Search Results (13,597)

Pile foundations are critical structural elements, and their integrity is essential for ensuring the stability and safety of construction projects. Low-strain pile integrity testing (LSPIT) is widely used for defect detection; however, conventional manual interpretation of reflectograms is both time-consuming and susceptible to human error. This study presents a deep learning-driven approach utilizing transfer learning with convolutional neural networks (CNNs) to automate pile defect detection. A dataset of 328 reflectograms collected from real construction sites, including 246 intact and 82 defective samples, was used to train and evaluate the model. To address class imbalance, oversampling techniques were applied. Several state-of-the-art pretrained CNN architectures were compared, with ConvNeXtLarge achieving the highest accuracy of 98.2%. The accuracy reported was achieved on a dedicated test set using real reflectogram data from actual construction sites, distinguishing this study from prior work relying primarily on synthetic data. The proposed novelty includes adapting pre-trained CNN architectures specifically for real-world pile integrity testing, addressing practical challenges such as data imbalance and limited dataset size through targeted oversampling techniques. The proposed approach demonstrates significant improvements in accuracy and efficiency compared to manual interpretation methods, making it a promising solution for practical applications in the construction industry. The proposed method demonstrates potential for generalization across varying pile lengths and geological conditions, though further validation with broader datasets is recommended. Full article

(1) Background: This study investigates whether older adult individuals support childcare policies not only out of altruism, but also due to extended self-interest arising from intergenerational co-residence. It challenges the conventional view that welfare attitudes are shaped solely by one’s own life-cycle needs. (2) Methods: Using the 2013 and 2016 waves of the Korean Welfare Panel Study waves of the Korean Welfare Panel Study, a difference-in-differences (DiD) approach compares attitudes toward government childcare spending between older adults living with children (Co-residing Older Adults) and those who do not (Non-co-residing Older Adults), before and after universal childcare policies were introduced in 2013. (3) Results: The Co-residing Older Adults consistently expressed stronger support for family policies than their counterparts. However, this support did not significantly increase after the 2013 reform, indicating that extended self-interest may not be sensitive to short-term policy changes. (4) Conclusions: Extended self-interest appears to be a stable orientation shaped by family context rather than a flexible, policy-reactive stance. These findings highlight the role of intergenerational household ties in shaping welfare attitudes and offer implications for fostering generational solidarity in aging societies. Full article

Background: Psoriasis is a chronic inflammatory skin disease linked to systemic comorbidities, including metabolic, cardiovascular, and autoimmune disorders. Thyroid dysfunction, particularly hypothyroidism, has been observed in patients with moderate-to-severe psoriasis, suggesting possible shared inflammatory pathways. Objectives: This study aims to explore the relationship between psoriasis and thyroid dysfunction in adults with moderate-to-severe psoriasis undergoing biologic therapy to determine whether psoriasis predisposes individuals to thyroid disorders and to identify demographic or clinical factors influencing this association. Materials and Methods: A cross-sectional study included adult patients with moderate-to-severe psoriasis receiving biologic therapy, recruited from the Psoriasis Unit at the Dermatology Department of Hospital Universitario San Cecilio in Granada, Spain, from 2017 to 2023. Patients with mild psoriasis or those treated with conventional systemic therapies were excluded. The data collected included demographics and clinical characteristics, such as age, sex, BMI (body mass index), and psoriasis severity (psoriasis severity was evaluated using the Psoriasis Area Severity Index (PASI), body surface area (BSA) involvement, Investigator’s Global Assessment (IGA), pruritus severity using the Numerical Rating Scale (NRS), and impact on quality of life through the Dermatology Life Quality Index (DLQI)). Thyroid dysfunction, including hypothyroidism and subclinical hypothyroidism, was assessed based on records from the Endocrinology Department. Results: Thyroid dysfunction was found in 4.2% of patients, all classified as hypothyroidism, primarily subclinical. The affected patients were generally older, with a mean age of 57.4 years. No significant differences in psoriasis severity (PASI, BSA) or treatment response were observed between patients with and without thyroid dysfunction. Conclusion: Our findings suggest hypothyroidism is the main thyroid dysfunction in psoriatic patients, independent of psoriasis severity. The lack of impact on psoriasis severity suggests hypothyroidism may be an independent comorbidity, warranting further research into shared inflammatory mechanisms. Full article

