bluuebunny/crossref_metadata_2025 huggingface dataset:
Molecular Evolution of CatSper in Mammals and Function of Sperm Hyperactivation in Gray Short-Tailed Opossum
Authors: Hwang Jae Yeon , Maziarz Jamie , Wagner Günter P. , Chung Jean-Ju
Published: April 2021

Males have evolved species-specifical sperm morphology and swimming patterns to adapt to different fertilization environments. In eutherians, only a small fraction of the sperm overcome the diverse obstacles in the female reproductive tract and successfully migrate to the fertilizing site. Sperm arriving at the fertilizing site show hyperactivated motility, a unique motility pattern displaying asymmetric beating of sperm flagella with increased amplitude. This motility change is triggered by Ca2+ influx through the sperm-specific ion channel, CatSper. However, the current understanding of the CatSper function and its molecular regulation is limited in eutherians. Here, we report molecular evolution and conservation of the CatSper channel in the genome throughout eutherians and marsupials. Sequence analyses reveal that CatSper proteins are slowly evolved in marsupials. Using an American marsupial, gray short-tailed opossum (Monodelphis domestica), we demonstrate the expression of CatSper in testes and its function in hyperactivation and unpairing of sperm. We demonstrate that a conserved IQ-like motif in CatSperζ is required for CatSperζ interaction with the pH-tuned Ca2+ sensor, EFCAB9, for regulating CatSper activity. Recombinant opossum EFCAB9 can interact with mouse CatSperζ despite high sequence divergence of CatSperζ among CatSper subunits in therians. Our finding suggests that molecular characteristics and functions of CatSper are evolutionarily conserved in gray short-tailed opossum, unraveling the significance of sperm hyperactivation and fertilization in marsupials for the first time.
Enhancing a Natural Killer: Modification of NK Cells for Cancer Immunotherapy
Authors: Islam Rasa , Pupovac Aleta , Evtimov Vera , Boyd Nicholas , Shu Runzhe , Boyd Richard , Trounson Alan
Published: April 2021

Natural killer (NK) cells are potent innate immune system effector lymphocytes armed with multiple mechanisms for killing cancer cells. Given the dynamic roles of NK cells in tumor surveillance, they are fast becoming a next-generation tool for adoptive immunotherapy. Many strategies are being employed to increase their number and improve their ability to overcome cancer resistance and the immunosuppressive tumor microenvironment. These include the use of cytokines and synthetic compounds to bolster propagation and killing capacity, targeting immune-function checkpoints, addition of chimeric antigen receptors (CARs) to provide cancer specificity and genetic ablation of inhibitory molecules. The next generation of NK cell products will ideally be readily available as an “off-the-shelf” product and stem cell derived to enable potentially unlimited supply. However, several considerations regarding NK cell source, genetic modification and scale up first need addressing. Understanding NK cell biology and interaction within specific tumor contexts will help identify necessary NK cell modifications and relevant choice of NK cell source. Further enhancement of manufacturing processes will allow for off-the-shelf NK cell immunotherapies to become key components of multifaceted therapeutic strategies for cancer.
Three-Dimensional Finite Element Analysis of the Veneer—Framework Thickness in an All-Ceramic Implant Supported Fixed Partial Denture
Authors: Kalluri Lohitha , Seale Bernard , Satpathy Megha , Esquivel-Upshaw Josephine F. , Duan Yuanyuan
Published: April 2021

This study was performed as an adjunct to an existing clinical study to validate the effect of veneer: framework thickness ratio on stress distribution in an implant-supported all-ceramic fixed partial denture. Two commercially available titanium dental implants with corresponding customized abutments and a patient-retrieved all-ceramic fixed partial denture were scanned using a high-resolution micro-CT scanner. Reconstructed 3D objects, along with a simulated bone surface, were incorporated into a non-manifold assembly and meshed simultaneously using Simpleware software (Synopsys Simpleware ScanIP Version P-2019.09; Mountain View, CA). Three such volume meshes (Model A, Model B, Model C) corresponding to veneer: framework thickness ratios of 3:1, 1:1, and 1:3 respectively were created, and exported to a finite element analysis software (ABAQUS). An axial load of 110 N was applied uniformly on the occlusal surfaces to calculate the static stresses and contour plots were generated in the post-processing module. From the data obtained, we observed optimum stress distribution in Model B. Also, the tensile stresses were concentrated in the posterior connector region of the prosthesis in all three models tested. Within the limitations of this study, we can conclude that equal thickness of veneer and framework layers would aid in better stress distribution.
Two Advanced Models of the Function of MRT Public Transportation in Taipei
Authors: Chen You-Shyang , Lin Chien-Ku , Chen Su-Fen , Chen Shang-Hung
Published: April 2021

Tour traffic prediction is very important in determining the capacity of public transportation and planning new transportation devices, allowing them to be built in accordance with people’s basic needs. From a review of a limited number of studies, the common methods for forecasting tour traffic demand appear to be regression analysis, econometric modeling, time-series modeling, artificial neural networks, and gray theory. In this study, a two-step procedure is used to build a predictive model for public transport. In the first step of this study, regression analysis is used to find the correlations between two or more variables and their associated directions and strength, and the regression function is used to predict future changes. In the second step, the regression analysis and artificial neural network methods are assessed and the results are compared. The artificial neural network is more accurate in prediction than regression analysis. The study results can provide useful references for transportation organizations in the development of business operation strategies for managing sustainable smart cities.
Low-Memory Indoor Positioning System for Standalone Embedded Hardware
Authors: Bae Han Jun , Choi Lynn
Published: April 2021

