Search results for: regression tree

Authors: David Cook, Brynhildur Davidsdottir, Dadi. M. Kristofersson

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The approval of development projects with significant environmental impacts implies that the economic costs of the affected environmental resources must be less than the financial benefits, but such irreversible decisions are frequently made without ever attempting to estimate the monetary value of the losses. Due to this knowledge gap in the processes informing decision-making, development projects are commonly approved despite the potential for social welfare to be undermined. Heeding a repeated call by the OECD to commence economic accounting of environmental impacts as part of the cost-benefit analysis process for Icelandic energy projects, this paper sets out the results pertaining to the nation’s first two contingent valuation studies of geothermal areas likely to be developed in the near future. Interval regression using log-transformation was applied to estimate willingness to pay (WTP) for the preservation of the high-temperature Eldvörp and Hverahlíð fields. The estimated mean WTP was 8,333 and 7,122 ISK for Eldvörp and Hverahlíð respectively. Scaled up to the Icelandic population of national taxpayers, this equates to estimated total economic value of 2.10 and 1.77 billion ISK respectively. These results reinforce arguments in favour of accounting for the environmental impacts of Iceland’s future geothermal power projects as a mandatory component of the exploratory and production license application process. Further research is necessary to understand the economic impacts to specific ecosystem services associated with geothermal environments, particularly connected to changes in recreational amenity. In so doing, it would be possible to gain greater comprehension of the various components of total economic value, evolving understanding of why one geothermal area – in this case, Eldvörp – has a higher preservation value than another.

Keywords: decision-making, contingent valuation, geothermal energy, preservation

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Authors: Agada N. Ihuoma, Nagata Yasunori

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Artificial intelligence (AI) techniques play a crucial role in predicting the expected energy outcome and its performance, analysis, modeling, and control of renewable energy. Renewable energy is becoming more popular for economic and environmental reasons. In the face of global energy consumption and increased depletion of most fossil fuels, the world is faced with the challenges of meeting the ever-increasing energy demands. Therefore, incorporating artificial intelligence to predict solar radiation outcomes from the intermittent sunlight is crucial to enable a balance between supply and demand of energy on loads, predict the performance and outcome of solar energy, enhance production planning and energy management, and ensure proper sizing of parameters when generating clean energy. However, one of the major problems of forecasting is the algorithms used to control, model, and predict performances of the energy systems, which are complicated and involves large computer power, differential equations, and time series. Also, having unreliable data (poor quality) for solar radiation over a geographical location as well as insufficient long series can be a bottleneck to actualization. To overcome these problems, this study employs the anaconda Navigator (Jupyter Notebook) for machine learning which can combine larger amounts of data with fast, iterative processing and intelligent algorithms allowing the software to learn automatically from patterns or features to predict the performance and outcome of Solar Energy which in turns enables the balance of supply and demand on loads as well as enhance production planning and energy management.

Keywords: artificial Intelligence, backward elimination, linear regression, solar energy

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Authors: A. Dinelka Panagoda, Bathiya Bandara, Chamod Wijetunga, Chathura Malinda, Lakmal Rupasinghe, Chethana Liyanapathirana

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This research takes us forward with the concepts of Federated Learning and Software-Defined Networking (SDN) to introduce an efficient malware detection technique and provide a mitigation mechanism to give birth to a resilient and automated healthcare sector network system by also adding the feature of extended privacy preservation. Due to the daily transformation of new malware attacks on hospital Integrated Clinical Environment (ICEs), the healthcare industry is at an undefinable peak of never knowing its continuity direction. The state of blindness by the array of indispensable opportunities that new medical device inventions and their connected coordination offer daily, a factor that should be focused driven is not yet entirely understood by most healthcare operators and patients. This solution has the involvement of four clients in the form of hospital networks to build up the federated learning experimentation architectural structure with different geographical participation to reach the most reasonable accuracy rate with privacy preservation. While the logistic regression with cross-entropy conveys the detection, SDN comes in handy in the second half of the research to stack up the initial development phases of the system with malware mitigation based on policy implementation. The overall evaluation sums up with a system that proves the accuracy with the added privacy. It is no longer needed to continue with traditional centralized systems that offer almost everything but not privacy.

Keywords: software-defined network, federated learning, privacy, integrated clinical environment, decentralized learning, malware detection, malware mitigation

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Authors: Ali panahi-Kosar Khosravi

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Earthquake resilience is one of the most important theoretical and practical concepts in crisis management. Over the past few decades, the rapid growth of urban areas and developing lower urban areas (especially in developing countries) have made them more vulnerable to human and natural crises. Therefore, the resilience of urban communities, especially low-income and unhealthy neighborhoods, is of particular importance. The present study seeks to assess and evaluate the resilience of neighborhoods in the center of district 6 of Tabriz in terms of awareness, knowledge and personal skills, social and psychological capital, managerial-institutional, and the ability to return to appropriate and sustainable conditions. The research method in this research is descriptive-analytical. The authors used library and survey methods to collect information and a questionnaire to assess resilience. The statistical population of this study is the total households living in the four neighborhoods of Shanb Ghazan, Khatib, Gharamalek, and Abuzar alley. Three hundred eighty-four families from four neighborhoods were selected based on the Cochran formula using a simple random sampling method. A one-sample t-test, simple linear regression, and structural equations were used to test the research hypotheses. Findings showed that only two social and psychological awareness and capital indicators in district 6 of Tabriz had a favorable and approved status. Therefore, considering the multidimensional concept of resilience, district 6 of Tabriz is in an unfavorable resilience situation. Also, the findings based on the analysis of variance indicated no significant difference between the neighborhoods of district 6 in terms of resilience, and most neighborhoods are in an unfavorable situation.

