Cost Management Research Articles

Fuzzy Integrated Delphi-ISM-MICMAC Hybrid Multi-Criteria Approach to Optimize the Artificial Intelligence (AI) Factors Influencing Cost Management in Civil Engineering

Fuzzy Integrated Delphi-ISM-MICMAC Hybrid Multi-Criteria Approach to Optimize the Artificial Intelligence (AI) Factors Influencing Cost Management in Civil Engineering

The TransFORmation of IndiGEnous PrimAry HEAlthcare Delivery (FORGE AHEAD): economic analysis

BackgroundIndigenous populations have increased risk of developing diabetes and experience poorer treatment outcomes than the general population. The FORGE AHEAD program partnered with First Nations communities across Canada to improve access to resources by developing community-driven primary healthcare models.MethodsThis was an economic assessment of FORGE AHEAD using a payer perspective. Costs of diabetes management and complications during the 18-month intervention were compared to the costs prior to intervention implementation. Cost-effectiveness of the program assessed incremental differences in cost and number of resources utilization events (pre and post). Primary outcome was all-cause hospitalizations. Secondary outcomes were specialist visits, clinic visits and community resource use. Data were obtained from a diabetes registry and published literature. Costs are expressed in 2023 Can$.ResultsStudy population was ~ 60.5 years old; 57.2% female; median duration of diabetes of 8 years; 87.5% residing in non-isolated communities; 75% residing in communities < 5000 members. Total cost of implementation was $1,221,413.60 and cost/person $27.89. There was increase in the number and cost of hospitalizations visits from 8/$68,765.85 (pre period) to 243/$2,735,612.37. Specialist visits, clinic visits and community resource use followed this trend.ConclusionConsidering the low cost of intervention and increased care access, FORGE AHEAD represents a successful community-driven partnership resulting in improved access to resources.

A Study on The Cost And Profit Efficiency of Islamic and Conventional Bank Islamic Windows in Oman: A Proposed Framework

Objective: This study aims to analyze the efficiency of Islamic and conventional banks and their respective Islamic windows in Oman in terms of costs and profits. Theoretical Framework: The research employs a framework that examines cost and profit efficiency within the banking sector, contrasting the performance of full-fledged Islamic banks and Islamic windows of conventional banks. This framework also investigates the impact of bank-specific variables on efficiency levels. Method: Using empirical data from the Omani banking sector, the study quantifies efficiency by analyzing bank-specific variables such as capitalization, profitability, operational costs, and loan activity. The comparison includes both Islamic banks and the Islamic windows of conventional banks as of the end of the third quarter of 2022. Results and Discussion: The findings reveal that, overall, banks in Oman are more efficient at generating profits than controlling costs. Conventional banks, on average, demonstrate higher efficiency in both cost and profit metrics compared to Islamic banks. There exists a positive correlation between both types of efficiencies and factors like bank capitalization and profitability, while a negative correlation is evident with operational costs. Furthermore, increased loan activity is associated with higher profit efficiency but adversely affects cost efficiency. Research Implications: These results underscore significant efficiency disparities between Islamic and conventional banking sectors. They highlight the need for Islamic banks to enhance their cost management strategies without compromising profit generation, leveraging the benefits derived from their association with parent conventional banks. Originality/Value: The study contributes to the literature by providing a comparative analysis of cost and profit efficiencies in Islamic and conventional banks, with a particular focus on the unique market dynamics of Oman. This research is valuable for stakeholders in the Islamic banking industry, offering insights into leveraging existing infrastructures and enhancing operational efficiencies.

