Evaluation Criteria Research Articles

A phase 2 study of a brachyury-targeting vaccine in combination with radiation therapy for the treatment of advanced chordoma.

This was a single-arm, phase 2 clinical trial of Bavarian Nordic (BN)-Brachyury vaccine plus radiotherapy (RT) designed to determine the objective response rate (ORR), progression-free survival (PFS), and safety of the combination in chordoma. A total of 29 adult patients with advanced chordoma were treated with two subcutaneous priming vaccine doses of modified vaccinia Ankara-Bavarian Nordic (MVA-BN)-Brachyury and one vaccine dose of fowlpox virus (FPV)-Brachyury before RT. After RT, booster vaccinations were given with FPV-Brachyury every 4 weeks for 4 doses, then every 12 weeks (week 110). A minimum RT dose of >8 Gy in one fraction for each target was required. Response was evaluated by modified Response Evaluation Criteria in Solid Tumors 1.1 (mRECIST), where only radiated lesions were considered targets, and by standard RECIST 1.1 in a subset of patients. Two of 26 evaluable patients experienced durable partial response (PR) (ORR of 7.7%; 90% confidence interval [CI], 2.6-20.8]) by mRECIST 1.1. A total of 21 patients (80.8%; 90% CI, 65.4-90.3) had stable disease, and three patients (11.5%; 90% CI, 4.7-25.6) had progressive disease as best response per mRECIST 1.1. Median PFS was not reached during the study. This trial confirms the safety of BN-Brachyury and RT. Although the study did not meet the predefined study goal of four responses in 29 patients, we did observe two PRs and a PFS of greater than 2 years. For a vaccine-based study in chordoma, an ultra-rare disease where response rates are low, a randomized study or novel trial designs may be required to confirm activity.

РЕАЛІЗАЦІЯ ДИФЕРЕНЦІЙОВАНОГО ПІДХОДУ ПРИ НАВЧАННІПРОГРАМУВАННЮ МОВОЮ PYTHON ЗДОБУВАЧІВЗАГАЛЬНОЇ СЕРЕДНЬОЇ ОСВІТИ

Students choose their future path starting from school. The learner can determine their abilities when they genuinely understand their potential and prospects in a specific subject or direction. A differentiated approach helps explore the limits of knowledge and encourages its expansion. The paper discusses the implementation of a differentiated approach in teaching computer science, particularly in programming. Tasks are proposed to students, emphasizing the method of solving. Each learner chooses the method that suits them best. Evaluation criteria are provided in advance, helping students identify the aspects of the task to focus on. An example task demonstrating the implementation of a differentiated approach involves calculating the recommended body weight for a woman and a man using the Broca's Formula. Depending on the complexity chosen by the student, this task can be solved using a linear structure, applying branching, or developing a widget. Widgets allow students to demonstrate the use of libraries and functions in the Python programming language. Various solutions in Python and recommendations for the placement of such tasks in the study of a specific topic are also provided. During the defense, all students become acquainted with different task implementations, allowing each student to understand various execution methods and choose a more challenging one next time. The presented example can be extended to other topics, in the study of other programming languages or programming environments. Prospects for further research include developing a system of multi-level programming tasks for the purpose of implementing differentiated learning

Evaluating and classifying market alternatives using the CAPMA technique to assess potential export volume: an application for Turkey’s fig exports

PurposeAppropriate target market selection and classification are complex, time-consuming, and strategically important management decisions. The current study proposes and implements a new systematic approach that evaluates and ranks alternative markets’ potential to increase the export volume of Turkey’s fig exports.Design/methodology/approachThe classification approach of potential market alternatives (CAPMA) method, which was developed to evaluate, compare, and classify alternative markets according to their potential, was used in this study. CAPMA, an objective decision-making technique, is based on calculating the classification coefficient and classifying the alternatives into four dimensions, taking this coefficient into consideration. In the current study, 25 alternative markets were analysed on the basis of four evaluation criteria and classified into four dimensions according to their potential to increase export volume.FindingsAccording to the application results, alternative markets with the greatest potential to increase export volume were identified as the United States of America (USA), Netherlands, China, and Spain. The USA has the greatest potential for expansion of export volume. By implementing correct and effective marketing strategies, fig export volume has the potential to reach very high levels.Originality/valueThe study’s results on alternative markets for fig exports were categorized, countries with greater potential to increase export volume were identified, and findings that could contribute to the development of the sector were obtained. The approach proposed in the current research can be used to determine the target market of many other products, especially agricultural products, whose production is concentrated within a specific geography.

