Miracle-dz/UniFAR-FTUs huggingface dataset:
Scientific potential of chitosan blending with different polymeric materials: A review

Chitosan, the second most abundant natural fiber after cellulose, is a partially deacetylated polymer of N-acetyl-d-glucosamine. Chitosan is nontoxic, biodegradable, and biocompatible. It also has film-forming properties. Chitosan is blended with many polymeric materials such as: poly(methyl methacrylate), epoxy, polystyrene, polyaniline, polysulfone, and polycarbonate. Chitosan has been used as a filler as well as a fiber material in thermoplastic polymers. However, polymer/chitosan blends may show incompatibility owing to repulsion between polar chitosan functional groups and hydrophobic polymeric matrices. Other limitations associated with the using chitosan in blends are high moisture absorption, low processing temperature, low heat stability, and low flame resistance. Consequently, the fabrication techniques, miscibility, mechanical strength, morphology, and structural features of polymer/chitosan blends have been investigated. Moreover, chitosan addition as a compatibilizer in blended systems has been explored. There are many potential applications for polymer/chitosan in membrane technology, dye removal, packaging materials, drug delivery, tissue engineering, and biochemical relevance.
Discovering the staring people from social networks

In this paper, we study a novel problem of staring people discovery from social networks, which is concerned with finding people who are not only authoritative but also sociable in the social network. We formalize this problem as an optimization programming problem. Taking the co-author network as a case study, we define three objective functions and propose two methods to combine these objective functions. A genetic algorithm based method is further presented to solve this problem. Experimental results show that the proposed solution can effectively find the staring people from social networks.
Developers assignment for analyzing pull requests

A new collaboration approach is becoming increasingly common in open-source projects: the pull request model. In this kind of collaboration, developers that do not belong to the core team of a project can submit contributions to the core team. In projects that receive many pull requests, the task of assigning developers to analyze them is a difficult one. In this work, we propose to use data mining techniques, more specifically, classification strategies, in order to suggest the most appropriate developers to analyze a contribution, considering the pull request model. The experiments were conducted using 21 open source projects, each one characterized by 14 attributes. The first set of experiments aimed at indicating just one developer to analyze the pull request. The obtained predictive accuracy ranged from 22.45% to 68.27%. The Random Forest classifier achieved the best result in 76% on the projects. In the second set of experiments, we conclude that, when suggesting three developers to analyze a pull request, the chance of identifying the developer that actually analyzed the pull request ranged from 47.33% to 95.47%.
Bulk termination of the quasicrystalline fivefold surface of Al70Pd21Mn9

The structure of the Al 7 0 Pd 2 1 Mn 9 surface has been investigated using high-resolution scanning tunneling microscopy. From two large fivefold terraces on the surface in a short decorated Fibonacci sequence, atomically resolved surface images have been obtained. One of these terraces carries a rare local configuration in the form of a ring. The location of the corresponding sequence of terminations in the bulk model M of icosahedral i-AlPdMn based on the three-dimensional tiling T* ( 2 F ) of an F phase has been estimated using this ring configuration and the requirement from low-energy electron diffraction work of Gierer et al. that the average atomic density of the terminations is 0.136 atoms per A 2 . A termination contains two atomic plane layers separated by a vertical distance of 0.48 A. The position of the bulk terminations is fixed within the layers of Bergman polytopes in the model M: they are 4.08 A in the direction of the bulk from a surface of the most dense Bergman layers. From the coding windows of the top planes in terminations in M we conclude that a Penrose (P1) tiling is possible on almost all fivefold terraces. The shortest edge of the tiling P1 is either 4.8 or 7.8 A. The experimentally derived tiling of the surface with the ring configuration has an edge length of 8.0 ′0.3 A and hence matches the minimal edge length expected from the model.
c-MET receptor tyrosine kinase as a molecular target in advanced hepatocellular carcinoma

c-MET is the membrane receptor for hepatocyte growth factor (HGF), also known as scatter factor or tumor cytotoxic factor, a mitogenic growth factor for hepatocytes. HGF is mainly produced by cells of mesenchymal origin and it mainly acts on neighboring epidermal and endothelial cells, regulating epithelial growth and morphogenesis. HGF/MET signaling has been identified among the drivers of tumorigenesis in human cancers. As such, c-MET is a recognized druggable target, and against it, targeted agents are currently under clinical investigation. c-MET overexpression is a common event in a wide range of human malignancies, including gastric, lung, breast, ovary, colon, kidney, thyroid, and liver carcinomas. Despite c-MET overexpression being reported by a large majority of studies, no evidence for a c-MET oncogenic addiction exists in hepatocellular carcinoma (HCC). In particular, c-MET amplification is a rare event, accounting for 4%–5% of cases while no mutation has been identified in c-MET oncogene in HCC. Thus, the selection of patient subgroups more likely to benefit from c-MET inhibition is challenging. Notwithstanding, c-MET overexpression was reported to be associated with increased metastatic potential and poor prognosis in patients with HCC, providing a rationale for its therapeutic inhibition. Here we summarize the role of activated HGF/MET signaling in HCC, its prognostic relevance, and the implications for therapeutic approaches in HCC.
Evolving decision-tree induction algorithms with a multi-objective hyper-heuristic