Keywords: resilience, statistical analysis, earthquake, district 6 of tabriz

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Authors: Watcharapong Yaowarat, Thanee Kaewthummanukul, Waruntorn Jongrungrotsakul

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Noise-induced hearing loss, the most significant occupational and safety problem among the working population, can be effectively prevented through hearing protection devices (HPDs) use. This study aimed to examine whether the following factors, perceived benefits, perceived barriers, perceived self-efficacy, and interpersonal and situational influences about using hearing protection could predict HPD use among 132 qualified workers in production lines at Kaolin Mineral Dressing factories, Uttaradit and Lampang provinces. Data collection was undertaken from August to September 2020 according to the interview form developed by Yaruang et al. (2010), which was assured by a panel of experts and its reliability value was at an acceptable level. Data analysis was performed using logistic regression analysis. The results revealed that only the situational factor of using hearing protection could predict HPD use, which accounted for 21.80 percent of the total variance for HPD use. It was also found that the study sample who had a score for the situational factors on using hearing protection greater than or equal to the median was 4.16 times more likely to use HPDs than those who had lower median scores. (OR = 4.16, p < .05). The results, thus, indicate that organization policies addressing worker health along with enhancing a supportive environment for HPD use, in particular, the provision of various HPDs, are of great importance. Therefore, occupational health nurses and related health teams should enhance workers’ use of HPDs effectively through knowledge dissemination by adopting strategies appropriate to the workplace context leading to an achievement of worker health policy focusing on work safety.

Keywords: predicting factors, hearing protection device, factors predicting hearing protection device use, kaolin mineral dressing factories

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Authors: N. F. Hamid, A. Kipar, J. Stewart, D. J. Antoine, B. K. Park, D. P. Williams

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Acetaminophen (APAP) is a widely used analgesic that is safe at therapeutic doses. The mouse model of APAP has been extensively used for studies on pathogenesis and intervention of drug induced liver injury based on the CytP450 mediated formation of N-acetyl-p-benzo-quinoneimine and, more recently, as model for mechanism based biomarkers. Delay of the fasted CD1 mice to rebound to the basal level of hepatic GSH compare to fed mice is reported in this study. Histologically, 15 hours fasted mice prior to APAP treatment leading to overall more intense cell loss with no evidence of apoptosis as compared to non-fasted mice, where the apoptotic cells were clearly seen on cleaved caspase-3 immunostaining. After 15 hours post APAP administration, hepatocytes underwent stage of recovery with evidence of mitotic figures in fed mice and return to completely no histological difference to control at 24 hours. On the contrary, the evidence of ongoing cells damage and inflammatory cells infiltration are still present on fasted mice until the end of the study. To further measure the regenerative capacity of the hepatocytes, the inflammatory mediators of cytokines that involved in the progression or regression of the toxicity like TNF-α and IL-6 in liver and spleen using RT-qPCR were also included. Yet, quantification of proliferating cell nuclear antigen (PCNA) has demonstrated the time for hepatic regenerative in fasted is longer than that to fed mice. Together, these data would probably confirm that fasting prior to APAP treatment does not only modulate liver injury, but could have further effects to delay subsequent regeneration of the hepatocytes.

Keywords: acetaminophen, liver, proliferating cell nuclear antigen, regeneration, apoptosis

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Authors: Gadanya, A.M., Ponfa, S., Jibril, M.M., Abubakar, S. M.

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Background: Edible insects such as grasshopper are important sources of food for humans, and have been consumed as traditional foods by many indigenous communities especially in Africa, Asia, and Latin America. These communities have developed their skills and techniques in harvesting, preparing, consuming, and preserving edible insects, widely contributing to the role played by the use of insects in human nutrition. Aim/ objective: This study was aimed at determining the effect of insect enriched sprouted soyabean /millet based food on some gut health markers in albino rats. Methods. Four different formulations of Complementary foods (i.e Complementary Food B (CFB): sprouted millet (SM), Complementary Food C (CFC): sprouted soyabean (SSB), Complementary Food D (CFD): sprouted soybean and millet (SSBM) in a ratio of (50:50) and Complementary Food E (CFE): insect (grasshopper) enriched sprouted soybean and millet (SSBMI) in a ratio of (50:25:25)) were prepared. Proximate composition and short chain fatty acid contents were determined. Thirty albino rats were divided into5 groups of six rats each. Group 1(CDA) were fed with basal diet and served as a control group, while groups 2,3,4 and 5 were fed with the corresponding complimentary foods CFB, CFC, CFD and CFE respectively daily for four weeks. Concentrations of fecal protein, serum total carotenoids and nitric oxide were determined. DNA extraction for molecular isolation and characterization were carried out followed by PCR, the use of mega 11 software and NCBI blast for construction of the phylogenetic tree and organism identification respectively. Results: Significant increase (P<0.05) in percentage ash, fat, protein and moisture contents, as well as short chain fatty acid (acetate, butyrate and propionate) concentrations were recorded in the insect enriched sprouted composite food (CFE) when compared with the CFA, CFB, CFC and CFD composite food. Faecal protein, carotenoid and nitric oxide concentrations were significantly lower (P>0.05) in group 5 in comparison to groups 1to 4. Ruminococcus bromii and Bacteroidetes were molecularly isolated and characterized by 16s rRNA from the sprouted millet/sprouted soybean and the insect enriched sprouted soybean/sprouted millet based food respectively. The presence of these bacterial strains in the feaces of the treated rats is an indication that the gut of the treated rats is colonized by good gut bacteria, hence, an improved gut health. Conclusion: Insect enriched sprouted soya bean/sprouted millet based complementary diet showed a high composition of ash, fat, protein and fiber. Thus, could increase the availability of short chain fatty acids whose role to the host organism cannot be overemphasized. It was also found to have decrease the level of faecal protein, carotenoid and nitric oxide in the serum which is an indication of an improvement in the immune system function.

Keywords: gut-health, insect, millet, soybean, sprouted

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Authors: Gaurav Kumar Mishra, Sanjeeva Nayaka, Dalip Kumar Upreti

