Output Figures Research Articles

Publication-ready single nucleotide polymorphism visualization with snipit.

Snipit is an analysis and visualization tool designed for summarizing single nucleotide polymorphisms in sequences in comparison to a reference sequence. This tool efficiently catalogues nucleotide and amino acid differences, enabling clear comparisons through customizable, publication-ready figures. With features such as configurable colour palettes, customizable record sorting, and the ability to output figures in multiple formats, snipit offers a user-friendly interface for researchers across diverse disciplines. In addition, snipit includes a specialized recombi-mode for illustrating recombination patterns, which can highlight otherwise often difficult-to-detect relationships between sequences. Snipit is an open-source python-based tool that is hosted on GitHub under a GNU-GPL 3.0 licence (https://github.com/aineniamh/snipit). It can be installed from PyPi using pip. Source code and additional documentation can be found on the GitHub repository.

Experimental Measurement of Fixed-Tilt Solar Panel and Vertical-Tilted Single-Axis Solar Tracker (VTSAT) Real-Time Solar Panel Output Power”

Renewable solar energy is becoming more and more vital, and photovoltaic (PV) solar panel efficiency optimization is essential for sustainable energy generation. This study describes an experiment that uses a solar panel multimeter to measure the output power of a fixed-tilt solar panel and a vertical-tilted single-axis solar tracker (VTSAT) in real time. This measurement indicates that solar panel performance varies with several external factors, including temperature fluctuations. Perform a comparison analysis in this study between a vertical-tilted single-axis solar tracker (VTSAT) and a traditional fixed-tilt solar panel. Two 50-watt solar panels' output data were measured using a solar panel multimeter. Utilizing this comparison analysis, assess these panels' real-world performance. Determining the individual efficiency of the two solar panels will be made easier by analyzing the output figures. Moreover, the goal is to compute the daily energy production produced by every kind of solar panel under standard climatic conditions.

Modifying the success story of Sweden: Revised output and labour productivity figures for manufacturing, 1869–1950

AbstractThe rampant growth rate of output and productivity in manufacturing borne out by Swedish Historical National Accounts (HNA) has nurtured the notion that the Swedish rise to prosperity was propelled by the confluence of disproportionately high levels of sophistication and very low levels of output per worker. The thrust of the argument is that this unique configuration allowed Sweden to leapfrog into modernization. The time has come to put this arresting claim under scrutiny, which is the foremost aim of this paper. This claim, we argue, is founded on a questionable empirical foundation. The most frequently used series of outputs from manufacturing at large and from groups of industries are those of the Swedish HNA. For several reasons, these series are inappropriate to use in studies assessing the rate of output and productivity increases before 1950. We have established new series of output and labour input for manufacturing at large between 1869 and 1950 that are suitable for investigations of productivity growth rates. The resulting series significantly raises the level of output per worker in the early part of the period and hence lowers the estimated growth rates of productivity for the era as a whole.

Moving towards One Health surveillance of antibiotic resistance in France: a semi-quantitative evaluation of the level of collaboration within the national surveillance system.

Collaboration between surveillance programmes is the keystone of One Health surveillance and international organizations call for integrated surveillance systems to manage antibiotic resistance (ABR). In France, the ABR surveillance system covers human, animal, food and the environment sectors, but appears to be fragmented, questioning its level of integration. This study aimed to evaluate collaboration within this system and to formulate recommendations towards more integration. ECoSur, a semi-quantitative tool, was used to evaluate collaboration between surveillance programmes. A total of 31 attributes were evaluated using information from the literature and 52 interviews with surveillance actors from all four sectors. Evaluation results were visualized via three output figures displaying aspects related to governance and functionality of collaboration. Results were validated by an expert committee. Overall, the French collaborative strategy for ABR surveillance was well formalized and relevant to its objectives. However, a cross-sectoral coordination body was lacking to help with its practical implementation. The environmental sector was largely uncovered, but its integration appeared necessary to meet the strategy objectives. Data sharing and joint data analyses between programmes were insufficient, mainly due to limited resources and data interoperability issues. Collaboration was operational for internal and external communication of the results. Twelve recommendations were suggested to decision makers to foster collaboration within the French surveillance system and feed future strategies against ABR. This first evaluation of collaboration within the French ABR surveillance system produced concrete recommendations to move towards One Health integrated surveillance. Both the approach and the findings could be of interest to other countries.

