bluuebunny/crossref_metadata_2025 huggingface dataset:
PONE
Authors: Lan Tian , Mao Xian-Ling , Wei Wei , Gao Xiaoyan , Huang Heyan
Published: November 2020

Open-domain generative dialogue systems have attracted considerable attention over the past few years. Currently, how to automatically evaluate them is still a big challenge. As far as we know, there are three kinds of automatic evaluations for open-domain generative dialogue systems: (1) Word-overlap-based metrics; (2) Embedding-based metrics; (3) Learning-based metrics. Due to the lack of systematic comparison, it is not clear which kind of metrics is more effective. In this article, we first measure systematically all kinds of metrics to check which kind is best. Extensive experiments demonstrate that learning-based metrics are the most effective evaluation metrics for open-domain generative dialogue systems. Moreover, we observe that nearly all learning-based metrics depend on the negative sampling mechanism, which obtains extremely imbalanced and low-quality samples to train a score model. To address this issue, we propose a novel learning-based metric that significantly improves the correlation with human judgments by using augmented
PO
sitive samples and valuable
NE
gative samples, called PONE. Extensive experiments demonstrate that PONE significantly outperforms the state-of-the-art learning-based evaluation method. Besides, we have publicly released the codes of our proposed metric and state-of-the-art baselines.
1
Making Apps
Authors: Clarke-Midura Jody , Sun Chongning , Pantic Katarina
Published: November 2020

In response to the need to broaden participation in computer science, we designed a summer camp to teach middle-school-aged youth to code apps with MIT App Inventor. For the past four summers, we have observed significant gains in youth's interest and self-efficacy in computer science, after attending our camps. The majority of these youth, however, were youth from our local community. To provide equal access across the state and secure more diversity, we were interested in examining the effect of the camp on a broader population of youth. Thus, we partnered with an outreach program to reach and test our camps on youth from low-income high-poverty areas in the Intermountain West. During the summer of 2019, we conducted two sets of camps: locally advertised app camps that attracted youth from our local community and a second set of camps as part of a larger outreach program for youth from low-income high-poverty areas. The camps for both populations followed the same design of personnel, camp activities, structure, and curriculum. However, the background of the participants was slightly different. Using survey data, we found that the local sample experienced significant gains in both self-efficacy and interest, while the outreach group only reported significant gains in self-efficacy after attending the camp. However, the qualitative data collected from the outreach participants indicated that they had a positive experience both with the camp and their mentors. In this article, we discuss the camp design and findings in relation to strategies for broadening participation in Computer Science education.
Deep Learning for Sequential Recommendation
Authors: Fang Hui , Zhang Danning , Shu Yiheng , Guo Guibing
Published: November 2020

In the field of sequential recommendation, deep learning--(DL) based methods have received a lot of attention in the past few years and surpassed traditional models such as Markov chain-based and factorization-based ones. However, there is little systematic study on DL-based methods, especially regarding how to design an effective DL model for sequential recommendation. In this view, this survey focuses on DL-based sequential recommender systems by taking the aforementioned issues into consideration. Specifically, we illustrate the concept of sequential recommendation, propose a categorization of existing algorithms in terms of three types of behavioral sequences, summarize the key factors affecting the performance of DL-based models, and conduct corresponding evaluations to showcase and demonstrate the effects of these factors. We conclude this survey by systematically outlining future directions and challenges in this field.
A systematic approach to deriving incremental type checkers
Authors: Pacak André , Erdweg Sebastian , Szabó Tamás
Published: November 2020

Static typing can guide programmers if feedback is immediate. Therefore, all major IDEs incrementalize type checking in some way. However, prior approaches to incremental type checking are often specialized and hard to transfer to new type systems. In this paper, we propose a systematic approach for deriving incremental type checkers from textbook-style type system specifications. Our approach is based on compiling inference rules to Datalog, a carefully limited logic programming language for which incremental solvers exist. The key contribution of this paper is to discover an encoding of the infinite typing relation as a finite Datalog relation in a way that yields efficient incremental updates. We implemented the compiler as part of a type system DSL and show that it supports simple types, some local type inference, operator overloading, universal types, and iso-recursive types.
Exposing cache timing side-channel leaks through out-of-order symbolic execution
Authors: Guo Shengjian , Chen Yueqi , Yu Jiyong , Wu Meng , Zuo Zhiqiang , Li Peng , Cheng Yueqiang , Wang Huibo
Published: November 2020

As one of the fundamental optimizations in modern processors, the
out-of-order
execution boosts the pipeline throughput by executing independent instructions in parallel rather than in their program orders. However, due to the side effects introduced by such microarchitectural optimization to the CPU cache, secret-critical applications may suffer from timing side-channel leaks. This paper presents a symbolic execution-based technique, named SymO
3
, for exposing cache timing leaks under the context of
out-of-order
execution. SymO
3
proposes new components that address the modeling, reduction, and reasoning challenges of accommodating program analysis to the software code
out-of-order
analysis. We implemented SymO
3
upon KLEE and conducted three evaluations on it. Experimental results show that SymO
3
successfully uncovers a set of cache timing leaks in five real-world programs. Also, SymO
3
finds that, in general, program transformation from compiler optimizations shrink the surface to timing leaks. Furthermore, augmented with a speculative execution modeling, SymO
3
identifies five more leaky programs based on the compound analysis.
Programming with a read-eval-synth loop
Authors: Peleg Hila , Gabay Roi , Itzhaky Shachar , Yahav Eran
Published: November 2020

