Search results for: Yuan George Shan

Authors: Yue Sun, Yuan Wang

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The Grand Canal of China has been in use for more than two thousand years. It runs through the central and eastern regions of China and communicates with the five major river systems of Haihe River, Yellow River, Huaihe River, Yangtze River and Qiantang River from north to south. It is a complex, systematic and comprehensive water conservancy project in the period of agricultural civilization and includes the three parts of the Beijing-Hangzhou Canal, the Sui and Tang Dynasties Canal and the Eastern Zhejiang Canal. It covers eight provinces and cities including Beijing, Tianjin, Hebei, Shandong, Jiangsu, Zhejiang, Henan and Anhui. The Grand Canal is an important channel connecting the Central Plains and the Beijing-Hangzhou Canal, and it is also an important waterway trade channel. Nowadays, although the Grand Canal no longer bears the burden of communicating water transportation between the north and the south, the site of the Grand Canal is still a “historical museum” of the lifestyle of people who lived on the canal from the Ming and Qing Dynasties to the Republic of China. By means of literature reading and field investigation, this paper compares the different protection strategies of the Grand Canal in the region between the ancient villages of Huaxian and Xunxian, which witness the vicissitudes of canal water transport, to explore whether the protective renovation of historical and cultural routes is “protection” or “destruction”, and puts forward some protection suggestions.

Keywords: The Grand Canal, heritage conservation, cultural route, ancient villages, strategies

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Authors: Xiyao Shan, Pavlos Evangelidis, Adam Kositsky, Naoki Ikeda, Yasuo Kawakami

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The human triceps surae (two bi-articular gastrocnemii and one mono-articular soleus) have aponeuroses in the posterior and anterior aspects of each muscle, where the anterior aponeuroses of the gastrocnemii adjoin the posterior aponeurosis of the soleus, possibly contributing to the intermuscular force transmission between gastrocnemii and soleus. Since the mechanical behavior of these aponeuroses at different knee- and ankle-joint positions remains unclear, the purpose of this study was to clarify this through observations of the localized changes in passive stiffness of the posterior aponeuroses, muscle belly and adjoining aponeuroses of the medial gastrocnemius (MG) induced by different knee and ankle angles. Eleven healthy young males (25 ± 2 yr, 176.7 ± 4.7 cm, 71.1 ± 11.1 kg) participated in this study. Each subject took either a prone position on an isokinetic dynamometer while the knee joint was fully extended (K180) or a kneeling position while the knee joint was 90° flexed (K90), in a randomized and counterbalanced order. The ankle joint was then passively moved through a 50° range of motion (ROM) by the dynamometer from 30° of plantar flexion (PF) to 20° of dorsiflexion (DF) at 2°/s and the ultrasound shear-wave velocity was measured to obtain shear moduli of the posterior aponeurosis, MG belly, and adjoining aponeuroses. The main findings were: 1) shear modulus in K180 was significantly higher (p < 0.05) than K90 for the posterior aponeurosis (across all ankle angles, 10.2 ± 5.7 kPa-59.4 ± 28.7 kPa vs. 5.4 ± 2.2 kPa-11.6 ± 4.1 kPa), MG belly (from PF10° to DF20°, 9.7 ± 2.2 kPa-53.6 ± 18.6 kPa vs. 8.0 ± 2.7 kPa-9.5 ± 3.7 kPa), and adjoining aponeuroses (across all ankle angles, 17.3 ± 7.8 kPa-80 ± 25.7 kPa vs. 12.2 ± 4.5 kPa-52.4 ± 23.0 kPa); 2) shear modulus of the posterior aponeuroses significantly increased (p < 0.05) from PF10° to PF20° in K180, while shear modulus of MG belly significantly increased (p < 0.05) from 0° to PF20° only in K180 and shear modulus of adjoining aponeuroses significantly increased (p < 0.05) across the whole ROM of ankle both in K180 and K90. These results suggest that different knee-joint positions can affect not only the bi-articular gastrocnemius but also influence the mechanical behavior of aponeuroses. In addition, compared to the gradual stiffening of the adjoining aponeuroses across the whole ROM of ankle, the posterior aponeurosis became slack in the plantar flexed positions and then was stiffened gradually as the knee was fully extended. This suggests distinct stiffening for the posterior and adjoining aponeuroses which is joint position-dependent.

Keywords: aponeurosis, plantar flexion and dorsiflexion, shear modulus, shear wave elastography

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Authors: George Abu-Aqil, Leah Tsror, Elad Shufan, Shaul Mordechai, Mahmoud Huleihel, Ahmad Salman

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Pectobacterium and Dickeya spp which negatively affect a wide range of crops are the main causes of the aggressive diseases of agricultural crops. These aggressive diseases are responsible for a huge economic loss in agriculture including a severe decrease in the quality of the stored vegetables and fruits. Therefore, it is important to detect these pathogenic bacteria at their early stages of infection to control their spread and consequently reduce the economic losses. In addition, early detection is vital for producing non-infected propagative material for future generations. The currently used molecular techniques for the identification of these bacteria at the strain level are expensive and laborious. Other techniques require a long time of ~48 h for detection. Thus, there is a clear need for rapid, non-expensive, accurate and reliable techniques for early detection of these bacteria. In this study, infrared spectroscopy, which is a well-known technique with all its features, was used for rapid detection of Pectobacterium and Dickeya spp. at the strain level. The bacteria were isolated from potato plants and tubers with soft rot symptoms and measured by infrared spectroscopy. The obtained spectra were analyzed using different machine learning algorithms. The performances of our approach for taxonomic classification among the bacterial samples were evaluated in terms of success rates. The success rates for the correct classification of the genus, species and strain levels were ~100%, 95.2% and 92.6% respectively.

