bluuebunny/crossref_metadata_2025 huggingface dataset:
The Gut Microbial Metabolite Pyrogallol Is a More Potent Inducer of Nrf2-Associated Gene Expression Than Its Parent Compound Green Tea (-)-Epigallocatechin Gallate
Authors: Liu Chen , Boeren Sjef , Miro Estruch Ignacio , Rietjens Ivonne M. C. M.
Published: August 2022

(-)-Epigallocatechin gallate (EGCG) has been associated with multiple beneficial effects. However, EGCG is known to be degraded by the gut microbiota. The present study investigated the hypothesis that microbial metabolism would create major catechol-moiety-containing microbial metabolites with different ability from EGCG to induce nuclear factor-erythroid 2-related factor 2 (Nrf2)-mediated gene expression. A reporter gene bioassay, label-free quantitative proteomics and reverse transcription quantitative real-time polymerase chain reaction (RT-qPCR) were combined to investigate the regulation of Nrf2-related gene expression after exposure of U2OS reporter gene or Hepa1c1c7 cells in vitro to EGCG or to its major microbial catechol-moiety-containing metabolites: (-)-epigallocatechin (EGC), gallic acid (GA) and pyrogallol (PG). Results show that PG was a more potent inducer of Nrf2-mediated gene expression than EGCG, with a 5% benchmark dose (BMD5) of 0.35 µM as compared to 2.45 µM for EGCG in the reporter gene assay. EGC and GA were unable to induce Nrf2-mediated gene expression up to the highest concentration tested (75 µM). Bioinformatical analysis of the proteomics data indicated that Nrf2 induction by PG relates to glutathione metabolism, drug and/or xenobiotics metabolism and the pentose phosphate pathway. Taken together, our findings demonstrate that the microbial metabolite PG is a more potent inducer of Nrf2-associated gene expression than its parent compound EGCG.
Potential of Egg as Complementary Food to Improve Nutrient Intake and Dietary Diversity
Authors: Faber Mieke , Malan Linda , Kruger Herculina S. , Asare Hannah , Visser Marina , Mukwevho Tshiphiri , Ricci Cristian , Smuts Cornelius M.
Published: August 2022

The original aim was to determine the effect of egg consumption on infant growth in a low socioeconomic community in South Africa in a randomized controlled trial. Enrolment was, however, prematurely stopped due to COVID-19 lockdown regulations. The resultant small sample (egg group n = 70; control group n = 85) was followed up to assess the feasibility of egg consumption for eight months in terms of dietary intake, egg usage and perceived effects of lockdown on child feeding. Egg consumption remained low in the control group, <10% consumed egg ≥4 days/week at the follow-up points. In the egg group, egg was frequently consumed at midpoint (daily 87.1%, 4–6 days 8.1%) and endpoint (daily 53.1%, 4–6 days 21.9%). At endpoint, dietary intake of cholesterol and vitamin D was higher, and intake of niacin and vitamin B6 lower in the egg group compared to the control group. Dietary diversity was low, 36.2% of the egg group and 18.9% of the control group (p < 0.05) achieved minimum dietary diversity at endpoint. No babies developed egg allergy or sensitization, and adjusted regression analysis showed that frequency of egg intake was not related with the incidence or duration of allergy-related symptoms. This study showed that frequent egg consumption can contribute safely to complementary food for babies, especially in low- and middle-income countries.
Incidence, Risk Factors and Prediction of Secondary Hyperparathyroidism in Preterm Neonates under 32 Weeks’ Gestational Age
Authors: Avila-Alvarez Alejandro , Perez Tato Helena , Sucasas Alonso Andrea , Prado Carro Ana , Fuentes Carballal Jesus
Published: August 2022

In preterm newborns, secondary hyperparathyroidism (HPTH) is an underdiagnosed and undertreated entity. Its detection in the context of metabolic bone mineral disease (MBD) screening programs may be important to guide nutritional treatment. We designed a retrospective cohort study to determine the incidence of HPTH in very premature infants. As secondary objectives, we studied the risk factors, morbidities, and biochemical alterations associated with HPTH. A total of 154 preterm newborns ≤32 weeks gestational age (GA) were included. Of these, 40.3% (n = 62) presented with HPTH. In the multivariate analysis, independent risk factors for HPTH were cesarean section (OR: 4.00; 95% CI: 1.59–10.06), oxygen during resuscitation (OR: 3.43; 95% CI: 1.09–10.81), invasive mechanical ventilation (OR: 3.56; 95% CI: 1.63–7.77) and anemia requiring transfusion (OR: 2.37; 95% CI: 1.01–5.57). Among the analytical variables, serum calcium (OR: 0.53; 95% CI: 0.29–0.97), serum phosphate (OR: 2.01; 95% CI: 1.39–2.92), vitamin D (OR: 0.96; 95% CI: 0.93–1), and the calcium/creatinine ratio in urine (OR: 0.05; 95% CI: 0.01–0.28) were independently associated with HPTH. The simplified predictive model included GA and calcium/creatinine ratio in urine and demonstrated an AUC of 0.828. We concluded that HPTH is a frequent entity among very premature infants and that further studies are required to determine the role of HPTH in MBD and the clinical applicability of prediction models.
Effects of Caffeine on Performances of Simulated Match, Wingate Anaerobic Test, and Cognitive Function Test of Elite Taekwondo Athletes in Hong Kong
Authors: Sun Fenghua , Siu Agatha Yi-Sum , Wang Kangle , Zhang Borui , Chan Man-Him , Chan Ka-Hon , Kong Pui-Sze , Man Kei-Yee , Chow Gary Chi-Ching
Published: August 2022

