bluuebunny/crossref_metadata_2025 huggingface dataset:
Photodynamic Therapy with Zinc Phthalocyanine Inhibits the Stemness and Development of Colorectal Cancer: Time to Overcome the Challenging Barriers?
Authors: Gholizadeh Mahsa , Doustvandi Mohammad Amin , Mohammadnejad Fateme , Shadbad Mahdi Abdoli , Tajalli Habib , Brunetti Oronzo , Argentiero Antonella , Silvestris Nicola , Baradaran Behzad
Published: November 2021

Photodynamic therapy (PDT) is a light-based cancer therapy approach that has shown promising results in treating various malignancies. Growing evidence indicates that cancer stem cells (CSCs) are implicated in tumor recurrence, metastasis, and cancer therapy resistance in colorectal cancer (CRC); thus, targeting these cells can ameliorate the prognosis of affected patients. Based on our bioinformatics results, SOX2 overexpression is significantly associated with inferior disease-specific survival and worsened the progression-free interval of CRC patients. Our results demonstrate that zinc phthalocyanine (ZnPc)-PDT with 12 J/cm2 or 24 J/cm2 irradiation can substantially decrease tumor migration via downregulating MMP9 and ROCK1 and inhibit the clonogenicity of SW480 cells via downregulating CD44 and SOX2. Despite inhibiting clonogenicity, ZnPc-PDT with 12 J/cm2 irradiation fails to downregulate CD44 expression in SW480 cells. Our results indicate that ZnPc-PDT with 12 J/cm2 or 24 J/cm2 irradiation can substantially reduce the cell viability of SW480 cells and stimulate autophagy in the tumoral cells. Moreover, our results show that ZnPc-PDT with 12 J/cm2 or 24 J/cm2 irradiation can substantially arrest the cell cycle at the sub-G1 level, stimulate the intrinsic apoptosis pathway via upregulating caspase-3 and caspase-9 and downregulating Bcl-2. Indeed, our bioinformatics results show considerable interactions between the studied CSC-related genes with the studied migration- and apoptosis-related genes. Collectively, the current study highlights the potential role of ZnPc-PDT in inhibiting stemness and CRC development, which can ameliorate the prognosis of CRC patients.
Radical and Ionic Mechanisms in Rearrangements of o-Tolyl Aryl Ethers and Amines Initiated by the Grubbs–Stoltz Reagent, Et3SiH/KOtBu
Authors: Kolodziejczak Krystian , Stewart Alexander J. , Tuttle Tell , Murphy John A.
Published: November 2021

Rearrangements of o-tolyl aryl ethers, amines, and sulfides with the Grubbs–Stoltz reagent (Et3SiH + KOtBu) were recently announced, in which the ethers were converted to o-hydroxydiarylmethanes, while the (o-tol)(Ar)NH amines were transformed into dihydroacridines. Radical mechanisms were proposed, based on prior evidence for triethylsilyl radicals in this reagent system. A detailed computational investigation of the rearrangements of the aryl tolyl ethers now instead supports an anionic Truce–Smiles rearrangement, where the initial benzyl anion can be formed by either of two pathways: (i) direct deprotonation of the tolyl methyl group under basic conditions or (ii) electron transfer to an initially formed benzyl radical. By contrast, the rearrangements of o-tolyl aryl amines depend on the nature of the amine. Secondary amines undergo deprotonation of the N-H followed by a radical rearrangement, to form dihydroacridines, while tertiary amines form both dihydroacridines and diarylmethanes through radical and/or anionic pathways. Overall, this study highlights the competition between the reactive intermediates formed by the Et3SiH/KOtBu system.
Development of Starch-Based Materials Using Current Modification Techniques and Their Applications: A Review
Authors: Amaraweera Sumedha M. , Gunathilake Chamila , Gunawardene Oneesha H. P. , Fernando Nimasha M. L. , Wanninayaka Drashana B. , Dassanayake Rohan S. , Rajapaksha Suranga M. , Manamperi Asanga , Fernando Chakrawarthige A. N. , Kulatunga Asela K. , Manipura Aruna
Published: November 2021

Starch is one of the most common biodegradable polymers found in nature, and it is widely utilized in the food and beverage, bioplastic industry, paper industry, textile, and biofuel industries. Starch has received significant attention due to its environmental benignity, easy fabrication, relative abundance, non-toxicity, and biodegradability. However, native starch cannot be directly used due to its poor thermo-mechanical properties and higher water absorptivity. Therefore, native starch needs to be modified before its use. Major starch modification techniques include genetic, enzymatic, physical, and chemical. Among those, chemical modification techniques are widely employed in industries. This review presents comprehensive coverage of chemical starch modification techniques and genetic, enzymatic, and physical methods developed over the past few years. In addition, the current applications of chemically modified starch in the fields of packaging, adhesives, pharmaceuticals, agriculture, superabsorbent and wastewater treatment have also been discussed.
Characteristics and Pathogenicity of the Cell-Adapted Attenuated Porcine Epidemic Diarrhea Virus of the Non-S INDEL Cluster
Authors: Vu Thi Thu Hang , Yeom Minjoo , Moon Hyoungjoon , Tran Thi Nhan , Le Van Phan , Song Daesub
Published: November 2021

