A BRIEF KNOWLEDGE OF BANAFSHA (VIOLA ODORATA LINN.) & OTHER VIOLA SPECIES

All over the world Viola genus in the Violet family Violaceae is broadly distributed. It is the largest genus in the family containing 500 species. Products isolated from them as are- Essential oils, Glycosides (Iridin, Violaquercitrin, Violutoside), Carbohydrate (Inulin), Ester (Methyl salicylate), Mustard oil (Phenyl ethyl), Colouring matters (Luteolin, Quercetin) etc. Importance of Violaceae family in traditional medicines has been mentioned. Many medicinal herbs used for therapeutic applications such as act as blood purifier, treatment of bruises, ulcers, respiratory infections, renal disorders etc belong to this family. Viola odorata also known as sweet violet & it is a rich source of vitamin c. Traditionally is very much effective in jaundice, anti-inflammatory, anti-pyretic, anti bacterial, hepato-protective activity. Viola odorata syrup made from flower petals improves cough suppression in children with asthma. Intranasal administration of Viola odorata extract oil is sedative to the brain and is helpful in insomnia suffering patients. A Unani medicine named as Joshanda used in form of decoction for cough & colds contain this valuable herb. In Chinese system of medicine it has been prescribed against Cancerous growth. In France Viola syrup is used as cough remedy. Cultivation of Violets in England occurs largely Startford-upon-Avon for syrup formation, which when mixed with Almond oil used as laxative in children. In olden time it was believed that Viola flowers are beneficial for eyes. Traditional knowledge when tested Pharmacologically & Phyto-chemically it will give us new effective therapeutic agents. This article is compilation of different aspect of Viola odorata and other Viola species such as their botanical classification, morphological feature, geographical distribution, chemical constituents, pharmacological properties and ethno-medicinal uses.&nbsp

Tuberculosis shoulder: a diagnostic dilemma

Tuberculosis of the shoulder can be difficult to diagnose in the early stages. If not diagnosed early, bony tuberculosis may reduce quality of life. Therefore, tuberculosis should be suspected in cases of long standings pain in the shoulder. we report a case of a female patient presenting to us after 18 months of initiations of symptoms suggestive of periarthritis of shoulder. Failure of conservative therapy and worsening of symptoms she needed further investigation and surgical management. With Biopsy she was diagnosed tuberculosis shoulder, TB shoulder to be a case of tuberculosis shoulder. The patient had a good recovery functionally following debridement and ATT. Thus, TB shoulder can also present as a case of periarteritis shoulder making its diagnosis at early stages difficult

THERAPEUTIC SIGNIFICANCE OF FENUGREEK W.S.R TO ITS HYPOLIPIDEMIC ACTIVITY

The term Hyperlipidemia denotes excessive cholesterol in the blood. It is both LDL and triglycerides that are elevated in hyperlipidemia. As per Ayurveda, In Hyperlipidemia, Medodhatu vitiates because of improper working of Parthiva and Aapbhutagni rasa and Medodhatvagni. Mainly Asthivahasrotas are affected. Asthivahasrotas build from Medo and Jaghan part. Fenugreek having lipolytic property and it primarily works on Annahvahasrotas and Asthivahasrotas. It decreases cholesterol level, reduces body weight by decreasing plasma triglycerides and having hepatoprotective effect. Fenugreek (Trigonella foenum graecum) commonly known as Methi, family Fabaceae is a annual plant, cultivated world wide as a semiarid crop. The seeds of fenugreek are used as condiment and dried leaves as flavouring agent. Vegetative parts are rich in vit A, vit B and iron. Constituents of fenugreek seeds include flavonoids, alkaloids, coumarins, saponins; most prevalent alkaloid is trigonelline and coumarins include cinnamic acid and scopoletin. In southern part of india roasted seeds in the form of infusion are indicated in diarrhoea and small pox. It is an appetizer and carminative. Its porridge is used as galactagogue. Having antidiabetic, antiallergic, lactation induced, anti-oxidant potency. In this article we are going to discuss about fenugreek in all aspects including its Anti-hyperlipidemic action

