bluuebunny/crossref_metadata_2025 huggingface dataset:
Socioeconomic and Governance Factors Disentangle the Relationship between Temperature and Antimicrobial Resistance: A 10-Year Ecological Analysis of European Countries
Authors: Maugeri Andrea , Barchitta Martina , Magnano San Lio Roberta , Agodi Antonella
Published: April 2023

Although previous studies showed that warmer temperatures may be associated with increased antimicrobial resistance (AMR) rates, unmeasured factors may explain the observed relationship. We conducted a ten-year ecological analysis to evaluate whether temperature change was associated with AMR across 30 European countries, considering predictors that can determine a geographical gradient. Using four data sources, we created a dataset of: annual temperature change (FAOSTAT database); AMR proportions for ten pathogen–antibiotic combinations (ECDC atlas); consumption of antibiotics for systemic use in the community (ESAC-Net database); population density, gross domestic product (GDP) per capita, and governance indicators (World Bank DataBank). Data were obtained for each country and year (2010–2019) and analyzed through multivariable models. We found evidence of a positive linear association between temperature change and AMR proportion across all countries, years, pathogens, and antibiotics (β = 0.140; 95%CI = 0.039; 0.241; p = 0.007), adjusting for the effect of covariates. However, when GDP per capita and the governance index were included in the multivariable model, temperature change was no longer associated with AMR. Instead, the main predictors were antibiotic consumption (β = 0.506; 95%CI = 0.366; 0.646; p < 0.001), population density (β = 0.143; 95%CI = 0.116; 0.170; p < 0.001), and the governance index (β = −1.043; 95%CI = −1.207; −0.879; p < 0.001). Ensuring the appropriate use of antibiotics and improving governance efficiency are the most effective ways of counteracting AMR. It is necessary to conduct further experimental studies and obtain more detailed data to investigate whether climate change affects AMR.
Evaluation of a Pediatric Community-Acquired Pneumonia Antimicrobial Stewardship Intervention at an Academic Medical Center
Authors: Puzz Lauren , Plauche Emily A. , Cretella David A. , Harrison Virginia A. , Wingler Mary Joyce B.
Published: April 2023

(1) Background: Pneumonia is the leading diagnosis associated with antibiotic use in hospitalized children. The Infectious Diseases Society of America published pediatric community-acquired pneumonia (CAP) guidelines in 2011, but adherence to recommendations varies across institutions. The purpose of this study was to evaluate the impact of an antimicrobial stewardship intervention on antibiotic prescribing in pediatric patients admitted to an academic medical center. (2) Methods: This single-center pre/post-intervention evaluation included children admitted for CAP during three time periods (pre-intervention and post-intervention groups 1 and 2). The primary outcomes were changes in inpatient antibiotic selection and duration following the interventions. Secondary outcomes included discharge antibiotic regimens, length of stay, and 30-day readmission rates. (3) Results: A total of 540 patients were included in this study. Most patients were under five years of age (69%). Antibiotic selection significantly improved, with prescriptions for ceftriaxone decreasing (p < 0.001) and ampicillin increasing (p < 0.001) following the interventions. Antibiotic duration decreased from a median of ten days in the pre-intervention group and post-intervention group 1 to eight days in post-intervention group 2. (4) Conclusions: Our antibiotic stewardship intervention directed at pediatric CAP treatment resulted in improved antibiotic prescriptions and provides data that can be used to further educate providers at our institution.
Clinical Diagnostics of Bacterial Infections and Their Resistance to Antibiotics—Current State and Whole Genome Sequencing Implementation Perspectives
Authors: Avershina Ekaterina , Khezri Abdolrahman , Ahmad Rafi
Published: April 2023

Antimicrobial resistance (AMR), defined as the ability of microorganisms to withstand antimicrobial treatment, is responsible for millions of deaths annually. The rapid spread of AMR across continents warrants systematic changes in healthcare routines and protocols. One of the fundamental issues with AMR spread is the lack of rapid diagnostic tools for pathogen identification and AMR detection. Resistance profile identification often depends on pathogen culturing and thus may last up to several days. This contributes to the misuse of antibiotics for viral infection, the use of inappropriate antibiotics, the overuse of broad-spectrum antibiotics, or delayed infection treatment. Current DNA sequencing technologies offer the potential to develop rapid infection and AMR diagnostic tools that can provide information in a few hours rather than days. However, these techniques commonly require advanced bioinformatics knowledge and, at present, are not suited for routine lab use. In this review, we give an overview of the AMR burden on healthcare, describe current pathogen identification and AMR screening methods, and provide perspectives on how DNA sequencing may be used for rapid diagnostics. Additionally, we discuss the common steps used for DNA data analysis, currently available pipelines, and tools for analysis. Direct, culture-independent sequencing has the potential to complement current culture-based methods in routine clinical settings. However, there is a need for a minimum set of standards in terms of evaluating the results generated. Additionally, we discuss the use of machine learning algorithms regarding pathogen phenotype detection (resistance/susceptibility to an antibiotic).
New Antimicrobial Resistance Strategies: An Adaptive Resistance Network Conferring Reduced Glycopeptide Susceptibility in VISA
Authors: Aguglia Elvira , Chines Eleonora , Stefani Stefania , Cafiso Viviana
Published: April 2023

