bluuebunny/crossref_metadata_2025 huggingface dataset:
Production and Properties of Microbial Polyhydroxyalkanoates Synthesized from Hydrolysates of Jerusalem Artichoke Tubers and Vegetative Biomass
Authors: Volova Tatiana G. , Kiselev Evgeniy G. , Demidenko Alexey V. , Zhila Natalia O. , Nemtsev Ivan V. , Lukyanenko Anna V.
Published: December 2021

One of the major challenges in PHA biotechnology is optimization of biotechnological processes of the entire synthesis, mainly by using new inexpensive carbon substrates. A promising substrate for PHA synthesis may be the sugars extracted from the Jerusalem artichoke. In the present study, hydrolysates of Jerusalem artichoke (JA) tubers and vegetative biomass were produced and used as carbon substrate for PHA synthesis. The hydrolysis procedure (the combination of aqueous extraction and acid hydrolysis, process temperature and duration) influenced the content of reducing substances (RS), monosaccharide contents, and the fructose/glucose ratio. All types of hydrolysates tested as substrates for cultivation of three strains—C. necator B-10646 and R. eutropha B 5786 and B 8562—were suitable for PHA synthesis, producing different biomass concentrations and polymer contents. The most productive process, conducted in 12-L fermenters, was achieved on hydrolysates of JA tubers (X = 66.9 g/L, 82% PHA) and vegetative biomass (55.1 g/L and 62% PHA) produced by aqueous extraction of sugars at 80 °C followed by acid hydrolysis at 60 °C, using the most productive strain, C. necator B-10646. The effects of JA hydrolysates on physicochemical properties of PHAs were studied for the first time. P(3HB) specimens synthesized from the JA hydrolysates, regardless of the source (tubers or vegetative biomass), hydrolysis conditions, and PHA producing strain employed, exhibited the 100–120 °C difference between the Tmelt and Tdegr, prevailing of the crystalline phase over the amorphous one (Cx between 69 and 75%), and variations in weight average molecular weight (409–480) kDa. Supplementation of the culture medium of C. necator B-10646 grown on JA hydrolysates with potassium valerate and ε-caprolactone resulted in the synthesis of P(3HB-co-3HV) and P(3HB-co-4HB) copolymers that had decreased degrees of crystallinity and molecular weights, which influenced the porosity and surface roughness of polymer films prepared from them. The study shows that JA hydrolysates used as carbon source enabled productive synthesis of PHAs, comparable to synthesis from pure sugars. The next step is to scale up PHA synthesis from JA hydrolysates and conduct the feasibility study. The present study contributes to the solution of the critical problem of PHA biotechnology—finding widely available and inexpensive substrates.
Tailoring Poly(lactic acid) (PLA) Properties: Effect of the Impact Modifiers EE-g-GMA and POE-g-GMA
Authors: dos Santos Filho Edson Antonio , Luna Carlos Bruno Barreto , Siqueira Danilo Diniz , Ferreira Eduardo da Silva Barbosa , Araújo Edcleide Maria
Published: December 2021

Poly(ethylene-octene) grafted with glycidyl methacrylate (POE-g-GMA) and ethylene elastomeric grafted with glycidyl methacrylate (EE-g-GMA) were used as impact modifiers, aiming for tailoring poly(lactic acid) (PLA) properties. POE-g-GMA and EE-g-GMA was used in a proportion of 5; 7.5 and 10%, considering a good balance of properties for PLA. The PLA/POE-g-GMA and PLA/EE-g-GMA blends were processed in a twin-screw extruder and injection molded. The FTIR spectra indicated interactions between the PLA and the modifiers. The 10% addition of EE-g-GMA and POE-g-GMA promoted significant increases in impact strength, with gains of 108% and 140%, respectively. These acted as heterogeneous nucleating agents in the PLA matrix, generating a higher crystallinity degree for the blends. This impacted to keep the thermal deflection temperature (HDT) and Shore D hardness at the same level as PLA. By thermogravimetry (TG), the blends showed increased thermal stability, suggesting a stabilizing effect of the modifiers POE-g-GMA and EE-g-GMA on the PLA matrix. Scanning electron microscopy (SEM) showed dispersed POE-g-GMA and EE-g-GMA particles, as well as the presence of ligand reinforcing the systems interaction. The PLA properties can be tailored and improved by adding small concentrations of POE-g-GMA and EE-g-GMA. In light of this, new environmentally friendly and semi-biodegradable materials can be manufactured for application in the packaging industry.
Effects of Dynamic Crosslinking on Crystallization, Structure and Mechanical Property of Ethylene-Octene Elastomer/EPDM Blends
Authors: Wang Yuan-Xia , Wang Chen-Chen , Shi Ying , Liu Li-Zhi , Bai Nan , Song Li-Fu
Published: December 2021

