Miracle-dz/UniFAR-FTUs huggingface dataset:
Bioaccumulation of some trace element (Zn, Fe, Pb and Cu) in the gills and tissues of Clarias gariepinus and Oreochromis niloticus in River Ogbese, Ondo State, Nigeria

River Ogbese support many human activities (domestic, agricultural, fishing, industrial activities) leading to its extensive contamination and accumulation of heavy metals which can cause both environmental and public health hazard. In order to ascertain the quality of the river, a study was carried out to determine some trace element concentration (Zn, Fe, Pb and Cu) in gills and tissues of Clarias gariepinus and Oreochromis niloticus, being the most dominant fish species in the water body. Thus, ten samples each of C. gariepinus (21.0 – 37.4TL, 171.7 – 305.8 g) and O. niloticus (15.2 – 20.6 TL, 70.8 – 150.5 g) were collected from River Ogbese and the concentration of Zinc, Iron, Lead and Copper were analyzed both in the gills and the flesh using atomic absorption spectrophotometry (AAS). The study revealed that the highest concentration of iron was obtained in the gills and tissues of both fishes; C. gariepinus (gill - 6.70-4.23±0.72, tissue - 6.84 - 5.27±0.44) and O. niloticus (gill - 6.79 - 1.89±1.42, tissue - 5.83-4.27±0.58). The metal concentration occurred in the order Fe>Zn>Cu>Pb. In general, accumulation of the essential elements; Zn, Fe, Cu were higher than the non-essential elements; Pb. This could be due to the fact that these essential elements are naturally abundant in Nigeria soil. The bioaccumulation of zinc and lead are significant (P>0.05) in the tissues of both species while iron varies significantly (P>0.05) in their gills. There is no significant variation (P<0.05) observed among zinc, lead and copper accumulated in the gills of both species. Key words: River Ogbese, heavy metals, Clarias gariepinus and Oreochromis niloticus.
BASIC PRINCIPLES OF DYNAMIC PSYCHIATRY

It would be far easier if we could avoid the patient as we explore the realm of psychopathology; it would be far simpler if we could limit ourselves to examining the chemistry and physiology of his brain, and to treating mental events as objects alien to our immediate experience, or as mere variables in impersonal statistical formulae. Important as these approaches are for the understanding of human behavior, they cannot alone uncover or explain all the relevant facts. To see into the mind of another, we must repeatedly immerse ourselves in the flood of his associations and feelings; we must be ourselves the instrument that sounds him.
Humanistic Care in Nursing: Concept Analysis Using Rodgers' Evolutionary Approach

Background: Despite the importance and prominent role as a clinical, theoretical, and research approach in nursing practice, humanistic care nature and boundaries are not explicit and challenging for nurses to understand. This study was conducted to clarify the concept of humanistic care in nursing. Materials and Methods: Based on Rogers's evolutionary concept analysis, keywords such as “humanistic car *,” “caring behave *,” “humanistic nurs *,” “humanistic model of care,” were searched in PubMed, SCOPUS, Science Direct, Web of Science, WILEY, Springer, SAGE, ProQuest, SID, Iranmedex without time limit until November 2018. Sixty-five documents in nursing and ten documents in the medical discipline were finalized for thematic analysis. Results: Nine attributes of the humanistic care, including “excellence in clinical literacy,” “creating a healing environment,” “a comprehensive and unique viewpoint,” “contribution to clients' adaptation and flourishing of their talents,” “unrequited love and affection,” “preservation of human dignity,” “real presence,” “constructive dynamic interaction,” and “nurse's self-care,” were recognized. Assessing the historical and evolutionary course of the concept's semantic tendency revealed three periods: The focus in first, second, and third was on the nurse-patient relationship, quantitative tendency/measurement, and metaphysics/spiritual humanism, respectively. The comparison of interdisciplinary differences indicated greater semantic comprehensiveness and depth in the nursing discipline. Conclusions: Clear and practical definition and identification of humanistic care in nursing can be helpful in the further development of existing knowledge, instrumentation, designing guidelines, clinical interventions, knowledge translation, and correction of concept misuse. The identified antecedents and consequences can be in various aspects of clinical management.
An Investigation on the Application of the Technology Acceptance Model (TAM) to Evaluate the Adoption of ERP Solutions in MSMEs of Odisha

