bluuebunny/crossref_metadata_2025 huggingface dataset:
Development of a High-Power Capacity Open Source Electrical Stimulation System to Enhance Research into FES-Assisted Devices: Validation of FES Cycling
Authors: Coelho-Magalhães Tiago , Fachin-Martins Emerson , Silva Andressa , Azevedo Coste Christine , Resende-Martins Henrique
Published: January 2022

Since the first Cybathlon 2016, when twelve teams competed in the FES bike race, we have witnessed a global effort towards the development of stimulation and control strategies to improve FES-assisted devices, particularly for cycling, as a means to practice a recreational physical activity. As a result, a set of technical notes and research paved the way for many other studies and the potential behind FES-assisted cycling has been consolidated. However, engineering research needs instrumented devices to support novel developments and enable precise assessment. Therefore, some researchers struggle to develop their own FES-assisted devices or find it challenging to implement their instrumentation using commercial devices, which often limits the implementation of advanced control strategies and the possibility to connect different types of sensor. In this regard, we hypothesize that it would be advantageous for some researchers in our community to enjoy access to an entire open-source FES platform that allows different control strategies to be implemented, offers greater adaptability and power capacity than commercial devices, and can be used to assist different functional activities in addition to cycling. Hence, it appears to be of interest to make our proprietary electrical stimulation system an open-source device and to prove its capabilities by addressing all the aspects necessary to implement a FES cycling system. The high-power capacity stimulation device is based on a constant current topology that allows the creation of biphasic electrical pulses with amplitude, width, and frequency up to 150 mA, 1000 µs, and 100 Hz, respectively. A mobile application (Android) was developed to set and modify the stimulation parameters of up to eight stimulation channels. A proportional-integral controller was implemented for cadence tracking with the aim to improve the overall cycling performance. A volunteer with complete paraplegia participated in the functional testing of the system. He was able to cycle indoors for 45 min, accomplish distances of more than 5 km using a passive cycling trainer, and pedal 2400 m overground in 32 min. The results evidenced the capacity of our FES cycling system to be employed as a cycling tool for individuals with spinal cord injury. The methodological strategies used to improve FES efficiency suggest the possibility of maximizing pedaling duration through more advanced control techniques.
Lightweight Payload Encryption-Based Authentication Scheme for Advanced Metering Infrastructure Sensor Networks
Authors: Abosata Nasr , Al-Rubaye Saba , Inalhan Gokhan
Published: January 2022

The Internet of Things (IoT) connects billions of sensors to share and collect data at any time and place. The Advanced Metering Infrastructure (AMI) is one of the most important IoT applications. IoT supports AMI to collect data from smart sensors, analyse and measure abnormalities in the energy consumption pattern of sensors. However, two-way communication in distributed sensors is sensitive and tends towards security and privacy issues. Before deploying distributed sensors, data confidentiality and privacy and message authentication for sensor devices and control messages are the major security requirements. Several authentications and encryption protocols have been developed to provide confidentiality and integrity. However, many sensors in distributed systems, resource constraint smart sensors, and adaptability of IoT communication protocols in sensors necessitate designing an efficient and lightweight security authentication scheme. This paper proposes a Payload Encryption-based Optimisation Scheme for lightweight authentication (PEOS) on distributed sensors. The PEOS integrates and optimises important features of Datagram Transport Layer Security (DTLS) in Constrained Application Protocol (CoAP) architecture instead of implementing the DTLS in a separate channel. The proposed work designs a payload encryption scheme and an Optimised Advanced Encryption Standard (OP-AES). The PEOS modifies the DTLS handshaking and retransmission processes in PEOS using payload encryption and NACK messages, respectively. It also removes the duplicate features of the protocol version and sequence number without impacting the performance of CoAP. Moreover, the PEOS attempts to improve the CoAP over distributed sensors in the aspect of optimised AES operations, such as parallel execution of S-boxes in SubBytes and delayed Mixcolumns. The efficiency of PEOS authentication is evaluated on Conitki OS using the Cooja simulator for lightweight security and authentication. The proposed scheme attains better throughput while minimising the message size overhead by 9% and 23% than the existing payload-based mutual authentication PbMA and basic DTLS/CoAP scheme in random network topologies with less than 50 nodes.
Cybersecurity Enterprises Policies: A Comparative Study
Authors: Mishra Alok , Alzoubi Yehia Ibrahim , Gill Asif Qumer , Anwar Memoona Javeria
Published: January 2022