Multi-objective optimization has been widely used in evolutionary computation for solving problems in which two or more conflicting objectives need to be optimized in a simultaneous fashion. This paper presents a multi-objective hyper-heuristic based on evolutionary algorithms that automatically designs complete decision-tree induction algorithms. Such algorithms are designed to generate decision trees that present an interesting trade-off between predictive performance and complexity. The proposed approach is tested over 20 UCI datasets, and it is compared with a single-objective hyper-heuristic as well as with traditional decision-tree induction algorithms. Experimental results show that the proposed approach can match the top predictive performance achieved by the baseline methods, without significant loss in model comprehensibility.
Deep Representation for Patient Visits from Electronic Health Records

We show how to learn low-dimensional representations (embeddings) of patient visits from the corresponding electronic health record (EHR) where International Classification of Diseases (ICD) diagnosis codes are removed. We expect that these embeddings will be useful for the construction of predictive statistical models anticipated to drive personalized medicine and improve healthcare quality. These embeddings are learned using a deep neural network trained to predict ICD diagnosis categories. We show that our embeddings capture relevant clinical informations and can be used directly as input to standard machine learning algorithms like multi-output classifiers for ICD code prediction. We also show that important medical informations correspond to particular directions in our embedding space.
Prenatal maternal depression and child serotonin transporter linked polymorphic region (5-HTTLPR) and dopamine receptor D4 (DRD4) genotype predict negative emotionality from 3 to 36 months

Abstract Prenatal maternal depression and a multilocus genetic profile of two susceptibility genes implicated in the stress response were examined in an interaction model predicting negative emotionality in the first 3 years. In 179 mother–infant dyads from the Maternal Adversity, Vulnerability, and Neurodevelopment cohort, prenatal depression (Center for Epidemiologic Studies Depressions Scale) was assessed at 24 to 36 weeks. The multilocus genetic profile score consisted of the number of susceptibility alleles from the serotonin transporter linked polymorphic region gene (5-HTTLPR): no long-rs25531(A) (LA: short/short, short/long-rs25531(G) [LG], or LG/LG] vs. any LA) and the dopamine receptor D4 gene (six to eight repeats vs. two to five repeats). Negative emotionality was extracted from the Infant Behaviour Questionnaire—Revised at 3 and 6 months and the Early Child Behavior Questionnaire at 18 and 36 months. Mixed and confirmatory regression analyses indicated that prenatal depression and the multilocus genetic profile interacted to predict negative emotionality from 3 to 36 months. The results were characterized by a differential susceptibility model at 3 and 6 months and by a diathesis–stress model at 36 months.
PD‐1 blockade enhances the antitumor efficacy of GM‐CSF surface‐modified bladder cancer stem cells vaccine

Eliminating cancer stem cells (CSCs) is a key issue in eradicating tumor. The streptavidin–granulocyte‐macrophage‐colony stimulating factor (SA–GM‐CSF) surface‐modified bladder CSCs vaccine previously developed using our protein–anchor technology could effectively induce specific immune response for eliminating CSCs. However, program death receptor‐1 (PD‐1)/program death ligand 1 (PD‐L1) signaling in tumor microenvironment results in tumor‐adaptive immune resistance. Although the CSCs vaccine could increase the number of CD8+T cells, a part of these CD8+T cells expressed PD‐1. Moreover, the CSCs vaccine upregulated the PD‐L1 expression of tumor cells, resulting in immune resistance. Adding PD‐1 blockade to the CSCs vaccine therapy increased the population of CD4+, CD8+ and CD8+IFN‐γ+ but not CD4+ Foxp3+T cells and induced the highest production of IFN‐γ. PD‐1 blockade could effectively enhance the functions of tumor‐specific T lymphocytes generated by the CSCs vaccine. This combination therapy improved the cure rate among mice and effectively protected the mice against a second CSCs cell challenge, but not a RM‐1 cell challenge. These results indicate that PD‐1 blockade combined with the GM‐CSF‐modified CSCs vaccine effectively induced a strong and specific antitumor immune response against bladder cancer.
Caregivers’ lived experience in trying to read slight movements in a child with severe brain injury: A phenomenological study

