bluuebunny/crossref_metadata_2025 huggingface dataset:
Biological Properties of Transition Metal Complexes with Metformin and Its Analogues
Authors: Rusanov Daniil A. , Zou Jiaying , Babak Maria V.
Published: April 2022

Metformin is a widely prescribed medication for the treatment and management of type 2 diabetes. It belongs to a class of biguanides, which are characterized by a wide range of diverse biological properties, including anticancer, antimicrobial, antimalarial, cardioprotective and other activities. It is known that biguanides serve as excellent N-donor bidentate ligands and readily form complexes with virtually all transition metals. Recent evidence suggests that the mechanism of action of metformin and its analogues is linked to their metal-binding properties. These findings prompted us to summarize the existing data on the synthetic strategies and biological properties of various metal complexes with metformin and its analogues. We demonstrated that coordination of biologically active biguanides to various metal centers often resulted in an improved pharmacological profile, including reduced drug resistance as well as a wider spectrum of activity. In addition, coordination to the redox-active metal centers, such as Au(III), allowed for various activatable strategies, leading to the selective activation of the prodrugs and reduced off-target toxicity.
Particle Engineering by Nano Spray Drying: Optimization of Process Parameters with Hydroethanolic versus Aqueous Solutions
Authors: Almansour Khaled , Ali Raisuddin , Alheibshy Fawaz , Almutairi Tariq J. , Alshammari Rakan F. , Alhajj Nasser , Arpagaus Cordin , Elsayed Mustafa M.A.
Published: April 2022

Nano spray drying has emerged as an outstanding platform for engineering micro- and nanoparticles, with growing applications in various areas of drug delivery. As a new technology involving distinct technical design, parameters of the nano spray drying process are not fully elucidated. In a quality-by-design approach, the aim of the current study was to gain thorough understanding of critical determinants of product characteristics in the Büchi Nano Spray Dryer B-90. Following a factorial experimental design, a series of spray drying experiments were conducted to gain new insights into the influences of the inlet temperature, the spray solvent, and the solute concentration in the spray solution on the yield, the moisture content, and the particle size of the nano spray-dried powder material. Special consideration was given to the potential of using hydroethanolic in comparison with aqueous solvent systems and to particle engineering for pulmonary drug delivery. Lactose and mannitol, widely used as excipients in dry powder inhalation formulations, were used as model materials. Lactose and mannitol are known to spray dry in amorphous and crystalline forms, respectively. The yields of spray drying of lactose and mannitol amounted generally to 71.1 ± 6.6% w/w and 66.1 ± 3.5% w/w, respectively. The spray-dried materials exhibited generally a number-weighted median particle diameter of 1.6 ± 0.2 μm and a volume-weighted median particle diameter of 5.1 ± 1.0 μm. A detailed analysis of the results improved understanding of the interplay between process parameters in the Nano Spray Dryer. The results demonstrate that optimization of spray generation is the key to yield optimization. On the other hand, particle size is determined by the spray mesh pore size and the spray solution degree of saturation. Selection of an appropriate spray solvent and using spray solution additives could optimize spray flow. In parallel, the spray solvent and the solute concentration in the spray solution determine the degree of saturation. Guidance on optimization of particle engineering by nano spray drying is provided.
Application of Nanomaterials in the Prevention, Detection, and Treatment of Methicillin-Resistant Staphylococcus aureus (MRSA)
Authors: Hulme John
Published: April 2022

Due to differences in geographic surveillance systems, chemical sanitization practices, and antibiotic stewardship (AS) implementation employed during the COVID-19 pandemic, many experts have expressed concerns regarding a future surge in global antimicrobial resistance (AMR). A potential beneficiary of these differences is the Gram-positive bacteria MRSA. MRSA is a bacterial pathogen with a high potential for mutational resistance, allowing it to engage various AMR mechanisms circumventing conventional antibiotic therapies and the host’s immune response. Coupled with a lack of novel FDA-approved antibiotics reaching the clinic, the onus is on researchers to develop alternative treatment tools to mitigate against an increase in pathogenic resistance. Mitigation strategies can take the form of synthetic or biomimetic nanomaterials/vesicles employed in vaccines, rapid diagnostics, antibiotic delivery, and nanotherapeutics. This review seeks to discuss the current potential of the aforementioned nanomaterials in detecting and treating MRSA.
Model-Based Product Temperature and Endpoint Determination in Primary Drying of Lyophilization Processes
Authors: Juckers Alex , Knerr Petra , Harms Frank , Strube Jochen
Published: April 2022

