Considered one of the finest first-generation Nigerian writers, John Pepper Clark-Bekederemo, who passed away on 13th October, 2020, had been categorised as a Eurocentric writer. This work assesses the authenticity or otherwise of this critics’ perception of Clark by critiquing his America, their America. By analysing this autobiography vis-à-vis the notion of self and other which is a theoretical concern in contemporary travel writing, it was established, among other things, that every culture has its dark sides which it must not feel too proud to change as time and situation demand; that Clark vehemently rejects the Americans’ claim of sophistication and superiority of their culture over African culture. The paper concludes that contemporary travel writing should be a rightful site for negotiating cultural, political and diplomatic compromises between the Self and the Other since the gulf may be difficult to close altogether.

With the great development of intelligent transportation systems (ITS), travel time prediction has attracted the attentions of many researchers and a large number of prediction methods have been developed. However, as an unavoidable topic, the predictability of travel time series is the basic premise for travel time prediction has received less attention than the methodology. Based on the analysis of the complexity of travel time series, this paper defines travel time predictability to express the probability of correct travel time prediction and proposes an entropy-based method to measure the upper bound of travel time predictability. Multiscale entropy is employed to quantify the complexity of travel time series, and the relationships between entropy and the upper bound of travel time predictability are presented. Empirical studies are made with vehicle trajectory data in an express road section. The effectiveness of time scales, tolerance, and series length to entropy and travel time predictability are analysis, and some valuable suggestions about the accuracy of travel time predictability are discussed. Finally, the comparisons between travel time predictability and actual prediction results from two prediction models, ARIMA and BPNN, are conducted. Experimental results demonstrate the validity and reliability of the proposed travel time predictability.

Body temperature responses were recorded during phases of work (waiting to work in close proximity to search site, active work in a search site, and post-work recovery crated in vehicle) in human remains detection dogs during search training. State or federally certified human remains detection dogs (n = 8) completed eight iterations of searching, rotating through six different types of search environments to detect numerous scent sources including partial and complete, buried, hidden, or fully visible human remains. Internal temperature (Tgi) of the body was measured continuously using an ingestible thermistor in the gastrointestinal tract. Mean total phase times were: waiting to work: 9.17 minutes (± 2.27); active work: 8:58 minutes (± 2:49); and post work recovery: 24:04 minutes (± 10.59). Tgi was impacted by phase of work (P < 0.001) with a small increase during active work, with mean peak temperature 39.4 °C (± 0.34 ºC) during that period. Tgi continued to increase for a mean of 7:37 (± 6:04) minutes into the post-work recovery phase in the handler’s vehicle with a mean peak Tgi of 39.66 °C (± 0.41 ºC). No significant increase in temperature was measured during the waiting to work phase, suggesting anticipation of work did not appear to contribute to overall body temperature increase during the waiting to work recovery cycle. Continued increase of gastrointestinal body temperature several minutes after cessation of exercise indicates that risk of heat injury does not immediately stop when the dog stops exercising, although none of the dogs in this study reached clinically concerning body temperatures or displayed any behavioral signs suggestive of pending heat injury. More work is needed to better understand the impact of vehicle crating on post-work recovery temperatures in dogs.

(1) Background: Travel medicine practice has not been a part of practice in the community pharmacies in Japan. However, it’s getting more common for pharmacists to run travel clinic in North America. With ongoing globalization, Japanese pharmacists might be practicing travel medicine in future. This descriptive study is to examine the current knowledge, attitudes, and practices among Japanese community pharmacists. (2) Methods: Invitation to the study was sent to all pharmacies or corporates listed on Nippon Pharmacist Association member list plus one another large size pharmacy chain that was not member of NPhA. Community pharmacists working under those companies received a weblink to the survey. The survey was conducted from June to July 2017 by online questionnaire. (3) Results: The self-declared knowledge level of infectious diseases as well as travel vaccinations was generally low. The frequency of correct answer of the antibiotic resistance in South East Asia was 48.5%. Knowledge level of qunine resistance to Plasmodium falciparum malaria in Ghana and Nicaragua was very low. (4) Conclusions: Japanese community pharmacists are not familiar with travel related infectious diseases and vaccines used in travel medicine. The knowledge on the antibiotic resistance in traveler’s diarrhea and malaria prophylaxis was all low that is consistent with low degree of exposure to travel health questions from patients in daily practice and low percentage of intention to earn travel health certificates.

