bluuebunny/crossref_metadata_2025_split huggingface dataset:
Retracted: Electrically Excited Plasmonic Ultraviolet Light Sources
Authors: Ahmadivand Arash 
Published: May 2021

AbstractThe emission of photons from metal‐insulator‐metal (MIM) nanojunctions through inelastic tunneling of electrically driven electrons is a well‐acknowledged approach to develop miniaturized light sources and ultradense photonic instruments. Generally, the existing research in the optimization of electromigrated tunneling junctions is principally centered on the generation of visible and near‐infrared lights. This study reports on the near‐ultraviolet (NUV, λ ≈ 355 nm) light emission from enhanced tunneling of electrons using aluminum nanoelectrodes. Compared to conventional noble metals, the high electron density and low screening of aluminum enable supporting of pronounced local fields at high energies (i.e, ultraviolet (UV)). As the color of light can be straightforwardly determined by the properties of tunneling structures, the exquisite features of aluminum have empowered the fashioning of tunneling devices that are able to effectively sustain plasmons at short wavelengths and emit UV light with high photon yield. This demonstration is a breakthrough in the generation of high‐energy beams using electrically excited aluminum tunneling platforms, which promisingly accelerates the implementation of electrically tunable and ultradense UV light sources.
Synthetic Image Rendering Solves Annotation Problem in Deep Learning Nanoparticle Segmentation
Authors: Mill Leonid , Wolff David , Gerrits Nele , Philipp Patrick , Kling Lasse , Vollnhals Florian , Ignatenko Andrew , Jaremenko Christian , Huang Yixing , De Castro Olivier , Audinot Jean‐Nicolas , Nelissen Inge , Wirtz Tom , Maier Andreas , Christiansen Silke 
Published: May 2021

AbstractNanoparticles occur in various environments as a consequence of man‐made processes, which raises concerns about their impact on the environment and human health. To allow for proper risk assessment, a precise and statistically relevant analysis of particle characteristics (such as size, shape, and composition) is required that would greatly benefit from automated image analysis procedures. While deep learning shows impressive results in object detection tasks, its applicability is limited by the amount of representative, experimentally collected and manually annotated training data. Here, an elegant, flexible, and versatile method to bypass this costly and tedious data acquisition process is presented. It shows that using a rendering software allows to generate realistic, synthetic training data to train a state‐of‐the art deep neural network. Using this approach, a segmentation accuracy can be derived that is comparable to man‐made annotations for toxicologically relevant metal‐oxide nanoparticle ensembles which were chosen as examples. The presented study paves the way toward the use of deep learning for automated, high‐throughput particle detection in a variety of imaging techniques such as in microscopies and spectroscopies, for a wide range of applications, including the detection of micro‐ and nanoplastic particles in water and tissue samples.
A displacement based approach for the analysis, development, and design of reinforced concrete
Authors: Oehlers Deric John , Visintin Phillip 
Published: May 2021

AbstractPrior to cracking, reinforced concrete (RC) has full‐interaction (FI) behavior, that is there is negligible slip between adjacent elements. After cracking, the regions in the vicinity of a crack exhibit partial‐interaction (PI), that is relative slip between elements occurs. RC development has in the past relied heavily on FI strain based approaches and, consequently, they are in general not able to directly simulate the PI behavior associated with RC. Because of this deficiency in simulation, safe design rules have had to be developed either empirically or semi‐empirically using a vast amount of member level testing to calibrate correction factors which are applied to virtually all aspects of RC design. As a result of this reliance on experimental calibration, the application of these empirical rules is limited by the range of testing that has been undertaken and this creates a feedback loop necessitating the further testing of large scale elements. In this paper, it is shown that a displacement based approach, that is a PI approach, can directly simulate through mechanics the RC PI behaviors and, hence, significantly reduces the need for member testing required to develop design rules. It is shown how only material testing is required in order to quantify the member behavior which, consequently, should both reduce the cost of development and expedite the development of safe design rules for a particular type of fiber concrete.
Marham‐Mafasel decrease joint inflammation and IL‐1β gene expression in rheumatoid arthritis animal model
Authors: Majidi Mohammad , Heidarnejad Fatemeh , Naseri Mohsen , Bonakdar Shahin , Salimi Maryam , Yaraee Roya 
Published: May 2021

