Exploitable Research Articles

Genetic diversity of food-medicinal Lycium spp. in China: Insights from chloroplast genome

ObjectiveGoji (fruits of Lycium spp.) is commonly consumed as food and medicine. The increasing market demand for goji has led to its wide cultivation and broad breeding, which might cause loss of genetic diversity. This study aims to uncover the genetic diversity of the cultivated and wild Lycium. MethodsThe chloroplast genome (CPG) of 34 accessions of Chinese food-medicinal Lycium spp., including the popular cultivars and their wild relatives, was re-sequenced and assembled, based on which the genetic diversity was evaluated. ResultsSequence structural comparison shows that CPG is comparatively conserved within species. Phylogenetic analysis indicates that CPG is sufficient for the discrimination of Lycium species; combined with nuclear ribosomal internal transcribed spacer (Nr ITS) sequences, materials with mixed genetic backgrounds can be identified. Nucleotide diversity analysis reveals that the modern cultivars are probably with a common maternal parent, while the wild accessions are with higher level of genetic diversity. ConclusionFor the first time this study reveals the intraspecies genetic diversity of Lycium spp. using CPG, highlighting the urgent conservation demand of wild genetic resources of Lycium. Our study also demonstrates that CPG provides crucial evidence for identification of Lycium species with mixed genetic backgrounds and highlights the importance of the wild relatives in genetic diversity conservation. This CPG-based technology will contribute to the sustainable development of medicinal plants broadly.

Forecasting demands of blood components based on prediction models

BackgroundAn adequate blood supply is an important guarantee for saving lives and protecting health. In order to manage the blood supply more effectively when the condition of demand and supply are uncertainty, it is very important to forecast the demands of blood resources. Materials and methodsSARIMAX model and LSTM model were integrated into the prediction system of blood station. The collection and supply data of blood components was directly imported into the forecasting models to achieve automatic data update and model update. The forecasting daily demands of apheresis platelets, washing red blood cells (RBCs), suspended RBCs and plasma were recorded from January to June 2023 and compared with real data. ResultsThe prediction models had good forecasting performances. In the goodness of fit results of apheresis platelet model, the maximum value of coefficient of determination (R2) could reach 87.6%, and the minimum value of the mean absolute percentage error (MAPE) was only 0.0037. The predicted data of washing RBCs could be basically fitted, and the MAPE was 0.0121. For the prediction of suspended RBCs, the R2 was greater than 66%, and the MAPE could be 0.0372. The plasma model generated very high goodness of fit results, with R2 of over 90% and the lowest MAPE of 0.0394. ConclusionThe forecasting models, which predicts future demands of different blood components based on historical data, can help managers to overcome the challenges of blood stock control more effectively, thereby reducing blood waste and blood shortages.

Larval performance of Zophobas morio (F.) (Coleoptera: Tenebrionidae) on various diets enriched with post-distillation residues and essential oils of aromatic and medicinal plants

The increasing demands for resources driven by the global population necessitate exploring sustainable alternatives for affordable animal protein over the use of traditional protein sources. Insects, with their high protein content, offer a promising solution, especially when reared on agricultural post-distillation residues for enhanced sustainability and cost-effectiveness. We assessed the development of Zophobas morio (F.) (Coleoptera: Tenebrionidae) larvae on diets enriched with essential oils and post-distillation residues from Greek aromatic and medicinal plants. Two aromatic plant mixtures (A and B) were examined. Mixture A consisted of post-distillation residues, while Mixture B incorporated these residues along with essential oils. Insect rearing diets were enriched with different proportions (10, 20, and 30 %) of these mixtures, with wheat bran serving as the control. Enrichment positively influenced larval development without compromising survival. Larval weight remained unchanged with Mixture A, but improved with Mixture B. No adverse effects were detected in the case of the enriched diets, although higher concentrations of Mixture B prolonged development time.

Evolutionary Dual-Stream Transformer.

