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Psoriasis is a common skin disease with complex mechanisms, and its diagnosis and treatment bring many challenges. In recent years, machine learning (ML) techniques have been proposed as a new tool to improve this disease's diagnosis and treatment process. With the ability to learn from limited data and transfer knowledge from one field to another, these techniques have a high potential to improve diagnosis accuracy and treatment efficiency. However, using ML in diagnosing and treating psoriasis is associated with several challenges, including data limitations, the complexity of algorithms, and the need for high expertise to implement them properly. By presenting a detailed taxonomy, this article examines the applications and challenges of using ML techniques in psoriasis and analyzes the latest achievements in this field. The results of this study show that ML techniques have increased the accuracy of psoriasis diagnosis by 35% and improved treatment efficiency by 29%. In addition, these techniques reduced the data processing time by 21% and improved the overall treatment process. Also, these methods have increased the success rate of patient survival predictions by 15%. Finally, by examining the existing challenges and providing solutions to overcome these challenges, this research will help researchers and experts in this field develop new strategies to improve the diagnosis and treatment of psoriasis by better understanding ML applications. [ABSTRACT FROM AUTHOR]

Offshore low-permeability thin interbedded reservoirs contain significant oil reserves and are crucial for future development. However, due to the high cost and operational challenges associated with offshore fracturing, large-scale fracturing common in onshore fields is uneconomical. Furthermore, offshore low-permeability reservoirs often have sparse well placement and wide well spacing, in contrast to onshore low-permeability fields, which leads to low recovery. Additionally, there is a lack of comprehensive theory on optimizing the well patterns and fracture networks to maximize net income, highlighting the need for further research. This study tackles these issues in a low-permeability thin interbedded reservoir in the Bozhong Oilfield by using reservoir numerical simulation. First, fracture parameters, including fracture half-length and conductivity, are optimized for different well patterns. Subsequently, well pattern optimization is conducted under fractured conditions, targeting maximum net income under various conditions. The results indicate that when fractures are confined to a single reservoir layer and the main reservoir layer accounts for less than 36% of the development section, fractured directional well patterns yield a higher net income. Conversely, when fractures penetrate all reservoir layers, fractured horizontal wells with closer fracture spacing a higher number of fractures are the most profitable option, particularly in offshore fields with large well spacing. The findings provide critical insights into optimizing well patterns and fracture network designs for offshore low-permeability thin interbedded reservoirs. [ABSTRACT FROM AUTHOR]

Background: Good quality sleep is important in order to have better cognitive performance and to avoid health problems. OBJECTIVES: 1. To assess the Sleep quality among M.B.B.S interns in a tertiary care centre.2. To find the Correlation between Body Mass Index and Sleep quality. Methodology: A Cross sectional study was conducted among Interns of a tertiary care centre southern Tamilnadu in the month of August 2023 and the sleep quality was assessed using Sleep Quality Scale. Date were collected after getting consent and entered in MS Excel and analysed using SPSS. The Correlation between BMI and Sleep quality were analysed. RESULTS: Mean age of the participants was 24.03 among them 34.8% were males and 65.2% were females. Mean BMI of the participants was 22 with the minimum BMI of 17 and the maximum BMI of 35. Mean total score was 34.93 with the minimum score of 8 and the maximum score of 64. There is weak correlation between BMI and Sleep quality. Conclusion: Optimal level of balance between training and adequate sleep is important in residency programs. Our study indicates that there is no relationship between BMI and sleep quality among M.B.B.S interns in Kanyakumari district. [ABSTRACT FROM AUTHOR]

Background: Every year, Traumatic brain injury (TBI) affects people all over the world in a significant way. In the treatment of TBI, sedatives are employed as neuroprotectors to lower intracranial pressure (ICP) and the cerebral metabolic rate of oxygen (CMRO2). The aim of the work was to compare the efficacy of dexmedetomidine versus propofol in TBI patients regarding the cerebral blood flow velocity (CBFV), CMRO2 and 28-day mortality. Methods: This prospective clinical double-blinded randomized study was conducted on 72 patients with TBI. The patients were allocated equally into group D (dexmedetomidine), group P (propofol) and given sedation for 48hrs. Richmond Agitation-Sedation Scale was used for assessment of sedation level. Jugular venous bulb oxygen saturation (SjVO2) and transcranial Doppler measurements of middle cerebral artery (MCA) flow velocity and diameter(d) were recorded at admission, 6 hr, 12hr, 24hr and 48hr. Results: Both dexmedetomidine and propofol are comparable for managing TBI. There was a significant reduction in cerebral perfusion pressure (CPP) and CMRO2 in each group, but CBF showed an increase with both sedatives. Propofol exhibited a more increase in CBFV. However, neither sedative significantly affected ICP nor 28-mortality rate. Conclusions: In patients with TBI, dexmedetomidine and propofol sedative agents showed comparable effect on mean arterial pressure (MAP), ICP, CPP, CBF, CMRO2 and mortality rate but HR and mean flow velocity (MFV) were significantly less with dexmedetomidine than propofol. While both sedatives decrease MAP, HR, CPP, CMRO2 and MCA diameter and increase MFV, CBF and SjVO2 when compared to admission values. [ABSTRACT FROM AUTHOR]

