Learning Objects Content Presentation Adaptation Model Considering Students' Learning Styles

Learning styles (LSs) correspond to the individual preferences of a person regarding the modes and forms in which he/she prefers to learn throughout the teaching/learning process. The content presentation of learning objects (LOs) using knowledge about the students’ LSs offers them digital educational resources tailored to their individual learning preferences. In this context, the most relevant characteristics of the LSs along with the most appropriate forms of LOs' content presentation were mapped and associated. Such was performed in order to define the composition of an adaptive model of LO's content presentation considering the LSs, which was called Adaptation of Content Presentation of Learning Objects Considering Learning Styles (ACPLOLS). LO prototypes were created with interfaces that were adapted to students' LSs. These prototypes were based on a model created for validation of the approaches that were used, which were established through experiments with the students. The results of subjective measures of students' emotional responses demonstrated that the ACPLOLS has reached the desired results in relation to the adequacy of the LOs interface, in accordance with the Felder-Silverman LSs Model.

A Review on Bearing Capacity Factor Nγ of Shallow Foundations with Different Shapes

There are several methods for calculating the bearing capacity factors of foundations and retaining walls. In this paper, the bearing capacity factor Nγ (shape factor) for different types of foundation have been investigated. The formula for bearing capacity on c–φ–γ soil can still be expressed by Terzaghi’s equation except that the bearing capacity factor Nγ depends on the surcharge ratio, and friction angle φ. It is apparent that the value of Nγ increases irregularly with the friction angle of the subsoil, which leads to an excessive increment in Nγ of foundations with larger width. Also, the bearing capacity factor Nγ will significantly decrease with an increase in foundation`s width. It also should be highlighted that the effect of shape and dimension will be less noticeable with a decrease in the relative density of the soil. Hence, the bearing capacity factor Nγ relatively depends on foundation`s width, surcharge and roughness ratio. This paper presents the results of various studies conducted on the bearing capacity factor Nγ of: different types of shallow foundation and foundations with irregular geometry (ring footing, triangular footing, shell foundations and etc.) Further studies on the effect of bearing capacity factor Nγ on mat foundations and the characteristics of this factor with or without consideration for the presence of friction between soil and foundation are recommended.

Catalytic Pyrolysis of Sewage Sludge for Upgrading Bio-Oil Quality Using Sludge-Based Activated Char as an Alternative to HZSM5

Due to the concerns about the depletion of fossil fuel sources and the deteriorating environment, the attempt to investigate the production of renewable energy will play a crucial role as a potential to alleviate the dependency on mineral fuels. One particular area of interest is generation of bio-oil through sewage sludge (SS) pyrolysis. SS can be a potential candidate in contrast to other types of biomasses due to its availability and low cost. However, the presence of high molecular weight hydrocarbons and oxygenated compounds in the SS bio-oil hinders some of its fuel applications. In this context, catalytic pyrolysis is another attainable route to upgrade bio-oil quality. Among different catalysts (i.e., zeolites) studied for SS pyrolysis, activated chars (AC) are eco-friendly alternatives. The beneficial features of AC derived from SS comprise the comparatively large surface area, porosity, enriched surface functional groups and presence of a high amount of metal species that can improve the catalytic activity. Hence, a sludge-based AC catalyst was fabricated in a single-step pyrolysis reaction with NaOH as the activation agent and was compared with HZSM5 zeolite in this study. The thermal decomposition and kinetics were invested via thermogravimetric analysis (TGA) for guidance and control of pyrolysis and catalytic pyrolysis and the design of the pyrolysis setup. The results indicated that the pyrolysis and catalytic pyrolysis contain four obvious stages and the main decomposition reaction occurred in the range of 200-600 °C. Coats-Redfern method was applied in the 2nd and 3rd devolatilization stages to estimate the reaction order and activation energy (E) from the mass loss data. The average activation energy (Em) values for the reaction orders n = 1, 2 and 3 were in the range of 6.67-20.37 kJ/mol for SS; 1.51-6.87 kJ/mol for HZSM5; and 2.29-9.17 kJ/mol for AC, respectively. According to the results, AC and HZSM5 both were able to improve the reaction rate of SS pyrolysis by abridging the Em value. Moreover, to generate and examine the effect of the catalysts on the quality of bio-oil, a fixed-bed pyrolysis system was designed and implemented. The composition analysis of the produced bio-oil was carried out via gas chromatography/mass spectrometry (GC/MS). The selected SS to catalyst ratios were 1:1, 2:1 and 4:1. The optimum ratio in terms of cracking the long-chain hydrocarbons and removing oxygen-containing compounds was 1:1 for both catalysts. The upgraded bio-oils with HZSM5 and AC were in the total range of C4-C17 with around 72% in the range of C4-C9. The bio-oil from pyrolysis of SS contained 49.27% oxygenated compounds while the presence of HZSM5 and AC dropped to 7.3% and 13.02%, respectively. Meanwhile, generation of value-added chemicals such as light aromatic compounds were significantly improved in the catalytic process. Furthermore, the fabricated AC catalyst was characterized by BET, SEM-EDX, FT-IR and TGA techniques. Overall, this research demonstrated that AC is an efficient catalyst in the pyrolysis of SS and can be used as a cost-competitive catalyst in contrast to HZSM5.

