bluuebunny/crossref_metadata_2025 huggingface dataset:
Dynamic Refractive Index‐Matching for Adaptive Thermoresponsive Smart Windows
Authors: Li Jianing , Lu Xuegang , Zhang Yin , Wen Xiaoxiang , Yao Kangkang , Cheng Fei , Wang Dingchen , Ke Xiaoqin , Zeng Hao , Yang Sen
Published: June 2022

Thermoresponsive smart windows (TRSWs) take great advantages in energy‐efficient buildings and on‐demand devices owing to their self‐adaptiveness and external energy consumption‐free nature. Currently used TRSWs largely rely on thermal‐induced phase transitions in single‐material systems, however, the intrinsic characteristics of which may not be suited for practical window utilization, such as poor luminous transparency and fixed critical temperature (Tc). Herein, an adaptive TRSW based on dynamic refractive index (RI) matching between two phases is demonstrated, which is facilely fabricated by embedding ethylene glycol solution microdroplets into polydimethylsiloxane (PDMS) via a one‐step emulsification approach, realizing a smart temperature response in PDMS. The TRSW presents high transparency (≈92%) and bidirectional transparency‐temperature response (≈20% at 73 °C, ≈40% at 8 °C). Moreover, the RI dispersion generates a unique effect of wavelength selectivity with temperature. Notably, the effective optical‐temperature response with variable Tc could be tuned over a wide range of 13–68 °C by adjusting the EGS concentration. The proposed strategy with dynamic RI matching allows TRSW construction to extend beyond phase transitional materials and greatly broadens the applicable scope of TRSWs, which is promising in the fields of smart optical devices such as smart windows, anti‐counterfeiting, optical switches, and optical selection.
Radicals Scavenging MOFs Enabling Targeting Delivery of siRNA for Rheumatoid Arthritis Therapy
Authors: Guo Lina , Zhong Shenghui , Liu Peng , Guo Man , Ding Jinsong , Zhou Wenhu
Published: June 2022

Macrophages play essential roles in the progression of rheumatoid arthritis (RA), which are polarized into the pro‐inflammatory M1 phenotype with significant oxidative stress and cytokines excretion. Herein, an active targeting nanomedicine based on metal‐organic frameworks (MOFs) to re‐educate the diseased macrophages for RA therapy is reported. The MOFs are prepared via coordination between tannic acid (TA) and Fe3+, and anti‐TNF‐α siRNA is loaded via a simple sonication process, achieving high loading capacity comparable to cationic vectors. The MOFs show excellent biocompatibility, and enable rapid endo/lysosome escape of siRNA via the proton‐sponge effect for effective cytokines down‐regulation. Importantly, such nanomedicine displays intrinsic radicals scavenging capability to eliminate a broad spectrum of reactive oxygen and nitrogen species (RONS), which in turn repolarizes the M1 macrophages into anti‐inflammatory M2 phenotypes for enhanced RA therapy in combination with siRNA. The MOFs are further modified with bovine serum albumin (BSA) to allow cascade RA joint and diseased macrophages targeted delivery. As a result, an excellent anti‐RA efficacy is achieved in a collagen‐induced arthritis mice model. This work provides a robust gene vector with great translational potential, and offers a vivid example of rationally designing MOF structure with multifunctionalities to synergize with its payload for enhanced disease treatment.
A new gecko (Squamata, Gekkota) from the Eocene of Geiseltal (Germany) implies long‐term persistence of European Sphaerodactylidae
Authors: Villa Andrea , Wings Oliver , Rabi Márton
Published: June 2022

Gekkota (geckos and pygopods) constitute a diverse and early diverging clade of squamates, but their highly fragmentary fossil record allows only limited insights into their evolutionary history. Even long‐known classic Palaeogene Lagerstätten, such as the Eocene Messel and Geiseltal, remained uninformative for gecko evolution. Here we describe an articulated near‐complete crown‐gekkotan skull from the Eocene of Geiseltal. The skull represents one of the most complete and oldest fossil geckos from the Cenozoic and warrants the naming of a new taxon, Geiseleptes delfinoi gen. et sp. nov. Parsimony analysis of an expanded morphological dataset that comprehensively samples fossil geckos recovers at least two lineages in the Palaeogene of Europe: Gekkonidae and Sphaerodactylidae. Further clades may have been present but require further support. The new species, together with several other European extinct taxa, belongs to the extant clade Sphaerodactylidae. Published molecular phylogenies imply a European dispersal from Africa for the clade, and G. delfinoi constrains the timing of this event to no later than the middle Eocene. Within Sphaerodactylidae, several Eocene, Oligocene and Miocene species form the stem‐lineage of the extant Mediterranean‐endemic Euleptes europaea of which G. delfinoi is the oldest representative. We here define the new clade Euleptinae for this group. Euleptine geckos had an unusually long evolutionary history in Cenozoic Europe and may represent one of the very few vertebrate clades with a persistent presence since the early Palaeogene, indicating extreme adaptability. As the oldest known crown‐sphaerodactylid, G. delfinoi represents an important fossil calibration for divergence dating analyses of geckos.
Key Question for Literacy Co‐Teachers: What Possibilities Do We Have Together?
Authors: McTigue Erin M. , Gourvennec Aslaug Fodstad , Solheim Oddny Judith
Published: June 2022

