bluuebunny/crossref_metadata_2025_split huggingface dataset:
Cellulose and the role of hydrogen bonds: not in charge of everything
Authors: Wohlert Malin , Benselfelt Tobias , Wågberg Lars , Furó István , Berglund Lars A. , Wohlert Jakob 
Published: November 2021

AbstractIn the cellulose scientific community, hydrogen bonding is often used as the explanation for a large variety of phenomena and properties related to cellulose and cellulose based materials. Yet, hydrogen bonding is just one of several molecular interactions and furthermore is both relatively weak and sensitive to the environment. In this review we present a comprehensive examination of the scientific literature in the area, with focus on theory and molecular simulation, and conclude that the relative importance of hydrogen bonding has been, and still is, frequently exaggerated.
Explaining and predicting human behavior and social dynamics in simulated virtual worlds: reproducibility, generalizability, and robustness of causal discovery methods
Authors: Volkova Svitlana , Arendt Dustin , Saldanha Emily , Glenski Maria , Ayton Ellyn , Cottam Joseph , Aksoy Sinan , Jefferson Brett , Shrivaram Karthnik 
Published: November 2021

AbstractGround Truth program was designed to evaluate social science modeling approaches using simulation test beds with ground truth intentionally and systematically embedded to understand and model complex Human Domain systems and their dynamics Lazer et al. (Science 369:1060–1062, 2020). Our multidisciplinary team of data scientists, statisticians, experts in Artificial Intelligence (AI) and visual analytics had a unique role on the program to investigate accuracy, reproducibility, generalizability, and robustness of the state-of-the-art (SOTA) causal structure learning approaches applied to fully observed and sampled simulated data across virtual worlds. In addition, we analyzed the feasibility of using machine learning models to predict future social behavior with and without causal knowledge explicitly embedded. In this paper, we first present our causal modeling approach to discover the causal structure of four virtual worlds produced by the simulation teams—Urban Life, Financial Governance, Disaster and Geopolitical Conflict. Our approach adapts the state-of-the-art causal discovery (including ensemble models), machine learning, data analytics, and visualization techniques to allow a human-machine team to reverse-engineer the true causal relations from sampled and fully observed data. We next present our reproducibility analysis of two research methods team’s performance using a range of causal discovery models applied to both sampled and fully observed data, and analyze their effectiveness and limitations. We further investigate the generalizability and robustness to sampling of the SOTA causal discovery approaches on additional simulated datasets with known ground truth. Our results reveal the limitations of existing causal modeling approaches when applied to large-scale, noisy, high-dimensional data with unobserved variables and unknown relationships between them. We show that the SOTA causal models explored in our experiments are not designed to take advantage from vasts amounts of data and have difficulty recovering ground truth when latent confounders are present; they do not generalize well across simulation scenarios and are not robust to sampling; they are vulnerable to data and modeling assumptions, and therefore, the results are hard to reproduce. Finally, when we outline lessons learned and provide recommendations to improve models for causal discovery and prediction of human social behavior from observational data, we highlight the importance of learning data to knowledge representations or transformations to improve causal discovery and describe the benefit of causal feature selection for predictive and prescriptive modeling.
A note on the Gannon–Lee theorem
Authors: Schinnerl Benedict , Steinbauer Roland 
Published: November 2021

AbstractWe prove a Gannon–Lee theorem for non-globally hyperbolic Lorentzian metrics of regularity $$C^1$$

C
1

, the most general regularity class currently available in the context of the classical singularity theorems. Along the way, we also prove that any maximizing causal curve in a $$C^1$$

C
1

-spacetime is a geodesic and hence of $$C^2$$

C
2

-regularity.
Citizen science in cities: an overview of projects focused on urban Australia
Authors: Roger Erin , Motion Alice 
Published: November 2021