Cybersecurity is a critical issue that must be prioritized not just by enterprises of all kinds, but also by national security. To safeguard an organization’s cyberenvironments, information, and communication technologies, many enterprises are investing substantially in cybersecurity these days. One part of the cyberdefense mechanism is building an enterprises’ security policies library, for consistent implementation of security controls. Significant and common cybersecurity policies of various enterprises are compared and explored in this study to provide robust and comprehensive cybersecurity knowledge that can be used in various enterprises. Several significant common security policies were identified and discussed in this comprehensive study. This study identified 10 common cybersecurity policy aspects in five enterprises: healthcare, finance, education, aviation, and e-commerce. We aimed to build a strong infrastructure in each business, and investigate the security laws and policies that apply to all businesses in each sector. Furthermore, the findings of this study reveal that the importance of cybersecurity requirements differ across multiple organizations. The choice and applicability of cybersecurity policies are determined by the type of information under control and the security requirements of organizations in relation to these policies.
A Lightweight Passive Human Tracking Method Using Wi-Fi
Authors: Fang Jian , Wang Lei , Qin Zhenquan , Lu Bingxian , Zhao Wenbo , Hou Yixuan , Chen Jenhui
Published: January 2022

Target tracking is a critical technique for localization in an indoor environment. Current target-tracking methods suffer from high overhead, high latency, and blind spots issues due to a large amount of data needing to be collected or trained. On the other hand, a lightweight tracking method is preferred in many cases instead of just pursuing accuracy. For this reason, in this paper, we propose a Wi-Fi-enabled Infrared-like Device-free (WIDE) method for target tracking to realize a lightweight target-tracking method. We first analyze the impact of target movement on the physical layer of the wireless link and establish a near real-time model between the Channel State Information (CSI) and human motion. Secondly, we make full use of the network structure formed by a large number of wireless devices already deployed in reality to achieve the goal. We validate the WIDE method in different environments. Extensive evaluation results show that the WIDE method is lightweight and can track targets rapidly as well as achieve satisfactory tracking results.
Deep Learning Approach for Automatic Microaneurysms Detection
Authors: Mateen Muhammad , Malik Tauqeer Safdar , Hayat Shaukat , Hameed Musab , Sun Song , Wen Junhao
Published: January 2022

In diabetic retinopathy (DR), the early signs that may lead the eyesight towards complete vision loss are considered as microaneurysms (MAs). The shape of these MAs is almost circular, and they have a darkish color and are tiny in size, which means they may be missed by manual analysis of ophthalmologists. In this case, accurate early detection of microaneurysms is helpful to cure DR before non-reversible blindness. In the proposed method, early detection of MAs is performed using a hybrid feature embedding approach of pre-trained CNN models, named as VGG-19 and Inception-v3. The performance of the proposed approach was evaluated using publicly available datasets, namely “E-Ophtha” and “DIARETDB1”, and achieved 96% and 94% classification accuracy, respectively. Furthermore, the developed approach outperformed the state-of-the-art approaches in terms of sensitivity and specificity for microaneurysms detection.
Precise Monitoring of Soil Salinity in China’s Yellow River Delta Using UAV-Borne Multispectral Imagery and a Soil Salinity Retrieval Index
Authors: Yu Xinyang , Chang Chunyan , Song Jiaxuan , Zhuge Yuping , Wang Ailing
Published: January 2022

Monitoring salinity information of salinized soil efficiently and precisely using the unmanned aerial vehicle (UAV) is critical for the rational use and sustainable development of arable land resources. The sensitive parameter and a precise retrieval method of soil salinity, however, remain unknown. This study strived to explore the sensitive parameter and construct an optimal method for retrieving soil salinity. The UAV-borne multispectral image in China’s Yellow River Delta was acquired to extract band reflectance, compute vegetation indexes and soil salinity indexes. Soil samples collected from 120 different study sites were used for laboratory salt content measurements. Grey correlation analysis and Pearson correlation coefficient methods were employed to screen sensitive band reflectance and indexes. A new soil salinity retrieval index (SSRI) was then proposed based on the screened sensitive reflectance. The Partial Least Squares Regression (PLSR), Multivariable Linear Regression (MLR), Back Propagation Neural Network (BPNN), Support Vector Machine (SVM), and Random Forest (RF) methods were employed to construct retrieval models based on the sensitive indexes. The results found that green, red, and near-infrared (NIR) bands were sensitive to soil salinity, which can be used to build SSRI. The SSRI-based RF method was the optimal method for accurately retrieving the soil salinity. Its modeling determination coefficient (R2) and Root Mean Square Error (RMSE) were 0.724 and 1.764, respectively; and the validation R2, RMSE, and Residual Predictive Deviation (RPD) were 0.745, 1.879, and 2.211.
Winter Wheat Nitrogen Estimation Based on Ground-Level and UAV-Mounted Sensors
Authors: Song Xiaoyu , Yang Guijun , Xu Xingang , Zhang Dongyan , Yang Chenghai , Feng Haikuan
Published: January 2022

