Search results for: ingroup identification

Authors: Levent Dumenci, Laura A. Siminoff

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Health literacy has been shown to predict a variety of health outcomes. Reliable identification of persons with limited cancer health literacy (LCHL) has been proved questionable with existing instruments using an arbitrary cut point along a continuum. The CHLT-6, however, uses a latent mixture modeling approach to identify persons with LCHL. The purpose of this study was to estimate two-week and six-month stability of identifying persons with LCHL using the CHLT-6 with a discrete latent variable approach as the underlying measurement structure. Using a test-retest design, the CHLT-6 was administered to cancer patients with two-week (N=98) and six-month (N=51) intervals. The two-week and six-month latent test-retest agreements were 89% and 88%, respectively. The chance-corrected latent agreements estimated from Dumenci’s latent kappa were 0.62 (95% CI: 0.41 – 0.82) and .47 (95% CI: 0.14 – 0.80) for the two-week and six-month intervals, respectively. High levels of latent test-retest agreement between limited and adequate categories of cancer health literacy construct, coupled with moderate to good levels of change-corrected latent agreements indicated that the CHLT-6 classification of limited versus adequate cancer health literacy is relatively stable over time. In conclusion, the measurement structure underlying the instrument allows for estimating classification errors circumventing limitations due to arbitrary approaches adopted by all other instruments. The CHLT-6 can be used to identify persons with LCHL in oncology clinics and intervention studies to accurately estimate treatment effectiveness.

Keywords: limited cancer health literacy, the CHLT-6, discrete latent variable modeling, latent agreement

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Authors: Svetlana Gudkova

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The Internet of Things experiences a rapid growth bringing inevitable changes into many spheres of human activities. As the Internet has changed the social and business landscape, IoT as its extension, can bring much more profound changes in economic value creation and competitiveness of the economies. It has been already recognized as the next industrial revolution. However, the development of IoT is in a great extent stimulated by the entrepreneurial activity. To expand and reach its full potential it requires proactive entrepreneurs, who explore the potential and create innovative ideas pushing the boundaries of IoT technologies' application further. The goal of the research is to analyze, how entrepreneurs utilize the opportunities created by IoT and how do they stimulate the development of IoT through discovering of new ways of generating economic value and creating opportunities, which attract other entrepreneurs. The qualitative research methods have been applied to prepare the case studies. Entrepreneurs are recognized as an engine of economic growth. They introduce innovative products and services into the market through the creation of a new combination of the existing resources and utilizing new knowledge. Entrepreneurs not only create economic value but what is more important, they challenge the existing business models and invent new ways of value creation. Through identification and exploitation of entrepreneurial opportunities, they create new opportunities for other entrepreneurs. It makes the industry more attractive to other profit/innovation-driven start-ups. IoT creates numerous opportunities for entrepreneurs in the different industries. Smart cities, healthcare, manufacturing, retail, agriculture, smart vehicles and smart buildings benefit a lot from IoT-based breakthrough innovations introduced by entrepreneurs. They reinvented successfully the business models and created new entrepreneurial opportunities for other start-ups to introduce next innovations.

Keywords: entrepreneurship, internet of things, breakthrough innovations, start-ups

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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: Julian Wise

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Newcrest Mining is one of the world’s top five gold and rare earth mining organizations by production, reserves and market capitalization in the world. This paper elaborates on the data acquisition processes employed by Newcrest in collaboration with Fortune 500 listed organization, Insight Enterprises, to standardize machine learning solutions which process data from over a hundred thousand distributed Internet of Things (IoT) devices located at mine sites globally. Through the utilization of software architecture cloud technologies and edge computing, the technological developments enable for standardized processes of machine learning applications to influence the strategic optimization of mineral processing. Target objectives of the machine learning optimizations include time savings on mineral processing, production efficiencies, risk identification, and increased production throughput. The data acquired and utilized for predictive modelling is processed through edge computing by resources collectively stored within a data lake. Being involved in the digital transformation has necessitated the standardization software architecture to manage the machine learning models submitted by vendors, to ensure effective automation and continuous improvements to the mineral process models. Operating at scale, the system processes hundreds of gigabytes of data per day from distributed mine sites across the globe, for the purposes of increased improved worker safety, and production efficiency through big data applications.

Keywords: mineral technology, big data, machine learning operations, data lake

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Authors: Simona Pileviciene

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On 24th January 2014, Lithuania notified two primary cases of African swine fever (ASF) in wild boars. The animals were tested positive for ASF virus (ASFV) genome by real-time PCR at the National Reference Laboratory for ASF in Lithuania (NRL), results were confirmed by the European Union Reference Laboratory for African swine fever (CISA-INIA). Intensive wild and domestic animal monitoring program was started. During the period of 2014-2017 ASF was confirmed in two large commercial pig holding with the highest biosecurity. Pigs were killed and destroyed. Since 2014 ASF outbreak territory from east and south has expanded to the middle of Lithuania. Diagnosis by PCR is one of the highly recommended diagnostic methods by World Organization for Animal Health (OIE) for diagnosis of ASF. The aim of the present study was to compare singleplex real-time PCR assays to a duplex assay allowing the identification of ASF and internal control in a single PCR tube and to compare primers, that target the p72 gene (ASF 250 bp and ASF 75 bp) effectivity. Multiplex real-time PCR assays prove to be less time consuming and cost-efficient and therefore have a high potential to be applied in the routine analysis. It is important to have effective and fast method that allows virus detection at the beginning of disease for wild boar population and in outbreaks for domestic pigs. For experiments, we used reference samples (INIA, Spain), and positive samples from infected animals in Lithuania. Results show 100% sensitivity and specificity.

