bluuebunny/crossref_metadata_2025_split huggingface dataset:
WITHDRAWN: An Analysis of Extreme Machine Learning Models
Authors: Pande Shubhangi , Rathore Neeraj , Purohit Anuradha 
Published: August 2021

Abstract
Machine learning applications employ FFNN (Feed Forward Neural Network) in their discipline enormously. But, it has been observed that the FFNN requisite speed is not up the mark. The fundamental causes of this problem are: 1) for training neural networks, slow gradient descent methods are broadly used and 2) for such methods, there is a need for iteratively tuning hidden layer parameters including biases and weights. To resolve these problems, a new emanant machine learning algorithm, which is a substitution of the feed-forward neural network, entitled as Extreme Learning Machine (ELM) introduced in this paper. ELM also come up with a general learning scheme for the immense diversity of different networks (SLFNs and multilayer networks). According to ELM originators, the learning capacity of networks trained using backpropagation is a thousand times slower than the networks trained using ELM, along with this, ELM models exhibit good generalization performance. ELM is more efficient in contradiction of Least Square Support Vector Machine (LS-SVM), Support Vector Machine (SVM), and rest of the precocious approaches. ELM’s eccentric outline has three main targets: 1) high learning accuracy 2) less human intervention 3) fast learning speed. ELM consider as a greater capacity to achieve global optimum. The distribution of application of ELM incorporates: feature learning, clustering, regression, compression, and classification. With this paper, our goal is to familiarize various ELM variants, their applications, ELM strengths, ELM researches and comparison with other learning algorithms, and many more concepts related to ELM.
Primary Non-adherence to Pharmacotherapy Among Patients With Chronic Diseases: A Case Study of Slovakia
Authors: Szalay Tomáš , Ištokovičová Petra , Mužik Roman , Knapčoková Veronika , Benková Beáta 
Published: August 2021

Abstract
BackgroundePrescription enables to investigate primary non-adherence (PNA) to pharmacotherapy by studying the percentage of prescriptions which have been issued (a prescription record present) but not dispensed in a pharmacy (a dispensation record missing) out of a total number of registered prescriptions. Identification of non-adherence enables to analyze its causes and target them efficiently.MethodsThis paper investigates PNA rate for prescriptions issued to patients with chronic diseases such as hypertension, diabetes mellitus and hypercholesterolemia (N=108 735), and its dependence on the following variables: geographic location, age, sex, social status, physicians specialty and the level of patient‘s co-payment for medications. The presented dataset comprises a private health insurance company’s prescription data collected over a period of 12 months (January 2018 – December 2018).ResultsThe PNA rate for ePrescriptions issued to patients with the above-mentioned chronic diseases reached up to 4.0%. In general, the PNA rate showed decrease with increasing comorbidity as well as with age. Primary non-adherence rates were lowest for the prescriptions written by general practitioners (3.6%). Among health insurance premium defaulters who pay the full price of prescribed medications, the PNA rate showed decrease with their cost. Significantly higher PNA rate was observed among premium payers (40.4%) compared with premium defaulters (3.5%).ConclusionsInterestingly, the very high rate of adherence among patients with chronic diseases exceeds the numbers previously reported in the literature, where adherence rate ≥80% is described as ‘good’ adherence. This could be partially explained by the fact that the present study included only chronic-disease patients undergoing a medical treatment – non-diagnosed patients or patients without a medical treatment were not considered.
Ecological Risk Assessment of Pharmaceuticals and Personal Care Products in the Water Environment of 15 Cities in Japan
Authors: NISHINO TAKAHIRO , Kato Mika , Miyazawa Yoshitaka , Tojo Toshiki , Asakawa Daichi , Okata Masanori , Matsumura Chisato , Haga Yuki , Kakoi Takuya , Hasegawa Hitomi , Okamura Tetsuro , Sawai Atsushi 
Published: August 2021

