Efficient Technique Research Articles

Four-Layer Wound Closure Technique with Barbed Sutures for Inframammary Fold in Mastopexy Augmentation.

The inframammary fold (IMF) is an important landmark in breast aesthetic surgery. In augmentation mastopexy procedures, secure and accurate placement of the IMF is essential to aesthetic outcomes and to allow the new IMF to heal in the correct position without displacement. The authors present a simple and efficient four-layer wound closure technique using barbed sutures for closure of the repositioned IMF in augmentation mastopexy procedures. This method was previously described by the first author for reset of the IMF in breast augmentation surgery and has been adapted to the longer IMF incision in augmentation mastopexy procedures. A retrospective review was undertaken of 335 patients who underwent bilateral breast augmentation mastopexy procedures with a Wise pattern technique at a single unit. The newly reset IMF was closed using barbed sutures and a four-layer closure technique. There were no cases of complications related to wound healing or wound dehiscence. One patient required explantation for an infected implant. The four-layer wound closure technique with barbed sutures provides a quick and efficient method for accurate closure of the newly reset IMF, with positive outcomes related to wound healing. Secure and accurate placement of the inframammary fold is crucial in augmentation mastopexy procedures. The use of a four-layer wound closure technique with barbed sutures provides an efficient method for accurate closure of the newly reset inframammary fold. This method was previously described by the first author for reset of the IMF in breast augmentation surgery and has been adapted to the longer IMF incision in augmentation mastopexy procedures. This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266 .

Performance analysis of distillate quality in solar still using culinary discharge

ABSTRACT The scarcity of clean water is a pressing global problem resulting from limited freshwater resources and substantial sewage discharge. It is essential to develop cost-effective and straightforward methods for converting wastewater into potable water to ensure the long-term sustainability of the human population. In this study, we introduce a simple and efficient technique that combines a single slope solar still (SSSS) with a sand bed filtration system. We evaluated the effectiveness of this technique by examining various water quality parameters, including pH, total dissolved solids, electrical conductivity, turbidity, alkalinity, hardness, biochemical oxygen demand, chemical oxygen demand, phosphate, nitrate, and E. coli, for kitchen wastewater (KWW), settled kitchen wastewater (SKWW), and borewell water (BW). Our results showed that the SSSS process successfully removed impurities and bacteria via solar evaporation, resulting in significant improvements in all water quality parameters. The SKWW demonstrated the highest efficiency of 40%, with a water depth of 1 cm and a daily freshwater yield of 3.1 Lm-2. The SSSS process offers several advantages over conventional wastewater treatment methods, including high performance, ease of use, portability, and low cost, making it a promising solution for obtaining clean water in remote areas.

Simulation and FPGA based Implementation of PI and Fuzzy Controllers for Cascaded Asymmetric Multilevel Inverter

The main objective of this work is to improve the performance of Multilevel Inverter by using the novel LS-PD- PWM and controlling technique instead of the existing approach. The proposed work focus on closed loop controller such as existing PI and Fuzzy Logic Controller for resistive load with Multilevel Inverter. The proposed Asymmetric fifteen level Inverter offers less THD and high frequency than the Asymmetric nine level inverter. Asymmetric multilevel inverter is used to reduce the switching losses and THD. In this work is the generation and implementation of Pulse Width Modulation (PWM) techniques using Field Programmable Gate Array (FPGA) for Multilevel Inverter. PWM can be generated via Microprocessors, Microcontroller, FPGA and DSP Processors. Higher density Programmable Logic Devices (PLD) such as FPGAs can be used to amalgamate large amounts of logic into a single Integrated. Pulse width modulation (PWM) is generally used in power converter control. To generate LS-PD- PWM by using FPGA, this occupies less memory capacity and accurate than conventional one. An efficient PWM generation technique is performed using FPGA for lower frequency applications. Simulation and synthesis is done by ModelSim6.3c and Xilinx10.1. Further, the Implementation is carried out by FPGA Spartan3 Xc3s50. Key Word: PWM, FPGA, PLD (Programmable Logic Devices), LS-PD-PWM

