bluuebunny/crossref_metadata_2025 huggingface dataset:
Size does matter — the eco-evolutionary effects of changing body size in fish
Authors: Ahti Pauliina A. , Kuparinen Anna , Uusi-Heikkilä Silva
Published: May 2020

Body size acts as a proxy for many fitness-related traits. Body size is also subject to directional selection from various anthropogenic stressors such as increasing water temperature, decreasing dissolved oxygen, fisheries, as well as natural predators. Changes in individual body size correlate with changes in fecundity, behaviour, and survival and can propagate through populations and ecosystems by truncating age and size structures and changing predator–prey dynamics. In this review, we will explore the causes and consequences of changing body size in fish in the light of recent literature and relevant theories. We will investigate the central role of body size in ecology by first discussing the main selective agents that influence body size: fishing, increasing water temperature, decreasing dissolved oxygen, and predation. We will then explore the impacts of these changes at the individual, population, and ecosystem levels. Considering the relatively high heritability of body size, we will discuss how a change in body size can leave a genetic signature in the population and translate to a change in the evolutionary potential of the species.
Recent total cross section measurements in electron scattering from molecules
Authors: Szmytkowski Czesław , Możejko Paweł
Published: May 2020

The grand-total cross sections (TCSs) for electron scattering from a range of molecules, measured over the period 2009–2019 in various laboratories, with the use of different electron transmission systems, are reviewed. Where necessary, the presented TCS data are also compared to earlier results. Collection of investigated molecular targets (biomolecules, biofuels, molecules of technological application, hydrocarbons) reflects their current interest in biology, medicine, ecology and industry. Most of measurements covered the energy range from about 1 eV to some hundreds of eV, with a few exceptions extending those limits down to near thermal or up to almost high impact energies. The importance of reliable TCS data in the field of electron-scattering physics is emphasized. Problems encountered in TCS experiments are also specified.

Graphical abstract
On Component Connectivity of Hierarchical Star Networks
Authors: Gu Mei-Mei , Chang Jou-Ming , Hao Rong-Xia
Published: May 2020

For an integer [Formula: see text], the [Formula: see text]-component connectivity of a graph [Formula: see text], denoted by [Formula: see text], is the minimum number of vertices whose removal from [Formula: see text] results in a disconnected graph with at least [Formula: see text] components or a graph with fewer than [Formula: see text] vertices. This naturally generalizes the classical connectivity of graphs defined in term of the minimum vertex-cut. This kind of connectivity can help us to measure the robustness of the graph corresponding to a network. The hierarchical star networks [Formula: see text], proposed by Shi and Srimani, is a new level interconnection network topology, and uses the star graphs as building blocks. In this paper, by exploring the combinatorial properties and fault-tolerance of [Formula: see text], we study the [Formula: see text]-component connectivity of hierarchical star networks [Formula: see text]. We obtain the results: [Formula: see text], [Formula: see text] and [Formula: see text] for [Formula: see text].
Constructions of (r,t)-LRC Based on Totally Isotropic Subspaces in Symplectic Space Over Finite Fields
Authors: Wang Gang , Niu Min-Yao , Fu Fang-Wei
Published: May 2020

Linear code with locality [Formula: see text] and availability [Formula: see text] is that the value at each coordinate [Formula: see text] can be recovered from [Formula: see text] disjoint repairable sets each containing at most [Formula: see text] other coordinates. This property is particularly useful for codes in distributed storage systems because it permits local repair of failed nodes and parallel access of hot data. In this paper, two constructions of [Formula: see text]-locally repairable linear codes based on totally isotropic subspaces in symplectic space [Formula: see text] over finite fields [Formula: see text] are presented. Meanwhile, comparisons are made among the [Formula: see text]-locally repairable codes we construct, the direct product code in Refs. [8], [11] and the codes in Ref. [9] about the information rate [Formula: see text] and relative distance [Formula: see text].
Monomial Generalized Almost Perfect Nonlinear Functions
Authors: Kuroda Masamichi
Published: May 2020

Generalized almost perfect nonlinear (GAPN) functions were defined to satisfy some generalizations of basic properties of almost perfect nonlinear (APN) functions for even characteristic. In particular, on finite fields of even characteristic, GAPN functions coincide with APN functions. In this paper, we study monomial GAPN functions for odd characteristic. We give monomial GAPN functions whose algebraic degree are maximum or minimum on a finite field of odd characteristic. Moreover, we define a generalization of exceptional APN functions and give typical examples.
MODELING DISPROPORTIONAL EFFECTS OF EDUCATING INFECTED KENYAN YOUTH ON HIV/AIDS
Authors: RONOH MARILYN , CHIROVE FARAIMUNASHE , WAIRIMU JOSEPHINE , OGANA WANDERA
Published: May 2020

