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The remarkable advance of all-polymer solar cells (all-PSCs) achieved in the past decades is primarily powered by the innovation of polymer acceptors. However, most of high-performance all-PSCs are dominantly fabricated with halogenated solvents, which are detrimental to human bodies and the environment. Herein, eco-friendly solvent-processed all-PSCs were developed, based on wide-bandgap polymer poly[4,8-bis(5-(2-ethylhexylthio)thiophen-2-yl)-benzo-[1,2-b;4,5-b']dithiophene-alt-2,5-di(butyloctylthiophen-2-yl) -thiazolo[5,4-d]thiazole] (PSTZ) as donor and newly synthesized narrow-bandgap polymer 5,6-dicyano-2,1,3-benzothiadiazole indacenodithiophene (DCNBT-IDT) as acceptor. When processed with o-xylene and THF, PSTZ : DCNBT-IDT-based all-PSCs yielded remarkable power conversion efficiencies of 7.23 and 8.77 % with high short-circuit currents of 12.94 and 14.12 mA cm-2 , respectively. The results indicated that the utilization of an all-polymer blend based on narrow polymer acceptor and compatible polymer donor is an effective strategy for advancing eco-friendly solvent-processed all-PSCs.

Anomaly detection is an important issue in trajectory data mining. Various approaches have been proposed to address this issue. However, most previous studies focus only on outlier detection but rarely on pattern mining of anomalous trajectories. Mining patterns of anomalous trajectories can reveal the underlying mechanisms of these outliers. This paper studies four distinct patterns of anomalous trajectories, and proposes a method to detect and classify them. First, we present the difference and intersection set (DIS) distance metric to evaluate the similarity between any two trajectories. Based on this distance, we design an anomaly score function to quantify the differences between different types of anomalous trajectories and normal trajectories. We further propose an anomalous trajectory detection and classification (ATDC) method to find anomalies in different anomalous patterns. Finally, we evaluate the proposed ATDC method through extensive experiments on real cab trajectory data. The results show that the proposed approach outperforms existing methods by a significant margin.

A substrate plays a crucial role in controlled growth and property modulation of two-dimensional (2D) transition-metal dichalcogenides (TMDCs). In this work, we report multiple regulation over grow...

Baseline wander is a common problem in analysis with Fourier Transform Infrared Spectrometer (FTIR). And it is necessary to correct baseline drift for further quantitative and qualitative analysis....

With the development of laser technology, high power diode lasers have found the increasing various applications in many fields, including industry, advanced manufacturing, aerospace, Lidar and medical systems etc.. The near field non-linearity (Smile) and lasing uniformity of emitters for high power diode laser arrays are critical to high reliable optically coupled modules and laser heads in a cladding system. In order to obtain the lower smile and higher lasing uniformity, two CTEmatched substrates (Copper Tungsten-CuW) are employed to bond a single GaAs-based diode laser array with the cavity length of 2mm on a Micro Channel Cooler (MCC) using Gold-Tin hard solder. This double-CuW MCC-packaged structure is called DMCC which enables a diode laser array bonded on a CuW/MCC/CuW structure with all AuSn solder. Structural optimization has been carried out to reduce the thermal stress and smile for this package. Simulation results indicate that the smile and thermal stress is lowered 0.24μm and 16MPa, respectively. According to the simulation results, single bar DMCC-packaged diode lasers with lower Smile value are fabricated and characterized. The experimental results show that the ratio of Smile (average smile ~0.87μm) l1μm is ~71% and higher ~19% than that of conventional structure (average smile ~1.2μm). Importantly, the quantity ratio of lasing emitters (≥46 emitters) in a diode laser array is significantly raised from ~62% to 85% after the optimization of CuW submount.

Toothbrushing epilepsy is a rare form of reflex epilepsy (RE) with sporadic incidence. To characterize the genetic profile of reflex epilepsy patients with tooth brushing-induced seizures in a Chinese family. Solo clinical whole-exome sequencing (WES) of the proband, a 37-year-old Chinese man, was performed to characterize the genetic etiology of toothbrushing epilepsy. Mutations in the maternal X-linked synapsin 1 (SYN1) identified in the proband and his family members were confirmed by Sanger sequencing. The pathogenicity of these mutations was determined using in silico analysis. The proband had four episodes of toothbrushing-induced seizures. The semiology included nausea, twitching of the right side of the mouth and face, followed by a generalized tonic-clonic seizure (GTCS). The proband's elder maternal uncle had three toothbrushing-induced epileptic seizures at the age of 26. The proband's younger maternal uncle had no history of epileptic seizures but had a learning disability and aggressive tendencies. We identified a deleterious nonsense mutation, c.1807C>T (p.Q603Ter), in exon 12 of the SYN1 gene (NM_006950), which can result in a truncated SYN1 phosphoprotein with altered flexibility and hydropathicity. This novel mutation has not been reported in the 1000G, EVS, ExAC, gnomAD, or HGMD databases. We identified a novel X-linked SYN1 exon 12 mutant gene in a Chinese family with toothbrushing epilepsy. Our findings provide novel insights into the mechanism of this complex form of reflex epilepsy that could potentially be applied in disease diagnosis.

Room allocation is a challenging task in detention centers since lots of related people need to be held separately with limited rooms. It is extremely difficult and risky to allocate rooms manually, especially for organized crime groups with close connections. To tackle this problem, we develop an intelligent room allocation system for detention centers to provide optimized room allocation schemes automatically. We first formalize the detention room allocation problem as inverse graph partitioning, which can measure the quality of room allocation schemes. Then, we propose two heuristic algorithms to achieve the global optimization and local optimization of detention room allocation. Experiment results on real-world datasets show that the proposed algorithms significantly outperform manual allocation and suggest that the system is of great practical application value., Comment: Accepted by IEEE CASE 2021

