bluuebunny/crossref_metadata_2025 huggingface dataset:
Emodin, a Natural Anthraquinone, Increases Uric Acid Excretion in Rats with Potassium Oxonate-Induced Hyperuricemia
Authors: Hou Shen-Wei , Chen Szu-Ju , Shen Jing-Dung , Chen Huey-Yi , Wang Shih-Jing , Wang Chia-Han , Man Kee-Ming , Liu Po-Len , Tsai Ming-Yen , Chen Yung-Hsiang , Chen Wen-Chi
Published: May 2023

The treatment of hyperuricemia and gout is mostly based on lowering serum uric acid levels using drugs, such as allopurinol, or increasing urinary excretion of uric acid. However, some patients still experience adverse reactions to allopurinol and turn to Chinese medicine as an alternative. Therefore, it is crucial to design a preclinical study to obtain more convincing data on the treatment of hyperuricemia and gout with Chinese medicine. This study aimed to explore the therapeutic effect of emodin, a Chinese herbal extract, in a rat model of hyperuricemia and gout. In this study, we used 36 Sprague–Dawley rats, which were randomly divided into six groups for experimentation. Hyperuricemia was induced in rats by intraperitoneal injections of potassium oxonate. The efficacy of emodin in reducing serum uric acid levels was demonstrated by comparing the positive control group with groups treated with three different concentrations of emodin. The inflammatory profiles, including interleukin (IL)-1β, IL-6, and tumor necrosis factor-α levels, were unaffected by emodin treatment. In the experimental results, it was observed that the serum uric acid concentration in the vehicle control group was 1.80 ± 1.14, while the concentrations in the moderate and high concentration emodin groups were 1.18 ± 0.23 and 1.12 ± 0.57, resulting in no significant difference in uric acid concentration between these treatment groups and the control group, indicating that emodin has a therapeutic effect on hyperuricemia. The increase in the fractional excretion of uric acid (FEUA) demonstrated that emodin promoted urinary uric acid excretion without significantly affecting the inflammatory profile. Thus, emodin reduced the serum uric acid concentration to achieve effective treatment of hyperuricemia and gout by increasing urinary excretion. These results were supported by the measured serum uric acid and FEUA levels. Our data have potential implications for the treatment of gout and other types of hyperuricemia in clinical practice.
Technology Personalities in the Classroom: A New Classification System of TechTypes from Expert to Techy Turtle
Authors: Oestreich Julie H. , Guy Jason W.
Published: May 2023

The incorporation of technology in higher education has increased rapidly in recent years to allow for remote work and to promote active learning. Technology use could align with personality type and adopter status as defined by the diffusion of innovations theory. A review of the literature was conducted using PubMed with 106 articles found, and 2 articles meeting the inclusion criteria of the study. Search terms included “technology AND education”, “pharmacy AND personality”, “technology AND faculty AND personality”, and “technology AND health educators AND personality”. This paper highlights the current literature and introduces a new classification system to describe the technology personalities of instructors. The proposed personality types (TechTypes) include expert, budding guru, adventurer, cautious optimist, and techy turtle. Awareness of the advantages and disadvantages of each personality type—as well as one’s own technology personality—may guide the selection of collaborators and tailor technology training for future growth.
Photobiomodulation Therapy Mitigates Salivary Gland Damage Induced by Radioactive Iodine Ablation
Authors: Campos Luana , Magliano Gabriela Campos , Hotsumi Andressa Matucci , Faria Daniele de Paula , Garcez Alexandre Teles , Godoy Fernando , Arana-Chavez Victor Elias , Simões Alyne
Published: May 2023

(1) Background: Thyroid tissue ablation with radioactive iodine (RAI) has been successfully used in the treatment of differentiated thyroid cancers. However, as a side effect, RAI may induce salivary gland (SG) hypofunction, which has been alternatively managed with photobiomodulation therapy (PBMT). In our study, we assessed the effects of RAI on the SGs and further analyzed whether PBMT can minimize tissue damage. (2) Methods: Balb/c mice were allocated into three groups, as follows: RI, submitted to RAI orally; RIL, similar to RI, but with PBMT for SG hypofunction; and C, control group. The animals were euthanized on days 0, 10, and 90 after RAI. (3) Results: A decrease in tri-iodothyronine (T3) and thyroxine (T4) serum levels was observed both in the RI and RIL groups. In addition, a decrease in SG weight and morphological alterations were shown in the RI group throughout the experimental period, as well as a significant increase in total protein and peroxidase concentrations, and catalase activity. On day 90, the RI group presented less collagen and fewer sodium/iodine channels, with higher rates of cell apoptosis. Pertechnetate (Na99mTcO4) uptake was also affected in the RI group in all experimental times. Interestingly, although the RIL group also presented some alterations regarding these parameters, they were not statistically different from those of the C group on day 90. (4) Conclusions: Our results provide evidence that RAI induces harmful effects on the SGs, which can be successfully managed with PBMT.
On the Quenching Mechanism of Ce, Tb Luminescence and Scintillation in Compositionally Disordered (Gd, Y, Yb)3Al2Ga3O12 Garnet Ceramics
Authors: Dubov Valery , Kuznetsova Daria , Kamenskikh Irina , Komendo Ilia , Malashkevich Georgii , Ramanenka Andrei , Retivov Vasili , Talochka Yauheni , Vasil’ev Andrei , Korzhik Mikhail
Published: May 2023

