In a trip planning service, travelers first set a starting point, a destination, and a sequential list of specific points of interest types (e.g., museums, restaurants, and parks). Based on this information, the service searches the spatial database to customize the best travel itinerary for the tourist. However, in previous studies, planners only considered the time factor when designing the optimal route, and failed to fully consider the quality of each point of interest. In this study, we specifically leveraged the capabilities of large language model to parse and respond to complex travel-related user queries. To apply large language model to route planning, we fine-tuned the model to understand geotagging and user travel preferences. We have introduced a novel graph search algorithm combined with large language model output, which optimizes the route search process to provide optimal travel recommendations by taking into account various factors such as distance length, budget constraints, and popularity of tourist attractions. In addition, we have integrated real-time traffic data and historical travel data to further improve the prediction accuracy and application usefulness of the model. In the experimental validation phase, we designed a series of benchmarks to compare the performance of the system with traditional algorithms and other machine learning-based route planning methods. Experimental results show that our model has a significant improvement compared with traditional methods in improving the speed and accuracy of path selection.

he paper presents an innovative method for tourist route planning inside a destination. The necessity of reorganizing the tourist routes within a destination comes as an immediate response to the Covid-19 crisis. The implementation of the method inside tourist destinations can bring an important advantage in transforming a destination into a safer destination in times of Covid-19 and post-Covid-19. The existing trend of shortening the tourist stay length has been accelerated while the epidemic became a pandemic. Moreover, the wariness for future pandemics has brought into spotlight the issue of overcrowded attractions inside a destination at certain moments. The method presented in this paper proposes a backtracking algorithm, more precisely an adaptation of the travelling salesman problem. The method presented is aimed to facilitate the navigation inside a destination and to revive certain less-visited sightseeing spots inside a destination while facilitating conformation with the social distancing measures imposed for Covid-19 control.

The stability of the filling roof as an important bearing unit in the stope of the access stope in the filling mining method is of great significance to guarantee the safe and efficient production of the mine. Arrangement of mining approach in downward cemented filling stope is the key factor af-fecting stability of filling body roof. Based on combination of laboratory test, theoretical analysis and numerical simulation, the influence of different mining approach arrangement on stability of filling body roof is analyzed. The weak filling surface is formed between adjacent mining paths. The mechanical strength of the weak filling surface is significantly reduced by laboratory experiments. The relationship between distribution of the weak filling surface, azimuth angle and stability of filling roof is further studied by numerical simulation. The results show that the stability of the filler roof is the best when the upper and lower stratified mining approach is arranged vertically.

Relay protection service is the most crucial service carried by the electric power communication network, which is directly linked to the safe operation of the power grid. In the route planning of power services, a route planning architecture for the power communication network is constructed in this paper, considering the operation and maintenance requirements, such as relay protection service overload (RPSO) and dual route. To minimize network risk variance, the problem of single-service route allocation is formulated by taking the factors into account such as service delay, link bandwidth utilization, and RPSO constraints. Based on $k$ shortest paths algorithm, a route planning scheme for the power services is proposed, which considers RPSO and risk balance, and a strategy for implementing multi-service route planning of the communication network is studied. The simulation results show that the proposed route planning strategy can effectively avoid relay protection service overload, reduce network risk variance, and balance network risk.

Automated Guided Vehicles are self-guided vehicles used in manufacturing and warehouses for material transport. They play a vital role in just-in-time material delivery, ensuring smooth production lines. However, disruptions in their fixed routes can lead to efficiency losses. This paper studies unexpected disruptions in mobile robot routes, assessing the costs of rectification using the E* analysis. The study highlights the significant additional cost of such disruptions, underscoring the importance of their consideration in AGV route planning to enhance system resilience.

