bluuebunny/crossref_metadata_2025 huggingface dataset:
“What works?” Systematic reviews and meta‐analyses of the investigative interviewing research literature
Authors: Meissner Christian A.
Published: February 2021

While the practice of investigative interviewing has traditionally been grounded in customary knowledge, decades of research have now enhanced our understanding of the limits of these practices and led to the development of novel, theoretically informed approaches. The maturity of any science is likely best evidenced in the conduct of systematic reviews and meta‐analyses, and the investigative interviewing research literature has reached just such a period in its development. This paper reviews current “best practices” in research synthesis, describes the variety of meta‐analyses conducted in the investigative interviewing research literature to date, and introduces the nine reviews that comprise the current special issue. It concludes by summarizing the lessons learned from these syntheses with respect to improving our research methods, measures, and approaches in the investigative interviewing literature.
Examination of Indium Triphospholyls as Precursors for Nanoparticle Synthesis
Authors: Rund Reinhard , Bauer Susanne , Stauber Andreas , Seidl Michael , Ojo Wilfried‐Solo , Ferrari Fabio , Chaudret Bruno , Nayral Céline , Delpech Fabien , Scheer Manfred
Published: February 2021

The synthesis and characterization of the new compounds K(P3C2R2) [R=Ad (2), sBu (3)] and In(P3C2R2) [R=Ad (4), Mes (5)] are described. Further, the synthesis of indium nanoparticles via a single‐source precursor approach using In(1,2,4‐P3C2tBu2) (1) as precursor is reported. These nanoparticles were characterized by TEM, HRTEM, EDX, XRD, NMR, and optical spectroscopy.
Intelligent task scheduling of distributed wireless sensor network to monitor building environment
Authors: Wang Yifei
Published: February 2021

A wireless sensor network (WSN) is constructed based on the distributed cyber‐physical system for the indoor environment of smart buildings. The task allocation strategy in WSN is designed by considering computable complexity and dynamic scheduling for the dynamic task scheduling problem in the smart building. First, each task is divided as several subtasks which are calculated by the appropriate computing nodes. Then, the sub‐tasks are allocated according to a task scheduling sequence table which is constructed by the scheduling priority. The tasks are processed in the order in task scheduling sequence table. The simulations show that the proposed task scheduling can effectively reduce the communication time and waiting time of tasks in the distributed and computable WSN in the intelligent building indoor environment. Meanwhile, it can also improve the success rate of task scheduling. Finally, the proposed task scheduling can optimize the operating efficiency of the smart building system.
ICN‐driven group psychology visualization analysis mechanism using reinforcement learning
Authors: Qin Yewen
Published: February 2021

Reinforcement Learning (RL) has been widely considered as a robust method to complete the large‐scale data analysis with high computation efficiency, learning ability, and stability, and it has been applied into many fields, such as transaction detection, trajectory identification, behavior recognition and so on. With the rapid progress of human society, people's psychological pressure gradually becomes heavier and heavier. In order to avoid the social tragedy, it is certainly worth doing the group psychology analysis. Therefore, this paper uses RL to achieve the group psychology visualization analysis instead of the abstract data presentation. In other words, this paper also handles the analyzed data results on the group psychology behaviors by the visualization method. In addition, in order to accelerate the process of data visualization under the large‐scale environment, this paper also introduces the concept of Information‐Centric Networking (ICN) paradigm to support the name‐based community detection by separating IP addresses. The experiments include two parts. On one hand, RL‐based group psychology analysis method is evaluated. On the other hand, ICN‐based visualization method is evaluated. The results prove that the integrated group psychology visualization analysis mechanism is acceptable.
Nonlinear iterative perturbation scheme with simplified spherical harmonics (SP3) light propagation model for quantitative photoacoustic tomography
Authors: Wang Yihan , Xu Menglu , Gao Feng , Kang Fei , Zhu Shouping
Published: February 2021

When using quantitative photoacoustic tomography (q‐PAT) reconstruction to recover the optical absorption coefficients of tissue, the commonly used diffusion equation has several limitations in the case of the objects that have small geometries and high‐absorption or low‐scattering areas. Furthermore, the conventional perturbation reconstruction strategy is unsatisfactory when the target tissue containing large heterogeneous features. We herein present a modified q‐PAT implementation that employs the higher‐order photon migration model achieving the tradeoff between mathematical rigidity and computational efficiency. Besides, a nonlinear iterative method is proposed to obtain the perturbations of optical absorption considering the updating of the sensitivity matrix in calculating the fluence perturbations. Consequently, the distribution of tissue optical properties can be recovered in a robust way even if the targets with high absorption are included. The proposed approach has been validated by simulation, phantom and in vivo experiments, exhibiting promising performances in image fidelity and quantitative feasibility for practical applications.
Effects of transglutaminase glycosylated soy protein isolate on its structure and interfacial properties
Authors: Zhang Anqi , Cui Qiang , Yu Zhichao , Wang Xibo , Zhao Xin‐huai
Published: February 2021

BACKGROUNDS

The structural and interfacial properties of soybean protein isolate (SPI) after glycosylation by the transglutaminase method were studied. It is hoped that preliminary explorations will find a new food ingredient and broader application of SPI in the food industry.

