bluuebunny/crossref_metadata_2025 huggingface dataset:
Protective Effects of a Polyphenol-Rich Blueberry Extract on Adult Human Neural Progenitor Cells
Authors: Zheng Tong , Bielinski Donna F. , Fisher Derek R. , Zhang Jianyi , Shukitt-Hale Barbara
Published: September 2022

The aging process impacts neural stem cells and causes a significant decline in neurogenesis that contributes to neuronal dysfunction leading to cognitive decline. Blueberries are rich in polyphenols and have been shown to improve cognition and memory in older humans. While our previous studies have shown that blueberry supplementations can increase neurogenesis in aged rodents, it is not clear whether this finding can be extrapolated to humans. We thus investigated the effects of blueberry treatments on adult hippocampal human neural progenitor cells (AHNPs) that are involved in neurogenesis and potentially in memory and other brain functions. Cultured AHNPs were treated with blueberry extract at different concentrations. Their viability, proliferation, and differentiation were evaluated with and without the presence of a cellular oxidative stressor, dopamine, and potential cellular mechanisms were also investigated. Our data showed that blueberry extract can significantly increase the viability and proliferation rates of control hippocampal AHNPs and can also reverse decreases in viability and proliferation induced by the cellular stressor dopamine. These effects may be associated with blueberry’s anti-inflammatory, antioxidant, and calcium-buffering properties. Polyphenol-rich berry extracts thus confer a neuroprotective effect on human hippocampal progenitor cells in vitro.
The Synthesis and Biological Evaluation of Aloe-Emodin-Coumarin Hybrids as Potential Antitumor Agents
Authors: Shang Hai , Hu Yue , Li Jingrong , Li Lingyu , Tian Yu , Li Xiaoxue , Wu Qi , Zou Zhongmei
Published: September 2022

A series of novel aloe-emodin–coumarin hybrids were designed and synthesized. The antitumor activity of these derivatives was evaluated against five human tumor cell lines (A549, SGC-7901, HepG2, MCF-7 and HCT-8). Some of the synthesized compounds exhibited moderate to good activity against one or more cell lines. Particularly, compound 5d exhibited more potent antiproliferative activity than the reference drug etoposide against all tested tumor cell lines, indicating that it had a broad spectrum of antitumor activity and that it may provide a promising lead compound for further development as an antitumor agent by structural modification. Furthermore, the structure–activity relationship study of the synthesized compounds was also performed.
Effect of D-Limonene Nanoemulsion Edible Film on Banana (Musa sapientum Linn.) Post-Harvest Preservation
Authors: Hou Chih-Yao , Hazeena Sulfath Hakkim , Hsieh Shu-Ling , Li Bao-Hong , Chen Min-Hung , Wang Ping-Yu , Zheng Bao-Qing , Liang Yu-Shen
Published: September 2022

D-limonene (4-isopropenyl-1-methylcyclohexene) is an important compound in several citrus essential oils (such as orange, lemon, tangerine, lime, and grapefruit). It has been used as a flavoring agent and as a food preservative agent, with generally recognized as safe (GRAS) status. D-limonene has been well-studied for its anti-inflammatory, antioxidant, anti-cancer, and antibacterial properties. The antibacterial activity of D-limonene against food-borne pathogens was investigated in this study by preparing a D-limonene nanoemulsion. The D-limonene solution and nanoemulsion have been prepared in six concentrations, 0.04%, 0.08%, 0.1%, 0.2%, 0.4%, and 0.8% (v/v), respectively, and the antibacterial activity was tested against four food-borne pathogens (Staphylococcus aureus, Listeria monocytogenes, Salmonella enterica, and Escherichia coli). The results showed that the D-limonene nanoemulsion had good nanoscale and overall particle size uniformity, and its particle size was about 3~5 nm. It has been found that the D-limonene solution and nanoemulsion have a minimal inhibitory concentration of 0.336 mg/mL, and that they could inhibit the growth of microorganisms efficiently. The data indicate that the D-limonene nanoemulsion has more antibacterial ability against microorganisms than the D-limonene essential oil. After bananas are treated with 1.0% and 1.5% D-limonene nanoemulsion coatings, the water loss of the bananas during storage and the percentage of weight loss are reduced, which can inhibit the activity of pectinase. The application of a biocoating provides a good degree of antibacterial activity and air and moisture barrier properties, which help with extending the shelf life of bananas.
Effect of Hybrid Nanofluids Concentration and Swirling Flow on Jet Impingement Cooling
Authors: Jen Wai Ooi , Gunnasegaran Prem , Hasini Hasril
Published: September 2022

