bluuebunny/crossref_metadata_2025 huggingface dataset:
Skin Anti-Aging Efficacy of Enzyme-Treated Supercritical Caviar Extract: A Randomized, Double-Blind, Placebo-Controlled Clinical Trial
Authors: Na Gwi Hwan , Kim SukJin , Jung Hyun Mook , Han Sang Hun , Han Jehee , Koo Yean Kyoung
Published: December 2023

Oxidative stress in the skin, induced by an unhealthy lifestyle and exposure to UVB radiation, leads to skin aging, including reduced elasticity, formation of wrinkles, moisture loss, and inflammation. In a previous study, we revealed the photoaging effects of enzyme-treated caviar extract (CV) by regulating collagen and hyaluronic acid synthase, melanogenesis, anti-oxidant mechanisms, and inflammation in a UVB irradiation-induced mice model. HPLC and MALDI-TOF were performed to determine the effect of enzyme treatment on the free amino acid contents and peptide molecular weight in supercritical caviar extract. As results of the analysis, CV is mainly composed of low-molecular-weight peptides consisting of leucine, tyrosine, and phenylalanine. Based on our in vitro and in vivo study, we conducted a clinical trial to assess the skin anti-aging efficacy of CV. In this randomized, double-blind, placebo-controlled trial, we measured indicators related to elasticity, wrinkles, and skin hydration at 4 and 8 weeks after consumption of CV. The subjects were categorized into caviar, combination, and placebo groups. After 4 weeks, skin hydration, dermal hydration, and transepidermal water loss all showed significant improvement. Furthermore, after 8 weeks, skin elasticity indexes—R2 (total elasticity), R5 (net elasticity), and R7 (ratio of elastic recovery to total deformation)—exhibited significant increases. Improvement in wrinkle indicators (Rmax, Ra, and Rz) and the whitening indicator melanin pigment was also observed. This is the first report showing that CV has significant skin anti-aging efficacy on human skin. In conclusion, our study suggests that CV can be used as skin anti-aging nutraceuticals through positive effects on skin condition in clinical trials.
Diet-Attributable Greenhouse Gas Emissions and Acute Myocardial Infarction in Costa Rica Heart Study
Authors: Aljahdali Abeer A. , Campos Hannia , Granados Keylin , Jones Andrew D. , Baylin Ana
Published: December 2023

Adopting sustainable dietary patterns is essential for planetary and human health. As data to address this issue are lacking in Latino populations, this study examined the association between diet-attributable greenhouse gas emissions (GHGEs) and myocardial infarction (MI) in a Costa Rica Heart Study. This analysis included 1817 cases of a first non-fatal acute MI during hospitalization and their matched population-based controls, by age, sex, and area of residence. A validated food frequency questionnaire was used to quantify habitual dietary intake and diet-attributable GHGEs (kg CO2 equivalent (eq.)/year). Due to the matching design, conditional logistic regression was used. Red meat consumption contributed approximately 50% to the total diet-attributable GHGEs among both cases and controls. Higher diet-attributable GHGEs were associated with increased odds of acute MI. The odds of MI were 63% higher (OR = 1.63; 95% CI 1.20–2.21) among participants in the highest quintile (median diet-attributable GHGEs = 6247 kg CO2 eq./year) compared to the lowest quintile (median diet-attributable GHGEs = 2065 kg CO2 eq./year). An increasing linear trend in the odds of acute MI and diet-attributable GHGEs was detected (p-trend 0.0012). These findings highlight the importance of reducing red meat consumption to sustainably mitigate the incidence of MI and improve planetary health.
Relationship between Diet Quality and Socioeconomic and Health-Related Factors in Adolescents by Gender
Authors: Colillas-Malet Ester , Bosque-Prous Marina , Esquius Laura , González-Casals Helena , Lafon-Guasch Aina , Fortes-Muñoz Paula , Espelt Albert , Aguilar-Martínez Alicia
Published: December 2023

Adolescence is a key period for consolidating heathy lifestyles and proper eating habits that can last into adulthood. To analyze the diet quality of Spanish adolescents and its association with socioeconomic factors and health behaviors by gender, a cross-sectional study was conducted using data from the DESKcohort project, consisting of a biannual panel survey on health, health behaviors, and associated determinants, collected in secondary education centers. The study population consisted of 7319 students aged 12 to 18 years. Data were collected from October 2019 to March 2020. The dependent variable was diet quality score according to the Spanish adaptation of the Healthy Eating Index (S-HEI). The independent variables included were socioeconomic factors and health behaviors. We conducted linear regression separately by gender. Diet quality score was significantly higher for girls than for boys (68 and 65, respectively, p < 0.001). For both genders, poorer diet quality was associated with a low level of physical activity [−0.9 (95% CI = −1.6:−0.2) in boys, −1.2 (95% CI = −1.9:−0.4) in girls], alcohol use [−2.5 (95% CI = −3.7:−1.3) in boys, −1.0 (95% CI = −1.9:0.0) in girls], poor self-perceived health [−1.1 (95% CI = −2.4:0.2) in boys, −3.5 (95% CI = −4.6:−2.4) in girls], and having attended Intermediate Level Training Cycles [−2.9 (95% CI = −4.3:−1.5) in boys, −1.9 (95% CI = −3.5:−0.3) in girls]. In girls, poorer diet quality also was associated with low mood [−1.1 (95% CI = −1.9:−0.3)]. The variance was 9% in boys and 12% in girls. Our results highlight the need to consider socioeconomic and health-related factors, as well as gender, when conducting interventions to promote healthy eating among adolescents.
Study of Serum Copper and Zinc Levels and Serum Cu/Zn Ratio among Polish Women with Endometrial Cancer
Authors: Kluza Katarzyna , Zawlik Izabela , Janowska Magdalena , Kmieć Aleksandra , Paszek Sylwia , Potocka Natalia , Skrzypa Marzena , Zuchowska Alina , Kluz Marta , Wróbel Andrzej , Baszuk Piotr , Pietrzak Sandra , Marciniak Wojciech , Miotla Pawel , Lubiński Jan , Gronwald Jacek , Kluz Tomasz
Published: December 2023