Background The prenatal test of cell-free fetal DNA (cffDNA) is also known as noninvasive prenatal testing (NIPT) with high sensitivity and specificity. This study is to evaluate the performance of NIPT and its clinical relevance with various clinical indications. Methods A retrospective analysis was conducted on 14,316 pregnant women with prenatal indications, including advanced maternal age (≥35 years), maternal serum screening abnormalities, the thickened nuchal translucency (≥2.5 mm) and other ultrasound abnormalities, twin pregnancy/IVF-ET pregnancy, etc. The whole-genome sequencing (WGS) of maternal plasma cffDNA was employed in this study. Results A total of 189 (1.32%) positive NIPT cases were identified, and 113/189 (59.79%)cases were confirmed by invasive prenatal testing. Abnormal serological screening (53.14%) was the most common indication, followed by elderly pregnancy (23.02%). The positive prediction value for T21, T18, T13, sex chromosome abnormalities, other autosomal aneuploidy abnormalities, and CNV abnormalities were 91.84, 68.75,37.50, 66.67, 14.29, and 6.45%, respectively. The positive rate and the true positive rate of nuchal translucency (NT) thickening were the highest (4.17 and 3.33%), followed by the voluntary requirement group (3.49 and 1.90%) in the various prenatal screening indications. The cffDNA concentration was linearly correlated with gestational age (≥10 weeks) and the positive NIPT group’s Z-score values. Conclusions whole-genome sequencing of cffDNA has extremely high sensitivity and specificity for T21, high sensitivity for T18, sex chromosome abnormalities, and T13. It also provides evidence for other abnormal chromosomal karyotypes (CNV and non-21/18/13 autosomal aneuploidy abnormalities). The cffDNA concentration is closely related to the gestational age and determines the specificity of NIPT. Our results highlight NIPT’s clinical significance, which is an effective prenatal screening tool for high-quality care of pregnancy., Highlights The whole-genome sequencing of cell-free fetal DNA from maternal plasma is an effective prenatal screening tool for pregnancies with various prenatal indications.The concentration of cffDNA was linear with gestational age and the Z-score values of the positive NIPT group.NIPT has a significant positive predictive value for pregnancies with prenatal indications.

Synthesizing nanomaterials at the expense of solar energy and the associated energy generation have utmost significance as far as environmental sustainability is concerned. Here, sunlight-assisted ...

Range-ambiguous spacecraft relative orbits based on linear dynamics for elliptic chief orbits were studied for the purpose of sequential relative orbit estimation with range-only measurements. Usin...

The consensus extended Kalman filter is employed for the problem of multiple chief spacecraft cooperatively estimating the orbit of one deputy spacecraft in a connected communication network. The i...

Blockchain is experiencing rapid development and has the full potential of revolutionizing the IoT platform in the industrial field. In this paper, a light-weighted Blockchain-based platform for IIoT is presented to address security, trust, and island connection problem in the process of IIoT ecosystem construction. BPIIoT is comprised of the on-chain network and the off-chain network. All transactions are processed in the on-chain network such as including digital signature based on access control and programmable permission. The off-chain network deals with the storage, complex data processing, and other problems that blockchain cannot solve. The smart contract is utilized as the service contract of consumers and manufacture resources, providing on-demand manufacturing service. Two smart application cases, manufacturing equipment data sharing and maintenance service sharing from smart manufacturing, are implemented to explain the smart contract for equipment maintenance service and status data sharing service throughout maintenance, repair, and operation service network by the BPIIoT.

The outbreak and widely spread of coronavirus disease 2019 (COVID-19) has become a global public health concern. COVID-19 has caused an unprecedented and profound impact on the whole world, and the prevention and control of COVID-19 is a global public health challenge remains to be solved. The retrospective analysis of the large scale tests of SARS-CoV-2 RNA may indicate some important information of this pandemic. We selected 12400 SARS-CoV-2 tests detected in Wuhan in the first semester of 2020 and made a systematic analysis of them, in order to find some beneficial clue for the consistent prevention and control of COVID-19.SARS-CoV-2 RNA was detected in suspected COVID-19 patients with real-time fluorescence quantitative PCR (RT-qPCR). The patients' features including gender, age, type of specimen, source of patients, and the dynamic changes of the clinical symptoms were recorded and statistically analyzed. Quantitative and qualitive statistical analysis were carried out after laboratory detection.The positive rate of SARS-CoV-2 was 33.02% in 12,400 suspected patients' specimens in Wuhan at the first months of COVID-19 epidemics. SARS-CoV-2 RT-qPCR test of nasopharyngeal swabs might produce 4.79% (594/12400) presumptive results. The positive rate of SARS-CoV-2 RNA was significantly different between gender, age, type of specimen, source of patients, respectively (P < .05). The median window period from the occurrence of clinical symptom or close contact with COVID-19 patient to the first detection of positive PCR was 2 days (interquartile range, 1-4 days). The median interval time from the first SARS-CoV-2 positive to the turning negative was 14 days (interquartile range, 8-19.25 days).This study reveals the comprehensive characteristics of the SARS-CoV-2 RNA detection from multiple perspectives, and it provides important clues and may also supply useful suggestions for future work of the prevention and treatment of COVID-19.

Mobile crowdsensing enables people to collect and process a massive amount of information by using social resources without any cost on sensor deployment or model training. Many schemes focusing on the problems of task assignment and privacy preservation have been proposed so far. However, the privacy-preserving of requesters and task access control, which are vital to mobile crowdsensing, is barely considered in the literature. To address the aforementioned issues, a fine-grained task access control system for mobile crowdsensing is proposed. In particular, the requester can decide the group of task performers who can access the task by utilizing attribute-based encryption technology. T he untrusted crowdsensing platform cannot obtain any sensitive information concerning the requester or the task, while the qualified task performers are capable of retrieving tasks within 0.85 ms. Security analysis and experimental results are presented to show the feasibility and efficiency of the proposed system.

Background and Purpose. Diabetes is common in COVID-19 patients and associated with unfavorable outcomes. We aimed to describe the characteristics and identify the risk factors for COVID-19 patients complicated with diabetes. Methods. In this multicenter retrospective study, patients with COVID-19 in China were included and classified into two groups according to whether they were complicated with diabetes or not. Demographic symptoms and laboratory data were extracted from medical records. Univariable and multivariable logistic regression methods were used to explore the risk factors. Results. 538 COVID-19 patients were finally included in this study, of whom 492 were nondiabetes and 46 were diabetes. The median age was 47 years (IQR 35.0-56.0). And the elderly patients with diabetes were more likely to have dry cough, and the alanine aminotransferase, lactate dehydrogenase, Ca, and mean hemoglobin recovery rate were higher than the other groups. Furthermore, we also found the liver and kidney function of male patients was worse than that of female patients, while female cases should be paid more attention to the occurrence of bleeding and electrolyte disorders. Moreover, advance age, blood glucose, gender, prothrombin time, and total cholesterol could be considered as risk factors for COVID-19 patients with diabetes through the multivariable logistic regression model in our study. Conclusion. The potential risk factors found in our study showed a major piece of the complex puzzle linking diabetes and COVID-19 infection. Meanwhile, focusing on gender and age factors in COVID-19 patients with or without diabetes, specific clinical characteristics, and risk factors should be paid more attention by clinicians to figure out a targeted intervention to improve clinical efficacy worldwide.