Lyophilization process design still relies mainly on empirical studies with high experimental loads. In the regulatory demanded Quality by Design approach, process modeling is a key aspect. It allows process design, optimization and process control to ensure a safe process and product quality. A modeling approach is outlined that is able to predict the primary drying endpoint and temperature profile of distinct vials. Model parameters are determined by a reproducible determination concept. Simulated results are validated with a fractional factorial Design of Experiments (DoE) in pilot scale. The model shows higher accuracy and precision than the experiments and similar parameter interactions for both the endpoint and temperature determination. This approach can now be used to explore the primary design space in lyophilization process design. This paper proposes a distinct method for endpoint determination and product temperature prediction by a modeling approach based on Velardi et al. combined with a distinct model parameter determination according to Wegiel et al. and Tang et al.
Treating Pulmonary Fibrosis with Non-Viral Gene Therapy: From Bench to Bedside
Authors: Huang Teng , Gao Jia , Cai Long , Xie Hao , Wang Yuhan , Wang Yi , Zhou Qing
Published: April 2022

Idiopathic pulmonary fibrosis (IPF) is a chronic, progressive lung disease characterized by irreversible lung scarring, which achieves almost 80% five-year mortality rate. Undeniably, commercially available pharmaceuticals, such as pirfenidone and nintedanib, exhibit certain effects on improving the well-being of IPF patients, but the stubbornly high mortality still indicates a great urgency of developing superior therapeutics against this devastating disease. As an emerging strategy, gene therapy brings hope for the treatment of IPF by precisely regulating the expression of specific genes. However, traditional administration approaches based on viruses severely restrict the clinical application of gene therapy. Nowadays, non-viral vectors are raised as potential strategies for in vivo gene delivery, attributed to their low immunogenicity and excellent biocompatibility. Herein, we highlight a variety of non-viral vectors, such as liposomes, polymers, and proteins/peptides, which are employed in the treatment of IPF. By respectively clarifying the strengths and weaknesses of the above candidates, we would like to summarize the requisite features of vectors for PF gene therapy and provide novel perspectives on design-decisions of the subsequent vectors, hoping to accelerate the bench-to-bedside pace of non-viral gene therapy for IPF in clinical setting.
Non-Heading Chinese Cabbage Database: An Open-Access Platform for the Genomics of Brassica campestris (syn. Brassica rapa) ssp. chinensis
Authors: Li Zhidong , Li Ying , Liu Tongkun , Zhang Changwei , Xiao Dong , Hou Xilin
Published: April 2022

The availability of a high-quality genome sequence of Brassica campestris ssp. chinensis NHCC001 has paved the way for deep mining of genome data. We used the B. campestris NHCC001 draft genome to develop a comprehensive database, known as the non-heading Chinese cabbage database, which provides access to the B. campestris NHCC001 genome data. The database provides 127,347 SSR, from which 382,041 pairs of primers were designed. NHCCDB contains information on 105,360 genes, which were further classified into 63 transcription factor families. Furthermore, NHCCDB provides eight kinds of tools for biological or sequencing data analyses, including sequence alignment tools, functional genomics tools, comparative genomics tools, motif analysis tools, genome browser, primer design, and SSR analysis tools. In addition, eight kinds of graphs, including a box plot, Venn diagram, corrplot, Q-Q plot, Manhattan plot, seqLogo, volcano plot, and a heatmap, can be generated rapidly using NHCCDB. We have incorporated a search system for efficient mining of transcription factors and genes, along with an embedded data submit function in NHCCDB. We believe that the NHCCDB database will be a useful platform for non-heading Chinese cabbage research and breeding.
Sequencing Biodegradable and Potentially Biobased Polyesteramide of Sebacic Acid and 3-Amino-1-propanol by MALDI TOF-TOF Tandem Mass Spectrometry
Authors: Rizzarelli Paola , La Carta Stefania , Mirabella Emanuele Francesco , Rapisarda Marco , Impallomeni Giuseppe
Published: April 2022

Biodegradable and potentially biobased polyesteramide oligomers (PEA-Pro), obtained from melt condensation of sebacic acid and 3-amino-1-propanol, were characterized by nuclear magnetic resonance (NMR), matrix assisted laser desorption/ionization-time of flight/time of flight-mass spectrometry/mass spectrometry (MALDI-TOF/TOF-MS/MS), thermogravimetric analysis (TGA), and pyrolysis-gas chromatography/mass spectrometry (Py-GC/MS). NMR analysis showed the presence of hydroxyl and amino terminal groups as well as carboxylic groups of the sebacate moiety. Hydroxyl and carboxyl termination had the same abundance, while the amine termination was 2.7-times less frequent. Information regarding the fragmentation pathways and ester/amide bond sequences was obtained by MALDI-TOF/TOF-MS/MS analysis performed on sodiated adducts of cyclic species and linear oligomers. Different end groups did not influence the observed fragmentation. Three fragmentation pathways were recognized. The β-hydrogen-transfer rearrangement, which leads to the selective scission of the –O–CH2– bonds, was the main mechanism. Abundant product ions originating from –CH2–CH2– (β–γ) bond cleavage in the sebacate moiety and less abundant ions formed by –O–CO– cleavages were also detected. TGA showed a major weight loss (74%) at 381 °C and a second degradation step (22% weight loss) at 447 °C. Py-GC/MS performed in the temperature range of 350–400 °C displayed partial similarity between the degradation products and the main fragments detected in the MALDI-TOF/TOF-MS/MS experiments. Degradation products derived from amide bonds were related to the formation of CN groups, in agreement with the literature.
Mechanical Behavior of Alkasite Posterior Restorations in Comparison to Polymeric Materials: A 3D-FEA Study
Authors: Ausiello Pietro , Dal Piva Amanda Maria de Oliveira , di Lauro Alessandro Espedito , Garcia-Godoy Franklin , Testarelli Luca , Tribst João Paulo Mendes
Published: April 2022