Postharvest Chemical Treatment of Physiologically Induced Stem End Blockage Improves Vase Life and Water Relation of Cut Flowers

Wound-induced xylem occlusion significantly affects the vase life of cut flowers, as oxidative stress and the polymerization of phenolic compounds lead to the deposition of phenolic compounds/secondary metabolites in the stem ends of cut flowers to heal open tissues of freshly cut stems and prevent microbial invasion. However, this deposition causes blockage of vessels, reduced water uptake, and shortened vase life. The physiological plugging of vessels is linked with various oxidative enzymes’ (PAL, PPOs, LACs, and COs) actions taken to increase the synthesis of different compounds, e.g., lignin, suberin, tyloses, gel, and latex, in wounded areas. The use of chemical preservatives/enzyme inhibitors is one of the safest and most efficient techniques employed to minimize vascular blockage and inhibit phenolic compounds deposition and exudation. This review mainly discusses the types of oxidative enzymes, their pathways and biochemistry along with production of secondary metabolites, their biosynthesis, and their modes of action involved in vascular blockage. It also summarizes the different types of preservatives used in postharvest treatments to improve relative water uptake, flower fresh weight, petal protein content, and hydraulic conductance and prolong the vase life of cut flowers during storage. It is hoped that this elaborate study will help researchers in designing new studies concerning occlusion caused by the accumulation of phenolic compounds in vessels.

Topological Invariants of Hexagonal Cage Network by Using Algebraic Polynomials

In this article, we go beyond earlier limits in the analysis by using algebraic polynomials to compute the topological indices for hexagonal cage networks. We investigate hexagonal cage networks of different orders and copies by introducing M-Polynomials and Forgotten polynomials, and we derive novel closed formulae and conclusions for a broad range of topological indices. We also create an efficient technique to compute , a pivotal polynomial, as part of our work. In addition to computing, we apply algebraic polynomials to the analysis of these indices, providing more insights into their structural significance in hexagonal cage networks. This work illuminates the algebraic underpinnings of these intricate networks and broadens the scope of topological index computation, with implications for a variety of scientific domains. These polynomials allow us to calculate several features of the network, such as the first and second Zagreb, modified Zagreb, General Randić, inverse General Randić, harmonic, symmetric division, inverse sum, and so on. There are now new closed formulae and outcomes available. Additionally, we offer a technique for calculating the polynomial . We also use algebraic polynomials to analyses all of the aforementioned indices.

The application of laser‑induced fluorescence in oil spill detection.

Over the past two decades, oil spills have been one of the most serious ecological disasters, causing massive damage to the aquatic and terrestrial ecosystems as well as the socio-economy. In view of this situation, several methods have been developed and utilized to analyze oil samples. Among these methods, laser-induced fluorescence (LIF) technology has been widely used in oil spill detection due to its classification method, which is based on the fluorescence characteristics of chemical material in oil. This review systematically summarized the LIF technology from the perspective of excitation wavelength selection and the application of traditional and novel machine learning algorithms to fluorescence spectrum processing, both of which are critical for qualitative and quantitative analysis of oil spills. It can be seen that an appropriate excitation wavelength is indispensable for spectral discrimination due to different kinds of polycyclic aromatic hydrocarbons' (PAHs) compounds in petroleum products. By summarizing some articles related to LIF technology, we discuss the influence of the excitation wavelength on the accuracy of the oil spill detection model and proposed several suggestions on the selection of excitation wavelength. In addition, we introduced some traditional and novel machine learning (ML) algorithms and discussed the strengths and weaknesses of these algorithms and their applicable scenarios. With an appropriate excitation wavelength and data processing algorithm, it is believed that laser-induced fluorescence technology will become an efficient technique for real-time detection and analysis of oil spills.