In the war against the COVID-19 pandemic, the world is experiencing severe resource constraints. Although transmission routes are well understood, we suspect that they cause different disease consequences. We evaluate them in different forms to understand how they affect infection rates and disease severity. In determining how they affect disease outcome, we evaluated target tissue vulnerability, functional role, defense mechanisms, viral concentration, infection vicinity to target vital tissue, and host factors. We found that direct lung infection is the most lethal transmission route followed by bronchi infection. Transmissions by physical contacts, foods, and blood by low viral concentration (as expected in normal human activities) pose lower or much lower risks unless the infection is followed by subsequent lung exposures. After adding transmission route, treatment timings, and improper treatments into the list of known risk factors, we found that death rate and disability rate for young or healthy persons are nearly zero. We show that population based medical model improperly shifts nominal death rate from few vulnerable people to the population resulting in unnecessary population panic, and such panic is responsible for shutting down human activities and the world economy. Finally, we examined limitations in population-based mitigating measures and proposed for governmental and private adoption community guidelines, which are mainly to enable vulnerable people avoid exposures, prevent non-vulnerable people from serving as viral transmitters, get rid of high-risk exposure modes in working environment, improve safety for people in buses, ships and planes, and reduce death and disability rates for infected people.

Recently, there has been growing interest in using smart eHealth systems to manage asthma. However, limitations still exist in providing smart services and accurate predictions tailored to individual patients’ needs. This study aims to develop an adaptive ubiquitous computing framework that leverages different bio-signals and spatial data to provide personalized asthma attack prediction and safe route recommendations. We proposed a smart eHealth framework consisting of multiple layers that employ telemonitoring application, environmental sensors, and advanced machine-learning algorithms to deliver smart services to the user. The proposed smart eHealth system predicts asthma attacks and uses spatial data to provide a safe route that drives the patient away from any asthma trigger. Additionally, the framework incorporates an adaptation layer that continuously updates the system based on real-time environmental data and daily bio-signals reported by the user. The developed telemonitoring application collected a dataset containing 665 records used to train the prediction models. The testing result demonstrates a remarkable 98% accuracy in predicting asthma attacks with a recall of 96%. The eHealth system was tested online by ten asthma patients, and its accuracy achieved 94% of accuracy and a recall of 95.2% in generating safe routes for asthma patients, ensuring a safer and asthma-trigger-free experience. The test shows that 89% of patients were satisfied with the safer recommended route than their usual one. This research contributes to enhancing the capabilities of smart healthcare systems in managing asthma and improving patient outcomes. The adaptive feature of the proposed eHealth system ensures that the predictions and recommendations remain relevant and personalized to the current conditions and needs of the individual.

Without protective and/or therapeutic agents the SARS-CoV-2 infection known as coronavirus disease 2019 (COVID-19) is quickly spreading worldwide. It has surprising transmissibility potential, since it could infect all ages, gender, and human sectors. It attacks respiratory, gastrointestinal, urinary, hepatic, and endovascular systems and can reach the peripheral nervous system (PNS) and central nervous system (CNS) through known and unknown mechanisms. The reports on the neurological manifestations and complications of the SARS-CoV-2 infection are increasing exponentially. Herein, we enumerate seven candidate routes, which the mature or immature SARS-CoV-2 components could use to reach the CNS and PNS, utilizing the within-body crosstalk between organs. The majority of SARS-CoV-2 infected patients suffer from some neurological manifestations (e.g., confusion, anosmia, and ageusia). It seems that although the mature virus did not reach the CNS or PNS of the majority of patients, its unassembled components and/or the accompanying immune-mediated responses may be responsible for the observed neurological symptoms. The viral particles and/or its components have been specifically documented in endothelial cells of lung, kidney, skin, and CNS. This means that the blood-endothelial-barrier may be considered as the main route for SARS-CoV-2 entry into the nervous system, with the barrier disruption being more logical than barrier permeability, as evidenced by postmortem analyses.

