bluuebunny/crossref_metadata_2025 huggingface dataset:
Deep Learning-Based Human Emotion Detection Framework Using Facial Expressions
Authors: Hou Jie
Published: February 2022

Automatic recognition of facial expression is an emerging study in the recognition of emotions. Emotion plays a significant role in understanding people and is usually related to sound decisions, behaviors, human activities, and intellect. The scientific community needs accurate and deployable technologies to understand human beings’ emotional states to establish practical and emotional interactions between human beings and machines. In the paper, a deep learning-based human emotion detection framework (DL-HEDF) has been proposed to evaluate the probability of digital representation, identification, and estimation of feelings. The proposed DL-HEDF analyzes the impact of emotional models on multimodal identification. The paper introduces emerging works that use existing methods like convolutional neural networks (CNN) for human emotion identification based on language, sound, image, video, and physiological signals. The proposed emphasis on the province study illustrates the shape and display of sample size emotional stimulation. While the findings obtained are not a province, the evidence collected indicates that deep learning could be sufficient to classify face emotion. Deep learning can enhance interaction with people because it allows computers to acquire perception by learning characteristics. And by perception, robots can offer better responses, enhancing the user experience dramatically. Six basic emotional levels have been successfully classified. The suggested way of recognizing emotions has then proven effective. The output results are obtained as an analysis of the ratio of the facial expression of 87.16%, accuracy evaluation ratio being 88.7%, improving facial recognition ratio is 84.5%, and the expression intensity ratio is 82.2%. The emotional simulation ratio is 93.0%.
Anycast Service Grooming Algorithm of Cloud Computing Based on Wireless Communication Network
Authors: Wei Hong , Li Zhiyong
Published: February 2022

In order to improve the energy efficiency of optical interconnection network between data centers, a hybrid path transmission energy-saving routing algorithm with service duration awareness is proposed for Anycast service. In order to reduce the number of new optical path and working components, single path transmission is preferred; If the traffic is blocked, the transmission energy consumption is minimized. In addition, the traffic grooming strategy based on spectrum reservation is introduced to reduce the cost of protecting bandwidth and optical transceiver. Simulation results show that: compared with the traditional energy-saving routing algorithm, the proposed algorithm can significantly reduce the network energy consumption, effectively avoid the excessive increase of traffic blocking rate, and achieve the balance of network energy consumption and performance.
A Study on the Development of Design thinking in the Fourth Industrial Revolution — Focused on Micro Manufacturing Space
Authors: Chun Hyunjin
Published: February 2022

Recent advances in technology have accelerated the Fourth Industrial Revolution. With the emergence of artificial intelligence, not only the manufacturing sector but also all sectors of society are expected to undergo changes in the future. In this age of the Fourth Industrial Revolution, it is going to be more important for learners to improve their creativity than to acquire knowledge. So scholars are exploring new ways of teaching to cultivate suitable talent for the future society. Among these various methods of education, Maker Education at Micro Manufacturing Space is recognized as the optimal method for the AI era. This study, in light of this, analyzed the operation of Micro Manufacturing Space, which is located in a university, and further suggested the direction of development of Micro Manufacturing Space in the Fourth Industrial Revolution. The results of this study are as follows. At the university’s Micro Manufacturing Space, students can be trained to think innovatively and improve creativity. In addition, this space can also be used as an open learning and meeting space for university students to visit freely. Moreover, the place can be built for the purpose of a start-up space. Therefore, future Micro Manufacturing Space in universities, as it were, will definitely prove to be a multifunctional space providing support to foster and improve creativity of the main force of the future of society. The findings can be used as theoretical basic data in the creation of a Micro Manufacturing Space for design thingking.
Viscous fluid accelerating model in modified gravity
Authors: Tarai Sankarsan , Ray Pratik P. , Mishra B. , Tripathy S. K.
Published: February 2022

In the framework of extended theory of gravity, an accelerating cosmological model has been presented in this paper in an anisotropic space-time. The extended gravity is considered as [Formula: see text] gravity with the matter field as viscous fluid. The role of viscous coefficient has been discussed on the cosmic expansion issue. In the developed formalism, a variable Hubble parameter has been incorporated to express the dynamical parameter with respect to redshift. The model is observed to be compatible with recent observational data.
Spectral Analysis of Subduction Zone Earthquakes for Coastal Stations and Applications to Stochastic Finite-Fault Simulation Method
Authors: Chen Su , Fu Lei , Dai Zhijun , Chen Shiyang , Li Xiaojun
Published: February 2022

