bluuebunny/crossref_metadata_2025_split huggingface dataset:
Characteristics of Process Parameters in Fused Deposition Modelling Process
Authors: Siregar Ikhsan , Saedon J.B. , Adenan Mohd Shahriman , Azmi Mohammad Firdaus Mohammed 
Published: May 2020

Abstract
Additive manufacturing has received incredible attention as a crucial emerging technology as three-dimensional printing offers wide range of industrial applications. This article outlines empirical analyses on the influence of key process parameters such as print speed, infill speed and layer resolution on roughness of the surface and time taken of Fused Deposition Modelling (FDM) processed of Polylactic Acid (PLA) part. Influence of each parameter couple with analysis of variance were utilize using full factorial design. The optimum parameters setting for best surface roughness and lower machining time also being determined. Experimental results indicate that optimal factor settings for each performance characteristic are different.
Bearing Damage Detection using Support Vector Machine
Authors: Sukendi  , Isranuri Ikhwansyah , Suherman  
Published: May 2020

Abstract
Vibration can be used for preventive condition monitoring in industrial equipment. Vibration measurement may avoid unexpected damages. The measurement data can be analyzed either by using signal processing or machine learning. This work assessed bearing damage detection as bearing is intensively used in industrial mechanical equipment. The assessment was performed experimentally by developing system prototype and measurement tools, including the use of laser vibrometer and a labjack as well as support vector machine to predict some types of damages. The work has been able to predict the BPFI, BPFO, BSF, and FTF damages by 93.125% accuracy. However, accuracy plunged to 61.25% when bearing damages were of three types: BPFO, BSF and FTF.
Facial Recognition-Based Automatic Door Access System Using Extreme Learning Machine
Authors: Rahmat R F , Zai E N , Fawwaz I , Aulia I 
Published: May 2020

Abstract
Facial recognition is one of the best forms of security since it is biometric-based security that uses biological features of the face. One of the artificial neural networks that can be implemented in the face recognition case is Extreme Learning Machine with the assistance of Local Binary Pattern in obtaining the facial features. The testing process in this study used 150 face images for training data and 60 face images for test data. The test was carried out using several three parameters of the hidden neuron numbers, namely 10, 30, and 50, and also five parameters of the image condition, namely feature, expression, face direction, lighting, and webcam distance. The system achieved the highest accuracy of 90% using 50 hidden neurons.
The Development of Mobile and Server Application for Traffic Data Collection Based on Location-Based Services (LBS)
Authors: Gunawan D , Priyanka  , Sitompul O S 
Published: May 2020

Abstract
Traffic data includes various data such as the number of vehicles, vehicle velocity, or travel time that might lead to meaningful information for the traffic engineers. This research aims to collect the traffic data based on the Location Based Services (LBS) by utilizing the Global Positioning System (GPS) in a smartphone. The drivers bring the smartphone and collecting the traffic data while driving the vehicle. It is done in real-time by running the mobile application in background service. The data includes the date, timestamp, latitude, longitude, device ID, and vehicle velocity. These data are temporarily stored in the internal smartphone database, then synchronized to the database in the server application. According to the result, the large number of online taxi drivers and a longer time to collect the data should be considered to cover a wide area.
Combination of Rail Fence Cipher Algorithm and Least Significant Bit Technique to Secure the Image File
Authors: Rachmawati Dian , Budiman Mohammad Andri , Yusuf Akhmad 
Published: May 2020

Abstract
Image is a visual representation of an object The process of sending information, especially images, can be done anywhere and with any intermediary, but not all information is public. Sometimes someone needs privacy or security from data or information that will be sent or received. One way to secure image files is to use cryptography. Cryptography is the study of how to keep data or messages safe when sent, from the sender to the recipient, without experiencing interference from third parties. In this study cryptography used is Rail Fence Cipher that was combined with steganography, so that the secret message could not be seen in plain view. Steganography serves to hide secret messages in other messages, so the secret is a very hidden existence. There are several methods in Steganography, one of which is Least Significant Bit. The concept of Least Significant Bit works by replacing the last bit of RGB image, where the message is converted first into bits. Based on experiments conducted on the Rail Fence Cipher algorithm, the time of encryption and decryption needed when the resolution of the image gets larger is linearly proportional to the value. The image does not show significant changes before and after inserting a secret message.
A vague memory can affect first-return time
Authors: Sakiyama Tomoko 
Published: May 2020

