bluuebunny/crossref_metadata_2025 huggingface dataset:
Computational analysis of hereditary spastic paraplegia mutations in the kinesin motor domains of KIF1A and KIF5A
Authors: Mahase Vidhyanand , Sobitan Adebiyi , Johnson Christina , Cooper Farion , Xie Yixin , Li Lin , Teng Shaolei
Published: August 2020

Hereditary spastic paraplegias (HSPs) are a genetically heterogeneous collection of neurodegenerative disorders categorized by progressive lower-limb spasticity and frailty. The complex HSP forms are characterized by various neurological features including progressive spastic weakness, urinary sphincter dysfunction, extra pyramidal signs and intellectual disability (ID). The kinesin superfamily proteins (KIFs) are microtubule-dependent molecular motors involved in intracellular transport. Kinesins directionally transport membrane vesicles, protein complexes, and mRNAs along neurites, thus playing important roles in neuronal development and function. Recent genetic studies have identified kinesin mutations in patients with HSPs. In this study, we used the computational approaches to investigate the 40 missense mutations associated with HSP and ID in KIF1A and KIF5A. We performed homology modeling to construct the structures of kinesin–microtubule binding domain and kinesin–tubulin complex. We applied structure-based energy calculation methods to determine the effects of missense mutations on protein stability and protein–protein interaction. The results revealed that the most of disease-causing mutations could change the folding free energy of kinesin motor domain and the binding free energy of kinesin–tubulin complex. We found that E253K associated with ID in KIF1A decrease the protein stability of kinesin motor domains. We showed that the HSP mutations located in kinesin–tubulin complex interface, such as K253N and R280C in KIF5A, can destabilize the kinesin–tubulin complex. The computational analysis provides useful information for understanding the roles of kinesin mutations in the development of ID and HSPs.
Low light image denoising solution with contrast enhancement in curvelet domain using Gaussian mixture adaptation model
Authors: Sreekala K. , Kumar H. C. Sateesh , Raja K. B.
Published: August 2020

Images captured under low light are noisy and consist of unidentifiable features. Low light noise problem occurs in imaging devices because of smaller sensor size or insufficient exposure. Low light image denoising is an exacting task in many image processing applications. This paper proposes a patch-based image denoising method for low light images in the curvelet domain with contrast enhancement. Curvelet transform is a directional transform and it gives the best sparse representation for images with edges. Here the Expectation–Maximization (EM) algorithm, based on the Gaussian mixture adaptation method is performed in the curvelet domain for denoising. EM Algorithm helps in computing the Gaussian mixture model (GMM) parameters from the patches which are used in maximum a posteriori estimation to update them. GMM parameters and patches are updated periodically until a satisfactory result is achieved. Simulation is performed on standard test data set, and then extended to natural low light noisy images. The results of the proposed technique are then compared using quality metrics such as Peak Signal to Noise Ratio and Structural Similarity Index. It is observed that the use of curvelet transform in denoising process helps to restore the structural information satisfactorily.
A Comparison Between Weakly-Compressible Smoothed Particle Hydrodynamics (WCSPH) and Moving Particle Semi-Implicit (MPS) Methods for 3D Dam-Break Flows
Authors: Amaro Rubens A. , Cheng Liang-Yee , Buruchenko Sergei K.
Published: August 2020

Lagrangian particle-based methods have opened new perspectives for the investigation of complex problems with large free-surface deformation. Some well-known particle-based methods adopted to solve non-linear hydrodynamics problems are the smoothed parti- cle hydrodynamics (SPH) and the moving particle semi-implicit (MPS). Both methods model the continuum by a system of Lagrangian particles (points), but adopting distinct approaches for the numerical operators, pressure calculation, and boundary conditions. Despite the ability of the particle-based methods in modeling highly nonlinear hydrodynamics, some shortcomings, such as unstable pressure computation and high computational cost remain. In order to assess the performance of these two methods, the weakly-compressible SPH (WCSPH) parallel solver, DualSPHysics, and an in-house incompressible MPS solver are adopted in this work. Two test cases consisting of three-dimensional (3D) dam-break problems are simulated, and wave heights, pressures and forces are compared with the available experimental data. The influence of the artificial viscosity on the accuracy of WCSPH is investigated. Computational times of both solvers are also compared. Finally, the relative benefits of the methods for solving free-surface problems are discussed, therefore providing directions of their applicability.
Business Model Innovation: A Systematic Literature Review
Authors: Kraus Sascha , Filser Matthias , Puumalainen Kaisu , Kailer Norbert , Thurner Selina
Published: August 2020

Researching business models (BM) and in specific business model innovation recently received growing attention by academics and practitioners due to increasing global competition and the constant need for adjustment to changing environments among others. Therefore, the main objective of our study is to provide an overview of the state-of-the-art of research on business model innovation by conducting a systematic literature review (SLR). Our review provides a deeper understanding and breakdown of key components of BMI. Likewise, our study identifies organizational, environmental, and societal factors influencing BMI and proposes avenues for future research.
Yamabe solitons and gradient Yamabe solitons on three-dimensional N(k)-contact manifolds
Authors: Suh Young Jin , De Uday Chand
Published: August 2020

