Miracle-dz/UniFAR-FTUs huggingface dataset:
Genome report of three novel bacteriophages targeting different multidrug resistant clinical isolates (Escherichia, Klebsiella and Salmonella) from Enterobacteriaceae family

Application of bacteriophages (phages) to treat complex multidrug resistant bacterial infection is gaining traction because of its efficacy and universal availability. However, as phages are specific to their host, a diverse collection of locally isolated phage from various geographical locations is required to formulate a wide host range phage cocktail. Here, we report morphological and genomic features of three newly isolated phages from river water of the urban region in Kathmandu, Nepal, targeting three different bacteria ( Escherichia coli, Klebsiella pneumoniae and Salmonella spp. ) from the Enterobacteriaceae family. Morphological identification and genome analysis indicated that two phages (Escherichia phage vB_EcoM_TU01 and Klebsiella phage vB_KpnP_TU02) were strictly lytic and free from integrases, virulence factors, toxins and known antimicrobial resistance genes whereas Salmonella phage vB_SalS_TU03 was possibly a temperate phage. The genomic features of these phages indicate that natural phages are capable of lysing pathogenic bacteria and have potential to be used therapeutically.
Towards N–N-Doped Carbon Dots: A Combined Computational and Experimental Investigation

The introduction of N doping atoms in the carbon network of Carbon Dots is known to increase their quantum yield and broaden the emission spectrum, depending on the kind of N bonding introduced. N doping is usually achieved by exploiting amine molecules in the synthesis. In this work, we studied the possibility of introducing a N–N bonding in the carbon network by means of hydrothermal synthesis of citric acid and hydrazine molecules, including hydrated hydrazine, di-methylhydrazine and phenylhydrazine. The experimental optical features show the typical fingerprints of Carbon Dots formation, such as nanometric size, excitation dependent emission, non-single exponential decay of photoluminescence and G and D vibrational bands in the Raman spectra. To explain the reported data, we performed a detailed computational investigation of the possible products of the synthesis, comparing the simulated absorbance spectra with the experimental optical excitation pattern. The computed Raman spectra corroborate the hypothesis of the formation of pyridinone derivatives, among which the formation of small polymeric chains allowed the broad excitation spectra to be experimentally observed.
The effects of base rate neglect on sequential belief updating and real-world beliefs

Base-rate neglect is a pervasive bias in judgment that is conceptualized as underweighting of prior information and can have serious consequences in real-world scenarios. This bias is thought to reflect variability in inferential processes but empirical support for a cohesive theory of base-rate neglect with sufficient explanatory power to account for longer-term and real-world beliefs is lacking. A Bayesian formalization of base-rate neglect in the context of sequential belief updating predicts that belief trajectories should exhibit dynamic patterns of dependence on the order in which evidence is presented and its consistency with prior beliefs. To test this, we developed a novel ‘urn-and-beads’ task that systematically manipulated the order of colored bead sequences and elicited beliefs via an incentive-compatible procedure. Our results in two independent online studies confirmed the predictions of the sequential base-rate neglect model: people exhibited beliefs that are more influenced by recent evidence and by evidence inconsistent with prior beliefs. We further found support for a noisy-sampling inference model whereby base-rate neglect results from rational discounting of noisy internal representations of prior beliefs. Finally, we found that model-derived indices of base-rate neglect—including noisier prior representation—correlated with propensity for unusual beliefs outside the laboratory. Our work supports the relevance of Bayesian accounts of sequential base-rate neglect to real-world beliefs and hints at strategies to minimize deleterious consequences of this pervasive bias.
Macro- and Micro-Expressions Facial Datasets: A Survey

Automatic facial expression recognition is essential for many potential applications. Thus, having a clear overview on existing datasets that have been investigated within the framework of face expression recognition is of paramount importance in designing and evaluating effective solutions, notably for neural networks-based training. In this survey, we provide a review of more than eighty facial expression datasets, while taking into account both macro- and micro-expressions. The proposed study is mostly focused on spontaneous and in-the-wild datasets, given the common trend in the research is that of considering contexts where expressions are shown in a spontaneous way and in a real context. We have also provided instances of potential applications of the investigated datasets, while putting into evidence their pros and cons. The proposed survey can help researchers to have a better understanding of the characteristics of the existing datasets, thus facilitating the choice of the data that best suits the particular context of their application.
Antileishmanial Efficacy of the Calpain Inhibitor MDL28170 in Combination with Amphotericin B