The high antigenic diversity of porcine epidemic diarrhea virus (PEDV) means that porcine epidemic diarrhea (PED) is a challenge for the global pig industry. Understanding the circulation of the virus to determine an optimal vaccine strategy is important in controlling the disease. In this study, we describe the genetic diversity of circulating PEDV based on the full sequences of spike genes of eight positive samples collected in Vietnam since 2018. Additionally, we developed a live attenuated vaccine candidate from the cell-adapted PEDV2 strain, which was continuously passaged until level 103 in VERO-CCL81 cells. PEDV2-p103, which belongs to the emerging non-S INDEL cluster, exhibited low virus shedding, did not induce lesions in the small intestine of challenged piglets, and had a high titer in the VERO-CCL81 cell at 48 h post-infection. These results suggest that the PEDV2-p103 strain could be a potential oral attenuated vaccine, and its immunogenicity and efficacy should be further assessed through in vivo tests.
Evaluation of Student Pharmacists’ Attitudes and Perceptions of Hormonal Contraception Prescribing in Indiana
Authors: Papineau J. Henry , Newlon Jenny L. , Ades Ryan S. , Vernon Veronica , Wilkinson Tracey A. , Thoma Lynn M. , Meredith Ashley H.
Published: November 2021

Community pharmacists’ scope of practice is expanding to include hormonal contraceptive prescribing. Prior to introducing statewide legislation, it is important to assess the perceptions of future pharmacists. A cross-sectional survey was distributed to 651 third- and fourth-year professional students enrolled at three colleges of pharmacy in Indiana. Data were collected between September and October 2019 to assess students’ attitudes about prescribing hormonal contraceptives, readiness to prescribe, perceived barriers, and desire for additional training. In total, 20.9% (n = 136) students responded. Most (89%, n = 121) believe that pharmacist-prescribed hormonal contraceptives would be beneficial to women in Indiana, and 91% (n = 124) reported interest in providing this service. Liability, personal beliefs, and religious beliefs were the most commonly cited perceived barriers. Most students felt they received adequate teaching on hormonal contraceptive methods (90%, n = 122) and hormonal contraceptive counseling (79%, n = 107); only 5% (n = 7) felt ready to provide the service at the time of survey completion. Student pharmacists in their final two years of pharmacy school are interested in prescribing hormonal contraceptives and believe that this service would be beneficial. This expansion of pharmacy practice would likely be supported by future pharmacists who feel the service could provide benefit to women seeking hormonal contraceptives in Indiana.
Photocatalytic Reduction of CO2 over Iron-Modified g-C3N4 Photocatalysts
Authors: Edelmannová Miroslava , Reli Martin , Kočí Kamila , Papailias Ilias , Todorova Nadia , Giannakopoulou Tatiana , Dallas Panagiotis , Devlin Eamonn , Ioannidis Nikolaos , Trapalis Christos
Published: November 2021

Pure g-C3N4 sample was prepared by thermal treatment of melamine at 520 °C, and iron-modified samples (0.1, 0.3 and 1.1 wt.%) were prepared by mixing g-C3N4 with iron nitrate and calcination at 520 °C. The photocatalytic activity of the prepared materials was investigated based on the photocatalytic reduction of CO2, which was conducted in a homemade batch reactor that had been irradiated from the top using a 365 nm Hg lamp. The photocatalyst with the lowest amount of iron ions exhibited an extraordinary methane and hydrogen evolution in comparison with the pure g-C3N4 and g-C3N4 with higher iron amounts. A higher amount of iron ions was not a beneficial for CO2 photoreduction because the iron ions consumed too many photogenerated electrons and generated hydroxyl radicals, which oxidized organic products from the CO2 reduction. It is clear that there are numerous reactions that occur simultaneously during the photocatalytic process, with several of them competing with CO2 reduction.
Secure Continuous-Variable Quantum Key Distribution with Machine Learning
Authors: Huang Duan , Liu Susu , Zhang Ling
Published: November 2021

Quantum key distribution (QKD) offers information-theoretical security, while real systems are thought not to promise practical security effectively. In the practical continuous-variable (CV) QKD system, the deviations between realistic devices and idealized models might introduce vulnerabilities for eavesdroppers and stressors for two parties. However, the common quantum hacking strategies and countermeasures inevitably increase the complexity of practical CV systems. Machine-learning techniques are utilized to explore how to perceive practical imperfections. Here, we review recent works on secure CVQKD systems with machine learning, where the methods for detections and attacks were studied.
The Opposite Roles of White Light in Regulating Germination of Fresh and Aged Seed in Tobacco
Authors: Wang Yao , Zhang Min , Dong Shuai , Liu Yi-Ling , Li Zhen-Hua
Published: November 2021

