This study aims to enhance urban sustainability by analyzing the spatial distribution and underlying causes of vacant homes in Asan, Chungcheongnam-do. Various statistical methods were employed to analyze date concerning the number of vacant stores, population changes, land use complexity, and the physical characteristics of land and buildings; these factors were found to influence the prevalence of vacant homes across Asan. Additionally, it was found that distinct factors differentially affect specific regions, such as old downtown areas versus rural villages. This indicates that reducing vacant homes in these areas requires distinct policies tailored to the unique circumstances of each region. For instance, in old town areas, small lot ratios and land use complexity are significant, while in rural villages, the average number of floors and land use complexity play a major role. This study highlights the diverse factors influencing the prevalence of vacant homes and suggests that to effectively address this issue, policies should be developed that are tailored to the unique characteristics of each area, categorized at both the city and local levels. Full article

Loneliness has become a pressing topic, especially among young adults and during the COVID-19 pandemic. In a randomized controlled trial with 253 healthy adults, we evaluated the differential efficacy of two 10-week app-delivered mental training programs: one based on classic mindfulness and one on an innovative partner-based socio-emotional practice (Affect Dyad). We show that the partner-based training resulted in greater reductions in loneliness than the mindfulness-based training. This effect was shown on three measures of loneliness: general loneliness assessed with the 20-item UCLA Loneliness Scale, state loneliness queried over an 8-day ecological momentary assessment in participants’ daily lives, and loneliness ratings required before and after daily practice. Our study provides evidence for the higher efficacy of a mental training approach based on a 12 min practice conducted with a partner in reducing loneliness and provides a novel, scalable online approach to reduce the increasing problem of loneliness in society. Full article

The aim of this study was to evaluate the effects of different drying methods on bioactive compounds and to analyze their composition in Verbascum sinaiticum (V. sinaiticum) leaf extracts using UHPLC-ESI-QTOF-MS/MS. V. sinaiticum is traditionally used as an herbal medicine, yet it has undergone limited scientific investigations regarding its secondary metabolites. V. sinaiticum leaves were dried using oven dryers at 50 °C, 60 °C, and 70 °C, as well as a freeze dryer. The leaves were then extracted using 50% and 70% aqueous ethanol and 100% aqueous solutions. The results showed that the highest contents of TPC and TFC were observed when 70% aqueous ethanol was used during freeze drying, reaching 181.73 mg GAE/g dw and 78.57 mg CE/g dw, respectively. The strongest correlations were observed between the TFC and DPPH radical scavenging activity (0.9082), followed by TPC and ABTS assays (0.8933) and TPC and DPPH (0.8272). In the FTIR analysis, freeze drying exhibited a lower intensity of the phenolic -OH functional groups, contrasting with significant denaturation observed during oven drying at 70 °C. Metabolite analysis identified 29 compounds in V. sinaiticum leaves, further confirming the presence of 14 phenolic and flavonoid compounds, including kaempferol, catechin, gallic acid, and myricetin derivatives, consistent with the experimentally observed antioxidant capacity. This study highlights the impact of drying methods on the bioactive composition of V. sinaiticum and underscores its potential as a source of antioxidants for food, nutraceutical, and pharmaceutical applications. Full article

The skeletal muscles account for approximately 40% of the body weight and are crucial in movement, nutrient absorption, and energy metabolism. Muscle loss and decline in function cause a decrease in the quality of life of patients and the elderly, leading to complications that require early diagnosis. Positron emission tomography/computed tomography (PET/CT) offers non-invasive, high-resolution visualization of tissues. It has emerged as a promising alternative to invasive diagnostic methods and is attracting attention as a tool for assessing muscle function and imaging muscle diseases. Effective imaging of muscle function and pathology relies on appropriate radiopharmaceuticals that target key aspects of muscle metabolism, such as glucose uptake, adenosine triphosphate (ATP) production, and the oxidation of fat and carbohydrates. In this review, we describe how [¹⁸F]fluoro-2-deoxy-D-glucose ([¹⁸F]FDG), [¹⁸F]fluorocholine ([¹⁸F]FCH), [¹¹C]acetate, and [¹⁵O]water ([¹⁵O]H₂O) are suitable radiopharmaceuticals for diagnostic imaging of skeletal muscles. Full article