Analysis on Lean Management of Real Estate Projects Oriented by Target Cost Management

Analysis on Lean Management of Real Estate Projects Oriented by Target Cost Management

Study on Fault Monitoring Technology of Photovoltaic Panel Based on Thermal Infrared and Optical Remote Sensing

Abstract. Rapid access to the operating status of Photovoltaic (PV) panels and troubleshooting can save management and maintenance costs for the development of PV power plants, which is important for PV power plant management and power generation capacity assurance. The use of remote sensing technology to identify the faults of photovoltaic panels has developed rapidly, however, current research usually relies only on a single optical data source to identify and count the area of PV panels in a PV electric field, although there are literature on PV panel fault detection, only the surface fault identification of PV panels is tested, while the internal faults (such as panel bad points or bad lines) cannot be identified because of the limitations of optical remote sensing. In this paper, a photovoltaic panel fault monitoring technology based on multi-source remote sensing is proposed. The optical and thermal infrared hybrid data combined with deep learning technology are used to achieve rapid and accurate fault identification and localization of PV panel arrays. It can not only automatically identify PV panels that are obscured by dust and foreign objects, but also locate PV panels that have bad dots or bad lines, which greatly improves the ability and effectiveness of remote sensing PV panel fault monitoring. The high-resolution unmanned air vehicle (UAV) optical image and thermal infrared image are applied in this experiment. The Mask RCNN algorithm is used to accurately locate and number the photovoltaic panel of the optical image. Then, the fault scene classification model is established for the multi-type fault characteristics of the optical image and thermal infrared image within the panel range, so as to identify five types of faults, such as dust cover, branch cover, bird droppings cover, internal bad points and bad lines of PV panel, which effectively solves the problem that the single optical remote sensing image cannot identify the internal component faults of the photovoltaic panel under normal conditions.

Assessing the Effectiveness of Pruning in an Olive Orchard Using a Drone and a Multispectral Camera: A Three-Year Study

The uses of precision oliviculture have increased in recent years to improve the quality and quantity of extra virgin olive oil. In traditional and intensive systems, biennial pruning is often applied to balance and maintain plant vigour, aiming at reducing management costs. This study presents the results of a three-year experiment with the objective of quantifying the effects of biennial pruning on the vegetative vigour of olive trees, investigating the geometric and spectral characteristics of each canopy determined with multispectral images acquired by UAV. The experiment was carried out in an olive orchard located in western Sicily (Italy). Multispectral images were acquired using a UAV in automatic flight configuration at an altitude of 70 m a.g.l. The segmentation and classification of the images were performed using Object-Based Image Analysis (OBIA) based on the Digital Elevation Model (DEM) and orthomosaic to extract the canopy area, height, volume and NDVI for each plant. This study showed that the technology and image analysis processing used were able to estimate vigour parameters at different canopy densities, compared to field measurements (R2 = 0.97 and 0.96 for canopy area and volume, respectively). Furthermore, it was possible to determine the amount of removed biomass for each plant and vigour level. Biennial pruning decreased the number of plants initially classified as LV (low-vigour) and maintained a vegetative balance for MV (medium-vigour) and HV (high-vigour) plants, reducing the spatial variability in the field.

Comparison of Long-Term Healthcare Cost and Utilisation of Nonoperative and Surgical Management of Thumb CMC Arthritis.

Background: Thumb carpometacarpal joint (CMC) osteoarthritis is the most symptomatic hand arthritis but the long-term healthcare burden for managing this condition is unknown. We sought to compare total healthcare cost and utilisation for operative and nonoperative treatments of thumb CMC arthritis. Methods: We conducted a retrospective longitudinal analysis using a large nationwide insurance claims database. A total of 18,705 patients underwent CMC arthroplasty (trapeziectomy with or without ligament reconstruction tendon interposition) or steroid injections between 1 October 2015 and 31 December 2018. Primary outcomes, healthcare utilisation and costs were measured from 1 year pre-intervention to 3 years post-intervention. Generalised linear mixed effect models adjusted for potentially confounding factors such as the Elixhauser comorbidity score with propensity score matching were applied to evaluate the association between the primary outcomes and treatment type. Results: A total of 13,646 patients underwent treatment through steroid injections, and 5,059 patients underwent CMC arthroplasty. At 1 year preoperatively, the surgery group required $635 more healthcare costs (95% CI [594.28, 675.27]; p < 0.001) and consumed 42% more healthcare utilisation (95% CI [1.38, 1.46]; p < 0.0001) than the steroid injection group. At 3 years postoperatively, the surgery group required $846 less healthcare costs (95% CI [-883.07, -808.51], p < 0.0001) and had 51% less utilisation (95% CI [0.49, 0.53]; p < 0.0001) annually. Cumulatively over 3 years, the surgical group on average was $4,204 costlier than its counterpart secondary to surgical costs. Conclusions: CMC arthritis treatment incurs high healthcare cost and utilisation independent of other medical comorbidities. At 3 years postoperatively, the annual healthcare cost and utilisation for surgical patients were less than those for patients who underwent conservative management, but this difference was insufficient to offset the initial surgical cost. Level of Evidence: Level III (Therapeutic).