RESULTS

The contents of free amino proves that transglutaminase can insert glucosamine into SPI through its transamination, and realize the enzymatic glycosylated SPI. The results of structure properties showed that a decrease in the content of the α‐helical structure indicates that the rigid structure of the protein is opened and the flexibility is increased. The blue shift of the maximum fluorescence intensity of soy protein isolate‐glucosamine with transglutaminase (SPI‐G) indicates the formation of a new substance; scanning electron microscopy shows that the SPI‐G powder can be seen at a magnification of 2000×, and the protein structure becomes soft. The results of interfacial properties found that enzymatic protein glycosylation exposes the internal hydrophobic groups of SPI, resulting in increased surface hydrophobicity, increased emulsification and emulsification stability, and reduced surface tension.

CONCLUSION

It shows that SPI‐G effectively improves the interfacial properties of SPI, providing a theoretical basis for the application of enzymatic glycosylation of SPI in the food industry. © 2021 Society of Chemical Industry
The leucine zipper EF‐hand containing transmembrane protein‐1 EF‐hand is a tripartite calcium, temperature, and pH sensor
Authors: Lin Qi‐Tong , Lee Rachel , Feng Allen L. , Kim Michael S. , Stathopulos Peter B.
Published: February 2021

Leucine Zipper EF‐hand containing transmembrane protein‐1 (LETM1) is an inner mitochondrial membrane protein that mediates mitochondrial calcium (Ca2+)/proton exchange. The matrix residing carboxyl (C)‐terminal domain contains a sequence identifiable EF‐hand motif (EF1) that is highly conserved among orthologues. Deletion of EF1 abrogates LETM1 mediated mitochondrial Ca2+ flux, highlighting the requirement of EF1 for LETM1 function. To understand the mechanistic role of this EF‐hand in LETM1 function, we characterized the biophysical properties of EF1 in isolation. Our data show that EF1 exhibits α‐helical secondary structure that is augmented in the presence of Ca2+. Unexpectedly, EF1 features a weak (~mM), but specific, apparent Ca2+‐binding affinity, consistent with the canonical Ca2+ coordination geometry, suggested by our solution NMR. The low affinity is, at least in part, due to an Asp at position 12 of the binding loop, where mutation to Glu increases the affinity by ~4‐fold. Further, the binding affinity is sensitive to pH changes within the physiological range experienced by mitochondria. Remarkably, EF1 unfolds at high and low temperatures. Despite these unique EF‐hand properties, Ca2+ binding increases the exposure of hydrophobic regions, typical of EF‐hands; however, this Ca2+‐induced conformational change shifts EF1 from a monomer to higher order oligomers. Finally, we showed that a second, putative EF‐hand within LETM1 is unreactive to Ca2+ either in isolation or tandem with EF1. Collectively, our data reveal that EF1 is structurally and biophysically responsive to pH, Ca2+ and temperature, suggesting a role as a multipartite environmental sensor within LETM1.
New pre‐attachment Striga resistant sorghum adapted to African agro‐ecologies
Authors: Mallu Tesfamichael S , Mutinda Sylvia , Githiri Stephen M , Achieng Odeny Damaris , Runo Steven
Published: February 2021

BACKGROUND

Pre‐attachment resistance to the parasitic plants Striga hermonthica and S. asiatica occurs in sorghum mutants designated low germination stimulant 1 (lgs1). However, only a few of these mutants have been identified and their resistance validated. Additionally, pre‐attachment resistance in sorghum beyond lgs1 mutants has not been explored. We used lgs1‐specific markers to identify new lgs1‐like mutants in a diverse global sorghum collection. The sorghum collection was also evaluated for pre‐attachment resistance against Striga using an in vitro assay that measured Striga germination activity and radicle growth.

RESULTS

From a total of 177 sorghum accessions, 60 recorded mean germination levels of below 42%, which is comparable with the previously identified lgs1‐like sorghum (SRN39 and IS9830) used as controls in this study. Furthermore, 32 of these accessions recorded Striga radicle lengths comparable or lower than the controls (0.42 mm). Thirty‐eight accessions contained the lgs1 mutation and although overall, lgs1 mutants had considerably reduced Striga germination, some low inducers of Striga germination were wild‐type for lgs1. Germination was positively but weakly correlated with radicle length pointing to additional radicle growth inhibitory activity.

CONCLUSIONS

lgs1 mutations, alongside other mechanisms for low Striga germination stimulation, are prevalent in sorghum, and poor Striga radicle growth is suggestive of host‐derived inhibition. As an outcome, our study makes available multiple Striga‐resistant sorghum with adaptability to diverse agro‐ecological regions in sub‐Saharan Africa making immediate deployment possible.