Light is one of the important environmental factors for seeds to evaluate whether the natural environment is appropriate for germination and subsequent seedlings emergence. The mechanism of light-mediated germination is mainly concerned with fresh seeds (FS) of model plants but is poorly understood in aged seeds. Here, the effects of light on germination of FS and naturally aged seeds (NAS) in tobacco and their relationship with plant hormones gibberellins (GA) and abscisic acid (ABA) were investigated. The results demonstrated that light promoted and inhibited the germination of FS and NAS, respectively. GA and ABA were involved in the germination control of NAS, as well as in FS. However, light suppressed GA signal and stimulated ABA signal in NAS, whereas it stimulated GA signal and suppressed ABA signal in FS. In addition, light stimulated the GA accumulation and reduction in ABA in FS while inhibiting the increase in GA level in NAS. Together, the present study demonstrates that light has opposite effects on the germination of FS and NAS, which are closely related to the metabolism and/or signaling of plant hormones ABA and GA.
Equivalence Ratio Measurements in CH4/Air Gases Based on the Spatial Distribution of the Emission Intensity of Femtosecond Laser-Induced Filament
Authors: Li Ming , Gu Jiangpeng , Zhang Dayuan , Gao Qiang , Li Bo
Published: November 2021

Femtosecond lasers have been used in combustion diagnostics. Based on the characteristics of femtosecond laser filamentation, many diagnostic techniques have been developed. Here, we propose a method, based on femtosecond laser filamentation, for equivalence ratio measurements in CH4/air gases. By measuring the spatially resolved spectra of the femtosecond laser-induced filament, we found that the variation of the equivalence ratio in the flow field would affect the spatial distribution of the emission intensity of femtosecond laser-induced filament. On this basis, the equivalence ratio was calibrated by using the relative spatial positions of N2 (337 nm) and C2 (516.5 nm) signals in the filament. This method overcomes the interference of local air disturbance, having lower measurement uncertainty.
Study of Natural Convection of Lithium-Ion Battery Module Employing Phase Change Material
Authors: Wu Horng-Wen , Ciou Yi-Chen , Wu Jun-Kuan , Huang De-An
Published: November 2021

When the Lithium-ion battery operates at high temperature, it would bring about short circuit; if it reaches a critical temperature, it will explode. It is important to reduce its maximum temperature by appropriate heat transfer technique. When it operates without an external force for cooling, it needs natural convection technique to take away heat dissipation. Therefore, this study numerically examines three-dimensional transient natural convection of cylindrical lithium-ion batteries inside a rectangular pack with air between cylinders. The heat transfer technique in this study applies PCM (phase change material) between cylinders without or with fin array on top changing distance between cells. The results indicated that for no fin array, the package adopting the PCM could achieve the peak temperature 14.2 °C smaller than the package adopting the air. However, the package adopting the PCM with fin array vertical to the top of the package can best enhance average Nusselt number by 120% compared with using air and no fin array. Replacing the air by the PCM can keep the peak temperature of the batteries within the desirable operation range.
Numerical Modelling and Multi Objective Optimization Analysis of Heavy Vehicle Chassis
Authors: Agarwal Abhishek , Mthembu Linda
Published: November 2021

The primary supporting structure of an automobile and its other vital systems is the chassis. The chassis structure is required to bear high shock, stresses, and vibration, and therefore it should possess adequate strength. The objective of current research is to analyze a heavy motor vehicle chassis using numerical and experimental methods. The CAD design and FE analysis is conducted using the ANSYS software. The design of the chassis is then optimized using Taguchi design of Experiments (DOE); the optimization techniques used are the central composite design (CCD) scheme and optimal space filling (OSF) design. Thereafter, sensitivity plots and response surface plots are generated. These plots allow us to determine the critical range of optimized chassis geometry values. The optimization results obtained from the CCD design scheme show that cross member 1 has a higher effect on the equivalent stresses as compared to cross members 2 and 3. The chassis mass reduction obtained from the CCD scheme is approximately 5.3%. The optimization results obtained from the OSF scheme shows that cross member 2 has a higher effect on equivalent stress as compared to cross members 1 and 3. The chassis mass reduction obtained from optimal space filling design scheme is approximately 4.35%.
Biomass Combustion Control in Small and Medium-Scale Boilers Based on Low Cost Sensing the Trend of Carbon Monoxide Emissions
Authors: Mižáková Jana , Piteľ Ján , Hošovský Alexander , Pavlenko Ivan , Ochowiak Marek , Khovanskyi Serhii
Published: November 2021

The article deals with the possibility of efficient control of small and medium-scale biomass-fired boilers by implementing low-cost sensors to sense the trend of carbon monoxide emissions into control of the biomass combustion process. Based on the theoretical analysis, a principle block diagram of the process control system was designed for the possibility of providing near-optimal control of the biomass combustion regardless of its quality parameters. A cost-effective hardware solution to obtain the dependence of CO emissions on O2 concentration in flue gas during combustion and new control algorithms was implemented into the process control and monitoring system of the biomass-fired boilers to test them in the real operation. A description of the designed control system, a data analysis of the monitored values and their impact on combustion process, and some results of the implemented control of the real biomass combustion process are presented in the article.
Simultaneous Quantitative Detection of HCN and C2H2 in Combustion Environment Using TDLAS
Authors: Weng Wubin , Aldén Marcus , Li Zhongshan
Published: November 2021

