Productivity Of System Research Articles

Nanobiotechnology-mediated sustainable agriculture and post-harvest management

• We describe nanotechnology applications in various fields of agriculture, namely seed storage, seed germination, plant growth, priming, fertigation and crop productivity. • We emphasize the use of nanomaterials for the post-harvest management of fruits and vegetables. • Nanomaterials used as intelligent delivery systems for crop productivity, stress tolerance and plant adaptation are discussed. • Nanomaterials used as sensors for precision agriculture and crop protection. Humans directly depend on food and agriculture. However, an estimated one- third of agricultural produce is wasted every year post-harvest loss. The major reasons for post-harvest loss include microbial contamination, moisture content, degradation, and adverse effects of the physical and chemical methods used for storage. Conventional post-harvest methods do not adequately prevent the loss of agricultural produce therefore, new strategies are increasingly needed to address the shortcomings of traditional agricultural post-harvest practices. In this regard, nanotechnology (the manipulation of materials at <100 nm) has emerged as a promising field to replace traditional practices. The use of engineered nanoagroparticles greatly enhances agricultural productivity and mitigates the environmental issues posed by conventional chemical fertilizers. This review aims to describe applications of nanotechnology in various fields of agriculture including seed storage, seed germination, plant growth, priming, fertigation and crop productivity. In addition, nanomaterials used as intelligent delivery systems for crop productivity, stress tolerance and plant adaptation are discussed. Moreover, nanomaterials used as sensors for precision agriculture and crop protection are described in detail. Importantly, we discuss the use of nanomaterials as fertilizers to replace chemical fertilizers in sustainable agriculture. Finally, we emphasize the use of nanomaterials for the post-harvest management of fruits and vegetables.

From automation toward integration of process planning: a state-of-the-art review

The two main objective functions for designing the manufacturing system are, improving the manufacturing system's productivity and production quality. Process planning is an integral part of manufacturing system design. In this work, the study of process plan evolution over the period has been reviewed, keeping in mind the design objectives. Based on the technological advancements, the process plan evolution has been classified into two periods. The first evolution relates to automation, in which efforts are made to automate the manual activities of conventional process plans, which leads to the development of Computer-Aided Process Planning (CAPP). As long as the systems are deterministic with fixed structures and capabilities, CAPP is a good solution. Due to the uncertainty in the market for product demand, the new manufacturing systems are becoming more and more dynamic to handle the product variety demand. In that case, just automation is not enough to achieve the objective functions of system design. Designers have to consider the integration of the manufacturing system life cycle. So the second evolution of the process plan relates to, the consideration of performance indicators defined due to the system integration. For the second evolution, the literature review of the reconfigurable process plan (RPP) is performed considering both automation and integration of the system.

Enhancement of observability using Kubernetes operator

Observability is the ability for us to monitor the state of the system, which involves monitoring standard metrics like central processing unit (CPU) utilization, memory usage, and network bandwidth. The more we can understand the state of the system, the better we can improve the performance by recognizing unwanted behavior, improving the stability and reliability of the system. To achieve this, it is essential to build an automated monitoring system that is easy to use and efficient in its working. To do so, we have built a Kubernetes operator that automates the deployment and monitoring of applications and notifies unwanted behavior in real time. It also enables the visualization of the metrics generated by the application and allows standardizing these visualization dashboards for each type of application. Thus, it improves the system's productivity and vastly saves time and resources in deploying monitored applications, upgrading Kubernetes resources for each application deployed, and migration of applications.

Managing Stochastic Bucket Brigades on Discrete Work Stations

Bucket brigades are notably used to coordinate workers in production systems. We study a J‐station, I‐worker bucket brigade system. The time duration for each worker to serve a job at a station is exponentially distributed with a rate that depends on the station's expected work content and the worker's work speed. Our goal is to maximize the system's productivity or to minimize its inter‐completion time variability. We analytically derive the throughput and the coefficient of variation (CV) of the inter‐completion time. We study the system under two cases. (i) If the work speeds depend only on the workers, the throughput gap between the stochastic and the deterministic systems can be up to [Formula: see text] when the number of stations is small. Either maximizing the throughput or minimizing the CV of the inter‐completion time, the slowest‐to‐fastest worker sequence always outperforms the reverse sequence for the stochastic bucket brigade. To maximize the throughput, more work content should be assigned to the stations near the faster workers. In contrast, to minimize the CV of the inter‐completion time, more work content should be allocated to the stations near the slower workers. (ii) If the work speeds depend on the workers and the stations such that the workers may not dominate each other at every station, the asymptotic throughput can be expressed as a function of the average work speeds and the asymptotic expected blocked times of the workers, and can be interpreted as the sum of the effective production rates of all the workers.

