Miracle-dz/UniFAR-FTUs huggingface dataset:
Navigating job satisfaction in family firms during crisis

Occupational health is one of the aspects significantly affected during crisis periods. It is essential to learn about the factors that improve organizational capacity in coping with such shocks. This study investigates how the working environment of a family business influences job satisfaction during crises. Conducting a survey with 516 employees at the peak of the pandemic, the research utilizes structural equation analysis, revealing that family business environments can mitigate burnout, enhance affective commitment, and consequently, boost job satisfaction. The study highlights the need to manage burnout and utilize resources, such as employee commitment, for family firms to sustain job satisfaction amidst disruptions. It deepens the comprehension of family businesses’ crisis response, emphasizing the significance of human resource commitment and management. The investigation illuminates the dynamic interplay between the work environment, employee well-being, and organizational resilience, providing valuable insights for both theoretical understanding and practical application.
Human Exposure to Field Radiated by Vertical Dipole Antenna over a Lossy Half-Space using Analytical Approach

—The paper deals with an efficient procedure to study human exposure to vertical dipole antenna above a flat lossy half space. The closed form expressions for the corresponding irradiated electrical field are obtained assuming the sinusoidal and triangular current distribution along the antenna, respectively. The corresponding integral field expressions are evaluated by means of numerical integration and analytical procedures. The computations have been undertaken in the far field zone for various antenna parameters and compared to rigorous numerical model. Provided the field radiated from the vertical dipole is determined, whole body average Specific Absorption Rate (SAR WB ) is computed in a simple parallelepiped model of the human body and cylindrical model of the human body, respectively.
Specific Antimicrobial Activities Revealed by Comparative Evaluation of Selected Gemmotherapy Extracts

Nowadays, unprecedented health challenges are urging novel solutions to address antimicrobial resistance as multidrug-resistant strains of bacteria, yeasts and moulds are emerging. Such microorganisms can cause food and feed spoilage, food poisoning and even more severe diseases, resulting in human death. In order to overcome this phenomenon, it is essential to identify novel antimicrobials that are naturally occurring, biologically effective and increasingly safe for human use. The development of gemmotherapy extracts (GTEs) using plant parts such as buds and young shoots has emerged as a novel approach to treat/prevent human conditions due to their associated antidiabetic, anti-inflammatory and/or antimicrobial properties that all require careful evaluations. Seven GTEs obtained from plant species like the olive (Olea europaea L.), almond (Prunus amygdalus L.), black mulberry (Morus nigra L.), walnut (Juglans regia L.), blackberry (Rubus fruticosus L.), blackcurrant (Ribes nigrum L.) and bilberry (Vaccinium myrtillus L.) were tested for their antimicrobial efficiency via agar diffusion and microbroth dilution methods. The antimicrobial activity was assessed for eight bacterial (Bacillus cereus, Staphylococcus aureus, Salmonella enterica subsp. enterica, Proteus vulgaris, Enterococcus faecalis, Escherichia coli, Pseudomonas aeruginosa and Listeria monocytogenes), five moulds (Aspergillus flavus, Aspergillus niger, Aspergillus ochraceus, Penicillium citrinum, Penicillium expansum) and one yeast strain (Saccharomyces cerevisiae). The agar diffusion method revealed the blackberry GTE as the most effective since it inhibited the growth of three bacterial, four moulds and one yeast species, having considered the total number of affected microorganism species. Next to the blackberry, the olive GTE appeared to be the second most efficient, suppressing five bacterial strains but no moulds or yeasts. The minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) were then determined for each GTE and the microorganisms tested. Noticeably, the olive GTE appeared to feature the strongest bacteriostatic and bactericidal outcome, displaying specificity for S. aureus, E. faecalis and L. monocytogenes. The other GTEs, such as blueberry, walnut, black mulberry and almond (the list indicates relative strength), were more effective at suppressing microbial growth than inducing microbial death. However, some species specificities were also evident, while the blackcurrant GTE had no significant antimicrobial activity. Having seen the antimicrobial properties of the analysed GTEs, especially the olive and black mulberry GTEs, these could be envisioned as potential antimicrobials that might enhance antibiotic therapies efficiency, while the blackberry GTE would act as an antifungal agent. Some of the GTE mixtures analysed have shown interesting antimicrobial synergies, and all the antimicrobial effects observed argue for extending these studies to include pathological microorganisms.
Relationships between triglyceride-glucose index and incident gestational diabetes mellitus: a prospective cohort study of a Korean population using publicly available data