: Micro, Small and Medium Enterprises (MSMEs) have played a vital role in economic development of India. MSME in India has the potential to increase the share of contribution to GDP from the current 8 per cent to about 15 per cent by the year 2020. Despite the prevalence of computing in all aspects of society, some computer systems may not be fully accepted by their intended users or become underutilized. ERP systems have become the most common IT strategy for most large companies but still many small companies have not used it yet in their organisations. ERP (Enterprise Resource Planning) is a way to integrate the data and processes of an organization into one single system. Its main goal is to integrate data and processes from all areas of the organization and unify it, to provide ease of access and an efficient work flow. Thus, acceptance and use of information technologies in MSMEs remain a paramount issue in information systems (IS) research and practice. Extending previous research by integrating computer self-efficacy, Prior experience, technical support and subjective norms as external variables to the technology acceptance model (TAM), this study examines the direct and indirect effects of these factors on ERP system acceptance and use. The results indicated that external variables had significant direct effects on perceived usefulness and perceived ease of use as well as indirect effects on attitude and behavioral intention. However, the effect of perceived ease of use on attitude was stronger than that of perceived usefulness. In turn, attitude demonstrated a negligible impact on behavioural intention. These findings highlight several implications for research and practice.
Comparative Study of the Effect of Three Oral Care Protocols on Ventilator-Associated Pneumonia in Critically Ill Patients: A Clinical Trial

Background: Oral care plays a significant role in reducing the incidence of Ventilator-Associated Pneumonia (VAP) in Intensive Care Units (ICUs). The aim of this study was to investigate the effect of three oral care protocols on the incidence of VAP in Mechanically-Ventilated (MV) patients hospitalized in ICUs. Materials and Methods: This parallel randomized clinical trial was performed in 2019 on 71 MV adult patients with endotracheal intubation hospitalized in ICUs. The patients were divided into three groups: a 7-day oral care by using swab (group 1), two-times-brushing group (group 2), and four-times-brushing group (group 3) by using chlorhexidine. The data related to the incidence of pneumonia were analyzed during several days using Chi-square and ANOVA tests. Results: The incidence of pneumonia on the fourth day of the intervention in the first group (35.00%) was significantly higher than that of the two intervention groups (10.00%) (χ2 = 5.86, df = 2, p = 0.03)). The mean score of modified clinical pulmonary infection in the third group was significantly lower seven days after the intervention than before the intervention (p = 0.04) and the fourth day of intervention (p = 0.003). In the first group, this score was significantly higher in the fourth day of the intervention than the seventh day (p = 0.003). Conclusions: Based on the results, the oral care protocol, including four-times-brushing, reduced the risk of VAP more than two times brushing. Therefore, the use of this protocol is recommended to provide a minimum level of oral care and reduce the risk of VAP in MV patients.
A parallel sampling algorithm for inverse problems with linear and nonlinear unknowns

We derive a parallel sampling algorithm for computational inverse problems that present an unknown linear forcing term and a vector of nonlinear parameters to be recovered. It is assumed that the data is noisy and that the linear part of the problem is ill-posed. The vector of nonlinear parameters m is modeled as a random variable. A dilation parameter alpha is used to scale the regularity of the linear unknown and is also modeled as a random variable. A posterior probability distribution for (m; alpha) is derived following an approach related to the maximum likelihood regularization parameter selection [5]. A major difference in our approach is that, unlike in [5], we do not limit ourselves to the maximum likelihood value of alpha. We then derive a parallel sampling algorithm where we alternate computing proposals in parallel and combining proposals to accept or reject them as in [4]. This algorithm is well-suited to problems where proposals are expensive to compute. We then apply it to an inverse problem in seismology. We show how our results compare favorably to those obtained from the Maximum Likelihood (ML), the Generalized Cross Validation (GCV), and the Constrained Least Squares (CLS) algorithms.
1 . 1 Conceptualising a Costing Model for the Impact of Terrorism

