Comparison of Outcomes of Extracorporeal Shockwave Lithotripsy with Ureteroscopic Lasertripsy for Management of Proximal Ureteral Stones.

OBJECTIVE: To compare the outcomes of extracorporeal shockwave lithotripsy with ureterorenoscopy and lasertripsy for managing upper ureteral stones of size 10mm to 15mm. STUDY DESIGN: Observational, cross-sectional study. Place and Duration of the Study: Department of Urology, Sindh Institute of Urology and Transplantation (SIUT), from December 2020 to December 2021. METHODOLOGY: A total of 168 patients with the diagnosis of proximal ureteric stone of size 1-1.5 cm were enrolled for this study. Patients were divided into two groups by simple random method. Group 1 patients underwent ureteroscopic lithotripsy (URS) and lasertripsy while Group 2 patients were subjected to extracorporeal shockwave lithotripsy (ESWL). Patients' demography, operative time, duration of hospitalisation, complication rate and stone-free rates, were recorded for both groups. Frequency and percentages were calculated for categorical variables and mean and standard deviation were calculated for continuous variables. For comparison of continuous variables, one-way ANOVA was applied, and Chi-square test was applied to compare the categorical variables. The p-value ≤0.05 was taken as significant. RESULTS: The mean age was of 39.55 ± 14.06 years, with the majority falling within the age group of 26 to 40 years. There were more males (116, 69%) than females (52, 31%). Most of the patients did not have a history of diabetes or hypertension. Sixty-two patients had previous history of stones. The average duration of ureteric stone disease was 3.18 ± 3.14 months. The mean size of the ureteric stone was 10.82 ± 3.19mm. The procedure duration was significantly shorter for URS, as compared to ESWL (33.81 ± 15.42 minutes vs. 45.00 ± 0.00 minutes, p=<0.01. The overall stone clearance rate was significantly higher after URS (83.3%) as compared to ESWL (64.2%, p=0.05). CONCLUSION: URS was a superior treatment option as compared to ESWL. However, the selection of the most appropriate procedure should be based on a tailored approach considering the patient's preference and the size of the stones. KEY WORDS: Extracorporeal shockwave lithotripsy (ESWL), Ureteroscopic lithotripsy (URS), Modified clavien classification system (MCCS), Ureteric stone.

Strain-Induced Uphill Hydrogen Distribution in Perovskite Oxide Films.

Incorporating hydrogen into transition-metal oxides (TMOs) provides a facile and powerful way to manipulate the performances of TMOs, and thus numerous efforts have been invested in developing hydrogenation methods and exploring the property modulation via hydrogen doping. However, the distribution of hydrogen ions, which is a key factor in determining the physicochemical properties on a microscopic scale, has not been clearly illustrated. Here, focusing on prototypical perovskite oxide (NdNiO3 and La0.67Sr0.33MnO3) epitaxial films, we find that hydrogen distribution exhibits an anomalous "uphill" feature (against the concentration gradient) under tensile strain, namely, the proton concentration enhances upon getting farther from the hydrogen source. Distinctly, under a compressive strain state, hydrogen shows a normal distribution without uphill features. The epitaxial strain significantly influences the chemical lattice coupling and the energy profile as a function of the hydrogen doping position, thus dominating the hydrogen distribution. Furthermore, the strain-(H+) distribution relationship is maintained in different hydrogenation methods (metal-alkali treatment) which is first applied to perovskite oxides. The discovery of strain-dependent hydrogen distribution in oxides provides insights into tailoring the magnetoelectric and energy-conversion functionalities of TMOs via strain engineering.

Protonation-Induced Colossal Lattice Expansion in La2/3Sr1/3MnO3.

Ion injection controlled by an electric field is a powerful method to manipulate the diverse physical and chemical properties of metal oxides. However, the dynamic control of ion concentrations and their correlations with lattices in perovskite systems have not been fully understood. In this study, we systematically demonstrate the electric-field-controlled protonation of La2/3Sr1/3MnO3 (LSMO) films. The rapid and room-temperature protonation induces a colossal lattice expansion of 9.35% in tensile-strained LSMO, which is crucial for tailoring material properties and enabling a wide range of applications in advanced electronics, energy storage, and sensing technologies. This large expansion in the lattice is attributed to the higher degree of proton diffusion, resulting in a significant elongation in the Mn-O bond and octahedral tilting, which is supported by results from density functional theory calculations. Interestingly, such a colossal expansion is not observed in LSMO under compressive strain, indicating the close dependence of ion-electron-lattice coupling on strain states. These efficient modulations of the lattice and magnetoelectric functionalities of LSMO via proton diffusion offer a promising avenue for developing multifunctional iontronic devices.

