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Featured Application: Synchromodal optimisation; decision support systems; dynamical transport optimisation. Intermodal freight transport (IFT) requires a large number of optimisation measures to ensure its attractiveness. This involves numerous control decisions on different time scales, making integrated optimisation with traditional methods almost unfeasible. Recently, a new trend in optimisation science has emerged: the application of Deep Learning (DL) to combinatorial problems. Neural combinatorial optimisation (NCO) enables real-time decision-making under uncertainties by considering rich context information—a crucial factor for seamless synchronisation, optimisation, and, consequently, for the competitiveness of IFT. The objective of this study is twofold. First, we systematically analyse and identify the key actors, operations, and optimisation problems in IFT and categorise them into six major classes. Second, we collect and structure the key methodological components of the NCO framework, including DL models, training algorithms, design strategies, and review the current State of the Art with a focus on NCO and hybrid DL models. Through this synthesis, we integrate the latest research efforts from three closely related fields: optimisation, transport planning, and NCO. Finally, we critically discuss and outline methodological design patterns and derive potential opportunities and obstacles for learning-based frameworks for integrated optimisation problems. Together, these efforts aim to enable a better integration of advanced DL techniques into transport logistics. We hope that this will help researchers and practitioners in related fields to expand their intuition and foster the development of intelligent decision-making systems and algorithms for tomorrow's transport systems. [ABSTRACT FROM AUTHOR]

This review focuses on the pivotal role of radiotracers in breast cancer imaging, emphasizing their importance in accurate detection, staging, and treatment monitoring. Radiotracers, labeled with radioactive isotopes, are integral to various nuclear imaging techniques, including positron emission tomography (PET) and positron emission mammography (PEM). The most widely used radiotracer in breast cancer imaging is 18F-fluorodeoxyglucose (18F-FDG), which highlights areas of increased glucose metabolism, a hallmark of many cancer cells. This allows for the identification of primary tumors and metastatic sites and the assessment of tumor response to therapy. In addition to 18F-FDG, this review will explore newer radiotracers targeting specific receptors, such as estrogen receptors or HER2, which offer more personalized imaging options. These tracers provide valuable insights into the molecular characteristics of tumors, aiding in tailored treatment strategies. By integrating radiotracers into breast cancer management, clinicians can enhance early disease detection, monitor therapeutic efficacy, and guide interventions, ultimately improving patient outcomes. Ongoing research aimed at developing more specific and sensitive tracers will also be highlighted, underscoring their potential to advance precision medicine in breast cancer care. [ABSTRACT FROM AUTHOR]

This study presents a comprehensive evaluation of catalytic ozonation as an effective strategy for indigo dye bleaching, particularly examining the performance of four carbon-based catalysts, activated carbon (AC), multi-walled carbon nanotubes (MWCNT), graphitic carbon nitride (g-C3N4), and thermally etched nanosheets (C3N4-TE). The study investigates the efficiency of catalytic ozonation in degrading Potassium indigotrisulfonate (ITS) dye within the constraints of short contact times, aiming to simulate real-world industrial wastewater treatment conditions. The results reveal that all catalysts demonstrated remarkable decolorization efficiency, with over 99% of indigo dye removed within just 120 s of mixing time. Besides, the study delves into the mechanisms underlying catalytic ozonation reactions, elucidating the intricate interactions between the catalysts, ozone, and indigo dye molecules with the processes being influenced by factors such as PZC, pKa, and pH. Furthermore, experiments were conducted to analyze the adsorption characteristics of indigo dye on the surfaces of the materials and its impact on the catalytic ozonation process. MWCNT demonstrated the highest adsorption efficiency, effectively removing 43.4% of the indigo dye color over 60 s. Although the efficiency achieved with C3N4-TE was 21.4%, which is approximately half of that achieved with MWCNT and less than half of that with AC, it is noteworthy given the significantly lower surface area of C3N4-TE. [ABSTRACT FROM AUTHOR]

Simple Summary: Resistance to standard therapies represents a major challenge in melanoma treatment. This is mainly related to the high heterogeneity of this malignancy due to the presence of different types of cells in the tumor mass. Cancer stem cells (CSCs) are a small subset of cells endowed with self-renewal and tumorigenic capacity and the ability to escape anticancer therapies. Melanoma CSCs can be identified by the expression of biomarkers and intracellular pathways deeply involved in their malignant phenotype. Dissecting the molecular mechanisms underlying CSC biological functions might pave the way for novel therapeutic approaches. Herein, we highlight the intricate bidirectional communication between melanoma CSCs and their surrounding cells in the tumor microenvironment and discuss how this interplay might impact the processes of drug resistance and tumor relapse. We also address the potential benefits of CSC-targeted strategies, in combination with conventional drugs, for improving melanoma treatment strategies. Cutaneous melanoma still represents a significant health burden worldwide, being responsible for the majority of skin cancer deaths. Key advances in therapeutic strategies have significantly improved patient outcomes; however, most patients experience drug resistance and tumor relapse. Cancer stem cells (CSCs) are a small subpopulation of cells in different tumors, including melanoma, endowed with distinctive capacities of self-renewal and differentiation into bulk tumor cells. Melanoma CSCs are characterized by the expression of specific biomarkers and intracellular pathways; moreover, they play a pivotal role in tumor onset, progression and drug resistance. In recent years, great efforts have been made to dissect the molecular mechanisms underlying the protumor activities of melanoma CSCs to provide the basis for novel CSC-targeted therapies. Herein, we highlight the intricate crosstalk between melanoma CSCs and bystander cells in the tumor microenvironment (TME), including immune cells, endothelial cells and cancer-associated fibroblasts (CAFs), and its role in melanoma progression. Specifically, we discuss the peculiar capacities of melanoma CSCs to escape the host immune surveillance, to recruit immunosuppressive cells and to educate immune cells toward an immunosuppressive and protumor phenotype. We also address currently investigated CSC-targeted strategies that could pave the way for new promising therapeutic approaches for melanoma care. [ABSTRACT FROM AUTHOR]

Sodium alginate (SA)–purple sweet potato peel extracts (PPE) from industrial waste indicator films were developed at different drying temperatures (25, 30, 35, 40, 45, 50, and 55 °C). The effects of drying temperatures on the film's structural, physical, and sensitive properties were investigated. On the structural properties, scanning electron microscopy, Fourier transform infrared spectroscopy, and X-ray diffraction indicated that compactness, intermolecular interactions, and crystallinity of indicator films were improved at a lower drying temperature. On the physical properties, with the drying temperature increasing, elongation at the break increased significantly (p < 0.05); ΔE and water-vapor permeability decreased significantly (p < 0.05); and thickness and tensile strength initially increased significantly (90.46 → 98.46, 62.99 → 95.73) and subsequently decreased significantly (98.46 → 71.93, 95.73 → 55.44) (p < 0.05), with the maximum values obtained at 30 °C. On sensitivity, the corresponding colors of the films became lighter as the drying temperature increased, and the films exhibited relatively excellent pH and NH3 sensitivity, with easily discernible color changes at lower temperatures. The results of this paper revealed that the overall film characteristics are improved at lower drying temperatures, which will provide valuable references for selecting the drying temperature for preparing indicator films as a guide for industrialized production. [ABSTRACT FROM AUTHOR]

