Real-world clinical experience of using anti-programmed death-ligand 1 (PD-L1) immune checkpoint inhibitors (ICIs) combined with chemotherapy in the first-line treatment of extensive-stage small-cell lung cancer (SCLC) patients has rarely been reported. In this study, we aimed to perform a retrospective multicenter clinical analysis of extensive-stage SCLC patients receiving first-line therapy with anti-PD-L1 ICIs combined with chemotherapy. Between November 2018 and March 2022, 72 extensive-stage SCLC patients receiving first-line atezolizumab or durvalumab in combination with chemotherapy, according to the cancer center databases of Linkou, Chiayi, and Kaohsiung Chang Gung Memorial Hospitals, were retrospectively included in the analysis. Twenty-one patients (29.2%) received atezolizumab and fifty-one (70.8%) received durvalumab. Objective response (OR) and disease control (DC) rates of 59.7% and 73.6%, respectively, were observed with first-line ICI plus chemotherapy. The median progression-free survival (PFS) was 6.63 months (95% confidence interval (CI), 5.25–8.02), and the median overall survival (OS) was 16.07 months (95% CI, 15.12–17.0) in all study patients. A high neutrophil-to-lymphocyte ratio (NLR; >4) and a high serum lactate dehydrogenase (LDH) concentration (>260 UL) were identified as independent unfavorable factors associated with shorter OS in the multivariate analysis. Regarding safety, neutropenia was the most common grade 3 treatment-related adverse event (AE), but no treatment-related deaths occurred in the study patients. First-line anti-PD-L1 ICIs combined with chemotherapy are effective and safe for male extensive-stage SCLC patients. Further therapeutic strategies may need to be developed for patients with unfavorable outcomes (e.g., baseline high NLR and serum LDH level). Full article

While crises, like pandemics, have a negative impact on mental health, hope may affect it positively. However, hope during COVID-19 has hardly been explored. In this study, we explored the hope of interviewees in a podcast on hope in Amsterdam during the COVID-19 pandemic, which sought variations in the gender, spiritual backgrounds, and places of work of the interviewees. Underpinned by hermeneutic phenomenology, we thematically analyzed the six transcribed episodes. We found that the present was sketched as closed down, while hope related to (the potential of) spaces and the future opening up. Sources of hope were the vaccine, good weather, faith and trust, and the history of Amsterdam, which was characterized by resilience. Several participants appreciated their everyday life in a new way: COVID-19 made them slow down and aware of what really mattered, which was a source of hope. Frequently mentioned sources of hope were connections with others, and especially solidarity. Also, showing solidarity was identified as a way of offering hope to others. We conclude that both in our study and in several religions, the link between hope and solidarity is common, and that hope is a spiritual topic that is worth addressing in mental health care. Full article

Background and Objectives: In lumbar spine radiography, the oblique view is frequently utilized to assess the presence of spondylolysis and the morphology of facet joints. It is crucial to instantly determine whether the oblique angle is appropriate for the evaluation and the necessity of retakes after imaging. This study investigates the feasibility of using a convolutional neural network (CNN) to estimate the angle of lumbar oblique images. Since there are no existing lumbar oblique images with known angles, we aimed to generate synthetic lumbar X-ray images at arbitrary angles from computed tomography (CT) images and to estimate the angles of these images using a trained CNN. Methods: Synthetic lumbar spine X-ray images were created from CT images of 174 individuals by rotating the lumbar spine from 0° to 60° in 5° increments. A line connecting the center of the spinal canal and the spinous process was used as the baseline to define the shooting angle of the synthetic X-ray images based on how much they were tilted from the baseline. These images were divided into five subsets and trained using ResNet50, a CNN for image classification, implementing 5-fold cross-validation. The models were trained for angle estimation regression and image classification into 13 classes at 5° increments from 0° to 60°. For model evaluation, mean squared error (MSE), root mean squared error (RMSE), and the correlation coefficient (r) were calculated for regression analysis, and the area under the curve (AUC) was calculated for classification. Results: In the regression analysis for angles from 0° to 60°, the MSE was 14.833 degree², the RMSE was 3.820 degrees, and r was 0.981. The average AUC for the 13-class classification was 0.953. Conclusion: The CNN developed in this study was able to estimate the angle of an lumbar oblique image with high accuracy, suggesting its usefulness. Full article

