Miracle-dz/UniFAR-FTUs huggingface dataset:
“Falls prevention among older people and care providers: protocol for an integrative review”

AIM To review the evidence about the role of care providers in fall prevention in older adults aged ≥ 65 years, this includes their views, strategies, and approaches on falls prevention and effectiveness of nursing interventions. BACKGROUND Some fall prevention programmes are successfully implemented and led by nurses and it is acknowledged the vital role they play in developing plans for fall prevention. Nevertheless, there has not been a systematic review of the literature that describes this role and care providers' views on fall's prevention initiatives. DESIGN A convergent synthesis of qualitative, quantitative, and mixed methods studies. The eligibility criteria will be based on participants, interventions/exposure, comparisons, and outcomes for quantitative studies and on population, the phenomena of interest and the context, for qualitative studies. To extract data and assess study qualities members of the research team will work in pairs according to their expertise. The review will follow the guidelines for integrative reviews and the proposed methods will adhere to the PRISMA statement checklist complemented by the ENTREQ framework. As qualitative synthesis are emergent, all procedures and changes in procedure will be documented. DISCUSSION The review has a constructivist drive as studies that combine methods ought to be paradigmatic driven. Review questions are broad to allow issues emerge and have purposefully left the design flexible to allow for adjustments as the review progresses. The review seeks to highlight the roles that care providers play in fall prevention and their views on fall's prevention initiatives.
Joint Spectrum Sensing and Resource Allocation Scheme in Cognitive Radio Networks with Spectrum Sensing Data Falsification Attack

Spectrum sensing and spectrum sharing are two fundamental issues in a cognitive radio network (CRN). The spectrum sensing data falsification (SSDF) attack imposes bad effects on both spectrum sensing and spectrum sharing. To deal with SSDF attacks and to incentivize secondary users (SUs) to behave well, a joint spectrum sensing and resource allocation (JSSRA) scheme in a CRN is proposed in this paper. The JSSRA problem is formulated as a weighted-proportional-fairness-based resource-allocation optimization problem under the constraint that the primary user (PU) network is sufficiently protected. The problem is decomposed into two subproblems, namely, the resource allocation subproblem and cooperative SU number decision subproblem, which are solved by the Lagrangian dual algorithm and the brute-force algorithm, respectively. Moreover, a user-selection method based on reinforcement learning is presented to select reliable SUs for cooperative spectrum sensing (CSS). In addition, the SU's trust degree is updated according to its behavior in CSS and is used in the sensed resource-allocation process. The key point of our proposed scheme is to make SUs improve the sensing reliability and prevent SUs from behaving maliciously by an incentive mechanism. Comprehensive performance evaluation is conducted by computer simulation. It is shown that the proposed JSSRA scheme deals with the SSDF attack well in cooperative sensing process to improve system robustness and achieves a significant system utility gain in resource allocation.
Active learning for networked data based on non-progressive diffusion model

We study the problem of active learning for networked data, where samples are connected with links and their labels are correlated with each other. We particularly focus on the setting of using the probabilistic graphical model to model the networked data, due to its effectiveness in capturing the dependency between labels of linked samples. We propose a novel idea of connecting the graphical model to the information diffusion process, and precisely define the active learning problem based on the non-progressive diffusion model. We show the NP-hardness of the problem and propose a method called MaxCo to solve it. We derive the lower bound for the optimal solution for the active learning setting, and develop an iterative greedy algorithm with provable approximation guarantees. We also theoretically prove the convergence and correctness of MaxCo. We evaluate MaxCo on four different genres of datasets: Coauthor, Slashdot, Mobile, and Enron. Our experiments show a consistent improvement over other competing approaches.
Characterization and Evaluation of Phenol Degrading Bacillus Spp. for Enhancing the Softness of Coir Fiber