Keywords: soft rot enterobacteriaceae (SRE), pectobacterium, dickeya, plant infections, potato, solanum tuberosum, infrared spectroscopy, machine learning

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Authors: Ghulam Mustafa Kamal, Xiaohua Wang, Bin Yuan, Abdullah Ijaz Hussain, Jie Wang, Shahzad Ali Shahid Chatha, Xu Zhang, Maili Liu

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Organic food products are becoming increasingly popular in recent years, as consumers have turned more health conscious and environmentally aware. A lot of consumers have understood that the organic foods are healthier than conventionally produced food stuffs. Price difference between conventional and organic foods is very high. So, it is very common to cheat the consumers by mislabeling and adulteration. Our study describes the 1H NMR based approach to characterize and differentiate soy sauce prepared from organically and conventionally grown raw materials (wheat and soybean). Commercial soy sauce samples fermented from organic and conventional raw materials were purchased from local markets. Principal component analysis showed clear separation among organic and conventional soy sauce samples. Orthogonal partial least squares discriminant analysis showed a significant (p < 0.01) separation among two types of soy sauce yielding leucine, isoleucine, ethanol, glutamate, lactate, acetate, β-glucose, sucrose, choline, valine, phenylalanine and tyrosine as important metabolites contributing towards this separation. Abundance ratio of 13C to 12C was also evaluated by 1H NMR spectroscopy which showed an increased ratio of 13C isotope in organic soy sauce samples indicating the organically grown wheat and soybean used for the preparation of organic soy sauce. Results of the study can be helpful to the end users to select the soy sauce of their choice. This information could also pave the way to further trace and authenticate the raw materials used in production of soy sauce.

Keywords: 1H NMR, multivariate analysis, organic, conventional, 13C isotopic ratio, soy sauce

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Authors: Kiran Nair, Jincy George, Suhaib Anagreh

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Artificial intelligence (AI) in a marketing context is a form of a deterministic tool designed to optimize and enhance marketing tasks, research tools, and techniques. It is on the verge of transforming marketing roles and revolutionize the entire industry. This paper aims to explore the current dissemination of the application of artificial intelligence (AI) in the marketing mix, reviewing the scope and application of AI in various aspects of sales and distribution management. The paper also aims at identifying the areas of the strong impact of AI in factors of sales and distribution management such as distribution channel, purchase automation, customer service, merchandising automation, and shopping experiences. This is a qualitative research paper that aims to examine the impact of AI on sales and distribution management of 30 multinational brands in six different industries, namely: airline; automobile; banking and insurance; education; information technology; retail and telecom. Primary data is collected by means of interviews and questionnaires from a sample of 100 marketing managers that have been selected using convenient sampling method. The data is then analyzed using descriptive statistics, correlation analysis and multiple regression analysis. The study reveals that AI applications are extensively used in sales and distribution management, with a strong impact on various factors such as identifying new distribution channels, automation in merchandising, customer service, and purchase automation as well as sales processes. International brands have already integrated AI extensively in their day-to-day operations for better efficiency and improved market share while others are investing heavily in new AI applications for gaining competitive advantage.

Keywords: artificial intelligence, sales and distribution, marketing mix, distribution channel, customer service

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Authors: Manal Suleiman, George Abu-Aqil, Uraib Sharaha, Klaris Riesenberg, Itshak Lapidot, Ahmad Salman, Mahmoud Huleihel

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Klebsiella pneumoniae is one of the most aggressive multidrug-resistant bacteria associated with human infections resulting in high mortality and morbidity. Thus, for an effective treatment, it is important to diagnose both the species of infecting bacteria and their susceptibility to antibiotics. Current used methods for diagnosing the bacterial susceptibility to antibiotics are time-consuming (about 24h following the first culture). Thus, there is a clear need for rapid methods to determine the bacterial susceptibility to antibiotics. Infrared spectroscopy is a well-known method that is known as sensitive and simple which is able to detect minor biomolecular changes in biological samples associated with developing abnormalities. The main goal of this study is to evaluate the potential of infrared spectroscopy in tandem with Random Forest and XGBoost machine learning algorithms to diagnose the susceptibility of Klebsiella pneumoniae to antibiotics within approximately 20 minutes following the first culture. In this study, 1190 Klebsiella pneumoniae isolates were obtained from different patients with urinary tract infections. The isolates were measured by the infrared spectrometer, and the spectra were analyzed by machine learning algorithms Random Forest and XGBoost to determine their susceptibility regarding nine specific antibiotics. Our results confirm that it was possible to classify the isolates into sensitive and resistant to specific antibiotics with a success rate range of 80%-85% for the different tested antibiotics. These results prove the promising potential of infrared spectroscopy as a powerful diagnostic method for determining the Klebsiella pneumoniae susceptibility to antibiotics.

Keywords: urinary tract infection (UTI), Klebsiella pneumoniae, bacterial susceptibility, infrared spectroscopy, machine learning

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Authors: Wei-Shan Wang, Klaus Vogel, Felix Gabler, Maik Wiemer, Thomas Gessner

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Metallic glasses, which are free of grain boundaries, have superior properties including large elastic limits, high strength, and excellent wear and corrosion resistance. Therefore, bulk metallic glasses (BMG) and thin film metallic glasses (TFMG) have been widely developed and investigated. Among various kinds of metallic glasses, Pd-Cu-Si TFMG, which has lower elastic modulus and better resistance of oxidation and corrosions compared to Zr- and Fe-based TFMGs, can be a promising candidate for MEMS applications. However, the study of Pd-TFMG membrane is still limited. This paper presents free-standing Pd-based metallic glass membranes with large area fabricated on wafer level for the first time. Properties of Pd-Cu-Si thin film metallic glass (TFMG) with various deposition parameters are investigated first. When deposited at 25°C, compressive stress occurs in the Pd76Cu6Si18 thin film regardless of Ar pressure. When substrate temperature is increased to 275°C, the stress state changes from compressive to tensile. Thin film stresses are slightly decreased when Ar pressure is higher. To show the influence of temperature on Pd-TFMGs, thin films without and with post annealing below (275°C) and within (370°C) supercooled liquid region are investigated. Results of XRD and TEM analysis indicate that Pd-TFMGs remain amorphous structure with well-controlled parameters. After verification of amorphous structure of the Pd-TFMGs, free-standing Pd-Cu-Si membranes were fabricated by depositing Pd-Cu-Si thin films directly on 200nm-thick silicon nitride membranes, followed by post annealing and dry etching of silicon nitride layer. Post annealing before SiNx removal is used to further release internal stress of Pd-TFMGs. The edge length of the square membrane ranges from 5 to 8mm. The effect of post annealing on Pd-Cu-Si membranes are discussed as well. With annealing at 370°C for 5 min, Pd-MG membranes are fully distortion-free after removal of SiNx layer. Results show that, by introducing annealing process, the stress-relief, distortion-free Pd-TFMG membranes with large area can be a promising candidate for sensing applications such as pressure and gas sensors.

