bluuebunny/crossref_metadata_2025 huggingface dataset:
Migration and Development
Authors: Wihtol de Wenden Catherine
Published: July 2023

The topic of the relationship between migration and development is one of the most controversial areas in migration research and policy. For a long time, it was considered that development was an alternative to migration, because in European history, emigration flows from Southern European countries came to an end when those countries experienced economic growth and developed more democratic political systems. In Spain, Portugal, Italy, and Greece, migration decreased or disappeared around the time of their entry into the EU. However, the assumption that the same patterns will emerge in countries on the southern rim of the Mediterranean Sea runs into several problems. The first problem relates to the demographic situation. Italy, Spain, Portugal, and Greece have all experienced a rapid demographic decrease and have thus ceased to offer a reserve of labour force for Northern Europe, as they did in the 1970s. The second reason is the gradual convergence of living standards in those Southern European countries compared with those of Northern Europe, which developed around the same time as European freedom of circulation was achieved. Freedom of circulation also created opportunities for circulation without settlement, a trend which similarly increased in Eastern European countries, when citizens of new EU Member States adopted mobility as a way of life between Romania, Poland, and Western European countries. For Eastern Europe after the 1990s, circular migration became possible as a result of the opening of borders thanks to their entry into the EU. Over the last 30 years, all Southern European countries, which were formerly emigration countries, became new immigration countries.
Deep Renovation: Definitions, Drivers and Barriers
Authors: Lynn Theo , Rosati Pierangelo , Egli Antonia
Published: July 2023

This chapter defines the key elements of the deep renovation life cycle. Investment in deep renovation is driven by various rationales, including societal, economic, environmental, energy security, quality, opportunistic, and catalytic motivations and benefits. At the same time, both deep renovation and digital technology adoption to support deep renovation are impacted by challenges presented in humans, organisational processes, technologies and external environments. This chapter explores the key drivers and barriers to deep renovation and associated digitalisation. It establishes the motivation for the remainder of the book.
Embedded Sensors, Ubiquitous Connectivity and Tracking
Authors: Arnesano Marco , Mansi Silvia Angela
Published: July 2023

The digitalisation of the deep renovation process and built environment is enabled by ubiquitous connectivity and monitoring of the environment itself, the artefacts and actors within it, and events that occur. Such monitoring is important for efficient construction management, dynamic peak demand reduction, affordability, and occupants’ well-being. Sensor networks based on Internet of Things (IoT) technologies represent an important prerequisite for both optimising and redefining the stages of the building process to meet environmental challenges. This chapter provides an overview of how computation capabilities are being integrated into the physical environment and the role of sensor networks in the context of deep renovation. The key advantages and benefits of these technologies at the pre, during and post-renovation stages are discussed together with different use cases. The value of sensor network infrastructures and the legal and ethical implications of the use of such sensor infrastructures is also discussed.
Building Performance Simulation
Authors: Dimara Asimina , Krinidis Stelios , Ioannidis Dimosthenis , Tzovaras Dimitrios
Published: July 2023

Simulation is a proven technique that uses computational, mathematical, and machine learning models to represent the physical characteristics, expected or actual operation, and control strategies of a building and its energy systems. Simulations can be used in a number of tasks along the deep renovation life cycle, including: (a) integrating simulations with other knowledge-based systems to support decision-making, (b) using simulations to evaluate and compare design scenarios, (c) integrating simulations with real-time monitoring and diagnostic systems for building energy management and control, (d) integrating multiple simulation applications, and (e) using virtual reality (VR) to enable digital building design and operation experiences. While building performance simulation is relatively well established, there are numerous challenges to applying it across the renovation life cycle, including data integration from fragmented building systems, and modelling human-building interactions, amongst others. This chapter defines the building performance simulation domain outlining significant use cases, widely used simulation tools, and the challenges for implementation.
Digital Twins and Their Roles in Building Deep Renovation Life Cycle
Authors: Pan Yuandong , Hu Zhiqi , Brilakis Ioannis
Published: July 2023

Digital twins have started to diffuse within architecture, engineering, construction, and operations (AECO), based on their emerging and anticipated benefits to the various stakeholders involved in the building life cycle. However, their applications are still at an early stage, and much effort is still needed to exploit their full potential. This chapter explains some key notions to help understand digital twins in AECO. It exposes the various definitions of digital twins and illustrates the basic steps and relevant methods for creating a digital twin. The chapter also provides an overview of the state-of-the-art deep learning methods for digital twins and discusses some real-life use cases. Finally, the chapter discusses the benefits and challenges associated with the adoption of digital twins.
Additive Manufacturing and the Construction Industry
Authors: Chougan Mehdi , Al-Kheetan Mazen J. , Ghaffar Seyed Hamidreza
Published: July 2023

Additive manufacturing (AM), including 3D printing, has the potential to transform the construction industry. AM allows the construction industry to use complex and innovative geometries to build an object, building block, wall, or frame from a computer model. As such, it has potential opportunities for the construction industry and specific applications in the deep renovation process. While AM can provide significant benefits in the deep renovation process, it is not without its own environmental footprint and barriers. In this chapter, AM is defined, and the main materials used within the construction industry are outlined. This chapter also explores the benefits and challenges of implementing AM within the construction industry before concluding with a discussion of the future areas of development for AM in construction.
Grundlagen: Verarbeitung
Authors: Dhungel Anna-Katharina
Published: August 2023