ABSTRACT Coir is a unique versatile and most resistant fiber among all commercially available natural fibers. The rigidity and toughness of the coir fiber due to its high phenylpropanoid content makes its usage limited for tough textured products. In this study, an eco-friendly microbial formulation was developed using phenol degrading strains to improve the quality of the coir fiber. The coir fiber treated with these bacterial strains showed enhanced brightness, reduced flexural rigidity, and increase in softness. Scanning electron micrograph analysis confirmed the improved surface texture of the treated fiber. The application of phenol degrading Bacillus spp. promises to be an effective eco-friendly strategy for the quality improvement of coir fiber.
Visual Speech Enhancement

When video is shot in noisy environment, the voice of a speaker seen in the video can be enhanced using the visible mouth movements, reducing background noise. While most existing methods use audio-only inputs, improved performance is obtained with our visual speech enhancement, based on an audio-visual neural network. We include in the training data videos to which we added the voice of the target speaker as background noise. Since the audio input is not sufficient to separate the voice of a speaker from his own voice, the trained model better exploits the visual input and generalizes well to different noise types. The proposed model outperforms prior audio visual methods on two public lipreading datasets. It is also the first to be demonstrated on a dataset not designed for lipreading, such as the weekly addresses of Barack Obama.
A New Multiattribute Decision Making Support Tool for Identifying Critical Components in Power Transmission Systems

The present context of the electric industry, characterized by competitive markets, privatization, and regulatory of technical requirements forces the power utilities to optimize their asset management practices and develop the requisite decision plans techno-economically. Practically approaching, this paper devises a new support tool based on a multiattribute decision making (MADM) framework in combination with analytical hierarchical process (AHP) to determine the most critical components of power transmission systems. Measure of system-wide reliability performance, outage cost, marginal clearing prices demonstrative of market fairness, and network losses are among the attributes considered in this paper for component criticality assessment. With the frequent existence of qualitative and quantitative attributes, the proposed approach can effectively help to deal with the existent uncertainty and conventional judgment vagueness. As verified in a case study on the IEEE Reliability Test System (IEEE-RTS), the proposed framework introduces its applicability and efficiency for the practical asset management optimizations in electric utilities.
Experimental And Theoretical Investigation Of The Fracture Behaviour Of Glass Beads/Epoxy Compositions Using Microscratching

Concrete, ceramic, and other quasi-brittle materials contain pre-existing cracks and complex structure on various internal length-scales. Quantifying the fracture behavior of these heterogeneous materials using different testing methods is a challenge and is an argumentative subject . To selectively study the impact of microstructure on micro-scale fracture parameter this article presents an experimental and theoretical investigation of the fracture toughness of a representative composite material consisting of glass beads embedded in epoxy using microscratching and conventional three-point bending tests. Existing analysis formulas for microscratch data assumes homogeneity near the indenter tip. This study finds that this assumption may need to be reconsidered. By controlling the volume fraction of glass beads (representing an inclusion) in the matrix of the composite material, it is possible to control the amount, or direction, of crack development and reduce the stress concentration within the material during loading . As a result, an increase in the fracture toughness of the composites and improved fracture properties is obtained.
The Cosmic Ultraviolet Baryon Survey (CUBS) VII: on the warm-hot circumgalactic medium probed by O VI and Ne VIII at 0.4 $\lesssim$ z $\lesssim$ 0.7