Accelerograms of 58 subduction zone earthquakes recorded by 25 K-NET coastal stations located in Sagami Bay and its adjacent regions were used to analyze the spectral properties of the source, propagation path, and site effects by using the generalized inversion technique. The inverted [Formula: see text] values vary from 1.7[Formula: see text]MPa to 17.4[Formula: see text]MPa, with an average value of 4.89[Formula: see text]MPa and a standard deviation of [Formula: see text]. Although the depths of the selected earthquakes are confined to 30 km, which is similar to those of the crustal earthquakes, this study obtains an average [Formula: see text] which coincides with the plate-boundary earthquakes rather than the crustal earthquakes. It implies that the stress condition of the plate-boundary region varies from the inland crust. The obtained [Formula: see text] is similar to the previous studies. The [Formula: see text] of the selected stations varies from 0.0479[Formula: see text]s to 0.0904[Formula: see text]s, indicating high-frequency attenuation for the coastal area. The inverted site response shows the systematic tendency for different site classes. The amplification levels of class A sites fluctuate around one between 1[Formula: see text]Hz and 10[Formula: see text]Hz. Class B sites indicate peak amplification at the resonant frequency distributed between 3[Formula: see text]Hz and 10[Formula: see text]Hz. Most of the Classes D and E sites have peak amplification below about 4[Formula: see text]Hz. Using the inversion results as the input parameters of the stochastic finite-fault method, an [Formula: see text] subduction zone earthquake was simulated. The resulting response spectra corresponded to the observations and confirmed that the inverted parameters are reasonable.
Multidirectional Linear Site Response Analysis by Applying the SBSR Technique to KiK-net Data
Authors: Shi Yang , He Hong-Jun , Miao Yu
Published: February 2022

Numerous works have highlighted the importance of the site response analysis of vertical ground motion in the earthquake engineering field. However, most studies have focused on nonlinear site response analysis. Hence, the knowledge of the linear site response analysis of vertical ground motion is inadequate. In this study, we perform multidirectional linear site response analysis by applying the surface-to-borehole spectral ratio (SBSR) technique to the Kiban–Kyoshin strong-motion observation network (KiK-net) seismic data. We find the hyperbolic relationships between multiple natural frequencies and the corresponding fundamental frequency. We propose empirical formulas, which can reduce the error in the multiple natural frequencies estimated by a single-layer model. Moreover, a brief investigation is conducted to provide an extra evidence for a previous correction method to the horizontal-to-vertical spectral ratio (HVSR) technique. The results of this study provide the empirical tools and can be utilized as a reference for the multidirectional linear site response analysis based on seismic observations.
Experimental Study on Dynamic Modulus and Damping Ratio of Rubber–Sand Mixtures Over a Wide Strain Range
Authors: Liu Qifei , Zhuang Haiyang , Wu Qi , Zhao Kai , Chen Guoxing
Published: February 2022

This paper systematically investigates the dynamic behavior of sandy soils mixed with recycled tire rubber over a wide strain range in the order of 10[Formula: see text]–10[Formula: see text], using combined resonant column and cyclic triaxial tests for measurement of the shear modulus and damping ratio. The experiment integrates small-strain tests using a resonant column apparatus and large-strain tests using a cyclic triaxial apparatus. The results demonstrated that the addition of rubber particles significantly enhances the linear elastic properties of the host sandy soils and improves the critical shear strain from which the rubber–sand mixtures change from linear to nonlinear stress–strain behavior. The critical shear strain is therefore introduced as the function of rubber content (RC), to identify the influence of RC on the strain-dependent dynamic properties of the host sandy soils. Then, a well-calibrated prediction formula is applied in conjunction with the concept of binary packing material to describe the behavior of the host sandy soils with various RC. Remarkably, the obtained normalized shear modulus and damping ratio vs. shear strain relationships address the limitations of existing testing methods to simultaneously capture the soil dynamic properties at low-strain (stiffness) and the large-strain (energy dissipation) regimes. The model constants can be simply determined through a unique set of explicit expressions which incorporate some basic index properties of the host sand and recycled tire rubber. In this regard, the proposed procedure provides a significant advantage in the evaluation of strain-dependent dynamic properties of rubber–sand mixtures in practice.
A nonlinear optimal control method against the spreading of epidemics
Authors: Rigatos G. , Abbaszadeh M. , Cuccurullo G.
Published: February 2022

To define a vaccination policy and antiviral treatment against the spreading of viral infections a nonlinear optimal (H-infinity) control approach is proposed. Actually, because of the scarcity of the resources for treating infectious diseases in terms of vaccines, antiviral drugs and other medical facilities, there is need to implement optimal control against the epidemics deployment. In this approach, the state-space model of the epidemics dynamics undergoes first approximate linearization around a temporary operating point which is recomputed at each time-step of the control method. The linearization is based on Taylor series expansion and on the computation of the associated Jacobian matrices. Next, an optimal (H-infinity) feedback controller is developed for the approximately linearized model of the epidemics. To compute the controller’s feedback gains an algebraic Riccati equation is solved at each iteration of the control algorithm. Furthermore, the global asymptotic stability properties of the control scheme are proven through Lyapunov stability analysis. This paper’s results confirm that optimal control of the infectious disease dynamics allows for eliminating its spreading while also keeping moderate the consumption of the related medication, that is vaccines and antiviral drugs.
Bipolar disorder diagnosis with cubic bipolar fuzzy information using TOPSIS and ELECTRE-I
Authors: Jamil Nimra , Riaz Muhammad
Published: February 2022