Nanofluids have become increasingly salient in heat transfer applications due to their promising properties that can be tailored to meet specific needs. The use of nanofluids in jet impingement flows has piqued the interest of numerous researchers owing to the significant heat transfer enhancement, which is vital in the technological dependence era in every aspect of life, particularly in engineering applications and industry. The aim of this current work is to investigate the effect of hybrid nanofluids concentration and swirling flow on jet impingement cooling through experimental approach. The hybrid nanofluids are prepared through a two-step method and the characterization process is carried out to study the stability and morphological structure of the sample prepared. The prepared hybrid nanofluids are then used as a cooling agent to evaluate the heat transfer performance of jet impinging system. The experimental investigation compares the performance of swirling impinging jets (SIJs) with conventional impinging jets (CIJs) under various jet-to-plate distance (H/D) ratios and nanofluid concentrations. The effects of adding surfactant on nanofluids are also examined. The heat transfer performance of ZnO/water and CuO/water mono-nanofluids are used as comparison to ZnO-CuO/water hybrid nanofluid. The results show that the thermal performance of ZnO-CuO/water hybrid nanofluid is better than that of the mono-nanofluids. Furthermore, as the mass fraction increases, the heat transfer rates improve. The effect of heat transmission by swirling impinging jets is better than that of conventional impinging jets under similar operating conditions. At H/D = 4, Re = 20,000 and hybrid nanofluid concentration at 0.1% under SIJ is observed to have the highest overall Nusselt number.
Biodistribution of Multimodal Gold Nanoclusters Designed for Photoluminescence-SPECT/CT Imaging and Diagnostic
Authors: Jarockyte Greta , Stasys Marius , Poderys Vilius , Buivydaite Kornelija , Pleckaitis Marijus , Bulotiene Danute , Matulionyte Marija , Karabanovas Vitalijus , Rotomskis Ricardas
Published: September 2022

Highly biocompatible nanostructures for multimodality imaging are critical for clinical diagnostics improvements in the future. Combining optical imaging with other techniques may lead to important advances in diagnostics. The purpose of such a system would be to combine the individual advantages of each imaging method to provide reliable and accurate information at the site of the disease bypassing the limitations of each. The aim of the presented study was to evaluate biodistribution of the biocompatible technetium-99m labelled bovine serum albumin–gold nanoclusters (99mTc-BSA-Au NCs) as photoluminescence-SPECT/CT agent in experimental animals. It was verified spectroscopically that radiolabelling with 99mTc does not influence the optical properties of BSA-Au NCs within the synthesized 99mTc-BSA-Au NCs bioconjugates. Biodistribution imaging of the 99mTc-BSA-Au NCs in Wistar rats was performed using a clinical SPECT/CT system. In vivo imaging of Wistar rats demonstrated intense cardiac blood pool activity, as well as rapid blood clearance and accumulation in the kidneys, liver, and urinary bladder. Confocal images of kidney, liver and spleen tissues revealed no visible uptake indicating that the circulation lifetime of 99mTc-BSA-Au NCs in the bloodstream might be too short for accumulation in these tissues. The cellular uptake of 99mTc-BSA-Au NCs in kidney cells was also delayed and substantial accumulation was observed only after 24-h incubation. Based on our experiments, it was concluded that 99mTc-BSA-Au NCs could be used as a contrast agent and shows promise as potential diagnostic agents for bloodstream imaging of the excretory organs in vivo.
Comparative Analysis of LiMPO4 (M = Fe, Co, Cr, Mn, V) as Cathode Materials for Lithium-Ion Battery Applications—A First-Principle-Based Theoretical Approach
Authors: Kanungo Sayan , Bhattacharjee Ankur , Bahadursha Naresh , Ghosh Aritra
Published: September 2022

The rapidly increasing demand for energy storage has been consistently driving the exploration of different materials for Li-ion batteries, where the olivine lithium-metal phosphates (LiMPO4) are considered one of the most potential candidates for cathode-electrode design. In this context, the work presents an extensive comparative theoretical study of the electrochemical and electrical properties of iron (Fe)-, cobalt (Co)-, manganese (Mn)-, chromium (Cr)-, and vanadium (V)-based LiMPO4 materials for cathode design in lithium (Li)-ion battery applications, using the density-functional-theory (DFT)-based first-principle-calculation approach. The work emphasized different material and performance aspects of the cathode design, including the cohesive energy of the material, Li-intercalation energy in olivine structure, and intrinsic diffusion coefficient across the Li channel, as well as equilibrium potential and open-circuit potential at different charge-states of Li-ion batteries. The results indicate the specification of the metal atom significantly influences the Li diffusion across the olivine structure and the overall energetics of different LiMPO4. In this context, a clear correlation between the structural and electrochemical properties has been demonstrated in different LiMPO4. The key findings offer significant theoretical and design-level insight for estimating the performance of studied LiMPO4-based Li-ion batteries while interfacing with different application areas.
Copper-Arsenic-Sulfide Thin-Films from Local Raw Materials Deposited via RF Co-Sputtering for Photovoltaics
Authors: Centeno Pedro , Alexandre Miguel , Neves Filipe , Fortunato Elvira , Martins Rodrigo , Águas Hugo , Mendes Manuel J.
Published: September 2022

The inexorable increase of energy demand and the efficiency bottleneck of monocrystalline silicon solar cell technology is promoting the research and development of alternative photovoltaic materials. Copper-arsenic-sulfide (CAS) compounds are still rather unexplored in the literature, yet they have been regarded as promising candidates for use as p-type absorber in solar cells, owing to their broad raw material availability, suitable bandgap and high absorption coefficient. Here, a comprehensive study is presented on the structural and optoelectronic properties of CAS thin-films deposited via radio-frequency magnetron co-sputtering, using a commercial Cu target together with a Cu-As-S target with material obtained from local resources, specifically from mines in the Portuguese region of the Iberian Pyrite Belt. Raman and X-ray diffraction analysis confirm that the use of two targets results in films with pronounced stoichiometry gradients, suggesting a transition from amorphous CAS compounds to crystalline djurleite (Cu31S16), with the increasing proximity to the Cu target. Resistivity values from 4.7 mΩ·cm to 17.4 Ω·cm are obtained, being the lowest resistive films, those with pronounced sub-bandgap free-carrier absorption. The bandgap values range from 2.20 to 2.65 eV, indicating promising application as wide-bandgap semiconductors in third-generation (e.g., multi-junction) photovoltaic devices.
The Influence of Electrode Thickness on the Structure and Water Splitting Performance of Iridium Oxide Nanostructured Films
Authors: Altowyan Abeer S. , Shaban Mohamed , Abdelkarem Khaled , El Sayed Adel M.
Published: September 2022

