Product Lifetime Research Articles

Dynamics of extreme climatic variables for viticulture in the main zones of ampelocenosis of the Krasnodar region

Modern climate changes affect all branches of agriculture. Everywhere there is an increase in air temperature, changes in precipitation, an increase in extreme weather events. Since the productive lifespan of a grape plant is 30-40 years, it is necessary to assess climatic changes in order to create a variety adapted to changes. The purpose of the research is to assess changes in extreme heat supply and relative humidity in the main viticultural areas of the Krasnodar region. The average values of extreme heat supply and relative humidity variables of two climatological periods of 1961–1990 and 1991–2020, their changes over time and the course of variable’s anomalies of 1991–2020 compared with the average values of 1961–1990 are calculated. An increase in the absolute maximum air temperature by 0.2–1.6 °C for the period 1991–2020 was noted compared to the previous period, with the exception of Novorossiysk (decrease by 1.4 °C); an increase in the average absolute maximum air temperature by 1.5–2.5 °C, an increase in the number of days with a maximum air temperature above +35 °C by 1.0–2.3 days; a decrease in the average relative humidity of April–October by 0.7–2.7 % and an increase in the number of days with a minimum relative humidity of less than 30 % over the summer by 0.8–5.4 days. The variability of these variables over time for the period 1991–2020 is consistent with the change in the average. An increase in the absolute maximum was established (by 0.65–0.9 °C/10 years), the number of days with a maximum air temperature above +35 °C (by 0.8–1.1 days/10 years), the number of days with a minimum relative humidity of less than 30% over the summer (by 1.2–7.2 days/10 years); decrease in the average relative humidity of April–October (by 0.5–6.5 %/10 years). These changes indicate an increase in climate extremes and the frequency of unfavorable conditions for grapes in the summer, which requires an adjustment of the assortment.

What is the impact of demand patterns on integrated online-offline and buy-online-pickup in-store (BOPS) retail in a smart supply chain management?

Retailers aim to provide in-person and remote interactions to accelerate purchases through hybrid methods, which introduce additional delivery and emissions loads but create a seamless shopping experience. The challenges of unified inventory, customer information, pricing, demand forecasting complications, and order fulfillment are met successfully in the hybrid methods. Here, a smart supply chain management that integrates traditional physical presence with cloud-based and hybrid buy-online-pickup in-store channels is optimized to meet customer demand in different demand patterns. The demand patterns considered are linear, cubic, and normalized functions of the selling price, the advertising cost, and the product lifetime. The article incorporates sustainable supply chain and omnichannel strategies to optimize supply chain performance and profitability. The paper compares the results of the proposed models with traditional supply chain models and provides some managerial insights and suggestions for online retailers. Numerical simulation reveals that nonlinear price dependence in demand provides an opportunity for higher promotional investment with a substantial rise in optimal selling price and overall profit. The shift-to-imperfect probability is seen to be the volatile component in the solution surface. The markup of the offline channel has a greater impact than buy-online-pickup in-store markup.

Investigation of Far Infrared Emission and UV Protection Properties of Polypropylene Composites Embedded with Candlenut-Derived Biochar for Health Textiles.

Far infrared radiation (FIR) within the wavelength range of 4-14 μm can offer human health benefits, such as improving blood flow. Therefore, additives that emit far infrared radiation have the potential to be incorporated into polymer/fabric matrices to develop textiles that could promote health. In this study, biochar derived from candlenuts and pyrolyzed with activated carbon (AC) was incorporated into polypropylene (PP) films and investigated for its potential as a health-promoting textile additive. The properties of biochar were compared with other far infrared (FIR) emitting additives such as hematite, Indian red ochre, and graphene. The addition of biochar increased FIR emissivity to 0.90, which is 9% higher than that of pristine PP. Additionally, biochar enhanced UV and near-infrared (NIR) blocking capabilities, achieving an ultra-protection factor (UPF) of 91.41 and NIR shielding of 95.85%. Incorporating 2 wt% biochar resulted in a 3.3-fold higher temperature increase compared to pristine PP after 30 s of exposure to an FIR source, demonstrating improved heat retention. Furthermore, the ability to achieve the lowest thermal effusivity among other additives supports the potential use of biochar-incorporated fabric as a warming material in cold climates. The tensile properties of PP films with biochar were superior to those with other additives, potentially contributing to a longer product lifespan. Additionally, samples with red ochre exhibited the highest FIR emissivity, while samples with hematite showed the highest capacity for UV shielding.