Background: Vancomycin-intermediate Staphylococcus aureus (VISA) emerges typically in the healthcare-associated methicillin-resistant S. aureus and more rarely in community-acquired S. aureus (CA-MRSA). VISA is a serious concern for public health due to its association with persistent infections, the failure of vancomycin treatment, and poor clinical outcomes. Currently, the burden of VISA is somewhat high, even though vancomycin is the mainstay treatment for severe MRSA infections. The molecular mechanisms of reduced glycopeptide susceptibility in S. aureus are constantly under investigation but have still not yet been fully characterized. Methods: Our goal was to investigate the reduced glycopeptide susceptibility mechanisms emerging in a VISA CA-MRSA versus its vancomycin-susceptible (VSSA) CA-MRSA parents in a hospitalized patient undergoing glycopeptide treatment. Comparative integrated omics, Illumina MiSeq whole-genome sequencing (WGS), RNA-Seq, and bioinformatics were performed. Results: Through a comparison of VISA CA-MRSA vs. its VSSA CA-MRSA parent, mutational and transcriptomic adaptations were found in a pool of genes involved, directly or indirectly, in the biosynthesis of the glycopeptide target conferring or supporting the VISA phenotype, and its cross-resistance with daptomycin. This pool included key genes responsible for the biosynthesis of the peptidoglycan precursors, i.e., D-Ala, the D-Ala-D-Ala dipeptide termini of the pentapeptide, and its incorporation in the nascent pentapeptide, as key targets of the glycopeptide resistance. Furthermore, accessory glycopeptide-target genes involved in the pathways corroborated the key adaptations, and thus, supported the acquisition of the VISA phenotype i.e., transporters, nucleotide metabolism genes, and transcriptional regulators. Finally, transcriptional changes were also found in computationally predicted cis-acting small antisense RNA triggering genes related both to the key or accessory adaptive pathways. Conclusion: Our investigation describes an adaptive resistance pathway acquired under antimicrobial therapy conferring reduced glycopeptide susceptibility in a VISA CA-MRSA due to a comprehensive network of mutational and transcriptional adaptations in genes involved in pathways responsible for the biosynthesis of glycopeptide’s target or supporters of the key resistance path.
Influence of Increased Radiation Background on Antioxidative Responses of Helianthus tuberosus L.
Authors: Polivanova Oksana B. , Tiurin Kirill N. , Sivolapova Anastasia B. , Goryunova Svetlana V. , Zhevora Sergey V.
Published: April 2023

As a result of the accident at the Chornobyl Nuclear Power Plant, significant territories were exposed to ionizing radiation. Some isotopes, such as 137Cs, are capable of making a significant impact on living organisms in the long-term perspective. The generation of reactive oxygen species is one mechanism by which ionizing radiation affects living organisms, initiating mechanisms of antioxidant protection. In this article, the effect of increased ionizing radiation on the content of non–enzymatic antioxidants and the activity of antioxidant defense enzymes of Helianthus tuberosum L. was studied. This plant is widely distributed in Europe and characterized by high adaptability to abiotic factors. We found that the activity of antioxidant defense enzymes, such as catalase and peroxidase, weakly correlated with radiation exposure. The activity of ascorbate peroxidase, on the contrary, is strongly positively correlated with radiation exposure. The samples growing on the territory with constant low exposure to ionizing radiation were also characterized by an increased concentration of ascorbic acid and water-soluble phenolic compounds compared to the controls. This study may be useful for understanding the mechanisms underlying the adaptive reactions of plants under prolonged exposure to ionizing radiation.
Numerical Investigation on Aerodynamics of a Rectangular Blade Rotor under Mars Air Conditions Using Large Eddy Simulation
Authors: Huang Jie , Huang Daqing , Chen Tao , Li Hongda
Published: April 2023

The study of the aerodynamics of a flight vehicle under Martian air conditions is experimentally difficult due to its characteristics such as low air density and temperature, making the vehicle operate at an ultra-low Reynolds number, which in turn introduces a complex flow field. In this paper, to find a proper computational fluid dynamics (CFD) method with which to better understand the aerodynamics of rotor-type aircraft under Martian air conditions, the aerodynamic performance of a rotor with rectangular blades under ultra-low density Martian air conditions is studied. A simulation scheme using a large eddy simulation solver and sliding meshing technology is established, and the method is verified based on experimental results from a Mars Air Simulator (MAS). In addition, the influence of the test bench and chamber is investigated through flow field analysis. The results show that the established method can predict lift in a very accurate manner, but that the torque prediction is not so promising. The study also determines that the fixture and the chamber wall of an MAS has little influence on the prediction of aerodynamic performance due to the quickly decreasing of flow speed and dissipation of vortexes. The test bench has about 5% influence on lift prediction, possibly due to the ground effect of the bench. In addition, simulation under actual Martian air conditions shows that the results agree well with the MAS experiment’s results, indicating that the temperature difference has little influence on the lift performance, and therefore that the MAS is a good tool for the lift prediction of Martian helicopters.
Evaluation of an Eye-Tracking-Based Method for Assessing the Visual Performance with Progressive Lens Designs
Authors: Concepcion-Grande Pablo , Chamorro Eva , Cleva José Miguel , Alonso José , Gómez-Pedrero Jose A.
Published: April 2023

