Miracle-dz/UniFAR-FTUs huggingface dataset:
Exploring the Entrepreneurial Intentions of Science and Engineering Students in China: A Q Methodology Study

The entrepreneurial intentions of Chinese students have received rapidly evolving attention, with the “mass entrepreneurship and innovation” program as a driving force, which encourages individuals to start their own business. Entrepreneurial intention, which is perceived as being a predictor of entrepreneurial behavior, has generally been explored in the existing literature on the basis of the theory of planned behavior and the intention–behavior model. Since intention is a psychological notion, it is important to investigate the motivation for developing entrepreneurial intention from a subjective perspective. The aim of this study is to identify the objective factors that determine Chinese science and engineering students’ entrepreneurial intentions, and to understand how these different factors affect their intention to become an entrepreneur. Q methodology, which is a technological combination of qualitative and quantitative research, was conducted using thirty Chinese science and engineering students, and this paper reports their individual attitudes and discourses concerning their entrepreneurial intentions. After compiling 32 Q sets of statements and performing factor analysis, three distinct types of entrepreneurs were revealed. The findings suggest that a subjective approach to entrepreneurship education should be taken to enhance science and engineering students’ entrepreneurial intentions. Some theoretical and practical implications of these findings for techno-entrepreneurship education and development are also discussed.
Cognitive Functions in Bipolar Affective Disorder Current Episode Depression

The study focusses on cognitive functions in bipolar affective disorder (BAD) patients currently in depression.The study was conducted on 60 BAD patients current episode depression and 60Â normal controls. BAD patient fulfilling the inclusion and exclusion criteria was taken up forÂ the study. Apart from recording their socio-demographic and clinical details, all subjects wereÂ rated on the Hamilton Depression Rating Scale (Hamilton, 1960) and the Young Mania Rating Scale (Young et al., 1978) and Global assessment of functioning scale (DSM-IV, 1992). ThenÂ the appropriate psychological tool was applied for assessing the cognitive functions. SimilarÂ procedure was applied for the normal controls, except that General Health Questionnaire-12Â was applied in this group. Bipolar affective disorder patients, current episode depression hadÂ greater deficits on cognitive functioning than normal controls in all domains except in attention, concentration and recent memory. Keywords: cognitive, bipolar, depression.
Local and Installation-Wide Black- Capped Vireo Dynamics on the Fort Hood, Texas Military Reservation.

Abstract : The Black-capped Vireo is a shrubland passerine that was federally listed as an endangered species in 1987. A substantial population nesting on Fort Hood, Texas, has been monitored since the year of its listing. This report presents results from that program, including extensive territory monitoring and bird banding. Results are presented in three forms; data collected on a regional basis, regional data combined for installation-wide totals, and data collected from study sites located within three primary regions. Regional and study site data collection protocols differed by the frequency and constancy of territory monitoring. These protocols provided installation-wide overviews as well as closer survey of local populations. In 1987 and 1988, nesting success throughout the installation was exceedingly low and brood parasitism was severe. An effective cowbird mitigation program has resulted in a notable reduction in the incidence of parasitism and nesting dynamics have dramatically improved. While vast improvement is clear, the viability of the installation-wide population is yet to be determined. Recent data suggested that vireos in some areas on the installation were producing young at levels indicative of self-maintaining populations, while others were not. The percentage of first time breeders increased, which suggests improved population stability.
A robust pest identification system using morphological analysis in neural networks

Timely detection of pests play a major role in agriculture. There exist many pest identification systems, but almost all of them suffer from the misclassification due to lighting, background clutter, heterogeneous capturing devices as well as the pest being partially visible or in the different orientation. This misclassification may cause tremendous yield loss. To mitigate this situation, we proposed an architecture to provide high classification accuracy under the aforementioned conditions using morphology and skeletonization along with neural networks as classifiers. We have considered the crop rice as a use case as it is the staple food grain of almost the entire population of India. The amount of pesticides used is highest in rice as compared to all other food grains. This paper offers a robust technique to identify the pests in rice crops. The performance of the proposed architecture is tested with an image dataset, and the experimental results reveal that our proposed approach provides better classification accuracy than the existing pest detection approaches in the literature. Furthermore, the experimental results also provide the performance comparison among the popular classifiers.
Coupling between the terrestrial carbon and water cycles—a review

The terrestrial carbon and water cycles are strongly coupled. As atmospheric carbon dioxide concentration increases, climate and the coupled hydrologic cycle are modified, thus altering the terrestrial water cycle and the availability of soil moisture necessary for plants’ carbon dioxide uptake. Concomitantly, rising surface carbon dioxide concentrations also modify stomatal (small pores at the leaf surface) regulation as well as biomass, thus altering ecosystem photosynthesis and transpiration rates. Those coupled changes have profound implications for the predictions of the carbon and water cycles. This paper reviews the main mechanisms behind the coupling of the terrestrial water and carbon cycles. We especially focus on the key role of dryness (atmospheric dryness and terrestrial water availability) on carbon uptake, as well as the predicted impact of rising carbon dioxide on the water cycle. Challenges related to this coupling and the necessity to constrain it based on observations are finally discussed.
Testing of the Taylor Frozen-in-flow Hypothesis at Electron Scales in the Solar Wind Turbulence

