Exploring the spatial distribution of tourist attractions and comprehending the spatio-temporal behaviors of tourists within tourist attractions can provide local planning agencies, destination marketing organizations, and government departments with essential evidence for decision-making processes. This study examines the spatio-temporal behavior patterns of tourists in the Kushan Scenic Area by analyzing GPS trajectory data acquired from social media platforms. The investigation primarily utilizes three research methodologies: grid analysis, Markov chain, and K-means clustering. The grid analysis results reveal three spatial distribution patterns within the scenic area, while the outcomes from the Markov chain and K-means clustering delineate six tourist movement patterns, along with three choices regarding travel time. This finding holds significant practical implications for enhancing the attractiveness of scenic areas, optimizing spatial layout, and improving tourists’ experiences. Full article

Liver diseases, including non-alcoholic fatty liver disease (NAFLD), are a growing global health issue. Environmental exposure to toxic metals can harm the liver, increasing the risk of NAFLD. Essential elements are vital for liver health, but imbalances or deficiencies can contribute to the development of NAFLD. Therefore, understanding the interplay between toxic metals and essential elements in liver disease is important. This study aims to assess the individual and combined effects of toxic metals (lead(Pb), cadmium (Cd), mercury (Hg)), and essential elements (manganese and selenium) on the risk of liver disease. Methods: We assessed the individual and combined effects of Pb, Cd, Hg, manganese (Mn), and selenium (Se) on liver disease risk using data from the National Health and Nutrition Examination Survey between 2017 and 2018. We performed descriptive statistics and linear regression analysis and then utilized Bayesian Kernel Machine Regression (BKMR) techniques such as univariate, bivariate, and overall effect analysis. BKMR enabled the assessment of non-linear exposure–response functions and interactions between metals and essential elements. Posterior Inclusion Probabilities (PIPs) were calculated to determine the importance of each metal and essential element in contributing to liver disease. Regarding our study results, the regression analysis of liver injury biomarkers ALT, AST, ALP, GGT, total bilirubin, and the FLI—an indicator of NAFLD—with toxic metals and essential elements, adjusting for covariates such as age, sex, BMI, alcohol consumption, ethnicity, income, and smoking status, demonstrated the differential effects of these contaminants on the markers of interest. Our BKMR analysis provided further insights. For instance, the PIP results underscored Pb’s consistent importance in contributing to liver disease (PIP = 1.000), followed by Hg (PIP = 0.9512), Cd (PIP = 0.5796), Se (PIP = 0.5572), and Mn (PIP = 0.4248). Our univariate analysis showed a positive trend with Pb, while other exposures were relatively flat. Our analysis of the single-variable effects of toxic metals and essential elements on NAFLD also revealed that Pb significantly affected the risk of NAFLD. Our bivariate analysis found a positive (toxic) trend when Pb was combined with other metals and essential elements. For the overall exposure effect of exposure to all the contaminants together, the estimated risk of NAFLD showed a steady increase from the 60th to the 75th percentile. In conclusion, our study indicates that Pb exposure, when combined with other toxic metals and essential elements, plays a significant role in bringing about adverse liver disease outcomes. Full article

Enantioseparation of nineteen liquid crystalline racemic mixtures obtained based on (R,S)-2-octanol was studied in reversed-phase mode on an amylose tris(3-chloro-5-methylphenylcarbamate) (ReproSil Chiral-MIG) and a cellulose tris(3,5-dichlorophenylcarbamate) (ReproSil Chiral-MIC). These polysaccharide-based chiral stationary phase (CSP) columns for High-Performance Liquid Chromatography (HPLC) were highly effective in recognizing isomers of minor structural differences. The mobile phase (MP), which consists of acetonitrile (ACN)/water (H₂O) at different volume ratios, was used. The mobile phases were pumped at a flow rate of 0.3, 0.5, or 1 mL·min⁻¹ with a column temperature of 25 °C, using a UV detector at 254 nm. The order of the elution was also determined. The chromatographic parameters, such as resolution (R_s), selectivity (α), and the number of theoretical plates, i.e., column efficiency (N), were determined. The polysaccharide-based CSP columns have unique advantages in separation technology, and this study has shown the potential usefulness of the CSP columns in separating liquid crystalline racemic mixtures belonging to the same homologous series. Full article

