bluuebunny/crossref_metadata_2025 huggingface dataset:
A Study on the Mechanical Properties of an Automobile Part Additively Printed through Periodic Layer Rotation Strategies
Authors: Yang Min-Seok , Kang Ji-Heon , Kim Ji-Wook , Kim Kun-Woo , Kim Da-Hye , Sung Ji-Hyun , Ko Dae-Cheol , Lee Jae-Wook
Published: December 2021

In metal product manufacturing, additive manufacturing (AM) is a method that has the advantage of fabricating complex shapes and customized production, unlike existing machining methods. However, owing to the characteristics of the AM process, anisotropy of macrostructure occurs because of various causes such as the scan direction, melting, fusion, and cooling of the powdered material. The macrostructure anisotropy is realized from the scan direction, and when a single layer is stacked in one direction, it is expressed as orthogonal anisotropy. Here, the classical lamination theory is applied to simply calculate the individual orthotropic layers by superimposing them. Through this, the authors analyzed whether the mechanical properties of the product are isotropically expressed with a periodic layer rotation strategy. To determine if the mechanical properties can be reasonably considered to be isotropic, a shock absorber mount for a vehicle was manufactured by AM. The tensile and vibration test performed on the product was compared with the finite element analysis and experimental results. As a result of the comparison, it was confirmed that the macroscopically of the product was considered isotropic as the load-displacement diagram and the fracture location coincided, as well as the natural frequency and mode shape.
Development of Growth Media from Agricultural By-Products for Cultivation of PUFA-Producing Sicyoidochytrium minutum
Authors: Eiríksdóttir Heiðrún , Stefánsson Magnús Örn , Einarsson Hjörleifur
Published: December 2021

The demand for novel sources of marine oils, which contain polyunsaturated fatty acids (PUFAs), has increased due to the realization of the importance of PUFAs, e.g., docosahexaenoic acid (DHA), in the human diet. However, the natural supply is limited. By-product peptones (BYPP) intended as a growth medium for the PUFA-producing strain Sicyoidochytrium minutum of family Thraustochytriaceae were produced after several experiments on the pancreatic digestion of bovine lungs and spleens. S. minutum was able to grow in a medium containing BYPP made from the pancreatic digestion of lung and spleen with glycerol, resulting in 1.14 ± 0.03 g cell dry weight (CDW)/L and 1.44 ± 0.24 g CDW/L, respectively, after 5 days of incubation at 25 °C, compared to 1.92 ± 0.25 g CDW/L in Basal Medium (BM) containing tryptone, peptone, and glycerol. The lipid content, obtained after growth in lung BYPP media with glycerol as a carbon source, was significantly higher (28.17% ± 1.33 of dry weight) than in the control basal medium (BM) (21.72% ± 2.45); however, DHA as a percentage of total fatty acids was lower in BYPP than in the control BM (25.24% ± 1.56 and 33.02% ± 2.37, respectively). It is concluded that low-value by-products from abattoirs can be used as ingredients for the cultivation of oligogenic Thraustochytriaceae.
Pharmacokinetics and Metabolism Study of Deep-Sea-Derived Butyrolactone I in Rats by UHPLC–MS/MS and UHPLC–Q-TOF-MS
Authors: Wu Liang , Xie Chun-Lan , Yang Xian-Wen , Chen Gang
Published: December 2021

Butyrolactone I (BTL-I) is a butanolide isolated from the deep-sea-derived fungus, Aspergillus sp. It provides a potential new target for the prevention and treatment of food allergies. This study aimed to investigate the metabolic and pharmacokinetic profile of BTL-I in rats. The metabolic profiles were obtained by UHPLC–Q-TOF-MS. As a result, eleven metabolites were structurally identified, and the proposed metabolic pathways of BTL-I were characterized. The main metabolites were the oxidative and glucuronidative metabolites. In addition, a sensitive UHPLC–MS/MS method was established for the quantitation of BTL-I in rat plasma (LOQ = 2 ng/mL). The method was fully validated and successfully applied to the pharmacokinetic study of BTL-I in rats after oral administration or intravenous administration. The oral bioavailability was calculated as 6.29%, and the maximum plasma concentrations were 9.85 ± 1.54 ng/mL and 17.97 ± 1.36 ng/mL for intravenous and intragastric dosing groups, respectively.
NMR-Based Configurational Assignments of Natural Products: Gibbs Sampling and Bayesian Inference Using Floating Chirality Distance Geometry Calculations
Authors: Immel Stefan , Köck Matthias , Reggelin Michael
Published: December 2021

Floating chirality restrained distance geometry (fc-rDG) calculations are used to directly evolve structures from NMR data such as NOE-derived intramolecular distances or anisotropic residual dipolar couplings (RDCs). In contrast to evaluating pre-calculated structures against NMR restraints, multiple configurations (diastereomers) and conformations are generated automatically within the experimental limits. In this report, we show that the “unphysical” rDG pseudo energies defined from NMR violations bear statistical significance, which allows assigning probabilities to configurational assignments made that are fully compatible with the method of Bayesian inference. These “diastereomeric differentiabilities” then even become almost independent of the actual values of the force constants used to model the restraints originating from NOE or RDC data.
Heavy Metals in Sapropel of Lakes in Suburban Territories of Vilnius (Lithuania): Reflections of Paleoenvironmental Conditions and Anthropogenic Influence
Authors: Ignatavičius Gytautas , Satkūnas Jonas , Grigienė Alma , Nedveckytė Irena , Hassan Howlader Rahidul , Valskys Vaidotas
Published: December 2021

