In 2024, the Calorie Counter app had the largest number of collected data points possibly linked to the user identity. Out of the total 22 collected data types, 20 were linked to the users' identity, while seven data points could potentially be used to track users. Calorie counting app Eato did not display any of the collected data types that could potentially be used to track users. The iOS mobile app for the Weight Watchers Program collected seven different data points that were not linked to users.

1. File Information

This dataset is a synthetic dataset created based on sampling statistics from the Taiwan Ministry of Health and Welfare. It includes data on height, weight, BMI, and age of individuals, making it suitable for various health-related analyses.

2. Meta Data

3. Potential Analyses

Exploratory Data Analysis (EDA):

• Distribution analysis for height, weight, and BMI.
• Age and gender-based trends.

Regression Analysis:

• Linear Regression: Predict weight based on height and BMI.
• Logistic Regression: Classify individuals by BMI categories.

Clustering and Classification:

• Group individuals into categories (e.g., underweight, healthy, overweight) based on BMI.

Time-Series/Trend Analysis:

• Investigate how health metrics (BMI) evolve over age groups.

Feel free to leave comments on the discussion. I'd appreciate your upvote if you find my dataset useful! 😀

The low birth-weight rate measures the percentage of live births with weights below 2500 grams. A low birth-weight can affect health outcomes later in life, and is an illustrative indicator for the overall health of the measured population.

The low birth-weight rate in Champaign County has been above 8 percent since 2011, the earliest Reporting Year available in the dataset. This is close to the statewide rate, which returned to 8.4 percent from Reporting Year 2021 through present after a slight decrease in recent years. The lowest county low birth-weight rate in the state is 5.6 percent (Carroll County in the northwest corner of the state), while the highest county low birth-weight rate in the state is 11.9 percent (Pulaski County in southernmost Illinois).

This data was sourced from the University of Wisconsin's Population Health Institute's and the Robert Wood Johnson Foundation’s County Health Rankings & Roadmaps. Each year’s County Health Rankings uses data from years prior. Therefore, the 2023 County Health Rankings (“Reporting Year” in the table) uses data from 2014-2020 (“Data Years” in the table).

Source: University of Wisconsin Population Health Institute. County Health Rankings & Roadmaps 2023.

Annual itinerant movements by aircraft weight group, broken down by maximum take-off weight categories ranging from under 2,000 kgs to over 136,000 kgs, and by type of power plant (jet, turbo-propellers, piston, helicopters and gliders) for airports without air traffic control towers.

A common feature of preclinical animal experiments is repeated measurement of the outcome, e.g., body weight measured in mice pups weekly for 20 weeks. Separate time point analysis or repeated measures analysis approaches can be used to analyze such data. Each approach requires assumptions about the underlying data and violations of these assumptions have implications for estimation of precision, and type I and type II error rates. Given the ethical responsibilities to maximize valid results obtained from animals used in research, our objective was to evaluate approaches to reporting repeated measures design used by investigators and to assess how assumptions about variation in the outcome over time impact type I and II error rates and precision of estimates. We assessed the reporting of repeated measures designs of 58 studies in preclinical animal experiments. We used simulation modelling to evaluate three approaches to statistical analysis of repeated measurement data. In particular, we assessed the impact of (a) repeated measure analysis assuming that the outcome had non-constant variation at all time points (heterogeneous variance) (b) repeated measure analysis assuming constant variation in the outcome (homogeneous variance), (c) separate ANOVA at individual time point in repeated measures designs. The evaluation of the three model fitting was based on comparing the p-values distributions, the type I and type II error rates and by implication, the shrinkage or inflation of standard error estimates from 1000 simulated dataset. Of 58 studies with repeated measures design, three provided a rationale for repeated measurement and 23 studies reported using a repeated-measures analysis approach. Of the 35 studies that did not use repeated-measures analysis, fourteen studies used only two time points to calculate weight change which potentially means collected data was not fully utilized. Other studies reported only select time points (n = 12) raising the issue of selective reporting. Simulation studies showed that an incorrect assumption about the variance structure resulted in modified error rates and precision estimates. The reporting of the validity of assumptions for repeated measurement data is very poor. The homogeneous variation assumption, which is often invalid for body weight measurements, should be confirmed prior to conducting the repeated-measures analysis using homogeneous covariance structure and adjusting the analysis using corrections or model specifications if this is not met.