Dimensionality Reduction in Modal Analysis for Structural Health Monitoring

Autonomous structural health monitoring (SHM) of many structures and bridges became a topic of paramount importance for maintenance purposes and safety reasons. This paper proposes a set of machine learning (ML) tools to perform automatic feature selection and detection of anomalies in a bridge from vibrational data and compare different feature extraction schemes to increase the accuracy and reduce the amount of data collected. As a case study, the Z-24 bridge is considered because of the extensive database of accelerometric data in both standard and damaged conditions. The proposed framework starts from the first four fundamental frequencies extracted through operational modal analysis (OMA) and clustering, followed by time-domain filtering (tracking). The fundamental frequencies extracted are then fed to a dimensionality reduction block implemented through two different approaches: feature selection (intelligent multiplexer) that tries to estimate the most reliable frequencies based on the evaluation of some statistical features (i.e., entropy, variance, kurtosis), and feature extraction (auto-associative neural network (ANN)) that combine the fundamental frequencies to extract new damage sensitive features in a low dimensional feature space. Finally, one-class classification (OCC) algorithms perform anomaly detection, trained with standard condition points, and tested with normal and anomaly ones. In particular, principal component analysis (PCA), kernel principal component analysis (KPCA), and autoassociative neural network (ANN) are presented and their performance are compared. It is also shown that, by evaluating the correct features, the anomaly can be detected with accuracy and an F1 score greater than 95%.

Rolling Element Bearing Diagnosis by Improved Envelope Spectrum: Optimal Frequency Band Selection

The Rolling Element Bearing (REB) vibration diagnosis is worth of special interest by the variety of REB and the wide necessity of those elements in industrial applications. The presence of a localized fault in a REB gives rise to a vibrational response, characterized by the modulation of a carrier signal. Frequency content of carrier signal (Spectral Frequency –f) is mainly related to resonance frequencies of the REB. This carrier signal is modulated by another signal, governed by the periodicity of the fault impact (Cyclic Frequency –α). In this sense, REB fault vibration response gives rise to a second-order cyclostationary signal. Second order cyclostationary signals could be represented in a bi-spectral map, where Spectral Coherence –SCoh are plotted against f and α. The Improved Envelope Spectrum –IES, is a useful approach to execute REB fault diagnosis. IES could be applied by the integration of SCoh over a predefined bandwidth on the f axis. Approaches to select f-bandwidth have been recently exposed by the definition of a metric which intends to evaluate the magnitude of the IES at the fault characteristics frequencies. This metric is represented in a 1/3-binary tree as a function of the frequency bandwidth and centre. Based on this binary tree the optimal frequency band is selected. However, some advantages have been seen if the metric is changed, which in fact tends to dictate different optimal f-bandwidth and so improve the IES representation. This paper evaluates the behaviour of the IES from a different metric optimization. This metric is based on the sample correlation coefficient, detecting high peaks in the selected frequencies while penalizing high peaks in the neighbours of the selected frequencies. Prior results indicate an improvement on the signal-noise ratio (SNR) on around 86% of samples analysed, which belong to IMS database.

