Miracle-dz/UniFAR-FTUs huggingface dataset:
Effect of nitrogen-accommodation ability of electrodes in SiNx-based resistive switching devices

Nitrides could create opportunities of tuning resistive-switching (RS) characteristics due to their different electrical properties and ionic chemistry with oxides. Here, we reported on the effect of nitrogen-accommodation ability of electrodes in SiNx-based RS devices. The Ti/SiNx/Pt devices show a self-compliance bipolar RS with excellent reliability. The W/SiNx/Pt devices provide an unstable RS and fall to an intermediate resistance state (IRS) after a set process. The low resistance states of the Ti/SiNx/Pt devices obey Ohmic conduction and Frenkel-Poole emission from a conductive channel. The IRS of the W/SiNx/Pt devices conforms to Schottky emission and Fowler-Nordheim tunneling from a conductive channel/insulator/electrode structure. A nitrogen-ion-based model is proposed to explain the experimental results. According to the model, the nitrogen-accommodation ability of the electrodes dominates the nitrogen-reservoir size and the nitrogen-ion migration at the metal/SiNx interface, modulating the RS .
Short Sleep Duration Was Associated with Increased Regional Body Fat in US Adults: The NHANES from 2011 to 2018

Background: The relationship between sleep duration and different regional fat is unclear. We aimed to investigate the association between sleep duration and different regional fat mass (FM) among a population of US adults. Methods: 9413 participants were included from the National Health and Nutrition Examination Survey (NHANES), from 2011 to 2018. The sleep duration was divided into short sleep (<7 h/day), normal sleep (7–9 h/day) and long sleep (>9 h/day). Different regional FM was measured by dual-energy X-ray absorptiometry, including trunk FM, arms FM and legs FM. Fat mass index (FMI) was obtained by dividing FM (kg) by the square of body height (m2). Multiple linear regression was used to evaluate the relationship between sleep duration and regional FMI. Results: The mean sleep duration was 7.1 ± 1.5 h/day. After adjusting for socio-demographic, lifestyle information, comorbid diseases and medications, short sleepers had higher trunk FMI (β = 0.134, 95% confidence interval (CI): 0.051–0.216, p = 0.001), arms FMI (β = 0.038, 95% CI: 0.016–0.06, p < 0.001) and legs FMI (β = 0.101, 95% CI: 0.044–0.158, p < 0.001) compared to normal sleepers, whereas no significant difference was found in long sleepers. The similar results were also observed in men, while short sleepers only had higher arms FM in women (all p < 0.01). In addition, compared to normal sleepers, short sleepers had higher arms FMI and legs FMI in the obese group (all p < 0.05), while no relationship was observed in non-obese group. Conclusions: Short sleep duration, but not long sleep duration, was independently related to the increased different regional body fat in US adults, especially in men and those with obesity.
Proteomic Investigation of the Role of Nucleostemin in Nucleophosmin-Mutated OCI-AML 3 Cell Line

Nucleostemin (NS; a product of the GNL3 gene) is a nucleolar–nucleoplasm shuttling GTPase whose levels are high in stem cells and rapidly decrease upon differentiation. NS levels are also high in several solid and hematological neoplasms, including acute myeloid leukaemia (AML). While a role in telomere maintenance, response to stress stimuli and favoring DNA repair has been proposed in solid cancers, little or no information is available as to the role of nucleostemin in AML. Here, we investigate this issue via a proteomics approach. We use as a model system the OCI-AML 3 cell line harboring a heterozygous mutation at the NPM1 gene, which is the most frequent driver mutation in AML (approximately 30% of total AML cases). We show that NS is highly expressed in this cell line, and, contrary to what has previously been shown in other cancers, that its presence is dispensable for cell growth and viability. However, proteomics analysis of the OCI-AML 3 cell line before and after nucleostemin (NS) silencing showed several effects on different biological functions, as highlighted by ingenuity pathway analysis (IPA). In particular, we report an effect of down-regulating DNA repair through homologous recombination, and we confirmed a higher DNA damage rate in OCI-AML 3 cells when NS is depleted, which considerably increases upon stress induced by the topoisomerase II inhibitor etoposide. The data used are available via ProteomeXchange with the identifier PXD034012.
Event-Triggered Tracking Control Scheme for Quadrotors with External Disturbances: Theory and Validations