DEEPEN stands for DE-risking Exploration of geothermal Plays in magmatic ENvironments. As part of the development of the DEEPEN 3D play fairway analysis (PFA) methodology for magmatic plays (conventional hydrothermal, superhot EGS, and supercritical), weights needed to be developed for use in the weighted sum of the different favorability index models produced from geoscientific exploration datasets. This GDR submission includes those weights. The weighting was done using two different approaches: one based on expert opinions, and one based on statistical learning. The weights are intended to describe how useful a particular exploration method is for imaging each component of each play type. They may be adjusted based on the characteristics of the resource under investigation, knowledge of the quality of the dataset, or simply to reduce the impact a single dataset has on the resulting outputs. Within the DEEPEN PFA, separate sets of weights are produced for each component of each play type, since exploration methods hold different levels of importance for detecting each play component, within each play type. The weights for conventional hydrothermal systems were based on the average of the normalized weights used in the DOE-funded PFA projects that were focused on magmatic plays. This decision was made because conventional hydrothermal plays are already well-studied and understood, and therefore it is logical to use existing weights where possible. In contrast, a true PFA has never been applied to superhot EGS or supercritical plays, meaning that exploration methods have never been weighted in terms of their utility in imaging the components of these plays. To produce weights for superhot EGS and supercritical plays, two different approaches were used: one based on expert opinion and the analytical hierarchy process (AHP), and another using a statistical approach based on principal component analysis (PCA). The weights are intended to provide standardized sets of weights for each play type in all magmatic geothermal systems. Two different approaches were used to investigate whether a more data-centric approach might allow new insights into the datasets, and also to analyze how different weighting approaches impact the outcomes. The expert/AHP approach involved using an online tool (https://bpmsg.com/ahp/) with built-in forms to make pairwise comparisons which are used to rank exploration methods against one-another. The inputs are then combined in a quantitative way, ultimately producing a set of consensus-based weights. To minimize the burden on each individual participant, the forms were completed in group discussions. While the group setting means that there is potential for some opinions to outweigh others, it also provides a venue for conversation to take place, in theory leading the group to a more robust consensus then what can be achieved on an individual basis. This exercise was done with two separate groups: one consisting of U.S.-based experts, and one consisting of Iceland-based experts in magmatic geothermal systems. The two sets of weights were then averaged to produce what we will from here on refer to as the "expert opinion-based weights," or "expert weights" for short. While expert opinions allow us to include more nuanced information in the weights, expert opinions are subject to human bias. Data-centric or statistical approaches help to overcome these potential human biases by focusing on and drawing conclusions from the data alone. More information on this approach along with the dataset used to produce the statistical weights may be found in the linked dataset below.

SUMMARY The objective of this study was to evaluate the performance of male colonial chickens fed diet supplemented with commercial probiotic (Calsporin ®). A total of 210 male chicks Label Rouge lineage were used and they were raised in experimental shed up to 30 days old. These birds had free access to the pickets of Tifton-85, from 31-90 days of age. The experimental design was completely randomized, two treatments, one containing feed supplemented with probiotic Bacillus subtillis (300 g t-1 Bacillus subtillis 1×109 UFCg-1) and another one without it, with ten replications per treatment, consisting of 21 chickens/replication. The mean of body weight (BW), weight gain (WG), feed intake (FI), feed conversion (FC), mortality and viability were evaluated. The data were submitted to variance analysis and the averages of the treatments were compared by the F-test at 5% of significance. The addition of probiotic (300 g t-1 Bacillus subtillis 1×109 UFCg-1) in the diet of Label Rouge broilers did not interfere in the MW, WG, and FC variables in the total period from 1 to 90 days (P>0.05); the MFI variable differed (P

This dataset contains counts of low birth weight (less than 2500 grams) live births occurring in the calendar year in England and Wales to mothers usually resident in England and Wales. Source: Office for National Statistics (ONS) Publisher: Neighbourhood Statistics Geographies: Local Authority District (LAD), Government Office Region (GOR), National Geographic coverage: England and Wales Time coverage: 1999 to 2007 Type of data: Administrative data