Research on the Impact of Digital Transformation on the High-Quality Development of Enterprises: A Case Study of the Manufacturing Industry

The manufacturing sector faces increasingly intense competitive pressures in its operational development. Adjusting production structures based on emerging technologies has become a crucial measure for the high-quality development of the manufacturing industry. It can activate the potential driven by big data elements to achieve economic transformation and innovative development in manufacturing. Digital transformation has brought new opportunities and challenges to the manufacturing industry. How to use digital technology to transform and upgrade cost management has become an urgent issue for the manufacturing sector. Based on this, this paper takes the manufacturing industry as an example, focusing on analyzing the impact of digital transformation on the high-quality development of enterprises and the optimization strategies.

The effect of manufacturing overhead on policies for allocating production capacity

This research explores how manufacturing overhead influences profit margins under different capacity allocation policies in a build-to-order context. By applying a multi-period Mixed-Integer-Programming model to assess industries with varying overhead structures, the study establishes a link between the levels of capacity allocation and profitability, underscoring the strategic significance of overhead costs in capacity management decisions. Our results indicate that industries with lower overhead costs benefit more significantly from increased capacity allocation, with up to a 25% improvement in profit, compared to a 5–10% improvement in higher overhead industries. Conversely, at full capacity demand rates, increased allocation levels detrimentally affect profit, particularly in industries with higher overhead ratios. The study utilises a 3-way ANOVA to confirm the significance of these findings, revealing that industry type, demand rates, and allocation levels are critical factors in optimising profit. This research highlights the need for a pragmatic approach to capacity allocation that aligns with industry characteristics and demand levels, steering away from revenue maximisation to a more holistic view of profitability that includes overhead cost management.

Geopolymer-Based Materials for the Removal of Ibuprofen: A Preliminary Study

Every year, new compounds contained in consumer products, such as detergents, paints, products for personal hygiene, and drugs for human and veterinary use, are identified in wastewater and are added to the list of molecules that need monitoring. These compounds are indicated with the term emerging contaminants (or Contaminants of Emerging Concern, CECs) since they are potentially dangerous for the environment and human health. To date, among the most widely used methodologies for the removal of CECs from the aquatic environment, adsorption processes play a role of primary importance, as they have proven to be characterized by high removal efficiency, low operating and management costs, and an absence of undesirable by-products. In this paper, the adsorption of ibuprofen (IBU), a nonsteroidal anti-inflammatory drug widely used for treating inflammation or pain, was performed for the first time using two different types of geopolymer-based materials, i.e., a metakaolin-based (GMK) and an organic–inorganic hybrid (GMK-S) geopolymer. The proposed adsorbing matrices are characterized by a low environmental footprint and have been easily obtained as powders or as highly porous filters by direct foaming operated directly into the adsorption column. Preliminary results demonstrated that these materials can be effectively used for the removal of ibuprofen from contaminated water (showing a concentration decrease of IBU up to about 29% in batch, while an IBU removal percentage of about 90% has been reached in continuous), thus suggesting their potential practical application.

