bluuebunny/crossref_metadata_2025 huggingface dataset:
What and How long: Prediction of Mobile App Engagement
Authors: Tian Yuan , Zhou Ke , Pelleg Dan
Published: September 2021

User engagement is crucial to the long-term success of a mobile app. Several metrics, such as dwell time, have been used for measuring user engagement. However, how to effectively predict user engagement in the context of mobile apps is still an open research question. For example, do the mobile usage contexts (e.g., time of day) in which users access mobile apps impact their dwell time? Answers to such questions could help mobile operating system and publishers to optimize advertising and service placement. In this article, we first conduct an empirical study for assessing how user characteristics, temporal features, and the short/long-term contexts contribute to gains in predicting users’ app dwell time on the population level. The comprehensive analysis is conducted on large app usage logs collected through a mobile advertising company. The dataset covers more than 12K anonymous users and 1.3 million log events. Based on the analysis, we further investigate a novel mobile app engagement prediction problem—can we predict simultaneously what app the user will use next and how long he/she will stay on that app? We propose several strategies for this joint prediction problem and demonstrate that our model can improve the performance significantly when compared with the state-of-the-art baselines. Our work can help mobile system developers in designing a better and more engagement-aware mobile app user experience.
Unstructured Text Enhanced Open-Domain Dialogue System: A Systematic Survey
Authors: Ma Longxuan , Li Mingda , Zhang Wei-Nan , Li Jiapeng , Liu Ting
Published: September 2021

Incorporating external knowledge into dialogue generation has been proven to benefit the performance of an open-domain Dialogue System (DS), such as generating informative or stylized responses, controlling conversation topics. In this article, we study the open-domain DS that uses unstructured text as external knowledge sources (
U
nstructured
T
ext
E
nhanced
D
ialogue
S
ystem (
UTEDS
)). The existence of unstructured text entails distinctions between UTEDS and traditional data-driven DS and we aim at analyzing these differences. We first give the definition of the UTEDS related concepts, then summarize the recently released datasets and models. We categorize UTEDS into Retrieval and Generative models and introduce them from the perspective of model components. The retrieval models consist of Fusion, Matching, and Ranking modules, while the generative models comprise Dialogue and Knowledge Encoding, Knowledge Selection (KS), and Response Generation modules. We further summarize the evaluation methods utilized in UTEDS and analyze the current models’ performance. At last, we discuss the future development trends of UTEDS, hoping to inspire new research in this field.
Reiterman’s Theorem on Finite Algebras for a Monad
Authors: Adámek Jiří , Chen Liang-Ting , Milius Stefan , Urbat Henning
Published: September 2021

Profinite equations are an indispensable tool for the algebraic classification of formal languages. Reiterman’s theorem states that they precisely specify pseudovarieties, i.e., classes of finite algebras closed under finite products, subalgebras and quotients. In this article, Reiterman’s theorem is generalized to finite Eilenberg-Moore algebras for a monad 
T
on a category  D: we prove that a class of finite
T
-algebras is a pseudovariety iff it is presentable by profinite equations. As a key technical tool, we introduce the concept of a profinite monad
T
^
associated to the monad
T
, which gives a categorical view of the construction of the space of profinite terms.
EXPSPACE-Completeness of the Logics K4 × S5 and S4 × S5 and the Logic of Subset Spaces
Authors: Hertling Peter , Krommes Gisela
Published: September 2021

It is known that the satisfiability problems of the product logics K4 × S5 and S4 × S5 are NEXPTIME-hard and that the satisfiability problem of the logic SSL of subset spaces is PSPACE-hard. Furthermore, it is known that the satisfiability problems of these logics are in N2EXPTIME. We improve the lower and the upper bounds for the complexity of these problems by showing that all three problems are in ESPACE and are EXPSPACE-complete under logspace reduction.
Collaborative Reflection-Augmented Autoencoder Network for Recommender Systems
Authors: Xia Lianghao , Huang Chao , Xu Yong , Xu Huance , Li Xiang , Zhang Weiguo
Published: September 2021

As the deep learning techniques have expanded to real-world recommendation tasks, many deep neural network based Collaborative Filtering (CF) models have been developed to project user-item interactions into latent feature space, based on various neural architectures, such as multi-layer perceptron, autoencoder, and graph neural networks. However, the majority of existing collaborative filtering systems are not well designed to handle missing data. Particularly, in order to inject the negative signals in the training phase, these solutions largely rely on negative sampling from unobserved user-item interactions and simply treating them as negative instances, which brings the recommendation performance degradation. To address the issues, we develop a
C
ollaborative
R
eflection-Augmented
A
utoencoder
N
etwork (CRANet), that is capable of exploring transferable knowledge from observed and unobserved user-item interactions. The network architecture of CRANet is formed of an integrative structure with a reflective receptor network and an information fusion autoencoder module, which endows our recommendation framework with the ability of encoding implicit user’s pairwise preference on both interacted and non-interacted items. Additionally, a parametric regularization-based tied-weight scheme is designed to perform robust joint training of the two-stage CRANetmodel. We finally experimentally validate CRANeton four diverse benchmark datasets corresponding to two recommendation tasks, to show that debiasing the negative signals of user-item interactions improves the performance as compared to various state-of-the-art recommendation techniques. Our source code is available at https://github.com/akaxlh/CRANet.
Question Tagging via Graph-guided Ranking
Authors: Zhang Xiao , Liu Meng , Yin Jianhua , Ren Zhaochun , Nie Liqiang
Published: September 2021