Microplastics (of size < 5mm) pollution in our environment is of current concern by researchers, public media and non-governmental organizations. Implications by their presence in aquatic and soil ecosystems have been well studied and documented, but less attention has been paid on airborne microplastics (MPs). Studies concerning airborne microplastics started from 2016 and only a few (n=7) have been published till date. Although, studies may increase in the following years, since air is very important for human survival. Microplastics have been observed in atmospheric fallouts in indoor and outdoor environments using a sampling or vacuum pump, rain sampler and/or particulate fallout collector. Identification and quantification have been carried out by visual, spectroscopic and spectrometric techniques. Factors such as meterological, climatic and anthropogenic influence the distribution and movement of airborne MP. Human exposure may be through inhalation or dermal route with their potential biopersistence and translocation. Ingestion may cause localized inflammation and cancer due to responses by the immune cells, especially in individuals with compromised metabolism and poor clearance mechanisms. Ecological risks involve possible contamination of the ecosystem through a dynamic relationship of MPs in soil, water and air forming a MP contamination cycle. The present review aimed at providing a comprehensive overview of current knowledge or information regarding microplastics in air, identifies gap in knowledge and give suggestions for future research.

This paper assesses the use the Global Sustainable Tourism Criteria (GSTC) indicators for monitoring tourism along a mountainous route. The study was carried out along a mountain route in the Drakensberg Mountains of South Africa. A survey was carried out among tourism businesses, local communities and local government officials located along the Maluti Route, which passes though the eastern part of the Free State Province of South Africa. This study constitutes the first assessment in which the GSTC indicators are applied in the assessment of the sustainability of route tourism in South Africa. The study first evaluated the importance of each indicator by considering the level of application in tourism business organisations before examining the perceptions of local community members and local government officials regarding the applicability of the indicators in the assessment of tourism sustainability. The results suggest that there is a general appreciation of tourism sustainability among tourism business operators although shortcomings were evident on environmental and socio-economic indicators. In conclusion, the paper suggests ways through which tourism sustainability could be enhanced among different players along the Maluti Route.

This literature review was aimed to identifying the opportunistic bacterial pathogens that can be transmitted by contaminated food and represent a current threat for patients particularly suscep-tible to infections because of underlying conditions or predisposing factors. The analysis was focused on recent case or outbreak reports, and systematic reviews published in years 2019 - 2023 and resulted in sorting 24 bacterial groups comprising genera or species able to cause a variety of systemic or invasive infections if ingested with food or drinking water. These included both bacteria known to cause mild infections in immunocompetent persons and bacteria considered innocuous that are used in food fermentation or as probiotics. No recent cases from dietary routes were reported for bacteria of critical importance as nosocomial pathogens and widely occurring in food products, primarily, Acinetobacter baumanii and Klebsiella pneumoniae. However, the very first sources of their introduction in the clinical environment still need to be estab-lished. In many instances, risky dietary habits such as eating raw fish, seafood, raw meat, unpasteurized milk and derived products or the lack of control on fermentation processes led to the reported illnesses, pointing out to the necessity to improve the hygiene of production and consumer’s awareness of risks.

This paper addresses the alliance route network design problem considering uncertainty of unit transportation cost. An alliance route network is constructed based on the hub-and-spoke (HS) network , in which airlines can achieve inter-area passenger transport through their international gateways. The design problem is formulated with a robust model containing a set of uncertain cost parameters. The model is established based on the three-subscript model of the HS network. A case study collected from real-world data is used to test the proposed model. The results show that the robust solution can reduce the impact of cost uncertainty.

Purpose of Review Multipotent Mesenchymal stromal cells (MSCs) have recently risen to prominence in regenerative medicine for their powerful intrinsic properties of self-regeneration, immunomodulation, and multi-potency. They exhibited an excellent safety profile in early-phase clinical trials. Nevertheless, MSCs-based therapy suffers reduced efficacy in randomized clinical trials due to a poor understanding of their proper delivery modalities. Here, we intend to explore the current application of MSCs after tissue injuries. We specifically focus on tissue source, delivery routes, metabolic fitness, and cell dose. We further discuss potential approaches to optimize in vivo engraftment. Recent findings MSCs therapeutic effect mediates by paracrine and contact factors, which are cells' intrinsic physiological processes. The cell culture expansion process does not destroy MSCs' intrinsic properties. In vivo persistence of administered MSCs determines their therapeutic potency. Cell viability, fitness, immune match, and delivery route meticulously regulate their in vivo persistency. Different genetic or chemical modification strategies are currently applied to extend their in vivo lifespan and boost their pharmaceutical effect. Summary Improving the in vivo persistence of implanted MSCs could facilitate its clinical translation. This review highlights the pros and cons of different MSCs’ delivery strategies used in clinical or preclinical studies, emphasizing various modification approaches. These can promote prolonged graft cell survival.