Investigation of Tbilisi City Atmospheric Air Pollution with PM in Usual and Emergency Situations Using the Observational and Numerical Modeling Data

Pollution of the Tbilisi atmospheric air with PM2.5 and PM10 in usual and pandemic situations by using the data of 5 stationary observation points is investigated. The values of the statistical characteristic parameters of PM in the atmosphere of Tbilisi are analyzed and trend graphs are constructed. By means of analysis of pollution levels in the quarantine and usual periods the proportion of vehicle traffic in pollution of city is estimated. Experimental measurements of PM2.5, PM10 in the atmosphere have been carried out in different districts of the city and map of the distribution of their concentrations were constructed. It is shown that maximum pollution values are recorded in the city center and along major motorways. It is shown that the average monthly concentrations vary in the range of 0.6-1.6 Maximum Permissible Concentration (MPC). Average daily values of concentration vary at 2-4 days intervals. The distribution of PM10 generated as a result of traffic is numerical modeled. The modeling results are compared with the observation data.

The Contribution of Edgeworth, Bootstrap and Monte Carlo Methods in Financial Data

Edgeworth Approximation, Bootstrap and Monte Carlo Simulations have a considerable impact on the achieving certain results related to different problems taken into study. In our paper, we have treated a financial case related to the effect that have the components of a Cash-Flow of one of the most successful businesses in the world, as the financial activity, operational activity and investing activity to the cash and cash equivalents at the end of the three-months period. To have a better view of this case we have created a Vector Autoregression model, and after that we have generated the impulse responses in the terms of Asymptotic Analysis (Edgeworth Approximation), Monte Carlo Simulations and Residual Bootstrap based on the standard errors of every series created. The generated results consisted of the common tendencies for the three methods applied, that consequently verified the advantage of the three methods in the optimization of the model that contains many variants.

Mnemotopic Perspectives: Communication Design as Stabilizer for the Memory of Places

The ancestral relationship between humans and geographical environment has long been at the center of an interdisciplinary dialogue, which sees one of its main research nodes in the relationship between memory and places. Given its deep complexity, this symbiotic connection continues to look for a proper definition that appears increasingly negotiated by different disciplines. Numerous fields of knowledge are involved, from anthropology to semiotics of space, from photography to architecture, up to subjects traditionally far from these reasonings. This is the case of Design of Communication, a young discipline, now confident in itself and its objectives, aimed at finding and investigating original forms of visualization and representation, between sedimented knowledge and new technologies. In particular, Design of Communication for the Territory offers an alternative perspective to the debate, encouraging the reactivation and reconstruction of the memory of places. Recognizing mnemotopes as a cultural object of vertical interpretation of the memory-place relationship, design can become a real mediator of the territorial fixation of memories, making them increasingly accessible and perceptible, contributing to build a topography of memory. According to a mnemotopic vision, Communication Design can support the passage from a memory in which the observer participates only as an individual to a collective form of memory. A mnemotopic form of Communication Design can, through geolocation and content map-based systems, make chronology a topography rooted in the territory and practicable; it can be useful to understand how the perception of the memory of places changes over time, considering how to insert them in the contemporary world. Mnemotopes can be materialized in different format of translation, editing and narration and then involved in complex systems of communication. The memory of places, therefore, if stabilized by the tools offered by Communication Design, can make visible ruins and territorial stratifications, illuminating them with new communicative interests that can be shared and participated.

