Deep Learning for Unified Table and Caption Detection in Scientific Documents

This study explores the extraction of tables and their corresponding captions from scientific documents, aiming to enhance the capabilities of information extraction and analysis. Although there have been significant advancements in table extraction and analysis, there remains a gap in extracting tables along with their respective captions, which encapsulate the complete informational context. This research focuses on selecting and fine-tuning deep learning models while creating specific datasets for the chosen task. By utilizing a subset of the TableBank dataset and implementing manual annotation, the study employs Faster R-CNN and Mask R-CNN models hosted by LayoutParser, which is pre-trained on the PubLayNet dataset. The overall training pipeline is implemented using the Detectron2 framework. The experimental phases involve a systematic increase in dataset size and document layout complexity, along with extensive hyperparameter searches to improve overall detection accuracy. The results indicate that the fine-tuned models demonstrate high accuracy and robustness towards the proposed methodologies in extracting document elements from the scientific documents. Notably, the Mask R-CNN with the ResNeXt-101 backbone achieved optimal results, highlighting the importance of model and backbone architecture, dataset variability, and hyperparameter tuning. These findings open doors for future research applications that might utilize the combined context of document elements in diverse document scenarios, facilitating better knowledge extraction

Yarsagumba collection and marketing: A key income source of people in Api Nampa conservation area, Darchula, Nepal

Yarsagumba the Himalayan gold rush is the major part of the economy of the himalayan people in the Darchula distict. Our study was conducted in Khandeshwori region of the the Darchula district to quantify the contribution of Yarsagumba on the total household income of the harvester and to reveal the problems releated to its harvesting and selling. Income from Yarshagumba accounted upto 68% in this region. Geo-physical problems were observed most during collection along with significant conflicts and lower productivity. Price variation is the major market problem of those Yarshagumba harvesting peoples. Social factors like family size, adult members and educational factors have significant impact in total collection and income. The highest price obtained was Rs.18408.33, average price was Rs.15308.33 and the lowest price was Rs. 10205. Benefit to cost or expenses (BC) ratio found in research area was 5.13. Having sharp eye vision school children were taken for the collection and have to leave school for time. Although the data is emerging on medicinal use and market of Yarshagumba little systematic research has explored village level harvesting practice and socioeconomic impacts, especially in this region of Nepal

Prevalence of anemia and mortality among anemic patients with COVID-19 in a tertiary care setting in Nepal

Introduction: The COVID-19 pandemic first detected in December 2019 has claimed so many lives globally as well as in Nepal. Inflammatory changes in SARS-CoV-2 infection can lead to anemia. This study aims to find the prevalence of anemia and mortality among anemic patients in COVID patients admitted to a tertiary care centre in Nepal. Method: A descriptive cross-sectional study with data collected retrospectively between May 2021 to February 2022 on patients with proven COVID-19 admitted to Patan Hospital. Result: Among 890, anemia was prevalent in 296(33.25%) (CI 95%, 30.17-36.35) patients which was more among the female population. The mean hemoglobin was 10.68±1.62 g/dl in anemic patients. Mild anemia was present in 215(72.6%) patients followed by moderate in 64(21.6%) patients and severe in 17(5.8%) patients. The mortality in anemic patients was 43(14.5%). Conclusion: One third of COVID-19 patients admitted to Patan Hospital had anemia which was found to be similar to studies done in similar setting. One in four COVID-19 patients with anemia had died was found to be lower than other studies done in similar settings

Search for gravitational-lensing signatures in the full third observing run of the LIGO-Virgo network

Gravitational lensing by massive objects along the line of sight to the source causes distortions of gravitational wave-signals; such distortions may reveal information about fundamental physics, cosmology and astrophysics. In this work, we have extended the search for lensing signatures to all binary black hole events from the third observing run of the LIGO--Virgo network. We search for repeated signals from strong lensing by 1) performing targeted searches for subthreshold signals, 2) calculating the degree of overlap amongst the intrinsic parameters and sky location of pairs of signals, 3) comparing the similarities of the spectrograms amongst pairs of signals, and 4) performing dual-signal Bayesian analysis that takes into account selection effects and astrophysical knowledge. We also search for distortions to the gravitational waveform caused by 1) frequency-independent phase shifts in strongly lensed images, and 2) frequency-dependent modulation of the amplitude and phase due to point masses. None of these searches yields significant evidence for lensing. Finally, we use the non-detection of gravitational-wave lensing to constrain the lensing rate based on the latest merger-rate estimates and the fraction of dark matter composed of compact objects