Bipolar disorder ([Formula: see text]) is a neurodegenerative disease that consists of two main manifestations: mania and depression. In the clinical diagnosis of [Formula: see text], there are two primary components. First and foremost is itself [Formula: see text] which is often wrongly diagnosed as unipolar depression in clinical finding. This is so because in clinical diagnosis the first factor is often neglected due to its approach towards positivity. As a result, the element of bipolarity dies down, and the condition worsens. The second disadvantage is that [Formula: see text] is frequently misdiagnosed due to comparable indications and symptoms. To overcome these diagnosis issues, a cubic bipolar fuzzy set (CBFS) which comprises both bipolar fuzzy set (BFS) and interval-valued bipolar fuzzy set (IVBFS) is very helpful for clinical diagnosis of [Formula: see text]. A CBFS has the ability to handle bipolarity with suitable closed intervals to express positive and negative grades to build a solid numerical demonstrating interaction to analyze this disorder effectively. For these objectives, the algorithms of technique for the order of preference by similarity to positive ideal solution (TOPSIS) and elimination and choice translating reality (ELECTRE-I) for multi-criteria decision-making (MCDM) based on CBF information are developed. The application of proposed algorithms is presented for clinical diagnosis of [Formula: see text]. In order to discuss efficiency and validity of the proposed MCDM approaches, we apply the authenticity test for ranking of feasible alternatives and optimal decision by TOPSIS and ELECTRE-I. The comparison analysis of proposed MCDM approaches with existing techniques is also given.
Generalized viscosity approximation method for minimization and fixed point problems of quasi-pseudocontractive mappings in Hadamard spaces
Authors: Abass H. A. , Mebawondu A. A. , Aremu K. O. , Oyewole O. K.
Published: February 2022

In this paper, we introduce a generalized viscosity method which includes a sequence of contractive mappings for approximating solutions of fixed point problem of finitely many resolvents of a lower semi-continuous function together with a fixed point problem of countable infinite family of [Formula: see text]-Lipschitzian and quasi-pseudocontractive mappings in Hadamard spaces. We establish a strong convergence result without imposing a compactness condition of the proposed algorithm to an element in the intersection of the set of solutions of fixed point problem of finitely many resolvents of a lower semi-continuous function and fixed point problem of countable infinite family of quasi-pseudocontractive mappings. We display a numerical example to show the applicability of our main result. Our results complement and extend many recent results in literature.
Virtual outcrop-based analysis of channel and crevasse splay sandstone body architecture in the Middle Jurassic Ravenscar Group, Yorkshire, NE England
Authors: Rahman M. Mostafizur , Howell John A. , Macdonald David I. M.
Published: February 2022

Well-exposed fluvio-deltaic deposits of the Middle Jurassic Ravenscar Group (Yorkshire coast) provide a direct analogue for North Sea reservoirs, but previous studies were restricted to a few accessible bays. This study used lidar and drone photogrammetry to create near-continuous virtual outcrops, 21 km long and 30–150 m thick, in an area which is largely inaccessible. Remote sensing data were supplemented by 45 outcrop logs and data from 27 pre-existing, behind-outcrop boreholes to improve understanding of the geometries, architectures and stacking patterns of 10 distinct sandbody types; the most important reservoir analogue units are channels and crevasse splay bodies. Channel bodies are 30–2038 m wide and 2–28 m thick with
W
/
T
ratio ranges of 5–105; the majority are multi-storey with an average thickness of 8 m and width of 182 m, while the single-storey channel bodies average 4 m thick and 50 m wide. Crevasse splays are 15–>1285 m wide and 0.3–6.5 m thick with
W
/
T
ratio ranges of 50–>541. There is a marked lateral and vertical change in channel body dimensions and facies proportion. The study suggests that the channel architecture and depositional nature of these successions are controlled by base-level fluctuation and floodplain topography.

Supplementary material
: Fieldwork-based sedimentary logs, borehole core-based sedimentary logs with facies proportions, workflow to prepare virtual outcrop, method to estimate true width of sandbody, correlation panel of crevasse splay bodies, interpreted virtual outcrops, and dimensional data of channel, crevasse splay and crevasse channel bodies are available at
https://doi.org/10.6084/m9.figshare.c.5795793
FreeSia: A Cyber-physical System for Cognitive Assessment through Frequency-domain Indoor Locomotion Analysis
Authors: Khodabandehloo Elham , Alimohammadi Abbas , Riboni Daniele
Published: February 2022