Background: Body dissatisfaction (BD) has been consistently linked to adverse consequences on mental health and overall well-being, and is recognized as a significant contributing factor in the initiation and persistence of eating disorders (EDs). Empirical evidence has demonstrated that an elevated body mass index (BMI) and media influence and pressure about a thin ideal heighten the risk of subsequent BD. Moreover, suggestibility, a propensity to accept and act upon messages without critical evaluation, has been shown to be positively associated with greater susceptibility to the influence of sociocultural messages that endorse the thin ideal. This study aimed to assess whether suggestibility moderates the association between BMI and BD in women. Methods: A total of 117 women completed assessments using the Eating Disorder Inventory-3 (EDI-3) BD subscale and the Suggestibility Inventory, which encompasses a general suggestibility index and a subscale that evaluates susceptibility to influence by others. We conducted moderation analyses employing the PROCESS macro, with BMI as the central predictor, BD as the outcome variable, and suggestibility and its subscale as moderators. Results: The findings revealed statistically significant positive moderating interactions for both the general suggestibility index and susceptibility to influence by others. Specifically, women who exhibited high levels of suggestibility and susceptibility to influence by others demonstrated a more pronounced increase in BD as their BMI increased. Conclusions: These outcomes are in line with the sociocultural model of EDs, suggesting that greater susceptibility to external influences amplifies the impact of societal pressures to conform to thin ideals. [ABSTRACT FROM AUTHOR]

Background: Perinatal hypoxia may result in coagulation dysfunction. Diminished blood flow or oxygen to the fetus/neonate during the perinatal period can cause bone marrow and liver function impairment, leading to thrombocytopenia, impaired synthesis of clotting and fibrinolytic factors, and increased destruction of platelets in the small blood vessels. The goal of the present study was to evaluate the hemostatic status of newborns with perinatal hypoxia via the non-activated thromboelastometry (NATEM) assay in cord blood samples. Methods: 134 hypoxic neonates born in our maternity unit over a 1.5-year period were enrolled in this observational cohort study, and 189 healthy neonates served as the control group. Participation in the study was voluntary and parents signed informed consent prior to recruitment. Demographic and clinical data were recorded on admission, and the NATEM method was performed on cord blood samples. The following NATEM values were evaluated: clotting time (CT), alpha angle (α-angle), clot formation time (CFT), clot amplitude at 5 and 10 min. (A5, A10), maximum clot firmness (MCF), clot lysis index at 60 min. after CT (LI60), and maximum clot elasticity (MCE). Statistical analysis was conducted utilizing the SAS for Windows 9.4 software platform. Results: Neonates with perinatal hypoxia exhibited decreased fibrinolytic potential in comparison to healthy neonates, as indicated by increased LI60, and this difference was statistically significant (LΙ60: 94 (92–96) Vs 93 (91–95), p value = 0.0001). There were no statistically significant differences noted among the remaining NATEM variables. Conclusion: Our findings indicate decreased fibrinolytic potential in hypoxic neonates in comparison to healthy neonates, suggesting that NATEM could serve as an effective tool for promptly identifying hemostasis dysfunction in this group of neonates. [ABSTRACT FROM AUTHOR]

While comprehensive knowledge networks can be instrumental in finding solutions to complex problems or supporting the development of detailed simulation models, their large number of nodes and edges can become a hindrance. When the representation of a network becomes opaque, they stop fulfilling their role as a shared representation of a system between participants and modelers; hence, participants are less engaged in the model-building process. Combating the information overload created by large conceptual models is not merely a matter of changing formats: shifting from an unwieldy diagram to enormous amounts of text does not promote engagement. Rather, we posit that participants need an environment that provides details on demand and where interactions with a model rely primarily on a familiar format (i.e., text). In this study, we developed a visual analytics environment where linked visualizations allow participants to interact with large conceptual models, as shown in a case study with hundreds of nodes and almost a thousand relationships. Our environment leverages several advances in generative AI to automatically transform (i) a conceptual model into detailed paragraphs, (ii) detailed text into an executive summary of a model, (iii) prompts about the model into a safe version that avoids sensitive topics, and (iv) a description of the model into a complementary illustration. By releasing our work open source along with a video of our case study, we encourage other modelers to use this approach with their participants. Their feedback and future usability studies are key to respond to the needs of participants by improving our environment given individual preferences, models, and application domains. [ABSTRACT FROM AUTHOR]

This case study explores the potential of integrating attentional bias modification training (ABMT) with mirror exposure therapy (MET), utilizing virtual reality and eye-tracking, for a 14-year-old girl diagnosed with anorexia nervosa (AN). The ABMT-MET intervention was used alongside a standard treatment program called Home Treatment (HoT), which combines cognitive behavioral therapy with family-based therapy. Though the patient began HoT with a 3-week inpatient phase, the ABMT-MET intervention specifically took place during the subsequent Home Treatment sessions. The experimental treatment, comprising five consecutive weekly sessions, was bookended by pre- and post-assessment sessions and included a six-month follow-up. During the sessions, the patient engaged in systematic and hierarchical exposure to a virtual representation of her silhouette, with gradual adjustments made to the avatar's body mass index (BMI) toward a healthier range. ABMT sessions, conducted before each MET session, aimed to redistribute the patient's focus evenly across her body, successfully neutralizing her initial attentional bias toward non-weight-related body parts. The patient demonstrated consistent decreases in anxiety and fear of weight gain, effectively progressing through the BMI hierarchy in the virtual setting. Post-treatment assessments indicated significant enhancements in body dissatisfaction, drive for thinness, body-checking behaviors, and body appreciation, with these gains preserved at the six-month follow-up, although the attentional bias returned to pre-treatment levels. Though the single-case design limits definitive conclusions, these findings suggest ABMT-MET may be a promising adjunct therapy for AN, requiring further research for confirmation. [ABSTRACT FROM AUTHOR]

Hypothyroidism is a frequently diagnosed endocrine disorder. Common signs and symptoms include fatigue, cold intolerance, hoarseness, dry skin, constipation, a slow relaxation phase of deep tendon reflexes, and bradycardia. However, some patients may exhibit atypical signs and symptoms, which can result in diagnostic confusion. Pituitary hyperplasia resulting from longstanding primary hypothyroidism was first described by Niepce in 1851. It is usually asymptomatic, but sometimes, in addition to symptoms of overt hypothyroidism, patients may complain of headaches, hypopituitarism, visual field impairment, and hyperprolactinemia. Furthermore, on imaging, pituitary hyperplasia can be mistaken for a pituitary adenoma. Distinguishing between the two is crucial, as their management differs; the former often responds to thyroid hormone replacement therapy, while the latter might need treatment with surgery and/or radiotherapy. Here we describe a patient who developed pituitary hyperplasia in the setting of longstanding uncompensated primary hypothyroidism due to a lack of compliance with levothyroxine replacement therapy. We also review the clinical, laboratory, and radiologic findings of the case reports available in the literature up to now in order to improve the knowledge and the care of the disease. [ABSTRACT FROM AUTHOR]

Why do customers incorporate concerns about social and environmental issues into the decision-making process? How ethical are food choices in the modern world? Answers to these questions have often revolved around how informed consumers might be and whether they have the appropriate skills to act on concerns they might have. Today, ethical food consumption is a growing market where consumers' behavior shifts from the rational manner focusing on the products price and attributes to the food ethics associated with environment, social welfare, public health, and morality. Using data selected from a purposive sample of 20 consumers, this study employed a qualitative research procedure to explore the main dimensions that influence the decision-making process and eating preferences in the post-COVID 19 era and within an economically turbulent environment. The main results showed that health protection, sustainability, and social wefare constitute the main axes of ethical food consumption. Participants were found to be more individualists than altruists since the "personal health" dimension was the most prevalent. Future research should extend these findings and explore variations in the ethical consumption factors among various consumer segments. [ABSTRACT FROM AUTHOR]