Objectives: Vitamin D deficiency has been associated with psychiatric disorders and behavioral phenotypes such as Attention-Deficit/Hyperactivity Disorder (ADHD). Considering that vitamin D levels are polygenic, we aim to evaluate the overall effects of its genetic architecture on symptoms of inattention, hyperactivity, and impulsivity and on the serum levels of vitamin D in two independent samples of adults, as well as the specific effects of five relevant polymorphisms in vitamin D-related genes. Methods: We evaluated 870 subjects from an ADHD sample (407 cases and 463 controls) and 319 subjects from an academic community (nutrigenetic sample). Vitamin D serum levels were obtained through Elisa test and genetic data by TaqMan™ allelic discrimination and Infinium PsychArray-24 BeadChip genotyping. Polygenic Scores (PGS) were calculated on PRSice2 based on the latest GWAS for Vitamin D and statistical analyses were conducted at Plink and SPSS software. Results: Vitamin D PGSs were associated with inattention in the ADHD sample and with hyperactivity when inattention symptoms were included as covariates. In the nutrigenetic sample, CYP2R1 rs10741657 and DHCR7 rs12785878 were nominally associated with impulsivity and hyperactivity, respectively, and both with vitamin D levels. In the clinical sample, RXRG rs2134095 was associated with impulsivity. Discussion: Our findings suggest a shared genetic architecture between vitamin D levels and ADHD symptoms, as evidenced by the associations observed with PGS and specific genes related to vitamin D levels. Interestingly, differential effects for vitamin D PGS were found in inattention and hyperactivity, which should be considered in further studies involving ADHD. [ABSTRACT FROM AUTHOR]

Covalent organic frameworks (COFs) exhibit considerable potential in gas separations owing to their remarkable stability and tunable pore structures. Nevertheless, their application as gas separation membranes is hindered by limited size-sieving capabilities and poor processability. In this study, we propose a novel molecular weaving strategy that combines hydroxyl polymers and 2D TpPa-SO 3 H COF nanosheets, achieving high gas separation efficiency. Driven by the strong electrostatic interactions, the hydroxyl chains thread through the COF pores, effectively weaving and assembling the composites to achieve exceptional flexibility and high mechanical strength. The penetrated chains also reduce the effective pore size of COFs, and combined with the "secondary confinement effect" stemming from abundant CO 2 sorption sites in the channels, the PVA@TpPa-SO 3 H membrane demonstrates a remarkable H 2 permeance of 1267.3 GPU and an H 2 /CO 2 selectivity of 43, surpassing the 2008 Robson upper bound limit. This facile strategy holds promise for the manufacture of large-area COF-based membranes for small-sized gas separations., (© 2024 Wiley-VCH GmbH.)

MXenes, a rapidly emerging class of 2D transition metal carbides, nitrides, and carbonitrides, have attracted significant attention for their outstanding properties, including high electrical conductivity, tunable work function, and solution processability. These characteristics have made MXenes highly versatile and widely adopted in the next generation of optoelectronic devices, such as perovskite and organic solar cells. However, their integration into silicon-based optoelectronic devices remains relatively underexplored, despite silicon's dominance in the semiconductor industry. In this review, a timely summary of the recent progress in utilizing Ti-based MXenes, particularly Ti 3 C 2 T x , in silicon-based optoelectronic devices is provided. The composition, synthesis methods, and key properties of MXenes that contribute to their potential for enhanced device performance are focused on. Furthermore, the latest advancements in MXene applications in silicon-based solar cells and photodetectors are discussed from fundamental and applied perspectives. Finally, the key challenges and future opportunities for the integration of MXenes in silicon-based optoelectronic devices are outlined., (© 2025 Wiley‐VCH GmbH.)

Efficient utilization of solar energy is widely regarded as a crucial solution to addressing the energy crisis and reducing reliance on fossil fuels. Coupling photothermal and photochemical conversion can effectively improve solar energy utilization yet remains challenging. Here, inspired by the photosynthesis system in green plants, we report herein an artificial solar energy converter (ASEC) composed of light-harvesting units as solar collector and oriented ionic hydrophilic channels as reactors and transporters. Based on such architecture, the obtained ASEC (namely ASEC-NJFU-1) can efficiently realize parallel production of freshwater and H 2 O 2 from natural seawater under natural light. The total solar energy conversion (SEC) of ASEC-NJFU-1 reaches up to 8047 kJ m -2  h -1 , corresponding to production rates of freshwater and H 2 O 2 are 3.56 kg m -2-1  h -1 and 19 mM m -2  h -1 , respectively, which is a record-high value among all photothermal-photocatalytic systems reported to date. Mechanism investigation of combining spectrum and experimental studies indicated that the high SEC performance for ASEC-NJFU-1 was attributed to the presence of plant bioinspired architecture with carbon nanotubes as solar-harvestor and COF-based oriented aerogel as reactors and transporters. Our work thus establishes a novel artificial photosynthesis system for highly efficient solar energy utilization., (© 2025 Wiley-VCH GmbH.)