Genetic analysis for reproductive and longevity traits in Landlly sows

The rate of reproduction and lifetime productivity of the animals determine the success of a herd. As these features significantly impact sow productivity, welfare, and profitability, there is considerable interest in global swine breeding programmes to genetically select better sows for these attributes. In this scenario, reliable heritability estimates and genetic correlations between traits are essential for the success of genetic selection for such traits. The goals of the current study were to examine the reproductive and longevity traits and to estimate the genetic and phenotypic parameters for these traits in Landlly sows kept at a swine production farm, Izatnagar, Uttar Pradesh, India. The effect of non-genetic factors on different reproductive traits was estimated using SPSS version 16.0 and Bayesian approach which were utilized to estimate the genetic parameters for reproductive and longevity traits. The current study’s finding that the year and season of birth significantly affect reproductive traits generally suggests that there is potential for boosting productivity by optimising managemental practices. The heritability estimates were low for the reproductive and longevity traits, indicating a very little additive genetic variance in these traits, and individual selection will not be helpful for improving them. As some traits, such as LSB_FF & LSW_FF and LSB _SF & LSW_SF, have a moderate genetic correlation, indirect selection can be used to improve these two pairs of features.

Selecting the most successfull recycling strategy over daily consumption products: application of q-Rung Orthopair Fuzzy Topsis method

Recycling is the process of collecting and reusing that helps the countries to achieve their sustainable development goals. This study, for the first time in the literature, considers the recycling of many daily consumption products as a decision-making problem with the q-rung orthopair fuzzy (q-ROF) approach. In Turkey, recycling initiatives are primarily led by the government and municipalities, involving either reprocessing in public facilities or collaboration with private enterprises. The research evaluates the effectiveness of recycling strategies, considering paper, plastic, textiles, batteries, frying oils, electronics, glass, and wood as alternative products. Criteria such as convertibility rate, resource usage for recycling, converted product lifespan, recycling process complexity, economic gain, product consumption rate, and trading opportunities are employed in the decision-making process. The q-rung orthopair fuzzy Technique for Order Preference by Similarity to Ideal Solution (q-ROFTOPSIS) method is applied to assess these criteria. Decision makers, comprising a recycling expert, a recycling business engineer, and an academician specializing in recycling studies, contribute to the evaluation. The study reveals electronic products as the most successful in recycling, while frying oils exhibit the least success.

The effect of repair and lifetime extension on the environmental performance of energy-using products. Application to electric water kettles

This study evaluates the environmental impacts of extending the lifetime of electric kettles through repair strategies by means of the Life Cycle Assessment (LCA) methodology. A total of 2640 scenarios were analysed, each considering six variables: material composition, usage intensity, year of failure, failure management, lifetime extension, and end-of-life (EoL) management. The results demonstrate that extending kettle lifetimes through repair can reduce the total environmental impact by up to 35 %, particularly in scenarios where low-energy use is combined with maximum lifetime extension. The use phase contributed the most to the environmental impact, accounting for 48–64 % of the total in most scenarios, driven primarily by energy consumption during kettle operation. In contrast, material composition and EoL management had a smaller effect, representing only 5–10 % of the impact. Repairs focused on lime descaling were the most effective, reducing the environmental burden by up to 20 %, while repairs involving component replacement were less impactful in this regard. These findings underscore the potential of repair strategies to significantly reduce the environmental footprint of household appliances. Policymakers should prioritise repairability in product design and promote consumer awareness to extend product lifetimes and achieve lower environmental impacts.

