Real-time delay-multiply-and-sum beamforming with coherence factor for in vivo clinical photoacoustic imaging of humans

In the clinical photoacoustic (PA) imaging, ultrasound (US) array transducers are typically used to provide B-mode images in real-time. To form a B-mode image, delay-and-sum (DAS) beamforming algorithm is the most commonly used algorithm because of its ease of implementation. However, this algorithm suffers from low image resolution and low contrast drawbacks. To address this issue, delay-multiply-and-sum (DMAS) beamforming algorithm has been developed to provide enhanced image quality with higher contrast, and narrower main lobe compared but has limitations on the imaging speed for clinical applications. In this paper, we present an enhanced real-time DMAS algorithm with modified coherence factor (CF) for clinical PA imaging of humans in vivo. Our algorithm improves the lateral resolution and signal-to-noise ratio (SNR) of original DMAS beam-former by suppressing the background noise and side lobes using the coherence of received signals. We optimized the computations of the proposed DMAS with CF (DMAS-CF) to achieve real-time frame rate imaging on a graphics processing unit (GPU). To evaluate the proposed algorithm, we implemented DAS and DMAS with/without CF on a clinical US/PA imaging system and quantitatively assessed their processing speed and image quality. The processing time to reconstruct one B-mode image using DAS, DAS with CF (DAS-CF), DMAS, and DMAS-CF algorithms was 7.5, 7.6, 11.1, and 11.3 ms, respectively, all achieving the real-time imaging frame rate. In terms of the image quality, the proposed DMAS-CF algorithm improved the lateral resolution and SNR by 55.4% and 93.6 dB, respectively, compared to the DAS algorithm in the phantom imaging experiments. We believe the proposed DMAS-CF algorithm and its real-time implementation contributes significantly to the improvement of imaging quality of clinical US/PA imaging system.11Ysciescopu

In Vivo Photoacoustic Imaging of Anterior Ocular Vasculature: A Random Sample Consensus Approach

Visualizing ocular vasculature is important in clinical ophthalmology because ocular circulation abnormalities are early signs of ocular diseases. Photoacoustic microscopy (PAM) images the ocular vasculature without using exogenous contrast agents, avoiding associated side effects. Moreover, 3D PAM images can be useful in understanding vessel-related eye disease. However, the complex structure of the multi-layered vessels still present challenges in evaluating ocular vasculature. In this study, we demonstrate a new method to evaluate blood circulation in the eye by combining in vivo PAM imaging and an ocular surface estimation method based on a machine learning algorithm: a random sample consensus algorithm. By using the developed estimation method, we were able to visualize the PA ocular vascular image intuitively and demonstrate layer-by-layer analysis of injured ocular vasculature. We believe that our method can provide more accurate evaluations of the eye circulation in ophthalmic applications. ? The Author(s) 2017.1110Ysciescopu

Motor starting with shunt capacitors: An alternate approach to voltage dip control

Induction motors are known to cause undesirable voltage dip because of high inrush current during starting, especially when fed from weak AC systems. For this reason, large motors are often started with reduced voltage. This thesis proposes full-voltage motor starting with shunt capacitors. Two types of capacitors are used: power factor correction capacitor and start capacitor. The start capacitor is determined to maximize the input impedance during starting in order to reduce the initial inrush current. The analysis shows that shunt capacitors improve the voltage dip and the motor acceleration significantly but introduce some level of waveform distortion during each starting period. The start capacitor is found to be very effective in voltage control, but additional components such as damping resistor must be added to effectively reduce the waveform distortion. A centrifugal switch is used to replace the start capacitor and damping resistor by a power factor correction capacitor as the motor reaches a predetermined speed. The feasibility of the proposed scheme is proven through a mathematical model and associated computer simulations. The simulation results are verified by laboratory experiments