If a three-dimensional [Formula: see text]-contact metric manifold [Formula: see text] admits a Yamabe soliton of type [Formula: see text], then the manifold has a constant scalar curvature and the flow vector field [Formula: see text] is Killing. Furthermore, either [Formula: see text] has a constant curvature [Formula: see text] or the flow vector field [Formula: see text] is a strict contact infinitesimal transformation. Also, we prove that if the metric of a three-dimensional [Formula: see text]-contact metric manifold [Formula: see text] admits a gradient Yamabe soliton, then either the manifold is flat or the scalar curvature is constant. Moreover, either the potential function is constant or the manifold is of constant sectional curvature [Formula: see text]. Finally, we have given an example to verify our result.
Semiclassical treatment of an attractive inverse-square potential in an elastic medium with a disclination
Authors: Bakke K. , Furtado C.
Published: August 2020

We analyze the interaction of the induced electric dipole moment of a neutral particle with an electric field in elastic medium with a charged disclination from a semiclassical point of view. We show that the interaction of the induced electric dipole moment of a neutral particle with an electric field can yield an attractive inverse-square potential, where it is influenced by the topology of the disclination. Then, by using the Wentzel, Kramers and Brillouin approximation based on the Langer transformation, we show that the centrifugal term of the radial equation must be modified due to the influence of the topology of the disclination. Besides, we obtain the bound states solutions to the Schrödinger equation.
Experimental Investigation of Hysteretic Performance of Self-Centering Glulam Beam-to-Column Joint with Friction Dampers
Authors: Huang Linjie , Zhou Zhen , Liu Hao , Si Yi
Published: August 2020

In this study, friction dampers (FDs) were placed at the top and bottom of a post-tensioned (PT) self-centering glulam (SCG) beam-to-column joint to dissipate earthquake energy. PT tendons were installed in two externally elongated slots at the centroid of the beam to provide the system with self-centering capacity so that the system can return to its original position after an earthquake. Theoretical and experimental analyses of the beam-to-column joint were performed to investigate the effects of various design parameters, such as the total clamping forces applied to the FDs and initial forces of the PT tendons, on the hysteretic performance of the FD-SCG joint under cyclic loading. During the tests, the backbone members (glulam beam and column) and main connecting members (PT tendons and FDs) were measured to always be within the elastic limit range. Both the theoretical and experimental results indicated that under low initial PT forces and clamping forces, the energy is dissipated primarily by FDs; in contrast, under high PT forces and clamping forces, some energy is dissipated by the glulam materials, owing to the occurrence of minor local damage in the specimen, in the direction perpendicular to the grain. Moreover, the FD-SCG joint can be suitably designed to achieve the desired stiffness, load capacity, self-centering ability, energy dissipation capability, and expected overall system response.
Arithmetic–geometric energy of specific graphs
Authors: Zheng Lu , Tian Gui-Xian , Cui Shu-Yu
Published: August 2020

Let [Formula: see text] be a simple graph of order [Formula: see text] with vertex set [Formula: see text] and edge set [Formula: see text]. The arithmetic–geometric matrix [Formula: see text] of [Formula: see text] is a matrix of order [Formula: see text] defined by [Formula: see text] if [Formula: see text] and 0 otherwise, where [Formula: see text] stands for the degree of the vertex [Formula: see text] in [Formula: see text]. The arithmetic–geometric characteristic polynomial of [Formula: see text] is the characteristic polynomial of [Formula: see text]. The arithmetic–geometric energy [Formula: see text] of [Formula: see text] is the sum of absolute values of all eigenvalues of [Formula: see text]. In this paper, we obtain the arithmetic–geometric characteristic polynomial and arithmetic–geometric energy of some specific graphs. In addition, we also consider the arithmetic–geometric characteristic polynomial and arithmetic–geometric energy change of these graphs when one edge is deleted.
Classification of rings with toroidal co-annihilating-ideal graphs
Authors: Khoeilar Rana , Amjadi Jafar
Published: August 2020

Let [Formula: see text] be a commutative ring with identity. The co-annihilating-ideal graph of [Formula: see text], denoted by [Formula: see text], is a graph whose vertex set is the set of all nonzero proper ideals of R and two distinct vertices [Formula: see text] and [Formula: see text] are adjacent whenever [Formula: see text]. In this paper, we study the planarity and genus of [Formula: see text]. In particular, we characterize all Artinian rings [Formula: see text] for which the genus of [Formula: see text] is zero or one.
2-Distance coloring of planar graph
Authors: Bu Yue Hua , Cao Jiao Jiao
Published: August 2020

