Miracle-dz/UniFAR-FTUs huggingface dataset:
Comparison of the High Cycle Fatigue Behavior of the Orthodontic NiTi Wires: An in Vitro Study

Comparison of the high cycle fatigue behavior of the orthodontic NiTi wires: an in vitro study. Clín Integr. ABSTRACT Objective: To compare the high-cycle fatigue behavior of four commercially available NiTi orthodontic wires. Material and Methods: Twelve NiTi orthodontic wires, round, 0.016-in, three per brand, were selected and divided into four groups: G1 - Heat-activated NiTi, G2 - Superelastic NiTi, G3 - Therma-Ti, and G4 - CopperNiTi. The atomic absorption spectrometry method was used to determine the chemical composition of investigated NiTi wires. We also performed a fatigue test at three-point bending using a universal testing machine for 1000 cycles in a 35 °C water bath. For the first and thousandth cycle, the average plateau load and the plateau length were determined in the unloading area of the force versus displacement diagram. In addition, we calculated the difference between the average plateau load of the first and thousandth cycle ( ∆ F), as well as the difference between the plateau length of both cases ( ∆ L). Results: According to our results, there were no significant differences between the average plateau load of the first and thousandth cycles of each group (p>0.05) and in the plateau length of the first and thousandth cycles of the groups (p>0.05). Conclusion: There were no significant differences between the groups changing the superelasticity property after high-cycle fatigue.
Timeliness of Microbiology Test Result Reporting and Association with Outcomes of Adults Hospitalised with Unspecified Pneumonia: A Data Linkage Study

Background Pneumonia is one of the leading causes of mortality and morbidity worldwide. Microbiology tests play a critical role in the diagnosis of pneumonia. Our study aimed to determine microbiology result reporting times and evaluate their association with outcomes of adult patients (≥18 years) hospitalised with pneumonia. Methods This is a 3-year (2016–2018) retrospective cohort study in six hospitals in New South Wales, Australia. The study data were obtained by linking hospital and laboratory system databases. Result reporting times including time from admission to the first and the last microbiology test results were determined. The outcome measures were hospital length of stay (LOS) and in-hospital mortality. We fit median and logistic regression to evaluate the association of time-to-first microbiological result with hospital LOS and in-hospital mortality, respectively. Results A total of 6,298 patients met the inclusion criteria. Of these, 85.3% (n = 5,375) ordered at least one microbiology test. The top 5 microbiology tests were blood culture, urine culture, respiratory polymerase chain reaction (PCR), urine antigen, and sputum culture. The median time-to-first microbiology result was 26 hrs while the median time-to-last test result was 144 hrs. The rate of in-hospital mortality was 5.9% (n = 371). After adjusting for confounders, every 5 hrs increase in the time-to-first microbiology test was associated with an increase of 3.9 hrs in the median hospital LOS [95% Confidence Interval (CI), 3.5 to 4.3; P ≤ 0.001]. There was no association between time-to-first microbiology result and in-hospital mortality (OR 1.01; 95% CI 1.00–1.02; P=0.122). Conclusion Time-to-first microbiology result reporting was significantly associated with hospital LOS but not with in-hospital mortality. Further research should be conducted to understand if improving result reporting times can reduce the length of hospital stay of patients.
Strong phylogenetic signals in global plant bioclimatic envelopes

Aim: The environmental preferences of species are an important facet of their response to changing conditions, and these have long been thought to exhibit phylogenetic conservatism. However, these bioclimatic envelopes have not previously been imputed from climate records at the date and location of occurrence, and the strength of their phylogenetic signal has not been studied at a broad scale. Here, we combine records from global climate reconstructions with contemporaneous plant occurrences for all available terrestrial plant species and test for phylogenetic niche conservatism
PARTIAL SUBSTITUTION OF CONCENTRATE MIX WITH DRIED Leucaena leucocephala LEAF REDUCED in vitro METHANE PRODUCTION IN RAMS WITHOUT AFFECTING THE NUTRIENT INTAKE AND PERFORMANCE TRAITS