Free route airspace (FRA) is a new concept of European air transport. It has been designed to eliminate the negative impact of air traffic on the environment, minimize fuel consumption, simplify and expand flight planning. In our research, FRA is modelled by using graph theory, networks, and convex analysis. We also looked for answers to the question which are the basic mathematical properties of airspace? Basic mathematical properties are expressed using axioms. Therefore, in our work, we state the general, basic axiom of airspace based on our FRA research. The axiom is given using practical, significant entry points and geodetic coordinates.

The recent detection of SARS-CoV-2 RNA in feces has led to speculation that it can be transmitted via the fecal-oral/ocular route. This review aims to critically evaluate the incidence of gastrointestinal (GI) symptoms, the quantity and infectivity of SARS-CoV-2 in feces and urine, and whether these pose an infection risk in sanitary settings, sewage networks, wastewater treatment plants, and the wider environment (e.g. rivers, lakes and marine waters). Overall, severe GI dysfunction is only evident in a small number of COVID-19 cases, with 11 ± 2% exhibiting diarrhea and 12 ± 3% exhibiting vomiting and nausea. In addition to these cases, SARS-CoV-2 RNA can be detected in feces from some asymptomatic, mildly- and pre-symptomatic individuals. Fecal shedding of the virus peaks in the symptomatic period and can persist for several weeks, but with declining abundances in the post-symptomatic phase. SARS-CoV-2 RNA is occasionally detected in urine, but reports in fecal samples are more frequent. The abundance of the virus genetic material in both urine (ca. 10²-10⁵ gc/ml) and feces (ca. 10²-10⁷ gc/ml) is much lower than in nasopharyngeal fluids (ca. 10⁵-10¹¹ gc/ml). There is strong evidence of multiplication of SARS-CoV-2 in the GI tract and infectious virus has occasionally been recovered from both urine and stool samples. The level and infectious capability of SARS-CoV-2 in vomit remain unknown. In comparison to enteric viruses transmitted via the fecal-oral route (e.g. norovirus, adenovirus), the likelihood of SARS-CoV-2 being transmitted via feces or urine appears lower due to the lower relative amounts of virus present in feces/urine. The biggest risk of transmission will occur in clinical and care home settings where secondary handling of people and urine/fecal matter occurs. In addition, while SARS-CoV-2 RNA genetic material can be detected by in wastewater, this signal is greatly reduced by conventional treatment. Our analysis also suggests the likelihood of infection due to contact with sewage-contaminated water (e.g. swimming, surfing, angling) or food (e.g. salads, shellfish) is extremely low or negligible based on very low predicted abundances and limited environmental survival of SARS-CoV-2. These conclusions are corroborated by the fact that over eight million global cases of COVID-19 have occurred, but exposure to feces or wastewater has never been implicated as a transmission vector.