Keywords: amorphous alloy, annealing, metallic glasses, TFMG membrane

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Authors: Tai Yuan Yu, Pei-Jen Wang

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A simulation scheme of rotational motions for predictions of bump-type gas foil bearings operating at steady-state is proposed; and, the scheme is based on multi-physics coupling computer aided engineering packages modularized with computational fluid dynamic model and structure elasticity model to numerically solve the dynamic equation of motions of a hydrodynamic loaded shaft supported by an elastic bump foil. The bump foil is assumed to be modelled as infinite number of Hookean springs mounted on stiff wall. Hence, the top foil stiffness is constant on the periphery of the bearing housing. The hydrodynamic pressure generated by the air film lubrication transfers to the top foil and induces elastic deformation needed to be solved by a finite element method program, whereas the pressure profile applied on the top foil must be solved by a finite element method program based on Reynolds Equation in lubrication theory. As a result, the equation of motions for the bearing shaft are iteratively solved via coupling of the two finite element method programs simultaneously. In conclusion, the two-dimensional center trajectory of the shaft plus the deformation map on top foil at constant rotational speed are calculated for comparisons with the experimental results.

Keywords: computational fluid dynamics, fluid structure interaction multi-physics simulations, gas foil bearing, load capacity

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Authors: Hung Hing Chan, Tai-Shan Hu

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Kaohsiung has been an industrial city of Taiwan for over a hundred year. Consequently, there are several abandoned industrial lands left when the process of deindustrialization has started, resulting in the decay of the adjacent urban communities. These industrial lands, which are brownfields that are potentially or already contaminated by hazardous substances, have created social injustice to the surrounding communities. The redevelopments of industrial lands bring a sustainable development to the communities, while the redevelopments can be in different forms, depending on the natural conditions. This research studies the possible approaches to facilitate social sustainability of urban regeneration resulted from the industrial land redevelopment projects, which has always been ignored. The aim of the research is to find out the best western practices of brownfield redevelopment to facilitate social aspect of sustainable urban regeneration and make a contribution to the industrial land redevelopment of Taiwan. The research is conducted via literature review and case study. Industrial land redevelopment has been a social focus in the blighted communities to promote urban regeneration after the post-industrial age. The tendency of this kind of redevelopment is towards constructing the built environment, as a result the environmental and economic aspect of sustainability of the redeveloped industrial land will be boosted, while the social aspect will not be necessarily better since the local communities affected are rarely engaged in the decision-making process and inadequate resource allocation to the projects is not guaranteed. To ensure the improvement of social sustainability is reached, the recommendations of this research, such as civic engagement, a formation of dedicated brownfield regeneration agency and resource allocation to employ brownfield process manager and to strategic communication, should be incorporated into the real practices of industrial land-led urban regeneration. Besides, the case study also shows that the social sustainability of industrial land-led urban regeneration can be promoted by (1) upholding the local feature and public participation in the regeneration process, (2) allocating resources and enforcing responsibility system, and (3) assuring financial resource for the urban regeneration projects and residents. Subsequent research will involve in-depth interviews with the chiefs of the village of related communities in Kaohsiung and questionnaire with the community members to comprehend their opinions regarding social sustainability, aiming at evaluating the social sustainability and finding out which kind of redevelopment project tends to support the social dimension of sustainable development more.

Keywords: brownfield, industrial land, redevelopment, social sustainability, urban regeneration

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Authors: Joseph George, Anne Kotteswara Roa

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Skin disease is one of the most common and popular kinds of health issues faced by people nowadays. Skin cancer (SC) is one among them, and its detection relies on the skin biopsy outputs and the expertise of the doctors, but it consumes more time and some inaccurate results. At the early stage, skin cancer detection is a challenging task, and it easily spreads to the whole body and leads to an increase in the mortality rate. Skin cancer is curable when it is detected at an early stage. In order to classify correct and accurate skin cancer, the critical task is skin cancer identification and classification, and it is more based on the cancer disease features such as shape, size, color, symmetry and etc. More similar characteristics are present in many skin diseases; hence it makes it a challenging issue to select important features from a skin cancer dataset images. Hence, the skin cancer diagnostic accuracy is improved by requiring an automated skin cancer detection and classification framework; thereby, the human expert’s scarcity is handled. Recently, the deep learning techniques like Convolutional neural network (CNN), Deep belief neural network (DBN), Artificial neural network (ANN), Recurrent neural network (RNN), and Long and short term memory (LSTM) have been widely used for the identification and classification of skin cancers. This survey reviews different DL techniques for skin cancer identification and classification. The performance metrics such as precision, recall, accuracy, sensitivity, specificity, and F-measures are used to evaluate the effectiveness of SC identification using DL techniques. By using these DL techniques, the classification accuracy increases along with the mitigation of computational complexities and time consumption.

Keywords: skin cancer, deep learning, performance measures, accuracy, datasets

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Authors: Samuel Munaf, Kevin Swingler, Franz Brülisauer, Anthony O’Hare, George Gunn, Aaron Reeves

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Web scraping and text mining are popular computer science methods deployed by public health researchers to augment traditional epidemiological surveillance. However, within veterinary disease surveillance, such techniques are still in the early stages of development and have not yet been fully utilised. This study presents an exploration into the utility of incorporating internet-based data to better understand the smallholder farming communities within Scotland by using online text extraction and the subsequent mining of this data. Web scraping of the livestock fora was conducted in conjunction with text mining of the data in search of common themes, words, and topics found within the text. Results from bi-grams and topic modelling uncover four main topics of interest within the data pertaining to aspects of livestock husbandry: feeding, breeding, slaughter, and disposal. These topics were found amongst both the poultry and pig sub-forums. Topic modeling appears to be a useful method of unsupervised classification regarding this form of data, as it has produced clusters that relate to biosecurity and animal welfare. Internet data can be a very effective tool in aiding traditional veterinary surveillance methods, but the requirement for human validation of said data is crucial. This opens avenues of research via the incorporation of other dynamic social media data, namely Twitter and Facebook/Meta, in addition to time series analysis to highlight temporal patterns.

