Miracle-dz/UniFAR-FTUs huggingface dataset:
Sustainable Surface Water Storage Development: Measuring Economic Benefits and Ecological and Social Impacts of Reservoir System Configurations

This paper illustrates an approach to measuring economic benefits and ecological and social impacts of various configurations of reservoir systems for basin-wide planning. It suggests indicators and examines their behavior under several reservoir arrangement scenarios using two river basins in Sri Lanka as examples. A river regulation index is modified to take into account the volume of flow captured by reservoirs and their placement and type. Indices of connectivity illustrate that the lowest river connectivity in a basin results from a single new reservoir placed on the main stem of a previously unregulated river between the two locations that command 50% and 75% of the basin area. The ratio of the total affected population to the total number of beneficiaries is shown to increase as the cumulative reservoir capacity in a river basin increases. An integrated index comparing the performance of different reservoir system configurations shows that while results differ from basin to basin, the cumulative effects of a large number of small reservoirs may be comparable to those with a few large reservoirs, especially at higher storage capacities.
A novel single‐feed filtering dielectric resonator antenna using slotline‐loaded coupling structure

This paper proposes a novel single‐feed filtering dielectric resonator antenna (FDRA) using fusion design method and the microstrip‐slot coupled feeding structure. Two pairs of slotlines are elaborately designed and perpendicularly loaded on the coupling slot to provide two radiation nulls at the edges of the passband. Therefore, a compact DRA with a quasi‐elliptic function bandpass response is constructed without extra filter circuits. Furthermore, two radiation nulls can be individually controlled through changing the length of the corresponding slotlines. For proving the effectiveness of the design, a prototype FDRA operation at 3.45 GHz is fabricated and measured. The measured results show that the peak realized gain is 5.84 dBi and the ‐10dB impedance bandwidth is 10.29% (3.29 ‐ 3.65 GHz). The proposed FDRA not only has good performance, but also has simple design.
Orally Administrated Recombinant Vaccinia Virus Displaying ROP4 Induces Protection against Toxoplasma gondii Challenge Infection

Recombinant vaccinia viruses (rVVs) are attenuated viruses and are widely utilized as vectored vaccine platforms against numerous diseases. However, the protective efficacy of these rVV vaccines against Toxoplasma gondii and the resulting mucosal immunity has not been thoroughly assessed. Here, rVVs expressing the rhoptry protein 4 (ROP4) of T. gondii were generated. To evaluate the protection induced by the vaccines, mice were orally immunized with the ROP4-rVVs and subsequently challenge-infected with a lethal dose of T. gondii ME49 strain. Immunization with the rVVs induced higher levels of parasite-specific IgG and IgA antibody responses in sera compared to unimmunized control (NC). Upon challenge infection, significantly higher levels of IgG or IgA antibody responses in the brain, intestines, and vaginal samples were found in the immunized mice compared to NC. The ROP4-rVV vaccination elicited potent IgG and IgA secreting cell (ASC) responses, while substantially enhancing germinal center B cell, as well as CD4+ and CD8+ T cell responses from lymphoid organs. The production of pro-inflammatory cytokines IFN-γ and IL-6 in the brains was markedly diminished following immunization. The immunized mice also experienced reduced bodyweight loss and possessed fewer brain cysts than the control group. These results suggest that oral delivery of ROP4 displaying rVVs induced mucosal and systemic immunities that contributed to protection against lethal T. gondii challenge infection.
Association of Organizational Context, Collaborative Practice Models, and Burnout Among Physician Assistants in Oncology

