bluuebunny/crossref_metadata_2025 huggingface dataset:
Screening for new red blood cell alloantibodies after transfusion in patients with sickle cell disease
Authors: Rankin Alexander , Darbari Deepika , Campbell Andrew , Webb Jennifer , Mo Yunchuan Delores , Jacquot Cyril , Delaney Meghan , Luban Naomi L. C. , Nickel Robert Sheppard
Published: May 2021

Background

Patients with sickle cell disease (SCD) are frequent recipients of red blood cell (RBC) transfusions and are at risk for RBC alloimmunization. RBC alloimmunization is diagnosed by identifying RBC alloantibodies as part of pre‐transfusion testing, but this testing fails to detect alloantibodies that have evanesced. It may be beneficial to screen for new RBC alloantibody development after transfusion before possible antibody evanescence.

Study Design and Methods

Our institution started a new initiative for episodically transfused patients with SCD to obtain at least one antibody screen 2–6 months after transfusion as part of their clinical care. A database was created to prospectively track all transfused patients for 1 year and their post‐transfusion antibody screen results. Patients received prophylactically CEK‐matched RBC units.

Results

During the study year, 138 patients with SCD received a total of 242 RBC transfusions. Patients with a history of an RBC alloantibody (n = 13, 9.4%) had previously received more RBC units than non alloimmunized patients (median 11 vs. 2 RBC units, p = .0002). A total of 337 post‐transfusion antibody screens were obtained in 127 patients (92.0%) with 110 patients (79.7%) having at least one antibody screen 2–6 months post‐transfusion. With this prospective testing, two new RBC alloantibodies (anti‐C and ‐M) were identified in two patients.

Conclusion

It is feasible to test for new RBC alloantibody development in most episodically transfused patients with SCD as part of their routine care. The yield of this screening appears low with CEK matching, but it could still provide important information for individual patients.
Analysis of Radial Roller Bearing Rating Life in Complex Loading Conditions
Authors: Ivannikov Vladimir , Leontiev Mikhail , Degtyarev Sergey , Popov Valeriy
Published: May 2021

An approach for accurate life analysis of radial roller bearings in complex loading conditions is presented. It employs ISO 16281 and accounts not only for external radial loads applied to the inner ring but also for (i) internal bearing clearance, (ii) flexibility of the bearing rings, (iii) rings out-of-roundness, (iv) inertia effects, (v) rolling elements profile, and (vi) rings misalignment. In the last decades, these factors have been becoming more and more important for modern high-performance jet engines, whose shafts are commonly hollow and the housing and the rings thicknesses may be of comparable magnitudes. To obtain the distribution of internal contact forces, an advanced static model of a bearing with deformable, potentially misaligned, rings is developed. The bending deformations of the rings are reproduced superimposing deformed shapes from each of the arising internal contact force applied individually. Bearing rollers are allowed to have non-cylindrical profile, and its geometry is approximated by means of slices each having constant diameter. A robust numerical scheme for solving the resultant set of equations with the aid of the barrier functions method is constructed. To increase even further the accuracy of rating life analysis, distributions of the contact stresses between the roller and the ring surfaces, obtained by solving numerically the problem of non-Hertzian interaction, are added to computations. A numerical benchmark test is presented to demonstrate the applicability of the developed approach. It shows how the aforementioned factors influence the bearing contact forces and its rating life.
Fast SARS-CoV-2 virus detection using disposable cartridge strips and a semiconductor-based biosensor platform
Authors: Xian Minghan , Luo Hao , Xia Xinyi , Fares Chaker , Carey Patrick H. , Chiu Chan-Wen , Ren Fan , Shan Siang-Sin , Liao Yu-Te , Hsu Shu-Min , Esquivel-Upshaw Josephine F. , Chang Chin-Wei , Lin Jenshan , Ghivizzani Steven C. , Pearton Stephen J.
Published: May 2021

Detection of the SARS-CoV-2 spike protein and inactivated virus was achieved using disposable and biofunctionalized functional strips, which can be connected externally to a reusable printed circuit board for signal amplification with an embedded metal–oxide–semiconductor field-effect transistor (MOSFET). A series of chemical reactions was performed to immobilize both a monoclonal antibody and a polyclonal antibody onto the Au-plated electrode used as the sensing surface. An important step in the biofunctionalization, namely, the formation of Au-plated clusters on the sensor strips, was verified by scanning electron microscopy, as well as electrical measurements, to confirm successful binding of thiol groups on this Au surface. The functionalized sensor was externally connected to the gate electrode of the MOSFET, and synchronous pulses were applied to both the sensing strip and the drain contact of the MOSFET. The resulting changes in the dynamics of drain waveforms were converted into analog voltages and digital readouts, which correlate with the concentration of proteins and virus present in the tested solution. A broad range of protein concentrations from 1 fg/ml to 10 μg/ml and virus concentrations from 100 to 2500 PFU/ml were detectable for the sensor functionalized with both antibodies. The results show the potential of this approach for the development of a portable, low-cost, and disposable cartridge sensor system for point-of-care detection of viral diseases.
School-age children benefit from voice gender cue differences for the perception of speech in competing speech
Authors: Nagels Leanne , Gaudrain Etienne , Vickers Deborah , Hendriks Petra , Başkent Deniz
Published: May 2021

