Cost-benefit Research Articles

Automated Inventory Management Systems with IoT Integration to Optimize Stock Levels and Reduce Carrying Costs for SMEs: A Comprehensive Review

Automated inventory management systems integrated with Internet of Things (IoT) technology represent a transformative approach for Small and Medium-sized Enterprises (SMEs) in optimizing their stock levels and reducing carrying costs. A literature review also shows that there is progress in developing automated solutions, such as IoT sensors, real- time data analytics, and cloud-based applications that improve inventory control. A study shows that the adoption of IoT in automation has seen improvement in the accuracy of inventory, a reduction in stockouts, and carrying costs among SMEs. Research suggests operational improvements including reduced downtime from real time tracking, reverse logistics systems with intuitive demand forecasting for ideal stock replenishment and automation of reordering systems while effectively managing working capital. Materials and Methods: Research methodology encompassed a comprehensive analysis of peer-reviewed literature, case studies, and empirical research focusing on automated inventory management systems with IoT integration in SMEs. Criteria for choosing the literature included articles focusing on the outcomes of IoT implementation, technical integration, and performance of inventory systems. Data extraction main concern was on the efficiencies of the SC such as inventory accuracy, carrying costs, stockouts, and ROI. Descriptive methods used involved comparisons between pre-implementation and post- implementation data, use of statistical tools for measurement of performance enhancement and assessment of factors important in the deployment of the system. Results Implementation of IoT-integrated automated inventory management systems demonstrated significant improvements across multiple performance metrics. Studies reported average inventory accuracy improvements of 25-35%, reduction in carrying costs [1] by 20-30%, and decrease in stockout incidents by 35-45%. Real-time monitoring capabilities led to improved demand forecasting accuracy by 40%, while automated reordering systems reduced manual processing time by 60%. Cloud-based platforms enabled better inventory visibility and control, resulting in working capital optimization of 15-25%. SMEs implementing integrated systems reported enhanced supplier collaboration, reduced lead times, and improved customer satisfaction levels. Cost-benefit analyses indicated positive ROI within 12-18 months of system deployment. Discussion Analysis reveals several key factors contributing to successful implementation of automated inventory management systems with IoT integration. Critical success factors include proper system architecture design, effective change management strategies, and comprehensive staff training programs. Integration challenges primarily revolve around initial investment costs, technical expertise requirements, and system interoperability concerns. Studies show that the greater gains are experienced by SMEs with higher ITOR and those engaged in intricate supply chain operations. Literature review also points to differences in implementation strategies across different sectors and in their recovery, with manufacturing and retail sectors having the highest levels of adoption and improvement. Conclusion IoT-integrated automated inventory management solutions should be adopted by SMEs and are affirmed by ample data to help optimize stock status and minimize carrying costs. The tangible benefits that could be noted are accuracy in inventory, less operational costs, visibility of supply chain, and optimal use of working capital. In appointing the factors affecting the implementation success, it requires the assessment of the technical feasibility and organisational readiness as well as the management of change strategies. Research shows that dynamic technology factors will continue to improve the system’s performance and increased availability to SMEs. Due to advancement in IoT technology, artificial intelligence and cloud computing, there are potential factors that may boost the performance and cost of automatically Managed inventory systems in the future.

