Evaluating temperature dynamics: a single-center prospective randomized pilot study of holmium versus thulium laser fiber for renal stones.

Background: We aimed to evaluate and compare the rise in the temperature for the safety of the kidney parenchyma on firing the Holmium: Yttrium Aluminium Garnet laser and the Thulium Fiber Laser during laser lithotripsy in humans.

Method: We included 30 pre-stented patients with renal calculi undergoing Retrograde intra-renal surgery. They were randomized into two groups - 15 patients underwent holmium laser lithotripsy and 15 patients underwent TFL laser lithotripsy.

Polycystic Ovarian Syndrome: A Review of Multi-omics Analyses.

Polycystic Ovary Syndrome (PCOS) is among the most prevalent endocrinological abnormalities of young females, posing a grave public health challenge to the society. The objective of the present literature review is to analyze the enormous amount of information available by way of numerous multi-omic studies, and to explore a meaningful relationship between various factors such as genetic, proteomic, environmental etc. to understand the multifactorial metabolic disorder in a proper manner.

Current insights into molecular mechanisms of environmental stress tolerance in Cyanobacteria.

The photoautotrophic nature of cyanobacteria, coupled with their fast growth and relative ease of genetic manipulation, makes these microorganisms very promising factories for the sustainable production of bio-products from atmospheric carbon dioxide. However, both in nature and in cultivation, cyanobacteria go through different abiotic stresses such as high light (HL) stress, heavy metal stress, nutrient limitation, heat stress, salt stress, oxidative stress, and alcohol stress. In recent years, significant improvement has been made in identifying the stress-responsive genes and the linked pathways in cyanobacteria and developing genome editing tools for their manipulation.

Biophysical and spectroscopical insights into structural modulation of species in the aggregation pathway of superoxide dismutase 1.

Superoxide dismutase 1 (SOD1) aggregation is implicated in the development of Amyotrophic Lateral Sclerosis (ALS). Despite knowledge of the role of SOD1 aggregation, the mechanistic understanding remains elusive. Our investigation aimed to unravel the complex steps involved in SOD1 aggregation associated with ALS.

Who drives weight stigma? A multinational exploration of clustering characteristics behind weight bias against preconception, pregnant, and postpartum women.

Background: Weight bias is a global health challenge and community members are endorsed as the most common source of weight bias. The nature of weight biases specifically against preconception, pregnant, and postpartum (PPP) women from the perspective of community members is not known, especially in terms of cross-cultural trends. We investigated the magnitude of explicit and implicit weight bias and profiles of characteristics associated with harbouring weight bias.

Intrusion detection in metaverse environment internet of things systems by metaheuristics tuned two level framework.

Internet of Things (IoT) is one of the most important emerging technologies that supports Metaverse integrating process, by enabling smooth data transfer among physical and virtual domains. Integrating sensor devices, wearables, and smart gadgets into Metaverse environment enables IoT to deepen interactions and enhance immersion, both crucial for a completely integrated, data-driven Metaverse. Nevertheless, because IoT devices are often built with minimal hardware and are connected to the Internet, they are highly susceptible to different types of cyberattacks, presenting a significant security problem for maintaining a secure infrastructure.

Extracellular vesicles in seminal plasma of Sahiwal cattle bulls carry a differential abundance of sperm fertility-associated proteins for augmenting the functional quality of low-fertile bull spermatozoa.

Poor male fertility significantly affects dairy production, primarily due to low conception rates (CR) in bulls, even when cows are inseminated with morphologically normal sperm. Seminal plasma is a key factor in evaluating the fertilizing ability of bull semen. The extracellular vesicles (EVs) in seminal plasma contain fertility-associated proteins like SPAM1, ADAM7, and SP10, which influence sperm function and fertilizing potential.

Re-locative guided search optimized self-sparse attention enabled deep learning decoder for quantum error correction.

Heavy hexagonal coding is a type of quantum error-correcting coding in which the edges and vertices of a low-degree graph are assigned auxiliary and physical qubits. While many topological code decoders have been presented, it is still difficult to construct the optimal decoder due to leakage errors and qubit collision. Therefore, this research proposes a Re-locative Guided Search optimized self-sparse attention-enabled convolutional Neural Network with Long Short-Term Memory (RlGS2-DCNTM) for performing effective error correction in quantum codes.

Comparative analysis of brushless DC and switched reluctance motors for optimizing off-grid water pumping.

Off-grid water pumping systems (OGWPS) have become an increasingly popular area of research in the search for sustainable energy solutions. This paper presents a finite element method (FEM)-based design and analysis of Brushless-DC (BLDC) and Switched Reluctance Motors (SRM) designed for low-power water pumping applications. Utilizing adaptive finite element analysis (FEA), both motors were designed with identical ratings and design parameters to ensure a fair comparison.

Prediction of the transient coolant jet released from the nose cone at supersonic flow via machine learning.