A frequent programming pattern for small tasks, especially expressions, is to repeatedly evaluate the program on an input as its editing progresses. The Read-Eval-Print Loop (REPL) interaction model has been a successful model for this programming pattern. We present the new notion of Read-Eval-Synth Loop (RESL) that extends REPL by providing in-place synthesis on parts of the expression marked by the user. RESL eases programming by synthesizing parts of a required solution. The underlying synthesizer relies on a partial solution from the programmer and a few examples.

RESL hinges on bottom-up synthesis with general predicates and sketching, generalizing programming by example. To make RESL practical, we present a formal framework that extends observational equivalence to non-example specifications.

We evaluate RESL by conducting a controlled within-subjects user-study on 19 programmers from 8 companies, where programmers are asked to solve a small but challenging set of competitive programming problems. We find that programmers using RESL solve these problems with far less need to edit the code themselves and by browsing documentation far less. In addition, they are less likely to leave a task unfinished and more likely to be correct.
Adversarial examples for models of code
Authors: Yefet Noam , Alon Uri , Yahav Eran
Published: November 2020

Neural models of code have shown impressive results when performing tasks such as predicting method names and identifying certain kinds of bugs. We show that these models are vulnerable to
adversarial examples
, and introduce a novel approach for
attacking
trained models of code using adversarial examples. The main idea of our approach is to force a given trained model to make an incorrect prediction, as specified by the adversary, by introducing small perturbations that do not change the program’s semantics, thereby creating an adversarial example. To find such perturbations, we present a new technique for Discrete Adversarial Manipulation of Programs (DAMP). DAMP works by deriving the desired prediction with respect to the model’s
inputs
, while holding the model weights constant, and following the gradients to slightly modify the input code.

We show that our DAMP attack is effective across three neural architectures: code2vec, GGNN, and GNN-FiLM, in both Java and C#. Our evaluations demonstrate that DAMP has up to 89% success rate in changing a prediction to the adversary’s choice (a targeted attack) and a success rate of up to 94% in changing a given prediction to any incorrect prediction (a non-targeted attack). To defend a model against such attacks, we empirically examine a variety of possible defenses and discuss their trade-offs. We show that some of these defenses can dramatically drop the success rate of the attacker, with a minor penalty of 2% relative degradation in accuracy when they are not performing under attack.

Our code, data, and trained models are available at https://github.com/tech-srl/adversarial-examples .
Testing differential privacy with dual interpreters
Authors: Zhang Hengchu , Roth Edo , Haeberlen Andreas , Pierce Benjamin C. , Roth Aaron
Published: November 2020

Applying differential privacy at scale requires convenient ways to check that programs computing with sensitive data appropriately preserve privacy. We propose here a fully automated framework for
testing
differential privacy, adapting a well-known “pointwise” technique from informal proofs of differential privacy. Our framework, called DPCheck, requires no programmer annotations, handles all previously verified or tested algorithms, and is the first fully automated framework to distinguish correct and buggy implementations of PrivTree, a probabilistically terminating algorithm that has not previously been mechanically checked.

We analyze the probability of DPCheck mistakenly accepting a non-private program and prove that, theoretically, the probability of false acceptance can be made exponentially small by suitable choice of test size.

We demonstrate DPCheck’s utility empirically by implementing all benchmark algorithms from prior work on mechanical verification of differential privacy, plus several others and their incorrect variants, and show DPCheck accepts the correct implementations and rejects the incorrect variants.

We also demonstrate how DPCheck can be deployed in a practical workflow to test differentially privacy for the 2020 US Census Disclosure Avoidance System (DAS).
Geometry types for graphics programming
Authors: Geisler Dietrich , Yoon Irene , Kabra Aditi , He Horace , Sanders Yinnon , Sampson Adrian
Published: November 2020

In domains that deal with physical space and geometry, programmers need to track the coordinate systems that underpin a computation. We identify a class of geometry bugs that arise from confusing which coordinate system a vector belongs to. These bugs are not ruled out by current languages for vector-oriented computing, are difficult to check for at run time, and can generate subtly incorrect output that can be hard to test for.

