UWB Based Static Gesture Classification

Our paper presents a robust framework for UWB-based static gesture recognition, leveraging proprietary UWB radar sensor technology. Extensive data collection efforts were undertaken to compile datasets containing five commonly used gestures. Our approach involves a comprehensive data pre-processing pipeline that encompasses outlier handling, aspect ratio-preserving resizing, and false-color image transformation. Both CNN and MobileNet models were trained on the processed images. Remarkably, our best-performing model achieved an accuracy of 96.78%. Additionally, we developed a user-friendly GUI framework to assess the model's system resource usage and processing times, which revealed low memory utilization and real-time task completion in under one second. This research marks a significant step towards enhancing static gesture recognition using UWB technology, promising practical applications in various domains

Fertility benefits of controlled ovarian stimulation and intrauterine insemination in different stages of endometriosis in a fertility centre in Southern India: a retrospective study

Background: To determine the fertility benefit of controlled ovarian hyperstimulation and intra uterine insemination (IUI) in different stages of Endometriosis. It was a retrospective observational study done in Kinder women’s hospital and fertility centre, Cherthala, Kerala, India.Methods: A retrospective analysis of 100 patients with isolated endometriosis (I and II vs. III and IV) who underwent IUI between January 2018 to December 2019 were selected. Cycle fecundity rates and clinical pregnancy rates and pregnancies above 28 weeks were measured. Clinical pregnancy rates with COH and IUI were also compared between grade I/II vs III/IV endometriosis.Results: A total of 16 (16%) pregnancy were achieved with controlled ovarian hyperstimulation (COH) and IUI in patients with endometriosis which included 11 (11%) clinical pregnancies and 5 (5%) miscarriages. 10% clinical pregnancies were achieved in grade I/II endometriosis and 1% in grade III/IV endometriosis. 68.75% of the pregnant patients progressed to pregnancy of >28 weeks.Conclusions: The grade of endometriosis affected the clinical pregnancy rate in COH with IUI. The treatment success of COH with IUI was noted to be greater in minimum or mild endometriosis i.e., grade I/II. The treatment modality is ineffective in moderate to severe grades of endometriosis i.e., III/IV

An unusual case of interstitial pregnancy: a case report

Ectopic pregnancy (EP) has been found to be a common cause of morbidity, and on occasion, mortality among women in the reproductive age groups. The incidence of EP is 1-2% of all pregnancies. 93-97% of EP are tubal with the interstitial type consisting only 3-4%. A 31-year-old female patient with primary infertility underwent IVF (In Vitro Fertilization). Pregnancy was confirmed by βHCG (beta human chorionic gonadotropin). Her ultrasonography reported a mass in the right cornual region. The uterine cavity was empty. Laparoscopy was performed followed by resection of the right cornua with tubes. Histopathology report confirmed the diagnosis of Interstitial Pregnancy (IP). The patient had an uneventful post-operative period and was discharged the next day. EP is a common complication seen in cases undergoing IVF, and IP is a rare form of EP. Hence, early diagnosis and prompt intervention is required to avoid a potentially life-threatening situation

Medicago truncatula symbiosis mutants affected in the interaction with a biotrophic root pathogen.

Understanding how plants balance between enabling microbial symbionts and fending off pathogens has direct implications both for basic plant biology and optimal use of crop plants in agriculture. The degree to which the processes associated with these two types of interactions overlap is poorly known. Recent studies revealed that symbiotic and pathogenic filamentous microbes require common plant genetic elements to establish colonisation (Wang et al., 2012; Rey et al., 2013), supporting the long-held view that plants have evolved the ability to accommodate microbes (Parniske, 2000) and that pathogens have exploited these pathways. However, the extent to which plant genes implicated in fungal or bacterial symbioses are involved in interactions with biotrophic pathogens is unknown and research has been hampered by the lack of suitable common host experimental systems. P. palmivora, a root-infecting oomycete, is an aggressive biotrophic pathogen of M. truncatula, a model legume plant that is widely used in symbiosis research. Expression of fluorescent proteins in P. palmivora permits visualisation of infection structures in M. truncatula roots. During its initial biotrophic colonisation of M. truncatula roots which lasts until about 48 hours post infection (hpi), P. palmivora zoospores expressing tdtomato red fluorescent protein (isolate AJ-td) germinate and form appressoria to penetrate the epidermis followed by rapid colonisation of the root cortex apoplast and projection of short specialised hyphae, termed haustoria into plant cells (Fig. 1a). P. palmivora infection is accompanied by visible disease development in M. truncatula seedlings consisting of translucent tissue at the root tip at two days post inoculation (dpi) and tissue browning in upper parts of the root at three dpi. (Fig. 1b, see also supplementary material). Concomitant with a switch to a nectrophic lifestyle, the pathogen enters the vasculature (Fig. 1a).We wish to thank numerous members of the symbiosis community for providing plant material and fruitful discussions (see table S1), to S. Whisson and H. Judelson for providing fluorescent protein expression vectors and M. Smoker and T. Yunusov for help with P. palmivora culturing and transformation. We are grateful to S. Kamoun for his continued support and input into an early draft of this manuscript. This work was supported by the Gatsby Charitable Foundation [RG62472 to S.S.]; by the Royal Society (RG69135 to S.S.) and by a Marie Curie Intra-European fellowship [FP7-PEOPLE-2013-IEF, SYMUNITY- EC project 624398 to T.R.].This is the author accepted manuscript. The final published version is available from Wiley at http://onlinelibrary.wiley.com/doi/10.1111/nph.13233/abstract

