Productive Research Articles (Page 1)

ABSTRACT This paper investigates the determinants and stability conditions of the public debt‐to‐GDP ratio within a theoretical framework representing the main characteristics of a monetary economy of production. To this end, we develop a dynamic Stock‐Flow Consistent (SFC) model based on the Supermultiplier approach, incorporating both bank and fiat money, capital accumulation and endogenous public debt service. Steady‐state values are derived, and stability is assessed through both analytical and simulation‐based approaches. Our main findings show that the public debt‐to‐GDP ratio is positively influenced by the saving rate and negatively influenced by the growth rate of autonomous demand components and the capital intensity of the economy. The effects of the interest rate and tax rate are found to be non‐linear, depending on the growth regime emerging in the economy. Under the “standard‐regime”, the tax rate has a negative impact, while the impact of the policy rate is positive. Given the exogenous parameters, and under the stability conditions, there exists a long‐run level of public debt‐to‐GDP ratio toward which the economy converges. These results challenge the rationale for applying blanket regulations on public budgets, disregarding the distinct traits of each economic system.

Developing highly efficient and stable electrocatalysts from inexpensive and earth-abundant elements represents a significant advancement in overall water splitting (OWS). This study focuses on the synthesis and evaluation of palladium-modified cobalt–phosphorus (PdCoP) and cobalt–iron–phosphorus (PdCoFeP) coatings for use as electrocatalysts in hydrogen evolution (HER), oxygen evolution (OER) and overall water splitting (OWS) in alkaline media. A facile electroless plating method is adopted to deposit the CoP and CoFeP coatings onto a copper surface (Cu sheet), with sodium hypophosphite (NaH2PO2) acting as the reducing agent. Pd crystallites were incorporated on CoP and CoFeP coatings using the galvanic displacement method. This study details morphological characterization (using SEM, EDX, and XRD), as well as electrochemical activity testing, for both HER and OER using linear sweep voltammetry (LSV) at different temperatures. The stability of the catalysts for HER was evaluated using chronoamperometry (CA) and chronopotentiometry (CP). The results show that the Pd-modified CoFeP and CoP catalysts exhibited lower overpotentials of 207 and 227 mV, respectively, for HER and 396 mV for OER at a current density of 10 mA cm−2 compared to the unmodified CoFeP and CoP catalysts. The innovation achieved in this study lies in combining a facile, low-cost deposition method (electroless plating followed by galvanic displacement) with a novel, highly effective ternary composition (PdCoFeP) that exploits synergistic electronic and morphological effects to achieve superior bifunctional performance for alkaline OWS, achieving a low cell voltage of 1.69 V at a current density of 10 mA cm−2. Overall, this research demonstrates that these synthesized materials are promising candidates for sustainable and economical hydrogen production.

A manual meat grinder is one of the essential tools for Micro, Small, and Medium Enterprises (MSMEs) in supporting the production process of meat-based food products. However, most of the designs available on the market still have several limitations, such as non-ergonomic working positions, low energy efficiency, and relatively high production costs. These conditions affect user productivity and comfort during operation. Based on these issues, this study aims to develop a more effective and valuable manual meat grinder design by applying the Value Engineering (VE) methodology based on Del L. Younker’s approach. The VE methodology is used to identify the main and supporting functions of the tool, analyze the relationship between cost and benefit, and generate alternative designs that can enhance functionality without compromising performance quality. The research process is carried out through six main stages: information, function analysis, creative, evaluation, development, and presentation. The results of the implementation show that the new design improves energy efficiency, reduces production costs, and enhances user comfort through ergonomic improvements. Thus, the Value in a single paragraph around 250-300 words. Engineering approach proposed by Del L. Younker has proven effective in supporting the development of simple, functional, and economical product designs that meet the needs of MSMEs.

Thiosemicarbazones down-regulate N-Myc expression in neuroblastoma cells via transcriptional and post-translational mechanisms.