Over the past couple of decades, Global positioning system (GPS) technology has been utilized to collect large-scale data from travel surveys. As the precise spatiotemporal characteristics of travel could be provided by GPS devices, the issues of traditional travel survey, such as misreporting and non-response, could be addressed. Considering the defects of dedicated GPS devices (e.g., need much money to buy devices, forget to take devices to collect data, limit the simple size because of the number of devices, etc.), and the phenomenon that the smartphone is becoming one of necessities of life, there is a great chance for the smartphone to replace dedicated GPS devices. Although, several general reviews have been done about smartphone-based GPS travel survey in the literature review section in some articles, a systematic review from smartphone-based GPS data collection to travel mode detection has none. The included studies were searched from six databases. The purpose of this review is to critically assess the current literature on the existing methodologies of travel mode detection based on GPS raw data collected by smartphones. Meanwhile, according to the systematic comparison among different methods from data-preprocessing to travel mode detection, this paper could carefully provide the Strengths and Weaknesses of existing methods. Furthermore, it is the crucial step to develop the methodologies and applications of GPS raw data collected by smartphones.

With considerable growth in the Information &amp; Communication Technologies, several smartphone-based mobility platforms have already sprung up and they have the potential of transforming the mobility ecosystem completely. However, mobility-based smartphone app usage pattern across various user groups in Indian cities is unknown, and this knowledge is vital for introducing new consolidated apps-based services. Therefore, using primary data from a survey carried out in Bhopal (India), this article analyses the usage pattern of smartphone apps for trip planning activities and travel outcomes across various user groups at the personal and household level. The research offers empirical indication of relationships between smartphone app usage for trip planning (like departure time, choosing a destination, choosing the mode, se-lecting route, communicating, and coordinating trips, and performing tasks online instead of visiting) and resulting travel outcomes including vehicle kilometers travelled (for purposes like work/education, shopping, and recreation), social gathering, new place visits and group trips. The chi-square test has been used to test and interpret several socioeconomic variables that could in-fluence this relationship, such as gender, age, income, etc. This study's findings provide important behavioral insights that may be useful in policy discussions.

In this research article, we are going to study the concept of the theory of relativity and after extracting the essential information, we will try to find a relation between the theory of relativity and the results we are obtaining through contemporary physics experiments. It has been investigated that traveling in time is not a dream anymore and time can pass at a different rate for some people.

Introduction: Travel-based continuing medical education (CME) has become a popular format for physicians looking to combine education with travel. Emergency Medicine Update Europe is a biennial accredited CME program combining high quality Emergency Medicine education with structured group activities including cycling, hiking and social activities. This unique design incorporates innovative educational practices but as a whole has not yet been evaluated. Methods: This was a participant observation-based, ethnographic-style case study of the Emergency Medicine Update Europe conference in Provence, France in 2015. Participant interviews and embedded observation methods were used to collect data. Data was then analyzed using thematic content analysis techniques. Results: We describe three phenomena from the data that we feel are highly influential in the success of the program and impact on learning. These include “social engagement and a sense of community”; “the value of a stimulating escape” and “the ‘flat’ faculty-learner relationships”. Discussion: These unique features, prioritized by participants, seem to be key to the apparent success of this model over more traditional CME approaches. To our knowledge this is the first empirical research in this area and improves our understanding of how to leverage these more sociologic components for more effective continuing medical education.