Co‐teaching offers a unique opportunity space for literacy instruction; however, this opportunity is rarely optimized and the result on students' literacy growth is often unimpressive. We propose that co‐teaching is only a structural intervention, but it can become a powerful pedagogical intervention if teachers approach co‐teaching as an opportunity space to try out effective pedagogical practices that lead to student literacy growth. Studying, through mixed methods, the practices of literacy co‐teachers in early elementary, we identified important trends connected to student growth. We concluded that shared responsibility was a feature of highly effective pairs. Next, through interviews, we captured nuances of how effective dyads formed working relationships, planned together, communicated, reflected on instruction together, and organized resources. From such findings, we propose a model of change for how co‐teaching may lead to student growth—via positive co‐teaching relationships and continual shared reflection of instructional practice. Mirroring highly effective co‐teachers' approach, we provide a series of reflective co‐teaching guides to support other pairs of co‐teachers. These guides lead reading teachers throughout a school year and continually return to the essential question of: What can we do together that I cannot do alone?
UK veterinary professionals’ perceptions and experiences of adverse drug reaction reporting
Authors: Davies Heather , Pinchbeck Gina , Noble Peter‐John M. , Diesel Gillian , Pirmohamed Munir , Anderson Nadine , Killick David R.
Published: June 2022

Background

Spontaneous reporting of suspected adverse drug reactions (ADRs) is the cornerstone of pharmacovigilance. Despite this, it is believed that there is significant under‐reporting in the veterinary setting. Low reporting rates delay marketing authorisation holders (MAHs) and regulators taking mitigating action in the case of safety concerns.

Method

We designed a survey to explore the perceptions, attitudes and experiences of UK veterinary professionals towards ADR reporting. The survey was advertised widely through conventional and social media and at several conferences.

Results

In total, 260 respondents completed the survey, including 210 veterinary surgeons, 49 veterinary nurses and one suitably qualified person. Respondents generally understood the need to report ADRs. The main barrier to reporting was the suspected ADR being well known, and the most popular potential facilitator identified was the ability to report via the practice management system. Facilitation via education in the form of a pharmacovigilance themed continuing professional development event was particularly popular among veterinary nurses, who reported time as being less of a barrier to reporting than their veterinary surgeon counterparts.

Conclusions

Our findings suggest that technological interventions to facilitate reporting and empowerment of veterinary nurses to report through a tailored training event should be explored further.
Good Workplaces at Vets Cymru
Authors: Knowles‐Bacon Megan
Published: June 2022

BVA Welsh Branch is delighted to be returning to Vets Cymru this year and catching up with members in Wales. Megan Knowles‐Bacon, BVA policy officer, shares more on the event.
Abusive clients: a young vet's perspective
Authors: Moore Alice
Published: June 2022

As BVA launches its #RespectYourVetTeam campaign to tackle client abuse towards the profession, early‐career vet Alice Moore offers an insight into the experience of newly qualified members of the profession.
Robust feasibility verification and region inner-point detection algorithms for geometric shape objects applied to electric machine optimization workflow
Authors: Ban Branko , Stipetic Stjepan
Published: June 2022

In most cases, the search for the optimal design of an electrical machine is closely related to its 2D radial cross section. When optimizing a 2D cross section, special attention must be paid to the geometry and to the definition of the parameters along with their boundaries. Even if properly bounded, complex geometries generated by optimization algorithms can lead to geometrically infeasible candidates. These cannot be manufactured because they contain generally undesirable geometric relationships between air, magnets, and steel. Different commercial and open-source finite element analysis (FEA) design tools treat the infeasible designs differently. The results vary from simulation stop to successful FEA calculation of the infeasible candidate, which wastes time by producing useless data. To prevent the infeasible designs from entering the optimization competition and possibly appearing incorrectly as optimal solutions, and to reduce optimization time, it is important to capture the infeasible designs during optimization. Moreover, the FEA tool requires a precisely determined interior point to assign the material to each closed region (air, steel, epoxy, magnet...). This can be very challenging for complex geometries. To avoid creating geometry or material regions that are not valid, this paper proposes a novel robust methods for checking feasibility and determining interior points on geometric shape objects. In this paper, the proposed method is applied to the optimization of electrical machines.
Completeness of certain metric spaces of measures
Authors: Dorsch Florian
Published: June 2022

We prove that the set of finite Borel measures on a separable and directionally limited metric space $$(X,\mathtt {d})$$