SCT: Summary Caption Technique for Retrieving Relevant Images in Alignment with Multimodal Abstractive Summary

This work proposes an efficient Summary Caption Technique that considers the multimodal summary and image captions as input to retrieve the correspondence images from the captions that are highly influential to the multimodal summary. Matching a multimodal summary with an appropriate image is a challenging task in computer vision and natural language processing. Merging in these fields is tedious, though the research community has steadily focused on cross-modal retrieval. These issues include the visual question-answering, matching queries with the images, and semantic relationship matching between two modalities for retrieving the corresponding image. Relevant works consider questions to match the relationship of visual information and object detection and to match the text with visual information and employing structural-level representation to align the images with the text. However, these techniques are primarily focused on retrieving the images to text or for image captioning. But less effort has been spent on retrieving relevant images for the multimodal summary. Hence, our proposed technique extracts and merge features in the Hybrid Image Text layer and captions in the semantic embeddings with word2vec where the contextual features and semantic relationships are compared and matched with each vector between the modalities, with cosine semantic similarity. In cross-modal retrieval, we achieve top five related images and align the relevant images to the multimodal summary that achieves the highest cosine score among the retrieved images. The model has been trained with seq-to-seq modal with 100 epochs, besides reducing the information loss by the sparse categorical cross entropy. Further, experimenting with the multimodal summarization with multimodal output dataset, in cross-modal retrieval, helps to evaluate the quality of image alignment with an image-precision metric that demonstrate the best results.

Efficiency of Desiccation, Decomposition and Release of Nutrients in the Biomass of Forage Plants of the Genus Brachiaria After Intercropping with Sorghum in Integrated Systems for Soybean Productivity

ABSTRACT The implementation of more sustainable soil management strategies, such as the use of cover crop for no-till system with crop rotation, can help increase nutrient use efficiency and consequently decrease the use of mineral fertilizers for agriculture. In this context, the objective was to evaluate the efficiency of desiccation, decomposition and release of nutrients in the biomass of forage plants of the genus Brachiaria after intercropping with sorghum in integrated systems for soybean productivity. The experiment was conducted in the field in two agricultural seasons in randomized block design with four repetitions. The treatments consisted of biomass obtained after sorghum intercropping with forage plants of the Brachiaria genus (Brachiaria ruziziensis, Brachiaria brizantha cv. Marandu, Brachiaria brizantha cv. Xaraés, Brachiaria brizantha cv. BRS Piatã, Brachiaria brizantha cv. BRS Paiaguás, Brachiaria cv. BRS Ipyporã), sorghum biomass in monoculture, which after cutting for grain production, remained fallow for one year and an additional soybean treatment without soil cover biomass. The results showed that Cropping systems on sorghum and forage biomass resulted in a 25.64% increase in soybean yields compared to soybeans grown without soil cover. The use of tropical forage as a cover crop in integrated systems proved to be an efficient technique for biomass production, in order to minimize the effect of water deficit during soybean development, and nutrient cycling, which resulted in the replacement of mineral potassium fertilization for the no-till soybean system, by making better use of soil nutrients and contributing to greater sustainability.

Approximate Solution of PHI-Four and Allen–Cahn Equations Using Non-Polynomial Spline Technique

The aim of this work is to use an efficient and accurate numerical technique based on non-polynomial spline for the solution of the PHI-Four and Allen–Cahn equations. A recent discovery suggests that the PHI-Four equation focuses on its implications for particle physics and the behavior of scalar fields in the quantum realm. In materials science, ongoing research involves using the Allen–Cahn equation to understand and predict the evolution of microstructures in various materials as well as in biophysics. It depicts pattern formation in biological systems and the dynamics of spatial organization in tissues. To obtain an approximate solution of both equations, this technique uses forward differences for the time and cubic non-polynomial spline function for spatial descretization. The stability of the suggested technique is addressed using the von Neumann technique. Convergence test is carried out theoretically to show the order of convergence of the scheme. Some numerical tests are carried out to confirm accuracy and efficiency in terms of absolute error LR. Convergence rates for different test problems are also computed numerically. Numerical results and simulations obtained are compared with the existing methods.

