Miracle-dz/UniFAR-FTUs huggingface dataset:
Non-linear association of years of experience and burnout among nursing staff: a restricted cubic spline analysis

Background Occupational burnout is intricately linked to a spectrum of physical disorders encompassing respiratory, cardiovascular, and gastrointestinal conditions, as well as manifestations such as headaches, type 2 diabetes, elevated cholesterol levels, chronic fatigue, and muscle pain. Despite this association, there remains a paucity of research on the specific risk factors contributing to burnout among nurses in China. Methods This cross-sectional study utilized convenience sampling to recruit participants, with data analyzed from 1,774 nurse staffs. Psychosocial traits were assessed using the Three-Item Loneliness Scale for loneliness, the Generalized Anxiety Disorder 7-item scale (GAD-7) for anxiety symptoms, the 9-item Patient Health Questionnaire (PHQ-9) for depressive symptoms, the Connor Davidson Resilience Scale–10 item (CDRISC-10) for resilience, and the Maslach Burnout Inventory-Human Service Survey (MBI-HSS) for burn out. Restrictive cubic spline analysis to investigate the dose-response relationship between years of experience and burn out. Multivariate linear regression was employed to investigate the relationship between burnout and various risk factors. Results After controlling for basic demographic variables, good sleep quality was associated with a reduction in emotional exhaustion (β = −0.307, p < 0.001), while loneliness (β = 1.334, p < 0.001), depressive symptoms (β = 0.896, p < 0.001), and anxiety symptoms (β = 0.504, p < 0.001) were significantly associated with increased emotional exhaustion. Moreover, higher levels of resilience were positively associated with personal accomplishment (β = 0.635, p < 0.001). Regarding depersonalization, loneliness (β = 0.577, p < 0.001), depressive symptoms (β = 0.429, p < 0.001), and anxiety symptoms (β = 0.152, p < 0.01) were found to increase its level. Conversely, good resilience was associated with a decrease in depersonalization (β = −0.069, p < 0.001). The non-liner association between year of experience and emotional exhaustion was significantly (p < 0.05). Conclusion Our findings revealed that significant risk factors contributing to burnout among nursing staff including bad sleep quality, loneliness, lower level of resilience, anxiety symptoms, depressive symptoms. Moreover, a nonlinear correlation between years of experience and the likelihood of experiencing emotional exhaustion was exist.
Abnormalities in the KRAS Gene and Treatment Options for NSCLC Patients with the G12C Mutation in This Gene—A Literature Review and Single-Center Experience

Mutations in the KRAS gene are among the most common mutations observed in cancer cells, but they have only recently become an achievable goal for targeted therapies. Two KRAS inhibitors, sotorasib and adagrasib, have recently been approved for the treatment of patients with advanced non-small cell lung cancer with the KRAS G12C mutation, while studies on their efficacy are still ongoing. In this work, we comprehensively analyzed RAS gene mutations’ molecular background, mutation testing, KRAS inhibitors’ effectiveness with an emphasis on non-small cell lung cancer, the impact of KRAS mutations on immunotherapy outcomes, and drug resistance problems. We also summarized ongoing trials and analyzed emerging perspectives on targeting KRAS in cancer patients.
A Clinical Infrared Video-Oculoscopy Suppression Head Impulse (IR-cSHIMP) Test

Background: We propose a Suppression Head IMPulse (SHIMP) test method that provides for equipment only through the use of InfraRed Video-OculoScopy (IR-VOS) and allows horizontal and vertical semicircular canal function evaluation in bedside mode. We therefore named the test InfraRed clinical SHIMP (IR-cSHIMP). Methods: To check IR-cSHIMP diagnostic efficiency, we studied 22 normal subjects, 18 patients with unilateral, and 6 with bilateral deficient vestibulopathy. Each subject first underwent a vestibular examination and, only later, an IRc-SHIMP test. Results: When the IR-cSHIMP test was performed in the horizontal plane, all normal subjects showed anti-compensatory saccades. When the vertical semicircular canal function was evaluated, the same result was obtained in all normal subjects except three, which were considered false positives. In patients with vestibular deficits, the test performed in the horizontal and vertical planes were always pathological, with 100% agreement between clinical and instrumental tests. Conclusions: Our bedside method proved to be fast, simple, and effective in discriminating between healthy and pathological subjects. It required only the same skill as the better-known cHIT. For these reasons, we believe that the IR-cSHIMP should be part of daily clinical practice as a useful tool in the selection of patients to undergo more sophisticated investigations.
PARP Inhibitors in Metastatic Castration-Resistant Prostate Cancer: Unraveling the Therapeutic Landscape

