Quantile regression in partially linear varying coefficient models

Semiparametric models are often considered for analyzing longitudinal data for a good balance between flexibility and parsimony. In this paper, we study a class of marginal partially linear quantile models with possibly varying coefficients. The functional coefficients are estimated by basis function approximations. The estimation procedure is easy to implement, and it requires no specification of the error distributions. The asymptotic properties of the proposed estimators are established for the varying coefficients as well as for the constant coefficients. We develop rank score tests for hypotheses on the coefficients, including the hypotheses on the constancy of a subset of the varying coefficients. Hypothesis testing of this type is theoretically challenging, as the dimensions of the parameter spaces under both the null and the alternative hypotheses are growing with the sample size. We assess the finite sample performance of the proposed method by Monte Carlo simulation studies, and demonstrate its value by the analysis of an AIDS data set, where the modeling of quantiles provides more comprehensive information than the usual least squares approach.Comment: Published in at http://dx.doi.org/10.1214/09-AOS695 the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org

Gesture-aware Interactive Machine Teaching with In-situ Object Annotations

Interactive Machine Teaching (IMT) systems allow non-experts to easily create Machine Learning (ML) models. However, existing vision-based IMT systems either ignore annotations on the objects of interest or require users to annotate in a post-hoc manner. Without the annotations on objects, the model may misinterpret the objects using unrelated features. Post-hoc annotations cause additional workload, which diminishes the usability of the overall model building process. In this paper, we develop LookHere, which integrates in-situ object annotations into vision-based IMT. LookHere exploits users' deictic gestures to segment the objects of interest in real time. This segmentation information can be additionally used for training. To achieve the reliable performance of this object segmentation, we utilize our custom dataset called HuTics, including 2040 front-facing images of deictic gestures toward various objects by 170 people. The quantitative results of our user study showed that participants were 16.3 times faster in creating a model with our system compared to a standard IMT system with a post-hoc annotation process while demonstrating comparable accuracies. Additionally, models created by our system showed a significant accuracy improvement ($\Delta mIoU=0.466$) in segmenting the objects of interest compared to those without annotations.Comment: UIST 202

Output Feedback Control for Couple-Group Consensus of Multiagent Systems

This paper deals with the couple-group consensus problem for multiagent systems via output feedback control. Both continuous- and discrete-time cases are considered. The consensus problems are converted into the stability problem of the error systems by the system transformation. We obtain two necessary and sufficient conditions of couple-group consensus in different forms for each case. Two different algorithms are used to design the control gains for continuous- and discrete-time case, respectively. Finally, simulation examples are given to show the effectiveness of the proposed results

Winner versus Loser: Time-Varying Performance And Dynamic Conditional Correlation

Using multi-factor models in OLS and GARCH-M methodology, this paper provides a cross-sectional and time-series investigation of conditional and unconditional expected returns of real REITs index momentum portfolios against real estate property, large-cap stock small-cap stock, and bond index in USA. The expected returns and dynamic conditional correlations between REITs and those of other financial and tangible assets vary in period 1989-2010. REITs returns exhibit a higher correlation with up move of financial market, but a lower correlation in market downturns. REITs may possibly provide diversification benefits to multi-asset investment portfolio. We find that the performances of momentum returns are different from the NAREIT index, and display asymmetric volatility as well. Additionally, we find evidence that REITs momentum returns are varying between winner and loser by Wald test. The results of regressions also indicate that REITs return exhibits the greater sensitivity to large- and small-cap stock index, and less closely with those of bond and real estate index. The results also suggest that REITs not be viewed as a complete substitute for investment in tangible property of real estate

