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Soft wearable robotic gloves based on tendon-sheath mechanism are widely developed for assisting people with a loss of hand mobility. For these robots, knowing the fingertip forces applied to deformable objects is crucial in successfully grasping them without causing excessive deformations. Existing studies presented methods to predict fingertip force applied to rigid objects only using information from the actuation system. However, forces applied to deformable objects are subject to non-linearity and hysteresis in relation to the objects’ stiffness, which further complicates the problem. Therefore, this letter proposes a deep-learning model that can accurately estimate the fingertip forces applied to deformable objects using motor encoder values, motor current, and wire tension. Our model is based on an integrated system of Long Short-Term Memory models that 1) estimates stiffness of the grasped objects and 2) incorporates the estimated stiffness for predicting the fingertip forces. When evaluated using a TSM-based soft wearable robot, the proposed model recorded fingertip force estimation of 0.702 N RMSE, achieving 45% increase in accuracy compared to LSTM that does not consider the objects’ stiffness. The applicability of our method was evaluated by estimating the fingertip forces applied to common daily items and performing real-time force control.

In this study, we examine the effect of oxygen vacancies ( ${V}_{O}$ ) near the back surface of p-type tin monoxide (SnO) semiconductors on the device performance of its thin-film transistors (TFTs). Non-stoichiometry of the SnO surface layer was controlled through oxidant exposure conditions during alumina (Al2O3) growth using plasma-enhanced atomic layer deposition (PEALD). During the initial period of Al2O3 deposition, trimethylaluminum precursors absorbed oxygen from the SnO layer and created the ${V}_{O}$ , which can form a ${V}_{O}$ -rich region at the Al2O3/SnO interface. By modulating the oxygen plasma density during the PEALD process, the ${V}_{O}$ was effectively controlled, allowing the electrical characteristics to transition from ambipolar behavior to ${p}$ -channel only conduction. This study demonstrates the importance of the back surface of SnO, suggesting a new perspective of ambipolar behavior in p-type SnO semiconductors.

Introduction Patients with advanced aortic stenosis (AS) have a high risk of sleep-related breathing disorders (SRBD), yet prior research is limited to type III sleep apnea tests. Whereas the American Academy of Sleep Medicine recommends polysomnography for SRBD diagnosis in patients with significant cardiorespiratory disease, unattended studies are often more acceptable, especially to surgical candidates. We conducted this study to address the need for comprehensive sleep testing in patients with advanced AS. Methods We conducted unattended type II sleep tests in 23 adults aged 50 and older scheduled for surgical aortic valve replacement (SAVR) and not using positive airway pressure. We obtained demographics and medical history and administered Clinical Dementia Rating, Pittsburgh Sleep Quality Index, Epworth Sleepiness Scale, and 9-item Patient Health Questionnaire. We characterize this pre-surgical sample and report SRBD prevalence. Results Average age of the sample was 68.3 ± 7.2 (mean ± SD), and 74% were male. Charlson comorbidity index was 2.0 ± 2.0. Three (13%) had a global CDR of 0.5, consistent with mild cognitive impairment. Mean PSQI scores were 7.0 ± 3.6, ESS 6.7 ± 4.0, and PHQ-9 4.6 ± 5.3. No subject had an AHI < 5: 7 had a score of 5–14, 8 of 15–29, and 8 of 30 or greater. Mean obstructive AHI was 25.3 ± 20.7, central AHI 1.9 ± 3.4, and respiratory arousal index 8.7 ± 6.2. Total sleep time 362.7 ± 82.6 min with sleep efficiency of 82.1% ± 8.6%. Sleep stage data to be presented. Conclusion All subjects in this sample not using positive airway pressure had an AHI ≥ 5. Sixteen subjects (70%) had an AHI ≥ 15, indicating moderate to severe sleep apnea due to predominantly obstructive events. These results strongly suggest that patients with severe AS, especially those undergoing SAVR, would benefit from evaluation for SRBD. Support (if any) This research was supported in part by the National Institute on Aging, K23AG072383. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. Additional support provided by University of Rochester Medical Center funds through the Departments of Psychiatry and Cardiology/Cardiac Surgery.