Background: Micronutrients are important components for the homeostasis of the human body. The studies available in the literature of the subject on their impact on the risk of population diseases, including malignant neoplasms, are ambiguous. In this paper, the relationship between Cu and Zn serum levels and the occurrence of endometrial cancer have been analyzed. Methods: 306 patients (153 test group and 153 control group) matched for age were analyzed for Cu and Zn levels. Microelements levels were determined for sera collected during the hospitalization of patients by means of an inductively coupled plasma mass spectrometry. In addition, the Cu/Zn ratio in the population included in the study was analyzed. Univariable and multivariable analyzes were used to examine the relationship between the factors under study and the incidence of endometrial cancer. Results: Lower levels of elements were observed in the study group compared with the control group (Cu: 959.39 μg/L vs. 1176.42 μg/L, p < 0.001; Zn: 707.05 μg/L vs. 901.67 μg/L, p < 0.001). A statistically significant relationship with the occurrence of endometrial cancer was observed for Cu and Zn. The patients with the lowest Cu level had a significantly higher occurrence of endometrial cancer compared with reference tertile (OR 8.54; p < 0.001). Similarly, compared with the reference tertile, the patients with the lowest Zn levels had a significantly greater incidence of endometrial cancer (OR 15.0; p < 0.001). Conclusion: The results of the study suggest an association of endometrial cancer occurrence with lower Cu and Zn serum levels.
Effect of Nicotinamide Mononucleotide Concentration in Human Milk on Neurodevelopmental Outcome: The Tohoku Medical Megabank Project Birth and Three-Generation Cohort Study
Authors: Saito Yoshie , Sato Keigo , Jinno Shinji , Nakamura Yoshitaka , Nobukuni Takahiro , Ogishima Soichi , Mizuno Satoshi , Koshiba Seizo , Kuriyama Shinichi , Ohneda Kinuko , Morifuji Masashi
Published: December 2023

(1) Background: Breast milk is the only source of nutrition for breastfed infants, but few studies have examined the relationship between breast milk micronutrients and infant neurodevelopmental outcome in exclusively breastfed infants. The aim of this study was to characterize the association between nicotinamide adenine dinucleotide (NAD)-related compounds in the breast milk of Japanese subjects and infant neurodevelopmental outcome. (2) Methods: A total of 150 mother–child pairs were randomly selected from the three-generation cohort of the Tohoku Medical Megabank in Japan. Infants were exclusively breastfed for up to 6 months. Breast milk was collected at 1 month postpartum, and the quantity of NAD-related substances in the breast milk was quantified. The mothers also completed developmental questionnaires at 6, 12, and 24 months. The relationship between the concentration of NAD-related substances in breast milk and developmental indicators was evaluated via ordinal logistic regression analysis. (3) Results: Nicotinamide mononucleotide (NMN) was quantified as the major NAD precursor in breast milk. The median amount of NMN in the breast milk was 9.2 μM. The NMN concentration in breast milk was the only NAD-related substance in breast milk that showed a significant positive correlation with neurodevelopmental outcome in infants at 24 months. (4) Conclusions: The results suggest that NMN in human milk may be an important nutrient for early childhood development.
Consumption of Policosanol (Raydel®) Improves Hepatic, Renal, and Reproductive Functions in Zebrafish: In Vivo Comparison Study among Cuban, Chinese, and American Policosanol
Authors: Cho Kyung-Hyun , Kim Ji-Eun , Nam Hyo-Seon , Baek Seung-Hee , Bahuguna Ashutosh
Published: December 2023

