Search results for: plant disease identification

Authors: Zuliani Mahmood, Thirumulu Ponnuraj Kannan, Yean Yean Chan, Salahddin A. Al-Hudhairy

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Caries is the most common childhood disease which develops due to disturbances in the physiological equilibrium in the dental plaque resulting in demineralization of tooth structures. Plaque and dentine samples were collected from three different tooth surfaces representing caries progression (intact, over carious lesion and dentine) in children with early childhood caries (ECC, n=36). In caries free (CF) children, plaque samples were collected from sound tooth surfaces at baseline and after one year (n=12). The genomic DNA was extracted from all samples and subjected to 16S rRNA PCR amplification. The end products were cloned into pCR®2.1-TOPO® Vector. Five randomly selected positive clones collected from each surface were sent for sequencing. Identification of the bacterial clones was performed using BLAST against GenBank database. In the ECC group, the frequency of Lactobacillus sp. detected was significantly higher in the dentine surface (p = 0.031) than over the cavitated lesion. The highest frequency of bacteria detected in the intact surfaces was Fusobacterium nucleatum subsp. polymorphum (33.3%) while Streptococcus mutans was detected over the carious lesions and dentine surfaces at a frequency of 33.3% and 52.7% respectively. Fusobacterium nucleatum subsp. polymorphum was also found to be highest in the CF group (41.6%). Follow up at the end of one year showed that the frequency of Corynebacterium matruchotii detected was highest in those who remained caries free (16.6%), while Porphyromonas catoniae was highest in those who developed caries (25%). In conclusion, Streptococcus mutans and Porphyromonas catoniae are strongly associated with caries progression, while Lactobacillus sp. is restricted to deep carious lesions. Fusobacterium nucleatum subsp. polymorphum and Corynebacterium matruchotii may play a role in sustaining the healthy equilibrium in the dental plaque. These identified bacteria show promise as potential biomarkers in diagnosis which could help in the management of dental caries in children.

Keywords: early childhood caries, genotypic identification, oral bacteria, 16S rRNA

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Authors: P. S. Jagadeesh Kumar, Mingmin Pan, Xianpei Li, Yanmin Yuan, Tracy Lin Huan

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Researchers are doing enchanting research into the inherited features of Alzheimer’s disease and probable consistent therapies. In Alzheimer’s, memories are extinct in reverse order; memories formed lately are more transitory than those from formerly. Reminiscence therapy includes the conversation of past actions, trials and knowledges with another individual or set of people, frequently with the help of perceptible reminders such as photos, household and other acquainted matters from the past, music and collection of tapes. In this manuscript, the competence of reminiscence therapy for Alzheimer’s disease is measured using logistic regression based linear bootstrap aggregating. Logistic regression is used to envisage the experiential features of the patient’s memory through various therapies. Linear bootstrap aggregating shows better stability and accuracy of reminiscence therapy used in statistical classification and regression of memories related to validation therapy, supportive psychotherapy, sensory integration and simulated presence therapy.

Keywords: Alzheimer’s disease, linear bootstrap aggregating, logistic regression, reminiscence therapy

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Authors: Chih Hung Shih

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Eyewitness identification is one of the efficient information to identify suspects during criminal investigation. However eyewitness identification is improved frequently, inaccurate and plays vital roles in wrongful convictions. Most eyewitness misidentifications are made during police criminal investigation stage and then accepted by juries. Four failure investigation case studies in Taiwan are conduct to demonstrate how misidentifications are caused during the police investigation context. The result shows that there are several common grounds among these cases: (1) investigators lacked for knowledge about eyewitness memory so that they couldn’t evaluate the validity of the eyewitnesses’ accounts and identifications, (2) eyewitnesses were always asked to filter out several suspects during the investigation, and received investigation information which contaminated the eyewitnesses’ memory, (3) one to one live individual identifications were made in most of cases, (4) eyewitness identifications were always used to support the hypotheses of investigators, and exaggerated theirs powers when conform with the investigation lines, (5) the eyewitnesses’ confidence didn’t t reflect the validity of their identifications , but always influence the investigators’ beliefs for the identifications, (6) the investigators overestimated the power of the eyewitness identifications and ignore the inconsistency with other evidence. Recommendations have been proposed for future academic research and police practice of eyewitness identification in Taiwan.

Keywords: criminal investigation, eyewitness identification, investigative bias, investigative failures

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Authors: Bandana Saikia, Ashok Bhattacharyya