For current 905nm pulsed laser diode(PLD) for LiDAR applications, most of them are single channel chips each with a power range of 75W-120W designed for scanning multiple single points. In this work, kilowatt 905nm light source based on eight channel 905nm PLD mini-bars had been designed and packaged using flip chip bonding technology. A series of kilowatt 905nm PLD modules were fabricated and characterized. The maximum output power of 982W limited by the pulse driver was obtained for the first time under the condition of 100V@5ns,100kHz at room temperature. The spectral width of FWHM and FW90%E was 5.1nm and 7.2nm, respectively. The far field divergence test data indicated that the fast axis divergence@1/e2 and slow axis divergence@1/e2 was 0.38°and 27.59°, respectively. In the future, the fast axis divergence@1/e2 and the slow axis FoV can be designed and optimized for any particular LiDAR system.

A high peak power annularly-stacked laser diode pump has been designed and manufactured for a solid state laser (SSL), which is constructed by 12 single annular stacks composed of 3-bar laser diode (LD) submodules. High peak power and high wavelength uniformity have been considered. Macro channel cooling has been used during the operation of the annular stacks, at typical coolant flow rate of 2L/min. Heat dissipation and stress of a single annular stack have been simulated by finite element software, which shows high temperature uniformity of 3-bar submodules (plus or minus 0.5℃) and low package stress (11.8MP). The peak power of the annularly stacked laser diode pump has reached 234kW at a peak current of 450A or less. A high uniformity of centroid wavelength (802 plus or minus1nm) with a full width at half maximum (FWHM) of 4nm has been measured. More than 24 million shots have been verified for the 3-bar LD submodules.

Identifying viruses is crucial for pandemics. Detecting pathogenic viruses is difficult and usually needs to spend lots of time. Here, we propose a multi-model fusion method for viruses pathogenic detection(MMFPV). We use CatBoost, Reverse-complement Convolutional Neural Networks, and, Reverse-complement Long Short-Term Memory(RC-LSTM) as base models, then, using stacking to combine these models. This method directly detects pathogenic viruses from next-generation sequencing data without virus databases. The result shows that this novel detection method has good capabilities.

Intelligent fault diagnosis methods based on deep learning have been widely used in intelligent manufacturing. Most of these methods focus on the diagnosis of fault data with the same distribution in a single domain, but pay poor attention to the diagnosis of cross-domain fault data with different distributions. To address this problem, this paper firstly integrates the fault datasets from eight universities into a cross-domain dataset. A new model named one-dimensional improved LeNet-5 (ID ILeNet-5) is proposed for cross-domain fault diagnosis. One-dimensional convolutional operation is used for feature extraction and batch normalization technique is introduced to accelerate the network convergence in this model. The effectiveness and generalization performance of this method are verified using the aforementioned cross-domain dataset. The results demonstrate that our method outperforms the state-of-the-art transfer learning model with fewer parameters and shorter training time.

The 2019 novel coronavirus (2019-nCoV) epidemic continues, with the number of infections and deaths increasing. The respiratory tract is the main route of transmission of the virus, and the majority of symptoms are respiratory relative. Until now, there has been no reports concerning the nervous system onset. We present a 2019-nCoV patient with the onset of simple dizziness, accompanied by dry throat, no fever, no cough, no headache, no mental abnormality, and no obvious abnormality in the nuclear magnetic resonance imaging (MRI) of the head. Meanwhile, chest computed tomography (CT) scans showed multiple small spot shadows and interstitial changes in the early stage, especially in the extrapulmonary zone. There was a development of multiple ground-glass shadows and infiltrative shadows in both lungs with mild pleural effusion. The nucleic acid gene detection was positive, and thus the diagnosis of 2019-nCoV was confirmed. At last, the prognosis was good after active treatment. After antiviral and anti-infective treatment, the symptoms recovered. We presume that 2019-nCoV can also manifest in the nervous system alone, and lung CT, which has relative specificity, should be used as a routine screening method.

SummaryBackground2019-Novel coronavirus (2019-nCoV) outbreaks create challenges for hospital laboratories because thousands of samples must be evaluated each day. Sample types, interpretation methods, and corresponding laboratory standards must be established. The possibility of other infections should be assessed to provide a basis for clinical classification, isolation, and treatment. Accordingly, in the present study, we evaluated the testing methods for 2019-nCoV and co-infections.MethodsWe used a fluorescence-based quantitative PCR kit urgently distributed by the Chinese CDC to detect 8274 close contacts in the Wuhan region against two loci on the 2019-nCoV genome. We also analyzed 613 patients with fever who underwent multiple tests for 13 respiratory pathogens; 316 subjects were also tested for 2019-nCoV.FindingsAmong the 8274 subjects, 2745 (33.2%) had 2019-nCoV infection; 5277 (63.8%) subjects showed negative results in the 2019-nCoV nucleic acid test (non-2019-nCoV); and 252 cases (3.0%) because only one target was positive, the diagnosis was not definitive. Eleven patients who originally had only one positive target were re-examined a few days later; 9 patients (81.8%) were finally defined as 2019-nCoV-positive, and 2 (18.2%) were finally defined as negative. The positive rates of nCoV-NP and nCovORF1ab were 34.7% and 34.7%, respectively. nCoV-NP-positive only and nCovORF1ab-positive cases accounted for 1.5% and 1.5%, respectively. In the 316 patients with multiple respiratory pathogens, 104 were positive for 2019-nCov and 6/104 had co-infection with coronavirus (3/104), influenza A virus (2/104), rhinovirus (2/104), and influenza A H3N2 (1/104); the remaining 212 patients had influenza A virus (11/202), influenza A H3N2 (11/202), rhinovirus (10/202), respiratory syncytial virus (7/202), influenza B virus (6/202), metapneumovirus (4/202), and coronavirus (2/202).InterpretationClinical testing methods for 2019-nCoV require improvement. Importantly, 5.8% of 2019-nCoV infected and 18.4% of non-2019-nCoV-infected patients had other pathogen infections. It is important to treat combined infections and perform rapid screening to avoid cross-contamination of patients. A test that quickly and simultaneously screens as many pathogens as possible is needed.FundingNo founding was receivedResearch in contextEvidence before this studyWe searched PubMed for articles published up to January 31, 2020 using the keywords “2019 novel coronavirus” or “2019-nCoV”. No published study on the characteristics of 2019-nCoV tests or 2019-nCoV co-infections was found. We only noted recent laboratory findings for other tests of patients infected with 2019-nCoV.Added value of this studyPositive detection of nCoV-NP or nCovORF1ab is presented, and individuals with/without 2019-nCoV infections or with inconclusive results were identified. Patients with inconclusive results may be diagnosed with 2019-nCoV infection or found to be negative for the infection after resampling and retesting in the next few days. Approximately 5.8% of the subjects diagnosed with 2019-nCoV had co-infection.Implications of all the available evidenceManagement of the population showing inconclusive results should be given attention; additionally, such results can be minimized by improving the sampling, sample pretreatment, and testing methodologies. When diagnosing 2019-nCoV subjects, the possibility of co-infection should be considered. Finally, better clinical detection methods are needed to simultaneously screen as many pathogens as possible.

