bluuebunny/crossref_metadata_2025 huggingface dataset:
Deep Reinforcement Learning Model for Stock Portfolio Management Based on Data Fusion
Authors: Li Haifeng , Hai Mo
Published: March 2024

Deep reinforcement learning (DRL) can be used to extract deep features that can be incorporated into reinforcement learning systems to enable improved decision-making; DRL can therefore also be used for managing stock portfolios. Traditional methods cannot fully exploit the advantages of DRL because they are generally based on real-time stock quotes, which do not have sufficient features for making comprehensive decisions. In this study, in addition to stock quotes, we introduced stock financial indices as additional stock features. Moreover, we used Markowitz mean-variance theory for determining stock correlation. A three-agent deep reinforcement learning model called Collaborative Multi-agent reinforcement learning-based stock Portfolio management System (CMPS) was designed and trained based on fused data. In CMPS, each agent was implemented with a deep Q-network to obtain the features of time-series stock data, and a self-attention network was used to combine the output of each agent. We added a risk-free asset strategy to CMPS to prevent risks and referred to this model as CMPS-Risk Free (CMPS-RF). We conducted experiments under different market conditions using the stock data of China Shanghai Stock Exchange 50 and compared our model with the state-of-the-art models. The results showed that CMPS could obtain better profits than the compared benchmark models, and CMPS-RF was able to accurately recognize the market risk and achieved the best Sharpe and Calmar ratios. The study findings are expected to aid in the development of an efficient investment-trading strategy.
Detecting aortic valve stenosis based on the non-invasive blood pressure waveform—a proof of concept study
Authors: Kho Eline , Schenk Jimmy , Vlaar Alexander P. J. , Vis Marije M. , Wijnberge Marije , Stam Lotte B. , van Mourik Martijn , Jorstad Harald T. , Hermanns Henning , Westerhof Berend E. , Veelo Denise P. , van der Ster Bjorn J. P.
Published: March 2024

The incidence of aortic valve stenosis (AoS) increases with age, and once diagnosed, symptomatic severe AoS has a yearly mortality rate of 25%. AoS is diagnosed with transthoracic echocardiography (TTE), however, this gold standard is time consuming and operator and acoustic window dependent. As AoS affects the arterial blood pressure waveform, AoS-specific waveform features might serve as a diagnostic tool. Aim of the present study was to develop a novel, non-invasive, AoS detection model based on blood pressures waveforms. This cross-sectional study included patients with AoS undergoing elective transcatheter or surgical aortic valve replacement. AoS was determined using TTE, and patients with no or mild AoS were labelled as patients without AoS, while patients with moderate or severe AoS were labelled as patients with AoS. Non-invasive blood pressure measurements were performed in awake patients. Ten minutes of consecutive data was collected. Several blood pressure-based features were derived, and the median, interquartile range, variance, and the 1st and 9th decile of the change of these features were calculated. The primary outcome was the development of a machine-learning model for AoS detection, investigating multiple classifiers and training on the area under the receiver-operating curve (AUROC). In total, 101 patients with AoS and 48 patients without AoS were included. Patients with AoS showed an increase in left ventricular ejection time (0.02 s, p = 0.001), a delayed maximum upstroke in the systolic phase (0.015 s, p < 0.001), and a delayed maximal systolic pressure (0.03 s, p < 0.001) compared to patients without AoS. With the logistic regression model, a sensitivity of 0.81, specificity of 0.67, and AUROC of 0.79 were found. The majority of the population without AoS was male (85%), whereas in the population with AoS this was evenly distributed (54% males). Age was significantly (5 years, p < 0.001) higher in the population with AoS. In the present study, we developed a novel model able to distinguish no to mild AoS from moderate to severe AoS, based on blood pressure features with high accuracy. Clinical registration number: The study entailing patients with TAVR treatment was registered at ClinicalTrials.gov (NCT03088787, https://clinicaltrials.gov/ct2/show/NCT03088787). The study with elective cardiac surgery patients was registered with the Netherland Trial Register (NL7810, https://trialsearch.who.int/Trial2.aspx?TrialID=NL7810).
Parametric investigation of railway fastenings into the formation and mitigation of short pitch corrugation
Authors: Zhang Pan , Li Shaoguang , Dollevoet Rolf , Li Zili
Published: March 2024

Short pitch corrugation has been a problem for railways worldwide over one century. In this paper, a parametric investigation of fastenings is conducted to understand the corrugation formation mechanism and gain insights into corrugation mitigation. A three-dimensional finite element vehicle–track dynamic interaction model is employed, which considers the coupling between the structural dynamics and the contact mechanics, while the damage mechanism is assumed to be differential wear. Various fastening models with different configurations, boundary conditions, and parameters of stiffness and damping are built up and analysed. These models may represent different service stages of fastenings in the field. Besides, the effect of train speeds on corrugation features is studied. The results indicate: (1) Fastening parameters and modelling play an important role in corrugation formation. (2) The fastening longitudinal constraint to the rail is the major factor that determines the corrugation formation. The fastening vertical and lateral constraints influence corrugation features in terms of spatial distribution and wavelength components. (3) The strengthening of fastening constraints in the longitudinal dimension helps to mitigate corrugation. Meanwhile, the inner fastening constraint in the lateral direction is necessary for corrugation alleviation. (4) The increase in fastening longitudinal stiffness and damping can reduce the vibration amplitudes of longitudinal compression modes and thus reduce the track corrugation propensity. The simulation in this work can well explain the field corrugation in terms of the occurrence possibility and major wavelength components. It can also explain the field data with respect to the small variation between the corrugation wavelength and train speed, which is caused by frequency selection and jump between rail longitudinal compression modes.
Transformer Network-Aided Relative Pose Estimation for Non-cooperative Spacecraft Using Vision Sensor
Authors: Ahmed Jamal , Arshad Awais , Bang Hyochoong , Choi Yoonhyuk
Published: March 2024

