Natural bioactive compounds in dietary supplements and functional foods are valued for their role in health and disease prevention, leading to global demand. This has led to increased interest in cost-effective, scalable, and sustainable food and plant matrix chemical extraction technologies. This review contrasts classical and innovative bioactive extraction methods and demonstrates how eco-innovative approaches can be beneficial for food sustainability. Conventional techniques are widely used, but they frequently require substantial amount of solvent and energy as well as time, and they often harm the environment. On the other hand, new green technologies, such as ICD (instant controlled pressure drop) technology and PEF (pulsed electric field), SFE with CO2, UAE (power ultrasound assisted extractions) and MAE assist the efficiency of the extraction by reducing solvent consumption and waste/energy use. This review is original as it considers these strategies from technological and sustainability viewpoints, with focusing on extraction yield, process efficiency, eco-design and resource recovery. The present study emphasizes the necessity of combining technological performance with environmental and economic conditions to implement circular bioeconomy configurations in the nutraceutical and functional food sector. The biologically active compound extraction by the environmentally friendly techniques such as SFE, UAE, MAE, PEF and DIC improved the recovery of bioactive compounds with better quality in shorter duration and lesser consumption of resources than conventional methods. Nevertheless, expensive equipment cost, process optimization and absence of standardized evaluation criteria are the barriers for the development of this field. The integrated technology supported by online monitoring and multi-step operations under green solvent systems would be in high demand in the future. These sustainable global food systems are always the object of policies that consider regulatory frameworks, techno-economic study and life cycle assessment as key factors for industry to adopt them.

Maximizing the likelihood of a successful structural health monitoring application: A probabilistic approach to optimum sensor placement in bridges

Kidney stone disease (KSD) is heritable and genetic testing is becoming increasingly relevant to its management. However, it is unclear who should be offered genetic testing and what these investigations should entail. This review gives an overview of the existing evidence and future directions. In highly selected cohorts, genetic testing for monogenic disease can yield high diagnostic rates. These diagnoses can facilitate genetic counselling, familial testing, and targeted medical therapies.Our understanding of the role of rare intermediate effect size and common low effect size genetic variants is evolving. The clinical utility of polygenic risk scores and genetic sequencing in unselected cohorts remains uncertain. Genetic testing for monogenic KSD is advised in individuals with a strong family history and with recurrent stones. There is a need for large-scale studies, including in urology settings, to determine optimal criteria for patient selection in real world settings. Further research is required to define the role of genetic testing, including polygenic risk scores, in risk prediction, personalised management, and disease recurrence.

Osteoarthritis-related chronic joint pain substantially impairs function and quality of life. Aclinically relevant subgroup of patients remains insufficiently controlled by conservative care and is not yet eligible for, or declines, arthroplasty ("treatment gap"). First-line management includes weight reduction and physiotherapy, analgesics/nonsteroidal anti-inflammatory drugs (NSAIDs), intra-articular injections, and-when indicated-surgical options up to joint replacement. Transarterial periarticular embolization (TAPE) targets abnormal periarticular neovascularity/hypervascularity via superselective, blush-guided devascularization using temporary crystalline agents or resorbable/permanent microspheres. Accurate pain localization to the target joint and radiographic osteoarthritis (OA) grading are mandatory. Magnetic resonance imaging (MRI)/ultrasound may support selection by demonstrating inflammatory activity (synovitis/hypervascularity). Angiography identifies the pathological blush as the procedural endpoint. Across studies, technical success is near 100% with clinically meaningful improvements (typically ~30-40point pain reduction on a0-100 visual analog scale) and gains in Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC)/Knee Injury and Osteoarthritis Outcome Score (KOOS); however, sham-controlled randomized controlled trials (RCTs) show mixed results. Adverse events are uncommon and mainly mild/self-limited; major complications are rare. TAPE is apromising minimally invasive option, but its incremental benefit over placebo and optimal selection criteria require confirmation. Consider TAPE in specialized centers for refractory mild-to-moderate OA (strongest evidence for the knee; emerging data for hip/hand), using standardized protocols, particle sizes ≥ 100 µm when applicable, and strict nontarget prevention (e.g., skin cooling).

Feasibility and Safety of Same-Day Discharge Following Elective Mitral Transcatheter Edge-to-Edge Repair.