We formulate an age and sex-structured deterministic model to assess the effect of increasing comprehensive knowledge of HIV/AIDS disease in the infected Adolescent Girls and Young Women (AGYW) and, Adolescent Boys and Young Men (ABYM) populations in Kenya. Mathematical analysis of infection through sub-network analysis was carried out to trace various infection routes and the veracity of various transmission routes as well as the associated probabilities. Using HIV data in Kenya on our model, disproportional effects were observed when dispensation of comprehensive knowledge of HIV/AIDS was preferred in one population over the other. Effective dispensation of comprehensive knowledge of HIV/AIDS in both the infected AGYW and ABYM populations significantly slows down the infection spread but may not eradicate it.
A COUPLING ANALYSIS FOR HEAT TRANSFER AND WATER FLOW IN A FRACTAL ROUGH FRACTURE OF GEOTHERMAL RESERVOIRS
Authors: YE ZHIWEI , WANG J. G.
Published: May 2020

The coupling of heat transfer and water flow in rock fractures is a key issue to geothermal energy extraction. However, this coupling in a rough fracture has not been well studied so far. This paper will study this coupling in a rock fracture with different roughness. First, multi-scale and self-affine rough fracture are constructed through the Weierstrass–Mandelbrot function and embedded into a rock block. Its single scale trend line is also derived. Second, a roughness factor is proposed based on the standard deviation of each segment from the trend line and introduced into the governing equation of fracture flow. After coupling with heat transfer and matrix deformation, a thermal-hydro-mechanical (THM) coupling model is formulated for a rough fracture flow. Third, an analytical solution is derived through the Laplace transform and Stehfest method and used for the validation of this THM coupling model. Finally, the effects of fracture roughness and matrix deformation on heat transfer and fracture flow are numerically investigated. The simulation results indicate that the rock fracture with lower fractal dimension has higher heat transfer efficiency. The effect of fracture roughness on heat transfer is much greater than that of aperture variation induced by the shrinkage of rock matrix.
PETSc DMNetwork
Authors: Abhyankar Shrirang , Betrie Getnet , Maldonado Daniel Adrian , Mcinnes Lois C. , Smith Barry , Zhang Hong
Published: May 2020

We present DMNetwork, a high-level package included in the PETSc library for the simulation of multiphysics phenomena over large-scale networked systems. The library aims at applications that have networked structures such as those in electrical, gas, and water distribution systems. DMNetwork provides data and topology management, parallelization for multiphysics systems over a network, and hierarchical and composable solvers to exploit the problem structure. DMNetwork eases the simulation development cycle by providing the necessary infrastructure through simple abstractions to define and query the network components. This article presents the design of DMNetwork, illustrates its user interface, and demonstrates its ability to solve multiphysics systems, such as an electric circuit, a network of power grid and water subnetworks, and transient hydraulic systems over large networks with more than 2 billion variables on extreme-scale computers using up to 30,000 processors.
CovLets
Authors: Zhang Zhaoxin , Guo Changyong , Meng Fanzhi , Xu Taizhong , Huang Junkai
Published: May 2020

State-of-the-art techniques for image and video classification take a bottom-up approach where local features are aggregated into a global final representation. Existing frameworks (i.e., bag of words or Fisher vectors) are specifically designed to aggregate vector-valued features such as SIFT descriptors. In this article, we propose a technique to aggregate local descriptors in the form of covariance descriptors (CovDs) into a rich descriptor, which in essence benefit from the second-order statistics along the coding pipeline. The difficulty in aggregating CovDs arises from the fact that CovDs lie on the Riemannian manifold of symmetric positive definite (SPD) matrices. Therefore, the aggregating scheme must take advantage of metrics and the geometry of the SPD manifolds. In our proposal, we make use of the Stein divergence and Nyström method to embed the SPD manifold into a Hilbert space. We compare our proposal, dubbed CovLets, against state-of-the-art methods on several image and video classification problems including facial expression recognition and action recognition.
Emo2Vec
Authors: Wang Shuo , Maoliniyazi Aishan , Wu Xinle , Meng Xiaofeng
Published: May 2020

Sentiment analysis or opinion mining for subject information extraction from the text has become more and more dependent on natural language processing, especially for business and healthcare, since the online products and service reviews affect the consuming behaviors. Word embeddings that can map the words to low-dimensional vector representations have been widely used in natural language processing tasks. But the word embeddings based on context such as Word2Vec and GloVe fail to capture the sentiment information. Most of existing sentiment analysis methods incorporate emotional polarity (positive and negative) to improve the sentiment embeddings for the emotion classification. This article takes advantage of an emotional psychology model to learn the emotional embeddings in Chinese first. In order to combine the semantic space and an emotional space, we present two different purifying models from local (LPM) and global (GPM) perspectives based on Plutchik's wheel of emotions to add the emotional information into word vectors. The two models aim to improve the word vectors so that not only the semantically similar words but also the sentimentally similar words can be closer than before. The Plutchik's wheel of emotions model can give eight-dimensional vector for one word in emotional space that can capture more sentiment information than the binary polarity labels. The obvious advantage of the local purifying model is that it can be fit for any pretrained word embeddings. For the global purifying model, we can get the final emotional embeddings at once. These models have been extended to handle English texts. The experimental results on Chinese and English datasets show that our purifying model can improve the conventional word embeddings and some proposed sentiment embeddings for sentiment classification and multi-emotion classification.
Exploring Disorder-Aware Attention for Clinical Event Extraction
Authors: Yadav Shweta , Ramteke Pralay , Ekbal Asif , Saha Sriparna , Bhattacharyya Pushpak
Published: May 2020