The dynamic crosslinking method has been widely used to prepare rubber/plastic blends with thermoplastic properties, and the rubber phase is crosslinked in these blends. Both polyolefin elastomer (POE) and ethylene-propylene-diene monomer rubber (EPDM) can be crosslinked, which is different from usual dynamic crosslinking components. In this paper, dynamic crosslinked POE/EPDM blends were prepared. For POE/EPDM blends without dynamic crosslinking, EPDM can play a nucleation role, leading to POE crystallizing at a higher temperature. After dynamic crosslinking, the crosslinking points hinder the mobility of POE chains, resulting in smaller crystals, but having too many crosslinking points suppresses POE crystallization. Synchrotron radiation studies show that phase separation occurs and phase regions form in non-crosslinked blends. After crosslinking, crosslinking points connecting EPDM and part of POE chains, enabling more POE to enter the EPDM phase and thus weakening phase separation, indicates that dynamic crosslinking improves the compatibility of POE/EPDM, also evidenced by a lower β conversion temperature and higher α conversion temperature than neat POE from dynamic mechanical analysis. Moreover, crosslinking networks hinder the crystal fragmentation during stretching and provide higher strength, resulting in 8.3% higher tensile strength of a 10 wt% EPDM blend than neat POE and almost the same elongation at break. Though excessive crosslinking points offer higher strength, they weaken the elongation at break.
Correlation of Air Permeability to Other Breathability Parameters of Textiles
Authors: Adámek Karel , Havelka Antonin , Kůs Zdenek , Mazari Adnan
Published: December 2021

In the field of textile comfort of smart textiles, the breathability of the material is very important. That includes the flow of air, water and water vapours through the textile material. All these experiments are time consuming and costly; only air permeability is much faster and economical. The research is performed to find correlation between these phenomena of breathability and to predict the permeability based on only the air permeability measurement. Furthermore, it introduces a new way of expressing the Ret (water vapour resistance) unit according to SI standards as it is connected with the air permeability of garments. The need to find a correlation between air permeability and water vapour permeability is emphasised in order to facilitate the assessment of clothing comfort. The results show that there is a strong relation between air permeability and water vapour permeability for most of the textile material.
Local Variations in Carbohydrates and Matrix Lignin in Mechanically Graded Bamboo Culms
Authors: Jin Kexia , Ling Zhe , Jin Zhi , Ma Jianfeng , Yang Shumin , Liu Xinge , Jiang Zehui
Published: December 2021

The mechanical performance of bamboo is highly dependent on its structural arrangement and the properties of biomacromolecules within the cell wall. The relationship between carbohydrates topochemistry and gradient micromechanics of multilayered fiber along the diametric direction was visualized by combined microscopic techniques. Along the radius of bamboo culms, the concentration of xylan within the fiber sheath increased, while that of cellulose and lignin decreased gradually. At cellular level, although the consecutive broad layer (Bl) of fiber revealed a relatively uniform cellulose orientation and concentration, the outer Bl with higher lignification level has higher elastic modulus (19.59–20.31 GPa) than that of the inner Bl close to the lumen area (17.07–19.99 GPa). Comparatively, the cell corner displayed the highest lignification level, while its hardness and modulus were lower than that of fiber Bl, indicating the cellulose skeleton is the prerequisite of cell wall mechanics. The obtained cytological information is helpful to understand the origin of the anisotropic mechanical properties of bamboo.
Delving into the Role of Dietary Fiber in Gluten-Free Bread Formulations: Integrating Fundamental Rheological, Technological, Sensory, and Nutritional Aspects
Authors: Djordjević Marijana , Djordjević Miljana , Šoronja-Simović Dragana , Nikolić Ivana , Šereš Zita
Published: December 2021

The evidenced relevance of dietary fibers (DF) as functional ingredients shifted the research focus towards their incorporation into gluten-free (GF) bread, aiming to attain the DF contents required for the manifestation of health benefits. Numerous studies addressing the inclusion of DF from diverse sources rendered useful information regarding the role of DF in GF batter’s rheological properties, as well as the end product’s technological and nutritional qualities. The presented comprehensive review aspires to provide insight into the changes in fiber-enriched GF batter’s fundamental rheological properties, and technological, sensory, and nutritional GF bread quality from the insoluble and soluble DF (IDF and SDF) perspective. Different mechanisms for understanding IDF and SDF action on GF batter and bread were discussed. In general, IDF and SDF can enhance, but also diminish, the properties of GF batter and bread, depending on their addition level and the presence of available water in the GF system. However, it was seen that SDF addition provides a more homogenous GF batter structure, leading to bread with higher volumes and softer crumb, compared to IDF. The sensory properties of fiber-enriched GF breads were acceptable in most cases when the inclusion level was up to 7 g/100 g, regardless of the fiber type, enabling the labeling of the bread as a source of fiber.
Box Girder Optimization by Orthogonal Experiment Design and GA-BP Algorithm in the Gondola Car Body
Authors: Liu Wenfei , Wang Yuming , Wang Tianyou
Published: December 2021

Box girder is an important bearing and force transmitting component in the gondola car body; the rationality of its structure directly affects the life of the whole car body. In order to solve disadvantage of the traditional box girder optimization method, which mainly depends on design experience, the combined method of orthogonal experimental design and the genetic algorithm-back propagation (GA-BP) algorithm is used for the structural optimization of bolster beam in this paper. Nine groups of parameters were established by orthogonal experiment, which can give typical samples for GA-BP optimization. Then, the bolster beam is optimized by the GA-BP algorithm, and the new gondola car body model is established with the optimized parameters. The finite element analysis results show that the minimum stress is found by using the GA-BP algorithm, which is basically consistent with the simulation results. Finally, the results show that the combined method of orthogonal experimental design and GA-BP algorithm is feasible to the box girder optimization of the gondola car body. Meanwhile, the optimization results of bolster beam will provide a reference for the structural design of the heavy haul wagon body.
Ensemble Negatively-Charged Nitrogen-Vacancy Centers in Type-Ib Diamond Created by High Fluence Electron Beam Irradiation
Authors: Ishii Shuya , Saiki Seiichi , Onoda Shinobu , Masuyama Yuta , Abe Hiroshi , Ohshima Takeshi
Published: December 2021