Keywords: veterinary epidemiology, disease surveillance, infodemiology, infoveillance, smallholding, social media, web scraping, sentiment analysis, geolocation, text mining, NLP

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Authors: Christiana Ene Ogwuche, Joseph Amupitan, George Ndukwe, Rachael Ayo

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Maesobotrya barteri (Baill), belonging to the family Euphorbiaceae, is a medicinal plant growing widely in tropical Africa. The Aerial plant parts of Maesobotrya barteri (Baill) were collected fresh from Orokam, Ogbadibo local Government of Benue State, Nigeria in July 2013. Taxonomical identification was done by Mallam Musa Abdullahi at the Herbarium unit of Biological Sciences Department, ABU, Zaria, Nigeria. Pulverized aerial parts of Maesobotrya barteri (960g) was exhaustively extracted successively using petroleum ether, chloroform, ethyl acetate and methanol and concentrated in the rotary evaporator at 40°C. The Petroleum ether extract had the second highest activity against test microbes from preliminary crude microbial screenings. The Petroleum ether extract was subjected to phytochemical studies, antimicrobial analysis and column chromatography (CC). The column chromatography yielded fraction PE, which was further purified using preparative thin layer chromatography to give PE1. The structure of the isolated compound was established using 1-D NMR and 2-D NMR spectroscopic analysis and by direct comparison with data reported in literature was confirmed to be a mixture, an isomer of Betulinic acid and Oleanolic acid, both with the molecular weight (C₃₀H₄₈O₃). The bioactivity of this compound was carried out using some clinical pathogens and the activity compared with standard drugs, and this was found to be comparable with the standard drug.

Keywords: Maesobotrya barteri, medicinal plant, bioactivity, petroleum spirit extract, butellinic acid, oleanilic acid

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Authors: Rong Yuan, Zhao Tao

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Only a handful of literature have used to non-linear model to investigate the influencing factors of greenhouse gas (GHG) emissions in China’s manufacturing sectors. And there is a limit in investigating quantitatively and systematically the mechanism of correlation between economic development and GHG emissions considering inherent differences among manufacturing sub-sectors. Considering the sectorial characteristics, the manufacturing sub-sectors with various impacts of output on GHG emissions may be explained by different development modes in each manufacturing sub-sector, such as investment scale, technology level and the level of international competition. In order to assess the environmental impact associated with any specific level of economic development and explore the factors that affect GHG emissions in China’s manufacturing industry during the process of economic growth, using the threshold Stochastic Impacts by Regression on Population, Affluence and Technology (STIRPAT) model, this paper investigated the influence impacts of GHG emissions for China’s manufacturing sectors of different stages of economic development. A data set from 28 manufacturing sectors covering an 18-year period was used. Results demonstrate that output per capita and investment scale contribute to increasing GHG emissions while energy efficiency, R&D intensity and FDI mitigate GHG emissions. Results also verify the nonlinear effect of output per capita on emissions as: (1) the Environmental Kuznets Curve (EKC) hypothesis is supported when threshold point RMB 31.19 million is surpassed; (2) the driving strength of output per capita on GHG emissions becomes stronger as increasing investment scale; (3) the threshold exists for energy efficiency with the positive coefficient first and negative coefficient later; (4) the coefficient of output per capita on GHG emissions decreases as R&D intensity increases. (5) FDI shows a reduction in elasticity when the threshold is compassed.

Keywords: China, GHG emissions, manufacturing industry, threshold STIRPAT model

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Authors: Chun-Yuan Chen, Ming-Chang Li, Xiu-Hui Wen, Yi-Ching Tu

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The objective of this study explores GPS (Global Positioning System) applied to trace construction vehicles such as trucks or cranes, help to pattern the earth-dumping stations of traffic construction in Taiwan. Traffic construction in this research is defined as the engineering of high-speed railways, expressways, and which that distance more than kilometers. Audit the location and check the compliance with regulations of earth-dumping stations is one of important tasks in Taiwan EPA. Basically, the earth-dumping station was known as one source of particulate matter from air pollution during construction process. Due to GPS data can be analyzed quickly and be used conveniently, this study tried to find out dumping stations by modeling vehicles tracks from GPS data during work cycle of construction. The GPS data updated from 13 vehicles related to an expressway construction in central Taiwan. The GPS footprints were retrieved to Keyhole Markup Language (KML) files so that can pattern the tracks of trucks by computer applications, the data was collected about eight months- from Feb. to Oct. in 2017. The results of GPS footprints identified dumping station and outlined the areas of earthwork had been passed to the Taiwan EPA for on-site inspection. Taiwan EPA had issued advice comments to the agency which was in charge of the construction to prevent the air pollution. According to the result of this study compared to the commonly methods in inspecting environment by manual collection, the GPS with KML patterning and modeling method can consumes less time. On the other hand, through monitoring the GPS data from construction vehicles could be useful for administration to development and implementation of strategies in environmental management.

Keywords: automatic management, earth-dumping station, environmental management, Global Positioning System (GPS), particulate matter, traffic construction

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Authors: Tai Yuan Yu, Pei-Jen Wang

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Oil-free turbomachinery is considered one of the critical technologies for future green power generation systems as rotor machinery systems. Oil-free technology allows clean, compact, and maintenance-free working, and gas foil bearings, abbreviated as GFBs, are important for the technology. Since the first applications in the auxiliary power units and air cycle machines in the 1970s, obvious improvement has been created to the computational models for dynamic rotor behavior. However, many technical issues are still poorly understood or remain unsolved, and some of those are thermal management and the pattern of how pressure will be distributed in bearing clearance. This paper presents a three-dimensional, abbreviated as 3D, fluid-structure interaction model of single pad foil bearings and three pad foil bearings to predict bearing working behavior that researchers could compare characteristics of those. The coupling analysis model involves dynamic working characteristics applied to all the gas film and mechanical structures. Therefore, the elastic deformation of foil structure and the hydrodynamic pressure of gas film can both be calculated by a finite element method program. As a result, the temperature distribution pattern could also be iteratively solved by coupling analysis. In conclusion, the working fluid state in a gas film of various pad forms of bearings working characteristic at constant rotational speed for both can be solved for comparisons with the experimental results.