Differences in speakers' voice characteristics, such as mean fundamental frequency (F0) and vocal-tract length (VTL), that primarily define speakers' so-called perceived voice gender facilitate the perception of speech in competing speech. Perceiving speech in competing speech is particularly challenging for children, which may relate to their lower sensitivity to differences in voice characteristics than adults. This study investigated the development of the benefit from F0 and VTL differences in school-age children (4–12 years) for separating two competing speakers while tasked with comprehending one of them and also the relationship between this benefit and their corresponding voice discrimination thresholds. Children benefited from differences in F0, VTL, or both cues at all ages tested. This benefit proportionally remained the same across age, although overall accuracy continued to differ from that of adults. Additionally, children's benefit from F0 and VTL differences and their overall accuracy were not related to their discrimination thresholds. Hence, although children's voice discrimination thresholds and speech in competing speech perception abilities develop throughout the school-age years, children already show a benefit from voice gender cue differences early on. Factors other than children's discrimination thresholds seem to relate more closely to their developing speech in competing speech perception abilities.
On training targets for deep learning approaches to clean speech magnitude spectrum estimation
Authors: Nicolson Aaron , Paliwal Kuldip K.
Published: May 2021

Estimation of the clean speech short-time magnitude spectrum (MS) is key for speech enhancement and separation. Moreover, an automatic speech recognition (ASR) system that employs a front-end relies on clean speech MS estimation to remain robust. Training targets for deep learning approaches to clean speech MS estimation fall into three categories: computational auditory scene analysis (CASA), MS, and minimum mean square error (MMSE) estimator training targets. The choice of the training target can have a significant impact on speech enhancement/separation and robust ASR performance. Motivated by this, the training target that produces enhanced/separated speech at the highest quality and intelligibility and that which is best for an ASR front-end is found. Three different deep neural network (DNN) types and two datasets, which include real-world nonstationary and coloured noise sources at multiple signal-to-noise ratio (SNR) levels, were used for evaluation. Ten objective measures were employed, including the word error rate of the Deep Speech ASR system. It is found that training targets that estimate the a priori SNR for MMSE estimators produce the highest objective quality scores. Moreover, it is established that the gain of MMSE estimators and the ideal amplitude mask produce the highest objective intelligibility scores and are most suitable for an ASR front-end.
Influence of seabed on very low frequency sound recorded during passage of merchant ships on the New England shelf
Authors: Knobles D. P. , Wilson Preston S. , Neilsen Tracianne B. , Hodgkiss William S.
Published: May 2021

An examination of the received spectrogram levels of about twenty merchant ship recordings on two vertical line arrays deployed on the New England continental shelf during the Seabed Characterization Experiment 2017 has identified an acoustic feature that can be attributed to the group velocities of modes 1 and 2 being equal at a frequency f=F. The observation of such a feature is a result of βnm(2πF)=∞, where βnm is the waveguide invariant for modes n and m. For the New England Mudpatch, the average value of F is about 24.5 Hz. An effective seabed model is inferred from a feature inversion method that has a deep sediment layer which lies between 190 m and 290 m beneath the seafloor with sound speeds on the order of 1810 m/s. This effective sediment model appears to be consistent with a previous seismic survey on the New England shelf that identified a deep low speed layer about 250 m beneath the water sediment interface.
Using context to train time-domain echolocation click detectors
Authors: Roch Marie A. , Lindeneau Scott , Aurora Gurisht Singh , Frasier Kaitlin E. , Hildebrand John A. , Glotin Hervé , Baumann-Pickering Simone
Published: May 2021

This work demonstrates the effectiveness of using humans in the loop processes for constructing large training sets for machine learning tasks. A corpus of over 57 000 toothed whale echolocation clicks was developed by using a permissive energy-based echolocation detector followed by a machine-assisted quality control process that exploits contextual cues. Subsets of these data were used to train feed forward neural networks that detected over 850 000 echolocation clicks that were validated using the same quality control process. It is shown that this network architecture performs well in a variety of contexts and is evaluated against a withheld data set that was collected nearly five years apart from the development data at a location over 600 km distant. The system was capable of finding echolocation bouts that were missed by human analysts, and the patterns of error in the classifier consist primarily of anthropogenic sources that were not included as counter-training examples. In the absence of such events, typical false positive rates are under ten events per hour even at low thresholds.
Exploring Machine Learning Models Based on Accelerometer Sensor Alone or Combined With Gyroscope to Classify Home-Based Exercises and Physical Behavior in (Pre)sarcopenic Older Adults
Authors: Dedeyne Lenore , Wullems Jorgen A. , Dupont Jolan , Tournoy Jos , Gielen Evelien , Verschueren Sabine
Published: May 2021