In this Letter, we report a demonstration of p-channel tin monoxide (SnO) thin-film transistors (TFTs) with high field-effect mobility ( μFE) exceeding 10 cm2/Vs and hysteresis-free like behavior. We demonstrate that maintaining metallic states before encapsulation is a key process to enhance μFE in p-type SnO thin-films. Sustaining this meta-stability involves the following two processes during fabrication: (1) postdeposition annealing (PDA) in two steps and (2) encapsulation in the middle of each PDA. This simple process not only suppresses creation of oxidized states such as adverse Sn4+ but also facilitates the lateral growth of crystals with improved crystallinity by interfacial energy stabilization. The resultant SnO TFT reveals a record-high μFE up to 15.8 cm2/Vs with a negligible hysteresis of 0.1 V. This study suggests a practical route to grant high μFE to p-channel SnO TFTs without any dopant or complex postdeposition treatment.

Soft robots have been extensively researched due to their flexible, deformable, and adaptive characteristics. However, compared to rigid robots, soft robots have issues in modeling, calibration, and control in that the innate characteristics of the soft materials can cause complex behaviors due to non-linearity and hysteresis. To overcome these limitations, recent studies have applied various approaches based on machine learning. This paper presents existing machine learning techniques in the soft robotic fields and categorizes the implementation of machine learning approaches in different soft robotic applications, which include soft sensors, soft actuators, and applications such as soft wearable robots. An analysis of the trends of different machine learning approaches with respect to different types of soft robot applications is presented; in addition to the current limitations in the research field, followed by a summary of the existing machine learning methods for soft robots.

Based on the 2016 report by Centers for Disease Control and Prevention, it has been estimated that behavioral health disorders including dementia affect 65–90% of the estimated 1.5 million nursing home residents residing in 15,600 nursing homes across the United States. However, despite this, nursing home staff are often ill equipped to meet the mental health needs of their residents. Studies report that more than half of nursing homes do not have adequate access to psychiatric consultation, and three quarters are unable to obtain consultation and educational services for behavioral problems. The need for improved access to and quality of mental health services within nursing homes remains a pressing concern today. The aims of this session are to characterize the burden of mental illness in nursing home residents in the US and to describe the cutting-edge efforts to deliver psychiatric services to nursing homes by leveraging technology. First, Dr. Briana Mezuk from University of Michigan will describe a data science approach to estimate mental illness burden in nursing home as exemplified by her recent JAMA Psychiatry article on late-life suicides in long-term care facilities. Then, based on his ongoing AHRQ-funded randomized controlled trial, Dr. Glen Xiong from UC Davis will compare asynchronous telepsychiatry alongside synchronous telepsychiatry in skilled nursing facilities. Finally, Dr. Elizabeth Santos from University of Rochester will report the results from the analysis of the multifaceted URMC Geriatric Telepsychiatry Model implemented in 29 nursing homes across the Finger Lakes Region of New York State. Afterwards. Joel Streim from University of Pennsylvania will lead the discussion and Q&A with the audience.

We consider WIP-controlled line production systems with constant processing times.For a given QoS, both CONWIP and DBR outperform a Kanban.A DBR system needs less buffer capacity than or at most equal a CONWIP system.In general, a CONWIP system outperforms a DBR system under the same QoS.Under the certain condition a DBR system outperforms a CONWIP system. We compared three types of WIP-controlled line production systems with constant processing times such as Kanban, CONWIP (constant work-in-process) and DBR (drum-buffer-rope). Based on the observation that such WIP-controlled line production systems are equivalent to m-node tandem queues with finite buffers under communication blocking policy, we applied a max-plus algebra based solution method for the tandem queue to evaluate their performance. Within our knowledge, this research is the first attempt to apply an exact solution method for comparing all three WIP-controlled line production systems at a time. Six-node numerical examples were also used to demonstrate the proposed analysis. The numerical results can be generalized and also provide some insights in designing production systems under certain limited condition.

