Search results for: diagnostic accuracy

Authors: Shukla Ila, Azmi Lubna, S. S. Gupta, Ch. V. Rao

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Oxidative stress has been increasingly associated with the induction and progression of liver damage. The current study was conducted to record the effect of combination of Lactobacillus and Lichen rangiferinus extract (LRE + Lac) on the severity of injury in experimental alcoholic liver disease and how it affects plasma levels of prostaglandin E2, endotoxin, thromboxane B2, and leukotriene B4. Male Wistar rats were grouped into five comprising six animals in each group. Group 1 served as negative control. Groups 2-5 were administered 10% ethanol for six weeks. Group 3 was administered with extract (200 mg/kg), group 4 received the diet containing 10% ethanol plus a bolus of lactobacilli GG (1010 CFU), and group 5 animals were given silymarin along with alcohol and it served as positive control. Aspartate aminotransferase, alanine aminotransferase, alkaline phosphatase, total protein content, γ-glutamyltransferase, glutathione S-transferase, oxidative stress markers, glutathione, malondialdehyde and glutathione reductase were determined using standard diagnostic kits. Histopathological analysis of liver tissue was also made. A positive relation was found between plasma endotoxin levels and degree of liver injury. The pathology records were also related positively with leukotriene B4 and thromboxane B2. But a negative correlation was obtained with PgE2 levels. This study led us to hypothesize that the increased endotoxin levels modulate liver metabolism of eicosanoid, which gradually leads to liver injury. Endotoxemia increases leukotriene and thromboxane levels in plasma.

Keywords: lactobacillus, Lichen rangiferinus, endotoxemia, silymarin

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Authors: Eugene Y. J. Aw, J. W. Koh, S. H. Chew, K. E. Chua, P. L. Goh, Grace H. B. Foo, M. L. Leong

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This paper presents the evaluation of various soil testing methods such as the four-probe soil electrical resistivity method and cone penetration test (CPT) that can complement a newly developed novel rapid soil classification scheme using computer vision, to improve the accuracy and productivity of on-site classification of excavated soil. In Singapore, excavated soils from the local construction industry are transported to Staging Grounds (SGs) to be reused as fill material for land reclamation. Excavated soils are mainly categorized into two groups (“Good Earth” and “Soft Clay”) based on particle size distribution (PSD) and water content (w) from soil investigation reports and on-site visual survey, such that proper treatment and usage can be exercised. However, this process is time-consuming and labor-intensive. Thus, a rapid classification method is needed at the SGs. Four-probe soil electrical resistivity and CPT were evaluated for their feasibility as suitable additions to the computer vision system to further develop this innovative non-destructive and instantaneous classification method. The computer vision technique comprises soil image acquisition using an industrial-grade camera; image processing and analysis via calculation of Grey Level Co-occurrence Matrix (GLCM) textural parameters; and decision-making using an Artificial Neural Network (ANN). It was found from the previous study that the ANN model coupled with ρ can classify soils into “Good Earth” and “Soft Clay” in less than a minute, with an accuracy of 85% based on selected representative soil images. To further improve the technique, the following three items were targeted to be added onto the computer vision scheme: the apparent electrical resistivity of soil (ρ) measured using a set of four probes arranged in Wenner’s array, the soil strength measured using a modified mini cone penetrometer, and w measured using a set of time-domain reflectometry (TDR) probes. Laboratory proof-of-concept was conducted through a series of seven tests with three types of soils – “Good Earth”, “Soft Clay,” and a mix of the two. Validation was performed against the PSD and w of each soil type obtained from conventional laboratory tests. The results show that ρ, w and CPT measurements can be collectively analyzed to classify soils into “Good Earth” or “Soft Clay” and are feasible as complementing methods to the computer vision system.

Keywords: computer vision technique, cone penetration test, electrical resistivity, rapid and non-destructive, soil classification

Procedia PDF Downloads 236

Authors: Vikas S. Minchekar

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The eyewitness is a crucial source of evidence in the criminal judicial system. However, rely on the reminiscence of an eyewitness especially intoxicated eyewitness is not always judicious. It might lead to some serious consequences. Day by day, alcohol-related crimes or the criminal incidences in bars, nightclubs, and restaurants are increasing rapidly. Tackling such cases is very complicated to any investigation officers. The people in that incidents are violated due to the alcohol consumption hence, their ability to identify the suspects or recall these phenomena is affected. The studies on the effects of alcohol consumption on motor activities such as driving and surgeries have received much attention. However, the effect of alcohol intoxication on memory has received little attention from the psychology, law, forensic and criminology scholars across the world. In the Indian context, the published articles on this issue are equal to none up to present day. This field experiment investigation aimed at to finding out the effect of alcohol consumption on identification accuracy in lineups. Forty adult, social drinkers, and twenty sober adults were randomly recruited for the study. The sober adults were assigned into 'placebo' beverage group while social drinkers were divided into two group e. g. 'low dose' of alcohol (0.2 g/kg) and 'high dose' of alcohol (0.8 g/kg). The social drinkers were divided in such a way that their level of blood-alcohol concentration (BAC) will become different. After administering the beverages for the placebo group and liquor to the social drinkers for 40 to 50 minutes of the period, the five-minute video clip of mock crime is shown to all in a group of four to five members. After the exposure of video, clip subjects were given 10 portraits and asked them to recognize whether they are involved in mock crime or not. Moreover, they were also asked to describe the incident. The subjects were given two opportunities to recognize the portraits and to describe the events; the first opportunity is given immediately after the video clip and the second was 24 hours later. The obtained data were analyzed by one-way ANOVA and Scheffe’s posthoc multiple comparison tests. The results indicated that the 'high dose' group is remarkably different from the 'placebo' and 'low dose' groups. But, the 'placebo' and 'low dose' groups are equally performed. The subjects in a 'high dose' group recognized only 20% faces correctly while the subjects in a 'placebo' and 'low dose' groups are recognized 90 %. This study implied that the intoxicated witnesses are less accurate to recognize the suspects and also less capable of describing the incidents where crime has taken place. Moreover, this study does not assert that intoxicated eyewitness is generally less trustworthy than their sober counterparts.