Vision transformers (ViTs) are rapidly evolving and are widely used in computer vision. However, high-performance ViTs require many computations, which limit their further development in the vision field. In this article, a novel evolutionary dual-stream transformer (E-DST) model is proposed to alleviate the computational resource demand problem. A hybrid attention mechanism structure is proposed for a DST model. The DST model uses a dual-branch structure to fuse convolutional and transformer features. Combining the features learned by the transformer and convolution effectively saves model computational resources. In addition, an evolutionary optimizer is proposed to optimize the parameters of the model. The excellent search ability of the evolutionary algorithm is utilized to optimize the transformer model parameters. The convergence of the evolutionary optimizer is proved in this article. In addition, the proposed E-DST model is experimentally compared with a variety of classic models and their deformations based on three datasets. And, the evolutionary optimizer proves its generality in convolutional and recurrent neural networks. The experimental results show that the E-DST model can effectively reduce computational resources and that the evolutionary optimizer can solve large-scale optimization problems. In conclusion, our proposed method is feasible and effective.

Os Fundos de Investimento em Cadeias Produtivas Agroindustriais (Fiagro) e a problemática da exploração econômica de imóveis rurais por estrangeiros no Brasil

This article aims to analyze the Investment Funds in Agroindustrial Chains (Fiagro) as an alternative legal structure to promote the private agribusiness financing system and, mainly, the problem of their use in Brazil for the economic exploitation of rural properties by foreigners. Law no. 14,130/2021, mostly aimed at private financing of agribusiness through access to the volume of resources available in the capital market, brought the possibility for Fiagro to invest in rural properties (i.e. acquire and lease), which directly influences the problem presented. In theory, foreigners can be shareholders in a Fiagro and, through it, explore rural properties in Brazil. It is under this premise, therefore, that this article intends to analyze, using the deductive method, the problem surrounding the acquisition of rural properties by foreigners in Brazil in order to, from the perspective of the introduction of Fiagro, as well as the possibility of elimination or at least mitigation of the restrictions imposed by Law no. 5,709/91 and CF/88 through this instrument.

Evolution of New Energy Minerals Trade Pattern and Analysis of China’s Status Evolution

Copper, cobalt, nickel as the key raw materials for the new energy automobile industry, the supply and demand of resources and international trade are largely affected by the world economy and political pattern, and the risks and vulnerabilities of the resource industry chain are highlighted. Using the method of complex network to analyze the trade network of three kinds of mineral resources from the perspective of industrial chain, the following conclusions are drawn: (1) the global trade network of three kinds of new energy minerals in the whole industrial chain all presents the characteristics of complexity and connection enhancement, and has the characteristics of the network of the small world; (2) China has become an important hub in the global trade network of copper, cobalt, and nickel, and has a stronger ability to control the trade of other countries.

Prediction of Enterprise Human Resource Demand Based on Iot and Data Mining Technology

This paper analyzes the prediction model of enterprise human resource demand based on Internet of Things (IoT) technology and data mining technology. It also analyzes the impact of the company’s growth scale and other key factors on the demand for human resources, tries to establish a coupling factor model of enterprise development and economic benefits, and then analyzes and forecasts the enterprise’s personnel structure and quality structure. The experimental results show that the optimized human resource demand forecasting model integrates the advantages of the grey system model in data processing, can mine the inherent laws of unorganized data information, and provides a certain convenience for forecasting. Through the linear mapping and processing of sample data, the input and output reflect a kind of correlation, thus changing the fault tolerance of information, making the prediction in the calculation process more accurate, and its comprehensive accuracy can exceed 92.5%.