The problem of finding the best path trajectory in a graph is highly complex due to its combinatorial nature, making it difficult to solve. Standard search algorithms focus on selecting the best path trajectory by introducing constraints to estimate a suitable solution, but this approach may overlook potentially better alternatives. Despite the number of restrictions and variables in path planning, no solution minimizes the computational resources used to reach the goal. To address this issue, a framework is proposed to compute the best trajectory in a graph by introducing the mathematical morphology concept. The framework builds a lattice over the graph space using mathematical morphology operators. The searching algorithm creates a metric space by applying the morphological covering operator to the graph and weighing the cost of traveling across the lattice. Ultimately, the cumulative traveling criterion creates the optimal path trajectory by selecting the minima/maxima cost. A test is introduced to validate the framework’s functionality, and a sample application is presented to validate its usefulness. The application uses the structure of the avenues as a graph. It proposes a computable approach to find the most suitable paths from a given start and destination reference. The results confirm that this is a generalized graph search framework based on morphological operators that can be compared to the Dijkstra approach. Full article

This study focuses on the development of a body for an electric racecar, utilizing CAD software for the design. A simplified full-vehicle geometric model was constructed. Based on fundamental theories of computational fluid dynamics and using CAE software platforms, the shear stress transport (SST) k-ω physical model was chosen to establish a three-dimensional computational model of the racecar’s external flow field. Simulations were conducted to analyze the pressure, airflow streamlines, and velocity distribution around the body and its surrounding flow field, elucidating the impact of body shape structure on aerodynamic characteristics. Finally, a manufacturing process for the body was designed, and a prototype was produced and integrated into the complete vehicle for road testing. The results indicate that the designed electric racecar body maintained consistent airflow over its surface, meeting the basic requirements of aerodynamics. Full article

The steel industry is one the three biggest producers of carbon dioxide and it is experiencing technical challenges due to the gradual decrease in the quality of iron ore. Steel is extensively used in the construction industry for structural applications like steel components, while steel fibres are intensively used as additives to concrete in order to improve its performance. It is thus important to consider the use of recycled steel as a replacement for virgin steel in order to address the aforementioned environmental consequences. This paper applies the eco-efficiency framework to determine the economic and environmental implications of the use of recycled fibre in concrete as a replacement for virgin steel. A number of concrete mixes were considered that used virgin, recycled, and treated recycled rebar in concrete. The eco-efficiency framework, which uses a life-cycle assessment approach to calculate the environmental and economic values of concrete mixes in order to determine the portfolio positions of these concrete mixes, was used for comparison purposes and to establish the eco-efficient option(s). Whilst the recovery and recycling process is energy-intensive, the use of recycled steel fibre in reinforced concrete has been found to be eco-efficient and deliver the same level of mechanical performance compared to that obtained using virgin steel fibre. Treating steel fibre could improve its technical performance, but it was found to increase both costs and environmental impacts and was therefore identified as not being eco-efficient. Full article

Sorting unreelable inferior cocoons during the reeling process is essential for obtaining high-quality silk products. At present, silk reeling enterprises mainly rely on manual sorting, which is inefficient and labor-intensive. Automated sorting based on machine vision and sorting robots is a promising alternative. However, the accuracy and computational complexity of object detection are challenges for the practical application of automatic sorting, especially for small stains of inferior cocoons in images of densely distributed cocoons. To deal with this problem, an efficient fine-grained object detection network based on attention mechanism and multi-scale feature fusion, called AMMF-Net, is proposed for inferior silkworm cocoon recognition. In this model, fine-grained object features are key considerations to improve the detection accuracy. To efficiently extract fine-grained features of silkworm cocoon images, we designed an efficient hybrid feature extraction network (HFE-Net) that combines depth-wise separable convolution and Transformer as the backbone. It captures local and global information to extract fine-grained features of inferior silkworm cocoon images, improving the representation ability of the network. An efficient multi-scale feature fusion module (EMFF) is proposed as the neck of the object detection structure. It improves the typical down-sampling method of multi-scale feature fusion to avoid the loss of key information and achieve better performance. Our method is trained and evaluated on a dataset collected from multiple inferior cocoons. Extensive experiments validated the effectiveness and generalization performance of the HFE-Net network and the EMFF module, and the proposed AMMF-Net achieved the best detection results compared to other popular deep neural networks. Full article