Artificial Intelligence, Computational Simulations, and Extended Reality in Cardiovascular Interventions.

Artificial intelligence, computational simulations, and extended reality, among other 21st century computational technologies, are changing the health care system. To collectively highlight the most recent advances and benefits of artificial intelligence, computational simulations, and extended reality in cardiovascular therapies, we coined the abbreviation AISER. The review particularly focuses on the following applications of AISER: 1) preprocedural planning and clinical decision making; 2) virtual clinical trials, and cardiovascular device research, development, and regulatory approval; and 3) education and training of interventional health care professionals and medical technology innovators. We also discuss the obstacles and constraints associated with the application of AISER technologies, as well as the proposed solutions. Interventional health care professionals, computer scientists, biomedical engineers, experts in bioinformatics and visualization, the device industry, ethics committees, and regulatory agencies are expected to streamline the use of AISER technologies in cardiovascular interventions and medicine in general.

Correction to "Controllable Synthesis of a Porous PEI-Functionalized Co3O4/rGO Nanocomposite as an Electrochemical Sensor for Simultaneous as Well as Individual Detection of Heavy Metal Ions".

[This corrects the article DOI: 10.1021/acsomega.1c05989.].

Telehealth for COVID-19: A Conceptual Framework.

The world has been going through the global crisis of the coronavirus (COVID-19). It is a challenging situation for every country to tackle its healthcare system. COVID-19 spreads through physical contact with COVID-positive patients and causes potential damage to the country's health and economy system. Therefore, to overcome the chance of spreading the disease, the only preventive measure is to maintain social distancing. In this vulnerable situation, virtual resources have been utilized in order to maintain social distance, i.e., the telehealth system has been proposed and developed to access healthcare services remotely and manage people's health conditions. The telehealth system could become a regular part of our healthcare system, and during any calamity or natural disaster, it could be used as an emergency response to deal with the catastrophe. For this purpose, we proposed a conceptual telehealth framework in response to COVID-19. We focused on identifying critical issues concerning the use of telehealth in healthcare setups. Furthermore, the factors influencing the implementation of the telehealth system have been explored in detail. The proposed telehealth system utilizes artificial intelligence and data science to regulate and maintain the system efficiently. Before implementing the telehealth system, it is required that prearrangements be made, such as appropriate funding measures, the skills to know technological usage, training sessions, and staff endorsement. The barriers and influencing factors provided in this article can be helpful for future developments in telehealth systems and for making fruitful progress in fighting pandemics like COVID-19. At the same time, the same approach can be used to save the lives of many frontline workers.

Electrical Cardioversion-Associated Takotsubo Cardiomyopathy: A National Readmission Database 2018 Analysis and Systematic Review.

The incidence of cardioversion-associated takotsubo cardiomyopathy in patients with atrial fibrillation undergoing electrical cardioversion is unknown. We aimed to determine the incidence of cardioversion-associated takotsubo cardiomyopathy using a National Readmission Database 2018 and a systematic review. We identified all patients with the index diagnosis of atrial fibrillation who underwent electrical cardioversion and were readmitted within 30 days with a primary diagnosis of takotsubo cardiomyopathy by International Classification of Diseases, Tenth Revision, Clinical Modification codes to find the incidence and risk factors of the disease. A systematic review was performed by searching PubMed and Embase for patients with atrial fibrillation who underwent electrical cardioversion and developed takotsubo cardiomyopathy from inception to February 2022. Baseline characteristics and clinical presentation were displayed. Among 154 919 patients admitted with atrial fibrillation who underwent electrical cardioversion in National Readmission Database 2018, 0.027% were readmitted with takotsubo cardiomyopathy (mean age of 71.0 ± 3.5 years and 96.7% were female). Female sex is an independent predictor of electrical cardioversion-associated takotsubo cardiomyopathy [adjusted odds ratio = 49.77 (95% CI: 5.90-419.87)], while diabetes mellitus is associated with less risk of electrical cardioversion-associated takotsubo cardiomyopathy [adjusted odds ratio = 0.31 (95% CI: 0.10-0.99)]. The systematic review included 13 patients (mean age of 74.8 ± 9.6 years and 77% were female). Acute heart failure due to apical type takotsubo cardiomyopathy is the most common presentation within 48 hours. The recovery time is less than 1 week in milder cases but can take up to 2 weeks in severe cases. Cardioversion-associated takotsubo cardiomyopathy is a rare complication in patients with atrial fibrillation who underwent electrical cardioversion. Female patients have a 50-fold increased risk, but DM is associated with a 3-fold risk reduction. The majority of patients recover within 2 weeks with supportive care.