Abstract
First-return time is an important property for the return of particles or walkers to a start point. Recursive walks, which may be related to first-return time, are found in both random walk models and memory-based walk models. Achieving a balance between recursive walks and diffusive movements is a crucial but difficult modeling problem. Here, starting with a simple Brownian-walk model, I investigated how vague memorized information influences the first-return times of a walker. In the proposed model, the walker memorizes recently visited positions and recalls the direction in which it previously moved when returning to those positions. Using the recalled information, the walker then moves in the opposite direction to that previously traveled. In addition, the walker considers its recent experience and modifies its directional rules, i.e., memorized information, when the rule disturbs the recent flow of its movement. Thus, the proposed model effectively produces recursive walks in which a walker returns to a start point while demonstrating diffusive movements.
Quantum machine learning and quantum biomimetics: A perspective
Authors: Lamata Lucas 
Published: May 2020

AbstractQuantum machine learning has emerged as an exciting and promising paradigm inside quantum technologies. It may permit, on the one hand, to carry out more efficient machine learning calculations by means of quantum devices, while, on the other hand, to employ machine learning techniques to better control quantum systems. Inside quantum machine learning, quantum reinforcement learning aims at developing ‘intelligent’ quantum agents that may interact with the outer world and adapt to it, with the strategy of achieving some final goal. Another paradigm inside quantum machine learning is that of quantum autoencoders, which may allow one for employing fewer resources in a quantum device via a training process. Moreover, the field of quantum biomimetics aims at establishing analogies between biological and quantum systems, to look for previously inadvertent connections that may enable useful applications. Two recent examples are the concepts of quantum artificial life, as well as of quantum memristors. In this Perspective, we give an overview of these topics, describing the related research carried out by the scientific community.
Gene-based mediation analysis in epigenetic studies
Authors: Fang Ruiling , Yang Haitao , Gao Yuzhao , Cao Hongyan , Goode Ellen L , Cui Yuehua 
Published: May 2020

AbstractMediation analysis has been a useful tool for investigating the effect of mediators that lie in the path from the independent variable to the outcome. With the increasing dimensionality of mediators such as in (epi)genomics studies, high-dimensional mediation model is needed. In this work, we focus on epigenetic studies with the goal to identify important DNA methylations that act as mediators between an exposure disease outcome. Specifically, we focus on gene-based high-dimensional mediation analysis implemented with kernel principal component analysis to capture potential nonlinear mediation effect. We first review the current high-dimensional mediation models and then propose two gene-based analytical approaches: gene-based high-dimensional mediation analysis based on linearity assumption between mediators and outcome (gHMA-L) and gene-based high-dimensional mediation analysis based on nonlinearity assumption (gHMA-NL). Since the underlying true mediation relationship is unknown in practice, we further propose an omnibus test of gene-based high-dimensional mediation analysis (gHMA-O) by combing gHMA-L and gHMA-NL. Extensive simulation studies show that gHMA-L performs better under the model linear assumption and gHMA-NL does better under the model nonlinear assumption, while gHMA-O is a more powerful and robust method by combining the two. We apply the proposed methods to two datasets to investigate genes whose methylation levels act as important mediators in the relationship: (1) between alcohol consumption and epithelial ovarian cancer risk using data from the Mayo Clinic Ovarian Cancer Case-Control Study and (2) between childhood maltreatment and comorbid post-traumatic stress disorder and depression in adulthood using data from the Gray Trauma Project.
In Their Own Words: Douglas Futuyma
Authors: Verdier James M 
Published: May 2020