AbstractBackgroundRheumatoid arthritis (RA) is a systemic chronic disease with synovial membrane, tendon and articular tissue inflammation. Current treatments of RA have many side effects and are quite expensive. Today, new treatments procedures and inexpensive herbal drugs are developed. Marham‐Mafasel is mainly made out of two traditional herbs (Arnebia euchroma and Martricaria chamomilla).ObjectiveIn this study, for the first time, the impact of Marham‐Mafasel on joint inflammation, histopathological changes and IL‐1β gene expression was evaluated in RA animal model.MethodsThe RA was induced by a single s.c. injection of 0.1 ml Freund's complete adjuvant into the left hind footpad. In continuous, 15 RA male Wistar rats were used in three groups: I: Control; II: Treatment I (Piroxicam) and III: Treatment II (Marham‐Mafasel). The volume of the hind paw was measured every day from 0 to 19 using water changed volume approach. The inflammation in the joint was evaluated using histopathology assay and gene expression of IL‐1β was evaluated with use of Real‐Time PCR.ResultsHind paw swelling of Marham‐Mafasel at days 10th and 19th was reduced compared with the control group (p < 0.05). There was no statistically difference in histological degrading and changes index in three groups (p ≥ 0.05). Relative expression of IL‐1β in Marham‐Mafasel group was significantly decreased compared with other groups.ConclusionThe co‐administration of M. Chamomile and A. euchroma, called Marham‐Mafasel, decreases IL‐1β gene expression that leads to a reduction in inflammation in rheumatoid arthritis (RA) animal model.
Severe chronic idiopathic suppurative lymphoplasmacytic rhinitis in a dog
Authors: Cagnasso Federica , Roncone Silvia , Caccamo Roberta , Peano Andrea , Gianella Paola 
Published: May 2021

AbstractA 5‐year‐old, intact male, Border collie dog was evaluated because of a 10‐day history of right epistaxis. On physical examination, there was no evidence of nasal discharge. A mild depigmentation of the right nasal planum was observed. The infectious panel was negative for Leishmania infantum, Dirofilaria immitis, Angiostrongylus vasorum and tickborne infectious diseases. CT scan of the head, rhinoscopy, histopathologic examination of the right nasal mucosa, fungal culture and PCR sequencing were performed at initial diagnostic workup and follow‐up. A severe and diffuse chronic idiopathic suppurative lymphoplasmacytic rhinitis was diagnosed, along with isolation of Trichosporon ashaii. Because of the unsatisfactory clinical response to marbofloxacin, piroxicam, itraconazole and clotrimazole, oral prednisone was administered. After the initial 2 weeks, prednisone was progressively reduced and discontinued 9 months later. The dog showed complete disappearance of clinical signs, without recurrence after therapy discontinuation.
Convolutional Neural Network to Detect Deep Low-Frequency Tremors from Seismic Waveform Images
Authors: Kaneko Ryosuke , Nagao Hiromichi , Ito Shin-ichi , Obara Kazushige , Tsuruoka Hiroshi 
Published: May 2021