Caffeine (1,3,7-trimethylxanthine) is a widely consumed bioactive substance worldwide. Our recent study showed that a reduction in both reproduction and yolk protein production (vitellogenesis) caused by caffeine intake were improved by vitamin B12 supplementation, which is an essential co-factor in methionine metabolism. In the current study, we investigated the role of methionine in the reproduction of caffeine-ingested animals (CIAs). We assessed the effect of methionine metabolism on CIAs and found that caffeine intake decreased both methionine levels and essential enzymes related to the methionine cycle. Furthermore, we found that the caffeine-induced impairment of methionine metabolism decreased vitellogenesis and increased germ cell apoptosis in an LIN-35/RB-dependent manner. Interestingly, the increased germ cell apoptosis was restored to normal levels by methionine supplementation in CIAs. These results indicate that methionine supplementation plays a beneficial role in germ cell health and offspring development by regulating vitellogenesis. [ABSTRACT FROM AUTHOR]

The ability to efficiently separate CO2 from other light gases using membrane technology has received a great deal of attention due to its importance in applications such as improving the efficiency of natural gas and reducing greenhouse gas emissions. A wide range of materials has been employed for the fabrication of membranes. This paper highlights the work carried out to develop novel advanced membranes with improved separation performance. We integrated a polymerizable and amino acid ionic liquid (AAIL) with zeolite to fabricate mixed matrix membranes (MMMs). The MMMs were prepared with (vinylbenzyl)trimethylammonium chloride [VBTMA][Cl] and (vinylbenzyl)trimethylammonium glycine [VBTMA][Gly] as the polymeric support with 5 wt% zeolite particles, and varying concentrations of 1-butyl-3-methylimidazolium glycine, [BMIM][Gly] (5–20 wt%) blended together. The membranes were fabricated through photopolymerization. The extent of polymerization was confirmed using FTIR. FESEM confirmed the membranes formed are dense in structure. The thermal properties of the membranes were measured using TGA and DSC. CO2 and CH4 permeation was studied at room temperature and with a feed side pressure of 2 bar. [VBTMA][Gly]-based membranes recorded higher CO2 permeability and CO2/CH4 selectivity compared to [VBTMA][Cl]-based membranes due to the facilitated transport of CO2. The best performing membrane Gly-Gly-20 recorded permeance of 4.17 GPU and ideal selectivity of 5.49. [ABSTRACT FROM AUTHOR]

Modeling and simulation of complex systems frequently requires capturing probabilistic dynamics across multiple scales and/or multiple domains. Cyber–physical, cyber–social, socio–technical, and cyber–physical–social systems are common examples. Modeling and simulating such systems via a single, all-encompassing model is often infeasible, and thus composable modeling techniques are sought. Co-simulation and closure modeling are two prevalent composable modeling techniques that divide a multi-scale/multi-domain system into sub-systems, use smaller component models to capture each sub-system, and coordinate data transfer between component models. While the two techniques have similar goals, differences in their methods lead to differences in the complexity and computational efficiency of a simulation model built using one technique or the other. This paper presents a probabilistic analysis of the complexity and computational efficiency of these two composable modeling techniques for multi-scale/multi-domain complex system modeling and simulation applications. The aim is twofold: to promote awareness of these two composable modeling approaches and to facilitate complex system model design by identifying circumstances that are amenable to either approach. [ABSTRACT FROM AUTHOR]

Paratemporal methods based on tree expansion have proven to be effective in efficiently generating the trajectories of stochastic systems. However, combinatorial explosion of branching arising from multiple choice points presents a major hurdle that must be overcome to implement such techniques. In this paper, we tackle this scalability problem by developing a systems theory-based framework covering both conventional and proposed tree expansion algorithms for speeding up discrete event system stochastic simulations while preserving the desired accuracy. An example is discussed to illustrate the tree expansion framework in which a discrete event system specification (DEVS) Markov stochastic model takes the form of a tree isomorphic to a free monoid over the branching alphabet. We derive the computation times for baseline, non-merging, and merging tree expansion algorithms to compute the distribution of output values at any given depth. The results show the remarkable reduction from exponential to polynomial dependence on depth effectuated by node merging. We relate these results to the similarly reduced computation time of binomial coefficients underlying Pascal's triangle. Finally, we discuss the application of tree expansion to estimating temporal distributions in stochastic simulations involving serial and parallel compositions with potential real-world use cases. [ABSTRACT FROM AUTHOR]

Industry 4.0 enables the modernisation of machines and opens up the digitalisation of processes in the manufacturing industry. As a result, these machines are ready for predictive maintenance as part of Industry 4.0 services. The benefit of predictive maintenance is that it can significantly extend the life of machines. The integration of predictive maintenance into existing production environments faces challenges in terms of data understanding and data preparation for machines and legacy systems. Current AI frameworks lack adequate support for the ongoing task of data integration. In this context, adequate support means that the data analyst does not need to know the technical background of the pilot's data sources in terms of data formats and schemas. It should be possible to perform data analyses without knowing the characteristics of the pilot's specific data sources. The aim is to achieve a seamless integration of data as information for predictive maintenance. For this purpose, the developed data-sharing infrastructure enables automatic data acquisition and data integration for AI frameworks using interoperability methods. The evaluation, based on two pilot projects, shows that the step of data understanding and data preparation for predictive maintenance is simplified and that the solution is applicable for new pilot projects. [ABSTRACT FROM AUTHOR]

With the booming development of door-to-door housekeeping service, the platform faces the problem of order assignment. Improving the matching mechanism between orders and housekeepers based on a dynamic programming (DP) algorithm can not only achieve flexible order allocation but can also improve the service efficiency and service quality. In this paper, a single objective nonlinear programming model is established, which takes the maximum total weight value as the objective function to study the order allocation problem under offline and online conditions. Under the offline condition, the number of housekeepers is taken as the decision variable. The status of order and housekeeper, order time, and action trajectory are taken as constraints. For online assignment, the order backlog status is treated as the decision variable. The reliability of the model was verified using real data from 20 groups of housekeepers and 50 groups of orders. Finally, the effect of order backlog on online allocation is discussed and the optimal threshold and maximum weight are found. The online order assignment model is compared with the nearest distance assignment model. The results show that the online assignment model with a total weighted score of 1045.14 is better than the nearest distance assignment model with a score of 810.25. [ABSTRACT FROM AUTHOR]

Diagnosis of primary hyperparathyroidism (PHP) is based on blood assessments in terms of synchronous high calcium and PTH (parathormone), but further management, particularly parathyroid surgery that provides the disease cure in 95–99% of cases, requires an adequate localisation of the parathyroid tumour/tumours as the originating source, with ultrasound and 99m-Technetium (99m-Tc) sestamibi scintigraphy being the most widely used. We aimed to introduce an adult female case diagnosed with PHP displaying unexpected intra-operatory findings (ectopic thyroid tissue) in relation to concordant pre-operatory imaging modalities (ultrasound + dual-phase 99m-Tc pertechnetate and sestamibi scintigraphy + computed tomography) that indicated bilateral inferior parathyroid tumours. A sudden drop in PTH following the removal of the first tumour was the clue for performing an extemporaneous exam for the second mass that turned out to be non-malignant ectopic thyroid tissue. We overviewed some major aspects starting from this case in point: the potential pitfalls of pre-operatory imaging in PHP; the concordance/discordance of pre-parathyroidectomy localisation modalities; the need of using an additional intra-operatory procedure; and the clues of providing a distinction between pathological parathyroids and thyroid tissue. This was a case of adult PHP, whereas triple localisation methods were used before parathyroidectomy, showing concordant results; however, the second parathyroid adenoma was a false positive image and an ectopic thyroid tissue was confirmed. The pre-operatory index of suspicion was non-existent in this patient. Hybrid imaging modalities are most probably required if both thyroid and parathyroid anomalies are suspected, but, essentially, awareness of the potential pitfalls is mandatory from the endocrine and surgical perspectives. Current gaps in imaging knowledge to guide us in this area are expected to be solved by the significant progress in functional imaging modalities. However, the act of surgery, including the decision of a PTH assay or extemporaneous exam (as seen in our case), represents the key to a successful removal procedure. Moreover, many parathyroid surgeons may currently perform 4-gland exploration routinely, precisely to avoid the shortcomings of preoperative localisation. [ABSTRACT FROM AUTHOR]

