bluuebunny/crossref_metadata_2025 huggingface dataset:
Geographical prevalence of family history in patients with axial spondyloarthritis and its association with HLA-B27 in the ASAS-PerSpA study
Authors: Boel Anne , van Lunteren Miranda , López-Medina Clementina , Sieper Joachim , van der Heijde Desirée , van Gaalen Floris A
Published: March 2022

Background

A positive family history (PFH) of spondyloarthritis (SpA) consists of five SpA-related entities, of which a PFH of axial spondyloarthritis (axSpA) is most common in European patients with axSpA. Moreover, a PFH of axSpA is associated with human leucocyte antigen B27 (HLA-B27) positivity in these patients. It is unknown if this holds true in patients with axSpA in other parts of the world.

Objective

To investigate the geographical prevalence of a PFH of SpA and its association with HLA-B27 positivity in patients with axSpA worldwide.

Methods

Cross-sectional analyses included patients from the ASAS peripheral involvement in Spondyloarthritis (PerSpA) study from 24 countries worldwide with an axSpA diagnosis, known HLA-B27 status and family history. Logistic regression models were built to assess the effect of HLA-B27 status on the occurrence of PFH. This was repeated for each of the five SpA entities in a PFH.

Results

Among 2048 patients, axSpA was the most common SpA entity in a PFH in all geographical regions (Asia 28%, Europe and North America 27%, Latin America 20%, Middle East and North Africa 41%). A PFH of axSpA was associated with HLA-B27 positivity in Asia (OR 4.19), Europe and North America (OR 2.09) and Latin America (OR 3.95), but not in the Middle East and North Africa (OR 0.98), which has a lower prevalence of HLA-B27 positivity. A PFH of other SpA entities was less prevalent and not consistently associated with HLA-B27 positivity.

Conclusion

In patients with axSpA worldwide, axSpA was consistently the most common SpA entity in a family history and was associated with HLA-B27 positivity in all geographical regions but one.
IMPACT OF IP PROTECTION ON EXPORT TRADE: EVIDENCE FROM THE ASIA-PACIFIC FTAs
Authors: WANG LIYING , LOU YUAN , GAO XIANXIN
Published: March 2022

As intellectual property (IP) rules increasingly occur in the international trade policies, the change of IP rules in the free trade agreement (FTA) shows the trend of TRIPS-plus, leading the trade friction between countries into fierce IP competition. To clarify how the IP rules influence the export trade structure and to provide theoretical and practical advice for reconstructing free trade rules on international protection of intellectual property rights (IPRs), this study applies gap analysis and gravitation modeling on the 63 FTAs signed by significant economies in the Asia-Pacific region during the year 2000–2018. Finally, we find out that the sealing of the FTA IP rules would increase the proportion of IP-intensive and TM-intensive products in the total export trade. Incredibly pointed, enhancing the protection intensity is more significant for optimizing export trade structure in developed countries than in less developed countries.
Events
Authors: Samarasinghe Dilini
Published: March 2022

This section features information about upcoming events relevant to the readers of AI Matters, including those supported by SIGAI. We would love to hear from you if you are are organizing an event and would be interested in cooperating with SIGAI.For more information about conference support visit sigai.acm.org/activities/requesting sponsorship.html.
Nipping in the bud
Authors: Chakraborty Tanmoy , Masud Sarah
Published: March 2022

Since the proliferation of social media usage, hate speech has become a major crisis. Hateful content can spread quickly and create an environment of distress and hostility. Further, what can be considered hateful is contextual and varies with time. While online hate speech reduces the ability of already marginalised groups to participate in discussion freely, offline hate speech leads to hate crimes and violence against individuals and communities. The multifaceted nature of hate speech and its real-world impact have already piqued the interest of the data mining and machine learning communities. Despite our best efforts, hate speech remains an evasive issue for researchers and practitioners alike. This article presents methodological challenges that hinder building automated hate mitigation systems. These challenges inspired our work in the broader area of combating hateful content on the web. We discuss a series of our proposed solutions to limit the spread of hate speech on social media.
Creating knowledge graphs for geographic data on the web
Authors: Demidova Elena , Dsouza Alishiba , Gottschalk Simon , Tempelmeier Nicolas , Yu Ran
Published: March 2022

Geographic data plays an essential role in various Web, Semantic Web and machine learning applications. OpenStreetMap and knowledge graphs are critical complementary sources of geographic data on the Web. However, data veracity, the lack of integration of geographic and semantic characteristics, and incomplete representations substantially limit the data utility. Verification, enrichment and semantic representation are essential for making geographic data accessible for the Semantic Web and machine learning. This article describes recent approaches we developed to tackle these challenges.
LCSNet: End-to-end Lipreading with Channel-aware Feature Selection
Authors: Xue Feng , Yang Tian , Liu Kang , Hong Zikun , Cao Mingwei , Guo Dan , Hong Richang
Published: March 2022

