Miracle-dz/UniFAR-FTUs huggingface dataset:
Accurate FCS Model Predictive Current Control Technique for Surface-Mounted PMSMs at Low Control Frequency

In order to enhance the control performance of the surface-mounted permanent magnet synchronous machines (PMSM) working under the low frequency situations, this letter innovatively proposes an accurate finite control set (FCS) model predictive current control (MPCC) method. First, a novel predicting plant model in the continuous-time domain based on the numerical solutions of the PMSM state-space model (differential equations) is developed. Without using the linear discretization implementation, the influence of the low control frequency can be eliminated completely. Besides, a brand-new calculation delay compensation method based on delay time prediction and current precompensation is designed for the proposed FCS–MPCC strategy. Finally, experiments are conducted on a PMSM test bench with the control frequencies of 2 and 1 kHz to comprehensively verify the proposed algorithms.
Spotting—and treating—PTSD in primary care Combat, sexual assault, and random violence have left millions of Americans with PTSD. A 4-question screen can help you determine if your patient is among them.

CASE. Maureen S,* a patient in her late 50s with chronic pain due to severe degenerative disc disease and early-stage chronic obstructive pulmonary disease (COPD) from years of smoking, was referred to me (JRF) 5 years ago after her physician relocated. Because of her chronic health problems, I began scheduling monthly visits. But she rarely followed through on my recommendations, whether for smoking cessation, physical therapy, pain management, or mammography screening. As I got to know Maureen, it was clear that she was chronically depressed and anxious. I began asking her why she didn’t take better care of herself. Gradually, she provided the answers. Throughout her childhood, Maureen confi ded, her mother had subjected her to severe corporal punishment. From the time she was 7 until she reached her teens, Maureen’s “uncle” had sexually abused her. As an adult, she’d had a series of abusive relationships. The patient’s poor health and failure to care for herself, I suspected, were related to chronic post-traumatic stress disorder (PTSD).
Concurrent Wireless Power Transfer to Multiple Receivers With Additional Resonant Frequencies and Reduced Power Switches

This article presents a wireless power transfer (WPT) system that can deliver power to multiple receivers concurrently with additional resonant frequencies and reduced power switches. It employs three-phase high-frequency inverter with delta-type transmitting tanks. In this way, this WPT system can transfer the power with different resonant frequencies to multiple receivers simultaneously. Compared with the typical multiple-frequency and multiple-receiver WPT system, the proposed WPT system can save considerable amount of power switches. In addition, three additional resonant frequencies can be obtained by setting up original equivalent resonant tank in transmitting side without any change. Three modes, namely the single frequency transmission, concurrent frequency transmission, and additional frequency transmission, are performed and analyzed in detail. Finally, a test rig is built up to verify the performances of six independent frequencies, six kinds of concurrent double frequencies, and one concurrent ternary frequency transmission, with one dealt type transmitting tank.
Bulkyflip: A NAND-SPIN-Based Last-Level Cache With Bandwidth-Oriented Write Management Policy

High capacity last-level caches (LLCs) are being used to help alleviate the growing speed gap between the processor and main memory. However, traditional CMOS based memory technologies (SRAM, DRAM, et al.) for such LLCs consume high static power. Non-volatile memory such as STT-MRAM has been proposed as a low power solution for LLCs. Nevertheless, the high write current induces a so-called “supply current threshold” issue and limits the maximum number of bit-cells that can be written concurrently in one cycle in an STT-MRAM cache. This drawback significantly decreases the bandwidth of the STT-MRAM cache compared with SRAM. In this work, we present a hardware implementation of NAND-like spintronic memory (NAND-SPIN) LLC for the first time. By exploiting the unique erase-then-program operation for writing NAND-SPIN, we propose an adaptive buffer entry (ABE) write policy for each cache write access. Instead of writing a fixed number of bits sequentially, our method adaptively extends the write data length under a fixed maximum cache supply current. Compared to existing STT-MRAM caches, ‘ABE’ can achieve 70% performance improvements on average. Compared with the conventional early write terminate (EWT) policy, ‘ABE’ can save 33% write energy on average with negligible hardware overhead.
Dynamic Data Driven Applications Systems (DDDAS) for Structural Awareness

Structural health monitoring (SHM) seeks methods to characterize damage detection of systems during operation. One method for SHM is the Dynamic Data Driven Applications Systems (DDDAS) paradigm that integrates high-dimensional first principle models, real-time sensing, and control architectures. Over the last two decades, many DDDAS SHM results support space, air, and network awareness. In this paper, we highlight the opportunities to enhance developments towards systems, structures and materials awareness. In materials awareness, the goal is to use physics and computational modeling to support micro-properties analysis when only macro measurements are available. For structures modeling, the dynamic methods support a finite-element model optimization when only a subset of the sensor mesh has data. As a third example, systems awareness utilizes the environment to model structure properties, where the contextual information is generally available, but not precise enough for nanoanalysis. Future structures awareness can leverage DDDAS methods by capturing models of composites, metamaterials, and nanomaterials combined with advances in artificial intelligence/machine learning for prognosis, sensing, and control.
Influence of Information and Service Quality on Users' Continuous Use of Mobile Libraries in China

