Undernutrition among under-fives is one of the major public health challenges in Tanzania. However, there are limited studies assessing the contribution of cultural-related strategies in the prevention of child undernutrition in Tanzania. This study aimed at exploring participants’ experiential views regarding developing culturally sensitive strategies for the elimination of child undernutrition for under-fives in Rukwa, Iringa, Ruvuma, Songwe and Njombe regions located in the Southern Highlands in Tanzania. This study applied focus group discussions (FGDs) with forty practitioners to explore culturally-sensitive strategies for effectively preventing child undernutrition in Tanzania. The study participants were purposively selected, and thematic analysis was used to identify themes within the data. This study revealed that district- and lower-level administrative systems should prioritize nutrition interventions in their plans, allocating adequate resources to implement culturally sensitive nutrition interventions, while national-level organs need to strengthen institutional capacity and ensure the availability of funds, skilled human resources and a legal framework for the effective implementation and sustainability of nutrition interventions at the district- and lower-levels. This study highlights that for the successful implementation of culturally sensitive strategies towards the elimination of child undernutrition, there is a need to use a systems approach that allows for collaborative governance whereby different sectors act together to address the persistent malnutrition epidemic. Full article

This work focuses on the study and comparison of two mixing methods for the dispersion of Alumina-Toughened Zirconia (ATZ) within the polymer matrix of Poly(ε-caprolactone) (PCL). The dry-mixing method using solvent-free impact milling (M) and the solvent casting method with chloroform (SC) were investigated. Samples were produced by 3D printing, and specimens were printed at increasing ATZ loadings (namely, 10, 20, and 40 wt.%). The chemico-physical, mechanical, and cell interaction characteristics of the materials prepared with both mixing methods were studied. Solvent mixing allowed better dispersion of the ATZ in the polymer matrix with respect to dry mixing. In addition, dry mixing affected the molecular weight of the PCL/ATZ composites much more than the solvent casting method. For these reasons, materials obtained by solid mixing exhibited the worst mechanical performance with respect to those obtained by solvent casting, which showed increased Young’s moduli with increasing ATZ amounts. The in vitro biological response elicited in a mesenchymal stem cell model seemed to be influenced by the mixing method, with a preference for the composites obtained through solvent mixing and containing 20 or 40 wt.% of ATZ. Full article

Patients diagnosed with glioblastoma multiforme (GBM) continue to face a dire prognosis. Developing accurate and efficient contouring methods is crucial, as they can significantly advance both clinical practice and research. This study evaluates the AI models developed by MRIMath© for GBM T1c and fluid attenuation inversion recovery (FLAIR) images by comparing their contours to those of three neuro-radiologists using a smart manual contouring platform. The mean overall Sørensen–Dice Similarity Coefficient metric score (DSC) for the post-contrast T1 (T1c) AI was 95%, with a 95% confidence interval (CI) of 93% to 96%, closely aligning with the radiologists’ scores. For true positive T1c images, AI segmentation achieved a mean DSC of 81% compared to radiologists’ ranging from 80% to 86%. Sensitivity and specificity for T1c AI were 91.6% and 97.5%, respectively. The FLAIR AI exhibited a mean DSC of 90% with a 95% CI interval of 87% to 92%, comparable to the radiologists’ scores. It also achieved a mean DSC of 78% for true positive FLAIR slices versus radiologists’ scores of 75% to 83% and recorded a median sensitivity and specificity of 92.1% and 96.1%, respectively. The T1C and FLAIR AI models produced mean Hausdorff distances (<5 mm), volume measurements, kappa scores, and Bland–Altman differences that align closely with those measured by radiologists. Moreover, the inter-user variability between radiologists using the smart manual contouring platform was under 5% for T1c and under 10% for FLAIR images. These results underscore the MRIMath© platform’s low inter-user variability and the high accuracy of its T1c and FLAIR AI models. Full article