A model for identifying potentially inappropriate medication used in older people with dementia: a machine learning study.

Older adults with dementia often face the risk of potentially inappropriate medication (PIM) use. The quality of PIM evaluation is hindered by researchers' unfamiliarity with evaluation criteria for inappropriate drug use. While traditional machine learning algorithms can enhance evaluation quality, they struggle with the multilabel nature of prescription data. This study aimed to combine six machine learning algorithms and three multilabel classification models to identify correlations in prescription information and develop an optimal model to identify PIMs in older adults with dementia. This study was conducted from January 1, 2020, to December 31, 2020. We used cluster sampling to obtain prescription data from patients 65 yearsand older with dementia. We assessed PIMs using the 2019 Beers criteria, the most authoritative and widely recognized standard for PIM detection. Our modeling process used three problem transformation methods (binary relevance, label powerset, and classifier chain) and six classification algorithms. We identified 18,338 older dementia patients and 36 PIMs types. The classifier chain + categorical boosting (CatBoost) model demonstrated superior performance, with the highest accuracy (97.93%), precision (95.39%), recall (94.07%), F1 score (95.69%), and subset accuracy values (97.41%), along with the lowest Hamming loss value (0.0011) and an acceptable duration of the operation (371s). This research introduces a pioneering CC + CatBoost warning model for PIMs in older dementia patients, utilizing machine-learning techniques. This model enables a quick and precise identification of PIMs, simplifying the manual evaluation process.

Structural health monitoring of a swivel bridge for evaluating builder comfort under train-induced vibration

Abstract The swivel bridge being built overcrossing the railway service line, the builder’s comfort level under the train-induced vibration is one of the critical issues in the bridge construction process. This study compares the applicability and usage limits of existing vibration comfort evaluation indicators for reasonably selected vibration comfort evaluation criteria. A framework is therefore proposed to evaluate builder comfort under train-induced vibrations during the construction process. Taking a swivel bridge overcrossing the Shanghai-Kunming railway line as an example, the structural health monitoring system is performed in three construction stages of the swivel bridge. Then, the acceleration response is measured, the acceleration-based evaluation indicators are compared, and the builder comfort level is evaluated in the three construction stages. The results demonstrate that the on-site measured indicators are close to the standard limits, and the builder comfort on the swivel bridge under the excitation of passing trains should be given attention. 

Multi-Criteria Evaluation of the Institutional and Tax Environment for Business in the EU Economies

The purpose of this study is to evaluate the institutional and tax environment for businesses in 21 countries of the European Union (EU), using a multi-criteria analysis and, in particular, the PROMETHEE II method, based on thirteen evaluation criteria and the ranking of the European economies. Through the research, the importance of factors related to the efficiency of the tax administration, the tax capacity of the country, the growth rate of the economy, the quality of institutions, the level of corruption, the tax burden, the time of tax compliance and the political stability of the country is studied, in the formation of an attractive environment for the development of entrepreneurship in the EU economies. Moreover, the results of the analysis revealed the existence of significant fiscal and institutional differences between the EU economies under investigation, regarding the development of entrepreneurship. These differences are due to the size of the economy, the institutions, the history, the economic crises of each country and a wide range of dissimilar policy recommendations, which reflect asymmetric policy responses. The study concludes by offering theoretical and political recommendations to improve the institutional and fiscal environment in EU economies so that entrepreneurship can play an important role in improving the economic and social situation of a country.

