This retrospective study examines 248 test bolus examinations preceding contrast-enhanced magnetic resonance angiography (CE-MRA) to extract clinically relevant data for critical limb ischemia (CLI) management. The method involved a retrospective review of test bolus exams, analysing 60 graphs for time to peak (TTP), full-width half-maximum (FWHM) time, and time to continual rise in signal intensity. These values were correlated with heart function parameters (ejection fraction, ASA classification, Lee index, and MET score). The results indicate a mean TTP of 31.2 ± 7.3 s, showing a correlation between the ejection fraction and ASA classification. Patients with atrial fibrillation exhibited prolonged TTP compared to those without. Despite population heterogeneity, these findings facilitate risk stratification for limb-saving interventions in CLI. TTP emerges as a potential clinical cardiovascular parameter and a risk factor for vascular interventions. Given the variation in injection protocols across centres, this study underscores the importance of precise bolus arrival time documentation for future multicentre studies. Full article

The detrimental impact of toxic chemicals, gas, and oil spills in aquatic environments poses a severe threat to plants, animals, and human life. Regions such as Cancer Alley exemplify the profound consequences of inadequately controlled chemical spills, significantly affecting the local community. Given the far-reaching effects of these spills, it has become imperative to devise an efficient method for early monitoring, estimation, and cleanup, utilizing affordable and effective techniques. In this research, we explore the application of U-shaped neural Network (UNET) and U-shaped neural network transformer (UNETR) neural network models designed for the image segmentation of chemical and oil spills. Our models undergo training using the Commonwealth Scientific and Industrial Research Organization (CSIRO) dataset and the Oil Spill Detection dataset, employing a specialized filtering technique to enhance detection accuracy. We achieved training accuracies of 95.35% and 91% by applying UNET on the Oil Spill and the CSIRO datasets after 50 epochs of training, respectively. We also achieved a training accuracy of 75% by applying UNETR to the Oil Spill dataset. Additionally, we integrated mixed precision to expedite the model training process, thus maximizing data throughput. To further accelerate our implementation, we propose the utilization of the Field Programmable Gate Array (FPGA) architecture. The results obtained from our study demonstrate improvements in inference latency on FPGA. Full article

This study redefines the evaluation of urban traffic dominance by integrating complex network theory with multi-source spatiotemporal trajectory data, addressing the dynamic nature of various transportation modes, including public transit and shared mobility. Traditional traffic studies, which focus predominantly on static road traffic characteristics, overlook the fluid dynamics integral to urban transport systems. We introduce Relative Weighted Centrality (RWC) as a novel metric for quantifying dynamic traffic dominance, combining it with traditional static metrics to forge a comprehensive traffic dominance evaluation system. The results show the following: (1) Both static and dynamic traffic dominance display core-periphery structures centered around Huangpu District. (2) Dynamically, distinct variations in RWC emerge across different times and transport modes; during the early hours (0:00–6:00), shared bicycles show unique spatial distributions, the subway network experiences a notable decrease in RWC yet maintains its spatial pattern, and taxis exhibit intermediate characteristics. Conversely, the RWC for all modes generally increases during morning (6:00–12:00) and evening (18:00–24:00) peaks, with a pronounced decrease in subway RWC in the latter period. (3) The integration of dynamic evaluations significantly modifies conventional static results, emphasizing the impact of population movements on traffic dominance. This comprehensive analysis provides crucial insights into the strategic management and development of urban traffic infrastructure in Shanghai. Full article

Spacetime wormholes are evidently an essential component of the construction of a time machine. Within the context of general relativity, such objects require, for their formation, exotic matter—matter that violates at least one of the standard energy conditions. Here, we explore the possibility that higher-curvature gravity theories might permit the construction of a wormhole without any matter at all. In particular, we consider the simplest form of a generalized quasi topological theory in four spacetime dimensions, known as Einsteinian Cubic Gravity. This theory has a number of promising features that make it an interesting phenomenological competitor to general relativity, including having non-hairy generalizations of the Schwarzschild black hole and linearized equations of second order around maximally symmetric backgrounds. By matching series solutions near the horizon and at large distances, we find evidence that strong asymptotically AdS wormhole solutions can be constructed, with strong curvature effects ensuring that the wormhole throat can exist. Full article