A better understanding of wheat nitrogen status is important for improving N fertilizer management in precision farming. In this study, four different sensors were evaluated for their ability to estimate winter wheat nitrogen. A Gaussian process regression (GPR) method with the sequential backward feature removal (SBBR) routine was used to identify the best combinations of vegetation indices (VIs) sensitive to wheat N indicators for different sensors. Wheat leaf N concentration (LNC), plant N concentration (PNC), and the nutrition index (NNI) were estimated by the VIs through parametric regression (PR), multivariable linear regression (MLR), and Gaussian process regression (GPR). The study results reveal that the optical fluorescence sensor provides more accurate estimates of winter wheat N status at a low-canopy coverage condition. The Dualex Nitrogen Balance Index (NBI) is the best leaf-level indicator for wheat LNC, PNC and NNI at the early wheat growth stage. At the early growth stage, Multiplex indices are the best canopy-level indicators for LNC, PNC, and NNI. At the late growth stage, ASD VIs provide accurate estimates for wheat N indicators. This study also reveals that the GPR with SBBR analysis method provides more accurate estimates of winter wheat LNC, PNC, and NNI, with the best VI combinations for these sensors across the different winter wheat growth stages, compared with the MLR and PR methods.
3D Inductive Frequency Selective Structures Using Additive Manufacturing and Low-Cost Metallization
Authors: Vásquez-Peralvo Juan Andrés , Tamayo-Domínguez Adrián , Pérez-Palomino Gerardo , Fernández-González José Manuel , Wong Thomas
Published: January 2022

The use of additive manufacturing and different metallization techniques for prototyping radio frequency components such as antennas and waveguides are rising owing to their high precision and low costs. Over time, additive manufacturing has improved so that its utilization is accepted in satellite payloads and military applications. However, there is no record of the frequency response in the millimeter-wave band for inductive 3D frequency selective structures implemented by different metallization techniques. For this reason, three different prototypes of dielectric 3D frequency selective structures working in the millimeter-wave band are designed, simulated, and manufactured using VAT photopolymerization. These prototypes are subsequently metallized using metallic paint atomization and electroplating. The manufactured prototypes have been carefully selected, considering their design complexity, starting with the simplest, the square aperture, the medium complexity, the woodpile structure, and the most complex, the torus structure. Then, each structure is measured before and after the metallization process using a measurement bench. The metallization used for the measurement is nickel spray flowed by the copper electroplating. For the electroplating, a detailed table showing the total area to be metallized and the current applied is also provided. Finally, the effectiveness of both metallization techniques is compared with the simulations performed using CST Microwave Studio. Results indicate that a shifted and reduced band-pass is obtained in some structures. On the other hand, for very complex structures, as in the torus case, band-pass with lower loss is obtained using copper electroplating, thus allowing the manufacturing of inductive 3D frequency selective structures in the millimeter-wave band at a low cost.
A CMOS Integrator-Based Clock-Free Time-to-Digital Converter for Home-Monitoring LiDAR Sensors
Authors: He Ying , Park Sung Min
Published: January 2022

This paper presents a nine-bit integrator-based time-to-digital converter (I-TDC) realized in a 180 nm CMOS technology for the applications of indoor home-monitoring light detection and ranging (LiDAR) sensors. The proposed I-TDC exploits a clock-free configuration so as to discard clock-related dynamic power consumption and some notorious issues such as skew, glitch, and synchronization. It consists of a one-dimensional (1D) flash TDC to generate coarse-control codes and an integrator with a peak detection and hold (PDH) circuit to produce fine-control codes. A thermometer-to-binary converter is added to the 1D flash TDC, yielding four-bit coarse codes so that the measured detection range can be represented by nine-bit digital codes in total. Test chips of the proposed I-TDC demonstrate the measured results of the 53 dB dynamic range, i.e., the maximum detection range of 33.6 m and the minimum range of 7.5 cm. The chip core occupies the area of 0.14 × 1.4 mm2, with the power dissipation of 1.6 mW from a single 1.2-V supply.
A Laser-Based Multipass Absorption Sensor for Sub-ppm Detection of Methane, Acetylene and Ammonia
Authors: Duan Wei , Yan Fuwu , Wang Yu , Zhang Hui , Ma Liuhao , Wen Daxin , Wang Wei , Sheng Gang , Wang Qiang
Published: January 2022

A compact, sensitive laser-based absorption sensor for multispecies monitoring of methane (CH4), acetylene (C2H2) and ammonia (NH3) was developed using a compact multipass gas cell. The gas cell is 8.8 cm long and has an effective optical path length of 3.0 m with a sampling volume of 75 mL. The sensor is composed of three fiber-coupled distributed feedback lasers operating near 1512 nm, 1532 nm and 1654 nm, an InGaAs photodetector and a custom-designed software for data acquisition, signal processing and display. The lasers were scanned over the target absorption features at 1 Hz. First-harmonic-normalized wavelength modulation spectroscopy (f = 3 kHz) with the second harmonic detection (WMS-2f/1f) is employed to eliminate the unwanted power fluctuations of the transmitted laser caused by aerosol/particles scattering, absorption and beam-steering. The multispecies sensor has excellent linear responses (R2 > 0.997) within the gas concentration range of 1–1000 ppm and shows a detection limit of 0.32 ppm for CH4, 0.16 ppm for C2H2 and 0.23 ppm for NH3 at 1 s response time. The Allan–Werle deviation analysis verifies the long-term stability of the sensor, indicating a minimal detection limit of 20–34 ppb were achieved after 60–148 s integration time. Flow test of the portable multispecies sensor is also demonstrated in this work.
Lead-Free LiNbO3 Thick Film MEMS Kinetic Cantilever Beam Sensor/Energy Harvester
Authors: Barrientos Gabriel , Clementi Giacomo , Trigona Carlo , Ouhabaz Merieme , Gauthier-Manuel Ludovic , Belharet Djaffar , Margueron Samuel , Bartasyte Ausrine , Malandrino Graziella , Baglio Salvatore
Published: January 2022

