Miracle-dz/UniFAR-FTUs huggingface dataset:
Identifying the Agricultural Mechanics Knowledge and Skills Needed by Iowa School-based Agricultural Education Teachers

A historical portion of many school-based agricultural education (SBAE) programs, agricultural mechanics remains popular in schools across the nation. As such, pre-service and in-service teachers should be prepared to effectively deliver agricultural mechanics instruction (Burris, Robinson, & Terry, 2005). Agricultural education researchers (McKim & Saucier, 2012; Pate, Warnick, & Meyers, 2012) have identified many laboratory management competencies and welding skills that teachers should have; however, few knowledge and skill areas in other components of agricultural mechanics (e.g., woodworking, electricity, etc.) have been identified. Through the lens of Roberts and Ball’s (2009) content-based model for teaching agriculture, we used the Delphi technique to identify the agricultural mechanics knowledge and skills that Iowa SBAE teachers should possess to provide quality instruction. A panel of 10 expert Iowa SBAE teachers provided the data for the present study. After three rounds, a total of 85 items reached consensus, which included 35 technical skills (e.g., plasma cutting, etc.) and 49 “teacher skills”/laboratory management skills (e.g., ordering consumables). We concluded that SBAE stakeholders in Iowa should ensure that teachers are prepared to teach agricultural mechanics via coursework and professional development opportunities. We recommend that this study be replicated in other states.
Prediction of Student Final Exam Performance in an Introductory Programming Course: Development and Validation of the Use of a Support Vector Machine-Regression Model

This paper presents a Support Vector Machine predictive model to determine if prior programming knowledge and completion of in-class and take home formative assessment tasks might be suitable predictors of examination performance. Student data from the academic years 2012 - 2016 for an introductory programming course was captured via ViLLE e-learning tool for analysis. The results revealed that student prior programming knowledge and assessment scores captured in a predictive model, is a good fit of the data. However, while overall success of the model is significant, predictions on identifying at-risk students is neither high nor low and that persuaded us to include two more research questions. However, our preliminary post analysis on these test results show that on average students who secured less than 70% in formative assessment scores with little or basic prior programming knowledge in programming may fail in the final programming exam and increase the prediction accuracy in identifying at-risk students from 46% to nearly 63%. Hence, these results provide immediate information for programming course instructors and students to enhance teaching and learning process.
Material classification using convolution neural network (CNN) for x-ray based coded aperture diffraction system

Transmission x-ray systems rely on the measured photon attenuation coefficients for material imaging and classification. While this approach provides high quality imaging capabilities and satisfactory object discrimination in most situations, it lacks material-specific information. For airport security, this can be a significant issue as false alarms require additional time to be resolved by human operators, which impacts bag throughput and airport operations. Orthogonal techniques such as X-ray Diffraction Tomography (XRDT) using a coded aperture provide complementary chemical/molecular signatures that can be used to identify a target material. The combination of noisy signals, variability in the XRD form factors for the same material, and the lack of a comprehensive material library limits the classification performance of the correlation based methods. Using simulated data to train a 1D Convolution Neural Network (CNN), we found relative improvements in classification accuracy compared to the correlation based approach we used previously. These improvement gains were cross-validated using the simulated data, and provided satisfactory detection results against real experimental data collected on a laboratory prototype.
Wireless Power Transfer and Energy Harvesting: Current Status and Future Prospects

The rechargeable battery is the conventional power source for mobile devices. However, limited battery capacity and frequent recharging requires further research to find new ways to deliver power without the hassle of connecting cables. Novel wireless power supply methods, such as energy harvesting and wireless power transfer, are currently receiving considerable attention. In this article, an overview of recent advances in wireless power supply is provided, and several promising applications are presented to show the future trends. In addition, to efficiently schedule the harvested energy, an energy scheduling scheme in the EH-powered D2D relay network is proposed as a case study. To be specific, we first formulate an optimization problem for energy scheduling, and then propose a modified two stage directional water filling algorithm to resolve it.
Design Optimization for Low-Power Reconfigurable Switched-Capacitor DC-DC Voltage Converter

Low-power circuits often employ dynamic voltage scaling and energy harvesting. Such circuits need a power management unit that can convert the voltage source to a wide range of target voltages with high efficiency. Targeting such a power management unit, this paper presents a reconfigurable architecture of switched capacitor (SC) voltage converter. It introduces a design optimization methodology that can determine trade-off among design parameters to meet the goal. The proposed converter employs a reconfigurable topology with four capacitors. It provides 11 conversion ratios: 6 step-down and 5 step-up ratios supporting wide input/output voltage range. An analytical model for the output impedance of the proposed reconfigurable SC topology is presented. Using the model, the proposed optimization methodology can minimize the total power dissipation. To validate the proposed architecture and optimization methodology, the converter has been implemented in a 130-nm CMOS process using integrated capacitors of total size 2.2 nF. Simulation results show that the optimized converter circuit achieves an efficiency range from 83.41% to 74.69% for a load current of $100~\mu \text{A}$ .
Detecção de Posicionamento em Tweets sobre Política no Contexto Brasileiro