Background/Objectives: Inflammatory bowel disease (IBD) is characterized by chronic relapsing and remitting inflammation of the gastrointestinal tract. Fecal microbiota transplantation (FMT) has emerged as an FDA-approved treatment for recurrent Clostridioides difficile infections (CDIs), with promising potential in patients with IBD. This manuscript aimed to provide a comprehensive and updated review of the available literature on fecal microbiota transplantation, its clinical use in IBD in general, as well as in patients with IBD and CDI. Methods: An extensive literature search was performed from October 2024 to March 2025. All publications available within PubMed, Medline, Embase, Google Scholar, and Cochrane databases were reviewed. All original articles, case reports, review articles, systematic reviews, and meta-analyses were included. Qualitative and quantitative data were both extracted. Discussion: Intestinal microbiota is an integral part of the human body, and dysbiosis (an imbalance in the gut’s microbial community) has been linked with several pathologies. Dysbiosis in IBD is marked by reduced beneficial bacteria and increased pro-inflammatory pathogens, contributing to mucosal damage and immune dysregulation. FMT has emerged as a solution to dysbiosis, with the first case recorded in 1917. FMT has been successful in treating patients with CDI. The diagnostic value of the gut microbiome is currently being explored as a possible therapeutic approach to IBD. Several studies have assessed FMT in patients with IBD and CDI with promising results in both ulcerative colitis (UC) and Crohn’s disease (CD) but varying efficacy based on administration routes, donor selection, and processing methods. In the context of recurrent CDI in patients with IBD, FMT demonstrates a high cure rate and potential benefit in concurrently improving IBD activity. However, risks such as IBD flare-ups post-FMT remain a concern. Conclusions: FMT holds promising potential in the management of CDI in patients with IBD. By restoring microbial diversity and correcting dysbiosis, FMT offers a novel, microbiota-targeted alternative to conventional therapies. While data support its efficacy in improving disease remission, variability in outcomes underscores the need for standardized protocols and additional large-scale, controlled studies. Continued research efforts into donor selection, treatment regimens, and long-term safety will be critical to optimizing FMT’s role in IBD and CDI care as well as improving patient outcomes. Full article

Industrial effluents pose a significant concern because they contain a variety of metals and metalloids that have detrimental effects on the environment. Conventional techniques are widely used in effluent treatment plants (ETPs) to remove metallic pollutants; however, they are less effective, are costly, and generate secondary toxic waste. Mycosorbent would be a sustainable and economical alternative to conventional techniques, as it offers numerous advantages. In this study, we shed light on the development of mycosorbent, which could be potentially applicable in the treatment of industrial effluent. In a competitive (i.e., multimetal system) optimisation study, mycosorbent AD2 exhibited a maximum biosorption capacity of 3.7 to 6.20 mg/g at pH 6.0, with an initial metal ion concentration of 25 mg/L, a contact time of 2 h, at 50 ± 2 °C, and a pH_PZC of 5.3. The metal-removal capacity increased up to 1.23-fold after optimisation. The thermodynamic parameters confirmed that the AD2 mycosorbent facilitated an endothermic, feasible, and spontaneous biosorption process. The FT-IR and SEM characterisation analysis confirmed the adsorption of metals on the surface of the mycosorbent from the aqueous system. This study demonstrated that mycosorbent could be an effective tool for combating metallic pollutants in various industrial effluents. Full article

