Inventory Data Research Articles

Study on Forest Growing Stock Volume in Kunming City Considering the Relationship Between Stand Density and Allometry

Forest growing stock volume (GSV) is a fundamental indicator for assessing the status of forest resources. It reflects forest carbon storage levels and serves as a key metric for evaluating the carbon sequestration capacity of forest ecosystems, thereby playing a crucial role in supporting national “dual-carbon” objectives. Traditional allometric models typically estimate GSV using tree species, diameter at breast height (DBH), and canopy height. However, at larger spatial scales, these models often neglect stand density, resulting in substantial estimation errors in regions characterized by significant density variability. To enhance the accuracy of large-scale GSV estimation, this study incorporates high-resolution, spatially continuous forest structural parameters—including dominant tree species, stand density, canopy height, and DBH—extracted through the synergistic utilization of active (e.g., Sentinel-1 SAR, ICESat-2 photon data) and passive (e.g., Landsat-8 OLI, Sentinel-2 MSI) multi-source remote sensing data. Within an allometric modeling framework, stand density is introduced as an additional explanatory variable. Subsequently, GSV is modeled in a stratified manner according to tree species across distinct ecological zones within Kunming City. The results indicate that: (1) the total estimated GSV of Kunming City in 2020, based on remote sensing imagery and second-class forest inventory data collected in the same year, was 1.01 × 108 m3, which closely aligns with contemporaneous statistical records. The model yielded an R2 of 0.727, an RMSE of 537.566 m3, and a MAE of 239.767 m3, indicating a high level of overall accuracy when validated against official ground-based inventory plots organized by provincial and municipal forestry authorities; (2) the incorporation of the dynamic stand density parameter significantly improved model performance, which elevated R2 from 0.565 to 0.727 and significantly reduced RMSE. This result confirms that stand density is a critical explanatory factor; and (3) GSV exhibited pronounced spatial heterogeneity across both tree species and administrative regions, underscoring the spatial structural variability of forests within the study area.

Implementation of an Accounting Information System at a Grocery Store

In the digital era, both companies and MSMEs are starting to utilize technology to help their work. Grocery Store is store that sells various kinds of goods such as basic necessities, drinks, snacks, and daily necessities. This shop has many customers but the recording procedure is done manually. This research aims to help Grocery Stores by creating an accounting information system using the RAD (Rapid Application Development) method. This method was chosen in reason the effectiveness in developing and organizing the system structure. This accounting information system can help the store in managing transaction and inventory data better.

Rancang Bangun Sistem Informasi Manajemen Inventaris Sekolah di SMA Negeri 6 Solok Selatan

The manual inventory management system in schools presents various challenges, such as low efficiency, accuracy, and transparency in asset recording and reporting. This study aims to design and implement a web-based School Inventory Management Information System at SMA Negeri 6 Solok Selatan to support more effective and systematic inventory data management. Employing the Waterfall software development method and the Unified Modeling Language (UML) approach, the system was designed based on data collected through user observation and interviews, and functionally tested. The system was developed using the Laravel framework, PHP programming language, and MySQL database. The results show that the system successfully digitizes the entire process of inventory recording, storage, monitoring, and reporting. Features such as data search, asset grouping, and periodic reports facilitate inventory teachers in performing their tasks more efficiently and accurately. Moreover, the system enhances transparency and accountability in school asset management. In conclusion, the implementation of this information system significantly contributes to improving the quality of inventory management and is recommended as a digital solution for other schools facing similar challenges.

Forest Management Tool for Estimating Growth and Yield Stand Parameters in Pine Plantations. A Case of Sao Hill Forest Plantation