In recent years, the substantial growth in satellite data transmission tasks and volume, coupled with the limited availability of ground station hardware resources, has exacerbated conflicts among missions and rendered traditional scheduling algorithms inadequate. To address this challenge, this paper introduces an improved tabu genetic hybrid algorithm (ITGA) integrated with heuristic rules for the first time. Firstly, a constraint satisfaction model for satellite data transmission tasks is established, considering multiple factors such as task execution windows, satellite–ground visibility, and ground station capabilities. Leveraging heuristic rules, an initial population of high-fitness chromosomes is selected for iterative refinement. Secondly, the proposed hybrid algorithm iteratively evolves this population towards optimal solutions. Finally, the scheduling plan with the highest fitness value is selected as the best strategy. Comparative simulation experimental results demonstrate that, across four distinct scenarios, our algorithm achieves improvements in the average task success rate ranging from 1.5% to 19.8% compared to alternative methods. Moreover, it reduces the average algorithm execution time by 0.5 s to 28.46 s and enhances algorithm stability by 0.8% to 27.7%. This research contributes a novel approach to the efficient scheduling of satellite data transmission tasks. Full article

Oil-degrading bacteria have the ability to degrade alkanes present in crude oil because of a special enzymatic system, the alkane hydroxylase complex (AlkH). The mechanism for the transport and degradation of alkanes present in crude oil remains unclear, especially related to the first step in hydrocarbons oxidation. In this work, we present a novel model of the crude oil biodegradation mechanism by considering the contact between the oil drop and the cell and calculating the mass transfer coefficients in three oleophilic bacteria (B. licheniformis, P. putida and P. glucanolyticus). The mass transfer coefficients are evaluated under critical time conditions, when the kinetics and mass transport are in balance, and the difference in the values obtained (k_L α = 1.60 × 10⁻³, 5.25 × 10⁻⁴ and 6.19 × 10⁻⁴ m/d, respectively) shows the higher value of the mass transfer coefficient and higher biodegradation potential for B. licheniformis. Because the morphology of the cells has been analyzed by optical and electron microscopy, in the proposed model, the increase in the size of the cells in P. glucanolyticus compared to P. putida exhibits higher values of the mass transfer coefficients and this is attributed, as a novel statement, to a bigger window for alkanes transport (contact area) when the external area of the cell is bigger. Full article

To evaluate the flexural strength and flexural modulus of three recently introduced 3D-Printed resins and compare them with the flexural properties of other well known, already commercialized, and extensively used resin based dental materials. Three 3D-printed dental resins, a fiber-reinforced epoxy resin, a heat-cured bis-acrylate-based composite resin, two conventional CAD/CAM PMMA, and a graphene-reinforced CAD/CAM PMMA, were selected for this study. Ten prismatic-shaped specimens (2 × 2 × 25 mm) were fabricated for each material (n = 10). All specimens underwent a three-point bending test using a universal testing machine and were loaded until fracture. Flexural strength (MPa) and flexural modulus (MPa) mean values were calculated and compared using the on ranks One-Way ANOVA test. Scanning electron microscope analysis of the 3D-printed resins was performed. Significantly different flexural properties were recorded among the tested materials. The fiber-reinforced epoxy resin exhibited the highest flexural strength (418.0 MPa) while, among the 3D-printed resins, the best flexural strength was achieved by Irix-Max (135.0 MPa). Irix-Plus and Temporis led to the lowest mean flexural strength values (103.9 MPa and 101.3 MPa, respectively) of all the CAD/CAM milled materials, except for the conventional PMMA by Sintodent (88.9 MPa). The fiber-reinforced epoxy resin also showed the highest flexural modulus (14,672.2 MPa), followed by the heat-cured bis-acrylate composite (10,010.1 MPa). All 3D-printed resins had a higher flexural modulus than the conventional PMMA materials. CAD/CAM fiber-reinforced epoxy resin excels in flexural strength, with Irix-Max showing promising flexural properties, which could encourage its use for permanent restorations. Caution is needed with Irix-Plus and Temporis due to their lower flexural strength compared to other traditional materials. Full article