In this paper, we present integrated lead-free energy converters based on a suitable MEMS fabrication process with an embedded layer of LiNbO3. The fabrication technology has been developed to realize micromachined self-generating transducers to convert kinetic energy into electrical energy. The process proposed presents several interesting features with the possibility of realizing smaller scale devices, integrated systems, miniaturized mechanical and electromechanical sensors, and transducers with an active layer used as the main conversion element. When the system is fabricated in the typical cantilever configuration, it can produce a peak-to-peak open-circuit output voltage of 0.208 V, due to flexural deformation, and a power density of 1.9 nW·mm−3·g−2 at resonance, with values of acceleration and frequency of 2.4 g and 4096 Hz, respectively. The electromechanical transduction capability is exploited for sensing and power generation/energy harvesting applications. Theoretical considerations, simulations, numerical analyses, and experiments are presented to show the proposed LiNbO3-based MEMS fabrication process suitability. This paper presents substantial contributions to the state-of-the-art, proposing an integral solution regarding the design, modelling, simulation, realization, and characterization of a novel transducer.
How Long Should GPS Recording Lengths Be to Capture the Community Mobility of An Older Clinical Population? A Parkinson’s Example
Authors: Zhu Lynn , Boissy Patrick , Duval Christian , Zou Guangyong , Jog Mandar , Montero-Odasso Manuel , Speechley Mark
Published: January 2022

Wearable global position system (GPS) technology can help those working with older populations and people living with movement disorders monitor and maintain their mobility level. Health research using GPS often employs inconsistent recording lengths due to the lack of a standard minimum GPS recording length for a clinical context. Our work aimed to recommend a GPS recording length for an older clinical population. Over 14 days, 70 older adults with Parkinson’s disease wore the wireless inertial motion unit with GPS (WIMU-GPS) during waking hours to capture daily “time outside”, “trip count”, “hotspots count” and “area size travelled”. The longest recording length accounting for weekend and weekdays was ≥7 days of ≥800 daily minutes of data (14 participants with 156, 483.9 min recorded). We compared the error rate generated when using data based on recording lengths shorter than this sample. The smallest percentage errors were observed across all outcomes, except “hotspots count”, with daily recordings ≥500 min (8.3 h). Eight recording days will capture mobility variability throughout days of the week. This study adds empirical evidence to the sensor literature on the required minimum duration of GPS recording.
Flexible, Fully Printable, and Inexpensive Paper-Based Chipless Arabic Alphabet-Based RFID Tags
Authors: Yousaf Jawad , Almajali Eqab , Najjar Mahmoud El , Amir Ahmed , Altaf Amir , Elahi Manzoor , Alja’afreh Saqer Saleh , Rmili Hatem
Published: January 2022

This work presents the design and analysis of newly developed reconfigurable, flexible, inexpensive, optically-controlled, and fully printable chipless Arabic alphabet-based radio frequency identification (RFID) tags. The etching of the metallic copper tag strip is performed on a flexible simple thin paper substrate (ϵr = 2.31) backed by a metallic ground plane. The analysis of investigated tags is performed in CST MWS in the frequency range of 1–12 GHz for the determination of the unique signature resonance characteristics of each tag in terms of its back-scattered horizontal and vertical mono-static radar cross section (RCS). The analysis reflects that each tag has its own unique electromagnetic signature (EMS) due to the changing current distribution of metallic resonator. This EMS of each tag could be used for the robust detection and recognition of all realized 28 Arabic alphabet tags. The study also discusses, for the first time, the effect of the change in font type and size of realized tags on their EMS. The robustness and reliability of the obtained EMS of letter tags is confirmed by comparing the RCS results for selective letter tags using FDTD and MoM numerical methods, which shows very good agreement. The proposed tags could be used for smart internet of things (IoT) and product marketing applications.
Validating a Traffic Conflict Prediction Technique for Motorways Using a Simulation Approach
Authors: Formosa Nicolette , Quddus Mohammed , Papadoulis Alkis , Timmis Andrew
Published: January 2022

