Efficient Approach Research Articles

Spiral-shaped dual-port microstrip antenna for 5G/6G applications with wideband-to-narrowband transition using shape-memory alloy

Abstract We propose a compact, thermally reconfigurable dual-port microstrip antenna featuring a spiral-shaped design and shape-memory alloy (SMA) that enable switching between wideband and narrowband operation for 5G/6G communication systems. The SMA’s thermally induced shape-memory behavior allows reconfiguration in response to temperature changes without the need for electronic or optical control circuits, thus avoiding issues such as self-interference problem, high costs, regular maintenance requirements, and durability concerns. In the wideband mode, measured results show that Port 1 covers 4.7–10.5 GHz and Port 2 covers 4.5–8.3 GHz, which closely agrees with simulations. When the SMA is activated by heat, the antenna switches to the narrowband mode, where Port 1 operates at 7.6 and 9.5 GHz, and Port 2 operates at 8.9 GHz. A ground-plane isolation element ensures low coupling between the ports, with the envelope correlation coefficient remaining below 0.1 across all configurations. The antenna reaches a peak gain of 5.2 dBi and maintains consistent performance through repeated switching. By combining spiral-shaped geometry with a responsive smart material, this work presents a novel and efficient approach for designing reconfigurable dual-port antennas suitable for future wireless technologies.

Polymetallic copper-lead-zinc ores flotation process transforming based on MLA

Sulfide copper ores are commonly accompanied by pyrite, galena, and sphalerite, which creates a substantial diffi-culty in achieving selective separation during the flotation process. Even with the progress made in flotation tech-niques, there is an ongoing critical demand for efficient approaches that can reduce the impurity levels in the con-centrate. The concentrates obtained from the Xinyuan mine facility were analyzed using AMICS, revealing that the similar surface properties of minerals like chalcopyrite, bornite, galena, and sphalerite predominantly contribute to the elevated impurity content in the concentrates, with unliberated impurities being of secondary importance. To decrease the presence of liberated or unliberated impurities, the new flotation process includes regrinding and more selective reagents. This new flotation process has effectively increased the recovery rate of copper from 83.33% to 90.32%, while reducing the recovery rates of lead and zinc to 4.72% from 10.56% and to 3.14% from 4.51%, respec-tively, in copper concentrate. Additionally, it has resulted in an improvement in both the grade and recovery of lead, increasing from 55.57% to 61.14% and from 74.37% to 84.95%, respectively. Likewise, the grade and recovery of zinc have seen an increase, reaching from 52.60% to 55.47% and from 83.73% to 88.16%, respectively.

A novel image fusion approach for visual enhancement of facial vessels in surgical filler injections

ABSTRACT In the absence of visual perception of the subcutaneous blood vessels, the performance of facial filling procedures may result in serious complications, such as blindness, cerebral infarction, and potentially fatal outcomes. In order to improve the visibility of facial vessels to ensure the filler injection procedure safe, this paper reports an efficient physical-based image fusion approach that combines simultaneously captured visible and near-infrared (NIR) images to produce vessel-highlighted effects. The enhancement of vessels visibility involves applying a customized sharpening filter to the invisible NIR image prior to merging it with the color facial image. The quantitative and subjective assessments of the fusion images indicate that the suggested approach is capable of efficiently reproducing a clear representation of blood vessels and realistically preserving their color and structural texture. Therefore, this new approach may be utilized to improve the efficiency and accuracy in locating or marking facial blood vessels and enhance the injection safety and precision of surgical filler injections.

The Reliability and Validity of Star Performer™ a Computerized tool for Quantifying the Star Excursion Balance Test

Background The Star Excursion Balance Test (SEBT) is well recognized in both clinical and research settings as a reliable, valid, and responsive assessment. However, the SEBT is time consuming and inconvenient. To address this limitation, a new device called the Star Performer™ has been developed to improve the efficiency of SEBT. # Purpose To investigate the test-retest reliability of Star Performer™ device and compare its validity to traditional SEBT methods. Study Design Cross-sectional study Methods Twenty-five subjects with lower extremity injuries participated in this study. Each subject performed the SEBT twice, with approximately seven days between tests. The Star Performer™ device and a tape measure were used to record three test trials for each test direction with the average of the three reach distances being used for analysis. Test-retest reliability was evaluated by calculating the intra-class correlation coefficients (ICC 3,1) between the average reaching distance for each SEBT direction across the two testing sessions. To assess the validity of the Star Performer™ device, the averaged reaching distance for each SEBT direction was compared with the measurements obtained from the tape measure. Results Seventeen females (68%) and eight males (32%) with lower extremity injuries (mean age= 23.6 years, SD=3.9, range from 19-35) participated. The Star Performer™ demonstrated excellent test-retest reliability, with ICC 3,1 values ranging from 0.85 to 0.93 for the eight SEBT directions. The minimal detectable change at the 95% confidence level (MDC95) ranged from 2.56 to 5.37% for the eight directions. The Pearson correlation coefficients between the Star Performer™ and tape measure recordings ranged from 0.90 to 0.94 for the eight directions. Conclusion This study provides evidence supporting the test-retest reliability and validity of the Star Performer™ for assessing SEBT performance. These findings suggest that Star Performer™ offers a precise and efficient approach to evaluate SEBT performance in individuals with lower extremity injuries. Level of Evidence Level 3b

Machine-guided cell-fate engineering.