Mid-infrared (MIR) light-emitting devices play a key role in optical communications, thermal imaging, and material analysis applications. Two-dimensional (2D) materials offer a promising direction for next-generation MIR devices owing to their exotic optical properties, as well as the ultimate thickness limit. More importantly, van der Waals heterostructures—combining the best of various 2D materials at an artificial atomic level—provide many new possibilities for constructing MIR light-emitting devices of large tuneability and high integration. Here, we introduce a simple but novel van der Waals heterostructure for MIR light-emission applications built from thin-film BP and transition metal dichalcogenides (TMDCs), in which BP acts as an MIR light-emission layer. For BP–WSe2 heterostructures, an enhancement of ~200% in the photoluminescence intensities in the MIR region is observed, demonstrating highly efficient energy transfer in this heterostructure with type-I band alignment. For BP–MoS2 heterostructures, a room temperature MIR light-emitting diode (LED) is enabled through the formation of a vertical PN heterojunction at the interface. Our work reveals that the BP–TMDC heterostructure with efficient light emission in the MIR range, either optically or electrically activated, provides a promising platform for infrared light property studies and applications., Thin-film semiconductors enhance black phosphorus mid-infrared light emission Layering thin films of semiconducting transition metal dichalcogenides with thin-film black phosphorus enhances its ability to emit mid-infrared (MIR) light, which could facilitate MIR light emission investigations and applications. Xiaolong Chen of China’s Southern University of Science and Technology and colleagues layered thin flakes of black phosphorus (BP) with one or the other of a monolayer of tungsten diselenide (WSe2) or a thin film of molybdenum disulfide (MoS2). Thin-film BP is considered a promising MIR material, with potential applications in MIR photodetection and optical modulation. WSe2 efficiently transferred light energy to the BP, enhancing its MIR photoluminescence by up to 192%. On the other hand, the interface created by layering BP with MoS2 enabled the formation of a MIR light-emitting diode at room temperature.

We propose a mechanism to generate a single intense circularly polarized attosecond x-ray pulse from the interaction of a circularly polarized relativistic few-cycle laser pulse with an ultrathin foil at normal incidence. Analytical modeling and particle-in-cell simulation demonstrate that a huge charge-separation field can be produced when all the electrons are displaced from the target by the incident laser, resulting in a high-quality relativistic electron mirror that propagates against the tail of the laser pulse. The latter is efficiently reflected as well as compressed into an attosecond pulse that is also circularly polarized.

Background: Few studies have examined the association between treatment given time and clinical outcomes, which is indeed of great importance to clinical management of coronavirus disease 2019 (COVID-19). We performed this study to explore whether early treatment brings favorable clinical outcomes. Methods: In this retrospective multicenter study, we included patients aged 18 to 87 years with confirmed COVID-19 on admission from 54 hospitals in nine provinces of China from 21 January to 10 March, 2020. Final date of follow-up was March 17, 2020. All patients were treated by Lung cleansing & detoxifying decoction combined with western medicine. Patients were divided into four groups according to the interval from the first date of onset of symptoms to the date of starting a treatment, i.e., ≤1 week group (≤7 days), 1-2 weeks group (>7 days and ≤14 days), 2-3 weeks group (>14 days and ≤21 days) and >3 weeks group (>21 days). Multivariable Cox proportional hazard ratio (HR) models were used to estimate unadjusted and adjusted HRs and 95% confidence intervals (CIs) for the association between the treatment given time and clinical outcomes (time to recovery, days of viral shedding, duration of hospital stay, course of disease, fever and CT images). Findings: Of the 782 patients (median age was 46 years old, and 405 (52%) were male), there were 321 (41%) patients in ≤1 week group, 221 (28%) in 1-2 weeks group, 123 (16%) in 2-3 weeks group and 117 (15%) in >3 weeks group. Compared to patients in later treatment group (greater than 3 weeks), patients in earlier treatment groups of less than 1 week, 1 to 2 weeks, or 2 to 3 weeks had higher likelihood of recovery, with adjusted HR (95% CI) of 3.81 (2.65-5.48), 2.63 (1.86-3.73) and 1.92 (1.34-2.75), respectively. The median days of viral shedding was 13 days and 12 days in 2-3 weeks group and 3 weeks group (P=0.0137). The median course of disease decreased from 34 days to 24 days, 21 days and 18 days when treatment was given every one week in advance compared to that was given later than 3 weeks from the onset of symptoms (P

With the emergence of numerous link prediction methods, how to accurately evaluate them and select the appropriate one has become a key problem that cannot be ignored. Since AUC was first used for link prediction evaluation in 2008, it is arguably the most preferred metric because it well balances the role of wins (the testing link has a higher score than the unobserved link) and the role of draws (they have the same score). However, in many cases, AUC does not show enough discrimination when evaluating link prediction methods, especially those based on local similarity. Hence, we propose a new metric, called W-index, which considers only the effect of wins rather than draws. Our extensive experiments on various networks show that the W-index makes the accuracy scores of link prediction methods more distinguishable, and it can not only widen the local gap of these methods but also enlarge their global distance. We further show the reliability of the W-index by ranking change analysis and correlation analysis. In particular, some community-based approaches, which have been deemed effective, do not show any advantages after our reevaluation. Our results suggest that the W-index is a promising metric for link prediction evaluation, capable of offering convincing discrimination.

Brain storm optimizer (BSO), a new swarm intelligence paradigm inspired from the human brainstorming process, have received a surge of attentions. However, the original BSO easily suffers from the premature convergence due to its ineffective solution generation operation. In this paper, a two-stage learning strategy is proposed to accelerate the efficiency of the solution generation operation in BSO, thereby enhancing the convergence speed as well as the diversity of population. At the first stage, a learning automaton strategy is conducted to select an appropriate learning exemplar to guide the updating of each solution (i.e., idea). This strategy learns from the feedback information from the environment to enhance the exploration and exploitation. At the second stage, a comprehensive learning strategy is used to generate a set of directional learning exemplars, using utilize useful search experiences during the search. The experimental results on a set of CEC2017 benchmarks validate the effectiveness of the proposed strategy. Then, the resultant algorithm called ACLBSO is applied to resolving the quantitative association rule mining problem. Simulation results show that ACLBSO is a satisfactory optimizer to deal with the complex association rule mining problems.