The current study compared three policosanols from Cuba (sugarcane, Raydel®, policosanol (1), China (rice bran, Shaanxi, policosanol (2), and the USA (sugarcane, Lesstanol®, policosanol (3) in the treatment of dyslipidemia and protection of the liver, ovary, and testis in hypercholesterolemic zebrafish. After twelve weeks of supplementation of each policosanol (PCO, final 0.1% in diet, w/w) with a high cholesterol diet (HCD, final 4%, w/w), the Raydel policosanol (PCO1) group showed the highest survivability, approximately 89%. In contrast, Shaanxi policosanol (PCO2) and Lesstanol policosanol (PCO3) produced 73% and 87% survivability, respectively, while the HCD alone group showed 75% survivability. In the 12th week, the PCO1 group demonstrated the most modest increase in body weight along with significantly lower levels of total cholesterol (TC) and triglycerides (TG) in comparison to the HCD control group. Additionally, the PCO1 group exhibited the highest proportion of high-density lipoprotein (HDL)-cholesterol within TC. Notably, the PCO1 group displayed the lowest level of aspartate aminotransferase and alanine aminotransferase, minimal infiltration of inflammatory cells, reduced interleukin (IL)-6 production in the liver, a notable decline in reactive oxygen species (ROS) generation and mitigated fatty liver changes. HCD supplementation induced impairment of kidney morphology with the greatest extent of ROS production and apoptosis. On the other hand, the PCO 1 group showed a remarkably improved morphology with the least ROS generation and apoptosis. Within the ovarian context, the PCO1 group exhibited the most substantial presence of mature vitellogenic oocytes, accompanied by minimal levels of ROS and apoptosis. Similarly, in the testicular domain, the PCO1 group showcased optimal morphology for spermatogenesis, characterized by the least interstitial area and diminished production of ROS in testicular cells. At week 8, the PCO1 group showed the highest egg-laying ability, with around 244 eggs produced per mating. In contrast, the HCD alone, PCO2, and PCO3 groups showed significantly lower egg-laying ability (49, 59, and 86 eggs, respectively). The embryos from the PCO1 group exhibited the highest survivability with the fastest swimming ability and developmental speed. These results suggest that PCO1 consumption significantly enhanced the reproduction system, egg-laying ability, and embryo survivability. In conclusion, among the three policosanols, Cuban (Raydel®) policosanol had the strongest effect on survivability, improving dyslipidemia, liver protection, kidney, ovary, and testis with a restoration of the cell morphology, and the least ROS production and apoptosis-induced by HCD supplementation.
Knowledge of Kratom among Alabama Pharmacists
Authors: Penzak Scott R. , Durham Spencer H. , Phillippe Haley M. , Fox Brent I.
Published: December 2023

Kratom (Mitragyna speciosa) is a botanical substance whose leaves produce stimulant- and opioid-like effects. Kratom use has increased precipitously in the United States (U.S.) over the last decade, yet, in our experience, many pharmacists are unfamiliar with this herb. The purpose of this study was to assess pharmacists’ awareness and knowledge of kratom. This cross-sectional study used an online questionnaire to preferentially solicit community pharmacists’ knowledge of kratom and collect demographic information. The survey was sent via email to approximately 10,000 pharmacists, targeting those in the state of Alabama, U.S. Data were analyzed using descriptive statistics, and the Chi Square test was used to compare nominal data. A total of 257 participants responded to the survey. Almost 50% of participants had heard of kratom, and 50% had not. Compared to females, males were more likely to have heard of kratom (64% vs. 42%; p = 0.0015), as were pharmacists who worked for an independent pharmacy vs. a chain (61% vs. 41%; p = 0.025). Of the participants who had heard of kratom, only 14% considered themselves knowledgeable or very knowledgeable about the herb, and only 44% knew it was illegal in Alabama. These data indicate a need to further kratom education among community pharmacists in Alabama.
Pharmaco-Analysis of Psychedelics—Philo-Fictions about New Materialism, Quantum Mechanics, Information Science, and the Philosophy of Immanence
Authors: Paulus Stefan
Published: December 2023

Recent developments regarding the pharmacology of psychoactive substances are significant for treating depressions or opioid addictions. Current theories, hypotheses, and models of drug effects assume a cause–effect narrative, which is based on a stimulus/response mechanism. These narratives prioritize effects rather than conscious experiences. In this sense, drug experiences are quickly subsumed into common categories and codes of biological determinism. If subjective experiences are in the focus of the research, it quickly becomes a link to mystical, spiritual, or transcendental narratives. These classifications lead to epistemological doublets (Gadamer). In this article, psychedelic experiences of drug users are analyzed in the frame of the pharmaco-analysis by Deleuze/Guattari. These framed psychedelic experiences are interpreted by means of a non-philosophical approach through philo-fictions (Laruelle), i.e., contradictory assumptions and hyperspeculations. In this respect, the aim of this article is to bring philo-fictions in relation to psychedelic experiences and to discuss them with models of information science, quantum mechanics, new materialism, and the philosophy of immanence. The result will be an open synthesis, with the assumption of further reflections on the agency, immanence, and the wholeness of matter.
NaGdF4:Yb, Er, Tm Upconversion Nanoparticles for Bioimaging in Shortwave-Infrared Range: Study of Energy Transfer Processes and Composition Optimization
Authors: Pominova Daria , Proydakova Vera , Romanishkin Igor , Kuznetsov Sergei , Linkov Kirill , Tabachkova Nataliya , Ryabova Anastasia
Published: December 2023