Keywords: African swine fewer, real-time PCR, wild boar, domestic pig

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Authors: Preeyarach Whisetkhan, Malai Taweechotipatr, Ulisa Pachekrepapol

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Elevated level of blood cholesterol or hypercholesterolemia may lead to atherosclerosis and poses a major risk for cardiovascular diseases. Probiotics play a crucial role in human health, and probiotic bacteria that possesses bile salt hydrolase (BSH) activity can be used to lower cholesterol level of the host. The aim of this study was to investigate whether lactic acid bacteria (LAB) isolated from traditional Thai fermented foods were able to exhibit bile salt hydrolase activity and their use in fermented milk. A total of 28 isolates were tested for BSH activity by plate method on MRS agar supplemented with 0.5% sodium salt of taurodeoxycholic acid and incubated at 37°C for 48 h under anaerobic condition. The results showed that FN1-1 and FN23-3 isolates possessed strong BSH activity. FN1-1 and FN23-3 isolates were then identified for phenotype, biochemical characteristics, and genotype (16S rRNA sequencing). FN1-1 isolate showed 99.92% similarity to Lactobacillus pentosus DSM 20314(T), while FN23-3 isolate showed 99.94% similarity to Enterococcus faecium CGMCC1.2136 (T). Lactobacillus pentosus FN1-1 and Enterococcus faecium FN23-3 were tolerant of pH 3-4 and 0.3 and 0.8% bile. Bacterial count and pH of milk fermented with Lactobacillus pentosus FN1-1 at 37°C and 43°C were investigated. The results revealed that Lactobacillus pentosus FN1-1 was able to grow in milk, which led to decrease in pH level. Fermentation at 37°C resulted in faster growth rate than at 43 °C. Lactobacillus pentosus FN1-1 was a candidate probiotic to be used in fermented milk products to reduce the risk of high-cholesterol diseases.

Keywords: probiotics, lactic acid bacteria, bile salt hydrolase, cholesterol

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Authors: Najmeh Jafari, Sona Rostampour Yasouri

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Crimean-Congo hemorrhagic fever (CCHF) is an acute hemorrhagic disease. This disease is one of the common diseases between humans and animals, transmitted through tick bites or contact with the blood and secretions or carcasses of infected animals and humans. CCHF is more common in people who work with livestock, such as ranchers, butchers, farmers, slaughterhouse workers, healthcare workers, etc. Its hospital prevalence is also very high. Considering that CCHF can be transmitted through the consumption of food such as beef and sheep meat, this study aims to quickly identify and diagnose the Crimean-Congo fever virus in suspected patients through real-time PCR technique. In the summer of 1402, 20 blood samples were collected separately from Ahvaz and Gilan hospitals. An extraction kit was used to extract the virus RNA. Primers and probes were designed based on the S genomic region, the conserved region in CCHFV. Then, a real-time PCR technique was performed with specific primers and probes. It should be noted that the mentioned technique was repeated several times. The number of 4 samples from the examined samples was determined positive by real-time PCR. This technique has high sensitivity and specificity and the possibility of rapid detection of CCHFV. Therefore, the above method is a good candidate for quick disease diagnosis. By diagnosing the disease, the treatment process can be done faster, and the best prevention methods can be used to control the disease and prevent the death of patients.

Keywords: ahvaz, crimean-congo hemorrhagic fever, gilan, real time PCR

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Authors: Niranjan Devkota , Ram Kumar Phuya, Durga Lal Shreshta

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This paper estimates cost and benefit of adoption of climate change adaptation options available to the rural rice farmers of Nepal. Adoption of adaptation strategies, intensity of use of adaptation options, identification of labor and non-labor cost and finally per unit cost and benefit analysis of climate change adaptation were made. Multi-stage sampling technique was used to source respondents for the study and used structured questionnaire techniques to collect data from 773 households from seven districts; 3 from Terai and 4 from Hilly region of Nepal. The result revealed that there are 13 major adaptation options rice farmers practice in order to protect themselves from climatic risk. Among the given adaptation options, the first three popular adaptation options practiced by rice farmers are (i) increasing use of chemical fertilizer (60.93%) (ii) use of climate smart verities (49.29%) and (iii) change in nursery date (32.08%). Adaptation cost is obvious, based on that, the first three costly adaptation options are the alternative irrigation practice which incurred average cost of US $69.95 (US$ 1 = 102.84 Nepalese Rupees) followed by a denser plantation of local seeds ($ 20.69) and using climate smart varieties ($ 18.06). 88% farmers practiced more than one adaptation strategies on the same farm with the aim of reducing the effect of extreme climatic conditions. Total cost and revenue revealed that per unit total cost ranges from $28.34 to $32.79 whereas per unit total revenue ranges $33.4 to $49.02. Surprisingly, it is observed that farmers who do not adopt any adaptation options are able to receive highest income from per unit production. As Net Present Value (NPV) is positive and Benefit Cost Ration (BCR) is greater than one for every adaptation options that indicates the available adaptation options are profitable to the rice farmers.

