Search

Byline: Sachin. Gupta, Varniraj. Patel, Shivangi. Garg, Nikhil. Mehta Sir, GM1-gangliosidosis is a rare autosomal recessive lysosomal storage disorder characterized by a deficiency of the ß-galactosidase enzyme. Patients with GM1-gangliosidosis [...]

Switched Reluctance Motor (SRM) is one of the best alternative motor drives for induction and synchronous drives in present trends. However, the SRM can able to replace those synchronous and inductance machine by using effective controller for many applications. Apart from many controllers, Direct Torque Controller (DTC) has received much attention from researchers in these days due to its high superiority characteristics over other controllers. Moreover, compare to Proportional and Integral (PI) controller a Fuzzy controller can provide effective support to DTC during intermittent changes of speed and torque. Hence, Fuzzy controller based DTC has been implemented in this paper for novel configuration of converter to drive SRM. Generally more number of switches leads to more cost and poor performance. Therefore, a novel configuration of converter has been proposed in this paper for DTC of SRM. For analysis of system, the proposed method has been compared with vector based controller in this paper. The extensive results are presented to validate the proposed method for both the steady state and transient periods.

In recent years, advances in the surgical treatment of adult spinal deformity (ASD) have led to improved outcomes. Although these advances have helped drive the development of deformity surgery to meet the rising volume of patients seeking surgical treatment, many challenges have yet to be solved. Instrumentation failure remains one of the most common major complications following deformity surgery, associated with significant morbidity due to elevated re-operation rates among those experiencing mechanical complications. The two most frequently encountered subtypes of instrumentation failure are rod fracture (RF) and proximal junctional kyphosis/proximal junctional failure (PJK/PJF). While RF and PJK/PJF are both modes of instrumentation failure, they are two distinct entities with different clinical implications and treatment strategies. Considering that RF and PJK/PJF continue to represent a major challenge for patients with ASD and deformity surgeons alike, this review aims to discuss the incidence, risk factors, clinical impact, treatment strategies, preventive measures, and future research directions for each of these substantial complications. [ABSTRACT FROM AUTHOR]

Plant leaf diseases are challenging to categorize due to the complexity of the pattern variations and the high degrees of inter‐class similarity. Plant ailments harm food quality and production. To ensure the quality and quantity of harvests, it is essential to protect plants from disease. Detection of diseases at an early stage is the main and the most complex task for farmers due to common morphological properties like colour, shape, texture, and edges. In this study, a Hybrid Deep Learning model named Hybrid‐Convolutional Support Machine (H‐CSM) based on 'Support Vector Machine (SVM)', 'Convolutional Neural Network (CNN)' and 'Convolutional Block Attention Module (CBAM)' is proposed for the early diagnosis and classification of leaf diseases in plants leaf. The suggested model can initially identify different plant leaf illnesses, although it is not constrained to these. A database of pictures of plant leaves is used to test the suggested method based on different evaluation parameters. The results were highly promising, with an accuracy of up to 98.72% which has been increased by applying better learning methods. Farmers can quickly identify 36 common diseases with a little instruction for 14 plant categories, enabling them to take prompt preventive measures using the proposed method. [ABSTRACT FROM AUTHOR]

Aim: This study aimed to investigate the selection of postendodontic restorative materials and techniques for both anterior and posterior teeth by Indian endodontists and nonendodontists, along with other influencing factors. Methods: A total of 700 dentists, including both endodontists and nonendodontists, participated in this survey. The survey consisted of 22 questions and was administered through Google Forms and various online platforms. Participants were required to provide informed consent before completing the questionnaire. Results: The majority of endodontists (80.3%) and nonendodontists (72.6%) revealed a preference for resin composite as the primary restorative material for postendodontic restoration. Approximately half of the endodontists (50.0%) and 67.8% of nonendodontists typically waited for 1 week before proceeding with postendodontic restoration, with the presence of periapical lesions being the most common reason for this delay. Both endodontists (81.7%) and nonendodontists (73.4%) considered the amount of remaining tooth structure as the most crucial factor in guiding their choice of postendodontic restoration. The majority of both endodontists (75.3%) and nonendodontists (81.4%) preferred full-coverage crowns as the definitive postendodontic restoration. Furthermore, endodontists (95.4%) and nonendodontists (85.5%) reported that they only performed post and core restoration when necessary, and 84.7% of endodontists and 76.5% of nonendodontists believed that post and core restorations aided in supporting crowns. Conclusion: The outcomes of the survey imply that while endodontists in India demonstrate a more comprehensive comprehension of postendodontic restoration concepts, nonendodontists also exhibit a sufficient level of understanding essential for achieving clinical success. [ABSTRACT FROM AUTHOR]

Most textile manufacturing companies in the world heavily rely on manual labor, particularly in the fabric inspection section, especially for cotton fabric. Establishing smart manufacturing systems like industrial automation in the textile industry for cotton fabric inspection is important for error-free inspection. The proposed make-to-order (MTO) inventory model focuses on the strategic development of a supply chain network under fuzzy uncertainty. The distinctiveness of this research lies in integrating a methodology that involves human and machine interaction, along with allocating resources to investment in smart manufacturing. This article presents a case study of the Jagatjit Cotton Textiles (JCT) manufacturing company in Punjab, India, as an example to validate the model and check the performance of SMT in the fabric inspection process in cotton TC mills. This paper contributes by developing four distinct textile supply chain models with industrial automation under triangular and trapezoidal fuzzy demand. A numerical analysis is conducted to verify the effectiveness of installing automated fabric inspection machines in the cotton plant. This article proposes an iterative solution algorithm (KDPMG) to obtain the global optimum for the proposed model. A comparative study of the proposed algorithm, KDPMG, and the genetic algorithm (GA) is presented in this study to verify the credibility of the obtained results. It is observed that KDPMG provides more appropriate solutions to the problem compared to the GA. Moreover, the computational time of KDPMG is significantly less than that of the GA. The rigorous analysis reveals that maximum profit can be achieved under trapezoidal fuzzy demand with fully automated fabric inspection technology. Using a triangular fuzzy demand pattern, the model with fully automated smart manufacturing achieves an 8.62% higher profit compared to a traditional system. Similarly, in the case of a trapezoidal fuzzy demand pattern, the adoption of automation in cotton plants can achieve an 8.69% higher profit. Hence, the implementation of smart manufacturing systems in the mending section of the cotton textile industry proves to be more profitable compared to the traditional inspection process. [ABSTRACT FROM AUTHOR]

This article discusses a case of erythema elevatum diutinum (EED) associated with peripheral ulcerative keratitis (PUK) in a 61-year-old Chinese man. The patient presented with painful skin lesions on various parts of his body, which worsened in cold weather. He also experienced recurrent ocular symptoms, including hyperemia and blurred vision. The diagnosis of EED with PUK was established based on clinical and histopathological features. Erythema elevatum diutinum is a rare condition characterized by neutrophilic infiltration in the skin and other organs. [Extracted from the article]