bluuebunny/crossref_metadata_2025 huggingface dataset:
Water Intake and Adiposity Outcomes among Overweight and Obese Individuals: A Systematic Review and Meta-Analysis of Randomized Controlled Trials
Authors: Chen Qiao-Yi , Khil Jaewon , Keum NaNa
Published: March 2024

Background: Water consumption is believed to be a key factor in weight management strategies, yet the existing literature on the subject yields inconsistent findings. To systematically assess the scientific evidence regarding the effect of water intake on adiposity, we conducted a systematic review and meta-analysis of randomized controlled trials (RCTs) among overweight and obese populations. Methods: PubMed and Embase were searched for relevant articles published up to December 2023. The summary weighted mean difference (WMD) and 95% confidence interval (CI) were estimated using the DerSimonian–Laird random-effects model. Results: In this meta-analysis of eight RCTs, interventions to promote water intake or to substitute water for other beverages as compared to the control group resulted in a summary WMD of −0.33 kg (95% CI = −1.75–1.08, I2 = 78%) for body weight, −0.23 kg/m2 (95% CI = −0.55–0.09, I2 = 0%) for body mass index (BMI), and 0.05 cm (95% CI = −1.20–1.30, I2 = 40%) for waist circumference (WC). Among RCTs substituting water for artificially sweetened beverages, summary WMD was 1.82 kg (95% CI = 0.97–2.67, I2 = 0%) for body weight and 1.23 cm (95% CI = −0.03–2.48, I2 = 0%) for WC. Conversely, among RCTs substituting water for sugar-sweetened beverages, summary WMD was −0.81 kg (95% CI = −1.66–0.03, I2 = 2%) for body weight and −0.96 cm (95% CI = −2.06–0.13, I2 = 0%) for WC. Conclusions: In conclusion, water intake may not significantly impact adiposity among overweight and obese individuals. However, replacing sugar-sweetened beverages with water might offer a modest benefit in inducing weight loss.
An Adapted Questionnaire Tailored for Assessing the Risk of Vitamin D Deficiency in Children That Is Proving Useful in Guiding Clinical Interventions
Authors: Calcaterra Valeria , Cena Hellas , De Giuseppe Rachele , Biino Ginevra , Grazi Roberta , Manuelli Matteo , Zanelli Sara , Tagi Veronica , Vincenti Alessandra , Zuccotti Gianvincenzo , Fabiano Valentina
Published: March 2024

Background: The identification of vitamin D (VitD) deficiency in pediatric populations is essential for preventive healthcare. We refined and tested the Evaluation of Deficiency Questionnaire (EVIDENCe-Q) for its utility in detecting VitD insufficiency among children. Patients and methods: We enrolled 201 pediatric patients (aged between 3 and 18 years). Clinical evaluation and serum vitamin D levels were assessed in all subjects. The EVIDENCe-Q was updated to incorporate factors influencing VitD biosynthesis, intake, assimilation, and metabolism, with scores spanning from 0 (optimal) to 36 (poor). Results: We established scores for severe deficiency (<10 mg/dL) at 20, deficiency (<20 mg/dL) at 22, and insufficiency (<30 mg/dL) at 28. A score of 20 or greater was determined as the optimal cut-off for distinguishing VitD deficient from sufficient statuses, as evidenced by ROC curve analysis AUC = 0.7066; SE = 0.0841; sensitivity 100%, 95% CI 0.561–1. The most accurate alignment was seen with VitD insufficiency, defined as 25-OH-D3 < 20 ng/mL. Conclusions: This study confirms that the EVIDENCe-Q is a valid instrument for assessing the risk of vitamin D deficiency and insufficiency in children. It offers a practical approach for determining the need for clinical intervention and dietary supplementation of VitD in the pediatric population.
Maternal Seafood Consumption during Pregnancy and Cardiovascular Health of Children at 11 Years of Age
Authors: Pinar-Martí Ariadna , Fernández-Barrés Sílvia , Lázaro Iolanda , Fossati Serena , Fochs Silvia , Pey Núria , Vrijheid Martine , Romaguera Dora , Sala-Vila Aleix , Julvez Jordi
Published: March 2024

Nutrition is critical during pregnancy for the healthy growth of the developing infant, who is fully dependent on maternal dietary omega-3 supply for development. Fatty fish, a main dietary source of omega-3, is associated with decreased cardiovascular risk in adults. We conducted a longitudinal study based on a mother–offspring cohort as part of the project Infancia y Medio Ambiente (INMA) in order to assess whether fish intake during pregnancy relates to cardiovascular health in children. A total of 657 women were included and followed throughout pregnancy until birth, and their children were enrolled at birth and followed up until age 11–12. A semi-quantitative food frequency questionnaire was used to assess the daily intake of foods during the 1st and 3rd trimesters of pregnancy. Cardiovascular assessments included arterial stiffness (assessed by carotid–femoral pulse wave velocity [PWV]) and retinal microcirculation (photographic assessment of central retinal arteriolar and venular equivalent [CRAE and CRVE]). The association between maternal fish consumption and cardiovascular outcomes of offspring at 11 years of age was evaluated using multivariable linear regression models. There were no statistically significant differences in any cardiovascular endpoint in children whose mothers had a higher fish consumption during pregnancy compared to those with a lower fish consumption. We found a slightly higher PWV (β = 0.1, 95% CI = 0.0; 0.2, p for trend = 0.047) in children whose mothers had a higher consumption of canned tuna during the 1st trimester of pregnancy. Fish intake during pregnancy was found to be unrelated to the offspring’s cardiovascular health at 11 years of age. The beneficial cardiovascular effects of fish consumption during pregnancy on the offspring are still inconclusive.
Trichostatin C Synergistically Interacts with DNMT Inhibitor to Induce Antineoplastic Effect via Inhibition of Axl in Bladder and Lung Cancer Cells
Authors: Wang Chenyin , Lei Lijuan , Xu Yang , Li Yan , Zhang Jing , Xu Yanni , Si Shuyi
Published: March 2024

