Search

In this paper, our recent studies on the hot carrier degradation (HCD) in FinFETs, as well as HCD-induced dynamic variability, are summarized. The kinetics and statistics of FinFET HCD are experimentally investigated. New observations on HCD are reported, which are due to the simultaneous generation of both interface and oxide traps. Based on the trap-based approach, instead of the conventional carrier-based approach, the HCD and its variations are well-described with the proposed multi trap-based compact models, that are unified over the full $\{V_{gs},V_{ds}\}$ bias region. The typical average locations of the HCD-induced traps in FinFET under the worst-case stress condition are also identified. The results are helpful for the physical understanding and modeling of HCD, and the reliability-aware circuit design for FinFET technology.

Cloud computing is applied in various domains, among which social recommender systems are well-received because of their effectivity to provide suggestions for users. Social recommender systems perform well in alleviating cold start problem, but it suffers from shilling attack due to its natural openness. Shilling attack is an injection attack mainly acting on the training process of machine learning, which aims to advance or suppress the recommendation ranking of target items. Some researchers have studied the influence of shilling attacks in two perspectives simultaneously, which are user-item's rating and user-user's relation. However, they take more consideration into user-item's rating, and up to now, the construction of user-user's relation has not been explored in depth. To explore shilling attacks with complex relations, in this paper, we propose two novel attack models based on triangle relations in social networks. Furthermore, we explore the influence of these models on five social recommendation algorithms. The experimental results on three datasets show that the recommendation can be affected by the triangle relation attacks. The attack model combined with triangle relation has a better attack effect than the model only based on rating injection and the model combined with random relation. Besides, we compare the functions of triangle relations in friend recommendation and product recommendation.

With the downscaling of CMOS technology, the circuit design margin becomes more and more tight due to wider guardband, which is required to counteract the severer transistor aging and variations. Thus, reliability-enhanced circuit design is urgently needed to reduce the guardband. In this paper, a reliability-enhanced design framework based on approximate synthesis is proposed to completely eliminate the aging guardband. It mainly includes two key parts: first, a forward reliability simulation flow supporting statistical static timing analysis (SSTA) is performed to estimate the path failure rates after aging; if the timing constraints are not satisfied, then a backward delay-driven approximate logic synthesis flow will perform approximate local changes on the critical paths to reduce the delay until the reliability requirement is finally satisfied and no aging guardband is needed. The results show that the approximate circuit has a smaller aged delay than the original circuit, so that the path failure rates are significantly decreased. It indicates that the proposed design flow can convert the timing errors that have fatal impact on applications, into negligible error on low-significance bits to improve the resilience of circuits, which provides a new perspective of reliability-enhanced design at nanoscale.

Background Optimal fluid management in patients with COVID-19 has not been reported. This retrospective, multicenter study investigated the impact of intravenous infusion volume in the early stage of COVID-19 on clinical outcomes. Methods 127 patients from two tertiary hospitals were separated into the “conservative” and “liberal” groups based on average daily intravenous infusion volume within the first seven days after admission. Basic information, demographic and epidemiological characteristics, laboratory findings, treatments, and outcome measures were retrieved from medical records. The disease progression and prognosis were analyzed and compared. Results The average daily intravenous infusion volume within 7 days was 500 (150–700) ml/day in the conservative-strategy group (n = 87), and 1100 (1000–1288) ml/day in the liberal-strategy group (n = 40) (p p > 0.05). The final K+ in the liberal group was slightly higher than that at admission, and the final hematocrit level in the conservative group had a significant difference than that at admission (p p = 0.120). However, compared to the liberal group, conservative group had statistically lower rates of disease progression (9.3% vs 37.5%, p p p = 0.012). Conclusions Although there appeared to be no significant difference in the duration of hospitalization between using conservative and liberal fluid management strategies, the former was associated with lower rates of disease progression, mechanical ventilation and in-hospital mortality without increased nonpulmonary-organ dysfunction. These results support the importance of implementing conservative intravenous fluid infusion in the early stage of COVID-19.

Correlation filter-based trackers have achieved excellent performance in visual tracking in recent decade. Compared with traditional trackers, they show better robustness and efficiency. Most correlation filter based trackers learn the appearance model using only a single feature, like Histogram of Oriented Gridients feature, color naming feature, Gray features and so on. However, single-feature model can’t maintain great robustness in various complex situations. In order to solve this problem, we propose a High confidence correlation filter tacker based on multi-feature adaptive weighting. The tracker can acquire the initial weights using the information obtained in the second frame, and adaptively adjust the weights of different feature according to the tracking results of each frame. Moreover, we use a high confidence update strategy, and exploit the high confidence tracking results to update the model, so as to reduce the probability of model drift. We experiment the algorithm on 36 sequences of OTB-50 benchmark dataset, the experimental results show that our algorithm has a better performance compared with the original algorithm on multiple sequences such as Dragonbaby, Deer and Skating1. We also experiment our algorithm on our own sequence, in which our algorithm still has a better performance.