Keywords: climate change, adaptation options, cost benefit analysis, rural rice farmers, Nepal

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Authors: Alazar Nebyou, Sujata Pandit

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Lactic acid bacteria (LAB) are essential ingredients in probiotic foods, intestinal microflora, and dairy products that are capable of coping up with harsh gastrointestinal tract conditions and are available in a variety of environments. The objective of this study is to evaluate the probiotic property of LAB isolated from bovine milk. Milk samples were collected from local dairy farms. Samples were obtained using sterile test tubes and transported to a laboratory in the icebox for further biochemical characterization. Preliminary physiological and biochemical identification of LAB isolates was conducted by growing on MRS agar after ten-fold serial dilution. Seven of the best isolates were selected for the evaluation of the probiotic property. The LAB isolates were checked for resistance to antibiotics and their antimicrobial activity by disc diffusion assay and agar well diffusion assay respectively. Bile salt hydrolase activity of isolates was studied by growing isolates in a BSH medium with bile salt. Cell surface property of isolates was assayed by studying their autoaggregation and coaggregation percentage with S. aerues. All isolates were found BSH positive. In addition, BCM2 and BGM1 were susceptible to all antibiotic disks except BBM1 which was resistant to all antibiotic disks. BCM1 and BGM1 had the highest autoaggregation and coaggregation potential respectively. Since all LAB isolates showed gastrointestinal tolerance and good cell surface property they could be considered as good potential probiotic candidates for treatment and probiotic starter culture preparation.

Keywords: probiotic, aggregation, lactic acid bacteria, antimicrobial activity

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Authors: Ngonidzashe Mangoma, Caroline Marigold Sebata

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The release of cyanide-rich effluents from gold mines, and other industries, into the environment, is a global concern considering the well-known metabolic effects of cyanide in all forms of life. Such effluents need to be treated to remove cyanide, among other pollutants, before their disposal. This study aimed at investigating the possible use of bacteria in the biological removal of cyanide from cyanide-rich effluents. Firstly, cyanide-degrading bacteria were isolated from gold mine effluents and characterised. The isolates were then tested for their ability to grow in the presence of cyanide and their tolerance to increasing levels of the compound. To evaluate each isolate’s cyanide-degrading activities, isolates were grown in the simulated and actual effluent, and a titrimetric method was used to quantify residual cyanide over a number of days. Cyanide degradation efficiency (DE) was then calculated for each isolate. Identification of positive isolates involved 16S rRNA gene amplification and sequence analysis through BLAST. Six cyanide-utilising bacterial strains were isolated. Two of the isolates were identified as Klebsiella spp. while the other two were shown to be different strains of Clostridium bifermentans. All isolates showed normal growth in the presence of cyanide, with growth being inhibited at 700 mg/L cyanide and beyond. Cyanide degradation efficiency for all isolates in the simulated effluent ranged from 79% to 97%. All isolates were able to remove cyanide from actual gold mine effluent with very high DE values (90 – 94%) being recorded. Isolates obtained in this study were able to efficiently remove cyanide from both simulated and actual effluent. This observation clearly demonstrates the feasibility of the biological removal of cyanide from cyanide-rich gold mine effluents and should, therefore, motivate research towards the possible large-scale application of this technology.

Keywords: cyanide effluent, bioremediation, Clostridium bifermentans, Klebsiella spp, environment

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Authors: B. Chandar, M. K. Ramasamy, P. Madasamy

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The discovery and development of newer antibiotics are limited with the increase in resistance of such multi-drug resistant bacteria creating the need for alternative new therapeutic agents. The recently discovered New Delhi Metallo-betalactamase-1 (NDM-1), which confers antibiotic resistance to most of the currently available β-lactams, except colistin and tigecycline, is a global concern. Several antibacterial drugs approved are natural products or their semisynthetic derivatives, but plant extracts remain to be explored to find molecules that are effective against NDM-1 bacteria. Therefore, it is necessary to explore the possibility of finding new and effective antibacterial compounds against NDM-1 bacteria. In the present study, we have screened a diverse set South Indian plant species, and report most plant species as a potential source for antimicrobial compounds against NDM-1 bacteria. Ethanol extracts from the leaves of taxonomically diverse South Indian medicinal plants were screened for antibacterial activity against NDM-1 E. coli using streak plate method. Among the plant screened against NDM-1 E. coli, the ethanol extracts from many plant extracts showed minimum bactericidal concentration between 5 and 15 mg /ml and MIC between 2.54 and 5.12 mg/ml. These extracts also showed a potent synergistic effect when combined with antibiotics colistin and tetracycline. Combretum albidum that was effective was taken for further analysis. At 5mg/L concentration, these extracts inhibited the NDM-1 enzyme in vitro, and residual activity for Combretum albidum was 33.09%. Treatment of NDM-1 E. coli with the extracts disrupted the cell wall integrity and caused 89.7% cell death. The plant extract of Combretum albidum that was effective was subjected to fractionation and the fraction was further subjected to HPLC, LC-MS for identification of antibacterial compound.