We introduce a type system and language that prevents geometry bugs by reflecting the coordinate system for each geometric object. A value's geometry type encodes its reference frame, the kind of geometric object (such as a point or a direction), and the coordinate representation (such as Cartesian or spherical coordinates). We show how these types can rule out geometrically incorrect operations, and we show how to use them to automatically generate correct-by-construction code to transform vectors between coordinate systems. We implement a language for graphics programming, Gator, that checks geometry types and compiles to OpenGL's shading language, GLSL. Using case studies, we demonstrate that Gator can raise the level of abstraction for shader programming and prevent common errors without inducing significant annotation overhead or performance cost.
Hidden inheritance: an inline caching design for TypeScript performance
Authors: Wu Zhefeng , Sun Zhe , Gong Kai , Chen Lingyun , Liao Bin , Jin Yihua
Published: November 2020

TypeScript is a dynamically typed language widely used to develop large-scale applications nowadays. These applications are usually designed with complex class or interface hierarchies and have highly polymorphic behaviors. These object-oriented (OO) features will lead to inefficient inline caches (ICs) or trigger deoptimizations, which impact the performance of TypeScript applications.

To address this problem, we introduce an inline caching design called hidden inheritance (HI). The basic idea of HI is to cache the static information of class or interface hierarchies into hidden classes, which are leveraged to generate efficient inline caches for improving the performance of OO-style TypeScript programs. The HI design is implemented in a TypeScript engine STSC (Static TypeScript Compiler) including a static compiler and a runtime system. STSC statically generates hidden classes and enhanced inline caches, which are applied to generate specialized machine code via ahead-of-time compilation (AOTC) or just-in-time compilation (JITC). To evaluate the efficiency of this technique, we implement STSC on a state-of-the-art JavaScript virtual machine V8 and demonstrate its performance improvements on industrial benchmarks and applications.
Rethinking safe consistency in distributed object-oriented programming
Authors: Köhler Mirko , Eskandani Nafise , Weisenburger Pascal , Margara Alessandro , Salvaneschi Guido
Published: November 2020

Large scale distributed systems require to embrace the trade off between consistency and availability, accepting lower levels of consistency to guarantee higher availability. Existing programming languages are, however, agnostic to this compromise, resulting in consistency guarantees that are the same for the whole application and are implicitly adopted from the middleware or hardcoded in configuration files. In this paper, we propose to integrate availability in the design of an object-oriented language, allowing developers to specify different consistency and isolation constraints in the same application at the granularity of single objects. We investigate how availability levels interact with object structure and define a type system that preserves correct program behavior. Our evaluation shows that our solution performs efficiently and improves the design of distributed applications.
Precise static modeling of Ethereum “memory”
Authors: Lagouvardos Sifis , Grech Neville , Tsatiris Ilias , Smaragdakis Yannis
Published: November 2020

Static analysis of smart contracts as-deployed on the Ethereum blockchain has received much recent attention. However, high-precision analyses currently face significant challenges when dealing with the Ethereum VM (EVM) execution model. A major such challenge is the modeling of low-level, transient “memory” (as opposed to persistent, on-blockchain “storage”) that smart contracts employ. Statically understanding the usage patterns of memory is non-trivial, due to the dynamic allocation nature of in-memory buffers. We offer an analysis that models EVM memory, recovering high-level concepts (e.g., arrays, buffers, call arguments) via deep modeling of the flow of values. Our analysis opens the door to Ethereum static analyses with drastically increased precision. One such analysis detects the extraction of ERC20 tokens by unauthorized users. For another practical vulnerability (redundant calls, possibly used as an attack vector), our memory modeling yields analysis precision of 89%, compared to 16% for a state-of-the-art tool without precise memory modeling. Additionally, precise memory modeling enables the static computation of a contract’s gas cost. This gas-cost analysis has recently been instrumental in the evaluation of the impact of the EIP-1884 repricing (in terms of gas costs) of EVM operations, leading to a reward and significant publicity from the Ethereum Foundation.
Structure interpretation of text formats
Authors: Gulwani Sumit , Le Vu , Radhakrishna Arjun , Radiček Ivan , Raza Mohammad
Published: November 2020

Data repositories often consist of text files in a wide variety of standard formats, ad-hoc formats, as well as mixtures of formats where data in one format is embedded into a different format. It is therefore a significant challenge to parse these files into a structured tabular form, which is important to enable any downstream data processing.

We present Unravel, an extensible framework for structure interpretation of ad-hoc formats. Unravel can automatically, with no user input, extract tabular data from a diverse range of standard, ad-hoc and mixed format files. The framework is also easily extensible to add support for previously unseen formats, and also supports interactivity from the user in terms of examples to guide the system when specialized data extraction is desired. Our key insight is to allow arbitrary combination of extraction and parsing techniques through a concept called
partial structures
. Partial structures act as a common language through which the file structure can be shared and refined by different techniques. This makes Unravel more powerful than applying the individual techniques in parallel or sequentially. Further, with this rule-based extensible approach, we introduce the novel notion of
re-interpretation
where the variety of techniques supported by our system can be exploited to improve accuracy while optimizing for particular quality measures or restricted environments. On our benchmark of 617 text files gathered from a variety of sources, Unravel is able to extract the intended table in many more cases compared to state-of-the-art techniques.
A structural model for contextual code changes
Authors: Brody Shaked , Alon Uri , Yahav Eran
Published: November 2020

We address the problem of predicting
edit completions
based on a learned model that was trained on past edits. Given a code snippet that is partially edited, our goal is to predict a
completion of the edit for the rest of the snippet
. We refer to this task as the EditCompletion task and present a novel approach for tackling it. The main idea is to directly represent structural edits. This allows us to model the likelihood of the edit itself, rather than learning the likelihood of the edited code. We represent an edit operation as a path in the program’s Abstract Syntax Tree (AST), originating from the source of the edit to the target of the edit. Using this representation, we present a powerful and lightweight neural model for the EditCompletion task.

