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Authentication mechanisms deployed on access control systems undertake the responsibility of judging user identity to prevent unauthorized individuals from illegally approaching. In this article, we propose LIPAuth leveraging hand-dependent L ight I ntensity P attern to Auth enticate users. To be specific, lights released by a screen, are blocked and reflected by one hand above it; in this propagation process, hands exhibit user-specific ability in driving light absorption and attenuation due to owning unique structures, thereby outputting discriminative intensity patterns representing user identity. To implement LIPAuth , we first study the impact of screen contents on light intensity patterns, also explore the possibility of embedding hand structure biometrics into these patterns. We then design a customized dynamic stimulus-response mechanism for LIPAuth and make it resilient to the risks of potential registration profile leakage. Subsequently, we construct a joint pipeline consisting of signal processing and a learning-based generative adversarial network to overcome interference from variable user behaviors. More importantly, LIPAuth just utilizes common sensors to capture light signals, hence achieving low cost. We finally conduct extensive experiments in three scenarios to evaluate the authentication performance of LIPAuth prototype.

Objectives: In this study, we analyzed negative online public opinion in tertiary hospitals and evaluated corresponding risk by applying the Kaiser Model. Methods: Through data and expert group discussion, combined with the hospital's actual negative online public opinion management, we determined the opinions posing higher risk. The hospital's risk questionnaire for negative opinion was designed based on the Kaiser Model. The whole hospital staff was then trained and investigated. An Excel worksheet was used for statistical analysis and risk calculation.Results: According to the ranking of risk value, the top 5 negative online public opinions were drug supply and demand, in-hospital parking, handling of public health emergencies, the service attitude of hospital guidance staff, and interpretation of medical insurance policies. Conclusion: The hospital needs to revise and improve the emergency response plan for negative online public opinion based on the analysis results and reports of opinion risks. This is helpful for strengthening hospital-level emergency training, improving the hospital's ability to manage negative opinion risks, and promoting the hospital to become passive about negative online public opinion.

In preparation for an experiment with a laser-generated intense proton beam at the Laser Fusion Research Center at Mianyang to investigate the 11B(p,α)2α reaction, we performed a measurement at very low proton energy between 140 keV and 172 keV using the high-voltage platform at the Institute of Modern Physics, Lanzhou. The aim of the experiment was to test the ability to use CR-39 track detectors for cross-section measurements and to remeasure the cross-section of this reaction close to the first resonance using the thick target approach. We obtained the cross-section σ = 45.6 ± 12.5 mb near 156 keV. Our result confirms the feasibility of CR-39 type track detector for nuclear reaction measurement also in low-energy regions.

RFID technology has recently been exploited for not only identification but also fine-grained trajectory tracking and gesture recognition. While contact-based (a tag is attached to the target of interest) sensing has achieved promising results, contactless sensing still faces severe challenges such as low accuracy and inability to sense multiple targets simultaneously in proximity, restricting its applicability in real-world deployment. In this work, we present Tamera , a contactless RFID-based sensing system, which significantly improves the tracking accuracy, enables multi-commodity tracking, and even material and shopping behavior recognition. We successfully address multiple technical challenges, and design and implement our prototype on commodity RFID devices. We test the positioning accuracy of Tamera in a 5 m × 6 m laboratory. Tamera achieves a median error of 1.3 cm and 2.7 cm for contactless single- and multi-commodity tracking, respectively. In our laboratory, two shelves commonly found in the supermarket are arranged and the goods are placed on them. Tamera successfully localizes and identifies the material type (metal, plastic, paper, and glass) of the commodities on the shelf with an accuracy higher than 95%. Tamera successfully recognizes four shopping behaviors (taking commodity, replacing commodity, buying commodity, and invoking commodity) with an accuracy higher than 93%.

The inclusion of BCA molecules in SnO2 improves film coverage of ETL, regulates energy level, increases electron transport and migration ability, and enhances crystallization of perovskite. Overall, PSCs fabricated in open-air achieve a champion efficiency of 20.24%.

This work synthesized a hydrazone dye with a carbonyl and pyrazolone structure and benzene ring to passivate defects, significantly improving the perovskite solar cell's efficiency and stability.

In this paper, an ionic liquid (BMIMHSO4) was used to regulate the TiO2/perovskite interface. The interfacial interaction makes the BMIMHSO4 a connection in TiO2 and perovskite layers, providing high-efficiency electron extraction and thus improving device performance.

A core–shell structure material of silicon/nickel oxide nanosheets provides huge potential for high efficiency and long-term stability of metal halide perovskite solar cells.