Im vorigen Kapitel wurde das Thema Daten aus verschiedenen Perspektiven behandelt und erörtert. Nun geht es um die Frage, wie ein KI-System Daten verarbeitet. Hierfür werden zunächst die unterschiedlichen Trainingsmethoden vorgestellt: überwachtes Lernen (3.2), unüberwachtes Lernen (3.3) sowie bestärkendes Lernen (3.4). Es folgt die Einführung künstlicher neuronaler Netze (3.5), deren Entwicklung momentan rasant voranschreitet. Die beiden folgenden Abschnitte befassen sich mit den Verfahren Support Vector Machine (3.6) sowie lineare und logistische Regression (3.7). Das angeeignete Wissen kann in einer Übung reflektiert (3.8) und im eigenen Anwendungsfall eingesetzt werden (3.9).
Phase Spaces, Parity Operators, and the Born–Jordan Distribution
Authors: Koczor Bálint , vom Ende Frederik , de Gosson Maurice , Glaser Steffen J. , Zeier Robert
Published: August 2023

Phase spaces as given by the Wigner distribution function provide a natural description of infinite-dimensional quantum systems. They are an important tool in quantum optics and have been widely applied in the context of time–frequency analysis and pseudo-differential operators. Phase-space distribution functions are usually specified via integral transformations or convolutions which can be averted and subsumed by (displaced) parity operators proposed in this work. Building on earlier work for Wigner distribution functions (Grossmann in Commun Math Phys 48(3):191–194, 1976.https://doi.org/10.1007/BF01617867), parity operators give rise to a general class of distribution functions in the form of quantum-mechanical expectation values. This enables us to precisely characterize the mathematical existence of general phase-space distribution functions. We then relate these distribution functions to the so-called Cohen class (Cohen in J Math Phys 7(5):781–786, 1966.https://doi.org/10.1063/1.1931206) and recover various quantization schemes and distribution functions from the literature. The parity operator approach is also applied to the Born–Jordan distribution which originates from the Born–Jordan quantization (Born and Jordan in Z Phys 34(1):858–888, 1925.https://doi.org/10.1007/BF01328531). The corresponding parity operator is written as a weighted average of both displacements and squeezing operators, and we determine its generalized spectral decomposition. This leads to an efficient computation of the Born–Jordan parity operator in the number-state basis, and example quantum states reveal unique features of the Born–Jordan distribution.
Characterizing the supra- and subsolidus processes that generated the Current PGE–Cu–Ni deposit, Thunder Bay North Intrusive Complex, Canada: insights from trace elements and multiple S isotopes of sulfides
Authors: Brzozowski M. , Hollings P. , Heggie G. , MacTavish A. , Wilton D. , Evans-Lamswood D.
Published: July 2023

The Current deposit is hosted by serpentinized peridotite that intruded rocks of the Quetico Subprovince in the Midcontinent Rift, and is subdivided into three morphologically distinct regions — the shallow and thin Current–Bridge Zone in the northwest, the deep and thick 437–Southeast Anomaly (SEA) Zone in the southeast, and the thick Beaver–Cloud Zone in the middle. The magma parental to the Current deposit became saturated in sulfide as a result of the addition of external S from at least two sources — a deep source characterized by high Δ33S (< 3‰) values, and a shallow source, potentially the Archean metasedimentary country rocks, characterized by low Δ33S (< 0.3‰). Variations in Δ33S–S/Se–Cu/Pd values indicate that the contamination signatures were largely destroyed by interaction of the sulfide liquid with large volumes of uncontaminated silicate melt. The intrusion crystallized sequentially, with the Current–Bridge Zone crystallizing first, followed by the Beaver–Cloud Zone, and lastly by the 437–SEA Zone. This, along with the elevated Cu/Pd ratios in the 437–SEA Zone, which formed as a result of sulfide segregation during an earlier saturation event, and development of igneous layering in this zone, suggests that it represents the feeder channel to the Current deposit. After the intrusion crystallized, the base-metal sulfide mineralogy was modified by circulation of late-stage hydrothermal fluids, with pyrrhotite and pentlandite being replaced by pyrite and millerite, respectively. This fluid activity mobilized metals and semi-metals, including Fe, Ni, S, Se, Co, Cu, Ag, and As, but did not affect the PGE. This contribution highlights the importance of the interplay between magma dynamics and magmatic–hydrothermal processes in the formation of Ni–Cu–PGE-mineralized deposits.
Second-order homogenization of 3-D lattice materials towards strain gradient media: numerical modelling and experimental verification
Authors: Molavitabrizi Danial , Khakalo Sergei , Bengtsson Rhodel , Mousavi S. Mahmoud
Published: August 2023

