Miracle-dz/UniFAR-FTUs huggingface dataset:
The Assessment of Trainee Teachers: An Ethnography.

Dominant discourses of quality assurance in UK higher education posit assessment as a transparent and rigorous process through the ascription of the two key and inter-related concepts of validity and reliability. Drawing on ethnographic research into the assessment procedures and practices of one teacher-training course in England (a part-time course for teachers in the learning and skills sector which is delivered on a franchise basis across a network of further education colleges), this thesis demonstrates that claims to assessment validity and reliability are contestable. The thesis draws on three complementary social practice theories (communities of practice, new literacy studies and actor-network theory) in order to reveal assessment as being a complex, localised practice characterised by contingency and improvisatory behaviours on the part of both tutors and students, mediated by a variety of genres of textual artefacts. These divergent and complex practices are shown to disrupt dominant managerialist discourses of assessment practice in higher education. They are also shown to disrupt dominant definitions of learning, teaching and assessment in higher education, which predominantly rest on models of individual cognition and transferable skills, and which this thesis critiques through the use of social practice accounts of learning within communities of practice. The thesis demonstrates that assessment is more contingent and complex than dominant discourses of assessment practice in HE allow, thereby problematising claims to reliability and validity. The thesis makes contributions to current literature and research in two ways. Firstly, it concludes by offering a series of suggestions as to how assessment validity and reliability might be enhanced or reframed. Secondly, it demonstrates how communities of practice theory can be used critically to explore pedagogic activity, including assessment, within formal educational settings.
Detecting Salient Events in Large Corpora by a Combination of NLP and Data Mining Techniques

In this paper, we present a framework and a system that extracts "salient" events relevant to a query from a large collection of documents, and which also enables events to be placed along a timeline. Each event is represented by a sentence extracted from the collection. We have conducted some experiments showing the interest of the method for this issue. Our method is based on a combination of linguistic modeling (concerning temporal adverbial meanings), symbolic natural language processing techniques (using cascades of morpho-lexical transducers) and data mining techniques (namely, sequential pattern mining under constraints). The system was applied to a corpus of newswires in French provided by the Agence France Presse (AFP). Evaluation was performed in partnership with French newswire agency journalists.
Is bursectomy necessary for patients with gastric cancer invading the serosa?

BACKGROUND/AIMS To confirm the impact of bursectomy on survival, we reviewed the clinical records of patients who underwent radical total gastrectomy with bursectomy for gastric cancer invading the serosa, with special reference to the location of tumor invasion. METHODOLOGY From the records, patients were selected for this retrospective cohort study according to the following criteria: (a) Invasion beyond the serosal surface, (b) No metastases to liver, peritoneum, or distant organs, (c) Negative for peritoneal lavage cytology, and (d) Patients underwent curative D2 total gastrectomy with complete omental bursectomy. A total of 134 patients were eligible. These patients were divided into a group I which included patients with tumors that invaded only the posterior wall and a group II which included those with others. Survival was examined by uni- and multivariate analyses. RESULTS Survival rates at 3 and 5 years were 67.3% and 53.0% for group I and 68.8% and 53.8% for group II. There was no significant difference in the survival between the two groups (p=0.969), even if survival was stratified by various clinicopathological factors. Multivariate analyses demonstrated that the significant independent factors for the survival were macroscopic type and lymph node metastasis. Location of the invasion was not a significant factor. CONCLUSIONS These results suggested that bursectomy did not inhibit the spreading of tumor cells into the retro-stomach space. There might be no survival benefit of bursectomy in patients with gastric cancer.
A scalable pipelined complex valued matrix inversion architecture

This paper presents a fast, pipelined and scalable hardware architecture for inverting complex valued matrices. The matrix inversion algorithm involves, a QR-factorization based on the squared Givens rotations algorithm, the application of a recurrence algorithm for inversion of an upper triangular matrix R, and a matrix multiplication of R/sup -1/ with Q. We show that traditional triangular array architectures employing O(n/sup 2/) communicating processors can be mapped onto a scalable linear array architecture with only O(n) processors. The linear array architecture avoids drawbacks such as non-scalability, large area consumption and low throughput rate. The architecture is implemented using arithmetic operations with 12 bit fixed-point representation. The hardware implementation will be used as a core processor in a real-time smart antenna system.
High Intensity Exercise: Can It Protect You from A Fast Food Diet?