Electron beam irradiation into type-Ib diamond is known as a good method for the creation of high concentration negatively-charged nitrogen-vacancy (NV−) centers by which highly sensitive quantum sensors can be fabricated. In order to understand the creation mechanism of NV− centers, we study the behavior of substitutional isolated nitrogen (P1 centers) and NV− centers in type-Ib diamond, with an initial P1 concentration of 40–80 ppm by electron beam irradiation up to 8.0 × 1018 electrons/cm2. P1 concentration and NV− concentration were measured using electron spin resonance and photoluminescence measurements. P1 center count decreases with increasing irradiation fluence up to 8.0 × 1018 electrons/cm2. The rate of decrease in P1 is slightly lower at irradiation fluence above 4.0 × 1018 electrons/cm2 especially for samples of low initial P1 concentration. Comparing concentration of P1 centers with that of NV− centers, it suggests that a part of P1 centers plays a role in the formation of other defects. The usefulness of electron beam irradiation to type-Ib diamonds was confirmed by the resultant conversion efficiency from P1 to NV− center around 12–19%.
Reflections on Certain Principles That May Guide a New Commentary (Tafsir) of the Qur’an
Authors: Khalidi Tarif
Published: December 2021

The author starts from his experience as a translator of the Qur’an to argue on the need for a new commentary. The aim of such a new approach would be to convey a vision of Islam more in tune with Islamic history. Further, this is also needed in relation to the substantial Muslim communities living outside of the Muslim world. Antecedents are important in this and especially those coming from the so-called literary moment in the 20th-century Qur’an commentary tradition. A new commentary should be conducted by a committee. Additionally, the second part of the paper explores this possibility and what this committee should take care of in this direction, such as gender-consciousness or environment questions.
A Comparative Study of Interannual Oscillation Models for Determining Geophysical Polar Motion Excitations
Authors: Wińska Małgorzata
Published: December 2021

Similar to seasonal and intraseasonal variations in polar motion (PM), interannual variations are also largely caused by changes in the angular momentum of the Earth’s geophysical fluid layers composed of the atmosphere, the oceans, and in-land hydrologic flows (AOH). Not only are inland freshwater systems crucial for interannual PM fluctuations, but so are atmospheric surface pressures and winds, oceanic currents, and ocean bottom pressures. However, the relationship between observed geodetic PM excitations and hydro-atmospheric models has not yet been determined. This is due to defects in geophysical models and the partial knowledge of atmosphere–ocean coupling and hydrological processes. Therefore, this study provides an analysis of the fluctuations of PM excitations for equatorial geophysical components χ1 and χ2 at interannual time scales. The geophysical excitations were determined from different sources, including atmospheric, ocean models, Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow-On data, as well as from the Land Surface Discharge Model. The Multi Singular Spectrum Analysis method was applied to retain interannual variations in χ1 and χ2 components. None of the considered mass and motion terms studied for the different atmospheric and ocean models were found to have a negligible effect on interannual PM. These variables, derived from different Atmospheric Angular Momentum (AAM) and Oceanic Angular Momentum (OAM) models, differ from each other. Adding hydrologic considerations to the coupling of AAM and OAM excitations was found to provide benefits for achieving more consistent interannual geodetic budgets, but none of the AOH combinations fully explained the total observed PM excitations.
From 1/4° to 1/8°: Influence of Spatial Resolution on Eddy Detection Using Altimeter Data
Authors: Wang Yinuo , Chen Xiaoyan , Han Guiyan , Jin Pingping , Yang Jie
Published: December 2021

A substantial portion of ocean eddies, especially small ones, may be missed due to insufficient spatial or temporal sampling by satellite altimetry. In order to illustrate the influence of spatial resolution on eddy detection, this study provides a comparison of eddy identification, tracking, and analysis between two sets of merged altimeter data with spatial resolutions of 1/4° and 1/8°. One main study area (the Mediterranean Sea), and three confirmatory areas (the South-China Sea, the North-West Pacific, and the South-East Pacific) are chosen. The results show that the number and density of eddies captured by the 1/8° data are about twice as much as those captured by the 1/4° data, while the ratios of corresponding eddy parameters, i.e., radius, amplitude, (eddy kinetic energy (EKE)) are about 0.6–0.8 (1.3) for the two datasets (1/8° ÷ 1/4°). Long-term eddy tracking (1993–2018) is conducted in the Mediterranean Sea, indicating that the improvement in spatial resolution will increase the observed values of both the lifetime and the propagation distance of robust eddies. The number of eddies identified using the 1/4° data only accounts for ~30% to 60% of those identified using the 1/8° data. However, for eddies that can be detected using the two datasets, ~5% to 10% present errors (i.e., confusion). In comparison between the four regions, we find that for the enclosed seas with complex conditions, the increase in spatial resolution may lead to more significant improvements in the efficiency and accuracy of eddy detection.
Mapping Aquaculture Ponds for the Coastal Zone of Asia with Sentinel-1 and Sentinel-2 Time Series
Authors: Ottinger Marco , Bachofer Felix , Huth Juliane , Kuenzer Claudia
Published: December 2021