Geochemical and lithological parameters of sapropel in lakes, combined with pollen data and radiocarbon 14C dating, contain a wide spectrum of environmental information. This includes records of fluctuations of water level and changes of conditions of sedimentation, accumulation of organic matter and chemical elements due to climate change, human impacts and other environmental changes. Rising concentrations of hazardous substances in the natural sediments are likely to be a high risk to the natural environment. At the same time, they can greatly reduce opportunities for environmental engineering of lakes. Four lakes with different trophic states and anthropogenic pressures were chosen for this study in Lithuania. Higher concentrations of elements like Cr, Cu and Zn were not only detected in the top most layers of sapropel but also in deeper layers and are attributed to lithogenic association of trace elements in such deep layers. Concentrations of Pb were detected only in upper layers of sapropel which indicates the impact of anthropogenic activity. The main source of heavy metals was multidimensional anthropogenic pollution leading to a biogenic–anthropogenic association of elements. Sapropel with low concentrations of heavy metals exhibits a different inter-association matrix because most of the elements tend to form lithogenic–clastogenic associations.
Exercise Performance Upregulatory Effect of R-α-Lipoic Acid with γ-Cyclodextrin
Authors: Hashimoto Yuki , Yoshizawa Katsuhiko , Kaido Yuka , Takenouchi Akiko , Terao Keiji , Yasui Hiroyuki , Yoshikawa Yutaka
Published: December 2021

α-Lipoic acid (ALA) is a vitamin-like substance that is an indispensable supporting factor for a large number of enzymes. Due to its optical activity, ALA has optical isomers RALA and SALA. The major role of RALA is in energy metabolism. However, RALA cannot be used as a pharmaceutical or nutraceutical because it is sensitive to heat and acid conditions. Previous studies have shown that RALA complexed with γ-cyclodextrin (CD) has a higher antioxidant capacity than that of free RALA. The antioxidant enzyme system protects against intense exercise-induced oxidative damage and is related to the physical status of athletes. The aim of this study was to examine the effect of CD/RALA complex supplementation on antioxidant activity and performance during high-intensity exercise. Twenty-four male C3H/HeSlc mice were divided into four groups (n = 6): swimming+distilled water administration (C), swimming+CD/RALA supplementation (CD/RALA), swimming+RALA suplementation (RALA), and swimming+CD supplementation (CD). Blood ammonia elevation due to exercise stress was repressed by CD/RALA supplementation. The oxidative stress in the kidney increased after exercise and was reduced by CD/RALA supplementation. Our findings suggest that CD/RALA supplementation may be useful for improving the exercise performance in athletes.
The Role of Diet Quality in Mediating the Association between Ultra-Processed Food Intake, Obesity and Health-Related Outcomes: A Review of Prospective Cohort Studies
Authors: Dicken Samuel J. , Batterham Rachel L.
Published: December 2021

Prospective cohort studies show that higher intakes of ultra-processed food (UPF) increase the risk of obesity and obesity-related outcomes, including cardiovascular disease, cancer and type 2 diabetes. Whether ultra-processing itself is detrimental, or whether UPFs just have a lower nutritional quality, is debated. Higher UPF intakes are inversely associated with fruit, vegetables, legumes and seafood consumption. Therefore, the association between UPFs and poor health could simply be from excess nutrient intake or from a less healthful dietary pattern. If so, adjustment for dietary quality or pattern should explain or greatly reduce the size of the significant associations between UPFs and health-related outcomes. Here, we provide an overview of the literature and by using a novel approach, review the relative impact of adjusting for diet quality/patterns on the reported associations between UPF intake and health-related outcomes in prospective cohort studies. We find that the majority of the associations between UPFs, obesity and health-related outcomes remain significant and unchanged in magnitude after adjustment for diet quality or pattern. Our findings suggest that the adverse consequences of UPFs are independent of dietary quality or pattern, questioning the utility of reformulation to mitigate against the obesity pandemic and wider negative health outcomes of UPFs.
Nutrient Intake and Status in Adults Consuming Plant-Based Diets Compared to Meat-Eaters: A Systematic Review
Authors: Neufingerl Nicole , Eilander Ans
Published: December 2021