The literature in the field of higher-order homogenization is mainly focused on 2-D models aimed at composite materials, while it lacks a comprehensive model targeting 3-D lattice materials (with void being the inclusion) with complex cell topologies. For that, a computational homogenization scheme based on Mindlin (type II) strain gradient elasticity theory is developed here. The model is based on variational formulation with periodic boundary conditions, implemented in the open-source software FreeFEM to fully characterize the effective classical elastic, coupling, and gradient elastic matrices in lattice materials. Rigorous mathematical derivations based on equilibrium equations and Hill–Mandel lemma are provided, resulting in the introduction of macroscopic body forces and modifications in gradient elasticity tensors which eliminate the spurious gradient effects in the homogeneous material. The obtained homogenized classical and strain gradient elasticity matrices are positive definite, leading to a positive macroscopic strain energy density value—an important criterion that sometimes is overlooked. The model is employed to study the size effects in 2-D square and 3-D cubic lattice materials. For the case of 3-D cubic material, the model is verified using full-field simulations, isogeometric analysis, and experimental three-point bending tests. The results of computational homogenization scheme implemented through isogeometric simulations show a good agreement with full-field simulations and mechanical tests. The developed model is generic and can be used to derive the effective second-grade continuum for any 3-D architectured material with arbitrary geometry. However, the identification of the proper type of generalized continua for the mechanical analysis of different cell architectures is yet an open question.
Risk preference and entrepreneurial investment at the top of the wealth distribution
Authors: Fossen Frank M. , König Johannes , Schröder Carsten
Published: August 2023

We present evidence on how individual risk preferences are related to entrepreneurial investment among the wealthy. To do so, we use novel survey data from the top of the wealth distribution, which have been fully integrated into the 2019 German Socio-economic Panel Study. The data include private wealth balance sheets, in particular the value of own private business assets, and a standard measure of risk tolerance. We find that wealthy individuals are more likely to be entrepreneurs and invest a larger share of their wealth in their own businesses when they are more willing to take risks. A comparison with less wealthy individuals reveals that these associations are stronger among the wealthy. Since the wealthy dominate aggregate risky investment, their extraordinarily high preference for risk and its link to entrepreneurial activity should be taken into account in theory development, empirical analysis, and the design of public policies influencing the riskiness of income and wealth such as progressive taxation.
Influence of non-osteoporotic treatments in patients on active anti-osteoporotic therapy: evidence from the OSTEOMED registry
Authors: Coco-Martín María Begoña , Leal-Vega Luis , Blázquez-Cabrera José Antonio , Navarro Amalia , Moro María Jesús , Arranz-García Francisca , Amérigo María José , Sosa-Henríquez Manuel , Vázquez María Ángeles , Montoya María José , Díaz-Curiel Manuel , Olmos José Manuel , Ruiz-Mambrilla Marta , Filgueira-Rubio José , Pérez-Castrillón José Luis ,   on behalf of the OSTEOMED Group, Filgueira-Rubio José , Hernández-de Sosa Nerea , Calero-Bernal María Luz , Armengol-Sucarrats Dolors , de Escalante-Yanguas Begoña , Miranda-Díaz Cristina , Miranda-García María José , Giner-García Mercedes , Jareño-Chaumel Julia , Cotos-Canca Rafael , Hernández José Luis , Rodero-Hernández Francisco Javier , Sánchez-Molini Pilar , Aguado-Caballero José María , Cobeta-García Juan Carlos , Tirado-Miranda Raimundo
Published: July 2023

Purpose

To evaluate the effect of different non-osteoporotic drugs on the increase or decrease in the risk of incident fragility fractures (vertebral, humerus or hip) in a cohort of patients diagnosed with osteoporosis on active anti-osteoporotic therapy.

Methods

For this retrospective longitudinal study, baseline and follow-up data on prescribed non-osteoporotic treatments and the occurrence of vertebral, humerus or hip fractures in 993 patients from the OSTEOMED registry were analyzed using logistic regression models. The drugs evaluated with a possible beneficial effect were thiazides and statins, while the drugs evaluated with a possible harmful effect were antiandrogens, aromatase inhibitors, proton pump inhibitors, selective serotonin reuptake inhibitors, benzodiazepines, GnRH agonists, thyroid hormones, and oral and inhaled corticosteroids.

Results

Logistic regression analyses indicated that no treatment significantly improved fracture risk, with the only treatments that significantly worsened fracture risk being letrozole (OR = 0.18, p-value = 0.03) and oral corticosteroids at doses ≤ 5 mg/day (OR = 0.16, p-value = 0.03) and > 5 mg/day (OR = 0.27, p-value = 0.04).

Conclusion

The potential beneficial or detrimental effects of the different drugs evaluated on fracture risk are masked by treatment with anabolic or antiresorptive drugs that have a more potent action on bone metabolism, with two exceptions: letrozole and oral corticosteroids. These findings may have important clinical implications, as patients receiving these treatments are not fully protected by bisphosphonates, which may imply the need for more potent anti-osteoporotic drugs such as denosumab or teriparatide.
Deciphering the immune reaction leading to spontaneous melanoma regression: initial role of MHCII+ CD163− macrophages
Authors: Blanc Fany , Bertho Nicolas , Piton Guillaume , Leplat Jean-Jacques , Egidy Giorgia , Bourneuf Emmanuelle , Vincent-Naulleau Silvia , Prévost-Blondel Armelle
Published: August 2023