Asia dominates the world’s aquaculture sector, generating almost 90 percent of its total annual global production. Fish, shrimp, and mollusks are mainly farmed in land-based pond aquaculture systems and serve as a primary protein source for millions of people. The total production and area occupied for pond aquaculture has expanded rapidly in coastal regions in Asia since the early 1990s. The growth of aquaculture was mainly boosted by an increasing demand for fish and seafood from a growing world population. The aquaculture sector generates income and employment, contributes to food security, and has become a billion-dollar industry with high socio-economic value, but has also led to severe environmental degradation. In this regard, geospatial information on aquaculture can support the management of this growing food sector for the sustainable development of coastal ecosystems, resources, and human health. With free and open access to the rapidly growing volume of data from the Copernicus Sentinel missions as well as machine learning algorithms and cloud computing services, we extracted coastal aquaculture at a continental scale. We present a multi-sensor approach that utilizes Earth observation time series data for the mapping of pond aquaculture within the entire Asian coastal zone, defined as the onshore area up to 200 km from the coastline. In this research, we developed an object-based framework to detect and extract aquaculture at a single-pond level based on temporal features derived from high-spatial-resolution SAR and optical satellite data acquired from the Sentinel-1 and Sentinel-2 satellites. In a second step, we performed spatial and statistical data analyses of the Earth-observation-derived aquaculture dataset to investigate spatial distribution and identify production hotspots at various administrative units at regional, national, and sub-national scale.
A Novel Weighted Amplitude Modulation (WAM) System for Ambiguity Suppression of Spaceborne Hybrid Quad-Pol SAR
Authors: Zhang Yanyan , Chang Sheng , Wang Robert , Li Peng , Zhang Yongwei , Deng Yunkai
Published: December 2021

Quadrature-polarimetric synthetic aperture radar (quad-pol SAR) has extensive applications, including climate zones classification, extraction of surface roughness, soil moisture mapping, moving target indication, and rice mapping. Hybrid quad-pol SAR ameliorates the range ambiguity performance of conventional quad-pol SAR. However, the azimuth ambiguity of its cross-polarized (cross-pol) echo signals is serious, limiting the swath width of SAR. Therefore, this paper proposes a spaceborne weighted amplitude modulation (WAM) full-polarimetric (full-pol) SAR system, and it can suppress the azimuth ambiguity of hybrid quad-pol SAR. The performance boost of the azimuth ambiguity by the two imaging modes of the proposed SAR system is detailed and evaluated with the L-band system parameters. Moreover, the chirp scaling algorithm (CSA) is adopted to execute scene simulations for the two imaging modes. The results indicate that the proposed SAR system can effectively suppress the azimuth ambiguity of hybrid quad-pol SAR and verify the theoretical analysis.
Hyperspectral Remote Sensing Detection of Marine Oil Spills Using an Adaptive Long-Term Moment Estimation Optimizer
Authors: Jiang Zongchen , Zhang Jie , Ma Yi , Mao Xingpeng
Published: December 2021

Marine oil spills can damage marine ecosystems, economic development, and human health. It is important to accurately identify the type of oil spills and detect the thickness of oil films on the sea surface to obtain the amount of oil spill for on-site emergency responses and scientific decision-making. Optical remote sensing is an important method for marine oil-spill detection and identification. In this study, hyperspectral images of five types of oil spills were obtained using unmanned aerial vehicles (UAV). To address the poor spectral separability between different types of light oils and weak spectral differences in heavy oils with different thicknesses, we propose the adaptive long-term moment estimation (ALTME) optimizer, which cumulatively learns the spectral characteristics and then builds a marine oil-spill detection model based on a one-dimensional convolutional neural network. The results of the detection experiment show that the ALTME optimizer can store in memory multiple batches of long-term oil-spill spectral information, accurately identify the type of oil spills, and detect different thicknesses of oil films. The overall detection accuracy is larger than 98.09%, and the Kappa coefficient is larger than 0.970. The F1-score for the recognition of light-oil types is larger than 0.971, and the F1-score for detecting films of heavy oils with different film thicknesses is larger than 0.980. The proposed optimizer also performs well on a public hyperspectral dataset. We further carried out a feasibility study on oil-spill detection using UAV thermal infrared remote sensing technology, and the results show its potential for oil-spill detection in strong sunlight.
Analysis of Near-Surface Temperature Lapse Rates in Mountain Ecosystems of Northern Mexico Using Landsat-8 Satellite Images and ECOSTRESS
Authors: Rosas-Chavoya Marcela , López-Serrano Pablito Marcelo , Hernández-Díaz José Ciro , Wehenkel Christian , Vega-Nieva Daniel José
Published: December 2021

