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Wheelchair propulsion interventions typically teach manual wheelchair users to perform wheelchair propulsion biomechanics as recommended by the Clinical Practice Guidelines (CPG). Outcome measures for these interventions are primarily laboratory based. Discrepancies remain between manual wheelchair propulsion (MWP) in laboratory-based examinations and propulsion in the real-world. Current developments in machine learning (ML) allow for monitoring of MWP in the real world. In this study, we collected data from participants enrolled in two wheelchair propulsion interventions, then built an ML algorithm to distinguish CPG recommended MWP patterns from non-CPG-recommended patterns. Eight primary manual wheelchair users did not initially follow CPG recommendations but learned and performed CPG propulsion after the interventions. Participants each wore two inertial measurement units as they propelled their wheelchairs on a roller system, indoors overground, and outdoors. ML models were trained to classify propulsion patterns as following the CPG or not following the CPG. Video recordings were used for reference. For indoor detection, we found that a subject-independent model was able to achieve 85% accuracy. For outdoor detection, we found that the subject-independent model achieved 75.4% accuracy. These results provide further evidence that CPG and non-CPG-recommended MWP patterns can be predicted with wearable sensors using an ML algorithm.

Aims Both gefitinib and afatinib are epidermal growth factor tyrosine kinase inhibitors (EGFR-TKI) in the treatment of non-small cell lung cancer (NSCLC). It has been reported that gefitinib and afatinib could cause hepatotoxicity during the clinic treatment, therefore it is critical to investigate their hepatotoxicity systematically. In this study, zebrafish (Danio rerio) were used as model animals to compare the hepatotoxicity and their toxic mechanism. Main methods The zebrafish transgenic line [Tg (fabp10a: dsRed; ela3l:EGFP) was used in this study. After larvae developed at 3 days post fertilization (dpf), they were put into different concentrations of gefitinib and afatinib. At 6 dpf, the viability, liver area, fluorescence intensity, histopathology, apoptosis, transaminase reflecting liver function, the absorption of yolk sac, and the expression of relative genes were observed and analyzed respectively. Key findings Both gefitinib and afatinib could induce the larvae hepatotoxicity dose-dependently. Based on the liver morphology, histopathology, apoptosis and function assessments, gefitinib showed higher toxicity, causing more serious liver damage. Both gefitinib and afatinib caused abnormal expressions of genes related to endoplasmic reticulum stress (ERS) pathway and apoptosis. For example, jnk, perk, bip, chop, ire1, bid, caspase3 and caspase9 were up-regulated, while xbp1s, grp78, bcl-2/bax, and caspase8 were down-regulated. The hepatotoxicity difference of gefitinib and afatinib might be due to the different expression level of related genes.

Stamping processes remain crucial in manufacturing processes, therefore, diagnosing the condition of stamping tools is critical. One of the challenges in diagnosing stamping tool conditions is that traditionally, the tools need to be visually checked, and the production processes thus need to be halted. With the development of Industry 4.0, intelligent monitoring systems have been developed by using accelerometers and algorithms to diagnose the wear classification of stamping tools. Although several deep learning models such as the convolutional neural network (CNN), auto encoder (AE), and recurrent neural network (RNN) models have demonstrated promising results for classifying complex signals including accelerometer signals, the practicality of those methods are restricted due to the flexibility of adding new classes and low accuracy when faced to low numbers of samples per class. In this study, we applied deep metric learning (DML) methods to overcome these problems. DML involves extracting meaningful features using feature extraction modules to map inputs into embedding features. We compared the probability method, the contrastive method, and a triplet network to determine which method was most suitable for our case. The experimental results revealed that, compared with other models, a triplet network can be more effectively trained with limited training data. The triplet network demonstrated the best test results of the compared methods in the noised test data. Finally, when tested using unseen class, the triplet network and the probability method demonstrated similar results.

Students considering a masters in Finance Engineering or Artificial Intelligence in Finance are usually required to have an undergraduate background in science, technology, engineering, or mathematics (STEM). STEM students have a good capacity in mathematics and science, but they may not have studied financial theory. To facilitate the classroom teaching of the Capital Asset Pricing Model (CAPM) for STEM students, this paper seeks to expound on the essence of the theory starting at a two-asset framework. Adopting the concepts proposed by Merton (1972), this paper accomplishes the derivation by virtue of basic mathematical tools such as linear algebra, geometry, and statistics except for calculus. We show that the major aspects of Merton’s derivation of the CAPM for a universe of N assets may also be obtained in a two-asset world. Through the methods of this article, students will learn the in-depth theory of CAPM and its hands-on empirical tool. For example, students will realize that even if investors specify different threshold rewards, their different CAPMs will yield identical pricing for assets and portfolios.

