Information Production Research Articles

Evolving Social Media Strategies in Local Journalism: Experiences from Argentine Patagonia

Studies on journalistic work and production on social media typically focus on large media outlets in developed countries. In this article, we shift the lens to a peripheral area of a peripheral country: Argentine Patagonia. Our objective was to analyse journalistic production on Instagram, Facebook, and Twitter in the eight most-followed local and regional news media outlets. We analysed the narratives, the extent to which they apply transmedia journalism, and how they have evolved compared to studies from 2021. We also conducted structured interviews with social media managers to gain insight into their professional practices. We conclude that, 15 years since the creation of the first profiles, promoting website content remains the primary goal of North Patagonian media networks. Since 2021, there have been more frequent updates but less native production, especially on Facebook and Twitter. Despite the shortage of staff and precarious working conditions, some news media outlets have been able to innovate on Instagram, introducing a variety of multimedia formats, a more conversational tone, diverse update rhythms, adapted content, and even specific content that is organised into sections. Information production for the platforms has been integrated into journalistic routines even when public interaction with the audience remains very limited.

Quantifying antimicrobial consumption in the Chilean salmon industry using standardized metrics and indicators: The case of florfenicol and oxytetracycline

The adoption of standardized metrics and indicators of antimicrobial use (AMU) in the food animal industry is essential for the success of programs aimed at promoting the responsible and judicious use of antimicrobials in this activity. The objective of this study was to introduce the use of standardized AMU metrics and indicators to quantify the use of florfenicol and oxytetracycline in the Chilean salmon industry, and in this way evaluate the feasibility of their use given the type of health and production information currently managed by the National Fisheries and Aquaculture Service (SERNAPESCA), the Chilean agency responsible for regulating aquaculture in Chile. The data available from SERNAPESCA allowed the construction and evaluation of the most data-demanding AMU metrics and indicators. Consequently, the use of florfenicol and oxytetracycline administered by oral and parenteral routes was quantified using the treatment incidence based on both animal defined daily dose (TIDDDvet) and animal used daily dose (TIUDDA). To that end, the study included information from 1320 closed production cycles from farms rearing Atlantic salmon, coho salmon and rainbow trout that were active between January 2017 and December 2021. By applying standardized AMU metrics and indicators, we were able to determine that the median of TIDDDvet for florfenicol was 75.1 (80 % range, 20.0–158.0) DDDvet per ton-year at risk for oral procedures and 0.36 (80 % range, 0.07–1.19) DDDvet per ton-year at risk for parenteral procedures. For oxytetracycline, the median TIDDDvet was 3.09 (80 % range, 0.74–42.8) and 0.47 (80 % range, 0.09–1.68) DDDvet per ton-year at risk for oral and parenteral procedures, respectively. The median TIUDDA for treatments with florfenicol was 45.6 (80 % range, 10.9–96.5) UDDA per ton-year at risk for oral treatments and 0.28 (80 % range, 0.05–0.80) UDDA per ton-year at risk for parenteral treatments. For oxytetracycline, the median TIUDDA was 2.63 (80 % range, 0.61–28.2) UDDA per ton-year at risk for oral treatments and 0.41 (80 % range, 0.08–1.29) UDDA per ton-year at risk for parenteral treatments. This study demonstrates that it is feasible to move from traditional AMU metrics and indicators to standardized ones in the Chilean salmon industry. This is possible because the competent authority requires salmon farms to report detailed health and production information at a high frequency. The use of standardized AMU metrics and indicators can help the authority to have a more comprehensive view of the antimicrobial use in the Chilean salmon industry.

