Miracle-dz/UniFAR-FTUs huggingface dataset:
SemanticSLAM: Learning based Semantic Map Construction and Robust Camera Localization

Current techniques in Visual Simultaneous Localization and Mapping (VSLAM) estimate camera displacement by comparing image features of consecutive scenes. These algorithms depend on scene continuity, hence requires frequent camera inputs. However, processing images frequently can lead to significant memory usage and computation overhead. In this study, we introduce SemanticSLAM, an end-to-end visual-inertial odometry system that utilizes semantic features extracted from an RGB-D sensor. This approach enables the creation of a semantic map of the environment and ensures reliable camera localization. SemanticSLAM is scene-agnostic, which means it doesn't require retraining for different environments. It operates effectively in indoor settings, even with infrequent camera input, without prior knowledge. The strength of SemanticSLAM lies in its ability to gradually refine the semantic map and improve pose estimation. This is achieved by a convolutional long-short-term-memory (ConvLSTM) network, trained to correct errors during map construction. Compared to existing VSLAM algorithms, SemanticSLAM improves pose estimation by 17%. The resulting semantic map provides interpretable information about the environment and can be easily applied to various downstream tasks, such as path planning, obstacle avoidance, and robot navigation. The code will be publicly available at https://github.com/Leomingyangli/SemanticSLAM
ReachNet : Reachability maps in the presence of obstacles

Calculating an accurate representation of a manipulator’s capabilities supports motion planning and control tasks. The reachability index is one of the measures used to represent a manipulator’s capabilities within the workspace but the impact of obstacles on the reachability index is not extensively explored. The aim of this manuscript was to evaluate the methods of calculating an accurate reachability index distribution amidst environment obstacles. We propose and evaluate two methods for calculating the reachability index distribution where the machine learning approach came to be the faster method which allowed the model to be applicable in real-time mobile base placement of mobile manipulators. The neural network model may also be used for calculating other distributions of workspace quality measures.
Establishment of a Chinese Paremiological Minimum Based on International English Media

Paremiological Minimum (PM) is defined as a set of proverbs that all members of a particular speech community know or an average adult is expected to know (Ďurčo, 2015b). Acquiring such frequently used proverbs will lead to meaningful and effective communication by native speakers or foreign speakers (Mieder, 1993). The study of creating PM has been conducted in many countries globally for at least 50 years, but no researcher has engaged in PM for Chinese language. Classic Chinese proverbs are discourse symbols that embody Chinese values and represent traditional Chinese culture, and are frequently quoted by dignitaries from various countries and overseas media. This study proposes to build a Chinese Paremiological Minimum (CPM) by investigating Chinese proverbs in FACTIVA (2012-2021), from the media of English-language speaking communities with a view to identity the frequently quoted Chinese proverbs. Meantime, four selection criteria are placed emphases on the process of creating CPM: Currency, Internationality, Frequency and Authenticity, namely CIFA frame, different from the previous research approaches which merely focused on the frequency or familiarity for the PM creation. The establishment of CPM is bond to promote a further insight into the Chinese mind, language and culture, resulting in long-term benefits to speakers of other languages and English language learning and teaching in China, for the mastery of PM is an effective way to enhance language proficiency and understanding in intercultural communication.
Improved Semantic Segmentation Adversarial Networks Applied to Industrial Production Datasets

In industrial production, defect detection is a critical task. Traditional methods often require manual visual inspection, which is low in accuracy and time-consuming. As a key technology in the development of deep learning, semantic segmentation can serve as an effective defect detection method, locating the defect position and providing pixel-level semantic segmentation results that describe the shape and size of the defect, significantly improving production efficiency and product quality.Based on the features of the DAGM 2007 industrial optical detection datasets, this paper uses the SegAN network architecture that combines GAN network with semantic segmentation model and makes adjustments and improvements to it. Because low-level semantic information, such as edges and textures, is important for industrial defect detection, more skip connections are introduced to the original architecture to improve the sensitivity of the network to low-level semantic information in the datasets.Experimental results demonstrate that our improvements can effectively improve the Dice and MIoU index of semantic segmentation, achieving significant performance improvement compared to the original architectures.
Segmented exterior-rotor PMSM for increased torque density

Embedded permanent magnets are widely used for electrical machines with interior-rotor. This provides better protection of the magnets and enables the use of an additional reluctance torque for torque density improvements. For external rotors, the use of surface-mounted permanent magnets is common. The following paper analyses the application of inserted magnets at exterior-rotors with segmentation to achieve an increase in torque density.High pole electrical machines are often designed with a fractional-slot concentrated winding which leads to field harmonics. Therefore, an analytical method for qualitative comparison of different winding configurations for using reluctance torque with consideration of stator field harmonics is applied. Besides rotor saliency, the magnetic flux concentration is a positive effect of interior permanent magnets. Here, the flux leakage along mechanical necessary iron bridges is crucial. With the segmented rotor geometry, these iron bridges can be avoided for interior placed magnets. This allows a flux concentration for electrical machines with a high number of pole-pairs. The paper presents a simplified geometry-based approach to describe these improvements. The method is validated with a finite element analysis (FEA) and a prototype with a segmented rotor is built.
Semi-Supervised and Incremental Sequence Analysis for Taxonomic Classification