For a safe environment, humanity should be oriented towards renewable energy technology. Water splitting (WS), utilizing a photoelectrode with suitable thickness, morphology, and conductivity, is essential for efficient hydrogen production. In this report, iridium oxide (IrOx) films of high conductivity were spin-cast on glass substrates. FE-SEM showed that the films are of nanorod morphology and different thicknesses. UV-Vis spectra indicated that the absorption and reflectance of the films depend on their thickness. The optical band gap (Eg) was increased from 2.925 eV to 3.07 eV by varying the spin speed (SS) of the substrates in a range of 1.5 × 103–4.5 × 103 rpm. It was clear from the micro-Raman spectra that the films were amorphous. The Eg vibrational mode of Ir–O stretching was red-shifted from 563 cm−1 (for the rutile IrO2 single crystal) to 553 cm−1. The IrOx films were used to develop photoelectrochemical (PEC) hydrogen production catalysts in 0.5M of sodium sulfite heptahydrate Na2SO3·7H2O (2-electrode system), which exhibits higher hydrogen evaluation (HE) reaction activity, which is proportional to the thickness and absorbance of the used IrOx photocathode, as it showed an incident photon-to-current efficiency (IPCE%) of 7.069% at 390 nm and −1 V. Photocurrent density (Jph = 2.38 mA/cm2 at −1 V vs. platinum) and PEC hydrogen generation rate (83.68 mmol/ h cm2 at 1 V) are the best characteristics of the best electrode (the thickest and most absorbent IrOx photocathode). At −1 V and 500 nm, the absorbed photon-to-current conversion efficiency (APCE%) was 7.84%. Electrode stability, thermodynamic factors, solar-to-hydrogen conversion efficiency (STH), and electrochemical impedance spectroscopies (EISs) were also studied.
Comment on Du et al. Gender Differences in the Relationships between Perceived Stress, Eating Behaviors, Sleep, Dietary Risk, and Body Mass Index. Nutrients 2022, 14, 1045
Authors: Kuo Wan-Chin , Stevens Jennifer M. , Tebbe Elliot A.
Published: September 2022

We read Du et al. [...]
Impact of COVID-19 on Short- and Medium-Term Prescription of Enteral Nutrition in the General Population vs. Older People in the Community of Madrid, Spain
Authors: Luque Calvo Carolina , Mataix Sanjuan Ángel Luis , Candela Toha Ángel , Martínez Castro Nilda , Pintor Recuenco María Rosario , Calleja López José Luis , Botella-Carretero José Ignacio , Arrieta Blanco Francisco
Published: September 2022

We aimed to analyse the impact of COVID-19 during 2020 and 2021 on the prescription of enteral nutritional support and its expenditure in the Community of Madrid, Spain, compared to pre-pandemic data from 2016 in the general population vs. elderly. We analysed official electronic prescriptions of all public hospitals of the Community of Madrid. The population over 75 years of age have the higher prescription of nutritional supplements (p < 0.001 vs. other age groups), with no differences between the 45–64 age group compared to the 65–74 age group (χ2 = 3.259, p = 0.196). The first wave of COVID-19 or the first time there was a real awareness of the virus in Spain is similar in a way to the first peak of prescription of enteral nutrition in March 2020. The second peak of prescription was observed in the over 75 age group in July 2020, being more pronounced in December 2020 and March–April of the following year (F = 7.863, p = 0.041). The last peaks correspond to summer 2021 and autumn of the same year (p = 0.031—year 2021 vs. 2020, p = 0.011—year 2021 vs. 2019), where a relationship between increased prescription of enteral nutrition and COVID-19 cases is observed. High-protein and high-calorie dietary therapies were the most prescribed in patients with or without diabetes. All of this entailed higher cost for the Community of Madrid. In conclusion, COVID-19 significantly affected the prescription of nutritional support, especially in the population over 75 years of age.
The Positive Association of Plasma Levels of Vitamin C and Inverse Association of VCAM-1 and Total Adiponectin with Bone Mineral Density in Subjects with Diabetes
Authors: Jain Sushil K. , McLean William E. , Stevens Christopher M. , Dhawan Richa
Published: September 2022