AIMS AND OBJECTIVES To explore caregivers' lived experience of reading slight movements of a child with severe brain injury. BACKGROUND Despite increased need, the development of individual care for children with severe brain injuries has been prevented by their severe physical state and the poor reproducibility of their movements. In addition to a lack of evidence on the motor characteristics of patients with severe brain injury with multiple disabilities, their own development contributes to increasing variability in their states. Thus, caregivers are compelled to rely on their experiences, which have not been academically explored. DESIGN A qualitative study based on van Manen's method of hermeneutic phenomenology. METHODS Data were obtained through twenty-one 3-hr observation sessions and five 15- to 45-min group interviews. We observed a child (called AK) with severe brain injury and his 61 caregivers, and conducted group interviews with 28 caregivers. We focused on caregivers' experiences of reading AK's slight movements. The data were interpreted based on van Manen's hermeneutic phenomenological approach. RESULTS Four themes emerged as caregivers' experience in trying to read AK's slight movements. By considering "AK's physical state and his slight movements" and discovering "caregivers' 'sense of uncertainty' about AK's slight movements," caregivers could decipher "AK's multiple slight movements. " "Sharing" was found as a necessary aspect of these other three themes of reading AK's slight movements. CONCLUSIONS We presented caregivers' experiences as related to these four themes in their efforts to read the slight movements of AK. Due to AK's slight movements with poor reproducibility, "sharing" was necessary to read AK's slight movements, as it exposes caregivers' lived experience to the interpretation of multiple caregivers. RELEVANCE TO CLINICAL PRACTICE These four themes may be useful for assessing, guiding and promoting caregivers' use of sharing when reading the slight movements of children with severe brain injury.
Clinical relevance of the effects of reach-to-grasp training using trunk restraint in individuals with hemiparesis poststroke: A systematic review.

OBJECTIVE To evaluate the evidence for, and clinical relevance of, immediate and long-term effects of trunk restraint during reach-to-grasp training poststroke on movement patterns and functional abilities within the framework of the International Classification of Functioning, Disability and Health. DATA SOURCES PubMed, Web of Science, CINAHL, Embase, PEDro, Cochrane Library (publication dates January 1985 to March 2015). STUDY SELECTION Randomized controlled trials comparing training using trunk restraint with any other exercise training. DATA EXTRACTION Data were extracted by one researcher and checked by two other researchers. The Cochrane Collaboration's tool for assessing risk of bias and the Physiotherapy Evidence Database scale were used by two researchers to assess study quality and risk of bias. DATA SYNTHESIS Eight studies met the inclusion criteria. Five studies found better recovery of movement patterns (trunk displacement, elbow extension, and/or shoulder flexion - body function/structure) at post-test in the experimental compared with the control groups. Functional abilities (activity/participation) improved more in the experimental groups in 3 studies at post-test. Long-term effects were found in one study after 4 weeks. CONCLUSION Trunk restraint has immediate and some long-term effects in adults with chronic stroke. However, these effects are not consistently clinically relevant when referring to minimal detectable change or minimal clinically important difference values.
Data Scientist - Manager of the Discovery Lifecycle

Data Scientists are the masters of Big Data. Analyzing masses of versatile data leads to insights that, in turn, may connect to successful business strategies, crime prevention, or better health care just to name a few. Big Data is primarily approached as mathematical and technical challenge. This may lead to technology design that enables useful insights from Big Data. However, this technology-driven approach does not meet completely and consistently enough the variety of information consumer requirements. To catch up with the versatility of user needs, the technology aspect should probably be secondary. If we adopt a user-driven approach, we are more in the position to cope with the individual expectations and exigencies of information consumers. This article takes information discovery as the overarching paradigm in data science and explains how this perspective change may impact the view on the profession of the data scientist and, resulting from that, the curriculum for the education in data science. It reflects the result from discussions with companies participating in our student project cooperation program. These results are groundwork for the development of a curriculum framework for Applied Data Science.
A clinical protocol for the study of traditional medicine and human immunodeficiency virus-related illness.

A high-level meeting was subsequently organized in New Delhi by the DSPRUD on June 7 2001 to prepare the protocol. The committee that met comprised representatives from DSPRUD the Department of Indian Systems of Medicine and Homoeopathy the government of India the Indian Council of Medical Research Health India Foundation All India Institute of Medical Sciences Central Council for Research in Ayurveda and Siddha (CCRAS) Sir Ganga Ram Hospital New Delhi and the National Institute of Ayurveda Jaipur. After detailed discussions a model protocol was prepared and has been circulated to all participants. (authors)
Self-sensing estimator for micromachined electrostatic actuators and parameters’ optimisation

