Search Results (203)

Background/Objectives: Internet addiction (IA) and related behaviors, such as Internet Gaming Disorder (IGD) and social media addiction (SMA), have gained increasing research attention. Studies show gender differences, with males more likely to develop gaming-related addictions and females more prone to social media and phubbing behaviors. This study aimed to explore gender differences in Internet addiction and related behaviors in a Spanish sample, with the goal of identifying predictors and gender-specific patterns of IA. Methods: We conducted a cross-sectional study with 585 participants (265 male, 320 female) aged 18 to 35 years (M = 22.11, SD = 3.08). Data were collected using standardized questionnaires to assess IA, IGD, SMA, phubbing, Fear of Missing Out (FoMO), emotional dysregulation, personality traits, and prosociality. Correlation and regression analyses were used to identify gender-specific predictors of IA. Results: Males exhibited significantly higher scores for IA and IGD, while females showed higher scores for SMA and the “phone obsession” dimension of phubbing. No significant gender differences were found in the “communication disturbance” dimension of phubbing or in FoMO. Correlation analyses revealed significant associations between IA and psychological as well as technological variables. Gender-specific predictors of IA included social media engagement and emotional regulation for females, while gaming behaviors and communication patterns were more relevant for males. Conclusions: These findings highlight gender differences in IA, suggesting that tailored interventions should address unique online behaviors and emotional regulation challenges in males and females. Future research should refine gender-specific patterns to develop more effective, targeted prevention and treatment strategies. Full article

Senescence-resembling alterations on the lymphocytes of patients undergoing dialysis have been widely described. However, the pathophysiology behind these phenomena has not been clarified. In this study, we examined the impact of dialysis prescription on T and B lymphocytes, in patients undergoing dialysis.: T and B cell subsets were determined with flow cytometry in 36 patients undergoing hemodialysis and 26 patients undergoing hemodiafiltration, according to the expression of CD45RA, CCR7, CD31, CD28, CD57, and PD1 for T cells, and IgD and CD27 for B cells. The immune phenotype was associated with dialysis modality, hemofiltration volume, and mortality. Compared with hemodialysis, patients undergoing hemodiafiltration had a significantly decreased percentage of CD4+CD28-CD57- T cells [3.8 (2.4–5.3) vs. 2.1 (1.3–3.3)%, respectively, p = 0.002] and exhausted CD4+ T cells [14.1 (8.9–19.4) vs. 8.5 (6.8–11.7)%, respectively, p = 0.005]. Additionally, the hemofiltration volume was negatively correlated with CD8+ EMRA T cells (r = −0.46, p = 0.03). Finally, the increased exhausted CD4+ T cell percentage was associated with increased all-cause mortality in patients undergoing dialysis, independent of age. Hemodiafiltration, especially with high hemofiltration volume, may have beneficial effects on senescence-related immune phenotypes. Immune phenotypes may also be a predicting factor for mortality in patients undergoing dialysis. Full article

To facilitate the intelligent classification of unmanned highway toll stations, selecting effective and useful features is pivotal. This process involves achieving a tradeoff between the number of features and the classification accuracy while also reducing the acquisition costs of features. To address these challenges, a multimodal multi-objective feature selection (MMOFS) method is proposed in the current study. In the MMOFS, we utilize a multimodal multi-objective evolutionary algorithm to choose features for the unmanned highway toll station classification model and use the random forest method for classification. The primary contribution of the current study is to propose a feature selection method specifically designed for the classification model of unmanned highway toll stations. Experimental results using actual data from highway toll stations demonstrate that the proposed MMOFS outperforms the other two competitors in terms of PSP, HV, and IGD. Furthermore, the proposed algorithm can provide decision-makers with multiple equivalent feature selection schemes. This approach achieves a harmonious balance between the model complexity and the classification accuracy based on actual scenarios, thereby providing guidance for the construction of unmanned highway toll stations. Full article