We evaluated potential effects of deltamethrin and fipronil on tiger salamander (Ambystoma mavortium) body mass, behavioral activity, and insecticide tissue residues. Insecticides were applied at realistic concentrations in mesocosms mimicking prairie dog burrows, which are used as refuge by salamanders under natural conditions. Treatments included (1) deltamethrin dust, (2) prairie dog fecal pellets containing fipronil and fipronil sulfone, a metabolite, and (3) controls. Salamanders were monitored before and after treatments, under a before-after-control-impact design. We measured the mass of each individual approximately once per week to assess potential changes in body mass. We used custom-made open-source camera systems to monitor and quantify salamander aboveground activity relative to treatment at ~15 minute intervals; if a salamander was detected outside a burrow at a given point in time, the salamander was classified as active and outside the burrow. On the final day of the experiment, salamanders were euthanized using MS222; whole-body mass was determined, and gonad (ovaries and testes) and liver samples were removed from the carcasses using sterile dissection kits. All tissue was frozen until analysis. Gonad, liver, and whole body samples were assayed for deltamethrin using multiresidue extraction or for fipronil and fipronil sulfone using liquid chromatography with tandem mass spectrometry. This data release consists of four spreadsheets. The first spreadsheet (Fipronil_residues.csv) includes data on treatment (fipronil), sample type (gonads, liver, whole body), fipronil residues measured as nanograms per gram wet weight, and fipronil sulfone residues measured as nanograms per gram wet weight (None Detected = no residues detected). The second spreadsheet (Deltamethrin_residues.csv) includes data on treatment (deltamethrin), sample type (gonads, liver, whole body), and deltamethrin residues measured as nanograms per gram wet weight (None Detected = no residues detected). The third spreadsheet (Body_mass.csv) includes data on salamander identification number, treatment (control, deltamethrin, fipronil), date of body mass measurement, period of experiment (before or after treatment), and salamander body mass in grams. The fourth spreadsheet (Activity.csv) includes camera data on mesocosm identification number, treatment (control, deltamethrin, fipronil), period of experiment (before or after treatment), date of observation, time of observation (using a 24 hour clock), and a binomial variable (1 = yes, 0 = no) for whether or not the associated salamander was detected outside its burrow.

Dataset

This dataset was created by QUEENFI

Released under MIT

Contents

Just a mix of things to be helpful

Global Powered Industrial Trucks market size earned around $55.23 bn in 2023 and is expected to reach $75.28 bn by 2032, with a projected CAGR of 3.5%.

United States Import Value by Product: Silver: Semi-Manufactured Forms, Gross Weight data was reported at 16,500.000 USD th in Apr 2018. This records an increase from the previous number of 6,590.000 USD th for Mar 2018. United States Import Value by Product: Silver: Semi-Manufactured Forms, Gross Weight data is updated monthly, averaging 22,350.000 USD th from Jan 2007 (Median) to Apr 2018, with 136 observations. The data reached an all-time high of 128,000.000 USD th in Aug 2016 and a record low of 190.000 USD th in May 2016. United States Import Value by Product: Silver: Semi-Manufactured Forms, Gross Weight data remains active status in CEIC and is reported by US Census Bureau. The data is categorized under Global Database’s USA – Table US.WB006: Import Value.

Data consists of a record for each truck reporting to the Enterprise Weigh Scale (1999 to present) and Inuvik Weigh Scale (2021 to present). Fields include date and time of reporting, location name (Enterprise or Inuvik), type of goods carried, total vehicle weight, registered gross vehicle weight (GVWR), vehicle configuration, steering axle weight, drive axle(s) weight, axle group weights for up to 6 trailers, trip origin and trip destination. Each data file represents one month.

Overview

This dataset provides measurements related to the growth of cow based on various factors, including weight, height, volume, type of feed, and sunlight intensity. It consists of data points for two different types (A and B) and aims to facilitate analysis of how these variables affect cow growth.

Data Structure

• Weight (kg): Continuous variable representing the weight of the cow in kilograms.
• Height (cm): Continuous variable indicating the height of the cow in centimeters.
• Volume (liter): Continuous variable reflecting the volume associated with the cow (e.g., space or habitat) in liters.
• Type of Feed: Categorical variable indicating the type of feed (A or B) provided to the cow.
• Sunlight Intensity: Categorical variable denoting sunlight intensity (e.g., Gt for good, Lt for low).

Sample Data

Insights and Potential Analyses

• Correlations: Analyze how weight, height, and volume correlate with each other and with the type of feed and sunlight intensity.
• Comparison of Feed Types: Examine growth metrics (weight, height) between different types of feed (A vs. B) under varying sunlight conditions.
• Impact of Environmental Factors: Investigate the role of sunlight intensity on cow growth metrics.

Usage

This dataset can be utilized for research in cow husbandry, agricultural studies, or environmental science, providing insights into how various factors influence cow growth.

Data to form periodic lossless ternary seeds of maximum weight.

Detailed information can be found in the GitHub project (https://github.com/vtman/perlotSeeds). Codes to generate periodic blocks (binary and ternary) can also be found there.

Binary seeds can have only two symbols (0 = "do not care" = "_" or 1 = "match" = "#"). The length of a seed is the number of its elements, weight of a seed is the number of its 1-elements. The goal is to find seeds of maximum weight, so they can be used when there are two strings with a given number of mismatches. It is observed that in many cases these seeds of maximum weight have a periodic structure: the same block is repeated multiple times + its remainder. Blocks for binary seeds can be found with the help of the PerFSeeB project (https://github.com/vtman/PerFSeeB). These blocks have the maximum possible weight.