Diverging from conventional dephosphorization approaches, this study employs a novel pre-reduction and smelting separation (PR-SS) to efficiently co-recover iron and phosphorus from high-phosphorus oolitic iron ore, directly yielding Fe–P alloy, and the Fe–P alloy shows potential as feedstock for high-phosphorus weathering steel or wear-resistant cast iron, indicating promising application prospects. Using oolitic magnetite concentrate (52.06% Fe, 0.37% P) as feedstock, optimized conditions including pre-reduction at 1050 °C for 2 h with C/Fe mass ratio of 2, followed by smelting separation at 1550 °C for 20 min with 5% coke, produced a metallic phase containing 99.24% Fe and 0.73% P. Iron and phosphorus recoveries reached 99.73% and 99.15%, respectively. EPMA microanalysis confirmed spatial correlation between iron and phosphorus in the metallic phase, with undetectable phosphorus signals in vitreous slag. This evidence suggests preferential phosphorus enrichment through interfacial mass transfer along the pathway of the slag phase to the metal interface and finally the iron matrix, forming homogeneous Fe–P solid solutions. The phosphorus migration mechanism involves sequential stages: apatite lattice decomposition liberates reactive P₂O₅ under SiO₂/Al₂O₃ influence; slag–iron interfacial co-reduction generates Fe₃P intermediates; Fe₃P incorporation into the iron matrix establishes stable solid solutions. Full article

Thyroid hormones (thyroxine, T₄, and triiodothyronine, T₃) are indispensable for sustaining vertebrate life, and their deficiency gives rise to a wide range of symptoms characteristic of hypothyroidism, affecting 5–10% of the world’s population. The precursor for thyroid hormone synthesis is thyroglobulin (Tg), a large iodoglycoprotein consisting of upstream regions I-II-III (responsible for synthesis of most T₄) and the C-terminal CholinEsterase-Like (ChEL) domain (responsible for synthesis of most T₃, which can also be generated extrathyroidally by T₄ deiodination). Using CRISPR/Cas9-mediated mutagenesis, we engineered a knock-in of secretory ChEL into the endogenous TG locus. Secretory ChEL acquires Golgi-type glycans and is properly delivered to the thyroid follicle lumen, where T₃ is first formed. Homozygous knock-in mice are capable of thyroidal T₃ synthesis but largely incompetent for T₄ synthesis such that T₄-to-T₃ conversion contributes little. Instead, T₃ production is regulated thyroidally by thyrotropin (TSH). Compared to cog/cog mice with conventional hypothyroidism (low serum T₄ and T₃), the body size of ChEL-knock-in mice is larger; although, these animals with profound T₄ deficiency did exhibit a marked elevation of serum TSH and a large goiter, despite normal circulating T₃ levels. ChEL knock-in mice exhibited a normal expression of hepatic markers of thyroid hormone action but impaired locomotor activities and increased anxiety-like behavior, highlighting tissue-specific differences in T₃ versus T₄ action, reflecting key considerations in patients receiving thyroid hormone replacement therapy. Full article

Infectious diseases poses a growing public health challenge. The COVID-19 pandemic has further emphasized the urgent need for rapid, accessible diagnostics. This study presents the development of an integrated, flexible point-of-care (POC) diagnostic system for the rapid detection of Corynebacterium diphtheriae, the pathogen responsible for diphtheria. The system comprises a microfluidic polymerase chain reaction (micro-PCR) device and an electrochemical DNA biosensor, both fabricated on flexible substrates. The micro-PCR platform offers rapid DNA amplification overcoming the time limitations of conventional thermocyclers. The biosensor utilizes specific molecular recognition and an electrochemical transducer to detect the amplified DNA fragment, providing a clear and direct indication of the pathogen’s presence. The combined system demonstrates the effective amplification and detection of a gene fragment from a toxic strain of C. diphtheriae, chosen due to its increasing incidence. The design leverages lab-on-a-chip (LOC) and microfluidic technologies to minimize reagent use, reduce cost, and support portability. Key challenges in microsystem design—such as flow control, material selection, and reagent compatibility—were addressed through optimized fabrication techniques and system integration. This work highlights the feasibility of using flexible, integrated microfluidic and biosensor platforms for the rapid, on-site detection of infectious agents. The modular and scalable nature of the system suggests potential for adaptation to a wide range of pathogens, supporting broader applications in global health diagnostics. The approach provides a promising foundation for next-generation POC diagnostic tools. Full article

