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Loading of WS2 can greatly improve water splitting H2 generation efficiency of CdS in experiments. Here, we constructed WS2/CdS(100) and WS2/CdS(110) heterostructures with smaller mismatches and explored their interaction energy and band offset by first-principles calculations. Our calculation suggests that the WS2/CdS(100) interface with a stronger binding energy is more active in experiments, while the WS2/CdS(110) interface is metastable. The band alignment between CdS and WS2 is highly dependent on the orientation of the interfaces, and WS2/CdS(100) and WS2/CdS(110) belong to type-I and type-II band alignments, respectively. Therefore, a metal electrode and hole scavenger may be essential in experiments to help WS2/CdS(100) efficiently trap electrons, and a suitable substrate and an appropriate growth temperature are also needed to composite the CdS(110) surface to achieve a higher photocatalytic efficiency. In addition, we performed a detailed analysis of the macroscopic average potential and found that the calculated accuracy of potential difference across the heterostructures due to slab thickness is less than 80 meV at WS2/CdS interfaces. In total, our calculations not only explain the physical reasons for the increased efficiency of WS2/CdS, but also provide a detailed guideline for the design of a more efficient synergistic catalyst. [ABSTRACT FROM AUTHOR]

The abnormal structure of tumor vascular seriously hinders the delivery and deep penetration of drug in tumor therapy. Herein, an integrated and tumor microenvironment (TME)-responsive nanocarrier is designed, which can dilate vessle and improve the drug penetration by in situ releasing nitric oxide (NO). Briefly, S-nitroso-glutathione (GSNO) and curcumin (Cur) were encapsulatd into the Cu-doped zeolite imidazole framework-8 (Cu-ZIF-8) and modified with hyaluronic acid. The nanocarrier degradation in the weakly acidic of TME releases Cu2+, then deplete overexpressed intratumourally glutathione and transformed into Cu+, thus disrupting the balance between nicotinamide adenine dinucleotide phosphate and flavin adenine dinucleotide (NADPH/FAD) during the metabolism homeostasis of tumor. The Cu+ can generate highly toxic hydroxyl radical through the Fenton-like reaction, enhancing the chemodynamic therapeutic effect. In addition, Cu+ also decomposes GSNO to release NO by ionic reduction, leading to vasodilation and increased vascular permeability, significantly promoting the deep penetration of Cur in tumor. Afterwards, the orderly operation of cell cycle is disrupted and arrested in the S-phase to induce tumor cell apoptosis. Deep-hypothermia potentiated 2D/3D fluorescence imaging demonstrated nanocarrier regulated endogenous metabolism homeostasis of tumor. The cascade-catalysed multifunctional nanocarrier provides an approach to treat orthotopic tumor. [ABSTRACT FROM AUTHOR]

Background: Head and neck cancer treatment often leads to trismus, a condition characterized by limited mouth opening. Exercise‐based therapy is the most common intervention but there are no clear guidelines as to the optimal exercise regimen. Restorabite™ is a portable and force‐regulated trismus device designed to enhance exercise adherence. This study explores the adherence to exercises using Restorabite™ in head and neck cancer patients with trismus and identifies facilitators and barriers to exercise therapy. Materials and methods: Mixed‐methods, prospective cohort study undertaken at a quaternary oncology hospital, in Sydney Australia involving participants diagnosed with head and neck cancer diagnosed with trismus (maximal incisal opening under 35 mm). Patients underwent a 10‐week individualized trismus program using Restorabite™ with weekly speech pathology reviews. Exercise adherence was tracked through categorized descriptors. Data were collected prospectively at baseline, during 10 weeks of therapy with Restorabite™, and at 6‐ and 12‐month post‐trismus exercise. Participants described facilitators of trismus therapy, and barriers to completing the prescribed exercises. Clinical documentation of these responses was then analyzed using content analysis. Results: One‐hundred and thirty‐five participants were recruited. During the intervention 69% (n = 93) exercised as recommended, 24% (n = 32) exercised less, and 7% (n = 10) exercised more than recommended. At 6 months post‐intervention, 55.5% (n = 75) exercised as recommended, 38.5% (n = 52) exercised less, and 4% (n = 6) exercised more. At 12 months, 36% (n = 49) exercised as recommended, 48% (n = 62) exercised less, and 11% (n = 15) exercised more. MIO increased from a mean of 18.6 mm at baseline, to 30.1 mm at the end of the 10‐week intervention. This was maintained at 6 and 12 months (31.7 and 32.1 mm, respectively). Adherence to the exercise program was associated with greater improvement in maximum interincisal opening (p < 0.001). Facilitators of adherence included intrinsic motivation, device portability, perceived functional change, and external support tools. Barriers included cancer treatment toxicities, competing priorities, and health challenges. Positive outcomes included functional improvements, while negative outcomes included increased pain. Conclusions: Seventy‐six percent of patients prescribed Restorabite™ performed trismus exercises at or more than the recommended frequency. Facilitators and barriers identified provide insights into factors influencing adherence. Future research should involve comparative studies that compare the adherence and effectiveness of different exercise programs. [ABSTRACT FROM AUTHOR]

Free-space optics communication (FSO) can be used as a transmission medium for fiber optic sensing signals to make fiber optic sensing easier to implement; however, interference with the sensing signals caused by the optical turbulence and scattering of airborne particles in the FSO path is a potential problem. This work aims to deep denoise sensed signals from fiber Bragg grating (FBG) sensors based on FSO link transmission using advanced denoising deep learning techniques, such as stacked denoising autoencoders (SDAE). Furthermore, it will demodulate the sensed wavelength of FBGs by applying the deep belief network (DBN) technique. This is the first time the real FBG sensing experiment has utilized the actual noise interference caused by the environmental turbulence from an FSO link rather than adding noise through numerical processing. Consequently, the spectrum of the FBG sensors is clearly modulated by the noise and the issue with peak power variation. This complicates the determination of the center wavelengths of multiple stacked FBG spectra, requiring the use of machine learning techniques to predict these wavelengths. The results indicate that SDAE is efficient in denoising from the FBG spectrum, and DBN is effective in demodulating the central wavelength of the overlapped FBG spectrum. Thus, it is beneficial to implement an FSO link-based FBG sensing system in adverse weather conditions or atmospheric turbulence. [ABSTRACT FROM AUTHOR]

In view of the rapidly expanding medical and commercial applications of silver nanoparticles (AgNPs), their potential health risks and environmental effects are a significant growing concern. Earlier research by our group uncovered the embryotoxic potential of AgNPs, showing detrimental impacts of these nanoparticles on both pre- and post-implantation embryonic development. In the current study, we showed that low (50–100 μM) and high (200–400 μM) dose ranges of AgNPs trigger distinct cell death programs affecting mouse embryo development and further explored the underlying mechanisms. Treatment with low concentrations of AgNPs (50–100 μM) triggered ROS generation, in turn, inducing mitochondria-dependent apoptosis, and ultimately, harmful effects on embryo implantation, post-implantation development, and fetal development. Notably, high concentrations of AgNPs (200–400 μM) evoked more high-level ROS generation and endoplasmic reticulum (ER) stress-mediated necrosis. Interestingly, pre-incubation with Trolox, a strong antioxidant, reduced ROS generation in the group treated with 200–400 μM AgNPs to the level induced by 50–100 μM AgNPs, resulting in switching of the cell death mode from necrosis to apoptosis and a significant improvement in the impairment of embryonic development. Our findings additionally indicate that activation of PAK2 is a crucial step in AgNP-triggered apoptosis and sequent detrimental effects on embryonic development. Based on the collective results, we propose that the levels of ROS generated by AgNP treatment of embryos serve as a critical regulator of cell death type, leading to differential degrees of damage to embryo implantation, post-implantation development and fetal development through triggering apoptosis, necrosis or other cell death signaling cascades. [ABSTRACT FROM AUTHOR]