Background The connection between the triglyceride-glucose index (TyG index) and gestational diabetes mellitus (GDM) is currently debated. Our study aimed to investigate the connection between the TyG index and GDM within the Korean population. Methods Using publically accessible data in Korea, we performed a secondary study on a sample of 589 pregnant women who were carrying a single fetus. The analysis employed a binary logistic regression model, some sensitivity analyses, and subgroup analysis to investigate the association between the TyG index and the occurrence of GDM. To assess the TyG index’s potential to predict GDM, a receiver operating characteristic (ROC) study was also carried out. Results The mean age of the pregnant women was 32.065 ± 3.798 years old, while the mean TyG index was 8.352 ± 0.400. The prevalence rate of GDM was found to be 6.112%. Upon adjusting for potential confounding variables, a positive association was detected between the TyG index and incident GDM (OR = 12.923, 95%CI: 3.581–46.632, p = 0.00009). The validity of this connection was further confirmed by subgroup analysis and sensitivity analyses. With an area under the ROC curve of 0.807 (95%CI: 0.734–0.879), the TyG index showed strong predictive power for GDM. The TyG index’s ideal cutoff value for detecting GDM was found to be 8.632, with a sensitivity of 78.7% and a specificity of 72.2%. Conclusion The findings of our study provide evidence that an increased TyG index is significantly associated with the occurrence of GDM. Utilizing the TyG index during the 10–14 week gestational period may be a valuable tool in identifying pregnant individuals at a heightened risk for developing GDM. Early detection enables timely and efficacious interventions, thereby enhancing the prognosis of affected individuals.
Adaptive Fringe Pattern Projection Techniques for Imgae Saturation Avoidance in 3D Surface Measurement

Fringe-pattern projection (FPP) techniques are commonly used for surface-shape measurement in a wide range of applications including object and scene modeling, part inspection, and reverse engineering. Periodic intensity fringe patterns with a specific amplitude are projected by the projector onto an object and a camera captures images of the fringe patterns, which appear distorted by the object surface from the perspective of the camera. The images are then used to compute the height or depth of the object at each pixel. One of the problems with FPP is that camera sensor saturation may occur if there is a large change in ambient lighting or a large range in surface reflectivity when measuring object surfaces. Camera sensor saturation occurs when the reflected intensity exceeds the maximum quantization level of the camera. A low SNR occurs when there is a low intensity modulation of the fringe pattern compared to the amount of noise in the image. Camera sensor saturation and low SNR can result in significant measurement error. Careful selection of the camera aperture or exposure time can reduce the error due to camera sensor saturation or low SNR. However, this is difficult to perform automatically, which may be necessary when measuring objects in uncontrolled environments where the lighting may change and objects have different surface reflectivity. This research presents three methods to avoid camera sensor saturation when measuring surfaces subject to changes in ambient lighting and objects with a large range in reflectivity. All these methods use the same novel approach of lowering the maximum input gray level (MIGL) to the projector for saturation avoidance. This approach avoids saturation by lowering the reflected intensity so that formerly saturated intensities can be captured by the camera. The first method of saturation avoidance seeks a trade-off between robustness to intensity saturation and low SNR. Measurements of a flat white plate at different MIGL resulted in a trade-off MIGL that yielded the highest accuracy for a single adjustment of MIGL that is uniform within and across the projected images. The second method used several sets of images, taken at constant steps of MIGL, and combined the images pixel-by-pixel into a single set of composite images, by selecting the highest unsaturated intensities at each pixel. White plate measurements using this method had comparable accuracy to the first method but required more images to form the composite image. Measurement of a checkerboard showed a higher accuracy than the first method since the second method maintains a higher SNR when the object has a large range of reflectivity. The last method also used composite images where the step size was determined dynamically, based on the estimated percentage of pixels that would become unsat-
Climate change impacts on surface water resources in the Rheraya catchment (High Atlas, Morocco)