This article presents features of designing a two-axis inertially stabilized platform assigned for stabilization of observation units and devices, for example, cameras. The problem of stabilization of images is analysed, including electromechanical, optical, mechanical, and computer techniques. The appropriate structural diagrams are represented. The procedure of the synthesis for the inner and outer tracking loops of the control system is represented. The structure of control laws is proposed. The combined optimization criteria that ensure compromise between the tracking accuracy and resistance to disturbances on angular rate are represented. The structures of the synthesised regulators are described. The results of the synthesized system simulation are shown. The analysis of the simulation results is given. The system’s norms are calculated. The obtained results can be used in the area of stabilization of a wide class of instrumentation assigned for operation on moving objects.

The problem of optimizing the distribution of pixel density over the viewing area is considered, which ensures a minimum of redundancy of video images with a limited space for camera installations. A solution is presented to eliminate the redundancy of the informativeness of video signals, which leads to excessive resource costs for transmitting, storing, processing and displaying video signals. The proposed approach is based on an integral assessment of the continuous distribution of pixel density over the viewing area in comparison with the required value for solving a given observation task. The surveillance task is formalized — the definition of surveillance spaces and possible camera installation locations. A method for calculating the pixel density distribution over the viewing area is shown followed by optimizing the installation parameters according to the criteria of the minimum value of the redundancy coefficient when the required pixel density is reached or the maximum minimum pixel density with a given limitation on the redundancy coefficient. An integral coefficient and redundancy optimization criteria are proposed, taking into account the nature of the pixel density distribution and an optimization method that allows maximizing the minimum pixel density or minimizing the redundancy value of the video image. It is shown that the use of normalization in terms of both the minimum required pixel density and the length of the viewing area makes it possible to use the proposed criteria for most practical detection and identification tasks with different camera installation parameters. A practical example of using the method is given. The proposed criteria and method make it possible to increase the efficiency of the video surveillance system by reducing resource redundancy while maintaining the required information content. The results of the work are applicable to the tasks of video monitoring of a zone with one or more cameras as well as for solving various surveillance tasks in one zone. They can be used in the development of surveillance systems and computer-aided design programs for such systems.

ABSTRACT Clinical relevance Understanding the quality of care provided by existing refractive error services and aspects that influence quality enables educators and the workforce to develop interventions for delivering high-quality services. Background High-quality eye care services are required not only to address uncorrected refractive error but also maintain the needs of those wearing spectacles. This study aims to evaluate the quality of refractive error care in China by estimating the proportion and assessing factors associated with receiving optimal spectacles. Methods This cross-sectional study utilised trained unannounced standardised patients with various refractive error profiles to attend optical services in 2024 in Dali, China. Patients requested an eye examination, ordered and collected spectacles and a written prescription, and recorded testing provided. Baseline refractions were averaged from measurements conducted by three qualified refractionists. Spectacles and prescriptions were compared against the baseline and optimal criteria, and then against each other to assess appropriateness of spectacles made. Proportions for quality outcomes were calculated with robust standards errors to account for intra-service correlation. Univariable and multivariable logistic regression explored potential associations between spectacle quality and visit factors. Results Fourteen unannounced standardised patients visited 67 optical services completing 259 visits with 249 spectacles dispensed (181 single vision distance, 68 single vision near). Overall, 25.7% (95%CI:20.0–32.4%) and 38.8% (95%CI:33.5–44.5%) of spectacles and prescriptions, respectively, met the optimal criteria. Regression analyses indicated that males (OR:0.42, 95%CI:0.19–0.92, p = 0.03) were at reduced odds of receiving optimal spectacles, whereas those attending rural services were at significantly increased odds of receiving optimal spectacles (OR:2.82, 95%CI:1.40–5.69, p = 0.004). Conclusion The quality of refractive error care in Dali, China, shows a distinct need for improvement. The observed gender disparity in care requires further investigation, while understanding the systems and structures of rural services may provide insights to foster and improve urban services.

Interest in obesity has grown exponentially over the last years, with the availability of highly effective new pharmacological treatment options. The increasing use of pharmacological treatment options has stimulated debates on several fundamental issues, including (1) full recognition of obesity as a disease, and (2) optimization of the diagnostic criteria of obesity and the timing for offering different treatment options. We aim at critically discussing here the similarities, discrepancies, and potential misunderstandings suggested by the European Association for the Study of Obesity (EASO) and Lancet Diabetes Endocrinology Commission statements. In particular, two aspects are discussed: (1) the BMI limitations and the necessity to include visceral fat and, more in general, body composition assessment in the diagnosis of obesity; (2) the opportunity to consider obesity always as a clinically relevant chronic disease due to its biological, psychological, and social characteristics.