Advancements in Hydroponic Systems: A Comprehensive Review

Hydroponics, the practice of growing plants without soil using mineral nutrient solutions in water, represents a significant shift in agricultural methodologies. Modern hydroponic systems have evolved substantially since the early 20th century, with advancements in system design, automation, nutrient management, and environmental control enhancing efficiency, scalability, and applicability. This review examines recent innovations that have addressed traditional challenges and created new opportunities for hydroponic cultivation. Hydroponics offers advantages over traditional soil-based agriculture, including precise nutrient control, reduced water usage, and the elimination of soil-borne diseases and pests. These benefits are critical in addressing modern agricultural challenges such as soil degradation, water scarcity, and the need for increased food production for a growing global population. Hydroponic systems can be implemented in diverse environments, making them adaptable solutions for enhancing food security and sustainability. Key developments in various hydroponic systems are highlighted, including the Nutrient Film Technique (NFT), Deep Water Culture (DWC), Ebb and Flow, Aeroponics, Wick Systems, and Drip Systems. Innovations in these systems focus on optimizing nutrient delivery, oxygenation, and integrating sensors for precise control, improving overall performance and yield. Technological advancements, such as automation and control systems, sensors, and monitoring technologies, have revolutionized hydroponic farming by enabling real-time data collection and environmental management. The integration of the Internet of Things (IoT) and smart farming practices, combined with data analytics and machine learning, has further optimized system performance and decision-making. LED lighting and vertical farming techniques have maximized space utilization and improved crop yields, particularly in urban environments. Advances in nutrient solutions, disease management, and water quality have optimized plant health and resource efficiency. Economic and environmental considerations, including cost-benefit analyses and comparisons with traditional agriculture, highlight the potential for hydroponics to offer better returns on investment and reduce environmental impact. Despite the significant progress, challenges such as high initial setup costs and technical complexities remain. Future research opportunities and interdisciplinary collaborations are essential to address these challenges and drive further innovation in hydroponic farming.

Machine learning approach for detection of MACE events within clinical trial data.

Randomized controlled trials (RCTs) are the gold standard for clinical research but may not accurately reflect the impact of medicines in real-world settings. Supplementing RCTs with insights from real-world data (RWD) can address known limitations by including more diverse patient populations, additional types of sites-of-care, and practices more representative of the care most people receive. One current challenge in using RWD is the lack of an algorithmic approach to identifying outcomes. To address this, machine learning models for identifying a frequently used outcome, Major Adverse Cardiovascular Events (MACE), were developed in Clinical Trial Data (CTD). Anonymized CTD sourced from the Medidata Enterprise Data Store were used to develop model features on the condition that they would be useful for labelling MACE events and that they could also be found in RWD. These features were used to train three random forest models to identify each component of 3-point MACE in a patient's clinical trial journey. Performance metrics for the models are presented (recall = 0.72 [0.07], precision = 0.68 [0.12] - mean, [SD]) along with the top contributing features. We show that the models can be tuned specifically to replicate the adjudication panels' results and present a cost-benefit analysis for deploying such models in clinical trial settings. We demonstrate the viability of using advanced algorithms for identifying clinical outcomes in prospective clinical trials. Deployment of such models could reduce the resources required to conduct RCTs. Extending such models to RWD would facilitate approval of pragmatic clinical trials for regulatory submissions.

Cost–benefit analysis as a decision tool for effective conservation planning—The case of the Nyerere Selous‐Udzungwa wildlife corridor in Tanzania

AbstractCost benefit analysis (CBA) is used in many fields to ensure efficient allocation of scarce resources but is rarely applied in conservation. By using a common metric to evaluate projects in complex social‐ecological systems, CBA can help to maximize the impact of conservation funding. It can also help to interrogate issues of distributional equity, plan for effective community‐based conservation, and inform future research and strategic priorities. We demonstrate this using the example of the Nyerere Selous‐Udzungwa Wildlife Corridor in Tanzania, a wildlife corridor aiming to restore connectivity between two protected areas to enhance African elephant (Loxodonta africana) conservation outcomes and mitigate human–elephant conflict. We combine novel data on elephant crop depredation with crop price and productivity data, elephant valuation methods, and ecosystem service values to analyze corridor costs and benefits from contrasting global and local community perspectives. From the global perspective, we find benefits to outweigh costs by at least 4.6:1. From the communities' perspective, we find that while substantial benefits should secure buy‐in to the project, continued subsidy will be required to cover the costs. Our findings support generalized recommendations for application of CBA across diverse systems and conservation priorities.

Prophylactic closed-incisional negative pressure wound therapy following posterior instrumented spinal fusion: a single surgeon's experience and cost-benefit analysis.

