Search results for: disease surveillance

Authors: Rahul Kumar Singh, Apurva Sharma, Dilip Kumar Srivastava

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Tilting of our interest towards unconventional exploitation of hydrocarbons has raised a serious concern to environmentalists. Emerging technologies like horizontal/multi-lateral drilling with subsequent hydraulic fracturing or fracking etc., for exploitation of different conventional/unconventional hydrocarbon reservoirs, are related to creating micro-level seismic events below the surface of the earth. Monitoring of these micro-level seismic events is not possible by the conventional methodology of the seismic method. So, to tackle this issue, a new technology that is microseismic is very much in discussions around the globe. Multiple researches are being carried out these days around the globe in order to prove microseismic as a new essential in the E & P industry, especially for unconventional reservoir management. Microseismic monitoring is now used for reservoir surveillance, and the best application is checking the integrity of the caprock and containment of fluid in it. In general, in whatever terms we want to use micro-seismic related events monitoring and understanding the effectiveness of stimulation, this technology offers a lot of value in terms of insight into the subsurface characteristics and processes, and this makes it really a good geophysical method to be used in future.

Keywords: microseismic, monitoring, hydraulic fracturing or fracking, reservoir surveillance, seismic hazards

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Authors: Abdela Bulbula

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Background: Marek’s disease virus is a devastating infection, causing high morbidity and mortality in chickens in Ethiopia. Methods: The current study was conducted from March to November, 2021 with the general objective of performing antemortem and postmortem, isolation, and molecular detection of Marek’s disease virus from outbreak cases in southwestern Ethiopia. Accordingly, based on outbreak information reported from the study sites namely, Bedelle, Yayo, and Bonga towns in southwestern Ethiopia, 50 sick chickens were sampled. The backyard and intensive farming systems of chickens were included in the sampling and priorities were given for chickens that showed clinical signs that are characteristics of Marek’s disease. Results: By clinical examinations, paralysis of legs and wings, gray eye, loss of weight, difficulty in breathing, and depression were recorded on all chickens sampled for this study and death of diseased chickens was observed. In addition, enlargement of the spleen and gross lesions of the liver and heart were recorded during postmortem examination. The death of infected chickens was observed in both vaccinated and non-vaccinated flocks. Out of 50 pooled feather follicle samples, Marek’s disease virus was isolated from 14/50 (28%) by cell culture method and out of six tissue samples, the virus was isolated from 5/6(83.30%). By Real time polymerization chain reaction technique, which was targeted to detect the Meq gene, Marek’s disease virus was detected from 18/50 feather follicles which accounts for 36% of sampled chickens. Conclusion: In general, the current study showed that the circulating Marek’s disease virus in southwestern Ethiopia was caused by the oncogenic Gallid herpesvirus-2 (Serotype-1). Further research on molecular characterization of revolving virus in current and other regions is recommended for effective control of the disease through vaccination.

Keywords: Ethioi, Marek's disease, isolation, molecular

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Authors: Rachel Karasenty Saltoun, Charlotte Roddick, Chelsea D. Christie, Frances Chen

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Moving has become an integral part of many people’s lives. This research explores whether relocating to a new city is associated with an increase in loneliness and cardiovascular disease risk and if this increased risk diminishes with continued residency. To test this, various psychosocial variables and three cardiovascular disease risk markers (C-reactive protein, albumin, blood pressure) were assessed on two groups of individuals: those who have moved to Vancouver, Canada in the previous 6 weeks (‘Movers’) and those who have lived in Vancouver for at least five years (‘Non-Movers’). It was hypothesized that individuals who had recently relocated would have heightened levels of loneliness, blood pressure (BP), albumin, and C-reactive protein (CRP) compared to those who had not recently relocated. Length of residency was hypothesized to moderate these effects, such that after a few months, loneliness levels and cardiovascular disease risk would decrease among those who had recently relocated. Correlational analysis indicated a trend between the change in CRP and albumin levels and loneliness overtime on an individual level. However, these results must be interpreted with caution due to the small sample size. As Vancouver’s immigration rates continue to grow, this study has important implications regarding the social support resources offered to new immigrants, as well as bringing awareness at the healthcare level of the potential increase in cardiovascular disease risk among those who have recently relocated.

Keywords: cardiovascular disease risk, loneliness, moving, residential mobility

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Authors: Mai M. Farid, Ximeng Yang, Tomoharu Kuboyama, Chihiro Tohda

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Trigonelline is a major alkaloid component derived from Trigonella foenum-graecum L. (fenugreek) and has been reported before as a potential neuroprotective agent, especially in Alzheimer’s disease (AD). However, the previous data were unclear and used model mice were not well established. In the present study, the effect of trigonelline on memory function was investigated in Alzheimer’s disease transgenic model mouse, 5XFAD which overexpresses the mutated APP and PS1 genes. Oral administration of trigonelline for 14 days significantly enhanced object recognition and object location memories. Plasma and cerebral cortex were isolated at 30 min, 1h, 3h, and 6 h after oral administration of trigonelline. LC-MS/MS analysis indicated that trigonelline was detected in both plasma and cortex from 30 min after, suggesting good penetration of trigonelline into the brain. In addition, trigonelline significantly ameliorated axonal and dendrite atrophy in Amyloid β-treated cortical neurons. These results suggest that trigonelline could be a promising therapeutic candidate for AD.