Lipreading is a task of decoding the movement of the speaker’s lip region into text. In recent years, lipreading methods based on deep neural network have attracted widespread attention, and the accuracy has far surpassed that of experienced human lipreaders. The visual differences in some phonemes are extremely subtle and pose a great challenge to lipreading. Most of the lipreading existing methods do not process the extracted visual features, which mainly suffer from two problems. First, the extracted features contain lot of useless information such as noise caused by differences in speech speed and lip shape, for example. In addition, the extracted features are not abstract enough to distinguish phonemes with similar pronunciation. These problems have a bad effect on the performance of lipreading. To extract features from the lip regions that are more distinguishable and more relevant to the speech content, this article proposes an end-to-end deep neural network-based lipreading model (LCSNet). The proposed model extracts the short-term spatio-temporal features and the motion trajectory features from the lip region in the video clips. The extracted features are filtered by the channel attention module to eliminate the useless features and then used as input to the proposed Selective Feature Fusion Module (SFFM) to extract the high-level abstract features. Afterwards, these features are used as input to the bidirectional GRU network in time order for temporal modeling to obtain the long-term spatio-temporal features. Finally, a Connectionist Temporal Classification (CTC) decoder is used to generate the output text. The experimental results show that the proposed model achieves a 1.0% CER and 2.3% WER on the GRID corpus database, which, respectively, represents an improvement of 52% and 47% compared to LipNet.
Chair's letter
Authors: Carterette Ben
Published: March 2022

Dear IR community,

It is happening again. Conferences that were planning to host in-person events in the first half of 2022 are switching to fully virtual events. WSDM 2022 is the latest to do so, following CHIIR 2022 which made the switch in December. While this is disappointing for all of us that were hoping to travel again, and especially heartbreaking for the conference organizers, it is clearly the right thing to do given lockdowns and travel restrictions being reinstated in countries around the world. We continue to plan for a hybrid SIGIR 2022 with an in-person event in Madrid, taking into account the possibility of COVID-related restrictions that may reduce its size---or force us to cancel altogether.
Game over?
Authors: Medlar Alan , Głowacka Dorota
Published: March 2022

We present a systematic literature review of gamification in information retrieval, identifying 32 peer-reviewed articles spanning a period from 2012 to present day. Our study highlights that, with the exception of crowdsourcing relevance judgments, very few studies have investigated the application of gamification to search systems. Moreover, in articles that we would strictly define as being related to gamification (i.e. not games with a purpose or serious games), a majority did not present any real-world systems, user studies or empirical results. In numerous other fields, gamification has been used to successfully increase user engagement and productivity. We argue that the potential of gamification has been overlooked in information retrieval and, in particular, in interactive search settings. We conclude by discussing experimental obstacles and the potential benefits of evaluating gamification strategies in future interactive search systems.
Report on the 4th international workshop on narrative extraction from texts (Text2Story 2021) at ECIR 2021
Authors: Campos Ricardo , Jorge Alípio M. , Jatowt Adam , Bhatia Sumit , Finlayson Mark , Cordeiro João Paulo , Rocha Conceição , Ribeiro Alexandre , Mansouri Behrooz , Ansah Jeffery , Pasquali Arian
Published: March 2022

The Fourth International Workshop on Narrative Extraction from Texts (Text2Story'21) was held on the April 1

st

, 2021, in conjunction with the 43

rd

European Conference on Information Retrieval (ECIR 2021). Due to the Covid-19 outbreak, the workshop was held online on Zoom platform. During the course of the day, an average of more than 80 attendees had the opportunity to follow-up and discuss the recent advances in extraction and formal representation of narratives. The workshop consisted of two invited keynotes and ten paper presentations. The proceedings of the workshop are available online at http://ceur-ws.org/Vol-2860/

Date
: 1 April, 2021.

Website
: https://text2story21.inesctec.pt/.
Report on the 5th workshop on international and interdisciplinary perspectives on children & recommender and information retrieval systems (KidRec 2021) at IDC 2021
Authors: Fails Jerry Alan , Landoni Monica , Huibers Theo , Pera Maria Soledad
Published: March 2022

We summarize outcomes from the 2021 KidRec Workshop, co-located with the ACM Interaction Design and Children conference. The theme of the 5

th

edition of KidRec was
Search and Recommendation Technology through the Lens of a Teacher.
During the workshop, we discussed why teachers are one of the main stakeholders when designing information retrieval tools for the classroom and how to involve them as part of the research and development process to ensure that the resulting tools are suitable and supportive for learning.

Date
: 27 June, 2021.

Website
: https://kidrec.github.io/.
Report on the 44th international ACM SIGIR conference on research and development in information retrieval (SIGIR 2021)
Authors: Shah Chirag , Suel Torsten , Diaz Fernando , Mitra Bhaskar , Poblete Bárbara , Suleman Hussein , Verberne Suzan
Published: March 2022

ACM SIGIR 2021 conference was organized as a fully online event, with more than 1,000 attendees from dozens of countries, a large technical program, and several activities and initiatives not seen at SIGIR before. This conference report provides some of the important details of how the organizers navigated through changing environments - political, social, and public health - moving the conference from NYC to Montreal and then to online. In addition to that decision process, the report also highlights several new and renewed initiatives around diversity, equity, and inclusion (DEI). Written by the conference General Co-Chairs and the DEI Chairs, this report is meant to inform future conference organizers as well as the SIGIR community at large.