Surgical site infections (SSIs) following spine surgery are associated with morbidity and resource utilization. Applying prophylactic closed-incisional negative pressure wound therapy (ciNPWT) during posterior instrumented fusion has mixed results in reducing rates of wound complications and SSI. We evaluated the clinical efficacy and potential cost-savings associated with ciNPWT in high-risk patients receiving posterior instrumented spinal fusion. We retrospectively reviewed patients receiving posterior instrumented spinal fusion for any surgical indication between July 1, 2017 and December 31, 2019, and compared rates of wound dehiscence, SSI, and reoperation for wound complications between standard surgical dressings and ciNPWT. Surgical dressing selection was based on the senior author's assessment of infection risk factors. A total of 229 patients (n = 85 standard surgical dressings, n = 144 ciNPWT) were included. The ciNPWT group had significantly more risk factors for wound-related complications, including older age (61.8 vs. 58.5 years, p = 0.042), diabetes mellitus (36.8% vs. 23.5%, p = 0.037), more instrumented levels (5.6 vs. 3.9, p < 0.0001), estimated blood loss (1298 vs. 998 mL, p = 0.036), and deformity was the predominant operative indication (29.9% vs. 17.7%, p = 0.040). Prophylactic ciNPWT was associated with significantly lower rates of wound dehiscence (21.5% vs. 34.1%, p = 0.036) and SSI (8.3% vs. 21.2%, p = 0.005). Number needed to treat with ciNPWT to prevent one SSI was 8 patients. The cost of preventing one SSI was $4,560. Cost-benefit analysis demonstrated a potential mean savings of $21,662 per operative SSI prevented and $270,775 per 100 patients undergoing posterior instrumented fusion with ciNPWT. Prophylactic ciNPWT use is a cost-effective means of reducing rates of wound dehiscence and SSI following posterior instrumented fusion.

Predecisional information search adaptively reduces three types of uncertainty

How do people search for information when they are given the opportunity to freely explore their options? Previous research has suggested that people focus on reducing uncertainty before making a decision, but it remains unclear how exactly they do so and whether they do so consistently. We present an analysis of over 1,000,000 information-search decisions made by over 2,500 individuals in a decisions-from-experience setting that cleanly separates information search from choice. Using a data-driven approach supported by a formal measurement framework, we examine how people allocate samples to options and how they decide to terminate search. Three major insights emerge. First, predecisional information search has at least three drivers that can be interpreted as reducing three types of uncertainty: structural, estimation, and computational. Second, the selection of these drivers of information search is adaptive, sequential, and guided by environmental knowledge that integrates prior expectations, task instructions, and personal experiences. Third, predecisional information search exhibits substantial interindividual heterogeneity, with individuals recruiting different drivers of information search. Together, these insights suggest that human information search is complex in ways that cannot be fully explained by monolithic accounts of information search, including proposals focused on estimation uncertainty or cost-benefit analysis. We conclude that broader theories of human information-search behavior are necessary.

Tuberculosis Preventive Treatment for Pregnant People With Human Immunodeficiency Virus in South Africa: A Modeling Analysis of Clinical Benefits and Risks.

Although prior studies of tuberculosis-preventive treatment (TPT) for pregnant people with human immunodeficiency virus (PPWH) report conflicting adverse pregnancy outcome (APO) risks, international guidelines recommend TPT for PPWH. We used a microsimulation model to evaluate 5 TPT strategies among PPWH receiving antiretroviral therapy in South Africa: No TPT; 6 months of isoniazid (6H) or 3 months of isoniazid-rifapentine (3HP) during pregnancy (Immediate 6H or Immediate 3HP) or post partum (Deferred 6H or Deferred 3HP). The primary outcomes were maternal, fetal/infant, and combined deaths from causes potentially influenced by TPT (maternal tuberculosis, maternal hepatotoxicity, stillbirth, low birth weight [LBW], and infant tuberculosis). Tuberculosis during pregnancy confers 250% and 81% higher modeled risks of stillbirth and LBW, respectively. In lower-risk or higher-risk scenarios, immediate TPT confers 38% lower or 92% higher risks of stillbirth and 16% lower or 35% higher risks of LBW. Immediate TPT would minimize deaths among PPWH. When TPT confers higher stillbirth and LBW risks, immediate TPT would produce the most combined maternal and fetal/infant deaths, even with low maternal CD4 cell count and high tuberculosis incidence. If immediate TPT yields a <4% or <20% increase in stillbirth or LBW, immediate TPT would produce fewer combined deaths than deferred TPT (sensitivity analysis range, <2%-22% and <11%-120%, respectively). If APO risks are below identifiable thresholds, TPT during pregnancy could decrease combined maternal and fetal/infant deaths. Given uncertainty around isoniazid's risks, and the low threshold at which APO risks could outweigh benefits from tuberculosis deaths averted, studies of newer TPT regimens among PPWH are warranted to inform guidelines.