The Wnt/Frizzled signaling pathway participates in many inflammation-linked diseases. However, the inflammatory response mediated by the Wnt/Frizzled signaling pathway in experimental subarachnoid hemorrhage has not been thoroughly investigated. Consequently, in this study, we examined the potential role of the Wnt/Frizzled signaling pathway in early brain injury in rat models of subarachnoid hemorrhage. Simultaneously, possible neuroprotective mechanisms were also investigated. Experimental subarachnoid hemorrhage rat models were induced by injecting autologous blood into the prechiasmatic cistern. Experiment 1 was designed to examine expression of the Wnt/Frizzled signaling pathway in early brain injury induced by subarachnoid hemorrhage. In total, 42 adult rats were divided into sham (injection of equivalent volume of saline), 6-, 12-, 24-, 48-, 72-hour, and 1-week subarachnoid hemorrhage groups. Experiment 2 was designed to examine neuroprotective mechanisms of the Wnt/Frizzled signaling pathway in early brain injury induced by subarachnoid hemorrhage. Rats were treated with recombinant human Wnt1 (rhwnt1), small interfering Wnt1 (siwnt1) RNA, and monoclonal antibody of Frizzled1 (anti-Frizzled1) at 48 hours after subarachnoid hemorrhage. Expression levels of Wnt1, Frizzled1, β-catenin, peroxisome proliferator-activated receptor-γ, CD36, and active nuclear factor-κB were examined by western blot assay and immunofluorescence staining. Microglia type conversion and inflammatory cytokine levels in brain tissue were examined by immunofluorescence staining and enzyme-linked immunosorbent assay. Our results show that compared with the sham group, expression levels of Wnt1, Frizzled1, and β-catenin were low and reduced to a minimum at 48 hours, gradually returning to baseline at 1 week after subarachnoid hemorrhage. rhwnt1 treatment markedly increased Wnt1 expression and alleviated subarachnoid hemorrhage-induced early brain injury (within 72 hours), including cortical cell apoptosis, brain edema, and neurobehavioral deficits, accompanied by increasing protein levels of β-catenin, CD36, and peroxisome proliferator-activated receptor-γ and decreasing protein levels of nuclear factor-κB. Of note, rhwnt1 promoted M2-type microglia conversion and inhibited release of inflammatory cytokines (interleukin-1β, interleukin-6, and tumor necrosis factor-α). In contrast, siwnt1 RNA and anti-Frizzled1 treatment both resulted in an opposite effect. In conclusion, the Wnt/Frizzled1 signaling pathway may participate in subarachnoid hemorrhage-induced early brain injury via inhibiting the inflammatory response, including regulating microglia type conversion and decreasing inflammatory cytokine release. The study was approved by the Animal Ethics Committee of Anhui Medical University and First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China (approval No. LLSC-20180202) in May 2017.

Yin-gang Wu,1,2 Yingjiu Chao,1 Ge Gao,1 Dejun Bao,1 Yongfei Dong,1 Xiangpin Wei,1 Chaoshi Niu1,2 1Department of Neurosurgery, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui, 230001, People’s Republic of China; 2Brain Function and Brain Disease Anhui Provincial Key Laboratory, Hefei, Anhui, 230001, People’s Republic of ChinaCorrespondence: Chaoshi NiuDepartment of Neurosurgery, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui, 230001, People’s Republic of ChinaTel +86 18963788788Email niuchaoshi@126.comPurpose: Posttraumatic cerebral infarction (PTCI) is a common and relatively serious complication of traumatic brain injury (TBI) without a clear etiology. Evaluating risk factors in advance is particularly important to predict and avoid the occurrence of PTCI.Patients and Methods: We retrospectively analyzed 297 patients with moderate to severe TBI admitted to the Department of Neurosurgery in our hospital from January 2019 to September 2020 and evaluated the effects of various factors such as age, sex, admission Glasgow Coma Scale (GCS), skull base fracture, subarachnoid hemorrhage (SAH), brain herniation, hypotensive shock, and decompressive craniectomy on the incidence of PTCI. We also performed a multivariate logistics regression analysis on the relevant factors identified and evaluated the diagnostic value of each risk factor in advance by receiver operating characteristic (ROC) analyses.Results: Among the patients, 32 (10.77%) suffered PTCI. The incidence rates of PTCI in those with GCS scores of 3– 8 and 9– 12 were 15.87% (30/189) and 1.85% (2/108), respectively, while the rates were 18.84% (13/69), 15.03% (29/193), 18.57% (13/70), and 20.59% (14/68) in those with skull base fractures, traumatic SAH, brain herniation, and hypotensive shock, respectively, and 14.38% (23/160) in those who underwent decompressive craniectomy. These differences in PTCI incidence were statistically significant. However, the differences in PTCI incidence caused by patient age and sex were not statistically significant.Conclusion: Low GCS score, skull base fractures, traumatic SAH, brain herniation, hypotensive shock, and decompressive craniectomy are risk factors for the occurrence of PTCI, while age and sex are not significantly correlated with the occurrence of PTCI.Keywords: moderate or severe traumatic brain injury, posttraumatic cerebral infarction, risk factor

Academic research has shed light on the empirical relationships among a firm&rsquo, s corporate social responsibility (CSR), corporate social irresponsibility (CSiR) and firm performance and on the firm&rsquo, s customer satisfaction&ndash, firm performance relationship in different markets. However, little notice has been taken of whether the coexistence of corporate social responsibility, corporate social irresponsibility and customer satisfaction has an interactive effect on firm performance. This study aims to examine the effects of their interaction on firm performance from an investment perspective. Using unbalanced panel regression to test a sample of publicly traded firms from the United States, this study finds that, in general, firms with higher customer satisfaction earn positive changes in abnormal stock returns. For firms that engage in CSR, CSR positively affects corporate performance, whereas firms&rsquo, social irresponsibility activities reduce firms&rsquo, financial performance. All else equal, a positive interactive effect of CSiR and customer satisfaction on stock return was observed. The results reveal that high customer satisfaction can alleviate the negative effect of corporate social irresponsibility on firms&rsquo, financial performance. Our findings will help management executives and investors to understand that the negative effect of a firm&rsquo, s unforeseen events on firm performance can be weakened by increasing customer satisfaction.

