bluuebunny/crossref_metadata_2025 huggingface dataset:
Carbon sequestration in hedgerow biomass and soil in the temperate climate zone
Authors: Drexler Sophie , Gensior Andreas , Don Axel
Published: July 2021

Hedgerows are a traditional form of agroforestry in the temperate climate zone. The establishment of hedgerows may be a promising strategy to promote carbon (C) sinks for climate change mitigation. We therefore conducted a meta-analysis compiling data from 83 sites on soil organic carbon (SOC) stocks beneath hedgerows in comparison with adjacent croplands and grasslands, plus biomass data from 64 hedgerows. On average (± SD), the establishment of hedgerows on cropland increased SOC stocks by 32 ± 23 %. No significant differences were found between the SOC stocks of hedgerows and those of grassland. The average above-ground biomass stock was 47 ± 29 Mg C ha−1. Only one study reported measurements of below-ground biomass stocks and root/shoot ratios. Based on these measurements, an average below-ground biomass stock of 44 ± 28 Mg C ha−1 was estimated, but with high uncertainty. In total, hedgerows were estimated to store 104 ± 42 Mg ha−1 more C than croplands, with biomass contributing 84 % (87 ± 40 Mg C ha−1) and soil 16 % (17 ± 12 Mg C ha−1) to this amount. Total C sequestration with the establishment of hedgerows on cropland could be between 2.1 and 5.2 Mg ha−1 year−1 for a period of 50 and 20 years, respectively. Our results indicate that C stocks in hedgerows are on average comparable to estimates for forests. The establishment of hedgerows, especially on cropland, can therefore be an effective option for C sequestration in agricultural landscapes while enhancing biodiversity and soil protection.
The Role of Different Raw Materials in Lithic Technology and Settlement Patterns During the Middle Stone Age of Southern Africa
Authors: Will Manuel
Published: July 2021

The study of raw materials is an essential step in lithic analysis, regardless of the age, provenance, and technology of the assemblages. As in many other contexts of the Paleolithic, researchers of the Middle Stone Age (MSA) in southern Africa have often focused their attention on fine-grained, non-local rock types, such as silcrete. Here, I spotlight raw materials considered to be of lower suitability for knapping and frequently acquired from local sources. Due to their coarse-grained nature, artifacts from rock types such as calcrete, sandstone, and quartzite might show attributes that are different from finer-grained materials. Some of these knapped stones even constitute the substrate of the sites they are from, at times resulting in their neglect or not being recognized as anthropogenic artifacts. Knapped vein quartz features sharp and durable edges, but its complicated fracture mechanics hamper comparative analysis and provide methodological challenges. In this study, raw materials from different transport distances and with different presumed qualities are compared in terms of their roles in MSA lithic technology and settlement patterns. In the first step, the article focuses on the open-air special-purpose camp of Hoedjiespunt 1 (HDP1, Western Cape) and the rockshelter residential site of Sibudu (KwaZulu-Natal), especially on assemblages dated between ~ 130–100 and ~ 58 ka. Subsequently, I review relevant materials for the southern African MSA. At HDP1 and Sibudu, local raw materials of lower knapping suitability assume several roles, from the “staple” material for all manufacturing stages to special-purpose and “add-on” functions. In the broader southern African region, MSA knappers also used these rock types in a flexible manner with gradual differences but also similarities to their use of finer-grained raw material. These differences depend on a complex interaction of raw material availability, differential site use, and the position of the localities in the settlement system.
Does relative (absolute) efficiency affect capital costs?
Authors: Mali Dafydd , Lim Hyoung-Joo
Published: July 2021

In this paper, we examine the effect of relative/absolute firm efficiency on weighted average cost of capital (WACC). Using a sample of Korean listed firms, we find that WACC is negatively associated with relative firm efficiency (operational performance) suggesting that firms with higher (lower) relatively efficiency are expected to pay lower (higher) capital costs. When we repeat our analysis using absolute firm efficiency (ROA), we do not find a statistically significant relationship. Our results suggest relative efficiency which is estimated as output (sales) divided by the resources that are directly under the control of management is assessed by capital providers and impounded into a firm’s capital costs. Absolute efficiency (ROA) which is estimated as sales divided by total assets is not. Our results suggest that simple accounting ratios used in the accounting literature are not considered as informative to explain borrowing costs compared to relative efficiency that captures managerial operational performance.
Topological representation of cloth state for robot manipulation
Authors: Strazzeri Fabio , Torras Carme
Published: July 2021