This research provides a comprehensive analysis of the dynamic interplay between agent-based modeling (ABM) and artificial intelligence (AI) through a meticulous bibliometric study. This study reveals a substantial increase in scholarly interest, particularly post-2006, peaking in 2021 and 2022, indicating a contemporary surge in research on the synergy between AI and ABM. Temporal trends and fluctuations prompt questions about influencing factors, potentially linked to technological advancements or shifts in research focus. The sustained increase in citations per document per year underscores the field's impact, with the 2021 peak suggesting cumulative influence. Reference Publication Year Spectroscopy (RPYS) reveals historical patterns, and the recent decline prompts exploration into shifts in research focus. Lotka's law is reflected in the author's contributions, supported by Pareto analysis. Journal diversity signals extensive exploration of AI applications in ABM. Identifying impactful journals and clustering them per Bradford's Law provides insights for researchers. Global scientific production dominance and regional collaboration maps emphasize the worldwide landscape. Despite acknowledging limitations, such as citation lag and interdisciplinary challenges, our study offers a global perspective with implications for future research and as a resource in the evolving AI and ABM landscape. [ABSTRACT FROM AUTHOR]

A series of robust energetic polyurethane binders was developed by in situ grafting reactive spiranes to achieve the migration-resistant processing aid and compensate for the energy output. The reactive grafting spiranes (RGSs), bearing two highly ring-strained spiranes, were synthesized sequentially to provide a promising ring strain energy up to a maximum value of 290 kJ mol−1. The thermodynamic compatibility of the RGS with uncured glycidyl azido polymer (GAP) was studied quantitatively by analyzing the glass transition temperature of their blendings. The reactivity study of the catalyst-free click reaction with respect to spacer-dependent species was amplified by tracing the extent of the reaction and measuring the activation energy. The faster reactivity of propargyl species was evident from two experimental approaches, which were verified further by theoretical predictions. Interestingly, the energy gap difference in the frontier molecular orbitals agreed well with the difference in activation energy between the two types of spacer-dependent species. The mechanical and thermochemical enhancements of GAP-based polyurethane with RGS were basically gained from those highly ring-strained moieties. [ABSTRACT FROM AUTHOR]

Background: Transportation demand forecasting is an essential activity for logistics operators and carriers. It leverages business operation decisions, infrastructure, management, and resource planning activities. Since 2015, there has been an increase in the use of deep learning models in this domain. However, there is a gap in works comparing traditional statistics and deep learning models for transportation demand forecasts. This work aimed to perform a case study of aggregated transportation demand forecasts in 54 distribution centers of a Brazilian carrier. Methods: A computational simulation and case study methods were applied, exploring the characteristics of the datasets through autoregressive integrated moving average (ARIMA) and its variations, in addition to a deep neural network, long short-term memory, known as LSTM. Eight scenarios were explored while considering different data preprocessing methods and evaluating how outliers, training and testing dataset splits during cross-validation, and the relevant hyperparameters of each model can affect the demand forecast. Results: The long short-term memory networks were observed to outperform the statistical methods in ninety-four percent of the dispatching units over the evaluated scenarios, while the autoregressive integrated moving average modeled the remaining five percent. Conclusions: This work found that forecasting transportation demands can address practical issues in supply chains, specially resource planning management. [ABSTRACT FROM AUTHOR]

Dye-containing effluent generated in textile industries is polluting and complex wastewater. It should be managed adequately before its final destination. The up-flow anaerobic blanket (UASB) reactor application is an ecofriendly and cost-competitive treatment. The present study briefly reviews the UASB application for dye-containing wastewater valorization. Bioenergy and clean-water production potential during dye-containing wastewater treatment are emphasized to promote resource recovery in textile industries. Hydraulic retention time (HRT), organic loading rate (OLR), pH, temperature, and hydraulic mixing influence sludge granulation, microbial activity, and dye removal. HRT and OLR ranges of 6–24 h and 1–12 kg m−3 d−1 of chemical oxygen demand (COD) at a mesophilic temperature (30–40 °C) are recommended for efficient treatment. In these conditions, efficiencies of color and COD of 50–97% and 60–90% are reported in bench-scale UASB studies. Complex dye structures can hinder biomineralization. Pretreatment may be necessary to reduce dye concentration. Carbon-source and redox mediators are added to the UASB reactor to expedite kinetic reactions. A biogas yield of 1.48–2.70 L d−1 in UASB, which treats dye-containing effluents, is documented. Cotreatment of dye wastewater and locally available substrate could increase biogas productivity in UASB reactors. Organic waste generated in the textile industry, such as dye sludge, cotton, and starch, is recommended to make cotreatment cost competitive. Bioenergy production and water reuse allow environmental and economic benefits. Studies on combined systems integrating UASB and membrane processes, such as ultrafiltration and nanofiltration, for the production of reusable water and pretreatment of wastewater and sludge for improvements in biogas production might realize the complete potential for resource recovery of UASB technology. UASB bioenergy usage for integrated treatment trains can reduce operating costs and assist process sustainability in the textile industry. [ABSTRACT FROM AUTHOR]

There is an increasing awareness about body image disturbance and eating disorders which calls for a multidisciplinary approach. The usefulness of new technologies for improving body image distortion has been addressed in the scientific literature, but has not included current strategies such as Metaverse-related technologies. Seemingly, this is the first systematic review which focuses on the efficacy of Metaverse-related technologies in reducing body image disturbance related to eating disorders like Anorexia nervosa and Bulimia nervosa. The main objective of this study was to review the scientific studies published in the last decade to answer the following three questions: (1) Are Metaverse-related technologies useful in mitigating body image disturbance in patients diagnosed with Anorexia nervosa and Bulimia nervosa? (2) What are the advantages and disadvantages? (3) Are the patients satisfied after using this kind of technology? The results obtained were that 80% of the included studies found metaverse-related technologies useful for the improvement in body image disturbance, in addition to various advantages, such as a decrease in eating disorder symptomatology. Whereas patient satisfaction was only evaluated in 20% of the included studies, with the majority of patients evaluating the use of metaverse-related technologies positively. We will conduct a systematic review of the peer-reviewed literature from EBSCO Discovery Service, and Web of Science (WOS), following the PRISMA statements. Only Journal articles published from 2013 to the present, written in the English language, will be reviewed. The findings are expected to offer valuable insights for the development of novel approaches for the improvement in body image disturbance in healthcare settings. [ABSTRACT FROM AUTHOR]

