bluuebunny/crossref_metadata_2025 huggingface dataset:
Detecting Reconnaissance and Discovery Tactics from the MITRE ATT&CK Framework in Zeek Conn Logs Using Spark’s Machine Learning in the Big Data Framework
Authors: Bagui Sikha , Mink Dustin , Bagui Subhash , Ghosh Tirthankar , McElroy Tom , Paredes Esteban , Khasnavis Nithisha , Plenkers Russell
Published: October 2022

While computer networks and the massive amount of communication taking place on these networks grow, the amount of damage that can be done by network intrusions grows in tandem. The need is for an effective and scalable intrusion detection system (IDS) to address these potential damages that come with the growth of these networks. A great deal of contemporary research on near real-time IDS focuses on applying machine learning classifiers to labeled network intrusion datasets, but these datasets need be relevant pertaining to the currency of the network intrusions. This paper focuses on a newly created dataset, UWF-ZeekData22, that analyzes data from Zeek’s Connection Logs collected using Security Onion 2 network security monitor and labelled using the MITRE ATT&CK framework TTPs. Due to the volume of data, Spark, in the big data framework, was used to run many of the well-known classifiers (naïve Bayes, random forest, decision tree, support vector classifier, gradient boosted trees, and logistic regression) to classify the reconnaissance and discovery tactics from this dataset. In addition to looking at the performance of these classifiers using Spark, scalability and response time were also analyzed.
Reinforcement Learning-Aided Edge Intelligence Framework for Delay-Sensitive Industrial Applications
Authors: Zubair Islam Muhammad , Shahzad  , Ali Rashid , Haider Amir , Kim Hyung Seok
Published: October 2022

With the advancement in next-generation communication technologies, the so-called Tactile Internet is getting more attention due to its smart applications, such as haptic-enabled teleoperation systems. The stringent requirements such as delay, jitter, and packet loss of these delay-sensitive and loss-intolerant applications make it more challenging to ensure the Quality of Service (QoS) and Quality of Experience (QoE). In this regard, different haptic codec and control schemes were proposed for QoS and QoE provisioning in the Tactile Internet. However, they maximize the QoE while degrading the system’s stability under varying delays and high packet rates. In this paper, we present a reinforcement learning-based Intelligent Tactile Edge (ITE) framework to ensure both transparency and stability of teleoperation systems with high packet rates and variable time delay communication networks. The proposed ITE first estimates the network challenges, including communication delay, jitter, and packet loss, and then utilizes a Q-learning algorithm to select the optimal haptic codec scheme to reduce network load. The proposed framework aims to explore the optimal relationship between QoS and QoE parameters and make the tradeoff between stability and transparency during teleoperations. The simulation result indicates that the proposed strategy chooses the optimal scheme under different network impairments corresponding to the congestion level in the communication network while improving the QoS and maximizing the QoE. The end-to-end performance of throughput (1.5 Mbps) and average RTT (70 ms) during haptic communication is achieved with a learning rate and discounted factor value of 0.5 and 0.8, respectively. The results indicate that the communication system can successfully achieve the QoS and QoE requirements by employing the proposed ITE framework.
Super-Resolving Methodology for Noisy Unpaired Datasets
Authors: Min Sung-Jun , Jo Young-Su , Kang Suk-Ju
Published: October 2022

Although it is possible to acquire high-resolution and low-resolution paired datasets, their use in directly supervised learning is impractical in real-world applications. In the present work, we focus on a practical methodology for image acquisition in real-world conditions. The main method of noise reduction involves averaging multiple noisy input images into a single image with reduced noise; we also consider unpaired datasets that contain misalignments between the high-resolution and low-resolution images. The results show that when more images are used for average denoising, better performance is achieved in the super-resolution task. Quantitatively, for a fixed noise level with a variance of 60, the proposed method of using 16 images for average denoising shows better performance than using 4 images for average denoising; it shows 0.68 and 0.0279 higher performance for the peak signal-to-noise ratio and structural similarity index map metrics, as well as 0.0071 and 1.5553 better performance for the learned perceptual image patch similarity and natural image quality evaluator metrics, respectively.
Out-of-Plane Behavior of Masonry Prisms Retrofitted with Shape Memory Alloy Stripes: Numerical and Parametric Analysis
Authors: Tabrizikahou Alireza , Kuczma Mieczysław , Łasecka-Plura Magdalena
Published: October 2022

This paper provides a novel Finite Element (FE) simulation to estimate the out-of-plane response of masonry prisms retrofitted with Shape Memory Alloy (SMA) stripes. Empirical data were utilized to develop the computational analysis parameters (mechanical parameters for brick, mortar, and SMA materials) as well as the calibration of the computational FE-based models. For this purpose, a complete micro-modeling approach was applied, assuming perfect contact between mortar joints and brick units. A Concrete Damage Plasticity (CDP) model was developed to define the constitutive relation between brick and mortar. SMA stripes were mortar-installed on the surface of the prisms with a perfect connection. The masonry prism’s verified computational model was utilized to generate parametric research to explore the effect of varying SMA stripe thicknesses and different SMA usage (Ni-Ti or Cu-Zn-Al). The FE study findings indicated that, independent of their material type or thickness, using SMA stripes greatly minimizes brick prism deterioration. SMA stripes greatly decreased residual displacement and plastic strains. Parametric tests, however, revealed that employing Ni-Ti SMA and increasing its thickness is more effective with respect to the masonry prism out-of-plane response than Cu-Zn-Al SMA.
Improved Wearable Devices for Dietary Assessment Using a New Camera System
Authors: Sun Mingui , Jia Wenyan , Chen Guangzong , Hou Mingke , Chen Jiacheng , Mao Zhi-Hong
Published: October 2022