Emission of nitrogen oxides (NOx) and soot particles during the combustion of biomass fuels and municipal solid waste is a major environmental issue. Hydrogen cyanide (HCN) and acetylene (C2H2) are important precursors of NOx and soot particles, respectively. In the current work, infrared tunable diode laser absorption spectroscopy (IR-TDLAS), as a non-intrusive in situ technique, was applied to quantitatively measure HCN and C2H2 in a combustion environment. The P(11e) line of the first overtone vibrational band v1 of HCN at 6484.78 cm−1 and the P(27e) line of the v1 + v3 combination band of C2H2 at 6484.03 cm−1 were selected. However, the infrared absorption of the ubiquitous water vapor in the combustion environment brings great uncertainty to the measurement. To obtain accurate temperature-dependent water spectra between 6483.8 and 6485.8 cm−1, a homogenous hot gas environment with controllable temperatures varying from 1100 to 1950 K provided by a laminar flame was employed to perform systematic IR-TDLAS measurements. By fitting the obtained water spectra, water interference to the HCN and C2H2 measurement was sufficiently mitigated and the concentrations of HCN and C2H2 were obtained. The technique was applied to simultaneously measure the temporally resolved release of HCN and C2H2 over burning nylon 66 strips in a hot oxidizing environment of 1790 K.
Impact of Various Essential Oils and Plant Extracts on the Characterization of the Composite Seaweed Hydrocolloid and Gac Pulp (Momordica cochinchinensis) Edible Film
Authors: Tran Thuy Thi Bich , Vu Boi Ngoc , Saifullah Md , Nguyen Minh Huu , Pristijono Penta , Kirkman Timothy , Vuong Quan Van
Published: November 2021

Edible films and coatings have currently received increasing interest because of their potential in food applications. This study examined the effect of incorporated essential oils and natural plant extracts on the characteristics of the composite seaweed hydrocolloid and gac pulp films. Films were prepared by a casting technique, followed by measurement of physical, optical, barrier, mechanical, and structural properties. The results showed that adding plant oils and extracts significantly affected the physical, optical, mechanical, and structural properties of the composite films. Incorporation of the essential oils resulted in a reduction in moisture content and opacity while increasing values for Hue angle and elongation at break of the composite films. Besides, incorporation of the plant extracts showed increases in thickness, opacity, ΔE, Chroma, and elongation at the break, while there is a decrease in the Hue angle values of the composite films. In conclusion, incorporating plant essential oils and extracts into composite seaweed hydrocolloid and gac pulp films can enhance film properties, which can potentially be applied in food products.
A Mini Review on Pyrolysis of Natural Algae for Bio-Fuel and Chemicals
Authors: Xu Wei , Ding Keqiang , Hu Lihua
Published: November 2021

The disposal and use of natural algae have recently been the subject of great interest, due to increasing concern for environmental protection and resource utilization. In this paper, a mini review of recent research on the pyrolysis of natural algae, especially the algae from water blooms, is presented. The chemical compositions of the natural algae are summarized, and the pyrolysis properties of different compositions are reviewed. Non-catalytic, catalytic, and integrated catalytic processes are reviewed. Different ideas and methods for the production of bio-fuel or chemicals are discussed. Apparently, deoxygenation and denitrogenation are highly necessary for algae-based bio-fuel and catalysts play an important role in these processes. In addition, the integrated catalytic process, which involves catalysis and other operation conditions aside from the thermal treatment under inert atmosphere, shows potential for the valorization of algae-based bio-oil. Based on the recent concept and progress, the research gaps are discussed, followed by the challenges and proposals to achieve high-value utilization of the natural algae.
Evaluation of Eco-Environmental Quality in Qaidam Basin Based on the Ecological Index (MRSEI) and GEE
Authors: Jia Haowei , Yan Changzhen , Xing Xuegang
Published: November 2021

As the population has increased and the economy has developed in the Qaidam Basin, the demand for food and energy in the basin has increased, and the contradiction between economic development and ecological protection is gradually becoming prominent. In this study, the eco-environmental quality of the Qaidam Basin from 1986 to 2019 was evaluated and analyzed based on the Modified Remote Sensing Ecological Index (MRSEI) retrieved by the Google Earth Engine (GEE) and meteorological and socioeconomic auxiliary data. The results show that (1) the Qaidam Basin had a lower overall level of eco-environmental quality, with higher eco-environmental quality in the southeastern part of the basin and lower eco-environmental quality in the central and northwestern parts of the basin. (2) During the period of 1986 to 2019, the eco-environmental quality of the Qaidam Basin started to reverse in 2003; it decreased first and then increased, and the overall performance showed an upward trend over the past 34 years. The most obvious changes were in the northwestern, northeastern, southwestern and central parts of the basin. The eco-environmental quality continued to decline in the northwestern and rise in the northeastern and southwestern regions, and in the central part, it decreased first and then plateaued. (3) The eco-environmental quality of the Qaidam Basin was affected by both natural and human factors. From 1986 to 2019, the “warm and wet” climate in the basin promoted the growth of vegetation. Furthermore, the optimization of industrial structures alleviated the pressure of agriculture and livestock and jointly improved the ecological environment in the Qaidam Basin.
Analysis and Mitigation of Crosstalk Effect on Coastal GNSS-R Code-Level Altimetry Using L5 Signals from QZSS GEO
Authors: He Yunqiao , Xu Tianhe , Gao Fan , Wang Nazi , Meng Xinyue , Ning Baojiao
Published: November 2021