Health authorities increasingly recommend a more plant-based diet, rich in fruits, vegetables, pulses, whole grains and nuts, low in red meat and moderate in dairy, eggs, poultry and fish which will be beneficial for both health and the environment. A systematic review of observational and intervention studies published between 2000 and January 2020 was conducted to assess nutrient intake and status in adult populations consuming plant-based diets (mainly vegetarian and vegan) with that of meat-eaters. Mean intake of nutrients were calculated and benchmarked to dietary reference values. For micronutrient status, mean concentrations of biomarkers were calculated and compared across diet groups. A total of 141 studies were included, mostly from Europe, South/East Asia, and North America. Protein intake was lower in people following plant-based diets compared to meat-eaters, but well within recommended intake levels. While fiber, polyunsaturated fatty acids (PUFA), folate, vitamin C, E and magnesium intake was higher, eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) intake was lower in vegetarians and vegans as compared to meat-eaters. Intake and status of vitamin B12, vitamin D, iron, zinc, iodine, calcium and bone turnover markers were generally lower in plant-based dietary patterns compared to meat-eaters. Vegans had the lowest vitamin B12, calcium and iodine intake, and also lower iodine status and lower bone mineral density. Meat-eaters were at risk of inadequate intakes of fiber, PUFA, α-linolenic acid (ALA), folate, vitamin D, E, calcium and magnesium. There were nutrient inadequacies across all dietary patterns, including vegan, vegetarian and meat-based diets. As plant-based diets are generally better for health and the environment, public health strategies should facilitate the transition to a balanced diet with more diverse nutrient-dense plant foods through consumer education, food fortification and possibly supplementation.
Structured Waters Mediate Small Molecule Binding to G-Quadruplex Nucleic Acids
Authors: Neidle Stephen
Published: December 2021

The role of G-quadruplexes in human cancers is increasingly well-defined. Accordingly, G-quadruplexes can be suitable drug targets and many small molecules have been identified to date as G-quadruplex binders, some using computer-based design methods and co-crystal structures. The role of bound water molecules in the crystal structures of G-quadruplex-small molecule complexes has been analyzed in this study, focusing on the water arrangements in several G-quadruplex ligand complexes. One is the complex between the tetrasubstituted naphthalene diimide compound MM41 and a human intramolecular telomeric DNA G-quadruplex, and the others are in substituted acridine bimolecular G-quadruplex complexes. Bridging water molecules form most of the hydrogen-bond contacts between ligands and DNA in the parallel G-quadruplex structures examined here. Clusters of structured water molecules play essential roles in mediating between ligand side chain groups/chromophore core and G-quadruplex. These clusters tend to be conserved between complex and native G-quadruplex structures, suggesting that they more generally serve as platforms for ligand binding, and should be taken into account in docking and in silico studies.
Nuclear Imaging in Infective Endocarditis
Authors: Mikail Nidaa , Hyafil Fabien
Published: December 2021

Infective endocarditis (IE) is a life-threatening disease with stable prevalence despite prophylactic, diagnostic, and therapeutic advances. In parallel to the growing number of cardiac devices implanted, the number of patients developing IE on prosthetic valves and cardiac implanted electronic device (CIED) is increasing at a rapid pace. The diagnosis of IE is particularly challenging, and currently relies on the Duke-Li modified classification, which include clinical, microbiological, and imaging criteria. While echocardiography remains the first line imaging technique, especially in native valve endocarditis, the incremental value of two nuclear imaging techniques, 18F-fluorodeoxyglucose positron emission tomography with computed tomography (18F-FDG-PET/CT) and white blood cells single photon emission tomography with computed tomography (WBC-SPECT), has emerged for the management of prosthetic valve and CIED IE. In this review, we will summarize the procedures for image acquisition, discuss the role of 18F-FDG-PET/CT and WBC-SPECT imaging in different clinical situations of IE, and review the respective diagnostic performance of these nuclear imaging techniques and their integration into the diagnostic algorithm for patients with a suspicion of IE.
Quantitative Analysis of the Phase Transition Mechanism Underpinning the Systemic Self-Assembly of a Mechanopharmaceutical Device
Authors: Dunne Steven , Willmer Andrew R. , Swanson Rosemary , Almeida Deepak , Ammerman Nicole C. , Stringer Kathleen A. , Capparelli Edmund V. , Rosania Gus R.
Published: December 2021

Clofazimine (CFZ) is a poorly soluble, weakly basic, small molecule antibiotic clinically used to treat leprosy and is now in clinical trials as a treatment for multidrug resistant tuberculosis and COVID-19. CFZ exhibits complex, context-dependent pharmacokinetics that are characterized by an increasing half-life in long term treatment regimens. The systemic pharmacokinetics of CFZ have been previously represented by a nonlinear, 2-compartment model incorporating an expanding volume of distribution. This expansion reflects the soluble-to-insoluble phase transition that the drug undergoes as it precipitates out and accumulates within macrophages disseminated throughout the organism. Using mice as a model organism, we studied the mechanistic underpinnings of this increasing half-life and how the systemic pharmacokinetics of CFZ are altered with continued dosing. To this end, M. tuberculosis infection status and multiple dosing schemes were studied alongside a parameter sensitivity analysis (PSA) to further understanding of systemic drug distribution. Parameter values governing the sigmoidal expansion function that captures the phase transition were methodically varied, and in turn, the systemic concentrations of the drug were calculated and compared to the experimentally measured concentrations of drug in serum and spleen. The resulting amounts of drug sequestered were dependent on the total mass of CFZ administered and the duration of drug loading. This phenomenon can be captured by altering three different parameters of an expansion function corresponding to key biological determinants responsible for the precipitation and the accumulation of the insoluble drug mass in macrophages. Through this analysis of the context dependent pharmacokinetics of CFZ, a predictive framework for projecting the systemic distribution and self-assembly of precipitated drug complexes as intracellular mechanopharmaceutical devices of this and other drugs exhibiting similarly complex pharmacokinetics can be constructed.
Effects of Adipose-Derived Biogenic Nanoparticle-Associated microRNA-451a on Toll-like Receptor 4-Induced Cytokines
Authors: Wang Xinghua , Pham Anthony , Kang Lu , Walker Sierra A. , Davidovich Irina , Iannotta Dalila , TerKonda Sarvam P. , Shapiro Shane , Talmon Yeshayahu , Pham Si , Wolfram Joy
Published: December 2021