An unhealthy diet is strongly linked to obesity and numerous chronic diseases. Currently, over two-thirds of American adults are overweight or obese. Although dietary assessment helps people improve nutrition and lifestyle, traditional methods for dietary assessment depend on self-report, which is inaccurate and often biased. In recent years, as electronics, information, and artificial intelligence (AI) technologies advanced rapidly, image-based objective dietary assessment using wearable electronic devices has become a powerful approach. However, research in this field has been focused on the developments of advanced algorithms to process image data. Few reports exist on the study of device hardware for the particular purpose of dietary assessment. In this work, we demonstrate that, with the current hardware design, there is a considerable risk of missing important dietary data owing to the common use of rectangular image screen and fixed camera orientation. We then present two designs of a new camera system to reduce data loss by generating circular images using rectangular image sensor chips. We also present a mechanical design that allows the camera orientation to be adjusted, adapting to differences among device wearers, such as gender, body height, and so on. Finally, we discuss the pros and cons of rectangular versus circular images with respect to information preservation and data processing using AI algorithms.
Power Spectrum of Acceleration and Angular Velocity Signals as Indicators of Muscle Fatigue during Upper Limb Low-Load Repetitive Tasks
Authors: Moyen-Sylvestre Béatrice , Goubault Étienne , Begon Mickaël , Côté Julie N. , Bouffard Jason , Dal Maso Fabien
Published: October 2022

Muscle fatigue is a risk factor for developing musculoskeletal disorders during low-load repetitive tasks. The objective of this study was to assess the effect of muscle fatigue on power spectrum changes of upper limb and trunk acceleration and angular velocity during a repetitive pointing task (RPT) and a work task. Twenty-four participants equipped with 11 inertial measurement units, that include acceleration and gyroscope sensors, performed a tea bag filling work task before and immediately after a fatiguing RPT. During the RPT, the power spectrum of acceleration and angular velocity increased in the movement and in 6–12 Hz frequency bands for sensors positioned on the head, sternum, and pelvis. Alternatively, for the sensor positioned on the hand, the power spectrum of acceleration and angular velocity decreased in the movement frequency band. During the work task, following the performance of the fatiguing RPT, the power spectrum of acceleration and angular velocity increased in the movement frequency band for sensors positioned on the head, sternum, pelvis, and arm. Interestingly, for both the RPT and work task, Cohens’ d effect sizes were systematically larger for results extracted from angular velocity than acceleration. Although fatigue-related changes were task-specific between the RPT and the work task, fatigue systematically increased the power spectrum in the movement frequency band for the head, sternum, pelvis, which highlights the relevance of this indicator for assessing fatigue. Angular velocity may be more efficient to assess fatigue than acceleration. The use of low cost, wearable, and uncalibrated sensors, such as acceleration and gyroscope, in industrial settings is promising to assess muscle fatigue in workers assigned to upper limb repetitive tasks.
A New Compact Triple-Band Triangular Patch Antenna for RF Energy Harvesting Applications in IoT Devices
Authors: Benkalfate Chemseddine , Ouslimani Achour , Kasbari Abed-Elhak , Feham Mohammed
Published: October 2022

This work proposes a new compact triple-band triangular patch antenna for RF energy harvesting applications in IoT devices. It is realized on Teflon glass substrate with a thickness of 0.67 mm and a relative permittivity of 2.1. Four versions of this antenna have been designed and realized with inclinations of 0°, 30°, 60° and 90° to study the impact of the tilting on their characteristics (S11 parameter, radiation pattern, gain) and to explore the possibilities of their implementation in the architectures of electronic equipment according to the available space. The antenna is also realized on waterproof paper with a thickness of 0.1 mm and a relative permittivity of 1.4 for biomedical domain. All the antennas (vertical antenna, tilted antennas and antenna realized on waterproof paper) have a size of 39 × 9 mm2 and cover the 2.45 GHz and 5.2 GHz Wi-Fi bands and the 8.2 GHz band. A good agreement is obtained between measured and simulated results. Radiation patterns show that all the antennas are omnidirectional for 2.45 GHz and pseudo-omnidirectional for 5.2 GHz and 8.2 GHz with maximum measured gains of 2.6 dBi, 4.55 dBi and 6 dBi, respectively. The maximum measured radiation efficiencies for the three antenna configurations are, respectively, of 75%, 70% and 72%. The Specific Absorption Rate (SAR) for the antenna bound on the human body is of 1.1 W/kg, 0.71 W/kg and 0.45 W/kg, respectively, for the three frequencies 2.45 GHz, 5.2 GHz and 8.2 GHz. All these antennas are then applied to realize RF energy harvesting systems. These systems are designed, realized and tested for the frequency 2.45 GHz, −20 dBm input power and 2 kΩ resistance load. The maximum measured output DC power is of 7.68 µW with a maximum RF-to-DC conversion efficiency of 77%.
The Long-Range Biomimetic Covert Communication Method Mimicking Large Whale
Authors: Ahn Jongmin , Do Deawon , Kim Wanjin
Published: October 2022

