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Abstract Metal–organic frameworks (MOFs) deliver potential applications in electrochromism and energy storage. However, the poor intrinsic conductivity of MOFs in electrolytes seriously hampers the development of the above‐mentioned electrochemical applications, especially in one MOF electrode. Herein, a new Ni‐based MOF (denoted Ni‐DPNDI) is proposed with enhanced conductivity by π‐delocalized DPNDI connectors. Predictably, the obtained Ni‐DPNDI MOF achieves a conductivity of up to 4.63 S∙m−1 at 300 K. Profiting from its unique electronic structure, the Ni‐DPNDI MOF delivers excellent electrochromic and energy storage performance with a great optical modulation (60.8%), a fast switching speed (tc = 7.9 s and tb = 6.4 s), a moderate specific capacitance (25.3 mAh·g−1) and good cycle stability over 2000 times. Meanwhile, energy storage capacity is visual by the coloration states of Ni‐DPNDI film. As a proof of the potential application, a large‐area (100 cm2) electrochromic energy storage smart window is further designed and displayed. The strategy provides an interesting alternative to porous multifunctional materials for the new generation of electronic devices with diverse applications.

To remotely monitor the physiological status of the human body, long range (LoRa) communication has been considered as an eminently suitable candidate for wireless body area networks (WBANs). Typically, a Rayleigh-lognormal fading channel is encountered by the LoRa links of the WBAN. In this context, we characterize the performance of the LoRa system in WBAN scenarios with an emphasis on the physical (PHY) layer and medium access control (MAC) layer in the face of Rayleigh-lognormal fading channels and the same spreading factor interference. Specifically, closed-form approximate bit error probability (BEP) expressions are derived for the LoRa system. The results show that increasing the spreading factor (SF) and reducing the interference efficiently mitigate the shadowing effects. Moreover, in the quest for the most suitable MAC protocol for LoRa based WBANs, three MAC protocols are critically appraised, namely the pure ALOHA, slotted ALOHA, and carrier-sense multiple access. The coverage probability, energy efficiency, throughput, and system delay of the three MAC protocols are analyzed in Rayleigh-lognormal fading channel. Furthermore, the performance of the equal-interval-based and equal-area-based schemes is analyzed to guide the choice of the SF. Our simulation results confirm the accuracy of the mathematical analysis, and provide some useful insights for the future design of LoRa based WBANs on how to achieve the desired performance requirements for different conditions (i.e., different network radii and average numbers of end-devices) by using different SF allocation schemes and MAC protocols.

Wireless body area networks (WBANs) can provide continuous monitoring of human biological signals. Due to the limited energy of the sensors, wireless-powered system has been adopted to prolong network lifetime for implant WBANs. In this paper, we propose an energy buffer-aided wireless-powered relaying system for self-sustainable implant WBAN. The proposed system is composed of an off-body access point (AP) and many users, where an implant device is placed in body while a dual-mode wearable device with an energy buffer is attached on body for each user. In the downlink, the dual-mode wearable device simultaneously harvests energy that is stored in the energy buffer from a radio-frequency signal broadcasted by the AP and provides energy supply via wireless energy transfer to the implant device. In the uplink, the implant device uses harvested energy to transmit its collected data to the wearable device. Then the wearable device adopts the stored energy to decode and forward the data to the AP in an orthogonal multiple access way. We investigate two transmission policies for the wearable device, namely best-effort policy (BEP) and on-off policy (OOP). We derive the limiting distribution of the energy for both the BEP and OOP. Furthermore, the outage probability and average throughput of the proposed system with both the BEP and OOP are analyzed. Simulation results are presented to validate the analytical expressions and provide some useful insights.

