Production Output Research Articles

INFLUENCE OF PRODUCTION OF PRIMARY PRODUCTS ON THE RATE OF INFLATION IN THE REPUBLIC OF SERBIA

The optimization of production processes leads to an increase in the volume of output from the primary sector, as an instrument to protect the population from crossing the border of extreme poverty. The Republic of Serbia is a traditional producer of primary products, as evidenced by the realized surplus in the net export of agricultural crops. In the period after global financial crisis, the Republic of Serbia achieved an above-average inflation rate growth, compared to the countries of the European Union. In this research, we detect a significant participation of products from agriculture, forestry, fishing, mining to reduce the volatility of product prices. The purpose of the research is to prove the causal relationship between the rate of inflation and the volume of production primary products. The methodological part was carried out through the evaluation of the model using econometric methods. The conclusion indicates a high correlation between the production of primary outputs and the rate of inflation in the Serbian economy.

Innovative and efficient integrations of desalination plants coupled absorption, adsorption, and humidification-dehumidification desalination units employing external heat recovery techniques

Thermal desalination technologies have been developed recently to solve some pressing problems, such as high energy expenditure, increasing fuel costs, and environmental problems related to conventional plants. However, these technologies still need to be enhanced in terms of water production and gain output ratio (GOR). This paper presents innovative and efficient combined thermal desalination plants consisting of absorption (ABDS), adsorption (ADDS), and humidification-dehumidification (HDH) desalination units to enhance energy utilization, water production, and overall system performance. Four innovative combined desalination plants employing different external heat recovery scenarios are presented and compared. The result from each scenario is evaluated and compared with those of the standalone ABDS and with other studies found in the literature at the same heat source temperatures. The heat source is mainly utilized to drive the ABDS plant. The ADDS and HDH are driven by the heat rejection from the ABDS components with different external heat recovery scenarios. Results illustrated that the maximum freshwater production generated from the proposed scenarios ranges between 1.57 and 2.94 m3.day−1 with a GOR of between 1.38 and 1.75 at 120 °C. Raising heat source temperatures from 55 to 120 °C decreased the improvement in the water productivity from 618.5 to 224 % and decreased the enhancement in the GOR from 222.8 to 99 %. In scenarios where the ADDS and HDH are driven by the heat rejection from the absorption and condensation process of the ABDS, the maximum freshwater production results from the ABDS unit. On the other hand, in scenarios where the ADDS and HDH are driven by the outlet hot water from the ABDS-generator, the maximum freshwater production is obtained from the HDH unit. The finding provided that the proposed innovative scenarios have an effective improvement in overall system performance indicators.

Unleashing Economic Potential: Enhancing Cassava Production Efficiency in Nigeria

Purpose: This study is aimed at determining the economic efficiency of Manihot esculenta Crantz (Cassava) production in Nigeria’s Delta State. The study offers a detailed analysis of how socio-economic characteristics influence production output across both early and late farming seasons. Design/ Methodology/ Approach: This study employed a multi-stage random sampling approach in selecting a diverse cohort of 500 cassava farmers engaged in both early and late-season cultivation. Through rigorous personal interviews, primary data was gathered that was both comprehensive and insightful. Advanced parametric statistics and the Cobb-Douglas stochastic frontier function were used for the analysis. Findings: The mean economic efficiency scores were determined to be 0.63 for early-season farms, 0.78 for late-season farms, and 0.76 when considering all farms collectively. The output elasticities of material inputs, labour, and land were found to be 0.42, 0.61, and 0.05, respectively for all farms. For early-season farms, these values were 0.36, 0.68, and 0.04, whereas, for late-season farms, they were 0.31, 0.7, and 0.03. Research Limitation/Implications: This work concentrated on Cassava production efficiency within and around Nigeria’s Delta area. Practical Implication: Understanding the socio-economic factors that influence production during different seasons can help in designing strategies that maximize output in both early and late farming seasons. Social Implication: This study would help agricultural development economists and policy-makers in addressing the economic problems of Cassava farmers both present and future generations. Originality/Value: By examining both early and late farming seasons, the study provides a comprehensive understanding of how socio-economic factors vary across different agricultural cycles. This dual-season approach is relatively rare and offers more detailed insights into the dynamics of cassava production throughout the year.