The human cutaneous metastatic melanoma is the deadliest skin cancer. Partial, or less frequently complete spontaneous regressions could be observed, mainly mediated by T cells. Nevertheless, the underlying mechanisms are not fully unraveled. We investigated the first events of the immune response related to cancer regression in Melanoma-bearing Libechov Minipigs (MeLiM), a unique swine model of cutaneous melanoma that regresses spontaneously. Using a multiparameter flow cytometry strategy and integrating new clinical and histological criteria of the regression, we show that T cells and B cells are present only in the late stages, arguing against their role in the initial destruction of malignant cells. NK cells infiltrate the tumors before T cells and therefore might be involved in the induction of the regression process. Myeloid cells represent the main immune population within the tumor microenvironment regardless of the regression stage. Among those, MHCII+ CD163− macrophages that differ phenotypically and functionally compared to other tumor-associated macrophages, increase in number together with the first signs of regression suggesting their crucial contribution to initiating the regression process. Our study supports the importance of macrophage reprogramming in humans to improve current immunotherapy for metastatic melanoma.
Unifying incidence and prevalence under a time-varying general branching process
Authors: Pakkanen Mikko S. , Miscouridou Xenia , Penn Matthew J. , Whittaker Charles , Berah Tresnia , Mishra Swapnil , Mellan Thomas A. , Bhatt Samir
Published: August 2023

Renewal equations are a popular approach used in modelling the number of new infections, i.e., incidence, in an outbreak. We develop a stochastic model of an outbreak based on a time-varying variant of the Crump–Mode–Jagers branching process. This model accommodates a time-varying reproduction number and a time-varying distribution for the generation interval. We then derive renewal-like integral equations for incidence, cumulative incidence and prevalence under this model. We show that the equations for incidence and prevalence are consistent with the so-called back-calculation relationship. We analyse two particular cases of these integral equations, one that arises from a Bellman–Harris process and one that arises from an inhomogeneous Poisson process model of transmission. We also show that the incidence integral equations that arise from both of these specific models agree with the renewal equation used ubiquitously in infectious disease modelling. We present a numerical discretisation scheme to solve these equations, and use this scheme to estimate rates of transmission from serological prevalence of SARS-CoV-2 in the UK and historical incidence data on Influenza, Measles, SARS and Smallpox.
Existence of Almost Greedy Bases in Mixed-Norm Sequence and Matrix Spaces, Including Besov Spaces
Authors: Albiac Fernando , Ansorena José L. , Bello Glenier , Wojtaszczyk Przemysław
Published: July 2023

We prove that the sequence spaces $$\ell _p\oplus \ell _q$$

ℓ
p

⊕

ℓ
q

and the spaces of infinite matrices $$\ell _p(\ell _q)$$

ℓ
p

(

ℓ
q

)

, $$\ell _q(\ell _p)$$

ℓ
q

(

ℓ
p

)

and $$(\bigoplus _{n=1}^\infty \ell _p^n)_{\ell _q}$$

(

⨁

n
=
1

∞

ℓ
p
n

)

ℓ
q

, which are isomorphic to certain Besov spaces, have an almost greedy basis whenever $$0<p<1<q<\infty $$

0
<
p
<
1
<
q
<
∞

. More precisely, we custom-build almost greedy bases in such a way that the Lebesgue parameters grow in a prescribed manner. Our arguments critically depend on the extension of the Dilworth–Kalton–Kutzarova method from Dilworth et al. (Stud Math 159(1):67–101, 2003), which was originally designed for constructing almost greedy bases in Banach spaces, to make it valid for direct sums of mixed-normed spaces with nonlocally convex components. Additionally, we prove that the fundamental functions of all almost greedy bases of these spaces grow as $$(m^{1/q})_{m=1}^\infty $$

(

m

1
/
q

)

m
=
1

∞

.
The co-existence of peripheral and vestibular neuropathy in diabetes: a cross-sectional study
Authors: Mahalingasivam Aksayan Arunanthy , Jespersen Asger Krohn , Ejskjaer Niels , Hougaard Dan Dupont , Vestergaard Peter , Rasmussen Nicklas Højgaard-Hessellund , Røikjer Johan
Published: July 2023

Purpose

Diabetic neuropathy can lead to decreased peripheral sensation and motor neuron dysfunction associated with impaired postural control and risk of falling. However, the relationship between decreased peripheral sensation and impaired vestibular function in diabetes mellitus is poorly investigated. Therefore, the aim of this study was to investigate the relationship between peripheral and autonomic measurements of diabetic neuropathy and measurements of vestibular function.

Methods

A total of 114 participants with type 1 diabetes (n = 52), type 2 diabetes (n = 51) and controls (n = 11) were included. Vestibular function was evaluated by video head impulse testing. Peripheral neuropathy was assessed by quantitative sensory testing and nerve conduction. Autonomic neuropathy using the COMPASS 31 questionnaire. Data were analyzed according to data type and distribution.

Results

Measurements of vestibular function did not differ between participants with type 1 diabetes, type 2 diabetes or controls (all p-values above 0.05). Subgrouping of participants according to the involvement of large-, small- or autonomic nerves did not change this outcome. Correlation analyses showed a significant difference between COMPASS 31 and right lateral gain value (ρ = 0.23, p = 0.02,), while no other significant correlations were found.

Conclusion

Diabetic neuropathy does not appear to impair vestibular function in diabetes, by means of the VOR.

Clinical trials

NCT05389566, May 25th, 2022.
A network meta-analysis of efficacy, acceptability, and tolerability of antipsychotics in treatment-resistant schizophrenia
Authors: Dong Shimeng , Schneider-Thoma Johannes , Bighelli Irene , Siafis Spyridon , Wang Dongfang , Burschinski Angelika , Schestag Kristina , Samara Myrto , Leucht Stefan
Published: August 2023

Objective

Clozapine is considered as the standard treatment for this subgroup, but the evidence is not unequivocal. There are several potential alternatives being used because of the possible adverse effects of clozapine. We aimed to examine the efficacy and adverse events of different antipsychotics in treatment-resistant schizophrenia by performing a network meta-analysis.