Background: Novel coronavirus pneumonia (NCP) is often changing rapidly and fatal. Early detection and early triage of coronavirus disease 2019 (Covid-19) is the key to success management of the disease. An easily obtainable yet accurate variable for both diagnosis and prognosis is urgently needed. We aim to report predictive Value of the Neutrophil-to-Lymphocyte Ratio(NLR) for diagnosis and worse clinical course of the COVID-19, which have not been well demonstrated. Methods: Our study consisted of two stages, at the first stage, a retrospective, single-center, cohort study including was conducted in Heilongjiang, on admission, demographic, clinical, and laboratory data were collected and compared between patients with COVID-19 and patients with non COVID-19; we used multivariable logistic regression methods to explore the risk factors associated with COVID-19;A receiver operating characteristic(ROC) analysis was conducted to calculate the area under the curve(AUC) to assess predictive value of NLR for diagnosis of COVID 19. At the second stage, we conducted retrospective, multi-center and large sample study in 43 hospitals from ten provinces of China, COVID-19 patients with laboratory-confirmed divided into three groups including mild cases, ordinary cases and severe cases. Multivariate logistic regression methods were used to identify the risk factors for the deterioration of COVID-19, along with, a receiver operating characteristic (ROC) curve was also drawn to assess impact on the clinical course of the COVID-19. Findings: We recruited a total of 635 patients with COVID-19 and 27 cases with non COVID-19(Viral pneumonia) from 28 January to 25 February. A total of 88 cases were enrolled with a retrospective, single-center, cohort study from Heilongjiang province, of these, COVID-19 cases were 61(69%) and non COVID-19 cases were 27(31%). On admission, fever (69%) was the most common symptoms, cough (56%) and fatigue(53%). An average(SD) of NLR of COVID-19 patients and non- COVID-19 patients were3.48±2.04 and 2.21±1.14, respectively. multivariable regression showed increasing odds of COVID-19 patients associated with NLR(odds ratio 1.752, 95% CI 1.111-2.763, per 1 unit increase; p=0.016). In addition, the area under the curve (AUC) of NLR was 0.707 and cutoff value was 2.22. At the second stage, 635 patients with COVID were enrolled with a retrospective, multi-center, large sample study in the 43 settings from 10 provinces, of these, mild case were 86(14%), ordinary cases [486(76%)],severe cases[63(10%)], common symptoms was at onset of disease were cough[356(56%)], an average of NLR of 635 patients was 4.04±4.68, and elevated NLR with the deterioration of clinical course[mild case(2.73±2.28), ordinary cases(3.58±3.07), severe cases(9.38±10.52), P

BackgroundA worldwide outbreak of coronavirus disease (COVID-19), since 2019, has brought a disaster to people all over the world. Many researchers carried out clinical epidemiological studies on patients with COVID-19 previously, but risk factors for patients with different levels of severity are still unclear.Methods562 patients with laboratory-confirmed COVID-19 from 12 hospitals in China were included in this retrospective study. Related clinical information, therapies, and imaging data were extracted from electronic medical records and compared between patients with severe and non-severe status. We explored the risk factors associated with different severity of COVID-19 patients by logistic regression methods.ResultsBased on the guideline we cited, 509 patients were classified as non-severe and 53 were severe. The age range of whom was 5–87 years, with a median age of 47 (IQR 35.0–57.0). And the elderly patients (older than 60 years old) in non-severe group were more likely to suffer from fever and asthma, accompanied by higher level of D-dimer, red blood cell distribution width and low-density lipoprotein. Furthermore, we found that the liver and kidney function of male patients was worse than that of female patients in both severe and non-severe groups with different age levels, while the severe females had faster ESR and lower inflammatory markers. Of major laboratory markers in non-severe cases, baseline albumin and the lymphocyte percentage were higher, while the white blood cell and the neutrophil count were lower. In addition, severe patients were more likely to be accompanied by an increase in cystatin C, mean hemoglobin level and a decrease in oxygen saturation. Besides that, advanced age and indicators such as count of white blood cell, glucose were proved to be the most common risk factors preventing COVID-19 patients from aggravating.ConclusionThe potential risk factors found in our study have shown great significance to prevent COVID-19 patients from aggravating and turning to critical cases during treatment. Meanwhile, focusing on gender and age factors in groups with different severity of COVID-19, and paying more attention to specific clinical symptoms and characteristics, could improve efficacy of personalized intervention to treat COVID-19 effectively.

AIM As we are experiencing the progressive aging of our population, risk management of geriatric orthopedic patients is extremely important. The present study was carried out to identify independent predictors of surgical site infection and to better define the threshold value of serum albumin on postoperative wound infection in older patients. METHODS This retrospective multicenter study was carried out from January 2015 to June in 2017. A total of 3378 older patients (aged ≥60 years) were enrolled. We extracted the patients' demographics, characteristics of disease, treatment-related variables and indexes of laboratory examination. Receiver operating characteristic analysis was carried out to find the optimum cut-off value for serum albumin. Univariate and multivariate logistic analysis models were carried out, respectively, to determine independent predictors of surgical site infection. RESULTS A total of 123 patients developed wound infection in the present study. Surgical site infection prolonged hospitalization of patients by a mean of 14.2 days. The overall incidence was 3.64%, with 0.47% for deep infection and 3.16% for superficial infection. Independent predictors of surgical site infection identified by multivariate analysis were traumatic injury (odds ratio 12.42, 95% CI 6.80-22.12; P = 0.000), serum albumin

This paper describes a manifold of ambiguous spacecraft relative orbits that arise in sequential relative orbit estimation. The development herein assumes linear relative dynamics, a circular reference orbit, and range-only measurements. Using a formulation based on relative orbit elements, the ambiguous orbits are categorized into two cases: mirror orbits, which conserve the size and shape but transform the orientation of the true relative orbit, and deformed orbits, which both distort the shape and change the orientation. A special case, that of central ambiguous relative orbits, which are geometrically symmetric relative to the chief's local-vertical-local-horizontal frame is also discussed. The multiplicity of mirror ambiguous orbits, deformed ambiguous orbits and central ambiguous orbits are shown to be three, four and infinity, respectively. Numerical results using an extended Kalman filter are provided to confirm the existence of these ambiguous orbits. Furthermore, the observability is studied analytically with a nonlinear observability criterion using Lie derivatives. It is also shown by numerical results that the inclusion of nonlinearities in the filter model can help resist the tendency of an extended Kalman filter to converge to the ambiguous relative orbits. Finally, the persistence of these ambiguous orbits under unmodeled chief eccentricity error and J2 perturbation is studied.