ABSTRACT This study aimed to quantify possible climate change impacts on runoff for the Rheraya catchment (225 km2) located in the High Atlas Mountains of Morocco, south of Marrakech city. Two monthly water balance models, including a snow module, were considered to reproduce the monthly surface runoff for the period 1989‒2009. Additionally, an ensemble of five regional climate models from the Med-CORDEX initiative was considered to evaluate future changes in precipitation and temperature, according to the two emissions scenarios RCP4.5 and RCP8.5. The future projections for the period 2049‒2065 under the two scenarios indicate higher temperatures (+1.4°C to +2.6°C) and a decrease in total precipitation (−22% to −31%). The hydrological projections under these climate scenarios indicate a significant decrease in surface runoff (−19% to −63%, depending on the scenario and hydrological model) mainly caused by a significant decline in snow amounts, related to reduced precipitation and increased temperature. Changes in potential evapotranspiration were not considered here, since its estimation over long periods remains a challenge in such data-sparse mountainous catchments. Further work is required to compare the results obtained with different downscaling methods and different hydrological model structures, to better reproduce the hydro-climatic behaviour of the catchment. EDITOR M.C. Acreman ASSOCIATE EDITOR R. Hirsch
Impact of idealized future stratospheric aerosol injection on the large‐scale ocean and land carbon cycles

Using an Earth system model, we simulate stratospheric aerosol injection (SAI) on top of the Representative Concentration Pathways 8.5 future scenario. Our idealized method prescribes aerosol concentration, linearly increasing from 2020 to 2100, and thereafter remaining constant until 2200. In the aggressive scenario, the model projects a cooling trend toward 2100 despite warming that persists in the high latitudes. Following SAI termination in 2100, a rapid global warming of 0.35 K yr−1 is simulated in the subsequent 10 years, and the global mean temperature returns to levels close to the reference state, though roughly 0.5 K cooler. In contrast to earlier findings, we show a weak response in the terrestrial carbon sink during SAI implementation in the 21st century, which we attribute to nitrogen limitation. The SAI increases the land carbon uptake in the temperate forest‐, grassland‐, and shrub‐dominated regions. The resultant lower temperatures lead to a reduction in the heterotrophic respiration rate and increase soil carbon retention. Changes in precipitation patterns are key drivers for variability in vegetation carbon. Upon SAI termination, the level of vegetation carbon storage returns to the reference case, whereas the soil carbon remains high. The ocean absorbs nearly 10% more carbon in the geoengineered simulation than in the reference simulation, leading to a ∼15 ppm lower atmospheric CO2 concentration in 2100. The largest enhancement in uptake occurs in the North Atlantic. In both hemispheres' polar regions, SAI delays the sea ice melting and, consequently, export production remains low. In the deep water of North Atlantic, SAI‐induced circulation changes accelerate the ocean acidification rate and broaden the affected area.
Integrated seismic reflection and borehole geophysical studies at Les Mines Selbaie, Quebec

Integrating seismic reflection, borehole geophysical and physical rock property studies is an effective means of mapping lithological contacts and structures in the crystalline crust. At Les Mines Selbaie in the northern volcanic zone of the late Archean Abitibi Subprovince, a high-frequency seismic reflection profile has provided the first images of deep crustal structures of this important polymetallic mine site. Physical rock property and borehole geophysical studies confirm that prominent seismic reflections can be caused by lithological contacts, faults and sulphide mineralization. At Les Mines Selbaie, the first two of these are shown by this study. Clearly identifiable reflection images from sulphide mineralization have not been demonstrated in analysis of the profile. The seismic images provide useful information about gross structure in the vicinity of Les Mines Selbaie. They can also place important constraints on the sequence of tectonic events and, therefore, can aid future deep exploration programs.
Oznaczenia wieku granitu Karkonoszy metodą izochronową, rubinowo-strontową. na podstawie całych próbek skalnych