Thanks to the seamless integration of sensing, networking, and artificial intelligence, cyber-physical systems promise to improve healthcare by increasing efficiency and reducing costs. Specifically, cyber-physical systems are being increasingly applied in smart-homes to support independent and healthy aging. Due to the growing prevalence of noncommunicable diseases in the senior population, a key application in this domain is the detection of cognitive issues based on sensor data. In this article, we propose a novel cyber-physical system for cognitive assessment in smart-homes. Cognitive evaluation relies on clinical indicators characterizing symptoms of dementia based on the individual’s movement patterns. However, recognizing these patterns in smart-homes is challenging, because movement is constrained by the home layout and obstacles. Since different abnormal patterns are characterized by undulatory-like trajectories, we conjecture that frequency-based locomotion features may more effectively capture these patterns with respect to traditional features in the spatio-temporal domain. Based on this intuition, we introduce novel feature extraction techniques and adopt state-of-the-art machine learning algorithms for short- and long-term cognitive evaluation. Our system includes a user-friendly interface that enables clinicians to inspect the data and predictions. Extensive experiments carried out with a real-world dataset acquired from both cognitively healthy seniors and people with dementia show the superiority of our frequency-based features. Moreover, further experiments with an ensemble method show that prediction accuracy can be enhanced by combining features in the frequency and time domains.
Efficient Out-of-Distribution Detection Using Latent Space of
β
-VAE for Cyber-Physical Systems
Authors: Ramakrishna Shreyas , Rahiminasab Zahra , Karsai Gabor , Easwaran Arvind , Dubey Abhishek
Published: February 2022

Deep Neural Networks are actively being used in the design of autonomous Cyber-Physical Systems (CPSs). The advantage of these models is their ability to handle high-dimensional state-space and learn compact surrogate representations of the operational state spaces. However, the problem is that the sampled observations used for training the model may never cover the entire state space of the physical environment, and as a result, the system will likely operate in conditions that do not belong to the training distribution. These conditions that do not belong to training distribution are referred to as Out-of-Distribution (OOD). Detecting OOD conditions at runtime is critical for the safety of CPS. In addition, it is also desirable to identify the context or the feature(s) that are the source of OOD to select an appropriate control action to mitigate the consequences that may arise because of the OOD condition. In this article, we study this problem as a multi-labeled time series OOD detection problem over images, where the OOD is defined both sequentially across short time windows (change points) as well as across the training data distribution. A common approach to solving this problem is the use of multi-chained one-class classifiers. However, this approach is expensive for CPSs that have limited computational resources and require short inference times. Our contribution is an approach to design and train a single
β
-Variational Autoencoder detector with a partially disentangled latent space sensitive to variations in image features. We use the feature sensitive latent variables in the latent space to detect OOD images and identify the most likely feature(s) responsible for the OOD. We demonstrate our approach using an Autonomous Vehicle in the CARLA simulator and a real-world automotive dataset called nuImages.
Quick-Div: Rethinking Integer Divider Design for FPGA-based Soft-processors
Authors: Matthews Eric , Lu Alec , Fang Zhenman , Shannon Lesley
Published: February 2022

In today’s FPGA-based soft-processors, one of the slowest instructions is integer division. Compared to the low single-digit latency of other arithmetic operations, the fixed 32-cycle latency of radix-2 division is substantially longer. Given that today’s soft-processors typically only implement
radix-2
division—if they support hardware division at all—there is significant potential to improve the performance of integer dividers.

In this work, we present a set of high-performance, data-dependent, variable-latency integer dividers for FPGA-based soft-processors that we call
Quick-Div
. We compare them to various radix-N dividers and provide a thorough analysis in terms of latency and resource usage. In addition, we analyze the frequency scaling for such divider designs when (1) treated as a stand-alone unit and (2) integrated as part of a high-performance soft-processor. Moreover, we provide additional theoretical analysis of different dividers’ behaviour and develop a new better-performing
Quick-Div
variant, called
Quick-radix-4
. Experimental results show that our
Quick-radix-4
design can achieve up to 6.8× better performance and 6.1× better performance-per-LUT over the
radix-2
divider for applications such as random number generation. Even in cases where division operations constitute as little as 1% of all executed instructions,
Quick-radix-4
provides a performance uplift of 16% compared to the radix-2 divider.
Sensing the Sensor: Estimating Camera Properties with Minimal Information
Authors: Ghosh Pradipta , Liu Xiaochen , Qiu Hang , Vieira Marcos A. M. , Sukhatme Gaurav S. , Govindan Ramesh
Published: February 2022

Public outdoor surveillance cameras often have limited metadata describing their properties. Frequently, a public camera’s precise position, orientation, focal length, and image center are unknown; these attributes are necessary to precisely pinpoint the location of events seen in the camera. In this article, we ask: what is the minimal information needed to accurately estimate these properties for public cameras? We show, using a judicious combination of projective geometry, neural networks, and crowd-sourced annotations from human workers, that it is possible to, for example, localize 95% of the cameras in our test data set to within 12 m using a
single image
taken from the camera. This performance is an order of magnitude better than PoseNet, a state-of-the-art neural network that needs significantly more information than our approach, and can only estimate position and orientation (and not other properties). Finally, we show that the camera’s inferred pose and properties can help design a number of
virtual sensors
, all of which have good accuracy.
Review—Electrochemical Separation of Organic and Inorganic Contaminants in Wastewater
Authors: Gao Rui , Mosquera-Romero Suanny , Ntagia Eleftheria , Wang Xiaofei , Rabaey Korneel , Bonin Luiza
Published: February 2022

