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We report the magnetic-field-assisted electric-field-controlled domain switching of a magnetic single domain in a multiferroic/magnetoelectric Ni nanochevrons/[Pb(Mg1/3Nb2/3)O3]0.68–[PbTiO3]0.32 (PMN–PT) layered structure. Initially, a magnetic field was applied in the transverse direction across single-domain Ni nanochevrons to transform each of them into a two-domain state. Subsequently, an electric field was applied to the layered structure, exerting the converse magnetoelectric effect to transform/release the two-domain Ni nanochevrons into one of two possible single-domain states. Finally, the experimental results showed that approximately 50% of the single-domain Ni nanochevrons were switched permanently after applying our approach (i.e., the magnetization direction was permanently rotated by 180 degrees). These results mark important advancements for future nanoelectromagnetic systems. [ABSTRACT FROM AUTHOR]

Background: Potentially inappropriate medications (PIMs) in older adults are medications in which risks often outweigh benefits and are suggested to be avoided. Worldwide, many distinct guidelines and tools classify PIMs in older adults. Collating these guidelines and tools, mapping them to a medication classification system, and creating a crosswalk will enhance the utility of PIM guidance for research and clinical practice. Methods: We used the Anatomical Therapeutic Chemical (ATC) Classification System, a hierarchical classification system, to map PIMs from eight distinct guidelines and tools (2019 Beers Criteria, Screening Tool for Older Person's Appropriate Prescriptions [STOPP], STOPP‐Japan, German PRISCUS, European Union‐7 Potentially Inappropriate Medication [PIM] list, Centers for Medicare & Medicaid Services [CMS] High‐Risk Medication, Anticholinergic Burden Scale, and Drug Burden Index). Each PIM was mapped to ATC Level 5 (drug) and to ATC Level 4 (drug class). We then used the crosswalk (1) to compare PIMs and PIM drug classes across guidelines and tools to determine the number of PIMs that were index (drug‐induced adverse event) or marker (treatment of drug‐induced adverse event) drug of prescribing cascades, and (2) estimate the prevalence of PIM use in older adults continuously enrolled with fee‐for‐service Medicare in 2018 as use cases. Data visualization and descriptive statistics were used to assess guidelines and tools for both use cases. Results: Out of 480 unique PIMs identified, only three medications—amitriptyline, clomipramine, and imipramine and two drug classes—N06AA (tricyclic antidepressants) and N06AB (selective serotonin reuptake inhibitors), were noted in all eight guidelines and tools. Using the crosswalk, 50% of classes of index drugs and 47% of classes of marker drugs of known prescribing cascades were PIMs. Additionally, 88% of Medicare beneficiaries were dispensed ≥1 PIM across the eight guidelines and tools. Conclusion: We created a crosswalk of eight PIM guidelines and tools to the ATC classification system and created two use cases. Our findings could be used to expand the ease of PIM identification and harmonization for research and clinical practice purposes. [ABSTRACT FROM AUTHOR]

The performance of speech-processing models is heavily influenced by the speech corpus that is used for training and evaluation. In this study, we propose BAlanced Script PROducer (BASPRO) system, which can automatically construct a phonetically balanced and rich set of Chinese sentences for collecting Mandarin Chinese speech data. First, we used pretrained natural language processing systems to extract ten-character candidate sentences from a large corpus of Chinese news texts. Then, we applied a genetic algorithm-based method to select 20 phonetically balanced sentence sets, each containing 20 sentences, from the candidate sentences. Using BASPRO, we obtained a recording script called TMNews, which contains 400 ten-character sentences. TMNews covers 84% of the syllables used in the real world. Moreover, the syllable distribution has 0.96 cosine similarity to the real-world syllable distribution. We converted the script into a speech corpus using two text-to-speech systems. Using the designed speech corpus, we tested the performances of speech enhancement (SE) and automatic speech recognition (ASR), which are one of the most important regression- and classification-based speech processing tasks, respectively. The experimental results show that the SE and ASR models trained on the designed speech corpus outperform their counterparts trained on a randomly composed speech corpus. [ABSTRACT FROM AUTHOR]

