Efficient Downlink Channel Reconstruction for FDD Multi-Antenna Systems

In this paper, we propose an efficient downlink channel reconstruction scheme for a frequency-division-duplex multi-antenna system by utilizing uplink channel state information combined with limited feedback. Based on the spatial reciprocity in a wireless channel, the downlink channel is reconstructed by using frequency-independent parameters. We first estimate the gains, delays, and angles during uplink sounding. The gains are then refined through downlink training and sent back to the base station (BS). With limited overhead, the refinement can substantially improve the accuracy of the downlink channel reconstruction. The BS can then reconstruct the downlink channel with the uplink-estimated delays and angles and the downlink-refined gains. We also introduce and extend the Newtonized orthogonal matching pursuit (NOMP) algorithm to detect the delays and gains in a multi-antenna multi-subcarrier condition. The results of our analysis show that the extended NOMP algorithm achieves high estimation accuracy. Simulations and over-the-air tests are performed to assess the performance of the efficient downlink channel reconstruction scheme. The results show that the reconstructed channel is close to the practical channel and that the accuracy is enhanced when the number of BS antennas increases, thereby highlighting that the promising application of the proposed scheme in large-scale antenna array systems

A New Species of Genus Laboulbenia (Laboulbeniales) on Craspedophorus formosanus (Coleoptera, Carabidae) from Taiwan, with a Note on Laboulbenia asiatica

Laboulbenia taiwaniana sp. nov. on Craspedophorus formosanus is described from Taiwan and illustrated with photographs. It is characterized by a long, asymmetrical perithecium with an oblique apex and a pale-colored lower wall, a slender, evenly tapered receptacle with cylindrical cell I and II and trapezoidal cell IV, well developed appendages with black septa concentrated in the basal portion of the appendage system, and especially by black septa on the distal end of cell g. Laboulbenia asiatica, which was described from an Asian carabid--- Casnonia sp. ---in 1899 and was illustrated in 1908 by Thaxter, is reviewed and compared with L. taiwaniana morphologically

Tailoring excitonic states of van der Waals bilayers through stacking configuration, band alignment and valley-spin

Excitons in monolayer semiconductors have large optical transition dipole for strong coupling with light field. Interlayer excitons in heterobilayers, with layer separation of electron and hole components, feature large electric dipole that enables strong coupling with electric field and exciton-exciton interaction, at the cost that the optical dipole is substantially quenched (by several orders of magnitude). In this letter, we demonstrate the ability to create a new class of excitons in transition metal dichalcogenide (TMD) hetero- and homo-bilayers that combines the advantages of monolayer- and interlayer-excitons, i.e. featuring both large optical dipole and large electric dipole. These excitons consist of an electron that is well confined in an individual layer, and a hole that is well extended in both layers, realized here through the carrier-species specific layer-hybridization controlled through the interplay of rotational, translational, band offset, and valley-spin degrees of freedom. We observe different species of such layer-hybridized valley excitons in different heterobilayer and homobilayer systems, which can be utilized for realizing strongly interacting excitonic/polaritonic gases, as well as optical quantum coherent controls of bidirectional interlayer carrier transfer either with upper conversion or down conversion in energy

Sensor Selection and Integration to Improve Video Segmentation in Complex Environments

Background subtraction is often considered to be a required stage of any video surveillance system being used to detect objects in a single frame and/or track objects across multiple frames in a video sequence. Most current state-of-the-art techniques for object detection and tracking utilize some form of background subtraction that involves developing a model of the background at a pixel, region, or frame level and designating any elements that deviate from the background model as foreground. However, most existing approaches are capable of segmenting a number of distinct components but unable to distinguish between the desired object of interest and complex, dynamic background such as moving water and high reflections. In this paper, we propose a technique to integrate spatiotemporal signatures of an object of interest from different sensing modalities into a video segmentation method in order to improve object detection and tracking in dynamic, complex scenes. Our proposed algorithm utilizes the dynamic interaction information between the object of interest and background to differentiate between mistakenly segmented components and the desired component. Experimental results on two complex data sets demonstrate that our proposed technique significantly improves the accuracy and utility of state-of-the-art video segmentation technique. © 2014 Adam R. Reckley et al

An Exploration of In-Context Learning for Speech Language Model

Ever since the development of GPT-3 in the natural language processing (NLP) field, in-context learning (ICL) has played an important role in utilizing large language models (LLMs). By presenting the LM utterance-label demonstrations at the input, the LM can accomplish few-shot learning without relying on gradient descent or requiring explicit modification of its parameters. This enables the LM to learn and adapt in a black-box manner. Despite the success of ICL in NLP, little work is exploring the possibility of ICL in speech processing. This study proposes the first exploration of ICL with a speech LM without text supervision. We first show that the current speech LM does not have the ICL capability. With the proposed warmup training, the speech LM can, therefore, perform ICL on unseen tasks. In this work, we verify the feasibility of ICL for speech LM on speech classification tasks.Comment: The first two authors contributed equall

Protein-ligand binding region prediction (PLB-SAVE) based on geometric features and CUDA acceleration

[[abstract]]Background Protein-ligand interactions are key processes in triggering and controlling biological functions within cells. Prediction of protein binding regions on the protein surface assists in understanding the mechanisms and principles of molecular recognition. In silico geometrical shape analysis plays a primary step in analyzing the spatial characteristics of protein binding regions and facilitates applications of bioinformatics in drug discovery and design. Here, we describe the novel software, PLB-SAVE, which uses parallel processing technology and is ideally suited to extract the geometrical construct of solid angles from surface atoms. Representative clusters and corresponding anchors were identified from all surface elements and were assigned according to the ranking of their solid angles. In addition, cavity depth indicators were obtained by proportional transformation of solid angles and cavity volumes were calculated by scanning multiple directional vectors within each selected cavity. Both depth and volume characteristics were combined with various weighting coefficients to rank predicted potential binding regions. Results Two test datasets from LigASite, each containing 388 bound and unbound structures, were used to predict binding regions using PLB-SAVE and two well-known prediction systems, SiteHound and MetaPocket2.0 (MPK2). PLB-SAVE outperformed the other programs with accuracy rates of 94.3% for unbound proteins and 95.5% for bound proteins via a tenfold cross-validation process. Additionally, because the parallel processing architecture was designed to enhance the computational efficiency, we obtained an average of 160-fold increase in computational time. Conclusions In silico binding region prediction is considered the initial stage in structure-based drug design. To improve the efficacy of biological experiments for drug development, we developed PLB-SAVE, which uses only geometrical features of proteins and achieves a good overall performance for protein-ligand binding region prediction. Based on the same approach and rationale, this method can also be applied to predict carbohydrate-antibody interactions for further design and development of carbohydrate-based vaccines. PLB-SAVE is available at http://save.cs.ntou.edu.tw.[[booktype]]電子