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Conditional value-at-risk (CVaR) and conditional expected shortfall (CES) are widely adopted risk measures which help monitor potential tail risk while adapting to evolving market information. In this paper, we propose an approach to constructing simultaneous confidence bands (SCBs) for tail risk as measured by CVaR and CES, with the confidence bands uniformly valid for a set of tail levels. We consider one-sided tail risk (downside or upside tail risk) as well as relative tail risk (the ratio of upside to downside tail risk). A general class of location-scale models with heavy-tailed innovations is employed to filter out the return dynamics. Then, CVaR and CES are estimated with the aid of extreme value theory. In the asymptotic theory, we consider two scenarios: (i) the extreme scenario that allows for extrapolation beyond the range of the available data and (ii) the intermediate scenario that works exclusively in the case where the available data are adequate relative to the tail level. For finite-sample implementation, we propose a novel bootstrap procedure to circumvent the slow convergence rates of the SCBs as well as infeasibility of approximating the limiting distributions. A series of Monte Carlo simulations confirm that our approach works well in finite samples.
Robotic systems are usually controlled to repetitively perform specific actions for manufacturing tasks. The traditional control methods are domain-dependent and model-dependent with cost of much human efforts. They cannot meet the new requirements of generality and flexibility in many areas such as intelligent manufacturing and customized production. This paper develops a general model-free approach to enable robots to perform multi-step object sorting tasks through deep reinforcement learning. Taking projected heightmap images from different time steps as input without extra high-level image analysis and understanding, critic models are designed to produce a pixel-wise Q value map for each type of action. It is a new trial to apply pixel-wise Q value-based critic networks to solve multi-step sorting tasks that involve many types of actions and complex action constraints. The experimental validations on simulated and realistic object sorting tasks demonstrate the effectiveness of the proposed approach. Qualitative results (videos), code for simulated and realistic experiments, and pre-trained models are available at https://github.com/JiatongBao/DRLSorting
To set the sleeping mode for the Yutu-2 rover, a visual pose prediction algorithm including terrain reconstruction and pose estimation was first studied. The terrain reconstruction precision is affected by using only the stereo navigation camera (Navcam) images and the rotation angles of the mast. However, the hazard camera (Hazcam) pose is fixed, and an image network was constructed by linking all of the Navcam and Hazcam stereoimages. Then, the Navcam pose was refined based on a multiview block bundle adjustment. The experimental results show that the mean absolute errors of the check points in the proposed algorithm were 10.4 mm over the range of
from 2.0 to 6.1 m, and the proposed algorithm achieved good prediction results for the rover pose (the average differences of the values of the pitch angle and the roll angle were −0.19 degrees and 0.29 degrees, respectively). Under the support of the proposed algorithm, engineers have completed the remote setting of the sleeping mode for Yutu-2 successfully in the Chang’e-4 mission operations.
OBJECTIVES/GOALS: Diffusion basis spectrum imaging (DBSI) allows for detailed evaluation of white matter microstructural changes present in cervical spondylotic myelopathy (CSM). Our goal is to utilize multidimensional clinical and quantitative imaging data to characterize disease severity and predict long-term outcomes in CSM patients undergoing surgery. METHODS/STUDY POPULATION: A single-center prospective cohort study enrolled fifty CSM patients who underwent surgical decompression and twenty healthy controls from 2018-2021. All patients underwent diffusion tensor imaging (DTI), DBSI, and complete clinical evaluations at baseline and 2-years follow-up. Primary outcome measures were the modified Japanese Orthopedic Association score (mild [mJOA 15-17], moderate [mJOA 12-14], severe [mJOA 0-11]) and SF-36 Physical and Mental Component Summaries (PCS and MCS). At 2-years follow-up, improvement was assessed via established MCID thresholds. A supervised machine learning classification model was used to predict treatment outcomes. The highest-performing algorithm was a linear support vector machine. Leave-one-out cross-validation was utilized to test model performance. RESULTS/ANTICIPATED RESULTS: A total of 70 patients – 20 controls, 25 mild, and 25 moderate/severe CSM patients – were enrolled. Baseline clinical and DTI/DBSI measures were significantly different between groups. DBSI Axial and Radial Diffusivity were significantly correlated with baseline mJOA and mJOA recovery, respectively (r=-0.33, p<0.01; r=-0.36, p=0.02). When predicting baseline disease severity (mJOA classification), DTI metrics alone performed with 38.7% accuracy (AUC: 72.2), compared to 95.2% accuracy (AUC: 98.9) with DBSI metrics alone. When predicting improvement after surgery (change in mJOA), clinical variables alone performed with 33.3% accuracy (AUC: 0.40). When combining DTI or DBSI parameters with key clinical covariates, model accuracy improved to 66.7% (AUC: 0.65) and 88.1% (AUC: 0.95) accuracy, respectively. DISCUSSION/SIGNIFICANCE: DBSI metrics correlate with baseline disease severity and outcome measures at 2-years follow-up. Our results suggest that DBSI may serve as a valid non-invasive imaging biomarker for CSM disease severity and potential for postoperative improvement.