This research mainly aims to explore the factors that influence users' continuous use of mobile libraries. The findings of this study will provide empirical evidence to help improve the service and information quality of mobile libraries. Moreover, suggestions for optimization are provided with the objective of meeting user demands at its maximum. A theoretical model is constructed to reveal the impact of 11 influencing factors on users' continuous use of mobile libraries. Structural equation modeling is adopted to verify the theoretical model and research hypothesis based on the valid data obtained from a questionnaire survey. The study found that personalized services and information availability have positive impacts on the service quality of mobile libraries. Moreover, perceived mobility and information quality have positive impacts on the perceived usability of mobile libraries. Finally, perceived usability, service quality, and platform stability have significantly positive impacts on the willingness of users to continue usage of mobile libraries.
Modelling of cast-in-place concrete tunnel liners condition

Abstract Modelling the condition of highway tunnel liners helps to better understand the deterioration of tunnel liners and to more cost-effectively optimise the respective maintenance and rehabilitation activities. Previous research work has modelled the structural condition of concrete tunnel liners from the perspective of individual defects such as cracking or leakage. However, the overall structural condition of concrete tunnel liners, considering all relevant defects, has not yet been modelled. Most of the highway tunnels across the United States have been lined using the cast-in-place concrete method. As such, this research contributes to the body of knowledge through modelling the overall structural condition of cast-in-place concrete tunnel liners across the United States. A probabilistic model was designed, built, and validated to predict the deterioration of cast-in-place concrete tunnel liners. The deteriorated amount of tunnel liners was discretised into three condition states. The deterioration probability of tunnel liners was predicted using the ordered-probit analysis method. The developed model can help State Transportation Agencies across the U.S. empirically estimate the condition of cast-in-place concrete tunnel liners and effectively allocate their limited resources.
Feasibility Study on Thermography of Embedded Tumor Using Fiber Bragg Grating Thermal Sensor

Thermal imaging is one of the emerging non-invasive neuro-imaging techniques utilized for demarcation of intra-axial brain tumor borders. Tissue regions comprising of tumors is known to attain higher temperature on the surface due to the increased rate of blood flow and cell metabolism and therefore the variation in tissue surface temperature may be accounted as an indicator of a tumor existence. In the present work, Fiber Bragg Grating based Thermal Sensor (FBGTS) is developed for temperature measurement of a simulated tissue based on Agar material which mimics the soft tissue of brain. A heater is embedded inside the simulated tissue which mimics the tumor’s temperature variation inside the brain. The temperature of the embedded heater along with the surface temperature of the simulated tissue is acquired simultaneously using two FBGTS probes. Further, the temperature variations on the surface of the simulated tissue are studied for varying heater temperatures as well as for the varying position of the heater inside the simulated tissue, indicating varying positions of brain tumors. The present study proposes and demonstrates the feasibility of using FBGTS for thermography from which the possible detection and approximate position of an existing brain tumor can be evaluated.
A 0.5~0.7 V LC Digitally Controlled Oscillator Based on a Multi-Stage Capacitance Shrinking Technique

This paper presents a 2.4 GHz LC digitally controlled oscillator (DCO) at near-threshold supplies (0.5~0.7 V). It was a challenge to achieve a low voltage, low power, and high resolution simultaneously. DCOs with metal oxide semiconductor (MOS) varactors consume low power, but their resolution is limited. ΔΣ-DCOs can achieve a high resolution at the cost of high power consumption. A multi-stage capacitance shrinking technique was proposed in this paper to address the tradeoff mentioned above. The unit variable capacitance of the LC tank was largely reduced by the bridging capacitors and the number of stages. A current-reuse technique was used to further lower the power. Based on the above techniques, the prototype was fabricated using a 130-nm complementary MOS (CMOS) technology with multiple supplies (0.5~0.7 V for the DCO core, 1.2 V for the buffer). The measurement results showed that the phase noise at a 0.6-V supply was −126.27 dBc/Hz at 1 MHz and −125.9480 dBc/Hz at 1 MHz at the carriers of 2.4 GHz and 2.5 GHz, respectively. The best figure of merit (FoM) of 195.68 was obtained when VDD = 0.6 V. The DCO core consumed 1.1 mA at a 0.6-V supply.
A 14–50-GHz Phase Shifter With All-Pass Networks for 5G Mobile Applications

