bluuebunny/crossref_metadata_2025_split huggingface dataset:
Erfahrungen älterer, multimorbider Menschen in der COVID-19-Pandemie: eine qualitative Studie
Authors: Boehlen F. H. , Kusch M. K. P. , Reich P. , Wurmbach V. S. , Seidling H. M. , Wild B. 
Published: April 2022

Zusammenfassung
Hintergrund/Ziel der Studie
Die COVID-19-Pandemie und die Maßnahmen zu deren Eindämmung haben das soziale Leben auf ungeahnte Weise verändert. Multimorbide, ältere Menschen, die ein hohes Risiko für schwerwiegende Krankheitsverläufe haben, wurden mit Nachdruck gebeten, Kontakte zu meiden, um das Infektionsrisiko zu mindern. Während dies von einem psychosozialen Standpunkt besorgniserregend wirkt, gibt es auch Hinweise, dass Ältere gelassener mit der Krise umgehen. Ziel der Studie war es, die Haltung von multimorbiden, älteren Menschen in der Pandemie zu beschreiben. Dazu wurden ihr Erleben, ihre sozialen Kontakte und die Erfahrungen mit medizinischer Versorgung ausgewertet.

Material und Methoden
Zu 4 unterschiedlichen Zeitphasen (Juli 2020, September 2020, November 2020, Januar 2021) wurden halbstrukturierte Kurzinterviews zum Erleben der COVID-19-Pandemie mit multimorbiden, älteren Menschen in stationär-internistischer Behandlung geführt. Die Interviews wurden mithilfe der qualitativen Inhaltsanalyse analysiert.

Ergebnisse
Es wurden die Daten von 21 Personen (Alter: 58 bis 88 Jahre) ausgewertet. Es wurde deutlich, dass die COVID-19 Pandemie – auch über die Zeit – sehr unterschiedlich erlebt wurde. Während in Phasen hoher Infektionsraten starke Affekte formuliert wurden, zeigte sich im Verlauf eine stärkere Differenzierung bis zur Verschiebung der Sorgen auf die gesellschaftliche Entwicklung. Das Verhältnis gegenüber Präventionsmaßnahmen oder der ärztlichen Versorgung war von Akzeptanz und Unterstützung geprägt.

Diskussion
Diese Studie zeigt exemplarisch das Erleben älterer, multimorbider Menschen im Verlauf der Pandemie. Diese zeigen in vielen Bereichen ein hohes Maß an Anpassung und Reflexion sowie Akzeptanz der Umstände und sozialen Änderungen.
Wirkungen von Cariprazin auf Negativsymptome und kognitive Störungen bei Schizophrenie
Authors: Sachs Gabriele , Erfurth Andreas 
Published: April 2022

ZusammenfassungNegativsymptome und kognitive Beeinträchtigungen sind ein zentrales Merkmal der Schizophrenie. In den letzten Jahrzehnten hat das Interesse an Negativsymptomen und Kognition zugenommen. Eine moderne klinische Testung mit für diese Symptomatik spezifischen Messmethoden trägt zu einer angemessenen Diagnostik bei. Neuere Forschungen haben gezeigt, dass die Negativsymptomatik und die Kognition das psychosoziale Funktionsniveau, das Funktionieren im realen Leben, stark beeinträchtigen, insbesondere wenn sie primär und anhaltend sind. Trotz der Therapie der Schizophrenie mit Antipsychotika stellen Beeinträchtigungen der Alltagsfunktion immer noch ein großes Behandlungsproblem dar. Die Therapie der Negativsymptome und der Kognition ist zu einem vorrangigen Behandlungsziel bei Schizophrenie geworden. Cariprazin, mit bevorzugter Bindung zum Dopamin D3-Rezeptor, könnte als ein neuer Therapieansatz zur gezielten Behandlung von Negativsymptomen und kognitiver Dysfunktion hilfreich sein.
Striatal dopamine transporter imaging in Parkinson’s disease drug-naïve patients: focus on sexual dysfunction
Authors: Contaldi Elena , Magistrelli Luca , Gallo Silvia , Comi Cristoforo 
Published: April 2022

Abstract
Introduction
Dopamine is involved in sexual behavior, but dopaminergic imaging studies establishing the relationship between nigrostriatal dopaminergic degeneration and sexual dysfunction (SD) in Parkinson’s disease (PD) are lacking.

