Measurement of the pairwise kinematic Sunyaev-Zeldovich effect with Planck and BOSS data

We present a new measurement of the kinetic Sunyaev-Zeldovich effect (kSZ) using Planck cosmic microwave background (CMB) and Baryon Oscillation Spectroscopic Survey (BOSS) data. Using the `LowZ North/South' galaxy catalogue from BOSS DR12, and the group catalogue from BOSS DR13, we evaluate the mean pairwise kSZ temperature associated with BOSS galaxies. We construct a `Central Galaxies Catalogue' (CGC) which consists of isolated galaxies from the original BOSS data set, and apply the aperture photometry (AP) filter to suppress the primary CMB contribution. By constructing a halo model to fit the pairwise kSZ function, we constrain the mean optical depth to be $\bar{\tau}=(0.53\pm0.32)\times10^{-4}(1.65\,\sigma)$ for `LowZ North CGC', $\bar{\tau}=(0.30\pm0.57)\times10^{-4}(0.53\,\sigma)$ for `LowZ South CGC', and $\bar{\tau}=(0.43\pm0.28)\times10^{-4}(1.53\,\sigma)$ for `DR13 Group'. In addition, we vary the radius of the AP filter and find that the AP size of $7\,{\rm arcmin}$ gives the maximum detection for $\bar{\tau}$. We also investigate the dependence of the signal with halo mass and find $\bar{\tau}=(0.32\pm0.36)\times10^{-4}(0.8\,\sigma)$ and $\bar{\tau}=(0.67\pm0.46)\times10^{-4}(1.4\,\sigma)$ for `DR13 Group' with halo mass restricted to, respectively, less and greater than its median halo mass, $10^{12}\, h^{-1}{\rm M}_{\odot}$. For the `LowZ North CGC' sample restricted to $M_{\rm h} \gtrsim 10^{14}\, h^{-1}{\rm M}_\odot$ there is no detection of the kSZ signal because these high mass halos are associated with the high-redshift galaxies of the LowZ North catalogue, which have limited contribution to the pairwise kSZ signals.Comment: 11 pages, 11 figures, 2 table

Multicomponent bi-superHamiltonian KdV systems

It is shown that a new class of classical multicomponent super KdV equations is bi-superHamiltonian by extending the method for the verification of graded Jacobi identity. The multicomponent extension of super mKdV equations is obtained by using the super Miura transformation

A Mixed‑Methods Exploration of the Developmental Trajectory of Autonomous Motivation in Graduate Medical Learners

Self-determination theory (SDT), when applied to curricular construction, emphasizes curiosity, self-awareness, and resilience. Physicians need these qualities to face the challenges of clinical practice. SDT offers a lens for medical educators to track learner development toward sustainable, rewarding careers. This study describes the changes observed in learner communications about feelings of competence, relatedness, and autonomy across a 3-year family medicine training program designed to develop activated, lifelong learners

The R-matrix of the U_q(d_4(3)) algebra and g_2(1) affine Toda field theory

The R-matrix of the U_q(d_4(3)) algebra is constructed in the 8-dimensional fundamental representation. Using this result an exact S-matrix is conjectured for the imaginary coupled g_2(1) affine Toda field theory, the structure of which is found to be very similar to the previously investigated S-matrix of d_4(3) Toda theory. It is shown that this S-matrix is consistent with the results for the case of real coupling using the breather-particle correspondence. For q a root of unity it is argued that the theory can be restricted to yield Phi(11|12) perturbations of WA_2 minimal models.Comment: 18 pages, LaTeX file. Some comments added, typos and mistakes in the references are corrected. Problems with Postscript generation are fixe

A heteroleptic diradical Cr(iii) complex with extended spin delocalization and large intramolecular magnetic exchange

Successive chemical reductions of the heteroleptic complex [(tpy)Cr III(tphz)] 3+(tpy = terpyridine; tphz = tetrapyridophenazine) give rise to the mono- and di-radical redox isomers, [(tpy)Cr III(tphz? -)] 2+and [(tpy? -)Cr III(tphz? -)] +, respectively. As designed, the optimized overlap of the involved magnetic orbitals leads to extremely strong magnetic interactions between theS= 3/2 metal ion andS= 1/2 radical spins, affording well isolatedS T= 1 andS T= 1/2 ground states at room temperature. </p