Introduction: Identifying the complexity of palliative care needs is a key aspect of referral to specialized multidisciplinary early palliative care (EPC) teams. The PALCOM scale is an instrument consisting of five multidimensional assessment domains developed in 2018 and validated in 2023 to identify the level of complexity in patients with advanced cancer. (1) Objectives: The main objective of this study was to determine the degree of instability (likelihood of level change or death), health resource consumption and the survival of patients according to the level of palliative complexity assigned at the baseline visit during a 6-month follow-up. (2) Method: An observational, prospective, multicenter study was conducted using pooled data from the development and validation cohort of the PALCOM scale. The main outcome variables were as follows: (a) instability ratio (IR), defined as the probability of level change or death; (b) emergency department visits; (c) days of hospitalization; (d) hospital death; (e) survival. All the variables were analyzed monthly according to the level of complexity assigned at the baseline visit. (3) Results: A total of 607 patients with advanced cancer were enrolled. According to the PALCOM scale, 20% of patients were classified as low complexity, 50% as medium and 30% as high complexity. The overall IR was 45% in the low complexity group, 68% in the medium complexity group and 78% in the high complexity group (p < 0.001). No significant differences in mean monthly emergency department visits (0.2 visits/ patient/month) were observed between the different levels of complexity. The mean number of days spent in hospital per month was 1.5 in the low complexity group, 1.8 in the medium complexity group and 3.2 in the high complexity group (p < 0.001). The likelihood of in-hospital death was significantly higher in the high complexity group (29%) compared to the medium (16%) and low (8%) complexity groups (p < 0.001). Six-month survival was significantly lower in the high complexity group (24%) compared to the medium (37%) and low (57%) complexity groups (p < 0.001). Conclusion: According to the PALCOM scale, more complex cases are associated with greater instability and use of hospital resources and lower survival. The data also confirm that the PALCOM scale is a consistent and useful tool for describing complexity profiles, targeting referrals to the EPC and managing the intensity of shared care. Full article

The fetal splenic artery pulsatility index is a parameter that reflects fetal well-being and has been used as a predictor of adverse pregnancy outcomes. The aim of this study was to investigate the predictive value of the splenic artery pulsatility index in gestational diabetes mellitus class A1 cases for intensive care unit admission. In this prospective case-controlled study, only sixty single pregnancy cases diagnosed with gestational diabetes mellitus class A1 were evaluated. Fetal splenic artery Doppler parameters such as peak systolic velocity, pulsatility index, resistivity index, and end-diastolic velocity were measured in all cases. The rate of requirements for the neonatal intensive care unit was noted. In cases requiring fetal intensive care, the fetal splenic pulsatility index was found to be statistically significantly lower than in healthy cases without it (0.94 ± 0.29 vs. 1.70 ± 0.53, respectively, p < 0.001, Student’s t-test). When the fetal splenic PI cutoff value was selected as 1.105 cm3, the sensitivity was calculated as 97.9% and the specificity as 58.3% for predicting the need for fetal intensive care (AUC 0.968, p < 0.001, 95% CI 0.929–0.998). The use of a low fetal splenic artery PI parameter is a significant and good indicator for predicting the need for fetal intensive care according to the binary logistic regression analysis result (p = 0.006). This study suggests that evaluation of fetal splenic artery Doppler in mothers with gestational diabetes mellitus may be used to predict neonates requiring a newborn intensive care unit. Therefore, it is recommended that obstetricians use this simple, rapid, and valuable evaluation of fetal splenic artery Doppler and alert the neonatologist that a newborn intensive care unit may be required. Full article

Mitochondrial diseases (MDs) affect 4300 individuals, with different ages of presentation and manifestation in any organ. How defects in mitochondria can cause such a diverse range of human diseases remains poorly understood. In recent years, several published research articles regarding the metabolic and protein profiles of these neurogenetic disorders have helped shed light on the pathogenetic mechanisms. By investigating different pathways in MDs, often with the aim of identifying disease biomarkers, it is possible to identify molecular processes underlying the disease. In this perspective, omics technologies such as proteomics and metabolomics considered in this review, can support unresolved mitochondrial questions, helping to improve outcomes for patients. Full article

