Resource Reservation Research Articles

Saline-alkali land reclamation boosts topsoil carbon storage by preferentially accumulating plant-derived carbon

Saline–alkali land is an important cultivated land reserve resource for tackling global climate change and ensuring food security, partly because it can store large amounts of carbon (C). However, it is unclear how saline–alkali land reclamation (converting saline–alkali land into cultivated land) affects soil C storage. We collected 189 adjacent pairs of salt-affected and cultivated soil samples (0–30 cm deep) from the Songnen Plain, eastern coastal area, Hetao Plain, and northwestern arid area in China. Various soil properties, the soil inorganic C (SIC), organic C (SOC), particulate organic C (POC), and mineral-associated organic C (MAOC) densities, and plant- and microbial-derived C accumulation were determined. Saline–alkali land reclamation inconsistently affected the SIC density but significantly (P < 0.001) increased the SOC density. The SOC, POC, and MAOC densities were predicted well by the integrative soil amelioration index. Saline–alkali land reclamation significantly increased plant-derived C accumulation and the plant-derived C to microbial-derived C ratios in all saline–alkali areas, and less microbial transformation of plant-derived C (i.e., less lignin degradation or oxidation) occurred in cultivated soils than salt-affected soils. The results indicated that saline–alkali land reclamation leads to plant-derived C becoming the dominant contributor of SOC storage. POC storage and MAOC storage were strongly linked to plant- and microbial-derived C accumulation, respectively, caused by saline–alkali land reclamation. Our findings suggest that saline–alkali land reclamation increases C storage in topsoil by preferentially promoting plant-derived C accumulation.

Statistical analysis of gold production in South Africa using ARIMA, VAR and ARNN modelling techniques: Extrapolating future gold production, Resources–Reserves depletion, and Implication on South Africa's gold exploration

South African gold mining is one of the main contributors to the country's economic growth and employment creation. Assessment of future gold production is pivotal for positioning the country's supply security and contribution to the projected global demand. In this study, we modelled and forecasted South African and global gold production trends (1990–2022) using the Autoregressive Integrated Moving Average (ARIMA), Vector Autoregressive (VAR), and Autoregressive Neural Network (ARNN) techniques. The study also evaluated the impact of annual productions on the collated reserves (2008–2021) and the contribution of resource–reserve conversion in sustaining gold reserves within the South African goldfields. The ARIMA (1,1,0) model, based on root mean square error (RMSE), mean absolute error (MAE), and mean absolute percentage error (MAPE), outperformed both ARNN (1,1) and VAR (2) methods. The forecast of the ARIMA model showed an increase in South Africa's gold production, with a compounded annual growth rate (CAGR) of ∼0.6%. The model also predicted an increase in global gold production, with CAGR of ∼2.2%. The analyses of reserves–production trends showed that most South African mining companies have been depleting their gold reserves due to production and were minimally converting resources to reserves, averaging at ∼2%/year from 2017 till present. The minimal conversion may also reflect the challenging mining conditions (such as mining depths and underground flooding) and the mining industry's socio-political dynamics. We demonstrated that, if the resource–reserve conversion factor is maintained (at ∼2%/year and above), the forecasted production may sustain the current reserves (at > 2000 t Au excluding tailings) but deplete ∼27 % of the resources to reserves by 2040. However, if the conversion factor continues to decline (to <1 %), the forecasted gold production will reduce the reserves to < 500 t Au with ∼3% of the resources converted to reserves.

A Study on the Dynamic Evolution Paths of Social Risks in PPP Projects of Water Environmental Governance—From the Vulnerability Perspective

