With the rapid development of China’s civil aviation, the flow of air traffic in terminal areas is also increasing. Short-term air traffic flow prediction is of great significance for the accurate implementation of air traffic flow management. To enhance the accuracy of short-term air traffic flow prediction, this paper proposes a short-term air traffic flow prediction model based on complementary ensemble empirical mode decomposition (CEEMD) and long short-term memory (LSTM) of the Bayesian optimization algorithm and data differential processing. Initially, the model performs CEEMD on the short-term air traffic flow series. Subsequently, to improve prediction accuracy, the data differencing is employed to stabilize the time series. Finally, the smoothed sequences are, respectively, input into the LSTM network model optimized by the Bayesian optimization algorithm for prediction. After data reconstruction, the final short-term flow prediction result is obtained. The model proposed in this paper is verified by using the data from Shanghai Pudong International Airport. The results show that the evaluation indexes of the prediction accuracy and fitting degree of the model, RMSE (Root Mean Square Error), MAE (Mean Absolute Error), and R² (Coefficient of Determination), are 0.336, 0.239, and 97.535%, respectively. Compared to other classical time-series prediction models, the prediction accuracy is greatly improved, which can provide a useful reference for short-term air traffic flow prediction. Full article

(1) Background: This challenge is exacerbated by the aging of the rural population, leading to a scarcity of available manpower. To address this issue, the automation and mechanization of outdoor vegetable cultivation are imperative. Therefore, developing an automated cultivation platform that reduces labor requirements and improves yield by efficiently performing all the cultivation activities related to field vegetables, particularly onions and garlic, is essential. In this study, we propose methods to identify onion and garlic plants with the best growth status and accurately predict their live bulb weight by regularly photographing their growth status using a multispectral camera mounted on a drone. (2) Methods: This study was conducted in four stages. First, two pilot blocks with a total of 16 experimental units, four horizontals, and four verticals were installed for both onions and garlic. Overall, a total of 32 experimental units were prepared for both onion and garlic. Second, multispectral image data were collected using a multispectral camera repeating a total of seven times for each area in 32 experimental units prepared for both onions and garlic. Simultaneously, growth data and live bulb weight at the corresponding points were recorded manually. Third, correlation analysis was conducted to determine the relationship between various vegetation indexes extracted from multispectral images and the manually measured growth data and live bulb weights. Fourth, based on the vegetation indexes extracted from multispectral images and previously collected growth data, a method to predict the live bulb weight of onions and garlic in real time during the cultivation period, using functional regression models and machine learning methods, was examined. (3) Results: The experimental results revealed that the Functional Concurrence Regression (FCR) model exhibited the most robust prediction performance both when using growth factors and when using vegetation indexes. Following closely, with a slight distinction, Gaussian Process Functional Data Analysis (GPFDA), Random Forest Regression (RFR), and AdaBoost demonstrated the next-best predictive power. However, a Support Vector Machine (SVM) and Deep Neural Network (DNN) displayed comparatively poorer predictive power. Notably, when employing growth factors as explanatory variables, all prediction models exhibited a slightly improved performance compared to that when using vegetation indexes. (4) Discussion: This study explores predicting onion and garlic bulb weights in real-time using multispectral imaging and machine learning, filling a gap in research where previous studies primarily focused on utilizing artificial intelligence and machine learning for productivity enhancement, disease management, and crop monitoring. (5) Conclusions: In this study, we developed an automated method to predict the growth trajectory of onion and garlic bulb weights throughout the growing season by utilizing multispectral images, growth factors, and live bulb weight data, revealing that the FCR model demonstrated the most robust predictive performance among six artificial intelligence models tested. Full article

In this paper, we propose a geometric channel model for air-to-air (A2A) unmanned aerial vehicle (UAV) communication scenarios. The model is established by incorporating line-of-sight, specular reflection, and diffuse scattering components, and it can capture the impacts of UAV vibrations induced by the propeller’s rotation. Based on UAV heights and ground scatterer density, a closed-form expression is derived to jointly capture the zenith and azimuth angular distributions of diffuse rays. The power of diffuse rays is modeled according to the grazing angle of the rays and the electrical properties and roughness of the ground materials. Key statistics, including the temporal autocorrelation function, spatial cross-correlation function, Doppler power spectrum density, and coherence time are derived, providing an in-depth understanding of the time-variant characteristics of the channel. The results indicate that the presented model is capable of capturing certain A2A channel characteristics, which align with the corresponding theoretical analysis. The findings suggest that the scattering effect of the A2A channel is significantly influenced by the altitude of the UAV. Additionally, it is shown that UAV vibrations can introduce extra Doppler frequencies, notably decreasing the temporal correlation and coherence time of the channel. This effect is more prominent when the system operates at high-frequency bands. The effectiveness of the presented model is confirmed through a comparison of its statistics with those of an existing model and with available measurement data. Full article