Keywords: alzheimer’s disease, cortical neurons, LC-MS/MS analysis, trigonelline

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Authors: El Harraj Abdeslam, Raissouni Naoufal

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The detection of moving objects from a video image sequences is very important for object tracking, activity recognition, and behavior understanding in video surveillance. The most used approach for moving objects detection / tracking is background subtraction algorithms. Many approaches have been suggested for background subtraction. But, these are illumination change sensitive and the solutions proposed to bypass this problem are time consuming. In this paper, we propose a robust yet computationally efficient background subtraction approach and, mainly, focus on the ability to detect moving objects on dynamic scenes, for possible applications in complex and restricted access areas monitoring, where moving and motionless persons must be reliably detected. It consists of three main phases, establishing illumination changes in variance, background/foreground modeling and morphological analysis for noise removing. We handle illumination changes using Contrast Limited Histogram Equalization (CLAHE), which limits the intensity of each pixel to user determined maximum. Thus, it mitigates the degradation due to scene illumination changes and improves the visibility of the video signal. Initially, the background and foreground images are extracted from the video sequence. Then, the background and foreground images are separately enhanced by applying CLAHE. In order to form multi-modal backgrounds we model each channel of a pixel as a mixture of K Gaussians (K=5) using Gaussian Mixture Model (GMM). Finally, we post process the resulting binary foreground mask using morphological erosion and dilation transformations to remove possible noise. For experimental test, we used a standard dataset to challenge the efficiency and accuracy of the proposed method on a diverse set of dynamic scenes.

Keywords: video surveillance, background subtraction, contrast limited histogram equalization, illumination invariance, object tracking, object detection, behavior understanding, dynamic scenes

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Authors: Nqobile Muleya, Winston Garira, Godwin Mchau

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Citrus Black Spot (CBS) is a fungal disease that is responsible for huge economical loss and poses a threat to the citrus industry worldwide. We construct a mathematical model framework for citrus black spot between fruits to characterise the dynamics of the disease development, paying attention to the pathogen life cycle. We have made an observation from the model analysis that the initial inoculum from ascomata is very important for disease development and thereafter it is no longer important due to conidia which is responsible for secondary infection. Most importantly, the model indicated that ascospores and conidia are very important parameters in developing citrus black spot within a short distance. The basic reproductive number and its importance in relation to citrus black spot persistence are outlined. A numerical simulation of the model was done to explain the theoretical findings.

Keywords: epidemiological modelling, Guidnardia citricarpa, life cycle stage, fungal, disease development

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Authors: Himanshi Allahabadi

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Plants have found a widespread use in medicine traditionally, including the treatment of cognitive disorders, especially, neurodegenerative diseases such as Alzheimer's disease and Parkinson's disease. In terms of indigenous medicine, it has been found that many potential drugs can be isolated from plant products, including those for dementia. Plant product is widely distributed in plant kingdom and forms a major antioxidant source in the human diet, is Polyphenols. There are four important groups of polyphenols: phenolic acids, flavonoids, stilbenes, and lignans. Due to their high antioxidant capacity, interest in their study has greatly increased. There are several methods for discovering and characterizing active compounds isolated from plant sources, now available. The results obtained so far seem fulfilling, but additionally, mechanism of functioning of polyphenols at the molecular level, as well as their application in human health need to be researched upon. Also, even though the neuroprotective effects of flavonoids have been much talked about, much of the data in support of this statement has come from animal studies rather than human studies. This review is based on a multi-faceted study of medicinal plants, i.e. phytochemicals, with special focus on flavanones and their relevance in remedy of Parkinson's disease.

Keywords: dementia, parkinson's disease, flavanones, polyphenols, substantia nigra

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Authors: Lidia Kowalska, Edward Arseniuk

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Glume and leaf blotch is a disease of wheat caused by necrotrophic fungus Parastagonospora nodorum. It is a serious pathogen in many wheat-growing areas throughout the world. Use of resistant cultivars is the most effective and economical means to control the above-mentioned disease. Plant breeders and pathologists have worked intensively to incorporate resistance to the pathogen in new cultivars. Conventional methods of breeding for resistance can be supported by using the biotechnological ones, i.e., somatic embryogenesis and androgenesis. Therefore, an effort was undertaken to compare genetic variation in P. nodorum resistance among winter wheat somaclones, dihaploids and conventional varieties. For the purpose, a population of 16 somaclonal and 4 dihaploid wheat lines from six crosses were used to assess their resistance to P. nodorum under field conditions. Lines were grown in disease-free (fungicide protected) and inoculated micro plots in 2 replications of a split-plot design in a single environment. The plant leaves were inoculated with a mixture of P. nodorum isolates three times. Spore concentrations were adjusted to 4 x 10⁶ of viable spores per one milliliter. The disease severity was rated on a scale, where > 90% – susceptible, < 10% - resistant. Disease ratings of plant leaves showed statistically significant differences among all lines tested. Higher resistance to P. nodorum was observed more often on leaves of somaclonal lines than on dihaploid ones. On average, disease, severity reached 15% on leaves of somaclones and 30% on leaves of dihaploids. Some of the genotypes were showing low leaf infection, e.g. dihaploid D-33 (disease severity 4%) and a somaclone S-1 (disease severity 2%). The results from this study prove that dihaploid and somaclonal variation might be successfully used as an additional source of wheat resistance to the pathogen and it could be recommended to use in commercial breeding programs. The reported results prove that biotechnological methods may effectively be used in breeding for disease resistance of wheat to fungal necrotrophic pathogens.