The [Formula: see text]-2-distance coloring of graph [Formula: see text] is a mapping [Formula: see text] if any two vertices at distance at most two from each other get different colors. The 2-distance chromatic number is the smallest integer [Formula: see text] such that [Formula: see text] has a [Formula: see text]-[Formula: see text]-distance coloring, denoted by [Formula: see text]. The purpose of this paper is to prove that every planar graph [Formula: see text] without [Formula: see text]-cycle and intersecting [Formula: see text]-cycle and [Formula: see text] has [Formula: see text].
Quaternized Chitosan Modified Nanostructure Lipid Carriers for Topical Delivery of Coenzyme Q10
Authors: Liang Rong , Wang Yuxuan , Wu Lina , Ni Xinjiong , Yang Cheng
Published: August 2020

Nanostructured lipid carrier (NLC) is a new colloidal delivery system which can effectively solve the problems of stability and transdermal delivery of active ingredients with poor water solubility and biocompatibility. Coenzyme Q10 (CoQ10), as a lipophilic antioxidant, has poor chemical stability due to unsaturated double bonds in its molecular structure, which limits its addition and application in cosmetics. In this study, CoQ10 NLC was prepared using the mixture of Caprylyl/Capryl Glycoside (APG) and quaternized chitosan (QCS). The particle size of the QCS–APG–NLC was around 250 nm. Compared to NLC stabilized by APG, QCS–APG–NLC has better storage stability under high temperature and light conditions. In vitro transdermal experiment analysis and confocal laser scanning microscopy (CLSM) observation found that QCS modification can effectively increase the penetration amount of CoQ10 in the skin. So, it is suggested that QCS modified APG–NLC can be used as an effective transdermal delivery system for lipophilic active components.
A Review of Recent Advances in Coordination Between Unmanned Aerial and Ground Vehicles
Authors: Ding Yulong , Xin Bin , Chen Jie
Published: August 2020

Coordination between unmanned aerial vehicles (UAVs) and unmanned ground vehicles (UGVs) has received increasing attention in recent years. The list of successful applications of UAV–UGV coordination systems is growing and demonstrates that UAV–UGV coordination can provide real-world solutions that other types of coordination cannot offer. This paper systematically reviews the advances in UAV–UGV coordination systems during the period of 2015–2020 and offers a comprehensive investigation and analysis of the recent research. First, the essential elements in the UAV–UGV coordination systems are analyzed, and four key functional roles are identified. The close collaboration among functional roles can achieve the UAV–UGV coordination on perception, task, and motion. From the perspective of functional roles, UAV–UGV coordination systems can be further classified into eight categories. The functional-role-based category provides novel insights into analyzing various patterns of UAV–UGV coordination. This paper also discusses the challenges related to UAV–UGV coordination.
An Analysis of Complexity of Insider Attacks to Databases
Authors: Kul Gökhan , Upadhyaya Shambhu , Hughes Andrew
Published: August 2020

Insider attacks are one of the most dangerous threats to an organization. Unfortunately, they are very difficult to foresee, detect, and defend against due to the trust and responsibilities placed on the employees. In this article, we first define the notion of user intent and construct a model for a common scenario that poses a very high risk for sensitive data stored in the organization’s database. We show that the complexity of identifying pseudo-intents of a user in this scenario is coNP-Complete, and launching a
harvester
insider attack within the boundaries of the defined threat model takes linear time while a
targeted
threat model is an NP-Complete problem. We also discuss the general defense mechanisms against the modeled threats and show that countering the harvester insider attack takes quadratic time while countering the targeted insider attack can take linear to quadratic time, depending on the strategy chosen. We analyze the adversarial behavior and show that launching an attack with minimum risk is also an NP-Complete problem. Finally, we perform timing experiments with the defense mechanisms on SQL query workloads collected from a national bank to test the feasibility of using these systems in real time.
Mathematical Reconciliation of Medical Privacy Policies
Authors: Ranathunga Dinesha , Roughan Matthew , Nguyen Hung
Published: August 2020

Healthcare data are arguably the most private of personal data. This very private information in the wrong hands can lead to identity theft, prescription fraud, insurance fraud, and an array of other crimes. Electronic-health systems such as My Health Record in Australia holds great promise in sharing medical data and improving healthcare quality. But, a key privacy issue in these systems is the misuse of healthcare data by “authorities.” The recent General Data Protection Regulation (GDPR) introduced in the EU aims to reduce personal-data misuse. But, there are no tools currently available to accurately reconcile a domestic E-health policy against the GDPR to identify discrepancies. Reconciling privacy policies is also non-trivial, because policies are often written in free text, making them subject to human interpretation.

In this article, we propose a tool that allows the description of E-health privacy policies, represents them using formal constructs making the policies precise and explicit. Using this formal framework, our tool can automatically reconcile a domestic E-health policy against the GDPR to identify violations and omissions. We use our prototype to illustrate several critical flaws in Australia’s My Health Record policy, including a non-compliance with GDPR that allows healthcare providers to access medical records by default.
Building Semantic Metadata for Historical Archives through an Ontology-driven User Interface
Authors: Goy Annamaria , Colla Davide , Magro Diego , Accornero Cristina , Loreto Fabrizio , Radicioni Daniele Paolo
Published: August 2020

Historical archives represent an immense wealth, the potential of which is endangered by the lack of effective management and access tools. We believe that this issue can be faced by providing archive catalogs with a
semantic layer
, containing rich semantic metadata, representing the content of documents in a full-fledged formal machine-readable format. In this article, we present the contribution offered in this direction by the
PRiSMHA project
, in which the conceptual vocabulary of the semantic layer is represented by computational ontologies. However, acquiring semantic knowledge represents a well-known bottleneck for knowledge-based systems; to solve this problem, PRiSMHA relies on a
crowdsourcing collaborative model
, i.e., an online community of users who collaborate in building semantic representations of the content of archival documents. In this perspective, this article aims at answering the following
research question
:
Starting from the axioms characterizing concepts in the computational ontology underlying the system, how can we derive a user interface enabling users to formally represent the content of archival documents by exploiting the conceptual vocabulary provided by the ontology?