The present paper deals with a new two-in-one zero-dimensional (0D) organic–inorganic hybrid compound namely (C₆H₁₀N₂)₄[CdBr₆][CdBr₄]₂. This molecular crystal structure contains isolated CdBr₄ tetrahedra and CdBr₆ octahedra. The optical characterization by UV–Vis–NIR spectroscopy shows that the (C₆H₁₀N₂)₄[CdBr₆][CdBr₄]₂ exhibits a large gap energy of 4.97 eV. Under UV excitation, this hybrid material shows a bright cold white light emission (WLE) at room temperature. The photoluminescence (PL) analysis suggests that the WLE originates from the organic molecules. Density of states (DOS) analysis using the density functional theory (DFT) demonstrates that the calculated HOMO(Br)→LUMO(organic) absorption transition (4.1 eV) does not have significant intensity, while, the transition involving the valence band (VB) and the second and third conduction bands (CB) around 5 eV are allowed, which is in good agreement with the experimental gap value. The interesting theoretical result is that the LUMO(organic)→HOMO(Br) emission is allowed, which confirms the important role of the organic molecule in the emission mechanism, in good agreement with the experimental PL analysis. Full article

Clostridioides difficile infection (CDI) is an intestinal infection that causes morbidity and mortality and places significant burden and cost on the healthcare system, especially in recurrent cases. Antibiotic overuse is well recognized as the leading cause of CDI in high-risk patients, and studies have demonstrated that even short-term antibiotic exposure can cause a large and persistent disturbance to human colonic microbiota. The recovery and sustainability of the gut microbiome after dysbiosis have been associated with fewer CDI recurrences. Fecal microbiota transplantation (FMT) refers to the procedure in which human donor stool is processed and transplanted to a patient with CDI. It has been historically used in patients with pseudomembranous colitis even before the discovery of Clostridioides difficile. More recent research supports the use of FMT as part of the standard therapy of recurrent CDI. This article will be an in-depth review of five microbiome therapeutic products that are either under investigation or currently commercially available: Rebyota (fecal microbiota, live-jslm, formerly RBX2660), Vowst (fecal microbiota spores, live-brpk, formerly SER109), VE303, CP101, and RBX7455. Included in this review is a comparison of the products’ composition and dosage forms, available safety and efficacy data, and investigational status. Full article

Product design and manufacturing leverage 3D scanning for various applications. This study aims to investigate the effectiveness of 3D scanning in furniture production by surveying the literature and showcasing four real-world case studies. The literature review reveals that 3D data acquired from real-world objects have applications in research, rapid prototyping, restoration, and preservation of antique furniture, optimizing CNC machining processes, and measuring furniture components for quality control. The case study descriptions demonstrated the circumstances, rationale, and methodology for 3D scanning. All the case studies analyzed stem from the collaboration between the Laboratory for Product Development and Design at the Faculty of Mechanical Engineering at the University of Sarajevo and various furniture production enterprises from Bosnia and Herzegovina. The conclusions highlight that 3D scanning in the furniture sector is advantageous for developing computer-aided design models from early-stage design prototypes, validating the dimensional accuracy of manufactured components by comparing with CAD models, safeguarding and reconstructing vintage furniture, and remanufacturing formerly produced goods that lack complete technical records (reverse engineering). Full article

