Miracle-dz/UniFAR-FTUs huggingface dataset:
Effect of Orally Administered Bovine Lactoferrin on the Growth of Adenomatous Colorectal Polyps in a Randomized, Placebo-Controlled Clinical Trial

Lactoferrin (LF), a secreted, iron binding glycoprotein originally discovered as a component of milk, is found in a variety of exocrine secretions and in the secondary granules of polymorphonuclear leukocytes. Animal experiments have shown that oral administration of bovine lactoferrin (bLF) exerts anticarcinogenesis effects in the colon and other organs of the rat. The aim of this study was to determine whether oral bLF could inhibit the growth of adenomatous colorectal polyps in human patients. A randomized, double-blind, controlled trial was conducted in 104 participants, ages 40 to 75 years, with polyps ≤5 mm in diameter and likely to be adenomas. Participants were assigned to receive placebo, 1.5-g bLF, or 3.0-g bLF daily for 12 months. Target adenomatous polyps were monitored by colonoscopy. Ingestion of 3.0-g bLF significantly retarded adenomatous polyp growth in participants 63 years old or younger. Removal of adenomatous colorectal polyps is done as a preventative measure against colorectal cancer; however, polyps can be overlooked, and when detected, polypectomy is not always 100% effective in eradicating a polyp. Our study suggests that daily intake of 3.0 g of bLF could be a clinically beneficial adjunct to colorectal polyp extraction.
Leakage Reduction Techniques for Nanometer Scale CMOS Circuits

As we enter the nanoscale regime, power reduction is of increasing importance, but the established leakage reduction techniques will become less effective. Subthreshold leakage is being joined by band-to-band tunneling and gate leakage as the primary leakage mechanisms. The increased significance of these leakage components threatens the usefulness of some traditional leakage reduction techniques such as stacking and reverse body bias. We present modified versions of these techniques that result in lower total leakage (sub-threshold + gate + band-to-band tunneling) across future technology generations. These modified techniques consider the significance of each leakage mechanism in a given technology generation and make trade-offs accordingly. A novel stacking technique of input vector selection based on the relative contributions of sub-threshold leakage and gate leakage results in up to a 44% reduction in leakage compared to traditional stacking in 50nm devices. An optimal body bias selection technique bas ed on the relative contributions of sub-threshold leakage and band-to-band tunneling results in up to a 42% savings in leakage compared to the zero body bias case for 50nm devices. Since these techniques weigh the relative contributions of leakage components, they reflect the changing requirements as technologies scale.
Collective classification for unknown malware detection

Malware is any type of computer software harmful to computers and networks. The amount of malware is increasing every year and poses as a serious global security threat. Signature-based detection is the most broadly used commercial antivirus method, however, it fails to detect new and previously unseen malware. Supervised machine-learning models have been proposed in order to solve this issue, but the usefulness of supervised learning is far to be perfect because it requires a significant amount of malicious code and benign software to be identified and labelled in beforehand. In this paper, we propose a new method that adopts a collective learning approach to detect unknown malware. Collective classification is a type of semi-supervised learning that presents an interesting method for optimising the classification of partially-labelled data. In this way, we propose here, for the first time, collective classification algorithms to build different machine-learning classifiers using a set of labelled (as malware and legitimate software) and unlabelled instances. We perform an empirical validation demonstrating that the labelling efforts are lower than when supervised learning is used, while maintaining high accuracy rates.
Evaluation on performance of high-level sci-tech innovative talents in Jiangsu province based on grey incidence analysis

As high-level sci-tech innovative talents play an irreplaceable role, their introduction and training have been a sustained topic both for governments and scholars. Based on related difinitions, the input and output status of high-level sci-tech innovative talents in Jiangsu Province are analyzed firstly; then 7 relative efficiency indicators are chosen, which can systematically characterize innovation performance of high-level sci-tech talents; furthermore, by adopting Deng's grey incidence degree, the evaluation model of innovation performance established based on grey incidence degree. The result shows the model is simple and high-efficiency, reveals issues clearly even with poor data, and provides effective references for policy development and management of high-level sci-tech talents in Jiangsu province.
A Comparative Study on Semantic Techniques and Their Application in Information Retrieval

This paper investigates and compares taxonomical semantic techniques, which are human edited, and statistical semantic techniques, which are constructed using co-occurrence information of terms in documents. Further, the application of such techniques in the domain of information retrieval is investigated, mainly in the use of query expansion and keyword expansion. Two query expansion techniques are distinguished in this paper; global analysis techniques, which obtain expansion terms on the statistics of terms in the whole corpus, and local analysis techniques, which extracts expansion terms from a subset of the search results. Previous research claims that local analysis techniques outperform global analysis techniques. However, we disagree with this conclusion, because we think that global techniques can perform better if the semantics thesaurus is well constructed. Also we think that keyword expansion would be able to perform better than query expansion. We discuss how the semantic thesaurus and information retrieval using semantics can be improved.
Consequences of manganese replacement of copper for prion protein function and proteinase resistance