Methods
We retrospectively analyzed clinical and 123I-FP-CIT SPECT data of 43 drug-naïve PD patients. Based on the sexual function domain of the Non-Motor Symptoms Scale (NMSS), we identified 23 patients with sexual concerns (WSC), reporting a score ≥ 2 due to hyposexuality, and 20 patients without sexual concerns (NoSC). Dopamine transporter (DAT) uptake was assessed through semi-quantitative analysis in the most and least affected putamen (maP, laP), and most and least affected caudate (maC, laC). Total putamen-to-caudate ratio and total striatal binding ratio (tSBR) were also quantified.

Results
WSC and NoSC had similar demographic and disease-related characteristics. WSC displayed lower uptake values in maC (p = 0.016), maP (p = 0.004), laC (p = 0.019), laP (p = 0.009), and tSBR (p = 0.006). Pearson correlation analysis revealed, in the WSC group, moderate inverse correlations between the log-transformed SD scores and the uptake in maP (r =  − 0.473, p = 0.023), maC (r =  − 0.428, p = 0.042), laP (r = -0.437, p = 0.037), and tSBR (r =  − 0.460, p = 0.027). After controlling in a two-way ANCOVA model for age and sex, between-group differences,between WSC and NoSC remained statistically significant only for dopaminergic denervation in maP [F(1,38) = 7.478, p = 0.009)], laP [F(1,38) = 4.684, p = 0.037)], and tSBR [F(1,38) = 5.069, p = 0.030].

Conclusion
To the best of our knowledge, this is the first study reporting the relationship between the severity of SD and specific patterns of nigrostriatal dopaminergic denervation (especially involving both putamina) in newly diagnosed drug-naïve PD patients.
A Tighter Relaxation for the Relative Pose Problem Between Cameras
Authors: Garcia-Salguero Mercedes , Briales Jesus , Gonzalez-Jimenez Javier 
Published: April 2022

AbstractThis paper tackles the resolution of the Relative Pose problem with optimality guarantees by stating it as an optimization problem over the set of essential matrices that minimizes the squared epipolar error. We relax this non-convex problem with its Shor’s relaxation, a convex program that can be solved by off-the-shelf tools. We follow the empirical observation that redundant but independent constraints tighten the relaxation. For that, we leverage equivalent definitions of the set of essential matrices based on the translation vectors between the cameras. Overconstrained characterizations of the set of essential matrices are derived by the combination of these definitions. Through extensive experiments on synthetic and real data, our proposal is empirically proved to remain tight and to require only 7 milliseconds to be solved even for the overconstrained formulations, finding the optimal solution under a wide variety of configurations, including highly noisy data and outliers. The solver cannot certify the solution only in very extreme cases, e.g.noise $$100~{\texttt {pix}} $$

100

pix

and number of pair-wise correspondences under 15. The proposal is thus faster than other overconstrained formulations while being faster than the minimal ones, making it suitable for real-world applications that require optimality certification.
Pathogen disgust sensitivity: Individual differences in pathogen perception or pathogen avoidance?
Authors: van Leeuwen Florian , Jaeger Bastian 
Published: April 2022

AbstractThe emotion disgust motivates the avoidance of pathogens and contaminants. Individuals differ in their tendency to experience disgust and this is referred to as pathogen disgust sensitivity. Yet, it remains unclear which differences in psychological processes are captured by pathogen disgust sensitivity. We tested two hypotheses about how the information processing structure underlying pathogen avoidance might give rise to individual differences in pathogen disgust sensitivity. Participants (n = 998) rated the perceived health of individuals with or without facial blemishes and indicated how comfortable they would feel about having physical contact with them. For participants with high disgust sensitivity, facial blemishes were more indicative of poor health and perceived health was more strongly related to comfort with physical contact. These findings suggest that pathogen disgust sensitivity reflects individual differences in the tendency to interpret stimuli as an infection risk and the weight given to estimated infection risk when deciding who should be approached or avoided.
Sound of guns: digital forensics of gun audio samples meets artificial intelligence
Authors: Raponi Simone , Oligeri Gabriele , Ali Isra Mohamed 
Published: April 2022