Keywords: glume and leaf blotch, somaclonal, androgenic variation, wheat, resistance breeding

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Authors: S. Hallal, Z. Chami, A. Hadji-Lehtihet, S. Sokhal-Boudella, A. Berhoune, L. Yargui

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Gaucher disease is the most common lysosomal storage in our population, it is due to a deficiency of β –glucosidase acid. The enzyme deficiency causes a pathological accumulation of undegraded substrate in lysosomes. This metabolic overload is responsible for a multisystemic disease with hepatosplenomegaly, anemia, thrombocytopenia, and bone involvement. Neurological involvement is rare. The laboratory diagnosis of Gaucher disease consists of phenotypic diagnosis by determining the enzymatic activity of β - glucosidase by fluorimetric method, a study by genotypic diagnosis in the GBA gene, limiting the search recurrent mutations (N370S, L444P, 84 GG); PCR followed by an enzymatic digestion. Abnormal profiles were verified by sequencing. Monitoring of treated patients is provided by the determination of chitotriosidase. Our experience spaning a period of 6 years (2007-2014) has enabled us to diagnose 78 patients out of a total of 328 requests from the various departments of pediatrics, internal medicine, neurology. Genotypic diagnosis focused on the entire family of 9 children treated at pediatric CHU Mustapha, which help define the clinical form; or 5 of them had type III disease, carrying the L444P mutation in the homozygous state. Three others were composite (N370/L444P) (N370S/other unintended mutation in our study), and only in one family no recurrent mutation has been found. This molecular study permits screening of heterozygous essential for genetic counseling.

Keywords: Gaucher disease, mutations, N370S, L444P

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Authors: Mostafa A. Amer, I. A. El-Samra, I. I. Abou-ElSeoud, S. M. El-Abd, N. K. Shawertamimi

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Tomato Fusarium wilt disease caused by Fusarium oxysporum f. sp. Lycopercisi (FOL) is considered one of the most destructive diseases in Egypt. Effect of some biotic inducers such as Bacillus megaterium var. phosphaticum, Glomus intraradices and Glomus macrocarpum at seven different mixed treatments, was tested for their ability to induce resistance in tomato plants against the disease. According to pathogenicity tests, all the tested isolates of FOL showed wilt symptoms on both of the tested cultivars; however, they considerably varied in percentages of disease incidence (DI) and disease severity (DS). Castle Rock was more susceptible than Peto 86, which was relatively resistant. Pretreatment of both cultivars, under greenhouse conditions, with the tested biotic inducers alone or in combination with each other's, significantly increased the induction of chitinase, β-1,3-glucanase, peroxidase, and polyphenoloxidase and reduced disease incidence and severity, compared with untreated noninoculated (C1) and untreated inoculated (C2) controls. Application of a combination of BMP, with GI and GM was the most effective in increasing the induction rated of the tested enzymes, compared with the other treatments. Induction of enzymes in most of the tested bioinducers treatments gradually increased, attaining maximum values after 48 or/and 72 hrs after challenging with FOL, then gradually declined. GI was the least effective bioinducer.

Keywords: F. oxysporum f. sp. lycopersici, defense enzymes, induced systemic resistance, ISR, B. megaterium var. phosphaticum, G. macrocarpum, G. intraradices

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Authors: Osagiede Efosa Kelvin

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The Ebola virus disease (EVD); also Ebola hemorrhagic fever, is a disease of humans and other primates caused by Ebola viruses. Signs and symptoms typically start between two days and three weeks after contracting the virus as a fever, sore throat, muscle pain, and headaches. Then, vomiting, diarrhoea and rash usually follow, along with decreased function of the liver and kidneys. At this time, some people begin to bleed both internally and externally. The first death in Nigeria was reported on 25 July 2014: a Liberian-American with Ebola flew from Liberia to Nigeria and died in Lagos soon after arrival. As part of the effort to contain the disease, possible contacts were monitored –353 in Lagos and 451 in Port Harcourt On 22 September, the World Health Organisation reported a total of 20 cases, including eight deaths. The WHO's representative in Nigeria officially declared Nigeria Ebola-free on 20 October after no new active cases were reported in the follow-up contact. This paper looks at the Ebola Virus in general and the measures taken by Nigeria to combat its spread.

Keywords: Ebola virus, hemorrhagic fever, Nigeria, outbreak

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Authors: Hazel Ann Gianelli Cu, Stephanie Co, Radcliff Cobankiat

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Objectives: TRC101/Veverimer is an orally administered, non absorbed, sodium- and counterion-free hydrochloric acid binder for the treatment of metabolic acidosis associated with chronic kidney disease. The main objective of this study is to determine the efficacy of TRC 101/ Veverimer 6g/day in increasing serum bicarbonate levels of chronic kidney disease patients with metabolic acidosis. In this meta analysis, we also aim to look at safety outcomes, adverse effects and if the level of serum bicarbonate reached metabolic alkalosis when given TRC101/Veverimer. Methodology: Pubmed, Cochrane, Google Scholar and Science direct were used to search for randomized controlled trials about TRC101/Veverimer use in Chronic kidney disease patients with metabolic acidosis. Search strategy according to the Prisma checklist was done with evaluation of biases and synthesis of results using the Cochrane Review Manager software 5.4. Results: Two randomized controlled trials involving 371 chronic kidney disease patients were included in this study. Results show there was a significant increase in the serum bicarbonate level when given TRC101/Veverimer compared to the placebo. Both studies had a significant number of participants who completed the studies until the end. P value of <0.00001 was used in both studies with a confidence interval of 95%. Conclusion: TRC101/Veverimer 6g/day was shown to effectively and safely increase serum bicarbonate or achieve normalization in chronic kidney disease patients with metabolic acidosis as compared with a placebo. This was associated with delayed progression of kidney disease with improvement of physical functioning, however longer duration of future studies is ideal in order to assess further the long advantages and consequences of TRC 101/Veverimer.