Forty years ago the notion of configuration space (C-space) revolutionised robot motion planning for rigid and articulated objects. Despite great progress, handling deformable materials has remained elusive because of their infinite-dimensional shape-state space. Finding low-complexity representations has become a pressing research goal. This work tries to make a tiny step in this direction by proposing a state representation for textiles relying on the C-space of some distinctive points. A stratification of the configuration space for n points in the cloth is derived from that of the flag manifold, and topological techniques to determine adjacencies in manipulation-centred state graphs are developed. Their algorithmic implementation permits obtaining cloth state–space representations of different granularities and tailored to particular purposes. An example of their usage to distinguish between cloth states having different manipulation affordances is provided. Suggestions on how the proposed state graphs can serve as a common ground to link the perception, planning and manipulation of textiles are also made.
Prostate cancer survival in sub-Saharan Africa by age, stage at diagnosis, and human development index: a population-based registry study
Authors: Seraphin Tobias P. , Joko-Fru Walburga Y. , Manraj Shyam S. , Chokunonga Eric , Somdyala Nontuthuzelo I. M. , Korir Anne , N’Da Guy , Finesse Anne , Wabinga Henry , Assefa Mathewos , Gnangnon Freddy , Hansen Rolf , Buziba Nathan G. , Liu Biying , Kantelhardt Eva J. , Parkin Donald M.
Published: July 2021

Objectives

To estimate observed and relative survival of prostate cancer patients in sub-Saharan Africa (SSA) and to examine the influence of age, stage at diagnosis and the Human Development Index (HDI).

Patients and methods

In this comparative registry study, we selected a random sample of 1752 incident cases of malign prostatic neoplasm from 12 population-based cancer registries from 10 SSA countries, registered between 2005 and 2015. We analyzed the data using Kaplan-Meier and Ederer II methods to obtain outcome estimates and flexible Poisson regression modeling to calculate the excess hazards of death

Results

For the 1406 patients included in the survival analyses, 763 deaths occurred during 3614 person-years of observation. Of patients with known stage, 45.2% had stage IV disease, 31.2% stage III and only 23.6% stage I and II. The 1 and 5-year relative survival for the entire cohort was 78.0% (75.4–80.7) and 60.0% (55.7–64.6), while varying between the registries. Late presentation was associated with increased excess hazards and a 0.1 increase in the HDI was associated with a 20% lower excess hazard of death, while for age at diagnosis no association was found.

Conclusions

We found poor survival of SSA prostatic tumor patients, as well as high proportions of late stage presentation, which are associated with inferior outcome. This calls for investment in health-care systems and action regarding projects to raise awareness among the population to achieve earlier diagnosis and improve survival.
An enhanced design of a 5G MIMO antenna for fixed wireless aerial access
Authors: Almalki Faris A. , Angelides Marios C.
Published: July 2021

A recent market prediction is that 5G Fixed Wireless Access (FWA) will more than double over the next five years and trials at the same period in London suggest promising results. However, the shift to 5G FWA has raised a new set of research challenges in relation to speed of deployment and re-deployment, coverage, power consumption, end user mobility and last mile connectivity, to name just a few, because of the much higher expectations. A recent review reveals that key 5G Physical Layer technologies that will enable wide mobile and FWA have not kept up pace. In response to some of those research challenges, this paper presents the design of a 5G Multiple Input Multiple Output (MIMO) Antenna that is mounted on a tethered aerostat, and the combination of which serves as a 5G FWA aerial station. The antenna design features several novelties and the aerial station can provide last mile connectivity to a wide coverage footprint, with moderate power consumption and operating at high speeds. Both the evaluation of the antenna performance using several key performance indicators and the validation of the aerial station as a 5G FWA in a wireless sensor network (WSN) proof-of-concept application reveal efficiency gains.
Noise-based cyberattacks generating fake P300 waves in brain–computer interfaces
Authors: Martínez Beltrán Enrique Tomás , Quiles Pérez Mario , López Bernal Sergio , Huertas Celdrán Alberto , Martínez Pérez Gregorio
Published: July 2021

Most of the current Brain–Computer Interfaces (BCIs) application scenarios use electroencephalographic signals (EEG) containing the subject’s information. It means that if EEG were maliciously manipulated, the proper functioning of BCI frameworks could be at risk. Unfortunately, it happens in frameworks sensitive to noise-based cyberattacks, and more efforts are needed to measure the impact of these attacks. This work presents and analyzes the impact of four noise-based cyberattacks attempting to generate fake P300 waves in two different phases of a BCI framework. A set of experiments show that the greater the attacker’s knowledge regarding the P300 waves, processes, and data of the BCI framework, the higher the attack impact. In this sense, the attacker with less knowledge impacts 1% in the acquisition phase and 4% in the processing phase, while the attacker with the most knowledge impacts 22% and 74%, respectively.
SODALITE@RT: Orchestrating Applications on Cloud-Edge Infrastructures
Authors: Kumara Indika , Mundt Paul , Tokmakov Kamil , Radolović Dragan , Maslennikov Alexander , González Román Sosa , Fabeiro Jorge Fernández , Quattrocchi Giovanni , Meth Kalman , Di Nitto Elisabetta , Tamburri Damian A. , Van Den Heuvel Willem-Jan , Meditskos Georgios
Published: July 2021