Evaluating the cost-effectiveness of voclosporin for the treatment of lupus nephritis in the United States.

Lupus nephritis (LN) is a severe manifestation of systemic lupus erythematosus; up to 30% of patients with LN will develop end-stage kidney disease (ESKD). One of the main treatment goals for LN is preservation of kidney function, with early decreases in proteinuria associated with improved long-term outcomes. Voclosporin, a second-generation calcineurin inhibitor, was approved in the United States in 2021 for the treatment of active LN combined with background immunosuppression. The AURORA 1 study found that the use of voclosporin with low doses of mycophenolate mofetil and glucocorticoids yielded significant reductions in proteinuria. The AURORA 2 study showed long-term efficacy and safety of voclosporin over a 3-year period with kidney function preservation. The Institute for Clinical and Economic Review (ICER) is a nonprofit organization that evaluates medical evidence to help improve patient outcomes and control costs. In 2021, ICER published an economic model to estimate the impact and cost-effectiveness of LN therapies. From a US health care perspective, voclosporin was cost-effective at $149,260 per quality-adjusted life-year (QALY) and $131,528 per equal value of life-years gained (evLYG). At the time of the LN cost-effectiveness model (CEM) development, voclosporin was not yet approved in the United States and the cost of treating patients with LN with ESKD was not captured in the literature. To evaluate the cost-effectiveness of voclosporin given the emergence of new data. The LN CEM uses a short-term trial-based Markov model and long-term extrapolation using partitioned survival modeling data assuming adults with LN start with active disease, transitioning to complete or partial renal response, kidney failure, or death. In the current analysis, clinical data for voclosporin, duration of voclosporin treatment for nonresponders, and drug costs reflecting the 2023 price of voclosporin were updated. Additionally, health care payer costs of disease management were incorporated based on real-world claims data on the costs of treating patients with LN. Using the LN CEM with inputs reflecting the latest and most relevant evidence, the incremental cost of voclosporin per QALY was $88,076 and per evLYG was $77,643. For a subpopulation of Black, Hispanic, and Latino patients, the incremental cost of voclosporin per QALY was $77,435 and per evLYG was $67,828. Following the inclusion of updated data in the cost-effectiveness analysis, voclosporin remains a cost-effective therapy for the treatment of active LN including in a Black, Hispanic, and Latino subpopulation, substantially below the ICER willingness-to-pay threshold of $150,000/QALY.

Research on Logistics Cost Management Strategy for Wood Processing Industry Based on Environmentally Conscious Supply Chain

Introduction: The wood processing industry is an important component of the forestry industry; It is a green and low-carbon industry with low energy consumption and low environmental pollution. With the acceleration of global economic integration, logistics costs have become a key factor in improving the development level of wood processing enterprises and an important component of the competitiveness of the forestry industry. In response to the current problem of high logistics costs in Chinese wood processing enterprises, starting from the innovative concept of logistics cost management, a strategic management system for logistics costs is constructed using Environmentally Conscious Supply Chain, management theory; Strengthening the logistics cost management of wood processing enterprises in the forestry industry plays an important role in promoting China's transition from traditional quantity forestry to modern efficiency forestry. Objective: To improve the overall level of logistics cost management of the whole country's wood processing industry. Results and Discussion: Forestry is an integrated industry combining the economic value, ecological value and social value of forests. Due to the importance of t green coordinated and sustainable development of overall benefits in the forestry green supply chain, it is not only necessary to achieve economic benefits, but also to continuously increase resources and improve the ecological environment. Research Implications: This research can implemented in order to bring environmental sustainability

Agro-industrial waste management employing benefits of artificial intelligence.