RF sensing has been actively exploited in the past few years to enable novel IoT applications. Among different wireless technologies, WiFi-based sensing is most popular owing to the pervasiveness of WiFi infrastructure. However, one critical issue associated with WiFi sensing is that the information required for sensing can not be obtained from consumer-level devices such as smartphones or smart watches. The commonly-seen WiFi devices in our everyday lives actually can not be utilized for sensing. Instead, dedicated hardware with a specific WiFi card (e.g., Intel 5300) needs to be used for WiFi sensing. This paper involves Ultra-Wideband (UWB) into the ecosystem of RF sensing and makes RF sensing work on consumer-level hardware such as smartphones and smart watches for the first time. We propose a series of methods to realize UWB sensing on consumer-level electronics without any hardware modification. By leveraging fine-grained human respiration monitoring as the application example, we demonstrate that the achieved performance on consumer-level electronics is comparable to that achieved using dedicated UWB hardware. We show that UWB sensing hosted on consumer-level electronics is able to achieve fine granularity, robustness against interference and also multi-target sensing, pushing RF sensing one step towards real-life adoption.

While communication in the air has been a norm with the pervasiveness of WiFi and LTE infrastructure, underwater communication still faces a lot of challenges. Even nowadays, the main communication method for divers in underwater environment is hand gesture. There are multiple issues associated with gesture-based communication including limited amount of information and ambiguity. On the other hand, traditional RF-based wireless communication technologies which have achieved great success in the air can hardly work in underwater environment due to the extremely severe attenuation. In this paper, we propose UQRCom, an underwater wireless communication system designed for divers. We design a UQR code which stems from QR code and address the unique challenges in underwater environment such as color cast, contrast reduction and light interfere. With both real-world experiments and simulation, we show that the proposed system can achieve robust real-time communication in underwater environment. For UQR codes with a size of 19.8 cm x 19.8 cm, the communication distance can be 11.2 m and the achieved data rate (6.9 kbps ~ 13.6 kbps) is high enough for voice communication between divers.

Earphones are emerging as the most popular wearable devices and there has been a growing trend in bringing intelligence to earphones. Previous efforts include adding extra sensors (e.g., accelerometer and gyroscope) or peripheral hardware to make earphones smart. These methods are usually complex in design and also incur additional cost. In this paper, we present Earmonitor, a low-cost system that uses the in-ear earphones to achieve sensing purposes. The basic idea behind Earmonitor is that each person's ear canal varies in size and shape. We therefore can extract the unique features from the ear canal-reflected signals to depict the personalized differences in ear canal geometry. Furthermore, we discover that the signal variations are also affected by the fine-grained physiological activities. We can therefore further detect the subtle heartbeat from the ear canal reflections. Experiments show that Earmonitor can achieve up to 96.4% Balanced Accuracy (BAC) and low False Acceptance Rate (FAR) for user identification on a large-scale data of 120 subjects. For heartbeat monitoring, without any training, we propose signal processing schemes to achieve high sensing accuracy even in the most challenging scenarios when the target is walking or running.

Heterosis is the major event driving plant development and promoting crop breeding, but the molecular bases for this phenomenon remain elusive.We aim to explore the effect of three-dimensional (3D) chromatin architecture on the underlying mechanism of heterosis.Here, we constructed the North Carolina II (NC-II) population to select superior and inferior heterosis sets by comparing mid-parent heterosis (MPH) in Brassica napus. To decipher the impact of 3D chromatin architecture on the underlying mechanism of heterosis, we combined genetics, transcriptomics and 3D genomics approaches.We suggest that F1 hybrids with superior heterosis tend to contain more transcriptionally active A compartments compared with F1 hybrids with inferior heterosis, and approximately 19-21% compartment significantly altered in the F1 hybrids relative to the parental lines. Further analyses show that chromatin compartments correlate with genetic variance among parents, which may form the basis for differentially active chromatin compartments. Having more A compartments in F1 hybrids confers a more accessible chromatin circumstance, which promotes a higher proportion of highly expressed ELD (expression level dominance) genes in superior heterosis F1 hybrids (46-64%) compared with inferior heterosis F1 hybrids (22-31%). Moreover, genes related to hormones which affect plant growth, are more up-regulated with changes of 3D genome architecture, and we validate that increased hormone content contributes to cell proliferation and expansion by influencing the key genes of cell cycle thereby promoting leaf size.Dynamic 3D chromatin architecture correlates with genetic variance among parents and contributes to heterosis in Brassica napus.