The purpose of this study was to assess the ability of high intensity exercise to counteract the deleterious effects of a fast food diet on the cardiometabolic profile of young healthy men. Fifteen men were subjected to an exclusive fast food diet from a popular fast food restaurant chain (three extra value meals/day + optional snack) for 14 consecutive days. Simultaneously, participants were asked to perform each day high intensity interval training (HIIT) (15 × 60 sec sprint intervals (~90% of maximal heart rate)) on a treadmill. Fast food diet and energy expenditure profiles of the participants during the intervention were assessed as well as body composition (DXA), cardiometabolic profile (lipid, hepatic enzymes, glycated hemoglobin, glucose, insulin, hsC-reactive protein (hsCRP) and blood pressure) and estimated maximal oxygen consumption (VO2 max) pre- and post-experiment. We found significant improvements for fat mass, lean body mass, estimated VO2 max, fasting glucose, serum lipoprotein(a) and hsCRP after the intervention (p < 0.05). HDL-cholesterol significantly decreased (p < 0.002), but the triglycerides/HDL-cholesterol ratio did not change. All other cardiometabolic variables measured remained stable, which includes the primary outcome: the HOMA index (pre: 1.83 ± 1.2 vs. post: 1.54 ± 0.7 values; p = 0.35). In conclusion, in large part, insulin resistance and the cardiometabolic profile of young healthy individuals seems to be protected by HIIT from a fast food diet.
A Serum MicroRNA Signature Predicts Tumor Relapse and Survival in Triple-Negative Breast Cancer Patients

Purpose: Triple-negative breast cancers (TNBC) are associated with high risk of early tumor recurrence and poor outcome. Common prognostic biomarkers give very restricted predictive information of tumor recurrences in TNBC. Human serum contains stably expressed microRNAs (miRNAs), which have been discovered to predict prognosis in patients with cancer. The purpose of this study was to identify circulating biomarkers able to predict clinical outcome in TNBC. Experimental Design: We performed genome-wide serum miRNA expression and real-time PCR analyses to investigate the ability of miRNAs in predicting tumor relapse in serum samples from 60 primary TNBC. Patients were divided into training and testing cohorts. Results: By Cox regression analysis, we identified a four-miRNA signature (miR-18b, miR-103, miR-107, and miR-652) that predicted tumor relapse and overall survival. This miRNA signature was further validated in an independent cohort of 70 TNBC. A high-risk signature score was developed and significantly associated with tumor recurrence and reduced survival. Multivariate Cox regression models indicated that the risk score based on the four-miRNA signature was an independent prognostic classifier of patients with TNBC. Conclusions: This signature may serve as a minimally invasive predictor of tumor relapse and overall survival for patients with TNBC. This prediction model may ultimately lead to better treatment options for patients with TNBC. Clin Cancer Res; 21(5); 1207–14. ©2014 AACR.
Influence of the serotonin transporter promoter gene polymorphism on susceptibility to posttraumatic stress disorder

Posttraumatic stress disorder (PTSD) is a prevalent anxiety disorder marked by behavioral, physiologic, and hormonal alterations. The etiology of PTSD is unknown, although exposure to a traumatic event constitutes a necessary, but not sufficient, factor. Serotonergic dysfunction has been implicated in PTSD. The present study examined the possible association between the serotonin‐transporter‐linked polymorphic region (SERTPR) and PTSD. The genotype and allele frequencies of the SERTPR were analyzed in 100 PTSD patients and 197 unrelated healthy controls using a case–control design. The frequency of the s/s genotype was significantly higher in PTSD patients than in normal controls. These findings suggest that the SERTPR s/s genotype is one of the genetic factors for the susceptibility to PTSD. Further investigations are required into the influence of gene polymorphisms on the biological mechanisms of PTSD, its clinical expression, and its response to treatment. Depression and Anxiety 00:1–5, 2005. © 2005 Wiley‐Liss, Inc.
Machine-Learning Aided Optimal Customer Decisions for an Interactive Smart Grid