By 2050, the world's population is predicted to reach over 9 billion, which requires 70% increased production in agriculture and food industries to meet demand. This presents a significant challenge for the agri-food sector in all aspects. Agro-industrial wastes are rich in bioactive substances and other medicinal properties. They can be used as a different source for manufacturing products like biogas, biofuels, mushrooms, and tempeh, the primary ingredients in various studies and businesses. Increased importance is placed on resource recovery, recycling, and reusing (RRR) any waste using advanced technology like IoT and artificial intelligence. AI algorithms offer alternate, creative methods for managing agro-industrial waste management (AIWM). There are contradictions and a need to understand how AI technologies work regarding their application to AIWM. This research studies the application of AI-based technology for the various areas of AIWM. The current work aims to discover AI-based models for forecasting the generation and recycling of AIWM waste. Research shows that agro-industrial waste generation has increased worldwide. Infrastructure needs to be upgraded and improved by adapting AI technology to maintain a balance between socioeconomic structures. The study focused on AI's social and economic impacts and the benefits, challenges, and future work in AIWM. The present research will increase recycling and reproduction with a balance of cost, efficiency, and human resources consumption in agro-industrial waste management.

Advancing financial transparency and ethical governance: innovative cost management and accountability in higher education and industry

Advancing financial transparency and ethical governance in higher education and industry is imperative for fostering trust, accountability, and sustainability. This review explores innovative cost management strategies and accountability measures to achieve these goals. In both higher education and industry, financial transparency ensures stakeholders have access to accurate, timely, and comprehensible financial information. This transparency is crucial for building trust among investors, donors, regulators, and the public. Moreover, it facilitates informed decision-making and enhances organizational efficiency. One innovative approach to advancing financial transparency is the adoption of cloud-based financial management systems. These systems offer real-time data accessibility, automated reporting, and customizable dashboards, enabling institutions to track expenditures, revenue streams, and budget variances more effectively. Additionally, blockchain technology holds promise in ensuring the integrity and immutability of financial records, reducing the risk of fraud and corruption. Ethical governance goes hand in hand with financial transparency, emphasizing integrity, honesty, and accountability in organizational practices. Robust governance frameworks establish clear lines of responsibility, codes of conduct, and mechanisms for oversight. In higher education, this involves empowering governing boards with diverse expertise and ensuring academic and financial decisions align with institutional missions. To enhance ethical governance, institutions can implement whistleblower protection programs and conduct regular ethics training for employees. These initiatives promote a culture of transparency and integrity, encouraging individuals to report unethical behavior without fear of retaliation. Cost management plays a pivotal role in financial sustainability and ethical governance. Traditional cost-cutting measures often focus on reducing expenses without considering long-term implications. Innovative cost management, however, emphasizes efficiency, value creation, and sustainability. Activity-based costing is one such approach that allocates costs based on the activities that drive them, providing a more accurate understanding of resource consumption. This enables institutions to make informed decisions about resource allocation and pricing strategies. Furthermore, strategic sourcing and vendor management help optimize procurement processes, negotiate favorable contracts, and mitigate risks associated with third-party relationships. Collaborative partnerships with industry stakeholders can also facilitate knowledge sharing, resource pooling, and cost-saving opportunities. Accountability mechanisms are essential for ensuring that financial resources are used responsibly and in alignment with organizational objectives. Performance metrics and key performance indicators (KPIs) provide benchmarks for evaluating financial and operational performance. These metrics should be transparent, relevant, and aligned with strategic goals. Advancing financial transparency and ethical governance requires a multifaceted approach encompassing technological innovation, robust governance frameworks, strategic cost management, and accountability measures. By embracing these principles, both higher education institutions and industries can build trust, enhance efficiency, and achieve long-term sustainability. Keywords: Financial Transparency, Ethical Governance, Cost Management, Accountability, Higher Education, Industry

Pengendalian Biaya Tenaga Kerja dalam Organisasi Sektor Publik: Studi tentang Pengelolaan Pegawai Tidak Tetap (PTT) dan Alternatif Outsourcing