Thermoelectric (TE) generators directly convert heat into electricity, yet their performance is often limited by small temperature gradients. Width-modulated metamaterials with constrictions and expansions (constricted geometries) sustain larger temperature differences ΔT than constant-width counterparts due to reduced Transmissivity (Tr) - the geometric ratio of constriction to expansion cross-sections. A scaling behavior of transport and key TE performance metrics with Transmissivity is demonstrated from the nanoscale to the macroscale using analytical formalism and simulations across single- and multiple-constriction profiles. It is shown that ΔT, electrical and thermal resistances, efficiency, and output power are governed by a single scaling function g(Tr) - the conductance of a constricted geometry relative to a uniform-width counterpart-independent of carrier type, material, or operating conditions. Universal scaling formalism leads to Performance Design Maps and an analytical optimization criterion: maximum TE performance occurs at an optimal Transmissivity Tropt, where g(Tropt) = Bi, with Bi = hL/k denoting the Biot number and h, L, and k the convection coefficient, length, and thermal conductivity, respectively. Compared with the uniform geometry, the optimal constricted geometry produces a maximum output power reduced under fixed ΔT, by a factor of Bi/4, and enhanced under identical convective operating conditions by a factor of (1 + Bi)2/(4Bi). This work provides a theoretical framework for multiscale design and optimization of constricted geometries, thereby enabling systematic exploration of design strategies for next-generation TE modules based on advanced thermoelectric metamaterials analogous to nature's hierarchical structures for optimized functionality.

Complex Optimization Criterion and Its Implementation in Brachistochrone Problem on Inclined Plane

MLOps is a rapidly growing field in which optimizing resource allocation has become a key challenge. Despite the growing popularity of MLOps in production environments, there is a lack of articles in the literature that propose formal mathematical models for MLOps processes. This gap limits the development of analytical tools that support effective resource management in such systems. This study presents a mathematical model of an MLOps system and formulates a corresponding optimization problem. The model consists of three layers — processes, components, and servers — which serve as input parameters for the system, allowing for a flexible yet comprehensive representation of real-world MLOps architectures. Using this structure as a foundation, constraints and optimization criteria were established to enhance resource management. Finally, an objective function was proposed, whose minimization leads to improved system performance, reduced operational costs, and increased process reliability.

This paper introduces a Hybrid Tyrannosaurus Rex Optimization Algorithm (Hybrid TROA) combined with Variable Neighborhood Search (VNS), two variations of the Path Relinking strategy, and a randomized Nawaz-Enscore-Ham (NEH) heuristic to address the Permutation Flowshop Scheduling Problem (PFSP). The TROA is a novel bio-inspired meta-heuristic algorithm modeled on the hunting behavior of the prehistoric Tyrannosaurus Rex. Leveraging the potential of this newly developed and efficient algorithm, we propose a framework in which an initial population of solutions is generated using the randomized NEH heuristic. These solutions are then further optimized through VNS and Path Relinking, yielding highly satisfactory results for the PFSP. First, we consider two optimization criteria separately: the makespan and the total flow time. Next, we conduct a comparative study of the Hybrid TROA against other prominent meta-heuristics, along with a statistical analysis using non-parametric tests, to determine the best-performing method for each objective. According to our findings, the Hybrid TROA proves to be the most suitable method in this study for minimizing both targets. Finally, recognizing that contemporary industry demands both high productivity and energy efficiency, we propose an energy-efficient version of the classic PFSP, simultaneously considering two criteria for optimization: the makespan and total energy consumption. Our study introduces a novel objective function that achieves balanced optimization by integrating both criteria.

Machine learning-based clustering differentiates bilateral hepatocellular carcinoma characteristics and prognosis.

Dual-parameter ultrasonic guided wave packet characterization for ice thickness prediction and excitation signal optimization.

Many numerical methods of analysis of rigid shells, such as the displacement-based finite element method (FEM), finite difference energy method, method of separation of variables, kinematic method of the theory of limit equilibrium, and so on, were proposed and tested until 2000. Most problems of static and dynamic analysis of canonical shells were successfully solved at the same time. All these methods were used actively after the 2000, too. However, new problems began to appear before structural engineers, architects, and builders. These problems are associated with multi-layer shell walls, with the emergence of new composite construction materials, and therefore, with the solution of physically nonlinear problems. Geometricians presented several hundred new forms of middle surfaces of shells, and that is why the need to select optimal forms from several alternatives using criteria of optimality came into existence. The selection of necessary computing software from many of their types began to be a problem. New problems demanded new methods of approach for their solution. In this paper, a critical evaluation of proposed solutions on strength, stability, and vibration analysis of shells was conducted in connection with new problems that appeared after the year 2000. Rigid shells in the form of analytical surfaces, designed using the canon of parametric architecture, were taken as an example. Analytical middle surfaces of shells, which attracted the attention of architects after 2000, are pointed out, and suitable methods of analysis of these shells are noted for the first time. The review was compiled based on 112 fundamental scientific works published after 2000. Other scientific reviews devoted to the investigation of joint problems of geometry, application, and calculation of assembled rigid thin-walled shells with analytical middle surfaces were not found.