The present investigation evaluated the effect of the combination of different dental filling materials in Class I cavities under occlusal loading using three-dimensional finite elements analysis (FEA). Six computer-generated and restored models of a lower molar were created in the CAD software and compared according to the biomechanical response during chewing load condition. Two adhesively bonded bulk restorative materials [bulk-fill resin composite (BF) or Alkasite (Alk)] were evaluated with or without the presence of a base material below (flowable resin composite or glass ionomer cement). A food bolus was placed on the occlusal surface mimicking the compressive occlusal load (600 N) during the static linear analysis. The maximum principal stress (tensile) was calculated as stress criteria in enamel, dentin and restoration. All models showed high stresses along the enamel/restoration margin with a similar stress trend for models restored with the same upper-layer material. Stress values up to 12.04 MPa (Alk) or up to 11.12 MPa (BF) were recorded at the enamel margins. The use of flexible polymeric or ionic base material in combination with bulk-fill resin composite or Alk did not reduce the stress magnitude in dentine and enamel. Class I cavities adhesively restored with bulk-fill resin composite showed lighter stress concentration as well as Alk. Therefore, adhesively bonded Alk restoration showed a promising mechanical behavior when used with different base materials or as a bulk restoration for posterior Class I cavity.
Two Layer Sheets for Processing Post-Consumer Materials
Authors: Wittmann Lisa-Maria , Drummer Dietmar
Published: April 2022

An increasing percentage of post-consumer materials (PCR) is becoming more and more important in all processing methods in polymer technology, also due to the lack of raw materials and political demands. Very special requirements are placed on material properties such as viscosities in extrusion. Low viscosities and the presence of particles affect extrusion in a negative manner. In this study, the use of multilayer sheets is determined to both ensure extrudability and contribute to a significant improvement in surface qualities. The focus is placed on the influence of viscosity and particles on mono- und multilayer sheet quality. Therefore, two different virgin materials with a melt flow rate (MFR) of 3 g/10 min and 6 g/10 min and two different PCR materials with a MFR of 16 g/10 min and 50 g/10 min are processed both in monolayers and in two layer sheets. Rheological investigations, optical analysis, and film thickness distributions are used to show the relationship between matrix viscosity and particles. The results show that the use of multilayer extrusion can improve both extrudability and sheet quality, so that multilayer sheets can offer a significant potential in the processing of PCR materials.
Recent Progress and Potential Biomedical Applications of Electrospun Nanofibers in Regeneration of Tissues and Organs
Authors: Nayl AbdElAziz A. , Abd-Elhamid Ahmed I. , Awwad Nasser S. , Abdelgawad Mohamed A. , Wu Jinglei , Mo Xiumei , Gomha Sobhi M. , Aly Ashraf A. , Bräse Stefan
Published: April 2022

Electrospun techniques are promising and flexible technologies to fabricate ultrafine fiber/nanofiber materials from diverse materials with unique characteristics under optimum conditions. These fabricated fibers/nanofibers via electrospinning can be easily assembled into several shapes of three-dimensional (3D) structures and can be combined with other nanomaterials. Therefore, electrospun nanofibers, with their structural and functional advantages, have gained considerable attention from scientific communities as suitable candidates in biomedical fields, such as the regeneration of tissues and organs, where they can mimic the network structure of collagen fiber in its natural extracellular matrix(es). Due to these special features, electrospinning has been revolutionized as a successful technique to fabricate such nanomaterials from polymer media. Therefore, this review reports on recent progress in electrospun nanofibers and their applications in various biomedical fields, such as bone cell proliferation, nerve regeneration, and vascular tissue, and skin tissue, engineering. The functionalization of the fabricated electrospun nanofibers with different materials furnishes them with promising properties to enhance their employment in various fields of biomedical applications. Finally, we highlight the challenges and outlooks to improve and enhance the application of electrospun nanofibers in these applications.
A Review of Stand-Alone and Hybrid Microbial Electrochemical Systems for Antibiotics Removal from Wastewater
Authors: Zakaria Basem , Dhar Bipro
Published: April 2022

The growing concern about residual antibiotics in the water environment pushes for innovative and cost-effective technologies for antibiotics removal from wastewater. In this context, various microbial electrochemical systems have been investigated as an alternative to conventional wastewater technologies that are usually ineffective for the adequate removal of antibiotics. This review article details the development of stand-alone and hybrid or integrated microbial electrochemical systems for antibiotics removal from wastewater. First, technical features, antibiotics removal efficiencies, process optimization, and technological bottlenecks of these systems are discussed. Second, a comparative summary based on the existing reports was established to provide insights into the selection between stand-alone and hybrid systems. Finally, research gaps, the relevance of recent progress in complementary areas, and future research needs have been discussed.
Impacts of Land Use Changes on Net Primary Productivity in Urban Agglomerations under Multi-Scenarios Simulation
Authors: Chen Yuhan , Wang Jia , Xiong Nina , Sun Lu , Xu Jiangqi
Published: April 2022

