Miracle-dz/UniFAR-FTUs huggingface dataset:
Coupling Web Usage Mining with Content Mining for Recommendation Systems

In this paper, we introduce a novel approach for combining web usage mining and content mining. The approach is based on generating recommendations that take into consideration users' navigation history as well as contents of pages visited. The integration of usage and content data can be performed at the offline phase or at the online phase of the recommendation system. The former is referred to as pre-mining integration; while the latter is called post-mining integration. The current work is concerned with pre-mining integration. The main rationales of the combination are to improve the quality of recommendations generated; overcome the new item problem and to improve the clustering of users’ navigation patterns. In our experiments, the quality of clustering of user sessions is improved by 35% when compared with quality of clusters generated using usage patterns only. Also, the recommendations generated using the proposed approach are improved by 24% and 8% for the recall and precision respectively and when compared with recall and precision obtained by using usage data only.
An in vitro priming step increases the expression of numerous epidermal growth and migration mediators in a tissue‐engineering construct

An FDA‐approved, prototypic, living, bilayered skin construct (BSC) has been used for non‐healing wounds. Using this particular construct as proof of principle, we hypothesized that an in vitro ‘priming’ step may enhance its repertoire of expression of key mediators and genes. The priming step used here was incubation in Dulbecco's modified Eagle's medium (DMEM) for 24 h at 37°C and 5% CO2, with or without construct meshing. Microarray and ingenuity pathway analysis (IPA) showed that >1000 genes were overexpressed by the priming step, including interleukin 6 (IL‐6), which plays important roles in wound healing. Genes highly overexpressed by priming were those involved in epidermal proliferation and migration. Quantitative real‐time PCR (qRT–PCR), immunostaining and western blots verified the results. An epiboly assay (epidermal migration over dermis) showed that BSC epiboly was inhibited by IL‐6 neutralizing antibody. Back wounds of nude mice were treated with primed or control BSCs for 3 days prior to harvesting; primed BSCs showed a significantly (p = 0.006) greater level of epidermal migration vs unprimed. Our study demonstrates that an in vitro priming step induces wound healing‐related genes in the BSC, leading to a construct that could prove more effective in stimulating wound healing. Copyright © 2014 John Wiley & Sons, Ltd.
Transfer of Standards-Based Education in Rural Alaska: An Analysis of the Politics of Educational Transfer in the Tikishla School District

This article examines the politics of educational transfer in a rural Alaskan school district with schools in two Alaska Native villages and one non-Native community. The author examines why and how the district imported standards-based education. While the district presented its reform as a rational, consensus-driven policy process, this conventional version of the reform was disrupted by the superintendent's utilization of political strategies that promoted his personal agenda.
Technological determinism in educational technology research: some alternative ways of thinking about the relationship between learning and technology

This paper argues that research on the educational uses of technology frequently overemphasizes the influence of technology. Research in the field is considered a form of critical perspective, and assumptions about technology are questioned. Technological determinism is introduced, and different positions on this concept are identified. These are used to discuss the ways in which work within the field might be described as technologically deterministic. Four theoretical perspectives (activity theory, communities of practice, actor–network theory, and the social construction of technology) are then briefly characterized, demonstrating that alternative positions are viable, and positioning each in relation to the earlier discussion of technological determinism. The paper concludes by arguing that research, building on such alternative conceptions of technology, is important in developing our understanding of the relationship between technology and learning, as well as identifying potential methodological implications.
Handling imprecision in inputs using fuzzy logic to predict effort in software development

Accurate, precise and reliable estimates of effort at early stages of project development holds great significance for the industry to meet the competitive demands of today's world. The inherent imprecision present in the inputs of the algorithmic models like Constructive Cost Model (COCOMO) yields imprecision in the output, resulting in erroneous effort estimation. The development of software is characterized by parameters that possess certain level of fuzziness which requires that some degree of uncertainty be introduced in the models, in order to make the models realistic. Fuzzy logic based cost estimation models enable linguistic representation of the input and output of a model to address the vagueness and imprecision in the inputs, to make reliable and accurate estimates of effort. In this paper, we present an enhanced fuzzy logic based framework for software development effort prediction. The intermediate COCOMO is extended in the proposed study by incorporating the concept of fuzziness into the measurements of size, mode of development for projects and the cost drivers contributing to the overall development effort. The said framework tolerates imprecision, incorporates experts knowledge, explains prediction rationale through rules, offers transparency in the prediction system, and could adapt to changing environments with the availability of new data.
Adiponectin supplementation in pregnant mice prevents the adverse effects of maternal obesity on placental function and fetal growth

