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This book is ideal for practicing engineers working in design or packaging at LED companies and graduate students preparing for work in industry. This book also provides a helpful introduction for advanced undergraduates, graduates, researchers, lighting designers, and product managers interested in the fundamentals of LED design and production.

There have been many studies on neuromuscular adaptation after anterior cruciate ligament (ACL) reconstruction, while the understanding of muscle activation patterns in unreconstructed patients with ACL rupture is still limited. The aim of this study was to investigate the lower limb electromyographic characteristics of unreconstructed patients with complete ACL rupture in a single-legged hopping landing task in order to deepen the understanding of motor control strategies in the ACL-deficient state and to provide a reference for rehabilitation assessment and intervention. Forty-two subjects were recruited for this study using a case-control design, with an ACL injury group ( n  = 21) of patients with unilateral non-contact complete rupture without reconstruction and a control group ( n  = 21) of healthy individuals matched for gender, dominant leg, and level of exercise. All subjects completed a single-leg hop landing task and synchronized Noraxon Ultium surface EMG signals with Bertec force plate data via the QUALISYS 3D motion capture system. EMG data were recorded from the lateral femoral (VL), medial femoral (VM), biceps femoris (BF), semitendinosus (ST), and gluteus maximus (Gmax) muscles before and after the landing for 100 ms each. Calculated metrics included activation onset time (onset-IC), peak appearance time (peak-IC), activation duration, and standardized root mean square (RMS) values. Data were analyzed by two-way ANOVA or nonparametric Scheirer-Ray-Hare test, and the significance level was set at p  < 0.05. BF ( p  = 0.0409) and Gmax ( p  = 0.0469) sustained activation of the dominant leg in the injury group was significantly longer than that of the dominant leg in the control group. The onset-IC of BF ( p  = 0.0457), ST ( p  = 0.0277), and Gmax ( p  = 0.0192) of the dominant leg in the injury group was significantly earlier than that of the dominant leg in the control group. The peak-IC of BF ( p  = 0.0457) and ST ( p  = 0.0280) of the dominant leg in the injury group was significantly later than that of the dominant leg in the control group. The peak RMS of VL ( p  = 0.0171), VM ( p  = 0.0054), and Gmax ( p  = 0.0003) in the dominant leg of the injury group was significantly lower than that of the dominant leg of the control group in 100 ms after IC. Unreconstructed patients, averaging 18 months after ACL injury, continued to maintain a similar muscle pre-activation sequence as healthy individuals during the jump landing task, but showed a prolonged activation duration and reduced activation intensity, suggesting that neuromuscular activity was adjusted to maintain the kinematic profile. The delay in the peak of the posterior muscle groups (especially BF and ST) may be used to synergize tibial rearward movement and reduce forward movement and internal rotation, thus constituting a compensatory protective mechanism. The results of this study provide evidence for neuromuscular adaptation in the ACL-deficient state and are informative for preoperative functional assessment and rehabilitation intervention strategies.

Antibacterial activity is one of the most vital characteristics for Titanium (Ti) dental implants. Coating antibacterial material onto Ti surfaces is an effective approach to enhance their intrinsic antibacterial ability. However, a cost-effective but efficient coating strategy for realizing this objective still remains challenging. In this study, we proposed a novel implant surface modification strategy for coating silver nanoparticles onto the porous Ti surface via a facile electron beam evaporation (EBE) approach. Porous Ti surfaces were firstly prepared by sand-blasting large grit acid-etching (SLA) process. Then, the silver nanoparticles coating thickness on the porous Ti surface was adjusted and optimized by altering the duration of EBE process. Consequently, composite porous Ti surfaces with different silver thicknesses were synthesized. Polished Ti (PT) surface without SLA or EBE process was also prepared as the controlled blank group. The surface characterizations were analyzed by SEM, AFM, and XPS. After that, the antibacterial properties of all groups were tested with bacteria counting method, bacterial viability test, live/dead bacterial staining, and SEM examination. Results show that silver nanoparticles were uniformly distributed on the porous Ti surfaces after the SLA and EBE processes. After being incorporated with silver nanoparticles, the composite surfaces successfully inhibited the growth of Escherichia coli (E. coli) and Staphylococcus aureus (S. aureus). The antibacterial ratio (AR) values of SLA-Ag groups increased with the increasing silver thickness and are significantly higher than those of PT and SLA groups. Therefore, by the SLA and EBE processes, the composite porous Ti surfaces modified with silver nanoparticles coatings demonstrate superior antibacterial property compared with pure Ti surfaces, which is highly promising for enhancing the antibacterial functions of dental implants.