The Journey from Lean Manufacturing to Industry 4.0: The Rail Manufacturing Process in Mexico

Nowadays, Lean Manufacturing and Industry 4.0 are very important in every country. One of the main benefits is continued market presence. It has been identified that there is a need to change existing educational programs, as well as update the knowledge and skills of existing employees. It should be borne in mind that behind each technological improvement, there is a human being. Human talent cannot be neglected. The main objectives of this article are to review the link between Lean Manufacturing, the incorporation of Industry 4.0 and the steps to follow to implement it; analyze the current situation and study the implications and benefits of this new trend, with a particular focus on Mexico. Lean Manufacturing and Industry 4.0 implementation waves must always take care of the most important capital – intellectual capital. The methodology used in this article comprised the following steps: reviewing the reality of the fourth industrial revolution, reviewing employees’ skills on the journey to become world-class, and analyzing the situation in Mexico. Lean Manufacturing and Industry 4.0 were studied not as exclusive concepts, but as complementary ones. The methodological framework used is focused on motivating companies’ collaborators to guarantee common results, innovate, and remain in the market in the face of new requirements from company stakeholders. The key findings were that both trends emphasize the need to improve communication across the entire company and incorporate new technologies into everyday work, from the shop floor to administrative staff, to help improve processes. Taking care of people, activities and processes will bring a company success. In the specific case of Mexico, companies in all sectors need to be aware of and implement technological improvements according to their specific needs. Low-cost labor represents one of the most typical barriers. In conclusion, companies must build a roadmap according to their strategy and needs to achieve their short, medium- and long-term goals.

A Modern Review of the Spintronic Technology: Fundamentals, Materials, Devices, Circuits, Challenges, and Current Research Trends

Spintronic, also termed spin electronics or spin transport electronics, is a kind of new technology, which exploits the two fundamental degrees of freedom- spin-state and charge-state of electrons to enhance the operational speed for the data storage and transfer efficiency of the device. Thus, it seems an encouraging technology to combat most of the prevailing complications in orthodox electron-based devices. This novel technology possesses the capacity to mix the semiconductor microelectronics and magnetic devices’ functionalities into one integrated circuit. Traditional semiconductor microelectronic devices use only the electronic charge to process the information based on binary numbers, 0 and 1. Due to the incessant shrinking of the transistor size, we are reaching the final limit of 1 nm or so. At this stage, the fabrication and other device operational processes will become challenging as the quantum effect comes into play. In this situation, we should find an alternative future technology, and spintronic may be such technology to transfer and store information. This review article provides a detailed discussion of the spintronic technology: fundamentals, materials, devices, circuits, challenges, and current research trends. At first, the fundamentals of spintronics technology are discussed. Then types, properties, and other issues of the spintronic materials are presented. After that, fabrication and working principles, as well as application areas and advantages/disadvantages of spintronic devices and circuits, are explained. Finally, the current challenges, current research areas, and prospects of spintronic technology are highlighted. This is a new paradigm of electronic cum magnetic devices built on the charge and spin of the electrons. Modern engineering and technological advances in search of new materials for this technology give us hope that this would be a very optimistic technology in the upcoming days.

