Production Scenarios Research Articles

The Potential Perspective of Processing Rice Husk as SiO<sub>2</sub> Source to Tetraalkoxysilane in Indonesia

Tetra-alkoxysilane (TROS) is one of the useful chemicals and it can be processed to produce semiconductor and photovoltaic devices. Now, the transformation of silica (SiO2) to TROS is garnering interest due to the potential of extracting it from biomass. As the 14th largest country, Indonesia possesses an abundant source of SiO2 from mining activities and agricultural waste, notably rice husk (RH). However, only a little concrete action is planned for leveraging RH into a more valuable industrial substance. This review will explain two routes for TROS—conventional and direct—comparing their respective benefits and drawbacks. Additionally, it presents a simulation of various scenarios for scaling TROS production to an industrial level, considering technoeconomic and environmental assessment aspects. The focus then shifts to Indonesia’s strategic trajectory for 2045, offering recommendations to enhance resource utilization for economic and national development.

Reduction of methyltestosterone concentration in feed during masculinization of Nile tilapia (Oreochromis niloticus) in biofloc system

Most larviculture of Nile tilapia is carried out in ponds with a large presence of live food, with temperature variations throughout the day and year, and feed leftoovers due to dissipation in the water. As a consequence, the masculinization process needs to be done with a high concentration of 17α-methyltestosterone (MT) in the diet. Production in closed systems, such as biofloc technology (BFT), allows controlling the water temperature, uses a smaller volume of water and generates less effluent, being an alternative system for the masculinization process. This study evaluated the masculinization rates of Nile tilapia in the BFT, with a controlled temperature (∼28 °C), using concentrations of MT in the feed lower than those recommended for masculinization in ponds and BFT (60 mg ∙ Kg−1 of feed). Tilapia larvae (post yolk sac absorption) were raised in BFT (2 larvae ∙ L−1 or 100 larvae ∙ tank−1) and submitted to different concentrations of MT in the diet (0, 30, 40, 50 and 60 mg ∙ Kg−1 of feed), which was offered five times a day for a period of 28 days. The experimental design was entirely randomized. After the hormonal treatment, the water in the tanks was completely replaced with new water, free of hormonal residues, where the fry remained until they reached a viable size for sexing. It was also tested to maintain the original water used during the hormonal treatment period, during the post-experimental period, where 30 mg ∙ Kg−1 of feed was used. The water quality variables (temperature, pH, dissolved oxygen, settleable solids, total suspended solids, alkalinity, nitrogen compounds, salinity, phosphate and organic carbon) and growth performance variables (final body weight and length, specific growth rate, condition factor and survival) did not differ between MT concentration in the diet (p > .05). The treatment without hormone (control) presented 73.6% of males and the treatments that received hormone showed masculinization rates >99%, significantly higher than control (p < .05), but did not differ from each other (p > .05). The percentage of male individuals in the control treatment was high and this may have occurred because of the temperature of 28 °C throughout the experiment. However, this percentage of males is not considered high enough for production, which requires higher rates close to 100% as possible. The MT was not detected in the water 12 h after the last feeding with feed containing hormone. Thus, it is feasible to use a lower concentration (30 mg of MT ∙ Kg−1 of feed) in BFT. Our study has a direct impact on the global tilapia production scenario, offering a new environmentally sustainable masculinization protocol, using less water and hormones in the process and avoiding the release of hormonal residues.

Stochastic Optimization of the Management Schedule of Korean Pine Plantations

Korean pine is one of the most important tree species in northeastern China, where Korean pine plantations produce timber and edible seeds. Often, seeds create more income than timber. Predicting the timber and cone yields of alternative management schedules of the plantations involves uncertainty because the future climatic conditions for tree growth and cone production are unknown. This study developed a simulation model that generates stochastic variation around the predictions of tree growth and cone yield models, allowing the forest manager to seek cutting schedules that maximize the expected amounts of timber or cones, or the expected economic profit, under uncertain future states of nature. Stochastic analysis also facilitates management optimizations for different risk attitudes. The differential evolution algorithm and the developed stochastic simulation model were used to optimize the management of planted Korean pine. Timber and cone yields of a management schedule were calculated under 100 different scenarios for tree growth and cone production. When the growth and cone yield scenarios were stationary (no temporal trends), the optimal management schedules were similar to those of deterministic optimization. The benefits of stochastic optimization increased when it was assumed that the tree growth scenarios may contain climate-change-induced trends. Non-stationary growth variation led to shorter optimal rotation lengths than stationary growth variation. Increasing risk tolerance shortened optimal rotations.