Criteria for selection of technology to exploit groundwater in water-scarce area in Vietnam

Abstract. Water extraction solutions in the high mountainous areas of Northern Vietnam commonly include rainwater harvesting, dug wells, drilled wells, groundwater springs, and hanging lakes. However, many water supply systems operate inefficiently and lack flexibility. This study established 10 criteria for selecting groundwater exploitation technology, divided into three groups: water resources, economic and technical, social, and environmental criteria. These criteria aim to identify appropriate water extraction technologies suitable for high mountainous and water-scarce regions, ensuring the long-term and efficient operation of water supply systems. The Geographic Information System (GIS) approach was utilized, integrating the criteria using the Analytical Hierarchy Process (AHP) method to select suitable water extraction technologies. The research results indicate that the evaluation criteria for determining suitable areas for implementing sustainable water extraction technologies, and the weights assigned to these criteria, ensure a consistent ratio (CR) <10 % according to the hierarchical analysis method. This article presents the results of identifying areas suitable for implementing groundwater extraction technologies using drilled wells, based on seven criteria within three groups: water resources, economic and technical, and social criteria. The GIS approach has been employed, and the criteria have been integrated using the AHP to select and determine the areas suitable for implementing groundwater extraction technologies using drilled wells.

Enhancing Software Developer Selection with Integrated F-AHP and F-TOPSIS Techniques

This study focuses on enhancing the selection process for software developers by integrating the Fuzzy Analytic Hierarchy Process (F-AHP) and the Fuzzy Technique for Order Preference by Similarity to Ideal Solution (F-TOPSIS). The primary objective is to address the uncertainties and ambiguities in determining evaluation criteria and weights, thereby facilitating accurate decision-making when faced with multiple criteria and alternatives. Conducted within a software development company in Bandung, Indonesia, the study involved evaluating ten potential candidates for the software developer position. The methodology employed F-AHP to assess the importance of each criterion through pairwise comparisons, and F-TOPSIS to rank the candidates based on these criteria weights. The results revealed that Candidate CK-7 exhibited the highest closeness coefficient (CCi), making them the top candidate, while CK-4 ranked the lowest. This integrated approach provided a systematic and transparent framework for decision-making, demonstrating its effectiveness in optimizing recruitment processes. The study contributes to the field by offering a robust decision-making tool that can be adapted to various industries, ensuring the selection of high-quality employees who meet necessary competencies, thereby improving overall productivity and performance.

Analysis of tumor regression after concurrent radiochemotherapy for locally advanced hypopharyngeal carcinoma

Objective: To investigate the pathological characteristics of tumor regression and the expression level of chemoradiotherapy resistance-related molecular markers after preoperative concurrent radiochemotherapy in patients with locally advanced hypopharyngeal carcinoma. Methods: The clinical data of 44 patients with locally advanced hypopharyngeal carcinoma who underwent preoperative concurrent radiochemotherapy in the Department of Head and Neck Surgery of Shandong Otolaryngology Hospital from August 2016 to August 2020 were retrospectively analyzed. All patients received preoperative concurrent chemotherapy and radiotherapy. After radiochemotherapy, electronic laryngoscopy and imaging examination were performed to assess the tumor regression status. After 4 weeks, surgical resection was performed, and the specimens of the primary focus were processed as continuous pathological sections. After operation, HE staining and TdT-mediated dUTP nick-end labeling (TUNEL) method were used to detect the distribution characteristics and apoptosis of the remaining cancer focus, and immunohistochemistry was performed to determine the proliferation of the remaining cancer focus and the expression of radiation resistance-related molecular markers [signal transducer and activator of transcription 3 (STAT3), hypoxia-inducible factor-1alpha (HIF-1α), sex determining region Y-box 2 (SOX2), and P53]. Results: A total of 44 patients were included, all of whom were male, with a mean age of (58.3±3.5) years. There were 40 cases of pyriform sinus carcinoma and 4 cases of posterior pharyngeal wall carcinoma. Twenty-nine cases were in stage T3 and 15 cases were in stage T4. There were 6 stage Ⅲ cases and 38 stage Ⅳ cases. According to the response evaluation criteria in solid tumors (RECIST), 13 patients achieved complete response (CR), 22 patients had partial response (PR), and 9 patients achieved stable disease (SD) after concurrent radiochemotherapy. The primary lesion resection methods included 19 cases of hypopharyngeal circumferential resection and 2 cases of total laryngectomy and partial hypopharyngeal resection. Twenty-three cases underwent supracricoid cartilage subtotal laryngectomy cricoid tongue fixation (CHP). Among 22 patients with PR, 10 had large PR (remission rate ≥70%) and 12 had small PR (remission rate <70%). The residual tumor was found in 30 patients (68.2%) after resection of all primary lesions by HE staining of pathological sections, of which 3 patients (3/13) with CR had residual cancer, all of which were focal residues. In large PR patients, residual cancer was detected in 6 cases (6/10), scattered in 4 cases, and focal residual in 2 cases, respectively. Large residual tumors were detected in small PR and SD patients. TUNEL method did not show any sign of apoptosis in 30 specimens with residual cancer focus, and the positive expression rate of Ki-67 was less than 10%. The expression of STAT3 (3.40±2.49 vs 5.23±3.02, t=-2.932, P=0.007) in 19 cases (63.3%) and HIF-1α (3.73±2.66 vs 6.97±3.05, t=-4.45, P<0.001) in 22 cases (73.3%) of residual cancer were significantly higher than those before radiochemotherapy. Other molecular markers showed no significant changes. All patients were followed up for 3 years. The 2-year survival rate was 59.3%, and the 3-year survival rate was 54.1%. Conclusions: Preoperative radiochemotherapy can make some patients with locally advanced hypopharyngeal carcinoma achieve complete or significant remission in clinical evaluation, but pathological detection still shows some residual cancer lesions with enhanced anti-apoptosis ability and decreased proliferation activity.