The Chinese economy is transitioning from high-speed development to high-quality development, and water environmental governance is a key factor promoting economic transformation. Due to low returns and high investment in China’s water environmental governance, the PPP (public–private-partnership) model is often adopted. However, the PPP model has historically faced challenges adapting to local conditions in China, leading to social risks in the PPP projects of water environmental governance. To reduce these risks, this paper takes a vulnerability perspective, employing the system dynamics simulation method to explore the dynamic evolution process of social risks in the PPP projects of water environmental governance. The main results show the following: (1) the external manifestations of social risks during the construction and operation periods vary significantly, exhibiting notable fluctuations; (2) during the construction period, there is a surge in social risks followed by a returns to lower than normal levels, then a gradual upward trend; during the operation period, social risks initially decrease to a lower level before gradually increasing; and (3) city class, relevant legal systems, and resource reserves emerge as critical factors influencing vulnerability and social risks. The higher the city class, the lower the project vulnerability; the soundness of the legal system for PPP projects can effectively reduce vulnerability and social risks; sufficient resource reserves can reduce social risks. Based on the above findings, this paper proposes several suggestions aiming to reduce the vulnerability and social risks in PPP projects, optimize the process of water environmental governance, and further promote the sustainable development of water environmental governance and the high-quality economy of China.

Enteric parasites Cyclospora cayetanensis and Cryptosporidium hominis in domestic and wildlife animals in Ghana

BackgroundEnteric parasitic infections remain a major public health problem globally. Cryptosporidium spp., Cyclospora spp. and Giardia spp. are parasites that cause diarrhea in the general populations of both developed and developing countries. Information from molecular genetic studies on the speciation of these parasites and on the role of animals as vectors in disease transmission is lacking in Ghana. This study therefore investigated these diarrhea-causing parasites in humans, domestic rats and wildlife animals in Ghana using molecular tools.MethodsFecal samples were collected from asymptomatic school children aged 9–12 years living around the Shai Hills Resource Reserve (tourist site), from wildlife (zebras, kobs, baboons, ostriches, bush rats and bush bucks) at the same site, from warthogs at the Mole National Park (tourist site) and from rats at the Madina Market (a popular vegetable market in Accra, Ghana. The 18S rRNA gene (18S rRNA) and 60-kDa glycoprotein gene (gp60) for Cryptosporidium spp., the glutamate dehydrogenase gene (gdh) for Giardia spp. and the 18S rDNA for Cyclospora spp. were analyzed in all samples by PCR and Sanger sequencing as markers of speciation and genetic diversity.ResultsThe parasite species identified in the fecal samples collected from humans and animals included the Cryptosporidium species C. hominis, C. muris, C. parvum, C. tyzzeri, C. meleagridis and C. andersoni; the Cyclopora species C. cayetanensis; and the Gardia species, G. lamblia and G. muris. For Cryptosporidium, the presence of the gp60 gene confirmed the finding of C. parvum (41%, 35/85 samples) and C. hominis (29%, 27/85 samples) in animal samples. Cyclospora cayetanensis was found in animal samples for the first time in Ghana. Only one human sample (5%, 1/20) but the majority of animal samples (58%, 51/88) had all three parasite species in the samples tested.ConclusionsBased on these results of fecal sample testing for parasites, we conclude that animals and human share species of the three genera (Cryptosporidium, Cyclospora, Giardia), with the parasitic species mostly found in animals also found in human samples, and vice-versa. The presence of enteric parasites as mixed infections in asymptomatic humans and animal species indicates that they are reservoirs of infections. This is the first study to report the presence of C. cayetanensis and C. hominis in animals from Ghana. Our findings highlight the need for a detailed description of these parasites using high-throughput genetic tools to further understand these parasites and the neglected tropical diseases they cause in Ghana where such information is scanty.Graphical

Super absorbent polymer (SAP) on water‐salt transport in saline alkali soil: Effects of dosage, height and thickness

AbstractSoil salinisation is a pervasive form of land degradation posing a significant threat to the global environment. Saline soil, covering roughly 10% of the total land area, represents a crucial reserve of land resources. The use of super absorbent polymer (SAP) impacts capillary water movement through the soil because of its exceptional water absorption and retention capabilities. SAP is expected to influence the intricate water‐salt migration processes and their redistribution within soil. This study employed soil column experiments to investigate the impacts of varying SAP dosages (A), heights (B) and thicknesses (C) on soil water and salt transport in the Tianjin Binhai New Area, China. The main findings showed that: (1) average capillary water rise rate decreased with SAP dosage increase. The groundwater recharge trend in time was like that of capillary water rise height; (2) SAP usage increased water and salt content on the application layer and reduced surface soil salt accumulation; (3) the best SAP combination for application was 1.1% SAP at 17–18 cm from the groundwater level. This study provides basic effective SAP application strategies for preventing soil salinisation.