With the increasing prevalence of portable devices and the popularity of community Question Answering (cQA) sites, users can seamlessly post and answer many questions. To effectively organize the information for precise recommendation and easy searching, these platforms require users to select topics for their raised questions. However, due to the limited experience, certain users fail to select appropriate topics for their questions. Thereby, automatic question tagging becomes an urgent and vital problem for the cQA sites, yet it is non-trivial due to the following challenges. On the one hand, vast and meaningful topics are available yet not utilized in the cQA sites; how to model and tag them to relevant questions is a highly challenging problem. On the other hand, related topics in the cQA sites may be organized into a directed acyclic graph. In light of this, how to exploit relations among topics to enhance their representations is critical. To settle these challenges, we devise a graph-guided topic ranking model to tag questions in the cQA sites appropriately. In particular, we first design a topic information fusion module to learn the topic representation by jointly considering the name and description of the topic. Afterwards, regarding the special structure of topics, we propose an information propagation module to enhance the topic representation. As the comprehension of questions plays a vital role in question tagging, we design a multi-level context-modeling-based question encoder to obtain the enhanced question representation. Moreover, we introduce an interaction module to extract topic-aware question information and capture the interactive information between questions and topics. Finally, we utilize the interactive information to estimate the ranking scores for topics. Extensive experiments on three Chinese cQA datasets have demonstrated that our proposed model outperforms several state-of-the-art competitors.
Lower Bounds on OBDD Proofs with Several Orders
Authors: Buss Sam , Itsykson Dmitry , Knop Alexander , Riazanov Artur , Sokolov Dmitry
Published: September 2021

This article is motivated by seeking lower bounds on OBDD(∧, w, r) refutations, namely, OBDD refutations that allow weakening and arbitrary reorderings. We first work with 1 - NBP ∧ refutations based on read-once nondeterministic branching programs. These generalize OBDD(∧, r) refutations. There are polynomial size 1 - NBP(∧) refutations of the pigeonhole principle, hence 1-NBP(∧) is strictly stronger than OBDD}(∧, r). There are also formulas that have polynomial size tree-like resolution refutations but require exponential size 1-NBP(∧) refutations. As a corollary, OBDD}(∧, r) does not simulate tree-like resolution, answering a previously open question.

The system 1-NBP(∧, ∃) uses projection inferences instead of weakening. 1-NBP(∧, ∃

k

is the system restricted to projection on at most
k
distinct variables. We construct explicit constant degree graphs
G

n

on
n
vertices and an ε > 0, such that 1-NBP(∧, ∃

ε
n

) refutations of the Tseitin formula for
G

n

require exponential size.

Second, we study the proof system OBDD}(∧, w, r
ℓ
), which allows ℓ different variable orders in a refutation. We prove an exponential lower bound on the complexity of tree-like OBDD(∧, w, r
ℓ
) refutations for ℓ = ε log
n
, where
n
is the number of variables and ε > 0 is a constant. The lower bound is based on multiparty communication complexity.
A Review on Question Generation from Natural Language Text
Authors: Zhang Ruqing , Guo Jiafeng , Chen Lu , Fan Yixing , Cheng Xueqi
Published: September 2021

Question generation is an important yet challenging problem in Artificial Intelligence (AI), which aims to generate natural and relevant questions from various input formats, e.g., natural language text, structure database, knowledge base, and image. In this article, we focus on question generation from natural language text, which has received tremendous interest in recent years due to the widespread applications such as data augmentation for question answering systems. During the past decades, many different question generation models have been proposed, from traditional rule-based methods to advanced neural network-based methods. Since there have been a large variety of research works proposed, we believe it is the right time to summarize the current status, learn from existing methodologies, and gain some insights for future development. In contrast to existing reviews, in this survey, we try to provide a more comprehensive taxonomy of question generation tasks from three different perspectives, i.e., the types of the input context text, the target answer, and the generated question. We take a deep look into existing models from different dimensions to analyze their underlying ideas, major design principles, and training strategies We compare these models through benchmark tasks to obtain an empirical understanding of the existing techniques. Moreover, we discuss what is missing in the current literature and what are the promising and desired future directions.
Knowledge Preserving and Distribution Alignment for Heterogeneous Domain Adaptation
Authors: Wu Hanrui , Wu Qingyao , Ng Michael K.
Published: September 2021

Domain adaptation aims at improving the performance of learning tasks in a target domain by leveraging the knowledge extracted from a source domain. To this end, one can perform knowledge transfer between these two domains. However, this problem becomes extremely challenging when the data of these two domains are characterized by different types of features, i.e., the feature spaces of the source and target domains are different, which is referred to as heterogeneous domain adaptation (HDA). To solve this problem, we propose a novel model called Knowledge Preserving and Distribution Alignment (KPDA), which learns an augmented target space by jointly minimizing information loss and maximizing domain distribution alignment. Specifically, we seek to discover a latent space, where the knowledge is preserved by exploiting the Laplacian graph terms and reconstruction regularizations. Moreover, we adopt the Maximum Mean Discrepancy to align the distributions of the source and target domains in the latent space. Mathematically, KPDA is formulated as a minimization problem with orthogonal constraints, which involves two projection variables. Then, we develop an algorithm based on the Gauss–Seidel iteration scheme and split the problem into two subproblems, which are solved by searching algorithms based on the Barzilai–Borwein (BB) stepsize. Promising results demonstrate the effectiveness of the proposed method.
COVID-Safe Spatial Occupancy Monitoring Using OFDM-Based Features and Passive WiFi Samples
Authors: Li Junye , Sharma Aryan , Mishra Deepak , Batista Gustavo , Seneviratne Aruna
Published: September 2021

