Search Results (14,610)

Introduction: Exposure to violence is an adverse experience associated with the perpetration of violent future behaviors such as child-to-parent violence. Objective: The objectives were to analyze the psychometric properties of the Violence Exposure Scale (VES) in a sample of Ecuadorian adolescents as well as its measurement invariance by sex and age; analyze the differences in exposure to violence across four settings (home, school, street, and TV), in two time frames (last year and childhood), according to sex and age; and analyze the relationship between exposure to violence in the four settings and in both time frames with child-to-parent violence. Methods: A cross-sectional study was conducted using a probabilistic sample of 2150 Ecuadorian adolescents (55% female), aged 12 to 18 years (M = 14.53; SD = 1.55). Participants completed the adapted version of the VES and the Child-to-Parent Violence Questionnaire (CPV-Q). Confirmatory factor analyses, reliability testing, convergent and discriminant validity analyses, and measurement invariance assessments were performed. Results: The VES showed excellent model fit in both versions, VES¹ (last year) and VES² (before age 10), with strong goodness-of-fit indices (VES¹: CFI = 0.988; RMSEA = 0.055; VES²: CFI = 0.994; RMSEA = 0.044). Reliability was good (α_o and ω_o ≤ 0.80; G.6 and CR ≤ 0.70). Effect sizes ranged from 0.11 to 0.31 for violence by children toward parents and reached up to 0.83 among the different forms of victimization. Conclusions: The adaptation of the VES in Ecuadorian adolescents showed validity and reliability in assessing exposure to violence. Girls were more at risk at home, while boys were more exposed at school and in the community. Full article

Background: Repeat induced abortion (defined as ≥two lifetime procedures) is becoming more common worldwide, yet its independent influence on women’s psychological health remains contested, particularly in settings where access to modern contraception is restricted. Objectives: This review sought to quantify the burden of depression, anxiety, stress, and generic quality of life (QoL) among women with repeat abortions and to determine how barriers to contraceptive access alter those outcomes. Methods: Following the preregistered PRISMA-2020 protocol, PubMed, Embase and Scopus were searched from inception to 31 June 2025. Results: Eight eligible studies comprising approximately 262,000 participants (individual sample sizes up to 79,609) revealed wide variation in psychological morbidity. Prevalence of clinically significant symptoms ranged from 5.5% to 24.8% for depression, 8.3% to 31.2% for anxiety, and 18.8% to 27% for perceived stress; frequent mental distress affected 12.3% of women in neutral policy environments but rose to 21.9% under highly restrictive abortion legislation. Having three or more abortions, compared with none or one, increased the odds of depressive symptoms by roughly one-third (pooled OR ≈ 1.37, 95% CI 1.13–1.67). Contextual factors exerted comparable or stronger effects: abortions sought for socioeconomic reasons elevated depression odds by 34%, unwanted disclosure of the abortion episode increased depressive scores by 0.62 standard deviations, and low partner support raised them by 0.67 SD. At the structural level, every standard deviation improvement in a state’s reproductive rights index reduced frequent mental distress odds by 5%, whereas enactment of a near-total legal ban produced an absolute increase of 6.8 percentage points. QoL outcomes were less frequently reported; where measured, denied or heavily delayed abortions were associated with a 0.41-unit decrement on a seven-point life satisfaction scale. Conclusions: Psychological morbidity after abortion clusters where legal hostility, financial hardship, or interpersonal coercion constrain contraceptive autonomy while, in comparison, the mere number of procedures is a weaker predictor. Interventions that integrate stigma-free mental health support with confidential, affordable, and rights-based contraception are essential to protect well-being in women who experience repeat abortions. Full article

Urban traffic noise has become an increasingly significant environmental and public health issue, with many cities—particularly those experiencing rapid urban growth, such as Kuwait—recording levels that often exceed recommended limits. In this study, we present a detailed, data-driven approach for assessing and predicting equivalent continuous noise levels (LAeq) in residential neighborhoods. The analysis draws on measurements taken at 12 carefully chosen sites covering different road types and urban settings, resulting in 21,720 matched observations. A range of predictors was considered, including road classification, traffic composition, meteorological variables, spatial context, and time of day. Four predictive models—Linear Regression, Support Vector Machine (SVM), Gaussian Process Regression, and Bagged Trees—were evaluated through 5-fold cross-validation. Among these, the Bagged Trees model achieved the strongest performance (R² = 0.91, RMSE = 2.13 dB(A)). To better understand how the model made its predictions, we used SHAP (SHapley Additive Explanations) analysis, which showed that road classification, location, heavy vehicle volume, and time of day had the greatest influence on noise levels. The results identify the main determinants of traffic noise in Kuwait’s urban areas and emphasize the role of targeted design and planning in its mitigation. Full article

