Table Structure Extraction with Bi-directional Gated Recurrent Unit Networks

Tables present summarized and structured information to the reader, which makes table structure extraction an important part of document understanding applications. However, table structure identification is a hard problem not only because of the large variation in the table layouts and styles, but also owing to the variations in the page layouts and the noise contamination levels. A lot of research has been done to identify table structure, most of which is based on applying heuristics with the aid of optical character recognition (OCR) to hand pick layout features of the tables. These methods fail to generalize well because of the variations in the table layouts and the errors generated by OCR. In this paper, we have proposed a robust deep learning based approach to extract rows and columns from a detected table in document images with a high precision. In the proposed solution, the table images are first pre-processed and then fed to a bi-directional Recurrent Neural Network with Gated Recurrent Units (GRU) followed by a fully-connected layer with soft max activation. The network scans the images from top-to-bottom as well as left-to-right and classifies each input as either a row-separator or a column-separator. We have benchmarked our system on publicly available UNLV as well as ICDAR 2013 datasets on which it outperformed the state-of-the-art table structure extraction systems by a significant margin.Comment: Proceedings of the 15th International Conference on Document Analysis and Recognition (ICDAR) 2019, Sydney, Australi

Current Knowledge and Therapeutic Strategies of Herbal Medicine for Acute Diarrhea

Diarrhea is a common gastrointestinal problem characterized by loose watery stool and mild to severe dehydration. Annually, about 1.7–5 billion new cases of diarrhea were reported. In developing countries, it is more common, where young kids have diarrhea approximately three times/year. In 2013, 1.26 million deaths occurred due to diarrhea, whereas in 1990, the figure was slightly higher (2.58 million). In 2012, diarrhea was the second most common reason of death (11%, n = 0.76 million) in children less than 5 years. Although various synthetic drugs are being prescribed as standard therapy for diarrhea, they have side effects. It is possible to prescribe the herbal medicine for diarrhea, which is safe and effective. In this study, medicinal plants discussed are proven to be scientifically active in diarrheal diseases. This study reviews about current medicinal plants used in the treatment of diarrhea. The use of medicinal plants for diarrhea results in improvement of the symptom. Moreover, studies on large scale are needed to characterize the beneficial role of medicinal plants in the treatment of diarrhea

Design of high gain base station antenna array for mm-wave cellular communication systems

Millimeter wave (mm-Wave) wireless communication systems require high gain antennas to overcome path loss effects and thereby enhance system coverage. This paper presents the design and analysis of an antenna array for high gain performance of future mm-wave 5G communication systems. The proposed antenna is based on planar microstrip technology and fabricated on 0.254 mm thick dielectric substrate (Rogers-5880) having a relative permittivity of 2.2 and loss tangent of 0.0009. The single radiating element used to construct the antenna array is a microstrip patch that has a configuration resembling a two-pronged fork. The single radiator has a realized gain of 7.6 dBi. To achieve the gain required by 5G base stations, a 64-element array antenna design is proposed which has a bore side gain of 21.2 dBi at 37.2 GHz. The 8 × 8, 8 × 16, and 8 × 32 antenna array designs described here were simulated and optimized using CST Microwave Studio, which is a 3D full-wave electromagnetic solver. The overall characteristics of the array in terms of reflection-coefficient and radiation patterns makes the proposed design suitable for mm-Wave 5G and other communication systems.Dr. Mohammad Alibakhshikenari acknowledges support from the CONEX-Plus programme funded by Universidad Carlos III de Madrid and the European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No. 801538. In addition, this work was partially supported by Ministerio de Ciencia, Innovación y Universidades, Gobierno de España (Agencia Estatal de Investigación, Fondo Europeo de Desarrollo Regional -FEDER-, European Union) under the research grant PID2021-127409OB-C31 CONDOR. The authors also sincerely appreciate funding from Researchers Supporting Project number (RSP2023R58), King Saud University, Riyadh, Saudi Arabia

