bluuebunny/crossref_metadata_2025 huggingface dataset:
Anemia and incidence of dementia in patients with new-onset type 2 diabetes: a nationwide population-based cohort study
Authors: Choi Jae Woo , Kim Tae Hyun , Han Euna
Published: August 2020

Introduction

This study aimed to examine the association between anemia and the incidence of dementia in patients with new-onset type 2 diabetes.

Research design and methods

This study used the Korean National Health Insurance Service-Health Screening Cohort and included 32 590 participants aged ≥40 years who were diagnosed with new-onset type 2 diabetes between 2004 and 2007 and followed up until 2013. Anemia was defined according to the criteria provided by the WHO, hemoglobin <120 g/L for women and <130 g/L for men, and was measured from after diagnosis date of type 2 diabetes to 2007. Dementia was defined by the Classification of Diseases 10th revision code as primary diagnosis and was measured from after hemoglobin measurement to 2013. We calculated the adjusted HR (AHR) and 95% CI to assess the risk of dementia using multivariable Cox proportional hazards regression models.

Results

We identified 1682 patients who developed dementia within a 7.5-year follow-up. Among patients with type 2 diabetes, patients with anemia were associated with an increased risk of dementia than those without anemia (AHR, 1.21; 95% CI 1.06 to 1.39). Patients with mild (AHR, 1.18; 95% CI 1.03 to 1.38) and moderate (AHR, 1.39; 95% CI 1.06 to 1.83) anemia were associated with an increased risk of dementia than those without anemia among patients with type 2 diabetes. Men (AHR, 1.47; 95% CI 1.16 to 1.83) and middle-aged adults (AHR, 1.31; 95% CI 1.03 to 1.75) with anemia were associated with an increased risk of dementia than their counterparts without anemia among patients with type 2 diabetes.

Conclusions

Our findings suggest that anemia is significantly associated with an increased risk of dementia among patients with newly diagnosed type 2 diabetes.
Future role for adoptive T-cell therapy in checkpoint inhibitor-resistant metastatic melanoma
Authors: Borch Troels Holz , Andersen Rikke , Ellebaek Eva , Met Özcan , Donia Marco , Marie Svane Inge
Published: August 2020

Personalized cell therapy targeting tumor antigens with expanded tumor-infiltrating lymphocytes (TILs) has shown great promise in metastatic melanoma (MM) since the 90s. However, MM was first-in line to benefit from the wave of checkpoint inhibitors (CPI), which shifted the focus of immunotherapy almost fully to immune CPI. Still, the majority of patients fail to benefit from CPI treatment, raising the intriguing question on how TIL therapy may fit into the changing landscape of melanoma treatment. We took advantage of data from a unique cohort of patients with MM treated with T-cell therapy in consecutive clinical trials at our institution across the last 10 years. Based on detailed data on patient characteristics, pre-TIL and post-TIL treatments and long-term follow-up, we were able to address the important issue of how TIL therapy can be positioned in the current CPI era. We found that previous progression on anticytotoxic T-lymphocyte-associated protein 4 do not seem to harm neither rate nor duration of response to TIL therapy. Importantly, even in the hard-to-treat population of patients who progressed on antiprogrammed cell death protein 1 (anti-PD-1), an objective response rate of 32% was achieved, including durable responses. Yet, median progression-free survival was reduced in this anti-PD-1 refractory population. Trial registration number: ClinicalTrials.gov ID: NCT00937625, NCT02379195 and NCT02354690.
DSR-GUP Black Hole based on COW experiment and Einstein–Bohr’s photon box
Authors: Farahani Nasrin , Hassanabadi Hassan , Kříž Jan , Chung Won Sang , Zarrinkamar Saber
Published: August 2020

In this paper, by studying the COW experiment and the Einstein Bohr’s photon box, we investigate the associated modified phase shift and Hawking temperature. Next, we comment on the effective Newton constant suggested by the doubly special relativity based on the generalized uncertainty principle.
Enhanced photocatalytic performance of NaNbO3 nanorods by loading Al2O3 nanoparticles
Authors: Xia Hetian , Zhao Yu , Li Weili , Song Ruixuan , Zhang Yulei , Fei Weidong
Published: August 2020

Herein, we report the fabrication of UV-active NaNbO3/Al2O3 (30 wt.%) ferroelectric heterojunction photocatalyst with enhanced photoelectrochemical activity to Methylene Blue (MB). Pure NaNbO3 nanorods (NRs) were synthesized by a facile hydrothermal process and NaNbO3/Al2O3 composite was prepared by an ultrasonic vibration method. The heterostructures showed a remarkable increase in photocurrent density and the MB degradation ratio reached 88% in the initial 15 min and eventually reached 98.6% in 75 min. The high photocatalytic efficiency is attributed to the ferroelectric polarization of NaNbO3 with the forming of heterojunction electric fields assisted by Al2O3. These properties demonstrate that NaNbO3/Al2O3 ferroelectric heterojunction photocatalyst shows promising photoactivity and provides an effective method to improve the photocatalytic properties of other ferroelectrics.
Band engineering of borophene superlattice based on zigzag nanoribbons: A DFT study
Authors: Zhang Yi , Ju Weiwei , Li Tongwei , Li Haisheng
Published: August 2020

