Miracle-dz/UniFAR-FTUs huggingface dataset:
Association of Depression With 10-Year and Lifetime Cardiovascular Disease Risk Among US Adults, National Health and Nutrition Examination Survey, 2005–2018

Introduction Although an association between depression and incident cardiovascular disease (CVD) risk has been established, no US studies have quantified this association using standard primary care assessments or among younger adults who are not routinely screened for CVD risk. We estimated the association of mild and major depression with 1) 10-year atherosclerotic CVD (ASCVD) risk for people aged 40 to 79 years and 2) high lifetime CVD risk prevalence for people aged 20 to 39 years. Methods We conducted a cross-sectional analysis of data from the 2005–2018 National Health and Nutrition Examination Survey for adults aged 20 to 39 years (n = 10,588) and adults aged 40 to 79 years (n = 16,848). We used the Patient Health Questionnaire-9 [PHQ-9] to classify no depression (PHQ-9 score, 0–4), mild depression (PHQ-9 score, 5–9) and major depression (PHQ-9 score ≥10). Results Among women aged 40 to 79, ASCVD absolute risk was 6.0% for no depression, 6.9% for mild depression, and 7.6% for major depression (P < .001 vs no depression). Among men aged 40 to 79, the corresponding absolute ASCVD risks were 9.9%, 11.1%, and 11.3%, respectively (P < .001 vs no depression). High lifetime CVD risk prevalence for women aged 20 to 39 was 41.9% for no depression, 53.2% for mild depression, and 66.5% for major depression (P < .001 vs no depression). For men aged 20–39 the corresponding high lifetime risk percentages were 53.3%, 64.8%, and 74.4% respectively (P < .001 vs no depression). Conclusion Mild and major depression are associated with elevated 10-year ASCVD risk and substantially elevated lifetime CVD risk among younger people ineligible for ASCVD risk assessment. Jointly addressing depression and CVD risk and extending prevention efforts to younger adults are warranted.
Leak Identification Based on CS-ResNet under different leakage Apertures for Water-Supply Pipeline

Considering the problem of difficulty in transmission and storage due to a large amount of data in the water-supply network monitoring system based on a wireless sensor network (WSN), we propose a sparse representation of the water-supply network monitoring data by using compressed sensing (CS) method. At the same time, aiming at the problem of low leakage identification accuracy caused by information loss under compressed sensing, we propose a leak identification method for a water-supply pipe network based on compressed sensing and deep residual neural network (ResNet). Firstly, under the condition that the observation matrix ensures the integrity of signal information, the compressed sensing theory is used to compress and observe leakage signals to obtain observation data, to reduce the redundant information and volume of the data. At the same time, the observation data is preprocessed to realize the transformation of a one-dimensional signal to a two-dimensional matrix. Then the residual neural network is trained by using the two-dimensional data to realize the automatic, efficient, and accurate leak identification under different leakage apertures. Experimental results show that the proposed method can obtain relatively high accuracy and greatly reduce the training time of ResNet by using compressed data. When the Compression rate (CR) is 70% and the observation matrix is a Gaussian random matrix, the average accuracy is 96.67% and the training time is only 50% compared to uncompressed data. The research work provides a new intelligent leak identification under different leak apertures using WSN and has important application prospects in saving water resources.
Development and testing of an impedance controller on an anthropomorphic robot for extreme environment operations

This thesis explores the use of impedance control on an anthropomorphic robot for operations in extreme, poorly mapped environments. First, a dynamic model was developed for a Baxter Research Robot. This model improved on standard dynamic models for similar robots by including the dynamics of the actuators in the system. Specifically, it was demonstrated that when the effective inertia of the actuators is neglected, the system will transmit 1.6 times more force to the environment than the model predicts. A force based Cartesian impedance controller was then implemented on Baxter, and numerous ways to modulate the endpoint impedance, including feedback and geometric configuration, were discussed and compared. Finally, a series of scaled down tasks similar to ones which are required in the decommissioning of offshore oil fields were then completed on Baxter using the Cartesian impedance controller. Overall, it was demonstrated that by using this more advanced control scheme, Baxter was (1) capable of satisfactorily completing the scaled down tasks, (2) more robust against errors in the map of the environment than with traditional controllers, and (3) capable of improving the map of its environment while completing the task. Thesis Supervisor: Neville Hogan Title: Sun Jae Professor of Mechanical Engineering
Volumetric Mesh Progress by Improving the Surface Mesh Quality

