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The seamless integration of emerging directional liquid transport (DLT) technology with traditional textile materials has ushered in the next‐generation multifunctional textiles, i.e., DLT textiles, which will play a vital role in areas such as wearable smart materials and ecological environmental protection. To further promote the combination of DLT technology and textile technology, a concise overview of the research progress in DLT textiles, including the basic transport mechanisms, various preparation strategies and diversified applications of DLT textiles is provided. In this review, the theoretical mechanisms of directional transport from the perspective of wetting and wicking is discussed. Besides, the preparation strategies of DLT textiles, and categorized them into three categories is summarized: fiber‐based DLT textiles, fabric‐based DLT textiles, and fiber/fabric hybrid‐based textiles. Subsequently, the current and potential applications of DLT textiles are classified and discussed, mainly focusing on functional clothing, oil‐water separation, fog collection, distillation, sensors, biomedicine, and so on. Finally, the challenges and prospects of DLT textile research to enhance the functionality and application performance is outlined. [ABSTRACT FROM AUTHOR]

Plant stomata play a crucial role in photosynthesis by regulating transpiration and gas exchange. Meanwhile, environmental cues can also affect the formation of stomata. Stomatal formation, therefore, is optimized for the survival and growth of the plant despite variable environmental conditions. To adapt to environmental conditions, plants open and close stomatal pores and even regulate the number of stomata that develop on the epidermis. There are great differences in the leaf structure and developmental origin of the cell in the leaf between Arabidopsis and grass plants. These differences affect the fine regulation of stomatal formation due to different plant species. In this paper, a comprehensive overview of stomatal formation and the molecular networks and genetic mechanisms regulating the polar division and cell fate of stomatal progenitor cells in dicotyledonous plants such as Arabidopsis and Poaceae plants such as Oryza sativa and Zea mays is provided. The processes of stomatal formation mediated by plant hormones and environmental factors are summarized, and a model of stomatal formation in plants based on the regulation of multiple signaling pathways is outlined. These results contribute to a better understanding of the mechanisms of stomatal formation and epidermal morphogenesis in plants and provide a valuable theoretical basis and gene resources for improving crop resilience and yield traits. [ABSTRACT FROM AUTHOR]

Background: Despite hip function typically deteriorating in the post-collapse stage of osteonecrosis of the femoral head (ONFH), some patients can still demonstrate long-term favorable hip function, a state termed "survival with collapse". This study aims to identify the characteristics of patients suitable for "survival with collapse" in cases of ONFH. Methods: This cross-sectional study included 65 patients (87 hips) diagnosed with post-collapse ONFH for ≥ 3 years (average 9.1 years, range 3–23 years). Hip function was assessed using the Harris Hip Score (HHS). Demographic, clinical, and radiographic data were compared between the favorable group (HHS > 80) and the poor group (HHS ≤ 80). Independent protective factors for hip function were identified by multivariate analysis and receiver operating characteristic (ROC) curve analysis was further applied to evaluate these factors' diagnostic efficacy. Results: The favorable and poor groups included 46 and 41 hips, respectively. Significant differences were found in body mass index (BMI), Association Research Circulation Osseous (ARCO) stage, collapse degree, Japanese Investigation Committee (JIC) classification, necrotic size, and hip subluxation between the two groups (p < 0.05). Multivariate logistic regression identified collapse < 3 mm(OR:14.49, 95%CI: 3.52–59.68, p < 0.001), JIC types B (OR: 11.08, 95% CI: 1.07-115.12, p < 0.05) and C1(OR: 5.18, 95% CI: 1.47–18.20, p < 0.05) as independent protective factors for hip function, while BMI (OR: 0.76, 95% CI: 0.59–0.97, p = 0.029) was an independent risk factor. ROC curve analysis demonstrated that both collapse degree (AUC = 0.798, sensitivity = 91.3%, specificity = 68.3%, p < 0.0001) and JIC classification (AUC = 0.787, sensitivity = 80.4%, specificity = 73.2%, p < 0.0001) had satisfactory diagnostic value for hip function. Combining JIC classification and collapse degree (AUC = 0.868, sensitivity = 76.1%, specificity = 85.4%, p < 0.0001) significantly enhanced diagnostic efficacy compared to using either alone (p < 0.05). Conclusion: In ONFH, femoral head collapse does not necessarily determine a poor prognosis. Patients with mild collapse (< 3 mm) and preserved anterolateral wall are more likely to retain satisfactory hip function, making them candidates for "survival with collapse." [ABSTRACT FROM AUTHOR]