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Our nature exhibited presence of a number of unique plants which can be used as indicator of environmental condition of particular place. Lichens are unique plant which has an ability to absorb not only organic, inorganic and metaloties but also absorb radioactive nuclide substances present in the environment. In the present study pyrenocarpous lichens will used as indicator of good forest health in a particular place. The Pyrenocarpous lichens are simple crust forming with black dot like perithecia have few characters for their taxonomical segregation as compared to their foliose and fruticose brethrean. The thallus colour and nature, presence and absence of hypothallus are only few characters of thallus are used to segregate the pyrenocarpous taxa. The fruiting bodies of pyrenolichens i.e. ascocarps are perithecia. The perithecia and the contents found within them posses many important criteria for the segregation of pyrenocarpous lichen taxa. The ascocarp morphology, ascocarp arrangement, the perithecial wall, ascocarp shape and colour, ostiole shape and position, ostiole colour, ascocarp anatomy including type of paraphyses, asci shape and size, ascospores septation, ascospores wall and periphyses are the valuable charcters used for segregation of different pyrenocarpous lichen taxa. India is represented by the occurrence of the 350 species of 44 genera and eleven families. Among the different genera Pyrenula is dominant with 82 species followed by the Porina with 70 species. Recently, systematic of the pyrenocarpous lichens have been revised by American and European lichenologists using phylogenetic methods. Still the taxonomy of pyrenocarpous lichens is in flux and information generated after the completion of this study will play vital role in settlement of the taxonomy of this peculiar group of lichens worldwide. The Indian Himalayan region exhibit rich diversity of pyrenocarpous lichens in India. The western Himalayan region has luxuriance of pyrenocarpous lichens due to its unique topography and climate condition. However, the eastern Himalayan region has rich diversity of pyrenocarpous lichens due to its warmer and moist climate condition. The rich moist and warmer climate in eastern Himalayan region supports forest with dominance of evergreen tree vegetation. The pyrenocarpous lichens communities are good indicator of young and regenerated forest type. The rich diversity of lichens clearly indicates that moist of the forest within the eastern Himalayan region has good health of forest. Due to fast pace of urbanization and other developmental activities will defiantly have adverse effects on the diversity and distribution of pyrenocarpous lichens in different forest type and the present distribution pattern will act as baseline data for carried out future biomonitoring studies in the area.

Keywords: lichen diversity, indicator species, environmental factors, pyrenocarpous

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Authors: Md Ruhul Amin

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This study was conducted in the experimental field of the Department of Entomology, Bangabandhu Sheikh Mujibur Rahman Agricultural University, Gazipur, Bangladesh during November 2017 to May 2018 with a view to understanding the seasonal abundance of the major sucking pests namely thrips, aphid and red spider mite on rose. The findings showed that the thrips started to build up their population from the middle of January with abundance 1.0 leaf⁻¹, increased continuously, reached to the peak level (2.6 leaf⁻¹) in the middle of February and then declined. Aphid started to build up their population from the second week of November with abundance 6.0 leaf⁻¹, increased continuously, reached to the peak level (8.4 leaf⁻¹) in the last week of December and then declined. Mite started to build up their population from the first week of December with abundance 0.8 leaf⁻¹, increased continuously, reached to the peak level (8.2 leaf⁻¹) in the second week of March and then declined. Thrips and mite prevailed until the last week of April, and aphid showed their abundance till last week of May. The daily mean temperature, relative humidity, and rainfall had an insignificant negative correlation with thrips and significant negative correlation with aphid abundance. The daily mean temperature had significant positive, relative humidity had an insignificant positive, and rainfall had an insignificant negative correlation with mite abundance. The multiple linear regression analysis showed that the weather parameters together contributed 38.1, 41.0 and 8.9% abundance on thrips, aphid and mite on rose, respectively and the equations were insignificant.

Keywords: aphid, mite, thrips, weather factors

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Authors: Malory Jonata

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Chlordecone (CLD) is an organochlorine pesticide used between 1971 and 1993 in both Guadeloupe and Martinique for the control of banana black weevil. The bishomocubane structure which characterizes this chemical compound led to high stability in organic matter and high persistence in the environment. Recently, researchers found that CLD can be degraded by isolated bacteria consortiums and, particularly, by bacteria such as Citrobacter sp 86 and Delsulfovibrio sp 86. Actually, six transformation product families of CLD are known. Moreover, the latest discovery showed that CLD was disappearing faster than first predicted in highly contaminated soil in Guadeloupe. However, the toxicity of transformation products is still unknown, and knowledge has to be deepened on the degradation ways and chemical characteristics of chlordecone and its transformation products. Microbial fuel cells (MFC) are electrochemical systems that can convert organic matter into electricity thanks to electroactive bacteria. These bacteria can exchange electrons through their membranes to solid surfaces or molecules. MFC have proven their efficiency as bioremediation systems in water and soils. They are already used for the bioremediation of several organochlorine compounds such as perchlorate, trichlorophenol or hexachlorobenzene. In this study, a three-electrodes system, inspired by MFC, is used to try to degrade chlordecone using bacteria from a mangrove swamp in Martinique. As we know, some mangrove bacteria are electroactive. Furthermore, the CLD rate seems to decline in mangrove swamp sediments. This study aims to prove that electroactive bacteria from a mangrove swamp in Martinique can degrade CLD thanks to a three-electrodes bioelectrochemical system. To achieve this goal, the tree-electrodes assembly has been connected to a potentiostat. The substrate used is mangrove water and sediments sampled in the mangrove swamp of La Trinité, a coastal city in Martinique, where CLD contamination has already been studied. Electroactive biofilms are formed by imposing a potential relative to Saturated Calomel Electrode using chronoamperometry. Moreover, their comportment has been studied by using cyclic voltametry. Biofilms have been studied under different imposed potentials, several conditions of the substrate and with or without CLD. In order to quantify the evolution of CLD rates in the substrate’s system, gas chromatography coupled with mass spectrometry (GC-MS) was performed on pre-treated samples of water and sediments after short, medium and long-term contact with the electroactive biofilms. Results showed that between -0,8V and -0,2V, the three-electrodes system was able to reduce the chemical in the substrate solution. The first GC-MS analysis result of samples spiked with CLD seems to reveal decreased CLD concentration over time. In conclusion, the designed bioelectrochemical system can provide the necessary conditions for chlordecone degradation. However, it is necessary to improve three-electrodes control settings in order to increase degradation rates. The biological pathways are yet to enlighten by biologicals analysis of electroactive biofilms formed in this system. Moreover, the electrochemical study of mangrove substrate gives new informations on the potential use of this substrate for bioremediation. But further studies are needed to a better understanding of the electrochemical potential of this environment.