We conduct a thorough evaluation, comparing our approach to a variety of representation and modeling approaches that are driven by multiple strong models such as LSTMs, Transformers, and neural CRFs. Our experiments show that our model achieves a 28% relative gain over state-of-the-art sequential models and 2× higher accuracy than syntactic models that learn to generate the edited
code
, as opposed to modeling the
edits
directly.

Our code, dataset, and trained models are publicly available at https://github.com/tech-srl/c3po/ .
Revisiting iso-recursive subtyping
Authors: Zhou Yaoda , Oliveira Bruno C. d. S. , Zhao Jinxu
Published: November 2020

The Amber rules are well-known and widely used for subtyping iso-recursive types. They were first briefly and informally introduced in 1985 by Cardelli in a manuscript describing the Amber language. Despite their use over many years, important aspects of the metatheory of the iso-recursive style Amber rules have not been studied in depth or turn out to be quite challenging to formalize.

This paper aims to revisit the problem of subtyping iso-recursive types. We start by introducing a novel declarative specification that we believe captures the “spirit” of Amber-style iso-recursive subtyping. Informally, the specification states that two recursive types are subtypes
if all their finite unfoldings are subtypes
. The Amber rules are shown to be sound with respect to this declarative specification. We then derive a
sound
,
complete
and
decidable
algorithmic formulation of subtyping that employs a novel
double unfolding
rule. Compared to the Amber rules, the double unfolding rule has the advantage of: 1) being modular; 2) not requiring reflexivity to be built in; and 3) leading to an easy proof of transitivity of subtyping. This work sheds new insights on the theory of subtyping iso-recursive types, and the new double unfolding rule has important advantages over the original Amber rules for both implementations and metatheoretical studies involving recursive types. All results are mechanically formalized in the Coq theorem prover. As far as we know, this is the first comprehensive treatment of iso-recursive subtyping dealing with unrestricted recursive types in a theorem prover.
Macros for domain-specific languages
Authors: Ballantyne Michael , King Alexis , Felleisen Matthias
Published: November 2020

Macros provide a powerful means of extending languages. They have proven useful in both general-purpose and domain-specific programming contexts. This paper presents an architecture for implementing macro-extensible DSLs on top of macro-extensible host languages. The macro expanders of these DSLs inherit the syntax system, hygienic expansion, and more from the host. They transform the extensible DSL syntax into a DSL core language. This arrangement has several important consequences. It becomes straightforward to integrate the syntax of various DSLs and the host language when their expanders share these inherited components. Also, a DSL compiler may be designed around a fixed core language, even for an extensible DSL. Finally, macros empower programmers to safely grow DSLs on their own and tailor them to their needs.
Polyelectrolyte Complex Coacervates: Recent Developments and New Frontiers
Authors: Rumyantsev Artem M. , Jackson Nicholas E. , de Pablo Juan J.
Published: November 2020

Polyelectrolyte complex coacervates represent a wide class of materials with applications ranging from coatings and adhesives to pharmaceutical technologies. They also underpin multiple biological processes, which are only now beginning to be deciphered. The means by which molecular-scale architecture propagates into macroscopic structure, thermodynamics, and dynamics in complex coacervates is of central concern in physics, chemistry, biology, and materials science. How does polyion charge sequence dictate thermodynamic behavior? How does one tailor rheology or interfacial tension using macromolecular architecture? What emergent functionality from polymer complex coacervates has biological consequences? Recent developments in coacervate science shed light on many of these issues and raise exciting new challenges for the close integration of theory, simulations, and experiment.
Brown Algal Model Organisms
Authors: Coelho Susana M. , Cock J. Mark
Published: November 2020

Model organisms are extensively used in research as accessible and convenient systems for studying a particular area or question in biology. Traditionally, only a limited number of organisms have been studied in detail, but modern genomic tools are enabling researchers to extend beyond the set of classical model organisms to include novel species from less-studied phylogenetic groups. This review focuses on model species for an important group of multicellular organisms, the brown algae. The development of genetic and genomic tools for the filamentous brown alga Ectocarpus has led to it emerging as a general model system for this group, but additional models, such as Fucus or Dictyota dichotoma, remain of interest for specific biological questions. In addition, Saccharina japonica has emerged as a model system to directly address applied questions related to algal aquaculture. We discuss the past, present, and future of brown algal model organisms in relation to the opportunities and challenges in brown algal research.
Detection and Diagnostic Utilization of Cellular and Cell-Free Tumor DNA
Authors: Dudley Jonathan C. , Diehn Maximilian
Published: November 2020