Keywords: chronic kidney disease, metabolic acidosis, Veverimer, TRC101

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Authors: G. C. Tikkiwal, Mukesh Upadhyay

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During the surveillance operations at war or peace time, the Radar operator gets a scatter of targets over the screen. This may be a tracked vehicle like tank vis-à-vis T72, BMP etc, or it may be a wheeled vehicle like ALS, TATRA, 2.5Tonne, Shaktiman or moving army, moving convoys etc. The Radar operator selects one of the promising targets into Single Target Tracking (STT) mode. Once the target is locked, the operator gets a typical audible signal into his headphones. With reference to the gained experience and training over the time, the operator then identifies the random target. But this process is cumbersome and is solely dependent on the skills of the operator, thus may lead to misclassification of the object. In this paper we present a technique using mathematical and statistical methods like Fast Fourier Transformation (FFT) and Principal Component Analysis (PCA) to identify the random objects. The process of classification is based on transforming the audible signature of target into music octave-notes. The whole methodology is then automated by developing suitable software. This automation increases the efficiency of identification of the random target by reducing the chances of misclassification. This whole study is based on live data.

Keywords: radar target, fft, principal component analysis, eigenvector, octave-notes, dsp

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Authors: Sintayehu W. Dejene, Ignas M. A. Heitkönig, Herbert H. T. Prins, Zewdu K. Tessema, Willem F. de Boer

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Current theories on diversity-disease relationships describe host species diversity and species identity as important factors influencing disease risk, either diluting or amplifying disease prevalence in a community. Whereas the simple term ‘diversity’ embodies a set of animal community characteristics, it is not clear how different measures of species diversity are correlated with disease risk. We, therefore, tested the effects of species richness, Pielou’s evenness and Shannon’s diversity on bTB risk in cattle in the Afar Region and Awash National Park between November 2013 and April 2015. We also analysed the identity effect of a particular species and the effect of host habitat use overlap on bTB risk. We used the comparative intradermal tuberculin test to assess the number of bTB infected cattle. Our results suggested a dilution effect through species evenness. We found that the identity effect of greater kudu - a maintenance host – confounded the dilution effect of species diversity on bTB risk. bTB infection was positively correlated with habitat use overlap between greater kudu and cattle. Different diversity indices have to be considered together for assessing diversity-disease relationships, for understanding the underlying causal mechanisms. We posit that unpacking diversity metrics is also relevant for formulating control strategies to manage cattle in ecosystems characterized by seasonally limited resources and intense wildlife-livestock interactions.

Keywords: evenness, diversity, greater kudu, identity effect, maintenance hosts, multi-host disease ecology, habitat use overlap

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Authors: Surachart Koyadun

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Introduction: Plasmodium knowlesi (P. knowlesi) malaria is a zoonotic disease that is classified as type 5 of human malaria. Commonly found in macaques (Macaca fascicularis) and (Macaca nemestrina), P. knowlesi is capable of resulting in both uncomplicated and severe malaria in humans. Situation of P. knowlesi malaria in Phang-Nga province for the past 3 years from 2020 – 2022 revealed no case report in 2020, however, a total of 14 cases had been reported in 2021 - 2022. This research aimed to 1) study the epidemiology of P. knowlesi, 2) examine the clinical manifestations of P. knowlesi patients, 3) analyze the ecology and entomology of P. knowlesi, and 4) analyze the diagnosis and treatment of P. knowlesi. Method: This research was a retrospective descriptive study/case report. The study was conducted in 14 patients with P. knowlesi malaria between 2021 and 2022 in 4 districts of Phang-Nga Province, Thailand including Thapput, Kapong, Takuapa and Khuraburi. Results: The study subjects of P. knowlesi malaria were all males. Most of them were working age groups as farmers and worked in forest or plantation areas. All had no history of blood transfusions. Most of the patients did not use mosquito nets and had a history of camping in the forest prior to the onset of fever. An analysis of all 14 sources of infection unveiled the area is home to macaques, and that area has detected Anopheles mosquito, which is the carrier of the disease. Majority of them got sick in the dry season of Thailand (December-April). The main symptoms brought to the hospital were fever, chills, headache, body aches. Laboratory findings on the first day of diagnosis were as follows: The white blood cell count was found within the normal range. In the proportion of white blood cells, eosinophils were found to be slightly higher than normal. Slight anemia was found on early examination. The platelet count was found to be below normal in all cases. Severely low platelet count (2,000 cells/mm3) was found in severe cases with multiple complications. No patient was found dead but 85.7% of complications were found, with acute renal failure being the most common. Patients with delayed diagnosis and treatment of malaria (inaccurate diagnosis or late access to the hospital) had the highest severity and complications than those who had seen the doctor since the first 3-4 days of illness or the screening of symptoms and risk history by the malaria clinic staff at vector-borne disease control unit. Conclusion and Recommendation: P. knowlesi malaria is an emerging infectious disease transmitted from animals to humans. There are challenges in epidemiology, entomology, ecology for effective surveillance, prevention and control. Early diagnosis and treatment would reduce complications and prevent death.

