Miracle-dz/UniFAR-FTUs huggingface dataset:
Biorefining of platinum group metals from model waste solutions into catalytically active bimetallic nanoparticles

Bacteria can fabricate platinum group metal (PGM) catalysts cheaply, a key consideration of industrial processes and waste decontaminations. Biorecovery of PGMs from wastes is promising but PGM leachates made from metallic scraps are acidic. A two‐step biosynthesis ‘pre‐seeds’ metallic deposits onto bacterial cells benignly; chemical reduction of subsequent metal from acidic solution via the seeds makes bioscaffolded nanoparticles (NPs). Cells of Escherichia coli were seeded using Pd(II) or Pt(IV) and exposed to a mixed Pd(II)/Pt(IV) model solution under H2 to make bimetallic catalyst. Its catalytic activity was assessed in the reduction of Cr(VI), with 2 wt% or 5 wt% preloading of Pd giving the best catalytic activity, while 1 wt% seeds gave a poorer catalyst. Use of Pt seeds gave less effective catalyst in the final bimetallic catalyst, attributed to fewer and larger initial seeds as shown by electron microscopy, which also showed a different pattern of Pd and Pt deposition. Bimetallic catalyst (using cells preloaded with 2 wt% Pd) was used in the hydrogenation of soybean oil which was enhanced by ~fourfold using the bimetallic catalyst made from a model waste solution as compared to 2 wt% Pd preloaded cells alone, with a similar selectivity to cis C18:1 product as found using a Pd‐Al2O3 commercial catalyst.
Multi-Criteria Virtual Machine Placement in Cloud Computing Environments: A literature Review

Cloud computing is a revolutionary process that has impacted the manner of using networks. It allows a high level of flexibility as Virtual Machines (VMs) run elastically workloads on physical machines in data centers. The issue of placing virtual machines (VMP) in cloud environments is an important challenge that has been thoroughly addressed, although not yet completely resolved. This article discusses the different problems that may disrupt the placement of VMs and Virtual Network Functions (VNFs), and classifies the existing solutions into five major objective functions based on multiple performance metrics such as energy consumption, Quality of Service, Service Level Agreement, and incurred cost. The existing solutions are also classified based on whether they adopt heuristic, deterministic, meta-heuristic or approximation algorithms. The VNF placement in 5G network is also discussed to highlight the convergence toward optimal usage of mobile services by including NFV/Software-Defined-Network technologies.
Is there an association between PAWP/WBP2NL sequence, expression, and distribution in sperm cells and fertilization failures in ICSI cycles?

Successful fertilization in mammals depends on the sperm's ability to initiate intracellular Ca2+ oscillations in the egg, a phenomenon that is elicited by Sperm‐oocyte activating factors (SOAFs), whose quantitative and/or qualitative defect might result in fertilization failure. One such proposed factor is Post‐acrosomal WW domain‐binding protein (PAWP/WBP2NL), although its ability to activate human oocytes has been questioned and its implication in human fertilization failure remains unknown. Here, we sought to determine if PAWP/WBP2NL expression and distribution in sperm cells associate with low/complete fertilization failure in males participating in intracytoplasmic sperm injection (ICSI) cycles. This prospective study was conducted on eight couples referred for elective ICSI with either the woman's own (n = 4) or a donor eggs (n = 4). Eight sperm donor samples used in ICSI, which resulted in normal fertilization rates, were used as the control group. For each male patient and donor sperm, PAWP/WBP2NL sequence, protein expression, and cellular distribution were analyzed by PCR amplification‐sequencing, Western blot, and immunofluorescence, respectively. PAWP/WBP2NL was present in all samples, and no significant differences were detected between patients with fertilization failure and donors in sequence variants or mean protein expression, or in the proportion of PAWP/WBP2NL‐positive sperm. In conclusion, no clear association between PAWP/WBP2NL protein expression in sperm and fertilization outcome in ICSI were observed from this cohort.
The Influence of Nurses' Demographics on Patient Participation in Hospitals: A Cross‐Sectional Study

