Miracle-dz/UniFAR-FTUs huggingface dataset:
A unified modeling and analysis framework for galloping piezoelectric energy harvesters

Galloping-based piezoelectric energy harvesters (GPEH) connected with various interface circuits are usually analyzed by treating their advanced structures and circuits separately, and a general model is missing to gain insights at a system level. To tackle this issue, this paper proposes a unified framework that enables an integrated view of the physics of linear GPEHs in multiple domains at the system level. In addition, it elucidates the similarities and differences among power behaviors of GPEHs connected with various interface circuits. It is based on two major elements: an equivalent circuit representing the entire system, and an equivalent impedance representing the interface circuit. Firstly, the electromechanical system is linearized and modeled in the electrical domain by an equivalent self-excited circuit with a negative resistive element representing the external aerodynamic excitation, and a general load impedance representing the interface circuit. Then, a closed-form, analytical expression of the harvested power is obtained based on the Kirchhoff’s Voltage Law, from which the optimal load, maximum power, power limit, and critical electromechanical coupling (minimum coupling to reach the power limit) are determined. In this unified analysis, the exact type of energy harvesting interface circuit is not assumed. After that, the power characteristics of a GPEH connected with five representative interface circuits are analytically derived and discussed separately, by using the particular equivalent impedance of the interface circuit of interest. It is shown that they are subjected to the same power limit. However, the critical electromechanical coupling depends on the type of circuit.
Barriers to career advancement: Asian Americans in the U.S. aerospace industry

This qualitative study explored the lack of Historically Underrepresented Population (HUP) inclusion in management and leadership roles. Specifically, why Asian Americans (AA) do not reach executive levels in southern California aerospace and defense companies (SCDCs). The AA members of HUP are among the highest educated and display model-behavior characteristics, yet, somehow do not thrive in management assignments. The U.S. defense industry has operated in a single-customer market, and that customer (the U.S. Government) is imposing social change agendas, to establish a leadership that is reflective of the company’s diversity. Exacerbating the underrepresentation of AAs is a shrinking domestic defense appropriations budget and business growth opportunities overseas. These conditions present the need for the development of a diverse management pipeline that can provide needed agility in industry leadership to enable both compliance and growth. In the course of this research, a pilot group and a main study sample of subjects were interviewed to characterize both the employee traits and their experience within the corporate environment. The study exposed environmental factors such as micro-aggressions (i.e., bullying) and other corporate impediments, as well as AA behavior traits that make this population conflict and risk averse. These qualities keep them from entering the management pipeline during their early career, where they could acquire the skills and develop the soft skills needed for later career senior management and leadership assignments. A proposed path forward to motivate aspirants onto the management track, as well as corporate behavior transformation to institutionalize AA pipelining, is recommended. The outcomes of this study provide an opportunity for transforming the leadership of the southern California defense contractors.
The Bibliometric Analysis on The Worldwide Agricultural Financing Literature: The Mapping and Direction

The financial support plays a role in the most stage of agricultural sector. There are many literatures in this field, unfortunately, none of these maps in order to give the direction for the impactful future studies. This study quantitatively analyses 224 articles on Agricultural Financing literature during ten years period. Our selected papers were gained from the indexed-Scopus database that represented by English-language articles. Using a bibliometric approach, we investigate the field’s performance and evolution of the agricultural financing literature. A significant increase in the number of publications was seen in the last period of our observation. We find the most frequent author is Turvey, CG who comes from the most relevant country. We noted that the leader of author and country are not necessarily the impactful one. However, the Agricultural Finance Review occurs as the most frequent and impactful journal. We offer future research directions on agricultural financing, rice/maize, productivity, sustainability and smallholder farmer. This study gives the information that there is a rarely occurrence of Indonesian as the country’s contributor. Therefore, there is a great opportunity for Indonesian scholars to bring a novel from Indonesia’s agricultural wisdom. We encourage Indonesian Scholars to enhance the quantity and quality publications.
Molecular dynamics inferred transfer learning models for finite‐strain hyperelasticity of monoclinic crystals: Sobolev training and validations against physical constraints

We present a machine learning framework to train and validate neural networks to predict the anisotropic elastic response of a monoclinic organic molecular crystal known as β$$ \beta $$ ‐HMX in the geometrical nonlinear regime. A filtered molecular dynamic (MD) simulations database is used to train neural networks with a Sobolev norm that uses the stress measure and a reference configuration to deduce the elastic stored free energy functional. To improve the accuracy of the elasticity tangent predictions originating from the learned stored free energy, a transfer learning technique is used to introduce additional tangential constraints from the data while necessary conditions (e.g., strong ellipticity, crystallographic symmetry) for the correctness of the model are either introduced as additional physical constraints or incorporated in the validation tests. Assessment of the neural networks is based on (1) the accuracy with which they reproduce the bottom‐line constitutive responses predicted by MD, (2) the robustness of the models measured by detailed examination of their stability and uniqueness, and (3) the admissibility of the predicted responses with respect to mechanics principles in the finite‐deformation regime. We compare the training efficiency of the neural networks under different Sobolev constraints and assess the accuracy and robustness of the models against MD benchmarks for β$$ \beta $$ ‐HMX.
Market Segmentation by Motivations in Ecotourism: Application in the Posets-Maladeta Natural Park, Spain