Keywords: bioelectrochemistry, bioremediation, chlordecone, mangrove swamp

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Authors: Yao Song

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Objectives: We aimed to explore the clinicodemographic characteristics and prognosis of grey zone squamous cell cancer (GZSCC) located in the overlapping or ambiguous area of the oral cavity and oropharynx and to identify valuable factors that would improve its differential diagnosis and prognosis. Methods: Information of GZSCC patients in the Surveillance, Epidemiology, and End Results (SEER) database was compared to patients with an oral cavity (OCSCC) and oropharyngeal (OPSCC) squamous cell carcinomas with corresponding HPV status, respectively. Kaplan-Meier method with log-rank test and multivariate Cox regression analysis were applied to assess associations between clinical characteristics and overall survival (OS). A predictive model integrating age, gender, marital status, HPV status, and staging variables was conducted to classify GZSCC patients into three risk groups and verified internally by 10-fold cross validation. Results: A total of 3318 GZSCC, 10792 OPSCC, and 6656 OCSCC patients were identified. HPV-positive GZSCC patients had the best 5-year OS as HPV-positive OPSCC (81% vs. 82%). However, the 5-year OS of HPV-negative/unknown GZSCC (43%/42%) was the worst among all groups, indicating that HPV status and the overlapping nature of tumors were valuable prognostic predictors in GZSCC patients. Compared with the strategy of dividing GZSCC into two groups by HPV status, the predictive model integrating more variables could additionally identify a unique high-risk GZSCC group with the lowest OS rate. Conclusions: GZSCC patients had distinct clinical characteristics and prognoses compared with OPSCC and OCSCC; integrating HPV status and other clinical factors could help distinguish GZSCC and predict their prognosis.

Keywords: GZSCC, OCSCC, OPSCC, HPV

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Authors: Vincent A. Adzika, Franklin N. Glozah, Collins S. K. Ahorlu

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Background: Sickle Cell Disease (SCD) is of major public-health concern globally, with majority of patients living in Africa. Despite its relevance, there is a dearth of research to determine the socio-demographic distribution and psychosocial impact of SCD in Africa. The objective of this study therefore was to examine the socio-demographic distribution and psychosocial consequences of SCD among patients in Ghana and to assess their quality of life and coping mechanisms. Methods: A cross-sectional research design was used, involving the completion of questionnaires on socio-demographic characteristics, quality of life of individuals, anxiety and depression. Participants were 387 male and female patients attending a sickle cell clinic in a public hospital. Results: Results showed no gender and marital status differences in anxiety and depression. However, there were age and level of education variances in depression but not in anxiety. In terms of quality of life, patients were more satisfied by the presence of love, friends, relatives as well as home, community and neighbourhood environment. While pains of varied nature and severity were the major reasons for attending hospital in SCD condition, going to the hospital as well as having Faith in God was the frequently reported mechanisms for coping with an unbearable SCD attacks. Multiple regression analysis showed that some socio-demographic and quality of life indicators had strong associations with anxiety and/or depression. Conclusion: It is recommended that a multi-dimensional intervention strategy incorporating psychosocial dimensions should be considered in the treatment and management of SCD.

Keywords: anxiety, depression, sickle cell disease, socio-demographic quality of life, characteristics, Ghana

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Authors: Ehsan Pegah, Huabei Liu

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Determination of the internal friction angle (φ) in natural soil deposits is an important issue in geotechnical engineering. The main objective of this study was to examine the evaluation of this parameter in overconsolidated granular soil deposits by using the P-wave velocity and the anisotropic components of S-wave velocity (i.e., both the vertical component (SV) and the horizontal component (SH) of S-wave). To this end, seventeen pairs of P-wave and S-wave seismic refraction profiles were carried out at three different granular sites in Iran using non-invasive seismic wave methods. The acquired shot gathers were processed, from which the P-wave, SV-wave and SH-wave velocities were derived. The reference values of φ and overconsolidation ratio (OCR) in the soil deposits were measured through laboratory tests. By assuming cross-anisotropy of the soils, the P-wave and S-wave velocities were utilized to develop an equation for calculating the coefficient of lateral earth pressure at-rest (K₀) based on the theory of elasticity for a cross-anisotropic medium. In addition, to develop an equation for OCR estimation in granular geomaterials in terms of SH/SV velocity ratios, a general regression analysis was performed on the resulting information from this research incorporated with the respective data published in the literature. The calculated K₀ values coupled with the estimated OCR values were finally employed in the Mayne and Kulhawy formula to evaluate φ in granular soil deposits. The results showed that reliable values of φ could be estimated based on the seismic wave velocities. The findings of this study may be used as the appropriate approaches for economic and non-invasive determination of in-situ φ in granular soil deposits using the surface seismic surveys.

Keywords: angle of internal friction, overconsolidation ratio, granular soils, P-wave velocity, SV-wave velocity, SH-wave velocity

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Authors: Prabhat Kashyap, Krishan Kumar

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Delhi, the capital of India, is one of the most populated and polluted city among the world. In terms of air quality, Delhi’s air is degrading day by day & becomes worst of any major city in the world. The role of biogenic volatile organic compounds (BVOCs) is not much studied in cities like Delhi as a culprit for degraded air quality. They not only play a critical role in rural areas but also determine the atmospheric chemistry of urban areas as well. Particularly, Isoprene (2-methyl 1,3-butadiene, C5H8) is the single largest emitted compound among other BVOCs globally, that influence the tropospheric ozone chemistry in urban environment as the ozone forming potential of isoprene is very high. It is mainly emitted by vegetation & a small but significant portion is also released by vehicular exhaust of petrol operated vehicles. This study investigates the spatial and temporal variations of quantitative measurements of isoprene emissions along with different traffic tracers in 2 different seasons (post-monsoon & winter) at four different locations of Delhi. For the quantification of anthropogenic and biogenic isoprene, two sites from traffic intersections (Punjabi Bagh & CRRI) and two sites from vegetative locations (JNU & Yamuna Biodiversity Park) were selected in the vicinity of isoprene emitting tree species like Ficus religiosa, Dalbergia sissoo, Eucalyptus species etc. The concentrations of traffic tracers like benzene, toluene were also determined & their robust ratios with isoprene were used to differentiate anthropogenic isoprene with biogenic portion at each site. The ozone forming potential (OFP) of all selected species along with isoprene was also estimated. For collection of intra-day samples (3 times a day) in each season, a pre-conditioned fenceline monitoring (FLM) carbopack X thermal desorption tubes were used and further analysis was done with Gas chromatography attached with mass spectrometry (GC-MS). The results of the study proposed that the ambient air isoprene is always higher in post-monsoon season as compared to winter season at all the sites because of high temperature & intense sunlight. The maximum isoprene emission flux was always observed during afternoon hours in both seasons at all sites. The maximum isoprene concentration was found to be 13.95 ppbv at Biodiversity Park during afternoon time in post monsoon season while the lower concentration was observed as low as 0.07 ppbv at the same location during morning hours in winter season. OFP of isoprene at vegetation sites is very high during post-monsoon because of high concentrations. However, OFP for other traffic tracers were high during winter seasons & at traffic locations. Furthermore, high correlation between isoprene emissions with traffic volume at traffic sites revealed that a noteworthy share of its emission also originates from road traffic.