Tumor cell-induced platelet aggregation (TCIPA) is a mechanism for the protection of tumor cells in the bloodstream and the promotion of tumor progression and metastases. The platelet C-type lectin-like receptor 2 (CLEC-2) can bind podoplanin (PDPN) on a cancer cell surface to facilitate TCIPA. Selective blockage of PDPN-mediated platelet–tumor cell interaction is a plausible strategy for inhibiting metastases. In this study, we aimed to screen for aptamers, which are the single-stranded DNA oligonucleotides that form a specific three-dimensional structure, bind to specific molecular targets with high affinity and specificity, bind to PDPN, and interfere with PDPN/CLEC-2 interactions. The systematic evolution of ligands by exponential enrichment (SELEX) was employed to enrich aptamers that recognize PDPN. The initial characterization of ssDNA pools enriched by SELEX revealed a PDPN aptamer designated as A1 displaying parallel-type G-quadruplexes and long stem-and-loop structures and binding PDPN with a material with a dissociation constant (Kd) of 1.3 ± 1.2 nM. The A1 aptamer recognized both the native and denatured form of PDPN. Notably, the A1 aptamer was able to quantitatively detect PDPN proteins in Western blot analysis. The A1 aptamer could interfere with the interaction between PDPN and CLEC-2 and inhibit PDPN-induced platelet aggregation in a concentration-dependent manner. These findings indicated that the A1 aptamer is a candidate for the development of biosensors in detecting the levels of PDPN expression. The action by A1 aptamer could result in the prevention of tumor cell metastases, and if so, could become an effective pharmacological agent in treating cancer patients. [ABSTRACT FROM AUTHOR]

Summary: The design of GHz‐bandwidth super‐source‐follower‐based low‐pass filters (SSF‐LPFs) is investigated. The transfer function is derived by considering transistor parasitics. The behaviors of SSF‐LPFs can be predicted accurately with these formulas. The theoretical values of pole/zero frequencies of the circuit agree well with the corresponding simulation results. Moreover, the relationship between the Q factor and the phase margin of the biquadratic filter is revealed. Two 1.3‐GHz 4th‐order LPFs are designed using 90‐nm CMOS technology, where one contains a high‐Q biquad with a small phase margin and a low‐Q biquad, while the other is built with two biquads with moderate Q factors and sufficient phase margins. For the former, the discrepancy between the theoretical and simulated phase margin is <2°, and the discrepancy between the theoretical and simulated corner frequency is <6%. For the latter, the discrepancy between the theoretical and simulated phase margin is <4°, and the discrepancy between the theoretical and simulated corner frequency is <4%. The filter containing biquads with sufficient phase margins is fabricated and occupies an area of 0.44 mm2. Consuming 14.4 mW, the filter delivers a bandwidth of 1.3 GHz, P1dB of −11.94 dBm, and IIP3 of −4.5 dBm. [ABSTRACT FROM AUTHOR]

Introduction: The thulium fiber laser (TFL) generates a focused beam, which can be transmitted to laser fibers with small core diameters and may facilitate in situ lower-pole lithotripsy. This study compares lithotripsy performance of the 150 and 200 µm TFL in a lower pole benchtop kidney model. Materials and Methods: Using a 3D model printed from an actual kidney, in situ laser lithotripsy was performed on 1 cm lower-pole BegoStones (calcium oxalate monohydrate consistency) using four different settings (all 20W) and two fiber sizes (150 and 200 µm). Procedure time, laser time, total pulse energy, and fiber stripping were compared between the two fibers using an ANOVA or independent t-test. Results: The 150 µm fiber at 0.2 J × 100 Hz had the shortest lasing and procedure time (17.3 and 18.5 minutes) and lowest total pulse energy (20.75 kJ) compared with other study arms (p < 0.001). Overall procedure time, lasing time, and total pulse energy were significantly different between the 8 settings (p < 0.001 for all). At higher frequency (100 and 200 Hz), lasing time was significantly faster compared with 20 and 50 Hz (19.9 vs 27.3 minutes; p < 0.001). Furthermore, the average total procedure time was shorter with 150 µm compared with 200 µm regardless of settings (23.2 vs 29.8 minutes; p < 0.001). Conclusion: The 150 µm fiber results in shorter procedure and lasing time at lower total energy levels during lower-pole in situ lithotripsy. Overall, the fastest setting was 0.2 J and 100 Hz with the 150 µm fiber. Smaller laser fibers can potentially allow more efficient in situ laser lithotripsy with better irrigation and visibility at higher deflection angles. [ABSTRACT FROM AUTHOR]

Highly substituted naphthalene derivatives were prepared via palladium‐catalyzed reaction of 5‐(2‐bromophenyl)pent‐3‐en‐1‐ynes with arylboronic acids. Typically, reaction of 3‐bromo‐4‐(3‐(4‐chlorophenyl)‐5‐phenyl‐1‐(p‐tolyl)pent‐2‐en‐4‐yn‐1‐yl)‐N‐methylaniline (1a) with PhB(OH)2 in the presence of Pd(PPh3)4 as the catalyst under basic conditions provided 8‐benzhydryl‐7‐(4‐chlorophenyl)‐N‐methyl‐5‐(p‐tolyl)naphthalen‐2‐amine (2a) quantitatively. Overall, 19 new naphthalene compounds were obtained by this methodology and their structures were characterized by spectroscopic methods. In addition, crystal structure of 2j was determined to confirm the structural details. Reaction pathway leading to the desired product is also discussed. [ABSTRACT FROM AUTHOR]

Objective: This study provided a quantitative prediction of best-corrected visual acuity (BCVA) for cataract patients using the inverse problem algorithm (IPA) technique earlier proposed by the authors. Methods: To this end, seven risk factors (age, BMI, MAP, IOP, HbA1c, LDL-C, and gender) were linked by a semi-empirical formula by normalizing each factor into a dimensionless range of −1.0 to +1.0. The adopted inverse problem algorithm (IPA) technique was run via a self-developed program in STATISTICA 7.0, featuring a 29-term nonlinear equation considering seven risk factors, cross-interaction between various pairs of factors, and one constant term [7 + (7 × 6)/2 + 1 = 29]. The IPA neglected quadratic, triple, or quadruple factors′ cross-interactions. This study used a dataset of 632 cataract patients to attain a reliable BCVA prediction with a variance of 0.929. A verification dataset of 160 patients with similar symptoms was used to verify this approach′s feasibility, reaching a good correlation with R2 = 0.909. Results: The verification group′s derived average AT (agreement) (9.12 ± 27.00%) indicated a slight deviation between the theoretical prediction and practical BCVA. The significant factors were age, body mass index (BMI), and intraocular pressure (IOP), whereas mean arterial pressure (MAP), hemoglobin A1c (HbA1c), low-density-lipoprotein cholesterol (LDL-C), and gender insignificantly contributed to BCVA. Conclusions: The proposed approach is instrumental in AI-assisted clinical diagnosis, yielding robust BCVA predictions for individual cataract patients based on their biological indices before the ophthalmological examination procedure. [ABSTRACT FROM AUTHOR]

To enhance the removal of COD (Chemical Oxygen Demand) by microalgae, this study constructed a novel microalgae–microalgae microbial fuel cell system (AA-MFC). It investigated the coupling relationship between the COD treatment efficiency at the anode and the production of high-value microalgal products at the cathode, as well as explored the effects of different initial inoculum densities and light–dark cycles. The experiment first measured the operational performance of the newly constructed AA-MFC in open-circuit and closed-circuit modes, demonstrating that this novel AA-MFC could start up rapidly within 32 h and operate stably. The results showed that the AA-MFC enhanced the removal of COD and the growth of microalgae biomass at the anode while maintaining stable power generation. When the initial inoculation density of the anode was 1.2 × 108 cell/cm2 and the light–dark cycle time was 18:6 h, the AA-MFC had the most obvious promoting effect on the COD removal of the anode. Compared with normal culture conditions, the COD removal rate increased by 26.0% to 96.1%. These results indicate that the AA-MFC can not only effectively remove pollutants, but also promote the accumulation of high-value microalgae biomass. [ABSTRACT FROM AUTHOR]