Because cancer is caused by an accumulation of genetic mutations, mutant DNA released by tumors can be used as a highly specific biomarker for cancer. Although this principle was described decades ago, the advent and falling costs of next-generation sequencing have made the use of tumor DNA as a biomarker increasingly practical. This review surveys the use of cellular and cell-free DNA for the detection of cancer, with a focus on recent technological developments and applications to solid tumors. It covers ( a) key principles and technology enabling the highly sensitive detection of tumor DNA; ( b) assessment of tumor DNA in plasma, including for genotyping, minimal residual disease detection, and early detection of localized cancer; ( c) detection of tumor DNA in body cavity fluids, such as urine or cerebrospinal fluid; and ( d) challenges posed to the use of tumor DNA as a biomarker by the phenomenon of benign clonal expansions.
Molecular Pathogenesis of Merkel Cell Carcinoma
Authors: DeCaprio James A.
Published: November 2020

Merkel cell carcinoma (MCC) is an aggressive neuroendocrine carcinoma of the skin with two distinct etiologies. Clonal integration of Merkel cell polyomavirus DNA into the tumor genome with persistent expression of viral T antigens causes at least 60% of all MCC. UV damage leading to highly mutated genomes causes a nonviral form of MCC. Despite these distinct etiologies, both forms of MCC are similar in presentation, prognosis, and response to therapy. At least three oncogenic transcriptional programs feature prominently in both forms of MCC driven by the virus or by mutation. Both forms of MCC have a high proliferative growth rate with increased levels of cell cycle–dependent genes due to inactivation of the tumor suppressors RB and p53, a strong MYC signature due to MYCL activation by the virus or gene amplification, and an attenuated neuroendocrine differentiation program driven by the ATOH1 transcription factor.
Spin Splitting Spectroscopy of Heavy Quark and Antiquarks Systems
Authors: Mansour Hesham , Gamal Ahmed , Abolmahassen M.
Published: November 2020

Phenomenological potentials describe the quarkonium systems likecc¯,bb,¯ and b¯cwhere they give a good accuracy for the mass spectra. In the present work, we extend one of our previous works in the central case by adding spin-dependent terms to allow for relativistic corrections. By using such terms, we get better accuracy than previous theoretical calculations. In the present work, the mass spectra of the bound states of heavy quarks cc¯,bb¯,and 𝐵𝑐 mesons are studied within the framework of the nonrelativistic Schrödinger equation. First, we solve Schrödinger’s equation by Nikiforov-Uvarov (NU) method. The energy eigenvalues are presented using our new potential. The results obtained are in good agreement with the experimental data and are better than the previous theoretical estimates.
Athlete Social Support Network Modeling Based on Modern Valence Bond Theory
Authors: Zhao Ningshe
Published: November 2020

Based on the Valence Bond theory, an attempt is proposed to the complex network. The principle of chemical bonding of the basic particles that make up the substance creates a metaphor between the formation of social networks. By analyzing the integration of atoms by relying on the chemical bonds between particles, then the social basis for the connection between social network nodes should depend on the tangible or intangible attribute resources that characterize social capital around the main node. Based on the above analysis, the social node is divided into active nodes and passive nodes, and a dynamic model of social network formation is proposed, the Valence Bond model of social network. Through this model, the actual athlete group nodes are depicted, and the representation of the model and the evolution of network structure are given with the actual data.
A Comparative Analysis of Strategic Values of Four Silk-Road International Transport Corridors Based on a Fuzzy Integral Method with Comprehensive Weights
Authors: Wang Chengfu , Huang Chengfeng , Guan Haichang , Zeng Tao
Published: November 2020

This paper carries out a comparative analysis of the strategic values of four silk-road international transport corridors, “China-Pakistan-Iran-Turkey” (CPIT), “China-Mongolia-Russia” (CMR), “Bangladesh-China-India-Myanmar” (BCIM), and “China-Singapore-Egypt-Greece” (CSEG). These corridors aim to reactivate the Northwest, North, South, and Marine Silk Road during the period of the “Belt and Road” (B&R), reflect China’s overarching strategic goal of “furnishing land-sea internal and external linkage and achieving east-west mutual aid,” and possess important strategic values. To facilitate the comparison, this paper constructs a hierarchical model and evaluation index system for assessing the strategic value of international transport corridors (SVITC). From China’s perspective, this paper uses a fuzzy integral method with comprehensive weights to evaluate and compare the SVITC of the four international corridors as fuzzy integrals can handle interdependent indices and comprehensive weights can accommodate both subjective and objective weights. In the evaluation process, we first clarify the strategic attributes and characteristics of each corridor and identify its corresponding missions so that the overseas infrastructure projects along the four corridors can be carried out smoothly. By assessing their strategic values and ranking them accordingly, we offer the policy maker with useful information to prioritize investment opportunities and deploy limited resources in the construction of these corridors. Finally, this comparative study identifies the weaknesses and strengths in different corridors, which allow them to learn from each other, make joint progress, and strengthen linkages and integrations, thereby providing a set of feasible solutions for the construction of B&R international corridors.
Nutritional Status and Anthropometric Indices in relation to Menstrual Disorders: A Cross-Sectional Study
Authors: Taheri Reihaneh , Mesbah Ardekani Fakhrodin , Raeisi Shahraki Hadi , Heidarzadeh-Esfahani Neda , Hajiahmadi Salimeh
Published: November 2020

