bluuebunny/crossref_metadata_2025_split huggingface dataset:
Analysis of community question‐answering issues via machine learning and deep learning: State‐of‐the‐art review
Authors: Roy Pradeep Kumar , Saumya Sunil , Singh Jyoti Prakash , Banerjee Snehasish , Gutub Adnan 
Published: May 2022

AbstractOver the last couple of decades, community question‐answering sites (CQAs) have been a topic of much academic interest. Scholars have often leveraged traditional machine learning (ML) and deep learning (DL) to explore the ever‐growing volume of content that CQAs engender. To clarify the current state of the CQA literature that has used ML and DL, this paper reports a systematic literature review. The goal is to summarise and synthesise the major themes of CQA research related to (i) questions, (ii) answers and (iii) users. The final review included 133 articles. Dominant research themes include question quality, answer quality, and expert identification. In terms of dataset, some of the most widely studied platforms include Yahoo! Answers, Stack Exchange and Stack Overflow. The scope of most articles was confined to just one platform with few cross‐platform investigations. Articles with ML outnumber those with DL. Nonetheless, the use of DL in CQA research is on an upward trajectory. A number of research directions are proposed.
Rethinking the image feature biases exhibited by deep convolutional neural network models in image recognition
Authors: Dai Dawei , Li Yutang , Wang Yuqi , Bao Huanan , Wang Guoyin 
Published: May 2022

AbstractIn recent years, convolutional neural networks (CNNs) have been applied successfully in many fields. However, these deep neural models are still considered as “black box” for most tasks. One of the fundamental issues underlying this problem is understanding which features are most influential in image recognition tasks and how CNNs process these features. It is widely believed that CNN models combine low‐level features to form complex shapes until the object can be readily classified, however, several recent studies have argued that texture features are more important than other features. In this paper, we assume that the importance of certain features varies depending on specific tasks, that is, specific tasks exhibit feature bias. We designed two classification tasks based on human intuition to train deep neural models to identify the anticipated biases. We designed experiments comprising many tasks to test these biases in the Res Net and Dense Net models. From the results, we conclude that (1) the combined effect of certain features is typically far more influential than any single feature; (2) in different tasks, neural models can perform different biases, that is, we can design a specific task to make a neural model biased towards a specific anticipated feature.
Stream level rank constrained transceiver design in MIMO interference channel networks
Authors: Zhang Yifei , Zhou Xiaotian , Zhang Haixia , Yuan Dongfeng 
Published: May 2022

AbstractAn interference leakage minimisation transceiver design for multiple‐input multiple‐output Interference Channel networks is proposed by making use of the full rank constraint of the desired signal, the low rank constraint and low power constraint of the interference signal. The objective is to suppress interference leakage caused by not only the signal from other users, but also the other streams from the same user. To do so, the transmit precoding matrix and the receive filtering matrix are iteratively optimised through convex optimisation tools at stream level. Furthermore, a Min–Max interference leakage algorithm is also proposed to suppress the maximum interference from user, with the purpose of guaranteeing the fairness among users. Simulation results demonstrate that taking inter‐stream interference into consideration can significantly improve the effectiveness of multiple‐input multiple‐output Interference Channel networks, while the Min–Max method can slightly increase the system capacity under certain conditions. It can be also confirmed that the trade‐off among effectiveness, fairness and robustness exists in the transceiver optimisation of multiple‐input multiple‐output Interference Channel networks.
Impedance modelling and stability assessment for grid‐connected dual‐PWM adjustable speed drives with motor torque oscillations
Authors: Yang Dirui , Jiang Jianguo 
Published: May 2022