This article studies the tracking control of a quadrotor unmanned aerial vehicle (UAV) under time-varying external disturbances. An event-triggered sliding mode control (SMC) strategy is proposed by introducing a new triggering condition form of desired trajectory, quadrotor position, and velocity. In the sense of Lyapunov theory, the stability of the entire closed-loop control system is analyzed, and it is proved that the tracking error is adjusted to an adjustable set around zero. We show that the Zeno phenomenon can be avoided; that is, a positive minimum inter-event time is assured. One of the salient features of the proposed strategy is that it can reduce the update frequency of the control efforts, thereby ensuring desirable tracking performance under limited communication bandwidth. Comparative simulation and experimental results are provided to show the efficacy of our framework.
BURNOUT SYNDROME AMONG MEDICAL PROFESSIONALS: 
LITERATURE REVIEW

Relevance: Burnout syndrome in medical staff is a sensitive topic of health care, as this condition can directly affect treatment and care, that is, the patient’s satisfaction with the medical service and the psychological state of the medical staff as a whole. Burnout syndrome includes several risk factors that can directly affect the spread of this syndrome. Thus, the psychological state of medical personnel and the prevention of burnout syndrome is an important healthcare aspect. The purpose of the study was to review the literature on the spread, risk factors, and prevention of burnout syndrome in medical staff. Methods: The research for papers was made using the PubMed, Cochrane Library, Medscape, CINAHL, and Google Scholar search engines, e-Library.ru and CyberLeninka electronic libraries. Inclusion criteria: search depth of 10 years (2012-2022), original articles, literature reviews, meta-analyses and systematic reviews, open-access full-text articles in English and Russian. Exclusion criteria: low-quality articles not meeting the search criteria or containing unclear information and conclusions, reports, abstracts, and newspaper articles. In total, the review included 47 articles. Results: The literature review showed that burnout syndrome among medical staff is spreading every year and requires high-quality prevention methods. Conclusion: The literature review showed that emotional burnout syndrome among medical workers is a global problem and has become one of the most noticeable issues in healthcare. From the point of risk factors, professional factors rank first, followed by social, physiological, and other factors. The reviewed foreign and domestic publications insufficiently study the burnout syndrome prevention measures and their efficacy.
Understanding Individual’s Behaviors in Urban Environments

—UrbanContext is an urban computing context abstraction model that follows an individual centered approach and validates the use of the Theory of Roles to understand the behavior of the individual within a social environment. The roles deﬁned in UrbanContext allow the interpretation of the states of the individual, facilitating its interaction with the environment and offering services without damaging its privacy. In this paper, we mainly describe a real evaluation scenario for UrbanContext at the UBI platform in Oulu (Finland).
The DURABLE Trial 24-week Results: Safety and Efficacy of Insulin Lispro Mix 75/25 Versus Insulin Glargine Added to Oral Antihyperglycemic Drugs in Patients with Type 2 Diabetes

1 Division of Endocrinology, Department of Medicine, University of North Carolina School of Medicine, Chapel Hill, NC, USA 2 Endocrinology & Metabolism, University Medical Center, Groningen and University of Groningen, The Netherlands 3 Internal Medicine and Epidemiology, University of Michigan, Ann Arbor, MI, USA 4 Desert Oasis Health Care, Inc., Palm Springs, CA, USA 5 US Medical Division, Lilly USA, LLC, Indianapolis, Indiana
Enhancing the Sentiment Classification Accuracy of Twitter Data using Machine Learning Algorithms