This study utilized NHANES data from 2007 to 2018 to investigate the correlation between frailty and the Conicity Index (CI) in individuals aged 60 and above in the United States. The study used NHANES data from 2007 to 2018.CI was calculated as CI = wc / [0.109 × sqrt(bw / Height)]. Frailty was assessed by the frailty index (≥ 0.25). Weighted multivariate logistic regression analysis, subgroup analyses, and interaction tests were used to investigate the connection between CI and the prevalence of frailty. Generalized additive modeling (GAM) was employed to address any non-linear patterns, and the predictive capability of CI for frailty was evaluated by receiver operating characteristic (ROC) analysis. With a 69% rise in the prevalence of frailty for every 0.1 unit increase in the fully adjusted model, the results demonstrated a strong and positive relationship between CI and frailty prevalence (OR: 1.69, 95% CI: 1.53,1.86; P < 0.001). When CI was categorized, the group with the highest CI had a significantly higher prevalence of frailty than the group with the lowest CI (OR = 2.79, 95% CI: 2.22,3.51; P < 0.001). The association between CI and prevalence of frailty was significant in all subgroups. In addition, statistically significant interactions were present in most subgroups. When the CI > reached 1.35, the GAM model demonstrated a threshold effect and a significant nonlinear connection, with a 105% rise in the prevalence of frailty for every 0.1 unit increase in CI. In the male group, CI was a significantly greater indicator of the prevalence of frailty than both BMI and WC. According to this study, frailty in older persons is substantially correlated with a higher CI. Although greater confirmation in large-scale prospective research is required, this study indicates that increased CI is a more reliable predictor of the prevalence of frailty in older men and is significantly linked with its occurrence.

Wavelength-selective thermal emitters (WS-TEs) have been frequently designed to achieve desired target emissivity spectra, as a typical emissivity engineering, for broad applications such as thermal camouflage, radiative cooling, and gas sensing, etc. However, previous designs require prior knowledge of materials or structures for different applications and the designed WS-TEs usually vary from applications to applications in terms of materials and structures, thus lacking of a general design framework for emissivity engineering across different applications. Moreover, previous designs fail to tackle the simultaneous design of both materials and structures, as they either fix materials to design structures or fix structures to select suitable materials. Herein, we employ the deep Q-learning network algorithm, a reinforcement learning method based on deep learning framework, to design multilayer WS-TEs. To demonstrate the general validity, three WS-TEs are designed for various applications, including thermal camouflage, radiative cooling and gas sensing, which are then fabricated and measured. The merits of the deep Q-learning algorithm include that it can (1) offer a general design framework for WS-TEs beyond one-dimensional multilayer structures; (2) autonomously select suitable materials from a self-built material library and (3) autonomously optimize structural parameters for the target emissivity spectra. The present framework is demonstrated to be feasible and efficient in designing WS-TEs across different applications, and the design parameters are highly scalable in materials, structures, dimensions, and the target functions, offering a general framework for emissivity engineering and paving the way for efficient design of nonlinear optimization problems beyond thermal metamaterials. We proposed a general deep reinforcement learning framework to design materials and structures simultaneously for wavelength-selective thermal emitters with broad applications in emissivity engineering.

Marine engineering thick plates are essential structural materials for large vessels and offshore platforms, and optimizing their manufacturing processes is critical for advancing marine equipment. This study examined the microstructural and property variations in 120 mm-thick S460 plates fabricated by thermo-mechanical controlled processing (TMCP). A finite element model was developed to simulate the cooling phase, enabling the prediction of the internal cooling path in the thick plate. An optimized cooling scheme was proposed, which was validated against the model and implemented. The following key results were obtained: (1) Under the initial cooling parameters (initial temperature: 715 °C, duration: 130 s), the 60 mm depth toughness was severely compromised, as evidenced by a low −40 °C impact energy of 59 J, significantly lower than values observed at the10 mm and 30 mm depth positions. Microstructural analysis revealed that the 60 mm depth region was dominated by ferritic bainite and pearlite, with a pearlite content of 8.7%. Numerical simulations further indicated a 60 mm depth cooling rate of 1.10 °C/s under these conditions. (2) Model predictions confirmed the original 60 mm depth cooling rate of 1.10 °C/s. The optimized process increased the initial cooling temperature to 725 °C and extended the cooling time to 160 s, achieving an enhanced 60 mm depth cooling rate of 1.36 °C/s. (3) The optimized process remarkably improved the 60 mm depth impact energy to 144 J, achieving near-complete elimination of pearlite, increased granular bainite content, refined M-A constituent size, and enhanced density of high-angle grain boundaries. This study demonstrates that enhancing internal temperature gradients and prolonging cooling durations can effectively inhibit microstructural degradation in 60 mm depth regions of thick plates, providing both theoretical foundations and practical methodologies for optimizing TMCP processes of extra-thick steel plates.