Primary Chondrosarcoma in L-shaped Crossed Fused Renal Ectopia Coexisting with Papillary Urothelial Carcinoma in Urinary Bladder – An Enigmatic Entity with Poor Prognosis

Primary renal chondrosarcomas are rare tumors that are high-grade in nature and, unfortunately, have poorly understood pathogenesis and extremely low prognosis. The coexistence of a discrete malignancy in the urinary bladder is even rarer, with the occurrence of distinct papillary urothelial carcinoma in the urinary bladder in this case. The clinical presentation is nonspecific, and the primary radiological investigations have a limited scope in providing specific diagnosis of this entity. The final diagnosis is possible on thorough histopathological examination of the resected specimen, which requires extensive sampling and meticulous reporting. As of now, the only way to achieve a better prognosis is by early diagnosis. It is necessary to keep the possibility of occurrence of sarcomas at rare sites in the differential diagnoses. The cytogenetic and molecular abnormalities associated with this entity need to be elucidated to achieve a more satisfactory outcome concerning the overall management of the patient

CIFKAS A Measurer of Functional Disability Status in Knee Osteoarthritis

Knee osteoarthritis (OA) results in structural and functional abnormalities and reduced functional performance abilities. In developing countries majority of population lives in rural areas having limited resources and socio-cultural biodiversity. Their personal, socio-cultural and occupational habits vary and need to be addressed. So a culturally relevant and contextually appropriate, Composite Indian Functional Knee Assessment Scale (CIFKAS) for measuring the functional status in knee osteoarthritis was formulated. 128 participants from various geographical regions of India of age range 40 to 60 years using convenient sampling were included and informed consent signed by the participants. Each participant was assigned to one of the two groups. 39 participants in group A reported no episode of knee pain while 89 participants in group B reported at least one episode of knee pain in the last two months. Each participant was assessed on Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) and CIFKAS and statistical analysis was done. The Pearson correlation coefficient calculated for all 128 subjects for pain, physical functional abilities and total functional disability score were 0.878, 0.925 and 0.945 respectively. Between group analysis was done using Independent t test and p value was found to be not significant for pain (≤178), highly significant for physical functional abilities (p≤0001) and very significant for total functional disability status score (p≤004). The results indicate that both WOMAC and CIFKAS are highly correlated and there is no difference between the two for measuring pain, but for functional ability and overall functional disability status within their functional context, CIFKAS is a better tool than WOMAC.KEYWORDS: Knee osteoarthritis; Functional disability; Socio-cultural biodiversities; Functional contextInternet Journal of Medical Update 2012 January;7(1):47-5

Poor emotional responsiveness in clinical hypertension:Reduced accuracy in the labelling and matching of emotional faces amongst individuals with hypertension and prehypertension