The necessity of drug combinations to treat leishmaniasis came to the surface mainly because of the toxicity of current treatments and the emergence of resistant strains. The calpain inhibitor MDL28170 has previously shown anti-Leishmania activity, therefore its use in association with standard drugs could provide a new alternative for the treatment strategy against leishmaniasis. In this study, we analyzed the potential of the combination of MDL28170 and the antileishmanial drug amphotericin B against Leishmania amazonensis and Leishmania chagasi. The compounds were tested in the combination of the ½ × IC50 value of MDL28170 plus the ¼ × IC50 value of amphotericin B, which led to an increment in the anti-promastigote activity when compared to the single drug treatments. This drug association revealed several and severe morphophysiological changes on parasite cells, such as loss of plasma membrane integrity, reduced size of flagellum, and depolarization of mitochondrial membrane potential besides increased reactive oxygen species production. In addition, the combination of both drugs had a deleterious effect on the Leishmania–macrophage interaction, reflecting in a significant anti-amastigote action, which achieved a reduction of 50% in the association index. These results indicate that the combination treatment proposed here may represent a new alternative for leishmaniasis chemotherapy.
Predictors of New-onset Diabetes After Kidney Transplantation During 2019-nCoV Pandemic: A Unison of Frequentist Inference and Narrow AI

BACKGROUND: New-onset diabetes after kidney transplant (NODAT) is a severe metabolic complication that frequently occurs in recipients following transplantation. AIM: The study aims to verify NODAT, compare cases and non-cases of this entity, and explore potential predictors in recipients within 1 year following kidney transplantation. METHODS: The research is a retrospective study of 90 renal transplant recipients (n = 90). Demographic factors and clinical aspects were analyzed using non-Bayesian statistics and machine learning (ML). The clinical aspects included the glycated hemoglobin (HbA1c) level, associated viral infections (hepatitis B virus [HBV], hepatitis C virus [HCV], and cytomegalovirus [CMV]), prior kidney transplant, hemodialysis status, body mass index (BMI) at transplant time, and 3 months later, primary causes of renal failure, and post-transplant therapeutics. All individuals were on cyclosporine and prednisolone treatment. RESULTS: The mean age was 39 (±1.5) years; recipients included 27 females (30%) and 63 males (70%). Donor type was live related (16, 17.8%) or live unrelated (74, 82.2%); 27 recipients (30%) had O+ blood group, while 70% belonged to other groups. Thirteen recipients (14.4%) were not on dialysis. Only 32 individuals (35.6%) developed NODAT. Concerning virology, confirmed by real-time polymerase chain reaction before transplantation, 19 recipients (21.1%) were CMV positive, 9 (10%) were HCV positive, and 2 (2.2%) had HBV. CONCLUSIONS: In reconciliation with frequentist statistics, the dual ML model validated several predictors that either negatively (protective) or positively (harmful) influenced HbA1c level, the majority of which were significant at 95% confidence interval. Individuals who are HCV and CMV positive are predicted to develop NODAT. Further, older individuals, with blood group O+ve, prior history of hemodialysis, a relatively high BMI before the transplant, and receiving higher doses of prednisolone following the transplant are more likely to develop NODAT. The current study represents the first research from Iraq to explore NODAT predictors among kidney transplant recipients using frequentist statistics and artificial intelligence models.
Impacts of Skill Centrality on Regional Economic Productivity and Occupational Income

A well-developed perspective in the study of urban systems is that cities are complex systems that manifest as networks of interdependent economic units. These units might be occupations, industries, labor skills, patent technologies, etc. Much research has focused on describing the nature of these networks, quantifying their links, and suggesting applications for policymakers. In this paper, we examine the US skill network, focusing on the relationship between network centrality and economic performance. Here, nodes are represented by individual labor skills, and edge weights are derived from the colocation pattern of skill pairs among 384 US metropolitan statistical areas. The centrality of skills, using three centrality measures, is then aggregated to the occupational and metropolitan level. We find that occupations with higher skill centrality are associated with greater annual salaries, and metropolitan areas with higher skill centrality have higher productivity rates. Overall, these results suggest that the application of traditional network metrics to this view of cities as complex networks can offer new insights into the dynamics of regional economies.
A Novel Method to Generate UWB Shaping Pulses Based on Compressed Chirp

Based on compressed chirp pulses and the linear superposition of these signals,a novel method to generate ultra wide band(UWB) shaping pulses was proposed.It is flexible and easy to get UWB shaping pulses,which not only can comply with the requirement of a special spectrum mask,but also can suppress the co-channel interference between UWB and the existing narrow band systems.The simulation results show that the power spectral density(PSD) distribution of the UWB shaping pulse is accorded with the federal communications commission(FCC) mask very well,and also has very high spectrum utilization ratio.It needn't to reduce the transmitted power in the whole UWB frequency band to resolve the co-existence problem between UWB and the narrow band communication systems.
Learning Deep Features for Robotic Inference From Physical Interactions