Image inpainting algorithm based on inference attention module and two-stage network

Current image inpainting techniques often yield distorted structures or blurred textures that clash with the surrounding context, particularly when addressing extensive missing regions or highly textured images. These methods often struggle to reconstruct realistic and coherent image structures. To address this challenge, we introduce a two-stage network image restoration approach that leverages an inferential attention mechanism. In the first stage, an edge generation network is employed to produce plausible phantom edge information. Subsequently, an image complementation network is utilized to complete the image restoration process. To enhance the visual realism and restoration accuracy of the generated images, we incorporate an inferential attention mechanism within the image complementation network. This mechanism effectively mitigates inconsistencies in the generated features, leading to the production of more meaningful and effective information. We evaluate our proposed method on benchmark datasets, including Places2 dataset, CelebFaces Attributes dataset, and Paris StreetView dataset. The experimental results can demonstrate that the proposed method achieves better Structural Similarity Index and Peak Signal-to-noise Ratio than others. These metrics indicate superior performance compared to existing image inpainting methods, delivering higher image inpainting accuracy and more realistic image reconstruction effect.

Forecasting of Inland Fish Production: Case of Catla (<em>Catla catla</em>) and Gift Tilapia (<em>Oreochromis niloticus</em>) Production in Udawalawa Reservoir in Sabaragamuwa Province, Sri Lanka

This study focused on assessing and forecasting Catla (Catla catla) and Tilapia (Oreochromis niloticus) production in the Udawalawe reservoir in Sri Lanka using an 11-year time series data from 2010 to 2021. The relevant secondary data were collected from the National Aquaculture Development Authority of Sri Lanka (NAQDA). Unit root tests, Dickey-Fuller tests, and Seasonal Auto Regressive Integrated Moving Average (SARIMA) models and trend analysis were applied for the data analyses. According to the results, stationarity behaviour was observed in both Catla and Tilapia production information series. Hence, SARIMA (2,2,1) (1,0,1)12 is the appropriate empirical model for forecasting Catla production. Furthermore, the maximum average landings of Catla production were observed in the March-June time period. SARIMA (1,0,1) (1,1,1)12 was indicated as the most suitable model to forecast Tilapia production in the reservoir. The maximum average of Tilapia production was also observed in the March-June period. Both the SARIMA model and trend analysis gave approximately equal production information regarding Catla and Tilapia. Thus, these findings showed that the SARIMA model has more accuracy than trend analysis when analysing the time series information for short durations. However, when the duration becomes larger, forecasting is not suitable using the SARIMA model, and trend analysis gives a clear view up to a certain level. Both Catla and Tilapia production exhibited significant changing patterns and multiple seasonalities. Thus, trend analysis gives valuable insights than SARIMA model in long term predictions in case of this study. These findings are highly important for enhancing fish production in this reservoir, as they predict future fish catches under the current reservoir conditions.

Building a web-based Comprehensive School Portal System Using the CodeIgniter Framework

With the various advantages and conveniences that the internet can provide, various fields of human activity have begun to use internet technology to help facilitate the activities they undertake. Likewise with the education sector in managing its administration. The web is one of the internet technologies that is widely used to facilitate monitoring of school activities because it can be accessed easily anywhere and at any time, from school facilities to school activities. Through the use of a web data system, problems involving redundancy of student information, insynchronization between existing information and slow production of information can be overcome. By designing an information system or web-based portal, you can increase performance effectiveness.

Modelling heat stress effects on milk production traits in Tunisian Holsteins using a random regression approach.

This study investigated the impact of temperature and humidity on milk production traits in Tunisian dairy cows, analysing population-level trends and individual cow responses using various modelling techniques and heat stress (HS) indices. Two distinct datasets were used for this purpose: the first included 551,139; 331,654 and 302,396 test-day records for milk, fat and protein yields, respectively. The second supplemented the production information with daily average (THIavg) and maximum (THImax) temperature-humidity index (THI) data. Three main parts of analyses were conducted simultaneously: classical least squares, identification of HS thresholds and associated production losses and assessment of individual cow responses using random regression models (RRM) fitting various continuous functions that include/exclude individual effects. The best model, determined by goodness-of-fit measurements, was a cubic polynomial function that accounted for individual variation and THIavg as a heat load measure. HS thresholds were established at THIavg/THImax of 70/74 for milk yield, 50/55 for fat percentage, 59/66 for protein percentage, 54/63 for fat yield and 56/66 for protein yield. According to the fitted polynomial models, daily milk production traits showed a curvilinear decline with accelerated loss rates beyond the established thermal thresholds. However, for all models and thermal indices, maximum daily production losses remained below 164 g/day, 4.4 g/day and 6.1 g/day for milk, fat and protein yields, respectively. Despite these losses, the relatively high thermal thresholds and lower associated production losses suggest that Tunisian dairy cows can tolerate high heat loads. Moreover, observed variations in response patterns indicate potential for selecting heat-tolerant individuals within this population.