AbstractThe grid‐connected dual‐PWM adjustable speed drives (ASDs) modulate the energy of the motor torque oscillation and inject it into the power system, potentially causing low‐frequency oscillation (LFO) in the grid. In this study, considering the motor torque oscillation and harmonic common‐modulation of the both‐side converters, the precise sequence impedance models are derived for dual‐PWM ASDs using the harmonic linearisation method. Based on the derived impedance of dual‐PWM ASD, the torque oscillation, which is equivalent to the time‐varying impedance, causes a series of discontinuities at the torque‐oscillation‐related frequencies on its amplitude‐frequency curve. Moreover, these discontinuous drops make it more likely to intersect with the amplitude‐frequency curve of the grid impedance, which may lead to LFO of the grid. Then, by applying the proposed impedance model and Bode plot, the stability of the grid‐ASD cascade system with motor torque oscillation is assessed. The conclusions of stability analysis demonstrate the exact mechanism that the mechanical system oscillations lead to the grid‐converter cascade system instability through the common‐modulation and coupling of the dual‐PWM ASD. Finally, experimental results on a 3 kW ASD system in the laboratory and measured results on the distribution grid in the Shanghai Yangshan Deepwater Port area verify the correctness and effectiveness of the proposed model and stability assessment.
A new transformerless quadratic buck–boost converter with high‐voltage gain ratio and continuous input/output current port
Authors: Okati Mustafa , Eslami Mahdiyeh , Jafari Shahbazzadeh Mehdi , Shareef Hussain 
Published: May 2022

AbstractA new transformerless quadratic buck–boost converter with a common ground and a high‐voltage gain ratio of D/(1−D)2 is proposed in this study. The output and input currents of the proposed structure are continuous due to the presence of inductive filters in the output and input ports. The continuity of the output current simultaneously reduces the voltage ripple and also the capacitor stress at the output port. With the proposed quadratic structure, a lower total switching device power and a higher voltage gain ratio are attained at the same duty cycle. Due to the advantages of the proposed structure, it can be widely used with renewable energy. The presented model is investigated in terms of steady‐state analysis, continuous conduction mode, small‐signal modelling, and efficiency with parasitic resistance effects. To validate the performance of the proposed converter, experiments are conducted in the laboratory to claim the theoretical waveforms obtained from the piecewise linear electrical circuit simulation (PLECS) simulation.
Robust prequalification process of a distribution system operator considering N‐1 contingency
Authors: Jeong Chang Min , Kim Seung Wan , Park Jung Sung , Yoon Yong Tae , Moon Hee Seung 
Published: May 2022

AbstractA distributed energy resource aggregator (DERA) participates in the wholesale energy market (WEM) on behalf of aggregated distributed renewable energy sources (DRESs). The DERA manages DRESs according to the dispatch signal from the system operator (SO). However, a conventional independent SO that operates the WEM and transmission system does not monitor the distribution system. Therefore, overvoltage or overflow problems can occur during the generation of DRESs in a distribution system in which bids are accepted in the WEM. To address these problems, previous studies proposed the prequalification process. In the process, a distribution SO (DSO), which is responsible for the reliability of the distribution system, reviews DERA's bids before it is submitted to the WEM. However, these studies do not consider the outages of the system components. Therefore, we propose an N‐1 contingency prequalification process (N‐1 PP). The DSO manages the DERA's bid considering both the uncertainties and system states after the reconfiguration in contingency situations. In the proposed scheme, the DERA's bid is reviewed for severe faults and post‐reconfiguration systems. The results indicate that the N‐1 PP is more stable and durable than the prequalification process of previous studies.
Improved power maxima point of photovoltaic system using umbrella optimizing technique under PSCs: An experimental study
Authors: Sharma Amit Kumar , Pachauri Rupendra Kumar , Choudhury Sushabhan , Mahela Om Prakash , Khan Baseem , Gupta Ankur Kumar 
Published: May 2022

