bluuebunny/crossref_metadata_2025_split huggingface dataset:
Accuracy of the Arabic HCL - 32 and MDQ in detecting patients with bipolar disorder
Authors: Ouali Uta , Zgueb Yosra , Jouini Lamia , Aissa Amina , Jomli Rabaa , Ouertani Abdelhafidh , Omrani Adel , Nacef Fethi , Carta Mauro G. , Preti Antonio 
Published: July 2022

Abstract
Background: Studies about two most used and validated instruments for the early detection of BD, the 32 - item Hypomania Checklist (HCL - 32) and the Mood Disorder Questionnaire (MDQ)screeners, in non-Western countries are scarce. This study aimed to explore the reliability, factor structure, and criterion validity of the Arabic versions in a sample of Tunisian patients diagnosed with mood disorder. Methods: The sample included 59 patients with BD, 86 with unipolar MDD and 281 controls. Confirmatory factor analysis was applied to show that a single global score was an appropriate summary measure of the screeners in the sample. Receiver Operating Characteristic analysis was used to assess the capacity of the translated screeners to distinguish patients with BD from those with MDD and controls. Results: Reliability was good for both tools in all samples. The bifactor implementation of the most reported two-factor model had the best fit for both screeners. Both were able to distinguish patients diagnosed with BD from putatively healthy controls, and equally able to distinguish patients diagnosed with BD from patients with MDD. Conclusion: Both screeners work best in excluding the presence of BD in patients with MDD, which is an advantage in deciding whether or not to prescribe an antidepressant.
Construction of Blueberry Hardness Prediction Nutrient Content Model Based on Heterogeneous Stacking Ensemble Learning
Authors: Fu Shenghong , Feng Guohong , Zhu Yujie , Diao Pengfei 
Published: July 2022

Abstract
In order to effectively control the storage quality of blueberries, a prediction model between physical and chemical indicators of blueberries based on heterogeneous Stacking ensemble learning was proposed for the current situation of blueberry quality detection. Firstly, through the correlation analysis of blueberry hardness、mass with the vitamin C, and soluble solid content, a prediction model of the vitamin C and soluble solid content based on one-dimensional features of hardness and mass was established. Secondly, multi-dimensional features were added to the hardness to do the dimensional lift and the same study was carried out in the same dimension. Finally, the prediction effects of Stacking ensemble learning with a single model and the addition of multi-dimensional features were compared (The correlation coefficient and root mean square error of validation of the optimal models were 0.890、0.889 and 0.250、0.232). The results show that heterogeneous Stacking combined with the addition of multi-dimensional features has good predictive potential and provides a new way for blueberry quality detection.
Clinical outcomes following surgical management of deep infiltrating endometriosis: a retrospective cohort study
Authors: LEBORNE Perrine , HUBERLANT Stephanie , MASIA Florent , DE TAYRAC Renaud , LETOUZEY Vincent , ALLEGRE Lucie 
Published: July 2022

Abstract
Objectives: The main aim of the study was to evaluate severe post-operative complications following deep endometriosis surgery in a tertiary referral centre.Methods: This is a retrospective cohort study that included women who had surgery for deep infiltrating endometriosis between 1st January 2013 and 31st December 2019. Endometriosis was diagnosed based on clinical, imaging and histological parameters. We evaluated the rates of post-operative complications, potential risk factors for such complications and postoperative pregnancy rates.Results: A total of 165 patients were included in the final analysis. The median follow-up was 63 (25 - 106) months. Thirty-seven patients (22.42%) had hysterectomy, 60 (36.81%) had ureterolysis and 44 (26.67%) had colorectal surgery. The overall and severe rates of post-operative complications were 16.20% (n=23) and 2.42% (n=4) respectively. Of the variables assessed, operative time and age were the only statistically significant risk factor for complications on multivariate analysis. Among the women operated on for infertility, 34.5% (n=20/58) got pregnant following surgery with 30% of these spontaneously.Conclusions: This study demonstrates acceptable overall and severe post-operative complications and pregnancy rates after deep endometriosis surgery. This information should help clinicians when counselling women to enable them make an informed choice about their management.
A strategic approach in Forensic Investigation of Identical Twins from speech - Deep Learning Networks
Authors: A Revathi , N Sasikaladevi 
Published: July 2022