Effects of exercise training on cardiac output in subjects with heart failure with preserved ejection fraction (HFpEF) — a protocol for a systematic review and meta-analysis

BackgroundPatients with heart failure with preserved ejection fraction (HFpEF) commonly experience exercise intolerance, resulting in reduced cardiorespiratory fitness. This is characterised by a decreased maximal oxygen uptake (V̇O2peak), which is determined by the product of cardiac output (CO) and arteriovenous oxygen difference (a-vDO2). While exercise training has been shown to improve V̇O2peak in HFpEF patients, the effects on CO remain unclear. The aim of this study is to systematically review and analyse the current evidence on the effects of supervised exercise training on CO in patients with HFpEF.MethodsWe will systematically search for literature describing the effects of supervised exercise training on CO in patients with HFpEF. All eligible studies published before 30 June 2023 in the following electronic databases will be included: MEDLINE (Ovid), Embase (Ovid), SPORTDiscus (EBSCOhost), and CENTRAL (Cochrane Library). Effect sizes will be extracted for CO before and after a supervised exercise training intervention at rest and maximal exercise. Mass of heterogeneity (I2) will be calculated, and either fixed-effect models or random-effect models will be used for meta-analysis. To detect a potential publication bias, funnel plot analyses will be performed.DiscussionWhile several studies have reported a positive effect of supervised exercise training on cardiorespiratory fitness, attempts to assess the underlying determinants of V̇O2peak, CO, and a-vDO2 are much scarcer, especially in patients with HFpEF. From a physiological perspective, measuring CO before and after supervised exercise training seems to be a reasonable way to accurately operationalise a potential improvement in cardiac function.Systematic review registrationPROSPERO CRD42022361485.

Assessing the Environmental Performance of Agricultural Production Using a Parametric Approach: An Application for Crop Producers in Ukraine

ABSTRACT Agriculture is characterized not only by the production of desirable outputs but also by generating environmental pressures. This article emphasizes the necessity of accounting for “bad” outputs when assessing the performance of agricultural producers. It provides a first attempt to empirically evaluate the environmental performance of crop producers in Ukraine employing farm-level panel data. Our results suggest that the average environmental efficiency for crop producers in Ukraine was 0.84 over the period 2017–2019, meaning a reasonable scope exists for farmers to improve their environmental performance and contribute to meeting carbon reduction targets, as well as help achieve a green postwar economic recovery.

Development of a comprehensive environmental guidance and sustainability assessment for different organic fraction of municipal solid waste-to-biofuel scenarios based on life cycle analysis

The environmental impact assessment of organic fraction of municipal solid waste (OF/MSW)-to-biofuel structures is essential prior to scaling them up to identify worrisome impacts on ecosystems, resources, human health, and climate. The current article aims to address a sustainable and comprehensive guide for analyzing the environmental impacts (based on the life cycle analysis (LCA)) of different OF/MSW-to-biofuel structures. To analyze different structures, three pre-treatment procedures (namely, hot water/acetone organosolv/acid), two different hydrolysis treatment ways (acidic/enzymatic), and different fermentation alternative methods (ethanolic/acetone-ethanol-butanol fermentations) were considered. The findings of the research indicated that scenarios based on acetone-ethanol-butanol fermentation cannot address a favorable environmental performance (due to the insufficiency of the avoided effects of the output products to compensate the environmental burdens caused by acetone pre-treatment). In contrast, scenarios based on ethanolic fermentation integrated with hot water or acid-based pre-treatment process can address superior environmental performances compared to scenarios based on acetone-ethanol-butanol fermentation and ethanolic (with acetone pre-treatment). Comprehensively, Scenario S-4 (as most eco-friendly Scenario) yielded the greatest net environmental savings with reductions of −857.16 potentially disappeared fraction/m2 per year, −214.3 kg CO2 equivalent per ton of/MSW, and −3.33 GJ per ton of/MSW processed.