Aircraft targets, as high-value subjects, are a focal point in Synthetic Aperture Radar (SAR) image interpretation. To tackle challenges like limited SAR aircraft datasets and shortcomings in existing detection algorithms (complexity, poor performance, weak generalization), we present the Feature Enhancement and Multi-Scales Fusion Network (FEMSFNet) for SAR aircraft detection. FEMSFNet employs diverse image augmentation and integrates optimized Squeeze-and-Excitation Networks (SE) with residual network (ResNet) in a SdE-Resblock structure for a lightweight yet accurate model. It introduces ssppf-CSP module, an improved pyramid pooling model, to prevent receptive field deviation in deep network training. Tailored for SAR aircraft detection, FEMSFNet optimizes loss functions, emphasizing both speed and accuracy. Evaluation on the SAR Aircraft Detection Dataset (SADD) demonstrates significant improvements compared to the contrasted algorithms: precision rate (92%), recall rate (96%), and F1 score (94%), with a maximum increase of 12.2% in precision, 12.9% in recall, and 13.3% in F1 score. Full article

The “Content-Identifying Methodology”, or CIM, is an approach developed by environmental psychologists Rachel and Stephen Kaplan to understand the landscape characteristics that people find visually attractive. The Kaplans did this by surveying people’s landscape preferences and then analyzing the preferences to develop sets of landscape scenes to which people reacted in a similar pattern. The underlying assumption is that a common stimulus or content exists in the photographs of a set responsible for the preference. However, identifying the common stimulus or content in each set or grouping of scenes and how it affects preference can still be challenging. Eye-tracking is a tool that can identify what the survey participants were looking at when indicating their preference for a landscape. This paper demonstrates how eye-tracking was used in two different landscape preference studies to identify the content important to people’s preferences and provide insights into how the content affected preference. Eye-tracking can help identify a common stimulus, help determine if the stimulus is a physical or spatial characteristic of the landscape, and show how the stimulus varies in different landscape contexts. Full article

Melatonin and sericin exhibit antioxidant properties and may be useful in topical wound healing patches by maintaining redox balance, cell integrity, and regulating the inflammatory response. In human skin, melatonin suppresses damage caused by ultraviolet radiation (UVR) which involves numerous mechanisms associated with reactive oxygen species/reactive nitrogen species (ROS/RNS) generation and enhancing apoptosis. Sericin is a protein mainly composed of glycine, serine, aspartic acid, and threonine amino acids removed from the silkworm cocoon (particularly Bombyx mori and other species). It is of interest because of its biodegradability, anti-oxidative, and anti-bacterial properties. Sericin inhibits tyrosinase activity and promotes cell proliferation that can be supportive and useful in melanoma treatment. In recent years, wound healing patches containing sericin and melatonin individually have attracted significant attention by the scientific community. In this review, we summarize the state of innovation of such patches during 2021–2023. To date, melatonin/sericin-polymer patches for application in post-operational wound healing treatment has been only sparingly investigated and it is an imperative to consider these materials as a promising approach targeting for skin tissue engineering or regenerative dermatology. Full article

Purpose: to evaluate an SRT approach in patients with at least 10 lesions at the time of BM initial diagnosis. Methods: This is a monocentric prospective cohort of patients treated by SRT, followed by a brain MRI every two months. Subsequent SRT could be delivered in cases of new BMs during follow-up. The main endpoints were local control rate (LCR), overall survival (OS), and strategy success rate (SSR). Acute and late toxicity were evaluated. Results: Seventy patients were included from October 2014 to January 2019, and the most frequent primary diagnosis was non-small-cell lung cancer (N = 36, 51.4%). A total of 1174 BMs were treated at first treatment, corresponding to a median number of 14 BMs per patient. Most of the patients (N = 51, 72.6%) received a single fraction of 20–24 Gy. At 1 year, OS was 62.3%, with a median OS of 19.2 months, and SSR was 77.8%. A cumulative number of 1537 BM were treated over time, corresponding to a median cumulative number of 16 BM per patient. At 1-year, the LCR was 97.3%, with a cumulative incidence of radio-necrosis of 2.1% per lesion. Three patients (4.3%) presented Grade 2 toxicity, and there was no Grade ≥ 3 toxicity. The number of treated BMs and the treatment volume did not influence OS or SSR (p > 0.05). Conclusions: SRT was highly efficient in controlling the BM, with minimal side effects. In this setting, an SRT treatment should be proposed even in patients with ≥10 BMs at diagnosis. Full article