High energy input and chemicals additions are typically needed to deal with persistent pollutants, organic and inorganic, and organometallic complexes in wastewater. Particularly, organometallic complexes decrease the removal efficiency for other pollutants being treated with conventional technologies, which can lead to high operational costs and residues formation. The improperly treated wastewater contains nutrients (nitrogen and phosphorus), heavy metals, and persistent organics, which should be removed or recovered before discharging. Electrochemical technologies can achieve concomitant removal of persistent pollutants and resource recovery from wastewater, with the benefits of low chemical input, cost-effectiveness and reduced water consumption. In this review, we provide an overview of electrochemical technologies for the separation of organics and inorganics and their subsequent recovery. The focus is placed into electrodeposition, electrodialysis, membrane electrolysis, electrochemical oxidation, capacitive deionization, and bioelectrochemical systems. The main challenges considered at present are i) the cost and longevity of the materials, ii) the process efficiency and selectivity and iii) the complexity of the wastewater matrices. In this review it is projected that in the near future, the electrochemical separation and recovery of organics and inorganics will be preferred, as electrochemical cells powered by renewable energy can serve for decentralized and off-grid treatment approaches.
Review—Prospects of Nanomaterial-Based Biosensors: A Smart Approach for Bisphenol-A Detection in Dental Sealants
Authors: Verma Damini , Yadav Amit K. , Rathee Garima , Dhingra Kunaal , Das Mukherjee Maumita , Solanki Pratima R.
Published: February 2022

The use of Bisphenol-A (BPA) and its derivatives are rapidly increasing in dentistry for dental sealants and composite filling materials. The release of BPA from polymerized resin into saliva has aroused considerable concern regarding exposure to xenoestrogen by dental treatment. Many shreds of evidence have stated that leakage of BPA and its derivatives has posed health risks problems due to its endocrine-disrupting estrogenic properties. Various conventional techniques were designed for estimating leached BPA from dental sealants but having lengthy, complex procedures and requirements of technical experts, rapid utilization of these techniques is difficult. However, biosensors have emerged as a strong alternative to overcome these limitations. A vast range of electrochemical biosensors based on carbon and metal nanomaterials, molecularly-imprinted polymers, quantum dots, metal-organic frameworks, and polymer nanocomposites have been introduced for screening of BPA in real samples. But no study has been done to test leached BPA from dental sealants using biosensors. Therefore, we have provided an outlook of nanomaterials-based biosensors to test leached BPA from dental sealants. The present review also highlights different studies that assessed the absence/presence of BPA in the oral cavity after its use in dental materials. It also describes the challenges and future prospects in the progress of BPA-based biosensors.
Cyclic Voltammetry as a Probe of Selective Ion Transport within Layered, Electrode-Supported Ion-Exchange Membrane Materials
Authors: Xu Jiahe , Leddy Johna , Korzeniewski Carol
Published: February 2022

Cyclic voltammetry was applied to investigate the permselective properties of electrode-supported ion-exchange polymer films intended for use in future molecular-scale spectroscopic studies of bipolar membranes. The ability of thin ionomer film assemblies to exclude mobile ions charged similarly to the polymer (co-ions) and accumulate ions charged opposite to the polymer (counterions) was scrutinized through use of the diffusible redox probe molecules [Ru(NH3)6]3+ and [IrCl6]2−. With the anion exchange membrane (AEM) phase supported on a carbon disk electrode, bipolar junctions formed by addition of a cation exchange membrane (CEM) overlayer demonstrated high selectivity toward redox ion extraction and exclusion. For junctions formed using a Fumion® AEM phase and a Nafion® overlayer, [IrCl6]2− ions exchanged into Fumion® prior to Nafion® overcoating remained entrapped and the Fumion® excluded [Ru(NH3)6]3+ ions for durability testing periods of more than 20 h under conditions of interest for eventual in situ spectral measurements. Experiments with the Sustainion® anion exchange ionomer uncovered evidence for [IrCl6]2− ion coordination to pendant imidazolium groups on the polymer. A cyclic voltammetric method for estimation of the effective diffusion coefficient and equilibrium extraction constant for redox active probe ions within inert, uniform density electrode-supported thin films was applied to examine charge transport mechanisms.
(Keynote) Integrating Catalytic and Transport Functions within Multiscale Architectures
Authors: Rolison Debra R.
Published: February 2022

Our team at the U.S. Naval Research Laboratory is pursuing an opportunity unique within heterogeneous catalytic science: Correlating catalytic activity to our ability to integrate multiple transport and reactivity functions within practical, not model, architectures. We exploit sol–gel-derived aerogels as a hierarchical platform—structurally complex, but functionally simple—to address in detail whether controlling ionic transport to three-phase boundaries affects the catalytic activity of AuNP–modified oxide nanoarchitectures for model, CO-centered reactions and for the oxidation of water and alcohols. We can also address whether long ionic diffusion lengths (determined via impedance measurements) correlate with local ion mobility near the catalysis zone (monitored by NMR spectroscopy) and does either length scale affect catalytic activity (tracked by determining reaction turnover frequency)? Our synthetic processing protocols to control pore–solid architectures are established, ranging from a continuous 3D porous network with 1–100 nm pores (aerogel) to a continuous 3D porous network containing only 10–50 nm mesopores (ambigel) to a collapsed porous network with 10 nm pores (xerogel). The choice of architecture determines the through-connectedness of two critical transport networks: electrical wiring along the solid network and facile molecular flux through the pore network (approaching open-medium diffusion rates). This class of hierarchical nanoarchitectures provides a tunable platform with which to develop comprehensive mechanistic understanding that will allow us to design next-generation catalytic architectures with superior performance.
(Invited) High Surface Area, Amorphous Titania with Reactive Ti3+ through a Photo-Assisted Synthesis Method for Photocatalytic H2 Generation
Authors: Chan Candace K. , Zywitzki Dennis , Tüysüz Harun
Published: February 2022