This study aimed to investigate the effects of caffeine on performances of simulated match, Wingate Anaerobic Test (WAnT), and cognitive function test of elite taekwondo athletes. Ten elite taekwondo athletes in Hong Kong volunteered to participate in two main trials in a randomized double-blinded crossover design. In each main trial, 1 h after consuming a drink with caffeine (CAF) or a placebo drink without caffeine (PLA), the participants completed two simulated taekwondo match sessions followed by the WAnT. The participants were instructed to complete three cognitive function tests, namely the Eriksen Flanker Test (EFT), Stroop Test, and Rapid Visual Information Processing Test, at baseline, before exercise, and immediately after the simulated matches. They were also required to wear functional near-infrared spectroscopy equipment during these tests. Before exercise, the reaction time in the EFT was shorter in the CAF trial than in the PLA trial (PLA: 494.9 ± 49.2 ms vs. CAF: 467.9 ± 38.0 ms, p = 0.035). In the WAnT, caffeine intake increased the peak power and mean power per unit of body weight (by approximately 13% and 6%, respectively, p = 0.018 & 0.042). The performance in the simulated matches was not affected by caffeine intake (p = 0.168). In conclusion, caffeine intake enhances anaerobic power and may improve certain cognitive functions of elite taekwondo athletes in Hong Kong. However, this may not be enough to improve the simulated match performance.
Role of Vitamin K in Selected Malignant Neoplasms in Women
Authors: Markowska Anna , Antoszczak Michał , Markowska Janina , Huczyński Adam
Published: August 2022

The main function of vitamin K in the human organism is its activity in the blood clotting cascade. Epidemiological studies suggest that reduced intake of vitamin K may contribute to an increased risk of geriatric diseases such as atherosclerosis, dementia, osteoporosis, and osteoarthritis. A growing number of studies also indicate that vitamin K may be involved not only in preventing the development of certain cancers but it may also support classical cancer chemotherapy. This review article summarizes the results of studies on the anticancer effects of vitamin K on selected female malignancies, i.e., breast, cervical, and ovarian cancer, published over the past 20 years. The promising effects of vitamin K on cancer cells observed so far indicate its great potential, but also the need for expansion of our knowledge in this area by conducting extensive research, including clinical trials.
Potential Pharmaceutical Applications of Quercetin in Cardiovascular Diseases
Authors: Papakyriakopoulou Paraskevi , Velidakis Nikolaos , Khattab Elina , Valsami Georgia , Korakianitis Ioannis , Kadoglou Nikolaos PE
Published: August 2022

Quercetin, as a member of flavonoids, has emerged as a potential therapeutic agent in cardiovascular diseases (CVDs) in recent decades. In this comprehensive literature review, our goal was a critical appraisal of the pathophysiological mechanisms of quercetin in relation to the classical cardiovascular risk factors (e.g., hyperlipidemia), atherosclerosis, etc. We also assessed experimental and clinical data about its potential application in CVDs. Experimental studies including both in vitro methods and in vivo animal models mainly outline the following effects of quercetin: (1) antihypertensive, (2) hypolipidemic, (3) hypoglycemic, (4) anti-atherosclerotic, and (5) cardioprotective (suppressed cardiotoxicity). From the clinical point of view, there are human studies and meta-analyses implicating its beneficial effects on glycemic and lipid parameters. In contrast, other human studies failed to demonstrate consistent favorable effects of quercetin on other cardiometabolic risk factors such as MS, obesity, and hypertension, underlying the need for further investigation. Analyzing the reason of this inconsistency, we identified significant drawbacks in the clinical trials’ design, while the absence of pharmacokinetic/pharmacodynamic tests prior to the studies attenuated the power of clinical results. Therefore, additional well-designed preclinical and clinical studies are required to examine the therapeutic mechanisms and clinical efficacy of quercetin in CVDs.
A Versatile Class of 1,4,4-Trisubstituted Piperidines Block Coronavirus Replication In Vitro
Authors: De Castro Sonia , Stevaert Annelies , Maldonado Miguel , Delpal Adrien , Vandeput Julie , Van Loy Benjamin , Eydoux Cecilia , Guillemot Jean-Claude , Decroly Etienne , Gago Federico , Canard Bruno , Camarasa Maria-Jose , Velázquez Sonsoles , Naesens Lieve
Published: August 2022

There is a clear need for novel antiviral concepts to control SARS-CoV-2 infection. Based on the promising anti-coronavirus activity observed for a class of 1,4,4-trisubstituted piperidines, we here conducted a detailed analysis of the structure–activity relationship of these structurally unique inhibitors. Despite the presence of five points of diversity, the synthesis of an extensive series of analogues was readily achieved by Ugi four-component reaction from commercially available reagents. After evaluating 63 analogues against human coronavirus 229E, four of the best molecules were selected and shown to have micromolar activity against SARS-CoV-2. Since the action point was situated post virus entry and lying at the stage of viral polyprotein processing and the start of RNA synthesis, enzymatic assays were performed with CoV proteins involved in these processes. While no inhibition was observed for SARS-CoV-2 nsp12-nsp7-nsp8 polymerase, nsp14 N7-methyltransferase and nsp16/nsp10 2’-O-methyltransferase, nor the nsp3 papain-like protease, the compounds clearly inhibited the nsp5 main protease (Mpro). Although the inhibitory activity was quite modest, the plausibility of binding to the catalytic site of Mpro was established by in silico studies. Therefore, the 1,4,4-trisubstituted piperidines appear to represent a novel class of non-covalent CoV Mpro inhibitors that warrants further optimization and development.
Redox-Responsive Polymersomes as Smart Doxorubicin Delivery Systems
Authors: Ferrero Carmen , Casas Marta , Caraballo Isidoro
Published: August 2022