In this article, an ultra-broadband phase shifter (PS) with a 14–50-GHz bandwidth (defined by a phase error below 1/2 LSB) is presented to address the multiband requirements of 5G millimeter-wave (mm-wave) systems. The PS construction is based on all-pass networks (APNs), which have shown broad bandwidth capabilities in a lower frequency range. Aiming toward 5G mobile applications, the proposed 2-bit, 45° phase resolution PS was implemented in 0.25- $\mu \text{m}$ BiCMOS, manufactured, and measured, achieving an insertion loss of 7.4 ± 0.26 dB at 28 GHz and 10 ± 0.22 dB at 39 GHz, with an rms gain and phase error <0.27 dB and <4° from 24 to 30 GHz, respectively, and <0.33 dB and <6° from 37 to 43.5 GHz, demonstrating its capabilities to cover the 5G mm-wave spectrum.
Study of the Dynamic Behaviour of Circular Membranes with Low Tension

The dynamic behaviour of membranes has been widely studied by well-known authors for a long time. A clear distinction can be made between the behaviour of membranes without tension (plate case) and membranes subjected to large tension or pre-strain in their plane (membrane case). In classical theories, less attention has been paid to membranes subjected to a low level of tension, which solution is between both extreme cases. Recently, certain fields of research are demanding solutions for this intermediate behaviour. It is the case of membranes present in MEMS and sensor or the response of the tympanic membrane in mammals hearing system. In this paper, the behaviour of plates and circular membranes with boundary conditions clamped in the edges has been studied. The natural frequencies for both cases (plate and membrane) have been calculated using the solutions of the traditional theories and these have been compared with the numerical frequencies calculated by finite element analysis. The dynamic response of membrane with low tension, corresponding to a transition between these extreme behaviours, has also been calculated. A theoretical solution has been used complemented with a wide set of numerical finite elements calculations. The analytical and numerical solutions are very close, being the error made using both methods very low; nevertheless, there are no analytical solutions for the entire transition zone between the plate and membrane behaviour. Therefore, this range has been completed using finite element analysis. Broad ranges of geometric configurations have been studied. The transition behaviour of the membrane has been clearly identified. The main practical consequences of these results have been discussed, in particular focused on the response of the tympanic membrane.
Malicious PDF Detection Model against Adversarial Attack Built from Benign PDF Containing JavaScript

Intelligent attacks using document-based malware that exploit vulnerabilities in document viewing software programs or document file structure are increasing rapidly. There are many cases of using PDF (portable document format) in proportion to its usage. We provide in-depth analysis on PDF structure and JavaScript content embedded in PDFs. Then, we develop the diverse feature set encompassing the structure and metadata such as file size, version, encoding method and keywords, and the content features such as object names, keywords, and readable strings in JavaScript. When features are diverse, it is hard to develop adversarial examples because small changes are robust for machine-learning algorithms. We develop a detection model using black-box type models with the structure and content features to minimize the risk of adversarial attacks. To validate the proposed model, we design the adversarial attack. We collect benign documents containing multiple JavaScript codes for the base of adversarial samples. We build the adversarial samples by injecting the malware codes into base samples. The proposed model is evaluated against a large collection of malicious and benign PDFs. We found that random forest, an ensemble algorithm of a decision tree, exhibits a good performance on malware detection and is robust for adversarial samples.
A PFC Based EV Battery Charger Using a Bridgeless Isolated SEPIC Converter

Conventional power factor correction (PFC) circuits in electric vehicle (EV) battery chargers have the efficiency limitation due to high conduction loss associated with a diode bridge rectifier (DBR) at the input. To mitigate this issue, a bridgeless (BL) single ended primary inductance converter (SEPIC) with improved power quality, is presented in this article. The input current shows a unity power factor operation over the entire charging duration. Due to elimination of DBR and the current conduction through relatively less number of devices, conduction losses are significantly reduced. This, in turn, improvises the charger efficiency as compared to conventional BL SEPIC converter. The overall performance of proposed charger is illustrated with the help of various operating modes, design equations, simulation-based performance and experimental validation under steady state as well as over wide fluctuations in ac mains voltage. The EV battery is charged at constant current/ constant voltage control mode, which provides satisfactory results for improved efficiency and inherent PFC, thus, improving overall performance of the charger.
Isolation of a Multi-Drug Resistant and Kpc Positive Salmonella Group E from a Patient with Severe Combined Immunodeficiency

