We propose two Tseng methods with double inertial steps and self-adaptive step sizes to approximate the zero of the sum of two maximal monotone operators in real Hilbert spaces. These methods are based on the inertial technique and regularization ideas. Unlike several existing approaches, our proposed methods do not require the Lipschitz continuity assumptions for the associated single-valued operator. Additionally, we employ a more efficient self-adaptive step size technique that generates non-monotonic sequence of step sizes, eliminating the need for time-consuming line search procedures. Under relaxed assumptions, we establish the strong convergence of the proposed algorithms and apply them to solve other optimization problems. Finally, numerical experiments demonstrate the comparative advantages of our methods over existing methods in the literature.

We consider the free-form optimization of eigenvalues in electromagnetic systems by means of shape variations with respect to small deformations. The objective is to optimize a particular eigenvalue to a target value. We utilize the mixed variational formulation of the Maxwell eigenvalue problem as proposed by Kikuchi (1987) in function spaces of H ( curl ; Ω ) and H 1 ( Ω ) . To handle this formulation, suitable transformations of these spaces are utilized, e.g. of Piola-type for the space of H ( curl ; Ω ) . This allows for a formulation of the problem on a fixed reference domain together with a domain mapping. Local uniqueness of the solution is obtained by a normalization of the eigenfunctions. This allows us to derive adjoint formulas for derivatives of the eigenvalues with respect to domain variations. For the solution of the resulting optimization problem, we develop a particular damped inverse BFGS method that allows for an easy line search procedure while retaining positive definiteness of the inverse Hessian approximation. The problem is discretized by mixed finite elements and a numerical example shows the efficiency of the proposed approach.

Introduction . In Part I of this review, we collate and analyze established approaches to cancer pain management, encompassing routine, emerging, and promising methods. Emphasis is placed on transparent search procedures, comparability of evidence, and the practical applicability of conclusions for both bedside clinicians and the development of methodological guidance and recommendations. The objective was to critically synthesize the evidence on the effectiveness and safety of pharmacological analgesia in adult oncology patients and to delineate key areas of uncertainty to guide further research and implementation. Materials and methods . We conducted a narrative review with elements of a structured search (October 2025; updated on 23 Oct 2025). Sources included PubMed/MEDLINE, Embase, the Cochrane Library, Scopus, Web of Science, and eLIBRARY.ru; clinical trial registries (ClinicalTrials. gov and WHO ICTRP); and documents from relevant professional societies. The primary time window was 2000–2025 (with no strict limits for foundational studies). 63 sources were included in the final analysis for Part I. Sections . The review addresses pharmacological strategies for cancer-related pain. The lowest therapeutic responsiveness, despite the need for rapid symptom control, is typically observed in nociplastic pain (central sensitization). High resistance is also characteristic of mixed pain syndromes in which neuropathic pain coexists with a predominant nociceptive component. Refractory central neuropathic pain frequently necessitates the use of ketamine and cannabinoids; however, the evidence base is constrained by small randomized controlled trials and a considerable burden of adverse effects. Conclusions . Standard analgesic approaches provide acceptable effectiveness with well-characterized adverse reactions and contraindications. Nevertheless, a substantial cohort of patients continues to require more contemporary, safer, and pathophysiology-informed strategies for cancer pain control.

<p>Bicultural individuals are increasingly recognized as valuable resources in international organizations, yet their specific role and impact within international project contexts remain underexplored. This study presents a theory-driven literature review on bicultural resourcefulness in international projects, informed by systematic search procedures, aiming to consolidate current knowledge, assess empirical findings, and identify research needs. A structured keyword-based search following Webster and Watson was conducted across major academic databases, resulting in five empirical studies. The review revealed a limited but growing body of literature highlighting the competencies of bicultural professionals, including bicultural competence, boundary spanning, and cultural mediation. Key research gaps were identified, particularly regarding differences between first- and second-generation biculturals, their impact on project-related outcomes, and the organizational conditions that enable the effective use of their skillsets. The findings underscore the need for a more nuanced understanding of biculturalism beyond broad, generic identity framings. This review contributes to the emerging discourse in international management by combining a Multicultural Input-Process-Output (MIPO)-oriented integrative framework with a focused research agenda for further empirical investigation on bicultural professionals in project-based contexts.</p>