Tese de Doutoramento em Engenharia Mecânica, no ramo de Gestão e Robótica Industrial, apresentada ao Departamento de Engenharia Mecânica da Faculdade de Ciências e Tecnologia da Universidade de CoimbraA presente tese foca-se na integração e avaliação de metodologias distintas com o objetivo de fazer a deteção de limões nas árvores em cenários naturais, ou seja, de cenários com iluminação não controlada. A proposta apresentada dista das restantes abordagens, discutida na revisão bibliográfica, por ser endereçada a um fruto até agora não avaliado e por apostar num sistema de visão artificial simples, passível de ser aplicado em contexto real de trabalho. De acordo com o estado da arte, os métodos de aprendizagem supervisionada são os mais eficazes na segmentação e deteção dos frutos nas condições precedentes. Com base neste pressuposto foi criada uma base de dados de referência, composta por cinco classes de elementos, para treino e avaliação dos classificadores SVM na segmentação das imagens. Adicionalmente, um outro conjunto de imagens é usado para avaliar a deteção dos frutos através de classificadores baseados nos métodos de Haar, HOG e LBP. A segmentação inicial das imagens é realizada a partir de uma árvore de decisão, em que é avaliada a resposta do modelo a um classificador SVM denominado global, treinado segundo a estratégia um contra todos, e a outros dois modelos compostos por vários classificadores SVM, treinados com a estratégia um contra um. Em qualquer um destes casos, o objetivo é separar os pixels dos limões da restante imagem, pelo que, no final, a avaliação do desempenho dos modelos de classificação é realizada considerando apenas duas classes de elementos (C=2), a classe dos limões e a classe do background. Devido à elevada quantidade de combinações possíveis de características de cor e parametrizações do SVM é proposto um método que convirja para as soluções de classificação ótimas. Além disso, este método é responsável pela determinação das características, aparentemente mais significativas para a correta segmentação dos frutos, ao longo dos vários estágios de treino em que se incrementa o número de características a analisar. Com as imagens segmentadas são avaliadas as respostas de diversos classificadores na deteção dos frutos nas árvores, onde se conclui que os métodos de Haar e HOG permitem melhores resultados do que os classificadores LBP, contrariamente ao que seria esperado, de acordo com a bibliografia revista. A metodologia de segmentação dos frutos proposta, para as 133 imagens de teste, apresenta uma taxa média de TP = 93.14 % para uma taxa de FP = 2.34 %, através da aplicação do classificador SVM, designado de global. Este processo de segmentação tem um tempo de execução, em média, de 145 ms. Relativamente à deteção dos limões, a configuração que resulta na maior deteção dos frutos visíveis nas 44 imagens apresenta como desempenho uma Precision = 80.19 % e Recall = 92.39 %, atingidos por um classificador de Haar executado, em média com uma duração de 36 ms por imagem; porém, se para a aplicação final for mais relevante a menor ocorrência de falsos-alarmes, o melhor modelo de classificação é obtido com a metodologia HOG, executada em 50 ms, onde se obtém uma Precision = 85.37 % e Recall = 76.09 %. Os resultados alcançados por um simples sistema de visão artificial, apenas com aquisição de imagens a cores no espectro visível, estão ao nível dos melhores resultados alcançados e identificados na literatura revista. Excetuam-se apenas os resultados conseguidos pela introdução de modelos de Deep Learning. Apesar dos resultados alcançados, e em função dos modelos de cor usados para atenuar os impactos das variações das condições de luz, é admissível que a metodologia proposta possa falhar em condições de iluminação deficiente. Nestes casos é recomendável a utilização de iluminação artificial, que poderá até aumentar o contraste entre os frutos e os restantes elementos captados nas imagens. Além disso é benéfica a introdução de metodologias que permitam a correta de deteção de frutos que se encontrem parcialmente sobrepostos.This thesis is focused on the integration and evaluation of several methodologies aiming to detect lemons on trees in natural outdoor scenarios, without controlled light conditions. Current approach is different from the previous ones identified on literature, because it addresses a fruit not evaluated before using a simple vision system, which only acquire RGB images, suitable for real tasks conditions. Based on state of the art review, the supervised learning methods are more effective than the unsupervised ones to segment and detect fruits in uncontrolled light scenarios. Considering such previous findings, it is created a reference database of lemons fruits scenarios to train, validate and test SVM classifiers and also to evaluate the performance of Haar, HOG and LBP classifiers. Segmentation of citrus fruits is performed by a decision tree and three different schemes of SVM classifiers: through a global classifier trained by the strategy of one vs all; and through two sets of SVM classifiers, trained differently, by the strategy one vs one. The final performance evaluation is a two class problem, because only interests to distinguish between the remaining scenario and lemons in each image. To avoid constraints from light changes on RGB color space, all simulations are performed using color components from YCbCr, HSV and chromaticity color spaces. Additionally, they were created two color indexes derived from chromaticity color space. Evaluating all combinations of color components plus SVM parameters by brute-force methods, it is an inefficient process. So, it is proposed a method based on hill-climbing algorithm that converge to the optimal configuration on SVM parametrization. After each stage of training and aiming to increase the number of features evaluated by SVM, it is proposed a method that filter the best set of features for further evaluations based on AUC (Area Under the Curve) results. Since the ground truth database is not extensive as desired and its population contains some noise, it is proposed another method to split the data to train, validate and test the classifiers, instead of traditional k-fold. According to achieved results, this proposal fits well on the presented case. Using the SVM-based segmented images, they are evaluated the Haar, HOG and LBP classifiers to perform the fruits detection. In opposition to previous findings, Haar and HOG classifiers performs better than LBP. For the 133 images used to test segmentation methods, the best response is achieved by the global classifier related to true-positive rate of 93.14 % and a false-positive rate of 2.34 %. For such configuration, the segmentation is performed by 145 ms on average. About detection, the best Recall of 92.39 % corresponds to a Precision of 80.19 % achieved by Haar classifiers, executed in 36 ms. If the precision is relevant for a specific application, the best result corresponds to the use of HOG classifiers that response with a Precision of 85.37 % to a Recall of 76.09 %, executed on 47 ms on average per image. Current results achieved by a simple vision system and by acquiring only RGB images are similar to the state of the art results, except when compared to Deep Learning methods whose perform better but also more computationally demanding to train. Notwithstanding promising results, the proposed methodology tends to fail when exposed to low light scenarios. In such conditions it is highly advisable to use controlled external light sources, not only to compensate the low light conditions, but also to enhance the contrast between fruits and the remaining scenario. Additionally, it may be useful the introduction of new methods in order to detect correctly individual fruits grouped.FCT – Fundação para a Ciência e a Tecnologia, projeto: UID/EMS/00285/201