The use of ionic liquid [emim][Tf2N] as an additive in polyethersulphone (PES) and nano-sized silico-aluminophosphate-34 (SAPO-34) mixed matrix membrane was studied through the incorporation of different amounts of [emim][Tf2N] in the membrane composition, as presented in this work, varying from 10 to 40 wt%. Through gas permeation tests using CO2 and N2, the membrane composition containing 20 wt% [emim][Tf2N] led to the highest increase in CO2 permeability and CO2/N2 selectivity. The use of low concentrations of additive (10–20 wt%) promoted a state called antiplasticization; in this state, the permeability was even more regulated by the kinetic diameter of the species which, in this work, permitted achieving a higher CO2/N2 selectivity while increasing the CO2 permeability until an optimal condition. [emim][Tf2N] also promoted a better dispersion of SAPO-34 particles and an increase in the flexibility of the polymeric matrix when compared to a film with the same composition without [emim][Tf2N]. Moreover, the characterizations corroborated that the inclusion of [emim][Tf2N] increased the zeolite dispersion and improved the polymer/zeolite compatibility and membrane flexibility, characterized by a decrease in glass transition temperature, which helped in the fabrication process while presenting a similar thermal resistance and hydrophilicity as neat PES membrane, without affecting the membrane structure, as indicated by FTIR and a contact angle analysis. [ABSTRACT FROM AUTHOR]

A new fast, sensitive, and environmentally friendly analytical method has been developed for the simultaneous determination of Ba, Be, Cd, Cr, Cu, Fe, Hg, Mn, Ni, Pb, and Zn in wastewater samples using inductively coupled plasma optical emission spectroscopy (ICP OES). A preconcentration step using a magnetic dispersive solid-phase extraction (MDSPE) technique with a new magnetic sorbent was performed. The new sorbent material was a carbon containing magnetic cobalt and nitrogen groups. This material was synthetized using controlled pyrolysis of a zeolitic imidazolate framework (i.e., ZIF-67). In order to optimize the experimental parameters that affect the MDSPE procedure, a multivariate optimization strategy, using Plackett–Burman and circumscribed central composite designs (CCD), was used. The method has been evaluated employing optimized experimental conditions (i.e., sample weight, 10 g; sample pH, 7.6; amount of sorbent, 10 mg; dispersive agent, vortex; complexing agent concentration, 0.5%; ionic concentration, 0%; eluent, HCl; eluent concentration, 0.5 M; eluent volume, 300 μL; elution time, 3 min and extraction time, 3 min) using external calibration. Limits of detection (LODs) in a range from 0.073 to 1.3 μg L−1 were obtained, and the repeatability was evaluated at two different levels, resulting in relative standard deviations below 8% for both levels (n = 5). An increase in the sensitivity was observed due to the high enrichment factors (i.e., 3.2 to 13) obtained compared with direct ICP OES analysis. The method was also validated through carrying out recovery studies that employed a real wastewater sample and through the analysis of a certified reference material (ERM®-CA713). The recovery values obtained with the real wastewater were between 94 and 108% and between 90 and 109% for the analysis of ERM®-CA713, showing negligible matrix effects. [ABSTRACT FROM AUTHOR]

Online food delivery services today are considered an essential service that gets significant attention worldwide. Many companies and individuals are involved in this field as it offers good income and numerous jobs to the community. In this research, we consider the problem of online food delivery services and how we can increase the number of received orders by couriers and thereby increase their income. Multi-agent reinforcement learning (MARL) is employed to guide the couriers to areas with high demand for food delivery requests. A map of the city is divided into small grids, and each grid represents a small area of the city that has different demand for online food delivery orders. The MARL agent trains and learns which grid has the highest demand and then selects it. Thus, couriers can get more food delivery orders and thereby increase long-term income. While increasing the number of received orders is important, protecting customer location is also essential. Therefore, the Protect User Location Method (PULM) is proposed in this research in order to protect customer location information. The PULM injects differential privacy (DP) Laplace noise based on two parameters: city area size and customer frequency of online food delivery orders. We use two datasets—Shenzhen, China, and Iowa, USA—to demonstrate the results of our experiments. The results show an increase in the number of received orders in the Shenzhen and Iowa City datasets. We also show the similarity and data utility of courier trajectories after we use our obfuscation (PULM) method. [ABSTRACT FROM AUTHOR]

Porous TiO2-doped polyaniline and polyaniline nanocomposite fibers prepared by the in situ polymerization technique using anionic surfactant in an ice bath were studied. The prepared nanocomposites were characterized by FTIR spectroscopy and XRD patterns for structural analysis. The surface morphology of the polyaniline and its nanocomposites was examined using SEM images. DC conductivity shows the three levels of conductivity inherent in a semiconductor. Among the nanocomposites, the maximum DC conductivity is 5.6 S/cm for 3 wt.% polyaniline-TiO2 nanocomposite. Cyclic voltammetry shows the properties of PANI due to the redox peaks of 0.93 V and 0.24 V. Both peaks are due to the redox transition of PANI from the semiconductor to the conductive state. The hydrogen absorption capacity is approximately 4.5 wt.%, but at 60 °C the capacity doubles to approximately 7.3 wt.%. Conversely, 3 wt.% PANI—TiO2 nanocomposites have a high absorption capacity of 10.4 wt.% compared to other nanocomposites. An overall desorption capacity of 10.4 wt.% reduced to 96% was found for 3 wt.% TiO2-doped PANI nanocomposites. [ABSTRACT FROM AUTHOR]

This article presents a comprehensive review of the existing literature on the topic of data assimilation for agent-based models, with a specific emphasis on pedestrians and passengers within the context of transportation systems. This work highlights a plethora of advanced techniques that may have not been previously employed for online pedestrian simulation, and may therefore offer significant value to readers in this domain. Notably, these methods often necessitate a sophisticated understanding of mathematical principles such as linear algebra, probability theory, singular value decomposition, optimization, machine learning, and compressed sensing. Despite this complexity, this article strives to provide a nuanced explanation of these mathematical underpinnings. It is important to acknowledge that the subject matter under study is still in its nascent stages, and as such, it is highly probable that new techniques will emerge in the coming years. One potential avenue for future exploration involves the integration of machine learning with Agent-based Data Assimilation (ABDA, i.e., data assimilation methods used for agent-based models) methods. [ABSTRACT FROM AUTHOR]

Managing the logistics and safety of an election system, from delivering voting machines to the right locations at the right time to ensuring that voting lines remain reasonable in length is a complex problem due to the scarcity of resources, especially human poll workers, and the impact of human behavior and disrupting events on the performance of this critical system. These complexities grew with the need for physical distancing during the COVID-19 pandemic coinciding with multiple key national elections, including the 2020 general presidential election in the USA. In this paper, we propose a digital clone platform leveraging agent-based simulation to model and experiment with resource allocation decisions and voter turnout fluctuations and facilitate "what-if" scenario testing of any election. As a use case, we consider three different concurrent polling location problems, namely, resource allocation, polling layout, and management. The main aim is to reduce voter waiting time and provide visibility of different scenarios for polling and state-level managers. We explain the proposed simulation platform based on Fulton County for the 2020 presidential US election. Fulton County had 238 polling locations in 2020, which provided publicly available voter turnout data. The developed platform realistically models at the county level and at specific locations, suggesting the possible allocation of finite resources among locations in the county and the configuration of each location, accounting for physical, legal, and technical constraints. Multiple realistic scenarios were developed and embedded into the simulation platform to evaluate and verify the different systems. The system performance and key attributes of the election system, such as waiting time, resource utilization, and layout safety, were tested and validated. [ABSTRACT FROM AUTHOR]