This paper proposes an AI-driven automated test generation framework for vehicle control units (VCUs), integrating natural language processing (NLP) and dynamic variable binding. To address the critical limitation of traditional AI-generated test cases lacking executable variables, the framework establishes a closed-loop transformation from requirements to executable code through a five-layer architecture: (1) structured parsing of PDF requirements using domain-adaptive prompt engineering; (2) construction of a multidimensional variable knowledge graph; (3) semantic atomic decomposition of requirements and logic expression generation; (4) dynamic visualization of cause–effect graphs; (5) path-sensitization-driven optimization of test sequences. Validated on VCU software from a leading OEM, the method achieves 97.3% variable matching accuracy and 100% test case executability, reducing invalid cases by 63% compared to conventional NLP approaches. This framework provides an explainable and traceable automated solution for intelligent vehicle software validation, significantly enhancing efficiency and reliability in automotive testing. Full article

Poly(ε-caprolactone)-b-polysarcosine (PCL-b-PSar) block copolymers (BCPs) emerge as a promising alternative to conventional poly(ε-caprolactone)-b-poly(ethylene oxide) BCPs for biomedical applications, leveraging superior biocompatibility and biodegradability. In this study, we synthesized two series of PCL-b-PSar BCPs with controlled polymerization degrees (DP of PCL: 45/67; DP of PSar: 28–99) and low polydispersity indexes (Đ ≤ 1.1) and systematically investigated their crystallization-driven self-assembly (CDSA) in alcohol solvents (ethanol, n-butanol, and n-hexanol). It was found that the limited solubility of PSar in alcohols resulted in competition between micellization and crystallization during self-assembly of PCL-b-PSar, and thus coexistence of lamellae and spherical micelles. To overcome this morphological heterogeneity, we developed a modified self-seeding method by employing a two-step crystallization strategy (i.e., T_c1 = 33 °C and T_c2 = 8 °C), achieving conversion of micelles into crystals and yielding uniform self-assembled structures. PCL-b-PSar BCPs with short PSar blocks tended to form well-defined two-dimensional lamellar crystals, while those with long PSar blocks induced formation of hierarchical structures in the PCL₄₅ series and polymer aggregation on crystal surfaces in the PCL₆₇ series. Solvent quality notably influenced the self-assembly pathways of PCL₄₅-b-PSar₂₈. Lamellar crystals were formed in ethanol and n-butanol, but micrometer-scale dendritic aggregates were generated in n-hexanol, primarily due to a significant Hansen solubility parameter mismatch. This study elucidated the CDSA mechanism of PCL-b-PSar in alcohols, enabling precise structural control for biomedical applications. Full article

This study proposes the Weight-Incorporating A* (WIA*) algorithm for mobile robot path planning. The WIA* algorithm integrates three weight factors into the Conventional A* cost function: an Obstacle Collision (OC) weight factor for collision avoidance, a Path Distance (PD) weight factor for path length optimization, and a Driving Suitability (DS) weight factor for environmental considerations. Experimental validation was conducted using nine 2D grid maps and a 3D virtual environment. The results show that WIA* achieved zero obstacle collisions compared to an average of 9.11 collisions with Conventional A*. Although WIA* increased path length by 12.69%, it reduced driving suitability cost by 93.88%, achieving zero cost in six out of nine test environments. The algorithm demonstrates effective collision-free path generation while incorporating environmental factors for practical mobile robot navigation. Full article

Hydrogen is widely recognized as a key enabler of the clean energy transition, but the lack of safe, efficient, and scalable storage technologies continues to hinder its broad deployment. Conventional hydrogen storage approaches, such as compressed hydrogen storage, cryo-compressed hydrogen storage, and liquid hydrogen storage, face limitations, including high energy consumption, elevated cost, weight, and safety concerns. In contrast, solid-state hydrogen storage using carbon-based adsorbents has gained growing attention due to their chemical tunability, low cost, and potential for modular integration into energy systems. This review provides a comprehensive evaluation of hydrogen storage using carbon-based materials, covering fundamental adsorption mechanisms, classical materials, emerging architectures, and recent advances in computationally AI-guided material design. We first discuss the physicochemical principles driving hydrogen physisorption, chemisorption, Kubas interaction, and spillover effects on carbon surfaces. Classical adsorbents, such as activated carbon, carbon nanotubes, graphene, carbon dots, and biochar, are evaluated in terms of pore structure, dopant effects, and uptake capacity. The review then highlights recent progress in advanced carbon architectures, such as MXenes, three-dimensional architectures, and 3D-printed carbon platforms, with emphasis on their gravimetric and volumetric performance under practical conditions. Importantly, this review introduces a forward-looking perspective on the application of artificial intelligence and machine learning tools for data-driven sorbent design. These methods enable high-throughput screening of materials, prediction of performance metrics, and identification of structure–property relationships. By combining experimental insights with computational advances, carbon-based hydrogen storage platforms are expected to play a pivotal role in the next generation of energy storage systems. The paper concludes with a discussion on remaining challenges, utilization scenarios, and the need for interdisciplinary efforts to realize practical applications. Full article

