bluuebunny/crossref_metadata_2025_split huggingface dataset:
Localization Using DeepLab in Document Images Taken by Smartphones
Authors: Baniadamdizaj Shima 
Published: July 2022

AbstractThe seamless integration of statistics from virtual and paper files could be very crucial for the know-how control of efficient. A handy manner to obtain that is to digitize a report from a picture. This calls for the localization of the report in the picture. Several approaches are deliberate to resolve this hassle; however, they are supported historical picture method strategies that are not robust to intense viewpoints and backgrounds. Deep Convolutional Neural Networks (CNNs), on the opposite hand, have been validated to be extraordinarily strong to versions in heritage and perspective of view for item detection and classification duties. Inspired by their robustness and generality, we advocate a CNN-primarily based totally technique for the correct localization of files in real-time. We advocate the new utilization of Neural Networks (NNs) for the localization hassle as a key factor detection hassle. The proposed technique ought to even localize snapshots that don't have a very square shape. Also, we used a newly amassed dataset that has extra tough duties internal and is in the direction of a slipshod user. The result is knowledgeable in 3 specific classes of snapshots and our proposed technique has 100% accuracy on easy one and 77% on average. The result is as compared with the maximum famous report localization strategies and cell applications.
Performance Comparison of Deep Residual Networks-Based Super Resolution Algorithms Using Thermal Images: Case Study of Crowd Counting
Authors: Rizvi Syed Zeeshan , Farooq Muhammad Umar , Raza Rana Hammad 
Published: July 2022

AbstractHumans are able to perceive objects only in the visible spectrum range which limits the perception abilities in poor weather or low illumination conditions. The limitations are usually handled through technological advancements in thermographic imaging. However, thermal cameras have poor spatial resolutions compared to RGB cameras. Super-resolution (SR) techniques are commonly used to improve the overall quality of low-resolution images. There has been a major shift of research among the Computer Vision researchers towards SR techniques particularly aimed for thermal images. This paper analyzes the performance of three deep learning-based state-of-the-art SR algorithms namely Enhanced Deep Super Resolution (EDSR), Residual Channel Attention Network (RCAN) and Residual Dense Network (RDN) on thermal images. The algorithms were trained from scratch for different upscaling factors of ×2 and ×4. The dataset was generated from two different thermal imaging sequences of BU-TIV benchmark. The sequences contain both sparse and highly dense type of crowds with a far field camera view. The trained models were then used to super-resolve unseen test images. The quantitative analysis of the test images was performed using common image quality metrics such as PSNR, SSIM and LPIPS, while qualitative analysis was provided by evaluating effectiveness of the algorithms for crowd counting application. After only 54 and 51 epochs of RCAN and RDN respectively, both approaches were able to output average scores of 37.878, 0.986, 0.0098 and 30.175, 0.945, 0.0636 for PSNR, SSIM and LPIPS respectively. The EDSR algorithm took the least computation time during both training and testing because of its simple architecture. This research proves that a reasonable accuracy can be achieved with fewer training epochs when an application-specific dataset is carefully selected.
Normalization and Bias in Time Series Data
Authors: Asesh Aishwarya 
Published: July 2022

AbstractData normalization is an important preprocessing step in data mining and Machine Learning (ML) technique. Finding an acceptable approach to deal with time series normalization, on the other hand, is not an easy process. This is because most standard normalizing approaches rely on assumptions that aren’t true for the vast majority of time series. The first is that all time series are stationary, which means that their statistical characteristics, such as mean and standard deviation, do not vary over time. The time series volatility is assumed to be uniform in the second assumption. These concerns are not addressed by any of the approaches currently accessible in the literature. This research provides theoretical and experimental evidence, that normalizing time series data, can prove to be of utmost value by trimming non necessary data points and achieving minimum information loss, by using the concept of Minimal Time Series Representation (MTSR).
Case Studies in Biocultural Diversity from Southeast Asia—Traditional Ecological Calendars, Folk Medicine and Folk Names
Authors: Franco F. Merlin , Knudsen Magne , Hassan Noor Hasharina 
Published: July 2022