AbstractThe installation of dense seismometer arrays in Japan approximately 20 years ago has led to the discovery of deep low-frequency tremors, which are oscillations clearly different from ordinary earthquakes. As such tremors may be related to large earthquakes, it is an important issue in seismology to investigate tremors that occurred before establishing dense seismometer arrays. We use deep learning aiming to detect evidence of tremors from past seismic data of more than 50 years ago, when seismic waveforms were printed on paper. First, we construct a convolutional neural network (CNN) based on the ResNet architecture to extract tremors from seismic waveform images. Experiments applying the CNN to synthetic images generated according to seismograph paper records show that the trained model can correctly determine the presence of tremors in the seismic waveforms. In addition, the gradient-weighted class activation mapping clearly indicates the tremor location on each image. Thus, the proposed CNN has a strong potential for detecting tremors on numerous paper records, which can enable to deepen the understanding of the relations between tremors and earthquakes.
Wronskian indices and rational conformal field theories
Authors: Das Arpit , Gowdigere Chethan N. , Santara Jagannath 
Published: May 2021

Abstract
The classification scheme for rational conformal field theories, given by the Mathur-Mukhi-Sen (MMS) program, identifies a rational conformal field theory by two numbers: (n, l). n is the number of characters of the rational conformal field theory. The characters form linearly independent solutions to a modular linear differential equation (which is also labelled by (n, l)); the Wronskian index l is a non-negative integer associated to the structure of zeroes of the Wronskian.In this paper, we compute the (n, l) values for three classes of well-known CFTs viz. the WZW CFTs, the Virasoro minimal models and the $$ \mathcal{N} $$
N
= 1 super-Virasoro minimal models. For the latter two, we obtain exact formulae for the Wronskian indices. For WZW CFTs, we get exact formulae for small ranks (upto 2) and all levels and for all ranks and small levels (upto 2) and for the rest we compute using a computer program. We find that any WZW CFT at level 1 has a vanishing Wronskian index as does the $$ {\hat{\mathbf{A}}}_{\mathbf{1}} $$

A
̂

1

CFT at all levels. We find intriguing coincidences such as: (i) for the same level CFTs with $$ {\hat{\mathbf{A}}}_{\mathbf{2}} $$

A
̂

2

and $$ {\hat{\mathbf{G}}}_{\mathbf{2}} $$

G
̂

2

have the same (n, l) values, (ii) for the same level CFTs with $$ {\hat{\mathbf{B}}}_{\mathbf{r}} $$

B
̂

r

and $$ {\hat{\mathbf{D}}}_{\mathbf{r}} $$

D
̂

r

have the same (n, l) values for all r ≥ 5.Classifying all rational conformal field theories for a given (n, l) is one of the aims of the MMS program. We can use our computations to provide partial classifications. For the famous (2, 0) case, our partial classification turns out to be the full classification (achieved by MMS three decades ago). For the (3, 0) case, our partial classification includes two infinite series of CFTs as well as fifteen “discrete” CFTs; except three all others have Kac-Moody symmetry.
Schrödinger Operators with Reverse Hölder Class Potentials in the Dunkl Setting and Their Hardy Spaces
Authors: Hejna Agnieszka 
Published: May 2021

AbstractFor a normalized root systemRin$${\mathbb {R}}^N$$RNand a multiplicity function$$k\ge 0$$k≥0let$${\mathbf {N}}=N+\sum _{\alpha \in R} k(\alpha )$$N=N+∑α∈Rk(α). We denote by$$dw({\mathbf {x}})=\varPi _{\alpha \in R}|\langle {\mathbf {x}},\alpha \rangle |^{k(\alpha )}\,d{\mathbf {x}}$$dw(x)=Πα∈R|⟨x,α⟩|k(α)dxthe associated measure in$${\mathbb {R}}^N$$RN. Let$$L=-\varDelta +V$$L=-Δ+V,$$V\ge 0$$V≥0, be the Dunkl–Schrödinger operator on$${\mathbb {R}}^N$$RN. Assume that there exists$$q >\max (1,\frac{{\mathbf {N}}}{2})$$q>max(1,N2)such thatVbelongs to the reverse Hölder class$$\mathrm{{RH}}^{q}(dw)$$RHq(dw). We prove the Fefferman–Phong inequality forL. As an application, we conclude that the Hardy space$$H^1_{L}$$HL1, which is originally defined by means of the maximal function associated with the semigroup$$e^{-tL}$$e-tL, admits an atomic decomposition with local atoms in the sense of Goldberg, where their localizations are adapted toV.
Behandlungszufriedenheit bei Patienten mit zervikaler Dystonie
Authors: Ip Chi Wang , Schramm Axel , Maisonobe Pascal , Zaragatski Emma , Sycha Thomas 
Published: May 2021

