Trends in soil organic carbon (SOC) were analyzed in the soils from the oldest Czech long-term field experiment, the Prague-Ruzyně Long-Term Fertilizer Experiment, conducted on Haplic Luvisol since 1955. The aim of the work was to compare the long-term dynamics of SOC in contrasting crop rotations and different fertilization regimes. The trial design includes two crop rotations (CR): simple CR with two-year rotation of sugar beet and spring wheat, and multi-crop rotation (MCR) with nine crops. Four fertilization treatments were chosen for SOC analysis: unfertilized control, only mineral fertilization (NPK), farmyard manure application (FYM), as well as FYM and NPK application. SOC content was significantly affected by both fertilization and crop rotation practices. In the simple CR, both the unfertilized control and the NPK treatment exhibited a consistent decline in SOC content over the study period, with percentages decreasing from an initial 1.33% in 1955 to 1.15% and 1.14%, respectively. Although the FYM and FYM + NPK treatments showed an increase in SOC content in the 1990s, a gradual decline was recorded in the last two decades. This decrease was not observed in MCR: positive C balances were recorded in all treatments within MCR, with the largest increase in SOC stock occurring when NPK was combined with FYM. In contrast, over the last decade, C balances have decreased in simple CR for all treatments except FYM. This trend coincides with changes in the local climate, particularly rising temperatures. The results indicate that diversified crop rotations and FYM fertilization are effective in mitigating the negative impacts of changing environmental conditions on SOC stocks. Full article

The lack of efficient ways to dispose of lignocellulosic agricultural residues is a serious environmental issue. Low temperatures greatly impact the ability of organisms to degrade these wastes and convert them into nutrients. Here, we report the isolation and genomic characterization of a microbial consortium capable of degrading corn straw at low temperatures. The microorganisms isolated showed fast cellulose-degrading capabilities, as confirmed by scanning electron microscopy and the weight loss in corn straw. Bacteria in the consortium behaved as three diverse and functionally distinct populations, while fungi behaved as a single population in both diversity and functions overtime. The bacterial genus Pseudomonas and the fungal genus Thermoascus had prominent roles in the microbial consortium, showing significant lignocellulose waste-degrading functions. Bacteria and fungi present in the consortium contained high relative abundance of genes for membrane components, with amino acid breakdown and carbohydrate degradation being the most important metabolic pathways for bacteria, while fungi contained more genes involved in energy use, carbohydrate degradation, lipid and fatty acid decomposition, and biosynthesis. Full article

Compared to pathogens Pseudomonas aeruginosa and P. putida, P. donghuensis HYS has stronger virulence towards Caenorhabditis elegans. However, the underlying mechanisms haven’t been fully understood. The heme synthesis system is essential for Pseudomonas virulence, and former studies of HemN have focused on the synthesis of heme, while the relationship between HemN and Pseudomonas virulence were barely pursued. In this study, we hypothesized that hemN2 deficiency affected 7-hydroxytropolone (7-HT) biosynthesis and redox levels, thereby reducing bacterial virulence. There are four hemN genes in P. donghuensis HYS, and we reported for the first time that deletion of hemN2 significantly reduced the virulence of HYS towards C. elegans, whereas the reduction in virulence by the other three genes was not significant. Interestingly, hemN2 deletion significantly reduced colonization of P. donghuensis HYS in the gut of C. elegans. Further studies showed that HemN2 was regulated by GacS and participated in the virulence of P. donghuensis HYS towards C. elegans by mediating the synthesis of the virulence factor 7-HT. In addition, HemN2 and GacS regulated the virulence of P. donghuensis HYS by affecting antioxidant capacity and nitrative stress. In short, the findings that HemN2 was regulated by the Gac system and that it was involved in bacterial virulence via regulating 7-HT synthesis and redox levels were reported for the first time. These insights may enlighten further understanding of HemN-based virulence in the genus Pseudomonas. Full article