The objective of the proposed work is to perform monocular vision-based relative 6-DOF pose estimation of the non-cooperative target spacecraft relative to the chaser satellite in rendezvous operations. In this work, the convolutional neural network (CNN) is replaced by the high-resolution transformer network to predict the feature points of the target satellite. The self-attention mechanism inside the transformer provides the advantage of overcoming the inadequacies of the translation equivariance, 2D neighborhood awareness, and long-range dependencies in CNN. First, the 3D model of the target satellite is reconstructed using the inverse direct linear transform (IDLT) method. Then, the pose estimation pipeline is developed with a learning-based image-processing subsystem and geometric optimization of the pose solver. The image-processing subsystem performs target localization using CNN-based architecture. Then, the key points detection network performs regression to predict 2D key points using the transformer-based network. Afterward, the predicted key points based on their confidence scores are projected onto the corresponding 3D points, and the pose value is computed using the efficient perspective-n-point method. The pose is refined using the non-linear iterative Gauss–Newton method. The proposed architecture is trained and tested on the spacecraft pose estimation dataset and it shows superior accuracy both in translation and rotation values. The architecture has shown robustness against the drastically changing clutter background and light conditions in the space images due to the self-attention mechanism. Moreover, this method consumes less computation resources by using fewer floating-point operations and trainable parameters with low input image resolution.
Dufour and Soret effects on double diffusive Casson fluid flow with the influence of internal heat source
Authors: Vinod Y. , Nagappanavar Suma Nagendrappa , Raghunatha K. R. , Sangamesh
Published: March 2024

This study focuses on the control of the cross-diffusion effects on the thermosolutal Casson fluid stream with an internal heat source. These effects have practical applications in geothermal energy extraction, cooling of electronic devices, petroleum engineering, and polymer processing. With the help of similarity transformations, the governing equations are transformed to nonlinear ordinary differential equations (ODEs). The highly nonlinear differential equations are solved with the help of Bernoulli wavelet numerical scheme, and the outputs are compared with previous literature to validate the findings. The study investigates the forces of various physical parameters on the velocity, temperature, and concentration of the fluid and presents the outcomes in graphical form. In addition, the study provides information on skin friction, heat and mass transfers in tabular format. Overall, the research contributes to a better understanding of the behaviour of non-Newtonian fluids under different thermal and concentration gradients and has practical implications in various industrial processes. Our findings demonstrate the remarkable effectiveness and accessibility of the Bernoulli wavelet method in solving coupled nonlinear ODEs of this nature. The results exhibit outstanding agreement, particularly in engineering applications involving coupled nonlinear ODEs.
Multi-scale invariant solutions in plane Couette flow: a reduced-order model approach
Authors: McCormack Matthew , Cavalieri André V.G. , Hwang Yongyun
Published: March 2024

Plane Couette flow at Reynolds number

$Re=1200$

(based on the channel half-height and half the velocity difference between the top and bottom plates) is investigated with a spatial domain designed to retain only two spanwise integral length scales. In this system, the computation of invariant solutions that are physically representative of the turbulent state has been understood to be challenging. To address this challenge, our approach is to employ an accurate reduced-order model with 600 degrees of freedom (Cavalieri & Nogueira, Phys. Rev. Fluids, vol. 7, 2022, L102601). Using the two-scale energy budget and the temporal cross-correlation of key observables, it is first demonstrated that the model contains most of the multi-scale physical processes identified recently (Doohan et al., J. Fluid Mech., vol. 913, 2021, A8); i.e. the large- and small-scale self-sustaining processes, the energy cascade for turbulent dissipation, and an energy-cascade mediated small-scale production mechanism. Invariant solutions of the reduced-order model are subsequently computed, including 96 equilibria and 43 periodic orbits. It is found that none of the computed equilibrium solutions are able to reproduce an accurate energy balance associated with the multi-scale dynamics of the turbulent state. Incorporation of unsteadiness into invariant solutions is seen to be essential for a sensible description of the multi-scale turbulent dynamics and the related energetics, at least in this type of flow, as periodic orbits with a sufficiently long period are mainly able to describe the complex spatio-temporal dynamics associated with the known multi-scale phenomena.
Indigenous Movements in the Andes in the Twenty-First Century
Authors: Altmann Philipp
Published: March 2024

This essay reviews the following works:

Indianidad evanescente en los Andes de Ecuador. By Víctor Bretón Solo de Zaldívar. Quito: FLACSO Ecuador; Ediciones Universitat de Lleida, 2022. Pp. xxxix + 372. €22.00 paperback, free downloadable e-book. ISBN: 9789978676301.

Indigene Autonomie in Lateinamerika: Zwischen Selbstbestimmung und staatlicher Kontrolle. By Michael Fackler. Bielefeld, Germany: Transcript, 2021. Pp. 322. €60.00 hardcover, €60.00 e-book. ISBN: 9783837657982.