Keywords: antibacterial activity, combretum albidum, Escherichia coli, NDM-1

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Authors: Manoj K. Kumar, Deepthi Bathala

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Man has the need to know and feel as a part of the historical continuum and it is this continuum that reinforces his identity. Architecture and the built environment contribute to this identity as established by the various identity theories exploring the relationship between the two. Architecture which is organic has been successful in maintaining a continuum of identity until the advent of globalization when the world saw a drastic shift to architecture of ‘placelessness’. The answer to the perfect synthesis of ‘universalization’ and ‘regionalism’ is an ongoing quest. However, history has established a smooth transition from vernacular to colonial to modern unlike the architecture of today. The traditional Kerala architecture has evolved from the tropical climate, geography, local needs, materials, skills and foreign influences. It is unique in contrast to the architecture of the neighboring states as a result of the geographical barriers however influenced by the architecture of the Orient due to trade relations. Through 1805 to 1950, the European influence on the architecture of Kerala resulted in the emergence of the colonial style which managed to establish a continuum of the traditional architecture. The paper focuses on the identification of the components of architecture that established the continuity of place-identity in the architecture of Kerala and examines the transition from the traditional Kerala architecture to colonial architecture during the colonial period. Visual surveys based on the principles of urban design, cognitive mapping, typology analysis followed by the strong understanding of the morphological and built environment along with the matrix method are the research tools used. The understanding of these components of continuity can be useful in creating buildings which people can relate to in the present day. South-Asia shares the history of colonialism and the understanding of these components can pave the way for further research on how to establish a regional identity in the era of globalization.

Keywords: colonial, identity, place, regional

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Authors: Md. Shaiful Islam, Mahani Bt. Stapa

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To help learners overcome their struggle in developing proficiency in spoken English, self-regulated learning strategies seem to be promising. Students in the private universities in Bangladesh are expected to communicate with the teachers, peers, and staff members in English, but most of them suffer from their inadequate oral communicative competence in English. To address this problem, the researchers adopted a qualitative research approach to answer the research questions. They employed the learner diary method to collect data from the first-semester undergraduate students of a reputed private university in Bangladesh who were involved in writing weekly diaries about their use of self-regulated learning strategies to improve speaking in an English speaking course. The learners were provided with prompts for writing the diaries. The thematic analysis method was applied to analyze the entries of the diaries for the identification of themes. Seven strategies related to the effectiveness of SRL for the improvement of spoken English were identified from the data, and they include goal-setting, strategic planning, identifying the sources of self-motivation, help-seeking, environmental restructuring, self-monitoring, and self-evaluation. However, the students reported in their diaries that they faced challenges that impeded their SRL strategy use. Five challenges were identified, and they entail the complex nature of SRL, lack of literacy on SRL, teachers’ preference for controlling the class, learners’ past habit of learning, and students’ addiction to gadgets. The implications the study addresses include revising the syllabus and curriculum, facilitating SRL training for students and teachers, and integrating SRL in the lessons.

Keywords: private university in Bangladesh, proficiency, self-regulated learning, spoken English

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Authors: Choppala Pratheek, Vineet Ahuja

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Background: Crohn's disease (CD) recurrence following surgery is a common challenge, and current detection methods rely on risk factors identified in Western populations. This study aimed to investigate the risk factors and rates of postoperative CD recurrence in a tuberculosis-endemic region like India. Retrospective data was collected from a structured database from a specialty IBD clinic by reviewing case files from January 2005 to December 2021. Inclusion criteria involved CD patients diagnosed based on the ECCO-ESGAR consensus guidelines, who had undergone at least one intestinal resection and had a minimum follow-up period of one year at the IBD clinic. Results: A total of 90 patients were followed up for a median period of 45 months (IQR, 20.75 - 72.00). Out of the 90 patients, 61 received ATT prior to surgery, with a mean delay in diagnosis of 2.5 years, although statistically non-significant (P=0.078). Clinical recurrence occurred in 50% of patients, with the cumulative rate increasing from 13.3% at one year to 40% at three years. Among 63 patients who underwent endoscopy, 65.7% showed evidence of endoscopic recurrence, with the cumulative rate increasing from 31.7% at one year to 55.5% at four years. Smoking was identified as a significant risk factor for early endoscopic recurrence (P=0.001) by Cox regression analysis, but no other risk factors were identified. Initiating post-operative medications prior to clinical recurrence delayed its onset (P=0.004). Subgroup analysis indicated that endoscopic monitoring aided in the early identification of recurrence (P=0.001). The findings contribute to enhancing post-operative CD management strategies in such regions where the disease burden is escalating.

Keywords: crohns, post operative, tuberculosis-endemic, risk factors

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Authors: Mahdi Bastan, Ali Mohammad Ahmadvand, Fatemeh Soltani Khamsehpour

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Health organizations’ sustainable development has nowadays become highly affected by customers’ satisfaction due to significant changes made in the business environment of the healthcare system and emerging of Competitiveness paradigm. In case we look at the hospitals and other health organizations as service providers concerning profit issues, the satisfaction of employees as interior customers, and patients as exterior customers would be of significant importance in health business success. Furthermore, satisfaction rate could be considered in performance assessment of healthcare organizations as a perceived quality measure. Several researches have been carried out in identification of effective factors on patients’ satisfaction in health organizations. However, considering a systemic view, the complex causal relations among many components of healthcare system would be an issue that its acquisition and sustainability requires an understanding of the dynamic complexity, an appropriate cognition of different components, and effective relationships among them resulting ultimately in identifying the generative structure of patients’ satisfaction. Hence, the presenting paper applies system dynamics approaches coherently and methodologically to represent the systemic structure of customers’ satisfaction of a health system involving the constituent components and interactions among them. Then, the results of different policies taken on the system are simulated via developing mathematical models, identifying leverage points, and using scenario making technique and then, the best solutions are presented to improve customers’ satisfaction of the services. The presenting approach supports taking advantage of decision support systems. Additionally, relying on understanding of system behavior Dynamics, the effective policies for improving the health system would be recognized.