Ferromagnetic pipes are widely used in the oil and gas industry. They are subject to cracks due to corrosion, pressure, and fatigue. It is significant to detect cracks for the safety of pipes. A residual magnetic field testing (RMFT) system is developed for crack detection in ferromagnetic pipes. Based on this background, a detection probe based on an array of tunneling magneto-resistive (TMR) sensors and permanent magnets is exploited. The probe is able to partially magnetize the pipe wall and collect magnetic signals simultaneously. First, a theoretical analysis of RMFT is presented. The physics principle of RMFT is introduced, and a finite element model is built. In the finite element simulations, the effects of the crack length and depth on the RMFT signal are analyzed, and the signal characteristics are selected to represent the crack size. Next, the validated experiments are conducted to demonstrate the feasibility of the proposed RMFT method in this paper. Full article

In the context of the technological era, the smart tourism construct serves as a bridge between human and the artificial worlds, combining social sciences and neurosciences. This study aims to explore smart tourism through neuroscientific methods in order to shape the future of tourism destinations, using a hybrid methodology combining bibliometric techniques and content analysis. The findings reveal the integration of diverse scientific domains, highlighting a transdisciplinary approach. They offer clear evidence that neuroscientific methods in smart tourism integrate multiple areas of scientific knowledge, surpassing disciplinary boundaries. “Destination” stands out alongside “emotion”, “visual attention” and eye tracking (ET). The collaboration network reveals the emergence of a new school, called neurotourism in the 21st century, formed mainly by actors and organizations from the Global North, evoking the need to include the Global South in the research scenario. The predominant methods include ET, heart rate (HR), and electroencephalography (EEG), suggesting triangulation with traditional methods for robust results. Virtual reality emerges as the primary immersive technology, promising insights when integrated with neurosciences. This study’s practical and theoretical contributions guide smart tourism strategies and enhance destination experiences through neuroscientific methods, addressing a gap in the scientific literature while advancing ontological and epistemological understanding. Full article

The adsorption of Pb(II) and Cd(II) on three commercial microporous activated carbons was analysed. Adsorption kinetics and statistics were investigated, and the results were described with different models. The highest values of the correlation coefficient R² were obtained for the pseudo-second-order kinetics model for all ions tested and all sorbents used. The adsorption process was found to be determined by both diffusion in the liquid layer and intraparticle diffusion. The adsorption equilibrium is very well described by Langmuir, Temkin, Thoth or Jovanovic isotherm models. Based on the values of n from the Freundlich isotherm and K_L from the Langmuir isotherm, the adsorption of cadmium and lead ions was found to be favourable. The highest monolayer capacities were obtained during the adsorption of lead ions (162.19 mg/g) and for cadmium (126.34 mg/g) for activated carbon WG-12. This carbon is characterised by the highest amount of acid functional groups and the largest specific surface area. The adsorption efficiency of the tested ions from natural water is lower than that from a model solution made from deionised water. The lowest efficiencies are obtained when the process occurs from highly mineralised water. Full article

While understandings of Johannine Christianity have been many and varied, single-issue analyses no longer suffice. Things were more complex than simply inferring that synagogue-Johannine tensions, pneumatizing Gnostics, heretical secessionists, or Petrine ecclesiasts was the lone issue. Nor is a two-level reading of the Johannine narrative plausible, as there is no evidence of alien material underlying John’s story of Jesus. Thus, the early, middle, and later phases of the Johannine tradition must be taken into consideration, as an autonomous memory of Jesus is best seen as developing in a first edition, which was finalized later by the Johannine Elder after writing the Epistles. Within that perspective, Social Identity Complexity Theory is well applied as a means of understanding a number of partners in dialogue within the Johannine Situation, including the stances of Jesus remembered by the Fourth Evangelist and Johannine Elder, who addressed no fewer than seven crises over seven decades within the cosmopolitan Johannine Situation. Full article

Ultrasound is widely used for tendon assessment due to its safety, affordability, and portability, but its subjective nature poses challenges. This study aimed to develop a new quantitative analysis tool based on artificial intelligence to identify statistical patterns of healthy and pathological tendons. Furthermore, we aimed to validate this new tool by comparing it to experts’ subjective assessments. A pilot database including healthy controls and patients with patellar tendinopathy was constructed, involving 14 participants with asymptomatic (n = 7) and symptomatic (n = 7) patellar tendons. Ultrasonographic images were assessed twice, utilizing both the new quantitative tool and the subjective scoring method applied by an expert across five regions of interest. The database contained 61 variables per image. The robustness of the clinical and quantitative assessments was tested via reliability analyses. Lastly, the prediction accuracy of the quantitative features was tested via cross-validated generalized linear mixed-effects logistic regressions. These analyses showed high reliability for quantitative variables related to “Bone” and “Quality”, with ICCs above 0.75. The ICCs for “Edges” and “Thickness” varied but mostly exceeded 0.75. The results of this study show that certain quantitative variables are capable of predicting an expert’s subjective assessment with generally high cross-validated AUC scores. A new quantitative tool for the ultrasonographic assessment of the tendon was designed. This system is shown to be a reliable and valid method for evaluating the patellar tendon structure. Full article