This study presents the Forest Inventory Tool (FIT), designed for estimating and forecasting stand volume, growth, yield, and tree size distribution for Pinus patula plantations in Tanzania. The tool is designed to accommodate growth dynamics changes associated with the manipulation of management practices. Implementing management plans is often hindered by challenges such as budgetary constraints, weather state and market fluctuations often disrupt the implementation of management plans. These disruptions may lead to the omission of critical practices like thinning and harvesting, resulting in discrepancies between the analysed and forecasted metrics in the management plan and the actual stand state. The tool addresses these challenges by automating data processing, enabling real-time updates, and reducing reliance on manual analysis to update the stand structure that is prone to error. The FIT development followed the standard forest management prescriptions outlined in the forest management plan, which directs the five-year operations (e.g. thinning, pruning, planting and clear-felling). It was designed using Excel VBA to integrate inventory data with management prescriptions. Forest data were collected through stratified systematic sampling across 60 compartments. The FIT applies yield models to forest inventory data to inform forest structure and forecast its development under different management practices. The tool generates key stand parameters for forest management, including an overview of the plantation, stand summaries for a five-year management plan, and dynamic updates on plantation status. It provides an automated solution for managing plantations by supporting decision-making. It is recommended that the tool be expanded to support a broader range of species and be developed into an app or web-based platform to improve its applicability across different forest types and ensure remote access.

Inventory of Mental Health Services in Academia and Researchers' Awareness of Their Availability: Mixed Method Research Protocol and Pilot Study in Switzerland.

To inventory occupational health services (OHS) in European higher education institutions (HEI) and assess researchers' awareness of these services. The protocol, validated in Switzerland, combined a mapping study of OHS with semi-structured interviews with researchers. Data were analyzed using MAXQDA software and triangulated with OHS inventory data. OHS in 14 Swiss HEI typically include basic medical consultations, mental health counselling, and legal advice. Access varies by users' status, often favoring students. Service varies across institutions, creating potential inequalities. At one Swiss HEI, twelve researchers were interviewed; stress derived primarily from time pressure and work overload. Respondents desired better communication with management and a more supportive environment. Despite the availability of four OHS at this HEI, awareness of, and confidence in these services were low, and confidentiality concerns led many to seek external support. Interviewees had limited awareness of available mental health related OHS, and most decided not to rely on institutional HEI services due to confidentiality related concerns. External psychological help services appear more trusted and potentially more effective.

Towards Digital Transformation in Administrative Inventory Control: A Web-Based System Development Study

The inventory information system currently employed by the General Administration Department remains largely manual, relying on Microsoft Office Excel. This approach results in inefficiencies, particularly in the retrieval and processing of inventory data, which tends to be slow and prone to errors. In response to these limitations, this study aims to develop a more efficient, user-friendly inventory management system that improves access to information and streamlines data and file handling. The proposed system is designed to enhance operational efficiency within administrative units, particularly the logistics sub-division, by providing accurate records of goods management activities, including procurement, inventory, and transactional processes. With the implementation of this system, it is expected that the handling of university logistics data will become faster, more reliable, and less prone to human error. Moreover, access to logistical information will be more readily available whenever required, supporting timely and informed decision-making.

SISTEM INFORMASI PEMINJAMAN DAN PENGEMBALIAN ALAT-ALAT LABORATORIUM DESAIN KOMUNIKASI VISUAL SMKN 6 KUPANG BERBASIS WEB

The information system for borrowing and returning laboratory equipment is a solution to increase efficiency and effectiveness in the management of tools in the Visual Communication Design (DKV) laboratory of the State Vocational High School 6 Kupang. The borrowing process that has been carried out manually has the potential to cause various problems, such as delays in returns, loss of tools, and difficulties in collecting inventory data. This research aims to design and build a web-based laboratory equipment lending and return management system that can simplify the process of borrowing and returning equipment, as well as minimize the risk of loss and damage through accurate and real-time recording. The system development method used is the Waterfall method, which includes needs analysis, design, implementation, testing, and maintenance. This research is expected to be a web-based system that can make it easier for students to borrow and return tools online, as well as store all borrowing data in a centralized database. With this system, it is hoped that the management of DKV laboratory equipment at the State Vocational High School 6 Kupang can run more efficiently and transparently.