IoT-based applications need to be dynamically orchestrated on cloud-edge infrastructures for reasons such as performance, regulations, or cost. In this context, a crucial problem is facilitating the work of DevOps teams in deploying, monitoring, and managing such applications by providing necessary tools and platforms. The SODALITE@RT open-source framework aims at addressing this scenario. In this paper, we present the main features of the SODALITE@RT: modeling of cloud-edge resources and applications using open standards and infrastructural code, and automated deployment, monitoring, and management of the applications in the target infrastructures based on such models. The capabilities of the SODALITE@RT are demonstrated through a relevant case study.
Early-Life Environmental and Child Factors Associated with the Presence of Disruptive Behaviors in Seven-Year-Old Children with Autistic Traits in the Avon Longitudinal Study of Parents and Children
Authors: Breider Simone , Hoekstra Pieter J. , Wardenaar Klaas J. , van den Hoofdakker Barbara J. , Dietrich Andrea , de Bildt Annelies
Published: July 2021

We studied the association of early-life environmental and child factors with disruptive behaviors in children with autistic traits around age 7, in the Avon Longitudinal Study of Parents and Children (n = 6,401). Logistic regression with the least absolute shrinkage and selection operator indicated that disruptive behaviors were associated with prenatal smoking, no seafood-consumption during pregnancy, breech presentation at delivery, neonatal feeding problems, low social-economic situation, suboptimal preschool family environment, maternal depression, maternal antisocial behavior, male sex, and difficult child temperament. Compared to controls, male sex, maternal depression, and suboptimal preschool family environment were related to autistic traits without disruptive behaviors. Thus, there may be a difference in early-life factors related to autism spectrum disorder with and without disruptive behaviors.
The Potential of Bioeconomic Innovations to Contribute to a Social-Ecological Transformation: A Case Study in the Livestock System
Authors: Friedrich Jonathan , Bunker Ingrid , Uthes Sandra , Zscheischler Jana
Published: July 2021

Environmental crises, which are consequences of resource-intensive lifestyles and are characterized to a large extent by both a changing climate and a loss of biodiversity, stress the urgent need for a global social-ecological transformation of the agro-food system. In this regard, the bioeconomy and bioeconomic innovations have frequently been seen as instrumental in addressing these grand challenges and contributing to more sustainable land use. To date, the question of how much bioeconomic innovations contribute to sustainability objectives remains unanswered. Against this background, we study four bioeconomic innovations using the case study of animal production and manure utilization in relation to their potential contributions to a social-ecological transformation. The analysis is based on the application of analytical categories derived from the literature that assess the normativity of these innovations and their implicit cultural changes. The results show that the innovations examined manifest existing thought styles and the incumbent socio-technical regime rather than contribute to a more fundamental transition. In this respect, we stress the importance of evolving alterative ideas in innovation design, applying more integrative approaches, such as embedding innovation processes into transdisciplinary processes, and developing adaptive and reflective governance approaches. In return, bioeconomic innovations should adjust towards the design mission of a social-ecological transformation and include a multitude of actors to discuss and harmonize contesting imaginaries and ethical concerns.
A sampling approach to Debiasing the offline evaluation of recommender systems
Authors: Carraro Diego , Bridge Derek
Published: July 2021

Offline evaluation of recommender systems (RSs) mostly relies on historical data, which is often biased. The bias is a result of many confounders that affect the data collection process. In such biased data, user-item interactions are Missing Not At Random (MNAR). Measures of recommender system performance on MNAR test data are unlikely to be reliable indicators of real-world performance unless something is done to mitigate the bias. One widespread way that researchers try to obtain less biased offline evaluation is by designing new, supposedly unbiased performance metrics for use on MNAR test data. We investigate an alternative solution, a sampling approach. The general idea is to use a sampling strategy on MNAR data to generate an intervened test set with less bias — one in which interactions are Missing At Random (MAR) or, at least, one that is more MAR-like. An existing example of this approach is SKEW, a sampling strategy that aims to adjust for the confounding effect that an item’s popularity has on its likelihood of being observed. In this paper, after extensively surveying the literature on the bias problem in the offline evaluation of RSs, we propose and formulate a novel sampling approach, which we call WTD; we also propose a more practical variant, which we call WTD_H. We compare our methods to SKEW and to two baselines which perform a random intervention on MNAR data. We empirically validate for the first time the effectiveness of SKEW and we show our approach to be a better estimator of the performance that one would obtain on (unbiased) MAR test data. Our strategy benefits from high generality (e.g. it can also be employed for training a recommender) and low overheads (e.g. it does not require any learning).
On new methods to construct lower bounds in simplicial branch and bound based on interval arithmetic
Authors: G.-Tóth B. , Casado L. G. , Hendrix E. M. T. , Messine F.
Published: July 2021

