Abstract: The COVID-19 pandemic is unprecedented in terms of its global reach and economic impacts. Historically, investment in infrastructure development projects has been touted to boost the economic growth of a nation. The State and Local governments responsible for delivering infrastructure assets work under tight budgets. Therefore, it is important to understand which infrastructure projects have the highest potential of boosting economic growth in the post-pandemic era. This paper presents relationships between infrastructure projects and economic growth. Statistical relationships between investment in different types of infrastructure projects (transit, water and wastewater, highways, power, manufacturing etc.) and indicators of economic growth are presented using historic data between 2002 and 2020 from the U.S. Census Bureau and U.S. Bureau of Economic Analysis (BEA). The outcome of the paper is the comparison of statistical correlations between investment in different types of infrastructure projects and indicators of economic growth. The comparison of the statistical correlations is useful in ranking the types of infrastructure projects based on their ability to influence economic prosperity. Therefore, investment in the infrastructures with the higher rank will have a better chance of boosting the economic growth. Once, the ranks are derived, they can be used by the decision-makers in infrastructure investment related decision-making process.
Abstract: In a time period populated by legacy newspaper readers who throw around the term “fake news” as though it has long been a part of the lexicon, journalism schools must convince would-be students that their degree is still viable and that they are not teaching a curriculum of deception. As such, journalism schools’ academic administrators tasked with creating and maintaining conversant curricula must stay ahead of legacy newspaper industry trends – both in the print and online products – and ensure that what is being taught in the classroom is both fresh and appropriate to the demands of the evolving legacy newspaper industry. This study examines the information obtained from the result of interviews of journalism academic administrators in order to identify institutional pedagogy for recent journalism school graduates interested in pursuing careers at legacy newspapers. This research also explores the existing relationship between journalism school academic administrators and legacy newspaper editors. The results indicate the value administrators put on various academy teachings, and they also highlight a perceived disconnect between journalism academic administrators and legacy newspaper hiring editors.
Abstract: In agricultural production and breeding, implementing automatic picking robot in orchard farming to reduce human labour and error is challenging. The core function of it is automatic identification based on machine vision. This paper focuses on apple detection and counting in orchards and implements several deep learning methods. Extensive datasets are used and a semi-automatic annotation method is proposed. The proposed deep learning models are in state-of-the-art YOLO family. In view of the essence of the models with various backbones, a multi-dimensional comparison in details is made in terms of counting accuracy, mAP and model memory, laying the foundation for realising automatic precision agriculture.
Abstract: Detecting subjectively biased statements is a vital task. This is because this kind of bias, when present in the text or other forms of information dissemination media such as news, social media, scientific texts, and encyclopedias, can weaken trust in the information and stir conflicts amongst consumers. Subjective bias detection is also critical for many Natural Language Processing (NLP) tasks like sentiment analysis, opinion identification, and bias neutralization. Having a system that can adequately detect subjectivity in text will boost research in the above-mentioned areas significantly. It can also come in handy for platforms like Wikipedia, where the use of neutral language is of importance. The goal of this work is to identify the subjectively biased language in text on a sentence level. With machine learning, we can solve complex AI problems, making it a good fit for the problem of subjective bias detection. A key step in this approach is to train a classifier based on BERT (Bidirectional Encoder Representations from Transformers) as upstream model. BERT by itself can be used as a classifier; however, in this study, we use BERT as data preprocessor as well as an embedding generator for a Bi-LSTM (Bidirectional Long Short-Term Memory) network incorporated with attention mechanism. This approach produces a deeper and better classifier. We evaluate the effectiveness of our model using the Wiki Neutrality Corpus (WNC), which was compiled from Wikipedia edits that removed various biased instances from sentences as a benchmark dataset, with which we also compare our model to existing approaches. Experimental analysis indicates an improved performance, as our model achieved state-of-the-art accuracy in detecting subjective bias. This study focuses on the English language, but the model can be fine-tuned to accommodate other languages.