Efficient single image-based dehazing technique using convolutional neural networks

Efficient single image-based dehazing technique using convolutional neural networks

PVDF piezoelectric sensor based on solution blow spinning fibers for structural stress/strain health monitoring

Strain monitoring is of great significance to the maintenance and safe operation of engineering structures. To address the shortcomings of piezoelectric ceramics such as high inflexibility and brittleness, in this study, polyvinylidene fluoride (PVDF) fibrous films were prepared by a safe and efficient solution blow spinning technique. In the case of similar β-phase content, the preparing efficiency of PVDF fibers by the solution blow spinning method increased by about 8–10 times compared to that of electrospinning method in our previous work. The fibers with average diameter of 0.79 μm had the highest β-phase content, around 83%. A flexible piezoelectric fiber sensor with simple design for structural strain monitoring was prepared based on the PVDF fibers. The sensor responded well to strains as low as 23 μϵ, better than commercial strain gauges, with a high response accuracy of 1.11 mV/μϵ. And the piezoelectric properties of the sensors could charge a 4.7 μF capacitor to 3 V in 40 s, offering the potential for low-cost, self-powered structural health monitoring.

Postharvest Physiology and Handling of Guava Fruit.

Guavas are typical tropical fruit with high nutritional and commercial value. Because of their thin skin and high metabolic rate, guavas are highly susceptible to water loss, physical damage, and spoilage, severely limiting their shelf-life. Guavas can typically only be stored for approximately one week at room temperature, making transportation, storage, and handling difficult, resulting in low profit margins in the industry. This review focuses on the physiological and biochemical changes and their molecular mechanisms which occur in postharvest guavas, and summarizes the various management strategies for extending the shelf-life of these sensitive fruits by means of physical and chemical preservation and their combinations. This review also suggests future directions and reference ideas for the development of safe and efficient shelf-life extension techniques.

Investigation of Drilling Holes in CFRP for Aircraft Using cBN Electroplated Ball End Mill Using Helical Interpolation Motion

Investigation of Drilling Holes in CFRP for Aircraft Using cBN Electroplated Ball End Mill Using Helical Interpolation Motion

Social Media Monitoring Of Airbnb Reviews Using AI: A Sentiment Analysis Approach For Immigrant Perspectives In The UK

This paper presents a novel approach for monitoring social media content related to Airbnb reviews, explicitly focusing on the sentiments expressed by immigrants in the United Kingdom. The proposed system, a Quick Search System, leverages machine learning techniques to perform sentiment analysis on many Airbnb reviews. The system aims to provide timely and insightful information about the experiences and sentiments of immigrants in the UK, as reflected in their Airbnb reviews. By employing state-of-the-art machine learning algorithms, the system enables efficient and accurate sentiment classification, allowing for the identification of key themes and sentiments expressed by immigrant users. The study demonstrates the potential of this approach in gaining a deeper understanding of immigrant perspectives within the context of peer-to-peer accommodation, and its implications for social media monitoring and customer satisfaction management.This present study has conducted a critical analysis utilizing efficient feature extraction techniques, including N-grams and TF-IDF, to optimize identifying positive, neutral, and negative feedback. Furthermore, five different models were utilized, and the training and testing processes were accompanied by parameter tuning. Ultimately, the study concluded that the Random Forest (RF) classifier performed exceptionally well, achieving a 95% accuracy rate.

Ionic Liquid-Enhanced Assembly of Nanomaterials for Highly Stable Flexible Transparent Electrodes

HighlightsWe present a method that utilizes ionic liquid-enhanced nanomaterial assembly to fabricate highly stable and large-area MXene-silver nanowire electrodes with ordered layered structures.This approach emphasizes the use of hydrophobic and nonvolatile ionic liquids, which form stable interfaces with water by reducing interface energy, preventing the sedimentation loss of nanomaterials during assembly.The prepared electrodes not only exhibit excellent optoelectronic properties (9.4 Ω sq−1 sheet resistance and 93% transmittance), but also have exceptional antioxidant capacity.