Can markets for nature conservation be successful? An integrated assessment of a product label for biodiversity practices in Germany

Biodiversity is declining in many ecosystems, particularly in agricultural landscapes. So far, instruments such as the Common Agricultural Policy (CAP) have not been able to halt this trend. Stricter legal regulations tend to be poorly received by farmers and this leads to conflicts. However, their acceptance is crucial as agriculture is a major stakeholder in biodiversity conservation. In this context, market-based approaches are alternative or complementary instruments for biodiversity conservation. However, there are few examples in Germany and the potential economic feasibility on a larger scale has hardly been investigated. We, therefore, analyzed the economic and agronomic impacts of a potential new market label for biodiversity-friendly products on conventional arable farms in two German case study regions – Brandenburg and North Rhine-Westphalia (NRW) – with different agricultural frameworks. The label requirements were defined in advance by a group of experts in the field of nature conservation. In terms of methodology, we combined a survey of nine companies in the food sector, for instance food retailers, that looked at potential price premium scenarios for products with the label and economic land use modelling. The participation of farms led to an average reduction of gross margins per hectare of arable land of approximately 64 € in Brandenburg and about 96 € in NRW. This revealed spatial disparities. Regarding biodiversity impacts, pesticide use was reduced by about 50 % in both regions. This indicated a high level of effectiveness coupled with comparably moderate farm adaptation costs. Price premiums under the market label for potatoes, wheat, and rye averaging 10 % could almost compensate for the loss of farm income in both regions. Premiums between 5 % and 10 % were also the order of magnitude estimated by the companies that took part in the survey. At the same time, the survey did show that potential transaction costs could be quite high. We, therefore, concluded that the market alone was unlikely to finance the introduction of the label in the case study regions. There was a need for accompanying instruments such as the CAP or private business investment. However, given the case study character, the results should be interpreted with caution and cannot be considered representative of all German or European agricultural conditions. They require further research. Nevertheless, our results are highly relevant for policy makers, as they show that biodiversity conservation, at least in the study regions considered, cannot be tackled with one single instrument, but requires a mix of different ones. For instance, a combination of policies and private initiatives, such as the CAP and a private market label like the one considered in the study.

Optimising microgrid energy management: Leveraging flexible storage systems and full integration of renewable energy sources

The significance of microgrid systems has grown considerably. This research proposes an innovative approach to manage uncertainty in microgrids by employing energy storage systems as the exclusive flexible resource. To address this challenge, a mathematical problem is formulated as a two-stage stochastic programming model, considering two uncertainties in the microgrid: wind and photovoltaic production. The microgrid system encompasses multiple components, including a diesel generator, a microturbine, wind and photovoltaic power generation, an energy storage system, and the microgrid’s demand. Notably, the microgrid exhibits two distinctive features: (i) the complete integration of wind and photovoltaic production, and (ii) the utilisation of an energy storage system as the sole flexible resource. The objective is to minimise the expected cost of the microgrid system while determining the optimal capacity of the energy storage system to meet the energy balance constraint. This constraint takes into account the varying scenarios of wind and photovoltaic production. The decisions are taking for a duration of 8760 h, a long-term evaluation. A case study is presented for actual data from Greece and the results show high volatility of the renewable energy sources implies higher energy storage system capacity as a sole flexible source for avoiding renewable curtailment.