Copper nanoparticles (CuNPs) are extensively used in electronics, cosmetics, fungicides, and various other fields due to their distinctive qualities. However, this widespread usage can contribute to environmental contamination and heightened health risks for living organisms. Despite their prevalent use, the ecological impacts and biosafety of CuNPs remain inadequately understood. The present study aims to delve into the potential toxic effects of CuNPs on zebrafish (Danio rerio) embryos, focusing on multiple indexes such as embryonic development, neurotoxicity, oxidative stress, and inflammatory response. The results revealed a notable increase in the death rate and deformity rate, alongside varying degrees of decrease in hatching rate and heart rate following CuNPs exposure. Particularly, the frequency of spontaneous tail coiling significantly declined under exposure to CuNPs at concentrations of 500 µg/L. Furthermore, CuNPs exposure induced alterations in the transcriptional expression of GABA signaling pathway-related genes (gabra1, gad, abat, and gat1), indicating potential impacts on GABA synthesis, release, catabolism, recovery, and receptor binding. Additionally, CuNPs triggered oxidative stress, evidenced by disruption in superoxide dismutase (SOD), catalase (CAT), and glutathione peroxidase (GPx) activities, along with elevated malondialdehyde (MDA) levels. This oxidative stress subsequently led to a proinflammatory cascade, as demonstrated by the increased transcriptional expression of inflammatory markers (il-1β, tnf-α, il-6, and il-8). Comparative analysis with copper ion (provided as CuCl₂) exposure highlighted more significant changes in most indexes with CuCl₂, indicating greater toxicity compared to CuNPs at equivalent concentrations. In conclusion, these findings provide valuable insights into the toxic effects of CuNPs on zebrafish embryo development and neurotransmitter conduction. Furthermore, they present technical methodologies for assessing environmental and health risks associated with CuNPs, contributing to a better understanding of their biosafety and ecological impact. Full article

The realization of efficient and accurate detection of biomolecules has become a key scientific issue in the field of life sciences. With the rapid development of nanotechnology, electrochemical sensors constructed from the superior physical and chemical properties of nanomaterials show faster and more accurate detection. Among nanomaterials, two-dimensional conductive MOF (2D cMOF) is considered to be a star material in electrochemical sensors due to its remarkable conductivity, high porosity, and stability. In this paper, a Cu₃(HHTP)₂/SPE electrochemical sensor for the detection of ascorbic acid (AA) was constructed by modifying 2D cMOF (Cu₃(HHTP)₂) on the surface of the screen-printed electrode (SPE). The sensor exhibited excellent catalytic activity in the detection of AA, with a lower detection limit of 2.4 μmol/L (S/N = 3) and a wide linear range of 25–1645 μmol/L. This high catalytic activity can be attributed to the abundant catalytic sites in Cu₃(HHTP)₂ and the rapid electron transfer between Cu⁺ and Cu²⁺, which accelerates the oxidation of AA. This work lays a foundation for the subsequent development of MOFs with special electrochemical catalytic properties and the integration of 2D cMOF into intelligent electrical analysis devices. Full article

Distributed Energies Resources (DERs) can be controlled for supporting the voltage regulation at nodes of an Active Distribution Network (ADN) where they are connected. However, since the ADN is a Multi-Input Multi-Output (MIMO) system with coupled dynamics, the controller of a DER mutually interacts with all other controllers through the distribution lines. These interactions lead to operating conflicts which may drive the ADN to work close to its voltage stability boundaries. To achieve a stable voltage regulation without new investment in the existing ADNs, the present paper proposes a straightforward decentralized design of the multi-loop controllers based on the property of integral controllability. The main feature of the method is that the design problem can be expressed by a single parameter designed both for reducing the effects of the undesired coupling and for increasing the degree of robust stability in the presence of parameter uncertainty in the matrix plant. Simulation studies are developed to illustrate the design result and the performance achieved under different operating conditions. The performance is also compared with the one obtained by another method in terms of the integral absolute error. Full article