Indigene Resistencia: Der Widerstand der bolivianischen TIPNIS-Bewegung. By Maximilian Held. Bielefeld, Germany: Transcript, 2022. Pp. 276. €45.00 hardcover, free downloadable e-book. ISBN: 9783837663686.

La revolución del arcoiris y su escala de grises: Movimiento indígena del Ecuador. By Stalin Herrera Revelo. Buenos Aires: CLACSO, 2022. Pp. 135. Free downloadable e-book. ISBN: 9789878133799.

Indigenous Civil Society in Latin America: Collective Action in the Digital Age. By Pascal Lupien. Chapel Hill: University of North Carolina Press, 2023. Pp. vii + 284. $29.95 paperback, $99.00 hardcover, $22.99 e-book. ISBN: 9781469672625.

¡Así encendimos la mecha! Treinta años del levantamiento indígena en Ecuador: Una historia permanente. Edited by Floresmilo Simbaña, Adriana Victoria Rodríguez Caguana, and Mateo Martínez Abarca. Quito: Ediciones Abya Yala, 2020. Pp. 220. $15.00 paperback, free downloadable e-book. ISBN: 9789942884107.
ATELLANA ACTORS AND PLAYWRIGHTS IN THE EPIGRAPHIC EVIDENCE
Authors: González Galera Víctor
Published: March 2024

This contribution provides a study of the fabula Atellana from an epigraphic perspective. It brings together the existing inscriptions related to this dramatic genre, explaining the challenges that one faces when trying to identify possible Atellana actors. It also examines the status of Atellana performers and playwrights, contrasting the information provided by literary sources, especially Livy, with the data obtained from inscriptions, which indicate an increasing professionalization of Atellana actors in the first century a.d. Finally, this article poses some questions concerning the development, continuity and geographical diffusion of Atellan comedy in the Imperial era in the light of the epigraphic material and also in comparison with the evidence available for other popular shows, specifically mime and pantomime, which suggests that by the second century a.d. the Atellana was no longer performed on public stages but was rather represented in private settings and studied for its linguistic and rhetorical peculiarities.
From covalent transition states in chemistry to noncovalent in biology: from β- to Φ-value analysis of protein folding
Authors: Fersht Alan R.
Published: March 2024

Solving the mechanism of a chemical reaction requires determining the structures of all the ground states on the pathway and the elusive transition states linking them. 2024 is the centenary of Brønsted’s landmark paper that introduced the β-value and structure-activity studies as the only experimental means to infer the structures of transition states. It involves making systematic small changes in the covalent structure of the reactants and analysing changes in activation and equilibrium-free energies. Protein engineering was introduced for an analogous procedure, Φ-value analysis, to analyse the noncovalent interactions in proteins central to biological chemistry. The methodology was developed first by analysing noncovalent interactions in transition states in enzyme catalysis. The mature procedure was then applied to study transition states in the pathway of protein folding – ‘part (b) of the protein folding problem’. This review describes the development of Φ-value analysis of transition states and compares and contrasts the interpretation of β- and Φ-values and their limitations. Φ-analysis afforded the first description of transition states in protein folding at the level of individual residues. It revealed the nucleation-condensation folding mechanism of protein domains with the transition state as an expanded, distorted native structure, containing little fully formed secondary structure but many weak tertiary interactions. A spectrum of transition states with various degrees of structural polarisation was then uncovered that spanned from nucleation-condensation to the framework mechanism of fully formed secondary structure. Φ-analysis revealed how movement of the expanded transition state on an energy landscape accommodates the transition from framework to nucleation-condensation mechanisms with a malleability of structure as a unifying feature of folding mechanisms. Such movement follows the rubric of analysis of classical covalent chemical mechanisms that began with Brønsted. Φ-values are used to benchmark computer simulation, and Φ and simulation combine to describe folding pathways at atomic resolution.
Linear Theory Analysis and One‐Dimensional Hybrid Simulations of High‐Frequency EMIC Waves in a Dipole Magnetic Field
Authors: Min Kyungguk
Published: March 2024

Narrowband (Δf ≲ 0.1fcp), high‐frequency (0.9fcp ≲ f < fcp) electromagnetic ion cyclotron (EMIC) waves, or HFEMIC waves for short, are a relatively new type of EMIC waves, where fcp is the proton cyclotron frequency. Here, we investigate the instability threshold conditions and the nonlinear evolution of HFEMIC waves at parallel propagation. First, linear theory analysis is extended to a regime relevant to HFEMIC waves (parallel proton beta β‖p < 0.01). The instability threshold follows a similar anisotropy‐β‖p relation and requires a large value of anisotropy (T⊥p/T‖p ≳ 10) for wave growth. As a result of decreasing group velocity, the convective growth rate at a fixed threshold exhibits a similar inverse relation with β‖p. Heavy ions affect the instability only weakly, primarily through the introduction of stop bands. Second, we carry out one‐dimensional hybrid simulations in a parabolic background magnetic field, with initial parameters constrained by observation. Despite the narrow source region (within about ±3° latitude), HFEMIC waves can grow well above the thermal noise level due in large part to a small group velocity of HFEMIC waves. The saturation level is well within the range of observational amplitudes, and the quasilinear process primarily determines the wave evolution. Finally, we demonstrate that the present results compare favorably to the recent statistical results, thereby supporting anisotropic low‐energy protons as free energy source for HFEMIC waves.
Synthesis of Benzene and Phenol From the Irradiation of Benzonitrile: Water Ices by (<10 eV) Electrons: Application to the Planets and Meteorites Surface Chemistry
Authors: Abdoul‐Carime H. , Lathuilière B. , Nedelec P. , Kopyra J.
Published: March 2024