As the proportion and importance of the indoor spaces in daily life are gradually increasing, spatial information and personal location information become more important in indoor spaces. In order to apply indoor positioning technologies in any places and for any targets inexpensively and easily, the system should utilize simple sensors and devices. In addition, due to the scalability, it is necessary to perform indoor positioning algorithms on the device itself, not on the server. In this paper, we construct standalone embedded hardware for performing the indoor positioning algorithm. We use the geomagnetic field for indoor localization, which does not require the installation of infrastructure and has more stable signal strength than RF RSS. In addition, we propose low-memory schemes based on the characteristics of the geomagnetic sensor measurement and convergence of the target’s estimated positions in order to implement indoor positioning algorithm to the hardware. We evaluate the performance in two testbeds: Hana Square (about 94 m × 26 m) and SK Future Hall (about 60 m × 38 m) indoor testbeds. We can reduce flash memory usage to 16.3% and 6.58% for each testbed and SRAM usage to 8.78% and 23.53% for each testbed with comparable localization accuracy to the system based on smart devices without low-memory schemes.
An Active/Reactive Power Control Strategy for Renewable Generation Systems
Authors: Andrade Iván , Pena Rubén , Blasco-Gimenez Ramón , Riedemann Javier , Jara Werner , Pesce Cristián
Published: April 2021

The development of distributed generation, mainly based on renewable energies, requires the design of control strategies to allow the regulation of electrical variables, such as power, voltage (V), and frequency (f), and the coordination of multiple generation units in microgrids or islanded systems. This paper presents a strategy to control the active and reactive power flow in the Point of Common Connection (PCC) of a renewable generation system operating in islanded mode. Voltage Source Converters (VSCs) are connected between individual generation units and the PCC to control the voltage and frequency. The voltage and frequency reference values are obtained from the P–V and Q–f droop characteristics curves, where P and Q are the active and reactive power supplied to the load, respectively. Proportional–Integral (PI) controllers process the voltage and frequency errors and set the reference currents (in the dq frame) to be imposed by each VSC. Simulation results considering high-power solar and wind generation systems are presented to validate the proposed control strategy.
Vitalization Strategies for the Building Energy Management System (BEMS) Industry Ecosystem Based on AHP Analysis
Authors: Kim Eunji , Ha Yoonhee
Published: April 2021

The combination of building energy management technology and technology of the Fourth Industrial Revolution has a significant potential for reducing energy consumption and, hence, CO2 emissions. However, numerous studies have indicated barriers preventing market growth. These challenges are mainly attributed to characteristics of the ecosystem of the building energy management systems (BEMS) industry. Thisstudy aimed to identify the major challenges hindering the deployment of BEMS in combination with Fourth Industrial Revolution technologies and to derive policies conducive to the achievement of the effective BEMS industry ecosystem. An analytic hierarchy process (AHP) survey was conducted on key players in the ecosystem to achieve this. The main elements of the ecosystem, economic, institutional, technology, and social system that earned weight, followed a decreasing trend in this order. Among the sub-elements, the payback period, upfront cost, electricity pricing scheme, energy consumption/CO2 emission reduction, and government support system ranked first to fifth places, respectively. This result can be used to determine the element in need of priority allocation of resources while establishing an effective BEMS. However, the priority depends on the development stage at which the industry is at, and other elements should not be overlooked.
Chemosensory Device Assisted-Estimation of the Quality of Edible Oils with Repetitive Frying
Authors: Lee Jookyeong , Boo Changguk , Hong Seong-jun , Shin Eui-Cheol
Published: April 2021

This study investigated chemosensory degradations of soybean and canola oils with repeated frying in order to estimate the quality of the oils. Methods: Chemical parameters including oxygen induction time, acid value, p-anisidine value, malondialdehyde, and total polar compounds were measured. Electronic nose and electronic tongue analyses were performed to assess sensory properties. Multivariate analyses were employed to investigate relationships among tastes and volatile compounds using principal component analysis (PCA) and Pearson’s correlation analysis. Results: All chemical parameters increased with repeated frying in both oils. Electronic nose analysis found ethyl butyrate, 2-heptenal, and 2,4-pentanedione as major volatiles for soybean oil and ethyl butyrate and linalool for canola oil. As the numbers of frying increased, all volatiles showed an increased concentration in various extents. In multivariate analyses, ethyl butyrate revealed strong positive correlations with sourness, umami, and sweetness, and umami showed strong positive correlations with sourness and saltiness (p < 0.05). PCA confirmed that in PC1 with 49% variance, sourness, saltiness, and umami were at similar rates while acetyl pyrazine, 2,4-pentadieone, and 1-octanol were found at similar rates. Canola oil was chemically more stable and less susceptible to deterioration in all chemical parameters compared to soybean oil, resulting in a relatively better quality oil when repeatedly fried. Conclusion: The results suggested that minimum repeated frying (5 times) degrades chemosensory characteristics of both oils, thereby compromising their quality. The findings of this study will be utilized as a foundation for quality control of fried foods in food industry, fried food development, and fast-food industry.
Effects of Isochoric Freezing Conditions on Cut Potato Quality
Authors: Zhao Yuanheng , Bilbao-Sainz Cristina , Wood Delilah , Chiou Bor-Sen , Powell-Palm Matthew J. , Chen Liubiao , McHugh Tara , Rubinsky Boris
Published: April 2021

