bluuebunny/crossref_metadata_2025 huggingface dataset:
Randomized phase II trial of avelumab alone or in combination with cetuximab for patients with previously treated, locally advanced, or metastatic squamous cell anal carcinoma: the CARACAS study
Authors: Lonardi Sara , Prete Alessandra Anna , Morano Federica , Messina Marco , Formica Vincenzo , Corsi Domenico Cristiano , Orciuolo Corrado , Frassineti Giovanni Luca , Zampino Maria Giulia , Casagrande Mariaelena , Masi Gianluca , Ronzoni Monica , Scartozzi Mario , Buonadonna Angela , Mosconi Stefania , Ratti Margherita , Sartore-Bianchi Andrea , Tamburini Emiliano , Prisciandaro Michele , Bergamo Francesca , Spada Massimiliano , Corallo Salvatore , Vettore Valentina , Loupakis Fotios , Fassan Matteo , Del Bianco Paola , Zagonel Vittorina , Pietrantonio Filippo
Published: November 2021

Background

No standard therapies beyond first line are established for advanced squamous cell anal carcinoma (aSCAC). Earlier preliminary data suggest activity of epidermal growth factor receptor (EGFR) inhibition and programmed cell death ligand (PD-(L))1 blockade in patients with previously treated disease. Aim of this study was to explore activity and safety of avelumab with/without cetuximab in patients with aSCAC.

Methods

In this open-label, non-comparative, ‘pick the winner’, multicenter randomized phase II trial (NCT03944252), patients with aSCAC progressing after one or more lines of treatment were randomized 1:1 to the anti-PD-L1 agent avelumab alone (arm A) or combined with cetuximab (arm B). Overall response rate (ORR) was the primary endpoint. With one-sided α error set at 0.05 and power of 80%, at least 4 responses out of 27 patients per arm had to be observed to declare the study positive. Secondary endpoints were progression free survival (PFS), overall survival (OS), and safety.

Results

Thirty patients per arm were enrolled. Three patients in arm A and five in arm B achieved partial response: primary endpoint was reached in combination arm. ORR was 10% (95% CI 2.1 to 26.5) and 17% (95% CI 5.6 to 34.7) in arms A and B; disease control rate was 50% (95% CI 31.3 to 68.7) in arm A and 57 (95% CI 37.4–74.5) in arm B. At a median follow-up of 26.7 months (IQR 26.5–26.9), median PFS was 2.0 months (95% CI 1.8 to 4.0) in arm A and 3.9 (95% CI 2.1 to 5.6) in arm B. Median OS was 13.9 months (95% CI 7.7 to 19.4) in arm A and 7.8 (95% CI 6.2 to 11.2) in arm B. Acceptable safety profile was observed in both arms.

Conclusions

CARACAS study met its primary endpoint in arm B, documenting promising activity of dual EGFR and PD-L1 blockade in aSCAC.
Selectively targeting myeloid-derived suppressor cells through TRAIL receptor 2 to enhance the efficacy of CAR T cell therapy for treatment of breast cancer
Authors: Nalawade Saisha A , Shafer Paul , Bajgain Pradip , McKenna Mary K , Ali Arushana , Kelly Lauren , Joubert Jarrett , Gottschalk Stephen , Watanabe Norihiro , Leen Ann , Parihar Robin , Vera Valdes Juan Fernando , Hoyos Valentina
Published: November 2021

Background

Successful targeting of solid tumors such as breast cancer (BC) using chimeric antigen receptor (CAR) T cells has proven challenging, largely attributed to the immunosuppressive tumor microenvironment (TME). Myeloid-derived suppressor cells (MDSCs) inhibit CAR T cell function and persistence within the breast TME. To overcome this challenge, we have developed CAR T cells targeting tumor-associated mucin 1 (MUC1) with a novel chimeric costimulatory receptor that targets tumor necrosis factor–related apoptosis-inducing ligand receptor 2 (TR2) expressed on MDSCs.

Methods

The function of the TR2.41BB costimulatory receptor was assessed by exposing non-transduced (NT) and TR2.41BB transduced T cells to recombinant TR2, after which nuclear translocation of NFκB was measured by ELISA and western blot. The cytolytic activity of CAR.MUC1/TR2.41BB T cells was measured in a 5-hour cytotoxicity assay using MUC1+ tumor cells as targets in the presence or absence of MDSCs. In vivo antitumor activity was assessed using MDSC-enriched tumor-bearing mice treated with CAR T cells with or without TR2.41BB.

Results

Nuclear translocation of NFκB in response to recombinant TR2 was detected only in TR2.41BB T cells. The presence of MDSCs diminished the cytotoxic potential of CAR.MUC1 T cells against MUC1+ BC cell lines by 25%. However, TR2.41BB expression on CAR.MUC1 T cells induced MDSC apoptosis, thereby restoring the cytotoxic activity of CAR.MUC1 T cells against MUC1+ BC lines. The presence of MDSCs resulted in an approximately twofold increase in tumor growth due to enhanced angiogenesis and fibroblast accumulation compared with mice with tumor alone. Treatment of these MDSC-enriched tumors with CAR.MUC1.TR2.41BB T cells led to superior tumor cell killing and significant reduction in tumor growth (24.54±8.55 mm3) compared with CAR.MUC1 (469.79±81.46 mm3) or TR2.41BB (434.86±64.25 mm3) T cells alone. CAR.MUC1.TR2.41BB T cells also demonstrated improved T cell proliferation and persistence at the tumor site, thereby preventing metastases. We observed similar results using CAR.HER2.TR2.41BB T cells in a HER2+ BC model.