Abstract The clinical applications of the association of cortical thickness and white matter fiber with freezing of gait (FoG) are limited in patients with Parkinson’s disease (PD). In this retrospective study, using white matter fiber from diffusion-weighted imaging and cortical thickness from structural-weighted imaging of magnetic resonance imaging, we investigated whether a machine learning-based model can help assess the risk of FoG at the individual level in patients with PD. Data from the Parkinson’s Disease Progression Marker Initiative database were used as the discovery cohort, whereas those from the Fujian Medical University Union Hospital Parkinson’s Disease database were used as the external validation cohort. Clinical variables, white matter fiber, and cortical thickness were selected by random forest regression. The selected features were used to train the support vector machine(SVM) learning models. The median area under the receiver operating characteristic curve (AUC) was calculated. Model performance was validated using the external validation cohort. In the discovery cohort, 25 patients with PD were defined as FoG converters (15 men, mean age 62.1 years), whereas 60 were defined as FoG nonconverters (38 men, mean age 58.5 years). In the external validation cohort, 18 patients with PD were defined as FoG converters (8 men, mean age 66.9 years), whereas 37 were defined as FoG nonconverters (21 men, mean age 65.1 years). In the discovery cohort, the model trained with clinical variables, cortical thickness, and white matter fiber exhibited better performance (AUC, 0.67–0.88). More importantly, SVM-radial kernel models trained using random over-sampling examples, incorporating white matter fiber, cortical thickness, and clinical variables exhibited better performance (AUC, 0.88). This model trained using the above mentioned features was successfully validated in an external validation cohort (AUC, 0.91). Furthermore, the following minimal feature sets that were used: fractional anisotropy value and mean diffusivity value for right thalamic radiation, age at baseline, and cortical thickness for left precentral gyrus and right dorsal posterior cingulate gyrus. Therefore, machine learning-based models using white matter fiber and cortical thickness can help predict the risk of FoG conversion at the individual level in patients with PD, with improved performance when combined with clinical variables.

Reversible metal electrodeposition (RME)-based electrochromic devices have been attracting significant research interest due to their merits of low cost, simple configuration, and high extinction coefficients. As the key component in the electrochromic system, RME electrolytes with various metal ions and additives have endowed the RME device with flexible functionalities in energy-saving applications such as energy-efficient displays, smart windows, and camouflages. However, it is still challenging to research a widespread commercial application before some critical issues can be solved such as poor reversibility, low optical memory of the mirror state, and slow switching speed. Here, we offer a critical review of the recent progress of RME electrochromic devices based on aqueous, organic, ionic liquid, and eutectic electrolytes. Furthermore, the main challenges and perspectives for RME electrolytes are highlighted and discussed.

BackgroundThe association between coffee and mortality risk has been found in most previous studies, and recent studies have found an association between coffee consumption and cognition. However, there is still a lack of research exploring whether the association between coffee and mortality is influenced by cognitive function.ObjectiveThe purpose of this study was to explore the association of coffee, caffeine intake in coffee and decaffeinated coffee with all-cause mortality and cardiovascular disease (CVD) mortality in older adults with different cognitive performances.MethodsThe study was based on data from the National Health and Nutrition Examination Survey (NHANES) 2011–2014. Coffee and caffeine consumption data were obtained from two 24-h dietary recalls. Individual cognitive functions were assessed by CERAD-word learning test (CERAD-WLT), animal fluency test (AFT), and digit symbol substitution test (DSST). In addition, principal component analysis (PCA) was performed with the above test scores to create global cognitive score. The lowest quartile of scores was used to classify cognitive performance. Cox regression and restricted cubic spline (RCS) were applied to assess the relationship between coffee and caffeine consumption and mortality.ResultsIn the joint effects analysis, we found that those with cognitive impairment and who reported without drinking coffee had the highest risk of all-cause and cardiovascular mortality compared with others. In the analysis of population with cognitive impairment, for all-cause mortality, those who showed cognitive impairment in the AFT displayed a significant negative association between their total coffee consumption and mortality {T3 (HR [95% CI]), 0.495 [0.291–0.840], p = 0.021 (trend analysis)}. For DSST and global cognition, similar results were observed. Whereas for CERAD-WLT, restricted cubic spline (RCS) showed a “U-shaped” association between coffee consumption and mortality. For CVD mortality, a significant negative trend in coffee consumption and death was observed only in people with cognitive impairment in AFT or DSST. In addition, we observed that decaffeinated coffee was associated with reduced mortality in people with cognitive impairment.ConclusionOur study suggested that the association between coffee consumption and mortality is influenced by cognition and varies with cognitive impairment in different cognitive domains.

Highlights Transition metal phosphates were first developed for the electrochromic application. The obtained NiHPO4·3H2O film achieves an ultra-large optical modulation of 90.8%, and the electrochromic mechanism is systematically elucidated using in situ and ex situ techniques. A large-area electrochromic smart window with 100 cm2 is constructed, which displays superior performances in regulating natural lighting and storing electrical charges.