Zusammenfassung
Hintergrund
Obwohl Botulinumtoxin‑A (BoNT-A) von Leitlinien als First-line-Therapie der fokalen zervikalen Dystonie (ZD) empfohlen wird, existieren kaum Langzeitdaten zu den Behandlungsmodalitäten in der klinischen Routine.

Fragestellung
Die vorliegende Subgruppenanalyse untersuchte Patientenzufriedenheit und Symptomkontrolle unter Berücksichtigung von Behandlungsmodalitäten der BoNT-A-Therapie zwischen ZD-Patienten in Deutschland und Österreich (DE/AT, n = 79) und der internationalen Gesamtkohorte (n = 995).

Material und Methoden
INTEREST-IN-CD2 war eine prospektive, multizentrische, longitudinale Beobachtungsstudie, die über 3 Jahre der Therapie erwachsener Patienten mit idiopathischer ZD unter BoNT-A-Behandlung folgte. Primärer Endpunkt war die Patientenzufriedenheit mit der Therapie gemessen an der maximalen Zufriedenheit zwischen 2 Injektionen und der Zufriedenheit zum Zeitpunkt der Reinjektion.

Ergebnisse
Die Therapiezufriedenheit im Wirkmaximum war in beiden Populationen im Studienverlauf stabil und vergleichbar gut (82,3–92,7 % bzw. 85,0–89,9 %). Mit nachlassender BoNT-A-Wirkung zum Ende des Behandlungsintervalls sank die Zufriedenheit ab: Zu Studienbeginn in beiden Gruppen ähnlich (54,2 % vs. 51,4 %), fiel sie numerisch in der der DE/AT-Gruppe bis auf 32,7 % ab, blieb dagegen in der Gesamtpopulation stabil. Die Toronto Western Spasmodic Torticollis Rating Scale(TWSTRS)- und Tsui-Scores zeigten keine wesentlichen Unterschiede zwischen der DE/AT-Gruppe und der Gesamtpopulation.

Schlussfolgerungen
Die Studie bestätigt insgesamt eine gute klinische Symptomkontrolle durch BoNT‑A. Die im Vergleich von DE/AT zur internationalen Gesamtkohorte gesehenen numerischen Unterschiede in der aktuellen Zufriedenheit sind möglicherweise bedingt durch abweichende Anteile BoNT-A-naiver Patienten beider Gruppen, da diese unterschiedliche Zufriedenheit als vorbehandelte Patienten äußerten.
The effect of cryogenic machining of S2 glass fibre composite on the hole form and dimensional tolerances
Authors: Koklu Ugur , Morkavuk Sezer , Featherston Carol , Haddad Malik , Sanders David , Aamir Muhammad , Pimenov Danil Yu , Giasin Khaled 
Published: May 2021