Monte-Carlo Tree Search for Behavior Planning in Autonomous Driving

The integration of autonomous vehicles into urban and highway environments necessitates the development of robust and adaptable behavior planning systems. This study presents an innovative approach to address this challenge by utilizing a Monte-Carlo Tree Search (MCTS) based algorithm for autonomous driving behavior planning. The core objective is to leverage the balance between exploration and exploitation inherent in MCTS to facilitate intelligent driving decisions in complex scenarios. We introduce an MCTS-based algorithm tailored to the specific demands of autonomous driving. This involves the integration of carefully crafted cost functions, encompassing safety, comfort, and passability metrics, into the MCTS framework. The effectiveness of our approach is demonstrated by enabling autonomous vehicles to navigate intricate scenarios, such as intersections, unprotected left turns, cut-ins, and ramps, even under traffic congestion, in real-time. Qualitative instances illustrate the integration of diverse driving decisions, such as lane changes, acceleration, and deceleration, into the MCTS framework. Moreover, quantitative results, derived from examining the impact of iteration time and look-ahead steps on decision quality and real-time applicability, substantiate the robustness of our approach. This robustness is further underscored by the high success rate of the MCTS algorithm across various scenarios.Comment: 6 pages, 3 figure

DiffS2UT: A Semantic Preserving Diffusion Model for Textless Direct Speech-to-Speech Translation

While Diffusion Generative Models have achieved great success on image generation tasks, how to efficiently and effectively incorporate them into speech generation especially translation tasks remains a non-trivial problem. Specifically, due to the low information density of speech data, the transformed discrete speech unit sequence is much longer than the corresponding text transcription, posing significant challenges to existing auto-regressive models. Furthermore, it is not optimal to brutally apply discrete diffusion on the speech unit sequence while disregarding the continuous space structure, which will degrade the generation performance significantly. In this paper, we propose a novel diffusion model by applying the diffusion forward process in the \textit{continuous} speech representation space, while employing the diffusion backward process in the \textit{discrete} speech unit space. In this way, we preserve the semantic structure of the continuous speech representation space in the diffusion process and integrate the continuous and discrete diffusion models. We conduct extensive experiments on the textless direct speech-to-speech translation task, where the proposed method achieves comparable results to the computationally intensive auto-regressive baselines (500 steps on average) with significantly fewer decoding steps (50 steps).Comment: Accepted in EMNLP2023 main conferenc

Placental expression of AChE, α7nAChR and NF-κB in patients with preeclampsia

Objectives: This study aimed to investigate placental expression of AChE, α7nAChR and NF-κB in patients with preeclampsia and discuss about its clinical significance. Material and methods: mRNA expression levels of acetylcholine (AChE), alpha-7 nicotinic acetylcholine receptor (α7nAChR) and nuclear factor-kB (NF-κB) in placenta were detected by qRT-PCR, and protein levels were determined by immunohis­tological analysis and Western Blot in 35 women with preeclampsia (including 20 cases of mild preeclampsia and 15 cases of severe preeclampsia) and 30 cases in control group, respectively. Results: The expression of AChE mRNA and protein in placenta increased significantly in patients with preeclampsia compared with the control group (p < 0.01). It was lower in patients with severe preeclampsia than in patients with mild preeclampsia (p < 0.05). The expression of α7nAChR mRNA and protein in placenta decreased significantly in patients with preeclampsia compared with the control group (p < 0.01). However, the expression of α7nAChR mRNA and protein in patients with severe preeclampsia was higher than that in patients with mild preeclampsia, without significant difference(p > 0.05). The expression of NF-κB protein in placenta decreased significantly in patients with preeclampsia compared with the control group(p < 0.01). It was higher in patients with severe preeclampsia than in patients with mild preeclampsia (p < 0.05), but there was no significant difference between preeclampsia group and control group in the expression of NF-κB mRNA in placenta (p > 0.05). The results of Western blotting assay were consistent with those of immunohistochemistry. Conclusions: Abnormal expression of AChE, α7nAChR and NF-κB in placenta may be associated with preeclampsia. Cho­linergic anti-inflammatory pathway may play an important role in the pathogenesis of preeclampsia

Platelet Membrane-Coated Nanocarriers Targeting Plaques to Deliver Anti-CD47 Antibody for Atherosclerotic Therapy