Our solution includes the following steps:
(a)
a manually defined configuration, acting as a pre-filter, to hide “unsuited” classes, properties, and relations;
(b)
an algorithm, combining heuristics and reasoning, which extracts from the ontology all and only the “compatible” properties and relations, given an entity (event) type; and
(c)
a set of strategies to rank, group, and present the entity (event) properties and relations, based on the results of a study with users. This integrated solution enabled us to design an
ontology-driven user interface
enabling users to characterize entities, and in particular (historical) events, on the basis of the vocabulary provided by the ontology.
Art for Space
Authors: Franceschet Massimo
Published: August 2020

We investigate the overlapping of the concepts of prestige and success in art. To this end, we invited a group of art experts and a group of artists to select a small number of artworks that they deemed of high quality among those the crypto art gallery SuperRare displays. We then matched the selections with indicators of market success for the same artworks. We find that prestigious artworks selected by art experts and artists are also successful in the gallery marketplace, tracing an interesting link between prestige and success in the art context. We also observe a clear divergence between the roles of art expert and art maker (artist).
Active Vibration Control of PID Based on Receptance Method
Authors: Peng Lijuan , Wang Jian , Yu Guicheng , Wang Zuoxue , Yin Aijun , Ren Hongji
Published: August 2020

Active vibration control approaches have been widely applied on improving reliability of robotic systems. For linear vibratory systems, the vibration features can be altered by modifying poles and zeros. To realize the arbitrary assignment of the closed-loop system poles and zeros of a linear vibratory system, in this paper, an active PID input feedback vibration control method is proposed based on the receptance method. The establishment and verification of the proposed method are demonstrated. The assignable poles during feedback control are calculated and attached with importance to expand the application of the integral control. Numerical simulations are conducted to verify the validity of the proposed method in terms of the assignment of closed-loop poles, zeros, and both. The results indicate that the proposed method can be used to realize the active vibration control of closed-loop system and obtain the desired damping ratio, modal frequency, and dynamic response.
The Value of Haematological Parameters and Tumour Markers in the Prediction of Intestinal Obstruction in 1474 Chinese Colorectal Cancer Patients
Authors: Cao Yinghao , Ke Songqing , Gu Junnan , Mao Fuwei , Yao Shuang , Deng Shenghe , Yan Lizhao , Wu Ke , Liu Li , Cai Kailin
Published: August 2020

Intestinal obstruction, a life-threatening problem, often occurs in patients with advanced colorectal cancer (CRC). However, the cause of obstruction is still unknown. Very few prediction models for intestinal obstruction in CRC exist, and their results are unreliable. Therefore, we investigated whether preoperative serum tumour markers (STMs) combined with haematological and biochemical markers could be used as predictors. We retrospectively analysed 1474 patients with CRC who underwent radical resection after admission. Several clinical features, STMs, and serum biochemical and haematological indicators were analysed. Predictors of intestinal obstruction were analysed with univariate and multivariate logistic regression. The accuracy of the multivariate predictors of obstruction was measured by the area under the receiver operating characteristic (ROC) curve (AUC). The Kaplan-Meier method was used to create survival curves. Obstruction was found more in males (62.18%), never-smokers (73.95%), the left colon (54.20%), the tumour diameter>4.5 cm (55.88%), high differentiation (89.50%), and negative nerve invasion (70.17%). The serum tumour markers (STMs) and peripheral blood routine indexes (PBRI) were significantly associated with obstructive status (p<0.05). Multivariate analysis demonstrated that the neutrophil and lymphocyte counts, carcinoembryonic antigen, carbohydrate antigen 19-9, carbohydrate antigen 125, albumin, alkaline phosphatase, gamma-glutamyl transpeptidase, total protein, and neutrophil-to-lymphocyte ratio were predictors of intestinal obstruction (p<0.05). The AUC for the curve with all the eight factors was 0.715 (95% confidence interval: 0.673-0.758). The STMs and PBRI were related to the obstruction status of the patients, and they could be used in combination with other clinical factors to significantly improve diagnosis and management of intestinal obstruction in CRC patients.
COVID-19 Outbreak in Colombia: An Analysis of Its Impacts on Transport Systems
Authors: Arellana Julian , Márquez Luis , Cantillo Victor
Published: August 2020