With the downscaling of CMOS technology, the reliability issue has become inevitable. Even in fault-tolerant applications, the effects of timing violation caused by the transistor aging are unacceptable. In the past, the traditional method to solve timing violation is to add a wide frequency guardband, which will lead to the decrease of speed. In this paper, the reliability of the approximate computing is evaluated in an image processing applications. And a method to improve circuit reliability is proposed. The results show that this method can turn critical path timing errors, which are difficult to predict and seriously hurt circuit reliability, into deterministic logic simplification errors, and thus the actual function of the circuit is not affected.

Objective: To investigate the relationship between low ocular perfusion pressure (OPP) with acute non-arterial anterior ischemic optic neuropathy (ANAION).Methods: Forty- six patients (46 eyes) with ANAION from July 2010 to December 2016 were retrospectively analyzed. The 24-h intraocualr pressure (IOP) in sitting position was measured by non-contact tonometer. The brachial artery systolic blood pressure (SBP) and diastolic blood pressure (DBP) were simultaneously measured by electrocardiogram monitor. The 24-h OPP was calculated according to the measured blood pressure and intraocular pressure: OPP= 45% DBP-IOP. OPP< 10mmHg was defined as low OPP. Sudden visual acuity declining or visual field defect was recorded as the attack of ANAION. 24h was divided into four periods: period A (1-6 A.M), period B (6-12 A.M), period C (12-18 P.M) and period D (18-24 P.M). The correlation between low OPP and ANAION was analyzed. Statistical method was used by Person correlation analysis.Results: There was a statistical difference in the low OPP in the four periods (P< 0.05). The most common period of low OPP was period A (1-6 A.M), with the incidence of low OPP as high as 58.3%. There was a statistical difference in the incidence of ANAION in the four periods (P< 0.05). Most common time period of ANAION was also period A (1-6 A.M), with the incidence rate as high as 46.3%. Person correlation analysis showed that the period of low OPP was associated with the period of ANAION onset (r=0.934, P < 0.05).Conclusion: There was a significant clinical correlation between low OPP and ANAION. Period A (1-6 A.M) was the high-risk period for low OPP and ANAION. The occurrence of ANAION can be reduced by elevating the OPP to improve the blood perfusion of the anterior optic nerve.

The 2019-nCoV is officially called SARS-CoV-2 and the disease is named COVID-19. This viral epidemic in China has led to the deaths of over 1800 people, mostly elderly or those with an underlying chronic disease or immunosuppressed state. This is the third serious Coronavirus outbreak in less than 20 years, following SARS in 2002-2003 and MERS in 2012. While human strains of Coronavirus are associated with about 15% of cases of the common cold, the SARS-CoV-2 may present with varying degrees of severity, from flu-like symptoms to death. It is currently believed that this deadly Coronavirus strain originated from wild animals at the Huanan market in Wuhan, a city in Hubei province. Bats, snakes and pangolins have been cited as potential carriers based on the sequence homology of CoV isolated from these animals and the viral nucleic acids of the virus isolated from SARS-CoV-2 infected patients. Extreme quarantine measures, including sealing off large cities, closing borders and confining people to their homes, were instituted in January 2020 to prevent spread of the virus, but by that time much of the damage had been done, as human-human transmission became evident. While these quarantine measures are necessary and have prevented a historical disaster along the lines of the Spanish flu, earlier recognition and earlier implementation of quarantine measures may have been even more effective. Lessons learned from SARS resulted in faster determination of the nucleic acid sequence and a more robust quarantine strategy. However, it is clear that finding an effective antiviral and developing a vaccine are still significant challenges. The costs of the epidemic are not limited to medical aspects, as the virus has led to significant sociological, psychological and economic effects globally. Unfortunately, emergence of SARS-CoV-2 has led to numerous reports of Asians being subjected to racist behavior and hate crimes across the world.

The COVID-19 pandemic is a significant global event in the history of infectious diseases. The SARS-CoV-2 appears to have originated from bats but is now easily transmissible among humans, primarily through droplet or direct contact. Clinical features of COVID-19 include high fever, cough, and fatigue which may progress to ARDS. Respiratory failure can occur rapidly after this. The primary laboratory findings include lymphopenia and eosinopenia. Elevated D-dimer, procalcitonin, and CRP levels may correlate with disease severity. Imaging findings include ground-glass opacities and patchy consolidation on CT scan. Mortality is higher in patients with hypertension, cardiac disease, diabetes mellitus, cancer, and COPD. Elderly patients are more susceptible to severe disease and death, while children seem to have lower rates of infection and lower mortality. Diagnostic criteria and the identification of persons under investigation have evolved as more data has emerged. However, the approach to diagnosis is still very variable from region to region, country to country, and even among different hospitals in the same city. The importance of a clinical pathway to implement the most effective and relevant diagnostic strategy is of critical importance to establish the control of this virus that is responsible for more and more deaths each day.