AbstractThis paper discusses the umbrella optimizing technique (UOT), a novel approach to track maximum power point (MPP) of a solar photovoltaic (PV) system under partial shading conditions (PSCs).Since PSCs have a direct impact on the power generated by PV modules, many researchers have developed a variety of maximum power point tracking (MPPT) approaches to address this issue. Perturb and Observe (P&O) is a traditional method for tracking the maximum power of a PV module under PSCs. The fundamental issue with this traditional technique is that the algorithm misleads the step size and chases the wrong direction under PSCs to track MPP. The proposed algorithm finds the maximum power peak among several observed peaks caused by partial shading of a PV module. At each instance, the proposed algorithm checks for local or global peaks and adjusts the duty cycle of the inverse SEPIC DC–DC converter accordingly.In experimental study, UOT shows better performance in terms of tracking efficiency, tracking time, output power and output current.It exhibits a power boost of 3.39–4.14% with 9.09–16.66% faster tracking in different PSCs. A comparison of different optimization techniques illustrates that the UOT has higher tracking performance.
Performance evaluation of wireless compressed‐image transmission over discrete Fourier transform‐based orthogonal frequency division multiple access system
Authors: Al‐Ashwal Nagi H. , Al soufy Khaled A. , Al‐Kamali Faisal S. , Swillam Mohamed A. 
Published: May 2022

AbstractOrthogonal frequency division multiple access (OFDMA) has been attracting much attention in the recent generation of wireless communications to meet the required demands arising from the explosive growth of Internet, multimedia and broadband services. Currently, images transmission is one of the main parts of wireless communication. However, an image file transmission requires sending a large amount of data which consumes a huge bandwidth so that the image must be compressed to reduce the amount of information to be transmitted. The aim of this paper is to evaluate the wireless transmission of the compressed image over discrete Fourier transform (DFT)‐based OFDMA DFT‐OFDMA system for different compression methods, different modulation schemes and different subcarriers mapping schemes over three wireless channels including SUI3, vehicular A and uniform. The required minimum signal‐to‐noise ratio (SNR) to recover the transmitted compressed image is determined to evaluate the system performance. For the sake of diversity, nine compression techniques are used in this work. The MATLAB simulator is used to determine the required minimum SNR to recover the transmitted compressed image for each compression method. The results show that the performance of the set partitioning in hierarchical trees three‐dimensional for true colour images (SPIHT‐3D) method is nearly better than that of other compression methods, especially when the QPSK and interleaved system are considered.
Akute Aortendissektion: Ein lebensbedrohlicher Notfall auch in der
neurologischen Notfallmedizin
Authors: Madlener Marie , Onur Oezguer A. , Müller-Ehmsen Jochen , Fink Gereon R. , Burghaus Lothar 
Published: May 2022

ZusammenfassungEine akute Aortendissektion ist selten, aber lebensbedrohlich. Die Symptome
hängen von der Lokalisation und Minderperfusion der nachgeschalteten
Organe oder Extremitäten ab und sind dementsprechend variabel. Es
können neurologische Symptome auftreten, die nicht unmittelbar zur
Diagnosestellung führen und so die notwendige Therapie
verzögern. Die Kenntnis der Frühsymptome und Warnsignale einer
Aortendissektion sind deswegen auch in der neurologischen Notfallversorgung
wichtig, um die Betroffenen schnell zu identifizieren und der Akuttherapie
zuzuführen. Eine Fehldiagnose mit verzögerter Therapieeinleitung
kann die Prognose der Patienten deutlich verschlechtern. Ziel dieser Arbeit ist
es, einen standardisierten Diagnostik- und Therapiealgorithmus bei Verdacht auf
eine akute Aortendissektion in der neurologischen Notfallversorgung zu
etablieren. Eine enge interdisziplinärer Zusammenarbeit ist dabei
essentiell.
Risk of recurrence after endoscopic resection of nonpedunculated T1 colorectal cancer
Authors: Arthursson Victoria , Medic Selma , Syk Ingvar , Rönnow Carl-Fredrik , Thorlacius Henrik 
Published: May 2022