AbstractClassifying a weapon based on its muzzle blast is a challenging task that has significant applications in various security and military fields. Most of the existing works rely on ad-hoc deployment of spatially diverse microphone sensors to capture multiple replicas of the same gunshot, which enables accurate detection and identification of the acoustic source. However, carefully controlled setups are difficult to obtain in scenarios such as crime scene forensics, making the aforementioned techniques inapplicable and impractical. We introduce a novel technique that requires zero knowledge about the recording setup and is completely agnostic to the relative positions of both the microphone and shooter. Our solution can identify the category, caliber, and model of the gun, reaching over 90% accuracy on a dataset composed of 3655 samples that are extracted from YouTube videos. Our results demonstrate the effectiveness and efficiency of applying Convolutional Neural Network (CNN) in gunshot classification eliminating the need for an ad-hoc setup while significantly improving the classification performance.
The impact of external auditors on firms’ financial restatements: a review of archival studies and implications for future research
Authors: Velte Patrick 
Published: April 2022

AbstractA systematic literature review includes 69 archival studies on the impact of external auditors on firms’ financial restatements, based on principal agent theory. In more detail, we separate between auditor incentives and auditor competencies to supply a high audit quality. Financial restatements represent one of the most important proxies of audit quality in archival audit research, stressing an increased relevance in empirical research, business practice and regulatory initiatives. The review highlights that many studies on auditor incentives and competencies show inconclusive results on firms’ financial restatements (e.g., fee and rotation studies). But there are indications that especially auditor expertise and audit firm size significantly decrease financial restatements. In discussing potential future research, we emphasize the need for a more detailed analysis of restatements proxies, controls for audit risk, inclusion of (corporate) governance mechanisms as possible moderators or mediators, and sustainability issues of the audit team.
Long-term dog consumption during the Holocene at the Sierra de Atapuerca (Spain): case study of the El Portalón de Cueva Mayor site
Authors: Galindo-Pellicena M.Ángeles , Sala Nohemi , De Gaspar Ignacio , Iriarte Eneko , Blázquez-Orta Raquel , Arsuaga Juan Luis , Carretero José Miguel , García Nuria 
Published: April 2022

AbstractEvidence of dog consumption at the El Portalón de Cueva Mayor site (Sierra de Atapuerca, Spain) from the Holocene is revealed for the first time. The taxonomical and taphonomical studies of the animal bones from the El Portalón site have been carried out. The morphological and metrical analyses indicate that 130 dog bone remains have been identified from the El Portalón site, including from the Neolithic (NISP = 23), Chalcolithic (Pre-Bell Beaker Chalcolithic and Bell Beaker Chalcolithic) (26), Early Bronze Age, Middle Bronze Age and Late Bronze Age (81). The anthropic evidence encompasses cut marks, fresh bone fractures, human tooth marks and fire modifications, thus constituting clear evidence of cynophagy, at least in the Chalcolithic and Bronze Age levels in different contexts (habitat and funerary) from the El Portalón site (Atapuerca, Burgos). Furthermore, the fire alterations on two bone remains from the Neolithic suggest likely dog consumption due to the domestic character of the stratigraphical units where these bone remains were found. The taphonomic evidence suggests that domestic dogs were, at least occasionally, part of the diet of the humans who inhabited the El Portalón site, a fact that might be caused either by food shortages and hunger or as dog meat was considered as a delicacy.
Energy storage for black start services: A review
Authors: Zhao Yanqi , Zhang Tongtong , Sun Li , Zhao Xiaowei , Tong Lige , Wang Li , Ding Jianning , Ding Yulong 
Published: April 2022

AbstractWith the increasing deployment of renewable energy-based power generation plants, the power system is becoming increasingly vulnerable due to the intermittent nature of renewable energy, and a blackout can be the worst scenario. The current auxiliary generators must be upgraded to energy sources with substantially high power and storage capacity, a short response time, good profitability, and minimal environmental concern. Difficulties in the power restoration of renewable energy generators should also be addressed. The different energy storage methods can store and release electrical/thermal/mechanical energy and provide flexibility and stability to the power system. Herein, a review of the use of energy storage methods for black start services is provided, for which little has been discussed in the literature. First, the challenges that impede a stable, environmentally friendly, and cost-effective energy storage-based black start are identified. The energy storage-based black start service may lack supply resilience. Second, the typical energy storage-based black start service, including explanations on its steps and configurations, is introduced. Black start services with different energy storage technologies, including electrochemical, thermal, and electromechanical resources, are compared. Results suggest that hybridization of energy storage technologies should be developed, which mitigates the disadvantages of individual energy storage methods, considering the deployment of energy storage-based black start services.
Application of machine and deep learning techniques to estimate NMR-derived permeability from conventional well logs and artificial 2D feature maps
Authors: Masroor Milad , Emami Niri Mohammad , Rajabi-Ghozloo Amir Hossein , Sharifinasab Mohammad Hassan , Sajjadi Mozhdeh 
Published: April 2022