Introduction: family is the factor that influences the growth of children in a family. Stunting is a condition that must be of special concern because it can resistor the physical development and mental of children. The family's role and function in increasing family resilience is very needed in the compliance nutritional status of children under five. Objectives: The aim of this study was to see the relationship between family resilience and the incidence of stunting in children. Methods: This study used a literature review method, and the literature search procedure was conducted using databases such as PubMed and Google Scholar. Keywords included "family resilience," "family role," "family function," "stunting," "malnutrition," and "food security." Inclusion criteria covered peer- reviewed quantitative studies (cross-sectional, case-control, cohort) published between 2016–2021 in English or Indonesian, with full-text availability. Exclusion criteria included non-full-text articles, narrative reviews, case reports, and unrelated topics. Results: Results 8 journals sorted by research topic. 2 journals discuss the role of family and family support on nutritional status related to stunting and 6 journals discuss food security related to stunting. The findings indicate that multiple aspects of family resilience, including family roles, food security, parenting, and dietary diversity, play a crucial role in preventing stunting. Conclusions: From this study it was concluded that there was a relationship between family resilience with stunting in children.

Leprosy remains a persistent public health issue in Brazil, particularly in the Semiarid region, where its persistence reflects not only biological transmission but also structural inequality. Despite the availability of free multidrug therapy, the disease continues to affect socially vulnerable populations, revealing a paradox between therapeutic capacity and epidemiological persistence. This study aims to analyze leprosy in the Brazilian Semiarid as a biopolitically mediated phenomenon, shaped by territorial inequality, stigma, and limited access to care. An integrative literature review was conducted, including studies published between 2019 and 2026, selected through systematic search, screening, and critical appraisal procedures. The synthesis incorporated epidemiological, social, and health system perspectives to construct a comprehensive analytical framework. The results indicate that leprosy is spatially concentrated in vulnerable territories, where rural dispersion and limited health infrastructure hinder early diagnosis. High rates of physical disability at diagnosis reveal systemic delays, while failures in primary health care and contact surveillance sustain transmission. Stigma and institutional silence further contribute to delayed care and social exclusion. The discussion highlights that leprosy persistence is embedded in a nexus of vulnerability, where territory, access, and social conditions interact to produce unequal outcomes. Clinical cure does not eliminate the social consequences of the disease, reinforcing cycles of exclusion. It is concluded that leprosy in the Semiarid must be addressed as a form of social injustice. Effective control requires not only treatment, but also territorial equity, active surveillance, and policies aimed at social reintegration.

Sarcopenia and malnutrition have detrimental health related outcomes not limited to falls, weakness, fractures, increased hospital length of stay, increased risk of infections, morbidity and mortality. Ultrasound is an establishing imaging modality that can be utilized at point-of care to measure muscle mass and quality. It is cheaper, less invasive, and more accessible than other gold-standard measurements of muscle mass. It is proposed that dietitians can utilize this measurement in clinical practice to support both diagnosis and monitoring of malnutrition and sarcopenia, however current evidence has not been synthesized. The search was completed in May 2024. MEDLINE, EMBASE, PubMed and Cochrane databases were searched. Search terms and search procedures were transposed across different databases based on known Booleen operators. Due to paucity of evidence in the area, a broad search strategy was employed. Simply the combination of synonyms of ultrasound and dietitian within any field was used to ensure any kind of ultrasound measured by a dietitian was captured. The initial search identified 946 titles for review from which 228 duplicates were removed, leaving 718 for screening. After screening, 55 papers remained for full-text review. Ten papers were included for appraisal. All peer-reviewed papers were observational, 441 participants in total were included (both healthy participants and patient cohorts). Study quality was low, with study design, documentation of training, timing of measurement and blinding poorly defined. The reference standard (if any) was inconsistent. All studies were basic research, none were translated into clinical practice. Quad muscle thickness was the most common measurement. Reliability of dietitians was reported in most, with intra-rater ICC ranges from 0.63 to 0.95 between dietitians and 'experts' (intensivists, trained clinicians or sonographers). Training undertaken was reported in half the papers reviewed but details were limited. Emerging evidence suggests dietitians have potential to develop skills in measuring muscles with ultrasound. Overall, there remains a paucity of publications in the area, particularly when considering dietitian training and reliability in various ultrasound measurements. There should be progress in Further studies with regard to verifying necessary training for dietitians to ensure accurate readings as an advanced scope of practice for dietitians.