Recent cutting-edge approaches to the integration of solid-liquid extraction with deep eutectic solvents: Toward a greener procedure for biomass valorization

As the global demand for sustainable and renewable resources intensifies, there is an imperative to explore innovative technologies for biomass valorization. This review delves into a promising avenue, providing an overview of green approaches that combine solid-liquid extraction (SLE) with a type of solvent known as deep eutectic solvents (DESs) in a synergistic manner. SLE, a conventional method for isolating bioactive compounds from biomass, is recognized for its effectiveness in sample preparation. However, it often involves the use of environmentally harmful solvents. Subsequently, DESs have emerged as an eco-friendly alternative to traditional solvents. Composed of naturally occurring and benign components, these DESs exhibit unique properties that render them suitable for various extraction processes. The integration of SLE with DESs introduces a novel approach to biomass valorization. This review explores the synergistic effects between SLE and DESs to optimize extraction yields, improve selectivity, and reduce overall energy consumption. Furthermore, the nature of DESs aligns with the principles of green chemistry, positioning them as a sustainable alternative to traditional solvents.

A progress of Public-Private Partnerships in São Paulo's housing policy: challenges and conflicts in accessing decent housing

The article aims to analyze the advancement of Public-Private Partnerships (PPPs) in housing for social interest in the central area of São Paulo. Based on a literature review and document research, it was found that such partnerships have presented limitations in providing housing for the low-income population, leading to conflicts and displacements in strategic areas of interest to the real estate market. This facilitates investor access to housing services and allows construction companies to use urban planning tools for economic exploitation and the mobilization of public lands in the city. Housing PPPs come in a context of weakened housing policies and increased private sector involvement in public services, driven by neoliberal thinking. This situation raises questions about the effectiveness of PPPs in meeting the needs of vulnerable populations living in inadequate or deficient housing. Financing difficulties for lower-income families and the displacements carried out for new housing developments have led to the relocation of local residents and workers, some of whom have been pushed into environmentally fragile and peripheral areas. As a result, there is a growing role of the private sector in decisions regarding the production of housing for social interest, which not only fails to extend its reach to the poorest groups but also creates problems related to urban density and urban sprawl. These issues need to be addressed to promote more just and sustainable cities in their social, environmental, and economic aspects, committed to reducing inequalities, socio-spatial segregation, and promoting democratic governance in cities.

The Historical Analysis of National Integration in Pakistan: A Case Study of General Pervez Musharraf Era

National cohesion encapsulates political, social, cultural, and economic Integration. Ever since its creation, Pakistan has been tormented by the problem of national Integration and competing regional demands within the context of nation or State. The relations between the center and the provinces have never been exemplary. During the last 75 years, constitutional and political upheavals have increased misunderstanding amongst the provinces, and an atmosphere of mistrust exists within the center. Various national political parties and leaders have been highlighting widespread dissatisfaction with the affairs of the state institutions, regional disparities, economic exploitation, centralization of authority, and finances in the country. Successive regimes, because of vested agendas, have never succeeded in achieving complete national cohesion. Consequently, the threat to national Integration from within remains alive and has increased manifolds. This case study concludes shortcomings in national cohesion by the historical analysis of National Integration in Pakistan up to General Pervez Musharraf, and it suggests dynamic and viable measures to strengthen the federation and enhance national cohesion, but it further needs to be enhanced by resolving the above-mentioned issue of National Integration on a priority basis. This study also suggests certain recommendations in the light of research findings.

Practical design of reservoirs for rainwater use in buildings in Brazil: behavioural analysis and modelling

Abstract The new version of NBR 15527 (ABNT 2019) determines that any methodology used for the design of rainwater reservoirs must be performed considering the demand for rainwater resources. Thus, the objective of this study was to develop mathematical models for the design of rainwater reservoirs in residential buildings for all Brazilian states. Different use scenarios were simulated, which included drinking water demands of 100, 150, 200 and 300 litres per capita and rainwater replacement for drinking water at rates of 25, 35, 45 and 55%, according to rainfall data from the last decade. The optimal and maximal volumes of each scenario were calculated using the yield after spill (YAS) behavioural method. Based on the values of the volumes obtained, the studied municipalities were grouped, and for each group, the practical models were adjusted and evaluated using the coefficient of determination (R²) and the root mean square error (RMSE). A good adherence of the models to the observed data was observed, which simplified the estimation of the volume for rainwater reservoirs; practical applications demand that designs use discreet daily rainfall values.