Air pollutants and greenhouse gases (GHGs) represent major challenges in our era, contributing to climate change and global health issues. These problems arise from a variety of well-known sources, including motor vehicles. Almost all nations, Thailand included, have formulated and implemented policies to curb greenhouse gas (GHG) emissions in line with the requirements and commitments of the Paris Agreement. The evaluation of specific air pollutants and GHG emissions originating from road vehicles utilises the Thailand database, referencing the year 2019. Data intersections from 2019 to 2022 are grounded in actual data collected from relevant departments in Thailand, while projections for 2023–2030 are forecasted based on the baseline year. The secondary database used in the International Vehicle Emission model is adjusted according to real-world driving data to accurately reflect country-specific emission factors. Dynamic emission factors for specific air pollutants and GHGs are evaluated and integrated with the average Vehicle Kilometres Travelled (VKT) for each vehicle category. The Business-As-Usual (BAU) scenario is then examined, based on existing policies aimed at reducing air pollutants and GHG emissions in Thailand’s transport sector. These policies include strategies for the adoption of electric vehicles and the promotion of public transport to reduce VKT. Under the BAU scenario, the overall number of road vehicles in Thailand, including passenger cars, motorcycles, pickups, vans, trucks, and buses, is expected to increase by approximately 6.58% by 2030, leading to a rise in specific air pollutants and GHG emissions compared to the 2019 baseline. However, by adhering to Thailand’s strategies and transitioning to new electric passenger cars and buses, greenhouse gas emissions and specific air pollutants from the road transport sector will be significantly reduced. Full article

In this review, the main issues related to the conservation and valorization of Plant Genetic Resources for Food and Agriculture (PGRFA) will be primarily addressed. The conservation of PGRFA concerning outcrossing plants poses a significant challenge. For this reason, this review will cover the key challenges related to all stages, starting from in situ sampling, collection in the germplasm bank, and conservative reproductive methods. Integrated approaches involving the combined use of classical and molecular techniques will be described for the characterization of accessions. Within this framework, some successful Italian case studies focused on maize will be reported as well. Full article

Nuclear speckles are compartments enriched in splicing factors present in the nucleoplasm of eucaryote cells. Speckles have been studied in mammalian culture and tissue cells, as well as in some non-mammalian vertebrate cells and invertebrate oocytes. In mammals, their morphology is linked to the transcriptional and splicing activities of the cell through a recruitment mechanism. In rats, speckle morphology depends on the hormonal cycle. In the present work, we explore whether a similar situation is also present in non-mammalian cells during the reproductive cycle. We studied the speckled pattern in several tissues of a viviparous reptile, the lizard Sceloporus torquatus, during two different stages of reproduction. We used immunofluorescence staining against splicing factors in hepatocytes and oviduct epithelium cells and fluorescence and confocal microscopy, as well as ultrastructural immunolocalization and EDTA contrast in Transmission Electron Microscopy. The distribution of splicing factors in the nucleoplasm of oviductal cells and hepatocytes coincides with the nuclear-speckled pattern described in mammals. Ultrastructurally, those cell types display Interchromatin Granule Clusters and Perichromatin Fibers. In addition, the morphology of speckles varies in oviduct cells at the two stages of the reproductive cycle analyzed, paralleling the phenomenon observed in the rat. The results show that the morphology of speckles in reptile cells depends upon the reproductive stage as it occurs in mammals. Full article

Riemerella anatipestifer (RA) is an economically important pathogen in the duck industry worldwide that causes high mortality and morbidity in infected birds. We previously found that upregulated IL-17A expression in ducks infected with RA participates in the pathogenesis of the disease, but this mechanism is not linked to IL-23, which primarily promotes Th17 cell differentiation and proliferation. RNA sequencing analysis was used in this study to investigate other mechanisms of IL-17A upregulation in RA infection. A possible interaction of IL-26 and IL-17 was discovered, highlighting the potential of IL-26 as a novel upstream cytokine that can regulate IL-17A during RA infection. Additionally, this process identified several important pathways and genes related to the complex networks and potential regulation of the host immune response in RA-infected ducks. Collectively, these findings not only serve as a roadmap for our understanding of RA infection and the development of new immunotherapeutic approaches for this disease, but they also provide an opportunity to understand the immune system of ducks. Full article

