Search Results (1,458)

Background: Cancer-related fatigue (CRF) is a prevalent, persistent, and multidimensional symptom in breast cancer patients, negatively affecting physical function and quality of life (QoL). Dietary interventions have emerged as safe and cost-effective strategies to alleviate CRF. Methods: This assessor-blinded, randomized controlled trial evaluated the effects of a 12-week dietary quality-based nutrition education program on CRF in breast cancer patients. A total of 128 participants were randomly assigned to the intervention, which received nutrition education based on the Chinese Healthy Eating Index (CHEI), or the control group, which received standard care. Outcomes, including CRF (Revised Piper Fatigue Scale), dietary quality (CHEI), body mass index (BMI), self-management efficacy (Strategies Used by People to Promote Health, SUPPH) and QoL (Functional Assessment of Cancer Therapy-Breast, FACT-B) were assessed at baseline and post-intervention. Results: Of the 128 participants, 111 (86.7%) completed follow-up. Linear mixed-effects models demonstrated a significant group × time interaction for total RPFS scores. After adjusting for age, BMI, cancer stage, pain, anxiety, and depression, the intervention group showed a significantly larger reduction in RPFS scores (β = −1.426, 95% CI: −1.959~−0.893, p < 0.001, Cohen’s d = −0.97). In addition, after adjusting for the same covariates, significant improvements were observed in CHEI (β = 4.799, 95% CI: 1.383~8.215, p = 0.006, Cohen’s d = 0.75), SUPPH scores (β = 16.657, 95% CI: 12.557~20.758, p < 0.001, Cohen’s d = 1.65) and FACT-B scores (β = 12.688, 95% CI: 9.250~16.125, p < 0.001, Cohen’s d = 1.16) in the intervention group, all showing meaningful changes compared with the control group. Conclusions: Dietary quality-based nutrition education significantly alleviated CRF and improved other health-related outcomes in breast cancer patients, suggesting that nutrition education may be an effective strategy for managing CRF and supporting recovery during breast cancer treatment. Full article

Hybrid renewable energy systems (HRESs), mixing conventional and renewable power sources and occasionally storage units, have become the norm regarding electricity generation. Robust long-term planning of such systems requires stakeholders to test different layouts and system configurations, while their operational management relies on forecasting surpluses and deficits to achieve optimal decision making. However, both tasks, which in fact constitute a flow allocation problem across power networks, are subject to multiple peculiarities, arising from the nonlinear dynamics of the underlying processes, subject to numerous technical and operational constraints. Interestingly, a mutual problem emerges in water resource systems, also comprising network-type storage, abstraction and conveyance components. In this vein, triggered from well-established simulation approaches from the water domain, we introduce a generic (i.e., topology-free) and time-agnostic framework, the key methodological elements of which are: (a) the graph-based representation of the power fluxes; (b) the effective handling of energy uses and constraints through virtual nodes and edges; (c) the implementation of priorities via proper assignment of virtual costs across all graph components; and (d) the configuration of the overall problem as a network linear programming context, which allows the use of exceptionally fast solvers. Specific adjustments are required to address highly complex issues within HRESs, particularly the representation of conventional thermal and pumped-storage hydropower units, as well as the power losses across transmission lines. The modeling approach is stress-tested by means of configuring a hypothetical HRES in a non-interconnected Aegean island, i.e., Sifnos, Greece. Full article

Real surveillance systems require weakly supervised video anomaly detection due to the fact that long untrimmed videos do not always have accurate temporal labels. Models will be required to label a video as normal or abnormal and also to identify sparse anomaly areas with mere video-level supervision. In this paper, we introduce ST-CapsNet, which is a spatio-temporal capsule network that enhances weakly supervised localization of anomalies by using a structured representation and temporal agreement. Every video is broken down into 32 parts and coded with 512-dimensional 3D CNN (Convolutional Neural Network) features. Primary capsules record patterns of segments as vectors, and temporal capsules are created by dynamic routing over time, enabling the related abnormal segments to provide support to a common event representation. Training is based on a multiple-instance learning model that has a bag-level BCE (Binary Cross-Entropy) loss, a ranking loss between abnormal and normal separation, and smoothness and sparsity regularization to impose temporal consistency and sparse event behavior. The weakly supervised FAST (Focused and Accelerated Subset Training) split experiments on the UCF-Crime weakly supervised FAST split demonstrate that ST-CapsNet is better than strong baselines. The findings indicate that capsule routing is an effective part of the whole temporal reasoning of weakly supervised surveillance anomaly detection. Full article