Because of changing consumer habits, manufacturing processes are shifting from mass production to small-batch production, which is making machining more complex and increasing demands for precision and stability. Machine tools, and thus machining accuracy, are affected by factors such as temperature and cutting load. Existing online estimation techniques often require the installation of additional sensors at specific locations, an approach that has cost and reliability issues, thus limiting industry's acceptance of these techniques. In practice, most manufacturers rely on offline detection methods, meaning that machining accuracy deviations can take some time to detect. In this study, we developed a technology for monitoring the status of machine tools; this technology, rather than requiring the installation of sensors, uses servo sensor signals to estimate accuracy, diagnose faults, and make recommendations regarding cutting depth parameters. The proposed method leverages a small number of experiments combined with extensive finite element analysis to construct a big data database, followed by the sensitivity and regression analyses of the generated database to produce an estimation model that evaluates machine tool conditions through servo feedback. The results showed that using linear regression to estimate the machine tool's status achieves good accuracy and that linear regression is easier to implement for real-time compensation. Ultimately, these results can enhance production efficiency and machining accuracy, as well as prevent unforeseen breakdowns. [ABSTRACT FROM AUTHOR]

Trismus commonly arises after surgery for head and neck cancer (HNC) and its severity is potentiated by postoperative radiotherapy. While the benefit of trismus rehabilitation after surgery and radiotherapy is well established, the evidence during radiotherapy is less clear. This may be due to poor adherence to trismus exercises secondary to acute mucositis. This study assessed the feasibility of using a novel trismus device during adjuvant radiotherapy for HNC in patients with acute postoperative trismus. Prospective single-arm cohort feasibility study. Eligible patients had undergone surgery with curative intent for HNC, planned for adjuvant radiotherapy, and were suitable for trismus rehabilitation. Participants completed a 10-week exercise program using a novel jaw stretching device. Study outcomes were adherence, maximal incisal opening (MIO), and trismus-related function and quality of life scores, assessed at baseline, 10 weeks, and 6 months after commencing exercises. Nine patients diagnosed with trismus after primary surgery were recruited. The mean increase in MIO at 10 weeks was 7.8 mm (range −4 to 15 mm, p = 0.03), and at 6 months was 10.6 mm (range 1–26 mm, p = 0.03). Significant improvements were observed in trismus-related quality of life (Gothenburg Trismus Questionnaire; p = 0.04). Adherence to the exercises was 100% in week 1–2, 67% in weeks 3–6, and 100% at 10 weeks (1 month post radiation). This study demonstrates the feasibility of using a novel jaw stretching device during adjuvant radiotherapy. Further evaluation is warranted to assess the effectiveness of early intervention and prevention of trismus during HNC radiotherapy. Level of Evidence: IV [ABSTRACT FROM AUTHOR]

Aerostatic bearings technology has been increasingly applied in the precision engineering and high-tech industries over the last decades, due to their considerable advantages including high motion accuracy, high speeds, low friction, and environment-friendly operations. This article presents a comprehensive and critical review with the historical progress on the state-of-the-art in research and development of design and analysis methods for aerostatic bearings and the associated products. The article also attempts to identify and discuss the scientific and technological challenges in air-bearing design and development, their future research development and trends, and their potential applications. [ABSTRACT FROM AUTHOR]

Giant trees are pivotal in forest ecosystems, yet our current understanding of their significance is constrained primarily by the limited knowledge of their precise locations and structural characteristics. Amidst escalating human‐induced disturbances globally, there is an urgent need to devise a practical approach to discover and measure giant trees accurately and efficiently.Here, we propose a novel light detection and ranging (lidar)‐based framework designed for the discovery and measurement of giant trees. Our framework integrates cutting‐edge lidar platforms, including spaceborne, Unmanned Aerial Vehicle (UAV), and backpack lidar, to create an end‐to‐end workflow. The algorithm involved in the proposed framework was compiled into a code package and made available as open source.The method successfully identified the tallest trees in China, including the tallest tree in Asia, a Cupressus austrotibetica with a height of 102.3 m, discovered in Yarlung Zangbo Grand Canyon in May 2023. This finding has not only established a new record but also demonstrated the efficacy of our proposed framework. Utilising lidar data, we performed meticulous measurements at both individual and stand levels, revealing the unique characteristics of this giant tree.The new framework for the discovery and measurement of giant trees, encompassing detailed procedures and codes, is expected to facilitate the discovery and measurement of giant trees with high efficiency, thus fostering advancements in giant tree ecology. [ABSTRACT FROM AUTHOR]

Inverse problems are typically tackled using deterministic optimization methods that may become trapped in a local minimum or probabilistic methods that can be computationally demanding. In this study, we explore the potential of the back propagation neural network (BPNN) optimized by the genetic algorithm (GA) for onshore transient electromagnetic (TEM) inversion. The GA is employed to optimize the initial parameters of the BPNN, enhancing its global optimization ability. Once the BPNN optimized by GA (GA-BPNN) is properly trained, it can provide the distribution of subsurface electrical conductivity (σ) in 0.1 s. We train the GA-BPNN using synthetic datasets generated by TEM forward modeling and assess its reliability using both synthetic and field data. Theoretical simulations demonstrate that compared with BPNN, the error of GA-BPNN on the inversion results of six samples is reduced by 23.2%. Furthermore, this method can provide reliable results even in the presence of noise in the TEM response. Finally, applying this inversion method to karst exploration with measured data proves the reliability and robustness of the proposed method. The proposed method can support quasi-real-time imaging of subsurface structures and provides a powerful tool for the interpretation of field TEM data. [ABSTRACT FROM AUTHOR]

The development of fast‐charging lithium‐ion batteries with high energy density is hindered by the sluggish Li+ transport and substantial polarization within graphite electrodes. Herein, this study proposes that the integrated design of liquid electrolyte and solid electrolyte, a dual‐phase electrolyte (DP‐electrolyte), can facilitate Li+ transport within a thick electrode. A 3D Li3PS4 (LPS) network is constructed within the graphite electrode to form the LPS/graphite electrode. This is achieved through the in situ conversion of the P4S16 into the LPS, a process introduced during the slurry processing. Both experimental findings and simulation outcomes indicate that this design mitigates the concentration polarization due to the improved Li+ transport capability with an overall high Li+ transference number within the electrode. With a high capacity of ≈3.1 mAh cm−2 attributed to the graphite electrode, the LiNi0.6Co0.2Mn0.2O2 (NCM622)||LPS/graphite cells demonstrate superior fast‐charging capability (4 C, 15 min, charging to ≈87.7%) and stable cycling performance (4 C, 700 cycles, ≈80% capacity retention). Furthermore, they exhibit commendable low‐temperature performance. The Ah‐level pouch cell achieves 87.5% recharge in 15 min with an energy density of ≈221.5 Wh kg−1. This work offers an alternative avenue for the advancement of fast‐charging lithium‐ion batteries with practical high energy density. [ABSTRACT FROM AUTHOR]