(
X
,
d
)

is complete with respect to the metric $${\mathbf {d}}_{{\mathcal {A}}}(\mu ,\nu )=\sup _{A\in {\mathcal {A}}}\left| \mu (A)-\nu (A)\right| $$

d
A

(
μ
,
ν
)

=

sup

A
∈
A

μ
(
A
)
-
ν
(
A
)

for all families of Borel sets $${\mathcal {A}}$$
A
that contain every closed ball of X. This allows to prove the existence and uniqueness of the invariant Borel probability measure of certain Markov processes on X. A natural application is a Markov process induced by a random similitude.
Application of 3D printing in assessment and demonstration of stab injuries
Authors: Simon Gábor , Tóth Dénes , Heckmann Veronika , Poór Viktor Soma
Published: June 2022

In stabbing related fatalities, the forensic pathologist has to assess the direction of wound track (thus, the direction of the stabbing) and the weapon’s possible characteristics by examining the stab wound. The determination of these characteristics can be made only with a high level of uncertainty, and the precise direction of the stabbing is often difficult to assess if only soft tissues are injured. Previously reported techniques used for the assessment of these wound characteristics have substantial limitations. This manuscript presents a method using today’s easily accessible three-dimensional (3D) printing technology for blade-wound comparison and wound track determination. Scanning and 3D printing of knives is a useful method to identify weapons and determine the precise stabbing direction in a stabbing incident without compromising the trace evidence or the autopsy results. Ballistic gel experiment, and dynamic stabbing test experiments prove the method can be applied in safety, without compromising the autopsy results. Identification of the exact knife is not possible with complete certainty but excluding certain knives will decrease the number of necessary DNA examinations, hence it can lower the burden on forensic genetic laboratories. The method addresses many of the shortcomings of previously used methods of probe insertion or post-mortem CT. Insertion of the printed knife into the wound gives a good visual demonstration of the stabbing direction, thus easing the forensic reconstruction of the stabbing incident. After combining the 3D printing with photogrammetry, the achieved 3D visualization is useful for courtroom demonstration and educational purposes.
Survey on reinforcement learning for language processing
Authors: Uc-Cetina Víctor , Navarro-Guerrero Nicolás , Martin-Gonzalez Anabel , Weber Cornelius , Wermter Stefan
Published: June 2022

In recent years some researchers have explored the use of reinforcement learning (RL) algorithms as key components in the solution of various natural language processing (NLP) tasks. For instance, some of these algorithms leveraging deep neural learning have found their way into conversational systems. This paper reviews the state of the art of RL methods for their possible use for different problems of NLP, focusing primarily on conversational systems, mainly due to their growing relevance. We provide detailed descriptions of the problems as well as discussions of why RL is well-suited to solve them. Also, we analyze the advantages and limitations of these methods. Finally, we elaborate on promising research directions in NLP that might benefit from RL.
Blackout and supply chains: Cross-structural ripple effect, performance, resilience and viability impact analysis
Authors: Ivanov Dmitry
Published: June 2022

Increased electricity consumption along with the transformations of the energy systems and interruptions in energy supply can lead to a blackout, i.e., the total loss of power in an area (or a set of areas) of a longer duration. This disruption can be fatal for production, logistics, and retail operations. Depending on the scope of the affected areas and the blackout duration, supply chains (SC) can be impacted to different extent. In this study, we perform a simulation analysis using anyLogistix digital SC twin to identify potential impacts of blackouts on SCs for scenarios of different severity. Distinctively, we triangulate the design and evaluation of experiments with consideration of SC performance, resilience, and viability. The results allow for some generalizations. First, we conceptualize blackout as a special case of SC risks which is distinctively characterized by a simultaneous shutdown of several SC processes, disruption propagations (i.e., the ripple effect), and a danger of viability losses for entire ecosystems. Second, we demonstrate how simulation-based methodology can be used to examine and predict the impacts of blackouts, mitigation and recovery strategies. The major observation from the simulation experiments is that the dynamics of the power loss propagation across different regions, the blackout duration, simultaneous unavailability of supply and logistics along with the unpredictable customer behavior might become major factors that determine the blackout impact and influence selection of an appropriate recovery strategy. The outcomes of this research can be used by decision-makers to predict the operative and long-term impacts of blackouts on the SCs and viability and develop mitigation and recovery strategies. The paper is concluded by summarizing the most important insights and outlining future research agenda toward SC viability, reconfigurable SC, multi-structural SC dynamics, intertwined supply networks, and cross-structural ripple effects.
Exploring data-driven innovation: What’s missing in the relationship between big data analytics capabilities and supply chain innovation?
Authors: Bhatti Sabeen Hussain , Hussain Wan Mohd Hirwani Wan , Khan Jabran , Sultan Shahbaz , Ferraris Alberto
Published: June 2022