Exploring the impact of individual capabilities on ecosystem services and farmers’ well-being is conducive to discovering the complex relationship between ESs and human well-being, and has clear practical value for the sustainable management and improvement of farmers’ well-being in ecologically fragile areas in China. An importance–accessibility index of ESs was constructed and the objective well-being and subjective well-being of farmers were assessed. Subsequently, the relationship among capabilities, ESs, and well-being was elucidated based on a structural equation model. The results showed that fruits, pest control, fuelwood, water conservation, and wild food were the ES types that contributed most to farmers’ well-being. There were some similarities and differences between the dimensions of objective and subjective well-being. For example, farmers with adequate leisure time reported higher leisure satisfaction and farmers with relatively adequate income levels reported the lowest income satisfaction. The direct effect of capabilities on ESs and objective well-being was significant, and the direct effect of capabilities on their subjective well-being was not significant. Their capabilities had a significant indirect impact on their objective well-being by influencing ESs and did not have a significant indirect impact on their subjective well-being by influencing ESs; their capabilities had a significant indirect impact on their subjective well-being by influencing the ESs and objective well-being. Physical health, mental health, and agricultural skills were the key types of capabilities that influenced the farmers’ access to ESs and well-being. Improving these capabilities can enable local farmers to more fully access ESs and improve their well-being. Full article

In light of the European Union’s zero-emissions policy and the growing demand for energy associated with technological advances, it is necessary to consider adopting technologies and innovative solutions that simultaneously reduce greenhouse gas emissions while increasing potential extraction from existing hydrocarbon deposits, for example. This can result in increased production from deposits with low reservoir energy values or those in which the energy value does not allow the resource to be exploited on its own. By using a hydraulic drilling nozzle that harnesses the hydraulic energy of the fluid stream for workover, the possibility of increasing the contact between the reservoir layer and the producing well increases in direct proportion to the number of small-diameter radial wells drilled with a hydraulic rotary head from a horizontal well toward the reservoir layer. The main aspect of this paper is to outline an algorithm for the design of rotary drilling heads to maximize the use of the hydraulic energy from fluid streams flowing from the face of innovative drilling tools. The presented design algorithm allows changing the mutual position between the holes in the face section and the angle of the holes with respect to the longitudinal axis of the designed hydraulic rotary nozzle, simplifying the design work. The use of the rotary head developed using this algorithm enables seamless drilling in rocks with compressive strength R_c = 50 MPa, considering the drilling progress at ROP = 4 mm/s. Full article

The ability to inhibit conflicting information is pivotal in the dynamic and high-speed context of fast-ball sports. However, the behavioral and electrophysiological characteristics underlying the cognitive inhibition processes associated with table tennis expertise remain unexplored. This study aims to bridge these research gaps by utilizing the color-word Stroop task and the spatial Stroop task alongside event-related potential (ERP) measurements to investigate domain-general and domain-specific cognitive inhibition among table tennis athletes. The study involved a total of 40 participants, including 20 table tennis athletes (11 males and 9 females; mean age 20.75 years) and 20 nonathletes (9 males and 11 females; mean age 19.80 years). The group differences in the Stroop effect on behavioral outcomes and ERP amplitudes were compared within each task, respectively. In the color-word Stroop tasks, athletes exhibited smaller incongruent-related negative potential amplitudes (N_inc; 300–400 ms; p = 0.036) and a diminished Stroop effect on late sustained potential amplitudes (LSP; 500–650 ms; p = 0.028) than nonathletes, although no significant differences were observed in behavioral outcomes (p > 0.05). Conversely, in the spatial Stroop tasks, athletes not only responded more swiftly but also exhibited reduced Stroop effects on both LSP amplitudes (350–500 ms; p = 0.004) and reaction times (p = 0.002) relative to nonathletes. These findings suggest that table tennis athletes excel in cognitive inhibition in the context of both domain-general and domain-specific tasks, particularly exhibiting enhanced performance in tasks that are closely aligned with the demands of their sport. Our results support the neural efficiency hypothesis and improve our understanding of the interactions between cognitive functions and table tennis expertise. Full article