Sentiment analysis or opinion mining is the study of public opinions, sentiments, attitudes, and emotions expressed in social media. This is one of the most dynamic research areas in natural language processing and text mining in current years. It is a domain that involves the finding of user sentiment, emotion and opinion within natural language text. The growing significance of sentiment analysis coincides with the increase of social media such as reviews, forum discussions, blogs, micro-blogs, Twitter, and social networks. Common applications of sentiment analysis include the automatic determination of whether a review posted online (of a movie, a book, or a consumer product) is positive or negative toward the item being reviewed. This research work shows the various pathways to perform a computational treatment of sentiments and opinions. The main aim of this work is to classify the sentiment of twitter data using machine learning algorithms. The sentiment classifications have been classified into two types which are emotional classification and polarity classification. This work has been carried out on polarity classification, which is used to classify the text such as positive, negative, and neutral. The polarity classification is done by using the subjectivity lexicon. After the polarity classification two machine learning algorithms are employed to enhance the accuracy of sentiment classification. In the Pre-processing phase, the tweets are preprocessed by using various techniques. Sentiment classification is the essential phase, where preprocessed tweets are taken as input to sentiment classification. The sentiment classification can be done by using subjectivity lexicon. The third phase of the proposed work is to compare and evaluate the performance of two machine learning algorithms which are Support Vector Machine and Decision tree.
Towards an Understanding of the Role of Aragonite in the Mechanical Properties of Nacre

Towards Nacre, also known as mother-of-pearl, is a biocomposite material that exhibits higher strength and fracture toughness than its component materials. It derives its strength from the brick-and-mortar layering of aragonite (CaCO 3 ) platelets and organic binder. It is believed that the protein binder helps redistribute the stress throughout all tablets for optimal mechanical performance. In this study, we attempt to measure the mechanical properties of aragonite within nacre and compare them to bulk aragonite and bulk nacre and understand the redistribution of stresses. Here we show that x-ray diﬀraction techniques are useful for isolating and measuring strain of crystallites within a composite material. Our results show that the apparent stiﬀness of aragonite varies with crystallographic directions and is higher than the stiﬀness of bulk nacre in all cases, meaning that aragonite tablets are exposed to less than the average bulk stress. The average force applied to the bulk sample is partitioned between the aragonite and the binder, so that the protein layer bears as much as 27.2% of the total applied force. Diﬀerent crystallographic directions exhibit behaviors diﬀerent than bulk aragonite or bulk nacre. These are related to texture of aragonite platelets (i.e. preferred orientations within nacre). By examining nacre, we can obtain a better understanding of the mechanical relationship between the ceramic and polymer in composite materials. We expect that x-ray diﬀraction will become the standard method for probing the mechanical properties of composite materials.
Escherichia coli Produces a Cytoplasmic a-Amylase, AmyA

In the gap between two closely linked flagellar gene clusters on the Escherichia coi and Salmonella typhimurium chromosomes (at about 42 to 43 min on the E. coi map), we found an open reading frame whose sequence suggested that it encoded an a-amylase; the deduced amino acid sequences in the two species were 87% identical. The strongest similarities to other ct-amylases were to the excreted liquefying a-amylases of bacilli, with >40% amino acid identity; the N-terminal sequence of the mature bacillar protein (after signal peptide cleavage) aligned with the N-terminal sequence of the E. coli or S. typhimurium protein (without assuming signal peptide cleavage). Minicell experiments identified the product of the E. coil gene as a 56-kDa protein, in agreement with the size predicted from the sequence. The protein was retained by spheroplasts rather than being released with the periplasmic fraction; cells transformed with plasmids containing the gene did not digest extracellular starch unless they were lysed; and the protein, when overproduced, was found in the soluble fraction. We conclude that the protein is cytoplasmic, as predicted by its sequence. The purified protein rapidly digested amylose, starch, amylopectin, and maltodextrins of size G6 or larger; it also digested glycogen, but much more slowly. It was specific for the ac-anomeric linkage, being unable to digest cellulose. The principal products of starch digestion included maltotriose and maltotetraose as well as maltose, XhoI- XbaI portion of pIK1001 ligated into SalI-XbaI-digested pIK1201 the NruI-NruI portion of pIK1001 inserted into pUC19. pOYAl has an insert that contains all of the nonflagellar DNA between flagellar re- gions IIIa and IlIb of S. typhimurium (24). Other plasmids are described in
Note on multiattribute decision making in intuitionistic fuzzy context