Event extraction is one of the crucial tasks in biomedical text mining that aims to extract specific information concerning incidents embedded in the texts. In this article, we propose a deep learning framework that aims to identify the attributes (severity, course, temporal expression, and document creation time) associated with the medical concepts extracted from electronic medical records. The bi-directional long short-term memory network assisted by the attention mechanism is utilized to uncover the important aspects of the patient’s medical conditions. The attention mechanism specific to the medical disorder mention can focus on various parts of the sentence when different disorders are considered as input. The proposed methodology is evaluated on benchmark ShARe/CLEF eHealth Evaluation Lab 2014 shared task 2 datasets. In addition to the CLEF dataset, we also used the social media text, especially the medical blog posts. Experimental results of the proposed approach illustrate that our proposed approach achieves significant performance improvements over the state-of-the-art techniques and the highly competitive deep learning--based baseline methods.
Deep Neighborhood Component Analysis for Visual Similarity Modeling
Authors: Liu Xueliang , Yang Xun , Wang Meng , Hong Richang
Published: May 2020

Learning effective visual similarity is an essential problem in multimedia research. Despite the promising progress made in recent years, most existing approaches learn visual features and similarities in two separate stages, which inevitably limits their performance. Once useful information has been lost in the feature extraction stage, it can hardly be recovered later. This article proposes a novel end-to-end approach for visual similarity modeling, calleddeep neighborhood component analysis, which discriminatively trains deep neural networks to jointly learn visual features and similarities. Specifically, we first formulate a metric learning objective that maximizes the intra-class correlations and minimizes the inter-class correlations under the neighborhood component analysis criterion, and then train deep convolutional neural networks to learn a nonlinear mapping that projects visual instances from original feature space to a discriminative and neighborhood-structure-preserving embedding space, thus resulting in better performance. We conducted extensive evaluations on several widely used and challenging datasets, and the impressive results demonstrate the effectiveness of our proposed approach.
Learning Three-dimensional Skeleton Data from Sign Language Video
Authors: Brock Heike , Law Felix , Nakadai Kazuhiro , Nagashima Yuji
Published: May 2020

Data for sign language research is often difficult and costly to acquire. We therefore present a novel pipeline able to generate motion three-dimensional (3D) skeleton data from single-camera sign language videos only. First, three recurrent neural networks are learned to infer the three-dimensional position data of body, face, and finger joints for a high resolution of the signer’s skeleton. Subsequently, the angular displacements of all joints over time are estimated using inverse kinematics and mapped to a virtual sign avatar for animation. Last, the generated data are evaluated in detail, including a sign language recognition and sign language synthesis scenario. Utilizing a neural word classifier trained on real motion capture data, we reliably classify word segments built from our newly generated position data with similar accuracy as motion capture data (absolute difference 3.8%). Furthermore, qualitative evaluation of sign animations shows that the avatar performs natural movements that are comprehensible and resemble animations created with original motion capture data.
Knowledge Transfer in Vision Recognition
Authors: Lu Ying , Luo Lingkun , Huang Di , Wang Yunhong , Chen Liming
Published: May 2020

In this survey, we propose to explore and discuss the common rules behind knowledge transfer works for vision recognition tasks. To achieve this, we firstly discuss the different kinds of reusable knowledge existing in a vision recognition task, and then we categorize different knowledge transfer approaches depending on where the knowledge comes from and where the knowledge goes. Compared to previous surveys on knowledge transfer that are from the problem-oriented perspective or from the technique-oriented perspective, our viewpoint is closer to the nature of knowledge transfer and reveals common rules behind different transfer learning settings and applications. Besides different knowledge transfer categories, we also show some research works that study the transferability between different vision recognition tasks. We further give a discussion about the introduced research works and show some potential research directions in this field.
Typal Heterogeneous Equality Types
Authors: Pitts Andrew M.
Published: May 2020

The usual homogeneous form of equality type in Martin-Löf Type Theory contains identifications between elements of the same type. By contrast, the heterogeneous form of equality contains identifications between elements of possibly different types. This short note introduces a simple set of axioms for such types. The axioms are shown to be equivalent to the combination of systematic elimination rules for both forms of equality, albeit with typal (also known as “propositional”) computation properties, together with Streicher’s Axiom K, or equivalently, the principle of uniqueness of identity proofs.
Exploring and Understanding Participants’ Perceptions of Facial Emoji Likert Scales in Online Surveys
Authors: Alismail Sarah , Zhang Hengwei
Published: May 2020

The present study aims to explore participants’ experiences in interacting with a facial emoji Likert scale in online surveys to understand their perceptions, interpretations, and opinions of emojis in online surveys. A qualitative research approach has been adopted. This article contributes to the existing body of knowledge on emojis and online survey questionnaires by presenting a detailed exploratory qualitative study of 42 participants’ insights, perceptions, and interpretations of the facial emoji Likert scale in a specific context (i.e., a course evaluation survey). The data analysis reveals seven categories that emerged from the transcribed interviews and the interviewers’ written notes from the cognitive interviews regarding participants’ perceptions of interacting with the facial emoji–based Likert scale.
Model Checking MITL Formulae on Timed Automata
Authors: Menghi Claudio , Bersani Marcello M. , Rossi Matteo , Pietro Pierluigi San
Published: May 2020

Timed Automata (TA) is de facto a standard modelling formalism to represent systems when the interest is the analysis of their behaviour as time progresses. This modelling formalism is mostly used for checking whether the behaviours of a system satisfy a set of properties of interest. Even if efficient model-checkers for Timed Automata exist, these tools are not easily configurable. First, they are not designed to easily allow adding new Timed Automata constructs, such as new synchronization mechanisms or communication procedures, but they assume a fixed set of Timed Automata constructs. Second, they usually do not support the Metric Interval Temporal Logic (MITL) and rely on a precise semantics for the logic in which the property of interest is specified, which cannot be easily modified and customized. Finally, they do not easily allow using different solvers that may speed up verification in different contexts.