Industrial engineer and Industry 4.0? Empirical evidence from the Brazilian context considering the relation between competences and technologies

PurposeManufacturing systems have undergone radical changes because of the implementation of physical and digital innovating technologies with high levels of connectivity, interoperability and autonomy. In this regard, the objective of this study was to investigate whether industrial engineers graduated in recent years in Brazil are prepared or not to work in companies and industries within the scope of Industry 4.0 technologies in a way that they positively contribute to the implementation and management of such technologies.Design/methodology/approachTo achieve these objectives, a literature review and a survey on managers of the industrial sector acting in Brazil were carried out as the research strategies. The data collected were analyzed through a quantitative approach by means of the structural equations modeling method.FindingsThe hypothesis that the competencies of industrial engineers currently graduating in Brazil have a positive impact on the implementation and management of Industry 4.0 technologies has been confirmed. Predicting the evolution of production scenarios, understanding the interaction between organizations and their impacts on competitiveness and keeping abreast of technological advancements, organizing them and putting them to the service of business and societal demands were the competencies that obtained the highest factor loadings in the construct of industrial engineer competencies. In addition, cloud manufacturing, automation and robotization were the competencies that obtained the highest factor loadings in the industry 4.0 construct.Originality/valueThe analysis of skills development stands out as a source of competitive advantage for companies that intend to transition to a production system aligned with the principles of Industry 4.0, considering the training of professionals in an emerging economy context.

Evaluation and use of recently introduced sheep breeds to Uruguay

Sheep numbers in Uruguay have declined over the last 30 years. In the north and northeast there are extensive wool and dual-purpose systems, respectively, where both wool and meat impact on income. In the south, small-scale family sheep meat production systems have flourished. In this thesis I report work pertaning to production systems in the south (1) and northeast (2) regions. Corriedale (C) is the predominant breed in the country. Milchschaf (M) has been disseminated in the south but C still prevails in the northeast. There is a paucity of rigorous evaluations of these breeds or alternatives that could be more profitable, such as Highlander (H) for the south and Dohne Merino (DM) for the northeast. I experimentally assessed: in 1), wool production, reproduction and growth in C, H and M, and in 2), wool quality and body traits in ewe hoggets from rotational crossbreeding between C and DM. In 1), wool production was better in C, but H and M outperformed C in live weight and reproductive performance. In 2), genotypes with greater proportions of DM produced lower fleece weight, and those with greater proportions of C produced coarser fibre diameter, with no differences in wool quality or morphological traits related to meat aptitude. Gross margins (GM) integrate physical performance with product values and costs, allowing monetary comparison between genotypes. I calculated GMs for a number of production and market scenarios. In 1), most often GM was greatest for H, followed by M. The differences in favor of H and M over C decreased when I considered higher feed requirements for H and M. The GM of H and M increased by assuming they were wool-less (the cost of harvesting exceeds the value of the wool produced). In 2), I considered low and high prices for wool of different fibre diameter. GM was greatest for ¾DM and ⅝DM at low prices, and for ¾DM and ½DM at high prices. C had the lowest GM in all scenarios. I recommend H for southern systems and research on hair sheep breeds. In extensive dual-purpose systems, rotational crossbreeding between C and DM allows for improved wool income without losing meat potential. I formulate recommendations about future genotype evaluations, integrating them with current within breed genetic evaluations.

A Long-Term Video Tracking Method for Group-Housed Pigs

Pig tracking provides strong support for refined management in pig farms. However, long and continuous multi-pig tracking is still extremely challenging due to occlusion, distortion, and motion blurring in real farming scenarios. This study proposes a long-term video tracking method for group-housed pigs based on improved StrongSORT, which can significantly improve the performance of pig tracking in production scenarios. In addition, this research constructs a 24 h pig tracking video dataset, providing a basis for exploring the effectiveness of long-term tracking algorithms. For object detection, a lightweight pig detection network, YOLO v7-tiny_Pig, improved based on YOLO v7-tiny, is proposed to reduce model parameters and improve detection speed. To address the target association problem, the trajectory management method of StrongSORT is optimized according to the characteristics of the pig tracking task to reduce the tracking identity (ID) switching and improve the stability of the algorithm. The experimental results show that YOLO v7-tiny_Pig ensures detection applicability while reducing parameters by 36.7% compared to YOLO v7-tiny and achieving an average video detection speed of 435 frames per second. In terms of pig tracking, Higher-Order Tracking Accuracy (HOTA), Multi-Object Tracking Accuracy (MOTP), and Identification F1 (IDF1) scores reach 83.16%, 97.6%, and 91.42%, respectively. Compared with the original StrongSORT algorithm, HOTA and IDF1 are improved by 6.19% and 10.89%, respectively, and Identity Switch (IDSW) is reduced by 69%. Our algorithm can achieve the continuous tracking of pigs in real scenarios for up to 24 h. This method provides technical support for non-contact pig automatic monitoring.

