bluuebunny/crossref_metadata_2025_split huggingface dataset:
Humanities, criticality and transparency: global health histories and the foundations of inter-sectoral partnerships for the democratisation of knowledge
Authors: Bhattacharya Sanjoy , Medcalf Alexander , Ahmed Aliko 
Published: June 2020

AbstractHistorians of medicine have been influential actors in a broader movement to highlight the social, institutional and administrative benefits of historical research, and its relevance for national and international policy intended to extend and improve contemporary healthcare. Historical perspectives are fundamentally useful to health policy actors because questions about what it is to be healthy, to suffer disease or disability, and the presentation and acceptance of solutions are interwoven in culturally and historically complex webs of meaning. Historians, as they have examined the social and cultural social determinants of health, have also used their work as public engagement, educational and policy resource tools, demonstrating that history is an effective way of making key issues in science, medicine and well-being more administratively responsive and accessible to lay audiences. This article explores such issues through the case study of the long-running World Health Organization (WHO) Global Health Histories project. Established in late 2004, the project’s enduring rationale has been that understanding the history of health helps the global public health community to respond to the challenges of today and help shape a healthier future. It has sought to do this by bringing together researchers and policy-makers into honest and democratic conversations and exchanges of ideas. The aim has been to stimulate a fusion between historical evidence and current policy approaches to many of the most urgent health issues. This article discusses the challenges and opportunities in bringing health history and policy together, and explores the importance of explaining historical method and the need to convince policy partners how history is evidence-based, that it can access and provide useful strategic information from archives of major institutions, and, therefore, a useful contributor to making policy initiatives adaptable and acceptable within complex polities and societies.
Situated data analysis: a new method for analysing encoded power relationships in social media platforms and apps
Authors: Rettberg Jill Walker 
Published: June 2020

AbstractThis paper proposes situated data analysis as a new method for analysing social media platforms and digital apps. An analysis of the fitness tracking app Strava is used as a case study to develop and illustrate the method. Building upon Haraway’s concept of situated knowledge and recent research on algorithmic bias, situated data analysis allows researchers to analyse how data is constructed, framed and processed for different audiences and purposes. Situated data analysis recognises that data is always partial and situated, and it gives scholars tools to analyse how it is situated, and what effects this may have. Situated data analysis examines representations of data, like data visualisations, which are meant for humans, and operations with data, which occur when personal or aggregate data is processed algorithmically by machines, for instance to predict behaviour patterns, adjust services or recommend content. The continuum between representational and operational uses of data is connected to different power relationships between platforms, users and society, ranging from normative disciplinary power and technologies of the self to environmental power, a concept that has begun to be developed in analyses of digital media as a power that is embedded in the environment, making certain actions easier or more difficult, and thus remaining external to the subject, in contrast to disciplinary power which is internalised. Situated data analysis can be applied to the aggregation, representation and operationalization of personal data in social media platforms like Facebook or YouTube, or by companies like Google or Amazon, and gives researchers more nuanced tools for analysing power relationships between companies, platforms and users.
The Rosetta Stone and the Nemrud Nomos: the discovery of significant textual and astronomical similarities
Authors: Crijns Maurice 
Published: June 2020

AbstractCommagene was an independent and wealthy kingdom in the east of present Turkey from ca. 160 to 20 BCE. A text referred to as Nomos (Dörner) describes the astro-religion of Commagene (Crijns). The text on the Egyptian Rosetta Stone describes the Ptolemaic astro-religion (Rosetta Stone Online Project). It is shown here that the Rosetta text is a precursor of the Nomos, based on textual and astronomical evidence. The coronation dates as mentioned in both texts display a similar configuration in the sky as substantiated by the configuration on the Lion Horoscope at the top of Mt. Nemrud. Not only the date can be calculated, but also the precise time. The time is determined by an annual phenomenon of the marker star Sirius and Regulus, respectively. The latter has been overseen by scholars and underlines the importance of having at least a basic understanding of archaeoastronomy. These unnoticed similarities indicate that the astro-religions of the Middle East are not stand alone cults. The significant similarities point at a shared heritage i.e., a star cult dating maybe as far back as the era of the Fertile Crescent at the dawn of mankind.
Gender gaps in urban mobility
Authors: Gauvin Laetitia , Tizzoni Michele , Piaggesi Simone , Young Andrew , Adler Natalia , Verhulst Stefaan , Ferres Leo , Cattuto Ciro 
Published: June 2020