Objective: Alzheimer's disease (AD) pathology is featured by the extracellular accumulation of amyloid‐β (Aβ) plaques and intracellular tau neurofibrillary tangles in the brain. We studied whether Aβ and tau accumulation are independently associated with future cognitive decline in the AD continuum. Methods: Data were acquired from the Alzheimer's Disease Neuroimaging Initiative (ADNI) public database. A total of 1272 participants were selected based on the availability of Aβ‐PET and CSF tau at baseline and of those 777 participants with follow‐up visits. Results: We found that Aβ‐PET and CSF tau pathology were related to cognitive decline across the AD clinical spectrum, both as potential predictors for dementia progression. Among them, Aβ‐PET (A + T− subjects) is an independent reliable predictor of longitudinal cognitive decline in terms of ADAS‐13, ADNI‐MEM, and MMSE scores rather than tau pathology (A − T+ subjects), indicating tau accumulation is not closely correlated with future cognitive impairment without being driven by Aβ deposition. Of note, a high percentage of APOE ε4 carriers with Aβ pathology (A+) develop poor memory and learning capacity. Interestingly, this condition is not recurrence in terms of the ADNI‐MEM domain when adding APOE ε4 status. Finally, the levels of Aβ‐PET SUVR related to glucose hypometabolism more strongly in subjects with A + T− than A − T+ both happen at baseline and longitudinal changes. Conclusions: In conclusion, Aβ‐PET alone without tau pathology (A + T−) measure is an independent reliable predictor of longitudinal cognitive decline but may nonetheless forecast different status of dementia progression. However, tau accumulation alone without Aβ pathology background (A − T+) was not enough to be an independent predictor of cognitive worsening. [ABSTRACT FROM AUTHOR]

On the basis of "Carbon Peak and Carbon Neutral" goals, carbon sequestration projects are increasing in China. The integrity of cement sheaths, as an important factor affecting carbon sequestration projects, has also received more attention and research. When CO2 is injected into the subsurface from sequestration wells, the cement sheath may mechanically fail due to the pressure accumulated inside the casing, which leads to the sealing of the cement sheath failing. The elasticity and strength parameters of the cement sheath are considered in this paper. The critical bottom-hole injection pressures of inclined well sections under anisotropic formation stresses at different depths were calculated for actual carbon-sealing wells in the X block—the CO2 sequestration target block. The sensitivity factors of the critical bottom-hole injection pressure were also analyzed. It was found that the cement sheath damage criterion was tensile damage. The Young's modulus and tensile strength of the cement sheath are the main factors affecting the mechanical failure of the cement sheath, with Poisson's ratio having the second highest influence. An increase in the Young's modulus, Poisson's ratio, and tensile strength of the cement sheath can help to improve the mechanical stability of cement sheaths in CO2 sequestration wells. This model can be used for the design and evaluation of cement in carbon sequestration wells. [ABSTRACT FROM AUTHOR]

Background: Despite extensive work to identify diagnostic plasma markers for Parkinson's disease (PD), there are still no accepted and validated surrogate biomarkers. Mitophagy‐associated proteins (MAPs), including PTEN‐induced putative kinase 1 (PINK1), Parkin, phosphoglycerate mutase 5 (PGAM5), BCL2 interacting protein 3 (BNIP3), and phosphorylated‐TBK1 (p‐TBK1), are, to our best knowledge, not well studied as a panel of biomarkers of neurodegeneration in PD. Methods: The study population comprised 116 age‐matched controls (HC), 179 PD patients, alongside and 90 PD syndromes (PDs) divided between two cohorts: (i) the modeling cohort (cohort 1), including 150 PD, 97 HC, and 80 PDs; and (ii) the validated cohort (cohort 2), including 29 PD, 19 HC, and 10 PDs. Results: MAPs are elevated in the plasma of PD patients. PINK1, Parkin, and PGAM5 displayed the top three measurable increase trends in amplitude compared to BNIP3 and p‐TBK1. Moreover, the area under the curve (AUC) values of PINK1, PGAM5, and Parkin were ranked the top three MAP candidates in diagnosis accuracy for PD from HC, but the MAPs make it hard to differentiate PD from PDs. In addition, there are higher plasma PINK1‐Parkin levels and prominent diagnostic accuracy in A‐synuclein (+) subjects than in A‐synuclein (−) subjects. Conclusions: These results uncover that plasma MAPs (PINK1, Parkin, and PGAM5) may be potentially useful diagnostic biomarkers for PD diagnosis. Studies on larger cohorts would be required to test whether elevated plasma MAP levels are related to PD risk or prognosis. [ABSTRACT FROM AUTHOR]

To address the current problems of insufficient vehicle detection accuracy and slow detection speed in complex traffic monitoring scenarios, a lightweight vehicle detection algorithm based on YOLOv8 model is proposed. Firstly, FasterNet is used to replace the backbone feature extraction network of YOLOv8, which reduces redundant computation and memory access, and improves the detection accuracy and inference speed of the model.Secondly, the SimAM attention module is added to the Backbone and Neck sections, which enhances the important features of the target vehicles without increasing the original network parameters, and improves the feature fusion capability. Then, to address the problem of poor detection of small-sized vehicles under dense traffic flow, a small target detection head is added to better capture the features and contextual information of small-sized vehicles. Finally, Wise- IoU, which can adaptively adjust the weight coefficients, is used as the loss function of the improved model, which enhances the regression performance of the bounding box and the robustness of the detection.The experimental results on the UA-DETRAC dataset show that compared with the original model, the improved method in this paper is able to achieve better detection accuracy and speed in the traffic monitoring system, with the mAP and FPS improved by 3.06 percengtage points and 3.36%, respectively, which effectively improves the problem of the poor detection of small-target vehicles in the complex traffic scenarios, and achieves a good balance between accuracy and speed. [ABSTRACT FROM AUTHOR]