Assessing computational reproducibility in Behavior Research Methods

Psychological science has thrived thanks to new methods and innovative practices. Journals, including Behavior Research Methods (BRM), continue to support the dissemination and evaluation of research assets including data, software/hardware, statistical code, and databases of stimuli. However, such research assets rarely allow for computational reproducibility, meaning they are difficult to reuse. Therefore, in this preregistered report, we explore how BRM’s authors and BRM structures shape the landscape of functional research assets. Our broad research questions concern: (1) How quickly methods and analytical techniques reported in BRM can be used and developed further by other scientists; (2) Whether functionality has improved following changes to BRM journal policy in support of computational reproducibility; (3) Whether we can disentangle such policy changes from changes in reproducibility over time. We randomly sampled equal numbers of papers (N = 204) published in BRM before and after the implementation of policy changes. Pairs of researchers recorded how long it took to ensure assets (data, software/hardware, statistical code, and materials) were fully operational. They also coded the completeness and reusability of the assets. While improvements were observed in all measures, only changes to completeness were altered significantly following the policy changes (d = .37). The effects varied between different types of research assets, with data sets from surveys/experiments showing the largest improvements in completeness and reusability. Perhaps more importantly, changes to policy do appear to have improved the life span of research products by reducing natural decline. We conclude with a discussion of how, in the future, research and policy might better support computational reproducibility within and beyond psychological science.

Constant Stress-Partially Accelerated Life Tests of Vtub-Shaped Lifetime Distribution under Progressive Type II Censoring

In lifetime tests, the waiting time for items to fail may be long under usual use conditions, particularly when the products have high reliability. To reduce the cost of testing without sacrificing the quality of the data obtained, the products are exposed to higher stress levels than normal, which quickly causes early failures. Therefore, accelerated life testing is essential since it saves costs and time. This paper considers constant stress-partially accelerated life tests under progressive Type II censored samples. This is realized under the claim that the lifetime of products under usual use conditions follows Vtub-shaped lifetime distribution, which is also known as log-log distribution. The log–log distribution is highly significant and has several real-world applications since it has distinct shapes of its probability density function and hazard rate function. A graphical description of the log–log distribution is exhibited, including plots of the probability density function and hazard rate. The log–log density has different shapes, such as decreasing, unimodal, and approximately symmetric. Several mathematical properties, such as quantiles, probability weighted moments, incomplete moments, moments of residual life, and reversed residual life functions, and entropy of the log–log distribution, are discussed. In addition, the maximum likelihood and maximum product spacing methods are used to obtain the interval and point estimators of the acceleration factor, as well as the model parameters. A simulation study is employed to assess the implementation of the estimation approaches under censoring schemes and different sample sizes. Finally, to demonstrate the viability of the various approaches, two real data sets are investigated.

Method for assessing the durability of structures under stationary and non-stationary random loading using variational mode decomposition (VMD)

In the era of digital transformation, most devices are equipped with a variety of sensors, which provide information to be used in developing intelligent models for predicting the fatigue life. The development of digital models of real objects for fatigue life estimation faces the lack of algorithms for performing such an estimation. The problem arises in the adaptive and automatic analysis of signals from real sensors installed on the object and their subsequent processing to estimate the fatigue life of the object. We propose a new method for assessing the fatigue life of structures based on application of the adaptive method of variational mode decomposition to signals gained from sensors, including non-stationary ones. Variational mode decomposition involves decomposition of an initial complex random process into simpler random processes (modes) that are stationary and narrowband. An original method of summarizing damage resulted from the action of the modes obtained as a result of the decomposition is used. The developed method can be used as an algorithmic support for the generation of digital doubles of the residual lifetimes of natural products. The proposed method is compared with the «rainflow» method in the time domain. Different realizations of random stationary and non-stationary signals with different bandwidths are compared numerically. In addition, the traditional frequency methods of Dirlik and Benasciutti have been compared with the «rainflow» method. The analysis showed good results for the proposed method, i.e., the error was smaller compared to traditional frequency methods, especially for non-stationary processes.

Exploring Product Design Innovation through Repair Techniques: Insights from Knowledge and Experience

Repair has been a longstanding activity in human society. However, in modern times, the production strategy of “planned obsolescence” has led to a decline in product quality and lifespan, resulting in closed and non-repairable products. Additionally, advertising manipulates consumers' desires, leading them to prefer replacing old items with new ones rather than repairing them. This has resulted in issues such as overconsumption, massive waste, and recycling challenges. Nevertheless, many DIY repair enthusiasts promote repair activities through communities and online media, highlighting the joy and creativity of repair. This unique relationship of care between people and objects extends the life of products and alters their original appearance and function, creating new possibilities to meet consumers’ needs. This study analyzes actual cases to explore how DIY repairers innovate during the repair process, reinterpret old items, and elucidate the interaction between people and objects. Furthermore, it argues that repair activities represent a radical approach to mitigating waste and are crucial for advancing sustainable development.

