Asian Journal of Current Research

Marketing Analytics for Gastrointestinal Cancer Prevention and Early Detection: Emerging Trends, Analytical Frameworks and Research Directions

2026-09-18T11:50:20+00:00

Gastrointestinal (GI) cancers, such as colorectal, gastric, liver, pancreatic, and oesophageal cancers, continue to represent a serious public health concern because of their high prevalence and mortality and frequent delayed diagnosis. The evolution of marketing analytics offers new opportunities to address existing barriers to prevention and early diagnosis through evidence-based decision-making, tailored communication, and screening interventions. This narrative review analyses the current state of marketing analytics applications in GI cancer prevention and early detection, with a focus on social marketing, behavioural models, artificial intelligence (AI), digital health, and emerging marketing analytics approaches. The epidemiological landscape of GI cancers, prevention and screening methods, marketing analytics tools and analytical frameworks supporting patient engagement and screening uptake, and recent developments, including AI, big data, precision marketing, explainable AI, social media analytics, and real-time analytics, are reviewed in the context of current research challenges and gaps. The review indicates that integrating marketing analytics with behavioural science and AI technologies can support risk identification, more efficient resource allocation, improved screening uptake, and greater health equity.

Genotype by Trait (GT) Biplot Analysis for Multi-trait Evaluation and Selection in Sesame (Sesamum indicum) Genotypes

2026-09-07T11:39:27+00:00

Multi-trait evaluation of genotypes is a cornerstone of modern plant breeding, and graphical analytical tools such as the Genotype by Trait (GT) biplot have become indispensable for simultaneously interpreting complex genotype–trait relationships. In the present investigation, GT biplot analysis was employed to evaluate 45 sesame genotypes during Rabi 2025–26 across 14 yield and yield-attributing traits. The two principal components, PC1 (24.52%) and PC2 (18.45%), collectively accounted for 42.97% of the total variation. The which-won-where polygon view of the GT biplot delineated nine sectors with vertex genotypes TPTS-83, TPTS-94, TPTS-152, TPTS-66, TPTS-144, TPTS-45, TPTS-69, RMT-586 and RMT-631 exhibiting superior performance for their respective trait clusters. TPTS-66 was associated with days to 50 per cent flowering, days to maturity, plant height, first capsule height, specific leaf area and oil content, whereas TPTS-69 and RMT-586 were associated with branching traits, number of capsules per plant, capsule length, thousand-seed weight, harvest index and seed yield per plant. The vector view of the GT biplot revealed significant positive associations of seed yield per plant with harvest index, 1000-seed weight, number of primary and secondary branches, number of capsules per plant, SPAD chlorophyll meter reading (SCMR) and capsule length. The genotype TPTS-45 was identified as the ideal genotype, with JCS-3993, TPTS-144, VS-21-008, TPTS-244, TPTS-69 and VS-20-001 ranking as the most desirable. The discriminativeness versus representativeness analysis highlighted seed yield per plant, number of capsules per plant, number of primary and secondary branches, plant height and first capsule axis height as the most informative and reliable traits for genotype selection. These findings provide a robust framework for multi-trait-based selection and hybridisation in sesame breeding programmes aimed at developing high-yielding, early-maturing cultivars with improved oil content.

Assessment of Heavy Metal Levels in Surface Water and Sediment from Mini-Welele River in Mgbuosimini Community, Rivers State, Nigeria

2026-09-10T11:59:16+00:00

This study assessed the concentrations, spatial distribution and pollution status of selected heavy metals in surface water and sediment from the Mini-Welele River in Mgbuosimini Community, Obio/Akpor Local Government Area, Rivers State, Nigeria. Five sampling stations were established along the river to represent sections influenced by different levels of settlement, drainage and other human activities. Surface water samples were collected in clean acid-washed polyethylene bottles, preserved with nitric acid, digested and analysed by flame atomic absorption spectrophotometry. Surficial sediment samples were collected from the same stations, air-dried, homogenised, sieved, acid-digested and analysed for metals using the same instrumental technique. Surface water was analysed for Cd, Cr, Cu, Fe, Pb, Mn and Ni, while sediment was analysed for Cr, Pb and Ni. Because only station-level mean concentrations were available, the data were treated descriptively using ranges, means, standard deviations, total metal burden, comparison with guideline values and sediment pollution indices. Surface water mean concentrations followed the order Fe (1.480 mg/L) > Pb (0.658 mg/L) > Ni (0.514 mg/L) > Cr (0.353 mg/L) > Cd (0.141 mg/L) > Mn (0.119 mg/L) > Cu (0.070 mg/L). Cr, Fe, Pb, Ni and Cd exceeded the guideline values used for screening comparison, while Cu and Mn were below the respective comparison limits. Sediment mean concentrations followed the order Pb (49.18 mg/kg) > Cr (35.26 mg/kg) > Ni (19.56 mg/kg). Contamination factor values indicated low to moderate Cr contamination, moderate to considerable Pb contamination and low Ni contamination. Geoaccumulation index values generally indicated unpolluted to moderately polluted sediment conditions, while pollution load index values below 1 suggested no overall combined pollution load for the sediment metals assessed. The findings show measurable heavy metal inputs into the Mini-Welele River, particularly in surface water and Pb-enriched sediment zones. Routine monitoring, waste-control enforcement, community awareness and more detailed seasonal studies are recommended.