In this paper, a hierarchical smart grid architecture is presented. The concept of smart home is extended in two aspects: 1) from traditional households with smart devices, such as advanced metering infrastructure, to intelligent entities with instantaneous and distributive decision-making capabilities; and 2) from individual households to general customer units of possibly large scales. We then develop a hidden mode Markov decision process (HM-MDP) model for a customer real-time decision-making problem. This real-time decision-making framework can effectively be integrated with demand response schemes, which are prediction based and therefore inevitably lead to real-time power-load mismatches. With the Baum-Welch algorithm adopted to learn the nonstationary dynamics of the environment, we propose a value iteration (VI)-based exact solution algorithm for the HM-MDP problem. Unlike conventional VI, the concept of parsimonious sets is used to enable a finite representation of the optimal value function. Instead of iterating the value function in each time step, we iterate the representational parsimonious sets by using the incremental pruning algorithm. Although this exact algorithm leads to optimal policies giving maximum rewards for the smart homes, its complexity suffers from the curse of dimensionality. To obtain a low-complexity real-time algorithm that allows adaptively incorporating new observations as the environment changes, we resort to Q-learning-based approximate dynamic programming. Q-learning offers more flexibility in practice because it does not require specific starting and ending points of the scheduling period. Performance analysis of both exact and approximate algorithms, as compared with the other possible alternative decision-making strategies, is presented in simulation results.
BCL2A1a Over-Expression in Murine Hematopoietic Stem and Progenitor Cells Decreases Apoptosis and Results in Hematopoietic Transformation

We previously reported the development of a lethal myeloid sarcoma in a non-human primate model utilizing retroviral vectors to genetically modify hematopoietic stem and progenitor cells. This leukemia was characterized by insertion of the vector provirus into the BCL2A1 gene, with resultant BCL2A1 over-expression. There is little information on the role of this anti-apoptotic member of the BCL2 family in hematopoiesis or leukemia induction. Therefore we studied the impact of Bcl2a1a lentiviral over-expression on murine hematopoietic stem and progenitor cells. We demonstrated the anti-apoptotic function of this protein in hematopoietic cells, but did not detect any impact of Bcl2a1a on in vitro cell growth or cell cycle kinetics. In vivo, we showed a higher propensity of HSCs over-expressing Bcl2a1a to engraft and contribute to hematopoiesis. Mice over-expressing Bcl2a1a in the hematologic compartment eventually developed an aggressive malignant disease characterized as a leukemia/lymphoma of B-cell origin. Secondary transplants carried out to investigate the primitive origin of the disease revealed the leukemia was transplantable. Thus, Bcl2a1 should be considered as a proto-oncogene with a potential role in both lymphoid and myeloid leukemogenesis, and a concerning site for insertional activation by integrating retroviral vectors utilized in hematopoietic stem cell gene therapy.
NGF rescues hippocampal cholinergic neuronal markers, restores neurogenesis, and improves the spatial working memory in a mouse model of Huntington's Disease.

BACKGROUND Recent studies in Huntington's disease (HD) mouse models and patients suggest that hippocampal neurons and their cholinergic afferents are involved in the cognitive deficits seen in the disease. Nerve growth factor (NGF) is an essential regulator of cholinergic neuronal survival and neurotransmission. OBJECTIVE We asked whether NGF might be involved in HD and if intra-cerebroventricular infusion of NGF can rescue hippocampal cholinergic neuronal markers, restore neurogenesis, and improve the spatial working memory in R6/1 mouse model of HD. METHODS We quantified NGF protein level by enzyme-linked immunosorbent assay (ELISA), intracerebroventricularly infused NGF, assessed cholinergic neuronal markers by Western blotting and quantitative RT-PCR, evaluated neurogenesis by immunohistochemistry, and studied spatial working memory using radial maze. RESULTS By quantifying NGF protein in the hippocampus of the R6/1 mice at different ages, we found progressive decreases in NGF protein levels. We then increased NGF levels in the R6/1 mice through intra-cerebroventricular infusion. We observed elevations of the cholinergic neurochemical markers vesicular acetylcholine transporter (VAChT) and choline acetyltransferase (ChAT) in the hippocampus and in the septal region, which contain the cell bodies of basal forebrain cholinergic neurons (BFCNs), but not in the striatum that harbors cholinergic interneurons. Finally, we found that NGF infusion also restored hippocampal neurogenesis and improved spatial working memory. CONCLUSIONS Our results suggest that intracerebral injections of NGF might be a valuable therapy against cognitive symptoms in HD and should be further studied in HD animal models and patients.
Maximum Fuzzy Entropy and Immune Clone Selection Algorithm for Image Segmentation