In this paper, the usage of a predictive surrogate model for the estimate of flow variables in the transient phase of coolant injection from the nose cone by combining the Long Short-Term Memory (LSTM) and Proper Orthogonal Decomposition (POD) technique. The velocity, pressure, and mass fraction of the counterflow jet is evaluated via this hybrid technique and the source of discrepancy of a predictive surrogate model with Full order model is explained in this study. The POD modes for the efficient prediction of the different flow variables are defined.

Effect of boiling water soaking on the mechanical properties and durability of nanoclay-enhanced bamboo and glass fiber epoxy composites.

Fiber-reinforced polymer composites are subjected to harsh environmental conditions over the course of their designed lifespan. Studying the aging process of fiber-reinforced polymer composites exposed to boiling water is critical for improving their durability. This study uses a hand lay-up technique to fabricate composites from glass fiber, bamboo fiber, nanoclay, and epoxy.

Digital framework for georeferenced multiplatform surveillance of banana wilt using human in the loop AI and YOLO foundation models.

Bananas (Musa spp.) are a critical global food crop, providing a primary source of nutrition for millions of people. Traditional methods for disease monitoring and detection are often time-consuming, labor-intensive, and prone to inaccuracies.

An optimal workflow scheduling in IoT-fog-cloud system for minimizing time and energy.

Today, with the increasing use of the Internet of Things (IoT) in the world, various workflows that need to be stored and processed on the computing platforms. But this issue, causes an increase in costs for computing resources providers, and as a result, system Energy Consumption (EC) is also reduced. Therefore, this paper examines the workflow scheduling problem of IoT devices in the fog-cloud environment, where reducing the EC of the computing system and reducing the MakeSpan Time (MST) of workflows as main objectives, under the constraints of priority, deadline and reliability.

Soliton solutions of the (2 + 1)-dimensional Jaulent-Miodek evolution equation via effective analytical techniques.

In this study, we investigate the [Formula: see text]-D Jaulent-Miodek (JM) equation, which is significant due to its energy-based Schrödinger potential and applications in fields such as optics, soliton theory, signal processing, geophysics, fluid dynamics, and plasma physics. Given its broad utility, a rigorous mathematical analysis of the JM equation is essential. The primary objective of this work is to derive exact soliton solutions using the Modified Sub-Equation (MSE) and Modified Auxiliary Equation (MAE) techniques.

Nano urea's environmental edge and economic efficacy in boosting wheat grain yield across diverse Indian agro-climates.

The gradual increase in the consumption of mineral nitrogen is leading to heightened levels of harmful air pollutants, particularly NO emissions from the agriculture sector. A potential solution to address the issues arising from the excessive use of urea in wheat is the substitution of conventional urea with nano urea. This study aimed to quantify the effects of nano urea, both independently and in conjunction with prilled urea, under various agroclimatic and sowing conditions in India.

Circularly polarized dual-band resonance in a miniaturized implantable antenna using combined hexagonal and rhombic patches.

The design and characterisation of a novel dual-band implantable antenna with compact size is presented in this research. The antenna, which is [Formula: see text] in size and operates at two critical frequencies-0.954 GHz in the UHF band and 2.

Design and Implementation of universal converter using ANN controller.

This paper details the hardware implementation of a Universal Converter controlled by an Artificial Neural Network (ANN), utilizing key components such as six Insulated Gate Bipolar Transistors (IGBTs), two inductors, and two capacitors for energy storage and voltage smoothing. A Digital Signal Processor (DSP) serves as the core controller, processing real-time input and feedback signals, including voltage and current measurements, to dynamically manage five operational modes: rectifier buck, inverter boost, DC-DC buck, DC-DC boost, and AC voltage control. The pre-trained ANN algorithm generates pulse-width modulation (PWM) signals to control the switching of the IGBTs, optimizing timing and duty cycles for efficient operation.

Study of dissipation dynamics and persistent toxicity of selected insecticides in chilli using LCMSMS.

Chilli, a globally cultivated and consumed crop is significantly impacted by Thrips parvispinus. The reliance on pesticides could result in residue contamination, adversely affecting quality, leading to export rejections and health risks to consumers. This study evaluated the bioefficacy and persistent toxicity of fipronil and tolfenpyrad against thrips in chilli, and persistence of their residues.

Deepening water scarcity in breadbasket nations.

Water is crucial for meeting sustainability targets, but its unsustainable use threatens human wellbeing and the environment. Past assessments of water scarcity (i.e.

Development of a handheld GPU-assisted DSC-TransNet model for the real-time classification of plant leaf disease using deep learning approach.

In agriculture, promptly and accurately identifying leaf diseases is crucial for sustainable crop production. To address this requirement, this research introduces a hybrid deep learning model that combines the visual geometric group version 19 (VGG19) architecture features with the transformer encoder blocks. This fusion enables the accurate and précised real-time classification of leaf diseases affecting grape, bell pepper, and tomato plants.

Artificial Intelligence and Identification of the Deceased: a Narrative Review With Implications in Forensic Science.

Identification of the dead is of utmost importance in mass disasters, war crimes, and forensic examinations. The biological profile, established by a forensic anthropologist is one the necessary steps involved in the identification of the dead. Several parameters can be estimated such as sex, age, stature, biogeographical affinity, and DNA profile of the unknown person.