Objectives: The ATN's different modalities (fluids and neuroimaging) for each of the Aβ (A), tau (T), and neurodegeneration (N) elements are used for the biological diagnosis of Alzheimer's disease (AD). We aim to identify which ATN category achieves the highest potential for diagnosis and predictive accuracy of longitudinal cognitive decline. Methods: Based on the availability of plasma ATN biomarkers (plasma‐derived Aβ42/40, p‐tau181, NFL, respectively), CSF ATN biomarkers (CSF‐derived Aβ42/Aβ40, p‐tau181, NFL), and neuroimaging ATN biomarkers (18F‐florbetapir (FBP) amyloid‐PET, 18F‐flortaucipir (FTP) tau‐PET, and fluorodeoxyglucose (FDG)‐PET), a total of 2340 participants were selected from ADNI. Results: Our data analysis indicates that the area under curves (AUCs) of CSF‐A, neuroimaging‐T, and neuroimaging‐N were ranked the top three ATN candidates for accurate diagnosis of AD. Moreover, neuroimaging ATN biomarkers display the best predictive ability for longitudinal cognitive decline among the three categories. To note, neuroimaging‐T correlates well with cognitive performances in a negative correlation manner. Meanwhile, participants in the "N" element positive group, especially the CSF‐N positive group, experience the fastest cognitive decline compared with other groups defined by ATN biomarkers. In addition, the voxel‐wise analysis showed that CSF‐A related to tau accumulation and FDG–PET indexes more strongly in subjects with MCI stage. According to our analysis of the data, the best three ATN candidates for a precise diagnosis of AD are CSF‐A, neuroimaging‐T, and neuroimaging‐N. Conclusions: Collectively, our findings suggest that plasma, CSF, and neuroimaging biomarkers differ considerably within the ATN framework; the most accurate target biomarkers for diagnosing AD were the CSF‐A, neuroimaging‐T, and neuroimaging‐N within each ATN modality. Moreover, neuroimaging‐T and CSF‐N both show excellent ability in the prediction of cognitive decline in two different dimensions. [ABSTRACT FROM AUTHOR]

In order to withstand high-temperature environments, ultra-high molecular weight polyethylene (UHMWPE) fibers with cooling properties are being increasingly used in personal thermal management textiles during the summer. However, there is relatively little research on its combination with knitting. In this paper, we combine UHMWPE fiber and knitting structure to investigate the impact of varying UHMWPE fiber content and different knitting structures on the heat and humidity comfort as well as the cooling properties of fabrics. For this purpose, five kinds of different proportions of UHMWPE and polyamide yarn preparation, as well as five kinds of knitted tissue structures based on woven tissue were designed to weave 25 knitted fabrics. The air permeability, moisture permeability, moisture absorption and humidity conduction, thermal property, and contact cool feeling property of the fabrics were tested. Then, orthogonal analysis and correlation analysis were used to statistically evaluate the properties of the fabrics statistically. The results show that as the UHMWPE content increases, the air permeability, heat conductivity, and contact cool feeling property of the fabrics improve. The moisture permeability, moisture absorption and humidity conductivity of fabrics containing UHMWPE are superior to those containing only polyamide. The air permeability, moisture permeability, and thermal conductivity of the fabrics formed by the tuck plating organization are superior to those of the flat needle plating and float wire plating organization. The fabric formed by 2 separate 2 float wire organization has the best moisture absorption, humidity conduction, contact cool feeling property. [ABSTRACT FROM AUTHOR]

The frequency-shift demodulation is a primary demodulation method in phase-sensitive optical time domain reflectometry (Φ-OTDR) with intrinsic resistance to interference fading. So far, the least mean squares (LMS) estimation method has the optimal demodulation accuracy and robustness. However, it takes much processing time due to the step-by-step sliding operation. In this work, we propose a fast LMS estimation method based on cross-correlation calculation to accelerate the demodulation while maintaining accuracy. Experiments are performed along a 9 km sensing fiber with a 4 m spatial resolution. The performance of the fast LMS, LMS, and cross-correlation methods are compared by using the same parameters. Compared with the LMS method, the fast LMS achieves a 12-time improvement in processing speed while remaining the same demodulation accuracy. Although the proposed fast LMS method takes slightly more time than the cross-correlation method (1.6 times), it improves the demodulation accuracy ∼6 dB for the vibration signal and ∼2.1 dB for the overall demodulation accuracy. [ABSTRACT FROM AUTHOR]