AbstractS2 glass fibre reinforced epoxy composites are widely used in aeronautical applications owing to their excellent strength to weight ratio. Drilling glass fibres can be cumbersome due to their abrasive nature and poor thermal conductivity. Moreover, the use of conventional coolants is not desirable due to contamination and additional costs for cleaning the machine part. An alternative is to use environmentally friendly coolants such as liquid nitrogen (LN2) which have been previously employed in machining metals and composites. The current study investigates the effect of drilling S2 glass fibre composite in a bath of LN2. The study aims to evaluate the effect of spindle speed, feed rate and the presence of cryogenic cooling on the form and dimensional tolerances of the hole (hole size, circularity, cylindricity and perpendicularity). Design of experiments and analysis of variance (ANOVA) were used to determine the contribution of the input parameters on the analysed hole quality metrics. Results indicated that drilling S2 glass fibre in a cryogenic bath increased hole size significantly beyond the nominal hole diameter. The hole circularity and cylindricity were reduced compared to holes drilled under dry condition under all cutting parameters due to enhanced thermal stability during the drilling process. The current study aims to provide the scientific and industrial communities with the necessary knowledge on whether cryogenic bath cooling strategy provides better hole quality output compared to dry drilling and other cryogenic cooling strategies which were previously reported in the open literature.
Toward a global reference database of COI barcodes for marine zooplankton
Authors: Bucklin Ann , Peijnenburg Katja T. C. A. , Kosobokova Ksenia N. , O’Brien Todd D. , Blanco-Bercial Leocadio , Cornils Astrid , Falkenhaug Tone , Hopcroft Russell R. , Hosia Aino , Laakmann Silke , Li Chaolun , Martell Luis , Questel Jennifer M. , Wall-Palmer Deborah , Wang Minxiao , Wiebe Peter H. , Weydmann-Zwolicka Agata 
Published: May 2021

AbstractCharacterization of species diversity of zooplankton is key to understanding, assessing, and predicting the function and future of pelagic ecosystems throughout the global ocean. The marine zooplankton assemblage, including only metazoans, is highly diverse and taxonomically complex, with an estimated ~28,000 species of 41 major taxonomic groups. This review provides a comprehensive summary of DNA sequences for the barcode region of mitochondrial cytochrome oxidase I (COI) for identified specimens. The foundation of this summary is the MetaZooGene Barcode Atlas and Database (MZGdb), a new open-access data and metadata portal that is linked to NCBI GenBank and BOLD data repositories. The MZGdb provides enhanced quality control and tools for assembling COI reference sequence databases that are specific to selected taxonomic groups and/or ocean regions, with associated metadata (e.g., collection georeferencing, verification of species identification, molecular protocols), and tools for statistical analysis, mapping, and visualization. To date, over 150,000 COI sequences for ~ 5600 described species of marine metazoan plankton (including holo- and meroplankton) are available via the MZGdb portal. This review uses the MZGdb as a resource for summaries of COI barcode data and metadata for important taxonomic groups of marine zooplankton and selected regions, including the North Atlantic, Arctic, North Pacific, and Southern Oceans. The MZGdb is designed to provide a foundation for analysis of species diversity of marine zooplankton based on DNA barcoding and metabarcoding for assessment of marine ecosystems and rapid detection of the impacts of climate change.
Exploring the molecular content of CHO exosomes during bioprocessing
Authors: Keysberg Christoph , Hertel Oliver , Schelletter Louise , Busche Tobias , Sochart Chiara , Kalinowski Jörn , Hoffrogge Raimund , Otte Kerstin , Noll Thomas 
Published: May 2021

Abstract
In biopharmaceutical production, Chinese hamster ovary (CHO) cells derived from Cricetulus griseus remain the most commonly used host cell for recombinant protein production, especially antibodies. Over the last decade, in-depth multi-omics characterization of these CHO cells provided data for extensive cell line engineering and corresponding increases in productivity. However, exosomes, extracellular vesicles containing proteins and nucleic acids, are barely researched at all in CHO cells. Exosomes have been proven to be a ubiquitous mediator of intercellular communication and are proposed as new biopharmaceutical format for drug delivery, indicator reflecting host cell condition and anti-apoptotic factor in spent media. Here we provide a brief overview of different separation techniques and subsequently perform a proteome and regulatory, non-coding RNA analysis of exosomes, derived from lab-scale bioreactor cultivations of a CHO-K1 cell line, to lay out reference data for further research in the field. Applying bottom-up orbitrap shotgun proteomics and next-generation small RNA sequencing, we detected 1395 proteins, 144 micro RNA (miRNA), and 914 PIWI-interacting RNA (piRNA) species differentially across the phases of a batch cultivation process. The exosomal proteome and RNA data are compared with other extracellular fractions and cell lysate, yielding several significantly exosome-enriched species.