Coastal Global Navigation Satellite System Reflectometry (GNSS-R) can be used as a valuable supplement for conventional tide gauges, which can be applied for marine environment monitoring and disaster warning. Incidentally, an important problem in dual-antenna GNSS-R altimetry is the crosstalk effect, which means that the direct signal leaks into the down-looking antenna dedicated to the reflected signals. When the path delay between the direct and reflected signals is less than one chip length, the delay waveform of the reflected signal is distorted, and the code-level altimetry precision decreases consequently. To solve this problem, the author deduced the influence of signal crosstalk on the reflected signal structure as the same as the multipath effect. Then, a simulation and a coastal experiment are performed to analyze the crosstalk effect on code delay measurements. The L5 signal transmitted by the Quasi-Zenith Satellite System (QZSS) from a geosynchronous equatorial orbit (GEO) satellite is used to avoid the signal power variations with the elevation, so that high-precision GNSS-R code altimetry measurements are achieved in the experiment. Theoretically and experimentally, we found there exists a bias in proportion to the power of the crosstalk signals and a high-frequency term related to the phase delay between the direct and reflected signals. After weakening the crosstalk by correcting the delay waveform, the results show that the RMSE between 23-h sea level height (SSH) measurements and the in-situ observations is about 9.5 cm.
Daily Flood Monitoring Based on Spaceborne GNSS-R Data: A Case Study on Henan, China
Authors: Yang Wentao , Gao Fan , Xu Tianhe , Wang Nazi , Tu Jinsheng , Jing Lili , Kong Yahui
Published: November 2021

Flood is a kind of natural disaster that is extremely harmful and occurs frequently. To reduce losses caused by the hazards, it is urgent to monitor the disaster area timely and carry out rescue operations efficiently. However, conventional space observers cannot achieve sufficient spatiotemporal resolution. As spaceborne GNSS-R technique can observe the Earth’s surface with high temporal and spatial resolutions; and it is expected to provide a new solution to the problem of flood hazards. During 19–21 July 2021, Henan province, China, suffered a catastrophic flood and urban waterlogging. In order to test the feasibility of flood disaster monitoring on a daily basis by using GNSS-R observations, the CYGNSS (Cyclone Global Navigation Satellite System) Level 1 Science Data were processed for a few days before and after the flood to obtain surface reflectivity by correcting the analog power. Afterwards, the flood was monitored and mapped daily based on the analysis of changes in surface reflectivity from spaceborne GNSS-R mission. The results were evaluated based on the image from MODIS (Moderate Resolution Imaging Spectroradiometer) data, and compared with the observations of SMAP (Soil Moisture Active Passive) in the same period. The results show that the area with high CYGNSS reflectivity corresponds to the flooded area monitored by MODIS, and it is also in high agreement with SMAP. Moreover, CYGNSS can achieve more detailed mapping and quantification of the inundated area and the duration of the flood, respectively, in line with the specific situation of the flood. Thus, spaceborne GNSS-R technology can be used as a method to monitor floods with high temporal resolution.
The Comparative Estimation of Primary Students’ Programming Outcomes Based on Traditional and Distance Out-of-School Extracurricular Informatics Education in Electronics Courses during the Challenging COVID-19 Period
Authors: Panskyi Taras , Biedroń Sebastian , Grudzień Krzysztof , Korzeniewska Ewa
Published: November 2021

The authors decided to investigate the impact of the lockdown period and the resulting limitations in informatics education, especially programming, in out-of-school electronics courses using traditional and distance learning modes in primary school COVID-19 pandemic settings. Two extracurricular courses were held successively; the first electronics course was performed in a traditional out-of-school learning mode using Arduino kits, while the other was held using the TinkerCad circuits virtual environment in distance learning mode. A structured questionnaire was administered to students to map their knowledge of programming. The questionnaire consists of three emotional dimensions: enjoyment, satisfaction and motivation. The fourth dimension was dedicated to the students’ programming outcomes. Three emotional dimensions were addressed to primary school students, while the fourth dimension was addressed to the tutors’ observations toward the students’ programming outcomes. The obtained results revealed that learning modes have no significant impact on students perceiving the programming issues. However, three emotional dimensions revealed a significant difference in the students’ enjoyment, satisfaction and motivation in favor of the traditional learning mode. Our findings are of particular interest in light of possible crisis-prompted distance education in the future but can also serve to inform government institutions and policymakers seeking to develop effective concepts for successful distance learning.
An Alternative Statistical Characterization of TWDP Fading Model
Authors: Maric Almir , Kaljic Enio , Njemcevic Pamela
Published: November 2021