On the development of criteria for determining the effectiveness of technical working groups: A case study about information processes in marine conservation and fisheries management in Belize

Use of scientific information in evidence-based decision-making is critically important in addressing coastal and ocean management concerns. In an ecosystem-based management context, ensuring that the “right” information (reliable) is available can be particularly challenging as the information often resides in different organizations with different management mandates. Many governmental and intergovernmental organizations have used a range of approaches, including technical advisory committees and working groups, to facilitate multidisciplinary input into the development of appropriate policies and management practices. This study examined the roles of multiple stakeholders participating in technical working groups that assist in decision-making for marine fisheries management in Belize, a coastal country in Central America. Through interviews with members of three working groups – the Spawning Aggregation Working Group, the Managed Access Working Group, and the National Hicatee Conservation and Monitoring Network – and decision-makers in the Belize Fisheries Department, information production processes and pathways for information uptake into policy were investigated. Major characteristics of communication at the science-policy interface associated with each working group were revealed. Important communication enablers and barriers were identified related to the operation of the working groups, such as membership commitment and resource availability, which influenced knowledge exchange within and outside the groups. Based on the results, a set of requirements for the creation and operation of effective working groups was formulated with regard to requisite inputs, the operational processes, and the types and uses of the information outputs of the groups. These requirements serve as a foundation for development of indicators of the effectiveness of working groups in environmental management contexts that support communication and decision-making at science-policy interfaces.

Informed Voting

Abstract Information production by shareholders is essential for proxy voting to produce efficient outcomes. We propose a stock return-based measure to capture informed voting. Our measure, the vote alpha, quantifies the extent to which a shareholder votes in the direction that the market perceives as value increasing. Using data on mutual funds’ proxy voting records, we find that the vote alpha exhibits persistence. Our main result shows that the voting pattern of high vote alpha funds positively predicts long-run abnormal stock returns following contentious votes, suggesting that these funds possess information about the shareholder value implication of contentious governance proposals.

Historical structuring and technological evolution of the national geodetic network of Chile - horizontal

The Military Geographic Institute (IGM) wasset up in accordance with the Decree Law N°1.664 of the 29th of August, 1922 and is currently the official technical and permanent service of the State, in all geographic matters, in compliance with the second point of Article N.° 2 of Law N.° 15284 of 1963. Among the most important of its tasks is the mission of providing a Reference Frame in accordance with the requirements of the international standards of each epoch, for the production of geo-referenced information. The National Geodesic Network (RGN in Spanish initials) has been thereference framefor all geodesic and cartographic activities and portrayals over time. It is made up of geodesic points set up at strategic locations across and along this territory, measured and calculated by this Institute; these have plane, geographic and altitude coordinate values. Currently, the horizontal component of the SIRGAS-Chile RGN consists of a set of Continuous Operation Reference Stations (CORS), providing daily GNSS data and official coordinates for the various uses of national development.Chile, due to its special geographic situation, arising from its location and its long, narrow, and elongated territory has had to adopt, over time, various geodesic reference systems in accordance with the requirements of international organisations that support and promote geodesy. Moreover, since 1922, these reference systems have evolved due to substantial progress in technology, defining a RGN that is modern and precise at this time.