Context. Population studies have shown a trend in decreasing vitamin C status and increasing prevalence of osteoporosis in patients with diabetes and non-diabetic people. Dietary vitamin C consumption is linked to improvement in bone mineral density (BMD) in epidemiological studies. VCAM-1 and adiponectin are known to activate osteoclasts, which increase bone loss. Aim: This study examined whether there is any association between the circulating level of vitamin C and BMD and whether the beneficial effect of vitamin C on BMD was linked to a simultaneous decrease in circulating levels of adiponectin and VCAM-1 in subjects with diabetes. Methods: Patients with diabetes (T2D, n = 74) and age-matched non-diabetic controls (n = 26) were enrolled in this study. Fasting blood levels of glycemia, adiponectin, VCAM-1, inflammation biomarkers, and vitamin C were determined in both groups. The BMD of the lumbar spine (L1–L4), left femur, and right femur was determined using a DXA scan in subjects with diabetes. Results: Patients with diabetes had lower levels of vitamin C and higher levels of VCAM-1 and inflammatory cytokines. There was a significant positive association between vitamin C blood levels and lumbar spine BMD as well as a significant negative association between total adiponectin and VCAM-1 levels with that of vitamin C and lumbar BMD in patients with diabetes. Total adiponectin and VCAM-1 also showed a negative association with BMD of both the right and left femurs. The inter-relationship among the circulating levels of vitamin C and VCAM-1 and BMD was strong and is a novel finding. Conclusions: This study reports a positive association of circulating vitamin C levels and the BMD and that the beneficial effects of vitamin C on BMD could be linked to a simultaneous lowering in circulating VCAM-1 and total adiponectin levels. Thus, dietary vitamin C consumption has potential to lower inflammation and the risk of osteoporosis in subjects with diabetes.
Vitamin D-Binding Protein, Bioavailable, and Free 25(OH)D, and Mortality: A Systematic Review and Meta-Analysis
Authors: Zhu Anna , Kuznia Sabine , Boakye Daniel , Schöttker Ben , Brenner Hermann
Published: September 2022

Introduction: Observational studies reported inverse associations between serum total 25-hydroxyvitamin D (25(OH)D) concentrations and mortality. Evolving evidence indicated, however, that bioavailable or free 25(OH)D may be even better predictors of mortality. We conducted a systematic review and meta-analysis to summarize the epidemiological evidence on associations of vitamin D-binding protein (VDBP), albumin-bound, bioavailable, and free 25(OH)D, with mortality. Methods: We systematically searched PubMed and Web of Science, up to 27 May 2022. Predictors of interest included serum or plasma concentrations of VDBP, albumin-bound, bioavailable, and free 25(OH)D. Assessed health outcomes were all-cause and cause-specific mortality. We included studies reporting associations between these biomarkers and mortality outcomes. We applied random-effects models for meta-analyses to summarize results from studies assessing the same vitamin D biomarkers and mortality outcomes. Results: We identified twelve eligible studies, including ten on VDBP, eight on bioavailable 25(OH)D, and eight on free 25(OH)D. No study reported on albumin-bound 25(OH)D and mortality. In meta-analyses, the highest levels of bioavailable and free 25(OH)D were associated with 37% (hazard ratio (HR): 0.63, 95% confidence interval (CI): 0.46, 0.87), and 29% (HR: 0.71, 95% CI: 0.53, 0.97) decrease in all-cause mortality, respectively, compared with the lowest levels. These estimates were similar to those for total 25(OH)D (HR: 0.67, 95% CI: 0.56, 0.80) observed in the same studies. Higher VDBP levels were associated with lower all-cause mortality in cancer patient cohorts. However, no such association was observed in general population cohorts. Conclusions: Similar inverse associations of total, bioavailable, and free 25(OH)D with mortality suggest that bioavailable and free 25(OH)D do not provide incremental value in predicting mortality.
Design, Synthesis, In Silico Testing, and In Vitro Evaluation of Thiazolidinone-Based Benzothiazole Derivatives as Inhibitors of α-Amylase and α-Glucosidase
Authors: Khan Shoaib , Iqbal Shahid , Khan Marwa , Rehman Wajid , Shah Mazloom , Hussain Rafaqat , Rasheed Liaqat , Khan Yousaf , Dera Ayed A. , Pashameah Rami Adel , Alzahrani Eman , Farouk Abd-ElAziem
Published: September 2022

In this study, a stepwise reaction afforded thiazolidinone-based benzothiazole derivatives 1–15, and the synthesized derivatives were then screened for biological significance and found to be the leading candidates against α-amylase and α-glucosidase enzymes. Almost all derivatives showed excellent to good activity ranging against α-amylase, IC50 = 2.10 ± 0.70 to 37.50 ± 0.70 μM, and α-glucosidase, IC50 = 3.20 ± 0.05 to 39.40 ± 0.80 μM. Some analogues such as 4 (2.40 ± 0.70 and 3.50 ± 0.70 μM), 5 (2.30 ± 0.05 and 4.80 ± 0.10 μM), and 6 (2.10 ± 0.70 and 3.20 ± 0.70 μM) were found with folds better activity than that of the standard drug acarbose (9.10 ± 0.10 and 10.70 ± 0.10 μM), respectively. Moreover, the structure–activity relationship (SAR) has been established for all compounds. A molecular docking study has been carried out to explore the binding interactions against α-amylase and α-glucosidase enzymes.
Xanthine Oxidase Inhibitory Activity and Chemical Composition of Pistacia chinensis Leaf Essential Oil
Authors: Huang Chi-Ya , Chang Yu-Yi , Chang Shang-Tzen , Chang Hui-Ting
Published: September 2022

