Search results for: plant disease classification

Authors: Soyon Kim, Edward Kim

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In order to retrieve information from the massive stream of songs in the music industry, music search by title, lyrics, artist, mood, and genre has become more important. Despite the subjectivity and controversy over the definition of music genres across different nations and cultures, automatic genre classification systems that facilitate the process of music categorization have been developed. Manual genre selection by music producers is being provided as statistical data for designing automatic genre classification systems. In this paper, an automatic music genre classification system utilizing non-negative matrix factorization (NMF) is proposed. Short-term characteristics of the music signal can be captured based on the timbre features such as mel-frequency cepstral coefficient (MFCC), decorrelated filter bank (DFB), octave-based spectral contrast (OSC), and octave band sum (OBS). Long-term time-varying characteristics of the music signal can be summarized with (1) the statistical features such as mean, variance, minimum, and maximum of the timbre features and (2) the modulation spectrum features such as spectral flatness measure, spectral crest measure, spectral peak, spectral valley, and spectral contrast of the timbre features. Not only these conventional basic long-term feature vectors, but also NMF based feature vectors are proposed to be used together for genre classification. In the training stage, NMF basis vectors were extracted for each genre class. The NMF features were calculated in the log spectral magnitude domain (NMF-LSM) as well as in the basic feature vector domain (NMF-BFV). For NMF-LSM, an entire full band spectrum was used. However, for NMF-BFV, only low band spectrum was used since high frequency modulation spectrum of the basic feature vectors did not contain important information for genre classification. In the test stage, using the set of pre-trained NMF basis vectors, the genre classification system extracted the NMF weighting values of each genre as the NMF feature vectors. A support vector machine (SVM) was used as a classifier. The GTZAN multi-genre music database was used for training and testing. It is composed of 10 genres and 100 songs for each genre. To increase the reliability of the experiments, 10-fold cross validation was used. For a given input song, an extracted NMF-LSM feature vector was composed of 10 weighting values that corresponded to the classification probabilities for 10 genres. An NMF-BFV feature vector also had a dimensionality of 10. Combined with the basic long-term features such as statistical features and modulation spectrum features, the NMF features provided the increased accuracy with a slight increase in feature dimensionality. The conventional basic features by themselves yielded 84.0% accuracy, but the basic features with NMF-LSM and NMF-BFV provided 85.1% and 84.2% accuracy, respectively. The basic features required dimensionality of 460, but NMF-LSM and NMF-BFV required dimensionalities of 10 and 10, respectively. Combining the basic features, NMF-LSM and NMF-BFV together with the SVM with a radial basis function (RBF) kernel produced the significantly higher classification accuracy of 88.3% with a feature dimensionality of 480.

Keywords: mel-frequency cepstral coefficient (MFCC), music genre classification, non-negative matrix factorization (NMF), support vector machine (SVM)

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Authors: Ladda Her, Juntip Kanjanasilp, Ratree Sawangjit, Nathorn Chaiyakunapruk

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Cough is the common symptom of the respiratory tract infections or non-infections; the duration of cough indicates a classification and severity of disease. Herbal medicines can be used as the alternative to drugs for relief of cough symptoms from acute and chronic disease. Eucalyptus was used for reducing cough with evidences suggesting it has an active role in reduction of airway inflammation. The present study aims to evaluate efficacy and safety of eucalyptus for relief of cough symptom in respiratory disease. Method: The Cochrane Library, MEDLINE (PubMed), Scopus, CINAHL, Springer, Science direct, ProQuest, and THAILIS databases. From its inception until 01/02/2019 for randomized control trials. We follow for the efficacy and safety of eucalyptus for reducing cough. Methodological quality was evaluated by using the Cochrane risk of bias tool; two reviewers in our team screened eligibility and extracted data. Result: Six studies were included for the review and five studies were included in the meta-analysis, there were 1.911 persons including children (n: 1) and adult (n: 5) studies; for study in children and adult were between 1 and 80 years old, respectively. Eucalyptus was used as mono herb (n: 2) and in combination with other herbs form (n: 4). All of the studies with eucalyptus were compared for efficacy and safety with placebo or standard treatment, Eucalyptus dosage form in studies included capsules, spray, and syrup. Heterogeneity was 32.44 used random effect model (I² = 1.2%, χ² = 1.01; P-value = 0.314). The efficacy of eucalyptus was showed a reduced cough symptom statistically significant (n = 402, RR: 1.40, 95%CI [1.19, 1.65], P-value < 0.0001) when compared with placebo. Adverse events (AEs) were reported mild to moderate intensity with mostly gastrointestinal symptom. The methodological quality of the included trials was overall poor. Conclusion: Eucalyptus appears to be beneficial and safe for relieving in respiratory diseases focus on cough frequency. The evidence was inconclusive due to limited quality trial. Well-designed trials for evaluating the effectiveness in humans, the effectiveness for reducing cough symptom in human is needed. Eucalyptus had safety as monotherapy or in combination with other herbs.