Environmental awareness and carrying out tourism activities in nature are increasing today. Therefore, the present study has been conducted in a natural park, and its objectives are the following: (a) identify the motivation of ecotourism; (b) determine the segmentation by motivations of ecotourism; and (c) establish the relationship between the segments and variables of satisfaction and loyalty such as return, recommendation and saying positive things about the destination. The study was carried out in the Posets-Maladeta Natural Park located in Spain, in the center of the Pyrenees mountain range. The sample consisted of 341 surveys obtained in situ. To analyze the data, exploratory factor analysis, confirmatory factor analysis and nonhierarchical segmentation of K-means were used. The results in ecotourism applied to a natural park show seven motivational dimensions: self-development, interpersonal relations, construction of personal relations, escape, reward, appreciation of nature and ego defense function. The results also reveal the existence of three segments of ecotourists: “reward and escape”, “nature” and “multiple motives”. The “reward and escape” segment shows the highest score in satisfaction and loyalty variables. The results will serve as development guides for the administrators of the natural parks and in the elaboration of ecotourism products according to the demand found.
Identification and Validation of Reliable Reference Genes for Gene Expression Studies in Koelreuteria paniculata

RT-qPCR is considered a rapid and reliable technique for analyzing gene expression. This technique is commonly used to analyze the expression of various genes at diverse transcriptional levels in different samples. However, few studies have characterized ornamental Koelreuteria species for reliable reference genes. In this study, eight reference genes were evaluated as controls in RT-qPCR with SYBR green to quantify gene expression in different Koelreuteria paniculata samples. All selected reference genes showed a broad range of Ct values in all samples, which was supportive of their variable expression. Our results showed significant variation in the stable expression of K. paniculata genes. Sample data, analyzed using geNorm, NormFinder, and BestKeeper, showed that phospholipase (PLA2) and β-actin (ACT) were the most suitable and statistically reliable reference genes, whereas ribosomal protein L13 (RPL13) and elongation factor 1-α (EF1α) were less stable and unsuitable for use as internal controls. To compare gene expression levels, two or more reference genes should be used for data normalization. Thus, the stability and expression of both PLA2 and ACT were believed to provide better normalization and quantification of the transcript levels for gene expression studies in K. paniculata.
DYNAMIC CLIMATE CONTROL IN COMBINATION WITH AVERAGE TEMPERATURE CONTROL SAVES ENERGY IN ORNAMENTALS

Abstract In the past decades, attempts have been made to produce pot plants in dynamic environments based on models for plant growth and gas exchange aiming at a reduced energy use. The energy minimising and daylight dependent control system IntelliGrow has been developed for production of pot plants and vegetables. Its basic principles are simple, as temperature and CO2 concentration are regulated according to outdoor Photosynthetic Photon Flux Density (PPFD), based on photosynthesis models. The experiments in spring 2003 included six climate strategies. Four were dynamic controls optimized to 80% or 90% of potential photosynthesis with a base temperature of 15 or 17 °C, in all cases with ventilation at 30 °C. Two reference climates were used; one of 18 °C day and 17 °C night temperature and one average temperature control set at 18 °C, both ventilated at 4 °C above the temperature set point. A dynamic climate allows the temperature to fluctuate within the wide range from minimum to ventilation set point, but to ensure a reliable development of the plants an average temperature of 18 °C was used in all treatments. The climate strategy reached the predetermined average temperature January to March and an overshoot was seen in March to May. The lowest energy use was found in the 15 °C 80% photosynthesis climate. The production time of the plants (time to flowering) did not differ between the treatments. The plants responded positively in terms of dry weight accumulation to dynamic climates even though the differences were small and in many cases not significant. The results indicate, that using a combination of a dynamic climate control based on photosynthesis with an average temperature control can yield a significant energy saving, but also plants with improved external quality.
Where's the harm? Screening student evaluations of teaching for offensive, threatening or distressing comments