A REVIEW ON BANGLADESH-CHINA-INDIA-MYANMAR ECONOMIC CORRIDOR IN THE CONTEXT OF BANGLADESH’S INTEREST

Carrying out study on BCIM economic corridor is extremely important; because, Bangladesh is surrounded by India, Myanmar and China, where Bangladesh needs to maintain friendly relations with these three neighboring countries. China is rising rapidly in terms of socio-economic and political development in the South, Southeast and Northeast Asian region. China has the highest foreign currency reserves through which many countries of South, Southeast and Northeast Asia might be economically benefitted. Besides, India is a big country with huge population which might be a potential development partner of South and Southeast Asian countries. On the other hand, Myanmar has huge reserves of gas, oil and other mineral resources from which Bangladesh can be greatly benefitted. This study has found that the BCIM economic corridor is very significant for Bangladesh’s regional connectivity, people to people contacts, cultural exchanges, soft–power diplomacy and economic interests. This study has a geostrategic and development cooperation implication for the South Asian region. This study is an important policy paper for Bangladesh’s geopolitical and economic interests.

FinOps-driven optimization of cloud resource usage for high-performance computing using machine learning

Cloud computing is gaining popularity in high-performance computing applications. Its utilization enables advanced simulations when local computing resources are limited. However, cloud usage may increase costs and entail resource unavailability risks. This article presents an original approach that employs machine learning to predict long-term cloud resource usage. This enables optimizing resource utilization through appropriate reservation plans, reducing the associated costs. The solution developed utilizes statistical models, XGBoost, neural networks and the Temporal Fusion Transformer. Long-term prediction of cloud resource consumption, especially the Cloud Resource Usage Optimization System that is critical for prolonged simulations, involves using prediction results to dynamically create resource reservation plans across various virtual machine types for HPC on the Google Cloud Platform. Experiments using real-life production data demonstrate that the TFT prediction model improved prediction quality (by 31.4%) compared to the best baseline method, particularly in adapting to chaotic changes in resource consumption. However, it should be noted that the best prediction model in terms of error magnitude might not be the most suitable for resource reservation planning. This was validated by the neural network-based method, introducing an FR metric for forecast evaluation. Resource reservation plans were assessed both qualitatively and quantitatively, focusing on various aspects like a service-level agreement compliance and potential downtime. This paper is an extension of work originally presented during the International Conference on Computational Science — ICCS 2023, entitled “Long-Term Prediction of Cloud Resource Usage in High-Performance Computing”.

Signature-based Adaptive Cloud Resource Usage Prediction Using Machine Learning and Anomaly Detection

One of the challenges in managing cloud computing clusters is assigning resources based on the customers’ needs. For this mechanism to work efficiently, it is imperative that there are sufficient resources reserved to maintain continuous operation, but not too much to avoid overhead costs. Additionally, to avoid the overhead of acquisition time, it is important to reserve resources sufficiently in advance. This paper presents a novel reliable general-purpose mechanism for prediction-based resource usage reservation. The proposed solution should be capable of operating for long periods of time without drift-related problems, and dynamically adapt to changes in system usage. To achieve this, a novel signature-based ensemble prediction method is presented, which utilizes multiple distinct prediction algorithms suited for various use-cases, as well as an anomaly detection mechanism used to improve prediction accuracy. This ensures that the mechanism can operate efficiently in different real-life scenarios. Thanks to a novel signature-based selection algorithm, it is possible to use the best available prediction algorithm for each use-case, even over long periods of time, which would typically lead to drifts. The proposed approach has been evaluated using real-life historical data from various production servers, which include traces from more than 1,500 machines collected over more than a year. Experimental results have demonstrated an increase in prediction accuracy of up to 21.4 percent over the neural network approach. The evaluation of the proposed approach highlights the importance of choosing the appropriate prediction method, especially in diverse scenarios where the load changes frequently.

