These days, many attempts are being made worldwide to use drones for food delivery. Especially in the case of food, fast delivery is required, while maintaining its temperature and taste to the maximum. Therefore, using drones is suitable for food delivery because they can move through the air without being affected by traffic congestion. In this study, the purpose is to develop an optimal algorithm that can complete the delivery of customer food orders in the shortest time using drones. We have applied mathematical-model-based optimization techniques to develop an algorithm that reflects the given problem situation. Since the delivery capacity of drones is limited, and especially small, multiple drones may be used to deliver the food ordered by a particular customer. What is important here is that the drones assigned to one customer must arrive consecutively within a short period of time. This fact is reflected in this mathematical model. In the numerical example, it can be confirmed that the proposed algorithm operates optimally by comparing a case where the arrival time of multiple drones assigned to one customer is limited to a certain time and a case when it is not. Full article

This study aims to assess the ability of old, immobilized fresh, and free fresh green microalgae (a Bracteacoccus sp.) to remove methyl orange (MO) dye from aqueous solutions. The effects of four factors, including initial MO concentration (5–25 mg L⁻¹), adsorbent dose (0.02–0.10 g mL⁻¹), temperature (4–36 °C), and contact time (5–95 min), were examined. The Box–Behnken design (BBD) was used to determine the number of required experiments and the optimal conditions expected to provide the highest removal percentage of MO dye from aqueous solutions. The experimental data were applied to four isotherm models (Langmuir, Freundlich, Dubinin–Radushkevich (D–R), and Temkin isotherm models) and three kinetic models (pseudo–first–order, pseudo–second–order, and Elovich kinetic models). The results indicate that the highest removal of MO (97%) could be obtained in optimal conditions consisting of an initial MO concentration of 10.0 mg L⁻¹, an adsorbent dose of 0.10 g mL⁻¹, a temperature of 20 °C, and a contact time of 75 min. Moreover, the experimental data were best fitted by the Langmuir and Temkin isotherm models and followed a pseudo-second-order kinetic model. The interaction between MO and the Bracteacoccus sp. was confirmed by UV and ESI/MS analyses, indicating that MO removal occurred via both sorption and degradation processes. Full article

The description of the electron–electron interactions in two-dimensional materials has a dimensional mismatch, where electrons live in (2 + 1)D while photons propagate in (3 + 1)D. In order to define an action in (2 + 1)D, one may perform a dimensional reduction of quantum electrodynamics in (3 + 1)D (QED4) into pseudo-quantum electrodynamics (PQED). The main difference between this model and QED4 is the presence of a pseudo-differential operator in the Maxwell term. However, besides the Coulomb repulsion, electrons in a material are subjected to several microscopic interactions, which are inherent in a many-body system. These are expected to reduce the range of the Coulomb potential, leading to a short-range interaction. Here, we consider the coupling to a scalar field in PQED for explaining such a mechanism, which resembles the spontaneous symmetry breaking (SSB) in Abelian gauge theories. In order to do so, we consider two cases: (i) by coupling the quantum electrodynamics to a Higgs field in (3 + 1)D and, thereafter, performing the dimensional reduction; and (ii) by coupling a Higgs field to the gauge field in PQED and, subsequently, calculating its effective potential. In case (i), we obtain a model describing electrons interacting through the Yukawa potential and, in case (ii), we show that SSB does not occur at one-loop approximation. The relevance of the model for describing electronic interactions in two-dimensional materials is also addressed. Full article

Dual humanoid robot collaborative control systems possess better flexibility and adaptability in complex environments due to their similar structures to humans. This paper adopts a distributed model predictive controller based on the leader–follower approach to address the collaborative transportation control issue of dual humanoid robots. In the dual-robot collaborative control system, network latency issues may arise due to unstable network conditions, affecting the consistency of dual-robot collaboration. To solve this issue, a communication protocol was constructed through socket communication for dual-robot collaborative consistency, thereby resolving the problem of consistency in dual humanoid robot collaboration. Additionally, due to the complex structure of humanoid robots, there are deficiencies in position tracking accuracy during movement. To address the poor accuracy in position tracking, this paper proposes a distributed model predictive control that considers historical cumulative error, thus enhancing the position tracking accuracy of dual-robot collaborative control. Full article