Effects of cow feed efficiency, longevity, heterosis, and lifetime productivity on profitability of heifer selection and cow-calf operations

This study investigated factors influencing heifer replacement and cow-calf profitability using 361 cows (born 2011-2018) at the Lacombe Research and Development Centre, Alberta, Canada. Profitability was measured by marginal returns (MR) incorporating feed costs, heifer opportunity cost, calf and cull revenues, and a premium for cows retained in the herd. The study evaluated the linear effects of lifetime productivity, feed efficiency (residual feed intake adjusted for off-test backfat thickness; RFIfat), and genomic retained heterozygosity, an indicator of heterosis, on MR, feed costs, total costs, and net revenue (NR). Lifetime productivity, defined by the cumulative weight of calves weaned, was positively associated with MR and NR (P < 0.01). RFIfat influenced total cost, MR, and NR (P < 0.05), with MR improved by $168.50 cow-1 yr-1 for each unit decrease in RFIfat, although regression and group mean comparisons were not fully consistent. Genomic retained heterozygosity positively impacted MR and NR, with a 10% increase enhanced MR and NR by $21.80 and $20.50 cow-1 yr-1, respectively. Cow breed type did not affect longevity, MR, or NR. In conclusion, RFIfat and genomic diversity were important factors to consider in heifer replacement decisions when lifetime DMI was estimated as described in the present study.

Impact of the circular economy on ecological footprint: evidence from Germany.

The circular economy practices contribute to sustainable development by maximising efficiency, utilising renewable resources, extending product lifespans, and implementing waste reduction strategies. This study investigates the individual impacts of four sources of the circular economy on the ecological footprint in Germany, a country that is among the pioneers in establishing a comprehensive roadmap for the circular economy. The four sources examined are renewable energy consumption (REC), recycling, reuse, and repair of materials. Using time series data from 1990 to 2021, the study employed the dynamic autoregressive distributed lag (ARDL) simulation technique and also applied kernel-based linear regression (KRLS) to test the robustness of the results. The findings revealed that reuse practices significantly reduce the ecological footprint in both the short and long run. REC and repair also substantially decrease the ecological footprint, as shown by the simulation analysis. Conversely, while recycling is generally considered crucial for minimising environmental impact, in this study, it was found to contribute to environmental degradation. This paradox may be attributed to the nascent state of the recycling industry and data limitations. The results from KRLS confirm the findings of the dynamic ARDL. It is recommended that policymakers develop measures that are appropriate, efficient, and targeted to enhance the role of each source of the circular economy in reducing the ecological footprint in Germany. The major limitation of the study is its reliance on the indirect measures of circular economy attributed to the non-availability of data on direct measures.

Tropical peat soil changes across successive oil palm generations in Sarawak, Malaysia

Oil palm is commonly replanted once reaching the end of its productive lifespan. This cyclical planting practice in oil palm plantations could have long-term implications for the humification and properties of tropical peat soil. This study aimed to investigate the changes observed across successive generations of oil palm plantations in Sarawak, Malaysia. Fourier Transform Infrared Spectroscopy (FTIR) was applied to examine the quality of the Soil Organic Matter (SOM), specifically the functional groups, humification index, Hydrophobicity Index (HI), and Degree of Degradation (DDI). Overall, the peat humification trend was in the order of 2nd Gen > Forest >1st Gen. The higher presence of recalcitrant compounds of lignin in the soil was attributed to the higher HI and lower DDI in the 2nd Gen. The relationship between the Pyrophosphate Solubility Index (PSI) and the humification index further revealed a significant increase in the relative abundance of humic substances with the maturity of degraded organic matter. These findings suggest a notable transition, implicating a shift towards a more stable form of SOM over the long-term utilization of tropical peatland for oil palm plantations. This is characterised by a significant increase in the relative abundance of aromatic, phenolic, and carboxylic functional groups. The study also highlights the need for further research on the linkage between these changes and greenhouse gas emissions to enhance our understanding of the long-term biogeochemical cycle of oil palm on tropical peatlands.