AbstractMobile phone data have been extensively used to study urban mobility. However, studies based on gender-disaggregated large-scale data are still lacking, limiting our understanding of gendered aspects of urban mobility and our ability to design policies for gender equality. Here we study urban mobility from a gendered perspective, combining commercial and open datasets for the city of Santiago, Chile. We analyze call detail records for a large cohort of anonymized mobile phone users and reveal a gender gap in mobility: women visit fewer unique locations than men, and distribute their time less equally among such locations. Mapping this mobility gap over administrative divisions, we observe that a wider gap is associated with lower income and lack of public and private transportation options. Our results uncover a complex interplay between gendered mobility patterns, socio-economic factors and urban affordances, calling for further research and providing insights for policymakers and urban planners.
“Indiscipline” in context: a political-economic grounding for dangerous driving behaviors among Tro-Tro drivers in Ghana
Authors: Boateng Festival Godwin 
Published: June 2020

AbstractThis paper attempts a better explanation for the causes of dangerous driving behaviors among “Tro-Tro”(minibus) drivers in Ghana. The current media, policy, and academic coverage of the problem reveals an immutable discourse that considers the behaviors (such as over speeding) as a function of moral failure, indiscipline, or bad attitudes on the part of the drivers. Often little consideration is given to the context of the behaviors and their influences. This paper provides an alternative explanation that considers the behaviors as predictable actions that are systematically connected to the Tro-Tro industry. Tro-Tro drivers operate within a precarious work climate marked by problems such as low wages; cut-throat competition; high level of job insecurity; imposition of non-negotiable throat-cutting daily fees by car owners and harassments from bribe-demanding corrupt police officers. The exigencies of meeting these numerous financial and other demands of their work,not moral failure, are what fuel dangerous driving behaviors among the drivers. Based on this analysis, the present public policy of using penal populism (i.e., heavy fines and prison sentences) to address road trauma in Ghana is ineffective for inducing safer driving behaviors among Tro-Tro drivers. Interventions to reduce road transport problems involving such commercial passenger vehicles in Ghana and other developing countries similarly situated must be broad, more-wider reaching and include initiatives that also address the range of political-economic causes, motivations, and constraints that incentivize the drivers to drive dangerously. The paper contributes to the sustainable development goals of ensuring safe and sustainable transport (SDG 11.2), and reducing deaths and injuries from road accidents (SDG 3.6).
Knowing qualia: reloading the displaced perception model
Authors: de Sá Pereira Roberto Horácio 
Published: June 2020

AbstractHow does one know the phenomenal character of one’s own experience? I aim to present and defend a new view of the epistemology of qualia that addresses this issue. My view results from a reworking of Dretske’s displaced perception model. The guiding line is the key Wittgensteinian insight of his Private Language Argument, namely the claim that no inner perception of qualia can justify our corresponding qualia-beliefs. My reworking of the original model starts with the rejection of Dretske’s representationalism, as well as any other metaphysical views about the ultimate nature of qualia. The reworking of the displaced perception model I am proposing is supposed to be compatible with any available metaphysical view on qualia. The second step consists of rejecting the epistemological misgivings of the original model, namely the view that knowing qualia requires “connecting beliefs” along with “meta-representations.” Yet, Dretske’s crucial mistake has been to force knowledge of qualia into the “belief-box.” As a matter of fact, there is only one belief involved in introspecting qualia, namely the qualia-belief itself. The third final step is this. Assuming the key Wittgensteinian insight, I argue that introspection of qualia is a process that is both epistemically reliable and automatic. It is reliable because it dispenses with justification of any beliefs whatsoever. Moreover, it is automatic because it also dispenses with reflexive connecting beliefs. For example, it takes nonconceptual awareness of the color blue as an input and automatically yields the belief that phenomenal blue is the conscious character of my experience of the sky as an output just by employing the concept BLUE.
On the integral characteristic function of the Sturm-Liouville problem
Authors: Valovik D. V. 
Published: June 2020