The impact of price policy on the production and marketing of Wheat in Nineveh governorate (Mosul and Telkaif district) as a model for the 2019-2020 agricultural season.

The research aims to analyze the economic implications of the State's policy in the production and marketing of wheat crops in Nineveh governorate (Mosul and Telkaif judiciary) by comparing private and social prices by adopting the method of the policy analysis matrix and calculating the standards derived from there. The study results showed that the protection measures showed that there was government support and subsidization for producers of this crop. This is apparent when examining the nominal protection coefficient figures for output per dunum (1.322, 1.370, 1.310 and 1.327) for each of the three categories and the entire sample, respectively. Nominal input protection coefficient values were per dunum (0.486, 0.436, 0.487 and 0.474) for each of the three categories and the entire sample, respectively. The comparative advantage indicators showed that the crop in Nineveh governorate (Mosul and Telkaif judiciary) had a comparative advantage and global competitiveness to produce, The value of the special cost ratio per dunum (0.284, 0.318, 0.319 and 0.316) for each of the three categories and the entire sample respectively. The study recommends increasing government support for crops that have a comparative advantage in their production and are globally competitive to achieve self-sufficiency and then reach the export stage.

Omnidirectional-Sensor-System-Based Texture Noise Correction in Large-Scale 3D Reconstruction.

The evolution of cameras and LiDAR has propelled the techniques and applications of three-dimensional (3D) reconstruction. However, due to inherent sensor limitations and environmental interference, the reconstruction process often entails significant texture noise, such as specular highlight, color inconsistency, and object occlusion. Traditional methodologies grapple to mitigate such noise, particularly in large-scale scenes, due to the voluminous data produced by imaging sensors. In response, this paper introduces an omnidirectional-sensor-system-based texture noise correction framework for large-scale scenes, which consists of three parts. Initially, we obtain a colored point cloud with luminance value through LiDAR points and RGB images organization. Next, we apply a voxel hashing algorithm during the geometry reconstruction to accelerate the computation speed and save the computer memory. Finally, we propose the key innovation of our paper, the frame-voting rendering and the neighbor-aided rendering mechanisms, which effectively eliminates the aforementioned texture noise. From the experimental results, the processing rate of one million points per second shows its real-time applicability, and the output figures of texture optimization exhibit a significant reduction in texture noise. These results indicate that our framework has advanced performance in correcting multiple texture noise in large-scale 3D reconstruction.

Generalized Programming Idea for Making the Thermoelectric Device Using MATLAB Software for Cu2Bi2Te3 and Cu2Sb2Te3

Device fabrication using simulation process and modeling are one of the most leading researches in present days. Here, the Thermoelectric Device performance is analyzed with basic coding using MATLAB software. The MATLAB based fabrication of thermoelectric generator lead to analysis the power efficiency and ZT performance for the materials (Cu2Bi2Te3 and Cu2Sb2Te3). All parameters were optimized and the function output (Figure of Merit) was 2.59 (no unit) for Cu2Bi2Te3 and 0.657 (no unit) for Cu2Sb2Te3.

CLARITY: a Shiny app for interactive visualisation of the bovine physical-genetic map.

The arrangement of markers on the genome can be defined in either physical or linkage terms. While a physical map represents the inter-marker distances in base pairs, a genetic (or linkage) map pictures the recombination rate between pairs of markers. High-resolution genetic maps are key elements for genomic research, such as fine-mapping of quantitative trait loci, but they are also needed for creating and updating chromosome-level assemblies of whole-genome sequences. Based on published results on a large pedigree of German Holstein cattle and newly obtained results with German/Austrian Fleckvieh cattle, we aim at providing a platform that allows users to interactively explore the bovine genetic and physical map. We developed the R Shiny app CLARITY available online at https://nmelzer.shinyapps.io/clarity and as R package at https://github.com/nmelzer/CLARITY that provides access to the genetic maps built on the Illumina Bovine SNP50 genotyping array with markers ordered according to the physical coordinates of the most recent bovine genome assembly ARS-UCD1.2. The user is able to interconnect the physical and genetic map for a whole chromosome or a specific chromosomal region and can inspect a landscape of recombination hotspots. Moreover, the user can investigate which of the frequently used genetic-map functions locally fits best. We further provide auxiliary information about markers being putatively misplaced in the ARS-UCD1.2 release. The corresponding output tables and figures can be downloaded in various formats. By ongoing data integration from different breeds, the app also facilitates comparison of different genome features, providing a valuable tool for education and research purposes.