Energy-conserving cold chain with ambient temperature, path flexibility, and hybrid fleet: formulation and heuristic approach

Cold chain logistics networks represent intricate systems that require harmonisation of their influence on the economy, environment, and society. However, simultaneously achieving these goals is hard. This paper defined a comprehensive model aiming to achieve a tradeoff of these goals related to cost efficiency, product quality, delivery timeliness, and environmental impacts. Meanwhile, the influences of ambient temperature, path flexibility, and hybrid fleet on the proposed dual-mode location-routing problem-based cold chain logistics (DMLRPCCL) are analyzed. A meticulously crafted hyper-heuristic framework employing Q-learning has been developed to address the complexity of cold chains to obtain high-quality solutions. The numerical study has shown that the proposed model can analyze various scenarios for perishable products and evaluate their impact on cost, emissions, and quality. The proposed algorithm is efficient and effective in achieving competitive results compared to three tailored algorithms. Extensive analyses are performed to empirically assess the effect of path flexibility, hybrid fleet, and ambient temperature on the DMLRPCCL planning. Several managerial insights are presented.

Well-to-wheel carbon footprint and cost analysis of gasoline, diesel, hydrogen ICE, hybrid and fully electric city buses

Carbon emissions in mobility, as one of the primary causes of global warming, are regulated by various organizations with different legislations. Different energy sources and power-train solutions are used to comply with these constraints. Hydrogen-fueled, fully electric, and hybrid vehicles are at the forefront of these technologies. Within the scope of this study, gasoline-, diesel-, and hydrogen-fueled internal combustion engines, and fully electric and serial hybrid 18-m city bus vehicles were modeled. Comprehensive analyses of emissions and costs, considering both the entire energy production and consumption cycles for various vehicle types were conducted. Models that are primarily based on fuel consumption data show that while fully electric vehicles currently have the lowest emissions, hydrogen-fueled vehicles can play a more prominent role soon with the increasing production of green hydrogen. For the first step of hydrogen implementation in the industry, H2ICE is a promising for both reduced carbon emissions in mobility and cost-effectiveness. If the forecasted hydrogen production and distribution scenario is adopted by industrial and energy organizations, it is evident that by the year 2030, more environmentally friendly operation can be achieved particularly in the context of public transportation. Embracing this approach is likely to lead to positive environmental sustainability impacts in future transportation systems.

A Bayesian analysis of adaptation of mountain grassland production to global change

Abstract In mountains, grasslands managed for livestock production sustain local economies, culture and identity. However, their future fodder production is highly uncertain under climate change: While an extended growing season may be beneficial, more frequent and intense summer droughts could also reduce fodder quantity and quality. Land use and land cover (LULC) changes are another major driver of grassland biomass production, but combined effects of future land use transitions and climate change are rarely quantified. We modelled combined climate and LULC scenarios for grassland production of the Maurienne Valley (French Alps) by 2085. We built a Bayesian Belief Network (BBN) from long‐term grassland production monitoring data complemented with expert knowledge. We assessed the potential of two candidate adaptations, intensification as an incremental solution and silvopastoralism as a transformative solution to compensate combined impacts of two climate scenarios and three land use change scenarios. Total biomass production was far more sensitive to LULC than to climate scenarios. Production losses were largest under the conservation LULC scenario (−28% on average between 2020 and 2085), followed by the tourism development scenario (−7%) and the business‐as‐usual scenario (+3%). Climate change under representative concentration pathways (RCP) 8.5 altered the seasonality of production by increasing potential production from May to July while decreasing summer regrowth. Synthesis and applications: Changes in LULC are more decisive for global biomass production than climate change. However, under the most extreme climate change scenario (RCP8.5), the seasonal shift in production and increased interannual variability threaten the current grass‐based protected designation of origin (PDO) production system. Only the intensification adaptation solution showed significant gains in total biomass production. Still, the silvopastoralism would require less investment compared to the intensification and have a similar efficiency when assessing the gains of biomass by the surface concerned with adaptation solutions. Along with decreased total annual production due to decreasing grassland area compounded by more extreme climate change, the seasonal shift in production and increased interannual variability threaten the current grass‐based PDO production system. Further Bayesian modelling co‐developed with local stakeholders and experts could greatly contribute to adaptation planning of the regional production system.