Subthreshold depression could be a significant precursor to and a risk factor for major depression. However, reliable estimates of the prevalence and its contribution to developing major depression under different terminologies depicting subthreshold depression have to be established.
By searching PubMed and Web of Science using predefined inclusion criteria, we included 1 129 969 individuals from 113 studies conducted. The prevalence estimates were calculated using the random effect model. The incidence risk ratio (IRR) was estimated by measuring the ratio of individuals with subthreshold depression who developed major depression compared to that of non-depressed individuals from 19 studies (88, 882 individuals).
No significant difference in the prevalence among the different terminologies depicting subthreshold depression (Q = 1.96, p = 0.5801) was found. By pooling the prevalence estimates of subthreshold depression in 113 studies, we obtained a summary prevalence of 11.02% [95% confidence interval (CI) 9.78–12.33%]. The youth group had the highest prevalence (14.17%, 95% CI 8.82–20.55%), followed by the elderly group (12.95%, 95% CI 11.41-14.58%) and the adult group (8.92%, 95% CI 7.51–10.45%). Further analysis of 19 studies' incidence rates showed individuals with subthreshold depression had an increased risk of developing major depression (IRR = 2.95, 95% CI 2.33–3.73), and the term minor depression showed the highest IRR compared with other terms (IRR = 3.97, 95% CI 3.17–4.96).
Depression could be a spectrum disorder, with subthreshold depression being a significant precursor to and a risk factor for major depression. Proactive management of subthreshold depression could be effective for managing the increasing prevalence of major depression.
Previous analyses of grey and white matter volumes have reported that schizophrenia is associated with structural changes. Deep learning is a data-driven approach that can capture highly compact hierarchical non-linear relationships among high-dimensional features, and therefore can facilitate the development of clinical tools for making a more accurate and earlier diagnosis of schizophrenia.
To identify consistent grey matter abnormalities in patients with schizophrenia, 662 people with schizophrenia and 613 healthy controls were recruited from eight centres across China, and the data from these independent sites were used to validate deep-learning classifiers.
We used a prospective image-based meta-analysis of whole-brain voxel-based morphometry. We also automatically differentiated patients with schizophrenia from healthy controls using combined grey matter, white matter and cerebrospinal fluid volumetric features, incorporated a deep neural network approach on an individual basis, and tested the generalisability of the classification models using independent validation sites.
We found that statistically reliable schizophrenia-related grey matter abnormalities primarily occurred in regions that included the superior temporal gyrus extending to the temporal pole, insular cortex, orbital and middle frontal cortices, middle cingulum and thalamus. Evaluated using leave-one-site-out cross-validation, the performance of the classification of schizophrenia achieved by our findings from eight independent research sites were: accuracy, 77.19–85.74%; sensitivity, 75.31–89.29% and area under the receiver operating characteristic curve, 0.797–0.909.
These results suggest that, by using deep-learning techniques, multidimensional neuroanatomical changes in schizophrenia are capable of robustly discriminating patients with schizophrenia from healthy controls, findings which could facilitate clinical diagnosis and treatment in schizophrenia.
