Miracle-dz/UniFAR-FTUs huggingface dataset:
Therapeutic Outcome of Self-Control and Social Interaction Interventions on Negative Body Image among in-school Adolescents with Low Health literacy in Southwest Nigeria

Low health literacy is found to be consistently associated with negative body image. This study examined the effectivenessof Self-Control Therapy (SCT) and Social Interaction Skills Training (SIST) in managing negative body image among senior secondary school students with low health literacy in Southwest Nigeria. The design is pretest-post-test, control group quasi-experimental while the factorial matrix adopted was 3×2×3. Through multi-stage sampling, three Catholic Senior Secondary Schools in Southwest Nigeria were selected. Ninety (90) students, (Males=34, Females= 56) with age range of 14 years to 16 years were randomly selected and assigned to treatment conditions. The experimental groups were exposed to ten Sessions of treatments while the control group served as a comparison group. Body Self-Image Questionnaire-Short Form (BSIQ-SF) (α=0.83), Health Literacy Scale(α=0.88), and Rosenberg Self Esteem Scale (α=0.81) were used for data collection while Analysis of Covariance (ANCOVA) and Bonferroni test were used for data analysis. Results showed a significant main effect of the treatments on the negative body image of the adolescents (F (2, 90) = 1602.50; partial η2=0.98). Participants in SCT had the least adjusted post-test mean score (34.07), followed by SIST (35.23) and control (66.13) groups. Sex of the participants had no significant interaction effect on the treatment outcome. Participants with high self-esteem had a better reduction in managing negative body image (44.27) than those with moderate self-esteem (44.51) and low self-esteem (47.30). A two-way interaction effect of treatments and self-esteem was found. This result provides support for the use of SCT and SIST to manage negative body image of senior secondary school students. These two therapies are therefore, recommended to stakeholders as viable therapies for the treatment of negative body image.
Predicting Worsted Spinning Performance with an Artificial Neural Network Model

For a given fiber spun to pre-determined yarn specifications, the spinning performance of the yarn usually varies from mill to mill. For this reason, it is necessary to develop an empirical model that can encompass all known processing variables that exist in different spinning mills, and then generalize this information and be able to accurately predict yarn quality for an individual mill. This paper reports a method for predicting worsted spinning performance with an artificial neural network (ANN) trained with backpropagation. The applicability of artificial neural networks for predicting spinning performance is first evaluated against a well established prediction and benchmarking tool (Sirolan Yarnspec™). The ANN is then subsequently trained with commercial mill data to assess the feasibility of the method as a mill-specific performance prediction tool. Incorporating mill-specific data results in an improved fit to the commercial mill data set, suggesting that the proposed method has the ability to predict the spinning performance of a specific mill accurately.
Runoff from Cotton Fields Fertilized with Poultry Litter

Broiler litter is a valuable soil amendment for crop production, with litter typically applied to land areas used for grazing and/or hay production. Historically, farmers have based litter application rates on the nitrogen (N) needs of the receiving crop; however, this results in over–application of phosphorus (P). To alleviate the tendency to accumulate P in nearby watersheds, export of litter to other regions has been proposed. A field study was conducted at the University of Arkansas Northeast Research and Extension Center at Keiser, Arkansas, to quantify the impact of poultry litter on runoff water quality from cotton (Gossypium hirsutum L.) cropland in the Mississippi River Delta. Six 0.6–ha fields were fertilized with either commercial fertilizer (annually 140 kg N ha –1 yr –1 in a split application) or poultry litter (7,200 to 9,200 kg litter ha –1 yr –1 ). Runoff from each field was diverted through an H–flume, where water samples were collected. Stage was recorded and used to compute runoff flow. Concentration and mass loss of eight water–quality analytes were measured from 21 individual runoff events over a three–year monitoring period. Seedcotton yield was lower from the litter–fertilized plots, suggesting a need for refinements in the production system. Three–year total mass losses of total suspended solids (TSS) and nitrate nitrogen (NO3–N), as well as total runoff volume, were reduced from fields receiving poultry litter compared to fields receiving commercial fertilizer. Differences associated with the two fertilizer treatments did not clearly exhibit a systematic change over three years, as would be expected if soil structure were changing as a result of the organic amendments. Although total TSS mass loss was reduced, concentrations of nutrients associated with the solid fraction of chicken litter increased periodically in runoff events that immediately followed litter application. Moreover, total loss of orthophosphate P from litter–treated fields was four times greater than from fields fertilized conventionally. Additional research is needed to ensure that poultry litter exported to the Mississippi River Delta region can be applied as part of an integrated crop fertility program that results in the desired agronomic performance while protecting and enhancing water quality.
Sampling Alternatives from Colossal Choice Set: Application of Markov Chain Monte Carlo Algorithm