This paper estimates the economic impact of terrorism at $US 33 billion in 2018. In the 18 years from 2000 to 2018, terrorism cost the world economy $US 855 billion. Thismodel follows themethodology of the 2019Global Terrorism Index and uses a bottom-up cost accounting approach to aggregate the cost of four indicators that result from the incidents of terrorism. The four indicators include terrorism-related deaths, injuries, property damage and GDP losses. The findings of this paper show that global terrorism peaked in 2014 with 33,555 deaths globally and a consequential economic impact of $US 111 billion. From 2011 to 2014, terrorism-related deaths increased by 353%, and terrorist incidents rose by 190%. The 100 incidents with the highest economic impact from deaths and injuries are included in the analysis. The September 11, 2001 attacks in theUnited States stands as the incident with the highest economic impact accounting for deaths and injuries only at $US 40.6 billion, this is followed by the Sinjar massacre in Sinjar, Nineveh, Iraq at $US 4.3 billion.
Towards Image Data Hiding via Facial Stego Synthesis with Generative Model

Stego synthesis-based data hiding aims to directly produce a plausible natural image to convey secret message. However, most of the existing works neglected the possible communication degradations and forensic actions, which commonly occur in practice. In this paper, we devise a generative adversarial network (GAN)-based framework to synthesize facial stego images. The framework consists of four components: generator, extractor, discriminator and forensic network. Specifically, the generator is deployed to generate a realistic facial stego image from the secret message and key, while the extractor aims at extracting the secret message from the stego image with the provided secret key. To combat forensics, we explicitly integrate a forensic network into the proposed framework, which is responsible for guiding the update of generator. Three degradation layers are further incorporated, enforcing the generator to characterize the communication degradations. Experimental results demonstrate that the proposed framework could accurately extract the secret message and effectively resist the forensic detection and certain degradations, while attaining realistic facial stego images.
SPECIES SPECIFIC DIFFERENCES IN TRANSLATIONAL REGULATION OF DIHYDROFOLATE REDUCTASE

We have observed that rodent cell lines (mouse, hamster) contain approximately 10 times the levels of dihydrofolate reductase as human cell lines, yet the sensitivity to methotrexate (ED50), the folate antagonist that targets this enzyme, is similar. Our previous studies showed that dihydrofolate reductase protein levels increased after methotrexate exposure; and we proposed that this increase was due to the relief of feedback inhibition of translation as a consequence of methotrexate binding to dihydrofolate reductase. In the current report we show that unlike what was observed in human cells, DHFR levels do not increase in hamster cells following methotrexate exposure. We provide evidence to show that although there are differences in the putative mRNA structure between hamster and human mRNA in the dihydrofolate reductase binding region previously identified, “ hamsterization” of this region in human dihydrofolate reductase mRNA did not change the level of the enzyme or its induction by methotrexate. Further experiments showed that human dihydrofolate reductase is a promiscuous enzyme, and that it is the difference between the hamster and human dihydrofolate reductase protein, rather than the DHFR mRNA, that determines the response to methotrexate exposure. We also present evidence to suggest that the translational upregulation of dihydrofolate reductase by MTX in tumor cells is an adaptive mechanism that decreases sensitivity to this drug.
What Language Model to Train if You Have One Million GPU Hours?

The crystallization of modeling methods around the Transformer architecture has been a boon for practitioners. Simple, well-motivated architectural variations can transfer across tasks and scale, increasing the impact of modeling research. However, with the emergence of state-of-the-art 100B+ parameters models, large language models are increasingly expensive to accurately design and train. Notably, it can be difficult to evaluate how modeling decisions may impact emergent capabilities, given that these capabilities arise mainly from sheer scale alone. In the process of building BLOOM--the Big Science Large Open-science Open-access Multilingual language model--our goal is to identify an architecture and training setup that makes the best use of our 1,000,000 A100-GPU-hours budget. Specifically, we perform an ablation study at the billion-parameter scale comparing different modeling practices and their impact on zero-shot generalization. In addition, we study the impact of various popular pre-training corpora on zero-shot generalization. We also study the performance of a multilingual model and how it compares to the English-only one. Finally, we consider the scaling behaviour of Transformers to choose the target model size, shape, and training setup. All our models and code are open-sourced at https://huggingface.co/bigscience .
Parallel introgression and selection on introduced alleles in a native species