Methods

We searched the Cochrane Schizophrenia Group register for randomized-controlled trials (up to March 06, 2022) and MEDLINE (up to January 20, 2023). We included blinded and open studies and participants with a broad definition of treatment resistance. The primary outcome was overall symptoms of schizophrenia; secondary outcomes were response to treatment, positive and negative symptoms of schizophrenia, discontinuation, side effects, quality of life, and functioning. The study was registered in Open Science Framework (https://osf.io/9nf2y/).

Results

We included 60 studies involving 6838 participants in the network meta-analysis. In the primary outcome, clozapine and olanzapine were more efficacious than risperidone, haloperidol, fluphenazine, sertindole, chlorpromazine, and quetiapine (range of mean SMDs, − 0.11 to − 0.48). The difference between clozapine and olanzapine was trivial and uncertain (SMD − 0.05, 95% CI, − 0.21 to 0.11). The result of other efficacy outcomes as well as subgroup and sensitivity analyses were consistent with the primary analysis. Clozapine and olanzapine were associated with more weight gain, and clozapine was associated with more sedation events compared to many other antipsychotics.

Conclusions

Clozapine remains the gold standard for patients with treatment-resistant schizophrenia. Olanzapine seems to be second-best and could be tried before switching to clozapine.
Neurological symptoms after COVID-19 vaccination: a report on the clinical presentation of the first 50 patients
Authors: Gerhard Ameli , Raeder Vanessa , Pernice Helena Franziska , Boesl Fabian , Schroeder Maria , Richter Jonathan , Endres Matthias , Prüß Harald , Hahn Katrin , Audebert Heinrich J. , Franke Christiana
Published: July 2023

Objectives

Neurological symptoms associated with Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) vaccination were discovered in the context of billions of administered vaccine doses. The clinical manifestations often resemble post Coronavirus Disease 2019 (post-COVID-19) syndrome (PCS) features and may be considered as post-COVID-19 vaccine syndrome (PVS). Data regarding frequency, severity and pathophysiological mechanisms are scarce.

Methods

We assessed routine clinical examinations in 50 patients reporting new-onset neurological symptoms after SARS-CoV-2 vaccination, including neurological examination, laboratory and electrophysiology tests, as well as self-report questionnaires measuring fatigue, depressive symptoms, anxiety, risk of somatic symptom disorder, and health-related quality of life. Patients were included when symptoms occurred after confirmed COVID-19 vaccination and without prior SARS-CoV-2 infection, and if no alternative diagnosis was found to explain the symptoms.

Results

The most frequently reported symptoms were paraesthesia (56%), fatigue (46%) and cognitive impairment (36%). Neurological, routine laboratory, and electrophysiological examinations did not yield distinct pathological findings. Neuropsychological testing of a subgroup revealed deficits in attention, executive function and memory.

Discussion

The spectrum of clinical manifestations post-vaccination poses a substantial overlap with PCS symptoms. As no pathological findings were obtained in routine diagnostics, uncertainty remains about the underlying pathophysiological mechanisms and requires further investigation beyond routine work-up.
An unusual cause of chronic neuropathic pain: report of a case of multiple intradural spinal arachnoid cysts and review of the literature
Authors: El-Hajj Victor Gabriel , Edström Erik , Elmi-Terander Adrian , Fletcher-Sandersjöö Alexander
Published: August 2023

Spinal arachnoid cysts (SACs) arise either intra- or extradurally and are usually solitary, while cases of multiple SACs have been scarcely reported in the literature. Herein, we report on a rare case of multiple and recurring intradural spinal arachnoid cysts (SACs) causing severe spinal cord compression and neuropathic radicular pain, in a 35-year-old female with a 10-year follow-up. Two separate attempts at surgery were performed but only provided temporary relief since the cysts recurred and new ones formed along the entirety of the spinal cord. Finally, a conservative approach with physiotherapy and a combination of analgesic medications was pursued.
Amino acids, post-translational modifications, nitric oxide, and oxidative stress in serum and urine of long COVID and ex COVID human subjects
Authors: Mikuteit Marie , Baskal Svetlana , Klawitter Sandra , Dopfer-Jablonka Alexandra , Behrens Georg M. N. , Müller Frank , Schröder Dominik , Klawonn Frank , Steffens Sandra , Tsikas Dimitrios
Published: July 2023