Keywords: biogenic VOCs, isoprene emission, anthropogenic isoprene, urban vegetation

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Authors: Habte Tadesse Likassa, Bacha Edosa

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Customer’s satisfaction was very important thing that is required for the existence of banks to be more productive and success in any organization and business area. The main goal of the study is assessing and identifying factors that influence customer’s satisfaction in West Shoa Zone of Commercial Bank of Ethiopia (Holeta, Ginchi, Ambo, Gedo and Bako). Stratified random sampling procedure was used in the study and by using simple random sampling (lottery method) 520 customers were drawn from the target population. By using Probability Proportional Size Techniques sample size for each branch of banks were allocated. Both descriptive and inferential statistics methods were used in the study. A binary logistic regression model was fitted to see the significance of factors affecting customer’s satisfaction in this study. SPSS statistical package was used for data analysis. The result of the study reveals that the overall level of customer’s satisfaction in the study area is low (38.85%) as compared those who were not satisfied (61.15%). The result of study showed that all most all factors included in the study were significantly associated with customer’s satisfaction. Therefore, it can be concluded that based on the comparison of branches on their customers satisfaction by using odd ratio customers who were using Ambo and Bako are less satisfied as compared to customers who were in Holeta branch. Additionally, customers who were in Ginchi and Gedo were more satisfied than that of customers who were in Holeta. Since the level of customers satisfaction was low in the study area, it is more advisable and recommended for concerned body works cooperatively more in maximizing satisfaction of their customers.

Keywords: customers, satisfaction, binary logistic, complain handling process, waiting time

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Authors: Sergio Andres Rojas, Julian Benavides Franco, Juan Tomas Sayago

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An increasing amount of research demonstrates how market mood affects financial markets, but their primary goal is to demonstrate how Trump's tweets impacted US interest rate volatility. Following that lead, this work evaluates the effect that Trump's tweets had during his presidency on local and international stock markets, considering not just volatility but the direction of the movement. Three indexes for Trump's tweets were created relating his activity with movements in the S&P500 using natural language analysis and machine learning algorithms. The indexes consider Trump's tweet activity and the positive or negative market sentiment they might inspire. The first explores the relationship between tweets generating negative movements in the S&P500; the second explores positive movements, while the third explores the difference between up and down movements. A pseudo-investment strategy using the indexes produced statistically significant above-average abnormal returns. The findings also showed that the pseudo strategy generated a higher return in the local market if applied to intraday data. However, only a negative market sentiment caused this effect on daily data. These results suggest that the market reacted primarily to a negative idea reflected in the negative index. In the international market, it is not possible to identify a pervasive effect. A rolling window regression model was also performed. The result shows that the impact on the local and international markets is heterogeneous, time-changing, and differentiated for the market sentiment. However, the negative sentiment was more prone to have a significant correlation most of the time.

Keywords: market sentiment, Twitter market sentiment, machine learning, natural dialect analysis

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Authors: Lavanya Annadi, Fahimeh Jafari

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Transportation brings immense benefits to society, but it also has its costs. Costs include such as the cost of infrastructure, personnel and equipment, but also the loss of life and property in traffic accidents on the road, delays in travel due to traffic congestion and various indirect costs in terms of air transport. More research has been done to identify the various factors that affect road accidents, such as road infrastructure, traffic, sociodemographic characteristics, land use, and the environment. The aim of this research is to predict the probabilistic crash prediction of vehicles using machine learning due to natural and structural reasons by excluding spontaneous reasons like overspeeding etc., in the United States. These factors range from weather factors, like weather conditions, precipitation, visibility, wind speed, wind direction, temperature, pressure, and humidity to human made structures like road structure factors like bump, roundabout, no exit, turning loop, give away, etc. Probabilities are dissected into ten different classes. All the predictions are based on multiclass classification techniques, which are supervised learning. This study considers all crashes that happened in all states collected by the US government. To calculate the probability, multinomial expected value was used and assigned a classification label as the crash probability. We applied three different classification models, including multiclass Logistic Regression, Random Forest and XGBoost. The numerical results show that XGBoost achieved a 75.2% accuracy rate which indicates the part that is being played by natural and structural reasons for the crash. The paper has provided in-deep insights through exploratory data analysis.

Keywords: road safety, crash prediction, exploratory analysis, machine learning

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Authors: Usha Loganathan, Haresh Pandya

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Analysis and correlation of soil properties represent an important outset for precision agriculture and is currently promoted and implemented in the developed world. Establishing relationships among indices of soil salinity has always been a challenging task in salt affected soils necessitating unique approaches for their reclamation and management to sustain long term productivity of Soil. Soil salinity indices like Electrical Conductivity (EC) and Sodium Adsorption Ratio (SAR) are normally used to characterize soils as either sodic or saline sodic. Currently, Determination of Soil sodium adsorption ratio is a more accepted and reliable measure of soil salinity. However, it involves arduous and protracted laboratory investigations which demand evolving new and economical methods to determine SAR based on simple soil salinity index. A linear regression model to predict soil SAR from soil electrical conductivity has been developed and presented in this paper as per which, soil SAR could very well be worked out as a pedotransfer function of soil EC. The present study was carried out in Orathupalayam (11.09-11.11 N latitude and 74.54-77.59 E longitude) in the vicinity of Orathupalayam Reservoir of Noyyal River Basin, India, over a period of 3 consecutive years from September 2013 through February 2016 in different locations chosen randomly through different seasons. The research findings are discussed in the light of micro level farming practices in India and recommend determination of SAR as a low cost technology aiding in the effective management of salt affected agricultural land.

