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This panel dataset integrates three core sources: the China Labor-force Dynamic Survey (CLDS, 2012/2014/2016), the U.S. NCEI’s Global Summary of the Day (GSOD) meteorological data, and the China City Statistical Yearbook. Meteorological data were spatially interpolated via inverse distance weighting (IDW) into 0.1°×0.1° grids, with missing values imputed using five nearest stations. City-level annual average temperature (primary variable, plus its squared term for non-linearity testing) and annual precipitation were derived. The dependent variable is the natural logarithm of individual annual total income. Controls include individual attributes (age, education years) and urban socioeconomic indicators (fiscal expenditure-to-GDP ratio, economic agglomeration, secondary industry share, GDP growth rate). Standard data cleaning (coding unification, outlier removal, price deflation) was applied. The final sample includes 29,629 valid observations, with a mean log income of 9.773, average annual temperature of 16.425°C, and mean age of 44.117 years. This dataset merges micro individual heterogeneity with macro climatic and economic data, supporting analyses of temperature’s causal effects on labor income and related mechanisms.

Analise_Filogenia_hondialvs

Dataset and analysis output in SPSS

This dataset contains data related to the Hindi translation, cultural adaptation, validation, and test–retest reliability testing of the Telematic Fugl Meyer Assessment Scale–Upper Extremity (TFMA-UE) in stroke patients. The purpose of the study was to develop a standardized Hindi version of the TFMA-UE and evaluate its psychometric properties for use among Hindi-speaking stroke survivors. The TFMA-UE is a widely used clinical outcome measure for assessing upper extremity motor recovery following stroke, particularly in tele-rehabilitation settings. The dataset includes demographic and clinical details of participants such as age, gender, type of stroke, duration since stroke onset, affected side, and severity of upper limb impairment. It also contains translated assessment forms, scoring records, expert review data, and statistical outputs generated during validation and reliability analysis. The Hindi translation was performed using a standardized forward–backward translation process to ensure semantic and cultural equivalence with the original English version. Content validity was evaluated by a panel of rehabilitation experts, including physiotherapists and neurologists, using item-level and scale-level validity indices. Construct validity was assessed through comparison with established upper extremity functional assessment measures. Reliability analysis included internal consistency and test–retest reliability. Cronbach’s alpha was used to determine internal consistency, while Intraclass Correlation Coefficients (ICC) were used to evaluate stability of scores across repeated assessments. Additional statistical measures such as standard error of measurement (SEM) and descriptive statistics are included in the dataset. All participant information was anonymized, and data collection was conducted according to institutional ethical guidelines. The dataset may be useful for researchers, clinicians, and rehabilitation professionals involved in stroke rehabilitation, tele-rehabilitation, psychometric testing, and cross-cultural adaptation of clinical assessment tools. The validated Hindi TFMA-UE can support reliable remote assessment of upper extremity motor function in Hindi-speaking stroke populations and may contribute to improved accessibility of rehabilitation services in diverse clinical settings.

Damselfly community data collected in 2023 and 2025 from 24 ponds across Northern England and Wales.

This dataset contains 32,341 viewer comments collected from two YouTube channels associated with the Pro Kabaddi League (PKL) — the official Pro Kabaddi League channel and the Star Sports channel — spanning six consecutive seasons (Seasons 7 through 12, approximately 2019 to 2024). The PKL, established in 2014, is one of India's most prominent professional sports leagues and is built around kabaddi, a traditional indigenous contact sport. Comments were gathered from a range of video content including live match broadcasts, recorded replays, highlight clips, short-form videos, and post-match press conferences. Raw comments — including those written in Hindi, Tamil, Telugu, Marathi, and other Indian regional languages — were translated into English using the OpenAI API, cleaned, and filtered to remove very short entries and special symbols. Each comment was then classified into one of three quality tiers: Rich (detailed, player- or tactic-specific content), Moderate (some context but limited depth), and Poor (generic or off-topic). The dataset is structured as a single CSV file with two tabs — one per channel — and each row contains the original comment, the preprocessed version, season label, video type, timestamp, like count, and classification label. The dataset is suitable for research in natural language processing, sentiment analysis, sports fan engagement, digital media studies, sports marketing, and multilingual text analytics. It is the first publicly available annotated comment corpus from the Pro Kabaddi League.

Frequency response functions (FRFs) of a twelve-story structure with 3,390 degrees of freedom (1,130 nodes × 3 directions), computed over 100 discrete frequency points in the range 0–20 Hz. Data were generated using SAP2000 steady-state analysis and cover 22 cases: one healthy (undamaged) baseline state and 21 damage scenarios.

simulation file of experimental data

This resource consists of a three-dimensional model of the skull of a scarlet macaw (Ara chloropterus), developed to address the lack of adapted materials in the teaching of Natural Sciences for visually impaired students. The material presents tactile-visual characteristics, including identification captions for sighted people and in Braille. The project integrates 3D printing and laser cutting technologies to create a resource with tactile significance, resistance, and safety, allowing the exploration of content such as anatomy, evolution, and biodiversity in regular or multifunctional classrooms.

The North-eastern Himalaya witnessed earthquakes in 1697 CE (Sadiya), 1714 CE (Bhutan-Arunachal), and 1950 CE (Tibet–Assam). Previous studies along the Himalayan Frontal Thrust of the Assam seismic gap and within the meizoseismal zone of the 1950 earthquake reported evidence of primary surface faulting of the 1697 and 1950 CE earthquakes. Due to the sparse distribution of paleoseismological trenches and limited historical archives, it has been quite difficult to precisely locate the lateral limits of the surface ruptures of the 1697 and 1950 events and to constrain the recurrence intervals of these earthquakes. Also, a correlation between the endpoints of historical ruptures and transverse discontinuities along the active fault strike is unknown in the Assam-Arunachal segment. Toward this, palaeoseismological investigations were conducted at Niglok village, between the Subansiri and Siang River valleys, Arunachal Pradesh, to determine the lateral termination of the surface rupture of the northeast Himalayan earthquake events. This is the first study to provide evidence of the lateral extent and rupture termination of the primary surface faulting by 1697 and 1950 CE earthquakes, the role of variation in MHT geometry and transverse structural heterogeneities in their rupture propagation, and the recurrence interval variability in north-eastern Himalayan regions.