Stimuli-responsive polymersomes have emerged as smart drug delivery systems for programmed release of highly cytotoxic anticancer agents such as doxorubicin hydrochloride (Dox·HCl). Recently, a biodegradable redox-responsive triblock copolymer (mPEG–PDH–mPEG) was synthesized with a central hydrophobic block containing disulfide linkages and two hydrophilic segments of poly(ethylene glycol) methyl ether. Taking advantage of the self-assembly of this amphiphilic copolymer in aqueous solution, in the present investigation we introduce a solvent-exchange method that simultaneously achieves polymersome formation and drug loading in phosphate buffer saline (10 mM, pH 7.4). Blank and drug-loaded polymersomes (5 and 10 wt.% feeding ratios) were prepared and characterized for morphology, particle size, surface charge, encapsulation efficiency and drug release behavior. Spherical vesicles of uniform size (120–190 nm) and negative zeta potentials were obtained. Dox·HCl was encapsulated into polymersomes with a remarkably high efficiency (up to 98 wt.%). In vitro drug release studies demonstrated a prolonged and diffusion-driven release at physiological conditions (~34% after 48 h). Cleavage of the disulfide bonds in the presence of 50 mM glutathione (GSH) enhanced drug release (~77%) due to the contribution of the erosion mechanism. Therefore, the designed polymersomes are promising candidates for selective drug release in the reductive environment of cancer cells.
In Vitro Models of the Blood–Cerebrospinal Fluid Barrier and Their Applications in the Development and Research of (Neuro)Pharmaceuticals
Authors: Dabbagh Fatemeh , Schroten Horst , Schwerk Christian
Published: August 2022

The pharmaceutical research sector has been facing the challenge of neurotherapeutics development and its inherited high-risk and high-failure-rate nature for decades. This hurdle is partly attributable to the presence of brain barriers, considered both as obstacles and opportunities for the entry of drug substances. The blood–cerebrospinal fluid (CSF) barrier (BCSFB), an under-studied brain barrier site compared to the blood–brain barrier (BBB), can be considered a potential therapeutic target to improve the delivery of CNS therapeutics and provide brain protection measures. Therefore, leveraging robust and authentic in vitro models of the BCSFB can diminish the time and effort spent on unproductive or redundant development activities by a preliminary assessment of the desired physiochemical behavior of an agent toward this barrier. To this end, the current review summarizes the efforts and progresses made to this research area with a notable focus on the attribution of these models and applied techniques to the pharmaceutical sector and the development of neuropharmacological therapeutics and diagnostics. A survey of available in vitro models, with their advantages and limitations and cell lines in hand will be provided, followed by highlighting the potential applications of such models in the (neuro)therapeutics discovery and development pipelines.
Quantitative Evaluation of the Phase Function Effects on Light Scattering and Radiative Transfer in Dispersed Systems
Authors: Ma Lanxin , Hu Lechuan , Jia Chengwei , Wang Chengchao , Liu Linhua
Published: August 2022

The light scattering properties of particles play important roles in radiative transfer in many dispersed systems, such as turbid atmosphere, ocean water, nanofluids, composite coatings and so on. As one of the scattering property parameters, the scattering phase functions of particles are strongly dependent on the particle size, size distribution, and morphology, as well as on the complex refractive indices of the particles and surrounding media. For the sake of simplicity, the empirical phase function models are widely used in many practical applications. In this work, we focus on the radiative transfer problem in dispersed systems composed of spherical particles, and give quantitative analyses of the impact of scattering phase functions on the radiative transfer process. We fit the scattering phase functions of four different types of practical dispersed systems using four previously proposed empirical phase function models, including the Henyey–Greenstein (HG) model, Cornette Shanks (CS) model, Reynold and McCormick (RM) model and two-term Reynolds–McCormick (TTRM) model. By comparing the radiative transfer characteristics (i.e., hemispherical reflectance, hemispherical transmittance and total absorptance) of dispersed layers calculated using the Monte Carlo method, the relative errors caused by using the empirical phase functions are systematically investigated. The results demonstrate that the HG, CS and RM models cause obvious errors in the calculation of hemispherical reflectance in many cases. Meanwhile, the induced errors show no obvious regularity, but are related to the particle size and layer optical thickness. Due to the good fitting effect in both forward and backward directions, the TTRM model provides significantly higher performances in fitting the phase functions of all considered cases than the widely used single-term parametrizations. Moreover, for different particle sizes and layer optical thicknesses, the induced errors of the TTRM model in radiative transfer characteristics are very small, especially for the case of polydisperse particles. Our results can be used to guide the design, analysis and optimization of dispersed systems in practical optics and photonics applications.
Intracranial In Situ Thermosensitive Hydrogel Delivery of Temozolomide Accomplished by PLGA–PEG–PLGA Triblock Copolymer Blending for GBM Treatment
Authors: Gu Weinan , Fan Ranran , Quan Jingnan , Cheng Yi , Wang Shanshan , Zhang Hui , Zheng Aiping , Song Shenghan
Published: August 2022

