Opportunities and challenges for Chinese elderly care industry in smart environment based on occupants' needs and preferences

New developments in intelligent devices for assisting elderly people can provide elders with friendly, mutual, and personalized interactions. Since the intelligent devices should continually make an important contribution to the smart elderly care industry, smart services or policies for the elders are recently provided by a large number of government programs in China. At present, the smart elderly care industry in China has attracted numerous investors’ attention, but the smart elderly care industry in China is still at the beginning stage. Though there are great opportunities in the market, many challenges and limitations still need to be solved. This study analyzes 198 news reports about opportunities and challenges in the smart elderly care industry from six major Chinese portals. The analysis is mainly based on needs assessment for elderly people, service providers, and the Chinese government. It is concluded that smart elderly care services satisfy the elders’ mental wants and that needs for improving modernization services are the most frequently mentioned opportunities. Also, the frequently mentioned challenges behind opportunities are intelligent products not being able to solve the just-needed, user-consumption concept and the ability to pay, which is the most frequently mentioned challenge. The results of this study will enable stakeholders in the smart elderly care industry to clarify the opportunities and challenges faced by smart elderly care services in China’s development process and provide a theoretical basis for better decision making

Tin Nanoparticles Encapsulated Carbon Nanoboxes as High-Performance Anode for Lithium-Ion Batteries

One of the crucial challenges for applying Sn as an anode of lithium-ion batteries (LIBs) is the dramatic volume change during lithiation/delithiation process, which causes a rapid capacity fading and then deteriorated battery performance. To address this issue, herein, we report the design and fabrication of Sn encapsulated carbon nanoboxes (denoted as Sn@C) with yolk@shell architectures. In this design, the carbon shell can facilitate the good transport kinetics whereas the hollow space between Sn and carbon shell can accommodate the volume variation during repeated charge/discharge process. Accordingly, this composite electrode exhibits a high reversible capacity of 675 mAh g−1 at a current density of 0.8 A g−1 after 500 cycles and preserves as high as 366mAh g−1 at a higher current density of 3 A g−1 even after 930 cycles. The enhanced electrochemical performance can be ascribed to the crystal size reduction of Sn cores and the formation of polymeric gel-like layer outside the electrode surface after long-term cycles, resulting in improved capacity and enhanced rate performance

View Vertically: A Hierarchical Network for Trajectory Prediction via Fourier Spectrums

Understanding and forecasting future trajectories of agents are critical for behavior analysis, robot navigation, autonomous cars, and other related applications. Previous methods mostly treat trajectory prediction as time sequence generation. Different from them, this work studies agents' trajectories in a "vertical" view, i.e., modeling and forecasting trajectories from the spectral domain. Different frequency bands in the trajectory spectrums could hierarchically reflect agents' motion preferences at different scales. The low-frequency and high-frequency portions could represent their coarse motion trends and fine motion variations, respectively. Accordingly, we propose a hierarchical network V$^2$-Net, which contains two sub-networks, to hierarchically model and predict agents' trajectories with trajectory spectrums. The coarse-level keypoints estimation sub-network first predicts the "minimal" spectrums of agents' trajectories on several "key" frequency portions. Then the fine-level spectrum interpolation sub-network interpolates the spectrums to reconstruct the final predictions. Experimental results display the competitiveness and superiority of V$^2$-Net on both ETH-UCY benchmark and the Stanford Drone Dataset.Comment: Accepted to ECCV 202

Investigation of hearing loss in elderly vertigo and dizziness patients in the past 10 years