Formulation and evaluation of amoxapine mucoadhesive buccal films

Among innovative drug delivery methods, buccal mucoadhesive systems have been attracting much interest recently because of their capacity to stick to the oral mucosa, stay there, and gradually release their drug content. By improving medication absorption through the oral mucosa and reducing the hepatic first-pass impact, buccal mucoadhesive films can increase the drug's bioavailability and enhance its therapeutic effect. The current study aimed to synthesize the medicine as a buccal bioadhesive film, which reduces the frequency of dosage form administration by releasing the drug at a sufficient concentration over time. Because this formulation is simple to administer and requires no water to swallow, improved patient compliance is one of its benefits. Dissolving profile as investigated in USP dissolving apparatus type 1 using saliva at pH 6.8. The impact of factors such as polymer type, concentration, and release profile of Amoxapine was investigated. The formulation was optimized Based on several evaluation criteria, including drug content and in-vitro drug release. Formulation F6 successfully releases the drug in 7 hours. The stability studies followed ICH recommendations, and the results showed that the optimized formulation was stable. The IR spectra demonstrated the stable qualities of Amoxapine in a mixture of polymers utilized and revealed the absence of interaction between the drug and the selected polymer.

Improving the classification of a nanocomposite using nanoparticles based on a meta-analysis study, recurrent neural network and recurrent neural network Monte-Carlo algorithms

This paper may be the first meta-analysis that presents a comprehensive synthesis of scientific works spanning the last five years, focusing on methodologies and results related to the analysis of nanocomposite using nanoparticles. The primary objective is to identify the optimal algorithm using software information and leading to better classification methodology. Specifically, this study comes up with the advantages and the drawbacks of the most used algorithms and proposes an enhancement and performance of Recurrent Neural Networks based on Long Short Term Memory (LSTM) neurons. Besides, a comparison of Deep Learning methods for the classification of polymeric nanoparticles, with polypropylene serving as a case study will be implemented. Experiment comparisons are conducted to assess with one physical property, later expanded to four properties and finally to eight properties. Neural networks, including Artificial Neural Networks (ANN), Recurrent Neural Networks (RNN), and Recurrent Neural Networks-Monte Carlo, are employed for simulations. The evaluation criteria encompass accuracy, calculation time, mean square error (MSE) and other metrics. The findings contribute to the selection of an optimal algorithm for the analysis of polymeric nanoparticles, emphasizing the potential of Deep Learning methodologies, particularly Recurrent Neural Networks Monte Carlo, in advancing classification accuracy and efficiency.