Due to the lack of sensitivity of visual acuity (VA) measurement to quantify differences in visual performance between progressive power lenses (PPLs), in this study, we propose and evaluate an eye-tracking-based method to assess visual performance when wearing PPLs. A wearable eye-tracker system (Tobii-Pro Glasses 3) recorded the pupil position of 27 PPL users at near and distance vision during a VA test while wearing three PPL designs: a PPL for general use (PPL-Balance), a PPL optimized for near vision (PPL-Near), and a PPL optimized for distance vision (PPL-Distance). The participants were asked to recognize eye charts at both near and distance vision using centered and oblique gaze directions with each PPL design. The results showed no statistically significant differences between PPLs for VA. However, significant differences in eye-tracking parameters were observed between PPLs. Furthermore, PPL-Distance had a lower test duration, complete fixation time, and number of fixations at distance evaluation. PPL-Near has a lower test duration, complete fixation time, and number of fixations for near vision. In conclusion, the quality of vision with PPLs can be better characterized by incorporating eye movement parameters than the traditional evaluation method.
Ontology with Deep Learning for Forest Image Classification
Authors: Kwenda Clopas , Gwetu Mandlenkosi , Fonou-Dombeu Jean Vincent
Published: April 2023

Most existing approaches to image classification neglect the concept of semantics, resulting in two major shortcomings. Firstly, categories are treated as independent even when they have a strong semantic overlap. Secondly, the features used to classify images into different categories can be the same. It has been demonstrated that the integration of ontologies and semantic relationships greatly improves image classification accuracy. In this study, a hybrid ontological bagging algorithm and an ensemble technique of convolutional neural network (CNN) models have been developed to improve forest image classification accuracy. The ontological bagging approach learns discriminative weak attributes over multiple learning instances, and the bagging concept is adopted to minimize the error propagation of the classifiers. An ensemble of ResNet50, VGG16, and Xception models is used to generate a set of features for the classifiers trained through an ontology to perform the image classification process. To the authors’ best knowledge, there are no publicly available datasets for forest-type images; hence, the images used in this study were obtained from the internet. Obtained images were put into eight categories, namely: orchards, bare land, grassland, woodland, sea, buildings, shrubs, and logged forest. Each category comprised 100 images for training and 19 images for testing; thus, in total, the dataset contained 800 images for training and 152 images for testing. Our ensemble deep learning approach with an ontology model was successfully used to classify forest images into their respective categories. The classification was based on the semantic relationship between image categories. The experimental results show that our proposed model with ontology outperformed other baseline classifiers without ontology with 96% accuracy and the lowest root-mean-square error (RMSE) of 0.532 compared to 88.8%, 86.2%, 81.6%, 64.5%, and 63.8% accuracy and 1.048, 1.094, 1.530, 1.678, and 2.090 RMSE for support-vector machines, random forest, k-nearest neighbours, Gaussian naive Bayes, and decision trees, respectively.
Effect of Milling Parameters on Amplitude Spectrum of Vibrations during Milling Materials Based on Wood
Authors: Hortobágyi Áron , Koleda Peter , Koleda Pavol , Kminiak Richard
Published: April 2023

Milling with use of CNC machines is a well-established method and much research was concluded on this topic. However, when it comes to wood and wood composites, the material non-homogeneity brings a lot of variability into cutting conditions. As a part of research into potential signals for nesting milling, material vibrations at clamping points were examined in this study. The main goal was to conclude if cutting parameters have a statistically significant effect on measurement. The place of measurement was analyzed so it was accessible to the machine operator. Medium density fiberboard and particleboard specimens were cut through by razor and spiral mill, with spindle rotating 10,000 and 20,000 min−1 and feed rates 2, 6, 10 m·min−1. Vibrations were measured at vacuum grippers, and were then processed by fast Fourier transform. Then, frequency spectrum maxima were compared, as well as amplitude sizes. Main frequencies were of roughly 166 Hz and multiples, suggesting their origin in tool rotation. When maxima were compared, tool use, spindle rotation, and feed rate seemed to affect the result. Frequency spectrum amplitudes were subjected to analysis of variance, significant effect was found on spindle speed, tool, and specimen material. No significant effect was found with differing feed rates.
An Overview on Management and Valorisation of Winery Wastes
Authors: Niculescu Violeta-Carolina , Ionete Roxana-Elena
Published: April 2023