Extracellular vesicles (EVs) are cell-released nanoparticles that transfer biomolecular content between cells. Among EV-associated biomolecules, microRNAs (miRNAs/miRs) represent one of the most important modulators of signaling pathways in recipient cells. Previous studies have shown that EVs from adipose-derived mesenchymal stromal cells (MSCs) and adipose tissue modulate inflammatory pathways in macrophages. In this study, the effects of miRNAs that are abundant in adipose tissue EVs and other biogenic nanoparticles (BiNPs) were assessed in terms of altering Toll-like receptor 4 (TLR4)-induced cytokines. TLR-4 signaling in macrophages is often triggered by pathogen or damage-induced inflammation and is associated with several diseases. This study demonstrates that miR-451a, which is abundant in adipose tissue BiNPs, suppresses pro-inflammatory cytokines and increases anti-inflammatory cytokines associated with the TLR4 pathway. Therefore, miR-451a may be partially responsible for immunomodulatory effects of adipose tissue-derived BiNPs.
An Adaptive Biosystems Engineering Approach towards Modeling the Soluble-to-Insoluble Phase Transition of Clofazimine
Authors: Willmer Andrew R. , Dunne Steven , Swanson Rosemary , Almeida Deepak , Ammerman Nicole C. , Stringer Kathleen A. , Capparelli Edmund V. , Rosania Gus R.
Published: December 2021

Clofazimine (CFZ) is a weakly basic, small-molecule antibiotic used for the treatment of mycobacterial infections including leprosy and multidrug-resistant tuberculosis. Upon prolonged oral administration, CFZ precipitates and accumulates within macrophages throughout the host. To model the pharmacokinetics of CFZ, the volume of distribution (Vd) was considered as a varying parameter that increases with continuous drug loading. Fitting the time-dependent change in drug mass and concentration data obtained from CFZ-treated mice, we performed a quantitative analysis of the systemic disposition of the drug over a 20-week treatment period. The pharmacokinetics data were fitted using various classical compartmental models sampling serum and spleen concentration data into separate matrices. The models were constructed in NONMEM together with linear and nonlinear sigmoidal expansion functions to the spleen compartment to capture the phase transition in Vd. The different modeling approaches were compared by Akaike information criteria, observed and predicted concentration correlations, and graphically. Using the composite analysis of the modeling predictions, adaptive fractional CFZ sequestration, Vd and half-life were evaluated. When compared to standard compartmental models, an adaptive Vd model yielded a more accurate data fit of the drug concentrations in both the serum and spleen. Including a nonlinear sigmoidal equation into compartmental models captures the phase transition of drugs such as CFZ, greatly improving the prediction of population pharmacokinetics and yielding further insight into the mechanisms of drug disposition.
Two Novel Palbociclib-Resorcinol and Palbociclib-Orcinol Cocrystals with Enhanced Solubility and Dissolution Rate
Authors: Duan Chenxin , Liu Wenwen , Tao Yunwen , Liang Feifei , Chen Yanming , Xiao Xinyi , Zhang Guisen , Chen Yin , Hao Chao
Published: December 2021

Palbociclib (PAL) is an effective anti-breast cancer drug, but its use has been partly restricted due to poor bioavailability (resulting from extremely low water solubility) and serious adverse reactions. In this study, two cocrystals of PAL with resorcinol (RES) or orcinol (ORC) were prepared by evaporation crystallization to enhance their solubility. The cocrystals were characterized by single crystal X-ray diffraction, Hirshfeld surface analysis, powder X-ray diffraction, differential scanning calorimetry, thermogravimetric analysis, Fourier transform infrared and scanning electron microscopy. The intrinsic dissolution rates of the PAL cocrystals were determined in three different dissolution media (pH 1.0, pH 4.5 and pH 6.8), and both cocrystals showed improved dissolution rates at pH 1.0 and pH 6.8 in comparison to the parent drug. In addition, the cocrystals increased the solubility of PAL at pH 6.8 by 2–3 times and showed good stabilities in both the accelerated stability testing and stress testing. The PAL-RES cocrystal also exhibited an improved relative bioavailability (1.24 times) than PAL in vivo pharmacokinetics in rats. Moreover, the in vitro cytotoxicity assay of PAL-RES showed an increased IC50 value for normal cells, suggesting a better biosafety profile than PAL. Co-crystallization may represent a promising strategy for improving the physicochemical properties of PAL with better pharmacokinetics.
The Orthodox Dry Seeds Are Alive: A Clear Example of Desiccation Tolerance
Authors: Matilla Angel J.
Published: December 2021

