bluuebunny/crossref_metadata_2025 huggingface dataset:
Root‐zone soil organic carbon enrichment is sensitive to land management across soil types and regions
Authors: Franzluebbers Alan J.
Published: October 2021

Measuring and monitoring changes in soil organic C (SOC) concentrations and stocks are important for understanding ecosystem functions. Sequestration of SOC has traditionally been measured from resource‐intensive studies over extended periods of time, but an alternative approach of calculating root‐zone SOC enrichment is described here as a proxy for estimating SOC sequestration using nonlinear distribution of SOC concentration in the surface 30 cm. From literature data across 52 studies, estimated SOC concentration at 30‐cm depth was not different between pairs of conservation management and conventional‐till cropland, suggesting support for the concept of using SOC concentration at 30‐cm depth as a baseline concentration from which enrichment can be calculated. Root‐zone SOC enrichment across this (n = 420) and an earlier study (n = 171) was 12.0 ± 0.6 Mg C ha–1 (mean ± SE) under conventional‐till cropland (n = 209), 16.1 ± 0.6 Mg C ha–1 under no‐till cropland (n = 269), 20.6 ± 1.0 Mg C ha–1 under grassland (n = 90), and 25.8 ± 3.8 Mg C ha–1 under woodland (n = 23). Regional climatic conditions and soil texture were important in influencing baseline SOC storage and total SOC stock but were minor factors in affecting root‐zone SOC enrichment with conservation management. Root‐zone SOC enrichment is a relatively simple and straightforward calculation method to indicate SOC sequestration, and if deployed across a diversity of management and farm locations, could lead to better SOC stock inventories and analyses of how contemporary management influences SOC stock change in different ecoregions.
Data‐drivensparse partial least squares
Authors: Lorenzo Hadrien , Cloarec Olivier , Thiébaut Rodolphe , Saracco Jérôme
Published: October 2021

In the supervised high dimensional settings with a large number of variables and a low number of individuals, variable selection allows a simpler interpretation and more reliable predictions. That subspace selection is often managed with supervised tools when the real question is motivated by variable prediction. We propose a partial least square (PLS) based method, called data‐driven sparse PLS (ddsPLS), allowing variable selection both in the covariate and the response parts using a single hyperparameter per component. The subspace estimation is also performed by tuning a number of underlying parameters. The ddsPLS method is compared with existing methods such as classical PLS and two well established sparse PLS methods through numerical simulations. The observed results are promising both in terms of variable selection and prediction performance. This methodology is based on new prediction quality descriptors associated with the classicaland, and uses bootstrap sampling to tune parameters and select an optimal regression model.
Evolution, trends and future research lines in corporate social responsibility and tourism: A bibliometric analysis and science mapping
Authors: Sánchez‐Camacho Carlos , Carranza Rocío , Martín‐Consuegra David , Díaz Estrella
Published: October 2021

Corporate social responsibility (CSR) has become a topic of growing interest in countless areas, and the number of studies focused on researching different CSR aspects is increasing. Nevertheless, this type of research within the tourism sector is less developed compared to other fields. Consequently, a significant research opportunity in the tourism industry has been detected. Therefore, this study uses the SciMAT software to analyze 1800 articles published on CSR within the tourism field through the co‐word analysis technique. Findings led to conclude that the entire scientific production within this field is composed of eight major thematic areas: (1) Business activity‐financial performance, (2) Attitude and behaviour, (3) Marketing perspective, (4) Sustainable tourism, (5) Sustainability, (6) Governmental action, (7) Environmental awareness and motivation and (8) Impact of major events. Additionally, interpretation of the main findings of the bibliometric analysis and implications for future trends of CSR in the tourism field has been discussed.
Bayesian consensus clustering for multivariate longitudinal data
Authors: Lu Zihang , Lou Wendy
Published: October 2021

In clinical and epidemiological studies, there is a growing interest in studying the heterogeneity among patients based on longitudinal characteristics to identify subtypes of the study population. Compared to clustering a single longitudinal marker, simultaneously clustering multiple longitudinal markers allow additional information to be incorporated into the clustering process, which reveals co‐existing longitudinal patterns and generates deeper biological insight. In the current study, we propose a Bayesian consensus clustering (BCC) model for multivariate longitudinal data. Instead of arriving at a single overall clustering, the proposed model allows each marker to follow marker‐specific local clustering and these local clusterings are aggregated to find a global (consensus) clustering. To estimate the posterior distribution of model parameters, a Gibbs sampling algorithm is proposed. We apply our proposed model to the primary biliary cirrhosis study to identify patient subtypes that may be associated with their prognosis. We also perform simulation studies to compare the clustering performance between the proposed model and existing models under several scenarios. The results demonstrate that the proposed BCC model serves as a useful tool for clustering multivariate longitudinal data.
Optimized Methodology for the Calculation of Electrostriction from First‐Principles
Authors: Tanner Daniel S. P. , Bousquet Eric , Janolin Pierre‐Eymeric
Published: October 2021