Keywords: malaria, plasmodium knowlesi, epidemiology, ecology, entomology, diagnosis, treatment

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Authors: Vivek Mahadev, Manoj Kumar, Neelu Mathur, Brahm Dutt Pandey

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Perimeter guarding and protection of critical installations require prompt intrusion detection and assessment to take effective countermeasures. Currently, visual and electronic surveillance are the primary methods used for perimeter guarding. These methods can be costly and complicated, requiring careful planning according to the location and terrain. Moreover, these methods often struggle to detect stealthy and camouflaged insurgents. The object of the present work is to devise a surveillance technique using seismic sensors that overcomes the limitations of existing systems. The aim is to improve intrusion detection, assessment, and characterization by utilizing seismic sensors. Most of the similar systems have only two types of intrusion detection capability viz., human or vehicle. In our work we could even categorize further to identify types of intrusion activity such as walking, running, group walking, fence jumping, tunnel digging and vehicular movements. A virtual fence of 60 meters at GCNEP, Bahadurgarh, Haryana, India, was created by installing four underground geophones at a distance of 15 meters each. The signals received from these geophones are then processed to find unique seismic signatures called features. Various feature optimization and selection methodologies, such as LightGBM, Boruta, Random Forest, Logistics, Recursive Feature Elimination, Chi-2 and Pearson Ratio were used to identify the best features for training the machine learning models. The trained models were developed using algorithms such as supervised support vector machine (SVM) classifier, kNN, Decision Tree, Logistic Regression, Naïve Bayes, and Artificial Neural Networks. These models were then used to predict the category of events, employing weighted ensemble voting to analyze and combine their results. The models were trained with 1940 training events and results were evaluated with 831 test events. It was observed that using the weighted ensemble voting increased the efficiency of predictions. In this study we successfully developed and deployed the virtual fence using geophones. Since these sensors are passive, do not radiate any energy and are installed underground, it is impossible for intruders to locate and nullify them. Their flexibility, quick and easy installation, low costs, hidden deployment and unattended surveillance make such systems especially suitable for critical installations and remote facilities with difficult terrain. This work demonstrates the potential of utilizing seismic sensors for creating better perimeter guarding and protection systems using multiple machine learning models in weighted ensemble voting. In this study the virtual fence achieved an intruder detection efficiency of over 97%.

Keywords: geophone, seismic perimeter surveillance, machine learning, weighted ensemble method

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Authors: Oluwaponmile David Alao

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Due to an increase in the death rate as a result of heart attack. There is need to develop a system that can be useful in the diagnosis of the disease at the medical centre. This system will help in preventing misdiagnosis that may occur from the medical practitioner or the physicians. In this research work, heart disease dataset obtained from UCI repository has been used to develop an intelligent prediction diagnosis system. The system is modeled on a feedforwad neural network and trained with back propagation neural network. A recognition rate of 86% is obtained from the testing of the network.

Keywords: heart disease, artificial neural network, diagnosis, prediction system

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Authors: Manish Subedi, Bijay Bartaula, Ashok R. Pant, Purbesh Adhikari, Sanjib K. Sharma

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Background: The pattern of glomerular disease varies worldwide. In absence of kidney disease/Kidney biopsy registry in Nepal, the exact etiology of different forms of glomerular disease is primarily unknown in our country. Method: We retrospectively analyzed 175 cases of renal biopsies performed from dated September 2014 to August 2016 at B. P. Koirala Institute of Health Sciences, Dharan, Nepal. Results: The commonest indication for renal biopsy was nephrotic syndrome (34.9%), followed by Systemic lupus erythematosus with suspected renal involvement (22.3%). Majority of patients were in the 30-60 year bracket (57.2%), with the mean age of the patients being 35.37 years. The average number of glomeruli per core was 13, with inadequate sampling in 5.1%. IgA nephropathy (17%) was found to be the most common primary glomerular disease, followed by membranous nephropathy (14.6%) and FSGS (14.6%). The commonest secondary glomerular disease was lupus nephritis. Complications associated with renal biopsy were pain at biopsy site in 18% of cases, hematuria in 6% and perinephric hematoma in 4% cases. Conclusion: The commonest primary and secondary glomerular disease was IgA nephropathy and lupus nephritis respectively. The high prevalence of Systemic lupus erythematosus with lupus nephritis among Nepalese in comparison with other developing countries warrants further evaluation. As an initial attempt towards documentation of glomerular diseases in the national context, this study should serve as a stepping stone towards the eventual establishment of a full-fledged national registry of glomerular diseases in Nepal.

Keywords: glomerular, Nepal, renal biopsy, systemic lupus erythematoses

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Authors: Robert Miller, Fred Soltero, Sandra Allan, Denise Bonilla

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The Tropical Bont Tick (TBT), Amblyomma variegatum, was introduced to the Caribbean in the mid-1700s. Since it has spread throughout the Caribbean dispersed by cattle egrets (Bubulcus ibis). Tropical Bont Ticks vector many pathogens to livestock and humans. However, only the livestock diseases heartwater, Ehrlichia (Cowdria) ruminantium, and dermatophilosis, Dermatophilus congolensis, are associated with TBT in the Caribbean. African tick bite fever (Rickettsia africae) is widespread in Caribbean TBT but human cases are rare. The Caribbean Amblyomma Programme (CAP) was an effort led by the Food and Agricultural Organization to eradicate TBTs from participating islands. This 10-year effort successfully eradicated TBT from many islands. However, most are reinfested since its termination. Pheromone technology has been developed to aid in TBT control. Although not part of the CAP treatment scheme, this research established that pheromones in combination with pesticide greatly improves treatment efficiencies. Additionally, pheromone combined with CO₂ traps greatly improves active surveillance success. St. Croix has a history of TBT outbreaks. Passive surveillance detected outbreaks in 2016 and in May of 2021. Surveillance efforts are underway to determine the extent of TBT on St Croix. Puerto Rico is the next island in the archipelago and is at a greater risk of re-infestation due to active outbreaks in St Croix. Tropical Bont Ticks were last detected in Puerto Rico in the 1980s. The infestation started on the small Puerto Rican island of Vieques, the closest landmass to St Croix, and spread to the main island through cattle movements. This infestation was eradicated with the help of the Tropical Cattle Tick (TCT), Rhipicephalus (Boophilus) microplus, eradication program. At the time, large percentages of Puerto Rican cattle were treated for ticks along with the necessary material and manpower mobilized for the effort. Therefore, a shift of focus from the TCT to TBT prevented its establishment in Puerto Rico. Currently, no large-scale treatment of TCTs occurs in Puerto Rico. Therefore, the risk of TBT establishment is now greater than it was in the 1980s. From Puerto Rico, the risk of TBT movement to the American continent increases significantly. The establishment of TBTs in the Americas would cause $1.2 billion USD in losses to the livestock industry per year. The USDA Agricultural Research Service recently worked with the USDA Animal Health Inspection Service and the Puerto Rican Department of Agriculture to modernize the management of the TCT. This modernized program uses safer pesticides and has successfully been used to eradicate pesticide-susceptible and -resistant ticks throughout the island. The objective of this work is to prevent the infestation of Puerto Rico by TBTs by combining the current TCT management efforts with TBT surveillance in Vieques. The combined effort is designed to eradicate TCT from Vieques while using the treated cattle as trap animals for TBT using pheromone impregnated tail tags attached to treated animals. Additionally, active surveillance using CO₂-baited traps combined with pheromone will be used to actively survey the environment for free-living TBT. Knowledge gained will inform TBT control efforts in St. Croix.