Soil erosion affects agricultural and environmental sustainability and needs to be addressed. The Cagayan de Oro River Basin (CDORB), one of the major river basins in the Philippines, provides economic, social, and environmental services to the city and municipalities inside the basin. More than 70% of the area of the river basin is devoted to various forms of agricultural production. Land cover critically influences erosion dynamics as vegetation reduces rainfall impact, enhances infiltration, and limits sediment transport. This study employs the Hydrologic Engineering Center–Hydrologic Modeling System (HEC-HMS) integrated with the Modified Universal Soil Loss Equation (MUSLE) to evaluate soil erosion under different rainfall return periods (5, 10, 25, 50, 100 years) and four land cover scenarios: No Reforestation Intervention (NI), Maximum Forest Cover (MF), Slope-Based Land Use (SB), and Reforestation on Public Domain (PD). Model results showed that soil loss increased with rainfall intensity, with NI yielding the highest average erosion of 1443 t ha−1. Conservation scenarios reduced erosion by up to 53% compared to NI. Among the conservation scenarios, MF, SB, and PD yielded average erosion of 21, 716, and 1304 t ha−1, respectively. While the MF scenario had the least soil loss, no space was assigned for economic production. On the other hand, the SB approach offered the best balance, halving erosion across all rainfall return periods, but at the same time has sufficient space available for economic production. These findings demonstrate the scientific value of integrating HEC-HMS and MUSLE for event-based erosion modeling and highlight how comparing multiple land-cover scenarios can inform data-driven land use planning and policy formulation for sustainable watershed management.

This essay investigates the political economy of platform-dependent cultural production, focusing on music streaming, mobile games, and short-form video. While platforms still present themselves as democratizing tools, access to the means of production is decoupled from equitable opportunities for distribution, marketing, and monetization. The essay walks through studies that discuss this dynamic such as researchers counting songs on Spotify playlists, app store revenues, or using large-scale datasets of views on TikTok. The old blockbuster logic is alive and well, whether in 30-second TikTok clips or mobile games that rake in millions. To conceptualize these examples, the essay advances the heuristic of ‘platform dependency.’ By situating these patterns within longer histories of digitization, the essay underscores continuities alongside novel platform-specific asymmetries. It ends with a call for renewed scholarly attention to the flow of money and data across geographies and media industry sectors.

Driven by the dual imperatives of environmental protection and performance enhancement, the automotive industry has introduced new priorities for lightweight design in new energy vehicles. Automotive lightweight materials face the main challenges of uniform dispersion of the nanoparticles, scalable and economical manufacturing processes, dependable and lasting multi-material integration, and durability under service conditions. This review investigates the use of nanomaterials in lightweighting automotive applications by surveying the four main classes of carbon, ceramic, silicon, and polymer nanocomposites and evaluating their synthesis routes, interfacial engineering, and performance metrics. A mixed approach using literature review and specific case studies was applied to compare the mechanical properties, dispersion stability, and scale up difficulties of different nanofiller systems. Significant works on carbon nanotube and graphene reinforced carbon fibre composites, alumina nanocoated, high aspect ratio silicon carbide nanowires, and nano-clay enhanced polymers were studied to calculate mass loss, stiffness loss, and loss of durability in the body, chassis, and interior components. The obtained results revealed that the incorporation of nanomaterials enables component weight reductions of 10 to 60% while continuing to provide good structural strength, stiffness, and corrosion or wear resistance. Problems with nanoscale particle agglomeration, economic mass production, and safety standardization were noted. The review provided final remarks on optimizing dispersion techniques to minimize material and process expenditure, effectively accelerating the use of nanotechnology in automotive.

This study looked into the economic production of self-compacting concrete (SCC) using affordable and locally available materials such as fly ash (FA), laterites (LA), and polyethylene terephthalate (PET) fibres. To achieve optimal properties of SCC, Response Surface Methodology (RSM) - Central Composite Design (CCD) was employed. Thus, twenty different SCC mixes were designed with varying input factor combinations (FA: 0–40%, LA: 0-50%, and PET fibre: 0–2%) and tested for six responses (rheological properties, namely slump flow, V-funnel time, and L-Box; and mechanical properties, namely compressive, split-tensile, and flexural strengths test). Mathematical models were created in response to the experimental results and assessed using analysis of variance (ANOVA) test. L-Box, V-funnel, and Slump flow test results showed that while fly ash may improve the flowability of SCC, inclusion of high volume of PET-fibres (above 1%) and laterite (above 25%), has high negative impact on SCC flowability. The results further revealed that inclusion of PET-fibres in SCC largely improves the flexural strength (FS) and split tensile strength (STS) by about 20%. However, high volume of laterite contributes negatively to the strength values. Although SCC’s compressive strength decreased with addition of each or a combination of the three different materials, a combination of 20% fly ash, 25% laterite and 1% PET-fibres can result in strength values that are comparative to that of the control mix. The RSM models developed showed relatively good predictive capabilities especially for the compressive strength, L-box and V-funnel models with adjusted R 2 values ranging between 0.8 – 0.9. Among all the combinations, it is recommended that 20% FA, 25% LA, and 1% PET fibres be adopted in production of sustainable and cost-effective self-compacting concrete, as it gave relatively stable characteristics compared to the control mix in terms of the strength and rheological properties.

