bluuebunny/crossref_metadata_2025 huggingface dataset:
Supplementary Figure 6 from Discovery and Characterization of Novel Mutant FLT3 Kinase Inhibitors
Authors: Weisberg Ellen , Choi Hwan Geun , Barrett Rosemary , Zhou Wenjun , Zhang Jianming , Ray Arghya , Nelson Erik A. , Jiang Jingrui , Moreno Daisy , Stone Richard , Galinsky Ilene , Fox Edward , Adamia Sophia , Kung Andrew L. , Gray Nathanael S. , Griffin James D.
Published: April 2023

Supplementary Figure 6 from Discovery and Characterization of Novel Mutant FLT3 Kinase Inhibitors
Supplementary Figure 5F from Discovery and Characterization of Novel Mutant FLT3 Kinase Inhibitors
Authors: Weisberg Ellen , Choi Hwan Geun , Barrett Rosemary , Zhou Wenjun , Zhang Jianming , Ray Arghya , Nelson Erik A. , Jiang Jingrui , Moreno Daisy , Stone Richard , Galinsky Ilene , Fox Edward , Adamia Sophia , Kung Andrew L. , Gray Nathanael S. , Griffin James D.
Published: April 2023

Supplementary Figure 5F from Discovery and Characterization of Novel Mutant FLT3 Kinase Inhibitors
Supplementary Table S1 from Keratin down-regulation in vimentin-positive cancer cells is reversible by vimentin RNA interference, which inhibits growth and motility
Authors: Paccione Rachel J. , Miyazaki Hiroshi , Patel Vyomesh , Waseem Ahmad , Gutkind J. Silvio , Zehner Zendra E. , Yeudall W. Andrew
Published: April 2023

Supplementary Table S1 from Keratin down-regulation in vimentin-positive cancer cells is reversible by vimentin RNA interference, which inhibits growth and motility
Supplementary Data from Docetaxel-Resistant Prostate Cancer Cells Remain Sensitive to S-Trityl-l-Cysteine–Mediated Eg5 Inhibition
Authors: Wiltshire Carolyn , Singh Babloo L. , Stockley Jacqueline , Fleming Janis , Doyle Brendan , Barnetson Robert , Robson Craig N. , Kozielski Frank , Leung Hing Y.
Published: April 2023

Supplementary Data from Docetaxel-Resistant Prostate Cancer Cells Remain Sensitive to S-Trityl-l-Cysteine–Mediated Eg5 Inhibition
Supplementary Fig. S2 from In vivo silencing of a molecular target by short interfering RNA electroporation: tumor vascularization correlates to delivery efficiency
Authors: Takei Yoshifumi , Nemoto Toshio , Mu Ping , Fujishima Tatsuya , Ishimoto Takuji , Hayakawa Yasuhiko , Yuzawa Yukio , Matsuo Seiichi , Muramatsu Takashi , Kadomatsu Kenji
Published: April 2023

Supplementary Fig. S2 from In vivo silencing of a molecular target by short interfering RNA electroporation: tumor vascularization correlates to delivery efficiency
Supplementary Table S2 from Artemin-Stimulated Progression of Human Non–Small Cell Lung Carcinoma Is Mediated by BCL2
Authors: Tang Jian-Zhong , Kong Xiang-Jun , Kang Jian , Fielder Graeme C. , Steiner Michael , Perry Jo K. , Wu Zheng-Sheng , Yin Zhinan , Zhu Tao , Liu Dong-Xu , Lobie Peter E.
Published: April 2023

Quantitative PCR analyses of gene expression pattern upon forced expression of ARTN in H1299 cells
Supplementary Data from Tolfenamic acid enhances pancreatic cancer cell and tumor response to radiation therapy by inhibiting survivin protein expression
Authors: Konduri Santhi , Colon Jimmie , Baker Cheryl H. , Safe Stephen , Abbruzzese James L. , Abudayyeh Ala , Basha Md. Riyaz , Abdelrahim Maen
Published: April 2023

Supplementary Data from Tolfenamic acid enhances pancreatic cancer cell and tumor response to radiation therapy by inhibiting survivin protein expression
Supplementary Table 1 from Evaluation of Selective γ-Secretase Inhibitor PF-03084014 for Its Antitumor Efficacy and Gastrointestinal Safety to Guide Optimal Clinical Trial Design
Authors: Wei Ping , Walls Marlena , Qiu Ming , Ding Richard , Denlinger Robert H. , Wong Anthony , Tsaparikos Kosta , Jani Jitesh P. , Hosea Natilie , Sands Michelle , Randolph Sophia , Smeal Tod
Published: April 2023

Supplementary Table 1 from Evaluation of Selective γ-Secretase Inhibitor PF-03084014 for Its Antitumor Efficacy and Gastrointestinal Safety to Guide Optimal Clinical Trial Design
Supplementary Figure 7 from GSK1838705A inhibits the insulin-like growth factor-1 receptor and anaplastic lymphoma kinase and shows antitumor activity in experimental models of human cancers
Authors: Sabbatini Peter , Korenchuk Susan , Rowand Jason L. , Groy Arthur , Liu Qi , Leperi Dominic , Atkins Charity , Dumble Melissa , Yang Jingsong , Anderson Kelly , Kruger Ryan G. , Gontarek Richard R. , Maksimchuk Kenneth R. , Suravajjala Sapna , Lapierre Russell R. , Shotwell J. Brad , Wilson Joseph W. , Chamberlain Stanley D. , Rabindran Sridhar K. , Kumar Rakesh
Published: April 2023