Study on the Evolution of Spatiotemporal Dynamics and Regional Differences in the Development of Digital Agriculture in China

In the current study, an index system for digital agriculture growth was constructed. The index encompasses six key dimensions, namely production, operation, service, management, sustainability, and digital information infrastructure. Data from 30 Chinese provinces between 2011 and 2020 were collected and analyzed using the entropy method, Moran index, Dagum’s Gini coefficient, and the kernel density estimate. An in-depth analysis of the development level and spatial patterns, dynamic evolution and intra- and inter-regional differences in China (i.e., eastern, western, and central regions) was conducted. From the result, an overall growing trend of digital agriculture in China was observed, with a relatively more advanced status in the eastern region. A positive spatial dependence, showing a “high-high” and “low-low” (HH, LL) trend, was obtained. However, the regional spatial dependence has generally weakened since 2019. The intra-regional differences were large in western and eastern areas, while the greatest inter-regional differences were unveiled between western and eastern regions. The country’s overall differences mainly stemmed from inter-regional differences. The overall kernel density curves moved to the right over time, showing a trend of a gradual rise in digital agricultural growth, accompanied by a polarization pattern in the western region.

Environmental factors and management practices associated with beef cattle carcass quality in the mid-west of Brazil.

The "Precoce MS" program, established by the Brazilian government in Mato Grosso do Sul in 2017, aims to encourage beef producers to harvest animals at younger ages to enhance carcass quality. About 40% of the beef produced in the state now comes from this program, which offers tax refunds ranging from 49% to 67% based on carcass classification and production system. Despite the program success, with participants delivering younger animals (with a maximum of 4 incisors), there remains significant variability in carcass quality. This paper investigates management practices and environmental factors affecting farm performance regarding carcass quality. Data from all animals harvested between the beginning of 2017 and the end of 2018 were analyzed, totaling 1,107 million animals from 1,470 farms. Farm performance was assessed based on the percentage of animals achieving grades "AAA" and "AA." Each batch of harvested cattle from each farm was categorized into two groups: high farm performance (HFP, with more than 50% of animals classified as "AAA" or "AA") and low farm performance (LFP, with less than 50% classified as such). A predictive logistic model was developed to forecast farm performance (FP) using 14 continuous and 15 discrete pre-selected variables. The most effective model, obtained through backward stepwise variable selection, had an R 2 of 0.18, accuracy of 71.5%, and AUC of 0.715. Key predictors included animal category, production system type, carcass weight, individual identification, traceability system, presence of a feed plant, location, and the Normalized Difference Vegetation Index (NDVI) from the 12-mo average before harvest. Developing predictive models of carcass quality by integrating data from commercial farms with other sources of information (animal, production system, and environment) can improve our understanding of production systems, optimize resource allocation, and advance sustainable animal production. Additionally, they offer valuable insights for designing and implementing better sectorial, social, and environmental policies by public administrations, not only in Brazil but also in other tropical and subtropical regions worldwide.

Local IPOs and Household Stock Market Participation

Abstract The decrease in companies going public has received widespread attention, and the associated costs are widely debated. We document high local IPO activity leads to increases in stock market participation of 5–6%. This is striking given that such participation represents a key factor toward building wealth. Local IPOs increase both households’ propensity to own stock and their percent equity holdings. The attention channel drives effects: local IPOs attract attention to the market, through increased information production and publicity. The wealth channel has little influence, consistent with local IPOs not generating wealth shocks for most households.

Assessing social capital and its impact on economic performance: A comparative study of members and non-members of farmer producer companies in India