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Endophytic microbes and their metabolites positively impact overall plant health, which may have a potential implication in agriculture. In the present study, 177 bacterial endophytes and 57 fungal endophytes were isolated, with the highest recovery rate from tomato roots. A maximum of 112 endophytes were isolated during monsoon, followed by 64 isolates and 58 isolates isolated during pre-monsoon and post-monsoon periods, respectively, indicating the rich diversity in bacterial and fungal endophytes of tomato crops from different locations of Assam, India. Further, the endophytes were evaluated for their antagonistic potential against Fusarium oxysporum f. sp. lycopersici. Fungal endophytic isolate AAUTLF (Endophytic Fungi of Tomato Leaf from Assam Agricultural University, Assam, India area) and bacterial endophyte D1B (Endophytic bacteria of tomato from Dhemiji, India district) showed the highest antifungal activity against the pathogen both in vitro and in vivo. Based on 5.8 rDNA sequence analysis of fungal and 16S rDNA sequence of bacteria endophytes, the most effective fungal and bacterial isolates against FOL were identified as Trichoderma asperellum AAUTLF and Stenotrophomonas maltophilia D1B, respectively. The isolates showed an antagonistic effect against Fusarium oxysporum f.sp. lycopersici in-vitro and reduced the disease index of Fusarium wilt in tomatoes by 64.4% under pot conditions. Trichoderma asperellum AAUTLF produced an antifungal compound viz., 6-pentyl-2H-pyran-2-one, which also possesses growth-promoting characteristics. The bacteria Stenotrophomonas maltophilia D1B produced antifungal compounds, including benzothiazole, oleic acid, phenylacetic acid, and 3-(Hydroxy-phenyl-methyl)-2,3-dimethyl-octan-4-one. This would be of high importance for the source of antagonistic strains and biocontrol of tomato Fusarium wilt, as well as other plant fungal diseases.

Keywords: root endophytes, Stemotrophomonas, Trichoderma, benzothiazole, 6-pentyl-2H-pyran-2-one

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Authors: Fidel Lòpez Saca, Carlos Avilés-Cruz, Miguel Magos-Rivera, José Antonio Lara-Chávez

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Automated object recognition and identification systems are widely used throughout the world, particularly in assembly lines, where they perform quality control and automatic part selection tasks. This article presents the design and implementation of an object recognition system in an assembly line. The proposed shapes-color recognition system is based on deep learning theory in a specially designed convolutional network architecture. The used methodology involve stages such as: image capturing, color filtering, location of object mass centers, horizontal and vertical object boundaries, and object clipping. Once the objects are cut out, they are sent to a convolutional neural network, which automatically identifies the type of figure. The identification system works in real-time. The implementation was done on a Raspberry Pi 3 system and on a Jetson-Nano device. The proposal is used in an assembly course of bachelor’s degree in industrial engineering. The results presented include studying the efficiency of the recognition and processing time.

Keywords: deep-learning, image classification, image identification, industrial engineering.

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Authors: Jay L. Fu

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Patients with Alzheimer's disease progressively lose their memory and thinking skills and, eventually, the ability to carry out simple daily tasks. The disease is irreversible, but early detection and treatment can slow down the disease progression. In this research, publicly available MRI data and demographic data from 373 MRI imaging sessions were utilized to build models to predict dementia. Various machine learning models, including logistic regression, k-nearest neighbor, support vector machine, random forest, and neural network, were developed. Data were divided into training and testing sets, where training sets were used to build the predictive model, and testing sets were used to assess the accuracy of prediction. Key risk factors were identified, and various models were compared to come forward with the best prediction model. Among these models, the random forest model appeared to be the best model with an accuracy of 90.34%. MMSE, nWBV, and gender were the three most important contributing factors to the detection of Alzheimer’s. Among all the models used, the percent in which at least 4 of the 5 models shared the same diagnosis for a testing input was 90.42%. These machine learning models allow early detection of Alzheimer’s with good accuracy, which ultimately leads to early treatment of these patients.

Keywords: Alzheimer's disease, clinical diagnosis, magnetic resonance imaging, machine learning prediction

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Authors: A. Majidian

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The life prediction of thermal power plant components is necessary to prevent the unexpected outages, optimize maintenance tasks in periodic overhauls and plan inspection tasks with their schedules. One of the main critical components in a power plant is condenser because its failure can affect many other components which are positioned in downstream of condenser. This paper deals with factors affecting life of condenser. Failure rates dependency vs. these factors has been investigated using Artificial Neural Network (ANN) and fuzzy logic algorithms. These algorithms have shown their capabilities as dynamic tools to evaluate life prediction of power plant equipments.

Keywords: life prediction, condenser tube, neural network, fuzzy logic

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Authors: Dona Pamoda W. Jayatunga, Veer Bala Gupta, Eugene Hone, Ralph N. Martins

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Being a neurodegenerative disorder, Alzheimer’s disease (AD) affects a majority of the elderly demented worldwide. The key risk factors for AD are age, metabolic syndrome, allele status of APOE gene, head injuries and lifestyle. The progressive nature of AD is characterized by symptoms of multiple cognitive deficits exacerbated over time, leading to death within a decade from clinical diagnosis. However, it is revealed that AD originates via a prodromal phase that spans from one to few decades before symptoms first manifest. The key pathological hallmarks of AD brains are deposition of amyloid beta (Aβ) plaques and neurofibrillary tangles (NFT). However, the yet unknown etiology of the disease fails to distinguish mitochondrial dysfunction between a cause or an outcome. The absence of early diagnosis tools and definite therapies for AD have permitted recruits of nutraceutical-based approaches aimed at reducing the risk of AD by modulating lifestyle or be used as preventive tools during AD prodromal state before widespread neurodegeneration begins. The objective of the present study was to investigate beneficial effects of luteolin, a plant-based flavone compound, against AD. The neuroprotective effects of luteolin on amyloid beta (Aβ) (1-42)-induced neurotoxicity was measured using cultured human neuroblastoma BE(2)-M17 cells. After exposure to 20μM Aβ (1-42) for 48 h, the neuroblastoma cells exhibited marked apoptotic death. Co-treatment of 20μM Aβ (1-42) with luteolin (0.5-5μM) significantly protected the cells against Aβ (1-42)-induced toxicity, as assessed by the MTS [3-(4,5-dimethylthiazol-2-yl)-5-(3-carboxymethoxyphenyl)-2(4sulfophenyl)-2H-tetrazolium, inner salt; MTS] reduction assay and the lactate dehydrogenase (LDH) cell death assay. The results suggest that luteolin prevents Aβ (1-42)-induced apoptotic neuronal death. However, further studies are underway to determine its protective mechanisms in AD including the activity against tau hyperphosphorylation and mitochondrial dysfunction.