Abstract
We introduce a function whose zeros, and only these zeros, are eigenvalues of the corresponding Sturm-Liouville problem. The boundary conditions of the problem depend continuously on the spectral parameter. Therefore, it makes sense to call the function thus constructed a characteristic function of the Sturm-Liouville problem (however, it is not a characteristic function in the ordinary sense). An investigation of the function thus obtained enables us to prove the solvability of the problem in question, to find the asymptotic behaviour of the eigenvalues, to obtain comparison theorems, and to introduce an indexing of the eigenvalues and the zeros of eigenfunctions in a natural way.
Bibliography: 31 titles.
Uncoupling DNA damage from chromatin damage to detoxify doxorubicin
Authors: Qiao Xiaohang , van der Zanden Sabina Y. , Wander Dennis P. A. , Borràs Daniel M. , Song Ji-Ying , Li Xiaoyang , van Duikeren Suzanne , van Gils Noortje , Rutten Arjo , van Herwaarden Tessa , van Tellingen Olaf , Giacomelli Elisa , Bellin Milena , Orlova Valeria , Tertoolen Leon G. J. , Gerhardt Sophie , Akkermans Jimmy J. , Bakker Jeroen M. , Zuur Charlotte L. , Pang Baoxu , Smits Anke M. , Mummery Christine L. , Smit Linda , Arens Ramon , Li Junmin , Overkleeft Hermen S. , Neefjes Jacques 
Published: June 2020

Significance
Anthracyclines like doxorubicin are anticancer drugs, used by over 1 million cancer patients annually. However, they cause severe side effects, most notably, cardiotoxicity and therapy-related malignancies. It is unclear whether these side effects are directly linked to their anticancer activity. Doxorubicin exerts two activities: DNA damage and chromatin damage. Here, we show that both activities conspire in the cardiotoxicity, while doxorubicin variants with only chromatin-damaging activity remain active anticancer drugs devoid of side effects. This challenges the concept that doxorubicin works primarily by inducing DNA double-strand breaks and reveals another major anticancer activity, chromatin damage. Translating these observations will yield anticancer drugs for patients that are currently excluded from doxorubicin treatment and improve the quality of life of cancer survivors.
Effect of cycling specialization on effort and physiological responses to uphill and flat cycling at similar intensity
Authors: Gandia Soriano Alexis , Carpes Felipe P. , Rodríguez Fernández Alejandro , Priego‐Quesada Jose Ignacio 
Published: June 2020

AbstractPower output is considered one of the best tools to control external loads in cycling, but the relationship between a target power output and the physiological responses may suffer from the effects of road gradient, which is also affected by cyclist specialization. The objective was to determine the effects of cyclist specialization on effort perception and physiological response (heart rate and lactate concentration) while sustaining efforts at similar power output but riding on two different road gradients. Nineteen male competitive road cyclists performed two randomized trials of 10 min at 0% (velodrome) and 10 min at 6% road gradient (field uphill), at an intensity of 10% ± 3% below the individual's functional threshold power. Cadence was kept between 75 and 80 rpm in both trials and posture remained unchanged during the tests. Heart rate, speed, cadence, power output, blood lactate, and rate of perceived effort were measured for each trial. K‐means cluster analyses differentiate uphill (n = 10) and flat specialists (n = 9) according to lactate responses. Flat specialists presented lower heart rate (p < 0.001 and ES = 0.2), perceived exertion (p < 0.01 and ES = 0.7), and blood lactate concentration (p < 0.001 and ES = 0.7) riding on the flat than uphill. Uphill specialists presented lower perceived exertion (p < 0.01 and ES = 0.8) and blood lactate concentration (p < 0.01 and ES = 0.5) riding uphill than on the flat. In conclusion, the combination of cyclist specialization and road gradient affects physiological and effort perception parameters in response to a similar power output demand. These factors deserve attention in training schedules and monitoring performance using power output data.
Optimality and universality in quantum Zeno dynamics
Authors: Belan Sergey , Parfenyev Vladimir 
Published: June 2020