Remnant forest patches within agricultural landscapes may play an underappreciated role in tropical carbon storage. Understanding their carbon storage contribution will inform land-use policies to balance economic production with forest-based climate mitigation strategies, especially in tropical developing countries where agriculture dominates. This study quantified and compared carbon stocks of five biomass pools (overstorey, understorey, litter, roots, and soil) using 54 nested plots established in nine pairs of remnant forest patches and adjacent banana (Musa spp.) agroecosystems in Bukidnon, Southern Philippines. Results showed that forest patches stored most carbon in the overstorey layer (65-75%) followed by roots (18-22%), litter (5-8%) and understorey layers (< 2%). Banana agroecosystems stored more carbon in the pseudostems and litter layer with 40-45% and 45-50% of the total biomass carbon, respectively, while roots had only 8-10%. The absence of understorey vegetation in banana plantations may indicate the intensive nature of management practices in this agroecosystem. Forest patches stored significantly higher carbon in the overstorey (77.06 ± 69.71 Mg C ha−1), understorey (1.24 ± 0.44 Mg C ha−1), and roots (20.43 ± 17.23 Mg C ha−1). Interestingly, litter carbon was higher in banana agroecosystems (20.40 ± 12.15 Mg C ha−1) than in forest patches (7.67 ± 3.43 Mg C ha−1) likely due to the practice of leaving banana residues after harvest. Total biomass carbon was two to three times greater in forest patches (106.39 ± 88.40 Mg C ha−1), with significantly higher carbon accumulation (2.62 ± 2.18 Mg C ha−1 yr−1) and CO2 fixation rates (9.60 ± 7.98 Mg CO2-eq ha−1 yr−1) than banana plantations. Although SOC levels were statistically comparable between the two land uses, further research is needed to confirm whether the apparent stability of SOC in banana plantations is sustainable or whether it represents a transient stage before eventual depletion. Nonethless, we recommend to prioritize the conservation and restoration of forest patches as permanent features within agricultural landscapes to optimize carbon storage and mitigate ecological degradation.

This study assesses the economic performance, scale efficiency, and production challenges in Nigeria’s catfish aquaculture sector across pre-COVID and COVID periods, with post-COVID insights from sectoral perspectives. Using a nationally representative dataset, the analysis combines scale-based evaluation, descriptive statistics, profitability metrics, and a quadratic cost function. Findings show that small-scale producers dominate the industry, though technical efficiency and profitability vary by scale. While the sector remained profitable with average profits per kilogram of N126.60 and N159.48 in pre-COVID and COVID periods, respectively, micro- and small-scale farmers recorded low returns, with many experiencing margins that may not justify continued participation. Feed-related challenges, particularly cost and quality, were the most frequently reported constraints and exit reasons. Reliance on imported feeds has declined due to increased domestic feed production. The estimated optimal production scale is between 28,000 kg/year in the pre-COVID period and 31,000 kg/year during COVID, with unit production costs minimized at approximately ₦491/kg and ₦573/kg, respectively. In the post-pandemic context, macroeconomic pressures such as inflation and currency volatility have further reduced profit margins, making resilience more critical.

ABSTRACTIn recent years, the market's demand for gluten‐free products has been steadily rising, and similarly, the interest in the functionalization of the food matrix to obtain healthier products has been increasing. Furthermore, there is a growing interest in valorizing agri‐food by‐products that still contain ingredients that enhance the nutritional properties of food. The objective of this study was to evaluate the cooking and texture quality parameters, starch digestibility, and total dietary fiber of gluten‐free pasta enriched with varying additions (10% and 15%) of two food industry by‐products: tomato waste powder and linseed cake powder. The results indicate that the enriched gluten‐free pasta samples exhibited improved nutritional profiles, although some quality parameters were at times affected. The linseed cake powder improved resistant starch content, lowered cooking loss, and increased adhesiveness more effectively than the tomato waste powder. Conversely, tomato waste powder‐enriched gluten‐free pasta had higher dietary fiber (6.5% and 8.7% with 10% and 15% addition, respectively) and increased cooking loss (by 100% and 131% for 10% and 15%, respectively), as well as lowered firmness (by 9% and 34% for 10% and 15%, respectively). Nevertheless, all enriched samples showed a significant reduction in their predicted glycemic index, which corresponded to the level of by‐product addition. This study demonstrates the potential of utilizing food industry by‐products to enhance the nutritional value of gluten‐free pasta, thereby supporting a circular economy in food production.