It is often the case that a discrete choice model cannot be applied to forecasting because the choice set is unmanageably large and choice probabilities cannot be evaluated in a practical manner. For example, an activity-based analysis of travel behavior often involves an astronomical number of potential activity travel patterns, resulting in an enormous choice set when one attempts to formulate the behavior as a discrete choice. A colossal choice set makes it practically impossible to define the full choice set and to evaluate the choice probability of each pattern for forecasting. An algorithm is presented for the simulation of individuals’ activity travel choice by sampling activity travel patterns from a colossal choice set, according to their choice probabilities as determined by a discrete choice model without enumeration of the full choice set. Numerical examples demonstrate the practicality and effectiveness of the algorithm in forecasting the effects on activity travel patterns of transportation policy measures.
Measurement of Contact Stresses for Different Truck Tire Types To Evaluate Their Influence on Near-Surface Cracking and Rutting

Two pavement distress mechanisms have become more prevalent in recent years: near-surface rutting and surface-initiated wheelpath cracking. Some possible factors causing these failure mechanisms include higher traffic volumes, use of lower-quality materials, and changes in tire type and structure. Although all of these factors may play a role, this study concentrated on the effects of changes in tire type and structure on surface distress. Within the last decade, trucking companies have shifted from operation on bias ply tires to an exclusive use of radial tires and the gradual introduction of wide-base (super-single) radial tires. This prevalence of radial tires causes a major change in pavement surface loading characteristics and is shown to help explain the development of surface rutting and cracking. Tire contact stresses were measured for bias ply, radial, and wide-base radial truck tires at various loads and inflation pressures to investigate the effects of tire structure, loading, and inflation pressure on surface loads applied to pavements. It was determined that contact stresses vary significantly for the different types of tires investigated. The observed variations were explained by the differences in tire construction. In fact, tire structure appeared to have a greater influence on contact stresses than variations in either load or inflation pressure for a given tire type. It was shown that the specific characteristics of the complex contact stresses under truck tires have a strong influence on asphalt pavement cracking and rutting and must be considered for proper design and evaluation of asphalt pavements.
Investigation of binary Josephson arrays for arbitrary waveform synthesis

Arrays of Josephson junctions have been used successfully for many years as the primary standard of voltage. A recent development has been the fabrication of arrays, based on non-hysteretic Josephson junctions, which allows the voltage output to be changed almost instantaneously. When these arrays are divided into binary segments a ‘digital-to-analogue converter’ with quantum accuracy is created. The properties of two types of array, a SINIS array, using intrinsic shunting of the Josephson junctions, and a SIS array with external, on-chip shunting have been investigated. The accuracy of the generated voltages and AC properties of the arrays when driven with a purpose-built, programmable current bias source are discussed. It is anticipated that a Josephson standard having waveforms with calculable rms values of AC voltage will soon be available.
WATER QUALITY IMPACTS OF NATURAL FILTER STRIPS IN KARST AREAS

Naturally occurring riparian filter strips are widely recommended as a technique for removing chemicals from flow prior to entering a stream. Data on their effectiveness is sparse as is information on the partitioning of chemicals trapped by various mechanisms in these strips. Studies were conducted on the effectiveness of natural riparian grass buffer strips in removing sediment, atrazine, nitrogen and phosphorus from surface runoff. The strips were located in a karst watershed. No-till and conventional-tillage erosion plots served as the sediment and chemical source area. Runoff from the plots was directed onto 4.57, 9.14, and 13.72 m filter strips where the inflow and outflow concentrations and flow rates were measured. Trapping percentages for sediment and chemicals typically ranged above 90%. An evaluation was made of the distribution of trapped chemicals among infiltrated mass and mass stored in the surface layer. The analysis showed that most of the chemicals were trapped by infiltration into the soil matrix and that trapping efficiency increased with filter stip length and with fraction of water infiltrated.
EVALUATION OF NO-TILLAGE CROP PRODUCTION WITH SUBSURFACE DRIP IRRIGATION ON SOILS WITH COMPACTED LAYERS

Subsurface drip irrigation offers many advantages for management of water and nutrients, but its effectiveness may be limited by weather or soil conditions. Solving soil problems, such as compaction, in subsurface drip irrigation systems is understandably difficult using deep tillage. We hypothesized that the need for deep tillage in conservation tillage systems may be reduced if the compacted soil layers are kept moist enough for root growth. A twoyear experiment that included wheat, soybean, and cotton under no-tillage culture was conducted with subsurface drip irrigation. The irrigation system had been used for five years before this experiment and provided two irrigation drip line spacings (1 m and 2 m) and three irrigation amounts (6, 9, and 12 mm/application). Irrigated soybean yields were greater than rainfed in one of the two years. No differences in yield occurred among irrigation drip line spacing or irrigation amounts. Also, neither cotton nor wheat yields were increased by irrigation. Observations during the growing seasons, cotton root observations after harvest, and soil strength measurements during the spring indicate that considerable soil compaction occurred at very shallow soil depths (< 5 cm) and restricted root growth. This compaction probably limited the efficacy of subsurface drip irrigation, which was located at the 30-cm depth. Based on these results, it appears that strategies must be developed to reduce soil strength to obtain optimum no-tillage crop production with subsurface drip irrigation on these soils.
Characterizing the severity and risk of drought in the Poudre River, Colorado