In single-spacecraft observations the Taylor frozen-in-flow hypothesis is usually used to infer wavenumber spectra of turbulence from the frequency ones. While this hypothesis can be valid at MHD scales in the solar wind because of the small phase speeds of the fluctuations in comparison with the solar wind flow speed, its validity at electron scales is questionable. In this paper, we use Cluster data to verify the validity of the Taylor hypothesis in solar wind turbulence using the test proposed in Sahraoui et al. based on the assumption that the spectral breaks occur at ρi and ρe. Using a model based on the dispersion relation of the linear whistler mode and the estimated ratios of the spectral breaks of the magnetic energy observed in the free-streaming solar wind, we find that 32% of the events would violate the Taylor hypothesis because of their high frequency (in the plasma rest frame) compared to the Doppler shift · (∣ωplas/k·V ∣ > 0.5). Furthermore, the model shows that those events would correspond to whistler modes with propagation angles θkB ≤ 68°. The limitations of the method used and the implications of the results on future spacecraft measurements of electron-scale turbulence are discussed.
Differential gene expression in growth factors, epithelial mesenchymal transition and chemotaxis in the diffuse type compared with the intestinal type of gastric cancer

Gastric cancer (GC) is a highly heterogeneous disease and one of the major causes of cancer-related mortality worldwide. Diffuse-type gastric adenocarcinoma (or poorly cohesive- with independent cells) is characterized by aggressive behavior (rapid invasion, chemoresistance and peritoneal metastasis), as compared with intestinal-subtype adenocarcinoma. Diffuse subtype GC additionally has a substantially increasing incidence rate in Europe and the USA, and was often associated with younger age. Our objective was to analyze the expression and clinical significance of genes involved in several signaling pathways in diffuse-type GC. Tumors samples and non-malignant gastric tissues were obtained from patients with GC (diffuse-type and intestinal-subtype adenocarcinoma). The expression of 33 genes coding for proteins involved in four categories, growth factors and receptors, epithelial-mesenchymal transition, cell proliferation and migration, and angiogenesis was determined by reverse transcription-quantitative polymerase chain reaction. The expression of 22 genes was significantly upregulated in diffuse-type GC and two were downregulated (including CDH1) compared with normal tissues. Among these genes, acompared with intestinal-subtype adenocarcinoma, diffuse-type GC revealed elevated levels of IGF1 and IGF1R, FGF7 and FGFR1, ZEB2, CXCR4, CXCL12 and RHOA, and decreased levels of CDH1, MMP9 and MKI67. The expression of selected genes was compared with other genes and according to clinical parameters. Furthermore, TGF-β expression was significantly increased in linitis, a sub-population of diffusely infiltrating type associated with extensive fibrosis and tumor invasion. Our study identified new target genes (IGF1, FGF7, CXCR4, TG-β and ZEB2) whose expression is associated with aggressive phenotype of diffuse-type GC.
RNA-seq analyses of antibiotic resistance mechanisms in Serratia marcescens

The present study aimed to further clarify the genetic mechanisms responsible for the antimicrobial resistance of Serratia marcescens (S. marcescens) using RNA sequencing. Three drug-susceptible S. marcescens strains (named MYQT1, MYQT2, and MYQT3) and three multidrug-resistant S. marcescens strains (named MYQT4, MYQT5, and MYQT6) were isolated from six different patients and subjected to RNA sequencing. Differentially expressed genes (DEGs) between the multidrug-resistant S. marcescens strains and drug-susceptible strains were screened and compared, followed by functional enrichment analysis. In addition, a protein-protein interaction (PPI) network was constructed, and significant modules were extracted from it. Genes enriched in the significant modules were subjected to further enrichment analysis. MYQT3 had very a different expression pattern from MYQT1 and MYQT2, and thus, MYQT3 was excluded from the following analysis. A total of 225 DEGs were identified, of which SMDB11_RS09300 (GTP cyclohydrolase FolE2) was the most significantly upregulated with a log2 FC of 6.4; these DEGs were enriched in different GO terms, including hydrogen sulfide biosynthetic process, sulfur compound transmembrane transporter activity, and ABC transporter complex. Additionally, several genes were identified to be important genes in the PPI network, including SMDB11_RS17755 (upregulated; glutamate synthase large subunit), SMDB11_RS00590 (upregulated; sulfite reductase subunit α), and SMDB11_RS04505 (upregulated; cystathionine β-synthase). Thus, SMDB11_RS09300, SMDB11_RS17755, SMDB11_RS00590, and SMDB11_RS04505 may play significant roles in the antimicrobial resistance of S. marcescens by participating in folate metabolism or the integrity of cell membranes. However, further experiments are required to clarify these findings.
Organisational commitment level of subcontracted labourers working at public hospitals: Case of Sanliurfa