Keywords: intoxicated eyewitness, memory, social drinkers, lineups

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Authors: X. Wang

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Timely and accurate information on urban building damage caused by earthquake is important basis for disaster assessment and emergency relief. Very high resolution (VHR) remotely sensed imagery containing abundant fine-scale information offers a large quantity of data for detecting and assessing urban building damage in the aftermath of earthquake disasters. However, the accuracy obtained using spectral features alone is comparatively low, since building damage, intact buildings and pavements are spectrally similar. Therefore, it is of great significance to detect urban building damage effectively using multi-source data. Considering that in general height or geometric structure of buildings change dramatically in the devastated areas, a novel multi-stage urban building damage detection method, using bi-temporal spectral, height and corner information, was proposed in this study. The pre-event height information was generated using stereo VHR images acquired from two different satellites, while the post-event height information was produced from airborne LiDAR data. The corner information was extracted from pre- and post-event panchromatic images. The proposed method can be summarized as follows. To reduce the classification errors caused by spectral similarity and errors in extracting height information, ground surface, shadows, and vegetation were first extracted using the post-event VHR image and height data and were masked out. Two different types of building damage were then extracted from the remaining areas: the height difference between pre- and post-event was used for detecting building damage showing significant height change; the difference in the density of corners between pre- and post-event was used for extracting building damage showing drastic change in geometric structure. The initial building damage result was generated by combining above two building damage results. Finally, a post-processing procedure was adopted to refine the obtained initial result. The proposed method was quantitatively evaluated and compared to two existing methods in Port au Prince, Haiti, which was heavily hit by an earthquake in January 2010, using pre-event GeoEye-1 image, pre-event WorldView-2 image, post-event QuickBird image and post-event LiDAR data. The results showed that the method proposed in this study significantly outperformed the two comparative methods in terms of urban building damage extraction accuracy. The proposed method provides a fast and reliable method to detect urban building collapse, which is also applicable to relevant applications.

Keywords: building damage, corner, earthquake, height, very high resolution (VHR)

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Authors: Seyed Davar Siadat, Samira Tarashi, Abolfazl Fateh, Arfa Moshiri

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Background: The global health issue of tuberculosis (TB) still affects patients in every country. TB control may not be as effective as it should be, especially when resistant strains are involved. In this regard, mycobacterial MTases play a major role in tuberculosis, but the mechanisms underlying their function have yet to be fully deciphered. Methods: Five resistant isolates of M.tb were accumulated. As a reference strain, M.tb H37Rv (ATCC 27249) was used. For this analysis, seven putative mycobacterial MTase genes (Rv0645c, Rv1694, Rv2966c, Rv3919c, Rv2756c, Rv1988, and Rv3263), as well as Rv1392 as SAM synthase, were selected. Comparing mutations and expression levels of MTases in different strains was accomplished by PCR-sequencing and qRT-PCR. The relative expression levels of these genes were calculated using the 2 -ΔΔCt method. Results: The Rv3919c gene (T to G in codon 341) and Rv1392 gene (G to A in codon 97) were the only mutations found in the INHR strain. In all sensitive and resistant isolates, Rv0645c, Rv3263, Rv2756c, and Rv2966c were overexpressed. However, the expression of Rv1988 and Rv3919c decreased in the sensitive strains, whereas the expression of Rv1694 increased. There was also a decreased expression of Rv1392 in the INHR isolate. Conclusion: The presence of mycobacterial MTases as well as resistance to antibiotics were found to be correlated in M.tb strains. Undoubtedly, there are some MTases that are associated with the virulence process. It is necessary to conduct additional studies to fully explore the impact of mycobacterial MTases within specific strains of M.tb to develop novel diagnostic and treatment strategies.

Keywords: mycobacterium tuberculosis, drug resistance, methyltransferases, s-adenosylmethionine

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Authors: Raneem Osama Salem, Ayesha Nuzhat, Fatimah Nasser Al Shehri, Nasser Al Hamdan

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Background: Recently, most medical schools around the globe are using simulation for teaching and assessing students’ clinical skills and competence. There are many obstacles that could face students and faculty when simulation sessions are introduced into undergraduate curriculum. Objective: The aim of this study is to obtain the opinion of undergraduate medical students and our faculty regarding the role of simulation in undergraduate curriculum, the simulation modalities used, and perceived barriers in implementing stimulation sessions. Methods: To address the role of simulation, modalities used, and perceived challenges to implementation of simulation sessions, a self-administered pilot tested questionnaire with 18 items using a 5 point Likert scale was distributed. Participants included undergraduate male medical students (n=125) and female students (n=70) as well as the faculty members (n=14). Result: Various learning outcomes are achieved and improved through the technology enhanced simulation sessions such as communication skills, diagnostic skills, procedural skills, self-confidence, and integration of basic and clinical sciences. The use of high fidelity simulators, simulated patients and task trainers was more desirable by our students and faculty for teaching and learning as well as an evaluation tool. According to most of the students,' institutional support in terms of resources, staff and duration of sessions was adequate. However, motivation to participate in the sessions and provision of adequate feedback by the staff was a constraint. Conclusion: The use of simulation laboratory is of great benefit to the students and a great teaching tool for the staff to ensure students learning of the various skills.

