bluuebunny/crossref_metadata_2025_split huggingface dataset:
Refactoring and performance analysis of the main CNN architectures: using false negative rate minimization to solve the Clinical Images Melanoma Detection Problem
Authors: Biasi Luigi Di , De Marco Fabiola , Citarella Alessia Auriemma , Castrillón-Santana Modesto , Barra Paola , Tortora Genoveffa 
Published: November 2022

Abstract
Background: Melanoma is one of the deadliest tumors in the world. Early detection is critical for first-line therapy in this tumor pathology and it remains challenging due to the need for histological analysis to ensure correctness in diagnosis. Therefore, multiple computer-aided diagnosis (CAD) systems working on melanoma images were proposed to mitigate the need of a biopsy. However, although the high global accuracy is declared in literature results, the CAD systems for the health fields must focus on the lowest false negative rate (FNR) possible to qualify as a diagnosis support system. The final goal must be to avoid classification type 2 errors to prevent life-threatening situations. Another goal could be to create an easy-to-use system for both physicians and patients.
Results: To achieve the minimization of type 2 error, we performed a wide exploratory analysis of the principal convolutional neural network (CNN) architectures published for the multiple image classification problem; we adapted these networks to the melanoma clinical image binary classification problem (MCIBCP). We collected and analyzed performance data to identify the best CNN architecture, in terms of FNR, usable for solving the MCIBCP problem. Then, to provide a starting point for an easy-to-use CAD system, we used a clinical image dataset (MED-NODE) because clinical images are easier to access: they can be taken by a smartphone or other hand-size devices. Despite the lower resolution than dermoscopic images, the results in the literature would suggest that it would be possible to achieve high classification performance by using clinical images. In this work, we used MED-NODE, which consists of 170 clinical images (70 images of melanoma and 100 images of naevi). We optimized the following CNNs for the MCIBCP problem: Alexnet, DenseNet, GoogleNet Inception V3, GoogleNet, MobileNet, ShuffleNet, SqueezeNet, and VGG16.
Conclusions: The results suggest that a CNN built on the VGG or AlexNet structure can ensure the lowest FNR (0.07) and (0.13), respectively. In both cases, discrete global performance is ensured. 73% (accuracy), 82% (sensitivity) and 59% (specificity) for VGG; 89% (accuracy), 87% (sensitivity) and 90% (specificity) for AlexNet.
"Comparison of sexual function of people with colorectal cancer with and without colostomy bag in Tabriz hospitals 2022"
Authors: Dahouri Amirmohammad , Sahebihagh Mohammadhassan , Gilani Neda 
Published: November 2022

Abstract
Cancer is a family of diseases unique to multicellular organisms characterized by uncontrolled growth and proliferation of cells. Gastrointestinal Cancer is one of the most common cancers associated with high mortality. Colon and rectal cancer are among the most critical public health problems worldwide, so nearly one million new colon and rectal cancer cases are diagnosed every year, and nearly half of the cases die. In 1999, Laumann and his colleagues defined sexual dysfunction as a significant public health problem. Many people who have survived colorectal Cancer are sexually active. These people can have problems with their sexual performance due to reasons such as therapeutic surgeries, radiotherapy, or the presence of an ostomy. This study is descriptive-comparative. To conduct the above study, 252 patients with colorectal Cancer were included in the study by a convenient method based on the inclusion criteria and after obtaining informed consent. The data collection tools included the demographic information form, the International Index of Erectile Function (IIEF), and the Women's Sexual Function Index (FSFI). The validity and reliability of these questionnaires have already been measured. Statistical analyzes were performed using IBM SPSS statistics version 24. According to the results of statistical analysis, the IIEF total score for men with a colostomy is 26.17 ± 15.30 and without a colostomy, is 29.05 ± 17.14, as well as the total FSFI score for women with a colostomy, is 7.21 ± 6.40 and without a colostomy is 14.67 ± 9.10. There was no statistically significant difference in the sexual performance score of men with pouches compared to men without pouches (P > 0.05). The sexual performance score of women with bags compared to women without bags had a lower sexual performance score, which was statistically significant (P < 0.05). Therefore, an ostomy in women causes a drop in FSFI. Health planners at the macro level and health service providers at the micro level should be aware of the importance of this issue and provide timely interventions to improve sexual performance and pay special attention to those aspects of FSFI that are of great importance.
Sustainable valorization of wood residue for the production of biofuel materials via continuous flow hydrothermal liquefaction
Authors: Acaru Silviu , Abdullah Rosnah , Lim Ren Chong 
Published: November 2022