Isochoric freezing is a pressure freezing technique that could be used to retain the beneficial effects of food storage at temperatures below their freezing point without ice damage. In this study, potato cylinders were frozen in an isochoric system and examined using full factorial combinations of three processing procedures (immersed in water, vacuum-packed and immersed in ascorbic acid solution), four freezing temperatures/pressures (−3 °C/37 MPa, −6 °C/71 MPa, −9 °C/101 MPa and −15 °C/156 MPa) and two average compression rates (less than 0.02 and more than 0.16 MPa/s). The effects of process variables on critical quality attributes of frozen potatoes after thawing were investigated, including mass change, volume change, water holding capacity, color and texture. Processing procedure and freezing temperature/pressure were found to be highly significant factors, whereas the significance of the compression rate was lower. For the processing procedures, immersion in an isotonic solution of 5% ascorbic acid best preserved quality attributes. At the highest pressure level of 156 MPa and low compression rate of 0.02 MPa/s, potato samples immersed in ascorbic acid retained their color, 98.5% mass and 84% elasticity modulus value. These samples also showed a 1% increase in volume and 13% increase in maximum stress due to pressure-induced hardening.
Fighting Deepfakes Using Body Language Analysis
Authors: Yasrab Robail , Jiang Wanqi , Riaz Adnan
Published: April 2021

Recent improvements in deepfake creation have made deepfake videos more realistic. Moreover, open-source software has made deepfake creation more accessible, which reduces the barrier to entry for deepfake creation. This could pose a threat to the people’s privacy. There is a potential danger if the deepfake creation techniques are used by people with an ulterior motive to produce deepfake videos of world leaders to disrupt the order of countries and the world. Therefore, research into the automatic detection of deepfaked media is essential for public security. In this work, we propose a deepfake detection method using upper body language analysis. Specifically, a many-to-one LSTM network was designed and trained as a classification model for deepfake detection. Different models were trained by varying the hyperparameters to build a final model with benchmark accuracy. We achieved 94.39% accuracy on the deepfake test set. The experimental results showed that upper body language can effectively detect deepfakes.
Fractals Parrondo’s Paradox in Alternated Superior Complex System
Authors: Zhang Yi , Wang Da
Published: April 2021

This work focuses on a kind of fractals Parrondo’s paradoxial phenomenon “deiconnected+diconnected=connected” in an alternated superior complex system zn+1=β(zn2+ci)+(1−β)zn,i=1,2. On the one hand, the connectivity variation in superior Julia sets is explored by analyzing the connectivity loci. On the other hand, we graphically investigate the position relation between superior Mandelbrot set and the Connectivity Loci, which results in the conclusion that two totally disconnected superior Julia sets can originate a new, connected, superior Julia set. Moreover, we present some graphical examples obtained by the use of the escape-time algorithm and the derived criteria.
Can Foraminal Stenosis Due to Lumbar Isthmic Spondylolisthesis Cause Axonopathy in the Lower Extremity?
Authors: Jo Seong Hyeon , Cho Jang Hyuk , Lee Dong Gyu
Published: April 2021

This study aimed to investigate, using electrodiagnosis, whether foraminal stenosis due to isthmic spondylolisthesis (IS) causes peripheral nerve axonopathy. We retrospectively reviewed the medical records of the Yeungnam University Hospital and included 46 patients (mean age = 60.8 ± 13.7 years; male:female = 24:22) with foraminal stenosis due to IS. We classified foraminal stenosis grading based on T2 and T1 sagittal spinal magnetic resonance imaging (MRI). Patients were divided into mild (n = 18) and severe foraminal stenosis (n = 28) groups. To evaluate axonopathy in the lower extremity, results of compound motor action potential (CMAP) of the extensor digitorum brevis muscle (EDB) and abductor hallucis brevis muscle (AHB), and sensory nerve action potential (SNAP) of the sural nerve were retrieved. No statistically significant difference was observed in the amplitude of CMAP of the EDB and AHB and SNAP of the sural nerve with the severity of foraminal stenosis. However, age showed a statistically significant relationship with the amplitude of NCS in the EDB, AHB, and sural nerves (p < 0.001). The severity of foraminal stenosis due to IS showed no relationship with axonopathy beyond age-related degeneration of the lower extremities. Therefore, if there is robust axonopathy in lower extremities, physicians should consider pathologies other than foraminal stenosis due to IS.
A Novel Method for COVID-19 Diagnosis Using Artificial Intelligence in Chest X-ray Images
Authors: Almalki Yassir Edrees , Qayyum Abdul , Irfan Muhammad , Haider Noman , Glowacz Adam , Alshehri Fahad Mohammed , Alduraibi Sharifa K. , Alshamrani Khalaf , Alkhalik Basha Mohammad Abd , Alduraibi Alaa , Saeed M. K. , Rahman Saifur
Published: April 2021