© 2021 Society of Chemical Industry
Weak cooling of the troposphere by tropical islands in simulations of the radiative‐convective equilibrium
Authors: Leutwyler David , Hohenegger Cathy
Published: February 2021

We assess whether tropical islands tend to warm or cool the troposphere. To this end, we use idealized simulations of the radiative‐convective equilibrium employing a simulation domain that contains flat tropical islands represented by a land surface scheme. Results show more frequent precipitation over land as coastal breezes establish, and gravity waves triggered by afternoon convection propagating away from the islands. These waves horizontally homogenize density and in doing so communicate convectively induced temperature anomalies from the islands onto the ocean. What is the influence of the islands on tropospheric temperature? The diurnal surface warming of the islands tends to push the afternoon convection over land towards a warmer moist adiabat and, along with it, the temperature profile of the troposphere. However, at the same time, drying of the land surface pulls it towards a colder moist adiabat. All in all, we find that islands cool rather than warm the troposphere. More specifically, we obtain a weakly colder domain‐mean troposphere during episodes with a larger share of precipitation over land, or when the prescribed land fraction is increased. In particular, we find that the cooling becomes more pronounced over large islands. Overall, the results indicate that the inability of evaporation to keep up with the daytime surface warming over land, in contrast to the ocean, is of key relevance for understanding land effects on the mean climate.
AI Nuclear Winter or AI That Saves Humanity? AI and Nuclear Deterrence
Authors: Akiyama Nobumasa
Published: February 2021

Nuclear deterrence is an integral aspect of the current security architecture and the question has arisen whether adoption of AI will enhance the stability of this architecture or weaken it. The stakes are very high. Stable deterrence depends on a complex web of risk perceptions. All sorts of distortions and errors are possible, especially in moments of crisis. AI might contribute toward reinforcing the rationality of decision-making under these conditions (easily affected by the emotional disturbances and fallacious inferences to which human beings are prone), thereby preventing an accidental launch or unintended escalation. Conversely, judgments about what does or does not suit the “national interest” are not well suited to AI (at least in its current state of development). A purely logical reasoning process based on the wrong values could have disastrous consequences, which would clearly be the case if an AI-based machine were allowed to make the launch decision (this virtually all experts would emphatically exclude), but grave problems could similarly arise if a human actor relied too heavily on AI input.
Robots and Rights: Reviewing Recent Positions in Legal Philosophy and Ethics
Authors: Schröder Wolfgang M.
Published: February 2021

Controversies about the moral and legal status of robots and of humanoid robots in particular are among the top debates in recent practical philosophy and legal theory. As robots become increasingly sophisticated, and engineers make them combine properties of tools with seemingly psychological capacities that were thought to be reserved for humans, such considerations become pressing. While some are inclined to view humanoid robots as more than just tools, discussions are dominated by a clear divide: What some find appealing, others deem appalling, i.e. “robot rights” and “legal personhood” for AI systems. Obviously, we need to organize human–robot interactions according to ethical and juridical principles that optimize benefit and minimize mutual harm. Avoiding disrespectful treatment of robots can help to preserve a normative basic ethical continuum in the behaviour of humans. This insight can contribute to inspire an “overlapping consensus” as conceptualized by John Rawls in further discussions on responsibly coordinating human/robot interactions.
What Is Consciousness, and Could Machines Have It?
Authors: Dehaene Stanislas , Lau Hakwan , Kouider Sid
Published: February 2021

The controversial question of whether machines may ever be conscious must be based on a careful consideration of how consciousness arises in the only physical system that undoubtedly possesses it: the human brain. We suggest that the word “consciousness” conflates two different types of information-processing computations in the brain: the selection of information for global broadcasting, thus making it flexibly available for computation and report (C1, consciousness in the first sense), and the self-monitoring of those computations, leading to a subjective sense of certainty or error (C2, consciousness in the second sense). We argue that despite their recent successes, current machines are still mostly implementing computations that reflect unconscious processing (C0) in the human brain. We review the psychological and neural science of unconscious (C0) and conscious computations (C1 and C2) and outline how they may inspire novel machine architectures.
Resourceful Program Synthesis from Graded Linear Types
Authors: Hughes Jack , Orchard Dominic
Published: February 2021

Linear types provide a way to constrain programs by specifying that some values must be used exactly once. Recent work ongraded modal typesaugments and refines this notion, enabling fine-grained, quantitative specification of data use in programs. The information provided by graded modal types appears to be useful for type-directed program synthesis, where these additional constraints can be used to prune the search space of candidate programs. We explore one of the major implementation challenges of a synthesis algorithm in this setting: how does the synthesis algorithm efficiently ensure that resource constraints are satisfied throughout program generation? We provide two solutions to thisresource managementproblem, adapting Hodas and Miller’s input-output model of linear context management to a graded modal linear type theory. We evaluate the performance of both approaches via their implementation as a program synthesis tool for the programming language Granule, which provides linear and graded modal typing.
Mitochondrial outer membrane permeabilization at the single molecule level
Authors: Dadsena Shashank , Jenner Andreas , García-Sáez Ana J.
Published: February 2021

