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Human hands play a very important role in daily object manipulation. Current prosthetic hands are capable of mimicking most functions of the human hand, but how to interact with prosthetic hands based on human intentions remains an open problem. In this article, we proposed a wearable ultrasound-based interface to achieve simultaneous and proportional control(1) of wrist rotation (pronation/supination)(2) and hand grasp (open/close). A semisupervised learning framework integrating principal component analysis and sparse Gaussian process regression (SPGP) was proposed to simplify the cumbersome model calibration, which is a key issue that hinders the practical application of existing simultaneous and proportional prosthetic control approaches. The proposed algorithms were verified with both offline and online experiments on 12 able-bodied subjects. The offline analysis showed that the first principal component of ultrasound features (PC#1) was inherently linear to wrist rotations and the SPGP was able to establish the mapping between ultrasound features and hand grasp kinematics with fewer training data. The online target achievement control test showed that the proposed method can achieve accurate control of a virtual prosthesis, with motion completion rate of 97.61 +/- 4.67%, motion completion time of 4.66 +/- 0.91 s, and stability error of 10.99 +/- 1.69 degrees. This is the first study to achieve online simultaneous and proportional control of wrist and hand kinematics using ultrasound and semisupervised learning, paving the way for the era of muscle morphology-driven prosthetic control.

Ultrasound super-resolution imaging through localisation and tracking of microbubbles can achieve sub-wave-diffraction resolution in mapping both micro-vascular structure and flow dynamics in deep tissue in vivo. Currently, it is still challenging to achieve high accuracy in localisation and tracking particularly with limited imaging frame rates and in the presence of high bubble concentrations. This study introduces microbubble image features into a Kalman tracking framework, and makes the framework compatible with sparsity-based deconvolution to address these key challenges. The performance of the method is evaluated on both simulations using individual bubble signals segmented from in vivo data and experiments on a mouse brain and a human lymph node. The simulation results show that the deconvolution not only significantly improves the accuracy of isolating overlapping bubbles, but also preserves some image features of the bubbles. The combination of such features with Kalman motion model can achieve a significant improvement in tracking precision at a low frame rate over that using the distance measure, while the improvement is not significant at the highest frame rate. The in vivo results show that the proposed framework generates SR images that are significantly different from the current methods with visual improvement, and is more robust to high bubble concentrations and low frame rates.

Background Delirium is a common complication clinically and is associated with the poor outcomes, yet it is frequently unrecognised and readily disregarded. Although the 3-minute diagnostic interview for confusion assessment method-defined delirium (3D-CAM) has been used in a variety of care settings, a comprehensive evaluation of its accuracy in all available care settings has not been performed. Objective This study aimed to evaluate the diagnostic test accuracy of the 3D-CAM in delirium detection through a systematic review and meta-analysis. Methods We systematically searched PubMed, EMBASE, the Cochrane Library, Web of Science, CINAHL (EBSCO) and ClinicalTrials.gov published from inception to 10 July 2022. The quality assessment of the diagnostic accuracy studies-2 tool was applied to evaluate methodological quality. A bivariate random effects model was used to pool sensitivity and specificity. Results Seven studies with 1,350 participants and 2,499 assessments were included, which were carried out in general medical wards, intensive care units, internal medical wards, surgical wards, recovery rooms and post-anaesthesia care units. The prevalence of delirium ranged from 9.1% to 25%. The pooled sensitivity and specificity were 0.92 (95% confidence interval [CI] 0.87–0.95) and 0.95 (95% CI 0.92–0.97), respectively. The pooled positive likelihood ratio was 18.6 (95% CI 12.2–28.2), the negative likelihood ratio was 0.09 (95% CI 0.06–0.14) and the diagnostic odds ratio was 211 (95% CI 128–349). Moreover, the area under the curve was 0.97 (95% CI 0.95–0.98). Conclusions The 3D-CAM has good diagnostic accuracy for delirium detection in different care settings. Further analyses illustrated that it had comparable diagnostic accuracy in older adults and patients with dementia or known baseline cognitive impairment. In conclusion, the 3D-CAM is recommended for clinical delirium detection.