Analysis of the Factors Influencing the Purchase of Electric Vehicles in Brazil

The transport sector, and especially the increase in individual vehicle ownership, contribute significantly to air pollution. The transition to electric vehicles (EVs) is seen as a sustainable alternative to reduce emissions of polluting gases. However, in Brazil, the EV market has not yet reached a significant size. Given this scenario, this study aims to analyze the factors that influence the decision to buy EVs in Brazil, highlighting personal, psychological, economic, performance, and environmental variables and barriers. The aim is also to develop a model with guidelines that can help stakeholders. The quantitative stage of the study involved a survey of 514 respondents. The data were analyzed using statistical methods, including structural equation modeling (SEM), which allowed for a deeper investigation of the proposed hypotheses. The survey findings reveal that, in the Brazilian context, performance factors—such as autonomy, availability of recharging infrastructure, and maintenance—are the main drivers influencing EV purchase decisions. Environmental factors, including energy reuse, pollution reduction, and minimizing environmental impacts, have also gained significant importance. Economic factors are crucial, particularly concerning cost–benefit perceptions. The differences between Brazil and other regions highlight the importance of accounting for cultural and economic variations when analyzing consumer behavior towards EVs.

HPB SO13 - Comparative analysis of cost and clinical benefit of Robotic Surgery (RS) vs Laparoscopic Surgery (LS) for the treatment of symptomatic liver cysts

Abstract Background The treatment for symptomatic liver cysts involves the removal of a large portion of the cyst wall (deroofing/fenestration). Robotic surgery (RS) is now used more commonly to treat liver cysts. It is unclear whether RS or laparoscopic surgery (LS) results in superior clinical or economic outcomes. The objective of this study is to compare the cost and clinical benefit of RS vs LS in adults with liver cyst(s). Method Patients meeting inclusion criteria were identified from operating notes and a prospectively held hospital database between 2019 to 2024. Eligible candidates were further investigated for post-operative outcome, length of stay (LOS), subsequent in-person clinic follow-ups for review and removal of drain, and further treatment in patients with recurrence of liver cyst. Financial data for all surgical equipment in RS and LS were provided by sales representatives from the relevant industries. Results Forty-four LS and seven RS patients were analysed. Neither approach recorded a return to theatre. There was no mortality in either group. There was a significantly shorter LOS for RS vs LS patients (median LOS=1 vs 2 days, p&amp;lt;0.05). There was no significant difference in bile leak, drain duration or cyst recurrence between LS and RS. The economic analysis revealed that without taking into account reduced LOS, the costs of RS and LS was £1261.70 and £1733.61 per procedure, respectively. The increased cost in LS was primarily due to multiple stapler firings (median staplers used=5) vs zero staplers in RS. Conclusion Robotic liver cyst surgery is cheaper and provides better clinical outcomes in terms of shorter LOS and reduced complications. Further studies are warranted to examine the long-term cost-effectiveness of RS.

Non-Smoke Tobacco Consumption in India: A Cost-Benefit Analysis

This study evaluates the economic and social impacts of non-smoke tobacco consumption in India and compares them with the tax revenue generated by the government from this industry. Non-smoke tobacco products, such as chewing tobacco and pan masala, are associated with various health and environmental problems, such as oral cancer and littering. The study uses the concept of externalities to analyse the costs and benefits of non-smoke tobacco consumption for the society and the government. Based on available data and assumptions, the study estimates the expenditure on oral cancer treatment and cleanliness, and the revenue from direct and indirect taxes on non-smoke tobacco products. The study finds that the government collects more revenue than it spends on mitigating the negative externalities of non-smoke tobacco consumption, but the social costs are still significant. The study suggests that the government should implement more effective tobacco taxation and control policies to reduce the consumption and harm of non-smoke tobacco products.