Conclusions

Our findings demonstrate that CAR T cells that coexpress the TR2.4-1BB receptor exhibit superior antitumor potential against breast tumors containing immunosuppressive and tumor promoting MDSCs, resulting in TME remodeling and improved T cell proliferation at the tumor site.
Gamma delta TCR anti-CD3 bispecific molecules (GABs) as novel immunotherapeutic compounds
Authors: van Diest Eline , Hernández López Patricia , Meringa Angelo D , Vyborova Anna , Karaiskaki Froso , Heijhuurs Sabine , Gumathi Bormin Jan , van Dooremalen Sanne , Nicolasen Mara J T , Gatti Lucrezia C D E , Johanna Inez , Straetemans Trudy , Sebestyén Zsolt , Beringer Dennis X , Kuball Jürgen
Published: November 2021

Background

γ9δ2 T cells hold great promise as cancer therapeutics because of their unique capability of reacting to metabolic changes with tumor cells. However, it has proven very difficult to translate this promise into clinical success.

Methods

In order to better utilize the tumor reactivity of γ9δ2T cells and combine this with the great potential of T cell engager molecules, we developed a novel bispecific molecule by linking the extracellular domains of tumor-reactive γ9δ2TCRs to a CD3-binding moiety, creating gamma delta TCR anti-CD3 bispecific molecules (GABs). GABs were tested in vitro and in vivo for ability to redirect T lymphocytes to a variety of tumor cell lines and primary patient material.

Results

GABs utilizing naturally occurring high affinity γ9δ2TCRs efficiently induced αβT cell mediated phosphoantigen-dependent recognition of tumor cells. Reactivity was substantially modulated by variations in the Vδ2 CDR3-region and the BTN2A1-binding HV4-region between CDR2 and CDR3 of the γ-chain was crucial for functionality. GABs redirected αβT cells against a broad range of hematopoietic and solid tumor cell lines and primary acute myeloid leukemia. Furthermore, they enhanced infiltration of immune cells in a 3D bone marrow niche and left healthy tissues intact, while eradicating primary multiple myeloma cells. Lastly, GABs constructed from natural high affinity γ9δ2TCR sequences significantly reduced tumor growth in vivo in a subcutaneous myeloma xenograft model.

Conclusions

We conclude that GABs allow for the introduction of metabolic targeting of cancer cells to the field of T cell engagers.
Clinical and molecular features of 66 patients with musculocontractural Ehlers−Danlos syndrome caused by pathogenic variants inCHST14(mcEDS-CHST14)
Authors: Minatogawa Mari , Unzaki Ai , Morisaki Hiroko , Syx Delfien , Sonoda Tohru , Janecke Andreas R , Slavotinek Anne , Voermans Nicol C , Lacassie Yves , Mendoza-Londono Roberto , Wierenga Klaas J , Jayakar Parul , Gahl William A , Tifft Cynthia J , Figuera Luis E , Hilhorst-Hofstee Yvonne , Maugeri Alessandra , Ishikawa Ken , Kobayashi Tomoko , Aoki Yoko , Ohura Toshihiro , Kawame Hiroshi , Kono Michihiro , Mochida Kosuke , Tokorodani Chiho , Kikkawa Kiyoshi , Morisaki Takayuki , Kobayashi Tetsuyuki , Nakane Takaya , Kubo Akiharu , Ranells Judith D , Migita Ohsuke , Sobey Glenda , Kaur Anupriya , Ishikawa Masumi , Yamaguchi Tomomi , Matsumoto Naomichi , Malfait Fransiska , Miyake Noriko , Kosho Tomoki
Published: November 2021

Background

Musculocontractural Ehlers−Danlos syndrome is caused by biallelic loss-of-function variants inCHST14(mcEDS-CHST14) orDSE(mcEDS-DSE). Although 48 patients in 33 families with mcEDS-CHST14have been reported, the spectrum of pathogenic variants, accurate prevalence of various manifestations and detailed natural history have not been systematically investigated.

Methods

We collected detailed and comprehensive clinical and molecular information regarding previously reported and newly identified patients with mcEDS-CHST14through international collaborations.

Results

Sixty-six patients in 48 families (33 males/females; 0–59 years), including 18 newly reported patients, were evaluated. Japanese was the predominant ethnicity (27 families), associated with three recurrent variants. No apparent genotype–phenotype correlation was noted. Specific craniofacial (large fontanelle with delayed closure, downslanting palpebral fissures and hypertelorism), skeletal (characteristic finger morphologies, joint hypermobility, multiple congenital contractures, progressive talipes deformities and recurrent joint dislocation), cutaneous (hyperextensibility, fine/acrogeria-like/wrinkling palmar creases and bruisability) and ocular (refractive errors) features were observed in most patients (>90%). Large subcutaneous haematomas, constipation, cryptorchidism, hypotonia and motor developmental delay were also common (>80%). Median ages at the initial episode of dislocation or large subcutaneous haematoma were both 6 years. Nine patients died; their median age was 12 years. Several features, including joint and skin characteristics (hypermobility/extensibility and fragility), were significantly more frequent in patients with mcEDS-CHST14than in eight reported patients with mcEDS-DSE.