Keywords: customer satisfaction, healthcare, scenario, simulation, system dynamics

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Authors: Famurewa Olumide Joseph, Akinsulore Adesanmi

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The current study investigated aggressive behaviour and its association with substance use disorder among senior secondary school students in Ilesha, Nigeria. Participants were three hundred and seventy-five (375) comprising (212) females and (163) males of senior secondary school students in Ilesa East and Ilesa West; who were randomly selected among the population of students from the schools. The mean age of the respondents was 14.61 years (S.D = 1.16), with 311 (82.9%) between 14 – 16 years. Female respondents were 212 (56.5%), while male respondents were 163 (43.5%). A cross sectional design was adopted. Three instruments were used for data collection. Buss Perry Aggression Questionnaire, Alcohol Use Disorder Identification Test (AUDIT) and Drug Abuse Screening Test (DAST). It was hypothesized that aggressive behaviour will be associated with substance use disorder among senior secondary school students in Ilesa East and Ilesa West. The result indicated that the overall prevalence of substance use disorder was 16.0%. Chi-Square test exploring the association between aggressive behaviour and substance use disorder shows that there is a significant association between aggressive behaviour and substance use disorder (χ2 =8.55, p =0.014). Results also showed that emotional problem (χ2 (2) =13.0; p = 0.001) was statistically significant while current medications intake (χ2 (2) =2.03; p =0.362) and overall wellbeing (χ2 (4) =2.49; p =0.646) were not statistically significant. There is an inverse association between prosocial behaviour and aggressive behaviour (r= -0.037, p>0.05). This indicates that as the level of prosocial behaviour increases, the level of aggressive behaviour among respondents decreases. However, alcohol use had no correlation with aggressive behaviour (r=0.070, p>0.05). Among the implications stated is that factors such as emotional symptoms, conduct problems, hyperactivity, peer problem and drug use contributed to the prevalence of aggressive behaviour among students. Suggestions for further studies were equally made.

Keywords: aggressive behaviour, alcohol, prevalence, students, substance use disorder (SUD)

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Authors: Anatoly Krivinsh

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The results of dissertation research "Preventing and combating corruption in public procurement" are presented in this publication. The study was conducted 2011 till 2013 in a Member State of the European Union, in the Republic of Latvia. Goal of the thesis is to explore corruption prevention and combating issues in public procurement sphere, to identify the prevalence rates, determinants and contributing factors and prevention opportunities in Latvia. In the first chapter the author analyses theoretical aspects of understanding corruption in public procurement, with particular emphasis on corruption definition problem, its nature, causes and consequences. A separate section is dedicated to the public procurement concept, mechanism and legal framework. In the first part of this work the author presents cognitive methodology of corruption in public procurement field, based on which the author has carried out an analysis of corruption situation in public procurement in Republic of Latvia. In the second chapter of the thesis, the author analyzes the problem of corruption in public procurement, including its historical aspects, typology and classification of corruption subjects involved, corruption risk elements in public procurement and their identification. During the development of the second chapter author's practical experience in public procurements was widely used. The third and fourth chapter deals with issues related to the prevention and combating corruption in public procurement, namely the operation of the concept, principles, methods and techniques, subjects in Republic of Latvia, as well as an analysis of foreign experience in preventing and combating corruption. The fifth chapter is devoted to the corruption prevention and combating perspectives and their assessment. In this chapter the author has made the evaluation of corruption prevention and combating measures efficiency in Republic of Latvia, assessment of anti-corruption legislation development stage in public procurement field in Latvia.

Keywords: prevention of corruption, public purchases, good governance, human rights

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Authors: Behnaz Sohani, Sahand Shahalinezhad, Amir Rahmani, Aliyu Aliyu

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Recently, medical imaging and specifically medical image processing is becoming one of the most dynamically developing areas of medical science. It has led to the emergence of new approaches in terms of the prevention, diagnosis, and treatment of various diseases. In the process of diagnosis of lung cancer, medical professionals rely on computed tomography (CT) scans, in which failure to correctly identify masses can lead to incorrect diagnosis or sampling of lung tissue. Identification and demarcation of masses in terms of detecting cancer within lung tissue are critical challenges in diagnosis. In this work, a segmentation system in image processing techniques has been applied for detection purposes. Particularly, the use and validation of a novel lung cancer detection algorithm have been presented through simulation. This has been performed employing CT images based on multilevel thresholding. The proposed technique consists of segmentation, feature extraction, and feature selection and classification. More in detail, the features with useful information are selected after featuring extraction. Eventually, the output image of lung cancer is obtained with 96.3% accuracy and 87.25%. The purpose of feature extraction applying the proposed approach is to transform the raw data into a more usable form for subsequent statistical processing. Future steps will involve employing the current feature extraction method to achieve more accurate resulting images, including further details available to machine vision systems to recognise objects in lung CT scan images.