Atherosclerosis, the principle cause of cardiovascular disease (CVD) worldwide, is mainly characterized by the pathological accumulation of diseased vascular cells and apoptotic cellular debris. Atherogenesis is associated with the upregulation of CD47, a key antiphagocytic molecule that is known to render malignant cells resistant to programmed cell removal, or "efferocytosis." Here, we have developed platelet membrane-coated mesoporous silicon nanoparticles (PMSN) as a drug delivery system to target atherosclerotic plaques with the delivery of an anti-CD47 antibody. Briefly, the cell membrane coat prolonged the circulation of the particles by evading the immune recognition and provided an affinity to plaques and atherosclerotic sites. The anti-CD47 antibody then normalized the clearance of diseased vascular tissue and further ameliorated atherosclerosis by blocking CD47. In an atherosclerosis model established in ApoE-/- mice, PMSN encapsulating anti-CD47 antibody delivery significantly promoted the efferocytosis of necrotic cells in plaques. Clearing the necrotic cells greatly reduced the atherosclerotic plaque area and stabilized the plaques reducing the risk of plaque rupture and advanced thrombosis. Overall, this study demonstrated the therapeutic advantages of PMSN encapsulating anti-CD47 antibodies for atherosclerosis therapy, which holds considerable promise as a new targeted drug delivery platform for efficient therapy of atherosclerosis

Seismic behaviour of composite shear wall with steel reinforced concrete frame and embedded perforated-steel plate

U radu se ispituje pet uzoraka posmičnih stijena raznih dimenzijskih i konstrukcijskih karakteristika kako bi se istražilo seizmičko ponašanje spregnute posmične stijene s armiranobetonskim okvirom ojačanim čelikom i ugrađenom perforiranom čeličnom pločom. Osim toga, niskociklično opterećenje se nanosi na uzorke s koeficijentom posmične zone od 1,5. Eksperimentalni podaci koriste se za analizu nosivosti, krutosti, duktilnosti, histerezne energije i karakteristika otkazivanja spomenutih uzoraka. Rezultati pokazuju da se spregnuta posmična stijena s armiranobetonskim okvirom ojačanim čelikom i ugrađenom čeličnom pločom odlikuje većom nosivošću, boljom duktilnošću, sporijim padom krutosti te većom sposobnošću rasapa energije u usporedbi s običnim armiranobetonskim posmičnim zidom. Osim toga, primjenom ugrađenih čeličnih ploča odgovarajuće debljine poboljšava se i seizmičko ponašanje spregnutih posmičnih stijena. Analizom čeličnih ploča iste debljine utvrđeno je da se uzorci s čeličnim vezicama seizmički bolje ponašaju od uzoraka sa zavarenim svornjacima. U završnom je dijelu razvijen računalni model za izračunavanje nosivosti CSW-a. Usporedba pokazuje dobru podudarnost rezultata proračuna i rezultata dobivenih mjerenjem.Experiments are conducted on five shear wall specimens of varying design and structural measures in order to investigate seismic behaviour of a composite shear wall with the steel-reinforced concrete frame and an embedded perforated-steel plate. In addition, low-cyclic load is applied on test specimens that have a shear span ratio of 1.5. Using the experimental data, the bearing capacity, stiffness, ductility, hysteretic energy, and failure characteristics of five specimens are analysed. The results show that the composite shear wall (CSW) with the steel reinforced concrete frame (SRCF) and embedded steel plate (ESP) has higher bearing capacity, better ductility, slower degradation of stiffness, and higher energy dissipation capacity, as compared to an ordinary reinforced concrete shear wall. Moreover, its seismic behaviour can be improved by using the ESP of an appropriate thickness. For the ESPs of identical thickness, the results show that the specimen that uses steel ties exhibits better seismic behaviour than those using welding studs. Finally, a computing model that can calculate the bearing capacity of the CSWs is developed. A comparison of calculated and measured results shows that the results are close to each other