In this work a new method for the calculation of the electrostrictive properties of materials using density functional theory is presented. The method relies on the thermodynamical equivalence, in a dielectric, of the quadratic mechanical responses (stress or strain) to applied electric stimulus (electric or polarization fields) to the strain or stress dependence of its dielectric susceptibility or stiffness tensors. Comparing with current finite‐field methodologies for the calculation of electrostriction, it is demonstrated that this presented methodology offers significant advantages of efficiency, robustness, and ease of use. These advantages render tractable the high throughput theoretical investigation into the largely unknown electrostrictive properties of materials, and the microscopic origins of giant electrostriction.
2D Material‐Based Photodetectors for Infrared Imaging
Authors: Cheng Zhongzhou , Zhao Tong , Zeng Haibo
Published: October 2021

As a dynamic research field, infrared (IR) detection and imaging presents broad prospect in spectra‐chemistry, biomedicine, and artificial intelligence. Due to the excellent properties, 2D materials are expected to overcome the serious manufacturing cost and integration problems of Si‐based photodetectors, providing opportunities for the universal application of IR imaging. Up to now, dozens of 2D materials are used to manufacture IR photodetectors. The ultrathin and flexible 2D material‐based optoelectronic devices, which are easy to machine and integrate, will demonstrate the application beyond imagination. In this review, first, the principle of IR detection and imaging is introduced, in which the single pixel and array imaging are discussed. Then the promising materials, toward broadband detection and special detection, are introduced in brief and the devices for imaging are summarized, including the mode based on light intensity and the strategy originated from polarization. Finally, it is prospected that the 2D materials have the capability to show the integral IR world, which contains large amount of valuable information such as molecular vibration spectra and significant applications such as artificial retina.
Communication and culture: A multispecies endeavour within a shared habitat
Authors: McIntyre‐Mills Janet J.
Published: October 2021

COVID‐19 can be seen as feedback for anthropocentric social, economic and environmental decision‐making that disrespects other living systems. The paper makes a case that respects for multiple species, and the onus of beneficence should be applied to all living systems of which we are a strand. Human beings are not exceptional insofar as they are able to communicate, make decisions, demonstrate a sense of community and show empathy or to make political calculations. What does this mean for the way we live our lives? Respect for persons needs to include animals, plants and the earth. It is time to rethink rights and responsibilities to protect habitat. Goodall stresses that the loss of habitat leads to species that have never been in contact before (and thus without any resistance) causing cross species infections.
Engineering extracellular vesicles for Alzheimer's disease: An emerging cell‐free approach for earlier diagnosis and treatment
Authors: Lazar Sabrina Valentina , Mor Sirjan , Wang David , Goldbloom‐Helzner Leora , Clark Kaitlin , Hao Dake , Farmer Diana Lee , Wang Aijun
Published: October 2021

Alzheimer's disease (AD) is a debilitating neurodegenerative disorder affecting over five million people globally and has no established cure. Current AD‐related treatments only alleviate cognitive and behavioral symptoms and do not address disease onset or progression, underlining the unmet need to create an effective, innovative AD therapeutic. Extracellular vesicles (EVs) have emerged as a new class of nanotherapeutics. These secreted, lipid‐bound cellular signaling carriers show promise for potential clinical applications for neurodegenerative diseases like AD. Additionally, analyzing contents and characteristics of patient‐derived EVs may address the unmet need for earlier AD diagnostic techniques, informing physicians of altered genetic expression or cellular communications specific to healthy and diseased physiological states. There are numerous recent advances in regenerative medicine using EVs and include bioengineering perspectives to modify EVs, target glial cells in neurodegenerative diseases like AD, and potentially use EVs to diagnose and treat AD earlier.

This article is categorized under:

Neurological Diseases > Biomedical Engineering

Neurological Diseases > Molecular and Cellular Physiology

Neurological Diseases > Stem Cells and Development
The role of leadership education in Native nation building at tribal colleges and universities
Authors: Youngbull Natalie Rose
Published: October 2021

This article explores how leadership education and program development is centered on the needs of students, local tribal communities, and institutional charter within the Tribal College and University (TCU) context. Two leadership‐based academic programs at two respective TCUs are discussed through the lens of a culturally appropriate framework of Native‐nation building to illustrate how leadership development at TCUs is focused on developing student leaders within and for tribal communities.
Digital wormholes
Authors: O’Neill Elizabeth
Published: October 2021

Cameras, microphones, and other sensors continue to proliferate in the world around us. I offer a new metaphor for conceptualizing these technologies: they are digital wormholes, transmitting representations of human persons between disparate points in space–time. We frequently cannot tell when they are operational, what kinds of data they are collecting, where the data may reappear in the future, and how the data can be used against us. The wormhole metaphor makes the mysteriousness of digital sensors salient: digital sensors have brought us to a strange place. If humans are to be capable of making sensible decisions while under observation by digital sensors, we must improve the epistemic position of potential sensor subjects.
Soil salinity variations and cotton growth under long-term mulched drip irrigation in saline-alkali land of arid oasis
Authors: Li Wenhao , Wang Zhenhua , Zhang Jinzhu , Zong Rui
Published: October 2021