To survive in the dry state, orthodox seeds acquire desiccation tolerance. As maturation progresses, the seeds gradually acquire longevity, which is the total timespan during which the dry seeds remain viable. The desiccation-tolerance mechanism(s) allow seeds to remain dry without losing their ability to germinate. This adaptive trait has played a key role in the evolution of land plants. Understanding the mechanisms for seed survival after desiccation is one of the central goals still unsolved. That is, the cellular protection during dry state and cell repair during rewatering involves a not entirely known molecular network(s). Although desiccation tolerance is retained in seeds of higher plants, resurrection plants belonging to different plant lineages keep the ability to survive desiccation in vegetative tissue. Abscisic acid (ABA) is involved in desiccation tolerance through tight control of the synthesis of unstructured late embryogenesis abundant (LEA) proteins, heat shock thermostable proteins (sHSPs), and non-reducing oligosaccharides. During seed maturation, the progressive loss of water induces the formation of a so-called cellular “glass state”. This glassy matrix consists of soluble sugars, which immobilize macromolecules offering protection to membranes and proteins. In this way, the secondary structure of proteins in dry viable seeds is very stable and remains preserved. ABA insensitive-3 (ABI3), highly conserved from bryophytes to Angiosperms, is essential for seed maturation and is the only transcription factor (TF) required for the acquisition of desiccation tolerance and its re-induction in germinated seeds. It is noteworthy that chlorophyll breakdown during the last step of seed maturation is controlled by ABI3. This update contains some current results directly related to the physiological, genetic, and molecular mechanisms involved in survival to desiccation in orthodox seeds. In other words, the mechanisms that facilitate that an orthodox dry seed is a living entity.
Isolation and Characterization of Polysaccharides from the Ascidian Styela clava
Authors: Valcarcel Jesus , Vázquez José Antonio , Varela Uxía R. , Reis Rui L. , Novoa-Carballal Ramon
Published: December 2021

Styela clava is an edible sea squirt farmed in Korea that has gradually invaded other seas, negatively impacting the ecology and economy of coastal areas. Extracts from S. clava have shown wide bioactivities, and ascidians have the unique capability among animals of biosynthesizing cellulose. Thus, S. clava is a relevant candidate for valorization. Herein, we aimed at surveying and characterizing polysaccharides in both tunic and flesh of this ascidian. To this end, we enzymatically hydrolyzed both tissues, recovering crystalline cellulose from the tunic with high aspect ratios, based on results from microscopy, X-ray diffraction, and infrared spectroscopy analyses. Alkaline hydroalcoholic precipitation was applied to isolate the polysaccharide fraction that was characterized by gel permeation chromatography (with light scattering detection) and NMR. These techniques allowed the identification of glycogen in the flesh with an estimated Mw of 7 MDa. Tunic polysaccharides consisted of two fractions of different Mw. Application of Diffusion-Ordered NMR allowed spectroscopically separating the low-molecular-weight fraction to analyze the major component of an estimated Mw of 40–66 kDa. We identified six different sugar residues, although its complexity prevented the determination of the complete structure and connectivities of the residues. The two more abundant residues were N-acetylated and possibly components of the glycosaminoglycan-like (GAG-like) family, showing the remaining similarities to sulfated galactans. Therefore, Styela clava appears as a source of nanocrystalline cellulose and GAG-like polysaccharides.
Sustainable Bio-Based Polymers: Towards a Circular Bioeconomy
Authors: Guzman-Puyol Susana , Benítez José J. , Heredia-Guerrero José A.
Published: December 2021

The valorization of biomass from different renewable resources (i [...]
Effects of Injection Molding Parameters on Properties of Insert-Injection Molded Polypropylene Single-Polymer Composites
Authors: Wang Jian , Mao Qianchao , Jiang Nannan , Chen Jinnan
Published: December 2021

The reinforcement and matrix of a polymer material can be composited into a single polymer composite (SPC), which is light weight, high strength, and has easy recyclability. The insert injection molding process can be used to realize the multiple production of SPC products with a short cycle time and wide processing temperature window. However, injection molding is a very complicated process; the influence of several important parameters should be determined to help in the future tailoring of SPCs to specific applications. The effects of varying barrel temperature, injection pressure, injection speed, and holding time on the properties of the insert-injection molded polypropylene (PP) SPC parts were investigated. It was found that the sample weight and tensile properties of the PP SPCs varied in different rules with the variations of these four parameters. The barrel temperature has a significant effect, followed by the holding time and injection pressure. Suitable parameter values should be determined for enhanced mechanical properties. Based on the tensile strength, a barrel temperature of 260 °C, an injection pressure of 127.6 MPa, an injection speed of 0.18 m/s, and a holding time of 60 s were determined as the optimum processing conditions. The best tensile strength and peel strength were up to 120 MPa and 19.44 N/cm, respectively.
Study and Investigation on 5G Technology: A Systematic Review
Authors: Dangi Ramraj , Lalwani Praveen , Choudhary Gaurav , You Ilsun , Pau Giovanni
Published: December 2021