Chemistry and Biological Activity of Feed Additive for Poultry Farming

Essential oils are one of the most important groups of biologically active substances present in plants. Due to the chemical diversity of components, essential oils and their preparations have a wide spectrum of pharmacological action. They have bactericidal, antiviral, fungicidal, antiprotozoal, anti-inflammatory, spasmolytic, sedative and other activities. They are expectorant, spasmolytic, sedative, hypotensive, secretion enhancing, antioxidant remedies. Based on preliminary pharmacological studies, we have developed a formulation called “Phytobiotic” containing essential oils, a feed additive for poultry as an alternative to antibiotics. Phytobiotic is a water-soluble powder containing a composition of essential oils of thyme, clary, monarda and auxiliary substances: dry extract of liquorice and inhalation lactose. On this stage of research, the goal was to study the chemical composition of provided phytobiotic, identify the main substances and determine their quantity, investigate the biological activity of phytobiotic through in vitro and in vivo studies. Using gas chromatography-mass spectrometry, 38 components were identified in phytobiotic, representing acyclic-, monocyclic-, bicyclic-, and sesquiterpenes. Together with identification of main active substances, their quantitative content was determined, including acyclic terpene alcohol β-linalool, acyclic terpene ketone linalyl acetate, monocyclic terpenes: D-limonene and γ-terpinene, monocyclic aromatic terpene thymol. Provided phytobiotic has pronounced and at the same time broad spectrum of antibacterial activity. In the cell model, phytobiotic showed weak antioxidant activity, and it was stronger in the ORAC (chemical model) tests. Meanwhile anti-inflammatory activity was also observed. When fowls were supplied feed enriched with phytobiotic, it was observed that gained weight of the chickens in the experimental group exceeded the same data for the control group during the entire period of the experiment. The survival rate of broilers in the experimental group during the growth period was 98% compared to -94% in the control group. As a result of conducted researches probable four different mechanisms which are important for the action of phytobiotics were identified: sensory, metabolic, antioxidant and antibacterial action. General toxic, possible local irritant and allergenic effects of phytobiotic were also investigated. Performed assays proved that formulation is safe.

Lead-Free Inorganic Cesium Tin-Germanium Triiodide Perovskites for Photovoltaic Application

The toxicity of lead associated with the lifecycle of perovskite solar cells (PSCs( is a serious concern which may prove to be a major hurdle in the path toward their commercialization. The current proposed lead-free PSCs including Ag(I), Bi(III), Sb(III), Ti(IV), Ge(II), and Sn(II) low-toxicity cations are still plagued with the critical issues of poor stability and low efficiency. This is mainly because of their chemical stability. In the present research, utilization of all inorganic CsSnGeI3 based materials offers the advantages to enhance resistance of device to degradation, reduce the cost of cells, and minimize the carrier recombination. The presence of inorganic halide perovskite improves the photovoltaic parameters of PCSs via improved surface coverage and stability. The inverted structure of simulated devices using a 1D simulator like solar cell capacitance simulator (SCAPS) version 3308 involves TCOHTL/Perovskite/ETL/Au contact layer. PEDOT:PSS, PCBM, and CsSnGeI3 used as hole transporting layer (HTL), electron transporting layer (ETL), and perovskite absorber layer in the inverted structure for the first time. The holes are injected from highly stable and air tolerant Sn0.5Ge0.5I3 perovskite composition to HTM and electrons from the perovskite to ETL. Simulation results revealed a great dependence of power conversion efficiency (PCE) on the thickness and defect density of perovskite layer. Here the effect of an increase in operating temperature from 300 K to 400 K on the performance of CsSnGeI3 based perovskite devices is investigated. Comparison between simulated CsSnGeI3 based PCSs and similar real testified devices with spiro-OMeTAD as HTL showed that the extraction of carriers at the interfaces of perovskite absorber depends on the energy level mismatches between perovskite and HTL/ETL. We believe that optimization results reported here represent a critical avenue for fabricating the stable, low-cost, efficient, and eco-friendly all-inorganic Cs-Sn-Ge based lead-free perovskite devices.

Photovoltaic Array Cleaning System Design and Evaluation

Dust accumulation on the photovoltaic module's surface results in appreciable loss and negatively affects the generated power. Hence, in this paper, the design of a photovoltaic array cleaning system is presented. The cleaning system utilizes one drive motor, two guide rails, and four sweepers during the cleaning process. The cleaning system was experimentally implemented for one month to investigate its efficiency on PV array energy output. The energy capture over a month for PV array cleaned using the proposed cleaning system is compared with that of the energy capture using soiled PV array. The results show a 15% increase in energy generation from PV array with cleaning. From the results, investigating the optimal scheduling of the PV array cleaning could be an interesting research topic.