This article presents a novel technique to perform model checking of Metric Interval Temporal Logic (MITL) properties on TA. The technique relies on the translation of both the TA and the MITL formula into an intermediate Constraint LTL over clocks (CLTLoc) formula, which is verified through an available decision procedure. The technique is flexible, since the intermediate logic allows the encoding of new semantics as well as new TA constructs, by just adding new CLTLoc formulae. Furthermore, our technique is not bound to a specific solver as the intermediate CLTLoc formula can be verified using different procedures.
Some Parameterized Dynamic Priority Policies for Two-Class M/G/1 Queues
Authors: Gupta Manu K. , Hemachandra N. , Venkateswaran J.
Published: May 2020

Completeness of a dynamic priority scheduling scheme is of fundamental importance for the optimal control of queues in areas as diverse as computer communications, communication networks, supply/value chains, and manufacturing systems. Ourfirst main contributionis to identify the mean waiting time completeness as a unifying aspect for four different dynamic priority scheduling schemes by proving their completeness and equivalence in two-class M/G/1 queues. These dynamic priority schemes are earliest due date based, head of line priority jump, relative priority, and probabilistic priority. We discuss major challenges in extending our results to three or more classes.

In oursecond main contribution, we characterize the optimal scheduling policies for the case studies in different domains by exploiting the completeness of the above dynamic priority schemes. The major theme of the second main contribution is resource allocation/optimal control in revenue management problems for contemporary systems such as cloud computing, high performance computing, ans so forth, where congestion is inherent. Using completeness and the theoretically tractable nature of relative priority policy, we study the impact of approximation in a fairly generic data network utility framework. Next, we simplify a complex joint pricing and scheduling problem for a wider class of scheduling policies.
What Do We Mean When We Talk about Artificial Intelligence?
Authors: Schaefer Robert
Published: May 2020

"...the step from not being able to do something at all to being able to do it a little bit is very much smaller than the next step - being able to do it well. In AI, this fallacious thinking seems to be all pervasive" -- Bar- Hillel.
Will RISC-V revolutionize computing?
Authors: Greengard Samuel
Published: May 2020

The open instruction set for microprocessors promises to reshape computing and introduce new, more powerful capabilities.
Measuring and mitigating OAuth access token abuse by collusion networks
Authors: Farooqi Shehroze , Zaffar Fareed , Leontiadis Nektarios , Shafiq Zubair
Published: May 2020

We uncovered a thriving ecosystem of large-scale reputation manipulation services on Facebook that leverage the principle of collusion.
Collusion networks
collect OAuth access tokens from colluding members and abuse them to provide fake likes or comments to their members. We carried out a comprehensive measurement study to understand how these collusion networks exploited popular third-party Facebook applications with weak security settings to retrieve OAuth access tokens. We infiltrated popular collusion networks using honeypots and identified more than one million colluding Facebook accounts by "milking" these collusion networks. We disclosed our findings to Facebook and collaborated with them to implement a series of countermeasures that mitigated OAuth access token abuse without sacrificing application platform usability for third-party developers.
Interview with Anastasia Salter
Authors: Atzenbeck Claus
Published: May 2020

Dr. Anastasia Salter is the Director of Graduate Programs for the College of Arts and Humanities, including the innovative interdisciplinary doctoral program in Texts & Technology. They have authored five books that draw on humanities methods alongside computational discourse and subjects, including most recently
Adventure Games: Playing the Outsider
(Bloomsbury 2020, with Aaron Reed and John Murray),
Toxic Geek Masculinity in Media
(Palgrave Macmillan 2017, with Bridget Blodgett) and
Jane Jensen: Gabriel Knight, Adventure Games, Hidden Objects
(Bloomsbury 2017). Dr. Salter is a former author for
ProfHacker
, a blog on technology and pedagogy formerly hosted by the Chronicle of Higher Education; Chair of the Electronic Literature Organization Conference 2020; and Co-Chair of ACM Hypertext and Social Media 20 in Orlando, Florida.
Using word embeddings for library and information science research
Authors: Katsurai Marie
Published: May 2020

In the research field of library and information science (LIS), pattern recognition and machine learning approaches have often been adopted to analyze massive amounts of textual data in digital libraries. In recent natural language processing, word embeddings have attracted much attention because they can capture semantic meanings and contexts. This paper presents a short survey of how word embeddings have been used in LIS research, especially focusing on articles published in LIS journals between 2009 and 2019. Our simple bibliographic analysis showed that at least 15 LIS journal papers used word embeddings. These 15 papers were briefly described under the following categories: knowledge extraction and visualization from scholarly data, classification in scholarly data, and others that focus on more general corpora.
RCLAda, or Bringing Ada to the Robot Operating System
Authors: Mosteo Alejandro R.
Published: May 2020