Purpose. Dietary habit and body composition can develop risk of menstrual disorders. The objective of this study was to assess the relationship between macronutrient intake, anthropometric indices, and menstrual disorders. Methods. This cross-sectional study was conducted on 217 women with an average age of 28.8 ± 7.9 years. Anthropometric indices including body mass index (BMI), waist circumference (WC), waist-to-hip ratio (WHR), and skinfold thickness from all participants were measured. Menstrual cycle characteristics were self-reported. The dietary habits were assessed by using a modified, semiquantitative 147 items Food Frequency Questionnaire (FFQ) by two trained dietitians. Chi-square and independent T-test were used to assess bivariate associations and logistic regression was implemented in SPSS 21. Results. Most of the participants (52.5%) suffered from at least one of the menstrual disorders including painful menstruation (41%), premenstrual syndrome (PMS) (24.9%), and irregular menstruation (22.1%). The mean of waist circumference in women with no complication was 76.0 ± 11.8 and in women with at least one disorder was 86.7 ± 14.0 (P<0.001). Our results suggest that women with no disorder consumed less calorie, carbohydrate, protein, and fat in comparison to women with at least one disorder (P<0.001). Furthermore, the proportion of all kinds of disorders among women, who had overweight or obesity, was significantly higher than women with normal BMI (P<0.001). Conclusion. Irregular menstruation, painful menstruation, and PMS were significantly associated with high intake of calories, proteins, carbohydrates, and total fat. Furthermore, menstruation-related complications were worsened by obesity.
Effect of Friction Coupling on Discharge Velocity Profiles and Force Chain Distribution of Maize Particles in Silos
Authors: Feng Yong , Yu Caihua , Pan Fan
Published: November 2020

The evolution mechanism of discharge velocity profiles and force chain distribution of maize particles in silos was studied based on the interaction between internal and external rolling friction of particles. Through EDEM, the silo and maize grain models were established for unloading simulation, whose flow pattern was compared with the silo unloading test to verify the rationality of the simulation. By slice observation, we compared and analyzed the time evolution rules of particle mesoscopic parameters under different friction conditions. The results show that the larger the interparticle friction coefficient is, the longer the total discharge time is and the smaller the coefficient of rolling friction between particles, the earlier the particle flow from mass flow to funnel flow. For silos with the funnel, the reduction of interparticle friction will change the limit between the mass flow and the funnel flow, thus increasing the area of the funnel flow. When the coefficient of rolling friction increases, the vertical velocity and angular velocity of the particle near the silo middle increase. However, the effects of internal and external friction coupling on the vertical velocity of the side particle, the horizontal velocity of the whole particle, and the spatial distribution and probability distribution of the force chain are more significant.
Clinical Outcome and Predictors of Intestinal Obstruction Surgery in Ethiopia: A Cross‐Sectional Study
Authors: Derseh Tesfaye , Dingeta Tariku , Yusouf Mohammed , Minuye Binyam
Published: November 2020

Background. Despite the advancement in the healthcare system, the impact of surgical interventions on public health systems will continue to grow. But predicting the outcome is challenging. Concerns related to unexpected outcomes and delays in the diagnosis of postoperative complications are the major issue. Intestinal obstruction is a common life‐threatening surgical condition followed by fatal and nonfatal postoperative complications. This study was aimed at assessing results after surgery for intestinal obstruction in a hospital of Ethiopia. Methodology. An institutional‐based cross‐sectional study was conducted among 254 postoperative patients admitted with intestinal obstruction from January 1, 2014, to December 31, 2017. Data were coded and entered into EpiData 4.2.0.0 software and exported to the Statistical Package for the Social Sciences version 22 for analysis. A binary logistic regression model was used for analysis. All variables with a p value < 0.25 during bivariable analysis were considered for multivariable logistic regression analysis. Results. The magnitude of poor surgical outcome of intestinal obstruction was 21.3% for patients enrolled into this investigation. The age group of ≥55 years (adjusted odds ratio (AOR) = 2.9, 95% CI: 1.03, 8.4), duration of illness of ≥24 hrs (AOR = 3.1, 95% CI: 1.03, 9.4), preoperative diagnosis of a gangrenous large bowel (AOR = 3.6, 95% CI: 1.3, 9.8), and a gangrenous small bowel (AOR = 4.2, 95% CI: 1.3, 13.7) were significantly associated with poor surgical outcome. Conclusions. The magnitude of poor surgical outcome was high. Age, late presentation of illness, and gangrenous bowel obstructions were significantly associated with poor outcomes. So, concern should be given in early detection and follow‐up of patients who came late and older patients.
Vertical Line Extension Decisions in a Competitive Market with Consumers’ Need for Product Uniqueness
Authors: Wang Jie , Su Qin , Wang Canyou
Published: November 2020

