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For the terrace slope and ridge plant slope, three sampling points were established in an “S”-shaped pattern at each slope position, with three corresponding points at the same positions on the control slope. In August 2024, undisturbed soil samples were collected from three layers: 0–20 cm, 20–40 cm, and 40–60 cm depth. The measured indicators include soil organic carbon (SOC), microbial biomass carbon (MBC) , dissolved organic carbon (DOC), easily oxidizable organic carbon (EOC), particulate and mineral-associated organic carbon (POC, MAOC), and steady-state organic carbon (S-SOC ). Table 1 shows the data of carbon fractions in terracing slope, Table 2 shows the relevant data of carbon fractions in ridge planting slope, and Table 3 shows the basic physical and chemical properties of the soil.

This repository hosts the genome assembly of Cucumis melo L. var. chate, reconstructed via a hybrid assembly of PacBio HiFi, ONT ultra-long, and Hi-C sequencing technologies. Data includes: - FASTA files: Primary and masked genome assemblies. - Comparative Tools: A conversion table linking this assembly to the existing reference. - Annotation Files: Gene models, transcriptomes, protein sequences, and transposable element (TE) characterizations. - Functional Annotation: A comprehensive table mapping Gene IDs to Gene Names, Gene Ontology (GO) terms, and detailed Functional Descriptions, facilitating downstream biological interpretation.

1. Summary This dataset contains processed and fully anonymized metadata from WhatsApp chat histories. It is designed for researchers in fields such as Computational Linguistics, Social Network Analysis (SNA), and Human-Computer Interaction (HCI). Unlike raw chat logs, this dataset preserves user privacy by removing all message content and personally identifiable information (PII), replacing them with structural descriptors (e.g., message length ranges, emoji arrays) and cryptographic hashes. 2. Methodology The raw data was processed using a custom Python pipeline centered on privacy-by-design. The transformation includes:Temporal Anonymization: Timestamps were shifted with a random noise offset (-4 to +5 seconds) and converted into relative_time_seconds to mask actual dates and times while preserving the cadence of interaction.Identity Masking: Senders and mentioned phone numbers were transformed into 16-character SHA256 hashes using a unique salt for each file.Content Abstraction: Textual content was discarded. In its place, the dataset provides binned message lengths (ranges), punctuation markers (interrogative/exclamatory), and extracted emoji lists.Conversation Clustering: An Inter-Quartile Range (IQR) based algorithm was used to segment messages into "sessions" or conversation_ids, identifying natural breaks in communication based on temporal gaps. 3. Data Description The data is provided in CSV format (semicolon-separated). Each file represents a specific group or chat, containing the following features: Column,Description id,Sequential message identifier within the file. conversation_id,Cluster ID representing a continuous session of interaction. num_characters,"Binned message length (e.g., ""1-10"", ""11-50"", ""500+"")." relative_time_seconds,Seconds elapsed since the start of the observation period. message_type,"Categorization of the entry (e.g., text, audio, image, sticker, system)." responds_to_id,The ID of the parent message in a reply thread (if applicable). array_emojis,List of unique emojis present in the original message. interrogative,Boolean; indicates the presence of question marks. exclamatory,Boolean; indicates the presence of exclamation marks. sender_hash,Salted SHA256 hash of the message sender. mentioned_phones_hash,"List of hashes for phone numbers mentioned via ""@"" in the text." 4. Potential Research Applications Interaction Dynamics: Analyzing response times and turn-taking patterns in digital communication.Non-Verbal Communication: Studying the usage and frequency of emojis across different conversation types.Network Topology: Mapping the flow of information through "responds_to" hilos (threads) and mentions.Behavioral Modeling: Detecting session-based patterns and communication bursts.

Overview This dataset contains experimental data on soil aggregate stability and the spatial redistribution of soil organic carbon (SOC) under varying slope gradients and soil management practices in the black soil region of Northeast China. It elucidates how physical barriers influence soil erosion and carbon transport on sloping farmlands. 1. Experimental Design & Methods Conducted in runoff plots within the Qinggou small watershed (Changchun City, Jilin Province), the study used a fully crossed design: Treatments: Furrow straw mulch (S) vs. No mulch/Control (CK). Slope Gradients: 3°, 6°, and 9°. Hillslope Positions: Upper (U), Middle (M), and Lower (L). Data includes water-stable aggregate fractions (macroaggregates >0.25 mm, microaggregates 0.053–0.25 mm, silt and clay <0.053 mm) and their associated SOC content (SOC_M, SOC_u, SOC_S&C). Calculated physical parameters include percentage of aggregate destruction (PAD), mean weight diameter (MWD), and geometric mean diameter (GMD). All measurements include three independent replicates (n=3), totaling 54 data rows. 2. Key Findings Furrow straw mulch shifts uniform soil erosion to selective sediment transport. Steep slopes (9°) drive significant SOC deposition at lower hillslope positions due to cumulative blocking effects. Mulch enhances water-stable aggregate stability (decreased PAD, increased MWD and GMD) specifically in sedimentation-prone zones. Macroaggregates act as the primary carrier for redistributed SOC across the hillslope. SOC conservation in this system relies on physical retention mechanisms rather than direct carbon input. 3. Data Interpretation & Usage Guidelines Sample Labels: In labels like "9°S-L", the number denotes the slope (9°), "S" indicates furrow straw mulch (absence means CK), and the final letter denotes the position (Upper, Middle, or Lower). Normalization: The mass proportions of the three aggregate fractions (Macro, Micro, Silt & Clay) sum to 100%. Users visualizing this data (e.g., stacked bar charts) should normalize the raw mass values to relative percentages. Spatial Dynamics: High SOC and macroaggregate values at the lower positions (L) on steep slopes indicate depositional sinks. These represent trapped sediment detached from upper positions, not a lack of erosion.