Background: Alternative splicing is a pivotal mechanism of post-transcriptional modification that contributes to the transcriptome plasticity and proteome diversity in metazoan cells. Although many splicing regulations around the exon/intron regions are known, the relationship between promoter-bound transcription factors and the downstream alternative splicing largely remains unexplored. Results: In this study, we present computational approaches to unravel the regulatory relationship between promoter-bound transcription factor binding sites (TFBSs) and the splicing patterns. We curated a fine dataset that includes DNase I hypersensitive site sequencing and transcriptomes across fifteen human tissues from ENCODE. Specifically, we proposed different representations of TF binding context and splicing patterns to examine the associations between the promoter and downstream splicing events. While machine learning models demonstrated potential in predicting splicing patterns based on TFBS occupancies, the limitations in the generalization of predicting the splicing forms of singleton genes across diverse tissues was observed with carefully examination using different cross-validation methods. We further investigated the association between alterations in individual TFBS at promoters and shifts in exon splicing efficiency. Our results demonstrate that the convolutional neural network (CNN) models, trained on TF binding changes in the promoters, can predict the changes in splicing patterns. Furthermore, a systemic in silico substitutions analysis on the CNN models highlighted several potential splicing regulators. Notably, using empirical validation using K562 CTCFL shRNA knock-down data, we showed the significant role of CTCFL in splicing regulation. Conclusion: In conclusion, our finding highlights the potential role of promoter-bound TFBSs in influencing the regulation of downstream splicing patterns and provides insights for discovering alternative splicing regulations. [ABSTRACT FROM AUTHOR]

A comprehensive study was conducted at a wave energy device test site located off the northeastern coast of Taiwan to assess the influence of oceanic currents on experimental equipment. A bottom-mounted 600 kHz acoustic Doppler current profiler, equipped with integrated temperature and pressure sensors, was deployed at a depth of approximately 31 m. This study, spanning from 6 June 2023 to 11 May 2024, recorded ocean current profiles by assembling data from 50 pings every 10 min, with a resolution of one meter per depth layer. The findings reveal that variations in water levels were predominantly influenced by the M2 tidal constituent, followed by the O1, K1, and S2 tides. Notably, seawater temperature fluctuations at the seabed were modulated by tides, especially the M2 tide. A significant drop in seawater temperature was also observed as the typhoon passed through the south of Taiwan. In terms of sea surface currents, the measured maximum current speed was 71.89 cm s−1, but the average current speed was only 15.47 cm s−1. Tidal currents indicated that the M4 and M2 tides were the most significant, with semimajor axes and inclination angles of 8.48 cm s−1 and 102.60°, and 7.00 cm s−1 and 97.76°, respectively. Seasonally, barotropic tidal currents were the strongest in winter. Additionally, internal tides were identified, with the first baroclinic mode being dominant. The zero-crossing depths varied between 14 and 18 m. During the summer, the M2 baroclinic tidal current displayed characteristics of the second baroclinic mode, with zero-crossing depths at approximately 7 m and 22 m. This node aligns with results from the empirical orthogonal function analysis and correlates with the depths' significant shifts in seawater temperature as measured by a conductivity, temperature, and depth instrument. Despite the velocities of internal tides not being strong, the directional variance between surface and bottom flows presents critical considerations for the deployment and operation of moored wave energy devices. [ABSTRACT FROM AUTHOR]

Forest–grassland ecotone (FGE) has essential ecological and economic value. Unfortunately, it is impacted greatly by environmental changes and anthropogenic disturbance, and is considered one of the most severely threatened biomes in China. To protect Chinese FGE, identifying its exact boundary and exploring its landscape structure dynamic are badly needed, especially on nationwide scale at one‐year temporal resolution. Here, we mapped the annual FGE distribution of China from 1990 to 2020, investigated its changing trends of area, location and landscape patterns, and revealed the underlying driving factors. Our results showed that FGE area over the 31 years totaled 1 011 870 km2, covering about 10.54% of China's land. The FGE area first increased from 1990 and peaked in 1999, and then kept decreasing until 2020. The FGE gravity center has moved accumulatively 590.15 km over the 31 years, with the net moving distance of 228.76 km southwestward. From 1990 to 2020, forest area increased continuously while grassland and cropland area decreased, but these three landscape types had been dominating the FGE. The increase in forest area was largely converted from grassland. The decline in grassland mainly resulted from its conversion into cropland and forest. Meanwhile, the conversion of cropland to grassland supplemented grassland loss to a certain extent. At landscape level, the total area with decreased fragmentation is larger than that with increased fragmentation. Returning Farmland to Grassland Project and land reclamation were primary drivers for changes of fragmentation in the northern and middle part of the FGE, while temperature and precipitation were primary drivers in southern part. Our results will improve the understanding into the dynamic trends of distribution and pattern of FGE at nationwide scale, and thus help to optimize the designing of ecological projects and protective schemes for FGE as a unique and integral biome. [ABSTRACT FROM AUTHOR]

Variation in emitted particle sizes between sources offers potential for source identification. Seven thousand two hundred particle size distributions collected in a single-family home were categorized into four classes: (1) smoking, (2) cooking, (3) household cleaning, and (4) background (no source). We created a multi-class classifier (neural network) to predict the presence of these three source types and background air. Number, surface, and volume concentration profiles (each with 16 particle size bins from 0.3 to 10 µm) were used as input features. Surface or volume concentration profiles were better predictors than number concentration profiles; accuracy was highest when concatenating the number, surface, and volume profiles (48 features). The model achieved ~ 98% accuracy in predicting the four classes when using a 10-unit hidden layer for the 48 input features (compared to ~ 66% for multinomial logistic regression). Smoking has the highest F-score among the four classes (0.999). We applied the model to time series of size-resolved concentrations for three successive indoor particle emissions (pan frying food, sweeping the floor, and smoldering marijuana). Time-varying probabilities of the four classes were visualized. We examined the effects of source, space, ventilation, and temperature/relative humidity on source identification. Using training examples from the single-family home, the model reasonably predicted smoking in another residence under different indoor settings (accuracies > 96%). This study applied, for the first time, the neural network method to identify patterns across different particle size distribution types (number, surface, and volume). It demonstrates the potential of using machine learning for source recognition of transient indoor aerosol emissions (e.g., identifying smoking in a rental property). [ABSTRACT FROM AUTHOR]

Fiber-optic sensors, such as fiber Bragg grating (FBG) sensors and fiber-optic interferometers, have excellent sensing capabilities for industrial, chemical, and biomedical engineering applications. This paper used machine learning to enhance the number of fiber-optic sensing placement points and promote the cost-effectiveness and diversity of fiber-optic sensing applications. In this paper, the framework adopted is the FBG cascading an interferometer, and a deep belief network (DBN) is used to demodulate the wavelength of the sampled complex spectrum. As the capacity of the fiber-optic sensor arrangement is optimized, the peak spectra from FBGs undergoing strain or temperature changes may overlap. In addition, overlapping FBG spectra with interferometer spectra results in periodic modulation of the spectral intensity, making the spectral intensity variation more complex as a function of different strains or temperature levels. Therefore, it may not be possible to analyze the sensed results of FBGs with the naked eye, and it would be ideal to use machine learning to demodulate the sensed results of FBGs and the interferometer. Experimental results show that DBN can successfully interpret the wavelengths of individual FBG peaks, and peaks of the interferometer spectrum, from the overlapping spectrum of peak-overlapping FBGs and the interferometer. [ABSTRACT FROM AUTHOR]

This work demonstrates the use of an erbium-doped fiber amplifier (EDFA), a tunable bandpass filter (TBF), and a tunable delay line interferometer (TDLI) to form a ring laser that produces multi-format, multi-wavelength laser beams. The TDLI serves as the core of the proposed laser generation system. TDLI harnesses the weak Fabry–Pérot (FP) interferences generated by its built-in 50/50 beamsplitter (BS) with unalterable filtering characteristics and the interferences with free spectral range (FSR) adjustable from each of its two outputs with nearly complementary phases to superpose and generate a variable interference standing wave. The interferometric standing wave and weak FP interferences are used to form a spatial-hole burning to promote the excitation of multi-format and multi-wavelength lasers. The proposed system enables dual-wavelength spacing ranging from 0.3 nm to 3.35 nm, with a switchable wavelength position at approximately 1527 nm to 1535 nm, providing flexible tunability. [ABSTRACT FROM AUTHOR]