Data-driven innovations (DDI) have significantly impacted firms’ operations thanks to the massive exploitation of huge data. However, to leverage big data and achieve supply chain innovation, a variety of complementary resources are necessary. In this study, we hypothesise that supply chain innovation (SCI) is dependent on firms’ big data analytics capabilities (BAC). Furthermore, we propose that this relation is mediated by two crucial capabilities of agility and adaptability that enable firms to efficiently meet the challenges of supply chain ambidexterity. Finally, we also test the moderating role of technology uncertainty in our research model. We collected data from 386 manufacturing firms in Pakistan and tested our model using structural equation modelling. The results confirmed our initial hypotheses that agility and adaptability both mediated our baseline relationship of BAC and big data innovation in supply chains. We further found support for the moderating role of technology uncertainty. Furthermore, technology uncertainty moderates the relationship between BAC and SCI. This study extends the current literature on digital analytics capabilities and innovation along the supply chain. Practically, our research suggests that investment in big data can result in affirmative consequences, if firms cultivate capabilities to encounter supply chain ambidexterity through agility and adaptability. Accordingly, we suggest that managers belonging to manufacturing firms need to build up these internal capabilities and to monitor and assess technology uncertainty in the environment.
Spatial performance analysis in basketball with CART, random forest and extremely randomized trees
Authors: Zuccolotto Paola , Sandri Marco , Manisera Marica
Published: June 2022

This paper proposes tools for spatial performance analysis in basketball. In detail, we aim at representing maps of the court visualizing areas with different levels of scoring probability of the analysed player or team. To do that, we propose the adoption of algorithmic modeling techniques. Firstly, following previous studies, we examine CART, highlighting strengths and weaknesses. With respect to what done in the past, here we propose the use of polar coordinates, which are more consistent with the basketball court geometry. In order to overcome CART’s drawbacks while maintaining its points of force, we propose to resort to CART-based ensemble learning algorithms, namely to Random Forest and Extremely Randomized Trees, which are shown to be able to give excellent results in terms of interpretation and robustness. Finally, an index is defined in order to measure the map’s graphical goodness, which can be used—jointly with measures of the out-of-sample error—to tune the algorithm’s parameters. The functioning of the proposed approaches is shown by the analysis of real data of the NBA regular season 2020/2021.
A stochastic optimization algorithm for analyzing planar central and balanced configurations in the n-body problem
Authors: Doicu Alexandru , Zhao Lei , Doicu Adrian
Published: June 2022

A stochastic optimization algorithm for analyzing planar central and balanced configurations in then-body problem is presented. We find a comprehensive list of equal mass central configurations satisfying the Morse equality up to$$n=12$$n=12. We show some exemplary balanced configurations in the case$$n=5$$n=5, as well as some balanced configurations without any axis of symmetry in the cases$$n=4$$n=4and$$n=10$$n=10.
Psychological Safety at Local Union Meetings: A Key to Unlock Meeting Attendance
Authors: Mellor Steven
Published: June 2022

We take a psychological view of local union meetings in reference to the problem of chronic low meeting attendance. This view suggests that local meetings are designed to encourage employees to experience safe environments in which they can strive to fulfill psychological needs, examples of which include a need to voice concerns and opinions, a need to participate in decision-making, and a need to be counted as a valued contributor to “our collective effort.” As such, we constructed a model to predict likely meeting attendance informed by literatures on team effectiveness, meeting design, and union participation. Extracting relationships from the cited literature relevant to local meetings, we positioned psychological safety experienced at meetings as a predictor of likely attendance in the next 12 months, with meeting effectiveness as rated by attending employees positioned as a mediator of the relationship. A test of the mediated model based on data collected from employees in 20 unions and 42 locals (N = 132) suggested support for the model, in which the effect of psychological safety on likely attendance was shown to unfold through meeting effectiveness. Future models of local attendance are discussed and an intervention aimed at solving the attendance problem is suggested.
The role of brokers in cultivating an inter-institutional community around open educational resources in higher education
Authors: Baas Marjon , Schuwer Robert , van den Berg Ellen , Huizinga Tjark , van der Rijst Roeland , Admiraal Wilfried
Published: June 2022

Brokers are individuals who facilitate transfer of knowledge and resources, and coordinate efforts across boundaries of organizations. They are defined by their role rather than their organizational position. Brokers might be imperative for the formation and maintenance of inter-institutional relationship as they have the responsibility and the necessary structural position to connect otherwise separate groups. In the context of this study, brokers had the role to cultivate an inter-institutional community around open educational resources (OER) by connecting groups of teachers across higher education institutes. OER provide higher education institutes with an aid to face the challenges of improving teaching and learning. Yet most OER users encounter challenges that relate to finding resources that are relevant, up-to-date, and of good quality. Communities could minimize this issue, but many OER initiatives fizzle out as expanding their impact is an arduous task. This qualitative descriptive study draws upon cultural-historical activity theory to understand the complexities associated with the role of brokers in creating sustainable collaboration on OER across 15 higher education institutes in the Netherlands. Data was collected from project documents, process reports, reflections reports, and a retrospective focus group. The findings show that brokers engaged in a wide variety of actions but that a small-scale, personal, and content-oriented approach to encourage teachers to engage with the OER repository and the online community was perceived as the most valuable. Brokers also experienced conflicts due to the demanding context they were operating in, the ambiguity of their role, and the organizational constraints they were confronted with. Practical implications refer to supporting higher education institutes that wish to initiate sustainable collaboration across institutes.
Exploring the effects of mobility and foreign nationality on internal career progression in universities
Authors: Seeber Marco , Debacker Noëmi , Meoli Michele , Vandevelde Karen
Published: June 2022