In recent years, governments applied intelligent transportation system (ITS) technique to provide several convenience services (e.g., garbage truck app) for residents. This study proposes a garbage truck fleet management system (GTFMS) and data feature selection and data clustering methods for travel time prediction. A GTFMS includes mobile devices (MD), on-board units, fleet management server, and data analysis server (DAS). When user uses MD to request the arrival time of garbage truck, DAS can perform the procedure of data feature selection and data clustering methods to analyses travel time of garbage truck. The proposed methods can cluster the records of travel time and reduce variation for the improvement of travel time prediction. After predicting travel time and arrival time, the predicted information can be sent to user’s MD. In experimental environment, the results showed that the accuracies of previous method and proposed method are 16.73% and 85.97%, respectively. Therefore, the proposed data feature selection and data clustering methods can be used to predict stop-to-stop travel time of garbage truck.

In recent years, local governments have been using transportation card data to monitor the use of public transport and improve the service. However, local governments that are applying a single-fare scheme are experiencing difficulties in using data for accurate identification of real travel patterns, policy decision support, etc. because the information on alighting stops of users is missing. This policy limits its functionality of utilizing data such as accurate identification of real travel patterns, policy decision support, etc. Various studies to overcome this limitation have been conducted in South Korea and other countries to develop es-timation methodologies of alighting stops. Even existing studies introduce an advanced method, we found the margin for better accuracy by combining various estimation methodologies for estimating alighting stops. This study reviewed previously conducted studies to classify data with missing alighting stop information into trip types and then applied an appropriate alighting stop estimation methodology for the characteristics of each trip type by stage. The proposed method is evaluated by utilizing transportation card data of the Seoul metropolitan area and checked the accuracy for each standard of allowable error for sensitivity analysis. Furthermore, the number of trips, accuracy, and valid tag rate were checked for each type to examine the need for classifying the trip types. Finally, our evaluation also examines the impact of classifying trip types on estimation accuracy. The evaluation criteria are accuracy of the number of trips and valid tag rate. The analysis shows that the stage-by-stage estimation methodology based on the trip type proposed in this study can es-timate users’ destinations more accurately than previous studies. Furthermore, based on the construction of nearly 100% valid tag data, this study differs from prior studies.

In order to evaluate the economy of superhighway, on the basis of the analysis of the cost of the ordinary expressway and high speed railway, the cost of superhighway is estimated. On this basis, the standard of the toll of superhighway at all levels is determined by reference to the standard of the construction cost and the toll collection standard of the ordinary expressway. According to the toll collection standard of superhighway and the fuel consumption cost of superhighway at all levels, the cost of single car and the single person cost of superhighway are calculated. Based on the analysis of highway passenger transport, railway passenger transport and civil aviation ticket price, the single person cost per kilometer of the above travel modes is calculated and compared with the single person travel cost per kilometer of superhighway. The results show that the single person cost of superhighway is between 0.29 and 0.47 yuan /km, which is 0.28 yuan /km higher than the highway bus, 0.18 yuan /km higher than the ordinary expressway self driving and 0.23 yuan /km higher than the express train, but 0.78 yuan/km lower than that of the first class seat of high-speed train, and is 0.92 yuan/km far lower than that of civil aviation flight economy class and 2.42 yuan/km lower than the business class. Therefore, the superhighway trip has certain advantages in economy.

A quick scan of the available literature on the subject of halal tourism reveals that many scholars and laypersons alike misconceive this concept. Whereas some suggest that halal tourism occurs whenever a Muslim individual travels somewhere, others retort that only pilgrimages by Muslim travelers regarded as halal tourism. More careful research of the literature shows that the truth is somewhere in between, as none of the above definitions is correct. Overall, it is this lack of clarity that has prompted an additional inquiry into the essence of halal tourism. This essay is a modest academic endeavor to ascertain what halal tourism is and what ideologies lie at its foundation. To answer these questions, the author employs the literature review research methodology, scrutinizing number sources. Ultimately, this essay has established that halal tourism not confined to religious pilgrimages alone. Indeed, halal tourism occurs whenever a Muslim individual travels for religion, business or leisure and uses only those services and facilities that conform to the teachings of Islam.