One important reason for offering customized products is to satisfy consumers’ need for product uniqueness. In this paper, we take consumers’ unique preferences into account to examine how firms make decisions on vertical line extensions with introducing a customized product. This study develops the consumer’s utility function, which captures consumers’ behavioural and emotional factors, and the results show that the high-quality firm always introduces an upward extension without uniqueness sensitivity. However, introducing a downward extension may be more profitable especially when consumers have the high unique ness sensitivity. We also find that the upward extension of the high-quality firm does not intensify competition with the low-quality firm, but its downward extension will intensify the competition between two firms, whether with or without unique preferences. We also analyse the low-quality firm’s extension decisions when it faces a high-end competitor and find that the low-quality firm may change from introducing a downward extension to introducing an upward extension when intrafirm quality differentiation is small.
Application of a New Type of Natural Calcined Bone Repair Material Combined with Concentrated Growth Factors in Bone Regeneration in Rabbit Critical‐Sized Calvarial Defect
Authors: Wang Xiaoyang , Tong Shuqing , Huang Shengyun , Ma Li , Liu Zhenxing , Zhang Dongsheng
Published: November 2020

Purpose. This study is aimed at investigating bone regeneration in critical‐sized defects in rabbit calvarium using a novel nano‐ (n‐) hydroxyapatite hybrid scaffold with concentrated growth factors (CGFs). Methods. Twenty‐four male adult rabbits were chosen to establish a critical‐sized bone defect model and randomly divided into two groups. Two defects of 15 mm diameter each were created in the parietal bone of each animal. Group A had n‐hydroxyapatite hybrid scaffold placed in the experimental defect on the right, and the left defect was unfilled as blank. Group B had hydroxyapatite hybrid scaffold mixed with CGF placed in the right defect and CGF on the left. Six animals in each group were sacrificed after 6 and 12 weeks. Cone‐beam computed tomography system scanning and hematoxylin and eosin (HE) staining were used to detect osteogenesis within the defects. Results. The treatment with n‐hydroxyapatite hybrid scaffold along with CGF resulted in a significantly higher amount of new bone at 6 and 12 weeks compared to the treatment with CGF alone and the controls. No apparent inflammation and foreign body reaction were observed through HE staining. Conclusions. The new synthesized n‐hydroxyapatite hybrid scaffold and CGF can be applied for bone defect regeneration to promote the process to a certain extent.
GJA1 Expression and Its Prognostic Value in Cervical Cancer
Authors: Meng Silu , Fan Xinran , Zhang Jianwei , An Ran , Li Shuang
Published: November 2020

Gap Junction Protein Alpha 1 (GJA1) belongs to the gap junction family and has been widely studied in cancers. We evaluated the role of GJA1 in cervical cancer (CC) using public data from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) database. The difference of GJA1 expression level between CC and normal tissues was analyzed by the Gene Expression Profiling Interactive Analysis (GEPIA), six GEO datasets, and the Human Protein Atlas (HPA). The relationship between clinicopathological features and GJA1 expression was analyzed by the chi‐squared test and the logistic regression. Kaplan–Meier survival analysis and Cox proportional hazard regression analysis were used to assessing the effect of GJA1 expression on survival. Gene set enrichment analysis (GSEA) was used to screen the signaling pathways regulated by GJA1. Immune Cell Abundance Identifier (ImmuCellAI) was chosen to analyze the immune cells affected by GJA1. The expression of GJA1 in CC was significantly lower than that in normal tissues based on the GEPIA, GEO datasets, and HPA. Both the chi‐squared test and the logistic regression showed that high‐GJA1 expression was significantly correlated with keratinization, hormone use, tumor size, and FIGO stage. The Kaplan–Meier curves suggested that high‐GJA1 expression could indicate poor prognosis (p = 0.0058). Multivariate analysis showed that high‐GJA1 expression was an independent predictor of poor overall survival (HR, 4.084; 95% CI, 1.354‐12.320; p = 0.013). GSEA showed many cancer‐related pathways, such as the p53 signaling pathway and the Wnt signaling pathway, were enriched in the high‐GJA1‐expression group. Immune cell abundance analysis revealed that the abundance of CD8 naive, DC, and neutrophil was significantly increased in the high‐GJA1‐expression group. In conclusion, GJA1 can be regarded as a potential prognostic marker of poor survival and therapeutic target in CC. Moreover, many cancer‐related pathways may be the critical pathways regulated by GJA1. Furthermore, GJA1 can affect the abundance of immune cells.
An Improved Deep Learning Model for Online Tool Condition Monitoring Using Output Power Signals
Authors: Dai Lang , Liu Tianyu , Liu Zhongyong , Jackson Lisa , Goodall Paul , Shen Changqing , Mao Lei
Published: November 2020