Keywords: cough, eucalyptus, cineole, herbal medicine, systematic review, meta-analysis

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Authors: Devarakonda Ramadevi, Dasari Rambabu, K. Suresh Babu, Battu Ganga Rao, Lakshmi Sirisha Kotikalapudi

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The phytochemical and biological evaluation of the whole plant of Derris scandens is belonging to the family fabaceae. The dried plant of D.scandens was procured from the tirumala. The completely dried powder of the whole plant was taken and ground to a coarse powder which was then subjected to Soxhlet extraction with hexane and chloroform successively for 36 hrs. Chloroform extract was filtered and concentrated by using rotary evaporator an about 100g extract was obtained. The chloroform extract was subjected to column chromatographed over silicagel. From the column chromatography seven compounds were isolated named as osajin, scandinone, scandenone, 4,5,7-tri hydroxy biprenyl isoflavone, derris isoflavone-A, scandenin and isoscandinone. D.scandens resulting in the isolation of seven compounds in the plant was confirmed by spectral data (1H NMR, 13C NMR, ESI-MS and FTIR). The isolated compounds were screened for antioxidant activity, antidiabetic activity, α-glucosidase (inhibitory activity) and anti-bacterial activity. The isolated seven compounds were tested for α-glucosidase inhibitory activity and antioxidant activity. All the seven compounds showed good α-glucosidase inhibitory activity and moderate antioxidant activity.

Keywords: Derris scandens, phytochemical, antioxident, antidiabetic, antibacterial activity

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Authors: Anas Cherqui, Audrey Pecourt, Manuella Catterou, Candice Mazoyon, Hervé Demailly, Vivien Sarazin, Frédéric Dubois, Jérôme Duclercq.

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Aphids are pests that can cause severe yield losses in field crops. Chemical control is currently widely used to control aphids, but this method is increasingly controversial. The pea is able to recruit bacteria that are beneficial to its development, growth and health. However, the effects of this microbial recruitment on plant-insect interactions have generally been underestimated. This study investigated the interactions between Pisum sativum, key bacteria of pea rhizosphere (Rhizobium and Sphingomonas species) and the pea aphid, Acyrthosiphon pisum. We assessed the bottom-up effects of single and combined bacterial inoculations on pea plant health and subsequent aphid performance, as well as the top-down effects of aphid infestation on soil functionality. The presence of S. sediminicola or S. daechungensis limited the fecundity of the pea aphid without strongly affecting its feeding behaviour. Nevertheless, these bacteria limited the effect of A. pisum on the plant phenotype. In addition, the aphid infestation decreased the soil functionality, suggesting a potential strategy to hinder the recruitment of beneficial microorganisms.

Keywords: Acyrthosiphon pisum, Pisum sativum, Sphingomonas, rhizobium, EPG, productivity

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Authors: Rania A. R. Soudan, Easter Joury

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Introduction: Psoriasis is a common chronic dermatologic disease. It may affect the mucous membranes. The presence of oral mucosal lesions has been a subject of controversy. The aim: To determine possible association between oral mucosal lesions and psoriasis, and to correlate the same with different types of psoriasis and severity of the disease. Materials and Methods: The oral mucosa was clinically examined in 100 randomly selected Syrian psoriatic patients presented to the Dermatological Diseases Hospital in Damascus University, Syria (February 2009 - December 2010), and in 100 matched controls. PASI index was used to evaluate the disease severity. Chi-square and Student t-test were used to compare differences between groups. Results: Oral mucosal lesions were observed in 72% of the psoriasis cases, while 46% of the control group’s subjects had oral lesions. Fissured tongue, geographic tongue, and red lesions were detected in 36%, 25%, and 7% of the examined psoriatics, respectively. These lesions were significantly more frequent in the psoriatics than in the controls. A correlation was found between furred tongue and the age of the psoriasis patients. However, an association was observed for fissured tongue, furred tongue with the severity of the disease, and for fissured tongue, white lesions, cheilitis with nail involvement. However, no correlation with the psoriasis types was recorded. Conclusion: Some oral mucosal lesions were associated with psoriasis, so these lesions may be considered as oral manifestations of this disease, and should be taken into account in new studies as possible predictors or markers of this dermatitis. Further studies are recommended to confirm these oral manifestations.

Keywords: psoriasis, tongue, mucosa, lesions

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Authors: Haonan Hu, Shuge Lei, Dasheng Sun, Huabin Zhang, Kehong Yuan, Jian Dai, Jijun Tang

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This paper focuses on the classification task of breast ultrasound images and conducts research on the reliability measurement of classification results. A dual-channel evaluation framework was developed based on the proposed inference reliability and predictive reliability scores. For the inference reliability evaluation, human-aligned and doctor-agreed inference rationals based on the improved feature attribution algorithm SP-RISA are gracefully applied. Uncertainty quantification is used to evaluate the predictive reliability via the test time enhancement. The effectiveness of this reliability evaluation framework has been verified on the breast ultrasound clinical dataset YBUS, and its robustness is verified on the public dataset BUSI. The expected calibration errors on both datasets are significantly lower than traditional evaluation methods, which proves the effectiveness of the proposed reliability measurement.