Supplementary Figure 7. Effect of GSK1838705 on ALK-driven tumor cells in vitro.
Supplementary Figure 5 from GSK1838705A inhibits the insulin-like growth factor-1 receptor and anaplastic lymphoma kinase and shows antitumor activity in experimental models of human cancers
Authors: Sabbatini Peter , Korenchuk Susan , Rowand Jason L. , Groy Arthur , Liu Qi , Leperi Dominic , Atkins Charity , Dumble Melissa , Yang Jingsong , Anderson Kelly , Kruger Ryan G. , Gontarek Richard R. , Maksimchuk Kenneth R. , Suravajjala Sapna , Lapierre Russell R. , Shotwell J. Brad , Wilson Joseph W. , Chamberlain Stanley D. , Rabindran Sridhar K. , Kumar Rakesh
Published: April 2023

Supplementary Figure 5. Anti-tumor activity of GSK1838705A in additional xenografts.
Supplementary Table 4 from Combinatorial pharmacologic approaches target EZH2-mediated gene repression in breast cancer cells
Authors: Sun Feng , Chan Eli , Wu Zhenlong , Yang Xiaojing , Marquez Victor E. , Yu Qiang
Published: April 2023

Supplementary Table 4 from Combinatorial pharmacologic approaches target EZH2-mediated gene repression in breast cancer cells
Supplementary Figure 1 from Combinatorial pharmacologic approaches target EZH2-mediated gene repression in breast cancer cells
Authors: Sun Feng , Chan Eli , Wu Zhenlong , Yang Xiaojing , Marquez Victor E. , Yu Qiang
Published: April 2023

Supplementary Figure 1 from Combinatorial pharmacologic approaches target EZH2-mediated gene repression in breast cancer cells
Adobe PDF - MCT-07-0312--Suppl_Fig_S2.pdf from Exemestane's 17-hydroxylated metabolite exerts biological effects as an androgen
Authors: Ariazi Eric A. , Leitão Andrei , Oprea Tudor I. , Chen Bin , Louis Teresa , Bertucci Anne Marie , Sharma Catherine G.N. , Gill Shaun D. , Kim Helen R. , Shupp Heather A. , Pyle Jennifer R. , Madrack Alexis , Donato Anne L. , Cheng Dong , Paige James R. , Jordan V. Craig
Published: April 2023

Adobe PDF - MCT-07-0312--Suppl_Fig_S2.pdf from Exemestane's 17-hydroxylated metabolite exerts biological effects as an androgen
Supplementary Fig. S1 from EphA4 promotes cell proliferation and migration through a novel EphA4-FGFR1 signaling pathway in the human glioma U251 cell line
Authors: Fukai Junya , Yokote Hideyuki , Yamanaka Ryuya , Arao Tokuzo , Nishio Kazuto , Itakura Toru
Published: April 2023

Supplementary Fig. S1 from EphA4 promotes cell proliferation and migration through a novel EphA4-FGFR1 signaling pathway in the human glioma U251 cell line
Supplementary Table S1 from Molecular mechanisms of the antiangiogenic and antitumor effects of mycophenolic acid
Authors: Domhan Sophie , Muschal Stefan , Schwager Christian , Morath Christian , Wirkner Ute , Ansorge Wilhelm , Maercker Christian , Zeier Martin , Huber Peter E. , Abdollahi Amir
Published: April 2023

Supplementary Table S1 from Molecular mechanisms of the antiangiogenic and antitumor effects of mycophenolic acid
Supplementary Data from ZD6474, a Multitargeted Inhibitor for Receptor Tyrosine Kinases, Suppresses Growth of Gliomas Expressing an Epidermal Growth Factor Receptor Mutant, EGFRvIII, in the Brain
Authors: Yiin Jia-Jean , Hu Bo , Schornack Paul A. , Sengar Raghvendra S. , Liu Kun-wei , Feng Haizhong , Lieberman Frank S. , Chiou Shih-Hwa , Sarkaria Jann N. , Wiener Erik C. , Ma Hsin-I , Cheng Shi-Yuan
Published: April 2023

Supplementary Data from ZD6474, a Multitargeted Inhibitor for Receptor Tyrosine Kinases, Suppresses Growth of Gliomas Expressing an Epidermal Growth Factor Receptor Mutant, EGFRvIII, in the Brain
Supplementary Table S1 from AMG 479, a fully human anti–insulin-like growth factor receptor type I monoclonal antibody, inhibits the growth and survival of pancreatic carcinoma cells
Authors: Beltran Pedro J. , Mitchell Petia , Chung Young-A , Cajulis Elaina , Lu John , Belmontes Brian , Ho Joanne , Tsai Mei Mei , Zhu Min , Vonderfecht Steven , Baserga Renato , Kendall Richard , Radinsky Robert , Calzone Frank J.
Published: April 2023

Supplementary Table S1 from AMG 479, a fully human anti–insulin-like growth factor receptor type I monoclonal antibody, inhibits the growth and survival of pancreatic carcinoma cells
Supplementary Table 2 from Paclitaxel-Dependent Cell Lines Reveal a Novel Drug Activity
Authors: Ganguly Anutosh , Yang Hailing , Cabral Fernando
Published: April 2023

Supplementary Table 2 from Paclitaxel-Dependent Cell Lines Reveal a Novel Drug Activity
Supplementary Figure 1 from miR-192/miR-215 Influence 5-Fluorouracil Resistance through Cell Cycle-Mediated Mechanisms Complementary to Its Post-transcriptional Thymidilate Synthase Regulation
Authors: Boni Valentina , Bitarte Nerea , Cristobal Ion , Zarate Ruth , Rodriguez Javier , Maiello Evaristo , Garcia-Foncillas Jesus , Bandres Eva
Published: April 2023