Objective Since the outbreak of Coronavirus Disease 2019 (COVID-19) in December 2019, various digestive symptoms have been frequently reported in patients infected with the virus. In this study, we aimed to further investigate the prevalence and outcomes of COVID-19 patients with digestive symptoms. Methods In this descriptive, cross-sectional, multicenter study, we enrolled confirmed patients with COVID-19 who presented to 3 hospitals from January 18, 2020, to February 28, 2020. All patients were confirmed by real-time polymerase chain reaction and were analyzed for clinical characteristics, laboratory data, and treatment. Data were followed up until March 18, 2020. Results In the present study, 204 patients with COVID-19 and full laboratory, imaging, and historical data were analyzed. The average age was 52.9 years (SD ± 16), including 107 men and 97 women. Although most patients presented to the hospital with fever or respiratory symptoms, we found that 103 patients (50.5%) reported a digestive symptom, including lack of appetite (81 [78.6%] cases), diarrhea (35 [34%] cases), vomiting (4 [3.9%] cases), and abdominal pain (2 [1.9%] cases). If lack of appetite is excluded from the analysis (because it is less specific for the gastrointestinal tract), there were 38 total cases (18.6%) where patients presented with a gastrointestinal-specific symptom, including diarrhea, vomiting, or abdominal pain. Patients with digestive symptoms had a significantly longer time from onset to admission than patients without digestive symptoms (9.0 days vs 7.3 days). In 6 cases, there were digestive symptoms, but no respiratory symptoms. As the severity of the disease increased, digestive symptoms became more pronounced. Patients with digestive symptoms had higher mean liver enzyme levels, lower monocyte count, longer prothrombin time, and received more antimicrobial treatment than those without digestive symptoms. Discussion We found that digestive symptoms are common in patients with COVID-19. Moreover, these patients have a longer time from onset to admission, evidence of longer coagulation, and higher liver enzyme levels. Clinicians should recognize that digestive symptoms, such as diarrhea, are commonly among the presenting features of COVID-19 and that the index of suspicion may need to be raised earlier in at-risk patients presenting with digestive symptoms. However, further large sample studies are needed to confirm these findings.

There is extensive evidence suggesting that microRNAs (miRs) can modulate the activity of oncogenes and tumor suppressors, and are associated with the occurrence of cancer. In the present study, the function of miR-363-3p in the progression of retinoblastoma (RB) was investigated. miR-363-3p expression in RB was decreased, and miR-363-3p protein levels were found to be inversely correlated with phosphatidylinositol-4,5-bisphosphate 3-kinase catalytic subunit α (PIK3CA) levels. Overexpression of miR-363-3p in an in vitro model of RB revealed that miR-363-3p had anticancer effects on RB and regulated PIK3CA, pyruvate dehydrogenase kinase 1 (PDK1) and phosphorylated protein kinase B (p-AKT) protein expression. Downregulation of miR-363-3p promoted cell proliferation of RB cells through PIK3CA, PDK1 and p-AKT protein expression. Knockdown of PIK3CA increased the anticancer effects of miR-363-3p in RB cells. Treatment with OSU-03012, a PDK1 inhibitor, accelerated the anticancer effects of miR-363-3p in RB cells. Taken together, the results demonstrate that miR-363-3p functions as a tumor suppressor in RB by targeting PIK3CA.

Recommender constantly suffers from the problems of data sparsity and cold-start. As suggested by social theories, people often alter their ways of behaving and thinking to cater to social environments, especially their friends. For this reason, prior studies have integrated social relations into recommender systems to help infer user preference when there are few available data, which is known as social recommendation. However, explicit social relations are also sparse and meanwhile are usually noisy. To enhance social recommendation, a few studies identify more reliable implicit relations for each user over the user-item and user-user networks. Among these research efforts, meta-paths guided search shows state-of-the-art performance. However, designing meta-paths requires prior knowledge from domain experts, which may hinder the applicability of this line of research. In this work, we propose a novel social recommendation model (JUST-BPR) with a meta-path-free strategy to search for implicit friends. Concretely, We adopt the idea of ’Jump and Stay’, which is a heterogeneous random walk technique, to social recommendation. Based on this idea, we manage to bypass the design of meta-paths and obtain high-quality implicit relations in a more efficient way. Then we integrate these implicit relations into an augmented social Bayesian Personalized Ranking model for top-N recommendation. Experiments on two real-world datasets show the superiority of the proposed method and demonstrate the differences between implicit friends discovered by meta-paths and JUST-BPR, respectively.

As a promising alternative to the fundamental device structure, the gate-all-around silicon nanowire transistor (GAA SNWT) has been studied extensively for decades. In this chapter, the device physics, compact modeling, and fabrication process of GAA SNWT are systematically reviewed, as well as its potential applications in terms of different technology diversities. In the first part, the bulk-Si based integration scheme, quasi-ballistic transport characterization, parasitic capacitance, and self-heating modeling of GAA SNWT are presented. Following that, the variability and reliability physics and models of GAA SNWT are studied in-depth. Finally, the application examples in electrostatic discharging, radio frequency/analog circuit, and bio-sensor of GAA SNWT are demonstrated.

Phase change memory (PCM) attracts wide attention for the memory-centric computing and neuromorphic computing. For circuit and system designs, PCM compact models are mandatory and their status are reviewed in this work. Macro models and physics-based models have been proposed in different stages of the PCM technology developments. Compact modeling of PCM is indeed more complex than the transistor modeling due to their multi-physics nature including electrical, thermal and phase transition dynamics as well as their interactions. Realizations of the PCM operations including threshold switching, set and reset programming in these models are diverse, which also differs from the perspective of circuit simulations. For the purpose of efficient and reliable designs of the PCM technology, open issues and challenges of the compact modeling are also discussed.