Low-frequency hydrophones are used to detect underwater low-frequency acoustic signals and are widely applied in marine science, resource exploration, environmental monitoring, and military operations. Their primary advantage lies in the fact that low-frequency acoustic waves experience less attenuation in water, enabling long-distance detection. This characteristic makes them indispensable for long-range and wide-area sensing. In this study, a piston-structured hydrophone using a stack of lead zirconate titanate (PZT) piezoelectric ceramic sheets is designed. Finite element simulation analysis is used to derive the output voltage variation in the piezoelectric ceramic stack as a function of its thickness and end-face diameter. The piston-structured hydrophone is then designed accordingly. Results show that the piston structure, combined with the longitudinal stacking of PZT piezoelectric ceramic sheets, enhances the sensitivity of the piezoelectric hydrophone. The prepared hydrophone has a directivity of 360° in the operating frequency range of 1 Hz to 1 kHz, as well as a flat frequency response and high sensitivity of −161 dB. These research results indicate that the proposed sonar design provides valuable reference for the development of low-frequency sonar with higher sensitivity, which is of great significance to the development of marine science. Full article

We examine the transition from the Fowler–Nordheim (FN) field emission regime to the space-charge-limited (SCLC) regime in the case of a pointed nanometric emitter with radius of curvature R ≥ 5 nm, for which the traditional FN equations do not hold. To accomplish this, we use the generalized FN equation for the emission law and the “time of flight” methodology to solve the equations of motion. Taking advantage of the fact that emission from emitters with R = a few nm takes place primarily along the emitter axis, we approximate the paths as linear, provided that the anode is at a far distant position from the cathode. In the approach to the SCLC regime, the calculated currents for emitters with R = a few nm may differ by orders of magnitude, compared to the currents of planar emitters, for the a given fixed anode–cathode separation D. Differences of even greater orders of magnitude are obtained for these currents when R is fixed and D is varied. Furthermore, the variation of currents with D is heavily dependent on R. However, for emitters with R ≥ 25 nm, no appreciable differences in current are observed, compared to the results obtained using the planar theory. An explanation for the observed trends is given. Full article

The purpose of this study is to construct diverse forms of exact soliton solutions and conduct a comprehensive qualitative analysis. For this aim, we use the Gross–Pitaevskii system, which belongs to the family of nonlinear Schrödinger equations. This model is considered to be iconic and significant because it has potential applications in applied sciences, such as in physics, where it is used to exemplify quantum systems like Bose–Einstein condensates and illustrate the propagation of waves in optical fibers. Employing analytical techniques, the modified sine–cosine/sinh–cosh and extended rational sinh–Gordon expansion methods, we extract several waves from solutions in the shape of trigonometric, hyperbolic, and rational forms. To further deepen our insights related to the system’s behavior, we execute a detailed dynamical analysis, including sensitivity, bifurcation, and chaos, using the corresponding Hamiltonian structure. We also derive the instability modulation using linear stability theory. Using Mathematica, we systematically simulate and verify all constructed results and present some solutions for appropriate parameter values using 2D, 3D, and contour plots. The outcomes provide fruitful insights relevant to multiple scientific domains, including optical fiber technology, plasma, and condensed matter physics. This work contributes to the ongoing study of nonlinear models by applying novel solution techniques and offering a broader perspective on the complex behavior of such systems. The novelty of this study lies in the fact that the proposed model has not been previously explored using the aforementioned advanced methods and comprehensive dynamical analyses. Full article

Urban forests serve as representations of nature within city landscapes. Green Forest, spanning 5,198,412 square meters, has been incorporated into the Municipality of Timișoara’s public domain and designated as a forest park. This fact increased green space per capita and enriched biodiversity within Timișoara’s landscape architecture. This study explores the diversity of Green Forest trees and highlights their contribution to the urban landscape. Statistical methods, including comparative and linear relationships analyses, were employed to assess significant variations in the dendrometric parameters of the analyzed tree species: mean tree height, mean trunk diameter at breast height (DBH), tree age, and stand density. Principal Component Analysis (PCA) and cluster analysis were applied to uncover underlying patterns in the data. Using ArchiCAD and Lumion, high-quality 3D visual representations were developed for an ecological education area, an active recreation region, and a passive recreation area within Green Forest. Due to their morphological characteristics and phenotypic traits, the predominant tree species include Quercus robur, Quercus cerris, Quercus rubra, Fraxinus excelsior, Acer platanoides, Acer pseudoplatanus, Ulmus campestris, and Robinia pseudoacacia, which contribute to Timișoara’s urban aesthetic. Moreover, the results of the dendrometric analysis provide a foundation for further research in urban ecology. A key practical application of this study is landscape design renderings, which provide detailed and realistic visualizations to effectively communicate the design and functionality of Green Forest’s spaces. If implemented, these developments will encourage public engagement with nature, promoting mental and physical well-being within the community. Full article