Tools for objective monitoring of home-based training and physical behavior (PB) in (pre)sarcopenic older adults are needed. The present study explored two approaches with machine learning models, including accelerometer data either with or without additional gyroscope data (in an inertial measurement unit). Twenty-five community-dwelling (pre)sarcopenic adults mean 80.7 [5.5] years) performed the Otago exercise protocol (OEP) and PB modules (e.g., sitting or walking) while wearing an inertial measurement unit on the lower back (Dynaport MoveMonitor; McRoberts, The Hague, The Netherlands). Machine learning (ML) models for classification were developed by two approaches (top-down and bottom-up approaches) and with two levels of classification: general (no wear, OEP, and PB) and detailed (all subclassifications). Classification output was compared with video recordings. For the bottom-up approach, one ML model was developed. For the top-down approach, data were first classified as no wear, OEP, or PB. Thereafter, OEP and PB were subclassified by one ML model each into subclassification. Only classification of the general classification no wear and the subclassification sitting/lying reached the acceptable performance threshold of 80%. This result was independent of the approach used. Moreover, a gyroscope did not improve performance. Despite the progress in ML techniques and monitors, objective compliance registrations remain challenging.
Primed CRISPR-Cas Adaptation and Impaired Phage Adsorption in Streptococcus mutans
Authors: Mosterd Cas , Moineau Sylvain
Published: May 2021

Bacteria are under the constant threat of viral predation and have therefore developed several defense mechanisms, including CRISPR-Cas systems. While studies on the mode of action of CRISPR-Cas systems have already provided great insights into phage-bacterium interactions, still more information is needed on the biology of these systems.
Epidemiology of Multidrug-Resistant Pseudomonas aeruginosa in the Middle East and North Africa Region
Authors: Al-Orphaly Mahmood , Hadi Hamad Abdel , Eltayeb Faiha Kamaleldin , Al-Hail Hissa , Samuel Bincy Gladson , Sultan Ali A. , Skariah Sini
Published: May 2021

Over the last decades, there has been a dramatic global increase in multidrug-resistant (MDR) pathogens particularly among Gram-negative bacteria (GNB).
Pseudomonas aeruginosa
is responsible for various health care-associated infections, while MDR
P. aeruginosa
causes significant morbidity and mortality. Middle East and North Africa (MENA) represent an unexplored geographical region for the study of drug resistance since many of these countries are at crossroads of high volume of travel, diverse expatriate populations, as well as high antibiotic consumption despite attempts to implement antimicrobial stewardship programs.
High-Surety Isothermal Amplification and Detection of SARS-CoV-2
Authors: Bhadra Sanchita , Riedel Timothy E. , Lakhotia Simren , Tran Nicholas D. , Ellington Andrew D.
Published: May 2021

One of the key approaches to treatment and control of infectious diseases, such as COVID-19, is accurate and rapid diagnostics that is widely deployable in a timely and scalable manner. To achieve this, it is essential to go beyond the traditional gold standard of quantitative PCR (qPCR) that is often faced with difficulties in scaling due to the complexity of infrastructure and human resource requirements.
Prevalence of peripheral neuropathy in pre-diabetes: a systematic review
Authors: Kirthi Varo , Perumbalath Anugraha , Brown Emily , Nevitt Sarah , Petropoulos Ioannis N , Burgess Jamie , Roylance Rebecca , Cuthbertson Daniel J , Jackson Timothy L , Malik Rayaz A , Alam Uazman
Published: May 2021

There is growing evidence of excess peripheral neuropathy in pre-diabetes. We aimed to determine its prevalence, including the impact of diagnostic methodology on prevalence rates, through a systematic review conducted according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. A comprehensive electronic bibliographic search was performed in MEDLINE, EMBASE, PubMed, Web of Science and the Cochrane Central Register of Controlled Trials from inception to June 1, 2020. Two reviewers independently selected studies, extracted data and assessed risk of bias. An evaluation was undertaken by method of neuropathy assessment. After screening 1784 abstracts and reviewing 84 full-text records, 29 studies (9351 participants) were included. There was a wide range of prevalence estimates (2%–77%, IQR: 6%–34%), but the majority of studies (n=21, 72%) reported a prevalence ≥10%. The three highest prevalence estimates of 77% (95% CI: 54% to 100%), 71% (95% CI: 55% to 88%) and 66% (95% CI: 53% to 78%) were reported using plantar thermography, multimodal quantitative sensory testing and nerve conduction tests, respectively. In general, studies evaluating small nerve fiber parameters yielded a higher prevalence of peripheral neuropathy. Due to a variety of study populations and methods of assessing neuropathy, there was marked heterogeneity in the prevalence estimates. Most studies reported a higher prevalence of peripheral neuropathy in pre-diabetes, primarily of a small nerve fiber origin, than would be expected in the background population. Given the marked rise in pre-diabetes, further consideration of targeting screening in this population is required. Development of risk-stratification tools may facilitate earlier interventions.
Bortezomib for anti-NMDAR encephalitis following daclizumab treatment in a patient with multiple sclerosis
Authors: Karunaratne Kushan , Ahrabian Dariush , Monaghan Bernadette , Campion Tom , Yousry Tarek , Lunn Michael P , Zandi Michael S , Howard Robin S , Kullmann Dimitri M , Spillane Jennifer , Walker Matthew , Chataway Jeremy
Published: May 2021

Background

Daclizumab is an anti-CD25 monoclonal antibody developed for the treatment of relapsing remitting multiple sclerosis, which was withdrawn worldwide in March 2018, due to emerging serious immune-mediated systemic andcentral nervous system adverse events. We report a case of anti-N-methyl-D-aspartate receptor (NMDAR) encephalitis occurring 14 weeks after stopping daclizumab, which responded to the proteasome inhibitor bortezomib.