Conclusion

This first international collaborative study of mcEDS-CHST14demonstrated that the subtype represents a multisystem disorder with unique set of clinical phenotypes consisting of multiple malformations and progressive fragility-related manifestations; these require lifelong, multidisciplinary healthcare approaches.
Intensified partner notification and repeat testing can improve the effectiveness of screening in reducing Chlamydia trachomatis prevalence: a mathematical modelling study
Authors: Hui Ben B , Hocking Jane S , Braat Sabine , Donovan Basil , Fairley Christopher K , Guy Rebecca , Spark Simone , Yeung Anna , Low Nicola , Regan David
Published: November 2021

Background

The Australian Chlamydia Control Effectiveness Pilot (ACCEPt) was a cluster randomised controlled trial designed to assess the effectiveness of annual chlamydia testing through general practice in Australia. The trial showed that testing rates increased among sexually active men and women aged 16–29 years, but after 3 years the estimated chlamydia prevalence did not differ between intervention and control communities. We developed a mathematical model to estimate the potential longer-term impact of chlamydia testing on prevalence in the general population.

Methods

We developed an individual-based model to simulate the transmission of Chlamydia trachomatis in a heterosexual population, calibrated to ACCEPt data. A proportion of the modelled population were tested for chlamydia and treated annually at coverage achieved in the control and intervention arms of ACCEPt. We estimated the reduction in chlamydia prevalence achieved by increasing retesting and by treating the partners of infected individuals up to 9 years after introduction of the intervention.

Results

Increasing the testing coverage in the general Australian heterosexual population to the level achieved in the ACCEPt intervention arm resulted in reduction in the population-level prevalence of chlamydia from 4.6% to 2.7% in those aged 16–29 years old after 10 years (a relative reduction of 41%). The prevalence reduces to 2.2% if the proportion retested within 4 months of treatment is doubled from the rate achieved in the ACCEPt intervention arm (a relative reduction of 52%), and to 1.9% if the partner treatment rate is increased from 30%, as assumed in the base case, to 50% (a relative reduction of 59%).

Conclusion

A reduction in C. trachomatis prevalence could be achieved if the level of testing as observed in the ACCEPt intervention arm can be maintained at a population level. More substantial reductions can be achieved with intensified case management comprising retesting of those treated and treatment of partners of infected individuals.
The history, etiology, and management of ginseng replant disease: a Canadian perspective in review
Authors: Westerveld Sean M. , Shi Fang
Published: November 2021

Ginseng replant disease (GRD) has had a major impact on the American ginseng (Panax quinquefolius L.) industry in Canada and is a threat to its survival. With only 150 yr of domestic ginseng cultivation, GRD and its effect on the industry in North America is well documented compared with replant diseases in other crops. However, minimal research has been published on the etiology and management of GRD. Research and observations of replant diseases of the major commercial Panax species worldwide are presented to propose mechanisms of GRD and potential management options. The available evidence suggests the specific involvement of the soil-borne fungus Ilyonectria mors-panacis (A.A. Hildebr.) A. Cabral & Crous combined with an unknown host-related factor as the ultimate cause of GRD, since other proposed mechanisms seem unlikely to have occurred in the diversity of regions where GRD is reported. Other abiotic and biotic factors influencing the severity of the disease are also likely to be involved. Given the lack of clarity in the scientific literature between problems associated with continuous cultivation of ginseng and true replant disease, a definition of GRD is proposed. The development of an effective and economical management regime will require a better understanding of the mechanisms of GRD. Potential management options include reducing ginseng debris after harvest of the first crop, preplant testing to identify low-risk sites for replanting, fumigation, alternative disinfestation techniques, and fungicides (including biofungicides) targeting I. mors-panacis.
Some possible Lagrangians for the quadratically damped system
Authors: Chung Won Sang , Hassanabadi Hassan
Published: November 2021

In this paper, some possible Lagrangians for the quadratically damped systems are investigated. The corresponding classical Hamiltonians are investigated with Hamilton equations. The quantum Hamiltonians are also constructed so that they may be Hermitian. As an example, the quantum mechanics for the harmonic oscillator with a small quadratic damping is discussed.
Bouncing universe in a heat bath
Authors: Araújo Filho A. A. , Petrov A. Yu.
Published: November 2021