BackgroundVertigo and hearing loss are both prevalent in the elderly. This study retrospectively analyzed hearing test results from elderly patients experiencing vertigo and dizziness at ENT outpatient over a 10-year period, in order to study the patterns of hearing loss in this patient population.MethodsNine thousand three hundred eighty four patients over 50 years old underwent retrospective collection and screening of outpatient diagnosis, pure tone audiometry, acoustic immittance measurement (tympanogram) and auditory brainstem response (ABR) test. The patient's audiograms are divided into 7 subtypes according to a set of fixed criteria. Meanwhile, K-Means clustering analysis method was used to classify the audiogram.ResultsThe Jerger classification of tympanogram in elderly patients with vertigo and dizziness showed the majority falling under type A. The leading audiogram shapes were flat (27.81% in right ear and 26.89% in left ear), high-frequency gently sloping (25.97% in right ear and 27.34% in left ear), and high-frequency steeply sloping (21.60% in right ear and 22.53% in left ear). Meniere's disease (MD; 30.87%), benign recurrent vertigo (BRV; 19.07%), and benign paroxysmal positional vertigo (BPPV; 15.66%) were the most common etiologies in elderly vestibular diseases. We observed statistically significant differences in hearing thresholds among these vestibular diseases (P < 0.001). K-Means clustering analysis suggested that the optimal number of clusters was three, with sample sizes for the three clusters being 2,747, 2,413, and 4,139, respectively. The ANOVA statistical results of each characteristic value showed P < 0.001.ConclusionThe elderly patients often have mild to moderate hearing loss as a concomitant symptom with vertigo. Female patients have better hearing thresholds than males. The dominant audiometric shapes in this patient population were flat, high-frequency gently sloping, and high-frequency steeply sloping according to a set of fixed criteria. This study highlights the need for tailored strategies in managing hearing loss in elderly patients with vertigo and dizziness

Tin Nanoparticles Encapsulated Carbon Nanoboxes as High-Performance Anode for Lithium-Ion Batteries

One of the crucial challenges for applying Sn as an anode of lithium-ion batteries (LIBs) is the dramatic volume change during lithiation/delithiation process, which causes a rapid capacity fading and then deteriorated battery performance. To address this issue, herein, we report the design and fabrication of Sn encapsulated carbon nanoboxes (denoted as Sn@C) with yolk@shell architectures. In this design, the carbon shell can facilitate the good transport kinetics whereas the hollow space between Sn and carbon shell can accommodate the volume variation during repeated charge/discharge process. Accordingly, this composite electrode exhibits a high reversible capacity of 675 mAh g−1 at a current density of 0.8 A g−1 after 500 cycles and preserves as high as 366 mAh g−1 at a higher current density of 3 A g−1 even after 930 cycles. The enhanced electrochemical performance can be ascribed to the crystal size reduction of Sn cores and the formation of polymeric gel-like layer outside the electrode surface after long-term cycles, resulting in improved capacity and enhanced rate performance

Inhalation of Hydrogen Attenuates Progression of Chronic Heart Failure via Suppression of Oxidative Stress and P53 Related to Apoptosis Pathway in Rats

Background: Continuous damage from oxidative stress and apoptosis are the important mechanisms that facilitate chronic heart failure (CHF). Molecular hydrogen (H2) has potentiality in the aspects of anti-oxidation. The objectives of this study were to investigate the possible mechanism of H2 inhalation in delaying the progress of CHF.Methods and Results: A total of 60 Sprague-Dawley (SD) rats were randomly divided into four groups: Sham, Sham treated with H2, CHF and CHF treated with H2. Rats from CHF and CHF treated with H2 groups were injected isoprenaline subcutaneously to establish the rat CHF model. One month later, the rat with CHF was identified by the echocardiography. After inhalation of H2, cardiac function was improved vs. CHF (p < 0.05), whereas oxidative stress damage and apoptosis were significantly attenuated (p < 0.05). In this study, the mild oxidative stress was induced in primary cardiomyocytes of rats, and H2 treatments significantly reduced oxidative stress damage and apoptosis in cardiomyocytes (p < 0.05 or p < 0.01). Finally, as a pivotal transcription factor in reactive oxygen species (ROS)-apoptosis signaling pathway, the expression and phosphorylation of p53 were significantly reduced by H2 treatment in this rat model and H9c2 cells (p < 0.05 or p < 0.01).Conclusion: As a safe antioxidant, molecular hydrogen mitigates the progression of CHF via inhibiting apoptosis modulated by p53. Therefore, from the translational point of view and speculation, H2 is equipped with potential therapeutic application as a novel antioxidant in protecting CHF in the future

31st Annual Meeting and Associated Programs of the Society for Immunotherapy of Cancer (SITC 2016) : part two