In this study, a phenol–formaldehyde resin–montmorillonite intercalation composite solution was used as a modifier to treat Chinese fir via impregnation and compression. The basic characteristics and wettability of the PF (phenol–formaldehyde)–montmorillonite impregnation solution were analyzed. The effects of the solid content of PF, the quantity of montmorillonite, and the impregnation time on the impregnation weight gain of Chinese fir were studied through orthogonal experiments. The results showed that when the amount of montmorillonite was 1%, the wettability of the PF–montmorillonite impregnation solution performed the best, the curing time was short, and the curing strength was high. The optimal impregnation process consists of a PF solid content of 25%, an impregnation time of 120 min, and a montmorillonite ratio of 1%. Under these conditions, the modified Chinese fir was prepared via hot pressing. The effects of the addition of montmorillonite and different levels of compressibility on the physical and mechanical properties of modified wood were studied. The physical and mechanical properties were found to be better when the compression ratio was 33%: the density increased from 0.33 g/cm³ to 0.58 g/cm³; the surface hardness increased from 33.6 HD to 70.9 HD; the static bending strength increased from 60.4 MPa to 98.7 MPa; and the elastic modulus increased from 6 390 MPa to 11 498 MPa. After 30 days of release, the compression rebound rate was 3.97%. Meanwhile, the micromorphology and heat resistance of the impregnated compressed Chinese fir showed that the PF–montmorillonite impregnation solution entered into the cell cavity and intercellular space of the Chinese fir and formed a good composite, thus improving the water resistance, heat resistance, and physical and mechanical properties. Full article

Nucleosomes are non-uniformly distributed across eukaryotic genomes, with stretches of ‘open’ chromatin strongly associated with transcriptionally active promoters and enhancers. Understanding chromatin accessibility patterns in normal tissue and how they are altered in pathologies can provide critical insights to development and disease. With the advent of high-throughput sequencing, a variety of strategies have been devised to identify open regions across the genome, including DNase-seq, MNase-seq, FAIRE-seq, ATAC-seq, and NicE-seq. However, the broad application of such methods to FFPE (formalin-fixed paraffin-embedded) tissues has been curtailed by the major technical challenges imposed by highly fixed and often damaged genomic material. Here, we review the most common approaches for mapping open chromatin regions, recent optimizations to overcome the challenges of working with FFPE tissue, and a brief overview of a typical data pipeline with analysis considerations. Full article

This paper explores how water and water-based systems change their structure under different conditions, such as pH, temperature, and electric fields. These changes affect the properties and performance of living and non-living systems that use water or water-based systems in various technologies. We can use pH, temperature, and electric fields to measure and control the structural changes in water and water-based systems and improve the outcomes of different technologies in biology and medicine. More research is needed to understand how various factors influence the structure of water and water-based systems and how this affects living and non-living systems. Full article

Due to the coexistence of Al³⁺ and RE³⁺ and their similar properties, the separation of aluminum from rare earths is difficult. In this study, selective precipitation was used to separate aluminum from rare earth chloride solution via electrochemical regulated hydrolysis. By controlling the current density and electrolytic time, the rate of hydroxyl ion production was regulated, and the selective separation of rare earth and aluminum was realized according to the different precipitation sequences. By altering the temperature, current density, pH value, and other parameters, the separation performance of aluminum from rare earth in mixed rare earth chloride systems was systematically investigated. The removal rate of aluminum reached 88.35%, and the loss rate of rare earth was only 5.99% under optimized conditions. Compared with traditional neutralization hydrolysis, the new process showed higher efficiency and lower rare earth loss rate. Furthermore, a kinetic analysis of aluminum precipitation revealed that the reaction adhered to pseudo-first order kinetics. Additionally, the precipitate obtained via separation and filtration was amorphous alumina hydroxide with a small amount of rare earth attached. No reagent was consumed for the new process, which was more efficient and cleaner, providing a new idea for removing aluminum impurities from rare earth solutions. Full article

This paper presents a miniaturized-structure high-gain antipodal Vivaldi antenna (AVA) operating in the millimeter-wave (mm-wave) band. A gradient-length microstrip-patch-based director is utilized on the flares of the AVA to enhance gain. Additionally, an array of metallic vias is incorporated along the lateral and horizontal edges of the antenna for further gain enhancement and bandwidth extension. Based on the proposed structure, the AVA can achieve a peak gain of 11.9 dBi over a relative bandwidth of 71.24% within 16.5–36.6 GHz as measured, while the electrical dimension is only 1.54 × 2.69 × 0.07 ${{\mathsf{\lambda }}_c}^3$. The measured results show good agreement with the simulated ones. Owning the characteristics of being high-gain and ultra-wideband, and having a compact size, the proposed AVA can be a competitive candidate for future millimeter-wave communication. Full article