Introduction Alzheimer's disease (AD) is a disabling, common cause of dementia, and agitation is one of the most common and distressing symptoms for patients with AD. Escitalopram for agitation in Alzheimer's disease (S-CitAD) tests a novel, clinically derived therapeutic approach to treat agitation in patients with AD. Methods S-CitAD is a NIH-funded, investigator-initiated, randomized, multicenter clinical trial. Participants receive a structured psychosocial intervention (PSI) as standard of care. Participants without sufficient response to PSI are randomized to receive 15 mg escitalopram/day or a matching placebo in addition to PSI. Primary outcome is the Modified Alzheimer's Disease Cooperative Study - Clinical Global Impression of Change (mADCS-CGIC). Discussion S-CitAD will provide information about a practical, immediately available approach to treating agitation in patients with AD. S-CitAD may become a model of how to evaluate and predict treatment response in patients with AD and agitation as a neuropsychiatric symptom (ClinicalTrials.gov Identifier: NCT03108846).

Introduction Although depression is a putative risk factor for delirium after coronary artery bypass graft (CABG) surgery, it is unclear to what extent this risk is independent of cognitive impairment and cerebrovascular disease. This study concurrently examines depression (mild or major), mild cognitive impairment (MCI) and cerebrovascular disease (defined as intracranial atherosclerosis) as post-CABG delirium risk factors. Methods This prospective, observational cohort study recruited and assessed 131 subjects without dementia undergoing CABG surgery at a tertiary-care, academic hospital. Preoperative cognitive assessment included Clinical Dementia Rating and neuropsychological battery; depression was assessed using Depression Interview Structured Hamilton. Baseline intracranial stenosis was evaluated by transcranial Doppler of bilateral middle cerebral arteries (MCA). Study psychiatrists assessed delirium on postoperative days 2–5 using the Confusion Assessment Method. Results Average age of the study sample was 65.8 (SD: 9.2) years, and 27% were female. MCI prevalence was 24%, preoperative depression 10%, lifetime depression 35%, and MCA stenosis (≥ 50%) 28%. Sixteen percent developed delirium. Multivariate analysis revealed that age, MCI (OR 5.1, 95% CI 1.3–20.1), and preoperative depression (OR 9.9, 95% CI 1.3–77.9)—but not lifetime depression—predicted delirium. MCA stenosis and its severity predicted delirium in univariate but not multivariate analysis. Right MCA stenosis severity predicted delirium severity but left-sided stenosis severity did not. Conclusions Our findings indicate that the risk of delirium attributable to depression could extend beyond the potential moderating influence of cognitive impairment and cerebrovascular disease. Even mild depression and cognitive impairment before CABG appear to deserve recognition for their effect on post-CABG cognitive health. This research was funded by The NOAHS study (PI: HB Lee) is supported by R01 MH085740. Exploratory analysis of this study was supported by the CEDARTREE Program (K07 AG041835; PI: SK Inouye).

There has been no analytic expression for a multi-node queue even with constant processing times because of a correlation caused by blocking between nodes. This study introduces explicit expressions for moments and tail probability of stationary waiting times in a Poisson-driven deterministic 2-node tandem queue with blocking. Unlike the normal queueing theory, we derive these expressions from the previous results based on the max-plus algebraic approach. Two blocking policies are considered: blocking before service (BBS) and blocking after service (BAS).

With a high prevalence of well-established risk dementia risk factors (e.g. tobacco, alcohol use, hypertension, and diabetes), there is a dire need for data on prevalence and correlates of cognitive impairment and related service utilization among older Korean Americans. Memory and Aging study of Koreans (MASK) is a two-stage epidemiological survey with two-step sampling strategy to obtain a representative sample. We screened 1,118 older Korean Americans (mean age: 70.7, female: 67.2%) with a Korean version of the Mini-Mental State Exam, and 118 persons sampled from two levels of performance on the MMSE underwent the second stage clinical evaluation that included the Consortium to Establish a Registry for Alzheimer’s Disease (CERAD). Preliminary analysis estimated that community prevalence of mild cognitive impairment in this population was 28.4% (CI: 18.2%-41.5%) and dementia was 7.2% (3.8% - 13.2%). Correlates of cognitive impairment, and potential barriers to the services will be discussed during this presentation.