Vessel detection is critical for ensuring maritime transportation and navigational safety, creating a pressing need for detection methodologies that are more efficient, precise, and intelligent in the maritime domain. Nonetheless, accurately detecting vessels across multiple scales remains challenging due to the diversity in vessel types and locations, similarities in ship hull shapes, and disturbances from complex environmental conditions. To address these issues, we introduce an innovative FSN-YOLO framework that utilizes enhanced YOLOv8 with multi-layer attention feature fusion. Specifically, FSN-YOLO employs the backbone structure of FasterNet, enriching feature representations through super-resolution processing with a lightweight Convolutional Neural Network (CNN), thereby achieving a balance between processing speed and model size without compromising accuracy. Furthermore, FSN-YOLO uses the Receptive-Field Attention (RFA) mechanism to adaptively fine-tune the feature responses between channels, significantly boosting the network’s capacity to capture critical information and, in turn, improve the model’s overall performance and enrich the discriminative feature representation of ships. Experimental validation on the Seaship7000 dataset showed that, compared to the baseline YOLOv8l approach, FSN-YOLO considerably increased accuracy, recall rates, and [email protected]:0.95 by absolute margins of 0.82%, 1.54%, and 1.56%, respectively, positioning it at the forefront of current state-of-the-art models. Full article

A series of lead-free Rb₂ZrCl₆:xTe⁴⁺ (x = 0%, 0.1%, 0.5%, 1.0%, 2.0%, 3.0%, 5.0%, 10.0%) perovskite materials were synthesized through a hydrothermal method in this work. The substitution of Te⁴⁺ for Zr in Rb₂ZrCl₆ was investigated to examine the effect of Te⁴⁺ doping on the spectral properties of Rb₂ZrCl₆ and its potential applications. The incorporation of Te⁴⁺ induced yellow emission of triplet self-trapped emission (STE). Different luminescence wavelengths were regulated by Te⁴⁺ concentration and excitation wavelength, and under a low concentration of Te⁴⁺ doping (x ≤ 0.1%), different types of host STE emission and Te⁴⁺ triplet state emission could be achieved through various excitation energies. These luminescent properties made it suitable for applications in information encryption. When Te⁴⁺ was doped at high concentrations (x ≥ 1%), yellow triplet state emission of Te⁴⁺ predominated, resulting in intense yellow emission, which stemmed from strong exciton binding energy and intense electron-phonon coupling. In addition, a Rb₂ZrCl₆:2%Te⁴⁺@RTV scintillating film was fabricated and a spatial resolution of 3.7 lp/mm was achieved, demonstrating the potential applications of Rb₂ZrCl₆:xTe⁴⁺ in nondestructive detection and bioimaging. Full article

The release of flammable gases during battery thermal runaway poses a risk of combustion and explosion, endangering personnel safety. The convective and diffusive properties of the gas make it challenging to accurately measure gas state, complicating the assessment of the battery pack exhaust design. In this paper, a thermal resistance network model is established, which is used to calculate the battery thermal runaway propagation. Gas accumulation after thermal runaway venting of a LiFeO₄ module is studied using ANSYS Fluent under different venting schemes. The results show that the scheme of battery inversion and simultaneous exhaust from the side and bottom of the module is optimal. The methods and results presented can guide the design of LiFeO₄ cell pack runners. Full article

Water pollution is one of the main challenges currently facing scientists around the world because of the rapid growth in industrial activities. On this basis, 2D nanolayered and nanohybrid structures, which are based on a ternary system of nickel–titanium–zinc, are considered favorable sources for designing effective nanocomposites for the photocatalytic degradation of industrial pollutants in a short period of time. These nanocomposites were designed by modifying two-dimensional nanolayers to produce a three-dimensional porous structure of multi-doped Ni/Ti-ZnO nanocomposites. Additionally, another additive was produced by constructing nanohybrids of nickel–titanium–zinc combined with a series of hydrocarbons (n-capric acid, myristic acid, stearic acid, suberic acid, and sebacic acid). Energy-dispersive X-ray spectrometry, X-ray diffraction, scanning electron microscopy, infrared spectroscopy, and thermal analyses confirmed the growth of the nanolayered and nanohybrid materials in addition to the production of nanocomposites. The positive role of the dopants (nickel and titanium) in producing an effective photocatalyst was observed through a significant narrowing of the band gap of zinc oxide to 3.05–3.10 eV. Additionally, the high photocatalytic activity of this nanocomposite enabled the complete removal of colored dye from water after 25 min of UV radiation. In conclusion, this study proposes an unconventional approach for designing new optical nanocomposites for purifying water. Additionally, it suggests a novel supporting method for designing new kinds of nanohybrids based on multi-metals and organic acids. Full article