Energy Marketing and Fiscal Regulation of a Competitive Energy Efficiency System

Introduction. Developing and implementing the principles of the energy-saving approach concept actualizes the need to define energy marketing tasks and fiscal regulation tools for energy conservation to increase the efficiency of using resources in the energy sector.
 Aim and tasks. The aim of this study is to form and substantiate the expediency of implementing directions for energy marketing development and fiscal regulation of implementing energy-saving measures to achieve the goals of national economic recovery and large-scale energy modernization.
 The results. The main tasks of energy marketing in monitoring the current world environment based on information and communication technologies have been defined and substantiated, and that should become a source of competitive advantage in the electric energy market and obtain significant income for market participants. It has been proven that using oligopoly models to determine the equilibrium condition of the electric energy market will make it possible to form a corrective managerial influence on the development of a competitive energy industry. With a 3-fold increase in the demand parameter, it has been established that the electricity market reaches equilibrium under the equilibrium model of supply functions with larger electricity production volumes and lower prices than in other models. It has been proposed to introduce tools for fiscal regulation by introducing energy-saving technologies into a single system of solutions to increase energy efficiency and energy saving.
 Conclusions. Analysing and generalizing the features of energy market participants’ interaction using a wide range of oligopoly models made it possible to develop recommendations for implementing strategic security-related tasks. If these tasks are not realized, the risks of losing energy independence will increase, and the economic potential necessary for the restoration and further development of the national economy will continue to be lost based on the principles of sustainable development and a systematic approach to setting and achieving the goal of the national energy-saving policy. The feasibility of introducing tools for budget regulation is also justified, which will create a robust creative basis for implementing an effective strategy for managing the demand for energy resources.

The effect of different temperature in membrane-less microbial fuel cell under series and parallel circuit mode for power generation and bioremediation

Demand for energy resources is increasing rapidly, leading to excessive exploitation of fossil fuels. The production of chicken, which is a popular source of protein, generates a huge amount of waste. Microbial fuel cells (MFC) have the potential to generate clean, sustainable, and environmentally benign electricity by utilizing electrogenic bacteria present in chicken manure (CM), while also decreasing the amount of waste. The present study was conducted to assess the effect of different temperatures and numbers of chambers in series and parallel circuits on the performance of membrane-less MFCs (ML-MFCs). The central composite design (CCD) based on response surface methodology (RSM) was applied to optimize the performance of ML-MFCs in series and parallel circuits, with a focus on chemical oxygen demand (COD) removal efficiency (R2 = 0.958 and 0.967), biomass (R2 = 0.995 and 0.836), and power density (R2 = 0.958 and 0.825). The study revealed that the highest COD removal (series: 89.554%, parallel: 84.994%), biomass (series: 1.095 mg/L, parallel: 2.267 mg/L), and power density (series: 0.551 W/m2, parallel: 0.360 W/m2) were achieved when the pre-treatment temperature was 40 °C. The best ML-MFC condition was plotted on the polarization curve in order to analyze the nature of ML-MFC. Findings of this study suggest that ML-MFCs have great potential for electricity generation and waste reduction, and the optimization of operating conditions can enhance their performance.

Natural resource development, economic policy uncertainty and urban residents’ consumption in China: a nonlinear ARDL and time-varying parameter vector autoregressive with stochastic volatility approach