Two series of (Gd, Y, Yb)3Al2Ga3O12 quintuple compounds with a garnet structure and solely doped with Ce and Tb were prepared in the form of ceramics by sintering in oxygen at 1600 °C for two hours and studied for the interaction of activator ions with ytterbium ions entering the matrix. It was shown that the photoluminescence and scintillation of Ce3+ ions are completely suppressed, predominantly by tunneling ionization through the charge transfer state (CTS) of the Ce4+-Yb2+ ions. The photoluminescence of Tb3+ ions is quenched in the presence of ytterbium, but not completely due to the poor resonance conditions of Tb3+ intraconfiguration transitions and the CTS of the single Yb3+ and the CTS of Ce4+-Yb2+ ions. The scintillation in the visible range of both Ce3+- and Tb3+-doped samples is intensely quenched as well, which indicates strong competition from Yb3+ ions to activators in interaction with the Gd substrate.
Mechanical Properties of Ternary Composite from Waste Leather Fibers and Waste Polyamide Fibers with Acrylonitrile-Butadiene Rubber
Authors: Hang Le Thuy , Do Quoc-Viet , Hoang Luu , Nguyen Luc The , Linh Nguyen Pham Duy , Doan Vu Anh
Published: May 2023

This study aimed to improve the mechanical properties of a composite material consisting of waste leather fibers (LF) and nitrile rubber (NBR) by partially replacing LF with waste polyamide fibers (PA). A ternary recycled composite NBR/LF/PA was produced by a simple mixing method and vulcanized by compression molding. The mechanical properties and dynamic mechanical properties of the composite were investigated in detail. The results showed that the mechanical properties of NBR/LF/PA increased with an increase in the PA ratio. The highest tensile strength value of NBR/LF/PA was found to have increased about 1.26 times, that is from 12.9 MPa of LF50 to 16.3 MPa of LF25PA25. Additionally, the ternary composite demonstrated high hysteresis loss, which was confirmed by dynamic mechanical analysis (DMA). The presence of PA formed a non-woven network that significantly enhanced the abrasion resistance of the composite compared to NBR/LF. The failure mechanism was also analyzed through the observation of the failure surface using scanning electron microscopy (SEM). These findings suggest that the utilization of both waste fiber products together is a sustainable approach to reducing fibrous waste while improving the qualities of recycled rubber composites.
Roll-Out Deployment Process Analysis of a Fiber Reinforced Polymer (FRP) Composite Tape-Spring Boom
Authors: Wang Sicong , Xu Shuhong , Lu Lei , Sun Lining
Published: May 2023

Deployable extendable booms are widely used in aerospace technology due to many advantages they have, such as high folded-ratio, lightweight and self-deployable properties. A bistable FRP composite boom can not only extend its tip outwards with a corresponding rotation speed on the hub, but can also drive the hub rolling outwards with a fixed boom tip, which is commonly called roll-out deployment. In a bistable boom’s roll-out deployment process, the second stability can keep the coiled section from chaos without introducing a controlling mechanism. Because of this, the boom’s roll-out deployment velocity is not under control, and a high moving speed at the end will give the structure a big impact. Therefore, predicting the velocity in this whole deployment process is necessary to be researched. This paper aims to analyze the roll-out deployment process of a bistable FRP composite tape-spring boom. First, based on the Classical Laminate Theory, a dynamic analytical model of a bistable boom is established through the energy method. Afterwards, an experiment is introduced to produce some practical verification for comparison with the analytical results. According to the comparison with the experiment, the analytical model is verified for predicting the deployment velocity when the boom is relatively short, which can cover most booms using CubeSats. Finally, a parametric study reveals the relationship between the boom properties and the deployment behaviors. The research of this paper will give some guidance to the design of a composite roll-out deployable boom.
Wave Attenuation in Additively Manufactured Polymer Acoustic Black Hole Structures Considering the Viscoelastic Effect
Authors: Huang Wei , Ji Hongli , Ding Ye , Qiu Jinhao
Published: May 2023

The acoustic black hole (ABH) is a feature commonly found in thin-walled structures that is characterized by a diminishing thickness and damping layer with an efficient wave energy dissipation effect, which has been extensively studied. The additive manufacture of polymer ABH structures has shown promise as a low-cost method to manufacture ABHs with complex geometries, exhibiting even more effective dissipation. However, the commonly used elastic model with viscous damping for both the damping layer and polymer ignores the viscoelastic changes that occur due to variations in frequency. To address this, we used Prony exponential series expansion to describe the viscoelastic behavior of the material, where the modulus is represented by a summation of decaying exponential functions. The parameters of the Prony model were obtained through experimental dynamic mechanical analysis and applied to finite element models to simulate wave attenuation characteristics in polymer ABH structures. The numerical results were validated by experiments, where the out-of-plane displacement response under a tone burst excitation was measured by a scanning laser doppler vibrometer system. The experimental results illustrated good consistency with the simulations, demonstrating the effectiveness of the Prony series model in predicting wave attenuation in polymer ABH structures. Finally, the effect of loading frequency on wave attenuation was studied. The findings of this study have implications for the design of ABH structures with improved wave attenuation characteristics.
Mechanical Properties Optimization of Hybrid Aramid and Jute Fabrics-Reinforced Graphene Nanoplatelets in Functionalized HDPE Matrix Nanocomposites
Authors: Costa Ulisses Oliveira , Garcia Filho Fabio da Costa , Río Teresa Gómez-del , Rodrigues João Gabriel Passos , Simonassi Noan Tonini , Monteiro Sergio Neves , Nascimento Lucio Fabio Cassiano
Published: May 2023

