinal cord. Among various types of stem cells, bone marrow derived mesenchymal stem cells is highly expected as candidates for the stem cell therapy. The result of the current research showed that direct intramedullary injection to the injured spinal cord site in subacute phase is most effective. Neurological examination, electrophysiologic studies, and magnetic resonance imaging are commonly used to assess the effectiveness of treatment. Diffusion tensor imaging visualizing white matter tract can be also alternative option to identify neuronal regeneration. Despite various challenging issues, stem cell therapy will open new perspectives for SCI treatment.
Classifying human-robot interaction: an updated taxonomy

This paper extends taxonomy of human-robot interaction (HRI) introduced in 2002 to include additional categories as well as updates to the categories from the original taxonomy. New classifications include measures of the social nature of the task (human interaction roles and human-robot physical proximity), task type, and robot morphology.
High Ion/Ioff current ratio graphene field effect transistor: the role of line defect

The present paper casts light upon the performance of an armchair graphene nanoribbon (AGNR) field effect transistor in the presence of one-dimensional topological defects. The defects containing 5–8–5 sp2-hybridized carbon rings were placed in a perfect graphene sheet. The atomic scale behavior of the transistor was investigated in the non-equilibrium Green's function (NEGF) and tight-binding Hamiltonian frameworks. AGNRFET basic terms such as the on/off current, transconductance and subthreshold swing were investigated along with the extended line defect (ELD). The results indicated that the presence of ELDs had a significant effect on the parameters of the GNRFET. Compared to conventional transistors, the increase of the Ion/Ioff ratio in graphene transistors with ELDs enhances their applicability in digital devices.