Abstract
Identification of convict by using several biometrics namely face, finger print, iris, DNA patterns and so on is currently in vogue. Speech is seldom used for such tasks since this process becomes more challenging if it is needed to identify an offender from among identical twin pairs because twins exhibit similar characteristics in contemplating manners, style and expression of emotions. In this work, cost effective speech is used as a biometric to identify twin among twin pairs including identical twins. This work involves the use of perceptual features and deep learning techniques to identify a twin and the performance of the system is analysed by using recognition accuracy, false rejection rate and false acceptance rate as metrics. Deep machine learning techniques namely Recurrent neural networks and Convolutional neural networks are used for creating models for twin pairs. Among the perceptual features, features with filters spaced in Equivalent Rectangular Bandwidth (ERB) and MEL scale have provided 100% as accuracy for both text dependent and text independent modes of classifying the respective twin among the twin pairs based on Convolutional neural network. Perceptual features with filters spaced in BARK scale have provided better accuracy of 98% as compared to other perceptual features for text dependent and independent twin identification by using RNN based machine learning classifier. Hence the experimental results explicitly shows that, proposed method works effectively for twins identification compared to the other existing methods.
A genomic blueprint of the healthy human oesophageal microbiome
Authors: Gilroy Rachel , Adam Mina E , Kumar Bhaskar , Pallen Mark J 
Published: July 2022

Abstract
Background. The oesophageal microbiome is thought to contribute to the pathogenesis of oesophageal cancer. However, investigations using culture and molecular barcodes have provided only a low-resolution view of this important microbial community. We therefore exploited culturomics and metagenomic binning to generate a catalogue of reference genomes from the healthy human oesophageal microbiome, alongside a comparison set from saliva. Results. Twenty-two distinct colonial morphotypes from healthy oesophageal samples were genome-sequenced. These fell into twelve species clusters, eleven of which represented previously defined species. Two isolates belonged to a novel species, which we have named Rothia gullae. We performed metagenomic binning of reads generated from UK samples from this study alongside reads generated from Australian samples in the recent study by Deshpande et al., 2018. Metagenomic binning generated 136 medium or high-quality metagenome-assembled genomes (MAGs). MAGs were assigned to 56 species clusters, eight representing novel Candidatus species, which we have named Ca. Granulicatella gullae, Ca. Streptococcus gullae, Ca. Nanosynbacter quadramensis, Ca. Nanosynbacter gullae, Ca. Nanosynbacter colneyensis, Ca. Nanosynbacter norwichensis, Ca. Nanosynococcus oralis and Ca. Haemophilus gullae. Five of these novel species belong to the recently described phylum Patescibacteria. Although members of the Patescibacteria are known to inhabit the oral cavity, this is the first report of their presence in the oesophagus. Eighteen of the metagenomic species were, until recently, identified only by hard-to-remember alphanumeric placeholder designations. Here we illustrate the utility of a set of recently published arbitrary Latinate species names in providing user-friendly taxonomic labels for microbiome analyses. Our non-redundant species catalogue contained 63 species derived from cultured isolates or MAGs. Mapping revealed that these species account for around half of the sequences in the oesophageal and saliva metagenomes. Although no species was present in all oesophageal samples, 60 species occurred in at least one oesophageal metagenome from either study, with 50 identified in both cohorts. Conclusions. Recovery of genomes and discovery of new species represents an important step forward in our understanding of the oesophageal microbiome. The genes and genomes that we have released into the public domain will provide a base line for future comparative, mechanistic and intervention studies
Clinical implications and genetical insights of SOX6 expression in acute myeloid leukemia
Authors: Li Yan , Jiang Duanfeng , Zhang Qin , Liu Enyi , Shao Haigang 
Published: July 2022