Medical Visual Question Answering (Med-VQA) faces significant limitations in application development due to sparse and challenging data acquisition. Existing approaches focus on multi-modal learning to equip models with medical image inference and natural language understanding, but this worsens data scarcity in Med-VQA, hindering clinical application and advancement. This paper proposes the ITLTA framework for Med-VQA, designed based on field requirements. ITLTA combines multi-label learning of medical images with the language understanding and reasoning capabilities of large language models (LLMs) to achieve zero-shot learning, meeting natural language module needs without end-to-end training. This approach reduces deployment costs and training data requirements, allowing LLMs to function as flexible, plug-and-play modules. To enhance multi-label classification accuracy, the framework uses external medical image data for pretraining, integrated with a joint feature and label attention mechanism. This configuration ensures robust performance and applicability, even with limited data. Additionally, the framework clarifies the decision-making process for visual labels and question prompts, enhancing the interpretability of Med-VQA. Validated on the VQA-Med 2019 dataset, our method demonstrates superior effectiveness compared to existing methods, confirming its outstanding performance for enhanced clinical applications. Full article

The potentials of ABO replacer of ENZ and DFM on growth performance, AID, colonic VFAs, gut morphology, fecal score and diarrhea incidence were evaluated. We randomly assigned 120 piglets to four experimental diets that included: (1) control diet (CON), fed the basal ration; (2) ABO was added at 250 ppm of in-feed ABO; (3) ENZ was added at a rate of 3 kg/ton feed; (4) DFM was added with 50 × 10⁶ cfu/g of Bacillus subtilis and 2 × 10⁶ cfu/g of Lactobacillus spp. at a rate of 1.2 kg/ton feed. A complete randomized design used six pens per treatment with five pigs per pen. Pigs had ad libitum access to feed and water throughout the 6-week trial. Feed intake and BW were recorded on weeks 0, 2, 4 and 6, as well as fecal scores and diarrhea incidences (visually recorded and calculated). At weeks 2 and 4, a sub-sample of pigs (n = 6) was sacrificed for intestinal morphology, enzyme activity and VFAs. The results of the study demonstrated that DFM piglets showed increased final BW (3 kg) (p < 0.001) vs. CON. Likewise, ADG was positively affected by the incorporation of ABO, ENZ and DFM in the diets, with an average increase of 8 to 17% on ADG compared with CON (p < 0.001). The AID of gross energy, organic matter, CP and EAAs in piglets fed ENZ and DFM were significantly higher (p < 0.05) than those of CON and ABO at weeks 2 and 4. Inclusion of DFM increased intestinal morphology, enzymatic activities and propionic and butyric acid more than in pigs fed CON, ABO and ENZ (p < 0.05). The fecal score and diarrhea incidence generally decreased over time in pigs fed DFM (p < 0.05). These findings indicate that dietary supplementation with DFM has better effects at any period on growth performance, CP and AA digestibility and beneficially altered the intestinal health in weanling piglets. Full article