In humanitarian aid scenarios, the model of cumulative capacitated vehicle routing problem can be used in vehicle scheduling, aiming at delivering materials to recipients as quickly as possible, thus minimizing their wait time. Traditional approaches focus on this metric, but practical implementations must also consider factors such as driver labor intensity and the capacity for on-site decision-making. To evaluate driver workload, the operation times of relief vehicles are typically used, and multi-objective modeling is employed to facilitate on-site decision-making. This paper introduces a multi-objective cumulative capacitated vehicle routing problem considering operation time (MO-CCVRP-OT). Our model is bi-objective, aiming to minimize both the cumulative wait time of disaster-affected areas and the extra expenditures incurred by the excess operation time of rescue vehicles. Based on the traditional grey wolf optimizer algorithm, this paper proposes a dynamic grey wolf optimizer algorithm with floating 2-opt (DGWO-F2OPT), which combines real number encoding with an equal-division random key and ROV rules for decoding; in addition, a dynamic non-dominated solution set update strategy is introduced. To solve MO-CCVRP-OT efficiently and increase the algorithm’s convergence speed, a multi-objective improved floating 2-opt (F2OPT) local search strategy is proposed. The utopia optimum solution of DGWO-F2OPT has an average value of two fitness values that is 6.22% lower than that of DGWO-2OPT. DGWO-F2OPT’s average fitness value in the algorithm comparison trials is 16.49% less than that of NS-2OPT. In the model comparison studies, MO-CCVRP-OT is 18.72% closer to the utopian point in Euclidean distance than CVRP-OT. Full article

We propose a genetic algorithm for optimizing oil skimmer assignments, introducing a tailored repair operation for constrained assignments. Methods essentially involve simulation-based evaluation to ensure adherence to South Korea’s regulations. Results show that the optimized assignments, compared to current ones, reduced work time on average and led to a significant reduction in total skimmer capacity. Additionally, we present a deep neural network-based surrogate model, greatly enhancing efficiency compared to simulation-based optimization. Addressing inefficiencies in mobilizing locations that store oil skimmers, further optimization aimed to minimize mobilized locations and was validated through scenario-based simulations resembling actual situations. Based on major oil spills in South Korea, this strategy significantly reduced work time and required locations. These findings demonstrate the effectiveness of the proposed genetic algorithm and mobilized location minimization strategy in enhancing oil spill response operations. Full article

Submerged aquatic vegetation plays a fundamental role as a habitat for the biodiversity of marine species. To carry out the research and monitoring of submerged aquatic vegetation more efficiently and accurately, it is important to use advanced technologies such as underwater robots. However, when conducting underwater missions to capture photographs and videos near submerged aquatic vegetation meadows, algae can become entangled in the propellers and cause vehicle failure. In this context, a neurobiologically inspired control architecture is proposed for the control of unmanned underwater vehicles with redundant thrusters. The proposed control architecture learns to control the underwater robot in a non-stationary environment and combines the associative learning method and vector associative map learning to generate transformations between the spatial and velocity coordinates in the robot actuator. The experimental results obtained show that the proposed control architecture exhibits notable resilience capabilities while maintaining its operation in the face of thruster failures. In the discussion of the results obtained, the importance of the proposed control architecture is highlighted in the context of the monitoring and conservation of underwater vegetation meadows. Its resilience, robustness, and adaptability capabilities make it an effective tool to face challenges and meet mission objectives in such critical environments. Full article

Ever since Varela and Maturana proposed the concept of autopoiesis as the minimal requirement for life, there has been a focus on cellular systems that erect topological boundaries to separate themselves from their surrounding environment. Here, we reconsider whether the existence of such a spatial boundary is strictly necessary for self-producing entities. This work presents a novel computational model of a minimal autopoietic system inspired by dendrites and molecular dynamic simulations in three-dimensional space. A series of simulation experiments where the metabolic pathways of a particular autocatalytic set are successively inhibited until autocatalytic entities that could be considered autopoietic are produced. These entities maintain their distinctness in an environment containing multiple identical instances of the entities without the existence of a topological boundary. This gives rise to the concept of a metabolic boundary which manifests as emergent self-selection criteria for the processes of self-production without any need for unique identifiers. However, the adoption of such a boundary comes at a cost, as these autopoietic entities are less suited to their simulated environment than their autocatalytic counterparts. Finally, this work showcases a generalized metabolism-centered approach to the study of autopoiesis that can be applied to both physical and abstract systems alike. Full article