A shift in dengue cases toward the adult population, accompanied by an increased risk of severe cases of dengue in the elderly, has created an important emerging issue in the past decade. To understand the level of past DENV infection among older adults after a large dengue outbreak occurred in southern Taiwan in 2015, we screened 1498 and 2603 serum samples from healthy residents aged ≥ 40 years in Kaohsiung City and Tainan City, respectively, to assess the seroprevalence of anti-DENV IgG in 2016. Seropositive samples were verified to exclude cross-reaction from Japanese encephalitis virus (JEV), using DENV/JEV-NS1 indirect IgG ELISA. We further identified viral serotypes and secondary DENV infections among positive samples in the two cities. The overall age-standardized seroprevalence of DENV-IgG among participants was 25.77% in Kaohsiung and 11.40% in Tainan, and the seroprevalence was significantly higher in older age groups of both cities. Although the percentages of secondary DENV infection in Kaohsiung and Tainan were very similar (43.09% and 44.76%, respectively), DENV-1 and DENV-2 spanned a wider age range in Kaohsiung, whereas DENV-2 was dominant in Tainan. As very few studies have obtained the serostatus of DENV infection in older adults and the elderly, this study highlights the need for further investigation into antibody status, as well as the safety and efficacy of dengue vaccination in these older populations., Author summary The dengue virus (DENV) has rapidly spread out in tropical and sub-tropical regions. To measure the level of past DENV infections in the older population, we conducted a post-outbreak serosurvey in 2016 among a total of 4,101 older and elderly adults in Kaohsiung and Tainan cities in southern Taiwan. Our results showed district- and city-level differences in the overall seroprevalence of anti-DENV IgG antibody, increased seroprevalence with age, heterogeneous distributions of DENV serotypes, and similar percentages of secondary DENV infection in both metropolises, closely matching past histories of dengue outbreaks. This study demonstrates the importance of monitoring individual’s antibody status among the older and elderly population and highlights the need to investigate the safety and efficacy of dengue vaccination in these populations in the future.

Nanotechnologies have been regarded as general-purpose, and interdisciplinary technology converged with different implications of technologies. This paper aims to explore the global Nano collaboration of research and development (R&D) by patent analysis to realize the sustainable development of nanotechnology and investigate the influence of global R&D collaboration on patent quality. The primary findings indicated that the number of issued patents grew sharply since 2002, and the major collaborative fields in terms of nanotechnology are nanoelectronic and nanomaterials. Finally, the collaboration among star assigners, global partnership, and the indicator of patent centrality had a positive impact on patent quality, except that university-industry collaboration did not show a significant effect on patent quality. One part of the reason is that industries have not yet fully recognised nanotechnology opportunities with a risk-averse attitude toward market uncertainties. Overall, the relationship of global R&D collaboration is an essential factor in promoting the sustainable development of the patent quality of nanotechnology. An effective patenting strategy and high-quality application of nanotechnology R&D could secure protection for innovations to reinforce core competitiveness in the business.

We demonstrate the photo-thermal (PT) spectroscopy of a 1.53-μm acetylene line using an optical heterodyne interferometer (OHI). A double-pass acousto-optic modulator is used as the frequency shifter and beam splitter in the OHI. The PT excitation beam overlaps with the probe beam of OHI, and the PT-induced phase change on the probe beam is detected by the OHI. Due to the nearly equal path length of the OHI scheme, we can observe the PT signal without using feedback control to maintain the path difference of the OHI arms.

Heat-assisted magnetic recording (HAMR) is being developed as the next generation magnetic recording technology. Critical components of this technology, such as the plasmonic near-field transducer and high anisotropy granular FePt media, as well as recording demonstrations and fully integrated drives have been reported. One of the remaining ongoing challenges of magnetic recording in general and HAMR in particular has been the demonstration of high linear density recording, approaching the grain-size (GS) limit of the recording media, and a clear pathway to smaller GSs while maintaining good magnetic properties and distributions. This paper will demonstrate the extensibility of FePt-based media down to the 5 nm center-to-center range. A linear recording density of 3000 kilobits per inch (kbpi), or a bit length of 8.5 nm, approaching the GS limit of this media, has been demonstrated on recording media with a slightly larger GS of 7 nm center-to-center, and using an HAMR head with high thermal gradient >10 K/nm. Key parameters of the media include the microstructure, the thermal design and magnetic properties, most importantly the tradeoff between achievable GS, media moment–thickness product, Mrt, and the distributions of the magnetic switching field and the Curie temperature. Further optimizing the composition, growth, and architecture of the media stack to achieve all the prerequisite magnetic and thermal properties for high signal-to-noise ratios in the smallest demonstrated GS media allows linear recording densities of up to 4000 kbpi, and areal densities in the 3–4 tera-bits-per-square-inch range can be extrapolated based on geometrical scaling.