The operative microscope (OM) has revolutionized the field of modern spine surgery, however, it remains limited by several drawbacks. Recently, the exoscope (EX) system has been designed to assistant spine surgery. It provides a three-dimensional (3D) high-definition (HD) operative experience and becomes an alternative to the OM. The aim of the study was to evaluate the clinical outcomes, advantages and limitations of EX-assisted minimally invasive transforaminal lumbar interbody fusion (EMIS-TLIF) and OM-assisted MIS-TLIF (OMIS-TLIF).The clinical outcomes were assessed in 47 patients with lumbar degenerative diseases (LDD) who underwent MIS-TLIF assisted with the OM or EX between January 2019 and September 2020. A total of 22 were treated with EMIS-TLIF, and 25 received OMIS-TLIF. Perioperative parameters (including sex, age, number of fusion levels and body mass index), perioperative parameters (operation time, intraoperative blood loss, postoperative drainage, postoperative hospitalization stay, and duration of follow-up), visual analogue scale (VAS) of back pain, VAS of leg pain, Oswestry disability index (ODI) scores and clinical outcomes were assessed and compared. Image quality, handling of equipment, ergonomics, 3D glasses and educational usefulness were scored according to a questionnaire.Operation time in the OMIS-TLIF group (121.92 ± 16.92 min) was significantly increased compared with that in the EMIS-TLIF group (111.00 ± 19.87 min) (P 0.05). The VAS of the back pain and ODI scores in the EMIS-TLIF group were significantly lower compared with the OMIS-TLIF group at 1 week postoperatively (P 0.05). The good-excellent outcomes rate was 90.91% in the EMIS-TLIF group and 88.00% in the OMIS-TLIF group, and there was no significant difference. A total of 44 visits completed the questionnaire. The results of the questionnaire showed that the EX has exhibited advantages regarding handing of equipment, ergonomics and educational usefulness, and comparable image quality as compared with the OM, however, operating surgeons complained uncomfortable sensation when wearing 3D glasses.The EMIS-TLIF was a safe and effective procedure in the management of LDD as compared with the OMIS-LIF. Meanwhile, EMIS-TLIF might resulted in a short operation time.

We examine the role of experienced CEO in the CEO succession and their contributions to the performance of focal firms. We utilize the propensity score matching with difference in differences (PSM-DID) model to evaluate to what extent experienced CEO succession affects the total factor productivity (TFP) growth. Based on the analysis of 1,675 listed manufacturing companies in China, results show that experienced CEO in succession significantly improves firms’ TFP. Our analysis demonstrates that, on average, the event of hiring an experienced CEO succession yields a 3.1% increase in TFP improvement compared with nonsuccession firms. This positive effect can be continued for three years. Furthermore, the heterogeneous effect of experienced CEO succession on TFP is shown between different categories of focal firms (i.e., high-tech versus low-tech enterprises).

Headphones continue to grow more intelligent as new functions (e.g., touch-based gesture control) appear. These functions usually rely on auxiliary sensors (e.g., accelerometer and gyroscope) that are available in smart headphones. However, for those headphones that do not have such sensors, supporting these functions becomes a daunting task. This paper presents HeadFi, a new design paradigm for bringing intelligence to all headphones. Instead of adding auxiliary sensors into headphones, HeadFi turns the pair of drivers that are readily available inside all headphones into a versatile sensor to enable new applications, spanning across mobile health, user-interface, and context-awareness. HeadFi works as a plug-in peripheral connecting the headphones and the pairing device (e.g., a smartphone). The simplicity (can be as simple as just two resistors) and small form factor of this design lend itself to be embedded into the pairing device as an integrated circuit. We envision that HeadFi can serve as a vital supplementary solution to existing smart headphone design by directly transforming large amounts of existing "dumb" headphones into intelligent ones.

Recent years have witnessed increasing attention from both academia and industry on contact-free acoustic sensing. Due to the pervasiveness of audio devices and fine granularity of acoustic sensing, it has been applied in numerous fields, including human-computer interaction and contact-free health sensing. Though promising, the limited working range hinders the wide adoption of acoustic sensing in real life. To break the sensing range limit, we propose to deploy the acoustic device on a moving platform (i.e., a robot) to support applications that require larger coverage and continuous sensing. In this paper, we propose SonicBot, a system that enables contact-free acoustic sensing under device motion. We propose a sequence of signal processing schemes to eliminate the impact of device motion and then obtain clean target movement information that is previously overwhelmed by device movement. We implement SonicBot using commercial audio devices and conduct extensive experiments to evaluate the performance of the proposed system. Experiment results show that our system can achieve a median error of 1.11 cm and 1.31 mm for coarse-grained and fine-grained tracking, respectively. To showcase the applicability of our proposed system in real-world settings, we perform two field studies, including coarse-grained gesture sensing and fine-grained respiration monitoring when the acoustic device moves along with a robot.