Capturing the criticality of a water distribution network (WDN) is difficult because of its many constituent factors. In terms of operation, the arrangement of demand nodes and how they connect have a significant influence. This study aims to integrate hydraulic and topologic aspects into a single criticality measure by adapting the structural hole influence matrix concept. This method applies the nodal demand to the corresponding pipes to construct a weighted network. The matrix stores each node’s local and global connection information, and the criticality value is then assigned based on the adjacency information. The criticality value can reveal the locations in terms of nodes or pipes that are vital for maintaining a network’s level of service. By analyzing pipe-failure scenarios, the criticality value can be related to the loss of performance. Assessing the nodal criticality change behavior under an increased stress scenario can help uncover the impacted areas. The metric for district metered area (DMA) creation demonstrates its potential as a weighting to be considered. This unified criticality metric enables the evaluation of nodes and pipes in a WDN, thereby enabling resilient and sustainable development planning. Full article

Background: Progressive auditory dysfunction is common in patients with generalized neurodegenerative conditions, but clinicians currently lack the diagnostic tools to determine the location/degree of the pathology and, hence, to provide appropriate intervention. In this study, we present the white-matter microstructure measurements derived from a novel diffusion-weighted magnetic resonance imaging (dMRI) technique in a patient with axonal auditory neuropathy and consider the findings in relation to the auditory intervention outcomes. Methods: We tracked the hearing changes in an adolescent with Riboflavin Transporter Deficiency (Type 2), evaluating the sound detection/discrimination, auditory evoked potentials, and both structural- and diffusion-weighted MRI findings over a 3-year period. In addition, we explored the effect of bilateral cochlear implantation in this individual. Results: Between the ages of 15 years and 18 years, the patient showed a complete loss of functional hearing ability. The auditory brainstem response testing indicated an auditory neuropathy with evidence of normal cochlear function but disrupted auditory neural activity. While three structural MRI assessments across this period showed a clinically normal cochleovestibular anatomy, the dMRI evaluation revealed a significant loss of fiber density consistent with axonopathy. The subsequent cochlear implant function was affected with the high levels of current required to elicit auditory sensations and concomitant vestibular and facial nerve stimulation issues. Conclusions: The case study demonstrates the ability of dMRI technologies to identify the subtle white-matter microstructure changes in the auditory pathway, which may disrupt the neural function in patients with auditory axonopathy. Full article

Objective: To understand the prevalence of home-related anxiety among adolescent athletes during the novel coronavirus pandemic and to ascertain the factors influencing this anxiety. Methods: We employed cluster sampling to select 1150 adolescent athletes (aged 8–18 years) from six sports training schools in Yantai City, Shandong Province. Mental health status was assessed and recorded. Chi-square tests and multivariable logistic regression were used to analyze the factors contributing to athletes’ anxiety. Results: The survey revealed a COVID-19 infection rate of 38.23% (437 individuals) with an anxiety score of 40.98 ± 8.20 and an anxiety detection rate of 11.29% (129 individuals) during the COVID-19 epidemic. Female athletes exhibited a higher anxiety rate of 14.40% compared to 8.40% in male athletes. Multivariate analysis identified female gender as a risk factor for anxiety (OR = 1.64), while participation in aquatics emerged as a protective factor (OR = 0.24, 95% CI: 1.08–2.48). Professional training duration exceeding three years increased anxiety risk (OR = 3.05, 95% CI: 1.67–5.58), as did not seeking help during difficulties (OR = 2.59, 95% CI: 1.33–5.01). Interestingly, parental care was linked to increased anxiety risk (OR = 2.44, 95% CI 1.34–4.44), while care from friends was protective (OR = 0.60, 95% CI: 0.36–1.01), which was possibly due to the pressure associated with parental expectations. Conclusions: Adolescent athletes, particularly females and those with extended training durations, exhibit a heightened susceptibility to anxiety. This study also highlights that athletes who proactively seek assistance during challenging situations tend to experience lower anxiety levels. Additionally, a lack of COVID-19 infection and the involvement of concerned parents contribute to reduced anxiety among these young athletes. Full article