AbstractBiocultural diversity refers to the dynamic interrelationship between the Earth’s biological, cultural, and
linguistic diversity. The concept draws strength from the fact that biodiversity-rich regions of the world are also rich in cultural and linguistic diversities. This volume adds to scholarship in biocultural diversity with case studies from geographical Southeast Asia. The chapters presented in the volume, based on research in Brunei Darussalam, Indonesia, Malaysia, the Philippines, and Northeast India demonstrate i) how traditional ecological calendars and calendar keepers serve as repositories of knowledge on landscapes and their resources, ii) the importance of folk medicine for healthcare in contemporary Southeast Asia, and iii) how folk names of flora and fauna serve as condensed forms of traditional knowledge on biodiversity. While highlighting the importance of customary ways of knowing and categorizing the environment in areas such as resource management, conservation, and healthcare, the chapters also demonstrate that traditional environmental knowledge and the practical skills which accompany it are not necessarily widely shared and are under constant threat. As Southeast Asia marches forward in pursuit of economic growth, it would also have to ensure that its biocultural diversity stays alive, nurturing local communities for generations to come.
Calendar Keepers: The Unsung Heroes in Indigenous Landscape Management
Authors: Lokho Kreni , Franco F. Merlin , Narasimhan D. 
Published: July 2022

AbstractIndigenous communities use their calendric knowledge to carry out landscape management activities. Using the example of the Mao Naga community of Northeast India, we demonstrate that keepers of such calendars are facilitators of landscape management activities of the community. The Mao Naga community chief once served as the chief calendar keeper from whom calendric information flowed to village-level calendar keepers. The chief calendar keeper processed information on the skyscape and local seasonal indicators and disseminated it to the village-level calendar keepers, and other community members. The calendar keepers determined the dates for sacred holidays calledgenna, and festivals which in turn determined landscape management activities that include agriculture, hunting and fire management. The village-level calendar keepers combined calendric information received from the chief calendar keeper with their own observation of skyscape and local seasonal indicators. The observation of local seasonal indicators by the village-level calendar keepers enabled them to keep the ecological calendar dynamic, flexible and relevant to the landscape. The Mao Council has introduced a printed traditional calendar which makes it easier for determining lunar months and festival days. But it lacks information on sacred holidays and local seasonal indicators. We recommend that the printed traditional calendar be developed further to include information on sacred holidays and local seasonal indicators. The improvised printed ecological calendar should then be administered by the calendar keepers.
The Intersection of Kedayan Folk Medicine and Traditional Ecological Calendar
Authors: Bakar Nurzahidah , Franco F. Merlin , Hassan Noor Hasharina 
Published: July 2022

AbstractA noteworthy feature of folk and codified traditional medicines is their ability to combine drug-based therapies with spiritual therapies. This unique combination differentiates them from the drug-based approach employed by modern biomedicine and renders them highly relevant to contemporary healthcare. Like folk medicine, traditional ecological calendars also embody the traditional knowledge held by local communities. However, the influence of ecological calendars on folk medicine has been largely underexplored; studies have mostly considered ecological calendars and folk medicine independent of each other. In this chapter, we provide an understanding of the traditional knowledge of the Kedayan community of Brunei Darussalam with specific reference to their folk medicine and their traditional ecological calendar. Data was collected through in-depth interviews that the first author held with sixteen knowledgeable elders from the Kedayan community of Brunei Darussalam between January 2018 and June 2018. The Kedayan classify causes of ailments broadly into two: ailments caused by factors of the unseen realm and factors of the seen realm. The former are treated by spiritual therapies and the latter using practices rooted in the humoral concept of well-being. The Kedayan traditional ecological calendar stipulates the right time for harvesting medicinal herbs and administering them. It links the potency of medicinal herbs to tidal cycles and also provides information on the seasonal occurrence of ailments. By focussing on the interface between the Kedayan folk medicine and the ecological calendar, the chapter draws attention to a hitherto underexplored area in folk medicine.
Culture, Ethics of Care, Community, and Language in Online Learning Environments: Supporting Adult Educators in a Digital Era
Authors: Hedayati-Mehdiabadi Amir , Gunawardena Charlotte N. 
Published: July 2022