This paper presents two automated correspondence-search algorithms for stereo laser triangulation in multimedia (refractive) environments, enforcing coplanarity through forward ray tracing without iterative back-projection. By shifting computations from image to object space, the methods directly minimize either the skew distance between refracted rays or the distance between their intersections with a laser plane, yielding strict refractive geometry within a single optimization loop. The methods are validated on an automated wood conservation monitoring system, where a stereo camera system with a line laser operates over a water-filled conservation tank. This application provides the environment for both algorithmic efficiency and accuracy requirements, demanding sub-millimeter precision over extended monitoring periods. Both algorithms reconstruct timber structures with high quality with the added planar constraint substantially reducing noise and edge outliers while slightly lowering point density. Water-surface estimation achieves plane-fit RMS of about 0.2 mm with a similar ground sample distance (GSD) and agrees with independent ruler measurements within 2 mm, enabling water-level monitoring over 14 epochs and cross-validation with calibration-derived plane parameters. Reference measurements on a 230 × 230 mm plane and three 50 mm spheres yield sub-millimeter residuals, with the plane constraint providing higher precision and fewer outliers. Finally, the computational efficiency is evaluated, showing favorable results for one of the algorithms compared to a standard procedure for correspondence search. Results demonstrate efficient, accurate, and transferable stereo laser triangulation through water and straightforward extensibility to multi-camera systems or non-perpendicular laser–water incidence angles. • Two novel correspondence search approaches for refractive stereo laser triangulation. • Application of the approaches on an automated wood conservation monitoring system. • Evaluation of the proposed approach against reference shapes. • Measurement of water planes with a stereo laser triangulation system. • Validation of water plane parameters with independent measurements.

To realize three-dimensional (3-D) underdetermined parameter estimation for near-field (NF) sources by L-shaped nested arrays, two NF localization methods based on the exact spherical wavefront model are proposed, including the cumulant-based method and the covariance-based method, which utilizes the temporal-spatial domain cumulants and correlations of NF sources, respectively. The cumulant algorithm constructs virtual received data through delayed fourth-order cumulant calculations of the original received data, while the covariance algorithm involves delayed autocovariance and delayed cross-covariance calculations. Subsequently, spatial-spectrum based subspace method is applied to both cumulant-based and covariance-based 3-D NF localization, where the former requires a 3-D spectral search procedure and the latter involves a one-dimensional and a two-dimensional spatial spectrum estimator to obtain the 3-D parameters. Furthermore, the computational complexity, the maximum number of identifiable NF sources and performance analysis of two proposed algorithms are provided. Simulation results demonstrate that the two proposed algorithms can achieve underdetermined 3-D parameter estimation for NF sources without any matching processes procedure. While the covariance algorithm has lower computational complexity, the cumulant algorithm performs better in parameter estimation.

Diabetes Mellitus (DM) is a major global health concern associated with serious complications, high healthcare costs, and reduced quality of life. Musculoskeletal pain is a common complication and contributes to limitations in daily activities and increased healthcare utilization. Pain is a multidimensional phenomenon typically classified as nociceptive, neuropathic, or nociplastic; however, evidence regarding pain mechanisms and phenotypes in people with DM remains limited. This review aimed to synthesize and critically review the literature on musculoskeletal pain in individuals with DM, focusing on pain mechanisms and phenotypes according to the International Association for the Study of Pain (IASP) classification. A narrative review with systematic search procedures examined the applicability of the seven clinical criteria proposed by the IASP for nociplastic pain to musculoskeletal pain phenotyping. Searches were conducted in PubMed and Web of Science from inception to December 2025. Evidence was analyzed according to the IASP nociplastic pain criteria to explore alignment with pain phenotyping approaches. Overall, the literature indicates that neuropathic pain mechanisms are relatively well documented and consistently reported in individuals with diabetes, while nociceptive musculoskeletal drivers are also described but with more limited and heterogeneous evidence. In contrast, evidence addressing hypersensitivity phenomena and other domains related to nociplastic pain remains scarce and is still emerging. This pattern suggests that current research on pain in people with DM remains focused on neuropathic mechanisms. Future research adopting standardized pain phenotyping frameworks is needed to support more precise and individualized pain management strategies in this population.