Land use is closely related to the sustainability of ecological development. This paper employed a patch-generating land use simulation (PLUS) model for the multi-scenario simulation of urban agglomerations. In addition, mathematical analysis methods such as Theil-Sen Median trend analysis, R/S analysis, Getis-Ord Gi* index and unary linear regression were used to study the temporal and spatial evolution characteristics of net primary productivity (NPP) for the impact of land use changes on NPP in urban agglomerations from 2000 to 2020 and to forecast the future trend of NPP. The results indicate that urban expansion is obvious in the baseline scenario and in the ecological protection scenario. In the scenario of cropland protection, the urban expansion is consistent with the land use plan of the government for 2035. The NPP in Beijing decreased gradually from northwest to southeast. The hot spot areas are concentrated in the densely forested areas in the mountainous areas of northwest. The cold spot areas are mainly concentrated in the periphery of urban areas and water areas. The NPP will continue to increase in forest and other areas under protection and remain stable in impervious surfaces. The NPP of Beijing showed a strong improvement trend and this trend will continue with the right ecological management and urban planning of the government. The study of land use in urban agglomeration and the development trend of vegetation NPP in the future can help policymakers rationally manage future land use dynamics and maintain the sustainable development of urban regional ecosystems.
Using InSAR Time Series to Monitor Surface Fractures and Fissures in the Al-Yutamah Valley, Western Arabia
Authors: Aldaajani Thamer , Simons Mark , Yunjun Zhang , Bekaert David , Almalki Khalid A. , Liu Yuan-Kai
Published: April 2022

Western Arabia routinely experiences geophysical phenomena that deform the surface of the earth in a variety of ways. These phenomena include earthquakes, volcanic eruptions, sinkholes, and earth fissuring and fracturing. We perform a time-series analysis of interferometric synthetic aperture radar (InSAR) observations derived from the ESA Sentinel-1 radar satellite constellation to map regional surface displacements in western Arabia as a function of time. We rely on InSAR products generated by the JPL-Caltech ARIA project to detect regions with short wavelength anomalies, and then manually reprocess InSAR products at a higher resolution for these regions to maximize spatial and temporal coverage. We post-process InSAR products using MintPy workflows to develop the InSAR time series. We report short wavelength anomalies localized within alluvial valleys across western Arabia and find a 5 cm/year line-of-sight surface displacement within the Al-Yutamah Valley. Part of the observed subsidence is correlated with surface fractures that developed in conjunction with severe rainfall events in regions characterized mainly by alluvial sediments at the surface. Regions of observed subsidence that are not associated with any surface fractures or fissures are correlated with the presence of basalt layers at the surface. Both regions are subject to groundwater exploitation. The observed subsidence is inferred to be driven by groundwater withdrawal perhaps modulated by the presence of a preexisting depositional environment (e.g., paleo-lake deposits) that promotes unconsolidated soil compaction.
LiDAR-Based Real-Time Panoptic Segmentation via Spatiotemporal Sequential Data Fusion
Authors: Wang Weiqi , You Xiong , Yang Jian , Su Mingzhan , Zhang Lantian , Yang Zhenkai , Kuang Yingcai
Published: April 2022

Fast and accurate semantic scene understanding is essential for mobile robots to operate in complex environments. An emerging research topic, panoptic segmentation, serves such a purpose by performing the tasks of semantic segmentation and instance segmentation in a unified framework. To improve the performance of LiDAR-based real-time panoptic segmentation, this study proposes a spatiotemporal sequential data fusion strategy that fused points in “thing classes” based on accurate data statistics. The data fusion strategy could increase the proportion of valuable data in unbalanced datasets, and thus managed to mitigate the adverse impact of class imbalance in the limited training data. Subsequently, by improving the codec network, the multiscale features shared by semantic and instance branches were efficiently aggregated to achieve accurate panoptic segmentation for each LiDAR scan. Experiments on the publicly available dataset SemanticKITTI showed that our approach could achieve an effective balance between accuracy and efficiency, and it was also applicable to other point cloud segmentation tasks.
Land Degradation Assessment with Earth Observation
Authors: Symeonakis Elias
Published: April 2022

For decades now, land degradation has been identified as one of the most pressing problems facing the planet [...]
Automatic Relative Radiometric Normalization of Bi-Temporal Satellite Images Using a Coarse-to-Fine Pseudo-Invariant Features Selection and Fuzzy Integral Fusion Strategies
Authors: Moghimi Armin , Mohammadzadeh Ali , Celik Turgay , Brisco Brian , Amani Meisam
Published: April 2022