AbstractNuclear magnetic resonance (NMR) logs can provide information on some critical reservoir characteristics, such as permeability, which are rarely obtainable from conventional well logs. Nevertheless, high cost and operational constraints limit the wide application of NMR logging tools. In this study, a machine learning (ML)-based procedure is developed for fast and accurate estimation of NMR-derived permeability from conventional logs. Following a comprehensive preprocessing on the collected data, the procedure is trained and tested on a well log dataset, with selected conventional logs as inputs, and NMR-derived permeability as target, shallow and deep learning (DL) methods are applied to estimate permeability from selected conventional logs through artificial production of NMR-derived information from the input data. Three supervised ML algorithms are utilized and evaluated, including random forest (RF), group method of data handling (GMDH), and one-dimensional convolutional neural network (1D-CNN). Additionally, a modified two-dimensional CNN (named as Residual 2D-CNN) is developed which is fed by artificial 2D feature maps, generated from available conventional logs. The hyper-parameters of the ML and DL models are optimized using genetic algorithm (GA) to improve their performances. By comparing the output of each model with the permeability derived from NMR log, it is illustrated that nonlinear machine and deep learning techniques are helpful in estimation of NMR permeability. The obtained accuracy of RF, GMDH, 1D-CNN and Res 2D-CNN models, respectively, is 0.90, 0.90, 0.91 and 0.97 which indicate that Res 2D-CNN model is the most efficient method among the other applied techniques. This research also highlights the importance of using generated feature maps for training Res 2D-CNN model, and the essential effect of the applied modifications (i.e., implementing residual and deeper bottleneck architectures) on improving the accuracy of the predicted output and reducing the training time.
SARS-CoV-2 impairs the disassembly of stress granules and promotes ALS-associated amyloid aggregation
Authors: Li Yichen , Lu Shuaiyao , Gu Jinge , Xia Wencheng , Zhang Shengnan , Zhang Shenqing , Wang Yan , Zhang Chong , Sun Yunpeng , Lei Jian , Liu Cong , Su Zhaoming , Yang Juntao , Peng Xiaozhong , Li Dan 
Published: April 2022

AbstractThe nucleocapsid (N) protein of SARS-CoV-2 has been reported to have a high ability of liquid-liquid phase separation, which enables its incorporation into stress granules (SGs) of host cells. However, whether SG invasion by N protein occurs in the scenario of SARS-CoV-2 infection is unknow, neither do we know its consequence. Here, we used SARS-CoV-2 to infect mammalian cells and observed the incorporation of N protein into SGs, which resulted in markedly impaired self-disassembly but stimulated cell cellular clearance of SGs. NMR experiments further showed that N protein binds to the SG-related amyloid proteins via non-specific transient interactions, which not only expedites the phase transition of these proteins to aberrant amyloid aggregation in vitro, but also promotes the aggregation of FUS with ALS-associated P525L mutation in cells. In addition, we found that ACE2 is not necessary for the infection of SARS-CoV-2 to mammalian cells. Our work indicates that SARS-CoV-2 infection can impair the disassembly of host SGs and promote the aggregation of SG-related amyloid proteins, which may lead to an increased risk of neurodegeneration.
Using augmented reality to reduce workload in offshore environments
Authors: Maibach Malte-Jörn , Jones Michael , Walko Christian 
Published: April 2022