Keywords: Amblyomma variegatum, caribbean, eradication, Rhipicephalus (boophilus) microplus, pheromone

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Authors: Muhtasim Shafi Kader, Fizar Ahmed, Annesha Acharjee

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Machine learning and data mining are crucial in health care, as well as medical information and detection. Machine learning approaches are now being utilized to improve awareness of a variety of critical health issues, including diabetes detection, neuron cell tumor diagnosis, COVID 19 identification, and so on. Parkinson’s disease is basically a disease for our senior citizens in Bangladesh. Parkinson's Disease indications often seem progressive and get worst with time. People got affected trouble walking and communicating with the condition advances. Patients can also have psychological and social vagaries, nap problems, hopelessness, reminiscence loss, and weariness. Parkinson's disease can happen in both men and women. Though men are affected by the illness at a proportion that is around partial of them are women. In this research, we have to get out the accurate ML algorithm to find out the disease with a predictable dataset and the model of the following machine learning classifiers. Therefore, nine ML classifiers are secondhand to portion study to use machine learning approaches like as follows, Naive Bayes, Adaptive Boosting, Bagging Classifier, Decision Tree Classifier, Random Forest classifier, XBG Classifier, K Nearest Neighbor Classifier, Support Vector Machine Classifier, and Gradient Boosting Classifier are used.

Keywords: naive bayes, adaptive boosting, bagging classifier, decision tree classifier, random forest classifier, XBG classifier, k nearest neighbor classifier, support vector classifier, gradient boosting classifier

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Authors: R. Harihara Prakash, Shweta R. Parikh, Sangna S. Sheth

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The purpose of this study was to explore the usefulness of the Mini-BESTest compared to the Berg Balance Scale in evaluating balance in people with Parkinson's Disease (PD) of varying severity. Evaluation were done to obtain (1) the distribution of patients scores to look for ceiling effects, (2) concurrent validity with severity of disease, and (3) the sensitivity & specificity of separating people with or without postural response deficits. Methods and Material: Seventy-seven(77) people with Parkinson's Disease were tested for balance deficits using the Berg Balance Scale, Mini-BESTest. Unified Parkinson’s Disease Rating Scale (UPDRS) III and the Hoehn & Yahr (H&Y) disease severity scales were used for classification. Materials used in this study were case record sheet, chair without arm rests or wheels, Incline ramp, stopwatch, a box, 3 meter distance measured out and marked on the floor with tape [from chair]. Statistical analysis used: Multiple Linear regression was carried out of UPDRS jointly on the two scores for the Berg and Mini-BESTest. Receiver operating characteristic curves for classifying people into two groups based on a threshold for the H&Y score, to discriminate between mild PD versus more severe PD.Correlation co-efficient to find relativeness between the two variables. Results: The Mini-BESTest is highly correlated with the Berg (r = 0.732,P < 0.001), but avoids the ceiling compression effect of the Berg for mild PD (skewness −0.714 Berg, −0.512 Mini-BESTest). Consequently, the Mini-BESTest is more effective than the Berg for predicting UPDRS Motor score (P < 0.001 Mini-BESTest versus P = 0.72 Berg), and for discriminating between those with and without postural response deficits as measured by the H&Y (ROC).

Keywords: balance, berg balance scale, MINI BESTest, parkinson's disease

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Authors: Nirupama Dixit, Anyaa Mittal, Neeru Sood

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Alzheimer’s disease (AD) is a progressive form of dementia, contributing to up to 70% of cases, mostly observed in elderly but is not restricted to old age. The pathophysiology of the disease is characterized by specific pathological changes in brain. The changes (i.e. accumulation of metal ions in brain, formation of extracellular β-amyloid (Aβ) peptide aggregates and tangle of hyper phosphorylated Tau protein inside neurons) damage the neuronal connections irreversibly. The current issues in improvement of life quality of Alzheimer's patient lies in the fact that the diagnosis is made at a late stage of the disease and the medications do not treat the basic causes of Alzheimer's. The targeted delivery of drug through the blood brain barrier (BBB) poses several limitations via traditional approaches for treatment. To overcome these drug delivery limitation, nanoparticles provide a promising solution. This review focuses on current strategies for efficient targeted drug delivery using nanoparticles and improving the quality of therapy provided to the patient. Nanoparticles can be used to encapsulate drug (which is generally hydrophobic) to ensure its passage to brain; they can be conjugated to metal ion chelators to reduce the metal load in neural tissue thus lowering the harmful effects of oxidative damage; can be conjugated with drug and monoclonal antibodies against BBB endogenous receptors. Finally this review covers how the nanoparticles can play a role in diagnosing the disease.