Mountain ecosystems provide environmental goods, which can be threatened by climate change. Near-Surface Temperature Lapse Rate (NSTLR) is an essential factor used for thermal and hydrological analysis in mountain ecosystems. The aims of the present study were to estimate NSTLR and to identify its relationship with aspect, Local solar zenith angle (LSZA) and Evaporative Stress Index (ESI) for two seasons of the year in a mountain ecosystem at the North of Mexico. Normalized Land Surface Temperature (NLST) was estimated using environmental and topographical variables. LSZA was calculated from slope to consider the effect of solar position. NSTLR was estimated through simple linear models. Observed NSTLR was 9.4 °C km−1 for the winter and 14.3 °C km−1 for the summer. Our results showed variation in NSTLR by season. In addition, aspect, LSZA and ESI also influenced NSTLR regulation. In addition, Northwest and West aspects exhibited the highest NSTLR. LSZA angles closest to 90° were related with a decrease in NSTLR for both seasons. Finally, ESI values associated with less evaporative stress were related to lower NSTLR. These results suggest potential of Landsat-8 LST and ECOSTRESS ESI to capture interactions of temperature, topography, and water stress in complex ecosystems.
An ICT Prototyping Framework for the “Port of the Future”
Authors: Barasti Davide , Troscia Martina , Lattuca Domenico , Tardo Alexandr , Barsanti Igor , Pagano Paolo
Published: December 2021

Seaports are genuine, intermodal hubs connecting seaways to inland transport links, such as roads and railways. Seaports are located at the focal point of institutional, industrial, and control activities in a jungle of interconnected information systems. System integration is setting considerable challenges when a group of independent providers are asked to implement complementary software functionalities. For this reason, seaports are the ideal playground where software is highly composite and tailored to a large variety of final users (from the so-called port communities). Although the target would be that of shaping the Port Authorities to be providers of (digital) innovation services, the state-of-the-art is still that of considering them as final users, or proxies of them. For this reason, we show how a canonical cloud, virtualizing a distributed architecture, can be structured to host different, possibly overlapped, tenants, slicing the information system at the infrastructure, platform, and software layers. Resources at the infrastructure and platform layers are shared so that a variety of independent applications can make use of the local calculus and access the data stored in a Data Lake. Such a cloud is adopted by the Port of Livorno as a rapid prototyping framework for the development and deployment of ICT innovation services. In order to demonstrate the versatility of this framework, three case studies relating to as many prototype ICT services (Navigation Safety, e-Freight, and Logistics) released within three industrial tenants are here presented and discussed.
Bionic for Training: Smart Framework Design for Multisensor Mechatronic Platform Validation
Authors: Foresti Ruben , Statello Rosario , Delmonte Nicola , Lo Muzio Francesco Paolo , Rozzi Giacomo , Miragoli Michele , Sarli Leopoldo , Ferrari Gianluigi , Macaluso Claudio , Maggio Marcello Giuseppe , Pisani Francesco , Costantino Cosimo
Published: December 2021

Home monitoring supports the continuous improvement of the therapy by sharing data with healthcare professionals. It is required when life-threatening events can still occur after hospital discharge such as neonatal apnea. However, multiple sources of external noise could affect data quality and/or increase the misdetection rate. In this study, we developed a mechatronic platform for sensor characterizations and a framework to manage data in the context of neonatal apnea. The platform can simulate the movement of the abdomen in different plausible newborn positions by merging data acquired simultaneously from three-axis accelerometers and infrared sensors. We simulated nine apnea conditions combining three different linear displacements and body postures in the presence of self-generated external noise, showing how it is possible to reduce errors near to zero in phenomena detection. Finally, the development of a smart 8Ws-based software and a customizable mobile application were proposed to facilitate data management and interpretation, classifying the alerts to guarantee the correct information sharing without specialized skills.
Two-Stage Segmentation Framework Based on Distance Transformation
Authors: Huang Xiaoyang , Lin Zhi , Jiao Yudi , Chan Moon-Tong , Huang Shaohui , Wang Liansheng
Published: December 2021

With the rise of deep learning, using deep learning to segment lesions and assist in diagnosis has become an effective means to promote clinical medical analysis. However, the partial volume effect of organ tissues leads to unclear and blurred edges of ROI in medical images, making it challenging to achieve high-accuracy segmentation of lesions or organs. In this paper, we assume that the distance map obtained by performing distance transformation on the ROI edge can be used as a weight map to make the network pay more attention to the learning of the ROI edge region. To this end, we design a novel framework to flexibly embed the distance map into the two-stage network to improve left atrium MRI segmentation performance. Furthermore, a series of distance map generation methods are proposed and studied to reasonably explore how to express the weight of assisting network learning. We conduct thorough experiments to verify the effectiveness of the proposed segmentation framework, and experimental results demonstrate that our hypothesis is feasible.
Advances in Optical Based Turbidity Sensing Using LED Photometry (PEDD)
Authors: Fay Cormac D. , Nattestad Andrew
Published: December 2021