Opinions shared over the Web constitute big volumes of data. Moreover, they may contain stances that are expressed directly or indirectly. Hence, stance detection may help to define the polarity related to a target idea. Here, we present the characterization of a broad set of tweets in Portuguese about the 2018 Brazilian presidential race. Such a set serves as the basis for automatic stance detection through a semi-supervised approach. In our evaluation, we find clues on the presence of bots in the network. We also evaluate three classifiers with paired statistical test, and our results present F-Measure above 94%.
Tourists’ Preferences for Alpine Pastures Maintenance

Traditional extensive agriculture is the main factor of landscape management in the mountains: a large part of the Alps is modelled by agriculture. Interpreted as a multifunctional activity, including landscape modelling and maintenance, agriculture generates the conditions under which mountain pasture landscape is an economic resource potentially exploitable by tourism. The aim of this work is to draw the profiles of tourists of mountain pastures and to estimate their Willingness to Pay (WTP)for landscape pastures resilience. The innovation of this work lies in the use of a multivariate approach using Contingent Valuation Method (CVM), Multiple Correspondence Analysis (MCA) and Hierarchical Cluster Analysis (HCA). The analysis obtained three clusters that identify different tourists’ profiles. The main result is the existence of a positive WTP for the permanence of pasture systems with an agricultural management. Policy guidelines have been proposed to institutions owning pastures and huts to manage these assets.
Efficacy of APD in perioperative period of non-abdominal operation for peritoneal dialysis patients

Objectives: Whether automated peritoneal dialysis (APD) is a feasible strategy in perioperative period of uremic patients undergoing nonabdominal surgery remains unclear. This study was conducted to research the perioperative management and the best choice of dialysis modalities for peritoneal dialysis patients. Materials and methods: A retrospective analysis was made on the clinical data of 58 ESRD patients who had received peritoneal dialysis for more than three months were treated with APD during perioperative period from July 2015 to March 2018 in the Second Affiliated Hospital of Soochow University. The differences of clinical parameters, such as urine volume, ultrafiltration volume, hemoglobin, renal function and electrolytes were collected and analyzed before and after APD. Results: The vital signs of 58 patients were stable after APD treatment, and there were no significant differences in 24-hour urine volume, hemoglobin and electrolytes (calcium, phosphorus, potassium, sodium) before and after surgery (P>0.05). Compared with those before treatment, the amount of ultrafiltration increased significantly (P<0.05), creatinine, urea nitrogen and parathyroid hormone decreased significantly (P<0.05), while albumin decreased (P<0.05). Conclusion: Application of APD for peritoneal dialysis patients undergoing nonabdominal surgery during the perioperative period is safe and effective.
Influence of Thiameturon and DPX-L5300 on Wild Oats (Avena fatua) Control with Barban, Diclofop, AC 222,293, and Difenzoquat

In field studies, wild oat control with AC 222,293 and difenzoquat was not reduced when each herbicide was applied in combination with thiameturon or DPX-L5300. Mixtures of barban with thiameturon gave wild oats control similar to barban applied alone, but mixtures of barban with DPX-L5300 sometimes gave less wild oats control than barban applied alone. Control was reduced when diclofop was applied in combination with thiameturon in 1985 but not in 1986. When antagonism occurred, addition of crop oil concentrate (COC) at 1.2 L/ha to the diclofop-thiameturon spray mixture overcame the antagonism. When diclofop was applied in combination with DPX-L5300, control was reduced and antagonism could not be overcome by increasing the diclofop rate or by adding COC to the spray mixture. In greenhouse studies the inert ingredients in the thiameturon and DPX-L5300 formulations did not antagonize diclofop activity on wild oats. TLC analysis of 14C-diclofop solutions with and without thiameturon or DPX-L5300 revealed neither degradation products of diclofop nor evidence of complexing between diclofop and thiameturon or diclofop and DPX-L5300. Diclofop antagonism by thiameturon or DPX-L5300 was not due to a chemical or physical interaction between the herbicides in the spray mixture.
Demand Prediction with Machine Learning Models; State of the Art and a Systematic Review of Advances