Keywords: fluid-structure interaction, multi-physics simulations, gas foil bearing, oil-free, transient thermo-hydrodynamic

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Authors: Kimiyo Shimomai, Mihoko Harada

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This study is a literature review of the psychological reactions that occur in end-of-life cancer patients who are nearing death. It searched electronic databases and selected literature related to psychological studies of end-of-life patients. There was no limit on the search period, and the search was conducted until the second week of December 2021. The keywords were specified as “death and dying”, “terminal illness”, “end-of-life”, “palliative care”, “psycho-oncology” and “research”. These literatures referred to Holly (2017): Comprehensive Systematic Review for Advanced Practice Nursing, P268 Figure 10.3 to ensure quality. These literatures were selected with a dissertation score of 4 or 5. The review was conducted in two stages with reference to the procedure of George (2002). First, these references were searched for keywords in the database, and then relevant references were selected from the psychology and nursing studies of end-of-life patients. The number of literatures analyzed was 76 for overseas and 17 for domestic. As for the independent variables, "physical variable" was the most common in 36 literatures (66.7%), followed by "psychological variable" in 35 literatures (64.8%), "spiritual variable" in 21 literatures (38%), and "social variable" in 17 literatures. (31.5%), "Variables related to medical care / treatment" were 16 literatures (29.6%). To summarize the relationship between these independent variables and the dependent variable, when the dependent variable is "psychological variable", the independent variables are "psychological variable", "social variable", and "physical variable". Among the independent variables, the physical variables were the most common. The psychological responses that occur in end-stage cancer patients who are nearing death are mutually influenced by psychological, social, and physical variables. Therefore, it supported the "total pain" advocated by Cicely Saunders.

Keywords: cancer patient, end-of-life, literature review, psychological process

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Authors: Hameed Ullah, Karim Elakabawi, Han KE, Najeeb Ullah, Habib Ullah, Sardar Ali Shah, Hamad Haider Khan, Muhammad Asad Khan, Ning Guo, Zuyi Yuan

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Background: Predictors of decreased fractional flow reserve at left circumflex coronary artery after left main (LM) crossover stenting are still lacking. The objectives of the present study were to provide the predictors for low Fractional flow reserve (FFR) at coronary artery (LCx) and the possible treatment strategies for the compromised LCx-together with their long term outcomes. Methods: A total of 563 included patients out of 1974 patients admitted to our hospital from February 2015 to November 2020 with significant distal LM-bifurcation lesions. The enrolled patients underwent single-stent cross-over PCI under IVUS guidance with further LCx intervention as indicated by measured FFR. Results: The included patients showed angiographic significant LCx ostial affection after LM-stenting, but only 116 (20.6%) patients had FFR <0.8. The 3-year composite MACE rates were comparable between the high and low FFR groups (16.8% vs. 15.5%, respectively; P=0.744). In a multivariable analysis, a low FFR in the LCx was associated with post-stenting MLA of the LCx (OR: 0.032, P <0.001), post-stenting LCx-plaque burden (OR: 1.166, P <0.001), post-stenting LM-MLA (OR: 0.821, P =0.038) and pre-stenting LCx-MLA (OR: 0.371, P =0.044). In patients with low FFR, management of compromised LCx with DEB had the lowest 3-year MACE rate (8.1%) as compared to either KBI (17.5%) or stenting group (20.5%), P =0.299. Conclusion: FFR-guided LCx intervention can avoid unnecessary LCx intervention. The post-stenting predictors of low FFR include post-stenting MLA and plaque burden of the LCx and MV stent length. The 3-year MACE rates were comparable between high FFR patients and patients who had low FFR and were adequately managed.

Keywords: fractional flow reserve, left main stem, percutaneous coronary interventions, intravascular ultrasound

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Authors: Takeshi Takemoto, Naoya Suzuki, Naohisa Takagaki, Satoru Komori, Masako Terui, George Truscott

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Drag coefficient is an important parameter in order to correctly estimate the air-sea momentum flux. However, The parameterization of the drag coefficient hasn’t been established due to the variation in the field data. Instead, a number of drag coefficient model formulae have been proposed, even though almost all these models haven’t discussed the extreme wind speed range. With regards to such models, it is unclear how the drag coefficient changes in the extreme wind speed range as the wind speed increased. In this study, we investigated the effect of the drag coefficient models concerning the air-sea momentum flux in the extreme wind range on a global scale, comparing two different drag coefficient models. Interestingly, one model didn’t discuss the extreme wind speed range while the other model considered it. We found that the difference of the models in the annual global air-sea momentum flux was small because the occurrence frequency of strong wind was approximately 1% with a wind speed of 20m/s or more. However, we also discovered that the difference of the models was shown in the middle latitude where the annual mean air-sea momentum flux was large and the occurrence frequency of strong wind was high. In addition, the estimated data showed that the difference of the models in the drag coefficient was large in the extreme wind speed range and that the largest difference became 23% with a wind speed of 35m/s or more. These results clearly show that the difference of the two models concerning the drag coefficient has a significant impact on the estimation of a regional air-sea momentum flux in an extreme wind speed range such as that seen in a tropical cyclone environment. Furthermore, we estimated each air-sea momentum flux using several kinds of drag coefficient models. We will also provide data from an observation tower and result from CFD (Computational Fluid Dynamics) concerning the influence of wind flow at and around the place.