Comprehensive rotorcraft simulation codes are the workhorses for designing and simulating helicopters and their rotors under steady and unsteady operating conditions. These codes are also used to predict helicopters’ limits as they approach rotor stall conditions. This paper focuses on the prediction of maximum rotor thrust when hovering (due to stall limits) and the thrust and power characteristics when the collective control angle is further increased. The aerodynamic factors that may significantly affect the results are as follows: steady vs. unsteady aerodynamics, steady vs. dynamic stall, blade tip losses, curvature flow, yaw angle, inflow model, and blade-vortex interaction. The inflow model and tip losses are found to be the most important factors. For real-world applications vortex-based inflow models are considered the best choice, as they reflect the blade circulation distribution within the inflow distribution. Because the focus is on the impact of aerodynamic modeling on rotor stall, the blade design and its flexibility are intentionally not considered. Full article

A new methodology for solving the fuzzy multiobjective optimization problems is proposed in this paper by considering the fusion of cooperative game theory and genetic algorithm. The original fuzzy multiobjective optimization problem needs to be transformed into a scalar optimization problem, which is a conventional optimization problem. Usually, the assignments of suitable coefficients to the corresponding scalar optimization problem are subjectively determined by the decision makers. However, these assignments may cause some biases by their subjectivity. Therefore, this paper proposes a mechanical procedure to avoid this subjective biases. We are going to formulate a cooperative game using the $\alpha$-level functions of the multiple fuzzy objective functions. Under this setting, the suitable coefficients can be determined mechanically by involving the core values of the cooperative game, which is formulated using the multiple fuzzy objective functions. We shall prove that the optimal solutions of the transformed scalar optimization problem are indeed the nondominated solutions of fuzzy multiobjective optimization problem. Since the core-nondominated solutions will depend on the coefficients that are determined by the core values of cooperative game, there will be a lot of core-nondominated solutions that will also depend on the corresponding coefficients. In order to obtain the best core-nondominated solution, we shall invoke the genetic algorithms by evolving the coefficients. Full article

Public–Private Partnerships (PPPs) are formed to finance and deliver large infrastructural projects that may not be entirely feasible by governments alone. This study investigates the intricate role of financial risks, subsidies, and bidding criteria in the context of PPPs in India, and their relationship to the amount and extent of investments made by private partners. Studies have claimed that the success of PPP projects is determined by the type of funding, the nature of risk undertaken by investors, and the bidding criteria used by a government to attract investors. However, there is sparse literature on these variables impacting the private investment in these projects. Thus, in an attempt to address this gap, we collated data from the World Bank for a ten-year period (i.e., 2009 to 2019) for the study variables, and used regression to analyze the hypotheses, while adopting both SPSS 24 and PROCESS Macro. This study disapproved some commonly held notions of risk relationships, such as the government using “viability gap” funding to attract private investment, and that “leverage” does not moderate the relationship between risk assumed and private investment, thereby contributing to the literature on private investment in PPPs as impacted by several factors. This study is among the first to recognize and elaborate on financial risk relationships, specifically in the context of Indian PPPs. These findings are significant for both private and public participants in terms of financial considerations in PPP projects, especially within the ambits of emerging markets. Full article

One-step carbonization was explored to prepare biochar using the residue of a traditional Chinese herbal medicine, Atropa belladonna L. (ABL), as the raw material. The resulting biochar, known as ABLB4, was evaluated for its potential as a sustainable material for norfloxacin (NOR) adsorption in water. Subsequently, a comprehensive analysis of adsorption isotherms, kinetics, and thermodynamics was conducted through batch adsorption experiments. The maximum calculated NOR adsorption capacity was 252.0 mg/g at 298 K, and the spontaneous and exothermic adsorption of NOR on ABLB4 could be better suited to a pseudo-first-order kinetic model and Langmuir model. The adsorption process observed is influenced by pore diffusion, π–π interaction, electrostatic interaction, and hydrogen bonding between ABLB4 and NOR molecules. Moreover, the utilization of response surface modeling (RSM) facilitated the optimization of the removal efficiency of NOR, yielding a maximum removal rate of 97.4% at a temperature of 304.8 K, an initial concentration of 67.1 mg/L, and a pH of 7.4. Furthermore, the biochar demonstrated favorable economic advantages, with a payback of 852.5 USD/t. More importantly, even after undergoing five cycles, ABLB4 exhibited a consistently high NOR removal rate, indicating its significant potential for application in NOR adsorption. Full article

