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Speech Emotion Recognition (SER) is a rapidly evolving field of research aimed at identifying and categorizing emotional states through the analysis of speech signals. As SER holds significant socio-cultural and commercial importance, researchers are increasingly leveraging machine learning and deep learning techniques to drive advancements in this domain. A high-quality dataset is an essential resource for SER studies in any language. Despite Urdu being the 10th most spoken language globally, there is a significant lack of robust SER datasets, creating a research gap. Existing Urdu SER datasets are often limited by their small size, narrow emotional range, and repetitive content, reducing their applicability in real-world scenarios. To address this gap, the Urdu Speech Emotion Corpus (UrSEC) was developed. This comprehensive dataset includes 3500 Urdu speech signals sourced from 10 professional actors, with an equal representation of male and female speakers from diverse age groups. The dataset encompasses seven emotional states: Angry, Fear, Boredom, Disgust, Happy, Neutral, and Sad. The speech samples were curated from a wide collection of Pakistani Urdu drama serials and telefilms available on YouTube, ensuring diversity and natural delivery. Unlike conventional datasets, which rely on predefined dialogs recorded in controlled environments, UrSEC features unique and contextually varied utterances, making it more realistic and applicable for practical applications. To ensure balance and consistency, the dataset contains 500 samples per emotional class, with 50 samples contributed by each actor for each emotion. Additionally, an accompanying Excel file provides detailed metadata for each recording, including the file name, duration, format, sample rate, actor details, emotional state, and corresponding Urdu dialog. This metadata enables researchers to efficiently organize and utilize the dataset for their specific needs. The UrSEC dataset underwent rigorous validation, integrating expert evaluation and model-based validation to ensure its reliability, accuracy, and overall suitability for advancing research and development in Urdu Speech Emotion Recognition.

Objective: ECR adaptation for use with significant others. Three databases: 1) 183 young people of Spanish nationality with an average age of 21 years (SD = 3.33); 2) 202 participants were used, with an average age of 25 years (SD = 2.25); 3) Joint database.

We carried out a field experiment on BC addition in abandoned grasslands on the Loess Plateau to elucidate the effects of BC application on soil active N fractions (e.g., DON, MBN, NH4+-N, and NO3--N) and soil properties (e.g., physicochemical properties, microbial biomass, and related enzyme activities, etc.) in the abandoned grasslands on the Loess Plateau. We hypothesized that (1) BC addition could significantly facilitate the accumulation of soil active N fractions, but excessive addition of BC might reduce this facilitation, and (2) BC addition led to significant variations in the soil factors that influence the characteristics of accumulation and transformation of soil AON and DIN fractions. Soil water content (SWC) and temperature (ST) were determined in situ by the drying differential method and thermometer (JM624, Jinming Instrument Co., Tianjin, China), respectively (Xie et al., 2024). SOC and dissolved organic carbon (DOC) were determined through the K2Cr2O7 oxidation method, while TN and TP were determined by the Kjeldahl method and molybdenum antimony colorimetric method, respectively (Liu et al., 2022; Cao et al., 2023). In addition, NH4+-N, NO3--N, and dissolved total nitrogen (DTN) were determined by KCl solution leaching-Kjeldahl nitrogen determination and UV spectrophotometry, respectively (Zhang et al., 2022b; Chen et al., 2024a). DON was the difference between the DTN and the contents of NH4+-N and NO3--N. Microbial biomass carbon (MBC) and MBN were determined by chloroform fumigation-K2SO4 extraction, and microbial biomass phosphorus (MBP) was determined by chloroform fumigation-NaHCO3 extraction (Zhang et al., 2022b; Mao et al., 2024). Urease (Ure) was determined by the urease colorimetric method (Ren et al., 2016), and β-1,4-N-acetylglucosaminidase (NAG) was determined by the p-nitrophenol colorimetric method of Liu et al. (Liu et al., 2023).

Patient satisfaction with nursing care reflects patients' perceptions of the care they receive from nurses during their hospital stay. Patient satisfaction is a vital measure of healthcare service quality and significantly impacts the overall patient experience. It indicates how effectively healthcare systems, providers, and institutions fulfill patients' expectations and address their needs. Patient satisfaction with nursing care was measured using the Patient Satisfaction Instrument. This study aimed to examine patient satisfaction with nursing care and associated factors in hospitals across the culturally diverse Amhara region. Data are presented in Stata DTA File and Microsoft Excel 97-2003 Worksheet formats.

unprocessed Western data for Figure 1B, unprocessed microscopy data for Figure 1C

This database contains a comprehensive collection of simulated ultrasonic guided wave signals generated using a validated Stochastic Finite Element Methodology. It includes stochastic data from 64 damage configurations, encompassing 16 crack positions with 4 different crack length

This dataset contains all relevant data supporting the manuscript titled "Standardizing pre-processing methods for gas flux data from automated head chamber systems." This manuscript will be submitted for review in Animal - Open Space. This work aims to standardize data pre-processing methods for scientists using the GreenFeed system. The analysis utilized data from 5 previously published experiments, with 3 from pastoral systems and 2 from finishing systems.

The aim of this study was to systematically investigate the protective effect of Herbacetin (Her) against lipopolysaccharide (LPS)-induced inflammatory lung injury and its related mechanisms. Firstly, a mouse model of inflammatory lung injury was successfully constructed by intratracheal drip injection of LPS, and its protective effect on mice with inflammatory lung injury was evaluated by observing the overall lung tissue morphology changes, lung histopathological injury, lung wet-to-dry weight ratio, lung organ coefficients, total proteins, and inflammatory factor contents. The results showed that administration of Her treatment improved LPS-induced lung histopathological injury, reduced lung tissue edema, decreased the content of pro-inflammatory factors TNF-α, IL-6 and IL-1β, and reduced the number of inflammatory cells. Meanwhile, our results also showed that two neutrophil populations (Fth1hi Neu and Prok2hi Neu) in two different locations existed in the lung tissues of mice with LPS-induced inflammatory lung injury, and that LPS stimulation promoted the aggregation of Fth1hi Neu and the release of pro-inflammatory factors in the lung tissues, which was accompanied by a decrease in the content of the anti-inflammatory factor IL-10. Administration of Her treatment increased the content of the anti-inflammatory factor IL-10 in lung tissues, promote apoptosis and clearance of Fth1hi Neu, reduce the aggregation of Fth1hi Neu in lung tissues, and ameliorate the inflammatory injury of lung tissues. In conclusion, Her had a significant protective effect on LPS-induced inflammatory lung injury in mice, and its mechanism of action was related to elevating IL-10 levels and reducing Fth1hi Neu accumulation.

We conducted a pilot study to investigate trusted messengers of the HPV vaccine and conducted 3 focus groups. As part of this pilot study, participants completed a brief demographics survey prior to participating in the focus groups. The current data includes: 1) demographic survey data - a quantitative SPSS file with basic demographic and background information, 2) focus group transcripts - a word document which includes the transcript from 3 focus groups.