The sustainable development and utilization of saline-alkali land are closely related to holding fast the minimum cultivated land area of China. The change of soil salt in cotton field under long-term mulched drip irrigation (MDI) is connected with the development of the national cotton industry. From 2015 to 2019, five cotton fields with different applying years of MDI, which were reclaimed in 2004, 2008, 2010, 2012 and 2015 respectively and were saline-alkali wasteland before, were monitored continuously in the Manas River irrigation area of Xinjiang. By means of continuous location monitoring and spatial–temporal variability (For example, the monitoring data of cotton fields under MDI in 2004, 2008, 2010, 2012 and 2015, and in the year of 2015 were counted as 12, 8, 6, 4 and 1 years, respectively), the spatial–temporal variations of soil salt and ions in cotton field with 1-16a MDI technology were presented. The cotton growth characteristics and its main influencing factors were also analyzed in the study. The results showed that saline-alkali cotton field experienced changed from intensive saline soil to moderate saline soil and finally to non-saline soil under long-term MDI. The change of soil salt and the response of cotton growth to soil salt were divided into three typical stages. Firstly, soil desalinated rapidly in 1-4a MDI cotton field, which the annual average desalination rate was 24.93% in 0–100 cm soil layer (root zone). Additionally, the survival rate of cotton rocketed from 1.48% to 42.04%, and yield increased sharply from 72.43 kg ha−1 to 3075.90 kg ha−1. Soil desalination was lower in 5-11a MDI cotton field, which the annual average desalination rate was 10.92% at the root zone. The annual survival rate and yield of cotton increased by 6.26% and 5.18%, respectively. After 12a MDI, the soil salt in cotton field tended to be generally constant, which the average salt content in root zone was less than 2.49 g kg−1. The survival rate of cotton was stable above 90.39%, and the yield per unit area exceeded 5401.32 kg ha−1. Ions, sodium absorption ratio and Cl− and SO42− equivalent ratio (CSER) in cotton soil also decreased with the extension of MDI. Salt composition changed year by year, but the type of intensive saline soil had always been chloride-sulphate solonchak (0.2 < CSER < 1). In practice, with a higher irrigation quota and ideal irrigation water quality, the soil salt environment of saline-alkali soil MDI cotton field had developed in favor of cotton growth in an oasis irrigation area. However, this management practice caused between 124.21–143.61 mm of water resources waste. Therefore, we should further enhanced the consciousness of water-saving and implemented quota management in practice.
The development of a wax layer on the interior wall of a circular pipe transporting heated oil: the effects of temperature-dependent wax conductivity
Authors: Mason Sophie Lauren , Meyer John Christopher , Needham David John
Published: October 2021

In this paper, we develop and significantly extend the thermal phase change model, introduced in Needham et al. (QJMAM 67:93–125, 2014), describing the process of paraffinic wax layer formation on the interior wall of a circular pipe transporting heated oil, when subject to external cooling. In particular, we allow for the natural dependence of the solidifying paraffinic wax conductivity on local temperature. We are able to develop a complete theory, and provide efficient numerical computations, for this extended model. Comparison with recent experimental observations is made, and this, together with recent reviews of the physical mechanisms associated with wax layer formation provide significant support for the thermal model considered here.
Conjectures and Disconfirmations: Confirming the Standard Model Higgs
Authors: King Martin
Published: October 2021

One model in particular, the Standard Model Higgs, is taken to have been confirmed by the Higgs boson discovery at the LHC, even though many models are compatible with the data. Some models even provided riskier predictions and should perhaps be regarded as having been even more strongly confirmed. This paper sketches an argument demonstrating this by comparing the confirmation of the Standard Model Higgs with that of the Higgs in minimal supersymmetry. The paper then attempts to provide a way of understanding this result by modelling it as a case of eliminative induction.
Subsidizing unit donations: matches, rebates, and discounts compared
Authors: Diederich Johannes , Eckel Catherine C. , Epperson Raphael , Goeschl Timo , Grossman Philip J.
Published: October 2021

An influential result in the literature on charitable giving is that matching subsidies dominate rebate subsidies in raising funds. We investigate whether this result extends to “unit donation” schemes, a popular alternative form of soliciting donations. There, the donors’ choices are over the number of units of a charitable good to fund at a given unit price, rather than the amount of money to give. Comparing matches and rebates as well as simple discounts on the unit price, we find no evidence of dominance in our online experiment: the three subsidy types are equally effective overall. At a more disaggregated level, rebates lead to a higher likelihood of giving, while matching and discount subsidies lead to larger donations by donors. This suggests that charities using a unit donation scheme enjoy additional degrees of freedom in choosing a subsidy type. Rebates merit additional consideration if the primary goal is to attract donors.
Generating networks of genetic processors
Authors: Campos Marcelino , Sempere José M.
Published: October 2021