The Applications of WFEM in the Exploration of Medium-Depth Geothermal Resources

Medium-depth geothermal energy mainly consists of two types, hydrothermal and dry-heat rock. With huge resource reserves, its exploration and development are of great significance to the transformation of China’s energy structure and the realization of the goal of “Double-Carbon”. From the differences in the electrical characteristics between hydrothermal and hot dry rock geothermal resources, this project uses the numerical modeling of the wide field electromagnetic (WFEM) method as a tool to design a model of typical geothermal resources. Then, we summarize and analyze the detection capability of the WFEM by calculating the WFEM response under the conditions of different depths, resistivity values, thickness-to-depth ratios and other parameters. Moreover, aiming at the key problems faced by the WFEM in real applications, we discuss the factors affecting the detection accuracy and give solutions to improve the reliability of the detection results. Finally, the medium-depth geothermal energy detection in the Jiyang Depression of Shandong is presented as an example, showing how the WFEM detection technique was used with the inversion result profile obtained. By comparing the results of geomagnetic and seismic detection on the same survey line, it is demonstrated that the WFEM method has great potential in the exploration of medium-depth geothermal energy and can be the preferred method.

The Interests of the United States of America in the Persian Gulf Countries and Security Problems

Energy resources play an important role in the process of organizing the national security of a state, which is why establishing control over them is one of the most important goals. That is why the countries of the Persian Gulf are the subject of interest of the leading states of the world, the epicenter of the struggle to secure control over the natural resources of the region. The Persian Gulf is an area of special interest in this direction because it is where the largest reserves of hydrocarbon resources in the world are located today.The Persian Gulf region includes eight states, of which, except for Iran, all countries are Arab (Iraq, Bahrain, Qatar, the United Arab Emirates, Kuwait, Saudi Arabia, and Oman). The vast majority of them have the largest deposits of hydrocarbon resources, which determines the great interest in them in the world.Since oil and natural gas have an important place in the modern world economy, the role of countries with these natural resources in world politics is also great. Since the countries of the Persian Gulf have the largest reserves of natural gas and oil in the world, it can be said that the strategic importance of this region will increase in the coming decades.The relevance of the research is also determined by the fact that the successful pursuit of the above-mentioned states' own strategic interests is facilitated by systematic intelligence activities. Along with this, the relevance of the research is defined by the fact that on the international level from a military-political point of view, the region is important due to the possibilities of deployment of military bases in the target states, including through intelligence activities, and to identify the threats expected from them.

Deconstructing the organizational resilience of construction firms in major emergencies: A text mining analysis of listed construction companies in China

The COVID-19 pandemic has resulted in unprecedented huge losses for construction companies in terms of capital, labor, and project construction, highlighting a significant lack of organizational resilience (OR) within the construction industry. How to improve the OR of construction companies has become the key to resolve the crisis. However, there is a lack of systematic insights into the structure and dimensions of OR, as well as a gap in empirical evidence to explain how construction firms systematically construct OR. Therefore, this paper systematically identifies 19 resilience topics and their language descriptions by mining the resilience-related information in 1572 annual reports and expert interview data of listed companies in the Chinese construction industry during the COVID-19 pandemic, using a combination of the topic model and language model. Following the basic concept of OR, a framework of OR dimensions in the construction firms that integrates actions, resources, and capabilities is developed to uncover the complex resilience characteristics of construction firms. The results show that OR sought by listed companies in the construction industry consists of resilient actions, resilience resources, and resilience capabilities. Resilient actions stem from motivating, restraining, protecting, and exploring actions. The resilience resources include the resource reserves of organization, technology, and knowledge, while the resilience capabilities are dynamic capabilities that integrate prevention, response, adaptation, monitoring, perception, and recovery. The findings not only deconstruct the OR framework for construction companies to cope with crises, but also provide new paths for construction managers to cultivate the OR of companies in practice.