AbstractConsidering the increase in the number of online courses and programs across the globe, preparing educators for creating inclusive online environments for learners to thrive is imperative. The worldwide pandemic of 2020, in a sense, only accelerated the already rising trends of online course offerings in higher education and further expanded it to other sections of education and geographical locations. Reviewing the existing literature and building on the authors’ experiences, this chapter uses a cultural and ethical lens to examine issues related to community and language to contribute to the design of equitable and inclusive online learning environments. Although these issues impact all segments of the educational enterprise, given the authors’ experiences with adult learning, the focus in this chapter will be on adults as learners.
Applicability of Electrostatic Separation on Talc-Containing Mineral Samples for Production of a High-Grade Talc Concentrate in Comparison to Flotation
Authors: Luckeneder Christoph , Gehringer Sabrina , Flachberger Helmut 
Published: July 2022

AbstractIn the course of this study, the applicability of electrostatic separation and flotation for processing a mineral sample rich in talc was examined. The aim was a comparison of those two separation processes and the concentrates obtained. Furthermore the separation behaviour of the silicates and carbonates was a goal of the examination. The electrostatic separation test work was conducted with a triboelectric belt separator. The feed, an artificially prepared mineral sample, was composed of four components: talc, quartz, dolomite, and magnesite. The lab scale test work was done exclusively at the Chair of Mineral Processing, Montanuniversitaet Leoben, Austria.
Assessing urban sustainability: a proposal for indicators, metrics and scoring—a case study in Colombia
Authors: Jorge-Ortiz Andrea , Braulio-Gonzalo Marta , Bovea María Dolores 
Published: July 2022

AbstractAlthough there are different methodologies for evaluating the sustainability of urban areas in Latin America, they usually apply to a specific city as a whole and cannot be generalized to other cities; besides, they do not address smaller urban units, such as the district, and rarely approach all sustainability dimensions. This study aims to propose a methodology for the evaluation of urban sustainability in the context of a country, whose approach can be adapted to evaluate the urban sustainability of any country or territory, taking into account environmental, social, economic and institutional aspects. The methodology is structured as an ordered protocol in five stages: (I) revision of PROGRAMMES on urban sustainability, (II) revision and cluster of indicators, (III) definition of indicators and metrics, (IV) definition of the scoring method of indicators, and (V) graphical representation of indicators. Accordingly, the methodology was applied in the context of Colombia, particularly to the medium-sized city of Mosquera, as a case study, and both as a whole and by socio-economic strata. As a result, a set of indicators with their corresponding metrics and score in sustainability levels was obtained, as well as a graphical representation that facilitates the interpretation of results and enables the comparison of different urban areas within the city. The results made it possible to identify vulnerable or degraded urban areas, and on a lower level, to detect specific critical aspects that require the implementation of improvements geared towards a more sustainable urban environment. The overall conclusion is that there is room for improvement in the municipality, since its level of sustainability ranges, generally, from 1 to 2 on a scale of 3.
A closer look at referring expressions for video object segmentation
Authors: Bellver Miriam , Ventura Carles , Silberer Carina , Kazakos Ioannis , Torres Jordi , Giro-i-Nieto Xavier 
Published: July 2022

AbstractThe task of Language-guided Video Object Segmentation (LVOS) aims at generating binary masks for an object referred by a linguistic expression. When this expression unambiguously describes an object in the scene, it is namedreferring expression(RE). Our work argues that existing benchmarks used for LVOS are mainly composed of trivial cases, in which referents can be identified with simple phrases. Our analysis relies on a new categorization of the referring expressions in the DAVIS-2017 and Actor-Action datasets into trivial and non-trivial REs, where the non-trivial REs are further annotated with seven RE semantic categories. We leverage these data to analyze the performance of RefVOS, a novel neural network that obtains competitive results for the task of language-guided image segmentation and state of the art results for LVOS. Our study indicates that the major challenges for the task are related to understanding motion and static actions.
Contemporary Contamination of Urban Floodplains in Chennai (India)
Authors: Bellanova Luisa , Uphoff Fabienne , Bellanova Piero , Engels Nina , P. Prabu , Pulipatti Yaswanth , Lehmkuhl Frank , Schulte Phillip , Reicherter Klaus , Schwarzbauer Jan 
Published: July 2022