As humans cause the redistribution of species ranges, hybridization between previously allopatric species is on the rise. Such hybridization can have complex effects on overall fitness of native species as new allelic combinations are tested. Widespread species introductions provide a unique opportunity to study selection on introgressed alleles in independent, replicated populations. We examined selection on alleles that repeatedly introgressed from introduced rainbow trout (Oncorhynchus mykiss) into native westslope cutthroat trout (Oncorhynchus clarkii lewisi) populations in western Canada. We found that the degree of introgression of individual single nucleotide polymorphisms from the invasive species into the native is correlated between independent watersheds. A number of rainbow trout alleles have repeatedly swept to high frequency in native populations, suggesting parallel adaptive advantages. Using simulations, we estimated large selection coefficients up to 0.05 favoring several rainbow trout alleles in the native background. Although previous studies have found reduced hybrid fitness and genome‐wide resistance to introgression in westslope cutthroat trout, our results suggest that some introduced genomic regions are strongly favored by selection. Our study demonstrates the utility of replicated introductions as case studies for understanding parallel adaptation and the interactions between selection and introgression across the genome. We suggest that understanding this variation, including consideration of beneficial alleles, can inform management strategies for hybridizing species.
Genistein antagonizes gliadin-induced CFTR malfunction in models of celiac disease

In celiac disease (CD), an intolerance to dietary gluten/gliadin, antigenic gliadin peptides trigger an HLA-DQ2/DQ8-restricted adaptive Th1 immune response. Epithelial stress, induced by other non-antigenic gliadin peptides, is required for gliadin to become fully immunogenic. We found that cystic-fibrosis-transmembrane-conductance-regulator (CFTR) acts as membrane receptor for gliadin-derived peptide P31-43, as it binds to CFTR and impairs its channel function. P31-43-induced CFTR malfunction generates epithelial stress and intestinal inflammation. Maintaining CFTR in an active open conformation by the CFTR potentiators VX-770 (Ivacaftor) or Vrx-532, prevents P31-43 binding to CFTR and controls gliadin-induced manifestations. Here, we evaluated the possibility that the over-the-counter nutraceutical genistein, known to potentiate CFTR function, would allow to control gliadin-induced alterations. We demonstrated that pre-treatment with genistein prevented P31-43-induced CFTR malfunction and an epithelial stress response in Caco-2 cells. These effects were abrogated when the CFTR gene was knocked out by CRISP/Cas9 technology, indicating that genistein protects intestinal epithelial cells by potentiating CFTR function. Notably, genistein protected gliadin-sensitive mice from intestinal CFTR malfunction and gliadin-induced inflammation as it prevented gliadin-induced IFN-γ production by celiac peripheral-blood-mononuclear-cells (PBMC) cultured ex-vivo in the presence of P31-43-challenged Caco-2 cells. Our results indicate that natural compounds capable to increase CFTR channel gating might be used for the treatment of CD.
Analysis of the Behavior of WBP to Terminate the Pulmonary TB Transmission Chain in Medan and Lubuk Pakam Prison

Indonesia still holds the 2nd place in terms of the number of TB patients in the world. The prevalence of pulmonary TB in prisons is estimated to be 3 times higher than the general population. According to the report from the Department of Law and Human Rights of Sumatera Utara Province, from 2009 to 2011, the number of new pulmonary TB cases among the residents of prison/correctional facility tended to increase every year, an increase of an average of 7.2%. A research on the behavior of Warga Binaan Pemasyarakatan (WBP) is carried out to terminate the TB transmission (sputum, coughing, smoking, wearing masks, sleeping history and smoking) behavior. The type of this research is cross-sectional with the entire population of WBP in Medan and Lubuk Pakam Prison. The data collection is performed by interview using a questionnaire. The data analysis is conducted by univariate and bivariate. The results show there is a relationship of knowledge with cough behavior (p = 0.011) and wearing mask behavior (p = 0.011), there is a relationship between attitude and sleeping in one room behavior (p = 0.032). There is no relationship between knowledge and attitude with smoking behavior and throwing sputum behavior.
Operational Characteristics of SSDs in Enterprise Storage Systems: A Large-Scale Field Study