Productivity improvement using value stream mapping and simulation - case studies

Companies are implementing lean manufacturing tools to keep their competitiveness over their competitors by improving the manufacturing system's productivity enhancement of the product. The present study has been carried out in two manufacturing industries to justify lean thinking using value stream mapping and simulation of manufacturing system processes. The study explains the necessary steps from initially identifying the product among list of products for VSM analysis to carry out value stream of the product. Current state map has been prepared with the help of brainstorming to find potential shortcomings in the entire mapped process. Future state map has been prepared to overcome current map's shortcoming; further simulation was done to analyse the effect of the change in the production line. The results are validated by using advanced quantitative tools to justify the overall improvements. Results indicated that significant reduction of lead time by 23.6% and reduction in value added time by 9% which further improves the productivity by 4.2%. Further results of fuzzy AHP indicated 22.5% contribution of VSM and simulation in overall improvement.

Crop Improvement for Circular Bioeconomy Systems

HighlightsWe describe and demonstrate a multidimensional framework to integrate environmental and genomic predictors to enable crop improvement for a circular bioeconomy.A model training procedure based on multiple phenotypes is shown to improve predictive skill.The decision set comprised of model outputs can inform selection for both productivity and circularity metrics.Abstract. Contemporary agricultural systems are poised to transition from linear to circular, adopting concepts of recycling, repurposing, and regeneration. This transition will require changing crop improvement objectives to consider the entire system, and thus provide solutions to improve complex systems for higher productivity, resource use efficiency, and environmental quality. The methods and approaches that underpinned the doubling of yields during the last century may no longer be fully adequate to target crop improvement for circular agricultural systems. Here we propose a multidimensional framework for prediction with outcomes useful to assess both crop performance traits and environmental sustainability of the designed agricultural systems. The study focuses on maize harvestable grain yield and total carbon production, water use, and use efficiency for yield and carbon. The framework builds on the crop growth model whole genome prediction system, which is enabled by advanced phenomics and the integration of symbolic and sub-symbolic artificial intelligence. We demonstrate the approach and prediction accuracy advantages over a standard statistical genomic prediction approach used to breed maize hybrids for yield, flowering time, and kernel set using a dataset comprised of 7004 hybrids, 103 breeding populations, and 62 environments resulting from six years of experimentation in maize drought breeding in the U.S. We propose this framework to motivate a dialogue for how to enable circularity in agriculture through prediction-based systems design. Keywords: Circular bioeconomy, Circular economy, Crop improvement, Crop models, Drought, Gene editing, Genomic prediction, Maize, Plant breeding.

Upotreba veštačke inteligencije na traktorima u operacijama na njivama - pregled

According to UN Food and Agriculture Organization [1], the population of the world will increase by 2 billion by 2050. However, only 4% additional land will come under cultivation by then. It could be inferred that, with the global population expected to reach 9.1 billion in 2050, 70 percent more food needs to be produced, otherwise about 370 million people would be in hunger in 2050. In this light, the use of latest technological solutions to make farming more efficient remains one of the greatest imperatives. While Artificial Intelligence (AI) sees a lot of direct application across sectors, it can also bring a paradigm shift in how we see farming today. AI-powered solutions will not only enable farmers to do more with less, it will also improve quality and ensure faster go-to-market for crops. This paper presents a review of the applications of AI in tractor field operations. The paper discusses elaborately, the use of robotics as a form of artificial intelligence which is very useful in tractor field operations such as tillage, weeding, seeding, herbicide spraying, and harvesting. A typical focus is laid on the strength and limitations of the applications and the way in utilizing expert systems for higher productivity.

Explication of Conventional and Smart Irrigation Systems with Challenging Factors

Throughout the world agriculture is the essential source of food. Therefore it is necessary to have a proper irrigation system for good productivity in agriculture. There are several factors that affect irrigation system such as irregularity in the distribution of rainfall, water scarcity, superfluous irrigation, scant irrigation, climate change, degradation of water quality etc. Each irrigation systems are combined with various technologies and proposed with various methods to enhance the irrigation management and reduce the water usage. Furthermore to raise the soil fertilization and diminish crop disease through the irrigation will help to magnify the productivity. The paper focused and analysed the existing and modern irrigation systems. This facilitates farmers to select suitable irrigation system according to their specifications.

