Miracle-dz/UniFAR-FTUs huggingface dataset:
Enabling Factors and Barriers for Adopting Engineering Curricula in High Schools: School, District, and State Administrator Perspectives (Fundamental)

Pre-college engineering education has been on a sharp rise in the United States. Numerous schools offer some variation of an engineering curricula, but challenges remain regarding socio-cultural perceptions of engineering, teacher training, curricular alignment with state standards, and policy decisions. Many past studies have examined students’ and teachers’ knowledge, perceptions, and beliefs regarding pre-college engineering instruction. Few studies have investigated the viewpoints of school administrators, or state and district personnel. This qualitative study investigated perspectives of three such administrators in a southwest US public high school. The school was one of nine pilot locations offering a new engineering course designed to ‘demystify’ engineering for high school students and teachers from all walks of life. Results converged around four major themes: 1) relevance and current state of pre-college engineering education, 2) teacher certification and professional development, 3) industry connections, and 4) expectations of pre-college engineering curricula. The resulting themes shed light on long standing issues affecting adoption of engineering at the pre-college level and highlight a few areas that upcoming pre-college engineering education programs could focus on.
Impact Absorbing and Compensation for Heavy Object Catching With an Unmanned Aerial Manipulator

Maintaining stability after catching an object is essential for the flight safety of unmanned aerial manipulators (UAMs). Current research on UAM catching stationary or moving targets neglects the impact of the target and the introduced center of mass (COM) displacement. This letter proposes an approach to absorb the impact during the capture of fast-flying heavy targets by UAMs, ultimately reducing UAM movement. An angular momentum theorem-based fast target mass estimation algorithm is proposed to estimate the target mass within the limited catching time. With the estimated target mass, a mass compensated impedance controller for a brushless motor-based arm and a compensation algorithm for the UAM attitude controller are proposed. An innovative aspect of our approach is utilizing the estimated target mass to adjust the impedance controller and compensate for COM displacement, which enables effective absorption of the target's impact and reduces UAM movement. We validate our proposed approach through simulation and real-world experiments. The results demonstrate that our approach significantly reduces UAM body displacement after capturing fast-flying heavy targets, enhancing UAM's flight safety.
Alcohol and Caffeine Co-Administration Increased Acetylcholinesterase Activity and Inflammatory Cytokines in Sleep-Deprived Rats: Implications for Cognitive Decline and Depressive-Like Manifestations

Sleep deprivation is a major health problem in modern society; it has been worsened by alcohol and caffeine intake to stay awake and improve bodily activities, an experience common among night-shift workers. For the present study, 50 adult male Wistar rats weighing between 150 g and 200 g were randomly selected and divided into 5 groups of 10 rats each (n = 10). Group 1 was the control group; group 2 was the group of sleep-deprived (SD) rats; group 3 was composed SD rats submitted to the administration of 20% alcohol; group 4 comprised SD rats submitted to the administration of 200 mg/kg of caffeine; and Group 5 was composed of SD rats who underwent the co-administration of 20% alcohol and 200 mg/kg of caffeine. At the end of 28 days, the animals were euthanized, and blood samples were collected for biochemical analysis. Memory, anxiety, social behavior and locomotive activity were assessed using the Y-maze, the elevated plus maze, the hole-board and three-chambered social approach tests, and the open field test. The plasma levels of the acetylcholinesterase (AChE) enzyme and inflammatory cytokines (interleukin 6 [IL-6], interleukin 10 [IL-10], and tumor necrosis factor beta, [TNF-β]) were also measured. Data was expressed as mean ± standard error of the mean [SEM] values, and the data were analyzed through analysis of variance (ANOVA) followed by the Tukey post hoc test, with significance set at p < 0.05 . The results revealed that sleep deprivation, and the co-administration of alcohol and caffeine impair memory in rats. Sleep deprivation also caused a significant increase in anxiety and anxiety-related behavior, with decreased social interaction, in rats. Locomotive activity was improved in SD rats, especially in those to which alcohol was administered. Sleep deprivation significantly reduced acetylcholinesterase activity among SD rats and those to which alcohol was administered when compared with the controls. The plasma levels of IL-6, IL-10 and TNF-β were significantly increased in SD rats when compared with the controls. The administration of alcohol and caffeine separately, as well as their co-administration, significantly increased cytokine levels in rats.
Bringing the Concept of Climate-Smart Agriculture to Life