Keywords: medical imaging, ultrasound imaging, XAI, uncertainty measurement, trustworthy AI

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Authors: Sajjad Jafari

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Background and Aim: The use of herbal medicines has a long history. Today, due to the resistance of microorganisms to antibiotics and antimicrobial substances, herbal medicines have attracted attention due to their significant antimicrobial effects and low toxicity. This study aims to systematically review the antimicrobial effects of different plant extracts (Quercus infectoria) as possible candidates for treating infectious diseases. Material and Methods: The present study is a review study by searching reputable scientific databases such as PubMed, Google Scholar, Scopus, and Web of Science from 2000 to 2023 using the keywords Antimicrobial, Quercus infectoria, Medicinal herbal, Infectious diseases the latest information obtained. Results: In this study, 45 articles were found and reviewed. Quercus infectoria is a small tree native to Greece, Asia Minor, and Iran. Quercus is a plant genus in the family of Fagaceae. This species is generally known under the name ‘‘baloot” in Iran and is commonly used as a medicinal plant. The extracts used included water, hydro-alcoholic, ethanol, methanol. This plant had high inhibition activity and a lethal effect on gram-positive and gram-negative bacteria of ATCC strains, hospital, and resistant strains. Therefore, in addition to antibacterial effects, antiparasitic and antifungal effects. The seed of the plant was the most used and the most effective antimicrobial extract among the ethanol and methanol extracts. Conclusion: The findings of this study suggest that Quercus infectoria has significant antimicrobial effects against a wide range of microorganisms. This makes it a potential candidate for the development of new antimicrobial drugs. Further research is needed to confirm the efficacy and safety of Quercus infectoria in clinical trials.

Keywords: antimicrobial, Quercus infectoria, medicinal herbal, infectious diseases

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Authors: Septiawan A. Saputro, Purnami Widyaningsih, Sutanto Sastraredja

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Measles is a disease which can spread caused by a virus and has been a priority’s Ministry of Health in Indonesia to be solved. Each infected person can be recovered and get immunity so that the spread of the disease can be constructed with susceptible infected recovered (SIR). To prevent the spread of measles transmission, the Ministry of Health holds vaccinations program. The aims of the research are to derive susceptible vaccinated infected recovered (SVIR) model, to determine the patterns of disease spread with SVIR model, and also to apply the SVIR model on the spread of measles in Indonesia. Based on the article, it can be concluded that the spread model of measles with vaccinations, that is SVIR model. It is a first-order differential equation system. The patterns of disease spread is determined by solution of the model. Based on that model Indonesia will be a measles-free nation in 2186 with the average of vaccinations scope about 88% and the average score of vaccinations failure about 4.9%. If it is simulated as Ministry of Health new programs with the average of vaccinations scope about 95% and the average score of vaccinations failure about 3%, then Indonesia will be a measles-free nation in 2184. Even with the average of vaccinations scope about 100% and no failure of vaccinations, Indonesia will be a measles-free nation in 2183. Indonesia’s target as a measles-free nation in 2020 has not been reached.

Keywords: measles, vaccination, susceptible infected recovered (SIR), susceptible vaccinated infected recovered (SVIR)

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Authors: Grecco M. Ante, Princess Rochelle O. Gan

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Plants that can absorb greater than 10,000 µg Ni/g dry mass in their stems and leaves are termed as ‘hypernickelophores’. Chelators are chemicals that make the metals in the soil more soluble, making them a potential enhancer for phytoextraction. This study aims to observe the effect of different concentrations of the chelating agent ethylene diamine tetraacetate (EDTA) on the metal uptake (or rate of phytoextraction) of Nickel by Phyllanthus sp. nov. The plant is found to be a hyperickelophore in normal conditions. The addition of EDTA increased the metal uptake of the plant. The increasing amount of the chelating agent causes a decrease in the phytoextraction of the plant but moves the onset of its peak of maximum nickel content in its tissue to an earlier time. The chelator-assisted phytoextraction of nickel by Phyllanthus sp. nov. is proven to be an efficient auxiliary mining operation for nickel laterite mines.

Keywords: phytomining, Phyllanthus sp. nov., EDTA, nickel, laterite

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Authors: Jaiden Xuan Schraut, Leon Liu, Yiqiao Yin

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Computer vision in medical diagnosis has achieved a high level of success in diagnosing diseases with high accuracy. However, conventional classifiers that produce an image to-label result provides insufficient information for medical professionals to judge and raise concerns over the trust and reliability of a model with results that cannot be explained. In order to gain local insight into cancerous regions, separate tasks such as imaging segmentation need to be implemented to aid the doctors in treating patients, which doubles the training time and costs which renders the diagnosis system inefficient and difficult to be accepted by the public. To tackle this issue and drive AI-first medical solutions further, this paper proposes a multi-output network that follows a U-Net architecture for image segmentation output and features an additional convolutional neural networks (CNN) module for auxiliary classification output. Class activation maps are a method of providing insight into a convolutional neural network’s feature maps that leads to its classification but in the case of lung diseases, the region of interest is enhanced by U-net-assisted Class Activation Map (CAM) visualization. Therefore, our proposed model combines image segmentation models and classifiers to crop out only the lung region of a chest X-ray’s class activation map to provide a visualization that improves the explainability and is able to generate classification results simultaneously which builds trust for AI-led diagnosis systems. The proposed U-Net model achieves 97.61% accuracy and a dice coefficient of 0.97 on testing data from the COVID-QU-Ex Dataset which includes both diseased and healthy lungs.