The Coronavirus disease 2019 (COVID-19) is an infectious disease spreading rapidly and uncontrollably throughout the world. The critical challenge is the rapid detection of Coronavirus infected people. The available techniques being utilized are body-temperature measurement, along with anterior nasal swab analysis. However, taking nasal swabs and lab testing are complex, intrusive, and require many resources. Furthermore, the lack of test kits to meet the exceeding cases is also a major limitation. The current challenge is to develop some technology to non-intrusively detect the suspected Coronavirus patients through Artificial Intelligence (AI) techniques such as deep learning (DL). Another challenge to conduct the research on this area is the difficulty of obtaining the dataset due to a limited number of patients giving their consent to participate in the research study. Looking at the efficacy of AI in healthcare systems, it is a great challenge for the researchers to develop an AI algorithm that can help health professionals and government officials automatically identify and isolate people with Coronavirus symptoms. Hence, this paper proposes a novel method CoVIRNet (COVID Inception-ResNet model), which utilizes the chest X-rays to diagnose the COVID-19 patients automatically. The proposed algorithm has different inception residual blocks that cater to information by using different depths feature maps at different scales, with the various layers. The features are concatenated at each proposed classification block, using the average-pooling layer, and concatenated features are passed to the fully connected layer. The efficient proposed deep-learning blocks used different regularization techniques to minimize the overfitting due to the small COVID-19 dataset. The multiscale features are extracted at different levels of the proposed deep-learning model and then embedded into various machine-learning models to validate the combination of deep-learning and machine-learning models. The proposed CoVIR-Net model achieved 95.7% accuracy, and the CoVIR-Net feature extractor with random-forest classifier produced 97.29% accuracy, which is the highest, as compared to existing state-of-the-art deep-learning methods. The proposed model would be an automatic solution for the assessment and classification of COVID-19. We predict that the proposed method will demonstrate an outstanding performance as compared to the state-of-the-art techniques being used currently.
Measurements of Serum Mac-2-Binding Protein Glycosylation Isomer and Shear Wave Velocity in Health Checkups Are Useful in Screening for Non-Alcoholic Steatohepatitis
Authors: Tamai Hideyuki , Okamura Jumpei , Ohoshi Takashi , Wakasaki Hisao
Published: April 2021

Liver-related mortality rates in patients with non-alcoholic steatohepatitis (NASH) increase with advancing liver fibrosis stage. The present study aimed to elucidate whether adding non-invasive liver fibrosis tests to a comprehensive health checkup system is useful for NASH screening. Both serum Mac-2-binding protein glycosylation isomer (M2BPGi) and point shear wave elastography (pSWE) using ultrasonography were performed for 483 health checkup subjects who consented to participate in this prospective study. Outcomes in positive subjects were surveyed 1 year later. Eighty-eight subjects (18%) showed positive results for at least one liver fibrosis test, with 63 subjects positive for pSWE, 33 subjects positive for M2BPGi, and 72 subjects showing no significant elevation of liver enzymes. The secondary consultation rate for positive subjects was 52% (46/88). However, as 15 of those 46 subjects visited a non-liver-specialist and could not undergo detailed examination, the secondary examination rate was only 35% (31/88). For the 31 subjects who received secondary examination, NASH was diagnosed in 14 subjects, other chronic liver disease (CLD) in 6 subjects, and no CLD in 11 subjects. Additional liver fibrosis tests using M2BPGi and pSWE appear useful in health checkups when screening for CLD, especially for NASH.
Cytopathology Practice in the COVID-19 Era: Focus on Sample Workload
Authors: Iaccarino Antonino , Dello Iacovo Filippo , Pisapia Pasquale , De Luca Caterina , Malapelle Umberto , Bellevicine Claudio , Troncone Giancarlo , Vigliar Elena
Published: April 2021

Since the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) outbreak was declared a pandemic, the magnitude of coronavirus disease 2019 (COVID-19) has continued to grow, putting an unprecedented strain on all medical fields. Its effects on cytopathology workloads have been dramatic. Indeed, despite the implementation of several laboratory biosafety recommendations, cytological screening activities and cytological sampling of patients at low risk of malignancy have been postponed to limit the risk of contagion and to lessen the strain on overwhelmed hospital facilities. In this scenario, a drastic reduction in the total number of cytological specimens has been observed worldwide. This review summarizes the current evidence of the impact of the COVID-19 pandemic on cytopathology practice by focusing on its impact on cytological sample workload.
CEO–Employee Pay Gap, Productivity and Value Creation
Authors: Przychodzen Wojciech , Gómez-Bezares Fernando
Published: April 2021

This study examines the effect of the CEO–employee pay gap on productivity and performance. Using extensive data of 751 constituents of the Standard and Poor’s (S&P) 1500 index between the years 1992–2016, we found a cubic relationship between salary differential and corporate productivity, with a rising gap adversely affecting productivity principally when it is both too low, as well as too high; intermediate pay inequality levels are less influential. A contrast in the productivity effects of the CEO–worker pay gap for firms with high average salaries and more employees was noticeable, whereas positive productivity gains were present even with a high salary gap. Thus, big companies with a highly skilled workforce are able to achieve tangible benefits through higher salary differentiation. On the other hand, companies with lower average salaries and lower capital intensity were characterized by the negative effects of wage dispersion on productivity. As a result, increasing inequality aversion is an important issue affecting performance among smaller, lower skilled labor dependent firms. Additionally, female CEOs had a significant and positive lagged effect on productivity. Finally, firm market valuation was positively stimulated by the increasing pay gap.
The Influence of Information Sharing through Social Network Sites on Customers’ Attitudes during the Epidemic Crisis of COVID-19
Authors: Alhubaishy Abdulaziz , Aljuhani Abdulmajeed
Published: April 2021