Abstract
Almost half of the wood resulted from mass deforestation for infrastructure and agricultural developments is declared waste. To mitigate the impact and exploit renewable sources of energy sustainably it is paramount to explore their further utilizations. Hydrothermal liquefaction (HTL) technology holds the promise to convert biomass into biofuels. In this study, conversion of wood residue under continuous flow, subcritical HTL was investigated under two conditions; untreated and alkaline pretreated. Results show that 4% NaOH pretreatment increased the production of fermentation sugar, glucose, by 1.8-fold (equivalent to 90 g/L) and facilitated faster recovery times compared to raw wood. Also, at 0.2 MPa HTL, the alkaline pretreatment shifted the hydrolysis of arabinose and cellobiose to rhamnose and increased the fluid's acidity from pH of 6.1 to pH of 3.5. Under the pretreatment, the energy output from glucose reached 246 kJ and the average Net Energy Ratio for glucose during liquefaction reached values as high as 63%. These results will usher in new waste conversion methods into sustainable biofuels via continuous flow HTL, thereby supporting the green energy transition towards net zero.
A Partially Hidden Policy Attribute-based Encryption Supporting Outsourced Authentication and Attribute Revocation
Authors: Fan Kai , Du Lingwei , Li Wenhao , Bai Yuhan , Yang Yintang , Yang Kan , Li Hui 
Published: November 2022

Abstract
Ciphertext-Policy Attribute-based Encryption (CP-ABE) has been used as an important access control approach to protect the data security. The data owner uploads the access policy in the form of plaintext to the cloud, potentially disclosing personal information about the data owner. Hidden-Policy CP-ABE schemes have been proposed to partially hide the policy or fully hide the policy. However, such schemes may incur high overhead on identity authentication and user revocation. In this paper, we propose a new partially hidden policy CP-ABE (OAAR-PHP-ABE) to address the low authentication efficiency and lack of support for attribute revocation of existing PHP-CP-ABE schemes. We give the cloud server a portion of the calculation of the encryption parameters to complete during the encryption step. The final ciphertext is encrypted by data owners using the outsourced encrypted ciphertext, which reduces the data owner's computational workload. In the decryption phase, we divide the user's key into two parts: the outsourced decryption key and the user's secret key. The cloud use outsourced decryption keys to help users complete user authentication and partial decryption. Users just need to conduct an exponentiation operation to recover the plaintext after receiving the outsourced decrypted ciphertext, which can significantly reduce users' computational overhead. In addition, a dynamic revocation algorithm for users and attributes in the system is also designed.
Formulation Development And Evaluation Of Aegle Marmelos Polysaccharide As a Matrix Former
Authors: Patil Aishwarya , Gadade Deepak , Wakure Balaji 
Published: November 2022

Abstract
Background-
The goal of the whole study was to examine the formulation of tablets containing sustained-release metoprolol succinate employing Aegle marmelose (Bael), a member of the Rutaceae family, as the matrix forming polymer. Excipients play an important function in enhancing a formulation's quality.
Result-The use of aegle marmelose polymers in pharmacy is similar to that of synthetic polymers, which have a wide range of potential applications in innovative drug delivery systems as matrix formers. Due to the fact that these polysaccharide gums are naturally plentiful, biocompatible, biodegradable, and non-immunogenic, and because they boost the economy by giving people access to low-cost formulations made using locally accessible materials. In order to get the desired features of components for drug delivery systems, they can also be altered in a variety of ways, which makes them competitive with the synthetic additives that are now available. The formulation of metoprolol succinate matrix tablets uses the fruits of the Aegle marmelosto as a binder. The metoprolol succinate tablet was created using a 32 factorial design (F1 to F9), and from that F6 batch, tablets were tested for weight variation, hardness, friability, drug content, drug release research, stability study, solubility study, swelling property, and drug excipients compatibility..
Conclusion-Metoprolol succinate tablets that have been manufactured and tested for stability reveal no major alterations, making aegel marmalos polysaccharide a more suitable natural binder than synthetic one Additionally, the goal of the study was to determine the potential of natural polysaccharide.
Novelets: A New Primitive that Allows Online Detection of Emerging Behaviors in Time Series
Authors: Mercer Ryan , Keogh Eamonn 
Published: November 2022