This chapter is written for the welfare of the society, questioning and enlightening the effects of the increment or decrement in the percentage of quality of air causing pollution due to the rise in the traffic post-lockdown due to COVID-19 in metro cities, specifically in Delhi. In this chapter, we address the question about people's preference in moving in the shared taxis to their workplaces or their reluctance and denial of the idea of moving in the shared vehicle because of the fear of getting infected. The sensitivity of the situation will compel the people to move in a single occupied vehicle (SOV). The rise in the number of vehicles on the roads will result in traffic jams and different kinds of pollution where people battling with the pandemic will inevitably get exposed to other health-related issues. We use a BPR (Bureau of Public Roads) model to combat this issue endangering the environment and public health. We exploit the BPR function to relate average travel time to the estimated number of commuters travelling by car. We collect mode share data from the NITI Ayog, the State Resource Centre and other authentic sources, which gives unique figures of the impact of shared mobility in India and how, in its absence, various sectors will get affected. Using the given data and the BPR, we evaluate increased vehicle volumes on the road if different portions of transit and carpool users switch to single-occupancy vehicles and its effect on multiple other factors. Based on the study of densely populated city, Delhi, we predict that cities with significant transit ridership are at risk for extreme traffic and pollution unless transit systems can resume safe with effective protocols.

Identifying group movement patterns of crowds and understanding group behaviors is valuable for urban planners, especially when the groups are special such as tourist groups. In this paper, we present a framework to discover tourist groups and investigate the tourist behaviors using mobile phone call detail records (CDRs). Unlike GPS data, CDRs are relatively poor in spatial resolution with low sampling rates, which makes it a big challenge to identify group members from thousands of tourists. Moreover, since touristic trips are not on a regular basis, no historical data of the specific group can be used to reduce the uncertainty of trajectories. To address such challenges, we propose a method called group movement pattern mining based on similarity (GMPMS) to discover tourist groups. To avoid large amounts of trajectory similarity measurements, snapshots of the trajectories are firstly generated to extract candidate groups containing co-occurring tourists. Then, considering that different groups may follow the same itineraries, additional traveling behavioral features are defined to identify the group members. Finally, with Hainan province as an example, we provide a number of interesting insights of travel behaviors of group tours as well as individual tours, which will be helpful for tourism planning and management.

Understanding tourist behaviour during and after major tourism crises is essential to help destinations recover. The COVID-19 pandemic, a period of uncertainty and risk, makes it relevant to assess factors that influence travel intentions. There has been little research on tourist behaviour during health crises and, in particular, on perceived health risk and uncertainty effects on travel intentions. This study was carried out during the first months of the pandemic in Brazil and aims to investigate the role of health risk perception and intolerance of uncertainty on travel intentions for 2020 and 2021. We applied an online survey to 1,150 Brazilian participants from March to May of 2020. Our findings indicate that perceived COVID-19 severity, perceived probability of contracting it, and expected pandemic duration are significant predictors of travel intentions for both years. This paper sheds new light on tourist behaviour in the context of global health crises.

Nearly three months have passed since the emergence of the severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2), which caused the rapidly spreading Coronavirus Disease 2019 (COVID-19) pandemic. To date, there have been more than 550,000 confirmed cases and more than 25,000 deaths globally caused by COVID-19. Chinese health authorities, where the virus emerged, have taken prompt strict public health measures to control and prevent the spread of the outbreak. In the kingdom of Saudi Arabia, unprecedented precautionary strict measures were applied to slow virus entry and to mitigate the risk of the outbreak. Here, we review the experience learned during the Middle East Respiratory Syndrome Coronavirus (MERS-CoV) epidemic in Saudi Arabia, which has been in the country since 2012, and is expected to have helped the country to be well prepared for the current COVID-19 pandemic. We also discuss the country readiness, improvement in research and development, and the unprecedented rapid precautionary measures that have been taken by the Saudi government thus far.