The treatment landscape of metastatic prostate cancer (mPCa) is rapidly evolving with the recent approvals of poly-ADP ribose polymerase inhibitors (PARPis) as monotherapy or as part of combination therapy with androgen receptor pathway inhibitors in patients with metastatic castration-resistant prostate cancer (mCRPC). Already part of the therapeutic armamentarium in different types of advanced cancers, these molecules have shaped a new era in mPCa by targeting genomic pathways altered in these patients, leading to promising responses. These agents act by inhibiting poly-ADP ribose polymerase (PARP) enzymes involved in repairing single-strand breaks in the DNA. Based on the PROfound and TRITON3 trials, olaparib and rucaparib were respectively approved as monotherapy in pretreated patients with mCRPC and alterations in prespecified genes. The combinations of olaparib with abiraterone (PROpel) and niraparib with abiraterone (MAGNITUDE) were approved as first-line options in patients with mCRPC and alterations in BRCA1/2, whereas the combination of talazoparib with enzalutamide (TALAPRO-2) was approved in the same setting in patients with alterations in any of the HRR genes, which are found in around a quarter of patients with advanced prostate cancer. Additional trials are already underway to assess these agents in an earlier hormone-sensitive setting. Future directions will include refining the treatment sequencing in patients with mCRPC in the clinic while taking into account the financial toxicity as well as the potential side effects encountered with these therapies and elucidating their mechanism of action in patients with non-altered HRR genes. Herein, we review the biological rationale behind using PARPis in mCRPC and the key aforementioned clinical trials that paved the way for these approvals.
Late-Holocene atmospheric dust deposition in eastern Canada (St. Lawrence North Shore)

Dust deposition in two ombrotrophic peatlands (Baie and Ile du Havre peatland (IDH) bogs) of the Estuary and Gulf of the St. Lawrence in eastern Canada was reconstructed using elemental geochemistry. The rare earth elements (REEs) and other lithogenic element concentrations were measured by ICP-oES and Q-ICP-MS along two peat cores spanning the last 4000 years. Principal component analyses on the geochemical profiles show that REEs display the same behavior as Al, Ti, Sc, and Zr, all conservative elements, which suggests that REEs are immobile in the studied peat bogs and can be used as tracers of dust deposition. Plant macrofossils were also used to infer past environmental and humidity changes. The dust fluxes were reconstructed using the sum of REEs (ΣREE). The range of dust deposition varies from 0.2 to 3.8 g m−2 yr−1 in the Baie bog, while the IDH bog shows lower fluxes ranging between 0.1 and 1.2 g m−2 yr−1. The highest dust fluxes in the Baie bog were recorded from 1750–1000 cal. BP to 600–100 cal. BP and occur at the same time as periods of high variability in the macrofossil record (i.e. successive layers dominated by Sphagnum or Ericaceae). The timing of these events in the dust and macrofossil records also corresponds to documented cold periods. These two periods have been identified as episodes of climatic instability, which could have been caused by changes in the wind regime.
Diffuse irrigation systems for the production of watermelon in the Sabanas subregion, Sucre – Colombia