Supplementary Figure 1 from miR-192/miR-215 Influence 5-Fluorouracil Resistance through Cell Cycle-Mediated Mechanisms Complementary to Its Post-transcriptional Thymidilate Synthase Regulation
Supplementary Figure 6 from Lipoxin A4 and Its Analogue Suppress the Tumor Growth of Transplanted H22 in Mice: The Role of Antiangiogenesis
Authors: Chen Ying , Hao Hua , He Songqing , Cai Lei , Li Yongsheng , Hu Shunze , Ye Duyun , Hoidal John , Wu Ping , Chen Xiaoping
Published: April 2023

Supplementary Figure 6 from Lipoxin A4 and Its Analogue Suppress the Tumor Growth of Transplanted H22 in Mice: The Role of Antiangiogenesis
Supplementary Figure 2 from Lipoxin A4 and Its Analogue Suppress the Tumor Growth of Transplanted H22 in Mice: The Role of Antiangiogenesis
Authors: Chen Ying , Hao Hua , He Songqing , Cai Lei , Li Yongsheng , Hu Shunze , Ye Duyun , Hoidal John , Wu Ping , Chen Xiaoping
Published: April 2023

Supplementary Figure 2 from Lipoxin A4 and Its Analogue Suppress the Tumor Growth of Transplanted H22 in Mice: The Role of Antiangiogenesis
Supplementary Figure 1 from Lipoxin A4 and Its Analogue Suppress the Tumor Growth of Transplanted H22 in Mice: The Role of Antiangiogenesis
Authors: Chen Ying , Hao Hua , He Songqing , Cai Lei , Li Yongsheng , Hu Shunze , Ye Duyun , Hoidal John , Wu Ping , Chen Xiaoping
Published: April 2023

Supplementary Figure 1 from Lipoxin A4 and Its Analogue Suppress the Tumor Growth of Transplanted H22 in Mice: The Role of Antiangiogenesis
Supplementary Figure 1 from Rapamycin Regulates Stearoyl CoA Desaturase 1 Expression in Breast Cancer
Authors: Luyimbazi David , Akcakanat Argun , McAuliffe Priscilla F. , Zhang Li , Singh Gopal , Gonzalez-Angulo Ana Maria , Chen Huiqin , Do Kim-Anh , Zheng Yuhuan , Hung Mien-Chie , Mills Gordon B. , Meric-Bernstam Funda
Published: April 2023

Supplementary Figure 1 from Rapamycin Regulates Stearoyl CoA Desaturase 1 Expression in Breast Cancer
Supplementary Fig. S7 from Dual silencing of insulin-like growth factor-I receptor and epidermal growth factor receptor in colorectal cancer cells is associated with decreased proliferation and enhanced apoptosis
Authors: Kaulfuβ Silke , Burfeind Peter , Gaedcke Jochen , Scharf Jens-Gerd
Published: April 2023

Supplementary Fig. S7 from Dual silencing of insulin-like growth factor-I receptor and epidermal growth factor receptor in colorectal cancer cells is associated with decreased proliferation and enhanced apoptosis
Supplementary Fig. S5 from Dual silencing of insulin-like growth factor-I receptor and epidermal growth factor receptor in colorectal cancer cells is associated with decreased proliferation and enhanced apoptosis
Authors: Kaulfuβ Silke , Burfeind Peter , Gaedcke Jochen , Scharf Jens-Gerd
Published: April 2023

Supplementary Fig. S5 from Dual silencing of insulin-like growth factor-I receptor and epidermal growth factor receptor in colorectal cancer cells is associated with decreased proliferation and enhanced apoptosis
Supplementary Fig. S2 from Dual silencing of insulin-like growth factor-I receptor and epidermal growth factor receptor in colorectal cancer cells is associated with decreased proliferation and enhanced apoptosis
Authors: Kaulfuβ Silke , Burfeind Peter , Gaedcke Jochen , Scharf Jens-Gerd
Published: April 2023

Supplementary Fig. S2 from Dual silencing of insulin-like growth factor-I receptor and epidermal growth factor receptor in colorectal cancer cells is associated with decreased proliferation and enhanced apoptosis
Adobe PDF - MCT-06-0552--Suppl_Table_S2.pdf from Preclinical selection of a novel poly(ADP-ribose) polymerase inhibitor for clinical trial
Authors: Thomas Huw D. , Calabrese Christopher R. , Batey Michael A. , Canan Stacie , Hostomsky Zdenek , Kyle Suzanne , Maegley Karen A. , Newell David R. , Skalitzky Donald , Wang Lan-Zhen , Webber Stephen E. , Curtin Nicola J.
Published: April 2023

Adobe PDF - MCT-06-0552--Suppl_Table_S2.pdf from Preclinical selection of a novel poly(ADP-ribose) polymerase inhibitor for clinical trial
Supplementary Table S3 from Reversine, a novel Aurora kinases inhibitor, inhibits colony formation of human acute myeloid leukemia cells
Authors: D'Alise Anna Morena , Amabile Giovanni , Iovino Mariangela , Di Giorgio Francesco Paolo , Bartiromo Marta , Sessa Fabio , Villa Fabrizio , Musacchio Andrea , Cortese Riccardo
Published: April 2023

Supplementary Table S3 from Reversine, a novel Aurora kinases inhibitor, inhibits colony formation of human acute myeloid leukemia cells
Supplementary Table S1 from Reversine, a novel Aurora kinases inhibitor, inhibits colony formation of human acute myeloid leukemia cells
Authors: D'Alise Anna Morena , Amabile Giovanni , Iovino Mariangela , Di Giorgio Francesco Paolo , Bartiromo Marta , Sessa Fabio , Villa Fabrizio , Musacchio Andrea , Cortese Riccardo
Published: April 2023