Upconversion nanoparticles are promising for many applications. For triple-doped nanoparticles (NPs), the luminescence intensity shows a non-linear dependence on the rare-earth ion concentration, making it difficult to obtain bright phosphors with high energy output. We investigated the energy transfer processes in β-NaGdF4:Yb-Er-Tm NPs and considered strategies for increasing the thulium luminescence intensity, in particular, the use of core–shell structures. The luminescence spectra were analyzed in the short-wavelength infrared (SWIR) and visible (VIS) regions. The Er3+ and Tm3+ luminescence lifetimes in the VIS region were measured to study the energy transfer processes between the active ions. The quenching of the Tm3+ luminescence in the SWIR region was observed. However, both Er3+ and Tm3+ luminescence bands were observed in the VIS range. We attribute these effects to energy transfer between Tm3+ 3F4 → 3H6 and Er3+ 4I13/2 → 4I9/2, which occurs due to overlap of Er3+ and Tm3+ luminescence bands, and also to competition between Er3+ and Tm3+ for energy transfer from Yb3+. For core–shell NPs, when Tm3+ and Er3+ are separated into adjacent layers, quenching cannot be avoided, likely due to the mutual diffusion of ions during shell synthesis. The most optimal strategy to obtain luminescence in the SWIR range is to use an inert intermediate shell between the layers containing Tm3+ and Er3+.
Do Successful Researchers Reach the Self-Organized Critical Point?
Authors: Ghosh Asim , Chakrabarti Bikas K.
Published: December 2023

The index of success of the researchers is now mostly measured using the Hirsch index (h). Our recent precise demonstration, that statistically h∼Nc∼Np, where Np and Nc denote, respectively, the total number of publications and total citations for the researcher, suggests that average number of citations per paper (Nc/Np), and hence h, are statistical numbers (Dunbar numbers) depending on the community or network to which the researcher belongs. We show here, extending our earlier observations, that the indications of success are not reflected by the total citations Nc, rather by the inequalities among citations from publications to publications. Specifically, we show that for highly successful authors, the yearly variations in the Gini index (g, giving the average inequality of citations for the publications) and the Kolkata index (k, giving the fraction of total citations received by the top (1−k) fraction of publications; k=0.80 corresponds to Pareto’s 80/20 law) approach each other to g=k≃0.82, signaling a precursor for the arrival of (or departure from) the self-organized critical (SOC) state of his/her publication statistics. Analyzing the citation statistics (from Google Scholar) of thirty successful scientists throughout their recorded publication history, we find that the g and k for the highly successful among them (mostly Nobel laureates, highest rank Stanford cite-scorers, and a few others) reach and hover just above (and then) below that g=k≃0.82 mark, while for others they remain below that mark. We also find that all the lower (than the SOC mark 0.82) values of k and g fit a linear relationship, k=1/2+cg, with c=0.39, as suggested by an approximate Landau-type expansion of the Lorenz function, and this also indicates k=g≃0.82 for the (extrapolated) SOC precursor mark.
Equation-Oriented Modeling and Optimization of a Biorefinery Based on Avocado Waste
Authors: Sousa Daniel , Rodrigues Diogo , Castro Pedro M. , Matos Henrique A.
Published: December 2023

Due to the growth in the consumption of avocado in recent years, the amount of waste caused by avocado peel and seed has increased. Avocado waste can be transformed into valuable products such as energy, biofuels, and biological products using integrated processes in a biorefinery. This paper considers the detailed modeling, simulation, and optimization of a biorefinery for the production of phenolic compounds, bioethanol, biological xylitol, syngas, and electrical power from avocado seed and peel, using Aspen Plus in equation-oriented mode as a process simulation tool. For a biorefinery in nominal conditions, it is possible to achieve a gross profit of approximately 30×106 USD/year for capital costs of USD 31.4×106, while the combined effect of process optimization and heat integration allows reaching a gross profit of 37×106 USD/year for capital costs of USD 30.7×106. These results of the optimized plant show its potential to take advantage of avocado seed and peel in a profitable and sustainable way. This detailed equation-based model paves the way for superstructure optimization of a biorefinery for avocado waste processing.
Fixed-Time Control of a Robotic Arm Based on Disturbance Observer Compensation
Authors: Zhang Gang , Pan Jing , Li Tianli , Wang Zheng , Wang Duansong
Published: December 2023

Backstepping-based fixed-time tracking control is proposed for a robotic arm system to solve the problem of trajectory tracking control under system uncertainties, which ensures the robotic arm system can realize stable tracking control within a fixed time independent of the initial state of the system. In addition, to address the uncertainties in the robotic arm system, a control strategy based on disturbance observer compensation is designed, which provides feed-forward compensation through the accurate estimation of the system uncertainties and enhances the system’s robustness. Finally, a two-link robotic arm model is used for simulation experiments, and the comparison results show that the control scheme designed in this article can effectively improve the robotic arm’s tracking accuracy and convergence speed.
Bentonite Modified with Surfactants—Efficient Adsorbents for the Removal of Non-Steroidal Anti-Inflammatory Drugs
Authors: Obradović Milena , Daković Aleksandra , Smiljanić Danijela , Marković Marija , Ožegović Milica , Krstić Jugoslav , Vuković Nikola , Milojević-Rakić Maja
Published: December 2023