Keywords: multi-output network model, U-net, class activation map, image classification, medical imaging analysis

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Authors: Hasan Basri Jumin, Henni Rosneti, Agusnimar

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Crude palm oil liquid sludge sewage was treated to maize with 400 cc/plant could be increased mean relative growth rates, net assimilation rate, leaf area and dry weight of seed. There are indicated that 400 cc / plant treated to maize significantly increase the average of mean relative growth rates into 0.32 g.day-1. Net assimilation rates increase from 13.5 mg.m-2.day-1 into 34.5 mg.m-2.day-1, leaf area at 50 days after planting increase from 1419 cm-2 into 2458 cm-2 and dry weight of seed from 38 g per plant into 43 g per plant. Crude palm oil liquid sludge waste chemical analysis indicated that, there are no exceed threshold content of dangerous metals and biology effects. Cadmium content as heavy metal is lower than threshold of human healthy tolerance. Therefore, it has no syndrome effect to human health. Biological oxygen demands and chemical oxygen demands as indicators for micro-organism activities, there are under the threshold of human healthy tolerance.

Keywords: crude-palm-oil, fertilizer, liquid-sludge, maize, pollutant, waste

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Authors: Seema Garcha, Sheetal Chopra, Navraj Sarao

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Plant hormones play a role in internal colonization by beneficial microbes and also systemic acquired resistance. They define qualitative and quantitative nature of root microbiome and also influence dynamics of root rhizospheric soil. The present study is an attempt to relate salicylic acid (signal molecule) content and qualitative nature of root endophytes at various stages in the growth of rice varieties of commercial value- Parmal 121 and Basmati 1121. Root seedlings of these varieties were raised using tissue culture techniques and then they were transplanted in the fields. Cultivation was done using conventional methods in agriculture. Field soil contained 0.39% N, 75.12 Kg/hectare of phosphorus and 163.0 Kg/hectare of potassium. Microfloral profiling of the root tissue was done using the selective microbiological medium. The salicylic acid content was estimated using HPLC-Agilent 1100 HPLC Series. Salicylic acid level of Basmati 1121 remained relatively low at the time of transplant and 90 days after transplant. It increased marginally at 60 days. A similar trend was observed with Parmal 121 as well. However, Parmal variety recorded 0.935 ug/g of salicylic acid at 60 days after transplant. Salicylic acid content decreased after 90 days as both the rice varieties remained disease free. The endophytic root microflora was established by 60 days after transplant in both the varieties after which their population became constant. Rhizobium spp dominated over Azotobacter spp. Genetic profiling of endophytes for nitrogen-fixing ability is underway.

Keywords: plant-microbe interaction, rice, root microbiome, salicylic acid

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Authors: Dalave S. C., S. G. Auti, B. J. Apparao

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Centella asiatica (L) Urban, commonly known as Brahmi and Mandookaparni is a valuable medicinal plant highly valued for its asiaticoside and madecassoside. It is widely used in Ayurveda and Unani systems of medicine. Attempts are made in the present investigation to improve the genotype of Centella plant that can yield higher amount of the therapeutically active compounds viz., asiaticosides and madecassosides, employing techniques of polyploidy breeding. Young developing shoots of Centella were treated with different concentrations of colchicine for varying time intervals. 0.4 % colchicine for 6 hours duration at room temperature was effective in inducing autopolyploidy in this plant. The colchicine treated plants were allowed to reproduce vegetatively for several generations in a polyhouse. The colchicine treated plants showed significant increase in plant size, fresh & dry weights, vigorous growth, broad leaves and double the number of chromosomes. HPTLC analysis of dried leaves of control and polyploid plants, even after 9th generations, revealed that the tetraploids synthesized at two times more asiaticoside and madecassoside, as compared to control, untreated diploid plants.

Keywords: Centella asiatica, polyploidy, asiaticosides, madecassoside, HPTLC

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Authors: Ian Marc G. Cabugsa, Zarine M. Hermita

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Phytoextraction capability of T. catappa in contaminated soils was done in the improvised greenhouse. The plant samples were planted to the soil which contained different concentrations of copper. Chelating agent EDTA was added to observe the uptake and translocation of copper in the plant samples. Results showed a significant increase of copper accumulation with the addition of EDTA at 250 and 1250 mgˑkg-1 concentration of copper in the contaminated soils (p<0.05). While translocation of copper was observed in all treatments, translocation of copper is not significantly enhanced by the addition of EDTA (p>0.05). Uptake and translocation were not directly affected the presence of EDTA. Furthermore, this study suggests that the T. catappa is not a hyperaccumulator of copper, and there is no relationship observed between the length of the plant and the copper uptake in all treatments.

Keywords: chelating agent EDTA, hyperaccumulator, phytoextraction, phytoremediation, terminalia catappa

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Authors: H. C. Chinwenyi, H. D. Ibrahim, J. O. Adekunle

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The incubation period is defined as the time from infection with a microorganism to development of symptoms. In this research, two disease models: one with incubation period and another without incubation period were studied. The study involves the use of a  mathematical model with a single incubation period. The test for the existence and stability of the disease free and the endemic equilibrium states for both models were carried out. The fourth order Runge-Kutta method was used to solve both models numerically. Finally, a computer program in MATLAB was developed to run the numerical experiments. From the results, we are able to show that the endemic equilibrium state of the model with incubation period is locally asymptotically stable whereas the endemic equilibrium state of the model without incubation period is unstable under certain conditions on the given model parameters. It was also established that the disease free equilibrium states of the model with and without incubation period are locally asymptotically stable. Furthermore, results from numerical experiments using empirical data obtained from Nigeria Centre for Disease Control (NCDC) showed that the overall population of the infected people for the model with incubation period is higher than that without incubation period. We also established from the results obtained that as the transmission rate from susceptible to infected population increases, the peak values of the infected population for the model with incubation period decrease and are always less than those for the model without incubation period.