PURPOSE: Despite an increase in the number of physician assistants (PAs) in the oncology workforce, their potential to meet anticipated demand for oncology services may be hindered by high rates of burnout. The aim of this study was to examine the association between organizational context (OC) and burnout among oncology PAs to better understand factors associated with burnout. METHODS: A national survey of oncology PAs was conducted to explore relationships between burnout and the OC in which the PA practiced. The Areas of Worklife Survey (AWS) assessed OC by examining six key workplace qualities (workload, control, reward, community, fairness, and values). Burnout was assessed using the Maslach Burnout Inventory. RESULTS: PAs demonstrating burnout scored significantly lower across all domains of the AWS than those without burnout (P < .001 for each AWS subscale). The median score for each domain of the AWS and burnout (No v Yes) were as follows: workload (3.33 v 2.67), control (3.67 v 3.00), reward (4.00 v 3.67), community (4.00 v 3.67), fairness (3.33 v 2.67), and values (4.00 v 3.33). Multivariable analysis found that mismatches between the PA and their work environment in workload (odds ratio [OR] = 1.99; 95% CI, 1.32 to 3.02; P = .001), reward (OR = 1.89, 95% CI, 1.18 to 3.02; P = .008), and values (OR = 2.25; 95% CI, 1.31 to 3.88; P = .003) were more likely to report burnout. Differences in burnout in the context of workload were not explained by patient volume, practice structure, or professional autonomy. CONCLUSION: Workload, reward, and values were associated with greater odds of burnout, with workload being the most common mismatch in job fit. Sustainable workloads and consistency in rewards (financial, institutional, and social) for oncology PAs should be an employer's focus to help mitigate their risk of burnout.
Noise Annoyance Prediction of Urban Substation Based on Transfer Learning and Convolutional Neural Network

The noise pollution caused by urban substations is an increasingly serious problem, as is the issue of local residents being disturbed by substation noise. To accurately assess the degree of noise annoyance caused by substations to surrounding residents, we established a noise annoyance prediction model based on transfer learning and a convolution neural network. Using the model, we took the noise spectrum as the input, the subjective evaluation result as the target output, and the AlexNet network model with a modified output layer and corresponding parameters as the pre-training model. In a fixed learning rate and epoch setting, the influence of different mini-batch size values on the prediction accuracy of the model was compared and analyzed. The results showed that when the mini-batch size was set to 4, 8, 16, and 32, all the data sets had convergence after 90 iterations. The root mean square error (RMSE) of all validation sets was lower than 0.355, and the loss of all validation sets was lower than 0.067. As the mini-batch size increased, the RMSE, loss, and mean absolute error (MAE) of the verification set gradually increased, while the number of iterations and the training duration decreased gradually. In this test, a mini-batch size value of four was appropriate. The resultant convolutional neural network model showed high accuracy and robustness, and the error between the prediction result and the subjective evaluation result was between 2% and 7%. The model comprehensively reflects the objective metrics affecting subjective perception, and accurately describes the subjective perception of urban substation noise on human ears.
NOx–Smoke Trade-off Characteristics in a Palm Oil-Fueled CRDI Diesel Engine under Various Injection Pressures and EGR Rates

Palm oil is one of the most common and productive vegetable oils, so it is often used as an excellent feedstock for biodiesel production. However, due to the high viscosity and other issues of palm oil, it cannot be directly used as an alternative fuel for diesel engines unless some treatment is carried out. In this study, the effects of palm oil-diesel blend fuel on the nitrogen oxides (NOx)–smoke trade-off characteristics were investigated in a common rail direct injection (CRDI) diesel engine under various injection pressures and exhaust gas recirculation (EGR) rates. It was found that NOx and smoke from the combustion of fuel containing 50% palm oil (P50D50) were simultaneously suppressed by 3% and 3.1% compared with diesel fuel at an injection pressure of 400 bar, respectively. The performance of P50D50 was comparable to that of diesel, but at high injection pressure and high EGR rate, it showed shorter ignition delay (ID) and lower smoke emission.
Genome-Wide Identification of DNA Binding with One Finger (Dof) Gene Family in Tartary Buckwheat (Fagopyrum tataricum) and Analysis of Its Expression Pattern after Exogenous Hormone Stimulation