By performing density functional theory (DFT) calculations, we demonstrate that periodically repeating heterostructures of zigzag borophene nanoribbons (BNR) of different widths can form stable borophene superlattice (BSL). The energy band structures of BSL can be modulated through modifying the width and length of the segments. A metal-semiconductor transition can be obtained when the length of each segment is lengthened, whereas, the magnetism of BSL is influenced by the width of the segments. In those magnetic systems, the magnetic moments are mainly localized on protruding B atoms located at the edge, while no magnetic moments occur in the center B atoms. The hydrogenated BNR and BSL are further investigated. The hydrogenation can modify the electronic properties of BNR and BSL as well as quench the magnetism. All hydrogenated BNR and BSL are non-magnetic. Our results indicate that great potential exists in these systems for borophene utilization in nanoelectronics and spintronics.
Decision Support Techniques for Dermatology Using Case-Based Reasoning
Authors: Jiji G. Wiselin , Rajesh A. , Raj P. Johnson Durai
Published: August 2020

Identification of skin disease has become a challenging task with the origination of various skin diseases. This paper presents a case-based reasoning (CBR) decision support system to enhance dermatological diagnosis for rural and remote communities. In this proposed work, an automated way is introduced to deal with the inconsistency problem in CBRs. This new hybrid architecture is to support the diagnosis in multiple skin diseases. The architecture used case-based reasoning terminology facilitates the medical diagnosis. Case based reasoning system retrieves the data which contains symptoms and treatment plan of the disease from the data repository by the way of matching visual contents of the image, such as shape, texture, and color descriptors. The extracted feature vector is fed into a framework to retrieve the data. The results proved using ROC curve that the proposed architecture yields high contribution to the computer-aided diagnosis of skin lesions. In experimental analysis, the system yields a specificity of 95.25% and a sensitivity of 86.77%. Our empirical evaluation has a superior retrieval and diagnosis performance when compared to the performance of other works.
Complex Systems and How Complex Non-Profits can Harness the Flow of Information
Authors: Freeburg Darin
Published: August 2020

Non-profits must continuously adapt themselves to changing circumstances, but they often lack the resources necessary to adapt successfully. This paper proposes a model to help non-profits overcome this challenge. It explains the role of information in the adaptation of complex systems and suggests a process that non-profits can follow to direct the flow of this information. The Information for Innovation Model (IIM) presented in the paper explains how the inflow and outflow of information influences a system’s adaptation. A series of steps are then proposed for the design of Communities of Practice (CoP) that can help organisations implement the model. Librarians, trained in information-seeking and focused on increasing their reach beyond the library, can support a non-profit following these steps. This paper contributes to the literature on complexity science by articulating a process that organisations can follow to influence the inflow and outflow of information. This process highlights new roles for both CoPs and librarians within non-profits. This is important because non-profits often lack resources necessary for innovation, and librarians are looking for new ways to extend their reach.
Emergent classical universes from initial quantum states in a tomographical description
Authors: Stornaiolo Cosimo
Published: August 2020

Quantum and classical physical states are represented in a unified way when they aredescribed by symplectic tomography. Therefore this representation allows us to study directly the necessary conditions for a classical universe to emerge from a quantum state. In a previous work on the de Sitter universe this was done by comparing the classical limit of the quantum tomograms with those resulting from the classical cosmological equations.

In this paper, we first review these results and extend them to all the de Sitter models. We show further that these tomograms can be obtained directly from transposing the Wheeler–De Witt equation to the tomographic variables. Subsequently, because the classic limits of the quantum tomograms are identified with their asymptotic expressions, we find the necessary conditions to extend the previous results by taking the tomograms of the WKB solutions of the Wheeler–DeWitt equation with an any potential. Furthermore, in the previous works, we found that the de Sitter models undergo the quantum-to-classical transition when the cosmological constant decays to its present value, we discuss at the end how far we can extend this result to more general models.

In the conclusions, after discussing any improvements and developments of the results of this work, we sketch a phenomenological approach from which to extract information about the initial states of the universe.
Parametric Study of Droplet Formation and Characteristics Within Microfluidic Devices — A Case Study
Authors: Salehi Seyedeh Sarah , Shamloo Amir , Hannani Siamak Kazemzadeh
Published: August 2020

Droplet-based microfluidics technologies hold great attention in a wide range of applications, including chemical analysis, drug screening, and food industries. This work aimed to describe the effects of different physical properties of the two immiscible phases on droplet formation in a flow-focusing microfluidic device and determining proper flow rates to form a droplet within the desired size range. A numerical model was developed to solve the governing equations of two-phase flow and the results were validated with previous experimental results. The results demonstrate different types of droplet formation regimes from dripping to jetting and different production rates of droplets as a consequence of the impact of each property on fluid flow, including the viscosity ratio, density, interfacial tension, and the flow rate ratio. Based on the results, flow rate, viscosity, and interfacial tension strongly affect the droplet formation regime as well as its size and shape. Droplet diameter increases by increasing the dispersed to continuous phase flow rate as well as the interfacial tension while it decreases by increasing the viscosity ratio and the continuous phase density. Moreover, the formation of satellite droplets was modeled, and the effect of interfacial tension, the viscosity of the dispersed phase and the continuous phase density were found to be important on the conditions that the satellite droplets are suppressed. Since the formation of the satellite droplets induces polydispersity in droplet size, this phenomenon is avoided. Collectively, choosing appropriate aqueous and oil phases with proper physical properties is crucial in forming monodisperse droplets with defined size and shape.
The First Moments and Semi-Moments of Fuzzy Variables Based on an Optimism-Pessimism Measure with Application for Portfolio Selection
Authors: Dzuche Justin , Tassak Christian Deffo , Kamdem Jules Sadefo , Fono Louis Aimé
Published: August 2020