Sustainability and South Africa’s mature mines: The innovation imperative

Given the current reserves, numerous South African Witwatersrand gold and Bushveld platinum mines have a shorter remaining lifespan than the period they have been in full production. This situation presents a paradox: while mines aim for sustainable development, the inherently unsustainable nature of mining poses challenges. A fundamental question emerges: how can mines approaching the end of their economic lives enhance sustainability? One approach is to extend their production lifespan. This approach is especially important in the context of South Africa with its already unacceptably high unemployment rate. Mature mines in established mining jurisdictions face sustainability issues. Thus, this study argues that innovative skills development, research, and partnerships can help sustain mining operations, although commodity prices fluctuate and mines near the end of their economic viability. The study presents novel ideas to assist mature mines in extending their life and reducing the vulnerability of affected mine workers.

A distribution-free method for reliability improvement based on design of experiments

Given growing consumer expectations for enhanced product lifespans, there is a particular focus on improving product reliability. Design of Experiments (DOE) is a useful tool for identifying significant factors and determining factor levels to enhance product reliability. Current research commonly assumes that the lifetime data follows a specific distribution. This overlooks the possibility that erroneous assumptions about the data distribution may lead to imprecise factors identification. Additionally, factorial effect principles are often disregarded in factors effects identification. In this paper, a distribution-free method named Factor-Effect Bayesian Quantile Regression (FEBQR) is proposed to address the aforementioned issues. We first construct a new set of factor indicator variables, considering the principles of effect sparsity, weak effect hierarchy, and effect heredity. Then we develop a novel model that extends the Bayesian quantile regression framework by incorporating the principle of factor effects to describe the relationship between percentile lifetimes and factor effects. Unknown parameter estimates are obtained through the Gibbs sampling algorithm, and significant factors are identified based on the posterior mean of the proposed factor indicator variables. Two practical examples are illustrated using the proposed method. Compared with traditional methods, the proposed method provides more accurate factor identification results.

Fostering sustainable consumer behaviour: Unravelling the determinants of repair intentions for smart appliances

Consumer demand for repair services is vital for prolonging product lifespan, yet factors influencing the repair intention for smart appliances remain unclear. Addressing this gap, we propose an extended theory of planned behaviour, incorporating four additional constructs: environmental knowledge, cost of repair, financial benefit, and data security. We collected data from 383 participants in the United Kingdom, which we analysed using a partial least squares approach. Results reveal that the cost of repair, perceived behavioural control, attitude, and financial benefit directly impact repair intention, while subjective norms do not. Environmental knowledge indirectly influences repair intention through attitude mediation, and data security's impact is not moderated by attitude. This extended theory offers a theoretical foundation for future related studies, providing insights for repair providers, environmental NGOs, and policymakers. Our findings can inform interventions promoting repair behaviour and guide policies incentivising consumers, thus increasing the demand for repair services.

Estimation of the Reliability Function of the Generalized Rayleigh Distribution under Progressive First-Failure Censoring Model

This study investigates the statistical inference of the parameters, reliability function, and hazard function of the generalized Rayleigh distribution under progressive first-failure censoring samples, considering factors such as long product lifetime and challenging experimental conditions. Firstly, the progressive first-failure model is introduced, and the maximum likelihood estimation for the parameters, reliability function, and hazard function under this model are discussed. For interval estimation, confidence intervals have been constructed for the parameters, reliability function, and hazard function using the bootstrap method. Next, in Bayesian estimation, considering informative priors and non-information priors, the Bayesian estimation of the parameters, reliability function, and hazard function under symmetric and asymmetric loss functions is obtained using the MCMC method. Finally, Monte Carlo simulation is conducted to compare mean square errors, evaluating the superiority of the maximum likelihood estimation and Bayesian estimation under different loss functions. The performance of the estimation methods used in the study is illustrated through illustrative examples. The results indicate that Bayesian estimation outperforms maximum likelihood estimation.