Significance Obesity and metabolic syndrome may, in part, originate in fetal life. In particular, babies of mothers with obesity and/or gestational diabetes mellitus (GDM) are often large at birth and have increased adiposity, which predisposes them to the development of metabolic disease later in life. Maternal obesity and GDM are typically associated with low circulating levels of adiponectin (ADN), and we found that ADN supplementation to pregnant obese mice completely normalized the changes in placental function and prevented fetal overgrowth caused by maternal obesity. These findings suggest that strategies to increase ADN levels in maternal obesity and GDM may alleviate the adverse effects of these pregnancy complications on the fetus. Mothers with obesity or gestational diabetes mellitus have low circulating levels of adiponectin (ADN) and frequently deliver large babies with increased fat mass, who are susceptible to perinatal complications and to development of metabolic syndrome later in life. It is currently unknown if the inverse correlation between maternal ADN and fetal growth reflects a cause-and-effect relationship. We tested the hypothesis that ADN supplementation in obese pregnant dams improves maternal insulin sensitivity, restores normal placental insulin/mechanistic target of rapamycin complex 1 (mTORC1) signaling and nutrient transport, and prevents fetal overgrowth. Compared with dams on a control diet, female C57BL/6J mice fed an obesogenic diet before mating and throughout gestation had increased fasting serum leptin, insulin, and C-peptide, and reduced high-molecular-weight ADN at embryonic day (E) 18.5. Placental insulin and mTORC1 signaling was activated, peroxisome proliferator-activated receptor-α (PPARα) phosphorylation was reduced, placental transport of glucose and amino acids in vivo was increased, and fetal weights were 29% higher in obese dams. Maternal ADN infusion in obese dams from E14.5 to E18.5 normalized maternal insulin sensitivity, placental insulin/mTORC1 and PPARα signaling, nutrient transport, and fetal growth without affecting maternal fat mass. Using a mouse model with striking similarities to obese pregnant women, we demonstrate that ADN functions as an endocrine link between maternal adipose tissue and fetal growth by regulating placental function. Importantly, maternal ADN supplementation reversed the adverse effects of maternal obesity on placental function and fetal growth. Improving maternal ADN levels may serve as an effective intervention strategy to prevent fetal overgrowth caused by maternal obesity.
Bone age assessment by dual-energy X-ray absorptiometry in children: an alternative for X-ray?

OBJECTIVE The aim of the study was to validate dual-energy X-ray absorptiometry (DXA) as a method to assess bone age in children. METHODS Paired dual-energy X-ray absorptiometry (DXA) scans and X-rays of the left hand were performed in 95 children who attended the paediatric endocrinology outpatient clinic of University Hospital Rotterdam, the Netherlands. We compared bone age assessments by DXA scan with those performed by X-ray. Bone age assessment was performed by two blinded observers according to the reference method of Greulich and Pyle. Intra-observer and interobserver reproducibility were investigated using the intraclass correlation coefficient (ICC), and agreement was tested using Bland and Altman plots. RESULTS The intra-observer ICCs for both observers were 0.997 and 0.991 for X-ray and 0.993 and 0.987 for DXA assessments. The interobserver ICC was 0.993 and 0.991 for X-ray and DXA assessments, respectively. The mean difference between bone age assessed by X-ray and DXA was 0.11 years. The limits of agreement ranged from -0.82 to 1.05 years, which means that 95% of all differences between the methods were covered by this range. CONCLUSIONS Results of bone age assessment by DXA scan are similar to those obtained by X-ray. The DXA method seems to be an alternative for assessing bone age in a paediatric hospital-based population.
The developmental sequence of gene expression within the rod photoreceptor lineage in embryonic zebrafish