Short-range biomimetic covert communications have been developed using dolphin whistles for underwater acoustic covert communications. Due to a channel characteristics difference by range, the conventional short-range methods cannot be directly applied to long-range communications. To enable long-range biomimicking communication, overcoming the large multipath delay and a high degree of mimic (DoM) in the low-frequency band is required. This paper proposes a novel biomimetic communication method that preserves a low bit-error rate (BER) with a large DoM in the low-frequency band. For the transmission, the proposed method utilizes the time-dependent frequency change of the whistle, and its receiver obtains additional SNR gain from the multipath delay. Computer simulations and practical ocean experiments were executed to demonstrate that the BER performance of the proposed method is better than the conventional methods. For the DoM assessment, the novel machine learning-based method was utilized, and the result shows that the whistles generated by the proposed method were recognized as the actual whistle of the right humpback whale.
Design of a Tri-Band Wearable Antenna for Millimeter-Wave 5G Applications
Authors: Ahmad Sarosh , Boubakar Hichem , Naseer Salman , Alim Mohammad Ehsanul , Sheikh Yawar Ali , Ghaffar Adnan , Al-Gburi Ahmed Jamal Abdullah , Parchin Naser Ojaroudi
Published: October 2022

A printed monopole antenna for millimeter-wave applications in the 5G frequency region is described in this research. As a result, the proposed antenna resonates in three frequency bands that are designated for 5G communication systems, including 28 GHz, 38 GHz, and 60 GHz (V band). For the sake of compactness, the coplanar waveguide (CPW) method is used. The overall size of the proposed tri-band antenna is 4 mm × 3 mm × 0.25 mm. Using a watch strap and human tissue, such as skin, the proposed antenna gives steady results. At 28 GHz, 38 GHz, and 60 GHz, the antenna’s gain is found to be 5.29 dB, 7.47 dB, and 9 dB, respectively. The overall simulated radiation efficiency is found to be 85% over the watch strap. Wearable devices are a great fit for the proposed tri-band antenna. The antenna prototype was built and tested in order to verify its performance. It can be observed that the simulated and measured results are in close contact. According to our comparative research, the proposed antenna is a good choice for smart 5G devices because of its small size and simple structure, as well as its high gain and radiation efficiency.
MEMS-Based Micro Sensors for Measuring the Tiny Forces Acting on Insects
Authors: Takahashi Hidetoshi
Published: October 2022

Small insects perform agile locomotion, such as running, jumping, and flying. Recently, many robots, inspired by such insect performance, have been developed and are expected to be smaller and more maneuverable than conventional robots. For the development of insect-inspired robots, understanding the mechanical dynamics of the target insect is important. However, evaluating the dynamics via conventional commercialized force sensors is difficult because the exerted force and insect itself are tiny in strength and size. Here, we review force sensor devices, especially fabricated for measuring the tiny forces acting on insects during locomotion. As the force sensor, micro-force plates for measuring the ground reaction force and micro-force probes for measuring the flying force have mainly been developed. In addition, many such sensors have been fabricated via a microelectromechanical system (MEMS) process, due to the process precision and high sensitivity. In this review, we focus on the sensing principle, design guide, fabrication process, and measurement method of each sensor, as well as the technical challenges in each method. Finally, the common process flow of the development of specialized MEMS sensors is briefly discussed.
A Novel Distributed Vibration Sensor Based on Fading Noise Reduction in Multi-Mode Fiber
Authors: Lu Lidong , Su Xingchen , Zhang Chenglong , Gao Qinghao , Yang Hongwei
Published: October 2022

Multi-mode fiber (MMF) is used in a polarization-sensitive optical time domain reflectometer (OTDR) for vibration event location and spectrum analysis. The vibration events acting on MMF are considered to be the optical polarization state and phase diversifying process for fading noise reduction. In addition, data averaging with continuous positions and the fast Fourier transform (FFT) method is proposed to extract the spectrum of the vibration events. In the experiment, the vibration events are loaded at the positions of 5.167 and 10.145 km, respectively, along MMF. The experimental results demonstrate that the vibration event can effectively diversify the optical polarization state and phase of the Rayleigh scattering light to make the averaged OTDR trace behind the vibration position converge rapidly, which helps to locate corresponding vibration events and extract the vibration spectrum. It is inferred that the new distributed vibration sensor shall have a lower false alarm rate, as it can greatly reduce the errors caused by randomness of the sensing light signals. Additionally, it also saves time in comparison with the method that analyzes the vibration spectra for all the positions along the fiber under test.
Automatic User Preferences Selection of Smart Hearing Aid Using BioAid
Authors: Siddiqui Hafeez Ur Rehman , Saleem Adil Ali , Raza Muhammad Amjad , Zafar Kainat , Russo Riccardo , Dudley Sandra
Published: October 2022