Optimization of Renewable Energy Hydrogen Production Systems Using Volatility Improved Multi-Objective Particle Swarm Algorithm

Optimizing the energy structure to effectively enhance the integration level of renewable energy is an important pathway for achieving dual carbon goals. This study utilizes an improved multi-objective particle swarm optimization algorithm based on load fluctuation rates to optimize the architecture and unit capacity of hydrogen production systems. It investigates the optimal configuration methods for the architectural model of new energy hydrogen production systems in Xining City, Qinghai Province, as well as the internal storage battery, ALK hydrogen production equipment, and PEM hydrogen production equipment, aiming at various scenarios of power sources such as wind, solar, wind–solar complementary, and wind–solar–storage complementary, as well as intermittent hydrogen production scenarios such as hydrogen stations, hydrogen metallurgy, and continuous hydrogen production scenarios such as hydrogen methanol production. The results indicate that the fluctuation of hydrogen load scenarios has a significant impact on the installed capacity and initial investment of the system. Compared with the single-channel photovoltaic hydrogen production scheme, the dual-channel hydrogen production scheme still reduces equipment capacity by 6.04% and initial investment by 6.16% in the chemical hydrogen scenario with the least load fluctuation.

Análise da Produção Científica em Oncológicos na Base de Dados Scopus

According to data from the United Nations, cancer is the second leading cause of death in the world. Due to its chemical properties, technetium-99m remains the most used radioisotope in the diagnosis of cancers. Thus, the present work analyzed through bibliometrics the characteristics of the world scientific production on technetium-99m, presented in articles from the Scopus database between 2001 and 2021. The search terms “(99mtc OR technetium OR technetium-99m) were used. AND (cancer OR tumor)”, with the filters “Title” and “Summary” in the search fields united by the Boolean operator “OR”. Then, the data were exported so that the construction and visualization of bibliographic networks could be carried out using the VOSviewer® program. The analysis of articles and journals showed that, in the number of publications, the United States, the Journal of Nuclear Medicine, The Netherlands Cancer Institute and the author Mishra, A.K. (India). Regarding the analyzes analyzed with VOSviewer®, the following stand out: the author Shuang Liu (co-citation of authors); and the words article and human (co-occurrence of keywords); Fan Wang (bibliographic coupling). It is hoped that this study will help stakeholders who have carried out research on technetium-99m radiopharmaceuticals to understand the scenario of scientific production.

Metabolic Engineering of Corynebacterium glutamicum for the Production of Flavonoids and Stilbenoids.

Flavonoids and stilbenoids, crucial secondary metabolites abundant in plants and fungi, display diverse biological and pharmaceutical activities, including potent antioxidant, anti-inflammatory, and antimicrobial effects. However, conventional production methods, such as chemical synthesis and plant extraction, face challenges in sustainability and yield. Hence, there is a notable shift towards biological production using microorganisms like Escherichia coli and yeast. Yet, the drawbacks of using E. coli and yeast as hosts for these compounds persist. For instance, yeast's complex glycosylation profile can lead to intricate protein production scenarios, including hyperglycosylation issues. Consequently, Corynebacterium glutamicum emerges as a promising alternative, given its adaptability and recent advances in metabolic engineering. Although extensively used in biotechnological applications, the potential production of flavonoid and stilbenoid in engineered C. glutamicum remains largely untapped compared to E. coli. This review explores the potential of metabolic engineering in C. glutamicum for biosynthesis, highlighting its versatility as a cell factory and assessing optimization strategies for these pathways. Additionally, various metabolic engineering methods, including genomic editing and biosensors, and cofactor regeneration are evaluated, with a focus on C. glutamicum. Through comprehensive discussion, the review offers insights into future perspectives in production, aiding researchers and industry professionals in the field.