Two-wave with diffuse power (TWDP) is one of the most promising models for the description of small-scale fading effects in 5G networks, which employs mmWave band, and in wireless sensor networks deployed in different cavity environments. However, its current statistical characterization has several fundamental issues. Primarily, conventional TWDP parameterization is not in accordance with the model’s underlying physical mechanisms. In addition, available TWDP expressions for PDF, CDF, and MGF are given either in integral or approximate forms, or as mathematically untractable closed-form expressions. Consequently, the existing TWDP statistical characterization does not allow accurate evaluation of system performance in all fading conditions for most modulation and diversity techniques. In this regard, physically justified TWDP parameterization is proposed and used for further calculations. Additionally, exact infinite-series PDF and CDF are introduced. Based on these expressions, the exact MGF of the SNR is derived in a form suitable for mathematical manipulations. The applicability of the proposed MGF for derivation of the exact average symbol error probability (ASEP) is demonstrated with the example of M-ary PSK modulation. The derived M-ary PSK ASEP expression is further simplified for large SNR values in order to obtain a closed-form asymptotic ASEP, which is shown to be applicable for SNR > 20 dB. All proposed expressions are verified by Monte Carlo simulation in a variety of TWDP fading conditions.
Distributed Optical Fiber Sensor Applications in Geotechnical Monitoring
Authors: Minardo Aldo , Zeni Luigi , Coscetta Agnese , Catalano Ester , Zeni Giovanni , Damiano Emilia , De Cristofaro Martina , Olivares Lucio
Published: November 2021

We report the experimental application of distributed optical fiber sensors, based on stimulated Brillouin scattering (SBS), to the monitoring of a small-scale granular slope reconstituted in an instrumented flume and subjected to artificial rainfall until failure, and to the monitoring of a volcanic rock slope. The experiments demonstrate the sensors’ ability to reveal the sudden increase in soil strain that foreruns the failure in a debris flow phenomenon, as well as to monitor the fractures in the tuff rocks. This study offers an important perspective on the use of distributed optical fiber sensors in the setting up of early warning systems for landslides in both rock and unconsolidated materials.
A Deep Learning Approach for Foot Trajectory Estimation in Gait Analysis Using Inertial Sensors
Authors: Guimarães Vânia , Sousa Inês , Correia Miguel Velhote
Published: November 2021

Gait performance is an important marker of motor and cognitive decline in older adults. An instrumented gait analysis resorting to inertial sensors allows the complete evaluation of spatiotemporal gait parameters, offering an alternative to laboratory-based assessments. To estimate gait parameters, foot trajectories are typically obtained by integrating acceleration two times. However, to deal with cumulative integration errors, additional error handling strategies are required. In this study, we propose an alternative approach based on a deep recurrent neural network to estimate heel and toe trajectories. We propose a coordinate frame transformation for stride trajectories that eliminates the dependency from previous strides and external inputs. Predicted trajectories are used to estimate an extensive set of spatiotemporal gait parameters. We evaluate the results in a dataset comprising foot-worn inertial sensor data acquired from a group of young adults, using an optical motion capture system as a reference. Heel and toe trajectories are predicted with low errors, in line with reference trajectories. A good agreement is also achieved between the reference and estimated gait parameters, in particular when turning strides are excluded from the analysis. The performance of the method is shown to be robust to imperfect sensor-foot alignment conditions.
Deep Learning for the Industrial Internet of Things (IIoT): A Comprehensive Survey of Techniques, Implementation Frameworks, Potential Applications, and Future Directions
Authors: Latif Shahid , Driss Maha , Boulila Wadii , Huma Zil e , Jamal Sajjad Shaukat , Idrees Zeba , Ahmad Jawad
Published: November 2021

The Industrial Internet of Things (IIoT) refers to the use of smart sensors, actuators, fast communication protocols, and efficient cybersecurity mechanisms to improve industrial processes and applications. In large industrial networks, smart devices generate large amounts of data, and thus IIoT frameworks require intelligent, robust techniques for big data analysis. Artificial intelligence (AI) and deep learning (DL) techniques produce promising results in IIoT networks due to their intelligent learning and processing capabilities. This survey article assesses the potential of DL in IIoT applications and presents a brief architecture of IIoT with key enabling technologies. Several well-known DL algorithms are then discussed along with their theoretical backgrounds and several software and hardware frameworks for DL implementations. Potential deployments of DL techniques in IIoT applications are briefly discussed. Finally, this survey highlights significant challenges and future directions for future research endeavors.
A Highly Sensitive Ammonia Gas Sensor Using Micrometer-Sized Core–Shell-Type Spherical Polyaniline Particles
Authors: Matsuguchi Masanobu , Nakamae Tomoki , Fujisada Ryoya , Shiba Shunsuke
Published: November 2021

A highly sensitive NH3 gas sensor based on micrometer-sized polyaniline (PANI) spheres was successfully fabricated. The PANI microspheres were prepared via a facile in situ chemical oxidation polymerization in a polystyrene microsphere dispersion solution, resulting in a core–shell structure. The sensor response increased as the diameter of the microspheres increased. The PSt@PANI(4.5) sensor, which had microspheres with a 4.5 μm average diameter, showed the largest response value of 77 for 100 ppm dry NH3 gas at 30 °C, which was 20 times that of the PANI-deposited film-based sensor. Even considering measurement error, the calculated detection limit was 46 ppb. A possible reason for why high sensitivity was achieved is simply the use of micrometer-sized PANI spherical particles. This research succeeded in providing a new and simple technology for developing a high-sensitivity NH3 gas sensor that operates at room temperature.
Brain MR Image Enhancement for Tumor Segmentation Using 3D U-Net
Authors: Ullah Faizad , Ansari Shahab U. , Hanif Muhammad , Ayari Mohamed Arselene , Chowdhury Muhammad Enamul Hoque , Khandakar Amith Abdullah , Khan Muhammad Salman
Published: November 2021