Noisy environments, changes and variations in the volume of speech, and non-face-to-face conversations impair the user experience with hearing aids. Generally, a hearing aid amplifies sounds so that a hearing-impaired person can listen, converse, and actively engage in daily activities. Presently, there are some sophisticated hearing aid algorithms available that operate on numerous frequency bands to not only amplify but also provide tuning and noise filtering to minimize background distractions. One of those is the BioAid assistive hearing system, which is an open-source, freely available downloadable app with twenty-four tuning settings. Critically, with this device, a person suffering with hearing loss must manually alter the settings/tuning of their hearing device when their surroundings and scene changes in order to attain a comfortable level of hearing. However, this manual switching among multiple tuning settings is inconvenient and cumbersome since the user is forced to switch to the state that best matches the scene every time the auditory environment changes. The goal of this study is to eliminate this manual switching and automate the BioAid with a scene classification algorithm so that the system automatically identifies the user-selected preferences based on adequate training. The aim of acoustic scene classification is to recognize the audio signature of one of the predefined scene classes that best represent the environment in which it was recorded. BioAid, an open-source biological inspired hearing aid algorithm, is used after conversion to Python. The proposed method consists of two main parts: classification of auditory scenes and selection of hearing aid tuning settings based on user experiences. The DCASE2017 dataset is utilized for scene classification. Among the many classifiers that were trained and tested, random forests have the highest accuracy of 99.7%. In the second part, clean speech audios from the LJ speech dataset are combined with scenes, and the user is asked to listen to the resulting audios and adjust the presets and subsets. A CSV file stores the selection of presets and subsets at which the user can hear clearly against the scenes. Various classifiers are trained on the dataset of user preferences. After training, clean speech audio was convolved with the scene and fed as input to the scene classifier that predicts the scene. The predicted scene was then fed as input to the preset classifier that predicts the user’s choice for preset and subset. The BioAid is automatically tuned to the predicted selection. The accuracy of random forest in the prediction of presets and subsets was 100%. This proposed approach has great potential to eliminate the tedious manual switching of hearing assistive device parameters by allowing hearing-impaired individuals to actively participate in daily life by automatically adjusting hearing aid settings based on the acoustic scene.
Literature Review on Human Resource Churning—Theoretical Framework, Costs and Proposed Solutions
Authors: Pirrolas Olga Alexandra Chinita , Correia Pedro Miguel Alves Ribeiro
Published: October 2022

As a result of the complexity and multiplicity of definitions of the concept of human resource churning, to guide this entire research, the cost resulting from replacements was taken as a premise. Although churning is related to turnover, there are differences, turnover has as its focus the turnover of workers and churning is also related to the same approach, but this concept has as its focus the costs associated with the replacements of workers derived from voluntary departures, i.e., churning is only related to the costs of hiring from replacements. Despite the complexity and multiplicity of definitions of the concept of churning, to guide the present research, we chose to adopt as our premise the costs resulting from the voluntary exits of workers, that is, the relationship between resulting costs associated with employee substitutions. The present investigation intended to identify the causes of churning through the identification of its main dimensions. This theoretical research resorted to the following methodology: a literature review and an empirical study review that approached the subject of the churning of human resources. The resulting outcome enabled us to identify how these dimensions had an influence on the management of human resources regarding the mitigation of the occurrence of churning and the application of strategic measures to retain workers. In this regard, we have identified as main dimensions the work environment; leadership; recognition; schedule flexibility; wage; career progression, responsibility, and retention of human resources.
Wetting Pattern of Cow Urine Patch in an Andisol Assessed through Bromide Concentration Distribution: A Pilot Study
Authors: Ramírez-Sandoval Magdalena A. , Pinochet Dante E. , Rivero M. Jordana
Published: October 2022

Cow urine is a rich source of mobile nutrients such as nitrate (NO3−) and potassium (K+). The aim of this experiment was to evaluate the wetting pattern distribution through soil profile of cow urine patch in an andisol. Two field experiments across two consecutive years were carried out to compare cow urine patches in relation to initial wetting pattern and volume of soil affected. Bromide (Br−) has successfully been used as an inert hydrologic tracer to indicate the movement of NO3− and K+ in soil–water systems. The distribution of Br− (used as a urine tracer) on the soil surface and down the profile was irregular in all the patches. Cow urine patches covered a surface area of 0.27 and 0.35 m2, respectively, and penetrated to a depth of 70 cm. The rapid downward movement of urine occurred through macropore flow but even so, between 27% and 40% of the applied Br− was detected in the 0–5 cm soil layer. Br− showed concentrations greater than 1500 mg kg−1 and up to 3000 mg kg−1, and as the concentration of Br− decreases, the frequency and depth of affected layers increases. Despite the differences in moisture and in the distribution of the Br− concentration in both years, the concentration frequency of 500 to 1500 mg kg−1 represented around 37% of the affected volume of soil (bulb of urine) in both years. Up to 40% of the bulb represented N equivalent rates between 187 and 975 kg N ha−1. These values can potentially be emitted in gases such as NH3, N2O, and N2. It is suggested that the presence of N in the volume of affected soil could vary due to the moisture content of the soil, and that in andisols of southern Chile under permanent grasslands there are a large number of macropores that would induce preferential flows.
Extreme Tail Ratios and Overrepresentation among Subpopulations with Normal Distributions
Authors: Hill Theodore P. , Fox Ronald F.
Published: October 2022