Natural lignocellulosic fibers (NLFs) have been used as a reinforcement for polymer matrix composites in the past couple of decades. Their biodegradability, renewability, and abundance make them appealing for sustainable materials. However, synthetic fibers surpass NLFs in mechanical and thermal properties. Combining these fibers as a hybrid reinforcement in polymeric materials shows promise for multifunctional materials and structures. Functionalizing these composites with graphene-based materials could lead to superior properties. This research optimized the tensile and impact resistance of a jute/aramid/HDPE hybrid nanocomposite by the addition of graphene nanoplatelets (GNP). The hybrid structure with 10 jute/10 aramid layers and 0.10 wt.% GNP exhibited a 2433% increase in mechanical toughness, a 591% increase in tensile strength, and a 462% reduction in ductility compared to neat jute/HDPE composites. A SEM analysis revealed the influence of GNP nano-functionalization on the failure mechanisms of these hybrid nanocomposites.
The Combustion of Forest Humus Blended with Low-Rank Coal: Effects of Oxygen Ratio and Blending Ratio
Authors: Zhou Guoli , Zhang Tong , Lou Chenfei , Wang Kunpeng , Yun Qinghang , Li Peng , Qu Xiaoyang , Li Guosheng
Published: May 2023

In this study, the combustion characteristics of pine needles, pine needle humus, and the co-combustion of these two types of biomass with coal were compared. In addition, the optimization of the combustion performance of coal/humus was assisted through the following studies: (i) the combustion performance of coal/pine needle humus was studied under four different oxygen concentrations (N2, 10%O2/90%N2, 20%O2/80%N2, and 40%O2/60%N2); (ii) the synergistic effect between the humus and coal during combustion was also investigated by adjusting the blending ratio and oxygen content; (iii) the mechanisms of the optimized combustion processes were expounded by kinetics and thermodynamics discussion. The results demonstrated that the combustion characteristics of the coal/humus blends were found to be higher than those of the coal/pine needle blends. The coupling interactions of the oxygen content and blending ratio contributed to the significant synergistic effect between the two fuels, and the synergistic effect showed a nonlinear variation with an increased oxygen concentration. The synergistic effect in a rich oxygen environment (O240%/N260%) is 5.1 times greater than that in the synthetic air (O220%/N280%) and 13.8 times greater than that in the oxygen-poor environment (O210%/N290%). Hence, the blending ratio could be adjusted to maintain the intensity of the synergistic effect in an oxygen-rich atmosphere.
Mixing Transport Mechanism of Three-Phase Particle Flow Based on CFD-DEM Coupling
Authors: Ge Man , Chen Juntong , Zhao Longyun , Zheng Gaoan
Published: May 2023

The mixing transport courses of three-phase particle flows exist in some industrial applications, such as metallurgy material extraction, lithium electric slurry dispersion, and material mixing in the high-end chemical industry. Its mixing transport mechanism is a fluid–structure coupling dynamic issues with intensive shear and nonlinear characteristics, making the real-time prediction of the flow field face challenges. To address the above problem, a bidirectional fluid–structure coupling three-phase particle flow dynamic model is built based on the coupled computational fluid dynamics and discrete element model (CFD-DEM) to explore the mixing transport mechanism. An interphase coupling solution method is utilized to solve the interaction effects of the fluid and particle. Research results illustrate that the proposed method modeling can well reveal the mixing transport mechanism of the three-phase particle flows. Due to the additive effects of stirring speed, stirring blade size, and stirring blade structure, the flow field near the blade has a high-velocity gradient change, while the flow field away from the stirring blade has no significant change. When the particle material settles and accumulates to a certain extent, the particle movement is blocked, and the stirring speed of the particle material near the blade is reduced. The mixing effect of the particle material will be reduced near the wall. It can provide a valuable reference for particle flow transport and pattern identification and support technical support for lithium electric homogenate mixing, chemical extraction, and pharmacy process regulation.
The Formation of an Ice-Contact Proglacial Lake and Its Impact on Glacier Change: A Case Study of the Tanymas Lake and Fedchenko Glacier
Authors: Li Zhijie , Wang Ninglian , Chang Jiawen , Zhang Quan
Published: May 2023