Bringing the Concept of Climate-Smart Agriculture to Life: Insights from CSA Country Profiles across Africa, Asia, and Latin America The Climate-Smart Agriculture (CSA) Country Profile Series assesses climate change challenges and solutions in the agricultural sectors of more than 30 countries across Africa, Asia, and Latin America and the Caribbean (LAC). This report introduces the first analysis of a new dataset drawn from these profiles, aggregating bottom-up results from individual expert assessments of CSA technologies. It offers the most complete overview to date of technologies considered climate-smart around the world. The emerging insights shed light on technologies in different locations and farming systems, their strengths and weaknesses across different dimensions of climate-smartness, and their specific barriers to adoption. As a result, a more concrete and specific picture of CSA emerges that could help demystify the concept, reveal synergies between the three CSA pillars (productivity, adaptation, and mitigation), and allow for more targeted technology deployment and scale-up.
The Role of Sports Clubs in Promoting Social Integration among People with Disabilities in Saudi Arabia

Recently, interest in sports has increased due to its benefits for growth and development. People with disabilities face many challenges when engaging in sports compared to their peers without disabilities due to stigma and socio-cultural prejudices directed against them. Despite the important role that sports clubs may play in promoting social inclusion, few studies in Saudi Arabia have focused on this population. Hence, this study was one of the first to examine the role of sports clubs in promoting social integration among people with disabilities in Saudi society and the effect of demographic and social factors on social integration among people with disabilities recruited from sports clubs in southern Saudi Arabia. The sample included 205 disabled adults aged 18-40 years (M = 29.8 years; SD = 3.82 years). Data were collected using a social inclusion questionnaire for people with disabilities. About 51% of disabled people had low, and 13.17% had high social integration. The levels of social inclusion varied by gender, age, type of disability, academic level, and duration of participation in the club. These findings highlight the need to develop appropriate strategies to enhance the role of sports clubs in promoting the social inclusion of individuals with disabilities. More active efforts should also be made to provide professional coaches with the funds and facilities necessary for the effective operation of sports clubs.
Spatial variability pattern and mapping of selected soil properties in hilly areas of Hindukush range northern, Pakistan

Soil samples at 0-20 cm depth were collected from major crop areas of Hindukush mountainous range, District Chitral, extreme Northwestern Pakistan, during April 2014 to assess their physico-chemical properties and spatial distribution pattern. 103 soil samples were analyzed and maps were created by geostatistical technique of inverse distance weighting and kriging techniques using GIS and GS win-7 computer software. The soil texture ranged from silt loam to dominantly sandy loam, slightly acidic to alkaline and moderate to highly calcareous but with no salinity indication. Soil organic matter was higher than 2 % in about 75 % of samples. Soil pH, EC and lime showed slight dependence on each other with r values from 0.4 to 0.5 while OM varied independently as indicated by their lower correlation values. Semivariogram analysis showed that soil pH, lime, OM had strong spatial dependence (nugget-sill ratio, <25%) while silt, sand, EC had moderately (nugget-sill ratio, 25-75%) and clay had weakly distributed in the area. Linear, Gaussian and exponential models were used for different soil parameter based on nugget, mean prediction error and root mean square standardize prediction error values and maps were developed through extension techniques to cover all the area outside the sampling points.
Do international rankings affect public opinion?

International rankings push governments to adopt better policies by providing comparative information on states’ performance. How do citizens respond to this information? We answer this question through a preregistered survey experiment in Israel, testing the effect of rankings in the fields of human rights and the environment. We find that citizens respond to international rankings selectively. Informed about a high ranking given to their country, citizens tend to express a more positive assessment of the country’s performance. By contrast, they seem to dismiss poor rankings of their country. We further find that poor rankings on a polarising issue, such as human rights, might face a particularly strong resistance from citizens. Overall, our results engage with and support recent scholarship sceptical of the impact of international shaming on public opinion. Even gentle shaming – expressed through a low numerical grade – might not be well received by the public.
Regional W‐Phase Source Inversion for Moderate to Large Earthquakes in China and Neighboring Areas

Earthquake source characterization has been significantly speeded up in the last decade with the development of rapid inversion techniques in seismology. Among these techniques, the W‐phase source inversion method quickly provides point source parameters of large earthquakes using very long period seismic waves recorded at teleseismic distances. Although the W‐phase method was initially developed to work at global scale (within 20 to 30 min after the origin time), faster results can be obtained when seismological data are available at regional distances (i.e., Δ ≤ 12°). In this study, we assess the use and reliability of regional W‐phase source estimates in China and neighboring areas. Our implementation uses broadband records from the Chinese network supplemented by global seismological stations installed in the region. Using this data set and minor modifications to the W‐phase algorithm, we show that reliable solutions can be retrieved automatically within 4 to 7 min after the earthquake origin time. Moreover, the method yields stable results down to Mw = 5.0 events, which is well below the size of earthquakes that are rapidly characterized using W‐phase inversions at teleseismic distances.
Tropical Decadal Variability and the Rate of Arctic Sea Ice Decrease