The usefulness of ultra-fast track cardiac anaesthesia may give great benefits to patients; however, its usefulness has not been completely evaluated in infants and toddlers, who are generally considered the most difficult group for ultra-fast track cardiac anaesthesia.
A total of 130 children were allocated randomly into to a ultra-fast track cardiac anaesthesia group (Group D) or a conventional anaesthesia group (Group C) (each n = 65). In Group D, dexmedetomidine was administrated at a dosage of 1 µg/kg/hour after induction. The patient- controlled intravenous analgesia was dexmedetomidine and sufentanil. In Group C, patients were infused with of the same volume of normal saline, and sufentanil alone for patient-controlled intravenous analgesia. The dosages of sufentanil, extubation time, haemodynamic parameters, postoperative hospitalisation conditions, pain and sedation scores, blood gas analysis, and inotropic scores were all recorded.
The dosage of sufentanil (1.49 ± 0.05 vs. 3.81 ± 0.04 µg, p < 0.001) and extubation time (2.63 ± 0.52 vs. 436.60 ± 22.19 minutes, p < 0.001) in Group D were all significantly lower than those in Group C. Moreover, cardiac intensive care unit stay time, total hospital stay, hospitalisation costs, postoperative lactate levels, and inotropic scores were also significantly lower in Group D.
Using of ultra-fast track cardiac anaesthesia in infants and toddlers is effective, it not only reduce the perioperative requirement for opioids and shorten the extubation time but also decreases the inotrope requirement and provide a better postoperative condition for young children.
To explore the characteristics of the mitochondrial genome (mitogenome) of the squeaking silkmoths Rhodinia, a genus of wild silkmoths in the family Saturniidae of Lepidoptera, and reveal phylogenetic relationships, the mitogenome of Rhodinia fugax Butler was determined. This wild silkmoth spins a green cocoon that has potential significance in sericulture, and exhibits a unique feature that its larvae can squeak loudly when touched. The mitogenome of R. fugax is a circular molecule of 15,334 bp long and comprises 13 protein-coding genes, two ribosomal RNA genes, 22 transfer RNA genes, and an A + T-rich region, consistent with previous observations of Saturniidae species. The 370-bp A + T-rich region of R. fugax contains no tandem repeat elements and harbors several features common to the Bombycidea insects, but microsatellite AT repeat sequence preceded by the ATTTA motif is not present. Mitogenome-based phylogenetic analysis shows that R. fugax belongs to Attacini, instead of Saturniini. This study presents the first mitogenome for Rhodinia genus.
In recent years, the controlling nutritional status (CONUT) score has increasingly became an effective indicator associated with tumor prognosis. This study was conducted to synthesise data on the prognostic value of CONUT score on patients with upper tract urothelial carcinoma (UTUC) or renal cell carcinoma (RCC) undergoing nephrectomy. We designed and performed a systematic analysis of studies that verified the correlation between preoperative CONUT score and prognosis for UTUC and RCC using PubMed, Web of Science and Embase. The conclusion was clarified by pooled hazard ratios (HR) and 95% confidence intervals (95% CI). Subgroup analysis were further conducted in accordance with different primary tumor. Six studies involving 3529 patients were included in this evidence synthesis, which revealed that the CONUT score had a potential role to predict the survival of UTUC and RCC patients accepting surgery. Pooled analysis showed that the overall survival (OS, HR 2·32, p < 0·0001), cancer-specific survival (CSS, HR 2·68, p < 0·0001) and disease-free survival (DFS, HR 1·62, p < 0·00001) were inferior in the high CONUT score group when compared with low score group. Subgroup analysis revealed that this result was in line with UTUC (OS: HR 1·86, p = 0·02; CSS: HR 2·24, p = 0·01; DFS: HR 1·54, p < 0·00001) and RCC (OS: HR 3·05, p < 0·00001; CSS: HR 3·47, p < 0·00001; DFS: HR 2·21, p = 0·0005) patients respectively. Consequently, the CONUT score is a valuable preoperative index to predict the survival of patients with UTUC or RCC undergoing nephrectomy.