MRI images are visually inspected by domain experts for the analysis and quantification of the tumorous tissues. Due to the large volumetric data, manual reporting on the images is subjective, cumbersome, and error prone. To address these problems, automatic image analysis tools are employed for tumor segmentation and other subsequent statistical analysis. However, prior to the tumor analysis and quantification, an important challenge lies in the pre-processing. In the present study, permutations of different pre-processing methods are comprehensively investigated. In particular, the study focused on Gibbs ringing artifact removal, bias field correction, intensity normalization, and adaptive histogram equalization (AHE). The pre-processed MRI data is then passed onto 3D U-Net for automatic segmentation of brain tumors. The segmentation results demonstrated the best performance with the combination of two techniques, i.e., Gibbs ringing artifact removal and bias-field correction. The proposed technique achieved mean dice score metrics of 0.91, 0.86, and 0.70 for the whole tumor, tumor core, and enhancing tumor, respectively. The testing mean dice scores achieved by the system are 0.90, 0.83, and 0.71 for the whole tumor, core tumor, and enhancing tumor, respectively. The novelty of this work concerns a robust pre-processing sequence for improving the segmentation accuracy of MR images. The proposed method overcame the testing dice scores of the state-of-the-art methods. The results are benchmarked with the existing techniques used in the Brain Tumor Segmentation Challenge (BraTS) 2018 challenge.
Analysis of Laser Sensors and Camera Vision in the Shoe Position Inspection System
Authors: Klarák Jaromír , Kuric Ivan , Zajačko Ivan , Bulej Vladimír , Tlach Vladimír , Józwik Jerzy
Published: November 2021

Inspection systems are currently an evolving field in the industry. The main goal is to provide a picture of the quality of intermediates and products in the production process. The most widespread sensory system is camera equipment. This article describes the implementation of camera devices for checking the location of the upper on the shoe last. The next part of the article deals with the analysis of the application of laser sensors in this task. The results point to the clear advantages of laser sensors in the inspection task of placing the uppers on the shoe’s last. The proposed method defined the resolution of laser scanners according to the type of scanned surface, where the resolution of point cloud ranged from 0.16 to 0.5 mm per point based on equations representing specific points approximated to polynomial regression in specific places, which are defined in this article. Next, two inspection systems were described, where one included further development in the field of automation and Industry 4.0 and with a high perspective of development into the future. The main aim of this work is to conduct analyses of sensory systems for inspection systems and their possibilities for further work mainly based on the resolution and quality of obtained data. For instance, dependency on scanning complex surfaces and the achieved resolution of scanned surfaces.
Air Corridors: Concept, Design, Simulation, and Rules of Engagement
Authors: Muna Sabrina Islam , Mukherjee Srijita , Namuduri Kamesh , Compere Marc , Akbas Mustafa Ilhan , Molnár Péter , Subramanian Ravichandran
Published: November 2021

Air corridors are an integral part of the advanced air mobility infrastructure. They are the virtual highways in the sky for the transportation of people and cargo in a controlled airspace at an altitude of around 1000 ft. to 2000 ft. above ground level. These corridors will be utilized by (unmanned) air taxis, which will be deployed in rural and metropolitan regions to carry passengers and freight, as well as air ambulances, which will be deployed to offer first responder services such as 911 emergencies. This paper presents fundamental insights into the design of air corridors with high operational efficiency as well as zero collisions. It begins with the definitions of air cube, skylane or track, intersection, vertiport, gate, and air corridor. Then a multi-layered air corridor model is proposed. Traffic at intersections is analyzed in detail with examples of vehicles turning in different directions. The concept of capacity of an air corridor is introduced along with the nature of distribution of locations of vehicles in the air corridor and collision probability inside the corridor are discussed. Finally, results of traffic flow simulations are presented.
Intelligent Mining of Urban Ventilation Corridors Based on High-Precision Oblique Photographic Images
Authors: Chen Chaoxiang , Ye Shiping , Bai Zhican , Wang Juan , Zhang Zongbiao , Ablameyko Sergey
Published: November 2021

With the advancement of urbanization and the impact of industrial pollution, the issue of urban ventilation has attracted increasing attention. Research on urban ventilation corridors is a hotspot in the field of urban planning. Traditional studies on ventilation corridors mostly focus on qualitative or simulated research on urban climate issues such as the intensified urban heat island effect, serious environmental pollution, and insufficient climate adaptability. Based on the high-precision urban remote sensing image data obtained by aeromagnetic oblique photography, this paper calculates the frontal area density of the city with reference to the urban wind statistics. Based on the existing urban patterns, template matching technology was used to automatically excavate urban ventilation corridors, which provides scientific and reasonable algorithmic support for the rapid construction of potential urban ventilation corridor paths. It also provides technical methods and decision basis for low-carbon urban planning, ecological planning and microclimate optimization design. This method was proved to be effective through experiments in Deqing city, Zhejiang Province, China.
An Extended Methodology for Sizing Solar Unmanned Aerial Vehicles: Theory and Development of a Python Framework for Design Assist
Authors: da Silva José Roberto Cândido , Pacheco Gefeson Mendes
Published: November 2021