Glioblastoma (GBM) recurrence after surgical excision has grown to be a formidable obstacle to conquer. In this research, biodegradable thermosensitive triblock copolymer, poly(D, L–lactic acid–co–glycolic acid)–b–poly(ethylene glycol)–b–poly(D, L–lactic acid–co–glycolic acid (PLGA–PEG–PLGA) was utilized as the drug delivery system, loading with micronized temozolomide(micro-TMZ) to form an in situ drug–gel depot inside the resection cavity. The rheology studies revealed the viscoelastic profile of hydrogel under various conditions. To examine the molecular characteristics that affect gelation temperature, 1H–NMR, inverse gated decoupling 13C–NMR, and GPC were utilized. Cryo-SEM and XRD were intended to disclose the appearance of the hydrogel and the micro-TMZ existence state. We worked out how to blend polymers to modify the gelation point (Tgel) and fit the correlation between Tgel and other dependent variables using linear regression. To simulate hydrogel dissolution in cerebrospinal fluid, a membraneless dissolution approach was used. In vitro, micro-TMZ@PLGA–PEG–PLGA hydrogel exhibited Korsmeyer–Peppas and zero–order release kinetics in response to varying drug loading, and in vivo, it suppressed GBM recurrence at an astoundingly high rate. Micro-TMZ@PLGA–PEG–PLGA demonstrates a safer and more effective form of chemotherapy than intraperitoneal TMZ injection, resulting in a spectacular survival rate (40%, n = 10) that is much more than intraperitoneal TMZ injection (22%, n = 9). By proving the viability and efficacy of micro-TMZ@PLGA–PEG–PLGA hydrogel, our research established a novel chemotherapeutic strategy for treating GBM recurrence.
Thermal Stability, Mechanical Properties and Ceramization Mechanism of Epoxy Resin/Kaolin/Quartz Fiber Ceramifiable Composites
Authors: Xue Chenyi , Qin Yan , Fu Huadong , Fan Jiamin
Published: August 2022

The application of epoxy resins in high temperature and thermal protection fields is limited due to their low decomposition temperature and low carbon residual rate. In this paper, epoxy resin (EP)/quartz fiber (QF) ceramifiable composites were prepared using a prepreg-molding process. The thermal stability, phase change and mechanical properties after high-temperature static ablation and ceramization mechanism of EP/QF ceramifiable composites were investigated. The addition of glass frits and kaolinite ceramic filler dramatically increases the thermal stability of the composites, according to thermogravimetric (TG) studies. The composite has a maximum residual weight of 61.08%. The X-ray diffraction (XRD) results show that the mullite ceramic phase is generated, and a strong quartz diffraction peak appears at 1000 °C. The scanning electron microscope (SEM) and element distribution analyses reveal that the ceramic phase generated inside the material, when the temperature reaches 1000 °C, effectively fills the voids in composites. The composites have a bending strength of 175.37 MPa at room temperature and retain a maximum bending strength of 12.89 MPa after 1000 °C treatment.
The Influence of Flame Retardants on Combustion of Glass Fiber-Reinforced Epoxy Resin
Authors: Korobeinichev Oleg , Shaklein Artem , Trubachev Stanislav , Karpov Alexander , Paletsky Alexander , Chernov Anatoliy , Sosnin Egor , Shmakov Andrey
Published: August 2022

For the first time, next to the flammability tests (LOI, UL-94 HB, VBB, TGA), experimental tests and computer simulation have been conducted on the flame spread and combustion of glass fiber-reinforced epoxy resins (GFRER) with 6% graphene and 6% DDM-DOPO flame-retardant additives. The downward rates of flame spread (ROS) in opposed flow with oxidizer and the upward ROS along GFRER composites have been first measured as well as the distribution of temperature over the combustion surface of the composites with flame-retardant additives and without them. The LOI and UL-94 HB tests showed a reduction in the flammability of GFRER when flame retardants were added and predicted a higher effectiveness of DDM-DOPO compared to graphene. Adding DDM-DOPO resulted in increasing the rate of formation of the volatile pyrolysis products and their yield, indicating, together with the other data obtained, the gas phase mechanism of the flame retardant’s action. Adding graphene resulted in an increase in the soot release on the burning surface and an increase in the amount of non-volatile pyrolysis products on the burning surface, reducing the amount of fuel that participated in the oxidation reactions in the gas phase. The developed numerical combustion model for GFRER with a DDM-DOPO additive, based on the action of DDM-DOPO as a flame retardant acting in the gas phase, satisfactorily predicts the effect of this flame retardant on the reduction in downward ROS over GFRER for 45–50% oxygen concentrations. The developed model for GFRER with graphene additive, based on a reduction in the amount of fuel and increase in the amount of incombustible volatile pyrolysis products when graphene is added, predicts with good accuracy downward ROS over GFRER depending on oxygen concentration.
The Effect of Changes in Settings from Multiple Filling Points to a Single Filling Point of an Industry 4.0-Based Yogurt Filling Machine
Authors: Chen Jinping , Khan Razaullah , Cui Yanmei , Salah Bashir , Liu Yuanpeng , Saleem Waqas
Published: August 2022