Presents an efficient spoken-access approach for both Chinese text and Mandarin speech information retrieval. Highlights include human-computer interaction via voice input, speech query recognition at the syllable level, automatic term suggestion, relevance feedback techniques, and experiments that show an improvement in the effectiveness of information retrieval via speech interaction. (Author/LRW)

In this paper, we consider the learning process of a probabilistic self-organizing map (PbSOM) as a model-based data clustering procedure that preserves the topological relationships between data clusters in a neural network. Based on this concept, we develop a coupling-likelihood mixture model for the PbSOM that extends the reference vectors in Kohonen's self-organizing map (SOM) to multivariate Gaussian distributions. We also derive three expectation--maximization (EM)-type algorithms, called the SOCEM, SOEM, and SODAEM algorithms, for learning the model (PbSOM) based on the maximum-likelihood criterion. SOCEM is derived by using the classification EM (CEM) algorithm to maximize the classification likelihood; SOEM is derived by using the EM algorithm to maximize the mixture likelihood; and SODAEM is a deterministic annealing (DA) variant of SOCEM and SOEM. Moreover, by shrinking the neighborhood size, SOCEM and SOEM can be interpreted, respectively, as DA variants of the CEM and EM algorithms for Gaussian modellbased clustering. The experimental results show that the proposed PbSOM learning algorithms achieve comparable data clustering performance to that of the deterministic annealing EM (DAEM) approach, while maintaining the topology-preserving property. Index Terms--Classification expectation--maximization (CEM) algorithm, deterministic annealing expectation--maximization (DAEM) algorithm, expectation--maximization (EM) algorithm, model-based clustering, probabilistic self-organizing map (PbSOM), self-organizing map (SOM).

Hotel housekeepers face multiple serious work-induced hazards that can cause occupational disabilities affecting their health. This study investigated the short-term impact of a foam roller exercise as an intervention to improve hotel housekeeper range of motion (ROM). Researchers conducted a quasi-experimental study among hotel housekeepers at two hotels. Five housekeepers at the first hotel participated in 30-minute per day group foam roller exercises during a six-week study period. Seven housekeepers at the second hotel served as a comparison group, not participating in the exercises but completing the range of motion measurements at the beginning and end of the study. Interviews were conducted among the experimental exercise group to obtain their personal feedback regarding the foam roller exercises. This study found significantly improved range of motion in the shoulders, hips, and wrists of the exercise group after six weeks of daily foam roller exercises. No significant changes in range of motion were found in the comparison group. Qualitative data collected from interviews with exercise participants revealed the following benefits of the group foam roller exercises: muscle relaxation, reduction of body pain, providing a feeling of overall wellness, enhancing energy, and improving team relationships. This study provides evidence that foam roller exercises may be an effective intervention to improve range of motion for hotel housekeepers and may mitigate their body pain induced by their cleaning tasks. Foam rollers are user-friendly and cost-effective and can be used by hotel housekeepers or workers involved in physically demanding jobs as recovery tools. [ABSTRACT FROM AUTHOR]