Keywords: Alzheimer's disease, β-amyloid plaques, blood brain barrier, metal chelators, nanoparticles

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Authors: Somorjeet Sharma Shamurailatpam, Rabindra Das, A. Suchitra Devi

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Computer and video display users might complain about Asthenopia, burning, dry eyes etc. The management of dry eyes is often not in the lines of severity. Following systematic evaluation and grading, dry eye disease is one condition that can be practiced at all levels of ophthalmic care. In the present study, different spectrum causing dry eye and prevalence of dry eye disease in computer users of Manipur, India are determined with 600 individuals (300 cases and 300 control). Individuals between 15 and 50 years who used computers for more than 3 hrs a day for 1 year or more were included. Tear break up time (TBUT) and Schirmer’s test were conducted. It shows that 33 (20.4%) out of 164 males and 47 (30.3%) out of 136 females have dry eye. Possible explanation for the observed result is discussed.

Keywords: asthenopia, computer vision syndrome, dry eyes, Schirmer's test, TBUT

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Authors: Rafael Marinho de Andrade, Elcio Hideti Shiguemori, Rafael Duarte Coelho dos Santos

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Relying on computer vision, many clever things are possible in order to make the world safer and optimized on resource management, especially considering time and attention as manageable resources, once the modern world is very abundant in cameras from inside our pockets to above our heads while crossing the streets. Thus, automated solutions based on computer vision techniques to detect, react, or even prevent relevant events such as robbery, car crashes and traffic jams can be accomplished and implemented for the sake of both logistical and surveillance improvements. In this paper, we present an approach for vehicles’ abnormal behaviors detection from highway footages, in which the vectorial data of the vehicles’ displacement are extracted directly from surveillance cameras footage through object detection and tracking with a deep convolutional neural network and inserted into a long-short term memory neural network for behavior classification. The results show that the classifications of behaviors are consistent and the same principles may be applied to other trackable objects and scenarios as well.

Keywords: artificial intelligence, behavior detection, computer vision, convolutional neural networks, LSTM, highway footage

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Authors: Retno A. Vinarti, Lucy M. Hederman

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This research describes a knowledge model for a system which give personalized alert to users about infectious disease risks in the context of weather, location and time. The knowledge model is based on established epidemiological concepts augmented by information gleaned from infection-related data repositories. The existing disease risk prediction research has more focuses on utilizing raw historical data and yield seasonal patterns of infectious disease risk emergence. This research incorporates both data and epidemiological concepts gathered from Atlas of Human Infectious Disease (AHID) and Centre of Disease Control (CDC) as basic reasoning of infectious disease risk prediction. Using CommonKADS methodology, the disease risk prediction task is an assignment synthetic task, starting from knowledge identification through specification, refinement to implementation. First, knowledge is gathered from AHID primarily from the epidemiology and risk group chapters for each infectious disease. The result of this stage is five major elements (Person, Infectious Disease, Weather, Location and Time) and their properties. At the knowledge specification stage, the initial tree model of each element and detailed relationships are produced. This research also includes a validation step as part of knowledge refinement: on the basis that the best model is formed using the most common features, Frequency-based Selection (FBS) is applied. The portion of the Infectious Disease risk model relating to Person comes out strongest, with Location next, and Weather weaker. For Person attribute, Age is the strongest, Activity and Habits are moderate, and Blood type is weakest. At the Location attribute, General category (e.g. continents, region, country, and island) results much stronger than Specific category (i.e. terrain feature). For Weather attribute, Less Precise category (i.e. season) comes out stronger than Precise category (i.e. exact temperature or humidity interval). However, given that some infectious diseases are significantly more serious than others, a frequency based metric may not be appropriate. Future work will incorporate epidemiological measurements of disease seriousness (e.g. odds ratio, hazard ratio and fatality rate) into the validation metrics. This research is limited to modelling existing knowledge about epidemiology and chain of infection concepts. Further step, verification in knowledge refinement stage, might cause some minor changes on the shape of tree.

Keywords: epidemiology, knowledge modelling, infectious disease, prediction, risk

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Authors: Mukurdipi Ray, Seema Singh

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Extrauterine endometrial stromal sarcoma (ESS) is a rare entity and typified by delayed recurrence of primary ESS. Here, we present an unusual case of uterine ESS in a woman with a history of hysterectomy. A 19-year-old girl, underwent a hysterectomy and bilateral salpingo-oophorectomy for uterine ESS 12 months ago and now after remaining disease free for nine months ago she presented with ascites along with pelvic and peritoneal mass. Intraoperatively, the large omental mass was found, and optimal cytoreduction with total omentomy (supracolic and infracolic ) total peritonectomy and hyperthermic intraperitoneal chemotherapy (HIPEC) was offered to the patient. Final histopathology report showed the involvement of only omentum by ESS cells. Immunohistochemistry (IHC) and receptor study were done and it was positive for CD-10 and desmin and negative for CK- 7. This case highlights the rarity of extrauterine ESS in the omentum with a known history of primary uterine ESS which was treated successfully with the above-mentioned procedure. Though active and long-term surveillance is recommended to monitor for late recurrences.