Simple Summary A number of studies have demonstrated that DNA binding with one finger (Dof) proteins are involved in multiple biological processes. In the present study, Dof genes or proteins in Tartary buckwheat (FtDofs) were systematically analysed, including their physical properties, phylogenetic relationships, structure, motif composition, cis-acting elements present in promoter regions, chromosomal distribution, gene duplication events, syntenic relationships, expression patterns in different tissues and different fruit developmental stages and responses to exogenous hormone stimulation. The results indicated that the expansion of FtDofs was mainly due to segmental duplication. The tissue-specific expression patterns of FtDofs and their positive responses to exogenous hormone stimulation suggest that they play important roles in the growth and development of Tartary buckwheat as well as in the adaptation to environmental changes. Collectively, this study lays a foundation for further exploration of the function of FtDof genes in Tartary buckwheat. Abstract DNA binding with one finger (Dof) proteins have been proven to be involved in multiple biological processes. However, genome-wide identification of the Dof gene family has not been reported for Tartary buckwheat (Fagopyrum tataricum). In this study, 35 FtDof proteins were identified, and they could be divided into nine phylogenetic subgroups. Proteins within the same subgroup had similar gene structure and motif composition. Moreover, abundant cis-acting elements were present in the promoter regions of FtDof genes. Segmental duplication was the primary driving force for the evolution of the FtDof gene family. Synteny analysis indicated that Tartary buckwheat was closer to dicotyledons, and more orthologous Dof genes existed among them. The expression pattern of FtDofs in different tissues and at different fruit developmental stages varied. Different tissues contained several genes that were specifically expressed. FtDof expression was mainly upregulated under methyl jasmonate treatment and downregulated under other hormone treatments. Taken together, FtDofs may play important roles in the growth and development of Tartary buckwheat and in response to abiotic and biotic stresses. Therefore, the genome-wide identification and expression pattern analysis of the Tartary buckwheat Dof gene family lays a foundation for further exploration of the functional characteristics of FtDofs in the future.
Impact Damage Detection of a Glass Fabric Composite Using Carbon Fiber Sensors with Regard to Mechanical Loading

Structural Health Monitoring (SHM) of composite structures leads to greater safety during operation and reduces the cost of regular inspections. Impact damage detection is an important SHM task. Since impact damage can significantly reduce the lifetime of composite structures, sensors for impact damage are of great interest. Carbon Fiber Sensors (CFSs) can be used to detect composite damage. CFSs are lightweight and compact, and they can be integrated during the manufacturing process. In our study, CFSs were manufactured from three types of carbon fiber tows and were integrated into different layers of the lay-up in order to investigate the influence on impact damage detection. The effect of mechanical loading and temperature change on the measured electrical resistance was investigated during cyclic flexural tests. It was revealed that, it is possible to distinguish between changes in measured signals due to impact and due mechanical loading. The change in the measured electrical signal caused by temperature can be eliminated. CFSs can be used for impact damage detection of a glass fabric composite. A combination of thermography and CFSs as an active heating element also provides good results in the field of impact damage detection
The ABC's (Autoimmunity, Blood Type, Cytokines) in Types and Severity of Reactions to COVID-19 Vaccines.