Microwave Assisted Magnetic Recording (MAMR) is a type of energy assisted recording technology that uses microwaves to assist in the recording process. This allows for the use of high anisotropy media to maintain good thermal stability at high areal densities [1]. In MAMR, a spin torque oscillator (STO) is placed between the main pole and trailing shield to generate a magnetic field at microwave frequencies. The magnetic recording trilemma [2] is overcome by reducing the coercive field of the media via this microwave field, thereby aiding in the switching of media grains. Appropriate media stack configurations for MAMR and STO optimization have been investigated by both analytical theory and micromagnetic simulation [3], [4], [5]. In this paper, MAMR performance is evaluated on a reference design using our MAMR micro-magnetic model and the results are reported using EWSNR metrics [6]. In this study, we compare performance metrics for MAMR with other recording technologies such as Perpendicular Magnetic Recording (PMR) and Heat Assisted Magnetic Recording (HAMR). Recording media dynamics are modeled using the Landau-Lifshitz-Gilbert (LLG) equation for PMR and MAMR, and utilizing the renormalized LLG method for HAMR [7]. The DC magnetic write field is a current generation PMR writer design with 55 nm physical pole width and 1.0 T peak field strength. The STO stack has an optimized geometry that applies a 3D circularly polarized AC field to the media. STO field strength (∼0.1Hk) and oscillating frequency (∼35GHz) are determined by the magnetic properties of the field generation layer (FGL) and the magnitude of the injected spin current. The magnetic head to media spacing (HMS) is fixed at 6.0 nm and head velocity is modeled to be 20 m/s. For MAMR, single layer media with varying anisotropy are considered. The PMR ECC multilayer media model, which is calibrated based on current PMR products, contains multiple magnetic layers and non-magnetic break layers that provide optimal exchange coupling. The HAMR media is a single layer L1 0 FePt media with a Curie temperature distribution of 3% and anisotropy field distribution of 10%. The down track thermal gradient used in the HAMR model is around 8K/nm, which is consistent with common near field transducer designs. The average media grain size is around 8.0 nm with 17% grain size distribution. A magnetoresistive reader with 30 nm width is used for obtaining the play back signal. Magnetic information is encoded using pseudo random bit sequences (PRBS), which mimic real user data. Figure 1 shows a comparison between PMR, HAMR and MAMR with thick free layer designs in terms of common performance metrics. Ensemble waveform analysis is used to calculate the total spatial SNR, the breakdown between transition and remanence SNR contributions, and the channel bit density (CBD) [6]. Bit error rate (BER) is calculated using a pattern dependent Viterbi detector [8]. The use of an NFT in HAMR allows the recording of much narrower tracks than PMR, with similar CBD and reasonable SNR and BER. In general, MAMR exhibits a large CBD, which may be related to intersymbol interference and track edge erasure caused by the demagnetization field. This high CBD results in much worse BER than both HAMR and PMR at all track width and linear density combinations considered. For the same ADC (shown in the last two table items in figure 1), SNR and BER are much better when the linear density is higher and the track width is larger. Since track edge demagnetization effects seem to have such a large effect in MAMR, this data suggests MAMR should aim to increase ADC via higher linear density and lower track density. For thick free layers, multi domains and multi-scattering contributions to electron’s propagation can greatly deteriorate STO performance. Therefore, SNR versus recording media Hk for MAMR with thin free layer designs below 15 nm and STO width of 40 nm is shown in Figure 2. The figure suggests an optimal for MAMR media of around 25 kOe. MAMR SNR degradation at 20 kOe is due to erasure effects for low Hk material [9]. For high anisotropy media ∼30 kOe, the transition SNR is reasonable (around 12 dB), but remanence noise is high, causing a 2 dB loss in total SNR.

The aim of this investigation was to compare the diagnostic performance of radiographers and deep learning algorithms in pulmonary nodule/mass detection on chest radiograph.A test set of 100 chest radiographs containing 53 cases with no pathology (normal) and 47 abnormal cases (pulmonary nodules/masses) independently interpreted by 6 trained radiographers and deep learning algorithems in a random order. The diagnostic performances of both deep learning algorithms and trained radiographers for pulmonary nodules/masses detection were compared.QUIBIM Chest X-ray Classifier, a deep learning through mass algorithm that performs superiorly to practicing radiographers in the detection of pulmonary nodules/masses (AUCMass: 0.916 vs AUCTrained radiographer: 0.778, P

Aims Gastric cancer (GC) is one of the most common malignant tumors in the world. Anti-angiogenic therapy is a useful strategy for the treatment of advanced GC. This study was aimed to systemically compare the anti-angiogenesis, anti-cancer efficacy, as well as the safety of four known anti-angiogenic drugs, namely ramucirumab, apatinib, regorafenib and cabozantinib. Main methods Anti-angiogenic effect was evaluated for the intersegmental vessels (ISVs) and subintestinal veins (SIVs) formation in the Tg (fli-1: EGFP) zebrafish embryos. Anti-cancer efficacy was tested for the in vivo cell proliferation in cell line derived tumor xenograft (CDX) model based on Tg (fli-1: EGFP) zebrafish embryos. Key findings All four drugs exhibited anti-angiogenic abilities and tumor inhibition effects in fli-1: EGFP transgenic zebrafish. Using zebrafish xenografted model, we found that effectiveness of ramucirumab in anti-GC-proliferation is better than apatinib, regorafenib and cabozantinib. The combination of anti-angiogenic drugs and cisplatin showed no significant benefit in tumors. Meanwhile, toxicity assay showed that all tested anti-angiogenic drugs could cause cardiovascular-related side effects. The therapeutic index (LD50/ED50) of cabozantinib is higher than apatinib and regorafenib, suggesting a potential as an anti-GC drug. Significance The comparison of GC-related anti-angiogenic drugs was first reported. It was found that cabozantinib had a potential as an anti-GC drug. Zebrafish model was an ideal animal model for the research of anti-angiogenic behaviors.