In this paper, we develop a thermal description for photon modes within the context of bouncing universe. Within this study, we start with a Lorentz-breaking dispersion relation which accounts for modified Friedmann equations with a bounce solution. We calculate the spectral radiance, the entropy, the Helmholtz free energy, the heat capacity and the mean energy. Nevertheless, the latter two ones turn out to contribute only in a trivial manner. Furthermore, one intriguing aspect gives rise to: for some configurations of [Formula: see text], [Formula: see text] and [Formula: see text], the thermodynamical behavior of the system seems to indicate instability. However, despite showing this particularity, the solutions of the thermodynamic functions in general turn out to agree with the literature, e.g. the second law of thermodynamics is maintained. More so, all the results are derived analytically and three different regimes of temperature of the universe are also considered, i.e. the inflationary era, the electroweak epoch and the cosmic microwave background.
Predator–Prey System: Bachelor Herding of the Prey Imposes Ecological Constraints on Predation
Authors: Kaushik Rajat , Banerjee Sandip
Published: November 2021

Bachelor herd behavior is very common among juvenile animals who have not become sexually matured but have left their parent groups. The complex grouping or schooling behavior provides vulnerable juveniles refuge from predation and opportunities for foraging, especially when their parents are not within the area to protect them. In spite of this, juvenile/immature prey may easily become victims because of their greenness while on the other hand, adult prey may be invulnerable to attack due to their tricky manoeuvring abilities to escape from the predators. In this study, we propose a stage-structured predator–prey model, in which predators attack only the bachelor herds of juvenile prey while adult prey save themselves due to small predator–prey size ratio and their fleeing capability, enabling them to avoid confrontation with the predators. Local and global stability analysis on the equilibrium points of the model are performed. Sufficient conditions for uniform permanence and the impermanence are derived. The model exhibits both transcritical as well as Hopf bifurcations and the corresponding numerical simulations are carried out to support the analytical results. Bachelor herding of juvenile prey as well as inaccessibility of adult prey restricts the uncontrolled predation so that prey abundance and predation remain balanced. This investigation on bachelor group defence brings out some unpredictable results, especially close to the zero steady state. Altogether, bachelor herding of the juvenile prey, which causes unconventional behavior near the origin, plays a significant role in establishing uniform permanence conditions, also increases richness of the dynamics in numerical simulations using the bifurcation theory and thereby, shapes ecosystem properties tremendously and may have a large influence on the ecosystem functioning.
Stability and Hopf Bifurcation of a Delayed Mutualistic System
Authors: Zhang Ruimin , Liu Xiaohui , Wei Chunjin
Published: November 2021

In this paper, we study a classic mutualistic relationship between the leaf cutter ants and their fungus garden, establishing a time delay mutualistic system with stage structure. We investigate the stability and Hopf bifurcation by analyzing the distribution of the roots of the associated characteristic equation. By means of the center manifold theory and normal form method, explicit formulae are derived to determine the stability, direction and other properties of bifurcating periodic solutions. Finally, some numerical simulations are carried out for illustrating the theoretical results.
Sliding Dynamics and Bifurcations of a Filippov System with Nonlinear Threshold Control
Authors: Tang Biao , Zhao Wuqiong
Published: November 2021

Considering the effectiveness of introducing the change rate of viral loads into the threshold setting policy for triggering interventions, we propose an immune-virus Filippov system with a nonlinear threshold. By developing new analytical and numerical methods, we systematically studied the rich dynamical behaviors and bifurcations of the proposed system, including the existence of three sliding segments and three pseudo-equilibria, boundary-center bifurcation, boundary-saddle bifurcation, pseudo-saddle-node bifurcation and tangency bifurcation. We further showed that the proposed system can exhibit virous structures in the coexistence of multiple steady states. Phenomena include bistability of two pseudo-equilibria, tristability and multiplestability of two pseudo-equilibria with regular equilibria or touching cycles. The modeling methods, as well as the analytical and numerical methods, can be widely applied to many other fields.
Shock waves in Euler equations for compressible medium
Authors: Liu Tai-Ping
Published: November 2021

Shock waves of arbitrary strength in the Euler equations for compressible media are studied. The admissibility condition for a shock wave is shown to be equivalent to its formation according to the entropy production criterion. The Riemann problem with large data has a unique admissible solutions. These quantitative results are based on the exact global expressions for the basic physical variables as the states move along the Hugoniot and wave curves.
DEVELOPMENT OF LOW-CARBON POWER TECHNOLOGIES AND THE STABILITY OF INTERNATIONAL CLIMATE COOPERATION
Authors: DUSCHA VICKI , KERSTING JAN , PETERSON SONJA , SCHLEICH JOACHIM , WEITZEL MATTHIAS
Published: November 2021

This paper explores the effects of the technological development of key low-carbon power technologies (photovoltaic (PV), wind, and carbon capture and storage (CCS)) on the stability of global climate cooperation under several assumptions about climate-related damage. The methodology combines cooperative game theory with a global computable general equilibrium (CGE) model allowing us to endogenize testing of stability of the global coalition and to include macroeconomic effects. Global cooperation is found to be stable only under mean or pessimistic assumptions about the development of key low-carbon power technologies and when damage is severe. If the technological development is favorable or climate damage is not severe, the gains from global cooperation are not sufficient to compensate for mitigation costs, because a nonglobal coalition of willing countries can then achieve emission reductions close to the global optimum. Finally, our findings support establishing nonglobal ‘climate clubs’ to overcome the lack of global cooperation in international climate policy.
Newly Identified COVID-19 Drug Candidates Based on Computational Strategies
Authors: Azerang Parisa , Yazdani Mohsen , RayatSanati Kimia , Tahghighi Azar
Published: November 2021