Being a vital component of electrical power systems, transformers significantly influence the system stability and reliability of power supplies. Damage to transformers may lead to significant economic losses. The efficient identification of transformer faults holds paramount importance for the stability and security of power grids. The existing methods for identifying transformer faults include oil chromatography analysis, temperature assessment, frequency response analysis, vibration characteristic examination, and leakage magnetic field analysis. These methods suffer from limitations such as limited sensitivity, complexity in operation, and a high demand for specialized skills. In this paper, we propose a method to identify external short-circuit faults of power transformers based on fault recording data on short-circuit currents. It involves analyzing the current signals of various windings during faults, extracting appropriate features, and utilizing a classification algorithm based on a support vector machine (SVM) to determine fault types and locations. The influence of different kernel functions on the classification accuracy of SVM is discussed. The results indicate that this method can proficiently identify the type and location of external short-circuit faults in transformers, achieving an accuracy rate of 98.3%. Full article

In order to drive electric vehicle adoption and bolster grid stability, the incorporation of battery swapping stations (BSSs) into the power grid is imperative. Conversely, network reconfiguration plays a crucial role in optimizing energy exchange within the power network, ensuring its economical and safe operation. Therefore, this study proposes an optimal planning method for battery swapping stations that integrates dynamic power distribution network reconfiguration while addressing technical aspects of the grid. The proposed method aims to concurrently optimize the placement and capacity of battery swapping stations, along with power distribution network reconfiguration, to enhance grid reliability and efficiency. The optimization model accounts for various factors including power quality, technical considerations, grid limitations, and operational expenses. A multi-objective optimization framework is devised to simultaneously reduce system losses, improve voltage stability, and mitigate environmental impacts of the power distribution network incorporating DG units. Case studies are conducted to illustrate the efficacy of the proposed approach in enhancing overall grid performance while accommodating the integration of battery swapping stations. The findings underscore the significance of considering technical factors and grid reconfiguration in battery swapping station planning to achieve optimal system operation and maximize benefits for electric vehicle users and grid operators alike. Full article

Since 2016, the Ministry of Ecology and Environment and the Beijing Municipal Government have adjusted the minimum concentration limit for ambient air dustfall several times, indicating that they attach great importance to dustfall. To grasp the pollution characteristics and sources of dustfall, in this work, the filtration method was used to determine the insoluble dustfall and water-soluble dustfall in the urban area of Beijing. From our analysis, the influence of the meteorological parameters on dustfall was found, and the chemical components of dustfall were determined. The positive matrix factorization (PMF) model was also utilized to analyze the sources of dustfall. The results indicated that the average amount of dustfall in 2021–2022 was 4.4 t·(km²·30 d)⁻¹, and the proportion of insoluble dustfall deposition was 82.4%. Dustfall was positively correlated with the average wind speed and temperature and negatively correlated with the relative humidity and rain precipitation. The impact of the meteorological parameters on insoluble dustfall and water-soluble dustfall was the opposite. The average proportions of crustal material, ions, organic matter, element carbon, trace elements, and unknown components were 48%, 16%, 14%, 1.4%, 0.20%, and 20%, respectively. The proportions of the crustal material and ions were the highest in spring (57%) and summer (37%). The contribution rates of fugitive dust source, secondary inorganic source, mobile source, coal combustion source, snow melting agent source, and other sources were 42.4%, 19.3%, 8.3%, 3.0%, 2.7%, and 24.3%, respectively. This study supported dustfall pollution control by analysing the pollutant characteristics and sources of dustfall from the standpoint of total chemical components. In order to better control dustfall pollution, control measures and evaluation standards for fugitive dust pollution should be formulated. Full article