In postembryonic zebrafish, rod photoreceptors are continuously generated from progenitors in the inner nuclear layer, which are derived from radial Müller glia that express the transcription factor pax6. We used BrdU incorporation, in combination with in situ hybridization for cell‐specific transcription factors, to establish the patterns of gene expression during rod lineage maturation in the embryonic zebrafish. Downregulation of pax6 expression was accompanied by sporadic upregulation of expression of the transcription factors NeuroD/nrd, rx1, crx, and Nr2e3/pnr. As cells of the rod lineage entered the outer nuclear layer, they became homogeneous, coordinately expressing NeuroD, rx1, crx, and Nr2e3. Postmitotic, maturing rods also expressed nrl, rod opsin, and rod transducin/gnat1. The presence of rx1 within the rod lineage and in maturing rods indicates that rx1 is not cone‐specific, as previously reported, and suggests a high degree of molecular similarity between rod and cone progenitor populations in the zebrafish. Developmental Dynamics 237:2903–1917, 2008. © 2008 Wiley‐Liss, Inc.
Diphtheria toxin entry into cells is facilitated by low pH

At neutral pH, NH4Cl and chloroquine protected cells against diphtheria toxin. A brief exposure of the cells to low pH (4.5-5.5) at 37 degrees completely abolished this protection. When, to cells preincubated with diphtheria toxin and NH4Cl, neutralizing amounts of anti-diphtheria toxin were added before the pH was lowered, the toxic effect was considerably reduced, but it was not completely abolished. A much stronger toxic effect was seen when antibodies were added immediately after incubation at low pH. Upon a short incubation with diphtheria toxin at low pH, the rate of protein synthesis in the cells decreased much faster than when the normal pH was maintained. The data suggest that, at low pH, diphtheria toxin (or its A fragment) penetrates directly through the surface membrane of the cell. The possibility is discussed that, when the medium has a neutral pH, the entry of diphtheria toxin involves adsorptive endocytosis and reduction of the pH in the vesicles possibly by fusion with lysosomes. Low pH did not facilitate the entry of the closely related toxins abrin, ricin, and modeccin.
Discriminative models for spoken language understanding

This paper studies several discriminative models for spoken language understanding (SLU). While all of them fall into the conditional model framework, different optimization criteria lead to conditional random fields, perceptron, minimum classification error and large margin models. The paper discusses the relationship amongst these models and compares them in terms of accuracy, training speed and robustness.
Effects of Sevoflurane, Propofol, and Adjunct Nitrous Oxide on Regional Cerebral Blood Flow, Oxygen Consumption, and Blood Volume in Humans

Background Anesthetic agents, especially volatile anesthetics and nitrous oxide (N2O), are suspected to perturb cerebral homeostasis and vascular reactivity. The authors quantified the effects of sevoflurane and propofol as sole anesthetics and in combination with N2O on regional cerebral blood flow (rCBF), metabolic rate of oxygen (rCMRO2), and blood volume (rCBV) in the living human brain using positron emission tomography. Methods 15O-labeled water, oxygen, and carbon monoxide were used as positron emission tomography tracers to determine rCBF, rCMRO2 and rCBV, respectively, in eight healthy male subjects during the awake state (baseline) and at four different anesthetic regimens: (1) sevoflurane alone, (2) sevoflurane plus 70% N2O (S+N), (3) propofol alone, and (4) propofol plus 70% N2O (P+N). Sevoflurane and propofol were titrated to keep a constant hypnotic depth (Bispectral Index 40) throughout anesthesia. End-tidal carbon dioxide was strictly kept at preinduction level. Results The mean ± SD end-tidal concentration of sevoflurane was 1.5 ± 0.3% during sevoflurane alone and 1.2 ± 0.3% during S+N (P < 0.001). The measured propofol concentration was 3.7 ± 0.7 &mgr;g/ml during propofol alone and 3.5 ± 0.7 &mgr;g/ml during P+N (not significant). Sevoflurane alone decreased rCBF in some (to 73–80% of baseline, P < 0.01), and propofol in all brain structures (to 53–70%, P < 0.001). Only propofol reduced also rCBV (in the cortex and cerebellum to 83–86% of baseline, P < 0.05). Both sevoflurane and propofol similarly reduced rCMRO2 in all brain areas to 56–70% and 50–68% of baseline, respectively (P < 0.05). The adjunct N2O counteracted some of the rCMRO2 and rCBF reductions caused by drugs alone, and especially during S+N, a widespread reduction (P < 0.05 for all cortex and cerebellum vs. awake) in the oxygen extraction fraction was seen. Adding of N2O did not alter the rCBV effects of sevoflurane and propofol alone. Conclusions Propofol reduced rCBF and rCMRO2 comparably. Sevoflurane reduced rCBF less than propofol but rCMRO2 to an extent similar to propofol. These reductions in flow and metabolism were partly attenuated by adjunct N2O. S+N especially reduced the oxygen extraction fraction, suggesting disturbed flow–activity coupling in humans at a moderate depth of anesthesia.
Towards Topological Exploration of Abandoned Mines