Analysis of Comprehensive Land Consolidation in Cultivated Land Reserve Resource Areas Based on Two-Level Geographical Unit Division

The scientific and reasonable division of geographical units of cultivated land reserve resource areas is an important foundation for comprehensive land consolidation (CLC). Saline–alkali land is an important cultivated land reserve resource, and is significant for ensuring food security. This paper constructs a two-level land consolidation index system for cultivated land reserve resource areas. The Kruskal graph theory clustering algorithm was used to divide the study area into four types of ecological zones. On the basis of ecological zones, the study area was further divided into three types of consolidation units. Finally, the spatial relationship between ecological zoning and land use types was clarified, and the classification distribution of land consolidation potential was determined through an analysis of the CLC of two-level geographical units. Da’an City, Jilin province, China, was selected as the study area. The results of this study show the following: (1) In Da’an City, the conservation priority areas are concentrated in the north, the development priority areas are concentrated in the central and southern areas, and the comprehensive upgrade areas and adjustment rebuilding areas are in the transition zones. (2) The CLC potential trend is low in the north but high in the south in Da’an City. This paper proposes a framework for a geographical unit delineation method for saline–alkali-enriched cultivated land reserve resource zones, and analyzes the spatial layout of ecological protection demands and land consolidation potential in Da’an City. The results and conclusions of this study will provide a reference for CLC in cultivated land reserve resource areas.

Awareness begets action: public climate attention and corporate green innovation

ABSTRACT In this study, we examine the effect and mechanism of public climate attention on corporate green innovation. We find that green innovation strengthens with increasing degrees of public climate attention. Moreover, the impact of public climate attention on green innovation is more significant when enterprises face more green development pressure and hold more resource reserves. Further investigation reveals that public climate attention contributes more to green innovation in samples of state-owned enterprises (SOEs), non-high-tech companies, and under more frequent extreme climate disasters. Finally, based on the differences in firm motivation for engaging in green innovation, we also explore the influence of public climate attention on firms’ substantive and strategic green innovations and find that public climate attention significantly contributes to both types of innovation. Our research results are of theoretical and practical significance for achieving dual-carbon goals and promoting sustainable social development and high-quality economic development.

Effect of rainfall on White Rhino calf survival depends on home range choice of the mother

Abstract Within African savannas, seasonal rainfall influences the survival of mammalian grazers by determining the availability and quality of food. The strength of these effects may, however, vary depending on the availability of reserve and buffer resources within the home range of an individual. From 1999 to 2019, 24% of the white rhino (Ceratotherium simum simum) calves born in Ithala Game Reserve died without a known cause. To explore this, we investigated the impacts of seasonal rainfall on calf survival, and whether these relationships were modified by the availability of woodlands (i.e., reserve resources) and bunch grasslands (i.e., buffer resources) within the home ranges established by the mothers. We found that nearly all of the deceased calves died during their first dry season after weaning had commenced. The likelihood of a calf surviving this period was positively influenced by rainfall during the dry season and negatively influenced by its duration. However, these effects were more pronounced when the availability of woodlands within the home range of the mother was high. Ultimately, calf deaths were caused by a combination of low dry season rainfall, long dry seasons, and the selection of home ranges with insufficient bunch grasslands by some mothers. With climate change models predicting increased dry season durations and a reduction in dry season rainfall, our results highlight future challenges for the conservation of white rhinos and other large herbivores.

In Situ Ca‐ and Mg‐ Codoped Biochar Derived from Tobacco Stem for Phosphate Adsorption and Desorption

AbstractPhosphorus is an important element for plant growth. The efficient use and recovery of phosphorus is crucial due to limited phosphate resource reserves. This study explored the potential application of an in situ Ca and Mg co‐doped biochar derived from tobacco stem to reclaim and reuse phosphate from aqueous solutions. We performed various batch adsorption experiments and industrial analysis based on different parameters. The findings indicate that biochar prepared using the raw material particle size range of 0.85–2 mm and pyrolyzed at 800 °C presented good pore structure and specific surface area. Ca and Mg elements in biochar exhibited great influence on its phosphate adsorption property. The maximum phosphate adsorption capacity of the tobacco stem‐based biochar was 54.66 mg/g, and the experimental data agreed with the Langmuir equation, suggesting monolayer adsorption. The adsorption process conformed to the pseudo‐second‐order kinetic equation, indicating that chemisorption was the dominant adsorption process and that the adsorption was controlled by intra‐particle diffusion. Furthermore, phosphate adsorbed on tobacco stem‐based in situ Ca and Mg co‐doped biochar was released under acidic, alkaline, and neutral conditions. Therefore, in situ Ca and Mg co‐doped biochar prepared from tobacco stems is a potential environmentally friendly and low‐cost adsorbent for phosphorus recovery.