Key points
• First-time comprehensive protein and miRNA characterization of CHO exosomes.
• Isolation protocol and time point of bioprocess strongly affect quality of extracellular vesicles.
• CHO-derived exosomes also contain numerous piRNA species of yet unknown function.
Evolution of psychosocial burden and psychiatric symptoms in patients with psychiatric disorders during the Covid-19 pandemic
Authors: Belz Michael , Hessmann Philipp , Vogelgsang Jonathan , Schmidt Ulrike , Ruhleder Mirjana , Signerski-Krieger Jörg , Radenbach Katrin , Trost Sarah , Schott Björn H. , Wiltfang Jens , Wolff-Menzler Claus , Bartels Claudia 
Published: May 2021

AbstractThe Covid-19 pandemic highly impacts mental health worldwide. Patients with psychiatric disorders are a vulnerable risk population for worsening of their condition and relapse of symptoms. This study investigates the pandemic-related course of psychosocial burden in patients with pre-existing mental disorders. With the newly developed Goettingen psychosocial Burden and Symptom Inventory (Goe-BSI) psychosocial burden has been traced retrospectively (1) before the pandemic (beginning of 2020), (2) at its beginning under maximum lockdown conditions (March 2020), and (3) for the current state after maximum lockdown conditions (April/May 2020). The Goe-BSI also integrates the Adjustment Disorder New Module (ADNM-20), assesses general psychiatric symptoms, and resilience. A total of 213 patients covering all major psychiatric disorders (ICD-10 F0-F9) were interviewed once in the time range from April, 24th until May 11th, 2020. Across all diagnoses patients exhibited a distinct pattern with an initial rise followed by a decline of psychosocial burden (p < 0.001, partial η2 = 0.09; Bonferroni-corrected pairwise comparisons between all three time-points: p < 0.05 to 0.001). Female gender and high ADNM-20 scores were identified as risk factors for higher levels and an unfavorable course of psychosocial burden over time. Most psychiatric symptoms remained unchanged. Trajectories of psychosocial burden vary in parallel to local lockdown restrictions and seem to reflect an adaptive stress response. For female patients with pre-existing mental disorders and patients with high-stress responses, timely and specific treatment should be scheduled. With the continuation of the pandemic, monitoring of long-term effects is of major importance, especially when long incubation times for the development of mental health issues are considered.
T cell plasticity in renal autoimmune disease
Authors: Soukou Shiwa , Huber Samuel , Krebs Christian F. 
Published: May 2021

AbstractThe presence of immune cells is a morphological hallmark of rapidly progressive glomerulonephritis, a disease group that includes anti-glomerular basement membrane glomerulonephritis, lupus nephritis, and anti-neutrophil cytoplasmic antibody (ANCA)–associated glomerulonephritis. The cellular infiltrates include cells from both the innate and the adaptive immune responses. The latter includes CD4+and CD8+T cells. In the past, CD4+T cell subsets were viewed as terminally differentiated lineages with limited flexibility. However, it is now clear that Th17 cells can in fact have a high degree of plasticity and convert, for example, into pro-inflammatory Th1 cells or anti-inflammatory Tr1 cells. Interestingly, Th17 cells in experimental GN display limited spontaneous plasticity. Here we review the literature of CD4+T cell plasticity focusing on immune-mediated kidney disease. We point out the key findings of the past decade, in particular that targeting pathogenic Th17 cells by anti-CD3 injection can be a tool to modulate the CD4+T cell response. This anti-CD3 treatment can trigger a regulatory phenotype in Th17 cells and transdifferentiation of Th17 cells into immunosuppressive IL-10-expressing Tr1 cells (Tr1exTh17 cells). Thus, targeting Th17 cell plasticity could be envisaged as a new therapeutic approach in patients with glomerulonephritis.