BACKGROUND Patient participation is an important issue in contemporary healthcare as it improves quality of care and enhances positive health outcomes. The participation of patients is mainly initiated by the nurses' willingness to share their power and responsibility, but knowledge on nurses' demographic characteristics influencing this behavior is nonexistent. This knowledge is essential to understand and improve patient participation. AIM To determine if nurses' demographic characteristics influence their willingness to engage in patient participation. METHODS A cross-sectional multicenter study in 22 general and three university hospitals with 997 nurses was performed. The Patient Participation Culture Tool for healthcare workers, which measures patient participation behavior, was used. Multilevel analysis, taking into account the difference in wards and hospitals, was used to identify the influence of demographic characteristics. RESULTS A position as supervisor (range: p < .001-.028) and a higher level of education (range: p = <.001-.012) show significant higher scores. Younger nurses seem to be more reluctant in accepting a collaborative patient role (p = .002) and coping with more active patient behavior (p < .001). This new role was less accepted by nurses on geriatric wards (p = .013), who also showed less sharing of information with their patients (p < .001). LINKING EVIDENCE TO ACTION Age and level of education influence nurses' willingness to share power and responsibility with their patients, perhaps indicating that patient participation behavior is an advanced nursing skill and multifaceted interventions, are needed for optimal implementation. Moreover, supervising nurses have different perceptions on patient participation and possibly regard patient participation as an easier task than their team members. This could lead to misunderstandings about the expectations toward patient participation in daily practice, leading to struggles with their nursing staff. Both findings implicate that implementing patient participation on a wide scale is more difficult than expected, which is conflicting with the widespread societal demand for more participation.
The sink or SWIM hypothesis; a roadmap from pathology to work instability

Abstract Purpose: Selecting the most appropriate health-related work outcome to evaluate an intervention can be fraught with difficulty. To aid clinicians in navigating this problem we have developed a model, which illustrates how pathology can affect specific measureable quantities, such as work instability. Methods: Using a modified-Delphi procedure, a panel of experts met initially to analyze the content of 95 health-related work outcome measures and organize the identified areas of measurement into a coherent model, complemented by a narrative review of the literature. This initial model underwent two rounds of stakeholder-based feedback, the results of which were incorporated in the final expert panel meeting to produce the States-traits Work Instability Model (SWIM). Results: The States-traits Work Instability Model (SWIM) illustrates how changes to an individual’s physical and psychological states and traits might affect their work-related performance, well-being and self-efficacy. Moreover, each concept utilized in the model was specifically selected as it represents a measurable quantity, for which there are tools available. Conclusion: The SWIM is arguably the first holistic model of work that is based on both the clinical realities of vocational rehabilitation, sociological research, and is born from analyzing the basis of practical measurements. Implications for Rehabilitation Work Instability • Work instability has multiple causes many of which are amenable to intervention • The model clarifies the measureable domains of vocational rehabilitation interventions, which is of particular benefit for services working with people with disability at work who are struggling to remain in work • The model conceptualizes how the potential areas for intervention may be related based on evidence available in the literature.
A computational technique for the robust root locus

In this paper, the authors present a modified method for generating multiparameter root loci of both continuous and discrete time systems. A more practical computational method for plotting the robust root locus is developed. The graph of the locations of the poles of the transfer function of the closed-loop system corresponding to each gain can be plotted readily and accurately with this method. The sensitivity of poles to the coefficients of the characteristic polynomial can thus be examined, and the appropriate tuning gain selected to achieve a better robustness. Also, a stricter bound of the zeros of the characteristic polynomial is given to further reduce the complexity of the computation of the robust root locus. The technique is applied to the design of robotic manipulators. Simulations of controller design for the PUMA 762 robot disk grinding process are included. >
Ultrasound-targeted microbubbles combined with a peptide nucleic acid binding nuclear localization signal mediate transfection of exogenous genes by improving cytoplasmic and nuclear import