<b>Abstract</b><br /> <b>Background:</b> Postpartum depression (PPD is a prevalent and disabling condition with significant consequences for maternal and infant well-being. Women who conceive through assisted reproductive technologies (ART) may experience distinct psychological vulnerabilities in the postpartum period due to prolonged infertility, treatment-related stress, and prior pregnancy loss. Digital health interventions (DHIs) have emerged as promising tools for addressing perinatal mental health needs; however, their relevance and effectiveness for women following assisted reproduction remain insufficiently synthesized.<br /> <b>Objective:</b> This narrative review aims to critically examine the current evidence on digital health interventions for postpartum depression in the context of assisted reproduction, with a focus on conceptual relevance, methodological strengths and limitations, and implications for clinical practice and future research.<br /> <b>Methods:</b> A structured narrative synthesis was conducted using transparent search procedures across major bibliographic databases, including PubMed, PsycINFO, Scopus, and Web of Science. Peer-reviewed empirical studies, reviews, and key conceptual papers addressing digital mental health interventions for postpartum depression were included, with particular attention to the representation and reporting of ART-conceived populations.<br /> <b>Results:</b> Existing digital interventions—such as mobile health applications, web-based psychotherapy, telepsychology, and emerging AI-supported tools—demonstrate feasibility and acceptability in general postpartum populations. However, ART-specific evidence remains limited, with most studies embedding women who conceive through assisted reproduction within broader perinatal samples and rarely tailoring intervention content to infertility-related psychological experiences. Methodological heterogeneity, small sample sizes, short follow-up periods, and limited subgroup analyses constrain the strength of population-specific conclusions.<br /> <b>Conclusions:</b> Digital health interventions hold considerable promise for addressing postpartum depression following assisted reproduction, but current evidence is largely indirect. Conceptually, DHIs align well with the psychological needs of ART populations; empirically, however, rigorous validation is lacking. Future research should prioritize ART-specific trials, longitudinal designs, participatory co-design approaches, and integration with clinical care pathways to develop effective, personalized, and equitable digital mental health solutions for this high-risk population.

Bullying remains a serious school-based problem because it harms victims’ emotional well-being, academic engagement, and social functioning. Although cognitive behavioral therapy (CBT) has been widely recognized as a promising intervention for bullying victims, recent evidence synthesizing its effectiveness across studies remains limited. Therefore, this study aimed to analyze the effectiveness of CBT in helping victims of bullying through a systematic literature review. This study employed a Systematic Literature Review design. The review instrument consisted of keyword-based search procedures and inclusion–exclusion criteria used to identify relevant studies. Data were collected from Google Search and Google Scholar using the keywords “cognitive behavioral therapy” and “bullying victims,” with the review limited to full-text journal articles published between 2021 and 2025. From 207 identified records, five eligible articles were selected for in-depth review. The data were analyzed through screening, evaluation, and comparison of similarities and differences across the selected studies. The findings show that CBT is effective in reducing anxiety, depression, trauma-related reactions, and low self-esteem among bullying victims, while improving self-confidence, emotional control, social skills, and positive thinking. CBT was found to be applicable in individual and group formats, including techniques such as thought stopping. These findings imply that CBT is not only useful as a therapeutic intervention but also has potential as a preventive school-based approach for building safer and more supportive learning environments.

This paper addresses the Distance-Constrained Inventory Routing Problem (DCIRP), a complex problem that combines inventory management and vehicle routing in a logistics context. The problem arises in the context of a specialty gas delivery company that maintains a specialty gas holding facility at each customer’s site and uses several trucks to deliver specialty gas, with the additional constraint that drivers are limited to the number of kilometers they can drive each day. A Mixed Integer Linear Programming (MILP) formulation is proposed to model the DCIRP. The DCIRP is a variant of the Inventory Routing Problem (IRP), and an NP-hard combinatorial optimization problem. The main objective of this research is to improve the efficiency and effectiveness of DCIRP resolution, while accounting for vehicle capacity constraints, customer inventory levels, and delivery route distance constraints. By optimizing routes and inventory management, the company’s operations become more sustainable. To solve the problem, three solution approaches are proposed. The first is an exact method based on the MILP formulation. The second is a matheuristic that uses an inventory-first, route-second (IFRS) approach, including a minimum route cost approximation and a local search procedure. The results show that the proposed matheuristic produces high-quality solutions with a reasonable computational effort.