During the COVID-19 pandemic, authorities have been asking for social distancing to prevent transmission of the virus. However, enforcing such distancing has been challenging in tight spaces such as elevators and unmonitored commercial settings such as offices. This article addresses this gap by proposing a low-cost and non-intrusive method for monitoring social distancing within a given space, using Channel State Information (CSI) from passive WiFi sensing. By exploiting the frequency selective behavior of CSI with a Support Vector Machine (SVM) classifier, we achieve an improvement in accuracy over existing crowd counting works. Our system counts the number of occupants with a 93% accuracy rate in an elevator setting and predicts whether the COVID-Safe limit is breached with a 97% accuracy rate. We also demonstrate the occupant counting capability of the system in a commercial office setting, achieving 97% accuracy. Our proposed occupancy monitoring outperforms existing methods by at least 7%. Overall, the proposed framework is inexpensive, requiring only one device that passively collects data and a lightweight supervised learning algorithm for prediction. Our lightweight model and accuracy improvements are necessary contributions for WiFi-based counting to be suitable for COVID-specific applications.
User Profiling Based on Nonlinguistic Audio Data
Authors: Shen Jiaxing , Cao Jiannong , Lederman Oren , Tang Shaojie , Pentland Alex “Sandy”
Published: September 2021

User profiling refers to inferring people’s
attributes of interest
(
AoIs
) like gender and occupation, which enables various applications ranging from personalized services to collective analyses. Massive nonlinguistic audio data brings a novel opportunity for user profiling due to the prevalence of studying spontaneous face-to-face communication. Nonlinguistic audio is coarse-grained audio data without linguistic content. It is collected due to privacy concerns in private situations like doctor-patient dialogues. The opportunity facilitates optimized organizational management and personalized healthcare, especially for chronic diseases. In this article, we are the first to build a user profiling system to infer gender and personality based on nonlinguistic audio. Instead of linguistic or acoustic features that are unable to extract, we focus on conversational features that could reflect AoIs. We firstly develop an adaptive voice activity detection algorithm that could address individual differences in voice and false-positive voice activities caused by people nearby. Secondly, we propose a gender-assisted multi-task learning method to combat dynamics in human behavior by integrating gender differences and the correlation of personality traits. According to the experimental evaluation of 100 people in 273 meetings, we achieved 0.759 and 0.652 in F1-score for gender identification and personality recognition, respectively.
Multi-interest Diversification for End-to-end Sequential Recommendation
Authors: Chen Wanyu , Ren Pengjie , Cai Fei , Sun Fei , De Rijke Maarten
Published: September 2021

Sequential recommenders capture dynamic aspects of users’ interests by modeling sequential behavior. Previous studies on sequential recommendations mostly aim to identify users’ main recent interests to optimize the recommendation accuracy; they often neglect the fact that users display multiple interests over extended periods of time, which could be used to improve the diversity of lists of recommended items. Existing work related to diversified recommendation typically assumes that users’ preferences are static and depend on post-processing the candidate list of recommended items. However, those conditions are not suitable when applied to sequential recommendations. We tackle sequential recommendation as a list generation process and propose a unified approach to take accuracy as well as diversity into consideration, called
multi-interest, diversified, sequential recommendation
. Particularly, an implicit interest mining module is first used to mine users’ multiple interests, which are reflected in users’ sequential behavior. Then an interest-aware, diversity promoting decoder is designed to produce recommendations that cover those interests. For training, we introduce an interest-aware, diversity promoting loss function that can supervise the model to learn to recommend accurate as well as diversified items. We conduct comprehensive experiments on four public datasets and the results show that our proposal outperforms state-of-the-art methods regarding diversity while producing comparable or better accuracy for sequential recommendation.
Enhancing Performance of Anode-Free Li-Metal Batteries by Addition of Ceramic Nanoparticles: Part I.
Authors: Mukra Tzach , Marrache Roy , Shekhter Pini , Peled Emanuel
Published: September 2021

Because of their higher energy density, compared to lithium-ion batteries, rechargeable lithium-metal batteries (LMB) have been considered one of the most attractive next-generation energy-storage systems. A promising approach to improve LMB performance, that has gained interest in recent years, is the use of anode-free lithium-metal batteries (AFLMB). Such battery configuration enables elimination of the problem of using excessive amounts of lithium in LMBs, hence increasing the specific energy of the battery. In this work we studied the effect of adding nanoscale ceramic oxides in carbonate-based electrolytes on the cycling performance of the cell and on its anodic SEI properties. The oxides studied were Al2O3, TiO2 and SiO2. It was found that the nanoparticle oxide additives significantly improve the coulombic efficiency (CE) and the capacity retention (CR). TiO2 and Al2O3 presented typical performance with CE of 99.4% and 98.8% and CR of 70% after 36 and 39 cycles, respectively. XPS and EIS measurements were also conducted and showed the superiority of the addition of nanoparticle oxides.
Clean and Reproducible Voltammetry of Copper Single Crystals with Prominent Facet-Specific Features Using Induction Annealing
Authors: Raaijman Stefan J. , Arulmozhi Nakkiran , da Silva Alisson H. M. , Koper Marc T. M.
Published: September 2021