The development of an efficient delivery system is critical for the successful treatment of cardiovascular diseases using non-viral gene therapies. Cytoplasmic and nuclear membrane barriers reduce delivery efficiency by impeding the transfection of foreign genes. Thus, a gene delivery system capable of transporting exogenous genes may improve gene therapy. The present study used a novel strategy involving ultrasound-targeted microbubbles and peptide nucleic acid (PNA)-binding nuclear localization signals (NLS). Ultrasound-targeted microbubble destruction (UTMD) and PNA-binding NLS were used to improve the cytoplasmic and nuclear importation of the plasmid, respectively. Experiments were performed using antibody-targeted microbubbles (AT-MCB) that specifically recognize the SV40T antigen receptor expressed on the membranes of 293T cells, resulting in the localization of ultrasound microbubbles to 293T cell membranes. Furthermore, PNA containing NLS was inserted into the enhanced green fluorescent protein (EGFP)-N3 plasmid DNA (NLS-PNA-DNA), which increased nuclear localization. The nuclear import and gene expression efficiency of the AT-MCB with PNA-binding NLS were compared with AT-MCB alone or a PNA-binding NLS. The effect of the AT-MCB containing PNA-binding NLS on transfection was investigated. The ultrasound and AT-MCB delivery significantly enhanced the cytoplasmic intake of exogenous genes and maintained high cell viability. The nuclear import and gene expression of combined microbubble- and PNA-transfected cells were significantly greater compared with cells that were transfected with AT-MCB or DNA with only PNA-binding NLS. The quantity of EGFP-N3 plasmids in the nuclei was increased by >5.0-fold compared with control microbubbles (CMCB) and NLS-free plasmids. The gene expression was ~1.7-fold greater compared with NLS-free plasmids and 1.3-fold greater compared with control microbubbles. In conclusion, UTMD combined with AT-MCB and a PNA-binding NLS plasmid significantly improved transfection efficiency by increasing cytoplasmic and nuclear DNA import. This method is a promising strategy for the noninvasive and effective delivery of target genes or drugs for the treatment of cardiovascular diseases.
V-Cycle Multigrid for Cell-Centered Finite Differences

We introduce and analyze a V-cycle multigrid algorithm for cell-centered finite difference methods applied to second-order elliptic boundary value problems. Unlike conventional cell-centered multigrid algorithms that use the natural injection operator for prolongation, we use a new prolongation operator whose energy norm we prove is bounded by 1 in the constant coefficient case and 1+Ch in the nonconstant case. We are thus able to use general finite element multigrid theory to conclude that the V-cycle either converges well or serves as a reasonably good preconditioner, respectively. While our theory does not establish optimal performance, our numerical experiments do show that the resulting algorithm converges much faster than the conventional schemes. In fact, these results show that the energy norm convergence factor is small and remains bounded uniformly in the finest mesh size, while that of the conventional algorithm grows.
Pitfalls in supermatrix phylogenomics

In the mid-2000s, molecular phylogenetics turned into phylogenomics, a development that improved the resolution of phylogenetic trees through a dramatic reduction in stochastic error. While some then predicted “the end of incongruence”, it soon appeared that analysing large amounts of sequence data without an adequate model of sequence evolution amplifies systematic error and leads to phylogenetic artefacts. With the increasing flood of (sometimes low-quality) genomic data resulting from the rise of high-throughput sequencing, a new type of error has emerged. Termed here “data errors”, it lumps together several kinds of issues affecting the construction of phylogenomic supermatrices (e.g., sequencing and annotation errors, contaminant sequences). While easy to deal with at a single-gene scale, such errors become very difficult to avoid at the genomic scale, both because hand curating thousands of sequences is prohibitively time-consuming and because the suitable automated bioinformatics tools are still in their infancy. In this paper, we first review the pitfalls affecting the construction of supermatrices and the strategies to limit their adverse effects on phylogenomic inference. Then, after discussing the relative non-issue of missing data in supermatrices, we briefly present the approaches commonly used to reduce systematic error.
Agent‐Based Web Services Framework and Development Environment