Predicting left ventricular hypertrophy from ECG: the never-ending search for the optimal diagnostic criteria.

During human motor skill training and physical rehabilitation, there exists an inherent trade-off between task difficulty and user performance. Characterizing this trade-off is crucial for evaluating user performance, designing assist-as needed (AAN) protocols, and assessing the efficacy of training protocols. In this study, we propose a novel human-in-the loop (HiL) Pareto optimization approach to characterize the trade off between the performance and the perceived challenge level of motor learning or rehabilitation tasks. We adapt Bayesian multi criteria optimization to systematically and efficiently perform HiL Pareto characterizations. Our HiL optimization employs a hybrid model measuring performance with a quantitative metric, while the perceived challenge level is captured with a qualitative metric derived from preference-based user feedback. We demonstrate the utility of the framework through three use cases in the context of a manual skill training task with haptic feedback. First, we demonstrate how the characterized trade-off can be used to design a sample AAN training protocol and evaluate the group level efficacy of the proposed AAN protocol relative to a baseline assistance protocol. Second, we demonstrate that individual-level comparisons of the trade-offs characterized before and after the training session enable fair evaluation of training progress under different assistance levels, providing insights even when users cannot perform the task without assistance. Third, we show that the characterized trade-offs also enable fair performance comparisons across users, since they capture each user's best possible performance at all feasible assistance levels.

In order to optimize engineering and surveying support for the building and repair of motorways and roads, it is proposed to use the latest surveying instruments and technologies, the effective use of which often depends on choosing the best available option based on an assessment of their technical and economic characteristics. The use of new instruments and technologies makes it possible to significantly expand the range of tasks, speed and accuracy of their implementation, and increase the availability of topographic and geodetic materials when developing project documentation. The article is devoted to the analysis of the current state of development of the electronic theodolite market, the study of their main characteristics and features of application. Among the characteristics considered are multiplicity of magnification, battery life, dust and moisture protection, angular measurement accuracy, liquid crystal display characteristics, weight, cost (price) of the device, and warranty period. The task of selecting the best theodolite (as a management decision) is formulated based on the use of T. Saaty’s Analytic Hierarchy Process. The issue of expert assessment of criteria is discussed. The main stages of solving the problem are presented. A reasonable approach to evaluating individual criteria in the case of conflicting information about them is justified. The practical use of the hierarchy analysis method is illustrated by the problem of evaluating the technical level of some models of electronic theodolites. It is proposed to take into account, as additional criteria, the specifics of working with other systems, the nature and causes of possible errors during measurements, contradictory and incomplete information regarding the measuring devices under consideration. Keywords: electronic theodolites, hierarchy analysis method, optimization criteria and alternatives, normalized vectors of local priorities of criteria and alternatives, assessment of the technical level of electronic theodolites.

The increasing volume of traffic flows in modern cities, the growing complexity of urban transport network structures, and higher efficiency requirements for logistics processes necessitate the development of new approaches to modeling and optimizing delivery tasks. Traditional methods of transport system analysis prove insufficiently effective under conditions of high data dimensionality, network dynamism, and numerous interconnected constraints. An approach to forming a logistics problem space for urban transport networks based on indexing, classification, and the use of data mining and deep learning methods is investigated. A formalization of the urban transport network is proposed as a multi-component dynamic system, including nodes, links, routes, and transport service entities. The indexing of logistics problems is performed considering cargo types, temporal characteristics, demand structure, and transport infrastructure status. The possibility of classifying and clustering problems based on conceptual graphs and evolutionary computation methods is demonstrated. A system of optimization criteria is formulated from the perspectives of both the customer and the carrier, aimed at reducing transport costs, delivery time, and urban network load. The results provide a foundation for using deep learning methods for intelligent traffic management across various datasets. The proposed approach allows considering the set of logistics problems in an urban transport network as an element of an intelligent decision support system. Dimensionality reduction is achieved through network zoning, vehicle specialization, and formalization of typical delivery scenarios. The findings can be used to build adaptive route optimization models and predict transport processes in complex urban systems.