We compared a DBR(drum-buffer-rope) system with a CONWIP(constant work-in-process) system in a production line with constant processing times. Based on the observation that a WIP-controlled line production system such as DBR and CONWIP is equivalent to a m-node tandem queue with finite buffer, we applied a max-plus algebra based solution method for the tandem queue to evaluate the performance of two systems. Numerical examples with 6 workstations were also used to demonstrate the proposed analysis. The mathematical analyses support that CONWIP outperforms DBR in terms of expected waiting time and WIP. Unlike the CONWIP case, sequencing workstations in a DBR affects the performance of the system. Delaying a bottleneck station in a DBR reduces expected waiting time. Key words : CONWIP, DBR, tandem queue, max-plus linear system요 약이 연구는 상수 공정 시간을 갖는 라인생산시스템에서 CONWIP 과 DBR이 각각 max-plus 선형시스템의 특수형태임을 밝히고 max-plus 대수에 기반한 안정대기시간 연구결과를 이용하여 CONWIP 와 DBR의 성능을 비교 분석하였다 . CONWIP의 경우, 생산시스템 내의 체류시간은 DBR의 경우보다 항상 짧다는 사실이 수학적으로 규명되었고 예제를 통해 계산 , 비교되었다. 한편 두 경우에서 모두 , 애로공정이후 노드에서의 대기시간은 유한버퍼의 크기와 공정의 순서에 무관함을 확인하였다 . CONWIP에서는 시스템 내 평균 대기시간 또는 체류시간이 공정의 순서에 무관하지만 , DBR에서는 애로공정이 뒤로 갈수록 감소함을 확인하였다.주요어 : CONWIP, DBR, tandem queue, max-plus 선형 시스템

International audience; Increasing the level of detail (LOD) in brushstrokes within areas of interest improved the realism of painterly rendering. Using a modified quad-tree, we segmented an image into areas with similar levels of saliency; each of these segments was then used to control the brush strokes during rendering. We could also simulate real oil painting steps based on saliency information. Our method runs in a reasonable fine and produces results that are visually appealing and competitive with previous techniques.

We present a fog generation algorithm in 2D images. The proposed algorithm provides a scattering model for the approximated calculation of fog density. The scattering model needs parameters of distance and altitude information. However, 2D images do not include those information, so that we calculate them from the depth information generated in an interactive manner, and estimate the scattering factor by using the scattering model. Then we generate fog effect on an input image using the scattering factor by distance-oriented selection blur and color blending. With the algorithm, we can easily create the fog-effected images and fog generated animation from 2D images.

We consider a stationary waiting time in a Poisson driven single-server m-node tandem queue with either constant or non-overlapping service times. Each node except for the first one has a finite buffer, and is operated under production blocking. By using (max,+ )-algebra, we explicitly express the stationary waiting time at each node as a function of finite buffer capacities. We also address that the explicit expression is separable and monotone decreasing with respect to the buffer sizes. These properties are applied to a buffer allocation problem with probabilistic constraints on stationary waiting times.

Texture transfer re-renders a target image with high-frequency information (texture) taken from parts of a reference image that is matched locally to the target image using characteristics such as color. In this paper, we add a directional factor based on the flow of the target image, creating a stroke-like effect that follows edges more accurately. In addition, we propose a method to clearly express object boundaries by considering the effect of the medium on edges in the reference image. We also show how to select an appropriate weight for this directional factor from the reference image. We demonstrate the suitability of this improved form of texture transfer for expressing various artistic styles, and compare our results with those from previous texture-transfer algorithms. We find that our algorithm can be adapted to texture synthesis as well.