The Robot Operating System (ROS) is a commonly used framework in many fields of robotics research, with increasing presence in the industry. The next iteration of this framework, ROS2, aims to improve observed shortcomings of its predecessor like deterministic memory allocation and real-time characteristics. The officially supported languages in ROS2 are C++ and Python, although several other contributed APIs for other languages exist. RCLAda is an API and accompanying tools for the ROS2 framework that enable the programming of ROS2 nodes in pure Ada with seamless integration into the ROS2 workflow.
What about online doctoral students? A review of e-Learning literature
Authors: McGaha Kristina , Hart Diana , Aoki Wendy
Published: May 2020

Recent increases in accessibility, enrollment in e-learning, and diversification of distance learning format delivery (such as MOOCs) have put e-learning in a state of perpetual evolution. The result is a dynamic environment where research as recent as five years ago may no longer be relevant. A review of contemporary e-learning research is needed to understand current trends in the industry of e-learning as well as determine where further research is needed. This article describes six themes identified in the literature by reviewing journal articles centric to e-learning from 2014 to 2019 using qualitative content analysis. The themes represent what is largely covered in the literature (e-learning anxiety, e-learning pedagogy, and student-centered models), and what is underserved in the literature?namely the dissemination and investigation of online doctoral programs. This article will briefly discuss these themes using highlighted works. The researchers will also explain the need to continue researching specialized e-learning subgroups, specifically online doctoral students.
Mining Social Media Data for Biomedical Signals and Health-Related Behavior
Authors: Correia Rion Brattig , Wood Ian B. , Bollen Johan , Rocha Luis M.
Published: May 2020

Social media data have been increasingly used to study biomedical and health-related phenomena. From cohort-level discussions of a condition to population-level analyses of sentiment, social media have provided scientists with unprecedented amounts of data to study human behavior associated with a variety of health conditions and medical treatments. Here we review recent work in mining social media for biomedical, epidemiological, and social phenomena information relevant to the multilevel complexity of human health. We pay particular attention to topics where social media data analysis has shown the most progress, including pharmacovigilance and sentiment analysis, especially for mental health. We also discuss a variety of innovative uses of social media data for health-related applications as well as important limitations of social media data access and use.
Fingerprinting Redox Heterogeneity in Electrodes during Extreme Fast Charging
Authors: Mistry Aashutosh , Usseglio-Viretta Francois L. E. , Colclasure Andrew , Smith Kandler , Mukherjee Partha P.
Published: May 2020

Conventionally, battery electrodes are rationalized as homogeneous reactors. It proves to be an erroneous interpretation for fast transients, where mass transport limitations amplify underlying heterogeneities. Given the lack of observability of associated fast spatiotemporal dynamics, redox activity in inhomogeneous electrodes is superficially explored. We resort to a physics-based description to examine the extreme fast charging of lithium-ion battery electrodes. Representative inhomogeneity information is extracted from electrode tomograms. We discover such electrodes to undergo preferential intercalation, localized lithium plating and nonuniform heat generation as a result of distributed long- and short-range interactions. The spatial correlations of these events with the underlying inhomogeneity are found to be nonidentical. Investigation of multiple inhomogeneity fields reveals an exponential scaling of plating severity and early onset in contrast to the homogeneous limit. Anode and cathode inhomogeneities couple nonlinearly to grow peculiar electrodeposition patterns. These mechanistic insights annotate the complex functioning of spatially nonuniform electrodes.
Cleaning Solutions for Removal of ∼30 nm Ceria Particles from Proline and Citric Acid Containing Slurries Deposited on Silicon Dioxide and Silicon Nitride Surfaces
Authors: Gowda Akshay , Seo Jihoon , Ranaweera Charith K. , Babu S. V.
Published: May 2020

A previously developed aqueous cleaning solution (4.2 mol l−1 each of H2O2 and NH4OH) was found to be ineffective in cleaning oxide/nitride surfaces after contamination with ceria particles from slurries containing proline or citric acid. However, a cleaning solution consisting of 1 wt% ascorbic acid, 1 wt% ammonium carbonate and 50 ppm triton X-100 at pH 12, aided by ultrasonic cleaning, removed these ceria particles, even those as small as ∼30 nm, from both oxide and nitride surfaces with efficiencies >99% as determined by AFM imaging. Fourier transform infrared (FTIR) spectroscopy results indicated that ceria particles treated with these additives can also bind with oxide/nitride surfaces through Si–O–C and Si–O–H bonds, in addition to any Ce–O–Si, where the C and H atoms are from the additives adsorbed on the ceria particles. All these bonds are broken effectively by the nucleophilic attack of hydroxyl anions in the cleaning solution while triton X-100 in the cleaning solution reduces adhesion between the particles and the film surface and facilitates cleaning via a wetting mechanism. More importantly, ascorbic acid and ammonium carbonate prevent particle redeposition by complexing with the removed particles and blocking the active Ce3+ species on their surface.
Experimental analysis of T cell epitopes for designing liver cancer vaccine predicted by system-level immunoinformatics approach
Authors: Muhammad Syed Aun , Zafar Sidra , Rizvi Samana Zahra , Imran Imran , Munir Fahad , Jamshed Muhammad Babar , Ali Amjad , Wu Xiaogang , Shahid Numan , Zaeem Muhammad , Zhang Qiyu
Published: May 2020