Abstract
Background: Transcription factor SOX6 belongs to Sry‐related high‐mobility‐group box (SOX) family, has been reported to be downregulated and act as a tumor-suppressor gene in various solid tumors, but in acute myeloid leukemia (AML) is incompletely understood.Methods: The SOX6 expression was analyzed between AML patients and normal controls from public data and our research cohort. Correlations between SOX6 expression and clinical, genetic features together with survival were further analyzed.Results: In both public and our present datasets, we demonstrated that SOX6 expression is notably downregulated in AML patients compared with normal controls. Moreover, the expression level of SOX6 was dynamic, along with the disease status. SOX6 was significantly decreased in relapsed/refractory AML compared with complete remission AML. Clinically, SOX6 underexpression was signifcantly correlated with bone marrow blasts, and WBC counts. Furthermore, decreased expression of SOX6 was more common in core binding factor AML (CBF-AML), rarely found in complex karyotype AML (CK-AML), and correlated with FLT3 mutations. By survival analyses, low-expression of SOX6 was associated with shorter overall survival (OS) and event-free survival (EFS) among cytogenetic normal AML (CN-AML) patients. Moreover, both univariate and multivariate analyses showed that low SOX6 expression was an independent unfavorable prognostic biomarker for CN-AML.Conclusions: Our fndings indicated that SOX6 underexpression, as a frequent event in AML, was associated with genetic abnormalities and prognosis in AML. SOX6 might be a valuable biomarker for risk stratification, predicting prognosis and relapse of AML.
Hole-carrier-dominant transport in 2D single-crystal copper
Authors: Kang Kyungrok , Cheon Miyeon , Ok Jong Mok , Kim Su Jae , Lee Yousil , Regmi Binod , Kim Young-Hoon , Kim Young-Min , Kim Seong-Gon , Yang Heejun , Jeong Se-Young 
Published: July 2022

Abstract
The intrinsic nature of electronic transport has been screened by the carrier scattering at grain boundaries in two-dimensional noble metals, such as copper. Here, by realizing the impossible assumption of growing without grain boundaries in thin films, we demonstrate that the transport by hole carriers in 2D copper is the intrinsic nature, which has been screened by the scattering of carriers at grain boundaries. Unlike the grain boundaries, twin boundaries are invisible to conduction carriers, but even a slight tilt from regular twin boundaries is recognized as grain boundaries to electrons, so only complete suppression of grain boundaries can reveal the hidden hole-like characteristic of 2D-single crystal copper. The hole carriers can be explained by the concave Fermi surface of the 2D single-crystal copper, which suggests a breakthrough in manipulating the polarity of majority carriers in metals based on grain boundary engineering in a 2D geometry.
Logarithmic Harnack inequalities and differential Harnack estimates for p-Laplacian on Riemannian manifolds
Authors: Wang Yu-Zhao , Xue Yan 
Published: July 2022

Abstract
In this paper, we study logarithmic Harnack inequalities and differential Harnack estimates for p-Laplacian on Riemannian manifolds, We prove the logarithmic Harnack inequalities for Lp-log-Sobolev functions on Riemannian manifolds with Ricci curvature bounded below, which is related to the Lp-log-Sobolev constant. We obtain a new Li-Yau type differential Harnack estimates for positive solution to p-Laplacian parabolic equation with logarithmic nonlinearity. These results generalize the works of Chung-Yau, F.-Y. Wang and X. Cao ect. for the classic L2 case.Mathematics Subject Classification (2020). 58J05; 58J65
Effectiveness and safety of ustekinumab for the treatment of psoriasis in long-term clinical experience
Authors: Gönülal Melis , Öztürk Aylin , Doğan Sinan , Balcı Didem Didar 
Published: July 2022