While micromobility has seen a significant rise of interest across policy, industry and academia, a detailed conceptualisation of it has so far been missing from the scientific literature. This paper develops a multi-dimensional conceptualisation of micromobility, in conjunction with a new socio-technical definition. To do so, it reviews related concepts; it analyses how the term micromobility has been used; and it critically engages with existing definitions most frequently cited in this literature. Building on these insights, we develop a multi-dimensional conceptualization of micromobility. Our definition of micromobility covers a wide range of mobility options that can typically be manoeuvred by one human without motor assistance, at least for short distances, and that are ‘micro’ in terms of energy demand, environmental impact, and use of road space, relative to automobility. According to our conceptualisation, micromobility modes comprise fully human powered, partially motor assisted and fully powered options. They typically do not exceed 25 kilometres per hour (or 45 for faster ones) and weigh (often significantly) less than 350 kilogram, while often providing some (public) health benefits. Trip lengths are typically less than 15 kilometres and daily distance travelled less than 80 kilometres. This new definition has relevance for future transport and mobility scholarship, as well as policy and evaluation. Advantages of a new and widely accepted definition and conceptualisation of micromobility could include more robust design standards, legislation, as well as evaluation metrics and methods, all leading to greater understanding of, and attention paid to, this form of mobility. This paper highlights the important role that micromobilities could play in moving beyond automobility, to create more sustainable and just mobility futures.

The aim of this work is to assess the influence of Friction Stir Welding (FSW), process parameters, optimized tool traveling speed, and corrosion resistance of the 0.95 Mg-Al-alloy and pure copper weldment. Samples of aluminum-copper with and without deformation were characterized to investigate the metallurgical effects created during the welding deformation process. Effect of process parameters on microstructure and corrosion rate have been investigated for all the samples. All the electrochemical and polarization tests were done in 3.5 wt.% NaCl solution. Scanning Kelvin Probe (SKP) was done to detect the localized corrosion on the surface. Optical micrography observation indicated that the primary α-Al phase, which was formed during solidification can effectively limit the growth of Cu₉Al₄ phase. Finer acicular α-Al precipitates were observed in CuAl matrix during joining process that tends to coarser with the increase in tools travel speed. The electrochemical and polarization results showed that among all the tool travelling speed the specimen joined at tool travelling speed of 40 mm/min shows the best non-corrosive property.

The purpose of this study was to report data analysis results from the International Health Regulations (2005) Ship Sanitation Certificates (SSC), recorded in the European Information System (EIS). International sea trade and population movements by ships can contribute to the global spread of diseases. SSC are issued to ensure the implementation of control measures if public health risk exists on board. EIS designed according to the World Health Organization (WHO) “Handbook for Inspection of Ships and Issuance of SSC”. Inspection data were recorded and SSC issued by inspectors working at European ports were analysed. From July 2011-February 2017, 107 inspectors working at 54 ports in 11 countries inspected 5579 ships. Of these, there were 29 types under 85 flags (including 19 EU flags). As per IHR (2005) 10,281 Ship Sanitation Control Exception Certificates (SSCEC) and 296 Ship Sanitation Control Certificates (SSCC) were issued, 74 extensions to existing SSC were given, 7565 inspection findings were recorded, and 47 inspections were recorded without issuing an SSC. The most frequent inspection findings were the lack of potable water quality monitoring reports (23%). Ships aged ≥12 years (Odds Ratio, OR = 1.77, 95%Confidence Intervals, CI = 1.37–2.29) with an absence of cargo at time of inspection (OR = 3.36, 95%CI = 2.51–4.50) had a higher probability of receiving an SSCC, while ships under the EU flag had a lower probability of having inspection findings (OR = 0.72, 95%CI = 0.66–0.79). Risk factors to prioritise the inspections according to IHR were identified by using the EIS. A global information system, or connection of national or regional information systems and data exchange, could help to better implement SSC using common standards and procedures.