With the ever-increasing advancements in the technology of driver assistant systems, there is a need for a comprehensive way to identify traffic conflicts to avoid collisions. Although significant research efforts have been devoted to traffic conflict techniques applied for junctions, there is dearth of research on these methods for motorways. This paper presents the validation of a traffic conflict prediction algorithm applied to a motorway scenario in a simulated environment. An automatic video analysis system was developed to identify lane change and rear-end conflicts as ground truth. Using these conflicts, the prediction ability of the traffic conflict technique was validated in an integrated simulation framework. This framework consisted of a sub-microscopic simulator, which provided an appropriate testbed to accurately simulate the components of an intelligent vehicle, and a microscopic traffic simulator able to generate the surrounding traffic. Results from this framework show that for a 10% false alarm rate, approximately 80% and 73% of rear-end and lane change conflicts were accurately predicted, respectively. Despite the fact that the algorithm was not trained using the virtual data, the sensitivity was high. This highlights the transferability of the algorithm to similar road networks, providing a benchmark for the identification of traffic conflict and a relevant step for developing safety management strategies for autonomous vehicles.
Augmenting Social Science Research with Multimodal Data Collection: The EZ-MMLA Toolkit
Authors: Schneider Bertrand , Hassan Javaria , Sung Gahyun
Published: January 2022

While the majority of social scientists still rely on traditional research instruments (e.g., surveys, self-reports, qualitative observations), multimodal sensing is becoming an emerging methodology for capturing human behaviors. Sensing technology has the potential to complement and enrich traditional measures by providing high frequency data on people’s behavior, cognition and affects. However, there is currently no easy-to-use toolkit for recording multimodal data streams. Existing methodologies rely on the use of physical sensors and custom-written code for accessing sensor data. In this paper, we present the EZ-MMLA toolkit. This toolkit was implemented as a website and provides easy access to multimodal data collection algorithms. One can collect a variety of data modalities: data on users’ attention (eye-tracking), physiological states (heart rate), body posture (skeletal data), gestures (from hand motion), emotions (from facial expressions and speech) and lower-level computer vision algorithms (e.g., fiducial/color tracking). This toolkit can run from any browser and does not require dedicated hardware or programming experience. We compare this toolkit with traditional methods and describe a case study where the EZ-MMLA toolkit was used by aspiring educational researchers in a classroom context. We conclude by discussing future work and other applications of this toolkit, potential limitations and implications.
Design Space Exploration of a Multi-Model AI-Based Indoor Localization System
Authors: Kotrotsios Konstantinos , Fanariotis Anastasios , Leligou Helen-Catherine , Orphanoudakis Theofanis
Published: January 2022

In this paper, we present the results of a performance evaluation and optimization process of an indoor positioning system (IPS) designed to operate on portable as well as miniaturized embedded systems. The proposed method uses the Received Signal Strength Indicator (RSSI) values from multiple Bluetooth Low-Energy (BLE) beacons scattered around interior spaces. The beacon signals were received from the user devices and processed through an RSSI filter and a group of machine learning (ML) models, in an arrangement of one model per detected node. Finally, a multilateration problem was solved using as an input the inferred distances from the advertising nodes and returning the final position approximation. In this work, we first presented the evaluation of different ML models for inferring the distance between the devices and the installed beacons by applying different optimization algorithms. Then, we presented model reduction methods to implement the optimized algorithm on the embedded system by appropriately adapting it to its constraint resources and compared the results, demonstrating the efficiency of the proposed method.
Finite Impulse Response Filter-Based Track Formation for Preceding Vehicle Tracking Using Automotive Radars
Authors: Pak Jung Min
Published: January 2022

Automotive radars, which are used for preceding vehicle tracking, have attracted significant attention in recent years. However, the false measurements that occur in cluttered roadways hinders the tracking process in vehicles; thus, it is essential to develop automotive radar systems that are robust against false measurements. This study proposed a novel track formation algorithm to initialize the preceding vehicle tracking in automotive radar systems. The proposed algorithm is based on finite impulse response filtering, and exhibited significantly higher accuracy in highly cluttered environments than a conventional track formation algorithm. The excellent performance of the proposed algorithm was demonstrated using extensive simulations under real conditions.
The Stability and Suitability of the Bhasan Char Island as an Accommodation for the Forcibly Displaced Myanmar Nationals (FDMN)
Authors: Gazi Md. , Kamal A. , Uddin Md. , Bhuiyan Md. , Rahman Md.
Published: January 2022

Assessing the dynamics of Bhasan Char is very crucial, as the Government of Bangladesh (GoB) has recently selected the island as the accommodation of the FDMN. This article critically evaluates the spatiotemporal morphological variations due to erosion, accretion, and subsurface deformation of the island through multi-temporal geospatial and geophysical data analysis, groundwater quality-quantity, and also determines the nature and rate of changes from 2003 to 2020. This is the first study in this island on which multi-temporal Landsat Satellite Imagery and seismic data have been used with geospatial techniques with Digital Shoreline Analysis System (DSAS) and petrel platform, respectively. The analysis of satellite images suggests that the island first appeared in 2003 in the Bay of Bengal, then progressively evolved to the present stable condition. Significant changes have taken place in the morphological and geographical conditions of the island since its inception. Since 2012, the island has been constantly accreted by insignificant erosion. It receives tidally influenced fluvial sediments from the Ganges-Brahmaputra-Meghna (GBM) river system and the sedimentary accretion, in this case, is higher than the erosion due to relatively weaker wave action and longshore currents. It has gained approximately 68 km2 area, mostly in the northern part and because of erosion in the south. Although the migration of the Bhasan Char was ubiquitous during 2003–2012, it has been concentrated in a small area to the east since 2018. The net shoreline movements (NSM) suggest that the length of the shoreline enlarged significantly by around 39 km in 2020 from its first appearance. Seismic and GPS data clearly indicate that the island is located on the crest of a slowly uplifting low-amplitude anticline, which may result in a stable landform around the island. Based on the analysis of historical data, it has been assessed that the current configuration of Bhasan Char would not be severely affected by 10–15-foot-high cyclone. Therefore, FDMN rehabilitation here might be safer that would be a good example for future geo-environmental assessment for any areas around the world for rehabilitation of human in remote and vulnerable island. The findings of this research will facilitate the government’s decision to rehabilitate FDMN refugees to the island and also contribute to future research in this area.
The Potential of Blockchain Technology in Higher Education as Perceived by Students in Serbia, Romania, and Portugal
Authors: Kuleto Valentin , Bucea-Manea-Țoniş Rocsana , Bucea-Manea-Țoniş Radu , Ilić Milena P. , Martins Oliva M. D. , Ranković Marko , Coelho Ana Sofia
Published: January 2022