Keywords: asymptotic stability, Hartman-Grobman stability criterion, incubation period, Routh-Hurwitz criterion, Runge-Kutta method

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Authors: Gholam Reza Mirzaei

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This research aimed to investigate the effectiveness of acceptance and commitment therapy (ACT) in reducing corona disease anxiety in the staff working at Shahid Beheshti Hospital of Shiraz. The current research was a quasi-experimental study having pre-test and post-test with two experimental and control groups. The statistical population of the research included all the staff of Shahid Beheshti Hospital of Shiraz in 2021. From among the statistical population, 30 participants (N =15 in the experimental group and N =15 in the control group) were selected by available sampling. The materials used in the study comprised the Cognitive Emotion Regulation Questionnaire (CERQ) and Corona Disease Anxiety Scale (CDAS). Following data collection, the participants’ scores were analyzed using SPSS 20 at both descriptive (mean and standard deviation) and inferential (analysis of covariance) levels. The results of the analysis of covariance (ANCOVA) showed that acceptance and commitment therapy (ACT) is effective in reducing Corona disease anxiety (mental and physical symptoms) in the staff working at Shahid Beheshti Hospital of Shiraz. The effectiveness of acceptance and commitment therapy (ACT) on reducing mental symptoms was 25.5% and on physical symptoms was 13.8%. The mean scores of the experimental group in the sub-scales of Corona disease anxiety (mental and physical symptoms) in the post-test were lower than the mean scores of the control group.

Keywords: acceptance and commitment therapy, corona disease anxiety, hospital staff, Shiraz

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Authors: Mpho Mokoatle, Darlington Mapiye, James Mashiyane, Stephanie Muller, Gciniwe Dlamini

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Great advances in high-throughput sequencing technologies have resulted in availability of huge amounts of sequencing data in public and private repositories, enabling a holistic understanding of complex biological phenomena. Sequence data are used for a wide range of applications such as gene annotations, expression studies, personalized treatment and precision medicine. However, this rapid growth in sequence data poses a great challenge which calls for novel data processing and analytic methods, as well as huge computing resources. In this work, a machine and statistical learning approach for DNA sequence classification based on $k$-mer representation of sequence data is proposed. The approach is tested using whole genome sequences of Mycobacterium tuberculosis (MTB) isolates to (i) reduce the size of genomic sequence data, (ii) identify an optimum size of k-mers and utilize it to build classification models, (iii) predict the phenotype from whole genome sequence data of a given bacterial isolate, and (iv) demonstrate computing challenges associated with the analysis of whole genome sequence data in producing interpretable and explainable insights. The classification models were trained on 104 whole genome sequences of MTB isoloates. Cluster analysis showed that k-mers maybe used to discriminate phenotypes and the discrimination becomes more concise as the size of k-mers increase. The best performing classification model had a k-mer size of 10 (longest k-mer) an accuracy, recall, precision, specificity, and Matthews Correlation coeffient of 72.0%, 80.5%, 80.5%, 63.6%, and 0.4 respectively. This study provides a comprehensive approach for resampling whole genome sequencing data, objectively selecting a k-mer size, and performing classification for phenotype prediction. The analysis also highlights the importance of increasing the k-mer size to produce more biological explainable results, which brings to the fore the interplay that exists amongst accuracy, computing resources and explainability of classification results. However, the analysis provides a new way to elucidate genetic information from genomic data, and identify phenotype relationships which are important especially in explaining complex biological mechanisms.

Keywords: AWD-LSTM, bootstrapping, k-mers, next generation sequencing

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Authors: Darlington Mapiye, Mpho Mokoatle, James Mashiyane, Stephanie Muller, Gciniwe Dlamini

Abstract:

Great advances in high-throughput sequencing technologies have resulted in availability of huge amounts of sequencing data in public and private repositories, enabling a holistic understanding of complex biological phenomena. Sequence data are used for a wide range of applications such as gene annotations, expression studies, personalized treatment and precision medicine. However, this rapid growth in sequence data poses a great challenge which calls for novel data processing and analytic methods, as well as huge computing resources. In this work, a machine and statistical learning approach for DNA sequence classification based on k-mer representation of sequence data is proposed. The approach is tested using whole genome sequences of Mycobacterium tuberculosis (MTB) isolates to (i) reduce the size of genomic sequence data, (ii) identify an optimum size of k-mers and utilize it to build classification models, (iii) predict the phenotype from whole genome sequence data of a given bacterial isolate, and (iv) demonstrate computing challenges associated with the analysis of whole genome sequence data in producing interpretable and explainable insights. The classification models were trained on 104 whole genome sequences of MTB isoloates. Cluster analysis showed that k-mers maybe used to discriminate phenotypes and the discrimination becomes more concise as the size of k-mers increase. The best performing classification model had a k-mer size of 10 (longest k-mer) an accuracy, recall, precision, specificity, and Matthews Correlation coeffient of 72.0 %, 80.5 %, 80.5 %, 63.6 %, and 0.4 respectively. This study provides a comprehensive approach for resampling whole genome sequencing data, objectively selecting a k-mer size, and performing classification for phenotype prediction. The analysis also highlights the importance of increasing the k-mer size to produce more biological explainable results, which brings to the fore the interplay that exists amongst accuracy, computing resources and explainability of classification results. However, the analysis provides a new way to elucidate genetic information from genomic data, and identify phenotype relationships which are important especially in explaining complex biological mechanisms