Apoptotic cell death is essential for development, immune function or tissue homeostasis, and its mis-regulation is linked to various diseases. Mitochondrial outer membrane permeabilization (MOMP) is a central event in the intrinsic apoptotic pathway and essential to control the execution of cell death. Here we review current concepts in regulation of MOMP focusing on the interaction network of the Bcl-2 family proteins as well as further regulatory elements influencing MOMP. As MOMP is a complex spatially and temporally controlled process, we point out the importance of single-molecule techniques to unveil processes which would be masked by ensemble measurements. We report key single-molecule studies applied to decipher the composition, assembly mechanism and structure of protein complexes involved in MOMP regulation.
Corticosteroid enhances epithelial barrier function in intestinal organoids derived from patients with Crohn’s disease
Authors: Xu Pan , Elizalde Montserrat , Masclee Ad , Pierik Marieke , Jonkers Daisy
Published: February 2021

Corticosteroids (CS), first-line therapeutics for Crohn’s disease (CD) with moderate or severe disease activity, were found to restore intestinal permeability in CD patients, whereas the underlying molecular events are still largely unknown. This study aimed to investigate the effect and mechanisms of CS prednisolone on epithelial barrier using CD patient-derived intestinal organoids. 3D intestinal organoids were generated from colon biopsies of inactive CD patients. To mimic the inflammatory microenvironment, a mixture of cytokines containing TNF-α, IFN-γ, and IL-1β were added to the organoid culture with or without pre-incubation of prednisolone or mifepristone. Epithelial permeability of the organoids was assessed by FITC-D4 flux from the basal to luminal compartment using confocal microscopy. Expression of junctional components were analyzed by qRT-PCR, immunofluorescence staining, and western blot. Activity of signaling pathways were analyzed using western blot. Exposure of the cytokines significantly disrupted epithelial barrier of the intestinal organoids, which was partially restored by prednisolone. On the molecular level, the cytokine mixture resulted in a significant reduction in E-cadherin and ILDR-1, an increase in CLDN-2, MLCK, and STAT1 phosphorylation, whereas prednisolone ameliorated the abovementioned effects induced by the cytokine mixture. This study demonstrates that prednisolone confers a direct effect in tightening the epithelial barrier, identifies novel junctional targets regulated by prednisolone, and underscores intestinal barrier restoration as a potential mechanism that contributes to the clinical efficacy of prednisolone in CD patients.

Key messages

Prednisolone confers a direct preventive effect against cytokine-induced barrier dysfunction.

Prednisolone regulates the expression of CLDN-2, E-cadherin, and ILDR-1.

The effect of prednisolone is GR-, MLCK-, and STAT1-dependent.
Resting-state networks in the course of aging—differential insights from studies across the lifespan vs. amongst the old
Authors: Jockwitz C. , Caspers S.
Published: February 2021

Resting-state functional connectivity (RSFC) has widely been used to examine reorganization of functional brain networks during normal aging. The extraction of generalizable age trends, however, is hampered by differences in methodological approaches, study designs and sample characteristics. Distinct age ranges of study samples thereby represent an important aspect between studies especially due to the increase in inter-individual variability over the lifespan. The current review focuses on comparing age-related differences in RSFC in the course of the whole adult lifespan versus later decades of life. We summarize and compare studies assessing age-related differences in within- and between-network RSFC of major resting-state brain networks. Differential effects of the factor age on resting-state networks can be identified when comparing studies focusing on younger versus older adults with studies investigating effects within the older adult population. These differential effects pertain to higher order and primary processing resting-state networks to a varying extent. Especially during later decades of life, other factors beyond age might come into play to understand the high inter-individual variability in RSFC.
The effect of hydrogeological and hydrochemical dynamics on landslide triggering in the central highlands of Ethiopia
Authors: Mebrahtu Tesfay Kiros , Banning Andre , Girmay Ermias Hagos , Wohnlich Stefan
Published: February 2021

The volcanic terrain at the western margin of the Main Ethiopian Rift in the Debre Sina area is known for its slope stability problems. This report describes research on the effects of the hydrogeological and hydrochemical dynamics on landslide triggering by using converging evidence from geological, geomorphological, geophysical, hydrogeochemical and isotopic investigations. The chemical characterization indicates that shallow to intermediate aquifers cause groundwater flow into the landslide mass, influencing long-term groundwater-level fluctuations underneath the landslide and, as a consequence, its stability. The low content of total dissolved solids and the bicarbonate types (Ca–Mg–HCO3and Ca–HCO3) of the groundwater, and the dominantly depleted isotopic signature, indicate a fast groundwater flow regime that receives a high amount of precipitation. The main causes of the landslide are the steep slope topography and the pressure formed during precipitation, which leads to an increased weight of the loose and weathered materials. The geophysical data indicate that the area is covered by unconsolidated sediments and highly decomposed and weak volcanic rocks, which are susceptible to sliding when they get moist. The heterogeneity of the geological materials and the presence of impermeable layers embodied within the highly permeable volcanic rocks can result in the build-up of hydrostatic pressure at their interface, which can trigger landslides. Intense fracturing in the tilted basalt and ignimbrite beds can also accelerate infiltration of water, resulting to the build-up of high hydrostatic pressure causing low effective normal stress in the rock mass, giving rise to landslides.
Assessment of the effect of water-table depth on riparian vegetation along the middle and lower reaches of the Manasi River, Northwest China
Authors: Wang Zhan , Wang Wenke , Zhang Zaiyong , Hou Xinyue , Duan Lei , Yao Dongjie
Published: February 2021