Author(s): Liu, YY; Liu, F; Wang, R; Luo, JW; Jiang, X; Huang, R; Li, SS; Wang, LW | Abstract: The complexity of charge trapping in semiconductor devices, such as high-κ MOSFETs, is increasing as the devices themselves become more complicated. To facilitate research into such charge-trapping issues, here we propose an optimized simulation framework that is composed of density-functional theory (DFT) for electronic structure calculation and Marcus theory for the calculation of charge-trapping rates. The DFT simulations are either carried out or corrected by using the Heyd-Scuseria-Ernzerhof hybrid functional. Using this framework, the hole-trapping characteristics along multiple paths in Si/SiO2/HfO2 stacks are investigated, and the relative importance of each path is revealed by calculating its exact hole-trapping rate. Besides the study on crystalline stacks, we also create an amorphous stack, which is more realistic compared with experiments and real devices, to reveal more active trapping centers and to study the statistical feature of charge trapping induced by structural disorder. In addition, to seek effective measures for relieving these charge-trapping problems, the effects of hydrogen and fluorine passivations are discussed, and physical insights for improving the performance of high-κ MOSFETs are provided.

In this work, ultrathin indium tin oxide (ITO) radio frequency (RF) transistors have been demonstrated for the first time, where inverted gate structure are used with a flexible polyimide substrate using magnetron sputtering at a thermal budget below 200 °C. The 160 nm channel length device exhibits excellent DC characteristics, including mobility of 26 cm2/V•s and an I on /I off ratio of 6.6×108. A record-high extrinsic cut-off frequency (f T ) of 2.1 GHz and an extrinsic maximum oscillation frequency (f max ) of 3.7 GHz have also been obtained, which are more than one order of magnitude higher than previous results on flexible substrate. A high conversion gain of -20.9 dB has been achieved for the gigahertz frequency mixer based on flexible ITO RF transistor. Moreover, the stability of DC and RF performance under different bending conditions up to 50,000 bending cycles or down to 1 mm bending radius are studied without device failure.

In this paper, we report high-speed ultrathin-body (3.5 nm) indium-tin-oxide (ITO) transistors using high-k HfLaO dielectrics with a thickness of 5 nm. Because of its low dielectric constant and large bandgap, ITO is a promising channel material for scaling below the 5 nm regime for advanced low-power electronics with excellent short-channel-immunity. Here, we fabricate sub-100-nm channel length ITO transistors with ultrahigh on/off ratio near 1011 and ultralow off-state current below 10 fA/μm. The 15-nm-long ITO transistor exhibits high performance with the maximum on-state current of 970 μA/μm and peak g m of 400 μS/μm at V ds = 0.5 V. NAND, NOR, and SRAM based on enhancement/depletion mode (E/D) inverters have achieved full rail-to-rail output characteristics and stable memory function. Finally, We demonstrated a stage delay of 0.49 ns/stage for a 5-stage ring oscillator based on bootstrapped mode (BST) inverter, which is the best among all results based on metal-oxides transistors.

Background Vertebral compression fracture is one of the most common complications of osteoporosis. In this study an unilateral curved vertebroplasty device was developed, and the safety, effectiveness, and surgical parameters of curved vertebroplasty (CVP) in the treatment of painful osteoporotic vertebral compression fractures was investigated and compared with traditional bipedicular vertebroplasty (BVP). Methods We investigated 104 vertebral augmentation procedures performed over 36 months. CVP and BVP procedures were compared for baseline clinical variables, pain relief (Visual Analog Scale, VAS), disability improvement (Oswestry Disability Index, ODI), operation time, number of fluoroscopic images, volume of cement per level, and cement leakage rate for each level treated. Complications and refracture incidence were also recorded in the two groups. Results The VAS and ODI in both group had no significant difference preoperative (P > 0.05), and a significant postoperative improvement in the VAS scores and ODI was found in both group (P P 0.05). Neither group had any serious complications. Five and two patients in the BVP group developed refractures at non-adjacent and adjacent levels, respectively, with one patient developing refractures twice; however, none of the patients in the CVP group developed refractures at any level. Conclusions Our findings revealed that both CVP and BVP were safe and effective treatments for osteoporotic vertebral compression fractures, and CVP entails a shorter operation time, less exposure to fluoroscopy, and lower rate of cement leakage.

Objective Inflammatory back pain (IBP) is often an early manifestation of spondyloarthritis (SpA), but the prognosis of patients with incident IBP is unknown. This study was undertaken to investigate long-term outcomes in patients with IBP, and predictors of progression to SpA, in a population-based cohort. Methods We conducted a retrospective, longitudinal study using the Rochester Epidemiology Project, a longstanding population-based cohort of residents of Olmsted County, MN. Patients ages 16-35 years with clinical visits for back pain from 1999 to 2003 were identified, and we screened these patients for the presence of new-onset IBP and performed medical record reviews to collect data on clinical, laboratory, and imaging features of SpA. Outcomes in these patients were followed up until July 2016. We used survival analysis for competing risks to examine progression to either SpA, a non-SpA diagnosis, or resolution of back pain. Recursive partitioning was used to identify predictors of progression to SpA. Results Among 5,304 patients with back pain, we identified 124 patients with new-onset IBP. After a median follow-up of 13.2 years, IBP had progressed to SpA in 39 patients, 15 patients developed a non-SpA diagnosis, and 58 patients had resolution of IBP. At 10 years, the probability of having SpA was 30%, while the probability of resolution of IBP was 43%. The most important predictors for progression to SpA were uveitis, male sex, and family history of SpA. Conclusion In a minority of patients, new-onset IBP progresses to SpA, while IBP resolves in many. That IBP often resolves may explain the difference between the prevalence of IBP (3-6%) and the prevalence of SpA (0.4-1.3%).