Privacy-preserving pathological data sharing among multiple remote parties

The sharing of pathological data is highly important in various applications, such as remote diagnosis, graded diagnosis, illness treatment, and specialist system development. However, ensuring reliable, secure, privacy-preserving, and efficient sharing of pathological data poses significant challenges. This paper presents a novel solution that leverages blockchain technology to ensure reliability in pathological data sharing. Additionally, it employs conditional proxy re-encryption (C-PRE) and public key encryption with equality test technology to control the scope and preserve the privacy of shared data. To assess the practicality of our solution, we implemented a prototype system using Hyperledger Fabric and conducted evaluations with various metrics. We also compared the solution with relevant schemes. The results demonstrate that the proposed solution effectively meets the requirements for pathological data sharing and is practical in production scenarios.

PRODUCCIÓN DE JAMAICA (Hibiscus sabdariffa L.) EN MÉXICO: RETOS Y PROSPECTIVA ESTRATÉGICA

&lt;p&gt;&lt;strong&gt;Background.&lt;/strong&gt; Mexico has favorable agroclimatic conditions for the development of roselle, a crop with high world demand; however, it has low yields and domestic consumption relies more than 50% on imports. &lt;strong&gt;Objective. &lt;/strong&gt;To describe the national production scenario and identifying the main challenges, as well as the strategic factors to increase potential of this crop in Mexico. &lt;strong&gt;Methodology.&lt;/strong&gt; The research was conducted in three phases, using a descriptive, correlational and explanatory approach. Qualitative and quantitative information was collected through documentary review, in-depth interviews and panel of experts. The methods of analysis were descriptive statistics, correlational statistics and structural analysis MICMAC (Matrice d' Impacts Croisés Multiplication Appliqués à un Classement). &lt;strong&gt;Results.&lt;/strong&gt; It was found that, in 2021, the per capita consumption was 137.58 g. During the period 2009-2019, the national production of roselle showed an increase of 56.2%, which is attributed to intensive growth. The high demand for labor in the harvest, the low prices of imported roselle, and the lack of government and scientific attention, impossibility of development of this crop. &lt;strong&gt;Implications.&lt;/strong&gt; This study helps to understand the productive dynamics of roselle cultivation in Mexico as well as provides information and strategies to enhance its development. &lt;strong&gt;Conclusion.&lt;/strong&gt; The key factors for the evolution of roselle production in the long term are differentiated public policies, competitiveness (substitutes, quality, prices) and social organization.&lt;strong&gt;&lt;/strong&gt;&lt;/p&gt;

PSII-10 Development of an interdisciplinary undergraduate and graduate course in precision livestock farming systems

Abstract The modern livestock industry is increasingly adopting data, technologies, and automation into daily husbandry and management routines and decisions. These advances in precision livestock farming (PLF) enable improved financial margins, sustainability, efficiency, and animal productivity and welfare. However, there is currently a gap between the engineers and data scientists designing the technologies and the animal scientists and caretakers using them. At North Carolina State University a novel course on PLF Systems for undergraduate and graduate students was developed in the Department of Animal Science. Through lecture delivery, livestock production scenarios, scientific literature, and data-based homework assignments students explored data collection, management, analysis, and data-based decision making. Students gained hands-on experience with a variety of sensor types and signal processing through lab-based activities. Basic hardware and software development concepts were explored during an Arduino-based microcontroller activity. The course was developed and refined using student feedback to include additional sensor and lab-based days and additional in-class supported activities utilizing Excel for data manipulation, processing, and presentation. Self-reported student learning results were collected across two semesters (19 students; 18 Animal Science, 1 Biological Engineering) with84% of students indicated the course was effective in increasing their ability to evaluate and implement technology in livestock production systems and 74% of students reported increased knowledge of coding and software, as well as their ability to clean, analyze, and make sense of raw data. The topics and delivery methods implemented in this course could inform the basis for development of similar interdisciplinary PLF courses at other academic institutions.