In order to further investigate the level of online medical services in China and improve the medical experience of patients, this study aims to establish an online review-driven picture fuzzy multi-criteria group decision-making (MCGDM) approach for the online medical service evaluation of doctors. First, based on the Aczel–Alsina t-norm and t-conorm, the normal picture fuzzy Aczel–Alsina operations involving a variable parameter are defined to make the corresponding operations more flexible than other operations. Second, two picture fuzzy Aczel–Alsina aggregation operators are developed, and the corresponding properties are discussed as well. Third, combined with the online review information of China’s medical platform Haodaifu, the online review-driven evaluation attributes and their corresponding weights are obtained, which can make the evaluation model more objective. Fourth, an extended normal picture fuzzy complex proportional assessment (COPRAS) decision-making method for the service quality evaluation of online medical services is proposed. Finally, an empirical example is presented to verify the feasibility and validity of the proposed method. A sensitivity analysis and a comparison analysis are also conducted to demonstrate the effectiveness and flexibility of the proposed approach. Full article

Saving energy and resources has become increasingly important for industrial applications. Foremost, this requires knowledge about the energy requirement. For this purpose, this paper presents a state-based energy requirement model for mobile robots, e.g., automated guided vehicles or autonomous mobile robots, that determines the energy requirement by integrating the linearized power requirement parameters within each system state of the vehicle. The model and their respective system states were verified using a qualitative process analysis of 25 mobile robots from different manufacturers and validated by comparing simulated data with experimental data. For this purpose, power consumption measurements over 461 operating hours were performed in experiments with two different industrial mobile robots. System components of a mobile robot, which require energy, were classified and their power consumptions were measured individually. The parameters in the study consist of vehicle speed, load-handling duration, load, utilization, material flow and layout data, and charging infrastructure system frequency, yet these varied throughout the experiments. Validation of the model through real experiments shows that, in a $99\%$ confidence interval, the relative deviation in the modeled power requirement for a small-scale vehicle is $[-1.86\%,-1.14\%]$, whereas, for a mid-scale vehicle, it is $[-0.73\%,-0.31\%]$. This sets a benchmark for modeling the energy requirement of mobile robots with multiple influencing factors, allowing for an accurate estimation of the energy requirement of mobile robots. Full article

Background: The decreased perfusion of osteosarcoma in dynamic contrast-enhanced (DCE) MRI, reflecting a good histological response to neoadjuvant chemotherapy, has been described. Purpose: In this study, we aim to explore the potential of the relative wash-in rate as a prognostic factor for event-free survival (EFS). Methods: Skeletal high-grade osteosarcoma patients, treated in two tertiary referral centers between 2005 and 2022, were retrospectively included. The relative wash-in rate (rWIR) was determined with DCE-MRI before, after, or during the second cycle of chemotherapy (pre-resection). A previously determined cut-off was used to categorize patients, where rWIR < 2.3 was considered poor and rWIR ≥ 2.3 a good radiological response. EFS was defined as the time from resection to the first event: local recurrence, new metastases, or tumor-related death. EFS was estimated using Kaplan–Meier’s methodology. Multivariate Cox proportional hazard model was used to estimate the effect of histological response and rWIR on EFS, adjusted for traditional prognostic factors. Results: Eighty-two patients (median age: 17 years; IQR: 14–28) were included. The median follow-up duration was 11.8 years (95% CI: 11.0–12.7). During follow-up, 33 events occurred. Poor histological response was not significantly associated with EFS (HR: 1.8; 95% CI: 0.9–3.8), whereas a poor radiological response was associated with a worse EFS (HR: 2.4; 95% CI: 1.1–5.0). In a subpopulation without initial metastases, the binary assessment of rWIR approached statistical significance (HR: 2.3; 95% CI: 1.0–5.2), whereas its continuous evaluation demonstrated a significant association between higher rWIR and improved EFS (HR: 0.7; 95% CI: 0.5–0.9), underlining the effect of response to chemotherapy. The 2- and 5-year EFS for patients with a rWIR ≥ 2.3 were 85% and 75% versus 55% and 50% for patients with a rWIR < 2.3. Conclusion: The predicted poor chemo response with MRI (rWIR < 2.3) is associated with shorter EFS even when adjusted for known clinical covariates and shows similar results to histological response evaluation. rWIR is a potential tool for future response-based individualized healthcare in osteosarcoma patients before surgical resection. Full article