The prion protein (PrP) binds copper and has antioxidant activity enhancing the survival of neurones in culture. The ability of the PrP to bind other cations was tested and it was found that only manganese could substitute for copper. Although initially manganese‐loaded PrP exhibited similar structure and activity to copper‐loaded PrP, after aging, manganese‐loaded PrP became proteinase resistant and lost function. It was also found that manganese could be incorporated into PrP expressed by astrocytes and that this PrP was partially proteinase resistant. These results show that it is possible to generate proteinase‐resistant PrP from cells and suggest a possible mechanism for the formation of the scrapie isoform of the PrP as generated in sporadic prion disease.
CURVES+ web server for analyzing and visualizing the helical, backbone and groove parameters of nucleic acid structures

Curves+, a revised version of the Curves software for analyzing the conformation of nucleic acid structures, is now available as a web server. This version, which can be freely accessed at http://gbio-pbil.ibcp. fr/cgi/Curves_plus/, allows the user to upload a nucleic acid structure file, choose the nucleotides to be analyzed and after optionally setting a number of input variables, view the numerical and graphic results online or download files containing a set of helical, backbone and groove parameters that fully describe the structure. PDB format files are also provided for offline visualization of the helical axis and groove geometry.
Graphical model approximations of random finite set filters

Random finite sets (RFSs) has been a fruitful area of research in recent years, yielding new approximate filters such as the probability hypothesis density (PHD), cardinalised PHD (CPHD), and multiple target multi-Bernoulli (MeMBer). These new methods have largely been based on approximations that side-step the need for measurement-to-track association. Comparably, RFS methods that incorporate data association, such as Morelande and Challa's (M-C) method, have received little attention. This paper provides a RFS algorithm that incorporates data association similarly to the M-C method, but retains computational tractability via a recently developed approximation of marginal association weights. We describe an efficient method for resolving the track coalescence phenomenon which is problematic for joint probabilistic data association (JPDA) and related methods (including M-C). The method utilises a network flow optimisation, and thus is tractable for large numbers of targets. Finally, our derivation also shows that it is natural for the multi-target density to incorporate both a Poisson point process (PPP) component (representing targets that have never been detected) and a multi-Bernoulli component (representing targets under track). We describe a method of recycling, in which tracks with a low probability existence are transferred from the multi-Bernoulli component to the PPP component, effectively yielding a hybrid of M-C and PHD.
Boundary torsion and convex caps of locally convex surfaces

We prove that the torsion of any closed space curve which bounds a simply connected locally convex surface vanishes at least 4 times. This answers a question of Rosenberg related to a problem of Yau on characterizing the boundary of positively curved disks in Euclidean space. Furthermore, our result generalizes the 4 vertex theorem of Sedykh for convex space curves, and thus constitutes a far reaching extension of the classical 4 vertex theorem. The proof involves studying the arrangement of convex caps in a locally convex surface, and yields a Bose type formula for these objects.
Facilitating Cognitive Presence in Online Learning: Interaction Is Not Enough

This study assessed the depth of online learning, with a focus on the nature of online interaction in four distance education course designs. The Study Process Questionnaire was used to measure the shift in students' approach to learning from the beginning to the end of the courses. Design had a significant impact on the nature of the interaction and whether students approached learning in a deep and meaningful manner. Structure and leadership were found to be crucial for online learners to take a deep and meaningful approach to learning.
Draft : Have you checked your IPC performance lately ?

IPC mechanisms in UNIX systems were developed for a range of different purposes, but their performance is increasingly unpredictable due to diversification in multicore hardware layouts and the popularity of OS virtualisation. Perhaps surprisingly, no standard benchmarking suite exists to compare the performance of different IPC mechanisms on a machine. To address this need, we developed ipc-bench, and discovered significant and sometimes counter-intuitive differences when running on many-core and virtualised hardware. In this paper, we characterise a subset of these results on hardware available to us. However, we also make a much larger data set available, and provide means to enable a wider community to gather further data on a larger scale. ipc-bench integrates with revision control to make it easy to record and publish performance results, aggregate them and track their provenance using a popular code sharing website. We hope that making this tool available will result in a corpus of useful open data to guide the development of hypervisors, kernels and programming frameworks.
Clinical manifestations of intermediate allele carriers in Huntington disease