Background The long-term outcome after local excision of T1 colorectal cancer (CRC) remains unknown. The aim of this study was to examine clinical and histopathological risk factors for recurrence in patients with T1 CRC undergoing endoscopic resection.
Methods This was a retrospective registry-based population study on prospectively collected data of all patients with nonpedunculated T1 CRC undergoing only local excision (no salvage surgery) in Sweden between 2009 and 2018. Potential risk factors for recurrence, including age, sex, tumor location, resection margins, lymphovascular, perineural, and submucosal invasion, grade of differentiation, and mucinous subtype, were analyzed using univariate and multivariate cox regression.
Results Median follow-up time was 60 months, and 28 /602 patients (4.7 %) had a recurrence (13 local and 18 distant). Recurrence rate stratified by submucosal invasion was: Sm1 3.5 % (14 /397), Sm2 6.0 % (8 /133), and Sm3 8.3 % (6 /72), with no significant differences. Resection margins, lymphovascular and perineural invasion, grade of differentiation, mucinous subtype, and age were not significant risk factors for recurrence. In contrast, rectal location was found to be a significant risk factor for tumor recurrence in multivariate analysis (hazard ratio 3.08, P = 0.006). The 3– and 5-year disease-free survival was 96.2 % and 91.1 %, respectively, in T1 CRC patients undergoing endoscopic resection.
Conclusion Tumor recurrence was rare (4.7 %) in this large population-based study on recurrence after local excision of nonpedunculated T1 CRC. Rectal location was an independent risk factor for recurrence, suggesting the need for strict surveillance after endoscopic resection of early rectal cancer.
Recent Developments in Transannular Reactions
Authors: Reyes Efraim , Vicario Jose L. , Prieto Liher , Carrillo Luisa , Uria Uxue 
Published: May 2022

AbstractTransannular reactions have shown a remarkable performance for the construction of polycyclic scaffolds from medium- or large-sized cyclic molecules in an unconventional manner. Recent examples of transannular reactions reported from 2011 have been reviewed, emphasizing the excellent performance of this approach when accessing the target compounds. This review also highlights how this methodology provides an alternative approach to other commonly used strategies for the construction of cyclic entities such as cyclization or cycloaddition reactions.1	Introduction2	Transannular Cycloadditions and Electrocyclizations3	Transannular Conjugate Additions4	Transannular 1,2-Addition to Ketones, Imines, Esters, and Amides5	Transannular Reactions via Electrophilic Activation of Olefins6	Transannular Ring-Opening of Epoxides7	Transannular Alkylations of Enolates and Related Species8	Miscellaneous Transannular Reactions9	Concluding Remarks
French Athletics Stakeholders’ Perceptions of Relevance and
Expectations on Injury Prevention
Authors: Edouard Pascal , Ruffault Alexis , Bolling Caroline , Navarro Laurent , Martin Simon , Depiesse Frédéric , Oestergaard Nielsen Rasmus , Verhagen Evert 
Published: May 2022

AbstractThis study aimed to explore how stakeholders in athletics perceive the relevance
of injury prevention, determine their communication preferences, and describe
their expectations regarding injury prevention. We conducted a cross-sectional
study using an exploratory online survey with high-level athletes (i. e.
listed by the French ministry of sports), non-high-level athletes (i. e.
all competitive level except high-level athletes), coaches, and health
professionals licensed with the French Federation of Athletics. The survey was
composed of three parts regarding stakeholder’s characteristics (4
questions), perceived relevance (2 questions), communication preferences and
expectations (3 questions) towards injury prevention. There were 2,864
responders to the survey. Almost all responders found that injury prevention is
relevant (97.7% [95% CI 97.0% to 98.2%]),
without any significant differences in the distribution between
stakeholders’ age, experience and sex (p>0.05). About
three-quarters of the stakeholders preferred to find injury prevention
information on a website (77.4%) without significant differences between
stakeholders’ categories (p>0.05); other media to find
injury prevention information was chosen by less than 50% of responders.
Expectations about injury prevention were mainly explanations, advice and tips
about injury knowledge, management and prevention, based on expert opinion
and/or scientific research. In conclusion, these results confirm that
injury prevention is a challenge shared by numerous stakeholders in athletics,
within France, and provide some orientation on how and what information to
disseminate to these stakeholders.
Hemodynamic Response During Different Set Configurations of a
Moderate-load Resistance Exercise
Authors: Rúa-Alonso María , Mayo Xian , Rial-Vázquez Jessica , Fariñas Juan , Aracama Asier , Iglesias-Soler Eliseo 
Published: May 2022