This paper is concerned with fuzzy entropy definition used for image segmentation. The key problem associated with this method is to find the optimal parameter combination of membership function so that an image can be transformed into fuzzy domain with maximum fuzzy entropy. An improved immune clone selection algorithm (ICSA) is proposed to search the optimal parameter combination. Then, we compare the proposed ICSA with other artificial intelligence models. The experiment indicates that the proposed method is quite effective and ubiquitous.
Deep dyspareunia and sex life after laparoscopic excision of endometriosis.

BACKGROUND Among subjects with endometriosis and deep dyspareunia (DD), those with endometriosis of the uterosacral ligament (USLE) have the most severe impairment of sexual function. This study examines the effect of laparoscopic excision of endometriosis on DD and quality of sex life. METHODS This observational cohort prospective study included 68 women with endometriosis suffering DD (intensity of pain >or= 6 on a 10-cm visual analogue scale). Patients underwent laparoscopic full excision of endometriosis. Following surgery, they were asked to use nonhormonal contraception devices. Before surgery, at 6- and at 12-month follow-up, patients answered a self-administered questionnaire based on the Sexual Satisfaction Subscale of the Derogatis Sexual Functioning Inventory. RESULTS At 6- and 12-month follow-up, women with and without USLE had significant improvement in DD. Subjects with USLE reported increased variety in sex life, increased frequency of intercourse, more satisfying orgasms with sex, relaxing more easily during sex and being more relaxed and fulfilled after sex. Similar improvements were observed among women without USLE; however, for some variables statistical significance was not reached. CONCLUSIONS Surgical excision of endometriosis improves not only DD but also the quality of sex life.
Multiple bifurcation Analysis in a Neural Network Model with Delays

A synchronized neural network model with delays is considered. The bifurcations arising from the zero root of the corresponding characteristic equation have been studied by employing the center manifold theorem, normal form method and bifurcation theory. It is shown that the system may exhibit transcritical/pitchfork bifurcation, or Bogdanov–Takens bifurcation. Some numerical simulation examples are given to justify the theoretical results.
CBR as a Framework for Design : Augmenting CBR with other AI techniques

Design is an activity in which the role of experience plays a larger part in the generation of alternative designs than theoretical or formal knowledge. This has lead to increasing interest in CBR as a way of assisting and/or automating portions of the design process. However, there are major areas in the CBR paradigm that do not address the needs of practical CBR. Here CBR is presented as a framework for design, with other AI techniques supporting different aspects of CBR. Specifically, knowledge discovery is used to assist in the development of CBR knowledge and genetic algorithms in the generation of design solutions. design profession rarely accounts for the design process, but rather records the design experience as documented projects. Therefore, we consider CBR as an overall framework for intelligent design support and look at how other AI techniques fit in that framework. Case-Based Reasoning (CBR) is a reasoning paradigm used in Artificial Intelligence that uses knowledge in the form of previous experiences as the basis for solving new problems. The main "reasoning cycle" employed by a CBR framework for design is shown in Figure 1.
Acana Supplementary Materials Gotoh Algorithm

Gotoh Algorithm essentially extends the Needleman-Wunsch algorithm and the Smith-Waterman algorithm to enable them working efficiently with the affine gap cost model. In the affine gap cost model, the penalty for a gap segment is calculated by a linear function of the gap segment length. Supposing a BLOSUM scoring matrix is used for aligning a pair of sequences A and B of length m and n, respectively. The Gotoh improved Needleman-Wunsch algorithm for a optimally global alignment can be summarized by the following recursion relations:
Letter by Ciliberti and Capucci Regarding Article, "Medical Therapy for Secondary Prevention and Long-Term Outcome in Patients With Myocardial Infarction With Nonobstructive Coronary Artery Disease".