Spatial ability (SA) is the mental ability to create, maintain, and manipulate abstract visual representations. Studies have shown that SA is a strong predictor of success in the fields of science, technology, engineering, and mathematics (STEM). More recently, attention has extended to the field of architecture, a discipline where spatial thinking skills are fundamental, yet students in this field have not been extensively examined in terms of their spatial abilities. Therefore, SA skills are essential for students in engineering and architecture during their initial academic phases. This research was conducted within an interdisciplinary academic college and describes in detail a new integrated and hybrid training program that is part of a recent mixed-methods study. This program was built to effectively enhance the SA of first-year undergraduate students in a cost-effective manner, using a multi-method teaching strategy. The training program spanned more than 20 h across four sessions. This article focuses on the training methodology, encompassing four key phases, and serves as a complementary article to the one that was just published separately, describing the effectiveness of this intervention program as measured using SA standard tests. Notably, in certain scenarios, these phases were combined rather than being standalone independent modules. The traditional teaching method (TTM) lays the foundation for SA knowledge via lectures and collaborative interactions. Subsequently, computer-based learning (CBL), using tools such as SketchUp and GeoGebra, facilitates in-depth virtual geometric exploration. Augmented reality (AR) training offers an immersive learning experience, allowing students to interact with 3D objects in real-world environments. Finally, the building real model (BRM) phase transforms 2D designs into tangible 3D structures. This study highlights the comprehensive training approach, emphasizing the robust learning environment facilitated by integrating these phases as part of the full mixed-methods research. The suggested integrated training program was qualitatively explored through post-intervention evaluations to understand participants’ experiences and perceptions. Full article

Background: The purpose of the study is to compare the visual outcomes and complications of sutured scleral fixation (SSF), a traditional and conservative surgical approach, and the newer and faster Yamane technique for secondary intraocular lens placement. Methods: A literature search was performed on PubMed, Embase, and Scopus on studies published between 1 July 2017 to 29 September 2023. Outcomes analyzed included the final best corrected visual acuity (BCVA) between 3 and 12 months to assess the effectiveness of the procedure, post-operative month (POM) 1 BCVA to assess the speed of visual recovery, endothelial cell count (ECC), absolute refractive error, surgical duration, and complication rates. Additional subgroup analyses were performed based on surgeon experience with the technique. Single-surgeon studies had an average of 26 procedures performed, whereas multiple-surgeon studies averaged only 9 procedures performed; these were then used to delineate surgeon experience. A sample-size weighted mean difference (MD) meta-analysis was performed across all variables using RevMan 5.4.1; p < 0.05 was considered statistically significant. Results: Thirteen studies with 737 eyes were included: 406 eyes were included in the SSF group, and 331 eyes were included in the Yamane group. There was no significant difference in the final BCVA between groups in both the single-surgeon versus multiple-surgeon studies (MD = −0.01, 95% CI: [−0.06, 0.04], p = 0.73). In the single-surgeon studies, the BCVA at POM1 was significantly improved in the Yamane group compared to SSF (MD = −0.10, 95% CI: [−0.16, −0.04], p = 0.002). In the multiple-surgeon studies, there was no significant difference in BCVA at POM1 (MD = −0.06, 95% CI: [−0.16, 0.04], p = 0.23). The Yamane group had a shorter surgical duration than SSF in both single-surgeon and multiple-surgeon studies (MD = −24.68, 95% CI: [−35.90, −13.46], p < 0.0001). The ECC, refractive error, and complication rates did not significantly differ amongst all groups. Conclusions: The Yamane technique demonstrated similar long-term visual outcomes and complication rates to the traditional SSF. Visual recovery was significantly faster in the Yamane group in the single-surgeon studies. The operative times were shorter across all Yamane groups. Based on these findings, it is advisable to consider the Yamane technique as a viable, and perhaps preferable, option for patients requiring secondary IOL placement, alongside traditional SSF methods. Full article