The acoustic nonlinearity parameter of skeletal muscles changes with their contractions and has the potential to be utilized for exoskeleton control. In our previous work, a system comprising a wearable ultrasound probe was developed to estimate the acoustic nonlinearity parameter in vivo by measuring amplitudes of second-harmonic ultrasound. The estimating accuracy was found to be significantly affected by the corruption between echoes due to the limited axial resolution of ultrasound. As both frequency components of the single echo and the extent of corruption are unknown, a method based on a bi-directional deconvolution is proposed in this paper to decompose corrupted echoes, and integrated into the measuring system. Eight subjects were recruited for the in vivo measurement of the biceps brachii acoustic nonlinearity parameter, thickness, and elbow torque. Linear regression between the elbow torque and (1) the estimated acoustic nonlinearity parameter, (2) the thickness demonstrated the correlations, with average coefficients of determinations ( $R^{2}$ ) of 0.861 and 0.633 respectively. This work paves a way for estimating the acoustic nonlinearity parameter of skeletal muscles in vivo .

Perfusion by the microcirculation is key to the development, maintenance and pathology of tissue. Its measurement with high spatiotemporal resolution is consequently valuable but remains a challenge in deep tissue. Ultrasound Localization Microscopy (ULM) provides very high spatiotemporal resolution but the use of microbubbles requires low contrast agent concentrations, a long acquisition time, and gives little control over the spatial and temporal distribution of the microbubbles. The present study is the first to demonstrate Acoustic Wave Sparsely-Activated Localization Microscopy (AWSALM) and fast-AWSALM for in vivo super-resolution ultrasound imaging, offering contrast on demand and vascular selectivity. Three different formulations of acoustically activatable contrast agents were used. We demonstrate their use with ultrasound mechanical indices well within recommended safety limits to enable fast on-demand sparse activation and destruction at very high agent concentrations. We produce super-localization maps of the rabbit renal vasculature with acquisition times between 5.5 s and 0.25 s, and a 4-fold improvement in spatial resolution. We present the unique selectivity of AWSALM in visualizing specific vascular branches and downstream microvasculature, and we show super-localized kidney structures in systole (0.25 s) and diastole (0.25 s) with fast-AWSALM outdoing microbubble based ULM. In conclusion, we demonstrate the feasibility of fast and selective measurement of microvascular dynamics in vivo with subwavelength resolution using ultrasound and acoustically activatable nanodroplet contrast agents.

Super-resolution ultrasound (SRUS) imaging through localising and tracking sparse microbubbles has been shown to reveal microvascular structure and flow beyond the wave diffraction limit. Most SRUS studies use standard delay and sum (DAS) beamforming, where large main lobe and significant side lobes make separation and localisation of densely distributed bubbles challenging, particularly in 3D due to the typically small aperture of matrix array probes. This study aims to improve 3D SRUS by implementing a low-cost 3D coherence beamformer based on channel signal variance, as well as two other adaptive weight-based coherence beamformers: nonlinear beamforming with p-th root compression and coherence factor. The 3D coherence beamformers, together with DAS, are compared in computer simulation, on a microflow phantom, and in vivo. Simulation results demonstrate that the adaptive weight-based beamformers can significantly narrow the main lobe and suppress the side lobes for modest computational cost. Significantly improved 3D SR images of microflow phantom and a rabbit kidney are obtained through the adaptive weight-based beamformers. The proposed variance-based beamformer performs best in simulations and experiments., Ultrasound localisation microscopy (ULM), super-resolution, contrast-enhanced ultrasound, 3D beamforming