AbstractCitizen science offers a unique opportunity to connect urban-dwellers with the often hidden natural world upon their doorsteps and to contribute to authentic research that increases knowledge of urban ecology and biodiversity. With the majority of Australia’s population residing in large cities, this diverse potential pool of participants in science creates a significant opportunity to increase the spatial and temporal scale of research. Herein, we provide an overview of Australian urban citizen science projects based on an analysis of the projects listed in the Australian Citizen Science Association’s Citizen Science Project Finder. We draw out key features (such as those with research questions specific to cities such as reintroduction and persistence of species in urban environments) from urban citizen science projects that make them suitable for the urban environment and use these features to suggest recommendations for further expansion and development of this important subset of projects. We conclude that the number and diversity of urban citizen science projects is relatively low in Australia, and advocate for an increase in initiatives that can tap into a large pool of potential participants for the benefit of science and society.
Pine wilt disease detection in high-resolution UAV images using object-oriented classification
Authors: Sun Zhao , Wang Yifu , Pan Lei , Xie Yunhong , Zhang Bo , Liang Ruiting , Sun Yujun 
Published: November 2021

AbstractPine wilt disease (PWD) is currently one of the main causes of large-scale forest destruction. To control the spread of PWD, it is essential to detect affected pine trees quickly. This study investigated the feasibility of using the object-oriented multi-scale segmentation algorithm to identify trees discolored by PWD. We used an unmanned aerial vehicle (UAV) platform equipped with an RGB digital camera to obtain high spatial resolution images, and multi-scale segmentation was applied to delineate the tree crown, coupling the use of object-oriented classification to classify trees discolored by PWD. Then, the optimal segmentation scale was implemented using the estimation of scale parameter (ESP2) plug-in. The feature space of the segmentation results was optimized, and appropriate features were selected for classification. The results showed that the optimal scale, shape, and compactness values of the tree crown segmentation algorithm were 56, 0.5, and 0.8, respectively. The producer’s accuracy (PA), user’s accuracy (UA), and F1 score were 0.722, 0.605, and 0.658, respectively. There were no significant classification errors in the final classification results, and the low accuracy was attributed to the low number of objects count caused by incorrect segmentation. The multi-scale segmentation and object-oriented classification method could accurately identify trees discolored by PWD with a straightforward and rapid processing. This study provides a technical method for monitoring the occurrence of PWD and identifying the discolored trees of disease using UAV-based high-resolution images.
Why and Where to Fund Carbon Capture and Storage
Authors: Mintz-Woo Kian , Lane Joe 
Published: November 2021

AbstractThis paper puts forward two claims about funding carbon capture and storage. The first claim is that there are moral justifications supporting strategic investment into CO2 storage from global and regional perspectives. One argument draws on the empirical evidence which suggests carbon capture and storage would play a significant role in a portfolio of global solutions to climate change; the other draws on Rawls’ notion of legitimate expectations and Moellendorf’s Anti-Poverty principle. The second claim is that where to pursue this strategic investment poses a morally non-trivial problem, with considerations like near-term global distributive justice and undermining legitimate expectations favouring investing in developing regions, especially in Asia, and considerations like long-term climate impacts and best uses of resources favouring investing in the relatively wealthy regions that have the best prospects for successful storage development.
Quantitative assessments of late radiation-induced skin and soft tissue toxicity and correlation with RTOG scales and biological equivalent dose in breast cancer
Authors: Huang Y. , Sanz J. , Rodríguez N. , Duran X. , Martínez A. , Li X. , Foro P. , Conde M. , Zhao M. , Liu F. , Reig A. , Dengra J. , Membrive I. , Pérez P. , Algara M. 
Published: November 2021

Abstract
Purpose
Radiation-induced toxicity (RIT) is usually assessed by inspection and palpation. Due to their subjective and unquantitative nature, objective methods are required. This study aimed to determine whether a quantitative tool is able to assess RIT and establish an underlying BED-response relationship in breast cancer.

Methods
Patients following seven different breast radiation protocols were recruited to this study for RIT assessment with qualitative and quantitative examination. The biologically equivalent dose (BED) was used to directly compare different radiation regimens. RIT was subjectively evaluated by physicians using the Radiation Therapy Oncology Group (RTOG) late toxicity scores. Simultaneously an objective multiprobe device was also used to quantitatively assess late RIT in terms of erythema, hyperpigmentation, elasticity and skin hydration.