Abstract: This study presents an investigation of diesel vehicle particulate-phase emissions with neat ultralow sulphur diesel (B0, ULSD) and 5% waste cooking oil-based biodiesel blend (B5) in Hong Kong. A Euro VI light duty diesel vehicle was tested under transient (New European Driving Cycle (NEDC)), steady-state and idling on a chassis dynamometer. Chemical analyses including organic carbon (OC), elemental carbon (EC), as well as 30 polycyclic aromatic hydrocarbons (PAHs) and 10 oxygenated PAHs (oxy-PAHs) were conducted. The OC fuel-based emission factors (EFs) for B0 ranged from 2.86 ± 0.33 to 7.19 ± 1.51 mg/kg, and those for B5 ranged from 4.31 ± 0.64 to 15.36 ± 3.77 mg/kg, respectively. The EFs of EC were low for both fuel blends (0.25 mg/kg or below). With B5, the EFs of total PAHs were decreased as compared to B0. Specifically, B5 reduced total PAH emissions by 50.2%, 30.7%, and 15.2% over NEDC, steady-state and idling, respectively. It was found that when B5 was used, PAHs and oxy-PAHs with lower molecular weight (2 to 3 rings) were reduced whereas PAHs/oxy-PAHs with medium or high molecular weight (4 to 7 rings) were increased. Our study suggests the necessity of taking atmospheric and health factors into account for biodiesel application as an alternative motor fuel.
Abstract: This paper presents the research and application of model predictive scheduled charging of electric vehicles (EV) subject to limited available power resource. To focus on algorithm and operational characteristics, the EV interface to the source is modelled as a battery state equation during the charging operation. The researched methods allow for the priority scheduling of EV charging in a multi-vehicle regime and when subject to limited source power availability. Priority attribution for each connected EV is described. The validity of the developed methodology is shown through the simulation of different scenarios of charging operation of multiple connected EVs including non-scheduled and scheduled operation with various numbers of vehicles. Performance of the developed algorithms is also reported with the recommendation of the choice of suitable parameters.
Abstract: The requirement for maintaining data integrity in laboratory operations is critical for regulatory compliance. Automation of procedures reduces incidence of human errors. Quality control laboratories located in low-income economies may face some barriers in attempts to automate their processes. Since data from quality control tests on pharmaceutical products are used in making regulatory decisions, it is important that laboratory reports are accurate and reliable. Zinc Sulphate (ZnSO4) tablets is used in treatment of diarrhea in pediatric population, and as an adjunct therapy for COVID-19 regimen. Unfortunately, zinc content in these formulations is determined titrimetrically; a manual analytical procedure. The assay for ZnSO4 tablets involves time-consuming steps that contain mathematical formulae prone to calculation errors. To achieve consistency, save costs, and improve data integrity, validated spreadsheets were developed to simplify the two critical steps in the analysis of ZnSO4 tablets: standardization of 0.1M Sodium Edetate (EDTA) solution, and the complexometric titration assay procedure. The assay method in the United States Pharmacopoeia was used to create a process flow for ZnSO4 tablets. For each step in the process, different formulae were input into two spreadsheets to automate calculations. Further checks were created within the automated system to ensure validity of replicate analysis in titrimetric procedures. Validations were conducted using five data sets of manually computed assay results. The acceptance criteria set for the protocol were met. Significant p-values (p < 0.05, α = 0.05, at 95% Confidence Interval) were obtained from students’ t-test evaluation of the mean values for manual-calculated and spreadsheet results at all levels of the analysis flow. Right-first-time analysis and principles of data integrity were enhanced by use of the validated spreadsheet calculators in titrimetric evaluations of ZnSO4 tablets. Human errors were minimized in calculations when procedures were automated in quality control laboratories. The assay procedure for the formulation was achieved in a time-efficient manner with greater level of accuracy. This project is expected to promote cost savings for laboratory business models.