Aromatic compounds are present in the interstellar space and on carbonaceous meteorites where they intriguingly represent the most important constituents along with the water ice. Exposed to the cosmic radiation, more complex species are generated via processes that are still far from being understood. The present study aims at studying the chemistry of benzonitrile in water ice environment when exposed to the ballistic low energy free electrons produced abundantly along the radiation tracks. Here we show that phenol and benzene are synthetized at the electron energy above but also below 6 eV via different routes, which can be selectively activated by tuning the electron energy. The reactivity presented in this work may contribute to a better understanding of the time evolution, via models and simulations, of species present in interstellar space ices and meteorites.
Defense against adversarial attacks: robust and efficient compressed optimized neural networks
Authors: Kraidia Insaf , Ghenai Afifa , Belhaouari Samir Brahim
Published: March 2024

In the ongoing battle against adversarial attacks, adopting a suitable strategy to enhance model efficiency, bolster resistance to adversarial threats, and ensure practical deployment is crucial. To achieve this goal, a novel four-component methodology is introduced. First, introducing a pioneering batch-cumulative approach, the exponential particle swarm optimization (ExPSO) algorithm was developed for meticulous parameter fine-tuning within each batch. A cumulative updating loss function was employed for overall optimization, demonstrating remarkable superiority over traditional optimization techniques. Second, weight compression is applied to streamline the deep neural network (DNN) parameters, boosting the storage efficiency and accelerating inference. It also introduces complexity to deter potential attackers, enhancing model accuracy in adversarial settings. This study compresses the generative pre-trained transformer (GPT) by 65%, saving time and memory without causing performance loss. Compared to state-of-the-art methods, the proposed method achieves the lowest perplexity (14.28), the highest accuracy (93.72%), and an 8 × speedup in the central processing unit. The integration of the preceding two components involves the simultaneous training of multiple versions of the compressed GPT. This training occurs across various compression rates and different segments of a dataset and is ultimately associated with a novel multi-expert architecture. This enhancement significantly fortifies the model's resistance to adversarial attacks by introducing complexity into attackers' attempts to anticipate the model's prediction integration process. Consequently, this leads to a remarkable average performance improvement of 25% across 14 different attack scenarios and various datasets, surpassing the capabilities of current state-of-the-art methods.
Aesculus hippocastanum extract and the main bioactive constituent β-escin as antivirals agents against coronaviruses, including SARS-CoV-2
Authors: Peñaranda Figueredo Freddy Armando , Vicente Josefina , Barquero Andrea Alejandra , Bueno Carlos Alberto
Published: March 2024

Respiratory viruses can cause life-threatening illnesses. The focus of treatment is on supportive therapies and direct antivirals. However, antivirals may cause resistance by exerting selective pressure. Modulating the host response has emerged as a viable therapeutic approach for treating respiratory infections. Additionally, considering the probable future respiratory virus outbreaks emphasizes the need for broad-spectrum therapies to be prepared for the next pandemics. One of the principal bioactive constituents found in the seed extract of Aesculus hippocastanum L. (AH) is β-escin. The clinical therapeutic role of β-escin and AH has been associated with their anti-inflammatory effects. Regarding their mechanism of action, we and others have shown that β-escin and AH affect NF-κB signaling. Furthermore, we have reported the virucidal and broad-spectrum antiviral properties of β-escin and AH against enveloped viruses such as RSV, in vitro and in vivo. In this study, we demonstrate that β-escin and AH have antiviral and virucidal activities against SARS-CoV-2 and CCoV, revealing broad-spectrum antiviral activity against coronaviruses. Likewise, they exhibited NF-κB and cytokine modulating activities in epithelial and macrophage cell lines infected with coronaviruses in vitro. Hence, β-escin and AH are promising broad-spectrum antiviral, immunomodulatory, and virucidal drugs against coronaviruses and respiratory viruses, including SARS-CoV-2.
The fluorochrome-to-protein ratio is crucial for the flow cytometric detection of tissue factor on extracellular vesicles
Authors: Weiss René , Mostageer Marwa , Eichhorn Tanja , Huber Silke , Egger Dominik , Spittler Andreas , Tripisciano Carla , Kasper Cornelia , Weber Viktoria
Published: March 2024

Extracellular vesicles (EVs) have crucial roles in hemostasis and coagulation. They sustain coagulation by exposing phosphatidylserine and initiate clotting by surface expression of tissue factor (TF) under inflammatory conditions. As their relevance as biomarkers of coagulopathy is increasingly recognized, there is a need for the sensitive and reliable detection of TF+ EVs, but their flow cytometric analysis is challenging and has yielded controversial findings for TF expression on EVs in the vascular system. We investigated the effect of different fluorochrome-to-protein (F/P) ratios of anti-TF-fluorochrome conjugates on the flow cytometric detection of TF+ EVs from activated monocytes, mesenchymal stem cells (MSCs), and in COVID-19 plasma. Using a FITC-labeled anti-TF antibody (clone VD8), we show that the percentage of TF+ EVs declined with decreasing F/P ratios. TF was detected on 7.6%, 5.4%, and 1.1% of all EVs derived from activated monocytes at F/P ratios of 7.7:1, 6.6:1, and 5.2:1. A similar decline was observed for EVs from MSCs and for EVs in plasma, whereas the detection of TF on cells remained unaffected by different F/P ratios. We provide clear evidence that next to the antibody clone, the F/P ratio affects the flow cytometric detection of TF+ EVs and should be carefully controlled.
The functional aspects of selective exposure for collective decision-making under social influence
Authors: Oh Poong , Peh Jia Wang , Schauf Andrew
Published: March 2024