Recently, there has been worldwide growth in consumer nutrition awareness, which has resulted in a market-driven increase in the demand for “functional food”, which, in addition to traditional nutrients, also contains ingredients with specific properties that have a beneficial effect on human health. One of the types of functional food is so-called “probiotic food”, which includes, for example, frozen desserts. These products appear attractive to the consumer because of their sensory, nutritional and refreshing qualities. Due to progress in science, genetics, the acquisition of new sources of probiotic microorganisms and new plant varieties, the beneficial effects of the characteristic metabolites of the microbiome—so-called postbiotics—and also aspects of NGPs (Next Generation Probiotics), work is under way to optimize the technology used during the production of such products. At the same time, there is an observed market-based increase in the supply of new formulations based only on plant-origin materials with different technological modifications, including prebiotic enrichment, which allows for the production of a synbiotic product. Therefore, the objective of this study is a narrative review, in combination with the authors’ own experiments, concerning the impact of various factors on functional, plant-origin frozen desserts, from the point of view of maintaining their quality. Full article

2-phenylethanol (2-PE) is a valuable aromatic alcohol with diverse applications in cosmetics, food, beverages, and pharmaceutical industries. Currently, 2-PE is produced either through chemical synthesis or by extraction from plant materials. However, both conventional production methods have their own limitations. Therefore, there is a need for more eco-friendly and cost-effective approaches to produce natural 2-PE. Biotechnological routes, particularly microbial fermentations, hold promise for natural 2-PE production, especially when using low-cost substrates. In this study, 2-PE was produced by de novo synthesis via the shikimate pathway, using the yeast Yarrowia lipolytica in a medium composed of sugar beet molasses (SBM) and yeast extract (YE) as carbon and nitrogen sources, respectively. A genetically engineered strain was generated, in which the SUC2 gene was transformed, expressing the invertase enzyme, enabling Y. lipolytica to efficiently utilize SBM as a cost-effective substrate. A central composite design allowed for the optimization of the concentrations of the carbon and nitrogen sources, resulting in approximately 0.71 g_(2-PE)/L_{(culture medium)}. The results obtained highlight the potential of utilizing SBM as a low-cost substrate for 2-PE production, advancing biotechnological approaches in fragrance synthesis. Full article

Extra energy consumption, inefficient nitrogen removal, and excessive sludge production are major challenges faced by wastewater treatment plants (WWTPs) that rely on the traditional activated sludge process. Fermentation of wasted activated sludge (WAS) and novel nitrogen removal technologies based on partial nitrification (PN) have emerged as promising solutions to these issues. Recent studies have revealed an innovative strategy that integrates these two processes by supplementing fermentation liquid into activated sludge to induce PN. This review summarizes the research progress on PN establishment induced by the fermentation process. The microbiology and establishment methods of PN are briefly introduced, followed by a detailed discussion on the process, influencing factors, and product characteristics of WAS fermentation. The core section focuses on the side-stream and main-stream approaches of fermentation-induced PN, comparing their performance and application prospects. The potential mechanisms are explored, with an emphasis on the roles of free ammonia for the side-stream approach and the high tolerance of ammonium oxidizers to in-site fermentation stress for the main-stream approach. Finally, the limitations of the current research and future perspectives are discussed, highlighting the need for further investigation into microbial ecology, process optimization, and long-term stability. This review aims to provide insights into the synergistic integration of WAS fermentation and PN for sustainable and energy-efficient wastewater treatment. Full article

The Cornus kousa tree, which is of Asian origin, is often cultivated for ornamental purposes and used in traditional medicine. The tree produces sugar-rich fruits, which are potential habitats for natural yeasts. The identification of new yeast strains has many advantages for the industry and research. This study aimed to isolate and identify yeast species from C. kousa fruits and to understand their microbial ecology. Ripe and rotten fruits, which had fallen on the ground naturally, were collected and soaked in culture media, followed by plate spreading for colony growth. The morphological examination revealed three distinct colony types, including two from the ripe fruits and one from the rotten fruits. The analysis of the internal transcribed spacer 1 region indicated three yeast strains corresponding to the three colony types: Torulaspora delbrueckii and Pichia kluyveri from the ripe fruits and Saccharomyces cerevisiae from the rotten fruits. The metabolic characterizations demonstrated that all three yeasts efficiently consumed glucose and produced alcohol. S. cerevisiae exhibited the strongest fermentation ability and the highest growth rate. These findings showed that Cornus kousa fruit is a source of diverse yeast species, with distinct species associated with different states of fruit decomposition. Full article