In process optimization, a process is adjusted so as to optimize a set of parameters while meeting constraints, with the objective to either minimize the total processing time or maximize the throughput. This article focused on the process optimization of a fully automated yogurt and flavor-filling machine developed based on the industrial revolution 4.0 concept. Mathematical models were developed for minimizing the total processing time or maximizing the throughput of an Industry 4.0-based yogurt filling system with two different machine settings called Case-I and Case-II. In Case-I, the yogurt and flavors are filled at two distinct points while Case-II considers the filling of yogurt and flavors at a single point. The models were tested with real data and the results revealed that Case-II is faster than Case-I in processing a set of customer orders. The results were used as inputs for the single-dimension rules to check which one results in more intended outputs. Additionally, different performance measures were considered and the one with most importance to the management was selected.
Myths of Brotherly Animosity and the Civil Wars of Biblical Israel
Authors: Zohar Diklah
Published: August 2022

A recurrent theme in the Hebrew Bible is brotherly animosity. Cain and Abel, Jacob and Esau, and Solomon and Adonijah are but a few examples. This variety seems to reflect a fundamental conflict in ancient society. In this article, I argue that all these stories function as ethos myths. After describing the various stories with an attempt to single out the motivations behind them, they will be put into the social context that probably fueled them. Although the stories are extremely varied, they all share at least one common element, namely: it is always the younger brother who turns out to be God’s favorite. A second element is the jealousy of the older brother in the special status of the younger. Against the historical background of long-lasting civil war between the smaller kingdom of Judah and the larger, militarily stronger, and more financially stable kingdom of Israel, I argue that these stories were adapted to fit into the Judean narrative for the sake of strengthening its self-image as a small kingdom struggling against a stronger opponent who is motivated by jealousy. The mythical conflict reflects the complexity of the struggle between the two kingdoms, in which Judah identifies itself as being the ‘younger child’ or the ‘little brother’, who is blessed by God. Such myths give justification to the military struggle and feed the self-conviction narratives of the superiority of Judah as being divinely chosen.
Integration of Vertical and Horizontal Deformation Derived by SAR Observation for Identifying Landslide Motion Patterns in a Basaltic Weathered Crust Region of Guizhou, China
Authors: Zhu Yifei , Yao Xin , Yao Chuangchuang , Zhou Zhenkai , Gu Zhenkui , Yao Leihua
Published: August 2022

In recent years, due to adverse geological conditions, intense human engineering activities, and extreme weather conditions, catastrophic landslides have frequently occurred in southwest China, causing severe loss of life and property. Identifying the kinematic features of potential landslides can effectively support landslide hazard prevention. This study proposes a remote sensing identification method for rotational, planar traction, and planar thrust slides based on geomorphic features as well as vertical and slope-oriented deformation rates. Rotational landslides are characterized by similar vertical and horizontal deformation rates, with vertical deformation mainly occurring at the head and gradually decreasing along the slope, while horizontal deformation mainly occurs at the foot and gradually increases along the slope. As for the planar slide, the dominant deformation is in the horizontal direction. It is further classified into the planar traction and planar thrust types according to the driving position. The vertical deformation of planar traction slides is concentrated at the foot, while the vertical deformation of planar thrust slides is concentrated at the head of the landslide. We identified 1 rotational landslide, 10 planar traction landslides and 10 planar thrust landslides in the basalt weathering crust area of Guizhou. Field investigations of three landslides verified the method’s accuracy. Combining two-dimensional rainfall and time-series deformations, we found that there is a significant positive correlation between landslide deformation acceleration and precipitation. The landslide kinematic identification method proposed in this paper overcomes the shortcomings of the inability to accurately characterize landslide motion by line-of-sight displacement and realizes the non-contact identification of active landslide motion patterns, which is an essential reference value for geological disaster prevention and control in the study area.
Thermal Contribution of the Local Climate Zone and Its Spatial Distribution Effect on Land Surface Temperature in Different Macroclimate Cities
Authors: Li Ninglv , Wang Bin , Yao Yang , Chen Liding , Zhang Zhiming
Published: August 2022

Local climate zones (LCZs) provide a comprehensive framework to examine surface urban heat islands (SUHIs), but information is lacking on their thermal contributions and spatial effects in different macroclimate cities. A standard framework for distinguishing between the cooling effect and heating effect and spatial effect analysis based on the LCZ scheme was conducted in five distinct macroclimate cities, i.e., Yuanjiang (arid climate), Jinghong (tropical climate), Kunming (subtropical climate), Zhaotong (temperate climate), and Shangri-La (alpine climate). The results indicated that (1) built-up zones presented heating effects in Jinghong and Shangri-La, but opposite results were observed in Yuanjiang and Zhaotong. (2) The thermal contributions of natural zones with dense trees (LCZAs) and waterbodies (LCZGs) showed cooling effects in the five cities regardless of season. (3) The spatial effect of heating LCZs on land surface temperature (LST) was more significant than that of cooling LCZs in Jinghong and Shangri-La, but the opposite results occurred in Yuanjiang and Kunming. Moreover, the spatial effect was lower in Zhaotong than in other cities. (4) Lower LST differences between natural zones and built-up zones in winter than in summer decreased the spatial effects. In summary, the thermal contributions of LCZs and their spatial heating/cooling effects were different among five distinct climate backgrounds, which implies that targeted measures must be used in different macroclimates.
Recovering Regional Groundwater Storage Anomalies by Combining GNSS and Surface Mass Load Data: A Case Study in Western Yunnan
Authors: Xu Pengfei , Jiang Tao , Zhang Chuanyin , Shi Ke , Li Wanqiu
Published: August 2022