A semilinear quadratic equation of the form $A_{ij}\left(x\right)u^{ij}=B_i(x,u)u^i+F(x,u)$ defines a metric $A_{ij}$; therefore, it is possible to relate the Lie point symmetries of the equation with the symmetries of this metric. The Lie symmetry conditions break into two sets: one set containing the Lie derivative of the metric wrt the Lie symmetry generator, and the other set containing the quantities $B_i(x,u),F(x,u).$ From the first set, it follows that the generators of Lie point symmetries are elements of the conformal algebra of the metric $A_{ij}$, while the second set serves as constraint equations, which select elements from the conformal algebra of $A_{ij}.$ Therefore, it is possible to determine the Lie point symmetries using a geometric approach based on the computation of the conformal Killing vectors of the metric $A_{ij}$. In the present article, the nonlinear Poisson equation ${\Delta }_{g}u-f\left(u\right)=0$ is studied. The metric defined by this equation is 1 + 2 decomposable along the gradient Killing vector ${\partial }_t$. It is a conformally flat metric, which admits 10 conformal Killing vectors. We determine the conformal Killing vectors of this metric using a general geometric method, which computes the conformal Killing vectors of a general $1+(n-1)$ decomposable metric in a systematic way. It is found that the nonlinear Poisson equation ${\Delta }_{g}u-f\left(u\right)=0$ admits Lie point symmetries only when $f\left(u\right)=ku$, and in this case, only the Killing vectors are admitted. It is shown that the Noether point symmetries coincide with the Lie point symmetries. This approach/method can be used to study the Lie point symmetries of more complex equations and with more degrees of freedom. Full article

Carbon uptake of vegetation is controlled by phenology and photosynthetic carbon uptake capacity. However, our knowledge of the seasonal responses of vegetation productivity to phenological and physiological changes in alpine ecosystems is still weak. In this study, we quantified the spatio-temporal variations of vegetation phenology and gross primary productivity (GPP) across the source region of the Yellow River (SRYR) by analyzing MODIS-derived vegetation phenology and GPP from 2001 to 2019, and explored how vegetation phenology and maximum carbon uptake capacity (GPP_max) affected seasonal GPP over the region. Our results showed that the SRYR experienced significantly advanced trends (p < 0.05) for both start (SOS) and peak (POS) of the growing season from 2001 to 2019. Spring GPP (GPP_spr) had a significantly increasing trend (p < 0.01), and the earlier SOS had obvious positive effects on GPP_spr. Summer GPP (GPP_sum) was significantly and negatively correlated to POS (p < 0.05). In addition, GPP_max had a significant and positive correlation with GPP_sum and GPP_ann (p < 0.01), respectively. It was found that an earlier spring-summer phenology and higher photosynthetic peak enhanced the photosynthetic efficiency of vegetation in spring and summer and altered the seasonal patterns of vegetation productivity in the SRYR under warming and wetting climates. This study indicated that not only spring and autumn phenology but also summer phenology and maximum carbon uptake capacity should be regarded as crucial indicators regulating the carbon uptake process in alpine ecosystems. This research provides important information about how changes in phenology affect vegetation productivity in alpine ecosystems under global climate warming. Full article

Bovine Dewclaw Dermatitis (BDCD) is a hoof disease characterized by inflammation of the second and fifth accessory digits and the skin in this region. This pathology is poorly described in the literature; however, it has recently been observed in beef cattle in the Amazon Biome, Brazil. The objective of this study was to perform a clinical diagnosis and identify the risk factors associated with BDCD onset in cattle in the studied biome. Samples were collected from eight farms with extensive breeding systems located in Xinguara, Rondon do Pará, Curionópolis, and Ipixuna do Pará in the state of Pará, Brazil. A total of 706 Nellore and Nellore crossbred with taurine bovine of both sexes were evaluated, with males aged between 2 and 4 years and a mean weight of 650 kg, and females aged between 2 and 11 years and a mean weight of 400 kg. Distal extremities were inspected during cattle management, and in cases of dewclaw lesions, a specific examination was carried out after proper restraint. Cattle were diagnosed with BDCD on all farms analyzed. Of the 706 cattle inspected, 49 (6.94%) showed BDCD, of which 19 (38.77%) were Nellore and 30 (61.22%) were crossbred. This was the first study to determine BDCD’s occurrence in extensive farming systems in the Amazon region, also showing that pastures with large amounts of stumps and stones, the physical structure of pens, and trauma and injury incidence during animal management are the most important predisposing factors for the onset of BDCD. Full article