As a non-destructive, fast, and cost-effective technique, near-infrared (NIR) spectroscopy has been widely used to determine the content of bioactive components in tea. However, due to the similar chemical structures of various catechins in black tea, the NIR spectra of black tea severely overlap in certain bands, causing nonlinear relationships and reducing analytical accuracy. In addition, the number of NIR spectral wavelengths is much larger than that of the modeled samples, and the small-sample learning problem is rather typical. These issues make the use of NIRS to simultaneously determine black tea catechins challenging. To address the above problems, this study innovatively proposed a wavelength selection algorithm based on feature interval combination sensitivity segmentation (FIC-SS). This algorithm extracts wavelengths at both coarse-grained and fine-grained levels, achieving higher accuracy and stability in feature wavelength extraction. On this basis, the study built four simultaneous prediction models for catechins based on extreme learning machines (ELMs), utilizing their powerful nonlinear learning ability and simple model structure to achieve simultaneous and accurate prediction of catechins. The experimental results showed that for the full spectrum, the ELM model has better prediction performance than the partial least squares model for epicatechin (EC), epicatechin gallate (ECG), epigallocatechin (EGC), and epigallocatechin gallate (EGCG). For the feature wavelengths, our proposed FIC-SS-ELM model enjoys higher prediction performance than ELM models based on other wavelength selection algorithms; it can simultaneously and accurately predict the content of EC (${\mathrm{R}}_{\mathrm{p}}^2$ = 0.91, RMSEP = 0.019), ECG (${\mathrm{R}}_{\mathrm{p}}^2$ = 0.96, RMSEP = 0.11), EGC (${\mathrm{R}}_{\mathrm{p}}^2$ = 0.97, RMSEP = 0.15), and EGCG (${\mathrm{R}}_{\mathrm{p}}^2$ = 0.97, RMSEP = 0.35) in black tea. The results of this study provide a new method for the quantitative determination of the bioactive components of black tea. Full article

This study presents the results of the development and testing of a methodology for selecting parameters of the characteristics of fast valving in a steam turbine for emergency power system management to maintain dynamic stability based on machine learning algorithms. Modern power systems have reduced inertia and increased stochasticity due to the active integration of renewable energy sources. As a result, there is an increased likelihood of incorrect operation in traditional emergency automation devices, developed on the principles of deterministic analysis of transient processes. To date, it is possible to increase the adaptability and accuracy of emergency power system management through the application of machine learning algorithms. In this work, fast valving in a steam turbine was chosen as the considered device of emergency automation. To form the data sample, the IEEE39 mathematical model was used, for which benchmark laws of change in the position of the cutoff valve during the fast valving of a steam turbine were selected. The considered machine learning algorithms for classifying the law of change in the position of the steam turbine’s cutoff valve, k-nearest neighbors, support vector machine, decision tree, random forest, and extreme gradient boosting were used. The results show that the highest accuracy corresponds to extreme gradient boosting. For the selected eXtreme Gradient Boosting algorithm, the classification accuracy on the training set was 98.17%, and on the test set it was 97.14%. The work also proposes a methodology for forming synthetic data for the use of machine learning algorithms for emergency management of power systems and suggests directions for further research. Full article

In this study, a solid masterbatch of starch–iodine complex with 6.7 wt.% iodine was prepared in pellet form using a ZSK-30 twin-screw extruder. Thermogravimetric (TGA) and isothermal TGA analysis of the pellets revealed that there was no significant loss of iodine due to sublimation during reactive extrusion. These solid pellets demonstrated antifungal properties when applied to strawberries via dip coating in an aqueous solution, extending their shelf life from two days to eight days, thereby reducing fungal growth and visual decay. Furthermore, the solid pellets displayed antibacterial activity against E. coli, as evidenced by the clear zone of inhibition observed in the Kirby–Bauer test. To enhance practical application, these pellets were further blended with PLA-PBAT film formulations at 10 and 18% by wt. to make blown films with effective iodine loadings of 0.7 and 1.3% by wt. These films showed superior antibacterial activity against E. coli compared with PLA control films and the commercial silver antimicrobial-containing films during direct inoculation tests as per ISO 22196. Tensile strength and elongation at break in machine direction (MD) for the starch–iodine-containing blown films were comparable to the control films in MD, but tensile strength was reduced to 37–40% in the transverse direction (TD). This was due to a non-uniform dispersion of the starch–iodine complex in the films, as confirmed by the visual and SEM analyses. Thus, this study illustrates the practical utility of the solid starch–iodine complex as a safe and efficient means of introducing iodine into an environment, mitigating the typical hazards associated with handling solid iodine. Full article