The global COVID-19 outbreak has demanded drastic actions and policies from the governments and local authorities to stem the spread of the virus. Most of the measures involve behavioural changes from citizens to reduce their social contact to a minimum. Thus, these actions influence individual activity patterns and transport systems in different ways. This paper studies the short-term impacts on the transport system caused by the different policies adopted by the Colombian government and local authorities to contain the COVID-19 spread. Using official and secondary data concerning the seven most populated cities in Colombia, we analyse the impacts on three components of the transport system: air transport, freight transport, and urban transport. Results show that national policies and local decisions have decreased the demand for motorised trips across the cities, diminishing congestion levels, reducing transit ridership, and creating a reduction in transport externalities. The country banned air transport for passengers and only allowed air cargo for medical and necessary supplies, which will have negative consequences for the economics of the airline industry. During the first three months of the COVID-19, freight was the most resilient transport component. However, freight trips diminished around 38%, affecting mainly the supply chain of nonessential products. During the pandemic, governments need to provide subsidies to maintain the system supply to avoid crowdedness and promote active transport by allocating less-used street space to cyclists and pedestrians. In the short term, transportation service providers will face a financial crisis, deepened by the pandemic, which will require government assistance for their recovery.
Association between Cardiovascular Burden and Requirement of Intensive Care among Patients with Mild COVID-19
Authors: Tai Shi , Tang Jianjun , Yu Bilian , Tang Liang , Wang Yang , Zhang Huilin , Zhu Weihong , Xiao Kui , Wen Chuan , Tan Chongqin , Jiang Zhongbiao , Jiang Chuanhao , Zhu Li , Jiang Li , Liu Qiming , Hu Xinqun , Fang Zhenfei , Li Xuping , Sun Jiaxing , Zhu Zhaowei , Yang Hui , Tu Tao , Xiao Yichao , Chen Mingxian , He Yuhu , Chai Xiangping , Xu Junmei , Zhou Shenghua
Published: August 2020

Background. Information regarding the impact of cardiovascular (CV) conditions on disease progression among patients with mild coronavirus disease 2019 (COVID-19) is limited. Methods. This study evaluated the association of underlying CV conditions with disease progression in patients with mild COVID-19. The primary outcome was the need to be transferred to the designated hospital for intensive care due to COVID-19 disease progression. The patients were divided into with and without CV conditions as well as stable and intensive care groups. Results. Of the 332 patients with mild COVID-19, the median age was 51 years (IQR, 40-59 years), and 200 (61.2%) were female. Of the 48 (14.5%) patients with CV conditions, 23 (47.9%) progressed to severe disease status and required intensive care. Compared with patients without CV conditions, patients with CV conditions were older and more likely to have fatigue, chest tightness, and myalgia. The rate of requiring intensive care was significantly higher among patients with CV conditions than in patients without CV conditions (47.92% vs. 12.4%; P<0.001). In subgroup analysis, the rate of requiring intensive care was also higher among patients with either hypertension or coronary heart disease (CHD) than in patients without hypertension or CHD. The multivariable regression model showed that CV condition served as an independent risk factor for intensive care (odds ratio (OR), 2.652 (95% CI, 1.019-6.899)) after adjustment for various cofounders. Conclusions. Patients with mild COVID-19 complicating CV conditions are susceptible to develop severe disease status and requirement for intensive care.
RCC2 Promotes Esophageal Cancer Growth by Regulating Activity and Expression of the Sox2 Transcription Factor
Authors: Calderon-Aparicio Ali , Yamamoto Hiroyuki , De Vitto Humberto , Zhang Tianshun , Wang Qiushi , Bode Ann M. , Dong Zigang
Published: August 2020

Regulator of chromosome condensation 2 (RCC2) is a protein located in the centrosome, which ensures that cell division proceeds properly. Previous reports show that RCC2 is overexpressed in some cancers and could play a key role in tumor development, but the mechanisms concerning how this occurs are not understood. Furthermore, no evidence exists regarding its role in esophageal cancer. We studied the relevance of RCC2 in esophageal cancer growth and its regulation on Sox2, an important transcription factor promoting esophageal cancer. RCC2 was overexpressed in esophageal tumors compared with normal tissue, and this overexpression was associated with tumorigenicity by increasing cell proliferation, anchorage-independent growth, and migration. These oncogenic effects were accompanied by overexpression of Sox2. RCC2 upregulated and stabilized Sox2 expression and its target genes by inhibiting ubiquitination-mediated proteasome degradation. Likewise, RCC2 increased the transcriptional activity and promoter binding of Sox2. In vivo studies indicated that RCC2 and Sox2 were overexpressed in esophageal tumors compared with normal tissue, and this upregulation occurs in the esophageal basal cell layer for both proteins. In conditional knockout mice, RCC2 deletion decreased the tumor nodule formation and progression in the esophagus compared with wild-type mice. Proliferating cell nuclear antigen expression, a cell proliferation marker, was also downregulated in RCC2 knockout mice. Overall, our data show for the first time that RCC2 is an important protein for the stabilization and transcriptional activation of Sox2 and further promotion of malignancy in esophageal cancer.