The need for reliable maps of subterranean spaces too hazardous for humans to occupy has motivated the use of robotic technology as mapping tools. As such, we present a systemic approach to autonomous topological exploration of a mine environment to facilitate the process of mapping. This approach focuses upon the interaction of three high-level processes: topological planning, intersection identification and local navigation. Topological planning tasks the robot to investigate stretches of mine corridor for the purpose of collecting data. Intersection identification converts sensory input into topological components used to construct an online topological map and provide the robot with a global sense of position. Local navigation transforms topological exploration objectives into robot actuation enabling traversal of mine corridors. These processes are described in detail with results presented from experiments conducted at a research coal mine near Pittsburgh, PA.
Bidirectional-Convolutional LSTM Based Spectral-Spatial Feature Learning for Hyperspectral Image Classification

This paper proposes a novel deep learning framework named bidirectional-convolutional long short term memory (Bi-CLSTM) network to automatically learn the spectral-spatial features from hyperspectral images (HSIs). In the network, the issue of spectral feature extraction is considered as a sequence learning problem, and a recurrent connection operator across the spectral domain is used to address it. Meanwhile, inspired from the widely used convolutional neural network (CNN), a convolution operator across the spatial domain is incorporated into the network to extract the spatial feature. In addition, to sufficiently capture the spectral information, a bidirectional recurrent connection is proposed. In the classification phase, the learned features are concatenated into a vector and fed to a Softmax classifier via a fully-connected operator. To validate the effectiveness of the proposed Bi-CLSTM framework, we compare it with six state-of-the-art methods, including the popular 3D-CNN model, on three widely used HSIs (i.e., Indian Pines, Pavia University, and Kennedy Space Center). The obtained results show that Bi-CLSTM can improve the classification performance by almost 1.5 % as compared to 3D-CNN.
Differential expression and bioinformatics analysis of circRNA in osteosarcoma

Aim: This research aims to investigate the expression profile of circRNA in osteosarcoma and to identify the underlying pathogenesis core genes of osteosarcoma. Methods: Illumina HiSeq was used to screen differentially expressed circRNAs between the tumour tissues and paracancerous tissues of three osteosarcoma patients. Bioinformatics analysis was used to analyse their potential functions. Five differentially expressed circRNAs were selected to detect the relative expression level in tumour and paracancerous tissues of ten osteosarcoma patients by real-time PCR. The databases such as DisGeNET and miRWalk were used to collect related genes or miRNAs. Results: A total of 259 differentially expressed circRNAs were evaluated in patients with osteosarcoma, of which 132 were up-regulated and 127 were down-regulated. Compared with that in paracancerous tissues, circ_32279 and circ_24831 were significantly down-regulated while circ_2137 and circ_20403 were significantly up-regulated in osteosarcoma tissues. The differential expression of circRNA is closely linked to biological processes and molecular functions. The difference in circRNA was mainly linked to the ‘phosphatidylinositol signalling system’ signal pathway and the ‘inositol phosphate metabolism’ signal pathway. Conclusion: The present study identified a profile of abnormal regulation of circRNA in osteosarcoma. Bioinformatics analysis indicates that the deregulated circRNAs may be related to the occurrence and development of osteosarcoma.
An Epistemic Logic for Arbitration (Extended Abstract)