Keywords: Aβ (1-42)-induced toxicity, Alzheimer’s disease, luteolin, neuroblastoma cells

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Authors: Mualla McManus, Jenna Luche Thaye

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World Health Organisation International Classification of Disease codes were created to define disease including infections in order to guide and educate diagnosticians. Most infectious diseases such as syphilis are clearly defined by their ICD 10 codes and aid/help to educate the clinicians in syphilis diagnosis and treatment globally. However, current ICD 10 codes for relapsing fever Borreliosis and Lyme disease are less clearly defined and can impede appropriate diagnosis especially if the clinician is not familiar with the symptoms of these infectious diseases. This is despite substantial number of scientific articles published in peer-reviewed journals about relapsing fever and Lyme disease. In the USA there are estimated 380,000 people annually contacting Lyme disease, more cases than breast cancer and 6x HIV/AIDS cases. This represents estimated 0.09% of the USA population. If extrapolated to the global population (7billion), 0.09% equates to 63 million people contracting relapsing fever or Lyme disease. In many regions, the rate of contracting some form of infection from tick bite may be even higher. Without accurate and appropriate diagnostic codes, physicians are impeded in their ability to properly care for their patients, leaving those patients invisible and marginalized within the medical system and to those guiding public policy. This results in great personal hardship, pain, disability, and expense. This unnecessarily burdens health care systems, governments, families, and society as a whole. With accurate diagnostic codes in place, robust data can guide medical and public health research, health policy, track mortality and save health care dollars. Better defined ICD codes are the way forward in educating the diagnosticians about relapsing fever and Lyme diseases.

Keywords: WHO ICD codes, relapsing fever, Lyme diseases, World Health Organisation

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Authors: Akmal E. Egamberdiev, Alim M. Nigmatullaev, Trobjon Kh. Makhkamov

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The results of scientific research on the biomorphological features of Ajuga turkestanica (Regel) Brig., its role in plant communities, modern distribution areas, and raw material reserves are presented. Plant ontogeny is divided into 3 periods and 9 growth stages. Information on its seasonal and diurnal flowering and seed productivity is provided. As a result of the research, the participation of the studied species in plant communities, its place, the structure and floristic composition of communities were determined, and as a result, for the first time, the description of 11 new associations in 7 formations of Ajuga turkestanica, and a schematic map of the geolocation of formations and associations of plants in Uzbekistan is given. A. turkestanica (within the range) are divided into 3 categories and 21 massifs. Its current biological reserve is 93.5±35.3 tons, its usable reserve is 46.2±13.8 tons, and the reserve that can be prepared in 1 year is 28.4±5.42 tons.

Keywords: ontogeny, seed productivity, seasonal flowering, formation, association, dominant, subdominant, areal, biological reserve, operational reserve, annual reserve, GIS map

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Authors: Davies Obaromi, Qin Yongsong, James Ndege, Azeez Adeboye, Akinwumi Odeyemi

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The basic model usually used in disease mapping, is the Besag, York and Mollie (BYM) model and which combines the spatially structured and spatially unstructured priors as random effects. Bayesian Conditional Autoregressive (CAR) model is a disease mapping method that is commonly used for smoothening the relative risk of any disease as used in the Besag, York and Mollie (BYM) model. This model (CAR), which is also usually assigned as a prior to one of the spatial random effects in the BYM model, successfully uses information from adjacent sites to improve estimates for individual sites. To our knowledge, there are some unrealistic or counter-intuitive consequences on the posterior covariance matrix of the CAR prior for the spatial random effects. In the conventional BYM (Besag, York and Mollie) model, the spatially structured and the unstructured random components cannot be seen independently, and which challenges the prior definitions for the hyperparameters of the two random effects. Therefore, the main objective of this study is to construct and utilize an extended Bayesian spatial CAR model for studying tuberculosis patterns in the Eastern Cape Province of South Africa, and then compare for flexibility with some existing CAR models. The results of the study revealed the flexibility and robustness of this alternative extended CAR to the commonly used CAR models by comparison, using the deviance information criteria. The extended Bayesian spatial CAR model is proved to be a useful and robust tool for disease modeling and as a prior for the structured spatial random effects because of the inclusion of an extra hyperparameter.