Solid State Drive End to End Reliability Prediction, Characterization and Control

A flaw or drift from expected operational performance in one component (NAND, PMIC, controller, DRAM, etc.) may affect the reliability of the entire Solid State Drive (SSD) system. Therefore, it is important to ensure the required quality of each individual component through qualification testing specified using standards or user requirements. Qualification testing is time-consuming and comes at a substantial cost for product manufacturers. A highly technical team, from all the eminent stakeholders is embarking on reliability prediction from beginning of new product development, identify critical to reliability parameters, perform full-blown characterization to embed margin into product reliability and establish control to ensure the product reliability is sustainable in the mass production. The paper will discuss a comprehensive development framework, comprehending SSD end to end from design to assembly, in-line inspection, in-line testing and will be able to predict and to validate the product reliability at the early stage of new product development. During the design stage, the SSD will go through intense reliability margin investigation with focus on assembly process attributes, process equipment control, in-process metrology and also comprehending forward looking product roadmap. Once these pillars are completed, the next step is to perform process characterization and build up reliability prediction modeling. Next, for the design validation process, the reliability prediction specifically solder joint simulator will be established. The SSD will be stratified into Non-Operating and Operating tests with focus on solder joint reliability and connectivity/component latent failures by prevention through design intervention and containment through Temperature Cycle Test (TCT). Some of the SSDs will be subjected to the physical solder joint analysis called Dye and Pry (DP) and Cross Section analysis. The result will be feedbacked to the simulation team for any corrective actions required to further improve the design. Once the SSD is validated and is proven working, it will be subjected to implementation of the monitor phase whereby Design for Assembly (DFA) rules will be updated. At this stage, the design change, process and equipment parameters are in control. Predictable product reliability at early product development will enable on-time sample qualification delivery to customer and will optimize product development validation, effective development resource and will avoid forced late investment to bandage the end-of-life product failures. Understanding the critical to reliability parameters earlier will allow focus on increasing the product margin that will increase customer confidence to product reliability.

Shaking Force Balancing of Mechanisms: An Overview

The balancing of mechanisms is a well-known problem in the field of mechanical engineering because the variable dynamic loads cause vibrations, as well as noise, wear and fatigue of the machines. A mechanical system with unbalance shaking force and shaking moment transmits substantial vibration to the frame. Therefore, the objective of the balancing is to cancel or reduce the variable dynamic reactions transmitted to the frame. The resolution of this problem consists in the balancing of the shaking force and shaking moment. It can be fully or partially, by internal mass redistribution via adding counterweights or by modification of the mechanism's architecture via adding auxiliary structures. The balancing problems are of continue interest to researchers. Several laboratories around the world are very active in this area and new results are published regularly. However, despite its ancient history, mechanism balancing theory continues to be developed and new approaches and solutions are constantly being reported. Various surveys have been published that disclose particularities of balancing methods. The author believes that this is an appropriate moment to present a state of the art of the shaking force balancing studies completed by new research results. This paper presents an overview of methods devoted to the shaking force balancing of mechanisms, as well as the historical aspects of the origins and the evolution of the balancing theory of mechanisms.

Impact of Climate Change on Sea Level Rise along the Coastline of Mumbai City, India

Sea-level rise being one of the most important impacts of anthropogenic induced climate change resulting from global warming and melting of icebergs at Arctic and Antarctic, the investigations done by various researchers both on Indian Coast and elsewhere during the last decade has been reviewed in this paper. The paper aims to ascertain the propensity of consistency of different suggested methods to predict the near-accurate future sea level rise along the coast of Mumbai. Case studies at East Coast, Southern Tip and West and South West coast of India have been reviewed. Coastal Vulnerability Index of several important international places has been compared, which matched with Intergovernmental Panel on Climate Change forecasts. The application of Geographic Information System mapping, use of remote sensing technology, both Multi Spectral Scanner and Thematic Mapping data from Landsat classified through Iterative Self-Organizing Data Analysis Technique for arriving at high, moderate and low Coastal Vulnerability Index at various important coastal cities have been observed. Instead of data driven, hindcast based forecast for Significant Wave Height, additional impact of sea level rise has been suggested. Efficacy and limitations of numerical methods vis-à-vis Artificial Neural Network has been assessed, importance of Root Mean Square error on numerical results is mentioned. Comparing between various computerized methods on forecast results obtained from MIKE 21 has been opined to be more reliable than Delft 3D model.