With the implementation of the International Maritime Organization’s (IMO) sulfur cap 2020, shipowners have had to choose suitable sulfur oxide emission abatement solutions to respond to this policy. The use of Very Low Sulfur Fuel Oil (VLSFO) and the installation of scrubbers are the main response solutions for bulk carriers today. In recent years, the epidemic has gradually improved, and the options facing shipowners may change. Based on the Clarkson Shipping Intelligence Network, this paper collects data related to newbuilding bulk carriers after the implementation of this policy, considers several factors affecting shipowners’ decision, and adopts a machine learning approach for the first time to build a model and make predictions on emission abatement solutions to provide some reference for shipowners to choose a more suitable solution. The results of the study show that the Extreme Gradient Boosting (XGBoost) model is more suitable for the problem studied in this paper, and the highest prediction accuracy of about 84.25% with an Area Under the Curve (AUC) value of 0.9019 is achieved using this model with hyperparameter adjustment based on a stratified sampling divided data set. The model makes good predictions for newbuilding bulk carriers. In addition, the deadweight tonnage and annual distance traveled of a ship have a greater degree of influence on the choice of its option, which can be given priority in the decision making. In contrast to traditional cost–benefit analyses, this study incorporates economic and non-economic factors and uses machine learning methods for effective classification, which have the advantage of being fast, comparable, and highly accurate. Full article

It is crucial to identify the structures of active sites to understand how catalysts function and to use that understanding to develop better catalytic materials. ZSM-5 zeolites with dominant Al(IV)-2 sites have been developed in this work. ¹H-²⁷Al 2D HMQC and 2D ¹H TQ(DQ)-SQ NMR experiments have been performed to investigate the structural properties of this acidic site. The Al(IV)-2 sites have Brønsted and Lewis acid characteristics. The catalytic performance of Al(IV)-2 sites has been tested by n-dodecane cracking reactions. The catalytic results show that the Brønsted acidic strength of the Al(IV)-2 sites is comparable to that of the Al(IV)-1 sites, but the Al(IV)-2 sites’ Lewis acid characteristics provide extra catalytic activity. We have gained valuable insights into the characteristics of Al(IV)-2 acid sites within these materials. Full article

Polyhydroxyalkanoates (PHA) have received attention owing to their biodegradability and biocompatibility, with studies exploring PHA-producing bacterial strains. As vegetable oil provides carbon and monomer precursors for poly(3-hydroxybutyrate-co-3-hydroxyhexanoate) (P(3HB-co-3HHx)), oil-utilizing strains may facilitate PHA production. Herein, Cupriavidus necator BM3-1, which produces 11.1 g/L of PHB with 5% vegetable oil, was selected among various novel Cupriavidus necator strains. This strain exhibited higher preference for vegetable oils over sugars, with soybean oil and tryptone determined to be optimal sources for PHA production. BM3-1 produced 33.9 g/L of exopolysaccharides (EPS), which was three-fold higher than the amount produced by H16 (10.1 g/L). EPS exhibited 59.7% of emulsification activity (EI24), higher than that of SDS and of EPS from H16 with soybean oil. To evaluate P(3HB-co-3HHx) production from soybean oil, BM3-1 was engineered with P(3HB-co-3HHx) biosynthetic genes (phaC_Ra, phaA_Re, and phaJ_Pa). BM3-1/pPhaCJ produced 3.5 mol% of 3HHx and 37.1 g/L PHA. BM3-1/pCB81 (phaCAJ) produced 32.8 g/L PHA, including 5.9 mol% 3HHx. Physical and thermal analyses revealed that P(3HB-co-5.9 mol% 3HHx) was better than PHB. Collectively, we identified a novel strain with high vegetable oil utilization capacity for the production of EPS, with the option to engineer the strain for P(3HB-co-3HHx). Full article