Background. Through in vitro studies, dried Leucaena leucocephala leaf (DLL) was identified as potential candidate in mitigating enteric methane (CH4) emission. Nevertheless, its efficiency as suitable feed for sheep has not been determined in Ethiopia. Objective. To assess the suitability of replacing the concentrate mix (CM) with DLL on voluntary intake, growth performance in rams and in vitro CH4 production. Methodology. Thirty yearling rams were first stratified according to their initial body weight similarities and then individuals from each stratum were randomly assigned to five treatment diets with six rams each. The control diet contained CM with 346 g/head/d (T1), and treatment diets replacing the CM in the control diet with DLL at a rate of 5% (T2), 10% (T3), 15% (T4) and 20% (T5) with the corresponding CM to DLL mixture ratio of 346:0, 329:17, 311:35, 294:52 and 277:69 g/head/day. Grass hay was provided ad libitum to all rams. Data were collected on fed intake and body weight. Methane (CH4) production was determined along with 24h in vitro gas production (GP). Digestible organic matter (DOM) and Metabolizable energy (ME) were estimated from 24h GP. Results. The contents of ash, crude protein (CP), neutral detergent fiber (NDFom), acid detergent fiber (ADFom) and acid detergent lignin were higher in DLL than in the control diet while it contained the lowest EE value. The DLL had the highest Ca and K values as compared to the control diet. The feed intake, live weight and weight gain did not differ (P>0.05) among rams supplemented with various levels of DLL. The total intake of CP increased across treatment diets and was significantly higher for T3, T4 and T5 than T1 and T2 diets. None of the supplementation levels of L. leucocephala affected the total intake of DM, NDFom and ADFom. There was a linear reduction (p<0.05) of in vitro CH4 production as the levels of DLL in the diet were increased. It was lowest in T4 and T5 diets being significantly different from those of T1 and T2. The T5 diet showed the lowest values and differed (p<0.05) from those of T1, T2 and T3. The ME and DOM values were higher (p<0.05) in T1 and T2 diets than that of T4 and T5. No difference in ME and DOM values were observed between T1, T2 and T3 diets as well as among T4 and T5 diets. Implications. The current findings suggest that conventional CM could be replaced with DLL up to 20% as alternative protein source in ruminant nutrition in tropical and sub-tropical regions. Conclusion. The replacement of CM with DLL significantly reduced the in vitro CH4 production across treatment diets without affecting the voluntary intake and growth performance parameters in rams.
Dark personality traits and the use of sources of guidance at work: a comparison between the United States and Brazil

Purpose: The objective of this research was to statistically test significant correlations between dark personality traits and employee’s use of sources of guidance when dealing with different events at work, comparing the United States and Brazil. Methodology: 220 employees from a Brazilian university and 166 employees from an American university filled out a paper-and-pencil questionnaire comprised of two previously-validated scales. Based on the theoretical review about the constructs, 10 hypotheses were raised to be empirically tested through Pearson correlation (r) tests. Findings: The dark personality trait Machiavellianism was positively correlated with the use of Informal Rules and negatively correlated with the use of Formal Rules and Procedures as a guidance source at work in the American sample. In addition, the dark personality trait Psychopathy was negatively correlated with the use of Formal Rules and Procedures as a guidance source at work in the Brazilian sample. Practical implications: The findings have implications for administrators and human resource professionals, who can benefit from knowledge about correlations between dark personality traits and employee’s attitude of relying on sources of guidance at work, especially when it comes to recruiting and selecting processes. Limitations: Although the research was restricted to correlations, it elaborated a robust ground for causality investigations. Originality: The investigation involved two countries with a cross-cultural approach. In an international and multicultural scenario, it becomes strategic to deeper investigate specificities of work-related constructs in different nations, aiming at effective and contextualized management practices.
MOISTURE SORPTION ISOTHERMS OF QUINOA SEEDS: THERMODYNAMIC ANALYSIS