The intrinsic noise of giant magnetoresistive (GMR) sensors is large at low frequencies, and their resolution is inevitably significantly limited. Investigation of GMR noise requires the use of measurement systems that have lower noise than the sample. In this context, the main purpose of this study is to evaluate the effectiveness of two electronic noise measurement configurations of a single GMR sensing element. The first method connects the sample in a voltage divider configuration and the second method connects in a Wheatstone bridge configuration. Three amplification set-ups were investigated: a low-noise amplifier, an ultra-low-noise amplifier and an instrumentation amplifier. Using cross-correlation, the noise of the measurement system introduced by the amplifiers was reduced. Noise spectra were recorded at room temperature in the frequency range of 0.5 Hz to 10 kHz, under different sample bias voltages. The measurements were performed in zero applied magnetic field and in a field corresponding to the maximum sensitivity of the sensor. From the noise spectra, the detectivity of the sensor was determined to be in the 200–300 nT/√Hz range. Good agreement was observed between the results obtained using all three set-ups, suggesting the effectiveness of the noise measurement systems applied to the magnetoresistive sensor. Full article

Ternary hybrid nanofluid have been revealed to possess a wide range of application disciplines reaching from biomedical engineering, detection of cancer, over or photovoltaic panels and cells, nuclear power plant engineering, to the automobile industry, smart cells and and eventually to heat exchange systems. Inspired by the recent developments in nanotechnology and in particular the high potential ability of use of such nanofluids in practical problems, this paper deals with the flow of a three phase nanofluid of MWCNT-Au/Ag nanoparticles dispersed in blood in the presence of a bidirectional stretching sheet. The model derived in this study yields a set of linked nonlinear PDEs, which are first transformed into dimensionless ODEs. From these ODEs we get a dataset with the help of MATHEMATICA environment, then solved using AI-based technique utilizing Levenberg Marquardt Feedforward Algorithm. In this work, flow characteristics under varying physical parameters have been studied and analyzed and the boundary layer phenomena has been investigated. In detail horizontal, vertical velocity profiles as well as temperature distribution are analyzed. The findings reveal that as the stretching ratio of the surface coincide with an increase the vertical velocity as the surface has thinned in this direction minimizing resistance to the fluid flow. Full article

Background/Objectives: Cerebral palsy (CP) is one of the most common causes of permanent motor disability in children, and its consequences for upper limb function have a significant impact on the patient’s independence and quality of life. Virtual reality is attracting increasing interest as a modern, engaging and effective method of physiotherapy for children with cerebral palsy. This systematic literature review aimed to synthesize current scientific data on the impact of virtual-reality-based physiotherapy on upper limb function in children with cerebral palsy. Methods: The review was conducted in accordance with PRISMA 2020 guidelines. PubMed, Science Direct, Scopus, Web of Science, Research Gate and Google Scholar databases were searched for studies published between 2010 and 2025. Six original studies meeting the following criteria were included in the analysis: virtual reality therapy, population of children with cerebral palsy, physiotherapy goals related to the upper limb and availability of full text. Results: All included studies demonstrated a positive impact of virtual reality on at least one functional parameter of the upper limb, including range of motion, muscle strength, coordination and manual precision. Task-oriented training, immersive virtual reality environments and home-based therapy supported by remote monitoring proved to be the most effective. The effects were particularly noticeable in children with moderate impairment at GMFCS I–III. Conclusions: Virtual reality represents a safe and promising technology to support upper limb physiotherapy in children with cerebral palsy. It can be used both in clinical and home settings, contributing to increased exercise intensity and motivation. Further long-term studies using high-quality methodology are needed to determine the sustainability of the effects and their impact on everyday living. Full article