Relative radiometric normalization (RRN) is important for pre-processing and analyzing multitemporal remote sensing (RS) images. Multitemporal RS images usually include different land use/land cover (LULC) types; therefore, considering an identical linear relationship during RRN modeling may result in potential errors in the RRN results. To resolve this issue, we proposed a new automatic RRN technique that efficiently selects the clustered pseudo-invariant features (PIFs) through a coarse-to-fine strategy and uses them in a fusion-based RRN modeling approach. In the coarse stage, an efficient difference index was first generated from the down-sampled reference and target images by combining the spectral correlation, spectral angle mapper (SAM), and Chebyshev distance. This index was then categorized into three groups of changed, unchanged, and uncertain classes using a fast multiple thresholding technique. In the fine stage, the subject image was first segmented into different clusters by the histogram-based fuzzy c-means (HFCM) algorithm. The optimal PIFs were then selected from unchanged and uncertain regions using each cluster’s bivariate joint distribution analysis. In the RRN modeling step, two normalized subject images were first produced using the robust linear regression (RLR) and cluster-wise-RLR (CRLR) methods based on the clustered PIFs. Finally, the normalized images were fused using the Choquet fuzzy integral fusion strategy for overwhelming the discontinuity between clusters in the final results and keeping the radiometric rectification optimal. Several experiments were implemented on four different bi-temporal satellite images and a simulated dataset to demonstrate the efficiency of the proposed method. The results showed that the proposed method yielded superior RRN results and outperformed other considered well-known RRN algorithms in terms of both accuracy level and execution time.
A CFAR Algorithm Based on Monte Carlo Method for Millimeter-Wave Radar Road Traffic Target Detection
Authors: Yang Bo , Zhang Hua
Published: April 2022

The development of Intelligent Transportation Systems (ITS) puts forward higher requirements for millimeter-wave radar surveillance in the traffic environment, such as lower time delay, higher sensitivity, and better multi-target detection capability. The Constant False Alarm Rate (CFAR) detector plays a vital role in the adaptive target detection of the radar. Still, traditional CFAR detection algorithms use a sliding window to find the target limit radar detection speed and efficiency. In such cases, we propose and discuss a CFAR detection method, which transforms the Monte Carlo simulation principle into randomly sampling instantaneous Range–Doppler Matrix (RDM) data, to improve the detection ability of radar for moving targets such as pedestrians and vehicles in the traffic environment. Compared with conventional methods, simulation and real experiments show that the method breaks through the reference window limitation and has higher detection sensitivity, higher detection accuracy, and lower detection delay. We hope to promote the detection application of millimeter-wave radar in road traffic scenes.
A Correction Method to Systematic Phase Drift of a High Resolution Radar for Foreign Object Debris Detection
Authors: Wang Yuming , Song Qian , Wang Jian , Du Baoqiang , Wang Pengyu
Published: April 2022

Due to the small size and various types of foreign object debris (FOD), radar detection of FOD on airport runways is a great challenge, and there are often a large number of false alarms in the detection results. Arc-scanning synthetic aperture radar (AS-SAR) is an emerging method for detecting FOD targets, which achieves omnidirectional coverage with a very high azimuth resolution. However, this method faces a similar challenge. A direct way to reduce false alarms is to increase the detection threshold based on enhancing the target signal-to-noise ratio (SNR), and in this paper, the coherent accumulation of multiple images is used to improve the target SNR. The stable phase is also an important feature of the target distinguishing background. Therefore, it is important to maintain the stability of the target phase. Aiming at the systematic phase drift (SPD) caused by atmospheric disturbance and system hardware, a spatial and temporal model is established, a corresponding correction approach is proposed, and the performance of the correction approach is validated by field experiments.
Mapping Tidal Flats of the Bohai and Yellow Seas Using Time Series Sentinel-2 Images and Google Earth Engine
Authors: Chang Maoxiang , Li Peng , Li Zhenhong , Wang Houjie
Published: April 2022

Tidal flats are one of the most productive ecosystems on Earth, providing essential ecological and economical services. Because of the increasing anthropogenic interruption and sea level rise, tidal flats are under great threat. However, updated and large-scale accurate tidal flat maps around the Bohai and Yellow Seas are still relatively rare, hindering the assessment and management of tidal flats. Based on time-series Sentinel-2 imagery and Google Earth Engine (GEE), we proposed a new method for tidal flat mapping with the Normalized Difference Water Index (NDWI) extremum composite around the Bohai and Yellow Seas. Tidal flats were derived from the differences of maximum and minimum water extent composites. Overall, 3477 images acquired from 1 Oct 2020 to 31 Oct 2021 produced a tidal flat map around the Bohai and Yellow Seas with an overall accuracy of 94.55% and total area of 546,360.2 ha. The resultant tidal flat map at 10 m resolution, currently one of the most updated products around the Bohai and Yellow Seas, could facilitate the process of sustainable policy making related to tidal flats and will help reveal the processes and mechanisms of its responses to natural and human disturbance.
The Increasing Frequency of Terms Denoting Political Extremism in U.S. and U.K. News Media
Authors: Rozado David , Kaufmann Eric
Published: April 2022