The discovery of non-toxic, bioresorbable silicon electronics is a major breakthrough in the fields of transient, dissolvable biomedical implants and environmental monitors, as it opens up the possibility of producing versatile components based on established semiconductor processes. However, given the limited lifespan of such electronics, it is essential to consider economical manufacturing and production strategies that reduce the unit price for commercialization. Here, we introduce a solution-processable and photo-patternable approach that is facile, cost-effective, and widely accessible for a monolithic 3D fabrication of soft, stretchable, and transient electronics. Optimized chemical synthesis and rational materials engineering yield biodegradable/biocompatible organic insulators, semiconductors, and conductors that can be layered/assembled in sophisticated configurations without impairing underlying components. Direct solution-casting of the materials enables the fabrication of sensors with various modalities and transistors. In vivo implantation of soft, conformable electrode arrays into the brain and heart of animal models demonstrates spatiotemporal electrophysiological monitoring (electroencephalography and electrocardiography) and therapeutic interventions (epileptic seizure suppression and cardiac pacing), highlighting the broad applicability in diverse bio-integrated electronic systems.

To implement the development concept of “lucid waters and lush mountains are invaluable assets”, China began to implement a ban on commercial logging of natural forests in 2015. The implementation of the ban has affected the structural adjustment of China's forestry industry. Based on the analysis of the internal relationship between the logging ban policy and industrial structure adjustment, this study uses the grey relational analysis method to explore the dynamic changes in China's forestry industry structure before and after the implementation of the natural forest logging ban policy and predict the development of China's forestry industry in the next 12 years through the GM (1, 1) model. Research shows that the implementation of the ban policy has the greatest impact on the development of the tertiary industry. The planting and collection of economic forest products have become an important industry in the primary industry, and enterprises are gradually shifting their focus to non-wood forests. Forest tourism and leisure services have become green and key industries with great growth potential in the forestry tertiary industry. In the future, China will maintain the industrial pattern of “two, one and three,” and the industrial structure will continue to be optimized.

The proliferation of advanced text-to-image generative AI represents a paradigmatic shift in visual culture. It instigates a profound crisis for established concepts of authorship and aesthetics while also raising critical questions about artistic labor and the political economy of cultural production. This study investigates the complex negotiations between human creators and algorithmic systems. This study employed a qualitative, multi-modal methodology. A visual semiotic analysis was conducted on a curated corpus of 300 artworks from Midjourney, DALL-E 3, and Stable Diffusion, sampled to mitigate platform-specific biases. This was triangulated with a thematic analysis of semi-structured interviews with a purposive sample of 15 artists and designers actively using these tools. The methodological limitations, specifically the sample's "adopter-centric" bias, are explicitly acknowledged. The visual analysis identified a distinct "algorithmic gaze" characterized by hyper-compositing, surreal corporeal logic, and stylistic convergence, reflecting both the system's non-human perspective and the biases of its training data. The thematic analysis of artist interviews revealed three dominant experiential themes: the artist's role being reframed as curatorial, the creative process as a form of dialogue, and the interaction as an exploration of the system's "latent space". These participant narratives often frame the interaction in terms of empowerment and collaboration. In conclusion, generative AI reconfigures authorship into a distributed network phenomenon. However, this study argues that this posthuman collaboration occurs within a system structured by significant power asymmetries. The aesthetics of the algorithmic gaze are not neutral but are shaped by the commercial and ideological imperatives of the platforms. The artist's experience of empowerment coexists with broader material processes of deskilling, alienation, and the centralization of cultural production. Understanding this new paradigm requires a critical synthesis of posthumanist theory and political economy.

Many existing economic production quantity (EPQ) models are based on the assumption of an exponential demand rate. However, this assumption does not accurately reflect the demand pattern of most real-life items, as product demand rarely changes at an exponential rate. In practice, demand often varies throughout the inventory cycle; it may start slow, increase gradually, and decline toward the end, making the power demand rate a more realistic representation. This research proposes an optimal production model for non-instantaneous processes of decaying goods with a two-stage production period, power demand pattern, linear holding cost, and partial backorder. Shortages are allowed and partially backlogged. The necessary and sufficient conditions for the existence of an optimal solution are established. The model determines the optimal time with a positive inventory, duration of shortages, total production cost, and economic production quantity. We demonstrate the models validity through a numerical example and then conduct a comparative analysis with an existing model. Results show that the proposed model produces a lower average total production cost, indicating better performance. Furthermore, a sensitivity analysis is conducted on selected parameters to evaluate their impact on total cost and EPQ, with recommendations provided to help manufacturers minimize costs.