FOXO-regulated OSER1 reduces oxidative stress and extends lifespan in multiple species

FOXO transcription factors modulate aging-related pathways and influence longevity in multiple species, but the transcriptional targets that mediate these effects remain largely unknown. Here, we identify an evolutionarily conserved FOXO target gene, Oxidative stress-responsive serine-rich protein 1 (OSER1), whose overexpression extends lifespan in silkworms, nematodes, and flies, while its depletion correspondingly shortens lifespan. In flies, overexpression of OSER1 increases resistance to oxidative stress, starvation, and heat shock, while OSER1-depleted flies are more vulnerable to these stressors. In silkworms, hydrogen peroxide both induces and is scavenged by OSER1 in vitro and in vivo. Knockdown of OSER1 in Caenorhabditis elegans leads to increased ROS production and shorter lifespan, mitochondrial fragmentation, decreased ATP production, and altered transcription of mitochondrial genes. Human proteomic analysis suggests that OSER1 plays roles in oxidative stress response, cellular senescence, and reproduction, which is consistent with the data and suggests that OSER1 could play a role in fertility in silkworms and nematodes. Human studies demonstrate that polymorphic variants in OSER1 are associated with human longevity. In summary, OSER1 is an evolutionarily conserved FOXO-regulated protein that improves resistance to oxidative stress, maintains mitochondrial functional integrity, and increases lifespan in multiple species. Additional studies will clarify the role of OSER1 as a critical effector of healthy aging.

Revolutionizing Grain and Particle Size Measurement in Metals: The Role of Sensor-Assisted Metallographic Image Analysis.

Metallographic image analysis is vital in the field of metal science due to its potential to automate the sensing process for grain and particle size estimation. To ensure the good quality and reliability of metal products, analysis of the integrity of metallic components is required. In contemporary manufacturing processes, microscopic analysis is a crucial step, mainly when complex systems like gearboxes, turbines, or engines are assembled using various components from multiple suppliers. A final product's quality, durability, and lifespan are determined via the quality analysis of properties of a material with proper tolerances. A flaw in a single component can cause the breakdown of the entire finished product. To ensure the good quality of a material, micro-structural analysis is necessary, which includes the routine measurement of inclusions. The particle and grain sizes of particulate samples are the most crucial physical characteristics of metals. Their measurement is routinely conducted across various industries, and they are frequently considered essential parameters in the creation of many products. This paper discusses the role of sensors in enhancing the accuracy and efficiency of metallographic image analysis, as well as the challenges and limitations associated with this technology. The paper also highlights the potential applications of sensor-assisted metallographic image analysis in various industries, such as aerospace, automotive, and construction. The paper concludes by identifying future research directions for this emerging field, including the development of more sophisticated algorithms for grain and particle size estimation, the integration of multiple sensors for more accurate measurements, and the exploration of new sensing modalities for metallographic image analysis.

The role of melatonin in delaying senescence and maintaining quality in postharvest horticultural products.

The postharvest lifespan of horticultural products is closely related to loss of nutritional quality, accompanied by a rapid decline in shelf life, commercial value, and marketability. Melatonin (MT) application not only maintains quality but also delays senescence in horticultural products. This paper reviews biosynthesis and metabolism of endogenous MT, summarizes significant effects of exogenous MT application on postharvest horticultural products, examines regulatory mechanisms of MT-mediated effects, and provides an integrated review for understanding the positive role of MT in senescence delay and quality maintenance. As a multifunctional molecule, MT coordinates other signal molecules, such as ABA, ETH, JA, SA, NO, and Ca2+, to regulate postharvest ripening and senescence. Several metabolic pathways are involved in regulation of MT during postharvest senescence, including synthesis and signal transduction of plant hormones, redox homeostasis, energy metabolism, carbohydrate metabolism, and degradation of pigment and cell wall components. Moreover, MT regulates expression of genes related to plant hormones, antioxidant systems, energy generation, fruit firmness and colour, membrane integrity, and carbohydrate storage. Consequently, MT could become an emerging and eco-friendly preservative to extend shelf life and maintain postharvest quality of horticultural products.