This paper explores the influence of crisis-related information on customers’ recommendations and purchase intentions. Various studies have investigated the role of risk-related information in terms of its certainty and immediacy. This research introduces a model that differentiates and investigates different types of information provided by organizations through social network sites (SNSs) that are related to the coronavirus (COVID-19) crisis, including situational information and precautionary measures information specifically. The proposed model targeted users of SNSs in Saudi Arabia, where around 72.38% of its population is considered active SNSs users with 3 h of average daily time spent on SNSs. Based on the survey data collected from 356 online shoppers in Saudi Arabia, structural equation modeling (SEM) was applied to test the proposed model. The reliability of instrument was tested using Confirmatory Factor Analysis (CFA), where the results showed acceptable model fit indices (X2/df = 2.6, GFI = 0.93, CFI = 0.94, TLI = 0.93, and RMSEA = 0.067). Based on that, the structural model was built and tested, which also showed acceptable fit indices (X2/df = 2.9, GFI = 0.92, CFI = 0.93, TLI = 0.91, and RMSEA = 0.073). The findings highlight that situational and adopted precautionary measures information had a significant impact on recommendations (γ=0.73) and purchase intentions (γ=0.39). Further, organizations that hold themselves accountable for broadcasting updated information related to the crisis and disseminating the necessary preventive measures develop a high level of recommendations and purchase intentions among customers. A personal recommendation construct was confirmed as a partial mediator, where an indirect significant influence was found of broadcasting information on purchase intention through personal recommendation (γ=0.309). Therefore, this paper suggests that organizations should consider offering customers all the necessary types of information related to the COVID-19 crisis.
Risk Evaluation of Electric Power Grid Enterprise Related to Electricity Transmission and Distribution Tariff Regulation Employing a Hybrid MCDM Model
Authors: Li Wenjin , Li Bingkang , Fang Rengcun , You Peipei , Zou Yuxin , Xu Zhao , Guo Sen
Published: April 2021

In China, a new-round marketization reform of electricity industry is in progress, and the electricity transmission and distribution tariff reform is the core and important task. Currently, the electricity transmission and distribution tariff regulation has gone to the second round in China, and the electric power grid enterprises are facing a closed-loop regulatory system and an increasingly strict regulatory environment. Therefore, it is urgent to evaluate the risk of electric power grid enterprise that is related to electricity transmission and distribution tariff regulation, which can aid the electricity regulators and electric power grid enterprise operators to manage risk and promote the sustainable development of electric power industry. In this paper, a hybrid novel multi-criteria decision making (MCDM) method combining the fuzzy Best-Worst method (FBWM) and improved fuzzy comprehensive evaluation method based on a vague set is proposed for the risk evaluation of electric power grid enterprise related to electricity transmission and distribution tariff regulation. The risk evaluation index system is built. Subsequently, the FBWM is utilized to determine the optimal weights of electric power grid enterprise risk criteria, and the improved fuzzy comprehensive evaluation method that is based on vague set is employed to rank the comprehensive risk grade of electric power grid enterprise related to electricity transmission and distribution tariff regulation. The risk of a province-level electric power grid enterprise that is located in Northern China is empirically evaluated using the proposed MCDM method, and the result indicates that the overall risk of this province-level electric power grid enterprise belongs to ‘High’ grade, but it is very close to ‘Very High’ grade. The results indicate that the proposed hybrid novel MCDM method in this paper is effective and practical. Meanwhile, it provides a new view for the risk evaluation of electric power grid enterprise that is related to electricity transmission and distribution tariff regulation.
Pontryagin Neural Networks with Functional Interpolation for Optimal Intercept Problems
Authors: D’Ambrosio Andrea , Schiassi Enrico , Curti Fabio , Furfaro Roberto
Published: April 2021

In this work, we introduce Pontryagin Neural Networks (PoNNs) and employ them to learn the optimal control actions for unconstrained and constrained optimal intercept problems. PoNNs represent a particular family of Physics-Informed Neural Networks (PINNs) specifically designed for tackling optimal control problems via the Pontryagin Minimum Principle (PMP) application (e.g., indirect method). The PMP provides first-order necessary optimality conditions, which result in a Two-Point Boundary Value Problem (TPBVP). More precisely, PoNNs learn the optimal control actions from the unknown solutions of the arising TPBVP, modeling them with Neural Networks (NNs). The characteristic feature of PoNNs is the use of PINNs combined with a functional interpolation technique, named the Theory of Functional Connections (TFC), which forms the so-called PINN-TFC based frameworks. According to these frameworks, the unknown solutions are modeled via the TFC’s constrained expressions using NNs as free functions. The results show that PoNNs can be successfully applied to learn optimal controls for the class of optimal intercept problems considered in this paper.
Regulatory Estimates for Defaulted Exposures: A Case Study of Spanish Mortgages
Authors: González Marta Ramos , Ureña Antonio Partal , Fernández-Aguado Pilar Gómez
Published: April 2021