Abstract
The effective lifetime of a quantum state can increase (the quantum Zeno effect) or decrease (the quantum anti-Zeno effect) in the response to increasing frequency of the repeated measurements and the multiple transitions between these two regimes are potentially possible within the same system. An interesting question arising in this regards is how to choose the optimal schedule of repeated measurements to achieve the maximal possible decay rate of a given quantum state. Addressing the issue of optimality in the quantum Zeno dynamics, we derive a range of rigorous results, which are, due to generality of the theoretical framework adopted here, applicable to the majority of models appeared in the quantum Zeno literature. In particular, we prove the universal dominance of the regular stroboscopic sampling in the sense that it always provides the shortest expected decay time among all possible measurement procedures. However, the implementation of the stroboscopic protocol requires the knowledge of the optimal sampling period which may depend on the fine details of the quantum problem. We demonstrate that this difficulty can be overcome with the tricky non-regular measurement schedule inspired by the scale-free restart strategy used to speed up the completion of the probabilistic algorithms and Internet tasks in computer science as it allows to achieve a near-optimal decay rate in the absence of detailed knowledge of the underlying quantum statistics. Besides, our general approach reveals unexpected universality displayed by the quantum systems subject to the optimally tuned rate of Poissonian measurements and the simple statistical criteria to discriminate between Zeno and anti-Zeno regimes following from this universality. We illustrate our findings with an example of Zeno dynamics in the system of optically-trapped ultra-cold atoms and discuss the implications arising from them.
Discontinuous Galerkin discretization for quantum simulation of chemistry
Authors: McClean Jarrod R , Faulstich Fabian M , Zhu Qinyi , O’Gorman Bryan , Qiu Yiheng , White Steven R , Babbush Ryan , Lin Lin 
Published: June 2020

Abstract
All-electron electronic structure methods based on the linear combination of atomic orbitals method with Gaussian basis set discretization offer a well established, compact representation that forms much of the foundation of modern correlated quantum chemistry calculations—on both classical and quantum computers. Despite their ability to describe essential physics with relatively few basis functions, these representations can suffer from a quartic growth of the number of integrals. Recent results have shown that, for some quantum and classical algorithms, moving to representations with diagonal two-body operators can result in dramatically lower asymptotic costs, even if the number of functions required increases significantly. We introduce a way to interpolate between the two regimes in a systematic and controllable manner, such that the number of functions is minimized while maintaining a block-diagonal structure of the two-body operator and desirable properties of an original, primitive basis. Techniques are analyzed for leveraging the structure of this new representation on quantum computers. Empirical results for hydrogen chains suggest a scaling improvement from O(N
4.5) in molecular orbital representations to O(N
2.6) in our representation for quantum evolution in a fault-tolerant setting, and exhibit a constant factor crossover at 15 to 20 atoms. Moreover, we test these methods using modern density matrix renormalization group methods classically, and achieve excellent accuracy with respect to the complete basis set limit with a speedup of 1–2 orders of magnitude with respect to using the primitive or Gaussian basis sets alone. These results suggest our representation provides significant cost reductions while maintaining accuracy relative to molecular orbital or strictly diagonal approaches for modest-sized systems in both classical and quantum computation for correlated systems.
Extreme learning machine adapted to noise based on optimization algorithms
Authors: Vásquez A , Mora M , Salazar E , Gelvez E 
Published: June 2020