Two series of dual-core star-shaped polyfluorenes (DC-TPAs and DC-SBFs) based on a small quantity of green-emitting phenylmaleimide cores and a good deal of non-emissive cores were prepared by a one-pot Suzuki reaction. Triphenylamine (TPA) and 9,9-spirobifluorene (SBF) are employed as the non-emissive cores to construct DC-SBFs and DC-TPAs, respectively. Due to the π-conjugation extended by the fluorene units, the phenylmaleimide core displays a yellow emission which contributes to the white emission with the blue-emitting polyfluorene arms. DC-SBFs with four arms exhibit a better protection for emissive cores and a higher energy transfer efficiency than DC-TPAs with three arms. Consequently, the quantum yield of white emission of the polymers in the film was improved by changing TPA into SBF as the non-emissive core, reaching 0.80 for DC-SBF03. Additionally, the electrons and holes can be transported smoothly in DC-SBFs. A very high electroluminescent efficiency was obtained for DC-SBF03 with a maximum luminous efficiency of 17.4 cd A−1, power efficiency of 10.9 lm W−1 and external quantum efficiency of 6.2% when applied in the solution-processing white polymeric light-emitting devices (WPLEDs) with a LiF/Al cathode. The results denote that the non-emissive core plays a key role in the performance of the star-shaped single white polymers. It provides another way to improve the efficiencies of WPLEDs by designing simple non-emissive cores of the dual-core polymers, and avoiding the complicated synthesis of fluorophores.

State estimation is a key issue of battery management system (BMS) to improve the energy utilization of lithium-ion battery in electric vehicle, the performance of which relies on the accuracy of equivalent model over full-range sate of charge (SOC). However, the widely applied equivalent circuit model (ECM) has limitations at low SOC range. In this paper, an optimized equivalent model is proposed combining the lithium-ion battery internal electrochemical processes with the ECM. For one thing, the proposed model is able to offer high accuracy by considering solid-phase diffusion into the update of open circuit voltage (OCV) and describing the polarization at the solid-liquid interface from the electrochemical perspective. For another thing, the proposed approximate method for describing internal electrochemical micro-variables with external electric macro-variables allows the model to avoid a series of partial differential equations. In addition, online parameter identification based on the forgetting factor based recursive least square method (FFRLS) makes the proposed model well-adapted to dynamic working conditions. Compared with the ECM under multiple working conditions, the proposed model is proven to provide a better performance over full-range SOC especially at the low-range area below 20%.

Temperature measurement is critical for many scientific experiments and technological applications. Diverse thermometers have been developed for the thermal sensing at macroscopic length scales. However, in situ and quantitative temperature measurement of nanoscale objects in a convenient approach is still a challenge. Here, we demonstrate a new type of optically readable VO2 nanowire-based thermometer, based on the unique axial gradient phase transition behavior along single-domain VO2 nanowires, which is attributed to the hydrogen doping of single-crystalline VO2 nanowires through hydrothermal fabrication and the hydrogen engineering via a postannealing process. Besides the appropriate microscopic size and user-friendly operation, the as-prepared optically readable VO2 nanowire-based thermometers have ultrahigh relative sensitivity (∼17.4%/K) and temperature resolution (∼0.026 K), enabling the sensitive monitoring of the thermal environment of small spaces or the temperature of even nanoscale structures.

Gas explosion in coal mines caused a large number of deaths, injuries and property losses. Gas explosion still happens occasionally in recent years. It is known that most people died from CO poisoning in gas explosion. But the details of toxic gases produced and their impacts on people need further investigation. In order to study the products and species in gas explosion, an analysis of chemical kinetic characteristics was conducted using CHEMKIN III with detailed mechanism (GRI-Mech3.0) package. A closed homogeneous 0-D reactor was adopted to investigate the kinetic behavior of gas explosion. The initial conditions were set, similar to those in the real tunnel environment. The profiles of four reactants, toxic gases and free radicals were obtained. The threshold values of people exposed to different poisonous gases were analyzed to study their impacts on people. Sensitivity analysis of key elementary reaction to free radical was performed to find possible reactions which can suppress gas explosion. The results show that the ignition delay time is the longest at fuel-rich condition. The O 2 concentration decreases from 19% to 2% at stoichiometric ratio, which could not support normal respiration after explosion. It is found that the concentration of CO ranks the highest among the four toxic gases. Toxicity analysis indicates that those exposed to such condition will soon die of asphyxia. This is consistent with the accident investigation findings that the majority of fatalities result from inhalation of CO. The concentration of CO at fuel-rich condition is higher than that at fuel-lean condition. The relationship between the final free radical concentration and initial CH 4 concentration exhibits a reverse U shape. Sensitivity analysis reveals that free radicals are mostly sensitive to the intermediate reaction R156 (forward direction) and R158 (reverse direction). It provides a possible direction to research the corresponding chemicals for gas explosion suppression. This work would provide theoretical support for gas explosion suppression technology and decision-making of personal protection in rescuing trapped coal miners. It is of great importance for developing suppression chemicals of gas explosion.

Background: Proprioceptive recovery has received an increased amount of attention after undergoing anterior cruciate ligament (ACL) reconstruction. However, ACL reconstruction without rehabilitation training could not significantly improve the reduction and function of the proprioceptor. This study aimed to explore whether nerve growth factor (NGF) could cause proprioceptive changes after ACL reconstruction through histopathological and electrophysiological evaluations. Methods: A total 28 mature New Zealand white rabbits were used in the study, 24 to develop the model of ACL injury and ACL reconstruction. These included the experimental group (n=12; injected with NGF 20 µg/week at the second month after surgery) and the experimental control group (n=12), and 4 for blank control group. In the 4th, 8th, and 12th months, the changes in ACL nerves were measured by somatosensory evoked potentials (SEPs) and electromyogram (EMG). Furthermore, gold chloride staining was performed to detect the changes in morphology and quantity of the proprioceptors in ACL. Results: Electrophysiological tests showed that the incubation of SEPs and EMG in both the experimental group and the experimental control group were prolonged, and the amplitude decreased when compared with the blank control group (all, P

Predictive Maintenance (PdM) is a maintenance strategy which predicts equipment failures before they occur and then performs maintenance in advance to avoid the occurrence of failures. A PdM system generally consists of four main components: data acquisition and preprocessing, fault diagnostics, fault prognostics and maintenance decision-making. Recently, massive condition monitoring data of equipment, also known as the industrial big data, has shown explosive growth. A large number of research works, including theoretical studies and industrial applications, have focused on implementing PdM with industrial big data analytics. This paper aims to provide a brief overview on the PdM system in the era of big data, with a particular emphasis on models, methods and algorithms of data-driven fault diagnostics and prognostics. In addition, a conclusion with a discussion on possible future trends in the research field of PdM is also given.