Student evaluation surveys provide educational institutions with important feedback regarding the student experience of teaching and courses; however, qualitative comments can contain offensive, insulting or threatening content. Large educational institutions generate thousands of comments per academic term; therefore, manual screening processes to find potentially harmful comments are not generally feasible. We developed a methodology for semi-automated screening of student comments that incorporates a machine learning decision support system and a detailed psychological assessment protocol. In a case study at a large public Australian university, our system identified 4,258 out of 62,049 (6.9%) comments as potentially harmful and requiring further review. Feedback from stakeholders demonstrates that this methodology is useful in reducing staff workload and could be broadly applied to different settings. Implications for practice or policy: Educational institutions can adopt this methodology to dramatically decrease the number of working hours required to screen harmful free-text comments. Researchers can use the proposed psychology-based assessment as an example of how to develop a protocol to categorise comments. Educators and researchers can use this case study to follow best practices to develop their own decision support system that implements free-text comment classifiers.
Finite element analysis of surface tension on piston due to pressure variation

Piston is an important component of the motor vehicle that can pump or result in a pressure thus enabling to generate the components to reciprocate the engine. Commonly, it is made of mixed aluminum in which in the work process of engine, it receives the high level of pressure and heat that later emerges the pressure on the surface. To observe the distribution of the surface pressure on the piston due to the high pressure and temperature, it cannot be manually done but by means of the approach of the finite element method through the Ansys sofware. The variation of the simulated surface pressures consisted of 5, 10, 15 and 20 MPa with various pedestals given. Based upon the simulation result, it was found that the variety of the pressures received by the piston surface has caused the level of pressure experienced by piston also changed. It was similar with the result of the use of different positions of pedestals in which it could lead to a change in the pressure concentration of piston.
Towards Custom-Designed Professional Training Contents and Curriculums through Educational Process Mining

Educational Process Mining constitutes a new opportunity to better understand students’ learning habits and finely analyze the complete set of educational proc esses. In this paper, we investigate further the potential and cha llenges of Process Mining in the field of professional training. Firstly, we focus on the mining and the analysis of social netw orks between course units or training providers. Secondl y, we propose a two-step clustering approach for partitioning educational processes following key performance ind icators. KeywordsProcess Mining; Educational Data Mining; Curriculum Mining; Key Performance Indicators; ProM.
Development and Evaluation of Molecular Pen-Side Assays without Prior RNA Extraction for Peste des Petits Ruminants (PPR) and Foot and Mouth Disease (FMD)

Animal diseases such as peste des petits ruminants (PPR) and foot and mouth disease (FMD) cause significant economic losses in endemic countries and fast, accurate in-field diagnostics would assist with surveillance and outbreak control. The detection of these pathogens is usually performed at reference laboratories, tested using assays that are recommended by The World Organisation for Animal Health (OIE), leading to delays in pathogen detection. This study seeks to demonstrate a proof-of-concept approach for a molecular diagnostic assay that is compatible with material direct from nasal swab sampling, without the need for a prior nucleic acid extraction step, that could potentially be applied at pen-side for both PPR and FMD. The use of such a rapid, low-cost assay without the need for a cold chain could permit testing capacity to be established in remote, resource limited areas and support the surveillance activities necessary to meet the goal of eradication of PPR by 2030. Two individual assays were developed that detect > 99% of PPR and FMD sequences available in GenBank, demonstrating pan-serotype FMD and pan-lineage PPR assays. The ability for the BioGene XF reagent that was used in this study to lyse FMD and PPR viruses and amplify their nucleic acids in the presence of unprocessed nasal swab eluate was evaluated. The reagent was shown to be capable of detecting the viral RNA present in nasal swabs collected from naïve and infected target animals. A study was performed comparing the relative specificity and sensitivity of the new assays to the reference assays. The study used nasal swabs collected from animals before and after infection (12 cattle infected with FMDV and 5 goats infected with PPRV) and both PPR and FMD viral RNA were successfully detected two to four days post-infection in all animals using either the XF or reference assay reagents. These data suggest that the assays are at least as sensitive as the reference assays and support the need for further studies in a field setting.
Fiber Preparation from Micronized Oat By-Products: Antioxidant Properties and Interactions between Bioactive Compounds

This study aimed to investigate the possibility of utilizing oat by-products for fiber preparation. Oat husk (OH) and oat bran (OB) were micronized and used to prepare a novel product rich in fiber and with enhanced antioxidant properties. The basic chemical composition and phenolic acid profile were determined in OH and OB. The antioxidant properties of OH and OB were also analyzed. The type and strength of interactions between the biologically active compounds from their mixtures were characterized by an isobolographic analysis. The analyses showed that the sum of phenolic acids was higher in OH than in OB. Ferulic acid was dominant in both OH and OB; however, its content in OH was over sixfold higher than that in OB. The results also suggested that both OH and OB can be used for preparing fiber with enhanced antioxidant properties. The optimal composition of the preparation, with 60–70% of OH and 30–40% of OB, allows for obtaining a product with 60–70% fiber and enhanced antioxidant activity due to bioactive substances and their synergistic effect. The resulting product can be a valuable additive to various food and dietary supplements.
Photodegradation of Organic Pollutants in Seawater and Hydrogen Production via Methanol Photoreforming with Hydrated Niobium Pentoxide Catalysts