Efficacy of new generation herbicide mixtures in irrigated maize (Zea mays)

The experiment was conducted during rainy (kharif) seasons of 2020 and 2021 at Tamil Nadu Agricultural University, Coimbatore, Tamil Nadu to study the efficacy of new generation herbicide mixtures in irrigated maize (Zea mays L.). The experiment was laid out in a randomized complete block design (RCBD) consisted of 9 treatments including pre-emergence herbicides, new generation post emergence herbicides and other weed management practices [T1, Weedy check; T2, Weed free check; T3, Spraying of atrazine @1 kg/ha as pre-emergence + Hand weeding on 25 DAS (days after sowing); T4, Spraying of atrazine @0.75 kg/ha as pre-emergence + Spraying of topramezone @25.2 g/ha as post-emergence on 25 DAS; T5, Spraying of atrazine @0.75 kg/ha as pre emergence + Tembotrione @120 g/ha on 25 DAS; T6, Spraying of atrazine @1 kg/ha as pre-emergence + Topramezone @25.2 g/ha on 25 DAS; T7, Spraying of atrazine @1 kg/ha as pre-emergence + Tembotrione @120 g/ha on 25 DAS; T8, Spraying of topramezone @25.2 g/ha + atrazine @0.75 kg/ha on 15 DAS; and T9, Spraying of tembotrione @120 g/ha + atrazine @0.75 kg/ ha on 15 DAS], replicated thrice. The results evinced that application of topramezone at 25.2 g/ha + atrazine at 0.75 kg/ha on 15th day after sowing significantly reduced the weed density and dry weight leading to higher weed control efficiency and lower weed index of 62.0% and 3.1%, respectively, during both the years of study. This treatment resulted in higher grain yield (7675 kg/ha), net returns (₹72884/ha) and benefit cost (B:C) ratio (2.33) in irrigated maize.

A mixed method approach to analysing patterns and drivers of antibiotic use and resistance in beef farms in Argentina

IntroductionAntimicrobial resistance is a challenge to be faced by all livestock sectors; within beef farming, antibiotic use patterns vary by country and management practices. Argentina is a country with high beef production &amp;amp; consumption but limited information surrounding antibiotic use. The aims of this project was to understand how antibiotics are being used across the beef industry in Argentina and exploring drivers of usage.MethodsQuantitative and qualitative data was collected by: A survey of breeding and feedlot farms including antibiotic use (from purchase data); a detailed analysis of two feedlot farms’ therapeutic antibiotic use records; a survey of vets’ views on certain antibiotic practices; and a focus group of farmers and vets focusing on wider influences affecting decision making. Antibiotic use data was calculated using mg/population corrected unit (PCU) (ESVAC) and thematic analysis was used to identify drivers of antibiotic use among participants.ResultsThe median use across 17 farms that supplied purchase data was 76.52 mg/kg PCU (ESVAC; IQR = 36.81 mg/kg PCU [ESVAC]). The detailed farm records showed that the largest reason for treatment was group treatments (72.92% of treatments) followed by treatment for respiratory disease (12.75% of treatments). Macrolides accounted for 76.37% of treatments. Nearly half of farms used routine prophylactic treatment for arriving animals (n = 7/18). The use of quarantine and ‘sick pens’ were seen as important by surveyed vets with antibiotic prophylaxis and in-feed antibiotics seen as contributors to antibiotic resistance. The focus group highlighted the influence of the economic and political landscape on husbandry practices and the responsibility the farming sector had towards antibiotic stewardship.DiscussionOverall, Argentine beef feedlots resemble North American beef feedlots in terms of antibiotic practices but with considerably lower usage, with in-feed monensin representing a large proportion of total ABU. The adaptation period presents a challenge to animal health; antibiotics are administered a prophylaxis, metaphylactic and individual treatments depending on farm management practices. Further research into internationally comparable measures of ABU and detailed cost-benefit analysis of practical, on-farm interventions are needed to aid improved antimicrobial stewardship in livestock systems globally.

Economic evaluation of the Liverpool heart failure virtual ward model.