Date
: 15--21 July, 2021.

Website
: http://sigir.org/sigir2021/.
Report on women in IR (WIR 2021) at SIGIR 2021
Authors: Goharian Nazli , Bast Hannah
Published: March 2022

The SIGIR'21 Women in IR event
1
, co-organized by SIGIR WIR co-chairs, Nazli Goharian (US East Coast) and Hannah Bast (Central Europe), took place on July 13-14 and was attended by ~70 participants. Due to Covid-19, SIGIR'21 was held online. To accommodate all the time zones, we organized two sessions (A and B) on the same topics. Session A, which was scheduled at a good time for the US and Europe, was well attended by around 52 participants. Session B, which was aimed for Asia-Pacific, had only around 15 participants, where several already attended the earlier session. The low attendance of Session B caused a significant delay in the start of the session which impacted negatively the session due to the very late / middle of night of the organizers physical location. This year's theme was "
Community Engagement & Influence
" covering two topics: 1. Gender pay disparity and the community feedback and input which were captured via a survey and presented during the session, and 2. A presentation and discussion on the notion of hero culture.

Date
: 13--14 July, 2021.
Report on the 1st workshop on the perspectives on the evaluation of recommender systems (PERSPECTIVES 2021) at RecSys 2021
Authors: Zangerle Eva , Bauer Christine , Said Alan
Published: March 2022

Evaluation is a central step when it comes to developing, optimizing, and deploying recommender systems. The PERSPECTIVES 2021 workshop at the 15th ACM Conference on Recommender Systems brought together academia and industry to critically reflect on the evaluation of recommender systems. The primary goal of the workshop was to capture the current state of evaluation from different, and maybe even diverging or contradictory perspectives.

Date
: 25 and 30 September 2021.

Website
: https://perspectives-ws.github.io/2021/.
Report on the 1st workshop on argumentation knowledge graphs (ArgKG 2021) at AKBC 2021
Authors: Ghosal Tirthankar , Al-Khatib Khalid , Hou Yufang , de Waard Anita , Freitag Dayne
Published: March 2022

The first workshop on Argumentation Knowledge Graphs (ArgKG) was held virtually at the Automated Knowledge Base Construction (AKBC 2021) conference on October 7, 2021. ArgKG @ AKBC 2021 brought together the Computational Argumentation and Knowledge Graphs communities, aiming to promote cross-pollination of ideas and encourage discussions and collaborations between the two communities. This paper describes the workshop and compiles several of its findings and insights.

Date
: 7 October, 2021.

Website
: https://argkg21.argmining.org.
Report on the 15th round of NII testbeds and community for information access research (NTCIR-15)
Authors: Kato Makoto P. , Liu Yiqun , Kando Noriko , Clarke Charles L. A.
Published: March 2022

This is a report on the NTCIR-15 conference held online in December 2020. NTCIR is a sesquiannual research project designed to evaluate various information access technologies, including information retrieval, information recommendation, question answering, natural language processing, etc. 55 active research groups from 22 countries\regions have participated in one or more of the seven tasks in NTCIR-15. This report introduces the highlights of the conference, describes the scope and task designs of the seven tasks organized at NTCIR-15.

Date
: 8--11 December, 2020.

Website
: http://research.nii.ac.jp/ntcir/ntcir-15/.
Supporting search engines with knowledge and context
Authors: Voskarides Nikos
Published: March 2022

Search engines leverage knowledge to improve information access. Such knowledge comes in different forms: unstructured knowledge (e.g., textual documents) and structured knowledge (e.g., relationships between real-world objects and topics). In order to effectively leverage knowledge, search engines should account for context, i.e., information about the user and query. In this thesis, we aim to support search engines in leveraging knowledge while accounting for context.

In the first part of this thesis, we study how to make structured knowledge more accessible to the user when the search engine proactively provides such knowledge as context to enrich search results. As a first task, we study how to retrieve descriptions of knowledge facts from a text corpus. Next, we study how to automatically generate knowledge fact descriptions. And finally, we study how to contextualize knowledge facts, that is, to automatically find facts related to a query fact.

In the second part of this thesis, we study how to improve interactive knowledge gathering. We focus on conversational search, where the user interacts with the search engine to gather knowledge over large unstructured knowledge repositories. We study multi-turn passage retrieval as an instance of conversational search and focus on query resolution, that is, add missing context from the conversation history to the current turn. We model query resolution as a term classification task and propose a method to address it.

In the final part of this thesis, we focus on search engine support for professional writers in the news domain. We study how to support such writers create event-narratives by exploring knowledge from a corpus of news articles. We propose a dataset construction procedure for this task that relies on existing news articles to simulate incomplete narratives and relevant articles. We study the performance of multiple rankers, lexical and semantic, and provide insights into the characteristics of this task.

Awarded by
: University of Amsterdam, Amsterdam, The Netherlands on 5 February 2021.

Supervised by
: Maarten de Rijke.