The key problem to solving constrained multi-objective optimization problems (CMOPs) is how to achieve a balance between objectives and constraints. Unfortunately, most existing methods for CMOPs still cannot achieve the above balance. To this end, this paper proposes an adaptive constraint relaxation-based evolutionary algorithm (ACREA) for CMOPs. ACREA adaptively relaxes the constraints according to the iteration information of population, whose purpose is to induce infeasible solutions to transform into feasible ones and thus improve the ability to explore the unknown regions. Completely ignoring constraints can cause the population to waste significant resources searching for infeasible solutions, while excessively satisfying constraints can trap the population in local optima. Therefore, balancing constraints and objectives is a crucial approach to improving algorithm performance. By appropriately relaxing the constraints, it induces infeasible solutions to be transformed into feasible ones, thus obtaining more information from infeasible solutions. At the same time, it also establishes an archive for the storage and update of solutions. In the archive update process, a diversity-based ranking is proposed to improve the convergence speed of the algorithm. In the selection process of the mating pool, common density selection metrics are incorporated to enable the algorithm to obtain higher-quality solutions. The experimental results show that the proposed ACREA algorithm not only achieved the best Inverse Generation Distance (IGD) value in 54.6% of the 44 benchmark test problems and the best Hyper Volume (HV) value in 50% of them, but also obtained the best results in seven out of nine real-world problems. Clearly, CP-TSEA outperforms its competitors. Full article

This paper introduces the Improved Evolution Strategy Reinforcement Learning (I-ES) algorithm. The I-ES algorithm is designed to minimize the makespan and total energy consumption (TEC) in a multi-objective dynamic scheduling problem within a hybrid flow shop. It addresses key challenges such as flexible preventive maintenance for machines, random job arrivals, uncertain processing times, and the setup time. An experimental comparison of the I-ES-based approach with Evolution Strategy Reinforcement Learning (ES) algorithms and scheduling rules, which are a combination of job selection rules and machine selection rules, has been carried out by designing problem examples. The Generational Distance (GD) and Inverted Generational Distance (IGD) metrics of the I-ES algorithm are obtained by averaging all the instances as 389.14 and 1476.25, respectively, which are smaller than the other compared algorithms, so the results show that the I-ES algorithm can obtain solutions with superior convergence compared to that of the ES algorithm and dispatching rules. Full article

This paper addresses the multi-operator human–robot collaborative disassembly line balancing problem aimed at minimizing the number of workstations, workstation idle time, and disassembly costs, considering the diversity of end-of-life products and the characteristics of their components. A hybrid artificial fish swarm algorithm (HAFSA) is designed in accordance with the problem characteristics and applied to a disassembly case of a hybrid refrigerator. Comparative experiments with the non-dominated sorting genetic algorithm II (NSGA-II) and teaching–learning-based optimization (TLBO) algorithms demonstrate the superiority of the proposed algorithm. Finally, the performance of the three algorithms is evaluated based on non-dominated rate (NR), generational distance (GD), and inverted generational distance (IGD) metrics. Full article

While online gaming has become a choice for relaxation and entertainment in today’s digital age, Internet Gaming Disorder (IGD) has also become a widely concerning mental disorder. Nature connectedness has been found to effectively reduce addiction-related risks and alleviate symptoms of addictive behaviors. It is a relatively lacking but very important factor influencing psychological recovery and regulation in the digital society. This study aims to explore the relationship between nature connectedness and IGD, and the mediating roles of intolerance of uncertainty and desire thinking. A total of 571 young people voluntarily participated in the questionnaire survey. The results showed that: (1) nature connectedness was negatively correlated with IGD; (2) intolerance of uncertainty plays a mediating role between nature connectedness and IGD; and (3) intolerance of uncertainty and desire thinking plays a chain mediating role between nature connectedness and IGD. Analysis of the research results indicates that nature connectedness can effectively reduce IGD and reveal its mechanism of action. The findings provide new insights for the study and intervention of IGD in the digital age. Full article

This research aims to explore the effect of Internet Gaming Disorder (IGD) and online gaming behaviors related to IGD. The explored behaviors were based on games with microtransactions. Using a revised portrait value questionnaire (PVQ-RR), 186 respondents from 18 to 52 years old were asked about gaming behaviors. Online gaming behaviors such as the duration of online gaming and the payment for online games had a reciprocal relationship with IGD. Stimulation, achievement, hedonism, power through dominance, and personal security were correlated with playing paid online games. It is necessary to consider the fact that the values of the games are related to online gaming behaviors. Positive online gaming behaviors need to be developed. Full article