Lake-terminating glaciers have some peculiar behaviors compared to land-terminating glaciers, but in-depth observation is still limited regarding their formation, which is crucial for understanding the glacier–lake interaction. Here, the long-term evolutions of Tanymas Lake and the Fedchenko Glacier were investigated based on Landsat images, Google Earth imagery, KH-9 images, glacier surface elevation and velocity change datasets, and meteorological records. The results indicate that Tanymas Lake is both an ice-contact proglacial lake and an ice-dammed lake. It covered an area of 1.10 km2 in September 2022, and it is one of the largest glacial lakes in Pamir and even in HMA. The initial basin of Tanymas Lake is a moraine depression in Tanymas Pass, and the blocked dam is the Tanymas-5 Glacier and its terminal moraine. Tanymas Lake was in an embryonic stage before August 2005, in a formation and expansion stage from August 2005 to September 2018, and in a new expansion stage after September 2018. In this process, the Tanymas terminus of the Fedchenko Glacier also transformed from a land terminus to a partial lake terminus, and then to a complete lake terminus. The formation of Tanymas Lake is associated with the accumulation of glacial meltwater and the blockage of drainage, while the slow expansion of Tanymas Lake is related to the cold climate and slight glacier mass loss of Central Pamir. In the coming decades, with the accelerated mass loss of the Tanymas terminus of the Fedchenko Glacier, the area, depth, and water storage of Tanymas Lake will continue to increase, accompanied by the growing GLOF risk.
Common-Mode Clutter Filtering for the Problem of Sounding Multilayer Media Using Ground-Penetrating Radar
Authors: Gorst Aleksandr , Tseplyaev Ilya , Eremeev Aleksandr , Satarov Rail , Shipilov Sergey , Fedyanin Ivan , Khmelev Vitaly , Romanov Dmitry , Eremin Roman
Published: May 2023

Eliminating common-mode clutter in data is one of the key aspects of road sensing with GPR. Common-mode interference can occur as a result of multipath propagation of an electromagnetic signal when the reflected signal from the same object arrives at the receiver from different directions and with different delays. Similar phenomena also occur when using antennas raised above the surface due to multiple reflections between the air–surface interface and the antenna. These interferences can significantly distort the data received by the GPR and interfere with the accurate determination of the parameters of the roadway. Therefore, the elimination of common-mode clutter is an important task to improve the quality of the obtained results. In this paper, we consider a method for filtering common-mode clutter in the radar data of the multichannel GPR “Terrazond”, which were obtained by sounding a test section of a highway. The results obtained during filtering can then be used to determine the thickness of the pavement layers using approaches that take into account the signal delay determined by the amplitude jump, for example, the common point method or if the permittivity of each layer is known. The obtained thicknesses of pavement layers are compared with the results obtained during core drilling by the Russian Road Research Institute.
Prediction of Mine Subsidence Based on InSAR Technology and the LSTM Algorithm: A Case Study of the Shigouyi Coalfield, Ningxia (China)
Authors: Ma Fei , Sui Lichun , Lian Wei
Published: May 2023

The accurate prediction of surface subsidence induced by coal mining is critical to safeguarding the environment and resources. However, the precision of current prediction models is often restricted by the lack of pertinent data or imprecise model parameters. To overcome these limitations, this study proposes an approach to predicting mine subsidence that leverages Interferometric Synthetic Aperture Radar (InSAR) technology and the long short-term memory network (LSTM). The proposed approach utilizes small baseline multiple-master high-coherent target (SBMHCT) interferometric synthetic aperture radar technology to monitor the mine surface and applies the long short-term memory (LSTM) algorithm to construct the prediction model. The Shigouyi coalfield in Ningxia Province, China was chosen as a study area, and time series ground subsidence data were obtained based on Sentinel-1A data from 9 March 2015 to 7 June 2016. To evaluate the proposed approach, the prediction accuracies of LSTM and Support Vector Regression (SVR) were compared. The results show that the proposed approach could accurately predict mine subsidence, with maximum absolute errors of less than 2 cm and maximum relative errors of less than 6%. The findings demonstrate that combining InSAR technology with the LSTM algorithm is an effective and robust approach for predicting mine subsidence.
An ISAR Shape Deception Jamming Method Based on Template Multiplication and Time Delay
Authors: Liu Ying-Xi , Zhang Qun , Xiong Shi-Chao , Ni Jia-Cheng , Wang Dan , Wang Hao-Bo
Published: May 2023

The deception jamming method based on Digital Radio Frequency Memory (DRFM) for Inverse Synthetic Aperture Radar (ISAR) has been a widely studied topic in recent decades. Typically, jamming signals generated using two-dimensional or three-dimensional false target models can create realistic false targets on the ISAR image. However, existing deception jamming methods cannot eliminate or revise the original echo, which can be retained by multiple anti-jamming methods once the radar judges out receiving the jamming signal. Additionally, these methods require large storage space for the models. Otherwise, the false targets cannot be generated realistically. To address these issues, this paper proposes a jamming signal generation algorithm based on two-dimensional template multiplication modulation and template time delay. The frequency shift and time delay relationship between the signals intercepted by the jammer and the real target echo is analyzed and derived in detail. With the use of these detailed derivations, it is possible to add and remove scatters by precisely locating the false scatter on the real ISAR image. The real target’s shape naturally changes as a result of the addition and removal of scatters. Furthermore, this method can adaptively change the resolution of the false target’s ISAR image with the radar pulse width and the accumulated pulse number. Meanwhile, the false target size on the ISAR image can be adjusted adaptively by altering the false template resolution. These features of the proposed method offer increased flexibility and efficiency for deception jamming. By accurately determining the position of false scatter on the ISAR image, this method offers improved performance compared with the existing techniques. Simulation results demonstrate the effectiveness of the proposed deception jamming method.
Assessing Sustainability over Space and Time: The Emerging Roles of GIScience and Remote Sensing
Authors: Estoque Ronald C.
Published: May 2023