The current Web services technologies have not exploited sufficient semantics and approaches to dynamic service‐oriented operations in open environments. This paper argues that such operations can be realized through agent‐oriented interaction approaches. The key challenge is to develop an integration framework for the two paradigms, agent‐ and service‐oriented, in a way that capitalizes on their individual strengths. This paper proposes the notion of agent‐based Web services (AWS). We address several critical issues, including the appropriate architectural framework and the structure of its main elements (agent‐based Web services), their meta‐model, supporting technologies, integration method, and implementation approach. An integrated development environment for this framework called SOAStudio has been developed and tested by implementing a case study of a reverse auction e‐marketplace.
Physical-Layer Security with Multiuser Scheduling in Cognitive Radio Networks

In this paper, we consider a cognitive radio network that consists of one cognitive base station (CBS) and multiple cognitive users (CUs) in the presence of multiple eavesdroppers, where CUs transmit their data packets to CBS under a primary user's quality of service (QoS) constraint while the eavesdroppers attempt to intercept the cognitive transmissions from CUs to CBS. We investigate the physical-layer security against eavesdropping attacks in the cognitive radio network and propose the user scheduling scheme to achieve multiuser diversity for improving the security level of cognitive transmissions with a primary QoS constraint. Specifically, a cognitive user (CU) that satisfies the primary QoS requirement and maximizes the achievable secrecy rate of cognitive transmissions is scheduled to transmit its data packet. For the comparison purpose, we also examine the traditional multiuser scheduling and the artificial noise schemes. We analyze the achievable secrecy rate and intercept probability of the traditional and proposed multiuser scheduling schemes as well as the artificial noise scheme in Rayleigh fading environments. Numerical results show that given a primary QoS constraint, the proposed multiuser scheduling scheme generally outperforms the traditional multiuser scheduling and the artificial noise schemes in terms of the achievable secrecy rate and intercept probability. In addition, we derive the diversity order of the proposed multiuser scheduling scheme through an asymptotic intercept probability analysis and prove that the full diversity is obtained by using the proposed multiuser scheduling.
Adaptive Sampling Scheme for Learning in Severely Imbalanced Large Scale Data

Imbalanced data poses a serious challenge for many machine learning and data mining applications. It may significantly affect the performance of learning algorithms. In digital marketing applications, events of interest (positive instances for building predictive models) such as click and purchase are rare. A retail website can easily receive a million visits every day, yet only a small percentage of visits lead to purchase. The large amount of raw data and the small percentage of positive instances make it challenging to build decent predictive models in a timely fashion. In this paper, we propose an adaptive sampling strategy to deal with this problem. It efficiently returns high quality training data, ensures system responsiveness and improves predictive performances.
Glutamate: a major excitatory transmitter in neuroendocrine regulation.