Duckiepond is an education and research development environment that includes software systems, educational materials, and of a fleet of autonomous surface vehicles Duckieboat. Duckieboats are designed to be easily reproducible with parts from a 3D printer and other commercially available parts, with flexible software that leverages several open source packages. The Duckiepond environment is modeled after Duckietown and AI Driving Olympics environments: Duckieboats rely only on one monocular camera, IMU, and GPS, and perform all ML processing using onboard embedded computers. Duckiepond coordinates commonly used middlewares (ROS and MOOS) and containerized software packages in Docker, making it easy to deploy. The combination of learning-based methods together with classic methods enables important maritime missions: track and trail, navigation, and coordinate among Duckieboats to avoid collisions. Duckieboats have been operating in a man-made lake, reservoir and river environments. All software, hardware, and educational materials are openly available (https://robotx-nctu.github.io/duckiepond), with the goal of supporting research and education communities across related domains.

Animal models reveal that deafferenting forelimb injuries precipitate reorganization in both contralateral and ipsilateral somatosensory cortices. The functional significance and duration of these effects are unknown, and it is unclear whether they also occur in injured humans. We delivered cutaneous stimulation during functional magnetic resonance imaging (fMRI) to map the sensory cortical representation of the intact hand and lower face in a group of chronic, unilateral, upper extremity amputees (N = 19) and healthy matched controls (N = 29). Amputees exhibited greater activity than controls within the deafferented former sensory hand territory (S1f) during stimulation of the intact hand, but not of the lower face. Despite this cortical reorganization, amputees did not differ from controls in tactile acuity on their intact hands. S1f responses during hand stimulation were unrelated to tactile acuity, pain, prosthesis usage, or time since amputation. These effects appeared specific to the deafferented somatosensory modality, as fMRI visual mapping paradigm failed to detect any differences between groups. We conclude that S1f becomes responsive to cutaneous stimulation of the intact hand of amputees, and that this modality-specific reorganizational change persists for many years, if not indefinitely. The functional relevance of these changes, if any, remains unknown.

This paper presents requirements to DeepLinQ and its architecture. DeepLinQ proposes a multi-layer blockchain architecture to improve flexibility, accountability, and scalability through on-demand queries, proxy appointment, subgroup signatures, granular access control, and smart contracts in order to support privacy-preserving distributed data sharing. In this data-driven AI era where big data is the prerequisite for training an effective deep learning model, DeepLinQ provides a trusted infrastructure to enable training data collection in a privacy-preserved way. This paper uses healthcare data sharing as an application example to illustrate key properties and design of DeepLinQ.

Measuring activities of daily living (ADLs) using wearable technologies may offer higher precision and granularity than the current clinical assessments for patients after stroke. This study aimed to develop and determine the accuracy of detecting different ADLs using machine-learning (ML) algorithms and wearable sensors. Eleven post-stroke patients participated in this pilot study at an ADL Simulation Lab across two study visits. We collected blocks of repeated activity (“atomic” activity) performance data to train our ML algorithms during one visit. We evaluated our ML algorithms using independent semi-naturalistic activity data collected at a separate session. We tested Decision Tree, Random Forest, Support Vector Machine (SVM), and eXtreme Gradient Boosting (XGBoost) for model development. XGBoost was the best classification model. We achieved 82% accuracy based on ten ADL tasks. With a model including seven tasks, accuracy improved to 90%. ADL tasks included chopping food, vacuuming, sweeping, spreading jam or butter, folding laundry, eating, brushing teeth, taking off/putting on a shirt, wiping a cupboard, and buttoning a shirt. Results provide preliminary evidence that ADL functioning can be predicted with adequate accuracy using wearable sensors and ML. The use of external validation (independent training and testing data sets) and semi-naturalistic testing data is a major strength of the study and a step closer to the long-term goal of ADL monitoring in real-world settings. Further investigation is needed to improve the ADL prediction accuracy, increase the number of tasks monitored, and test the model outside of a laboratory setting., United States Department of Health & Human Services 90BISA0015, United States Department of Health & Human Services National Institutes of Health (NIH) - USA K01HD095388

This study aimed to explore the effect of free perforating branch flap on the reconstruction of huge soft-tissue defects on the scalp and face.Sixteen cases of huge soft-tissue defects on the scalp and face were reconstructed by nine latissimus dorsi-free perforator flaps and seven anterolateral thigh-free perforator flaps. The defects area was from 12 cm× 7 cm to 20 cm × 11 cm, while the flaps area was from 14 cm × 8 cm to 23 cm × 12 cm. The survival, planeness, chromatic aberration, radiotherapy toleration of flap and the function, scar of donor site were observed postoperatively.All of the flaps were survived completely, and 15 cases presented for primary reconstruction; one underwent secondary reconstruction. One of the patients died one-year postoperatively due to intracranial tumor recurrence and the others had no recurrence. All of the flaps showed perfect shape and appropriate thickness. No roentgen ulcer was observed except for some extent of chromatic aberration. The donor-site scar was larvaceous and the function was good.This study indicated that the latissimus dorsi-free perforator flap or anterolateral thigh-free perforator flap was an ideal choice for the reconstruction of defects on the scalp and face.

In this letter, we demonstrate high-performance AlGaN/GaN Schottky barrier diodes (SBDs) on Si substrate with a recessed-anode structure for reduced turn-on voltage $V_{\mathrm {ON}}$ . The impact of the surface roughness after the recessed-anode formation on device characteristics is investigated. An improved surface condition can reduce the leakage current and enhance the breakdown voltage simultaneously. A low turn-on voltage of only 0.73 V can be obtained with a 50-nm recess depth. In addition, the different lengths of Schottky extension acting like a field plate are investigated. A high reverse breakdown voltage of 2070 V and a low specific ON-resistance of 3.8 $\text{m}\Omega \cdot \textrm {cm}^{2}$ yield an excellent Baliga’s figure of merit of 1127 MW/cm2, which can be attributed to the low surface roughness of only 0.6 nm and also a proper Schottky extension of 2 $\mu \text{m}$ to alleviate the peak electric field intensity in the SBDs.