This study presents a photoresist-free patterning method for solution-processed indium zinc oxide (IZO) thin films using two photochemical exposure techniques, namely pulsed ultraviolet (UV) light and UV-ozone, and a plasma-based method using oxygen (O₂) plasma. Pulsed UV light delivers short, high-intensity flashes of light that induce localised photochemical reactions with minimal thermal damage, whereas UV-ozone enables smooth and uniform surface oxidation through continuous low-pressure UV irradiation combined with in situ ozone generation. By contrast, O₂ plasma generates ionised oxygen species via radio frequency (RF) discharge, allowing rapid surface activation, although surface damage may occur because of energetic ion bombardment. All three approaches enabled pattern formation without the use of conventional photolithography or chemical developers, and the UV-ozone method produced the most uniform and clearly defined patterns. The patterned IZO films were applied as active layers in bottom-gate top-contact thin-film transistors, all of which exhibited functional operation, with the UV-ozone-patterned devices exhibiting the most favourable electrical performance. This comparative study demonstrates the potential of photochemical and plasma-assisted approaches as eco-friendly and scalable strategies for next-generation IZO patterning in electronic device applications. Full article

This paper calculates the expected cost of uncertainty in solar and wind energy using the uncertainty cost function (UCF), with a primary focus on computational processing time. The comparison of processing time for the uncertainty cost quantification (UCQ) is conducted through three methods: the Monte Carlo simulation method (MC), numerical integration method, and analytical method. The MC simulation relies on random simulations, while numerical integration employs established numerical formulations. These methods are commonly used for solving cost optimization problems in power systems. However, the analytical method is a less conventional approach. The analytical method for calculating uncertainty costs is closely related to the UCF, as it relies on a mathematical representation of the impact of uncertainty on costs, which is modeled through the UCF. A multi-objective approach was employed for scheduling an energy management system, that is to say, thermal–wind–solar energy systems, proposing a simplified method for modeling controllable renewable generation through UCF with an analytical method, instead of the complex probability distributions typically used in traditional methods. This simplification reduces complexity and computational processing time in optimization problems, offering greater accuracy in approximating real distributions and adaptability to various scenarios. The simulations performed yielded positive results in improving cost estimation and computational efficiency, making it a promising tool for enhancing economic distribution and grid operability. Full article

Swine infectious diseases, often caused by multiple co-infecting agents, pose severe global threats to pig health and industry economics. Conventional single-plex testing assays, whether relying on pathogen antigens or nucleic acids, exhibit limited efficacy in the face of co-infection events. The modern nucleic acid-based multiplex testing (NAMT) methods demonstrate substantial strengths in the simultaneous detection of multiple pathogens involving co-infections owing to their remarkable sensitivity, exceptional specificity, high-throughput, and short turnaround time. The development, commercialization, and application of NAMT assays in swine infectious disease surveillance would be advantageous for early detection and control of pathogens at the onset of an epidemic, prior to community transmission. Such approaches not only contribute to saving the lives of pigs but also aid pig farmers in mitigating or preventing substantial economic losses resulting from infectious disease outbreaks, thereby alleviating unwanted pressure on animal and human health systems. The current literature review provides an overview of some modern NAMT methods, such as multiplex quantitative real-time PCR, multiplex digital PCR, microarrays, microfluidics, next-generation sequencing, and their applications in the diagnosis of swine infectious diseases. Furthermore, the strengths and weaknesses of these methods were discussed, as well as their future development and application trends in swine disease diagnosis. Full article