With a diverse and widely distributed global resource base, woody biomass is a compelling organic feedstock for conversion to renewable liquid fuels. In California, woody biomass comprises the largest fraction of underutilized biomass available for biofuel production, but conversion to fuels is challenged both by recalcitrance to deconstruction and by toxicity toward downstream saccharification and fermentation due to organic acids and phenolic compounds generated during pretreatment. In this study, we optimize pretreatment and scale-up of an integrated one-pot process for deconstruction of California woody biomass using the ionic liquid (IL) cholinium lysinate [Ch][Lys] as a pretreatment solvent. By evaluating the impact of solid loading, solid removal, yeast acclimatization, fermentation temperature, fermentation pH, and nutrient supplementation on final ethanol yields and titers, we achieve nearly full conversion of both glucose and xylose to ethanol with commercial C5-utilizing Saccharomyces cerevisiae. We then demonstrate process scalability in 680 L pilot-scale fermentation, achieving >80% deconstruction efficiency, >90% fermentation efficiency, 27.7 g/L ethanol titer, and >80% ethanol distillation efficiency from the IL-containing hydrolysate post fermentation. This fully integrated process requires no intermediate separations and no intermediate detoxification of the hydrolysate. Using an integrated biorefinery model, current performance results in a minimum ethanol selling price of $8.8/gge. Reducing enzyme loading along with other minor process improvements can reduce the ethanol selling price to $3/gge. This study is the largest scale demonstration of IL pretreatment and biofuel conversion known to date, and the overall biomass-to-ethanol efficiencies are the highest reported to date for any IL-based biomass-to-biofuel conversion.

This article provides a method to convert landfill-designated municipal solid waste (MSW, paper-rich and food-rich) to bioproducts through integrated bioprocessing, also a way of improving the MSW ...

Objective: While surface electromyography (sEMG) is still dominant in the field of muscle-computer interface, ultrasound (US) sensing has been regarded as a promising alternative to sEMG, owing to its ability to precisely monitor muscle deformations. Among different US modalities, A-mode US is more compact and cost-effective for wearable applications against its cumbersome B-mode counterpart. In this article, we conduct a comprehensive comparison of wearable A-mode US and sEMG on gesture recognition and isometric muscle contraction force estimation. Methods: We experimented with eight types of gesture, with a range of 0–60% maximum voluntary contraction for each motion. Results: Results show that A-mode US outperforms sEMG on gesture recognition accuracy, robustness, and discrete force estimation accuracy, while sEMG is superior to US on continuous force estimation accuracy and ease of use in force estimation. Moreover, an extended online experiment demonstrates that the complementary advantages of US and sEMG on gesture recognition and continuous force estimation can be combined for the achievement of multi-class proportional gesture control. Significance: This article demonstrates the potential of A-mode US in automated gesture recognition, and the prospect of sEMG/US fusion for proportional gesture interaction.

Feedstock variability is a significant barrier to the scale-up and commercialization of lignocellulosic biofuel technologies. Variability in feedstock characteristics and behavior creates numerous ...

Feedstock variability that originates from biomass production and field conditions propagates through the value chain, posing a significant challenge to the emerging biorefinery industry. Variability in feedstock properties impacts feeding, handling, equipment operations, and conversion performance. Feedstock quality attributes, and their variations, are often overlooked in assessing feedstock value and utilization for conversion to fuels, chemicals, and products. This study developed and employed a multiscale analytical characterization approach coupled with data analytic methods to better understand the sources and distribution of feedstock quality variability through evaluation of 24 corn stover bales collected in 4 counties of Iowa. In total, 216 core samples were generated by sampling nine positions on each bale using a reliable bale coring process. The samples were characterized for a broad suite of physicochemical properties ranging across field and bale, macro, micro, and molecular scales. Results demonstrated that feedstock quality attributes can vary at all spatial scales and that multiple sources of variability must be considered in order to establish and manage biomass quality for conversion processes.