This article discusses the management of labor costs in the public sector with a focus on the management of non-permanent employees (PTT) and outsourcing alternatives. This research highlights problems in personnel management, especially employee expenditure costs that must be borne by government agencies. This study reviews cost control systems, labor costs, and methods for managing honorary staff costs in government. The findings show that outsourcing is more efficient than recruiting PTT or temporary workers as a solution to control labor costs. Additionally, this paper recommends Activity Based Costing (ABC) method for public sector organizations to provide valuable information related to detailed cost data. This research shows that decentralizing recruitment in local governments can improve efficiency, effectiveness and fairness, but can also lead to corruption and disparities in the distribution of human resources. Cost control, outsourcing, and the use of Activity-Based Costing (ABC) can help public sector organizations manage costs and increase operational efficiency. To achieve better governance, operational efficiency and effective cost control, public sector organizations need to consider the various strategies and methods described in this research.

Identification of novel genes associated with herbicide tolerance in Lentil (Lens culinaris ssp. culinaris Medik.)

Weeds pose a major constraint in lentil cultivation, leading to decrease farmers’ revenues by reducing the yield and increasing the management costs. The development of herbicide tolerant cultivars is essential to increase lentil yield. Even though herbicide tolerant lines have been identified in lentils, breeding efforts are still limited and lack proper validation. Marker assisted selection (MAS) can increase selection accuracy at early generations. Total 292 lentil accessions were evaluated under different dosages of two herbicides, metribuzin and imazethapyr, during two seasons at Marchouch, Morocco and Terbol, Lebanon. Highly significant differences among accessions were observed for days to flowering (DF) and maturity (DM), plant height (PH), biological yield (BY), seed yield (SY), number of pods per plant (NP), as well as the reduction indices (RI) for PH, BY, SY and NP. A total of 10,271 SNPs markers uniformly distributed along the lentil genome were assayed using Multispecies Pulse SNP chip developed at Agriculture Victoria, Melbourne. Meta-GWAS analysis was used to detect marker-trait associations, which detected 125 SNPs markers associated with different traits and clustered in 85 unique quantitative trait loci. These findings provide valuable insights for initiating MAS programs aiming to enhance herbicide tolerance in lentil crop.

Application of BIM+GIS Integration Technology in the Construction of Urban Intelligent Water Informatization

Urban intelligent water informatization is the process of managing and operating urban water systems with the use of contemporary information and communication technology in order to increase productivity, security, and sustainability. Establishing the appropriate infrastructure is the initial stage in building an intelligent water system so that management can choose wisely how to manage and operate the water system. Building information modeling (BIM) is a digital depiction of a building's or infrastructure's structural and functional details. In most metropolitan regions, a fast development phase is predicted to cause several water issues, including water resource shortages, floods, poor drainage, and water resource contamination. As a result, a practical approach is required for urban intelligent water information technology with the help of artificial intelligence techniques. Intelligent water systems may be built using Building Information Modeling (BIM) software to increase the system's effectiveness, stability, and durability. By offering a potent tool for storing and analyzing geographical data connected to the water distribution system, a geographic information system (GIS) can play a crucial role in the development of urban intelligent water informatization using ArcGIS mapping Software. The Internet of Things (IoT) system is used to implement intelligent water informatization, hardware implementation using ESP32, and software development using MQTT Broker and Node-Red. As a result, we recommended utilizing BIM+GIS integration technology for building urban intelligent water informatization. The suggested system is evaluated using management efficiency, urban flood control, innovative Construction, intensive management, and computation cost. In this research, the main objective is to identify where there are water leaks broken pipes and early warning system and monitoring system for flash flood disasters in urban areas. The result findings show that the integration of BIM and GIS provides a comprehensive platform for managing complex water informatization infrastructure projects and maximizes efficiency and sustainability.