A sublingual vaccine comprising Poly(I:C) adjuvant and influenza HA antigen was evaluated for safety in both mice and macaque monkeys relative to its intranasal counterpart. Safety was assessed with harmful effects corresponding to upregulation of the inflammation-associated genes: Saa3, Tnf, IL6, IL1b, Ccl2, Timp1, C2, Ifi4, Aif1, Omp, Nos2, and/or Gzmb in mice and SAA2, TNF, IL6, IL1B, CCL2, TIMP, C2, AIF1, and GZMB in macaques. Quantitative gene expression analyses were performed using RT-qPCR with RNA samples from four tissues: olfactory bulb, pons, lung, tongue, and (submandibular) lymph node from both mice and macaques. In mice, the intranasally delivered vaccine markedly upregulated the inflammation-related genes in the olfactory bulb 1 day and 7 days after vaccination. The adverse effects of intranasal vaccination were also observed in macaques, however to a lesser extent than in mice. The intranasal vaccination also upregulated these genes in the pons of both mice and macaques. In contrast, the sublingual vaccine did not adversely affect the olfactory bulb or pons in either mice or macaques. The intranasally administered vaccine significantly upregulated these genes in the lungs only 1 day after vaccination, but not 7 days later, in both mice and macaques. We conclude that intranasal vaccination results in unfavorable side effects corresponding to upregulated inflammatory genes in the brain (olfactory bulb and pons). Sublingual vaccination, however, did not induce these side effects in either mice or macaque and was hence evaluated as safe.

The article describes the methodology of the experimental analysis of operational and cost-effective assessment using geographic information system (GIS) technologies, as opposed to the assessment of the tourism potential of the nature of the Fergana Valley in Uzbekistan using long term and costly classical approaches. Based on the ArcGIS (10.8) grid index approach of 20 natural geographical indicators of the valley, such as geographical location, relief, climate, hydrographic and biological, the level of tourism comfort was determined and the location of 6 tourist-recreation zones were defined. The level of accuracy of the tourist-recreational zones all situated utilizing GIS technologies was confirmed by field-expedition approaches.

Effects of the convection flow, atmospheric diffusivity and humidity on evolution and travel distances of exhaled aerosol clouds by an infected person are considered. The aim of this work is to evaluate the importance of aerosol transmission routes and the effectiveness of the 2-metre separation distance policy. A potential impact of use of face masks on the infection transmission rate, and an opportunity to reduce infection in hospitals, care homes and other public spaces by appropriate monitoring and filtering of air are also considered. The results obtained demonstrate that aerosol particles generated by coughing and sneezing can travel over 30 m. Modelling of the evolution of aerosol clouds generated by coughing and sneezing enables us to evaluate the deposition dose of aerosol particles in healthy individuals. For example, a person in a public place (e.g. supermarket or car park) can accumulate in the respiratory system up to 200 virus copies in 2 min time by breathing in virus laden aerosols. Wearing face mask considerably reduces the deposited load down to 2 virus copies per 2 min. The modelling also suggests that it should be possible to measure virus causing COVID-19 (SARS-CoV-2) within aerosol particles in hospitals and public places, e.g. care homes and supermarkets.

Dispatching goods is becoming more difficult to manage in the field of logistics due to the high demand for order shipments. This is relative to the increasing popularity of the use of e-commerce platforms among consumers, where delivery of products is required as compared to buying in physical stores. Dispatch management is one of the critical components in a supply chain since it covers the coordination tasks among stakeholders from warehouse up to the consumer’s doorstep. In this study, the authors intend to propose a framework leveraging geographic information to sustain the logistics operations, specifically in terms of managing last-mile delivery and return trip orders. This includes scheduling, communications, and inventory of goods shipment. A mobile application built on this framework was integrated with a waypoint order optimization algorithm considering the entire route traversing all the required pick-up and delivery points. It was pilot tested with an actual dispatch operation of a logistics company yielding a decrease of 87% in total shipment time, 79% in operations cost, and 3% in carbon footprint per vehicle. With the adoption of this framework, the study aims to contribute to the overall efficiency and sustainability of logistics operations in a wider geographic range.