: Zhi Pei and Li Zheng [8], introduced a particular score function and an accuracy function to rank intuitionistic fuzzy sets (IFSs). They considered the degree of membership, degree of non membership and degree of hesitation with descending order of importance. We further recall an optimization model to estimate the relative degree of importance of each quantity given by the above mentioned authors. In this paper we identify certain anomalies in the accuracy function given in [8], we propose a new accuracy function and a revised optimization model.
Technology acceptance of mobile health applications in GCC countries: case of Kuwait

Information technologies solutions have proven to bring many opportunities. For instance, the information technologies have proven to improve the efficiency and effectiveness of healthcare in the developed countries. However, the drivers and barriers to accept mobile applications and information technologies adoption within healthcare are little researched for the GCC countries where the information technologies adoption is relatively new. The current research is a pilot study that investigate unbiased evaluation of different end-users’ views on information technologies solutions in Kuwait. To catch up with the growth, the GCC countries have attempted to revolutionize the healthcare systems throughout the applications of information technologies solutions including mobile computing solutions and educate users with better methods to receive customized health services. The present paper examined the issues by using the framework of Technology Acceptance Model (TAM) and Q methodology to grasp insights and reflections of different viewpoints of end-user’s adoption factors. One of the findings indicated that the perceived security risk was the least an obstacle factor for mobile applications adoptions and acceptance. Another chief factor for such adoption is the perceived usefulness and perceived ease of use domains which present significant elements for the escalating embracing of mobile health application among end-users in Kuwait. Accordingly, the data analytics indicated two factors labeled as “technology readiness” competent end-users and “risk insensitive” end-users.
Syngeneic Lymphoma Model Presentation and Tumor-Specific CTLs in a NK Cells Negatively Regulate Antigen

NK cells are known to kill tumor cells and produce proinﬂammatory cytokines that lead to the generation of tumor-speciﬁc CTLs. Many studies have used MHC class I-deﬁcient tumor cells and/or adjuvants that induce NK cell responses. In this study, the focus was on less-immunogenic lymphoma cells that express MHC class I as a model to study NK cell responses to tumors that do not directly stimulate NK cell activation. When RMA tumor cells that expressed a truncated version of OVA, or RMA cells alone, were injected into mice that were depleted of NK cells, the mice developed an increased number of tumor-speciﬁc CTLs, increased IFN- (cid:1) responses, and a higher amount of Ag presentation in draining LNs compared with mice with intact NK cells. These data suggest that NK cells can inhibit the development of effective adaptive immunity in the absence of signals that trigger NK cell activation. The Journal of Immunology, 2007, 178: 6140–6147.
The effect of optimization of the heart rate in patients with dilated cardiomyopathy on left ventricular ejection fraction and global longitudinal strain