A novel approach for aerogenerators- triple state absorption-based cooling system

The capacity of wind turbines is growing steadily, but their operations require significant energy, particularly for large turbines that utilize their own electricity. Unlike other types of power plants, such as hydro and coal-based plants, wind turbines rely on electricity from the grid for their operations, which is not factored into their output figures. While there are several power consumption functions within a wind turbine, this paper focuses on the cooling system for power electronic interfaces. The paper proposes a viable solution that involves a solar thermal-driven cooling system capable of providing cooling, heating, and energy storage simultaneously. This method is particularly well-suited for using solar thermal energy since it enables thermochemical storage within the system itself. By implementing this approach, the amount of net electricity generated by wind turbines will be significantly increased, resulting in a much shorter main energy rate of return due to the higher net power output.

Estimating the Crop Acreage of Menthol Mint Crop from Remote Sensing Satellite Imagery Using ANN

Acreage estimates are crucial for forecasting menthol mint acreage, as crop output figures fluctuate from year to year in response to fluctuations in the market price of menthol mint oil. Thus, there are yearly fluctuations in the maximum price that farmers can obtain. Since low production arises from low rates, and high production results from high prices, these acreage estimate studies may be useful in lowering uncertainty regarding menthol mints’ output. The widespread adoption of remote sensing technologies for assessing crop acreage at both the national and international levels can be attributed to their low cost, ease of use, and flexibility. The extent of an area planted with menthol mint in the Vishakhapatnam district of Andhra Pradesh, India, was estimated using Sentinel-2A satellite data for that year. After conducting a comprehensive ground survey, the area of the menthol mint crop was estimated using an adaptive maximum chance-type set of rules for taluk-level statistics. According to the research, the Bheemunipatnam taluk in the Vishakhapatnam district was the most productive in growing menthol mint. Using customer and manufacturer accuracies of 89.13% and 87.23%, along with the average accuracy (90.67%) and kappa rate (0.9), the total acreage of menthol mint crop in the study region was estimated to be around 58,000,284.70 ha (0.844). A further aim in this study was to estimate the acreage planted with early and late menthol mint. Around 26,123.50 ha and 29,911.40 ha were found to be home to early menthol mint and late menthol mint, respectively. This method shows promise for early- and late-stage crop acreage assessment of menthol mint using a localised degree of precision.

Analysis of Cleaner Production Performance in Manufacturing Companies Employing Artificial Neural Networks

Cleaner production has emerged as a comprehensive paradigm, aiming to reduce, or even avoid, the environmental impact in the production stage, in a broad variety of fields. However, the great number of interacting factors makes the assessment of efficiency and the identification of critical factors pose significant challenges to researchers and companies. Artificial intelligence and, particularly, artificial neural networks have proven their suitability to lead with diverse multi-variable problems, but have not yet been applied to model production systems. In this work, we employ dimensionality reduction in combination with a fully connected feed-forward multi-layer perceptron to model the relation between the input (cleaner production techniques) and output variables (cleaner production performance) and, subsequently, quantify the sensibility of the different output variables on the input variables. In particular, we consider Product Design, Production Processes, and Reuse as the input latent variables, whereas the Environmental Performance of Product, Environmental Performance of Processes, and Economic Performance comprises the output variables of our model. The results, employing data collected from a direct survey of 205 Brazilian companies, reveal that the best configuration for the ANN uses eight neurons in the hidden layer. Regarding sensitivity, the obtained results show that improving practices with poor marks leads to a higher enhancement of output figures. In particular, since reuse presents mainly low marks, it can be identified as an area for improvement, in order to increase overall performance.