History: A 5-year old male was admitted last February 2013 for multiple infections secondary to Severe Combined Immunodeficiency. He was treated with different antibiotics for Mycobacterial, Fungal and Multiple opportunistic Bacterial Infections. Patient complained of gastrointestinal pain and mild diarrhea. The first request for stool culture was made on May 6, 2013 and the Microbiology Laboratory identified the organism by VITEK 2 compact (Biomeriux) as Salmonella Group. Polyvalent slide latex agglutination (Sifin Germany) was used and typed it as Group E Salmonella. Sensitivity results were resistant to all Cephalosporins, Fluoroquinolones, and Aminopenicillins and Penicillins with beta lactamase inhibitor. Carbapenems were all sensitive and attending physician started Imipenem. After 15 days, the second culture was repeated. Salmonella group E was isolated with the same sensitivity pattern but this time gave an intermediate result on Ertapenem. The third stool culture was done after five days. Salmonella group E was isolated with same sensitivity pattern but carbapenems were all reported resistant. Manual ESBL and Modified Hodge tests were performed according to the CLSI and ESCMID guidelines. Both yielded negative. Sample was sent to Milan, Italy for Molecular Typing. Results showed that the organism was positive for the Carbapenemase class KpC. Patient was treated successfully with Colistin. Conclusion: The investigators were able to isolate the first Salmonella non-typhi (Group E) that is highly resistant to Carbepenems, Cephalosporins & other anti-Salmonella drugs. Salmonella spp. is generally sensitive to a wide variety of antibiotics. ESCMID and CLSI recommend only a few antibiotics to be tested against Salmonella typhi and Salmonella non-typhi. Ampicillin, Co-trimoxazole, a flouroquinolone and a 3rd generation Cephalosporin antibiotics in cases of extra intestinal Salmonellosis must be reported in the sensitivity panel. This case reports the 1st strain of Salmonella non-typhi that is highly resistant to these anti-microbials and responded only to Colistin.
CMOS Voltage Reference using a Self-Cascode Composite Transistor and a Schottky Diode

This work presents an investigation of the temperature behavior of self-cascode composite transistors (SCCTs). Results supported by silicon measurements show that SCCTs can be used to generate a proportional to absolute temperature voltage or even a temperature-compensated voltage. Based on the achieved results, a new circuit topology of a resistorless voltage reference circuit using a Schottky diode is also presented. The circuit was fabricated in a 130 nm BiCMOS process and occupied a silicon area of 67.98 µm × 161.7 µm. The averaged value of the output voltage is 720.4 mV, and its averaged line regulation performance is 2.3 mV/V, calculated through 26 characterized chip samples. The averaged temperature coefficient (TC) obtained through five chip samples is 56 ppm/°C in a temperature range from −40 to 85°C. A trimming circuit is also included in the circuit topology to mitigate the impact of the fabrication process effects on its TC. The circuit operates with a supply voltage range from 1.1 to 2.5 V.
Narkosemedikamente – Analgesieren, sedieren, relaxieren

Abstract: Man braucht sie zwar nicht so häufig – aber wenn, dann muss sie sicher gelingen: die Notfallnarkose. Als Mitarbeiter im Rettungsdienst müssen Sie meist die Medikamente vorbereiten oder spritzen. Hier stellen wir die wichtigsten Substanzen vor. Denn ohne Kenntnis ausgewählter Narkotika ist eine leitliniengerechte Notfallnarkose nicht möglich.
Decision-Making Method for Estimating Malware Risk Index

Most recent cyberattacks have employed new and diverse malware. Various static and dynamic analysis methods are being introduced to detect and defend against these attacks. The malware that is detected by these methods includes advanced present threat (APT) attacks, which allow additional intervention by attackers. Such malware presents a variety of threats (DNS, C&C, Malicious IP, etc.) This threat information used to defend against variants of malicious attacks. However, the intelligence that is detected in this manner is used in the blocking policies of information-security systems. Consequently, it is difficult for staff who perform Computer Emergence Response Team security control to determine the extent to which cyberattacks such as malware are a potential threat. Additionally, it is difficult to use this intelligence to establish long-term defense strategies for specific APT attacks or implement intelligent internal security systems. Therefore, a decision-making model that identifies threat sources and malicious activities (MAs) that occur during the static and dynamic analysis of various types of collected malware and performs machine learning based on a quantitative analysis of these threat sources and activities is proposed herein. This model estimates malware risk indices (MRIs) in detail using an analytic hierarchy process to analyze malware and the probabilities of MAs. The analysis results were significant, as the consistency index of the estimated MRI values for 51300 types of malware, which were collected during a specific control period, was maintained at <0.051.
Applying Random Forest and Multipath Fingerprints to Enhance TDOA Localization Systems

This letter proposes a method to apply the random forest (RF) algorithm for exploiting the multipath information and enhance the time difference of arrival (TDOA) localization systems performance. This new approach aims to enhance the performance of a location system in outdoor scenarios, where there are technical restrictions to deploy them in line-of-sight condition. A site-specific fingerprint is extracted with ray-tracing simulations to produce a multipath dataset. The signals are processed with a multidimensional cross-correlation function, called volume cross-correlation (VCC) function, to extract the multipath features from the TDOAs measurements. The machine learning framework searches the points in the scenario, trying to find the most likely to be the emitter position using the processed features and the radio map.