Lifelong learning approaches that include digital, transversal, and practical skills (i.e., critical thinking, communication, collaboration, information literacy, analytical, metacognitive, reflection, and other research skills) are required in order to be equitable and inclusive and stimulate personal development. Realtime interaction between teachers and students and the ability for students to choose courses from curricula are guaranteed by decentralized online learning. Moreover, through blockchain, it is possible to acquire skills regarding the structure and content while also implementing learning tools. Additionally, documentation validation should be equally crucial to speeding up the process and reducing costs and paperwork. Finally, blockchains are open and inclusive processes that include people and cultures from all walks of life. Learning in Higher Education Institutions (HEI) is facilitated by new technologies, connecting blockchain to sustainability, which helps understand the relationship between technologies and sustainability. Besides serving as a secure transaction system, blockchain technology can help decentralize, provide security and integrity, and offer anonymity and encryption, therefore, promoting a transaction rate increase. This study investigates an alternative in which HEI include a blockchain network to provide the best sustainable education system. Students’ opinions were analyzed, and they considered that blockchain technology had a very positive influence on learning performance.
Lantana camara: Poisonous Species and a Potential Browse Species for Goats in Southern Africa—A Review
Authors: Ntalo Malizo , Ravhuhali Khuliso Emmanuel , Moyo Bethwell , Hawu Onke , Msiza Ntokozo Happy
Published: January 2022

Among the possible impacts of plant invaders on South African biodiversity, water supplies, and rangeland production, Lantana camara is ranked the highest in terms of its environmental impact. Globally, L. camara is regarded as one of the most ecologically and economically destructive invasive alien plants. The spread of L. camara affects the environment and threatens livestock productivity due to its toxicity to animals (especial cattle and sheep) in most semi-arid areas of South Africa. Lantana camara is known to have high concentrations of nutrients that are beneficial to livestock, but most previous research has concentrated on its toxicity. To enrich our knowledge on its nutritive value, further research has to evaluate its dietary impact on the growth and health of different ruminant livestock species, particularly goats. This review evaluates L. camara as a potential browse species for goats in southern Africa, and its adverse effects on goats and other ruminant livestock are also presented. The review describes L. camara and its distribution globally, its poisonous effect to livestock, and potential use as an alternative forage to browsing animals such as goats, which have proved resistant to its harmful traits. The high crude protein content, low fibre and adequate macro-minerals for small ruminants makes L. camara a good ruminant protein supplement in semi-arid areas. In addition to other biological control strategies, the prospects of using goats as a biological management tool is discussed. The research will contribute to the understanding of the control measures of L. camara while improving the productivity of small stock, especially goats. This means that a balanced understanding of its nutritional value as a source of protein and its negative impact on the environment should be considered in developing mitigation strategies to arrest its spread. We, therefore, recommend the use of goats in the control of L. camara; however, further studies are needed to limit its toxic effects, and thus improve its value.
Modification of Freezing Point for Hydrogel Extinguishant and Its Effect on Comprehensive Properties in Simulated Forest Fire Rescue
Authors: Han Ziwei , Chen Peiyao , Hou Meifang , Li Qianqian , Su Guijin , Meng Jing , Shi Bin , Deng Jie
Published: January 2022