The present work aimed to study the water sorption behavior of quinoa seeds analyzing the hysteresis phenomenon and determining thermodynamic properties. Static gravimetric technique was used to obtain the equilibrium moisture content of quinoa seeds in different temperature conditions (15, 25, 35 e 50 °C) and relative humidity (between 11 and 96%). Equilibrium moisture content data were adjusted by eight mathematical models and the Modified Halsey model was the best one to describe the water sorption phenomena of quinoa seeds. Hygroscopic equilibrium moisture content of quinoa seeds is directly proportional to the water activity and decreases with increasing temperature. The hysteresis phenomena were observed throughout the range of water activity, showing more evident at low temperatures. Integral isosteric heat and differential entropy decreased with the increase of equilibrium moisture content. Gibbs free energy decreased with the increase of temperature and equilibrium moisture content. Compensation enthalpy-entropy theory was confirmed and the sorption mechanism is controlled by enthalpy.
Computationally Efficient Surrogate-Assisted Design of Pyramidal-Shaped 3-D Reflectarray Antennas

Reflectarrays (RAs) have been attracting considerable interest in recent years due to their appealing features, in particular, the possibility of realizing pencil-beam radiation patterns, as in the phased arrays, but without the necessity of incorporating the feeding networks. These characteristics make them attractive solutions, among others, for satellite communications or mobile radar antennas. Notwithstanding, available microstrip implementations are inherently narrow-band and heavily affected by conductor and surface wave losses. RAs based on grounded dielectric layers offer improved performance and flexibility in terms of shaping the phase reflection response. In either case, a large number of variables (induced by the need for independent adjustment of individual unit cell geometries) and the necessity of handling several requirements make the design process of reflectarrays a challenging endeavor. In particular, RA optimization is extremely expensive when conducted at the level of electromagnetic (EM) simulation models, otherwise necessary to ensure reliability. A practical solution is a surrogate-assisted design with the metamodels constructed for the RA unit elements. Unfortunately, conventional modeling methods require large numbers of training data samples to render accurate surrogates, which turns detrimental to the optimization process efficiency. This work proposes an alternative approach with the unit element representations constructed using deep learning with automated adjustment of the model architecture. As a result, design-ready surrogates can be constructed using only a few hundred samples, and the total RA optimization cost is reduced to only a handful of equivalent EM analyses of the entire array. Our approach is validated using an RA incorporating 3-D pyramidal-shaped elements and favorably compared to benchmark techniques. Experimental verification of the obtained design is discussed as well.
Deep Learning Empowered Structural Health Monitoring and Damage Diagnostics for Structures with Weldment via Decoding Ultrasonic Guided Wave

Welding is widely used in the connection of metallic structures, including welded joints in oil/gas metallic pipelines and other structures. The welding process is vulnerable to the inclusion of different types of welding defects, such as lack of penetration and undercut. These defects often initialize early-age cracking and induced corrosion. Moreover, welding-induced defects often accompany other types of mechanical damage, thereby leading to more challenges in damage detection. As such, identification of weldment defects and interaction with other mechanical damages at their early stage is crucial to ensure structural integrity and avoid potential premature failure. The current strategies of damage identification are achieved using ultrasonic guided wave approaches that rely on a change in physical parameters of propagating waves to discriminate as to whether there exist damaged states or not. However, the inherently complex nature of weldment, the complication of damages interactions, and large-scale/long span structural components integrated with structure uncertainties pose great challenges in data interpretation and making an informed decision. Artificial intelligence and machine learning have recently become emerging methods for data fusion, with great potential for structural signal processing through decoding ultrasonic guided waves. Therefore, this study aimed to employ the deep learning method, convolutional neural network (CNN), for better characterization of damage features in terms of welding defect type, severity, locations, and interaction with other damage types. The architecture of the CNN was set up to provide an effective classifier for data representation and data fusion. A total of 16 damage states were designed for training and calibrating the accuracy of the proposed method. The results revealed that the deep learning method enables effectively and automatically extracting features of ultrasonic guided waves and yielding high precise prediction for damage detection of structures with welding defects in complex situations. In addition, the effectiveness and robustness of the proposed methods for structure uncertainties using different embedding materials, and data under noise interference, was also validated and findings demonstrated that the proposed deep learning methods still exhibited a high accuracy at high noise levels.
A Patient with Sickle Cell Disease and Recurrent Venous Thromboembolism after Renal Transplantation