A Necessary Shift in Design Education: From Outputs to Outcomes

AbstractTraditionally, design – and by extension design education – has focused on the creation of distinct outputs (forms, artefacts, and objects) that satisfy a specific purpose and need. Historically these needs – and often the designed outputs themselves – have been dictated not by the designer but by clients and also through established disciplinary practices. Design was broadly framed as a commercial industry, where a client needed something (a poster, a chair) and the designer provided the requested output. Design education practices grew out of a master‐apprentice approach, where students often learned by recreating idealized outputs repetitively. This didactic and skills‐acquisition approach was sufficient when design focused on distinct fields (e.g., graphic, industrial, or fashion design), specific outputs, and traditionally understood challenges. As the field of design has expanded – in the scope of practice, the complexity of challenges tackled, and the range of collaborators – there is a need to re‐examine our pedagogy. Traditional design education approaches are insufficient for the role that design needs to play in the 21st century. In this paper, I argue that a critical consideration of this re‐examination is the reframing of a central tenet of design education, which is the production of outputs. Instead, what is needed is a re‐focus considering the outcomes of design practice – the processes involved, and the effects of our design actions and artefacts. I identify seven principal and interconnected factors that drive the need for this shift in focus.

Multi-objective optimization design of a solar-powered integrated multi-generation system based on combined SCO2 Brayton cycle and ORC using machine learning approach

In order to reduce the use of fossil fuels and meet the needs of different energy products, this paper proposes an integrated multi-generation system that can produce power, cooling, and freshwater. A mathematical model is established to analyze the system performance from the perspectives of energy, exergy and economics. Different machine learning algorithms are used to develop prediction models of the system performance. By comparing the predictive performance of different machine learning models, the optimal model is obtained to replace the thermodynamic model of the proposed system to accelerate the optimization process. The results show that the backpropagation neural network (BPNN) model demonstrates the highest predictive accuracy and the lowest relative error fluctuation. When comparing the multi-objective optimization results of the BPNN model with those of the thermodynamic model, it can be observed that the results achieved through both models are very close. Furthermore, the optimization time using the BPNN model is significantly shorter than the thermodynamic model. Finally, under the conditions of solar radiation intensity of 950 W/m2, heliostat field area of 1000 m2, and heat source temperature of 838.15 K, the total product output, thermal efficiency, exergy efficiency, and levelized cost of energy at the final optimal point obtained through BPNN model-based optimization are 2.486 MW, 26.16 %, 23.64 %, and 0.105 $/kWh, respectively. The net power output, cooling capacity, and freshwater flow rate are 2.006 MW, 131.06 kW, and 8.27 m3/h, respectively.

Exergy-water nexus of a multi-energy complementary trigeneration system with different fuel mixture ratios

Complex coupling relationships of energy, exergy and water streams in multi-energy complementary systems due to different characteristics of energy flows are necessarily revealed to determine the intensities of downstream products. This paper proposes a multi-energy complementary trigeneration system driven by biomass, solar energy, and natural gas to generate cooling, heating, and power products. An exergy-water analysis approach, considering energy levels of streams, is adopted to determine the exergy and water footprint intensities per unit energy products. A life cycle assessment method is used to calculate the water footprint of biomass and natural gas as the primary energy sources. The relationship between the exergy and water footprint intensity of the system equipment and output products is presented and discussed with the mixture ratios of natural gas and biomass product gas. Furthermore, the cumulative exergy and water footprint intensity of products are analyzed under different system working conditions, such as mixture ratio of biomass and natural gas and the solar irradiance. When the same mixture volume gas fuels drive the trigeneration system, the overall exergy efficiency is 25.38 % while the efficiency including the upstream cumulative exergy destruction is only 21.93 %. The unit water footprint intensities of power and cooling products based on exergy measurement are 7.12 kg/kWh and 36.32 kg/kWh, respectively. The exergy-water footprint sensitivity of biomass and natural gas on system product intensities are implemented to consider the uncertain variables. When the mixture ratio increases from 0 to 1, the cumulative exergy destruction of system power is declined by 35.62 % under the uncertain ranges of ±50 %. Also, its water footprint is declined by 91.62 %. The proposed model provides an effective tool to reveal the exergy-water nexus and determine the intensities of multi-energy products.