Possibility, necessity and credibility measures are used in the literature in order to deal with imprecision. Recently, Yang and Iwamura [L. Yang and K. Iwamura, Applied Mathematical Science 2(46) (2008) 2271–2288] introduced a new measure as convex linear combination of possibility and necessity measures and they determined some of its axioms. In this paper, we introduce characteristics (parameters) of a fuzzy variable based on that measure, namely, expected value, variance, semi-variance, skewness, kurtosis and semi-kurtosis. We determine some properties of these characteristics and we compute them for trapezoidal and triangular fuzzy variables. We display their application for the determination of optimal portfolios when assets returns are described by triangular or trapezoidal fuzzy variables.
Connected Soft Graph
Authors: Thenge Jyoti D. , Reddy B. Surendranath , Jain Rupali S.
Published: August 2020

The theory of soft set offers a mathematical tool to deal with uncertainty. Nowadays, work on soft graph theory is progressing rapidly. In this paper, we define connected soft graph and derive some results. We also define cut vertex and bridge of soft graph along with some results on it.
Enigma Variations: A Review Article
Authors: Vela Velupillai K.
Published: August 2020

In this essay, which began as a Review Article of the book X, Y & Z: The Real Story of How Enigma was Broken by Dermot Turing, I discuss some of the background details of the Enigma Cypher Machine. The machine was supposed to be ‘unbreakable’, as claimed (in particular) by the manufacturers. It was repeatedly broken by Polish and British mathematicians, employed in their respective countries’ (and France’s) bureaus; in particular, heroically, by Alan Turing (at Bletchley Park, UK) and Marian Rejewski (in Poznań, Warsaw and France) — but others played important parts, too.
Influential Performance of Nodes Identified by Relative Entropy in Dynamic Networks
Authors: Marjai Péter , Kiss Attila
Published: August 2020

For decades, centrality has been one of the most studied concepts in the case of complex networks. It addresses the problem of identification of the most influential nodes in the network. Despite the large number of the proposed methods for measuring centrality, each method takes different characteristics of the networks into account while identifying the “vital” nodes, and for the same reason, each has its advantages and drawbacks. To resolve this problem, the TOPSIS method combined with relative entropy can be used. Several of the already existing centrality measures have been developed to be effective in the case of static networks, however, there is an ever-increasing interest to determine crucial nodes in dynamic networks. In this paper, we are investigating the performance of a new method that identifies influential nodes based on relative entropy, in the case of dynamic networks. To classify the effectiveness, the Suspected-Infected model is used as an information diffusion process. We are investigating the average infection capacity of ranked nodes, the Time-Constrained Coverage as well as the Cover Time.
Therapeutic observation of electroacupuncture treatment for primary dysmenorrhea
Authors: Hu Tiantian , Shen Lihua , Du Yijie
Published: August 2020

Objective: To observe the clinical efficacy of electroacupuncture treatment for primary dysmenorrhea.

Methods: In total 75 patients with primary dysmenorrhea were randomized into electroacupuncture with point injection group (37 patients), and electroacupuncture group (38 patients). Cox Menstrual Symptom Scale (CMSS) and Visual Analogue Scale (VAS) were observed before and after three treatment interventions, and the clinical efficacies were compared.

Results: The total effective rates were 91.9% and 86.8%, and the difference was not significant ([Formula: see text]).

Conclusions: Electroacupuncture with point injection and electroacupuncture are effective methods in treating primary dysmenorrhea, and the difference between the two groups is not statistically significant.
The
Proceedings of the Yorkshire Geological Society
and its contribution to the study of the Chalk Group of northern England
Authors: Hildreth P. N.
Published: August 2020

Papers devoted to chalk-related topics have varied in frequency since the foundation of a geological society in Yorkshire. There have been contributions from vicars, corn merchants, a wallpaper manufacturer, a corset maker and a car salesman, as well as academics and professional geologists. Many early ideas have become established. Indeed, the concept of a Chalk Group Northern Province was suggested by the Reverend J.F. Blake as early as 1878. The keen observation and painstaking recording of other early workers such as Lamplugh on Flamborough Head were continued in the late twentieth century by, for example, Whitham and Mitchell, and the advent of modern technology enabled new dimensions of study. Following a ‘dark age’ of very few contributions, a 1978 publication, though short, finally proposed an accepted lithostratigraphy for the northern chalk that is distinct from that of the south, and in so doing became what might be considered a milestone paper. This ‘renaissance’ bloomed into a ‘golden age’; North Sea activities, advanced technology and a rekindling of interest in chalk stratigraphy and palaeontology all contributed to the publication of a spate of papers. Exactly 50% of all papers and over 50% of all authors involved were published between 1987 and the present day.
An Overview of Hardware Implementation of Membrane Computing Models
Authors: Zhang Gexiang , Shang Zeyi , Verlan Sergey , Martínez-del-Amor Miguel Á. , Yuan Chengxun , Valencia-Cabrera Luis , Pérez-Jiménez Mario J.
Published: August 2020