Apartment buildings, which make up 83% of all structures in Jordan, play a crucial role in the country's construction sector. This study examines the main barriers that are preventing the implementation of low-carbon emission techniques in these buildings. It uses the Fuzzy Delphi Method to collect ideas from 14 housing investors. The results suggest that a major obstacle is the insufficient knowledge among end-users regarding environmental concerns, along with financial limitations, resulting in a lack of enthusiasm for low-carbon construction initiatives. Moreover, insufficient cooperation between consultants and contractors leads to subpar constructability, which is worsened by the prevailing conventional procurement method that prioritizes cost and schedule above environmental consequences. To further investigate, it is advisable to examine the utilization of contemporary procurement methods, such as Design-Build and Construction Management, in the housing industry of Jordan. These alternative methods have the potential to solve the current difficulties by promoting more effective and environmentally friendly building practices. This will help increase the use of low-carbon emission solutions and improve the overall sustainability of Jordan's construction sector.

Bandung and Lembang are the cities that are chosen by many tourists (local and foreign) as their destinations. Geographically, these cities are placed side-by-side and each city has its own characteristics. As in Bandung, there are many hotels and culinary spots, meanwhile, in Lembang, there are many scenery tourism spots. Tourists usually have limited time to visit all the destinations on holiday, which makes them choose several tourist destinations to visit. In this paper, the tourism itinerary recommendation system is proposed by calculating the most optimal route between destinations and approaching the Vehicle Routing Problem with Time Windows. The optimal route is defined by using Dijkstra the shortest path algorithm by using the collaboration between the road information (road length, traffic condition, travel time, and weather condition) and criteria weight that is determined using the Analytics Hierarchy Process as the graph weights. According to the simulation results, the criteria weights are 6.9%, 62.7%, 18.6%, and 11.9% for Route Length, Traffic Condition, Travel Time, and Weather Condition respectively. Moreover, the optimal number of tourism itinerary plans for the tourist in this research is 4 destinations. As the usage of computational resources, it takes 31.8% of CPU and 61.9% of Memory usage. For the time processing, it increases exponentially as the increment of number of requested stops. The output of this research is expected to be a solution to the tourist itinerary plan, especially in Bandung and Lembang.

The Standard Model (SM) fails to account for either the triplication of fermion families or chiral symmetry breaking in the electroweak sector. Here we show that both phenomena arise from the approach to chaos of quantum theory near the Fermi scale.

The COVID-19 pandemic has great adverse impacts on personal life, the U.S. economy, and the world economy. Freezing all human activities is not a sustainable measure. Thus we want to develop a public intervention framework that allows people to resume personal and economic activities. In this article, we examined transmission routes, disease severity, personal vulnerability, available treatments, and person-person interactions to establish a general public intervention framework. We divide people into risk groups, non-risk group and group that may serve as viral transmitters, explore interactions between individual persons within each group and between different groups, and propose interaction behavior modifications to mitigate viral exposures. For the non-risk groups, we identified preventive measures that can help them avoid the most serious exposures and infections that pose higher death risks. The invention measures for the vulnerable groups include prior-exposure measures, heightened protective measures, interaction behavior changes, post-exposure remedial measures, and multiple factors treatments to reduce death and disability risks. The multiple interventions and two-ways defensive behavior modifications are expected to result in reduced rate of detectable infections and lowered disease severity for the vulnerable groups. In this framework, most human activities and economic activities can continue as normal. With time passing, the population acquires population immunity against the COVID-19 virus. Implementation of this intervention framework requires considerable resources and governmental effects while the multiple factors treatment protocol requires the support of health care professionals.

This article explores how Artificial Intelligence (AI) is drastically changing the logistics industry by transforming operations and significantly improving customer satisfaction. Through meticulous analysis of real-life cases and extensive examination of numerical data, this comprehensive research thoroughly investigates the profound impact of AI on supply chain management. The findings clearly reveal the multifaceted role of AI in significantly reducing costs, greatly improving delivery accuracy, and significantly enhancing inventory control. AI is not just an incremental advancement, but rather a revolutionary leap forward for the future logistics industry, firmly paving the way for unparalleled automation, digital transformation, and operational effectiveness.