Arkapushpa Taila - Pharmaceutical review w.s.r. to Artavakshaya

Women undergo rhythmic and periodic changes in the body that reflect and maintain fertility. These changes are externally visible as menstrual cycle. Menstruation is affected by a multitude of factors. There are issues related to menstruation that affect other systems and vice versa. It could also lead to sub fertility and infertility. Artavakshaya is one among those, where the menstruation is affected. Even though it is not mentioned separately as a disease but it appears as a symptom in many of the gynaecological disorders like oligomenorrhea / hypomenorrhea. In Ayurveda we have plenty of Dravyas and Yogas which help to treat the same. Even though we have plenty of options there are many formulations which are not yet explored, Arka (Calotropis procera) is one among them. We get reference of Arkapushpa Taila from Bharata Bhaishajya Ratnakara for Rudhirasrava. This basic concept is taken and an effort is made to understand the utility of this Taila in Artavakshaya. Even though the drug Arka is widely available, the unavailability of Arkapushpa Taila in the market made to prepare the Arkapushpa Taila and see the efficacy, difficulty and clinical utility of it

Deep feature representation for automated plant species classification from leaf images

Automated plant species classification using leaf images holds immense potential for advancing agricultural research, biodiversity conservation, and ecological monitoring. This study introduces a novel approach leveraging deep feature representation to achieve accurate and efficient classification based on leaf morphology. Convolutional neural networks (CNNs), including VGG16, ResNet50, DenseNet1, Inception, and Xception, are employed to extract high-level features from leaf images, capturing intricate patterns essential for species differentiation. To manage the extensive feature set extracted by these models, optimization techniques such as principal component analysis (PCA), variance thresholding, and recursive feature elimination (RFE) are applied. These methods streamline the feature set, making the classification process more efficient. The optimized features are then trained using classifiers like support vector machine (SVM), k-nearest neighbors (K-NN), decision trees (DT), and naive Bayes (NB), achieving average accuracies of 98.6%, 96.6%, 99.6%, and 99.7%, respectively, across various cross-validation methods. Experimental results on benchmark datasets demonstrate the effectiveness of this approach, achieving state-of-the-art performance in plant species classification. This work underscores the potential of deep feature representation in automated plant species classification, offering valuable insights for applications in agriculture, ecology, and environmental science

A study of clinical and etiological profile of mitral valve dysfunction

Background: Heart valve diseases are a leading cause of cardiovascular morbidity and mortality globally; putting a significant strain on healthcare resources. In developing countries, rheumatic heart disease (RHD) remains the most common type of heart valve disease. Mitral valve disease is the most frequent of the valvular heart diseases. Mitral valve disease is a distressing and painful condition, and requires immediate attention before they result in death. Methods: This was a prospective observational study done from September 2019 to February 2021, at the Department of General Medicine, Goa Medical College and Hospital, Bambolim, Goa: A tertiary care hospital in Goa. Results: Out of the 50 patients enrolled in the study 44% patients had MS ,18% had MR and 38%had MR+MS. Mean age of the study population was 41 to 50 years of which 54% patients were females. All isolated Mitral Stenosis patients were rheumatic origin. Of the 9 MR patients, predominant form of MR was ischemic (66.66%), followed by rheumatic (22.22%) and MVP (11.11%). 19 patients had MR+MS, predominant form was rheumatic (84.21%). It was also observed that 42% each of total patients had pulmonary hypertension and congestive cardiac failure, 40% had pulmonary edema, while 30% had atrial fibrillations complications. Conclusions: Our study revealed that the most common valve dysfunction observed is mitral stenosis, with a female preponderance and its most common etiology being rheumatic. Further it was also observed that the most common complication is pulmonary hypertension and congestive cardiac failure

Constraints in Organizations of Agricultural Knowledge Creation, Information Management and Technology Delivery System in Bundelkhand Region of Uttar Pradesh, India