The Networks of Genetic Processors (NGPs) are non-conventional models of computation based on genetic operations over strings, namely mutation and crossover operations as it was established in genetic algorithms. Initially, they have been proposed as acceptor machines which are decision problem solvers. In that case, it has been shown that they are universal computing models equivalent to Turing machines. In this work, we propose NGPs as enumeration devices and we analyze their computational power. First, we define the model and we propose its definition as parallel genetic algorithms. Once the correspondence between the two formalisms has been established, we carry out a study of the generation capacity of the NGPs under the research framework of the theory of formal languages. We investigate the relationships between the number of processors of the model and its generative power. Our results show that the number of processors is important to increase the generative capability of the model up to an upper bound, and that NGPs are universal models of computation if they are formulated as generation devices. This allows us to affirm that parallel genetic algorithms working under certain restrictions can be considered equivalent to Turing machines and, therefore, they are universal models of computation.
Need-Based Transfers Enhance Resilience to Shocks: An Agent-Based Model of a Maasai Risk-Pooling System
Authors: Campennì Marco , Cronk Lee , Aktipis Athena
Published: October 2021

Maasai and other Maa-speaking pastoralists in Kenya and Tanzania have a risk-pooling system that they refer to by their word for the umbilical cord (osotua). Gifts from one osotua partner to another are contingent on the recipient’s need and do not create any debt. We refer to such gifts as need-based transfers. Maa-speakers also have a system of debt-based transfers (esile) in which gifts must be repaid. We designed an agent-based model to compare the impacts on herd survival of need-based and debt-based transfers on networks of varying topologies and sizes and with different degrees of temporal correlation of shocks felt by the agents. We found that the use of need-based rather than debt-based transfers, greater network modularity, greater network size, and decreased correlation among shocks were associated with increased rates of survival.
Crisis of Authority: The Truth of Post-Truth
Authors: Enroth Henrik
Published: October 2021

This article is a critique of the notion of post-truth. Drawing on the work of Hannah Arendt, I argue that the epistemological crisis suggested by the notion of post-truth is epiphenomenal to a more general crisis of authority, a crisis that is poorly understood in the literature. I also argue that revisiting Arendt’s account of authority can help us elucidate the vexed dynamics of authority in modern society, as well as the dynamics behind its current crisis. The post-truth situation is a loss of authority that is political before it presents as epistemological. Effectively addressing this situation, I conclude, is a much more challenging and complex proposition than what is suggested in the literature on post-truth.
Collaborating with Virtual Assistants in Organizations: Analyzing Social Loafing Tendencies and Responsibility Attribution
Authors: Stieglitz Stefan , Mirbabaie Milad , Möllmann Nicholas R. J. , Rzyski Jannik
Published: October 2021

Organizations increasingly introduce collaborative technologies in form of virtual assistants (VAs) to save valuable resources, especially when employees are assisted with work-related tasks. However, the effect of VAs on virtual teams and collaboration remains uncertain, particularly whether employees show social loafing (SL) tendencies, i.e., applying less effort for collective tasks compared to working alone. While extant research indicates that VAs collaboratively working in teams exert greater results, less is known about SL in virtual collaboration and how responsibility attribution alters. An online experiment with N = 102 was conducted in which participants were assisted by a VA in solving a task. The results indicate SL tendencies in virtual collaboration with VAs and that participants tend to cede responsibility to the VA. This study makes a first foray and extends the information systems (IS) literature by analyzing SL and responsibility attribution thus updates our knowledge on virtual collaboration with VAs.
Review of Manufacturing Process Defects and Their Effects on Memristive Devices
Authors: Poehls L. M. Bolzani , Fieback M. C. R. , Hoffmann-Eifert S. , Copetti T. , Brum E. , Menzel S. , Hamdioui S. , Gemmeke T.
Published: October 2021

Complementary Metal Oxide Semiconductor (CMOS) technology has been scaled down over the last forty years making possible the design of high-performance applications, following the predictions made by Gordon Moore and Robert H. Dennard in the 1970s. However, there is a growing concern that device scaling, while maintaining cost-effective production, will become infeasible below a certain feature size. In parallel, emerging applications including Internet-of-Things (IoT) and big data applications present high demands in terms of storage and computing capability, combined with challenging constraints in terms of size, power consumption and response latency. In this scenario, memristive devices have become promising candidates to complement the CMOS technology due to their CMOS manufacturing process compatibility, great scalability and high density, zero standby power consumption and their capacity to implement high density memories as well as new computing paradigms. Despite these advantages, memristive devices are also susceptible to manufacturing defects that may cause unique faulty behaviors that are not seen in CMOS, increasing significantly the complexity of test procedures. This paper provides a review about the manufacturing process of memristives devices, focusing on Valence Change Mechanism (VCM)-based memristive devices, and a comparative analysis of the CMOS and memristive device manufacturing processes. Moreover, this paper identifies possible manufacturing failure mechanisms that may affect these novel devices, completing the list of the already known mechanisms, and provides a discussion about possible faulty behaviors. Note that the identification of these mechanisms provides insights regarding the possible memristive devices’ defective behaviors, enabling to derive more accurate fault models and consequently, more suitable test procedures.
MSN: A Playground Framework for Design and Evaluation of MicroServices-Based sdN Controller
Authors: Arzo Sisay Tadesse , Scotece Domenico , Bassoli Riccardo , Barattini Daniel , Granelli Fabrizio , Foschini Luca , Fitzek Frank H. P.
Published: October 2021