Supplementary Table S1 from Reversine, a novel Aurora kinases inhibitor, inhibits colony formation of human acute myeloid leukemia cells
Supplementary Figure Legend from Small Interfering RNA Targeting 14-3-3ζ Increases Efficacy of Chemotherapeutic Agents in Head and Neck Cancer Cells
Authors: Matta Ajay , DeSouza Leroi V. , Ralhan Ranju , Siu K.W. Michael
Published: April 2023

Supplementary Figure Legend from Small Interfering RNA Targeting 14-3-3ζ Increases Efficacy of Chemotherapeutic Agents in Head and Neck Cancer Cells
Supplementary Fig. S3 from Multiple signaling pathways must be targeted to overcome drug resistance in cell lines derived from melanoma metastases
Authors: Smalley Keiran S.M. , Haass Nikolas K. , Brafford Patricia A. , Lioni Mercedes , Flaherty Keith T. , Herlyn Meenhard
Published: April 2023

Supplementary Fig. S3 from Multiple signaling pathways must be targeted to overcome drug resistance in cell lines derived from melanoma metastases
Simulation and harmonic analysis of hybrid distributed energy generation based microgrid system using intelligent technique
Authors: Kaur Jaspreet , Khosla Anita
Published: April 2023

Wind and solar photovoltaic (PV) based hybrid renewable energy generation are environmentally friendly and reasonable. This study describes a hybrid distributed energy generations (DEGs)-based microgrid framework where DC-DC converter, three-stage inverter with fuzzy logics control (FLC), and LC filter channel are coupled with the PV and wind energy. In India, wind and PV energies are affordable for hybrid power frameworks since they are ecological well-disposed and broadly accessible. Generally, these sources produce a fluctuating yield voltage that prompts harm to the working grid on a steady inventory. The proposed model of the hybrid-based framework is executed utilizing MATLAB/Simulink. A boost converter being associated with PV cluster is associated with the basic DC bus also a battery is used by a two-way DC to DC converter, and connected into the utility framework by a typical DC to AC inverter. Wind cluster and PV is linked with maximum power point tracking (MPPT) to produce the higher capacity to the grid, and the charging and discharging of the battery energy can be done to adjust the energy between DEGs generation and utility network. In this paper, various cases of harmonic analysis are executed on MATLAB-simulation and feasibility of proposed grid models and FLC-based intelligent control.
A 48-MW floating photovoltaic design and integration to a grid
Authors: Adrianti Adrianti , Kurnia Agung Thoriq , Nasir Muhammad , Anugrah Pinto
Published: April 2023

Photovoltaic is one of the renewable power sources with the highest growth in recent decades. However, large photovoltaic capacities require enormous areas for installing the modules, which is frequently troublesome. This issue could be addressed by a floating photovoltaic system since it can be installed on the surface of unutilised lakes, and dams. This study aims to design a 48-MW floating photovoltaic at Lake Singkarak and determine a connected substation to the West Sumatra Grid. PVsystem and digsilent powerfactory were used in this study as the calculation and simulation tools. The study’s results discover that the 48-MW floating photovoltaic design consists of 96,000 photovoltaic modules of 500 Wp and 16 inverters of 3,000 kVA. Simulation results showed that Solok substation is the most optimum choice to connect the floating PV, as it provides better voltage profiles, fewer power losses and a shorter distance. The harmonic simulation also showed the THDv of 2.14% at 150 kV of Solok substation, which is still within acceptable limits.
Assessment of a single-phase single-stage grid-connected photovoltaic system
Authors: Anang Nurhazwani , Mariam Wan Muda Wan , Zalani Daud Muhamad
Published: April 2023

A grid-connected photovoltaic (GCPV) system plays an important role in the development of green technology. However, generated photovoltaic (PV) power that is injected into the grid causes instability in the grid system. Previous studies have shown that power quality for a three-phase system is thoroughly being discussed, but not for a single-phase system. Single-phase system also contribute to instability in low-voltage grid networks during high power penetration as majority of the single-phase GCPV nowadays are installed on rooftops. Thus, in this study, the power quality of a single-phase single-stage GCPV system is investigated based on the total harmonic distortion (THD), power factor (PF), and the generated active (P) and reactive (Q) power during different solar irradiance and varying loads conditions. A model of the GCPV system was developed in MATLAB/Simulink, so that certain variables can be varied to observe their effect towards the power quality. The results show that the current and voltage of generated PV power are synchronized and having low current THD which is less than 1% for all cases. PF values are also in the acceptable range in compliance to IEC 61727 standard which is 0.9971, and the generated PQ is in accordance to the connected load.
Soil pH periodic assortment with smart irrigation using aerial triboelectric nanogenerator
Authors: Karthikeyan Dhandapani , Kannan Deeba , Gunasekaran Brindha , Selvaraj Hemalatha , Gupta Saurabh , Ramkumar Ravindran , Vijayakumar Krishnasamy
Published: April 2023

The paper presents an idea on pre-emptively ascertaining the soil pH value on an agriculture field amalgaming drone for aerial photo and subsequent smart irrigation model with the help of internet of things (IoT). The drone used for the aerial footage (multispectral imaging) consists of specialized cameras with filters that would help in ascertaining vegetation and health of the crops in the agriculture land. The IoT device used in smart irrigation model consists of sensors which accumulate data and execute the commands given in a recurring fashion of delay. Moreover, the use of triboelectric nanogenerator (TENG) would help in feasible energy harvesting for agricultural land use.
An integrated multi-level feature fusion framework for crowd behaviour prediction and analysis
Authors: Yadakere Murthygowda Manu , Guralamata Krishnegowda Ravikumar , Salekoppalu Venkataramu Shashikala
Published: April 2023

