Miracle-dz/UniFAR-FTUs huggingface dataset:
Perceived Climate Change and Determinants of Adaptation Responses by Smallholder Farmers in Central Ethiopia

Climate change is a global phenomenon but disproportionately affects smallholder farmers, prompting them to use various coping and adaptation strategies to counter the problem. This study aimed to examine the trends of climate parameters, assess farmers’ perception of climate change, and identify the strategies of adaptation measures in central Ethiopia. Climate data were obtained from the National Meteorological Agency. Survey data were collected from 120 randomly selected households in 2017 and complemented with focus group discussions. The Mann–Kendall approach was used to detect climate trends, while a rainfall anomaly was calculated using the rainfall anomaly index. Multinomial logit model was used to examine determinants of farmers’ adaptation to the perceived change. In most of the cases, farmers’ perceptions were in accordance with climate trend analyses. Farmers used crop diversification, adjustments of planting dates, destocking of livestock, seasonal migration, crop rotation, and climate information services to adapt to climate-related shocks. Empirical results showed that the age and education of the household heads, family size, access to extension services, and farm and nonfarm incomes had a significant association with the adaptation practices farmers took. The existence of strong correlations between the demographic, socio-institutional variables, and the choice of adaptation strategies suggests the need to strengthen local institutions to enhance the adaptation of smallholder farmers to climate change.
Joint Constant-Envelope Waveform and Receiver Design for MIMO Radar in the Presence of Clutter

Aiming to improve the detection performance of colocated multiple-input-multiple-output( MIMO) radar in the presence of strong clutter,we addressed the joint optimization problem of the waveform and receiver based on maximizing signal to clutter plus noise ratio( SCNR). Considering that practical radar systems employ constant envelope signals,we also imposed a constant envelope constraint on the waveform. During the optimizations,we divided the joint design problem into two steps,and proposed an algorithm for the design of the constant envelope waveform based on semi-definite relaxation( SDR) and Gaussian randomizations. Numerical simulations show that the proposed algorithm converges with increasing SCNR. Moreover,compared with the optimal waveform under the energy constraint,the SCNR loss is negligible. Finally,the capability of adaptive clutter suppression and improved detection performance of the proposed algorithm is clearly demonstrated.
What to Expect from COVID-19 and from COVID-19 Vaccine for Expecting or Lactating Women

Recent studies identified pregnancy as a high-risk condition for the development of maternal-fetal complications in the case of the SARS-CoV-2 infection. Therefore, the scientific community is now considering pregnant women a “fragile” category that should be vaccinated with high priority. The number of pregnant women undergoing hospitalization since summer 2021, including Intensive Care Unit admission, is growing, as well as the risk of preterm birth. Evidence from both animals and humans suggest that, similarly to other vaccines routinely administered in pregnancy, COVID-19 vaccines are not crossing the placenta, do not increase the risk of miscarriage, preterm birth, stillbirth, the birth of small gestational age neonates, as well as the risk of congenital abnormalities. To date, the World Health Organization and scientific literature are promoting and encouraging the vaccination of all pregnant and lactating women. The aim of our narrative review is to present the available literature regarding this issue with the aim to provide appropriate answers to the most frequent requests, doubts, and fears that have led many expecting and lactating women not to become vaccinated during this pandemic period.
Efficacy of three hormonal treatments for cystic ovarian disease and subsequent reproductive performance in dairy cows

Cystic ovarian disease (COD) is a common ovarian disorder that causes major reproductive failure in dairy cows leading to significant economic losses in the dairy industry. This study aimed to evaluate the efficacy and the response of cows with ovarian cysts to three different treatments regardless of the cyst type. At 50 days postpartum, were considered to have an ovarian cyst when possessing a follicle with a diameter ≥ 17 mm in the absence of a corpus luteum in two ultrasonographic examinations performed at 7 days intervals. In the second examination considered (Day 0), 51 cystic Holstein cows were assigned randomly into one of 3 treatment groups. ; GnRH group ( n =12) treated with 100 μg gonadorelin as a single dose, GP group ( n =12) received (100 μg gonadorelin on day 0 followed by 500 μg of cloprostenol sodium on day 7, CIDR group ( n =12) treated with intravaginal progesterone-releasing insert CIDR on the day 0: and 100 μg gonadorelin then an injection of 500 µg cloprostenol sodium IM on day 7. The CIDR was removed on day 8, and a second GnRH injection was given on day 9. From day 9, animals were observed for estrus and inseminated with proven frozen-thawed semen. Control Group ( n =15) represents cows that did not receive any treatment. Pregnancy was confirmed by ultrasound on day 28 post-insemination. Results showed that the GP group achieved the highest estrus induction rate (EIR). Thus, 44.4% of treated cows come in estrus less than 10 days and 100 % by day 20. While GnRH group showed EIR with 25% in less than 10 days and 62.5 % at the day 20. The CIDR group showed EIR (0%) in less than 10 days and 100 % at the day 20. Total conception rate (3 cycles after treatment) GP recorded (88.9%) GnRH group (87.5%) and CIDR (85.7%), while pregnancy rates (PR) was highest (66.7%) in GP protocol compared to GnRH (58.3%), and CIDR (49.9%). In conclusion, our results showed that the (GP group) had the best reproductive performance (earliest and highest estrus induction rate and highest pregnancy rate after treatment regardless of the type of the cyst.
Prevalence of Metabolic Syndrome and Association with Physical Activity and Frailty Status in Spanish Older Adults with Decreased Functional Capacity: A Cross-Sectional Study