Results
In 194 patients, in terms of the objective measurements, treated breasts showed higher erythema and hyperpigmentation and lower elasticity and hydration than untreated breasts (p < 0.001, p < 0.001, p < 0.001, p = 0.019, respectively). As the BED increased, Δerythema and Δpigmentation gradually increased as well (p = 0.006 and p = 0.002, respectively). Regarding the clinical assessment, the increase in BED resulted in a higher RTOG toxicity grade (p < 0.001). Quantitative assessments were consistent with RTOG scores. As the RTOG toxicity grade increased, the erythema and pigmentation values increased, and the elasticity index decreased (p < 0.001, p = 0.016, p = 0.005, respectively).

Conclusions
The multiprobe device can be a sensitive and simple tool for research purpose and quantitatively assessing RIT in patients undergoing radiotherapy for breast cancer. Physician-assessed toxicity scores and objective measurements revealed that the BED was positively associated with the severity of RIT.
Assessment of Paleocene to lower Oligocene formations and basement to estimate the potential hydrocarbon reservoirs using seismic inversion: a case study in the Upper Assam Shelf, India
Authors: Rai Neha , Singha Dip Kumar , Chatterjee Rima 
Published: November 2021

AbstractThe upper Assam shelf is a self-slope basin in north-east India, filled with nearly 7 km of sedimentary rocks of tertiary period with the granite basement and various oil fields along the border of the Naga thrust. The major producing fields are structural and strati-structural. The study area is placed in between the Mikir hills and Naga thrust. The objective of the study is to identify potential hydrocarbon reservoir zones in the geologically complex south upper of the Assam shelf using estimates of acoustic impedance and porosity derived by 3D post-stack seismic inversion. Well data, such as sonic velocity and density logs, from two wells (namely, KA and TE) are used in the inversion and validation of results. Inversion results are used to build a geological model in the form of acoustic impedance from which we derive 3D porosity cube which are used for hydrocarbon potential in the Paleocene to lower Oligocene sands, and the Precambrian basement. Although the amplitude maps provide an indication of potential reservoirs, the extent of these zones are much better identified in the inverted impedance maps and the corresponding estimated high-porosity zones. The analysis predicted the potential reservoir rocks in the Sylhet, Kopili and Barail formations, in which the Sylhet and Kopili appear to have good potential zones. Near the vicinity of the Naga thrust belt, the proximity of potential reservoir is predicted in the Kopili, Sylhet formation and in the fractured basement, respectively.
An undergraduate medical curriculum framework for providing care to transgender and gender diverse patients: A&nbsp;modified Delphi study
Authors: Ellaway Rachel H. , Thompson Nicole L. , Temple-Oberle Claire , Pacaud Danièle , Frecker Helena , Jablonski Theodore J. , Demers James , Mattatall Fiona , Raiche Joe , Hull Andrea , Jalil Rabiya 
Published: November 2021

Introduction The lack of attention to transgender and gender diverse (TGD) people in undergraduate medical education (UME) is a point of concern, particularly among medical students. A project was undertaken to develop a UME curriculum framework for teaching the healthcare needs of TGD people. Methods Using a modified Delphi methodology, four rounds of surveys were presented to an expert stakeholder group that included content experts, generalist physicians, UME teaching faculty, and medical students. Questions covered what content should be taught, who should teach the content, and how much time should be dedicated for this teaching. Once the Delphi process was complete, feedback on the provisional framework was sought from members of the TGD community to ensure it represented their needs and perspectives. Results 71 panel members and 56 community members participated in the study. Core values included the scope of the framework, and topics such as inclusivity, and safety in practice and in teaching. The framework included terminology, epidemiology, medical and surgical treatment, mental health, sexual and reproductive health, and routine primary care. There was also guidance on who should teach, time to be allocated, and the learning environment. Discussion There is a clear need to train tomorrow’s doctors to provide competent and respectful healthcare services to and for TGD patients. Although local factors will likely shape the way in which this framework will be implemented in different contexts, this paper outlines a core UME-level curriculum framework for Canada and, potentially, for use in other parts of the world.
How to Treat Childhood Sexual Abuse Related PTSD Accompanied by Risky Sexual Behavior: A Case Study on the Use of Dialectical Behavior Therapy for Posttraumatic Stress Disorder (DBT-PTSD)
Authors: Steil Regina , Schneider Angelina , Schwartzkopff Laura 
Published: November 2021