Abstract
Much of the world’s data is time series. While offline exploration of time series can be useful, time series is almost unique in allowing the possibility of direct and immediate intervention. For example, if we are monitoring an industrial process and have an algorithm that predicts imminent failure, we could direct a controller to open a pressure release valve or initiate an evacuation plan. There is a plethora of tools to monitor time series for known behaviors (pattern matching), previously unknown highly conserved behaviors (motifs), evolving behaviors (chains) and unexpected behaviors (anomalies). In this work, we claim that there is another useful primitive, emerging behaviors, that are worth monitoring for. We call such behaviors Novelets. We explain that Novelets are not anomalies, chains, or motifs but can be informally thought of as initially apparent anomalies that are later discovered to be motifs. We will show that Novelets have a natural interpretation in many disciplines, including science, medicine, and industry. As we will further demonstrate, Novelet discovery can have many downstream uses, including prognostics and abnormal behavior detection. We will demonstrate the utility of our proposed primitive on a diverse set of challenging domains.
Torrential forced KdV equation : Soliton solutions over a hole
Authors: Beyoud Samira 
Published: November 2022

Abstract
Torrential flow of an incompressible and a perfect fluid over a hole is investigated in infinite channel, with a focus on the steady case of the governed equation. The flow is supposed to be two-dimensional and irrotational. The problem studied here included just the influence of the gravity $g$ and the surface-tension effects are neglected. The issue has been programed and run on a computer to solve a nonlinear ordinary differential equation of the third order, called the forced Korteweg de Vries equation. The obtained results in the torrential flow, have been represented graphically by varying the shape of the hole, its cavity, and also the value of the Froude number λ.
Robust Control Allocation Method for Uncertain Systems Based on the Algorithms of Maximum-minimum and Improved Fish Swarm
Authors: Yang Xingyuan , Tong Xi , Fang Yangwang 
Published: November 2022

Abstract
In this paper, a novel robust control allocation method for a control system with uncertain parameters is proposed based on the algorithms of maximum-minimum and improved fish swarm. Based on the algorithm of maximum-minimum, the control allocation problem with an uncertain allocation matrix is transformed into the definite control allocation problem; then by using an improved fish swarm algorithm, the resultant control allocation problem is solved. Finally, the simulation results show that the proposed robust control allocation method has better robustness to system modeling uncertainty and possesses stronger anti-interference ability than the existing control allocation methods.
Accurate TDOA Localization Based On Trajectory Prediction to Deal With Positioning Nodes Failure
Authors: Liu XiangLi , Yu HongBo , Li Zan 
Published: November 2022

Abstract
The multi-point cooperative TDOA positioning can achieve good positioning accuracy. But when some positioning nodes are blocked or fail, the positioning equation will be unsolved and lead to the failure location algorithm. A TDOA localization algorithm based on trajectory prediction is proposed to deal with the positioning nodes failure. Firstly, based on the target trajectory before the failure of the location node, the trajectory of the target in the next stage is predicted by machine learning. Then the predicted trajectory information is used to estimate the information of the failed node, so as to realize the solution of the TDOA positioning equation. The proposed algorithm is verified through the positioning error analysis comapared with other positioning strategies.
Superfluid drain vortex
Authors: Ruffenach Wandrille , Galantucci Luca , Barenghi Carlo F. 
Published: November 2022

Abstract
Drain vortices are among the most common vortices observed in everyday life, yet their physics is complex due to the competition of vorticity's transport and diffusion, and the presence of viscous layers and a free surface. Recently, it has become possible to study experimentally drain vortices in superfluid liquid helium, a fluid in which the physics is simplified by the absence of viscosity and the quantisation of the circulation. Using the Gross-Pitaevskii equation, we make a simple model of the problem which captures the essential physics ingredients, showing that the superfluid drain vortex consists of a bundle of vortex lines which twist, thus strengthening the axial flow into the drain.
Accurate Broadband Balanced Terahertz Tripler Design with Thermal and High-Frequency Effects
Authors: Wei Haomiao , Zhang Yong , Cui Jianhang , Liu Xiaoyu , Wang Li , Chen Yang 
Published: November 2022