Turbidity is one of the primary metrics to determine water quality in terms of health and environmental concerns, however analysis typically takes place in centralized facilities, with samples periodically collected and transported there. Large scale autonomous deployments (WSNs) are impeded by both initial and per measurement costs. In this study we employ a Paired Emitter-Detector Diode (PEDD) technique to quantitatively measure turbidity using analytical grade calibration standards. Our PEDD approach compares favorably against more conventional photodiode-LED arrangements in terms of spectral sensitivity, cost, power use, sensitivity, limit of detection, and physical arrangement as per the ISO 7027 turbidity sensing standard. The findings show that the PEDD technique was superior in all aforementioned aspects. It is therefore more ideal for low-cost, low-power, IoT deployed sensors. The significance of these findings can lead to environmental deployments that greatly lower the device and per-measurement costs.
How Trend of Increasing Data Volume Affects the Energy Efficiency of 5G Networks
Authors: Lorincz Josip , Klarin Zvonimir
Published: December 2021

As the rapid growth of mobile users and Internet-of-Everything devices will continue in the upcoming decade, more and more network capacity will be needed to accommodate such a constant increase in data volumes (DVs). To satisfy such a vast DV increase, the implementation of the fifth-generation (5G) and future sixth-generation (6G) mobile networks will be based on heterogeneous networks (HetNets) composed of macro base stations (BSs) dedicated to ensuring basic signal coverage and capacity, and small BSs dedicated to satisfying capacity for increased DVs at locations of traffic hotspots. An approach that can accommodate constantly increasing DVs is based on adding additional capacity in the network through the deployment of new BSs as DV increases. Such an approach represents an implementation challenge to mobile network operators (MNOs), which is reflected in the increased power consumption of the radio access part of the mobile network and degradation of network energy efficiency (EE). In this study, the impact of the expected increase of DVs through the 2020s on the EE of the 5G radio access network (RAN) was analyzed by using standardized data and coverage EE metrics. An analysis was performed for five different macro and small 5G BS implementation and operation scenarios and for rural, urban, dense-urban and indoor-hotspot device density classes (areas). The results of analyses reveal a strong influence of increasing DV trends on standardized data and coverage EE metrics of 5G HetNets. For every device density class characterized with increased DVs, we here elaborate on the process of achieving the best and worse combination of data and coverage EE metrics for each of the analyzed 5G BSs deployment and operation approaches. This elaboration is further extended on the analyses of the impact of 5G RAN instant power consumption and 5G RAN yearly energy consumption on values of standardized EE metrics. The presented analyses can serve as a reference in the selection of the most appropriate 5G BS deployment and operation approach, which will simultaneously ensure the transfer of permanently increasing DVs in a specific device density class and the highest possible levels of data and coverage EE metrics.
Data-Driven and Model-Driven Joint Detection Algorithm for Faster-Than-Nyquist Signaling in Multipath Channels
Authors: Deng Xiuqi , Bian Xin , Li Mingqi
Published: December 2021

In recent years, Faster-than-Nyquist (FTN) transmission has been regarded as one of the key technologies for future 6G due to its advantages in high spectrum efficiency. However, as a price to improve the spectrum efficiency, the FTN system introduces inter-symbol interference (ISI) at the transmitting end, whicheads to a serious deterioration in the performance of traditional receiving algorithms under high compression rates and harsh channel environments. The data-driven detection algorithm has performance advantages for the detection of high compression rate FTN signaling, but the current related work is mainly focused on the application in the Additive White Gaussian Noise (AWGN) channel. In this article, for FTN signaling in multipath channels, a data and model-driven joint detection algorithm, i.e., DMD-JD algorithm is proposed. This algorithm first uses the traditional MMSE or ZFinear equalizer to complete the channel equalization, and then processes the serious ISI introduced by FTN through the deepearning network based on CNN or LSTM, thereby effectively avoiding the problem of insufficient generalization of the deepearning algorithm in different channel scenarios. The simulation results show that in multipath channels, the performance of the proposed DMD-JD algorithm is better than that of purely model-based or data-driven algorithms; in addition, the deepearning network trained based on a single channel model can be well adapted to FTN signal detection under other channel models, thereby improving the engineering practicability of the FTN signal detection algorithm based on deepearning.
Flow Sensing-Based Congestion Detection for D2D Streaming on a 5G gNB
Authors: Lee Chongdeuk
Published: December 2021

To provide high-quality streaming services in device-to-device (D2D) communications, performance parameters such as encoding rate, decoding rate, and flow rate should be detected and monitored. The proposed algorithm provides a method to detect time streaming for traffic flows in D2D communications, and a sequence to detect rate imbalance. This paper proposes a new FS-CDA (flow sensing-based congestion detecting algorithm) to prevent high congestion rates and assist an optimized D2D streaming service in 5G-based wireless mobile networks. The proposed algorithm detects and controls flow imbalance for streaming segments during D2D communications, and it includes operations such as transmission rate monitoring, rate adjustment functions, and underflow and overflow sensing for these operations. The paper aims to effectively control traffic flow rates caused by adjacent channel bandwidth, high bit rate error, and heterogeneous radio interference, and to enhance the performance of D2D streaming services by performing such operations. The proposed algorithm for D2D streaming services is measured by deriving the individual weight of certain versions of a streaming flow. Based on the given operations, the simulation results indicated that the proposed algorithm has better performance with respect to average congestion control ratio, PSNR, and average throughput than other methods.
Reliability and Repeatability of ACL Quick Check®: A Methodology for on Field Lower Limb Joint Kinematics and Kinetics Assessment in Sport Applications
Authors: Guiotto Annamaria , Ciniglio Alfredo , Spolaor Fabiola , Pavan Davide , Cibin Federica , Scaldaferro Alex , Sawacha Zimi
Published: December 2021