Patients treated for oral cancer, may experience restricted mouth opening (trismus). Barriers such as cost have limited the utilization of traditional jaw stretching devices, and consequently, patients experience problems with swallowing, oral care, communication, and cancer surveillance. The safety and efficacy of Restorabite™, a new device designed to overcome these barriers, is evaluated prospectively over 12 months. This phase II investigator‐led trial included patients with chronic trismus underwent 10‐weeks of trismus therapy using Restorabite™. Safety, adherence, changes in mouth opening, and patient‐reported outcomes are presented. 114/120 participants with trismus completed the intervention, and 104 had their progress monitored for 12 months. Thirteen participants withdrew due to tumour recurrence. At the completion of the intervention, mouth opening improved by 10.4 mm (p <.001). This increased to 13.7 mm at 12 months (p <.001). Patient reported outcome all significantly improved and 47 participants were no longer classified as having trismus. There were no serious treatment related adverse events. In patients with trismus following head and neck cancer treatment, a 10‐week programme of jaw stretching exercises using Restorbite™ safely improves mouth opening and associated quality of life outcomes with high adherence and the benefits are maintained for 12‐months. [ABSTRACT FROM AUTHOR]

The rise of antibiotic resistance poses a significant public health crisis, particularly due to limited antimicrobial options for the treatment of infections with Gram‐negative pathogens. Here, an antimicrobial peptide (AMP) SR25 is characterized, which effectively kills both Gram‐negative and Gram‐positive bacteria through a unique dual‐targeting mechanism without detectable resistance. Meanwhile, an SR25‐functionalized hydrogel is developed for the efficient treatment of infected diabetic wounds. SR25 is obtained through genome mining from an uncultured bovine enteric actinomycete named Nonomuraea Jilinensis sp. nov. Investigations reveal that SR25 has two independent cellular targets, disrupting bacterial membrane integrity and restraining the activity of succinate:quinone oxidoreductase (SQR). In a diabetic mice wound infection model, the SR25‐incorporated hydrogel exhibits high efficacy against mixed infections of Escherichia coli (E. coli) and methicillin‐resistant Staphylococcus aureus (MRSA), accelerating wound healing. Overall, these findings demonstrate the therapeutic potential of SR25 and highlight the value of mining drugs with multiple mechanisms from uncultured animal commensals for combating challenging bacterial pathogens. [ABSTRACT FROM AUTHOR]

Deploying distributed fiber-optic sensor (DFOS) technology to gather environmental parameters over expansive areas is an essential monitoring strategy in the context of comprehensive searches for anomalous places. This study utilizes a single temperature measurement channel within a commercial Raman-based distributed temperature sensing (RDTS) interrogator and divides it into two separate, uncorrelated paths to enable spatial duplex temperature measurements. The distinction between temperature events corresponding to each path in the dual separate path (DSP) in RDTS can be achieved when temperature events are concurrently occurring in the DSP. Additionally, the RDTS–DSP solution may integrate free space optics (FSO) into its fiber path, which serves to enhance the user-friendliness, scalability, and cost-effectiveness of DFOS technology. An RDTS measurement channel can effectively function as a DSP, thus doubling the RDTS measurement pathway, and can be combined with FSO to significantly improve RDTS performance. [ABSTRACT FROM AUTHOR]

This work is focused on performance computation of high speed rotor bearing system with partial composite texture. Since its viscosity at varying speeds affects working performance in different partial composite texture, therefore at design and development stage, it is necessary to know the composite texture and thermal effect acting on rotor‐bearing system that causes variation of performance. The effects of partial composite texture size and position on the performance of the bearing are studied. After the optimal structural parameters are determined, the effects of the partial composite texture and fluid thermos structure coupling on the bearing capacity, stiffness, and friction coefficient of the oil film are analysed. The results show that after considering the influence of thermal effect, the performance enhancement of composite texture bearing is better than that of smooth bearing. Considering the temperature effect, the bearing capacity of the composite textured bearing is increased by 51.4% compared with that of the smooth bearing, and the friction coefficient is reduced to 22.4%, which is better than the value without considering the temperature effect, the accuracy of the results is verified by experiments. This study provides a theoretical basis for the design of hydrostatic bearing and improving its performance. [ABSTRACT FROM AUTHOR]

Introduction While retail sales and retailer inspection studies generally indicate high compliance with state sales restrictions on Nicotine Vaping Products (NVPs) within the restricted area, studies using survey data generally indicate that most users could readily continue gaining access to restricted NVPs. Our study bridges a gap in the current literature and investigates the potential role of cross-state border purchases to evade state emergency NVP sales restrictions in 2019. Aims and Methods The study sample was restricted to NVP sales from the states neighboring Massachusetts, Rhode Island, and Washington, three states that implemented all NVP or flavored NVP sales restrictions in 2019. Among these neighboring states, the 2019 weekly county-level NVP sales by flavors (tobacco, mint/menthol, and other flavors) were compiled using Nielsen Scanner data. A quasi-experimental, comparison group pre–post study design was used to study the impacts of NVP sales restrictions on cross-state border NVP purchases. Results Weekly NVP sales for border counties significantly increased in response to the MA, RI, and WA bans for tobacco flavored (56%, 45%, 14%, respectively), menthol/mint flavored (51%, 2%, 41%, respectively), and other flavored (79%, 3%, 4%, respectively) products, compared to sales for non-border counties (all p -values <.01). Conclusions Our study identified significant cross-state border NVP purchases in all studied states to circumvent NVP emergency sales restrictions in response to the EVALI outbreak. Policymakers should factor in these purchasing behaviors to evade sales restrictions when evaluating any future potential policies at the state or local levels. Implications While retail sales data and retailer inspections indicate high compliance with Nicotine Vaping Product (NVP) flavor sales restrictions from major retail outlets, survey data obtain mixed findings on the effects of sales restrictions on vaping behaviors. Our study identified a significant increase in cross-state border NVP purchases to circumvent NVP sales restrictions in 2019, consistent across all three settings of Massachusetts, Rhode Island, and Washington. Policymakers should factor in these cross-state border NVP purchases in response to sales restrictions when evaluating any future potential NVP sales restrictions. [ABSTRACT FROM AUTHOR]

Ultra-precision machining (UPM) of Ti-6Al-4V alloy is widely regarded as a challenging material processing due to excessive tool wear and chemical reactivity of the tool and workpiece. Tool wear has a significant influence on the surface quality and also causes damage to the substrate. Therefore, it is critical to consider the tool condition during diamond turning, especially as precision machining moves toward intelligent systems. Consequently, there is a need for effective ways for in-process tool wear monitoring in UPM. This study aims to monitor the diamond tool wear using time-frequency-based wavelet analysis on vibrational signals acquired during the machining of Additively Manufactured (AM) Ti6Al4V alloy. The analysis employed Daubechies wavelet (db4, level 8) to establish a correlation between the Standard Deviation (SD) of the magnitude in the decomposed vibrational signal obtained from both the fresh and used tools. The analysis revealed that at a feed rate of 1 mm/min, the change in SD is 32.3% whereas at a feed rate of 5 mm/min, the change in SD is 8.4%. Furthermore, the flank wear and microfractures are observed using a scanning electron microscope on the respective flank and rake face of the diamond tool. [ABSTRACT FROM AUTHOR]