Analysis, modelling, and financial perspectives of reverse mortgage implementation in Colombia

PurposeIncreased life expectancy in recent years, together with the downward trend in fertility rates, will accelerate the aging of the Latin American population (Flamini and et al., 2018) [1]. This demographic change represents a problem for pension systems as the economic capacity to finance the retirement of the population could be insufficient in the future. This creates a favorable scenario for new financial products, including reverse mortgages. This study determines, from the supply approach, the potential of reverse mortgages in the main cities of Colombia as a complement to the financing of old age according to the guidelines of Benavides et al. (Benavides Franco et al., Jan. 2021) [2]. MethodologyThe following variables were used: housing prices, interest rates, mortality rates, and the consumer price index. The econometric testing simulates the possible paths of these variables, estimates the probability of occurrence of the paths, and calculates the expected losses of bidding banks. FindingsThe results show that reverse mortgages are a good complement to Colombia's pension system and confirm the feasibility of implementation at city level. It is recommended that the State stimulate the growth of this market and improve the corresponding regulatory framework. OriginalityThis study confirms the hypothesis that the reverse mortgages are a good complement to the pension system with city-level data. Specifically, it uses housing prices and mortality records from the main cities of the country (Bogotá, Cali, and Medellín) to capture their idiosyncrasies.

DL-RSM: Deep learning-integrated Response Surface Methodology for positive and negative-ideal environmental conditions estimation for crop yield

Understanding the most suitable and unsuitable environmental scenarios for crop production is critical to ensuring food security and sustainability. In this direction, the presented work proposes a novel approach, DL-RSM, to identify the optimized levels of environmental factors for wheat yield by integrating the Deep Learning technique with Response Surface Methodology (RSM). The uniqueness of this approach lies in its utilization of a 1-Dimensional Convolutional Neural Network model for response surface modelling. Additionally, the study has investigated the combination of numerical methods-based partial derivative calculation with a deep learning model. Specifically, our approach incorporates a symmetric difference quotient-based method for calculating partial derivatives, ultimately leading to the determination of optimal parameter values. Besides, multiple positive and negative ideal solutions are obtained from the modelled response surface using a modified gradient-based method. The effectiveness of our approach is illustrated through a case study on finding the optimized parameter values for the district-wise wheat yields of the Indo-Gangetic plains of India. The study results demonstrate the combinations of monthly rainfall levels and min. and max. temperature variations correspond to maximizing and minimizing wheat yield in the target region. The presented results provide significant insights into the relationship between wheat yields and the considered environmental factors that have not been sufficiently covered in the existing literature. The proposed methodology can benefit agricultural scientists, policymakers and farmers by offering an innovative approach to maximize crop yield and minimize resource utilization. Moreover, the study findings provide novel insights into the development of similar optimization strategies for other crops and systems.

New Perceptions of Ancient Commerce Driven by Underwater Ancient Site Investigations: A Case Study of Xinfeng River Basin

In the 1950s and 1960s, to address the flooding issues and power shortage that hindered national construction, the Xinfeng River hydropower plant was planned and built to prevent floods, store water, and generate electricity. Consequently, many ancient ruins in the study area were drowned, including ancient post roads, channels, villages, towns, bridges, and other relic sites. By checking historical data and adopting integrated underwater acoustic detection, we conducted a comprehensive cultural-relics survey on the flooded area under Wanlv Lake in the Xinfeng River Basin. A side-scan sonar detection of the underwater relics within the flooded area confirmed the spatial distribution of cultural relics in the Xinfeng River Basin. It portrayed ancient people’s production and life scenarios, outlined the migration and trade history within the region and beyond, and contributed to the enrichment of the literature and understanding of ancient shipping and trade in the basin.