Aberrant epigenetic modifications are fundamental contributors to the pathogenesis of various cancers. Consequently, targeting these aberrations with small molecules, such as histone deacetylase (HDAC) inhibitors and DNA methyltransferase (DNMT) inhibitors, presents a viable strategy for cancer therapy. The objective of this study is to assess the anti-cancer efficacy of trichostatin C (TSC), an analogue of trichostatin A sourced from the fermentation of Streptomyces sp. CPCC 203909. Our investigations reveal that TSC demonstrates potent activity against both human lung cancer and urothelial bladder cancer cell lines, with IC50 values in the low micromolar range. Moreover, TSC induces apoptosis mediated by caspase 3/7 and arrests the cell cycle at the G2/M phase. When combined with the DNMT inhibitor decitabine, TSC exhibits a synergistic anti-cancer effect. Additionally, protein analysis elucidates a significant reduction in the expression of the tyrosine kinase receptor Axl. Notably, elevated concentrations of TSC correlate with the up-regulation of the transcription factor forkhead box class O1 (FoxO1) and increased levels of the proapoptotic proteins Bim and p21. In conclusion, our findings suggest TSC as a promising anti-cancer agent with HDAC inhibitory activity. Furthermore, our results highlight the potential utility of TSC in combination with DNMT inhibitors for cancer treatment.
AmBisome® Formulations for Pediatrics: Stability, Cytotoxicity, and Cost-Effectiveness Studies
Authors: Zuccari Guendalina , Villa Carla , Iurilli Valentina , Barabino Paola , Zorzoli Alessia , Marimpietri Danilo , Caviglia Debora , Russo Eleonora
Published: March 2024

Liposomal amphotericin B (Ambisome®) is the gold standard for the treatment and prevention of fungal infections both in the adult and pediatric populations. The lyophilized dosage form has to be reconstituted and diluted by hospital staff, but its management can be challenging due to the spontaneous tendency of amphotericin B to form aggregates with different biological activity. In this study, the colloidal stability of the liposomes and the chemical stability of amphotericin B were investigated over time at storage conditions. Three liposomal formulations of amphotericin B at 4.0 mg/mL, 2.0 mg/mL, and 0.2 mg/mL were prepared and assayed for changes regarding the dimensional distribution, zeta potential, drug aggregation state, and onset of by-products. Our analyses highlighted that the most diluted formulation, kept at room temperature, showed the greatest changes in the aggregation state of the drug and accordingly the highest cytotoxicity. These findings are clinically relevant since the lower dosages are addressed to the more vulnerable patients. Therefore, the centralization of the dilution of AmBisome® at the pharmacy is of fundamental importance for assuring patient safety, and at the same time for reducing medication waste, as we demonstrated using the cost-saving analysis of drug expense per therapy carried out at the G. Gaslini children hospital.
Recent Advances in Alginate-Based Hydrogels for Cell Transplantation Applications
Authors: Kavand Alireza , Noverraz François , Gerber-Lemaire Sandrine
Published: March 2024

With its exceptional biocompatibility, alginate emerged as a highly promising biomaterial for a large range of applications in regenerative medicine. Whether in the form of microparticles, injectable hydrogels, rigid scaffolds, or bioinks, alginate provides a versatile platform for encapsulating cells and fostering an optimal environment to enhance cell viability. This review aims to highlight recent studies utilizing alginate in diverse formulations for cell transplantation, offering insights into its efficacy in treating various diseases and injuries within the field of regenerative medicine.
Irrational Use of Medications among Adults with Insomnia: An Observational Study at a Sleep Clinic in Mexico
Authors: Carvalho-Silva Lucelya , Jiménez-Correa Ulises , Santana-Miranda Rafael , Heyerdahl-Viau Ivo , Benitez-Morales Jonatan , García-Casas Mireya , Martínez-Núñez Juan Manuel
Published: March 2024