In the context of the network operation of urban rail transit systems, disruptions caused by signal interruptions influence not only the operation of the service at a single station but also the level of service of the whole network. Moreover, it is even possible to induce the cascading failure of the urban rail transit network. Therefore, it is essential to maintain the real-time dynamic monitoring of abnormal stations in urban rail transit systems for security reasons. Based on the large amounts of automated fare collection (AFC) data, a real-time calculation method to estimate the influence intensity of the passenger flow is presented, the spatiotemporal distribution of the influence characteristics is analyzed, and the propagation law of disruptions in the urban rail transit network is explored. First, the fluctuation threshold of passenger flow in a normal situation for all stations was calculated. Accordingly, abnormal stations influenced by the disruption were identified. Then, an evaluation method for calculating the influence intensity of the passenger flow was proposed. Finally, a real-world case study based on the Beijing rail transit system was conducted. All abnormal stations were identified dynamically and displayed in real time, and the distribution and propagation law of abnormal stations were constructed by spatiotemporal diagrams. The influence intensity of passenger flow was analyzed in detail from the perspective of the whole network and representative stations. The results revealed that transfer stations were more vulnerable to the effects of disruption, and the duration for which these stations were affected was longer than that of ordinary stations. Moreover, short-distance travelers were less affected by the disruption than long-distance travelers. The method proposed in this paper can provide a theoretical basis for rail management departments to grasp the characteristics of passenger flow in real time, formulate disposal measures dynamically, and provide more accurate information services for passengers.

Balantioides coli plays an important role in the diarrhea of weaned piglets, but its pathogenic potential and interaction with gut microbes remain unclear. To investigate the impact of B. coli colonization on the gut bacterial structure and function of weaned piglets, a metagenomic analysis based on shotgun sequencing was performed on fresh fecal samples collected from ten B. coli-colonized piglets and eight B. coli-free ones in this study. The results showed that decreasing diversity and shifted composition and function of the bacterial community were detected in the weaned piglets infected by B. coli. In contrast to the B. coli-negative group, the relative abundances of some members of the Firmicutes phylum including Clostridium, Ruminococcus species, and Intestinimonas butyriciproducens, which produce short-chain fatty acids, were significantly reduced in the B. coli-positive group. Notably, some species of the Prevotella genus (such as Prevotella sp. CAG:604 and Prevotella stercorea) were significantly increased in abundance in the B. coli-positive piglets. A functional analysis of the gut microbiota demonstrated that the differential gene sets for the metabolism of carbohydrates and amino acids were abundant in both groups, and the more enriched pathways in B. coli-infected piglets were associated with the sugar-specific phosphotransferase system (PTS) and the two-component regulatory system, as well as lipopolysaccharide (LPS) biosynthesis. Furthermore, several species of Prevotella were significantly positively correlated to the synthesis of lipid A, leading to the exporting of endotoxins and, thereby, inducing inflammation in the intestines of weaned piglets. Taken together, these findings revealed that colonization by B. coli was distinctly associated with the dysbiosis of gut bacterial structure and function in weaned piglets. Lower relative abundances of Clostridiaceae and Ruminococcaceae and higher abundances of Prevotella species were biomarkers of B. coli infection in weaned piglets.

Macrophages are very important immune cells and play critical roles in tumour immunity. Macrophage subtypes can be divided into classical polarization (M1 macrophages) and alternative polarization (M2 macrophages) under different microenvironments. Krüppel-like factor 4 (KLF4) is an essential transcription factor for macrophage polarization. Our previous study has shown that KLF4 SUMOylation plays an important role in macrophage M2 polarization. In the present study, small ubiquitin-like modifier (SUMO) specific peptidase (SENP)1 was identified as a specific protease for KLF4 de-SUMOylation, with the SENP1-KLF4 axis playing a vital role in M1 macrophage polarization by affecting the nuclear factor kappa B signalling pathway. Additionally, the activity of tumour cells was weakened by KLF4 SUMOylation deficient macrophages. Hence, the SENP1-KLF4 axis is considered to play a crucial role in regulating lipopolysaccharide-induced macrophage M1 polarization, thereby affecting the activity of tumour cells. Therefore, the SENP1-KLF4 axis has therapeutic potential as a target in cancer therapy.

With lowering costs of sequencing and genetic profiling techniques, genetic drivers can now be detected readily in tumors but current prognostic models for Natural-killer/T cell lymphoma (NKTCL) have yet to fully leverage on them for prognosticating patients. Here, we used next-generation sequencing to sequence 260 NKTCL tumors, and trained a genomic prognostic model (GPM) with the genomic mutations and survival data from this retrospective cohort of patients using LASSO Cox regression. The GPM is defined by the mutational status of 13 prognostic genes and is weakly correlated with the risk-features in International Prognostic Index (IPI), Prognostic Index for Natural-Killer cell lymphoma (PINK), and PINK-Epstein-Barr virus (PINK-E). Cox-proportional hazard multivariate regression also showed that the new GPM is independent and significant for both progression-free survival (PFS, HR: 3.73, 95% CI 2.07-6.73; p