The COVID-19 has raised a public health catastrophe in early 2020 worldwide. Despite several approved vaccines that have repressed the pandemic and decreased the mortality rate since then, attempts to discover an effective antiviral drug have not indicated reliable results. In this research, in silico studies (virtual screening and molecular docking) were performed based on quinoline structure to identify novel drug candidates against SARS-CoV-2 before laboratory evaluations. A chemical library consisting of 548 compounds was collected from literature mining of five databases to select the best ligands interacting with three target proteins of SARS-CoV-2, including the main protease, spike protein, and chimeric receptor-binding domain in a complex of human angiotensin-converting enzyme 2. The top five compounds that presented suitable binding energy against each target protein are reported in detail for the first time. Notably, new compound N-4-(6-methyl-3-pyridinyl) phenyl)-9-acridinamine showed high affinity to all selected proteins. These identified compounds will help in speeding up the drug development against COVID-19.
C3PO:

C

loud-based

C

onfidentiality-preserving

C

ontinuous Query

P

r

o

cessing
Authors: Savvides Savvas , Kumar Seema , Stephen Julian James , Eugster Patrick
Published: November 2021

With the advent of the Internet of things (IoT), billions of devices are expected to continuously collect and process sensitive data (e.g., location, personal health factors). Due to the limited computational capacity available on IoT devices, the current de facto model for building IoT applications is to send the gathered data to the cloud for computation. While building private cloud infrastructures for handling large amounts of data streams can be expensive, using low-cost public (untrusted) cloud infrastructures for processing continuous queries including sensitive data leads to strong concerns over data confidentiality.

This article presents C3PO, a confidentiality-preserving, continuous query processing engine, that leverages the public cloud. The key idea is to intelligently utilize partially homomorphic and property-preserving encryption to perform as many computationally intensive operations as possible—without revealing plaintext—in the untrusted cloud. C3PO provides simple abstractions to the developer to hide the complexities of applying complex cryptographic primitives, reasoning about the performance of such primitives, deciding which computations can be executed in an untrusted tier, and optimizing cloud resource usage. An empirical evaluation with several benchmarks and case studies shows the feasibility of our approach. We consider different classes of IoT devices that differ in their computational and memory resources (from a Raspberry Pi 3 to a very small device with a Cortex-M3 microprocessor) and through the use of optimizations, we demonstrate the feasibility of using partially homomorphic and property-preserving encryption on IoT devices.
Formal Modelling and Automated Trade-off Analysis of Enforcement Architectures for Cryptographic Access Control in the Cloud
Authors: Berlato Stefano , Carbone Roberto , Lee Adam J. , Ranise Silvio
Published: November 2021

To facilitate the adoption of cloud by organizations, Cryptographic Access Control (CAC) is the obvious solution to control data sharing among users while preventing partially trusted Cloud Service Providers (CSP) from accessing sensitive data. Indeed, several CAC schemes have been proposed in the literature. Despite their differences, available solutions are based on a common set of entities—e.g., a data storage service or a proxy mediating the access of users to encrypted data—that operate in different (security) domains—e.g., on-premise or the CSP. However, the majority of these CAC schemes assumes a fixed assignment of entities to domains; this has security and usability implications that are not made explicit and can make inappropriate the use of a CAC scheme in certain scenarios with specific trust assumptions and requirements. For instance, assuming that the proxy runs at the premises of the organization avoids the vendor lock-in effect but may give rise to other security concerns (e.g., malicious insiders attackers).

To the best of our knowledge, no previous work considers how to select the best possible architecture (i.e., the assignment of entities to domains) to deploy a CAC scheme for the trust assumptions and requirements of a given scenario. In this article, we propose a methodology to assist administrators in exploring different architectures for the enforcement of CAC schemes in a given scenario. We do this by identifying the possible architectures underlying the CAC schemes available in the literature and formalizing them in simple set theory. This allows us to reduce the problem of selecting the most suitable architectures satisfying a heterogeneous set of trust assumptions and requirements arising from the considered scenario to a decidable Multi-objective Combinatorial Optimization Problem (MOCOP) for which state-of-the-art solvers can be invoked. Finally, we show how we use the capability of solving the MOCOP to build a prototype tool assisting administrators to preliminarily perform a “What-if” analysis to explore the trade-offs among the various architectures and then use available standards and tools (such as TOSCA and Cloudify) for automated deployment in multiple CSPs.
A Unified Perspective for Disinformation Detection and Truth Discovery in Social Sensing: A Survey
Authors: Xu Fan , Sheng Victor S. , Wang Mingwen
Published: November 2021