Abstract
The extreme learning machine for neural networks of feedforward of a single hidden layer randomly assigns the weights of entry and analytically determines the weights the output by means the Moore-Penrose inverse, this algorithm tends to provide an extremely fast learning speed preserving the adjustment levels achieved by classifiers such as multilayer perception and support vector machine. However, the Moore-Penrose inverse loses precision when using data with additive noise in training. That is why in this paper a method to robustness of extreme learning machine to additive noise proposed. The method consists in computing the weights of the output layer using non-linear optimization algorithms without restrictions. Tests are performed with the gradient descent optimization algorithm and with the Levenberg-Marquardt algorithm. From the implementation it is observed that through the use of these algorithms, smaller errors are achieved than those obtained with the Moore-Penrose inverse.
Conditioning of extreme learning machine for noisy data using heuristic optimization
Authors: Salazar E , Mora M , Vásquez A , Gelvez E 
Published: June 2020

Abstract
This article provides a tool that can be used in the exact sciences to obtain good approximations to reality when noisy data is inevitable. Two heuristic optimization algorithms are implemented: Simulated Annealing and Particle Swarming for the determination of the extreme learning machine output weights. The first operates in a large search space and at each iteration it probabilistically decides between staying at its current state or moving to another. The swarm of particles, it optimizes a problem from a population of candidate solutions, moving them throughout the search space according to position and speed. The methodology consists of building data sets around a polynomial function, implementing the heuristic algorithms and comparing the errors with the traditional computation method using the Moore–Penrose inverse. The results show that the heuristic optimization algorithms implemented improve the estimation of the output weights when the input have highly noisy data.
Assessment of left ventricle dynamic from cardiac magnetic resonance imaging by means a correspondence approach
Authors: Bravo A , Vera M , Valbuena O 
Published: June 2020

Abstract
In this research, an approach to assess the heart dynamics is reported. The cardiac magnetic resonance images are considered for assessing the left ventricle motion and deformation. The shape of the cavity is obtained by means a segmentation procedure based on a clustering algorithm at an initial instant. This three-dimensional structure is used to establish a region of interest around the border of the structure. An optical flow method allows determining the displacement vector of this region and then defining the shapes of the cavity during the all cardiac cycle. The points of the left ventricle are followed using the displacement vectors in the cardiac cycle, obtaining thus, a dense motion field of the cavity. This approximate deformation field is refined with a correspondence method that working in the three-dimensional space. The mapping of the points that define the left ventricle in the cardiac cycle obtained with the correspondence procedure are then used for computing a set of clinical parameters that allows assessing the motion and deformation of this principal structure of the human heart. The torsion, radial and longitudinal contraction are quantified. The obtained results are promising for evaluating the heart dynamics.
Data analysis for a set of university student lists using the k-Nearest Neighbors machine learning method
Authors: Pedrozo D , Barajas F , Estupiñán A , Cristiano K L , Triana D A 
Published: June 2020

Abstract
A tool using machine learning which organizes, clean and analyzes data in massive quantities was developed. So that the user can make predictions about different aspects of a list of more than 2000 students, using the k-nearest neighbor machine learning method. Data were obtained from a Colombian university, which has previously it has been cleaned and organized to accommodate the input parameters into a script. The computational tool was written in python from Jupyter notebook. The script is able to perform analysis predictive of the different filters previously chosen for decision raking by the example of marketing, the tool will keep track of financial actions and of the different categories chosen for students at the university, allowing a global analysis and thus choose the best options from all data granted. Among these categories we can classify method of payment, the value paid, what is the method of most commonly used payout by students, individual averages per semester and academic programs, addresses, and academic careers among others.