Software-defined networking decouples control and data plane in softwarized networks. This allows for centralized management of the network, but complete centralization of the controller functions raises potential issues related to failure, latency, and scalability. Distributed controller deployment is adopted to optimize scalability and latency problems. However, existing controllers are monolithic, resulting in code inefficiency for distributed deployment. Some seminal ongoing efforts have been proposed with the idea of disaggregating the SDN controller architecture into an assembly of various subsystems, each of which can be responsible for a certain controller task. These subsystems are typically implemented as microservices and deployed as virtual network functions, in particular as Docker Containers. This enables flexible deployment of controller functions. However, these proposals (e.g., $$\mu$$
μ
ONOS) are still in their early stage of design and development, so that a full decomposition of the SDN controller is not been available yet. To fill that gap, this article derives some important design guidelines to decompose an SDN controller into a set of microservices. Next, it also proposes a microservices-based decomposed controller architecture, foreseeing communications issues between the controller sub-functions. These design and performance considerations are also proven via the implementation of the proposed architecture as a solution, called Micro-Services based SDN controller (MSN), based on the Ryu SDN controller. Moreover, MSN includes different network communication protocols, such as gRPC, WebSocket, and REST-API. Finally, we show experimental results that highlight the robustness and latency of the system on a networking testbed. Collected results prove the main pros and cons of each network communication protocol and an evaluation of our proposal in terms of system resilience, scalability and latency.
Heterogeneity and state dependence in firms’ access to bank credit
Authors: Aristei David , Angori Gabriele
Published: October 2021

This paper investigates firms’ access to bank credit in eleven euro area countries over the periods 2014–2019. Exploiting firm-level longitudinal data, we analyse loan demand and credit rationing probabilities, accounting for sample selection, unobserved heterogeneity and state dependence. Empirical results show that small and informationally opaque businesses, with deteriorated public support and credit history, face greater difficulties in obtaining bank loans. Furthermore, we provide evidence of a significant degree of state dependence in access to credit. In particular, firms that have already experienced credit restrictions are more likely to face further constraints, while enterprises that applied for bank financing in the past seem to have easier access to credit. Focusing on the subset of firms actually needing additional bank financing, we also find that past credit restrictions significantly reduce their current demand, providing evidence of a significant discouragement effect.
Likelihood theory for the graph Ornstein-Uhlenbeck process
Authors: Courgeau Valentin , Veraart Almut E. D.
Published: October 2021

We consider the problem of modelling restricted interactions between continuously-observed time series as given by a known static graph (or network) structure. For this purpose, we define a parametric multivariate Graph Ornstein-Uhlenbeck (GrOU) process driven by a general Lévy process to study the momentum and network effects amongst nodes, effects that quantify the impact of a node on itself and that of its neighbours, respectively. We derive the maximum likelihood estimators (MLEs) and their usual properties (existence, uniqueness and efficiency) along with their asymptotic normality and consistency. Additionally, an Adaptive Lasso approach, or a penalised likelihood scheme, infers both the graph structure along with the GrOU parameters concurrently and is shown to satisfy similar properties. Finally, we show that the asymptotic theory extends to the case when stochastic volatility modulation of the driving Lévy process is considered.
Power Control for Cognitive Radio Networks: A Game Theoretic Approach
Authors: Gulzar Waqas , Waqas Abdullah , Dilpazir Hammad , Khan Anwar , Alam Ashfaq , Mahmood Hasan
Published: October 2021

In communication industry one of the most rapidly growing area is wireless technology and its applications. The efficient access to radio spectrum is a requirement to make this communication feasible for the users that are running multimedia applications and establishing real-time connections on an already overcrowded spectrum. In recent times cognitive radios (CR) are becoming the prime candidates for improved utilization of available spectrum. The unlicensed secondary users share the spectrum with primary licensed user in such manners that the interference at the primary user does not increase from a predefined threshold. In this paper, we propose an algorithm to address the power control problem for CR networks. The proposed solution models the wireless system with a non-cooperative game, in which each player maximize its utility in a competitive environment. The simulation results shows that the proposed algorithm improves the performance of the network in terms of high SINR and low power consumption.
Compact Probe for Non-Contact Ultrasonic Inspection with the Gas-Coupled Laser Acoustic Detection (GCLAD) Technique
Authors: Vangi D. , Bruzzi M. , Caron J. N. , Gulino M. S.
Published: October 2021

Background

Gas-Coupled Laser Acoustic Detection (GCLAD) is a non-contact ultrasonic detection technique whose functioning relies on the deviation that a probe laser beam sustains when intersected by an acoustic wavefront propagating in a fluid. The maximum sensitivity of the technique is typically obtained when the ultrasound insists on an ample portion of the probe laser beam extension, but such a condition can be unfeasible in several non-destructive testing applications (as in case of limited accessibility to the component).