Farmer producer companies (FPCs), modern farmer collectives registered under India’s Companies Act, play a crucial role in providing core services like input supply, marketing, technical, and financial support, as well as auxiliary services such as social capital and consultancy, which are linked to higher economic performance and innovation. The study analyzes the levels of social capital among members and non-members of FPCs and their relationship to the economic performance of their members. The data on social capital were collected from 20 FPCs (292 members and 77 non-members) from Maharashtra state of India. Unpaired student T-tests and Mann-Whitney tests were performed to compare the levels of social capital among the members and non-members. OLS regression was performed to understand the difference in social capital and its effect on economic performance. The results reveal that all the indicators of social capital were significantly higher for the members (Mean = 4.27) than for non-members (Mean = 3.14). The social capital indicators related to membership and participation in groups (p-value < 0.10) and the sharing of production and other information (p-value < 0.01) positively affected economic performance. Higher levels of education (p-value < 0.05) and frequent contact with members (p-value < 0.01) positively affected, whereas higher landholding (p-value < 0.10) and years of membership (p-value < 0.01) negatively affected the economic performance of members. As the Indian government plans to add 10,000 FPCs in the next three years, the strategy to increase the social capital of FPCs may enhance the overall resilience and sustainability of rural economies.

AN ONTOLOGICAL MODEL OF WORKERS’ REMUNERATION WITHIN THE CONTEXT OF AN ENTERPRISE DIGITAL TRANSFORMATION

The article is devoted to issues related to the modeling of the business process of forming wages for manufacturing enterprise workers in the context of digital transformation. The importance of modeling the business process of paying workers is shown, on which the efficiency of the production process largely depends, and, accordingly, the efficiency of the enterprise as a whole. A model for the formation of workers’ wages has been developed, including information, technological and organizational aspects. An objective assessment of the work of workers leads to increased motivation, high-performance and high-quality work. The application of a balanced scorecard system is shown, which makes it possible to move from strategy to operational planning, taking into account the mutual influence of four modules – financial, production, consumer and innovation. Together, these modules have a significant impact on improving the efficiency of the entire enterprise. However, without digital transformation, it is impossible to consider the innovative activity of an enterprise. In addition, it is only in the conditions of digital information that it is possible to abandon the poorly documented distribution of shift-daily tasks to workers and promptly monitor their implementation. The development of a methodology for paying workers leads to the fact that having operational results of production activities, it is possible to objectively evaluate the work of workers, monitor their activities and determine the amount of encouragement not only once a month, but also daily. The implementation of this technique allows you to activate workers to perform shift-daily tasks within the time limits set by the plan and in the prescribed range, increase production discipline, encourage economical use of material, energy and other resources. In addition, production information is promptly displayed in the management system, which allows managers to have an up-to-date picture of the production plan implementation.

Automated optimization for steel mold of precast components based on multi-objective evolutionary algorithm

Designing an economical and reliable steel mold for precast concrete (PC) components can accelerate the promotion of prefabricated buildings. This paper presents an automated design framework for a steel mold of PC components to generate manufacturing information, including dimensions and location of each plate. The profile and dimensions of PC components are extracted from the shop drawings, and a finite element model of the steel mold is established and initialized. A multi-objective optimization model considering material usage and manufacturing convenience is developed to determine the geometry and quantity of plates in steel molds. The non-dominated sorting genetic algorithm II (NSGA-II) is applied to obtain a Pareto solution set for steel mold design. The production information in DXF format can be automatically generated by parsing Industry Foundation Classes (IFC) model. The cost-effectivity and practicality of the proposed framework were verified via the design case for a real PC stair mold.

Supporting Successful Multicultural Societies Education is Key to National Progress

Successful societies depend on everyone signing up to core values and actions. In multicultural settings the acceptance of differences in the way people operate has led to rules flouted, bringing chaos and conflict. Core to successful relationships are narrative language abilities, which enable creative as well as critical thinking to broaden and improve information processing and production. Critical, linear thinking analyses a situation, based on facts and data, whilst the creative, lateral approach develops new ideas and solutions. A study shows how language and thinking competencies have declined to hinder interactions between people - vital for new interdisciplinary job-roles now that technology is taking over routines. Focus on developing direct talk, to assist effective collaboration and learning is advocated. Training is required to appreciate language dual function to develop effectively, but also stratify people to potentially add to inequality if not aware. Most learning problems, at all student levels, are rooted in low levels of language, thinking and communication, which receive limited attention in teaching and training. The article looks at the background to thinking and expression and considers a route to more successful multicultural societies.