Keywords: endrometrial stromal sarcoma, complete cytoreduction, hyperthermic intra peritoneal chemotherapy, total omentectomy

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Authors: Fatemeh Keshavarz

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Background: Rheumatoid arthritis (RA) is one of the most common autoimmune diseases, often leading to joint damage and physical disability. This study aimed to investigate the relationship of serum levels of interleukin 17 and anti-CCP factor with disease severity in RA patients. Materials and Methods: Fifty-four patients with RA confirmed by clinical and laboratory criteria were recruited. A 5 ml venous blood sample was taken from every patient, its serum was separated. Based on clinical data and severity of symptoms, patients were classified into three groups of those with mild, moderate, and severe symptoms. Serum levels of IL-17 and anti-CCP in all samples were measured using ELISA. Results: Analysis of IL-17 serum levels in different groups showed that its amount was higher in the group with mild clinical symptoms than in other groups. Comparison of IL-17 serum levels between mild and moderate disease severity groups showed a statistically significant relationship. There was also a positive linear relationship between anti-CCP and serum IL-17 levels in different groups of the disease, and serum IL-17 levels were inversely related to the duration of exposure to the disease. Conclusion: Higher IL-17 serum levels in patients with mild symptom severity confirm that this highly specific marker is involved in the pathogenesis of RA and may be effective in initiating patients’ clinical symptoms.

Keywords: IL-17, anti-CCP, rheumatoid arthritis, autoimmune

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Authors: Nicole Ramlachan, Samuel Mark West

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Lung cancer is the leading cause of cancer-associated deaths in North America, with the vast majority being non-small cell lung cancer (NSCLC), with a five-year survival rate of only 24%. Non-invasive discovery of biomarkers associated with early-diagnosis of NSCLC can enable precision oncology efforts using liquid biopsy-based multiomics profiling of plasma. Although tissue biopsies are currently the gold standard for tumor profiling, this method presents many limitations since these are invasive, risky, and sometimes hard to obtain as well as only giving a limited tumor profile. Blood-based tests provides a less-invasive, more robust approach to interrogate both tumor- and non-tumor-derived signals. We intend to examine 30 stage III-IV NSCLC patients pre-surgery and collect plasma samples.Cell-free DNA (cfDNA) will be extracted from plasma, and next-generation sequencing (NGS) performed. Through the analysis of tumor-specific alterations, including single nucleotide variants (SNVs), insertions, deletions, copy number variations (CNVs), and methylation alterations, we intend to identify tumor-derived DNA—ctDNA among the total pool of cfDNA. This would generate data to be used as an accurate form of cancer genotyping for diagnostic purposes. Using liquid biopsies offer opportunities to improve the surveillance of cancer patients during treatment and would supplement current diagnosis and tumor profiling strategies previously not readily available in Trinidad and Tobago. It would be useful and advantageous to use this in diagnosis and tumour profiling as well as to monitor cancer patients, providing early information regarding disease evolution and treatment efficacy, and reorient treatment strategies in, timethereby improving clinical oncology outcomes.

Keywords: genomics, multiomics, clinical genetics, genotyping, oncology, diagnostics

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Authors: Teja Koduru

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Untreated Lyme disease can lead to neurological, cardiac, and dermatological complications. Rapid diagnosis of the erythema migrans (EM) rash, a characteristic symptom of Lyme disease is therefore crucial to early diagnosis and treatment. In this study, we aim to utilize deep learning frameworks including Tensorflow and Keras to create deep convolutional neural networks (DCNN) to detect images of acute Lyme Disease from images of erythema migrans. This study uses a custom database of erythema migrans images of varying quality to train a DCNN capable of classifying images of EM rashes vs. non-EM rashes. Images from publicly available sources were mined to create an initial database. Machine-based removal of duplicate images was then performed, followed by a thorough examination of all images by a clinician. The resulting database was combined with images of confounding rashes and regular skin, resulting in a total of 683 images. This database was then used to create a DCNN with an accuracy of 93% when classifying images of rashes as EM vs. non EM. Finally, this model was converted into a web and mobile application to allow for rapid diagnosis of EM rashes by both patients and clinicians. This tool could be used for patient prescreening prior to treatment and lead to a lower mortality rate from Lyme disease.

Keywords: Lyme, untreated Lyme, erythema migrans rash, EM rash

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Authors: Zahra Rakhshan Masoudi, Sona Rostampour Yasouri

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Considering that the only way to save the lives of patients and healthy people who have suffered sudden accidents is blood transfusion, what is important is the presence of the known HCV virus as the most important cause of the disease after blood transfusion. HCV is one of the major global problems, and its transmission through blood causes life-threatening complications and extensive legal, social and economic consequences. On the one hand, unfortunately, there is still no effective vaccine available to prevent HCV. In Iran, the exact statistics of the prevalence of this disease have not yet been fully announced. The main purpose of this study is to investigate the prevalence rate and rapid diagnosis of HCV among those who refer to laboratory centers in Tehran. From spring to winter of 1401 (2022-2023), 2166 blood samples were collected from laboratory centers in Tehran. Blood samples were evaluated for the presence of HCV by Electrochemiluminescence (ECL) and PCR techniques along with specific HCV primers. In general, 36 samples (1.6%) were tested positive by the mentioned techniques. The results indicated that the ECL technique is a sensitive and specific diagnostic method for detecting HCV in the early stages of the disease and can be very helpful and provide the possibility of starting the treatment steps to prevent the exacerbation of the disease earlier. Also, the results of PCR technique showed that PCR is an accurate, sensitive and fast method for definitive diagnosis of HCV. It seems that the incidence rate of this disease is increasing in Iran, and investigating the spread of the disease throughout Iran for a longer period of time in the continuation of our research can be helpful in the future to take the necessary measures to prevent the transmission of the disease to people and the rapid onset Treatment steps for patients with HCV should be carried out.

Keywords: electrochemiluminescence, HCV, PCR, prevalence

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