This study introduces a comparative analysis of two deep learning (multilayer perceptron neural networks (MLP-NN) and the long short term memory networks (LSTMN)) models for transit travel time prediction. The two models were trained and tested using one-year worth of data for a bus route in Blacksburg, Virginia. In this study, the travel time was predicted between each two successive stations to all the model to be extended to include bus dwell times. Additionally, two additional models were developed for each category (MLP of LSTM): one for only segments including controlled intersections (controlled segments) and another for segments with no control devices along them (uncontrolled segments). The results show that the LSTM models outperform the MLP models with a RMSE of 17.69 sec compared to 18.81 sec. When splitting the data into controlled and uncontrolled segments, the RMSE values reduced to 17.33 sec for the controlled segments and 4.28 sec for the uncontrolled segments when applying the LSTM model. Whereas, the RMSE values were 19.39 sec for the controlled segments and 4.67 sec for the uncontrolled segments when applying the MLP model. These results demonstrate that the uncertainty in traffic conditions introduced by traffic control devices has a significant impact on travel time predictions. Nonetheless, the results demonstrate that the LSTMN is a promising tool that can has the ability to account for the temporal correlation within the data. The developed models are also promising tools for reasonable travel time predictions in transit applications.

Traditional travel agencies and tour operators are recognized as relevant stakeholders in the tourism distribution chain, even though their role as transforming agents in the achievement of more sustainable tourism is beginning to be accepted. This document collects the main topics and the most recent approaches from the academic literature in its analysis of Corporate Social Responsibility (CSR) practices developed by these intermediaries. The work has been structured around six recurring themes in most of the studies carried out: the new intermediaries that operate on the Internet; the role of travel agencies and tour operators in tourism sustainability; the influence of the size of the company; CSR as a disruptive innovation in this sector; the potential of the sustainable tourism supply chain; and the motivations and attitudes of the managers of these businesses when they engage with responsibility. This last topic is developed in greater detail since it is closely linked to the previous ones and dictates in most cases the meaning and function of the sustainable performance.

This study attempts to investigate a method for creating an index from mobility data that not only correlates with the number of people who relocate to a place but also has causal influence on the number of such individuals. By creating an index based on human mobility data, it becomes possible to predict the influence of urban development on future residential movements. In this paper, we propose a method called the travel cost method for multiple places (TCM4MP) by extending the conventional travel cost method (TCM). We assume that the opportunity cost of travel time on non-working days reflects the convenience and amenities of a neighborhood. However, conventional TCM does not assume that the opportunity cost of travel time varies according to the departure place. In this paper, TCM4MP is proposed to estimate the opportunity cost of travel time with respect to the departure place. We consider such estimation to be possible due to the use of massive mobility data. We assume that the opportunity cost of travel time on non-working days reflects the convenience and amenities of the neighborhood. Therefore, we consider that the opportunity cost of travel time has a causal influence on future residential mobility. In this paper, the validity of the proposed method is tested using the smart card data of public transportation in Western Japan. Our proposed method is beneficial for urban planners in estimating the effects of urban development and detecting the shrinkage and growth of a population.

To estimate the recreational value provided by the Foy’s Lake annually using the most applicable model for on-site data is the main objective of this study. Adhere to the objective of this study; Individual Travel Cost Method (ITCM) has been applied and Zero Truncated Poisson Regression Model has been found plausible among other models to estimate consumer surplus. Based on the findings of the study, an estimate of the consumer surplus or recreational benefits per trip per visitor can be recommended as BDT 5,875 or US $ 73.44 and counting the consumer surplus per trip per visitor, the annual recreational value (total consumer surplus) provided by the lake is found to be BDT 321 million or US $ 40.2 million.

Studying Active Transportation (AT) is widespread in America and Europe's research and stud-ies that include Latent variables (LV) are growing to identify exact results of finding what to do to increase the utility of AT. LVs help us to have more accurate research. LVs are defined as psy-chological factors like feeling safe while you ride at night and thus they are not subjective and hard to understand but very important to increase the utility of using AT modes. In this study, most of the previous studies about bicycling have been reviewed. In this research, different var-iables including subjective and LVs are conducted for maximizing the use of bicycle utility and introduced to have better sight for future researchers to deal with modeling AT mode choice. Results represent the importance of having 'will' for using a bicycle, especially in difficult situa-tions and cultural barriers that affect the cycling of women.