The model of membrane computing, also known under the name of P systems, is a bio-inspired large-scale parallel computing paradigm having a good potential for the design of massively parallel algorithms. For its implementation it is very natural to choose hardware platforms that have important inherent parallelism, such as field-programmable gate arrays (FPGAs) or compute unified device architecture (CUDA)-enabled graphic processing units (GPUs). This article performs an overview of all existing approaches of hardware implementation in the area of P systems. The quantitative and qualitative attributes of FPGA-based implementations and CUDA-enabled GPU-based simulations are compared to evaluate the two methodologies.
Design Guidelines and Recommendations for Multimodal, Touchscreen-based Graphics
Authors: Gorlewicz Jenna L. , Tennison Jennifer L. , Uesbeck P. Merlin , Richard Margaret E. , Palani Hari P. , Stefik Andreas , Smith Derrick W. , Giudice Nicholas A.
Published: August 2020

With content rapidly moving to the electronic space, access to graphics for individuals with visual impairments is a growing concern. Recent research has demonstrated the potential for representing basic graphical content on touchscreens using vibrations and sounds, yet few guidelines or processes exist to guide the design of multimodal, touchscreen-based graphics. In this work, we seek to address this gap by synergizing our collective research efforts over the past eight years and implementing our findings into a compilation of recommendations, which we validate through an iterative design process and user study. We start by reviewing previous work and then collate findings into a set of design guidelines for generating basic elements of touchscreen-based multimodal graphics. We then use these guidelines to generate exemplary graphics in mathematics, specifically bar charts and geometry concepts. We discuss the iterative design process of moving from guidelines to actual graphics and highlight challenges. We then present a formal user study with 22 participants with visual impairments, comparing learning performance on using touchscreen-rendered graphics to embossed graphics. We conclude with qualitative feedback from participants on the touchscreen-based approach and offer areas of future investigation as these recommendation are expanded to include more complex graphical concepts.
FOX
Authors: Lyu Tianshu , Bing Lidong , Zhang Zhao , Zhang Yan
Published: August 2020

Community detection is a hot topic for researchers in the fields of graph theory, social networks, and biological networks. Generally speaking, a community refers to a group of densely linked nodes in the network. Nodes usually have more than one community label, indicating their multiple roles or functions in the network. Unfortunately, existing solutions aiming at overlapping community detection are not capable of scaling to large-scale networks with millions of nodes and edges. In this article, we propose a fast-overlapping-community-detection algorithm—FOX. In the experiment on a network with 3.9 millions nodes and 20 millions edges, the detection finishes in 41 min and provides the most qualified results. The second-fastest algorithm, however, takes almost five times longer to run. As for another network with 22 millions nodes and 127 millions edges, our algorithm is the only one that can provide an overlapping community detection result and it only takes 533 min. Our algorithm is a typical heuristic algorithm, measuring the closeness of a node to a community by counting the number of triangles formed by the node and two other nodes in the community. We also extend the exploitation of triangle to open-triangle, which enlarges the scale of the detected communities.
A dependently typed calculus with pattern matching and erasure inference
Authors: Tejiščák Matúš
Published: August 2020

Some parts of dependently typed programs constitute evidence of their type-correctness and, once checked, are unnecessary for execution. These parts can easily become asymptotically larger than the remaining runtime-useful computation, which can cause normally linear-time programs run in exponential time, or worse. We should not make programs run slower by just describing them more precisely.

Current dependently typed systems do not erase such computation satisfactorily. By modelling erasure indirectly through type universes or irrelevance, they impose the limitations of these means to erasure. Some useless computation then cannot be erased and idiomatic programs remain asymptotically sub-optimal.

In this paper, we explain why we need erasure, that it is different from other concepts like irrelevance, and propose a dependently typed calculus with pattern matching with erasure annotations to model it. We show that erasure in well-typed programs is sound in that it commutes with reduction. Assuming the Church-Rosser property, erasure furthermore preserves convertibility in general.

We also give an erasure inference algorithm for erasure-unannotated or partially annotated programs and prove it sound, complete, and optimal with respect to the typing rules of the calculus.

Finally, we show that this erasure method is effective in that it can not only recover the expected asymptotic complexity in compiled programs at run time, but it can also shorten compilation times.
Compiling effect handlers in capability-passing style
Authors: Schuster Philipp , Brachthäuser Jonathan Immanuel , Ostermann Klaus
Published: August 2020

Effect handlers encourage programmers to abstract over repeated patterns of complex control flow. As of today, this abstraction comes at a significant price in performance. In this paper, we aim to achieve abstraction without regret for effect handlers.