Valuers' Perception on Mitigating Material Uncertainty in Property Valuation

Property valuation is the process of estimating the market price of an asset, especially one carried out by a professional valuer. The estimated price significantly affected by uncertainties in the market where the impact of these uncertainties will be reflected in the output figure, i.e., the valuation. Thus, careful consideration is essential for valuation assignment in the relevant market. The existence of recent or contemporary evidence, and the degree of trustworthiness of that evidence when determining the level of uncertainty at a specific valuation date is a requirement to minimize the level of material uncertainty in property valuation process. In this context, the main purpose of this study is to figure out valuers’ perception on best mitigation measures for material uncertainty in property valuation procedure. The population of the study are the professional valuers who engaged in property valuation in Sri Lanka; members of Institute of Valuers of Sri Lanka (IVSL) and Royal Institution of Chartered Surveyors (RICS). The sampling techniques of the study is cluster sampling and total of 270 members answered the questionnaire distributed via email. The analysis results confirmed that COVID-19 pandemic situation, valuation assumptions and clients’ influence are major contributory factors on valuation uncertainty. However, the factor extraction and rotation confirmed that only uncertainty created by the COVID-19 pandemic situation and valuation assumptions are two significant elements on material uncertainty of valuation. The findings suggest that client influence may not be seen as a threat to the emergence of material uncertainty. Furthermore, the study identifies measures such as developing a digital land registration database, defining valuation procedures as per the guidelines of respective valuation institution, use of realistic valuation assumptions, and analysing long-term market behaviour are appropriate measures for mitigating material uncertainty in property valuation.

A Coding Basis and Three-in-One Integrated Data Visualization Method 'Ana' for the Rapid Analysis of Multidimensional Omics Dataset.

With innovations and advancements in analytical instruments and computer technology, omics studies based on statistical analysis, such as phytochemical omics, oilomics/lipidomics, proteomics, metabolomics, and glycomics, are increasingly popular in the areas of food chemistry and nutrition science. However, a remaining hurdle is the labor-intensive data process because learning coding skills and software operations are usually time-consuming for researchers without coding backgrounds. A MATLAB® coding basis and three-in-one integrated method, 'Ana', was created for data visualizations and statistical analysis in this work. The program loaded and analyzed an omics dataset from an Excel® file with 7 samples * 22 compounds as an example, and output six figures for three types of data visualization, including a 3D heatmap, heatmap hierarchical clustering analysis, and principal component analysis (PCA), in 18 s on a personal computer (PC) with a Windows 10 system and in 20 s on a Mac with a MacOS Monterey system. The code is rapid and efficient to print out high-quality figures up to 150 or 300 dpi. The output figures provide enough contrast to differentiate the omics dataset by both color code and bar size adjustments per their higher or lower values, allowing the figures to be qualified for publication and presentation purposes. It provides a rapid analysis method that would liberate researchers from labor-intensive and time-consuming manual or coding basis data analysis. A coding example with proper code annotations and completed user guidance is provided for undergraduate and postgraduate students to learn coding basis statistical data analysis and to help them utilize such techniques for their future research.

Pathways to Argentina's 2050 carbon-neutrality agenda: the roles of renewable energy transition and trade globalization.

The government of Argentina has recently declared its objective of turning the nation carbon-neutral by 2050. Thus, it is essential to identify the relevant factors which can facilitate the attainment of this environmental development target. Against this backdrop, this study aims to evaluate the impacts of renewable electricity output, trade globalization, economic growth, financial development, urbanization, and technological innovation on sectoral carbon dioxide emissions in Argentina during the 1971-2014 period. The findings, overall, suggest that enhancing renewable electricity output share in the total electricity output figure of the nation helps to curb carbon dioxide emissions generated from Argentina's energy, manufacturing and industry, residential and commercial buildings, and transportation sectors. Contrarily, greater trade globalization is evidenced to boost carbon dioxide emissions in almost all the aforementioned economic sectors. Besides, the findings also validate the existence of the carbon dioxide emission-induced environmental Kuznets curve hypothesis for all four sectors. In addition, financial development and urbanization are also evidenced to exert carbon dioxide emission-stimulating impacts, while technological innovation is witnessed to be necessary for curbing sector-based carbon dioxide emissionsin Argentina. Accordingly, to decarbonize the economy, this study recommends the government of Argentina to adopt necessary policies for fostering renewable energy transition within the electricity sector, greening the trade globalization strategies, achieving environmentally sustainable economic growth, developing the financial sector by introducing green financial schemes, planning sustainable urbanization, and financing technological development-oriented projects.