Keywords: simulators, medical students, skills, simulated patients, performance, challenges, skill laboratory

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Authors: Omar Farshad Jeelani, Makaire Njie, Viktoriia M. Korzhuk

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Recently, the application of AI-powered algorithms in healthcare continues to flourish. Particularly, access to healthcare information, including patient health history, diagnostic data, and PII (Personally Identifiable Information) is paramount in the delivery of efficient patient outcomes. However, as the exchange of healthcare information between patients and healthcare providers through AI-powered solutions increases, protecting a person’s information and their privacy has become even more important. Arguably, the increased adoption of healthcare AI has resulted in a significant concentration on the security risks and protection measures to the security and privacy of healthcare data, leading to escalated analyses and enforcement. Since these challenges are brought by the use of AI-based healthcare solutions to manage healthcare data, AI-based data protection measures are used to resolve the underlying problems. Consequently, this project proposes AI-powered safeguards and policies/laws to protect the privacy of healthcare data. The project presents the best-in-school techniques used to preserve the data privacy of AI-powered healthcare applications. Popular privacy-protecting methods like Federated learning, cryptographic techniques, differential privacy methods, and hybrid methods are discussed together with potential cyber threats, data security concerns, and prospects. Also, the project discusses some of the relevant data security acts/laws that govern the collection, storage, and processing of healthcare data to guarantee owners’ privacy is preserved. This inquiry discusses various gaps and uncertainties associated with healthcare AI data collection procedures and identifies potential correction/mitigation measures.

Keywords: data privacy, artificial intelligence (AI), healthcare AI, data sharing, healthcare organizations (HCOs)

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Authors: Mokrane Selma

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The shift towards decision making (DM) based on artificial intelligence (AI) techniques will change the way in which consumer markets and our societies function. Through AI, predictive analytics is being used by businesses to identify these patterns and major trends with the objective to improve the DM and influence future business outcomes. This paper proposes an Artificial Neural Network (ANN) approach to predict the success of telemarketing calls for selling bank long-term deposits. To validate the proposed model, we uses the bank marketing data of 41188 phone calls. The ANN attains 98.93% of accuracy which outperforms other conventional classifiers and confirms that it is credible and valuable approach for telemarketing campaign managers.

Keywords: bank telemarketing, prediction, decision making, artificial intelligence, artificial neural network

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Authors: Abdulrahman Algaeed

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The Ophthalmic Ultrasound is the easiest method of early diagnosing Retinoblastoma after clinical examination. It can be done with ease without sedation. King Khaled Eye Specialist Hospital is a tertiary care center where Retinoblastoma patients are often seen and treated there. The first modality to rule out the disease is Ophthalmic Ultrasound. Classic Retinoblastoma is easily diagnosed by using the conventional 10MHz Ophthalmic Ultrasound probe in the regular clinic setup. Retinal lesion with multiple, very highly reflective surfaces within lesion typical of Calcium deposits. The use of Standardized A-scan is very useful where internal reflectivity is classified as very highly reflective. Color Doppler is extremely useful as well to show the blood flow within lesion/s. In conclusion: Ophthalmic Ultrasound should be the first tool to be used to diagnose Retinoblastoma after clinical examination. The accuracy of the Exam is very high.

Keywords: doppler, retinoblastoma, reflectivity, ultrasound

Procedia PDF Downloads 111

Authors: A. A. M. A. S. S. Perera, L. A. Ranasinghe, T. K. H. Nimeshika, D. M. Dhanushka Dissanayake, Namalie Walgampaya

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Nowadays, skin fungal diseases are mostly found in people of tropical countries like Sri Lanka. A skin fungal disease is a particular kind of illness caused by fungus. These diseases have various dangerous effects on the skin and keep on spreading over time. It becomes important to identify these diseases at their initial stage to control it from spreading. This paper presents an automated skin fungal disease identification system implemented to speed up the diagnosis process by identifying skin fungal infections in digital images. An image of the diseased skin lesion is acquired and a comprehensive computer vision and image processing scheme is used to process the image for the disease identification. This includes colour analysis using RGB and HSV colour models, texture classification using Grey Level Run Length Matrix, Grey Level Co-Occurrence Matrix and Local Binary Pattern, Object detection, Shape Identification and many more. This paper presents the approach and its outcome for identification of four most common skin fungal infections, namely, Tinea Corporis, Sporotrichosis, Malassezia and Onychomycosis. The main intention of this research is to provide an automated skin fungal disease identification system that increase the diagnostic quality, shorten the time-to-diagnosis and improve the efficiency of detection and successful treatment for skin fungal diseases.