Abstract
To assess the ecological risk of pharmaceuticals and personal care products (PPCPs) to the water environment of several cities in Japan, major local environmental research institutes, a private company, and an academic institution launched a joint research project in 2019. Under this initiative, local environmental research institutes surveyed the concentrations of 46 types of PPCPs at 59 points distributed across 15 cities in Japan. IDEA Consultants, Inc. calculated the unknown values of predicted no-effect concentration (PNEC) of six chemicals (telmisartan, candesartan, fexofenadine, diphenhydramine, diphenyl sulfone, and ketotifen) through bioassay experiments on aquatic organisms. Among the researched chemicals, the concentrations of clarithromycin, 14-hydroxyclarithromycin, erythromycin, diclofenac, carbamazepine, and telmisartan exceeded the PNEC in at least one sampling point. However, ozone treatment removed most of these chemicals, except for certain phosphate ester flame retardants. The mass balance of chemicals in the Tamagawa River flowing through Tokyo Prefecture was calculated by multiplying the concentration of each chemical with the flow rate at each sampling point in the river. The measured load of most chemicals at each sampling point of the Tamagawa River coincided to a certain extent with the cumulative load accumulated from the tributaries and sewage treatment plants to the uppermost point (Nagata Bridge). However, the measured load of diclofenac was significantly smaller than the estimated values at each sampling point, suggesting that diclofenac photodegrades while flowing down the river.
Influence of diets supplemented with naturally protected or unprotected eucalyptus oil on methane production and lactating buffalo productivity
Authors: Abo-Donia Fawzy Mohamed , Elaref Mohamed Youssif , Mahgoub Abd El-Moniem Ali Sayed , Deraz Tarek Abd El Wahab Ahmed , Nayel Usama Aboelez 
Published: August 2021

Abstract
This study was designed to investigate the influence of naturally protected eucalyptus oil supplementation in a form of leaves (EUL) or mature seed capsules (EUS) compared to crude eucalyptus oil (EUO). The control group (G1) received a diet containing concentrate feed mixture, fresh berseem, rice straw, and corn silage. Whereas the G2, G3, and G4 animals have a diet supplemented with 200 g/head/day of EUL or EUS or 4 mL/head/day EUO, respectively. Supplementation of EUL or EUS increased NH3-N, SCFA’s, and concentrations of acetic acid in-vitro. Bacterial total count, protozoa, and cellulolytic bacteria increased (P < 0.05) with EUL and EUS supplementation. Methane production dropped (P < 0.05) with EUS, EUL, and EUO supplementation. Milk fat decreased (P < 0.05) with EUO supplementation, while an adverse trend was shown for lactose. No differences in feed conversion were found among EUS, EUL, and EUO. Blood total protein, albumin, and urea increased (P < 0.05) with supplementation of EUL or EUS compared to EUO. EUO supplementation yielded increased (P < 0.05) AST, ALT, glucose, and creatinine. Supplementation with EUL, EUS, or EUO decreased (P < 0.05) DM, OM, and CP digestibility. While digestibility of EE with supplementation by EUL, EUS, or EUO was higher (P < 0.05). The digestion coefficient of NDF and ADF decreased (P < 0.05) with supplemental EUL, EUS, or EUO compared to the G1 diet. Feeding EUS increased the values of TDN and DCP compared to EUL, which increased than EUO. Our results confirm that the naturally protected form of leaves or seeds mitigates the undesirable effects of directly supplementing crude eucalyptus oil.
Comparing Pair and Self Dynamics of Scaffolding by Written Languaging in English as a Foreign Language Learning
Authors: Pourdana Natasha , Khalili Gholamhassan Famil , Keshanchi Elnaz 
Published: August 2021