We investigate whether the funding liquidity risk to institutional investors influences the negative relation between expected returns and variance (the ‘‘Low-volatility anomaly’’). With the Taiwan stock market as a setting, we implement a multivariate Markov switching model and use the funding liquidity risk to model the time-varying transition probabilities of the regime-switching process to capture changes in the funding liquidity risk regime. Our evidence documents that the low-volatility anomaly is most pronounced when there is high funding liquidity risk. When there is low funding liquidity risk, however, the low-volatility anomaly has a significant reversal. These results imply that the increased funding liquidity risk due to financial shock transmitted from parent banks is associated with higher selling pressure on institutional investors’ high-volatility stocks, leading to the low-volatility anomaly.

In this study, Si implantation was used to improve the interface properties of SiC/SiO2 in 4H-SiC lateral MOSFETs. In lateral n-channel MOSFETs, a 4%–6% improvement on the linear and saturation current was observed with Si implantation. From high/low-frequency CV measurements, the Si-implanted n-type MOS capacitor showed a 20% lower interface state density than the non-implanted ones at an energy level of E C − E = 0.2 eV, without degrading oxide integrity. Lateral p-channel MOSFETs, on the other hand, showed a 36.5% reduction in the linear current and a 16.6% reduction in the saturation current with Si implantation. Furthermore, the temperature coefficients of lateral and vertical MOSFETs implanted by Si were monitored up to 175 °C. The temperature coefficients of the Si-implanted n-channel and p-channel lateral MOSFETs were nearly identical to those of their non-implanted counterparts.

Cutting tool machining quality and accuracy calibration has always been an important indicator of the performance of machine tools, machine tool testing technology is particularly the key point. In this paper, an optical based non-contact five-axis machine tool calibration system with IOT feature is presented. It can be obtained once the three-dimensional detection signals, combined with embedded systems for data calculation and communication using Wi-Fi wireless. Test hardware includes two sets of laser light source, two sets of photoelectric sensors and spherical lens and DSP processor. The proposed calibration IOT system has simple for setup, low cost, high precision features for calibration five-axis motor and static error.

Magnetic hard disk drives (HDDs) store over 90% of the world’s digital data enabling the internet and economical access to data to power everything from social media to self-driving cars. Heat assisted magnetic recording (HAMR) is being developed as the next recording system for HDDs. HAMR will bring profound changes to the HDD components and architecture, incorporating laser diodes in an innovative plasmonic light delivery system into the recording heads, and novel nano-magnetic materials and layer architectures in the recording media [1]. Seagate demonstrated the promise of HAMR with a 1 -2 Tb/in2 areal density demonstration [2, 3] and the subsequent demonstration of a fully functional drive with more than 1000 write power-on hours [4, 5]. The significant progresses have been enabled by breakthroughs in media and head technology together with drive integration. With continuing development efforts in reliability and data density HAMR will serve the demand for economical hard disk drive storage solutions for the world’s ever growing data. As announced in a recent blog, Seagate is now shipping HAMR units to select customers for integration tests, and will start shipping commercial HAMR products to key customers by the end of 2018 [6]. This paper will cover the key enablers for HAMR technology to support both high areal density and linear density, which will be critical for bringing a new “S” curve for the magnetic recording industry. It will also be discussed about the challenges and breakthroughs in fundamental magnetic properties for the recording layer and near field optical transducers, to support the extension of HAMR to around 4-5 Tbit/in2.

Heat-assisted magnetic recording (HAMR) is being developed as the next generation magnetic recording technology. Critical components of this technology, such as plasmonic near-field transducer (NFT) and high anisotropy granular FePt media, as well as the performance and reliability of fully integrated drives have been reported. This paper will focus on the progress and challenges of HAMR media, including microstructure and thermal design as well as the testing and characterization at high field and high temperature. Due to the importance of the Curie temperature distribution, $\sigma T_{C}$ , for HAMR, we present a newly developed temperature-dependent complex ac susceptibility method to extract $\sigma T_{C}$ for HAMR media. Such novel magnetic characterization methods have been used in combination with other high field magnetic metrology and spin-stand recording to provide feedback for continuous improvements of HAMR media. Together with NFT and write head design, the thermal design, $\sigma T_{C}$ , and microstructure of the media are key factors to reduce the transition jitter below 2 nm as demonstrated in a previously reported 1 Tb/in2 HAMR demonstration. Here, we report the further improvements by significantly enabling higher linear density (>2500 kfci) HAMR and steady progress in areal density to 1.402 Tb/in2.