Keywords: Circularity Index, Grey Level Run Length Matrix, Grey Level Co-Occurrence Matrix, Local Binary Pattern, Object detection, Ring Detection, Shape Identification

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Authors: Sophia Liang Zhou

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For investors, businesses, consumers, and governments, an accurate assessment of future housing prices is crucial to critical decisions in resource allocation, policy formation, and investment strategies. Previous studies are contradictory about macroeconomic determinants of housing price and largely focused on one or two areas using point prediction. This study aims to develop data-driven models to accurately predict future housing market trends in different markets. This work studied five different metropolitan areas representing different market trends and compared three-time lagging situations: no lag, 6-month lag, and 12-month lag. Linear regression (LR), random forest (RF), and artificial neural network (ANN) were employed to model the real estate price using datasets with S&P/Case-Shiller home price index and 12 demographic and macroeconomic features, such as gross domestic product (GDP), resident population, personal income, etc. in five metropolitan areas: Boston, Dallas, New York, Chicago, and San Francisco. The data from March 2005 to December 2018 were collected from the Federal Reserve Bank, FBI, and Freddie Mac. In the original data, some factors are monthly, some quarterly, and some yearly. Thus, two methods to compensate missing values, backfill or interpolation, were compared. The models were evaluated by accuracy, mean absolute error, and root mean square error. The LR and ANN models outperformed the RF model due to RF’s inherent limitations. Both ANN and LR methods generated predictive models with high accuracy ( > 95%). It was found that personal income, GDP, population, and measures of debt consistently appeared as the most important factors. It also showed that technique to compensate missing values in the dataset and implementation of time lag can have a significant influence on the model performance and require further investigation. The best performing models varied for each area, but the backfilled 12-month lag LR models and the interpolated no lag ANN models showed the best stable performance overall, with accuracies > 95% for each city. This study reveals the influence of input variables in different markets. It also provides evidence to support future studies to identify the optimal time lag and data imputing methods for establishing accurate predictive models.

Keywords: linear regression, random forest, artificial neural network, real estate price prediction

Procedia PDF Downloads 100

Authors: Sanaa I. Abu Alasal, Madleen M. Esbeih, Eman R. Fayyad, Rami S. Gharaibeh, Mostafa Z. Ali, Ahmed A. Freewan, Monther M. Jamhawi

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This research proposes a novel reconstruction protocol for restoring missing surfaces and low-quality edges and shapes in photos of artifacts at historical sites. The protocol starts with the extraction of a cloud of points. This extraction process is based on four subordinate algorithms, which differ in the robustness and amount of resultant. Moreover, they use different -but complementary- accuracy to some related features and to the way they build a quality mesh. The performance of our proposed protocol is compared with other state-of-the-art algorithms and toolkits. The statistical analysis shows that our algorithm significantly outperforms its rivals in the resultant quality of its object files used to reconstruct the desired model.

Keywords: meshes, point clouds, surface reconstruction protocols, 3D reconstruction

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Authors: Monika Szpringer, Mariola Wojciechowska, Robert Dutkiewicz, Grażyna Nowak-Starz, Marzena Olędzka

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The main aim of this article is to determine the phenomenon of stress among academic teachers as well as to identify the extent to which the teachers experience work-related psychological risks. It is also important to support academic teachers trade unions in scope of stress-oriented activities, including psychological dangers in the assessment of risk in the workplace (college). The authors used a method of a diagnostic survey with a polling as a technique and authors’ questionnaire as a tool. The survey was conducted between September and December of 2013 and it comprised 1890 academic teachers from five voivodeships. The study reveals that 84.0% of the respondents found the work of an academic teacher to be borne with a considerable stress. The percentage values of the most frequent causes of stress are as follows: frequent changes of both organisational and didactic matters as well as overwhelming bureaucracy (77.8 %), time pressure regarding professional development and related risk of losing job (68.2 %), difficult working conditions (45.4%), conflicts and rivalry between teachers (44.1%), excessive amount of duties as well as increasing requirements and demanding attitude of students (33.7%). Work-related stress affects or significantly affects the private life of 69 % and 66.4 % of the respondents respectively. The majority of the people surveyed deals with stress by undertaking various activities, with 40% pointing at using various substances, mostly cigarettes and alcohol (p > 0,05) Physical ailments were experienced by 81% of the respondents, in 9% they were rare and 8 % of the respondents had never experienced such disorders. The entire group of the surveyed people (100 %) claimed that they have no possibility of contacting a psychologist at their workplace (p > 0.05), and they stated that the need of contacting specialists does exist.

Keywords: stress, academic teachers, psychological risks, work-related

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Authors: Ernesto A. Lagarda-Leyva, Manuel A. Valenzuela L., José G. Oshima C., Arnulfo A. Naranjo-Flores

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From August to December of 2016, a diagnostic and strategic planning study was carried out on the supply chain of the company Agropecuaria GABO S.A. de C.V. The final product of the study was the development of the strategic plan and a project portfolio to meet the demands of the three links in the supply chain of the Roma tomato exported annually to the United States of America. In this project, the strategic objective of ensuring the proper handling of the product was selected and one of the goals associated with this was the employment of quantitative methods to support decision making. Considering the antecedents, the objective of this case study was to develop a model to analyze the behavioral dynamics in the distribution chain, from the logistics of storage and shipment of Roma tomato in 81-case pallets (11.5 kg per case), to the two pre-cooling rooms and eventual loading onto transports, seeking to reduce the bottleneck and the associated costs by means of a dynamic interface. The methodology used was that of system dynamics, considering four phases that were adapted to the purpose of the study: 1) the conceptualization phase; 2) the formulation phase; 3) the evaluation phase; and 4) the communication phase. The main practical conclusions lead to the possibility of reducing both the bottlenecks in the cooling rooms and the costs by simulating scenarios and modifying certain policies. Furthermore, the creation of the dynamic interface between the model and the stakeholders was achieved by generating interaction with buttons and simple instructions that allow making modifications and observing diverse behaviors.