Keywords: lung cancer detection, image segmentation, lung computed tomography (CT) images, medical image processing

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Authors: Hassan Ibrahim

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The prevalence of hyperacusis, an auditory condition characterized by heightened sensitivity to sounds, continues to rise, posing challenges for effective diagnosis and intervention. It is believed that this work deepens will deepens the understanding of hyperacusis etiology by employing graph theory as a novel analytical framework. We constructed a comprehensive graph wherein nodes represent various factors associated with hyperacusis, including aging, head or neck trauma, infection/virus, depression, migraines, ear infection, anxiety, and other potential contributors. Relationships between factors are modeled as edges, allowing us to visualize and quantify the interactions within the etiological landscape of hyperacusis. it employ the concept of the metric dimension of a connected graph to identify key nodes (landmarks) that serve as critical influencers in the interconnected web of hyperacusis causes. This approach offers a unique perspective on the relative importance and centrality of different factors, shedding light on the complex interplay between physiological, psychological, and environmental determinants. Visualization techniques were also employed to enhance the interpretation and facilitate the identification of the central nodes. This research contributes to the growing body of knowledge surrounding hyperacusis by offering a network-centric perspective on its multifaceted causes. The outcomes hold the potential to inform clinical practices, guiding healthcare professionals in prioritizing interventions and personalized treatment plans based on the identified landmarks within the etiological network. Through the integration of graph theory into hyperacusis research, the complexity of this auditory condition was unraveled and pave the way for more effective approaches to its management.

Keywords: auditory condition, connected graph, hyperacusis, metric dimension

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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: Abewardhana Arachchi Bandula Dimuthu Priyadarshana Abewardhana, Rasika Nirosh Gonapinuwala Vithanage, Karawe Thanthreege Amila Madusanka Perera, Asanka Sanjeewa Karunarathne, Navullage Mayuri Radhika Perera

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The phenomenon of irregular migration and human trafficking presents multifaceted challenges to Sri Lanka, with specific focus on the migration routes to the United Arab Emirates (UAE), the Sultanate of Oman, and Malaysia. This research critically assesses the efficacy of a pilot project instituted at Bandaranaike International Airport aimed at the identification and deterrence of potential irregular migrants. Additionally, the study conducts a nuanced analysis of the geographical tendencies pertaining to passengers who revise their migration intentions at the airport. Pertinently, the findings indicate that Colombo and Gampaha Districts emerge as the most susceptible to human trafficking, with Galle, Nuwaraeliya, Rathnapura, and Polonnaruwa Districts following as areas of elevated concern, particularly within the framework of the 'visit visa' scenario. These insights emanate from an extensive data collection period spanning 50 days of the pilot project, encompassing 1,479 passengers, of which 46 returnees reported to the Safe Migration Promotion Unit. The research is founded on the twin objectives of comprehending the motivations of passengers and evaluating the effectiveness of interventions, with a view to devising precision-targeted prevention strategies. Through this endeavor, the study actively contributes to the safeguarding of the rights and welfare of migrants, significantly advancing the ongoing battle against irregular migration.

Keywords: irregular migration, human trafficking, airport interventions, geographic trends

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Authors: Catriona Hilliard

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Food identity is synonymous with many national tourism destinations and perceptions in tourist source markets – stereotypes could include snails in France; beer in Britain and Germany; paella in Spain - and is an accepted element of national identity that can be incorporated into tourism experiences. Irish transatlantic food connections are culturally strong with diaspora subsequent generations in the US displaying an online interest in traditional Irish food, even with a twist. Back ‘home’, the value of the local indigenous experience was a specific element of the way The Gathering 2013 was promoted to the Irish diaspora, developing community interest and input to tourism. Over the past 20 years, Ireland has realized the value of its food industry to tourism. This has included the establishment of food development programmes for the hospitality industry; food festivals as a possible element of the tourist experience; and a programmes of food ambassadors to market Irish produce and to encourage service providers to understand; utilize and incorporate this into their offerings. Irish produce is being now actively marketed as part of the proposed tourism experience, to particular segment markets including transatlantic visitors. In addition, individual providers are becoming aware of the value of the market, and how to gain from it. Also, networks of food providers have developed collaborative structures of promoting their experiences to audiences, displaying a cluster approach of tourism development towards that sector. A power point presentation will look at how Irish produce contributes to tourism marketing and promotion of Ireland to America; how that may have assisted sustainable development of communities here; and hopes to elicit some discussion relating to longer term identification of Irish food, as part of tourism, for the potential benefit of the ‘locale’.

Keywords: Irish, USA, food, tourism

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Authors: C. Xavier Mendieta, J. J McArthur

Abstract:

Governments are playing an increasingly active role in reducing carbon emissions, and a key strategy has been the introduction of mandatory energy disclosure policies. These policies have resulted in a significant amount of publicly available data, providing researchers with a unique opportunity to develop location-specific energy and carbon emission benchmarks from this data set, which can then be used to develop building archetypes and used to inform urban energy models. This study presents the development of such a benchmark using the public reporting data. The data from Ontario’s Ministry of Energy for Post-Secondary Educational Institutions are being used to develop a series of building archetype dynamic building loads and energy benchmarks to fill a gap in the currently available building database. This paper presents the development of a benchmark for college and university residences within ASHRAE climate zone 6 areas in Ontario using the mandatory disclosure energy and greenhouse gas emissions data. The methodology presented includes data cleaning, statistical analysis, and benchmark development, and lessons learned from this investigation are presented and discussed to inform the development of future energy benchmarks from this larger data set. The key findings from this initial benchmarking study are: (1) the importance of careful data screening and outlier identification to develop a valid dataset; (2) the key features used to develop a model of the data are building age, size, and occupancy schedules and these can be used to estimate energy consumption; and (3) policy changes affecting the primary energy generation significantly affected greenhouse gas emissions, and consideration of these factors was critical to evaluate the validity of the reported data.