Based on initial reports of the association of blood types, especially type A, on increasing susceptibility and more severe disease in patients with Covid-19 disease, an observational study was performed to determine if there would be any correlation of bad side effects to the COVID-19 vaccines, associated with blood types, especially type A. At the time of study, only mRNA vaccines had been approved and available, thus Moderna and Pfizer were the ones evaluated. If an association was found, then the same evaluation could be done with vector vaccines, such as Johnson and Johnson, which was recently approved. Vaccine reactions were categorized as “Bad”, if the participant experienced 6 of 9 of the following symptoms: fever (temperature >100.4 F), extreme fatigue, headaches, body aches, chills, nausea, vomiting, arm soreness > 3 days, and numbness in any area of the body. “Moderate”, having 3 or 4 of the symptoms and “Mild”, having 1 or 2 symptoms. Comparing participants with bad reactions; 28 of 39 type A (71.7%) vs. 4 of 39 type O (10.2%) experienced bad reactions, (Chi-square found P<.001). When comparing participants with at least moderate reactions, type A, B, AB together (52) vs. type O (39), there were 40/52 (76.9%) in type A, B & AB group, vs. 7/39 (17.9%) in type O people. There have been reported findings of patients with prolonged, long term and chronic health consequences, months after the initial illness, referred to as (Long COVID). If these are seen as a result of vaccination too, especially those with severe initial reactions, people may find themselves deciding if the risk of developing a chronic illness, outweighs the risk of acquiring the COVID-19 disease. Abbreviations: Coronavirus disease (COVID-19); World Health Organization (WHO); Center for Disease Control (CDC); Acute Respiratory Syndrome (ARS); Electric Health Record (EHR); Emergency Use Authorization (EUA); Interleukins (IL).
Gamification in Genetics: Effects of Gamified Instructional Materials on the STEM Students’ Intrinsic Motivation

Gamification in education offers an innovative way of learning. However, some studies claim that, while it helps raise students' motivation, the kind of motivation is extrinsic and, so, intrinsic motivation declines with time. The researchers used the descriptive research design to describe the STEM students’ intrinsic motivation along with the utilization of game elements in teaching genetics through a learning management system. The researchers collected quantitative data using the Intrinsic Motivation Inventory, which were analyzed through descriptive statistics and complemented with qualitative data from the students' journals and interviews. Overall, the students agreed (M = 5.38, SD = 1.20) that gamification, despite being characterized as extrinsically motivating, had intrinsically motivated them. Its proper implementation helps students adapt to and overcome unfavorable behaviors towards competitiveness and emphasizes the role of teachers in facilitating learning. Time constraints, peer pressure, and distractions were noted; hence, more research is needed to address these challenges and determine the long-term effects of gamification.
A Systematic Method for Selecting Molecular Descriptors as Features When Training Models for Predicting Physiochemical Properties

Machine learning has proven to be a powerful tool for accelerating biofuel development. Although numerous models are available to predict a range of properties using chemical descriptors, there is a trade-off between interpretability and performance. Neural networks provide predictive models with high accuracy at the expense of some interpretability, while simpler models such as linear regression often lack in accuracy. In addition to model architecture, feature selection is also critical for developing interpretable and accurate predictive models. We present a method for systematically selecting molecular descriptor features and developing interpretable machine learning models without sacrificing accuracy. Our method simplifies the process of selecting features by reducing feature multicollinearity and enables discoveries of new relationships between global properties and molecular descriptors. To demonstrate our approach, we developed models for predicting melting point, boiling point, flash point, yield sooting index, and net heat of combustion with the help of the Tree-based Pipeline Optimization Tool (TPOT). For training, we used publicly available experimental data for up to 8351 molecules. Our models accurately predict various molecular properties for organic molecules (mean absolute percent error (MAPE) ranges from 3.3% to 10.5%) and provide a set of features that are well-correlated to the property. This method enables researchers to explore sets of features that significantly contribute to the prediction of the property, offering new scientific insights. To help accelerate early stage biofuel research and development, we also integrated the data and models into a open-source, interactive web tool.
Adaptive Servo-Ventilation as a Novel Therapeutic Strategy for Chronic Heart Failure

The introduction of new therapeutics for patients with chronic heart failure, including sacubitril/valsartan, sodium-glucose cotransporter 2 inhibitors, and ivabradine, in addition to beta-blockers, angiotensin converting enzyme inhibitors, and mineralocorticoid receptor antagonists, lends an opportunity for significant clinical risk reduction compared to what was available just one decade ago. Further clinical options are needed, however, for patients with residual clinical congestion refractory to these therapies. Adaptive servo-ventilation is a novel therapeutic option to address significant clinical volume in cases resistant to medical therapy. The aggregate benefit of these additional therapeutic strategies in addition to foundational medical therapy may be a promising option in the selected candidates who do not achieve acceptable clinical and quality-of-life improvements with oral medical therapy alone. Now is the era to reconsider the implication of an adaptive servo-ventilation-therapy-incorporated medical therapeutic strategy for patients with congestive heart failure.
ECONOMIC VALUATION OF A NATURAL RECREATION AREA: THE VULCANOTOUR IN MERAPI VULCANO