Methods

Following lack of effective clinical response to first line (corticosteroid, plasma exchange, intravenous immunoglobulin) and second line (rituximab) treatments, bortezomib therapy was commenced. The patient received six cycles of bortezomib treatment.

Results

Clinical improvement was noted 4 weeks after the first of six cycles of bortezomib and the patient experienced sustained clinical improvement.

Conclusion

Our case provides further class IV evidence of the use of bortezomib therapy for treatment refractory anti-NMDAR encephalitis.
Hyperbaric oxygen treatment impacts oxidative stress markers in patients with necrotizing soft-tissue infection
Authors: Hedetoft Morten , Jensen Peter Østrup , Moser Claus , Vinkel Julie , Hyldegaard Ole
Published: May 2021

Necrotizing soft-tissue infection (NSTI) is a rare, severe, and fast-progressing bacterial infection associated with a high risk of developing sepsis or septic shock. Increasing evidence indicates that oxidative stress is crucial in the development and progression of sepsis, but its role in NSTI specifically has not been investigated. Some patients with NSTI receive hyperbaric oxygen (HBO2) treatment as the restoration of oxidative stress balance is considered an important mechanism of action, which HBO2 facilitates. However, a gap in knowledge exists regarding the effect of HBO2 treatment on oxidative stress in patients with NSTI. In the present observational study, we aimed to investigate HBO2 treatment effects on known markers of oxidative stress in patients with NSTI. We measured plasma myeloperoxidase (MPO), superoxide dismutase (SOD), heme oxygenase-1 (HO-1) and nitrite+nitrate in 80 patients with NSTI immediately before and after their first HBO2 treatment, and on the following day. We found that HBO2 treatment was associated with a significant increase in MPO and SOD by a median of 3.4 and 8.8 ng/mL, respectively. Moreover, we observed an HBO2 treatment-associated increase in HO-1 in patients presenting with septic shock (n=39) by a median of 301.3 pg/mL. All markers were significantly higher in patients presenting with septic shock compared to patients without shock, and all markers correlated with disease severity. High baseline SOD was associated with 90-day mortality. In conclusion, HBO2 treatment was associated with an increase in MPO and SOD in patients with NSTI, and oxidative stress was more pronounced in patients with septic shock.
Covid-19 Reinfection: A Rapid Systematic Review of Case Reports and Case Series
Authors: Wang Jingzhou , Kaperak Christopher , Sato Toshiro , Sakuraba Atsushi
Published: May 2021

The COVID-19 pandemic has infected millions of people worldwide and many countries have been suffering from a large number of deaths. Acknowledging the ability of SARS-CoV-2 to mutate into distinct strains as an RNA virus and investigating its potential to cause reinfection is important for future health policy guidelines. It was thought that individuals who recovered from COVID-19 generate a robust immune response and develop protective immunity; however, since the first case of documented reinfection of COVID-19 in August 2020, there have been a number of cases with reinfection. Many cases are lacking genomic data of the two infections, and it remains unclear whether they were caused by different strains. In the present study, we undertook a rapid systematic review to identify cases infected with different genetic strains of SARS-CoV-2 confirmed by PCR and viral genome sequencing. A total of 17 cases of genetically confirmed COVID-19 reinfection were found. One immunocompromised patient had mild symptoms with the first infection but developed severe symptoms resulting in death with the second infection. Overall, 68.8% (11/16) had similar severity; 18.8% (3/16) had worse symptoms; and 12.5% (2/16) had milder symptoms with the second episode. Our case series shows that reinfection with different strains is possible, and some cases may experience more severe infections with the second episode. The findings also suggest that COVID-19 may continue to circulate even after achieving herd immunity through natural infection or vaccination, suggesting the need for longer-term transmission mitigation efforts.
Algebraic treatment of the Bateman Hamiltonian
Authors: Fernández Francisco M.
Published: May 2021

We apply the algebraic method to the Bateman Hamiltonian and obtain its natural frequencies and ladder operators from the adjoint or regular matrix representation of that operator. Present analysis shows that the eigenfunctions compatible with the complex eigenvalues obtained earlier by other authors are not square integrable. In addition to this, the ladder operators annihilate an infinite number of such eigenfunctions.
Graph Attention Network with Focal Loss for Seizure Detection on Electroencephalography Signals
Authors: Zhao Yanna , Zhang Gaobo , Dong Changxu , Yuan Qi , Xu Fangzhou , Zheng Yuanjie
Published: May 2021