The Manasi riparian zone in northwestern China has become a survival habitat for numerous native plant species and requires urgent protection owning to rapid expansion of farmland. The critical factor affecting the growth of desert riparian vegetation in arid regions is recognized to be groundwater, but in this region the threshold of water-table depth for riparian species has been rarely studied. To determine the association between species and their major growth factors and to ascertain the water-table depth threshold, this study employed field investigation, a logarithm distribution model and canonical correspondence analysis. According to the findings, (1) the water-table depth largely regulates the species distribution; (2) from the results of the logarithm distribution model, the water-table depth appropriate for herbs is 1–1.5 m and for shrubs it is 2–4 m, and a water-table depth of less than 6 m could satisfy the growth requirement of major species; (3) species diversity peaks at the water-table depths of 2–3, 3–5, and 2–4 m for herbs, shrubs and all species, respectively; (4) the frequency of appearance ofPhragmites communis(grass herb) andTamarix chinensis(deciduous shrub) was not as sensitive to depth to water table. To reconstruct a riparian zone,Phragmites communisandTamarix chinensiscould be planted in areas with water-table depth of less than 3 m and 2–5 m, respectively. These results may contribute to suitable policy regarding vegetation restoration.
Can a More Variable Species Win Interspecific Competition?
Authors: Uchmański Janusz
Published: February 2021

An individual-based approach is used to describe population dynamics. Two kinds of models have been constructed with different distributions illustrating individual variability. In both models, the growth rate of an individual and its final body weight at the end of the growth period, which determines the number of offspring, are functions of the amount of resources assimilated by an individual. In the model with a symmetric distribution, the half saturation constant in the Michaelis–Menten function describing the relationship between the growth of individuals and the amount of resources has a normal distribution. In the model with an asymmetric distribution, resources are not equally partitioned among individuals. The individual who acquired more resources in the past, will acquire more resources in the future. A single population comprising identical individuals has a very short extinction time. If individuals differ in the amount of food assimilated, this time significantly increases irrespectively of the type of model describing population dynamics. Individuals of two populations of competing species use common resources. For larger differences in individual variability, the more variable species will have a longer extinction time and will exclude less variable species. Both populations can also coexist when their variabilities are equal or even when they are slightly different, in the latter case under the condition of high variability of both species. These conclusions have a deterministic nature in the case of the model with the asymmetric distribution—repeated simulations give the same results. In the case of the model with the symmetric distribution, these conclusions are of a statistical nature—if we repeat the simulation many times, then the more variable species will have a longer extinction time more frequently, but some results will happen (although less often) when the less variable species has a longer extinction time. Additionally, in the model with the asymmetric distribution, the result of competition will depend on the way of the introduction of variability into the model. If the higher variability is due to an increase in the proportion of individuals with a low assimilation of resources, it can produce a longer extinction time of the less variable species.
Creating a robot localization monitor using particle filter and machine learning approaches
Authors: Eder Matthias , Reip Michael , Steinbauer Gerald
Published: February 2021

Robot localization is a fundamental capability of all mobile robots. Because of uncertainties in acting and sensing, and environmental factors such as people flocking around robots, there is always the risk that a robot loses its localization. Very often behaviors of robots rely on a reliable position estimation. Thus, for dependability of robot systems it is of great interest for the system to know the state of its localization component. In this paper we present an approach that allows a robot to asses if the localization is still correct. The approach assumes that the underlying localization approach is based on a particle filter. We use deep learning to identify temporal patterns in the particles in the case of losing/lost localization. These patterns are then combined with weak classifiers from the particle set and sensor perception for boosted learning of a localization estimator. Through the extraction of features generated by neural networks and its usage for training strong classifiers, the robots localization accuracy can be estimated. The approach is evaluated in a simulated transport robot environment where a degraded localization is provoked by disturbances cased by dynamic obstacles. Results show that it is possible to monitor the robots localization accuracy using convolutional as well as recurrent neural networks. The additional boosting using Adaboost also yields an increase in training accuracy. Thus, this paper directly contributes to the verification of localization performance.
North American channel catfish, Ictalurus punctatus: a neglected but potentially invasive freshwater fish species?
Authors: Haubrock Phillip J. , Copp Gordon H. , Johović Iva , Balzani Paride , Inghilesi Alberto F. , Nocita Annamaria , Tricarico Elena
Published: February 2021