Abstract: The privacy paradox describes a phenomenon whereby there is no connection between stated privacy concerns and privacy behaviours. We need to understand the underlying reasons for this paradox if we are to help users to preserve their privacy more effectively. In particular, the Social Networking System (SNS) domain offers a rich area of investigation due to the risks of unwise information disclosure decisions. Our study thus aims to untangle the complicated nature and underlying mechanisms of online privacy-related decisions in SNSs. In this paper, we report on the findings of a Systematic Literature Review (SLR) that revealed a number of factors that are likely to influence online privacy decisions. Our deductive analysis approach was informed by Communicative Privacy Management (CPM) theory. We uncovered a lack of clarity around privacy attitudes and their link to behaviours, which makes it challenging to design privacy-protecting SNS platforms and to craft legislation to ensure that users’ privacy is preserved.
Abstract: Based on a convenience sample of 2,092 participants from across all 50 states of the United States, a survey was conducted to explore Americans’ mask-wearing behaviors during COVID-19 according to their political convictions, religious beliefs, and ethnic cultures from late July to early September, 2020. The purpose of the study is to provide evidential support for government policymaking so as to drive up more effective public policies by taking into consideration the variance in these social factors. It was found that the respondents’ party affiliation or preference, religious belief, and ethnicity, in addition to their health condition, gender, level of concern of contracting COVID-19, all affected their mask-wearing habits both in March, the initial coronavirus outbreak stage, and in August, when mask-wearing had been made mandatory by state governments. The study concludes that pandemic awareness campaigns must be run among all citizens, especially among African Americans, Muslims, and Republicans, who have the lowest rates of wearing masks, in order to protect themselves and others. It is recommended that complementary cognitive bias awareness programs should be implemented in non-Black and non-Muslim communities to eliminate social concerns that deter them from wearing masks.
Abstract: This paper focuses on a sense of belonging, isolation, and the use of a learning management system as a “third space” for connection and community. Given student use of learning management systems (LMS) for courses on campuses, moderate to high use of social media and hand-held devices, the author explores the possibilities of LMS as a third space. The COVID-19 pandemic has exacerbated student experiences of isolation, and research indicates that students who experience a sense of belonging have a greater likelihood for academic retention and success. The impacts on students of an LMS designed for student employee orientation and training were examined through a mixed methods approach, including a survey, individual interviews, and focus groups. The sample involved 250-450 undergraduate student employees at a US northwestern university. The goal of the study was to find out the efficiency and effectiveness of the orientation information for a wide range of student employees from multiple student affairs departments. And unexpected finding emerged within the study in 2015 and was noted again as a finding in the 2017 study. Students reported feeling like they individually connected to the department, and further to the university because of the LMS orientation. They stated they could see themselves as part of the university community and like they belonged. The orientation, through the LMS, was designed for and occurred online (asynchronous), prior to students traveling and beginning university life for the academic year. The students indicated connection and belonging resulting from some of the design features. With the onset of COVID-19 and prolonged sheltering in place in North America, as well as other parts of the world, students have been precluded from physically gathering to educate and learn. COVID-19 essentially paused face-to-face education in 2020. Media, governments, and higher education outlets have been reporting on widespread college student stress, isolation, loneliness, and sadness. In this context, the author conducted a current mixed methods study (online survey, online interviews) of students in advanced degree programs, like Ph.D. and Ed.D. specifically investigating isolation and sense of belonging. As a part of the study a prototype of a Canvas site was experienced by student interviewees for their reaction of this Canvas site prototype as a “third” space. Some preliminary findings of this study are presented. Doctoral students in the study affirmed the potential of LMS as a third space for community and social academic connection.