Automatic seizure detection from electroencephalogram (EEG) plays a vital role in accelerating epilepsy diagnosis. Previous researches on seizure detection mainly focused on extracting time-domain and frequency-domain features from single electrodes, while paying little attention to the positional correlations between different EEG channels of the same subject. Moreover, data imbalance is common in seizure detection scenarios where the duration of nonseizure periods is much longer than the duration of seizures. To cope with the two challenges, a novel seizure detection method based on graph attention network (GAT) is presented. The approach acts on graph-structured data and takes the raw EEG data as input. The positional relationship between different EEG signals is exploited by GAT. The loss function of the GAT model is redefined using the focal loss to tackle data imbalance problem. Experiments are conducted on the CHB-MIT dataset. The accuracy, sensitivity and specificity of the proposed method are 98.89[Formula: see text], 97.10[Formula: see text] and 99.63[Formula: see text], respectively.
A Real-Time Pricing Scheme with Advertisement Competition Based on Multi-Leader–Multi-Follower Game in Smart Community
Authors: Dai Yeming , Qi Yao , Li Lu , Gao Hongwei
Published: May 2021

In this paper, an advertising differential game model is proposed to describe the competition among different power retailers for attracting users in continuous time. After the equilibrium of advertising differential game is obtained, a multi-leader–multi-follower game model is developed to study the real-time pricing scheme in smart community. The power retailers calculate the optimal prices in response to the users’ power consumption and obtain the non-cooperation Nash equilibrium, and then the multi-leader–multi-follower game equilibrium is found. The numerical simulation is performed to discuss the influence of different factors on the payoff of power retailers and users and to verify the rationality of the proposed pricing scheme. The results show that both advertising efficiency and user scale have positive effects on the revenues of the power retailers. Besides, the rise of electricity price has negative effect on users’ utilities, meanwhile it makes the revenues of power retailers increase at first and then decrease. Moreover, power retailers will not transfer advertising costs to the users in the form of incremental electricity price.
Min–Max Scheduling of Batch or Drop-Line Jobs Under Agreeable Release and Processing Times
Authors: Gao Yuan
Published: May 2021

We study the Pareto optimization scheduling on an unbounded parallel-batch machine with jobs having agreeable release dates and processing times for minimizing makespan and maximum cost simultaneously. The jobs considered in this paper are of two types: batch jobs and drop-line jobs. For batch jobs, the completion time of a job is given by the completion time of the batch containing this job. For drop-line jobs, the completion time of a job is given by the starting time of the batch containing this job plus the processing time of this job. For both of batch jobs and drop-line jobs, we present polynomial-time algorithms for finding all Pareto optimal points.
Possible Einstein’s cluster models in embedding class one spacetime
Authors: Singh Ksh. Newton , Rahaman Farook , Laishram Modhuchandra , Sharma Rakesh
Published: May 2021

For the first time, we present Einstein’s cluster model in embedding class one spacetime. This paper shows that for any neutral configurations there is only one Einstein cluster solution in embedding class one. In fact, one can find two solutions where the first solution i.e. [Formula: see text] and [Formula: see text] is an unphysical one as it has zero density profile as well as violates the Pandey–Sharma condition (i.e. not a class one solution). However, the second solution can describe matter distribution representing Einstein’s cluster which is in static and equilibrium as it satisfies the static stability criterion and TOV-equation. The second solution not only satisfies the above conditions, but also satisfies the energy conditions. The equation of state parameter [Formula: see text] is less than unity signifying that it can represent physical matters. Further, we have also shown that the Einstein’s clusters may also exhibit the properties of compact stars.
Numerical semigroups of small and large type
Authors: Singhal Deepesh
Published: May 2021

A numerical semigroup is a sub-semigroup of the natural numbers that has a finite complement. Some of the key properties of a numerical semigroup are its Frobenius number [Formula: see text], genus [Formula: see text] and type [Formula: see text]. It is known that for any numerical semigroup [Formula: see text]. Numerical semigroups with [Formula: see text] are called almost symmetric, we introduce a new property that characterizes them. We give an explicit characterization of numerical semigroups with [Formula: see text]. We show that for a fixed [Formula: see text] the number of numerical semigroups with Frobenius number [Formula: see text] and type [Formula: see text] is eventually constant for large [Formula: see text]. The number of numerical semigroups with genus [Formula: see text] and type [Formula: see text] is also eventually constant for large [Formula: see text].
Emission characteristics of target black fragments in 16O-Emulsion collisions at 3.7AGeV
Authors: Kamel S. , Abdallah N. , Yousef Hesham A. , El-Falaky E.
Published: May 2021

As a function of collision centrality, the multiplicity and angular distributions for the slowest target fragments (black particles) emitted in interactions of 16O ions with emulsion nuclei at 3.7[Formula: see text]A[Formula: see text]GeV were investigated. The multiplicity distribution is unaffected by the projectile’s energy or mass. At different impact parameters, the higher moments of multiplicity distributions of black particles were measured. The calculated values of the scaled variance (variance divided by the mean) show that the emission of slower target fragments at high energies is not a statistically independent process in all cases. At various projectile spectators, the angular distributions of the emitted black particles were investigated. The obtained data were compared to the statistical model’s predictions to describe the process responsible for producing secondary particles.
MULTIFRACTAL DETRENDED FLUCTUATIONS ANALYSIS FOR IBOVESPA ASSETS
Authors: DE ARAUJO FERNANDO HENRIQUE ANTUNES , FERNANDES LEONARDO HENRIQUE SILVA
Published: May 2021