Design of a Website-Based Goods Inventory Information System at the Grocery Store

This research aims to design and build a website-based inventory information system at the Dewi Grocery Store. The problem currently faced by stores is that capturing and managing inventory data is still manual, causing problems such as difficulty monitoring stock, recording errors and making old reports. The research method used is Agile Methods, consisting of requirements, design, implementation, verification and maintenance. System design using Laravel, Visual Studio Code, MySQL, XAMPP, Draw.io, and Whimsical. The research result is a website-based inventory information system application that can help the Dewi Grocery Store manage inventory data effectively and efficiently. The sales inventory system is functional and user-friendly, making it a valuable tool for Dewi Grocery Store to effectively manage sales inventory and provide accurate reports. The application has category management features, item data, sales, and report creation, as well as prediction features to help shop owners make decisions. The results of black box, expert, and user testing show the application is worthy of use with scores of 94%, 76%, and 83 %, respectively.

Factors affecting the occurrence of biomass-dense forests in Sweden

ABSTRACT Energy production from wood-based biomass is recognized as a sustainable energy source under current EU regulations. This approach could significantly contribute to Sweden’s energy strategy, given the country’s vast forestlands, which cover 27.9 million ha. This study explores factors influencing the occurrence of biomass-dense forests’ – stem-dense forests with small diameter trees (BDFs) – across Sweden, considering large-scale variables, site characteristics, and management settings. Using Swedish National Forest Inventory data, we found that stand age and site productivity were the strongest predictors of BDF occurrence nationally and regionally, with older, low-productivity stands accumulating high biomass due to prolonged periods without thinning. BDFs were most common in northern regions (Northern and Southern Norrland) where long rotation cycles and seasonal thinning constrains, and high-elevation sites favored BDFs formation. Additionally, soil conditions played a critical role, with BDFs more frequent on wet, and peat soils, which are less productive and are less frequently thinned. Our results also demonstrated high complexity of site conditions and their interactive effects on the occurrence of BDFs. Nevertheless, we suggest that stand age, site productivity, tree species composition, and soil moisture can guide biomass management decisions, including thinning practices, in the context of increasing demand for renewable energy.

Value Extraction from End-of-Life Textile Products in Pakistan

Overconsumption and unplanned disposal of garments result in millions of tons of textile products going to landfills. Understanding the environmental benefits and impact of various recycling options is crucial for integrating recycling into the apparel waste stream. This study aims to assess the environmental impacts of products made from post-consumer textile waste fibers, highlighting the importance of closed-loop textile supply chains in developing countries. Using Open LCA software, the cradle-to-gate approach for life cycle assessment is used to calculate the environmental impacts of post-consumer textile waste, virgin cotton, virgin polyester fibers, and their blends in two different scenarios. The life cycle inventory data for functional units (1000 kg apparel) has been collected from the industrial units and the Ecoinvent v3.0 database. The results of 16 environmental impact categories are computed, showing that textile products made from virgin cotton fiber have 60% more global warming potential than those made from post-consumer textile waste fibers. Hence, the environmental impact of textile products can be controlled by recycling them. Consumption of post-consumer textile waste fiber is the key to reducing the new material needs in the textile supply chain. The closed-loop apparel supply chain can help developing countries generate maximum financial value with minimal environmental damage. In developing countries, value extraction from post-consumer textile waste recycling is essential to meet international consumer demands for cleaner production.

Architectural Patterns for Building Scalable Enterprise Forecasting Platforms

The architecture of modern enterprise forecasting platforms incorporates sophisticated components for managing hierarchical data structures, real-time collaboration, and dynamic scaling capabilities. These platforms address challenges in multi-channel inventory management, data synchronization, and forecast accuracy through innovative cloud technologies and architectural patterns. The implementation demonstrates significant improvements in synchronization speed, response times, and forecast accuracy while maintaining data consistency across distributed systems. The integration of advanced security mechanisms, real-time collaboration features, and performance optimization strategies enables organizations to handle complex forecasting scenarios across multiple organizational hierarchies. Through careful consideration of architectural patterns and implementation strategies, these platforms provide robust solutions for enterprise-scale forecasting challenges while ensuring data integrity, user productivity, and system reliability across distributed environments.