Objective: To develop an objective and efficient method to automatically identify Parkinson’s disease (PD) and healthy control (HC). Methods: We design a novel model based on residual network (ResNet) architecture, named PD-ResNet, to learn the gait differences between PD and HC and between PD with different severity levels. Specifically, a polynomial elevated dimensions technique is applied to increase the dimensions of the input gait features; then, the processed data is transformed into a 3-dimensional picture as the input of PD-ResNet. The synthetic minority over-sampling technique (SMOTE), data augmentation, and early stopping technologies are adopted to improve the generalization ability. To further enhance the classification performance, a new loss function, named improved focal loss function, is developed to focus on the train of PD-ResNet on the hard samples and to discard the abnormal samples. Results: The experiments on the clinical gait dataset show that our proposed model achieves excellent performance with an accuracy of 95.51%, a precision of 94.44%, a recall of 96.59%, a specificity of 94.44%, and an F1-score of 95.50%. Moreover, the accuracy, precision, recall, specificity, and F1-score for the classification of early PD and HC are 92.03%, 94.20%, 90.28%, 93.94%, and 92.20%, respectively. Furthermore, the accuracy, precision, recall, specificity, and F1-score for the classification of PD with different severity levels are 92.03%, 94.29%, 90.41%, 93.85%, and 92.31%, respectively. Conclusion: Our proposed method shows better performance than the traditional machine learning and deep learning methods. Clinical impact: The experimental results show that the proposed method is clinically meaningful for the objective assessment of gait motor impairment for PD patients.

Abstract In recent years, flexible stress sensors capable of monitoring diverse body movements and physiological signals have been attracting great attention in the fields of healthcare systems, human–machine interfaces, and wearable electronics. Inspired by the structure of natural eggshell inner membrane (ESIM), we developed a pressure sensor based on MXene (Ti3C2Tx)/Ag NWs (silver nanowires) composite electrodes and the micro-structured dielectric layer to meet the application requirements of wide detection range and long-term stability for the sensors. In the light of the nanoscale-microarray of the dielectric layer and the rough surface of electrode materials, this pressure sensor is expected to allow great and persistent deformation during the loading process. As a result, the device is characterized by an improved sensitivity, fast response (in the millisecond range), wide detection range (0–600 kPa), and long-term stability. The outstanding performance of the proposed sensor makes it possible to detect various human activities, such as speaking, air blowing, clenching, walking, finger/knee/elbow bending, and striking, demonstrating its good application prospects in wearable and flexible electronic devices.

Underwater acoustic (UWA) communications face many challenges, such as large multipath delay, severe fading and the time-varying distortions. Chaotic modulations have shown advantages in UWA communications, but the reliability of current chaotic modulations is still not guaranteed. In this paper, a short-length protograph low-density parity-check (P-LDPC) code design framework for the differential chaotic bit-interleaved coded modulation (DC-BICM) system for UWA communication is proposed. This design framework, considering the requirements of short codes in UWA communications, integrates the DC-BICM system, UWA channel and the differential evolutionary code searching algorithm. Through this design framework, the optimized short P-LDPC code can be obtained. Simulation results show that the DC-BICM system with the proposed P-LDPC code can obtain more than 0.48 dB coding gain and reduce 32.6%~69.5% of the average number of iterations compared with the counterparts. Moreover, the reconstructed underwater image with the proposed P-LDPC code is clearest with the highest peak-signal-noise ratio value when compared with counterparts.

Parkinson’s disease (PD) can be divided into postural instability and difficult gait (PIGD) and tremor dominance (TD) subtypes. However, potential neural markers located in the dorsal ventral side of the subthalamic nucleus (STN) for delineating the two subtypes of PIGD and TD have not been demonstrated. Therefore, this study aimed to investigate the spectral characteristics of PD on the dorsal ventral side. The differences in the β oscillation spectrum of the spike signal on the dorsal and ventral sides of the STN during deep brain stimulation (DBS) were investigated in 23 patients with PD, and coherence analysis was performed for both subtypes. Finally, each feature was associated with the Unified Parkinson’s Disease Rating Scale (UPDRS). The β power spectral density (PSD) in the dorsal STN was found to be the best predictor of the PD subtype, with 82.6% accuracy. The PSD of dorsal STN β oscillations was greater in the PIGD group than in the TD group (22.17% vs. 18.22%; p < 0.001). Compared with the PIGD group, the TD group showed greater consistency in the β and γ bands. In conclusion, dorsal STN β oscillations could be used as a biomarker to classify PIGD and TD subtypes, guide STN-DBS treatment, and relate to some motor symptoms.