(021) Eight-Dot Extended Corporotomy versus Conventional Corporotomy for Malleable Penile Prosthesis Implantation

Abstract Introduction To date, malleable type penile prosthesis implantation (MPPI) remains the more popular in developing countries, owing to its relative economic cost. Despite the simplicity of the procedure, there still may be areas of improvement and refinement to optimize procedure efficiency and accuracy subsequently improving postoperative outcomes while reducing complication risk. Objective We aimed to compare the eight-dot extended corporotomy and the conventional corporotomy techniques for MPPI with regard to operative time and postoperative complications. Methods We conducted a prospective randomized interventional clinical study on 51 subjects. Patients were randomized into 2 groups: the eight-dot group (n=27) and the conventional group (n=24). The eight-dot group underwent MPPI using the eight-dot extended corporotomy as previously described (VJPU - Eight-dot Extended Corporotomy: A More Secure, Aesthetic and Time Efficient Technique for Semirigid Penile Prosthesis Implantation, n.d.). The conventional group underwent MPPI using conventional limited corporotomies that were closed via continuous running sutures. We compared both groups in terms of corporotomy opening to closure time, overall procedure time, and perioperative complications. The follow-up period was 3 months. Results Upon timing in seconds (s), a significant time difference between the 2 groups was demonstrated for suture placement, corporotomy incision and implant placement, corporotomy closure, and total procedure duration. Although patients in the eight-dot group required a longer time for suture placement vs the conventional group (486 vs 201 s, respectively, p < 0.001), the durations for the remaining implantation steps, as well as the whole procedure, were significantly shorter for the former group. Corporotomy opening followed by implant placement took significantly less time for the eight-dot group (1090 s) vs the conventional group (1313 s), p <0.001. Moreover, insertion of implant rods was subjectively easier with no need for aggressive bending owing to the extended corporotomy length. Similarly, corporotomy closure using the 8-dot technique was 10.13 minutes swifter than the conventional group (220 s vs. 828 s, respectively, p < 0.001). The total procedure length was over 8 minutes shorter for the eight-dot group as opposed to the conventional group (2527 vs 3027 s, respectively, p < 0.001). In terms of postoperative complications in the form of pain, swelling, hematoma, and infection, there were no significant differences between both groups. Conclusions The eight-dot extended corporotomy technique is a safe and time-saving approach compared to the conventional limited corporotomy technique, making the MPPI procedure more efficient. A swifter procedure decreases both patient exposure to anesthesia and device exposure to air which in turn lowers the risk for potential postoperative complications. Disclosure No.

Efficient technique for evaluation of three-dimensional elastic–plastic fracture mechanics parameters based on equivalent distributed stress concept

This study proposes an efficient technique for the evaluation of the elastic–plastic fracture mechanics (EPFM) parameters of three-dimensional (3D) cracks based on the modified crack cohesive force (CCF) model. In the current method, the 3D crack’s EPFM parameters are analyzed by applying the pseudo crack face traction (CFT) to a two-dimensional (2D) center crack in an infinite plate. This pseudo traction is called the equivalent distributed stress (EDS). The EDS to be applied on the 2D center crack is determined in a manner that reproduces the relationship between crack length and stress intensity factor (SIF) of the intended 3D crack. Once EDS is determined, EPFM parameters for 3D cracks can be obtained instantly by using the center crack’s analytical closed-form solutions. This approach can compute the 3D crack’s EPFM parameters in dramatically less computation time than 3D finite element (FE) analysis. The effectiveness of the proposed method is validated by comparing the EPFM parameters of a 3D penny-shape crack obtained from this method against the reference analytical solutions and numerical FE analysis results. The parameters determined by the present method show excellent agreement with the reference solutions.

High-throughput extraction and automatic purification of alternariol from edible and medicinal herbs based on aptamer-functionalized magnetic nanoparticles.