This paper presents a newly established sample of 103 unique galaxies or galaxy groups at $0.4\lesssim z\lesssim 0.7$ from the Cosmic Ultraviolet Baryon Survey (CUBS) for studying the warm-hot circumgalactic medium (CGM) probed by both O VI and Ne VIII absorption. The galaxies and associated neighbors are identified at $<1$ physical Mpc from the sightlines toward 15 CUBS QSOs at $z_{\rm QSO}\gtrsim 0.8$. A total of 30 galaxies or galaxy groups exhibit associated O VI $\lambda\lambda$ 1031, 1037 doublet absorption within a line-of-sight velocity interval of $\pm250$ km/s, while the rest show no trace of O VI to a detection limit of $\log N_{\rm OVI}/{\rm cm^{-2}}\approx13.7$. Meanwhile, only five galaxies or galaxy groups exhibit the Ne VIII $\lambda\lambda$ 770,780 doublet absorption, down to a limiting column density of $\log N_{\rm NeVIII}/{\rm cm^{-2}}\approx14.0$. These O VI- and Ne VIII-bearing halos reside in different galaxy environments with stellar masses ranging from $\log M_{\rm star}/M_\odot \approx 8$ to $\approx11.5$. The warm-hot CGM around galaxies of different stellar masses and star formation rates exhibits different spatial profiles and kinematics. In particular, star-forming galaxies with $\log M_{\rm star}/M_\odot\approx9-11$ show a significant concentration of metal-enriched warm-hot CGM within the virial radius, while massive quiescent galaxies exhibit flatter radial profiles of both column densities and covering fractions. In addition, the velocity dispersion of O VI absorption is broad with $\sigma_v>40$ km/s for galaxies of $\log M_{\rm star}/M_\odot>9$ within the virial radius, suggesting a more dynamic warm-hot halo around these galaxies. Finally, the warm-hot CGM probed by O VI and Ne VIII is suggested to be the dominant phase in sub-$L^*$ galaxies with $\log M_{\rm star}/M_\odot\approx9-10$ based on their high ionization fractions in the CGM.
Use of bamboo (Bambusa balcooa) as reinforcement in concrete beam

In this study concrete beams were tested where a bamboo (Bambusa balcooa) was used as both flexural and shear reinforcement, keeping other physical parameters constant. Eight singly reinforced beams were used in flexure test. Two beams were prepared to use bamboo externally as flexural reinforcement. And four beams were prepared for shear test. Keeping other physical parameters constant the variables were flexural and shear reinforcement. The maximum 2.43 times more load with respect to the non-reinforced beams was taken by the beams where bamboo was used as flexural reinforcement, the maximum 3.93 times more load with respect to the non-reinforced beams was taken by the beams where bamboo was used as shear reinforcement. The results were analysed using the conventional moment equations, shear equations and the equation developed from bond stress. Finally, some designs of bamboo-reinforced beam were done to understand the effectiveness of the findings.
Experiences of mothers of sexually abused children in North-West province, post disclosure

Background Sexual violence against children is increasing at an alarming rate in South Africa. In 2010 the South African Police Service (SAPS) reported 21 538 rape cases of children under 18 years. In the North-West province (NWP) 5039 incidents of rape cases were reported in 2009. Mothers often experience emotional pain following child sexual abuse disclosure. It is seldom acknowledged that these mothers experience trauma and need support, post disclosure. The researcher has no known evidence of research conducted on the experiences of these mothers in NWP. Objective The objective of the study was to explore and describe the experiences of mothers of sexually abused children post disclosure of the abuse. Method The research design was qualitative, exploratory, descriptive and contextual. Purposive sampling was used to select mothers of sexually abused children aged 23 to 59 years whose children ranged from 0 to 16 years. Permission to conduct the study was sought from the Provincial Department of Health and informed consent was obtained from the mothers. Interviews were conducted with a sample of n = 17 until data saturation. Data were collected through in-depth interviews using a voice recorder and field notes to enhance triangulation. Tesch’s method of open coding was used to analyse data. Results Findings indicated that mothers experienced emotional pain post sexual abuse. They expressed shock, anger and guilt for not noticing the abuse. They showed significant depression as a result of lack of support by stakeholders. Conclusion Mothers experienced secondary trauma that poses social and psychological challenges with far-reaching implications.
Sentiment Polarity Extension for Context-Sensitive Recommender Systems