Концептуальні передумови розвитку підприємства: державне регулювання цифровізації

Studying the foreign experience in the development of digitalization on the example of advanced countries is based on two main models: the model of evolutionary development of digitalization based on market competition and the administrative model for regulating the development of digitalization. The author of the study proposed a mixed model, which is a synthesis of a model of evolutionary development of digitalization on the basis of market competition with elements of administrative regulation of this activity. A comprehensive study of the world experience of government regulation of digitalization and the features and prospects of its development allowed the author to form a model of government regulation of Digitalization of Ukraine, which is a systematized, generalized vision of the efficient policy of government regulation of Digitalization in Ukraine. The proposed author’s model of government regulation of Digitalization of Ukraine is an interrelated system of goals, objectives, functions, methods, principles, and infrastructure. To achieve the goal of ensuring sustainable balanced development of digitalization – the government regulation should be aimed at solving a number of tasks: accelerating economic growth and attracting investment; transformation of all spheres of economic activity and business processes on the basis of competitiveness and efficiency; development of innovative technologies, networks, and platforms; creation of digital strategic partnerships; availability and openness of digital technologies; implementation of intellectual capital, transformation of the system of social productivity.

The Negative Effect of Heavy Metal Salts on the Body of Mammal Animals

The main purpose of this presented article was to explain the need to study the amount of heavy metal salts in the environment where animals live, in the water, in air, and in the food and fodder consumed. This article presents materials from the literature on the effects of heavy metal salts on the body of animals and the environment in which they live. The cited analytical data showed that the general information on the negative effects of heavy metal salts on the body is sufficient, but their effects on the digestive tract and morpho-functional properties of rabbits should be studied in depth. Therefore, we planned to focus our scientific work on this topic. The article mainly refers to salts of heavy metals cadmium, lead, and mercury (Cd, Pb, Hg). It is noted in the literature that heavy metal salts have a negative effect on the body of animals. We focused mainly on data on the effects of heavy metals on farm animals, including rabbits. But it is clear that the authors referred to were referring to experimental animals. These negative effects are manifested in the form of disorders of digestive functions, disorders of neurovegetative processes, increasing incidence of cardiovascular disease, rapid heart failure, deterioration of calcium metabolism, as well as impaired haemoglobin metabolism. Disorders of protein metabolism manifest themselves in the form of cases of hyperproteinaemia and dysproteinaemia. The results of the evaluation of the organism of healthy animals in chemically and radioactively contaminated areas showed the accumulation of significant levels of chemical elements in their organism. We mainly looked at the effects of heavy metal salts on farm animals. The cited analytical data showed that the general information on the negative effects of heavy metal salts on the body is sufficient, but the effects on the activity of organ systems in the body (respiration, blood and blood circulation, digestion, reproduction, productivity and immunological systems) have not been comprehensively studied.

Protocol for a single-centre mixed-method pre–post single-arm feasibility trial of a culturally appropriate 6-week pulmonary rehabilitation programme among adults with functionally limiting chronic respiratory diseases in Malawi

IntroductionMalawi has a substantial burden of chronic respiratory diseases (CRDs) which cause significant morbidity and loss of economic productivity, affecting patients, families and health systems. Pulmonary rehabilitation (PR) is a...

Integrated nutrient management system for productivity and profitability of potato (Kufri Chipsona-3) Under Punjab Condition

A field experiment was conducted to study the effect of integrated nutrient management on the vegetative growth, yield and quality of potato cultivar Kufri Chipsona-3 in sandy loam soils of Punjab. The field experiment was laid out in a randomized block design which involved the integrated use of different biofertilizers, organic manures and chemical fertilizers i.e., NPK, FYM (Farm Yard Manure), vermicompost, bio-fertilizers (phosphorus solubilizing bacteria and Vesicular Arbuscular Mycorrhizae) and absolute control to study the yield and quality parameters. The study revealed that maximum yield (27.9 t/ha) was obtained in the treatment which included integrated use of 75% recommended dose of NPK + FYM (Farm Yard Manure) @ 50 t/ha + PSB @ 10 kg/ha as compared to other treatments. The treatment also had positive effect on growth, quality and other yield attributes viz. plant height (39.85 cm, 48.73 cm and 51.62 cm at 30, 60 and 90 days after sowing respectively), number of compound leaves (41.84, 46.46 and 49.49 at 30, 60 and 90 days after sowing respectively), dry matter content (20.66%) and specific gravity (1.12 g/cm3) but the treatment had no significant effect on chlorophyll content. The benefit: cost ratio was also higher in the same treatment.