Sentence similarity modeling plays an important role in Natural Language Processing (NLP) tasks, and thus has received much attention. In recent years, due to the success of word embedding, the neural network method has achieved sentence embedding, obtaining attractive performance. Nevertheless, most of them focused on learning semantic information and modeling it as a continuous vector, while the syntactic information of sentences has not been fully exploited. On the other hand, prior works have shown the benefits of structured trees that include syntactic information, while few methods in this branch utilized the advantages of sentence compression. This paper makes the first attempt to absorb their advantages by merging these techniques in a unified structure, dubbed as CACV-tree (Compression Attention Constituency Vector-tree). The experimental results, based on 14 widely used datasets, demonstrate that our model is effective and competitive, compared against state-of-the-art models.

Muscle quality and the physiological condition of fish are affected greatly by the culture environment. In aquaculture ponds, a bio-floating bed planted with vegetation is often used to improve water quality. This study investigated the growth and muscle quality of grass carp (Ctenopharyngodon idellus) cultured in ponds equipped with bio-floating beds. Fish were cultured in two replicated pond groups from May to November. Fish in the first group were cultured in the experimental ponds equipped with a bio-floating bed planted with Ipomoea aquatica, whereas fish in the other group were reared in the control ponds without a bio-floating bed. Compared with the control ponds, the experimental ponds had better water quality with significant lower concentrations of nitrite and ammonia. Grass carp in the experimental group obtained greater muscle weight gain, significant higher content of crude protein, and significant lower crude fat level than the fish in the control group. The muscular levels of pH, water-holding capacity, and antioxidant capacity decreased significantly in the control group compared to the experimental group. Texture profile analysis revealed higher values of hardness, springiness, gumminess, and chewiness of white muscle in the experimental group. The higher values of cohesiveness and resilience of white muscle occurred in the control group. The fillets of fish in the experimental group also received higher grades in the sensory evaluation of springiness, overall acceptability, aroma, and palatability. These results indicate that growth performance and muscle quality of grass carp were improved by the application of bio-floating bed technology in the culture ponds.

High power QCW diode laser stacks have been widely used in pumping applications for years. Different package structures of diode laser stacks are applied for pumping the cylindrical rod crystal, such as modular G-Stack, horizontal, vertical and annular arrays. Annular array is preferred in pumping of QCW mode with low duty cycle and short pulse width, due to the advantage of compact structural size, uniform light beam distribution and convenient electric connection. However, the development of annular diode laser array using hard solder is difficult because of the complex bonding process of diode laser on annular heatsink with conventional bonding fixture. Furthermore the stress and thermal behavior is yet to be well studied on the annular diode laser array. In this work, a sophisticated annular diode laser array was developed using hard solder. Optimized structure and thermal design were conducted to achieve uniform light beam distribution and good heat dissipation. Stress release structure of diode laser stack is applied to reduce the risk of chip crack and deviation of spatial spectrum. The annular diode laser array consists of 44 bars in a ring, with the peak output power of each bar over 500W. The maximum output power of each bar reaches 673 W.

With the rapid development of economy, the lifespan of electronic products has been shortened, leading to the generation of more and more electronic waste (E-waste). E-waste that is composed of metals and metalloids has been paid much attention by researchers from all over the world. Methods including physical, chemical, and biological technologies are adopted to dispose of E-waste. Considering energy consumption and environmentally friendly advantages, biological methods are regarded as the most suitable technology for disposing of E-waste. This chapter discusses the generation of E-waste in the world, the introduction of multiple technologies in disposing E-waste, especially the biological method, and the specific applications of the biological method in E-waste, which using microorganisms to extract precious metals, heavy metals, and metalloids. The mechanisms and influencing factors of the biological method are introduced. An example of the biological method in recycling of E-waste is also investigated. The applications of biological method in E-waste relevant areas are also discussed. Finally, the prospects for applications of the biological method for E-waste are also highlighted.

Reduction of the customers’ exposure risk of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in the retail buildings, i.e., supermarkets and small shops where residents purchase daily necessities is of prime importance during pandemic. In this study, the main influencing factors of the exposure risk of SARS-CoV-2, namely the occupant density, dwell time, and fresh air volume per person, were on-sited measured in 5 supermarkets and 21 small shops in Shenzhen, China. The small shops with an occupant area per person of 4.7 m2/per presented a more crowded environment than the supermarkets with an occupant area per person of 18.8 m2/per. The average dwell time of customers in the supermarkets linearly increased with the floor area and its probability distribution was fitted well by the Gamma distribution with a shape parameter of 3.0. The average dwell time of customers in the supermarkets was relatively longer than the combination of five types of small shops. In addition, the measured average outdoor air change rate of the small shops by natural ventilation was 10.7 h−1, while that of the supermarkets by mechanical ventilation was only 0.7 h−1. Correspondingly, the CO2 concentration in the small shops was 100–150 ppm lower than the supermarkets. The small shops provided an average fresh air volume per person of 216 m3/(h·per), far exceeding the supermarkets with a value of 95 m3/(h·per).

Rational design of photocatalyst with wide solar-spectrum absorption, negligible electron-hole recombination, and maximized redox potential is an essential prerequisite for achieving commercial-scale photocatalytic H2 production. This contribution combines surface plasmon resonance and Z-scheme charge transport in a single photocatalyst (Ag-ZnO-CeO2 heterostructure) aiming to improve its performance for photocatalytic H2 production. The Ag-ZnO-CeO2 heterostructure is fabricated via sunlight-driven combustion and deposition approaches. The successful construction is confirmed by several characterization techniques. The Z-scheme configuration is verified by in situ irradiated XPS and ESR analyses. Ag plays dual rules as an electron mediator to facilitate the Z-scheme charge transport and plasmonic material to maximize the light absorption in the visible region. The designed photocatalyst exhibits significantly enhanced photocatalytic activity for H2 production (18345 μmol h−1 g−1) under simulated sunlight irradiation. This work offers the opportunity of constructing efficient Z-scheme photocatalyst from wide bandgap semiconductors with full-visible light response, suppressed electron-hole recombination, and optimized redox potential.