Organobentonites have been applied for the removal of two common non-steroidal anti-inflammatory drugs, ibuprofen (IBU) and diclofenac sodium (DS), from aqueous solutions. Two surfactants, one with and the other without benzyl group (octadecyldimethylbenzylammonium chloride, ODMBA, and hexadecyltrimethylammonium bromide, HDTMA), in amounts equivalent to 50, 75, and 100% of the cation exchange capacity of bentonite were used for the preparation of organobentonites. Successful modification of bentonite was confirmed by several methods: X-ray powder diffraction (XRPD), point of the zero charge (pHPZC), determination of exchanged inorganic cations in bentonite, determination of textural properties, and scanning electron microscopy (SEM). Kinetic and thermodynamic data on the adsorption of IBU and DS showed that drug adsorption was controlled by the type and the amount of surfactant incorporated into the bentonite and by their arrangement in the interlayer space and at the surface of organobentonites. The adsorption of both drugs increased with an increase in the amount of both surfactants in organobentonites. The presence of the benzyl group in organobentonites enhanced the adsorption of IBU and DS and was more pronounced for IBU. Drug adsorption fits the pseudo-second-order kinetic model the best. The thermodynamic data revealed that the adsorption process was endothermic in nature and with increase of the amount of both surfactants drug adsorption processes were more spontaneous. The results obtained from this study revealed that adsorbents based on surfactants modified bentonite are promising candidates for IBU and DS removal from contaminated water.
Potential Effects of Anthropogenic Radiofrequency Radiation on Cetaceans
Authors: Balmori-de la Puente Alfonso , Balmori Alfonso
Published: December 2023

Cetaceans are cast to shore for a large number of reasons, although sometimes it is not clear why. This paper reviews the types and causes of cetacean strandings, focusing on mass strandings that lack a direct scientific explanation. Failure of cetacean orientation due to radiofrequency radiation and alterations in the Earth’s magnetic field produced during solar storms stand out among the proposed causes. This paper proposes the possibility that anthropogenic radiofrequency radiation from military and meteorological radars may also cause these strandings in areas where powerful radars exist. A search of accessible databases of military and meteorological radars in the world was carried out. Research articles on mass live strandings of cetaceans were reviewed to find temporal or spatial patterns in the stranding concentrations along the coast. The data showed certain patterns of spatial and temporal evidence in the stranding concentrations along the coast after radar setup and provided a detailed description of how radars may interfere with cetacean echolocation from a physiological standpoint. Plausible mechanisms, such as interference with echolocation systems or pulse communication systems, are proposed. This work is theoretical, but it leads to a hypothesis that could be empirically tested. Further in-depth studies should be carried out to confirm or reject the proposed hypothesis.
Synodality and Decision-Making Processes: Towards New Bodies of Participation in the Church
Authors: Zaccaria Francesco
Published: December 2023

The church’s synodal conversion requires a reform of its decision-making processes. Facing the challenge of keeping in balance the common dignity of all the baptized and the value of the hierarchical structure of the church, the participation of all the faithful in decision-making processes is grounded in biblical and theological arguments and defined as a co-responsibility in taking joint decisions. The analysis of two synodal bodies recently established within the Catholic Church in the Amazon and Germany delineates new directions for the renewal of decision-making structures in the church. These directions entail reforming the existing participatory structures and creating new deliberative bodies in the church. Looking at church reality and the practice of consultation and decision-making, synodal conversion ultimately requires the reform of training for church leaders with a view to changing church mindsets and culture.
Suitable-Matching Areas’ Selection Method Based on Multi-Level Saliency
Authors: Jiang Supeng , Luo Haibo , Liu Yunpeng
Published: December 2023

Scene-matching navigation is one of the essential technologies for achieving precise navigation in satellite-denied environments. Selecting suitable-matching areas is crucial for planning trajectory and reducing yaw. Most traditional selection methods of suitable-matching areas use hierarchical screening based on multiple feature indicators. However, these methods rarely consider the interrelationship between different feature indicators and use the same set of screening thresholds for different categories of images, which has poor versatility and can easily cause mis-selection and omission. To solve this problem, a suitable-matching areas’ selection method based on multi-level saliency is proposed. The matching performance score is obtained by fusing several segmentation levels’ salient feature extraction results and performing weighted calculations with the sub-image edge density. Compared with the hierarchical screening methods, the matching performance of the candidate areas selected by our algorithm is at least 22.2% higher, and it also has a better matching ability in different scene categories. In addition, the number of missed and wrong selections is significantly reduced. The average matching accuracy of the top three areas selected by our method reached 0.8549, 0.7993, and 0.7803, respectively, under the verification of multiple matching algorithms. Experimental results show this paper’s suitable-matching areas’ selection method is more robust.
Influence of South-to-North Water Diversion on Land Subsidence in North China Plain Revealed by Using Geodetic Measurements
Authors: Wang Jingqi , Ding Kaihua , Chen Xiaodong , Guo Rumeng , Sun Heping
Published: December 2023