In the present study, the relationships between the application of a diffuse tool applied to irrigation systems in watermelon crops are explored, as well as modeling and simulation as a tool applied to the same crop. Both tools were worked through Matlab® software, control cards with sensors and meteorological stations, where the data related to the climatic conditions of the Study Region were taken and measured. It is concluded that the simulated and applied system is economically viable as an alternative for the increase of production in small, medium and large farmers of Watermelon, in the Sabanas Region of the Department of Sucre. In addition, the system is technically stable from the point of view of Control Theory with an error ratio of less than 1.5%, demonstrating good levels of liquid optimization and energy consumption.
Deformable Convolution Kernel and Residual Learning Assisted Irregular Seismic Data Interpolation

The enhancement of seismic migration and inversion processes critically depends on the precise interpolation of seismic data. In recent years, the rapid advancements in deep learning (DL) have led to the widespread adoption of convolutional neural networks (CNNs) in seismic interpolation applications. Nonetheless, the inherent limitations of traditional CNNs, due to the fixed structure of their convolution kernels, impede the extraction of high-level features of seismic data. The accuracy of CNN-based seismic data characterization and interpolation is open to improvement. Therefore, we introduce deformable convolution kernels and design a novel deformable convolution residual-U-Net (DRU-Net) for a more nuanced characterization and interpolation of seismic data. The proposed DRU-Net allows a deformable convolution kernel with adaptive shape adjustments for the receptive field by using learnable offsets to effectively extract advanced features from the training data. In conjunction with a residual learning approach, the DRU-Net significantly refines the network’s learning process and boosts interpolation precision. Through numerical experiments on synthetic and field data with irregular traces missing, the proposed DRU-Net achieves superior precision in seismic data interpolation compared with traditional U-Net and U-Net with the squeeze and excitation block (SE-block).
EFFECT OF SALICYLIC ACID APPLICATION ON COTTON (Gossypium hirsutum L.) YIELD AND FIBRE QUALITY

This study was carried out to determine the effect of SA (salicylic acid) application on the yield, yield components, and fibre quality characteristics of cotton at different growth stages (squaring, flowering and squaring + flowering). The experiment was carried out at Siirt University, Faculty of Agriculture, Department of Field Crop’s experimental area during the 2022 cotton growing season. The experimental design was a split-plot design with four replications. The main plot and sub-plots consisted of SA applications [Control (0.0 mM), squaring (1.0 mM), flowering (1.0 mM), squaring (0.5 mM) + flowering (0.5 mM)] and varieties (MAY 455, Stoneville 468, Fiona), respectively. SA application and variety interactions were significant in terms of the first boll opening days and the number of nodes. There were significant differences between varieties, except for the number of monopodial branches, number of bolls, chlorophyll content value, normalised difference vegetation index value, and micronaire and fibre strength. The MAY 455 cotton variety had the highest values in terms of seed cotton yield (2993.1 kg ha-1) plant height (62.14 cm), boll weight (6.51 g), seed cotton weight per boll (4.90 g), number of seeds per boll (29.46), number of nodes to first fruiting branch (8.65), fibre yield (1361.0 kg ha−1) and 100-seed weight (8.82 g), while the Fiona variety came to the fore in terms of number of days to first boll opening (118.0 d), number of sympodial branches (7.56), number of nodes per plant (17.79), ginning percentage (46.45%), fibre length (828.52 mm) and fibre reflectance (82.18 Rd). There was a slight increase in yield (223.8 kg ha−1) compared to the control. SA application may show different effects on each cotton variety, and the positive effect may increase by applying SA at different intervals.
Analysis of Water Quality Using Physico- Chemical Parameters Hosahalli Tank in Shimoga District, Karnataka, India

Tank in Shimoga District, Karnataka. Monthly Changes in Physical and Chemical Parameters Such as Water Temperature, Turbidity, Total Dissolved Solids, pH, Dissolved Oxygen, Free Carbon dio for a periods of one year from 1st January 2007 to 31st December 2007. All Parameters were within the permissible limits. The results indicate that the tank is Non-polluted and can be used for Domestic, Irrigation and Fisheries.
Statistical facies classification from multiple seismic attributes: comparison between Bayesian classification and expectation–maximization method and application in petrophysical inversion