Background: To determine the patterns of irrational use of medications among a sample of adult patients with insomnia. Methods: We included 89 adult patients diagnosed with chronic insomnia who had consumed medications for this disorder during the 12 months prior to admission to a specialized Sleep Disorders Clinic (SDC) in Mexico City. With a 13-item survey, information was gathered on patterns of medication use and irrational use, considering therapeutic indications, dose, route of administration, and duration of treatment. Results: The participants had taken hypnotics (65%), antidepressants (21%), anticonvulsants (8%), and antipsychotics (6%), and 92% had irrational use of their medication. Irrational use was greatest with benzodiazepines and antipsychotics. There were two main types of irrational use: (1) 47% of participants had consumed a drug unsuitable for their condition, although it was almost always prescribed by a doctor, and (2) 43% had consumed a drug for longer than the maximum time recommended. Conclusion: It is worrisome to find that the irrational use of medications to treat insomnia, especially benzodiazepines and antipsychotics is widespread. Although most participants had acquired their medication by prescription, for many the drug was inappropriate to treat their condition. It should be mandatory that patients with insomnia receive specialized medical attention in primary clinical care.
A Theory of Best Choice Selection through Objective Arguments Grounded in Linear Response Theory Concepts
Authors: Ausloos Marcel , Rotundo Giulia , Cerqueti Roy
Published: March 2024

In this study, we propose how to use objective arguments grounded in statistical mechanics concepts in order to obtain a single number, obtained after aggregation, which would allow for the ranking of “agents”, “opinions”, etc., all defined in a very broad sense. We aim toward any process which should a priori demand or lead to some consensus in order to attain the presumably best choice among many possibilities. In order to specify the framework, we discuss previous attempts, recalling trivial means of scores—weighted or not—Condorcet paradox, TOPSIS (Technique for Order Preference by Similarity to Ideal Solution), etc. We demonstrate, through geometrical arguments on a toy example and with four criteria, that the pre-selected order of criteria in previous attempts makes a difference in the final result. However, it might be unjustified. Thus, we base our “best choice theory” on the linear response theory in statistical physics: we indicate that one should be calculating correlations functions between all possible choice evaluations, thereby avoiding an arbitrarily ordered set of criteria. We justify the point through an example with six possible criteria. Applications in many fields are suggested. Furthermore, two toy models, serving as practical examples and illustrative arguments are discussed.
Phytochemical Profiles of Plant Materials: From Extracts to Added-Value Ingredients
Authors: Raudone Lina , Savickiene Nijole
Published: March 2024

In the scientific research on medicinal and food plants, studying phytochemical profiles in plant materials has gained increasing attention over the years [...]
Separation Methods of Phenolic Compounds from Plant Extract as Antioxidant Agents Candidate
Authors: Susanti Ike , Pratiwi Rimadani , Rosandi Yudi , Hasanah Aliya Nur
Published: March 2024

In recent years, discovering new drug candidates has become a top priority in research. Natural products have proven to be a promising source for such discoveries as many researchers have successfully isolated bioactive compounds with various activities that show potential as drug candidates. Among these compounds, phenolic compounds have been frequently isolated due to their many biological activities, including their role as antioxidants, making them candidates for treating diseases related to oxidative stress. The isolation method is essential, and researchers have sought to find effective procedures that maximize the purity and yield of bioactive compounds. This review aims to provide information on the isolation or separation methods for phenolic compounds with antioxidant activities using column chromatography, medium-pressure liquid chromatography, high-performance liquid chromatography, counter-current chromatography, hydrophilic interaction chromatography, supercritical fluid chromatography, molecularly imprinted technologies, and high-performance thin layer chromatography. For isolation or purification, the molecularly imprinted technologies represent a more accessible and more efficient procedure because they can be applied directly to the extract to reduce the complicated isolation process. However, it still requires further development and refinement.
Comparative Analysis of the Effects of Incorporating Post-Industrial Recycled LLDPE and Post-Consumer PE in Films: Macrostructural and Microstructural Perspectives in the Packaging Industry
Authors: Ballestar de las Heras Ricardo , Colom Xavier , Cañavate Javier
Published: March 2024

In accordance with the Circular Economy Package of the European directive, the Spanish government compels manufacturers of plastic bags to include into their products a minimum of 70% of polyethylene (PE) waste. Following this mandate can be challenging and requires a deep knowledge of the alterations produced by the recycling in the main components of a plastic bag film: lineal low-density polyethylene (LLDPE), the LLDPE recycled post-industry, generated as waste from an industrial process (rLLDPE) and the PE recycled from post-consumer use (rPE), that has been picked up, cleaned, and reprocessed. This study provides insight in the macro and microstructural changes produced by several cycles of recycling in these materials. Specimens in the form of film for supermarket bags formed with these polymers have been subjected to several recycling sequences. The process closely mimics industrial processes. Four cycles have been applied to the samples. The evolution of mechanical properties, including tensile strength, elongation at break, and tear and impact tests, shows an obvious decrease due to degradation that is not an impediment for practical use after the four cycles of recycling according to the main specifications defined by the producer. Colorimetric measurements reveal no significant variations in the color of the films. The results of the FTIR and TGA analysis show degradation phenomena and changes in crystallinity in branching and the apparition of crosslinking that are in consonance with the mechanical data. There is also a difference between both types of recycled PE. In general, rLLDPE is more affected by the recycling than rPE. According to our findings, the limiting property would be the tearing. By comparing these values with bags available in the market, manufactured from 70–80% recycled material, we can infer that while two reprocessing cycles can lead to good results, a maximum of four cycles of recycling is advisable.
Modeling Internal Flow Patterns of Sessile Droplets on Horizontally Vibrating Substrates
Authors: Shan Yanguang , Yin Tianyi
Published: March 2024