AbstractIncreased risks of economic policy uncertainty and overexploitation of natural resources exist in China. At the same time, the growth rate of urban residents’ consumption has generally declined. The paper analyses the role of economic policy uncertainty (EPU) and natural resource exploitation on the urban residents’ consumption in China. Based on the data from the first quarter of 2002 to the third quarter of 2021, the paper uses a nonlinear autoregressive distributed lag model to verify the asymmetric effects. Then the paper constructs a time-varying parameter vector autoregressive model with stochastic volatility term to analyze the nonlinear responses. Impulse response analysis was used to further explain the relationship between the three. The negative impact of rising EPU on urban residents’ consumption is larger than its reduction. Negative shocks to natural resource development increase the urban residents’ consumption. Positive shocks reduce the urban residents’ consumption. There is a time-varying non-linear effect of EPU and natural resource development on urban residents’ consumption in China. The negative impact of EPU on urban consumption has been further exacerbated by major crises such as the financial crisis, COVID-19 and the post-crisis period. The negative impact of natural resource development diminished after the government introduced industrial upgrading policies and environmental regulations. This study provides constructive suggestions for the optimization of economic policies and the improvement of urban consumption. This study also enriches consumer theory and provides new evidence for the resource curse hypothesis.

The information needs of users in the metaverse communities: a grounded theory study

PurposeThis article aims to understand users' information needs in the metaverse communities and to analyze the similarities and differences between their information needs and those of users in Internet communities.Design/methodology/approachThis study conducted semi-structured interviews with users in the metaverse communities to gather raw data. Grounded theory research methods were employed to code and analyze the collected interview data, resulting in the extraction of 40 initial concepts, 15 subcategories and 5 main categories. Based on Maslow’s hierarchy of needs theory, this paper constructs the hierarchical model of users' information needs in the metaverse communities. It compares the differences between users' information needs in the metaverse and Internet fields.FindingsThe user’s information needs in the metaverse communities are divided into two types: deficiency needs and growth needs. Deficiency needs have two levels. The first level is the demand for basic information resources. The second level is the users demand for information assistance. Growth needs have three levels. The first level is the need for information interactions. The second level is the need for community rules. The ownership information in the community rules can provide proof of user status, assets and so on. The third level is the need for users to contribute and share their own created information content.Originality/valueThis article presents the latest research data from in-depth interviews with users in the metaverse communities. It aims to help builders and managers of metaverse communities understand users' information needs and improve the design of virtual communities.

Application of big data analysis in water pollution monitoring

Contemporarily, the quick development of an abundant amount of big data analysis technologies has brought great convenience to individuals' everyday existence. In terms of environmental protection, especially water pollution monitoring, this technological progress is particularly critical. As the global demand for clean water resources grows and global industrialization intensifies pollution of the water environment, the adoption of advanced data analysis technologies has become critical. Among the vast array of machine learning architectures, three particularly stand out due to their significance and widespread adoption: the artificial neural network (ANN), which serves as a foundational pillar in understanding complex data patterns; the multi-layer perceptron neural network (MLPNN), a sophisticated evolution that allows for deeper computations and learning; and the adaptive neuro-fuzzy inference system (ANFIS), which brilliantly combines neural and fuzzy logic principles for intricate problem solving. These models not only have high accuracy due to their wide application, but they still have their own limitations. This article aims to introduce the methods, basic principles, and application scenarios of these models. In addition, this article also compares the advantages and limitations of these machine learning models, thereby providing some new ideas for future improvements and innovations in model algorithms, application scenarios, and integration.

Advances in zero liquid discharge multigeneration plants: A novel approach for integrated power generation, supercritical desalination, and salt production

In light of the escalating worldwide demand for energy and water resources, the imperative for developing sustainable multigeneration systems has gained prominence in recent research and development. This study aims to investigate the feasibility and performance of a novel multigeneration plant operating at supercritical conditions to simultaneously generate freshwater, power, and dry salt as a by-product while eliminating liquid discharge. This approach offers a promising solution to address the interconnected challenges of energy and water sustainability. The theory contends that combining supercritical desalination with power generation increases energy efficiency and water production rates, surpassing conventional systems. Therefore, a model is developed employing a supercritical once-through boiler capable of supplying the necessary heat duty required for steam generation from the integrated desalination plant, producing power. Additionally, multiple heat exchangers and flash separators are implemented, enhancing freshwater productivity and obtaining dry salt, eliminating the need for brine waste disposal. A thorough sensitivity analysis is conducted utilizing a robust model developed on Aspen HYSYS to ascertain the optimal operational parameters of the proposed plant. The findings of this study underscore the potential of concurrent production of 1.65 million m3/year of freshwater, 302.5 GWh of electricity, and 64,845 ton/year of dry salt for 0.38 $/m3, 0.07 $/kWh, and 0.02 $/kg, respectively. In conclusion, this research highlights the prospects of revolutionary progress in multigeneration systems for sustainable development.