NEXT DATING OF GRANITE SAMPLE FROM THE KARKONOSZE MOUNTAINS USING RB-SR TOTAL ROCK ISOCHRONE METHOD Summary Different kind of Karkonosze granite were dated by four Rb/ Sr total rock isochrones. Furthermore, three other samples have been dated using the conventional method. The granite with biotite schlieren (Huta quarry, near Szklarska Poreba) gives the isochrone, which points out to the age of 328 M.y. and Sri = 0,7064 ± 22. The porphyritic granite from Michalowice quarry gives an isochrones age of 329 ± 17 M.y. with Sri = 0,7056 ± 11. The common isochrone, which contain the isotopic data from the lakuszyce borehole (porphyritic granite) and from the Michalowice quarry gives the age of 324 ± 11 M.y. with Sri = 0,7059 ± 7. The equigranular range granite, from the Maly Staw, yielded (five points isochrone) on 309 ± 3 M.y. with Sri = 0,7073. The leucogranite from the Huta quarry exhibits the age of 310 M.y. using conventional method. Two other samples, from Michalowice quarry, have been dated using the conventional method. These two samples are probably ancient enclaves, more or less assimilated by granitic magma. These samples exhibit the oldest age in the granitic Karkonosze Mts as yet, that is 350 M.y. The evolution of the Karkonosze pluton appears to have been rather a long process, which lasted at least over 20 M.y. It is suggested, that in Karkonosze Mts there exists some younger granite, which has not been dated till now.
Probing visual short-term memory : is color- or location-based probing a more efficient way to retrieve visual information from visual short-term memory?

Visual short-term memory is believed to have a capacity for up to four to five objects, regardless of their combination, but the complexity of the combination results in lower precision (Alvarez & Cavanagh, 2004; Luck & Vogel, 1997). Others argue that the capacity of visual short-term memory was less than four objects, and that the capacity was higher for simple feature objects than for complex feature objects (Xu & Chun, 2006). Many studies have been done concerning visual short-term memory (see, e.g., Luck & Vogel 1997; Alvarez & Cavanagh, 2004; Baddeley & Hitch, 1974) with great success, but despite their attribution there are still some questions unanswered. The main goal of this study was to test whether a coloror location-based probing was a more efficient way to retrieve information from visual short-term memory. This was tested through five experiments. In the experiments, two cueing conditions were used: color and spatial cueing, except in Experiment 2 and 3 where a symbolic cue was added. In Experiment 1, 3, and 5, participants reported the orientation of the target bar. In Experiment 2 and 4, participants reported target letters integers.
Predator avoidance in night-feeding Dunlins Calidris alpina: a matter of concealment

The anti-predator behaviour of night-feeding Dunlins Calidris alpina was studied on a tidal flat in the Danish Wadden Sea. The observations indicated that Dunlins at night depress vocalization compared with day-feeding birds. Moreover, when Dunlins were approached by a raptor during day-time almost all took flight. In contrast, when Dunlins were disturbed at night only about 60% took flight, while most of the remaining birds froze. It is suggested that depressed vocalization and freezing at night are means to escape detection by owls. How the behavioural dichotomy (freezing and escape) during nocturnal disturbance is accomplished and how it affects the spacing behaviour of night-feeding Dunlins are discussed.
What's Next? From Analysis to Action

This paper describes how data-driven examination of barriers to successful completion of undergraduate engineering degrees amongst female-identifying and under-represented minority (URM) students at Seattle University has shaped the development of new policies and programs within the College of Science and Engineering to better support students from underrepresented or marginalized groups. This study is a continuation of a project in which we first analyzed graduation data to extract characteristics that differentiate students who do or do not successfully complete degrees within engineering. We followed the data analysis with a survey to better understand the experiences of students from underrepresented or marginalized groups. In Section 1 of this paper, we introduce Seattle University and our previous work. Following, in Section 2, we review relevant literature. In Section 3, we first present the results of focus groups conducted with students from a variety of backgrounds and experiences such as transfer students, female-identifying students, URM women, URM men, international students, and students who have either switched out of an engineering program or have a GPA that put them at risk to not complete an engineering degree. The focus groups confirmed the results of the survey: students from marginalized groups experience bias and microaggressions from other students and faculty. Combining past analysis and the new focus group results, we identified two primary trends that our programs will be targeting. First, that students from underrepresented and marginalized groups are more likely to seek out opportunities for community within their engineering and computer science programs. Second, that students from these populations reported an overall culture within the engineering and computer science programs that can feel unwelcoming and, at times, hostile.
MSFA-YOLO: A Multi-Scale SAR Ship Detection Algorithm Based on Fused Attention

