Tradition and mortality : evidence from twin infanticide in Africa

Mortality of twins relative to singletons is no greater today among African ethnicities that once practiced twin infanticide. We introduce data on historic twin infanticide and merge it with birth records from 23 African countries. We use the full sample, a border sample of adjacent societies with and without past twin infanticide, and a sample of twins. All three samples provide no evidence that past twin infanticide predicts greater differential twin mortality today. Twin infanticide and negative attitudes towards twins were suppressed by Africans, missionaries, and colonial governments. Where these channels were weak, we find evidence of greater twin mortality today

SwinFIR: Revisiting the SwinIR with Fast Fourier Convolution and Improved Training for Image Super-Resolution

Transformer-based methods have achieved impressive image restoration performance due to their capacities to model long-range dependency compared to CNN-based methods. However, advances like SwinIR adopts the window-based and local attention strategy to balance the performance and computational overhead, which restricts employing large receptive fields to capture global information and establish long dependencies in the early layers. To further improve the efficiency of capturing global information, in this work, we propose SwinFIR to extend SwinIR by replacing Fast Fourier Convolution (FFC) components, which have the image-wide receptive field. We also revisit other advanced techniques, i.e, data augmentation, pre-training, and feature ensemble to improve the effect of image reconstruction. And our feature ensemble method enables the performance of the model to be considerably enhanced without increasing the training and testing time. We applied our algorithm on multiple popular large-scale benchmarks and achieved state-of-the-art performance comparing to the existing methods. For example, our SwinFIR achieves the PSNR of 32.83 dB on Manga109 dataset, which is 0.8 dB higher than the state-of-the-art SwinIR method

V2I-Based Platooning Design with Delay Awareness

This paper studies the vehicle platooning system based on vehicle-to-infrastructure (V2I) communication, where all the vehicles in the platoon upload their driving state information to the roadside unit (RSU), and RSU makes the platoon control decisions with the assistance of edge computing. By addressing the delay concern, a platoon control approach is proposed to achieve plant stability and string stability. The effects of the time headway, communication and edge computing delays on the stability are quantified. The velocity and size of the stable platoon are calculated, which show the impacts of the radio parameters such as massive MIMO antennas and frequency band on the platoon configuration. The handover performance between RSUs in the V2I-based platooning system is quantified by considering the effects of the RSU's coverage and platoon size, which demonstrates that the velocity of a stable platoon should be appropriately chosen, in order to meet the V2I's Quality-of-Service and handover constraints

GraphPrompt: Biomedical Entity Normalization Using Graph-based Prompt Templates

Biomedical entity normalization unifies the language across biomedical experiments and studies, and further enables us to obtain a holistic view of life sciences. Current approaches mainly study the normalization of more standardized entities such as diseases and drugs, while disregarding the more ambiguous but crucial entities such as pathways, functions and cell types, hindering their real-world applications. To achieve biomedical entity normalization on these under-explored entities, we first introduce an expert-curated dataset OBO-syn encompassing 70 different types of entities and 2 million curated entity-synonym pairs. To utilize the unique graph structure in this dataset, we propose GraphPrompt, a prompt-based learning approach that creates prompt templates according to the graphs. GraphPrompt obtained 41.0% and 29.9% improvement on zero-shot and few-shot settings respectively, indicating the effectiveness of these graph-based prompt templates. We envision that our method GraphPrompt and OBO-syn dataset can be broadly applied to graph-based NLP tasks, and serve as the basis for analyzing diverse and accumulating biomedical data.Comment: 12 page

Towards the assignments for 11D21^{1}D_{2} and 13D21^{3}D_{2} meson nonets

In this work, we investigate the mass spectrum of $1^{1}D_{2}$ and $1^{3}D_{2}$ meson nonets in the framework of the meson mass matrix and Regge phenomenology. The results are compared with the values from different phenomenological models and may be useful for the assignment of the $1^{1}D_{2}$ and $1^{3}D_{2}$ meson nonets in the future.Comment: 13 pages, 6 figure

The Effects of Deregulated Ribosomal Biogenesis in Cancer

Ribosomes are macromolecular ribonucleoprotein complexes assembled from RNA and proteins. Functional ribosomes arise from the nucleolus, require ribosomal RNA processing and the coordinated assembly of ribosomal proteins (RPs), and are frequently hyperactivated to support the requirement for protein synthesis during the self-biosynthetic and metabolic activities of cancer cells. Studies have provided relevant information on targeted anticancer molecules involved in ribosome biogenesis (RiBi), as increased RiBi is characteristic of many types of cancer. The association between unlimited cell proliferation and alterations in specific steps of RiBi has been highlighted as a possible critical driver of tumorigenesis and metastasis. Thus, alterations in numerous regulators and actors involved in RiBi, particularly in cancer, significantly affect the rate and quality of protein synthesis and, ultimately, the transcriptome to generate the associated proteome. Alterations in RiBi in cancer cells activate nucleolar stress response-related pathways that play important roles in cancer-targeted interventions and immunotherapies. In this review, we focus on the association between alterations in RiBi and cancer. Emphasis is placed on RiBi deregulation and its secondary consequences, including changes in protein synthesis, loss of RPs, adaptive transcription and translation, nucleolar stress regulation, metabolic changes, and the impaired ribosome biogenesis checkpoint