Development of performance-based deterioration models for bridge components

This study examines bridge component deterioration patterns in Idaho, USA, using National Bridge Inventory (NBI) data collected from 1983 to 2023. A total of 5774 bridges were analyzed, representing 69 combinations of construction materials and structural system designs. The study focused on six common bridge types: prestressed concrete slab, prestressed concrete girder, concrete frame, concrete slab, concrete girder, and steel girder bridges. Kaplan–Meier survival analysis was applied to generate survival curves and assess deterioration over time. The results revealed that prestressed concrete girder, steel girder, and concrete girder bridges exhibited slower deterioration and retained higher condition ratings over time. In contrast, prestressed concrete slab and concrete slab bridges showed faster early deterioration, while concrete frame bridges experienced moderate deterioration patterns. A multiple regression analysis was also conducted to evaluate the influence of various factors on deck deterioration. Bridge age, freeze–thaw cycles, and snowfall days were found to be significant predictors of deterioration. In contrast, bridge length, span length, and average daily traffic (ADT) had minimal effects. The reduced model explained 89.4% of the variance in deterioration outcomes.

Environmental and Economic Assessment of Desktop vs. Laptop Computers: A Life Cycle Approach

This study evaluates and compares the environmental and economic implications of desktop and laptop computer systems throughout their life cycles using screening life cycle assessment (LCA) and life cycle costing (LCC) methodologies. The functional unit was defined as the use of one computer system for fundamental home and small-business productivity tasks for over four years. The analysis considered the production, use, and end-of-life phases. The results showed the desktop system had a higher overall carbon footprint (679.1 kg CO2eq) compared to the laptop (286.1 kg CO2eq). For both systems, manufacturing contributed the largest share of the emissions, followed by use. Desktops exhibited significantly higher use phase emissions, due to greater energy consumption. Life cycle cost analysis revealed that laptops had slightly lower total costs (EUR 593.88) than desktops (EUR 608.40) over the 4-year period, despite higher initial investment costs. Sensitivity analysis examining different geographical scenarios highlighted the importance of considering regional factors in the LCA. Manufacturer-provided data generally showed lower carbon footprint values than the modeled scenarios. This study emphasizes the need for updated life cycle inventory data and energy efficiency improvements to reduce the environmental impacts of computer systems. Overall, laptops demonstrated environmental and economic advantages over desktops in the defined usage cases.

Spatiotemporal variations in atmospheric CH4 concentrations and enhancements in northern China based on a comprehensive dataset: ground-based observations, TROPOMI data, inventory data, and inversions

Abstract. Methane (CH4) is a potent greenhouse gas with a global warming potential that is 28–36-fold higher than that of CO2 at the 100-year scale. Northern China notably contributes to CH4 emissions. However, high uncertainties remain in emissions, and observation gaps exist in this region, especially in urban areas. Here, we compiled a comprehensive dataset (available at https://doi.org/10.5281/zenodo.10957950) (Han et al., 2024b), including ground- and satellite-based observations, inventory data, and modeling results, to study the CH4 concentration, enhancement, and spatiotemporal variation in this area. High-precision in situ observations from Beijing and Xianghe revealed that obvious seasonal cycles and notable enhancements (500–1500 ppb) occurred at a regional background site (Shangdianzi). We found significant increasing trends in the CH4 concentration over time in both the ground- and satellite-based observations and positive correlations between these observations. Anthropogenic emissions largely contributed to surface concentration variations and their increases in middle and southern Shanxi Province and Hebei Province. The posterior concentrations generally agreed well with the surface in situ observations (mean biases ranging from −2.3 to 80.7 ppb), and the RMSE ranges from 110 to 185 ppb, which is in the range from 5 % to 10 % of the XCH4. Moreover, a generally spatially consistent pattern was observed between the results of posterior results and the Tropospheric Monitoring Instrument (TROPOMI) column CH4 observations in four seasons. The posterior surface CH4 concentrations (with a spatial resolution of 0.5° × 0.625°) revealed that southern Shanxi, northern Henan, and Beijing exhibited relatively high levels (an increase of ∼ 300 ppb), which were positively correlated with the PKU-CH4 v2 emission inventory data. The inversion results using TROPOMI observations was 24.0 Tg, a decrease of 15.6 %, or 4.4 Tg, compared with the prior EDGARv4.3.2 (28.5 Tg). This study provides a comprehensive dataset of CH4 concentrations and enhancements in high-emission areas, which can benefit at the level of the research community and policy-makers in designing future observations, conducting atmospheric inversions, and formulating policies and at the city level, where high-spatial-resolution atmospheric inversions are highly needed at the kilometer scale.