Introduction: This meta-analysis aims to assess the effectiveness and safety of warm acupuncture therapy for treating Primary sciatica. Methods: The following 9 databases will be search from their inception to December 6, 2020: MEDLINE, EMBASE, the Cochrane Central Register of Controlled Trials (CENTRAL), the Chinese Biomedical Literature Database (CBM), the Chinese Medical Current Content (CMCC), the Wan-Fang Database and the China National Knowledge Infrastructure (CNKI). Randomized controlled trials (RCTs) of warm acupuncture for treating Primary sciatica, Chinese or Japanese without restriction of publication status will be included. Two researchers will independently undertake study selection, extraction of data and assessment of study quality. Meta-analysis will be conducted after screening of studies. Data will be analyzed using risk ratio for dichotomous data, and standardized mean difference or weighted mean difference for continuous data. Dissemination: This meta-analysis will be disseminated electronically through a peer-reviewed publication or conference presentations. Conclusion: This study will provide evidence to judge whether warm acupuncture Trial registration number: INPLASY2020120109.

Foam ceramics as a porous medium have demonstrated huge utilization potentiality to suppress multiple and continuous gas explosions in coal mines. Explosion suppression ability and thermal conducti...

A large number of saliency models, each based on a different hypothesis, have been proposed over the past 20 years. In practice, while subscribing to one hypothesis or computational principle makes a model that performs well on some types of images, it hinders the general performance of a model on arbitrary images and large-scale data sets. One natural approach to improve overall saliency detection accuracy would then be fusing different types of models. In this paper, inspired by the success of late-fusion strategies in semantic analysis and multi-modal biometrics, we propose to fuse the state-of-the-art saliency models at the score level in a para-boosting learning fashion. First, saliency maps generated by several models are used as confidence scores. Then, these scores are fed into our para-boosting learner (i.e., support vector machine, adaptive boosting, or probability density estimator) to generate the final saliency map. In order to explore the strength of para-boosting learners, traditional transformation-based fusion strategies, such as Sum , Min , and Max , are also explored and compared in this paper. To further reduce the computation cost of fusing too many models, only a few of them are considered in the next step. Experimental results show that score-level fusion outperforms each individual model and can further reduce the performance gap between the current models and the human inter-observer model.

Graphical abstract, The coronavirus disease 2019 (COVID-19) epidemic has been almost controlled in China under a series of policies, including “early diagnosis and early treatment”. This study aimed to explore the association between early treatment with Qingfei Paidu decoction (QFPDD) and favorable clinical outcomes. In this retrospective multicenter study, we included 782 patients (males, 56 %; median age 46) with confirmed COVID-19 from 54 hospitals in nine provinces of China, who were divided into four groups according to the treatment initiation time from the first date of onset of symptoms to the date of starting treatment with QFPDD. The primary outcome was time to recovery; days of viral shedding, duration of hospital stay, and course of the disease were also analyzed. Compared with treatment initiated after 3 weeks, early treatment with QFPDD after less than 1 week, 1-2 weeks, or 2-3 weeks had a higher likelihood of recovery, with adjusted hazard ratio (HR) (95 % confidence interval [CI]) of 3.81 (2.65–5.48), 2.63 (1.86-3.73), and 1.92 (1.34-2.75), respectively. The median course of the disease decreased from 34 days to 24 days, 21 days, and 18 days when treatment was administered early by a week (P < 0.0001). Treatment within a week was related to a decrease by 1-4 days in the median duration of hospital stay compared with late treatment (P

Single-crystalline vanadium dioxide nanowires (VO2 NWs) have attracted significant interest due to their unique characteristics, which originate from the single-domain metal–insulator phase transition (MIT) property. However, the lack of facile technologies to produce vertical nanowire arrays (NAs) in a large area has limited the mass fabrication of VO2-based devices. Here, an antimony-assisted hydrothermal method is developed for the low-temperature production of wafer-scale vertical VO2 NAs on arbitrary substrates of glass, quartz, and silicon. Sb2O3 plays a key role in the controlled growth of pure VO2 (M1) by modulating the size, density, alignment, and MIT properties of VO2 NAs. Furthermore, the growth mechanism of vertical VO2 NAs is explained. In contrast to conventional fabrication technologies, the weak interaction between NA films and substrates enables a much easier transfer of VO2 NAs for various potential applications.

Hierarchical nanostructures are ideal architectures to harvest solar energy. The understanding of light absorption in single hierarchical structures is emergently important and greatly helpful in enhancing multiscale optical phenomena and light management. However, due to the geometrical complexity of hierarchical architectures, theoretical and experimental studies of light absorption have faced significant challenges. Here, we directly quantify light absorption in single hierarchical structures for the first time by utilizing VO2-based near field powermeter. It is found that light trapping is significantly enhanced in rough microwires when the roughness amplitude is comparable to the incident light wavelength. The roughness enhanced light absorption is verified as a general phenomenon on both VO2 and Si hierarchical structures. Therefore, our work not only provides a simple and quantitative method of measuring light absorption upon single geometrically complex structures in micro/nanoscale, but also contributes a general rule to rationally design of hierarchical structures for enhanced performance in photoelectric and photochemical applications.

Cold cathode fluorescent lamps (CCFLs), with mercury as their essential component, were widely used as backlight in liquid crystal display (LCD) appliances before 2008. Since 2008, the mercury-free light emitting diode started to be used as a substitute for CCFLs and the replacement finished in about 2014. Nowadays, CCFLs are obsolete products from the viewpoint of manufacture but they are important as waste. In recent years, large amounts of CCFLs are flowing to waste phase for treatment and this has become a major issue in most countries. To better understand and control the risk of CCFLs, the stock of mercury in CCFLs, its flow to waste phase and mercury emission with the life cycle of CCFLs in mainland China were estimated in this study. Results showed that there was 15.2 tons of mercury stocked in CCFLs in main LCD appliances (i.e., LCD televisions, LCD monitors, and laptop monitors) from 2003–2015. CCFLs and mercury started to flow to waste phase around the year 2007 and will likely peak in 2018 with an annual flow of 324.8 million units and 1.5 tons respectively, then will likely decline dramatically till 2030. Dismantling and production were the two main life stages of CCFLs with mercury vapor release, during which approximately 2.1 tons and 1.2 tons of mercury were released to the atmosphere respectively. The research also indicates that mercury recycling in specialized facilities was another life stage with high mercury emission risk in which the processes of shredding, separation, and residue disposal are inevitably accompanied by mercury release.