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The data generated from the study entited "Simple and reliable cotton leaf-disc bioassay method for thrips with note of field efficacy of insecticides " are submitted herewith.

The data in this dataset is collected from consumers who have experienced big-data-enabled price discrimination in OTAs.

This research is grounded in the hypothesis that interior interaction design plays a central role in shaping user trust, perceived safety, comfort, and adoption readiness in Urban Air Mobility (UAM). Specifically, the study hypothesises that visible safety cues, transparent communication, ergonomic comfort, and human-centered interaction features positively influence user acceptance of autonomous air mobility systems. Rather than viewing adoption as a direct outcome of technological performance, the study assumes that adoption is mediated through users’ experiential and psychological interpretations of the cabin environment. This dataset supports the study “Designing Trust in Urban Air Mobility: The Role of Interior Interaction Design in Shaping Safety and User Acceptance.” It comprises anonymised data collected through a two-phase online survey designed to examine user experience (UX) factors influencing trust, safety perception, comfort, usability, and adoption readiness in Urban Air Mobility (UAM). Phase 1 involved an exploratory pilot survey conducted with 44 urban travellers, aimed at refining survey items and validating the relevance of experiential constructs related to UAM interiors and interaction design. Insights from this phase informed the final structure of the survey instrument. Phase 2 consisted of the main survey administered to 261 urban travellers in India, using a structured questionnaire with Likert-scale items measuring five experiential constructs—trust, safety, comfort, usability, and adoption readiness—along with demographic variables such as age group and city of residence. This phase also included open-ended qualitative questions to capture contextual insights into user perceptions, concerns, and expectations regarding UAM interior environments. All responses were anonymised at the point of collection, and no personally identifiable information was recorded. The dataset was generated exclusively for academic research purposes and analysed using established quantitative and qualitative methods appropriate for design research.

This dataset includes the application effects of IVR technology in gynecological surgery.

CT raw images of Na₂SO₄ hydrate crystallization in clay were obtained by cooling specimens saturated with salt solution. Temperature conditions include bidirectional cooling, unidirectional cooling, and heating-cooling cycles.

To analyze the differences in metabolites in the muscle of crayfish, untargeted metabolomics technology was used to reveal the metabolic changes caused by different treatments. Organic acids and derivatives (34.14%), lipids/lipid-like molecules (27.64%), and organoheterocyclic compounds (10.09%) were the predominant molecular classes, reflecting the metabolic prioritization of energy substrates and membrane components in muscle tissue

This dataset supports the reproduction and extension of the experiments reported in “A predictive–comparative framework for construction cost control using long short-term memory and digital twin technologies”. It includes curated datasets and examples for LSTM-based construction cost forecasting, together with Digital Twin and BIM-enabled progress verification components. The package provides (i) processed training and evaluation data or scripts to generate the training inputs, (ii) a real-world case study example set, (iii) runnable code and configuration files for reproducing the main results, and optionally (iv) pre-trained model checkpoints and example outputs. Sensitive identifiers and project-specific confidential materials are removed or not included where applicable. Detailed file structure, usage instructions, and reproduction steps are provided in Dataset_Description.pdf.

The Karakalpak Speech Corpus is the first large-scale, publicly available speech-to-text dataset for the Karakalpak language, designed to support the development, evaluation, and benchmarking of automatic speech recognition (ASR) systems for this low-resource Turkic language. Research hypothesis The core hypothesis behind this dataset is that high-quality, carefully curated speech–text pairs, even at moderate scale, can enable state-of-the-art self-supervised models (such as Wav2Vec 2.0) to achieve strong recognition performance for low-resource languages. By providing sufficient phonetic, lexical, and speaker diversity, the corpus aims to bridge the data gap that has historically limited Karakalpak speech technology. What the data contains The dataset consists of: Speech recordings in WAV format (16 kHz, 16-bit PCM) Manually verified transcriptions in standard Karakalpak Latin orthography Speaker-independent splits for training, validation, and testing Each audio file corresponds to a single utterance, making the corpus suitable for end-to-end ASR, forced alignment, pronunciation modeling, and acoustic analysis. The recordings include: Read speech Conversational and narrative sentences Phonetically rich word sequences Numbers, commands, and daily expressions This ensures broad coverage of Karakalpak phonology, morphology, and vocabulary. How the data was gathered The corpus was collected from native Karakalpak speakers under controlled recording conditions. All recordings were made in quiet indoor environments using consumer-grade microphones and laptops at 16 kHz. Speakers were instructed to read predefined texts clearly and naturally. All transcriptions were manually checked and normalized to remove spelling inconsistencies, Unicode artifacts, and non-Karakalpak characters. This results in a clean and reproducible linguistic representation of spoken Karakalpak. What the data shows The dataset demonstrates that: Karakalpak phonemes and special letters (á, ó, ú, ı, ń, ś, ǵ) can be reliably captured and modeled A consistent orthography and vocabulary can be established for ASR training Speaker-independent evaluation is feasible When used to fine-tune Wav2Vec 2.0 models, the corpus produces low word error rates (WER) and character error rates (CER), confirming that the dataset contains sufficient acoustic and linguistic information for high-quality speech recognition.

Low-density lipoprotein receptor (LDLR) is crucial in regulating cholesterol metabolism. LDLR decreases cholesterol levels through receptor-mediated endocytosis. Inducible degrader of LDLR (IDOL) inhibits the uptake of low-density lipoprotein (LDL) by down-regulating the expression of LDLR, which leads to hypercholesterolemia. Research has demonstrated that the development of cerebral ischemia/reperfusion injury (CI/RI) is associated with elevated cholesterol levels in the brain. Our results showed that compared to normal mice, IDOL was highly expressed, and the expression of LDLR was significantly decreased in the MCAO mice. Knockout of IDOL can downregulate the expression of LDLR, upregulate the expression of Apolipoprotein E (ApoE) and Caspase-3, promote the occurrence of neuroinflammation and cell apoptosis in the MCAO mice, and play a particular protective role in CI/RI mice.

A CMT welding simulation was carried out in ANSYS Fluent. The simulation was completed through UDF programming combined with GUI-based operations. A case file has been uploaded to the database; users can download it and reproduce the results presented in the paper using the material parameters provided in the database.In this study, the mechanism of strength–ductility synergy in CMT arc additively manufactured Mg–Gd–Y–Zn–Zr alloys was clarified. At a wire feeding speed of 14 m/min, high heat input enhanced molten-pool flow and stirring, enabling bubble escape and nearly eliminating porosity. Meanwhile, increased heat input dispersed agglomerated Zr particles into the pool, providing abundant heterogeneous nucleation sites and causing abnormal grain refinement (~6.32 μm) despite a lower cooling rate. As a result, the alloy achieved 328 MPa UTS and 7.27% elongation, attributed to reduced pores, grain-refinement strengthening, basal slip activation, and continuous twinning.