AbstractChildhood and adolescent sexual abuse (CSA) is a traumatic experience associated with a variety of short- and long-term negative consequences. Theoretical models assume that an abuse related and learned distorted image of sexuality might lead CSA survivors to feel obligated to provide sex or engage in unwanted sexual practices in order to gain affection or prevent abandonment. Dialectical behavioral therapy for posttraumatic stress disorder (DBT-PTSD) is tailored to people with PTSD and comorbid emotion regulation deficits. This case study presents the results of an outpatient DBT-PTSD treatment of an adult patient with posttraumatic stress disorder following sexual and physical abuse. DBT-PTSD was used to treat the patient’s complex psychopathological problems and to decrease her risky sexual behavior, which manifested itself in highly dangerous sexual practices with her partner. The treatment took place over a period of 18 months, with a total of 72 sessions. At the end of the treatment, the patient no longer met criteria for PTSD as indicated by large reductions in the assessments used. Furthermore, she managed to distance herself from risky sexual practices and to remain in a satisfying relationship.
Identification of cinnabar existing in different objects using portable coupled XRF-XRD, laboratory-type XRD and micro-Raman spectroscopy: comparison of the techniques
Authors: Shen Jingyi , Shen Yijia 
Published: November 2021

Abstract
Cinnabar (α-HgS) is a common mineral used in various fields. The identification of cinnabar can be achieved by classic mineralogical methods and instrumental methods. X-ray diffraction (XRD) is the most reliable instrumental method for identifying material phases, but the sampling process and the immovable instrument limit its wider application in the cultural heritage field. The occurrence of Assing S. p. A. Surface Monitor, a portable system integrating X-ray fluorescence (XRF) and XRD, provides researchers with a new solution. Raw mineral, polished gemstone, pigment powder and Chinese ink stick claimed to be composed of cinnabar were measured by the system as well as laboratory-type XRD and micro-Raman techniques in this study. The qualitative XRF results were applied to determining the elements existing in the samples and thus defining the range of possible phases. Patterns obtained were compared carefully with the characteristic lines to determine the most likely phases, while the pattern appearances were compared in order to recognize the different states of cinnabar and generalize the experience for identifying cinnabar by the system. The Raman spectra obtained were compared and analyzed in order to learn the best parameters and determine the real composition of each sample. The results indicate that the XRF detector is sensitive enough to distinguish cinnabar from another red pigment, minium (Pb3O4), without destructive preparation provided that the desired phases occupy a major content in the sample, while the laser micro-Raman is even better in application range and measurement speed but correct analysis of the spectra is highly dependent on experience and literatures. The portable coupled XRF-XRD system and the micro-Raman provide researchers with convenient and efficient options to preliminarily identify minerals like cinnabar, which is significantly meaningful to several research fields including mineralogy, heritage science, material science, etc.

Article highlights

Two efficient and non-destructive methods for the preliminary identification of minerals like cinnabar were developed.

The optimum instrument parameters for the effective measurement of different cinnabar samples were given in detail.

