An Investigation into the Connection between Language Proficiency and Text Analysis Abilities in English Learners

This study’s objective is to evaluate whether or not there is a correlation between students’ command of the English language and their analytical prowess with regard to written material. Through quantitative and qualitative study on students with varied degrees of linguistic proficiency, it has been found that an increase in one’s level of linguistic competence is strongly and favorably associated with an increase in one’s ability for textual analysis. This discovery was made on students with varying levels of linguistic proficiency. Learners who have a higher degree of language competency are able to more effectively absorb vocabulary, grammatical structure, and logical links in the discourse when reading and interpreting English texts. This is because they have a better understanding of the English language. As a consequence of this, they are capable of performing text analysis in a manner that is both more effective and more accurate than before. This article’s goal is to give instructional strategies for learners of all language levels in order to optimize the process of strengthening those learners’ ability to evaluate texts. The target audience for this article is learners of all language levels. When these strategies are utilized, educators will be provided with practical recommendations that will assist them in more effectively directing students toward mastery of the basic text analysis skills. The outcomes of this study may, in some way, have an impact on the educational practice of teaching English as a second language

Vulnerability assessment of the fishery system in China’s coastal provinces since 2000

Coastal fishery systems are vital for both the environment and the economy, and at present, they face heightened vulnerability due to global climate change and natural disasters. A clearer understanding of the challenges that the system presents can be obtained by examining the vulnerabilities of fishery systems. This study employed a vulnerability scoping diagram framework and a multi-indicator approach combined with the entropy weight method for assigning weights to systematically evaluate the vulnerabilities of fishery systems in China’s coastal provinces. The spatiotemporal variation characteristics of vulnerability were analyzed and characterized, and the primary obstacles that affect vulnerability are discussed. The findings suggest that China’s coastal provinces’ fishery systems display vulnerability in terms of both time and space. From a temporal perspective, Liaoning, Hebei, and Shandong provinces exhibited an increasing trend in vulnerability, while Tianjin, Jiangsu, Zhejiang, Shanghai, Fujian, Guangdong, Guangxi, and Hainan showed decreasing trends. From a spatial perspective, Hainan and Liaoning’s fishery systems exhibited extremely high vulnerability in most years. In contrast, Tianjin consistently experienced extremely low vulnerability in most years. From the perspective of obstacles, the main factor was the funding for the extension of aquaculture technology, and this remained the primary obstacle factor across all years. The findings are significant for enhancing our understanding of vulnerability in fishery systems and for strengthening disaster prevention and mitigation measures. The results provide robust support for the improvement of management and the protection of fishery systems

catena-Poly[[[(1,10-phenanthroline)copper(I)]-μ-cyanido] ethanol hemisolvate]

In the title coordination polymer, {[Cu(CN)(C12H10N2)]·0.5C2H5OH}n, there are two CuI ions, two 1,10-phenanthroline (phen) ligands and two cyanide ions in the asymmetric unit along with a highly disordered ethanol solvent mol­ecule, which was modelled as being disordered over two sets of sites in a 0.829 (7):0.171 (7) ratio. The orientation/ordering of the C and N atoms of the cyanide ions could not be determined in the present refinement and they were modelled as being statistically disordered. Both copper ions are coordinated by an N,N′-bidentate phen ligand and two cyanide ligands, generating distorted tetra­hedral CuN2 Q 2 (Q = C or N) tetra­hedra. The μ-cyanide ligands link the metal ions, forming a zigzag chain propagating in [001]. The chains are cross-linked by numerous aromatic π–π stacking contacts between adjacent phen rings [minimum centroid–centroid separation = 3.620 (3) Å]

N-Benzyl­pyridin-2-amine

In the title compound, C12H12N2, the dihedral angle between the benzene and pyridine rings is 67.63 (8)°. Mol­ecules are linked into centrosymmetric dimers by a simple inter­molecular N—H⋯N hydrogen bond with graph-set motif R 2 2(8)

Self-consistent simulations of beam-beam interaction in future e + e - circular colliders including beamstrahlung and longitudinal coupling impedance

For the past generation {e}^{+}{e}^{\ensuremath{-}} storage ring colliders, we usually used natural bunch length or its impedance lengthened value in beam-beam simulations instead of considering the impedance directly. In the future colliders, such as FCC-ee and CEPC, the beam-beam interaction becomes essentially three dimensional. In order to increase the luminosity, the future accelerators will collide very intense beams of high energy with low emittances and small beta functions at the collision points exploiting the crab waist collision scheme with a large Piwinski angle. For these extreme parameters several new effects become important for the collider performance such as beamstrahlung, coherent X-Z instability, 3D flip-flop so that the longitudinal beam dynamics should be also treated in a self-consistent manner. In this paper we describe the numerical code for the self-consistent 3D beam-beam simulations including beamstrahlung and the longitudinal beam coupling impedance and study interplay of different effects arising in beam-beam collisions of the future colliders