Knee osteoarthritis (OA) often leads to altered balance control, joint motion and loading patterns during gait. Acupuncture has been proven to be effective in pain relief but its effects on inter-joint load-sharing for body balance have not been reported. The current study bridged the gap by quantifying the immediate effects of acupuncture on the inter-joint and inter-limb load-sharing in patients with knee OA during level walking in terms of the total support moment (Ms) and the contribution of individual joints to the total support moment. Gait analysis was performed on fifteen healthy controls and on fifteen patients with mild to moderate bilateral medial knee OA. After acupuncture treatment the patients with bilateral knee OA walked with significantly increased speed ([Formula: see text]), and were able to resist greater and closer-to-normal knee flexion moments ([Formula: see text]). They also changed the inter-joint sharing of the support moments with increased knee ([Formula: see text]) contributions, but reduced hip contributions ([Formula: see text]) to the sagittal Ms during single-limb support. They showed an asymmetric inter-limb load-sharing similar to the normal controls, with increased sharing of the time integral of both the sagittal and frontal whole body support moment by the leading limb during double-limb support ([Formula: see text]). The altered intra- and inter-limb contributions to the demand of supporting the body during gait suggests that acupuncture treatment led to immediate changes in the control strategy toward a normal pattern. However, the effects of these changes on the progression of the disease in the long term would require further investigation.

This study modifies the risk tolerance parameter in cumulative prospect theory (CPT) as a risk tolerance function of advertising to explain investors’ behaviors under uncertainty environment. Our model indicates that advertising would influence investors’ redemptions because advertising reduce the speed of CPT investors’ diminishing marginal sensitivity to their monetary outcomes when moving away from the reference point. Using mutual fund cash flows data set, this study finds that advertising changes the pattern of existing asymmetric redemption-performance relation, showing that investors are less willing to sell winning funds with high fund family advertising than those with low fund family advertising, and are more reluctant to redeem losing mutual funds with high fund family advertising than those with low fund family advertising.

Objective To explore the safety and efficacy of frameless stereotactic brain biopsy. Methods Diagnostic accuracy was calculated by comparing biopsy diagnosis with de?nitive pathology in 62 patients who underwent frameless stereotactic brain biopsy between January 2008 and December 2010 in Xiamen University Southeast Hospital. Preoperative characteristics and histological diagnosis were reviewed and then information was analysed to identify factors associated with the biopsy not yielding a diagnosis and complications. Results Diagnostic yield was 93.5%. No differences were found between pathological diagnosis and frozen pathological diagnosis. The most common lesions were astrocytic lesions, included 16 cases of low-grade glioma and 12 cases of malignant glioma. Remote hemorrhage, metastasis, and lymphoma were following in incidence. Multiple brain lesions were found in 17 cases (27.4%). Eleven cases were frontal lesions (17.7%), 8 were frontotemporal (12.9%), 6 were frontoparietal (9.7%), and 5 each were temporal, parietal, and parietotemporal lesions (8.1%). Postoperative complications occurred in 21.0% of the patients after biopsies, including 10 haemorrhages (16.1%) and 3 temporary neurological deficits (1 epilepsy, 1 headache, and 1 partial hemiparesis). No patient required operation for hematoma evacuation. Conclusion Frameless stereotactic biopsy is an effective and safe technique for histologic diagnosis of brain lesions, particularly for multifocal and frontal lesions.

The demand for greater storage capacity is fueled by current explosive usage of social media, cloud computing, and high-definition film and recording businesses.

In visual cryptographic scheme (VCS), each secret pixel is expanded to m subpixels in shadow images to encrypt a secret image. Apparently, we should put these m subpixels as a rectangle such that the blocks can be arranged compactly with each other. However, if the aspect ratio is viewed as important information of the secret image, the distortion occurs at the case that m is not a square. An aspect ratio invariant VCS (ARIVCS) was accordingly proposed to address the arrangement of subpixels. However, the existing ARIVCSs relied on adding dummy subpixels to the shadow images. In addition, their method needs a mapping pattern that reduces the number of dummy subpixels, but how to design a mapping pattern is a huge challenge. In this paper, we propose an easy solution to construct ARIVCS by image filtering and resizing.

The aim of this follow-up study was to examine factors related to a suicide attempt within 3 months of a prior attempt. Participants were recruited from a suicide-prevention center. Of 96 suicidal individuals who had participated in the baseline study, only 51 completed all measures at follow-up assessment. Study results showed that suicidal individuals who reattempted suicide during the first 3 months of follow-up care exhibited lower mean scores on all four domains of the brief version of the World Health Organization Quality-of-Life Instrument at follow-up assessment than at baseline. In contrast, individuals who did not reattempt suicide had higher quality-of-life scores across all domains between baseline and 3 months. The reattempt and no-reattempt groups differed significantly in the physical health and environmental domains. These results can be used by nurses to develop their abilities to recognize and prevent suicide reattempts in high-risk groups.

Embedded systems with digital signal processor (DSP) become more and more popular for the increasing requirement of supercomputing these days. Efficient development of DSP serials used in embedded systems shortens the embedded system R&D cycle. Functional verification is one of the most complex and expensive tasks during DSP serials design process. A random test platform which is urged for DSP serials verification is proposed in this paper. The platform can automatically generate the random test program. The platform also realized the recording and checking of simulation results, which make the verification more effective. In order to improve the efficiency of DSP verification, a testing experience library has been generated through the testing procedure. This platform can be transplanted for different DSP models easily by updating few modules. According to the verification results, this platform has satisfactory coverage of DSP models.

Past behavioural research has provided evidence that fund investors have the ability to predict fund performance; this is called the smart money effect. In this study we examine whether the smart money effect exists in the Taiwanese mutual fund market. Specifically, we investigate whether the smart money effect appears across UP and DOWN markets and whether this effect persists over time. Consistent with the literature, we find that the smart money effect exists over our sample period. Moreover, after categorizing the market states as either UP or DOWN markets, our evidence shows a significant smart money effect only following DOWN markets but not following UP markets. According to behavioural theories, bad market states evoke negative affective states in investors, so negatively affected investors may rely less on the use of heuristics and become more careful and logical in their investment decisions. This paper infers that the existence of a smart money effect after DOWN markets occurs because investors in negative emotional states are likely to use more detailed information processing in their decision making.