Enhancing prostate cancer diagnosis and reducing unnecessary biopsies with [18F]DCFPyL PET/CT imaging in PI-RADS 3/4 patients

For patients presenting with prostate imaging reporting and data system (PI-RADS) 3/4 findings on magnetic resonance imaging (MRI) examinations, the standard recommendation typically involves undergoing a biopsy for pathological assessment to ascertain the nature of the lesion. This course of action, though essential for accurate diagnosis, invariably amplifies the psychological distress experienced by patients and introduces a host of potential complications associated with the biopsy procedure. However, [18F]DCFPyL PET/CT imaging emerges as a promising alternative, demonstrating considerable diagnostic efficacy in discerning benign prostate lesions from malignant ones. This study aims to explore the diagnostic value of [18F]DCFPyL PET/CT imaging for prostate cancer in patients with PI-RADS 3/4 lesions, assisting in clinical decision-making to avoid unnecessary biopsies. 30 patients diagnosed with PI-RADS 3/4 lesions through mpMRI underwent [18F]DCFPyL PET/CT imaging, with final biopsy pathology results as the “reference standard”. Diagnostic performance was assessed through receiver operating characteristic (ROC) analysis, evaluating the diagnostic efficacy of molecular imaging PSMA (miPSMA) visual analysis and semi-quantitative analysis in [18F]DCFPyL PET/CT imaging. Lesions were assigned miPSMA scores according to the prostate cancer molecular imaging standardized evaluation criteria. Among the 30 patients, 13 were pathologically confirmed to have prostate cancer. The sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of visual analysis in [18F]DCFPyL PET/CT imaging for diagnosing PI-RADS 3/4 lesions were 61.5%, 88.2%, 80.0%, 75.0%, and 76.5%, respectively. Using SUVmax 4.17 as the optimal threshold, the sensitivity, specificity, positive predictive value, negative predictive value, and accuracy for diagnosis were 92.3%, 88.2%, 85.7%, 93.8%, and 90.0%, respectively. The area under the ROC curve (AUC) for semi-quantitative analysis was 0.94, significantly higher than visual analysis at 0.80. [18F]DCFPyL PET/CT imaging accurately diagnosed benign lesions in 15 (50%) of the PI-RADS 3/4 patients. For patients with PI-RADS 4 lesions, the positive predictive value of [18F]DCFPyL PET/CT imaging reached 100%. [18F]DCFPyL PET/CT imaging provides potential preoperative prediction of lesion nature in mpMRI PI-RADS 3/4 patients, which may aid in treatment decision-making and reducing unnecessary biopsies.

Navigating the Future of 3D Laparoscopic Liver Surgeries: Visualization of Internal Anatomy on Laparoscopic Images With Augmented Reality.

Liver tumor resection requires precise localization of tumors and blood vessels. Despite advancements in 3-dimensional (3D) visualization for laparoscopic surgeries, challenges persist. We developed and evaluated an augmented reality (AR) system that overlays preoperative 3D models onto laparoscopic images, offering crucial support for 3D visualization during laparoscopic liver surgeries. Anatomic liver structures from preoperative computed tomography scans were segmented using open-source software including 3D Slicer and Maya 2022 for 3D model editing. A registration system was created with 3D visualization software utilizing a stereo registration input system to overlay the virtual liver onto laparoscopic images during surgical procedures. A controller was customized using a modified keyboard to facilitate manual alignment of the virtual liver with the laparoscopic image. The AR system was evaluated by 3 experienced surgeons who performed manual registration for a total of 27 images from 7 clinical cases. The evaluation criteria included registration time; measured in minutes, and accuracy; measured using the Dice similarity coefficient. The overall mean registration time was 2.4±1.7 minutes (range: 0.3 to 9.5min), and the overall mean registration accuracy was 93.8%±4.9% (range: 80.9% to 99.7%). Our validated AR system has the potential to effectively enable the prediction of internal hepatic anatomic structures during 3D laparoscopic liver resection, and may enhance 3D visualization for select laparoscopic liver surgeries.