Metabolic syndrome (MetS) is a cluster of medical conditions associated with several health disorders. MetS and frailty can be related to prolonged physical deconditioning. There is a need to know whether there is concordance between the different ways of diagnosing it and to know their prevalence in Spanish older adults. Thus, the aims of this study were to describe the prevalence of MetS; to analyse the concordance between different definitions to diagnose MetS; and to study the associations between MetS, frailty status, and physical activity (PA) in older adults with decreased functional capacity. This report is a cross-sectional study involving 110 Spanish older adults of ages ≥65 years with decreased functional capacity. Clinical criteria to diagnose MetS was defined by different expert groups. Anthropometric measurements, blood biochemical analysis, frailty status, functional capacity, and PA were assessed. The Kappa statistic was used to determine the agreement between the five MetS definitions used. Student’s t-test and the Pearson chi-square test were used to examine differences between sex, frailty, and PA groups. The sex-adjusted prevalence of MetS assessed by the National Cholesterol Education Program—Third Adult Treatment Panel was 39.4% in men and 32.5% in women. The International Diabetes Federation and the Harmonized definitions had the best agreement (k = 1.000). The highest odds ratios (ORs) of cardiometabolic risk factors to develop MetS were elevated triglycerides (37.5) and reduced high-density lipoprotein cholesterol (27.3). Central obesity and hypertension prevalence were significantly higher in the non-active group (70.7% and 26.8%, respectively), compared to the active group (50.0% and 7.7%, respectively). Moreover, the active group (OR = 0.85, 95% CI = 0.35, 2.04) and active women group (OR = 0.77, 95% CI = 0.27, 2.20) appeared to show a lower risk of developing this syndrome. MetS is highly prevalent in this sample and changes according to the definition used. It seems that sex and frailty do not influence the development of MetS. However, PA appears to decrease central obesity, hypertension, and the risk of developing MetS.
Computational fluid dynamics simulations to optimize the filling of an underground mine cavity with fly ash

Abstract Subsidence caused by the underground spaces of abandoned mines is a potential danger to life and property. This study focuses on optimizing the filling of these cavities at a site in Korea to prevent subsidence and to reuse abandoned mine. Fly ash produced from thermoelectric power plants might be profitably used to fill the abandoned workings. Computational fluid dynamics (CFD) is used here to simulate fly ash injection into mine cavities by a volume-of-fluid method. The numerical experiments are run after the establishment of three input parameters, which are used to optimize two output parameters. This series of CFD simulations investigates the effects of filling with respect to the operation factors of the filling method. The filling operation is then optimized with regard to efficiency and equipment cost. A low injection point with drilling connection of vertical shafts gives the most efficient filling of underground mine cavities.
Do vocational college students ready for online learning in post-COVID instruction?

The purpose of this research is to examine the readiness level of vocational college students for online learning according to various variables. The sample of the study included 334 (231 freshmen and 103 sophomore) students studying at a vocational college of a state university in Turkiye. Data collection tool used in the research consisted of Student Demographics Form and Online Learning Readiness Scale. Quantitative data obtained from the study were statistically analyzed with Three Factor MANOVA for independent groups. The findings showed that the average level of readiness for online learning of participants was at good extent, the dimension with the highest average was online communication self-efficacy, and with the lowest average was computer/internet self-efficacy. It was determined that the level of readiness for online learning of participants did not differ significantly according to the graduated high school, department and grade level. Readiness for online learning needs to be considered in detail to help all students use online tools for learning in order to get the most out of their post-COVID education. It is recommended that students be provided with opportunities to improve their readiness for online learning, which is necessary for them to continue their lifelong learning.
Impact of Sarcopenia and Bone Mineral Density on Implant Failure after Dorsal Instrumentation in Patients with Osteoporotic Vertebral Fractures