Since game mechanics and their visual aspects have become more and more addictive, there is concern about the growing prevalence of Internet gaming disorder (IGD). In the current narrative review, we searched PubMed and Google Scholar databases for the keywords “igd biomarker gaming” and terms related to biomarker modalities. The biomarkers we found are grouped into several categories based on a measurement method and are discussed in the light of theoretical addiction models (tripartite neurocognitive model, I-PACE). Both theories point to gaming-related problems with salience and inhibition. The first dysfunction makes an individual more susceptible to game stimuli (raised reward seeking), and the second negatively impacts resistance to these stimuli (decreased cognitive control). The IGD patients’ hypersensitivity to reward manifests mostly in ventral striatum (VS) measurements. However, there is also empirical support for a ventral-to-dorsal striatal shift and transition from goal-directed to habitual behaviors. The deficits in executive control are demonstrated in parameters related to the prefrontal cortex (PFC), especially the dorsolateral prefrontal cortex (DLPFC). In general, the connection of PFC with reward under cortex nuclei seems to be dysregulated. Other biomarkers include reduced P3 amplitudes, high-frequency heart rate variability (HRV), and the number of eye blinks and saccadic eye movements during the non-resting state. A few studies propose a diagnostic (multimodal) model of IGD. The current review also comments on inconsistencies in findings in the nucleus accumbens (NAcc), anterior cingulate cortex (ACC), and precuneus and makes suggestions for future IGD studies. Full article

This study addresses the challenge of bearing-only target localization with sensor bias contamination. To enhance the system’s observability, inspired by plant phototropism, we propose a control barrier function (CBF)-based method for UAV motion planning. The rank criterion provides only qualitative observability results. We employ the condition number for a quantitative analysis, identifying key influencing factors. After that, a multi-objective, nonlinear optimization problem for UAV trajectory planning is formulated and solved using the proposed Nonlinear Constrained Multi-Objective Gray Wolf Optimization Algorithm (NCMOGWOA). Simulations validate our approach, showing a threefold reduction in the condition number, significantly enhancing observability. The algorithm outperforms others in terms of localization accuracy and convergence, achieving the lowest Generational Distance (GD) (7.3442) and Inverted Generational Distance (IGD) (8.4577) metrics. Additionally, we explore the effects of the CBF attenuation rates and initial flight path angles. Full article

The structural design of prestressed arched trusses presents a complex challenge due to the need to balance multiple conflicting objectives such as structural performance, weight, and constructability. This complexity is further compounded by the interdependent nature of the structural elements, which necessitates a comprehensive optimization approach. Addressing this challenge is crucial for advancing construction practices and improving the efficiency and safety of structural designs. The integration of advanced optimization algorithms and decision-making techniques offers a promising avenue for enhancing the design process of prestressed arched trusses. This study proposes the use of three advanced multi-objective optimization algorithms: NSGA-III, CTAEA, and SMS-EMOA, to optimize the structural design of prestressed arched trusses. The performance of these algorithms was evaluated using generational distance and inverted generational distance metrics. Additionally, the non-dominated optimal designs generated by these algorithms were assessed and ranked using multiple multi-criteria decision-making techniques, including SAW, FUCA, TOPSIS, PROMETHEE, and VIKOR. This approach allowed for a robust comparison of the algorithms and provided insights into their effectiveness in balancing the different design objectives. The results of the study indicated that NSGA-III exhibited superior performance with a GD value of 0.215, reflecting a closer proximity of its solutions to the Pareto front, and an IGD value of 0.329, indicating a well-distributed set of solutions across the Pareto front. In comparison, CTAEA and SMS-EMOA showed higher GD values of 0.326 and 0.436, respectively, suggesting less convergence to the Pareto front. However, SMS-EMOA demonstrated a balanced performance in terms of constructability and structural weight, with an IGD value of 0.434. The statistical significance of these differences was confirmed by the Kruskal–Wallis test, with p-values of 2.50×10−15 for GD and 5.15×10−06 for IGD. These findings underscore the advantages and limitations of each algorithm, providing valuable insights for future applications in structural optimization. Full article