Forecasting Electric Substation’s Load Curve Using GMDH-type Neural Network

Electric load forecasting plays an important role in the planning and operation of the power system for high productivity in any province in the region. A short-term electrical energy forecast for Sibalom, Antique, Philippines Substation was carried out using a GMDH-type neural network as its core algorithm, and the result was compared to that of regression analysis. The GMDH-type neural network was used to train and test weekly energy consumed in the substation from July 2020 to August 2020. The neural network was trained using a quadratic neural function. Root mean square error (RMSE) and mean absolute percentage error (MAPE) were used as performance indices to test the accuracy of the forecast. The neural network model gave a root mean square error (RMSE) of 3.57177%, a mean absolute percentage error (MAPE) of 2.35499%, and a correlation (R) value of 0.983591 while the regression analysis method gave a standard error of 99.39524 and a correlation (R) value of 0.907673. Results obtained show the efficacy of the GMDH-type neural network model in forecasting over the regression analysis method.

Molecular interaction analysis of β-1, 3 glucan binding protein with Bacillus licheniformis and evaluation of its immunostimulant property in Oreochromis mossambicus

Analyzing the health benefits of any two immunostimulants (synbiotics) in combined form and information on their interactions gain more visibility in the usage of synbiotics in aquafarms. With this intention, the current work explores the immunostimulant effect and structural interaction of synbiotic (β-1, 3 glucan binding protein from marine crab, Portunus pelagicus (Ppβ-GBP) and Bacillus licheniformis) on Oreochromis mossambicus. The experimental diet was prepared with Ppβ-GBP and B. licheniformis, and nourished to the fingerlings of O. mossambicus for 30 days. After the experimental trial, a higher growth rate and immune reactions (lysozyme, protease, myeloperoxidase and alkaline phosphatase activity) were noticed in the fish nourished with synbiotic (B. licheniformis and Ppβ-GBP) enriched diet. Moreover, the synbiotic enriched diet elevated the antioxidant responses like glutathione peroxidase (GSH-Px) and catalase (CAT) activity in the experimental diet-nurtured fish. At the end of the feed trial, synbiotic diet nourished fish shows an increased survival rate during Aeromonas hydrophila infection, reflecting the disease resistance potential of experimental fish. Also, the interaction between Ppβ-GBP and Bacillus licheniformis was analyzed through computational approaches. The results evidenced that, Ppβ-GBP interacts with the B. licheniformis through sugar-based ligand, β-glucan through a hydrogen bond with a good docking score. Thus, the synbiotic diet would be an effective immunostimulant to strengthen the fish immune system for better productivity.

Modelling research productivity of university researchers using research incentives to crowd-in motivation

PurposeThe overall aim of this research is to propose a research incentive framework for academic staff members at the South African universities of technology (UoTs).Design/methodology/approachAn exploratory case study methodology was applied, while a questionnaire was used to (1) identify the factors that stimulated staff members' research activities; (2) assess what was considered an appropriate way of measuring research productivity and (3) identify appropriate research awards, recognition and rewards. Working from the self-determination theory (SDT), the results of the data analysis were used to develop a framework for ensuring crowding-in of research incentives into intrinsic motivation. This framework is anchored on the three main components (competence, autonomy and social relatedness) of the cognitive evaluation theory (CET) that provides guidelines for the design of a research incentive system.FindingsIntrinsically motivated researchers tend to conduct research for their inherent satisfaction because it meets their basic individual psychological need for competence. Existing research incentives and productivity systems fail to provide intrinsic motivation for researchers. Recommendation for a framework for designing research incentive systems is centred on the researchers themselves. This approach contributes to a research environment that provides space for autonomy, creativity, flexibility and innovation and consequently a successful research output that is hinged on the ability to keep researchers intrinsically motivated.Originality/valueA conceptual framework is proposed specifically for technically focused UoT suggesting that crowding-in the motivation of researcher incentives results in improved intrinsic-based motivation. The autonomy of researchers in particular is regarded as the most important driver of such motivation, with the availability of resources, collegiality and research skills and development ranking as the most important aspects specifically driving intrinsic motivation. The framework not only provides a tool for institutions of higher education focused on developing the technical skills, but also offers management at any type of university challenged with low research outputs and a poor research ethos with an alternative method to improve both the quantity and quality of research outputs.