We observed substantial high levels of granzymes B in serum samples of component C6 (C6) and albumin (ALB) compared with control, indicating the activity of cytotoxic T cells. We concluded that C6 and ALB are likely to contain potential epitopes for the induction of protective effector molecules, supporting the feasibility of therapeutic peptide-based vaccine for liver cancer.
Impact of Jiggling Exercise as Conservative Treatment for Hip Osteoarthritis: A Report of Two Cases
Authors: Teramoto Yohei , Fukushima Kensuke , Koyama Tomohisa , Ohashi Yoshihisa , Uchiyama Katsufumi , Takahira Naonobu , Takaso Masashi
Published: May 2020

Total hip arthroplasty has been recognized as a feasible treatment for hip osteoarthritis, especially in advanced and terminal stages, but whether it is the best treatment for patients who are younger, have comorbidities, and/or are likely to have low compliance to medical treatment is unknown. Jiggling exercise, which involves the continuous shaking of the foot and leg in small steps, has been reported to be the easiest and a less invasive exercise for patients with hip osteoarthritis. We herein report two patients who performed jiggling exercise as conservative treatment and had successful outcomes. The first case was a 28-year-old woman with advanced-stage hip osteoarthritis that could not be treated with hip preservation surgery; furthermore, the patient refused to undergo total hip arthroplasty because of her young age. The second case was a 74-year-old woman with terminal-stage hip osteoarthritis in whom total hip arthroplasty was deemed not feasible because of possible low compliance due to mental disorder. One year after the initiation of the jiggling exercise, both patients had remarkable clinical improvement. Three years later, remarkable joint remodelling was also revealed in plain radiographs. Jiggling exercise might be a feasible conservative treatment option for joint preservation.
Brain Death Secondary to Rocky Mountain Spotted Fever Encephalitis
Authors: Rhodes Steven D. , Teagarden Alicia M. , Graner Brian , Lutfi Riad , John Chandy C.
Published: May 2020

A two-year-old female presented with acutely altered mental status following eight days of fever and rash. She had been camping at an Indiana campground 11 days prior to the onset of illness and was evaluated twice for her fever and rash prior to admission. Laboratory evaluation on admission revealed thrombocytopenia, hyponatremia, and elevated transaminases. The patient developed diffuse cerebral edema, and despite intensive care, the edema led to brain death from Rocky Mountain spotted fever (RMSF). We present this case to highlight the importance of considering RMSF and other tick-borne illnesses in a child with prolonged fever and rash in a nonendemic area and also the difficulty of diagnosis in early stages of disease. A detailed travel history, evaluation of key laboratory findings (white blood count, platelet count, and transaminases), and close follow-up if rash and fevers persist may help to improve detection of RMSF. If a tick-borne illness such as RMSF is suspected, empiric doxycycline therapy should be started immediately, as lab confirmation may take several days and mortality increases greatly after five days of symptoms.
Treatment of Infected Pseudoarthrosis in a Subtrochanteric Fracture in a Patient with Osteopetrosis
Authors: Lionel Llano , Barla Jorge D. , Diego Campelo , Danilo Taype , Sancineto Carlos F. , Carabelli Guido
Published: May 2020

Osteopetrosis is a disease of osteoclasts that results in failure of bone remodeling. Despite the sclerotic radiographic appearance of the thickened cortices and its material hardness, osteopetrotic bone is weak and prone to fracture by minor trauma. We report a case of a subtrochanteric fracture in an osteopetrotic patient, with further pseudoarthrosis and infection. Several surgical procedures were required, with further complications. The outcome of each procedure and the final result are also described.
Three-Point Boundary Value Problems for the Langevin Equation with the Hilfer Fractional Derivative
Authors: Wongcharoen Athasit , Ahmad Bashir , Ntouyas Sotiris K. , Tariboon Jessada
Published: May 2020

We discuss the existence and uniqueness of solutions for the Langevin fractional differential equation and its inclusion counterpart involving the Hilfer fractional derivatives, supplemented with three-point boundary conditions by means of standard tools of the fixed-point theorems for single and multivalued functions. We make use of Banach’s fixed-point theorem to obtain the uniqueness result, while the nonlinear alternative of the Leray-Schauder type and Krasnoselskii’s fixed-point theorem are applied to obtain the existence results for the single-valued problem. Existence results for the convex and nonconvex valued cases of the inclusion problem are derived via the nonlinear alternative for Kakutani’s maps and Covitz and Nadler’s fixed-point theorem respectively. Examples illustrating the obtained results are also constructed. (2010) Mathematics Subject Classifications. This study is classified under the following classification codes: 26A33; 34A08; 34A60; and 34B15.
Collectively Answering the Venetoclax BTK Inhibitor Sequencing Question in CLL
Authors: Rogers Kerry A.
Published: May 2020

Whether BTK inhibitors are effective when used after venetoclax in patients with chronic lymphocytic leukemia is an important unanswered question. In a large retrospective cohort study examining outcomes for next line treatment after venetoclax, BTK inhibitors were found to result in durable responses in patients who were not previously BTK inhibitor resistant.