Branch and Bound (B&B) algorithms in Global Optimization are used to perform an exhaustive search over the feasible area. One choice is to use simplicial partition sets. Obtaining sharp and cheap bounds of the objective function over a simplex is very important in the construction of efficient Global Optimization B&B algorithms. Although enclosing a simplex in a box implies an overestimation, boxes are more natural when dealing with individual coordinate bounds, and bounding ranges with Interval Arithmetic (IA) is computationally cheap. This paper introduces several linear relaxations using gradient information and Affine Arithmetic and experimentally studies their efficiency compared to traditional lower bounds obtained by natural and centered IA forms and their adaption to simplices. A Global Optimization B&B algorithm with monotonicity test over a simplex is used to compare their efficiency over a set of low dimensional test problems with instances that either have a box constrained search region or where the feasible set is a simplex. Numerical results show that it is possible to obtain tight lower bounds over simplicial subsets.
Thermo-catalytic studies on a mixture of plastic waste and biomass
Authors: Sebestyén Zoltán , Blazsó Marianne , Jakab Emma , Miskolczi Norbert , Bozi János , Czégény Zsuzsanna
Published: July 2021

The effects of various catalysts on the composition of volatile pyrolysis products of a plastic waste and biomass mixture (1:1) were studied, by pyrolyzing the mixture sample using slow and fast heating rate. Various zeolite catalysts (β-and Y-zeolites, ZSM-5 and FCC) and nickel-molybdenum catalyst on alumina support were applied to find suitable catalysts for upgrading the quality of the thermal decomposition products of the waste mixture. A sample to catalyst ratio of 2:1 was used in the experiments. The rate of evolution of the decomposition products under slow pyrolysis was measured by thermogravimetry/mass spectrometry (TG/MS). The composition of the pyrolyzates was analyzed in detail by pyrolysis–gas chromatography/mass spectrometry (Py-GC/MS) method. The influence of all applied catalysts was more pronounced on the plastic content of the sample than on biomass. The pyrolysis experiments revealed that the catalysts promoted the cracking reactions of the evolved hydrocarbons; furthermore, the formation of aromatic products was enhanced remarkably in the presence of all zeolite catalysts. Beta-zeolite and ZSM-5 catalysts were found the most effective in cracking hydrocarbons to gaseous products and in aromatization, while the highest CO2 formation was obtained by FCC from the biomass part of the studied waste mixture. NiMo catalyst promoted the H2 production from the plastic part; furthermore, slight aromatization and cracking effects were also observed.
Neuroregulatory role of ginkgolides
Authors: Gachowska Martyna , Szlasa Wojciech , Saczko Jolanta , Kulbacka Julita
Published: July 2021

The application of ginkgolides as a herbal remedy reaches ancient China. Over time many studies confirmed the neuroprotective effect of standard Ginkgo biloba tree extract—the only available ginkgolide source. Ginkgolides present a wide variety of neuroregulatory properties, commonly used in the therapy process of common diseases, such as Alzheimer’s, Parkinson’s, and many other CNS-related diseases and disorders. The neuroregulative properties of ginkgolides include the conditioning of neurotransmitters action, e.g., glutamate or dopamine. Besides, natural compounds induce the inhibition of platelet-activating factors (PAF). Furthermore, ginkgolides influence the inflammatory process. This review focuses on the role of ginkgolides as neurotransmitters or neuromodulators and overviews their impact on the organism at the molecular, cellular, and physiological levels. The clinical application of ginkgolides is discussed as well.
The Core of the Global Corporate Network
Authors: Giglio Ricardo , Lux Thomas
Published: July 2021

We investigate the network topology of a comprehensive data set of the world-wide population of corporate entities. In particular, we have extracted information on the boards of all companies listed in Bloomberg’s archive of company profiles in October, 2015, a total of almost 100,000 firms. We provide information on board membership overlaps at various levels, and, in particular, show that there exists a core of directors who accumulate a large number of seats and are highly connected among themselves both at the level of national networks and at the worldwide aggregated level.
Portability of semantic and spatial–temporal machine learning methods to analyse social media for near-real-time disaster monitoring
Authors: Havas Clemens , Resch Bernd
Published: July 2021

Up-to-date information about an emergency is crucial for effective disaster management. However, severe restrictions impede the creation of spatiotemporal information by current remote sensing-based monitoring systems, especially at the beginning of a disaster. Multiple publications have shown promising results in complementing monitoring systems through spatiotemporal information extracted from social media data. However, various monitoring system criteria, such as near-real-time capabilities or applicability for different disaster types and use cases, have not yet been addressed. This paper presents an improved version of a recently proposed methodology to identify disaster-impacted areas (hot spots and cold spots) by combining semantic and geospatial machine learning methods. The process of identifying impacted areas is automated using semi-supervised topic models for various kinds of natural disasters. We validated the portability of our approach through experiments with multiple natural disasters and disaster types with differing characteristics, whereby one use case served to prove the near-real-time capability of our approach. We demonstrated the validity of the produced information by comparing the results with official authority datasets provided by the United States Geological Survey and the National Hurricane Centre. The validation shows that our approach produces reliable results that match the official authority datasets. Furthermore, the analysis result values are shown and compared to the outputs of the remote sensing-based Copernicus Emergency Management Service. The information derived from different sources can thus be considered to reliably detect disaster-impacted areas that were not detected by the Copernicus Emergency Management Service, particularly in densely populated cities.
Disagreement and Deliberation: Evidence from Three Deliberative Mini-Publics
Authors: Grönlund Kimmo , Herne Kaisa , Strandberg Kim , Söderlund Peter
Published: July 2021