Abstract
In Their Own Words chronicles the stories of scientists who have made great contributions to their fields, particularly within the biological sciences. These short oral histories provide our readers a way to learn from and share their experiences. Each month, we will publish in the pages of BioScience and on our podcast, BioScience Talks (http://bioscienceaibs.libsyn.com), the results of these conversations. This oral history is with Douglas Futuyma, professor emeritus of ecology and evolution at Stony Brook University, in Stony Brook, New York. He previously served as president of the American Institute of Biological Sciences.
Note: Both the text and audio versions have been edited for clarity and length.
Comparing deep neural network and econometric approaches to predicting the impact of climate change on agricultural yield
Authors: Keane Michael , Neal Timothy 
Published: May 2020

SummaryPredicting the impact of climate change on crop yield is difficult, in part because the production function mapping weather to yield is high dimensional and nonlinear. We compare three approaches to predicting yields: (a) deep neural networks (DNNs), (b) traditional panel-data models, and (c) a new panel-data model that allows for unit and time fixed effects in both intercepts and slopes in the agricultural production function—made feasible by a new estimator called Mean Observation OLS (MO-OLS). Using U.S. county-level corn-yield data from 1950 to 2015, we show that both DNNs and MO-OLS models outperform traditional panel-data models for predicting yield, both in-sample and in a Monte Carlo cross-validation exercise. However, the MO-OLS model substantially outperforms both DNNs and traditional panel-data models in forecasting yield in a 2006–2015 holdout sample. We compare the predictions of all these models for climate change impacts on yields from 2016 to 2100.
The glycoconjugate-degrading enzymes of Clostridium perfringens: Tailored catalysts for breaching the intestinal mucus barrier
Authors: Low Kristin E , Smith Steven P , Abbott D Wade , Boraston Alisdair B 
Published: May 2020

Abstract
The gastrointestinal (GI) tract of humans and animals is lined with mucus that serves as a barrier between the gut microbiota and the epithelial layer of the intestine. As the proteins present in mucus are typically heavily glycosylated, such as the mucins, several enteric commensal and pathogenic bacterial species are well-adapted to this rich carbon source and their genomes are replete with carbohydrate-active enzymes targeted toward dismantling the glycans and proteins present in mucus. One such species is Clostridium perfringens, a Gram-positive opportunistic pathogen indigenous to the gut of humans and animals. The genome of C. perfringens encodes numerous carbohydrate-active enzymes that are predicted or known to target glycosidic linkages within or on the termini of mucus glycans. Through this enzymatic activity, the degradation of the mucosal layer by C. perfringens has been implicated in a number of GI diseases, the most severe of which is necrotic enteritis. In this review, we describe the wide array of extracellular glycoside hydrolases, and their accessory modules, that is possessed by C. perfringens, and examine the unique multimodularity of these proteins in the context of degrading the glycoconjugates in mucus as a potential component of disease.
The single EGF-like domain of mouse PAMR1 is modified by O-Glucose, O-Fucose and O-GlcNAc
Authors: Pennarubia Florian , Germot Agnès , Pinault Emilie , Maftah Abderrahman , Legardinier Sébastien 
Published: May 2020

AbstractEpidermal growth factor-like domains (EGF-LDs) of membrane and secreted proteins can be modified by N-glycans and/or potentially elongated O-linked monosaccharides such as O-glucose (O-Glc) found at two positions (O-Glc 1 and O-Glc2), O-fucose (O-Fuc) and O-N-acetylglucosamine (O-GlcNAc). The presence of three O-linked sugars within the same EGF-LD, such as in EGF-LD 20 of NOTCH1, has rarely been evidenced. We searched in KEGG GENES database to list mouse and human proteins with an EGF-LD sequence including one, two, three or four potential O-glycosylation consensus sites. Among the 129 murine retrieved proteins, most had predicted O-fucosylation and/or O-GlcNAcylation sites. Around 68% of EGF-LDs were subjected to only one O-linked sugar modification and near 5% to three modifications. Among these latter, we focused on the peptidase domain-containing protein associated with muscle regeneration 1 (PAMR1), having only one EGF-LD. To test the ability of this domain to be glycosylated, a correctly folded EGF-LD was produced in Escherichia coli periplasm, purified and subjected to in vitro incubations with the recombinant O-glycosyltransferases POGLUT1, POFUT1 and EOGT, adding O-Glc1, O-Fuc and O-GlcNAc, respectively. Using click chemistry and mass spectrometry, isolated PAMR1 EGF-LD was demonstrated to be modified by the three O-linked sugars. Their presence was individually confirmed on EGF-LD of full-length mouse recombinant PAMR1, with at least some molecules modified by both O-Glc1 and O-Fuc. Overall, these results are consistent with the presence of a triple O-glycosylated EGF-LD in mouse PAMR1.
Promoting sustainability through governance of eco-city indicators: a multi-spatial perspective
Authors: Deng Wu , Cheshmehzangi Ali , Ma Yuanli , Peng Zhen 
Published: May 2020