The present study was conducted to delineate the various constraints faced by the institutions doing agricultural knowledge, information management, and technology delivery. The Bundelkhand Region of U.P. was purposively chosen for this study because of the presence of  major institutes  such as  the Indian Grassland and Fodder Research Institute (IGFRI), Central Agroforestry Research Institute and agricultural universities located in Banda and Jhansi, ICAR KVKs, state government line departments, ATMA and many related NGOs. Secondary data were collected through the study of extant literature.  Identified major constraints were sorted out with the help of experts. Primary data was collected from officials of every organization through direct personal interviews and focussed group discussions. The total sample size was 50. The constraints were grouped into three categories; that is, constraints in knowledge creation, information management, and technology delivery. Rank Based Quotient (RBQ) method was used to quantify the responses, in order to establish the major constraints with severe effects. Findings revealed there is a need for knowledge experts to periodically train the work-force of the sampled organizations to update the skill of the scientists. Such up scaling of employees’ knowledge would increase digitalization, improve effective management of information; enhance coordination among different organizations while reducing duplicative efforts or misplaced efforts

Artificial neural network-based intelligent sensor-based electronic nose for food applications

Food commerce, especially for the general public, is greatly impacted by the capacity to identify and recognize chemical samples for food applications. Every chemical sample response has a unique, distinguishing smell. These advancements highlight the method of an artificial neural networks (ANN) to distinguish the distinctive fragrance from the reaction of substances. The categorization of various smell patterns has diminished confidence in ANN technology. Using an ANN technique and a sensor-based e-nose system for food applications, each chemical’s identification has been done commercially. The system comprises a 5-gas sensor selection that recognizes chemical talk while allowing for an improvement in permitting while falling gas is planned outside. To build a model of a different signal reaction, individual sensors are equally collected and merged into the innovation -favored sensor array. Demonstrates how it is related to the chemical test. The e-nose categorization has been tested with five different chemical samples and five different sensor classes. The e-nose approach, which comprises five sensors, can classify each chemical reaction model, starting with the results. With more sensors being employed, the classification accuracy of the precise chemical reaction improves. These data demonstrate that the ANN-based e-nose method promises a successful classification system for chemical sample responses for a characteristic odor sample

Overview of Mechanical Characterization of Bone using Nanoindentation Technique and Its Applications

The nanoindentation has proved to be a most promising technique in the investigation of the bone at the level of individual osteons and lamellae. It provides the nanomechanical properties of bone at submicron levels without being affected by its size, shape, and porosity. Its application in the study of bone requires the understanding of its functionality, modes, and influencing factors that have an impact on the outcome of the investigation. This necessitates a comprehensive a review. In the recent past, considerable attention is also paid to the elastic, time-dependent or viscoelastic response of the bone by conducting static, creep and nano-dynamic mechanical analysis (Nano-DMA) studies. Studies have also shown that at submicron levels, the mechanical properties of bone differ depending on the location and direction of testing within the bone, and among the individuals. Also, the impact of diseases progression and treatment procedures can be understood from variation in the biomechanical properties. This review focuses on the nanoindentation technique, its relevant modes used in the bone study, popular contact models used in the data analysis, various influencing parameters, recent applications such as the effect of aging, cancer, various diseases, and potential role in clinical studies such as to understand the effect of the treatment processes.</p

A VERY INFREQUENT ASSOCIATION OF WILLIAM-BEURAN SYNDROME AND TETRALOGY OF FALLOT

WB-S Autosomal Dominant Disorder is the most common genetic disorder. We report a case of 20 year old with infrequent association of WBS and TOF. Clinical examination and ECHO confirmed TOF, WB-S was suspected based on the clinical signs used in the scoring system of WB-S which were described by AAP(2001), FISH study was performed in this patient because of having more than 3 clinical signs of WB-S and FISH study showed 7q11.23 deletion and remains the gold standard laboratory investigation for WB-S. KEYWORDS:&nbsp;Tetralogy of Fallot; William Beuren Syndrome; Clinical Diagnosis; Fluroscence In Situ Hybridisation