Sustainability is a critical global challenge that requires comprehensive assessments of environmental, social, and economic indicators [...]
Trends and Challenges in AIoT/IIoT/IoT Implementation
Authors: Hou Kun Mean , Diao Xunxing , Shi Hongling , Ding Hao , Zhou Haiying , de Vaulx Christophe
Published: May 2023

For the next coming years, metaverse, digital twin and autonomous vehicle applications are the leading technologies for many complex applications hitherto inaccessible such as health and life sciences, smart home, smart agriculture, smart city, smart car and logistics, Industry 4.0, entertainment (video game) and social media applications, due to recent tremendous developments in process modeling, supercomputing, cloud data analytics (deep learning, etc.), communication network and AIoT/IIoT/IoT technologies. AIoT/IIoT/IoT is a crucial research field because it provides the essential data to fuel metaverse, digital twin, real-time Industry 4.0 and autonomous vehicle applications. However, the science of AIoT is inherently multidisciplinary, and therefore, it is difficult for readers to understand its evolution and impacts. Our main contribution in this article is to analyze and highlight the trends and challenges of the AIoT technology ecosystem including core hardware (MCU, MEMS/NEMS sensors and wireless access medium), core software (operating system and protocol communication stack) and middleware (deep learning on a microcontroller: TinyML). Two low-powered AI technologies emerge: TinyML and neuromorphic computing, but only one AIoT/IIoT/IoT device implementation using TinyML dedicated to strawberry disease detection as a case study. So far, despite the very rapid progress of AIoT/IIoT/IoT technologies, several challenges remain to be overcome such as safety, security, latency, interoperability and reliability of sensor data, which are essential characteristics to meet the requirements of metaverse, digital twin, autonomous vehicle and Industry 4.0. applications.
A New and Automated Method for Improving Georeferencing in Nighttime Thermal ECOSTRESS Imagery
Authors: Soszynska Agnieszka , van der Werff Harald , Hieronymus Jan , Hecker Christoph
Published: May 2023

Georeferencing accuracy plays a crucial role in providing high-quality ready-to-use remote sensing data. The georeferencing of nighttime thermal satellite imagery conducted by matching to a basemap is challenging due to the complexity of thermal radiation patterns in the diurnal cycle and the coarse resolution of thermal sensors in comparison to sensors used for imaging in the visual spectral range (which is typically used for creating basemaps). The presented paper introduces a novel approach for the improvement of the georeferencing of nighttime thermal ECOSTRESS imagery: an up-to-date reference is created for each to-be-georeferenced image, derived from land cover classification products. In the proposed method, edges of water bodies are used as matching objects, since water bodies exhibit a relatively high contrast with adjacent areas in nighttime thermal infrared imagery. The method was tested on imagery of the East African Rift and validated using manually set ground control check points. The results show that the proposed method improves the existing georeferencing of the tested ECOSTRESS images by 12.0 pixels on average. The strongest source of uncertainty for the proposed method is the accuracy of cloud masks because cloud edges can be mistaken for water body edges and included in fitting transformation parameters. The georeferencing improvement method is based on the physical properties of radiation for land masses and water bodies, which makes it potentially globally applicable, and is feasible to use with nighttime thermal infrared data from different sensors.
A New Temperature Correction Method for NaI(Tl) Detectors Based on Pulse Deconvolution
Authors: Xie Jianming , Yang Liu , Li Jinglun , Qi Sheng , Chen Wenzhuo , Xu Hang , Xiao Wuyun
Published: May 2023

To overcome the temperature effect of NaI(Tl) detectors for energy spectrometry without additional hardware, a new correction method was put forward based on pulse deconvolution, trapezoidal shaping and amplitude correction, named DTSAC. To verify this method, actual pulses from a NaI(Tl)-PMT detector were measured at various temperatures from −20 °C to 50 °C. Pulse processing and spectrum synthesis showed that the position drift of the 137Cs 662 keV peak was less than 3 keV, and the corresponding resolution at 662 keV of the sum spectra ranged from 6.91% to 10.60% with the trapezoidal width set from 1000 ns to 100 ns. The DTSAC method corrects the temperature effect via pulse processing, and needs no reference peak, reference spectrum or additional circuits. The method solves the problem of correction of pulse shape and pulse amplitude at the same time, and can be used even at a high counting rate.
An Autonomous City-Wide Light Pollution Measurement Network System Using LoRa Wireless Communication
Authors: Erwinski Krystian , Karpinska Dominika , Kunz Mieczyslaw , Paprocki Marcin , Czokow Jaroslaw
Published: May 2023