AbstractThe purpose of this paper is to present a case study of the latest practice on urban sustainability in China, focusing on the breakdown of city-wide overall indicators to a more controllable spatial level—i.e. individual land plots and individual buildings. We argue the importance of decomposing the indicators to smaller scales by understanding underlying principles such as indicators and their integration in the process of urban governance, i.e. enhancing multi-level policy coordination as an important and effective approach for developing eco-cities. This can provide a common ground of argument to monitor the progress at multiple spatial levels and form a collective effort to move a city towards sustainability. The novelty of this study is to highlight the role of eco-city development at multiple spatial levels and through urban governance. The local government needs to mobilize various stakeholders involved in the urban development process by providing sustainability targets in a transparent way. A collective effort from various stakeholder groups might be formed by linking them to a set of unified but spatial level-based targets.
Tumor Microenvironment Immune Response in Pancreatic Ductal Adenocarcinoma Patients Treated With Neoadjuvant Therapy
Authors: Michelakos Theodoros , Cai Lei , Villani Vincenzo , Sabbatino Francesco , Kontos Filippos , Fernández-del Castillo Carlos , Yamada Teppei , Neyaz Azfar , Taylor Martin S , Deshpande Vikram , Kurokawa Tomohiro , Ting David T , Qadan Motaz , Weekes Colin D , Allen Jill N , Clark Jeffrey W , Hong Theodore S , Ryan David P , Wo Jennifer Y , Warshaw Andrew L , Lillemoe Keith D , Ferrone Soldano , Ferrone Cristina R 
Published: May 2020

AbstractBackgroundNeoadjuvant folinic acid, fluorouracil, irinotecan, and oxaliplatin (FOLFIRINOX) and chemoradiation have been used to downstage borderline and locally advanced pancreatic ductal adenocarcinoma (PDAC). Whether neoadjuvant therapy-induced tumor immune response contributes to the improved survival is unknown. Therefore, we evaluated whether neoadjuvant therapy induces an immune response towards PDAC.MethodsClinicopathological variables were collected for surgically resected PDACs at the Massachusetts General Hospital (1998-2016). Neoadjuvant regimens included FOLFIRINOX with or without chemoradiation, proton chemoradiation (25 Gy), photon chemoradiation (50.4 Gy), or no neoadjuvant therapy. Human leukocyte antigen (HLA) class I and II expression and immune cell infiltration (CD4+, FoxP3+, CD8+, granzyme B+ cells, and M2 macrophages) were analyzed immunohistochemically and correlated with clinicopathologic variables. The antitumor immune response was compared among neoadjuvant therapy regimens. All statistical tests were 2-sided.ResultsTwo hundred forty-eight PDAC patients were included. The median age was 64 years and 50.0% were female. HLA-A defects were less frequent in the FOLFIRINOX cohort (P = .006). HLA class II expression was lowest in photon and highest in proton patients (P = .02). The FOLFIRINOX cohort exhibited the densest CD8+ cell infiltration (P &lt; .001). FOLFIRINOX and proton patients had the highest CD4+ and lowest T regulatory (FoxP3+) cell density, respectively. M2 macrophage density was statistically significantly higher in the treatment-naïve group (P &lt; .001) in which dense M2 macrophage infiltration was an independent predictor of poor overall survival.ConclusionsNeoadjuvant FOLFIRINOX with or without chemoradiation may induce immunologically relevant changes in the tumor microenvironment. It may reduce HLA-A defects, increase CD8+ cell density, and decrease T regulatory cell and M2 macrophage density. Therefore, neoadjuvant FOLFIRINOX therapy may benefit from combinations with checkpoint inhibitors, which can enhance patients’ antitumor immune response.
An uncommon case of inferior vena cava injury during atrial fibrillation ablation
Authors: Pastoricchio Manuela , Dell’Antonio Andrea , Zecchin Massimo , Bianco Elisabetta , Zucca Annalisa , Biloslavo Alan , Bortul Marina 
Published: May 2020