This article is based on three experiments in citizen deliberation. We ask whether disagreement at group level as well as at individual level influence participants’ experiences of deliberation. In all three experiments, participants discussed in small groups and answered surveys before and after deliberations. The experiments were population-based with random selection. The topic of the first deliberation was nuclear power, the second dealt with immigration, and the third concerned policies for a language spoken by a national minority. The degree of group level disagreement was subject to experimental manipulation. In the first experiment, all the participants discussed in groups with mixed opinions. In the second experiment, participants were first categorized according to their baseline views, and then randomly allocated into either mixed or like-minded groups. In the third experiment, everyone discussed in like-minded groups. A trained facilitator moderated all small group discussions in the first two experiments. In the language experiment, the participants were randomly assigned into two treatments: groups with both moderation and deliberative norms, and ‘placebo’ groups. Our dependent variables consist of participants’ self-reported experiences of being heard in the discussion, and their feelings of mutual respect. The results show that all participants—regardless of group level disagreement—tend to be satisfied with deliberation. The only exception is the first experiment, where disagreement decreased process satisfaction slightly. At the individual level, participants’ deviation from the group mean had almost no effect.
Minimal important change (MIC): a conceptual clarification and systematic review of MIC estimates of PROMIS measures
Authors: Terwee Caroline B. , Peipert John Devin , Chapman Robert , Lai Jin-Shei , Terluin Berend , Cella David , Griffiths Pip , Mokkink Lidwine B.
Published: July 2021

We define the minimal important change (MIC) as a threshold for a minimal within-person change over time above which patients perceive themselves importantly changed. There is a lot of confusion about the concept of MIC, particularly about the concepts of minimal important change and minimal detectable change, which questions the validity of published MIC values. The aims of this study were: (1) to clarify the concept of MIC and how to use it; (2) to provide practical guidance for estimating methodologically sound MIC values; and (3) to improve the applicability of PROMIS by summarizing the available evidence on plausible PROMIS MIC values. We discuss the concept of MIC and how to use it and provide practical guidance for estimating MIC values. In addition, we performed a systematic review in PubMed on MIC values of any PROMIS measure from studies using recommended approaches. A total of 50 studies estimated the MIC of a PROMIS measure, of which 19 studies used less appropriate methods. MIC values of the remaining 31 studies ranged from 0.1 to 12.7 T-score points. We recommend to use the predictive modeling method, possibly supplemented with the vignette-based method, in future MIC studies. We consider a MIC value of 2–6 T-score points for PROMIS measures reasonable to assume at this point. For surgical interventions a higher MIC value might be appropriate. We recommend more high-quality studies estimating MIC values for PROMIS.
Carboxymethylation of cinnamylalcohol with dimethyl carbonate over the slag-based catalysts
Authors: Kholkina Ekaterina , Kumar Narendra , Eränen Kari , Russo Vincenzo , Rahkila Jani , Peurla Markus , Wärnå Johan , Lehtonen Juha , Murzin Dmitry Yu.
Published: July 2021

The carboxymethylation of cinnamylalcohol with dimethyl carbonate was performed using low-cost catalysts obtained from desulfurization slag. Processing of steel slag performed by different techniques was resulted in a wide range of the catalysts with different morphological and structural properties. Catalytic evaluation of the slag catalysts illustrated diversity of the obtained results strongly dependent on the surface area, crystal morphology and basicity. Catalytic materials demonstrated high variability of the conversion (8–85%) exhibiting similar selectivity to the desired product – cinnamyl methyl carbonate (ca. 80%). A significant impact of ultrasonication on catalytic activity was observed. Comparison of the synthesized samples with commercial basic materials illustrated competitive ability of the slag catalysts. Based on the results of catalytic evaluation and product analysis the reaction network was proposed and verified by thermodynamic analysis. A kinetic model was developed to describe concentration dependencies in carboxymethylation.
Analysing the evolution of computer science events leveraging a scholarly knowledge graph: a scientometrics study of top-ranked events in the past decade
Authors: Lackner Arthur , Fathalla Said , Nayyeri Mojtaba , Behrend Andreas , Manthey Rainer , Auer Sören , Lehmann Jens , Vahdati Sahar
Published: July 2021

The publish or perish culture of scholarly communication results in quality and relevance to be are subordinate to quantity. Scientific events such as conferences play an important role in scholarly communication and knowledge exchange. Researchers in many fields, such as computer science, often need to search for events to publish their research results, establish connections for collaborations with other researchers and stay up to date with recent works. Researchers need to have a meta-research understanding of the quality of scientific events to publish in high-quality venues. However, there are many diverse and complex criteria to be explored for the evaluation of events. Thus, finding events with quality-related criteria becomes a time-consuming task for researchers and often results in an experience-based subjective evaluation. OpenResearch.org is a crowd-sourcing platform that provides features to explore previous and upcoming events of computer science, based on a knowledge graph. In this paper, we devise an ontology representing scientific events metadata. Furthermore, we introduce an analytical study of the evolution of Computer Science events leveraging the OpenResearch.org knowledge graph. We identify common characteristics of these events, formalize them, and combine them as a group of metrics. These metrics can be used by potential authors to identify high-quality events. On top of the improved ontology, we analyzed the metadata of renowned conferences in various computer science communities, such as VLDB, ISWC, ESWC, WIMS, and SEMANTiCS, in order to inspect their potential as event metrics.
Cross-country learning from patents: an analysis of citations flows in innovation trajectories
Authors: Giglio Carlo , Sbragia Roberto , Musmanno Roberto , Palmieri Roberto
Published: July 2021