This article explores how organizational mobility and foreign nationality affect a researcher’s chances of an internal career promotion in university systems that do not have rules preventing inbreeding and where teaching occurs mostly not in English but a local language. As a case study, we have examined the Flemish university system, the Dutch speaking part of Belgium, and developed expectations on the chances of promotion for mobile and foreign researchers compared to non-mobile and nationals. We use data for all postdoctoral and professorial staff between 1991 and 2017, for a total of 14,135 scientists. We calculated the chances of promotion with a competing risk model to take time into account and to disentangle the probability of two mutually exclusive risk events: promotion and leaving the university. The results show that international mobility and foreign nationality reduced the chances of promotion in the same university, and that mobile and foreign scientists were also more likely to leave any given university. These effects were particularly strong at an early stage: in the study period, 21.9% of non-mobile national postdocs became professor compared to just 1.2% of internationally mobile foreigners. These results would suggest that internationally mobile and foreign scientists struggle to advance in universities that lack rules preventing inbreeding and with little opportunity to teach in English.
Divergence/Connection Preservation Scheme in the Curvilinear Domain with a Small Geometric Approximation Error
Authors: Chun Sehun , Oh Taejin
Published: June 2022

Additional grid points are often introduced for the higher-order polynomial of a numerical solution with curvilinear elements. However, those points are likely to be located slightly outside the domain, even when the vertices of the curvilinear elements lie within the curved domain. This misallocation of grid points generates a mesh error, calledgeometric approximation error. This error is smaller than the discretization error but large enough to significantly degrade a long-time integration. Moreover, this mesh error is considered to be the leading cause of conservation error. Two novel schemes are proposed to improve conservation error and/or discretization error for long-time integration caused by geometric approximation error: The first scheme retrieves the original divergence of the original domain; the second scheme reconstructs the original path of differentiation, calledconnection, thus retrieving the original connection. The increased accuracies of the proposed schemes are demonstrated by the conservation error for various partial differential equations with moving frames on the sphere.
Impact of Opioid Use on Duration of Time Loss After Work-Related Lower Limb Injury
Authors: Szucs Katrina , Gray Shannon E.
Published: June 2022

Purpose This study sought to determine patterns of opioid use among workers with a compensated lower limb injury, factors associated with opioid use, and how opioid use is associated with time loss duration. Methods Claims and medication data were provided by the workers’ compensation regulator of Victoria, Australia, for claims lodged 2008–2018 from workers aged 15+ years with a lower limb injury. Descriptive statistics showed the number and prevalence of each opioid type (weak/strong) by demographic, claim and injury predictors. Binary and multinomial logistic regression determined the likelihood of any opioid use, and use of strong, weak or a combination of strong and weak opioids by predictors. Cox regression determined the effect of each opioid type on duration of time loss, controlling for predictors. Results There were 51,334 claims and of these 23.6% were dispensed opioids (9.2% for strong opioids only, 6.6% for weak opioids only and 7.8% for a combination). Weak opioids, on average, were dispensed 15 days earlier than strong opioids. Time loss claims and workers with fractures or hip injuries were most likely to be dispensed opioids. All opioids were associated with increased duration of time loss, with those dispensed both weak and strong opioids having the longest duration of time loss. Conclusions Any opioid use was associated with longer time loss duration, with increasing opioid strength having a greater effect. Review of pain management methods should be undertaken to reduce opioid use, which may have a positive impact on duration of time loss and long-term function.
Intergenerational Transmission of Peer Aggression
Authors: Wiertsema Maria , Vrijen Charlotte , van der Ploeg Rozemarijn , Kretschmer Tina
Published: June 2022

It is plausible that peer aggression—like general forms of aggression—is transmitted from one generation to the next. As such, parental behavior in childhood and adolescence may be associated with offspring aggressive behavior against peers. This study used 1970 British Cohort Study data to test intergenerational transmission of peer aggression. The baseline sample consisted of 13,135 participants. At the first assessment that was used in this study, participants were on average 4.95 years old (SD = 0.79; 48.20% female). At the last assessment, participants were on average 33.88 years old (SD = 0.36; 52.1% female). Models were computed for early and middle childhood, and adolescence. Significant associations between parents’ and offspring peer aggression were found in most models – especially when correlating aggression in similar developmental periods for parents and children. Other transmission mechanisms such as genetic transmission may be relevant and should be taken into account in future studies.
Uncertainty estimation based adversarial attack in multi-class classification
Authors: Alarab Ismail , Prakoonwit Simant
Published: June 2022