Review on Current Issues related to Work Related Musculoskeletal Disorders

Work-related musculoskeletal disorders (WMSDs) are one of the most common occupational ailments in recent decades, significantly limiting people's daily lives. Globally, WMSDs are the major cause of employee pain, impairment, absenteeism, reduced productivity, and large financial costs. WRMSDs are illnesses that develop over time because of long-term occupational exposure to varying-intensity loads. WRMSDs are produced by discomfort or injury to the muscles and bones of the upper limbs because of activity. Low-extremity illnesses, like upper-limb diseases, may be just as dangerous, There is a high prevalence of neck and upper extremity problems among computer users. Upper extremities diseases were more common in older personnel. The physiological outcome of prolonged, repetitive, or repeating muscle contractions with insufficient recovery is localised muscular fatigue (WMSDs). Muscle tiredness has a substantial impact on occupational task performance, hence preventing it is crucial. The key challenge in ergonomics is to create work that avoids WMSDs while retaining high levels of output quality and productivity. Uncomfortable postures are commonly recognised as a major contributor of MSD among construction workers. Because of their linearity, ergonomic metrics can be incorporated into assembly line design models. They can also be utilised to take use of efficient solution methods established for optimal line design which are beneficial in the assembly line industry. Real-time risk assessment for work-related musculoskeletal disorders (MSDs) has proven to be challenging to research. Working at a fast speed and performing repetitive activities, as well as maintaining non-neutral body postures, are all physical risk factors for WMSDs. This review discuses common issue related to WMSDs which includes upper extremity, upper limbs, carpal tunnel syndrome, awkward postures, muscle activity, muscle fatigue, assembly line and risk assessment. The aim is to provide an overview of the problems related to the subject matter.

Improving compressed matrix multiplication using control variate method

The seminal work by Pagh [1] proposed a matrix multiplication algorithm for real-valued squared matrices called Compressed Matrix Multiplication (CMM) having a sparse matrix output product. The algorithm is based on a popular sketching technique called Count-Sketch [2] and Fast Fourier Transform (FFT). For input square matrices A and B of order n and the product matrix AB with Frobenius norm ||AB||F, the algorithm offers an unbiased estimate for each entry, i.e., (AB)i,j of the product matrix AB with a variance bounded by ||AB||F2/b, where b is the compressed bucket size. Thus, the variance will eventually become high for a small bucket size. In this work, we address the high variance problem of CMM with the help of a simple and practical technique based on classical variance reduction methods in statistics. Our techniques rely on the Control Variate (CV) method. We suggest rigorous theoretical analysis for variance reduction and complement it via supporting empirical evidence.

Research on Catalytic Reaction of Cotton Straw Pyrolysis Based on Model Compounds

The study starts from the clean conversion of desulfurized ash and biomass resources, based on correlation analysis and Langmuir-Hinshelwood model, studies the components of cotton stalk pyrolysis products and describes the mechanism and effects of desulfurized ash as a catalyst in the pyrolysis process. Regression analysis, support vector machine, and other methods are used to predict the yield or output of pyrolysis products, which is of great significance for the efficient utilization and sustainable development of cotton stalks. The study found that desulfurized ash significantly promoted the thermal decomposition of cotton stalks, increased the pyrolysis gas yield and lower heating value, increased the production of hydrogen-rich gas in the pyrolysis gas, and reduced the production of carbon oxides. Through the study of model compounds, it was found that desulfurized ash has different catalytic effects on the process of cellulose and lignin components in cotton stalks generating pyrolysis gas.

The Impact of the Commercial Agriculture Credit Scheme (CACS) on the Agricultural Economy of Nigeria and its Total Output (2015-2019)

This study analyzed the impact of the Commercial Agriculture Credit Scheme (CACS) on the agricultural economy of Nigeria and its total output from 2015 to 2019, using quarterly data. Secondary data were obtained from the Central Bank of Nigeria (CBN) Annual Reports, the Federal Ministry of Agriculture and Rural Development (FMA & RD), and the National Bureau of Statistics (NBS). The study applied the Ordinary Least Square Multiple Regression Model for statistical analysis and used the National Gross Domestic Product (NGDP) and Agricultural Output (AGO) as dependent variables, while Commercial Agriculture Credit Facility Loan to Agriculture (CAL), Money Supply (M2), Unemployment rate (U) and Government Expenditure (G) were used as independent variables. Empirical findings show that there is no statistically significant relationship between CAL, M2, unemployment rate, government expenditure, and NGDP. Similarly, we did not establish a statistically significant relationship between CAL, M2, unemployment rate, government expenditure, and AGO. Overall, the evidence indicates that the desired impact of the Commercial Agriculture Credit Scheme in Nigeria is not being achieved. Arising from the above, we recommend that policymakers and the monetary authorities should investigate why there is a disconnect between the laudable CACS scheme and the ineffective outcome observed. In addition, structural challenges hindering productivity in the agricultural sector such as insecurity, poor road networks, and inadequate power supply should be addressed.