This study highlights the intricate relationship between Gray-Level Co-occurrence Matrix (GLCM) metrics and machine learning model performance in the context of plant disease identification. It emphasizes the importance of rigorous dataset evaluation and selection protocols to ensure reliable and generalizable classification outcomes. Through a comprehensive examination of publicly available plant disease datasets, focusing on their performance as measured by GLCM metrics, this research identified dataset_2 (D2), a database of leaf images, as the top performer across all GLCM analyses. These datasets were then utilized to train the DarkNet19 deep learning model, with D2 exhibiting superior performance in both GLCM analysis and DarkNet19 training (achieving about 91% testing accuracy) according to performance metrics such as accuracy, precision, recall, and F1-score. The datasets other than dataset_1 and 2 exhibited significantly low classification performance, particularly in supporting GLCM analysis. The findings underscore the need for transparency and rigor in dataset selection, particularly given the abundance of similar datasets in the literature and the growing trend of utilizing deep learning methods in future scientific research. Full article

The mapping of thermokarst landscapes and the assessment of their conditions are becoming increasingly important in light of a rising global temperature. Land cover maps provide a basis for quantifying changes in landscapes and identifying areas that are vulnerable to permafrost degradation. The study is devoted to assessing the current state of thermokarst terrain on Arga Island. We applied a random forests algorithm using the capabilities of the Google Earth Engine cloud platform for the supervised classification of the composite image. The analyzed composite consists of a Sentinel-2 image and a set of calculated indices. The study found that thermokarst-affected terrains occupy 35% of the total area, and stable terrains cover 29% at the time of image acquisition. The classifier has also mapped water bodies, slopes, and blowouts. The accuracy assessment revealed that the overall accuracy for all the different land cover classes was 98.34%. A set of other accuracy metrics also demonstrated a high level of performance. This study presents significant findings for assessing landscape changes in a region with unique environmental features. It also provides a potential basis for future interdisciplinary research and for predicting future thermokarst landscape changes in the Lena Delta area. Full article

Short carbon fiber (sCF)-based polymer composite parts enable one to increase in the material property range for additive manufacturing (AM) applications. However, room for technical and material improvement is still possible, bearing in mind that the commonly used fused filament fabrication (FFF) technique is prone to an extra filament-making step. Here, we compare FFF with direct pellet additive manufacturing (DPAM) for sCF-based composites, taking into account degradation reactions, print quality, and energy usage. On top of that, the matrix is based on industrial waste polymers (recycled polycarbonate blended with acrylonitrile butadiene styrene polymer and recycled propylene), additives are explored, and the printing settings are optimized, benefiting from molecular, rheological, thermal, morphological, and material property analyses. Despite this, DPAM resulted in a rougher surface finish compared to FFF and can be seen as a faster printing technique that reduces energy consumption and molecular degradation. The findings help formulate guidelines for the successful DPAM and FFF of sCF-based composite materials in view of better market appreciation. Full article

The demand for regenerative energy and electric automotive applications has grown in recent decades. Supercapacitors have multiple applications in consumer alternative electronic products due to their excellent energy density, rapid charge/discharge time, and safety. CuFe₂O₄-incorporated three-dimensional graphene sheet (3DGS) nanocomposites were studied by different characterization studies such as X-ray diffraction, transmission electron microscopy, and scanning electron microscopy. The electrochemical studies were based on cyclic voltammetry (CV), galvanostatic charge–discharge (GCD), and electrochemical impedance spectroscopy (EIS) measurements. As prepared, 3DGS/CuFe₂O₄ nanocomposites exhibited an excellent surface area, high energy storage with appreciable durability, and excellent electrocatalysis properties. A supercapacitor with 3DGS/CuFe₂O₄-coated nickel foam (NF) electrodes exhibited an excellent specific capacitance of 488.98 Fg⁻¹, a higher current density, as well as a higher power density. After charge–discharge cycles in a 2.0 M KOH aqueous electrolyte solution, the 3DGS/CuFe₂O₄/NF electrodes exhibited an outstanding cyclic stability of roughly 95% at 10 Ag⁻¹, indicating that the prepared nanocomposites could have the potential for energy storage applications. Moreover, the 3DGS/CuFe₂O₄ electrode exhibited an excellent electrochemical detection of chloramphenicol with a detection limit of 0.5 µM, linear range of 5–400 µM, and electrode sensitivity of 3.7478 µA µM⁻¹ cm⁻². Full article