Available at
: https://hdl.handle.net/11245.1/78187b29-2403-4711-800a-0f92fcb9b15c.
Investigation of Structural and Thermal Properties of Graphene Oxide Reinforced Epoxy Nanocomposites
Authors: Gaur M. S. , Raghav Rajesh Kumar , Sagar Rohan , Tiwari R. K.
Published: March 2022

The nanocomposites thin film was prepared by adding exfoliated GO in epoxy-hardner solution in different weight ratio. We investigate the thermal and surface properties of epoxy-graphene oxide (GO) nanocomposites using differential scanning calorimetry (DSC), fourier transform infrared spectroscopy (FTIR), atomic force microscopy (AFM) and contact angle measurement method. AFM and contact angle results are supporting that graphene oxide provides the best reinforcement in epoxy. AFM is investigated the dispersion of GO and structural morphology of epoxy nanocomposites. The FTIR results show that exfoliated GO of two-dimensional (2D) shape favors the hardening process of the epoxy matrix, increasing its reaction rate by observing an epoxy stretching frequency at 907 cm−1. The GO modified with amino group of epoxy lead to the increase of crosslinking density. FTIR absorption peak in 1700–1500 cm−1 regions is due to amino group. This attributes the significant increase of glass transition temperature of epoxy/GO nanocomposites . The contact angle and surface roughness increases with increase in concentration of GO in epoxy shows roughness induced hydrophobic surface. The solid surface energy was calculated by contact angle favors the good dispersion of GO in epoxy matrix.
Charged Particle Induced Etching and Functionalization of Two-Dimensional Materials
Authors: Elbadawi Christopher , Kianinia Mehran , Bendavid Avi , Lobo Charlene J.
Published: March 2022

Focused electron beam induced deposition and etching (FEBID and FEBIE) are direct-write nanofabrication techniques in which an electron beam is used to achieve nanostructure functionalization, etching or deposition. Either alone or in combination with in situ plasmas, these techniques can also be used to accelerate reactions that occur in ambient environment, with simultaneous high-resolution imaging. Here, we describe our recent work on etching, functionalization and directed assembly of a range of nano- and two-dimensional materials using temperature-dependent FEBIE experiments in an environmental scanning electron microscope (ESEM). As examples of the application of these techniques, we demonstrate processes for assembling arrays of nanodiamonds that can be used as magnetic field sensors, as well as for controlled etching of hexagonal boron nitride (hBN) and black phosphorus (BP).
Pricing Method of the Flexible Bus Service Based on Cumulative Prospect Theory
Authors: Ma Wanjing , Guo Yuhang , An Kun , Wang Lei
Published: March 2022

Pricing directly affects the sustainable development of the flexible bus service. This study proposes a profit maximization model and a social welfare maximization model for the flexible bus operator based on the cumulative prospect theory. Fares and uncertain travel time due to unforeseen detours in serving passengers jointly affect passengers’ mode choice. On the other hand, fares and passengers’ probabilistic choices over the flexible bus jointly determine the profits of the flexible bus company and social welfare. This study explores the relationship between the probability of passengers choosing the flexible bus, trip fares, and uncertain travel time. Serving more passengers indicates more profits, which also results in longer detour time thus decreasing the probability of passengers choosing the flexible bus. Considering the interactive influence among passengers, we further calculate the detour time distribution. Finally, a pricing model is established to compensate for the side effects of the detour. The results show that heterogeneous fares can help the flexible bus company to obtain higher profits but have negligible influence on social welfare. In addition, the development of long-distance services and regulations over the detour time can also help to obtain more profits.
Effect of Extended Lipid Core on the Hemodynamic Parameters: A Fluid-Structure Interaction Approach
Authors: Teymoori Morteza , Sadeghi Mahmood Reza , Rabbani Mohsen , Jahangiri Mehdi
Published: March 2022

Myocardial infarction is one of the leading causes of death in the developed countries. A majority of myocardial infarctions are caused by the rupture of coronary artery plaques. In order to achieve a better understanding of the effect of the extension of the lipid core into the artery wall on the change of flow field and its effect on plaque vulnerability, we have studied the hemodynamic parameters by utilizing a finite element method and taking into account the fluid-structure interaction (FSI). Four groups of stenosis models with different sizes of lipid core were used in the study. The fully developed pulsatile velocity profile of the right coronary artery was used as the inlet boundary condition, and the pressure pulse was applied as the outlet boundary condition. The non-Newtonian Carreau model was used to simulate the non-Newtonian behavior of blood. Results indicate that the extension of the lipid core into the artery wall influences the flow field; subsequently, creates favorable conditions for additional development of the lipid core which can lead to a higher risk of plaque rupture.
On the Nonlinearity of Extended
s
-Type Weighted Nakano Sequence Spaces of Fuzzy Functions with Some Applications
Authors: Bakery Awad A. , Mohamed Elsayed A. E.
Published: March 2022

We have defined and studied the weighted Nakano sequence spaces of fuzzy functions. We have constructed the ideal generated by extended

s

-fuzzy functions and the sequence spaces of fuzzy functions. We present some topological and geometric structures of this class of ideal and multiplication mappings acting on this sequence space of fuzzy functions. Moreover, the existence of Caristi’s fixed point is examined. To show how the work is done, some examples and applications to the existence of solutions for a class of nonlinear summable and matrix equations are also talked about.
Plant-Mediated Green Synthesis of Ag NPs and Their Possible Applications: A Critical Review
Authors: Poudel Darbin Kumar , Niraula Purushottam , Aryal Himal , Budhathoki Biplab , Phuyal Sitaram , Marahatha Rishab , Subedi Kiran
Published: March 2022