Metagenomic analysis is vital in determining what organisms are present in a microbial sample and why they are present. In this study, we explore the utility of MMseqs2, a bioinformatics pipeline, for taxonomic classification in metagenomics, focusing on 16S rRNA gene sequences. We evaluate the algorithm's performance in full dataset as well as batch-by-batch incremental processing, and more importantly, we add the capability of semi-supervised classification to this otherwise clustering only algorithm. Incremental updating is important because it allows seamless integration and processing of new data, whereas semi-supervised classification allows taxonomic identification of previously unknown organisms. We also evaluate the different clustering modes offered by MMseqs2, and compare MMseqs2 to our previously developed semi-supervised incremental algorithm SSI-VSEARCH. We show that MMseqs2's built-in clusterupdate function works well, and our semi-supervised classification capability adds new functionality to this bioinformatics processing pipeline.
Deficiency of diacylglycerol Kinase ζ promotes Beclin1-mediated autophagy via the mTOR/TFEB signaling pathway: Relevance to maladaptive cardiac hypertrophy

The activation Gq protein-coupled receptors (GPCRs) is a crucial factor contributing to maladaptive cardiac hypertrophy, and dysregulation of autophagy is implicated in its prohypertrophic effects. Previous studies have shown that diacylglycerol kinase zeta (DGKζ) can suppress cardiac hypertrophy by inhibiting the diacylglycerol (DAG)-PKC pathway in response to mechanical strain or growth agonists such as endothelin-1 (ET-1). However, the involvement of DGKζ in autophagy regulation remains poorly understood. In this study, we aimed to investigate the role of DGKζ in autophagy regulation during maladaptive cardiac hypertrophy. We found that Beclin1-mediated autophagy was involved in the development of maladaptive cardiac hypertrophy and dysfunction in response to prohypertrophic challenges of transverse aortic constriction (TAC) or ET-1. Deficiency of DGKζ promoted Beclin1-mediated autophagy, aggravated adverse cardiac remodeling, and cardiac dysfunction, which could be ameliorated by genetic deletion of Beclin1 or TFEB. Mechanistically, the deficiency of DGKζ disrupted the activation of AKT/mTOR signaling, the association between mTOR and TFEB, and favored the nuclear translocation of TFEB from the cytoplasm, leading to enhanced activation of Beclin1-mediated autophagy through ULK1/Beclin1 signaling and TFEB-dependent Beclin1 transcription. Taken together, these results suggest that the mechanisms by which DGKζ alleviates pathological cardiac hypertrophy may involve the regulation of Beclin1-mediated autophagy through the mTOR/TFEB signaling pathway.
Impact of interactive chemistry of stratospheric ozone on Southern Hemisphere paleoclimate simulation

A series of numerical simulations of the mid‐Holocene (6 kyr B.P.) climate are performed by using an Earth System Model of the Meteorological Research Institute of the Japan Meteorological Agency to investigate the impact of stratospheric ozone distribution, which is modulated by the change in orbital elements of the Earth, on the surface climate. The results of interactive ozone chemistry calculations for the mid‐Holocene and preindustrial periods are compared with those of the corresponding experiments in the fifth Coupled Model Intercomparison Project (CMIP5), in which the ozone distribution was prescribed to the 1850 Common Era level. The contribution of the interactive ozone chemistry in a quasi‐equilibrium state reveals a significant anomaly of up to +1.7 K in the Antarctic region for the annual mean zonal mean surface air temperature. This impact on the surface climate is explained by a similar mechanism to the cooling influence of the Antarctic ozone hole but opposite in sign: Weakening of the westerly jet associated with the Southern Annular Mode provides weakening of equatorward ocean surface current, sea ice retreat, and then warm sea surface temperature and surface air temperature. All the mid‐Holocene runs by CMIP5 models with the prescribed ozone had cold bias in sea surface temperature when compared with geological proxy data, whereas the bias is reduced in our simulations by using interactive ozone chemistry. We recommend that climate models include interactive sea ice and ozone distribution that are consistent with paleosolar insolation.
Eﬃcient Simulation of Clustering Jumps with CIR Intensity

We introduce a broad family of generalised self-exciting point processes with CIR-type intensities, and we develop associated algorithms for their exact simulation. The underlying models are extensions of the classical Hawkes process, which already has numerous applications in modelling the arrival of events with clustering or contagion eﬀect in ﬁnance, economics
An Aperture-Coupled-Cross-Resonator FSS Based Spatial Filtering Patch Antenna Array