Given several different populations, the relative proportions of each in the high (or low) end of the distribution of a given characteristic are often more important than the overall average values or standard deviations. In the case of two different normally-distributed random variables, as is shown here, one of the (right) tail ratios will not only eventually be greater than 1 from some point on, but will even become infinitely large. More generally, in every finite mixture of different normal distributions, there will always be exactly one of those distributions that is not only overrepresented in the right tail of the mixture but even completely overwhelms all other subpopulations in the rightmost tails. This property (and the analogous result for the left tails), although not unique to normal distributions, is not shared by other common continuous centrally symmetric unimodal distributions, such as Laplace, nor even by other bell-shaped distributions, such as Cauchy (Lorentz) distributions.
Safety Analysis of a Nuclear Power Plant against Unexpected Tsunamis
Authors: Kim Byung-Ho , Song Min-Jong , Cho Yong-Sik
Published: October 2022

The East Sea (Sea of Japan), surrounded by Korea, Japan, and Russia, is highly vulnerable to catastrophic tsunamis. Several nuclear power plants (NPPs) operate along the eastern coast of Korea and several more are under construction. Unexpected tsunamis can affect these power plants. The safety of NPPs has attracted worldwide attention since the Fukushima NPP accident. In this study, a coupled numerical model comprising propagation and run-up models was employed to investigate the safety of an NPP against unexpected tsunami attacks. The maximum and minimum tsunami heights and arrival times of the leading tsunami were numerically predicted to ensure the safety of the Uljin NPP, where six plants are already operational and two more are under construction. The predicted numerical results were compared with the safety guidelines proposed by relevant authorities. These results indicate that NPPs are reasonably safe from unexpected tsunamis. Additionally, we confirmed that the tsunami heights and arrival times of a leading tsunami becomes smaller and delayed as the latitude of the epicenter increased.
Sustaining the Environment: Critical Success Factors and Barriers of Solid Waste Management through Composting Practices by Rural Communities in Malaysia
Authors: Salleh Nurul Azita , Mohd Shafiei Mohd Wira , Anwar Aviasti , Zulhumadi Faisal , Hubadillah Siti Khadijah
Published: October 2022

Generally, rural areas can contain large amounts of organic and household wastes, which on average, is rarely managed well. Meanwhile, composting is a waste management method that decomposes organic waste biologically, thus contributing toward better waste management and environmental sustainability. However, exposure to more efficient waste management methods and the knowledge of the importance of composting are still low among rural communities. These communities also do not realise that composting has the added potential benefit of increasing household income. Therefore, this exploratory study was performed guided by two objectives, first to identify the critical success factors of composting practice for improving the economy and quality of life among rural communities, and second, to identify factors that hinder this composting practice. A quantitative approach was used for this purpose, where data were obtained through non-probability sampling from respondents located in 32 rural villages in the Kubang Pasu District of Kedah, Malaysia. The results of this study revealed that villagers living outside of city limits do not practice composting as part of their waste management. Among the barriers that were identified as preventing composting practice in these rural village communities, were the lack of knowledge, awareness, and interest in composting. However, some of these respondents indicated that they were aware of composting through television, radio, social media, newspapers, and from various programmes organised by certain organisations. In conclusion, this study has provided information as a guide to stakeholders for them to act by further educating rural communities about composting, perhaps highlighting more the potential benefits of earning a side income through the adoption of composting practices by producing and selling compost fertilisers.
Survival during Times of Disruptions: Rethinking Strategies for Enabling Business Viability in the Developing Economy
Authors: Ibidunni Ayodotun Stephen , Ayeni Adebanji William Adejuwon , Ogundana Oyedele Martins , Otokiti Bisayo , Mohalajeng Lerato
Published: October 2022

There exists a noticeable void in the literature about strategies that business operators, especially those in highly vulnerable economies, can adapt to sustain their survival and to achieve growth in economically turbulent times. This study investigated strategies that can support the viability and survival of businesses in times of environmental disruptions. The study adopted a qualitative research design that involved the interview of 31 business owners across different sectoral groups including fashion and telecommunication that are operating in Nigeria’s Small and Medium Enterprises (SMEs) sector. The interview sessions were audio recorded, transcribed verbatim and thematically analysed. The findings reveal that amid disruptions, the business owners were resilient and established diverse digital strategies that helped them to keep their businesses afloat throughout the time of disruption. This finding contributes to the field of entrepreneurship as it offers practical strategies for supporting business owners during times of disruptions, especially in a developing country context.
Biobased Acrylate Shells for Microcapsules Used in Self-Healing of Cementitious Materials
Authors: Souza Lívia Ribeiro de , Whitfield Briony , Al-Tabbaa Abir
Published: October 2022