This paper presents the improvements in the surface mesh quality and, consequently, in the finite element volumetric mesh when the planar facets triangulation is avoided during solid model generation. It also discusses some details and problems involving the implementation of this new approach. An example that illustrates the improvement obtained by the modifications is presented.
Investigation of Negative Bias Temperature Instability Effect in Nano PDSOI PMOSFET

The Negative Bias Temperature Instability (NBTI) effect of partially depleted silicon-on-insulator (PDSOI) PMOSFET based on 130 nm is investigated. First, the effect of NBTI on the IV characteristics and parameter degradation of T-Gate PDSOI PMOSFET was investigated by accelerated stress tests. The results show that NBTI leads to a threshold voltage negative shift, saturate drain current reduction and transconductance degradation of the PMOSFET. Next, the relationship between the threshold voltage shift and stress time, gate bias and temperature, and the channel length is investigated, and the NBTI lifetime prediction model is established. The results show that the NBTI lifetime of a 130 nm T-Gate PDSOI PMOSFET is approximately 18.7 years under the stress of VG = −1.2 V and T = 125 °C. Finally, the effect of the floating-body effect on NBTI of PDSOI PMOSFET is investigated. It is found that the NBTI degradation of T-Gate SOI devices is greater than that of the floating-body SOI devices, which indicates that the floating-body effect suppresses the NBTI degradation of SOI devices.
BLGVELET M TEKNOLOJLERNN Ö RENME-ÖRETME SÜRECNE ENTEGRASYONUNUNCELEMEDE BR ÇERÇEVE: ETKNLK KURAMI A FRAMEWORK TO INVESTIGATE ICT INTEGRATION INTO TEACHING-LEARNING PROCESS: ACTIVITY THEORY

OZET: Bilgi veletiim Teknolojileri (BT)'nin o �renme-o�retme surecine entegrasyonu, o �retmenler, o �renciler, BT koordinatoru, okul yonetimi, eitim programlaro ve okul kulturu gibi bir cok dinamii icinde barondoran karma �ok ve cok boyutlu bir surectir. Bu nedenle BT uygulamalaronon, icinde bulunduu balamla birlikte ele alonop irdelenmesi onemli gorunmektedir. Etkinlik Kuramo'non, bir taraftan BT'in o �renme ortamlarona nasol entegre edilecei konusunda dier yandan, BT'in kullanoldo�o balamdaki etkinlikler, icerikler ve kiiler araso sureclerin butunsel bir bako� acosoyla incelenebilmesinde onemli olanaklar sunabilecei ileri surulebilir. Buradan hareketle calo�mada, Etkinlik Kuramo'non temel yaposo ve ilkeleri acoklanarak, BT'in o �renme-o�retme surecine entegrasyonunun cok boyutlu olarak irdelenebilmesinde, Etkinlik Kuramo'ndan nasol yararlanolabilecei ortaya konulmaya calo�olmo�tor. ABSTRACT: The integration of Information and Communication Technologies (ICT) into teaching and learning processes is a complex process involving a lot of dynamics such as teachers, students, ICT coordinator, school management, curriculum and school culture. Therefore, handling and investigating ICT applications within its context seems important. It can be claimed that Activity Theory serves opportunities on one hand about how ICT can be integrated into learning environments and on the other hand to explore events, activities, contents and the interpersonal processes in the ICT using contexts from a holistic view. For this aim, in the study, by explaining the structure and the main principles of the Activity Theory, an opinion about how one can use Activity Theory for investigating ICT integration into teaching-learning process from a holistic perspective has been attempted.
E-appointments at primary care physicians during Covid-19 pandemic: viewpoint and satisfaction of medical consumers