Opinion diversity is crucial for collective decision-making, but maintaining it becomes challenging in the face of social influence. We propose selective exposure as an endogenous mechanism that preserves opinion diversity by forming exclusive subgroups of like-minded individuals, or echo chambers, which have been often perceived as an obstacle to achieving collective intelligence. We consider situations where a group of agents collectively make decisions about the true state of nature with the assumption that agents update their opinions by adopting the aggregated opinions of their information sources (i.e., naïve learning), or alternatively, replace incongruent sources with more like-minded others without adjusting their opinions (i.e., selective exposure). Individual opinions at steady states reached under these dynamics are then aggregated to form collective decisions, and their quality is assessed. The results suggest that the diversity-reducing effects of social influence are effectively confined within subgroups formed by selective exposure. More importantly, strong propensities for selective exposure maintain the quality of collective decisions at a level as high as that achieved in the absence of social influence. In contrast, naïve learning allows groups to reach consensuses, which are more accurate than initial individual opinions, but significantly undermines the quality of collective decisions.
Environmental stability of a uranium-plutonium-carbide phase
Authors: Etschmann Barbara , Missen Owen P. , Conradson Steven D. , Mills Stuart , Liu Yang , Brugger Joël
Published: March 2024

A plutonium-rich carbide, (U,Pu)(Al,Fe)3C3, was discovered in a hot particle from the Maralinga nuclear testing site in South Australia. The particle was produced between 1960 and 1963 and has been exposed to ambient conditions since then. The new phase belongs to a group of ternary carbides known as 'derivative-MAX phases'. It formed at high temperature within an explosion cloud via rapid eutectic crystallisation from a complex Al–Fe–U–Pu–C–O melt, and is the major Pu host in this particle. Despite signs of volume expansion due to radiation damage, (U,Pu)(Al,Fe)3C3 remains highly X-ray crystalline 60 years after its formation, with no evidence of Pu leaching from the crystals. Our results highlight that the high-energy conditions of (sub-)critical explosions can create unexpected species. Even micro-particles of a derivative-MAX phase can effectively retain low-valence (metallic-like character) Pu under environmental conditions; the slow physical and chemical weathering of these particles may contribute to the slow release of radionuclides over decades, explaining constant low-levels of radionuclides observed in fauna. This study further suggests that rapidly quenched eutectic melts may be engineered to stabilise actinides in nuclear waste products, removing the need for hydrometallurgical processing.
Impact of COVID-19 national response on primary care utilisation in Singapore: an interrupted time-series analysis
Authors: Tan Vanessa , Ang Gregory , Tan Kelvin Bryan , Chen Cynthia
Published: March 2024

Since the start of the pandemic, many national responses, such as nationwide lockdowns, have been implemented to curb the spread of COVID-19. We aim to assess the impact of Singapore’s national responses on primary care utilisation. We performed an interrupted time series using acute and chronic primary care data of 3 168 578 visits between 1 September 2019 and 31 August 2020 over four periods: before any measures were put in place, during Disease Outbreak Response System Condition (DORSCON) Orange, when Circuit Breaker was instituted, and when Circuit Breaker was lifted. We found significant mean reductions in acute and chronic primary care visits immediately following DORSCON Orange and Circuit Breaker. DORSCON Orange was associated with − 2020 mean daily visits (95% CI − 2890 to − 1150). Circuit Breaker was associated with a further − 2510 mean daily visits (95% CI − 3660 to − 1360). Primary care utilisation for acute visits remained below baseline levels even after the Circuit Breaker was lifted. These significant reductions were observed in both acute and chronic visits, with acute visits experiencing a steeper drop during DORSCON Orange. Understanding the impact of COVID-19 measures on primary care utilisation will be useful for future public health planning.
Research on the impact of digital technology applications on firms' dual innovation in the digital economy context
Authors: Peiyao Qiu , Benrui Chang
Published: March 2024

In recent years, applications of digital technology have gradually become the primary driving force for enterprise innovation. Although the impact of digital technology applications on enterprise innovation has been recognized by the academic community, existing studies have failed to systematically reveal the mechanism of digital technology applications on firms' dual innovation, overlooking the data-driven dynamic characteristics of innovation development in the digital era, and neglecting external conditions such as environmental complexity. Therefore, based on dynamic capability theory and resource orchestration theory, this study adopts a “technology-economy” research paradigm to explore and analyze the impact of digital technology applications on dual innovation. It also analyzes the mediating role of data-driven dynamic capabilities and the moderating effect of environmental complexity. The article conducts an empirical test using microdata of Chinese Shanghai and Shenzhen A-share listed firms from 2010 to 2021.The research results show that digital technology applications positively promote dual innovation of enterprises and exhibit certain heterogeneity. Data-driven dynamic capabilities play a mediating role in the relationship between digital technology applications and dual innovation. The study also tests the moderating effect of environmental complexity and finds that the higher environmental complexity in which the company operates, the stronger the facilitating effect of digital technology applications.
Ceratophyllum demersum the submerged macrophyte from the mining subsidence reservoir Nadrybie Poland as a source of anticancer agents
Authors: Masłyk Maciej , Lenard Tomasz , Olech Marta , Martyna Aleksandra , Poniewozik Małgorzata , Boguszewska-Czubara Anna , Kochanowicz Elżbieta , Czubak Paweł , Kubiński Konrad
Published: March 2024