In this work, the photocatalytic activity of Hydrated Niobium Pentoxide (synthesized by a simple and inexpensive method) was explored in two unknown reactions reported for this catalyst: the photodegradation of phenol in seawater and the photoreforming of methanol. The Hydrated Niobium Pentoxide (Nb1) was synthesized from the reaction of niobium ammoniacal oxalate NH4[NbO(C2O4)2·H2O]•XH2O with a strong base (NaOH). Further treatment of this catalyst with H2O2 led to a light-sensitive Hydrated Niobium Pentoxide (Nb2). The photocatalysts were characterized by XRD, DRS, SEM Microscopy, FTIR-ATR, EDX, and specific surface area (SBET). The characterization results demonstrate that the treatment of Hydrated Niobium Pentoxide sensitized the material, increased the surface area of the material, diminished the average particle size, and modified its surface charge, and formed peroxo groups on the catalytic surface. Although both photocatalysts (Nb1 and Nb2) were active for both proposed reactions, the sensitization of the photocatalyst was beneficial in distinct situations. In the photocatalytic degradation of phenol in seawater, the sensitization of the photocatalyst did not enhance the photocatalytic activity. In both photoreactions studied, the addition of the Pt° promoter readily increased the photocatalytic performance of both photocatalysts; in this case, the sensitized photocatalyst recorded the best results. The presence of OH• radicals was confirmed, and the great contribution of the Pt° promoter was in the increase in OH• radical generation; this increase was more effective in the sensitized photocatalyst. Our work demonstrated a simple and inexpensive way to synthesize niobium photocatalysts that can effectively be used in the photodegradation of phenol in seawater and in the photoreforming of methanol to produce hydrogen.
The Impact of Scaling on the Design of High-Speed Delta-Sigma A/D Converters

The evolution of the semiconductor industry during the last 50 years has been propelled by the tremendous progress achieved by the Complementary Metal-Oxide-Semiconductor (CMOS) manufacturing process. Digital integrated circuits (ICs) have widely proﬁted from CMOS scaling in terms of area, power, and speed, becoming the driver for the adoption of more and more advanced technology nodes. On the other hand, analog/mixed-signal ICs, challenged rather than favored by scaling, have struggled to keep the same progress pace. Therefore, the question arises whether it makes sense or not to scale analog-dominated integrated circuits into deca-nanometer CMOS processes. This dissertation investigates technology opportunities and design challenges oﬀered by advanced sub-100 nm CMOS processes, with a particular emphasis on the impact of scaling on the design of high-speed delta-sigma analog-to-digital converters (ADCs). The main shortcomings resulting from scaling are discussed, and circuit techniques aiming at combating such drawbacks are presented. In order to vindicate the theoretical ﬁndings and draw conclusions on the eﬀect of scaling, the very same third-order discrete-time (DT) delta-sigma modulator topology has been implemented ﬁrst in a mature 130 nm bulk CMOS process, and later in an advanced 28 nm FD-SOI CMOS technology. The former implementation achieves 63 dB dynamic range (DR) in a 25 MHz bandwidth (BW). The latter design features 64 dB DR in a 50 MHz BW while occupying half the area and consuming down to half the power when operated at the same speed. The two ADC prototypes were conceived as the basis for the development of new product lines for 4G wireless communications supporting up to full intraband carrier aggregation.
The Relative Effects of Trust and Distrust on Information Acceptance from Mobile Word-of-Mouth and the Moderating Role of Event Significance and the Aggregate Preference

Abstract This study examines how users accept the information from mobile Word-of-mouth (MWOM) information communication. In so doing, we investigate the role of both trust and distrust affecting the degree to which users would accept the recommendation made by MWOM and refer the information to other users. Furthermore, we identify specific evaluative judgments critical in enhancing trust and engendering distrust. We then examine the moderating role of event significance and the aggregate preference by other users reflected by the number of likes. The results indicate that trust has a greater influence than distrust in determining the information acceptance and referral of the recommendation made by MWOM. We also find that source expertise, message relevance, and altruism are more significant in inducing trust, while self-interest seeking is more critical in engendering distrust. The results show that our model is robust against different levels of event significance and the number of likes, although the relative significance of a few paths differs by these two moderating variables.
Supervisor support and customer orientation: The importance of learning goal orientation in the hotel industry

Abstract Drawing on goal orientation and substitutes for leadership theories, learning goal orientation is hypothesized as a moderator in the relationship between supervisor support and employee customer orientation. Participants were 328 employees of 4- and 5-star hotels in Singapore. Results show that employees with high learning goal orientation do not require a high degree of supervisor support to show a high degree of customer orientation. In contrast, supervisor support is especially important for employees with low learning goal orientation. Practical implications relate to the selection of new employees, individualized attention to current employees, organizational culture, and training.