Anorexia nervosa (AN) patients exhibit attentional bias (AB) related to the body, which is the tendency to pay greater attention to weight-related body areas compared to non-weight-related ones. This phenomenon has been linked to elevated levels of body dissatisfaction (BD) and may potentially reduce the effectiveness of body exposure therapy. The purpose of this pilot study is to assess the efficacy of a single session of a new body-related AB modification task (ABMT) that combines virtual reality with eye tracking in patients with AN. The goals of the ABMT are to reduce body-related AB by balancing attention between weight and non-weight-related body areas and to reduce BD levels. Twenty-three adolescent patients with AN were embodied in a virtual avatar and immersed in a virtual environment where they completed the ABMT. Body-related AB measures and BD levels were assessed before and after the training. A paired samples t-test showed statistically significant differences between pre-assessment and post-assessment; the complete fixation time on weight-related body parts was reduced and BD levels decreased. The initial evidence of the efficacy of this ABMT has important clinical implications, since AB and BD are considered risk factors for developing and maintaining eating disorder symptomatology among patients with AN. [ABSTRACT FROM AUTHOR]

Previous research has shown an association between body dissatisfaction and attentional biases toward the body, but the nature of this relationship is not clear. It is possible that dissatisfaction causes attentional bias or that dissatisfaction is a result of such bias. To clarify the causal relationship between these two variables, this study manipulated dissatisfaction in a sample of healthy women by exposing them to images of "ideal" bodies and observed whether this manipulation increased attentional biases toward different body parts. Fifty-seven women took part in a pre–post experimental design in which they observed an avatar representing themselves in a virtual mirror before and after being exposed to "thin ideal" photographs. Eye-tracking technology was employed to quantify the frequency and duration of fixations on weight-related and weight-unrelated body parts. The outcomes revealed a successful induction of body dissatisfaction, leading participants to display a heightened number of fixations and prolonged fixation durations on unrelated-weight body parts. These findings remained significant after controlling for the effects of trait body dissatisfaction and body mass index. The results imply that heightened body dissatisfaction fosters the aversion of attention from weight-related body parts, which may function as a protective mechanism for preserving self-esteem and promoting psychological well-being. [ABSTRACT FROM AUTHOR]

Xylooligosaccharides (XOS) are nondigestible compounds of great interest for food and pharmaceutical industries due to their beneficial prebiotic, antibacterial, antioxidant, and antitumor properties. The market size of XOS is increasing significantly, which makes its production from lignocellulosic biomass an interesting approach to the valorization of the hemicellulose fraction of biomass, which is currently underused. This review comprehensively discusses XOS production from lignocellulosic biomass, aiming at its application in integrated biorefineries. A bibliometric analysis is carried out highlighting the main players in the field. XOS production yields after different biomass pretreatment methods are critically discussed using Microsoft PowerBI® (2.92.706.0) software, which involves screening important trends for decision-making. Enzymatic hydrolysis and the major XOS purification strategies are also explored. Finally, the integration of XOS production into biorefineries, with special attention to economic and environmental aspects, is assessed, providing important information for the implementation of biorefineries containing XOS in their portfolio. [ABSTRACT FROM AUTHOR]

The aim of this article is to compare rocket propellants containing a traditional binder (hydroxyl-terminated polybutadiene) and an energetic binder (glycidyl azide polymer), as well as a perchlorate oxidising agent and a "green" one, i.e., ammonium perchlorate and phase-stabilised ammonium nitrate. We have outlined the effects of individual substances on the sensitivity parameters and decomposition temperature of the produced solid propellants. The linear combustion velocity was determined using electrical methods. Heats of combustion for the propellant samples and the thermal decomposition features of the utilised binders were investigated via differential scanning calorimetry (DSC). Activation energy values for the energetic decomposition of the propellants were determined via the Kissinger method, based on DSC measurements at varied heating rates. [ABSTRACT FROM AUTHOR]

An increasing number of high-performing gas separation membranes is reported almost on a daily basis, yet only a few of them have reached commercialisation while the rest are still considered pure research outcomes. This is often attributable to a rapid change in the performance of these separation systems over a relatively short time. A common approach to address this issue is the development of mixed matrix membranes (MMMs). These hybrid systems typically utilise either crystalline or amorphous additives, so-called fillers, which are incorporated into polymeric membranes at different loadings, with the aim to improve and stabilise the final gas separation performance. After a general introduction to the most relevant models to describe the transport properties in MMMs, this review intends to investigate and discuss the main advantages and disadvantages derived from the inclusion of fillers of different morphologies. Particular emphasis will be given to the study of the compatibility at the interface between the filler and the matrix created by the two different classes of additives, the inorganic and crystalline fillers vs. their organic and amorphous counterparts. It will conclude with a brief summary of the main findings. [ABSTRACT FROM AUTHOR]

Zeolites were modified by high-temperature roasting and chitosan loading, respectively. As a result, activated zeolite and chitosan-loading natural zeolite were obtained. They were used for the treatment of the micro-polluted irrigation water quality simulated by a low concentration (100 μg/L) of Cd(II) contamination. The static adsorption experiments showed that two types of modified zeolites were cost-effective and had high removal efficiency for low concentrations of Cd(II). The removal rates were 95.8% and 92.06%, respectively. The static adsorption experiments investigated the effects of modified zeolite dosage, pH, initial concentration of the solution, and adsorption time on the removal efficiency of cadmium ions. The dynamic adsorption experiments discussed the influence of factors such as dynamic adsorption medium type, influent filtration rate, and adsorbent amount on adsorption efficiency in the adsorption column. The dynamic adsorption experiments adopted intermittent operation to simulate the characteristics of micro-polluted irrigation water. The optimal operating conditions were determined as follows: single activated zeolite filter column or mixed medium (activated zeolite: chitosan loading natural zeolite = 4:1), filtration rate of 6 m/h, filter column height of 500 mm, adsorbent dosage of 30 g. The removal rate was more than 99.5%. The adsorption experiments were represented by Langmuir and Freundlich isotherm models. The adsorption results indicated that the adsorption of modified zeolite showed a better correlation with the Langmuir isotherm model than the Freundlich isotherm model. The adsorption process was described by pseudo-first-order and pseudo-second-order kinetic models, with the pseudo-second-order kinetic model being the predominant mechanism. The average concentration of Cd(II) in the effluent after filtration was 0.41 μg/L, which was far lower than the 0.01 mg/L stipulated in the standard for irrigation water quality (GB5084-2021), and met the requirements of the irrigation water quality standard. Activated zeolite and chitosan-loaded natural zeolite are good adsorbent materials that have broad application prospects in the treatment of micro-polluted irrigation water containing low concentrations of Cd(II). [ABSTRACT FROM AUTHOR]

Background: Digital twins have the potential to significantly improve the efficiency and sustainability of the agri-food supply chain by providing visibility, reducing bottlenecks, planning for contingencies, and improving existing processes and resources. Additionally, they can add value to businesses by lowering costs and boosting customer satisfaction. This study is aimed at responding to common scientific questions on the application of digital twins in the agri-food supply chain, focusing on the benefits, types, integration levels, key elements, implementation steps, and challenges. Methods: This article conducts a systematic literature review of recent works on agri-food supply chain digital twins, using a list of peer-reviewed studies to analyze concepts using precise and well-defined criteria. Thus, 50 papers were selected based on inclusion and exclusion criteria, and descriptive and content-wise analysis was conducted to answer the research questions. Conclusions: The implementation of digital twins has shown promising advancements in addressing global challenges in the agri-food supply chain. Despite encouraging signs of progress in the sector, the real-world application of this solution is still in its early stages. This article intends to provide firms, experts, and researchers with insights into future research directions, implications, and challenges on the topic. [ABSTRACT FROM AUTHOR]