INTRODUCTION: Use of e-appointment systems in primary care (EASPC) is a common practice in western countries, however, there is no evidence of implementation in R. N. Macedonia and other similar countries in development. OBJECTIVES: This study explores the viewpoints and satisfaction of medical consumers (MC) on EASPC, and the impact of Covid-19 global pandemic concerning their appointments at primary care physicians. METHODS: A survey on MC above the age of 15 years was conducted in July 2020. The results were analysed in SPSS 23. RESULTS: The majority of participants were in favour on implementing an EASPC despite their neutral satisfaction with the walk-in method. Furthermore, they were confident in its effectiveness in the fight against spreading of Covid-19. CONCLUSION: The MC opinion and satisfaction is crucial when developing health care systems and their implementation as a mix of services. For the system to succeed, it must be financed and supported adequately and as such, further research is necessary to explore a real-time EASPC usage.
AcoPalm: Acoustical Palmprint-Based Noncontact Identity Authentication

Biometric sensing has become a widely concerned authentication technology. Existing image-based methods are susceptible to light conditions and have privacy exposure risks, while contact authentication methods are not conducive to epidemic prevention requirements in public places. In this article, we propose a palmprint-based identification system by collecting backscattered signals of the inaudible acoustic signals, namely AcoPalm. AcoPalm does not require special hardware and contact operation for user authentication. First, frequency modulated continuous wave (FMCW) on acoustic signals are designed to extract static contours and palmprint changes and to model the unique biological characteristics of the individual palm. Second, a palmprint authentication model based on PENN is proposed to achieve high-precision multiuser authentication without mass training data. Finally, the system performance is evaluated in multiple smartphones and three scenarios. The experimental results show that AcoPalm can resist replay attack and imitation attack, and the authentication accuracy can reach 96.22%. Furthermore, AcoPalm achieves satisfactory experience in availability and practicality.
Overview of Sub-100 mV Oscillators

This paper presents a comprehensive review of the state of the art for oscillators operating at reduced supply voltage. The analysis and implementation examples of differ-ent types of oscillators, such as LC oscillators, transformer-based oscillators, and CMOS oscillators are presented. Expres-sions for the oscillation frequency and the minimum supply voltage limit are provided. The characteristics, advantages, and constrains of different topologies are discussed, providing a reference guideline for the choice of the best topology for a given application.
Power-Based Safety Layer for Aerial Vehicles in Physical Interaction Using Lyapunov Exponents

As the performance of autonomous systems increases, safety concerns arise, especially when operating in non-structured environments. To deal with these concerns, this work presents a safety layer for mechanical systems that detects and responds to unstable dynamics caused by external disturbances. The safety layer is implemented independently and on top of already present nominal controllers, like pose or wrench tracking, and limits power flow when the system’s response would lead to instability. This approach is based on the computation of the Largest Lyapunov Exponent (LLE) of the system’s error dynamics, which represent a measure of the dynamics’ divergence or convergence rate. By actively computing this metric, divergent and possibly dangerous system behaviors can be promptly detected. The LLE is then used in combination with Control Barrier Functions (CBFs) to impose power limit constraints on a jerk controlled system. The proposed architecture is experimentally validated on an Omnidirectional Micro Aerial Vehicle (OMAV) both in free flight and interaction tasks.
Machine learning based encrypted traffic classification using estimated application layer statistics

To provide the best Quality of Experience (QoE) to a user, prioritization of traffic flows is required to satisfy different Quality of Service (QoS) requirements of different applications. Traffic flows need to be classified into different QoS classes to prioritize traffic. Since encrypted traffic now comprises most of the Internet traffic, classification of encrypted traffic is necessary for a satellite broadband system. We propose a novel approach to classify encrypted traffic using machine learning (ML). Our approach uses a unique set of features which are based on actual measured application layer characteristics. We show that our technique can achieve an accuracy of over 96%. The approach needs only a few packets to classify a traffic flow and consequently, it can be used as a real-time classifier. The classification type corresponds to a QoS traffic class which is readily amenable to queuing and servicing at a customer premise equipment (CPE). Due to its low complexity, our ML approach can be easily implemented in a constrained embedded device such as a CPE.
Theory and design of quasi‐lumped‐element wideband filtering phase shifters