Capsicum species are important ornamental plants used as potted plants. Exposure to ethylene causes chlorophyll degradation and leaf and fruit abscission in ornamental peppers, resulting in a loss of their commercial value. The aim of this study was to evaluate pepper elite lines (C. annuum L.) to select ethylene-insensitive individuals with phenotypic stability. The experimental design used was entirely randomized, with 40 treatments × 3 days and ×2 years, following a split-split plot arrangement. The evaluated variables were leaves and fruit abscission, and chlorophyll a and b loss, expressed in percentages. The data were subjected to analysis of variance. The means were grouped by Scott–Knott criteria (p ≤ 0.01). Correlation and heritability were also estimated. The treatments were grouped using the Tocher method based on Mahalanobis-D² distance. A selection index was applied on lower genetic values for all evaluated variables. Through two-year replicated experiments, 12 ethylene-insensitive and phenotypically stable elite lines were identified and can be registered as new ethylene-insensitive cultivars. This fact confirms the efficiency of the selection applied along the years of breeding ethylene-insensitive lines using the pedigree method. Consequently, these elite lines are key genetic resources and suitable crossing material for breeding to improve the vase life of ornamental peppers. Full article

Objective: To address the heavy burden of ego depletion and decision conflict in patients with advanced cancer, this study employed network analysis to explore their interaction mechanisms and identify key intervention targets, overcoming the limitations of traditional linear studies. Methods: A total of 200 patients with advanced cancer were assessed using the Self-Regulatory Fatigue Scale (SRFS), Decisional Conflict Scale (DCS), and Functional Assessment of Cancer Therapy-General (FACT-G). A Gaussian Graphical Model (GGM) was constructed to identify key nodes. Results: Network analysis revealed a tight interactive network among ego depletion, decision conflict, and quality of life. Emotional Function (F3) and Emotional Fatigue (SF2) formed a core emotional cluster, while Uncertainty (D1) was the key cognitive hub. The core nodes F3, D1, and Social/Family Function (F2) were identified as crucial regulators connecting different modules. The core node with the highest Expected Influence was F4 (Functional Status, EI = 0.523), and the key bridge node connecting different modules was F2 (Social/Family Function, bridge strength = 1.114). D3 (Effective Decision-Making, EI = −0.469) was identified as a negative key node associated with adverse network effects. Quantitatively, the core nodes of the network were F4 (Functional Status, EI = 0.523), SF3 (Behavioral Fatigue, EI = 0.353), and SF1 (Cognitive Fatigue, EI = 0.326); the bridge nodes were F2 (Social/Family Function, bridge strength = 1.114), SF2 (Emotional Fatigue, bridge strength = 0.966), and D1 (Uncertainty, bridge strength = 0.858); and D3 (Effective Decision-Making, EI = −0.469) was the negative key node. Conclusions: This study challenges the traditional “symptom-specific treatment” model and proposes a new paradigm of “node-targeted intervention.” Qualitatively, this study clarifies the multidimensional interactive mechanism of ego depletion, decision conflict, and quality of life in advanced cancer patients, and identifies key intervention nodes with different functional attributes (core nodes, bridge nodes, negative nodes). It provides empirical evidence for developing targeted palliative care strategies, which may offer new insights for optimizing symptom management in this population. Clinical Relevance: This study highlights the importance of exploring the multidimensional interaction mechanisms between self-regulatory fatigue, decision conflict, and quality of life in advanced cancer patients, emphasizing the guiding role of core nodes (Functional Status, Behavioral Fatigue, Cognitive Fatigue), bridge nodes (Social/Family Function, Emotional Fatigue, Uncertainty), and the negative node (Effective Decision-Making) in precise intervention. The findings support the integration of node-targeted hierarchical interventions into routine palliative care for advanced cancer patients to break the symptom vicious cycle and enhance their quality of life. Full article