The study provides useful data for various fields including analytical science, material science, heritage science, etc.
Management of Wind Power Variations in Electricity System Investment Models
Authors: Göransson Lisa , Granfeldt Caroline , Strömberg Ann-Brith 
Published: November 2021

AbstractAccounting for variability in generation and load and strategies to tackle variability cost-efficiently are key components of investment models for modern electricity systems. This work presents and evaluates the Hours-to-Decades (H2D) model, which builds upon a novel approach to account for strategies to manage variations in the electricity system covering several days, the variation management which is of particular relevance to wind power integration. The model discretizes the time dimension of the capacity expansion problem into 2-week segments, thereby exploiting the parallel processing capabilities of modern computers. Information between these segments is then exchanged in a consensus loop. The method is evaluated with regard to its ability to account for the impacts of strategies to manage variations in generation and load, regional resources and trade, and inter-annual linkages. Compared to a method with fully connected time, the proposed method provides solutions with an increase in total system cost of no more than 1.12%, while reducing memory requirements to 1/26’th of those of the original problem. For capacity expansion problems concerning two regions or more, it is found that the H2D model requires 1–2% of the calculation time relative to a model with fully connected time when solved on a computer with parallel processing capability.
Exploring the benefits and challenges of Internet of Things (IoT) during Covid-19: a case study of Bangladesh
Authors: Sultana Nahida , Tamanna Marzia 
Published: November 2021

AbstractThe Internet of Things (IoT) is expected to have a huge impact, especially during the pandemic period. The study reveals that people are using the IoT mostly for education purposes (as students and educators), office work, banks and medical purposes during the pandemic. The topmost benefit of using IoT services experienced by people during pandemic situations is that it helps to strictly maintain physical distance. However, the greatest challenge faced by people is that the use of the IoT increases social distancing and reduces personal communication. Data were collected through a questionnaire distributed online and using a convenient random sampling method. A total of 260 participants’ properly completed responses were analyzed after conducting Three-fold validation. Research method was quantitative and empirical. Although, some studies have been found about IoT prospects in Bangladesh, no study has specifically explored the benefits and challenges of IoT services in diverse fields of Bangladesh during this new normal COVID-19 situation. The results can be beneficial to academic scholars, business professionals and organizations in different sectors and any other parties interested in determining the impact of IoT services on pandemic.
Lateral directional aircraft aerodynamic parameter estimation using adaptive stochastic nonlinear filter
Authors: Mohamed M. , Joy N. 
Published: November 2021

AbstractThis paper aims to accurately estimate the lateral directional aerodynamic parameters in real time irrespective of the variations in the process and measurement covariance matrices. The proposed algorithm for parameter estimation is based on the integration of adaptive techniques into a stochastic nonlinear filter. The proposed adaptive estimation algorithm is applied to flight test data, and the lateral directional derivatives are estimated in real time. The estimates are compared with those obtained from the Filter Error Method (FEM), an offline parameter estimation method accounting for process noise. The estimation results are observed to be very comparable, and the supremacy of the adaptive filter is illustrated by varying the covariance matrices of both process and measurement noises. The parameters estimated by the adaptive filter are found to converge to their actual values, whereas the estimates of the regular filter are observed to diverge from the actual values when changing the noise covariance matrices. The proposed adaptive algorithm can estimate the lateral directional aerodynamic derivatives more accurately without prior knowledge of either process or measurement noise covariance matrices. Hence, it is of great value in online implementations.
Beirut Explosion: The Largest Non-Nuclear Blast in History
Authors: Helou Mariana , El-Hussein Mahmoud , Aciksari Kurtulus , Salio Flavio , Della Corte Francesco , von Schreeb Johan , Ragazzoni Luca 
Published: November 2021

AbstractA massive explosion have ripped Beirut on August 4, 2020, leaving behind more than 6000 casualties, 800 regular floor admissions, 130 intensive care unit admissions, and over 200 deaths. Buildings were destroyed, hospitals in Beirut were also destroyed, others became nonfunctional. A disaster code was initiated in all the hospitals. Victims were transported by the Lebanese Red Cross or by volunteers to the nearest hospital that was still functional. Hospitals were flooded in patients, the coordination between health care centers was missing. Each hospital was functioning to its maximum capacity. With the many challenges we had, a rapid response was initiated. An effective triage done outside the Emergency had the major role in saving lives. After the Beirut Explosion, an assessment of the disaster plan and a major evaluation of the hospitals’ coordination is needed.