Additive Manufacturing (AM) has shown excellent research potential for biomedical implants, complex aerofoil structures, military applications, high-pressure cryogenic vessels, and automobile components. The mechanical properties exhibited by the additively manufactured Ti6Al4V ELI alloy components are significantly different from traditionally manufactured Ti6Al4V alloy due to the material anisotropy, orientation of the microstructure, and variation in heat treatments. Among AM techniques, SLM (Selective laser melting) offers unparalleled design flexibility with minimum impurities and high reproducibility. However, post-processing of additive manufactured components is essential due to their poor surface finish and lack of dimensional accuracy. Ti6Al4V ELI (Extra Low Interstitials) alloy is a difficult-to-cut material in Ultra-Precision Machining (UPM) due to its excessive tool wear, hardness, and chemical reactivity. Optimizing machining parameters for better surface finish by UPM is time-consuming and often not economical. Modeling and simulation provide a low-cost approach for the investigation of machining. In this work, a series of cutting experiments have been carried out on additively manufactured Ti6Al4V ELI alloy to study the cutting mechanism during UPM. In addition, Finite Element Model (FEM) is employed to understand the chip formation and cutting forces in UPM with a built-in Johnson-Cook (JC) model and a Johnson-Cook-TANH (JC-TANH) vectorized user-defined material subroutine (VUMAT) model. Cutting forces corresponding to the JC model and JC-TANH are examined with the experimental forces in literature, and the results are found to be fairly close. [ABSTRACT FROM AUTHOR]

This study introduces a novel meta-learning method to enhance diabetes detection using wearable sensor systems in smart health applications. Wearable sensor technology often needs to operate accurately across a wide range of users, each characterized by unique physiological and behavioral patterns. However, the specific data for a particular application or user group might be scarce. Moreover, collecting extensive training data from wearable sensor experiments is challenging, time-consuming, and expensive. In these cases, meta-learning can be particularly useful. This model can quickly adapt to the nuances of new users or specific applications with minimal data. Therefore, to solve the need for a huge amount of training data and to enable the application of artificial intelligence (AI) in data-scarce scenarios, a meta-learning method is proposed. This meta-learning model has been implemented to forecast diabetes, resolve cross-talk issues, and accurately detect R peaks from overlapping electrocardiogram (ECG) signals affected by movement artifacts, poor electrode contact, electrical interference, or muscle activity. Motion artifacts from body movements, external conditions such as temperature, humidity, and electromagnetic interference, and the inherent quality and calibration of the sensor can all contribute to noise. Contact quality between the sensor and the skin, signal processing errors, power supply variations, user-generated interference from activities like talking or exercising, and the materials used in the wearable device also play significant roles in the overall noise in wearable sensor data and can significantly distort the true signal, leading to erroneous interpretations and potential diagnostic errors. Furthermore, discrete wavelet transform (DWT) was also implemented to improve the quality of the data and enhance the performance of the proposed model. The demonstrated results confirmed that with only a limited amount of target data, the proposed meta-learning and DWT denoising method can adapt more quickly and improve the detection of diabetes compared to the traditional method. Therefore, the proposed system is cost-effective, flexible, faster, and adaptable, reduces the need for training data, and can enhance the accuracy of chronic disease detection such as diabetes for smart health systems. [ABSTRACT FROM AUTHOR]

A palladium-catalyzed one-pot amino-sulfonylation of aryl iodide derivatives with thiourea dioxide, PdCl2 dppf, and one-pot added hydroxylamine- O -sulfonic acid is presented. This amino-sulfonylation gave structure diversity to aryl primary sulfonamides and features good functional group compatibility, mild reaction conditions, excellent regioselectivity, and moderate to good yields. The robustness and potential of this method have also been successfully demonstrated by late-stage elaboration and gram-scale reaction. This approach achieves the divergent construction of the complex core structures that are prevalent in highly valuable natural products such as Sulpiride, Venetoclax, and Furosemide-. [ABSTRACT FROM AUTHOR]

Reconstructing critical-sized craniofacial bone defects is a global healthcare challenge. Current methods, like autologous bone transplantation, face limitations. Bone tissue engineering offers an alternative to autologous bone, with traditional approaches focusing on stimulating osteogenesis via the intramembranous ossification (IMO) pathway. However, IMO falls short in addressing larger defects, particularly in clinical scenarios where there is insufficient vascularisation. This review explores redirecting bone regeneration through endochondral ossification (ECO), a process observed in long bone healing stimulated by hypoxic conditions. Despite its promise, gaps exist in applying ECO to bone tissue engineering experiments, requiring the elucidation of key aspects such as cell sources, biomaterials and priming protocols. This review discusses various scaffold biomaterials and cellular sources for chondrogenesis and hypertrophic chondrocyte priming, mirroring the ECO pathway. The review highlights challenges in current endochondral priming and proposes alternative approaches. Emphasis is on segmental mandibular defect repair, offering insights for future research and clinical application. This concise review aims to advance bone tissue engineering by addressing critical gaps in ECO strategies. [ABSTRACT FROM AUTHOR]

Environmental changes can trigger endoplasmic reticulum (ER) stress and misfolded protein accumulation, potentially leading to pre-eclampsia (PE). Amyloid-β (Aβ) is a crucial misfolded protein that can overactivate autophagy. Our study assessed the expression of Aβ1−42 and autophagic activity in PE placental tissues and trophoblasts under ER stress. Placental tissues were surgically collected from normal pregnant women (NP) and pregnant women with late-onset PE (LOPE) delivering through cesarean section. The expression levels of Aβ1−42 were detected in both PE and NP placental tissues, as well as in tunicamycin (TM)-induced HTR-8/SVneo cells. Autophagy-related proteins, such as Beclin-1, the ratio of LC3-II to LC3-I, ATG5, and SQSTM1/p62 in the placental tissues and HTR-8/SVneo cells were measured by Western blot. The number and morphology of autophagosomes were observed using transmission electron microscopy (TEM). Potential targets associated with the unfolded protein response (UPR) in the placental tissues of NP and PE cases were screened using PCR Arrays. The misfolded protein was significantly upregulated in the PE group. In both PE placental tissues and TM-induced HTR-8/SVneo cells, not only was Aβ1−42 upregulated, but also Beclin-1, ATG5, and LC3BII/I were significantly increased, accompanied by an increase in autophagosome count, while SQSTM1/P62 was downregulated. A total of 17 differentially expressed genes (DEGs) associated with the UPR were identified, among which elevated calnexin (CANX) was validated in the placenta from both PE and TM-induced HTR-8/SVneo cells. Autophagy is significantly upregulated in PE cases due to ER stress-induced Aβ1−42 accumulation, likely mediated by autophagy-related proteins involved in the UPR. [ABSTRACT FROM AUTHOR]

This paper proposes a novel approach to enhance the multichannel fiber optic sensing systems by integrating an Inverse Fast Fourier Transform-based Deep Neural Network (IFFT-DNN) to accurately predict sensor responses despite signals overlapping and crosstalk between sensors. The IFFT-DNN leverages both frequency and time domain information, enabling a comprehensive feature extraction which enhances the prediction accuracy and reliability performance. To investigate the IFFT-DNN's performance, we propose a multichannel water level sensing system based on Free Space Optics (FSO) to measure the water level at multiple points in remote areas. The experimental results demonstrate the system's high precision, with a Mean Absolute Error (MAE) of 0.07 cm, even in complex conditions. Hence, this system provides a cost-effective and reliable remote water level sensing solution, highlighting its practical applicability in various industrial settings. [ABSTRACT FROM AUTHOR]