Cancerous Tumor Controlled Treatment Using Search Heuristic (GA)-Based Sliding Mode and Synergetic Controller.

Cancerous tumor cells divide uncontrollably, which results in either tumor or harm to the immune system of the body. Due to the destructive effects of chemotherapy, optimal medications are needed. Therefore, possible treatment methods should be controlled to maintain the constant/continuous dose for affecting the spreading of cancerous tumor cells. Rapid growth of cells is classified into primary and secondary types. In giving a proper response, the immune system plays an important role. This is considered a natural process while fighting against tumors. In recent days, achieving a better method to treat tumors is the prime focus of researchers. Mathematical modeling of tumors uses combined immune, vaccine, and chemotherapies to check performance stability. In this research paper, mathematical modeling is utilized with reference to cancerous tumor growth, the immune system, and normal cells, which are directly affected by the process of chemotherapy. This paper presents novel techniques, which include Bernstein polynomial (BSP) with genetic algorithm (GA), sliding mode controller (SMC), and synergetic control (SC), for giving a possible solution to the cancerous tumor cells (CCs) model. Through GA, random population is generated to evaluate fitness. SMC is used for the continuous exponential dose of chemotherapy to reduce CCs in about forty-five days. In addition, error function consists of five cases that include normal cells (NCs), immune cells (ICs), CCs, and chemotherapy. Furthermore, the drug control process is explained in all the cases. In simulation results, utilizing SC has completely eliminated CCs in nearly five days. The proposed approach reduces CCs as early as possible.

Investigating Inclusive Leadership and Pro-Social Rule Breaking in Hospitality Industry: Important Role of Psychological Safety and Leadership Identification.

This study aims to empirically examine the mediating effects of psychological safety and leadership identification on the relationship between inclusive leadership and pro-social rule breaking among hospitality employees. This study analyzes the survey data collected in three waves from 589 employees working in different hotels and restaurants operating in the Northern areas of Khyber Pakhtunkhwa, Pakistan. The scale validity, composite reliability, and hypotheses were assessed through PLS-SEM. The study found that inclusive leadership significantly impacts employees' pro-social rule-breaking. The study also found that leadership identification and psychological safety partially mediate the relationship between inclusive leadership and pro-social rule-breaking. Hospitality leaders can practice inclusive leadership characteristics because it may significantly enhance employee engagement in pro-social rule-breaking. Through their inclusive features, hospitality leaders can improve employees' psychological safety and leadership identification, enhancing frontline employees' pro-social rule-breaking.

First-in-Human Computational Preprocedural Planning of Left Main Interventions Using a New Everolimus-Eluting Stent.

Left main coronary artery stenting requires rigorous planning and optimal execution. This case series presents a new approach to left main stenting guided by preprocedural patient-specific computational simulations. Three patients with significant left main artery disease underwent simulation-guided intervention using a novel stent scaffold purpose-built for large coronary arteries. (Level of Difficulty: Advanced.).

Brain Decoding Using fMRI Images for Multiple Subjects through Deep Learning.