Machine-guided cell-fate engineering.

Automatic Detection of Standard Planes in Fetal Ultrasound Images based on Convolutional Neural Networks and Ensemble Learning

Introduction: The wide application of artificial intelligence in various fields has shown its potential to aid medical diagnosis. Ultrasound is an important tool used to evaluate fetal development and diagnose fetal diseases. Methods: However, traditional diagnostic methods are time-consuming and laborious. Therefore, we constructed an end-to-end automatic diagnosis system based on convolutional neural networks using ensemble learning to improve the robustness and accuracy of the system. Results: The system classifies the ultrasound image dataset into six categories, namely, abdomen, brain, femur, thorax, maternal cervix, and other planes. Conclusion: After experiments, the results showed that the proposed end-to-end system can considerably improve the detection accuracy of the standard plane.

Chondroitin sulfate: From bioactive molecule to versatile drug delivery system for advancing regenerative medicine.

Chondroitin sulfate: From bioactive molecule to versatile drug delivery system for advancing regenerative medicine.

A Hybrid PKI and Spiking Neural Network Approach for Enhancing Security and Energy Efficiency in IoMT-Based Healthcare 5.0.

In the rapidly evolving field of healthcare 5.0, the Internet of Medical Things (IoMT) is expected to be an enabler that allows smart medical devices to collaborate and communicate with healthcare networks to speed up procedures, enhance care, and improve disease management. However, one of the critical issues for these networks still remains the secure and energy-efficient transmission of sensitive patient data. Thus, a novel security framework is proposed in this work, in which a Public Key Infrastructure- Energy-Efficient Routing Protocol (PKI-EERP) with a Zebra Optimization Algorithm (ZOA) is incorporated in spiking neural networks. The method combines data security robustness of the spiking neural networks to detect anomalies and check for access control purposes, with the PKI encryption to provide safe encryption and key management. The ZOA optimizes energy consumption in WSNs, and as a result transmission energy is significantly reduced up to 35% compared to other implementations, and the network lifetime is increased by about 30% through effective load balancing. It enhances both the privacy and energy efficiency that are essential for the safe and reliable operation of IoMT systems in contemporary healthcare environments, thus improving patient outcomes as well as standards of operations.

Phage isolation, characterization, and antibiotic resistance profiling in Avian pathogenic Escherichia coli: Integrating data for a possible novel AMR surveillance model.

Phage isolation, characterization, and antibiotic resistance profiling in Avian pathogenic Escherichia coli: Integrating data for a possible novel AMR surveillance model.

Cellulose-derived biocatalysts and neutralizing gels for pesticides: How to eliminate and avoid intoxication?

Cellulose-derived biocatalysts and neutralizing gels for pesticides: How to eliminate and avoid intoxication?

Fabrication of a flexible nanofiber membrane for SERS detection of pollutants: An efficient and eco-friendly approach.

Fabrication of a flexible nanofiber membrane for SERS detection of pollutants: An efficient and eco-friendly approach.

An efficient lysate-based approach for biosynthesis of the pyrrolobenzodiazepine natural product tilimycin.

An efficient lysate-based approach for biosynthesis of the pyrrolobenzodiazepine natural product tilimycin.

Improving care of older adults with cancer: A randomized trial.