See related article by Mato et al., p. 3589
Effect of Intensive Blood Pressure Lowering on the Risk of Atrial Fibrillation
Authors: Soliman Elsayed Z. , Rahman AKM F. , Zhang Zhu-ming , Rodriguez Carlos J. , Chang Tara I. , Bates Jeffrey T. , Ghazi Lama , Blackshear Joseph L. , Chonchol Michel , Fine Lawrence J. , Ambrosius Walter T. , Lewis Cora E.
Published: May 2020

It remains uncertain whether intensive control of blood pressure (BP) results in a lower risk of atrial fibrillation (AF) in patients with hypertension. Using data from SPRINT (Systolic Blood Pressure Intervention Trial), which enrolled participants with hypertension at increased risk of cardiovascular disease, we examined whether intensive BP lowering (target systolic BP [SBP] <120 mm Hg), compared with standard BP lowering (target SBP<140 mm Hg), results in a lower risk of AF. This analysis included 8022 participants (4003 randomized to the intensive arm and 4019 to standard BP arm) who were free of AF at the time of enrollment and with available baseline and follow-up electrocardiographic data. AF was ascertained from standard 12-lead electrocardiograms recorded at biannual study examinations and an exit visit. During up to 5.2 years of follow-up and a total of 28 322 person-years, 206 incident AF cases occurred; 88 in the intensive BP-lowering arm and 118 in the standard BP-lowering arm. Intensive BP lowering was associated with a 26% lower risk of developing new AF (hazard ratio, 0.74 [95% CI, 0.56–0.98];
P
=0.037). This effect was consistent among prespecified subgroups of SPRINT participants stratified by age, sex, race, SBP tertiles, prior cardiovascular disease, and prior chronic kidney disease when interactions between treatment effect and these subgroups were assessed using Hommel adjusted
P
values. In conclusion, intensive treatment to a target of SBP <120 mm Hg in patients with hypertension at high risk of cardiovascular disease has the potential to reduce the risk of AF.

Registration—

URL:
https://www.clinicaltrials.gov
; Unique identifier: NCT01206062.
Kalanchoe ×estrelae (Crassulaceae subfam. Kalanchooideae): a new nothospecies for the hybrid between K. luciae and K. sexangularis

Authors: SMITH GIDEON F.
Published: May 2020

The cultivar name Kalanchoe Adanson (1763: 248) ‘Vivien’ Bischofberger (2015: 42) was established for a selection of the hybrid between K. luciae Raymond-Hamet (Hamet 1908: 256) (Fig. 1A) (see Smith 2020a for an explanation of the variable orthography of the name of Raymond-Hamet) and K. sexangularis Brown (1913: 120) (Fig. 1B) (Crassulaceae subfam. Kalanchooideae). The hybrid between these two species is variable and other forms of it, apart from K. ‘Vivien’, are also encountered in cultivation (Smith 2020b). Kalanchoe luciae and K. sexangularis are undoubtedly two of the most popular kalanchoes in domestic and amenity horticulture in South Africa, where they are indigenous (Smith et al. 2019b: 120). Geographically, both species extend northward into Zimbabwe and Mozambique in south-tropical Africa (Smith et al. 2019b: 189, 227).
Revision of Otoba (Myristicaceae)

Authors: JARAMILLO-VIVANCO TATIANA S. , BALSLEV HENRIK
Published: May 2020

Otoba is one of six American genera of Myristicaceae and recognized by having three stamens with almost fused to free filaments, globose arillate seeds and absence of bracteoles in the male flower. Species of Otoba are distinguished by a suite of characters, mainly pubescence of the ovary and anther shape. It is one of the most abundant genera of Myristicaceae, although the number of species is small: Otoba acuminata, O. cyclobasis, O. glycycarpa, O. gordoniifolia, O. gracilipes, O. latialata, O. lehmannii, O. novogranatensis, O. parvifolia and O. vespertilio. They occur from middle Central America through western Ecuador into the eastern parts of upper Amazonia.
Morphological and molecular evidence for a new species from China: Dendrobium yongjiaense (Orchidaceae: Malaxideae)

Authors: ZHOU ZHUANG , ZHANG SAI , YANG YAN-PING , MA LIANG , LAN SI-REN
Published: May 2020

A new orchid species, Dendrobium yongjiaense, from Zhejiang, China, is described and illustrated here. Detailed morphological study indicates that D. yongjiaense is similar to D. monticola and D. strongylanthum, but it differs in the shape and size of leaf, flower size, and a mid-lobe of the lip with densly distinct crystalline papillae and wrinkled 3–5 crest lines in middle. Molecular phylogeny analyses based on the nrITS and plastid DNA (matK and trnL-F) reveal that D. yongjiaense is a member of sect. Stachyobium, and genetically similar to D. monticola.
Asterina gordoniae sp. nov. (Asterinaceae), a new foliar mycobiont from Kerala, India