Something like normal functionality of tools in a manufacturing process is typically designed to ensure reliability, where fast and accurate identification of tool abnormal operation plays a vital role in intelligent manufacturing. In this study, a novel method is proposed to assess the cutting tool condition, which consists of a convolutional neural network with wider first-layer kernels (W-CONV), and long short-term memory (LSTM). The analysis benefits from the use of output power signals from the cutting tool, since they can be obtained easily and efficiently, enabling the proposed method to be applicable in practical operation for online condition monitoring. Moreover, effectiveness of the proposed method is investigated, using test data from cutting tools at various tool wear conditions. Results demonstrate that with the proposed method, tool wear condition can be identified accurately and efficiently. Furthermore, with test data collected at cutting tools with different sizes, the robustness of the proposed method can be further clarified.
Collapse‐Pounding Dynamic Responses of Adjacent Frame Structures under Earthquake Action
Authors: Jing Wei , Xing Shangshang , Song Yu
Published: November 2020

There are a large number of adjacent buildings in practical engineering application. The structure will collapse and impact the adjacent structures once the weak column is destroyed under seismic action, and, finally, the earthquake damage is aggravated. Material nonlinearity, initial imperfections, and contact problems in the process of collapse‐pounding are considered, and the three‐dimensional calculation model with unequal 8‐story and 6‐story height adjacent frames is established. The dynamic response of adjacent structures caused by collapse‐pounding is investigated when there is a weak column at different positions in the 8‐story frame, and the influence of gap size on the dynamic responses of adjacent structures is discussed. The results show that the impact force is larger when the weak column of the 8‐story frame is close to the top of the 6‐story frame; pounding increases the interlayer displacement angle of the 8‐story frame and decreases the interlayer displacement angle of the 6‐story frame in general; the impact force decreases first, then increases, and after that decreases with the increase of gap size; and the interlayer displacement angle distribution of the 6‐story frame is significantly affected after the collapse‐pounding of the 8‐story frame with a weak column. The collapse‐pounding problem of adjacent buildings under seismic action is very complex, which should be paid enough attention in engineering design and application.
Visual Acuity and Size of Choroidal Neovascularization in Highly Myopic Eyes with a Dome-Shaped Macula
Authors: Wang Lu , Lin Bin-wu , Yin Xiao-fang , Huang Wei-lan , Wang Yi-zhi , Pang Long
Published: November 2020

Introduction. A dome-shaped macula (DSM) is an inward convexity or anterior deviation of the macular area. DSM is believed as a protective factor in maintaining visual acuity in highly myopic eyes. Objective. To investigate the correlation between best-corrected visual acuity (BCVA), choroidal neovascularization (CNV), and a dome-shaped macula (DSM) in highly myopic eyes. Methods. In this retrospective and observational case series study, BCVA tests and optical coherence tomography (OCT) were performed in a total of 472 highly myopic eyes (refractive error ≥6.5 diopters or axial length ≥26.5 mm). CNV was detected by fundus fluorescein angiography (FFA), and the CNV area was measured by ImageJ software. BCVA, central retinal thickness (CRT), and the CNV area were compared between highly myopic eyes with and without DSM. Results. The data revealed 13 eyes with DSM complicated by CNV, for an estimated prevalence of 25%. The eyes with CNV in the DSM group showed worse BCVA than those in the non-DSM group (1.59 ± 0.69 and 0.63 ± 0.64, respectively,

p
<
0.05

), and the CNV area in the DSM group was larger than that in the non-DSM group (2793.91 ± 2181.24 and 1250.71 ± 1210.36 pixels, respectively,

p
<
0.05

). After excluding the eyes with CNV, the DSM group had better BCVA than the non-DSM group (0.33 ± 0.17 and 0.44 ± 0.48, respectively,

p
<
0.05

); however, no significant difference was observed in the CRT of eyes with CNV between the DSM group and the non-DSM group. Conclusion. These results show that DSM might be a protective mechanism for visual acuity, but its protective capability is limited. DSM eyes have better visual acuity within the protective capability. If a more powerful pathogenic factor exceeding the protective capability is present, then the eye will have more severe CNV and worse visual acuity.
Hydration Heat of Nonshrinkage Concrete in Large‐Diameter CFST Arch Ribs Cured at Low Temperatures
Authors: Shi Tuo , Deng Nianchun , Pan Dong , Wang Shi
Published: November 2020

To study the construction of concrete‐filled steel tubular (CFST) arch bridges in Tibet, China, the hydration‐temperature field of nonshrinkage concrete in large‐diameter CFST arch ribs was evaluated in a temperature‐testing box to simulate a low‐temperature environment. A finite element simulation was then conducted to replicate the experimental results. Finally, an improved formula with the parameters related to the diameter, the position, and the retarding time of concrete for predicting the hydration heat generated by non‐shrinkage concrete in large‐diameter CFST arch ribs cured at low temperatures was proposed. The formula results were shown to be consistent with the experimental results for low‐temperature conditions and large diameters. This research method can be extended to predict the hydration heat at all locations in different‐diameter CFSTs with different concrete mixes cured at various temperatures.