In this article, a new general and effective design method of miniaturized quasi‐lumped‐element wideband filtering phase shifters for integrated RF front‐end is proposed, which is promising in both industrial and academic fields. This wideband filtering phase shifter is built by exploring the multiple different kinds of lumped resonators and arranging them in an easily realizable form with stable performance on the single‐layer substrate using widely accessible and low‐cost PCB processing. In our design, wideband magnitude and phase shift responses with the multiple transmission zeros and small phase deviation are numerically established and obtained. A generalized synthesis method along with theoretical analysis and synthesis curves is proposed to determine its circuit parameters exactly. To verify the proposed design concept and method, two wideband phase shifter prototypes with the different topologies and specifications are implemented and tested. Comparisons of measured and simulated results show good accordance and verify theoretical predictions. These prototypes exhibit attractive features with satisfactory wide bandwidth, high frequency selectivity, small phase deviation, deep and wide stopband, miniaturized size, as well as flexible design freedom, compared to other existing works.
Developing the intelligent agriculture is the inevitable choice of modern agriculture building

This essay brief introduced the applied situation of information technology in the agriculture field in China, bring up that it is in the process of developing modern agriculture, shall according to our national situation, developing the agriculture intelligent technology, which is integrated with computer technology, multimedia information technology, and modern agriculture science, and to popularize it by the network system. The article made some research on the model of technology developing and the way of popularization.
State of Health Estimation for Lithium-Ion Battery via Recursive Feature Elimination on Partial Charging Curves

Knowing the batteries’ health state in electric vehicles (EVs) accurately and effectively would directly enhance the system’s reliability and safety. Accordingly, this article proposes a state of health (SOH) estimation method based on the collaboration of feature selection and machine learning methods. Specifically, actual EV data from more than 1200 charging processes are analyzed to designate the constrained voltage range for data processing. Features are then derived, extracted, and selected from the capacity-based curves to depict the battery degradation process and estimate the SOH. Afterward, to find the relevant SOH estimation features, a recursive approach is utilized for pruning the unimportant features cooperated with a linear regression (LR) model. SOH estimation is therefore realized based on the above-obtained features and a low computation cost linear regressor. Six lithium-ion batteries are used to verify the proposed method. The maximum estimation error can be quantitatively limited in the range of −1%–1% with the synergy of the model and features. Furthermore, comparative experiments demonstrate that the LR with optimized features could achieve a similar SOH estimation accuracy as the complicated nonlinear model but using less operating time.
Quantized feedback control of linear system with performance barrier

In this article, we investigate the quantized control problem of the continuous‐time linear system with performance barrier. The performance of the system is specified by a continuous decaying function. Considering the state quantization in the feedback, a dynamic quantization scheme and a control law with limited bandwidth are developed, such that the closed‐loop system is asymptotically stable and the specified performance barrier is satisfied. Based on the theory of control barrier function (CBF), the analysis on the performance guarantee of the closed‐loop system under quantization is established. Furthermore, the minimal bandwidth for the quantized system with the performance barrier is explicitly given. Finally, the effectiveness of the obtained result is illustrated by an example.
Design and Implementation of a High Resolution CMOS X-Ray Imager with Amorphous Selenium Sensor

This thesis presents a novel system for high resolution X-ray imaging in medical and industrial applications. Complementary metal-oxide-semiconductor (CMOS) technology is a standard technology used in most state of the art electronic systems including imagers. In addition, amorphous selenium (a-Se) is a photoconductor that is sensitive to a wide range of X-ray photon energies. Increasing the effective spatial resolution is one the primary goals of state of the art imaging systems. The objective of this thesis is to integrate the a-Se sensor and CMOS readout to make an ultra high resolution X-ray imager. Other features of the imager like noise, dynamic range, imaging speed, and fill factor are competitive with existing X-ray imaging systems. All of the signal reading circuitry is implemented on a custom CMOS chip and the a-Se sensor is deposited on top of it through post processing. This thesis also describe the design of external hardware and software needed to properly operate the imager. We demonstrate our imager with a 64 × 64 pixel array prototype containing 5.6 × 6.25 μm and 11.2× 6.25 μm pixel. Our results include characterization of the electronic and X-ray imaging performance of our system. We also show X-ray images with effective resolution down to 14 μm.
Aggregate Confusion: The Divergence of ESG Rating