The potential applications of Ag NPs are exciting and beneficial in a variety of fields; however, there is less awareness of the new risks posed by inappropriate disposal of Ag NPs. The Ag NPs have medicinal, plasmonic, and catalytic properties. The Ag NPs can be prepared via physical, chemical, or biological routes, and the selection of any specific route depends largely on the end-use. The downside of a physical and chemical approach is that it requires a wide space, high temperature, high temperature for a longer time to preserve the thermal stability of synthesized Ag NPs, and the use of toxic chemicals. Although these methods produce nanoparticles with high purity and well-defined morphology, it is critical to develop cost-effective, energy-efficient, and facile route, such as green synthesis; it suggests the desirable use of renewable resources by avoiding the use of additional solvents and toxic reagents in order to achieve the ultimate goal. However, each method has its pros and cons. The synthesized Ag NPs obtained using the green approach have larger biocompatibility and are less toxic towards the biotic systems. However, identifying the phytoconstituents that are responsible for nanoparticle synthesis is difficult and has been reported as a suitable candidate for biological application. The concentration of the effective bioreducing phytoconstituents plays a crucial role in deciding the morphology of the nanoparticle. Besides these reaction times, temperature, pH, and concentration of silver salt are some of the key factors that determine the morphology. Hence, careful optimization in the methodology is required as different morphologies have different properties and usage. It is due to which the development of methods to prepare nanoparticles effectively using various plant extracts is gaining rapid momentum in recent days. To make sense of what involves in the bioreduction of silver salt and to isolate the secondary metabolites from plants are yet challenging. This review focuses on the contribution of plant-mediated Ag NPs in different applications and their toxicity in the aquatic system.
Autologous Cytokine-Induced Killer Cell Immunotherapy Enhances Chemotherapy Efficacy against Multidrug-Resistant Tuberculosis
Authors: Tang Peijun , Chen Xingnian , Xu Junchi , Hu Yunlong , Ye Zhijian , Wang Xiafang , Xiao Yumei , Shen Xinghua , Zhang Jianping , Feng Yanjun , Shi Cuilin , Yu Xin , Yi Lixian , Chen Xinchun , Lu Binfeng , Xu Ping , Sun Zhongwen , Wu Meiying
Published: March 2022

Objective. Multidrug-resistant tuberculosis (MDR-TB) causes persistent infection and challenges tuberculosis control worldwide. T cell-mediated immunity plays a critical role in controlling Mycobacterium tuberculosis (Mtb) infection, and therefore, enhancing Mtb-specific T cell immune responses represents a promising therapeutic strategy against TB. Cytokine-induced killer (CIK) immunotherapy is based on autologous infusion of in vitro expanded bulk T cells, which include both pathogen-specific and nonspecific T cells from patient peripheral blood mononuclear cells (PBMC) into TB patients. Preclinical mouse studies have shown that the adoptive T cell therapy inhibited Mtb infection. However, the efficacy of CIK immunotherapy in the treatment of MDR-TB infection has not been evaluated in clinical trials. Methods. We performed a retrospective study of MDR-TB patients who received CIK immunotherapy in combination with anti-TB chemotherapy and those who had standard chemotherapy. Results. Our results showed that CIK immunotherapy in combination with anti-TB chemotherapy treatment increased the conversion rate of sputum smear and Mtb culture, alleviated symptoms, improved lesion absorption, and increased recovery. The kinetics of serology and immunology index monitoring data showed good safety profiles for the CIK treatment. Conclusion. Our study has provided strong evidence that CIK immunotherapy in combination with anti-TB chemotherapy is beneficial for MDR-TB patients. A multicenter clinical trial is warranted to evaluate CIK as a new immune therapy for MDR-TB.
Spatiotemporal Analysis of the Proportion of Unimproved Drinking Water Sources in Rural Ethiopia: Evidence from Ethiopian Socioeconomic Surveys (2011 to 2019)
Authors: Kassie Abere Wondimu , Mengistu Sintayehu Workineh
Published: March 2022