We present a language for effect handlers in _capability-passing style_ (λ

Cap

) and an implementation of this language as a translation to simply-typed lambda calculus in _iterated continuation-passing style_. A suite of benchmarks indicates that the novel combination of capability-passing style and iterated CPS enables significant speedups over existing languages with effect handlers or control operators. Our implementation technique is general and allows us to generate code in any language that supports first-class functions.

We then identify a subset of programs for which we can further improve the performance and guarantee full elimination of the effect handler abstraction. To formally capture this subset, we refine λ

Cap

to λ λ

Cap

with a more restrictive type system. We present a type-directed translation for λ λ

Cap

that inserts staging annotations and prove that no abstractions or applications related to effect handlers occur in the translated program. Using this second translation we observe additional speedups in some of the benchmarks.
Scala step-by-step: soundness for DOT with step-indexed logical relations in Iris
Authors: Giarrusso Paolo G. , Stefanesco Léo , Timany Amin , Birkedal Lars , Krebbers Robbert
Published: August 2020

The metatheory of Scala’s core type system—theDependent Object Types (DOT)calculus—is hard to extend, like the metatheory of other type systems combining subtyping and dependent types. Soundness of important Scala features therefore remains an open problem in theory and in practice. To address some of these problems, we use asemantics-firstapproach to develop a logical relations model for a new version of DOT, calledguarded DOT (gDOT). Our logical relations model makes use of an abstract form ofstep-indexing, as supported by the Iris framework, to model various forms of recursion in gDOT. To demonstrate the expressiveness of gDOT, we show that it handles Scala examples that could not be handled by previous versions of DOT, and prove using our logical relations model that gDOT provides the desired data abstraction. The gDOT type system, its semantic model, its soundness proofs, and all examples in the paper have been mechanized in Coq.
Sealing pointer-based optimizations behind pure functions
Authors: Selsam Daniel , Hudon Simon , de Moura Leonardo
Published: August 2020

Functional programming languages are particularly well-suited for building automated reasoning systems, since (among other reasons) a logical term is well modeled by an inductive type, traversing a term can be implemented generically as a higher-order combinator, and backtracking search is dramatically simplified by persistent datastructures. However, existing pure functional programming languages all suffer a major limitation in these domains: traversing a term requires time proportional to the tree size of the term as opposed to its graph size. This limitation would be particularly devastating when building automation for interactive theorem provers such as Lean and Coq, for which the exponential blowup of term-tree sizes has proved to be both common and difficult to prevent. All that is needed to recover the optimal scaling is the ability to perform simple operations on the memory addresses of terms, and yet allowing these operations to be used freely would clearly violate the basic premise of referential transparency. We show how to use dependent types to seal the necessary pointer-address manipulations behind pure functional interfaces while requiring only a negligible amount of additional trust. We have implemented our approach for the upcoming version (v4) of Lean, and our approach could be adopted by other languages based on dependent type theory as well.
Capital Flows and Leverage
Authors: Kalemli-Özcan Şebnem , Kwak Jun Hee
Published: August 2020

This article surveys the literature on capital flows and leverage. We summarize results from the existing papers and document new facts. The empirical literature takes both a macro and a micro approach. The macro approach focuses on aggregate data both over time and in the cross-section of countries, and it documents a positive correlation between total capital flows, build-ups in terms of external and domestic debt to GDP ratio, and financial crises. The micro approach uses granular data and focuses on leverage at the firm and bank level and associates this leverage with country-level capital flows and related exchange rate movements. We document new facts from a hybrid approach that focuses on the relationship between sector-level capital flows and sectoral leverage. We highlight the interconnections between different approaches and argue that harmonization of the macro and micro approaches can yield a more complete understanding of the effect of capital flows on country-, sector-, and firm- and bank-level leverage associated with credit booms and busts.
A Superoxide Involved Oxygen Reduction Reaction Mechanism on a Glassy Carbon Electrode in Caustic Media
Authors: Mattick Victoria F. , Jin Xinfang , White Ralph E. , Huang Kevin
Published: August 2020

In this work, a plain glassy carbon electrode has been investigated as a base platform to build a superoxide-ion-involved, 2-dimensional, multi-physics model to describe its oxygen reduction mechanism in caustic media. A rotating ring disk technique has been used to quantify the peroxide content and to compare the results predicted by a general multiphysics model, which was further used to extract the influencing kinetic parameters. There are three proposed models involving different mechanism combinations made up of: a sequential, single electron reduction of oxygen to superoxide, then to peroxide; a sequential two electron reduction of oxygen to peroxide followed by the final reduction to hydroxide; and a direct four electron reduction of oxygen straight to hydroxide. One model stands out to be the best description for the multistep oxygen reduction behavior of the glassy carbon electrode in 0.1 M KOH with very satisfactory results, which yields a series of important electrode kinetic transfer coefficients and exchange current densities for the elementary electrochemical reactions considered.
Machine learning-based classification and diagnosis of clinical cardiomyopathies
Authors: Alimadadi Ahmad , Manandhar Ishan , Aryal Sachin , Munroe Patricia B. , Joe Bina , Cheng Xi
Published: August 2020