Abstract
This study investigated the extent to which dynamics of scaffolding (self vs. pair) would impact the language learners’ written languaging in terms of quantity, focus, conceptual processes of languaging, and language learning improvement. To this end, in a pretest-posttest research design, we assigned 60 English-as-a-Foreign-Language undergraduate students into two groups of pair languagers and self-languagers before they engaged in three-stage (translating, comparing to the model translation, revising) Persian-to-English translation tasks. Content analysis of written languaging episodes (WLs) indicated that while pair languagers produced more WLs than the self-languagers, both groups used WLs in a descending order from Stage 1 to 3 in translation tasks. Also, distribution of lexis-focused (L-WL) and grammar-focused (G-WL) episodes indicated despite the fact that both pair and self-languagers produced more L-WL than G-WL episodes, pair languagers produced a larger amount of L-WL episodes than self-languagers who had relatively a higher record in production of G-WL episodes. Moreover, the proportions of conceptual processes incorporated into WLs was found to be uneven and more in favor of self-assessment and hypothesis formation by both groups. Finally, statistical analysis of variance (ANOVA) reported the advantage of pair languagers in language learning improvement over self-languagers, despite their mutual progress. The paper was concluded with a number of pedagogical implications.
Attainment of Stable (FTO/ZnO/CdS/CH3NH3SnI3/GaAs/Au) Perovskite Solar Cell With Above 23% Photovoltaic Performance Using Solar Capacitance Simulator
Authors: Qasim Irfan , Ahmad Owais , Rashid Asim , Zehra Tashfeen , Malik Muhammad Imran , Rashid Muhammad , Ahmed M. Waqar , Nasir M. Farooq 
Published: August 2021

Abstract
Solar energy is found to be low cost and abundant of all available energy resources and needs exploration of highly efficient devices for global energy requirements. We have investigated methyl ammonium tin halide (CH3NH3SnI3)-based perovskite solar cells (PSCs) for optimized device performance using solar capacitance simulator SCAPS-1D software. This study is a step forward towards availability of stable and non-toxic solar cells. We explored all necessary parameters such as metal work functions, thickness of absorber and buffer layers, charge carrier’s mobility and defect density for improved device performance. Calculations revealed that for the best efficiency of device the maximum thickness of the perovskite absorber layer must be 4.2 μm. Furthermore, optimized thickness values of (ZnO=0.01 μm) as electron transport layer (ETL), GaAs as hole transport layer (HTL=3.02 μm) and (CdS=10 nm) and buffer layer have provided power conversion efficiency (PCE) of 23.53%. Variation of open circuit voltage (Voc), Short circuit current (Jsc), Fill Factor (FF%) and quantum efficiency against thickness of all layers in FTO/ZnO/CdS/CH3NH3SnI3/GaAs/Au compositions have been critically explored and reported. Interface defects and defect density in different inserted layers have also been reported in this study as they can play a crucial for the device performance. Insertion of ZnO layer and CdS buffer layers have shown improved device performance and PCE. Current investigations may prove to be useful for designing and fabrication of climate friendly, non-toxic and highly efficient solar cells.
HIV Self-Testing Implementation, Distribution and Use Among Female Sex Workers in Cotonou, Benin: A Qualitative Evaluation of Acceptability and Feasibility
Authors: Moreau Marianne Boisvert , Kintin Frédéric D. , Atchekpe Septime , Batona Georges , Béhanzin Luc , Guédou Fernand A. , Gagnon Marie-Pierre , Alary Michel 
Published: August 2021

Abstract
Background

In Benin, the burden of HIV is disproportionately high among female sex workers (FSWs). HIV testing and knowledge of status are starting points for HIV treatment and prevention interventions. Despite the importance given to testing services in HIV control, its uptake among FSWs remains suboptimal in Benin. HIV self-testing (HIVST) may be useful for increasing testing rates in FSWs.
Methods

We conducted a pilot study of the distribution of saliva-based HIVST among FSWs in Cotonou and its surroundings, Benin. The HIVST promotion and distribution model included three complementary strategies: community-based, facility-based and secondary distribution. In this qualitative study, we explored the elements influencing HIVST implementation, distribution and use among FSWs. We assessed HIVST acceptability and feasibility in this population. We conducted 29 semi-structured individual interviews with FSWs. Data were interpreted with a thematic analysis method, using the Theoretical Domains Framework.
Results

Only two FSWs (6.9%) were aware of HIVST before participating in the study. All participants were interested in using HIVST if available in Benin. Many advantages of HIVST were mentioned, including: autonomy, privacy, accessibility, time saving, and the fact that it is a painless test. Barriers to the use of HIVST included: the fear of unreliability, the lack of psychological support and medical follow-up and the possibility of result dissimulation. Participants thought HIVST was easy to use without assistance. HIVST enabled linkage to care for a few FSWs in denial of their HIV-positive status. No case of suicide or violence associated with HIVST was reported. HIVST secondary distribution within FSWs social network was well received. FSWs’ boyfriends and clients showed interest in using the device. Some FSWs reported using HIVST to practice serosorting or to guide their decisions regarding condom use.
Conclusions