Currently, around 36% of the rural Ethiopian population is accessing drinking water from unimproved sources and it is unevenly distributed through time and geographic regions. Therefore, this study aimed to analyze the spatiotemporal patterns of unimproved drinking water sources and identify hotspot areas in rural Ethiopia. Ethiopian Socioeconomic Survey (ESS) data obtained from the Central Statistical Agency were used. It was conducted in four waves from 2011 to 2019. A two‐stage probability sampling design was applied. The sample of enumeration areas and households were taken as the first and second stages of sampling, respectively. A total of 3912, 3775, 3698, and 3115 sample households with complete information on drinking water sources were taken in each wave of ESS data, respectively. Weighted proportions, autocorrelation (Moran’s “I”) statistic, and hotspot analyses were applied to estimate the prevalence, test the presence of clustering, and identify vulnerable areas with unimproved drinking water sources. The STATA version 14, Excel, and ArcGIS 10.6 were used to manage and analyze data. The proportions of households with unimproved drinking water sources were 0.497, 0.385, 0.298, and 0.363 in consecutive waves of ESS data. The results also revealed the existence of geographical and temporal variations of access to drinking water from unimproved sources, and the most recent vulnerable (hotspot) areas in the borders of the West and East Gojjam zones in the western Amhara region, Zone one in southern Afar region, and Liben, Afder, Shebelle, Korahe, and Nobob zones in Somali region were identified. In conclusion, this study reveals significant geographic inequalities in the use of improved drinking water sources. This may be necessary for policies and coverage targeting the most vulnerable regions. The presented map and analytical approaches can provide a mechanism to monitor future reductions in inequality within countries by reflecting resource allocation priorities.
Optimal Charging Scheduling and Management with Bus‐Driver‐Trip Assignment considering Mealtime Windows for an Electric Bus Line
Authors: Jiang Yang , He Tong
Published: March 2022

Compared to a charging scheduling and management problem characterized by predetermined trip assignment, this study takes bus and driver scheduling into account, and mealtime windows must be guaranteed as one of the major labor regulations. A discretized mixed‐integer linear programming (MIPL) model is developed based on a single electric bus route. We aim to obtain fast and high‐quality global solutions for this problem, and the model can be easily executed by bus operators by directly invoking an available optimization solver such as IBM ILOG CPLEX. We test our model on a real round‐trip bus route. Numerical experiments show that CPLEX takes approximately 6 sec to obtain an optimal solution. The model can not only reasonably arrange daily trips for each electric bus and driver but also effectively determine the optimal charging schedule and management for an electric bus line. Besides, we analyze the sensitivity of the key parameters in the model. With the increase in the drivers’ maximum workload, the drivers’ average idle time decreases by approximately 11.25%. The objective value decreases by approximately 38.71% and 40.04% with increases in the battery capacity and fleet size, respectively, and the objective value increases by approximately 30.06% with the decrease in the initial battery driving range. In addition, we compare the effectiveness of our time discretization modeling method in solving the same case study to that from other similar studies, and the validity of our method can be verified by the calculation time. We also compare the computational efficiency of CPLEX in solving the same case study problem with and without implementing valid inequalities, and the computational efficiency of the valid inequality method is greatly improved. Finally, through the testing of a multiline network, the potential application of the model to a large‐scale traffic network is verified.
Secure Data Aggregation Aided by Privacy Preserving in Internet of Things
Authors: Liu X. , Wang X. , Yu K. , Yang X. , Ma W. , Li G. , Zhao X.
Published: March 2022

With the rapid development of Internet of Things (IoT), more and more wireless smart devices are widely deployed in its typical applications. These devices acquire numerous data, and their security transmission is a challenge issue due to the openness and broadcast nature of wireless network. Security data aggregation (SDA) plays a significant role in IoT which can not only protect the data privacy but also reduce the network traffic among smart devices. In this paper, a multiple application SDA (MASDA) mechanism is proposed and it can ensure the data confidentiality without losing the integrity of data transmission. Firstly, we discuss an improved homomorphic message authentication code (iHMAC) which can verify the integrity of sensing data and eliminate the injection of false data. Secondly, a multiple application elliptic curve cryptography mechanism (iECC) is described. We introduce multiple types of data simultaneous encryption into an elliptic curve encryption system. This encryption mechanism aggregates the encrypted sensing data and prevents the sensing from being tampered and leaked in relay nodes. Finally, MASDA is a multiple application mechanism and provide both the confidentiality and integrity compared with other SDA schemes. It fuses the sensing data of different applications in a single data packet, and the base station can recover them one-by-one. The security analysis and the simulation experiments verify that MASDA has better performances in terms of the security, the computation cost, the communication overhead, and the data accuracy.
Metaheuristic Approach to Resolve the Real-World Problem of Binder in Concrete by Synthesizing Natural Iron-Rich Binder System Using Chemical Activation
Authors: Xavier C. S. Belarmin , Rahim A. Abdul
Published: March 2022

This research confirms the metaheuristic way using the novel method of synthesis of inorganic chemical activator binder just by replacing the Al3+ ion to Fe3+ ion by chemical activation in the matrix using Taguchi’s orthogonal array. The laterite soil was made reactive using calcination processes, and the material used was Fe2O3; as a major source, it is then combined with aluminosilicate substances such as low calcium fly ash, and ground granulated blast furnace slag (GGBFS) and Alccofine individually are considered as binder materials, which are activated using alkaline and acid-based chemical activation. Furthermore, the outcomes using Taguchi’s optimization technique with the compressive strength behavior of each chemical inorganic polymer binder to evaluate the best suitable combination of binder with suitable activator are studied, and also, the molarity required for polymerization process is identified using the same. This is found to be the most successful and economical way to solve the real-world problem of binder by preparing the binder system from the natural source and to control the greenhouse effect from the construction industry.
CAD Interior Design Color Transfer Simulation Based on the Topological Information Area Matching Model
Authors: Wang Mingyan
Published: March 2022