The redistribution of surface mass (e.g., atmosphere, soil water, oceans, and groundwater) can cause load responses, resulting in vertical deformations of the crust. Indeed, the global navigation satellite system (GNSS)-based continuously operating reference stations (CORS) are able to accurately measure the vertical deformation caused by surface mass loads. In this study, the CORS was used to invert groundwater storage anomalies (GWSA), represented by the equivalent water height (EWH), after removing the effect of the non-groundwater surface mass load (atmospheric, groundwater, and non-tidal oceanic loads) from the vertical deformation monitored by CORS. In addition, the global and regional high-resolution surface mass models were combined to calculate the high-precision load deformation field in in western Yunnan using the remove–restore method, thereby obtaining more accurate surface mass load data and improving the accuracy of the inverted GWSA results. In order to assess the feasibility of the CORS inversion for the GWSA used, 66 CORS stations in western Yunnan Province were considered, presenting weekly GWSA data from 10 January 2018 to 31 December 2020. The results revealed significant seasonal variation in GWSA in the study area, showing an amplitude range of −200–200 mm. This approach is based on the already-established CORS network without requiring additional set-up costs. In addition, the reliability of CORS inverse results was assessed using Gravity Recovery and Climate Experiment (GRACE) inverse results and actual groundwater monitoring data. According to the obtained results, GWSA can be monitored by both CORS and GRACE data; however, CORS provided a more effective spatiotemporal resolution of GWSA. Therefore, the CORS network combined with surface mass load data is able to effectively monitor the spatiotemporal dynamics of GWSA in small-scale areas and provides important references for the study of hydrology.
Automatic Detection and Assessment of Pavement Marking Defects with Street View Imagery at the City Scale
Authors: Kong Wanyue , Zhong Teng , Mai Xin , Zhang Shuliang , Chen Min , Lv Guonian
Published: August 2022

Pavement markings could wear out before their expected service life expires, causing traffic safety hazards. However, assessing pavement-marking conditions at the city scale was a great challenge in previous studies. In this article, we advance the method of detecting and evaluating pavement-marking defects at the city scale with Baidu Street View (BSV) images, using a case study in Nanjing. Specifically, we employ inverse perspective mapping (IPM) and a deep learning-based approach to pavement-marking extraction to make efficient use of street-view imageries. In addition, we propose an evaluation system to assess three types of pavement-marking defects, with quantitative and qualitative results provided for each image. Factors causing pavement-marking defects are discussed by mapping the spatial distribution of pavement-marking defects at the city scale. Our proposed methods are conducive to pavement-marking repair operations. Beyond this, this article can contribute to smart urbanism development by creating a new road maintenance solution and ensuring the large-scale realization of intelligent decision-making in urban infrastructure management.
Nature-Inspired Search Method and Custom Waste Object Detection and Classification Model for Smart Waste Bin
Authors: Agbehadji Israel Edem , Abayomi Abdultaofeek , Bui Khac-Hoai Nam , Millham Richard C. , Freeman Emmanuel
Published: August 2022

Waste management is one of the challenges facing countries globally, leading to the need for innovative ways to design and operationalize smart waste bins for effective waste collection and management. The inability of extant waste bins to facilitate sorting of solid waste at the point of collection and the attendant impact on waste management process is the motivation for this study. The South African University of Technology (SAUoT) is used as a case study because solid waste management is an aspect where SAUoT is exerting an impact by leveraging emerging technologies. In this article, a convolutional neural network (CNN) based model called You-Only-Look-Once (YOLO) is employed as the object detection algorithm to facilitate the classification of waste according to various categories at the point of waste collection. Additionally, a nature-inspired search method is used as learning rate for the CNN model. The custom YOLO model was developed for waste object detection, trained with different weights and backbones, namely darknet53.conv.74, darknet19_448.conv.23, Yolov4.conv.137 and Yolov4-tiny.conv.29, respectively, for Yolov3, Yolov3-tiny, Yolov4 and Yolov4-tiny models. Eight (8) classes of waste and a total of 3171 waste images are used. The performance of YOLO models is considered in terms of accuracy of prediction (Average Precision—AP) and speed of prediction measured in milliseconds. A lower loss value out of a percentage shows a higher performance of prediction and a lower value on speed of prediction. The results of the experiment show that Yolov3 has better accuracy of prediction as compared with Yolov3-tiny, Yolov4 and Yolov4-tiny. Although the Yolov3-tiny is quick at predicting waste objects, the accuracy of its prediction is limited. The mean AP (%) for each trained version of YOLO models is Yolov3 (80%), Yolov4-tiny (74%), Yolov3-tiny (57%) and Yolov4 (41%). This result of mAP (%) indicates that the Yolov3 model produces the best performance results (80%). In this regard, it is useful to implement a model that ensures accurate prediction to develop a smart waste bin system at the institution. The experimental results show the combination of KSA learning rate parameter of 0.0007 and Yolov3 is identified as the accurate model for waste object detection and classification. The use of nature-inspired search methods, such as the Kestrel-based Search Algorithm (KSA), has shown future prospect in terms of learning rate parameter determination in waste object detection and classification. Consequently, it is imperative for an EdgeIoT-enabled system to be equipped with Yolov3 for waste object detection and classification, thereby facilitating effective waste collection.
Improved Algorithm for Insulator and Its Defect Detection Based on YOLOX
Authors: Han Gujing , Li Tao , Li Qiang , Zhao Feng , Zhang Min , Wang Ruijie , Yuan Qiwei , Liu Kaipei , Qin Liang
Published: August 2022