Keywords: building archetypes, data analysis, energy benchmarks, GHG emissions

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Authors: Hassan Ibrahim

Abstract:

The prevalence of hyperacusis, an auditory condition characterized by heightened sensitivity to sounds, continues to rise, posing challenges for effective diagnosis and intervention. It is believed that this work deepens will deepens the understanding of hyperacusis etiology by employing graph theory as a novel analytical framework. it constructed a comprehensive graph wherein nodes represent various factors associated with hyperacusis, including aging, head or neck trauma, infection/virus, depression, migraines, ear infection, anxiety, and other potential contributors. Relationships between factors are modeled as edges, allowing us to visualize and quantify the interactions within the etiological landscape of hyperacusis. it employ the concept of the metric dimension of a connected graph to identify key nodes (landmarks) that serve as critical influencers in the interconnected web of hyperacusis causes. This approach offers a unique perspective on the relative importance and centrality of different factors, shedding light on the complex interplay between physiological, psychological, and environmental determinants. Visualization techniques were also employed to enhance the interpretation and facilitate the identification of the central nodes. This research contributes to the growing body of knowledge surrounding hyperacusis by offering a network-centric perspective on its multifaceted causes. The outcomes hold the potential to inform clinical practices, guiding healthcare professionals in prioritizing interventions and personalized treatment plans based on the identified landmarks within the etiological network. Through the integration of graph theory into hyperacusis research, the complexity of this auditory condition was unraveled and pave the way for more effective approaches to its management.

Keywords: auditory condition, connected graph, hyperacusis, metric dimension

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Authors: Salma Baig, Bakrudeen Ali Ahmad, Ainnul Hamidah Syahadah Azizan, Hapipah Mohd Ali, Elham Rouhollahi, Mahmood Ameen Abdulla

Abstract:

Free radical damage induced by reactive oxygen species (ROS) contributes to etiology of many chronic diseases, cancer being one of them. Recent studies have been successful in ROS targeted therapies via antioxidants using mouse models in cancer therapeutics. The present study was designed to scrutinize anticancer activity, antioxidant activity of 5 different extracts of Thymus serpyllum in MDA-MB-231, MCF-7, HepG2, HCT-116, PC3, and A549. Identification of the phytochemicals present in the most active extract of Thymus serpyllum was conducted using gas chromatography coupled with mass spectrophotometry and antioxidant activity was measured by using DPPH radical scavenging and FRAP assay. Anticancer impact of the extract in terms of IC50 was evaluated using MTT cell viability assay. Results revealed that the hexane extract showed the best anticancer activity in HepG2 (Liver Carcinoma Cell Line) with an IC50 value of 23 ± 0.14 µg/ml followed by 25 µg/ml in HCT-116 (Colon Cancer Cell Line), 30 µm/ml in MCF-7 (Breast Cancer Cell Line), 35 µg/ml in MDA-MB-231 (Breast Cancer Cell Line), 57 µg/ml in PC3 (Prostate Cancer Cell Line) and 60 µg/ml in A549 (Lung Carcinoma Cell Line). GC-MS profile of the hexane extract showed the presence of 31 compounds with carvacrol, thymol and thymoquione being the major compounds. Phenolics such as Vitamin E, terpinen-4-ol, borneol and phytol were also identified. Hence, here we present the first report on cytotoxicity of hexane extract of Thymus serpyllum extract in HepG2 cell line with a robust anticancer activity with an IC50 of 23 ± 0.14 µg/ml.

Keywords: Thymus serpyllum L., hexane extract, GC-MS profile, antioxidant activity, anticancer activity, HepG2 cell line

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Authors: Bliss Singhal

Abstract:

Machine learning (ML) is a branch of Artificial Intelligence (AI) where computers analyze data and find patterns in the data. The study focuses on the detection of metastatic cancer using ML. Metastatic cancer is the stage where cancer has spread to other parts of the body and is the cause of approximately 90% of cancer-related deaths. Normally, pathologists spend hours each day to manually classifying whether tumors are benign or malignant. This tedious task contributes to mislabeling metastasis being over 60% of the time and emphasizes the importance of being aware of human error and other inefficiencies. ML is a good candidate to improve the correct identification of metastatic cancer, saving thousands of lives and can also improve the speed and efficiency of the process, thereby taking fewer resources and time. So far, the deep learning methodology of AI has been used in research to detect cancer. This study is a novel approach to determining the potential of using preprocessing algorithms combined with classification algorithms in detecting metastatic cancer. The study used two preprocessing algorithms: principal component analysis (PCA) and the genetic algorithm, to reduce the dimensionality of the dataset and then used three classification algorithms: logistic regression, decision tree classifier, and k-nearest neighbors to detect metastatic cancer in the pathology scans. The highest accuracy of 71.14% was produced by the ML pipeline comprising of PCA, the genetic algorithm, and the k-nearest neighbor algorithm, suggesting that preprocessing and classification algorithms have great potential for detecting metastatic cancer.

