A Variational Auto-Encoder Enabled Multi-Band Channel Prediction Scheme for Indoor Localization

Indoor localization is getting increasing demands for various cutting-edged technologies, like Virtual/Augmented reality and smart home. Traditional model-based localization suffers from significant computational overhead, so fingerprint localization is getting increasing attention, which needs lower computation cost after the fingerprint database is built. However, the accuracy of indoor localization is limited by the complicated indoor environment which brings the multipath signal refraction. In this paper, we provided a scheme to improve the accuracy of indoor fingerprint localization from the frequency domain by predicting the channel state information (CSI) values from another transmitting channel and spliced the multi-band information together to get more precise localization results. We tested our proposed scheme on COST 2100 simulation data and real time orthogonal frequency division multiplexing (OFDM) WiFi data collected from an office scenario

Accelerated search for BaTiO3-based piezoelectrics with vertical morphotropic phase boundary using Bayesian learning

An outstanding challenge in the nascent field of materials informatics is to incorporate materials knowledge in a robust Bayesian approach to guide the discovery of new materials. Utilizing inputs from known phase diagrams, features or material descriptors that are known to affect the ferroelectric response, and Landau–Devonshire theory, we demonstrate our approach for BaTiO(3)-based piezoelectrics with the desired target of a vertical morphotropic phase boundary. We predict, synthesize, and characterize a solid solution, (Ba(0.5)Ca(0.5))TiO(3)-Ba(Ti(0.7)Zr(0.3))O(3), with piezoelectric properties that show better temperature reliability than other BaTiO(3)-based piezoelectrics in our initial training data

Recent advances in ocular graft-versus-host disease

Ocular graft-versus-host-disease (GVHD) remains a significant clinical complication after allogeneic hematopoietic stem cell transplantation. Impaired visual function, pain, and other symptoms severely affect affected individuals’ quality of life. However, the diagnosis of and therapy for ocular GVHD involve a multidisciplinary approach and remain challenging for both hematologists and ophthalmologists, as there are no unified international criteria. Through an exploration of the complex pathogenesis of ocular GVHD, this review comprehensively summarizes the pathogenic mechanism, related tear biomarkers, and clinical characteristics of this disease. Novel therapies based on the mechanisms are also discussed to provide insights into the ocular GVHD treatment

Directors’ Informational Role in Corporate Voluntary Disclosure: An Analysis of Directors from Related Industries

Boards of directors play their role in corporate governance by advising and/or monitoring managers. In the corporate disclosure literature, prior research has documented directors’ monitoring role, yet empirical evidence on directors’ advising role is limited. Since the advising role often entails information transfer, we examine directors who concurrently serve as directors or executives in the firms’ related industries (DRIs) and hence possess valuable information about the firms’ external operating environment. We hypothesize and find that more DRIs on boards are associated with more accurate management forecasts. This association is stronger when firms face greater uncertainty, and holds in settings where DRIs are unlikely to monitor managers, suggesting a distinct advising role of DRIs. Our study highlights directors’ role as information suppliers and advisors who help shape corporate voluntary disclosure

Social Connections within Executive Teams and Management Forecasts

We examine the role of teamwork within the top executive teams in generating management forecasts. Using social connections within the executive team to capture the team’s interaction, cooperation, and teamwork, we find that social connections among team members are associated with higher management forecast accuracy, consistent with economic theories that information is dispersed within a firm and with sociology insights that social connections facilitate information sharing. Further analyses show that the association between social connections and forecast accuracy is stronger when the teams are just beginning to work together, when their firms face more uncertainty or adversity, and when the CEOs are less powerful. Our results hold for a subsample of executive teams that experience pseudo exogenous shocks to their social connectedness. Taken together, our results underscore the importance of teamwork among executives in the forecast generation process