Relationships between Sociosexuality and Dermatoglyphic Traits

In humans, prenatal development of brain dispositions to sex differences in mating behavior is difficult to study directly. Indirect prenatal markers, including dermatoglyphics, present a viable option. In this study we tested a hypothesis that some radio-ulnar contrasts in dermatoglyphic ridge counts could be related with human sociosexuality. Sociosexual Orientation Inventory (SOI) data from 180 young adults, along with fingerprints of their terminal phalanges (via hand scanning) were collected, and relationships between SOI and dermatoglyphics were analyzed. Typical sex differences in SOI were recorded with higher scores in males and lower in females. Among other results we found that on the index finger lower number of triradii and cores (i.e., mostly in loop type dermatoglyphic patterns) and radial-biased within-finger asymmetry in ridge counts typical for ulnar loops were connected with typical sex differences in SOI (higher in males and lower in females) while in subjects possessing an opposite dermatoglyphic arrangement – higher numbers of cores and triradii and ulnar-biased within-finger ridge count asymmetry typical in radial loops – sex differences in SOI scores disappeared. Recognized significant and systematic trends were mostly connected with variables derived from dermatoglyphic features on the 2nd and 4th fingers. Possible relationships with prenatal androgen causation are discussed.

Uncertainty in inventories for life cycle assessment: State‐of‐the‐art, challenges, and new technologies

Abstract Uncertainty is a critical factor that can hinder the quality and potential applications of life cycle assessment (LCA) results. A prominent source of uncertainty stems from the life cycle inventory (LCI) data. Various methodologies exist to estimate the uncertainty associated with LCI data, primarily based on the widely used structured pedigree matrix approach or the computationally intensive Monte Carlo simulation. This perspective review explores how new technologies (e.g., computational algorithms and data collection methods) from data science and related fields can contribute to identifying, quantifying, and reducing uncertainty in LCI modeling. A brief overview of the sources of uncertainty in LCI modeling and how they are addressed in current LCA practice is provided. Additionally, several new technologies are identified, and the potential benefits of their implementation in reducing uncertainties in LCI modeling are discussed. This perspective review concludes by identifying potential areas that require further development for these technologies.

Environmental impact assessment of maize cultivation system considering different irrigation methods

Maize is a key crop for the livestock sector being able to produce different fodder. Among these, ear maize silage is widely used as an energy source in the diets of pigs, dairy cows and fattening cattle. Given the variability of rainfall, irrigation plays a relevant role to achieve both satisfactory productivity and product quality. In this context, it is essential to explore the sustainability of different irrigation methods for maize cultivation.In this study, Life Cycle Assessment (LCA) was applied to evaluate the environmental impact of maize farms using different irrigation systems: pivot, drip, flood, and hose irrigation. One ton of ear maize silage at 48% moisture content was selected as functional unit and a “from cradle to farm gate” was considered as system boundary . Primary inventory data were collected mainly by surveys and interviews with the farmers. The Environmental Footprint 3.1 method was used to assess 14 impact categories. The results do not allow to clearly identify the best irrigation method across all environmental impact categories, therefore highlighting the need of trade-offs. While yield is the primary driver of environmental impacts, the influence of irrigation remains significant. Climate change was found to range from 116.66 kg CO2 eq./t of ear maize for flood irrigation to 207.42 kg CO2 eq./t for hose irrigation. Water use varied from 2178.29 m³ depriv./t for pivot irrigation to 10380.65 m³ depriv./t for flood irrigation. Regarding the contribution analysis, changing the considered environmental impact the main contribution varies, for example nitrous oxide is the main responsible to climate change, ammonia to particulate matter and acidification while nitrate and ammonia emissions to marine eutrophication. In conclusion, this study provides a basis for evaluating different irrigation methods, emphasising that irrigation plays a significant role in the overall environmental impact of maize cultivation, regardless of the end product.