There is a growing interest in using unmanned aerial vehicles (UAVs) in the most diverse application areas from agriculture to remote sensing, that determine the need to project and define mission profiles of the UAVs. In addition, solar photovoltaic energy increases the flight autonomy of this type of aircraft, forming the term Solar UAV. This study proposes an extended methodology for sizing Solar UAVs that take off from a runway. This methodology considers mission parameters such as operating location, altitude, flight speed, flight endurance, and payload to sizing the aircraft parameters, such as wingspan, area of embedded solar cells panels, runway length required for takeoff and landing, battery weight, and the total weight of the aircraft. Using the Python language, we developed a framework to apply the proposed methodology and assist in designing a Solar UAV. With this framework, it was possible to perform a sensitivity analysis of design parameters and constraints. Finally, we performed a simulation of a mission, checking the output parameters.
Verification of Angular Response of Sky Quality Meter with Quasi-Punctual Light Sources
Authors: Bartolomei Mirco , Olivieri Lorenzo , Bettanini Carlo , Cavazzani Stefano , Fiorentin Pietro
Published: November 2021

Sky Quality Meter (SQM) is a commercial instrument based on photometers widely used by amateur astronomers for skyglow measurement from the ground. In the framework of the MINLU project, two SQM-LE units were integrated in an autonomous sensor suite realized and tested at University of Padova for monitoring light pollution from drones or sounding balloons. During the ground tests campaign before airborne measurement, the performance of both SQM units was verified in laboratory using controlled light sources as a reference input; the results showed that both units presented an angular response deviating consistently from the expected performance and that the sensors’ field of view was larger than the one declared in the manufacturer’s datasheet. This aspect in particular would affect direct skyglow measurements during flight as light sources close to the boundaries of the field of view would not be attenuated but instead detected by the sensors. As a direct consequence, the measurement of low-intensity skyglows at stratospheric altitudes could be affected by high-intensity punctual sources acting as lateral disturbances. A dedicated test campaign was therefore conceived and realized to investigate SQM unit response to light sources in the field of view and identify the true angular response curve; the setup consisted in a controlled rotatory stage moving the unit in front of a fixed diffusive light source. Different test conditions were used to validate the experimental procedure, demonstrating the repeatability of the measurements. This paper presents the experimental campaign and the resulting SQM angular response curve; results indicate for both SQMs a larger than expected field of view and the presence of a double peak in the angular response, which is likely related to a non-perfect alignment of SQMs collimation optics. Furthermore, the wider resulting curves suggest that the contribution of lateral sources is more prominent with respect to the response predicted by the manufacturer. For this reason, the utilization of baffles to restrict SQMs field of view is analyzed to minimize the disturbance of lateral light sources and two different geometries are presented.
An Algorithm for Fitting Sphere Target of Terrestrial LiDAR
Authors: Shi Yintao , Zhao Gang , Wang Maomei , Xu Yi , Zhu Dadong
Published: November 2021

The sphere target played a vital role in terrestrial LiDAR applications, and solving its geometrical center based on point cloud was a widely concerned problem. In this study, we proposed a newly finite random search algorithm for sphere target fitting. Based on the point cloud data and the geometric characteristics of the sphere target, the algorithm realized the target sphere fitting from the perspective of probability and statistics with the help of parameter estimation. Firstly, an initial constraint space was constructed, and the initial center and radius were determined by finite random search. Then, the optimal spherical center and radius were determined gradually through continuous iterative optimization. We tested the algorithm with the simulated and realistic point cloud. Experimental results showed that the proposed algorithm could be effectively applied to all kinds of point cloud fitting. When the coverage rate was bigger than 30%, the fitting accuracy could reach within 0.01 mm for all kinds of point clouds. When the coverage rate was less than 20%, the fitting accuracy can reach ±1 mm, although it was reduced to a certain extent.
A Moving Ship Detection and Tracking Method Based on Optical Remote Sensing Images from the Geostationary Satellite
Authors: Yu Wei , You Hongjian , Lv Peng , Hu Yuxin , Han Bing
Published: November 2021

Geostationary optical remote sensing satellites, such as the GF-4, have a high temporal resolution and wide coverage, which enables the continuous tracking and observation of ship targets over a large range. However, the ship targets in the images are usually small and dim and the images are easily affected by clouds, islands and other factors, which make it difficult to detect the ship targets. This paper proposes a new method for detecting ships moving on the sea surface using GF-4 satellite images. First, the adaptive nonlinear gray stretch (ANGS) method was used to enhance the image and highlight small and dim ship targets. Second, a multi-scale dual-neighbor difference contrast measure (MDDCM) method was designed to enable detection of the position of the candidate ship target. The shape characteristics of each candidate area were analyzed to remove false ship targets. Finally, the joint probability data association (JPDA) method was used for multi-frame data association and tracking. Our results suggest that the proposed method can effectively detect and track moving ship targets in GF-4 satellite optical remote sensing images, with better detection performance than other classical methods.