In wireless communication, Fifth Generation (5G) Technology is a recent generation of mobile networks. In this paper, evaluations in the field of mobile communication technology are presented. In each evolution, multiple challenges were faced that were captured with the help of next-generation mobile networks. Among all the previously existing mobile networks, 5G provides a high-speed internet facility, anytime, anywhere, for everyone. 5G is slightly different due to its novel features such as interconnecting people, controlling devices, objects, and machines. 5G mobile system will bring diverse levels of performance and capability, which will serve as new user experiences and connect new enterprises. Therefore, it is essential to know where the enterprise can utilize the benefits of 5G. In this research article, it was observed that extensive research and analysis unfolds different aspects, namely, millimeter wave (mmWave), massive multiple-input and multiple-output (Massive-MIMO), small cell, mobile edge computing (MEC), beamforming, different antenna technology, etc. This article’s main aim is to highlight some of the most recent enhancements made towards the 5G mobile system and discuss its future research objectives.
Smart Monitoring and Control in the Future Internet of Things
Authors: Cicirelli Franco , Guerrieri Antonio , Vinci Andrea
Published: December 2021

The Internet of Things (IoT) and related technologies are promising in terms of realizing pervasive and smart applications, which, in turn, have the potential to improve the quality of life of people living in a connected world [...]
Smart Cutting Tools Used in the Processing of Aluminum Alloys
Authors: Dobrotă Dan , Racz Sever-Gabriel , Oleksik Mihaela , Rotaru Ionela , Tomescu Mădălin , Simion Carmen Mihaela
Published: December 2021

The processing of aluminum alloys in optimal conditions is a problem that has not yet been fully resolved. The research carried out so far has proposed various intelligent tools, but which cannot be used in the presence of cooling-lubricating fluids. The objective of the research carried out in the paper was to design intelligent tools that would allow a control of the vibrations of the tool tip and to determine a better roughness of the processed surfaces. The designed intelligent tools can be used successfully in the processing of aluminum alloys, not being sensitive to coolants-lubricants. In the research, the processing by longitudinal turning of a semi-finished product with a diameter Ø = 55 mm of aluminum alloy A2024-T3510 was considered. Two constructive variants of smart tools were designed, realized, and used, and the obtained results were compared with those registered for the tools in the classic constructive variant. The analysis of vibrations that occur during the cutting process was performed using the following methods: Fast Fourier Transform (FFT); Short-Time Fourier-Transformation (STFT); the analysis of signal of vibrations. A vibration analysis was also performed by modeling using the Finite Element Method (FEM). In the last part of the research, an analysis of the roughness of the processed surfaces, was carried out and a series of diagrams were drawn regarding curved profiles; filtered profiles; Abbott–Firestone curve. Research has shown that the use of smart tools in the proposed construction variants is a solution that can be used in very good conditions for processing aluminum alloys, in the presence of cooling-lubrication fluids.
Monitoring Wheat Powdery Mildew Based on Hyperspectral, Thermal Infrared, and RGB Image Data Fusion
Authors: Feng Ziheng , Song Li , Duan Jianzhao , He Li , Zhang Yanyan , Wei Yongkang , Feng Wei
Published: December 2021

Powdery mildew severely affects wheat growth and yield; therefore, its effective monitoring is essential for the prevention and control of the disease and global food security. In the present study, a spectroradiometer and thermal infrared cameras were used to obtain hyperspectral signature and thermal infrared images data, and thermal infrared temperature parameters (TP) and texture features (TF) were extracted from the thermal infrared images and RGB images of wheat with powdery mildew, during the wheat flowering and filling periods. Based on the ten vegetation indices from the hyperspectral data (VI), TF and TP were integrated, and partial least square regression, random forest regression (RFR), and support vector machine regression (SVR) algorithms were used to construct a prediction model for a wheat powdery mildew disease index. According to the results, the prediction accuracy of RFR was higher than in other models, under both single data source modeling and multi-source data modeling; among the three data sources, VI was the most suitable for powdery mildew monitoring, followed by TP, and finally TF. The RFR model had stable performance in multi-source data fusion modeling (VI&TP&TF), and had the optimal estimation performance with 0.872 and 0.862 of R2 for calibration and validation, respectively. The application of multi-source data collaborative modeling could improve the accuracy of remote sensing monitoring of wheat powdery mildew, and facilitate the achievement of high-precision remote sensing monitoring of crop disease status.
Artificial Intelligence-Enabled DDoS Detection for Blockchain-Based Smart Transport Systems
Authors: Liu Tong , Sabrina Fariza , Jang-Jaccard Julian , Xu Wen , Wei Yuanyuan
Published: December 2021