Human papillomavirus (HPV) vaccination protects against six types of cancer—cervical, anal, oropharyngeal, penile, vulvar, and vaginal. In the United States (U.S.), HPV vaccination coverage in college students remains low, especially in the Mid-South region, despite the highest risk of HPV infections and disease burden. However, few studies have assessed HPV vaccination among college students here. This study examined factors associated with HPV vaccination among college students in the Mid-South and explored preferred strategies for promoting vaccination. A mixed-methods design comprising a cross-sectional, self-report online survey and dyadic virtual interviews was conducted. Simple random sampling was performed to recruit a total of 417 undergraduate students aged 18–26 from March to May 2021; convenience sampling was performed to recruit three sex-matched dyads of a total of six (four female and two male) undergraduates from survey respondents who had not completed the HPV vaccine series in May 2021. Binary logistic regression analyses showed HPV vaccine knowledge and perceived barriers to vaccination were factors contributing to coverage for both female and male students, while perceived risks of HPV and vaccine hesitancy were factors only among female students. Findings from the qualitative content analysis identified college students' perceived barriers to the vaccination at multiple levels and preferred strategies for vaccination promotion, corroborating the findings from the survey study. The findings provide implications that benefit the development of tailored interventions aimed at facilitating catch-up vaccination among college students in the Mid-South region. There is an urgent need for further research and the implementation of effective strategies that address the identified barriers and improve HPV vaccine uptake in this population. [ABSTRACT FROM AUTHOR]

Agent-based computing remains an active field of research with the goal of building (semi-)autonomous software for dynamic ecosystems. Today, this task should be realized using dedicated, specialized frameworks. Over almost 40 years, multiple agent platforms have been developed. While many of them have been "abandoned", others remain active, and new ones are constantly being released. This contribution presents a historical perspective on the domain and an up-to-date review of the existing agent platforms. It aims to serve as a reference point for anyone interested in developing agent systems. Therefore, the main characteristics of the included agent platforms are summarized, and selected links to projects where they have been used are provided. Furthermore, the described platforms are divided into general-purpose platforms and those targeting specific application domains. The focus of the contribution is on platforms that can be judged as being under active development. Information about "historical platforms" and platforms with an unclear status is included in a dedicated website accompanying this work. [ABSTRACT FROM AUTHOR]

Cognitive biases have a significant impact on the etiology and treatment of eating disorders (EDs). These biases, including selective attentional bias (AB) to disliked body parts, may reinforce concerns about body shape, fear of gaining weight and body image disturbances and may contribute to dietary restriction and restraint. Decreasing AB could reduce core symptoms in anorexia nervosa (AN). This study represents a preliminary exploration aiming to assess whether AB towards weight-related (WR) and non-weight-related (NW) body parts could be reduced through an AB modification task in a virtual reality (VR) environment in healthy participants. A total of 54 female participants, aged 22.98 ± 1.89, were recruited. The task consisted of directing the participants' attention towards all body parts equally in a VR setting. Eye-tracking (ET) measurements (complete fixation time [CFT] and number of fixations [NF]) were made before and after the task. The results showed a significant reduction of the AB in the two groups with an initial AB towards WR body parts or towards NW body parts. Participants showed a tendency to more balanced (non-biased) attention after the intervention. This study provides evidence of the usefulness of AB modification tasks in a non-clinical sample. [ABSTRACT FROM AUTHOR]

Heavy metal pollution can adversely impact marine life, such as crabs, which can accumulate it in different organs and potentially transfer and biomagnify along the food chain in aquatic ecosystems. This study aimed to examine the concentrations of heavy metals (Cd, Cu, Pb, and Zn) in sediment, water, and crab tissues (gills, hepatopancreas, and carapace) of the blue swimmer crab Portunus pelagicus in the coastal areas of Kuwait, northwestern Arabian Gulf. Samples were collected from Shuwaikh Port, Shuaiba Port, and Al-Khiran areas. The accumulation of metals in crabs were higher in the carapace > gill > digestive gland, and the highest metal concentration was found in crabs collected from Shuwaikh > Shuaiba > Al-Khiran. The metal concentrations in the sediments were in the order Zn > Cu > Pb > Cd. Zn was the highest metal concentration detected in marine water sampled from the Al-Khiran Area, whereas the lowest metal was Cd sampled in water from the Shuwaikh Area. The results of this study validate the marine crab P. pelagicus as a relevant sentinel and prospective bioindicator for evaluating heavy metal pollution in marine ecosystems. [ABSTRACT FROM AUTHOR]

Exposure therapy is known to be an effective intervention in the treatment of anxiety-related disorders. In eating disorders, such as anorexia nervosa, anxiety and avoidance are identified as maintenance factors. Therefore, they may constitute an important treatment target, suitable for the use of exposure therapy. Remarkably, exposure techniques to target fears and avoidance behaviors are not commonly used in the treatment of anorexia nervosa. We present a practical guide for the implementation of exposure therapy in the treatment of anorexia nervosa. We outline how exposure therapy is supposed to work according to the inhibitory learning model and how the exposure intervention can be designed for individuals with anorexia nervosa. Practical examples are provided through the case presentation of a patient with anorexia nervosa who completed 31 exposure sessions that focused on her fears of food, eating, weight, weight gain, their feared social consequences and the associated safety behaviors. [ABSTRACT FROM AUTHOR]

The analyses of the influence of spatial harmonics on the electromagnetic torque of the multi-phase induction machine and reducing this influence are important tasks to ensure the high efficiency of the induction machine. Designing the machine to consider the influence of spatial harmonics is essential to ensure the desired mechanical and energy characteristics. In the case of the sinusoidal winding supply of the induction machine, the magnetomotive force has high spatial harmonics, which are caused by the machine-winding design. The interaction between the 5th, 7th, 11th and 13th spatial harmonics of the winding function and the first time-harmonic of the winding supply causes the appearance of the 6th and 12th harmonics in the electromagnetic torque of the machine. A prototype of the symmetrical six-phase induction machine and the experimental study for the influence of spatial harmonics on the harmonic content of the stator currents in different machine modes are given in this paper. The mathematical model of the six-phase induction machine has been developed using the average voltages in integration step method. The introduction of the harmonic components into the magnetization inductance in the mathematical model of the six-phase induction machine for taking into account the spatial harmonics of the machine-winding function is proposed in this paper. The adequacy of the mathematical model was confirmed by comparing the simulation and experimental results. The harmonic content of the electromagnetic torque, which is caused by spatial harmonic influence, is analyzed. [ABSTRACT FROM AUTHOR]

Textile waste usually ends up in landfills and causes environmental pollution. In this study, pretreatment methods for textile recycling, including autoclaving, freezing alkali/urea soaking, and alkaline pretreatment, were applied to textile waste with various cotton/polyester blending ratios. The best condition for enzymatic hydrolysis was a 60/40 textile waste blend of cotton/polyethylene terephthalate (PET) with a reusable chemical pretreatment (15% NaOH) at 121 °C for 15 min. The hydrolysis of pretreated textile waste by cellulase was optimized using response surface methodology (RSM) based on central composite design (CCD). The optimized conditions were 30 FPU/g of enzyme loading and 7% of substrate loading, which resulted in a maximum observed value of hydrolysis yield at 89.7%, corresponding to the predicted value of 87.8% after 96 h of incubation. The findings of this study suggest an optimistic solution for textile waste recycling. [ABSTRACT FROM AUTHOR]