Dilated cardiomyopathy (DCM) and ischemic cardiomyopathy (ICM) are two common types of cardiomyopathies leading to heart failure. Accurate diagnostic classification of different types of cardiomyopathies is critical for precision medicine in clinical practice. In this study, we hypothesized that machine learning (ML) can be used as a novel diagnostic approach to analyze cardiac transcriptomic data for classifying clinical cardiomyopathies. RNA-Seq data of human left ventricle tissues were collected from 41 DCM patients, 47 ICM patients, and 49 nonfailure controls (NF) and tested using five ML algorithms: support vector machine with radial kernel (svmRadial), neural networks with principal component analysis (pcaNNet), decision tree (DT), elastic net (ENet), and random forest (RF). Initial ML classifications achieved ~93% accuracy (svmRadial) for NF vs. DCM, ~82% accuracy (RF) for NF vs. ICM, and ~80% accuracy (ENet and svmRadial) for DCM vs. ICM. Next, 50 highly contributing genes (HCGs) for classifying NF and DCM, 68 HCGs for classifying NF and ICM, and 59 HCGs for classifying DCM and ICM were selected for retraining ML models. Impressively, the retrained models achieved ~90% accuracy (RF) for NF vs. DCM, ~90% accuracy (pcaNNet) for NF vs. ICM, and ~85% accuracy (pcaNNet and RF) for DCM vs. ICM. Pathway analyses further confirmed the involvement of those selected HCGs in cardiac dysfunctions such as cardiomyopathies, cardiac hypertrophies, and fibrosis. Overall, our study demonstrates the promising potential of using artificial intelligence via ML modeling as a novel approach to achieve a greater level of precision in diagnosing different types of cardiomyopathies.
Descriptive Cross-Sectional Study on Knowledge, Awareness, and Adherence to Medication among Hypertensive Patients at a Tertiary Care Centre in Colombo District, Sri Lanka
Authors: Pirasath S. , Sugathapala A. G. H. , Wanigasuriya K.
Published: August 2020

Objective. This study was aimed to assess the patient’s knowledge and awareness about hypertension and adherence to antihypertensive medication among hypertensive patients. Methods. The descriptive cross-sectional study was conducted in three medical clinics of Colombo South Teaching hospital, Kalubowila, Sri Lanka, from April 2019 to September 2019. Total of 384 hypertensive patients were recruited by systematic randomized controlled sampling and interviewed with validated questionnaires to assess their knowledge about hypertension and adherence to antihypertensive medication. Data were analyzed using SPSS (version 21) analytical package, and the chi-squared test was performed. Results. The total sample consisted of 384 hypertensive patients with a mean age of 59.32 (±12.34SD). This included 180 (46.9%) males and 204 (53.1%) females. The male : female ratio was approximately 9 : 10. Most of patients were with primary and ordinary educational status (65.9%), normal body mass index (54.9%), mild elevation of LDL cholesterol (76.3%), and coexistent ischemic heart disease (39.6%). The knowledge about hypertension among majority of patients was reasonable. However, they were unaware about normal values of blood pressure (69%, 95% of CI 1.92–2.09) and diagnostic values of hypertension (90.1%, 95% of CI 2.26–2.40). Moreover, they were unaware of their blood pressure values at time of diagnosis (75.3%, 95% of CI 2.09–2.25), at recent clinic visit (71.3%, 95% of CI 2.0-2.17), and target level (81.8%, 95% of CI 2.25-2.41). Most patients had adequate knowledge about the risk factors and complications of hypertension and were aware of their target organ damage (70.3%). Most patients believed that medication alone is not sufficient to control blood pressure (41.7%, 95% of CI 1.40-1.51) and adequate control of their blood pressure reduces complications (68.2%, 95% of CI 1.37-1.51). Most of the patients (71.8%) had reasonable good drug compliance. The forgetfulness was commonly attributed for nonadherence (69%, 95% of CI 1.26-1.36). Conclusions. The knowledge about hypertension among majority of patients was reasonable. But, they were unaware about their disease status and their diagnosis, target, and recent blood pressure values. Most of patients had adequate knowledge about the risk factors and complications of hypertension. However, they were unaware about their target organ damage due to hypertension. The drug compliance was reasonable among them. The forgetfulness was common reason for nonadherence. Therefore, healthcare professionals should implement individualized educational programmes to increase the awareness of disease status, appropriate blood pressure levels, and adherence of treatment to improve the outcome of patients.
Effects of Laser Scanning Speed on Microstructure, Microhardness, and Corrosion Behavior of Laser Cladding Ni45 Coatings
Authors: Qiao Yanxin , Huang Jie , Huang Ding , Chen Jian , Liu Wen , Wang Zhengbin , Zhibin Zheng
Published: August 2020