It is crucial to model skeletal muscles for muscle-centered health care, such as prosthetics. Here we hypothesize that the acoustic non-linearity parameter (B/A) can be utilized to partially represent the contraction state of skeletal muscles. Although previous work commonly measured the B/A value of tissues in vitro, the present study targets the biceps brachii muscle to investigate the relationship between the B/A value and the dynamics of the elbow. Furthermore, it is proposed that a correction method based on the angular spectrum theory be applied in vivo, and the dynamic metrics of the B/A value and its feasibility be verified through an underwater experiment. Seven participants were invited for the in vivo experiment, in which elbow torque and B/A values were measured simultaneously. The non-plane reflection was approximately treated through an integral method, leading to a modified B/A value. Then, linear regression was applied to characterize the B/A-torque relationship, with the calculated coefficient of determination (R2) ranging from 0.85-0.93. Experimental results indicate that the modified B/A value of the biceps brachii correlates well with elbow torque. This study not only paves the way to dynamic measurement of the B/A value of skeletal muscles in vivo, but also confirms that B/A can be used as a more comprehensive assessment criterion for muscle functions.

It is evident that the prevailing solution, myoelectric pattern recognition for prosthetic manipulation, constrains gesture-based interaction because of the lack of proportional control information such as exerted force. This paper reports an attempt, named simultaneous gesture recognition and muscle contraction force estimation, to realize proportional pattern recognition (PPR) control taking advantage of arm muscle deformation via wearable ultrasound sensing. We experiment with eight types of predefined hand motions, with a range of 0-60% maximum voluntary contraction (MVC) using a wearable multichannel A-mode ultrasound system. The experiment result demonstrates that above 93.7% of gestures are correctly recognized during dynamic muscle contraction forces (0-60% MVC), albeit only training at a slight force level (bf2, and normalized root-mean-square error (nRMSE) of 0.927 and 0.102, respectively. These research outcomes demonstrate the feasibility of ultrasound-based PPR control, paving the way for musculature-driven applications such as finer prosthetic control, remote manipulation, and rehabilitation treatment.

Though physiological signal based human-machine interfaces (HMIs) have recently developed rapidly, their practical use is restricted by many real-world environmental factors, one of which is muscle fatigue. This paper explores the sensitivities between surface electromyography (sEMG) and A-mode ultrasound (AUS) sensing modalities subject to muscle fatigue in the context of hand gesture recognition tasks. Two metrics, mean classification accuracy ( mCA) and decline rate ( DR), are proposed to evaluate the accuracy and muscle fatigue sensitivity between sEMG and AUS based HMIs. Muscle fatigue inducing experiment was designed and eight subjects were recruited to participate in the experiment. The gesture recognition accuracies of sEMG and AUS under non-fatigue state and fatigue state are compared through Mahalanobis distance based classifier linear discriminant analysis (LDA). In addition, Mahalanobis distance based metrics, repeatability index ( RI) and separability index ( SI), are introduced to evaluate the changes in the feature distribution during muscle fatigue and reveal the cause of the fatigue sensitivity difference between sEMG and AUS signals. The experimental results demonstrate that the fatigue robustness of AUS signal is better than that of sEMG signal. Specifically, with the employment of the LDA classifier trained under non-fatigue state, the testing accuracy of the sEMG signal on the non-fatigue state is 94.96%, while reduce to 68.26% on the fatigue state. The testing accuracy of the AUS signal on the corresponding states is 99.68% and 91.24% respectively. AUS signal attains higher mCA and lower DR, indicating that it has advantages over sEMG signal in terms of both accuracy and muscle fatigue sensitivity. In addition, the RI and RI/SI analysis reveal that before and after muscle fatigue, the consistency of AUS feature distribution is better than that of sEMG. These research outcomes validate that AUS is more tolerant to feature migration caused by muscle fatigue than sEMG.

It is important to convert waste shrimp shells into chitin and its derivatives, but it still faces disadvantages of pollution and long process. In this research, deep eutectic solvents made from choline chloride (ChCl) and p-toluenesulfonic acid monohydrate (TsOH) were used to convert shrimp shells into chitin or carbon materials through adjustment of temperature with a dissolution-regeneration method in one step. Obtained precipitates and regenerated products gradually changed from chitin to carbon materials with the temperature adjusted to 130 °C and 110 °C, respectively. The α-chitin with the highest purity of 97.9 ± 0.1 wt% was prepared using 15 wt% ChCl/TsOH (1:2, n:n) aqueous solution at 70 °C, and the yield was 59.4 ± 1.9 wt%. Moreover, the carbon materials prepared by ChCl/TsOH (1:4) treatment with water and ethanol as anti-solvent were S/N/O-doped carbon materials, which exhibited potential in the supercapacitor with a specific capacitance of 24.8 and 19.3 F/g at 1 A/g, respectively.