Information needs for transparency in blockchain-enabled sustainable food supply chains

The growing demand for transparency in sustainable food production creates a challenge for supply chains to meet the diverse information needs of stakeholders. This research addresses this challenge by identifying and prioritising information needs within sustainable food supply chains. Employing a mixed-methods approach, the study identified 14 information needs, categorised them into three clusters: a) product and quality details information, b) production and processing information, and c) sustainability information, and prioritised the information needs. Experts highly prioritised information needs on quality and safety, followed by product origin and nutrition/ingredients. The research suggests that blockchain technology can play a role in supporting consumer decision-making. These findings can inform the development of information-sharing systems that enhance transparency and support consumer decision-making in sustainable food supply chains.

Photometric and numerical study of comet C/2021 A1 (Leonard) near its estimated disruption date

Initially on an elliptical orbit, C/2021 A1 experimented significant changes in its orbital configuration due to planetary perturbations upon entering the planetary region. Images of the comet C/2021 A1 (Leonard) obtained in March 2022 allow to estimate that its disintegration occurred in December 2021. The aim of this paper is to analyze the comet’s dust behavior during the period when its disintegration is presumed to have commenced, so a series of images of this comet on the broadband B, V, and R filters were taken on December 21 and 23, 2021 with the 0.6 m Helen Sawyer Hogg (HSH) telescope at the Complejo Astronómico El Leoncito (CASLEO) to do a morphological, photometric, and numerical analysis of this comet. Analysis of the magnitudes and dust production rate suggests a significant increase in activity on December 21 compared to two days later, indicating a potential outburst. Digital filters were applied to enhance contrast in the cometary images, revealing two active regions on opposite sides of the nucleus. Additionally, the A(0°)fρ parameter was obtained for this comet. Finally, to gain deeper insights into Leonard’s dust behavior, observations were fitted to a newly developed theoretical model for studying dust comas. Combined with photometric data and gas production information from the literature, the analysis suggests that the comet’s activity on December 21, 2021, may mark the beginning of its disintegration.

Underwriter incentives and IPO pricing

We examine the impact of incentive fees paid to IPO underwriters at issuers' discretion on IPO pricing and short-term performance. We expect that better-incentivized underwriters produce more information required for IPO pricing reducing underwriters' reliance on investors' information production which requires compensation through IPO underpricing. Using a novel dataset, we find that incentive compensation mitigates the partial-adjustment phenomenon. IPOs with stronger incentives have more informative price ranges, higher price revisions, longer road shows and lower initial returns largely due to interaction effects between underwriters' incentives and their information-production capabilities. Using a battery of tests and addressing endogeneity, our results remain robust.

RESOURCE USE EFFICIENCY IN IMPROVE HYBRID TOMATO PRODUCTION IN AKWA IBOM STATE, SOUTHERN REGION OF NIGERIA

The study estimates the technical efficiency of tomato farmers in Akwa Ibom State in the Southern Region of Nigeria. One hundred and twenty tomato farmers were randomly selected using multistage sampling technique. Descriptive statistics and maximum likelihood estimation of the stochastic Cobb- Douglas production function were used to analyze the collected data. The results of socioeconomic characteristics showed that male farmers dominated tomato cultivation in the region. The majority of farmers were relatively young, educated, and had moderate household size but low social capital accumulation. The empirical results identified seeds, manure, fertilizer, farm size, hired labour and family labour as significant inputs in tomato production. The study found decreasing return to scale in tomato production in the region. An average technical efficiency index of 0.797 was estimated, which corresponds to an efficiency gap of approximately 20.30%. Determinants of technical efficiency were: farming experience, socialization, education, training, farm income, household size and non-farm income. To increase the technical efficiency of tomato farmers, it is recommended that they should be encouraged to join existing cooperatives to obtain production information that would improve their technical efficiency; and providing formal education, especially in rural areas, would encourage tomato farmers to update their knowledge and acquire more skills necessary for efficient management of farm resources.