Keywords: breast cancer, principal component analysis, genetic algorithm, k-nearest neighbors, decision tree classifier, logistic regression

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Authors: Khawla Askri, Mohamed Haythem Msaddek, AbdelAziz Sebei

Abstract:

Climate change combined with the increase in anthropogenic activities will affect coastal groundwater systems around the world and, more particularly, the Cap Bon region in the North East of Tunisia. This study aims to study the impact of climate change and human stress on the salinization and quantification of groundwater in the Wadi Chiba watershed. In this regard, a hydro-climatological study and a hydrogeological study were carried out based on the characterization of the aquifer system of the eastern coast at the level of the watershed of Wadi Chiba in order to seek to identify, first of all, the degradation of the state of the aquifer on the quantitative level by the study of the piezometric and its evolution over time. Secondly, we sought to identify the degradation of the state of the aquifer qualitatively by using the geochemical method, in particular the major elements, to assess the mineralization of the aquifer water and understand its hydrogeochemical functioning. The study of the Na + / Cl- and Ca2 + / Mg2 + chemical relationships confirmed the presence of a marine intrusion downstream of the Wadi Chiba watershed northeast of Cap-Bon accompanied by a piezometric depression. For this purpose, we proceeded to: 1) Mapping of both piezometric data and salinity. 2) The interpretation of the mapping results. 3)Identification of the origin of the localized deterioration in the quality of the aquifer water. Finally, the analysis of the results showed that the scarcity of water is already forcing human actions in the Chiba watershed due to the irrigation of agricultural lands and the overexploitation of the water table in the study area.

Keywords: climate change, human activities, water table, Wadi Chiba watershed, piezometric depression, marine intrusion

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Authors: Alisher Ibragimov, Sofya Senotrusova, Aleksandra Beliaeva, Egor Ushakov, Yuri Markin

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Mammography plays a critical role in screening for breast cancer in women, and artificial intelligence has enabled the automatic detection of diseases in medical images. Many of the current techniques used for mammogram analysis focus on a single view (mediolateral or craniocaudal view), while in clinical practice, radiologists consider multiple views of mammograms from both breasts to make a correct decision. Consequently, computer-aided diagnosis (CAD) systems could benefit from incorporating information gathered from multiple views. In this study, the introduce a method based on a Siamese neural network (SNN) model that simultaneously analyzes mammographic images from tri-view: bilateral and ipsilateral. In this way, when a decision is made on a single image of one breast, attention is also paid to two other images – a view of the same breast in a different projection and an image of the other breast as well. Consequently, the algorithm closely mimics the radiologist's practice of paying attention to the entire examination of a patient rather than to a single image. Additionally, to the best of our knowledge, this research represents the first experiments conducted using the recently released Vietnamese dataset of digital mammography (VinDr-Mammo). On an independent test set of images from this dataset, the best model achieved an AUC of 0.87 per image. Therefore, this suggests that there is a valuable automated second opinion in the interpretation of mammograms and breast cancer diagnosis, which in the future may help to alleviate the burden on radiologists and serve as an additional layer of verification.

Keywords: breast cancer, computer-aided diagnosis, deep learning, multi-view mammogram, siamese neural network

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Authors: Cigdem Safak Saglam

Abstract:

Most thermal power plants use steam as working fluid in their power cycle. Therefore, in addition to fuel, water is the other main input for thermal plants. Water and steam must be highly pure in order to protect the systems from corrosion, scaling and biofouling. Pure process water is produced in water treatment plants having many several treatment methods. Treatment plant design is selected depending on raw water source and required water quality. Although working principle of fossil-fuel fired thermal power plants are same, there is no standard design and equipment arrangement valid for all thermal power plant utility systems. Besides that, there are many other technology evaluation and selection criteria for designing the most optimal water systems meeting the requirements such as local conditions, environmental restrictions, electricity and other consumables availability and transport, process water sources and scarcity, land use constraints etc. Aim of this study is explaining the adopted methodology for technology selection for process water preparation and industrial waste water treatment plant in a thermal power plant project located in Tufanbeyli, Adana Province in Turkey. Thermal power plant is fired with indigenous lignite coal extracted from adjacent lignite reserves. This paper addresses all above-mentioned factors affecting the thermal power plant water treatment facilities (demineralization + waste water treatment) design and describes the ultimate design of Tufanbeyli Thermal Power Plant Water Treatment Plant.

Keywords: thermal power plant, lignite coal, pretreatment, demineralization, electrodialysis, recycling, ash dampening

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Authors: Sujan Tyata, Alison Shilpakar, Nayan Bakhadyo, Kushal K. C., Abhas Maskey

Abstract:

The Koshi River, acknowledged as the "Sorrow of Bihar," poses intricate challenges characterized by recurrent flooding. Within the Koshi Basin, floods have historically inflicted damage on infrastructure, agriculture, and settlements. The Koshi River exhibits a highly braided pattern across a 48 km stretch to the south of Chatara. The devastating flood from the Koshi River, which began in Nepal's Sunsari District in 2008, led to significant casualties and the destruction of agricultural areas.The catastrophe was exacerbated by a levee breach, underscoring the vulnerability of the region's flood defenses. A comprehensive understanding of environmental changes in the area is unveiled through satellite imagery analysis. This analysis facilitates the identification of high-risk zones and their contributing factors. Employing remote sensing, the analysis specifically pinpoints locations vulnerable to levee breaches. Topographical features of the area along with longitudinal and cross sectional profiles of the river and levee obtained from digital elevation model are used in the hydrological analysis for assessment of flood. To mitigate the impact of floods, the strategy involves the establishment of reservoirs upstream. Leveraging satellite data, optimal locations for water storage are identified. This approach presents a dual opportunity to not only alleviate flood risks but also catalyze the implementation of pumped storage hydropower initiatives. This holistic approach addresses environmental challenges while championing sustainable energy solutions.

Keywords: flood mitigation, levee, remote sensing, satellite imagery analysis, sustainable energy solutions

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