Substantial information related to human cerebral conditions can be decoded through various noninvasive evaluating techniques like fMRI. Exploration of the neuronal activity of the human brain can divulge the thoughts of a person like what the subject is perceiving, thinking, or visualizing. Furthermore, deep learning techniques can be used to decode the multifaceted patterns of the brain in response to external stimuli. Existing techniques are capable of exploring and classifying the thoughts of the human subject acquired by the fMRI imaging data. fMRI images are the volumetric imaging scans which are highly dimensional as well as require a lot of time for training when fed as an input in the deep learning network. However, the hassle for more efficient learning of highly dimensional high-level features in less training time and accurate interpretation of the brain voxels with less misclassification error is needed. In this research, we propose an improved CNN technique where features will be functionally aligned. The optimal features will be selected after dimensionality reduction. The highly dimensional feature vector will be transformed into low dimensional space for dimensionality reduction through autoadjusted weights and combination of best activation functions. Furthermore, we solve the problem of increased training time by using Swish activation function, making it denser and increasing efficiency of the model in less training time. Finally, the experimental results are evaluated and compared with other classifiers which demonstrated the supremacy of the proposed model in terms of accuracy.

Controllable Synthesis of a Porous PEI-Functionalized Co3O4/rGO Nanocomposite as an Electrochemical Sensor for Simultaneous as Well as Individual Detection of Heavy Metal Ions.

The present study focuses on the strategy of employing an electrochemical sensor with a porous polyethylenimine (PEI)-functionalized Co3O4/reduced graphene oxide (rGO) nanocomposite (NCP) to detect heavy metal ions (HMIs: Cd2+, Pb2+, Cu2+, and Hg2+). The porous PEI-functionalized Co3O4/rGO NCP (rGO·Co3O4·PEI) was prepared via a hydrothermal method. The synthesized NCP was based on a conducting polymer PEI, rGO, nanoribbons of Co3O4, and highly dispersed Co3O4 nanoparticles (NPs), which have shown excellent performance in the detection of HMIs. The as-prepared PEI-functionalized rGO·Co3O4·PEI NCP-modified electrode was used for the sensing/detection of HMIs by means of both square wave anodic stripping voltammetry (SWV) and differential normal pulse voltammetry (DNPV) methods for the first time. Both methods were employed for the simultaneous detection of HMIs, whereas SWV was employed for the individual analysis as well. The limits of detection (LOD; 3σ method) for Cd2+, Pb2+, Cu2+, and Hg2+ determined using the rGO·Co3O4·PEI NCP-modified electrode were 0.285, 1.132, 1.194, and 1.293 nM for SWV, respectively. Similarly, LODs of Cd2+, Pb2+, Cu2+, and Hg2+ were 1.069, 0.285, 2.398, and 1.115 nM, respectively, by DNPV during simultaneous analysis, whereas they were 0.484, 0.878, 0.462, and 0.477 nM, respectively, by SWV in individual analysis.

Energy Efficiency and Reliability Considerations in Wireless Body Area Networks: A Survey.

In this paper, we have reviewed and presented a critical overview of "energy-efficient and reliable routing solutions" in the field of wireless body area networks (WBANs). In addition, we have theoretically analysed the importance of energy efficiency and reliability and how it affects the stability and lifetime of WBANs. WBAN is a type of wireless sensor network (WSN) that is unique, wherever energy-efficient operations are one of the prime challenges, because each sensor node operates on battery, and where an excessive amount of communication consumes more energy than perceiving. Moreover, timely and reliable data delivery is essential in all WBAN applications. Moreover, the most frequent types of energy-efficient routing protocols include crosslayer, thermal-aware, cluster-based, quality-of-service, and postural movement-based routing protocols. According to the literature review, clustering-based routing algorithms are the best choice for WBAhinwidth, and low memory WBAN, in terms of more computational overhead and complexity. Thus, the routing techniques used in WBAN should be capable of energy-efficient communication at desired reliability to ensure the improved stability period and network lifetime. Therefore, we have highlighted and critically analysed various performance issues of the existing "energy-efficient and reliable routing solutions" for WBANs. Furthermore, we identified and compiled a tabular representation of the reviewed solutions based on the most appropriate strategy and performance parameters for WBAN. Finally, concerning to reliability and energy efficiency in WBANs, we outlined a number of issues and challenges that needs further consideration while devising new solutions for clustered-based WBANs.

An Improved Brain MRI Classification Methodology Based on Statistical Features and Machine Learning Algorithms.