A three-dimensional Navier–Stokes and continuity equation model is employed to numerically predict the resonant modes of sessile droplets on horizontally vibrating substrates. A dynamic contact angle model is implemented to simulate the contact angle variations during vibrations. The four resonant modes (n = 1, 2, 3 and 4) of a droplet under horizontal vibrations are investigated. Simulations are compared to experimental results for validation. Excellent agreement is observed between predicted results and experiments. The model is used to simulate the internal flow patterns within the droplet under resonant modes. It is found that the flow in all four resonant modes can be divided into the Stokes region, the gas–liquid interface region, and the transition region located in between. Numerical simulations show that the average velocity within the droplet increases with the increase in frequency, while the fluctuations in average velocity after reaching the steady state show different trends with the increase in frequency. It is also found that with an increase in the order of resonant modes, the contact angle difference between the two sides of the droplet increases, and the contact angle difference of the droplet is maximized when the applied frequency is the resonant frequency of the specified mode.
Synthesis of Integrated Material with Activation and Oxidation Functions by Mechanical Milling of Activated Carbon and Persulfate for Enhanced Tetracycline Degradation over Non-Radical Mechanism
Authors: Tan Peng , Meng Nuo , Cao Xuxin , Zhang Xiguo , Huang Yuanyuan , Li Tielong , Wang Wei
Published: March 2024

As an alternative to the traditional advanced oxidation process of adding potassium persulfate (PS) and its activator to the solution separately, in this study, M(AC-PS), an integrated activator and catalyst, was synthesized by vacuum ball milling of PS and activated carbon (AC) to improve the PS’s utilization efficiency. The joint mechanical milling caused a change in the preferentially exposed crystal surface of the PS and the generation of more π-π* structures on the AC, leading to successful and stable connection of the PS onto the surface of the AC. Within 40 min, the M(AC-PS) achieved a degradation rate of 97.3% for tetracycline (TC, 20 mg/L), while the mixed system where AC and PS were separately ball milled achieved only a 53.1% removal of TC. Reactive oxygen species and electrochemical tests showed that M(AC-PS) mainly oxidized TC through non-free radical mechanisms. In M(AC-PS), AC provided oxygen-containing functional groups (e.g., C=O) to activate the PS and electron holes as an electron transfer medium, generating 1O2 and promoting electron donation from the TC to enhance the oxidation of the TC. Almost no catalytic components were detected in the solution, indicating that the obtained solid composite material avoids the limitations of solid–liquid interface contact and mass transfer, and then improves the efficiency of activation and catalysis. This study presents a simple and feasible method for obtaining efficient and convenient material for the advanced oxidation treatment of wastewater.
“Christ Is Speaking”: The Psalms as the Grammar of Augustine’s Sermons
Authors: Love Matthew D.
Published: March 2024

The Psalms saturated Augustine’s sermons. He believed they were God’s words to the church as inspired Scripture, and the church’s words to God as prayer and praise. In the Psalms, he saw kenosis, the downward-directed God in Christ who emptied himself to take on human nature to stand in solidarity with the church and creation. He saw, too, the possibility of deification, the upward-directed church in Christ raised to share in the divine nature. Furthermore, Augustine believed that Christ himself spoke in the Psalms so that in them the church could hear his voice and come to know its own voice. In this essay, I examine why Augustine cherished the Psalms, and I consider how this might inspire contemporary preachers to cherish them and preach them. Moreover, I offer Augustine’s Christocentric preaching of the Psalms as a paradigm for how preachers might facilitate Christological formation among their congregants.
West Nile Virus Meningoencephalitis—A Consideration for Earlier Investigation
Authors: Burns David , Vinton Zachary , Chung Min Kyung , Cheng Johnny
Published: March 2024

West Nile Virus (WNV) is an arbovirus endemic to many countries and has caused over 56,000 cases, with 2776 deaths in the U.S. from 1999 to 2022. WNV occurs most often in the fall, typically affecting elderly populations in states like Nebraska and Arizona. Currently, supportive care is the only management for WNV. Our case is a female patient in her mid-70s in an intermountain state who presented in the fall with WNV meningoencephalitis and experienced a delay in care due to the unique clinical presentation. This demonstrates the importance of early inclusion of WNV in the differential for altered mental status, especially with WNV risk factors, and expedition of supportive care. Doing so could potentially reduce antibiotic duration and hospital costs.
Arctic Greening Trends: Change Points in Satellite-Derived Normalized Difference Vegetation Indexes and Their Correlation with Climate Variables over the Last Two Decades
Authors: Seo Minji , Kim Hyun-Cheol
Published: March 2024