Keywords: Besag2, CAR models, disease mapping, INLA, spatial models

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Authors: Yang Zhang, Jian He

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Heart disease is one of the leading causes of death in the world, and coronary heart disease (CHD) is one of the major heart diseases. Electrocardiogram (ECG) is widely used in the detection of heart diseases, but the traditional manual method for CHD prediction by analyzing ECG requires lots of professional knowledge for doctors. This paper introduces sliding window and continuous wavelet transform (CWT) to transform ECG signals into images, and then ResNet and Bi-LSTM are introduced to build the ECG feature extraction network (namely ECGNet). At last, an auxiliary system for coronary heart disease prediction was developed based on modified ResNet18 and Bi-LSTM, and the public ECG dataset of CHD from MIMIC-3 was used to train and test the system. The experimental results show that the accuracy of the method is 83%, and the F1-score is 83%. Compared with the available methods for CHD prediction based on ECG, such as kNN, decision tree, VGGNet, etc., this method not only improves the prediction accuracy but also could avoid the degradation phenomenon of the deep learning network.

Keywords: Bi-LSTM, CHD, ECG, ResNet, sliding window

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Authors: Gulcan Sahal, Isil Seyis Bilkay

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Candida species which often exist as commensal microorganisms in healthy individuals are major causes of important infections, especially in AIDS and immunocompromised patients, by means of their biofilm formation abilities. Therefore, in this study, determination of biofilm formation in different clinical strains of Candida species, investigation of strong biofilm forming Candida strains, examination of clinical information of each strong and weak biofilm forming Candida strains and investigation of some plant substances’ effects on biofilm formation of strong biofilm forming strains were aimed. In this respect, biofilm formation of Candida strains was analyzed via crystal violet binding assay. According to our results, biofilm levels of strains belong to different Candida species were different from each other. Additionally, it is also found that some plant substances effect biofilm formation. All these results indicate that, as well as C. albicans strains, other non-albicans Candida species also emerge as causative agents of infections and have biofilm formation abilities. In addition, usage of some plant substances in different concentrations may provide a new treatment against biofilm related Candida infections.

Keywords: anti-biofilm, biofilm formation, Candida species, biosystems engineering

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Authors: Deepika, Kashika Kapoor, Nistha Khanna, Lakshmi, Archna Kumar

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Plant-parasitic nematodes cause major loss in global food production and destroying at least 21.3% of food annually. About 4100 species of plant-parasitic nematodes are reported, out of this, Meloidogyne species is prominent and worldwide in distribution. Observing the harmful effects of chemical based nematicides, there is a great need for an eco-friendly, highly efficient, sustainable control measure for Meloidogyne. Therefore, In vitro study was carried out to observe the impact of volatile cues obtained from the Tagetes erecta leaves on plant parasitic nematodes. Volatile cues were collected from marigold leaves. For chemical characterization, GCMS (Gas Chromatography Mass Spectrometry) profiling was conducted. VOCs (Volatile Organic Compounds) profile of marigold indicated the presence of several types of alkanes, alkenes varying in number and quantity. Status of nematodes population by counting the live and dead individuals after applying a definite volume (100µl) of extract was recorded at different concentrations (100%, 50%, 25%) with contrast of control (hexane) during different time durations i.e.,24hr, 48hr and 72hr. Result indicated that mortality increases with increasing time (72hr) and concentration (100%) i.e., 50%. Thus, application of prominent compound present in Marigold in pure form may be tested individually or in combination to find out the most efficient active compound/s, which may be highly useful in eco-friendly management of targeted plant parasitic nematode.

Keywords: plant-parasitic nematode, meloidogyne, tagetes erecta, volatile organic compounds

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Authors: Arash Azarpanah, Masoud Zadehbagheri, Shorangiz Javanmardi

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Abiotic stresses are the principle threat to plant growth and crop productivity all over the world. In order to improve the germination of corn seeds in drought stress conditions, effect of seed priming by various concentrations of salicylic acid (SA) (0.8 and 0.2 mM) on activities of catalase and peroxidase in Zea mays L. plant (Var-Sc.704) was evaluated at Agriculture Research Center located in Arsenjan city in Iran, during summer 2013. A farm research was done in RCBD as factorial with three replications. We considered four irrigation was carried out once the cumulative evaporation from Pan Class A come to 40, 60, 80 and 100 mm. Results illustrated that drought stress significantly increased activities of catalase and peroxidase and also treatment with salicylic acid significantly increased activities of catalase and peroxidase. In addition, treatment with salicylic acid enhances drought tolerance in Zea mays L. plant (Var-Sc.704) with increasing activities of antioxidant enzymes.

Keywords: catalase, corn, salicylic acid, water deficits stress, cumulative evaporation, Pan Class A

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Authors: Parisa Alizadeh Oskuie, Shahram Baghban Ciruse

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The influence of arbuscular mycorrhizal (AM) fungus(Glomus mossea) on plant growth and leaf-water potential of tomato (lycopersicum esculentum L.cv.super star) were studied in potted culture water stress stress period of 3 months in greenhouse conditions with the soil matric potential maintained at Fc1, Fc2, Fc3, and Fc4 respectively (0.8,0.7,0.6,0.5 Fc). Seven-day-old seedlings of tomato were transferred to pots containing Glomus mossea or non-AMF. AM colonization significantly stimulated shoot dry matter and leaf-water potential but water stress significantly decreased leaf area, shoot dry matter colonization and leaf-water potential.