Model uncertainty has gained popularity in machine learning due to the overconfident predictions derived from standard neural networks which are not trustworthy. Recently, Monte-Carlo based adversarial attack (MC-AA) has been proposed as a simple uncertainty estimation method which is powerful in capturing data points that lie in the overlapping distribution of the decision boundary. MC-AA produces uncertainties by performing back-and-forth perturbations of a given data point towards the decision boundary using the idea of adversarial attacks. Despite its efficacy against other uncertainty estimation methods, this method has been only examined on binary classification problems. Thus, we present and examine MC-AA with multi-class classification tasks. We point out the limitation of this method with multiple classes which we tackle by converting multiclass problem into ‘one-versus-all’ classification. We compare MC-AA against other recent model uncertainty methods on Cora – a graph structured dataset – and MNIST – an image dataset. Thus, the conducted experiments are performed using a variety of deep learning algorithms to perform the classification. Consequently, we discuss the best results of model uncertainty with Cora data using LEConv model of AUC-score 0.889 and MNIST data using CNN of AUC-score 0.98 against other uncertainty estimation methods.
Designing postures for rehabilitation therapies in a multimodal system based on a 3D virtual environment and movement-based interaction
Authors: Penichet Víctor M. R. , Lozano María D. , Garrido Juan E. , Albertos-Marco Félix , Bond Raymond , Mulvenna Maurice D.
Published: June 2022

Technological advances have facilitated new approaches to support different needs in healthcare environments. In particular, in the field of rehabilitation therapies, we can find software applications that have been developed to support the performance of specific exercises, often with different customization options. However, there are still many gaps that need to be addressed to provide more and better global solutions. In this article, we present a novel system aimed at physiotherapists, which allows them to create new rehabilitation exercises designed to meet the specific needs of their patients. This implies the creation of individualized therapies that contribute to a better and faster recovery of patients. The system consists of a virtual 3D environment with a 3D skeleton representing the patient. The physiotherapist can interact with the skeleton to design the desired postures that the patient should practice according to their personal limitations. The system allows physiotherapists to compose a complete and personalized set of exercises. Alternatively, the physiotherapist may also create the postures by means of a motion sensing device using motion- and voice-based interaction. Both options pose research challenges that the authors have addressed to provide the solution presented in this paper.
Current Account Imbalances, Real Exchange Rates, and Nominal Exchange Rate Variability
Authors: Velic Adnan
Published: June 2022

This paper globally analyzes the bivariate relation between large current account imbalances and the real exchange rate over different degrees of nominal exchange rate variability. Employing both linear and nonlinear panel estimation procedures, we typically find an inverse long-run link between large imbalances and the real exchange rate at lower nominal exchange rate rigidity levels. This is in contrast to the often non-existent or positive comovement that materializes under lower nominal exchange rate variation. Our results thus suggest that greater nominal exchange rate adjustment can induce a stabilizing “current account”-“real exchange rate” relation. Meanwhile, current account adjustment speeds up with more flexible nominal exchange rates. Along the cross-section, the most salient findings are i) the striking positive relation between current account persistence and real exchange rate persistence based on country-specific estimates and ii) the inverse correlation between persistence in either the current account or real exchange rate and nominal exchange rate volatility.
The Effects of Solid Particle Containing Inks on the Printing Quality of Porous Pharmaceutical Structures Fabricated by 3D Semi-Solid Extrusion Printing
Authors: Teoh Xin-Yi , Zhang Bin , Belton Peter , Chan Siok-Yee , Qi Sheng
Published: June 2022

Purpose

Semi-solid extrusion (SSE) 3D printing has potential pharmaceutical applications for producing personalised medicine. However, the effects of ink properties and drug incorporation on the quality of printed medication have not been thoroughly studied, particularly for porous geometries. This study aimed to investigate the effects of the presence of solid drug particles in SSE inks on the printing quality of porous structures.

Method

The rheological behaviour of model inks of paracetamol (PCM)-hypromellose (HPMC) with different drug loadings were investigated and correlated to their printing qualities.

Results

For the inks with PCM loading above the drug solubility in which suspended solid drug particulates were present, the results confirmed that PCM loading and particle size significantly affected the ink viscosities at a low shear rate. At a low shear rate, the highest viscosity was identified when the highest drug loading and the smallest PCM particles were incorporated into the inks. However, the results indicated that the SSE printing parameters and printing quality of porous structures (with less porous structural deformation) have no clear correlation with the shear viscosity data, but a strong correlation with the dynamic oscillatory rheology of the inks.