Females have smaller anterior cruciate ligaments (ACLs) than males and smaller ACLs have been associated with a greater risk of ACL injury. Overall body dimensions do not adequately explain these sex differences. This study examined the extent to which quadriceps muscle volume (VOLQUAD) positively predicts ACL volume (VOLACL) once sex and other body dimensions were accounted for. Physically active males (N = 10) and females (N = 10) were measured for height, weight, and body mass index (BMI). Three‐Tesla magnetic resonance images of their dominant and nondominant thigh and knee were then obtained to measure VOLACL, quadriceps, and hamstring muscle volumes, femoral notch width, and femoral notch width index. Separate three‐step regressions estimated associations between VOLQUAD and VOLACL (third step), after controlling for sex (first step) and one body dimension (second step). When controlling for sex and sex plus BMI, VOLHAM, notch width, or notch width index, VOLQUAD consistently exhibited a positive association with VOLACL in the dominant leg, nondominant leg, and leg‐averaged models (p < 0.05). Findings were inconsistent when controlling for sex and height (p = 0.038–0.102). Once VOLQUAD was included, only notch width and notch width index retained a statistically significant individual association with VOLACL (p < 0.01). Statement of Clinical Significance: The positive association between VOLQUAD and VOLACL suggests ACL size may in part be modifiable. Future studies are needed to determine the extent to which an appropriate training stimulus (focused on optimizing overall lower extremity muscle mass development) can positively impact ACL size and structure in young females. [ABSTRACT FROM AUTHOR]

Combined electric and acoustic stimulation (EAS) has demonstrated better speech recognition than conventional cochlear implant (CI) and yielded satisfactory performance under quiet conditions. However, when noise signals are involved, both the electric signal and the acoustic signal may be distorted, thereby resulting in poor recognition performance. To suppress noise effects, speech enhancement (SE) is a necessary unit in EAS devices. Recently, a time-domain speech enhancement algorithm based on the fully convolutional neural networks (FCN) with a short-time objective intelligibility (STOI)-based objective function (termed FCN(S) in short) has received increasing attention due to its simple structure and effectiveness of restoring clean speech signals from noisy counterparts. With evidence showing the benefits of FCN(S) for normal speech, this study sets out to assess its ability to improve the intelligibility of EAS simulated speech. Objective evaluations and listening tests were conducted to examine the performance of FCN(S) in improving the speech intelligibility of normal and vocoded speech in noisy environments. The experimental results show that, compared with the traditional minimum-mean square-error SE method and the deep denoising autoencoder SE method, FCN(S) can obtain better gain in the speech intelligibility for normal as well as vocoded speech. This study, being the first to evaluate deep learning SE approaches for EAS, confirms that FCN(S) is an effective SE approach that may potentially be integrated into an EAS processor to benefit users in noisy environments. [ABSTRACT FROM AUTHOR]

Background: Given the relatively high risk of contralateral anterior cruciate ligament (ACL) injury in patients with ACL reconstruction (ACLR), there is a need to understand intrinsic risk factors that may contribute to contralateral injury.Hypothesis: The ACLR group would have smaller ACL volume and a narrower femoral notch width than healthy individuals after accounting for relevant anthropometrics.Study Design: Cross-sectional study.Level Of Evidence: Level 3.Methods: Magnetic resonance imaging data of the left knee were obtained from uninjured (N = 11) and unilateral ACL-reconstructed (N = 10) active, female, collegiate-level recreational athletes. ACL volume was obtained from T2-weighted images. Femoral notch width and notch width index were measured from T1-weighted images. Independent-samples t tests examined differences in all measures between healthy and ACLR participants.Results: The ACLR group had a smaller notch width index (0.22 ± 0.02 vs 0.25 ± 0.01; P = 0.004; effect size, 1.41) and ACL volume (25.6 ± 4.0 vs 32.6 ± 8.2 mm3/(kg·m)-1; P = 0.025; effect size, 1.08) after normalizing by body size.Conclusion: Only after normalizing for relevant anthropometrics, the contralateral ACLR limb had smaller ACL size and narrower relative femoral notch size than healthy individuals. These findings suggest that risk factor studies of ACL size and femoral notch size should account for relevant body size when determining their association with contralateral ACL injury.Clinical Relevance: The present study shows that the method of the identified intrinsic risk factors for contralateral ACL injury could be used in future clinical screening settings. [ABSTRACT FROM AUTHOR]