This study proposes a methodological approach to investigate cross-country creativity/knowledge flows by analyzing patent citation networks, taking the aircraft, aviation and cosmonautics (AAC) industry as a case study. It aims at shedding some light on the following research questions: (a) how cross-country creative/learning flows can be investigated; (b) have countries of current patent owners benefited from patent acquisitions. In fact, despite the well-established economic interest for (analyzing and forecasting) innovation trajectories, this research area is still unexplored, thus, motivating the need for such study. Over 43,000,000 patents have been analyzed whereby: (a) owners have performed cross-country patent acquisitions; (b) acquired patents (granted within 2005–2009) are cited by subsequent patents (2010–2015). Methodology and results are scalable to other industries and can be exploited by managers and policy makers to: (a) help firms forecasting innovation trajectories; (b) support governments in designing/implementing measures nurturing patented innovations in industries deemed relevant to national interest.
News media attention in Climate Action: latent topics and open access
Authors: Dehdarirad Tahereh , Karlsson Kalle
Published: July 2021

In this study we investigated whether open access could assist the broader dissemination of scientific research in Climate Action (Sustainable Development Goal 13) via news outlets. We did this by comparing (i) the share of open and non-open access documents in different Climate Action topics, and their news counts, and (ii) the mean of news counts for open access and non-open access documents. The data set of this study comprised 70,206 articles and reviews in Sustainable Development Goal 13, published during 2014–2018, retrieved from SciVal. The number of news mentions for each document was obtained from Altmetrics Details Page API using their DOIs, whereas the open access statuses were obtained using Unpaywall.org. The analysis in this paper was done using a combination of (Latent Dirichlet allocation) topic modelling, descriptive statistics, and regression analysis. The covariates included in the regression analysis were features related to authors, country, journal, institution, funding, readability, news source category and topic. Using topic modelling, we identified 10 topics, with topics 4 (meteorology) [21%], 5 (adaption, mitigation, and legislation) [18%] and 8 (ecosystems and biodiversity) [14%] accounting for 53% of the research in Sustainable Development Goal 13. Additionally, the results of regression analysis showed that while keeping all the variables constant in the model, open access papers in Climate Action had a news count advantage (8.8%) in comparison to non-open access papers. Our findings also showed that while a higher share of open access documents in topics such as topic 9 (Human vulnerability to risks) might not assist with its broader dissemination, in some others such as topic 5 (adaption, mitigation, and legislation), even a lower share of open access documents might accelerate its broad communication via news outlets.
Lattice Boltzmann Modeling of Drying of Porous Media Considering Contact Angle Hysteresis
Authors: Qin Feifei , Zhao Jianlin , Kang Qinjun , Derome Dominique , Carmeliet Jan
Published: July 2021

Drying of porous media is governed by a combination of evaporation and movement of the liquid phase within the porous structure. Contact angle hysteresis induced by surface roughness is shown to influence multi-phase flows, such as contact line motion of droplet, phase distribution during drainage and coffee ring formed after droplet drying in constant contact radius mode. However, the influence of contact angle hysteresis on liquid drying in porous media is still an unanswered question. Lattice Boltzmann model (LBM) is an advanced numerical approach increasingly used to study phase change problems including drying. In this paper, based on a geometric formulation scheme to prescribe contact angle, we implement a contact angle hysteresis model within the framework of a two-phase pseudopotential LBM. The capability and accuracy of prescribing and automatically measuring contact angles over a large range are tested and validated by simulating droplets sitting on flat and curved surfaces. Afterward, the proposed contact angle hysteresis model is validated by modeling droplet drying on flat and curved surfaces. Then, drying of two connected capillary tubes is studied, considering the influence of different contact angle hysteresis ranges on drying dynamics. Finally, the model is applied to study drying of a dual-porosity porous medium, where phase distribution and drying rate are compared with and without contact angle hysteresis. The proposed model is shown to be capable of dealing with different contact angle hysteresis ranges accurately and of capturing the physical mechanisms during drying in different porous media including flat and curved geometries.
Shape My Face: Registering 3D Face Scans by Surface-to-Surface Translation
Authors: Bahri Mehdi , O’ Sullivan Eimear , Gong Shunwang , Liu Feng , Liu Xiaoming , Bronstein Michael M. , Zafeiriou Stefanos
Published: July 2021