AbstractIn the offshore environment helicopters are widely used to transport crew and material from and to maritime wind farms. Due to unforeseeable and often inclement weather situations and challenging tasks these missions put a high workload on the helicopter pilots. In this paper two test campaigns are described which assess the utility of an affordable commercial-off-the-shelf (COTS) head-mounted display (HMD) to reduce workload for commercial maritime operations. The HMD system was implemented within the air vehicle simulator (AVES) at the German Aerospace Center (DLR). Three missions were flown with experienced offshore pilots, performed in a realistic scenario. Independent subjective assessments of both workload and situational awareness were obtained. Results from the studies show that the overall workload for all missions decreased and situational awareness increased when using the HMD. Opinions regarding overall benefit and advantages of the system were found to vary between pilots and missions.
Machines in the Triangle: a Pragmatic Interactive Approach to Information
Authors: Schumann Nadine , Du Yaoli 
Published: April 2022

AbstractA recurrent theme of human–machine interaction is how interaction is defined and what kind of information is relevant for successful communication. In accordance with the theoretical strategies of social cognition and technical philosophy, we propose a pragmatic interactive approach, to understand the concept of information in human–machine interaction. We start with the investigation of interpersonal interaction and human–machine interaction by concerning triangulation as guiding principle. To illustrate human–machine interaction, we will mainly focus on the interactive relationship between human cognitive skills and their technological environments. In triadic interaction, the concept of information cannot only be understood as a syntactic transformation as in the dyadic relationship. We argue that information as pragmatic action patterns can be understood as physically embodied units that is not purely formal but generated in interactive processes and stabilized in use. By exploring how the concept of affordance is applied in psychology, anthropology and human-centered design, we provide a notion of pragmatic information, focusing on users in the development and use of machines or software systems. The triadic interaction of end user, development team, and product leads to a successful human–machine interaction. This theoretical framework enables us to understand how the new socio-technological environments expand our scope of action and how we form, interpret, and learn to deal with patterns of action among ourselves and with machines.
Ethics of Nuclear Energy in Times of Climate Change: Escaping the Collective Action Problem
Authors: Friederich Simon , Boudry Maarten 
Published: April 2022

AbstractIn recent years, there has been an intense public debate about whether and, if so, to what extent investments in nuclear energy should be part of strategies to mitigate climate change. Here, we address this question from an ethical perspective, evaluating different strategies of energy system development in terms of three ethical criteria, which will differentially appeal to proponents of different normative ethical frameworks. Starting from a standard analysis of climate change as arising from an intergenerational collective action problem, we evaluate whether contributions from nuclear energy will, on expectation, increase the likelihood of successfully phasing out fossil fuels in time to avert dangerous global warming. For many socio-economic and geographic contexts, our review of the energy system modeling literature suggests the answer to this question is “yes.” We conclude that, from the point of view of climate change mitigation, investments in nuclear energy as part of a broader energy portfolio will be ethically required to minimize the risks of decarbonization failure, and thus the tail risks of catastrophic global warming. Finally, using a sensitivity analysis, we consider which other aspects of nuclear energy deployment, apart from climate change, have the potential to overturn the ultimate ethical verdict on investments in nuclear energy. Out of several potential considerations (e.g., nuclear waste, accidents, safety), we suggest that its potential interplay — whether beneficial or adverse — with the proliferation of nuclear weapons is the most plausible candidate.
Ultrahigh Density of Atomic CoFe-Electron Synergy in Noncontinuous Carbon Matrix for Highly Efficient Magnetic Wave Adsorption
Authors: Huang Wenhuan , Qiu Qiang , Yang Xiufang , Zuo Shouwei , Bai Jianan , Zhang Huabin , Pei Ke , Che Renchao 
Published: April 2022

AbstractImproving the atom utilization of metals and clarifying the M–M’ interaction is both greatly significant in assembling high-performance ultra-light electromagnetic wave-absorbing materials. Herein, a high-temperature explosion strategy has been successfully applied to assemble the hierarchical porous carbon sponge with Co–Fe decoration via the pyrolysis of the energetic metal organic framework. The as-constructed hybrid displays a superior reflection loss (RL) value of − 57.7 dB and a specific RL value of − 192 dB mg−1 mm−1 at 12.08 GHz with a layer thickness of 2.0 mm (loading of 15 wt%). The off-axis electron hologram characterizes the highly distributed numerous polarized nanodomain variable capacitors, demonstrating the dipole and interfacial polarization along the edges of the nanopores. More importantly, the X-ray absorption spectroscopy analysis verifies the mutual interaction between the metal cluster and carbon matrix and the electronic coupling responsible for the greatly improved electromagnetic wave absorption.