In order to effectively handle multiple tasks that are not predefined, a robotic agent needs to automatically map its high-dimensional sensory inputs into useful features. As a solution, feature learning has empirically shown substantial improvements in obtaining representations that are generalizable to different tasks, compared to feature engineering approaches, but it requires a large amount of data and computational capacity. These challenges are specifically relevant in robotics due to the low signal-to-noise ratios inherent to robotic data, and to the cost typically associated with collecting this type of input. In this article, we propose a deep probabilistic method based on convolutional variational autoencoders (CVAEs) to learn visual features suitable for interaction and recognition tasks. We run our experiments on a self-supervised robotic sensorimotor data set. Our data were acquired with the iCub humanoid and are based on a standard object collection, thus being readily extensible. We evaluated the learned features in terms of usability for: 1) object recognition; 2) capturing the statistics of the effects; and 3) planning. In addition, where applicable, we compared the performance of the proposed architecture with other state-of-the-art models. These experiments demonstrate that our model is capable of capturing the functional statistics of action and perception (i.e., images) which performs better than existing baselines, without requiring millions of samples or any hand-engineered features.
Defects detection and positioning for glass insulator from aerial images

By analyzing the characteristics of the glass insulator and its defects in aerial images of the unmanned aerial vehicle inspection system,a method is presented to extract glass insulator and detect defects.The OTSU's thresholding method is applied to H and S components in Hue,Saturation,Intensity(HSI) color space for image segmentation;and then,the distribution of the contours' angle and area is calculated by using the histogram method to obtain the position of glass insulators accurately.Feature detection algorithm is proposed to detect the glass insulators and mark out the defects.Experimental results indicate that the method can mark the location of the defects accurately in the aerial images with natural background,which has a good practical value.
New procedure to pre-select lactic acid bacteria able to control table-olive fermentation

Using 35 artisanal Calabrian table-olive brines, 153 strains of lactic acid bacteria were isolated. A screening procedure was designed, involving the following steps: 1) Gram stain, cellular morphology, homolactic fermentation, acidifying activity in MRS broth; 2) growth in olive paste with NaCl 11%; 3) increase of the antioxidant activity; 4) identification of the best strains. The proposed procedure allows an evaluation of the technological aptitude of lactic acid bacteria to ferment table olives excluding, cheaply and easily, all those strains definitely unable to act as starter. The use of olive paste as a screening medium allows the resistance of the new isolates against olive phenolic compounds to be tested. The selection of strains able to increase the antioxidant power of olive paste can improve the shelf-life of table olives.
Education Development Strategy on Base of the Analysis of Messages in the Russian-Speaking Segment of the Internet using SLMHM Model

The threat of the COVID epidemic and the subsequent isolation has dealt a serious blow to the education system, as there were significant obstacles to full-time teaching. In addition, many other problems of education have become actual, primarily ones associated with the transition to the information era. For example, the effects of the so-called technological singularity began to be felt, in which new technologies appear more and more often and do not have time to be comprehended by humanity. All these negative factors require an appropriate adaptation of the educational system to the dynamics of the real situation.This article contains a study of 100 statements in the Russian-speaking segment of the Internet containing a mention of education issues. The study is made through the prism of the Simple Learning Motivations Hierarchy Model (SLMHM). The purpose of this research is to demonstrate the capabilities of the SLMHM model for systematizing problems and determining the directions for finding their solutions. The education issues are considered within the framework of the study of the relationship between students, parents, school, society, and the environment (economy, ecology, etc.). The article describes a model of a flexible effective education system that includes 16 levels of development. The model can be used to assess educational processes in an educational institution or the educational branch as a whole, as well as to plan their improvement. Thus, one can talk about the possibility of using the SLMHM model in matters of strategic planning for the development of education. The article provides specific examples of determining the level of the issues in education according to the SLMHM model, as well as finding the actions to find their solution.
New Insights on Rotenone Resistance of Complex I Induced by the m.11778G>A/MT-ND4 Mutation Associated with Leber’s Hereditary Optic Neuropathy

The finding that the most common mitochondrial DNA mutation m.11778G>A/MT-ND4 (p.R340H) associated with Leber’s hereditary optic neuropathy (LHON) induces rotenone resistance has produced a long-standing debate, because it contrasts structural evidence showing that the ND4 subunit is far away from the quinone-reaction site in complex I, where rotenone acts. However, recent cryo-electron microscopy data revealed that rotenone also binds to the ND4 subunit. We investigated the possible structural modifications induced by the LHON mutation and found that its amino acid replacement would disrupt a possible hydrogen bond between native R340 and Q139 in ND4, thereby destabilizing rotenone binding. Our analysis thus explains rotenone resistance in LHON patients as a biochemical signature of its pathogenic effect on complex I.
Macroalgal Proteins: A Review