The uncontrolled outburst in population has led to crowd gatherings in various public places causing panic and disaster in certain unpleasant and extreme conditions. A study on the analysis of crowd accumulation has been carried out for various reasons that include management of crowd, design of a well-planned public space, the possibility for surveillance at every area and transportation systems. A lot of disasters also occurs due to uncontrollable crowd behaviour and poor crowd management. It could result in loss of property, fatalities or casualties. To avoid this, the conduct of a crowd of people has been studied and analyzed to control their movement and traffic. Hence, in this research work, integrated multi-level feature fusion (IMFF) framework is designed to predict the behaviour; further classification based on the local region is carried out to enhance the prediction. In the case of multi-level feature fusion; first level feature fusion utilizes the motion and appearance; second-level feature fusion utilizes the spatial connection and third-level utilizes the temporal connections. Further, the classification approach is integrated based on the local region is used to enhance the crowd behaviour prediction in terms of accuracy and faster. Moreover, performance evaluation is carried out considering the two distinctive datasets.
Harmful gases detection using artificial neural networks of the environment
Authors: Rai Pratiksha , Hasan Saeed Syed , Om Mishra Shri
Published: April 2023

This work describes a small, low-cost electronic nose device which can detect harmful substances that can harm human health, such as flammable gas like acetone, ethanol, butane as well as methane, among others. An artificial olfactory instrument consists of a set of metal oxide semiconductor sensors as well as a computer-based communications channel for signal gathering, proceeding, and presentation. We used three sensors instead of six, and the results were plotted as a variance, score as well as loading plot with crossvalidation. For gas identification, we use artificial neural network (ANN) and compare them to parallel factor analysis. Electronic nose (e-nose) has provided numerous benefits in a variety of logical study disciplines. Our goal is to create a sensor exhibit framework that can discriminate the most exceedingly contaminated gases while also being extremely responsive, precise, and less power consuming. Thus, for gas detection, we employ an ANN as well as make a comparison of results with parallel factor analysis (PARAFAC).
Detecting translation borrowings in huge text collections using various methods
Authors: Al-janabi Adel , Al-Zubaidi Ehsan Ali , Merzah Baqer M.
Published: April 2023

The purpose of this work is to investigate the problem of detecting transportable borrowings and text reuse. The article proposes a monolingual solution to this problem: translating the suspicious material into language collections for additional monolingual analysis. One of the major requirements for the suggested technique is robustness against machine learning ambiguities. The next step in the document analysis is split into two parts. The authors begin by retrieving documents-candidates that are similarity to other types of text recurrence. The paper proposes retrieving texts utilizing word clusters formed using distributional semantic for robustness. In the second stage, the authors use deep learning neural networks to compare the suspected document to candidates utilizing phrase embedding. The experimentation is carried out for the language pair “English-Arabic” on both articles and synthetic data.
Machine learning prediction of petty corruption intention among law enforcement officers
Authors: Masrom Suraya , Rahman Rahayu Abdul , Salleh Nor Asyiqin , Pitaloka Endang , Nor Mohd Auzan Md , Zakaria Nor Balkish
Published: April 2023

Law enforcement agencies face a widespread problem of corruption, which jeopardizes their credibility and institutional integrity. Thus, the primary goal of this study is to develop a machine learning prediction model for petty corruption intentions as an early warning system for law enforcement officials who fail to perform their duties and obligations with integrity. Using a questionnaire survey of two hundred twenty-five participants, from senior officers to rank and file police officers, this study presents the fundamental knowledge on the design and implementation of machine learning model based on six selected algorithms; generalized linear model, fast last margin, decision tree, random forest, gradient boosted trees, and support vector machine. In addition to demographic factors, the efficacy of each machine learning algorithm on petty corruption was evaluated using general strain theory (GST) attributes: financial stress, work stress, leadership pressure, and peer pressure. The findings indicated that peer pressure has given the highest weight of contributions to most of the machine learning algorithms. The most outperformed machine learning in terms of the classification accuracy is gradient boosted trees with accuracy above 90%. This paper presents useful knowledge to enhance the realization of implementing intelligent corruption detection tools.
Sentiment analysis of Twitter data regarding the agnipath scheme of the defense forces
Authors: Sajwan Vijaylakshmi , Awasthi Monisha , Goel Ankur , Sharma Priyank
Published: April 2023

Due to the popularity of social media today, people frequently share such criticism on Facebook, Twitter, Instagram, and other platforms. Therefore needs to know how your input from users of social media is generated in order to ascertain the public reaction to the policy that has been enacted. However, because of the comments, it is challenging to tell how many people have responded positive or negative. The objective of sentiment analysis of tweets is to provide insight into people’s attitudes and perceptions regarding an event. This study illustrates the role of Twitter in the announcement of a new army vacancy through the “agnipath scheme” dubbed “agniveer”. The result of this study can be used by the defense forces and government for decision making or policies related to the agnipath scheme. The study studied 4,000 English-language Twitter posts from July 3, 2022 to July 9, 2022. Manual text analysis revealed seven basic groups of tweet sentiments. The tweets’ positive, negative, and neutral emotions were shown using orange data mining software, a powerful machine learning, data mining, and data visualization toolset. Result shows that agnipath scheme is mostly accepted by the people.
Anomaly-based intrusion detection system based on feature selection and majority voting
Authors: Magdy Mina Eshak , Matter Ahmed M. , Hussin Saleh , Hassan Doaa , Elsaid Shaimaa Ahmed
Published: April 2023