Biomass-based Brayton-Stirling-AGMD polygeneration for small-scale applications in rural areas

The lack of access to electricity and clean water still affects a substantial proportion of rural areas worldwide, in particular the global south. This paper presents a sustainable polygeneration system that can provide electricity, heat, and drinking water by using agricultural residues in remote rural areas. This polygeneration system consists of a solid biomass-fueled Brayton-Stirling combined cycle system, a boiler, and an air-gap membrane distillation unit. Four different system operation modes were designed to examine the most ideal configurations for maximizing power output, overall efficiency, and/or clean water production, considering a polygeneration system designed for a rural village with daily demands of 13450 kWh electricity and 7.5 m3 drinking water. A thermodynamic analysis are employed to analyze and compare these modes, each operating under steady state conditions. The highest electricity output, up to 160 kW, while the highest clean water is up to 0.7 m3/h. The fuel consumption can reach 0.9 kWh/kg of solid fuel and provide up to 0.0045 m3 of freshwater. In addition, nonlinear multi-objective optimization is used to meet the power demands of typical day in rural areas by varying the polygeneration operation modes and turbine inlet temperature.

Dipolar Microenvironment Engineering Enabled by Electron Beam Irradiation for Boosting Catalytic Performance.

Creating a diverse dipolar microenvironment around the active site is of great significance for the targeted induction of intermediate behaviors to achieve complicated chemical transformations. Herein, an efficient and general strategy is reported to construct hypercross-linked polymers (HCPs) equipped with tunable dipolar microenvironments by knitting arene monomers together with dipolar functional groups into porous network skeletons. Benefiting from the electron beam irradiation modification technique, the catalytic sites are anchored in an efficient way in the vicinity of the microenvironment, which effectively facilitates the processing of the reactants delivered to the catalytic sites. By varying the composition of the microenvironment scaffold structure, the contact and interaction behavior with the reaction participants can be tuned, thereby affecting the catalytic activity and selectivity. As a result, the framework catalysts produced in this way exhibit excellent catalytic performance in the synthesis of glycinate esters and indole derivatives. This manipulation is reminiscent of enzymatic catalysis, which adjusts the internal polarity environment and controls the output of products by altering the scaffold structure.

Using MXene as a Chemically Induced Initiator to Construct High-Performance Cathodes for Aqueous Zinc-Ion Batteries.

MXene usually exhibits weak pseudo-capacitance behavior in aqueous zinc-ion batteries, which cannot provide sufficient reversible capacity, resulting in the decline of overall capacity when used as the cathode materials. Taking inspiration from polymer electrolyte engineering, we have conceptualized an in situ induced growth strategy based on MXene materials. Herein, 5.25 % MXene was introduced into the nucleation and growth process of vanadium oxide (HVO), providing the heterogeneous nucleation site and serving as an initiator to regulate the morphology and structural of vanadium oxide (T-HVO). The resulted materials can significantly improve the capacity and rate performance of zinc-ion batteries. The growth mechanism of T-HVO was demonstrated by both characterizations and DFT simulations, and the improved performance was systematically investigated through a series of in situ experiments related to dynamic analysis steps. Finally, the evaluation and comparison of various defect introduction strategies revealed the efficient, safety, and high production output characteristics of the in situ induced growth strategy. This work proposes the concept of in situ induced growth strategy and discloses the induced chemical mechanism of MXene materials, which will aid the understanding, development, and application of cathode in aqueous zinc-ion batteries.

