A polarization study of the supernova remnant CTB 80

We present a radio polarization study of the supernova remnant CTB 80 based on images at 1420 MHz from the Canadian Galactic plane survey, at 2695 MHz from the Effelsberg survey of the Galactic plane, and at 4800 MHz from the Sino-German 6cm polarization survey of the Galactic plane. We obtained a rotation measure (RM) map using polarization angles at 2695 MHz and 4800 MHz as the polarization percentages are similar at these two frequencies. RM exhibits a transition from positive values to negative values along one of the shells hosting the pulsar PSR B1951+32 and its pulsar wind nebula. The reason for the change of sign remains unclear. We identified a partial shell structure, which is bright in polarized intensity but weak in total intensity. This structure could be part of CTB 80 or part of a new supernova remnant unrelated to CTB 80.Comment: 12 pages, 6 figures, accepted for publication in RA

Lightning Attention-2: A Free Lunch for Handling Unlimited Sequence Lengths in Large Language Models

Linear attention is an efficient attention mechanism that has recently emerged as a promising alternative to conventional softmax attention. With its ability to process tokens in linear computational complexities, linear attention, in theory, can handle sequences of unlimited length without sacrificing speed, i.e., maintaining a constant training speed for various sequence lengths with a fixed memory consumption. However, due to the issue with cumulative summation (cumsum), current linear attention algorithms cannot demonstrate their theoretical advantage in a causal setting. In this paper, we present Lightning Attention-2, the first linear attention implementation that enables linear attention to realize its theoretical computational benefits. To achieve this, we leverage the thought of tiling, separately handling the intra-block and inter-block components in linear attention calculation. Specifically, we utilize the conventional attention computation mechanism for the intra-blocks and apply linear attention kernel tricks for the inter-blocks. A tiling technique is adopted through both forward and backward procedures to take full advantage of the GPU hardware. We implement our algorithm in Triton to make it IO-aware and hardware-friendly. Various experiments are conducted on different model sizes and sequence lengths. Lightning Attention-2 retains consistent training and inference speed regardless of input sequence length and is significantly faster than other attention mechanisms. The source code is available at https://github.com/OpenNLPLab/lightning-attention.Comment: Technical Report. Yiran Zhong is the corresponding author. The source code is available at https://github.com/OpenNLPLab/lightning-attentio

(2-Hydroxy­benzoato-κO 1)[tris­(1-methyl­benzimidazol-2-ylmethyl-κN 3)amine-κN]cobalt(II) perchlorate dimethyl­formamide sesquisolvate

In the title complex, [Co(C7H5O3)(C27H27N7)]ClO4·1.5C3H7NO, the CoII ion is five-coordinated by four N atoms from a tris­(N-methyl­benzimidazol-2-ylmeth­yl)amine (Mentb) ligand and one O atom from a salicylate ligand in a distorted trigonal–bipyramidal geometry with approximate mol­ecular C 3 symmetry. The perchlorate ion is disordered over two sites with equal occupancy. One dimethyl­formamide solvent mol­ecule lies on a general position and is disordered over two coplanar orientations with equal occupancy. A second dimethyl­formamide mol­ecule is disordered about a twofold rotation axis. There is an intra­molecular O—H⋯O hydrogen bond in the cation

Box2Poly: Memory-Efficient Polygon Prediction of Arbitrarily Shaped and Rotated Text

Recently, Transformer-based text detection techniques have sought to predict polygons by encoding the coordinates of individual boundary vertices using distinct query features. However, this approach incurs a significant memory overhead and struggles to effectively capture the intricate relationships between vertices belonging to the same instance. Consequently, irregular text layouts often lead to the prediction of outlined vertices, diminishing the quality of results. To address these challenges, we present an innovative approach rooted in Sparse R-CNN: a cascade decoding pipeline for polygon prediction. Our method ensures precision by iteratively refining polygon predictions, considering both the scale and location of preceding results. Leveraging this stabilized regression pipeline, even employing just a single feature vector to guide polygon instance regression yields promising detection results. Simultaneously, the leverage of instance-level feature proposal substantially enhances memory efficiency (>50% less vs. the state-of-the-art method DPText-DETR) and reduces inference speed (>40% less vs. DPText-DETR) with minor performance drop on benchmarks

Relationship between four tumor-associated bio-markers and prognosis of gastric cancer

Purpose: To investigate the relationship between prognosis of gastric cancer (GC) and the expression of P53, Epidermal growth factor receptor (EGFR), Human epidermal growth factor receptor-2 (HER-2), and Vascular endothelial growth factor (VEGF).Methods: One hundred and forty-seven patients admitted to People's Liberation Army General Hospital (Beijing, China) with diagnosis of locally advanced GC were enrolled in the study. Follow-up data were obtained by outpatient review or telephone follow-up. Expressions of P53, EGFR, HER-2 and VEGF were determined by immunohistochemical staining. The relationship between protein expression, clinico-pathological factors, disease-free survival time (DFS) and overall survival (OS) were analyzed.Results: The expressions of EGER, HER-2, P53 and VEGF in GC were 17.7, 17.0, 41.0 and 55.9%, respectively. The expressions of EGFR and P53 were positively correlated (r = 0.306, p < 0.05), while the expressions of VEGF and HER-2 were negatively correlated (r = -0.2, p < 0.05). The expressions of EGFR, HER-2 and VEGF were not related to the clinico-pathological factors (p > 0.05) while expression of P53 was related only to histological grade (p < 0.05). Univariate analysis showed that OS and DFS were longer (p < 0.05) when P53 was lowly expressed. Multiple-factor analysis revealed that histological grade, infiltration depth and P53 expression were independent factors that influenced DFS.Conclusion: These results indicate that the expression of P53, EGFR, HER2 and VEGF can be used to predict prognosis of GC and screening of patients’ benefits from adjuvant chemotherapy.Keywords: Gastric cancer, Prognosis, Biomarkers, Adjuvant chemotherap