COVID-19 vaccination certificates (CVCs) have played a key role in safe reopening of borders for international travel and trade, so understanding key stakeholder perceptions of enablers and barriers for their effective use is critical. The COVID-19 Vaccination Policy Research and Deci-sion-Support Initiative in Asia (CORESIA) was established to address policy questions related to CVCs. We conducted two online surveys, i.e., one for the public and one for health and non-health sector experts, from June to October 2021 in nine Asian countries. Descriptive analysis identified participants, enablers, and barriers. Most participants (78% public, 89% experts) accepted the use of CVCs, primarily to resume international travel (76%). Most respondents in both surveys wanted the minimum vaccination coverage to be 60% before CVCs were implemented nation-wide. Most of the public (82%) agreed to maintain existing non-pharmaceutical interventions, while most experts wanted risk-based testing and quarantine policy for incoming travellers (51%) and both digital and paper format CVCs (64%). Support for CVCs for international travel remains high in Asia. Recognising key enablers and barriers for effective use of CVCs from COVID-19 pandemic may help policymakers draft effective border policies for future epidemics.

With growing city tourism, there is an increasing need for urban travel demand models to consider traffic generated by visitors. Existing research has concentrated on socio-demographic and journey-related factors to determine what influences the mode choice of tourists. In contrast, revealed preference data, like travel time, is almost never considered. In this article, we present the results of discrete choice modeling of city tourists’ mode choice based on revealed preference data from a survey we conducted in Kassel, Germany. We used multinomial logit models and determined the model parameters using maximum likelihood estimations. Surprisingly, travel time played a smaller role in mode choice than understood from previously established knowledge about everyday mobility. In the final model, travel time was only significant for the alternative walking. Also, most other sociodemographic and journey-related variables showed no significant influence. The final model reproduced the mode choice, but the goodness of fit was lower than expected from other research. We conclude that modeling the travel behavior of tourists is more complex than everyday mobility. An alternative approach that we suggest would be to model trip chains rather than single trips.

In 1982, MIT physicist Frank Wilczek predicted and named ANYONS, quasiparticles (particle-like formations) that are confined to 2 dimensions and were discovered in 2020. The name might come from Prof. Wilczek's lighthearted comment "anything goes". This article's main goal is to show that anyons could be another name for 1) virtual particles, 2) Mobius strips, and 3) figure-8 Klein bottles. Along the way, we'll see the picture painted by the article confirm that Einstein's dream of gravitational-electromagnetic unity fits in with anyons being Mobius strips. The topological hypothesis offers an explanation of dark matter and dark energy. We'll also have encounters with intergalactic travel and imaginary computers. They really could exist but are imaginary in the sense that they use imaginary time (as well as space-time warping).

Alternative fuel vehicles, such as battery electric vehicles and hydrogen fuel cell vehicles, support the imperative to decarbonise the transport sector, but are not yet at a stage in their development where they can successfully compete with conventional fuel vehicles. This paper examines the influence of knowledge and persuasion on the decision to adopt or reject alternative fuel vehicles, underpinned by Rogers’ Diffusion of Innovations theory. A household questionnaire survey was undertaken with respondents in the Sutton Coldfield suburb of the United Kingdom city of Birmingham. This suburb was previously identified as having a strong spatial cluster of potential early adopters of alternative fuel vehicles. The results confirm that among respondents the knowledge of alternative fuel vehicles was limited and perceptions have led to the development of negative attitudes towards them. The reasons largely relate to three problems: purchase price, limited range, and poor infrastructure availability. The majority of respondents have passively rejected alternative fuel vehicles, such that they have never given consideration to adoption. This confirms that a concerted effort is required to inform the general public about alternative fuel vehicles.