Although copper is widely used as an electrocatalyst for the CO2 reduction reaction, often little emphasis is placed on identifying exactly the facet distribution of the copper surface. Furthermore, because of differing surface preparation methodologies, reported characaterization voltammograms (where applicable) often vary significantly between laboratories, even for surfaces of supposedly the same orientation. In this work, we describe a surface preparation methodology involving the combination of induction annealing and well-documented electrochemical steps, by which reproducible voltammetry for copper surfaces of different orientations can be obtained. Specifically, we investigated copper surfaces of the three principal orientations: {111}, {100} and {110}, and a representative polycrystalline surface. We compared these surfaces to surfaces reported in the literature prepared via either electropolishing or UHV-standard methodologies, where we find induction preparation to yield improvements in surface quality with respect to electropolished surfaces, though not quite as good as those obtained by UHV-preparation.
Protein biomarkers in breast cancer-derived extracellular vesicles for use in liquid biopsies
Authors: Li Dan , Lai Wenjia , Fan Di , Fang Qiaojun
Published: September 2021

Breast cancer is the most common malignant disease in women worldwide. Early diagnosis and treatment can greatly improve the management of breast cancer. Liquid biopsies are becoming convenient detection methods for diagnosing and monitoring breast cancer due to their noninvasiveness and ability to provide real-time feedback. A range of liquid biopsy markers, including circulating tumor proteins, circulating tumor cells, and circulating tumor nucleic acids, have been implemented for breast cancer diagnosis and prognosis, with each having its own advantages and limitations. Circulating extracellular vesicles are messengers of intercellular communication that are packed with information from mother cells and are found in a wide variety of bodily fluids; thus, they are emerging as ideal candidates for liquid biopsy biomarkers. In this review, we summarize extracellular vesicle protein markers that can be potentially used for the early diagnosis and prognosis of breast cancer or determining its specific subtypes.
In the balance: how do thrombospondins contribute to the cellular pathophysiology of cardiovascular disease?
Authors: Forbes Tessa , Pauza Audrys G. , Adams Josephine C.
Published: September 2021

Thrombospondins (TSPs) are multidomain, secreted proteins that associate with cell surfaces and extracellular matrix. In mammals, there is a large body of data on functional roles of various TSP family members in cardiovascular disease (CVD), including stroke, cardiac remodeling and fibrosis, atherosclerosis, and aortic aneurysms. Coding single nucleotide polymorphisms (SNPs) of TSP1 or TSP4 are also associated with increased risk of several forms of CVD. Whereas interactions and functional effects of TSPs on a variety of cell types have been studied extensively, the molecular and cellular basis for the differential effects of the SNPs remains under investigation. Here, we provide an integrative review on TSPs, their roles in CVD and cardiovascular cell physiology, and known properties and mechanisms of TSP SNPs relevant to CVD. In considering recent expansions to knowledge of the fundamental cellular roles and mechanisms of TSPs, as well as the effects of wild-type and variant TSPs on cells of the cardiovascular system, we aim to highlight knowledge gaps and areas for future research or of translational potential.
Vibration decreases the responsiveness of Ia afferents and spinal motoneurons in humans
Authors: Nito Mitsuhiro , Yoshimoto Takuya , Hashizume Wataru , Shindo Masaomi , Naito Akira
Published: September 2021

Vibration decreased the responsiveness of Ia afferents from the muscle exposed to vibration, and the duration of depressive effect was modulated by the duration and frequency of the vibration: a longer duration and a higher frequency of vibration led to a longer recovery time of the depression. In addition to this presynaptic effect, it also depressed the responsiveness of spinal motoneurons, indicating postsynaptic inhibition through specific circuits triggered by Ia impulses.
Study on the Seismic Effect of the Interbedded Soil Layer in the Yinchuan Alluvial Plain
Authors: Yang Shun , Han Xin , Lei Qiyun , Yu Sihan , Liu Chao
Published: September 2021

This paper presents a numerical analysis of two types of representative site profiles in the Yinchuan Plain under earthquake loading. The analyzed soil profiles, based on borehole investigations performed over the years, are used to explore the seismic response of the sites in this area. In total, eleven stratified soil models are used in this study, which can be grouped into two categories: a single interbedded soil model and multiple interbedded soil model. A one‐dimensional equivalent linearization method is applied to evaluate the seismic response of different soil models under four exceeding probabilities in terms of peak ground acceleration (PGA), peak ground velocity (PGV), peak ground displacement (PGD), and spectral acceleration (Sa). The results show that the significant amplification effect of PGA occurs in rare and extremely rare earthquakes, with an amplification ratio of 1.4∼1.7 when the single silty clay layer is located at the model ground. In this scenario, the spectral acceleration is amplified at a period of approximately 1.0 s. For the multilayered soil cases, the amplification effect tends to decrease, whereas the characteristic periods increase with increasing numbers of soil layers and the ground acceleration is deamplified under a high motion intensity when the number of soil layers is ≥ 5. This study, to a certain degree, has reference value for seismic microzonation in this area.
Measurement of Coordinated and Coupled Development and Evaluation of Sustainable Development for Marine Economic-Ecological Complex System
Authors: Wen Mingming , Liu Chang , Mamonov K. A. , Du Jun
Published: September 2021