Parallel plate actuators (PPAs) are widely used in micro-electro-mechanical systems. Control strategies for PPAs often require displacement and velocity feedback that may be measured with various sensing techniques, which may require additional structures or distort the steady-state behaviour. An alternative approach of designing an estimator using the measured voltage across the PPA without additional sensing structures and distortions is proposed in this work. This novel method can improve the performance and reduce the device's footprint with full-state (displacement and velocity) feedback information, using a series resistor. A system model using this configuration is investigated. The observability of this self-sensing technique is analysed using a small signal model. Then, a singular value decomposition is applied to examine how to further improve the observability by choosing appropriate parameters. Simulation and numerical studies were performed which validate this method.
Development of Flow within a Diffusing C-Duct – Experimental Investigation and Numerical Validation

Experimental investigation of flow development within a rectangular 90o curved diffusing C-duct of low aspect ratio and area ratio of 2 was carried out and the threedimensional computational results are then compared with the experimental results for numerical validation. All measurements were made in a turbulent flow regime (Re = 2.35x10 5 ), based on the duct inlet hydraulic diameter (dh = 0.0666m) and mass averaged inlet velocity of 60m/s. Wall pressures were measured through wall pressure taps. The mean velocities, static and total pressures at six cross-sectional planes (along the centreline of the diffuser) were obtained using a pre-calibrated three-hole pressure probe in null mode. The flow was numerically simulated by using different viscous models available in the commercial CFD software FLUENT 6.3. The experimental inlet and boundary conditions were used as input for the computation and validation of the numerical
Future warming and acidification result in multiple ecological impacts to a temperate coralline alga

Coralline algae are a crucial component of reef systems, stabilising reef substrate, providing habitat and contributing to accretion. Coralline algae and their surface microbial biofilms are also important as settlement cues for marine invertebrates, yet few studies address the impact of future environmental conditions on interactions between coralline algae, reef microbes and settlement by larvae of marine invertebrates. We exposed the temperate coralline algal species Amphiroa gracilis to warming and/or acidification scenarios for 21 days. Algae became bleached but photosystem II function was not measurably impacted. Settlement by larvae of the sea urchin Heliocidaris erythrogramma was reduced and the structure of the prokaryotic community associated with A. gracilis was altered. Coralline algae in ambient conditions were dominated by Alphaproteobacteria from the Rhodobacteraceae including Loktonella; those under warming were dominated by Bacteroidetes and Verrucomicrobia; acidification resulted in less Loktonella and more Planctomycetes and a combination of warming and acidification caused increases in Bacteroidetes, Verrucomicrobia and the Alphaproteobacteria family Hyphomonadaceae. These experiments indicate that predicted future environmental change may reduce the ability of some temperate reef coralline algae and associated reef microbes to facilitate settlement of invertebrate larvae as well as having a direct impact to algae via bleaching.
Classification of Twitter follow links based on the followers' intention

In Twitter, a user follows other users for various purposes, e.g., for information gathering, for personal communication, and for reading a chat by celebrities. As a result, the intention of followers behind follow links is different from case to case. We classify follow links in Twitter based on the followers' intention along with three classification axes: user-orientation, content-orientation, and mutuality. The combination of these three axes covers most major types of followers' intention found in Twitter. We collected 1760 Twitter follow links through a questionnaire and we found that (1) user-orientation and content-orientation have weak positive correlation, and user-orientation also has weak positive correlation with mutuality, but content-orientation has no correlation with mutuality, (2) content-oriented follows are more frequent than user-oriented follows even among communication-oriented users, and (3) the users have no clear intention for more than 20% of their follow links. We then constructed classifiers with various features of the followee, the follower, and their relationship. We also developed a method of classifying "lists" in Twitter into information lists and community lists, and used the types of lists including the followee. Our experiments show that (1) no single property is a prominent discriminator, and (2) classification accuracy for follow links by information-gathering users are higher than that for communication-oriented users.
Petroleum Sorption by Thermally Treated Rice Husks Derived from Agricultural Byproducts

Agricultural byproducts or residues are widely produced in Kazakhstan and their utilization as a sorbent material for petroleum spill can be developed as low cost, high tech environmental technology. Rice husk, an agricultural waste, was used as petroleum sorbent material. The present study examines the sorption capacity of thermally treated rice husk for different petroleum products. Results showed that the petroleum sorption capacity of this material prepared at 700 ВєC was 15 g/g for heavy crude petroleum. The material obtained by thermal treatment of rice husk has very good buoyancy characteristics, high petroleum sorption capacity and high hydrophobicity. The effects of heating temperature, contact time and petroleum density on the petroleum sorption capacity of thermally treated rice husks were further studied on the basis of phase composition, microstructure and morphology using X-ray diffraction analysis, FTIR spectrometry, optical digital microscopy and scanning electron microscopy (SEM). The results of the SEM and optical microscopy studies strongly indicate that thermal treatment is a suitable method to improve structure of husk particles regarding porosity compared to virgin samples. The research provides the basis for development of a new environmental material with optimal characteristics, providing efficient sorption of petroleum and petroleum products from aqueous medium.