Keywords: AWD-LSTM, bootstrapping, k-mers, next generation sequencing

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Authors: Yishu Gong, Liangliang Yang, Jianyu Zhang, Zhengyu Chen, Sihong He, Xusheng Zhang, Wei Zhang

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Alzheimer’s disease (AD) is a progressive neurodegenerative disorder that affects millions of people worldwide and is characterized by cognitive decline and behavioral changes. People living with Alzheimer’s disease often find it hard to complete routine tasks. However, there are limited objective assessments that aim to quantify the difficulty of certain tasks for AD patients compared to non-AD people. In this study, we propose to use speech emotion recognition (SER), especially the frustration level, as a potential biomarker for quantifying the difficulty patients experience when describing a picture. We build an SER model using data from the IEMOCAP dataset and apply the model to the DementiaBank data to detect the AD/non-AD group difference and perform longitudinal analysis to track the AD disease progression. Our results show that the frustration level detected from the SER model can possibly be used as a cost-effective tool for objective tracking of AD progression in addition to the Mini-Mental State Examination (MMSE) score.

Keywords: Alzheimer’s disease, speech emotion recognition, longitudinal biomarker, machine learning

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Authors: Münüre Tanur Erkoyuncu, Mustafa Yorgancılar

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Crop improvement through genetic engineering depends on effective and reproducible plant regeneration systems. Immature embryos are the most widely used explant source for in vitro regeneration in barley (Hordeum vulgare L.). However, immature embryos require the continuous growth of donor plants and the suitable stage for their culture is also certainly limited. On the other hand, mature embryos can be procured and stored easily; they can be studied throughout the year. In this study, an effective callus induction and plant regeneration were aimed to develop from mature embryos of different barley genotypes. The effect of medium (MS₁ and MS₂), auxin type (2,4-D, dicamba, picloram and 2,4,5-T) and concentrations (2, 4, 6 mg/l) on callus formation and effect of cytokinin type (TDZ, BAP) and concentrations (0.2, 0.5, 1.0 mg/l) on green plant regeneration were evaluated in mature embryo culture of barley. Callus and shoot formation was successful for all genotypes. By depending on genotype, MS₁ is the best medium, 4 mg/l dicamba is the best growth regulator in the callus induction and MS₁ is the best medium, 1 mg/l BAP is the best growth regulator in the shoot formation were determined.

Keywords: barley, callus, embryo culture, mature embryo

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Authors: Diana C. El Assal, Fatima Monteiro, Caroline May, Peter Barbuti, Silvia Bolognin, Averina Nicolae, Hulda Haraldsdottir, Lemmer R. P. El Assal, Swagatika Sahoo, Longfei Mao, Jens Schwamborn, Rejko Kruger, Ines Thiele, Kathrin Marcus, Ronan M. T. Fleming

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Degeneration of substantia nigra pars compacta dopaminergic neurons is one of the hallmarks of Parkinson's disease. These neurons have a highly complex axonal arborisation and a high energy demand, so any reduction in ATP synthesis could lead to an imbalance between supply and demand, thereby impeding normal neuronal bioenergetic requirements. Synaptic mitochondria exhibit increased vulnerability to dysfunction in Parkinson's disease. After biogenesis in and transport from the cell body, synaptic mitochondria become highly dependent upon oxidative phosphorylation. We applied a systems biochemistry approach to identify the metabolic pathways used by neuronal mitochondria for energy generation. The mitochondrial component of an existing manual reconstruction of human metabolism was extended with manual curation of the biochemical literature and specialised using omics data from Parkinson's disease patients and controls, to generate reconstructions of synaptic and somal mitochondrial metabolism. These reconstructions were converted into stoichiometrically- and fluxconsistent constraint-based computational models. These models predict that Parkinson's disease is accompanied by an increase in the rate of glycolysis and a decrease in the rate of oxidative phosphorylation within synaptic mitochondria. This is consistent with independent experimental reports of a compensatory switching of bioenergetic pathways in the putamen of post-mortem Parkinson's disease patients. Ongoing work, in the context of the SysMedPD project is aimed at computational prediction of mitochondrial drug targets to slow the progression of neurodegeneration in the subset of Parkinson's disease patients with overt mitochondrial dysfunction.

Keywords: bioenergetics, mitochondria, Parkinson's disease, systems biochemistry

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Authors: Zoran Šverko, Saša Vlahinić, Nino Stojković, Ivan Markovinović

Abstract:

In this article, the classification of target letters is performed using data from the EEG P300 Speller paradigm. Neural networks trained with the results of dynamic connectivity analysis between different brain regions are used for classification. Dynamic connectivity analysis is based on the adaptive window size and the imaginary part of the complex Pearson correlation coefficient. Brain dynamics are analysed using the relative intersection of confidence intervals for the imaginary component of the complex Pearson correlation coefficient method (RICI-imCPCC). The RICI-imCPCC method overcomes the shortcomings of currently used dynamical connectivity analysis methods, such as the low reliability and low temporal precision for short connectivity intervals encountered in constant sliding window analysis with wide window size and the high susceptibility to noise encountered in constant sliding window analysis with narrow window size. This method overcomes these shortcomings by dynamically adjusting the window size using the RICI rule. This method extracts information about brain connections for each time sample. Seventy percent of the extracted brain connectivity information is used for training and thirty percent for validation. Classification of the target word is also done and based on the same analysis method. As far as we know, through this research, we have shown for the first time that dynamic connectivity can be used as a parameter for classifying EEG signals.