Objective: There is controversy about the clinical consequences of intermediate alleles (IAs) in Huntington disease (HD). The main objective of this study was to establish the clinical manifestations of IA carriers for a prospective, international, European HD registry. Methods: We assessed a cohort of participants at risk with <36 CAG repeats of the huntingtin (HTT) gene. Outcome measures were the Unified Huntington's Disease Rating Scale (UHDRS) motor, cognitive, and behavior domains, Total Functional Capacity (TFC), and quality of life (Short Form–36 [SF-36]). This cohort was subdivided into IA carriers (27–35 CAG) and controls (<27 CAG) and younger vs older participants. IA carriers and controls were compared for sociodemographic, environmental, and outcome measures. We used regression analysis to estimate the association of age and CAG repeats on the UHDRS scores. Results: Of 12,190 participants, 657 (5.38%) with <36 CAG repeats were identified: 76 IA carriers (11.56%) and 581 controls (88.44%). After correcting for multiple comparisons, at baseline, we found no significant differences between IA carriers and controls for total UHDRS motor, SF-36, behavioral, cognitive, or TFC scores. However, older participants with IAs had higher chorea scores compared to controls (p = 0.001). Linear regression analysis showed that aging was the most contributing factor to increased UHDRS motor scores (p = 0.002). On the other hand, 1-year follow-up data analysis showed IA carriers had greater cognitive decline compared to controls (p = 0.002). Conclusions: Although aging worsened the UHDRS scores independently of the genetic status, IAs might confer a late-onset abnormal motor and cognitive phenotype. These results might have important implications for genetic counseling. ClinicalTrials.gov identifier: NCT01590589.
Ontology Based Personalized Search Engine

An ontology is a representation of knowledge as hierarchies of concepts within domain, using a shared vocabulary to denote the types, properties and interrelationships of those concepts [1][2]. Ontologies are often equated with classification of hierarchies of classes, class definitions, and the relations, but ontologies need not be limited to these forms. Ontologies are also not limited to conservative definitions, i.e., in the traditional logic sense that only introduce terminology and do not add any knowledge about the world (Enderton, 1972). To specify a conceptualization, axioms need to be proposed that constrain interpretation of defined terms [3]. Ontologies are frameworks for organizing information and are collections of URIs. It is a systematic arrangement of all important categories of objects and concepts within a particular field and relationship between them. Search engines are commonly used for information retrieval from web. The ontology based personalized search engine (OPSE) captures the user's priorities in the form of concepts by mining through the data which has been previously clicked by them. Search results need to be provided according to user profile and user interest so that highly relevant search data is provided to the user. In order to do this, user profiles need to be maintained. Location information is important for searching data; OPSE needs to classify concepts into content concepts and location concepts. User locations (gathered during user registration) are
A Bayesian Method for Robust Estimation of Distributional Similarities

Existing word similarity measures are not robust to data sparseness since they rely only on the point estimation of words' context profiles obtained from a limited amount of data. This paper proposes a Bayesian method for robust distributional word similarities. The method uses a distribution of context profiles obtained by Bayesian estimation and takes the expectation of a base similarity measure under that distribution. When the context profiles are multinomial distributions, the priors are Dirichlet, and the base measure is the Bhattacharyya coefficient, we can derive an analytical form that allows efficient calculation. For the task of word similarity estimation using a large amount of Web data in Japanese, we show that the proposed measure gives better accuracies than other well-known similarity measures.
Valuing nutrients in soil and water: concepts and techniques with examples from IWMI studies in the developing world

Research Reports IWMI's mission is to improve water and land resources management for food, livelihoods and nature. In serving this mission, IWMI concentrates on the integration of policies, technologies and management systems to achieve workable solutions to real problems—practical, relevant results in the field of irrigation and water and land resources. The publications in this series cover a wide range of subjects—from computer modeling to experience with water user associations—and vary in content from directly applicable research to more basic studies, on which applied work ultimately depends. Some research reports are narrowly focused, analytical and detailed empirical studies; others are wide-ranging and synthetic overviews of generic problems. Although most of the reports are published by IWMI staff and their collaborators, we welcome contributions from others. Each report is reviewed internally by IWMI's own staff and Fellows, and by external reviewers. The reports are published and distributed both in hard copy and electronically (www.iwmi.org) and where possible all data and analyses will be available as separate downloadable files. Reports may be copied freely and cited with due acknowledgment. The authors would like to thank Frits Penning de Vries for his support. His vision, cross-cutting through different IWMI themes towards a better integration of research aiming at increased water and soil productivity, was a major motivation. We would also like to thank Chris Scott for his contribution of the Mexican case study and are grateful to Thomas Enters, Meredith Giordano and our reviewers for their input and contributions to different versions of this study. Valuing nutrients in soil and water: Concepts and techniques with examples from IWMI studies in the developing world. Please send inquiries and comments to: iwmi@cgiar.org IWMI receives its principal funding from 58 governments, private foundations, and international and regional organizations known as the Consultative Group on International Agricultural Research (CGIAR).
Novel Antidepressant-Like Activity of Propolis Extract Mediated by Enhanced Glucocorticoid Receptor Function in the Hippocampus