Objective To describe the methodology utilized to evaluate cognitive function in the Multi-Ethnic Study of Atherosclerosis (MESA) and to present preliminary results by age, sex, and race/ethnicity. Design Cross-sectional measurements of a prospective observational cohort. Setting Residents of 6 U.S. communities free of cardiovascular disease at baseline (2000–02). Participants 4,591 adults who completed the fifth MESA clinical examination in 2011–12; mean age 70.3 (SD: 9.5) years, 53.1% women, 40.7% non-Hispanic white, 26.4% non-Hispanic black, 21.4% Hispanic, and 11.5% Chinese. Measurements The cognitive battery consisted of the Cognitive Abilities Screening Instrument (version 2) to evaluate global cognition, the Digit Symbol Code for processing speed and Digit Spans Forward and Backward to assess memory. Demographic, socioeconomic, and cultural covariates were also collected for descriptive statistics and multivariate modeling. Results Associations between socioeconomic factors and cognition revealed that age, race/ethnicity, education, occupational status, household income, health insurance type, household size, place of birth, years and generation in U.S., and the presence of the ApoE4 allele were significantly associated with performance on the cognitive tests, although patterns varied by specific test, racial/ethnicity, and sociocultural factors. Conclusion As many of the influencing cultural and socioeconomic factors measured here are complex, multifactorial, and may not be adequately quantified, caution has been recommended with regard to comparison and interpretation of racial/ethnic group performance differences from these cross-sectional models. These data provide a baseline for future exams and more comprehensive longitudinal analyses of the contributions of subclinical and clinical diseases to cognitive function and decline.

There has been a great change in manufacturing systems toward computer-controlled flexible manufacturing systems (FMS). The design and operation of the FMS involve intricate and interconnected decisions that result in the maximum performance of the system. However, the design and operational decisions have been made separately in consideration of a single-system performance measure. This paper presents a method for simultaneously determining design and control parameters of an FMS with the multiple performance objectives via full-factorial design of experiments, regression analysis and compromise programming. For a numerical example, the SIMAN simulator models a hypothetical FMS with six workstations. Eight design and control parameters are simultaneously determined by compromising four performance measures that are formulated using regression analysis.

Sleep disturbance is an important clinical complaint for individuals with nonmalignant pain conditions. This review is a broad introduction to the literature on sleep disturbance and chronic pain conditions. The article critically reviews studies of sleep disturbance in musculoskeletal pain, arthritis, headache, and fibromyalgia. Current neurobiological hypotheses regarding the pathogenesis of sleep disturbance and chronic pain, common comorbid disorders, and pharmacologic and non-pharmacologic treatments for sleep disturbance are reviewed.

Trick art is a genre of artistic expression that can give not only beautifulness but also entertainment. Lenticular image (or printing) is one skill of trick art that shows different image depend on the viewer’s viewpoint by controlling refraction of light. The object, seen by viewer in some view angle, goes shimmering when the viewer change the view angle. In computer graphics area, other trick arts were simulated, but simulation of lenticular image is not well progressed. So in this paper, we do simulate the lenticular Image. For this, we first set the position of input object image on the given background image depend on the similarity of gradient. And then blend the object into background image. Lastly, we cover the lenticular lens on the image that is the composition of original background image and blended image. Finally, we can generate the 3D scene which simulates the lenticular images.

In this paper, we present an algorithm that provides a focusing effect by transforming the character of strokes. The focusing point can be obtained by the density of edges, which refers to the amount of edges in a specific area. After the determination of the focusing point, the following work should be done. First, details and abstraction should be expressed by adjusting the brush size centering on the focusing point. Second, the direction of the brush should be determined so the view is focused through interpolation using the focusing point. Third the focusing point should be exaggerated by adjusting the blur and highlight effects. The focusing effects generated on the desired part through the above procedure can provide an effect of oil painting that has been realized by a human being.

Increasing the level of detail (LOD) in brushstrokes within areas of interest improved the realism of painterly rendering. Using a modified quad-tree, we segmented an image into areas with similar levels of saliency, each of these segments was then used to control the brush strokes during rendering. We could also simulate real oil painting steps based on saliency information. Our method produces results that are visually appealing and good for interactive system.

Nowadays smart phone is widely converge and the growth of mobile and small device market is rapidly increasing. And many image based applications are developed for generating contents. In this paper, we propose a system for human-friendly image generation from user chosen reference images. In mobile application research, performance and waiting time is main problems. Because mobile OS is not fast as PC. So we modify previous texture transfer techniques considering waiting time and performance. For this, we modified from scan-line approach to random-access approach. Our proposed system can make various artistic results automatically. From this framework, we develop android operating system based smart phone application. This system can be extended to various imaging devices (IPTV, camera, stylish photo).