In this study, we utilized NDVI data from the moderate resolution imaging spectroradiometer (MODIS) alongside climatic variables obtained from a reanalyzed dataset to analyze Arctic greening during the summer months (June–September) of the last two decades. This investigation entailed a detailed analysis of these changes across various temporal scales. The data indicated a continuous trend of Arctic greening, evidenced by a 1.8% per decade increment in the NDVI. Notably, significant change points were identified in June 2012 and September 2013. A comparative assessment of NDVI pre- and post-these inflection points revealed an elongation of the Arctic greening trend. Furthermore, an anomalous increase in NDVI of 2% per decade was observed, suggesting an acceleration in greening. A comprehensive analysis was conducted to decipher the correlation between NDVI, temperature, and energy budget parameters to elucidate the underlying causes of these change points. Although the correlation between these variables was relatively low throughout the summer months, a distinct pattern emerged when these periods were dissected and examined in the context of the identified change points. Preceding the change point, a strong correlation (approximately 0.6) was observed between all variables; however, this correlation significantly diminished after the change point, dropping to less than half. This shift implies an introduction of additional external factors influencing the Arctic greening trend after the change point. Our findings provide foundational data for estimating the tipping point in Arctic terrestrial ecosystems. This is achieved by integrating the observed NDVI change points with their relationship with climatic variables, which are essential in comprehensively understanding the dynamics of Arctic climate change, particularly with alterations in tundra vegetation.
A Survey of Seafloor Characterization and Mapping Techniques
Authors: Loureiro Gabriel , Dias André , Almeida José , Martins Alfredo , Hong Sup , Silva Eduardo
Published: March 2024

The deep seabed is composed of heterogeneous ecosystems, containing diverse habitats for marine life. Consequently, understanding the geological and ecological characteristics of the seabed’s features is a key step for many applications. The majority of approaches commonly use optical and acoustic sensors to address these tasks; however, each sensor has limitations associated with the underwater environment. This paper presents a survey of the main techniques and trends related to seabed characterization, highlighting approaches in three tasks: classification, detection, and segmentation. The bibliography is categorized into four approaches: statistics-based, classical machine learning, deep learning, and object-based image analysis. The differences between the techniques are presented, and the main challenges for deep sea research and potential directions of study are outlined.
A No-Reference Quality Assessment Method for Hyperspectral Sharpened Images via Benford’s Law
Authors: Hao Xiankun , Li Xu , Wu Jingying , Wei Baoguo , Song Yujuan , Li Bo
Published: March 2024

In recent years, hyperspectral (HS) sharpening technology has received high attention and HS sharpened images have been widely applied. However, the quality assessment of HS sharpened images has not been well addressed and is still limited to the use of full-reference quality evaluation. In this paper, a novel no-reference quality assessment method based on Benford’s law for HS sharpened images is proposed. Without a reference image, the proposed method detects fusion distortion by performing first digit distribution on three quality perception features in HS sharpened images, using the standard Benford’s law as a benchmark. The experiment evaluates 10 HS fusion methods on three HS datasets and selects four full-reference metrics and four no-reference metrics to compare with the proposed method. The experimental results demonstrate the superior performance of the proposed method.
The Synchrosqueezed Method and Its Theory-Analysis-Based Novel Short-Time Fractional Fourier Transform for Chirp Signals
Authors: Li Zhen , Gao Zhaoqi , Chen Liang , Gao Jinghuai , Xu Zongben
Published: March 2024

Time–frequency analysis is an important tool used for the processing and interpretation of non-stationary signals, such as seismic data and remote sensing data. In this paper, based on the novel short-time fractional Fourier transform (STFRFT), a new modified STFRFT is first proposed which can also generalize the properties of the modified short-time Fourier transform (STFT). Then, in the modified STFRFT domain, we derive the instantaneous frequency estimator for the chirp signal and present a new type of synchrosqueezing STFRFT (FRSST). The proposed FRSST presents many results similar to those of the synchrosqueezing STFT (FSST), and it extends the harmonic signal to a chirp signal that offers attractive new features. Furthermore, we provide a detailed analysis of the signal reconstruction, theories, and some properties of the proposed FRSST. Several experiments are conducted, and all of the results illustrate that the proposed FRSST is more effective than the FSST. Finally, based on the linear amplitude modulation and frequency modulation signal, we present a derivation for analyzing the limitations of the FRSST.
Comparison of Point Cloud Registration Techniques on Scanned Physical Objects
Authors: Denayer Menthy , De Winter Joris , Bernardes Evandro , Vanderborght Bram , Verstraten Tom
Published: March 2024

This paper presents a comparative analysis of six prominent registration techniques for solving CAD model alignment problems. Unlike the typical approach of assessing registration algorithms with synthetic datasets, our study utilizes point clouds generated from the Cranfield benchmark. Point clouds are sampled from existing CAD models and 3D scans of physical objects, introducing real-world complexities such as noise and outliers. The acquired point cloud scans, including ground-truth transformations, are made publicly available. This dataset includes several cleaned-up scans of nine 3D-printed objects. Our main contribution lies in assessing the performance of three classical (GO-ICP, RANSAC, FGR) and three learning-based (PointNetLK, RPMNet, ROPNet) methods on real-world scans, using a wide range of metrics. These include recall, accuracy and computation time. Our comparison shows a high accuracy for GO-ICP, as well as PointNetLK, RANSAC and RPMNet combined with ICP refinement. However, apart from GO-ICP, all methods show a significant number of failure cases when applied to scans containing more noise or requiring larger transformations. FGR and RANSAC are among the quickest methods, while GO-ICP takes several seconds to solve. Finally, while learning-based methods demonstrate good performance and low computation times, they have difficulties in training and generalizing. Our results can aid novice researchers in the field in selecting a suitable registration method for their application, based on quantitative metrics. Furthermore, our code can be used by others to evaluate novel methods.
Hybrid Precision Floating-Point (HPFP) Selection to Optimize Hardware-Constrained Accelerator for CNN Training
Authors: Junaid Muhammad , Aliev Hayotjon , Park SangBo , Kim HyungWon , Yoo Hoyoung , Sim Sanghoon
Published: March 2024