A smart public transport system is expected to be an integral part of our human lives to improve our mobility and reduce the effect of our carbon footprint. The safety and ongoing maintenance of the smart public transport system from cyberattacks are vitally important. To provide more comprehensive protection against potential cyberattacks, we propose a novel approach that combines blockchain technology and a deep learning method that can better protect the smart public transport system. By the creation of signed and verified blockchain blocks and chaining of hashed blocks, the blockchain in our proposal can withstand unauthorized integrity attack that tries to forge sensitive transport maintenance data and transactions associated with it. A hybrid deep learning-based method, which combines autoencoder (AE) and multi-layer perceptron (MLP), in our proposal can effectively detect distributed denial of service (DDoS) attempts that can halt or block the urgent and critical exchange of transport maintenance data across the stakeholders. The experimental results of the hybrid deep learning evaluated on three different datasets (i.e., CICDDoS2019, CIC-IDS2017, and BoT-IoT) show that our deep learning model is effective to detect a wide range of DDoS attacks achieving more than 95% F1-score across all three datasets in average. The comparison of our approach with other similar methods confirms that our approach covers a more comprehensive range of security properties for the smart public transport system.
Design and Analysis of Soft Error Rate in FET/CNTFET Based Radiation Hardened SRAM Cell
Authors: Muthu Bharathi Raj , Pushpa Ewins Pon , Dhandapani Vaithiyanathan , Jayaraman Kamala , Vasanthakumar Hemalatha , Oh Won-Chun , Sagadevan Suresh
Published: December 2021

Aerospace equipages encounter potential radiation footprints through which soft errors occur in the memories onboard. Hence, robustness against radiation with reliability in memory cells is a crucial factor in aerospace electronic systems. This work proposes a novel Carbon nanotube field-effect transistor (CNTFET) in designing a robust memory cell to overcome these soft errors. Further, a petite driver circuit to test the SRAM cells which serve the purpose of precharge and sense amplifier, and has a reduction in threefold of transistor count is recommended. Additionally, analysis of robustness against radiation in varying memory cells is carried out using standard GPDK 90 nm, GPDK 45 nm, and 14 nm CNTFET. The reliability of memory cells depends on the critical charge of a device, and it is tested by striking an equivalent current charge of the cosmic ray’s linear energy transfer (LET) level. Also, the robustness of the memory cell is tested against the variation in process, voltage and temperature. Though CNTFET surges with high power consumption, it exhibits better noise margin and depleted access time. GPDK 45 nm has an average of 40% increase in SNM and 93% reduction of power compared to the 14 nm CNTFET with 96% of surge in write access time. Thus, the conventional MOSFET’s 45 nm node outperforms all the configurations in terms of static noise margin, power, and read delay which swaps with increased write access time.
The Identification of Non-Driving Activities with Associated Implication on the Take-Over Process
Authors: Yang Lichao , Babayi Semiromi Mahdi , Xing Yang , Lv Chen , Brighton James , Zhao Yifan
Published: December 2021

In conditionally automated driving, the engagement of non-driving activities (NDAs) can be regarded as the main factor that affects the driver’s take-over performance, the investigation of which is of great importance to the design of an intelligent human–machine interface for a safe and smooth control transition. This paper introduces a 3D convolutional neural network-based system to recognize six types of driver behaviour (four types of NDAs and two types of driving activities) through two video feeds based on head and hand movement. Based on the interaction of driver and object, the selected NDAs are divided into active mode and passive mode. The proposed recognition system achieves 85.87% accuracy for the classification of six activities. The impact of NDAs on the perspective of the driver’s situation awareness and take-over quality in terms of both activity type and interaction mode is further investigated. The results show that at a similar level of achieved maximum lateral error, the engagement of NDAs demands more time for drivers to accomplish the control transition, especially for the active mode NDAs engagement, which is more mentally demanding and reduces drivers’ sensitiveness to the driving situation change. Moreover, the haptic feedback torque from the steering wheel could help to reduce the time of the transition process, which can be regarded as a productive assistance system for the take-over process.
Extraction of a Weak Flow Field for a Multi-Rotor Unmanned Aerial Vehicle (UAV) Using High-Speed Background-Oriented Schlieren (BOS) Technology
Authors: Liu Xianglei , Guo Tongxin , Zhang Pengfei , Jia Zhenkai , Tong Xiaohua
Published: December 2021

To optically capture and analyze the structure and changes of the flow field of a weak airflow object with high accuracy, this study proposes novel weak flow field extraction methods based on background-oriented schlieren. First, a fine background pattern texture and a sensor network layout were designed to satisfy the requirement of weak flow field extraction. Second, the image displacement was extracted by calculating the correlation matrix in the frequency domain for a particle image velocimetry algorithm, and further calculations were performed for the density field using Poisson’s equation. Finally, the time series baseline stacking method was proposed to obtain the flow field changes of weak airflow structures. A combustion experiment was conducted to validate the feasibility and accuracy of the proposed method. The results of a quad-rotor unmanned aerial vehicle experiment showed that the clear, uneven, and continuous quantitative laminar flow field could be obtained directly, which overcame the interference of the weak airflow, large field of view, and asymmetrical steady flow.
Cloud-Based User Behavior Emulation Approach for Space-Ground Integrated Networks
Authors: Tao Leiting , Wang Xiaofeng , Liu Yuan , Wu Jie
Published: December 2021