Objective

In the present work, a solution is provided enabling transformation of the GCLAD device in a point detector. This is based on the use of two mirrors for confining the laser beam in an area with limited width and depth, where reflections however maximize the portion of the probe laser beam subjected to ultrasonic oscillation.

Methods

The characteristics of the obtained GCLAD probe are thoroughly analysed by applying the device to the detection of surface acoustic waves, propagating on a metal bar and refracting into the air. Two different inspection configurations are considered, whose difference lies in the mutual orientation between laser beam and solid surface. The effect on the received signal amplitude of the number of beam reflections, the dimensions of the resulting device, and the bar axisimmetry is investigated in both configurations.

Results

The optimization of all the analysed standpoints enables obtaining a compact GCLAD probe that features the same signal amplitude of the non-compact alternative. To obtain maximum responsivity of the system, the number of reflections must be maximized, while the distance between the mirrors must be carefully set based on the employed inspection configuration and the eventual axisimmetry of the specimen. The devised GCLAD compact probe is capable of expanding the application range of the technique also to those cases in which the use of point detectors is desirable, without compromising the signal-to-noise ratio of the resulting acquisitions compared to the non-compact alternative.
The forest environmental frontier in Russia: Between sustainable forest management discourses and ‘wood mining’ practice
Authors: Dobrynin Denis , Jarlebring Natalya Yakusheva , Mustalahti Irmeli , Sotirov Metodi , Kulikova Elena , Lopatin Eugene
Published: October 2021

With 20% of the world’s forests, Russia has global potential in bioeconomy development, biodiversity conservation and climate change mitigation. However, unsustainable forest management based on ‘wood mining’ reduces this potential. Based on document analysis, participant observations and interviews, this article shows how non-state actors—environmental NGOs and forest companies—address forest resource depletion and primary forest loss in Russia. We analyse two key interrelated forest discourses driven by non-state actors in Russia: (1) intensive forest management in secondary forests as a pathway towards sustained yield and primary forest conservation; (2) intact forest landscapes as a priority in primary forest conservation. We illustrate how these discourses have been integrated into policy debates, institutions and practices and discuss their relation to relevant global discourses. The article concludes that despite successful cases in conserving intact forest landscapes, there is still a frontier between sustainable forest management discourses and forestry practice in Russia.
Lunar Crater Identification in Digital Images
Authors: Christian John A. , Derksen Harm , Watkins Ryan
Published: October 2021

It is often necessary to identify a pattern of observed craters in a single image of the lunar surface and without any prior knowledge of the camera’s location. This so-called “lost-in-space” crater identification problem is common in both crater-based terrain relative navigation (TRN) and in automatic registration of scientific imagery. Past work on crater identification has largely been based on heuristic schemes, with poor performance outside of a narrowly defined operating regime (e.g., nadir pointing images, small search areas). This work provides the first mathematically rigorous treatment of the general crater identification problem. It is shown when it is (and when it is not) possible to recognize a pattern of elliptical crater rims in an image formed by perspective projection. For the cases when it is possible to recognize a pattern, descriptors are developed using invariant theory that provably capture all of the viewpoint invariant information. These descriptors may be pre-computed for known crater patterns and placed in a searchable index for fast recognition. New techniques are also developed for computing pose from crater rim observations and for evaluating crater rim correspondences. These techniques are demonstrated on both synthetic and real images.
GUV-Net for high fidelity shoeprint generation
Authors: Hassan Muhammad , Wang Yan , Pang Wei , Wang Di , Li Daixi , Zhou You , Xu Dong
Published: October 2021

Shoeprints contain valuable information for tracing evidence in forensic scenes, and they need to be generated into cleaned, sharp, and high-fidelity images. Most of the acquired shoeprints are found with low quality and/or in distorted forms. The high-fidelity shoeprint generation is of great significance in forensic science. A wide range of deep learning models has been suggested for super-resolution, being either generalized approaches or application specific. Considering the crucial challenges in shoeprint based processing and lacking specific algorithms, we proposed a deep learning based GUV-Net model for high-fidelity shoeprint generation. GUV-Net imitates learning features from VAE, U-Net, and GAN network models with special treatment of absent ground truth shoeprints. GUV-Net encodes efficient probabilistic distributions in the latent space and decodes variants of samples together with passed key features. GUV-Net forwards the learned samples to a refinement-unit proceeded to the generation of high-fidelity output. The refinement-unit receives low-level features from the decoding module at distinct levels. Furthermore, the refinement process is made more efficient by inverse-encoded in high dimensional space through a parallel inverse encoding network. The objective functions at different levels enable the model to efficiently optimize the parameters by mapping a low quality image to a high-fidelity one by maintaining salient features which are important to forensics. Finally, the performance of the proposed model is evaluated against state-of-the-art super-resolution network models.
Comparative Study of SO2 and SO2/SO3 Poisoning and Regeneration of Cu/BEA and Cu/SSZ-13 for NH3 SCR
Authors: Auvray Xavier , Arvanitidou Maria , Högström Åsa , Jansson Jonas , Fouladvand Sheedeh , Olsson Louise
Published: October 2021