Metasurface-based wideband MIMO antenna for 5G millimeter-wave systems

This paper presents a metasurface based multiple-input multiple-output (MIMO) antenna with a wideband operation for millimeter-wave 5G communication systems. The antenna system consists of four elements placed with a 90 degree shift in order to achieve a compact MIMO system while a 2× 2 non-uniform metasurface (total four elements) is placed at the back of the MIMO configuration to improve the radiation characteristics of it. The overall size of the MIMO antenna is 24× 24 mm2 while the operational bandwidth of the proposed antenna system ranges from 23.5-29.4 GHz. The peak gain achieved by the proposed MIMO antenna is almost 7dB which is further improved up to 10.44 dB by employing a 2× 2 metasurface. The total efficiency is also observed more than 80% across the operating band. Apart from this, the MIMO performance metrics such as envelope correlation coefficient (ECC), diversity gain (DG), and channel capacity loss (CCL) are analyzed which demonstrate good characteristics. All the simulations of the proposed design are carried out in computer simulation technology (CST) software, and measured results reveal good agreement with the simulated one which make it a potential contender for the upcoming 5G communication systems.This work was supported in part by the Universidad Carlos III de Madrid and the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant Agreement No 801538, and in part by the the Ministerio de Ciencia, Innovación y Universidades, Gobierno de España (MCIU/AEI/FEDER,UE) under Grant RTI2018-095499-B-C31

Relationship between gaming disorder across various dimensions among PUBG players: a machine learning-based cross-sectional study

BackgroundPlayerUnknown’s battlegrounds (PUBG), a widely played multiplayer online game, has sparked interest and concern regarding its impact on players. This study explored the relationship between factors such as cultivation level, motivation, religious engagement, gaming disorder, and addiction among PUBG players.MethodsThis study employed a convenience sampling technique to select a sample of 500 PUBG players. An Artificial Neural Network (ANN) model was used to identify the primary factors contributing to the level of cultivation.ResultsMale participants exhibited a higher level of cultivation than their female counterparts did. According to the ANN model, gaming disorder exhibited the greatest normalized importance, with a value of 100%. This was followed by the religious level, which had a normalized importance of 54.6%. Additionally, motivation level and gaming addiction demonstrated normalized importance values of 47.6 and 44.4%, respectively. This study revealed a statistically significant correlation between engaging in PUBG and the cultivation effect observed among respondents.ConclusionThis study highlights several noteworthy factors, including gaming disorder, religious affiliation, motivation level, and gaming addiction. These factors offer valuable insights into understanding gaming behavior and devising effective interventions

Design of high gain base station antenna array for mm-wave cellular communication systems

Millimeter wave (mm-Wave) wireless communication systems require high gain antennas to overcome path loss effects and thereby enhance system coverage. This paper presents the design and analysis of an antenna array for high gain performance of future mm-wave 5G communication systems. The proposed antenna is based on planar microstrip technology and fabricated on 0.254 mm thick dielectric substrate (Rogers-5880) having a relative permittivity of 2.2 and loss tangent of 0.0009. The single radiating element used to construct the antenna array is a microstrip patch that has a configuration resembling a two-pronged fork. The single radiator has a realized gain of 7.6 dBi. To achieve the gain required by 5G base stations, a 64-element array antenna design is proposed which has a bore side gain of 21.2 dBi at 37.2 GHz. The 8 × 8, 8 × 16, and 8 × 32 antenna array designs described here were simulated and optimized using CST Microwave Studio, which is a 3D full-wave electromagnetic solver. The overall characteristics of the array in terms of reflection-coefficient and radiation patterns makes the proposed design suitable for mm-Wave 5G and other communication systems

Utilizing a 5G spectrum for health care to detect the tremors and breathing activity for multiple sclerosis

Utilizing fifth‐generation (5G) sensing in the health care sector with increased capacity and massive spectrum range increases the quality of health care monitoring systems. In this paper, 5G C‐band sensing operating at 4.8 GHz is used to monitor a particular body motion of multiple sclerosis patients, especially the tremors and breathing patterns. The breathing pattern obtained using 5G C‐band technology is compared with the invasive breathing sensor to monitor the subtle chest movements caused due to respiration. The 5G C‐band has a huge spectrum from 1 to 100 GHz, which enhances the capacity and performance of wireless communication by increasing the data rate from 20 Gb/s to 1 Tb/s. The system captures and monitors the wireless channel information of different body motions and efficiently identifies the tremors experienced since each body motion induces a unique imprint that is used for a particular purpose. Different machine learning algorithms such as support vector machine, k‐nearest neighbors, and random forest are used to classify the wireless channel information data obtained for various human activities. The values obtained using different machine learning algorithms for various performance metrics such as accuracy, precision, recall, specificity, Kappa, and F‐measure indicate that the proposed method can efficiently identify the particular conditions experienced by multiple sclerosis patients