A key component of the joint source-channel coding (JSCC) scheme based on double low-density parity-check (D-LDPC) codes is the introduction of a linking matrix between the source LDPC code and channel LDPC code, by which the decoding information including the source redundancy and channel state information can be transferred iteratively. However, the linking matrix is a fixed one-to-one mapping, i.e., an identity matrix in a conventional D-LDPC code system, which may not take full advantage of the decoding information. Therefore, this paper introduces a general linking matrix, i.e., a non-identity linking matrix, connecting the check nodes (CNs) of the source LDPC code and the variable nodes (VNs) of the channel LDPC code. Further, the encoding and decoding algorithms of the proposed D-LDPC coding system are generalized. A joint extrinsic information transfer (JEXIT) algorithm is derived for calculating the decoding threshold of the proposed system with a general linking matrix. In addition, several general linking matrices are optimized with the aid of the JEXIT algorithm. Finally, the simulation results demonstrate the superiority of the proposed D-LDPC coding system with general linking matrices.

This study aimed to investigate the association between beta oscillations and brain iron deposition. Beta oscillations were filtered from the microelectrode recordings of local field potentials (LFP) in the subthalamic nucleus (STN), and the ratio of the power spectral density of beta oscillations (PSDXb) to that of the LFP signals was calculated. Iron deposition in the deep gray matter (DGM) structures was indirectly assessed using quantitative susceptibility mapping (QSM). The Unified Parkinson’s Disease Rating Scale (UPDRS), part III, was used to assess the severity of symptoms. Spearman correlation coefficients were applied to assess the associations of PSDXb with QSM values in the DGM structures and the severity of symptoms. PSDXb showed a significant positive correlation with the average QSM values in DGM structures, including caudate and substantia nigra (SN) (p = 0.008 and 0.044). Similarly, the PSDXb showed significant negative correlations with the severity of symptoms, including axial symptoms and the gait in the medicine-off state (p = 0.006 for both). The abnormal iron metabolism in the SN and striatum pathways may be one of the underlying mechanisms for the occurrence of abnormal beta oscillations in the STN, and beta oscillations may serve as important pathophysiological biomarkers of PD.

Development of wearable devices relies on advance in power sources with complementary mechanical properties. Here the authors use a conductive, stretchable and healable composite to achieve sustained performance in a triboelectric nanogenerator under extreme deformation and after severe mechanical damage.

Electrochromic devices (ECDs) have a broad range of application prospects in many important energy efficient optoelectronic fields, such as smart windows, anti-glare rearview mirrors, low-energy displays, and infrared camouflage. However, there are some factors restricting their development, such as low coloration efficiency, slow switching speed, and poor cycling stability. Coordination polymer (CP) is a promising active material for the fabrication of high-performance ECD because of its ultrahigh coloration efficiency, fast switching speed, and excellent cycling stability. In this review, current advances of CP in energy efficient ECDs are comprehensively summarized and evaluated. Specifically, the effects of composition, coordination bonding, and microstructure of the bipyridine- and terpyridine-based CP on EC performances are introduced and discussed in detail. Then, the challenges and prospects of this booming field are proposed. Finally, the broad application prospects of the CPs-based EC materials and the corresponding devices are also demonstrated, which hold numerous revolutionary effects over our daily life. Hopefully, this review would provide useful guidance and further promote progress on the electrochromic and other optoelectronic fields.

Abstract The rational design of previously unidentified materials that could realize excellent electrochemical‐controlled optical and charge storage properties simultaneously, are especially desirable and useful for fabricating smart multifunctional devices. Here, a facile synthesis of a 1D π–d conjugated coordination polymer (Ni‐BTA) is reported, consisting of metal (Ni)‐containing nodes and organic linkers (1,2,4,5‐benzenetetramine), which could be easily grown on various substrates via a scalable chemical bath deposition method. The resulting Ni‐BTA film exhibits superior performances for both electrochromic and energy storage functions, such as large optical modulation (61.3%), high coloration efficiency (223.6 cm2 C−1), and high gravimetric capacity (168.1 mAh g−1). In particular, the Ni‐BTA film can maintain its electrochemical recharge‐ability and electrochromic properties even after 10 000 electrochemical cycles demonstrating excellent durability. Moreover, a smart energy storage indicator is demonstrated in which the energy storage states can be visually recognized in real time. The excellent electrochromic and charge storage performances of Ni‐BTA films present a great promise for Ni‐BTA nanowires to be used as practical electrode materials in various applications such as electrochromic devices, energy storage cells, and multifunctional smart windows.