As we address important societal needs, the circular economy equips us with the means to jointly combat climate change and biodiversity loss, including the revaluation of waste. The wine-making process is a huge generator of waste, creating problems for manufacturers every year; therefore, an appropriate management and valorisation of winery wastes are crucial, even if it is difficult. This results from the hardship of disposing of grape marc, which is considered a pollutant for the environment. In the past, the simplest option for this waste disposal was the payment of a fee around EUR 3000, which recently increased up to EUR 30,000–40,000. Several environmentally friendly technologies have been proposed for the recovery of cellar waste. Fermentation of grape residue, pruning, or wine-making lees have been reported to yield lactic acid, surfactants, xylitol, ethanol, and other compounds. In addition, grape pulp and seeds are rich in phenolic compounds, which have antioxidant properties, and tartaric acid from vinasse can be extracted and marketed. Additionally, complex phenol mixtures, such as those found in wine residues (seeds, bark, stems, or leaves), are effective as chemotherapeutic agents and can be used in medicine. In this review, the potential of using wine-making by-products, extracts, and their constituent parts as raw materials for adsorbents, biopolymers, natural reinforcing fillers, and sustainable energy production will be a key point of discussion. An overview on how wine producers, based on wine and wastes chemistry, can implement the circular economy as an alternative to the conventional linear economy (make, use, dispose) will be provided.
A Theory of Slope Shear Scouring and the Failure Mechanism of PFC3D on a Gangue Slope
Authors: Tian Yun , Wu Yong , Wang Hao , Li Hongtao , He Lindong , Zhao Hong
Published: April 2023

In this paper, scouring shear failure theory is optimized based on the gangue slope near the thermal power field in Baiguo Town, Panzhou City, Guizhou Province. Based on the particle flow PFC (particle flow code) 3D fluid–solid coupling method, the scouring failure mechanism of ditch no. 5 of the gangue slope is comprehensively analyzed from the perspectives of the failure mode, displacement, motion track, and stress–strain. We consider the scouring shear theory in respect of (c, φ); this theory is dominated by two types of scouring intensity factors and can effectively explain the internal mechanisms of gully formation. The rainfall scouring failure of gangue slopes can be divided into four stages: (1) integral splash erosion and local pitting at the bottom of the slope; (2) erosion diversion and pitting in the slope; (3) the tributary–slope crest extension schist erosion stage; and (4) integral gully erosion and the landslide stage. The failure process is not only characterized by discontinuous failure but also occurs in the order of bottom–middle–branch–top. A three-section stepped effect is observed during the process in which the gangue is scoured and destroyed, which fully verifies the intermittent characteristics of the scouring and destruction of gangue slopes. During the whole process, the maximum displacement is concentrated at the top of the slope, and its proportions are as follows: top of the slope > tributary > middle of the slope > foot of the slope. The peak displacement of the slope crest in the horizontal Y-direction accounts for 41.76%, and that in the Z-direction accounts for 45.84%. Scouring deposits can be divided into the arc erosion deposit mode and the sector erosion deposit mode. Mainstream gullies primarily control whether deposits are characterized as arc or straight erosion deposits. The later stage of the second phase of scouring is the incubation period of the tributary gully. The large accumulation makes the stress at the bottom of the slope increase sharply, and the fluctuation value is between 2 and 6.8 MPa. The generation of the branch notch is mainly determined by X-direction stress, and 8.6 MPa is the critical stress. In efforts to prevent and control rainfall and landslide, the slope foot area should be preferentially protected, and the soil mass in the slope should be reduced to prevent the maximum energy fluctuation caused by scouring, so as to prevent significant displacement damage of the slope top.
Accuracy Characterization of a MEMS Accelerometer for Vibration Monitoring in a Rotating Framework
Authors: Rossi Andrea , Bocchetta Gabriele , Botta Fabio , Scorza Andrea
Published: April 2023

Active and passive vibration control systems are of paramount importance in many engineering applications. If an external load excites a structure’s resonance and the damping is too low, detrimental events, such as crack initiation, growth and, in the worst case, fatigue failure, can be entailed. Damping systems can be commonly found in applications such as industrial machines, vehicles, buildings, turbomachinery blades, and so forth. Active control systems usually achieve higher damping effectiveness than passive ones, but they need a sensor to detect the working conditions that require damping system activation. Recently, the development of such systems in rotating structures has received considerable interest among designers. As a result, the development of vibration monitoring equipment in rotating structures is also a topic of particular interest. In this respect, a reliable, inexpensive and wireless monitoring system is of utmost importance. Typically, optical systems are used to measure vibrations, but they are expensive and require rather complex processing algorithms. In this paper, a wireless system based on a commercial MEMS accelerometer is developed for rotating blade vibration monitoring. The proposed system measurement accuracy was assessed by means of comparison with a reference wired measurement setup based on a mini integrated circuit piezoelectric (ICP) accelerometer adapted for data acquisition in a rotating frame. Both the accelerometers were mounted on the tip of the blade and, in order to test the structure under different conditions, the first four blade resonances were excited by means of piezoelectric actuators, embedded in a novel experimental setup. The frequency and amplitude of acceleration, simultaneously measured by the reference and MEMS sensors, were compared with each other in order to investigate the viability and accuracy of the proposed wireless monitoring system. The rotor angular speed was varied from 0 to 300 rpm, and the data acquisitions were repeated six times for each considered condition. The outcomes reveal that the wireless measurement system may be successfully used for vibration monitoring in rotating blades.
Calibration of Mean Wind Profiles Using Wind Lidar Measurements
Authors: Sepe Vincenzo , Avossa Alberto Maria , Rizzo Fabio , Ricciardelli Francesco
Published: April 2023