In this paper, we have proposed a novel methodology based on statistical features and different machine learning algorithms. The proposed model can be divided into three main stages, namely, preprocessing, feature extraction, and classification. In the preprocessing stage, the median filter has been used in order to remove salt-and-pepper noise because MRI images are normally affected by this type of noise, the grayscale images are also converted to RGB images in this stage. In the preprocessing stage, the histogram equalization has also been used to enhance the quality of each RGB channel. In the feature extraction stage, the three channels, namely, red, green, and blue, are extracted from the RGB images and statistical measures, namely, mean, variance, skewness, kurtosis, entropy, energy, contrast, homogeneity, and correlation, are calculated for each channel; hence, a total of 27 features, 9 for each channel, are extracted from an RGB image. After the feature extraction stage, different machine learning algorithms, such as artificial neural network, k-nearest neighbors' algorithm, decision tree, and Naïve Bayes classifiers, have been applied in the classification stage on the features extracted in the feature extraction stage. We recorded the results with all these algorithms and found that the decision tree results are better as compared to the other classification algorithms which are applied on these features. Hence, we have considered decision tree for further processing. We have also compared the results of the proposed method with some well-known algorithms in terms of simplicity and accuracy; it was noted that the proposed method outshines the existing methods.

An Efficient Methodology for Brain MRI Classification Based on DWT and Convolutional Neural Network.

In this paper, a model based on discrete wavelet transform and convolutional neural network for brain MR image classification has been proposed. The proposed model is comprised of three main stages, namely preprocessing, feature extraction, and classification. In the preprocessing, the median filter has been applied to remove salt-and-pepper noise from the brain MRI images. In the discrete wavelet transform, discrete Harr wavelet transform has been used. In the proposed model, 3-level Harr wavelet decomposition has been applied on the images to remove low-level detail and reduce the size of the images. Next, the convolutional neural network has been used for classifying the brain MR images into normal and abnormal. The convolutional neural network is also a prevalent classification method and has been widely used in different areas. In this study, the convolutional neural network has been used for brain MRI classification. The proposed methodology has been applied to the standard dataset, and for performance evaluation, we have used different performance evaluation measures. The results indicate that the proposed method provides good results with 99% accuracy. The proposed method results are then presented for comparison with some state-of-the-art algorithms where simply the proposed method outperforms the counterpart algorithms. The proposed model has been developed to be used for practical applications.

Observation of negative capacitance in antiferroelectric PbZrO3 Films.

Negative capacitance effect in ferroelectric materials provides a solution to the energy dissipation problem induced by Boltzmann distribution of electrons in conventional electronics. Here, we discover that besides ferroelectrics, the antiferroelectrics based on Landau switches also have intrinsic negative capacitance effect. We report both the static and transient negative capacitance effect in antiferroelectric PbZrO3 films and reveal its possible physical origin. The capacitance of the capacitor of the PbZrO3 and paraelectric heterostructure is demonstrated to be larger than that of the isolated paraelectric capacitor at room temperature, indicating the existence of the static negative capacitance. The opposite variation trends of the voltage and charge transients in a circuit of the PbZrO3 capacitor in series with an external resistor demonstrate the existence of transient negative capacitance effect. Strikingly, four negative capacitance effects are observed in the antiferroelectric system during one cycle scan of voltage pulses, different from the ferroelectric counterpart with two negative capacitance effects. The polarization vector mapping, electric field and free energy analysis reveal the rich local regions of negative capacitance effect with the negative dP/dE and (δ2G)/(δD2), producing stronger negative capacitance effect. The observation of negative capacitance effect in antiferroelectric films significantly extends the range of its potential application and reduces the power dissipation further.

Interfacial Control of Ferromagnetism in Ultrathin SrRuO3 Films Sandwiched between Ferroelectric BaTiO3 Layers.