In this study, we investigated the status of amino acids, their post-translational modifications (PTM), major nitric oxide (NO) metabolites and of malondialdehyde (MDA) as a biomarker of oxidative stress in serum and urine samples of long COVID (LoCo, n = 124) and ex COVID (ExCo, n = 24) human subjects collected in 2022. Amino acids and metabolites were measured by gas chromatography–mass spectrometry (GC–MS) methods using stable-isotope labelled analogs as internal standards. There were no differences with respect to circulating and excretory arginine and asymmetric dimethylarginine (ADMA). LoCo participants excreted higher amounts of guanidino acetate than ExCo participants (17.8 ± 10.4 µM/mM vs. 12.6 ± 8.86 µM/mM, P = 0.005). By contrast, LoCo participants excreted lower amounts of the advanced glycation end-product (AGE) NG-carboxyethylarginine (CEA) than ExCo participants did (0.675 ± 0.781 µM/mM vs. 1.16 ± 2.04 µM/mM, P = 0.0326). The serum concentrations of MDA did not differ between the groups, indicating no elevated oxidative stress in LoCo or ExCo. The serum concentration of nitrite was lower in LoCo compared to ExCo (1.96 ± 0.92 µM vs. 2.56 ± 1.08 µM; AUC, 0.718), suggesting altered NO synthesis in the endothelium. The serum concentration of nitrite correlated inversely with the symptom anxiety (r = − 0.293, P = 0.0003). The creatinine-corrected urinary excretion of Lys and its metabolite L-5-hydroxy-Lys correlated positively with COVID toes (r = 0.306, P = 0.00027) and sore throat (r = 0.302, P = 0.0003). Our results suggest that amino acid metabolism, PTM and oxidative stress are not severely affected in long COVID. LoCo participants may have a lower circulating NO reservoir than ExCo.
Numerical simulation of spatial temperature and salinity distribution in the Waiwera geothermal reservoir, New Zealand
Authors: Kempka Thomas , Kühn Michael
Published: August 2023

The geothermal reservoir in Waiwera was not sustainably managed for many decades. Hence, the responsible authority introduced a water management concept, whereby various independent models were developed and calibrated using observations. As these models were not yet able to reproduce all observations, constant model revisions are critical for efficient reservoir management. Results of a recent field campaign were used for the current model revision, considering two new main structural geological findings to reconstruct the natural reservoir state. Our simulation results demonstrate that a recently proven north-south trending fault in the study area plays a key role in improving the model. Further analysis suggests the presence of a not yet confirmed additional west-east aligned geologic fault in the north, since thermal convection is observed inland. Additional field campaigns are needed to acquire more information on the main geological fault zones as well as additional data on temperature and salinity distributions.
Assessment and comparison of probability scores to predict giant cell arteritis
Authors: Sargi Chadi , Ducharme-Benard Stephanie , Benard Valerie , Meunier Rosalie-Selene , Ross Carolyn , Makhzoum Jean-Paul
Published: August 2023

Introduction/objectives

To assess and compare the performance of the giant cell arteritis probability score (GCAPS), Ing score, Bhavsar-Khalidi score (BK score), color Doppler ultrasound (CDUS) halo count, and halo score, to predict a final diagnosis of giant cell arteritis (GCA).

Method

A prospective cohort study was conducted from April to December 2021. Patients with suspected new-onset GCA referred to our quaternary CDUS clinic were included. Data required to calculate each clinical and CDUS probability score was systematically collected at the initial visit. Final diagnosis of GCA was confirmed clinically 6 months after the initial visit, by two blinded vasculitis specialists. Diagnostic accuracy and receiver operator characteristic (ROC) curves for each clinical and CDUS prediction scores were assessed.

Results

Two hundred patients with suspected new-onset GCA were included: 58 with confirmed GCA and 142 without GCA. All patients with GCA satisfied the 2022 ACR/EULAR classification criteria. A total of 5/15 patients with GCA had a positive temporal artery biopsy. For clinical probability scores, the GCAPS showed the best sensitivity (Se, 0.983), whereas the BK score showed the best specificity (Sp, 0.711). As for CDUS, a halo count of 1 or more was found to have a Se of 0.966 and a Sp of 0.979. Combining concordant results of clinical and CDUS prediction scores showed excellent performance in predicting a final diagnosis of GCA.

Conclusion

Using a combination of clinical score and CDUS halo count provided an accurate GCA prediction method which should be used in the setting of GCA Fast-Track clinics.

Key Points• In this prospective cohort of participants with suspected GCA, 3 clinical prediction tools and 2 ultrasound scores were compared head-to-head to predict a final diagnosis of GCA.• For clinical prediction tools, the giant cell arteritis probability score (GCAPS) had the highest sensitivity, whereas the Bhavsar-Khalidi score (BK score) had the highest specificity.• Ultrasound halo count was both sensitive and specific in predicting GCA.• Combination of a clinical prediction tool such as the GCAPS, with ultrasound halo count, provides an accurate method to predict GCA.
Genetic and morphological characterization of a new genotype of nervous necrosis virus circulating among Nile tilapia in the south of Egypt
Authors: Gherbawy Youssuf Ahmed , Thabet Maha Aboelkassem , Sultan Serageldeen
Published: July 2023

Nervous necrosis virus (NNV) is the causative agent of viral nervous necrosis in freshwater and marine fishes. In this study, NNV circulating among wild and farmed Nile tilapia (Oreochromis niloticus) was genetically and morphologically characterized using reverse transcription polymerase chain reaction (RT-PCR), sequencing analysis, and transmission electron microscopy (TEM). Brain, eye, and other organ (spleen, kidney, heart, and liver) specimens were collected from 87 wild (66) and farmed (21) Nile tilapia fish during their adult or juvenile stage at different localities in Qena and Sohag governorates in southern Egypt. Among them, 57/87 fish showed suspected NNV clinical signs, and 30/87 were healthy. The results revealed that NNV was detected in 66 out of 87 fish (58.62% in the wild and 17.24% in farmed Nile tilapia by RT-PCR), and the prevalence was higher among diseased (55.17%) than in healthy (20.69%) fish. NNV was detected in the brain, eye, and other organs. Using TEM, virion size variations based on the infected organs were observed. Nucleotide sequence similarity indicated that NNVs had a divergence of 75% from other fish nodaviruses sequenced in Egypt and worldwide. Phylogenetic analysis distinguished them from other NNV genotypes, revealing the emergence of a new NNV genotype in southern Egypt. In conclusion, NNV is circulating among diseased and healthy Nile tilapia, and a new NNV genotype has emerged in southern Egypt.
Improved Resolution Estimate for the Two-Dimensional Super-Resolution and a New Algorithm for Direction of Arrival Estimation with Uniform Rectangular Array
Authors: Liu Ping , Ammari Habib
Published: August 2023