The study was conducted to examine the organisational commitment of employees/ subcontracted labourers,who were employed by using outsourcing method at 15 hospitals affiliated with the Public Hospitals Administration of Turkey in the province of Şanlıurfa and Harran University Research and Application Hospital to determine the correlation between demographic variables and organisational commitment. Organisational Commitment Scale with 18 items, developed by Allen and Meyer (1990), was used in the study. It was determined that the reliability rate of the Organisational Commitment Scale was 0.89 and this rate for its subscales was 0.90 for affective commitment, 0.77 forcontinuance commitment, and 0.75 for normative commitment. A statistically significant difference was found between the organisational commitment levels of employees participating in the study in terms of age, gender, marital status, educational background, and occupation. There was no statistically significant difference between the groups only in terms of working duration. A positive correlation was determined between demographic characteristics and organisational commitment.
An Initial Evaluation of a Concurrent Operant Analysis Framework to Identify Reinforcers for Work Completion

Although functional analysis is a powerful tool for testing the function of challenging behavior, it is not always feasible or appropriate to include as a component of functional behavior assessment (FBA). Alternative experimental analysis methods are needed to inform individualized interventions in schools, particularly for students who engage in passive forms of problem behavior. We evaluated a concurrent operant analysis (COA) framework to identify reinforcers for appropriate replacement behaviors for four students referred for FBA and reported by teachers to engage in low levels of work completion. After completing two COAs per student (researcher-as-therapist and teacher-as-therapist), we used alternating treatments designs to compare the effects of an intervention matched with COA outcomes to intervention conditions that were not matched to COA outcomes on levels of work completion and task engagement. COA outcomes corresponded across therapists for three of four participants and intervention results validated COA outcomes for two of these participants. Although results of this initial investigation seem promising, more research on COA frameworks is needed to determine their utility to guide reinforcement-based interventions in schools.
Context Aware Anomaly Behavior Analysis for Smart Home Systems

 Abstract — The Internet of Things (IoT) will lead to the development of advanced Smart Home services that are pervasive, cost-effective, and can be accessed by home occupants from anywhere and at any time. However, advanced smart home applications will introduce grand security challenges due to the increase in the attack surface. Current approaches do not handle cybersecurity from a holistic point of view; hence, a systematic cybersecurity mechanism needs to be adopted when designing smart home applications. In this paper, we present a generic intrusion detection methodology to detect and mitigate the anomaly behaviors happened in Smart Home Systems (SHS). By utilizing our Smart Home Context Data Structure, the heterogeneous information and services acquired from SHS are mapped in context attributes which can describe the context of smart home operation precisely and accurately. Runtime models for describing usage patterns of home assets are developed based on characterization functions. A threat-aware action management methodology, used to efficiently mitigate anomaly behaviors, is proposed at the end. Our preliminary experimental results show that our methodology can be used to detect and mitigate known and unknown threats, as well as to protect SHS premises and services.
Effectiveness of Social Media Approaches to Recruiting Young Adult Cigarillo Smokers: Cross-Sectional Study

Background The prevalence of social media use among youth and young adults suggests it is an appropriate platform for study recruitment from this population. Previous studies have examined the use of social media for recruitment, but few have compared platforms, and none, to our knowledge, have attempted to recruit cigarillo users. Objective The purpose of this study was to examine the effectiveness of different social media platforms and advertisement images for recruiting cigarillo users aged 14-28 years to complete a cigarillo use survey. Methods We obtained objective data for advertisement impressions for a 39-week social media recruitment campaign. Advertisements were targeted to users based on their age, geography, and interests. Effectiveness was defined as the percentage of approved surveys per advertising impression. Chi-square tests were performed to compare the effectiveness of different advertisement images and platforms. Results Valid survey completers (n=1089) were predominately older (25-28 years old, n=839, 77%). Of the 1089 survey completers, 568 (52%) identified as male, 335 (31%) as African American, and 196 (18%) as Hispanic. Advertisements delivered via Facebook/Instagram were more effective than Twitter; 311/1,027,738 (0.03%) vs 661/2,998,715 (0.02%); χ21=21.45, N=4,026,453); P<. 001. Across platforms, ads featuring exclusively an image of cigarillos were more effective (397/682,994, 0.06%) than ads with images of individuals smoking (254/1,308,675, 0.02%), individuals not smoking (239/1,393,134, .02%), and groups not smoking (82/641,650, 0.01%); χ23133. 73, N=4,026,453; P<. 001. Conclusions The campaign was effective in recruiting a diverse sample representative of relevant racial/ethnic categories. Advertisements on Facebook were more effective than Twitter. Advertisements that featured an image of a cigarillo were consistently the most effective and should be considered by others recruiting cigarillo users via social media.
Does Class Size Matter? An Exploration into Faculty Perceptions of Teaching High-Enrollment Online Courses