Keywords: air-sea interaction, drag coefficient, air-sea momentum flux, CFD (Computational Fluid Dynamics)

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Authors: Akumeyam Elvis Akum, Njanjo Thecla Anyongo Mukete, Fonkeng George Epah

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Globally, the goal of higher education is to enhance graduate employability skills. Paradoxically, Cameroon’s graduate employability rate is far below the graduation rate. This worrisome situation caused the researcher to hypothesize that the teaching and learning experiences account for this increasing disparity. The study sought to investigate the effect on graduate employability of the teaching of organizational, problem-solving, innovation, and risk management skills on graduate employability. The study adopted a descriptive survey design with a quantitative approach. Data was collected by quantitative techniques from a random sample of 385 graduates using closed-ended structured questionnaire. Generally, findings revealed that entrepreneurship education does not sufficiently enhance graduate employability in the University of Buea. Specifically, the teaching of organizational skills does not significantly enhance their employability, as an average of 55% of graduates indicated that the course did not sufficiently help them develop skills for planning, management of limited resources, collaboration, and the setting of priorities. Also, 60% of the respondents indicated that the teaching of problem-solving skills does not significantly enhance graduate employability at the University of Buea. Contrarily, 57% of the respondents agreed that through their experiences in entrepreneurship education, their innovation skills were improved. The study recommended that a practical approach to teaching should be adopted, with attention to societal needs. A framework to ensure the teaching of entrepreneurship to students at the undergraduate level is recommended, such that those who do not continue with university studies after their Bachelor’s degree would have acquired the needed skills for employability.

Keywords: employability, entrepreneurship education, graduate, innovative skills, organizational skills, problem-solving skills, risk management skills

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Authors: James Ponniah

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Christianity is the largest religious tradition of the world. What makes Christianity a world religion is its characteristics of universality and particularity. Its universality and particularity are closely interrelated. Its university is realized and embodied in its particularities and its particularity is recognized and legitimized through its universality. This paper focuses on the dimension of the particularity of Christianity in that it looks at the particularized ideas and discourses of Christian thinking in India in the 20th century and pays attention to the differing shifts and new shades of meaning in Indian Christian notion of God. Drawing upon the writings of select Indian theologians such as Brahmabandhab Upadhyaya, Sundar Sing, A.J Appasamy, Raymond Panikkar, Amalorpavadass and George Soares Prabhhu, this paper delves into how the contexts—be it personal, political, historical or ecclesial—bear upon the way Indian theologians have conceived and constructed the notion of God in their work. Focusing upon how they responded to the signs of their time through their theological narratives, the paper argues that the religion of Christianity can sustain its universality only when it translates its key notions such as God into indigenous categories and local idioms and thus makes itself relevant to the people among whom it is spread. Monotheistic God of Christianity has to accommodate plurality of expressions if Christian idea God has to capture and convey everyone’s experience of God. The case of Indian Christianity then reveals that a monolithic world religion will be experienced and recognised as truly universal only when it sheds its homogeneity and assumes a heterogeneous portrait through the acquisition of local idioms. Allowing culturally diverse idioms to influence theological categories is not inconsequential to—‘accommodating differences and accepting diversities,’ an issue we encounter within and beyond religious domains in our contemporary times.

Keywords: concept of God, heterogeneity, Indian Christianity, indigenous categories

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Authors: Mandlenkosi George Robert Mahlobo, Tumelo Seadira, Major Melusi Mabuza, Peter Apata Olubambi

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Cathodic protection (CP) has been widely considered a suitable technique for mitigating corrosion of buried metal structures. Plenty of efforts have been made in developing techniques, in particular non-destructive techniques, for monitoring and quantifying the effectiveness of CP to ensure the sustainability and performance of buried steel structures. The aim of this study was to investigate the evolution of the electrochemical processes at the steel/soil interface during the application of CP on steel in simulated soil. Carbon steel was subjected to electrochemical tests with NS4 solution used as simulated soil conditions for 4 days before applying CP for a further 11 days. A previously modified non-destructive voltammetry technique was applied before and after the application of CP to measure the corrosion rate. Electrochemical impedance spectroscopy (EIS), in combination with mathematical modeling through equivalent electric circuits, was applied to determine the electrochemical behavior at the steel/soil interface. The measured corrosion rate was found to have decreased from 410 µm/yr to 8 µm/yr between days 5 and 14 because of the applied CP. Equivalent electrical circuits were successfully constructed and used to adequately model the EIS results. The modeling of the obtained EIS results revealed the formation of corrosion products via a mixed activation-diffusion mechanism during the first 4 days, while the activation mechanism prevailed in the presence of CP, resulting in a protective film. The x-ray diffraction analysis confirmed the presence of corrosion products and the predominant protective film corresponding to the calcareous deposit.

Keywords: carbon steel, cathodic protection, NS4 solution, voltammetry, EIS

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Authors: Mei Han, Jinkou Zhao, Yuan Yao, Liangui Feng, Xianbin Ding, Guohui Wu, Chao Zhou, Lin Ouyang, Rongrong Lu, Bo Zhang

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To compare the HIV incidence estimated using BED capture enzyme linked immunosorbent assay (BED-CEIA) and observed in a cohort against the HIV incidence among men who have sex with men (MSM) measured by pooling polymerase chain reaction (pooling-PCR). A total of 617 MSM subjects were included in a respondent driven sampling survey in Chongqing in 2008. Among the 129 that were tested HIV antibody positive, 102 were defined with long-term infection, 27 were assessed for recent HIV infection (RHI) using BED-CEIA. The remaining 488 HIV negative subjects were enrolled to the prospective cohort and followed-up every 6 months to monitor HIV seroconversion. All of the 488 HIV negative specimens were assessed for acute HIV infection (AHI) using pooling-PCR. Among the 488 negative subjects in the open cohort, 214 (43.9%) were followed-up for six months, with 107 person-years of observation and 14 subjects seroconverted. The observed HIV incidence was 12.5 per 100 person-years (95% CI=9.1-15.7). Among the 488 HIV negative specimens, 5 were identified with acute HIV infection using pooling-PCR at an annual rate of 14.02% (95% CI=1.73-26.30). The estimated HIV-1 incidence was 12.02% (95% CI=7.49-16.56) based on BED-CEIA. The HIV incidence estimated with three different approaches was different among subgroups. In the highly HIV prevalent MSM, it costs US$ 1724 to detect one AHI case, while detection of one case of RHI with BED assay costs only US$ 42. Three approaches generated comparable and high HIV incidences, pooling PCR and prospective cohort are more close to the true level of incidence, while BED-CEIA seemed to be the most convenient and economical approach for at-risk population’s HIV incidence evaluation at the beginning of HIV pandemic. HIV-1 incidences were alarmingly high among MSM population in Chongqing, particularly within the subgroup under 25 years of age and those migrants aged between 25 to 34 years.