Hydrogels, as an emerging extinguishant, exhibit outstanding performance in forest fire rescues. However, the near-zero freezing point limits their application at low temperatures. Herein, a sensible candidate commercial extinguishant was selected for analysis, and its freezing point was modified based on the evaluation of water absorption rate, agglomeration, viscosity, and water dispersibility. Notably, the introduction of different antifreeze and flame retardant exhibited a significant disparate impact on the viscosity representative factor. Ten orthogonal experiments were performed to optimize the specific formulation. When ethylene glycol, urea and ammonium bicarbonate, and xanthan gum were applied as antifreeze, flame retardant, and thickener, with the addition amounts of 5 mL, 0.08 g and 0.04 g, and 0.12 g, respectively, the hydrogel extinguishant with 1% ratio in 50 mL of ultra-water featured the remarkable performance. Compared with the original extinguishant, the freezing point of the modified sample decreased from −0.3 to −9.2 °C. The sample’s viscosity was improved from 541 to 1938 cP, and the flame retardance time was more than 120 s. The results of corrosion and biotoxicity show that the optimized hydrogel extinguishant satisfies the national standards. This understanding provides a deeper insight into the application of low-temperature extinguishants in forest fires.
Assessing Relations between Cultural Ecosystem Services, Physical Landscape Features and Accessibility in Central-Eastern Europe: A PPGIS Empirical Study from Hungary
Authors: Valánszki István , Kristensen Lone Søderkvist , Jombach Sándor , Ladányi Márta , Filepné Kovács Krisztina , Fekete Albert
Published: January 2022

Despite the growing quantity of ecosystem-services-related research, there is still a lack of deeper understanding on cultural ecosystem services (CES). This is mainly due to the perception of CES, which can vary by geographic location and population. In this study, we present a Public Participation Geographic Information System (PPGIS) method in a Hungarian microregion. Our goal is to increase understanding on how cultural services are perceived in this geographical context and level, and how this relative importance is related to biophysical landscape features. We also consider the influence of accessibility on the perceived landscape and compare our findings with the results of other studies with different sociocultural backgrounds. The research consists of participatory mapping with 184 persons that were digitized and analyzed with GIS and statistical software. During the analysis, we identified CES hotspots and compared CES with landscape features, as well as CES perception with accessibility. Our results showed positive correlation of CES with land covers related to built-up areas, as well as aesthetic and recreational services with water bodies. Compared to other studies, we found different spatial relationships in the case of spiritual services, and higher importance of agricultural land covers during the CES perception, thanks to the Central-Eastern European (CEE) sociocultural background. Our study highlights the effect of accessibility on CES perception; nevertheless, these relationships varied by different infrastructural elements. We conclude by discussing the implications and limitations of our study and encouraging future landscape research to apply the PPGIS method in this geographical context.
What Is the Impact of Mass Timber Utilization on Climate and Forests?
Authors: Pasternack Rachel , Wishnie Mark , Clarke Caitlin , Wang Yangyang , Belair Ethan , Marshall Steve , Gu Hongmei , Nepal Prakash , Dolezal Franz , Lomax Guy , Johnston Craig , Felmer Gabriel , Morales-Vera Rodrigo , Puettmann Maureen , Van den Huevel Robyn
Published: January 2022

As the need to address climate change grows more urgent, policymakers, businesses, and others are seeking innovative approaches to remove carbon dioxide emissions from the atmosphere and decarbonize hard-to-abate sectors. Forests can play a role in reducing atmospheric carbon. However, there is disagreement over whether forests are most effective in reducing carbon emissions when left alone versus managed for sustainable harvesting and wood product production. Cross-laminated timber is at the forefront of the mass timber movement, which is enabling designers, engineers, and other stakeholders to build taller wood buildings. Several recent studies have shown that substituting mass timber for steel and concrete in mid-rise buildings can reduce the emissions associated with manufacturing, transporting, and installing building materials by 13%-26.5%. However, the prospect of increased utilization of wood products as a climate solution also raises questions about the impact of increased demand for wood on forest carbon stocks, on forest condition, and on the provision of the many other critical social and environmental benefits that healthy forests can provide. A holistic assessment of the total climate impact of forest product demand across product substitution, carbon storage in materials, current and future forest carbon stock, and forest area and condition is challenging, but it is important to understand the impact of increased mass timber utilization on forests and climate, and therefore also on which safeguards might be necessary to ensure positive outcomes. To thus assess the potential impacts, both positive and negative, of greater mass timber utilization on forests ecosystems and emissions associated with the built environment, The Nature Conservancy (TNC) initiated a global mass timber impact assessment (GMTIA), a five-part, highly collaborative research program focused on understanding the potential benefits and risks of increased demand for mass timber products on forests and identifying appropriate safeguards to ensure positive outcomes.
Nowcasting Entrepreneurship: Urban Third Place versus the Creative Class
Authors: Fang Li , Slaper Timothy
Published: January 2022

Researchers have long debated whether entrepreneurship policy should focus on place or people. In this paper, we extend the place-based versus people-based theories using contemporaneous and geographically granular web-user online activity data to predict a region’s proclivity for entrepreneurship. We compare two theoretical hypotheses: the urban third places—informal gathering locations—that facilitate social interaction and entrepreneurship, in contrast to the creative class which fosters entrepreneurial energy and opportunity in a region. Specifically, we assess whether business formation has a stronger statistical relationship with the browsing behavior of individuals visiting websites associated with third place locations—e.g., restaurants or bars—or the concentration of web browsing behavior associated with “the creative class”. Using U.S. county-level data, we find that both urban third places and the creative class can predict about 70% of the variations in regional business formation, with the creative class having a slight competitive edge.
Differences in Teachers’ Professional Action Competence in Education for Sustainable Development: The Importance of Teacher Co-Learning
Authors: Isac Maria Magdalena , Sass Wanda , Pauw Jelle Boeve-de , De Maeyer Sven , Schelfhout Wouter , Van Petegem Peter , Claes Ellen
Published: January 2022