Abstract
This paper presents an accurate design method applied to the terahertz broadband multipliers. The design method is divided into two steps: a self-consistent electro-thermal (E-T) model with frequency-dependent spreading resistance and an external matching circuit. The self-consistent electro-thermal model consists of three parts: the steady-state thermal model, the electro-thermal diode circuit model, and the three-dimensional (3-D) electromagnetic (EM) model. The steady-state thermal model and the electro-thermal diode circuit model are used to express the thermal effects of diode. In particular, in the EM model, a frequency-dependent spreading resistance is obtained by the fitting conductivity of actual doped buffer layers and extracted by the auxiliary circuit structures, which is used to express the high-frequency effects. Then, the external matching circuit is designed carefully to match external wideband response instead of single frequency point load-pull. Based on the design approach, a balanced 225–300 GHz frequency tripler with AlN substrate has been designed and manufactured. By introducing the high frequency spreading resistance, a better simulated-measured consistency is achieved compared to the single E-T model, no matter low input power (80 mW) or high input power (160 mW) condition.
Improving the swimming route optimization algorithm based on big data cloud computing and directional distance sequence processing
Authors: Song Qi 
Published: November 2022

Abstract
As the times become more and more informational, people's physical fitness is gradually decreasing, and many people can't even swim through a small pond. This is very fatal for people going out and encountering sudden falls. This paper aims to study the improvement of the swimming path selection algorithm based on big data cloud computing and sequential direction distance processing.This paper adopts experimental comparison method and experimental analysis method, using big data technology, optimizes and improves the swimming route based on the idea of directional distance sequential processing, and builds a Mamdani-type fuzzy system to quickly introduce the final result. The experimental results in this article show that the efficiency of the algorithm optimized from the direction alone or from the distance is far better than the sequential processing optimization of the first direction and then the distance. The efficiency of the direction and distance sequential processing is about 1/3 higher than the efficiency of the direction optimization, but It is about 3 times more efficient than optimizing the distance! For an algorithm, this improvement is very exaggerated. The improvement of the swimming route optimization algorithm based on big data cloud computing and direction and distance order processing will have important social significance.
Pay Attention To The Global Component: An Effective Defense Approach against Adversarial Attacking
Authors: Xu Jianfeng , Feng Xiaowei 
Published: November 2022

Abstract

Deep neural networks (DNNs) approaches have been widely applied for real-world machine learning applications. However, they were shown to be vulnerable to adversarial attacks. Nature images blended with human indistinguishable perturbations, so-called adversarial samples, can cause mis-classification of DNNs. On the other hand, recent defense approaches still suffer from strong attacks. This paper proposes a Matrix-Completion and Component Attention (MCCA) framework, a novel defense framework that leverages matrix completion and attention mechanism to defend the DNNs against adversarial attacks. MCCA would process the input (perturbed) images by two steps: firstly, the matrix completion is applied on the randomly masked inputs to execute the “reconstruc-tion” process; then, the reconstructed images will go through a DNN attached with flexible “attention” modules to enhance its classification performance. We show that the mask-reconstruction process can clear the area poisoned by perturbation, and maintain the global component in the processed image; while the attention module will capture such global component during the feed-forward phase, further make the DNNs focus on the area of major component during the classification step. These two processes would make the DNNs consistent with the typical perception of human beings. We conduct comprehensive experiments on three image benchmarks, comparing MCCA with state-of-the-art defense approaches. The quantitative comparisons demonstrate that our defense approach consistently outperforms prior techniques, improving the robustness against both black-box and white-box attacks.
Inter-rater reliability of the extended Composite Quality Score (CQS-2) – a pilot study
Authors: Mickenautsch Steffen , Rupf Stefan , Miletić Ivana , Strähle Ulf Tilman , Sturm Richard , Dhansay Faheema Kimmie- , Vidosusić Kata , Yengopal Veerasamy 
Published: November 2022