Electricity demand prediction is vital for energy production management and proper exploitation of the present resources. Recently, several novel machine learning (ML) models have been employed for electricity demand prediction to estimate the future prospects of the energy requirements. The main objective of this study is to review the various ML models applied for electricity demand prediction. Through a novel search and taxonomy, the most relevant original research articles in the field are identified and further classified according to the ML modeling technique, perdition type, and the application area. A comprehensive review of the literature identifies the major ML models, their applications and a discussion on the evaluation of their performance. This paper further makes a discussion on the trend and the performance of the ML models. As the result, this research reports an outstanding rise in the accuracy, robustness, precision and the generalization ability of the prediction models using the hybrid and ensemble ML algorithms.
Proteostasis collapse halts G1 progression and delimits replicative lifespan

Loss of proteostasis and cellular senescence are key hallmarks of cell aging, but whether they are subject to direct cause-effect relationships is not known. We show that most yeast cells arrest in G1 before death with low nuclear levels of cyclin Cln3, a key activator of Start extremely sensitive to chaperone status. Chaperone availability is seriously compromised in aged cells, and the G1 arrest coincides with massive aggregation of a metastable chaperone-activity reporter. A mathematical model integrating autocatalytic protein aggregation and a minimal Start network recapitulates empirical observations. As key predictions, G1-cyclin overexpression increases lifespan in a chaperone-dependent manner, and lifespan reduction by enforced protein aggregation is greatly alleviated by increased expression of specific chaperones or cyclin Cln3. Overall, our data indicate the crucial role of chaperone malfunction in setting lifespan in yeast cells, and configure a molecular pathway whereby proteostasis breakdown acts as a direct effector of cell senescence.
Macrophages in bacterial lung diseases: phenotype and functions (review)

This literature review is devoted to the analysis of the role of macrophages in the immunopathogenesis of infectious lung diseases of bacterial etiology. The article summarizes information about the origin of macrophages, their phenotypic and functional heterogeneity. The mechanisms of impaired protective function of innate immunity are associated with the polarization of the program of maturation and activation of macrophages in the direction to tolerogenic or immunoregulatory cells with phenotype of M2. Alveolar macrophages perform a variety of functions (from pro-inflammatory to regenerative) in the development of inflammation in the respiratory organs. Their inherent plasticity suggests that the same macrophages can change their phenotype and function depending on the microenvironment in the inflammatory focus at different stages of the disease. Understanding the mechanisms that regulate macrophage plasticity will be an important step towards realizing the potential of personalized immunomodulatory therapy.
Studies in Personal space

Surprisingly little is known about the way people use space. Social scientists in the field of human ecology have been concerned primarily with the distribution of such things as social classes, economic institutions, and mental illness. An almost unexplored area is microecology or the way that people in pairs or small groups arrange themselves. In the studies of Hediger (5), Howard (6), and Von Uexkull (15), "space" has had two different meanings. The more familiar of these refers to space in the geographic sense, i.e., space as area. It is most commonly discussed with reference to the animal's territory or home. However, some writers have applied the concept of territory to human behavior. W. F. Whyte (16) and Thrasher (14) have studied the territories of adolescent gangs. W. H. Whyte (17) also has studied the groupings of people within a housing development. Probably the most intensive investigation thus far has been that of Barker and Wright (2) in the Midwest. Yet this still remains relatively unexplored territory for social scientists. The second way in which the term "space" is used can be called "personal space of the organism. " Although it has its roots in the work of zoologists and ethologists, it is an entirely different concept from that of territory. Personal distance is the distance that the organism customarily places between itself and other organisms. This distance may vary from species to species and individual to individual. Hediger speaks of this as "flight distance" and has measured this for hundreds of animals. This concept would seem to have relevance for the study of human behavior, although it has never been studied empirically so far as we know. It seems obvious that people feel uncomfortable when they talk to others who either stand too close or too far away. The concept itself has been used several times in the literature. David Katz (8) used the term "personal space" and compared it to the shell of a snail. Von Uexkull used the graphic analogy of people "surrounded by soap-bubble worlds. " Stern (13) developed the concept of personal world. He noted that the physical world was without a center, but the
High-value, collaborative networks

Abstract Networks that generate collaboration and innovative ideas on a regular basis are characterized in this paper as high-value, collaborative networks. The initiation and development of these networks outside of the confines of a formal organization is analyzed in the context of the Engineering Project Organization Society (EPOS). The society, initiated by Professor Raymond Levitt, has existed for 15 years and continues to grow while retaining a core group of founding members. We conducted and analyzed interviews with society members to develop a framework that describes how individuals can form a core with sufficient pull to enable a network to form, stabilize and grow. The framework provides a perspective on how networks sustain through its individual members, the environment in which the network exists, and the rewards individuals obtain from being part of the network. Each of these elements by itself is insufficient to develop network stability; rather, it is the combination of a stable network core and continuous reinforcement of value from the network that serves to preserve and expand network membership. The development of the framework will benefit both academic and professional contexts by highlighting the key elements required to introduce and sustain a dynamic knowledge network.
Simulation Modelling of Microgrids with Photovoltaic Renewable Energy Sources using PSCAD