With the proliferation of social sensing, large amounts of observation are contributed by people or devices. However, these observations contain disinformation. Disinformation can propagate across online social networks at a relatively low cost, but result in a series of major problems in our society. In this survey, we provide a comprehensive overview of disinformation and truth discovery in social sensing under a unified perspective, including basic concepts and the taxonomy of existing methodologies. Furthermore, we summarize the mechanism of disinformation from four different perspectives (i.e., text only, text with image/multi-modal, text with propagation, and fusion models). In addition, we review existing solutions based on these requirements and compare their pros and cons and give a sort of guide to usage based on a detailed lesson learned. To facilitate future studies in this field, we summarize related publicly accessible real-world data sets and open source codes. Last but the most important, we emphasize potential future research topics and challenges in this domain through a deep analysis of most recent methods.
Challenges and Opportunities for Practical and Effective Dynamic Information Flow Tracking
Authors: Brant Christopher , Shrestha Prakash , Mixon-Baca Benjamin , Chen Kejun , Varlioglu Said , Elsayed Nelly , Jin Yier , Crandall Jedidiah , Oliveira Daniela
Published: November 2021

Information flow tracking was proposed more than 40 years ago to address the limitations of access control mechanisms to guarantee the confidentiality and integrity of information flowing within a system, but has not yet been widely applied in practice for security solutions. Here, we survey and systematize literature on dynamic information flow tracking (DIFT) to discover challenges and opportunities to make it practical and effective for security solutions. We focus on common knowledge in the literature and lingering research gaps from two dimensions— (i) the layer of abstraction where DIFT is implemented (software, software/hardware, or hardware) and (ii) the security goal (confidentiality and/or integrity). We observe that two major limitations hinder the practical application of DIFT for on-the-fly security applications: (i) high implementation overhead and (ii) incomplete information flow tracking (low accuracy). We posit, after review of the literature, that addressing these major impedances via hardware parallelism can potentially unleash DIFT’s great potential for systems security, as it can allow security policies to be implemented in a built-in and standardized fashion. Furthermore, we provide recommendations for the next generation of practical and efficient DIFT systems with an eye towards hardware-supported implementations.
Arms Race in Adversarial Malware Detection: A Survey
Authors: Li Deqiang , Li Qianmu , Ye Yanfang (Fanny) , Xu Shouhuai
Published: November 2021

Malicious software (malware) is a major cyber threat that has to be tackled with Machine Learning (ML) techniques because millions of new malware examples are injected into cyberspace on a daily basis. However, ML is vulnerable to attacks known as adversarial examples. In this article, we survey and systematize the field of Adversarial Malware Detection (AMD) through the lens of a unified conceptual framework of assumptions, attacks, defenses, and security properties. This not only leads us to map attacks and defenses to partial order structures, but also allows us to clearly describe the attack-defense arms race in the AMD context. We draw a number of insights, including: knowing the defender’s feature set is critical to the success of transfer attacks; the effectiveness of practical evasion attacks largely depends on the attacker’s freedom in conducting manipulations in the problem space; knowing the attacker’s manipulation set is critical to the defender’s success; and the effectiveness of adversarial training depends on the defender’s capability in identifying the most powerful attack. We also discuss a number of future research directions.
Capturing Dynamics of Information Diffusion in SNS: A Survey of Methodology and Techniques
Authors: Li Huacheng , Xia Chunhe , Wang Tianbo , Wen Sheng , Chen Chao , Xiang Yang
Published: November 2021

Studying information diffusion in SNS (Social Networks Service) has remarkable significance in both academia and industry. Theoretically, it boosts the development of other subjects such as statistics, sociology, and data mining. Practically, diffusion modeling provides fundamental support for many downstream applications (e.g., public opinion monitoring, rumor source identification, and viral marketing). Tremendous efforts have been devoted to this area to understand and quantify information diffusion dynamics. This survey investigates and summarizes the emerging distinguished works in diffusion modeling. We first put forward a unified information diffusion concept in terms of three components: information, user decision, and social vectors, followed by a detailed introduction of the methodologies for diffusion modeling. And then, a new taxonomy adopting hybrid philosophy (i.e., granularity and techniques) is proposed, and we made a series of comparative studies on elementary diffusion models under our taxonomy from the aspects of assumptions, methods, and pros and cons. We further summarized representative diffusion modeling in special scenarios and significant downstream tasks based on these elementary models. Finally, open issues in this field following the methodology of diffusion modeling are discussed.
Artificial Intelligence Security: Threats and Countermeasures
Authors: Hu Yupeng , Kuang Wenxin , Qin Zheng , Li Kenli , Zhang Jiliang , Gao Yansong , Li Wenjia , Li Keqin
Published: November 2021

In recent years, with rapid technological advancement in both computing hardware and algorithm, Artificial Intelligence (AI) has demonstrated significant advantage over human being in a wide range of fields, such as image recognition, education, autonomous vehicles, finance, and medical diagnosis. However, AI-based systems are generally vulnerable to various security threats throughout the whole process, ranging from the initial data collection and preparation to the training, inference, and final deployment. In an AI-based system, the data collection and pre-processing phase are vulnerable to sensor spoofing attacks and scaling attacks, respectively, while the training and inference phases of the model are subject to poisoning attacks and adversarial attacks, respectively. To address these severe security threats against the AI-based systems, in this article, we review the challenges and recent research advances for security issues in AI, so as to depict an overall blueprint for AI security. More specifically, we first take the lifecycle of an AI-based system as a guide to introduce the security threats that emerge at each stage, which is followed by a detailed summary for corresponding countermeasures. Finally, some of the future challenges and opportunities for the security issues in AI will also be discussed.
Understanding Hydrophobic Effects: Insights from Water Density Fluctuations
Authors: Rego Nicholas B. , Patel Amish J.
Published: November 2021