N-(1-Naphth­yl)benzene­sulfonamide

In the title compound, C16H13NO2S, the C—SO2—NH—C torsion angle is −70.1 (2)°. The dihedral angle between the planes of the naphthyl ring system and the phenyl ring is 34.67 (4)°. In the crystal, mol­ecules are linked by inter­molecular N—H⋯O hydrogen bonds into chains along [100]. There are also π–π inter­actions between adjacent naphthyl groups [inter­planar spacing = 3.541 (3) Å] for mol­ecules stacked along [100]

Seed Feature Maps-based CNN Models for LEO Satellite Remote Sensing Services

Deploying high-performance convolutional neural network (CNN) models on low-earth orbit (LEO) satellites for rapid remote sensing image processing has attracted significant interest from industry and academia. However, the limited resources available on LEO satellites contrast with the demands of resource-intensive CNN models, necessitating the adoption of ground-station server assistance for training and updating these models. Existing approaches often require large floating-point operations (FLOPs) and substantial model parameter transmissions, presenting considerable challenges. To address these issues, this paper introduces a ground-station server-assisted framework. With the proposed framework, each layer of the CNN model contains only one learnable feature map (called the seed feature map) from which other feature maps are generated based on specific rules. The hyperparameters of these rules are randomly generated instead of being trained, thus enabling the generation of multiple feature maps from the seed feature map and significantly reducing FLOPs. Furthermore, since the random hyperparameters can be saved using a few random seeds, the ground station server assistance can be facilitated in updating the CNN model deployed on the LEO satellite. Experimental results on the ISPRS Vaihingen, ISPRS Potsdam, UAVid, and LoveDA datasets for semantic segmentation services demonstrate that the proposed framework outperforms existing state-of-the-art approaches. In particular, the SineFM-based model achieves a higher mIoU than the UNetFormer on the UAVid dataset, with 3.3x fewer parameters and 2.2x fewer FLOPs.Comment: 11 page

TFormer: A Transmission-Friendly ViT Model for IoT Devices

Deploying high-performance vision transformer (ViT) models on ubiquitous Internet of Things (IoT) devices to provide high-quality vision services will revolutionize the way we live, work, and interact with the world. Due to the contradiction between the limited resources of IoT devices and resource-intensive ViT models, the use of cloud servers to assist ViT model training has become mainstream. However, due to the larger number of parameters and floating-point operations (FLOPs) of the existing ViT models, the model parameters transmitted by cloud servers are large and difficult to run on resource-constrained IoT devices. To this end, this paper proposes a transmission-friendly ViT model, TFormer, for deployment on resource-constrained IoT devices with the assistance of a cloud server. The high performance and small number of model parameters and FLOPs of TFormer are attributed to the proposed hybrid layer and the proposed partially connected feed-forward network (PCS-FFN). The hybrid layer consists of nonlearnable modules and a pointwise convolution, which can obtain multitype and multiscale features with only a few parameters and FLOPs to improve the TFormer performance. The PCS-FFN adopts group convolution to reduce the number of parameters. The key idea of this paper is to propose TFormer with few model parameters and FLOPs to facilitate applications running on resource-constrained IoT devices to benefit from the high performance of the ViT models. Experimental results on the ImageNet-1K, MS COCO, and ADE20K datasets for image classification, object detection, and semantic segmentation tasks demonstrate that the proposed model outperforms other state-of-the-art models. Specifically, TFormer-S achieves 5% higher accuracy on ImageNet-1K than ResNet18 with 1.4$\times$ fewer parameters and FLOPs.Comment: IEEE Transactions on Parallel and Distributed System

Bis[2-(1H-benzimidazol-2-yl)benzoato]copper(II) dihydrate

In the title compound, [Cu(C14H9N2O2)2]·2H2O, the Cu(II) ion lies on a centre of symmetry and is four-coordinated by two N atoms and two O atoms from two 2-(1H-benzimidazol-2-yl)benzoate ligands in a square-planar environment. The benzimidazol and benzyl rings form a dihedral angle of 42.8 (5)°. The mol­ecule contains two H-bonded carboxyl O acceptors and two H-bonded N—H donors in the benzimidazol groups, which inter­act with two symmetry-related uncoordinated water mol­ecules so that neighboring mol­ecular units are linked by (O—H)water⋯Ocarbox­yl hydrogen bonds with an R 2 4(8) graph-set motif, generating a helical chain in the a-axis direction. These chains are, in turn, inter­connected by (N—H)benzimidazol⋯Owater hydrogen bonds, forming a three-dimensional supra­molecular network