Keywords: agrilogistics, distribution, scenarios, system dynamics

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Authors: Aliasghar Golmohammadian, Sona Rostampour Yasouri

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One of the most important intestinal pathogenic strains is E. coli O₁₅₇:H₇. This pathogenic bacterium is transmitted to humans through water and food. E. coli O₁₅₇:H₇ is the main cause of Hemorrhagic colitis (HC), Hemolytic Uremic Syndrome (HUS), Thrombotic Thrombocytopenic Purpura (TTP) and in some cases death. Since E. coli O₁₅₇:H₇ can be transmitted through the consumption of different foods, including vegetables, agricultural products, and fresh dairy products, this study aims to identify and isolate E. coli O₁₅₇:H₇ from wastewater by PCR technique. One hundred twenty samples of water and wastewater were collected by Falcom Sterile from Shahrood and Neka cities. The samples were checked for colony formation after appropriate centrifugation and cultivation in the specific medium of Sorbitol MacConkey Agar (SMAC) and other diagnostic media of E. coli O₁₅₇:H₇. Also, the plates were observed macroscopically and microscopically. Then, the necessary phenotypic tests were performed on the colonies, and finally, after DNA extraction, the PCR technique was performed with specific primers related to rfbE and stx2 genes. The number of 5 samples (6%) out of all the samples examined were determined positive by PCR technique with observing the bands related to the mentioned genes on the agarose gel electrophoresis. PCR is a fast and accurate method to identify the bacteria E. coli O₁₅₇:H₇. Considering that E. coli bacteria is a resistant bacteria and survives in water and food for weeks and months, the PCR technique can provide the possibility of quick detection of contaminated water. Moreover, it helps people in the community control and prevent the transfer of bacteria to healthy and underground water and agricultural and even dairy products.

Keywords: E. coli O₁₅₇:H₇, PCR, water, wastewater

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Authors: Abdullah A. Al Qurashi, Hattan A. Hassani, Bader K. Alaslap

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Arrhythmogenic Right Ventricular Dysplasia/Cardiomyopathy (ARVD/C) is an uncommon, inheritable cardiac disorder characterized by the progressive substitution of cardiac myocytes by fibro-fatty tissues. This pathologic substitution predisposes patients to ventricular arrhythmias and right ventricular failure. The underlying genetic defect predominantly involves genes encoding for desmosome proteins, particularly plakophilin-2 (PKP2). These aberrations lead to impaired cell adhesion, heightening the susceptibility to fibrofatty scarring under conditions of mechanical stress. Primarily, ARVD/C affects the right ventricle, but it can also compromise the left ventricle, potentially leading to biventricular heart failure. Clinical presentations can vary, spanning from asymptomatic individuals to those experiencing palpitations, syncopal episodes, and, in severe instances, sudden cardiac death. The establishment of a diagnostic criterion specifically tailored for ARVD/C significantly aids in its accurate diagnosis. Nevertheless, the task of early diagnosis is complicated by the disease's frequently asymptomatic initial stages, and the overall rarity of ARVD/C cases reported globally. In some cases, as exemplified by the adult female patient in this report, the disease may advance to terminal stages, rendering therapies like Ventricular Tachycardia (VT) ablation ineffective. This case underlines the necessity for increased awareness and understanding of ARVD/C to aid in its early detection and management. Through such efforts, we aim to decrease morbidity and mortality associated with this challenging cardiac disorder.

Keywords: arrhythmogenic right ventricular dysplasia, cardiac disease, interventional cardiology, cardiac electrophysiology

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Authors: M. Zielina, W. Dabrowski, E. Radziszewska-Zielina

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Several different cements have been tested to evaluate their potential to leach calcium, chromium and aluminum ions in soft water environment. The research allows comparing some different cements in order to the potential risk of water contamination. This can be done only in the same environment. To reach the results in reasonable short time intervals and to make heavy metals measurements with high accuracy, demineralized water was used. In this case the conditions of experiments are far away from the water supply practice, but short time experiments and measurably high concentrations of elements in the water solution are an important advantage. Moreover leaching mechanisms can be recognized, our experiments reported here refer to this kind of cements evaluation.

Keywords: concrete corrosion, hydrogen sulfide, odors, reinforced concrete sewers, sewerage

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Authors: Shahram Naghizadeh Raeisi, Ali Alghooneh