Some studies have suggested that the Toll-like receptor 9 polymorphism (TLR9 rs352140) is closely related to the risk of bacterial meningitis (BM), but this is subject to controversy. This study set out to estimate whether the TLR9 rs352140 polymorphism confers an increased risk of BM. Relevant literature databases were searched including PubMed, Embase, the Cochrane Library and China National Knowledge Infrastructure (CNKI) up to August 2020. Seven case-control studies from four publications were enrolled in the present meta-analysis. Odds ratios (OR) and confidence intervals (95% CI) were calculated to estimate associations between BM risk and the target polymorphism. Significant associations identified were allele contrast (A vs. G: OR 0.66, 95% CI 0.59–0.75, P = 0.000), homozygote comparison (AA vs. AG/GG: OR 0.62, 95% CI 0.49–0.78, P = 0.000), heterozygote comparison (A vs. G: OR 0.74, 95% CI 0.61–0.91, P = 0.005), recessive genetic model (AA vs. AG/GG: OR 0.78, 95% CI 0.65–0.93, P = 0.006) and dominant genetic model (AA vs. AG/GG: OR 0.70, 95% CI 0.57–0.85, P = 0.000). The findings indicate that, in contrast to some studies, the TLR9 rs352140 polymorphism is associated with a decreased risk for BM.
No studies have reported on how to relieve distress or relax in medical health workers while wearing medical protective equipment in coronavirus disease 2019 (COVID-19) pandemic. The study aimed to establish which relaxation technique, among six, is the most feasible in first-line medical health workers wearing medical protective equipment.
This was a two-step study collecting data with online surveys. Step 1: 15 first-line medical health workers were trained to use six different relaxation techniques and reported the two most feasible techniques while wearing medical protective equipment. Step 2: the most two feasible relaxation techniques revealed by step 1 were quantitatively tested in a sample of 65 medical health workers in terms of efficacy, no space limitation, no time limitation, no body position requirement, no environment limitation to be done, easiness to learn, simplicity, convenience, practicality, and acceptance.
Kegel exercise and autogenic relaxation were the most feasible techniques according to step 1. In step 2, Kegel exercise outperformed autogenic relaxation on all the 10 dimensions among the 65 participants while wearing medical protective equipment (efficacy: 24 v. 15, no space limitation: 30 v. 4, no time limitation: 31 v. 4, no body position requirement: 26 v. 4, no environment limitation: 30 v. 11, easiness to learn: 28 v. 5, simplicity: 29 v. 7, convenience: 29 v. 4, practicality: 30 v. 14, acceptance: 32 v. 6).
Kegel exercise seems a promising self-relaxation technique for first-line medical health workers while wearing medical protective equipment among COVID-19 pandemic.
HfO2–Sm3TaO7 ceramics are prepared through a solid-state reaction method. The X-ray diffraction and structural refinement show that the phase structures of HfO2–Sm3TaO7 ceramics are an ordered orthorhombic phase and the space groups are belonging to Ccmm. The degree of the structural disorder increases with increasing HfO2 content. The solid solution mechanism reveals that Hf4+ exists in the form of interstitial ions that cause crystal expansion when the doping content is less than 4 mol%. When the doping concentration of HfO2 ≥ 4 mol%, the Hf4+ ions can substitute an equal number of Sm3+ and Ta5+ ions. The phase transition of Sm3TaO7 ceramics is removed with increasing HfO2 content, and the 8 mol% HfO2–Sm3TaO7 ceramics have a high thermal expansion coefficient of 10.2 × 10−6 K−1 at 1200 °C. The 2 mol% HfO2–Sm3TaO7 ceramics have the lowest thermal conductivity (1.03 W/m K at 900 °C), which is lower than previous research of the 7–8 YSZ. The outstanding thermophysical properties of HfO2–Sm3TaO7 ceramics indicate that they are potential thermal-barrier coating materials.