Keywords: dynamic connectivity analysis, EEG, neural networks, Pearson correlation coefficients

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Authors: Jae Ni Jang, Young Uk Kim

Abstract:

Background: Chat Generative Pre-training Transformer-3 (ChatGPT; San Francisco, California, Open Artificial Intelligence) is an artificial intelligence chatbot based on a large language model designed to generate human-like text. As the usage of ChatGPT is increasing among less knowledgeable patients, medical students, and anesthesia and pain medicine residents or trainees, we aimed to evaluate the accuracy of ChatGPT-3 responses to questions about the American Society of Anesthesiologists (ASA) classification based on patients’ underlying diseases and assess the quality of the generated responses. Methods: A total of 47 questions were submitted to ChatGPT using textual prompts. The questions were designed for ChatGPT-3 to provide answers regarding ASA classification in response to common underlying diseases frequently observed in adult patients. In addition, we created 18 questions regarding the ASA classification for pediatric patients and pregnant women. The accuracy of ChatGPT’s responses was evaluated by cross-referencing with Miller’s Anesthesia, Morgan & Mikhail’s Clinical Anesthesiology, and the American Society of Anesthesiologists’ ASA Physical Status Classification System (2020). Results: Out of the 47 questions pertaining to adults, ChatGPT -3 provided correct answers for only 23, resulting in an accuracy rate of 48.9%. Furthermore, the responses provided by ChatGPT-3 regarding children and pregnant women were mostly inaccurate, as indicated by a 28% accuracy rate (5 out of 18). Conclusions: ChatGPT provided correct responses to questions relevant to the daily clinical routine of anesthesiologists in approximately half of the cases, while the remaining responses contained errors. Therefore, caution is advised when using ChatGPT to retrieve anesthesia-related information. Although ChatGPT may not yet be suitable for clinical settings, we anticipate significant improvements in ChatGPT and other large language models in the near future. Regular assessments of ChatGPT's ASA classification accuracy are essential due to the evolving nature of ChatGPT as an artificial intelligence entity. This is especially important because ChatGPT has a clinically unacceptable rate of error and hallucination, particularly in pediatric patients and pregnant women. The methodology established in this study may be used to continue evaluating ChatGPT.

Keywords: American Society of Anesthesiologists, artificial intelligence, Chat Generative Pre-training Transformer-3, ChatGPT

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Authors: Jongho Park, Junwon Lee, Byeonghyun Choi, Kicheol Lee, Dongwook Kim

Abstract:

The typically-used oil sand plant foundations are driven pile or drilled shaft. With more strict environmental regulations world widely, it became more important to completely remove the foundation during the stage of plant demolition. However, it is difficult to remove driven piles or drilled shafts that are installed at a deeper and stronger depth to gain more bearing pile capacity. The helical pile can be easily removed after its use and recycled; therefore it is suitable for oil sand plant foundation. This study analyzes the behavior of helical piles in sands. Axial pile load tests were carried out the varying spacing of helix plates (helices), rotation speed and weight of axial loading during pile installation. From the experiments, optimal helix plate spacing, rotation speed, axial loading during installation were determined. In addition, the behavior of helical pile groups was examined varying pile spacing. Finally, the behavior of single helical piles and that of group helical piles were compared.

Keywords: oil sand plant, pile load test, helical pile, group helical pile, behavior

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Authors: M. Yusuf

Abstract:

The recent discovery of the phenomenon of RNA interference has led to its application in various aspects of plant improvement. Crops can be modified by engineering novel RNA interference pathways that create small RNA molecules to alter gene expression in crops or plant pests. RNA interference can generate new crop quality traits or provide protection against insects, nematodes and pathogens without introducing new proteins into food and feed products. This is an advantage in contrast with conventional procedures of gene transfer. RNA interference has been used to develop crop varieties resistant to diseases, pathogens and insects. Male sterility has been engineered in plants using RNA interference. Better quality crops have been developed through the application of RNA interference etc. The objective of this paper is to highlight the application of RNA interference in crop improvement and to project its potential future use to solve problems of agricultural production in relation to plant breeding.

Keywords: RNA interference, application, crop Improvement, agricultural production

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Authors: Simin Eydivand, Ali Ghanadieslami, Reza Amiri

Abstract:

Natural gas liquids (NGLs) are light hydrocarbons that are dissolved in associated or non‐associated natural gas in a hydrocarbon reservoir and are produced within a gas stream. There are different ways to calculate the price of NGL. In this study, a spreadsheet calculation method is used for calculation of NGL price with an attractive economy of IRR 25%. For a typical NGL Plant with 3,200,000 t/y capacity of investment and operation of 90% capacity to have IRR 25%, the price of NGL is calculated 277 $/t.