The trend for cold‐season (November‐December‐January‐February, NDJF) decreases in Arctic sea ice extent from 2000 to 2014 was about a factor of two larger than the 1979–2000 trend, and the warm‐season (June‐July‐August‐September, JJAS) trend was about a factor of three larger. Sensitivity experiments with an atmospheric model show that a negative convective heating anomaly in the tropical Pacific, associated with the negative Interdecadal Pacific Oscillation phase after 2000, produces an atmospheric teleconnection pattern over the Arctic comparable to the observations in NDJF but not JJAS. A positive convective heating anomaly over the tropical Atlantic, associated with warming sea surface temperatures there in the 2000–2014 period, produces a teleconnection pattern over the Arctic comparable to the observations in JJAS but not NDJF. Thus, the observed anomalously strong Arctic surface winds and sea ice drifts after 2000, which produced accelerated decreases in sea ice extent, likely had contributions from decadal‐time scale variability in the tropical Pacific and Atlantic.
Maize Intensification among Smallholder Farmers in Kenya: Understanding the Impacts of Climate

We explore how climate, climate risk and weather affect maize intensification among smallholders in Kenya. We find that each plays an important role in maize intensification choice. The economic implications of this choice are also analyzed. We find that the share of maize area planted to hybrid seeds contributes positively to expected crop income, without increasing exposure to income variability or downside risk. The promotion of maize hybrids is potentially a valuable adaptation strategy to support the well-being of smallholder farmers, especially if these prove tolerant to a wide range of conditions.
Deep Morphological Shrinkage Convolutional Autoencoder-Based Feature Learning of Vibration Signals for Gearbox Fault Diagnosis

Fault diagnosis is significant to guarantee the safety and reliability of the machinery. Local faults will make the collected vibration signals deviate from the normal signals. To extract fault-related features from vibration signals, many deep-learning-based methods have been proposed for machinery fault diagnosis recently. However, due to the extreme conditions (e.g., high background noise and limited labeled training samples), it is a challenging task to implement feature extraction from the collected signals with nonlinear and nonstationary characteristics. To implement feature extraction and noise reduction of vibration signals, this article proposes a novel network, that is, deep morphological shrinkage convolutional autoencoder (DMSCAE) for gearbox fault diagnosis considering the insufficient labeled training samples. First, a morphological convolutional autoencoder is proposed for noise filtering and feature extraction. Second, a multibranch structure with different structural elements (SEs) is used in the morphological layer to extract impulsive components. Finally, a soft thresholding-based shrinkage is employed to filter ineffective features, where an adaptative method is developed to adjust the threshold automatically in the backpropagation procedure. The experiments on two gearbox fault diagnosis tests are conducted to verify the performance of DMSCAE. The results indicate that DMSCAE obtains a better performance for fault diagnosis than other DNNs, for example, efficient channel attention network (ECANet) and self-calibrated convolutional network (SCNet).
Lecturers’ perceptions of a learning management system migration at an open distance learning institution

Learning management systems (LMSs) are common in higher education institutions and form the backbone of open distance and e-learning (ODeL) institutions. Migrating to any new form of technology is known to be a challenging endeavour and LMSs are no exception. This study uses the Unified Theory of Acceptance and Use of Technology (UTAUT) model to analyse open-ended responses to a questionnaire sent to lecturers at an ODeL institution during the migration from one LMS to another. In the study, 83 responses are analysed, and six major themes are discussed. The results indicate that timely and specific support is critical in a technological migration process, and communication around the migration is vital to the morale of lecturers involved. We noted many instances of anxiety due to increased workload factors. We recommend that institutions migrating from one LMS to another conduct pilot studies and focus on clear and effective communication while not underestimating the resources needed for successful migration processes. Keywords: Learning management systems, LMS, migration, Unified Theory of Acceptance and Use of Technology, UTAUT, open distance institutions Perceptions des enseignants concernant la migration d'un système de gestion de l'apprentissage dans un établissement de formation ouverte et à distance Résumé : Les systèmes de gestion de l'apprentissage (LMS) sont courants dans les établissements d'enseignement supérieur et constituent l'épine dorsale des établissements de formation ouverte et à distance (FOAD). La migration vers toute nouvelle forme de technologie est connue pour être une entreprise difficile et les LMS ne font pas exception à la règle. Cette étude utilise le modèle de la théorie unifiée de l'acceptation et de l'utilisation des technologies (UTAUT) pour analyser les réponses ouvertes à un questionnaire envoyé aux enseignants d'un établissement de FOAD pendant la migration d'un LMS à un autre. L'étude analyse 83 réponses et aborde six thèmes principaux. Les résultats indiquent qu'un soutien spécifique et opportun est essentiel dans un processus de migration technologique, et que la communication autour de la migration est vitale pour le moral des enseignants concernés. Nous avons relevé de nombreux cas d'anxiété dus à l'augmentation de la charge de travail. Nous recommandons aux institutions qui migrent d'un LMS à un autre de mener des études pilotes et de se concentrer sur une communication claire et efficace tout en ne sous-estimant pas les ressources nécessaires à la réussite des processus de migration. Mots-clés : Systèmes de gestion de l'apprentissage, LMS, migration, théorie unifiée de l'acceptation et de l'utilisation de la technologie, UTAUT, établissements de formation ouverte et à distance
Analyzing the Impact of Formal Education on Poverty Reduction among Rural Households in Northern Ghana: Evidence from the Jirapa District, Ghana