Amorphous titania-based photocatalysts are synthesized using a facile, UV-light mediated method and evaluated as photocatalysts for hydrogen evolution from water/methanol mixtures. The photocatalysts are prepared through the direct injection of a titanium alkoxide precursor into a water/methanol mixture, with subsequent hydrolysis, condensation, and polycondensation to form TiOx(OH)y species under UV-irradiation. The resulting amorphous titania materials exhibit an overall higher hydrogen evolution rate compared to a crystalline TiO2 reference (P25) on a molar basis of photocatalyst due to the highly porous structure and high surface area (~500 m2/g). The employed titanium alkoxide precursor did not play a major role in affecting the hydrogen evolution rate or the catalyst surface and morphology. A blue coloration, which is associated with the formation of Ti3+ species, was observed in the amorphous titania but not in P25 upon light irradiation and is enabled by the porous and disordered structure of the amorphous photocatalyst. The Ti3+ species are also used to reduce protons to H2 in the absence of light irradiation or reduce Pt2+ to form Pt nanoparticles. These Pt nanoparticles are smaller and better dispersed on the photocatalyst compared to particles prepared using conventional photodeposition, leading to higher H2 evolution rates. The results show that the direct injection method is a facile approach for the preparation of high surface area titania photocatalysts containing Ti3+ species with good photocatalytic activity for production of H2.
Prevalence and Triggering Factors of Childhood Anemia: An Application of Ordinal Logistic Regression Model
Authors: Islam Md. Akhtarul , Afroja Sohani , Khan Md. Salauddin , Alauddin Sharlene , Nahar Mst. Tanmin , Talukder Ashis
Published: February 2022

Introduction. Anemia is indeed a significant risk factor for children’s health as it affects growth retardation and has severe short and prolonged effects that follow in morbidity and death. Notwithstanding such ways to tackle anemia, the prevalence remains high in India and poses a severe public health concern. Objectives. The primary focus of this study was to find the prevalence and to determine the factors associated with the anemia of children under five years of age in India. Problem Statement. The increasing prevalence of childhood anemia and the life-threatening consequences for millions of children in India are a major concern. Knowing the relevant associated factors with childhood anemia is essential to reduce the frequency and severity level. Study design. For analysis purposes, this study utilized a cross-sectional study design. Methodology. Using the Indian Demographic and Health Survey 2015–16 data, we used chi-squared and gamma tests to find the association. Then, we utilized multinomial logistic regression and ordinal logistic regression to find the better model and the influencing factors of anemia in India. Results. In our study, we have found that children with highly educated mothers were 36.7% less likely (OR = 0.633,

P
≤
0.001

, 95% CI: 0.608, 0.658) to be higher anemic than the children with not educated mother. Children with moderate and severe anemic mothers were 163.3% (OR = 2.633,

P
≤
0.001

, 95% CI: 2.565, 7.704) more likely to be higher anemic than the children with not anemic mother. Not stunting children were 21.9% (OR = 0.781,

P
≤
0.001

, 95% CI: 0 .764, 0.797) less likely to be higher anemic than the stunting children. Children aged 36–59 months were 73.9% (OR = 0.361,

P
≤
0.001

, 95% CI: 0.353, 0.369) less likely to be higher anemic than the children aged 6–24 months. Again, the ACI value revealed that ordinal logistic regression was a better-fitted model for these data. Conclusion and contribution. The variables such as stunting, underweight, wasting, child age, size of the child, and source of drinking water were the most critical indicators for child anemia in India. In summary, our study result indicated the major socioeconomic and demographic factors associated with childhood anemia in India, which can help the policymaker to take quick decision to reduce the severity level.
Ordinal Logistic Regression Analysis in Determining Factors Associated with Socioeconomic Status of Household in Tepi Town, Southwest Ethiopia
Authors: Lelisho Mesfin Esayas , Wogi Abebe Argaw , Tareke Seid Ali
Published: February 2022