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The application of whey protein in drink industry to enhance the nutritional value of the products is important. Furthermore, the gelification of protein during thermal treatment and shelf life makes some limitations in its application. So, the main goal of this research is manufacturing of high concentrate whey protein orange drink with appropriate shelf life. In this way, whey protein was 5 to 30% hydrolyzed ( in 5 percent intervals at six stages), then thermal stability of samples with 10% concentration of protein was tested in acidic condition (T= 90 °C, pH=4.2, 5 minutes ) and neutral condition (T=120° C, pH:6.7, 20 minutes.) Furthermore, to study the shelf life of heat treated samples in 4 months at 4 and 24 °C, the time sweep rheological test were done. At neutral conditions, 5 to 20% hydrolyzed sample showed gelling during thermal treatment, whereas at acidic condition, was happened only in 5 to 10 percent hydrolyzed samples. This phenomenon could be related to the difference in hydrodynamic radius and zeta potential of samples with different level of hydrolyzation at acidic and neutral conditions. To study the gelification of heat resistant protein solutions during shelf life, for 4 months with 7 days intervals, the time sweep analysis were performed. Cross over was observed for all heat resistant neutral samples at both storage temperature, while in heat resistant acidic samples with degree of hydrolysis, 25 and 30 percentage at 4 and 20 °C, it was not seen. It could be concluded that the former sample was stable during heat treatment and 4 months storage, which made them a good choice for manufacturing high protein drinks. The Scheffe polynomial model and numerical optimization were employed for modeling and high protein orange drink formula optimization. Scheffe model significantly predicted the overal acceptance index (Pvalue<0.05) of sensorial analysis. The coefficient of determination (R2) of 0.94, the adjusted coefficient of determination (R2Adj) of 0.90, insignificance of the lack-of-fit test and F value of 64.21 showed the accuracy of the model. Moreover, the coefficient of variable (C.V) was 6.8% which suggested the replicability of the experimental data. The desirability function had been achieved to be 0.89, which indicates the high accuracy of optimization. The optimum formulation was found as following: Modified whey protein solution (65.30%), natural orange juice (33.50%), stevia sweetener (0.05%), orange peel oil (0.15%) and citric acid (1 %), respectively. Its worth mentioning that this study made an appropriate model for application of whey protein in drink industry without bitter flavor and gelification during heat treatment and shelf life.

Keywords: croos over, orange beverage, protein modification, optimization

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Authors: Rajendra N. Ghosh, Paramjeet Singh, Niranjan Khandelwal, Sameer Vyas, Pratibha Singhi, Naveen Sankhyan

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Background: Tuberculoma and neurocysticercosis (NCC) are two most common intracranial infections in developing country. They often simulate on neuroimaging and in absence of typical imaging features cause significant diagnostic dilemmas. Differentiation is extremely important to avoid empirical exposure to antitubercular medications or nonspecific treatment causing disease progression. Purpose: Better characterization and differentiation of CNS tuberculoma and NCC by using morphological and multiple advanced functional MRI. Material and Methods: Total fifty untreated patients (20 tuberculoma and 30 NCC) were evaluated by using conventional and advanced sequences like CISS, SWI, DWI, DTI, Magnetization transfer (MT), T2Relaxometry (T2R), Perfusion and Spectroscopy. rCBV,ADC,FA,T2R,MTR values and metabolite ratios were calculated from lesion and normal parenchyma. Diagnosis was confirmed by typical biochemical, histopathological and imaging features. Results: CISS was most useful sequence for scolex detection (90% on CISS vs 73% on routine sequences). SWI showed higher scolex detection ability. Mean values of ADC, FA,T2R from core and rCBV from wall of lesion were significantly different in tuberculoma and NCC (P < 0.05). Mean values of rCBV, ADC, T2R and FA for tuberculoma and NCC were (3.36 vs1.3), (1.09x10⁻³vs 1.4x10⁻³), (0.13 x10⁻³ vs 0.09 x10⁻³) and (88.65 ms vs 272.3 ms) respectively. Tuberculomas showed high lipid peak, more choline and lower creatinine with Ch/Cr ratio > 1. T2R value was most significant parameter for differentiation. Cut off values for each significant parameters have proposed. Conclusion: Quantitative MRI in combination with conventional sequences can better characterize and differentiate similar appearing tuberculoma and NCC and may be incorporated in routine protocol which may avoid brain biopsy and empirical therapy.

Keywords: advanced functional MRI, differentiation, neurcysticercosis, tuberculoma

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Authors: Te Wen Tu, Sen Yung Lee

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An alternative approach is proposed to develop the analytic solution for one dimensional heat conduction with one mixed type boundary condition and general time-dependent heat transfer coefficient. In this study, the physic meaning of the solution procedure is revealed. It is shown that the shifting function takes the physic meaning of the reciprocal of Biot function in the initial time. Numerical results show the accuracy of this study. Comparing with those given in the existing literature, the difference is less than 0.3%.

Keywords: analytic solution, heat transfer coefficient, shifting function method, time-dependent boundary condition

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Authors: Robin L. Rohrer

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Introduction: Pre-natal or early childhood exposure to the medical radiation used in diagnosis or treatment is an identified risk for childhood cancers but can be difficult to document. The author developed a family questionnaire/interview form to identify possible exposures. Aims: This retrospective study examines pre-natal and early childhood medical radiation exposure in a cohort of children diagnosed with a solid tumor including brain tumors from 1985-2015 at the Children’s Hospital of Pittsburgh (CHP). The hospital is a tri-state regional referral center which treats about 150-180 new cases of cancer in children per year. About 70% are diagnosed with a solid tumor. Methods: Each consented family so far (approximately 50% of the cohort) has been interviewed in person or by the phone call. Medical staff and psycho- social staff referred patient families for the interview with the author. Results: Among the families interviewed to date at least one medical radiation exposure has been identified (pre-conception, pre-natal or early childhood) in over 70% of diagnosed children. These exposures have included pre-conception sinus or chest CT or X-ray in either parent, sinus CT or X-ray in the mother or diagnostic radiation of chest or abdomen in children. Conclusions: Exposures to medical radiation for a child later diagnosed with cancer may occur at several critical junctures. These exposures may well contribute to a ‘perfect storm’ in the still elusive causes of childhood cancer. The author plans to expand the study from 1975 to present to hopefully further document these junctures.