Keywords: leaf-water potential, plant growth, tomato, VA mycorrhiza, water-stress

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Authors: Muhammad SAFDAR, Mehmet Ozaslan, Musarrat Abbas Khan

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Babesiosis is a haemoparasitic disease due to the multiplication of protozoan’s parasite, Babesia ovis in the red blood cells of the host, and contributes numerous economical losses, including sheep and goat ruminants. The early identification and successful treatment of Babesia Ovis spp. belong to the key steps of control and health management of livestock resources. The objective of this study was to construct a polymerase chain reaction (PCR) based method for the detection of Babesia spp. in small ruminants and to determine the risk factors involved in the spreading of babesiosis infections. A total of 100 blood samples were collected from 50 sheep and 50 goats along with different areas of Muzaffargarh, Pakistan, from randomly selected herds. Data on the characteristics of sheep and goats were collected through questionnaires. Of 100 blood samples examined, 18 were positive for Babesia ovis upon microscopic studies, whereas 11 were positive for the presence of Babesia spp. by PCR assay. For the recognition of parasitic DNA, a set of 500bp oligonucleotide was designed by PCR amplification with sequence 18S rRNA gene for B. ovis. The prevalence of babesiosis in small ruminant’s sheep and goat detected by PCR was significantly higher in female animals (28%) than male herds (08%). PCR analysis of the reference samples showed that the detection limit of the PCR assay was 0.01%. Taken together, all data indicated that this PCR assay was a simple, fast, specific detection method for Babesia ovis species in small ruminants compared to other available methods.

Keywords: Babesia ovis, PCR amplification, 18S rRNA, sheep and goat

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Authors: Sergey Sorokin, Irina Sorokina, Alexander Yazenin

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We present a solution to the Maxmin u/E parameters estimation problem of possibility distributions in m-dimensional case. Our method is based on geometrical approach, where minimal area enclosing ellipsoid is constructed around the sample. Also we demonstrate that one can improve results of well-known algorithms in fuzzy model identification task using Maxmin u/E parameters estimation.

Keywords: possibility distribution, parameters estimation, Maxmin u\E estimator, fuzzy model identification

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Authors: Jyotismita Talukdar

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In this paper, a study has been made on the possibility and accuracy of early prediction of several Heart Disease using Artificial Neural Network. (ANN). The study has been made in both noise free environment and noisy environment. The data collected for this analysis are from five Hospitals. Around 1500 heart patient’s data has been collected and studied. The data is analysed and the results have been compared with the Doctor’s diagnosis. It is found that, in noise free environment, the accuracy varies from 74% to 92%and in noisy environment (2dB), the results of accuracy varies from 62% to 82%. In the present study, four basic attributes considered are Blood Pressure (BP), Fasting Blood Sugar (FBS), Thalach (THAL) and Cholesterol (CHOL.). It has been found that highest accuracy(93%), has been achieved in case of PPI( Post-Permanent-Pacemaker Implementation ), around 79% in case of CAD(Coronary Artery disease), 87% in DCM (Dilated Cardiomyopathy), 89% in case of RHD&MS(Rheumatic heart disease with Mitral Stenosis), 75 % in case of RBBB +LAFB (Right Bundle Branch Block + Left Anterior Fascicular Block), 72% for CHB(Complete Heart Block) etc. The lowest accuracy has been obtained in case of ICMP (Ischemic Cardiomyopathy), about 38% and AF( Atrial Fibrillation), about 60 to 62%.

Keywords: coronary heart disease, chronic stable angina, sick sinus syndrome, cardiovascular disease, cholesterol, Thalach

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Authors: Omar Farahat Hassanein, A. Samer Ezeldin

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The construction industry is a very dynamic field. Every day new technologies and methods are developing to fasten the process and increase its efficiency. Hence, if a project uses fewer resources, it will be more efficient. This paper examines the recycling of concrete construction and demolition (C&D) waste to reuse it as aggregates in on-site applications for construction projects in Egypt and possibly in the Middle East. The study focuses on a stationary plant setting. The machinery set-up used in the plant is analyzed technically and financially. The findings are gathered and grouped to obtain a comprehensive cost-benefit financial model to demonstrate the feasibility of establishing and operating a concrete recycling plant. Furthermore, a detailed business plan including the time and hierarchy is proposed.