This study introduces a new internal diaphragm joint to connect steel beams with wall-type concrete-filled steel tubular (WCFST) columns. This study combines experimental research with numerical simulations for analysis. Firstly, one full-scale test specimen was designed and subjected to cyclic loading. The obtained failure mode and hysteresis curves illustrate that the joint specimens exhibit ample energy dissipation capacities. Subsequently, a reliable FE model was obtained based on experimental verification, and parametric analysis was conducted. The findings indicate that axial compression ratios critically affect the load-carrying capacity and displacement at failure, with a 2% reduction in capacity for each 0.1 increment in the ratio. The thicknesses of the column web and flange in the joint area are recommended to be 0.85 to 1.2 times and 1 to 1.2 times the beam flange thickness, respectively. The length of the internal diaphragm is advised to be between 0.2 and 0.3 times the width of the cross-section. Overall, these results significantly enrich our understanding of WCFST systems and will inform future design and construction best practices. Full article

In this paper, we use a semi-discretization method to consider the predator–prey model of Leslie type with ratio-dependent simplified Holling type IV functional response. First, we discuss the existence and stability of the positive fixed point in total parameter space. Subsequently, through using the central manifold theorem and bifurcation theory, we obtain sufficient conditions for the flip bifurcation and Neimark–Sacker bifurcation of this system to occur. Finally, the numerical simulations illustrate the existence of Neimark–Sacker bifurcation and obtain some new dynamical phenomena of the system—the existence of a limit cycle. Corresponding biological meanings are also formulated. Full article

This paper explores a historical innovation created by Henry Muncaster: a stationary steam engine featuring a single-cylinder horizontal design with a crosshead trunk guide. Through the application of engineering graphics techniques, we have elucidated the functioning of this invention by developing a 3D CAD model based on the original drawings published in Model Engineer magazine in 1957. However, the geometric modeling process faced challenges due to missing and erroneous dimensions for several components. Consequently, dimensional, geometric, and movement constraints were applied to ensure the coherence and functionality of the 3D CAD model, alongside conducting an interference analysis. Ultimately, the proper alignment of the cylinder and crosshead was ascertained, which is crucial for maintaining uniform forces and motions within the steam engine. This alignment is pivotal for achieving balanced operation, minimizing vibrations, and enhancing the overall efficiency of the invention. Full article

Culinary aromatic herbs (CAHs), used worldwide for culinary and industrial purposes, are recognized for their wide range of beneficial health effects including antimicrobial, antioxidant, anti-hyperlipidemic, anti-inflammatory, anti-type 2 diabetes mellitus, antitumorigenic and anticarcinogenic, and anti-hypertensive properties, in addition to glucose- and cholesterol-lowering activities as well as properties that affect mental health and cognition via their phytochemical constituents, such as polyphenols (flavonoids and non-flavonoids), sulfur- and nitrogen-containing compounds, alkaloids, minerals, and vitamins. Moreover, the volatile organic metabolites (VOMs) found in CAHs offer unique analytical biosignatures linked to their sensory qualities and organoleptic characteristics. This study aimed to establish the volatilomic pattern of CAHs commonly used in Europe and in the Mediterranean region, oregano (Origanum vulgare L.) and two savory species: savory (Satureja hortensis L.) and lemon savory (Satureja montana L. var. citriodora). The volatilomic pattern of CAHs was established using headspace solid-phase microextraction (HS-SPME) followed by gas chromatography–mass spectrometry (GC-MS) determination. This is a powerful strategy to unravel the potential health benefits related to the most important VOMs identified in each aromatic herb. This comprehensive understanding will aid in establishing the authenticity of these herbs, while also safeguarding against possible fraudulent activities and adulterations. A total of 112 VOMs from different chemical families were identified. Terpenoids amounted to the major chemical family in the investigated aromatic herbs accounting for 96.0, 95.1, and 79.7% of the total volatile composition for savory, lemon savory, and oregano, respectively. Apart from contributing to flavor profiles, certain identified VOMs also possess bioactive properties, opening interesting avenues for potential application in the food, pharmaceutical, and cosmetic sectors. The volatilomic pattern combined with unsupervised principal component analysis facilitated the differentiation of the aromatic herbs under investigation, revealing the most related VOMs in each sample, which can be used as markers for the authentication of these valuable aromatic herbs, such as caryophyllene oxide (103), camphene (6), p-cymene (23), and borneol (74), among others. In addition, some VOMs have a high influence on the aromatic herb’s bioactive potential, helping to prevent certain diseases including cancer, inflammatory-related diseases, diabetes, and cardiovascular diseases. Full article