Reducing pesticide residues in crops is essential to ensure food safety, protect human health, and promote environmental sustainability. In this study, activated carbon (AC) was applied as a soil amendment to investigate its effect on reducing residues of the pesticides cyantraniliprole and fluopyram in greenhouse-grown lettuce. The effectiveness of AC in reducing pesticide residues varies significantly based on pesticides and crops. Pesticide dissipation patterns in the soil and a set of pesticide residues of lettuce leaf and root tissues, as well as the soil surrounding the roots for each of the tested pesticides, were analyzed using liquid chromatography with tandem mass spectrometry (LC-MS/MS) during the test periods. The results showed different pesticide dissipation patterns for cyantraniliprole, fitting the first-order kinetics, and fluopyram. Nevertheless, both AC treatments exhibited a similar decreasing tendency in which cyantraniliprole residues ranged from 0.050 to 0.064 mg/kg in leaf and 0.019 to 0.034 mg/kg in root samples, while fluopyram residues ranged from 0.168 to 0.509 mg/kg in leaf and 0.315 to 0.787 mg/kg in root samples. The highest percentage reductions were 71.3% and 77.3% for cyantraniliprole in leaf and root samples, respectively, and 79.7% and 87.5% for fluopyram in leaf and root samples. In addition, the soil samples showed a more dynamic pattern of pesticide residues compared to those of the lettuce samples. The overall findings suggest that applying AC as a soil amendment in pesticide-treated soils has a positive effect on reducing residues of cyantraniliprole and fluopyram in lettuce. Therefore, this AC-treated soil amendment could be considered a safer agricultural practice with great potential for producing safer food resources from pesticide-contaminated soils. Thus, it is expected that proper utilization of AC plays an important role in the production of safe agri-food products to manage and generate a sustainable agricultural environment. Full article

Background: Atherogenic dyslipidemia is defined by the coexistence of high triglyceride concentrations, low levels of high-density lipoprotein cholesterol (HDL-C), and an excess of small, dense particles of low-density lipoprotein cholesterol (LDL-C). This lipid profile is strongly associated with an increased burden of cardiovascular disease and represents a leading cause of global morbidity and mortality. To better capture this risk, composite lipid ratios—including total cholesterol to HDL-C (TC/HDL-C), LDL-C to HDL-C (LDL-C/HDL-C), triglycerides to HDL-C (TG/HDL-C), and the atherogenic dyslipidemia index (AD)—have emerged as robust markers of cardiometabolic health, frequently demonstrating superior predictive capacity compared with isolated lipid measures. Despite extensive evidence linking these ratios to cardiovascular disease, few large-scale studies have examined their association with sociodemographic characteristics, lifestyle behaviors, and social isolation in working populations. Methods: We conducted a cross-sectional analysis of a large occupational cohort of Spanish workers evaluated between January 2021 and December 2024. Anthropometric, biochemical, and sociodemographic data were collected through standardized clinical protocols. Indices of atherogenic risk—namely the ratios TC/HDL-C, LDL-C/HDL-C, TG/HDL-C, and the atherogenic dyslipidemia index (AD)—were derived from fasting lipid measurements. The assessment of lifestyle factors included tobacco use, physical activity evaluated through the International Physical Activity Questionnaire (IPAQ), adherence to the Mediterranean dietary pattern using the MEDAS questionnaire, and perceived social isolation measured by the Lubben Social Network Scale. Socioeconomic classification was established following the criteria proposed by the Spanish Society of Epidemiology. Logistic regression models were fitted to identify factors independently associated with moderate-to-high risk for each lipid indicator, adjusting for potential confounders. Results: A total of 117,298 workers (71,384 men and 45,914 women) were included. Men showed significantly higher odds of elevated TG/HDL-C (OR 4.22, 95% CI 3.70–4.75) and AD (OR 2.95, 95% CI 2.70–3.21) compared with women, whereas LDL-C/HDL-C ratios were lower (OR 0.86, 95% CI 0.83–0.89). Advancing age was positively associated with all lipid ratios, with the highest risk observed in participants aged 60–69 years. Lower social class, smoking, physical inactivity, poor adherence to the Mediterranean diet, and low social isolation scores were consistently linked to higher atherogenic risk. Physical inactivity showed the strongest associations across all indicators, with ORs ranging from 3.54 for TC/HDL-C to 7.12 for AD. Conclusions: Atherogenic dyslipidemia and elevated lipid ratios are strongly associated with male sex, older age, lower socioeconomic status, unhealthy lifestyle behaviors, and reduced social integration among Spanish workers. These findings highlight the importance of workplace-based cardiovascular risk screening and targeted prevention strategies, particularly in high-risk subgroups. Interventions to promote physical activity, healthy dietary patterns, and social connectedness may contribute to lowering atherogenic risk in occupational settings. Full article