The measurement of corneal sensation allows clinicians to assess the status of corneal innervation and serves as a crucial indicator of corneal disease and eye health. Many devices are available to assess corneal sensation, including the Cochet–Bonnet aesthesiometer, the Belmonte Aesthesiometer, the Swiss Liquid Jet Aesthesiometer, and the newly introduced Corneal Esthesiometer Brill. Increasing the clinical use of in vivo confocal microscopy and optical coherence tomography will allow for greater insight into the diagnosis, classification, and monitoring of ocular surface diseases such as neurotrophic keratopathy; however, formal esthesiometric measurement remains necessary to assess the functional status of corneal nerves. These aesthesiometers vary widely in their mode of corneal stimulus generation and their relative accessibility, precision, and ease of clinical use. The development of future devices to optimize these characteristics, as well as further comparative studies between device types should enable more accurate and precise diagnosis and treatment of corneal innervation deficits. The purpose of this narrative review is to describe the advancements in the use of aesthesiometers since their introduction to clinical practice, compare currently available devices for assessing corneal innervation and their relative limitations, and discuss how the assessment of corneal innervation is crucial to understanding and treating pathologies of the ocular surface. Full article

The Cupressaceae family includes species considered to be medicinal. Their essential oil is used for headaches, colds, cough, and bronchitis. Cedar trees like Chamaecyparis lawsoniana (C. lawsoniana) are commonly found in urban areas. We investigated whether C. lawsoniana exerts some of its effects by modifying airway smooth muscle (ASM) contractility. The leaves of C. lawsoniana (363 g) were pulverized mechanically, and extracts were obtained by successive maceration 1:10 (w:w) with methanol/CHCl₃. Guinea pig tracheal rings were contracted with KCl, tetraethylammonium (TEA), histamine (HIS), or carbachol (Cch) in organ baths. In the Cch experiments, tissues were pre-incubated with D-600, an antagonist of L-type voltage-dependent Ca²⁺ channels (L-VDCC) before the addition of C. lawsoniana. Interestingly, at different concentrations, C. lawsoniana diminished the tracheal contractions induced by KCl, TEA, HIS, and Cch. In ASM cells, C. lawsoniana significantly diminished L-type Ca²⁺ currents. ASM cells stimulated with Cch produced a transient Ca²⁺ peak followed by a sustained plateau maintained by L-VDCC and store-operated Ca²⁺ channels (SOCC). C. lawsoniana almost abolished this last response. These results show that C. lawsoniana, and its active metabolite quercetin, relax the ASM by inhibiting the L-VDCC and SOCC; further studies must be performed to obtain the complete set of metabolites of the extract and study at length their pharmacological properties. Full article

The exploitation of iron ore could cause heavy metals pollution in the soils, which threatens the ecosystem and human health. In this study, soil, stream sediment, tailings, rock, and atmospheric deposition samples were collected from an iron mine in Baotou City. The concentrations of As, Cd, Cr, Cu, Hg, Ni, Pb, Zn, Al₂O₃, CaO, K₂O, MgO, Na₂O, SiO_2, and Fe₂O₃, as well as the mineral composition and heavy metal speciation of the samples, were analyzed for pollution assessment and source identification of heavy metals. The results reveal that the concentration of Cu in the soils was significantly higher than the background value, and an unpolluted to moderately polluted state was the main pollution level. By analyzing the relationship between Cu/Al₂O₃ and CaO in different samples, as well as the characteristics of the chemical index of alteration (CIA), mineral composition, and the chemical speciation of Cu in soils and profiles, the results suggest that tailings were the source of Cu pollution in soils. The distribution characteristics of Cu and CaO in stream sediments indicated that hydraulic transport may be one of the main migration pathways. In addition, wind transport may also be a pathway of migration. Full article