Implications:

This study shows that RCC2 controls Sox2 expression and transcriptional activity to mediate esophageal cancer formation.
Platinum-Induced Ubiquitination of Phosphorylated H2AX by RING1A Is Mediated by Replication Protein A in Ovarian Cancer
Authors: Sriramkumar Shruthi , Matthews Timothy D. , Ghobashi Ahmed H. , Miller Samuel A. , VanderVere-Carozza Pamela S. , Pawelczak Katherine S. , Nephew Kenneth P. , Turchi John J. , O'Hagan Heather M.
Published: August 2020

Platinum resistance is a common occurrence in high-grade serous ovarian cancer and a major cause of ovarian cancer deaths. Platinum agents form DNA cross-links, which activate nucleotide excision repair (NER), Fanconi anemia, and homologous recombination repair (HRR) pathways. Chromatin modifications occur in the vicinity of DNA damage and play an integral role in the DNA damage response (DDR). Chromatin modifiers, including polycomb repressive complex 1 (PRC1) members, and chromatin structure are frequently dysregulated in ovarian cancer and can potentially contribute to platinum resistance. However, the role of chromatin modifiers in the repair of platinum DNA damage in ovarian cancer is not well understood. We demonstrate that the PRC1 complex member RING1A mediates monoubiquitination of lysine 119 of phosphorylated H2AX (γH2AXub1) at sites of platinum DNA damage in ovarian cancer cells. After platinum treatment, our results reveal that NER and HRR both contribute to RING1A localization and γH2AX monoubiquitination. Importantly, replication protein A, involved in both NER and HRR, mediates RING1A localization to sites of damage. Furthermore, RING1A deficiency impairs the activation of the G2–M DNA damage checkpoint, reduces the ability of ovarian cancer cells to repair platinum DNA damage, and increases sensitivity to platinum.

Implications:

Elucidating the role of RING1A in the DDR to platinum agents will allow for the identification of therapeutic targets to improve the response of ovarian cancer to standard chemotherapy regimens.
Feature extraction and classification methods of facial expression: a survey
Authors: Moe Htay Moe
Published: August 2020

Facial Expression is a significant role in affective computing and one of the non-verbal communication for human computer interaction. Automatic recognition of human affects has become more challenging and interesting problem in recent years. Facial Expression is the significant features to recognize the human emotion in human daily life. Facial Expression Recognition System (FERS) can be developed for the application of human affect analysis, health care assessment, distance learning, driver fatigue detection and human computer interaction. Basically, there are three main components to recognize the human facial expression. They are face or face’s components detection, feature extraction of face image, classification of expression. The study proposed the methods of feature extraction and classification for FER.
MLGrafViz: multilingual ontology visualization plug-in for protégé
Authors: Florrence Merlin
Published: August 2020

Natural Language Processing (NLP) is rapidly increasing in all domains of knowledge acquisition to facilitate different language user. It is required to develop knowledge based NLP systems to provide better results.  Knowledge based systems can be implemented using ontologies where ontology is a collection of terms and concepts arranged taxonomically.  The concepts that are visualized graphically are more understandable than in the text form.   In this research paper, new multilingual ontology visualization plug-in MLGrafViz is developed to visualize ontologies in different natural languages. This plug-in is developed for protégé ontology editor. This plug-in allows the user to translate and visualize the core ontology into 135 languages.
Optimal economic dispatch of power generation solution using lightning search algorithm
Authors: Yahya Nassar Murad , Noor Abdullah Mohd , Ahmed Rahimoon Asif
Published: August 2020

Economic dispatch (ED) is the power demand allocating process for the committed units at minimum generation cost while satisfying system and operational constraints. Increasing cost of fuel price and electricity demand can increase the cost of thermal power generation. Therefore, robust and efficient optimization algorithm is required to determine the optimal solution for ED problem in power system operation and planning. In this paper the lightning search algorithm (LSA) is proposed to solve the ED problem. The system constraints such as power balance, generator limits, system transmission losses and valve-points effects (VPE) are considered in this paper. To verify the effectiveness of LSA in terms of convergence characteristic, robustness, simulation time and solution quality, the two case studies consists of 6 and 13 units have been tested. The simulation results show that the LSA can provide optimal cost than many methods reported in literature. Therefore, it has potential to solve many optimization problems in power dispatch and power system applications.
Machine learning building price prediction with green building determinant
Authors: Mohd Thuraiya , Jamil Syafiqah , Masrom Suraya
Published: August 2020

In the era of Industrial 4.0, many urgent issues in the industries can be effectively solved with artificial intelligence techniques, including machine learning. Designing an effective machine learning model for prediction and classification problems is an ongoing endeavor. Besides that, time and expertise are important factors that are needed to tailor the model to a specific issue, such as the green building housing issue. Green building is known as a potential approach to increase the efficiency of the building. To the best of our knowledge, there is still no implementation of machine learning model on GB valuation factors for building price prediction compared to conventional building development. This paper provides a report of an empirical study that model building price prediction based on green building and other common determinants. The experiments used five common machine learning algorithms namely Linear Regression, Decision Tree, Random Forest, Ridge and Lasso tested on a set of real building datasets that covered Kuala Lumpur District, Malaysia. The result showed that the Random Forest algorithm outperforms the other four algorithms on the tested dataset and the green building determinant has contributed some promising effects to the model.
Comparison of CNNs and SVM for voice control wheelchair
Authors: Sharifuddin Mohammad Shahrul Izham , Nordin Sharifalillah , Mohd Ali Azliza
Published: August 2020