Underground coal gasification (UCG) is a coal utilization technology that has attracted extensive attention over the years. In order to study the distribution and evolution law of the growth boundary of a coal gasification cavity under UCG, COMSOL numerical simulation software was used to conduct a multi-physical field-coupling numerical simulation of its growth process. In this study, we established a gasification reaction model of the cavity, and after simulation calculation, the growth boundary of the gasification cavity was obtained. Multiple data points were taken from the growth boundary of the gasification cavity for the fitting calculation, and the fitting function $y=F\left(x\right)$ of the gasification boundary growth was obtained. The core insight from this study is that a gasification boundary growth fitting function $y=F\left(x\right)$ was cross-fitted based on seven different gasification times $t$ (5 d, 20 d, 40 d, 60 d, 80 d, 110 d, 150 d) and 10 different gasification agent inflow velocities $v$ (0.1 m/s, 0.3 m/s, 0.5 m/s, 0.7 m/s, 1 m/s, 2 m/s, 4 m/s, 6 m/s, 8 m/s, 10 m/s) as orthogonal independent variables. An innovative multi-parameter fitting equation was constructed, $y=F\left(x,t,v\right)$, with the gasification time $t$ and the gasification agent inflow velocity $v$ as independent variables. This fitting equation, $y=F\left(x,t,v\right)$, can dynamically depict the gasification cavity boundary during the UCG process when different gasification times $t$ and gasification agent inflow velocities $v$ are inputted. The novelty of this study lies in the fact that it breaks through the limitations of traditional numerical simulation models that rely on a single variable, have limited adaptability, and focus on gasification cavities that lie mostly in the side-view direction. Moreover, through a multi-physics field-coupling numerical simulation in the top-view direction of the gasification cavity, we have improved the construction of the UCG numerical simulation model and cross-fitted the gasification boundary with respect to the gasification time $t$ and gasification agent inflow velocity $v$ to construct a fitting equation, achieving the quantitative representation of the nonlinear relationship between variables. Full article

Introduction: This review specifically focuses on interventional clinical trials in leukemias and myelodysplastic syndromes (MDS), summarizing how patient-reported outcome measures (PROMs) have been implemented to evaluate treatment effects rather than to directly influence clinical outcomes. Objective: Clinical outcomes of interest typically include response rates, disease-free survival (DFS), and overall survival (OS). Patient-reported outcome measures (PROMs) are standardized questionnaires that collect information regarding health outcomes directly from the patient and are used to evaluate new treatments and healthcare quality. In addition, the use of PROMs in cancer care has been shown to improve patient-provider communication and patient satisfaction. Material and Methods: This is a qualitative, narrative synthesis and review structured around PROMs focused on six critical themes: symptoms/symptom burden, physical, emotional, social/role, and functional status, and global health status measurement. Results: PROMs that are assessed in oncologic research include the EORTC QLQ-C30, FACT-Leu, QLQ-CLL16, and EQ-5D. PROs are associated with clinical outcomes such as DFS and OS, and the FACT-Leu scales, HRQOL and physical functioning scores were independent prognosticators of OS in patients with AML. Conclusions: Through our review, notable trends were identified that further highlight the importance of greater incorporation of PRO measures in future clinical trials, particularly in the understudied realm of hematologic malignancies, in order to better delineate the link between survival and HRQOL. Full article

The combination of supported lipid bilayers (SLBs) with the Quartz Crystal Microbalance with Dissipation monitoring (QCM-D) has been proven to be a powerful tool to simultaneously monitor mass and viscoelastic changes related to membrane binding-events. In this work, the above methodology is employed for the study of the interaction of the Early Endosomal Antigen 1 (EEA1) to a model lipid bilayer that mimics the early endosome (EE) membrane, focusing on the membrane composition. Starting with the formation of a lipid bilayer through the vesicles fusion technique, we investigated the formation of SLBs that incorporate phosphatidylinositol 3-phosphate (PI(3)P), a key component for EEA1 binding, in combination with other lipids, e.g., (1,2-dioleoyl-sn-glycero-3)-phosphocholine (DOPC), -phosphoserine (DOPS), -phosphoethanolamine (DOPE), and cholesterol (Chol). The interaction of the full-length coiled-coil EEA1 to the formed SLBs was further studied in real time with the QCM-D and characterized with respect to the lipid composition and pH. Our findings confirm that PI(3)P is essential for the EEA1–membrane interaction, while it was shown that Chol and phosphatidylserine greatly influence the binding event. In fact, including 30% Chol in a PI(3)P (3%):PS (6%) SLB resulted in almost double EEA1 binding than in the absence of Chol. Moreover, we employed the QCM-viscoelastic model available to analyze the QCM-D data with emphasis on the study of the protein conformation. Our results showed that, in our in vitro system, EEA1 is not fully extended and/or highly packed, but is mainly in a bent, distorted conformation with an average size close to 100 nm. This study complements previous works employing in vitro assays, also demonstrating the ability to reconstitute more complex biomimetic EE membranes containing inositol phospholipids on a QCM surface for the study of EEA1 binding. Full article