Liver haemangioma: common and uncommon findings and how to improve the differential diagnosis

Haemangiomas are common focal liver lesions, generally detected in the work-up of asymptomatic patients. From the pathological point of view, they can be classified as small (capillary) or large, with cavernous vascular spaces that may show thrombosis, calcifications and hyalinisation. The polymorphic imaging appearance of haemangiomas depends on their histological features and flow pattern. The widespread use of cross-sectional imaging has allowed an increased detection rate and a better characterisation of this benign tumour. Recent developments of ultrasound (US), computed tomography (CT) and magnetic resonance imaging (MRI) providing high spatial and temporal resolution, together with the use of new contrast agents and/or pulse sequences has broadened the spectrum of imaging findings, contributing to diagnostic refinement in difficult cases. The scope of the present article is to provide an overview of the range of appearances of haemangiomas, explored with recent cross-sectional imaging modalities, emphasising its atypical findings as explored by temporally resolved contrast-enhanced imaging

Using Redox-Active πbridging Ligand as a Control Switch of Intramolecular Magnetic Interactions

Intramolecular magnetic interactions in the dinuclear complexes [(tpy)­Ni­(tphz)­Ni­(tpy)]^<i>n</i>+ (<i>n</i> = 4, 3, and 2; tpy, terpyridine; tphz, tetrapyridophenazine) were tailored by changing the oxidation state of the pyrazine-based bridging ligand. While its neutral form mediates a weak antiferromagnetic (AF) coupling between the two <i>S</i> = 1 Ni­(II), its reduced form, tphz^•–, promotes a remarkably large ferromagnetic exchange of +214(5) K with Ni­(II) spins. Reducing twice the bridging ligand affords weak Ni–Ni interactions, in marked contrast to the Co­(II) analogue. Those experimental results, supported by a careful examination of the involved orbitals, provide a clear understanding of the factors which govern strength and sign of the magnetic exchange through an aromatic bridging ligand, a prerequisite for the rational design of strongly coupled molecular systems and high <i>T</i>_C molecule-based magnets

Can GPT models be Financial Analysts? An Evaluation of ChatGPT and GPT-4 on mock CFA Exams

Large Language Models (LLMs) have demonstrated remarkable performance on a wide range of Natural Language Processing (NLP) tasks, often matching or even beating state-of-the-art task-specific models. This study aims at assessing the financial reasoning capabilities of LLMs. We leverage mock exam questions of the Chartered Financial Analyst (CFA) Program to conduct a comprehensive evaluation of ChatGPT and GPT-4 in financial analysis, considering Zero-Shot (ZS), Chain-of-Thought (CoT), and Few-Shot (FS) scenarios. We present an in-depth analysis of the models' performance and limitations, and estimate whether they would have a chance at passing the CFA exams. Finally, we outline insights into potential strategies and improvements to enhance the applicability of LLMs in finance. In this perspective, we hope this work paves the way for future studies to continue enhancing LLMs for financial reasoning through rigorous evaluation

DocLLM: A layout-aware generative language model for multimodal document understanding

Enterprise documents such as forms, invoices, receipts, reports, contracts, and other similar records, often carry rich semantics at the intersection of textual and spatial modalities. The visual cues offered by their complex layouts play a crucial role in comprehending these documents effectively. In this paper, we present DocLLM, a lightweight extension to traditional large language models (LLMs) for reasoning over visual documents, taking into account both textual semantics and spatial layout. Our model differs from existing multimodal LLMs by avoiding expensive image encoders and focuses exclusively on bounding box information to incorporate the spatial layout structure. Specifically, the cross-alignment between text and spatial modalities is captured by decomposing the attention mechanism in classical transformers to a set of disentangled matrices. Furthermore, we devise a pre-training objective that learns to infill text segments. This approach allows us to address irregular layouts and heterogeneous content frequently encountered in visual documents. The pre-trained model is fine-tuned using a large-scale instruction dataset, covering four core document intelligence tasks. We demonstrate that our solution outperforms SotA LLMs on 14 out of 16 datasets across all tasks, and generalizes well to 4 out of 5 previously unseen datasets.Comment: 16 pages, 4 figure