The capital requirements derived from the Basel Accord were issued with the purpose of deploying a transnational regulatory framework. Further regulatory developments on risk measurement is included across several documents published both by the European Banking Authority and the European Central Bank. Among others, the referred additional documentation focused on the models’ estimation and calibration for credit risk measurement purposes, especially the Advanced Internal-Ratings Based models, which may be estimated both for non-defaulted and defaulted assets. A concrete proposal of the referred defaulted exposures models, namely the Expected Loss Best Estimate (ELBE) and the Loss Given Default (LGD) in-default, is presented. The proposed methodology is eventually calibrated on the basis of data from the mortgage’s portfolios of the six largest financial institutions in Spain. The outcome allows for a comparison of the risk profile particularities attached to each of the referred portfolios. Eventually, the economic sense of the results is analyzed.
A Linearization to the Sum of Linear Ratios Programming Problem
Authors: Borza Mojtaba , Rambely Azmin Sham
Published: April 2021

Optimizing the sum of linear fractional functions over a set of linear inequalities (S-LFP) has been considered by many researchers due to the fact that there are a number of real-world problems which are modelled mathematically as S-LFP problems. Solving the S-LFP is not easy in practice since the problem may have several local optimal solutions which makes the structure complex. To our knowledge, existing methods dealing with S-LFP are iterative algorithms that are based on branch and bound algorithms. Using these methods requires high computational cost and time. In this paper, we present a non-iterative and straightforward method with less computational expenses to deal with S-LFP. In the method, a new S-LFP is constructed based on the membership functions of the objectives multiplied by suitable weights. This new problem is then changed into a linear programming problem (LPP) using variable transformations. It was proven that the optimal solution of the LPP becomes the global optimal solution for the S-LFP. Numerical examples are given to illustrate the method.
A Review on Initialization Methods for Nonnegative Matrix Factorization: Towards Omics Data Experiments
Authors: Esposito Flavia
Published: April 2021

Nonnegative Matrix Factorization (NMF) has acquired a relevant role in the panorama of knowledge extraction, thanks to the peculiarity that non-negativity applies to both bases and weights, which allows meaningful interpretations and is consistent with the natural human part-based learning process. Nevertheless, most NMF algorithms are iterative, so initialization methods affect convergence behaviour, the quality of the final solution, and NMF performance in terms of the residual of the cost function. Studies on the impact of NMF initialization techniques have been conducted for text or image datasets, but very few considerations can be found in the literature when biological datasets are studied, even though NMFs have largely demonstrated their usefulness in better understanding biological mechanisms with omic datasets. This paper aims to present the state-of-the-art on NMF initialization schemes along with some initial considerations on the impact of initialization methods when microarrays (a simple instance of omic data) are evaluated with NMF mechanisms. Using a series of measures to qualitatively examine the biological information extracted by a given NMF scheme, it preliminary appears that some information (e.g., represented by genes) can be extracted regardless of the initialization scheme used.
Effect of Probability Distribution of the Response Variable in Optimal Experimental Design with Applications in Medicine
Authors: Pozuelo-Campos Sergio , Casero-Alonso Víctor , Amo-Salas Mariano
Published: April 2021

In optimal experimental design theory it is usually assumed that the response variable follows a normal distribution with constant variance. However, some works assume other probability distributions based on additional information or practitioner’s prior experience. The main goal of this paper is to study the effect, in terms of efficiency, when misspecification in the probability distribution of the response variable occurs. The elemental information matrix, which includes information on the probability distribution of the response variable, provides a generalized Fisher information matrix. This study is performed from a practical perspective, comparing a normal distribution with the Poisson or gamma distribution. First, analytical results are obtained, including results for the linear quadratic model, and these are applied to some real illustrative examples. The nonlinear 4-parameter Hill model is next considered to study the influence of misspecification in a dose-response model. This analysis shows the behavior of the efficiency of the designs obtained in the presence of misspecification, by assuming heteroscedastic normal distributions with respect to the D-optimal designs for the gamma, or Poisson, distribution, as the true one.
How to Explain the Cross-Section of Equity Returns through Common Principal Components
Authors: Cueto José Manuel , Grané Aurea , Cascos Ignacio
Published: April 2021

In this paper, we propose a procedure to obtain and test multifactor models based on statistical and financial factors. A major issue in the factor literature is to select the factors included in the model, as well as the construction of the portfolios. We deal with this matter using a dimensionality reduction technique designed to work with several groups of data called Common Principal Components. A block-bootstrap methodology is developed to assess the validity of the model and the significance of the parameters involved. Data come from Reuters, correspond to nearly 1250 EU companies, and span from October 2009 to October 2019. We also compare our bootstrap-based inferential results with those obtained via classical testing proposals. Methods under assessment are time-series regression and cross-sectional regression. The main findings indicate that the multifactor model proposed improves the Capital Asset Pricing Model with regard to the adjusted-R2 in the time-series regressions. Cross-section regression results reveal that Market and a factor related to Momentum and mean of stocks’ returns have positive risk premia for the analyzed period. Finally, we also observe that tests based on block-bootstrap statistics are more conservative with the null than classical procedures.
May Autogenous Grafts Increase the Effectiveness of Hyalonect Membranes in Intraosseous Defects: An Experimental In Vivo Study
Authors: Yilmaz Caner , Ersanli Selim , Karabagli Murat , Olgac Vakur , Bolukbasi Balcioglu Nilufer
Published: April 2021