A College Teacher’s Introduction to Jupyter Notebooks

This introduction to Jupyter Notebooks (JNBs) is an outcome of a year of learning, creating, and classroom testing JNBs in a variety of settings: a sabbatical with an urban violence reduction organization; an after school distance learning program for low to middle income high school students in Chicago; a general education computer-lab based math course; and finally two upper division courses for applied math majors at a liberal arts college. The examples include line graphs, histograms, and a pie chart of violent crime data created for a community organization, a high school/general education lab on computer music, a visualization of volumes computable by triple integrals, and creation of a .gif animation of a numerical solution to a 2-Dimensional PDE. In addition to executing and displaying output of computer code, JNBs can import data from files and external websites, interpret equations written in LaTeX, display PowerPoints in pdf format, and show videos posted on other websites. JNBs can also save output data, figures, and animations to files in a variety of formats. At a general education level, JNBs can enrich student learning experience by helping students overcome math anxiety through inclusion of the arts. At the undergraduate math major level, JNBs can create interesting visualizations/animations and support service learning projects. The appendix explains how to get started using JNBs. The learning curve for creating the JNBs described in this article is not that steep, and the low-hanging fruit from using JNBs for a wide-range of teaching contexts and for community service learning projects is plentiful.

Циклотронные защитные устройства СВЧ-диапазона для приемников РЛС

Brief overview of the latest developments of microwave cyclotron protective devices, their functioning and parameters is given. It is noted that these devices have a number of important advantages over other types of protective devices: they are autonomous, provide no peak of microwave power leaking to the output, frequency filtering and low noise figure (0.7-1.2 dB). The upper limit of the linearity of cyclotron protective devices in the signal transmission mode when the transmission coefficient is compressed by 1 dB is ~ 1 mW. The devices can operate with an input pulse power of up to 10 kW or more, while the attenuation of the input power in the protection mode is more than 60-80 dB. The recovery time of parameters after the end of a powerful input pulse is 10-20 ns. For devices of the 3-cm wavelength range, experimental data are given on the recovery time, the upper limit of linearity, attenuation of the input power in the protection mode, and filtration characteristics.

Revising growth history: new estimates of GDP for Norway, 1816–2019†

AbstractThis article offers revised historical national accounts for Norway for the period 1816–2019. The revisions have been carried out on both the production side and the expenditure side. The major difference is that the new series include a significantly broader set of data than the previous series. This makes it possible to calculate GDP for a wider set of industries with more detailed and precise data, in a way that is more in line with modern national accounting methodology. The new series deviate at some points from the previous series. In particular, they show higher growth rates during the last half of the nineteenth century until 1906 and lower growth rates from 1918 to 1930. This is basically due to improved quality of deflators and partly due to the extended use of a double deflation technique. The revised output and input figures play a less important role. In light of the revised series, parts of Norway's economic growth and development history should be revised. Comparisons with Denmark and Sweden reveal a relatively higher level of GDP per capita for Norway during the second half of the nineteenth century than according to the previous series.

Impacts of Ground Slope on Main Performance Figures of Solar Chimney Power Plants: A Comprehensive CFD Research with Experimental Validation