Authors: SABEENA ALIYARUKUNJU , BIJU HARIDAS , DHANUSHA SUDHAKARAN SUJATHA , SHIBURAJ SUGATHAN
Published: May 2020

A new black mildew fungus, Asterina gordoniae infecting leaves of Gordonia obtusa (Theaceae) collected from Thiruvananthapuram, Kerala is described and illustrated based on morphology. It differs from the four other Asterina species described on Theaceae by having smaller ascospores and sub-lobate to lobate appressoria.
Beyond Progression: Devising a New Training Model for Candidate Assessment, Advancement, and Advising at Columbia
Authors: Richardson Justin , Cabaniss Deborah L. , Halperin Jane , Vaughan Susan C. , Cherry Sabrina
Published: May 2020

Research over several decades has identified significant problems with the progression model—the traditional approach to assessment and advancement of psychoanalytic candidates—including candidates’ anxiety and uncertainty about the methods and fairness of their assessment, avoidance of conflictual issues with patients in order to keep cases, and reluctance to share their challenges with supervisors and advisors. In light of these findings, the Columbia Center for Psychoanalytic Training and Research restructured its psychoanalytic training programs. The progression committee, the progression advisor role, candidate application to advance through the program, and routine committee discussion of candidates were eliminated and replaced by confidential mentorship and a clear and predictable system of trainee advancement. Analytic competency—a requirement for graduation—is now determined solely from detailed written feedback regarding the candidate’s achievement of the Center’s learning objectives. The number of months of supervised analysis required for graduation has been reduced, as has the required length of the candidate’s longest case; in addition, three-times-weekly analyses are now accepted for credit. These changes are meant to increase the transparency, objectivity, and predictability of the training experience and reduce the pressure on clinical decision making and communication between trainees and faculty. An extensive evaluation of the impact of these innovations is currently under way.
Improving Working Conditions in Global Supply Chains: The Role of Institutional Environments and Monitoring Program Design
Authors: Short Jodi L. , Toffel Michael W. , Hugill Andrea R.
Published: May 2020

Activism seeking to improve labor conditions in global supply chains has led many transnational corporations to adopt codes of conduct and to monitor suppliers for compliance. Drawing on thousands of audits conducted by a major social auditor, the authors identify structural contingencies in the institutional environment and program design under which codes and monitoring are more likely to be associated with improvements in conditions. At the institutional level, suppliers improve more when they face greater risk that nongovernmental organizations and the press will expose harmful working conditions. They also improve more when their buyers have experienced negative publicity for supply chain labor abuses. At the program design level, suppliers improve more on average when audits are pre-announced, when auditors are highly trained, and especially when both elements are present. Extended analysis of variations across violation types reveals nuances to these findings. For instance, pre-announced audits were followed by greater improvement in occupational safety and health practices but not child labor practices. These findings can inform strategies for improving supply chain working conditions.
How can today’s substance-using youth be helped to quit? Perspectives of college students from Bangalore, India
Authors: Doraiswamy Padmavathy , Nattala Prasanthi , Murthy Pratima
Published: May 2020

Background:

Substance use among college students is increasing, yet research regarding their viewpoints on how they can be helped is sparse in India.

Aim:

The purpose of this study was to explore in depth the perspectives of college students as to how college youth can be helped to quit the use of psychoactive substances.

Method:

Data from focus group interviews with 38 adolescent college students were analyzed qualitatively to identify their viewpoints on how today’s college youth can be helped to quit substance use. Interviews were transcribed verbatim, themes and subthemes were identified.

Results:

Three major themes (with subthemes) were identified: (1) Patterns of use (commonly used substances, methods of using), (2) Perceived reasons for use (to reduce negative emotions, academic pressure, peer influence, more freedom, rebellious attitudes, media influence, modeling effect, childhood trauma, distrust from family/friends, lack of knowledge regarding the adverse impact of substances, poor life skills, cultural gender-based discrimination) and (3) Interventions needed to help college youth to quit substance use (need for interventions, basic principles to follow when developing interventions, content to be included, methods to be employed for delivering the intervention).

Conclusion:

The information from this study can guide the development of a comprehensive intervention that is relevant and tailor-made to the specific needs of the college student population.
Integration of Primary and Resale Platforms
Authors: Zou Tianxin , Jiang Baojun
Published: May 2020

Consumers can buy concert tickets from primary platforms (e.g., Ticketmaster) or from consumer-to-consumer resale platforms (e.g., StubHub). Recently, Ticketmaster has entered and been trying to control the resale market by prohibiting consumers from reselling on competing resale platforms. Several states in the United States have passed or are discussing laws requiring tickets to be transferrable on any resale sites, worrying that platform integration—Ticketmaster controlling both the primary and the resale platforms—will increase ticket service fees and harm musicians and consumers. This article establishes a game-theoretic framework and shows that the opposite can happen: platform integration can lower the service fees in both markets, alleviating double marginalization in the primary market and benefiting the musician and consumers. Moreover, with platform integration, the presence of a small number of scalpers can counterintuitively reduce the ticket price and benefit the musicians and consumers. In addition, platform competition in the resale market may harm consumers. This article further shows that these insights apply in other markets (e.g. used goods, peer-to-peer product-sharing markets) and provides suggestive empirical support for the theoretical results.