Interfaces between materials provide an intellectually rich arena for fundamental scientific discovery and device design. However, the frustration of magnetization and conductivity of perovskite oxide films under reduced dimensionality is detrimental to their device performance, preventing their active low-dimensional application. Herein, by inserting the ultrathin 4d ferromagnetic SrRuO3 layer between ferroelectric BaTiO3 layers to form a sandwich heterostructure, we observe enhanced physical properties in ultrathin SrRuO3 films, including longitudinal conductivity, Curie temperature, and saturated magnetic moment. Especially, the saturated magnetization can be enhanced to ∼3.12 µB/Ru in ultrathin BaTiO3/SrRuO3/BaTiO3 trilayers, which is beyond the theoretical limit of bulk value (2 µB/Ru). This observation is attributed to the synergistic ferroelectric proximity effect (SFPE) at upper and lower BaTiO3/SrRuO3 heterointerfaces, as revealed by the high-resolution lattice structure analysis. This SFPE in dual-ferroelectric interface cooperatively induces ferroelectric-like lattice distortions in RuO6 oxygen octahedra and subsequent spin-state crossover in SrRuO3, which in turn accounts for the observed enhanced magnetization. Besides the fundamental significance of interface-induced spin-lattice coupling, our findings also provide a viable route to the electrical control of magnetic ordering, taking a step toward low-power applications in all-oxide spintronics.

Potential of botanical driven essential oils against Haemonchus contortus in small ruminants / Potencial de aceites esenciales botánicos contra Haemonchus contortus en pequeños rumiantes

The livestock sector is continuously facing problems in controlling parasitic diseases especially Haemonchosis due to emergence of anthelminthic resistance and failure in vaccination control programmes. Therefore, to increase milk and meat production and emerging demand of meat free from drug residues development of new alternative approaches are appealing for prevention and control of Haemonchosis in small ruminants. Among alternatives, plants driven essentials oils have shown promising results in control of Haemonchus contortus infection at various concentrations by different assays including egg hatch assay, larval development assay, larval exsheathment assay and adult motility assay. Essential oils are complex mixtures of various impulsive or volatile compounds which have potential to control Haemonchosis. The current study reviews the therapeutic effects of essential oils of plants against Haemonchus contortus and to be used them against Haemonchus contortus for future perspectives.

El sector ganadero enfrenta continuamente problemas para controlar las enfermedades parasitarias, especialmente la hemoncosis, debido a la aparición de resistencia antihelmíntica y al fracaso en los programas de control de vacunación. Por lo tanto, para aumentar la producción de leche y carne, y la demanda emergente de carne libre de residuos de medicamentos, el desarrollo de nuevos enfoques alternativos es atractivo para la prevención y el control de la hemoncosis en pequeños rumiantes. Entre las alternativas, los aceites esenciales producidos por las plantas han mostrado resultados prometedores en el control de la infección por Haemonchus contortus a diversas concentraciones mediante diferentes ensayos, incluido el análisis de eclosión de huevos, el desarrollo de larvas, el análisis de vaciado de larvas y el ensayo de motilidad en adultos. Los aceites esenciales son mezclas complejas de varios compuestos impulsivos o volátiles que tienen potencial para controlar la hemonchosis. Este estudio revisa los efectos terapéuticos de los aceites esenciales de las plantas contra Haemonchus contortus y evalúa sus perspectivas futuras como agentes para combatir las enfermedades causadas por este parásito.

Electric Field Control of Phase Transition and Tunable Resistive Switching in SrFeO2.5.

SrFeO x (SFO x) compounds exhibit ionic conduction and oxygen-related phase transformation, having potential applications in solid oxide fuel cells, smart windows, and memristive devices. The phase transformation in SFO x typically requires a thermal annealing process under various pressure conditions, hindering their practical applications. Here, we have achieved a reversible phase transition from brownmillerite (BM) to perovskite (PV) in SrFeO2.5 (SFO2.5) films through ionic liquid (IL) gating. The real-time phase transformation is imaged using in situ high-resolution transmission electron microscopy. The magnetic transition in SFO2.5 is identified by fabricating an assisted La0.7Sr0.3MnO3 (LSMO) bottom layer. The IL-gating-converted PV phase of a SrFeO3-δ (SFO3-δ) layer shows a ferromagnetic-like behavior but applies a huge pinning effect on LSMO magnetic moments, which consequently leads to a prominent exchange bias phenomenon, suggesting an uncompensated helical magnetic structure of SFO3-δ. On the other hand, the suppression of both magnetic and exchange coupling signals for a BM-phased SFO2.5 layer elucidates its fully compensated G-type antiferromagnetic nature. We also demonstrated that the phase transition by IL gating is an effective pathway to tune the resistive switching parameters, such as set, reset, and high/low-resistance ratio in SFO2.5-based resistive random-access memory devices.