The employment of Massive MIMO technology in 5G communication results in a large number of RF channels in the base station. Therefore, the base station will suffer from the huge burden of equipping discrete bandpass filters under the traditional filtering strategy. An alternative filtering strategy called spatial filtering characterizes direct covering frequency selective surface (FSS) on multi-channel antenna array of base station and is expected to greatly relax the need for discrete bandpass filters. An aperture-coupled-cross-resonator (ACCR) FSS based spatial filtering scheme is investigated in this study. A low-profile spatial filtering patch array (LPSFPA) with thickness of <inline-formula> <tex-math notation="LaTeX">$0.07\lambda _{0}$ </tex-math></inline-formula> and operating around 3.6GHz is constructed by placing an asymmetrical ACCR FSS tightly upon a patch antenna array with a half-period lateral shift. A good out-of-band suppression at both band-edges and enhanced in-band impedance bandwidth are achieved when the main beam is scanned with an elevation angle range of 0° to 30° and arbitrary azimuth angle. To verify the design, a finite LPSFPA sample whose main beam can be directed to <inline-formula> <tex-math notation="LaTeX">$\theta _{\mathrm {b}}= 0^{\mathrm {\circ }}$ </tex-math></inline-formula>, <inline-formula> <tex-math notation="LaTeX">$15^{\mathrm {\circ }}$ </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">$30^{\mathrm {\circ }}$ </tex-math></inline-formula> in E plane by different phasing and power-dividing networks is fabricated and tested. The measured results show that the fabricated LPSFPA sample is superior to the ordinary radiation patch array without the ACCR FSS in terms of both the impedance bandwidth and out-of-band suppression for various main beam directions. For the normal-beam case, the measured −10dB impedance bandwidth is from 3.6-3.8 GHz; the measured out-of-band suppression level of peak realized gain is more than 19 dB in the lower band-edge from 3.2-3.5 GHz and 17 dB in the upper band-edge from 3.9-4.2 GHz. The proposed spatial filtering scheme has no negative influence on the radiation performance of the radiation patch array.
Inland and Near-Shore Water Profiles Derived from the High-Altitude Multiple Altimeter Beam Experimental Lidar (MABEL)

ABSTRACT Jasinski, M. ; Stoll, J.; Cook, W. ; Ondrusek, M. ; Stengel, E. , and Brunt, K. , 2016. Inland and near-shore water profiles derived from the high-altitude Multiple Altimeter Beam Experiemental Lidar (MABEL). In: Brock, J.C. ; Gesch, D.B. ; Parrish, C.E. ; Rogers, J.N. , and Wright, C.W. (eds.), Advances in Topobathymetric Mapping, Models, and Applications. Journal of Coastal Research, Special Issue, No. 76, pp. 44–55. Coconut Creek (Florida), ISSN 0749-0208. The Advanced Topographic Laser Altimeter System (ATLAS) on the Ice, Cloud, and Land Elevation Satellite (ICESat-2) mission is a six beam, low energy, high repetition rate, 532-nm laser transmitter with photon counting detectors. Although designed primarily for detecting height changes in ice caps, sea ice, and vegetation, the polar-orbiting satellite will observe global surface water during its designed three-year life span, including inland water bodies, coasts, and open oceans. In preparation for the mission, an ICESat-2 prototype, the Multiple Altimeter Beam Experimental Lidar (MABEL), was built and flown on high-altitude aircraft experiments over a range of inland and near-shore targets. The purpose was to test the ATLAS concept and to provide a database for developing an algorithm that detects along track surface water height and light penetration under a range of atmospheric and water conditions. The current analysis examines the datasets of three MABEL transects observed from 20 km above ground of coastal and inland waters conducted in 2012 and 2013. Transects ranged from about 2 to 12 km in length and included the middle Chesapeake Bay, the near-shore Atlantic coast at Virginia Beach, and Lake Mead. Results indicate MABEL's high capability for retrieving surface water height statistics with a mean height precision of approximately 5–7 cm per 100-m segment length. Profiles of attenuated subsurface backscatter, characterized using a Signal to Background Ratio written in Log10 base, or LSBR0, were observed over a range of 1.3 to 9.3 m, depending on water clarity and atmospheric background. Results indicate that observable penetration depth, although primarily dependent on water properties, was greatest when the solar background rate was low. Near-shore bottom reflectance was detected only at the Lake Mead site down to a maximum of 10 m under a clear night sky and low turbidity of approximately 1.6 Nephelometric Turbidity Units (NTU). The overall results suggest that the feasibility of retrieving operational surface water height statistics from space-based photon counting systems such as ATLAS is very high for resolutions down to about 100 m, even in partly cloudy conditions. The capability to observe subsurface backscatter profiles is achievable but requires much longer transects of several hundreds of meters.
AtptTrack: Asymmetric Transformer Tracker With Prior Templates