The development of marine economy has stimulated the need for marine natural products and services, as well as the demand and utilization intensity of marine resources. As a result, the coastal regions start to discharge more and more pollutants, posing a serious threat to marine ecoenvironment. Because of the interactions between marine economy and marine ecology, it is of practical significance to study the marine economic-ecological complex system (MEECS). However, the relevant studies have several common defects: the incomplete data statistics system, the limited attention on development law or action mechanism, and the lack of long-term quantitative and empirical analysis. To overcome these defects, this paper tries to measure the coordinated and coupled development (CCD) and evaluate the sustainable development of MEECS. Specifically, an ecology-dominated coordinated development model was proposed for the complex system, and a differential equation model was established to describe the dynamic coordinated development of the complex system. Through data envelopment analysis (DEA), the sustainable development of the complex system was evaluated based on its input-output efficiency. Through experiments, the outputs of decision-making units (DMUs) of our model were obtained, and the development of the subsystems in MEECS was evaluated comprehensively to verify the effectiveness of our algorithm.
Effect of the Fund Policy in a Remanufacturing System considering Ecodesign and Responsibility Transfer
Authors: Wang Shan , Chang Xiang-Yun , Huang Xin
Published: September 2021

This paper aims to evaluate the effectiveness of the fund policy on ecodesign and manufacturing/remanufacturing activities and the effectiveness of the manufacturer’s ecodesign responsibility transfer strategy. It considers a manufacturing and remanufacturing system composed of a single manufacturer and a single remanufacturer performing under relevant fund policy. The fund policy is innovatively designed by considering three dimensions: tax, reduction, and subsidy. Based on mathematical models and comparative analysis, the principal results show the following: (1) the impact scope of either the tax or the reduction dimension of the fund policy is larger than that of subsidy. The subsidy for encouraging remanufacturing is effective only when the remanufacturer uses some of the collected returns for remanufacturing. (2) The impact direction of tax, reduction, or subsidy is complicated, changing when the remanufacturer uses some of the collected returns for remanufacturing. (3) The responsibility transfer behavior of the manufacturer does not change the impact scope of the fund policy, but changes its impact strength and impact path. The impact of the responsibility transfer strategy on enterprises’ decision-making varies with different remanufacturing scenarios.
Ezetimibe Improves Rosuvastatin Effects on Inflammation and Vascular Endothelial Function in Acute Coronary Syndrome Patients Undergoing PCI
Authors: Sun Changqing , Zheng Wuyang , Liang Ling , Liu Zuheng , Sun Wenchao , Tang Rong
Published: September 2021

Background. Little is known of the acute effects of ezetimibe in patients with acute coronary syndrome (ACS) undergoing PCI. We investigated whether ezetimibe improves inflammation and vascular endothelial function in patients with ACS undergoing PCI. Methods. We randomized 171 patients with ACS undergoing PCI to receive ezetimibe 10 mg/day plus rosuvastatin 20 mg/day (combination group, n = 81) versus rosuvastatin 20 mg/day (rosuvastatin group, n = 90). Lipid profile, type II secretory phospholipase A2 (sPLA2-IIa), interleukin-1β (IL-1β), vascular cell adhesion molecule-1 (VCAM-1), and intercellular cell adhesion molecule-1 (ICAM-1) were measured at baseline and after 7 days. Three months after PCI, clinical outcomes were examined. Result. The levels of sPLA2-IIa and IL-1β reduced significantly in both groups, but more when ezetimibe and rosuvastatin were coadministered (sPLA2-IIa: 6.16 ± 2.67 vs. 7.42 ± 3.53 ng/ml,

p
=
0.01

; IL-1β: 37.39 ± 26.25 vs. 48.98 ± 32.26 pg/ml,

p
=
0.01

). A significant rise of VCAM-1 and ICAM-1 was observed on day 7 after PCI in the both groups, but was less in the combination group (VCAM-1: 918.28 ± 235.31 vs. 988.54 ± 194.41 ng/ml,

p
=
0.03

; ICAM-1: 213.01 ± 100.15 vs. 246.88 ± 105.71 ng/ml,

p
=
0.03

). Patients in the combination versus rosuvastatin group appeared to suffer from less major adverse events. Periprocedural therapy of ezetimibe improves rosuvastatin effects on proinflammatory responses and endothelial function associated with ACS patients undergoing PCI. This trial is registered with https://clinicaltrials.gov/ct2/show/ChiCTR-IPR-17012219 (Chinese Clinical Trial Registry, http://www.chictr.org.cn on 02/08/2017).
On the Multiplicity of a Proportionally Modular Numerical Semigroup
Authors: Gu Ze
Published: September 2021