Introduction: Avalanches pose significant dangers to winter recreationists, and avalanche airbags have become a prominent safety device. Airbags could increase users’ confidence, leading to risk compensatory behaviors, and paradoxically, putting users at a greater hazard despite their proven mortality reduction. This study assesses expert opinions and behaviors toward avalanche airbags in the Alpine region. The objective is to investigate the perception of skiing instructors, mountain guides, and rescuers of alpine countries toward airbag effectiveness, efficacy in preventing mortality, and their role during search and rescue operations. Methods: A cross-sectional survey of skiing instructors, mountain guides, and rescuers (i.e., experts) working in alpine countries (France, Italy, Switzerland, Germany, Liechtenstein, Austria) was conducted. Participants were selected via snowball sampling. Topics included training and experience of experts, risk propensity of clients and avalanche casualties, perception toward search and rescue procedures, and perceived efficacy of avalanche airbags. Results: Expected outcomes will cover expert opinions on the advantages and limitations of airbags, the influence of airbags on users’ risk-taking and risk compensation, airbags pros and cons in search and rescue scenarios, and general recommendations. Conclusion: This study will contribute to understanding how avalanche airbags are viewed by experts in snow-related mountain casualties. Eventually, this will add knowledge to better shape educational programs for winter recreationists, best practices, and policies for avalanche airbag use in high-risk environments.

Targeted mass spectrometry enables precise peptide quantification by identifying high-quality chromatographic peaks for area integration. Automated peak identification remains challenging, particularly for low-abundance targets, because of interference and noise. Existing approaches typically rely on two supervised learning models, one for selecting peak regions and the other for performing downstream quality control in a separate postprocessing step. However, deferring quality assessment to a separate stage may limit the ability to refine peak boundaries in pursuit of improved quality, as the initial selection is performed without explicit awareness of quality-related criteria. In this study, we present MsTargetPeaker, a quality-aware search procedure for identifying peak regions in targeted proteomics data. The method employs a reinforcement learning agent to guide Monte Carlo tree search to efficiently explore chromatograms and localize target peaks while minimizing interference. Peak quality is dynamically assessed during the search via a custom-designed reward function, which prioritizes regions with desirable peak characteristics and enables accurate and robust boundary determination. The reward function further incorporates cross-sample consensus profiles of candidate boundaries to improve the identification of low-quality or ambiguous signals. These innovations support fine-grained peak identification, enhancing both peak quality and quantification precision. In addition, the transparent reward calculation allows MsTargetPeaker to generate interpretable diagnostic quality reports, providing comprehensive metrics across transitions, peak groups, and sample replicates. This facilitates efficient detection of problematic cases for manual curation. Collectively, MsTargetPeaker offers a practical advancement toward robust and automated peak identification in targeted proteomics.

As with many metaheuristics, the Greedy Randomized Adaptive Search Procedure (GRASP) lacks an effective stopping rule in its standard form and relies on ineffective criteria. This often leads to a waste of computational resources. To address this limitation, rules based on Bayesian statistics, cumulative distribution function, extreme value theory, and machine learning algorithms have been proposed in the literature. However, these methods also present shortcomings, as they may fail on certain instance types or be computationally expensive. In response, this work seeks to better understand these shortcomings and overcome some of them through an ensemble-based machine learning approach. To demonstrate its capabilities, the new rule was evaluated on a custom dataset composed of execution data from three optimization problems and compared to a group of alternatives. The evaluation used cross-validation and an additional test designed to assess generalization across problems, in which the model was trained on two optimization problems and tested on a third. Two custom metrics focused on evaluating how well the rules stop the metaheuristic at predetermined points in the search are also introduced. The results indicate that the proposed stopping rule is competitive on harder instances.