The current article reports the investigation of three new Ni(II) complexes with ONS-donor dithiocarbazate ligands: [Ni(L¹)PPh₃] (1), [Ni(L²)PPh₃] (2), and [Ni(L²)Py] (3). Single-crystal X-ray analyses revealed mononuclear complexes with a distorted square planar geometry and the metal centers coordinated with a doubly deprotonated dithiocarbazate ligand and coligand pyridine or triphenylphosphine. The non-covalent interactions were investigated by the Hirshfeld surface and the results revealed that the strongest interactions were π⋅⋅⋅π stacking interactions and non-classical hydrogen bonds C–H···H and C–H···N. Physicochemical and spectroscopic methods indicate the same structures in the solid state and solution. The toxicity effects of the free ligands and Ni(II) complexes were tested on the human breast cancer cell line MCF-7 and non-malignant breast epithelial cell line MCF-10A. The half-maximal inhibitory concentration (IC₅₀) values, indicating that the compounds were potent in inhibiting cell growth, were obtained for both cell lines at three distinct time points. While inhibitory effects were evident in both malignant and non-malignant cells, all three complexes demonstrated lower IC₅₀ values for malignant breast cell lines than their non-malignant counterparts, suggesting a stronger impact on cancerous cell lines. Furthermore, molecular docking studies were performed showing the complex (2) as a promising candidate for further therapeutic exploration. Full article

Chitin and chitosan, abundant biopolymers derived from the shells of crustaceans and the cell walls of fungi, have garnered considerable attention in pharmaceutical circles due to their biocompatibility, biodegradability, and versatile properties. Deep eutectic solvents (DESs), emerging green solvents composed of eutectic mixtures of hydrogen bond acceptors and donors, offer promising avenues for enhancing the solubility and functionality of chitin and chitosan in pharmaceutical formulations. This review delves into the potential of utilizing DESs as solvents for chitin and chitosan, highlighting their efficiency in dissolving these polymers, which facilitates the production of novel drug delivery systems, wound dressings, tissue engineering scaffolds, and antimicrobial agents. The distinctive physicochemical properties of DESs, including low toxicity, low volatility, and adaptable solvation power, enable the customization of chitin and chitosan-based materials to meet specific pharmaceutical requirements. Moreover, the environmentally friendly nature of DESs aligns with the growing demand for sustainable and eco-friendly processes in pharmaceutical manufacturing. This revision underscores recent advances illustrating the promising role of DESs in evolving the pharmaceutical applications of chitin and chitosan, laying the groundwork for the development of innovative drug delivery systems and biomedical materials with enhanced efficacy and safety profiles. Full article

The consequences of COVID-19 constitute a significant burden to healthcare systems worldwide. Conducting an HRQoL assessment is an important aspect of the evaluation of the impact of the disease. The aim of this study was to investigate the prevalence of persistent symptoms and their impact on HRQoL and health status in COVID-19 convalescents. The study group consists of 46 patients who required hospitalization due to respiratory failure and who were subsequently evaluated 3 and 9 months after hospital discharge. At the follow-up visits, the patients were asked to assess their HRQoL using the EQ-5D-5L questionnaire. The results of chest CT, 6MWT, as well as the severity of the course of COVID-19 were also considered in the analysis. The obtained results have identified fatigue as the most common persistent symptom. The majority of the convalescents reported an impairment of HRQoL in at least one domain (80% and 82% after 3 and 9 months, respectively), of which the most common was that of pain/discomfort. The presence of ongoing symptoms may affect HRQoL in particular domains. The 6MWT outcome correlates with HRQoL 3 months after hospital discharge. Therefore, it may be useful in identifying patients with reduced HRQoL, allowing early interventions aimed at its improvement. Full article