Aerial insulator defect images have some features. For instance, the complex background and small target of defects would make it difficult to detect insulator defects quickly and accurately. To solve the problem of low accuracy of insulator defect detection, this paper concerns the shortcomings of IoU and the sensitivity of small targets to the model regression accuracy. An improved SIoU loss function was proposed based on the regular influence of regression direction on the accuracy. This loss function can accelerate the convergence of the model and make it achieve better results in regressions. For complex backgrounds, ECA (Efficient Channel Attention Module) is embedded between the backbone and the feature fusion layer of the model to reduce the influence of redundant features on the detection accuracy and make progress in the aspect. As a result, these experiments show that the improved model achieved 97.18% mAP which is 2.74% higher than before, and the detection speed could reach 71 fps. To some extent, it can detect insulator and its defects accurately and in real-time.
Dynamic Knowledge Distillation with Noise Elimination for RGB-D Salient Object Detection
Authors: Ren Guangyu , Yu Yinxiao , Liu Hengyan , Stathaki Tania
Published: August 2022

RGB-D salient object detection (SOD) demonstrates its superiority in detecting in complex environments due to the additional depth information introduced in the data. Inevitably, an independent stream is introduced to extract features from depth images, leading to extra computation and parameters. This methodology sacrifices the model size to improve the detection accuracy which may impede the practical application of SOD problems. To tackle this dilemma, we propose a dynamic knowledge distillation (DKD) method, along with a lightweight structure, which significantly reduces the computational burden while maintaining validity. This method considers the factors of both teacher and student performance within the training stage and dynamically assigns the distillation weight instead of applying a fixed weight on the student model. We also investigate the issue of RGB-D early fusion strategy in distillation and propose a simple noise elimination method to mitigate the impact of distorted training data caused by low quality depth maps. Extensive experiments are conducted on five public datasets to demonstrate that our method can achieve competitive performance with a fast inference speed (136FPS) compared to 12 prior methods.
MDS-Net: Multi-Scale Depth Stratification 3D Object Detection from Monocular Images
Authors: Xie Zhouzhen , Song Yuying , Wu Jingxuan , Li Zecheng , Song Chunyi , Xu Zhiwei
Published: August 2022

Monocular 3D object detection is very challenging in autonomous driving due to the lack of depth information. This paper proposes a one-stage monocular 3D object detection network (MDS Net), which uses the anchor-free method to detect 3D objects in a per-pixel prediction. Firstly, a novel depth-based stratification structure is developed to improve the network’s ability of depth prediction, which exploits the mathematical relationship between the size and the depth in the image of an object based on the pinhole model. Secondly, a new angle loss function is developed to further improve both the accuracy of the angle prediction and the convergence speed of training. An optimized Soft-NMS is finally applied in the post-processing stage to adjust the confidence score of the candidate boxes. Experiment results on the KITTI benchmark demonstrate that the proposed MDS-Net outperforms the existing monocular 3D detection methods in both tasks of 3D detection and BEV detection while fulfilling real-time requirements.
GR-ConvNet v2: A Real-Time Multi-Grasp Detection Network for Robotic Grasping
Authors: Kumra Sulabh , Joshi Shirin , Sahin Ferat
Published: August 2022

We propose a dual-module robotic system to tackle the problem of generating and performing antipodal robotic grasps for unknown objects from the n-channel image of the scene. We present an improved version of the Generative Residual Convolutional Neural Network (GR-ConvNet v2) model that can generate robust antipodal grasps from n-channel image input at real-time speeds (20 ms). We evaluated the proposed model architecture on three standard datasets and achieved a new state-of-the-art accuracy of 98.8%, 95.1%, and 97.4% on Cornell, Jacquard and Graspnet grasping datasets, respectively. Empirical results show that our model significantly outperformed the prior work with a stricter IoU-based grasp detection metric. We conducted a suite of tests in simulation and the real world on a diverse set of previously unseen objects with adversarial geometry and household items. We demonstrate the adaptability of our approach by directly transferring the trained model to a 7 DoF robotic manipulator with a grasp success rate of 95.4% and 93.0% on novel household and adversarial objects, respectively. Furthermore, we validate the generalization capability of our pixel-wise grasp prediction model by validating it on complex Ravens-10 benchmark tasks, some of which require closed-loop visual feedback for multi-step sequencing.
Preparing Wi-Fi 7 for Healthcare Internet-of-Things
Authors: Qadri Yazdan Ahmad , Zulqarnain  , Nauman Ali , Musaddiq Arslan , Garcia-Villegas Eduard , Kim Sung Won
Published: August 2022