This scale-up study demonstrated the feasibility of an ionic liquid (IL) pretreatment process at 40 kg scale, using the IL 1-ethyl-3-methylimidazolium acetate ([C2C1Im][OAc]) as the solvent. The pretreatment was followed by enzymatic hydrolysis through which the process efficiency for biomass conversion to monomeric sugars was determined. The results show that 43 wt% of switchgrass was dissolved in IL after 2 h of pretreatment at 160 °C with 15 wt% solid loading. A 120 h enzymatic hydrolysis of the pretreated switchgrass results in 96% glucan and 98% xylan conversion. [C2C1Im][OAc] pretreatment has been successfully scaled up to 40 kg with improved sugar titers and yields relative to bench scale (6 kg). The mass flow of the overall process was established and the major scale-up challenges of the process were identified. Keywords: Ionic liquid, 1-Ethyl-3-methylimidazolium acetate, Pretreatment, Scale up, Enzyme

A novel sensor technology is urgently required to sense the human motion behavior for wearable human–machine interfaces (HMIs) in a wide spectrum of applications, such as rehabilitation. The inherent limitations of surface electromyography signals and the shortages of the existing ultrasound-based sensors constrain the development of wearable devices from actually being applied to improve our life quality. In this paper, a lightweight A-mode probe, consisting of housing and polyvinylidene fluoride (PVDF) membrane, is proposed to enhance the detection of morphological changes of deep-layered muscles in the wearable HMI context. The PVDF-based probe, with 0.75-g weight and 0.6-mm thickness, is designed, simulated, fabricated, and validated in hand gesture recognition. Its classification accuracy achieves 97.64%±1.83%, which is practically accepted for the usage requirements of the existing wearable HMIs. This paper paves the way for feasible wearable HMIs in real-world applications with lightweight ultrasound probes.

A two-degrees-of-freedom (two-DOF) ultrasonic motor, which could output linear motions with two-DOF by using only one longitudinal–bending hybrid sandwich transducer, is proposed and tested in this paper. The motion in the horizontal ( X ) direction is achieved by the hybrid of the second longitudinal and fifth bending vibrations of the motor, while the motion in the vertical ( Y ) direction is gained by the composition of two orthogonal fifth bending vibrations. The proposed ultrasonic motor is designed and the principles for the two-DOF driving were analyzed. Then, the simulation analyses of the motor are accomplished to verify the described principles. Finally, a prototype is fabricated and its mechanical output characteristics are tested. The results indicate that the maximum no-load velocities of the motor in horizontal and vertical directions are 572 and 543 mm/s under the preload of 100 N and the voltage of 300 Vp-p, respectively. The maximum output forces in horizontal and vertical directions are 24 and 22 N when the preload is 200 N. The simulation and experiment results verify the feasibility of the proposed two-DOF ultrasonic motor.

A novel single-mode linear piezoelectric ultrasonic motor based on asymmetric structure is proposed. The motor adopts the combination of the first longitudinal vibration and the asymmetric mechanical structure to produce the oblique movement on the driving foot; then, the linear output motion is obtained under the friction coupling between the driving foot and the runner. The motor is designed and its operation principle is illustrated in detail. The transient analysis is developed to verify the formed movement on the driving foot. A prototype is manufactured and its vibration characteristics are measured by a scanning laser Doppler vibrometer. An experimental system is established and the output performances of the motor are tested and discussed. The results indicate that the maximal no-load velocity of the motor is about 127.31 mm/s under the voltage of 150 Vp-p and the preload of 30 N. The maximum thrust force is about 2.8 N when the voltage and preload are 150 Vp-p and 40 N. The related works in this paper has verified the feasibility of the proposed single-mode ultrasonic motor based on asymmetric structure.