Abstract
A 64-year-old man underwent catheter ablation (CA) of atrial fibrillation with intracardiac echocardiography (ICE) assistance. As the probe was advanced toward the right atrium, sudden abdominal pain was felt by the patient with hypotension and tachycardia requiring fluids and vasopressors for hemodynamic stabilization. The inferior vena cava (IVC) was injured by the passing probe and open repair was then performed. To our knowledge, this is the first reported case of symptomatic IVC laceration by the probe used for ICE during CA.
Minidumbbell structures formed by ATTCT pentanucleotide repeats in spinocerebellar ataxia type 10
Authors: Guo Pei , Lam Sik Lok 
Published: May 2020

Abstract
Spinocerebellar ataxia type 10 (SCA10) is a progressive genetic disorder caused by ATTCT pentanucleotide repeat expansions in intron 9 of the ATXN10 gene. ATTCT repeats have been reported to form unwound secondary structures which are likely linked to large-scale repeat expansions. In this study, we performed high-resolution nuclear magnetic resonance spectroscopic investigations on DNA sequences containing two to five ATTCT repeats. Strikingly, we found the first two repeats of all these sequences well folded into highly compact minidumbbell (MDB) structures. The 3D solution structure of the sequence containing two ATTCT repeats was successfully determined, revealing the MDB comprises a regular TTCTA and a quasi TTCT/A pentaloops with extensive stabilizing loop-loop interactions. We further carried out in vitro primer extension assays to examine if the MDB formed in the primer could escape from the proofreading function of DNA polymerase. Results showed that when the MDB was formed at 5-bp or farther away from the priming site, it was able to escape from the proofreading by Klenow fragment of DNA polymerase I and thus retained in the primer. The intriguing structural findings bring about new insights into the origin of genetic instability in SCA10.
Reinforcing the Racial Structure: Observed Race and Multiracial Internet Daters’ Racial Preferences
Authors: Feliciano Cynthia , Kizer Jessica M 
Published: May 2020

AbstractIs the growing multiracial population changing the US racial structure? This study examines how self-identifying with more than one racial group relates to racial dating choices—an outcome that reveals multiracial individuals’ agency in the process of racial boundary-making and reduction. Quantitative analyses of profiles drawn from the largest online dating website, combined with observer racial classifications of profile photos, reveal divergent patterns in racial preferences among multiracials who self-identify as part-Black compared with those who do not. Non-Black multiracials express racial preferences that are more similar to Whites than to minorities, consistent with Whitening theories suggesting that these groups situate themselves closer to Whites and reinforce the existing racial hierarchy. In contrast, part-Black multiracials’ preferences are more similar to Blacks. However, regardless of racial self-identity, multiracial online daters’ exclusion of Whites as possible dates depends upon how they are racially perceived by others—their observed race. In particular, among self-identified part-Black multiracials, those whom others view as non-Black are much more accepting of Whites as dates than are those whom others classify as Black. Since preferences for dating Whites vary substantially among individuals who self-identify as part-Black depending upon their observed race, this suggests a decline in the salience of the one-drop rule, even while some aspects of Black exceptionalism persist among multiracials whom others classify solely as Black.