Population growth is the driving change in the search for new, alternative sources of protein. Macroalgae (otherwise known as seaweeds) do not compete with other food sources for space and resources as they can be sustainably cultivated without the need for arable land. Macroalgae are significantly rich in protein and amino acid content compared to other plant-derived proteins. Herein, physical and chemical protein extraction methods as well as novel techniques including enzyme hydrolysis, microwave-assisted extraction and ultrasound sonication are discussed as strategies for protein extraction with this resource. The generation of high-value, economically important ingredients such as bioactive peptides is explored as well as the application of macroalgal proteins in human foods and animal feed. These bioactive peptides that have been shown to inhibit enzymes such as renin, angiotensin-I-converting enzyme (ACE-1), cyclooxygenases (COX), α-amylase and α-glucosidase associated with hypertensive, diabetic, and inflammation-related activities are explored. This paper discusses the significant uses of seaweeds, which range from utilising their anthelmintic and anti-methane properties in feed additives, to food techno-functional ingredients in the formulation of human foods such as ice creams, to utilising their health beneficial ingredients to reduce high blood pressure and prevent inflammation. This information was collated following a review of 206 publications on the use of seaweeds as foods and feeds and processing methods to extract seaweed proteins.
“We are Still Running around with the Same Rules, but We are Not the Same We Were 20 Years Ago” – Exploring the Perceptions of Youth Justice Professionals on Secure Training Centres

ABSTRACT Debates on the incarceration of children in residential settings has been ongoing for decades, with the United Nations Convention of the Rights of the Child and academic literature acknowledging that custody is not in the best interest of the child. In England, the problems associated with placing children in custody have been documents since 1999 and, nearly twenty years later, a BBC Panorama exposed the abuse of children at the hands of staff in the same Secure Training Center. This paper examines staff’ and other professional perceptions as to the purpose and direction of Secure Training Centers, youth custodial environments, through thematic analysis of semi-structured interviews with staff members employed in Secure Training Centers and other professionals in the youth justice sector (i.e. Social Workers, Youth Offending Officers and Managers). It seeks to identify perceptions on the purpose and challenge of Secure Training Centers in supporting children who have experiences adverse circumstances resulting in trauma. It illustrates the need for embedding trauma-informed “Child First” approaches in Secure Training Centers, and youth custodial environments globally, to enable staff to adequately support children to build empowering relationships.
Forbs included in conservation seed mixes exhibit variable blooming detection rates and cost‐effectiveness: implications for pollinator habitat design

Although forb‐rich plantings for pollinator habitat are becoming more common, natural resource managers lack insight on the cost‐effectiveness of forbs seeded in private land conservation programs. Additional information on the possible benefits of including more forb species in a mix may help guide the design of future pollinator habitat. We examined the detection of blooming forbs from seed mixes, colonization of non‐seeded blooming forbs, and bee utilization of forbs on private lands enrolled in United States Department of Agriculture (USDA) conservation programs. By obtaining the original seed mixes used on conservation program lands and sampling forbs and bees, we provide a first‐hand evaluation of the cost‐effectiveness of USDA conservation plantings in a field setting. We identified seeded forbs with the highest blooming detection rates and the most common colonizing forbs across 27 sites, the majority of which were considered young conservation plantings. We additionally designated 16 forbs as the most cost‐effective due to their higher‐than‐average blooming detection rate and lower‐than‐average seed cost. We found a positive association between seed mix richness and number of blooming, seeded forbs detected and found a negative association with blooming, non‐native colonizing forbs, which highlights potential benefits of increasing forb richness in seed mixes. However, we did not observe an association between seed mix richness and wild bee or honey bee counts. Examining the cost‐effectiveness of seeded forbs on USDA conservation enrollments and subsequent bee utilization can inform land managers in designing seed mixes for pollinator habitat.
Nursing risks and preventive strategies of the elderly: an interview-based study with staff at long-term care facilities

Background: The prevention and control of nursing risks play a critically important role in ensuring safety and maintaining the health of the elderly in long-term care facilities. Methods: In-depth interviews were conducted on participants in 16 long-term care facilities using a semi-structured interview. The transcribed interviews and field notes written during the visits were analyzed inductively following a constant comparative method as described in Grounded Theory. Data were analyzed using framework analysis and domains, and the NVivo 10 software was used to refine themes and build relationships among themes. The authors followed the COREQ guidelines to ensure rigour in the study.Results: A total of 28 participants (18 managers, 5 head nurses, 2 qualified nurses, and 3 healthcare assistants) were interviewed. In the risk warning model, nursing risks (factors that affect risks, consequences), risk early warning intervention measures (risk assessment, training, and education, comprehensive preventive measures), challenges and solutions as potential and observation variables affecting nursing risks, were aimed to reduce nursing risks in long-term care facilities.Conclusions: There are many nursing risk factors in long-term care facilities, among which nursing risk assessment plays an important intermediate role in risk prevention. Comprehensive measures can be formulated and implemented according to relevant nursing risk factors, referred to as the early warning model, to reduce the incidence of nursing risks and promote the safety of the elderly in long-term care facilities.