Keywords: BED-CEIA, HIV, incidence, pooled PCR, prospective cohort

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Authors: George Mahalu

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The Chua diode has been configured over time in various ways, using electronic structures like as operational amplifiers (OAs) or devices with gas or semiconductors. When discussing the use of semiconductor devices, tunnel diodes (Esaki diodes) are most often considered, and more recently, transistorized configurations such as lambda diodes. The paper-work proposed here uses in the modeling a lambda diode type configuration consisting of two Junction Field Effect Transistors (JFET). The original scheme is created in the MULTISIM electronic simulation environment and is analyzed in order to identify the conditions for the appearance of evolutionary unpredictability specific to nonlinear dynamic systems with chaos-induced behavior. The chaotic deterministic oscillator is one autonomous type, a fact that places it in the class of Chua’s type oscillators, the only significant and most important difference being the presence of a nonlinear device like the one mentioned structure above. The chaotic behavior is identified both by means of strange attractor-type trajectories and visible during the simulation and by highlighting the hypersensitivity of the system to small variations of one of the input parameters. The results obtained through simulation and the conclusions drawn are useful in the further research of ways to implement such constructive electronic solutions in theoretical and practical applications related to modern small signal amplification structures, to systems for encoding and decoding messages through various modern ways of communication, as well as new structures that can be imagined both in modern neural networks and in those for the physical implementation of some requirements imposed by current research with the aim of obtaining practically usable solutions in quantum computing and quantum computers.

Keywords: chaos, lambda diode, strange attractor, nonlinear system

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Authors: Einav Srulovici, Michal Grinstein-Weiss, George Knafl, Linda Beeber, Shawn Kneipp, Barbara Mark

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Background: The asset-building theoretical framework (ABTF) is acknowledged as the most complete framework thus far for depicting the relationships between asset accumulation (the stock of a household’s saved resources available for future investment) and health outcomes. Although the ABTF takes into consideration the reciprocal relationship between asset accumulation and health, no ABTF based study has yet examined this relationship. Therefore, the purpose of this study was to test the ABTF and psychological distress, focusing on the reciprocal relationship between assets accumulation and psychological distress. Methods: The study employed longitudinal data from 6,295 families from the 2001 and 2007 Panel Study of Income Dynamics data sets. Structural equation modeling (SEM) was used to test the reciprocal relationship between asset accumulation and psychological distress. Results: In general, the data displayed a good fit to the model. The longitudinal SEM found that asset accumulation significantly increased with a decreased in psychological distress over time, while psychological distress significantly increased with an increase in asset accumulation over time, confirming the existence of the hypothesized reciprocal relationship. Conclusions: Individuals who are less psychological distressed might have more energy to engage in activities, such as furthering their education or obtaining better jobs that are in turn associated with greater asset accumulation, while those who have greater assets may invest those assets in riskier investments, resulting in increased psychological distress. The confirmation of this reciprocal relationship highlights the importance of conducting longitudinal studies and testing the reciprocal relationship between asset accumulation and other health outcomes.

Keywords: asset-building theoretical framework, psychological distress, structural equation modeling, reciprocal relationship

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Authors: Iman A. Saad, Loay E. George

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Iris pattern is an important biological feature of human body; it becomes very hot topic in both research and practical applications. In this paper, an algorithm is proposed for iris recognition and a simple, efficient and fast method is introduced to extract a set of discriminatory features using first order gradient operator applied on grayscale images. The gradient based features are robust, up to certain extents, against the variations may occur in contrast or brightness of iris image samples; the variations are mostly occur due lightening differences and camera changes. At first, the iris region is located, after that it is remapped to a rectangular area of size 360x60 pixels. Also, a new method is proposed for detecting eyelash and eyelid points; it depends on making image statistical analysis, to mark the eyelash and eyelid as a noise points. In order to cover the features localization (variation), the rectangular iris image is partitioned into N overlapped sub-images (blocks); then from each block a set of different average directional gradient densities values is calculated to be used as texture features vector. The applied gradient operators are taken along the horizontal, vertical and diagonal directions. The low order norms of gradient components were used to establish the feature vector. Euclidean distance based classifier was used as a matching metric for determining the degree of similarity between the features vector extracted from the tested iris image and template features vectors stored in the database. Experimental tests were performed using 2639 iris images from CASIA V4-Interival database, the attained recognition accuracy has reached up to 99.92%.

Keywords: iris recognition, contrast stretching, gradient features, texture features, Euclidean metric

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Authors: Yuan-Jye Tseng, Ching-Yen Chen

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In the design cycle, a main design task is to determine the external shape of the product. The external shape of a product is one of the key factors that can affect the customers’ preferences linking to the motivation to buy the product, especially in the case of a consumer electronic product such as a mobile phone. The relationship between the external shape and the customer preferences needs to be studied to enhance the customer’s purchase desire and action. In this research, a design for customer preferences model is developed for investigating the relationships between the external shape and the customer preferences of a product. In the first stage, the names of the geometric features are collected and evaluated from the data of the specified internet web pages using the developed text miner. The key geometric features can be determined if the number of occurrence on the web pages is relatively high. For each key geometric feature, the numerical values are explored using the text miner to collect the internet data from the web pages. In the second stage, a cluster analysis model is developed to evaluate the numerical values of the key geometric features to divide the external shapes into several groups. Several design suggestion cases can be proposed, for example, large model, mid-size model, and mini model, for designing a mobile phone. A customer preference index is developed by evaluating the numerical data of each of the key geometric features of the design suggestion cases. The design suggestion case with the top ranking of the customer preference index can be selected as the final design of the product. In this paper, an example product of a notebook computer is illustrated. It shows that the external shape of a product can be used to drive customer preferences. The presented design for customer preferences model is useful for determining a suitable external shape of the product to increase customer preferences.