Two copper-exchanged zeolites, Cu/SSZ-13 and Cu/BEA, were studied as catalysts for the selective reduction of NOx by NH3 (NH3-SCR). Their activities for standard SCR (NOx = NO) and fast SCR (NOx = 50% NO + 50% NO2) were measured before and after sulfur poisoning at 250 °C. The effect of 30 ppm SO2 and a mixture of 24 ppm SO3 + 6 ppm SO2 was evaluated. The repetition of subsequent activity measurements served as regeneration method in SCR conditions. SO2 deactivated Cu/SSZ-13 whereas Cu/BEA was only moderately affected. SO3 led to stronger deactivation of both catalysts than SO2. However, also for this case, the Cu/BEA was significantly less affected than Cu/SSZ-13, even though Cu/BEA contained larger amount of stored sulfur. One possible reason for this could be the large pores of Cu/BEA, where the sulfur species possibly resulted in less sterical hindrance than in the small pore SSZ-13 structure. NH3 temperature-programmed desorption (NH3-TPD) showed no loss of storage sites upon sulfur treatment and subsequent regeneration. Partial activity recovery was observed after a period in SCR conditions at 400 °C and 500 °C. Temperature at 300 °C was insufficient to regenerate the catalysts. Diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) of NO adsorption suggested that SO2 interacts with the ZCuOH sites on Cu/SSZ-13, causing the strong poisoning.
Equal values of certain partition functions via Diophantine equations
Authors: Tengely Szabolcs , Ulas Maciej
Published: October 2021

Let $$A\subset \mathbb {N}_{+}$$

A
⊂

N
+

and by $$P_{A}(n)$$

P
A

(
n
)

denotes the number of partitions of an integer n into parts from the set A. The aim of this paper is to prove several result concerning the existence of integer solutions of Diophantine equations of the form $$P_{A}(x)=P_{B}(y)$$

P
A

(
x
)

=

P
B

(
y
)

, where A, B are certain finite sets.
Medication-related quality of life (MRQoL) in ambulatory older adults with multi-morbidity and polypharmacy
Authors: Jennings Emma L. M. , O’Mahony Denis , Gallagher Paul F.
Published: October 2021

Purpose

To assess medication-related quality-of-life (MRQoL) in multi-morbid older adults with polypharmacy and correlations with medications, frailty and health-related QoL.

Methods

With a cross sectional study of multi-morbid geriatric medicine outpatients, we assessed MRQoL (MRQol-LSv1), frailty status, potentially inappropriate medications, Medication Adherence Rating Scale (MARS), health-related-QoL (Short-Form 12, SF12) and medication burden (Living with Medicines Questionnaire, LMQv2).

Results

One-in-four (n = 59) of 234 outpatient attendees met inclusion criteria. Almost half (n = 106, 45%) were excluded due to cognition (MMSE < 26). Included participants (n = 27, mean age 80.2 years) experienced a median of 11 (IQR 9–13.5) co-morbidities and were prescribed a median of 10 (IQR 8–12.25) medications. Overall, MRQoL-LS.v.1 scores were low, suggesting good medication-related quality of life (median MRQoL-LS.v.1 score of 14, IQR 14–22). Correlations between MRQoL, number of daily medications, co-morbidity burden, LMQv2 score, SF12 scores and number of PIMs were non-significant.

Conclusion

MRQoL-LSv.1 is unsuitable for most patients attending geriatric ambulatory services.
Darwin's Argument by Analogy
Authors: White Roger M. , Hodge M.J.S. , Radick Gregory
Published: October 2021

In On the Origin of Species (1859), Charles Darwin put forward his theory of natural selection. Conventionally, Darwin's argument for this theory has been understood as based on an analogy with artificial selection. But there has been no consensus on how, exactly, this analogical argument is supposed to work – and some suspicion too that analogical arguments on the whole are embarrassingly weak. Drawing on new insights into the history of analogical argumentation from the ancient Greeks onward, as well as on in-depth studies of Darwin's public and private writings, this book offers an original perspective on Darwin's argument, restoring to view the intellectual traditions which Darwin took for granted in arguing as he did. From this perspective come new appreciations not only of Darwin's argument but of the metaphors based on it, the range of wider traditions the argument touched upon, and its legacies for science after the Origin.
Emotional cognition subgroups in unaffected first-degree relatives of patients with mood disorders
Authors: Kjærstad Hanne Lie , Varo Cristina , Meluken Iselin , Vieta Eduard , Vinberg Maj , Kessing Lars Vedel , Miskowiak Kamilla Woznica
Published: October 2021

Background

Patients with major depressive disorder (MDD) or bipolar disorder (BD) exhibit difficulties with emotional cognition even during remission. There is evidence for aberrant emotional cognition in unaffected relatives of patients with these mood disorders, but studies are conflicting. We aimed to investigate whether emotional cognition in unaffected first-degree relatives of patients with mood disorders is characterised by heterogeneity using a data-driven approach.