In this paper, we develop a new technique to obtain improved estimates for the computational resolution limits in two-dimensional super-resolution problems and present a new idea for developing two-dimensional super-resolution algorithms. To be more specific, our main contributions are fourfold: (1) Our work improves the resolution estimates for number detection and location recovery in two-dimensional super-resolution problems; (2) As a consequence, we derive a stability result for a sparsity-promoting algorithm in two-dimensional super-resolution problems [or direction of arrival Problems (DOA)]. The stability result exhibits the optimal performance of sparsity promoting in solving such problems; (3) Inspired by the new techniques, we propose a new coordinate-combination-based model order detection algorithm for two-dimensional DOA estimation and theoretically demonstrate its optimal performance, and (4) we also propose a new coordinate-combination-based MUSIC algorithm for super-resolving sources in two-dimensional DOA estimation. It has excellent performance and enjoys some advantages compared to the conventional DOA algorithms.
Heterologous gene expression system for the production of hydrolyzable tannin intermediates in herbaceous model plants
Authors: Oda-Yamamizo Chihiro , Mitsuda Nobutaka , Milkowski Carsten , Ito Hideyuki , Ezura Kentaro , Tahara Ko
Published: August 2023

Aluminum toxicity is the main factor limiting the elongation of plant roots in acidic soil. The tree species Eucalyptus camaldulensis is considerably more resistant to aluminum than herbaceous model plants and crops. Hydrolyzable tannins (HTs) accumulating in E. camaldulensis roots can bind and detoxify the aluminum taken up by the roots. However, in herbaceous model plants, HTs do not accumulate and the genes involved in the HT biosynthetic pathway are largely unknown. The aim of this study was to establish a method for reconstituting the HT biosynthetic pathway in the HT non-accumulating model plant Nicotiana benthamiana. Four E. camaldulensis enzymes were transiently expressed in N. benthamiana leaves via Agrobacterium tumefaciens-mediated transformation. These enzymes included dehydroquinate dehydratase/shikimate dehydrogenases (EcDQD/SDH2 and EcDQD/SDH3), which catalyze the synthesis of gallic acid, the first intermediate of the HT biosynthetic pathway that branches off from the shikimate pathway. The others were UDP-glycosyltransferases (UGT84A25 and UGT84A26), which catalyze the conversion of gallic acid to β-glucogallin, the second intermediate. The co-expression of the EcDQD/SDHs in transgenic N. benthamiana leaf regions promoted the synthesis of gallic acid. Moreover, the co-expression of the UGT84As in addition to the EcDQD/SDHs resulted in the biosynthesis of β-glucogallin, the universal metabolic precursor of HTs. Thus, we successfully reconstituted a portion of the HT biosynthetic pathway in HT non-accumulating N. benthamiana plants. This heterologous gene expression system will be useful for co-expressing candidate genes involved in downstream reactions in the HT biosynthetic pathway and for clarifying their in planta functions.
Precise orbit determination of LEO satellites: a systematic review
Authors: Selvan Kannan , Siemuri Akpojoto , Prol Fabricio S. , Välisuo Petri , Bhuiyan M. Zahidul H. , Kuusniemi Heidi
Published: August 2023

The need for precise orbit determination (POD) has grown significantly due to the increased amount of space-based activities taking place at an accelerating pace. Accurate POD positively contributes to achieving the requirements of Low-Earth Orbit (LEO) satellite missions, including improved tracking, reliability and continuity. This research aims to systematically analyze the LEO–POD in four aspects: (i) data sources used; (ii) POD technique implemented; (iii) validation method applied; (iv) accuracy level obtained. We also present the most used GNSS systems, satellite missions, processing procedures and ephemeris. The review includes studies on LEO–POD algorithms/methods and software published in the last two decades (2000–2021). To this end, 137 primary studies relevant to achieving the objective of this research were identified. After the investigation of these primary studies, it was found that several types of POD techniques have been employed in the POD of LEO satellites, with a clear trend observed for techniques using reduced-dynamic model, least-squares solvers, dual-frequency signals with undifferenced phase and code observations in post-processing mode. This review provides an understanding of the various POD techniques, dataset utilized, validation techniques, and accuracy level of LEO satellites, which have interest to developers of small satellites, new researchers and practitioners.
Factors influencing low incidence of double brooding in the Great Reed Warbler
Authors: Trnka Alfréd , Samaš Peter
Published: July 2023