Ultra-small magnetic Fe₃O₄ nanoparticles are successfully synthesized in basic solutions by using the radiolytic method of the partial reduction in Fe^III in the presence of poly-acrylate (PA), or by using the coprecipitation method of Fe^III and Fe^II salts in the presence of PA. The optical, structural, and magnetic properties of the nanoparticles were examined using UV–Vis absorption spectroscopy, high-resolution transmission electron microscopy (HRTEM), X-ray diffraction (XRD), and SQUID magnetization measurements. The HRTEM and XRD analysis confirmed the formation of ultra-small magnetite nanoparticles in a spinel structure, with a smaller size for radiation-induced particles coated by PA (5.2 nm) than for coprecipitated PA-coated nanoparticles (11 nm). From magnetization measurements, it is shown that the nanoparticles are superparamagnetic at room temperature. The magnetization saturation value Ms = 50.1 A m² kg⁻¹ of radiation-induced nanoparticles at 60 kGy is higher than Ms = 18.2 A m² kg⁻¹ for coprecipitated nanoparticles. Both values are compared with nanoparticles coated with other stabilizers in the literature. Full article

African swine fever (ASF) is an acute, hemorrhagic, highly contagious disease in pigs caused by African swine fever virus (ASFV). Our previous study identified that the ASFV MGF300-2R protein functions as a virulence factor and found that MGF300-2R degrades IKKβ via selective autophagy. However, the E3 ubiquitin ligase responsible for IKKβ ubiquitination during autophagic degradation still remains unknown. In order to solve this problem, we first pulled down 328 proteins interacting with MGF300-2R through immunoprecipitation-mass spectrometry. Next, we analyzed and confirmed the interaction between the E3 ubiquitin ligase TRIM21 and MGF300-2R and demonstrated the catalytic role of TRIM21 in IKKβ ubiquitination. Finally, we indicated that the degradation of IKKβ by MGF300-2R was dependent on TRIM21. In summary, our results indicate TRIM21 is the E3 ubiquitin ligase involved in the degradation of IKKβ by MGF300-2R, thereby augmenting our understanding of the functions of MGF300-2R and offering insights into the rational design of live attenuated vaccines and antiviral strategies against ASF. Full article

High-average-power narrow-linewidth tunable solid-state lasers in the wavelength region between 2 and 3 μm are attractive light sources for many applications. This paper reports a narrow-linewidth widely tunable laser system based on the polycrystalline Cr²⁺:ZnSe elements pumped by repetitively pulsed 2.1 µm Ho³⁺:YAG laser operating at a pulse rate of tens of kilohertz. An advanced procedure of ZnSe element doping and surface improvement was applied to increase the laser-induced damage threshold, which resulted in an increase in the output power of the Cr²⁺:ZnSe laser system. The high-average-power laser system comprised double master oscillators and power amplifiers: Ho³⁺:YAG and Cr²⁺:ZnSe laser oscillators, and Ho³⁺:YAG and Cr²⁺:ZnSe power amplifiers. The output wavelength was widely tuned within 2.3–2.7 µm by means of an acousto-optical tunable filter inside a Cr²⁺:ZnSe master oscillator cavity. The narrow-linewidth operation at the pulse repetition rate of 20–40 kHz in a high-quality beam with an average output power of up to 9.7 W was demonstrated. Full article

Bikeshare, as a convenient transport mode, can address the first- and last-mile travel needs of metro trips while generating many environmental benefits, such as reducing the use of environmentally unfriendly transport modes and lowering the carbon emissions of the urban transportation system. This paper takes bikeshare as a feeder mode of metro stations (BS-FMMS) as the research object and compares the spatial and temporal differences in the carbon emission reduction benefits of BS-FMMS on workdays and non-workdays by using the framework of BS-FMMS carbon reduction benefit analysis and the methods of time-series analysis, spatial aggregation analysis, and box plot analysis. The results show that the carbon emission reduction benefit of bikeshare has obvious morning and evening peaks on workdays, while it tends to be stable without obvious peaks during the day on non-workdays. From the perspective of spatial distribution, the carbon emission reduction benefits of BS-FMMS are more significant in the metro station areas in the south of Baoan district, the west of Nanshan district, the central of Longhua district, and the south of Futian district in Shenzhen city, and the metro stations where the carbon emission reduction benefits of the non-workday are greater than those of the workday are mainly concentrated in Nanshan district, Futian district, and Luohu district. There is a significant positive correlation between BS-FMMS ridership and carbon emission reduction. These findings can provide clear policy implications for the decarbonization development of urban transportation systems. Full article