Methods

Data from 94 unaffected relatives (33 of MDD patients; 61 of BD patients) and 203 healthy controls were pooled from two cohort studies. Emotional cognition was assessed with the Social Scenarios Test, Facial Expression Recognition Test and Faces Dot-Probe Test. Hierarchical cluster analysis was conducted using emotional cognition data from the 94 unaffected relatives. The resulting emotional cognition clusters and controls were compared for emotional and non-emotional cognition, demographic characteristics and functioning.

Results

Two distinct clusters of unaffected relatives were identified: a relatively ‘emotionally preserved’ cluster (55%; 40% relatives of MDD probands) and an ‘emotionally blunted’ cluster (45%; 29% relatives of MDD probands). ‘Emotionally blunted’ relatives presented with poorer neurocognitive performance (global cognition p = 0.010), heightened subsyndromal mania symptoms (p = 0.004), lower years of education (p = 0.004) and difficulties with interpersonal functioning (p = 0.005) than controls, whereas ‘emotionally preserved’ relatives were comparable to controls on these measures.

Conclusions

Our findings show discrete emotional cognition profiles that occur across healthy first-degree relatives of patients with MDD and BD. These emotional cognition clusters may provide insight into emotional cognitive markers of genetically distinct subgroups of individuals at familial risk of mood disorders.
INVOLVEMENT LOAD HYPOTHESIS PLUS
Authors: Yanagisawa Akifumi , Webb Stuart
Published: October 2021

The present meta-analysis aimed to improve on Involvement Load Hypothesis (ILH) by incorporating it into a broader framework that predicts incidental vocabulary learning. Studies testing the ILH were systematically collected and 42 studies meeting our inclusion criteria were analyzed. The model-selection approach was used to determine the optimal statistical model (i.e., a set of predictor variables) that best predicts learning gains. Following previous findings, we investigated whether the prediction of the ILH improved by (a) examining the influence of each level of individual ILH components (need, search, and evaluation), (b) adopting optimal operationalization of the ILH components and test format grouping, and (c) including other empirically motivated variables. Results showed that the resulting models explained a greater variance in learning gains. Based on the models, we created incidental vocabulary learning formulas. Using these formulas, one can calculate the effectiveness index of activities to predict their relative effectiveness more accurately on incidental vocabulary learning.
Nutrition knowledge assessment tools for older adults and their carers: a scoping review
Authors: Chin Shuyan , Wong Raymond , Hirani Vasant , O’Leary Fiona
Published: October 2021

Poor nutritional intake is common among older adults. Given that nutrition knowledge is an important determinant of eating behaviour and nutritional status, understanding areas of inadequate knowledge can guide educational interventions to reduce risk of nutritional deficiencies and promote healthy ageing. This review investigated tools assessing general nutritional knowledge of older adults and their carers. Following the Joanna Briggs for Scoping Reviews guidelines, 4 databases (MEDLINE, CINAHL, Global Health and Embase) and grey literature were searched. Studies of any type containing general nutrition knowledge assessment tools for older adults or their carers were included. In total, 6934 articles were identified, of which 24 met the eligibility criteria, and 23 unique nutrition knowledge assessment tools were included. Of these tools, 14 were original, 6 were modified from other tools and 3 used dietary-related responses from national dietary survey questions. 6 tools were developed for carers (mostly nurses) and 17 tools for older adults. Tools had between 4 and 110 items. The most common topics for general nutrition knowledge questions were related to nutrients and roles, food sources of nutrients, and diet–disease relationships. 8 tools were developed prior to 2000. Most studies did not specify or assess psychometric properties of the tool, with only 9 (38 %) and 6 (26 %) studies testing for reliability and validity, respectively, and only 1 tool was considered reliable. Additional research for the development of reliable and validated tools or the validation of existing tools to assess nutrition knowledge of older adults and their carers is needed across different healthcare settings.
Monitoring Tree Sway as an Indicator of Interception Dynamics Before, During, and Following a Storm
Authors: Ciruzzi Dominick M. , Loheide Steven P.
Published: October 2021

Understanding the role of trees in attenuating the timing and magnitude of effective precipitation reaching the land surface requires improved monitoring of interception dynamics. We developed a new field monitoring approach to leverage continuous monitoring of tree sway motion in quantifying continuous, dynamic time series of canopy water storage during storms. Using this approach, we additionally observed a hysteretic interception response in tree canopies, which indicates that interpreting interception processes through tree sway signals requires the consideration of changing water (i.e., mass) distribution during and following storms. These findings suggest that continuously monitoring tree sway motions offers a new technique to quantify interception processes. This advancement in whole tree interception may help improve our understanding of how interception affects ecosystem water availability/productivity and runoff dynamics that are important for both natural ecosystems and stormwater management in cities.