We present here a comparison between two statistical methods for facies classifications: Bayesian classification and expectation–maximization method. The classification can be performed using multiple seismic attributes and can be extended from well logs to three‐dimensional volumes. In this work, we propose, for both methods, a sensitivity study to investigate the impact of the choice of seismic attributes used to condition the classification. In the second part, we integrate the facies classification in a Bayesian inversion setting for the estimation of continuous rock properties, such as porosity and lithological fractions, from the same set of seismic attributes. The advantage of the expectation–maximization method is that this algorithm does not require a training dataset, which is instead required in a traditional Bayesian classifier and still provides similar results. We show the application, comparison, and analysis of these methods in a real case study in the North Sea, where eight sedimentological facies have been defined. The facies classification is computed at the well location and compared with the sedimentological profile and then extended to the 3D reservoir model using up to 14 seismic attributes.
The spatial coherence of alpine lakes

533 3.5 53.0 15.3 32.0 1.7 27.5 228,758 109,375 Mondsee 481 14.2 51.0 36.0 68.3 1.7 247.0 394,444 207,906 Attersee 469 45.9 3944.6 84.2 170.6 7.0 463.5 545,131 269,050 Hallstattersee 508 8.6 557.0 64.9 125.2 0.5 646.5 132,512 68,690 Wolfgangsee 538 12.8 667.1 52.0 113.1 3.9 124.8 246,154 113,174 Traunsee 422 25.6 2302.0 89.7 191.2 1.0 1417.0 285,396 134,031
The Impact of Heat on Health and Productivity among Maize Farmers in a Tropical Climate Area

Background Heat stress disorders may cause negative health outcome and subsequent productivity reduction especially in those who work under direct sunlight for an extended number of hours. Objective This study assessed the impact of heat on the health and productivity among maize farmers in a hot tropical country. Methods A cross-sectional study was conducted among 396 maize farmers, randomly selected across Gombe province, Nigeria. The wet bulb globe temperature monitor (WBGT) Model QuesTemp036 was used in determining the heat index. Health was determined using a validated questionnaire, while productivity was determined by recording work output based on the number of ridges cultivated during the working hours. Results The farms recorded mean heat index with standard deviation (SD) of 31.56 (2.19) and 34.08 (1.54) in the hours of 9 am to 12 pm and 12–3 pm respectively, which exceeded the threshold level set by the ACGIH. Heavy sweating (93.2%), tiredness (48.5%), dizziness (34.1%), and headache (40.4%) were experienced by the respondents almost on daily basis. The finding further showed a significant difference in the farmers' productivity during the three time duration of the work day (p < 0.001). The productivity was significantly higher between the hours of 6–9 am (p < 0.001) and 12–3 pm (p < 0.001), compared to the hours of 9 am to 12 pm (p < 0.001). The factors that significantly predict the productivity outcome include temperature (p < 0.001), gender (p < 0.001), age (p=0.033), and BMI (p=0.008). Conclusion The farmers were frequently experiencing heat exhaustion which decreased their productivity.
Ammonia Emissions from Livestock in the United States: From Farm-Level Models to a New National Inventory

The role of nitrogen as an environmental pollutant has long been established, but the significance and amount of ammonia emitted from livestock production has not been well-characterized in the United States. In order to better characterize the impacts of ammonia as an air pollutant and its role in the formation of fine particulate matter, we have used a semi-empirical process-based model to estimate ammonia emissions from beef cattle, swine, layer chickens, and broiler chickens in the United States. The semiempirical model is used so that the ammonia emissions can be simulated using a mass balance on nitrogen through the farm, tracking nitrogen from housing, storage, and application of manure, in addition to being constrained by a number of tuned parameters which ensure that the resulting emission factors are realistic. In addition, model inputs, including manure pH, manure volume, manure nitrogen content and manure dry matter content are taken from the existing literature. These previous studies were the first means by which the FEMs were evaluated, with the FEMs able to capture 20-70% of the variability in reported emissions. Next, observations from the National Air Emissions Monitoring Study were used to further test and evaluate the model, including the evaluation in its performance to characterize seasonal as well as day-to-day variability in emissions of ammonia; here again, seasonal variability was well-characterized with slightly more mixed results for daily variability in ammonia emissions. Then, emissions from these single farms were summed over the entire populations of cattle, swine and poultry in the US, using data from the National Climate Data Center and USDA National Animal Health Monitoring Survey for appropriate meteorology and manure management practices in different locations. Emissions total 1.7 Tg from our model: 723 Gg from swine, 435 Gg from beef, 202 Gg from dairy, and 357 Gg from poultry. These inventories were compared to the National Emissions Inventory which estimates 1.9 Tg of ammonia emissions from livestock in 2011. This work has demonstrated the model’s ability to characterize the variability in ammonia emissions from livestock and can be used to understand the air quality impacts of this variability.
Effectiveness of Web Applications on Improving Nutritional Status of Patients with Colorectal Cancer