To provide an update of the prevalence and incidence of axial spondyloarthritis in the general population and in patients with spondyloarthritis-related conditions, environmental risk factors for ankylosing spondylitis, progression from nonradiographic axial spondyloarthritis to ankylosing spondylitis, mortality, and risks for cardiovascular events in patients with ankylosing spondylitis.Increasingly, administrative healthcare data have been used to study disease frequency and outcomes. The prevalence of ankylosing spondylitis ranged from 9 to 30 per 10 000 persons, which are lower than previous estimates. Data on whether childhood infections influence the risk of ankylosing spondylitis were equivocal, while having been breast-fed may be protective. Progression of patients with nonradiographic axial spondyloarthritis to ankylosing spondylitis is slow, with estimates of 5.1% in 5 years and 19% in 10 years. Risk of mortality is slightly increased in ankylosing spondylitis. Risks for cardiovascular events in ankylosing spondylitis were either not different from, or only slightly higher than in controls. No studies have examined these outcomes in the broader group of patients with axial spondyloarthritis.Expanded use of administrative and registry data has facilitated studies of the epidemiology of ankylosing spondylitis, but lack of specific diagnostic codes limits use of these resources for studying axial spondyloarthritis in general.

A parameter extraction methodology of statistical process variations in FinFET is presented in this paper. First, the main impacts of various variation sources are decomposed, with detailed discussion on the correlation between threshold voltage and subthreshold swing. Second, following the Fin-edge roughness (FER) and gate-edge roughness (GER) compact models, the physical parameters, autocorrelation length and amplitude of root mean square of FER and GER, are extracted based on our proposed extraction procedure. Given a set of ${I}$ – ${V}$ (whether from TCAD or measured silicon data), this method can simply extract the process variation parameters from several experimental sets, such as experiments under different device geometries and/or bias conditions. With the extracted parameters integrated into compact models, the figure of merits of simulation program with integrated circuit emphasis results are well consistent with experimental measurements. The proposed methodology is not only helpful for model-based design-technology co-optimization, but also helpful for variation-aware circuit design.

With the downscaling of CMOS devices, dynamic variability induced by negative bias temperature instability (NBTI) has become a critical issue. In addition to the time-dependent device-to-device variation (DDV) of NBTI degradation, the cycle-to-cycle variation (CCV) originated from random trap occupation is found non-negligible and should be added into the total dynamic variation. This paper summarizes our recent studies on NBTI-induced dynamic variability, focusing on the CCV effect, with more details on the statistical modeling, circuit reliability simulation methodologies and experimental results. By adding the random trap occupation into consideration, a statistical model for total dynamic variation (DDV + CCV) is proposed. The effective occupancy probability peff is introduced as a key parameter for modeling and circuit reliability simulation. With the statistical trap response (STR) method and modified on-the-fly method, the proposed model is validated by the experimental evidence under both DC and AC NBTI. According to the model and experimental results, circuit reliability simulation framework is proposed for both long-term quasi-static and short-term transient performance evaluation with the additional impact of CCV. Two representative digital circuit units, ring oscillator (RO) and SRAM cell, are simulated under different conditions, indicating it necessary to consider the evident influence of the CCV in accurate circuit reliability evaluation. The results are helpful for the reliability/variability-aware circuit design in nanoscale technology.

Objective.To compare the efficacy of 6 tumor necrosis factor–α inhibitors (TNFi) in treatment of ankylosing spondylitis (AS) at 12 weeks and 24 weeks.Methods.We performed a systematic literature review of randomized controlled trials of TNFi in patients with active AS. We included trials that reported efficacy at 10 to 14 weeks (12–week analysis) and at 24 to 30 weeks (24-week analysis). We used Bayesian network metaanalysis (NMA) to compare their relative efficacy to improve the Bath Ankylosing Spondylitis Disease Activity Index (BASDAI), Bath Ankylosing Spondylitis Functional Index (BASFI), and C-reactive protein (CRP) level.Results.We included 20 trials of 6 TNFi, with 43 treatment arms and 3220 participants. All TNFi were significantly better than placebo in reducing BASDAI and BASFI at 12 weeks and 24 weeks; all but certolizumab pegol (CZP) were statistically better than placebo in reducing CRP at 12 weeks; all but CZP and infliximab-dyyb (IFX biosimilar) were significantly better than placebo in reducing CRP at 24 weeks. IFX was superior to the other TNFi in decreasing BASDAI at 12 weeks, but not at 24 weeks. Excluding 1 open-label trial, there were no differences among TNFi.Conclusion.Based on this NMA of clinical trials, IFX was superior to other TNFi in reducing BASDAI at 12 weeks, but sensitive to inclusion of an open-label trial, and its efficacy was diminished at 24 weeks. The analysis was limited by few direct comparison trials. Further study of relative safety and longterm effectiveness will help inform the choice of TNFi in treating active AS.