A Highly Sensitive Dip Strip for Detection of Phosphate in Water

Phosphorus is an essential nutrient for plant life which is most frequently found as phosphate in water. Once phosphate is found in abundance in surface water, a series of adverse effects on an ecosystem can be initiated. Therefore, a portable and reliable method is needed to monitor the phosphate concentrations in the field. In this paper, an inexpensive dip strip device with the ascorbic acid/antimony reagent dried on blotting paper along with wet chemistry is developed for the detection of low concentrations of phosphate in water. Ammonium molybdate and sulfuric acid are separately stored in liquid form so as to improve significantly the lifetime of the device and enhance the reproducibility of the device’s performance. The limit of detection and quantification for the optimized device are 0.134 ppm and 0.472 ppm for phosphate in water, respectively. The device’s shelf life, storage conditions, and limit of detection are superior to what has been previously reported for the paper-based phosphate detection devices.

Investigation of the Effects of Biodiesel Blend on Particulate-Phase Exhaust Emissions from a Light Duty Diesel Vehicle

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.

Exploring the Perspective of Service Quality in mHealth Services during the COVID-19 Pandemic

The impact of COVID-19 has a significant effect on all sectors of society globally. Health information technology (HIT) has become an effective health strategy in this age of distancing. In this regard, Mobile Health (mHealth) plays a critical role in managing patient and provider workflows during the COVID-19 pandemic. Therefore, the users' perception of service quality about mHealth services plays a significant role in shaping confidence and subsequent behaviors regarding the mHealth users' intention of use. This study's objective was to explore levels of user attributes analyzed by a qualitative method of how health practitioners and patients are satisfied or dissatisfied with using mHealth services; and analyzed the users' intention in the context of Taiwan during the COVID-19 pandemic. This research explores the experienced usability of a mHealth services during the Covid-19 pandemic. This study uses qualitative methods that include in-depth and semi-structured interviews that investigate participants' perceptions and experiences and the meanings they attribute to them. The five cases consisted of health practitioners, clinic staff, and patients' experiences using mHealth services. This study encourages participants to discuss issues related to the research question by asking open-ended questions, usually in one-to-one interviews. The findings show the positive and negative attributes of mHealth service quality. Hence, the significant importance of patients' and health practitioners' issues on several dimensions of perceived service quality is system quality, information quality, and interaction quality. A concept map for perceptions regards to emergency uses' intention of mHealth services process is depicted. The findings revealed that users pay more attention to "Medical care", "ease of use" and "utilitarian benefits" and have less importance for "Admissions and Convenience" and "Social influence". To improve mHealth services, the mHealth providers and health practitioners should better manage users' experiences to enhance mHealth services. This research contributes to the understanding of service quality issues in mHealth services during the COVID-19 pandemic.

An Exploratory Study on the Difference between Online and Offline Conformity Behavior among Chinese College Students

Conformity is defined as one in a social group changing his or her behavior to match the others’ behavior in the group. It is used to find that people show a higher level of online conformity behavior than offline. However, as anonymity can decrease the level of online conformity behavior, the difference between online and offline conformity behavior among Chinese college students still needs to be tested. In this study, college students (N = 60) have been randomly assigned into three groups: control group, offline experimental group, and online experimental group. Through comparing the results of offline experimental group and online experimental group with the Mann-Whitney U test, this study verified the results of Asch’s experiment, and found out that people show a lower level of online conformity behavior than offline, which contradicted the previous finding found in China. These results can be used to explain why some people make a lot of vicious remarks and radical ideas on the Internet but perform normally in their real life: the anonymity of the network makes the online group pressure less than offline, so people are less likely to conform to social norms and public opinions on the Internet. What is more, these results support the importance and relevance of online voting, because fewer online group pressures make it easier for people to expose their true ideas, thus gathering more comprehensive and truthful views and opinions.