Keywords: cluster analysis, customer preferences, design evaluation, design for customer preferences, product design

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Authors: Paridhi Agarwal, Kusum M. George

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A cynic is someone upset about the future prematurely. In today’s highly competitive workplace, cynicism has become a prominent concern. It is a controversial issue that brings about psychological disengagement and antagonism towards the management. In organizational sciences, scientific investigation of this negative work behavior is lacking, and so there is no universal definition so far. But most commonly, Organizational Cynicism (OC) has been characterized as an unfavorable attitude towards the organization, encompassing a belief that the organization has low integrity, negative affect, and depreciative behavioral tendencies. Given its prevalence, this study aims to contribute to the existing body of knowledge on OC. This research examines the predictability of OC from two factors- Perceived Organizational Support (POS) and Emotional Intelligence (EI) among millennials in India as well as identify contradictions in today’s scenario. Standardized Organizational Cynicism Scale comprising of three components, Perceived Organizational Support Questionnaire and Goleman’s Emotional Intelligence Test are used on a convenient sample of 104 corporate sector employees in the age range 22-35 years. Correlation test elucidated the relationships, and regression analysis revealed the level of influence of the above variables on OC. Surprisingly, Emotional-Social Awareness had stronger relationships with all dimensions of OC in males as compared to females. It was also seen that EI and POS, together with predicted OC, but separately, only POS accounted for variability in OC, and this impact was much stronger for males, implying that there are other important factors that make females cynical at work. Thus, the over-emphasis on EI training for the millennial generation has also been challenged in this study. It can be said that there are avertible preconditions to the negative attitude- OC. This research has important managerial implications in areas of recruitment, training, and organizational environment.

Keywords: emotional intelligence, millennials, organizational cynicism, perceived organizational support.

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Authors: George Vernon Byrd, Bhim Bahadur Ghaley, Eri Hayashi

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In urban farming, research and innovation are taking place at an unprecedented pace, and soilless growing technologies are emerging at different rates motivated by different objectives in various parts of the world. Local food production is ultimately a main objective everywhere, but adoption rates and expressions vary with socio-economic drivers. Herein, the status of hydroponics and aquaponics is summarized for four countries with diverse socio-economic settings: Europe (Denmark), Asia (Japan and Nepal) and North America (US). In Denmark, with a strong environmental ethic, soilless growing is increasing in urban agriculture because it is considered environmentally friendly. In Japan, soil-based farming is being replaced with commercial plant factories using advanced technology such as complete environmental control and computer monitoring. In Nepal, where rapid loss of agriculture land is occurring near cities, dozens of hydroponics and aquaponics systems have been built in the past decade, particularly in “non-traditional” sites such as roof tops to supplement family food. In the US, where there is also strong interest in locally grown fresh food, backyard and commercial systems have proliferated. Nevertheless, soilless growing is still in the research and development and early adopter stages, and the broad contribution of hydroponics and aquaponics to food security is yet to be fully determined. Nevertheless, current adoption of these technologies in diverse environments in different socio-economic settings highlights the potential contribution to food security with social and environmental benefits which contribute to several Sustainable Development Goals.

Keywords: aquaponics, hydroponics, soilless agriculture, urban agriculture

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Authors: George-Anokwuru Chioma Chidinma Bernadette

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This paper investigated the effect of trade liberalization on domestic private investment in Nigeria from 1981 to 2020. To achieve this objective, secondary data on domestic private investment, trade openness, exchange rate and interest rate were sourced from the statistical bulletin of Nigeria’s apex bank. The Autoregressive Distributed Lag (ARDL) technique was used as the main analytical tool. The ARDL Bounds test revealed the existence of long run association among the variables. The results revealed that trade openness and exchange rate have positive and insignificant relationship with domestic private investment both in the long and short runs. At the same time, interest rate has negative relationship with domestic private investment both in the long and short runs. Therefore, it was concluded that there is no significant relationship between trade openness, exchange rate, interest rate and domestic private investment in Nigeria during the period of study. Based on the findings, the study recommended that government should formulate trade policies that will encourage the growth of domestic private investment in Nigeria. To achieve this, government should ensure consistency in trade policies and at the same time strengthen the existing policies to build investors’ confidence. Also, government should make available an investment-friendly environment, as well as monitor real sector operators to ensure that foreign exchange allocations are not diverted. Government should increase capital investment in education, housing, transportation, agriculture, health, power, road construction, national defense, among others that will help the various sectors of the economy to function very well thereby making the business environment friendly thereby enhancing the growth and development of the country.

Keywords: trade openness, domestic private investment, ARDL, exchange rate

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Authors: Qingsong Xiong, Cheng Yuan, Qingzhao Kong, Haibei Xiong

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Deep-learning-driven approaches based on vibration responses have attracted larger attention in rapid structural condition assessment while obtaining sufficient measured training data with corresponding labels is relevantly costly and even inaccessible in practical engineering. This study proposes an integrated label propagation network for structural condition assessment, which is able to diffuse the labels from continuously-generating measurements by intact structure to those of missing labels of damage scenarios. The integrated network is embedded with damage-sensitive features extraction by deep autoencoder and pseudo-labels propagation by optimized fuzzy clustering, the architecture and mechanism which are elaborated. With a sophisticated network design and specified strategies for improving performance, the present network achieves to extends the superiority of self-supervised representation learning, unsupervised fuzzy clustering and supervised classification algorithms into an integration aiming at assessing damage conditions. Both numerical simulations and full-scale laboratory shaking table tests of a two-story building structure were conducted to validate its capability of detecting post-earthquake damage. The identifying accuracy of a present network was 0.95 in numerical validations and an average 0.86 in laboratory case studies, respectively. It should be noted that the whole training procedure of all involved models in the network stringently doesn’t rely upon any labeled data of damage scenarios but only several samples of intact structure, which indicates a significant superiority in model adaptability and feasible applicability in practice.

Keywords: autoencoder, condition assessment, fuzzy clustering, label propagation

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