Keywords: construction wastes, recycling, sustainability, financial model, concrete recycling, concrete life cycle

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Authors: Sarika Singh, Moin Uddin, M. Masroor A. Khan, Aman Sobia Chishti, Sangram Singh, Urooj Hassan Bhatt

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Mentha arvensis L. (Japanese mint) is a perennial plant carrying medicinal, aromatic, antiseptic, and anaesthetic properties. Plant-derived smoke-water (PDSW) plays a significant role in seed germination, seedling growth, and other physiological attributes. To ascertain the effect of PDSW and karrikinolide on Mentha arvensis L., a rhizome-soaking experiment was conducted on Mentha arvensis. Prior to planting, mint rhizomes were soaked for 24 hours with aqueous solutions of various concentrations of PDSW (1:125v/v, 1:250 v/v, 1:500 v/v, and 1:1000 v/v), karrikinolide (10-6M, 10⁻⁷M, 10⁻⁸M, and 10⁻⁹M) using double distilled water as control treatment. Rhizome soaking with 1:500 v/v concentration of PDSW and 10⁻⁸M concentration of KAR1 increased the growth attributes, including plant height, fresh weight, dry, leaf area, and leaf yield per plant of Mentha arvensis. Leaf physiological-parameters, viz. chlorophyll fluorescence, PSII activity, and total chlorophyll and carotenoid content, were also increased as a result of the application of this treatment PDSW (1:500 v/v) and KAR1 (10⁻⁸M). In addition, treatment with 1:500 v/v and 10⁻⁸M significantly increased the essential oil yield and active constituents of Mentha arvensis compared to the control. Results indicated that PDSW, being a cheap source of karrikins, might be successfully used to augment mint essential oil production.

Keywords: active constituents, essential oil, medicinal plant, mentha arvensis L

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Authors: Ofosuhene O. Apenteng, Noor Azina Ismail

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Recently tourism is a major foreign exchange earner in the World. In this paper, we propose the mathematical model to study the impact of tourists on the spread of HIV incidences using compartmental differential equation models. Simulation studies of reproduction number are used to demonstrate new insights on the spread of HIV disease. The periodogram analysis of a time series was used to determine the speed at which the disease is spread. The results indicate that with the persistent flow of tourism into a country, the disease status has increased the epidemic rate. The result suggests that the government must put more control on illegal prostitution, unprotected sexual activity as well as to emphasis on prevention policies that include the safe sexual activity through the campaign by the tourism board.

Keywords: HIV/AIDS, mathematical transmission modeling, tourists, stability, simulation

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Authors: Razuana Rahim, Abdul Aziz Abdul Raman

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In this work, a study was conducted to evaluate the feasibility of using Cleaner Production (CP) strategy to reduce carbon dioxide emission (CO2) in a plant that produces Otoshimi. CP strategy is meant to reduce CO2 emission while taking into consideration the economic aspect. For this purpose, a CP audit was conducted and the information obtained were analyzed and major contributors of CO2 emission inside the boundary of the production plant was identified. Electricity, water and fuel consumption and generation of solid waste and wastewater were identified as the main contributors. Total CO2 emission generated was 0.27 kg CO2 per kg of Otoshimi produced, where 68% was contributed by electricity consumption. Subsequently, a total of three CP options were generated and implementations of these options are expected to reduce the CO2 emission from electricity consumption to 0.16 kg CO2 per kg of Otoshimi produced, a reduction of about 14%. The study proves that CP strategy can be implemented even without any investment to reduce CO2 for a plant that produces Otoshimi.

Keywords: carbon dioxide emission, cleaner production audit, cleaner production options, otoshimi production

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Authors: Abiodun Olayinka, Daniel Dzidzienyo, Pangirayi Tongoona, Samuel Offei, Edwige Gaby Nkouaya Mbanjo, Chiedozie Egesi, Ismail Yusuf Rabbi

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Cassava (Manihot esculenta Crantz) is a major source of starch for various industrial applications. However, the traditional cultivation and harvesting methods of cassava are labour-intensive and inefficient, limiting the supply of fresh cassava roots for industrial starch production. To achieve improved productivity and quality of fresh cassava roots through mechanized cultivation, cassava cultivars with compact plant architecture and moderate plant height are needed. Plant architecture-related traits, such as plant height, harvest index, stem diameter, branching angle, and lodging tolerance, are critical for crop productivity and suitability for mechanized cultivation. However, the genetics of cassava plant architecture remain poorly understood. This study aimed to identify the genetic bases of the relationships between plant architecture traits and productivity-related traits, particularly starch content. A panel of 453 clones developed at the International Institute of Tropical Agriculture, Nigeria, was genotyped and phenotyped for 18 plant architecture and productivity-related traits at four locations in Nigeria. A genome-wide association study (GWAS) was conducted using the phenotypic data from a panel of 453 clones and 61,238 high-quality Diversity Arrays Technology sequencing (DArTseq) derived Single Nucleotide Polymorphism (SNP) markers that are evenly distributed across the cassava genome. Five significant associations between ten SNPs and three plant architecture component traits were identified through GWAS. We found five SNPs on chromosomes 6 and 16 that were significantly associated with shoot weight, harvest index, and total yield through genome-wide association mapping. We also discovered an essential candidate gene that is co-located with peak SNPs linked to these traits in M. esculenta. A review of the cassava reference genome v7.1 revealed that the SNP on chromosome 6 is in proximity to Manes.06G101600.1, a gene that regulates endodermal differentiation and root development in plants. The findings of this study provide insights into the genetic basis of plant architecture and yield in cassava. Cassava breeders could leverage this knowledge to optimize plant architecture and yield in cassava through marker-assisted selection and targeted manipulation of the candidate gene.