Opinion mining has become an important field of text mining. The limitations in case of supervised learning refer to domain dependence: a solution is highly dependent (if not specifically designed or at least specifically tuned) on a given data set (or at least specific domain). Our method is an attempt to overcome such limitations by considering the generic characteristics hidden in textual information. We aim to identify the sentiment polarity of documents that are part of different domains with the help of a uniform, cross-domain representation. It relies on three classes of original meta-features that can be used to characterize datasets belonging to various domains. We evaluate our approach using three datasets extensively used in the literature. The results for in-domain and cross-domain verification show that the proposed approach handles novel domains increasingly better as its training corpus grows, thus inducing domain-independence.
A novel approach to register sonar data for underwater robot localization

This paper proposes a novel approach to perform underwater robot localization using sonar data. The proposal relies on two key points: 1) the processing of the sonar measurements to build probabilistic point clouds; and 2) the registration of these point clouds. These key points are achieved by means of an acoustic model that removes the effects of the uneven ensonification followed by a probabilistic interpretation of the sonar measurements. Also, a registration algorithm is presented and used to match consecutively gathered scans in order to globally localize an autonomous underwater vehicles (AUV).
Recrafting Rights over Common Property Resources in Mexico*

I. Endogenous Evolution of Land Rights The propositions of Ester Boserup and the Property Rights School have dominated thinking about the endogenous evolution of land rights from open access to individual property. According to these views, there are two fundamental changes that push toward the privatization of a resource. One is its rising scarcity associated with population growth. The other is the rising value of the resource associated with greater market integration and the commercialization of agriculture. As long as there was land abundance and the resource had little commercial value, the marginal cost to current users of entry by an additional user was sufficiently small not to be worth opposing, and the magnitude of the externalities imposed in extraction by each user on all others was insignificant, making it not worth controlling. As the scarcity and value of the resource increases, changing property rights to regulate entry and to internalize the externality imposed by other users becomes profitable. Regulating entry requires transformation of the resource from open access to common property or to private property, limiting in each case access of the resource to a well-defined group of users. Internalizing externalities requires choosing between two options. One is to cooperate in the management of the common property resource (CPR) by introducing and enforcing rules that deter opportunism in the provision of services to the CPR and in the appropriation of resources from the CPR. The other is to divide the CPR among members of the community, either in subcoalitions where cooperation may prevail more easily or in individual allotments. The default option prevails when there is failure to enclose, failure to cooperate in the management of the CPR, and failure to enforce individual
Parallel trade of pharmaceuticals: The Danish market for statins

This paper investigates and quantifies the impact of parallel trade in markets for pharmaceuticals. The paper develops a structural model of demand and supply using data on price, sales, and the characteristics of statins in Denmark and simulates outcomes under a complete ban of parallel imports, keeping other regulatory schemes unchanged. There are two sets of key results. The first set focuses on price effects. On average, prices increase more in markets where the molecule has lost patent protection; wholesale prices for both generic and original products increase after competition from parallel importers is removed, but the final price paid by consumers (after deducting reimbursement) increases more for original products than for generics because most changes in wholesale prices are absorbed by the prevailing reimbursement rules. The second set of results reports the effects on market participants. My model takes into consideration consumers' preferences, allowing them to substitute between products. Prohibiting parallel imports induces consumers to substitute towards original products for which they have stronger preferences. In sum, banning parallel imports leads to (a) an increase in variable profits for original producers and a decrease for generic firms, (b) an increase in governmental health-care expenditures, and (c) a decrease in the welfare of Danish patients and firms.
Design and development of anisotropic laminate scaffolds of electrospun polycaprolactone for annulus fibrosus tissue engineering applications

In several cases, current therapies available to treat a large number of musculoskeletal system diseases are unsatisfactory as they provide only temporary or partial restoration of the damaged or degenerated site. In an attempt to maintain a high standard of life quality and minimise the economic losses due to the treatments of these frequently occurring ailments and subsequent lost working days, alternative therapies are being explored. Contrary to the current treatments, tissue engineering aims to regenerate the impaired tissue rather than repair and alleviate the symptoms; thus offering a definitive solution. The annulus fibrosus (AF) of the intervertebral disc (IVD) is a musculoskeletal system component frequently subjected to degeneration and rupture, characterised by predominance of anisotropically arranged collagen fibres. In the present thesis, electrospinning technology is used to fabricate polycaprolactone (PCL) scaffolds intended to replicate the anisotropic structure of the AF. [Continues. ]
Revealing Neurocomputational Mechanisms of Reinforcement Learning and Decision-Making With the hBayesDM Package