This study builds on a research-practitioner partnership embedded within an education for sustainable development (ESD) project and aims to explore the major potential challenges (i.e., disciplinary boundaries set by subject specialization, especially in secondary education) and success factors (i.e., teacher co-learning experiences in ESD) associated with differences in teachers’ professional action competence (PACesd) in a sample of 557 in-service teachers in primary and secondary schools in Flanders, Belgium. The study employed a recently validated PACesd measurement instrument and involved quantitative data analysis in a structural equation modelling framework. The results show that primary education teachers tend to report higher PACesd levels compared to their peers in secondary education. Moreover, regardless of educational level, gender and teaching experience, all teachers participating in a working group or a learning community in ESD are more likely to show higher levels of PACesd. Implications of the findings, limitations and directions for future research are discussed.
Mobility Patterns and Mode Choice Preferences during the COVID-19 Situation
Authors: Monterde-i-Bort Hector , Sucha Matus , Risser Ralf , Kochetova Tatiana
Published: January 2022

The empirical research on the COVID-19 epidemic’s consequences suggests a major drop in human mobility and a significant shift in travel patterns across all forms of transportation. We can observe a shift from public transport and an increase in car use, and in some cases also increase of cycling and (less often) walking. Furthermore, it seems that micromobility and, more generally, environmentally friendly and comanaged mobility (including shared services), are gaining ground. In previous research, much attention was paid to the mode choice preferences during lockdown, or early stages of the SARS-CoV-2 situation. The blind spot, and aim of this work, is how long observed changes in mode choice last and when or if we can expect the mode choice to shift back to the situation before the SARS-CoV-2 episodes. The research sample consisted of 636 cases; in total, 10 countries contributed to the sample examined in this study. The data were collected in two phases: the first in the spring of 2020 and the second in the fall of the same year. Results showed that respondents reduced mobility by car, local public transport and walking, but not bicycling during the lockdown, compared to the time before the pandemic started. When the easing came, respondents assessed their own use of the car and walking as almost back to normal. They also reported an increase in the use of public transport, but not reaching the level prior the pandemic by far. It seems that cycling was affected least by the pandemic; use of a bicycle hardly changed at all. As for the implication of our study, it is evident that special attention and actions will be needed to bring citizens back to public transport, as it seems that the impact of the pandemic on public transport use will last much longer than the pandemic itself.
Human Rights and Socio-Environmental Conflicts of Mining in Mexico: A Systematic Review
Authors: Camacho-Garza Abraham , Acevedo-Sandoval Otilio A. , Otazo-Sánchez Elena Ma. , Roman-Gutiérrez Alma D. , Prieto-García Francisco
Published: January 2022

Socio-environmental conflicts are situations that exemplify human rights transgressions caused by extractive activities. These are present in developing countries where extractivism, imperialism, and colonialism paradigms prevail. In the context of Mexico, criminalization, violence, and the absence of rule of law promote these conflicts, frequently aggravated by involvement with private interests. In the last 20 years, the relationship between human rights in the mining sector and its impact on the environment has been a critical research subject. This paper aims to carry out a systematic review to analyze human rights transgressions related to the mining industry’s impact in Mexico, and identify factors causing socio-environmental conflicts. The current study shows a systematic analysis based on the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) methodology. This method contributed to the collection of references that describe conflicts due to human rights transgressions and environmental damage in mining areas in Mexico. Human rights transgressions caused by mining in a Mexican context demonstrate the inability of the state to stop the increase in socio-environmental conflicts and its lack of concern towards preventing damage to the environment.
The Analysis of Company Growth Determinants Based on Financial Statements of the European Companies
Authors: Vuković Bojana , Peštović Kristina , Mirović Vera , Jakšić Dejan , Milutinović Sunčica
Published: January 2022

The primary aim of this paper is to determine the indicators that have an influence on the company growth in the field of agriculture, forestry, and fisheries during the six-year period (2014–2019). This sector is very important for sustainable development, bearing in mind the need to preserve natural resources, i.e., land, water, plant, and animal resources. Sustainable development of this sector is of satisfactory technical-technological development, economically sustainable, and socially acceptable. The sample consists of 1333 observations of active companies on the European market. Multiple regression analysis was used in order to thoroughly analyze the variables of growth. The obtained results showed that company size has a negative impact on growth, while return on assets and leverage have a positive impact on growth. The impact of these variables was statistically significant. Along with the influence of observed determinants based on data from financial statements, the future growth and development of companies in this sector will certainly depend on the volume of investments, pricing policy, credit and natural conditions, agricultural policy measures, and adequate institutional support through the provision of financial support and encouragement of exports of products. Institutional incentives for more intensive integration of the agriculture, forestry, and fisheries sector are aimed at achieving the concept of integrated sustainable development.