Keywords: electrical conductivity, orathupalayam, pedotranfer function, sodium adsorption ratio

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Authors: Zelalem Markos Borko

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Work-related stress is a reaction that occurs when the work weight progress toward becoming excessive. Therefore, unless properly managed, stress leads to high employee turnover, decreased performance, illness and absenteeism. Yet, little has been addressed regarding work-related stress and its predictors in the study area. Therefore, the objective of this study was to assess stress prevalence and its predictors in the study area. To that effect, a cross-sectional study design was conducted on 281 employees from the Ethiopian Federal Bureau of Investigation by using stratified random sampling techniques. Survey questionnaire scales were employed to collect data. Data were analyzed by percentage, Pearson correlation coefficients, simple linear regression, multiple linear regressions, independent t-test and one-way ANOVA statistical techniques. In the present study13.9% of participants faced high stress, whereas 13.5% of participants faced low stress and the rest 72.6% of officers experienced moderate stress. There is no significant group difference among workers due to age, gender, marital status, educational level, years of service and police rank. This study concludes that factors such as role conflict, performance over-utilization, role ambiguity, and qualitative and quantitative role overload together predict 39.6% of work-related stress. This indicates that 60.4% of the variation in stress is explained by other factors, so other additional research should be done to identify additional factors predicting stress. To prevent occupational stress among police, the Ethiopian Federal Bureau of Investigation should develop strategies based on factors that will help to develop stress reduction management.

Keywords: work-related stress, Ethiopian federal bureau of investigation, predictors, Addis Ababa

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Authors: Alicia Carranza, Hildemar Dos Santos, W. Lawrence Beeson, R. Patti Herring, Kimberly R. Freeman, Adam Arechiga

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Early exposure to trauma can impact health-related behaviors later in life, which poses a considerable challenge for young adults transitioning into independence when they are lacking the necessary skills and support to live a healthy life. The study will be a non-experimental, mixed methods pre- and post-test (where subjects will serve as their own controls) to determine the impact of an eight-week trauma-informed healthy lifestyle program on self-efficacy for adopting health-promoting behaviors and health outcomes among young adults. Forty-two adults, ages 18-24 who are living in Orange County, CA will be recruited to participate in the eight-week trauma-informed healthy living program. Baseline and post-intervention assessments will be conducted to assess changes in self-efficacy for nutrition and physical exercise, sleep quality and quantity, body mass index (kg/m2), and coping skills used by comparing pre- to post-intervention. Some of the planned activities include cooking demonstrations, mindful eating activities and media literacy using Instagram. Frequencies analyses, paired t-test, and multiple regression will be used to determine if there was a change in coping skills. The results of this study can serve to assess the potential for mitigating the effects of Adverse Childhood Experiences (ACEs), or other toxic stress, experienced during adolescence across the lifespan. Young adults who learn how to cope with stress in a healthy way and engage in a healthy lifestyle can be better prepared to role model that behavior to their children.

Keywords: nutrition, healthy lifestyle, trauma-informed, stress management

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Authors: Linnan Zhang

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Linguists, as well as psychologists, have shown great interests in implicit causality in reference processing. However, most frequently-used approaches to this issue are psychological experiments (such as eye tracking or self-paced reading, etc.). This research is a corpus-based one and is assisted with statistical tool – software R. The main focus of the present study is about the competition between verb-based implicit causality and theme structure’s influence on anaphora bias in Mandarin Chinese sentences. In Accessibility Theory, it is believed that salience, which is also known as accessibility, and relevance are two important factors in reference processing. Theme structure, which is a special syntactic structure in Chinese, determines the salience of an antecedent on the syntactic level while verb-based implicit causality is a key factor to the relevance between antecedent and anaphora. Therefore, it is a study about anaphora, combining psychology with linguistics. With analysis of the sentences from corpus as well as the statistical analysis of Multinomial Logistic Regression, major findings of the present study are as follows: 1. When the sentence is stated in a ‘cause-effect’ structure, the theme structure will always be the antecedent no matter forward biased verbs or backward biased verbs co-occur; in non-theme structure, the anaphora bias will tend to be the opposite of the verb bias; 2. When the sentence is stated in a ‘effect-cause’ structure, theme structure will not always be the antecedent and the influence of verb-based implicit causality will outweigh that of theme structure; moreover, the anaphora bias will be the same with the bias of verbs. All the results indicate that implicit causality functions conditionally and the noun in theme structure will not be the high-salience antecedent under any circumstances.

Keywords: accessibility theory, anaphora, theme strcture, verb-based implicit causality

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Authors: Olabisi Badmos, Daniel Callo-Concha, Babatunde Agbola, Andreas Rienow, Klaus Greve, Carsten Jurgens

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Slums are important components of city development planning, especially in Africa where slum growth is on par with urban growth. Purposefully, our knowledge on the residential choice of slum dwellers, which contributes to population growth in slums, is limited. This is the case in Lagos, a megacity reportedly dominated by slum dwellers. Thus, this study aims to disclose the factors influencing the residential choices and causes of people to remain in Lagos slums. Data was collected through questionnaire administration and focus group discussions. Descriptive statistics were used to analyze and describe the factors influencing residential location choice; logistic regression was utilized to determine the extent to which the neighborhood and household attributes, influence slum dwellers decisions to remain in the slums. Results showed that movement to Lagos was the main cause of population growth in slums; most of the migrants were from closer geopolitical zones (in Nigeria). Further, the movement patterns observed support two theories of human mobility in slums: slum as a sink, and as a final destination. Also, the factors that brought most of the slum dwellers to the slums (cheap housing, proximity to work etc.) differs from the ones that made them stay (Gender, employment status, housing status etc.). This study concludes that residential choice and intention to stay are the major contributors to population growth in a slum. It is therefore important for Lagos state Government to incorporate these elements of residential choices of slum dwellers in their slum management policies if the city aims to be free of slums by 2030

Keywords: Lagos, population growth, residential decision choices, slum

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Authors: Faseluka Olamide Tope

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Giving quality education to students with special needs requires that all necessary resources should be harnessed and digital devices has become important part of resources used as instructional materials in educating students with special needs. Teachers who will make use of these technologies are considered as a part of the most important elements in any educational programme and the effective usage of these technologies largely depends on them. Out of numerous determinants of the effective use of these digital devices, this study examines teachers’ attitude and knowledge as predictors of effective use of digital technology for education of special needs student in Oyo state, Nigeria. The descriptive survey research design of the expo-facto type was adopted for the study, using simple random sampling technique. The study was carried out among sixty (60) participants. Two research questions and two research hypotheses were formulated and used. The data collected through the research instruments for the study were analysedusing frequency, percentage, mean and standard deviation, Pearson, Product, Moment Correlation (PPMC) and Multiple Regression Analysis. The study revealed a significant relationship between teachers attitude (50, < 0.05) and effective use of digital technologies for special needs students. Furthermore, there was a significant contribution F (F=4.289; R=0.876 and R2 =0.758) in the joint contribution of the independent variable  (teacher’s attitude and teacher’s knowledge) and dependent variable (effective use of digital technologies) while teachers knowledge have the highest contribution(b=7.926, t=4.376), the study therefore revealed that teachers attitude and knowledge are potent factors that predicts the effective usage of digital technologies for the education of special needs student. The study recommended that due to the ever-changing nature of technology which comes with new features, teachers should be equipped with appropriate knowledge in order to effectively make use of them and teachers should also develop right attitude toward the use of digital technologies