AbstractWe aimed to determine the cardiovascular responses to two different set
configuration resistance-exercise protocols during a knee extension composed of
40 repetitions with a 15RM load and a total resting time of 360 seconds.
Twenty-four healthy sport science students randomly performed two sessions: (a)
a long set configuration (LSC: 4 sets of 10 repetitions with 2 min rest between
sets), and (b) a short set configuration (SSC: 8 sets of 5 repetitions with 51 s
rest between sets). Before and during exercise, peak and mean values of heart
rate, blood pressure, rate pressure product, and pulse pressure were obtained.
Results showed that both protocols increased the overall peak and mean blood
pressure values (p<0.001). However, LSC entailed a higher peak blood
pressure response at the last set (p=0.041) and an increase throughout
the first 30 repetitions (p≤0.007), whereas SSC kept steady after the
first 20 repetitions. Additionally, LSC caused higher overall peak and mean
heart rate and rate pressure product values (p≤0.003). Summarily,
although both protocols raised blood pressure, SSC reduced the extent of the
pressure and chronotropic response during resistance exercise.
Transition orbital projection approach for excited state tracking
Authors: Du Jiahui , Ma Yixuan , Ma Jing , Li Shuhua , Li Wei 
Published: May 2022

Quantitively comparing the features between different electronic excited states (ESs) is a crucial task in both potential energy surface (PES) studies and excited-state fragmentation approaches. However, it is still a challenging problem in regard to the comparison of complex and highly degenerate systems. Herein, we present a transition orbital projection (TOP) method to calculate the similarity of different ESs based on the configuration vectors of two types of transition densities. It fully considers four significant problems, including phase, hole-particle bijectivity, orbital permutation, and sign of configuration coefficients. TOP state-tracking-based excited-state optimization shows high robustness in several high-symmetric systems, which are difficult to describe with traditional state-tracking approaches. The TOP state-tracking method is expected to be widely applied to the PES of photochemical reactions, ES molecular dynamics to track the diabatic states, and fragmentation approaches for local excitation of large systems.
Machine learning accelerated random structure searching: Application to yttrium superhydrides
Authors: Charraud J.-B. , Geneste G. , Torrent M. , Maillet J.-B. 
Published: May 2022

The search for new superhydrides, promising materials for both hydrogen storage and high temperature superconductivity, made great progress, thanks to atomistic simulations and Crystal Structure Prediction (CSP) algorithms. When they are combined with Density Functional Theory (DFT), these methods are highly reliable and often match a great part of the experimental results. However, systems of increasing complexity (number of atoms and chemical species) become rapidly challenging as the number of minima to explore grows exponentially with the number of degrees of freedom in the simulation cell. An efficient sampling strategy preserving a sustainable computational cost then remains to be found. We propose such a strategy based on an active-learning process where machine learning potentials and DFT simulations are jointly used, opening the way to the discovery of complex structures. As a proof of concept, this method is applied to the exploration of tin crystal structures under various pressures. We showed that the α phase, not included in the learning process, is correctly retrieved, despite its singular nature of bonding. Moreover, all the expected phases are correctly predicted under pressure (20 and 100 GPa), suggesting the high transferability of our approach. The method has then been applied to the search of yttrium superhydrides (YHx) crystal structures under pressure. The YH6 structure of space group Im-3m is successfully retrieved. However, the exploration of more complex systems leads to the appearance of a large number of structures. The selection of the relevant ones to be included in the active learning process is performed through the analysis of atomic environments and the clustering algorithm. Finally, a metric involving a distance based on x-ray spectra is introduced, which guides the structural search toward experimentally relevant structures. The global process (active-learning and new selection methods) is finally considered to explore more complex and unknown YHx phases, unreachable by former CSP algorithms. New complex phases are found, demonstrating the ability of our approach to push back the exponential wall of complexity related to CSP.