The healthcare Internet of Things (H-IoT) is an interconnection of devices capable of sensing and transmitting information that conveys the status of an individual’s health. The continuous monitoring of an individual’s health for disease diagnosis and early detection is an important application of H-IoT. Ambient assisted living (AAL) entails monitoring a patient’s health to ensure their well-being. However, ensuring a limit on transmission delays is an essential requirement of such monitoring systems. The uplink (UL) transmission during the orthogonal frequency division multiple access (OFDMA) in the wireless local area networks (WLANs) can incur a delay which may not be acceptable for delay-sensitive applications such as H-IoT due to their random nature. Therefore, we propose a UL OFDMA scheduler for the next Wireless Fidelity (Wi-Fi) standard, the IEEE 802.11be, that is compliant with the latency requirements for healthcare applications. The scheduler allocates the channel resources for UL transmission taking into consideration the traffic class or access category. The results demonstrate that the proposed scheduler can achieve the required latency for H-IoT applications. Additionally, the performance in terms of fairness and throughput is also superior to state-of-the-art schedulers.
An Efficient Ensemble Deep Learning Approach for Semantic Point Cloud Segmentation Based on 3D Geometric Features and Range Images
Authors: Atik Muhammed Enes , Duran Zaide
Published: August 2022

Mobile light detection and ranging (LiDAR) sensor point clouds are used in many fields such as road network management, architecture and urban planning, and 3D High Definition (HD) city maps for autonomous vehicles. Semantic segmentation of mobile point clouds is critical for these tasks. In this study, we present a robust and effective deep learning-based point cloud semantic segmentation method. Semantic segmentation is applied to range images produced from point cloud with spherical projection. Irregular 3D mobile point clouds are transformed into regular form by projecting the clouds onto the plane to generate 2D representation of the point cloud. This representation is fed to the proposed network that produces semantic segmentation. The local geometric feature vector is calculated for each point. Optimum parameter experiments were also performed to obtain the best results for semantic segmentation. The proposed technique, called SegUNet3D, is an ensemble approach based on the combination of U-Net and SegNet algorithms. SegUNet3D algorithm has been compared with five different segmentation algorithms on two challenging datasets. SemanticPOSS dataset includes the urban area, whereas RELLIS-3D includes the off-road environment. As a result of the study, it was demonstrated that the proposed approach is superior to other methods in terms of mean Intersection over Union (mIoU) in both datasets. The proposed method was able to improve the mIoU metric by up to 15.9% in the SemanticPOSS dataset and up to 5.4% in the RELLIS-3D dataset.
Beamforming Design for Cooperative Intelligent Reflecting Surface-Assisted mmWave Communication
Authors: Qian Yuyan , Deng Honggui , Guo Aimin , Xiao Haoqi , Peng Chengzuo , Zhang Yinhao
Published: August 2022

In order to investigate the effect of cooperative Intelligent Reflecting Surface (IRS) in improving spectral efficiency, this paper explores the joint design of active and passive beamforming based on a double IRS-assisted model. First, considering the maximum power constraint of the active vector and the unit modulus constraint of the cooperative passive vector, we establish the non-linear and non-convex optimization problem of multi-user maximization weighted sum rate (WSR). Then, we propose an alternating optimization (AO) algorithm to design the active vector and the cooperative passive vector based on fractional programming (FP) and successive convex approximations (SCA). In addition, we conduct a study on the optimization of the passive reflection vector under discrete phase shift. The simulation results show that the proposed beamforming scheme of double IRS-assisted model performs better than the conventional single IRS-assisted model.
Effects of Origanum vulgare and Scutellaria baicalensis on the Physiological Activity and Biochemical Parameters of the Blood in Rats on a High-Fat Diet
Authors: Lieshchova Maryna , Brygadyrenko Viktor
Published: August 2022

The pharmacological effects of medicinal plants play a primary role in the mild correction of body weight in humans and animals, reducing the accumulation of fat in their bodies during a state of obesity. Origanum vulgare L. and Scutellaria baicalensis Georgi are widely used as food additives and medicinal plants, but their comprehensive physiological evaluation in model animals in a state of obesity has not been carried out. In a 30-day laboratory experiment on male rats which had developed obesity through a hypercaloric diet, the effects of adding the dry crushed grass O. vulgare or dry crushed roots of S. baicalensis to their feed was evaluated. During the experiment, the rats fed with O. vulgare increased in body weight to only 105.5% of their initial weight, while the body weight of the control group increased to 111.5%, and that of animals fed on S. baicalensis increased to 124.0% of their initial body weight. The average daily increase in the rats’ body weight when O. vulgare was added to their diet decreased to 205 mg/day, and when S. baicalensis was added, on the contrary, it increased to 1417 mg/day, compared to 700 mg/day among the control group. Under the influence of O. vulgare, the lipid metabolism of the rats normalized: the atherogenic index decreased to 33.7%, compared with the values of the control group, due to an increase in the concentration of high-density lipoproteins from cholesterol. The concentration of triglycerides decreased, and the concentration of glucose decreased. The roots of S. baicalensis being added into the diet of rats increased the activity of alkaline phosphatase and decreased the concentration of urea. The atherogenic index also decreased (by up to 35.5% in the control group) and the concentration of high-density lipoprotein cholesterol increased, while the concentrations of triglycerides and glucose decreased. The physical activity of the rats showed a slight tendency to decrease when both O. vulgare and S. baicalensis were added to their diet. Both plant species contributed to a decrease in the emotional status of animals, which was most pronounced when the O. vulgare grass was added to the feed. The results of the study demonstrate the potential of the use of O. vulgare and S. baicalensis as herbal supplementations for the correction of hyperlipidemia and type-2 diabetes mellitus in overweight patients.