Light pollution is an ongoing problem for city populations. Large numbers of light sources at night negatively affect humans’ day–night cycle. It is important to measure the amount of light pollution in order to effectively ascertain the amount of light pollution in the city area and effectively reduce it where possible and necessary. In order to perform this task, a prototype wireless sensor network for automated, long-term measurement of light pollution was developed for the Torun (Poland) city area. The sensors use LoRa wireless technology to collect sensor data from an urban area by way of networked gateways. The article investigates the sensor module architecture and design challenges as well as network architecture. Example results of light pollution measurements are presented, which were obtained from the prototype network.
Innovative Technologies for Occupational Health and Safety: A Scoping Review
Authors: Flor-Unda Omar , Fuentes Mauricio , Dávila Daniel , Rivera Mario , Llano Gladys , Izurieta Carlos , Acosta-Vargas Patricia
Published: May 2023

Technological advancements have allowed for the design and development of multiple intelligent devices that monitor the health and safety status of workers in the industry in general. This paper reviews and describes the alternative technologies and their potential for monitoring risk situations, vital signs, physical variables, worker positions, and behavioral trends of workers in their work activities in the workplace. A scoping review was conducted using PRISMA ScR in which information was extracted from 99 scientific articles related to these technological advances. The operational characteristics and utilities of devices whose primary function is to control better and monitor worker safety and health were identified. It was concluded that technology strongly improves the acquisition and sending of information. This information can be used to provide alerts and feedback to workers so that they act more safely and protect their health. In addition, technological developments have resulted in devices that eliminate operational risks by replacing manual activities with automated and autonomous tasks.
A Study on Disasters Induced by Head-On Ejection in High-Speed Driving under the Influence of Roof Drainage
Authors: Li Fenghui , Cheng Yunhai , Zhang Xiufeng , Li Dong , Huang Shunjie
Published: May 2023

During the gob-side entry driving of the Jurassic coal seam in Western China, ejection disasters occur under the influence of roof drainage, which rarely appear in the eastern mining area. To address this problem, a method combining theoretical analysis, numerical simulation, and field monitoring was used to study the disaster induced by head-on ejection during speedy driving under the influence of roof drainage in the context of gob-side entry driving of the 2202 auxiliary haulage roadway in a mine. A calculation model for the critical energy conditions for disasters induced by head-on ejection was established. The relationships between the driving velocity and the dynamic and static loads on the driving face and the disasters induced by ejection were clarified under the influence of roof drainage. The results indicate that the energy threshold for ejection-induced disaster is 12.23 kJ, and the elastic energy of the driving face induced only by static load fails to reach the energy threshold. When the driving velocity exceeds 5 m/d, microseismic activity in front of the driving face increases in a stepwise manner, and the influence of dynamic load intensifies. The superposition of accumulated elastic energy induced by static load and the energy transmitted by microearthquake to the driving face exceeds the energy threshold, resulting in the risk of ejection-induced disaster. Based on this, measures such as microseismic monitoring in front of the driving face, advanced pulverized coal monitoring, driving speed adjustment, and advanced pressure relief of large-diameter boreholes are adopted to ensure safe driving.
Analysis of the Professional Aspects of Medical Drugs Industry in the Republic of Serbia in Times of COVID-19 Pandemic
Authors: Milenković Jovana , Lakić Dragana , Bogavac-Stanojević Nataša
Published: May 2023

The research subject of this paper is the analysis of the attitudes of employees in pharmaceutical companies towards the business aspects of the pharmaceutical industry during and after the end of the pandemic in the Republic of Serbia. The aim is to examine the differences in the attitudes of employees, as well as to determine which variables predict the situations of endangering the professional reputation of pharmaceutical companies during the COVID-19 pandemic. The research was conducted by means of a survey during 2021 on a sample of 27 innovative and generic pharmaceutical companies. We used the SPSS program for descriptive statistics analysis, chi square test and binary logistic regression models. The findings show that there is a statistically significant difference in the expressed attitudes of employees in innovative and generic pharmaceutical companies in terms of coming to the office during the pandemic; the lack of medicines and medical devices used in the treatment of COVID-19 infections; the patient access to a chosen doctor; the expectations of the employees to continue working from home after the outbreak of the COVID-19 pandemic. The findings of the binary regression models show the slowdown in the supply chain, the access to doctors and working from the home office have not been perceived as creating situations of endangering professional reputations, that is, they contribute to the sustainable economic success. On the other hand, the introduction of digital technologies decreases the occurrence of conditions in which their professional reputation has been threatened.
Uncovering the Challenges of Sustainable Development in North Aceh: A Policy Analysis of Special Transfer Funds
Authors: Wijatmoko Erlan , Armawi Armaidy , Fathani Teuku Faisal
Published: May 2023

This study evaluates the management of two special funds in North Aceh, Indonesia, to promote sustainable development goals (SDGs) after a protracted conflict that brought the region to the brink of poverty and suffering. The special autonomy fund and the revenue-sharing funds for oil and gas are forms of fiscal decentralization provided by the central government to help Aceh recover from the conflict’s effects and natural disasters. Despite receiving these funds for over 13 years, Aceh remains among the poorest regions in Indonesia. This study used policy analyzing process theory to evaluate the management of these funds at the district level, specifically in North Aceh. A qualitative descriptive method that combines semi-structured interviews, field observations, and government documents, were used in this research. We revealed that the policy of managing these special funds has yet to achieve SDGs, particularly in North Aceh. The underutilization of revenue-sharing funds, the limited allocation of districts’ special autonomy funds, and the emphasis on infrastructure development as a priority have hindered progress and well-being, resulting in persistent poverty, unemployment, and continued dependence on transfer funds.
Assessing Chinese Textile and Apparel Industry Business Sustainability: The Role of Organization Green Culture, Green Dynamic Capabilities, and Green Innovation in Relation to Environmental Orientation and Business Sustainability
Authors: Xiaoyi Zhang , Yang Hailan , Kumar Nilesh , Bhutto Maqsood H. , Kun Wang , Hu Tianyang
Published: May 2023