Barium strontium titanates (Ba_1−xSr_xTiO₃, BST) with varying barium-to-strontium ratios were synthesized by the solid-state route (SSR) as well as by the sol–gel process (SGP). In the case of the SSR, the strontium amount x was varied from 0.0 to 0.25 in 0.05 steps, due to the enhanced synthetic effort, and in the case of the SGP, x was set only to 0.05, 0.15, and 0.25. The resulting properties after synthesis, calcination, and sintering, like particle size distribution, specific surface area, particle morphology, and crystalline phase were characterized. The expected tetragonal phase, free from any remarkable impurity, was found in all cases, and irrespective of the selected synthesis method. Pressed pellets were used for the measurement of the temperature and frequency-dependent relative permittivity enabling the estimation of the Curie temperatures of all synthesized BSTs. Irrespective of the selected synthesis method, the obtained Curie temperature drops with increasing strontium content to almost identical values, e.g., in the case of x = 0.15, a Curie temperature range 95–105 °C was measured. Thin BST films could be deposited on different substrate materials applying electrophoretic deposition in a good and reliable quality according to the Hamaker equation. The properties of the BSTs obtained by the simpler solid-state route are almost identical to the ones yielded by the more complex sol–gel process. In future, this result allows for a possible wider usage of BST perovskites for ferroelectric and piezoelectric devices due to the easy synthetic access by the solid-state route. Full article

Model-based approaches provide increasingly advanced opportunities for optimizing and accelerating bioprocess development. However, to accurately capture the complexity of biotechnological processes, continuous refinement of suitable models remains essential. A crucial gap in this field has been the lack of suitable model for describing Escherichia coli growth in cultivation media containing yeast extract, while accounting for key bioprocess parameters such as biomass, substrate, acetate, and oxygen. To address this, a published mechanistic macro-kinetic model for E. coli was extended with a set of mathematical equations that describe key aspects of the uptake of yeast extract. The underlying macro-kinetic approach is based on the utilization of amino acids in E. coli, where growth is primarily influenced by two distinct classes of amino acids. Using fed-batch cultivation data from an E. coli K-12 strain supplemented with yeast extract, it was demonstrated that the proposed model extensions were essential for accurately representing the bioprocess. This approach was further validated through fitting the model on cultivation data from five different yeast extracts sourced from various manufacturers. Additionally, the model enabled reliable predictions of growth dynamics across a range of yeast extract concentrations up to 20 g L⁻¹. Further differentiation of the data into batch and fed-batch revealed that for less complex datasets, such as those obtained from a batch phase, a simplified model can be sufficient. Due to its modular structure, the developed model provides the necessary flexibility to serve as a tool for the development, optimization, and control of E. coli cultivations with and without yeast extract. Full article

In this paper, we propose a formulation of the permutation flow and job shop scheduling problems using special recursive functions and show its equivalence to the existing classical formulation. Equivalence is understood in the sense that both ways of defining the problem describe the same set of feasible schedules for each pair of jobs and machine numbers. In this paper, the apparatus of recursive functions is used to describe and solve three problems: permutation flow shop; permutation flow shop with the addition of the ’and’ predicate extending the machine chain to an acyclic graph; and permutation job shop. The predicate ’and’ allows the description of the flow shop with assembly operation tasks. Recursive functions have a common domain and range. To calculate an optimal schedule for each of these three problems, a branch and bound method is considered based on a recursive function that implements a job swapping algorithm. The complexity of the optimization algorithm does not increase compared to the non-recursive description of the PFSP. This article presents some results for the calculation of optimal schedules on several test instances. It is expected that the new method, based on the description of recursive functions and their superposition, will be productive for formulating and solving some extensions of scheduling problems that have practical significance. Full article