Therapeutic monoclonal antibodies (mAbs) are crucial in modern medicine due to their effectiveness in treating various diseases. However, the structural complexity of mAbs, particularly their glycosylation patterns, presents challenges for quality control and biosimilarity assessment. This study explores the use of upper-hinge middle-up (UHMU)-level ultra-high-performance liquid chromatography–high-resolution mass spectrometry (LC-HRMS) analysis to improve N-glycan profiling of mAbs. Two specific enzymes, known as IgG degradation enzymes (IGDEs), were used to selectively cleave therapeutic mAbs above the hinge region to separate antibody subunits for further Fc glycan analysis by means of the UHMU/LC-HRMS workflow. The complexity of the mass spectra of IGDEs-digested mAbs was significantly reduced compared to the intact MS level, enabling reliable assignment and relative quantitation of paired Fc glycoforms. The results of the UHMU/LC-HRMS analysis of nine approved therapeutics highlight the significance of this approach for in-depth glycoform profiling. Full article

With internet gaming disorder (IGD) becoming more common, there are growing worries about the health of those it affects. This study examines how traits like Machiavellianism, psychopathy, and narcissism might connect family functioning to IGD. The research involved 1190 young adults who answered an online survey, sharing their personal experiences. To examine the mediation effects, latent variable structural equation modeling (SEM) was used, revealing complex relationships among the variables under investigation. Although all direct and indirect paths were statistically significant, the mediation effects of narcissism were positive only when Machiavellianism and psychopathy were not included as parallel mediators, but negative otherwise. The findings suggest that individuals with strong family functioning could be less likely to internalize manipulative behaviors and show a lack of empathy, traits that could contribute to their involvement in IGD. The results underscore the importance of recognizing the multifaceted nature of this phenomenon and provide valuable insights for developing comprehensive strategies to prevent and tackle IGD. Therefore, prevention and intervention efforts should consider the combined influences of family functioning, personality traits, and individual and contextual factors in the online environment to effectively address this problem. Full article

Immunoglobulin D (IgD) myeloma represents an uncommon subtype of multiple myeloma (MM), accounting for 1–2% of cases. Subjects affected by IgD MM have been demonstrated to have an inferior outcome and survival compared to those with other MM subtypes. A retrospective study was conducted on 15 patients (9 males and 6 females) diagnosed from 2008 to 2022 with IgD MM, in order to investigate the clinical and biochemical features at the moment of diagnosis, cytogenetic alterations, and survival times. The median age was 69 years, and higher frequencies of bone lesions, renal impairments, Bence–Jones proteinuria, and increased serum LDH were observed. Serum calcium levels were in the reference ranges. In the assessment of protein electrophoresis patterns, nine patients had a serum monoclonal protein that was not detectable. A cytogenetic analysis via fluorescence in situ demonstrated that the most common abnormalities were the deletion of 13q and IGH rearrangements. Patients treated with new chemotherapeutic drugs (immunomodulators, proteasome inhibitors), with or without autologous stem cell transplantation presented a higher median survival. The fundamental role of the laboratory in monoclonal IgD detection and the monitoring and studying of IgD MM cases enhances the knowledge of this disease, thus improving patient outcomes. Full article

Motivated by the revitalized interest in the digital simulation of medium- and high-energy physics phenomena, we investigate the dynamics following a Yukawa interaction quench on IBM Q. Adopting the zero-dimensional version of the scalar Yukawa coupling model as our point of departure, we design low-depth quantum circuits, emulating its dynamics with up to three bosons. In the one-boson case, we demonstrate circuit compression, i.e., a constant-depth circuit containing only two controlled-NOT (CNOT) gates. In the more complex three-boson case, we design a circuit in which one Trotter step entails eight CNOTs. Using an analogy with the traveling salesman problem, we also provide a CNOT cost estimate for higher boson number truncations. Based on these circuits, we quantify the system dynamics by evaluating the expected boson number at an arbitrary time after the quench and the survival probability of the initial vacuum state (the Loschmidt echo). We also utilize these circuits to drive adiabatic transitions and compute the energies of the ground- and first-excited states of the considered model. Finally, through error mitigation, i.e., zero-noise extrapolation, we demonstrate the good agreement of our results with a numerically exact classical benchmark. Full article