This paper explores the applicability of Lidar wind measurements for the calibration of mean wind profiles depending on the extension in time and space of the available measurements. Starting from logarithmic wind speed profiles corresponding to different site conditions, pseudo-experimental wind speed profiles are generated artificially by adding a zero-mean Gaussian-distributed noise, representative of realistic measurement errors. Then, a least-square fitting procedure is applied to identify the roughness length and the zero-plane displacement. The results obtained show an increase in the scatter of the estimated parameters of the logarithmic law with increasing elevation of the lowest measurement point. Then, a parametric study is developed to analyse the influence of the number of available experimental profiles on the uncertainty associated with the estimated logarithmic law parameters. Based on the results obtained, it can be pointed out that the availability of measurements at low elevations is essential to identify the logarithmic mean wind profile using a reasonable number of observations.
Feasibility of Visual Question Answering (VQA) for Post-Disaster Damage Detection Using Aerial Footage
Authors: Lowande Rafael De Sa , Sevil Hakki Erhan
Published: April 2023

Natural disasters are a major source of significant damage and costly repairs around the world. After a natural disaster occurs, there is usually a significant amount of damage, and with that, there are also a lot of costs involved with repairing and aiding all the people involved. In addition, the occurrence of natural phenomena has increased significantly in the past decade. With that in mind, post-disaster damage detection is usually performed manually by human operators. Taking into consideration all the areas one has to closely look into, as well as the difficult terrain and places with hard access, it becomes easy to understand how incredibly difficult it is for a surveyor to identify and annotate every single possible damage out there. Because of that, it has become essential to find new creative solutions for damage detection and classification in the case of natural disasters, especially hurricanes. This study focuses on the feasibility of using a Visual Question Answering (VQA) method for post-disaster damage detection, using aerial footage taken from an Unmanned Aerial Vehicle (UAV). Two other approaches are also utilized to provide comparison and to evaluate the performance of VQA. Our case study on our custom dataset collected after Hurricane Sally shows successful results using VQA for post-disaster damage detection applications.
A Quasiconformal-Based Geometric Model for Craniofacial Analysis and Its Application
Authors: Wong Ming-Hei , Li Meixi , Tam King-Man , Yuen Hoi-Man , Au Chun-Ting , Chan Kate Ching-Ching , Li Albert Martin , Lui Lok-Ming
Published: April 2023

We address the problem of craniofacial morphometric analysis using geometric models, which has important clinical applications for the diagnosis of syndromes associated with craniofacial dysmorphologies. In this work, a novel geometric model is proposed to analyze craniofacial structures based on local curvature information and Teichmüller mappings. A key feature of the proposed model is that its pipeline starts with few two-dimensional images of the human face captured at different angles, from which the three-dimensional craniofacial structure can be reconstructed. The 3D surface reconstruction from 2D images is based on a modified 3D morphable model (3DMM) framework. Geometric quantities around important feature landmarks according to different clinical applications can then be computed on each three-dimensional craniofacial structure. Together with the Teichmüller mapping, the landmark-based Teichmüller curvature distances (LTCDs) for every classes can be computed, which are further used for three-class classification. A composite score model is used and the parameter optimization is carried out to further improve the classification accuracy. Our proposed model is applied to study the craniofacial structures of children with and without the obstructive sleep apnoea (OSA). Sixty subjects, with accessible multi-angle photography and polysomnography (PSG) data, are divided into three classes based on the severity of OSA. Using our proposed model, our proposed model achieves a high 90% accuracy, which outperforms other existing models. This demonstrates the effectiveness of our proposed geometric model for craniofacial analysis.
Nonuniform Dichotomy with Growth Rates of Skew-Evolution Cocycles in Banach Spaces
Authors: Găină Ariana , Megan Mihail , Boruga (Toma) Rovana
Published: April 2023

This paper presents integral charaterizations for nonuniform dichotomy with growth rates and their correspondents for the particular cases of nonuniform exponential dichotomy and nonuniform polynomial dichotomy of skew-evolution cocycles in Banach spaces. The connections between these three concepts are presented.
Message in a Bottle: An Exploratory Study on the Role of Wine-Bottle Design in Capturing Consumer Attention
Authors: Ozturk Emel , Kilic Busra , Cubero Dudinskaya Emilia , Naspetti Simona , Solfanelli Francesco , Zanoli Raffaele
Published: April 2023

This study aims to investigate the influence of wine-bottle design and the position of labels on consumers’ visual attention in digital contexts. Two within-subjects experiments combined with implicit eye-tracking measures were implemented in Italy. The visual attention of twenty-four participants was measured using areas of interest metrics while being asked to view two differently shaped bottles in three orientations. Subsequently, four examples of each bottle type were displayed, positioning an organic logo in different areas. Attention and interest measures were captured and analysed using a factorial repeated-measures ANOVA. The results show that the shoulder is the bottle’s first and most fixated part. Significant differences in participants’ attention and interest were found according to the interaction of bottle type and bottle part, as well as bottle part and orientation. Furthermore, exploring the inclusion of an organic logo on different bottle parts provided consistent results. Wine producers and marketers could benefit from bottle anatomy and morphology to identify the best place to display essential information to capture the consumer’s visual attention and interest.
Modeling the Circadian Control of the Cell Cycle and Its Consequences for Cancer Chronotherapy
Authors: Leung Courtney , Gérard Claude , Gonze Didier
Published: April 2023