The application of cellulosic‐based materials on interfacial solar steam generation for highly efficient wastewater purification: A review

AbstractThe world's population is growing, leading to an increasing demand for freshwater resources for drinking, sanitation, agriculture, and industry. Interfacial solar steam generation (ISSG) can solve many problems, such as mitigating the power crisis, minimizing water pollution, and improving the purification and desalination of seawater, rivers/lakes, and wastewater. Cellulosic materials are a viable and ecologically sound technique for capturing solar energy that is adaptable to a range of applications. This review paper aims to provide an overview of current advancements in the field of cellulose‐based materials ISSG devices, specifically focusing on their applications in water purification and desalination. This paper examines the cellulose‐based materials ISSG system and evaluates the effectiveness of various cellulosic materials, such as cellulose nanofibers derived from different sources, carbonized wood materials, and two‐dimensional (2D) and 3D cellulosic‐based materials from various sources, as well as advanced cellulosic materials, including bacterial cellulose and cellulose membranes obtained from agricultural and industrial cellulose wastes. The focus is on exploring the potential applications of these materials in ISSG devices for water desalination, purification, and treatment. The function, advantages, and disadvantages of cellulosic materials in the performance of ISSG devices were also deliberated throughout our discussion. In addition, the potential and suggested methods for enhancing the utilization of cellulose‐based materials in the field of ISSG systems for water desalination, purification, and treatment were also emphasized.

Spatio-temporal metabolic rifts in urban construction material circularity

Global demand for resources currently exceeds Earth's carrying capacity. Representing a majority of global resource use, and associated environmental burdens, cities must address overconsumption by improving material circularity. This work explores the potential for the construction sector to reduce the indirect environmental impacts connected to increasing material circularity in the coming years. An urban metabolism simulation tool based on system dynamics and life cycle thinking is deployed to estimate the effects of circularization on environmental impacts. Illustrating with a case study of Montréal (Canada), impacts are disaggregated to supplier nations, provinces and territories. As material circularity increases over time, impacts decrease in the sub-national and international regions, but increase in the city due to the activities associated with second life valorisation. In supplier regions, especially Brazil, Mexico, and Norway, environmental impacts decrease between 80 and 100 % in all 18 impact categories by 2050. However, these decreases are found to be shared mostly among Canada's more developed trading partners, revealing an environmental justice risk for circular materiality to disproportionally favour the better-off. Five of the 18 categories did not undergo spatial burden-shifting, improving at all spatial levels in the assessment, while 13 showed decreased environmental impacts remotely at the expense of increased impacts within Montréal.

Future projection of water resources based on digitalisation and open data in a water-rich region: a case study of the city of Klagenfurt

Abstract Implementation of different strategies on the demand and supply side to deal with potential water scarcity is based on a comparison of future water demand and availability of water resources based on different scenarios of climate change and population growth. Especially, the Alpine region is characterised by many small and medium water supply systems (WSSs) having neither human resources nor time for advanced planning, requiring simple methods for estimating future development. Therefore, the aim of this work is to provide future projections of water demand, resource availability, and drinking water quality for an Alpine area based on simple approaches with minimal data requirements. As the results of the case study show, linear and polynomial regression with precipitation and temperature data can illustrate the temporal variation of system input and drinking water temperature with sufficient accuracy and is suitable for an estimation of future development. The groundwater modelling, however, requires the consideration of a non-linear term depending on the depth to obtain reasonable results. Due to the usage of open-access data and the easy approaches developed and applied, a good transferability to other case studies is expected which can provide stakeholders a first assessment of the future need for action.