The rapid advancement in AI requires efficient accelerators for training on edge devices, which often face challenges related to the high hardware costs of floating-point arithmetic operations. To tackle these problems, efficient floating-point formats inspired by block floating-point (BFP), such as Microsoft Floating Point (MSFP) and FlexBlock (FB), are emerging. However, they have limited dynamic range and precision for the smaller magnitude values within a block due to the shared exponent. This limits the BFP’s ability to train deep neural networks (DNNs) with diverse datasets. This paper introduces the hybrid precision (HPFP) selection algorithms, designed to systematically reduce precision and implement hybrid precision strategies, thereby balancing layer-wise arithmetic operations and data path precision to address the shortcomings of traditional floating-point formats. Reducing the data bit width with HPFP allows more read/write operations from memory per cycle, thereby decreasing off-chip data access and the size of on-chip memories. Unlike traditional reduced precision formats that use BFP for calculating partial sums and accumulating those partial sums in 32-bit Floating Point (FP32), HPFP leads to significant hardware savings by performing all multiply and accumulate operations in reduced floating-point format. For evaluation, two training accelerators for the YOLOv2-Tiny model were developed, employing distinct mixed precision strategies, and their performance was benchmarked against an accelerator utilizing a conventional brain floating point of 16 bits (Bfloat16). The HPFP selection, employing 10 bits for the data path of all layers and for the arithmetic of layers requiring low precision, along with 12 bits for layers requiring higher precision, results in a 49.4% reduction in energy consumption and a 37.5% decrease in memory access. This is achieved with only a marginal mean Average Precision (mAP) degradation of 0.8% when compared to an accelerator based on Bfloat16. This comparison demonstrates that the proposed accelerator based on HPFP can be an efficient approach to designing compact and low-power accelerators without sacrificing accuracy.
Method for Identification of Aberrations in Operational Data of Maritime Vessels and Sources Investigation
Authors: Cai Jie , Lützen Marie , John Adeline Crystal , Petersen Jakob Buus , Rytter Niels Gorm Maly
Published: March 2024

Sensing data from vessel operations are of great importance in reflecting operational performance and facilitating proper decision-making. In this paper, statistical analyses of vessel operational data are first conducted to compare manual noon reports and autolog data from sensors. Then, new indicators to identify data aberrations are proposed, which are the errors between the reported values from operational data and the expected values of different parameters based on baseline models and relevant sailing conditions. A method to detect aberrations based on the new indicators in terms of the reported power is then investigated, as there are two independent measured power values. In this method, a sliding window that moves forward along time is implemented, and the coefficient of variation (CV) is calculated for comparison. Case studies are carried out to detect aberrations in autolog and noon data from a commercial vessel using the new indicator. An analysis to explore the source of the deviation is also conducted, aiming to find the most reliable value in operations. The method is shown to be effective for practical use in detecting aberrations, having been initially tested on both autolog and noon report from four different commercial vessels in 14 vessel years. Approximately one triggered period per vessel per year with a conclusive deviation source is diagnosed by the proposed method. The investigation of this research will facilitate a better evaluation of operational performance, which is beneficial to both the vessel operators and crew.
Embeddable Chloride Sensor for Monitoring Chloride Penetration into Cement Mortar
Authors: Zhang Min , Fu Hua , Tian Li , Du Zhenxing , Wang Penggang
Published: March 2024

A composite solid chloride sensor consisting of two single sensors, i.e., Ag/AgCl working electrode and Mn/MnO2 reference electrode, was developed. The Ag/AgCl electrode was prepared by the anodic polarization method, while the Mn/MnO2 reference electrode was prepared using the powder compaction technique. Then, the electrochemical performances such as stability, reproducibility, and sensitivity of the composite and single sensors were investigated in a saturated Ca(OH)2 solution and mortar specimen. A current density of 0.5 mA/cm2 and polarization time of 2.5 h were the optimal preparation parameters of the Ag/AgCl selective electrode. The Ag/AgCl selective electrode showed a linear potential response with the logarithm of chloride ion content in solution and had good stability, reproducibility, and anti-polarization performances. In addition, the Mn/MnO2 electrode exhibited potential stability after being activated in an alkaline solution for 60 days. The composite sensor demonstrated exceptional sensitivity to the Cl− content, boasting a slope of approximately 51.1 mV/decade, and showcased excellent stability in both solution and mortar specimens. In every measurement, the time needed for the potential of a composite sensor to become stable was less than 30 s. The sensor enables non-destructive in situ monitoring of the chloride ion content in cement mortar, thus realizing early warning of deterioration of reinforcement and guaranteeing long service life of the structure.
Range-Intensity-Profile-Guided Gated Light Ranging and Imaging Based on a Convolutional Neural Network
Authors: Xia Chenhao , Wang Xinwei , Sun Liang , Zhang Yue , Song Bo , Zhou Yan
Published: March 2024