Mycotoxin contamination is widespread in plants and herbs, posing serious threats to the consumer and human health. Of them, alternariol (AOH) has attracted great attention as an "emerging" mycotoxin in medicinal herbs. However, a specific and high-throughput extraction method for AOH is currently lacking. Thus, developing an efficient pre-treatment technique for AOH detection is extremely vital. Here, a novel automated magnetic solid-phase extraction method was proposed for the highly efficient extraction of AOH. Combining the aptamer-functionalized magnetic nanoparticles (AMNPs) and the automatic purification instrument, AOH could be extracted in medicinal herbs in high throughput (20 samples) and a short time (30min). The main parameters affecting extraction were optimized, and the method was finally carried out by incubation AMNPs with 3mL of sample solution for 10min, and then desorption in 75% methanol for liquid-phase detection. Under optimal conditions, good reproducibility, stability, and selectivity were realized with an adsorption capacity of 550.84ng/mg. AOH extraction in three edible herbs showed good resistance to matrix interference with recovery rates from 86% to 111%. In combination with AMNPs and the automatic purification instrument, high-throughput and labor-free extraction of AOH in different complex matrices was achieved, which could be extended in other complex matrices.

Highly efficient separation of Sc3+ and Y3+ in acid solution by a graphene oxide membrane with interlayer sieving

Sc and Y are key rare earth elements and are widely used in lamp phosphors, lasers and high-performance alloys. However, highly efficient extraction and separation of Sc3+ and Y3+ is laborious, harmful, slow, and costly, strongly necessitating more efficient extraction and separation techniques. Here, we produced hydrated Sc3+- and hydrated Y3+-controlled graphene oxide (GO) membranes and find that both hydrated cations were completely self-rejected by the membrane. By combining this self-rejection effect of the larger hydrated Y3+-controlled GO membrane and the rapid passage of the membrane through the smaller hydrated Sc3+, we proposed a strategy to separate Sc3+ and Y3+ by using a hydrated Y3+-controlled GO membrane. The experimental results show that the permeation rate of Sc3+ exceeds that of Y3+ when the separation factor reaches 4.02, which can be attributed to the interlayer sieving effects of the GO membrane. Our finding illustrates the use of a forward osmosis process with a GO membrane for the efficient separation of Sc3+ and Y3+ by interlayer sieving, which provides a new effective and eco-friendly method for the separation of rare earth elements.

An Efficient Aspect-based Sentiment Classification with Hybrid Word Embeddings and CNN Framework

Background: As the e-commerce product reviews and social media posts are increasing enormously, the size of the database for polarity/ sentiment detection is a challenging task, and again, predicting polarities associated with respect to aspect terms end to end in a sentence is a havoc in real-time applications. Human behavior is influenced by the various opinions generated in society. Public opinion influences our decisions most often. Businesses and establishments always need to collect the opinion of the society, which they try to obtain using customer feedback forms and questionnaires or surveys, which help them to be aware of the shortcomings if any, and to use suggestions to improve quality. It works in the same way for customers as well and the opinions of other customers about a particular product can come in handy when deciding to buy a product. Objectives: In this work, an efficient Aspect-based Sentiment Classification technique has been introduced with a hybrid, multiple-word embedding methods and implemented using the CNN framework on large databases. Methods: Most of the traditional models have a limitation on the dependency for one or more similar types of aspect words for sentiment classification problem. However, these conventional models such as TF-ID, Word 2Vec and Glove method consumes much more time for word embedding process and Aspect terms generation and further process of aspect level sentiment classification. Further, these models are facing problems of high true negative rate and misclassification rate on large aspect databases in sentiment classification. In this article, we have introduced an efficient Proposed ensemble word embedding model in the CNN network and defined Hybrid Word2 Vec method, Hybrid Glove word embedding method and Hybrid Random Forest model for sentiment classification. Results: Experiments on a widely used benchmark prove that the proposed word embedding method- based classification technique results in to higher true positive rate with minimal misclassifications and also supports better runtime and accuracy than the traditional word embedding-based aspect level classification approaches. Conclusion: In this article, a hybrid ensemble feature ranking-based classification model is proposed on the large aspect databases. In this work, advanced multiple-word embedding methods are implemented to improve the essential feature extraction problem in the aspect level sentiment process. These multiple-word embedding methods are applied to the sentiment databases in the CNN framework.