A proportionally modular numerical semigroup is the set

S

a
,
b
,
c

of nonnegative integer solutions to a Diophantine inequality of the form

a
x
 
mod
 
b
≤
c
x

, where

a
,
b

, and

c

are positive integers. A formula for the multiplicity of

S

a
,
b
,
c

, that is,

m

S

a
,
b
,
c

=

k
b

/
a

for some positive integer

k

, is given by A. Moscariello. In this paper, we give a new proof of the formula and determine a better bound for

k

. Furthermore, we obtain

k
=
1

for various cases and a formula for the number of the triples

a
,
b
,
c

such that

k
≠
1

when the number

a
−
c

is fixed.
Cyperusspp.: A Review on Phytochemical Composition, Biological Activity, and Health‐Promoting Effects
Authors: Taheri Yasaman , Herrera-Bravo Jesús , Huala Luis , Salazar Luis A. , Sharifi-Rad Javad , Akram Muhammad , Shahzad Khuram , Melgar-Lalanne Guiomar , Baghalpour Navid , Tamimi Katayoun , Mahroo-Bakhtiyari Javad , Kregiel Dorota , Dey Abhijit , Kumar Manoj , Suleria Hafiz Ansar Rasul , Cruz-Martins Natália , Cho William C.
Published: September 2021

Cyperaceae are a plant family of grass‐like monocots, comprising 5600 species with a cosmopolitan distribution in temperate and tropical regions. Phytochemically,Cyperusis one of the most promising health supplementing genera of the Cyperaceae family, housing ≈950 species, withCyperus rotundusL. being the most reported species in pharmacological studies. The traditional uses ofCyperusspp. have been reported against various diseases,viz., gastrointestinal and respiratory affections, blood disorders, menstrual irregularities, and inflammatory diseases.Cyperusspp. are known to contain a plethora of bioactive compounds such asα‐cyperone,α‐corymbolol,α‐pinene, caryophyllene oxide, cyperotundone, germacrene D, mustakone, and zierone, which impart pharmacological properties to its extract. Therefore,Cyperussp. extracts were preclinically studied and reported to possess antioxidant, anti‐inflammatory, antimicrobial, anticancer, neuroprotective, antidepressive, antiarthritic, antiobesity, vasodilator, spasmolytic, bronchodilator, and estrogenic biofunctionalities. Nonetheless, conclusive evidence is still sparse regarding its clinical applications on human diseases. Further studies focused on toxicity data and risk assessment are needed to elucidate its safe and effective application. Moreover, detailed structure‐activity studies also need time to explore the candidature ofCyperus‐derived phytochemicals as upcoming drugs in pharmaceuticals.
Chinese Herbal Medicine Formula Guizhi Li-Zhong Tang as an Alternative to Antibiotic Feed Additives for Preventing Pneumonia in Piglets through Antioxidant, Anti-Inflammatory, and Antiapoptotic Protection
Authors: Wang Che-Hsuan , Wu Wan-Jhen , Su Li-Yu , Lu Chen-Wen , Wang Pei-Hwa , Lee Ming-Chung , Chuang Wu-Chang , Wang Sheue-Er , Wu Chung-Hsin
Published: September 2021

Weanling piglets often develop respiratory diseases such as pneumonia because they encounter substantial environmental stress. This study investigated an alternative herbal feed additive, Guizhi Li-Zhong Tang (GLZ), for preventing pneumonia in weanling piglets. An in vitro experiment demonstrated that GLZ has high antioxidant capacity and low cytotoxicity toward Kupffer cells. In addition, GLZ treatment can alleviate lipopolysaccharide (LPS)-induced damage in Kupffer cells. A total of 94 4-week-old piglets were randomly divided into three groups, which received sham treatment, 0.2% Tilmicosin antibiotic (TAB) treatment, or 0.2% GLZ treatment. Piglets receiving the GLZ treatment had a higher survival rate and higher immunoglobulin G levels but lower allergy-related eosinophil levels and cough incidence than did piglets receiving the sham or 0.2% TAB treatments. Through immunohistochemistry and Western blot analysis, we discovered that piglets receiving the 0.2% GLZ treatment had significantly higher expression of antioxidant-related SOD2 and lower expression of oxidative-stress-related 3-NT (

p
<
0.01

), inflammation-related TNF-α (

p
<
0.01

) and NF-κB (

p
<
0.05

), and apoptosis-related caspase-3 (

p
<
0.01

) in lung tissue than did piglets receiving the sham or 0.2% TAB treatment. Therefore, GLZ treatment is promising as an alternative to antibiotic medicine for weanling piglets because of its protective antioxidative, anti-inflammatory, and antiapoptotic effects in lung tissue.
A Magnetoelectric Hybrid Hydraulic Damper for the Mining Robot Suspension System
Authors: Hu Kun , Li Fei , Zhang Zhiyuan , Wang Shuang , Jiang Hao
Published: September 2021