The North American channel catfishIctalurus punctatushas been introduced to several locations in Europe but has received little or no scientific study despite its invasive attributes, including prolific reproduction, tolerance to a wide range of conditions, opportunistic feeding, at least partial ‘predator release’, and some evidence of environmental impacts (e.g. disease transmission). To assess the species’ potential invasiveness and the likely risks to native species and ecosystems in Europe, available literature from both North America and Europe was reviewed and used to carry out risk screenings of the species for the risk assessment areas, North and South Italy, using the Aquatic Invasiveness Screening Kit (AS-ISK), which was followed by a more detailed evaluation (for both North America and Europe) of the species’ potential impacts using the Environmental Impact Classification of Alien Taxa (EICAT) assessment protocol. The AS-ISK score indicated that channel catfish is likely to pose a high risk of being invasive in both North and South Italy, with EICAT scores indicating “Major” impacts for both North America and Europe, at high and medium confidence levels, respectively. The present results emphasise the urgent need to carry out in-depth studies on introduced populations of this species to understand better its invasive potential so as to inform management decisions on the appropriate control or eradication measures for invaded water bodies.
Added value of cardiovascular calcifications for prediction of recurrent cardiovascular events and cardiovascular interventions in patients with established cardiovascular disease
Authors: van ’t Klooster Cilie C. , van der Graaf Yolanda , Nathoe Hendrik M. , Bots Michiel L. , de Borst Gert J. , Visseren Frank L. J. , Leiner Tim ,   the UCC-SMART-study group, Asselbergs F. W. , Nathoe H. M. , de Borst G. J. , Bots M. L. , Geerlings M. I. , Emmelot M. H. , de Jong P. A. , Leiner T. , Lely A. T. , van der Kaaij N. P. , Kappelle L. J. , Ruigrok Y. M. , Verhaar M. C. , Visseren F. L. J. , Westerink J.
Published: February 2021

The purpose is to investigate the added prognostic value of coronary artery calcium (CAC), thoracic aortic calcium (TAC), and heart valve calcium scores for prediction of a combined endpoint of recurrent major cardiovascular events and cardiovascular interventions (MACE +) in patients with established cardiovascular disease (CVD). In total, 567 patients with established CVD enrolled in a substudy of the UCC-SMART cohort, entailing cardiovascular CT imaging and calcium scoring, were studied. Five Cox proportional hazards models for prediction of 4-year risk of MACE + were developed; traditional CVD risk predictors only (model I), with addition of CAC (model II), TAC (model III), heart valve calcium (model IV), and all calcium scores (model V). Bootstrapping was performed to account for optimism. During a median follow-up of 3.43 years (IQR 2.28–4.74) 77 events occurred (MACE+). Calibration of predicted versus observed 4-year risk for model I without calcium scores was good, and the c-statistic was 0.65 (95%CI 0.59–0.72). Calibration for models II–V was similar to model I, and c-statistics were 0.67, 0.65, 0.65, and 0.68 for model II, III, IV, and V, respectively. NRIs showed improvement in risk classification by model II (NRI 15.24% (95%CI 0.59–29.39)) and model V (NRI 20.00% (95%CI 5.59–34.92)), but no improvement for models III and IV. In patients with established CVD, addition of the CAC score improved performance of a risk prediction model with classical risk factors for the prediction of the combined endpoint MACE+ . Addition of the TAC or heart valve score did not improve risk predictions.
Origin, distribution, and perspective health benefits of particulate matter in the air of underground salt mine: a case study from Bochnia, Poland
Authors: Puławska Aleksandra , Manecki Maciej , Flasza Michał , Styszko Katarzyna
Published: February 2021

The composition and distribution of airborne particles in different locations in a salt mine were determined in terms of their origin, the distance from the air inlet, and the adaptation of post-mining chambers and corridors for tourists and general audience. The composition of aerosols in air was also evaluated from the perspective of human health. Air samples were collected on filters by using portable air pumps, in a historical underground salt mine in Bochnia (Poland), which is currently a touristic and recreation attraction and sanatorium. The particulate matter (PM) concentration was determined using the gravimetric method by weighing quartz filters. The content of carbon, water-soluble constituents, trace elements, and minerals was also determined. A genetic classification of the suspended matter was proposed and comprised three groups: geogenic (fragments of rock salt and associated minerals from the deposit), anthropogenic (carbon-bearing particles from tourist traffic and small amounts of fly ash, soot, and rust), and biogenic particles (occasional pollen). The total PM concentration in air varied between 21 and 79 μg/m3 (with PM4 constituting 4–24 μg/m3). The amount of atmospheric dust components coming from the surface was low and decreased with the distance from the intake shaft, thus indicating the self-cleaning process. NaCl dominated the water-soluble constituents, while Fe, Al, Ag, Mn, and Zn dominated the trace elements, with the concentration of majority of them below 30 ng/m3. These metals are released into air from both natural sources and the wear or/and corrosion of mining and tourists facilities in the underground functional space. No potentially toxic elements or constituents were detected. The presence of salt particles and salty spray in the atmosphere of salt mine, which may have anti-inflammatory and antiallergic properties, is beneficial to human health. This study will allow for a broader look at the potential of halotherapy in underground salt mines from a medical and regulatory point of view.
Representation of tree cover in global land cover products: Finland as a case study area
Authors: Majasalmi Titta , Rautiainen Miina
Published: February 2021