ABSTRACT Class size has been a popular topic for decades. There is renewed interest in this topic now with the growth of online learning. Online courses can accommodate hundreds, if not thousands, of students in a single course. Very little research, though, has been conducted recently on class size in online courses and the research that has been conducted is mixed. As the demand for online courses increases, so likely will class size. In this exploratory study, we investigated the perceptions and experiences of 37 faculty teaching high-enrollment online courses. In the following article, we report the results of our inquiry, implications for practice, and areas for additional research.
Self‐Affine Fractal Spatial and Temporal Variability of the San Pedro River, Southern Arizona

Prevailing mathematical models of alluvial channel evolution generate smooth, idealized longitudinal profiles. Alluvial channel longitudinal profiles in nature, however, have substantial multiscale spatial and temporal variability. In this paper we quantify the spatial and temporal hydrologic and geomorphic variability of a 90‐km‐long reach of the San Pedro River (San Pedro River) in southeastern Arizona and compare that variability to numerical models designed specifically to honor the spatial and temporal variability of alluvial channel systems in nature. A key motivation of this work is the power law frequency size distribution of wet and dry reaches observed in the San Pedro River. We demonstrate that such a distribution is consistent with self‐affine fractal variations of the depth to bedrock and the channel longitudinal profile. At large spatial scales, spatial variations in depth to bedrock control the accommodation space for groundwater, which, in turn, controls spatial variations in surface water discharge. At small spatial scales, the longitudinal profile controls spatial variations in surface water discharge by changing the distance between the channel bed and the water table. These results underscore the complex spatiotemporal behavior of dryland alluvial rivers and the tight coupling that is possible between hydrologic and geomorphic processes in such systems.
Factors of success: building and sustaining teaching professional development opportunities for doctoral students and postdocs

ABSTRACT This paper examines the key issues and elements to consider in developing and sustaining teaching development programs for doctoral students and postdoctoral scholars in connection to a large multi-institutional, higher education reform network. Based on interviews with 47 participants at eight member institutions and the central administration of the Center for the Integration of Research, Teaching, and Learning (CIRTL), we found five major components: campus culture, the program’s organizational placement, program leadership, program logistics, and the benefits acquired from adopting and adapting network ideas, knowledge, and resources.
Automatic Detection of Major Freeway Congestion Events using Wireless Traffic Sensor Data: Machine Learning Approach

Monitoring the dynamics of traffic in major corridors can provide invaluable insight for traffic planning purposes. An important requirement for this monitoring is the availability of methods to automatically detect major traffic events and to annotate the abundance of travel data. This paper introduces a machine learning-based approach for reliable detection and characterization of highway traffic congestion events from hundreds of hours of traffic speed data. Indeed, the proposed approach is a generic approach for detection of changes in any given time series, which is the wireless traffic sensor data in the present study. The speed data is initially time-windowed by a 10 h-long sliding window and fed into three neural networks that are used to detect the existence and duration of congestion events (slowdowns) in each window. The sliding window captures each slowdown event multiple times and results in increased confidence in congestion detection. The training and parameter tuning are performed on 17,483 h of data that include 168 slowdown events. These data are collected and labeled as part of the ongoing probe data validation studies at the Center for Advanced Transportation Technologies at the University of Maryland. The neural networks are carefully trained to reduce the chances of over-fitting to the training data. The experimental results show that this approach is able to successfully detect most of the congestion events, while significantly outperforming a heuristic rule-based approach. Moreover, the proposed approach is shown to be more accurate in estimation of the start time and end time of the congestion events.
Risk Management in Born Globals: the Case of Brazilian Craft Breweries

This work analyzes how risk management occurs in the internationalization process of Brazilian born global companies. Accordingly, we adopted the qualitative research approach, used a multiple case study strategy, and selected seven relevant craft breweries with national prominence. The findings highlight how risks are perceived in the internationalization process by managers and classified among commercial, intercultural, monetary and country risks. We also identified that these enterprises use different actions to mitigate risks, such as planning, market research, and building scenarios. The contributions discussed in this study are the identification of factors such as the international background of managers and the use of networks to minimize the perception of risk. Additionally, we discussed the ways in which risks are perceived and how the different mitigation strategies work. Finally, we proposed an integrated risk management model for the internationalization of born globals.