As a major grain-producing region in China, the North China Plain (NCP) faces serious challenges such as water shortage and land subsidence. In late 2014, the Central Route of the South-to-North Water Diversion Project (SNWD-C) began to provide NCP with water resources. However, the effectiveness of this supply in mitigating land subsidence remains a pivotal and yet unassessed aspect. In this paper, we utilized various geodetic datasets, including the Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow On (GRACE-FO), Global Navigation Satellite System (GNSS) and leveling data, to conduct a spatial-temporal analysis of the equivalent water height (EWH) and vertical ground movement in the NCP. The results reveal a noteworthy decline in EWH from 2011 to 2015, followed by a slight increase with minor fluctuations from 2015 to 2020, demonstrating a strong correlation with the water resources supplied by the SNWD-C. The GRACE-derived surface deformation rate induced by hydrological loading is estimated to be <1 mm/yr. In comparison, GNSS-derived vertical ground movements exhibit considerable regional differences during the 2011–2020 period. Substantial surface subsidence is evident in the central and eastern NCP, contrasting with a gradual uplift in the front plain of the Taihang Mountains. Three-stage leveling results indicate that the rate of subsidence in the central and eastern plains is gradually increasing with the depression area expanding from 1960 to 2010. Based on these geodetic results, it can be inferred that the SNWD-C’s operation since 2014 has effectively mitigated the reduction in terrestrial water storage in the NCP. However, land subsidence in the NCP persists, as the subsidence rate does not turn around in sync with the change in EWH following the operation of SNWD-C. Consequently, it’s necessary to maintain and enforce existing policies, including controlling groundwater exploitation and water resources supply (e.g., SNWD-C) to curtail the exacerbation of land subsidence in the NCP. Additionally, continuous monitoring of land subsidence by GRACE, GNSS, leveling and other geodetic techniques is crucial to enable timely policy adjustments based on monitoring results.
A Lightweight Man-Overboard Detection and Tracking Model Using Aerial Images for Maritime Search and Rescue
Authors: Zhang Yijian , Tao Qianyi , Yin Yong
Published: December 2023

Unmanned rescue systems have become an efficient means of executing maritime search and rescue operations, ensuring the safety of rescue personnel. Unmanned aerial vehicles (UAVs), due to their agility and portability, are well-suited for these missions. In this context, we introduce a lightweight detection model, YOLOv7-FSB, and its integration with ByteTrack for real-time detection and tracking of individuals in maritime distress situations. YOLOv7-FSB is our lightweight detection model, designed to optimize the use of computational resources on UAVs. It comprises several key components: FSNet serves as the backbone network, reducing redundant computations and memory access to enhance the overall efficiency. The SP-ELAN module is introduced to ensure operational speed while improving feature extraction capabilities. We have also enhanced the feature pyramid structure, making it highly effective for locating individuals in distress within aerial images captured by UAVs. By integrating this lightweight model with ByteTrack, we have created a system that improves detection accuracy from 86.9% to 89.2% while maintaining a detection speed similar to YOLOv7-tiny. Additionally, our approach achieves a MOTA of 85.5% and a tracking speed of 82.7 frames per second, meeting the demanding requirements of maritime search and rescue missions.
Comparative Study on Predicting Topography from Gravity Anomaly and Gravity Gradient Anomaly
Authors: Xu Huan , Tian Yuwei , Yu Jinhai , Anderson Ole Baltazar , Wang Qiuyu , Sun Zhongmiao
Published: December 2023

Owing to the dependence of algorithms on the measurement of ship soundings and geophysical parameters, the accuracy and coverage of topography still need to be improved. Previous studies have mostly predicted topography using gravity or gravity gradient, However, there is a relative lack of integrated research combining or comparing gravity and gravity gradient. In this study, we develop observation equations to predict topography based on vertical gravity anomalies (VG; also called gravity anomalies) and vertical gravity gradient (VGG) anomalies generated by a rectangular prism. The sources of interference are divided into medium- to high-frequency errors and low-frequency errors, and these new methods reduce these errors through regularization and error equations. We also use numerical simulations to test the efficiency of the algorithm and error-reduction method. Statistics show that VGG anomalies are more sensitive to topographic fluctuations; however, the linear correlation between VG anomalies and topography is stronger. Additionally, we use the EIGEN-6C4 model of VG and VGG anomalies to predict topography in shallow and deep-sea areas, with maximum depths of 2 km and 5 km, respectively. In the shallow and deep-sea areas, the root mean square (RMS) errors of VGG anomalies prediction are 93.8 m and 233.8 m, and the corresponding accuracies improved by 7.3% and 2.3% compared with those of VG anomaly prediction, respectively. Furthermore, we use cubic spline interpolation to fuse ship soundings and improve the accuracy of the final topography results. We develop a novel analytical algorithm by constructing an observation equation system applicable to VG and VGG anomalies. This will provide new insights and directions to refine topography prediction based on VG and VGG anomalies.
Learning Global Evapotranspiration Dataset Corrections from a Water Cycle Closure Supervision
Authors: Hascoet Tristan , Pellet Victor , Aires Filipe , Takiguchi Tetsuya
Published: December 2023

Evapotranspiration (E) is one of the most uncertain components of the global water cycle (WC). Improving global E estimates is necessary to improve our understanding of climate and its impact on available surface water resources. This work presents a methodology for deriving monthly corrections to global E datasets at 0.25∘ resolution. A principled approach is proposed to firstly use indirect information from the other water components to correct E estimates at the catchment level, and secondly to extend this sparse catchment-level information to global pixel-level corrections using machine learning (ML). Several E satellite products are available, each with its own errors (both random and systematic). Four such global E datasets are used to validate the proposed approach and highlight its ability to extract seasonal and regional systematic biases. The resulting E corrections are shown to accurately generalize WC closure constraints to unseen catchments. With an average deviation of 14% from the original E datasets, the proposed method achieves up to 20% WC residual reduction on the most favorable dataset.
Scene Classification Method Based on Multi-Scale Convolutional Neural Network with Long Short-Term Memory and Whale Optimization Algorithm
Authors: Ran Yingying , Xu Xiaobin , Luo Minzhou , Yang Jian , Chen Ziheng
Published: December 2023