Stochastic computing (SC), which processes the data in the form of random bit streams, has been used in neural networks due to simple logic gates performing complex arithmetic and the inherent high error-tolerance. However, SC-based neural network accelerators suffer from high latency, random fluctuations, and large hardware cost of pseudo-random number generators (PRNG), thus diminishing the advantages of stochastic computing. In this paper, we address these problems with a novel technique of generating bit streams in parallel, which needs only one clock for conversion and significantly reduces the hardware cost. Based on this parallel bitstream generator, we further present two kinds of convolutional neural network (CNN) accelerator architectures with digital and analog circuits, respectively, showing great potential for low-power applications.

Objective To update evidence-based recommendations for the treatment of patients with ankylosing spondylitis (AS) and nonradiographic axial spondyloarthritis (SpA). Methods We conducted updated systematic literature reviews for 20 clinical questions on pharmacologic treatment addressed in the 2015 guidelines, and for 26 new questions on pharmacologic treatment, treat-to-target strategy, and use of imaging. New questions addressed the use of secukinumab, ixekizumab, tofacitinib, tumor necrosis factor inhibitor (TNFi) biosimilars, and biologic tapering/discontinuation, among others. We used the Grading of Recommendations, Assessment, Development and Evaluation methodology to assess the quality of evidence and formulate recommendations and required at least 70% agreement among the voting panel. Results Recommendations for AS and nonradiographic axial SpA are similar. TNFi are recommended over secukinumab or ixekizumab as the first biologic to be used. Secukinumab or ixekizumab is recommended over the use of a second TNFi in patients with primary nonresponse to the first TNFi. TNFi, secukinumab, and ixekizumab are favored over tofacitinib. Co-administration of low-dose methotrexate with TNFi is not recommended, nor is a strict treat-to-target strategy or discontinuation or tapering of biologics in patients with stable disease. Sulfasalazine is recommended only for persistent peripheral arthritis when TNFi are contraindicated. For patients with unclear disease activity, spine or pelvis magnetic resonance imaging could aid assessment. Routine monitoring of radiographic changes with serial spine radiographs is not recommended. Conclusion These recommendations provide updated guidance regarding use of new medications and imaging of the axial skeleton in the management of AS and nonradiographic axial SpA.

This paper presents the recent advances of our new solution for accurate compact modeling and fast circuit simulation of random telegraph noise (RTN). The model and simulation flow has been implemented in HSPICE using OMI/TMI (CMC open model interface/TSMC model interface). This platform is helpful for the robust circuit design against RTN.

Although the metal-oxide-semiconductor field-effect transistor (MOSFET) has been the dominant device for modern very-large scale integration (VLSI) circuits for more than six decades, with the dawning of a post-Moore era, researchers are trying to find replacements. A foundation of modern digital computing is the encoding of digital values through a binary radix representation. However, as we enter into the post-Moore era, the challenges of increasing power density, signal noise, and device unreliability raise the question of whether this basic way of encoding data is still the best choice, particularly with novel electronic devices. Prior work has shown that binary radix encoding has some disadvantages. We argue that it is crucial to rethink the necessity of using this representation in the post-Moore era. In this paper, we review some recent development on computation-driven data encoding. We begin with stochastic encoding, a representation proposed a long time ago, discussing both its advantages and disadvantages. Then, we review several recent breakthroughs with variations of stochastic encoding that mitigate many of its disadvantages. Finally, we conclude the paper by extrapolating future directions for effective computation-driven data encoding.

Zn0.5Fe2.5O4 nanoparticles (NPs) of 22 nm are synthesized by a one-pot approach and coated with silica for magnetic hyperthermia agents. The NPs exhibit superparamagnetic characteristics, high-specific absorption rate (SAR) (1083 wg−1, f = 430 kHz, H = 27 kAm−1), large saturation magnetization (Ms = 85 emu g−1), excellent colloidal stability and low cytotoxicity. The cell uptake properties have been investigated by Prussian blue staining, transmission electron microscopy and the inductively coupled plasma-mass spectrometer, which resulted in time-dependent and concentration-dependent internalization. The internalization appeared between 0.5 and 2 h, the NPs were mainly located in the lysosomes and kept in good dispersion after incubation with human osteosarcoma MG-63 cells. Then, the relationship between cell uptake and magnetic hyperthermia performance was studied. Our results show that the hyperthermia efficiency was related to the amount of internalized NPs in the tumour cells, which was dependent on the concentration and incubation time. Interestingly, the NPs could still induce tumour cells to apoptosis/necrosis when extracellular NPs were rinsed, but the cell kill efficiency was lower than that of any rinse group, which indicated that local temperature rise was the main factor that induced tumour cells to death. Our findings suggest that this high SAR and biocompatible silica-coated Zn0.5Fe2.O4 NPs could serve as new agents for magnetic hyperthermia.