GoM DE: interpreting structure in sequence count data with differential expression analysis allowing for grades of membership

Parts-based representations, such as non-negative matrix factorization and topic modeling, have been used to identify structure from single-cell sequencing data sets, in particular structure that is not as well captured by clustering or other dimensionality reduction methods. However, interpreting the individual parts remains a challenge. To address this challenge, we extend methods for differential expression analysis by allowing cells to have partial membership to multiple groups. We call this grade of membership differential expression (GoM DE). We illustrate the benefits of GoM DE for annotating topics identified in several single-cell RNA-seq and ATAC-seq data sets

ViTaL: An Advanced Framework for Automated Plant Disease Identification in Leaf Images Using Vision Transformers and Linear Projection For Feature Reduction

Our paper introduces a robust framework for the automated identification of diseases in plant leaf images. The framework incorporates several key stages to enhance disease recognition accuracy. In the pre-processing phase, a thumbnail resizing technique is employed to resize images, minimizing the loss of critical image details while ensuring computational efficiency. Normalization procedures are applied to standardize image data before feature extraction. Feature extraction is facilitated through a novel framework built upon Vision Transformers, a state-of-the-art approach in image analysis. Additionally, alternative versions of the framework with an added layer of linear projection and blockwise linear projections are explored. This comparative analysis allows for the evaluation of the impact of linear projection on feature extraction and overall model performance. To assess the effectiveness of the proposed framework, various Convolutional Neural Network (CNN) architectures are utilized, enabling a comprehensive evaluation of linear projection's influence on key evaluation metrics. The findings demonstrate the efficacy of the proposed framework, with the top-performing model achieving a Hamming loss of 0.054. Furthermore, we propose a novel hardware design specifically tailored for scanning diseased leaves in an omnidirectional fashion. The hardware implementation utilizes a Raspberry Pi Compute Module to address low-memory configurations, ensuring practicality and affordability. This innovative hardware solution enhances the overall feasibility and accessibility of the proposed automated disease identification system. This research contributes to the field of agriculture by offering valuable insights and tools for the early detection and management of plant diseases, potentially leading to improved crop yields and enhanced food security.Comment: Accepted and scheduled for presentation at CML 2024, this work will be published as a book chapter in Lecture Notes in Networks and System

The Medicago truncatula GRAS protein RAD1 supports arbuscular mycorrhiza symbiosis and Phytophthora palmivora susceptibility.

The roots of most land plants are colonized by symbiotic arbuscular mycorrhiza (AM) fungi. To facilitate this symbiosis, plant genomes encode a set of genes required for microbial perception and accommodation. However, the extent to which infection by filamentous root pathogens also relies on some of these genes remains an open question. Here, we used genome-wide association mapping to identify genes contributing to colonization of Medicago truncatula roots by the pathogenic oomycete Phytophthora palmivora. Single-nucleotide polymorphism (SNP) markers most significantly associated with plant colonization response were identified upstream of RAD1, which encodes a GRAS transcription regulator first negatively implicated in root nodule symbiosis and recently identified as a positive regulator of AM symbiosis. RAD1 transcript levels are up-regulated both in response to AM fungus and, to a lower extent, in infected tissues by P. palmivora where its expression is restricted to root cortex cells proximal to pathogen hyphae. Reverse genetics showed that reduction of RAD1 transcript levels as well as a rad1 mutant are impaired in their full colonization by AM fungi as well as by P. palmivora. Thus, the importance of RAD1 extends beyond symbiotic interactions, suggesting a general involvement in M. truncatula microbe-induced root development and interactions with unrelated beneficial and detrimental filamentous microbes

Design Of Rubble Analyzer Probe Using ML For Earthquake

The earthquake rubble analyzer uses machine learning to detect human presence via ambient sounds, achieving 97.45% accuracy. It also provides real-time environmental data, aiding in assessing survival prospects for trapped individuals, crucial for post-earthquake rescue effort