Comparison of robot-assisted versus fluoroscopy-guided transforaminal lumbar interbody fusion (TLIF) for lumbar degenerative diseases: a systematic review and meta-analysis of randomized controlled trails and cohort studies

BackgroundAs an emerging technology in robot-assisted (RA) surgery, the potential benefits of its application in transforaminal lumbar interbody fusion (TLIF) lack substantial support from current evidence.ObjectiveWe aimed to investigate whether the RA TLIF is superior to FG TLIF in the treatment of lumbar degenerative disease.MethodsWe systematically reviewed studies comparing RA versus FG TLIF for lumbar degenerative diseases through July 2022 by searching PubMed, Embase, Web of Science, CINAHL (EBSCO), Chinese National Knowledge Infrastructure (CNKI), WanFang, VIP, and the Cochrane Library, as well as the references of published review articles. Both cohort studies (CSs) and randomized controlled trials (RCTs) were included. Evaluation criteria included the accuracy of percutaneous pedicle screw placement, proximal facet joint violation (FJV), radiation exposure, duration of surgery, estimated blood loss (EBL), and surgical revision. Methodological quality was assessed using the Cochrane risk of bias and ROBINS-I Tool. Random-effects models were used, and the standardized mean difference (SMD) was employed as the effect measure. We conducted subgroup analyses based on surgical type, the specific robot system used, and the study design. Two investigators independently screened abstracts and full-text articles, and the certainty of evidence was graded using the GRADE (Grading of Recommendations Assessment, Development and Evaluation) approach.ResultsOur search identified 539 articles, of which 21 met the inclusion criteria for quantitative analysis. Meta-analysis revealed that RA had 1.03-folds higher “clinically acceptable” accuracy than FG (RR: 1.0382, 95% CI: 1.0273–1.0493). And RA had 1.12-folds higher “perfect” accuracy than FG group (RR: 1.1167, 95% CI: 1.0726–1.1626). In the case of proximal FJV, our results indicate a 74% reduction in occurrences for patients undergoing RA pedicle screw placement compared to those in the FG group (RR: 0.2606, 95%CI: 0.2063- 0.3293). Seventeen CSs and two RCTs reported the duration of time. The results of CSs suggest that there is no significant difference between RA and FG group (SMD: 0.1111, 95%CI: -0.391–0.6131), but the results of RCTs suggest that the patients who underwent RA-TLIF need more surgery time than FG (SMD: 3.7213, 95%CI: 3.0756–4.3669). Sixteen CSs and two RCTs reported the EBL. The results suggest that the patients who underwent RA pedicle screw placement had fewer EBL than FG group (CSs: SMD: -1.9151, 95%CI: -3.1265–0.7036, RCTs: SMD: -5.9010, 95%CI: -8.7238–3.0782). For radiation exposure, the results of CSs suggest that there is no significant difference in radiation time between RA and FG group (SMD: -0.5256, 95%CI: -1.4357–0.3845), but the patients who underwent RA pedicle screw placement had fewer radiation dose than FG group (SMD: -2.2682, 95%CI: -3.1953–1.3411). And four CSs and one RCT reported the number of revision case. The results of CSs suggest that there is no significant difference in the number of revision case between RA and FG group (RR: 0.4087,95% CI 0.1592–1.0495). Our findings are limited by the residual heterogeneity of the included studies, which may limit the interpretation of the results.ConclusionIn TLIF, RA technology exhibits enhanced precision in pedicle screw placement when compared to FG methods. This accuracy contributes to advantages such as the protection of adjacent facet joints and reductions in intraoperative radiation dosage and blood loss. However, the longer preoperative preparation time associated with RA procedures results in comparable surgical duration and radiation time to FG techniques. Presently, FG screw placement remains the predominant approach, with clinical surgeons possessing greater proficiency in its application. Consequently, the integration of RA into TLIF surgery may not be considered the optimal choice.Systematic review registrationPROSPERO CRD42023441600.

Is MRI ready to replace biopsy during active surveillance?