Propolis is a natural product made by honeybees that has been widely used in folk medicine with a broad spectrum of biological activities. To investigate the antidepressant-like activity of propolis extract, CD-1 mice were administered an ethanol extract of propolis (50, 100, or 200 mg/kg, p.o.) prior to the behavioral test. The propolis extract-treated group showed a dose-dependent decrease in immobility time in the FST and tail suspension test without altering locomotor activity. Propolis extract decreased the limbic hypothalamic-pituitary-adrenal axis response to the FST as indicated by an attenuated corticosterone response and decreased in c-fos immunoreactive neurons in the hippocampal dentate gyrus. Western blot analysis revealed a reduction in hippocampal glucocorticoid receptor (GR) expression following the FST, which was reversed by propolis extract. Propolis extract also increased pGR(S220)/(S234) ratio by a differential phosphorylation in S220 and S234. FST-induced downregulation of cAMP-responsive element binding protein phosphorylation at S133 (pCREB) was restored by propolis extract, showing a strong and positive relationship between pCREB and pGR(S220)/(S234) ratio. These findings suggest that the propolis extract potentiates antidepressant-like activity by enhancing GR function which is one of the therapeutic mechanisms of antidepressant; thus, propolis extract may provide a novel therapy for depression.
Impact of kidney transplantation on cognitive profile

Aim. To assess the impact of kidney transplantation on neuropsychological functioning of Chronic Kidney Disease (CKD) patients. Methods. : 42 kidney transplant (KT) recipients and 41 healthy living donors –control group- were tested by a comprehensive neuropsychological battery: Neuropsi Attention and Memory, the Hospital Anxiety and Depression Scale, The Epworth Sleepiness Scale and the Hachinski Ischemic Scale. 28 patients were followed up 6 months after KT. Their kidney donors were evaluated pre as well as post donation (at same time of study group) for comparison. Results. An improvement in global cognitive functioning after KT was found (when learning effects were controlled). Patients improved in Stroop test and auditory/verbal delayed recall using cues. Conclusions. Renal transplant is suggested as an ideal solution as it eliminates factors (measurable or not) that have an impact over cognitive functioning.
Nakama: A Companion for Non-verbal Affective Communication

We present "Nakama": A communication device that supports affective communication between a child and its - geographically separated - parent. Nakama consists of a control unit at the parent's end and an actuated teddy bear for the child. The bear contains several communication channels, including social touch, temperature, and vibrotactile heartbeats; all aimed at increasing the sense of presence. The current version of Nakama is suitable for user evaluations in lab settings, with which we aim to gain a more thorough understanding of the opportunities and limitations of these less traditional communication channels.
Data collection method using two types of forwarding nodes for energy saving in triage network

Researches of sensor networks collecting patients' data with computerized triage tags, called Triage Network, are attracting attention. The listening power used in triage tags is the major factor of lots of energy consumption, and consumption of energy increases when sensor nodes always communicate with other nodes in active state. Hence, we suppose that sensor nodes are put to sleep periodically to avoid running out of battery. However, some nodes have mobility and nodes secede from the network according to patients conditions in Triage Network. The paths are failed and it is needed to reconstruct paths when these forwarding nodes move or secede from network. Therefore, data arrival ratio decreases and consumption of battery increases due to reconstruction of other paths. In this paper, we propose a data collection method using two types of forwarding nodes, Stable Nodes and Energy Efficient Nodes. This method uses two types of forwarding nodes according to priority of data and avoids loss of high priority data, improves the data arrival ratio and saves the energy consumption. We evaluate the proposed method and show its effectiveness using computer simulations.
A Main Memory Index Structure to Query Linked Data

A possible approach to query Linked Data combines the actual evaluation of a query with the traversal of data links in order to discover and retrieve potentially relevant data. An implementation of this idea requires approaches that support an efficient and flexible management of temporary, ad hoc data collections that emerge during query execution. However, existing proposals for managing RDF data primarily focus on persistent storage and query execution for large datasets and, thus, are unsuitable in our dynamic scenario which involves many small sets of data. In this paper we investigate main memory data structures to store Linked Data in a query execution system. We discuss the requirements for such a data structure, introduce three strategies that make use of hash table based indexes, and compare these strategies empirically. While this paper focuses on our query execution approach, the discussed data structures can also be applied to other approaches that retrieve Linked Data from remote sources via URI look-ups in order to process this data locally.