The implementation of water use restrictions in a given district is very much related to the severity of an evolving drought; thus, water management agencies such as City Water Departments often face the question of how critical or severe a particular drought event is. While this question has typically been examined using drought indices (e.g., the Palmer Drought Severity Index), unfortunately they do not provide any information on the frequency or recurrence time of the drought or on the risk that specific drought events may occur in a given time horizon. In this paper, the severity of alternative drought events are determined following a similar concept as for the severity of floods, i.e., the return period of a flood event, e.g., the 500-year flood. We develop procedures for determining drought severity based on historical data, generated data, and mathematical algorithms. In particular, we focus on the drought that has been occurring in the Western United States and take the Poudre River, Colo. , as an.
Crop identification and disease classification using traditional machine learning and deep learning approaches

Crop and disease classification is one of the important problems in automation of agricultural processes with multi-cropping method where the field is cultivated with more than one crop. In order to solve this classification problem, a study has been carried out in the field cultivating eggplant (Solanum melongena) and tomato (Solanum lycopersicum) using the images obtained from a mobile phone camera. Textural descriptors namely contrast, correlation, energy and homogeneity were extracted from the gray-scale converted RGB image for crop identification, i.e., (tomato or eggplant) and the same descriptors were extracted from the gray-scale converted image from Hue Saturation Value (HSV) for disease classification (due to Cercospora leaf spot disease or two-spotted spider infestation). Discriminant analysis, Naive Bayes algorithm, support vector machine and neural network were the classification algorithms used with a resulting best accuracy of 97.61%, 95.62%, 98.01% and 98.94% for crop identification, 86.09%, 76.52%, 86.96% and 86.04% for disease classification respectively. Similarly, application of algorithm with 6 histogram-based descriptors for health status detection resulted in an accuracy of 66.67%, 37.04%, 50% and 72.9% respectively. Deep learning algorithm namely AlexNet was also evaluated which resulted in an accuracy of 100% for crop identification, 89.36% for health status detection and 81.51% for disease classification. Among the algorithms, AlexNet resulted in the best average accuracy of 90.29% for the above classification tasks.
Design of Interdigitated Capacitors and Their Application to Gallium Arsenide Monolithic Filters

Theoretical expressions for the interelectrode capacitance and conductor losses for an array of microstrip transmission lines are presented. The effect of finite conductor thickness is included in the analysis by introducing equations for the effective width of the transmission lines. Good agreement between theory and experiment is observed up to 18 GHz. Experimental results obtained from a lumped-element GaAs monolithic bandpass filter are in excellent agreement with theory. The filter has 1.5-dB insertion loss at 11.95 GHz and greater than 22-dB loss in the stopband. The filter measures 0.58x 1.3x0. 203 mm.
Building teachers’ voices on teaching in a research-informed teaching course

ABSTRACT This study aims to understand the extent to which 56 teachers developed new academic-based voices about teaching in the context of a research-informed teaching course. The empirical evidence consisted of a set of 228 short reports written by participants on the course. Each report reflects a fragment of knowledge acquired by a teacher and includes four sections: the source of research information, the verbatim text extracted from research, its perceived usefulness, and the type of curriculum content. Each written report was considered a thematic unit of analysis, and data were analysed with qualitative and quantitative methods. Findings showed a wide variety of sources and features of academic information acquired by teachers, teachers’ differing purposes in using this information, and various curriculum-related contents. The findings also revealed three main types of teachers’ academic-based voices, which we have labelled theory-informed voice, practice-informed voice, and educational-tool-informed voice. The study demonstrates that each teachers’ voice was distinctly used in each identified curriculum content.
Mothers on the tenure track: what engineering and technology faculty still confront