This study aimed to compare and relate the body composition (obtained through anthropometry with the pentacompartmental model and the tricompartmental model by DXA) with bone mineral density and biochemical and nutritional parameters in Chilean adults with overweight/obesity and normal weight from La Araucanía region, Chile. A case-control study was conducted with 116 adults and volunteers from the PURE cohort, collecting sociodemographic data, BMI assessment, waist-to-hip ratio (WHR), and body composition using the pentacompartmental model (5CM) and tricompartmental model (3CM) by DXA, as well as bone mineral density (BMD). Blood biochemical parameters (fasting glucose and lipid profile), physical activity (PA) measured by GPAQ, and average dietary habits (R24h) were measured. In the overweight/obesity group, the 5CM and 3CM adipose mass were indirectly and moderately correlated with PA (p < 0.05), except in the male 5CM group. In the overweight/obesity group, muscle and fat-free mass (FFM) of the 5CM and 3CM correlated directly and moderately with blood fasting glucose (BFG) and BMD (p < 0.05), except in females, where FFM was not related to BMD but was related to residual mass (p < 0.01). Independent of gender and BMI, bone mineral content was positively and highly correlated with BMD (p < 0.0000). In the male overweight/obesity group, bone, skin, and residual mass were correlated with BFG (p < 0.05). In conclusion, for the assessment of non-athletic adult populations, more routine use of the 5CM in clinical practice is recommended. Full article

Nutrient fertilizer application to agricultural land has led to greenhouse gas emissions and has altered soil nitrogen (N) deposition. In soil, N can be degraded in four ways: entering surface water through water flow, absorption by plants and microorganisms, decomposition into gas, and deposition as minerals. This study proposes the concept of N degradability and aims to clarify how farming activities affect N degradability in soil. Over 260 soil profiles were excavated, and the effective soil depth, coordinates, soil types, and vegetation were recorded at each measurement point. The following characteristics were determined in the soil samples: pH, organic matter, total N, total phosphorus, total potassium, total soluble N, available phosphorus, and available potassium. The sample characteristics were subjected to Pearson correlation analysis, principal component analysis, and one-way analysis of variance. The 260 samples included four soil types: dark brown soil, black soil, albic black soil, and meadow soil. Black soil exhibited more stable N levels compared with the other three soil types, showing a tendency towards N accumulation. Ground vegetation was categorized into seven types: forest, rice, maize, red adzuki bean, grassland, soybean, and others. Forests contributed the most to N deposition. Conversely, planting maize led to a tendency for N loss compared with forests. This study can provide a reference for the sustainable development of agriculture and the balance of ecological protection. Full article

As has been widely documented, minority stress affects the psychosocial well-being of gay and lesbian people. Recently, researchers have turned their attention to psychological factors that may influence the level of minority stress experienced, in order to explain individual differences in perceptions of proximal minority stressors. The present research aimed at assessing the effect of attachment avoidance and anxiety on levels of perceived stigma and internalized homonegativity. A total of 163 participants who self-identified as lesbian or gay (M_age = 32.56, SD = 10.87) were recruited and responded to the self-report questionnaires. Two multiple regression models were applied to assess the association between adult attachment and perceived stigma and internalized homonegativity. Results showed a positive association between attachment anxiety and avoidance and internalized homonegativity, as well as between attachment avoidance and perceived stigma. The emerging results demonstrate the impact of attachment anxiety and avoidance on proximal minority stressors and provide useful data for interventions addressing lesbian and gay people aimed at promoting security-based strategies of affect regulation and positive representations of self and others, which in turn may reduce the level of proximal minority stressors experienced and promote psychosocial well-being. Full article