Keywords: Manihot esculenta Crantz, plant architecture, DArtseq, SNP markers, genome-wide association study

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Authors: Jyoti Agrawal

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Introduction: Renal diseases in children and young adult can be difficult to diagnose early as it may present only with few symptoms, tends to have different course than adult and respond variously to different treatment. The pattern of renal disease in children is different from developing countries as compared to developed countries. Methods: This study was a hospital based prospective observational study carried from March, 2014 to February 2015 at BP Koirala institute of health sciences. Patients with renal disease, both inpatient and outpatient from birth to 14 years of age were enrolled in the study. The diagnosis of renal disease was be made on clinical and laboratory criteria. Results: Total of 120 patients were enrolled in our study which contributed to 3.74% % of total admission. The commonest feature of presentation was edema (75%), followed by fever (65%), hypertension (60%), decreased urine output (45%) and hematuria (25%). Most common diagnosis was acute glomerulonephritis (40%) followed by Nephrotic syndrome (25%) and urinary tract infection (25%). Renal biopsy was done for 10% of cases and most of them were steroid dependent nephrotic syndrome. 5% of our cases expired because of multiorgan dysfunction syndrome, sepsis and acute kidney injury. Conclusion: Renal disease contributes to a large part of hospital pediatric admission as well as mortality and morbidity to the children.

Keywords: glomerulonephritis, nephrotic syndrome, renal disease, urinary tract infection

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Authors: Ranju Chowdhury, Santosh K. Sarkar

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Trace element accumulation potential of ten mangrove species in individual plant tissues (leaves, bark and root/pneumatophore) along with host sediments was carried out at 2 study sites of diverse environmental stresses of Indian Sundarban Wetland, a UNESCO world heritage site. The study was undertaken with the following objectives: (i) to investigate the extent of accumulation and the distribution of trace metals in plant tissues (ii) to determine whether sediment trace metal levels are correlated with trace metal levels in tissues and (iii) to find out the suitable candidate for phytoremediation species. Mangrove sediments showed unique potential in many- fold increase for most trace metals than plant tissues due to their inherent physicochemical properties. The concentrations of studied 11 trace elements (expressed in µg g -1) showed wide range of variations in host sediment with the following descending order: Fe (2865.31-3019.62) > Mn (646.04- 648.47 > Cu (35.03- 41.55) > Zn (32.51- 36.33) > Ni (34.4- 36.60) > Cr (27.5- 29.54) > Pb (11.6- 20.34) > Co (6.79- 8.55) > As (3.22- 4.41) > Cd (0.19- 0.22) > Hg (0.06- 0.07). The ranges of concentration of trace metals (expressed in µg g -1) for As, Cd, Co, Cr, Cu, Fe, Hg, Mn, Ni, Pb and Zn in plant tissues were 0.006- 0.31, 0.02- 2.97, 0.10- 4.80, 0.13- 6.49, 4.46- 48.30, 9.20- 938.13, 0.02- 0.13, 9.8- 1726.24, 5.41- 11.34, 0.04 - 7.64, 3.81- 52.20 respectively. Among all trace elements, Cd and Zn were highly bioaccumulated in Excoecaria agallocha (2.97 and 52.20 µg g -1 respectively). The bio- concentration factor (BCF) showed its maximum value (15.5) in E. agallocha for Cd, suggesting that it can be considered as a high-efficient plant for trace metal bioaccumulation. Therefore, phytoremediation could be extensively used for the removal of the toxic contaminants for sustainable management of Sundarban coastal regions.

Keywords: Indian Sundarban, mangroves, phytoremediation, trace elements

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Authors: Haidy Weliam Megaly Gouda

Abstract:

Dermatology is often a neglected specialty in low-resource settings despite the high morbidity associated with skin disease. This becomes even more significant when associated with HIV infection, as dermatological conditions are more common and aggressive in HIV-positive patients. African countries have the highest HIV infection rates, and skin conditions are frequently misdiagnosed and mismanaged because of a lack of dermatological training and educational material. The frequent lack of diagnostic tests in the African setting renders basic clinical skills all the more vital. This project aimed to improve the diagnosis and treatment of skin disease in the HIV population in a district hospital in Malawi. A basic dermatological clinical tool was developed and produced in collaboration with local staff and based on available literature and data collected from clinics. The aim was to improve diagnostic accuracy and provide guidance for the treatment of skin disease in HIV-positive patients. A literature search within Embassy, Medline and Google Scholar was performed and supplemented through data obtained from attending 5 Antiretroviral clinics. From the literature, conditions were selected for inclusion in the resource if they were described as specific, more prevalent, or extensive in the HIV population or have more adverse outcomes if they develop in HIV patients. Resource-appropriate treatment options were decided using Malawian Ministry of Health guidelines and textbooks specific to African dermatology. After the collection of data and discussion with local clinical and pharmacy staff, a list of 15 skin conditions was included, and a booklet was created using the simple layout of a picture, a diagnostic description of the disease and treatment options. Clinical photographs were collected from local clinics (with full consent of the patient) or from the book ‘Common Skin Diseases in Africa’ (permission granted if fully acknowledged and used in a not-for-profit capacity). This tool was evaluated by the local staff alongside an educational teaching session on skin disease. This project aimed to reduce uncertainty in diagnosis and provide guidance for appropriate treatment in HIV patients by gathering information into one practical and manageable resource. To further this project, we hope to review the effectiveness of the tool in practice.