Tourism is one of the strategic sectors that contributes significantly to both national and local economic growth. This article highlights the importance of the tourism sector, particularly marine tourism, in supporting sustainable development in Indonesia. Employing a descriptive approach and secondary data analysis, the article examines trends in foreign exchange earnings from Indonesia’s tourism sector between 2015 and 2024. The data reveal that although there was a sharp decline during the COVID-19 pandemic, foreign exchange earnings from this sector increased significantly in the following years. Beyond its economic impact, the tourism sector also plays a vital role in achieving the Sustainable Development Goals (SDGs), such as poverty alleviation, decent economic growth, responsible consumption and production, and the protection of marine ecosystems. This study recommends enhancing the appeal of both man-made and natural tourist attractions to support the sustainable development of marine tourism in Indonesia.

This study aims to assess the impact of six components of a conducive ecosystem on the productivity of oil palm smallholders in Bakong and Marudi, Sarawak. The components examined include safety, family labour, effective leadership, technology, environmental conditions, and collaborative networks. Despite extensive research on agricultural productivity, limited empirical studies have systematically evaluated how these interrelated ecosystem factors affect smallholder performance, particularly within the context of the Malaysian palm oil industry. Addressing this gap, the study offers a contextualised analysis of ecosystem-based productivity determinants in a key producing region. A quantitative approach was employed using a cross-sectional survey design involving 345 randomly selected smallholders from the Malaysian Palm Oil Board (MPOB) Miri Branch database. Data were collected through a structured questionnaire and analysed using descriptive statistics and multiple regression analysis. The findings reveal that all six ecosystem components positively influence smallholder productivity, with safety demonstrating the strongest impact (30.55%). However, only three components safety, family labour, and effective leadership were identified as statistically significant predictors. These results support the economic production theory and Maslow’s hierarchy of needs, highlighting the importance of both physical inputs and motivational factors in achieving optimal agricultural output. The study contributes novel insights by integrating both tangible and intangible ecosystem components within a unified analytical framework. It proposes that smallholder development strategies adopt an ecosystem-based approach, emphasizing farm security, community empowerment, and appropriate technology adoption. The findings have important implications for policy formulation and the advancement of sustainable practices in the palm oil industry.

The desert riparian forest oasis, dominated by Populus euphratica and Tamarix chinensis, is an important barrier to protect the economic production and habitat of the Tarim River Basin. However, there is still a lack of high-precision spatial distribution data of desert ri-parian forest species below 10 m. The recently launched PlanetScope CubeSat constella-tion, which provides daily earth observation imagery with a resolution of 3 m, offers a highly favorable dataset for mapping the high-resolution distribution of P. euphratica and T. chinensis and an unprecedented opportunity to explore the optimal phenology window to distinguish between them. In this study, time-series PlanetScope images were first used to extract phenological metrics of P. euphratica, dividing the annual life cycle into four phenology windows: duration of leaf expansion (DLE), duration of leaf maturity (DLM), duration of leaf fall (DLF), and duration of the dormancy period (DDP). The random forest model was used to obtain the classification accuracy of 16 phenological window combinations. Results indicate that after gap filling of vegetation index time series, the identification accuracy for P. euphratica and T. chinensis exceeded 0.90. Among individual phenology windows, the DLE window exhibited the highest classification accuracy (average F1-score 0.87). Among the two phenology window combinations, the DLE-DLF and DLE-DLM windows have the highest classification accuracy (average F1-score 0.90). Among the three phenology window combinations, DLE-DLM-DLF displayed the highest classification accuracy (average F1-score 0.91). Nevertheless, the inclusion of features within the DDP window led to a decrease in accuracy by 1–2% points, which was unfavorable for discriminating tree species. Additionally, features observed during the phenology asynchrony period were found to be more valuable for distinguishing between tree species. Our findings highlight the potential of PlanetScope constellation imagery in tree species classification, offering guidance for selecting optimal image acquisition timing and identifying the most valuable images within time series data for future large-scale tree mapping.

Investigating the impacts of future oil prices on the achievement of 1.5°C climate goal

This paper presents a mathematical framework for analysing the Economic Production Quantity (EPQ) model for items with non-instantaneous deterioration. The non-instantaneous nature of deterioration introduces complexities that are not present in the classical EPQ model with deterioration. This framework allows for a deeper exploration of the model's properties and enables a comprehensive investigation of optimal inventory levels, both with and without full backlogging. By identifying the stationary point of the objective function representing total inventory costs per unit time, a unique optimal inventory policy can be determined. Numerical examples are provided to illustrate the findings.