Background: Universal accessibility is one of the most active lines of intervention for people with disabilities and older adults. This accessibility has become a topic of growing interest regarding home access and use. Therefore, the main objective of this study was to create and validate a home assessment tool: the HESA II. Methods: The study was conducted in four phases: (1) agreement on variables by an expert panel; (2) development of 90 items according to the AOTA framework; (3) pilot test with n = 20; and (4) final study with 156 subjects where confirmatory factor analysis was performed. Results: The tool consisted of 85 items divided into five subscales related to each of the main spaces of Spanish homes: living room; kitchen; bedroom; and bathroom. Conclusions: The tool demonstrates good psychometric properties of reliability. The HESA II assesses home accessibility based on limitations in activity and participation restriction of the evaluated person as per the International Classification of Functioning, Disability, and Health rather than on a diagnosis, making it applicable to a wide range of groups. Full article

Young people with borderline intelligence functioning (BIF) have intellectual functioning at the border between intellectual disability and those considered neurotypical. This population group is often underrepresented in social research, which makes it difficult to understand their experiences and needs. The research aims to understand the daily lives of young people with BIF to identify needs that society might not be aware of. The study was conducted with a sample of 30 young people. The ethnomethodological design was appropriate for the study of the routines and daily dynamics of these young people, which allowed the researchers to understand the experiences and meanings of the participants from their own perspective. The analysis was carried out in the context of the subject of Qualitative Research Tools in Social Work with fourth-year students, through participant observation, semi-structured interviews, and field diaries. Data analysis was performed using the Atlas.ti23 qualitative content analysis program. The findings suggest a strong dependence on family and social support; a daily life marked by challenges; and a search for autonomy, among many other aspects. Collaboration with the participants allowed the researchers to better understand their experiences and needs from reflexivity. Full article

In this paper, we present an efficient method for solving a class of higher order fractional differential equations with general boundary conditions. The convergence of the numerical method is proved and an error estimate is given. Finally, eight numerical examples, both linear and nonlinear, are presented to demonstrate the accuracy of our method. The proposed method introduces suitable base functions to calculate the approximate solutions and only requires us to deal with the linear or nonlinear systems. Thus, our method is convenient to implement. Furthermore, the numerical results show that the proposed method performs better compared to the existing ones. Full article

The epidermal growth factor receptor (EGFR) is a pivotal target in cancer therapy due to its significance within the tyrosine kinase family. EGFR inhibitors like AG-1478 and PD153035, featuring a 4-anilinoquinazoline moiety, have garnered global attention for their potent therapeutic activities. While pre-clinical studies have highlighted the significant impact of halogen substitution at the C3’-anilino position on drug potency, the underlying mechanism remains unclear. This study investigates the influence of halogen substitution (X = H, F, Cl, Br, I) on the structure, properties, and spectroscopy of halogen-substituted 4-anilinoquinazoline tyrosine kinase inhibitors (TKIs) using time-dependent density functional methods (TD-DFT) with the B3LYP functional. Our calculations revealed that halogen substitution did not induce significant changes in the three-dimensional conformation of the TKIs but led to noticeable alterations in electronic properties, such as dipole moment and spatial extent, impacting interactions at the EGFR binding site. The UV–visible spectra show that more potent TKI-X compounds typically have shorter wavelengths, with bromine’s peak wavelength at 326.71 nm and hydrogen, with the lowest IC50 nM, shifting its lambda max to 333.17 nm, indicating a correlation between potency and spectral characteristics. Further analysis of the four lowest-lying conformers of each TKI-X, along with their crystal structures from the EGFR database, confirms that the most potent conformer is often not the global minimum structure but one of the low-lying conformers. The more potent TKI-Cl and TKI-Br exhibit larger deviations (RMSD > 0.65 Å) from their global minimum structures compared to other TKI-X (RMSD < 0.15 Å), indicating that potency is associated with greater flexibility. Dipole moments of TKI-X correlate with drug potency (ln(IC50 nM)), with TKI-Cl and TKI-Br showing significantly higher dipole moments (>8.0 Debye) in both their global minimum and crystal structures. Additionally, optical spectral shifts correlate with potency, as TKI-Cl and TKI-Br exhibit blue shifts from their global minimum structures, in contrast to other TKI-X. This suggests that optical reporting can effectively probe drug potency and conformation changes. Full article