Numerous Cymbidium species have significant commercial value globally due to their exotic ornamental flowers. Identifying Cymbidium species is challenging due to their similar shapes, which hinders their rational use and the conservation of germplasm resources. In the present study, firstly, four plastid loci (matK, rbcL, psbA-trnH, and atpF-atpH) and a nuclear locus (internal transcribed spacer, ITS) were initially examined to identify Cymbidium species. Secondly, we inferred the interspecific phylogeny of Cymbidium species using ITS sequences. All of these DNA regions, with the exception of atpF-atpH, could be readily amplified from Cymbidium, and the corresponding DNA sequences can be successfully obtained by sequencing. Our research demonstrated that ITS exhibited the highest intra- and interspecific divergences, the greatest barcoding gap, and the highest proportion of species identification. The phylogenetic analysis of Cymbidium species based on the ITS regions primarily corroborated the results obtained using traditional morphological methods. A comparative analysis of candidate DNA barcodes has shown that the ITS can be used not only for barcoding Cymbidium species but also for the phylogenetic analysis of Cymbidium. Full article

Early diagnosis of infections in young infants remains a clinical challenge. Young infants are particularly vulnerable to infection, and it is often difficult to clinically distinguish between bacterial and viral infections. Urinary tract infection (UTI) is the most common bacterial infection in young infants, and the incidence of associated bacteremia has decreased in the recent decades. Host RNA expression signatures have shown great promise for distinguishing bacterial from viral infections in young infants. This prospective study included 121 young infants admitted to four pediatric emergency care departments in the capital region of Denmark due to symptoms of infection. We collected whole blood samples and performed differential gene expression analysis. Further, we tested the classification performance of a two-gene host RNA expression signature approaching clinical implementation. Several genes were differentially expressed between young infants with UTI without bacteremia and viral infection. However, limited immunological response was detected in UTI without bacteremia compared to a more pronounced response in viral infection. The performance of the two-gene signature was limited, especially in cases of UTI without bloodstream involvement. Our results indicate a need for further investigation and consideration of UTI in young infants before implementing host RNA expression signatures in clinical practice. Full article

The use of machine learning algorithms in healthcare can amplify social injustices and health inequities. While the exacerbation of biases can occur and be compounded during problem selection, data collection, and outcome definition, this research pertains to the generalizability impediments that occur during the development and post-deployment of machine learning classification algorithms. Using the Framingham coronary heart disease data as a case study, we show how to effectively select a probability cutoff to convert a regression model for a dichotomous variable into a classifier. We then compare the sampling distribution of the predictive performance of eight machine learning classification algorithms under four stratified training/testing scenarios to test their generalizability and their potential to perpetuate biases. We show that both extreme gradient boosting and support vector machine are flawed when trained on an unbalanced dataset. We then show that the double discriminant scoring of type 1 and 2 is the most generalizable with respect to the true positive and negative rates, respectively, as it consistently outperforms the other classification algorithms, regardless of the training/testing scenario. Finally, we introduce a methodology to extract an optimal variable hierarchy for a classification algorithm and illustrate it on the overall, male and female Framingham coronary heart disease data. Full article