Background and Objectives: Age-related loss of bone and muscle mass are signs of frailty and are associated with an increased risk of falls and consecutive vertebral fractures. Management often necessitates fusion surgery. We determined the impacts of sarcopenia and bone density on implant failures (IFs) and complications in patients with spondylodesis due to osteoporotic vertebral fractures (OVFs). Materials and Methods: Patients diagnosed with an OVF according to the osteoporotic fracture classification (OF) undergoing spinal instrumentation surgery between 2011 and 2020 were included in our study. The skeletal muscle area (SMA) was measured at the third lumbar vertebra (L3) level using axial CT images. SMA z-scores were calculated for the optimal height and body mass index (BMI) adjustment (zSMAHT). The loss of muscle function was assessed via measurement of myosteatosis (skeletal muscle radiodensity, SMD) using axial CT scans. The bone mineral density (BMD) was determined at L3 in Hounsfield units (HU). Results: A total of 68 patients with OVFs underwent instrumentation in 244 segments (mean age 73.7 ± 7.9 years, 60.3% female). The median time of follow-up was 14.1 ± 15.5 months. Sarcopenia was detected in 28 patients (47.1%), myosteatosis in 45 patients (66.2%), and osteoporosis in 49 patients (72%). The presence of sarcopenia was independent of chronological age (p = 0.77) but correlated with BMI (p = 0.005). The zSMAHT was significantly lower in patients suffering from an IF (p = 0.0092). Sarcopenia (OR 4.511, 95% CI 1.459–13.04, p = 0.0092) and osteoporosis (OR 9.50, 95% CI 1.497 to 104.7, p = 0.014) increased the likelihood of an IF. Using multivariate analysis revealed that the zSMAHT (p = 0.0057) and BMD (p = 0.0041) were significantly related to IF occurrence. Conclusion: Herein, we established sarcopenic obesity as the main determinant for the occurrence of an IF after instrumentation for OVF. To a lesser degree, osteoporosis was associated with impaired implant longevity. Therefore, measuring the SMA and BMD using an axial CT of the lumbar spine might help to prevent an IF in spinal fusion surgery via early detection and treatment of sarcopenia and osteoporosis.
Optimisation of a stereo image analysis by densify the disparity map based on a deep learning stereo matching framework

Stereo vision is used in many application areas, such as robot-assisted manufacturing processes. Recently, many different efficient stereo matching algorithms based on deep learning have been developed to solve the limitations of traditional correspondence point analysis, among others. The challenges include texture-poor objects or non-cooperative objects. One of these end-to-end learning algorithms is the Adaptive Aggregation Network (AANet/AANet+), which is divided into five steps: feature extraction, cost volume construction, cost aggregation, disparity computation and disparity refinement. By combining different components, it is easy to create an individual stereo matching model. Our goal is to develop efficient learning methods for robot-assisted manufacturing processes for cross-domain data streams. The aim is to improve recognition tasks and process optimisation. To achieve this, we have investigated the AANet+ in terms of usability and efficiency on our own test-dataset with different measurement setups (passive stereo system). Input of the AANet+ are rectified stereo pairs of the test-dataset and a pre-trained model. Instead of generating our own training dataset, we used two pre-trained models based on the KITTI-2015 and SceneFlow datasets. Our research has shown that the pretrained model based on the Scene Flow dataset predicts disparities with better object delimination. Due to the Out-of-Distribution inputs, only reliable disparity predictions of the AANet are possible for test data sets with parallel measurement setup. We compared the results with two traditional stereo matching algorithms (SemiGlobal block matching and DAISY). Compared to the traditionally computed disparity maps, the AANet+ is able to robustly detect texture-poor objects and optically non-cooperative objects.
Challenges and Modification Strategies of Ni-Rich Cathode Materials Operating at High-Voltage

Ni-rich cathode materials have become promising candidates for lithium-based automotive batteries due to the obvious advantage of electrochemical performance. Increasing the operating voltage is an effective means to obtain a higher specific capacity, which also helps to achieve the goal of high energy density (capacity × voltage) of power lithium-ion batteries (LIBs). However, under high operating voltage, surface degradation will occur between Ni-rich cathode materials and the electrolytes, forming a solid interface film with high resistance, releasing O2, CO2 and other gases. Ni-rich cathode materials have serious cation mixing, resulting in an adverse phase transition. In addition, the high working voltage will cause microcracks, leading to contact failure and repeated surface reactions. In order to solve the above problems, researchers have proposed many modification methods to deal with the decline of electrochemical performance for Ni-rich cathode materials under high voltage such as element doping, surface coating, single-crystal fabrication, structural design and multifunctional electrolyte additives. This review mainly introduces the challenges and modification strategies for Ni-rich cathode materials under high voltage operation. The future application and development trend of Ni-rich cathode materials for high specific energy LIBs are projected.
Emotional Differences between Isomorphic Auctions