Traditional bioclimatic classification schemes have several inherent shortcomings; they do not represent anthropogenic impact, they contain a bias for global north representation, and they lack flexibility regarding novel climates that may arise due to climate change. Here we present an alternative approach, using a machine learning approach. We combine European Space Agency Land Cover Classification data with traditional bioclimate classification climate variables, and additional variables; latitude, elevation, and topography. We utilise a random forest algorithm to create a classification system that overcomes the limitations and biases of the traditional schemes. The algorithm produced is able to predict land cover classification globally at 0.5-degree resolution with 93% accuracy. The resulting classifications account for human impact, particularly via agriculture, are informed by the topography of a region, and avoids the biases that traditional bioclimatic schemes contain. The algorithm can provide insights into the drivers of land cover change, the spatial distribution of land cover change, the potential impacts on ecosystem services and human well-being. Furthermore, the random forest model serves as a novel approach to the prediction of future land cover, and can be used to identify regions at risk of a land cover transition. Our data-based machine learning approach produces larger land-cover changes due to climate change than a traditional bioclimatic scheme, especially in sensitive regions such as Amazonia. Overall, our new approach projects approximately 17.4 million square kilometre of land-cover change per degree celsius of global warming. Full article

The global demand for sustainable energy sources has led to extensive research regarding (green) hydrogen production technologies, with water splitting emerging as a promising avenue. In the near future the calculated hydrogen demand is expected to be 2.3 Gt per year. For green hydrogen production, 1.5 ppm of Earth’s freshwater, or 30 ppb of saltwater, is required each year, which is less than that currently consumed by fossil fuel-based energy. Functional ceramics, known for their stability and tunable properties, have garnered attention in the field of water splitting. This review provides an in-depth analysis of recent advancements in functional ceramics for water splitting, addressing key mechanisms, challenges, and prospects. Theoretical aspects, including electronic structure and crystallography, are explored to understand the catalytic behavior of these materials. Hematite photoanodes, vital for solar-driven water splitting, are discussed alongside strategies to enhance their performance, such as heterojunction structures and cocatalyst integration. Compositionally complex perovskite oxides and high-entropy alloys/ceramics are investigated for their potential for use in solar thermochemical water splitting, highlighting innovative approaches and challenges. Further exploration encompasses inorganic materials like metal oxides, molybdates, and rare earth compounds, revealing their catalytic activity and potential for water-splitting applications. Despite progress, challenges persist, indicating the need for continued research in the fields of material design and synthesis to advance sustainable hydrogen production. Full article

The increasing commercial, industrial, and medical applications of plastics cannot be halted during the coming years. Microplastics are a new class of plastic pollutants which have emerged as escalating environmental threats. The persistence, effects, and removal of MPs present in soil, water, and numerous organisms have become an important research field. However, atmospheric microplastics (AMPs), which are subcategorized into deposited and suspended, remain largely unexplored. This review presents the recent developments and challenges involved in fully understanding suspended and deposited AMPs. The evaluation of indoor suspended MP fibers needs to be critically investigated to understand their implications for human health. Furthermore, the transportation of AMPs to isolated locations, such as cryospheric regions, requires immediate attention. The major challenges associated with AMPs, which have hindered advancement in this field, are inconsistency in the available data, limited knowledge, and the lack of standardized methodologies for the sampling and characterization techniques of AMPs. Full article