We have read “Medical Therapy for Secondary Prevention and Long-Term Outcome in Patients With Myocardial Infarction With Nonobstructive Coronary Artery Disease” by Lindahl and colleagues with great interest, and congratulate the authors for their accurate analysis of this large population of patients with myocardial infarction with nonobstructive coronary arteries (MINOCA). 1 They retrospectively selected patients with MINOCA from the SWEDEHEART registry (the Swedish Web-system for Enhancement and Development of Evidence-based Care in Heart Disease Evaluated According to Recommended Therapies) thus obtaining a prevalence of 8.0%. For the first time, they clearly demonstrated an improvement in the prognosis of this population over …
Attacking the kad network - real world evaluation and high fidelity simulation using DVN

Summary The Kad network, an implementation of the Kademlia DHT protocol, supports the popular eDonkey peer-to-peer file sharing network and has over 1 million concurrent nodes. We describe several attacks that exploit critical design weaknesses in Kad to allow an attacker with modest resources to cause a significant fraction of all searches to fail. We measure the cost and effectiveness of these attacks against a set of 16 000 nodes connected to the operational Kad network. Using our large-scale simulator, DVN, we successfully scaled up to a 200 000 node experiment. We also measure the cost of previously proposed, generic DHT attacks against the Kad network and find that our attacks are much more cost effective. Finally, we introduce and evaluate simple mechanisms to significantly increase the cost of these attacks. Copyright © 2009 John Wiley & Sons, Ltd.
STABLE CARBON ISOTOPE STUDY OF THE PRAIRIE-FOREST TRANSITION SOIL IN LOUISIANA 1

The calcareous prairies of Louisiana are among the most endangered and the least understood ecosystems in North America. The major threat to this ecosystem is the invasion of woody plants, primarily eastern red cedar (Juniperus virginiana L.). We studied the vertical profile of soil organic C (SOC) and the stable carbon isotope (δ13C) from soil organic matter (SOM) to infer the vegetation history and to understand the C dynamics of these prairies. SOC decreased with depth (0–100 cm), but variation due to vegetation type (prairie, transition, forest) and landscape position were not statistically significant. The mean total SOC stock within the 0–30 cm depth from three sites, three vegetation types, and two landscape positions was 7.6 ± 0.4 kg/m2 (mean ± SE, n = 18). The SOM δ13C values within the 0–10 cm depth showed that although the forest vegetation was exclusively C3, the transition and the prairie vegetation were composed of a mixture of C3 and C4 plant functional forms. Statistical comparison of SOM δ13C values from the forest, transition, and prairie with depth showed that the SOM δ13C from the prairie and transition are significantly different from that of the forest up to the 30–40 cm depth. SOM δ13C values of the prairie and transition were not significantly different at all depths, suggesting that the invasion of C3 trees and shrubs observed within the transition may be a recent phenomenon coinciding with fire suppression. SOM δ13C below 30–40 cm indicated that in the past, a C4 community might have dominated the entire site.
Microtubules: The neuronic system of the neurons?

In this talk we review recent work on integrable models for Microtubule (MT) networks, subneural paracrystalline cytosceletal structures, which seem to play a fundamental role in the neurons. We cast here the complicated MT dynamics in the form of a 1+1-dimensional non-critical string theory, which can be formulated in terms of (dual) Dirichlet branes, according to modern perspectives. We suggest that the MTs are the microsites in the brain, for the emergence of stable, macroscopic quantum coherent states, identifiable with the ``preconscious states''. Quantum space-time effects, as described by non-critical string theory, trigger then an ``organized collapse'' of the coherent states down to a specific or ``conscious state''. The whole process we estimate to take O(1 sec), in excellent agreement with a plethora of experimental/observational findings. The complete integrability of the stringy model for MT proves sufficient in providing a satisfactory solution to memory coding and capacity. Such features might turn out to be important for a model of the brain as a quantum computer.