Background. Socioeconomic status (SES) refers to an individual’s or group’s social position or class, which is often determined by a combination of education, income, and occupation. Knowing factors that affect the SES of the society might help to take action and improve their economy. In addition, using an ordinal logistic regression model for ordered SES outcomes will yield suitable results and conclusions. This study aimed to utilize an ordinal logistic regression model to find the factors associated with SES for households in Tepi town, Southwest Ethiopia. Methods. The community-based cross-sectional study was carried out in Tepi town, southwest Ethiopia, with data collected from 382 households using a simple random sample technique. The ordinal logistic regression models were evaluated and contrasted for proper accounting of ordinal form. In addition, to come up with a better model, we compared fitted ordinal logistic models with the likelihood-ratio test and AIC criteria. We performed data analysis using STATA version 16. Results. Of all 382 household heads, 170 (45.5%), 120 (31.4%), and 92 (24.1%) were at low, medium, and high SES of households, respectively. According to the result of the multivariable, partial proportional odds model (PPOM), age, education level, family size, and the saving habit were significantly associated with the SES of households at a 5% level of significance. Conclusions. According to the findings of this study, ordinal regression may be a better option in the event of the ordinal form of the outcome. Furthermore, PPOM may be a preferable option if any of the covariates violate the proportionality requirement. Based on the result of this study, the most likely associated indicators with the SES of families in Tepi town, southwest Ethiopia, were family size, age, saving habit, and education level. It is recommended that action should be taken to improve the SES of households.
Thermo-Hydromechanical Coupling Responses Driven by a Central Heat Source in Unsaturated Soils
Authors: Wang Wei , Liu Jingjing , Chen Jing
Published: February 2022

Based on the thermodynamic and thermoelastic theory, the coupled governing equations of deformation, heat transfer, and moisture migration in unsaturated soils were given. The coupled calculation process was realized by the finite element method. The hydrothermal coupling characteristics of two cases of unsaturated kaolin clay were studied by using a self-developed test device, and the test results were compared with the numerical results. The results showed that when the initial saturation of the soil is high, the volumetric water content of the measured point increases, and then it is in a stable state during the heating process. When the initial saturation is low, the volumetric water content near the heat source increases firstly and then decreases during the heating process. The rise and fall of temperature make the volumetric water content of the soil irreversible. The volumetric water content of each measured point is lower than the initial state. The closer it is to the internal measured heat source, the more obvious this phenomenon is; the lower the initial saturation is, the more obvious it is.
Properties of Cementitious Repair Materials for Concrete Pavement
Authors: Yeo Shih Horng , Mo Kim Hung , Hosen Md. Akter , Mahmud Hilmi Bin
Published: February 2022

This review aims to provide an insight into concrete pavement repair materials by gathering the relevant research outcomes and specifications. It provides a systematic literature review that focuses on pavement repair and types of cementitious repair material. In general, conventional cementitious repair materials can be divided into 4 categories: ultra-rapid, rapid, accelerated, and normal strength gain. The mechanical and durability properties of conventional cementitious repair materials, i.e., calcium sulphoaluminate-based, calcium aluminate-based, polymer-modified concrete, and ordinary Portland cement-based repair materials are highlighted. The paper also discusses the newly developed ultra-high performance concrete and alkali-activated materials as potential repair materials for concrete pavement due to the good mechanical and durability performance. As a final point, this review may help readers to understand and determine the appropriate type of repair material when distress occurs in concrete pavement.
Medical Conditions, Oral Health Practices, and Barriers to Treatment among Patients Visiting a Teaching Dental Hospital in Eastern Saudi Arabia
Authors: Alonaizan Faisal A , Almas Khalid , Nazir Muhammad Ashraf , Almazrou Dalal , Alzamil Manar , AlOlyani Mohammed A.
Published: February 2022

Objective. To assess the prevalence of medical conditions, oral hygiene practices, and dental visits among patients who attended a teaching dental hospital in Dammam, Saudi Arabia. Materials & Methods. This retrospective cross-sectional study used patient records from 2009 to 2015 from the dental hospital of the College of Dentistry Imam Abdulrahman Bin Faisal University, Dammam. Patients’ demographics, medical history, oral hygiene practices, reasons for attending the facility, attendance patterns, and smoking habits were studied. Results. The study included 1502 records of patients with 65.1% of males and 34.9% of females. The prevalence of medical conditions was 25.7% in the study. The most common medical conditions included diabetes mellitus (7.2%), hypertension (6.5%), and anemia (4.7%). Only 21.8% reported visiting the dental hospital in the past one year. The prevalence of smoking was 16.7%, and this did not differ significantly between healthy and medically compromised patients (

P
=
0.165

). Fillings were the most common (21.6%) reason for visiting a dental hospital, followed by treatment for periodontal problems (12.9%) and oral lesions (12.6%), whereas treatment for braces (orthodontics) was the least common (5%) reason for visiting the hospital. The reasons for visiting the hospital did not differ significantly between healthy and medically compromised patients (

P
>
0.05

). The three most common barriers to dental visits included long waiting time (18.1%), fear of dental treatment (14.4%), and difficulty in getting an appointment (11.3%). Conclusion. The study showed that dental patients had a high prevalence of medical conditions. Diabetes mellitus was the most prevalent problem. Most patients visited the dental hospital to receive restorative treatment, and a long waiting time was the most common barrier to dental visits. Public health measures should be taken to improve the general health and oral care of patients.
The Optimization of Airport Management Based on Collaborative Optimization of Flights and Taxis
Authors: Ding Xiaobing , Liu Zhigang , Shi Gan , Hu Hua , Chen Jiaping , Yang Kaihe , Wan Su , Wu Jinlong
Published: February 2022