The mass $m_{{\mu }^{-}}$ of the negative muon is one of the parameters of the elementary particle Standard Model and it allows us to verify the CPT (charge–parity–time) symmetry theorem by comparing $m_{{\mu }^{-}}$ value with the mass $m_{{\mu }^{+}}$ of the positive muon. However, the experimental determination precision of $m_{{\mu }^{-}}$ is $3.1\mathrm{ppm}$, which is an order of magnitude lower than the determination precision of $m_{{\mu }^{+}}$ at $120\mathrm{ppb}$. The authors aim to determine $m_{{\mu }^{-}}$ and the magnetic moment ${\mu }_{{\mu }^{-}}$ with a precision of $\mathcal{O}\left(10\mathrm{ppb}\right)$ through spectroscopy of the hyperfine structure (HFS) of muonic helium-4 atom ${(}^4\mathrm{He}{\mu }^{-}{e}^{-})$ under high magnetic fields. ${}^4\mathrm{He}{\mu }^{-}{e}^{-}$ is an exotic atom where one of the two electrons of the ${}^4\mathrm{He}$ atom is replaced by a negative muon. To achieve the goal, it is necessary to determine the HFS of ${}^4\mathrm{He}{\mu }^{-}{e}^{-}$ with a precision of $\mathcal{O}\left(1\mathrm{ppb}\right)$. This paper describes the determination procedure of the HFS of ${}^4\mathrm{He}{\mu }^{-}{e}^{-}$ in weak magnetic fields reported recently, and the work towards achieving the goal of higher precision measurement. Full article

Considering the weak resistance to interference and generalization ability of traditional UAV visual landing navigation algorithms, this paper proposes a deep-learning-based approach for airport runway line detection and fusion of visual information with IMU for localization. Firstly, a coarse positioning algorithm based on YOLOX is designed for airport runway localization. To meet the requirements of model accuracy and inference speed for the landing guidance system, regression loss functions, probability prediction loss functions, activation functions, and feature extraction networks are designed. Secondly, a deep-learning-based runway line detection algorithm including feature extraction, classification prediction and segmentation networks is designed. To create an effective detection network, we propose efficient loss function and network evaluation methods Finally, a visual/inertial navigation system is established based on constant deformation for visual localization. The relative positioning results are fused and optimized with Kalman filter algorithms. Simulation and flight experiments demonstrate that the proposed algorithm exhibits significant advantages in terms of localization accuracy, real-time performance, and generalization ability, and can provide accurate positioning information during UAV landing processes. Full article

Climate change might benefit water-stress-adapted weeds, further impairing their management. To evaluate the impact of soil moisture regimes on the growth and reproductive behaviour of ACCase-resistant and ACCase-susceptible phenotypes of sterile oat (Avena sterilis subsp. ludoviciana (Durieu) Nyman), a greenhouse experiment was carried out in 2020 and 2021. The factors were soil moisture regimes (100% field capacity (FC) as well-watered, 75% FC, 50% FC, and 25% FC) and ACCase-resistant and ACCase-susceptible phenotypes of sterile oat. Increased drought stress conditions reduced the number of tillers per plant by 34, 55, and 83% and the number of seeds per plant by 36, 61, and 89% in the 75% FC, 50% FC, and 25% FC conditions, respectively, compared to the well-watered treatment. Notably, both phenotypes reacted similarly to water stress, with no interactions between the two factors. Regardless of water stress, the resistant phenotypes produced fewer seeds per plant, indicating fitness costs. However, due to their high plasticity, both phenotypes will still produce seeds even when facing severe water stress conditions. Thus, sterile oat is expected to continue infesting crop fields in the near future, but with ACCase-resistant phenotypes being less successful than susceptible ones in the absence of herbicide application. Full article

In today’s perishable products industry, the importance of sustainability as a critical consideration has significantly increased. This study focuses on the design of a sustainable perishable product supply chain network (SPPSCN), considering the factors of economics cost, environmental impacts, and social responsibility. The proposed model is a comprehensive production–location–inventory problem optimization framework that addresses multiple objectives, echelons, products, and periods. To solve this complex problem, we introduce three hybrid metaheuristic algorithms: bat algorithm (BA), shuffled frog leaping algorithm (SFLA), and cuckoo search (CS) algorithm, all hybrid with variable neighbourhood search (VNS). Sensitivity to input parameters is accounted for using the Taguchi method to tune these parameters. Additionally, we evaluate and compare these approaches among themselves and benchmark their results against a reference method, a hybrid genetic algorithm (GA) with VNS. The quality of the Pareto frontier is evaluated by six metrics for test problems. The results highlight the superior performance of the bat algorithm with variable neighbourhood search. Furthermore, a sensitivity analysis is conducted to evaluate the impact of key model parameters on the optimal objectives. It is observed that an increase in demand has a nearly linear effect on the corresponding objectives. Moreover, the impact of extending raw material shelf life and product shelf life on these objectives is limited to a certain range. Beyond a certain threshold, the influence becomes insignificant. Full article