Abstract
Background
This study aimed to investigate the long-term clinical experience with ustekinumab in patients with psoriasis.
Materials and methods
This retrospective cohort study group consisted of patients who presented to the dermatology outpatient clinics between January 2015 and January 2021, diagnosed with psoriasis, and were treated with ustekinumab. Data including gender, age, weight, disease duration, naïve and non-naïve status, psoriasis type, duration of medication, comorbidities, first psoriasis area and severity index (PASI) scores, the causes of treatment discontinuation, and previous treatments were retrospectively reviewed and analyzed.
Results
In total, 160 patients with psoriasis were treated with ustekinumab during the study period. Twenty-four cases were excluded. Among 136 patients, 84 (61,8%) were male and 52 (38,2%) were female patients. We found 80.55% of the non-naïve patients responded to ustekinumab treatment.
Conclusion
Ustekinumab can be an appropriate treatment option for non-naïve and resistant patients. Our findings suggest the positive effect persists in patients with favorable responses to the first or second dose of the ustekinumab treatment. Also, they showed male patients gave more rapid and more robust responses than female patients, and they were more enthusiastic about continuing the treatment.
Obtaining optical soliton solutions of the cubic-quartic Fokas-Lenells equation via three different analytical methods
Authors: Onder Ismail , Secer Aydin , Ozisik Muslum , Bayram Mustafa 
Published: July 2022

Abstract
In this study, we have focused on finding soliton solutions of the cubic-quartic Fokas-Lenells equation, which models the nonlinear pulse transmission through optical fiber, is a pretty new and updated model. We have used three different efficient analytical methods, namely, the Sinh-Gordon expansion method, enhanced modified extended tanh expansion method and unified Riccati equation expansion method. By modifying our proposed method and using it effectively, we have obtained much more optical solutions. We have supported the results with the 3D surface, 2D and contour plots of the soliton solutions, such as singular, periodic, periodic-singular, dark and M-shaped solitons. The originality of the method we propose is that it has never been used before. With the innovation of the method, we have obtained M-shaped solitons, which are very rarely obtainable in soliton waves. On the other hand, enhanced modified extended tanh expansion method have provided us more extra solutions. As the last and most important part, in order to examine physical behaviors, we have investigated the effect of the coefficient of the fourth order dispersion parameter on wave propagation by presenting the graphical representation.
Multifamily prevention approach for children and adolescents of parents with mental disorders
Authors: Tapias Eva , Vila-Badia Regina , Cárdenas M. , Ardévol I. , Lacasa F. , Ribalta T. , Pérez O. , Fuentes M. , Fumanal M.J , Vidal M. , Saltó C. , García A , Serrano C. , Ortiz E. , Grases N. , Coromina M 
Published: July 2022

Abstract
Introduction: 32% of children whose parents have mental condition are estimated to be diagnosed with some mental disorder later in life. As a consequence, a need arises to offer preventive psychological interventions aimed at these children. This article presents the results obtained after implementing the Kidstime programme. The aim of this paper is to investigate whether there are significant changes before and after the intervention and to establish participants´ degree of satisfaction with the program. Material and Methods: A design of repeated measures of pre-test and post-test intervention was used. 65 people participated in the program and pre-intervention and post-intervention data were obtained from 40 people through the following questionnaires: Self-Stigma Questionnaire (SSQ), Rosenberg´s self-esteem scale, Connor-Davidson Resilience Scale (CD-RISC), Parenting Practices Inventory (IPC), and strengths and difficulties questionnaire (SDQ). At the end of every workshop, a satisfaction survey was completed by children and adults, getting a total of 173 surveys. Results: Significant pre-post differences were found in the "involvement" and "expression of affection" subscales of the Parenting Patterns Inventory, as well as in children's "prosocial behavior" measured with the SDQ and in patients' self-stigma. There was no difference after intervention on other parameters. Conclusions: Kidstime program have shown to be effective in enhancing parents' emotional support for their children, improving children's prosocial behavior, and reducing patients´ stigma. It is believed that the resilience of children whose parents have mental issues can be fostered through this type of multidisciplinary, psycho-educational, playful intervention, which addresses parenting skills.
Gesture Recognition Using Deep Learning Techniques
Authors: Shukla Shubham 
Published: July 2022