TransNormerLLM: A Faster and Better Large Language Model with Improved TransNormer

We present TransNormerLLM, the first linear attention-based Large Language Model (LLM) that outperforms conventional softmax attention-based models in terms of both accuracy and efficiency. TransNormerLLM evolves from the previous linear attention architecture TransNormer by making advanced modifications that include positional embedding, linear attention acceleration, gating mechanisms, tensor normalization, and inference acceleration and stabilization. Specifically, we use LRPE together with an exponential decay to avoid attention dilution issues while allowing the model to retain global interactions between tokens. Additionally, we propose Lightning Attention, a cutting-edge technique that accelerates linear attention by more than twice in runtime and reduces memory usage by a remarkable four times. To further enhance the performance of TransNormer, we leverage a gating mechanism for smooth training and a new tensor normalization scheme to accelerate the model, resulting in an impressive acceleration of over $20\%$. Furthermore, we develop a robust inference algorithm that ensures numerical stability and consistent inference speed, regardless of the sequence length, showcasing superior efficiency during both training and inference stages. We also implement an efficient model parallel schema for TransNormerLLM, enabling seamless deployment on large-scale clusters and facilitating expansion to even more extensive models, i.e., LLMs with 175B parameters. We validate our model design through a series of ablations and train models with sizes of 385M, 1B, and 7B on our self-collected corpus. Benchmark results demonstrate that our models not only match the performance of state-of-the-art LLMs with Transformer but are also significantly faster. Code is released at: https://github.com/OpenNLPLab/TransnormerLLM.Comment: Technical Report. Yiran Zhong is the corresponding author. Zhen Qin, Dong Li, Weigao Sun, Weixuan Sun, Xuyang Shen contribute equally to this paper. Code is released at: https://github.com/OpenNLPLab/TransnormerLL

Lattice distortion inducing exciton splitting and coherent quantum beating in CsPbI3 perovskite quantum dots

Anisotropic exchange-splitting in semiconductor quantum dots (QDs) results in bright-exciton fine-structure-splitting (FSS) important for quantum information processing. Direct measurement of FSS usually requires single/few QDs at liquid-helium temperatures, because of its sensitivity to QD size and shape, whereas measuring and controlling FSS at an ensemble-level seem to be impossible unless all the dots are made to be nearly the same. Here we report strong bright-exciton FSS up to 1.6 meV in solution-processed CsPbI3 perovskite QDs, manifested as quantum beats in ensemble-level transient absorption at liquid-nitrogen to room temperatures. The splitting is robust to QD size and shape heterogeneity, and increases with decreasing temperature, pointing towards a mechanism associated with orthorhombic distortion of perovskite lattice. Effective-mass-approximation calculations reveal an intrinsic "fine-structure gap" that agrees well with the observed FSS. This gap stems from an avoided crossing of bright-excitons confined in orthorhombically-distorted QDs that are bounded by the pseudocubic {100} family of planes

DisenPOI: Disentangling Sequential and Geographical Influence for Point-of-Interest Recommendation

Point-of-Interest (POI) recommendation plays a vital role in various location-aware services. It has been observed that POI recommendation is driven by both sequential and geographical influences. However, since there is no annotated label of the dominant influence during recommendation, existing methods tend to entangle these two influences, which may lead to sub-optimal recommendation performance and poor interpretability. In this paper, we address the above challenge by proposing DisenPOI, a novel Disentangled dual-graph framework for POI recommendation, which jointly utilizes sequential and geographical relationships on two separate graphs and disentangles the two influences with self-supervision. The key novelty of our model compared with existing approaches is to extract disentangled representations of both sequential and geographical influences with contrastive learning. To be specific, we construct a geographical graph and a sequential graph based on the check-in sequence of a user. We tailor their propagation schemes to become sequence-/geo-aware to better capture the corresponding influences. Preference proxies are extracted from check-in sequence as pseudo labels for the two influences, which supervise the disentanglement via a contrastive loss. Extensive experiments on three datasets demonstrate the superiority of the proposed model.Comment: Accepted by ACM International Conference on Web Search and Data Mining (WSDM'23

Spatial Configuration and Density How Building Density Affects Spatial Arrangement of a Neighbourhood

A large body of research has focused on the various social, environmental and economic ways in which urban density might affect cities. When considering density as one of the elements of urban form, the measurements that studies usually apply, such as net or gross building density, do not have any link to the design of the built form. This paper argues that the same building density can yield different design layouts, thereby emphasising the need for developing other measurements of density in close relationship with design factors. To demonstrate this, several cases with various ranges of density (low, medium and high) were explored through spatial analysis and categorised in three clusters for further study with statistical tests. The results confirm meaningful differences between cases with the same density but different spatial design characteristics. The outcomes also indicate that the category of the cases based on conventional density measures, namely population density and building density (which are commonly used in urban studies), fail to capture design differences when density ranges differ. These results should draw attention to this phenomenon, which appears worthy of further investigation in future studies