Standard registration algorithms need to be independently applied to each surface to register, following careful pre-processing and hand-tuning. Recently, learning-based approaches have emerged that reduce the registration of new scans to running inference with a previously-trained model. The potential benefits are multifold: inference is typically orders of magnitude faster than solving a new instance of a difficult optimization problem, deep learning models can be made robust to noise and corruption, and the trained model may be re-used for other tasks, e.g. through transfer learning. In this paper, we cast the registration task as a surface-to-surface translation problem, and design a model to reliably capture the latent geometric information directly from raw 3D face scans. We introduce Shape-My-Face (SMF), a powerful encoder-decoder architecture based on an improved point cloud encoder, a novel visual attention mechanism, graph convolutional decoders with skip connections, and a specialized mouth model that we smoothly integrate with the mesh convolutions. Compared to the previous state-of-the-art learning algorithms for non-rigid registration of face scans, SMF only requires the raw data to be rigidly aligned (with scaling) with a pre-defined face template. Additionally, our model provides topologically-sound meshes with minimal supervision, offers faster training time, has orders of magnitude fewer trainable parameters, is more robust to noise, and can generalize to previously unseen datasets. We extensively evaluate the quality of our registrations on diverse data. We demonstrate the robustness and generalizability of our model with in-the-wild face scans across different modalities, sensor types, and resolutions. Finally, we show that, by learning to register scans, SMF produces a hybrid linear and non-linear morphable model. Manipulation of the latent space of SMF allows for shape generation, and morphing applications such as expression transfer in-the-wild. We train SMF on a dataset of human faces comprising 9 large-scale databases on commodity hardware.
Planning and Suitability Assessment of Large-scale Nature-based Solutions for Flood-risk Reduction
Authors: Mubeen Adam , Ruangpan Laddaporn , Vojinovic Zoran , Sanchez Torrez Arlex , Plavšić Jasna
Published: July 2021

Adverse effects of climate change are increasing around the world and the floods are posing significant challenges for water managers. With climate projections showing increased risks of storms and extreme precipitation, the use of traditional measures alone is no longer an option. Nature-Based Solutions (NBS) offer a suitable alternative to reduce the risk of flooding and provide multiple benefits. However, planning such interventions requires careful consideration of various factors and local contexts. The present paper provides contribution in this direction and it proposes a methodology for allocation of large-scale NBS using suitability mapping. The methodology was implemented within the toolboxes of ESRI ArcMap software in order to map suitability for four types of NBS interventions: floodplain restoration, detention basins, retention ponds, and river widening. The toolboxes developed were applied to the case study area in Serbia, i.e., the Tamnava River basin. Flood maps were used to determine the volume of floodwater that needs to be stored for reducing flood risk in the basin and subsequent downstream areas. The suitability maps produced indicate the potential of the new methodology and its application as a decision-support tool for selection and allocation of large-scale NBS.
Retention of eucalyptus harvest residues reduces soil compaction caused by deep subsoiling
Authors: de Melo Raphael Oliveira , da Fonseca Aymbiré Angeletti , de Barros Nairam Félix , Fernandes Raphael Bragança Alves , Teixeira Rafael da Silva , Melo Iago Nery , Martins Ricardo Previdente
Published: July 2021

Eucalyptus harvesting, forwarding and soil tillage operations are among the main causes for compaction of forest soils, with potential impacts on productivity. This concern is especially important in areas with soils that are naturally compacted (fragipans and duripans). In these soils, tillage operations include the use of subsoilers that can reach depths of more than one meter and require heavy tractors that exert high pressure on the soil. One of the ways to try to minimize the effect of this compaction is by retaining harvest residues. The objective of this study was to evaluate the impacts of eucalyptus harvesting on soil physical attributes, as well as to determine the potential of different types of residue management to reduce compaction from the soil tillage operation. Two experiments were conducted in the same area with a Yellow Argisol. In the first experiment, compaction caused by mechanized harvesting with harvester + forwarder was evaluated. In the second experiment, different managements of harvest residues were examined as potential modifiers of soil compaction during tillage for new plantings. For this, three managements systems were tested: (1) retention of all harvest residues and litter from the previous rotation (HR + L), (2) retention of litter from the previous rotation (L), and (3) removal of harvest residues and litter from the previous rotation (WR). Before and after harvest, sampling was carried out in the planting rows and inter-rows, and after tillage, samples were collected in the traffic line of the subsoiler-tractor set. In both experiments, undisturbed soil samples were collected from the center of the 0–10, 10–20, 20–40, 40–60, and 60–100 cm layers to determine soil density and total porosity. In each period and site of evaluation, mechanical resistance to penetration up to the 60-cm depth was also determined. The harvesting operation increased soil density at 0–10 and 60–100 cm depths only in the inter-rows. Retention of harvest residues and litter (HR + L) after harvesting avoided increases in soil density and penetration resistance caused by machine traffic during tillage. The results indicate the importance of retaining harvest residues on forest soils for achieving sustainable utilization and for conserving soil quality.
The archbishop’s dinner? Late medieval fish from Esztergom-Várhegy-Kőbánya, Hungary
Authors: Bartosiewicz László , Gál Erika
Published: July 2021