The mammalian cell cycle is governed by a network of cyclin/Cdk complexes which signal the progression into the successive phases of the cell division cycle. Once coupled to the circadian clock, this network produces oscillations with a 24 h period such that the progression into each phase of the cell cycle is synchronized to the day–night cycle. Here, we use a computational model for the circadian clock control of the cell cycle to investigate the entrainment in a population of cells characterized by some variability in the kinetic parameters. Our numerical simulations showed that successful entrainment and synchronization are only possible with a sufficient circadian amplitude and an autonomous period close to 24 h. Cellular heterogeneity, however, introduces some variability in the entrainment phase of the cells. Many cancer cells have a disrupted clock or compromised clock control. In these conditions, the cell cycle runs independently of the circadian clock, leading to a lack of synchronization of cancer cells. When the coupling is weak, entrainment is largely impacted, but cells maintain a tendency to divide at specific times of day. These differential entrainment features between healthy and cancer cells can be exploited to optimize the timing of anti-cancer drug administration in order to minimize their toxicity and to maximize their efficacy. We then used our model to simulate such chronotherapeutic treatments and to predict the optimal timing for anti-cancer drugs targeting specific phases of the cell cycle. Although qualitative, the model highlights the need to better characterize cellular heterogeneity and synchronization in cell populations as well as their consequences for circadian entrainment in order to design successful chronopharmacological protocols.
A Study on REM Sleep Homeostasis in the Day-Active Tree Shrew (Tupaia belangeri): Cold-Induced Suppression of REM Sleep Is Not Followed by a Rebound
Authors: van Hasselt Sjoerd J. , Epifani Luisa , Zantinge Danique , Vitkute Kornelija , Kas Martien J. H. , Allocca Giancarlo , Meerlo Peter
Published: April 2023

The function and regulation of rapid-eye-movement (REM) sleep is a topic of ongoing debate. It is often assumed that REM sleep is a homeostatically regulated process and that a need for REM sleep builds up, either during prior wakefulness or during preceding slow wave sleep. In the current study, we tested this hypothesis in six diurnal tree shrews (Tupaia belangeri), small mammals closely related to primates. All animals were individually housed and kept under a 12:12 light-dark cycle with an ambient temperature of 24 °C. We recorded sleep and temperature in the tree shrews for 3 consecutive 24 h days. During the second night, we exposed the animals to a low ambient temperature of 4 °C, a procedure that is known to suppress REM sleep. Cold exposure caused a significant drop in brain temperature and body temperature and also resulted in a strong and selective suppression of REM sleep by 64.9%. However, contrary to our expectation, the loss of REM sleep was not recovered during the subsequent day and night. These findings in a diurnal mammal confirm that the expression of REM sleep is highly sensitive to environmental temperature but do not support the view that REM sleep is homeostatically regulated in this species.
Automatic Segmentation of Osteonal Microstructure in Human Cortical Bone Using Deep Learning: A Proof of Concept
Authors: Littek Alina , McKenna Stephen J. , Chiam Wei Xiong , Kranioti Elena F. , Trucco Emanuele , García-Donas Julieta G.
Published: April 2023

Cortical bone microstructure assessment in biological and forensic anthropology can assist with the estimation of age-at-death and animal-human differentiation, for example. Osteonal structures within cortical bone are the key feature under analysis, with osteon frequency and metric parameters providing crucial information for the assessment. Currently, the histomorphological assessment consists of a time-consuming manual process for which specific training is required. Our work investigates the feasibility of automatic analysis of human bone microstructure images through the application of deep learning. In this paper, we use a U-Net architecture to address the semantic segmentation of such images into three classes: intact osteons, fragmentary osteons, and background. Data augmentation was used to avoid overfitting. We evaluated our fully automatic approach using a sample of 99 microphotographs. The contours of intact and fragmentary osteons were traced manually to provide ground truth. The Dice coefficients were 0.73 for intact osteons, 0.38 for fragmented osteons, and 0.81 for background, giving an average of 0.64. The Dice coefficient of the binary classification osteon-background was 0.82. Although further refinement of the initial model and tests with larger datasets are needed, this study provides, to the best of our knowledge, the first proof of concept for the use of computer vision and deep learning for differentiating both intact and fragmentary osteons in human cortical bone. This approach has the potential to widen and facilitate the use of histomorphological assessment in the biological and forensic anthropology communities.
A Novel Topology Optimization Protocol Based on an Improved Crow Search Algorithm for the Perception Layer of the Internet of Things
Authors: Bai Yang , Cao Li , Chen Binhe , Chen Yaodan , Yue Yinggao
Published: April 2023