With the continuous development of social economy, interior design has gradually become an important content pursued by people, especially the rise of European and American style, industrial style, and other design styles, which have a greater impact on the style of interior design. In view of these needs and limitations, a topological information area matching model is introduced by trial in this study. The relationship of area matching is defined by trial through combining the business analysis flow of interior design, accurately controlling the importance of color transfer, and effectively performing the effective transfer of coloring according to the matching area, to improve the integrity of the color transfer, reduce the influence of the variegation in the color transfer on the result according to the mutually harmonious color method, and significantly improve the mutual harmony of colors. The simulation experiment results show that the topological information area matching model is effective, can ensure the true color of the image color, can be effectively adjusted according to the local matching relationship and color, and can support the simulation of CAD interior design color transfer.
Monitoring Driving in a Monotonous Environment: Classification and Recognition of Driving Fatigue Based on Long Short-Term Memory Network
Authors: Han Hao , Li Kejie , Li Yi
Published: March 2022

The driver is one of the most important factors in road traffic. Monitoring the driver’s driving status can greatly improve the safety and road operation efficiency of urban road traffic in the case of multiple traffic modes. Fatigue has a significant impact on drivers’ safety on the road, particularly while driving in a monotonous environment for a long time. In this study, the eye movement parameters of 36 drivers were collected through the simulation experiment of a driving simulator. The pupil area and percentage of eye closure (PERCLOS) in driving scenes of the expressway and low-grade rural road were combined with the Stanford Sleepiness Scale (SSS) to determine the threshold of fatigue degree in different monotonous driving scenarios. A recognition model of different fatigue degrees of drivers is built based on the deep learning method of a long short-term memory network (LSTM) to detect the varied fatigue degrees of drivers. The result shows that the fatigue degree of drivers increases as driving time increases on both expressways and low-grade rural roads. In the same driving time, the driver felt tired faster on the expressway, and the fatigue degree was significantly higher than that on the country road. The recognition rate of the established fatigue degree recognition model for driver’s awake state, mild fatigue, moderate fatigue, and severe fatigue is 100%, 93.1%, 98.4%, and 100% respectively, and the total recognition rate can reach 97.8%, which is higher than the recognition accuracy of the traditional machine learning approach.
Melatonin Alleviates Neonatal Necrotizing Enterocolitis by Repressing the Activation of the NLRP3 Inflammasome
Authors: Xiong Xiaoyu , Bao Zhongkun , Mi Yanhong , Wang Xinhong , Zhu Jiajun
Published: March 2022

Objective. Necrotizing enterocolitis (NEC) is one of the commonest gastrointestinal critical diseases in newborns. Several researches have proven the efficacy of melatonin (MEL) on NEC, but the latent mechanisms were ambiguous. We designed the current research to evaluate the function and mechanism of MEL on NEC in a neonatal mouse model. Methods. The newborn mice were subjected to formula milk containing LPS and hypoxia to establish a NEC model and also intraperitoneally injected with MEL. During the experiment, all mice were closely monitored and weighed. The effect of MEL on the histopathological injury of the terminal ileum tissues, inflammation, and oxidative stress of serum in NEC mice was examined by hematoxylin-eosin (H&E) staining and ELISA. The effect of MEL on the NOD-like receptor family pyrin domain containing 3 (NLRP3) inflammasome was assessed via quantitative real-time PCR and Western blot. Results. MEL intensified the survival rate and body weight in NEC mice. The H&E staining illustrated that MEL improved the histopathological injury in NEC mice. Moreover, MEL repressed the IL-1β, TNF-α, and MDA levels of serum and enhanced the SOD and GSH-Px levels of serum in NEC mice. We also discovered that MEL attenuated the mRNA and protein levels of NLRP3, Toll-like Receptor 4 (TLR4), NF-κB, and caspase-1 of the terminal ileum tissues in NEC mice. Conclusion. Our research illuminated that MEL attenuated the severity of NEC via weakening the activation of the NLRP3 inflammasome.
Remote Sensing Data Processing of Urban Land Using Based on Artificial Neural Network
Authors: Zhang Han
Published: March 2022

With the rapid development of urbanization, the utilization rate of land has become the focus of attention. Remote sensing technology can provide a large amount of data for the prediction of urban land. It is also a thorny problem to find the correlation between the complex data of land change. The neural network technology has obvious advantages in finding the mapping relationship between high-dimensional and nonlinear data. This paper combines the dynamic changes of urban land and neural network methods to analyze the utilization rate and coverage of urban land in the future. In this paper, the data obtained by remote sensing technology is normalized and clustered to classify different types of urban land. Convolutional neural networks and long-short-term memory neural networks are used to extract the spatial and temporal dynamic characteristics of urban land use. The research results show that the clustering method used in this paper can reasonably classify different urban land types, especially the classification of buildings. The method of predicting the future trend of land use is also in line with the dynamic process of land use. The largest prediction error comes from the prediction of the building, and the largest error is only 2.56%, which is a reasonable error range. The smallest error does not exceed 1%, and the correlation coefficient between the real and predicted values of urban land use types reaches 0.9698.
Analysis of the Spatial Characteristics and Influencing Factors of e‐Commerce Industrial Chains from the Perspective of Embeddedness: Taking Xiong’an New Area in China as an Example
Authors: Gu Yifan , Ding Jianghui
Published: March 2022