This investigation explores the structural and electronic properties of low-temperature-grown (InAs)₄(GaAs)₃/Be-doped InAlAs and InGaAs/Be-doped InAlAs multiple quantum wells (MQWs), utilizing migration-enhanced epitaxy (MEE) and conventional molecular beam epitaxy (MBE) growth mode. Through comprehensive characterization methods including transmission electron microscopy (TEM), Raman spectroscopy, atomic force microscopy (AFM), pump–probe transient reflectivity, and Hall effect measurements, the study reveals significant distinctions between the two types of MQWs. The (InAs)₄(GaAs)₃/Be-doped InAlAs MQWs grown via the MEE mode exhibit enhanced periodicity and interface quality over the InGaAs/Be-InAlAs MQWs grown through the conventional molecule beam epitaxy (MBE) mode, as evidenced by TEM. The AFM results indicate lower surface roughness for the (InAs)₄(GaAs)₃/Be-doped InAlAs MQWs by using the MEE mode. Raman spectroscopy reveals weaker disorder-activated modes in the (InAs)₄(GaAs)₃/Be-doped InAlAs MQWs by using the MEE mode. This originates from utilizing the (InAs)₄(GaAs)₃ short period superlattices rather than InGaAs, which suppresses the arbitrary distribution of Ga and In atoms during the InGaAs growth. Furthermore, pump–probe transient reflectivity measurements show shorter carrier lifetimes in the (InAs)₄(GaAs)₃/Be-doped InAlAs MQWs, attributed to a higher density of antisite defects. It is noteworthy that room temperature Hall measurements imply that the mobility of (InAs)₄(GaAs)₃/Be-doped InAlAs MQWs grown at a low temperature of 250 °C via the MEE mode is superior to that of InGaAs/Be-doped InAlAs MQWs grown in the conventional MBE growth mode, reaching 2230 cm²/V.s. The reason for the higher mobility of (InAs)₄(GaAs)₃/Be-doped InAlAs MQWs is that this short-period superlattice structure can effectively suppress alloy scattering caused by the arbitrary distribution of In and Ga atoms during the growth process of the InGaAs ternary alloy. These results exhibit the promise of the MEE growth approach for growing high-performance MQWs for advanced optoelectronic applications, notably for high-speed optoelectronic devices like THz photoconductive antennas. Full article

Stenocereus queretaroensis fruits are endemic to Mexico. They have an excellent advantage in cultivation because they require little water and fertilizers. These plants do not require fungicides and herbicides, drastically reducing production costs. However, the nutritional contribution and potential health benefits of S. queretaroensis fruits are unknown. The physicochemical characterization, the content of bioactive compounds, and the antioxidant capacity (AOX) of four S. queretaroensis fruits (red, purple, yellow, and white) were evaluated. All fruits had a low sugar content (7.04–8.96%) and provided 4–5% dietary fiber. The purple and red fruits presented 19.7–20.29 mg/100 g fresh weight (fw) of total betalains, respectively, while the yellow fruit presented 9.21 mg/100 g fw of total carotenoids. The total soluble phenols were 54.86–62.14 mg/100 g fw. Flavonoids, hydroxycinnamic, and hydroxybenzoic acids were also found in all fruits in ascending order. The red fruit exhibited the highest AOX, followed by the yellow, purple, and white fruits. In conclusion, these fruits are a rich source of antioxidants and nutrients, highlighting that they provide 20% of daily consumption of dietary fiber and have a low caloric content. S. queretaroensis fruits, therefore, may have a high potential functionality, especially in people with diabetes and living with obesity. Full article

Embryonic stem-like cells (ES-like cells) are promising for medical research and clinical applications. Traditional methods involve “Yamanaka” transcription (OSKM) to derive these cells from somatic cells in vitro. Recently, a novel approach has emerged, obtaining ES-like cells from spermatogonia stem cells (SSCs) in a time-related process without adding artificial additives to cell cultures, like transcription factors or small molecules such as pten or p53 inhibitors. This study aims to investigate the role of the Nanog in the conversion of SSCs to pluripotent stem cells through both in silico analysis and in vitro experiments. We used bioinformatic methods and microarray data to find significant genes connected to this derivation path, to construct PPI networks, using enrichment analysis, and to construct miRNA-lncRNA networks, as well as in vitro experiments, immunostaining, and Fluidigm qPCR analysis to connect the dots of Nanog significance. We concluded that Nanog is one of the most crucial differentially expressed genes during SSC conversion, collaborating with critical regulators such as Sox2, Dazl, Pou5f1, Dnmt3, and Cdh1. This intricate protein network positions Nanog as a pivotal factor in pathway enrichment for generating ES-like cells, including Wnt signaling, focal adhesion, and PI3K-Akt-mTOR signaling. Nanog expression is presumed to play a vital role in deriving ES-like cells from SSCs in vitro. Finding its pivotal role in this path illuminates future research and clinical applications. Full article