Keywords: teachers’ knowledge, teachers’ attitude, digital devices, special needs students

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Authors: Zixuan Zhao, Lingbin Du, Le Wang, Youqing Wang, Yi Yang, Jingjun Chen, Hengjin Dong

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Objectives: Few results from public attitudes for lung cancer screening are available both in China and abroad. This study aimed to identify preferred lung cancer screening modalities in a Chinese population and predict uptake rates of different modalities. Materials and Methods: A discrete choice experiment questionnaire was administered to 392 Chinese individuals aged 50–74 years who were at high risk for lung cancer. Each choice set had two lung screening options and an option to opt-out, and respondents were asked to choose the most preferred one. Both mixed logit analysis and stepwise logistic analysis were conducted to explore whether preferences were related to respondent characteristics and identify which kinds of respondents were more likely to opt out of any screening. Results: On mixed logit analysis, attributes that were predictive of choice at 1% level of statistical significance included the screening interval, screening venue, and out-of-pocket costs. The preferred screening modality seemed to be screening by low-dose computed tomography (LDCT) + blood test once a year in a general hospital at a cost of RMB 50; this could increase the uptake rate by 0.40 compared to the baseline setting. On stepwise logistic regression, those with no endowment insurance were more likely to opt out; those who were older and housewives/househusbands, and those with a health check habit and with commercial endowment insurance were less likely to opt out from a screening programme. Conclusions: There was considerable variance between real risk and self-perceived risk of lung cancer among respondents, and further research is required in this area. Lung cancer screening uptake can be increased by offering various screening modalities, so as to help policymakers further design the screening modality.

Keywords: lung cancer, screening, China., discrete choice experiment

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Authors: Harini Chakkera

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Background: Inpatient hyperglycemia is an established independent risk factor among several patient cohorts with hospital readmission. This has not been studied after kidney transplantation. Nearly one-third of patients who have undergone a kidney transplant reportedly experience 30-day readmission. Methods: Data on first-time solitary kidney transplantations were retrieved between September 2015 to December 2018. Information was linked to the electronic health record to determine a diagnosis of diabetes mellitus and extract glucometeric and insulin therapy data. Univariate logistic regression analysis and the XGBoost algorithm were used to predict 30-day readmission. We report the average performance of the models on the testing set on five bootstrapped partitions of the data to ensure statistical significance. Results: The cohort included 1036 patients who received kidney transplantation, and 224 (22%) experienced 30-day readmission. The machine learning algorithm was able to predict 30-day readmission with an average AUC of 77.3% (95% CI 75.30-79.3%). We observed statistically significant differences in the presence of pretransplant diabetes, inpatient-hyperglycemia, inpatient-hypoglycemia, and minimum and maximum glucose values among those with higher 30-day readmission rates. The XGBoost model identified the index admission length of stay, presence of hyper- and hypoglycemia and recipient and donor BMI values as the most predictive risk factors of 30-day readmission. Additionally, significant variations in the therapeutic management of blood glucose by providers were observed. Conclusions: Suboptimal glucose metrics during hospitalization after kidney transplantation is associated with an increased risk for 30-day hospital readmission. Optimizing the hospital blood glucose management, a modifiable factor, after kidney transplantation may reduce the risk of 30-day readmission.

Keywords: kidney, transplant, diabetes, insulin

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Authors: Said Belaaouad

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This study aimed to explore the quantitative structure-activity relationship (QSAR) of 1,2,4-Triazine-3(2H)-one derivative as a potential anticancer agent against breast cancer. The electronic descriptors were obtained using the Density Functional Theory (DFT) method, and a multiple linear regression techniques was employed to construct the QSAR model. The model exhibited favorable statistical parameters, including R2=0.849, R2adj=0.656, MSE=0.056, R2test=0.710, and Q2cv=0.542, indicating its reliability. Among the descriptors analyzed, absolute electronegativity (χ), total energy (TE), number of hydrogen bond donors (NHD), water solubility (LogS), and shape coefficient (I) were identified as influential factors. Furthermore, leveraging the validated QSAR model, new derivatives of 1,2,4-Triazine-3(2H)-one were designed, and their activity and pharmacokinetic properties were estimated. Subsequently, molecular docking (MD) and molecular dynamics (MD) simulations were employed to assess the binding affinity of the designed molecules. The Tubulin colchicine binding site, which plays a crucial role in cancer treatment, was chosen as the target protein. Through the simulation trajectory spanning 100 ns, the binding affinity was calculated using the MMPBSA script. As a result, fourteen novel Tubulin-colchicine inhibitors with promising pharmacokinetic characteristics were identified. Overall, this study provides valuable insights into the QSAR of 1,2,4-Triazine-3(2H)-one derivative as potential anticancer agent, along with the design of new compounds and their assessment through molecular docking and dynamics simulations targeting the Tubulin-colchicine binding site.