The therapeutic effects of curcumin and its derivatives, based on research in recent years, are limited by their low bioavailability. To improve bioavailability and develop the medical field of application, different delivery systems have been developed that are adapted to certain environments or the proposed target type. This study presents some half-curcuminoids prepared by the condensation of acetylacetone with 4-hydroxybenzaldehyde (C1), 4-hydroxy-3-methoxybenzaldehyde (C2), 4-acetamidobenzaldehyde (C3), or 4-diethylaminobenzaldehyde (C4), at microwaves as a simple, solvent-free, and eco-friendly method. The four compounds obtained were characterized in terms of morphostructural and photophysical properties. Following the predictions of theoretical studies on the biological activities related to the molecular structure, in vitro tests were performed for compounds C1–C3 to evaluate the antitumor properties and for C4’s possible applications in the treatment of neurological diseases. The four compounds were encapsulated in two types of hydrogel matrices. First, the alginate–glucosamine network was generated and then the curcumin analogs were loaded (G1, G3, G5–G7, and G9). The second type of hydrogels was obtained by loading the active compound together with the generation of the hydrogel carrier matrices, by simply dissolving (G4 and G10) or by chemically binding half-curcuminoid derivatives to glucosamine (G2 and G8). Thus, two types of curcumin analog delivery systems were obtained, which could be applied in various types of medical treatments. Full article

Wheat plants are impacted by Fusarium head blight (FHB) infection, which poses a huge threat to wheat growth, development, storage and food safety. In this study, a fungal strain was isolated from diseased wheat plants and identified as Fusarium asiaticum F1, known to be a member of the Fusarium graminearum species complex, agents causally responsible for FHB. In order to control this disease, new alternatives need to be developed for the use of antagonistic bacteria. Bacillus velezensis E2 (B. velezensis E2), isolated from a previous investigation in our laboratory, showed a notable inhibitory effect on F. asiaticum F1 growth and deoxynivalenol (DON) synthesis in grains. The spore germination of F. asiaticum F1 was significantly reduced and the spores showed vesicular structures when treated with B. velezensis E2. Observations using scanning electron microscopy (SEM) showed that the hyphae of F. asiaticum F1 were shrunken and broken when treated with B. velezensis E2. The RNA-seq results of F1 hyphae treated with B. velezensis E2 showed that differentially expressed genes (DEGs), which were involved in multiple metabolic pathways such as toxin synthesis, autophagy process and glycan synthesis, especially the genes associated with DON synthesis, were significantly downregulated. In summary, those results showed that B. velezensis E2 could inhibit F. asiaticum F1 growth and reduce the gene expression of DON synthesis caused by F1. This study provides new insights and antagonistic mechanisms for the biological control of FHB during wheat growth, development and storage. Full article

Since industrialization, global temperatures have continued to rise. Human activities have resulted in heavy metals being freed from their original, fixed locations. Because of global warming, glaciers are melting, carbon dioxide concentrations are increasing, weather patterns are shifting, and various environmental forces are at play, resulting in the movement of heavy metals and alteration of their forms. In this general context, the impact of heavy metals on ecosystems and organisms has changed accordingly. For most ecosystems, the levels of heavy metals are on the rise, and this rise can have a negative impact on the ecosystem as a whole. Numerous studies have been conducted to analyze the combined impacts of climate change and heavy metals. However, the summary of the current studies is not perfect. Therefore, this review discusses how heavy metals affect ecosystems during the process of climate change from multiple perspectives, providing some references for addressing the impact of climate warming on environmental heavy metals. Full article