Geometric parameters in solar chimney power plants are numerically optimised for the purpose of better power output figures. Several parameters have been investigated in the pilot plant such as chimney height and diameter, collector diameter and slope, and slenderness. However, ground slope has not been studied to date despite its perspicuous impact on turbulent flow. In this study, the impacts of the different slope angles of the ground, where the solar radiation is absorbed through the collector, on the main performance parameters of the system are numerically analysed through a reliable CFD software ANSYS FLUENT. By considering the actual geometric figures of the pilot plant, a 3D model is constructed through DO (discrete ordinates) solar ray tracing algorithm and RNG k-ε turbulence model. For the solar intensity of 1000 W/m2, the maximum velocity inside the system is found to be 14.2 m/s, which is in good accordance with the experimental data of 15.0 m/s. Starting from 5 m inside the collector, the chimney inlet heights are reconfigured 0.209, 0.419, 0.625, 0.838, and 1.04 m, respectively, and when the ground slope is 0.1, 0.2, 0.3, 0.4, and 0.5°, the changes in the performance output of the system are investigated. For the reference case which refers to the horizontal ground, the maximum air velocity is determined to be 14.2 m/s and the power output is 54.3 kW. However, when the ground slope is made 0.5°, it is observed that the maximum velocity increases by 37% to 19.51 m/s, and the power output is enhanced to 63.95 kW with a rise of 17.7%. Sloping ground is found a key solution to improve the turbulent effects inside the plant, thus to enhance the electrical power output.

Analysis of Sales Predictions from the Point of View of the Increase in Daily Newspaper Sales

This study aims at Analysis of Sales Predictions from the Point of View of the Increase in Daily Newspaper Sales. The methods of this research is gather evidence through a variety of approaches, including library analysis and field research. This paper makes use of both qualitative and quantitative evidence. Primary data sources, namely data collected from respondents or direct interviews with business executives, specifically about marketing strategies, especially those relating to promotion. Secondary evidence. Promotional operations are carried out optimally, which is facilitated by sufficient costs, especially in potential areas. Apart from repeat buyers, the organization offers its goods in store, which enables the company to monitor its output figures accurately and seamlessly.

Comparing doppler-echocardiography and thermodilution for cardiac output measurements in resuscitated out-of-hospital cardiac arrest patients undergoing targeted temperature management

Abstract Funding Acknowledgements Type of funding sources: None. Background Cardiovascular dysfunction is common after out-of-hospital cardiac arrest (OHCA). Cardiac output measurements can be used to guide treatment during post-resuscitation care and echocardiography allows noninvasive cardiac output estimation. Purpose The aim of the present study was to compare Doppler echocardiography (doppler_CO) with thermodilution using pulmonary artery catheters (PAC_CO) for cardiac output estimation in a large and consecutively included cohort of comatose OHCA-patients undergoing targeted temperature management (TTM). Methods Single-center substudy of 171 patients included in the TTM-trial randomly assigned to 33 or 36 degrees C for 24 hours after OHCA. We measured PAC_CO and doppler_CO simultaneously shortly after admission and again after 24 hours. Measurements and Main Results We excluded 19 (11%) patients without PAC-measurement and 31 (18%) without doppler-measurements resulting in 120 paired measurements at admission. Patients were 61 (±11) years old, 86% were men and 91% had a witnessed OHCA. At ICU-admission, PAC_CO was 4.81 (±1.81) L/min. and doppler_CO was 3.74 (±1.38) L/min., with a mean bias of 1.07 (±1.65) L/min (with 95% limits of agreement of –2.16 to 4.04) L/min. Examining the Bland-Altman plot, precision fell with higher cardiac output (figure). A statistically significant, but moderate correlation was found between doppler_CO and PAC_CO at admission (r = 0.49), p < 0.0001). After 24 hours, PAC_CO was 4.63 (±1.38) L/min. and doppler_CO was 3.61 (±1.14) L/min, with a mean bias of 0.96 L/min. Assessing the change from admission to 24 hours, PAC_CO decreased averagely -0.12 (±2.22) L/min. and doppler_CO decreased -0.19 (±1.91) L/min. The changes from admission to 24 hours correlated between doppler_CO and PAC_CO (r = 0.55), p < 0.0001) with a mean bias of the changes of 0.07 L/min, with 95% limits of agreement of –3.76 to 3.91 L/min. Conclusions Changes in cardiac output during TTM may be evaluated with Doppler echocardiography with little mean bias compared to changes in CO measured with thermodilution, but relatively large changes are needed in the individual patient before it can be considered as real. Abstract Figure. Comparing Doppler vs. thermodilution