11002 Background: Undertreated symptoms are common among older adults with cancer. Previously, a lay health worker (LHW)-led proactive symptom assessment intervention was associated with reduced symptoms in one community clinic. Yet, the effect on acute care use, total costs, and end-of-life (EOL) care at scale remains unknown. Methods: Adults ages 75 years or older who were Medicare Advantage beneficiaries with newly diagnosed cancer were eligible to participate in this randomized trial across 43 clinics in Southern California and Arizona. Participants were randomized 1:1 into a control group (usual care alone) or an intervention group (usual care and LHW-led proactive, telephone-based weekly symptom assessments for 12 months using the validated Edmonton Symptom Assessment System) with a planned enrollment of at least 200 in both groups. The LHW reviewed assessments with a physician assistant who conducted follow-up for symptoms that changed by 2 points from a prior assessment or were rated 4 or greater. We used generalized regression models to compare acute care use and total costs (obtained from payer claims data) for 12-months follow-up or death, whichever was first, offset for length of follow-up, and, among those who died, compared EOL acute care use, costs, and acute care facility deaths. Results: 416 patients participated (216 control; 200 intervention) with median age of 82 years (range 75-99); 205 (49.28%) were Hispanic or Latino, 10 (2.4%) African American or Black, 12 (2.88%) Asian, 2 (0.48%) Native Hawaiian, 1 (0.24%) Pacific Islander, 180 (43.3%) Non-Hispanic White, 6 (1%) other; 219 (52.6%) were male; 118 (28.3%) had gastrointestinal, 92 (22%) had genitourinary, 62 (14.9%) had breast, and 48 (11.5%) had thoracic cancer; 171 (41%) had stage 4 disease. The intervention group had 53% lower odds of emergency department use (OR: 0.47, 95% CI 0.37-0.62) and 68% lower odds of hospital use (OR: 0.32, 95% CI 0.20-0.51) than the control group. Among deceased participants (71 (32.9%) control; 71 (35.5%) intervention), the intervention group had 68% lower odds of acute care (OR: 0.32, 95% CI 0.12-0.88), lower total costs of care by $12,000 USD per participant (p = 0.01), and 75% lower odds of an acute care facility death (OR 0.25; 95% CI 0.08-0.77). Conclusions: This proactive symptom assessment intervention may be one sustainable, scalable, efficient, and effective approach to improve care for older adults with cancer. Clinical trial information: NCT04463992 .

48-month comperative evaluation of a novel glass ionomer cement and a resin composite in restoring non-carious cervical lesions of patients with systemic diseases: A randomized clinical trial.

48-month comperative evaluation of a novel glass ionomer cement and a resin composite in restoring non-carious cervical lesions of patients with systemic diseases: A randomized clinical trial.

GBDTSVM: Combined Support Vector Machine and Gradient Boosting Decision Tree Framework for efficient snoRNA-disease association prediction.

GBDTSVM: Combined Support Vector Machine and Gradient Boosting Decision Tree Framework for efficient snoRNA-disease association prediction.

An efficient grid-based path planning approach using improved artificial bee colony algorithm

An efficient grid-based path planning approach using improved artificial bee colony algorithm

Liposome/AZIF-8 Janus nanoplatforms: Promising nanocarriers for improving chemotherapeutic outcomes in breast cancer treatment.

Liposome/AZIF-8 Janus nanoplatforms: Promising nanocarriers for improving chemotherapeutic outcomes in breast cancer treatment.

Efficient separation of lignocellulose component and furfural production from hemicellulose using a γ-valerolactone/H2O system.

Efficient separation of lignocellulose component and furfural production from hemicellulose using a γ-valerolactone/H2O system.

Non-invasively collected buccal cell mRNA and potential for a novel breast cancer signal.

e12539 Background: Breast cancer remains the most frequently diagnosed cancer globally, despite current available diagnostic methods such as mammograms and ultrasounds. While DNA genetic testing is widely used clinically, messenger RNA (mRNA) analysis can provide complementary diagnostic information, particularly regarding inflammatory pathways associated with cancer development. Intercellular mRNA communication is an essential hallmark of chronic inflammation associated with cancer development, and it is important to create an integrative computational tool that will identify unmet personalized human needs related to development of chronic diseases. We present a novel screening procedure combining mRNA genetic markers with machine learning algorithms to enhance breast cancer detection. Methods: Buccal cheek swab samples were collected non-invasively from breast cancer patients and controls across 40 U.S. clinical centers, and a custom microarray chip was developed to analyze 48 mRNA-based cytokine biomarkers, selected for their association with inflammatory pathways and cancer development. Next-generation sequencing was performed using a Thermo Fisher Genestudio S-5 following cDNA target amplification. We used these data to train a linear support vector machine to classify subjects with respect to their cancer status. We were particularly interested in identifying a small subset of these biomarkers that could yield significant results to create a lower-dimensional, efficient classification approach. Results: Our analysis identified a collection of six-biomarker combinations yielding excellent results (F-score ≥0.85). We present the two top-performing biomarker combinations (see table), along with their respective performance metrics. Conclusions: Our results demonstrate the potential of mRNA biomarker panels, combined with machine learning, to generate a signal for detecting breast cancer from non-invasively-collected samples. The high precision and recall values suggest clinical utility for early detection. Summary of top-performing systems for detecting breast cancer. Systems used a combination of six biomarkers selected from a panel of 48 cytokines known to be associated with cancer or inflammatory pathways. BM1 BM2 BM3 BM4 BM5 BM6 P R F1 AUC SYSTEM 1 CASP9 IL1B IL6 RGS2 SLC40A1 STK11 0.892 0.913 0.9 0.897 SYSTEM 2 HAMP IL10 RGS2 SLC22A4 STK11 TGFB1 0.888 0.902 0.892 0.849

A green degumming approach for lignocellulosic kenaf bast using ethanolamine deep eutectic solvent.

A green degumming approach for lignocellulosic kenaf bast using ethanolamine deep eutectic solvent.