A virtual ward (VW) supports patients who would otherwise need hospitalisation by providing acute care, remote monitoring, investigations, and treatment at home. By March 2024 the VW programme had treated 10 950 patients across six speciality VWs, including heart failure (HF). This evaluation presents the economic assessment of the Liverpool HF VW. A comprehensive economic cost comparison model was developed by York Health Economics Consortium (University of York) to compare the costs of the VW to standard hospital inpatient care (SC). The model included direct VW costs and additional costs across the care pathway. Costs and resource use for 648 patients admitted to the HF VW were calculated for 30 days post discharge and total cohort costs were extrapolated to a full year. Primary outcomes included costs related to length of stay, readmissions, and NHS 111 contact. The total cost for the HF VW pathway, including set-up costs, was £467 524. This results in an incremental net cost benefit of £735 512 compared to the total SC cost of £1 203 036, indicating a substantial net cost benefit of £1 135 per patient per episode (PPPE). This advantage remains despite initial setup expenses and ongoing costs such as home visits, virtual consultations, point-of-care (POC) testing and home monitoring equipment. Our HF VW model offers a substantial net cost benefit, driven by reduced hospital stays, fewer emergency department visits, and lower readmission rates. The study highlights the importance of considering system-wide impacts and continuous monitoring of VWs as they develop.

Green technology innovation or pollution substitution? an evolutionary game for high-Energy-consuming enterprises’ strategy from a consideration of energy-consuming trading rights

ABSTRACT The energy-consuming rights trading (ECRT) environmental regulatory policy starting from demand side reform has a significant influence on the enterprises’ production strategies. However, there is still a lack of research on dynamic mechanisms from a micro perspective. Referencing ECRT policy implementation, this paper incorporates government, the public, and high-energy-consuming enterprises into a unified framework, and constructs a tripartite evolutionary game model to explore the enterprises’ production strategy under the reward and punishment accountability mechanism. Then, a case study is addressed to examine the role of government. The results show that: (1) The steady-state conditions of the three parties depend on their own cost–benefit circumstances. Enterprises’ production strategy is driven by the coordination of the government and the public. (2) Achieving ideal equilibrium path evolution requires that the expected benefits of green technology innovation more strongly than the expected benefits of ‘pollution substitution’ practices. (3) A strict accountability system that includes penalties and rewards can enhance public supervision and accelerate the transformation of government active regulatory supervision strategies, stimulating the internal driving forces that motivate enterprises’ green technology innovation. The findings provide references for promoting the implementation of ECRT and helping to achieve the strategy of ecological civilisation construction.

Abstract 4143270: PREDICTIVE MODELS AID PHYSICIAN PROGNOSTICATION: A SECONDARY ANALYSIS EVALUATING INTEGRATED MODEL AND PHYSICIAN PROGNOSTIC ESTIMATES IN PATIENTS WITH HEART FAILURE WITH REDUCED EJECTION FRACTION

Background: In recent studies from a multicenter Canadian cohort of outpatients with heart failure (HF), we found that model predictions were significantly more accurate than HF cardiologists. In this study, trying to mimic practice, we evaluated the additional predictive value and clinical impact of model predictions to refine physician estimated risk of 1-year mortality by combining model and physician estimates. Methods: We included consented consecutive HF outpatients (LVEF &lt;40%) followed at 11 HF clinics in Canada. HF cardiologists estimated patient 1-year mortality using their clinical judgment. We calculated model predicted mortality using the Seattle HF Model (SHFM). We followed patients for at least a year to record mortality (or urgent heart transplant or ventricular assist device implant as mortality-equivalent events). Using random forest survival model and cross-validation, we compared the performance SHFM and the HF cardiologist alone, and the integrated HF cardiologist and the SHFM predictions by evaluating model discrimination (c-statistic), calibration (observed vs predicted event rate), risk reclassification and clinical net benefit analyses. Results: Among 1,643 HF patients, 1-year event rate was 9% (95%CI 8%-11%). The SHFM had the adequate discrimination (c-statistic 0.76) and excellent calibration while cardiologists showed adequate discrimination (c-statistic 0.75) and poor calibration with significant risk overestimation ( Figure 1 ). When the SHFM estimates were added physician predictions, discrimination significantly improved (0.82, 95%CI 0.78-0.86) with excellent calibration. By risk reclassification analysis, among patients with events, HF cardiologist better reclassified 44% than the SHFM or the integrated model. Among patients without event, however, HF cardiologists worse risk-classified 52% in comparison to SHFM and 71% to the integrated model. By net clinical benefit analysis ( Figure 2 ), when the decision to treat involves patients with 1-year mortality of &gt;5%, SHFM predictions would lead to higher benefit than guiding care by physician judgement. Integrating model and HF cardiologist predictions led to minimally increased benefit in comparison to SHFM alone. Conclusions: Integrating prediction from the SHFM to physician judgment or using the SHFM alone showed superior accuracy than HF cardiologist predictions, proving that model-informed care may provide more accurate prognostic information to tailor clinical decision making.