An established way to tackle model nonlinearities in projection-based model reduction is via relying on partial information. This idea is shared by the methods of gappy proper orthogonal decomposition (POD), missing point estimation (MPE), masked projection, hyper reduction, and the (discrete) empirical interpolation method (DEIM). The selected indices of the partial information components are often referred to as “magic points.” The original contribution of the work at hand is a novel randomized greedy magic point selection. It is known that the greedy method is associated with minimizing the norm of an oblique projection operator, which, in turn, is associated with solving a sequence of rank-one SVD update problems. We propose simplification measures so that the resulting greedy point selection has the following main features: (1) The inherent rank-one SVD update problem is tackled in a way, such that its dimension does not grow with the number of selected magic points. (2) The approach is online efficient in the sense that the computational costs are independent from the dimension of the full-scale model. To the best of our knowledge, this is the first greedy magic point selection that features this property. We illustrate the findings by means of numerical examples. We find that the computational cost of the proposed method is orders of magnitude lower than that of its deterministic counterpart. Nevertheless, the prediction accuracy is just as good if not better. When compared to a state-of-the-art randomized method based on leverage scores, the randomized greedy method outperforms its competitor. [ABSTRACT FROM AUTHOR]

The hypervapotron structure was considered to be a feasible configuration to meet the high heat-dissipating requirement of divertors in nuclear fusion devices. In this work, symmetric CuCrZr-based transverse microchannels (TMHC) and longitudinal microchannels (LMHC) with an integrated hypervapotron channel were proposed and manufactured, and subcooled flow boiling experiments were conducted using deionized water at an inlet temperature of 20 °C with a traditional flat-type hypervapotron channel (FHC) for comparison. The LMHC and TMHC obtained lower wall temperatures than the FHC for all conditions, and the TMHC yielded the lowest temperatures. The heat transfer coefficients of the LMHC and TMHC outperformed the FHC due to the enlarged heat transfer area, and the TMHC had the greatest heat transfer coefficient (maximumly increased by 132% compared to the FHC) because the transverse-arranged microchannels were conductive, promoting the convection and liquid replenishment ability by introducing branch flow between fins; however, the microchannels of the LMHC were insensible to flow velocities due to the block effect of longitudinal microchannels. The LMHC obtained the largest pressure drop, and the pressure drop for the FHC and TMHC were comparable since the transverse-placed microchannels had little effect on frictional pressure loss. The TMHC attained the greatest comprehensive thermohydraulic performance which might bring significant insight to the structural design of hypervapotron devices. [ABSTRACT FROM AUTHOR]

Forest stand mean height is a critical indicator in forestry, playing a pivotal role in various aspects such as forest inventory estimation, sustainable forest management practices, climate change mitigation strategies, monitoring of forest structure changes, and wildlife habitat assessment. However, there is currently a lack of large-scale, spatially continuous forest stand mean height maps. This is primarily due to the requirement of accurate measurement of individual tree height in each forest plot, a task that cannot be effectively achieved by existing globally covered, discrete footprint-based satellite platforms. To address this gap, this study was conducted using over 1117 km2 of close-range Light Detection and Ranging (LiDAR) data, which enables the measurement of individual tree height in forest plots with high precision. Besides, this study incorporated spatially continuous climatic, edaphic, topographic, vegetative, and Synthetic Aperture Radar data as explanatory variables to map the tree-based arithmetic mean height (ha) and weighted mean height (hw) at 30 m resolution across China. Due to limitations in obtaining basal area of individual tree within plots using UAV LiDAR data, this study calculated weighted mean height through weighting an individual tree height by the square of its height. In addition, to overcome the potential influence of different vegetation divisions at large spatial scale, we also developed a machine learning-based mixed-effects model to map forest stand mean height across China. The results showed that the average ha and hw across China were 11.3 m and 13.3 m with standard deviations of 2.9 m and 3.3 m, respectively. The accuracy of mapped products was validated utilizing LiDAR and field measurement data. The correlation coefficient (푟) for ha and hw ranged from 0.603 to 0.906 and 0.634 to 0.889, while RMSE ranged from 2.6 to 4.1 m and 2.9 to 4.3 m, respectively. Comparing with existing forest canopy height maps derived using the area-based approach, it was found that our products of ha and hw performed better and aligned more closely with the natural definition of tree height. The methods and maps presented in this study provide a solid foundation for estimating carbon storage, monitoring changes in forest structure, managing forest inventory, and assessing wildlife habitat availability. The dataset constructed for this study is publicly available at https://doi.org/10.5281/zenodo.12697784 (Chen et al., 2024). [ABSTRACT FROM AUTHOR]

Background: TBK1 positively regulates the growth factor-mediated mTOR signaling pathway by phosphorylating mTOR. However, it remains unclear how the TBK1-mTOR signaling pathway is regulated. Considering that STING not only interacts with TBK1 but also with MARCH1, we speculated that MARCH1 might regulate the mTOR signaling pathway by targeting TBK1. The aim of this study was to determine whether MARCH1 regulates the mTOR signaling pathway by targeting TBK1. Methods: The co-immunoprecipitation (Co-IP) assay was used to verify the interaction between MARCH1 with STING or TBK1. The ubiquitination of STING or TBK1 was analyzed using denatured co-immunoprecipitation. The level of proteins detected in the co-immunoprecipitation or denatured co-immunoprecipitation samples were determined by Western blotting. Stable knocked-down cells were constructed by infecting lentivirus bearing the related shRNA sequences. Scratch wound healing and clonogenic cell survival assays were used to detect the migration and proliferation of breast cancer cells. Results: We showed that MARCH1 played an important role in growth factor-induced the TBK1- mTOR signaling pathway. MARCH1 overexpression attenuated the growth factor-induced activation of mTOR signaling pathway, whereas its deficiency resulted in the opposite effect. Mechanistically, MARCH1 interacted with and promoted the K63-linked ubiquitination of TBK1. This ubiquitination of TBK1 then attenuated its interaction with mTOR, thereby inhibiting the growth factor-induced mTOR signaling pathway. Importantly, faster proliferation induced by MARCH1 deficiency was weakened by mTOR, STING, or TBK1 inhibition. Conclusion: MARCH1 suppressed growth factors mediated the mTOR signaling pathway by targeting the STING-TBK1-mTOR axis. [ABSTRACT FROM AUTHOR]

Background: The present study compares the anatomical and functional outcomes (best-corrected visual acuity (BCVA) and central macular thickness (CMT)) among membrane peeling with or without SF6 tamponade in patients with epiretinal membrane. Methods: We retrospectively reviewed patients diagnosed with macular pucker who underwent pars plana vitrectomy and membrane peeling in a tertiary center in Taiwan from January 2021 to December 2022. Subjects were categorized into with or without SF6 tamponade groups (SF6 group and BSS group). Postoperative intraocular pressure and complications were documented. Logistic regression analyses were performed to identify the prognostic factors during follow-up. Results: A total of 89 eyes were enrolled, including 34 eyes in the BSS group and 55 eyes in the SF6 group. The mean age was 66 years old, and a female predilection was demonstrated. Both groups possessed statistically significant improvement in BCVA and CMT after the operation. There was no significant difference in CMT between the groups at any time of observation, yet we observed significant differences in baseline BCVA and BCVA at last follow-up among the two groups. Both groups yielded an approximate enhancement of LogMAR 0.3 in BCVA postoperatively. There was no significant difference noted in postoperative IOP between the two groups. Conclusion: Membrane peeling with or without SF6 tamponade yields comparable outcomes anatomically and functionally. This may indicate that SF6 tamponade for idiopathic macular pucker surgery may not provide extra benefit, and therefore warrants reconsideration as standard procedure. [ABSTRACT FROM AUTHOR]

In this work, we demonstrate multi-channel GaN varactors with enhanced quality-factor (Q-factor) and cutoff frequency (f0) and present a comprehensive investigation of their current conduction mechanisms. The varactors were based on 1x-, 2x-, and 3x-channel GaN-on-SiC epitaxy with excellent channel conductivity, showing great enhancement of ∼270% both in Q-factor and in f0, thanks to the reduced resistance and capacitance by multi-channels in AC conduction. The DC leakage current (I) in the three types of devices is dominated by Poole–Frenkel (PF) emission and trap-assisted tunneling, before the depletion of the topmost channel and after the depletion of the bottommost channel, respectively. The I in multi-channel devices is dominated by two-dimensional variable range hopping of electrons along the vertical direction between channels, when the topmost channel is depleted while the bottommost channel is not. The analysis is supported by excellent agreement between experimental results and theoretical models, along with activation energies (EA) quantitatively and statistically determined, presenting a promising technology with key understandings for future performance enhancement. [ABSTRACT FROM AUTHOR]