In wireless sensor networks, each sensor node has a finite amount of energy to expend. The clustering method is an efficient way to deal with the imbalance in node energy consumption. A topology optimization technique for wireless sensor networks based on the Cauchy variation optimization crow search algorithm (CM-CSA) is suggested to address the issues of rapid energy consumption, short life cycles, and unstable topology in wireless sensor networks. At the same time, a clustering approach for wireless sensor networks based on the enhanced Cauchy mutation crow search algorithm is developed to address the issue of the crow algorithm’s sluggish convergence speed and ease of falling into the local optimum. It utilizes the Cauchy mutation to improve the population’s variety and prevent settling for the local optimum, as well as to broaden the range of variation and the capacity to carry out global searches. When the leader realizes he is being followed, the discriminative probability is introduced to improve the current person’s location update approach. According to the simulation findings, the suggested CM-CSA algorithm decreases the network’s average energy consumption by 66.7%, 50%, and 33.3% and enhances its connectivity performance by 52.9%, 37.6%, and 23.5% when compared to the PSO algorithm, AFSA method, and basic CSA algorithm.
Single-Atom Fe Nanozyme with Enhanced Oxidase-like Activity for the Colorimetric Detection of Ascorbic Acid and Glutathione
Authors: Gu Yue , Cao Zhongxu , Zhao Mengde , Xu Yanan , Lu Na
Published: April 2023

Single-atom nanozymes (SAzymes) have drawn ever-increasing attention due to their maximum atom utilization efficiency and enhanced enzyme-like activity. Herein, a facile pyrolysis strategy is reported for the synthesis of the iron–nitrogen–carbon (Fe-N-C) SAzyme using ferrocene trapped within porous zeolitic imidazolate framework-8 (ZIF-8@Fc) as a precursor. The as-prepared Fe-N-C SAzyme exhibited exceptional oxidase-mimicking activity, catalytically oxidizing 3,3′,5,5′-tetramethylbenzidine (TMB) with high affinity (Km) and fast reaction rate (Vmax). Taking advantage of this property, we designed two colorimetric sensing assays based on different interaction modes between small molecules and Fe active sites. Firstly, utilizing the reduction activity of ascorbic acid (AA) toward oxidized TMB (TMBox), a colorimetric bioassay for AA detection was established, which exhibited a good linear range of detection from 0.1 to 2 μM and a detection limit as low as 0.1 μM. Additionally, based on the inhibition of nanozyme activity by the thiols of glutathione (GSH), a colorimetric biosensor for GSH detection was constructed, showing a linear response over a concentration range of 1–10 μM, with a detection limit of 1.3 μM. This work provides a promising strategy for rationally designing oxidase-like SAzymes and broadening their application in biosensing.
Relative Neuroadaptive Effect of Resistance Training along the Descending Neuroaxis in Older Adults
Authors: Romare Mattias , Elcadi Guilherme H. , Johansson Elin , Tsaklis Panagiotis
Published: April 2023

Age-related decline in voluntary force production represents one of the main contributors to the onset of physical disability in older adults and is argued to stem from adverse musculoskeletal alterations and changes along the descending neuroaxis. The neural contribution of the above is possibly indicated by disproportionate losses in voluntary activation (VA) compared to muscle mass. For young adults, resistance training (RT) induces muscular and neural adaptations over several levels of the central nervous system, contributing to increased physical performance. However, less is known about the relative neuroadaptive contribution of RT in older adults. The aim of this review was to outline the current state of the literature regarding where and to what extent neural adaptations occur along the descending neuroaxis in response to RT in older adults. We performed a literature search in PubMed, Google Scholar and Scopus. A total of 63 articles met the primary inclusion criteria and following quality analysis (PEDro) 23 articles were included. Overall, neuroadaptations in older adults seemingly favor top-down adaptations, where the preceding changes of neural drive from superior levels affect the neural output of lower levels, following RT. Moreover, older adults appear more predisposed to neural rather than morphological adaptations compared to young adults, a potentially important implication for the improved maintenance of neuromuscular function during aging.
Social Media Use, Fake News and Mental Health during the Uncertain Times of the COVID-19 Pandemic in Ukraine
Authors: Haydabrus Andriy , Linskiy Igor , Giménez-Llort Lydia
Published: April 2023

A sample of 351 adults (women/men 4:1) aged 18 to 60 participated in an online survey administered during the first two waves (15 March–25 April and 10 October–25 November 2020) of the COVID-19 pandemic in Ukraine. The user ethnography profile was Generation Z (born in the 1990s), female (81.2%), Instagrammer (60.3%), unmarried (56.9%) and student (42.9%). An increased time spent on social media (3.18 h/day), searching for COVID-19-related information (1.01 h/day) after the first COVID-19 case and the observation of fake news that went viral (58.8%) decreased in the second wave. Alterations (increase or reduction) in sleep patterns (46.7%) and changes (increase or loss) in appetite (32.7%) affected participants’ well-being, but only sleep ameliorated in the second wave. Mental health reports unveiled moderate perceived stress (PSS-10: 20.61 ± 1.13) and mild anxiety (GAD-7: 14.17 ± 0.22), which improved in the second wave. A higher prevalence of severe anxiety (8.5%) was found among individuals in the first survey (8.5%) than those in the second (3.3%). Social media counteracted physical distance policies and played as an immediate source of (mis)information for users, but also anticipated the impact of the most uncertain times of this COVID-19 physical health crisis on well-being and mental health.
Increased Depression and the Worsening of Depressive Symptoms Associated with Physical Inactivity during the COVID-19 Pandemic: A Two-Phase Cross-Sectional Study
Authors: Leão Luana Lemos , Valadares Weslley Gomes de Araújo , Silva Nayra Suze Souza e , Duarte Stênio Fernando Pimentel , de Paula Alfredo Maurício Batista , Haikal Desirée Sant´Ana , Santos Sérgio Henrique Sousa , Soares Jeane , Cruz Joelton , Santos Jordana , Teixeira Gustavo Leal , Monteiro-Junior Renato Sobral
Published: April 2023