Techno Economic Evaluation of a Hand Operated Draper Separator for Decorticated Groundnut

2026-09-12T11:12:36+00:00

Performance studies of small cleaning machines almost always report cleaning efficiency and impurity as percentages and stop there. For the farmer who has to pay for the machine, however, the quantity that matters is the cost of producing a quintal of clean kernel, and that cost is governed as much by the kernel thrown away with the shell as by the cost of running the machine. A hand operated inclined draper separator for decorticated groundnut, fabricated for Rs. 9085, was therefore evaluated techno economically using the 54 cleaning trials of a 3 x 3 x 2 factorial experiment (deck angle 17, 22 and 27 degrees; conveyor speed 0.19, 0.34 and 0.55 m/s; feed rate 45 and 85 kg/h), in which every gram fed was accounted for by a closed mass balance. The hourly operating cost was Rs. 72.03, of which only Rs. 7.26 (10.1 %) was fixed, so the economics of the machine are almost entirely governed by how it is operated rather than by what it cost to build. Converting each treatment mean into a cost per quintal of clean kernel, using an assumed kernel value of Rs. 100/kg derived from the minimum support price, gave a range of Rs. 391 to Rs. 10,279 per quintal, a 26-fold spread produced by settings of the same machine. Kernel lost to the shell outlet accounted for 67 % of the cost even at the cheapest setting and for more than 90 % at poor settings, so loss, rather than machine cost, is the dominant economic term. The cheapest setting was 27 degrees at 0.55 m/s and 85 kg/h (Rs. 391 per quintal), which is neither the treatment that maximised cleaning efficiency nor the one selected by a desirability analysis of efficiency and shell loss; it wins because it delivers 55.4 kg/h of clean kernel against 21 to 23 kg/h for the alternatives at almost the same efficiency. The ranking was unchanged for kernel values from Rs. 70 to Rs. 130/kg. Operating at this setting shortens the payback period from 1.12 to 0.34 years and lowers the break-even use from 30.4 to 10.2 h/year.

Starch Based Edible Film Development and Enriched with Mulberry (Morus alba) Bioactive Compound: An Experimental Study

2026-09-16T12:49:42+00:00

This study focuses on the development of starch-based edible films enriched with mulberry (Morus alba) bioactive compounds and their evaluation in terms of physicochemical, antioxidant, and antimicrobial properties. Potato starch was selected as the primary film-forming polymer because of its biodegradability and strong oxygen-barrier ability, while mulberry leaf extract was incorporated to enhance functional activity owing to its rich content of polyphenols and flavonoids. The films were characterised for thickness, solubility, folding endurance, antioxidant activity (DPPH assay), and antimicrobial activity using agar diffusion methods. The results indicated that the addition of mulberry extract significantly improved antioxidant capacity, provided moderate antimicrobial effects against foodborne pathogens, and enhanced barrier and mechanical properties compared with control starch films. Despite the inherent limitations of starch-based films, such as sensitivity to water and reduced mechanical strength, the incorporation of mulberry bioactives effectively addressed some of these challenges. Overall, the findings indicate that mulberry-enriched starch-based edible films can serve as an eco-friendly and functional alternative to petroleum-based plastics, offering both food-preservation benefits and environmental sustainability. This innovation has potential applications in extending the shelf life of perishable foods while responding to consumer demand for safe, biodegradable, and health-promoting packaging materials.

Incident Response in Cybersecurity: A Systematic Review

2026-09-04T12:18:59+00:00

Background: Cybersecurity incident response is commonly described as a sequence of technical activities, yet major incidents are managed by people working across organisational boundaries, under uncertainty and time pressure. Evidence about the human, organisational, procedural and technological conditions that shape response performance has not been consolidated across sectors.

Objective: To determine which factors shape organisational cybersecurity incident-response performance and what evidence exists that training, structured processes, collaboration or decision support improve operational outcomes.

Methods: An openly accessible evidence search was completed on 6 July 2026 for English-language primary empirical reports published from 1 January 2000 to 30 June 2026. Six reproducible web searches were supplemented by backward citation checking. One reviewer screened records, assessed full texts, extracted data and applied the Mixed Methods Appraisal Tool 2018. Because designs, settings, outcomes and estimands were incompatible, findings were synthesised thematically without statistical pooling.

Results: Eighty-five records were identified, 11 duplicates were removed, 74 records were screened, 30 full-text reports were assessed and 26 reports representing 25 unique studies were included. Evidence was predominantly qualitative and spanned security operations centres, computer security incident response teams, critical infrastructure, finance, public administration and healthcare. Recurrent determinants were shared situation awareness, communication across tiers and shifts, role clarity, trusted informal networks, workload and staffing, realistic cross-functional training, usable tools and data, and learning that extends beyond immediate technical restoration. Healthcare studies showed that manual alternatives and local adaptation can preserve care, but may transfer substantial safety and wellbeing burdens to staff. Automation was perceived as useful, but respondents expressed limited willingness to delegate decisions without human oversight.

Conclusions: Cybersecurity incident response is a socio-technical capability rather than a discrete technical procedure. Moderate-confidence evidence supports investment in shared situation awareness, explicit coordination, sustainable staffing and deliberate learning. Evidence for particular training formats, automation strategies and objective improvements in detection, containment or recovery time remains limited. Prospective multi-site evaluations using common operational and human-factors outcomes are needed.