Venous thromboembolism (VTE) is a life-threatening complication, especially in case of recurrence. The appropriate duration of anticoagulant treatment following the first event is crucial. Risk factors that increase the risk of recurrence of VTE are many, and include medications, kidney disease, renal transplantation (RT), and a diagnosis of sickle cell disease (SCD). There are currently no guidelines that define the duration of anticoagulant therapy after the first event in a patient with RT. We report a case of recurring episodes of VTE after RT in a SCD patient. Our case suggests that the use of a long-term anticoagulant treatment may be recommended in patients with SCD and RT after the first event of VTE.
Tongue Root Configuration of the Apicoalveolar Trill /r/: An Ultrasound Imaging Study

Common descriptions of articulatory requirements for production of the alveolar trill /r/ mainly focus on describing the configuration of the anterior portions of the tongue, while in contrast, the more posterior parts receive limited attention. Understanding how the posterior portions of the tongue move is vital for understanding speech motor control, especially with regard to speech development. This study used ultrasound imaging of /r/ productions by adult native speakers of Spanish to characterize the contribution of the posterior portion of the tongue to effective production of the sound. The results show that beyond raising the anterior portion of the tongue for trilling, Spanish speakers also retract the back part of their tongue (i.e., the tongue root). This movement resembles that seen for the production of the rhotic English approximant (ɹ). Clinical implications are discussed.
Diagnostic performance of miR-21, miR-124, miR-132, and miR-200b serums in post-stroke cognitive impairment patients.

INTRODUCTION The diagnosis of post-stroke cognitive impairment (PSCI) mainly depends on neuro-psychological evaluation. It still lacks a sensitive and objective diagnostic biomarker. MicroRNAs (miRNAs, miRs) are novel and potential disease biomarkers. Our aim was to detect which specific miRNA is a good diagnostic biomarker for PSCI. MATERIAL AND METHODS There were 77 first-ever stroke patients enrolled. Blood samples were collected at 14 days after stroke. Level of serum miR-21, miR-124, miR-132, and miR-200b were determined by quantitative polymerase chain reaction. Mini-mental state examination (MMSE) scale was used to measure the cognitive function of patients. Factional anisotropy (FA) score of diffusion tensor imaging was applied to detect the alteration of white matter. In addition, the relationship between miRNA level and cognitive status was further explored by correlation analysis. RESULTS Finally, 45 PSCI and 32 post-stroke cognitive normality (PSCN) patients were enrolled. The expression of miR-21, miR-132, and miR-200b in PSCI patients was higher than in PSCN patients. In particular, the miR-21 level was substantially correlated with MMSE scores (r = 0.752, p < 0.001) and FA value (r = 0.636, p < 0.001). Additionally, the diagnostic performance of miR-21 alone or the combination of miR-21 and FA values performed well. CONCLUSIONS The miR-21 alone or combination of miR-21 and FA values are valuable diagnostic biomarkers in discriminating PSCI from PSCN.
COPD, but Not Asthma, Is Associated with Worse Outcomes in COVID-19: Real-Life Data from Four Main Centers in Northwest Italy