In genetics, we have four symbols in sequences (A, C, G, T). However, the chance of having a pointwise mutation is not the same for any pairs. A transition mutation (A ↔ G or C ↔ T) is often twice higher than a transversion mutation (A ↔ C, A ↔ T, G ↔ C, G ↔ T). Transition-constrained seeds use ternary alphabet {#, @, _} where @ is for a match or a transition mismatch. To generate ternary seeds, we first need to generate ternary blocks. These ternary blocks can be found when we use binary blocks. However, sometimes, we need to use binary blocks for less than the maximum weight.

BinaryDataLevel.zip contains binary blocks (mostly of maximum weight, but 1/5 are for smaller weights (less than one and a couple of blocks than two)).

Files T1V1.zip, T1V2.zip,..., and T8V1.zip contain ternary blocks in binary format. T4V2.zip and T7V2.zip are in the other dataset.

File bestTernary.zip contains ternary seeds of maximum weight (calculated as the number of # symbols + half of @ symbols)

Gross weight of goods handled in main ports by direction and type of cargo - quarterly data

BACKGROUND: Weight loss and malnutrition may be caused by many factors, including type of disease and treatment. AIM: The present study investigated the occurrence of in-hospital weight loss and related factors. METHOD: This cross-sectional study investigated the following variables of 456 hospitalized patients: gender, age, disease, weight variation during hospital stay, and type and acceptance of the prescribed diet. Repeated measures analysis of variance (ANOVA) was used for comparing patients' weight in the first three days in hospital stay and determining which factors affect weight. The generalized estimating equation was used for comparing the food acceptance rates. The significance level was set at 5%. RESULTS: The most prescribed diet was the regular (28.8%) and 45.5% of the patients lost weight during their stay. Acceptance of hospital food increased from the first to the third days of stay (p=0.0022) but weight loss was still significant (p

Global Electronic Weight Scale Market size was valued at USD 4.38 Billion in 2024 and is projected to reach USD 6.23 Billion by 2031, growing at a CAGR of 4.50% from 2024 to 2031.

The Electronic Weight Scale market is driven by the rising demand for precision and accuracy in weight measurement across various industries, including healthcare, retail, manufacturing, and logistics. In healthcare, the growing focus on fitness, health monitoring, and medical diagnostics is boosting the adoption of digital scales for tracking body weight and composition. In retail and food sectors, stringent regulations on product labeling and packaging drive the need for accurate weighing systems. Additionally, advancements in sensor technology, increased automation in industrial processes, and the rise of e-commerce are fueling the demand for electronic weight scales that offer reliability, ease of use, and connectivity features for data tracking and analysis.

BackgroundThis meta-analysis aims to evaluate efficacy and safety of tirzepatide for weight loss, including its dose-response relationship and adverse event profile.MethodsStudies were retrieved from high-impact journals and included phase 1 to phase 3 trials. Participants received tirzepatide at 5,10, or 15 mg doses or a placebo control. Weighted mean differences (WMD) and odds ratios (OR) with 95% confidence intervals (CIs) were used to evaluate treatment effects, and heterogeneity was assessed using I² statistic.ResultsTirzepatide induced a mean weight reduction of –10.39 kg versus placebo (95% CI: –10.80 to –9.99; p < 0.00001). Subgroup analyses by diabetes status showed that patients with type 2 diabetes lost –6.17 kg (95% CI: –7.16 to –5.17; p < 0.00001) at 5 mg, –8.57 kg (95% CI: –9.41 to –7.74; p < 0.00001) at 10 mg, and –9.60 kg (95% CI: –10.32 to –8.89; p < 0.00001) at 15 mg. Non-diabetic participants experienced greater absolute losses of –12.10 kg (95% CI: –13.47 to –10.72; p < 0.00001), –15.94 kg (95% CI: –17.25 to –14.62; p < 0.00001), and –17.86 kg (95% CI: –19.19 to –16.54; p < 0.00001) at the respective doses. Tirzepatide also markedly increased the odds of achieving clinically meaningful weight loss: ≥ 5% (OR=11.32; p < 0.0001), ≥ 10% (OR=14.77; p < 0.0001), and ≥ 15% (OR=18.07; p < 0.0001. Adverse events were more frequent with tirzepatide than placebo (OR=1.34; p < 0.0001), largely driven by gastrointestinal symptoms, whereas serious adverse events did not differ. Discontinuations due to side effects increased at higher doses (OR=2.31; p < 0.0001).ConclusionsTirzepatide induces significant, dose-dependent weight loss, with higher doses yielding greater reductions. While gastrointestinal side effects were common, they were generally mild to moderate and did not increase serious adverse events. These findings support tirzepatide as an effective weight management therapy, though strategies to mitigate gastrointestinal symptoms may improve adherence.