Recently, cyberattacks have been more complex than in the past, as a new cyber-attack is initiated almost every day. Therefore, researchers should develop efficient intrusion detection systems (IDS) to detect cyber-attacks. In order to improve the detection and prevention of the aforementioned cyber-attacks, several articles developed IDSs exploiting machine learning and deep learning. In this paper, a way to find network intrusions using a combination of feature selection and adoptive voting is investigated. NSL-KDD dataset, a high-dimensional dataset that has been widely used for network intrusion detection, is applied in this approach. Feature selection plays an important role for improving accuracy and testing time as it eliminates the less significant attributes from the data set, thus saving computational power and effort. The experimental results show that the proposed approach achieves an accuracy of 86.5% on the NSL-KDD test dataset using an adoptive voting algorithm trained with the selected features. In addition, the time to process each record is 97.5 microseconds, which reflects the proposed model's superior performance. Comparing the proposed model with the existing models in the literature shows that the proposed adaptive voting approach significantly improves intrusion detection accuracy, enhances computational efficiency, and reduces false positives.
Comparing performance of bastion host on cloud using Amazon web services vs terraform
Authors: Bailuguttu Sahana , Chavan Akshatha S. , Pal Oorja , Sannakavalappa Kavya , Chakrabarti Dipto
Published: April 2023

In addition to security advantages like implementing defense in depth and complying with compliance standards, current bastion services are simple to deploy and fit into the DevOps culture. Bastions continue to be the most dependable and secure options for secure access to cloud infrastructures because they offer administrative simplicity without surrendering compliance and security. In this paper, an experimental set up was conducted to measure the cycle time it takes to provision resources using manual point-and-click graphical user interface (GUI) in Amazon web services (AWS) and time it takes for codified infrastructure to make application programming interface (API) calls using terraform. It also focuses on the design and deployment of Bastion host on AWS and terraform, and the comparison between the two with respect to various parameters.
Do clinical decision support systems for prescribing improve patient safety? a systematic literature review
Authors: Kusumadewi Sri , Miladiyah Isnatin
Published: April 2023

Clinical decision support systems (CDSS) are developed independently or connected to the electronic health record (EHR) or other computerized systems. The study begins with identification by searching the literature through the Google Scholar, PubMed and ScienceDirect databases. The search results obtained 5,595 articles. Forty-two articles were obtained, which were used further. Most of the research focus is on "CDSS development and evaluation". In terms of impacts, the most common is "reduce prescribing errors". One of the biggest problems reported was the presence of "alert fatigue," which was felt to be disturbing to doctors and pharmacists. CDSS must be supported by a method that is able to indicate the presence of drug-drug interactions (DDI). The use of alerts indicating the presence of a DDI should be interpreted using clinical judgment to determine the risks and benefits of a particular drug for a specific patient. The performance of CDSS is mostly reported to have been able to reduce prescribing errors, which in turn will improve patient safety. However, increased adherence to clinical protocols has not been widely reported. Complaints that are still quite a lot reported are the presence of "alert fatigue", which can interfere with effectiveness.
Utilizing deep neural network for web-based blood glucose level prediction system
Authors: Alfian Ganjar , Saputra Yuris Mulya , Subekti Lukman , Rahmawati Ananda Dwi , Atmaji Fransiskus Tatas Dwi , Rhee Jongtae
Published: April 2023

Machine learning algorithms can be used to forecast future blood glucose (BG) levels for diabetes patients, according to recent studies. In this study, dataset from continuous glucose monitoring (CGM) system was used as the sole input for the machine learning models. To forecast blood glucose levels 15, 30, and 45 minutes in the future, we suggested deep neural network (DNN) and tested it on 7 patients with type 1 diabetes (T1D). The suggested prediction model was evaluated against a variety of machine learning models, such as k-nearest neighbor (KNN), support vector regression (SVR), decision tree (DT), adaptive boosting (AdaBoost), random forest (RF), and eXtreme gradient boosting (XGBoost). The experimental findings demonstrated that the proposed DNN model outperformed all other models, with average root mean square errors (RMSEs) of 17.295, 25.940, and 35.146 mg/dL over prediction horizons (PHs) of 15, 30, and 45 minutes, respectively. Additionally, we have included the suggested prediction model in web-based blood glucose level prediction tools. By using this web-based system, patients may readily acquire their future blood glucose levels, allowing for the generation of preventative alarms prior to crucial hypoglycemia or hyperglycemic situations.
Students’ satisfaction with the service quality of academic advising systems
Authors: Ghonmein Ali M. , Al-Moghrabi Khaldun G. , Alrawashdeh Tawfiq
Published: April 2023

Academic advising (AA) is an integral part of university education, as it has an indispensable role in helping students fulfil their goals in higher education, become responsible for their own learning, and formulate meaningful educational plans that perfectly match the abilities of each student. For this reason, educational institutions around the world are striving to upgrade their AA systems (AAS) to provide their students with personalized experiences. Meanwhile, modern technology can improve the advising process and facilitate the accomplishment of the corresponding tasks. Therefore, the integration of technology into AA not only offers more flexibility for the students but also improves the delivery of advising services. This study aimed i) to identify those factors that mainly affect the AAS services being offered in universities; and ii) to examine how the satisfaction of students with AAS is affected by service quality. A total of 400 students from the Information Technology College of Al-Hussein Bin Talal University (AHU) were invited to participate in an online survey for data collection, and a response rate of 90.50% was recorded. Results show that the satisfaction of students with the AAS is affected by trust, network quality, service quality, system quality, information quality, and perceived risk.
Examining Flavor Appeal (Liking), Emotions and Openness to Use in Adults Who Do Not Use E-cigarettes
Authors: Majeed Ban , Treadaway Hailey , Farsi Michma , Hatzigeorgiou Christos , O'Conner Kate , Heboyan Vehe , Eissenberg Thomas
Published: April 2023