Recently, Siamese-based trackers have emerged as the predominant focus in single object tracking research. However, the majority of these works concentrate on improving the backbone network of the tracker to enhance its performance, thereby overlooking the significant impact that the template and search region of the input to the tracker have on tracking accuracy. To address the aforementioned issues, we propose an Asymmetrical Transformer Tracker with Prior Templates (AtptTrack), consisting of a tracking branch and a template update branch. The function of the tracking branch is to receive input image pairs and tracking results to complete the tracking task. In the template update branch, an updating strategy is employed to compute the cosine similarity between the template and the tracking result. Based on this, four prior templates are generated, serving as essential supplementary features for the template. These prior templates are concatenated with the tracking results to create a hybrid template for subsequent tracking, enhancing the richness and accuracy of the template features. To further enrich the information content of the template and search region, we propose multi-scale patch embeddings to process input image pairs, which can enhance the completeness and continuity of the object features. Our tracker has been extensively tested on five benchmarks. The experiments demonstrate that our tracker achieves the state-of-the-art performance. Particularly on the OTB100 dataset, our tracker AtptTrack achieves an AUC score of 0.709, and it outperformed the second-place tracker in the deformation and occlusion challenges by 2.99% and 0.5%, respectively.
Determinant of stunting among children under-five years: A nationwide study in Zambia

Background: Stunting cases among children represent one of the most serious issues in human development. Zambia, in particular, has a higher number of stunting cases in Africa.Objective: The purpose of this research was to analyze the prevalence and determinant of stunting among children under-five years in Zambia. Methods: This study utilized data from the 2018 Zambia Demographic Health Survey (ZDHS), with a total of 1,710 surveys selected. We observed variables related to mothers, children, and the environment to assess stunting. Chi-Square and Binary Logistic Regression were used for data analysis.Results: A total of 22,16% children under five years in Zambia had a stunting. We found that factors such as low birth weight (<2500 grams) (OR = 3.24; 95% CI = 2.163-4.869), mothers with no education (OR = 1.80; 95% CI = 0.681-4.760), those with the poorest wealth index (OR = 2.30; 95% CI = 1.341-3.943), intervals between previous children less than 24 months (OR = 1.58; 95% CI = 1.107-2.270), and breastfeeding for more than 6 months (OR = 4.499; 95% CI = 3.179-6.67) were associated with a higher likelihood of stunting in Zambia.Conclusions: Our study demonstrates that stunting is associated with family and household factors, as well as breastfeeding practices. Policymakers should consider implementing structured policies to address stunting, particularly for expectant mothers, as a long-term solution.
Optical magnetic field enhancement by strong coupling for high sensitivity sensing

We theoretically investigate the coupling effect of propagating surface plasmon polariton (PSPP) and magnetic plasmon (MP) resonance in the simple optical metamaterial, which is composed of periodic gold nanowire grating, SiO2 spacer, and gold film on the SiO2 substrate. By changing the period of the gold nanowire grating, the strong coupling between MP resonance and PSPP forms the hybrid modes and presents the strong anti-crossing. The interesting phenomenon of Rabi splitting as large as 97.8 meV appears. The enhanced magnetic field intensity and sensitivity of the proposed structure are up to 550 times and 585 nm/RIU, respectively, which shows great potential in the field of label-free biosensing field.
Early Stopping of Non-productive Performance Testing Experiments Using Measurement Mutations

Modern software projects often incorporate some form of performance testing into their development cycle, intending to detect changes in performance between commits or releases. Performance testing generally relies on experimental evaluation using various benchmark workloads. To detect performance changes reliably, benchmarks must be executed many times to account for variability in the measurement results. While considered best practice, this approach can become prohibitively expensive when the number of versions and benchmark workloads increases. To alleviate the cost of performance testing, we propose an approach for the early stopping of non-productive experiments that are unlikely to detect a performance bug in a particular benchmark. The stopping conditions are based on benchmark-specific thresholds determined from historical data modified to emulate the potential effects of software changes on benchmark performance. We evaluate the approach on the GraalVM benchmarking project and show that it can eliminate about 50% of the experiments if we can afford to ignore about 15% of the least significant performance changes.
FBSE-Based JPEG Image Compression

The purpose of image compression is to minimize the storage space required to store images and maintain the relevant information in them. In this letter, we presented a Fourier–Bessel series expansion (FBSE)-based image compression technique, which is motivated by the joint photographic experts group (JPEG), which uses discrete cosine transform (DCT) in the process. FBSE of order-0 has structural similarity with DCT and provides real representation for real signals. The proposed methodology has used FBSE in place of DCT for image compression. The article compares the compression ratio of both the methodology, and results have shown better compression performance of FBSE-based image compression.