Leveraging the excellent feature representation capabilities of neural networks, deep learning methods have been widely adopted for object detection in synthetic aperture radar (SAR) images. However, persistent challenges are encountered in SAR ship detection due to factors such as small ship sizes, high noise levels, multiple targets, and scale variations. To address these complexities, in this paper, the MSFA-YOLO algorithm, a novel multiscale SAR ship detection approach em-powered by a fused attention mechanism, is presented. The proposed algorithm incorporates several key enhancements. The fused attention c2fSE module is integrated into the YOLOv8n baseline network to optimize feature extraction for SAR ships. In addition, the DenseASPP module is incorporated to enhance the model’s adaptability to ships of varying scales, improving its ca-pability to accommodate larger ships within lower model scales. Furthermore, the Wise-IoU loss function is adopted, and a dynamic non-monotonic focusing mechanism is employed for bounding box loss, significantly enhancing the model’s ability to handle low-quality images. Extensive experiments conducted on benchmark datasets, namely SAR-Ship-Dataset, SSDD, and HRSID, validate the robustness and reliability of the proposed model. Experimental results demonstrate significant performance improvements over YOLOv8n: a 3.1% enhancement in mAP75 and a 2.1% boost in mAP50–95 on the SAR-Ship-Dataset, a 0.7% increase in mAP75 and a 0.5% increase in mAP50–95 on the SSDD dataset, and a 1.8% increase in mAP75 and a 0.7% increase in mAP50–95 on the HRSID dataset. Exhibiting superior performance to existing SAR ship detection models in terms of accuracy, the MSFA-YOLO algorithm represents a significant advancement, establishing itself as the current state-of-the-art algorithm in SAR ship detection.
Construction of a co-expression network affecting intramuscular fat content and meat color redness based on transcriptome analysis

Introduction: Intramuscular fat content (IFC) and meat color are vital indicators of pork quality. Methods: A significant positive correlation between IFC and redness of meat color (CIE a* value) indicates that these two traits are likely to be regulated by shared molecular pathways.To identify candidate genes, hub genes, and signaling pathways that regulate these two traits, we measured the IFC and CIE a* value in 147 hybrid pigs, and selected individuls with extreme phenotypes for transcriptome analysis. Results: The results revealed 485 and 394 overlapping differentially expressed genes (DEGs), using the DESeq2, limma, and edgeR packages, affecting the IFC and CIE a* value, respectively. Weighted gene co-expression network analysis (WGCNA) identified four modules significantly correlated with the IFC and CIE a* value. Moreover, we integrated functional enrichment analysis results based on DEGs, GSEA, and WGCNA conditions to identify candidate genes, and identified 47 and 53 candidate genes affecting the IFC and CIE a* value, respectively. The protein protein interaction (PPI) network analysis of candidate genes showed that 5 and 13 hub genes affect the IFC and CIE a* value, respectively. These genes mainly participate in various pathways related to lipid metabolism and redox reactions. Notably, four crucial hub genes (MYC, SOX9, CEBPB, and PPAGRC1A) were shared for these two traits. Discussion and conclusion: After functional annotation of these four hub genes, we hypothesized that the SOX9/CEBPB/PPARGC1A axis could co-regulate lipid metabolism and the myoglobin redox response. Further research on these hub genes, especially the SOX9/CEBPB/PPARGC1A axis, will help to understand the molecular mechanism of the co-regulation of the IFC and CIE a* value, which will provide a theoretical basis for improving pork quality.