Background: Dilated cardiomyopathy (DCMP) is one of the disabling diseases all over the world including Iraq, and especially Basrah. It affects different age groups and both sexes. Aim: to see the effect of optimization of heart rate on left ventricular ejection fraction and average global longitudinal strain. Methodology and the Results: 33 patients with dilated cardiomyopathy (DCMP) are enrolled in this study from February 2019 to May 2021, their mean age was 39.6 year, 51.52% were male and female constitute 48.48%, the mean heart rate of those patients at the first visits was 102 beat per minute, the mean of their left ventricular ejection fraction (LVEF) at that time was 31%and the mean of their average global longitudinal (GLS) was -7%. That patient was treated by ant failure treatment with optimization of their heart rate, after 2 months of treatment their mean heart rate was significantly decrease to 76 BPM (P value < 0.001), however in spite of improvement in the functional capacity there was no significant correlation between the optimization of the heart rate and the LVEF (P value 0.317), on the other hand there was significant correlation in the average GLS after optimization of the heart rate (P value <0.006). Conclusion: optimization of the heart rate associated with improvement in the functional capacity and GLS. GLS estimation is better than LVEF estimation in the assessment
Effects of Aqueous and Pelletized Admixture of Piper nigrum L. on the Oviposition Behavior of Aedes aegypti Mosquitoes and its Larvicidal-Ovicidal Activity

This is a case of a 43-year-old male presenting with short stature and heart failure. The patient was admitted at the medicine ward of the Philippine General Hospital (PGH) for dyspnea. This paper will investigate several issues: differentiating congenital from acquired hypothyroidism, the relationship between hypothyroidism and the cardiomyopathies, and the therapeutic options in patients with cardiomyopathy secondary to hypothyroidism. The patient had been born full term to a then 31-year-old 4 Para 3 (G4P3), the 4 th of 9 siblings, with an apparently at facilitated by a traditional He was noted to be normal at The patient was allegedly at both years when he was He was to he patient the patient This is a case of a 43-year-old male presenting with short stature and heart failure. The patient was admitted at the medicine ward of the Philippine General Hospital (PGH) for dyspnea. This paper will investigate several issues: differentiating congenital from acquired hypothyroidism, the relationship between hypothyroidism and the cardiomyopathies, and the therapeutic options in patients with cardiomyopathy secondary to hypothyroidism. The patient had been born full term to a then 31-year-old 4 Para 3 (G4P3), the 4 th of 9 siblings, with an apparently delivery at facilitated by a traditional birth attendant. He was noted to be normal at The patient was allegedly at both physically years old when he was He was to a he patient one the the patient was apparently
Uncertain Inverse Method Based on λ -PDF and First Order Second Moment

： An inverse method based on λ -probability distribution function(PDF) and first order second moment is developed to effectively evaluate the influence of the uncertainty of measured response on the identified results of structural parameters. The quadric derivative of λ -PDF is used to model the PDF of the identified uncertain variable. The method includes a double-loop procedure. In the inner-loop the performance function is solved by first order second moment method to obtain the computational PDFs of the responses. In the outer-loop the uncertain inverse problem is transformed into an optimization problem by minimizing the moment errors of the measured and computational responses, and the optimization problem is solved by intergeneration projection genetic algorithm. The method proposed can not only effectively estimate the PDFs of the unknown structure variables, but also have a higher computational efficiency compared with the traditional statistical method. Two numerical examples and an engineering problem are used to demonstrate the feasibility and effectiveness of the proposed method.
Counterfactual Decoding for Anti-Hallucination Knowledge-grounded Dialogue Generation

The task of Knowledge-grounded Dialogue 001 (KGD) generation, which intentionally invokes 002 external knowledge resources to produce nat-003 ural and informative responses, has been a 004 popular topic these years. Empowered by the 005 large-scale pretrained language models, exist-006 ing methods have demonstrated impressive per-007 formance on this task. However, the hallucina-008 tion problem remains a serious problem, caus-009 ing unpredictable factual errors in the generated 010 results. Although serious efforts try to allevi-011 ate this phenomenon by data pre-processing 012 or fact-checking, these methods still heavily 013 rely on assistance from external tools or re-014 sources. Inspired by counterfactual reasoning, 015 we propose a lightweight and independent anti-016 hallucination mechanism in KGD by conduct-017 ing a causal effect analysis. Our example im-018 plementation’s benchmark and human evalua-019 tion results show that our method can signifi-020 cantly reduce hallucination without disrupting 021 the model performance. We hope our efforts 022 can call for more attention to utilizing causal 023 inference to solve relevant issues. 024