This paper investigates the divergence of environmental, social, and governance (ESG) ratings based on data from six prominent ESG rating agencies: KLD, Sustainalytics, Moody’s ESG (Vigeo-Eiris), S&P Global (RobecoSAM), Refinitiv (Asset4), and MSCI. We document the rating divergence and map the different methodologies onto a common taxonomy of categories. Using this taxonomy, we decompose the divergence into contributions of scope, measurement, and weight. Measurement contributes 56% of the divergence, scope 38%, and weight 6%. Further analyzing the reasons for measurement divergence, we detect a rater effect where a rater’s overall view of a firm influences the measurement of specific categories. The results call for greater attention to how the data underlying ESG ratings are generated.
Statistical Associations Between Geomagnetic Activity, Solar Wind, Solar Proton Events, and Winter NAO and AO Indices

Numerous studies have revealed evidence that winter climate in the Northern Hemisphere is related to the solar cycle and space weather. Most of the studies investigating the impact of space weather on the North Atlantic Oscillation and Artic Oscillation indices (NAOIs and AOIs) analyzed monthly or seasonal data. In this work, we evaluated the responses of winter NAOI/AOI to space weather changes on the day‐to‐day timescale during 1950–2020 by using an autoregressive (AR) model with additional predictors, such as month, linear trend, trends of solar irradiance and Kp indices, the Quasi‐Biennial Oscillation (QBO) and El Niño–Southern Oscillation, the presence of sudden stratospheric warming (SSW) and high stratospheric aerosol loading (HSAL), and space weather variables, reflecting the day‐to‐day effect. Winter daily NAOI (AOI) follows the AR model of the 4th (5th) order. We found a positive day‐to‐day effect of Kp, solar wind speed (SWS) > 300 km/s, By ≤ 3.15 nT, and solar wind dynamic pressure (P) with a lag of 2 days on the NAOI and the AOI. For the AOI, additionally, the period of 1 day before–2 days after the solar proton event onset had a negative effect, and the signal of Kp and SWS was observed only for the east QBO phase. For the NAOI, a stronger effect of P was found on the presence of a strongly positive QBO phase. A stronger signal of Kp and SWS was found during HSAL. The signal of SWS > 300 km/s on the NAOI/AOI was different in sign during the periods with and without SSW.
Experimental Investigation of Charge Sharing Induced SET Depending on Transistors in Abutted Rows in 65 nm Bulk CMOS Technology

The effect of transistors in abutted rows on charge sharing is investigated by changing the configuration of the transistors in abutted rows in this work. 3D TCAD numerical simulations indicate that the existence of transistors in abutted rows can mitigate the occurring probability of charge sharing, especially charge sharing induced by ion striking at the vicinity of n-well contact. The simulations also indicate that the single event double transient (SEDT) pulse width is reduced obviously by the transistors in abutted rows for ion strike location near n-well contact. A 65 nm test chip was designed in commercial 65nm twin-well bulk CMOS process, and heavy-ion experiment was conducted. The experiment results agree well with the simulation results, which indicates that the effect of transistors in abutted rows on single event sensitivity and the occurring probability of charge sharing is more than 10%, and then considering the effect of transistors in abutted rows is necessary in nanometer technology.
USING SHORT-BLOCK TURBO CODES FOR TELEMETRY AND COMMAND

The turbo code is a block code even though a convolutional encoder is used to construct codewords. Its performance depends on the code word length. Since the invention of the turbo code in 1993, most of the bit error rate (BER) evaluations have been performed using large block sizes, i.e., sizes greater than 1000, or even 10,000. However, for telemetry and command, a relatively short message (<500 bits) may be used. This paper investigates the turbo-coded BER performance for short packets. Fading channel is also considered. In addition, biased channel side information is adopted to improve the performance.