Soybean, a major source of oil and protein, has seen an annual increase in consumption when used in soybean-derived products and the broadening of its cultivation range. The demand for soybean necessitates a better understanding of the regulatory networks driving storage protein accumulation and oil biosynthesis to broaden its positive impact on human health. In this study, we selected a chromosome segment substitution line (CSSL) with high protein and low oil contents to investigate the underlying effect of donor introgression on seed storage through multi-omics analysis. In total, 1479 differentially expressed genes (DEGs), 82 differentially expressed proteins (DEPs), and 34 differentially expressed metabolites (DEMs) were identified in the CSSL compared to the recurrent parent. Based on Gene Ontology (GO) term analysis and the Kyoto Encyclopedia of Genes and Genomes enrichment (KEGG), integrated analysis indicated that 31 DEGs, 24 DEPs, and 13 DEMs were related to seed storage functionality. Integrated analysis further showed a significant decrease in the contents of the seed storage lipids LysoPG 16:0 and LysoPC 18:4 as well as an increase in the contents of organic acids such as L-malic acid. Taken together, these results offer new insights into the molecular mechanisms of seed storage and provide guidance for the molecular breeding of new favorable soybean varieties. Full article

Oxymetholone [C₂₁H₃₂O₃] and metribolone [C₁₉H₂₄O₂] are synthetic anabolic-androgenic agents which are included in the steroid class. Their ability to form new solid forms and their possibility to be included in host–guest β-cyclodextrin complexes was explored. The recrystallization of the compounds in a wide variety of solvents was accomplished. Two oxymetholone polymorphs and one oxymetholone acetic acid solvate were obtained:, while metribolone is reported only in the starting form. Their crystal structures were elucidated using single-crystal X-ray diffraction and the energies of intermolecular interactions were analyzed. Moreover, oxymetholone also showed the ability to be complexed in a new form of oxymetholone–β-cyclodextrin complex. The materials were also investigated by powder X-ray diffraction, DSC/DTA/TGA analysis, and FT-IR spectroscopy. Full article

In a hyperspectral image, there is a close correlation between spectra and a certain degree of correlation in the pixel space. However, most existing low-rank representation (LRR) methods struggle to utilize these two characteristics simultaneously to detect anomalies. To address this challenge, a novel low-rank representation with dual graph regularization and an adaptive dictionary (DGRAD-LRR) is proposed for hyperspectral anomaly detection. To be specific, dual graph regularization, which combines spectral and spatial regularization, provides a new paradigm for LRR, and it can effectively preserve the local geometrical structure in the spectral and spatial information. To obtain a robust background dictionary, a novel adaptive dictionary strategy is utilized for the LRR model. In addition, extensive comparative experiments and an ablation study were conducted to demonstrate the superiority and practicality of the proposed DGRAD-LRR method. Full article

The finite-difference time-domain (FDTD) method is a versatile electromagnetic simulation technique, widely used for solving various broadband problems. However, when dealing with complex structures and large dimensions, especially when applying perfectly matched layer (PML) absorbing boundaries, tremendous computational burdens will occur. To reduce the computational time and memory, this paper presents a Message Passing Interface (MPI) parallel scheme based on non-uniform conformal FDTD, which is suitable for convolutional perfectly matched layer (CPML) absorbing boundaries, and adopts a domain decomposition approach, dividing the entire computational domain into several subdomains. More importantly, only one magnetic field exchange is required during the iterations, and the electric field update is divided into internal and external parts, facilitating the synchronous communication of magnetic fields between adjacent subdomains and internal electric field updates. Finally, unmanned helicopters, helical antennas, 100−period folded waveguides, and 16 × 16 phased array antennas are designed to verify the accuracy and efficiency of the algorithm. Moreover, we conducted parallel tests on a supercomputing platform, showing its satisfactory reduction in computational time and excellent parallel efficiency. Full article

In this study, we analyze the CSMA Non-Persistent protocol with a finite number of nodes, providing more accurate results for applications like wireless sensor networks. The finite model addresses scenarios where the node count is moderate, capturing realistic system dynamics. Our analysis reveals a dependency on the node count, impacting system throughput. As the node count increases, throughput behavior aligns with Kleinrock’s infinite model. We derive a complex closed-form throughput expression for a finite quantity of nodes in the system, solved numerically, and offer an approximate expression for specific conditions. These insights advance understanding of low-contention network performance, especially in scenarios where the infinite model becomes inadequate. Full article