Background and Objectives: Guided bone regeneration (GBR) surgeries are used for dental implant placements with insufficient bone volume. Biomaterials used in GBR are expected to produce sufficient volume and quality of bone swiftly. This study aims to histologically evaluate the effectiveness of the use of Hyalonect membranes alone or with autogenous grafts in intraosseous defects. Materials and Methods: This study is an experimental study on sheep. Surgeries were performed under general anesthesia in accordance with ethical rules. Five 10 mm defects were surgically created in each ilium of six sheep. One defect was left empty in each ilium (group ED). The defects in the experimental group were covered with Hyalonect membrane while unfilled (group HY) or after being filled with autogenous bone grafts (ABG) (group G+HY). In the control group, the defects were either covered with collagen membrane while unfilled (group CM) or after being filled with the ABG group (G+CM). The sheep were histologically and histomorphometrically evaluated after being postoperatively sacrificed in the third and sixth week (three animals in each interval). Results: All animals completed the study without any complications. No difference was found between groups in the third and sixth weeks regarding the inflammation, necrosis, and fibrosis scores. The G+CM (52.83 ± 3.06) group was observed to have a significantly higher new bone formation rate than all the other groups in the third week, followed by the G+HY group (46.33 ± 2.25). Similar values were found for HY and CM groups (35.67 ± 4.55 ve 40.00 ± 3.41, respectively, p = 0.185), while the lowest values were observed to be in group ED (19.67 ± 2.73). The highest new bone formation was observed in group G+CM (82.33 ± 4.08) in the sixth week. There was no difference in new bone formation rates between groups G+CM, G+HY (77.17 ± 3.49, p = 0.206), and CM (76.50 ± 2.43, p = 0.118). The insignificant difference was found ED group and group HY (55.83 ± 4.92, 73.50 ± 3.27, respectively, p = 0.09). The residual graft amount in the G+CM group was found to be statistically significant at 3 weeks (p = 0.0001), compared to the G+HY group, and insignificantly higher at the 6th week (p = 0.4). Conclusions: In this study, close values were observed between G+HY and G+CM groups. Further experimental and clinical studies with different graft materials are required to evaluate the effectiveness of HY in GBR.
Flow Field and Temperature Field in a Four-Strand Tundish Heated by Plasma
Authors: Zhao Mengjing , Wang Yong , Yang Shufeng , Ye Maolin , Li Jingshe , Liu Yuhang
Published: April 2021

Tundish plasma heating is an effective method for achieving steady casting with low superheat and constant temperature. In order to study the flow field, temperature field in tundish heated by plasma, a three-dimensional transient mathematical model was established in the present work. A four-strand T-type tundish in a steelmaking plant was used to explore the changes in the flow field and temperature field of molten steel in the tundish under different plasma heating powers. The results showed that plasma heating affected the flow state of molten steel. It could eliminate the short-circuit flow at outlet. When the plasma heating was 500 kW, the molten steel had an obvious upward flow. The turbulence intensity was improved and distributed evenly with an increase in plasma heating power. In the prototype tundish, the temperature of the outlet was dropped by nearly 2–3 K within 300 s. With the increase of plasma heating power, the low temperature area in the tundish gradually was decreased. When the heating power was 1000 kW, the temperature difference of two outlets was 0.5 K and the overall temperature distribution was more uniform. The research results have a certain guiding significance for the selection of the actual plasma heating power on site.
Vibration Damping and Acoustic Behavior of PU-Filled Non-Stochastic Aluminum Cellular Solids
Authors: Carneiro Vitor Hugo , Puga Hélder , Meireles José
Published: April 2021

Aluminum-based cellular solids are promising lightweight structural materials considering their high specific strength and vibration damping, being potential candidates for future railway vehicles with enhanced riding comfort and low fuel consumption. The filling of these lattices with polymer-based (i.e., polyurethane) foams may further improve the overall vibration/noise-damping without significantly increasing their density. This study explores the dynamic (i.e., frequency response) and acoustic properties of unfilled and polyurethane-filled aluminum cellular solids to characterize their behavior and explore their benefits in terms of vibration and noise-damping. It is shown that polyurethane filling can increase the vibration damping and transmission loss, especially if the infiltration process uses flexible foams. Considering sound reflection, however, it is shown that polyurethane filled samples (0.27–0.30 at 300 Hz) tend to display lower values of sound absorption coefficient relatively to unfilled samples (0.75 at 600 Hz), is this attributed to a reduction in overall porosity, tortuosity and flow resistivity. Foam-filled samples (43–44 dB at 700–1200 Hz) were shown to be more suitable to reduce sound transmission rather than reflection than unfilled samples (21 dB at 700 Hz). It was shown that the morphology of these cellular solids might be optimized depending on the desired application: (i) unfilled aluminum cellular solids are appropriate to mitigate internal noises due to their high sound absorption coefficient; and (ii) PU filled cellular solids are appropriate to prevent exterior noises and vibration damping due to their high transmission loss in a wide range of frequencies and vibration damping.
Plasma Metabolomics to Evaluate Progression of Necrotising Enterocolitis in Preterm Pigs
Authors: Jiang Yan-Nan , Ye Yong-Xin , Sangild Per Torp , Thymann Thomas , Engelsen Søren Balling , Khakimov Bekzod , Jiang Ping-Ping
Published: April 2021