Nowadays, ultrasound imaging (US) has made extensive applications in the field of the medical imaging due to its particular advantages, in which the transducer plays an important role. The traditional single-frequency transducers can not meet the requirements of various medical applications, such as harmonic imaging (HI), second-order ultrasound field imaging (SURF) and acoustic radiation force imaging (ARFI). Therefore, multi-frequency, especially dual-frequency (DF) transducers are proposed, each of which transmits and/or receives the ultrasound in different frequencies. The multi-frequency transducer configurations mainly contain five types which named vertical stack, horizontal stack, transducers with polyvinylidene fluoride (PVDF) layer, interleaved arrays and annular array. In this paper, the design, fabrication and recent developments of the multi-frequency transducers are presented and compared by defragmenting more than a hundred papers.

A three-DOF ultrasonic motor is presented in this paper. The proposed motor consists of four piezoelectric ceramic plates and a mental base with a flange that can fix the motor on a rack. The proposed motor takes advantage of a longitudinal mode and two bending modes, different hybrids of which can realize three-DOF actuation. Because of symmetric structure of the proposed motor, the resonance frequencies of the two bending modes are identical. And the resonance frequency of the longitudinal mode was tuned closed to the ones of the bending modes by adjusting the structural parameters in modal analysis. Then trajectories of nodes on the driving foot were obtained by the transient analysis to verify the feasibility of driving principle. Experiments including vibration shape test and output characteristic test were executed. The starting voltages of the rotation along horizontal axes are about 10 Vp-p. Under driving voltages of 200 Vp-p, the output velocities of three DOF can reach 280 rpm, 277 rpm and 327 rpm, respectively. The results of the experiments indicate that the proposed motor is characterized by low starting voltages and high output velocities.

A novel piezoelectric actuator with two operating modes is proposed and tested in this work, whose unique feature is that it has different mechanical output performances under two bending resonance frequencies. The proposed actuator is fabricated by bonded eight pieces of lead zirconate titanate ceramic plates on an aluminum alloy beam symmetrically. When the ceramic plates are excited by signals with resonance frequency of the first bending mode of the actuator, two bending vibrations will be superimposed to form elliptical movements on the two driving tips, which is the first operating mode. The other operating mode can be realized easily by changing the working frequency to the second bending mode of the actuator. These two operating modes are calculated and compared in detail. The prototype achieves a maximum no-load speed of 171 mm/s and maximum thrust force of 0.6 N using the first operating mode, whereas these two values are increased to be about 208 mm/s and 0.76 N under the second operating mode. The weight of the proposed piezoelectric actuator is about 17.7 g, and the maximum force weight ratio is tested to be about 42.9 N/kg.

Sixteen cellulose rich municipal solid waste (MSW) blends were developed and screened using an acid-assisted ionic liquid (IL) deconstruction process. Corn stover and switchgrass were chosen to represent herbaceous feedstocks; non-recyclable paper (NRP) and grass clippings (GC) collected from households were chosen as MSW candidates given their abundance in municipal waste streams. The most promising MSW blend: corn stover/non-recyclable paper (CS/NRP) at 80/20 ratio was identified in milliliter-scale screening based on the sugar yield, feedstock cost, and availability. A successful scale-up (600-fold) of the IL-acidolysis process on the identified CS/NRP blend has been achieved. The sugar and lignin streams were recovered and characterized. Mass and material energy flows of the optimized process were presented. Feedstock cost for MSW blends was also discussed. Results suggest the promising potential of using MSW as a feedstock blending agent for biorefineries while maintaining sufficient performance and low feedstock cost. The bench scale (6 L) study is an essential step in demonstrating the scalability of this IL technology.