Poverty is a global phenomenon affecting most people in the developing world including Northern Ghana. The study analysed the nexus between formal education and poverty reduction among rural households in the Jirapa district of Northern Ghana using a mixed-method case study design. A four stage multiple sampling strategy was employed to collect primary data from 701 household heads in the study communities using semi-structured interviews and focus group discussions. The data were analysed using quantitative (regression, chi-square, cross-tabulation, frequencies, percentages) and qualitative analytic tools (content analysis with direct quotations). The results revealed that formal education increases the chances of occupying modernized housing structure and also one’s ability to meet his or her nutritional requirement. The relationship between formal education and poverty reduction (housing type, nutrition, monthly income, economic condition, financial dependency, job security, social exclusion, political exclusion) were statistically significant at the 1%, 5% and 10% probability levels. It is therefore imperative that education be made more accessible and possibly free to the Senior High level to enable households improve their livelihood opportunities.
Benthic Interactions With Renewable Energy Installations in a Temperate Ecosystem

Wave Hub is a Marine Renewable Energy Installation (MREI) off the southwest peninsular of the UK. Wave Hub’s seabed infrastructure, including the main connection unit and 18 km of seabed cable were deployed in 2010. This study assesses the species assemblages present within the Wave Hub development zone in the context of the ecological processes they contribute to local ecosystems. To enhance knowledge on the potential future impacts of MREI the effect of the power cable was quantified, with its associated 80,000 tonnes of rock armoring. Species assemblages were compared between rock armored and control sites two years after installation.
Hygroscopy as an Indicator of Specific Surface Area in Polymer Materials

Specific surface area (SSA) is an integral characteristic of the interfacial surface in poly-disperse systems, widely used for the assessment of technological properties in polymer materials and composites. Hygroscopic water content (Wh) is an obligate indicator of dispersed materials prior to any analysis of their chemical composition. This study links both indicators for the purpose of the express assessment of SSA using widely available Wh data, on the example of natural (starch, cellulose) and synthetic (acrylic hydrogels) polymer materials. The standard BET analysis of SSA using water vapor desorption was chosen as a reference method. In contrast to the known empirical correlations, this study is based on the fundamental thermodynamic theory of the disjoining water pressure for the connection of the analyzed quantities. The statistical processing of the results for the new methodology and the standard BET method showed their good compliance in a wide range of SSA from 200 to 900 m2/g. The most important methodological conclusion is the possibility of an accurate physically based calculation of hydrophilic SSA in polymer materials using their Wh data at a known relative humidity in the laboratory.
Green IoT Based on Tropical Weather: The Impact of Energy Harvesting in Wireless Sensor Network

Wireless Sensor Networks (WSNs) are a key component of Green IoT, as they play a critical role in many applications. However, a major challenge faced by WSNs is their limited energy capacity, which can impede their effectiveness. To address this issue, energy harvesting techniques are used to harness ambient energy and power the nodes, eliminating the need for frequent battery replacements or recharging. This study proposes a solar energy harvesting technique to prolong the lifespan of each wireless sensor node in a network. The aim of the research is to assess the impact of energy harvesting on wireless sensor networks with a focus on solar ambient light energy, as it is a critical component of achieving a Green Internet of Things (IoT). The study is adapted to the tropical weather of Malaysia and its forecasted conditions. Through the use of NetSim simulations, the energy efficiency and reliability of the network are evaluated using solar energy harvesting. The recharge rate for energy harvesting in a wireless sensor network is calculated to be 2.34W per day using a 55x70mm solar photovoltaic panel based on Malaysia weather forecasts and sun hours. This proposed method is successfully executed using NetSim, which utilizes real device parameters for a WSN in a simulated agriculture environment. The results show an overall improvement of 22.4 percent in performance parameters in all areas, including energy consumption, network layer, routing performance, and IEEE 802.15. 4 metrics, representing a significant improvement. With the implementation of solar energy harvesting, traditional energy of WSNs can benefit from developing smart agricultural monitoring systems. This efficient method and calculation for solar energy harvesting can help to sustain the infinite lifetime of WSN by optimizing the operational time to 18% of the duty cycle. Results demonstrate that the proposed method can effectively increase the energy efficiency and reliability of the network, making it a promising solution for WSNs operating in tropical regions. This research contributes to the development of sustainable and energy-efficient WSNs, promoting the Green IoT concept.