Enhancing Blackgram (Vigna mungo L.) Productivity through Good Agricultural Practices in Tamil Nadu, India

Large scale pulse seed production demonstrations on black gram under the TN IAMP scheme conducted by Agricultural College and Research Institute, Tamil Nadu Agricultural University, Vazhavachanur, Tiruvannamalai district, Tamil Nadu, India in 2 cluster villages at 50 farmer’s holdings during 2019-2020 and 2020-2021, respectively. The result and data analysis show an extension gap of 0.09 q/ha over farmers' traditional practices. The results revealed that TNIAMP intervention demonstrated registered higher growth and yield parameters viz., no. of clusters per plant, no. of pods per plant, grain yield and benefit-cost ratio compared to farmer’s practice grain yield and benefit cost ratio. TNIAMP pulse seed production intervention has had a good impact on pulse growing farmers of the Aliyar sub-basin, as they were motivated by good agricultural practices in the TNIAMP intervention plots and yielded an increase of 15.8 % higher than farmer’s practices.

Techno-Economic Analysis of BAU-STR Dryer for Rice Drying: An Approach to Accelerate Adoption

Postharvest food loss and waste offset worldwide agricultural productivity and food security. Insufficient drying and storage are the prominent drivers of food loss and waste in underdeveloped countries. Mechanical grain drying systems have distinct benefits over sun drying but are inaccessible to underserved communities due to high capital costs and energy demand. This study evaluated the techno-economic and financial performance of a half-ton-capacity BAU-STR dryer. The moisture extraction rate, drying rate, drying efficiency, and energy consumption were used as technical performance indicators. In contrast, the net present value (NPV), internal rate of return (IRR), benefit–cost ratio (BCR), and payback period were considered economic performance indicators. The technical performance analysis results revealed that the moisture content of rice was reduced from 19.5% to 13.5 ± 0.15% in 4.0 h with an average drying rate of 1.5%/h and a drying efficiency of 75.1%. The financial performance analysis resulted in a drying cost, NPV, IRR, BCR, and PBP of USD 0.96 per 100 kg of grain, USD 3018, 135%, 3.0, and 0.73 yr., respectively, when the annual use was 240 h. If the yearly use of the dryer increased from 240 to 720 h, a higher NPV, IRR, and BCR, as well as a lower payback period and drying cost, could be achieved. Adopting a BAU-STR dryer for drying grain (rice and corn) among underserved communities could play a key role in postharvest food loss and waste.

Inside the Mind of the Self-Deceiver: Foundational Issues in Relation to Human Defences and “the Unconscious”

AbstractThere are many foundational questions involved in understanding our defences. Are these manoeuvres unconscious processes to which we fall prey, as psychoanalytic metapsychology suggests? Or are they the product of a conscious and motivated strategy initiated by the individual? I argue for the latter. The concept of “unconscious defence” lacks explanatory power as it initiates an endless cycle of defence mechanisms. Alternatively, focus is directed towards consciousness and the pre-reflective moment when the ego evades addressing troubling content of consciousness. Existential philosophers such as Sartre (Being and nothingness, Methuen &amp; Co, 1943) and Fingarette (Self-deception, Routledge &amp; Kegan Paul, 1969) are used as stepping stones in making this “Copernican” shift in perspective, and core affective processes are introduced as the organismic centre of rotation behind our defences. Core affective processes play an important role in the toning of our emotions and moods, and I argue that they also play a leading role in the activation of our defences. Finally, ethical issues raised by self-deception in psychological practice are touched upon. Should the truth always be revealed, or should psychologists occasionally engage in cost-benefit analysis?