Necrotising enterocolitis (NEC) is a microbiome-dependent gut disease in preterm infants in early life. Antibiotic treatment is a common intervention for NEC. How NEC lesions, with or without antibiotics, affect plasma metabolome was explored in this study. Formula-fed preterm pigs were used as a model for human NEC and treated with saline, parenteral or oral antibiotics (n = 15–17) for four days after delivery. Gut tissues were collected for evaluation of NEC-like lesions and plasma for metabolomic analysis by proton nuclear magnetic resonance spectroscopy (1H-NMR). Metabolites were annotated, quantified and subjected to statistical modelling to delineate the effects of NEC and antibiotic treatment. Presence of severe NEC lesions, not antibiotic treatment, was the main drive for plasma metabolite changes. Relative to other pigs, pigs with severe NEC lesions had higher levels of alanine, histidine and myo-inositol, and lower levels of 3-hydroxybutyric acid and isobutyric acid. Across NEC lesion states (healthy, mild, severe), antibiotics directly affected only a few metabolites (tryptophan, 3-phenyllactic acid). Together and independently, NEC and antibiotic treatment affected circulating metabolites in preterm pigs. Amino acids and plasma metabolites, partly related to the gut microbiome, may be helpful to monitor progression of NEC lesions after proper validation.
Thermophilic Chloroflexi Dominate in the Microbial Community Associated with Coal-Fire Gas Vents in the Kuznetsk Coal Basin, Russia
Authors: Kadnikov Vitaly V. , Mardanov Andrey V. , Beletsky Alexey V. , Grigoriev Mikhail A. , Karnachuk Olga V. , Ravin Nikolai V.
Published: April 2021

Thermal ecosystems associated with areas of underground burning coal seams are rare and poorly understood in comparison with geothermal objects. We studied the microbial communities associated with gas vents from the coal-fire in the mining wastes in the Kemerovo region of the Russian Federation. The temperature of the ground heated by the hot coal gases and steam coming out to the surface was 58 °C. Analysis of the composition of microbial communities revealed the dominance of Ktedonobacteria (the phylum Chloroflexi), known to be capable of oxidizing hydrogen and carbon monoxide. Thermophilic hydrogenotrophic Firmicutes constituted a minor part of the community. Among the well-known thermophiles, members of the phyla Aquificae, Deinococcus-Thermus and Bacteroidetes were also found. In the upper ground layer, Acidobacteria, Verrucomicrobia, Actinobacteria, Planctomycetes, as well as Proteobacteria of the alpha and gamma classes, typical of soils, were detected; their relative abundancies decreased with depth. The phylum Verrucomicrobia was dominated by Candidatus Udaeobacter, aerobic heterotrophs capable of generating energy through the oxidation of hydrogen present in the atmosphere in trace amounts. Archaea made up a small part of the communities and were represented by thermophilic ammonium-oxidizers. Overall, the community was dominated by bacteria, whose cultivated relatives are able to obtain energy through the oxidation of the main components of coal gases, hydrogen and carbon monoxide, under aerobic conditions.
Seed Meals from Brassica nigra and Eruca sativa Control Artificial Nosema ceranae Infections in Apis mellifera
Authors: Nanetti Antonio , Ugolini Luisa , Cilia Giovanni , Pagnotta Eleonora , Malaguti Lorena , Cardaio Ilaria , Matteo Roberto , Lazzeri Luca
Published: April 2021

Nosema ceranae is a widespread parasite responsible for nosemosis Type C in Apis mellifera honey bees, reducing colony survival. The antibiotic fumagillin is the only commercial treatment available, but concerns are emerging about its persistence, safety, and pathogen resistance. The use of natural substances from Brassicaceae defatted seed meals (DSMs) with known antimicrobial and antioxidant properties was explored. Artificially infected bees were fed for 8 days with candies enriched with two concentrations, 2% and 4%, of two DSMs from Brassica nigra and Eruca sativa, containing a known amount of different glucosinolates (GSLs). The food palatability, GSL intake, bee survival, and treatment effects on N. ceranae spore counts were evaluated. Food consumption was higher for the two 2% DSM patties, for both B. nigra and E. sativa, but the GSL intake did not increase by increasing DSM to 4%, due to the resulting lower palatability. The 2% B. nigra patty decreased the bee mortality, while the higher concentration had a toxic effect. The N. ceranae control was significant for all formulates with respect to the untreated control (312,192.6 +/− 14,443.4 s.e.), and was higher for 4% B. nigra (120,366.3 +/− 13,307.1 s.e.). GSL hydrolysis products, the isothiocyanates, were detected and quantified in bee gut tissues. Brassicaceae DSMs showed promising results for their nutraceutical and protective effects on bees artificially infected with N. ceranae spores at the laboratory level. Trials in the field should confirm these results.