Despite the many changes in policy and practice that colleges and universities in the United States have instituted to help women faculty achieve work life balance, challenges persist. This article discusses the difficulties still faced by female engineering and engineering technology faculty who are trying to balance the demands of a successful academic career and motherhood. The data, both qualitative and quantitative, are derived from a survey of tenure track female faculty who are members of the Women in Engineering Division of the American Society for Engineering Education (ASEE). Data indicate that, despite the widespread adoption of policies intended to create a more helpful and collegial environment, almost 40% of the respondents rated the quality of the institutional support they receive as fair, poor, or very poor. This research identifies policies that appear to have succeeded, and others that appear to have made little difference, suggesting structural and cultural changes that would address the continuing problems that motherhood creates for female engineering and technology faculty. Such changes could prove helpful to female faculty generally, regardless of their disciplines.
Reference evapotranspiration forecasting using different artificial neural networks algorithms

The present study aims to apply artificial neural networks (ANNs) for reference evapotranspiration (ETo) prediction. Three different feed-forward artifical neural network (ANN) models, each using varied input combinations of previous months ETo, have been trained and tested. The output of the network was the one-month-ahead ETo. The networks learned to forecast one-month-ahead ETo for Mahanadi reservoir project area using the three learning methods namely quasi-Newton algorithm, Levenberg–Marquardt algorithm and backpropagation with adaptive learning rate algorithm. The training results were compared with each other, and performance evaluations were done for untrained data. The performance evaluations measured were standard error of estimates (SEE), raw standard error of estimates (RSEE), and model efficiency. The best ANN architecture for prediction of ETo was obtained for Mahanadi reservoir project area. The monthly reference evapotranspiration data were estimated by the Penman–Monteith method and used .
Full drive-by-wire dynamic control for four-wheel-steer all-wheel-drive vehicles

Most of the controllers introduced for four-wheel-steer (4WS) vehicles are derived with the assumption that the longitudinal speed of the vehicle is constant. However, in real applications, the longitudinal speed varies, and the longitudinal, lateral, and yaw dynamics are coupled. In this paper, the longitudinal dynamics of the vehicle as well as its lateral and yaw motions are controlled simultaneously. This way, the effect of driving/braking forces of the tires on the lateral and yaw motions of the vehicle are automatically included in the control laws. To address the dynamic parameter uncertainty of the vehicle, a chatter-free variable structure controller is introduced. Elimination of chatter is achieved by introducing a dynamically adaptive boundary layer thickness. It is shown via simulations that the proposed control approach performs more robustly than the controllers developed based on dynamic models, in which longitudinal speed is assumed to be constant, and only lateral speed and yaw rate are used as system states. Furthermore, this approach supports all-wheel-drive vehicles. Front-wheel-drive or rear-wheel-drive vehicles are also supported as special cases of an all-wheel-drive vehicle.
Responding to Mechanical Antigravity

†Based on the experiences of the NASA Breakthrough Propulsion Physics Project, suggestions are offered for constructively responding to proposals that purport breakthrough propulsion using mechanical devices. Because of the relatively large number of unsolicited submissions received (about 1 per workday) and because many of these involve similar concepts, this report is offered to help the would-be submitters make genuine progress as well as to help reviewers respond to such submissions. Devices that use oscillating masses or gyroscope falsely appear to create net thrust through differential friction or by misinterpreting torques as linear forces. To cover both the possibility of an errant claim and a genuine discovery, reviews should require that submitters meet minimal thresholds of proof before engaging in further correspondence; such as achieving sustained deflection of a level-platform pendulum in the case of mechanical thrusters.
Draught Requirement of Trailing-foot and Shallow Injection Equipment for Applying Slurry to Grassland

Abstract Surface spreading of slurry leads to the inevitable emission of ammonia into the environment. Injection of slurry on grassland reduces these emissions. However, injection of slurry by deep working injector tines with goose foot chisels (wings) requires high draught forces. This type of injection has the risk of the crop dying back under dry soil conditions and is not possible on all soil types. In recent years, new slurry application techniques for grassland have been developed that achieve a large reduction in emissions of ammonia, but require less draught force. These techniques include cutting a shallow slit in the sward, into which slurry is applied, and application of the slurry in bands on the soil surface using a trailing foot implement. In a series of experiments on sandy loam, clay and peat soils, the draught force requirement of single elements of five new slurry application techniques was investigated. The application techniques were a trailed sliding foot element and four shallow injection elements: angled-disc coulters (double-disc opener), thick-disc coulter, flat disc coulter followed by a vertical injection coulter and knife coulter followed by a vertical injection coulter. The application technique, working depth and soil conditions had a significant influence on the draught force. For a working depth of 5 cm, the required draught forces per shallow injector element, measured in this experiment, were in the range of 202–706 N for a double-disc opener, 284–991 N for a thick-disc coulter, 361–1260 N for a flat-disc coulter plus injector and 389–1358 N for a knife coulter plus injector. The lowest draught forces occurred on peat soil and the highest forces on dry clay. The trailing foot required an average draught force of 39 N. The draught force of the trailing foot did not relate to the soil conditions but an effect of the grass sward condition was suggested.