Our study shows a very high level of acceptability for HIVST among FSWs in Cotonou and its surroundings. Results also demonstrate the feasibility of implementing HIVST distribution in Benin. HIVST should be implemented in Benin quickly and free of charge for all individuals at risk of HIV. HIVST offer should be integrated with comprehensive sexual health and prevention services.
In Vivo Magnetic Resonance Imaging Evidence of Olfactory Bulbs Changes in a Newborn With Congenital Citomegalovirus: A Case Report
Authors: Bianchi Andrea , Coviello Caterina , Leonardi Valentina , Luzzati Michele , Chiti Stefano , Ermini Daniele , Miele Vittorio , Fainardi Enrico , Dani Carlo , Scola Elisa 
Published: August 2021

Abstract
Background
Citomegalovirus (CMV) infects approximately 1% of live newborns. About 10% of the infants affected by congenital CMV infection are symptomatic at birth and up to 60% of these infants will develop permanent neurological disabilities. Depending on gestational age (GA) at the time of infection, the involvement of central nervous system (CNS) can lead to malformations of cortical development, calcifications, periventricular white matter lesions and cysts, ventriculomegaly and cerebellar hypoplasia.
Case Presentation:
We report the MRI findings in a Caucasian female born at 32 weeks of post-menstrual age with post-birth diagnosis of congenital CMV infection showing an unusual and peculiar marked T2 hyperintensity of the inner part of olfactory bulbs in addition to the CMV related diffuse brain involvement. Despite the known extensively described fetal and neonatal Magnetic Resonance Imaging (MRI) findings in CMV infected fetuses and newborns, any in vivo MRI depiction of olfactory system damage have never been reported so far. Nevertheless, in murine studies CMV is known to infect the placenta during pregnancy showing particular tropism for neural stem cells of the olfactory system and previous neuropathologic study on CMV infected human fetal brains from 23 to 28 weeks of GA reported damage in the olfactory bulbs (OB) consisting in disseminated cytomegalic cells, inflammation, necrosis and neuronal and radial glial cell loss. Therefore, we assume an OB involvement and damage in congenital CMV infection.
Conclusion
To our knowledge this is the first in vivo MRI evidence of OB damage in a newborn with congenital CMV infection that may give new insights on CMV infection.
Rotational self-friction problem of elastic rods
Authors: Latrach Mohamed Ali , Chamekh Mourad 
Published: August 2021

Abstract
The aim of this paper is to extend the modeling of a hyperelastic rod undergoing large displacements with tangential self-friction to their modeling with rotational self-friction. As well as the discontinuity of contact force into a contact region not known in advance, taking into account the effects of friction in this problem type underlies more serious modeling, mathematical and numerical analysis difficulties. In this paper, we present an accurate modeling of rotational and tangential self-friction with Coulomb's law and also describe an augmented Lagrangian method to present a weak variational formulation approach of this problem. We then use the minimization method of the total energy to present an existence result of solution for the nonlinear penalized formulation. Finally, we give the linearization and the finite-element discretization of the weak variational formulation that can be useful for a numerical implementation.
Convolutional Neural Networks Inference Memory Optimization with Receptive Field-Based InputTiling
Authors: Zhuang Weihao , Hascoet Tristan , Chen Xunquan , Takashima Ryoichi , Takiguchi Tetsuya , Ariki Yasuo 
Published: August 2021