This study investigated the connection between asthma in US individuals and their body roundness index (BRI) and weight-adjusted waist index (WWI). According to data from the 2005–2018 National Health and Nutrition Examination Survey (NHANES), 3609 of the 25,578 persons in the survey who were 18 years of age or older reported having asthma. After adjusting for all confounders, the probability of asthma prevalence increased by 8% for every unit rise in BRI (OR = 1.08, 95% CI 1.06,1.11). The probability of asthma prevalence increased by 16% for every unit rise in WWI (OR = 1.16, 95% CI 1.08,1.25). The BRI and WWI indices were associated with prevalence and were nonlinearly correlated. The inflection points for threshold saturation effects were 4.36 and 10.69, respectively (log-likelihood ratio test, P  < 0.05). Relationship subgroup analyses showed that the positive associations between BRI and WWI and asthma were generalized across populations and there was no significant interaction in most subgroups. In addition, sensitivity analyses verified the robustness of these results, further confirming the conclusion of BRI and WWI as independent risk factors for asthma. Finally, receiver operating characteristic (ROC) analysis showed that BRI outperformed WWI in predicting asthma, suggesting the potential of BRI in early asthma screening. Overall, BRI and WWI are independent risk factors for asthma with important clinical applications.

Thermal camouflage, which is used to conceal objects in the infrared vision for confrontation with infrared detection in civilian or military applications, has garnered increasing attraction and interest recently. Compared with conductive thermal camouflage, that is to tune heat conduction to achieve equivalent temperature fields, radiative thermal camouflage, based on emissivity engineering, is more promising and shows much superiority in the pursuit of dynamic camouflage technology when resorting to stimuli-responsive materials. In this paper, we demonstrate the emissivity-engineered radiative metasurface to realize dynamic thermal camouflage functionality via a flying laser heat source on the metal-liquid-crystal-metal (MLCM) platform. We employ a rigorous coupled-wave algorithm to calculate the surface emissivity of Au/LC/Au microstructures, where the LC-orientation angle distribution is quantified by minimizing the emitted thermal energy standard deviation throughout the whole plate. Emissivity engineering on the MCLM platform is attributed to multiple magnetic polariton resonance, and agrees well with the equivalent electric circuit analysis. Through this electrical modulation strategy, the moving hot spot in the original temperature field is erased and a uniform temperature field is observed in the infrared camera instead, demonstrating the very good dynamic thermal camouflage functionality. The present MLCM-based radiative metasurface may open avenues for high-resolution emissivity engineering to realize novel thermal functionality and develop new applications for thermal metamaterials and meta-devices.

We study the pumping of matter-wave solitons formed in Bose–Einstein condensates with attractive atomic interactions that are loaded into optical superlattices, in which one of the lattices is moving with respect to the other. We find that the matter-wave solitons exhibit lattice-parameter-dependent nonlinear integer (fractional) pumping and trapping. Different from the perspective of linear band Chern numbers, treating solitons as effective classical particles provides a good understanding of the quantized pumping or trapping. This reveals an unexpected insight: the nonlinear adiabatic pumping may be classical, and the quantization may be accidental, as dictated by the spatial period of the sliding sublattice. This alternative perspective on understanding soliton pumping highlights the parameter-dependent transition between soliton quantized pumping and trapping, and it exposes the nonlinear transition from a trapped soliton to a pumped soliton with increasing nonlinearity, which has never been reported before.

The TianQin program is an independently proposed space-borne detection initiative from China. The inertial sensor, as a crucial component, is susceptible to disturbances from temperature fluctuations, the impact of which on acceleration measurements remains elusive. Therefore, a comprehensive analysis on the influence of temperature disturbance is necessary to avoid errors in acceleration measurement. In this study, we proposed a complete scheme for calculating the level of acceleration noise. Based on the traditional temperature control scheme of using a heat pipe, we developed a systematic heat transfer simulation model to obtain the temperature signals. These signals can then be converted into the frequency domain and used to calculate the acceleration noise level within the target bandwidth. Our results indicate that, with a temperature control of 0.13 K/Hz1/2@1 mHz, the largest contributions to acceleration noise come from the outgassing effect, radiometer effect, and radiative pressure effect, in descending order. The total noise peak is 3.6×10−12 m/(s2⋅Hz1/2) at 1 mHz, which is more than three orders of magnitude higher than the TianQin target of 10−15 m/(s2⋅Hz1/2). This study provides new avenues for evaluating measurement errors and solutions for the TianQin program.