The COVID-19 pandemic has increased the incidence of depression and other mental disorders in the general population, influenced by various individual and contextual factors. Physical activity (PA) interventions offer a promising approach to mitigating the negative mental health effects of the pandemic. This study aims to analyze the association between PA and depressive symptoms. A total of 785 individuals aged 37.4 ± 13.2 years (72.5% female) were evaluated at two different time points: the first between 2018 and 2019, and the second during the COVID-19 pandemic in 2020. Depressive symptoms, demographic, and socioeconomic data were assessed using the Beck Depression Inventory to estimate depressive symptoms. Frequency analysis and binary and multinomial regression were employed for data analysis. The prevalence of mild depressive symptoms increased from 23.1% before the pandemic to 35.1% during the pandemic. Our findings reveal that practicing PA before the pandemic was a protective factor (OR: 0.19; 95% CI: 0.13, 0.30; p < 0.001) against mild depressive symptoms. Additionally, individuals who continued to practice PA during the pandemic had a lower chance of presenting mild (OR: 0.21; 95% CI: 0.15, 0.30) and moderate/severe (OR: 0.15; 95% CI: 0.08, 0.27) symptoms. Furthermore, our study shows that PA, which was already a protective factor before the pandemic, remained protective during the pandemic, even for those with the highest levels of depression.
Automatic Detection of Pedestrian Crosswalk with Faster R-CNN and YOLOv7
Authors: Kaya Ömer , Çodur Muhammed Yasin , Mustafaraj Enea
Published: April 2023

Autonomous vehicles have gained popularity in recent years, but they are still not compatible with other vulnerable components of the traffic system, including pedestrians, bicyclists, motorcyclists, and occupants of smaller vehicles such as passenger cars. This incompatibility leads to reduced system performance and undermines traffic safety and comfort. To address this issue, the authors considered pedestrian crosswalks where vehicles, pedestrians, and micro-mobility vehicles collide at right angles in an urban road network. These road sections are areas where vulnerable people encounter vehicles perpendicularly. In order to prevent accidents in these areas, it is planned to introduce a warning system for vehicles and pedestrians. This procedure consists of multi-stage activities by sending warnings to drivers, disabled individuals, and pedestrians with phone addiction simultaneously. This collective autonomy is expected to reduce the number of accidents drastically. The aim of this paper is the automatic detection of a pedestrian crosswalk in an urban road network, designed from both pedestrian and vehicle perspectives. Faster R-CNN (R101-FPN and X101-FPN) and YOLOv7 network models were used in the analytical process of a dataset collected by the authors. Based on the detection performance comparison between both models, YOLOv7 accuracy was 98.6%, while the accuracy for Faster R-CNN was 98.29%. For the detection of different types of pedestrian crossings, YOLOv7 gave better prediction results than Faster R-CNN, although quite similar results were obtained.
Residential Building Energy Conservation in Mediterranean Climate Zone by Integrating Passive Solar and Energy Efficiency Design Strategies
Authors: Bekele Michael Tesfaye , Atakara Cemil
Published: April 2023

Residential buildings have a list of functions, and one of the top priories is the thermal comfort of its occupants. Thermal comfort can be one of the measurements of successful building performance, and it can be addressed in various ways to provide a good quality indoor climate. The way to address the need for thermal comfort determines the consumption and conservation of energy. Adapting passive strategies and thermal mass to a building can reduce energy consumption significantly. Applying these strategies to a building does not need additional investment from the initial capital, and renovating a building to implement the strategy will cut the energy usage of a building and save the additional financing of new technology for heating and cooling, ventilation, and so on. In this study, two residential buildings located in North Cyprus with the same geographical location, climate zone, and different construction materials were studied. The study aimed to make a technical test to reduce energy consumption and improve energy conservation in the building by applying passive solar and energy efficiency design strategies (PSEEDS). The thermal mass has been used and discussed as an improbable energy technique alongside other insulation materials and shading devices. The article discusses and compares the energy consumption and thermal comfort of traditional Mediterranean houses with contemporary houses. The study uses 2D drawings, 3D modeling, and energy simulation programs to evaluate energy consumption in both real and assumed scenarios. The study finds that traditional Mediterranean homes, with their thick walls and built-in shading mechanisms, require less energy for heating and cooling than contemporary houses. The implementation of passive solar energy efficient design strategies (PSEEDS) significantly reduces energy consumption in both types of houses, but traditional Mediterranean houses still show more efficiency due to their higher thermal mass. The research demonstrates that improving windows, examining the orientation of the structure, altering shade devices, and decreasing infiltration rates can reduce overall energy consumption by up to 34.71% To sum up, in this study, PSEEDS, the performance of thermal mass, and pre-design measures significantly decrease energy consumption. In addition, implementing passive strategies during a renovation of a building also compensates for the investment and lifecycle cost of new technologies and energy usage.