The most common cancer in Thailand is colorectal cancer (CRC). A lack of knowledge and misleading information from social media have contributed to cancer deaths from malnutrition. A web application is a tool that provides easy access to scientific nutritional information via an online platform. In this study, our goal was to compare the nutritional status of CRC patients using different nutrition-based educational tools with nutrition counseling, namely the Nutrition Educational Prototype based on Smartphone Web Applications (NEPSA) and standard hospital leaflets. Anthropometric and biochemical analyses and a dietary assessment, especially calories and protein, were measured during three visits. This study finally included 28 CRC patients who were undergoing chemotherapy and malnutrition with a body mass index (BMI) of <20 kg/m2. Thirteen participants received NEPSA while the remaining fifteen participants received a standard hospital leaflet. The results showed that NEPSAs improved nutritional outcomes by encouraging weight gain, increasing BMI, hemoglobin, hematocrit, and albumin levels, and consuming more calories and protein. NEPSA should be implemented to enhance the nutrition outcomes from anthropometric, biochemical, and dietary perspectives from nutrition advice among CRC patients. There could be positive impacts at the national level regarding equal accessibility to Thailand’s nutrition information.
Factors of Decreasing Learning Outcome in Islamic Religious Education During Covid-19 Pandemic at State Elementary School: A Study to Psychomorical Domain

The limited face to face learning policy implemented by the Indonesian government during the COVID-19 pandemic has received two forms of resistance: closed (practiced by teachers, parents, and students) and open (practiced by teachers). This resistance has made it difficult to resume face-to-face learning. As such, this article seeks to illustrate the public's resistance to the face to face policy and analyze the implications of this resistance in Madrasah Ibtidaiyah Islami. This article relies on data collected from online media as well as interviews with representatives of diverse elements of society.It shows that resistance has been rooted in several factors: familiarity with online learning, concern that health protocols would not be optimally implemented; and economic concerns. This article recommends conducting further research to obtain a deeper and more comprehensive understanding of the public's resistance to face to face.
Estimation of the Ocean Skin Temperature using the NASA GEOS Atmospheric Data Assimilation System

This report documents the status of the development of a sea surface temperature (SST) analysis for the Goddard Earth Observing System (GEOS) Version-5 atmospheric data assimilation system (ADAS). Its implementation is part of the steps being taken toward the development of an integrated earth system analysis. Currently, GEOS-ADAS SST is a bulk ocean temperature (from ocean boundary conditions), and is almost identical to the skin sea surface temperature. Here we describe changes to the atmosphere-ocean interface layer of the GEOS-atmospheric general circulation model (AGCM) to include near surface diurnal warming and cool-skin effects. We also added SST relevant Advanced Very High Resolution Radiometer (AVHRR) observations to the GEOS-ADAS observing system. We provide a detailed description of our analysis of these observations, along with the modifications to the interface between the GEOS atmospheric general circulation model, gridpoint statistical interpolation-based atmospheric analysis and the community radiative transfer model. Our experiments (with and without these changes) show improved assimilation of satellite radiance observations. We obtained a closer fit to withheld, in-situ buoys measuring near-surface SST. Evaluation of forecast skill scores corroborate improvements seen in the observation fits. Along with a discussion of our results, we also include directions for future work.