Conclusion

The key rheological parameters including storage modulus, loss modulus and complex viscosity of the ink increased with increasing drug loading for the inks containing solid drug particles. However, decreasing the particle size did not have a clear effect on the oscillatory rheology of the inks which can be potentially used for optimising the SSE 3D printing quality of porous geometries.
Biocompatible Cationic Lipoamino Acids as Counterions for Oral Administration of API-Ionic Liquids
Authors: Lai Anthony , Leong Nathania , Zheng Dan , Ford Leigh , Nguyen Tri-Hung , Williams Hywel D. , Benameur Hassan , Scammells Peter J. , Porter Christopher J. H.
Published: June 2022

Purpose

The use of ionic liquids (ILs) in drug delivery has focused attention on non-toxic IL counterions. Cationic lipids can be used to form ILs with weakly acidic drugs to enhance drug loading in lipid-based formulations (LBFs). However, cationic lipids are typically toxic. Here we explore the use of lipoaminoacids (LAAs) as cationic IL counterions that degrade or digest in vivo to non-toxic components.

Methods

LAAs were synthesised via esterification of amino acids with fatty alcohols to produce potentially digestible cationic LAAs. The LAAs were employed to form ILs with tolfenamic acid (Tol) and the Tol ILs loaded into LBF and examined in vitro and in vivo.

Results

Cationic LAAs complexed with Tol to generate lipophilic Tol ILs with high drug loading in LBFs. Assessment of the LAA under simulated digestion conditions revealed that they were susceptible to enzymatic degradation under intestinal conditions, forming biocompatible FAs and amino acids. In vitro dispersion and digestion studies of Tol ILs revealed that formulations containing digestible Tol ILs were able to maintain drug dispersion and solubilisation whilst the LAA were breaking down under digesting conditions. Finally, in vivo oral bioavailability studies demonstrated that oral delivery of a LBF containing a Tol IL comprising a digestible cationic lipid counterion was able to successfully support effective oral delivery of Tol.

Conclusions

Digestible LAA cationic lipids are potential IL counterions for weakly acidic drug molecules and digest in situ to form non-toxic breakdown products.
Estimation of canopy nitrogen content in winter wheat from Sentinel-2 images for operational agricultural monitoring
Authors: Bossung Christian , Schlerf Martin , Machwitz Miriam
Published: June 2022

Canopy nitrogen content (CNC, kg/ha) provides crucial information for site-specific crop fertilization and the usability of Sentinel-2 (S2) satellite data for CNC monitoring at high fertilization levels in managed agricultural fields is still underexplored. Winter wheat samples were collected in France and Belgium in 2017 (n = 126) and 2018 (n = 18), analysed for CNC and S2-spectra were extracted at the sample locations. A comparison of three established remote sensing methods to retrieve CNC was carried out: (1) look-up-table (LUT) inversion of the canopy reflectance model PROSAIL, (2) Partial Least Square Regression (PLSR) and (3) nitrogen-sensitive vegetation indices (VI). The spatial and temporal model transferability to new data was rigorously assessed. The PROSAIL-LUT approach predicted CNC with a root mean squared error of 33.9 kg/ha on the 2017 dataset and a slightly larger value of 36.8 kg/ha on the 2018 dataset. Contrary, PLSR showed an error of 27.9 kg N/ha (R2 = 0.52) in the calibration dataset (2017) but a substantially larger error of 38.4 kg N/ha on the independent dataset (2018). VIs revealed calibration errors were slightly larger than the PLSR results but showed much higher validation errors for the independent dataset (> 50 kg/ha). The PROSAIL inversion was more stable and robust than the PLSR and VI methods when applied to new data. The obtained CNC maps may support farmers in adapting their fertilization management according to the actual crop nitrogen status.
The effect of communicative purpose and reading medium on pauses during different phases of the textualization process
Authors: Valenzuela Ángel , Castillo Ramón D.
Published: June 2022

Multiple factors simultaneously interact during the writing process. The effect of these interacting factors must be considered if writing is studied as a dynamic and complex process that constantly changes. Based on that premise, the study aims to determine how the interaction between the reading medium and the communicative purpose of a writing task affects the pauses during different stages of the writing process. At the same time, it seeks to determine how this interaction is related to the writer's competence. Using a 2-by-2 experimental design, undergraduate students (n = 66) read documents (print or digital format) and completed a computer-embedded writing task with different communicative purposes (to persuade or to inform). While writing, pauses-related keystrokes were recorded. The results show that neither the reading medium nor the task purpose or the interaction of these two variables affect pauses. However, communicative purpose interacts with the stages of the writing process, so regardless of participants' writing competence, they took longer at the end of the writing process when the purpose was to persuade. Other interactions indicated that the type of pause interacts differentially with the stage and communicative purpose. These interactions and main effects were systematically related to the writer's competence; because once it was statistically controlled, these interactions and main effects were no longer significant. The results are analysed in terms of the cognitive processes underlying pauses, considering evidence from studies on hybrid reading-writing and integrated writing studies.
From industrial to digital citizenship: rethinking social rights in cyberspace
Authors: Tomasello Federico
Published: June 2022