To facilitate the ongoing transition towards carbon neutrality, the use of renewable materials for additive manufacturing has become increasingly important. Here, we report for the first time the fabrication of microcapsules from biobased acrylate shells using microfluidics. To select the shell, a wide range of biobased acrylates disclosed in the literature was considered according to their tensile strength, ductile transition temperature and global availability. Once acrylate epoxidised soybean oil (AESO) was selected, its viscosity was adjusted to valuables suitable for the microfluidic device using two different diluting agents. Double emulsions were successfully produced using microfluidics, followed by photopolymerisation of the shell and characterisation of the capsules. Microcapsules containing AESO and isobornyl acrylate (IBOA) were produced with an outer diameter ~490 μm, shell thickness ranging between 36 and 67 μm, and production rates around 2.4 g/h. The mechanical properties of the shell were characterised as tensile strength of 29.2 ± 7.7 MPa, Young’s modulus of 1.7 ± 0.4 GPa and the ductile transition temperature was estimated as 42 °C. To investigate physical triggering, microcapsules produced with a size of 481 ± 4 μm and with a measured shell thickness around 6 μm were embedded in the cementitious matrix. The triggered shells were observed with scanning electron microscopy (SEM) and the uniform distribution of the capsules in cement paste was confirmed using X-ray computed tomography (XCT). These advances can facilitate the wide application of biobased resins for the fabrication of microcapsules for self-healing in cementitious materials.
A Hybrid Multi-Cloud Framework Using the IBBE Key Management System for Securing Data Storage
Authors: Sohal Manreet , Bharany Salil , Sharma Sandeep , Maashi Mashael S. , Aljebreen Mohammed
Published: October 2022

Information storage and access in multi-cloud environments have become quite prevalent. In this paper, a multi-cloud framework is presented that secures users’ data. The primary goal of this framework is to secure users’ data from untrusted Cloud Service Providers (CSPs). They can collude with other malicious users and can hand over users’ data to these malicious users for their beneficial interests. In order to achieve this goal, the data are split into parts, and then each part is encrypted and uploaded to a different cloud. Therefore, client-side cryptography is used in this framework. For encrypting users’ data, the BDNA encryption technique is used. This framework presents a hybrid cryptographic approach that uses Identity-based Broadcast Encryption (IBBE) for managing the keys of the symmetric key algorithm (BDNA) by encrypting them with the particular version of IBBE. The work presented in this research paper is the first practical implementation of IBBE for securing encryption keys. Earlier, IBBE was only used for securely broadcasting data across many users over a network. The security of this hybrid scheme was proved through Indistinguishable Chosen-Ciphertext Attacks. This double encryption process makes the framework secure against all insiders and malicious users’ attacks. The proposed framework was implemented as a web application, and real-time storage clouds were used for storing the data. The workflow of the proposed framework is presented through screenshots of different working modules.
Effect of an Herbal Mixture of Oregano, Garlic, Sage and Rock Samphire Extracts in Combination with Tributyrin on Growth Performance, Intestinal Microbiota and Morphology, and Meat Quality in Broilers
Authors: Bonos Eleftherios , Skoufos Ioannis , Giannenas Ilias , Sidiropoulou Erasmia , Fotou Konstantina , Stylianaki Ioanna , Tsiftsoglou Olga , Lazari Diamanto , Venardou Brigkita , Galamatis Dimitrios , Skoufos Stylianos , Gouva Evangelia , Tzora Athina
Published: October 2022

The present study investigated the effects of two feed additives, the first containing an herbal mixture of oregano, garlic, sage, and rock samphire extracts and the second containing tributyrin (glyceryl tributyrate) when fed to broiler chickens. A total of 360 one-day-old chicks were randomly allocated to four treatments (6 replicate pens of 15 chicks). One treatment served as the unsupplemented control, whereas the feeds of the other three treatments were supplemented either with the herbal additive (3 g/kg), the tributyrin additive (1 g/kg), or both additives. The duration of the trial was 37 days. Data were collected on growth performance, intestinal microbiota and morphology, and some meat quality parameters. The combined supplementation improved (p < 0.05) weigh gain, feed conversion ratio, and the European Efficiency Factor. In the cecum, the combined supplementation lowered (p < 0.05) the microbial populations of aerobes, anaerobes, Escherichia coli, total Enterobacteriaceae, and Clostridium spp. compared to the other treatments. Fecal coccidial oocyst counts were also reduced (p < 0.01) by the combined supplementation. The herbal mixture supplementation improved (p < 0.05) breast and thigh meat resistance to oxidation. In conclusion, the combined dietary supplementation with the examined feed additives could be utilized to improve the performance and intestinal health of broiler chickens.
Spatiotemporal Prediction of Urban Online Car-Hailing Travel Demand Based on Transformer Network
Authors: Bi Shuoben , Yuan Cong , Liu Shaoli , Wang Luye , Zhang Lili
Published: October 2022