The emergence of the COVID-19 pandemic, followed by policy measures to combat the virus, evoked public protest movements world-wide. These movements were formed not only in the virtual world but also through local protest gatherings. In contrast to previous research that studied movements in the virtual world through digital network analysis, this study recognizes the importance of the spatial dimension of social movements through local interaction. We therefore introduce a large-scale spatial–social network analysis of a georeferenced Twitter user network to understand the regional connections and transnational influences of the local movement through the virtual network. Our findings indicate that the virtual social network is distinctly structured along geographic and linguistic boundaries. Furthermore, our analysis of transnational influences reveals that the connections within Austria itself hold greater significance compared to their impact on external regions. Full article

Background: Musicotherapy (MT) is a non-pharmacological, art-based intervention that employs music experiences within a therapeutic alliance to attend to clients’ physical, emotional, cognitive, and social requirements. This is the first study aiming at investigating the impact of MT on the psychological facets of children suffering from cancer. Methods: The study, combining the AQR and m-YPAS assessment tools, evaluated behavioral, sound–musical, and interactive parameters in pediatric oncology patients undergoing MT sessions during hospitalization. Fifty patients admitted to the Paediatric Oncology and Haematology Unit at Policlinico S. Orsola Hospital in Bologna, Italy, were enrolled, irrespective of their treatment regimen. Data collection occurred on the first day of the MT session between 3 p.m. and 5 p.m., with observations conducted by independent observers. In addition to traditional statistical analysis, network analysis was used to explore the combined interactions of all parameters, effectively discerning the distinctive roles played by each one during therapy sessions and their influence on all others. Results: Network analysis highlighted distinct patterns of interactions among parameters during the various sessions, emphasizing the role of positive emotions and a calm setting, the child’s ability to take the initiative in sessions, their sense of agency, and the parent’s role in guiding them. Significant differences were recorded at each time point between all variables considered. Conclusions: The results of this innovative study may pave the way for future multicenter studies aimed at further exploring the role of MT in children undergoing both curative and palliative treatments for cancer. Full article

Recently, a compound derived from recent scientific advances named 34 has emerged as the focus of this research, the aim of which is to explore its potential impact on solid tumor cell lines. Using a combination of bioinformatics and biological assays, this study conducted an in-depth investigation of the effects of 34. The results of this study have substantial implications for cancer research and treatment. 34 has shown remarkable efficacy in inhibiting the growth of several cancer cell lines, including those representing prostate carcinoma (PC3) and cervical carcinoma (HeLa). The high sensitivity of these cells, indicated by low IC₅₀ values, underscores its potential as a promising chemotherapeutic agent. In addition, 34 has revealed the ability to induce cell cycle arrest, particularly in the G2/M phase, a phenomenon with critical implications for tumor initiation and growth. By interfering with DNA replication in cancer cells, 34 has shown the capacity to trigger cell death, offering a new avenue for cancer treatment. In addition, computational analyses have identified key genes affected by 34 treatment, suggesting potential therapeutic targets. These genes are involved in critical biological processes, including cell cycle regulation, DNA replication and microtubule dynamics, all of which are central to cancer development and progression. In conclusion, this study highlights the different mechanisms of 34 that inhibit cancer cell growth and alter the cell cycle. These promising results suggest the potential for more effective and less toxic anticancer therapies. Further in vivo validation and exploration of combination therapies are critical to improve cancer treatment outcomes. Full article

Perfluorooctanoic acid (PFOA) contamination in water sources poses significant environmental and health concerns. The kinetic, equilibrium, and thermodynamic features of PFOA adsorption in the existence of natural organic matter (NOM) were thoroughly investigated in this work using granular activated carbon (GAC) modified by dielectric barrier discharge (DBD) plasma. The impacts of DBD plasma parameters on the adsorption process were systematically examined. The results demonstrated that GAC modified by DBD plasma exhibited enhanced adsorption performance for PFOA, even in the presence of NOM. The optimal condition for plasma-treated GAC was achieved with 20 min of plasma treatment time and 100 W of plasma power, resulting in 92% PFOA removal efficiency in deionized water (DIW) and 97% removal efficiency in Chao Phraya River water (CPRW). A kinetic investigation using the pseudo-first-order model (PFOM), the pseudo-second-order model (PSOM), and the Elovich model (EM) indicated that plasma treatment time and NOM presence influenced the adsorption capacity and rate constants of PFOA with the PSOM having emerged as the most fitting kinetic model. The Langmuir isotherm model indicates monolayer adsorption of PFOA on plasma-treated GAC, with higher maximum adsorption capacity while NOM is present. The Redlich–Peterson and Sips isotherm models indicated varying adsorption capacity and heterogeneity in the adsorption system. The Sips model was determined as the most fitting isotherm model. Furthermore, the favorable and spontaneous character of PFOA adsorption onto plasma-treated GAC was validated by thermodynamic analysis, with endothermic heat absorption during the process. Overall, this comprehensive investigation provides valuable insights into the adsorption characteristics of PFOA in the existence of NOM using GAC modified by DBD plasma. Full article