Polyvinyl chloride microplastics (PVC-MPs) are microplastic pollutants widely present in the environment, but their potential risks to human lung health and underlying toxicity mechanisms remain unknown. In this study, we systematically analyzed the effects of PVC-MPs on the transcriptome and metabolome of BEAS-2B cells using high-throughput RNA sequencing and untargeted metabolomics technologies. The results showed that exposure to PVC-MPs significantly reduced the viability of BEAS-2B cells, leading to the differential expression of 530 genes and 3768 metabolites. Further bioinformatics analyses showed that PVC-MP exposure influenced the expression of genes associated with fluid shear stress, the MAPK and TGF-β signaling pathways, and the levels of metabolites associated with amino acid metabolism. In particular, integrated pathway analysis showed that lipid metabolic pathways (including glycerophospholipid metabolism, glycerolipid metabolism, and sphingolipid metabolism) were significantly perturbed in BEAS-2B cells following PVC-MPs exposure. This study provides new insights and targets for a deeper understanding of the toxicity mechanism of PVC-MPs and for the prevention and treatment of PVC-MP-associated lung diseases. Full article

A long-term intake of a high-fat and high-fructose diet (HFFD), even a high-fat, high-fructose but low-protein diet (HFFD + LP), could cause obesity associated with cognitive impairments. In the present study, rats were subjected to a normal diet (ND), an HFFD diet, an HFFD + LP diet, and an HFFD with kidney bean protein (KP) diet for 8 weeks to evaluate the effect of KP on HFFD- or HFFD + LP-induced obesity and cognitive impairment. The results demonstrated that compared with the HFFD diet, KP administration significantly decreased the body weight by 7.7% and the serum Angiotensin-Converting Enzyme 2 (ACE-2) and Insulin-like Growth Factor 1 (IGF-1) levels by 14.4% and 46.8%, respectively (p < 0.05). In addition, KP suppressed HFFD-induced cognitive impairment, which was evidenced by 8.7% less time required to pass the water maze test. The 16s RNA analysis of the colonic contents showed that the relative abundance of Bifidobacterium, Butyricimonas, and Alloprevotella was increased by KP by 5.9, 44.2, and 79.2 times. Additionally, KP supplementation primarily affected the choline metabolic pathway in the liver, and the synthesis and functional pathway of neurotransmitters in the brain, thereby improving obesity and cognitive function in rats. Full article

A fundamental regulatory framework to elucidate the role of electrical stimulation (ES) in reducing long production cycles, enhancing protein utilization, and boosting product quality of dry-cured ham is essential. However, how mitochondria and enzymes in meat fibers are altered by ES during post-processing, curing, and fermentation procedures remains elusive. This study sought to explore the impact of ES on the regulation of heat shock proteins (HSP27, HSP70), apoptotic pathways, and subsequent influences on dry-cured pork loin quality. The gathered data validated the hypothesis that ES notably escalates mitochondrial oxidative stress and accelerates mitochondrial degradation along the ripening process. The proapoptotic response in ES-treated samples was increased by 120.7%, with a cellular apoptosis rate 5-fold higher than that in control samples. This mitochondrial degradation is marked by increased ratios of Bax/Bcl-2 protein along the time course, indicating that apoptosis could contribute to the dry-cured ham processing. ES was shown to further down-regulate HSP27 and HSP70, establishing a direct correlation with the activation of mitochondrial apoptosis pathways, accompanied by dry-cured ham quality improvements. The findings show that ES plays a crucial role in facilitating the ripening of dry-cured ham by inducing mitochondrial apoptosis to reduce HSP expression. This knowledge not only explains the fundamental mechanisms behind myofibril degradation in dry-cured ham production but also offers a promising approach to enhance quality and consistency. Full article

Agaricus bisporus, commonly known as the button mushroom, has attracted attention for its biological properties, including antimicrobial activities. Here, we evaluated the efficacy of ethanolic and acetonic extracts from white and brown A. bisporus against different bacterial strains, including antibiotic-resistant strains. Bioautography and principal component analysis identified the most active antibacterial compounds for each of the tested bacteria and indicated the main markers responsible for the strain-specific effects. In addition, the mushroom extracts demonstrated a synergistic impact when combined with the antistaphylococcal antibiotic AFN-1252. Full article