Materials management under conditions of uncertainty: Does it matter much in healthcare?

ABSTRACT Materials management in healthcare has considerably widened in scope. In addressing the research question in the title of this paper, we review the pertinent literature and analyze healthcare inventory modeling. In determining the proper quantity of materials to meet patient demand without incurring unnecessary costs, we find that uncertainty in healthcare inventory owes predominantly to aggregate demand. Stock-out cost arises as inventory is exhausted by much higher or inadequately forecasted demand, inefficiently replenished stock, insufficient safety stock, and cash flow challenges in procurement. Overstock cost can result from reduced demand that racks up inventory costs and leaves healthcare organizations with expired or obsolete inventory, further risking their bottom line. Absent supply chain disruptions, the organizational propensity to purchase, when prices are low, can be contained by inventory models whose assumptions of essentially constant and deterministic demand we examine. We suggest that optimal stock calculations blend approaches and measures in finance and operations management and account for limitations of stock-out, overstock, and pricing illustrative of uncertainty. Materials managers can thus use historical order, inventory, and other relevant data and evaluate financial risks more efficiently, given that managing inventory is based on the specific material or product, and uncertainty is practically the norm in healthcare.

Ensemble Learning-Based Approach for Forecasting Inventory Data in Prefabricated Component Warehousing

Accurately predicting the storage area of prefabricated components facilitates transshipment scheduling and prevents the waste of storage space. Due to the influence of numerous factors, precise prediction remains challenging. Currently, limited research has addressed the prediction of storage areas for prefabricated components, and effective solutions are lacking. To address this issue, a GRU model with an attention mechanism based on ensemble learning was proposed. The model employed the Bo-Bi-ATT-GRU approach to address the time series prediction of storage areas. A Bayesian optimization algorithm was utilized to enhance parameter tuning and training efficiency, while an ensemble learning framework improved model stability. In this study, a port container dataset was used for experimentation, with root mean square error (RMSE) and mean absolute percentage error (MAPE) as evaluation metrics. Compared with the GM model, the R2 of the proposed model improved by 3.38%. Experimental results demonstrated that the ensemble learning-based prediction model offered superior performance in forecasting the storage area of prefabricated components.

Grasping at water: a gap-oriented approach to bridging shortfalls in freshwater biodiversity conservation.

Freshwater biodiversity is the fastest declining part of the global biota, threatened by multiple stressors including habitat loss and fragmentation, climate change, invasive species, water pollution, and abstraction by humans. A multitude of recent agenda-setting publications have pointed out key objectives and goals for addressing this freshwater biodiversity crisis, but important gaps must be overcome to reach ambitious conservation targets. In this perspective, we complement these high-level papers in freshwater conservation by highlighting important gaps in knowledge, governance, and implementation. This gap-oriented approach is designed to facilitate meaningful action by highlighting missing 'pieces' in the conservation process, and their connection to existing and emerging solutions in the literature. We derive 13 overarching gaps from a conference session and informal synthesis of recent literature in freshwater biodiversity conservation to catalyse research, advocacy, and action to meet freshwater goals for the post-2020 Kunming-Montreal Global Biodiversity Framework (GBF). Key gaps include inventory data on global freshwater biodiversity, collating and mobilizing conservation evidence in practice, improving coordination of ecological governance at scale -including within and across catchments-and navigating trade-offs between economic development, resource consumption, and priorities for freshwater biodiversity. Finally, we apply this gap-oriented approach to key language describing GBF goals for freshwater biodiversity conservation, and point out existing and emerging solutions which may help address important gaps. Major themes that address multiple gaps include the use of Nature-based Solutions and Other Effective Area-based Conservation Measures (OECMs), navigation of water management trade-offs between human and environmental needs, co-production of knowledge with Indigenous and local people and other stakeholders, integration of conservation research and action between aquatic and terrestrial ecosystems, and funding and policy mechanisms to facilitate conservation action and support meaningful monitoring of conservation evidence across hydrological scales.