Abstract
Sign language is a method of communication that uses hand gestures and movements rather than words. It is mostly used by Deaf or hearing-impaired individuals. The paper discusses the process of using the hand gestures for Gesture Recognition Based on deep convolutional neural networks (CNN). In this a custom CNN model of five layers is built from the scratch and trained over 2400 images of hand gestures to identify 26 alphabets and 10 numerical from 0 to 9. The diversity and complexity of gestures, on the other hand, have a significant influence on gesture recognition owing to the surroundings, light source, cover, and other considerations. To improve the characteristics of gesture identification, the hand skin color is filtered through the YCbCr color space to segregate the gesture region to be identified, and the noise of the gesture edge is processed using the Gaussian filter. Another task of Speech recognition, often known as speech-to-text, refers to a machine’s or program’s capacity to recognise and transform spoken words into legible text. The vocabulary of rudimentary voice recognition software is restricted, and it can only recognise words and sentences uttered clearly. The paper also discusses the neural networks’ pattern matching ability on audio signals for the speech recognition process. In this an audio is generated and recognised using speech recognition google API which results in text processing using NLP. As a result a GIF or hand gestures are output on the screen corresponding to the audio.
Voice Spoofing Countermeasure for Voice Replay Attacks using Deep Learning
Authors: Zhou Jincheng , Hai Tao , Jawawi Dayang N. A. , Wang Dang , Ibeke Ebuka , Biamba Cresantus 
Published: July 2022

Abstract
In our everyday lives, we communicate with each other using several means and channels of communication, as communication is crucial in the lives of humans. Listening and speaking are the primary forms of communication. For listening and speaking, the human voice is indispensable. Voice communication is the simplest type of communication. The Automatic Speaker Verification (ASV) system verifies users with their voices. These systems are susceptible to voice spoofing attacks - logical and physical access attacks. Recently, there has been a notable development in the detection of these attacks. Attackers use enhanced gadgets to record users' voices, replay it for the ASV system, and be granted access for harmful purposes. In this work, we propose a secure voice spoofing countermeasure for the purpose of detecting voice replay attacks. We enhanced the ASV system security by building a spoofing countermeasure dependent on the decomposed signals that consists of prominent information. We used two main features— the Gammatone Cepstral Coefficients and Mel-Frequency Cepstral Coefficients— for the audio representation. For the classification of the features, we used Bi-directional Long-Short Term Memory Network in cloud, a deep learning classifier. We investigated numerous audio features and examined each feature’s capability to obtain the most vital details from the audio for it to be labelled genuine or a spoof speech. Furthermore, we use various machine learning algorithms to illustrate the superiority of our system compared to the traditional classifiers. The results of the experiments were classified according to the parameters of accuracy, precision rate, recall, F1-score, and Equal Error Rate (EER). The results were 97\%, 100\%, 90.19\% and 94.84\%, and 2.95\%, respectively.
Examining the asymmetric relationship between the national development plan and poverty reduction in Nigeria: Quantile analysis from 1980-2019
Authors: Zaria Yusuf Bala 
Published: July 2022

Abstract
Employing quantile regression to examine the foreign assistance for development, external debt as in stock and real effective exchange rate means a consumer basket of goods and services average effect on poverty reduction in Nigeria. The result reveals the existence of an average short, medium and long term symmetric relationship. At the same time, foreign debt has a negative and significant average effect on poverty reduction in the short term. Also, shows a positive average but insignificant relationship in the short and long term. It implies the national development plan for poverty reduction is insignificant due to corruption and erratic inflation fluctuations.