Objective: In this study, we examined emotional profiles, the pattern of intensities of evoked emotions, and the associations between emotions and openness in the use flavored e-cigarettes among adults who do not currently use e-cigarettes – younger/never smoked and older/currently smoked. Methods: We conducted an Internet experiment in women (N = 141) who do not currently use e-cigarettes. Experiment stimuli appeared as flavor names (classic tobacco, cool mint, fresh strawberry, top-shelf bourbon) and were randomly presented to participants who rated their evoked emotions using the EsSense™ Profile. Overall liking and openness to use were assessed per flavor. Seemingly unrelated regression models were constructed to determine factors associated with openness. Results: All flavors evoked greater intensities of negative emotions (disgusted, worried, and guilty) in younger/never smoked adults. The majority of the ratings on positive emotions (enthusiastic, interested, and satisfied) were positively and significantly correlated with flavor liking, whereas disgusted, was negatively correlated with flavor liking. Perceived harm was high whereas overall liking and openness were low. Flavor liking was significantly greater for “classic tobacco” in older/currently smoked (p < .001). Conclusions: Low intensities of positive emotions to flavor names suggest disinterest in e-cigarettes as a class product irrespective of flavor.
Analysis of complex fluid discharge from consumer dispensing bottles using rheology and flow visualization
Authors: Teoman Baran , Potanin Andrei , Armenante Piero M.
Published: April 2023

Complex fluids, such as gels, shampoos, and creams, are ubiquitous in the consumer product industry. However, little information is available on their discharge from consumer packaging, often resulting in a considerable heel, i.e., the residual waste material after the discharge process is complete. Here, we used rheological analysis and particle image velocimetry (PIV) to investigate the discharge of rheologically different fluids from a dispensing bottle provided with a modified hand pump. The fluids were described in terms of rheological parameters established by fitting rheometric data with the Carreau equation. The effect of operational parameters was also studied, which included the dip tube diameter, suction pressure, and volumetric flow rate. The data were also analyzed in terms of the dimensionless region of interest (ROI), which captures the relative “high-velocity” region in the fluid during the discharge process and is measured directly using PIV. Both rheological and operational parameters affect the heel at the end of the discharge process. The results presented here enable predicting the heel either by measuring ROI as in the case of transparent fluids and packages or by making use of the heel correlation with operational and rheological parameters also established in this work.
Dislocated time sequences – deep neural network for broken bearing diagnosis
Authors: Harlianto Pramudyana Agus , Adji Teguh Bharata , Setiawan Noor Akhmad
Published: April 2023

One of the serious components to be maintained in rotating machinery including induction motors is bearings. Broken bearing diagnosis is a vital activity in maintaining electrical machines. Researchers have explored the use of machine learning for diagnostic purposes, both shallow and deep architecture. This study experimentally explores the progress of dislocated time sequences–deep neural network (DTS–DNN) used to improve multi-class broken bearing diagnosis by using public data from Case Western Reserve University. Deep architectures can be utilized with the purpose of simplifying or avoiding any traditional feature extraction process. DNN is utilized for avoiding the pooling operation in Convolution neural network that could remove important information. The obtained results were compared with the present techniques. The examination resulted in 99.42% average accuracy which is higher than the present techniques.
On Oblique Domains of Janowski Functions
Authors: Kumar S. Sivaprasad , Yadav Pooja
Published: April 2023

We investigate certain properties of tilted (oblique) domains, associated with the Janow- ski function (1 + Az)/(1 + Bz), where A, B ∈ ℂ with A ≠ B and |B| ≤ 1. We find several bounds for these oblique domains and also establish various subordination, radius, argument estimates involving Janowski function with complex parameters. Moreover, some results also generalize earlier well-known results pertaining to Janowski function.
Weyl ρ-Almost Periodic Functions in General Metric
Authors: Kostić Marko
Published: April 2023

In this paper, we analyze the existence of Weyl distance in general metric and various classes of multi-dimensional Weyl p-almost periodic functions in general metric. The main structural properties for the introduced classes of Weyl almost periodic type functions are established. We also provide some applications of our theoretical results to the abstract Volterra integro-differential equations.
Talking about God from the Meaning of Life: Contributions from the Thought of Juan Antonio Estrada
Authors: Bedoya Bonilla Diego Fernando , Arboleda Mora Carlos
Published: April 2023

Juan Antonio Estrada, a Spanish philosopher and theologian, proposes the search for meaning in life as the theological place for a valid experience of God. The “achieved” or fully realized life, to which every human being aspires, is the proposal of salvation that Jesus makes possible with the proclamation of the Reign and that opens a hopeful future with Easter. By bringing reason and faith into dialogue, Estrada contributes to fundamental theology by talking about God, not from the traditional concepts of classical theology, but from the human experience related to the search for a deep meaning for existence. Although this author emphasizes the elements of a problematic faith with unresolved issues and doubts – including the timeless challenge of theodicy – his agonizing and perplexed position is full of confidence in the certainty that God’s salvation plan will inevitably come true. In this contingent life, everything remains incomplete; yet God in Jesus gives the ultimate meaning for life that all human beings grope for. This fundamental issue of human reflection will be developed by going deeper into Estrada’s philosophical and theological work.
Effects of heating on the antibacterial efficacy and physicochemical properties of plasma-activated water
Authors: Wang Bohua , Wang Wenjie , Xiang Qisen , Bai Yanhong
Published: April 2023