The selection of implants for fixing unstable femoral neck fractures (FNF) remains contentious. This study employs finite element analysis to examine the biomechanics of treating Pauwels type III femoral neck fractures using cannulated compression screws (3CS), biplane double-supported screw fixation (BDSF), and the femoral neck system (FNS). A three-dimensional model of the proximal femur was developed using computed tomography scans. Fracture models of the femoral neck were created with 3CS, BDSF, and FNS fixations. Von Mises stress on the proximal femur, fracture ends, internal fixators, and model displacements were assessed and compared across the three fixation methods (3CS, BDSF, and FNS) during the heel strike of normal walking. The maximum Von Mises stress in the proximal fragment was significantly higher with 3CS fixation compared to BDSF and FNS fixations (120.45 MPa vs. 82.44 MPa and 84.54 MPa, respectively). Regarding Von Mises stress distribution at the fracture ends, the highest stress in the 3CS group was 57.32 MPa, while BDSF and FNS groups showed 51.39 MPa and 49.23 MPa, respectively. Concerning implant stress, the FNS model exhibited greater Von Mises stress compared to the 3CS and BDSF models (236.67 MPa vs. 134.86 MPa and 140.69 MPa, respectively). Moreover, BDSF displayed slightly lower total displacement than 3CS fixation (7.19 mm vs. 7.66 mm), but slightly higher displacement than FNS (7.19 mm vs. 7.03 mm). This study concludes that BDSF outperforms 3CS fixation in terms of biomechanical efficacy and demonstrates similar performance to the FNS approach. As a result, BDSF stands as a dependable alternative for treating Pauwels type III femoral neck fractures. [ABSTRACT FROM AUTHOR]

This article builds on China's rich recorded history to present a newly constructed dataset of environmental events at the county-level for the period 1368 to 1911. Essential to the dataset construction is the use of recently developed AI techniques, including new optical character recognition, lexical analysis based on machine learning, and word frequency analysis. The result is that environmental information was extracted from different sources, comprised of structured collections of printed historical records, and then combined and parameterized to construct a county-level environmental dataset that includes information on the incidence of cold spells, droughts, floods, and wind events. The dataset is validated and Geographic Information Systems are used to manage and present the spatially disaggregated data. The new data are expected to benefit future researchers looking to study historical environmental extreme events, or examine their impact on other aspects of Chinese economy and society. [ABSTRACT FROM AUTHOR]

The extratropical stage of Hurricane Ida (2021) brought extreme subdaily rainfall and devastating flooding to parts of eastern Pennsylvania, New Jersey, and New York. We investigate the predictability and character of this event using 31-member ensembles of perturbed initial condition hindcasts with the Tropical Atlantic version of GFDL's System for High-resolution prediction on Earth-to-Local Domains (T-SHiELD), a ∼13-km global weather forecast model with a ∼3-km nested grid. At lead times of up to 4 days, the ensembles are able to capture the most extreme observed hourly and daily rainfall accumulations but are negatively biased in the spatial extent of heavy precipitation. Large intraensemble differences in the magnitudes and locations of simulated extremes suggest that although impacts were highly localized, risks were widespread. In Ida's tropical stage, interensemble spread in extreme hourly rainfall is well predicted by large-scale moisture convergence; by contrast, in Ida's extratropical stage, the most extreme rainfall is governed by mesoscale processes that exhibit chaotic and diverse forms across the ensembles. Our results are relevant to forecasting and communication in advance of extratropical transition and imply that flood preparedness efforts should account for the widespread possibility of severe localized impacts. Significance Statement: After making landfall in Louisiana, Hurricane Ida (2021) transitioned to an extratropical storm which brought extreme rainfall and unprecedented flooding to parts of the northeastern United States. To what extent were these impacts knowable in advance? We use a numerical weather model with very high resolution to produce ensemble hindcasts—simulations of a past weather event initialized with tiny perturbations to the initial conditions, representing dozens of equally plausible versions of Ida's extratropical stage. We find that the observed hourly and daily rainfall maxima fall within the simulated outcomes of ensembles initialized with lead times of about 4 days or less. The location and intensity of the heaviest rainfall vary widely across these ensembles, suggesting that many locations across the Northeast were exposed to some likelihood of extreme rainfall. [ABSTRACT FROM AUTHOR]

Background: Endocrine-disrupting chemicals (EDCs) are pervasive in everyday environments. The impacts of these chemicals, along with EDC-related lifestyle and dietary habits on neurocognitive function, are not well understood. Methods: The Chang Gung Community Medicine Research Center conducted a cross-sectional study involving 887 participants. From this initial cohort, 120 individuals were selected based on their EDC exposure scores for detailed analysis. Among these, 67 participants aged 55 years or older were further chosen to undergo cognitive impairment assessments using the Ascertain Dementia-8 (AD-8) questionnaire. Results: These 67 older participants did not significantly differ in age, albuminuria, or estimated glomerular filtration rate compared to those with lower impairment scores. This study revealed that mono-(2-ethylhexyl) phthalate (MEHP) levels (8.511 vs. 6.432 µg/g creatinine, p = 0.038) were associated with greater risk of cognitive impairment (AD-8 ≥ 2). Statistical models adjusting for age, gender, and diabetes indicated that MEHP levels positively correlated with AD-8 scores, achieving statistical significance in more comprehensive models (β ± SE: 0.160 ± 0.076, p = 0.042). Logistic regression analysis underscored a significant positive association between high MEHP levels and higher AD-8 scores (odds ratio: 1.217, p = 0.006). Receiver operating characteristic curves highlighted the association of high MEHP levels and EDC exposure scores for significant cognitive impairment, with areas under the curve of 66.3% and 66.6%, respectively. Conclusion: Exposure to EDCs, specifically di-(2-ethylhexyl) phthalate, the precursor to MEHP, may be associated with neurocognitive impairment in middle-aged and older adults. [ABSTRACT FROM AUTHOR]

Objective: Segmental bone defect animal studies require stable fixation which is a continuous experimental challenge. Large animal models are comparable to the human bone, but with obvious drawbacks of housing and costs. Our study aims to utilize CAD and 3D printing in the construction of a stable and reproducible segmental bone defect animal mode. Methods: CAD-aided 3D printed surgical instruments were incorporated into the construction of the animal model through preoperative surgical emulation. 20 3D printed femurs were divided into either experimental group using 3D surgical instruments or control group. In Vitro surgical time and accuracy of fixation were analysed and compared between the two groups. A mature surgical plan using the surgical instruments was then utilized in the construction of 3 segmental bone defect Beagle models in vivo. The Beagles were postoperatively assessed through limb function and imaging at 1, 2 and 3 months postoperatively. Results: In vitro experiments showed a significant reduction in surgical time from 40.6 ± 14.1 (23–68 min) to 26 ± 4.6 (19–36 min) (n = 10, p < 0.05) and the accuracy of intramedullary fixation placement increased from 71.6 ± 23.6 (33.3–100) % to 98.3 ± 5.37 (83–100) %, (n = 30, p < 0.05) with the use of CAD and 3D printed instruments. All Beagles were load-bearing within 1 week, and postoperative radiographs showed no evidence of implant failure. Conclusion: Incorporation of CAD and 3D printing significantly increases stability, while reducing the surgical time in the construction of the animal model, significantly affecting the success of the segmental bone defect model in Beagles. [ABSTRACT FROM AUTHOR]