Indoor mobile robots can be localized by using scene classification methods. Recently, two-dimensional (2D) LiDAR has achieved good results in semantic classification with target categories such as room and corridor. However, it is difficult to achieve the classification of different rooms owing to the lack of feature extraction methods in complex environments. To address this issue, a scene classification method based on a multi-scale convolutional neural network (CNN) with long short-term memory (LSTM) and a whale optimization algorithm (WOA) is proposed. Firstly, the distance data obtained from the original LiDAR are converted into a data sequence. Secondly, a scene classification method integrating multi-scale CNN and LSTM is constructed. Finally, WOA is used to tune critical training parameters and optimize network performance. The actual scene data containing eight rooms are collected to conduct ablation experiments, highlighting the performance with the proposed algorithm with 98.87% classification accuracy. Furthermore, experiments with the FR079 public dataset are conducted to demonstrate that compared with advanced algorithms, the classification accuracy of the proposed algorithm achieves the highest of 94.35%. The proposed method can provide technical support for the precise positioning of robots.
Comparison of Differences in Actual Cropland Evapotranspiration under Two Irrigation Methods Using Satellite-Based Model
Authors: Liu Yi , Ortega-Farías Samuel , Fan Yunfei , Hou Yu , Wang Sufen , Yang Weicai , Li Sien , Tian Fei
Published: December 2023

Remote sensing technology is widely used to obtain evapotranspiration (ETa), but whether it can distinguish the differences in farmland energy balance components and ETa under different irrigation methods has not been studied. We used Landsat 8 data as the primary dataset to drive the METRIC model and inverted the surface parameters and ETa of the Shiyang River Basin from 2014 to 2018. After improving the METRIC model using Ta obtained by the regression method instead of interpolation to calculate the net radiation flux (Rn), R2 was improved from 0.45 to 0.53, and the RMSE was reduced from 61 W/m2 to 51 W/m2. The ETa estimation results on satellite overpass days performed well, with R2 equal to 0.93 and RMSE equal to 0.48 mm when compared with the Eddy covariance method (EC) observations. Subsequently, the different growth stages and daily average ETa estimates of maize were compared with three observations (water balance, WB; Bowen ratio and energy balance method, BREB; and EC). The daily estimates of ETa correlate well with the observations of BREB (R2BI = 0.82, R2DI = 0.92; RMSEBI = 0.46 mm/day, RMSEDI = 0.32 mm/day) and EC (R2BI = 0.85, R2DI = 0.92; RMSEBI = 0.45 mm/day, RMSEDI = 0.34 mm/day), and the estimation for drip irrigation was found to be better than for border irrigation. The total accuracy of the ETa estimation on the five-year overpass day of maize farmland reached R2 = 0.93 and RMSE = 0.48 mm. With sufficient remote sensing data, the 4-year average ETa of maize was 31 mm lower for DI than for BI, and the mean value of ETa obtained from the three observation methods was 40 mm. The METRIC model can be used to distinguish ETa differences between the two irrigation methods in maize farmlands.
Links between Land Cover and In-Water Optical Properties in Four Optically Contrasting Swedish Bays
Authors: Kratzer Susanne , Allart Martin
Published: December 2023

The optical complexity of coastal waters is mostly caused by the water discharged from land carrying optical components (such as dissolved and particulate matter) into coastal bays and estuaries, and increasing the attenuation of light. This paper aims to investigate the links between in-water optical properties in four Swedish bays (from the northern Baltic proper up to the Bothnian bay) and the land use and land cover (LULC) in the respective catchment of each bay. The optical properties were measured in situ over the last decade by various research and monitoring groups while the LULC in each bay was classified using the Copernicus Land Monitoring Service based on Landsat 8/OLI data. The absorption coefficient of colored dissolve organic matter (CDOM) at 440 nm, aCDOM (440), was significantly correlated to Wetlands which may act as sources of CDOM, while Developed areas (Agricultural and Urban classes) were negatively correlated. The Agriculture class was also negatively related to suspended particulate organic matter (SPOM), whilst Coniferous Forests and Mixed Forests as well as Meadows were positively correlated. SPOM seems thus to mostly originate from Natural classes, possibly due to the release of pollen and other organic matter. Overall, the methods applied here allow for a better understanding of effects of land use and land cover on the bio-optical properties, and thus coastal water quality, on a macroscopic scale.
Advanced System-on-Chip Field-Programmable-Gate-Array-Powered Data Acquisition System for Pixel Detectors
Authors: Jiménez-Sánchez Jorge , Blanco-Carmona Pedro , Hinojo-Montero José María , Palomo Francisco Rogelio , Millán Rafael Luis , Muñoz-Chavero Fernando
Published: December 2023