Keywords: QSAR, molecular docking, ADMET, 1, 2, 4-triazin-3(2H)-ones, breast cancer, anticancer, molecular dynamic simulations, MMPBSA calculation

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Authors: Navneet Singh Deora, Aastha Deswal, H. N. Mishra

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Pasta is one of the most widely consumed food products around the world. Rapid determination of the moisture content in pasta will assist food processors to provide online quality control of pasta during large scale production. Rapid Fourier transform near-infrared method (FT-NIR) was developed for determining moisture content in pasta. A calibration set of 150 samples, a validation set of 30 samples and a prediction set of 25 samples of pasta were used. The diffuse reflection spectra of different types of pastas were measured by FT-NIR analyzer in the 4,000-12,000 cm-1 spectral range. Calibration and validation sets were designed for the conception and evaluation of the method adequacy in the range of moisture content 10 to 15 percent (w.b) of the pasta. The prediction models based on partial least squares (PLS) regression, were developed in the near-infrared. Conventional criteria such as the R2, the root mean square errors of cross validation (RMSECV), root mean square errors of estimation (RMSEE) as well as the number of PLS factors were considered for the selection of three pre-processing (vector normalization, minimum-maximum normalization and multiplicative scatter correction) methods. Spectra of pasta sample were treated with different mathematic pre-treatments before being used to build models between the spectral information and moisture content. The moisture content in pasta predicted by FT-NIR methods had very good correlation with their values determined via traditional methods (R2 = 0.983), which clearly indicated that FT-NIR methods could be used as an effective tool for rapid determination of moisture content in pasta. The best calibration model was developed with min-max normalization (MMN) spectral pre-processing (R2 = 0.9775). The MMN pre-processing method was found most suitable and the maximum coefficient of determination (R2) value of 0.9875 was obtained for the calibration model developed.

Keywords: FT-NIR, pasta, moisture determination, food engineering

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Authors: Getnet Gedefaw, Fentanesh Endalew, Bitewush Azmeraw, Bethelhem Walelign, Eyob Shitie

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Introduction: The issue of menstrual hygiene is often overlooked and has not been sufficiently addressed in the fields of reproductive health in low and middle-income countries. Inadequate menstrual hygiene practices can increase the risk of various infectious and chronic obstetric and gynaecological complications for girls and adolescents. Hence, this study seeks to investigate the knowledge, attitudes, and practices related to menstrual hygiene, along with the factors influencing them, among high school students. Methods: A facility based cross-sectional study was conducted involving a total of 423 study subjects. A systematic random sampling technique was utilized. Data was entered and analyzed through Epi data 3.1 and SPSS 22, respectively. Both univariable and multivariable logistic regression models were employed. A p-value of less than 0.05 was considered statistically significant. Results: This study revealed that 365(89.2%), 200(48.9%) and 196(47.9%) of the study participants have good knowledge, good practice, and good attitudes about menstrual hygiene, respectively. Being higher grade students (grade 10) [AOR=3.96, 95% CI =2.0-7.8] and having good practice of menstrual hygiene (AOR=2.52, 95% CI= 1.26-5) had a positive association with menstrual hygiene knowledge. Whereas maternal education level (AOR=1.86, 95% CI=1.18-2.9) and being a grade 10 student (AOR=2.3, 95% CI=1.48-3.56) were associated factors for practising menstrual hygiene. Additionally, being higher grade students (AOR=1.9, 95% CI=1.2-2.8), age ≥18 years (AOR=1.67, 95% CI=1.09-2.55) were statistically and positively associated with the attitude of menstrual hygiene. Conclusion: The study findings indicated that the knowledge of the study participants regarding menstrual hygiene was high, while their attitudes and practices towards menstrual hygiene were low. It is suggested that raising awareness among reproductive health groups and educating their families and parents could potentially lead to a positive change in their poor practices and attitudes towards menstrual hygiene.

Keywords: menstrual hygiene, menstruation, students, reproductive health

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Authors: Muftah H. El-Naas, Ameera F. Mohammad, Mabruk I. Suleiman, Mohamed Al Musharfy, Ali H. Al-Marzouqi

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CO₂ capture and storage technologies play a significant role in contributing to the control of climate change through the reduction of carbon dioxide emissions into the atmosphere. The present study evaluates and optimizes CO₂ capture through a process, where carbon dioxide is passed into pH adjusted high salinity water and reacted with sodium chloride to form a precipitate of sodium bicarbonate. This process is based on a modified Solvay process with higher CO₂ capture efficiency, higher sodium removal, and higher pH level without the use of ammonia. The process was tested in a bubble column semi-batch reactor and was optimized using response surface methodology (RSM). CO₂ capture efficiency and sodium removal were optimized in terms of major operating parameters based on four levels and variables in Central Composite Design (CCD). The operating parameters were gas flow rate (0.5–1.5 L/min), reactor temperature (10 to 50 ^oC), buffer concentration (0.2-2.6%) and water salinity (25-197 g NaCl/L). The experimental data were fitted to a second-order polynomial using multiple regression and analyzed using analysis of variance (ANOVA). The optimum values of the selected variables were obtained using response optimizer. The optimum conditions were tested experimentally using desalination reject brine with salinity ranging from 65,000 to 75,000 mg/L. The CO₂ capture efficiency in 180 min was 99% and the maximum sodium removal was 35%. The experimental and predicted values were within 95% confidence interval, which demonstrates that the developed model can successfully predict the capture efficiency and sodium removal using the modified Solvay method.

Keywords: CO2 capture, water desalination, Response Surface Methodology, bubble column reactor

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Authors: Arun K. Yadav, Adam J. Carroll, Gonzalo M. Estavillo, Greg J. Rebetzke, Barry J. Pogson

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Water limits crop productivity, so selecting for minimal yield-gap in drier environments is critical to mitigate against climate change and land-use pressures. To date, no markers measured in glasshouses have been reported to predict field-based drought tolerance. In the field, the best measure of drought tolerance is yield-gap; but this requires multisite trials that are an order of magnitude more resource intensive and can be impacted by weather variation. We investigated the responses of relative water content (RWC), stomatal conductance (gs), chlorophyll content and metabolites in flag leaves of commercial wheat (Triticum aestivum L.) cultivars to three drought treatments in the glasshouse and field environments. We observed strong genetic associations between glasshouse-based RWC, metabolites and Yield gap-based Drought Tolerance (YDT): the ratio of yield in water-limited versus well-watered conditions across 24 field environments spanning sites and seasons. Critically, RWC response to glasshouse drought was strongly associated with both YDT (r2 = 0.85, p < 8E-6) and RWC under field drought (r2 = 0.77, p < 0.05). Multiple regression analyses revealed that 98% of genetic YDT variance was explained by drought responses of four metabolites: serine, asparagine, methionine and lysine (R2 = 0.98; p < 0.01). Fitted coefficients suggested that, for given levels of serine and asparagine, stronger methionine and lysine accumulation was associated with higher YDT. Collectively, our results demonstrate that high-throughput, targeted metabolic phenotyping of glasshouse-grown plants may be an effective tool for the selection of wheat cultivars with high YDT in the field.

Keywords: drought stress, grain yield, metabolomics, stomatal conductance, wheat

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