Методика управленческого учета затрат и калькулирования себестоимости неамортизируемой организационно-технологической оснастки производства продукции промышленного предприятия

The article is devoted to the search for scientific and practical solutions aimed at improving the quality of the information and instrumental space of management cost accounting and calculating the cost of not amortised organizational and technological equipment of industrial enterprises. In the course of the conducted research on a number of economic entities of the Nizhny Novgorod region, methods of observation, collection, systematization, classification and reflection in information registers of information relevant to the studied subject area were used; complex managerial, practice-oriented and statistical types of analysis, scientific interpretation of accumulated data using calculations and graphical formalization; the existing theoretical and methodological approaches used in the subject area under study are considered; a methodology for managerial cost accounting and calculating the cost of OTP using analytical accounting registers formed directly in the context of this type of product is proposed. The integrated use of the proposed methodology will improve the quality of awareness of decision makers on production cost management; create institutional conditions for its application in the field of manufacturing products for their own technological needs.

Ultrafiltration fractionation of potentially inhibitory substances of hydrothermal liquefaction aqueous phase derived from municipal sludge

Hydrothermal liquefaction (HTL) is a promising thermo-chemical technology for municipal sludge treatment due to its potential for biocrude oil recovery and minimizing biosolids management costs. However, the process generates a high volume of an aqueous byproduct that needs to be treated due to its high chemical oxygen demand (COD) and various organic and inorganic compounds. Although the aqueous phase is known to contain recalcitrant and potentially inhibitory substances that may affect its biological treatment, their molecular weight distribution (MwD) and its impact on anaerobic biodegradability are poorly understood. Ultrafiltration (UF) was conducted to fractionate HTL aqueous into different molecular weight (Mw) fractions using 300, 100, 10, and 1 kDa membranes. Mesophilic biochemical methane potential (BMP) assays were conducted to assess the anaerobic biodegradability of each fraction, and the first-order model was used to calculate the degradation kinetics of potential inhibitory compounds. The highest percentage of organics (65 %) was found in the Mw<1 kDa range, whereas the 10>Mw>1 kDa had the lowest percentage (8 %). There was no significant difference in the cumulative specific methane produced from various Mw fractions (p>0.05). The Mw<1 kDa fraction had the highest first-order specific methane production rate (0.53 day−1), whereas the unfiltered HTL had the lowest (0.38 day−1). Although UF fractionation increased the rate of anaerobic degradation of HTL aqueous for the Mw<1 kDa fraction, the observed methane potential was only 55 % of the theoretical value. This implies that 45 % of COD remains undegraded even after permeation through the lowest Mw cut-off membrane. Therefore, further characterization of HTL aqueous is needed for compounds with molecular weights below 1 kDa to fully understand the nature of inhibitory organics and their impact on anaerobic digestion. Furthermore, pretreatments utilizing techniques such as adsorption and advanced oxidation may be necessary to enhance the specific methane yields from various HTL aqueous fractions, thereby bringing them closer to the theoretical yield.

Drivers of Spontaneous Plant Communities in Urban Parks: A Case from Nanjing, China

Urban plant diversity is one of the key elements for sustainable urban development. Urban plant landscapes not only create a variety of experiences for residents but also have a positive effect on their physiology and psychology. In order to better introduce nature into urban green spaces, this study conducted a field survey in Nanjing, China, to analyze the current situation of spontaneous plants in Nanjing’s urban green spaces and propose a plant planning strategy that takes into account both ecology and residents’ well-being. This study surveyed the herbaceous plant resources in 96 sample plots in nine typical urban parks in Nanjing, and recorded 284 plant species in 192 genera and 78 families. The research results show that the differences in plant diversity, richness, and evenness among urban parks in Nanjing are significant; combined with cluster analysis and ranking results, the total area of urban parks, green space construction time, lighting conditions, and management frequency have an impact on plant communities. Further analysis of the species composition of plant communities showed that moderate management frequency in urban parks can increase plant diversity. With the advantages of both high ecological benefits and low management costs, a model of “artificial plants + native spontaneous plants” was finally proposed for the planting of herbaceous plants in sustainable urban green spaces.