Mucosal vaccination appears to be suitable to protect against SARS-CoV-2 infection. In this study, we tested an intranasal mucosal vaccine candidate to COVID-19 constituted of a cationic liposome containing a trimeric SARS-CoV-2 spike protein and CpG-ODNs, a Toll-like receptor 9 agonist, as adjuvant. In vitro and in vivo experiments indicated the absence of toxicity following the intranasal administration of this vaccine formulation. First, we found that subcutaneous or intranasal vaccination protected hACE-2 transgenic mice from infection with the wild-type (Wuhan) SARS-CoV-2 strain, as shown by weight lost and mortality indicators. However, when compared to the subcutaneous administration, the intranasal route was more effective in the pulmonary clearance of the virus and induced higher neutralizing antibodies and anti-S IgA titers. In addition, the intranasal vaccination afforded protection against gamma, delta and omicron virus variants of concern. Furthermore, the intranasal vaccine formulation was superior to intramuscular vaccination with a recombinant, replication-deficient chimpanzee adenovirus vector encoding the SARS-CoV-2 spike glycoprotein (Oxford/AstraZeneca) in terms of virus lung clearance and production of neutralizing antibodies in serum and bronchial alveolar lavage (BAL). Finally, the intranasal liposomal formulation boosted heterologous immunity induced by previous intramuscular vaccination with the Oxford/AstraZeneca vaccine that was more robust than homologous immunity.

The real-time Railway Traffic Management Problem (rtRTMP) is discussed in the field of railway transportation. In this paper, rtRTMP is considered for planning shunting routes based on the use of routing methods on a spatial-temporal graph. An approach and algorithm of Spatial-Temporal Graph formation for rail yard transportation network is proposed. The idea is to construct an undirected loop-free Double Vertex Graph for determining optimal shunting routes consisting of several half-runs for several trains shunting under draw-out tracks capacity constraints. Experimental results on the rail yard simulation model are presented.

The development of wireless sensor networks (WSNs) technology comes with inherent limitations and vulnerabilities that make it exploitable by intruders. The fundamental goal of this article is to solve security problems related to black hole attacks, which interfere with the proper performance of the network and can lead to data leakage and loss. The proposed solution in this article is to apply IDS to a WSN for the first time. We also used the NS2.35 simulator to compare the three routing protocols, AODV, AODV under Hacker Node (HNAODV), and the proposed solution (IDSHNAODV) in the WSN model to reduce the effects of black hole attacks.

In Thailand, there are several bus fleets—predominantly diesel buses—which is an internal combustion engine (ICEs) in circulation. These fleets are consumed a lot of energy and cause pollution, especially by emitting GHGs and PM2.5. Battery electric buses (BEBs) have been proposed to address these issues. BEB fleets still have a high initial cost, which is why most fleet governance agencies, such as the Bangkok Mass Transit Authority (BMTA), are facing investment decisions. This study aims to develop an energy model for the BMTA BEB fleet by using their real operating data. The methodology for the development of the investment model with two steps is described; there is a BMTA bus route analysis step and a fleet management and charging design step. The output is illustrated in terms of the maximum number of BEBs that can be operated on a sample route with the minimum number of chargers. Interesting results were obtained with the first step: Two of the five BMTA bus routes can be changed into BEBs in phases with a limit of 200 kWh for the energy requirements for every two rounds. The results from the second step demonstrated that the maximum number of BEBs for the two routes was 13, with four charger plugs of charger, thus requiring 150 kW per plug. The charging profile peaked at 600 kW from 4:00 to 8:00 p.m. These results show the potential of the model for fleet design and investment decisions. The sample results from the models illustrate energy savings and cost evaluations for fleet management and design. Compared with diesel buses, THB 10.44 million per year can be saved in terms of energy costs by using a BEB fleet. An optimization model was used to assess the savings incurred due to the investment cost. More than 37% of the costs were saved. A full economic investigation should be carried out in the future. These results show only the energy used when the fleet has already been transformed into a BEB fleet in phases. The emphasis of battery size investigation and energy used were illustrated. They only depict an economic validation of the model, but do not refer to such projects’ feasibility, and the model has not yet been fully validated.