Active surveillance (AS) is a conservative management option recommended for patients diagnosed with low-risk prostate cancer (PCa) and selected cases with intermediate-risk PCa. The adoption of prostate MRI in the primary diagnostic setting has sparked interest in its application during AS. This review aims to examine the role and performance of multiparametric MRI (mpMRI) across the entire AS pathway, from initial stratification to follow-up, also relative to the utilization of the Prostate Cancer Radiological Estimation of Change in Sequential Evaluation (PRECISE) criteria. Given the high negative predictive value of mpMRI in detecting clinically significant PCa (csPCa), robust evidence supports its use in patient selection and risk stratification at the time of diagnosis or confirmatory biopsy. However, conflicting results have been observed when using MRI in evaluating disease progression during follow-up. Key areas requiring clarification include addressing the clinical significance of MRI-negative csPCa, optimizing MRI quality, determining the role of biparametric MRI (bpMRI) or mpMRI protocols, and integrating artificial intelligence (AI) for improved performance. CLINICAL RELEVANCE STATEMENT: MRI plays an essential role in the selection, stratification, and follow up of patients in active surveillance (AS) for prostate cancer. However, owing to existing limitations, it cannot fully replace biopsies in the context of AS. KEY POINTS: Multiparametric MRI (mpMRI) has become a crucial tool in active surveillance (AS) for prostate cancer (PCa). Conflicting results have been observed regarding multiparametric MRI efficacy in assessing disease progression. Standardizing MRI-guided protocols will be critical in addressing current limitations in active surveillance for prostate cancer.

OVAR-BPnet: A General Pulse Wave Deep Learning Approach for Cuffless Blood Pressure Measurement.

Pulse wave analysis, a non-invasive and cuffless approach, holds promise for blood pressure (BP) measurement in precision medicine. In recent years, pulse wave learning for BP estimation has undergone extensive scrutiny. However, prevailing methods still encounter challenges in grasping comprehensive features from pulse waves and generalizing these insights for precise BP estimation. In this study, we propose a general pulse wave deep learning (PWDL) approach for BP estimation, introducing the OVAR-BPnet model to powerfully capture intricate pulse wave features and showcasing its effectiveness on multiple types of pulse waves. The approach involves constructing population pulse waves and employing a model comprising an omni-scale convolution subnet, a Vision Transformer subnet, and a multilayer perceptron subnet. This design enables the learning of both single-period and multi-period waveform features from multiple subjects. Additionally, the approach employs a data augmentation strategy to enhance the morphological features of pulse waves and devise a label sequence regularization strategy to strengthen the intrinsic relationship of the subnets' output. Notably, this is the first study to validate the performance of the deep learning approach of BP estimation on three types of pulse waves: photoplethysmography, forehead imaging photoplethysmography, and radial artery pulse pressure waveform. Experiments show that the OVAR-BPnet model has achieved advanced levels in both evaluation indicators and international evaluation criteria, demonstrating its excellent competitiveness and generalizability. The PWDL approach has the potential for widespread application in convenient and continuous BP monitoring systems.

Adequacy of defects liability periods for public construction projects in Ghana

PurposeThe practice of the defects liability period (DLP) is a risk management strategy meant to secure durable and high-quality works. However, construction products continue to malfunction even after the expiration of DLPs. This study seeks to determine the adequacy of DLPs existing in the construction industry and propose appropriate DLPs for construction projects in the Ghanaian construction industry.Design/methodology/approachApplying quantitative research strategy, 124 questionnaires were retrieved from construction professionals surveyed. The data obtained were analysed using descriptive statistics, Cramer’s V and the significance test with the aid of Stata software.FindingsIt was found that defects start showing in both buildings and roads within 12 months after being handed over for the client’s use. The significance test and Cramer’s V analysis indicate low concordance amongst respondents that the 6–12 month DLPs existing in Ghana are adequate. It is found that the existing DLP practice does not provide sufficient security to clients.Practical implicationsConstruction project clients will need to include the tenderer’s proposed DLP as part of the tender evaluation criteria with the objective of picking up a signal of the quality of work to be delivered.Originality/valueThis paper is one of the pioneering studies addressing the issue of the adequacy of DLPs in the construction industry in the Sub-Saharan Africa region. The findings trigger policy and regulatory changes in conditions guiding construction contracts procured in most developing countries that have adopted and adapted to the World Bank Public Procurement Guidelines.