Verticillium lecani (Zimm.): A potential entomopathogenic fungus

Abstract Development of insect resistance and risk to the environment due to indiscriminate use of conventional chemical pesticides for insect pest management favored the introduction of one of the new alternatives as biological control. Entomopathogenic fungi are one of the most versatile biological control agents for sustainable management. The most considerable fungal species are Metarhizium spp., Beauveria spp., Nomuraea rileyi, Verticillium lecanii and Hirsutella spp. Out of these fungi, V, lecanii are opportunistic and widely distributed ascomycete fungi that has the ability to cause mycosis in a number of insects of orders Homoptera, Coleoptera and Lepidoptera. V. lecanii are easy to mass produce, store and are effective over a wide range of temperatures and humidity levels. It also provides a rapid kill at optimum doses and the fungus has been recently commercialized as a microbial agent for pest management. It has the additional features to produce extracelullar enzymes, such as chitinases which helps in promoting host colonization. It also shows compatibility with commonly used agrochemicals such as insecticides or fungicides and other biocontrol agents. Because of these numerous advantages, it can be considered as a potential biocontrol agent's in integrated pest management. Highlights • Verticillium lecanii as a potential entomopathogenic fungus and its mass productio

Epidemiology and Clinicopathological Profile of Renal Cell Carcinoma: A Review from Tertiary Care Referral Centre

Renal cell carcinoma (RCC) accounts for 3% of all adult cancers and 85% of all kidney tumours. Incidence of RCC is lower in Asian region, particularly in India, probably due to lack of reporting. Most of the data about RCC are from Western countries; and data from India are scarce, especially regarding para-neoplastic syndromes. We sought to determine the epidemiology, clinicopathological profile and management of RCCin a tertiary care centre in Western India. This was a retrospective study that involved data analysis of records of RCC patients who presented to our institution from April 2016 to February 2020. Laboratory investigations, including tests for paraneoplastic syndrome (PNS), and relevant radiologic investigations were performed and treatment was offered according to the stage, patient factors and available modalities. A total 142 RCC patients were included in the study. The median age of presentation was 58 years. Most of the patients (67%) were symptomatic, and 33% of the patients were asymptomatic, and the RCC was diagnosed incidentally. A large number of patients (56.3%) had PNS. The most common histopathologic type of RCC was clear cell carcinoma (68.8%), followed by papillary (20%) and chromophobe (8%) carcinoma. 40% of carcinomas with sarcomatoid differentiation were seen in patients under 50 years of age. Two cases of multicystic RCC were both seen in patients less than 50 years of age. 65.5% of the patients presented at Stage 1 and 2. Most surgeries (71.2%) were done in a minimally invasive manner. A significant number of patients were asymptomatic, in which RCC was detected incidentally. The age of presentation was earlier, yet the patients had a higher tumour stage. More than half of the patients had PNSs. Despite growing trend towards Western data, the significantly higher number of patients with PNSs and early age of presentation suggest inherent differences in tumour biology, possibly related to differences in genetic and environmental factors

Hardware implementation of intelligent systems

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