Facial information carries key personal privacy, and it is crucial to ensure its security through encryption. Traditional encryption for portrait images typically processes the entire image, despite the fact that most regions lack sensitive facial information. This approach is notably inefficient and imposes unnecessary computational burdens. To address this inefficiency while maintaining security, we propose a novel dual-region encryption model for portrait images. Firstly, a Multi-task Cascaded Convolutional Network (MTCNN) was adopted to efficiently segment facial images into two regions: facial and non-facial. Subsequently, given the high sensitivity of facial regions, a robust encryption scheme was designed by integrating a CNN-based key generator, the proposed three-dimensional Multi-module Nonlinear Feedback-coupled Chaotic System (3D-MNFC), DNA encoding, and bit reversal. The 3D-MNFC incorporating time-varying parameters, nonlinear terms and state feedback terms and coupling mechanisms has been proven to exhibit excellent chaotic performance. As for non-facial regions, the Logistic map combined with XOR operations is used to balance efficiency and basic security. Finally, the encrypted image is obtained by restoring the two ciphertext images to their original positions. Comprehensive security analyses confirm the exceptional performance of the regional model: large key space ($2^{536}$) and near-ideal information entropy (7.9995), NPCR and UACI values of 99.6055% and 33.4599%. It is worth noting that the model has been verified to improve efficiency by at least 37.82%. Full article

Additive manufacturing has been widely adopted in industry as an alternative to traditional manufacturing processes for complex component production. In fact, a diverse range of materials, particularly polymers, can be processed using 3D printing for biomechanical applications (e.g., prosthetics). However, in-depth evaluation of these materials is necessary to determine their suitability for demanding applications, such as those involving cyclic loading. Following previous work that studied Polylactic Acid (PLA) and Polyethylene Terephthalate Glycol-modified (PETG) under experimental fatigue testing, this study examines the fatigue behaviour of other current 3D-printed polymeric materials, namely Acrylonitrile Styrene Acrylate (ASA), Polycarbonate (PC), Polyamide 12 (Nylon 12), and Polycarbonate–Acrylonitrile Butadiene Styrene (blend) (PC-ABS), for which fatigue data remain limited or even non-existent. The findings revealed performance differences on Tensile Strength (σ_R), Young’s Modulus and Ultimate Strain among tensile specimens made from these materials and characterised S-N curves for both high-cycle (HCF) and low-cycle (LCF) fatigue regimes at room temperature, with a tensile load ratio (R = 0.05). These results establish relationships among fatigue limit and quasi-static mechanical properties, namely 25% × σ_r for ASA (8 MPa), 7% × σ_r for PC (3.6 MPa), 17% × σ_r for Nylon 12 (7.4 MPa), and 15% × σ_r for PC-ABS (4.7 MPa), as well as between mechanical properties and preliminary potential biomechanical applications. Main conclusions were further supported by micro-computed tomography (micro-CT), which revealed levels of porosity in between 4% and 11%, thermogravimetric analysis (TGA), differential scanning calorimetry (DSC), and Fourier transform infrared spectroscopy (FTIR). Full article

Transforming growth factor-beta 1 (TGF-β1)-stimulated clone 22 domain (TSC22D) family genes (including TSC22D1-TSC22D4) were identified as transcription factors. It has been demonstrated that they display multiple functions due to proteins’ isoforms, redundancy, and other factors. Formerly, researchers mainly focused on its functions, like controlling cell growth and development, cell apoptosis, and balance of osmotic pressure in vivo. Nowadays, growing evidence indicates that they also play an important role in metabolic regulation and the immune system and are expected to be a new potential target for the treatment of diabetes or obesity. Despite this, it has been shown that TSC22D family genes have an inhibitory effect in multiple tumors. In this review, we significantly synthesized advances in metabolism, showing that TSC22D3 could control lipid accumulation via modulating adipogenesis and adipose differentiation, while TSC22D4 could regulate insulin sensitivity and gluconeogenesis by affecting Akt (serine/threonine kinase, also known as protein kinase B, or PKB) phosphorylation. Moreover, we provide novel insights, including the fact that TSC22D family genes function as a double-edged sword in cancer due to the type of tumor and tumor microenvironment (TME). Full article