Search for eccentric black hole coalescences during the third observing run of LIGO and Virgo

Despite the growing number of confident binary black hole coalescences observed through gravitational waves so far, the astrophysical origin of these binaries remains uncertain. Orbital eccentricity is one of the clearest tracers of binary formation channels. Identifying binary eccentricity, however, remains challenging due to the limited availability of gravitational waveforms that include effects of eccentricity. Here, we present observational results for a waveform-independent search sensitive to eccentric black hole coalescences, covering the third observing run (O3) of the LIGO and Virgo detectors. We identified no new high-significance candidates beyond those that were already identified with searches focusing on quasi-circular binaries. We determine the sensitivity of our search to high-mass (total mass M>70 M⊙) binaries covering eccentricities up to 0.3 at 15 Hz orbital frequency, and use this to compare model predictions to search results. Assuming all detections are indeed quasi-circular, for our fiducial population model, we place an upper limit for the merger rate density of high-mass binaries with eccentricities 0<e≤0.3 at 0.33 Gpc−3 yr−1 at 90\% confidence level

Ultralight vector dark matter search using data from the KAGRA O3GK run

Among the various candidates for dark matter (DM), ultralight vector DM can be probed by laser interferometric gravitational wave detectors through the measurement of oscillating length changes in the arm cavities. In this context, KAGRA has a unique feature due to differing compositions of its mirrors, enhancing the signal of vector DM in the length change in the auxiliary channels. Here we present the result of a search for U(1)B−L gauge boson DM using the KAGRA data from auxiliary length channels during the first joint observation run together with GEO600. By applying our search pipeline, which takes into account the stochastic nature of ultralight DM, upper bounds on the coupling strength between the U(1)B−L gauge boson and ordinary matter are obtained for a range of DM masses. While our constraints are less stringent than those derived from previous experiments, this study demonstrates the applicability of our method to the lower-mass vector DM search, which is made difficult in this measurement by the short observation time compared to the auto-correlation time scale of DM

Comparative analysis of knowledge and management practices of insect pests of maize among IPM adopters and non-adopters in Sindhupalchok, Nepal

Integrated pest management (IPM) is a decision-based approach that involves optimizing the pest population below the economic threshold by the coordinated use of multiple tactics in an economically and environmentally sound manner. The adoption of IPM in farming practices prevents long-term pest damage by combining biological control, modification of cultural practices, habitual manipulation, and use of resistant varieties. In Nepal, mostly in hilly regions, haphazard chemical pesticide application has inevitable effects on human health, the environment, and the ecosystem. The haphazard chemical pesticide application in Sindhupalchok, Nepal originated mostly due to a knowledge gap in the identification of the stages of the lifecycle of pests, and the distinction between beneficial and harmful insects.  To compare the effectiveness of management practices between IPM adopters and non-adopters this study was framed for six months in Sangachokgadi municipality, Sindhupalchok, Nepal.  The knowledge gap among the maize growers in Sindhupalchok was assessed using both primary and secondary data collection methods. For primary data collection a comprehensive and structured questionnaire, face-to-face interview, phone call interview, and Key Informant Interview was conducted. Similarly, secondary data was collected from various articles and publications from Maize Zone, the Ministry of Agriculture and Livestock Development (MoALD), Nepal Agriculture Research Council (NARC), and National Maize Research Program (NMRP). The collected data were then analyzed (descriptive statistics, chi-square test, and indexing) by using computer software packages i.e., Statistical Package for Social Science (SPSS) version 26, and Microsoft Excel 2010. The analyzed data revealed maize growers adopting IPM practices for crop management are known to have significantly better knowledge of the life cycle of pests, were able to distinguish between beneficial and harmful insects, and had knowledge of appropriate fertilizer doses.  Further, the findings revealed IPM adopters had better knowledge of chemical pesticide handling which could minimize the chemical hazards among the farmers

Open data from the first and second observing runs of Advanced LIGO and Advanced Virgo

Advanced LIGO and Advanced Virgo are monitoring the sky and collecting gravitational-wave strain data with sufficient sensitivity to detect signals routinely. In this paper we describe the data recorded by these instruments during their first and second observing runs. The main data products are gravitational-wave strain time series sampled at 16384 Hz. The datasets that include this strain measurement can be freely accessed through the Gravitational Wave Open Science Center at http://gw-openscience.org, together with data-quality information essential for the analysis of LIGO and Virgo data, documentation, tutorials, and supporting software