Non-diabetic chronic kidney disease (ND-CKD) refers to the progressive and irreversible decline in kidney function occurring in the absence of diabetes mellitus—a distinction that sets it apart from the more prevalent diabetic CKD. While diabetic nephropathy remains the leading cause of CKD globally, ND-CKD encompasses a heterogeneous group of etiologies, including hypertensive nephrosclerosis, glomerulonephritis, and interstitial nephritis. Its incidence and prevalence are steadily increasing, particularly in aging populations, and are often underrecognized. Importantly, ND-CKD is not a benign entity; it independently contributes to systemic inflammation, oxidative stress, and metabolic dysregulation, which in turn amplify cardiovascular risk. Among the most severe complications is heart failure (HF), a complex syndrome arising from structural and functional impairments in cardiac performance. Despite ongoing advancements in HF management, mortality remains unacceptably high, ranging from 2–3% at 30 days to up to 50–75% over five years. Standard pharmacologic therapies frequently fall short in halting disease progression and may provoke undesirable side effects. This therapeutic gap has spurred growing interest in natural compounds with multi-targeted effects. Bioactive molecules such as arjunolic acid, kaempferol, luteolin, and resveratrol have shown anti-inflammatory and antioxidant properties that may offer dual benefits for both renal and cardiac function. By modulating shared molecular pathways—including those involved in inflammation, oxidative damage, and cellular dysfunction—these agents hold promise as adjunctive treatments in ND-CKD complicated by heart failure. Full article

The degree of informational redundancy is often examined in genetic studies but not yet detailed for taxa conceived as minimally monophyletic groups (microgenus). Evolutionary processes in microgenera were reviewed, detailing critical sets of traits, the novon, the immediate ancestron, and the ancestron. Calculations were made from known intra-genus character state changes for maximum entropy, Shannon entropy, and entropic redundancy. Additional evaluations of contrived data sets were intended to evaluate the range of informational variation in small, medium, and large numbers of species and traits. Results indicate that measures of Shannon information and redundancy are rather similar in all but microgenera with the smallest number of species and traits per species. Hypothetically, this similarity is due to the fairly constant balance between numbers of newly evolved traits and traits monothetically redundant because all are shared with all species in the genus. This balance may be explained by a selective construct or emergent property that balances innovation leading to the colonization of new niches and conservation of proven ancestral traits for survival sympatricially and peripatrically in the particular challenges of the ancestor’s niche. The entropic redundancy calculations indicate that 0.20 to 0.30 of the information in a microgenus serves as flexibility in survival adaptation at the genus level. Full article

In the last decades, the introduction of intermittent renewable energy sources has transformed the operation of power systems. In this framework, ancillary service markets (ASMs) play an important role, due to their contribution in supporting system operators to balance demand and supply and managing real-time contingencies. Usually, ASMs require that energy is committed before actual participation, hence scheduling systems of plants and microgrids are required to compute the dispatching program and bidding strategy before needs of the market are revealed. Since possible ASM requirements are given as input to scheduling systems, the chance of accessing accurate estimates may be helpful to define reliable dispatching programs and effective bidding strategies. Within this context, this paper proposes a methodology to estimate the revenue range of energy exchange proposals in the ASM. To this end, the possible revenues are discretized into ranges and a classification pattern recognition algorithm is implemented. Modeling is performed using extreme gradient boosting. Input data to be fed to the algorithm are selected because of relationships with the production unit making the proposal, with the location and temporal indication, with the grid power dispatch and with the market regulations. Different tests are set up using historical data referred to the Italian ASM. Results show that the model can appropriately estimate rejection and the revenue range of awarded bids and offers, respectively, in more than 82% and 70% of cases. Full article

To monitor large deformations in dovetail tenon joints of Dong ethnic wooden drum towers, this study designs a large-range Fiber Bragg Grating (FBG) strain sensor based on the FBG sensing principle. The NSGA-II algorithm is utilized to optimize the packaging structure of FBG strain sensors. Consequently, an adaptive optimization methodology for its packaging configuration is proposed. This study sets the optimization objectives as a 5000 με measurement range and 0.1 pm/με sensitivity. It employs the NSGA-II algorithm to optimize the structural dimensions and material properties of the large-range FBG strain sensor. This process yields three combinations that meet the requirements for monitoring large deformations in dovetail tenon joints of Dong wooden drum towers. Subsequent linearity experiments were conducted to verify the sensitivity stability and measurement range of the three large-range FBG strain sensors. The results show that within the measurement range of 0–6000 με, all three sensors achieve a strain sensitivity of 0.099 pm/με, with a fitted linear correlation coefficient of 0.999. Full article