Gout is a common metabolic disease caused by abnormal purine metabolism that promotes the formation and deposition of monosodium urate crystals within joints that causes acute arthritis and can seriously affect the daily life of patients. Pistacia chinensis is one of the traditional medicinal plants of the Anacardiaceae family, and there have been many studies on its biological activity, including anti-inflammatory, antidepressant, antibacterial, antioxidant, and hypoglycemic activities. The aim of this study was to evaluate the antigout effect of P. chinensis leaf essential oil and its constituents through xanthine oxidase inhibition. Leaf essential oil showed good xanthine oxidase inhibitory activity for both substrates, hypoxanthine and xanthine. Six fractions were obtained from open column chromatography, and fraction E1 exhibited the best activity. The constituents of leaf essential oil and fraction E1 were analyzed by GC-MS. The main constituents of both leaf essential oil and fraction E1 were limonene and 3-carene; limonene showed a higher inhibitory effect on xanthine oxidase. Based on the enzyme kinetic investigation, limonene was the mixed-type inhibitor against xanthine oxidase. The results revealed that Pistacia chinensis leaf essential oil and limonene have the potential to act as natural remedies for the treatment of gout.
Development of Nasal Vaccines and the Associated Challenges
Authors: Nian Xuanxuan , Zhang Jiayou , Huang Shihe , Duan Kai , Li Xinguo , Yang Xiaoming
Published: September 2022

Viruses, bacteria, fungi, and several other pathogenic microorganisms usually infect the host via the surface cells of respiratory mucosa. Nasal vaccination could provide a strong mucosal and systemic immunity to combat these infections. The intranasal route of vaccination offers the advantage of easy accessibility over the injection administration. Therefore, nasal immunization is considered a promising strategy for disease prevention, particularly in the case of infectious diseases of the respiratory system. The development of a nasal vaccine, particularly the strategies of adjuvant and antigens design and optimization, enabling rapid induction of protective mucosal and systemic responses against the disease. In recent times, the development of efficacious nasal vaccines with an adequate safety profile has progressed rapidly, with effective handling and overcoming of the challenges encountered during the process. In this context, the present report summarizes the most recent findings regarding the strategies used for developing nasal vaccines as an efficient alternative to conventional vaccines.
Effect of Laparoscopic Sleeve Gastrectomy on the Pharmacokinetics of Oral Omeprazole Using a Population Approach
Authors: Chen Kaifeng , Luo Ping , Zhu Shaihong , Lin Yaqi , Yang Nan , Huang Shuqi , Ding Qin , Zhu Liyong , Pei Qi
Published: September 2022

Omeprazole is commonly prescribed to obese patients and patients after laparoscopic sleeve gastrectomy (LSG). The pharmacokinetics of oral omeprazole after LSG are still unknown. Therefore, the aim of this study was to investigate the pharmacokinetics of oral omeprazole in obese patients before and after LSG. A total of 331 blood samples were collected from 62 obese patients preoperatively (visit 1) followed by 41 patients 7 days post-LSG (visit 2) and 20 patients 1 month post-LSG (visit 3). Population pharmacokinetic analysis was performed using NONMEM to characterize the effect of LSG on omeprazole absorption and disposition. A one-compartment model with 12 transit absorption compartments and linear elimination successfully described the data. Compared with pre-surgery, the oral omeprazole time to maximum plasma concentration (Tmax) was reduced and maximum plasma concentration (Cmax) was higher, but the apparent clearance (CL/F) and area under the plasma concentration–time curve (AUC) were unchanged 7 days and 1 month after surgery. In addition, the CYP2C19 genotype and liver function exhibited a significant influence on omeprazole CL/F. LSG increased the rate of omeprazole absorption but did not affect omeprazole exposure. A dose of 20 mg omeprazole once daily may be adequate for relieving gastrointestinal tract discomfort at short-term follow-up post-LSG.
Characterization of the Secretome of Pathogenic Candida glabrata and Their Effectiveness against Systemic Candidiasis in BALB/c Mice for Vaccine Development
Authors: Kamli Majid Rasool , Sabir Jamal S. M. , Malik Maqsood Ahmad , Ahmad Aijaz
Published: September 2022

Infections by non-albicans Candida species have increased drastically in the past few decades. Candida glabrata is one of the most common opportunistic fungal pathogens in immunocompromised individuals, owing to its capability to attach to various human cell types and medical devices and being intrinsically weakly susceptible to azoles. Immunotherapy, including the development of antifungal vaccines, has been recognized as an alternative approach for preventing and treating fungal infections. Secretory proteins play a crucial role in establishing host–pathogen interactions and are also responsible for eliciting an immune response in the host during candidiasis. Therefore, fungal secretomes can provide promising protein candidates for antifungal vaccine development. This study attempts to uncover the presence of immunodominant antigenic proteins in the C. glabrata secretome and delineate their role in various biological processes and their potency in the development of antifungal vaccines. LC–MS/MS results uncovered that C. glabrata secretome consisted of 583 proteins, among which 33 were identified as antigenic proteins. The protection ability of secretory proteins against hematogenously disseminated infection caused by C. glabrata was evaluated in BALB/c mice. After immunization and booster doses, all the animals were challenged with a lethal dose of C. glabrata. All the mice showing signs of distress were sacrificed post-infection, and target organs were collected, followed by histopathology and C. glabrata (CFU/mg) estimation. Our results showed a lower fungal burden in target organs and increased survival in immunized mice compared to the infection control group, thus revealing the immunogenic property of secreted proteins. Thus, identified secretome proteins of C. glabrata have the potential to act as antigenic proteins, which can serve as potential candidates for the development of antifungal vaccines. This study also emphasizes the importance of a mass-spectrometry approach to identifying the antigenic proteins in C. glabrata secretome.
Image Degradation Model for Dynamic Star Maps in Multiple Scenarios
Authors: Yang Haima , Jin Yan , Hu Yinan , Zhang Dawei , Yu Yong , Liu Jin , Li Jun , Jiang Xiaohui , Yu Xiaojun
Published: September 2022