The oxidation behavior of the selective laser melting (SLM)–fabricated Inconel 718 was investigated through isothermal oxidation testing at 650 °C for 500 h and compared with that of the as-cast and as-forged specimens at the same testing conditions. The effect of microstructure and surface roughness on the oxidation behavior of the SLM-fabricated, as-cast, and as-forged Inconel 718 specimens was examined. The result shows that Inconel 718 fabricated by SLM with the unique layer structure exhibited a better resistance to the 500 h oxidation at 650 °C compared with as-cast and as-forged 718 with coarse dendritic structure and uniform equiaxed grain microstructure, respectively. The influence of the surface roughness on the long-time oxidation resistance of SLM specimens is not pronounced compared with that of as-cast and as-forged specimens. The tiny dendrites instead of grain boundaries are a major influencing factor for the oxidation process of SLM specimens. The surface roughness has more evident influence on the oxidation resistance of as-forged specimens than that of the as-cast ones subjected to the 500 h oxidation at 650 °C.
The aim of this study was to investigate the combined effect of n-3 fatty acids (EPA and DHA, at an EPA:DHA ratio of 150:500) and phytosterol esters (PS) on non-alcoholic fatty liver disease (NAFLD) patients. We conducted a randomised, double-blind, placebo-controlled trial. Ninety-six NAFLD subjects were randomly assigned to the following groups: the PS group (receiving 3·3 g/d PS); the FO group (receiving 450 mg EPA + 1500 mg DHA/d); the PS + FO combination group (receiving 3·3 g/d PS and 450 mg EPA + 1500 mg DHA/d) and the PO group (a placebo group). The baseline clinical characteristics of the four groups were similar. The primary outcome was liver:spleen attenuation ratio (L:S ratio). The percentage increase in liver–spleen attenuation (≤1) in the PS + FO group was 36 % (P = 0·083), higher than those in the other three groups (PS group, 11 %, P = 0·519; FO group, 18 %, P = 0·071; PO group, 15 %, P = 0·436). Compared with baseline, transforming growth factor-β (TGF-β) was significantly decreased in the three study groups at the end of the trial (PS, P = 0·000; FO, P = 0·002; PS + FO, P = 0·001) and TNF-α was significantly decreased in the FO group (P = 0·036), PS + FO group (P = 0·005) and PO group (P = 0·032) at the end of the intervention. Notably, TGF-β was reduced significantly more in the PS + FO group than in the PO group (P = 0·032). The TAG and total cholesterol levels of the PS + FO group were reduced by 11·57 and 9·55 %, respectively. In conclusion, co-supplementation of PS and EPA + DHA could increase the effectiveness of treatment for hepatic steatosis.
SmTaO4 ceramics have excellent high-temperature phase stabilities and mechanical properties and show great potential for use as next-generation thermal barrier coating (TBC) materials. CeO2–SmTaO4 ceramics are prepared via high-temperature solid–state reaction. It retains a single monoclinic phase structure. Ce4+ was reduced to Ce3+ by high-temperature deoxidation, and the Ce3+ ions substitute for an equal number of Sm3+ ions. The CeO2–SmTaO4 ceramics had lower thermal conductivities [1.09–2.75 W/(m K)] than yttria-stabilized zirconia (YSZ) [2.1–2.7 W/(m K)] at 100–800 °C, which decreased dramatically with increasing temperature. SmTaO4 doped with 2% CeO2 had lower thermal conductivity [1.09 W/(m K), 800 °C] than SmTaO4 [1.42 W/(m K), 800 °C] and 2% ZrO2-doped SmTaO4 ceramics [1.22 W/(m K), 800 °C]. The low thermal conductivity is attributed to Ce3+ substitution for an equal number of Sm3+ ions, and because Ce3+ ions are the strongest phonon scattering centers, they can decrease the phonon mean free path effectively. The thermal expansion coefficient of 8% CeO2–SmTaO4 ceramics is approximately 10.3 × 10−6 K−1 at 1200 °C, which is slightly higher than that of both YSZ (10.0 × 10−6 K−1) and SmTaO4 (9.58 × 10−6 K−1). The outstanding thermophysical properties indicate that CeO2–SmTaO4 ceramics are potential TBC materials.