Hole velocity in black phosphorus exceeds most other semiconductors at room temperature and is even higher at low temperatures., As a strong candidate for future electronics, atomically thin black phosphorus (BP) has attracted great attention in recent years because of its tunable bandgap and high carrier mobility. Here, we show that the transport properties of BP device under high electric field can be improved greatly by the interface engineering of high-quality HfLaO dielectrics and transport orientation. By designing the device channels along the lower effective mass armchair direction, a record-high drive current up to 1.2 mA/μm at 300 K and 1.6 mA/μm at 20 K can be achieved in a 100-nm back-gated BP transistor, surpassing any two-dimensional semiconductor transistors reported to date. The highest hole saturation velocity of 1.5 × 107 cm/s is also achieved at room temperature. Ballistic transport shows a record-high 36 and 79% ballistic efficiency at room temperature and 20 K, respectively, which is also further verified by theoretical simulations.

Stochastic computing (SC) presents high error tolerance and low hardware cost, and has great potential in applications such as neural networks and image processing. However, the bitstream generator, which converts a binary number to bitstreams, occupies a large area and energy consumption, thus weakening the superiority of SC. In this paper, we propose a novel technique for generating bitstreams in parallel, which needs only one clock for conversion and significantly reduces the hardware cost. Synthesis results demonstrate that the proposed parallel bitstream generator improves 2.5x area and 712x energy consumption.

Convolutional neural network (CNN) achieves excellent performance on fascinating tasks such as image recognition and natural language processing at the cost of high power consumption. Stochastic computing (SC) is an attractive paradigm implemented in low power applications which performs arithmetic operations with simple logic and low hardware cost. However, conventional memory structure designed and optimized for binary computing leads to extra data conversion costs, which significantly decreases the energy efficiency. Therefore, a new memory system designed for SC-based multiply-accumulate (MAC) engine applied in CNN which is compatible with conventional memory system is proposed in this paper. As a result, the overall energy consumption of our new computing structure is 0.91pJ, which is reduced by 82.1% compared with the conventional structure, and the energy efficiency achieves 164.8 TOPS/W., 6 pages, 6 figures

In this paper, we propose a machine-learning assisted modeling framework in design-technology co-optimization (DTCO) flow. Neural network (NN) based surrogate model is used as an alternative of compact model of new devices without prior knowledge of device physics to predict device and circuit electrical characteristics. This modeling framework is demonstrated and verified in FinFET with high predicted accuracy in device and circuit level. Details about the data handling and prediction results are discussed. Moreover, same framework is applied to new mechanism device tunnel FET (TFET) to predict device and circuit characteristics. This work provides new modeling method for DTCO flow.

In this paper, the NBTI-induced circuit frequency degradation is found having a non-monotonic bias dependence, thus an optimal V DD can be assessed based on this reliability tradeoff. As a demonstration, based on our recently-developed compact aging model and circuit reliability simulator, NBTI-induced frequency degradation in inverters are simulated, in terms of various V th and V DD , considering two typical stress waveforms. The results show the relationships between the optimal V DD of circuit and various stress conditions, which are useful to the reliability-aware V DD optimization for CMOS technology.

To deeply understand the charge trapping process in high-k gate stacks, we theoretically investigate the hole trapping characteristics of interfacial oxygen vacancies in (110) and (100) Si/SiO 2 /HfO 2 stacks. Si/SiO 2 and SiO 2 /HfO 2 interfacial defects are studied, and the hole trapping rate of each defect is calculated through ab initio simulation combining density-functional theory and Marcus theory. Among the possible hole traps considered in this work, it is suggested that the oxygen vacancies at SiO 2 /HfO 2 interface are the dominant under strong negative gate bias stress, and those at Si/SiO 2 interface can be effective traps only when hydrogen atom (H) or hydroxyl (OH) is induced at the vacancy. Moreover, the most dominant hole trap among the considered traps in the (110) structure locates at the Si/SiO 2 interface, while that in the (100) structure locates at the SiO 2 /HfO 2 interface.

Convolutional neural networks (CNN) have achieved excellent performance on various tasks, but deploying CNN to edge is constrained by the high energy consumption of convolution operation. Stochastic computing (SC) is an attractive paradigm which performs arithmetic operations with simple logic gates and low hardware cost. This paper presents an energy-efficient mixed-signal multiply-accumulate (MAC) engine based on SC. A parallel architecture is adopted in this work to solve the latency problem of SC. The simulation results show that the overall energy consumption of our design is 5.03pJ per 26-input MAC operation under 28nm CMOS technology., Comment: 6 pages,6 figures

Reliability is an important consideration during semiconductor technology development, which ensures that the performances of devices, circuits, and systems are maintained over a specified period of time, leading to successful products. Device reliability is at the core of overall product reliability, which continues to remain an important area of research and has attracted the attention of IEEE Transactions on Electron Devices (T-ED) authors and readers throughout the years. Device reliability can be classified into two broad areas: gradual drift of device performance over time or sudden failure, and both are of importance for logic, memory, RF, and power devices. Different aspects of device reliability are usually reported, such as the development of electrical or physical characterization methods, investigation and modeling of a particular phenomenon, impact of material and processes on reliability, and development of reliability tolerant technologies.

In this paper, the recent advances of our studies on RTN are presented from device, circuit, and EDA perspectives. RTN characteristics in FinFETs are investigated and compared with planar devices. The AC RTN effect is discussed for understanding RTN impacts in practical circuit applications. Then, a new and efficient circuit simulation platform for RTN is presented for the first time, which has been implemented in HSPICE using OMI/TMI. In addition, some open questions related to RTN are discussed with outlooks.