Abstract
Aim
To establish the inter-rater reliability of the Composite Quality Score (CQS)-2 and to test the null hypothesis that it did not differ significantly from that of the first CQS version (CQS-1).
Materials and methods
Four independent raters from three countries were selected to rate 45 clinical trial reports using CQS-1 and CQS-2. The raters remained unaware of each other’s participation in this study until all rating had been completed. Each rater received only one rating template at a time in a random sequence for CQS-1 and CQS-2 rating. Raters completed each template and sent these back to the principal investigator. Each rater received their next template two weeks after submission of the completed previous template. The inter-rater reliabilities for the overall appraisal score of the CQS-1 and the CQS-2 were established by using the Brennan-Prediger coefficient (BPC). The coefficients of both CQS versions were compared by using the two-sample z-test. During secondary analysis, the BPCs for every criterion and each corroboration level for both CQS versions were established.
Results
The BPC for the CQS-1 was 0.85 (95% CI: 0.64–1.00) and for the CQS-2 it was 1.00 (95% CI: 0.94–1.00), suggesting a very high inter-rater reliability for both. The difference between the two CQS versions was statistically not significant (p = 0.17). The null hypothesis was accepted.
Conclusion
This study shows that the CQS-2 is associated with a very high inter-rater reliability, which did not statistically significantly differ from that of the CQS-1. The promising results of this study warrant further investigation in the applicability of the CQS-2 as an appraisal tool for prospective controlled clinical therapy trials.
Türkiye’de Karadeniz’in Farklı Bölgelerinde Üretilen Balık Unlarının Hayvan Besleme Açısından Değeri
Authors: ALDEMİR Reşit , TEKELİ Ahmet , ÜSTÜNDAĞ Berk , BİLGEÇLİ Kazım , BAYKAL ÇELİK Ladine 
Published: November 2022

Balık unu gerek insan tüketimine uygun olmayan balıkların, gerekse balıkçılık endüstrisinde arta kalan atıkların işlenip
kurutulması veya çeşitli teknolojik işlemlerden geçirilmesi sonucu elde edilmektedir. Balıkçılık endüstrisinin iki ana temel
ürünlerinden biri olan balık unu, yüksek aminoasit, vitamin ve mineral madde içeriğiyle yüksek sindirilebilirliğe sahip bir protein
kaynağı olarak yemlerde kullanılmaktadır. Balık ununu diğer yem hammaddelerinden üstün kılan en önemli özelliklerden biri de
içerdiği esansiyel aminoasitler ve uzun zincirli çoklu doymamış yağ asitleridir. Balık ununun rasyona katılması ile genç
hayvanlarda performans ve bağışıklık sistemi olumlu etkilenmektedir. Balık ununun kanatlı rasyonlarına %3-10, sığır ve koyun
rasyonlarına %5, domuz rasyonlarına da %10 katılabileceği ifade edilmektedir. Türkiye’de balık unu ve yağı üretiminin önemli
kısmı Karadeniz Bölgesinde yapılmaktadır. Bu çalışmada, Karadeniz Bölgesinde yer alan dört farklı balık unu fabrikasında alınan
balık unlarının besin madde içeriği değerlendirilmiştir. Buna göre en yüksek değerler; kuru madde (KM) %95.90 (p&lt;0.0001) ve
ham kül (HK) %17.20 (p&lt;0.0001) ile D, ham protein (HP) %73.40 (p&lt;0.0001) ile A, ham yağ (HY) %11.33 (p&lt;0.01) ile B,
metabolik enerji (ME, kanatlı) 3537.5 Kcal kg-1
(p&lt;0.001) ile B fabrikasında tespit edilmiştir. Çalışmada genel olarak bütün
amino asitler bakımından en yüksek değerler A fabrikasında, en düşük değerler D fabrikasında elde edilmiştir (p&lt;0.0001).
Esansiyel yağ asitlerinden linoleik ve linolenik asit miktarları bakımından fabrikalar arasında istatistiksel bir farkın olmadığı
(p˃0.01), palmitik asit, palmitoleik asit ve oleik asit düzeylerinin ise önemli düzeyde (p˃0.001) B fabrikasında görüldüğü tespit
edilmiştir. Ülkemizde yaygın olarak Karadeniz Bölgesinde üretilen balık unları arasında besin madde bileşenleri açısından
farklılık olduğu belirlenmiştir