This article presents a combined route and path planning strategy to guide Skid-Steer Mobile Robots (SSMRs) in scheduled harvest tasks within expansive crop rows with complex terrain conditions. The proposed strategy integrates: i) a global planning algorithm based on the Traveling Salesman Problem under the Capacitated Vehicle Routing approach and Optimization Routing (OR-tools from Google) to prioritize harvesting positions by minimum path length, unexplored harvest points, and vehicle payload capacity, and ii) a local planning strategy using Informed Rapidly-exploring Random Tree (IRRT*) to coordinate scheduled harvesting points while avoiding low-traction terrain obstacles. The global approach generates an ordered queue of harvesting locations, maximizing the crop yield in a workspace map. In the second stage, the IRRT* planner avoids potential obstacles, including farm layout and slippery terrain. The path planning scheme incorporates a traversability model and a motion model of SSMRs to meet kinematic constraints. Experimental results in a generic fruit orchard demonstrated the effectiveness of the proposed strategy. In particular, the IRRT* algorithm outperformed RRT and RRT* with 96.1% and 97.6% smoother paths, respectively. The IRRT* also showed improved navigation efficiency, avoiding obstacles and slippage zones, making it suitable for precision agriculture.

The most effective method of determining the coordinates of the railway track axis is mobile satellite measurements. However, there are situations when the satellite signal may be disturbed (due to field obstructions) or completely disappear (e.g. in tunnels). Then the ability to measure the value of the directional angle of a moving rail vehicle using an inertial system comes in handy. The directional angle is determined on a topographic map as the angle between the direction of the vehicle longitudinal axis (or the direction of a tangent to the track axis) and the reference direction, which is the north. The article presents a method for determining the directional angle of a railway line based on appropriate measurement data. The latter should be Cartesian coordinates of the track axis, allowing for the visualization of a given railway route and obtaining a general orientation about its course. The presented proposal for solving the problem refers to the assumptions made in the method of determining the curvature of the railway track axis using the moving chord.

Background/Objectives: Community-acquired methicillin-resistant Staphylococcus aureus (CA-MRSA) greatly complicates treatment of skin and soft tissue infections (SSTI). It was previ-ously found that subcutaneous (SQ) treatment with the mononuclear phagocyte (MP)-selective activator, complement peptide-derived immunostimulant-02 (CPDI-02; formerly EP67), increases prophylaxis of outbred CD-1 mice against SQ infection with CA-MRSA. Here, we determined if treatment with CPDI-02 also increases curative protection. Methods: Female CD-1 mice were challenged SQ with CA-MRSA USA300 LAC then CPDI-02 or inactive scCPDI-02 was administered by a topical, SQ, IM, or IV route at 6- or 24-hrs post-challenge. Dermal abscess sizes were compared over 10 days and CA-MRSA burden, neutrophils, MP, and pro-inflammatory cytokines were compared in dermal abscesses. CPDI-02 PK and distribution in female CD-1 mice were compared after IM or IV dosing and CPDI-02 toxicity was determined by IM dose escalation and repeat IM dosing in male and female CD-1 mice. Results: Repeat IM treatment with CPDI-02 starting at 6-hrs post-challenge decreased maximum abscess surface area, CA-MRSA burden, and time to resolu-tion, whereas repeat treatment by the topical, SQ, or IV route had no effect. Starting CPDI-02 treatment at 24-hrs post-challenge was ineffective regardless of route. Single IM treatment with CPDI-02 starting at 6-hrs post-challenge was as effective as repeat IM treatment, increased systemic exposure, and decreased initial levels of IL-1β and increased MP in dermal abscesses. CPDI-02 was tolerated to between 130-170 mg/kg for single IM dosing and 65-130 mg/kg for repeat IM dosing with males being more tolerant. Conclusions: Single early-stage IM treatment with CPDI-02 may increase curative protection against SSTI caused by CA-MRSA or other pathogens controlled by activated MP.