Online car-hailing has brought convenience to daily travel, whose accurate prediction benefits drivers and helps managers to grasp the characteristics of urban travel, so as to facilitate decisions. Spatiotemporal prediction in the transportation field has usually been based on a recurrent neural network (RNN), which has problems such as lengthy computation and backpropagation. This paper describes a model based on a Transformer, which has shown success in computer vision. The study area is divided into grids, and the structure of travel data is converted into video frames by time period, based on predicted spatiotemporal travel demand. The predictions of the model are closest to the real data in terms of spatial distribution and travel demand when the data are divided into 10 min intervals, and the travel demand in the first two hours is used to predict demand in the next hour. We experimentally compare the proposed model with the three most commonly used spatiotemporal prediction models, and the results show that our model has the best accuracy and training speed.
Corporate Social Responsibility Index for Mine Sites
Authors: Bascompta Marc , Sanmiquel Lluís , Vintró Carla , Yousefian Mohammad
Published: October 2022

A new quantitative index to analyse the corporate social responsibility (CSR) level of mine sites was developed, providing an easy and friendly tool to analyse and apply a continuous improvement approach to CSR levels, being able to involve all the potential stakeholders. The index can be used in any type of project and stage: prospecting and exploration, development, mining, processing, closure and rehabilitation. The system consists of two dimensions, environment and socio-economic, formed by 30 elements that analyse potential positive and negative impacts. Moreover, it can be adapted to the specific characteristics of any mining activity, including new elements if necessary. The system proposed can help to improve the positive implications of the mining industry, as well as improving transparency or stakeholder engagement and returns of the mining activity.
Effect of Different Activators on Properties of Slag-Gold Tailings-Red Mud Ternary Composite
Authors: Cui Haonan , Cheng Haili , Huang Tianyong , Yang Feihua , Lan Haoxiang , Li Jvlun
Published: October 2022

Red mud is a kind of solid waste produced in the process of aluminum extraction. Traditional methods of red mud treatment, such as open-pit accumulation and chemical recovery, are costly and environmentally hazardous. Gold tailings are industrial by-products produced in the process of gold mining and refining. In this study, NaOH, KOH, and Na2SiO3 were used as activators, and their effects on the properties of ternary cementitious composite containing blast furnace’s slag, gold tailings, and red mud were studied with the intention of preparing a new cementitious material that is an efficient recovery and utilization of solid waste. The macroscopic mechanical properties and hydration of the ternary cementation material were studied by means of compressive strength, XRD, FT-IR, and TG/DTG. The compressive strength testing showed that the maximum strength at 28 d was 43.5 MPa. The hydration products in the ternary cementitious system were studied by SEM and EDS, and it has been demonstrated that the strength of this cement was due to the formation of Aft (AFt, also known as Ettringite, has the chemical formula 3CaO·Al2O3·3CaSO4·32H2O. It is one of the important hydration products of cement-based cementitious materials, which can not only provide early strength for cement, but also compensate for early shrinkage of concrete.) and C-A-S-H gels. Samples activated by Na2SiO3 presented a most compact microstructure and the best macroscopic mechanical properties than the samples free of activator. The toxicity tests results showed that the content of heavy metal ions liberated by the cement’s leaching met the standard requirements, proving that the slag-gold tailings-red mud ternary composite was environmentally friendly.
Proline-Induced Modifications in Morpho-Physiological, Biochemical and Yield Attributes of Pea (Pisum sativum L.) Cultivars under Salt Stress
Authors: Shahid Sadia , Shahbaz Muhammad , Maqsood Muhammad Faisal , Farhat Fozia , Zulfiqar Usman , Javed Talha , Fraz Ali Muhammad , Alhomrani Majid , Alamri Abdulhakeem S.
Published: October 2022

Climate change is aggravating soil salinity, causing huge crop losses around the globe. Multiple physiological and biochemical pathways determine the ability of plants to tolerate salt stress. A pot experiment was performed to understand the impact of proline levels, i.e., 0, 10, 20 mM on growth, biochemical and yield attributes of two pea (Pisum sativum L.) cultivars (cv. L-888 and cv. Round) under salt stress (150 mM) along with control (0 mM; no stress). The pots were filled with river-washed sand; all the plants were irrigated with full-strength Hoagland’s nutrient solution and grown for two weeks before application of salt stress. Foliar spray of proline was applied to 46-day-old pea plants, once a week till harvest. Data for various growth and physio-biochemical attributes were collected from 70-day-old pea plants. Imposition of salt stress significantly checked growth, gas exchange characteristics [net CO2 assimilation rate (A), transpiration rate (E), stomatal conductance (gs)], total soluble proteins, concentration of superoxide dismutase (SOD), shoot and root K+ and Ca2+ contents, while sub-stomatal CO2 concentration (Ci), coefficient of non-photochemical quenching (qN), non-photochemical quenching (NPQ), concentration of catalase (CAT) and peroxidase (POD), free proline, and shoot and root Na+ contents increased substantially. Foliar application of proline significantly improved growth, yield, A, gs, activity of POD, and shoot and root K+ and Ca2+ contents, while decreased NPQ values in both pea cultivars under stress and non-stress conditions. Moreover, both pea cultivars showed significant differences as cv. Round exhibited a higher rate of growth, yield, gas exchange, soluble proteins, CAT activity, free proline, shoot and root K+ and Ca2+ contents compared to L-888. Hence, the outcomes of this study pave the way toward the usage of proline at 20 mM, and cv. Round may be recommended for saline soil cultivation.
Infosphere Is Reshaping: How the Internet of Things Leads Smart Campuses for Knowledge Management
Authors: Alblaihed Munthir A. , Ibrahem Usama M. , Altamimi Ahmed B. , Alqirnas Hind R. , Salem Magdy I.
Published: October 2022