The term political extremism is commonly used to refer to political attitudes considered to be outside the ideological mainstream. This study leverages computational content analysis of big data to longitudinally examine (1970–2019) the prevalence of terms denoting far-right and far-left political extremism in more than 30 million written news and opinion articles from 54 news media outlets popular in the United States and the United Kingdom. We find that the usage of terms denoting right and left political extremism has been increasing across news media outlets in both countries. This trend is particularly stark for far-right-denoting terms, which have been growing in prevalence since at least 2008. Most U.S. and U.K. news media outlets tend to use far-right-denoting terms substantially more often than they use far-left-denoting terms. The rising prevalence in news media of terms denoting political extremism is strongly correlated with similar growing usage of terms denoting prejudice and social justice discourse.
Biomechanical and Psychological Predictors of Failure in the Air Force Physical Fitness Test
Authors: Turner Jeffrey , Wagner Torrey , Langhals Brent
Published: April 2022

Physical fitness is a pillar of U.S. Air Force (USAF) readiness and ensures that Airmen can fulfill their assigned mission and be fit to deploy in any environment. The USAF assesses the fitness of service members on a periodic basis, and discharge can result from failed assessments. In this study, a 21-feature dataset was analyzed related to 223 active-duty Airmen who participated in a comprehensive mental and social health survey, body composition assessment, and physical performance battery. Graphical analysis revealed pass/fail trends related to body composition and obesity. Logistic regression and limited-capacity neural network algorithms were then applied to predict fitness test performance using these biomechanical and psychological variables. The logistic regression model achieved a high level of significance (p < 0.01) with an accuracy of 0.84 and AUC of 0.89 on the holdout dataset. This model yielded important inferences that Airmen with poor sleep quality, recent history of an injury, higher BMI, and low fitness satisfaction tend to be at greater risk for fitness test failure. The neural network model demonstrated the best performance with 0.93 accuracy and 0.97 AUC on the holdout dataset. This study is the first application of psychological features and neural networks to predict fitness test performance and obtained higher predictive accuracy than prior work. Accurate prediction of Airmen at risk of failing the USAF fitness test can enable early intervention and prevent workplace injury, absenteeism, inability to deploy, and attrition.
The Application of Industry 4.0 Technological Constituents for Sustainable Manufacturing: A Content-Centric Review
Authors: Ng Tan Ching , Lau Sie Yee , Ghobakhloo Morteza , Fathi Masood , Liang Meng Suan
Published: April 2022

Industry 4.0 has been associated with the rise of disruptive intelligence and information technologies. These cutting-edge technologies have the potential to increase productivity while simultaneously having a significant impact on social and environmental sustainability. As a result, manufacturers must evaluate the role of these innovative technologies in sustainable development, as these technologies have the potential to address prevalent sustainability issues. A content-centric study of the implementation of these Industry 4.0 cutting-edge technologies in sustainable manufacturing is currently absent. A systematic literature study was conducted to explain the potential contribution of these novel technologies to the economic, social, and environmental dimensions of manufacturing industries. This study describes how these cutting-edge technologies are used in sustainable manufacturing. The findings of this study are particularly beneficial to practitioners who seek to apply one or more digital technologies to sustainable development.
Development of Bioclimatic Passive Designs for Office Building in Burkina Faso
Authors: Zoure Abraham Nathan , Genovese Paolo Vincenzo
Published: April 2022

This article focuses on adopting effective and affordable bioclimatic building design strategies in Ouagadougou, in the Sudano-Sahelian zone of Burkina Faso. A model representing a standard office building and relevant parameters were input in EnergyPlus, and scenarios were analyzed to evaluate the effect of natural ventilation, window shading, dehumidification with night ventilation, and evaporative cooling with night ventilation on thermal comfort and energy consumption. First, the American Society of Heating, Refrigerating, and Air-conditioning Engineers (ASHRAE) Standard 55 adaptive comfort model was used to compare discomfort hours and interior temperatures between a conventional office design and improved models using passive approaches. The simulations further tested the reduction in energy cooling demand and energy consumption. The results demonstrated that natural ventilation was the most effective passive cooling technique, helping to reduce the annual discomfort hours by 40% and the annual energy consumption by 30%. Combining passive strategies is the best scenario, with a year of office occupancy resulting in just 617 h of discomfort, a 42% reduction in the annual energy cooling demand, and a 43% reduction in the annual energy consumption. The simulations demonstrated the effectiveness of affordable passive design solutions applicable even in existing office buildings and their significance for the sustainable development of fast-urbanizing Sub-Saharan countries.
Understanding the Urban Environment from Satellite Images with New Classification Method—Focusing on Formality and Informality
Authors: Cheng Qianwei , Zaber Moinul , Rahman AKM Mahbubur , Zhang Haoran , Guo Zhiling , Okabe Akiko , Shibasaki Ryosuke
Published: April 2022