AbstractFast growing coastal population centers face an increasing vulnerability to several emission sources of anthropogenic and industrial pollutants. The ongoing industrialization in emerging countries increases the environmental and human risk for people living in coastal megacities, especially in the global south of Asia. Extreme weather events, such as heavy rainfalls and resulting flood events, are projected to increase in frequency in the foreseen future, facing an increasing vulnerability to monsoon-induced floods and the release and distribution of xenobiotics causing harm to communities and the environment along a river’s pathway. To endeavor the unknown risks posed by these toxic floods and to assess the associated contamination distribution, the preserved organic geochemical signature from floodplain sediments is studied.This investigation evaluates the inorganic and organic pollutant assemblage in ten surface sediments along the Adyar and Cooum river in the urban areas of Chennai (southern India). Potentially toxic elements (Cr, Ni, Cu, Zn, Pb) show a continuous concentration decrease downstream. Four main groups of persistent organic pollutants have been detected: petrogenic pollutants (hopanes, PAHs), urban wastewater pollutants (LABs, DEHA, methyl-triclosan, octocrylene), technical compounds (Mesamoll®, DPE, NBFA), and pesticides (DDX). While most organic compounds show source specific properties, the definite sources for others remain vague based on the multitude of potential sources and diffusiveness of anthropogenic emissions. The chosen approaches have shown that urban wastewater pollutants and several technical compounds are suitable to assess the anthropogenic-induced contamination in floodplain sediments. However, sedimentary archives in fast-growing, urbanized environments are influenced and superimposed by anthropogenic alterations.
Tribological study on the surface modification of metal-on-polymer bioimplants
Authors: Shen Gang , Zhang Jufan , Culliton David , Melentiev Ruslan , Fang Fengzhou 
Published: July 2022

AbstractThe tribological performance of artificial joints is regarded as the main factor of the lifespan of implanted prostheses. The relationship between surface roughness and coefficient of friction (COF) under dry and lubricated conditions is studied. Results show that under dry test, friction coefficient is not reduced all the time with a decrease in surface roughness. On the contrary, a threshold of roughness value is observed, and frictional force increases again below this value. This critical value lies between 40 and 100 nm in Sa (roughness). This phenomenon is due to the transfer of friction mechanisms from abrasion to adhesion. Under wet test, COF always decreases with reduction in surface roughness. This result is mainly attributed to the existence of a thin layer of lubricant film that prevents the intimate contact of two articulating surfaces, thus greatly alleviating adhesion friction. Furthermore, surface texturing technology is successful in improving the corresponding tribological performance by decreasing friction force and mitigating surface deterioration. The even-distribution mode of texturing patterns is most suitable for artificial joints. By obtaining the optimal surface roughness and applying texturing technology, the tribological performance of polymer-based bioimplants can be greatly enhanced.
The role of liver kinase B1 in tumor progression through regulation of lipid metabolism
Authors: Geng Jialu , Zhang Yanghe , Meng Qingfei , Yan Hang , Wang Yishu 
Published: July 2022

AbstractThe somatic mutation of liver kinase B1 (LKB1) has been implicated in various tumors, which is reflected in the survival, proliferation, and metastasis of tumor cells. However, the regulation of LKB1 in lipid metabolism, a process that is involved in tumor progression is not completely clear. We conclude that LKB1 deficiency results in abnormal expression and activation of multiple molecules related to lipid metabolism which locate downstream of AMP-activated protein kinase (AMPK) or salt-induced kinase (SIK). Abnormal lipid metabolism induced by LKB1 deficiency contributes to the proliferation and metastasis of tumor cells through energy regulation.
Bikini Line Approach for Cosmetic Laparoscopic Cholecystectomy
Authors: Ibrahim Mostafa , Abdelgawaad Moamen Shalkamy , Hanna Ragai Sobhi 
Published: July 2022