Keywords: pediatric, solid tumors, medical radiation, cancer

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Authors: Jheanel E. Estrada, Larry A. Vea

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This study developed model to detect proper/improper sitting posture using the built in web camera which detects the upper body points’ location and distances (chin, manubrium and acromion process). It also established relationships of human body frames and proper sitting posture. The models were developed by training some well-known classifiers such as KNN, SVM, MLP, and Decision Tree using the data collected from 60 students of different body frames. Decision Tree classifier demonstrated the most promising model performance with an accuracy of 95.35% and a kappa of 0.907 for head and shoulder posture. Results also showed that there were relationships between body frame and posture through Body Mass Index.

Keywords: posture, spinal points, gyroscope, image processing, ergonomics

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Authors: Jadwiga Klukow, Anna Ksykiewicz-Dorota

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An analysis of the distribution of nurses’ working time constitutes vital information for the management in planning employment. The objective of the study was to analyze the distribution of nurses’ working time in an emergency department. The study was conducted in an emergency department of a teaching hospital in Lublin, in Southeast Poland. The catalogue of activities performed by nurses was compiled by means of continuous observation. Identified activities were classified into four groups: Direct care, indirect care, coordination of work in the department and personal activities. Distribution of nurses’ working time was determined by work sampling observation (Tippett) at random intervals. The research project was approved by the Research Ethics Committee by the Medical University of Lublin (Protocol 0254/113/2010). On average, nurses spent 31% of their working time on direct care, 47% on indirect care, 12% on coordinating work in the department and 10% on personal activities. The most frequently performed direct care tasks were diagnostic activities – 29.23% and treatment-related activities – 27.69%. The study has provided information on the complexity of performed activities and utilization of nurses’ working time. Enhancing the effectiveness of nursing actions requires working out a strategy for improved management of the time nurses spent at work. Increasing the involvement of auxiliary staff and optimizing communication processes within the team may lead to reduction of the time devoted to indirect care for the benefit of direct care.

Keywords: emergency nurses, nursing care, workload, work sampling

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Authors: Mohammad Naeem Lakanwall, Jamshid Abdul-Ghafar

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Background: Endocrinopathies are a commonly occurring entity, particularly those of the thyroid gland; however, there is a lack of scientific literature from Afghanistan, a country with very limited health care facilities and resources. To our best knowledge, this is the first study aimed to describe the frequency of occurrence and factors associated with thyroid dysfunction in the Afghan population. The aim of this study is to estimate the frequency and to identify factors associated with thyroid dysfunction among individuals coming to a tertiary care facility in Kabul, Afghanistan. Methods: A cross-sectional study was conducted from July to Sep 2018 at the Department of Clinical Pathology, French Medical Institute for Mothers and Children (FMIC), Kabul, Afghanistan. Blood samples were obtained, serum TSH levels were analyzed, and the patients were divided into three diagnostic categories according to their serum TSH concentrations: 1) hypothyroidism, 2) hyperthyroidism, 3) normal. Results: A total of 127 individuals were included in the final analysis. The majority of study participants (77%) were females. A large number of the participants (92%) did not have a family history of thyroid dysfunction. 74% of the participants in the study had normal TSH levels classified as normal thyroid function, (14%) had lower TSH levels, and (12%) higher TSH levels, classified as hyper and hypothyroid, respectively. Conclusions: The findings of the current study showed a high frequency of thyroid dysfunctions from a single center. Further large-scale studies are needed to find out the prevalence and document this entity for better health outcomes in the country.

Keywords: Afghanistan, factors, frequency, hypothyroid, hyperthyroid, thyroid, thyroid stimulating hormone

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Authors: V. Mentl, V. Koula, P. Mazal, J. Volák

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Nowadays, the acoustic emission is a widely recognized method of material damage investigation, mainly in cases of cracks initiation and growth observation and evaluation. This is highly important in structures, e.g. pressure vessels, large steam turbine rotors etc., applied both in classic and nuclear power plants. Nevertheless, the acoustic emission signals must be correlated with the real crack progress to be able to evaluate the cracks and their growth by this non-destructive technique alone in real situations and to reach reliable results when the assessment of the structures' safety and reliability is performed and also when the remaining lifetime should be evaluated. The main aim of this study was to propose a methodology for evaluation of the early manifestations of the fatigue cracks and their growth and thus to quantify the material damage by acoustic emission parameters. Specimens made of several steels used in the power producing industry were subjected to fatigue loading in the low- and high-cycle regimes. This study presents results of the crack growth rate measurement obtained by the classic compliance change method and the acoustic emission signal analysis. The experiments were realized in cooperation between laboratories of Brno University of Technology and West Bohemia University in Pilsen within the solution of the project of the Czech Ministry of Industry and Commerce: "A diagnostic complex for the detection of pressure media and material defects in pressure components of nuclear and classic power plants" and the project “New Technologies for Mechanical Engineering”.