Reinforcement learning and decision-making (RLDM) provide a quantitative framework and computational theories, with which we can disentangle psychiatric conditions into basic dimensions of neurocognitive functioning. RLDM offer a novel approach to assess and potentially diagnose psychiatric patients, and there is growing enthusiasm on RLDM and Computational Psychiatry among clinical researchers. Such a framework can also provide insights into the brain substrates of particular RLDM processes as exemplified by model-based functional magnetic resonance imaging (fMRI) or electroencephalogram (EEG). However, many researchers often find the approach too technical and have difficulty adopting it for their research. Thus, there remains a critical need to develop a user-friendly tool for the wide dissemination of computational psychiatric methods. We introduce an R package called hBayesDM (hierarchical Bayesian modeling of Decision-Making tasks), which offers computational modeling on an array of RLDM tasks and social exchange games. The hBayesDM package offers state-of-the-art hierarchical Bayesian modeling, where both individual and group parameters (i.e., posterior distributions) are estimated simultaneously in a mutually constraining fashion. At the same time, it is extremely user-friendly: users can perform computational modeling, output visualization, and Bayesian model comparisons–each with a single line of coding. Users can also extract trial-by-trial latent variables (e.g., prediction errors) required for model-based fMRI/EEG. With the hBayesDM package, we anticipate that anyone with minimal knowledge of programming can take advantage of cutting-edge computational modeling approaches and investigate the underlying processes of and interactions between multiple decision-making (e.g., goal-directed, habitual, and Pavlovian) systems. In this way, it is our expectation that the hBayesDM package will contribute to the dissemination of advanced modeling approaches and enable a wide range of researchers to easily perform computational psychiatric research within their populations.
Dysregulation of spliceosome gene expression in advanced prostate cancer by RNA-binding protein PSF

Significance Elevated downstream signals of androgen receptor (AR) and its variants are important for prostate cancer progression. We show that an RNA-binding transcriptional and splicing factor, splicing factor proline and glutamine-rich (PSF/SFPQ), predicts worse prognosis of prostate cancer patients. Inhibition of PSF expression repressed treatment-resistant prostate tumor growth in our animal model. Our global analysis of PSF-binding RNAs revealed that PSF enhances AR-regulated genes and noncoding RNAs associated with prostate cancer progression. Interestingly, various splicing factors, which are primary targets of PSF, are upregulated in metastatic prostate tumors. These enhanced factors form complexes with PSF to promote AR expression and splicing. Our findings suggest a role of RNA-binding protein for AR activation for prostate cancer progression. Developing therapeutic approaches are necessary for treating hormone-refractory prostate cancer. Activation of androgen receptor (AR) and its variants’ expression along with the downstream signals are mostly important for disease progression. However, the mechanism for marked increases of AR signals and its expression is still unclear. Here, we revealed that various spliceosome genes are aberrantly induced by RNA-binding protein PSF, leading to enhancement of the splicing activities for AR expression. Our high-speed sequence analyses identified global PSF-binding transcripts. PSF was shown to stabilize and activate key long noncoding RNAs and AR-regulated gene expressions in prostate cancer cells. Interestingly, mRNAs of spliceosome-related genes are putative primary targets of PSF. Their gene expressions are up-regulated by PSF in hormone-refractory prostate cancer. Moreover, PSF coordinated these spliceosome proteins to form a complex to promote AR splicing and expression. Thus, targeting PSF and its related pathways implicates the therapeutic possibility for hormone-refractory prostate cancer.