The effects of laser scanning speed on the microstructure, microhardness, and corrosion behavior of Ni45 coatings were investigated by using optical microscopy (OM), scanning electron microscopy (SEM), X-ray diffraction (XRD), microhardness, and electrochemical measurements. The results showed that increasing laser scanning speed promotes the transformation from planar crystals to dendrites and refines the grains concurrently. The γ-(Ni, Fe), FeNi3, and M23(C,B)6 are identified as the primary phase composition in the Ni45 coatings regardless of the laser scanning speed. Thereinto, the formation and growth of M23(C,B)6 precipitates can be inhibited with increasing laser scanning speed due to the higher cooling rate, which affects the microhardness distribution and corrosion resistance of the coating. On the one hand, the microhardness of the whole coating presents a downtrend with increasing laser scanning speed due to the reduction of M23(C,B)6 phase. On the other hand, the corrosion resistance in 0.5 M NaCl solution is improved to some extent at higher laser scanning speed because the less precipitation of M23(C,B)6 reduces the depletion of Cr around the precipitates. In contrast, all the coatings exhibit undifferentiated but poor corrosion resistance in the highly corrosive 0.5 M NaCl + 0.5 M H2SO4 solution.
A Technical Note on the Application of Interpolation Method on Modeling of 3D Surface Rock Layer
Authors: Yin Songyu , Zhou Yu
Published: August 2020

The planning stages of dredging require comprehensive and detailed analyses. Identifying the dredging environment is one of the important points. A three‐dimensional (3D) geological modeling technology has been shown to be a robust tool for representing and analyzing the conditions of geology. From a general perspective, a 3D model is established by some spatial surfaces. Based on a dredging project, this study investigated the estimation capability of an interpolation method of triangulation combined with BP neural network, for modeling a rock layer surface. The performance of the proposed model is compared with some conventional methods in the literature. The results showed that this interpolation method is effective to be employed for surface modeling of the rock layer.
Investigating the GWAS-Implicated Loci for Rheumatoid Arthritis in the Pakistani Population
Authors: Aslam Muhammad Muaaz , John Peter , Fan Kang-Hsien , Bhatti Attya , Aziz Wajahat , Ahmed Bashir , Feingold Eleanor , Demirci F. Yesim , Kamboh M. Ilyas
Published: August 2020

Rheumatoid arthritis (RA) is a complex and multifactorial autoimmune disorder with the involvement of multiple genetic and environmental factors. Genome-wide association studies (GWAS) have identified more than 50 RA genetic loci in European populations. Given the anticipated overlap of RA-relevant genes and pathways across different ethnic groups, we sought to replicate 58 GWAS-implicated SNPs reported in Europeans in Pakistani subjects. 1,959 unrelated subjects comprising 1,222 RA cases and 737 controls were collected from three rheumatology facilities in Pakistan. Genotyping was performed using iPLEX or TaqMan® methods. A total of 50 SNPs were included in the final association analysis after excluding those that failed assay design/run or postrun QC analysis. Fourteen SNPs (LINC00824/rs1516971, PADI4/rs2240336, CEP57/rs4409785, CTLA4/rs3087243, STAT4/rs13426947, HLA-B/MICA/rs2596565, C5orf30/rs26232, CCL21/rs951005, GATA3/rs2275806, VPS37C/rs595158, HLA-DRB1/rs660895, EOMES/rs3806624, SPRED2/rs934734, and RUNX1/rs9979383) were replicated in our Pakistani sample at false discovery rate (FDR) of <0.20 with nominal p values ranging from 4.73E-06 to 3.48E-02. Our results indicate that several RA susceptibility loci are shared between Pakistani and European populations, supporting the role of common genes/pathways.
Analytical Solutions for Characterizing Fluid Flow through Sand-Pack in Pipes
Authors: Gao Shichen , Tian Zhixin , Teng Bailu
Published: August 2020

When fluid flows through a pipe that is packed with sand particles, the fluid will bear the resistance from the sand-pack, as well as the viscous shear from the pipe wall. If the viscous shear from the pipe wall can be neglected, the fluid flow will obey Darcy’s law, and one can think the equivalent permeability of the packed-pipe equals the permeability of the sand-pack. However, if the viscous shear from the pipe wall cannot be neglected, the fluid flow will obey the Brinkman equation, and the permeability of the packed-pipe will be less than that of the sand-pack due to the additional viscous drag. In this work, on the basis of the Brinkman equation, we derived a series of analytical solutions for characterizing the fluid flow in packed-pipes. These solutions can be used to depict the velocity profiles, estimate the flux rate, and calculate the equivalent permeability of a packed-pipe. On the basis of these analytical solutions, we found that Poiseuille’s law is a special form of the derived equivalent permeability solution. We further divided the fluid flow in a packed-pipe into three regimes, including N-S flow, Brinkman flow, and Darcy flow. During the regime of Brinkman flow, the dimensionless flow velocity at the pipe center is 1, and the dimensionless flow velocity is gradually decreased to 0 at the pipe wall. We also investigated the effects of sorting, sand particle size, and sand-pack porosity on the packed-pipe permeability. The calculated results show that a more uniform size of the sand particles or a smaller mean particle diameter can lead to lower packed-pipe permeability. Compared to the sorting and mean particle diameter, the sand-pack porosity exerts a more significant effect on the packed-pipe permeability.
Distinguishing Lymphomatous and Cancerous Lymph Nodes in 18F-Fluorodeoxyglucose Positron Emission Tomography/Computed Tomography by Radiomics Analysis
Authors: Zheng Bo , Wu Jiayi , Zhao Zixuan , Ou Xuejin , Cao Peng , Ma Xuelei
Published: August 2020