Soil water and soil temperature are important ecological factors and driving forces for ecosystem restoration and sustainable development, possessing great significance for climate modeling and prediction. The Hengduan Mountains in southeastern Tibet, China, are located in a climate-change-sensitive area, and the study of soil hydrothermal dynamics in this area is of great significance for local and global climatic change and water resource utilization. This study, based on the soil hydrothermal and meteorological data of the Hengduan Mountain area in Southeast Tibet, analyzes the dynamic change patterns of soil hydrothermal and meteorological factors and explores their influencing relationships. It was found that the dynamic change in soil water content affected by precipitation was “bimodal” type. Among the meteorological factors, soil water content has the strongest correlation with relative humidity. The intra-annual variation curve of soil temperature is similar to that of the atmospheric temperature, showing a “unimodal” type, and has the highest correlation with atmospheric temperature. Specifically, it takes 70 mm and 170 mm of precipitation to change the soil water content and soil temperature at the 150 cm depth. For every 20 °C change in atmospheric temperature, soil temperature above 150 cm changes by an average of 7.2 °C. Full article

The current research aims to develop thermosensitive polymeric micelles loaded with risperidone for nasal administration, emphasizing the added benefits of their thermosensitive behavior under nasal conditions. An initial risk assessment facilitated the advanced development process, confirming that the key indicators of thermosensitivity were suitable for nasal application. The polymeric micelles exhibited an average size of 118.4 ± 3.1 nm at ambient temperature and a size of 20.47 ± 1.2 nm at 36.5 °C, in both cases in monodisperse distribution. Factors such as pH and viscosity did not significantly impact these parameters, demonstrating appropriate nasal applicability. The model formulations showed a rapid, burst-like drug release profile in vitro, accompanied by a quick and high permeation rate at nasal conditions. Overall, the Quality by Design-based risk assessment process led to the development of an advanced drug delivery system capable of administering risperidone through the nasal cavity. Full article

Saliva has shown considerable promise as a diagnostic medium for point-of-care (POC) and over-the-counter (OTC) diagnostic devices due to the non-invasive nature of its collection. However, a significant limitation of saliva-based detection is undesirable interference in a sensor’s readout caused by interfering components in saliva. In this study, we develop standardized sample treatment procedures to eliminate bubbles and interfering molecules while preserving the sample’s target molecules such as spike (S) protein and glucose. We then test the compatibility of the pretreatment system with our previously designed SARS-CoV-2 and glucose diagnostic biosensing systems for detecting S protein and glucose in subject saliva. Ultimately, the effectiveness of each filter in enhancing biomarker sensitivity is assessed. The results show that a 20 mg nylon wool (NW) filter shows an 80% change in viscosity reduction with only a 6% reduction in protein content, making it an appropriate filter for the salivary S protein diagnostic system. Meanwhile, a 30 mg cotton wool (CW) filter is identified as the optimal choice for salivary glucose detection, achieving a 90% change in viscosity reduction and a 60.7% reduction in protein content with a minimal 4.3% reduction in glucose content. The NW pretreatment filtration significantly improves the limit of detection (LOD) for salivary S protein detection by five times (from 0.5 nM to 0.1 nM) and it reduces the relative standard deviation (RSD) two times compared to unfiltered saliva. Conversely, the CW filter used for salivary glucose detection demonstrated improved linearity with an R² of 0.99 and a sensitivity of 36.6 μA/mM·cm², over twice as high as unfiltered saliva. This unique filtration process can be extended to any POC diagnostic system and optimized for any biomarker detection, making electrochemical POC diagnostics more viable in the current market. Full article