A texture transfer algorithm modifies the target image replacing the high frequency information with the example source image. Previous texture transfer techniques normally use such factors as color distance and standard deviation for selecting the best texture from the candidate sets. These factors are useful for expressing a texture effect of the example source in the target image, but are less than optimal for considering the object shape of the target image.In this paper, we propose a novel texture transfer algorithm to express the directional effect based on the flow of the target image. For this, we use a directional factor that considers the gradient direction of the target image. We add an additional energy term that respects the image gradient to the previous fast texture transfer algorithm. Additionally, we propose a method for estimating the directional factor weight value from the target image. We have tested our algorithm with various target images. Our algorithm can express a result image with the feature of the example source texture and the flow of the target image.

To test the hypothesis that sedation in elderly patients is often electrophysiologically equivalent to general anesthesia (GA).Prospective, observational study.Operating room of a university medical center.40 elderly patients (or=65 yrs of age) undergoing hip fracture repair with spinal anesthesia and propofol-based sedation.In the routine practice group (RP; n = 15), propofol sedation was administered per the usual routine of the anesthesiologist. In the targeted sedation group (TS; n = 25), sedation was titrated to an observer's assessment of alertness/sedation (OAA/S) score of 4 (ie, lethargic in response to name called) to 5 (ie, awake and alert).Both patient groups underwent processed electroencephalographic monitoring using bispectral index (BIS) intraoperatively. BIS levels were compared between groups to determine amount of surgical time spent in GA (BISor= 60).In the RP group, subjects spent 32.2% of surgical time at BIS levels consistent with GA. Although averaged BIS values during surgery increased from (mean +/- SD) 71 +/- 16 to 88 +/- 9 (P0.001), GA was still observed during 5% of surgical time in the TS group. Overall, 13 of 15 (87%) RP group patients and 11 of 25 (44%) TS group patients (P0.010) experienced some period of GA.BIS levels consistent with GA occur frequently in elderly patients during propofol-based sedation for spinal anesthesia. Altering routine practice such that sedation is titrated to a targeted clinically-determined sedation level reduces - but does not eliminate - this incidence.

Context There are no studies of the natural history of major depressive disorder that lack prevalence and clinic biases. Objectives To estimate risk factors for first lifetime onset and parameters of chronicity following the first episode, including duration, recovery, and recurrence, and to search for predictors of each parameter. Design Prospective population-based cohort study with 23 years of follow-up. Setting East Baltimore, Maryland, an urban setting. Participants Probability sample of 3481 adult household residents in 1981, including 92 with first lifetime onset of major depressive disorder during the course of the follow-up, and 1739 other participants followed up for at least 13 years. Outcome Measures Diagnostic Interview Schedule and Life Chart Interview. Results Female participants showed higher risk of onset of disorder, longer duration of episodes, and a nonsignificant tendency for higher risk of recurrence. Sex was not related to recovery. The median episode length was 12 weeks. About 15% of 92 individuals with first episodes did not have a year free of episodes, even after 23 years. About 50% of first episode participants recovered and had no future episodes. The evolution of the course was relatively stable from first to later episodes. Individuals with 1 or 2 short alleles of the serotonin transporter gene were at higher risk for an initial episode, but experienced episodes of shorter duration. There were few strong predictors of recovery or recurrence. Conclusions Major depressive disorder is unremitting in 15% of cases and recurrent in 35%. About half of those with a first-onset episode recover and have no furtherepisodes.

We introduce a new glass tile generation method for simulating Stained Glass using region segmentation algorithm and cubic spline interpolation method. We apply a Mean shift segmentation algorithm to a source image to extract a shape of glass tile. We merge regions by user input and use morphological operation to remove the invalid shape. To make the shape of glass tile, we apply cubic spline interpolation and obtain the leading and the region with smooth boundary. Next, we re-segment the region using the spline curves. Finally we apply the transformed colors to each region to create a whole glass tile.