Abstract: In this study, experiments were carried out to achieve a promising multifunctional and modified silicate based bioactive glass (BG). The main aim of the study was investigating the effect of lithium (Li) and magnesium (Mg) substitution, on in vitro bioactivity of substituted-58S BG. Moreover, it is noteworthy to state that modified BGs were synthesized in 60SiO2–(36-x)CaO–4P2O5–(x)Li2O and 60SiO2–(36-x)CaO–4P2O5–(x)MgO (where x = 0, 5, 10 mol.%) quaternary systems, by sol-gel method. Their performance was investigated through different aspects such as biocompatibility, antibacterial activity as well as their effect on alkaline phosphatase (ALP) activity, and proliferation of MC3T3 cells. The antibacterial efficiency was evaluated against methicillin-resistant Staphylococcus aureus bacteria. To do so, CaO was substituted with Li2O and MgO up to 10 mol % in 58S-BGs and then samples were immersed in simulated body fluid up to 14 days and then, characterized by X-ray diffraction, Fourier transform infrared spectroscopy, inductively coupled plasma atomic emission spectrometry, and scanning electron microscopy. Results indicated that this modification led to a retarding effect on in vitro hydroxyapatite (HA) formation due to the lower supersaturation degree for nucleation of HA compared with 58s-BG. Meanwhile, magnesium revealed further pronounced effect. The 3-(4,5 dimethylthiazol-2-yl)-2,5 diphenyltetrazolium bromide (MTT) and ALP analysis illustrated that substitutions of both Li2O and MgO, up to 5 mol %, had increasing effect on biocompatibility and stimulating proliferation of the pre-osteoblast MC3T3 cells in comparison to the control specimen. Regarding to bactericidal efficiency, the substitution of either Li or Mg for Ca in the 58s BG composition led to statistically significant difference in antibacterial behaviors of substituted-BGs. Meanwhile, the sample containing 5 mol % CaO/Li2O substitution (BG-5L) was selected as a multifunctional biomaterial in bone repair/regeneration due to the improved biocompatibility, enhanced ALP activity and antibacterial efficiency among all of the synthesized L-BGs and M-BGs.
Abstract: In order to determine the importance of small-system riverine heat flux on regional landfast sea ice breakup, our study explores the annual spring freshet of the Sagavanirktok River from 2014-2019. Seasonal heat cycling ultimately serves as the driving mechanism behind the freshet; however, as an emerging area of study, the extent to which inland thermodynamics influence coastal tundra geomorphology and connected landfast sea ice has not been extensively investigated in relation to small-scale Arctic river systems. The Sagavanirktok River is a small-to-midsized river system that flows south-to-north on the Alaskan North Slope from the Brooks mountain range to the Beaufort Sea at Prudhoe Bay. Seasonal warming in the spring rapidly melts snow and ice in a northwards progression from the Brooks Range and transitional tundra highlands towards the coast and when coupled with seasonal precipitation, results in a pulsed freshet that propagates through the Sagavanirktok River. The concentrated presence of newly exposed vegetation in the transitional tundra region due to spring melting results in higher absorption of solar radiation due to a lower albedo relative to snow-covered tundra and/or landfast sea ice. This results in spring flood runoff that advances over impermeable early-season permafrost soils with elevated temperatures relative to landfast sea ice and sub-ice flow. We examine the extent to which interannual temporal variability influences the onset and magnitude of river discharge by analyzing field measurements from the United States Geological Survey (USGS) river and meteorological observation sites. Rapid influx of heat to the Arctic Ocean via riverine systems results in a noticeable decay of landfast sea ice independent of ice breakup seaward of the shear zone. Utilizing MODIS imagery from NASA’s Terra satellite, interannual variability of river discharge is visualized, allowing for optical validation that the discharge flow is interacting with landfast sea ice. Thermal erosion experienced by sediment fast ice at the arrival of warm overflow preconditions the ice regime for rapid thawing. We investigate the extent to which interannual heat flux from the Sagavanirktok River’s freshet significantly influences the onset of local landfast sea ice breakup. The early-season warming of atmospheric temperatures is evidenced by the presence of storms which introduce liquid, rather than frozen, precipitation into the system. The resultant decreased albedo of the transitional tundra supports the positive relationship between early-season precipitation events, inland thermodynamic cycling, and degradation of landfast sea ice. Early removal of landfast sea ice increases coastal erosion in these regions and has implications for coastline geomorphology which stress industrial, ecological, and humanitarian infrastructure.