Forest extent mapping is required for climate modeling and monitoring changes in ecosystem state. Different global land cover (LC) products employ simple tree cover (referred also as “forest cover” or even “vegetation cover”) definitions to differentiate forests from non-forests. Since 1990, a large number of forest extent maps have become available. Although many studies have compared forest extent data, they often use old data (i.e., around the year 2000). In this study, we assessed tree cover representations of three different annual, global LC products (MODIS VCF (MOD44B, Collection 6 (C6)), MCD12Q1 (C6), and CCI LC (v.2.1.1)) using the Finnish Multi-Source National Forest Inventory (MS-NFI) data for the year 2017. In addition, we present an intercomparison approach for analyzing spatial representations of coniferous and deciduous species. Intercomparison of different LC products is often overlooked due to challenges involved in non-standard and overlapping LC class definitions. Global LC products are used for monitoring changes in land use and land cover and modeling of surface fluxes. Given that LC is a major driver of global change through modifiers such as land surface albedo, more attention should be paid to spatial mapping of coniferous and deciduous species. Our results show that tree cover was either overestimated or underestimated depending on the LC product, and classification accuracy varied between 42 and 75%. Intercomparison of the LC products showed large differences in conifer and deciduous species spatial distributions. Spatial mapping of coniferous and deciduous tree covers was the best represented by the CCI LC product as compared with the reference MS-NFI data.
Learning Automata-based Misinformation Mitigation via Hawkes Processes
Authors: Abouzeid Ahmed , Granmo Ole-Christoffer , Webersik Christian , Goodwin Morten
Published: February 2021

Mitigating misinformation on social media is an unresolved challenge, particularly because of the complexity of information dissemination. To this end, Multivariate Hawkes Processes (MHP) have become a fundamental tool because they model social network dynamics, which facilitates execution and evaluation of mitigation policies. In this paper, we propose a novel light-weight intervention-based misinformation mitigation framework using decentralized Learning Automata (LA) to control the MHP. Each automaton is associated with a single user and learns to what degree that user should be involved in the mitigation strategy by interacting with a corresponding MHP, and performing a joint random walk over the state space. We use three Twitter datasets to evaluate our approach, one of them being a new COVID-19 dataset provided in this paper. Our approach shows fast convergence and increased valid information exposure. These results persisted independently of network structure, including networks with central nodes, where the latter could be the root of misinformation. Further, the LA obtained these results in a decentralized manner, facilitating distributed deployment in real-life scenarios.
Testing Buddha: Is Acute Desire Associated with Lower Momentary Happiness?
Authors: Murphy Stephen L. , Ozaki Yuka , Friese Malte , Hofmann Wilhelm
Published: February 2021

A central Buddhist claim is that having desires causes suffering. While this tenet draws from the belief that an acute desire state is more momentarily aversive than a no-desire state, the efficacy of this belief has yet to be comprehensively examined. To empirically investigate this claim, we furnished data from two experience sampling studies across USA/Canadian (N = 101; 3224 observations) and Japanese cultures (N = 237; 8497 observations). We compared states of acute desire with states of no desire regarding momentary happiness. We then tested, in an additional step, whether acute desires at greater conflict with personal goals were associated with even lower levels of momentary happiness. Findings were consistent across studies, with participants experiencing greater momentary happiness when not experiencing a desire compared to experiencing acute desire. Also, the greater the desire conflicted with important goals the lower the momentary happiness. The present findings support a key basis of the Buddhist belief that having desires causes suffering, showing acute desire states on average to be more aversive than no desire states.
Autonomous long-range drone detection system for critical infrastructure safety
Authors: Zhang Xindi , Kusrini Kusrini
Published: February 2021