Resonant type longitudinal vibration transducers are used in this work to construct a linear piezoelectric actuator with four driving feet. Totally three longitudinal transducers are integrated in I-shape to form the proposed actuator, which contains one vertical transducer and two horizontal transducers. These three transducers vibrate under longitudinal modes with certain temporal sequence, whose vibrations are superimposed in the actuator to generate elliptical motions on the four driving feet. The three transducers are tuned to be suitable dimensions, under which they have very close 1st longitudinal resonance frequencies; the working frequency of the piezoelectric actuator is designed to be about 31.3 kHz. The vibration coupling problem between the longitudinal transducers are studied by calculating the motion trajectories of the four feet. It is found that the temporal shift of the longitudinal vibrations can be used to tune the movement trajectories; the four feet can get nearly the same vertical displacements under a phase shift of 105°. At last, the vibration characteristics and mechanical output performances of a prototype are measured. The working frequency of the prototype, the maximum speed, and the maximum thrust force are measured to be 33.15 kHz, 1563 mm/s, and 158.2 N, respectively.

Despite the prosperous development of the ultrasound-based human-machine interface, its reliability in the practical applications is still unevaluated. This paper gives priority to exploring the limb position effect on the ultrasound-based gesture recognition, where wearable A-mode ultrasound is utilized instead of its cumbersome B-mode counterpart. An online experiment under eight different limb positions is conducted to validate the performance of the ultrasound-based gesture recognition, with eight able-bodied subjects employed. Results show that the influence of limb movement on the ultrasound-based gesture recognition is not significant. Overall, the real-time motion completion rate and motion recognition accuracy are 97.1% and 94.5% across different limb positions, albeit only training at a natural limb position. Moreover, it takes only 177 ms for the system to successfully recognize the intended motions across various limb positions. These results demonstrate the reliability of the ultrasound-based gesture interaction, paving the way for its practical applications.

The effects of sodium sulfite pretreatment on the delignification rate, cellulose content, enzymatic hydrolysis efficiency, and glucose yield of corncob residues (CCR) were investigated. The optimum pretreatment conditions were as follows: 12% sodium sulfite, with a pH value of 7, a temperature of 160 °C, and a holding time of 20 min. Under the optimal conditions, the cellulose content in the pretreated residue was 85.17%, and sodium lignosulfonate with a sulfonation degree of 0.677 mmol/g was obtained in the waste liquids. A delignification rate of 77.45% was also achieved after the pretreatment. Enzymatic hydrolysis of pretreated CCR was carried out with cellulase (5 FPU/g substrate) and β-glucosidase (10 IU/g substrate) for 48 h. The untreated CCR were hydrolyzed using cellulase (20 FPU/g substrate) and β-glucosidase (10 IU/g substrate) for 48 h. The comparison results showed that sodium sulfite pretreatment improved the enzymatic hydrolysis efficiency and glucose yield, which increased by 28.80% and 20.10%, respectively. These results indicated that despite the application of low cellulase dosage, high enzymatic hydrolysis efficiency substrate could be produced, and the sodium lignosulfonate which can be used for oilfields and concrete additives was obtained from the sodium sulfite-pretreated CCR.

A rotary piezoelectric motor was proposed, in which the second and third bending vibrations of a transducer were superimposed to produce reverse elliptical movements on the two driving tips. The second bending mode was used to overcome the preload, whereas the third bending mode was used to rotate the rotor. The frequency tuning process of the two bending modes was discussed. The working frequency, the maximum no-load speed, the maximum torque and the maximum efficiency of the prototype were tested to be 23.8 kHz, 130 r/min, 2.96 N·m and 16.8%, respectively.

We report a simple method to synthesize spherical and irregular sodium lignosulfonate (SLS)-stabilized zinc oxide (ZnO) nanoparticles using water as a solvent, SLS as a stabilizing agent, and sodium hydroxide as a precipitation agent. The presence of SLS on the surface of ZnO nanoparticles can improve the dispersion of the nanoparticles and make them negatively charged. The negatively charged SLS-stabilized ZnO nanoparticles can be deposited onto cellulose paper through a layer-by-layer (LBL) approach. The resultant cellulose paper samples, coated with ZnO nanoparticles, show good antibacterial activity against both Gram-positive Bacillus subtilis and Gram-negative Escherichia coli.