Particle detector systems require data acquisition systems (DAQs) as their back-end. This paper presents a new edge-computing DAQ that is capable of handling multiple pixel detectors simultaneously and was designed for particle-tracking experiments. The system was designed for the ROC4SENS readout chip, but its control logic can be adapted for other pixel detectors. The DAQ was based on a system-on-chip FPGA (SoC FPGA), which includes an embedded microprocessor running a fully functional Linux system. An application using a client–server architecture was developed to facilitate remote control and data visualization. The comprehensive DAQ is very compact, thus reducing the typical hardware load in particle tracking experiments, especially during the obligatory characterization of particle telescopes.
Optical Coherence Tomography as a Non-Invasive Tool for Plant Material Characterization in Agriculture: A Review
Authors: Saleah Sm Abu , Kim Shinheon , Luna Jannat Amrin , Wijesinghe Ruchire Eranga , Seong Daewoon , Han Sangyeob , Kim Jeehyun , Jeon Mansik
Published: December 2023

Characterizing plant material is crucial in terms of early disease detection, pest control, physiological assessments, and growth monitoring, which are essential parameters to increase production in agriculture and prevent unnecessary economic losses. The conventional methods employed to assess the aforementioned parameters have several limitations, such as invasive inspection, complexity, high time consumption, and costly features. In recent years, optical coherence tomography (OCT), which is an ultra-high resolution, non-invasive, and real-time unique image-based approach has been widely utilized as a significant and potential tool for assessing plant materials in numerous aspects. The obtained OCT cross-sections and volumetrics, as well as the amplitude signals of plant materials, have the capability to reveal vital information in both axial and lateral directions owing to the high resolution of the imaging system. This review discusses recent technological trends and advanced applications of OCT, which have been potentially adapted for numerous agricultural applications, such as non-invasive disease screening, optical signals-based growth speed detection, the structural analysis of plant materials, and microbiological discoveries. Therefore, this review offers a comprehensive exploration of recent advanced OCT technological approaches for agricultural applications, which provides insights into their potential to incorporate OCT technology into numerous industries.
Study of the Impact of Data Compression on the Energy Consumption Required for Data Transmission in a Microcontroller-Based System
Authors: Piątkowski Dominik , Puślecki Tobiasz , Walkowiak Krzysztof
Published: December 2023

As the number of Internet of Things (IoT) devices continues to rise dramatically each day, the data generated and transmitted by them follow similar trends. Given that a significant portion of these embedded devices operate on battery power, energy conservation becomes a crucial factor in their design. This paper aims to investigate the impact of data compression on the energy consumption required for data transmission. To achieve this goal, we conduct a comprehensive study using various transmission modules in a severely resource-limited microcontroller-based system designed for battery power. Our study evaluates the performance of several compression algorithms, conducting a detailed analysis of computational and memory complexity, along with performance metrics. The primary finding of our study is that by carefully selecting an algorithm for compressing different types of data before transmission, a significant amount of energy can be saved. Moreover, our investigation demonstrates that for a battery-powered embedded device transmitting sensor data based on the STM32F411CE microcontroller, the recommended transmission module is the nRF24L01+ board, as it requires the least amount of energy to transmit one byte of data. This module is most effective when combined with the LZ78 algorithm for optimal energy and time efficiency. In the case of image data, our findings indicate that the use of the JPEG algorithm for compression yields the best results. Overall, our research underscores the importance of selecting appropriate compression algorithms tailored to specific data types, contributing to enhanced energy efficiency in IoT devices.
LSTM-Based Virtual Load Sensor for Heavy-Duty Vehicles
Authors: İşbitirici Abdurrahman , Giarré Laura , Xu Wen , Falcone Paolo
Published: December 2023

In this paper, a special recurrent neural network (RNN) called Long Short-Term Memory (LSTM) is used to design a virtual load sensor that estimates the mass of heavy vehicles. The estimation algorithm consists of a two-layer LSTM network. The network estimates vehicle mass based on vehicle speed, longitudinal acceleration, engine speed, engine torque, and accelerator pedal position. The network is trained and tested with a data set collected in a high-fidelity simulation environment called Truckmaker. The training data are generated in acceleration maneuvers across a range of speeds, while the test data are obtained by simulating the vehicle in the Worldwide harmonized Light vehicles Test Cycle (WLTC). Preliminary results show that, with the proposed approach, heavy-vehicle mass can be estimated as accurately as commercial load sensors across a range of load mass as wide as four tons.
Parsing Netlists of Integrated Circuits from Images via Graph Attention Network
Authors: Hu Wenxing , Zhan Xianke , Tong Minglei
Published: December 2023

A massive number of paper documents that include important information such as circuit schematics can be converted into digital documents by optical sensors like scanners or digital cameras. However, extracting the netlists of analog circuits from digital documents is an exceptionally challenging task. This process aids enterprises in digitizing paper-based circuit diagrams, enabling the reuse of analog circuit designs and the automatic generation of datasets required for intelligent design models in this domain. This paper introduces a bottom-up graph encoding model aimed at automatically parsing the circuit topology of analog integrated circuits from images. The model comprises an improved electronic component detection network based on the Swin Transformer, an algorithm for component port localization, and a graph encoding model. The objective of the detection network is to accurately identify component positions and types, followed by automatic dataset generation through port localization, and finally, utilizing the graph encoding model to predict potential connections between circuit components. To validate the model’s performance, we annotated an electronic component detection dataset and a circuit diagram dataset, comprising 1200 and 3552 training samples, respectively. Detailed experimentation results demonstrate the superiority of our proposed enhanced algorithm over comparative algorithms across custom and public datasets. Furthermore, our proposed port localization algorithm significantly accelerates the annotation speed of circuit diagram datasets.