Varying types of shots is a fundamental element in the language of film, commonly used by a visual storytelling director. The technique is often used in creating professional recordings of a live concert, but meanwhile may not be appropriately applied in audience recordings of the same event. Such variations could cause the task of classifying shots in concert videos, professional or amateur, very challenging. To achieve more reliable shot classification, we propose a novel probabilistic-based approach, named as coherent classification net (CC-Net), by addressing three crucial issues. First, we focus on learning more effective features by fusing the layer-wise outputs extracted from a deep convolutional neural network (CNN), pretrained on a large-scale data set for object recognition. Second, we introduce a frame-wise classification scheme, the error weighted deep cross-correlation model (EW-Deep-CCM), to boost the classification accuracy. Specifically, the deep neural network-based cross-correlation model (deep-CCM) is constructed to not only model the extracted feature hierarchies of CNN independently, but also relate the statistical dependencies of paired features from different layers. Then, a Bayesian error weighting scheme for a classifier combination is adopted to explore the contributions from individual Deep-CCM classifiers to enhance the accuracy of shot classification in each image frame. Third, we feed the frame-wise classification results to a linear-chain conditional random field module to refine the shot predictions by taking into account the global and temporal regularities. We provide extensive experimental results on a data set of live concert videos to demonstrate the advantage of the proposed CC-Net over existing popular fusion approaches for shot classification. [ABSTRACT FROM AUTHOR]

ABSTRACT: Determining the magnitude of quadriceps and hamstring muscle volume asymmetries in healthy individuals is a critical first step toward interpreting asymmetries as compensatory or abnormal in pathological populations. The purpose of this study was to determine the magnitude of whole and individual muscle volume asymmetries, quantified as right–left volume differences, for the quadriceps and hamstring muscles in a young and healthy population. Twenty‐one healthy individuals participated: Eleven females age = 22.6 ± 2.9 years and 10 males age = 23.2 ± 3.4 years. Whole muscle group and individual muscle volume asymmetries were quantified within the context of absolute measurement error using a 95% Limits of Agreement approach. Mean muscle asymmetries ranged from −3.0 to 6.0% for all individual and whole muscle groups. Whole muscle group 95% limits of agreements represented ±11.4% and ±8.8% volume asymmetries for the hamstrings and quadriceps, respectively. Individual muscle asymmetry 95% limits of agreements ranged from ∼ ± 11–13% for the vastii muscles while the biceps femoris short‐head (±33.5%), long‐head (±20.9%), and the rectus femoris (±21.4%) displayed the highest relative individual asymmetries. Individual muscle asymmetries exceeded absolute measurement error in 70% of all cases, with 26% of all cases exceeding 10% asymmetry. Although whole muscle group asymmetries appear to be near the 10% assumed clinical threshold of normality, the greater magnitude of individual muscle asymmetries highlights the subject‐ and muscle‐specific variability in volume asymmetry. Future research is warranted to determine if volume asymmetry thresholds exist that discriminate between healthy and pathological populations. Statement of Clinical Significance: Muscle volume asymmetries displayed in healthy individuals provide a reference for interpreting asymmetries in pathological populations. © 2017 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 36:963–970, 2018. [ABSTRACT FROM AUTHOR]

In this paper, we demonstrate a rotational actuator using a thermomagnetic-induced magnetic force interaction. The actuator consists of a magnetic rotary beam, stainless-steel bearing, mechanical frame, thermomagnetic Gadolinium sheets, and thermoelectric generators (TEGs). Experimental results show that applying a sequence of currents to the TEGs successfully produces sequential magnetic forces. Consequently, these sequential magnetic forces rotate the beam for revolutions. When applying a sequence set of currents of −0.5 and 1.3 A, the maximum rotation speed and maximum stall torque of the actuator is 3.81 rpm and $136.2~\mu $ Nm, respectively. Most importantly, the operating temperatures of other thermomagnetic (and electrothermal) actuators are usually high, but the operating temperature of our actuator is approximately room temperature (13 °C–27 °C). Therefore, our actuators have more practical applications. According to the above-mentioned features, we believe our actuator is an important alternative approach to developing future rotational actuators and motors. [ABSTRACT FROM AUTHOR]