Fourteenth–fifteenth century food refuse from the kitchen of the Esztergom archbishopric shows a significant diachronic increase in cyprinid bones, in particular those of carp. Meanwhile, contributions by large acipenserids and carnivorous species (catfish/wels, pike, percids) declined. Contemporaneous account books indirectly suggest that the archbishop’s kitchen must have increasingly relied on farmed carp fish. Sturgeons were a commodity sold by the archbishopric but rarely consumed. Expensive pikes were bought at low prices for the archbishop, possibly related to the small size of individuals found in the deposits. The poor representation of high-status fish is consonant with the scarcity of bones from large game in an assemblage dominated by domesticates. Wild game is represented by brown hare, partridge, and a variety of thrushes. These finds confirm that the foodways in the archbishop’s palace were more modest than expected on the basis of its social status. Increasing contributions by cyprinids and sterlet to the assemblage also coincide with the high relative frequency of their recipes in a sixteenth century cookbook.
Biophysical reviews top five: atomic force microscopy in biophysics
Authors: Ando Toshio
Published: July 2021

Since its invention in the late 1980s, atomic force microscopy (AFM), in which a nanometer-sized tip is used to physically interrogate the properties of a surface at high resolution, has brought about scientific revolutions in both surface science and biological physics. In response to a request from the journal, I have prepared a top-five list of scientific papers that I feel represent truly landmark developments in the use of AFM in the biophysics field. This selection is necessarily limited by number (just five) and subjective (my opinion) and I offer my apologies to those not appearing in this list.
Mining Knowledge of Respiratory Rate Quantification and Abnormal Pattern Prediction
Authors: Szczuko Piotr , Kurowski Adam , Odya Piotr , Czyżewski Andrzej , Kostek Bożena , Graff Beata , Narkiewicz Krzysztof
Published: July 2021

The described application of granular computing is motivated because cardiovascular disease (CVD) remains a major killer globally. There is increasing evidence that abnormal respiratory patterns might contribute to the development and progression of CVD. Consequently, a method that would support a physician in respiratory pattern evaluation should be developed. Group decision-making, tri-way reasoning, and rough set–based analysis were applied to granular computing. Signal attributes and anthropomorphic parameters were explored to develop prediction models to determine the percentage contribution of periodic-like, intermediate, and normal breathing patterns in the analyzed signals. The proposed methodology was validated employing k-nearest neighbor (k-NN) and UMAP (uniform manifold approximation and projection). The presented approach applied to respiratory pattern evaluation shows that median accuracies in a considerable number of cases exceeded 0.75. Overall, parameters related to signal analysis are indicated as more important than anthropomorphic features. It was also found that obesity characterized by a high WHR (waist-to-hip ratio) and male sex were predisposing factors for the occurrence of periodic-like or intermediate patterns of respiration. It may be among the essential findings derived from this study. Based on classification measures, it may be observed that a physician may use such a methodology as a respiratory pattern evaluation-aided method.
Morphological Variability of Silica Polymorphs within Crustal Xenoliths from Tapi Dyke Swarm, Northern Deccan Traps and their Petrogenetic Significance
Authors: Bhardwaj Savyasachi , Monteiro Aristle , Bhoyar Chandrakant , Duraiswami Raymond A.
Published: July 2021

Crustal xenoliths, mostly of granite gneiss, occur within mafic dykes from Ranala, Rajmane-Talwade and Vadli from within the Tapi rift, northern Deccan Traps. Many xenoliths are highly brecciated, show mylonite textures and rare pseudotachylite streaks. Widespread occurrence of tridymite and cristobalite± sanidine is confirmed in xenoliths in thin sections, scanning electron micrographs and x-ray diffraction analyses. The silica polymorphs exhibit diverse morphologies. The xenoliths record widespread cataclastic metamorphism, and mineralogical phase transformations due to contact metamorphism at temperatures ranging from 1400 to >1710 °C and pressures <0.1 GPa corresponding to sanidinite hornfels facies. Xenolith-based present study provides explicit field and petrological evidences which supports geophysical signature of a highly fractured, sheared, and faulted Precambrian basement beneath the Tapi rift. Some of these tectonic features provided pathways for magmatic plumbing system (feeder dykes) related to the Deccan Trap volcanism.
Stability Assessment of Ukhrul-Jessami Road Cut Slopes, Ukhrul District, Manipur
Authors: Bidyashwari H. , Okendro M. , Kushwaha R.A.S. , Chandra M.
Published: July 2021

The present study is to assess the slope stability of road cuts along the National Highway 150 (202 present). Rock mass classification enables preliminary assessment of rock slope failure and guide the planners to choose suitable alignment for road construction and engineering structures. This technique includes collection of data from the intact rock and discontinuity parameters. Seven locations have been selected for slope stability analysis using RMR, SMR and CoSMR techniques. These empirical methods are used to determine the mode of failures and characterise the slope as well. Kinematic analysis deciphers the causes of instability and the mode of discontinuous rock failures. Results shows majority of road section between Ukhrul and Jessami falls under partial stable to unstable zone.