In order to improve the damping and controllability of the mining robot suspension system, a new magnetoelectric hybrid suspension hydraulic damper, which is a semiactive suspension damper, is proposed based on the traditional hydraulic damper by introducing the magnetic‐electric hybrid suspension structure. The structure and working principle of the damper are introduced, respectively, and the mathematical models of the equivalent stiffness and equivalent damping of the system are calculated by the magnetic circuit method and the oil circuit method, while AMESim/Simulink cosimulation is carried out. In order to test the damping performance, a prototype of the magnetoelectric hybrid suspension hydraulic damper was fabricated. The results show that the vibration displacement amplitude can be reduced by 20% and the vibration acceleration amplitude can be reduced by 10% by adjusting the stiffness and damping of the system due to the magnetoelectric hybrid suspension structure. Moreover, the experimental results are consistent with the simulation results, which verify the effectiveness and superiority of this type of damper.
A Case Study on the Gas Drainage Optimization Based on the Effective Borehole Spacing in Sima Coal Mine
Authors: Ji Ming , Sun Zhong-guang , Sun Wei
Published: September 2021

Based on the dynamic expressions of permeability and porosity of the coal seam derived in the paper, a multiphysical field coupling numerical model of gas migration under the interaction of stress field and seepage field was established. The gas drainage project #3 Coal Seam operated by Sima Coal Industry Co., Ltd., was selected as the study object. Taking different drainage time periods in various positions of drainage holes into consideration, combined with the advance situation of the 1207 working face in the Sima Coal Mine, a mixed layout gas drainage scheme featured with the effective borehole spacing was obtained through the COMSOL multiphysics simulation. In addition, a series of field industrial tests were performed to validate the research result, revealing that comprehensively considering the extraction time of coal and optimizing the layout of extraction boreholes can effectively improve the engineering economic benefits.
Changes in Methylation Patterns of Tumor Suppressor Genes during Extended Human Embryonic Stem Cell Cultures
Authors: Kang Kyung Min , Lee Jeoung Eun , Park Ji Eun , Kim Hyunjin , Jang Hee Yeon , Go Minyeon , Lee Dong Ryul , Shim Sung Han
Published: September 2021

While studies on embryonic stem cells have been actively conducted, little is known about the epigenetic mechanisms in human embryonic stem cells (hESCs) in extended culture systems. Here, we investigated whether CpG island (CGI) methylation patterns of 24 tumor suppressor genes could be maintained during extended hESC cultures. In total, 10 hESC lines were analyzed. For each cell line, genomic DNA was extracted from early and late passages of cell cultures. CGI methylation levels of 24 tumor suppressor genes were analyzed using methylation-specific multiplex ligation-dependent probe amplification (MS-MLPA), pyrosequencing, and real-time polymerase chain reaction (PCR). Different CGI methylation patterns of CASP8, FHIT, and CHFR genes were identified in between early and late passages in some hESC lines. CGI methylation levels of CASP8 significantly increased at late passage in CHA-36, CHA-40, and CHA-42 cell lines compared to those at early passage. The CGI methylation of the FHIT gene was higher at late passage than at early passage in CHA-15, CHA-31, CHA-32, and iPS (FS)-1 cell lines but decreased at the late passage in CHA-20 and H1 cell lines. Different CGI methylation patterns were detected for the CHFR gene only in iPS (FS)-1, and the level significantly increased at late passage. Thus, our findings show that CGI methylation patterns could be altered during prolonged ESC cultures and examining these epigenetic changes is important to assess the maintenance, differentiation, and clinical usage of stem cells.
Huganbuzure Granule Attenuates Concanavalin-A-Induced Immune Liver Injury in Mice via Regulating the Balance of Th1/Th2/Th17/Treg Cells and Inhibiting Apoptosis
Authors: Wang Mengheng , Yin Hailong , Xia Yu , Tu Yijun , Zou Xinshuang , Song Wanci , Luo Laichun , Wu Hezhen , Yang Yanfang , Zan Junfeng , Liu Yanwen , Dan Hanxiong , Yin Qiang , You Pengtao
Published: September 2021

In Uygur medicine, Huganbuzure granule (HBG) is one of the classical prescriptions for liver protection. However, its role in immune liver injury remains unknown. This study evaluates the effect of HBG on concanavalin-A- (ConA-) induced immune liver injury and investigates its protective underlying mechanism. BALB/c mice were randomly divided into five groups (n = 24 mice per group): control, ConA, 1.6 g/kg HBG + ConA, 3.2 g/kg HBG + ConA, and 6 mg/kg prednisolone + ConA. HBG was intragastrically administrated once daily for ten consecutive days, prior to ConA (20 mg/kg) injection. The levels of alanine aminotransferase (ALT), aspartate aminotransferase (AST), total bilirubin (TBIL), superoxide dismutase (SOD), and malondialdehyde (MDA) in mouse serum were measured after ConA injection. Moreover, liver-related mRNA levels were evaluated by qPCR. The detection of liver-related proteins was assessed by immunohistochemistry and western blot analysis. Compared with the ConA group, HBG reduced the mRNA expression of IL-17A and IFN-γ and the protein expression of T-bet and ROR-γt. In addition, HBG increased the mRNA expression of IL-4 and TGF-β and protein expression of GATA3 and Foxp3, indicating that HBG regulated the balance of Th1/Th2 and Th17/Treg. Furthermore, HBG alleviated immune liver injury by reducing oxidative stress, inhibiting apoptosis, and decreasing the expression of p-JNK, p-ERK, p-p38, p-JAK1, p-STAT1, p-STAT3, and IRF1. Our data suggested that HBG attenuated ConA-induced immune liver injury by regulating the immune balance and inhibiting JAK1/STATs/IRF1 signaling, thereby reducing apoptosis induced by JNK activation. The findings indicate that HBG may be a promising drug for immune liver injury.
Influence Factors’ Analysis of the Face‐End Roof Leaks Exposed to Repeated Mining Based on Multiple Linear Regression
Authors: Li Qiang , Kong Dezhong , Wu Guiyi , Wen Zhijie , Shang Yuqi
Published: September 2021