Abstract First price and Dutch auctions are theoretically isomorphic, but previous experiments report that the institutions are not behaviorally isomorphic. This article uses facial analysis of video recordings of laboratory experiments to investigate whether these auctions invoke different emotional responses from bidders. The results indicate that bidders are angrier during the Dutch auction and that winners exhibit more contempt after the first price auction. Overall, subjects in both auctions appear to be mostly bored and depressed, but there is evidence that bidders exhibit more positive emotions as prices fall in the Dutch auction.
An examination of the psychosocial factors impacting workplace accommodation requests in individuals with mental disabilities.

BACKGROUND Individuals with mental health issues experience profound stigma and discrimination, which may contribute to a lack of accommodation utilization to address functional limitations of their work. OBJECTIVES This study examined how psychosocial factors may predict the request of accommodations by employed individuals with mental disabilities through the framework of social cognitive career theory. METHODS In the United States, 148 employed adults with mental disabilities completed an online questionnaire to ascertain self-efficacy, outcome expectation, affect, and workplace support. Logistic regression analyses were conducted to examine associations between respondents' psychosocial factors and request of accommodations. RESULTS Psychosocial factors (i.e., self-efficacy in accommodation request, outcome expectancy in employers' compliance with accommodation request, and non-person cost associated with request) were associated with impacting decisions to request accommodations among individuals with mental disabilities. CONCLUSIONS A focus on bolstering self-efficacy and outcome expectation may assist rehabilitation professionals with facilitating positive occupational outcomes for individuals with mental disabilities. Incorporating increased education on the possible implications of mental disabilities in the workplace may also promote successful employment outcomes.
UAV-BASED RIVER PLASTIC DETECTION WITH A MULTISPECTRAL CAMERA

Abstract. Plastic is the third world’s most produced material by industry (after concrete and steel), but people recycle only 9% of plastic that they have used. The other parts are either burned or accumulated in landfills and in the environment, the latter being the cause of many serious consequences, in particular when considering a long-term scenario. A significant part the plastic waste is dispersed in the aquatic environment, having a dramatic impact on the aquatic flora and fauna. This motivated several works aiming at the development of methodologies and automatic or semi-automatic tools for the plastic pollution detection, in order to enable and facilitate its recovery. This paper deals with the problem of plastic waste automatic detection in the fluvial and aquatic environment. The goal is that of exploiting the well-recognized potential of machine learning tools in object detection applications. A machine learning tool, based on random forest classifiers, has been developed to properly detect plastic objects in multi-spectral imagery collected by an unmanned aerial vehicle (UAV). In the developed approach, the outcome is determined by the combination of two random forest classifiers and of an area-based selection criterion. The approach is tested on 154 images collected by a multi-spectral proximity sensor, namely the MAIA-S2 camera, in a fluvial environment, on the Arno river (Italy), where an artificial controlled scenario was created by introducing plastic samples anchored to the ground. The obtained results are quite satisfactory in terms of object detection accuracy and recall (both higher than 98%), while presenting a remarkably lower performance in terms of precision and quality. The overall performance appears also to be dependent on the UAV flight altitude, being worse at higher altitudes, as expected.
Assessing Excoriation (Skin-Picking) Disorder: Clinical Recommendations and Preliminary Examination of a Comprehensive Interview

Excoriation (skin-picking) disorder (SPD) is a psychiatric condition with variable clinical presentation. We developed the Diagnostic Interview for Skin Picking Problems (DISP), a semi-structured interview designed to assess (1) DSM-5 criteria for SPD and (2) several clinical features of SPD, including the frequency and duration of picking episodes, and the proportion of time devoted to picking at different body areas. The DISP was administered along with other measures to 120 college students (88% women, average age = 22 years) with suspected skin picking problems (based on their responses to a screening survey). The results showed that the DISP had good inter-rater reliability, test–retest reliability over 1–5 months, and convergent/divergent validity. We also found that participants displayed divergent clinical characteristics depending on the pattern of frequency, duration, and body location of picking episodes (e.g., those who primarily picked at the fingers had a unique clinical presentation). Overall, the findings provide preliminary support for the psychometric properties and clinical utility of DISP. The results also underscore the importance of accurately assessing frequency, duration, and body location of picking episodes.