Abstract: A high pressure carbon dioxide (CO2) absorption from a specific gas in a conventional column has been evaluated by the Aspen HYSYS simulator using a wide range of single absorbents and blended solutions to estimate the outlet CO2 concentration, absorption efficiency and CO2 loading to choose the most proper solution in terms of CO2 capture for environmental concerns. The property package (Acid Gas-Chemical Solvent) which is compatible with all applied solutions for the simulation in this study, estimates the properties based on an electrolyte non-random two-liquid (E-NRTL) model for electrolyte thermodynamics and Peng-Robinson equation of state for the vapor and liquid hydrocarbon phases. Among all the investigated single amines as well as blended solutions, piperazine (PZ) and the mixture of piperazine and monoethanolamine (MEA) have been found as the most effective absorbents respectively for CO2 absorption with high reactivity based on the simulated operational conditions.
Abstract: In recent years, the number of individuals experiencing homelessness has increased in the United States. This paper analyzes 2019 data from 16 different emergency shelters in Monroe County, located in Upstate New York. The data were collected through the County’s Homeless Management Information System (HMIS), and individuals were de-identified and de-duplicated for analysis. The purpose of this study is to explore the basic characteristics of the homeless population in Monroe County, and the dynamics of shelter use. The results of this study showed gender as a significant factor when analyzing the relationship between demographic variables and recorded reasons for shelter entry. Results also indicated that age and ethnicity did not significantly influence odds of re-entering a shelter, but did significantly influence reasons for shelter entry. Overall, the most common recorded cause of shelter entry in 2019 in the examined county was eviction by primary tenant. Recommendations to better address recurrent shelter entry and potential chronic homelessness include more consideration for the diversity existing within the homeless population, and the dynamics leading to shelter stays, including enhanced funding and training for shelter staff, as well as expanded access to permanent supportive housing programs.
Abstract: This paper highlights the empirical results of analyzing the correlation between accounting information and systematic risk. This association is analyzed among financial ratios and systematic risk by considering the financial statement of 39 companies listed on the Tehran Stock Exchange (TSE) for five years (2014-2018). Financial ratios have been categorized into four groups and to describe the special features, as representative of accounting information we selected: Return on Asset (ROA), Debt Ratio (Total Debt to Total Asset), Current Ratio (current assets to current debt), Asset Turnover (Net sales to Total assets), and Total Assets. The hypotheses were tested through simple and multiple linear regression and T-student test. The findings illustrate that there is no significant relationship between accounting information and market risk. This indicates that in the selected sample, historical accounting information does not fully reflect the price of stocks.
Abstract: Biosensors play a significant role in the healthcare
sectors, scientific and technological progress. Developing electrodes
that are easy to manufacture and deliver better electrochemical
performance is advantageous for diagnostics and biosensing. They
can be implemented extensively in various analytical tasks such as
drug discovery, food safety, medical diagnostics, process controls,
security and defence, in addition to environmental monitoring.
Development of biosensors aims to create high-performance
electrochemical electrodes for diagnostics and biosensing. A
biosensor is a device that inspects the biological and chemical
reactions generated by the biological sample. A biosensor carries
out biological detection via a linked transducer and transmits the
biological response into an electrical signal; stability, selectivity,
and sensitivity are the dynamic and static characteristics that affect
and dictate the quality and performance of biosensors. In this
research, a developed experimental study for laser scribing technique
for graphene oxide inside a vacuum chamber for processing of
graphene oxide is presented. The processing of graphene oxide (GO)
was achieved using the laser scribing technique. The effect of the
laser scribing on the reduction of GO was investigated under two
conditions: atmosphere and vacuum. GO solvent was coated onto a
LightScribe DVD. The laser scribing technique was applied to reduce
GO layers to generate rGO. The micro-details for the morphological
structures of rGO and GO were visualised using scanning electron
microscopy (SEM) and Raman spectroscopy so that they could
be examined. The first electrode was a traditional graphene-based
electrode model, made under normal atmospheric conditions, whereas
the second model was a developed graphene electrode fabricated
under a vacuum state using a vacuum chamber. The purpose was
to control the vacuum conditions, such as the air pressure and the
temperature during the fabrication process. The parameters to be
assessed include the layer thickness and the continuous environment.