The sea ice albedo can amplify global climate change and affect the surface energy in the Arctic. In this paper, the data from Visible and Infra-Red Radiometer (VIRR) onboard Fengyun-3C satellite are applied to derive the Arctic sea ice albedo. Two radiative transfer models, namely, 6S and FluxNet, are used to simulate the reflectance and albedo in the shortwave band. Clear sky sea ice albedo in the Arctic region (60°~90°N) from 2016 to 2019 is derived through the physical process, including data preprocessing, narrowband to broadband conversion, anisotropy correction, and atmospheric correction. The results are compared with aircraft measurements and AVHRR Polar Pathfinder-Extended (APP-x) albedo product and OLCI MPF product. The bias and standard deviation of the difference between VIRR albedo and aircraft measurements are −0.040 and 0.071, respectively. Compared with APP-x product and OLCI MPF product, a good consistency of albedo is shown. And analyzed together with melt pond fraction, an obvious negative relationship can be seen. After processing the 4-year data, an obvious annual trend can be observed. Due to the influence of snow on the ice surface, the average surface albedo of the Arctic in March and April can reach more than 0.8. Starting in May, with the ice and snow melting and melt ponds forming, the albedo drops rapidly to 0.5–0.6. Into August, the melt ponds begin to freeze and the surface albedo increases. Full article

More sustainable biosensor production is growing in importance, allowing for the development of technological solutions for several industries, such as those in the health, chemical, and food sectors. Tracking the latest advancements in biosensors’ scientific production is fundamental to determining the opportunities for the future of the biosensing field. This article aims to map scientific production in the biosensors field by running a bibliometric analysis of journal articles registered in the Web of Science database under biosensor-related vital concepts. The key concepts were selected by researchers and biosensor technology developers working on the BioAssembler Horizon project. The findings lead to identifying the scientific and technological knowledge base on biosensing devices and tracking the main scientific organisations developing this technology throughout the COVID-19 period (2019–2023). The institutional origin of the publications characterised the global distribution of related knowledge competencies and research partnerships. These results are discussed, shedding light on the scientific, economic, political, and structural factors that contribute to the formation of a scientific knowledge-based focus on the performance and design of these sensors. Moreover, the lack of scientific ties between the three axes of organisations producing expertise in this area (China, USA, and Russia) points towards the need to find synergies through new mechanisms of co-authorship and collaboration. Full article

Bryophyllum pinnatum (BP) is a medicinal plant used to treat many conditions when taken as a leaf juice, leaves in capsules, as an ethanolic extract, and as herbal tea. These preparations have been chemically analyzed except for decoctions derived from boiled green leaves. In preparation for a clinical trial to validate BP tea as a treatment for kidney stones, we used NMR and MS analyses to characterize the saturation kinetics of the release of metabolites. During boiling of the leaves, (a) the pH decreased to 4.8 within 14 min and then stabilized; (b) regarding organic acids, citric and malic acid were released with maximum release time (t_max) = 35 min; (c) for glycoflavonoids, quercetin 3-O-α-L-arabinopyranosyl-(1 → 2)-α-L-rhamnopyranoside (Q-3O-ArRh), myricetin 3-O-α-L-arabinopyranosyl-(1 → 2)-α-L-rhamnopyranoside (M-3O-ArRh), kappinatoside, myricitrin, and quercitrin were released with t_max = 5–10 min; and (d) the total phenolic content (TPC) and the total antioxidant capacity (TAC) reached a t_max at 55 min and 61 min, respectively. In summary, 24 g of leaves boiled in 250 mL of water for 61 min ensures a maximal release of key water-soluble metabolites, including organic acids and flavonoids. These metabolites are beneficial for treating kidney stones because they target oxidative stress and inflammation and inhibit stone formation. Full article

Intelligent transportation and advanced mobility techniques focus on helping operators to efficiently manage navigation tasks in smart cities, enhancing cost efficiency, increasing security, and reducing costs. Although this field has seen significant advances in developing large-scale monitoring of smart cities, several challenges persist concerning the practical assignment of delivery personnel to customer orders. To address this issue, we propose an architecture to optimize the task assignment problem for delivery personnel. We propose the use of different cost functions obtained with deterministic and machine learning techniques. In particular, we compared the performance of linear and polynomial regression methods to construct different cost functions represented by matrices with orders and delivery people information. Then, we applied the Hungarian optimization algorithm to solve the assignment problem, which optimally assigns delivery personnel and orders. The results demonstrate that when used to estimate distance information, linear regression can reduce estimation errors by up to 568.52 km (1.51%) for our dataset compared to other methods. In contrast, polynomial regression proves effective in constructing a superior cost function based on time information, reducing estimation errors by up to 17,143.41 min (11.59%) compared to alternative methods. The proposed approach aims to enhance delivery personnel allocation within the delivery sector, thereby optimizing the efficiency of this process. Full article