Background The immunological escape of tumors represents one of the main ob- stacles to the treatment of malignancies. The blockade of PD-1 or CTLA-4 receptors represented a milestone in the history of immunotherapy. However, immune checkpoint inhibitors seem to be effective in specific cohorts of patients. It has been proposed that their efficacy relies on the presence of an immunological response. Thus, we hypothesized that disruption of the PD-L1/PD-1 axis would synergize with our oncolytic vaccine platform PeptiCRAd. Methods We used murine B16OVA in vivo tumor models and flow cytometry analysis to investigate the immunological background. Results First, we found that high-burden B16OVA tumors were refractory to combination immunotherapy. However, with a more aggressive schedule, tumors with a lower burden were more susceptible to the combination of PeptiCRAd and PD-L1 blockade. The therapy signifi- cantly increased the median survival of mice (Fig. 7). Interestingly, the reduced growth of contralaterally injected B16F10 cells sug- gested the presence of a long lasting immunological memory also against non-targeted antigens. Concerning the functional state of tumor infiltrating lymphocytes (TILs), we found that all the immune therapies would enhance the percentage of activated (PD-1pos TIM- 3neg) T lymphocytes and reduce the amount of exhausted (PD-1pos TIM-3pos) cells compared to placebo. As expected, we found that PeptiCRAd monotherapy could increase the number of antigen spe- cific CD8+ T cells compared to other treatments. However, only the combination with PD-L1 blockade could significantly increase the ra- tio between activated and exhausted pentamer positive cells (p= 0.0058), suggesting that by disrupting the PD-1/PD-L1 axis we could decrease the amount of dysfunctional antigen specific T cells. We ob- served that the anatomical location deeply influenced the state of CD4+ and CD8+ T lymphocytes. In fact, TIM-3 expression was in- creased by 2 fold on TILs compared to splenic and lymphoid T cells. In the CD8+ compartment, the expression of PD-1 on the surface seemed to be restricted to the tumor micro-environment, while CD4 + T cells had a high expression of PD-1 also in lymphoid organs. Interestingly, we found that the levels of PD-1 were significantly higher on CD8+ T cells than on CD4+ T cells into the tumor micro- environment (p < 0.0001). Conclusions In conclusion, we demonstrated that the efficacy of immune check- point inhibitors might be strongly enhanced by their combination with cancer vaccines. PeptiCRAd was able to increase the number of antigen-specific T cells and PD-L1 blockade prevented their exhaus- tion, resulting in long-lasting immunological memory and increased median survival

Electrical treeing: A phase-field model

Electrical treeing is a commonly observed phenomenon associated with dielectric breakdown in solid dielectrics. In this work, a phase-field model is developed to study the initiation and propagation of electrical trees in two different geometries: a parallel capacitor and a cylindrical capacitor. The model utilizes a continuous field of damage variable to distinguish the localized damaged regions from the undamaged bulk material. Factors that affect electrical tree morphology, including discharge speed and damage mobility, are studied. Electrical treeing tends to exhibit a fractal shape with more branches at a relatively high discharge speed relative to the rate of damage. Furthermore, the effect of fillers on electrical treeing is also studied. Numerical results suggest that fillers of lower permittivity, higher breakdown energy or lower damage mobility will promote fractal treeing and thus resist catastrophic breakdown

Research on Vehicle Lane Change Warning Method Based on Deep Learning Image Processing

In order to improve vehicle driving safety in a low-cost manner, we used a monocular camera to study a lane-changing warning algorithm for highway vehicles based on deep learning image processing technology. We improved the mask region-based convolutional neural network for vehicle target detection. Suitable anchor frame ratios were obtained by means of K-means++ method clustering for 66,389 vehicle targets with the width/height ratio, which is one more set of anchor frames than the original setting, so as to ensure that the generation accuracy of candidate frames can be improved without sacrificing more network performance. Using the vehicle target annotation set, we trained the vehicle targets. Through the analysis of indicators for mean average precision, a new set of anchor frames was added to improve the accuracy of vehicle target detection. Based on the improved vehicle detection network and an end-to-end lane detection network in series, we proposed an algorithm for the detection of highway vehicle lane-changing behavior with the first-person perspective by summing the inter-frame change rates in the vehicle lane-changing data pool. After the identification and verification of the marked lane-changing picture sequences, a lane-changing detection accuracy rate of 94.5% was achieved