Results presented show high accuracy and repeatability achieving low
cost productivity.
Abstract: The statement of the multi-objective optimization problem on combinatorial configurations is formulated, and the approach to its solution is proposed. The problem is of interest as a combinatorial optimization one with many criteria, which is a model of many applied tasks. The approach to solving the multi-objective optimization problem on combinatorial configurations consists of two stages; the first is the reduction of the multi-objective problem to the single criterion based on existing multi-objective optimization methods, the second stage solves the directly replaced single criterion combinatorial optimization problem by the horizontal combinatorial method. This approach provides the optimal solution to the multi-objective optimization problem on combinatorial configurations, taking into account additional restrictions for a finite number of steps.
Abstract: There is a real danger that both practitioners and researchers considering risks associated with megaprojects ignore or underestimate the impacts of cultural risk. The paper investigates the potential impacts of a failure to achieve cultural unity between the principal actors executing a megaproject. The principle relationships include the relationships between the principle Contractors and the project stakeholders or the project stakeholders and their principle advisors, Western Consultants. This study confirms that cultural dissonance between these parties can delay or disrupt the megaproject execution and examines why cultural issues should be prioritized as a significant risk factor in megaproject delivery. This paper addresses the practical impacts and potential mitigation measures, which may reduce cultural dissonance for a megaproject's delivery. This information is retrieved from on-going case studies in live infrastructure megaprojects in Europe and the Middle East's GCC states, from Western Consultants' perspective. The collaborating researchers each have at least 30 years of construction experience and are engaged in architecture, project management and contracts management, dealing with megaprojects in Europe or the GCC. After examining the cultural interfaces they have observed during the execution of megaprojects, they conclude that globally, culture significantly influences their efficient delivery. The study finds that cultural risk is ever-present, where different nationalities co-manage megaprojects and that cultural conflict poses a real threat to the timely delivery of megaprojects. The study indicates that the higher the cultural distance between the principal actors, the more pronounced the risk, with the risk of cultural dissonance more prominent in GCC megaprojects. The findings support a more culturally aware and cohesive team approach and recommend cross-cultural training to mitigate the effects of cultural disparity.
Abstract: Maneuver decision-making plays a critical role in high-performance intelligent driving. This paper proposes a risk assessment-based decision-making network (RADMN) to address the problem of driving strategy for the commercial vehicle. RADMN integrates two networks, aiming at identifying the risk degree of collision and rollover and providing decisions to ensure the effectiveness and reliability of driving strategy. In the risk assessment module, risk degrees of the backward collision, forward collision and rollover are quantified for hazard recognition. In the decision module, a deep reinforcement learning based on multi-objective optimization (DRL-MOO) algorithm is designed, which comprehensively considers the risk degree and motion states of each traffic participant. To evaluate the performance of the proposed framework, Prescan/Simulink joint simulation was conducted in highway scenarios. Experimental results validate the effectiveness and reliability of the proposed RADMN. The output driving strategy can guarantee the safety and provide key technical support for the realization of autonomous driving of commercial vehicles.
Abstract: Dependency theory was developed since 1950s, with economic concerns. It divided the world into two parts, the states of the peripheral (third world countries) and the states of the core (the developed capitalist countries). Another perspective developed to the theory with the implementation of the idea of semi-peripheral states in the new world order. With these divisions (core, peripheral, semi-peripheral) this study aims to develop a concept from the perspective of dependency theory, to understand the nature of the relationship of the U.S. with the Middle East Regions through its relation with Iran, Saudi Arabia, and Turkey. The tested countries (Saudi Arabia, Iran and Turkey) are seeking a foothold and influential role in the region. The paper argued that the U.S. directs its policies toward the region, in the way to guarantee no country of the region will be in semi-peripheral level (that could create competitions or danger on the U.S. interest). Therefore, U.S. policies in the region have varied from declaring war to diplomatic channels and sometimes ignoring. The paper is based on the dependency theory, and other international relations theories used to study the Middle East in the international context.