Abstract
Currently, deep learning plays an indispensable role in many fields, including computer vision, natural language processing, and speech recognition. Convolutional Neural Networks (CNNs) have demonstrated excellent performance in computer vision tasks thanks to their powerful feature extraction capability. However, as the larger models have shown higher accuracy, recent developments have led to state-of-the-art CNN models with increasing resource consumption. This paper investigates a conceptual approach to reduce the memory consumption of CNN inference. Our method consists of processing the input image in a sequence of carefully designed tiles within the lower subnetwork of the CNN, so as to minimize its peak memory consumption, while keeping the end-to-end computation unchanged. This method introduces a trade-off between memory consumption and computations, which is particularly suitable for high-resolution inputs. Our experimental results show that MobileNetV2 memory consumption can be reduced by up to 5.3 times with our proposed method. For ResNet50, one of the most commonly used CNN models in computer vision tasks, memory can be optimized by up to 2.3 times.
An Authentication Based Approach for Prevention of Spectrum Sensing Data Falsification Attacks in Cognitive Radio Network
Authors: Marriwala Nikhil , Punj Himanshu , Panda Sunita , Kaur Inderjeet , Rathore Deepak 
Published: August 2021

Abstract
This is the era of Intelligent cognitive radio network technology that provides the available spectrum with efficient utilization. Cognitive Radio technology must promise to allow interference-free spectrum access by users. The paper discusses the several attacks and motives of attacks. The authentication mechanism role to prevent the attacks for hassle-free spectrum utilization is demonstrated. In this paper, resolving the cognitive network security issues by the authentication mechanism and the methods and need of authentication is discussed. This paper addresses the research challenges in the way of securing the cognitive radio network and countermeasures in CRN security strategies. Cognitive radio is an empowering innovation that guarantees to achieve spectrum utilization. In cognitive radio networks, several security threats affect the process of cognitive radio. Spectrum sensing data falsification (SSDF) attack is most disruptive in which the malicious users degrade the decision-making process by sending the false sensing reports to data fusion centres thus preventing honest users from utilizing the spectrum. Hence, security is a very important issue in cognitive radio networks that needs to be addressed for proper utilization of available spectrum by the users. Cognitive radio technology must promise secure spectrum dynamic access to users. In this paper, to counter the SSDF attack, the trust-based security mechanism is demonstrated to authenticate the honest users and it is observed that the proposed framework in the MATLAB environment is efficient and able to detect malicious users. Cognitive radio technology is the strategy applied to the spectrum to make it efficient for wireless communication. The strategy is an intelligent way to access the spectrum as it can learn its environment and make decisions by easy adaptation of operating parameters. The multiple nodes scenario is a good perspective. Software-defined radio is an essential component of cognitive radio Here, secondary users can access the spectrum to primary users whenever their vacant spectrum is available. The initial step is to sense the spectrum available further steps are spectrum decision making, spectrum management, and spectrum mobility. The network is vulnerable to various attacks on spectrum sensing and policy protocols which lead to disturbing functionality of cognitive radio technology. The defence mechanism based on public-key cryptography is proposed in which PU is authenticated by appending signature provided to PU signal. Authentication with a tag to the primary users is another perspective proposed. CRN technology should provide integrity, confidentiality and authenticity to the users.
18β-Glycyrrhetinic Acid Suppresses Allergic Airway Inflammation through NF-κB and Nrf2/HO-1 Signaling Pathways in Asthma Mice
Authors: liu jianming , Xu Yanqi , Yan Minyu , Yu Yingjie , Guo Yongmei 
Published: August 2021

Abstract
18β-Glycyrrhetinic acid (18β-GA), the main bioactive component of Glycyrrhizae Radix, is considered a promising anti-inflammatory and antioxidant agent. Here, we evaluated the anti-inflammatory and antioxidant effects of 18β-GA in an ovalbumin (OVA)-induced asthma mouse model, and examined the role of NF-κB and Nrf2/HO-1 signaling pathways. The histopathological changes of lung tissue in mouse were assessed by histochemical staining and counting of inflammatory cells. The levels of IgE and inflammatory cytokines in the bronchoalveolar lavage fluid of mice were detected by ELISA. In OVA-induced asthmatic mice, 18β-GA treatment can significantly improve lung function and reduce lung inflammation including infiltration of inflammatory cells. In addition, 18β-GA reduced the OVA-induced NF-κB phosphorylation in lungs of mice while increasing the expression of Nrf2 and HO-1. These results indicate that 18β-GA protects OVA-induced allergic inflammation of airway by inhibiting phosphorylation of NF-κB and enhancing the Nrf2/HO-1 pathway, and serves as a potential treatment option for allergic inflammation of airway.