Abstract Reversible electrochemical mirror (REM) electrochromic devices with electrochemical tunability in multiple optical states are exciting alternatives to conventional electrochromic smart windows. Electrochromic devices are studied extensively, yet widespread adoptions have not been achieved due to problems associated with durability, switching speed, limited options on optical states, and cost. In this study, a REM electrochromic device based on CuSn alloy is developed, which offers highly reversible switching between transparent, greyish‐blue, and mirror states via reversible electrodeposition and dissolution. The alloying element, Sn acts as an electrochemical mediator, which facilitates the electrodeposition and dissolution of Cu. The CuSn‐based REM device shows superior cycling stability for 2400 cycles (transmittance mode) and 1000 cycles (reflectance mode). The electrodeposited CuSn alloy film is resistant to surface oxidation in ambient air, with a 2.9% difference in reflectance at 2000 nm after 3 days. In addition, the alloy film exhibits excellent NIR reflectance property with thermal modulation of 18.5 °C at a high temperature of 180 °C. The REM device with zero power consumption maintains its mirror state for at least 100 min, making it a promising candidate for energy‐efficient applications.

The emergence of soft energy devices provides new possibilities for various applications, it also creates significant challenges in the selection of structural design and material compatibility. Herein, we demonstrate a stretchable transmissive electrochromic energy storage device by inkjet-printing single layer of WO3 nanoparticles on an elastomeric transparent conductor. Such hybrid electrode is highly conductive and deformable, making it an excellent candidate for the application: large optical modulation of 40%, fast switching speed (

Spatially coupled protograph (SC-P) low-density parity-check codes can achieve excellent performance and simple implementation when the coupling length is sufficiently large. However, in the case of small coupling lengths, terminated SC-P (TE-SC-P) codes suffer from relatively weaker decoding thresholds and lower code rates compared with the original protograph codes. To address the above issues, we propose a novel design method to enhance the performance of such TE-SC-P codes. Specifically, we develop a bus-topology-like puncturing rule so as to formulate a new family of SC-P codes, referred to as punctured TE-SC-P (P-TE-SC-P) codes. Theoretical analyses and simulation results show that the proposed P-TE-SC-P codes possess significant performance gains over conventional SC-P codes and randomly punctured TE-SC-P (called RP-TE-SC-P) codes with relatively higher computational complexity.

Non-coherent capacity bounds for the M-ary differential chaos shift keying (DCSK) modulation system are derived and analyzed over multipath Rayleigh fading channels, deriving conditions on the channel state information/non-channel state information (CSI/NonCSI) and soft-decision/hard-decision (SD/HD), respectively. Meanwhile, the inter-symbol interference is modeled and analyzed mathematically. Through numerical simulations and analyses, it is found that: (1) the influences of the spreading factor β, multipath number L, modulation dimension M, CSI/NonCSI, and SD/HD on the non-coherent capacity bounds are significant; (2) there is a relatively broad range of code rates corresponding to the optimal system power in U-shaped capacity curves of the non-coherent reception; and (3) the U-shaped non-coherent capacity bounds are proven to exist by investigating the mechanism of the low density parity check coded the M-ary DCSK system. These results are useful as benchmarks for designing power-efficient coded M-ary DCSK systems.

Multiresolution M-ary differential chaos shift keying (MR-M-DCSK) modulation using nonuniformly spaced phase constellation is a promising technique that can satisfy different bit-error-rate (BER) requirements within one symbol over multipath fading channels. However, the BER performance always deteriorates as the modulation order M becomes larger. To overcome this shortcoming, a new hierarchical square-constellation-based M-DCSK communication system using non-uniformly spaced distance constellation is proposed, which can be easily extended to other-constellation scenarios, e.g., rectangular, star, and asymmetrical square constellations. Furthermore, an adaptive transmission scheme is designed by modifying the distance between the two constellation points in the last hierarchical level. In addition, theoretical BER expressions of the proposed systems are derived over multipath Rayleigh fading channels, which are consistent with the simulated results. Analytical and simulated results show that the proposed system not only can provide lower energy consumption as compared with the conventional MR-M-DCSK system but also can efficiently adjust BER performance based on the signal-to-noise ratio information. Therefore, the proposed system can serve as a desirable alternative for energy-efficient short-range wireless-communication applications.

In this paper, a square-constellation-based M-ary differential chaos-shift-keying (M-DCSK) communication system framework is proposed. The symbol-error-rate expression of the proposed system is derived over additive white Gaussian noise as well as multipath Rayleigh fading channels. Moreover, the peak-to-average-power-ratio (PAPR) performance is carefully analyzed for the newly proposed system. Based on the square-constellation-based M-DCSK framework, a simple least-square estimator is designed to demodulate the information exploiting pilot-assistant symbols. Analytical and simulated results show that the proposed system benefits from a lower energy consumption, but suffers from a higher PAPR compared with the circle-constellation-based M-DCSK system.