Growing social inequalities represent a major concern associated with the Digital Revolution. The article tackles this issue by exploring how welfare regulations and redistribution policies can be rethought in the age of digital capitalism. It focuses on the history and enduring crisis of social citizenship rights in their connection with technological changes, in order to draw a comparison between the industrial and the digital scenario. The first section addresses the link between the Industrial Revolution and the genesis of social rights. It describes the latter as a legal ‘machine’ designed to offset the imbalances produced by the technological movement of industrialization. The second and third sections introduce the notion of ‘industrial citizenship’ to describe the architecture of social rights in mature industrial societies and to contend that European systems of welfare are still largely modeled on an industrial standard. The fourth part investigates the impact of the Digital Revolution on this model of social citizenship. It identifies debates on basic income as a major trajectory for redesigning welfare regulations in a post-industrial era, and the digital user as a crucial emerging subject of rights. The final part explores how digital users could be entitled to social rights as data suppliers. To this end, it introduces the idea of ‘digital-social rights’ resulting from the incorporation of welfare and redistribution principles into emerging digital rights. Hence, it proposes a legal-political framework for the redistribution of the revenues generated by data in the form of a ‘digital basic income’ for citizens of cyberspace.
Remote Interpreting in Immigration Tribunals
Authors: Grieshofer Tatiana
Published: June 2022

As part of the response to the COVID-19 pandemic, many jurisdictions across the world introduced remote hearings as an alternative way of continuing to offer access to courts. This practice-based article discusses the report prepared by the author for a judicial review case which revolved around the claim that in immigration settings the quality of interpreting conducted in fully online hearings is inferior to interpreting in face-to-face hearings. In the absence of pre-existing research comparing the impact of the physical and fully online settings on interpreting, the author’s expert witness report explored linguistic principles governing conversation and turn-taking management, power relations and narrativisation and discursive practices in online and physical settings to illustrate communicative advantages and disadvantages of each environment. The article draws on the investigations conducted for the expert witness report and pursues the following aims: (1) reflect on the role of linguistic expertise required for the case; (2) detail the conclusions drawn and recommendations endorsed in the report; (3) discuss the importance of effective communication in immigration settings; (4) challenge common misconceptions in relation to how narratives are elicited, shared and perceived; (5) explore safeguarding strategies for enhancing discursive practices in fully remote hearings in order to improve non-native speakers’ access to justice.
Do young people really engage in sustainable behaviors in their lifestyles?
Authors: Piscitelli Alfonso , D’Uggento Angela Maria
Published: June 2022

In recent years, environmental problems have become a serious issue worldwide due to the increasing damage caused by climate change. People’s environmental awareness has grown, and public opinion is now demanding effective action from governments. Young people around the world are playing an important role in this, with the Fridays For Future movement, calling on policymakers to make environmental protection one of their political priorities. Through a survey of 1,975 high school students, this paper aims to contribute to the study of young people’s sustainable behaviors and their awareness to take effective action against environmental degradation, to explore their concerns and opinions about environmental issues, and to find out what ecological practices they are willing to adopt in their daily lives. Data analysis is conducted using tree-based methods to examine the sustainable behaviors and define the key practices that constitute them. The results of classification tree show that sustainable behaviors impact lifestyles, whether through less demanding actions such as turning off the faucet or appliances, or willingness to work as a volunteer, among others. The Random Forest provides us with a ranked list of sustainable behaviors that young people engage in to reduce and stop environmental degradation. The results of this study may be of interest to policy makers who need to plan educational pathways for students from elementary school to university, as environmental culture must be a cornerstone of our society.
Anscombe and Intentional Agency Incompatibilism (for human and animal agents)
Authors: Mayr Erasmus
Published: June 2022

In “Causality and Determination”, Anscombe stressed that, in her view, physical determinism and free action were incompatible. As the relevant passage suggests, her espousal of incompatibilism was not merely due to specific features of human ‘ethical’ freedom, but (also) due to general features of agency, intentionality, and voluntariness. For Anscombe went on to tentatively suggest that lack of physical determination was required for the intentional conduct of animals we would not classify as ‚free‘, too. In this paper, I examine three different lines of argument to establish Anscombe’s latter suggestion, which are based on general considerations about the causal efficacy of psychological-agential phenomena, the nature of agency, and the specific features of intentional agency. I start with Anscombe’s own claim from “The Causation of Action” that microphysical determinism would make psychological and personal phenomena epiphenomenal, before I turn to the view of ‘Agency Incompatibilism’, that genuine agency requires the absence of antecedent necessitation, and, lastly, to concerns about some crucial features of intentional agency which we find in both human and animal agents.