PROACTIVE HORIZONTAL SCALING METHOD FOR KUBERNETES

Context. The problem of minimizing redundant resource reservation while maintaining QoS at an agreed level is crucial for modern information systems. Modern information systems can include a large number of applications, each of which uses computing resources and has its own unique features, which require a high level of automation to increase the efficiency of computing resource management processes.&#x0D; Objective. The purpose of this paper is to ensure the quality of IT services at an agreed level in the face of significant dynamics of user requests by developing and using a method of proactive automatic application scaling in Kubernetes.&#x0D; Method. This paper proposes a proactive horizontal scaling method based on the Prophet time series prediction algorithm. Prometheus metrics storage is used as a data source for training and validating forecasting models. Based on the historical metrics, a model is trained to predict the future utilization of computation resources using Prophet. The obtained time series is validated and used to calculate the required number of application replicas, considering deployment delays.&#x0D; Results. The experiments have shown the effectiveness of the proposed proactive automated application scaling method in comparison with existing solutions based on the reactive approach in the selected scenarios. This method made it possible to reduce the reservation of computing resources by 47% without loss of service quality compared to the configuration without scaling.&#x0D; Conclusions. A method for automating the horizontal scaling of applications in Kubernetes is proposed. Although the experiments have shown the effectiveness of this solution, this method can be significantly improved. In particular, it is necessary to consider the possibility of integrating a reactive component for atypical load patterns.

Preparation and characterization of handsheet using cellulose based Agri-weed: A sustainable utilization of Urena Lobata fiber

The increasing depletion of reserves of natural resources has led to a growing worldwide focus on the exploitation of available waste in new domains. The presence of weedy plants is pervasive on a global scale and has detrimental effects on several aspects of the environment, agriculture, and people's health. Therefore, repurposing these Agri-weed plants for beneficial purposes would be a significant achievement. Furthermore, since raw materials constitute a substantial portion of manufacturing costs, using weeds as a feasible substitute for raw materials might potentially provide considerable advantages for manufacturers. In this study, an endeavor has been made to the utilization of agricultural waste “Urena Lobata”, for the purpose of paper production. In the interim, the utilization of Urena Lobata as an alternative and sustainable raw material for pulp and paper industry could potentially offer a beneficial approach to mitigation of deforestation. The effective production of handsheets with weights of 70 g/m2 and 80 g/m2 was achieved using Urena Lobata fiber, Bleached Urena Lobata Fiber, and hardwood kraft pulp. Mechanical characteristics of handsheet's were comprehensively examined by the bursting index, tensile strength, tear index, brightness percentage and scanning electron microscope for handsheet's morphology. The results show that the handsheets produced by Urena Lobata fiber exhibit a much lower brightness percentage, high tensile strength and bursting index. Alongside, handsheets by bleached Urena Lobata fiber indicate higher brightness percentage, satisfactory values for tensile strength, bursting index, and tear index. The prepared materials are suitable for a broad spectrum of prospective applications, encompassing newsprint, tissue paper, filtration paper as well as high-quality writing and printing paper.