The Efficient Market Hypothesis (EMH) can be considered the central pillar of support of the Modern Economic-Financial Theory. However, in the last few years, the EMH has been strongly contraried due to empirical evidence related to long-memory, fractal dimension and fat-tailed that were critical factors in formulating a theory opposed to EMH called Fractal Market Hypothesis (FMH). The purpose of this paper is to test the weak form of EMH for nine constituent assets of the Ibovespa index based on the Multifractal Detrended Fluctuations Analysis (MF-DFA). Our findings show overall scaling behavior approaching the uncorrelated regime, a lower degree of multifractality, the dominance of high fractal exponents, and a broad probability density function as the source of multifractality. Given this, Brazilian assets satisfied the EMH in the Fama’s sense because the multifractal properties inherent of time series returns for Brazilian assets tend to follow a random walk.
A NEW ANALYTICAL MODELING FOR FRACTAL BLASIUS EQUATION IN MICROGRAVITY SPACE
Authors: WEI CHUNFU
Published: May 2021

In this paper, the fractal derivative is employed to define the fractal Blasius equation in a microgravity space arising in fluid dynamics, and its fractal variational principle is successfully established by the fractal semi-inverse transform method. The approximate analytical solution of the fractal Blasius equation is obtained by the variational iteration method. Our results have theoretical significance and practical application value. The example shows the approximate approach is reliable and accurate.
NON-FICKIAN DIFFUSION IN TIME–SPACE FLUCTUATING DIFFUSIVITY LANDSCAPES: FROM SUPERFAST TO ULTRASLOW
Authors: LIANG YINGJIE , TIAN PEIBO , WANG SHUHONG , XU WEI
Published: May 2021

In this study, the local time and space structural derivative diffusion model is introduced to describe non-Fickian diffusion in heterogeneous media from ultraslow to superfast. Its equivalent heterogeneous diffusion process (HDP) model with time and space-dependent diffusion coefficient is also given. The connection and difference between the proposed model and the existing HDP models are compared. Different types of diffusion processes can be captured by selecting proper structural functions in the structural derivative model, which is determined based on the concentration of tracers, mean squared displacement (MSD) and diffusion coefficient of the heterogeneous media. The dynamics of the free cooling granular gases with constant restitution coefficient and velocity-dependent restitution coefficient is investigated to test the proposed model. The results show that the diffusion law of the granular particles is not uniform for the short and long-time scales, but one uniform diffusion law derived from the proposed model can well fit the data in different time scales. The patterns of the time-dependent diffusion coefficient are also simulated to deeply understand the complicated non-Fickian diffusion in complex system.
AN ERGODIC BSDE RISK REPRESENTATION IN A JUMP-DIFFUSION FRAMEWORK
Authors: GUAMBE CALISTO , MABITSELA LESEDI , KUFAKUNESU RODWELL
Published: May 2021

We consider the representation of forward entropic risk measures using the theory of ergodic backward stochastic differential equations in a jump-diffusion framework. Our paper can be viewed as an extension of the work considered by Chong et al. (2019) in the diffusion case. We also study the behavior of a forward entropic risk measure under jumps when a financial position is held for a longer maturity.
On 2k-Hitchin’s equations and Higgs bundles: A survey
Authors: Cardona S. A. H. , García-Compeán H. , Martínez-Merino A.
Published: May 2021

We study the [Formula: see text]-Hitchin’s equations introduced by Ward from the geometric viewpoint of Higgs bundles. After an introduction on Higgs bundles and [Formula: see text]-Hitchin’s equations, we review some elementary facts on complex geometry and Yang–Mills theory. Then, we study some properties of holomorphic vector bundles and Higgs bundles and we review the Hermite–Yang–Mills equations together with two functionals related to such equations. Using some geometric tools we show that, as far as Higgs bundles are concerned, [Formula: see text]-Hitchin’s equations are reduced to a set of two equations. Finally, we introduce a functional closely related to [Formula: see text]-Hitchin’s equations and we study some of its basic properties.
Cryptocurrencies as Pension Fund Components: Smart Move or Drinking the Kool-Aid?
Authors: Soland Marco , Schueffel Patrick
Published: May 2021

This study investigates whether cryptocurrencies can be considered a viable addition to pension funds. Using the regulatory setting of Switzerland, it is assessed whether adding crypto-components to a standard pension fund portfolio has positive effects on the fund’s risk and return figures. The empirical data supports the notion that cryptocurrency components may well increase the yield of a pension fund portfolio, yet this enhancement of yield comes at slightly higher risk levels. This increase in risk can be mitigated by adding an actively managed crypto-component to the portfolio rather than a passive investment product. The paper contributes to the ongoing debate in the area of financial innovations on the purpose and solidity of cryptocurrencies as an asset class.
k
D-STR: A Method for Spatio-Temporal Data Reduction and Modelling
Authors: Steadman Liam , Griffiths Nathan , Jarvis Stephen , Bell Mark , Helman Shaun , Wallbank Caroline
Published: May 2021

Analysing and learning from spatio-temporal datasets is an important process in many domains, including transportation, healthcare and meteorology. In particular, data collected by sensors in the environment allows us to understand and model the processes acting within the environment. Recently, the volume of spatio-temporal data collected has increased significantly, presenting several challenges for data scientists. Methods are therefore needed to reduce the quantity of data that needs to be processed in order to analyse and learn from spatio-temporal datasets. In this article, we present the

-
Dimensional Spatio-Temporal Reduction
method (

D-STR
) for reducing the quantity of data used to store a dataset whilst enabling multiple types of analysis on the reduced dataset.