In this paper, we develop an intelligent wheelchair using CNNs and SVM voice recognition methods. The data is collected from Google and some of them are self-recorded. There are four types of data to be recognized which are go, left, right, and stop. Voice data are extracted using MFCC feature extraction technique. CNNs and SVM are then used to classify and recognize the voice data. The motor driver is embedded in Raspberry PI 3B+  to control the movement of the wheelchair prototype. CNNs produced higher accuracy i.e. 95.30% compared to SVM which is only 72.39%. On the other hand, SVM only took 8.21 seconds while CNNs took 250.03 seconds to execute. Therefore, CNNs produce better result because noise are filtered in the feature extraction layer before classified in the classification layer. However, CNNs took longer time due to the complexity of the networks and the less complexity implementation in SVM give shorter processing time.
Optimization of detection of single line to ground fault by controlling peterson coil through ANFIS
Authors: Jabbar Feryal Ibrahim , Muhammad Soomro Dur , Hasan Tawafan Adnan , Noor bin Abdullah Mohd , Binti Mohammad Radzi Nur Hanis , Hussain Baloch Mazhar
Published: August 2020

The most common fault in the distribution network is the single line to ground fault (SLGF). With earthling in the distribution network, it causes electrical arc as well as a high voltage in the faulted phase compared to other two healthy phases. It increases the danger of separation and isolation in the power network. One of the classical technique to control the arc is through Peterson Coil (PC), which detects and turns off/reduces the electrical arc making the network safer, increasing its reliability and device's safety. To control the PC, some of the techniques used in this research area are PID, FL, NN etc. This paper presents Adaptive Neural-Fuzzy Inference System (ANFIS) technique to controlling the PC. It gives the best results by detecting the fault, reducing the electrical arc and minimizing the fault current to the rated current in a very short time. Moreover, this research focuses on suppressing fault current by looking at its higher and lower peaks. Also, it calculates the opposing inductance to compensate the capacitance caused. It will save thousands of tons of copper costs. This research was conducted using MATLAB. For the validity of the proposed technique results, PID control technique was used.
Age-based facial recognition using convoluted neural network deep learning algorithm
Authors: Jien Julius Yong Wu , Baharum Aslina , Wahab Shaliza Hayati A. , Saad Nordin , Omar Muhammad , Noor Noorsidi Aizuddin Mat
Published: August 2020

Face recognition is the use of biometric innovations that can see or validate a person by seeing and investigating designs depending on the shape of the individual. Face recognition is used largely for the purpose of well-being, despite the fact that passion for different areas of use is growing. Overall, face recognition innovations are worth considering because they have the potential for broad legal jurisdiction and different business applications. It is widely used in many spaces. How it works is a product of facial recognition processing facial geometry. The hole between the ear and the good way from the front to the jaw are the main variables. This code distinguishes the highlight of the face that is important for your facial separation and creates your facial expression. Therefore, this study gives an overview of age detection using a different combination of machine learning and image processing methods on the image dataset.
Adaptive neuro-fuzzy inference system based evolving fault locator for double circuit transmission lines
Authors: Naresh Kumar A , Sridhar P , Anil Kumar T , Ravi Babu T , Chandra Jagan Mohan V
Published: August 2020

Evolving faults are starting in one phase of circuit and spreading to other phases after some time. There has not been a suitable method for locating evolving faults in double circuit transmission line until now. In this paper, a novel method for locating different types of evolving faults occurring in double circuit transmission line is proposed by considering adaptive neuro-fuzzy inference system. The fundamental current and voltage magnitudes are specified as inputs to the proposed method. The simulation results using MATLAB verify the effectiveness and correctness of the protection method. Simulation results show the robustness of the method against different fault locations, resistances, time intervals, and all evolving fault types. Moreover, the proposed method yields satisfactory performance against percentage errors and fault location line parameters. The proposed method is easy to implement and cost-effective for new and existing double circuit transmission line installation
Forecasting accuracy: a comparative study between artificial neural network and autoregressive model for streamflow
Authors: Zurey Wan Nur Hawa Fatihah Wan , Ismail Shuhaida , Mustapha Aida
Published: August 2020