Analysis code and derived datasets for a feasibility-bounded diet optimization study across ten countries (4.15 billion people). The repository contains Python scripts, processed result tables, and reproducibility documentation for three phases of analysis: baseline dietary assessment, linear-programming optimization under plus-or-minus 50% intake-change bounds, and sensitivity and uncertainty analyses. Reported outcomes include DALYs averted and environmental indicators, including greenhouse gas emissions, land use, freshwater withdrawals, and eutrophication. The repository also includes region-specific FAO GLEAM v3.0 ruminant emission coefficients used in the environmental analyses. Upstream source datasets, including GBD 2023, Global Dietary Database 2018, and FAO Food Balance Sheets, are not redistributed because they are provided by third-party sources and may be subject to licensing or access restrictions; acquisition details are described in the accompanying README.

The Africa Supply and Use Tables Database is supported by the research initiative "Structural Transformation and Economic Growth" (STEG/CEPR). Any errors or omissions are entirely the responsibility of the GGDC (Groningen Growth and Development Centre) When using these data (for whatever purpose), please make the following reference: Mensah, E. B., and G. J. de Vries (2024). "The Role of Exports for Income and Job Creation in Sub-Saharan African Countries: New Evidence using the Africa Supply and Use Tables Database" GGDC research memorandum 197, DOI: 10.34894/QYFI1U. User information The ASUT includes the following data: Countries Cameroon Ethiopia Ghana Kenya Mauritius Nigeria Rwanda Senegal Tanzania South Africa Zambia Variables Supply table in basic prices (SUP) Use table in basic prices (USE_bas) Sectors Agriculture, ISIC Rev. 4 code: A Mining, ISIC Rev. 4 code: B Food, ISIC Rev. 4 code: C10t12 Textiles, ISIC Rev. 4 code: C13t15 Wood, ISIC Rev. 4 code: C16t18 Fuel, ISIC Rev. 4 code: C19t22 Metals, ISIC Rev. 4 code: C23t25 Electronics, ISIC Rev. 4 code: C26t27 Machinery, ISIC Rev. 4 code: C28 Transportation equipment, ISIC Rev. 4 code: C29t30 Other manufacturing, ISIC Rev. 4 code: C31t33 Utilities, ISIC Rev. 4 code: DtE Construction, ISIC Rev. 4 code: F Trade, ISIC Rev. 4 code: GnI Transport, ISIC Rev. 4 code: H Business services, ISIC Rev. 4 code: JnMN Financial services, ISIC Rev. 4 code: K Real estate, ISIC Rev. 4 code: L Public administration, ISIC Rev. 4 code: OtQ Other services, ISIC Rev. 4 code: RtU Other Variables Household consumption, Code: xCONS_h Government consumption, Code: xCONS_g Gross fixed capital formation, Code: xGFCF Changes in inventories, Code: xINV Exports, Code: xX Imports, Code: xM Total Supply at Basic Prices, Code: xSUP_bas Trade and Transport Margins, Code: xMRG Taxes less Subsidies on products, Code: xTXSP Total Supply at Purchaser Prices, Code: xSUP_pur Intermediate Inputs, Code: xII Value Added, Code: xVA Gross Output, Code: xGO ISO countrycode, Code: cnt Domestic or imported, Code: Dom_Imp Time period The dataset covers tables from 1990 to 2019. (2024-03-08)

Abstract: Languages vary considerably in marking future events. We investigated whether differences in future tense reference (FTR) across languages could explain cross-country variances in corporate capital structure. Using 798,123 firm-year observations across 71 countries from 1984 to 2019, we find that languages requiring future time marking (strong-FTR) tend to be associated with lower leverage ratio. Moreover, this language-leverage correlation strengthens under well-designed formal and informal institutions. Besides, strong-FTR languages are linked with faster leverage adjustments and reduced adjustment expenses. This study pioneers an exploration of the link between FTR in language and corporate capital structure through the lens of temporal belief precision, offering a new perspective on cross-country capital structure differences.

This dataset contains raw and processed single-molecule FRET (smFRET) data used to quantify Hfq-mediated annealing between bacterial sRNAs and mRNAs. It includes fluorescence time traces, extracted dwell times, FRET distributions, and analysis scripts supporting measurements of how seed length, Hfq-binding motifs, and motif spacing affect interaction stability and kinetics. The data enable independent reproduction of the analyses and reuse for modeling RNA–RNA interaction dynamics and RNA chaperone function. Funding: This research was funded by the National Science Centre, Poland, grant no 2022/46/E/NZ1/00462 and an EMBO Installation Grant IG 5730-2024.

Raw images of western blot and confocal microscopy.

Analysis of the database led to the description of a new species of rodent from the Ecuadorian Andes, discovered following the examination of specimens of Thomasomys spp.