Three-dimensional (3D) range-gated imaging can obtain high spatial resolution intensity images as well as pixel-wise depth information. Several algorithms have been developed to recover depth from gated images such as the range-intensity correlation algorithm and deep-learning-based algorithm. The traditional range-intensity correlation algorithm requires specific range-intensity profiles, which are hard to generate, while the existing deep-learning-based algorithm requires large number of real-scene training data. In this work, we propose a method of range-intensity-profile-guided gated light ranging and imaging to recover depth from gated images based on a convolutional neural network. In this method, the range-intensity profile (RIP) of a given gated light ranging and imaging system is obtained to generate synthetic training data from Grand Theft Auto V for our range-intensity ratio and semantic network (RIRS-net). The RIRS-net is mainly trained on synthetic data and fine-tuned with RIP data. The network learns both semantic depth cues and range-intensity depth cues in the synthetic data, and learns accurate range-intensity depth cues in the RIP data. In the evaluation experiments on both a real-scene and synthetic test dataset, our method shows a better result compared to other algorithms.
Essential Oil of Ocimum basilicum against Aedes aegypti and Culex quinquefasciatus: Larvicidal Activity of a Nanoemulsion and In Silico Study
Authors: de Sousa dos Santos Edla Lídia Vasques , Cruz Jorddy Neves , da Costa Glauber Vilhena , de Sá Ester Martins Félix , da Silva Alicia Karine Pereira , Fernandes Caio Pinho , de Faria Mota Oliveira Anna Eliza Maciel , Duarte Jonatas Lobato , Bezerra Roberto Messias , Tavares Josean Fechine , da Costa Tiago Silva , dos Anjos Ferreira Ricardo Marcelo , dos Santos Cleydson Breno Rodrigues , Souto Raimundo Nonato Picanço
Published: March 2024

Diseases transmitted by vectors such as Aedes aegypti and Culex quinquefasciatus (Diptera: Culicidae) have been responsible for endemics and epidemics in several countries, causing irreparable damage to human health. For this reason, vector control is one of the main strategies to prevent the contamination and dissemination of these etiological agents. In this study, the essential oil (EO) of Ocimum basilicum was obtained by hydrodistillation, and the compounds were identified by GC/MS. A nanoemulsion was obtained through a low-energy input method and evaluated by photon correlation spectroscopy. Bioassays were performed against 4th instar larvae of A. aegypti and C. quinquefasciatus. Furthermore, additional in silico studies of biological activity prediction and molecular docking for the acetylcholinesterase enzyme and juvenile hormone protein targets were performed with the 53 identified compounds of the EO. The major compounds identified in greater quantity were linalool (32.66%) and anethole (32.48%). The obtained nanoemulsion had an average size diameter between 244.6 and 280.4 nm and a polydispersity index below 0.250 during the entire storage period. The nanoemulsion was tested at concentrations of 10, 20, 30, 40, and 50 mg/L and the following activity values were observed: LC50 = 42.15 mg/L and 40.94 mg/L and LC90 = 50.35 mg/L and 48.87 mg/L for A. aegypti (24 h and 48 h); LC50 = 39.64 mg/L and 38.08 mg/L and LC90 = 52.58 mg/L and 54.26 mg/L for C. quinquefasciatus (24 h and 48 h). The in silico results showed better activity values for linalool, anethole, carvone, α-selinene, eugenol, and limonene. The α-selinene compound showed the best binding affinity with the insect acetylcholinesterase enzyme (−9.1 Kcal) in molecular docking, showing the importance of antagonist compounds in elucidating the mechanism of action for the investigated targets. Thus, the studied nanoemulsion was considered active against the tested species, becoming a potential alternative as an ecological bioinsecticide due to bioactivity and simplicity of formulation.
Comparing Attitudes toward Sexual Consent between Japan and Canada
Authors: Mukai Tomoya , Pioch Chantal , Sadamura Masahiro , Tozuka Karin , Fukushima Yui , Aizawa Ikuo
Published: March 2024

Japanese and Canadian laws regarding sexual assault vary in the degree to which they incorporate the concept of sexual consent, with Japanese law being less consent-oriented than Canadian law. Although the Japanese law has incorporated the concept of sexual consent in the 2023 amendment, the public understanding of the concept is still limited. Reflecting such difference, it could be expected that the general public in both countries also differ in their perceptions and attitudes regarding punishment of sexual crime and sexual consent. The present study aimed to test these expectations and further examine the mediational mechanism that explains the national difference between Japan and Canada. The data from 1125 Japanese and 1125 Canadian respondents showed that Japanese respondents were less likely to perceive the imposition of punishment on an alleged perpetrator described in scenarios as appropriate. In contrast, the difference in the perceived victim’s consent was significant only in three out of seven scenarios. The relation between nations (Japan vs. Canada) and perceived appropriateness of punishment was mediated by the perceived victim’s consent.
A Morphing-Based Future Scenario Generation Method for Stochastic Power System Analysis
Authors: Gao Yanna , Dong Hong , Hu Liujun , Lin Zihan , Zeng Fanhong , Ye Cantao , Zhang Jixiang
Published: March 2024