To meet the ground test requirements of star sensors, we establish the star map simulation algorithm and the interactive interface in multiple scenarios. The combination of the degradation model of star points, the imaging noise model, and the attitude disturbance model is introduced to solve the problem of different patterns of noise existing in the actual measurement, improving the traditional simulation model. In addition, a user-friendly interface design makes it easier for both scholars and average individuals to understand the parameters and then generate static single-frame star maps—or a series of dynamic sequence star maps—under various conditions. The results of the proposed star map simulation method are highly comparable to the actual captured star images, and this method can be applied for the tests and calibrations of star sensors.
Evaluation of Improvements in the Separation of Monolayer and Multilayer Films via Measurements in Transflection and Application of Machine Learning Approaches
Authors: Koinig Gerald , Kuhn Nikolai , Barretta Chiara , Friedrich Karl , Vollprecht Daniel
Published: September 2022

Small plastic packaging films make up a quarter of all packaging waste generated annually in Austria. As many plastic packaging films are multilayered to give barrier properties and strength, this fraction is considered hardly recyclable and recovered thermally. Besides, they can not be separated from recyclable monolayer films using near-infrared spectroscopy in material recovery facilities. In this paper, an experimental sensor-based sorting setup is used to demonstrate the effect of adapting a near-infrared sorting rig to enable measurement in transflection. This adaptation effectively circumvents problems caused by low material thickness and improves the sorting success when separating monolayer and multilayer film materials. Additionally, machine learning approaches are discussed to separate monolayer and multilayer materials without requiring the near-infrared sorter to explicitly learn the material fingerprint of each possible combination of layered materials. Last, a fast Fourier transform is shown to reduce destructive interference overlaying the spectral information. Through this, it is possible to automatically find the Fourier component at which to place the filter to regain the most spectral information possible.
Variations in Microstructural and Physicochemical Properties of Soy Wax/Soybean Oil-Derived Oleogels Using Soy Lecithin
Authors: Sena Biswajit , Dhal Somali , Sahu Deblu , Sarkar Preetam , Mohanty Biswaranjan , Jarzębski Maciej , Wieruszewski Marek , Behera Haladhar , Pal Kunal
Published: September 2022

Emerging natural-based polymers and materials progress and new technology innovations open the way for unique food products with high nutritional value development. In this regard, oleogel may be essential in replacing fatty acids from food products. In this study, we researched the effects of varied soy lecithin (SYL) concentrations on the various physicochemical characteristics of soy wax (SW)/refined soybean oil (RSO) oleogels. These oleogels had a soft texture. The microscopic analysis of the oleogels suggested that the thickness, length, and density of the wax crystals (needle-shaped) varied as the SYL content was changed. Colorimetric analysis indicated that the oleogels were slightly yellowish. FTIR spectrometry helped analyze the functional groups of the raw materials and the oleogels. All the functional groups present in the raw materials could be accounted for within the oleogels. The only exception is the hydrogen-bonding peak in SW, which was not seen in the FTIR spectrum of the oleogels. It was found that at a critical SYL content, the oleogel showed a stable and repeatable wax network structure. This can be described by the presence of the uniformly distributed fat crystal network in the sample. The DSC analysis revealed that the oleogel samples were thermo-reversible, with their melting and crystallization temperatures ~43 °C and ~22 °C, respectively. In gist, it can be concluded that the incorporation of SYL can impact the color, wax crystal network characteristics, thermal characteristics, and mechanical characteristics of the oleogels in a composition-dependent manner.
Mechanical, Structural, and Biological Characteristics of Polylactide/Wollastonite 3D Printed Scaffolds
Authors: Choudhary Rajan , Bulygina Inna , Lvov Vladislav , Zimina Anna , Zhirnov Sergey , Kolesnikov Evgeny , Leybo Denis , Anisimova Natalya , Kiselevskiy Mikhail , Kirsanova Maria , Senatov Fedor
Published: September 2022

The present work aimed to study the synergistic response of bioresorbable polylactide/bioactive wollastonite scaffolds towards mechanical stability, mesenchymal stromal cell colonization, and antibacterial activity in the physiological environment. Wollastonite was synthesized at 800 °C within 2 h by sol-gel combustion method. The surface area was found to be 1.51 m2/g, and Transmission Electron Microscopy (TEM) micrographs indicated the presence of porous structures. Fused deposition modeling was used to prepare 3D-printed polylactide/wollastonite and polylactide/hydroxyapatite scaffolds. Scanning Electron Microscopy (SEM) micrographs confirmed the interconnected porous structure and complex geometry of the scaffolds. The addition of wollastonite decreased the contact angle of the scaffolds. The mechanical testing of scaffolds examined by computational simulation, as well as machine testing, revealed their non-load-bearing capacity. The chemical constituent of the scaffolds was found to influence the attachment response of different cells on their surface. The incorporation of wollastonite effectively reduced live bacterial attachment, whereas the colonization of mesenchymal cells was improved. This observation confirms polylactide/wollastonite scaffold possesses both bactericidal as well as cytocompatible properties. Thus, the risk of peri-implant bacterial film formation can be prevented, and the biological fixation of the scaffold at the defect site can be enhanced by utilizing these composites.
Synthesis of Novel Non-Isocyanate Polyurethane/Functionalized Boron Nitride Composites
Authors: El Khezraji Said , Chaib Manal , Thakur Suman , Raihane Mustapha , Lopez-Manchado Miguel A. , Verdejo Raquel , Lahcini Mohammed
Published: September 2022