The purpose of this study was to conduct a cross-sectional analysis of the association between hearing aid use and cognitive decline in community-dwelling older adults with hearing impairment, stratified by cardiovascular risk level. This cross-sectional study covers 1857 hearing-impaired individuals selected among 10,674 community-dwelling older adults (≥65 years of age) in Japan. We investigate the association between hearing aid use and cognitive decline stratified by cardiovascular risk level, by assessing self-reported hearing impairment and hearing aid use, absolute cardiovascular risk, cognitive function, and potential confounding factors. The association between hearing impairment severity and increased cardiovascular risk, and the benefit of hearing aid use in preventing cognitive decline, were examined in a binomial logistic regression analysis, with the presence of cognitive decline as the objective variable. In the low cardiovascular risk group, hearing aid users had a lower odds ratio for decline in executive function than non-users (odds ratio = 0.61, 95% confidence interval: 0.39–0.98). However, there was no significant association between hearing aid use and cognitive decline in the high cardiovascular risk group (p > 0.05). Among older adults with hearing impairment, hearing aid use was associated with the maintenance of executive function in individuals of low cardiovascular risk. Full article

Real-time prediction of hull girder loads is of great significance for the safety of ship structures. Some scholars have used neural network technology to investigate hull girder load real-time prediction methods based on motion monitoring data. With the development of deep learning technology, a variety of recurrent neural networks have been proposed; however, there is still a lack of systematic comparative analysis on the prediction performance of different networks. In addition, the real motion monitoring data inevitably contains noise, and the effect of data noise has not been fully considered in previous studies. In this paper, four different recurrent neural network models are comparatively investigated, and the effect of different levels of noise on the prediction accuracy of various load components is systematically analyzed. It is found that the GRU network is suitable for predicting the torsional moment and horizontal bending moment, and the LSTM network is suitable for predicting the vertical bending moment. Although filtering has been applied to the original noise data, the prediction accuracy still decreased as the noise level increased. The prediction accuracy of the vertical bending moment and horizontal bending moment is higher than that of the torsional moment. Full article

 Remote and hybrid modes of instruction were employed as alternatives to in-person instruction as part of early mitigation efforts in response to the COVID-19 pandemic. We investigated the impact of a public school district’s instructional mode on cumulative incidence and transmission in the surrounding community by employing a generalized estimating equations approach to estimate the association with weekly COVID-19 case counts by zip code in Cuyahoga County, Ohio, from August to December 2020. Remote instruction only (RI) was employed by 7 of 20 school districts; 13 used some non-remote instruction (NRI) (2–15 weeks). Weekly incidence increased in all zip codes from August to peak in late fall before declining. The zip code cumulative incidence within NRI school districts was higher than in those offering only RI (risk ratio = 1.12, p = 0.01; risk difference = 519 per 100,000, 95% confidence interval (123–519)). The mean effect for NRI on emergent cases 2 weeks after mode exposure, controlling for Social Vulnerability Index (SVI), was significant only for high SVI zip codes 1.30, p < 0.001. NRI may be associated with increased community COVID-19 incidence, particularly in communities with high SVI. Vulnerable communities may need more resources to open schools safely.  Full article

So far, the cellular origin of glioblastoma (GBM) needs to be determined, with prevalent theories suggesting emergence from transformed endogenous stem cells. Adult neurogenesis primarily occurs in two brain regions: the subventricular zone (SVZ) and the subgranular zone (SGZ) of the hippocampal dentate gyrus. Whether the proximity of GBM to these neurogenic niches affects patient outcome remains uncertain. Previous studies often rely on subjective assessments, limiting the reliability of those results. In this study, we assessed the impact of GBM’s relationship with the cortex, SVZ and SGZ on clinical variables using fully automated segmentation methods. In 177 glioblastoma patients, we calculated optimal cutpoints of minimal distances to the SVZ and SGZ to distinguish poor from favorable survival. The impact of tumor contact with neurogenic zones on clinical parameters, such as overall survival, multifocality, MGMT promotor methylation, Ki-67 and KPS score was also examined by multivariable regression analysis, chi-square test and Mann–Whitney-U. The analysis confirmed shorter survival in tumors contacting the SVZ with an optimal cutpoint of 14 mm distance to the SVZ, separating poor from more favorable survival. In contrast, tumor contact with the SGZ did not negatively affect survival. We did not find significant correlations with multifocality or MGMT promotor methylation in tumors contacting the SVZ, as previous studies discussed. These findings suggest that the spatial relationship between GBM and neurogenic niches needs to be assessed differently. Objective measurements disprove prior assumptions, warranting further research on this topic. Full article