Keywords: prevalence and pattern of skin diseases, impact on quality of life, rural Nepal, interventions, quality switched ruby laser, skin color river blindness, clinical signs, 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: Anna Gaspard, Stéphane Boudreau, Martin Simard

Abstract:

Altered temperature and precipitation regimes associated with climate change generally result in improved conditions for plant growth. For Arctic and sub-Arctic ecosystems, this new climatic context favours an increase in primary productivity, a phenomenon often referred to as "greening". The development of an erect shrub cover has been identified as the main driver of Arctic greening. Although this phenomenon has been widely documented at the circumpolar scale, little information is available at the scale of plant communities, the basic unit of the Arctic, and sub-Arctic landscape mosaic. The objective of this study is to quantify the variation of NDVI within the different plant communities of Nunavik, which will allow us to identify the plant formations that contribute the most to the increase in productivity observed in this territory. To do so, the variation of NDVI extracted from Landsat images for the period 1984 to 2020 was quantified. From the Landsat scenes, annual summer NDVI mosaics with a resolution of 30 m were generated. The ecological mapping of Northern Quebec vegetation was then overlaid on the time series of NDVI maps to calculate the average NDVI per vegetation polygon for each year. Our results show that NDVI increases are more important for the bioclimatic domains of forest tundra and erect shrub tundra, and shrubby formations. Surface deposits, variations in mean annual temperature, and variations in winter precipitation are involved in NDVI variations. This study has thus allowed us to quantify changes in Nunavik's vegetation communities, using fine spatial resolution satellite imagery data.

Keywords: climate change, latitudinal gradient, plant communities, productivity

Procedia PDF Downloads 182

Authors: Sara Mostofian

Abstract:

The nuclear industry is a technology that can fulfill future energy needs but requires special attention to ensure safety and reliability while minimizing any environmental impact. To meet these expectations, the nuclear industry is exploring different reactor technologies for power production. Several designs are under development and the technical viability of these new designs is the subject of many ongoing studies. One of these studies considers the radioactive emissions and radioactive waste generated during the life of a nuclear power production plant to allow a successful license process. For all the modern technologies, a good understanding of the radioactivity generated in the process systems of the plant is essential. Some of that understanding may be gleaned from the performance of some prototype reactors of similar design that operated decades ago. This paper presents how, with that understanding, a model can be developed to estimate the emissions as well as the radioactive waste during the normal operation of a nuclear power plant. The model would predict the radioactive material concentrations in different waste streams. Using this information, the radioactive emission and waste generated during the life of these new technologies can be estimated during the early stages of the design of the plant.

Keywords: SMRs, activity transport, model, radioactive waste

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Authors: Merih Şimşek, Recep Keşli, Özgül Çetinkaya, Cengiz Demir, Adem Aslan

Abstract:

Bacteremia is a clinical entity with high morbidity and mortality rates when immediate diagnose, or treatment cannot be achieved. Microorganisms which can cause sepsis or bacteremia are easily isolated from blood cultures. Fifty-five positive blood cultures were included in this study. Microorganisms in 55 blood cultures were isolated by conventional microbiological methods; afterwards, microorganisms were defined in terms of the phenotypic aspects by the Vitek-2 system. The same microorganisms in all blood culture samples were defined in terms of genotypic aspects again by Multiplex-PCR DNA Low-Density Microarray System. At the end of the identification process, the DNA microarray system’s success in identification was evaluated based on the Vitek-2 system. The Vitek-2 system and DNA Microarray system were able to identify the same microorganisms in 53 samples; on the other hand, different microorganisms were identified in the 2 blood cultures by DNA Microarray system. The microorganisms identified by Vitek-2 system were found to be identical to 96.4 % of microorganisms identified by DNA Microarrays system. In addition to bacteria identified by Vitek-2, the presence of a second bacterium has been detected in 5 blood cultures by the DNA Microarray system. It was identified 18 of 55 positive blood culture as E.coli strains with both Vitek 2 and DNA microarray systems. The same identification numbers were found 6 and 8 for Acinetobacter baumanii, 10 and 10 for K.pneumoniae, 5 and 5 for S.aureus, 7 and 11 for Enterococcus spp, 5 and 5 for P.aeruginosa, 2 and 2 for C.albicans respectively. According to these results, DNA Microarray system requires both a technical device and experienced staff support; besides, it requires more expensive kits than Vitek-2. However, this method should be used in conjunction with conventional microbiological methods. Thus, large microbiology laboratories will produce faster, more sensitive and more successful results in the identification of cultured microorganisms.

Keywords: microarray, Vitek-2, blood culture, bacteremia

Procedia PDF Downloads 350