Plasma-activated water (PAW), which is the water treated by cold plasma, represents a promising strategy for food decontamination. However, studies of the influences of heating on the antibacterial efficacy and physicochemical characteristics of PAW are limited. Therefore, the present work is aimed at determining the effect of heating on the bactericidal effects and physicochemical properties of PAW. PAW (1.0 mL) was heated in a water bath at 30–80°C for 10 min. After being cooled to room temperature, the antibacterial efficacy and physicochemical properties of PAW were measured. Heating at 40–80°C for 10 min caused a significant decrease in the antibac-terial activity of PAW against Listeria monocytogenes and Salmonella typhimurium. After heating at 40–80°C for 10 min, the pH value and oxidation reduction potential (ORP) of PAW remained stable, and the level of nitrate and electrical conductivity of PAW remarkably increased, while hydrogen peroxide and nitrite contents significantly decreased. The combination treatment of PAW and mild heating (40–60°C for 4 min) showed greater anti-bacterial effect on L. monocytogenes and S. typhimurium. After the combined treatment of PAW with mild heating at 60°C for 4 min, the populations of L. monocytogenes and S. typhimurium decreased by 7.83 log10 CFU/mL and 9.35 log10 CFU/mL, respectively, which were significantly higher than that caused by PAW at 25°C or mild heating at 60°C alone. In summary, the antibacterial activity of PAW is significantly affected by the treatment temperature. This work provides a basis for the practical application of PAW in the food industry.
Clustering of Regions Using Basic Agricultural and Economic Criteria
Authors:   Orel State Agrarian University named after N.V. Parakhin, Shestakov R. B. , Lovchikova E. I. ,   Orel State Agrarian University named after N.V. Parakhin
Published: April 2023

The diversity of natural, climatic, and economic conditions of Russian regions implies a wide range of approaches to their classification. Simultaneously, the task of creating an abstract methodology for any branch of the national economy becomes more complicated. Effective clustering plays an important role in the establishment and implementation of agricultural and economic policies. The paper explores the potential of basic agricultural and economic regional clustering based on time series of main eco-nomic and agricultural development indicators. The dynamic segmentation technique was applied in order to monitor and predict the direction of meso-economic changes. Official Russian statistics were analysed to identify groups of indicators on production, production and institutional, and production and structural criteria. The k-means clustering algorithm was chosen as the key research method. Based on the three simulated regional segments, baseline average values were calculated. Then, the segments were classified according to the obtained characteristics. The outliers, significantly differing from the main data sets, were considered separately. The findings confirmed a wide spatial distribution of regions included in certain agricultural and economic segments. The presented classification can be applied to justify the directions and choice of instruments of agricultural and economic policy and a strategy for creating production clusters. Moreover, it can be used to plan the activities of regional agri-businesses and reduce their devel-opment imbalances. To improve the dynamic segmentation technique in the field of agricultural and economic development, the analysis can be expanded by changing the examined time interval, increasing the number of factors included in the model and their interactions, and introducing new clustering algorithms. Additionally, this model can be used to forecast structural changes and production dynamics.
Educational and Innovative Elements of Human Capital and Their Impact on Economic Growth
Authors:   University of Prešov, Daňová M. , Širá E. ,   University of Prešov
Published: April 2023

Human capital is an important factor for economic growth and the development of so-cio-economic systems. However, the appropriate expression of the value of human capital, the mecha-nism and its impact on economic development are still under discussion. It is hypothesised that there is a relationship between human capital and economic growth. To test this hypothesis, data on the group of Visegrad (V4) countries for the period 2000–2019 was analysed. The study examines the presence of a causal link between some attributes of human capital and economic growth and the conditions, un-der which its positive effects can be expected based on statistical methods. It also deals with the role and the applicability of some of its characteristics to express the impact of human capital on economic growth. The model revealed a positive, statistically significant relationship between gross domestic prod-uct per capita and the innovative capacity of human capital and the qualifications of employees. The im-pact of tools for human capital creation and development extends over a longer period and is reduced by the simultaneous action of other labour market factors. Currently, economies are affected by the Covid-19 pandemic. Corresponding changes are also noticeable in the way work is done, with more weight on the home office. It will be interesting to examine how this transformation will affect economic growth. The changes in the position of employees and the care of companies for human capital are also a good topic for further research that can be conducted every few years.
Advantages and Challenges of eLearning Before and After the COVID-19 Pandemic: Faculty and Student Perceptions in Saudi Education
Authors: Alhaider Siham Mousa , Nisa Sarwat un
Published: April 2023

Novelty and Topicality: The COVID-19 pandemic significantly affected the education sector, with eLearning transforming the global education system. Research Purpose: This study sheds light on how the English departments of King Khalid University overcame the pandemic’s impact, with respect to the shift to online learning. Motivation for the Study: The findings of the present study are of great importance for transforming the education system, not only in Saudi Arabia but worldwide. The globalization of education will help the universities of the Kingdom of Saudi Arabia make borderless, cost-effective education available to the citizens of the world from the comforts of their homes. Design and Methods: The study seeks to identify the challenges and advantages of eLearning, based on the perceptions of English-as-a-foreign-language (EFL) learners and instructors. The data were collected through Google forms and analysed using various SPSS software tools. Main findings: The findings revealed that the advantages of eLearning outweigh the challenges faced by students. The advantages of teaching English online include flexibility of learning, constant availability of learning materials, time efficiency, and the upgrade of technical skills. The major challenges for students and instructors include a lack of in-person interaction and poor Internet connectivity. Practical Implications: Notably, the study findings can improve the efficacy of eLearning in the education field in general and Saudi English departments in particular. Contribution: The outcomes can help explore future possibilities for reforming the education sector, both within and outside the Kingdom of Saudi Arabia.