The most common treatment approach for children diagnosed with attention deficit hyperactivity disorder (ADHD) involves drug therapy; however, persuading parents and motivating children in the early stages of treatment is challenging. Consequently, there is a growing interest among parents of children with ADHD in non-drug therapies. Moreover, recent advancements in information and communication technology have increased the accessibility of digital treatments for ADHD and non-drug therapy content. However, some challenges persist in confirming specific and objective effects. In this retrospective study, we developed game-type digital therapy content for children aged 6–16 years and monitored improvements in ADHD symptoms using the K-WISC-V subtest processing speed index. The analysis revealed that the rate of change in the sum of converted scores on the 14th day was 0.64% lower in the experimental group compared with the control group; however, on the 28th day, the rate of change increased by 6.93%. This suggests that the supplementary use of Neuroworld DTx therapy proved effective for visual enhancement. Furthermore, improvements were observed in visual discrimination, short-term memory, and motor cooperation abilities. Consequently, game-based digital content is an effective adjunctive therapy for children dealing with ADHD. Full article

An ion-exchange procedure of synthetic zeolite ZSM-5 (Si/Al = 15) was used to prepare three cobalt ZSM-5 zeolites (CoM-ZSM5 (M = Zn and Ni)) that were examined for OERs in alkaline media. The structural, morphological, and surface properties of the prepared materials were studied by X-ray powder diffraction, Fourier transform infrared spectroscopy, scanning electron microscopy with energy dispersive spectroscopy, and low-temperature nitrogen adsorption. All three electrocatalysts showed OER activity where CoNi-ZSM5 presented the highest current density (9.5 mA cm⁻² at 2 V), the lowest Tafel slope (134 mV dec⁻¹), and the lowest resistances of the charge transfer reaction (31.5 Ω). Overpotential (η_onset) at an onset potential of 410 mV for both CoNi-ZSM5 and Co-ZSM5 and 440 mV for CoZn-ZSM5 electrodes was observed. Co-ZSM5 showed somewhat lower OER catalytic activity than CoNi-ZSM5, while CoZn-ZSM5 demonstrated the lowest OER catalytic activity. The R_ct of CoZn-ZSM5 is significantly higher than the Rct of CoNi-ZSM5, which could lead to their different OER activities. Good OER stability and low price are the main advantages of the synthesized CoM-ZSM5 samples in this study. Full article

The repair of critical-sized calvarial defects is a challenging problem for orthopedic surgery. One of the promising strategies of bone bioengineering to enhance the efficacy of large bone defect regeneration is the combined delivery of stem cells with osteoinductive factors within polymer carriers. The purpose of the research was to study the regenerative effects of heparin-conjugated fibrin (HCF) hydrogel containing bone morphogenetic protein 2 (BMP-2) and adipose-derived pericytes (ADPs) in a rat critical-sized calvarial defect model. In vitro analysis revealed that the HCF hydrogel was able to control the BMP-2 release and induce alkaline phosphatase (ALP) activity in neonatal rat osteoblasts. In addition, it was found that eluted BMP-2 significantly induced the osteogenic differentiation of ADPs. It was characterized by the increased ALP activity, osteocalcin expression and calcium deposits in ADPs. In vivo studies have shown that both HCF hydrogel with BMP-2 and HCF hydrogel with pericytes are able to significantly increase the regeneration of critical-sized calvarial defects in comparison with the control group. Nevertheless, the greatest regenerative effect was found after the co-delivery of ADPs and BMP-2 into a critical-sized calvarial defect. Thus, our findings suggest that the combined delivery of ADPs and BMP-2 in HCF hydrogel holds promise to be applied as an alternative biopolymer for the critical-sized bone defect restoration. Full article