Neurodegenerative disorders are affecting millions of people worldwide, impacting the healthcare system of our society. Among them, Alzheimer’s disease (AD) is the most common form of dementia, characterized by severe cognitive impairments. Neuropathological hallmarks of AD are β-amyloid (Aβ) plaques and neurofibrillary tangles, as well as endoplasmic reticulum and mitochondria dysfunctions, which finally lead to apoptosis and neuronal loss. Since, to date, there is no definitive cure, new therapeutic and prevention strategies are of crucial importance. In this scenario, cannabinoids are deeply investigated as promising neuroprotective compounds for AD. In this study, we evaluated the potential neuroprotective role of cannabinerol (CBNR) in an in vitro cellular model of AD via next-generation sequencing. We observed that CBNR pretreatment counteracts the Aβ-induced loss of cell viability of differentiated SH-SY5Y cells. Moreover, a network-based transcriptomic analysis revealed that CBNR restores normal mitochondrial and endoplasmic reticulum functions in the AD model. Specifically, the most important genes regulated by CBNR are related mainly to oxidative phosphorylation (COX6B1, OXA1L, MT-CO2, MT-CO3), protein folding (HSPA5) and degradation (CUL3, FBXW7, UBE2D1), and glucose (G6PC3) and lipid (HSD17B7, ERG28, SCD) metabolism. Therefore, these results suggest that CBNR could be a new neuroprotective agent helpful in the prevention of AD dysfunctions. Full article

Spirulina platensis (SP) has gained popularity over the last few years, owing to its remarkable nutritional properties and high potential across various industrial sectors. In this study, we analyzed the volatile profile of eight SP samples from the same strain subjected to different drying (oven-drying, air-drying, and spray-drying) and storing conditions (“freshly prepared” and after 12 months of storage) using HS-SPME-GC-MS. Principal component analysis (PCA) was used as a multivariate technique to discern similarities and differences among the samples. The main aim was to assess the impact of the drying technique on the aroma profile and storage life of SP samples. Air-drying leads to the less pronounced formation of by-products related to heat treatment, such as Maillard and Strecker degradation compounds, but promotes oxidative and fermentative phenomena, with the formation of organic acids and esters, especially during storage. Thermal treatment, essential for limiting degradation and fermentation during storage and extending shelf life, alters the aroma profile through the formation of volatile compounds, such as Strecker aldehydes and linear aldehydes, from amino acid and lipid degradation. High temperatures in spray-drying favor the formation of pyrazines. The findings underscore the trade-offs inherent in choosing an appropriate drying method, thereby informing decision-making processes in industrial settings aimed at optimizing both product quality and efficiency. Full article

As autonomous driving technology advances, the imperative of ensuring pedestrian traffic safety becomes increasingly prominent within the design framework of autonomous driving systems. Pedestrian trajectory prediction stands out as a pivotal technology aiming to address this challenge by striving to precisely forecast pedestrians’ future trajectories, thereby enabling autonomous driving systems to execute timely and accurate decisions. However, the prevailing state-of-the-art models often rely on intricate structures and a substantial number of parameters, posing challenges in meeting the imperative demand for lightweight models within autonomous driving systems. To address these challenges, we introduce Social Spatio-Temporal Graph Multi-Layer Perceptron (Social-STGMLP), a novel approach that utilizes solely fully connected layers and layer normalization. Social-STGMLP operates by abstracting pedestrian trajectories into a spatio-temporal graph, facilitating the modeling of both the spatial social interaction among pedestrians and the temporal motion tendency inherent to pedestrians themselves. Our evaluation of Social-STGMLP reveals its superiority over the reference method, as evidenced by experimental results indicating reductions of 5% in average displacement error (ADE) and 17% in final displacement error (FDE). Full article