Unlocking Global Efficiency with Enhanced Milling Machines Worldwide

This study investigates the effectiveness of six milling machines at PT. INKA, a railroad car manufacturing company, focusing on CNC Plano 133 and Horizontal Milling 142. Utilizing Overall Equipment Effectiveness (OEE) and Age Replacement methods, the research aims to optimize machine performance and propose preventive maintenance strategies. Data spanning from January 2021 to December 2022 were collected and analyzed. Results indicate that both CNC Plano 133 and Horizontal Milling 142 exhibit suboptimal OEE values, primarily due to breakdown losses. Applying Age Replacement within 10 days significantly enhances reliability, with post-replacement reliability reaching 100%. The findings underscore the importance of preventive maintenance in improving milling machine reliability and overall productivity, thereby enhancing competitiveness and sustainability in the manufacturing sector. Highlight: Improved productivity: Preventive maintenance boosts milling machines' reliability and effectiveness. Resource efficiency: Analyzing OEE minimizes downtime, optimizes production output. Competitive edge: Enhanced performance sustains competitiveness, strengthens manufacturing sector's sustainability. Keyword: Milling machines, Overall Equipment Effectiveness (OEE), Preventive maintenance, Age Replacement, Manufacturing industry

Creation of an international laboratory network towards global microplastics monitoring harmonisation

Infrastructure is often a limiting factor in microplastics research impacting the production of scientific outputs and monitoring data. International projects are therefore required to promote collaboration and development of national and regional scientific hubs. The Commonwealth Litter Programme and the Ocean Country Partnership Programme were developed to support Global South countries to take actions on plastics entering the oceans. An international laboratory network was developed to provide the infrastructure and in country capacity to conduct the collection and processing of microplastics in environmental samples. The laboratory network was also extended to include a network developed by the University of East Anglia, UK. All the laboratories were provided with similar equipment for the collection, processing and analysis of microplastics in environmental samples. Harmonised protocols and training were also provided in country during laboratory setup to ensure comparability of quality-controlled outputs between laboratories. Such large networks are needed to produce comparable baseline and monitoring assessments.

Genetic Approaches to Improving Coffee Resistance Against Diseases and Pests in the Philippines

There is a huge demand for coffee in the Philippines but local supply has a long way to go at catching up. One way to aid local farmers is to develop coffee varieties with combined desirable traits including natural resistance against various diseases and insect pests. This can increase product output and reduce costs on chemical control that can, in turn, potentially increase their profits. This paper reviews and gives an overview of the genetic research on coffee toward improving plant defense. The most prominent diseases and pests plaguing plantations worldwide are noted. From studies using classical tools such as genetic marker analysis to recent ones using newer tools such as genomics and bioinformatics, global accomplishments are discussed alongside accomplishments in the Philippines. Inferences are also made from data collated from these studies. Overall, this review paper aims to assess the status of coffee research and identify gaps as well as prospects and needs for further investigation.

Productive use of energy of women-owned micro-, small-, and medium-sized enterprises: Insights from food and textile businesses in selected African countries

This paper presents a descriptive study focusing on the productive energy use of women-owned micro-, small-, and medium-sized enterprises that operate in Africa's food and textile sectors. Through a multidisciplinary approach, combining primary and secondary data collection methods, and integrating quantitative and qualitative tools, this study examines the relationship between the gender-based ownership structure of enterprises (i.e., sole female, female-female, and female-male) and energy consumption patterns, including demand levels, carrier use, access type (on-grid or off-grid), and expenditure. Despite limitations in scope and sample size, the findings shed light on gender-specific productive use practices.Findings show that female-owned businesses primarily rely on single or dual energy carriers, contrasting with female-male enterprises, which typically employ two or more energy carriers. Fuel usage varies among ownership structures, with diesel, biomass, and liquified petroleum gas being notable choices. Increasing diversity in ownership correlates with heightened awareness of energy metrics and monthly demand for electric and mechanical power, with some of the latter correlation also observed for thermal energy. Moreover, as ownership diversity increases, energy expenditure per kilogramme of production output decreases. Some sole female-owned enterprises surpass 100 USD/kg/month, female-female partnerships may reach 100 USD/kg/month, whereas female-male co-owned enterprises remain below 10 USD/kg/month.Beyond contributing to understanding gendered productive energy practices, this research also emphasises the importance of gender mainstreaming in productive use and energy access interventions. It highlights the need for renewable energy solutions, capacity-building programmes, and further research to address efficiency and accessibility challenges faced by women entrepreneurs.