In this paper, the technique of image noise cancellation is presented by employing cellular neural networks (CNN) and linear matrix inequality (LMI). The main objective is to obtain the templates of CNN by using a corrupted image and a corresponding desired image. A criterion for the uniqueness and global asymptotic stability of the equilibrium point of CNN is presented based on the Lyapunov stability theorem (i.e., the feedback template "A" of CNN is solved at this step), and the input template "B" of CNN is designed to achieve desirable output by using the property of saturation nonlinearity of CNN. It is shown that the problem of image noise cancellation can be characterized in terms of LMIs. The simulation results indicate that the proposed method is useful for practical application.

This study tested the hypothesis that patients with mild and severe medial knee osteoarthritis (OA) adopt different compensatory gait patterns to unload the deseased knee, in not only the frontal plane but also the sagittal plane. Fifteen patients with mild and 15 with severe bilateral medial knee OA, and 15 normal controls walked while the kinematic and kinetic data were measured. Compared to the normal group, both OA groups had significantly greater pelvic anterior tilt, swing-pelvis list, smaller standing knee abduction, as well as smaller standing hip flexor and knee extensor moments during stance. The severe group also had greater hip abduction, knee extension and ankle plantarflexion. The mild group successfully reduced the extensor moment and maintained normal abductor moment at the diseased knee mainly through listing and anterior tilting the pelvis. With extra compensatory changes at other joints and increased hip abductor moment, the severe group successfully reduced the knee extensor moment but failed to reduce the abductor moment. These results suggest that, apart from training of the knee muscles, training of the hip muscles and pelvic control are essential in the rehabilitative intervention of patients with knee OA, especially for more severe patients.

In this paper, a finite impulse response (FIR) equalizer for nonlinear discrete-time channels is designed by employing a hybrid genetic algorithm (GA) and linear matrix inequality (LMI) approach from an H∞ perspective. The GA technique is utilized to linearize the nonlinear channel model, and the approximate error can be viewed as a state uncertainty. Then, the design of the FIR equalizer is transformed into LMIs, and the coefficients of the FIR equalizer can be obtained by solving an LMI optimization problem. Finally, numerical examples are included to illustrate the effectiveness of the proposed methodology.

The MOSFET backscattering theory relies on a so-called "kB T" layer. In this letter, we adopt two different approaches to examine the temperature dependencies of the width spanned by this critical zone. First of all, a 55-nm channel length n-MOSFET is extensively characterized at three temperatures of 233 K, 263 K, and 298 K while undergoing a parameter decoupling/transformation process. A unique relationship is straightforwardly created and is comparable with that in the literature: The width of the "kBT" layer is proportional to the square root of temperature. The case of 77 K is also projected. Other corroborating evidence is a Monte Carlo particle simulation conducted on an 80-nm-long silicon conductor with the "kBT" layer's width proportional to the temperature in the high field region. Without adjusting any parameters, the backscattering theory is shown to work well for the demonstrated temperatures down to 77 K

Patients with knee OA show altered gait patterns, affecting their quality of living. The current study aimed to quantify the effects of bilateral knee OA on the intra-limb and inter-limb sharing of the support of the body during gait. Fifteen patients with mild, 15 with severe bilateral knee OA, and 15 healthy controls walked along a walkway while the kinematic and kinetic data were measured. Compared with the controls, the patients significantly reduced their knee extensor moments and the corresponding contributions to the total support moment in the sagittal plane (p

This study examines how a firm's advertising and R&D affects the firm's β-risk and idiosyncratic risk, which are metrics of interest to both finance executives and senior management. Due to the existence of a non-normal and heteroscedasticity dataset, we use quantile regression to analyze the sample to understand the full behavior of our non-normally distributed datapoints. The evidence of this study shows that: (1) Advertising is significantly associated with lower β-risk for firms with lower, median and higher β-risk. (2) R&D significantly increases β-risk for firms with median and higher β-risk firms. (3) Advertising is significantly associated with lower idiosyncratic risk for firms with higher idiosyncratic risk. (4) R&D is significantly associated with higher idiosyncratic risk for firms with median and higher idiosyncratic risk. In summary, our evidence shows that both advertising and R&D have a stronger effect on firms with higher β- and idiosyncratic risk than on those with lower β- and idiosyncratic risk, respectively. Our findings are useful to help both management executives and investors. Firm managers can allocate limited resources more efficiently to reduce their firm risk; investors could exert their influence on firm's senior executives to make decisions that are beneficial to stock returns.

A ported coax intrusion sensor is a perimeter line sensor that utilizes VHF leaky coaxial cable(s) to generate guided waves for detecting an object near the cable(s). The theory of operation for ported coax intrusion sensors is described, including: 1) the basic mechanism of generating guided waves, 2) the propagation characteristics of these guided waves, 3) the scattering mechanism of the guided wave by a target, 4) the scattered signal formulation at the receiver, and 5) the signal processing techniques for detecting a moving target.

A general theory of helical instabilities with different azimuthal propagation modes in an injected electron‐hole plasma is given by extending Holter’s theory. The theory can explain the following features of the recent helical instability measurement in p‐type InSb obtained by the launching technique: (i) threshold condition of the instability for different azimuthal modes, (ii) frequency dependence of the spatial amplification associated with different propagation modes, and (iii) characteristics of the carrier temperature.