D-STR uses hierarchical partitioning to find spatio-temporal regions of similar instances, and models the instances within each region to summarise the dataset. We demonstrate the generality of

D-STR with three datasets exhibiting different spatio-temporal characteristics and present results for a range of data modelling techniques. Finally, we compare

D-STR with other techniques for reducing the volume of spatio-temporal data. Our results demonstrate that

D-STR is effective in reducing spatio-temporal data and generalises to datasets that exhibit different properties.
The Complex Path to Quantum Resistance
Authors: Mashatan Atefeh , Heintzman Douglas
Published: May 2021

There is a new technology on the horizon that will forever change the information security and privacy industry landscape. Quantum computing, together with quantum communication, will have many beneficial applications but will also be capable of breaking many of today's most popular cryptographic techniques that help ensure data protection?in particular, confidentiality and integrity of sensitive information. These techniques are ubiquitously embedded in today's digital fabric and implemented by many industries such as finance, health care, utilities, and the broader information communication technology (ICT) community. It is therefore imperative for ICT executives to prepare for the transition from quantum-vulnerable to quantum-resistant technologies.
Photoelectrochemical Properties of TiO2/Sb2S3 Heterojunction with CuO Nanostructure as Photocathode
Authors: Xiao Mingxing , Pathak Rajesh , Zheng Dongping , Jiang Yuanyuan , Zhang Yingjie , Wei Kaiwen , Wu Fan
Published: May 2021

In this paper, two different nanostructures of CuO seeds layer and CuO nanocones array as photocathode were introduced for TiO2/Sb2S3 heterojunction to study the photoelectrochemical properties. The all-solid FTO/TiO2/Sb2S3/CuO seeds layer/FTO device and FTO/TiO2/Sb2S3/CuO nanocones array/FTO device could realize photoelectric conversion with a small photocurrent and photovoltage, and the photoelectrochemical properties of FTO/TiO2/Sb2S3/CuO nanocones array/FTO is even lower than that of the FTO/TiO2/Sb2S3/CuO seeds layer/FTO device due to the limited contact area between Sb2S3 and CuO nanocones. When the electrolyte I3
−/I− was filled into space between Sb2S3 and CuO seeds (nanocones array) photocathode, the photoelectrochemical performance was significantly improved, especially, the photocurrent is enhanced by two (four) orders of magnitude and the photovoltage is enhanced by two orders of magnitude than the device for both photocathodes without electrolyte. For better understanding the photoelectrochemical mechanism of different CuO nanostructure photocathodes, dynamic characterization of intensity-modulated photocurrent/photovoltage spectroscopy and photoelectrochemical impedance spectroscopy were carried out to study photo-generated electron and hole behaviors. Results showed that charge transfer rate in device with CuO seeds layer photocathode is significantly enhanced by CuO nanocones array photocathode. The better hole transfer also improved the charge separation in Sb2S3 and reduced their recombination rate, which results in the enhanced photocurrent and photovoltage by CuO nanocones array photocathode.
Day-Light Photocatalytic Degradation of Methylene Blue Using Graphene/ZnO Nanocomposite
Authors: Pat Zerrin
Published: May 2021

In this paper, novel graphene/ZnO nanocomposites were produced for day-light photocatalytic degradation of methylene blue (MB). Nanocomposites were prepared as to be ZnO (100 − x)% − x % Graphene nanocomposite (x = 0, 5, 10 and 15). For x = 10 and 15, nanocomposite films are transparent and also have electrical resistance. For day-light photocatalytic experiments, 5 ppm MB were prepared and masses of nanocomposite were selected as m = 0.03 g and m = 0.05 g. ZnO is a photocatalytic material. Our results show that graphene/ZnO nanocomposite is a powerful candidate for the high performance day-light photocatalytic applications. One another important finding is related with graphene concentration. Graphene concentration changed the photocatalytic mechanism of un-doped ZnO. For a nanocomposite of m = 0.03 g, the reaction rates of day-light photodegradation were bigger than that of the nanocomposite of m = 0.05 g for x = 10 and 15. But, the nanocomposite of m = 0.05 g for x = 10 and 15 were reached and passed the lower mass nanocomposite for MB degradation at long duration experiments. Graphene nanocomposites are proper and remarkable materials for the lowest mass day-light photodegradation of MB.
Investigating the Photodetectors and pH Sensors of Two-Dimensional MoS2 with Different Substrates
Authors: Chang Sheng-Po , Chen Tzu-Hsin , Liou Guan-Yuan , Huang Wei-Lun , Lai Wei-Chih , Chang Shoou-Jinn , Chen Jone F.
Published: May 2021