As we increasingly rely on SSDs for our storage needs, it is important to understand their operational characteristics in the ﬁeld, in particular since they vary from HDDs. This includes operational aspects, such as the level of write ampliﬁcation experienced by SSDs in production systems and how it is affected by various factors; the effectiveness of wear leveling; or the rate at which drives in the ﬁeld use up their program-erase (PE) cycle limit and what that means for the transition to future generations of ﬂash with lower endurance. This paper presents the ﬁrst large-scale ﬁeld study of key operational characteristics of SSDs in production use based on a large population of enterprise storage systems covering almost 2 million SSDs of a major storage vendor (NetApp).
Blue tits surviving in an ever-changing world

L23 Habitat “naturalness” sounds odd. I’d use level of anthropogenization or something similar instead. L24-25 I would say that ‘populations whose individuals. ’ as talking about the behavior of a population as a whole is somehow controversial. Populations do not exhibit behavior syndromes, individuals do. L38-39 Please, provide the (potential) reason for this decline. It is not clear if these two populations belong to the same habitat type (e.g., evergreen forest) or locality. Introduction: L46 Please, add Oxford (serial) comma after “trends”. L66 I would add a few examples of species or populations with strong density-dependent effects on their dynamics. Material & Methods: L198 The number of nestboxes is rather low in all the studied populations in comparison with other studies in which the number of boxes typically oscillates between 80 and 100. I am just curious about the mean occupation rate and the size of these woodlands (i.e., the number of breeding pairs per ha) (I am sure these details are given in previous studies carried out by the team but I think this info is appropriate for the purposes of the present study). In addition, besides occupation rates, it would be interesting to know if these (concrete? ) nestboxes are used by other species -e.g., great tits, crested tits, nuthatches, rock sparrows-, with
Towards Achieving Adversarial Robustness Beyond Perceptual Limits

The vulnerability of Deep Neural Networks to Adversarial Attacks has fuelled research towards building robust models. While most existing Ad-versarial Training algorithms aim towards defending against imperceptible attacks, real-world ad-versaries are not limited by such constraints. In this work, we aim to achieve adversarial robustness at larger epsilon bounds. We ﬁrst discuss the ideal goals of an adversarial defense algorithm beyond perceptual limits, and further highlight the shortcomings of naively extending existing training algorithms to higher perturbation bounds. In order to overcome these shortcomings, we pro-pose a novel defense, Oracle-Aligned Adversarial Training (OA-AT), that attempts to align the predictions of the network with that of an Oracle during adversarial training. The proposed approach achieves state-of-the-art performance at large epsilon bounds ( (cid:96) ∞ bound of 16 / 255 ) while outper-forming adversarial training algorithms such as AWP, TRADES and PGD-AT at standard perturbation bounds ( (cid:96) ∞ bound of 8 / 255 ) as well.
Improving the Timeliness of Bluetooth Low Energy in Noisy RF Environments

The ability to communicate within given delay bounds in noisy RF environments is crucial for Bluetooth Low Energy (BLE) applications used in safety-critical application domains. In this work, we experimentally study the latency of BLE communications in the presence of radio interference, and show that applications may incur long and unpredictable transmission delays. To mitigate this problem, we devise a model capturing the timeliness of connection-based BLE communications in noisy RF channels by expressing the impact of radio interference in terms of the number of connection events necessary to complete a successful data transmission (nCE ). We show that this quantity can be estimated using the timing information of commands sent over the host controller interface of common BLE devices, hence without additional communication overhead or energy expenditure. We finally show that a BLE application can make use of our model and recent nCE measurements to adapt its connection interval at runtime, improving its performance in the presence of radio interference. Experiments on the popular nRF52840 platform running Zephyr show that a BLE application can effectively increase the timeliness of its communications in noisy RF environments, reducing the number of delayed packets by up to a factor of 40.