In machine learning problems, labeled data are often in short supply. One of the feasible solution for this problem is transfer learning. It can make use of the labeled data from other domain to discriminate those unlabeled data in the target domain. In this paper, we propose a transfer learning framework based on similarity matrix approximation to tackle such problems. Two practical algorithms are proposed, which are the label propagation and the similarity propagation. In these methods, we build a hybrid graph based on all available data. Then the information is transferred cross domains through alternatively constructing the similarity matrix for different part of the graph. Among all related methods, similarity propagation approach can make maximum use of all available similarity information across domains. This leads to more efficient transfer and better learning result. The experiment on real world text mining applications demonstrates the promise and effectiveness of our algorithms.
Preventing HIV transmission through antiretroviral treatment-mediated virologic suppression: aspects of an emerging scientific agenda.

PURPOSE OF REVIEW This review describes important aspects of the research agenda that have emerged as a result of the recent findings of the HIV transmission study in sero-discordant couples conducted by the National Institute of Allergy and Infectious Disease (NIAID)-supported HIV Prevention Trials Network (HPTN) and referred to as HPTN 052. RECENT FINDINGS The HPTN 052 study provided strong evidence that antiretroviral treatment (ART), given to HIV-infected partners with the purpose of achieving and maintaining full virologic suppression, could prevent linked HIV transmission in sero-discordant couples. These findings have implications in all future combination prevention strategies. SUMMARY The HPTN 052 study demonstrated that sustained virus suppression, below detectable levels, can prevent HIV transmission in sero-discordant couples. As a result of this study, we have now identified ART as a key component for all combination prevention strategies. Additionally, this study demonstrates that HIV testing is the single door of entry for individualized HIV treatment and prevention. The challenge now is to create a robust, seamless linkage and retention system so that the vision of HIV treatment as prevention can be realized. Such a system will maximize both the treatment and the prevention benefits of ART. The research agenda outlined here describes the need to extend this finding to areas of implementation science, such as the development of simpler, easier to use point-of-care assays for virus load, and improved, better tolerated, more durable combinations and formulations of antiretroviral drugs.
Comparison of the 2 Most Popular Deconvolution Techniques for the Detection of Penumbral Flow in Acute Stroke

Background and Purpose— Dynamic susceptibility–weighted contrast–enhanced (DSC) magnetic resonance imaging (MRI) is used to identify the tissue-at-risk in acute stroke, but the choice of optimal DSC postprocessing in the clinical setting remains a matter of debate. Using 15O-water positron emission tomography (PET), we validated the performance of 2 common deconvolution methods for DSC-MRI. Methods— In (sub)acute stroke patients with consecutive MRI and PET imaging, DSC maps were calculated applying 2 deconvolution methods, standard and block-circulant single value decomposition. We used 2 standardized analysis methods, a region of interest–based and a voxel-based analysis, where PET cerebral blood flow masks of <20 mL/100 g per minute (penumbral flow) and gray matter masks were overlaid on DSC parameter maps. For both methods, receiver operating characteristic curve analysis was performed to identify the accuracy of each DSC-MR map for the detection of PET penumbral flow. Results— In 18 data sets (median time after stroke onset: 18 hours; median time PET to MRI: 101 minutes), block-circulant single value decomposition showed significantly better performance to detect PET penumbral flow only for mean transit time maps. Time-to-maximum (Tmax) had the highest performance independent of the deconvolution method. Conclusions— Block-circulant single value decomposition seems only significantly beneficial for mean transit time maps in (sub)acute stroke. Tmax is likely the most stable deconvolved parameter for the detection of tissue-at-risk using DSC-MRI.