Aquatic plants are a rich source of health-beneficial substances. One of such organisms is the submerged macrophyte Ceratophyllum demersum, which has not been sufficiently studied in this aspect so far. In this work, we have studied environmental conditions prevailing in a subsidence mining reservoir in Eastern Poland and shown that C. demersum can be harvested for further analysis even from artificial anthropogenic reservoirs. The phytochemical analysis of C. demersum ethanolic extract using LC–MS revealed high content of phenolic compounds (18.50 mg/g) (mainly flavonoids, 16.09 mg/g), including those that have not yet been identified in this plant, namely isorhamnetin, sakuranetin, taxifolin, and eriodictyol. Such rich flavonoid content is most likely responsible for the anticancer activity of the C. demersum extract, which was targeted especially at neoplastic cells of gastrointestinal tract origin. The flow cytometry analysis of treated cells showed an increased percentage of late apoptotic and necrotic cells. The fish embryo toxicity (FET) test showed safety of the extract towards Danio rerio fish up to the concentration of 225 µg/ml. This study has shown that the submerged macrophyte Ceratophyllum demersum can be taken into consideration as a rich source of a set of anticancer agents with chemopreventive potential.
Photogenerated chlorine radicals activate C(sp3)–H bonds of alkylbenzenes to access quinazolinones
Authors: Pan Xin-Yao , Sun Gui-Xia , Huang Fang-Ping , Qin Wen-Jian , Teng Qing-Hu , Wang Kai
Published: March 2024

An Fe-catalyzed visible-light induced condensation of alkylbenzenes with anthranilamides has been developed.
Wind turbine load optimization control and verification based on wind speed estimator with time series broad learning system method
Authors: Fu Deyi , Qin Shiyao , Kong Lingxing , Xue Yang , Gong Lice , Wang Anqing
Published: March 2024

With the rapid development of wind power, the power performance and mechanical load characteristics of wind turbine are simultaneously considered and focused. Normally, wind turbine senses the incoming flow characteristics through the nacelle mounted anemometer, due to the inability to perceive the characteristics of wind speed in advance, the control strategy makes the wind turbine itself to be at a passive state during the operation process. In this paper, a wind turbine mechanical load optimization control strategy based on an accurate wind speed estimator with time series Broad Learning System Method (BLSM) is designed, simulated and also verified. Firstly, the basic control theory of the BLSM and also a mechanical load optimization controller is designed. Then the OpenFAST is used to conduct a full‐life cycle simulation comparison study on mechanical load characteristics of wind turbine before and after the implementation of the optimization control strategy. Finally, a field empirical mechanical load test is performed on the wind turbine, which is configured with BLSM mechanical load optimization control technology. The findings indicate that the implementation of this control strategy can significantly mitigate the ultimate and fatigue loads of wind turbines, particularly the fatigue loads of tower base tilt and roll bending moments, with a reduction rate of approximately 6.2% and 4.3%, respectively.
Microstructure‐ionisation potential relationship analysis for understanding the molecular ionisation difference of natural esters during the impulse discharge via DFT calculation
Authors: Zhang Jingwen , Hao Jian , Ye Wenyu , Zhang Junyi , Liao Ruijin
Published: March 2024

Understanding the impulse discharge behaviour of natural ester (NE) is crucial for its safe application in high‐voltage transformers. The ionisation potential (IP) of triglycerides plays a significant role in the process of molecular ionisation during impulse discharge for NE. The correlation coefficients between molecular size, frontier orbital, electrostatic potential, polarity, and IP were analysed. And the quantitative microstructure‐IP model for triglycerides were built, which revealed that IP is strongly related to the highest occupied molecular orbital (HOMO) energy EHM, as well as the average value of positive electrostatic potential Vp(+), the average value of negative electrostatic potential Vp(−), and the surface area of negative electrostatic potential S(−). The HOMO and negative electrostatic potentials of saturated triglycerides are predominantly linked to the carbonyl O atoms. Conversely, in unsaturated triglycerides, the influence of C=C double bonds on HOMO and negative electrostatic potentials is more pronounced. Therefore, the IP of unsaturated NE with C=C bonds is lower than that of saturated NE, rendering it more susceptible to ionisation under a strong electric field which is unfavourable for impulse breakdown voltage. The structure‐property correlation analysis is valuable for understanding ionisation mechanism during the impulse discharge breakdown of NE at the microscopic level.
Global to multi‐scale local architecture with hardwired CNN for 1‐ms tomato defect detection
Authors: Li Yuan , Hu Tingting , Fuchikami Ryuji , Ikenaga Takeshi
Published: March 2024