Anterior cruciate ligament (ACL) lesion represents one of the most dramatic sport injuries. Even though clinical screenings aiming at identifying subjects at risk of injuries are gaining popularity, the use of sophisticated equipment still represents a barrier towards their widespread use. This study aimed to test both reliability and repeatability of a new methodology to assess lower limb joints kinematics and kinetics directly on field with the aid of video cameras and plantar pressure insoles. Ten athletes and one case study (post ACL surgery) were assessed in a gait laboratory, while performing double leg squats, through the simultaneous acquisition of stereophotogrammetry, force plates, commercial video cameras and plantar pressure insoles. Different sources of errors were investigated and both reliability and repeatability analysis performed. Minimum and maximum RMSE values of 0.74% (right knee joint center trajectory) and 64.51%, respectively (ankle dorsi-plantarflexion moment), were detected. Excellent to good correlation was found for the majority of the measures, even though very poor and inverse between-trials correlation was found on a restricted number of trials especially for the ankle dorsi-plantarflexion moment. These findings could be used in combination with already available screening tools in order to provide more repeatable results.
Mesoporous Silica Nanoparticles in Chemical Detection: From Small Species to Large Bio-Molecules
Authors: Parra Margarita , Gil Salvador , Gaviña Pablo , Costero Ana M.
Published: December 2021

A recompilation of applications of mesoporous silica nanoparticles in sensing from the last five years is presented. Its high potential, especially as hybrid materials combined with organic or bio-molecules, is shown. Adding to the multiplying effect of loading high amounts of the transducer into the pores, the selectivity attained by the interaction of the analyte with the layer decorating the material is described. Examples of the different methodologies are presented.
False Ceiling Deterioration Detection and Mapping Using a Deep Learning Framework and the Teleoperated Reconfigurable ‘Falcon’ Robot
Authors: Semwal Archana , Mohan Rajesh Elara , Melvin Lee Ming Jun , Palanisamy Povendhan , Baskar Chanthini , Yi Lim , Pookkuttath Sathian , Ramalingam Balakrishnan
Published: December 2021

Periodic inspection of false ceilings is mandatory to ensure building and human safety. Generally, false ceiling inspection includes identifying structural defects, degradation in Heating, Ventilation, and Air Conditioning (HVAC) systems, electrical wire damage, and pest infestation. Human-assisted false ceiling inspection is a laborious and risky task. This work presents a false ceiling deterioration detection and mapping framework using a deep-neural-network-based object detection algorithm and the teleoperated ‘Falcon’ robot. The object detection algorithm was trained with our custom false ceiling deterioration image dataset composed of four classes: structural defects (spalling, cracks, pitted surfaces, and water damage), degradation in HVAC systems (corrosion, molding, and pipe damage), electrical damage (frayed wires), and infestation (termites and rodents). The efficiency of the trained CNN algorithm and deterioration mapping was evaluated through various experiments and real-time field trials. The experimental results indicate that the deterioration detection and mapping results were accurate in a real false-ceiling environment and achieved an 89.53% detection accuracy.
Laser-Induced Graphene Electrodes Modified with a Molecularly Imprinted Polymer for Detection of Tetracycline in Milk and Meat
Authors: Abera Biresaw D. , Ortiz-Gómez Inmaculada , Shkodra Bajramshahe , J. Romero Francisco , Cantarella Giuseppe , Petti Luisa , Salinas-Castillo Alfonso , Lugli Paolo , Rivadeneyra Almudena
Published: December 2021

Tetracycline (TC) is a widely known antibiotic used worldwide to treat animals. Its residues in animal-origin foods cause adverse health effects to consumers. Low-cost and real-time measuring systems of TC in food samples are, therefore, extremely needed. In this work, a three-electrode sensitive and label-free sensor was developed to detect TC residues from milk and meat extract samples, using CO2 laser-induced graphene (LIG) electrodes modified with gold nanoparticles (AuNPs) and a molecularly imprinted polymer (MIP) used as a synthetic biorecognition element. LIG was patterned on a polyimide (PI) substrate, reaching a minimum sheet resistance (Rsh) of 17.27 ± 1.04 Ω/sq. The o-phenylenediamine (oPD) monomer and TC template were electropolymerized on the surface of the LIG working electrode to form the MIP. Surface morphology and electrochemical techniques were used to characterize the formation of LIG and to confirm each modification step. The sensitivity of the sensor was evaluated by differential pulse voltammetry (DPV), leading to a limit of detection (LOD) of 0.32 nM, 0.85 nM, and 0.80 nM in buffer, milk, and meat extract samples, respectively, with a working range of 5 nM to 500 nM and a linear response range between 10 nM to 300 nM. The sensor showed good LOD (0.32 nM), reproducibility, and stability, and it can be used as an alternative system to detect TC from animal-origin food products.
Power Allocation and Energy Cooperation for UAV-Enabled MmWave Networks: A Multi-Agent Deep Reinforcement Learning Approach
Authors: Domingo Mari Carmen
Published: December 2021