Excitatory amino acids (EAAs), such as glutamate and aspartate, are found in large concentrations in presynaptic boutons of a variety of important hypothalamic nuclei, including the arcuate nucleus, supraoptic nucleus, suprachiasmatic nucleus, paraventricular nucleus, organum vasculosa of the lamina terminalis (OVLT) and preoptic area (POA). Likewise, the different ionotropic/metabotropic EAA receptor subtypes are found in the same regions of the hypothalamus although there are differences in their individual patterns of localization. Furthermore, there is evidence supporting the presence of ionotropic N-methyl-D-aspartate (NMDA) receptors and non-NMDA (kainate and AMPA) receptors in the anterior lobe, intermediate lobe and posterior lobe of the pituitary. The majority of work to date has focused on the role of EAAs in the control of LH secretion. Administration of glutamate, NMDA, kainate or AMPA leads to rapid LH release mediated through the stimulation of hypothalamic GnRH release. The major site of NMDA action appears to be the OVLT/preoptic area--where GnRH cell bodies reside, whereas AMPA and kainate have been suggested to act primarily at the arcuate nucleus/median eminence--the site of GnRH nerve terminals. There is evidence that some of the effects of glutamate on GnRH release may involve activation of the novel neurotransmitter nitric oxide and possibly catecholamines. The physiological importance of EAAs in the control of LH surge expression is evidenced by the findings that the steroid-induced LH surge in ovariectomized animals and the preovulatory LH surge in cycling animals and in PMSG-primed animals is blocked by treatment with specific NMDA receptor antagonists, or non-NMDA receptor antagonists. EAAs also appear to be important in regulating the normal pulsatile pattern of LH release as evidenced by the finding that both the NMDA antagonist, AP5, and the AMPA/kainate antagonist, DNQX, lower mean LH levels, LH pulse amplitude and LH pulse frequency in the adult ovariectomized rat. A role for NMDA receptors in the achievement of puberty has been suggested since activation of NMDA receptors has been shown to advance the time of vaginal opening in the immature female rat, while kainate and DNQX were without effect. Steroids have been reported not to affect NMDA receptor binding in the hypothalamus; however, steroids appear to up-regulate AMPA receptor GluR1 subunit levels and non-NMDA receptor binding in the hypothalamus. Steroids also increase the release rates of glutamate and aspartate in the POA during the steroid-induced LH surge in the ovariectomized adult rat. (ABSTRACT TRUNCATED AT 400 WORDS)
Earn to P Ay a Ttention

We propose an end-to-end-trainable attention module for convolutional neural network (CNN) architectures built for image classification. The module takes as input the 2D feature vector maps which form the intermediate representations of the input image at different stages in the CNN pipeline, and outputs a 2D matrix of scores for each map. Standard CNN architectures are modified through the incorporation of this module, and trained under the constraint that a convex combination of the intermediate 2D feature vectors, as parameterised by the score matrices, must alone be used for classification. Incentivised to amplify the relevant and suppress the irrelevant or misleading, the scores thus assume the role of attention values. Our experimental observations provide clear evidence to this effect: the learned attention maps neatly highlight the regions of interest while suppressing background clutter. Consequently, the proposed function is able to bootstrap standard CNN architectures for the task of image classification, demonstrating superior generalisation over 6 unseen benchmark datasets. When binarised, our attention maps outperform other CNN-based attention maps, traditional saliency maps, and top object proposals for weakly supervised segmentation as demonstrated on the Object Discovery dataset. We also demonstrate improved robustness against the fast gradient sign method of adversarial attack.
fMRI Evidence for a Cortical Hierarchy of Pitch Pattern Processing

Pitch patterns, such as melodies, consist of two levels of structure: a global level, comprising the pattern of ups and downs, or contour; and a local level, comprising the precise intervals that make up this contour. An influential neuropsychological model suggests that these two levels of processing are hierarchically linked, with processing of the global structure occurring within the right hemisphere in advance of local processing within the left. However, the predictions of this model and its anatomical basis have not been tested in neurologically normal individuals. The present study used fMRI and required participants to listen to consecutive pitch sequences while performing a same/different one-back task. Sequences, when different, either preserved (local) or violated (global) the contour of the sequence preceding them. When the activations for the local and global conditions were contrasted directly, additional activation was seen for local processing in right planum temporale and posterior superior temporal sulcus (pSTS). The presence of additional activation for local over global processing supports the hierarchical view that the global structure of a pitch sequence acts as a “framework” on which the local detail is subsequently hung. However, the lateralisation of activation seen in the present study, with global processing occurring in left pSTS and local processing occurring bilaterally, differed from that predicted by the neuroanatomical model. A re-examination of the individual lesion data on which the neuroanatomical model is based revealed that the lesion data equally well support the laterality scheme suggested by our data. While the present study supports the hierarchical view of local and global processing, there is an evident need for further research, both in patients and neurologically normal individuals, before an understanding of the functional lateralisation of local and global processing can be considered established.