Introduction: Asthma, along with inhaled steroids, was initially considered a risk factor for worse clinical outcomes in COVID-19. This was related to the higher morbidity observed in asthma patients during previous viral outbreaks. This retrospective study aimed at evaluating the prevalence of asthma among patients admitted due to SARS-CoV-2 infection as well as the impact of inhaled therapies on their outcomes. Furthermore, a comparison between patients with asthma, COPD and the general population was made. Methods: All COVID-19 inpatients were recruited between February and July 2020 from four large hospitals in Northwest Italy. Data concerning medical history, the Charlson Comorbidity Index (CCI) and the hospital stay, including length, drugs and COVID-19 complications (respiratory failure, lung involvement, and the need for respiratory support) were collected, as well as the type of discharge. Results: patients with asthma required high-flow oxygen therapy (33.3 vs. 14.3%, p = 0.001) and invasive mechanical ventilation (17.9 vs. 9.5%, p = 0.048) more frequently when compared to the general population, but no other difference was observed. Moreover, asthma patients were generally younger than patients with COPD (59.2 vs. 76.8 years, p < 0.001), they showed both a lower mortality rate (15.4 vs. 39.4%, p < 0.001) and a lower CCI (3.4 vs. 6.2, p < 0.001). Patients with asthma in regular therapy with ICS at home had significantly shorter hospital stay compared to those with no treatments (25.2 vs. 11.3 days, p = 0.024). Discussion: Our study showed that asthma is not associated with worse outcomes of COVID-19, despite the higher need for respiratory support compared with the general population, while the use of ICS allowed for a shorter hospital stay. In addition, the comparison of asthma with COPD patients confirmed the greater frailty of the latter, according to their multiple comorbidities.
Relationship between COVID-19 Mortality, Hospital Beds, and Primary Care by Italian Regions: A Lesson for the Future

One of the characteristics of the SARS-CoV-2 infection in Italy is the significant regional difference in terms of lethality and mortality. These geographical variances were clear in the first wave and confirmed in the second one as well. The study aimed to analyze the correlation between regional differences in COVID-19 mortality and different regional care models, by retrospectively analyzing the association between the Italian COVID-19 deaths and the number of hospital beds, long-term care facilities, general practitioners (GPs), and the health expenditure per capita. The period considered was from 1 March 2020 to 1 March 2021. The number of hospital beds (p < 0.0001) and the number of GPs (p = 0.0094) significantly predicted the COVID-19 death rate. The Italian regions with a higher number of hospital beds and a lower number of GPs showed a higher number of deaths. Multivariate analyses confirmed the results. The Italian regions with a higher amount of centralized healthcare, as represented by the number of hospital beds, experienced a higher number of deaths, while the regions with greater community support, as exemplified by the number of the GPs, faced higher survival. These results suggest the need for a change in the current healthcare system organization.
Exploring Wellbeing Related Issues Arising From the Unregulated Use of Screen-Based Technology During Breaktimes in an International Middle School Environment

The following study uses a design-thinking and mixed methods research approach to elicit students’ views on the use of screen-based technology during break periods. An interest in this area emerged due to a noticeable reduction, in recent years, in the number of students spending time in outdoor play areas during morning and afternoon breaks. The context of the study is Year 1 of the IB Middle Years Program in an International IB School, in the Netherlands, which implements an inquiry-based approach to teaching and learning. The school is a 1:1 laptop, tablet, and ipad school, and the students, who are 11-12 years old, have unregulated open access to screen-based technology during lunch and break-times. This first part of the study, in line with the initial stages of the design-thinking process, involved initial exploratory interviews followed by whole-group surveys, and whole-group discussions to better understand the issue at hand. The findings indicate that students engage in a wide variety of screen-based activities during break-time, they have a range of opinions on how screen-based technology affects their well-being, and they hold differing perspectives on the need for the current levels of access to change. The students raised a number of questions surrounding the unregulated use of screen-based devices during break-times, and in a follow-up study they proceeded with design thinking approaches to generate practical solutions to the issues that were raised through this initial inquiry.