Batik is a piece of woven cloth decorated with beautiful patterns and designs and has become a signature product of the Malay Archipelago, including Malaysia and Indonesia. Batik industry consumes a large volume of water and produces a large amount of wastewater during the boiling process and dyeing process, both for hand-drawn (batik lukis) and block-printed (batik cap) batik. The release of colored effluents that contain a large number of dyes and chemicals can harm the environment and become a human health concern, particularly in south east Asian countries. Therefore, treatments of batik effluent are very crucial and have caught a lot of attention from researchers. The color removal is a major challenge, especially from this industry, as up until now there is no single and cost-effective treatment that can effectively decolorize as well as treat the dye effluent. Since batik is part of the textile industry, most treatment methods have been adapted from textile effluent treatment. Here, we review a variety of textile wastewater treatment techniques to make a good consideration of selecting the most appropriate method to be applied in batik wastewater. First, we briefly review the batik process, including the potential dyes that are mostly used in batik processing. Secondly, we describe all possible techniques and their performance to reduce dye concentration and decolorization. Finally, we review all advantages and disadvantages of these techniques for domestic and industrial applications. [ABSTRACT FROM AUTHOR]

A circular economy is imperative for environmental sustainability. In this context, biorefineries stand out as a means of production able to reduce the carbon footprint and the impact of global warming. Biorefineries may employ lignocellulosic biomass from various plant sources to produce bioproducts with the potential to replace fossil derivatives through synthesis by microorganisms without competing with food crops. Brewer's spent grain (BSG), the residue of the brewery production process, is an option with potential for use, being a cheap raw material highly available throughout the year. The chemical composition of this biomass is quite variable, with significant amounts of hemicellulose, mainly consisting of xylose and arabinose monomers that can be technologically converted into value-added products such as xylooligosaccharides, xylitol, second-generation ethanol (2G ethanol), biofilms and furfural. To this end, catalysts are unusual in making biorefineries increasingly competitive in the market, selectively optimizing reactions and reducing the environmental impact of the production processes of these bioproducts. The present review addresses the primary methods for extracting and processing hemicelluloses from BSG using either biocatalysts (enzymes) or homogenous (acids, alkali, and salts) and heterogenous catalysts (solid acids and metal oxide) that can be used to pretreat the biomass and obtain the preferred byproducts. The state of the art of optimized catalysis mechanisms is also presented. [ABSTRACT FROM AUTHOR]

To lay the foundation for environmentally friendly energetic polymer composites, GAP (glycidyl azide polymer) adhesive-based polymer films with different curing parameter R (mol ratio of hydroxyl/isocyanate) and energetic polymer composites with different RDX contents were studied. GAP/TDI (toluene diisocyanate)/GLY(glycerol) was selected as the adhesive system. The tensile strength and elongation at the break of the polymer film with R = 2.2, was 14.34 MPa and 176.86%, respectively, as observed by an AGS-J electronic universal testing machine. A relatively complete cross-linking network and high hydrogen bonding interaction were observed by LF-NMR (low-field nuclear magnetic resonance, where the cross-linking density was 11.06 × 10−4 mol/cm3) and FT-IR (fourier transform infrared spectroscopy, where the carbonyl bonding ratio was 64.84%). Forty percent RDX(hexogen) was added into the adhesive system. The tensile strength was 4.65 MPa, and the elongation at the break was 78.49%; meanwhile, the heat of the explosive was 2.87 MJ/kg, and the residue carbon rate was only 2.47%. The tensile cross-sections of energetic polymer composites were observed by SEM (Scanning electron microscopy). [ABSTRACT FROM AUTHOR]

Mirror exposure therapies (METs) have been shown to be effective in reducing body image disturbances through the habituation process. Virtual reality (VR) combined with eye-tracking techniques can provide innovative solutions to some of METs' limitations reported with patients with anorexia nervosa (AN), especially the negative influence of body-related attentional bias (AB). This pilot study aimed to assess the preliminary efficacy of a new VR-based AB modification task (ABMT) among healthy women and the procedure's user experience. AB levels towards weight- and non-weight-related body parts, using complete fixation time (CFT) and number of fixations (NF), were assessed throughout the ABMT procedure (300 trials). The user experience was evaluated at the end of the procedure. The results showed that VR-based ABMT was effective in reducing AB significantly after 150 trials for both CFT- and NF-based measures, although 225 trials were necessary to get the same result for women with an NF initially more oriented towards weight-related body parts. Overall, the software received a "C-rating" on a scale from "A" (most usable) to "F" (least usable). These results provide evidence of the opportunity to use a VR-based ABMT procedure to reduce AB and improve existing treatments for AN. [ABSTRACT FROM AUTHOR]

Artificial intelligence (AI) is a field of computer science that deals with the simulation of human intelligence using machines so that such machines gain problem-solving and decision-making capabilities similar to that of the human brain. Neuroscience is the scientific study of the struczture and cognitive functions of the brain. Neuroscience and AI are mutually interrelated. These two fields help each other in their advancements. The theory of neuroscience has brought many distinct improvisations into the AI field. The biological neural network has led to the realization of complex deep neural network architectures that are used to develop versatile applications, such as text processing, speech recognition, object detection, etc. Additionally, neuroscience helps to validate the existing AI-based models. Reinforcement learning in humans and animals has inspired computer scientists to develop algorithms for reinforcement learning in artificial systems, which enables those systems to learn complex strategies without explicit instruction. Such learning helps in building complex applications, like robot-based surgery, autonomous vehicles, gaming applications, etc. In turn, with its ability to intelligently analyze complex data and extract hidden patterns, AI fits as a perfect choice for analyzing neuroscience data that are very complex. Large-scale AI-based simulations help neuroscientists test their hypotheses. Through an interface with the brain, an AI-based system can extract the brain signals and commands that are generated according to the signals. These commands are fed into devices, such as a robotic arm, which helps in the movement of paralyzed muscles or other human parts. AI has several use cases in analyzing neuroimaging data and reducing the workload of radiologists. The study of neuroscience helps in the early detection and diagnosis of neurological disorders. In the same way, AI can effectively be applied to the prediction and detection of neurological disorders. Thus, in this paper, a scoping review has been carried out on the mutual relationship between AI and neuroscience, emphasizing the convergence between AI and neuroscience in order to detect and predict various neurological disorders. [ABSTRACT FROM AUTHOR]

As the main component of agricultural and forestry biomass, hemicellulose has the advantages of having an abundant source, biodegradability, nontoxicity and good biocompatibility. Its application in food packaging has thus become the focus of efficient utilization of biomass resources. However, due to its special molecular structure and physical and chemical characteristics, the mechanical properties and barrier properties of hemicellulose films are not sufficient, and modification for performance enhancement is still a challenge. In the field of food packaging materials preparation, modification of hemicellulose through blending with nanofibers or nanoparticles, both inorganic and organic, has attracted research attention because this approach offers the advantages of efficient improvement in the expected properties and better cost efficiency. In this paper, the composition of hemicellulose, the classification of nanofillers and the research status of hemicellulose-based nanocomposite films are reviewed. The research progress in modification of hemicellulose by using layered silicate, inorganic nanoparticles and organic nanoparticles in food packaging is described. Challenges and outlook of research in hemicellulose-based nanocomposite film in food packaging is discussed. [ABSTRACT FROM AUTHOR]