Techno-environ-economic-energy-exergy-matrices performance analysis of evacuated annulus tube with modified parabolic concentrator assisted single slope solar desalination system

In the present study, a sophisticated novel design of solar desalination system with evacuated annulus tube collector augmented unique combination of modified compound parabolic concentrators has been analyzed and simulated with the help of the computational tool (MATLABR2015a) for Techno-Environ-Economic-Energy-Matrices observations under the specific meteorological conditions of New Delhi, India. The current approach emphasizes the utility of modified parabolic concentrator integrated evacuated tube that effectively improves the solar absorbing performance of the irradiated solar energy uniformly through its periphery, as well as enhancing the thermo siphons working loom appreciably than the conventional applications of vacuum tubes. The proposed system is being optimized to get the maximum possible basin water temperature as 99.5 °C for the larger water depth (0.16m) at the same orientation of still top cover and evacuated tubes (30°). The maximum circulation rate (thermo siphon) is achieved as 54.96 kg/h. The daily overall energy-exergy efficiencies are 50.8% and 3.8%, respectively. The daily yield (16.2 kg/day or 5.4 kg/m2 with respect to the solar energy collection area and its production cost (0.005 $/l) at a nominal selling price (0.07 $/l) found good. The energy-exergy based CO2 mitigates and environmental earned revenue are 131.97 tons, 67.44 tons, $1318.36, and $673.77, respectively. The establishment cost of the system is quite low at $214.92, and the system's productivity is found as 940.8%, which is more than 100% that depicts the system as appreciably feasible. The noticeable yield output at low production cost, environmental revenue credits, high mitigation, and low pay-off time makes the system compatibly sustainable and feasible with smaller and effective collector areas for the respective solar irradiations.

Sustainable and digital education during and beyond the Covid-19 crisis.

Abstract The pandemic crisis has coincided with a time of global economic crisis. The education system has suffered from this double impact: the simultaneous closure of schools and universities and a significant worsening of the business and productivity system. Digitalisation in the education process started in the far past, but it has become a priority with the pandemic. The use of digital tools in the educational process ensured that the latter did not come to a complete standstill during the pandemic. Although digitalisation is seen as a possible solution to the problems facing schools, it can also be seen as a factor in widening the gap between rich and developing countries. The article proposes a reflection about education during the pandemic and the digitalisation process of schools in all its facets and at alle education level.

ANALISIS PENERAPAN SISTEM PENGENDALIAN MANAJEMEN TERHADAP PRODUKTIVITAS DAN PENGGAJIAN PERUSAHAAN PADA MASA PANDEMI

During this pandemic period, many companies have experienced a decline in performance in any aspect, but many companies are also able to maintain their performance even during the current pandemic from the many activities within the company that we do not know how to maintain their performance. The purpose of this study was to find out how to implement a management control system for company productivity and payroll during the pandemic. This study uses a descriptive qualitative method with the data used is primary data. Conclusion From the results and discussion above For the control system at the company CV. TRIO CIPTA has a control system with a new strategy that is more suitable to be applied during this pandemic so that the company that produces this RO machine can survive during this pandemic. Productivity at this company also experienced a very rapid increase.

Evaluation index system of cultivated land quality and productivity: A case study of Binyang County, Guangxi

Evaluation index system of cultivated land quality and productivity: A case study of Binyang County, Guangxi

Fisherman Community Development Model with Disaster Mitigation Perspective in Meranti Islands Regency

Meranti Islands Regency has coastal natural resources. On the other hand, this area also has the potential for natural disasters (coastal) and non-natural disasters that threaten the sustainability of resources and community welfare, so disaster mitigation efforts are needed. This study aims to formulate a model for developing Fisherman communities with a disaster mitigation perspective. This study uses MPE analysis and prospective analysis. The strategic basis for developing fisherman communities is increasing food security through the developing coastal based green industries, capacity building for local competitiveness and conservation of endemic species, and allocating budget proportionally to create local-based economic infrastructure and facilities development. The potential natural disasters that are more dominant in Meranti Islands Regency are abrasion, landslides, high waves and tidal flooding. A non-natural disaster is Covid-19 pandemic. Mitigation must be done is planting mangroves, building sheet piles, social engineering policies must be done by planting mangroves, building sheet piles, social engineering policies, and planting mangroves, building sheet piles, social engineering policies, and alternative livelihoods. The model for developing Fisherman communities with a disaster mitigation perspective in Meranti Islands Regency is optimizing coastal areas’ productivity and livelihood support systems.