Unmanned Aerial Vehicle (UAV)-assisted cellular networks over the millimeter-wave (mmWave) frequency band can meet the requirements of a high data rate and flexible coverage in next-generation communication networks. However, higher propagation loss and the use of a large number of antennas in mmWave networks give rise to high energy consumption and UAVs are constrained by their low-capacity onboard battery. Energy harvesting (EH) is a viable solution to reduce the energy cost of UAV-enabled mmWave networks. However, the random nature of renewable energy makes it challenging to maintain robust connectivity in UAV-assisted terrestrial cellular networks. Energy cooperation allows UAVs to send their excessive energy to other UAVs with reduced energy. In this paper, we propose a power allocation algorithm based on energy harvesting and energy cooperation to maximize the throughput of a UAV-assisted mmWave cellular network. Since there is channel-state uncertainty and the amount of harvested energy can be treated as a stochastic process, we propose an optimal multi-agent deep reinforcement learning algorithm (DRL) named Multi-Agent Deep Deterministic Policy Gradient (MADDPG) to solve the renewable energy resource allocation problem for throughput maximization. The simulation results show that the proposed algorithm outperforms the Random Power (RP), Maximal Power (MP) and value-based Deep Q-Learning (DQL) algorithms in terms of network throughput.
Practical Experiences of a Smart Livestock Location Monitoring System Leveraging GNSS, LoRaWAN and Cloud Services
Authors: Ojo Mike O. , Viola Irene , Baratta Mario , Giordano Stefano
Published: December 2021

Livestock farming is, in most cases in Europe, unsupervised, thus making it difficult to ensure adequate control of the position of the animals for the improvement of animal welfare. In addition, the geographical areas involved in livestock grazing usually have difficult access with harsh orography and lack of communications infrastructure, thus the need to provide a low-power livestock localization and monitoring system is of paramount importance, which is crucial not for a sustainable agriculture, but also for the protection of native breeds and meats thanks to their controlled supervision. In this context, this work presents an Internet of things (IoT)-based system integrating low-power wide area (LPWA) technology, cloud, and virtualization services to provide real-time livestock location monitoring. Taking into account the constraints coming from the environment in terms of energy supply and network connectivity, our proposed system is based on a wearable device equipped with inertial sensors, Global Positioning System (GPS) receiver, and LoRaWAN transceiver, which can provide a satisfactory compromise between performance, cost, and energy consumption. At first, this article provides the state-of-the-art localization techniques and technologies applied to smart livestock. Then, we proceed to provide the hardware and firmware co-design to achieve very low energy consumption, thus providing a significant positive impact to the battery life. The proposed platform has been evaluated in a pilot test in the northern part of Italy, evaluating different configurations in terms of sampling period, experimental duration, and number of devices. The results are analyzed and discussed for packet delivery ratio, energy consumption, localization accuracy, battery discharge measurement, and delay.
Modeling and Calibration for Dithering of MDRLG and Time-Delay of Accelerometer in SINS
Authors: Xing Jinlong , Yang Gongliu , Cai Tijing
Published: December 2021

At present, the design and manufacturing technology of mechanically dithered ring laser gyroscope (MDRLG) have matured, the strapdown inertial navigation systems (SINS) with MDRLG have been widely used in military and business scope. When the MDRLG is working, high-frequency dithering is introduced, which will cause the size effect error of the accelerometer. The accelerometer signal has a time delay relative to the system, which will cause the accelerometer time delay error. In this article, in order to solve the above-mentioned problem: (1) we model the size effect error of the mechanically dithering of the MDRLG and perform an error analysis for the size effect error of the mechanically dithering of the MDRLG; (2) we model the time delay error of accelerometer and perform an error analysis for the time delay error of accelerometer; (3) we derive a continuous linear 43-D SINS error model considering the above-mentioned two error parameters and expand the temperature coefficients of accelerometers, inner lever arm error, outer lever arm error parameters to achieve high-precision calibration of SINS. We use the piecewise linear constant system (PWCS) method during the calibration process to prove that all calibration parameters are observable. Finally, the SINS with MDRLG is used in laboratory conditions to test the validity of the calibration method.
The Influence of Cognitive Styles as Promoters of Entrepreneurial Orientation and Intrapreneurship as Drivers of Innovation: The Case of Pharmacy Professionals in Portugal
Authors: Rebelo Sílvia , Marques Carla Susana , Santos Gina
Published: December 2021

Innovation in the community pharmacy field has extreme importance in building customer loyalty and competitiveness and, during the COVID-19 pandemic, its value was even more noted. Thus, in this study, we aimed to assess the influence of cognitive styles (rational and intuitive) on individual entrepreneurial orientation and intrapreneurship and how they impact innovation. A questionnaire was applied to 209 community pharmacy professionals in Portugal during the COVID-19 pandemic, and PLS-SEM was used to statistically analyze the data obtained. For the results, we perceived those cognitive styles’ (rational and intuitive) impact on individual entrepreneurial orientation and partially on intrapreneurship, and this innovation is explained by individual entrepreneurial orientation and intrapreneurship. For the theoretical implications, we have contributed to the advancement of knowledge by establishing and understanding the relationship between the different dimensions suggested and, at the practical level for management, we have perceived where to act at the individual level, to improve innovation and provide suggestions in the directions suggested here. This study is original and innovative because there are no general studies in the literature that have related all the dimensions addressed here, and there is little current research in the community pharmacy field.