The aversion of hydrophobic solutes for water drives diverse interactions and assemblies across materials science, biology, and beyond. Here, we review the theoretical, computational, and experimental developments that underpin a contemporary understanding of hydrophobic effects. We discuss how an understanding of density fluctuations in bulk water can shed light on the fundamental differences in the hydration of molecular and macroscopic solutes; these differences, in turn, explain why hydrophobic interactions become stronger upon increasing temperature. We also illustrate the sensitive dependence of surface hydrophobicity on the chemical and topographical patterns the surface displays, which makes the use of approximate approaches for estimating hydrophobicity particularly challenging. Importantly, the hydrophobicity of complex surfaces, such as those of proteins, which display nanoscale heterogeneity, can nevertheless be characterized using interfacial water density fluctuations; such a characterization also informs protein regions that mediate their interactions. Finally, we build upon an understanding of hydrophobic hydration and the ability to characterize hydrophobicity to inform the context-dependent thermodynamic forces that drive hydrophobic interactions and the desolvation barriers that impede them.
Polycrystal CuO Curved Nanowires with Photocatalytic Antibacterial for Highly Sensitive Photoelectrochemical Detection of Ultralow-Concentration Ethanol in Solution
Authors: Liang Xu , Han Lu , Gong Pengwei , Zhu Sicong , Huang Ruibin , Chen Rongsheng , Ni Hongwei , Zhan Weiting
Published: November 2021

The polycrystal CuO curved nanowires on Cu mesh were synthesized by a facile alkalization method. This visible light-driven CuO curved nanowires were observed to have highly sensitivity for non-enzymatic ethanol sensing in solution and fast antibacterial property under flashlight irradiation. In order to reveal the mechanism of polycrystal CuO curved nanowires, the comparison between polycrystal CuO nanowires and single-crystal CuO nanowires were investigated based on the analysis of the morphology, nanostructure, theoretical modeling and photoelectrochemical performance. As a result, the highest photocurrent densities were obtained by polycrystal CuO curved nanowires, as the facet heterojunction in curved nanowires played a key role, which existed in the interface between facets CuO (111) and CuO (110) resulting in the effectively separation of photoelectron-holes, thereby increasing of the charge carrier density. Herein, the CuO curved nanowires were assembled as a photoelectrochemical sensor to detect the low concentration ethanol ranging from 10 to 100 nM, and then showed a highly sensitivity. The fast antibacterial performance of CuO curved nanowires was found to completely kill 107 CFU ml−1
E. coli under flashlight irradiation in 20 min. The proposed CuO curved nanowires electrode with self-cleaning performance can be ideal for monitoring the low concentration ethanol in real-time at room temperature as photoelectrodes.
On the Zr Electrochemical Conversion of Additively Manufactured AlSi10Mg: The Role of the Microstructure
Authors: Revilla Reynier I. , Rybin Clara A. , De Graeve Iris
Published: November 2021

Additively manufactured (AM) AlSi10Mg is one of the most studied AM aluminium alloys to date. While several studies have focused on investigating its mechanical properties and corrosion performance, very little work has been dedicated to study corrosion protection mechanisms and surface treatments applicable for this material. This work presents for the first time an analysis of the mechanism of Zr electrochemical conversion on AM AlSi10Mg parts. A comparison with the conventional cast alloy was also conducted. An analysis of the specimens using SEM/EDS provided interesting insights concerning the effect of the microstructure on the deposition of the Zr conversion layer. This work demonstrates that due to the very fine microstructure and distribution of alloying elements in AM AlSi10Mg, a homogeneous deposition of the Zr conversion layer is promoted. Conversely, the cast alloy is characterized by a very heterogeneous deposition of the Zr conversion layer due to the presence of relatively large Fe-containing intermetallic particles. The influence of the conversion coating on the corrosion performance of these materials was also studied. The results show that while the conversion treatment has no impact on the corrosion resistance of the cast alloy, it greatly improves the passivity of the AM AlSi10Mg samples.
Experimental Research on Axial Compression of Reinforced Concrete Short Circular Columns Strengthened with Prestressed Semicircular Steel Plates
Authors: Ren Zhenhua , Shen Yaqian , Zeng Xiantao , Sun Yuantian
Published: November 2021

According to the statistics of relevant departments, the total area of various existing buildings in China is at least 10 billion m2, of which about one‐third of the houses have reached the design life and the safety reserve is insufficient. It is not economical to demolish these houses and rebuild them, and the benefits of new buildings are far less than those of extending the service life of old buildings through reinforcement. Therefore, reinforcement technology is increasingly indispensable. Currently varying methods for the prestressed reinforcement of concrete columns are developed, but they are generally not practical. Strengthening concrete columns with prestressed semicircular steel plate is a new prestressed strengthening technology. In this article, the experimental study on the axial compression of a reinforced concrete circular section short column strengthened with prestressed semicircular steel plate is carried out by combining experimental and numerical simulation methods, and the calculation formula of the bearing capacity of the reinforced short column is established by finite element analysis.
[Retracted] Macroeconomic Image Analysis and GDP Prediction Based on the Genetic Algorithm Radial Basis Function Neural Network (RBFNN‐GA)
Authors: Zhu Mingxun , Meng Zhigang
Published: November 2021