Optimized Grid Partitioning and Scheduling in Multi-Energy Systems Using a Hybrid Decision-Making Approach

This paper presents a thorough review of our state-of-the-art technique for enhancing dynamic grid partitioning and scheduling in multi-energy source systems. We use a hybrid approach to T-spherical fuzzy sets, combining the alternative ranking order method accounting for the two-step normalization (AROMAN) method for alternating ranking order to enable two-step normalisation with the method based on removal effects of criteria (MEREC) for eliminating criteria effects. This enables us to obtain the highest level of accuracy from our findings. To ascertain the relative importance of these criteria, we use MEREC to perform a rigorous examination of the influence that each evaluation criterion has on the outcomes of the decision-making process. In addition, we use AROMAN to provide a strong foundation for assessing potential solutions by accounting for spherical fuzzy sets to account for any ambiguity. We illustrate how our approach successfully considers several factors, such as social acceptability, technical feasibility, environmental sustainability, and economic feasibility, through the analysis of an extensive case study. Our approach provides decision-makers (DMs) with a rigorous and rational framework for assessing and choosing the best grid division and scheduling options. This is done in an effort to support the administration and design of resilient and sustainable multi-energy systems. This research contributes to the growing body of knowledge in this area by offering insights that help to direct policy, planning, and investment decisions in the shift towards more sustainable energy infrastructures. Moreover, it adds to the growing body of information on multi-criteria decision-making (MCDM) in energy system optimization.

Metaheuristic algorithms and their applications in wireless sensor networks: review, open issues, and challenges

AbstractMetaheuristic algorithms have wide applicability, particularly in wireless sensor networks (WSNs), due to their superior skill in solving and optimizing many issues in different domains. However, WSNs suffer from several issues, such as deployment, localization, sink node placement, energy efficiency, and clustering. Unfortunately, these issues negatively affect the already limited energy of the WSNs; therefore, the need to employ metaheuristic algorithms is inevitable to alleviate the harm imposed by these issues on the lifespan and performance of the network. Some associated issues regarding WSNs are modelled as single and multi-objective optimization issues. Single-objective issues have one optimal solution, and the other has multiple desirable solutions that compete, the so-called non-dominated solutions. Several optimization strategies based on metaheuristic algorithms are available to address various types of optimization concerns relating to WSN deployment, localization, sink node placement, energy efficiency, and clustering. This review reports and discusses the literature research on single and multi-objective metaheuristics and their evaluation criteria, WSN architectures and definitions, and applications of metaheuristics in WSN deployment, localization, sink node placement, energy efficiency, and clustering. It also proposes definitions for these terms and reports on some ongoing difficulties linked to these topics. Furthermore, this review outlines the open issues, challenge paths, and future trends that can be applied to metaheuristic algorithms (single and multi-objective) and WSN difficulties, as well as the significant efforts that are necessary to improve WSN efficiency.

Animal Models of Chronic Migraine: From the Bench to Therapy.

Chronic migraine is a disabling progressive disorder without effective management approaches. Animal models have been developed and used in chronic migraine research. However, there are several problems with existing models. Therefore, we aimed to summarize and analyze existing animal models to facilitate translation from basic to clinical. The most commonly used models are the inflammatory soup induction model and the nitric oxide donor induction model. In addition, KATP openers have also been used in model induction. Based on the above models, some molecular targets have been identified, such as glutamate receptors. However, each model has its shortcomings and characteristics, and there are still some common problems that need to be solved, such as spontaneous headache, evaluation criteria after model establishment, and identification methods. In this review, we summarized and highlighted the advantages and limitations of the currently commonly used animal models of chronic migraine with a special focus on drug discovery and current therapeutic strategies, and discussed the directions that can be worked on in the future.