In view of the fact that the face‐end roof fall under repeated mining of close‐distance coal seams seriously affects the normal production of the working face, this paper takes working face 17101 as the background, different influencing factors of face‐end roof caving exposed to repeated mining are analyzed through field observation of mine pressure data, different calculation schemes are obtained by using the orthogonal experiment, the subsidence of the face‐end roof is taken as the judgment index, UDEC simulation software is used to calculate the subsidence of the face‐end roof when different influencing factors change, and the application of SPSS statistical software is used for various parameters of multivariate linear regression analysis. The research results show that the influence degree of different factors from large to small is, respectively, mining height > tip‐to‐face distance > advancing speed > distance of coal seams > surrounding rock strength > support setting load. It is necessary to strengthen the coordination of all influencing factors and comprehensively control the stability of the face‐end roof exposed to repeated mining. Through the analysis of the regression model, it is found that there is no collinearity among the influencing factors, which has a significant influence on the regression equation and regression coefficient, and the multiple linear regression equation has a good fitting effect. The model can predict the stability of the face‐end roof exposed to repeated mining, which provides a basis for controlling the face‐end roof exposed to repeated mining.
The Influence of Reservoir Composition on the Pore Structure of Continental Shale: A Case Study from the Qingshankou Formation in the Sanzhao Sag of Northern Songliao Basin, NE China
Authors: Yang Jianguo , Wang Liu , Li Shichao , Zuo Cheng , Xiao Fei , Chen Yuchu , Yao Yulai , Bai Longhui
Published: September 2021

Determining the pore structure characteristics and influencing factors of continental shale reservoir in the oil generation stage is of great significance for evaluating the shale oil reservoir space and analyzing shale oil enrichment mechanism. In this paper, shale from the first member of the Upper Cretaceous Qingshankou Formation (K2qn1) in the Songliao Basin was selected. X-ray diffraction (XRD), Rock-Eval pyrolysis, total organic carbon content (TOC), scanning electron microscopy (SEM), nitrogen gas adsorption (N2GA), and high-pressure mercury injection (HPMI) were used to clarify the composition characteristics of inorganic minerals and organic matter and determine the influencing factors of pore development in the K2qn1 shale. The results show that intergranular pores related to clay minerals and quartz, intragranular dissolution pores related to feldspar, and other mineral intragranular pores are developed. The organic matter pore is less developed, mainly composed of intragranular pores and crack pores of organic matter. Mesopores related to clay minerals are widely developed, rigid quartz particles can protect and support mesopores and macropores, and carbonate cementation can inhibit pore development. Although the TOC contents of shale are commonly less than 2.5%, it has a good positive correlation with porosity; TOC is greater than 2.5%, and the increase of residual oil fills part of the pores, leading to a decrease in porosity with the increase of TOC. Three types (types I, II, and III) of the reservoir space were classified by the combined pore size distribution diagram of N2GA and HPMI. By comparing the characteristics of pore structure parameters, it is found that Type I reservoir space is favorable for shale oil enrichment. It provides scientific guidance for shale oil exploration in the Songliao Basin.
Comparison of Canal Transportation, Separation Rate, and Preparation Time between One Shape and Neoniti (Neolix): An In Vitro CBCT Study
Authors: Kuzekanani Maryam , Sadeghi Faranak , Hatami Nima , Rad Maryam , Darijani Mansoureh , Walsh Laurence James
Published: September 2021

Purpose. This in vitro study compared root canal preparation in curved mesiobuccal canals of molar teeth using either the One Shape™ or the Neoniti (Neolix) rotary NiTi single-file systems, assessing canal transportation, instrument separation and time required for preparation. Methods. Extracted maxillary and mandibular human molar teeth with mesiobuccal canals having apical angles of curvature between 25 and 35o were selected and embedded in acrylic resin blocks, and an initial CBCT was taken. The teeth were divided into two equal groups (n = 20), and the canals were cleaned and shaped using either Neoniti™ or One Shape™ engine-driven NiTi rotary files. Each individual instrument was used to prepare 5 canals. The time required for the preparation of each canal was recorded. Postpreparation CBCT scans were taken and used to determine the extent of canal transportation at levels of 2, 4, 6, and 8 mm from the apex. The Kolmogorov–Smirnov test for normality was applied, and then, datasets were compared using independent t-tests, with a threshold of

P
<
0.05

. Results. Neoniti rotary files caused significantly less canal transportation of the curved canals (

P
=
0.0001

). On the other hand, the time required for canal preparation was significantly shorter for One Shape (

P
=
0.0001

). No instrument separation was recorded in both groups. Conclusion. Based on these results, the Neoniti™ rotary file system is preferred because it maintains the original shape of curved root canals better than One Shape™; even though this benefit comes at the cost of an increase in preparation time in clinical practice, the better technical performance may be more important than a difference in procedural time.