The prediction of gross domestic product (GDP) is a research hotspot, and its importance is self‐evident. Its complex internal change mechanism also increases the difficulty of analyzing GDP data. The genetic algorithm (GA) is applied to the parameter design of the radial basis function neural network (RBFNN) based on genetic algorithm optimization (RBFNN‐GA). An economic zone GDP image prediction model is proposed, which realizes the optimal design of the center vector, the base width vector of the RBFNN node function, and the weight between the hidden layer and output layer. Based on the GDP data over the years, this paper uses the RBFNN‐GA prediction model to analyze and predict the GDP image and compares the image prediction results. The results show that the genetic algorithm is used to optimize RBFNN, which gives full play to the advantages of the two algorithms. The relative error of the RBFNN‐GA prediction model is only 3.52%. Compared with the prediction results, the prediction accuracy is significantly higher than the ARIMA time series model and GM (1,1) model.
Blockchain Consensus Mechanism Based on Improved Distributed Consistency and Hash Entropy
Authors: Ma Jue
Published: November 2021

To improve the performance for distributed blockchain system, a novel and effective consensus algorithm is designed in this paper. It firstly constructs a more random additive constant through the generation matrix of the error correction code and uses the value of the hash entropy to prove that the constructed hash function can meet the requirements of high throughput and fast consensus in performance. In addition, a distributed consensus coordination service system is used in the blockchain system to realize the synchronization of metadata and ensure the consistency of block data, configuration information, and transaction information. The experiment results show that our proposed strategy can reduce the waste of computing resources, increase the block generation speed, and ensure the fairness of nodes participating in the competition, which is an effective solution to ensure the stable operation of the blockchain system.
[Retracted] Pose Estimation under Visual Sensing Technology and Its Application in Art Design
Authors: Song Bing , Li Meng , Lou Liping
Published: November 2021

The study is aimed at solving the problem of large measurement errors caused by the binocular camera in traditional 3D art design, which leads to inaccurate 3D information of the target. The contour information extraction in the process of human motion pose reconstruction is easily affected by the noise in the image. Therefore, a binocular stereo vision system is built first and it integrates image acquisition, camera calibration, and image processing. The dedistortion method is used to process the image because it can reduce errors. Second, a three‐dimensional human motion pose reconstruction model is implemented, the Gaussian template is used to remove the noise in the image frame, and the change detection template (CDM) is used to solve the problem of background “exposure” and “occlusion.” Finally, simulation experiments are designed to verify the system and model designed. Since the research on the application of pose estimation based on visual sensing technology in art design is still blank, such research has great significance and provides a reference for the research in the field. The literature analysis is used to expound and analyze the application of pose estimation based on visual sensing technology in visual communication design and environmental art design: (1) although the binocular stereo vision system causes some errors in the measurement, the overall error is controlled within 2% and the accuracy is high, which proves that it can be applied to the acquisition of three‐dimensional information of the target in art design; (2) there is a high degree of fitting between the video sequence data created by the three‐dimensional human motion pose reconstruction model designed and the real motion data, which indicates that this method has high accuracy in processing image sequences and the feasibility of applying it to human pose reconstruction in three‐dimensional art design is high; (3) through the analysis of the existing literature, it is found that most of the current visual‐based attitude assessment studies are carried out by using network cameras combined with computers, and the quality of the obtained images is low. The combination of binocular stereo sensor and attitude estimation technology can be applied to the design of advertising, animation, games, and packaging, making the behavior of virtual characters in animation and games more vivid. The combination provides convenience for the collection of environmental spatial information and object attitude information, the formulation of a design scheme, and real‐time monitoring of construction in environmental art design. The purpose of this study is to provide an important theoretical basis for the technical upgrading of art design.
Modelling of Deformation Resistance with Big Data and Its Application in the Prediction of Rolling Force of Thick Plate
Authors: Zhang Shun Hu , Che Li Zhi , Liu Xin Ying
Published: November 2021

The precision of traditional deformation resistance model is limited, which leads to the inaccuracy of the existing rolling force model. In this paper, the back propagation (BP) neural network model was established according to the industrial big data to accurately predict the deformation resistance. Then, a new rolling force model was established by using the BP neural network model. During the establishment of the neural network model, the data set of deformation resistance was established, which was calculated back from the actual rolling force data. Based on the data set after normalization, the BP neural network model of deformation resistance was established through the optimization of algorithm and network structure. It is shown that both the prediction accuracy of the neural network model on the training set and the test set are high, indicating that the generalization ability of the model is strong. The neural network model of the deformation resistance is compared with the theoretical one, and the maximum error is only 3.96%. Furthermore, by comparison with the traditional rolling force model, it is found that the prediction accuracy of the rolling force model imbedding with the present neural network model is improved obviously. The maximum error of the present rolling force model is just 3.86%. The research in this paper provides a new way to improve the prediction accuracy of rolling force model.