This article gauges Saudi universities’ readiness to integrate the Internet of Things (IoT) in knowledge management (KM) and identifies the challenges relating to its use. A descriptive–analytical approach was used to discuss the concepts, development, and general structure that characterize the IoT and its related challenges and to find ways to address them. This study used a three-axis questionnaire, which was applied to 275 faculty members and information technology officials in Saudi universities. The results revealed that a strategy related to the development of infrastructure and the provision of equipment and applications to deal with and analyze big data is needed, besides the conviction of the faculty and specialists in its potential in developing the teaching and learning environment in universities and providing unique research by interlinking the network of laboratories and research and training laboratories. The results also revealed that its effects on the university learning environment are gender, rank, and experience agonistic. Finally, 12 main criteria and 44 sub-applications were reached to manage the smart campus’s information generated by the IoT.
The Environmental Impact of Major Sport Events (Giga, Mega and Major): A Systematic Review from 2000 to 2021
Authors: Cerezo-Esteve Sergi , Inglés Eduard , Segui-Urbaneja Jordi , Solanellas Francesc
Published: October 2022

In the context of the Sustainable Development Goals interest and concerns about the environmental impact of major sporting events have become increasingly widespread, voiced not only by organizers, but also spectators and residents of affected areas, as well politicians and institutional representatives of the host territories. There are multiple studies of the economic, social, and legal impacts of major sport events. Although several studies have pointed to a range of environmental impacts, there is no clear consensus on the effects that a major event can have on the natural environment. Thus, the aim of this article is to carry out a systematic review of the state of the art. Following the steps proposed by the PRISMA protocol, a selection of scientific articles from between 2000 and 2021 was made. The overall analysis shows that the negatives outweigh the positives, as only 32.91% of the effects described in the articles are deemed to be positive, with 62.03% deemed to be negative, and finally, 5.06% found to be inconclusive. With varying degrees of success, organizers and promoters of major events are already attempting measures to reduce negative impacts and enhance positive ones.
Relationship between Soil Organic Carbon, Soil Nutrients, and Land Use in Linyi City (East China)
Authors: Wu Xiyuan , Wang Lizhi , An Juan , Wang Yun , Song Hongli , Wu Yuanzhi , Liu Qianjin
Published: October 2022

The distribution characteristics of soil organic carbon (SOC) and soil nutrients under different land-use types in Linyi City, East China, were studied. The spatial distribution of SOC under different land-use types and the relationship between SOC and soil nutrients were analyzed using remote sensing interpretation and soil sample analyses. The results showed that SOC in Linyi was mainly stored in drylands and paddy fields. SOC and total nitrogen (TN) levels were positively correlated for most land use types. There was a positive linear correlation between SOC and total K in the paddy fields. The coefficients of variation for SOC and TN differed greatly among the land use types studied. Total SOC storage was 8772.73 × 103 kg in the surface 0.2 m soil layer. The order of total SOC storage was drylands (6771.45 × 103 ton) > paddy field (764.67 × 103 ton) > nurseries (510.79 × 103 ton) > forest land (413.49 × 103 ton) > low-cover grasslands (238 × 103 ton) > bare land (74.35 × 103 ton). With the largest SOC storage, and C density, respectively, drylands and paddy fields are conducive to enhancing soil C sequestration, achieving low-carbon goals, and mitigating climate change.
Demographic Spatialization Simulation under the Active “Organic Decentralization Population” Policy
Authors: Liu Fang , Sun Weilun , Peng Ge
Published: October 2022

A matter of considerable concern is managing rapid population growth in a growing megacity. After years of endeavor, the “decentralize and population cap” policy has finally been implemented and has achieved some success in Beijing, China. Before applying what has been learnt from this experience to other places, two questions remain to be addressed: “Can urbanization result in land-population harmony under the double effects of accessible guiding plans and invisible push-pull forces?” and “What will be the likely geo-simulation of population density resulting from a city decentralization process?” Under the guidance of “orderly city development” theory, our research (1) simulated the effects of the “organic population decentralization” policy on future population density dynamics; (2) proposed a new framework that coupled models of Verhulst logistic differential population and Cellular Auto-Markov; and (3) analyzed the steering effect of the policy toward a spatial population distribution that could be described as “spread through decentralization.” The results showed that Beijing is currently at the beginning of the “suburbanization” stage. This study can help geographers obtain an innovative method that couples the existing spatial population patterns and the potential population size, which is beneficial for urban planners in determining the spatial structure of a relative equilibrium status for urban development.