Keywords: fatigue, crack growth rate, acoustic emission, material damage

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Authors: H. El-Messiry, M. El-Zainy, D. Abdelkhalek

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Cone-beam computed tomography (CBCT) provides high-quality 3-dimensional images of dental structures because of its high spatial resolution. The study of dental morphology is important in research as it provides information about diversities within a population. Many studies have shown different shapes and numbers of roots canals among different races, especially in molars. The aim of this study was to determine the morphology of root canals of mandibular first and third molars in a sample of Egyptian population using CBCT scanning. Fifty mandibular first Molars (M1) and fifty mandibular third (M3) extracted molars were collected. Thick rectangular molds were made using pink wax to hold the samples. Molars were embedded in the wax mold by aligning them in rows leaving arbitrary 0.5cm space between them. The molds with the samples in were submitted for CBCT scan. The number and morphology of root canals were assessed and classified according to Vertucci's classification. The mesial and the distal roots were examined separately. Finally, data was analyzed using Fisher exact test. The most prevalent mesial root canal frequency in M1 was type IV (60%) and type II (40 %), while M3 showed prevalence of type I (40%) and II (40%). Distal root canal morphology showed prevalence of type I in both M1 (66%) and M3 (86%). So, it can be concluded that CBCT scanning provides supplemental information about the root canal configurations of mandibular molars in a sample of Egyptian population. This study may help clinicians in the root canal treatment of mandibular molars.

Keywords: cone beam computed tomography, mandibular first molar, mandibular third molar, root canal morphology

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Authors: Fuzhang Zhao

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Particle swarm optimization (PSO) is becoming one of the most important swarm intelligent paradigms for solving global optimization problems. Although some progress has been made to improve PSO algorithms over the last two decades, additional work is still needed to balance parameters to achieve better numerical properties of accuracy, efficiency, and stability. In the optimal PSO algorithm, the optimal weightings of (√ 5 − 1)/2 and (3 − √5)/2 are used for the cognitive factor and the social factor, respectively. By the same token, the same optimal weightings have been applied for intensification searches and diversification searches, respectively. Perturbation and constriction effects are optimally balanced. Simulations of the de Jong, the Rosenbrock, and the Griewank functions show that the optimal PSO algorithm indeed achieves better numerical properties and outperforms the canonical PSO algorithm.

Keywords: diversification search, intensification search, optimal weighting, particle swarm optimization

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Authors: Djehich Mohamed Yousri

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In this research paper, the future of international relations is believed to have an important place on the theoretical and applied levels because policy makers in the world are in dire need of such analyzes that are useful in drawing up the foreign policies of their countries, and protecting their national security from potential future threats, and in this context, The topic raised a lot of scientific controversy and intellectual debate, especially in terms of the extent of the effectiveness, accuracy, and ability of foresight methods to identify potential futures, and this is what attributed the controversy to the scientific foundations for foreseeing international relations. An arena for intellectual discussion between different thinkers in international relations belonging to different theoretical schools, which confirms to us the conceptual and implied development of prediction in order to reach the scientific level.

Keywords: foresight, forecasting, international relations, international relations theory, concept of international relations

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Authors: Zahra Khan

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Surface-Enhanced Raman Spectroscopy (SERS) has received increased attention in recent years, focusing on biological and medical applications due to its great sensitivity as well as molecular specificity. In the context of biological samples, there are generally two methodologies for SERS based applications: label-free detection and the use of SERS tags. The necessity of tagging can make the process slower and limits the use for real life. Label-free detection offers the advantage that it reports direct spectroscopic evidence associated with the target molecule rather than the label. Reproducible, highly monodisperse gold nanoparticles (Au NPs) were synthesized using a relatively facile seed-mediated growth method. Different capping agents (TRIS, citrate, and CTAB) were used during synthesis, and characterization was performed. They were then mixed with different analyte solutions before drop-casting onto a glass slide prior to Raman measurements to see which NPs displayed the highest SERS activity as well as their stability. A host of different analytes were tested, both non-biomolecules and biomolecules, which were all successfully detected using this method at concentrations as low as 10-3M with salicylic acid reaching a detection limit in the nanomolar range. SERS was also performed on samples with a mixture of analytes present, whereby peaks from both target molecules were distinctly observed. This is a fast and effective rapid way of testing samples and offers potential applications in the biomedical field as a tool for diagnostic and treatment purposes.

Keywords: gold nanoparticles, label free, seed-mediated growth, SERS

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Authors: Awad Mohamed Elkhadir, Rajab M. Ben Yousef

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Background/Aim: Radiological technologists are medical professionals who perform diagnostic imaging tests such as X-rays, magnetic resonance imaging (MRI) scans, and computer tomography (CT) scans. Despite the recognition of image interpretation by British radiologists, it is still considered a problem in the Arab world. This study evaluates the perceptions of radiologists in the Middle East concerning the plain image interpretation of adults by radiologic technologist specialists. Methods: This is a cross-sectional study that follows a quantitative approach. A close-ended questionnaire was distributed among 103 participants who were radiologists by profession from various hospitals in Saudi Arabia and Sudan. The gathered data was then analyzed through Statistical Package for Social Sciences (SPSS). Results: The results showed that 29% recognized the Radiologic Technologist Specialist (RTS) role of writing image reports, while 61% did not. A total of 38% of participants believed that RTS image interpretation would help diagnose unreported radiographs. 47% of the sample responded that the workload and stress on radiologists would reduce by allowing reporting for RTS, while 37% did not. Lastly, 43% believe that image interpretation by RTS can be introduced into the Middle East in the future. Conclusion: The study's findings reveal that the combination of image reporting and radiography improves the care of the patients. The study's outcomes also show that the burden of the medical practitioners reduces due to image reporting of the radiographers. Further researches need to be conducted in the Arab World to obtain and measure the associated factors of the desired criteria.

Keywords: Arab world, image interpretation, radiographer, radiologist, Saudi Arabia, Sudan

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