Poly(hydroxyurethanes) (PHUs) have been suggested as isocyanate-free, low-toxicity alternatives to polyurethanes (PUs). However, PHUs present low mechanical properties due to the presence of side reactions that limit the production of high-molar mass polymers. Here, we present the synthesis under mild conditions and atmospheric pressure of bi-cyclic carbonate monomer for the production of PHU nanocomposites with good physical properties. The kinetics of the bi-cyclic carbonate synthesis and its complete conversion to urethane were followed by FTIR. The addition of functionalized boron nitrate (f-BN) with sucrose crystals improved the thermal degradation temperature as well as the glass transition by approximately 20 °C and 10 °C, respectively. The storage modulus of PHU films gradually increases with the concentration of f-BN in the composite.
Deforestation Detection in the Amazon Using DeepLabv3+ Semantic Segmentation Model Variants
Authors: de Andrade Renan Bides , Mota Guilherme Lucio Abelha , da Costa Gilson Alexandre Ostwald Pedro
Published: September 2022

The Amazon rainforest spreads across nine countries and covers nearly one-third of South America, being 69% inside Brazilian borders. It represents more than half of the remaining tropical forest on Earth and covers the catchment basin of the Amazon river on which 20% of the surface fresh water on the planet flows. Such an ecosystem produces large quantities of water vapor, helping regulate rainfall regimes in most of South America, with strong economic implications: for instance, by irrigating crops and pastures, and supplying water for the main hydroelectric plants in the continent. Being the natural habitat of one-tenth of the currently known species, the Amazon also has enormous biotechnological potential. Among the major menaces to the Amazon is the extension of agricultural and cattle farming, forest fires, illegal mining and logging, all directly associated with deforestation. Preserving the Amazon is obviously essential, and it is well-known that remote sensing provides effective tools for environmental monitoring. This work presents a deforestation detection approach based on the DeepLabv3+, a fully convolutional deep learning model devised for semantic segmentation. The proposed method extends the original DeepLabv3+ model, aiming at properly dealing with a strong class imbalanced problem and improving the delineation quality of deforestation polygons. Experiments were devised to evaluate the proposed method in terms of the sensitivity to the weighted focal loss hyperparameters—through an extensive grid search—and the amount of training data, and compared its performance to previous deep learning methods proposed for deforestation detection. Landsat OLI-8 images of a specific region in the Amazon were used in such evaluation. The results indicate that the variants of the proposed method outperformed previous works in terms of the F1-score and Precision metrics. Additionally, more substantial performance gains were observed in the context of smaller volumes of training data. When the evaluated methods were trained using four image tiles, the proposed method outperformed its counterparts by approximately +10% in terms of F1-score (from 63% to 73%); when the methods were trained with only one image tile, the performance difference in terms of F1-score achieved approximately +18% (from 49% to 67%).
A Comparison of Processing Schemes for Automotive MIMO SAR Imaging
Authors: Manzoni Marco , Tebaldini Stefano , Monti-Guarnieri Andrea Virgilio , Prati Claudio Maria , Russo Ivan
Published: September 2022

Synthetic Aperture Radar (SAR) imaging is starting to play an essential role in the automotive industry. Its day and night sensing capability, fine resolution, and high flexibility are key aspects making SAR a very compelling instrument in this field. This paper describes and compares three algorithms used to combine low-resolution images acquired by a Multiple-Input Multiple-Output (MIMO) automotive radar to form an SAR image of the environment. The first is the well-known Fast Factorized Back-Projection (FFBP), which focuses the image in different stages. The second one will be called 3D2D, and it is a simple 3D interpolation used to extract the SAR image from the Range-Angle-Velocity (RAV) data cube. The third will be called Quick&Dirty (Q&D), and it is a fast alternative to the 3D2D scheme that exploits the same intuition. A rigorous mathematical description of each algorithm is derived, and their limits are addressed. We then provide simulated results assessing different interpolation kernels, proving which one performs better. A rough estimation of the number of operations proves that both algorithms can be deployed using a real-time implementation. Finally, we will present some experimental results based on open road campaign data acquired using an eight-channel MIMO radar at 77 GHz, considering the case of a forward-looking geometry.
Partitionable High-Efficiency Multilayer Diffractive Optical Neural Network
Authors: Long Yongji , Wang Zirong , He Bin , Nie Ting , Zhang Xingxiang , Fu Tianjiao
Published: September 2022

A partitionable adaptive multilayer diffractive optical neural network is constructed to address setup issues in multilayer diffractive optical neural network systems and the difficulty of flexibly changing the number of layers and input data size. When the diffractive devices are partitioned properly, a multilayer diffractive optical neural network can be constructed quickly and flexibly without readjusting the optical path, and the number of optical devices, which increases linearly with the number of network layers, can be avoided while preventing the energy loss during propagation where the beam energy decays exponentially with the number of layers. This architecture can be extended to construct distinct optical neural networks for different diffraction devices in various spectral bands. The accuracy values of 89.1% and 81.0% are experimentally evaluated for MNIST database and MNIST fashion database and show that the classification performance of the proposed optical neural network reaches state-of-the-art levels.
Turning Movement Count Data Integration Methods for Intersection Analysis and Traffic Signal Design
Authors: Shokrolah Shirazi Mohammad , Chang Hung-Fu , Tayeb Shahab
Published: September 2022