Cyber-physical systems (CPSs) based on space-ground integrated networks (SGINs) enable CPSs to break through geographical restrictions in space. Therefore, providing a test platform is necessary for new technical verification and network security strategy evaluations of SGINs. User behavior emulation technology can effectively support the construction of a test platform. Given the inherent dynamic changes, diverse behaviors, and large-scale characteristics of SGIN users, we propose user behavior emulation technology based on a cloud platform. First, the dynamic emulation architecture for user behavior for SGINs is designed. Then, normal user behavior emulation strategy driven by the group user behavior model in real time is proposed, which can improve the fidelity of emulation. Moreover, rogue user behavior emulation technology is adopted, based on traffic replay, to perform the security evaluation. Specifically, virtual Internet Protocol (IP) technology and the epoll model are effectively integrated in this investigation to resolve the contradiction between large-scale emulation and computational overhead. The experimental results demonstrate that the strategy meets the requirement of a diverse and high-fidelity dynamic user behavior emulation and reaches the emulation scale of 100,000-level concurrent communication for normal users and 100,000-level concurrent attacks for rogue users.
Enhancing System Acceptance through User-Centred Design: Integrating Patient Generated Wellness Data
Authors: Pais Sarita , Petrova Krassie , Parry Dave
Published: December 2021

Gestational diabetes mellitus (GDM) is a condition that appears during pregnancy and is expected to be a temporary one. While patients are encouraged to manage it themselves, research findings indicate that GDM may negatively affect the foetus; in addition, there is an increased risk of women with GDM subsequently developing Type 2 diabetes. To alleviate the risks, women with GDM are advised to maintain a record of their diet and blood glucose levels and to attend regular clinical reviews. Rather than using a paper diary, women with GDM can maintain a record of their blood glucose level readings and other relevant data using a wellness mobile application (app). However, such apps are developed for general use and may not meet the specific needs of clinical staff (physicians, dietitians, obstetricians and midwives) involved in managing GDM; for example, an app may record glucose readings but not the details of a meal taken before or after the glucose reading. Second, the apps do not permanently store the data generated by the patient and do not support the transfer of these data to a clinical system or information portal. The mobile health (mHealth) system designed and developed in this research allows one to integrate different types of user generated wellness data into a centralised database. A user-centered design (UCD) approach informed by the technology acceptance model (TAM) was adopted. This paper investigates and evaluates the effectiveness of the approach with regard to facilitating system acceptance and future adoption through an early focus on enhancing system usefulness and ease of use. The functional system requirements of the proposed system were refined through a series of interviews with the perspective of clinical users; ease-of-use and usability issues were resolved through ‘think aloud’ sessions with clinicians and GDM patients.
Pros and Cons of CAD/CAM Technology for Infection Prevention in Dental Settings during COVID-19 Outbreak
Authors: Barenghi Livia , Barenghi Alberto , Garagiola Umberto , Di Blasio Alberto , Giannì Aldo Bruno , Spadari Francesco
Published: December 2021

The purpose of this commentary is to update the evidence reported in our previous review on the advantages and limitations of computer-aided design/computer-aided manufacturing technology in the promotion of dental business, as well as to guarantee patient and occupational safety. The COVID-19 pandemic led to an unprecedented focus on infection prevention; however, waves of COVID-19 follow one another, asymptomatic cases are nearly impossible to identify by triage in a dental setting, and the effectiveness of long-lasting immune protection through vaccination remains largely unknown. Different national laws and international guidelines (mainly USA-CDC, ECDC) have often brought about dissimilar awareness and operational choices, and in general, there has been very limited attention to this technology. Here, we discuss its advantages and limitations in light of: (a) presence of SARS-CoV-2 in the oral cavity, saliva, and dental biofilm and activation of dormant microbial infections; (b) the prevention of SARS-CoV-2 transmission by aerosol and fomite contamination; (c) the detection of various oral manifestations of COVID-19; (d) specific information for the reprocessing of the scanner tip and the ward from the manufacturers.
Predicting Fall Counts Using Wearable Sensors: A Novel Digital Biomarker for Parkinson’s Disease
Authors: Greene Barry R. , Premoli Isabella , McManus Killian , McGrath Denise , Caulfield Brian
Published: December 2021

People with Parkinson’s disease (PD) experience significant impairments to gait and balance; as a result, the rate of falls in people with Parkinson’s disease is much greater than that of the general population. Falls can have a catastrophic impact on quality of life, often resulting in serious injury and even death. The number (or rate) of falls is often used as a primary outcome in clinical trials on PD. However, falls data can be unreliable, expensive and time-consuming to collect. We sought to validate and test a novel digital biomarker for PD that uses wearable sensor data obtained during the Timed Up and Go (TUG) test to predict the number of falls that will be experienced by a person with PD. Three datasets, containing a total of 1057 (671 female) participants, including 71 previously diagnosed with PD, were included in the analysis. Two statistical approaches were considered in predicting falls counts: the first based on a previously reported falls risk assessment algorithm, and the second based on elastic net and ensemble regression models. A predictive model for falls counts in PD showed a mean R2 value of 0.43, mean error of 0.42 and a mean correlation of 30% when the results were averaged across two independent sets of PD data. The results also suggest a strong association between falls counts and a previously reported inertial sensor-based falls risk estimate. In addition, significant associations were observed between falls counts and a number of individual gait and mobility parameters. Our preliminary research suggests that the falls counts predicted from the inertial sensor data obtained during a simple walking task have the potential to be developed as a novel digital biomarker for PD, and this deserves further validation in the targeted clinical population.