The Dial-a-Ride Problem (DARP) focuses on designing vehicle routes and schedules to transport passengers between specified origins and destinations, with particular relevance to accessible transit systems. This study introduces a novel variant, termed the Heterogeneous DARP with Energy Replenishment Options (H-DARP-ERO), which simultaneously considers heterogeneous user demands with varying resource requirements, a heterogeneous electric vehicle fleet, and two energy replenishment options, namely recharging and battery swapping. A mixed-integer linear programming model is developed to jointly optimize passenger-vehicle assignment, routing, and energy replenishment decisions. To solve the problem, a Population-Guided Hybrid Genetic Algorithm (PG-HGA) is proposed, integrating customized encoding and decoding schemes, local search procedures, and adaptive population regulation mechanism to effectively balance exploration and exploitation. Experiments and a real-world case study demonstrate the efficiency and superiority of the proposed approach, and reveal how replenishment strategies and key parameters affect system performance, providing managerial insights for planning electric heterogeneous Dial-a-Ride systems.

Background: Literature reviews are essential in academic research because they establish theoretical foundations and identify research gaps. However, inconsistencies in methodological rigour and reporting practices often weaken their credibility and impact, underscoring the need for clearer standards to guide the conduct of high-quality reviews. Objectives: This study aimed to identify, analyse, and synthesise key methodological, theoretical, and practical principles that underpin rigorous and credible literature reviews in academic research. Methods: The study employed a qualitative integrative review design. Data were collected through a systematic examination of international methodological guidelines, peer-reviewed empirical studies, and relevant grey literature. The selected sources were analysed using thematic synthesis techniques to identify recurring standards, frameworks, and best practices in literature review methodology. Results: The findings indicated that high-quality literature reviews are characterized by clear alignment between review objectives and design, theoretically grounded analysis, researcher reflexivity, transparent search and selection procedures, and systematic coding and synthesis processes. The study also highlighted the importance of peer review mechanisms, adherence to ethical research standards, and the inclusion of diverse and credible sources in strengthening validity, reliability, and scholarly impact. Conclusion: Conducting a rigorous literature review requires structured methodological frameworks, procedural transparency, and ongoing critical reflection throughout the research process. A systematic and reflective approach enhances coherence, credibility, and academic contribution. Contribution: This study consolidates dispersed methodological insights into a practical and structured framework that offers actionable guidance for postgraduate students, early-career researchers, and experienced scholars seeking to produce coherent, trustworthy, and impactful literature reviews.

This paper investigates the problem of switching wagons in flat rail yards to form both an outbound train and additional blocks. We present a new encoding scheme for the studied problem in both stub-yards and through-yards, and formulate the studied problem as mixed integer linear models. Then, we reformulate our problem into a shortest-path problem in a huge hierarchical directed graph. To solve practical-size problem instances, we customise a greedy randomised adaptive search procedure, wherein a greedy randomised algorithm computes an initial solution quickly, which is further improved by a large neighbourhood search heuristic. Finally, we demonstrate the effectiveness and efficiency of our methods by solving a set of instances. Computational results reveal that our method is capable of computing good solutions for practical-size instances within a reasonable computation time. We also provide decision suggestions to support decision-making of rail staff by comprehensively analysing the features of our solutions.

Abstract This work introduces the Single Source Capacitated Partial Set Covering Location Problem (SSCPSCLP). Given a set of potential capacitated facilities and a set of customers with their demands, this problem consists of determining the facilities to be opened and the customers to be served to minimize the total cost of opening facilities, ensuring that at least a minimum amount of the total demand is served, only covered customers can be served, the capacity of the facilities is not exceeded, and each customer can be served by at most one facility. This work introduces a mathematical model for the problem and, since it is NP-hard, develops an algorithm based on the Tabu Search (TS) metaheuristic to handle large-scale instances. The TS algorithm explores the problem’s solution space through two neighborhoods, one of which is incorporated into a local search procedure that is periodically applied. The initial solution is generated either by a constructive greedy heuristic or by solving the linear relaxation of the SSCPSCLP. Four TS variants were proposed, differing in the method for generating the initial solution and in the use of local search. The results of computational experiments on instances from the literature show that the TS algorithm finds high-quality solutions in a shorter runtime than a mathematical programming-based solver and that the version using initial solutions from the linear relaxation of the problem and local search performs best.