Objective The long-term outcome of patients with nonradiographic axial spondyloarthritis (SpA) is unclear, particularly whether few or most progress to ankylosing spondylitis (AS). Our objective was to examine the progression to AS in a population-based inception cohort of patients with nonradiographic axial SpA. Methods The Rochester Epidemiology Project (REP) is a longstanding population-based study of health in the residents of Olmsted County, Minnesota. We searched the REP from 1985 to 2010 using diagnostic and procedural codes for back pain, HLA–B27, and magnetic resonance imaging of the pelvis, and we performed detailed chart reviews to identify subjects who fulfilled the Assessment of SpondyloArthritis international Society classification criteria for axial SpA but did not have AS. We followed these subjects from disease onset to March 15, 2015, and used survival analysis to measure the time to progression to AS. Results After screening 2,151 patients, we identified 83 subjects with new-onset nonradiographic axial SpA. Over a mean follow-up of 10.6 years, progression to AS occurred in 16 patients. The probability that the condition would remain as nonradiographic axial SpA at 5, 10, and 15 years was 93.6%, 82.7%, and 73.6%, respectively. There was more frequent and more rapid progression among subjects in the imaging arm (n = 18) than among those in the clinical arm (n = 65) (28% versus 17%; hazard ratio 3.50 [95% confidence interval 1.15–10.6], P = 0.02). Conclusion Progression to AS occurred in a minority (26%) of patients with nonradiographic axial SpA over as long as 15 years of follow-up. This suggests that the classification criteria for nonradiographic axial SpA identifies many patients in whom the condition is unlikely to progress to AS or that nonradiographic axial SpA represents a prolonged prodromal state that takes longer to evolve to AS and thus requires longer follow-up.

The 2019-nCoV is officially called SARS-CoV-2 and the disease is named COVID-19. This viral epidemic in China has led to the deaths of over 1800 people, mostly elderly or those with an underlying chronic disease or immunosuppressed state. This is the third serious Coronavirus outbreak in less than 20 years, following SARS in 2002-2003 and MERS in 2012. While human strains of Coronavirus are associated with about 15% of cases of the common cold, the SARS-CoV-2 may present with varying degrees of severity, from flu-like symptoms to death. It is currently believed that this deadly Coronavirus strain originated from wild animals at the Huanan market in Wuhan, a city in Hubei province. Bats, snakes and pangolins have been cited as potential carriers based on the sequence homology of CoV isolated from these animals and the viral nucleic acids of the virus isolated from SARS-CoV-2 infected patients. Extreme quarantine measures, including sealing off large cities, closing borders and confining people to their homes, were instituted in January 2020 to prevent spread of the virus, but by that time much of the damage had been done, as human-human transmission became evident. While these quarantine measures are necessary and have prevented a historical disaster along the lines of the Spanish flu, earlier recognition and earlier implementation of quarantine measures may have been even more effective. Lessons learned from SARS resulted in faster determination of the nucleic acid sequence and a more robust quarantine strategy. However, it is clear that finding an effective antiviral and developing a vaccine are still significant challenges. The costs of the epidemic are not limited to medical aspects, as the virus has led to significant sociological, psychological and economic effects globally. Unfortunately, emergence of SARS-CoV-2 has led to numerous reports of Asians being subjected to racist behavior and hate crimes across the world.

Zn 0.5 Fe 2.5 O 4 nanoparticles (NPs) of 22 nm are synthesized by a one-pot approach and coated with silica for magnetic hyperthermia agents. The NPs exhibit superparamagnetic characteristics, high-specific absorption rate (SAR) (1083 wg −1 , f = 430 kHz, H = 27 kAm −1 ), large saturation magnetization ( M s = 85 emu g −1 ), excellent colloidal stability and low cytotoxicity. The cell uptake properties have been investigated by Prussian blue staining, transmission electron microscopy and the inductively coupled plasma-mass spectrometer, which resulted in time-dependent and concentration-dependent internalization. The internalization appeared between 0.5 and 2 h, the NPs were mainly located in the lysosomes and kept in good dispersion after incubation with human osteosarcoma MG-63 cells. Then, the relationship between cell uptake and magnetic hyperthermia performance was studied. Our results show that the hyperthermia efficiency was related to the amount of internalized NPs in the tumour cells, which was dependent on the concentration and incubation time. Interestingly, the NPs could still induce tumour cells to apoptosis/necrosis when extracellular NPs were rinsed, but the cell kill efficiency was lower than that of any rinse group, which indicated that local temperature rise was the main factor that induced tumour cells to death. Our findings suggest that this high SAR and biocompatible silica-coated Zn 0.5 Fe 2. O 4 NPs could serve as new agents for magnetic hyperthermia.

Neural networks have been used in a variety of fields including speech process, image recognition and video classification. In this work, based on 16/14nm FinFET technology, the feasibility of the neuron circuit using stochastic computing is evaluated. Considering the practical technology issues, the impact of random variabilities is carefully examined under ultra-low voltage. Using handwritten digital MNIST database, a reliable validation accuracy in neural network based on stochastic computing neuron circuits can be obtained with an ultra-low V dd . The design optimization procedure of neuron circuits is also proposed, which can decrease the energy consumption without the penalty of accuracy.