A 1 millisecond (1‐ms) vision system that guarantees high efficiency and timely response for tomato defect detection is essential for factory automation. Because of various defect appearances, recently many existing researches focus on CNN based defect detection, but few of them attempt to reach high processing speed to adapt to the factorial assembly line. This paper proposes a global to multi‐scale local based parallel architecture with hardwired CNN for tomato defect detection. This architecture breaks down image‐wise detection into pixel‐wise localization and block‐wise classification. The pixel‐wise localization utilizes tomato‐aware information as constraints for localization performance. The block‐wise classification uses a fully pipelined network structure to obtain the classification result for each block as the pixel stream moves through the network. The classification network has a six‐layer lightweight network structure with quantization for hardwired type implementation on FPGA. The experiment results show that the proposed architecture processes 1000 FPS images with 0.9476 ms/frame delay. And for detection performance, this architecture keeps at 80.18%, only 1.31% lower than ResNet50 based detection system.
An image‐based runway detection method for fixed‐wing aircraft based on deep neural network
Authors: Chen Mingqiang , Hu Yuzhou
Published: March 2024

Visual information is important in final approach and landing phases for an approaching aircraft, it presents supplementary source for navigation system, and provides backup guidance when radio navigation fails, or even supports a complete vision‐based landing. Relative position and attitude can be solved from the runway features in the image. Traditional runway detection methods have high latency and low accuracy, which is unable to satisfy the requirements for a safe landing. This paper proposes a real‐time runway detection model, efficient runway feature extractor (ERFE), based on deep convolutional neural network, generating semantic segmentation and feature lines output. In order to evaluate the model's effectiveness, a benchmark is proposed to calculate the actual error between predicted feature line and ground truth one. A novel runway dataset which is based on pictures from Microsoft Flight Simulator 2020 (FS2020), is also proposed in this paper to train and test the model. The dataset will be released at https://www.kaggle.com/datasets/relufrank/fs2020‐runway‐dataset. ERFE shows excellent performance in FS2020 dataset, it gives satisfactory results even for real runway images excluded from our dataset.
„Nervenchirurgie“ im deutschsprachigen Raum – vom NervClub zum
Zertifikat
Authors: Assmus Hans , Antoniadis Gregor , Heinen Christian , Kneser Ulrich , Bahm Jörg
Published: March 2024

Der Nerv Club ist eine Kollegengemeinschaft im deutschsprachigen Raum, die alle
am peripheren Nerven interessierten Kollegen, ob konservativ oder chirurgisch
tätig, zusammenbringt. Der Artikel fasst die bisherige Geschichte des Nerv Club
und wesentliche Merkmale sowie Aktivitäten zusammen und beleuchtet insbesondere
das erarbeitete Zertifikat zur peripheren Nervenchirurgie. Neben jährlichen
Arbeitstreffen und einem alle zwei Jahre stattfindenden Plexussymposium gibt es
einen wissenschaftlichen Publikationspreis und ein online basiertes Journal, in
dem medizinische Arbeiten zur Nervenchirurgie veröffentlicht werden können.
Die hyperselektive Neurektomie bei spastischen Lähmungen der oberen
Extremität
Authors: Megerle Kai , Gohritz Andreas
Published: March 2024

Als hyperselektive Neurektomie wird eine gezielte Durchtrennung motorischer
Nervenfasern an ihrem Muskeleintritt bezeichnet, um bei spastischen Lähmungen
den gesteigerten Muskeltonus zu reduzieren. Diese Technik hat in den letzten
Jahren speziell an der oberen Extremität eine Renaissance erlebt. Wichtigste
Grundlage ist die exakte Kenntnis der topographschen Anatomie der
Muskelinnervation. Um Ausmaß und Lokalisation der Denervation exakt
kontrollieren zu können, ist eine präzise Darstellung der motorischen Nervenäste
notwendig. Für eine relevante Tonusminderung ist die Durchtrennung von 2/3 bis
4/5 der Nervenäste erforderlich. Diese Arbeit stellt die Entwicklung, Prinzipien
und Anwendung dieser Techniken an der oberen Extremität dar und gibt einen
Überblick über die klinischen Ergebnisse.
Funktionelle Ergebnisse peripherer Nervenverletzungen nach kindlichen
suprakondylären Humerusfrakturen: Vergleich operativer und konservativer
Behandlung
Authors: Deininger Stefanie , Antoniadis Gregor , Pedro Maria Teresa
Published: March 2024