Estimating the reliability of potential prediction is very crucial as our life depended heavily on it. Thus, a simulation that concerned hydrological factors such as streamflow must be enhanced. In this study, Autoregressive (AR) and Artificial Neural Networks (ANN) were used. The forecasting result for each model was assessed by using various performance measurements such as Mean Absolute Error (MAE), Root Mean Square Error (RMSE), Mean Absolute Percentage Error (MAPE), Mean Forecast Error (MFE) and Nash-Sutcliffe Model Efficiency Coefficient (CE). The experimental results showed the forecast performance of Durian Tunggal reservoir datasets by using ANN Model 7 with 7 hidden neurons has better forecast performance compared to AR (4). The ANN model has the smallest MAE (0.0116 m3/s), RMSE (0.0607 m3/s), MAPE (1.8214% m3/s), MFE (0.0058 m3/s) and largest CE (0.9957 m3/s) which show the capability of fitting to a nonlinear dataset. In conclusion, high predictive precision is an advantage as a proactive or precautionary measure that can be inferred in advance in order to avoid certain negative effects.
Modelling of time-to collision for unmanned aerial vehicle using particles swarm optimization
Authors: Sabikan Sulaiman Bin , W Nawawi. S. , Aziz NAA
Published: August 2020

A method for the development of Time-to-Collision (TTC) mathematical model for outdoor Unmanned Aerial Vehicle (UAV) using Particles Swarm Optimization (PSO), are presented. TTC is the time required for a UAV either to collide with any static obstacle or completely stop without applying any braking control system when the throttle is fully released. This model provides predictions of time before UAV will collide with the obstacle in the same path based on their parameter, for instance, current speed and payload. However, this paper focus on the methodology of the implementation of PSO to develop the TTC model for 5 different set of payloads. This work utilizes a quadcopter as our testbed system, that equipped with a Global Positioning System (GPS) receiver unit, a flight controller with data recording capability and ground control station for real-time monitoring. The recorded onboard flight mission data for 5 different set of payloads has been analyzed to develop a mathematical model of TTC through the PSO approach. The horizontal ground speed, throttle magnitudes and flight time stamp are extracted from the on-board quadcopter flight mission. PSO algorithm is used to find the optimal linear TTC model function, while the mean square error is used to evaluate the best fitness of the solution. The results of the TTC mathematical model for each payload are described.
Fault-type coverage based ant colony optimization algorithm for attaining smaller test suite
Authors: M Bharathi , V Sangeetha
Published: August 2020

In this paper, we proposed Fault-Type Coverage Based Ant Colony Optimization (FTCBACO) technique for test suite optimization. An algorithm starts with initialization of FTCBACO factors using test cases in test suite. Then, assign separate ant to each test case called vertex. Each ant chooses best vertices to attain food source called objective of the problem by means of updating of pheromone trails and higher probability trails. This procedure is repeated up to the ant reaches food source. In FTCBACO algorithm, minimal number of test cases with less execution time chosen by an ant to cover all faults type (objective) are taken as optimal solution. We measured the performance of FTCBACO against Greedy approach and Additional Greedy Approach in terms of fault type coverage, test suite size and execution time. However, the heuristic Greedy approach and Additional Greedy approach required more execution time and maximum test suite size to provide the best resolution for test suite optimization problem. Statistical investigations are performed to finalize the performance significance of FTCBACO with other approaches that concludes FTCBACO technique enriches the reduction rate of test suite and minimizes execution time of reducing test cases efficiently.
Region of interest-based image retrieval techniques: a review
Authors: Md Jan Mardhiyah , Zainal Nasharuddin , Jamaludin Shahrizan
Published: August 2020

This paper presents a review of the region of interest-based (ROI) image retrieval techniques. In this study, the techniques, the performance evaluation parameters, and databases used in image retrieval process are being reviewed. A part of an image that is considered important or a selected certain area of the image is what defines a region of interest. Retrieval performance in large databases can be improved with the application of content-based image retrieval systems which deals with the extraction of global and region features of images. The capability of reflecting users' specific interests with greater accuracy has shown to be more effective when using region-based features compared to global features. Segmentation, feature extraction, indexing, and retrieval of an image are the tasks required in retrieving images that contain similar regions as specified in a query. The idea of the region of interest-based image retrieval concepts is presented in this paper and it is expected to accommodate researchers that are working in the region-based image retrieval system field. This paper reviews the work of image retrieval researchers in the span of twenty years. The main goal of this paper is to provide a comprehensive reference source for scholars involved in image retrieval based on ROI.
Local search algorithms based on benchmark test functions problem
Authors: Bassel Atheer , M. Haglan Hussein , Sh. Mahmoud Akeel
Published: August 2020

Optimization process is normally implemented to solve several objectives in the form of single or multi-objectives modes. Some traditional optimization techniques are computationally burdensome which required exhaustive computational times. Thus, many studies have invented new optimization techniques to address the issues. To realize the effectiveness of the proposed techniques, implementation on several benchmark functions is crucial. In solving benchmark test functions, local search algorithms have been rigorously examined and employed to diverse tasks. This paper highlights different algorithms implemented to solve several problems. The capacity of local search algorithms in the resolution of engineering optimization problem including benchmark test functions is reviewed. The use of local search algorithms, mainly Simulated Annealing (SA) and Great Deluge (GD) according to solve different problems is presented. Improvements and hybridization of the local search and global search algorithms are also reviewed in this paper. Consequently, benchmark test functions are proposed to those involved in local search algorithm.