Urbanization plays a critical role in changing the urban environment. Most developed countries have almost completed urbanization. However, with more and more people moving to cities, the urban environment in developing countries is undergoing significant changes. Sustainable development cannot be achieved without significant changes in building, managing, and responding to changes in the urban environment. The classified measurement and analysis of the urban environment in developing countries and the real-time understanding of the evolution and characteristics of the urban environment are of great significance for decision-makers to manage and plan cities more effectively and maintain the sustainability of the urban environment. Hence, a method readily applicable for the state-of-the-art computational analysis can help conceive the rapidly changing urban socio-environmental dynamics that can make the policy-making process even more informative and help monitor the changes almost in real-time. Based on easily accessible data from Google Earth, this work develops and proposes a new urban environment classification method focusing on formality and informality. Firstly, the method gives a new model to scrutinize the urban environment based on the buildings and their surroundings. Secondly, the method is suited for the state-of-the-art machine learning processes that make it applicable and scalable for forecasting, analytics, or computational modeling. The paper first demonstrates the model and its applicability based on the urban environment in the developing world. The method divides the urban environment into 16 categories under four classes. Then it is used to draw the urban environment classes maps of the following emerging cities: Nairobi in Kenya, Mumbai in India, Guangzhou in China, Jakarta in Indonesia, Cairo in Egypt, and Lima in Chile. Then, we discuss the characteristics of different urban environments and the differences between the same class in different cities. We also demonstrate the agility of the proposed method by showing how this classification method can be easily augmented with other data such as population per square kilometer to aid the decision-making process. This mapping should help urban designers who are working on analyzing formality and informality in the developing world. Moreover, from the application point of view, this will provide training data sets for future deep learning algorithms and automate them, help establish databases, and significantly reduce the cost of acquiring data for urban environments that change over time. The method can become a necessary tool for decision-makers to plan sustainable urban spaces in the future to design and manage cities more effectively.
The Influence of Environmental Transformation on Small-Scale Fishing Communities’ Livelihood
Authors: Islam Rabiul , Ghani Ahmad Bashawir Abdul , Sultana Sabina , Mahyudin Emil
Published: April 2022

In Malaysia’s northern area, small-scale fishing (SSF) communities in inland open water are among the most vulnerable people. This study looked at the impact of climate change on small-scale fishing communities in Malaysia’s northern region from a vulnerability standpoint, using two vulnerability indexes. One is the Livelihood Vulnerability Index’ (LVI) and the other is the Vulnerability Framework Approach of IPCC (LVI-IPCC method). The primary purpose of this study is to assess how climate change affects small-scale fishing communities. Data on SSF households were collected at random from three states to suit the research goal: Kedah, Penang, and Perlis. For an interview, a total of 352 SSF families were contacted. According to the Livelihood Vulnerability Index (LVI) research, SSFs in Perlis are more susceptible than those in Kedah and Penang. Adjustments to food policy, health services, informal credit facilities, training, and the establishment of more effective early warning systems are all necessary initiatives that the government must take to enhance the quality of life for SSF communities.
Optimization of a Fuel Cost and Enrichment of Line Loadability for a Transmission System by Using Rapid Voltage Stability Index and Grey Wolf Algorithm Technique
Authors: Muppidi Rambabu , Nuvvula Ramakrishna S. S. , Muyeen S. M. , Shezan SK. A. , Ishraque Md. Fatin
Published: April 2022

Efficient transmission of power is a pressing concern in modern power systems as it could relieve additional investments (e.g., right of way) and may improve stability. Non-uniform loading of transmission lines (which normally occurs due to the inefficient transmission of power) may lead to overloading of a few lines. These lines would then be prone to voltage instability. However, this problem would be aggravated under the network contingency condition. This paper focuses on improving the line loadability of the transmission system by considering the benchmark voltage stability index named rapid voltage stability index. The optimal loadability problem is considered using the grey wolf algorithm. The proposed work is implemented on a standard IEEE 30 bus test system using MATLAB software by addressing the problem by using line stability voltage index and grey wolf algorithm in optimal power flow. Minimizations of cost of generation, carbon emissions, voltage deviation, and line losses have been considered as objectives and improve the line loadability of the transmission system. The simulation results show that the proposed method is very effective in improving line loadability, reducing line congestion and fuel cost. Furthermore, the methodology is tested rigorously under various contingency conditions and is shown to be very effective. The proposed method relieves transmission line congestion and reduces fuel costs using the rapid voltage stability index (RVSI) is tested on an IEEE 30-bus standard test system utilizing MATLAB for various contingency lines
Identification of Waste Based on Lean Principles as the Way towards Sustainability of a Higher Education Institution: A Case Study from Indonesia
Authors: Hartanti Lusia Permata Sari , Gunawan Ivan , Mulyana Ig. Jaka , Herwinarso Herwinarso
Published: April 2022