Double brooding, the laying of a second clutch after successfully fledging young from a first nest in a season, is a common reproductive strategy among short-lived birds to increase annual breeding success. Nevertheless, there is widespread intra- and interspecific variation in the probability of producing a second clutch. Given that the frequency of double brooding could affect population growth rate, knowing what factors contribute to this phenomenon is also important in the conservation management of threatened facultative double-brooded species. Here, we examine the frequency of double brooding and the factors affecting the probability of this reproductive strategy in a population of the Great Reed Warbler, Acrocephalus arundinaceus, in south-western Slovakia. Results of a 15-year study (2008–2022) revealed low overall rate of double brooding in the Great Reed Warbler (5.6% per year, 0–15.4%). The length of breeding season, timing of the first clutch laying date and the size of the first broods were key factors influencing the female's decision to initiate a second clutch. On the other hand, successful brood parasitism did not affect second clutch initiation, which contrasts with our prediction. Given that only monogamous or primary females initiated a second clutch after successfully rearing a first one, we assume that producing two broods within the same season may be an alternative strategy for monogamous males to increase their annual reproductive output in this facultatively polygynous species. Therefore, due to relatively high rate of polygyny, we probably cannot expect higher rate of double broodings in the Great Reed Warbler in the future either.
A survey of uncertainty in deep neural networks
Authors: Gawlikowski Jakob , Tassi Cedrique Rovile Njieutcheu , Ali Mohsin , Lee Jongseok , Humt Matthias , Feng Jianxiang , Kruspe Anna , Triebel Rudolph , Jung Peter , Roscher Ribana , Shahzad Muhammad , Yang Wen , Bamler Richard , Zhu Xiao Xiang
Published: July 2023

Over the last decade, neural networks have reached almost every field of science and become a crucial part of various real world applications. Due to the increasing spread, confidence in neural network predictions has become more and more important. However, basic neural networks do not deliver certainty estimates or suffer from over- or under-confidence, i.e. are badly calibrated. To overcome this, many researchers have been working on understanding and quantifying uncertainty in a neural network’s prediction. As a result, different types and sources of uncertainty have been identified and various approaches to measure and quantify uncertainty in neural networks have been proposed. This work gives a comprehensive overview of uncertainty estimation in neural networks, reviews recent advances in the field, highlights current challenges, and identifies potential research opportunities. It is intended to give anyone interested in uncertainty estimation in neural networks a broad overview and introduction, without presupposing prior knowledge in this field. For that, a comprehensive introduction to the most crucial sources of uncertainty is given and their separation into reducible model uncertainty and irreducible data uncertainty is presented. The modeling of these uncertainties based on deterministic neural networks, Bayesian neural networks (BNNs), ensemble of neural networks, and test-time data augmentation approaches is introduced and different branches of these fields as well as the latest developments are discussed. For a practical application, we discuss different measures of uncertainty, approaches for calibrating neural networks, and give an overview of existing baselines and available implementations. Different examples from the wide spectrum of challenges in the fields of medical image analysis, robotics, and earth observation give an idea of the needs and challenges regarding uncertainties in the practical applications of neural networks. Additionally, the practical limitations of uncertainty quantification methods in neural networks for mission- and safety-critical real world applications are discussed and an outlook on the next steps towards a broader usage of such methods is given.
DynaQ: online learning from imbalanced multi-class streams through dynamic sampling
Authors: Sadeghi Farnaz , Viktor Herna L. , Vafaie Parsa
Published: July 2023

Online supervised learning from fast-evolving data streams, particularly in domains such as health, the environment, and manufacturing, is a crucial research area. However, these domains often experience class imbalance, which can skew class distributions. It is essential for online learning algorithms to analyze large datasets in real-time while accurately modeling rare or infrequent classes that may appear in bursts. While methods have been proposed to handle binary class imbalance, there is a lack of attention to multi-class imbalanced settings with varying degrees of imbalance in evolving streams. In this paper, we present the Dynamic Queues (DynaQ) algorithm for online learning in multi-class imbalanced settings to fill this knowledge gap. Our approach utilizes a batch-based resampling method that creates an instance queue for each class to balance the number of instances. We maintain a queue threshold and remove older samples during training. Additionally, we dynamically oversample minority classes based on one of four rate parameters: recall, F1-score, $$\kappa _m$$

κ
m

, and Euclidean distance. Our learning algorithm consists of an ensemble that uses sliding windows and a soft voting schema while incorporating a drift detection mechanism. Our experimental results demonstrate the superiority of the DynaQ approach over state-of-the-art methods.
The Performance of a Time-Varying Filter Time Under Stable Conditions over Mountainous Terrain
Authors: Lehner Manuela , Rotach Mathias W.
Published: July 2023

Eddy-covariance data from five stations in the Inn Valley, Austria, are analyzed for stable conditions to determine the gap scale that separates turbulent from large-scale, non-turbulent motions. The gap scale is identified from (co)spectra calculated from different variables using both Fourier analysis and multi-resolution flux decomposition. A correlation is found between the gap scale and the mean wind speed and stability parameter z/L that is used to determine a time-varying filter time, whose performance in separating turbulent and non-turbulent motions is compared to the performance of constant filter times between 0.5 and 30 min. The impact of applying different filter times on the turbulence statistics depends on the parameter and location, with a comparatively smaller impact on the variance of the vertical wind component than on the horizontal components and the turbulent fluxes. Results indicate that a time-varying filter time based on a multi-variable fit taking both mean wind speed and stability into account and a constant filter time of 2–3 min perform best in that they remove most of the non-turbulent motions while at the same time capturing most of the turbulence. For the studied sites and conditions, a time-varying filter time does not outperform a well chosen constant filter time because of relatively small variations in the filter time predicted by the correlation with mean flow parameters.