Suprakondyläre Humerusfrakturen sind die häufigsten Ellbogenfrakturen im
Kindesalter bis 10 Jahre. Die Inzidenz von assoziierten Nervenverletzungen
variiert je nach Angaben bis zu 15%. Traumatische und iatrogene Läsionen
betreffen hauptsächlich den N. ulnaris. Die Regeneration peripherer Nerven ist
im Kindesalter vergleichsweise besser. In der vorliegenden Arbeit werden die
funktionellen Ergebnisse nach operativer und konservativer Therapie von
Nervenverletzungen bei Kindern nach suprakondylären Frakturen verglichen und auf
Einflussfaktoren untersucht. Bei dieser retrospektiven Vergleichsstudie wurden
klinische Daten kindlicher Nervenverletzungen nach suprakondylären
Humerusfrakturen, welche in einem Zeitraum von 13 Jahren (2008–2021) behandelt
wurden, ausgewertet. Eingeschlossen wurden Kinder, welche aufgrund ausbleibender
neurologischer/neurophysiologischer Besserung bis 6 Monate nach Trauma operativ
(Neurolysen, autologe Rekonstruktion) behandelt wurden oder bei rückläufiger
Symptomatik im gleichen Zeitraum konservativ nachbeobachtet wurden. Alle
Patienten wurden im Verlauf multidisziplinär behandelt. 48 Patienten (26
weiblich/22 männlich) mit Nervenverletzungen wurden in diese Studie
eingeschlossen. Alle Patienten erhielten in der Vorgeschichte eine operative
Behandlung mit Kirschner-Draht Spickung aufgrund dislozierter Frakturen. Das
mittlere Alter betrug 7±2 Jahre. Die initiale Symptomatik waren hochgradige
motorische Ausfälle bei allen Patienten und sensible Defizite in 87,5% (n=42).
Am häufigsten waren isolierte Läsionen des N. ulnaris (n=24, 50%). Bei 21
Patienten wurde der Nerv neurolysiert und bei 15 zusätzlich nach volar
verlagert. Bei 7 Kindern erfolgte eine autologe Rekonstruktion und 2 erhielten
ein Split Repair. Postoperativ war bei allen Patienten eine signifikante
Verbesserung der motorischen Funktion zu verzeichnen. Trotz vergleichbar
hochgradiger motorischer Ausfälle bei der Erstvorstellung wurden weitere 20
Kinder aufgrund der rückläufigen neurologischen Ausfälle konservativ therapiert.
Sie zeigten vergleichbar gute funktionelle Ergebnisse. In beiden Gruppen waren
keine schwerwiegenden Komplikationen verzeichnet worden. Die durchschnittliche
Nachbeobachtungszeit betrug 377,25±524,87 Tage. Die präsentierte Studie zeigt
exzellente funktionelle Ergebnisse nach der operativen Behandlung kindlicher
Nervenverletzungen ohne schwere Komplikationen. Kinder mit vergleichsweise
hochgradigen Läsionen bei der initialen Vorstellung haben auch ohne Operation
eine gute Chance für eine komplette Spontanremission. Aus diesem Grund sollte
die Operationsindikation bei Kindern sehr überlegt gestellt werden.
Hilft viel viel? Die Dosierungsfrage von Arzneipflanzen in der
Tiermedizin
Authors: Walkenhorst Michael , Ayrle Hannah
Published: March 2024

Im Hinblick auf eine wissenschaftlich sauber fundierte Dosierung von
Arzneipflanzen für die verschiedenen Tierarten gibt es noch viel zu tun. Der
Vergleich veterinärhistorischer mit ethnoveterinärmedizinisch basierter und
humanmedizinisch empfohlener Dosierung zeigt aber eine erfreuliche
Übereinstimmung. Viele Menschen (und hoffentlich auch Tiere) haben wohl mehr
oder weniger unabhängig voneinander schon gute Erfahrungen mit diesen
Dosierungen gemacht. Dabei scheint es nicht besorgniserregend zu sein, dass
Dosierungsangaben in ihrer Spannweite manchmal eine Zehnerpotenz oder (etwas)
mehr umfassen. Im Rahmen vergleichbarer Spannweiten liegen auch die Dosierungen
in Studien, die (beabsichtigte) Effekte von ein und derselben Arzneipflanze
gefunden haben. Die Dosis-Wirkungsbeziehung des Vielstoffgemischs pflanzlicher
Extrakte scheint nicht immer deutlich ausgeprägt zu sein, gleichzeitig gibt es
aber eine große therapeutische Breite. Diese lässt einigen Spielraum für
kreative therapeutische Individualisierung.
Comparison of Two-Dimensional IOTA Simple Rules and Three-Dimensional Ultrasonography in Preoperative Assessment of Adnexal Masses
Authors: Goel Rishu , Singhal Seema , Manchanda Smita , Rajan Saroj , Meena Jyoti , Bharti Juhi
Published: March 2024

Objective Accurate preoperative characterization of adnexal masses is essential for optimal patient management. Two-dimensional ultrasonography (USG) based “International Ovarian Tumuor Analysis Simple Rules (IOTA-SR)” are used primarily in clinical practice. Three-dimensional (3D) USG is an emerging modality. The authors conducted this study to compare the performance of 3D USG with IOTA-SR for preoperative differentiation of benign and malignant adnexal masses.

Methods This prospective observational study recruited 84 patients with adnexal masses undergoing surgical management. IOTA-SR and 3D USG with power Doppler examination were applied to characterize the masses and correlated with histopathology. Logistic regression analysis defined individual 2D and 3D USG parameters' significance in predicting malignancy. The receiver operating characteristic (ROC) curve was plotted for significant variables, and area under the curves (AUCs) with cut-off values were calculated using the Youden index.

Results Out of the 84 adnexal masses, 41 were benign and 43 were malignant. IOTA-SR were conclusive in 88.1% (74/84) cases, with a sensitivity of 83.78% (95% confidence interval [CI]: 67.99–93.81%) and specificity of 89.19% (95% CI: 74.58–96.97%). The sensitivity and specificity of 3D USG with power Doppler were 84% and 88%, respectively, with an AUC of 0.96 (95% CI: 0.92–0.99). Ten cases were inconclusive by the IOTA-SR, and 3D USG could further correctly differentiate four of these cases.

Conclusion The diagnostic performance of both techniques is comparable. With good diagnostic performance and easy applicability, IOTA-SR remain the standard of care. 3D USG, although a more objective assessment, requires further validation and standardization.