Lean management has generated new approaches to reduce non-value-adding activities in different sectors of the economy, including in higher education systems. Lean principles in higher education institutions (HEIs) contribute positively to sustainability performance. The current study aims to: (a) assess waste in HEIs based on lean principles and even their potential effect on sustainability; (b) establish the relationship among wastes; (c) develop a structural model using Interpretative Structural Modeling (ISM); (d) carry out the Matrice d’impacts Croisés Multiplication Appliqué Àun Classement (MICMAC) analysis. In Phase 1 of this study, the identification of waste modes in HEIs was established. In Phase 2, risk assessment of each waste mode was conducted using the waste-Failure Mode and Effect Analysis (w-FMEA) technique. In Phase 3, ISM-MICMAC was used to identify relationships among critical waste modes. The results showed that eighteen waste modes were identified as critical in HEIs—with six waste modes being autonomous determinants; four were dependent determinants, four were linkage determinants, and four were driver determinants. This study is expected to help academicians and practitioners understand HEI’s waste types by listing the critical wastes, mapping their interrelationship, identifying the driving power and dependence, and proposing mitigation actions. It will also contribute to the growing body of literature highlighting the waste in HEIs.
Emerging Solvent Regeneration Technologies for CO2 Capture through Offshore Natural Gas Purification Processes
Authors: Mohd Pauzi Mohd Mu’Izzuddin , Azmi Nurulhuda , Lau Kok Keong
Published: April 2022

It is estimated that 40% of natural gas reservoirs in the world are contaminated with acid gases (such as hydrogen sulfide and carbon dioxide), which hinder exploitation activities. The demand for natural gas will increase by 30% from 2020 to 2050, with the rise of industrial activities and the lifting of travel restrictions. The long-term production of these high acid-gas fields requires mitigation plans, which include carbon capture, utilization, and a storage process to reduce carbon emissions. Absorption is one the most established technologies for CO2 capture, yet it suffers from extensive energy regeneration and footprint requirements in offshore operations. Therefore, the aims of this paper are to review and analyze the recent developments in conventional and emerging solvent regeneration technologies, which include a conventional packed-bed column, membrane contactor, microwave heating, flash drum, rotating packed bed, and ultrasonic irradiation process. The conventional packed column and flash drum are less complex, with minimum maintenance requirements, but suffer from a large footprint. Even though the rotating packed-bed column and microwave heating demonstrate a higher solvent flexibility and process stability, both technologies require regular maintenance and high regeneration energy. Membrane contactor and ultrasonic irradiation absorption systems are compact, but restricted by various operational issues.
Do Basic Income Models Cope with Poverty and Inequality Sustainably? Some Critical Reflections and Alternatives
Authors: Koch Andreas
Published: April 2022

The United Nation’s Agenda 2030, with its seventeen sustainable development goals, aims to alleviate poverty and reduce social inequality, among other things. The political program provokes numerous ambitious measures but leaves room for various definitions and interpretations about which measures perform well. The challenge lies in understanding poverty and inequality in ways that move beyond a pure income-related perspective. In accepting this challenge, measures have been elabourated, which are supposed to advise the Austrian government in their efforts to implement the SDGs. The ‘unconditional basic income’ and the ‘all citizens’ insurance scheme’ represent two approaches among those measures, which call themselves for a comprehensive consideration of social justice. Both approaches will be discussed in terms of their political and normative claims. While basic income remains dominated by income, the insurance scheme engages with the question of who is entitled to benefits. Both approaches are ultimately unable to unfold their potentials as long as a territorial–administrative space concept is utilized. Since urban environments have their own specific social and spatial characteristics, it is essential to trigger a thorough discussion of political concepts which cope with the particular causes and effects of urban poverty, exclusion and inequality.
The Role of Plant Functional Diversity in Regulating Soil Organic Carbon Stocks under Different Grazing Intensities in Temperate Grassland, China
Authors: Sheng Zhilu , Du Jiaqiang , Sun Bingqing , Mao Jialin , Zhang Yangchengsi , Zhang Jing , Diao Zhaoyan
Published: April 2022

Grazing is very common in the grassland ecosystem, and it has a significant impact on the C stocks and cycle. One of the most important drivers of soil C stocks is functional diversity. However, limited studies have attempted to explore the effects of functional diversity on soil C stocks associated with grazing disturbance. This study was carried out in Hulunbeier grassland, Inner Mongolia, and four grazing intensities (no grazing (NG), light grazing (LG), moderate grazing (MG), and heavy grazing (HG)) were identified. The plant functional traits and important soil properties under different grazing intensities were measured. Functional identity and diversity were calculated based on the measured functional traits. The impacts of functional identity and diversity on soil organic carbon stocks (SOCstocks) were analyzed using a multi-model inference (MMI) approach. Our study showed that the functional diversity effect on soil C stocks varies depending on grazing intensity. We identified that functional richness has a significant impact on SOCstocks in NG. The community weighted mean of leaf area became the best predictor of SOCstocks in LG. As grazing intensified, functional divergence best explained SOCstocks in moderate and heavy grazing sites, and their relationship was positive. The major outcomes of this research could shed light on the mechanics of soil carbon storage.