Studies into microgrid stability and control schemes by industry engineers and academics require accurate simulation modelling in electromagnetic transient (EMT) environments. PSCAD, an EMT software package provides a suitable platform for conducting AC and DC power system studies but necessitates development of detailed and complex models. This paper presents the development, testing and validation of two microgrid models using PSCAD to assist current research into PV RES microgrid control schemes. The development of these models minimizes the in-depth software training required to design and implement relevant models using PSCAD. The first model provides a platform to investigate voltage control interactions at the point of common coupling (PCC) within a grid connected microgrid. The second model was developed to provide a model of islanded operation power sharing with master/slave communication control. This paper provides details of the model development and implementation for both relevant research scenarios. Using relevant simulations each model was tested for baseline function and control stability. Model steady-state stability validation was confirmed using Gauss-Seidel load-flow analytical calculations.
Ethnomedicinal plants used by tribal healers of Purulia as a remedy for arthritis: A preliminary survey

Arthritis is a chronic systemic inflammatory disease which is due to disorder of the immune system and can cause restricted mobility and death. Lack of effective treatment in remote areas results in financial burden and long-term expensive medication. Traditionally people living in remote areas depends on herbal resources for their livelihood. These suppositories are often used singly or in combination which are prescribed by village elderly or quacks and lacks the scientific basis. In the present survey which spanned for almost six months, we encountered 40 species of plant which were commonly used for treatment of arthritis. These surveys would help us to know the traditional knowledge which would lead to the development of ethno-botanic resources for inexpensive drugs for the treatment of arthritis and their scientific validation.
Atomic mixtures in radiofrequency dressed potentials

We have developed experimental techniques to confine two species of ultracold atoms in trapping potentials that are independently controlled by applied radiofrequency (rf) fields. Elementary species-selective manipulations are demonstrated for the isotopes 85Rb and 87Rb, such as changing the relative positions of the species. More detailed manipulations are possible, such as creating a double-well potential for one species that is overlapped with a single harmonic well of the other. We observed that both isotopes have long lifetimes in the rf-dressed potentials when separate; this is well known for 87Rb which has very favourable collision properties, but the stability of 85Rb in rf-dressed potentials had not previously been demonstrated. A large rate of inelastic inter-species collisions was observed when the clouds were brought together, and our results identify this as being due to two-body collisions between 85Rb and 87Rb. We explain the origin of these losses using a qualitative model. Our experimental data is compared to computations of the inelastic loss rate coefficients that have been carried out using coupled-channel calculations by theoretical chemists at Durham University. We have created double-well potentials for ultracold atoms by dressing with three rfs, as reported in our published work. Since this first demonstration we have eliminated sources of noise from the experimental apparatus using a systematic method, enabling a quantum degenerate gas of 87Rb to be loaded into a double-well potential with 6.7 micron separation between the wells. This is an order of magnitude improvement over our previously published work, and this separation is confirmed by matter-wave interference observed between atoms released from the two wells. In the near future, this apparatus will be able to split a quantum degenerate, two-dimensional gas, as has been performed for one-dimensional gases elsewhere. Moreover, many technical improvements have been implemented, allowing large amounts of data to be measured under highly reproducible conditions.
Understanding Interpersonal Influences on the Use of Formal Health Services among a Population of Iranian Women in Reproductive Age: A Qualitative Study

BACKGROUND: One of the most important factors contributing to using formal health care services by women is people who are involved in the social network around them. AIM: This study aimed to understand the interpersonal influences on the use of formal health services among Iranian women of reproductive age. METHODS: This study is a deductive content analysis approach based on the Health Promotion Model. Twenty-two semi-structured interviews were done with women of reproductive age and health care staffs in Qom, Iran. Transcripts were analysed by a deductive content analysis approach based on the Health Promotion Model (HPM). RESULTS: Three main categories and eight subcategories were drawn consisting of (1) social support with 4 subcategories including “Family support and influence”, “support of religious people”, “support of health care providers” and “negative social support”; (2) social pressure and expectations with 2 subcategories including “feeling pressure due to role-playing” and “society’s expectations regarding women’s health”, and (3) healthy role models with 2 subcategories including “family role models” and “modeling friends and peers in taking action for treatment”. CONCLUSION: A positive interpersonal influence in women acts as a strong incentive to seek health care when they are suffering from a disease, and prevents the chronicity of the disease by timely treatment.