Traffic simulation is widely used for modeling, planning, and analyzing different strategies for traffic control and road development in a cost-efficient manner. In order to perform an intersection simulation, random vehicle trip data are typically applied to an intersection network, making them unrealistic. In this paper, we address this issue by presenting two different methods of incorporating actual turning movement count (TMC) data and comparing their similarity for intersection simulation and analysis. The TMC of three intersections in Las Vegas are estimated separately for one hour using a developed vision-based tracking system and they are incorporated into Simulation of Urban MObility (SUMO) for estimating traffic measurements and traffic signal design. t-tests with a 95% confidence interval on the simulation variables demonstrate the importance of using a route-based creation method which injects vehicles into a simulation environment based on the frame-level departure time. The intersection analyses and comparisons are performed based on estimated traffic measurements such as travel time, density, lane density, occupancy, and normalized waiting time. Since the critical edge of each intersection network is identified based on a higher normalized waiting time, new traffic signal designs are suggested based on the actual critical turning movements and improvements in vehicle travel time are achieved to better accommodate the actual traffic demand.
Self-Optimizing Traffic Steering for 5G mmWave Heterogeneous Networks
Authors: Zeng Jun , Wang Hao , Luo Wei
Published: September 2022

Driven by growing mobile traffic, millimeter wave (mmWave) communications have recently been developed to enhance wireless network capacity. Due to insufficient coverage and the lack of support for mobility, mmWave is often deployed in the ultra-dense small cells of the 5G heterogeneous network. In this article, we first summarize the characteristics of the 5G heterogeneous network from the viewpoints of devices, spectra, and networks. We then propose a triple-band network structure which incorporates licensed bands, sub-6GHz unlicensed bands, and mmWave bands to support various types of mobile users. Based on the novel network structure, we further propose a self-optimizing traffic steering strategy which can intelligently steer traffic to specific networks and spectra according to the dynamic network and traffic environments. Several use cases are also discussed to facilitate the implementation of our proposals. Finally, we present numerical results to demonstrate that the proposed network structure and strategy can effectively enhance the system throughput and energy efficiency.
Vision-Sensor-Assisted Probabilistic Localization Method for Indoor Environment
Authors: Shi Hui , Yang Jianyu , Shi Jiashun , Zhu Lida , Wang Guofa
Published: September 2022

Among the numerous indoor localization methods, Light-Detection-and-Ranging (LiDAR)-based probabilistic algorithms have been extensively applied to indoor localization due to their real-time performance and high accuracy. Nevertheless, these methods are challenged in symmetrical environments when tackling global localization and the robot kidnapping problem. In this paper, a novel hybrid method that combines visual and probabilistic localization results is proposed. Augmented Monte Carlo Localization (AMCL) is improved for position tracking continually. LiDAR-based measurements’ uncertainty is evaluated to incorporate discrete visual-based results; therefore, a better diversity of the particle can be maintained. The robot kidnapping problem can be detected and solved by preventing premature convergence of the particle filter. Extensive experiments were implemented to validate the robustness and accuracy performance. Meanwhile, the localization error was reduced from 30 mm to 9 mm during a 600 m tour.
AI Based Digital Twin Model for Cattle Caring
Authors: Han Xue , Lin Zihuai , Clark Cameron , Vucetic Branka , Lomax Sabrina
Published: September 2022

In this paper, we develop innovative digital twins of cattle status that are powered by artificial intelligence (AI). The work is built on a farm IoT system that remotely monitors and tracks the state of cattle. A digital twin model of cattle based on Deep Learning (DL) is generated using the sensor data acquired from the farm IoT system. The physiological cycle of cattle can be monitored in real time, and the state of the next physiological cycle of cattle can be anticipated using this model. The basis of this work is the vast amount of data that is required to validate the legitimacy of the digital twins model. In terms of behavioural state, this digital twin model has high accuracy, and the loss error of training reach about 0.580 and the loss error of predicting the next behaviour state of cattle is about 5.197 after optimization. The digital twins model developed in this work can be used to forecast the cattle’s future time budget.
The Effect of Fractionation during the Vacuum Deposition of Stabilized Amorphous Selenium Alloy Photoconductors on the Overall Charge Collection Efficiency
Authors: Kasap Safa
Published: September 2022

The general fabrication process for stabilized amorphous selenium (a-Se) detectors is vacuum deposition. The evaporant alloy is typically selenium alloyed with 0.3–0.5%As to stabilize it against crystallization. During the evaporation, fractionation leads to the formation of a deposited film that is rich in As near the surface and rich in Se near the substrate. The As content is invariably not uniform across the film thickness. This paper examines the effect of non-uniform As content on the charge collection efficiency (CE). The model for the actual CE calculation is based on the generalized CE equation under small signals; it involves the integration of the reciprocal range-field product (the schubweg) and the photogeneration profile. The data for the model input were extracted from the literature on the dependence of charge carrier drift mobilities and lifetimes on the As content in a-Se1−xAsx alloys to generate the spatial variation of hole and electron ranges across the photoconductor film. This range variation is then used to calculate the actual CE in the integral equation as a function of the applied field. The carrier ranges corresponding to the average composition in the film are also used in the standard CE equation under uniform ranges to examine whether one can simply use the average As content to calculate the CE. The standard equation is also used with ranges from the spatial average and average inverse. Errors are then compared and quantified from the use of various averages. The particular choice for averaging depends on the polarity of the radiation-receiving electrode and the spatial variation of the carrier ranges.