Background. The National Comprehensive Cancer Network guidelines recommend excisional biopsies for the diagnosis of lymphomas. However, resection biopsies in all patients who are suspected of having malignant lymph nodes may cause unnecessary injury and increase medical costs. We investigated the usefulness of 18F-fluorodeoxyglucose positron emission/computed tomography- (18F-FDG-PET/CT-) based radiomics analysis for differentiating between lymphomatous lymph nodes (LLNs) and cancerous lymph nodes (CLNs). Methods. Using texture analysis, radiomic parameters from the 18F-FDG-PET/CT images of 492 lymph nodes (373 lymphomatous lymph nodes and 119 cancerous lymph nodes) were extracted with the LIFEx package. Predictive models were generated from the six parameters with the largest area under the receiver operating characteristics curve (AUC) in PET or CT images in the training set (70% of the data), using binary logistic regression. These models were applied to the test set to calculate predictive variables, including the combination of PET and CT predictive variables (PREcombination). The AUC, sensitivity, specificity, and accuracy were used to compare the differentiating ability of the predictive variables. Results. Compared with the pathological diagnosis of the patient’s primary tumor, the AUC, sensitivity, specificity, and accuracy of PREcombination in differentiating between LLNs and CLNs were 0.95, 91.67%, 94.29%, and 92.96%, respectively. Moreover, PREcombination could effectively distinguish LLNs caused by various lymphoma subtypes (Hodgkin’s lymphoma and non-Hodgkin’s lymphoma) from CLNs, with the AUC, sensitivity, specificity, and accuracy being 0.85 and 0.90, 77.78% and 77.14%, 97.22% and 88.89%, and 90.74% and 83.10%, respectively. Conclusions. Radiomics analysis of 18F-FDG-PET/CT images may provide a noninvasive, effective method to distinguish LLN and CLN and inform the choice between fine-needle aspiration and excision biopsy for sampling suspected lymphomatous lymph nodes.
Applications of Fractional Lower Order Synchrosqueezing Transform Time Frequency Technology to Machine Fault Diagnosis
Authors: Wang Haibin , Long Junbo
Published: August 2020

Synchrosqueezing transform (SST) is a high resolution time frequency representation technology for nonstationary signal analysis. The short time Fourier transform-based synchrosqueezing transform (FSST) and the S transform-based synchrosqueezing transform (SSST) time frequency methods are effective tools for bearing fault signal analysis. The fault signals belong to a non-Gaussian and nonstationary alpha (α) stable distribution with 1<α<2 and even the noises being also α stable distribution. The conventional FSST and SSST methods degenerate and even fail under α stable distribution noisy environment. Motivated by the fact that fractional low order STFT and fractional low order S-transform work better than the traditional STFT and S-transform methods under α stable distribution noise environment, we propose in this paper the fractional lower order FSST (FLOFSST) and the fractional lower order SSST (FLOSSST). In addition, we derive the corresponding inverse FLOSST and inverse FLOSSST. The simulation results show that both FLOFSST and FLOSSST perform better than the conventional FSSST and SSST under α stable distribution noise in instantaneous frequency estimation and signal reconstruction. Finally, FLOFSST and FLOSSST are applied to analyze the time frequency distribution of the outer race fault signal. Our results show that FLOFSST and FLOSSST extract the fault features well under symmetric stable (SαS) distribution noise.
Short-Chain Fatty Acids Ameliorate Diabetic Nephropathy via GPR43-Mediated Inhibition of Oxidative Stress and NF-κB Signaling
Authors: Huang Wei , Man Yi , Gao Chenlin , Zhou Luping , Gu Junling , Xu Huiwen , Wan Qin , Long Yang , Chai Li , Xu Youhua , Xu Yong
Published: August 2020

Diabetic nephropathy (DN) is a chronic low-grade inflammatory disease. Oxidative stress and nuclear factor kappa B (NF-κB) signaling play an important role in the pathogenesis of DN. Short-chain fatty acids (SCFAs) produced from carbohydrate fermentation in the gastrointestinal tract exert positive regulatory effects on inflammation and kidney injuries. However, it is unclear whether SCFAs can prevent and ameliorate DN. In the present study, we evaluated the role and mechanism of the three main SCFAs (acetate, propionate, and butyrate) in high-fat diet (HFD) and streptozotocin- (STZ-) induced type2 diabetes (T2D) and DN mouse models and in high glucose-induced mouse glomerular mesangial cells (GMCs), to explore novel therapeutic strategies and molecular targets for DN. We found that exogenous SCFAs, especially butyrate, improved hyperglycemia and insulin resistance; prevented the formation of proteinuria and an increase in serum creatinine, urea nitrogen, and cystatin C; inhibited mesangial matrix accumulation and renal fibrosis; and blocked NF-κB activation in mice. SCFAs also inhibited high glucose-induced oxidative stress and NF-κB activation and enhanced the interaction between β-arrestin-2 and I-κBα in GMCs. Specifically, the beneficial effects of SCFAs were significantly facilitated by the overexpression GPR43 or imitated by a GPR43 agonist but were inhibited by siRNA-GPR43 in GMCs. These results support the conclusion that SCFAs, especially butyrate, partially improve T2D-induced kidney injury via GPR43-mediated inhibition of oxidative stress and NF-κB signaling, suggesting SCFAs may be potential therapeutic agents in the prevention and treatment of DN.