The current study aims to evaluate the role of environmental orientation (EO) on green dynamic capabilities (GDCs), organization green culture (OGC), and green innovation (GIN) toward business sustainability (BUS) in the context of Chinese textile and apparel manufacturing firms. Natural resources-based view (NRBV) and dynamic capabilities view (DCV) were used as the theoretical lenses of the research. This study is quantitative, and a purposive sampling technique was employed to collect data from the managers working in textile and apparel manufacturing firms in China. The sample size consisted of 339 managers. Partial least-square structural equation modeling (PLS-SEM) was employed to analyze the data. The study’s findings show that EO significantly and positively influences OGC and GDCs. However, the positive influence of EO on GIN was insignificant. Moreover, the result indicates that GIN is a significant mediator in the relationships between OGC and BUS and GDCs and BUS. The results demonstrate how the Chinese textile and apparel industry EO improves GDCs, GIN, and OGC, which, in turn, benefits achieving long-term business sustainability.
Wave Power Trends over the Mediterranean Sea Based on Innovative Methods and 60-Year ERA5 Reanalysis
Authors: Acar Emine , Akpınar Adem , Kankal Murat , Amarouche Khalid
Published: May 2023

The present study aims to evaluate long-term wave power (Pwave) trends over the Mediterranean Sea using innovative and classical trend analysis techniques, considering the annual and seasonal means. For this purpose, the data were selected for the ERA5 reanalysis with 0.5° × 0.5° spatial resolution and 1 h temporal resolution during 60 years between 1962 and 2021. Spatial assessment of the annual and seasonal trends was first performed using the innovative trend analysis (ITA) and Mann–Kendall (MK) test. To obtain more detailed information, innovative polygon trend analysis (IPTA), improved visualization of innovative trend analysis (IV-ITA), and star graph methods were applied to annual, seasonal, and monthly mean Pwave at 12 stations selected. The results allow us to identify an increasing trend above the 10% change rate with the innovative method and above the 95% confidence level with the Mann–Kendall test in mean wave power in the Levantine basin and the Libyan Sea at all timescales. The use of various innovative methods offered similar results in certain respects and complemented each other.
Spatio-Temporal Analysis of Rural Development in China over the Past 40 Years
Authors: Lu Ying , de Vries Walter Timo
Published: May 2023

Over the past 40 years, rural China has witnessed drastic changes in its spatial and socio-economic development. In this study, we adopt a quantitative approach to analyze the spatio-temporal patterns of the rural development process. We build an indicator system with nine indicators from population, land, and industry dimensions and calculate the change rate of each indicator of 31 provinces in seven five-year development cycles from 1980 to 2018. Then, we identify five different development types and present their temporal evolution and spatial distribution. From the result, we can see that the predominant type changes under the influence of urbanization and industrialization processes and the development policies and strategies. The disparity between the western and eastern regions is obvious, and the city-clusters have a profound impact on the rural areas around them. We suggest that development policies and strategies should coordinate the relationship between population, land, and industry to achieve rural revitalization.
Exploring Corporate Sustainability in the Insurance Sector: A Case Study of a Multinational Enterprise Engaging with UN SDGs in Malaysia
Authors: Pranugrahaning Agnes , Donovan Jerome Denis , Topple Cheree , Masli Eryadi Kordi
Published: May 2023

Multinational enterprises (MNEs) are increasingly expected to integrate sustainability into their core business activities, moving beyond philanthropy or public advocacy. In particular, the financial sector is expected to support the Sustainable Development Goals (SDGs) as it plays a critical role in promoting sustainable development through its key roles as risk managers, insurers, investors and lenders. It has been acknowledged that the sector has the power to direct investments towards sustainable activities, encourage sustainable business practices, and promote sustainable development more broadly. However, for MNEs, including insurance companies, examining sustainability practices across subsidiaries operating in expanded geographic contexts becomes complex. Implementing corporate sustainability strategies is challenging, particularly when their globally-developed strategy intersects with local operations. However, limited attention has been given to the sustainability practices adopted by the financial sector at the subsidiary or local levels. This study aims to fill this gap by examining how multinational insurance companies operating in emerging markets manage their sustainability practices, particularly in aligning their global sustainability strategy with local operations. Utilising a corporate sustainability assessment process framework and focusing on the case study context of Allianz in Malaysia, this study provides a comprehensive picture not only of the sustainability practices that have been implemented but also of the important role that global and local operations play in translating global strategies to achieve sustainability into meaningful and contextualised local agendas for sustainability.
Economic Loss Assessment for Losses Due to Earthquake under an Integrated Building, Lifeline, and Transportation Nexus: A Spatial Computable General Equilibrium Approach for Shelby County, TN
Authors: Hu Yuchen , Cutler Harvey , Mao Yihua
Published: May 2023