Feasibility of snakehead fish hatchery (Channa striata) using a round pond in Labuan Amas Selatan district, Hulu Sungai Tengah regency, Kalimantan Selatan province, Indonesia

&lt;p&gt;This study aims to determine the technicalities and analyze the feasibility of &lt;em&gt;snakehead fish&lt;/em&gt; (&lt;em&gt;Chana striata&lt;/em&gt;) hatchery using round ponds in Labuan Amas Selatan District. The data collection methods used are observation, interviews, and documentation. The data analysis used is a qualitative descriptive analysis to determine the technical aspects of the fish hatchery, financial analysis to determine the feasibility of the business with profit analysis, Payback Period (PP), Break Event Point (BEP), Net Present Value (NPV), Net Benefit Cost (Net B/C), and Internal Rate of Return (IRR). The study results show that &lt;em&gt;snakehead fish&lt;/em&gt; hatchery using round ponds produces &lt;em&gt;snakehead fish&lt;/em&gt; seed in 7 cycles in one year; in each cycle, 6–10 pairs of &lt;em&gt;snakehead fish&lt;/em&gt; are used, which can be spawned with an average nursery time of 1.5 months. &lt;em&gt;Snakehead fish&lt;/em&gt; cultivation techniques include broodstock maintenance, broodstock selection, spawning, larval transfer and maintenance, nursery, harvesting, and marketing. The results of the business feasibility analysis obtained a profit value of IDR 63,465,000/year with a speedy return on investment for 1.64 years, the BEP value of production = 20,742 seed &amp;lt; the production value = 56,000 seed, and the BEP price of IDR 667/seed &amp;lt; the current price = IDR 1,800/seed. The NPV value at the hatchery reached IDR 366,007,925, meaning NPV &amp;gt; 0, Net B/C &amp;gt; 1 value of 4.62, and IRR value of 62.81%, which means it is greater than the current interest rate of 6%. Based on various financial analyses, the &lt;em&gt;snakehead fish&lt;/em&gt; hatchery business using round ponds is profitable and feasible.&lt;strong&gt;&lt;/strong&gt;&lt;/p&gt;

Effect of Methods of Establishment and Zinc Management on Growth and Yield of Rice (Oryza sativa L.)

The field experiment was conducted at Shradhay Bhagwati Singh Agriculture Research Farm (Hajipur), Chandra Bhanu Gupta Krishi Snatkottar Mahavidyalaya, B.K.T., Lucknow (Uttar Pradesh) during Kharif (rainy) season in 2023-24. The treatment consisted of three methods of establishment (M1 – Direct seeding in lines after pre-irrigation, M2 -Broadcast of sprouted seed on puddled soil , M3 – System of Rice intensification (SRI) of (25 x 25cm) 12 days old seedling.) and five Zinc management practices (Zn0- Without zinc (control), Zn1- Zinc Sulphate ZnSo4@20kg ha-1 (Basal), Zn2- Foliar spray of Zn@0.5% at tillering and panicle initiation stage, Zn3- Seedling dipping in 2% ZnSO4+ 2 Foliar of Zn@0.5% at tillering and Panicle stage, Zn4- Seedling dipping in 2 % ZnSO4 solution+ Foliar spray of Zn@0.2% at tillering and panicle initiation stage) were tested in split-plot design with 3 replications. The Experimental site was silty loam having medium organic carbon (0.70%) and available nitrogen (270 kg ha-1), phosphorous (27 kg ha-1) and Potassium (262 kg ha1). All the growth parameters, yield attributes, yield, Zinc content and uptake of Zn into grains and straw, were increased significantly with SRI method (M3) followed by direct seeding in Lines after pre-irrigation (M2). Amongst zinc management, all the growth parameters and yield attributes of rice were maximum under Seedling dipping in 2% ZnSO4+ 2 Foliar of Zn@0.5% at tillering and panicle initiation stage, followed by Seedling dipping in 2 % ZnSO4 solution+ Foliar spray of Zn@0.2% at tillering and panicle initiation stage the maximum gross income of Rs 158938.18 ha-1 was accrued with (SRI method + T4) treatment combination. However, a combination of SRI method along with T3 treatment accrued the maximum net profit of Rs 107981.21 ha-1 and benefit: cost ratio of 2.08 which was followed by a combination of SRI method along with T4 with net income of Rs 107234.99 ha-1 and benefit cost ratio of 2.07.