Impact of opioid-free analgesia on pain severity and patient satisfaction after discharge from surgery: multispecialty, prospective cohort study in 25 countries

Background: Balancing opioid stewardship and the need for adequate analgesia following discharge after surgery is challenging. This study aimed to compare the outcomes for patients discharged with opioid versus opioid-free analgesia after common surgical procedures.Methods: This international, multicentre, prospective cohort study collected data from patients undergoing common acute and elective general surgical, urological, gynaecological, and orthopaedic procedures. The primary outcomes were patient-reported time in severe pain measured on a numerical analogue scale from 0 to 100% and patient-reported satisfaction with pain relief during the first week following discharge. Data were collected by in-hospital chart review and patient telephone interview 1 week after discharge.Results: The study recruited 4273 patients from 144 centres in 25 countries; 1311 patients (30.7%) were prescribed opioid analgesia at discharge. Patients reported being in severe pain for 10 (i.q.r. 1-30)% of the first week after discharge and rated satisfaction with analgesia as 90 (i.q.r. 80-100) of 100. After adjustment for confounders, opioid analgesia on discharge was independently associated with increased pain severity (risk ratio 1.52, 95% c.i. 1.31 to 1.76; P < 0.001) and re-presentation to healthcare providers owing to side-effects of medication (OR 2.38, 95% c.i. 1.36 to 4.17; P = 0.004), but not with satisfaction with analgesia (beta coefficient 0.92, 95% c.i. -1.52 to 3.36; P = 0.468) compared with opioid-free analgesia. Although opioid prescribing varied greatly between high-income and low- and middle-income countries, patient-reported outcomes did not.Conclusion: Opioid analgesia prescription on surgical discharge is associated with a higher risk of re-presentation owing to side-effects of medication and increased patient-reported pain, but not with changes in patient-reported satisfaction. Opioid-free discharge analgesia should be adopted routinely

Health Capacity and Vulnerability in Context of COVID-19 Outbreak: An Analysis of 185 Countries

Background: The coronavirus disease 2019 (COVID-19) pandemic has affected most countries, afflicting severe damage. Mitigation measures to control the pandemic rely heavily on existing health capacity and vulnerability of each country. The health capacity and vulnerability with respect to COVID-19 outbreak for 185 countries was assessed in this study to identify those where capacity-building needs to be prioritized. Material and methods: The State Parties Annual Reporting data based on WHO International Health Regulations monitoring and evaluation framework was used to extract an indicator for national health capacity. Another indicator for vulnerability was extracted from INFORM epidemic risk index. These metrics were selected after evaluating their complementarity and availability. Results: Among 185 countries, 111 (60%) had health capacities at level 4 and 5 with most of them having vulnerability at level 3 and 4. Twenty-two (11.89%) countries had level 2 health capacity in place coupled with moderate to high vulnerability. Among continents, Europe had best while Africa had worst mean functional capacity and vulnerability scores. Conclusions: The results showed that most countries had sufficient response and reaction capacities to handle the pandemic. However, resources, intensified surveillance, and capacity building should be prioritized in vulnerable countries with ill-equipped national health capacities

Treatment options for paediatric brainstem gliomas

Paediatric brainstem gliomas (BSGs) can be classified broadly into two distinct categories: focal brainstem gliomas (FBSGs) and diffuse intrinsic pontine gliomas (DIPG). The former account for 20% of paediatric BSGs and are mostly indolent lesions with good prognosis. DIPGs constitute the remaining 80%, and are highly aggressive, malignant tumours having a dismal prognosis; being the foremost cause of death in children with brain tumours. Their poor response to treatment regimens is further complicated by their localization in eloquent brainstem areas, thereby making it difficult to establish a standardized framework of therapeutic intervention. In this review, the authors catalogue and appraise current treatment modalities utilized in the management of paediatric BSGs including steroid use, chemotherapy, radiotherapy, and surgery