Patent Analysis of Aluminum Based Sacrificial Anode Materials at Domestic and Abroad

Aluminum-based sacrificial anode is a new kind of sacrificial anode material developed rapidly in recent years. It has many advantages, such as low price, high potential of metal driving, large theoretical capacity and rich resource reserves, and is widely used in marine facilities and petroleum industry. However, the related contents of aluminum-based sacrificial anode are various and difficult to be analyzed statistically. On this basis, the relevant patents of aluminum-based sacrificial anode published at home and abroad are statistically analyzed. According to statistics, China's marine aluminum-based sacrificial anode material patent ratio is 73.4%, oil field aluminum-based sacrificial anode material patent ratio is 26.6% . Foreign patents on aluminum-based sacrificial anode have a long history, and the number of patents after 2000 is relatively small. In addition, according to the three categories of component design, preparation process and auxiliary device, the contents of relevant patents are statistically analyzed. It is found that in recent years, the number of patents related to aluminum-based sacrificial anode auxiliary device is higher than the other two types. In terms of the number of patents published, there has been a sharp increase since 2010, with more than half coming from corporate r &amp; D. At the same time, by classifying the composition of aluminum alloy sacrificial anode material in the patent, the content of zinc, indium, tin, magnesium and titanium in aluminum-based sacrificial anode materials and their effects on the properties of anode materials are summarized, the application of alloying elements at home and abroad is compared and analyzed. The effects of zinc content and gallium content on the performance of anode materials were discussed. Finally, some suggestions on the development of aluminum-based sacrifice are put forward.

Temporal analysis of the state of the Gbele Resource Reserve in the Upper West Region, Ghana

IntroductionThis paper assessed the changes in the forest cover of the Gbele Resource Reserve from 1990 to 2020. This provides a basis for strengthening management decisions to protect the resources in the Gbele Resource Reserve effectively.MethodsLandsat images for 1990, 2000, 2010 and 2020 were obtained from the United States Geological Service site. They were processed and classified in the System for Earth Observation Data Access, Processing, &amp;amp; Analysis for Land Monitoring (SEPAL), a web-based cloud computing platform. The accuracy of the images was assessed using 50 ground-truth points obtained from the 3-5 meter spatial and near-daily temporal resolution planet satellite images from Norway’s International Climate and Forest Initiative (NICFI). Post classification change detection was used to analyse the changes in land cover from 1990 to 2000, 2000 to 2010 and from 2010 to 2020.ResultsThe analysis revealed that the total forest area was 55273.2 ha. In 1990, 74.9 % of the reserve was open forest and 24.6 % was shrubs/grass. The open forest declined to 65.8 % in 2000 and further to 62.4 % in 2010 while the shrubs/grass cover increased to 35.7 in 2010. As of 2020, the forest increased to 73.6 % while the shrub/grass cover declined to 25.8 %.DiscussionThese changes could be attributed partly to widespread charcoal production in the fringe districts and rose wood harvesting in the early 2000s. charcoal production and rosewood logging have been livelihood sources for fringe communities. The ban on the harvest and exportation of rosewood after 2010 could partly explain the sharp increase in the open forest cover from 2010 to 2020. The changes in the extent of the reserve from 1990 to 2020 revealed that the reserve can vulnerable to excessive exploitation and can also be resilient if deliberate efforts are made to protect it. It is recommended that the fringe district and municipal Assemblies should strengthen the enforcement of the ban on the logging of the rosewood and trees in the reserve for the production of charcoal.

Poly(3-Methylthiophene)/Graphene Composite Cathode for Rechargeable Aluminum-Ion Batteries.

To reduce the dependence on traditional fossil energy, developing efficient energy storage systems is urgent. The reserves of aluminum resources in the earth's crust are extremely rich, which makes aluminum-ion batteries a promising competitor of new energy storage devices. Here, we report a poly(3-methylthiophene)/graphene (P3TH/Graphene) composite as the cathode of an aluminum-ion battery. The adjustment of polymer chain spacing by the methyl side chain provides a channel conducive to the transport of large-size AlCl4- complexes. The addition of electron donor groups also changes the electron delocalization characteristics of polymers and improves the specific capacity of the material. At the same time, the in situ composite of graphene can enhance the Π-Π interaction to form a favorable electronic transmission channel. At a current density of 200 mA g-1, the P3TH/Graphene composite showed a specific capacity of ∼150 mA g-1. The flexible structure of the polymer also guarantees the excellent rate capability of the composite.