Abstract
Four-port laparoscopic cholecystectomy (LC) is a standard procedure. Several alternative approaches have been described to make trocar scars invisible. This study describes and was successfully administered as a pilot for feasibility and safety of a bikini line port for better aesthetic results. In patients with symptomatic cholelithiasis undergoing LC between June 2021 and December 2021, bikini line ports were used in 67 patients. With the patient in the supine position, the first trocar (11 mm) was inserted into the abdomen through the umbilicus. The other three trocars were placed in the lower abdomen at the bikini line with the help of the camera. Standard instruments were used to perform the surgery. The mean operative time was 54.66 SD 14.1 min. No intraoperative or postoperative adverse events took place. The median follow-up for this cohort was 24 weeks. Cosmetic results were satisfactory for all patients. The use of one umbilical camera port and the other three ports in the bikini line in the lower abdomen completely hides the scars from the ports’ incision. The technique was quickly adopted by regular laparoscopic surgeons with usual instruments, much to the satisfaction of patients.
The Regulation of Alcohol Marketing in France: The Loi Evin at Thirty
Authors: Friant-Perrot Marine , Garde Amandine 
Published: July 2022

AbstractWhen adopted in 1991, the French Loi Evin was pioneering as one of the first in the world to regulate alcohol marketing as extensively. This short contribution assesses whether it remains fit for purpose over 30 years later. To this effect, it assesses its main provisions, considers the legislative amendments that have ensued as well as the extensive interpretation French courts have given of its scope, before concluding that the prospects for its revisions are limited in the near future.
Voluntary Registries to Support Improved Interaction Between Police and People Living with Dementia
Authors: Ross Heather M. , Bowman Diana M. , Wani Jessica M. 
Published: July 2022

AbstractThis paper provides an overview of the societal impact of a rising dementia population and examines the legal and ethical implications posed by voluntary registries as a community-oriented solution to improve interactions between law enforcement and individuals with dementia. It provides a survey of active voluntary registries across the United States, with a focus on Arizona, which has the highest projected growth for individuals living with dementia in the country.
High-Priced Sickle Cell Gene Therapies Threaten to Exacerbate US Health Disparities and Establish New Pricing Precedents for Molecular Medicine
Authors: Tessema Frazer A. , Sarpatwari Ameet , Rand Leah Z. , Kesselheim Aaron S. 
Published: July 2022

AbstractGene therapies to treat sickle cell disease are in development and are expected to have high costs. The large eligible population size — by far, the largest for a gene therapy — poses daunting budget challenges and threatens to exacerbate health disparities for Black patients, who make up the vast majority of American sickle cell patients.
Ordered Beta Regression: A Parsimonious, Well-Fitting Model for Continuous Data with Lower and Upper Bounds
Authors: Kubinec Robert 
Published: July 2022

AbstractI propose a new model, ordered Beta regression, for continuous distributions with both lower and upper bounds, such as data arising from survey slider scales, visual analog scales, and dose–response relationships. This model employs the cut point technique popularized by ordered logit to fit a single linear model to both continuous (0,1) and degenerate [0,1] responses. The model can be estimated with or without observations at the bounds, and as such is a general solution for these types of data. Employing a Monte Carlo simulation, I show that the model is noticeably more efficient than ordinary least squares regression, zero-and-one-inflated Beta regression, rescaled Beta regression, and fractional logit while fully capturing nuances in the outcome. I apply the model to a replication of the Aidt and Jensen (2014,European Economic Review72, 52–75) study of suffrage extensions in Europe. The model can be fit with the R packageordbetaregto facilitate hierarchical, dynamic, and multivariate modeling.