N4-methylcytosine (4mC) is a critical epigenetic modification that plays a pivotal role in the regulation of a multitude of biological processes, including gene expression, DNA replication, and cellular differentiation. Traditional experimental methods for detecting DNA N4-methylcytosine sites are time-consuming, labor-intensive, and costly, making them unsuitable for large-scale or high-throughput research. Computational methods for identifying DNA N4-methylcytosine sites enable the rapid and cost-effective analysis of DNA 4mC sites across entire genomes. In this study, we focus on the identification of DNA 4mC sites in the mouse genome. Although there are already some computational methods that can predict DNA 4mC sites in the mouse genome, there is still significant room for improvement in accurately predicting them due to their inability to fully capture the multifaceted characteristics of DNA sequences. To address this issue, we propose a new deep learning predictor called Mus4mCPred, which utilizes multi-view feature learning and deep hybrid networks for accurately predicting DNA 4mC sites in the mouse genome. The predictor Mus4mCPred firstly employed different encoding methods to extract the feature vectors of DNA sequences, then input these features generated by different encoding methods into various hybrid deep learning models for the learning and extraction of more sophisticated representations of these features, and finally fused the extracted multi-view features to serve as the final features for DNA 4mC site prediction in the mouse genome. Multi-view features enabled the more comprehensive capture of data characteristics, enhancing the feature representation of DNA sequences. The independent test results showed that the sensitivity (Sn), specificity (Sp), accuracy (Acc), and Matthews’ correlation coefficient (MCC) were 0.7688, 0.9375, 0.8531, and 0.7165, respectively. The predictor Mus4mCPred outperformed other state-of-the-art methods, achieving the accurate identification of 4mC sites in the mouse genome. Full article

Heart failure (HF) is characterized by low-grade immune-mediated inflammation due to increased Toll-like receptor (TLR) expression as response to endotoxin increase and dysregulated gut barrier permeability. We investigated TLR expression and possible gut dysbiosis in HF patients compared to a control group. We enrolled 80 Caucasian HF patients and 20 controls. Low-grade immune-mediated inflammation was evaluated by TLR expression, while gut dysbiosis by the detection of zonulin and bacterial endotoxin activity in a semi-quantitative (endotoxin activity assay [EAA]) and quantitative (limulus amebocyte lysate [LAL] test) way. Compared to controls, patients with HF showed significantly higher age and blood pressure values, worse metabolic profile and kidney function, higher inflammatory biomarkers levels, and lower levels of zonulin and endotoxin activity. When dividing failing patients in those with reduced ejection fraction (HF-rEF) and those with preserved ejection fraction (HF-pEF), HF-rEF patients showed significantly higher values of inflammatory biomarkers and TLR expression than HF-pEF patients. Gut permeability biomarkers inversely correlated with the severity of HF and positively with renal function. eGFR was retained as an independent predictor of zonulin variation in all the three groups of failing patients. Present data work to extend current knowledge about the role of gut microbiota in immune-mediated inflammation in HF. Full article

Purpose: We assessed the prognostic role of pro-inflammatory cytokines of the IL-1 superfamily in patients with pancreatic cancer. Methods: This retrospective study was performed using two independent cohorts of patients with pancreatic cancer: the International Cancer Genome Consortium (ICGC, N = 267) cohort and The Cancer Genome Atlas (TCGA, N = 178) cohort. Univariate Cox regressions were used to identify prognosis-related pro-inflammatory cytokines of the IL-1 superfamily. Cytokines associated with outcome were included in a multivariate Cox model with relevant clinicopathological variables to identify prognostic biomarkers. Results: IL-1α was the only pro-inflammatory cytokine of the IL-1 superfamily that was significantly associated with prognosis in both cohorts. In the training cohort (ICGC), the decile of patients with the lowest IL1A expression had better overall survival (HR = 1.99 [1.01–3.93], p = 0.05) and better relapse-free survival (HR = 1.85 [1.02–3.34], p = 0.04) than the group with the highest IL1A expression. The validation cohort (TCGA) confirmed these results: the decile with the lowest IL1A expression had better overall survival (HR = 3.00 [1.14–7.90], p = 0.03) and a lower risk of progression (HR = 3.11 [1.24–7.80], p = 0.01). Conclusions: IL1A is an independent prognostic marker and could be considered a potential therapeutic target in pancreatic cancer patients. Full article