Keywords: natural gas liquid, NGL, LPG, price, NGL fractionation, NF, investment, IRR, NPV

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Authors: Hami Ashraf, Farid Kosari

Abstract:

Graft-versus-host disease (GvHD) is a common complication of allogeneic hematopoietic stem cell transplantation that can lead to significant morbidity and mortality. Histopathological examination of affected tissues is an essential tool for diagnosing and grading GvHD in animal models, which are used to study disease mechanisms and evaluate new therapies. In this systematic review, we identified and analyzed original research articles in PubMed, Scopus, Web of Science, and Google Scholar that described grading systems for GvHD in animal models based on histopathological features. We found that several grading systems have been developed, which vary in the tissues and criteria they assess, the severity scoring scales they use, and the level of detail they provide. Skin, liver, and gut are the most commonly evaluated tissues, but lung and thymus are also included in some systems. Our analysis highlights the need for standardized criteria and consistent use of grading systems to enable comparisons between studies and facilitate the translation of preclinical findings to clinical practice.

Keywords: graft-versus-host disease, GvHD, animal model, histopathology, grading system

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Authors: J. Jayasuriya

Abstract:

In this research paper, a procedure for installing and assessment of a solar PV plant to generate optimal solar energy SPAV hostel at Vijayawada city was analyzed. The hostel was experiencing power disruption and had a need for an unceasing energy source. The solar panel is one of the best solutions to obtain uninterrupted clean renewable energy for an institutional building as it neither makes din nor pollutes the atmosphere. The electricity usage per month was initially measured to discriminate the energy change. The solar array was installed with its financial and environmental assessment considering recent market prices. All the aspects related to a solar PV plant were considered for the feasibility and efficiency of PV plant near this site i.e., the orientation of the site, the size and shape of the terrace, the sun path were considered while installing panels. Various precautions were taken to intercept the factors which cause interference in energy generation, with respect to temperature, overshadowing, the wiring of panels, pollution etc. The solar panels were frequently installed, monitored and maintained properly to procure optimal energy output. Result obtained with the assessment of the proposed plant and deflation in the electric bill will show the maximal energy that can be generated in a month on that particular site.

Keywords: solar efficiency, building sustainability, PV panel, solar energy

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Authors: Tahar Ghnaya, Majda Mnasri, Hanen Zaier, Rim Ghabriche, Chedly Abdelly

Abstract:

It is known that the symbiotic association between plant and microorganisms are beneficial for plant growth and resistance to metal stress. Hence, it was demonstrated that Arbuscular mycorrhizal fungi have a positive effect on host plants growing in metal polluted soils. Legume plants are those which normally associate to rhizobacteria in order to fix atmospheric nitrogen. The aim of this work was to evaluate the effect this type of symbiosis on the tolerance and the accumulation of Cd. We chose Medicago sativa, as a modal for host legume plants and Rhizobium mililoti 2011 as rhizobial strain. Inoculated and non-inoculated plants of M. sativa were submitted during three month to 0, 50, and 100 mgCd/kg dry soil. Results showed that the presence of Cd in the medium induced, in both inoculated and non-inoculated plants, a chlorosis and necrosis. However, these symptoms were more pronounced in non-inoculated plants. The beneficial effect of inoculation of M. sativa with R. meliloti, on plant growth was confirmed by the measurement of biomass production which showed that the symbiotic association between host plant and rhizobacteria alleviates significantly Cd effect on biomass production, so inoculated plants produced more dry weight as compared to non-inoculated ones in the presence of all Cd tretments. On the other hand, under symbiosis conditions, Cd was more accumulated in different plant organs. Hence, in these plants, shoot Cd concentration reached 425 and it was 280 µg/gDW in non-inoculated ones in the presence of 100 ppm Cd. This result suggests that symbiosis enhances the absorption and translocation of Cd in this plant. In nodules and roots, we detected the highest Cd concentrations, demonstrating that these organs are able to concentrate Cd in their tissues. These data confirm that M. sataiva, cultivated in symbiosis with Rhizobium mililoti could be used in phytoextraction of Cd from contaminated soils.

Keywords: Cd, phytoremediation, Medicago sativa, Arbuscular mycorrhizal

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Authors: Rian O. Miranda, Lidia V. de Sa, Julio C. Suita

Abstract:

The Brazilian Nuclear Energy Commission (CNEN) is the main manufacturer of radiopharmaceuticals in Brazil. The Nuclear Engineering Institute (IEN), located at Rio de Janeiro, is one of its main centers of research and production, attending public and private hospitals in the state. This radiopharmaceutical production is used in diagnostic and therapy procedures and allows one and a half million nuclear medicine procedures annually. Despite this, the country is not self-sufficient to meet national demand, creating the need for importation and consequent dependence on other countries. However, IEN facilities were designed in the 60's, and today its structure is inadequate in relation to the good manufacturing practices established by sanitary regulator (ANVISA) and radiological protection leading to the need for a new project. In order to adapt and increase production in the country, a new plant will be built and integrated to the existing facilities with a new 30 MeV Cyclotron that is actually in project detailing process. Thus, it is proposed to survey current CNEN and ANVISA standards for radiopharmaceutical production facilities, as well as the radiological protection analysis of each area of the plant, following good manufacturing practices recommendations adopted nationally besides licensing exigencies for radioactive facilities. In this way, the main requirements for proper operation, equipment location, building materials, area classification, and maintenance program have been implemented. The access controls, interlocks, segregation zones and pass-through boxes integrated into the project were also analyzed. As a result, IEN will in future have the flexibility to produce all necessary radioisotopes for nuclear medicine application, more efficiently by simultaneously bombarding two targets, allowing the simultaneous production of two different radioisotopes, minimizing radiation exposure and saving operating costs.

Keywords: cyclotron, legislation, norms, production, radiopharmaceuticals

Procedia PDF Downloads 133