How to efficiently guide passengers and ensure the order of airport operation is an urgent transport problem for airport management. Based on the analysis of the factors that affect the driver’s decision‐making, this paper deeply explores the collaborative association of the core factors, such as the number of flight arrivals in different periods and the average seeking distance of taxis. Firstly, according to the GPS data of taxis, the paper uses clustering algorithm to get the average passenger‐seeking time from the airport and makes matching interaction between the number of flights based on time distribution and the average passenger‐carrying capacity of vehicles in the parking garage, so as to build a decision‐making model based on the number of taxis N; secondly, it takes passenger safety and traffic order as the priority and uses M/M/S queuing model to integrate the two factors. Taking the maintenance cost and passenger evacuation time as constraints, the judgment condition of minimum cost Zmin and the optimal number of boarding points Sm are solved. Finally, taking the flight and taxi data of Shanghai Hongqiao Airport as an example, the driver’s decision‐making standard is simulated, and the accuracy of the model is verified by the deviation rate. It can provide decision‐making support for taxi management of urban transportation hub and rapid evacuation of airport passengers, so as to realize the collaborative optimization of airport flight arrival and taxi carrying order.
Evaluation of Therapeutic Benefits of a Novel Herbal Ingredient-Based Hyaluronic Acid Gel as Monotherapy for Inflammatory Enlargement of a Patient with Diabetes Mellitus
Authors: Lanka Jaahnavi , Kumar Santhosh
Published: February 2022

The reason for the destruction of the attachment apparatus in patients with periodontal disease is the supra- and the subgingival microflora. Hence, the treatment of this inflammatory gingival disease is primarily focused on eliminating the cause. The present case report assessed the therapeutic benefit of adjunctive use of a commercially available topical agent containing 1% hyaluronic acid gel combined with nonsurgical periodontal therapy. A patient aged 64 years with type 2 diabetes mellitus reported to the Department of Periodontology. He complained of gum enlargement and frequent bleeding during brushing. The patient was not under any medication for his diabetes control. On examination, there was a localized papillary gingival enlargement. Therefore, Klirich gel containing hyaluronic acid was applied on the surface of the gingiva during the first visit of the patient. During the follow-up visit, he continued with this adjunctive use of the gel along with the nonsurgical periodontal therapy. In addition, he controlled his blood sugar level with diet and exercise. During the follow-up visit after one year, there was a noticeable clinical change in the overall health of his gingiva.
Comparison of Performance of Photodiodes with Different Active Areas Using Acrylic and Quartz Cuvettes for Spectrophotometry in Direct Measurements of Glucose in Water and Human Blood Plasma by Optical Means Using Near-Infrared
Authors: De La Cruz Cortes Victor , Segura Félix Kristian , Flores García Francisco Gerardo , Cepeda Rubio Mario Francisco Jesús
Published: February 2022

Diabetes mellitus is one of the most relevant noncommunicable diseases; the WHO figures in its latest update that 422 million people suffer from it; additionally, it has remained for more than 20 years within the 10 main causes of death worldwide; this disease affects the population at any age; glucose measurement is used to assist the treatment of this disease by different methods that are classified as invasive, minimally invasive, and noninvasive, the latter being an area of recent development due that it is not traumatic for patients. This work consists of the experimental characterization of an optical system for plasma glucometry using near infrared by spectrophotometry. This glucometry system is based on the employ of an infrared LED with a wavelength of 1650 nm, a beam angle of 16°, and an output power of 1.6 mW that passes through the analyte (glucose in blood plasma) that is contained in cuvettes of different materials (acrylic and quartz) to subsequently affect a photodiode with different active areas ranging from 0.06 mm to 1.5 mm in order to evaluate the efficiency by comparing the sensitivity in the presence of glucose making additions ranging 100 mg/dl–1000 mg/dl within a dark chamber. The experiments showed that the use of photodiodes with a larger active area and the use of quartz cuvettes show a higher sensitivity compared to photodiodes with small active areas and the use of acrylic cuvettes. This configuration presented an R2 of 0.99 and a sensitivity of 0.225 mV/1 mg/dl of glucose; despite the fact that the initial voltage in each of the experimental repetitions varies, the downward voltage pattern is maintained; based on this, it is concluded that this method using this setup is feasible for plasma glucose measurement.
Analysis of Communication Compression and Transmission in a Multimedia and Internet of Things Environment Integrating Scene Elements
Authors: Jia Jia , Wu Guohua
Published: February 2022

In order to improve the effect of multimedia data transmission, this paper integrates scene elements to analyze the needs of multiple types of data transmission and uses the technology of the Internet of Things to analyze the compression and transmission of multimedia data communication. Moreover, this paper proposes a reversible information hiding algorithm for encrypted images based on pixel sorting and grouping prediction and discusses how to improve the prediction accuracy through the histogram of prediction errors. In addition, this paper designs a communication compression transmission system in a multimedia and Internet of Things environment integrating scene elements and builds system function modules and system processes. Finally, this paper verifies the performance of the proposed system by means of simulation experiments. From the experimental results, we can see that the system proposed in this paper has a good multimedia information transmission effect.