The development of unmanned aerial vehicles has been identified as a potential source of a weapon for causing operational disruptions against critical infrastructures. To mitigate and neutralise the threat posed by the misuse of drones against malicious and terrorist activity, this paper presents a holistic design of a long-range autonomous drone detection platform. The novelty of the proposed system lies in the confluence between the design of hardware and software components to effective and efficient localisation of the intruder objects. The research presented in the paper proposes the design and validation of a situation awareness component which is interfaced with the hardware component for controlling the focal length of the camera. The continuous stream of media data obtained from the region of vulnerability is processed using the object detection that is built on region based fully connected neural network. The novelty of the proposed system relies on the processing of multi-threaded dual-media input streams that are evaluated to mitigate the latency of the system. Upon the successful detection of malicious drones, the system logs the occurrence of intruders that consists of both event description and the associated media evidence for the deployment of the mitigation strategy. The analytics platform that controls the signalling of the low-cost sensing equipment contains the NVIDIA GeForce GTX 1080 for detecting drones. The experimental testbeds developed for the validation of the proposed system has been constructed to include environments and situations that are commonly faced by critical infrastructure operators such as the area of protection, drone flight path, tradeoff between the angle of coverage against the distance of coverage. The validation of the proposed system has resulted in yielding a range of intruder drone detection by 250m with an accuracy of 95.5%.
Client-driven animated GIF generation framework using an acoustic feature
Authors: Mujtaba Ghulam , Lee Sangsoon , Kim Jaehyoun , Ryu Eun-Seok
Published: February 2021

This paper proposes a novel, lightweight method to generate animated graphical interchange format images (GIFs) using the computational resources of a client device. The method analyzes an acoustic feature from the climax section of an audio file to estimate the timestamp corresponding to the maximum pitch. Further, it processes a small video segment to generate the GIF instead of processing the entire video. This makes the proposed method computationally efficient, unlike baseline approaches that use entire videos to create GIFs. The proposed method retrieves and uses the audio file and video segment so that communication and storage efficiencies are improved in the GIF generation process. Experiments on a set of 16 videos show that the proposed approach is 3.76 times more computationally efficient than a baseline method on an Nvidia Jetson TX2. Additionally, in a qualitative evaluation, the GIFs generated using the proposed method received higher overall ratings compared to those generated by the baseline method. To the best of our knowledge, this is the first technique that uses an acoustic feature in the GIF generation process.
Effect of Species Composition on Polycyclic Aromatic Hydrocarbon (PAH) Accumulation in Urban Forest Soils of Krakow
Authors: Lasota Jarosław , Łyszczarz Stanisław , Kempf Piotr , Kempf Marta , Błońska Ewa
Published: February 2021

Polycyclic aromatic hydrocarbons (PAHs) are among the most hazardous organic pollutants due to their toxic, carcinogenic, mutagenic properties, wide distribution, recalcitrance and stability in the environment. The study objective is to determine the impact of the species composition of tree stands on PAH accumulation in urban forest soils of Krakow. The study compared the impact of deciduous and coniferous species on similar soils on PAH biodegradation. Basic physicochemical properties, activity of enzymes involved in the nutrient cycle and PAH content were measured in soil samples. Our study shows lower accumulation of PAHs in soils with deciduous tree stands, which are characterized by higher pH and higher biochemical activity expressed by enzymatic activity. There is statistically significant difference in the enzymatic activity in the soils of deciduous tree stands, which results in differences in PAH accumulation. Among the studied deciduous species, soils with Norway maple and locust were characterized by highest enzymatic activity. At the same time, soils under these species were characterized by the lowest PAH accumulation. Among the coniferous species, highest PAH accumulation was observed under pine and spruce, where low enzymatic activity was observed at the same time.
An enhancement of the current design concepts for the improved consideration of residual stresses in fatigue-loaded welds
Authors: Nitschke-Pagel Th. , Hensel J.
Published: February 2021

The consideration of residual stresses in fatigue-loaded welds is currently done only qualitatively without reliable knowledge about their real distribution, amount and prefix. Therefore, the tools which enable a more or less unsafe consideration in design concepts are mainly based on unsafe experiences and doubtful assumptions. Since the use of explicitly determined residual stresses outside the welding community is state of the art, the target of the presented paper is to show a practicable way for an enhanced consideration of residual stresses in the current design tools. This is not only limited on residual stresses induced by welding, but also on post-weld treatment processes like HFMI or shot peening. Results of extended experiments with longitudinal fillet welds and butt welds of low and high strength steels evidently show that an improved use of residual stresses in fatigue strength approximation enables a better evaluation of peening processes as well as of material adjusted welding procedures or post-weld stress relief treatments. The concept shows that it is generally possible to overcome the existing extremely conservative but although unsafe rules and regulations and may also enable the improved use of high strength steels.
Correlation effect of transformed or corrected data inversion
Authors: Balázs László
Published: February 2021

Before performing the inversion process, the original measured data set is often transformed (corrected, smoothed, Fourier-transformed, interpolated etc.). These preliminary transformations may make the original (statistically independent) noisy measurement data correlated. The noise correlation on transformed data must be taken into account in the parameter fitting procedure (inversion) by proper derivation of likelihood function. The covariance matrix of transformed data system is no longer diagonal, so the likelihood based metrics, which determines the fitting process is also changed as well as the results of inversion. In the practice, these changes are often neglected using the “customary” estimation procedure (simple least square method) resulting wrong uncertainty estimation and sometimes biased results. In this article the consequence of neglected correlation is studied and discussed by decomposing the inversion functional to “customary” and additional part which represents the effect of correlation. The ratio of two components demonstrates the importance and justification of the inversion method modification.