Earthquakes have caused tremendous losses worldwide. Though unpredictable, comprehensive assessment of their impact on urban areas can facilitate effectiveness in mitigation strategies. This paper builds a spatial general equilibrium (SCGE) model for Shelby County, Tennessee, an area located in the most active seismic zone in the central and eastern U.S. Starting from the building, lifeline and transportation damages, this paper also develops means by which such damages can be integrated into the SCGE model for prompt effect estimation. Using novel approaches to represent substitution and shifting behaviors intra-regionally within the county, the model estimated a total of loss over $8 billion in domestic supply due to a hypothetical earthquake. Compared with the outcomes from the model without these behaviors, the magnitude of the losses is smaller in the model with these behaviors. This implies the resistance, resourcefulness and flexibility from economic resilience, as the level of physical damages do vary intra-regionally. Interestingly, although the percentage of losses in domestic supply varies almost linearly with the percentage loss in physical damage intra-regionally, the losses in employment are relatively evenly distributed. This also emphasizes the importance of the shifting and substitution behaviors which make the model profoundly spatial.
Predictive Churn Modeling for Sustainable Business in the Telecommunication Industry: Optimized Weighted Ensemble Machine Learning
Authors: Khoh Wee How , Pang Ying Han , Ooi Shih Yin , Wang Lillian-Yee-Kiaw , Poh Quan Wei
Published: May 2023

Customers are prominent resources in every business for its sustainability. Therefore, predicting customer churn is significant for reducing churn, particularly in the high-churn-rate telecommunications business. To identify customers at risk of churning, tactical marketing actions can be strategized to raise the likelihood of the churn-probable customers remaining as customers. This might provide a corporation with significant savings. Hence, in this work, a churn prediction system is developed to assist telecommunication operators in detecting potential churn customers. In the proposed framework, the input data quality is improved through the processes of exploratory data analysis and data preprocessing for identifying data errors and comprehending data patterns. Then, feature engineering and data sampling processes are performed to transform the captured data into an appropriate form for classification and imbalanced data handling. An optimized ensemble learning model is proposed for classification in this framework. Unlike other ensemble models, the proposed classification model is an optimized weighted soft voting ensemble with a sequence of weights applied to weigh the prediction of each base learner with the hypothesis that specific base learners in the ensemble have more skill than others. In this optimization, Powell’s optimization algorithm is applied to optimize the ensemble weights of influence according to the base learners’ importance. The efficiency of the proposed optimally weighted ensemble learning model is evaluated in a real-world database. The empirical results show that the proposed customer churn prediction system achieves a promising performance with an accuracy score of 84% and an F1 score of 83.42%. Existing customer churn prediction systems are studied. We achieved a higher prediction accuracy than the other systems, including machine learning and deep learning models.
A Symmetry Chaotic Model with Fractional Derivative Order via Two Different Methods
Authors: Elbadri Mohamed , Abdoon Mohamed A. , Berir Mohammed , Almutairi Dalal Khalid
Published: May 2023

In this article, we have investigated solutions to a symmetry chaotic system with fractional derivative order using two different methods—the numerical scheme for the ABC fractional derivative, and the Laplace decomposition method, with help from the MATLAB and Mathematica platforms. We have explored progressive and efficient solutions to the chaotic model through the successful implementation of two mathematical methods. For the phase portrait of the model, the profiles of chaos are plotted by assigning values to the attached parameters. Hence, the offered techniques are relevant for advanced studies on other models. We believe that the unique techniques that have been proposed in this study will be applied in the future to build and simulate a wide range of fractional models, which can be used to address more challenging physics and engineering problems.
The Treatment of Aquaculture Wastewater with Biological Aerated Filters: From the Treatment Process to the Microbial Mechanism
Authors: Ding Jiafeng , Meng Yunjuan , Lu Shihuan , Peng Yiwen , Yan Wen , Li Wenbing , Hu Jinchun , Ye Ting , Zhong Yuchi , Zhang Hangjun
Published: May 2023

Algal cell proliferation has posed significant problems for traditional water treatment facilities; these problems are attributed to surface hydrophilicity and electrostatic repulsion. Biological aerated filters (BAFs) have been extensively used in wastewater treatment to remove pollutants such as algal cells by utilizing the adsorption and separation capabilities of the filter media. In this study, a BAF was supplemented with biological filter medium (Marchantia polymorpha) to assess its effectiveness of pretreating aquaculture wastewater. In terms of process performance, steady and consistent treatment was achieved by the BAF with M. polymorpha (BAF2) under an algal cell density as high as 1.65 × 108 cell/L, with average removal rates for NH4+-N and algae cells of 74.4% and 81.9%, respectively. The photosynthetic activity parameters (rETRmax, α, Fv/Fm, and Ik) of the influent and effluent were quantitatively assessed, and M. polymorpha was found to remove algae by disrupting the photosynthetic system of the algal cells. Furthermore, the addition of the M. polymorpha filter medium enhanced the community structure of the functional microbes in the BAF system. The highest microbial community richness and diversity were observed in the BAF2. Meanwhile, M. polymorpha promoted an increase in the abundance of denitrifying bacteria, including Bdellovibrio and Pseudomonas. Overall, this work offers a unique perspective on the aquaculture wastewater pretreatment process and BAF design.