Daerah Istimewa (the special province of) Yogyakarta or usually abbreviated as DIY is the second biggest tourism destination in Indonesia, after Bali. DIY has more than 100 recreation sites. One of the famous recreation sites in DIY is Vulcanotour (VT) located in the area of Merapi Vulcano. This paper employed the individual travel cost method ITCM) to estimate the economic value of VT. We used OLS, Non-linear Normal/NLS, Poisson, and Negative Binomial methods to estimate the regression. This study used primary data from the management of VT and 60 visitors in the period of April to May 2013. The study found that the number of visits to VT was significantly affected by the number of trips to Yogyakarta City (the capital city of DIY). The economic value per visit of VT were ranged from USD 33.1 to USD 153.4. The study also concluded that the number of trips to VT is significantly influenced by the Yogyakarta city as a destination. In other words, the VT cannot be separated from other recreation destinations in DIY.Keywords: Natural recreation area; Individual Travel Cost Method (ITCM); Merapi Vulcano; Vulcanotour; Yogyakarta
THE EFFECT OF USING INSTRUCTIONAL RUBRICS ON EFL STUDENTS’ WRITING PERFORMANCE: A HIGH SCHOOL CASE IN THE MEKONG DELTA OF VIETNAM

Teaching EFL writing has been one of the most trending research fields recently. Among the techniques being tested, using instructional rubrics has drawn much attention from researchers and teachers. This study aimed to investigate the effectiveness of using rubrics in enhancing students’ writing skill and the students’ attitudes towards this technique. The study used the experimental research design. The participants were thirty English-majored eleventh-grade students (N=30) in a high school in Can Tho City, Viet Nam. The main research tools included two guiding rubrics, one writing pre-test, two writing post-tests, and a questionnaire. Holistic and analytic rubrics were used in the teaching of writing skill to the participants to help them understand the targets for learning and the standards of quality for their writing work. Data from the pre- and post- writing tests indicated significant changes in students’ writing performance after using both holistic and analytic rubrics. Besides, the results of the questionnaire revealed learners’ positive perceptions of this technique. It could be suggested that high school teachers should take into account the use of rubrics in teaching writing for EFL students. Article visualizations:
The characteristics of the b-value anomalies preceding the 2004 M w9.0 Sumatra earthquake

Abstract For earthquakes (M ≥ 4.9) that occurred in the region limited by latitudes 2°S–16°N and longitudes 90°E–101°E from 1 January 1973 to 25 December 2004, we investigated temporal variations of the b value in the aftershock zone to determine its abnormal characteristics prior to the 2004 M w9.0 Sumatra earthquake. The b value was estimated via the maximum likelihood method. We found that the b value significantly decreased by ∼36% in the aftershock zone from January 1990 to December 1999. From 2000 onwards until the Sumatra earthquake, the b value was persistently low (between 1.0 and 1.2). Furthermore, we calculated the spatial distribution of the relative changes in b value from 1990 to 1999. Only one area of larger relative declines in b value (>25%) was located very near to the epicentre of the Sumatra event. We also calculated the b values as a function of time for earthquakes in this area and its immediate vicinity. The result shows that the changes of b value with time around the epicentre is similar to that in the aftershock zone, but the relative decline amount is ∼40% around the epicentre, greater than that in the aftershock zone. Therefore, if our finding is confirmed, it will help to better constrain the location of future great earthquakes in seismic hazard analysis.