As multiple wind and solar photovoltaic farms are integrated into power systems, precise scenario generation becomes challenging due to the interdependence of power generation and future climate change. Future climate data derived from obsolete climate models, featuring diminished accuracy, less-refined spatial resolution, and a limited range of climate scenarios compared to more recent models, are still in use. In this paper, a morphing-based approach is proposed for generating future scenarios, incorporating the interdependence of power generation among multiple wind and photovoltaic farms using copula theory. The K-means method was employed for scenario generation. The results of our study indicate that the average annual variations in dry-bulb temperature (DBT), global horizontal irradiance (GHI), and wind speed (WS) are projected to increase by approximately 0.4 to 1.9 °C, 7.5 to 20.4 W/m2, and 0.3 to 1.7 m/s, respectively, in the forthcoming scenarios of the four considered Shared Socioeconomic Pathways (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5). It seems that accumulated maximum wind electricity output (WEO) and solar electricity output (SEO) will increase from 0.9% to 7.3% and 1.1% to 6.8%, respectively, in 2050.
Optimization of Ultrasonic-Assisted Extraction of Antioxidants in Apple Pomace (var. Belorusskoje malinovoje) Using Response Surface Methodology: Scope and Opportunity to Develop as a Potential Feed Supplement or Feed Ingredient
Authors: Malenica Dunja , Maciel Larissa Silva , Herodes Koit , Kass Marko , Bhat Rajeev
Published: March 2024

Apple pomace represents an underexploited source of bioactive compounds. This study examines the optimization of total phenolic content (TPC) and antioxidant extraction yield of apple pomace (variety: Belorusskoje malinovoje) using response surface methodology. The green extraction technique used was ultrasound-assisted extraction, and it was compared with conventional solvent extraction. The impact of extraction time and amplitude of ultrasound-assisted extraction on the yield of polyphenols and antioxidants has been evaluated. Total phenolic content was determined using an established TPC assay. The antioxidant activity of the apple pomace was determined using established assays 2,2-diphenyl-1-picrylhydrazyl (DPPH•) and 2,2′-azino-bis (3-ethylbenzothiazoline-6-sulfonic acid (ABTS•+). Furthermore, the potential of apple pomace as a feed material was explored by assessing its nutritional composition, vitamins, minerals, fatty acids, and amino acid content. The extraction of antioxidants and phenolic compounds was efficiently optimized using RSM. The optimal conditions for TPC and DPPH• analyses were achieved with an extraction time of 17.5 min and an ultrasound-assisted extraction amplitude of 20%. Optimal conditions for ABTS•+ were 5 min extraction time and 20% amplitude. Conventional and ultrasound-assisted extraction methods yielded comparable results. Moreover, apple pomace exhibits potential as a feed ingredient despite its modest protein content. This study contributes to the utilization of apple pomace by providing additional information on its antioxidant content and nutritional composition, thus contributing to its sustainable utilization in various industries, especially the livestock feed sector.
Elite Speech about Climate Change: Analysis of Sentiment from the United Nations Conference of Parties, 1995–2021
Authors: Mah Andrea , Song Eunkyung
Published: March 2024

The Conference of Parties (COP) is the longest running forum for international discussion of climate change and offers rich data in the form of speeches. Studying how elites have historically communicated about climate change can help us understand their approaches to address climate change. In this study, we analyzed 2493 COP statements from 1995 to 2021 to describe how sentiment is used, and to see whether specific issues associated with climate policy (adaptation, mitigation, financing, development, disasters) are discussed in particular sentiment contexts. Quantitative analysis (sentiment analysis with multi-level modelling) revealed that leaders expressed high levels of positive sentiment in these diplomatic statements, but also some negative sentiment. Over time, representatives at COP used more positive, angry, and fearful sentiments in speeches. Representatives of wealthier and more developed countries expressed themselves differently than those from less wealthy and developing countries. To examine sentiment surrounding policy issues we used embedding regression. Countries expressed different sentiments about adaptation, mitigation, and development depending on their development status, and about disasters depending on their wealth. Shifts in sentiment over time were observed when results were plotted graphically, and these shifts may be related to specific events and agreements. Using these two approaches, we highlight how those with the power to make top-down changes to address climate change have historically talked about this issue.
Statistical and Spatial Analysis of Large Truck Crashes in Texas (2017–2021)
Authors: Billah Khondoker , Sharif Hatim O. , Dessouky Samer
Published: March 2024

Freight transportation, dominated by trucks, is an integral part of trade and production in the USA. Given the prevalence of large truck crashes, a comprehensive investigation is imperative to ascertain the underlying causes. This study analyzed 2017–2021 Texas crash data to identify factors impacting large truck crash rates and injury severity and to locate high-risk zones for severe incidents. Logistic regression models and bivariate analysis were utilized to assess the impacts of various crash-related variables individually and collectively. Heat maps and hotspot analysis were employed to pinpoint areas with a high frequency of both minor and severe large truck crashes. The findings of the investigation highlighted night-time no-passing zones and marked lanes as primary road traffic control, highway or FM roads, a higher posted road speed limit, dark lighting conditions, male and older drivers, and curved road alignment as prominent contributing factors to large truck crashes. Furthermore, in cases where the large truck driver was determined not to be at fault, the likelihood of severe collisions significantly increased. The study’s findings urge policymakers to prioritize infrastructure improvements like dual left-turn lanes and extended exit ramps while advocating for wider adoption of safety technologies like lane departure warnings and autonomous emergency braking. Additionally, public awareness campaigns aimed at reducing distracted driving and drunk driving, particularly among truck drivers, could significantly reduce crashes. By implementing these targeted solutions, we can create safer roads for everyone in Texas.