e‐commerce has promoted the application of the Internet by traditional enterprises. While this phenomenon has deepened industrial embeddedness, it has also profoundly affected the development of traditional manufacturing and retail industries. Based on the embeddedness theory, this paper takes the e‐commerce industrial chain in Xiong’an New Area of China as an example, uses location entropy method and local spatial autocorrelation to analyze its spatial characteristics and influencing factors, and also discusses the features of embeddedness from each dimension of industrial chains. The results show the following: ① The supply chain of industry‐dependent e‐commerce is dominated by production wholesalers, and suppliers with cost advantages and commercial traditions are embedded in local characteristic industries; the e‐commerce value chain is dominated by production and processing activities, and the spatial orientation of the business model is affected by regional industrial functions; the e‐commerce enterprise chain is dominated by B2B enterprises, the high‐level agglomeration of which reflects the absolute scale advantage provided by the e‐commercialization of traditional industry. ② The distribution of the e‐commerce industrial chains of Xiong’an New Area is characterized by spatial heterogeneity and has obvious spatial agglomeration. The industrial chains are concentrated in Xiong County, followed by Rongcheng County, and Anxin County has the weakest agglomeration. ③ The main factors that cause the uneven distribution of the e‐commerce industrial chains in Xiong’an New Area include three aspects: transportation location advantages, traditional industrial foundation, and government policy regulation. Research can provide a scientific reference for accurately identifying the spatial development characteristics of the industrial chains from various perspectives and promoting the sustainable development and e‐commercialization of traditional industries.
Software Measurement by Using Artificial Intelligence
Authors: Tariq Aliza , Awan Mazhar Javed , Alshudukhi Jalawi , Alam Talha Mahboob , Alhamazani Khalid Twarish , Meraf Zelalem
Published: March 2022

Artificial intelligence (AI) is a subfield of computer science concerned with developing intelligent machines capable of performing tasks similar to those performed by humans. This human‐created intelligence began more than 60 years ago. The goal of previous generations of applications was to demonstrate generic human‐like behaviour. The goal has expanded with the advancement and increased compliance of this technology. It includes areas such as healthcare, gaming, and smart devices. The COVID‐19 epidemic has posed a significant barrier to maintaining a sustainable strategy for mental health support clients with major mental illnesses and clinicians who have had to shift delivery modes quickly. In this study, we have conducted a systematic literature review (SLR) to provide an overview of the current state of the literature related to software measurement of healthcare using artificial intelligence. The study followed a secondary research strategy. The systematic literature review aim was to analyze software measurement of mental health illness in terms of previous literature. This study screened out of 28 research papers out of 1076 initial searches. We used Science Direct, IEEE Xplore, Springer Link, ACM, and Hindawi as database search engines. The research objective was to explore the needs of software applications and automation in the healthcare sector to bring efficiency to the systems. The research concluded that the healthcare setting crucially requires the implementation of software automation.
Accuracy of Estimating Periodontitis and Its Risk Association Using Partial-Mouth Recordings for Surveillance Studies: A Systematic Review and Meta-Analysis
Authors: Alawaji Yasmine N. , Alshammari Abdulsalam , Aleksejuniene Jolanta
Published: March 2022

Objectives. Our aim is to conduct an up-to-date systematic review and meta-analysis pertaining to the accuracy of using the partial-mouth recording protocol (PRP) in surveillance studies to estimate the periodontitis prevalence, extent, severity, and its risk associations. Methods. Medline and Embase databases were searched for studies which assessed the periodontitis prevalence, severity, extent, or its risk associations using PRPs versus full-mouth recording protocols (FRPs); searches were conducted up until May 26, 2021. The risk of bias and the applicability of the studies were assessed using the QUADAS-2 tool. Both qualitative data synthesis and quantitative data synthesis were performed, and comparisons were done for the accuracy and precision of PRPs for different periodontitis outcomes. The study’s protocol was registered through the International Platform of Registered Systematic Review and Meta-analysis Protocols (registration number: INPLASY202160032). Results. A total of 14 studies were included. The studies had a considerable degree of heterogeneity, along with a moderate risk of bias and applicability concerns. Several factors influenced the accuracy or precision of using PRPs, including the age, distribution of periodontitis in the studied population, PRP selection, total PRP sites, the threshold for minimum sites with CAL, and the severity of periodontitis case definitions. Overall, the PRP with the highest accuracy and precision mainly included (1) a full-mouth protocol at the following partial sites: mesiobuccal-midbuccal-distolingual (MB-B-DL), mesiobuccal-distolingual (MB-DL), mesiobuccal-midbuccal-distobuccal (MB-B-DB), mesiobuccal-distobuccal (MB-DB), and 84 sites using the random site selection method (RSSM) and (2) random-half-mouth (RHM) protocols. Conclusions. The PRPs with the highest overall accuracy and precision in estimating the periodontitis prevalence, extent, severity, and risk associations included the full-mouth assessment at the following partial sites: MB-B-DL, MB-DL, MB-B-DB, MB-DB, and 84 sites using RSSM and RHM protocols.