We successfully fabricated MoS2 photodetectors with different layers by sulfurization. It is found that the dark current increases with the number of layers. The three-layer MoS2 photodetector has the largest response, which is 3.23 × 10−6 A/W at 10 V. However, the current of the switching light was less than that of the previous cycle. It was presumed that the lifetime of the light-excited carriers was short, or more carriers would be trapped in the defects every cycle. For MoS2 EGFET pH sensors, the sensitivity and linearity results showed that FSS performed better than on Si substrate with 200 nm SiO2. From the time-dependent response measurement, it was observed that the response of the two-layer MoS2 EGFET pH sensors is very fast and stable, showing good reliability. In the future, MoS2 sensors can be combined in different fields, such as biomedical science, agriculture, and fishery, for sensing applications and real-time monitoring.
[Retracted] Construction of Student Information Management System Based on Data Mining and Clustering Algorithm
Authors: Yin XueHong
Published: May 2021

Data mining is a new technology developed in recent years. Through data mining, people can discover the valuable and potential knowledge hidden behind the data and provide strong support for scientifically making various business decisions. This paper applies data mining technology to the college student information management system, mines student evaluation information data, uses data mining technology to design student evaluation information modules, and digs out the factors that affect student development and the various relationships between these factors. Predictive assessment of knowledge and personalized teaching decision‐making provide the basis. First, the general situation of genetic algorithm and fuzzy genetic algorithm is introduced, and then, an improved genetic fuzzy clustering algorithm is proposed. Compared with traditional clustering algorithm and improved genetic fuzzy clustering algorithm, the effectiveness of the algorithm proposed in this paper is proved. Based on the analysis system development related tools and methods, in response to the needs of the student information management system, a simple student information management system is designed and implemented, which provides a platform and data source for the next application of clustering algorithm for performance analysis. Finally, clustering the students’ scores with a clustering algorithm based on fuzzy genetic algorithm, the experimental results show that this method can better analyze the students’ scores and help relevant teachers and departments make decisions.
Effect of Biowaste on the High‐ and Low‐Temperature Rheological Properties of Asphalt Binders
Authors: Wang Xuancang , Guo Yuchen , Ji Guanyu , Zhang Yi , Zhao Jing , Su Hao
Published: May 2021

The growth of aquaculture has increased the production of oysters. However, the increased oyster shell volume has created serious environmental and recycling problems for the society. In order to study the sustainable utilization of waste oyster shells, asphalt binder of waste oyster shell powder was prepared by using modified asphalt material with waste oyster shells. The microstructure of oyster shell powder was analyzed by scanning electron microscopy experiments. The chemical composition of the asphalt binder was observed by Fourier transform infrared spectroscopy tests. The physical properties of the asphalt binder, including softness, high‐temperature performance, and plastic deformation capacity, were initially evaluated through three indicators’ tests on asphalt. A preliminary performance evaluation of the asphalt binder was performed. The high‐temperature stability of asphalt binders was evaluated using dynamic shear rheometry. The rutting resistance of the material was evaluated by temperature sweep tests, and the shear deformation resistance of the material was evaluated by frequency sweep tests. Multiple stress creep recovery tests determine the material’s ability to resist permanent deformation. The low‐temperature rheological properties were evaluated by bending beam rheology tests. The study found that the waste oyster shell powder is a biomass with a porous irregular petal shape. No new characteristic absorption peaks are formed by mixing with asphalt. And, it can improve the viscosity, thermal stability, and temperature‐sensitive properties of the material. It significantly improved the high‐temperature rheological performance, rutting coefficient, and recovery elasticity of the material. However, it has little effect on low‐temperature rheological performance. This study provides a solid foundation for the effective use of biowaste in engineering materials.
Spontaneous Smoking Cessation in Parents
Authors: Nabi-Burza Emara , Wasserman Richard , Drehmer Jeremy E. , Walters Bethany Hipple , Luo Mandy , Ossip Deborah , Winickoff Jonathan P. , Mohamed Haniki
Published: May 2021

Purpose. To determine the percentage of parents who report quitting spontaneously and examine the factors associated with these quits. Methods. As part of a cluster randomized control trial addressing parental smoking in a pediatric outpatient setting, 12-month follow-up survey data were collected from parents who had self-identified as smokers when exiting from 10 control practices. Parents were considered to have made a spontaneous quit if they reported not smoking a cigarette, even a puff, in the last 7 days and chose the statement “I did not plan the quit in advance; I just did it” when describing how their quit attempt started. Results. Of the 981 smoking parents enrolled at baseline, 710 (72%) completed the 12-month follow-up. Of these, 123 (17%) reported quitting, of whom 50 (41%) reported quitting spontaneously. In multivariable analysis, parents who reported smoking on some days vs. every day (OR 3.06 (95% CI 1.42, 6.62)) and that nobody had smoked in their home/car vs. someone had smoked in these settings in the past 3 months (OR 2.19 (95% CI 1.06, 4.54)) were more likely to quit spontaneously. Conclusions. This study shows that, of parents who quit smoking, a substantial percentage report quitting spontaneously and that intermittent smoking and smoke-free home/car policies are associated with reports of quitting spontaneously. Promoting smoke-free home/car policies, especially when parents are not willing to make a plan to quit smoking, might increase the likelihood that parents decide to quit without advance planning. Pediatric healthcare providers are uniquely positioned to use the child’s visit to motivate parents to quit smoking and eliminate their child’s exposure to tobacco smoke, regardless of the frequency of smoking or a readiness to plan a quit attempt. Clinical Trial Registration. This trial is registered with NCT01882348.