The objective of this paper was to give an overview of the expressed preference (EP) techniques of environmental valuation. These methods offer estimation of the value of a resource not necessarily willingness to pay (WTP) or willingness to Accept (WTA) compensation rather upper and lower values. The method of measuring individuals’ willingness to pay is usually based on contingent valuation method (CVM). This research focuses on defining, categorizing, and applicability of various environmental valuation techniques that have been and can be applied in attaching value to a given resource using expressed/Revealed preference methods. The study serves as a supplementary synthesis and discussion to the board of knowledge of resource valuation methods. More specifically, selected methods to discussed herein include; contingent valuation method, hedonic pricing model, travel cost method, trade-off game method, the costless-choice method, Delphi method, Replacement Cost Method, Relocation Cost Method, Opportunity cost method, and Cost-benefit Method. In the last part, applicability of the methods is fully illustrated to support future studies on resource valuation.

Fresh water springs are unique natural resources in Florida, currently under threat from increasing groundwater pumping and pollution resulting from a variety of sources. This paper estimates current recreation benefits from visiting springs using the travel cost method and elicits residents’ willingness to contribute for springs restoration using the contingent valuation method. It further compares the performance of count data models correcting for endogenous stratification and truncation, and finds that the annual consumer surplus per person per trip is between $20 and $43. Furthermore, visitors are willing to contribute $12 to $14 per person per trip for springs restoration without reducing trip demand.

Objectives to assess COVID-19 mortality rates per country population. To determine what if any independent country-specific variables from 9 different databases were correlated. Design population based retrospective cohort study. Setting analysis of global COVID-19 treatment and containment strategies using data from 9 worldwide websites. Participants 108 countries worldwide. Interventions none. Main Outcome Measures were COVID-19 death rates per country population analyzed by univariate and multivariate analysis. The main outcome parameters were to determine if there are any correlations between the percentage of countrywide COVID-19 deaths/population by the countries’ percent vaccinated. Secondary outcome measures include the effect of other independent variables on COVID-19 death rates per country population including: health expenditures per capita, annual income per capita, COVID-19 tests per 1000 people, stringency index (a measure of each countries containment strategies), hydroxychloroquine score (a measure of each countries use), ivermectin score (a measure of each countries use), hypertension, obesity, diabetes, and specific countries and geographic locations. Results COVID-19 vaccination rates ranged from 0-99% in 108 countries. Univariate analysis demonstrates the following independent variables to correlate with COVID-19 deaths/population (correlation coefficient, p value): countrywide COVID-19 vaccination rates (+0.2936, p=0.002); healthcare costs per capita (+0.3212, p=0.0007), income per capita (+0.3051, p=0.0013), COVID-19 tests per 1000 population (+0.6981 p=0.0307); stringency index (+0.3098, p=0.0011); hydroxychloroquine index (-0.1337, p=0.0678); and ivermectin index (-0.1383, p=0.1535). Conclusions Increasing rates of COVID-19 vaccination are associated with increase COVID-19 death rates per country population (p=0.002). Other variables associated include healthcare costs per capita (+0.3212, p=0.0007), income per capita (+0.3051, p=0.0013), COVID-19 tests per 1000 population (+0.6981 p=0.0307); and stringency index (+0.3098, p=0.0011).

Acute high altitude illnesses are of great concern for physicians and people traveling to high altitude. High Altitude Pulmonary Edema (HAPE) can be better understood through the Oxygen Transport Triad which involves the Pneumo-Dynamic Pump (Ventilation), the Hemo-Dynamic Pump (Heart and circulation), and Hemoglobin. The two pumps are the first physiologic response upon initial exposure to hypobaric hypoxia. Hemoglobin is the balancing energy-saving time-evolving equilibrating factor. The increased hemoglobin at high altitude reduces the percentage of dissolved oxygen in the arterial oxygen content with respect to sea level. At high altitude, the acid-base balance must be adequately interpreted using the high altitude Van-Slyke correction factors. Pulse-oximetry measurements during breath-holding at high altitude allow for the evaluation of high altitude diseases. The Tolerance to Hypoxia Formula shows that, paradoxically, the higher the altitude the more tolerance to hypoxia. All organisms adapt physiologically and optimally to a high-altitude environment to survive. Reduction of pulmonary hypertension in HAPE through oxygen administration results in a favorable outcome.