bluuebunny/crossref_metadata_2025 huggingface dataset:
Selection, Identification and Functional Performance of Ammonia-Degrading Microbial Communities from an Activated Sludge for Landfill Leachate Treatment
Authors: Petrilli Rossana , Fabbretti Attilio , Cerretani Alex , Pucci Kathleen , Pagliaretta Graziella , Picciolini Matteo , Napolioni Valerio , Falconi Maurizio
Published: January 2023

The increasing amounts of municipal solid waste and their management in landfills caused an increase in the production of leachate, a liquid formed by the percolation of rainwater through the waste. Leachate creates serious problems to municipal wastewater treatment plants; indeed, its high levels of ammonia are toxic for bacterial cells and drastically reduce the biological removal of nitrogen by activated sludge. In the present work, we studied, using a metagenomic approach based on next-generation sequencing (NGS), the microbial composition of sludge in the municipal wastewater treatment plant of Porto Sant’Elpidio (Italy). Through activated sludge enrichment experiments based on the Repetitive Re-Inoculum Assay, we were able to select and identify a minimal bacterial community capable of degrading high concentrations of ammonium (NH4+-N ≅ 350 mg/L) present in a leachate-based medium. The analysis of NGS data suggests that seven families of bacteria (Alcaligenaceae, Nitrosomonadaceae, Caulobacteraceae, Xanthomonadaceae, Rhodanobacteraceae, Comamonadaceae and Chitinophagaceae) are mainly responsible for ammonia oxidation. Furthermore, we isolated from the enriched sludge three genera (Klebsiella sp., Castellaniella sp. and Acinetobacter sp.) capable of heterotrophic nitrification coupled with aerobic denitrification. These bacteria released a trace amount of both nitrite and nitrate possibly transforming ammonia into gaseous nitrogen. Our findings represent the starting point to produce an optimized microorganisms’s mixture for the biological removal of ammonia contained in leachate.
Machine Learning Methods for Diabetes Prevalence Classification in Saudi Arabia
Authors: Almutairi Entissar S. , Abbod Maysam F.
Published: January 2023

Machine learning algorithms have been widely used in public health for predicting or diagnosing epidemiological chronic diseases, such as diabetes mellitus, which is classified as an epi-demic due to its high rates of global prevalence. Machine learning techniques are useful for the processes of description, prediction, and evaluation of various diseases, including diabetes. This study investigates the ability of different classification methods to classify diabetes prevalence rates and the predicted trends in the disease according to associated behavioural risk factors (smoking, obesity, and inactivity) in Saudi Arabia. Classification models for diabetes prevalence were developed using different machine learning algorithms, including linear discriminant (LD), support vector machine (SVM), K -nearest neighbour (KNN), and neural network pattern recognition (NPR). Four kernel functions of SVM and two types of KNN algorithms were used, namely linear SVM, Gaussian SVM, quadratic SVM, cubic SVM, fine KNN, and weighted KNN. The performance evaluation in terms of the accuracy of each developed model was determined, and the developed classifiers were compared using the Classification Learner App in MATLAB, according to prediction speed and training time. The experimental results on the predictive performance analysis of the classification models showed that weighted KNN performed well in the prediction of diabetes prevalence rate, with the highest average accuracy of 94.5% and less training time than the other classification methods, for both men and women datasets.
Prolonged Antibacterial Activity in Tannic Acid–Iron Complexed Chitosan Films for Medical Device Applications
Authors: Chevallier Pascale , Wiggers Helton José , Copes Francesco , Zorzi Bueno Cecilia , Mantovani Diego
Published: January 2023

Healthcare-associated infections (HAIs) represent a global burden, leading to significant mortality and generating financial costs. One important cause of HAIs is the microbiological contamination of implantable medical devices. In this context, a novel antimicrobial drug-eluting system, based on chitosan and loaded with gentamicin, a broad-spectrum antibiotic, was developed. The effects of the addition of tannic acid and different FeSO4 concentrations on the loaded antibiotic release were evaluated. The properties of the films were assessed in terms of thickness, swelling, mass loss and wettability. The films’ surface composition was characterized by X-ray photoelectron spectroscopy and Fourier-transform infrared spectroscopy. The antibiotic release in phosphate buffer saline was quantified by high-performance liquid chromatography–mass spectrometry, and the antibacterial activity was evaluated. Hemolysis and cytotoxicity were also assessed. The results showed that the addition of tannic acid and iron decreased the swelling degree and degradation due to strong interactions between the different components, thus impacting gentamicin release for up to 35 days. In conclusion, this study presents a novel strategy to produce low-cost and biocompatible antimicrobial drug-eluting systems with sustained and prolonged antibacterial activity over more than a month.
Molecularly Imprinted Magnetic Nanocomposite Based on Carboxymethyl Dextrin for Removal of Ciprofloxacin Antibiotic from Contaminated Water
Authors: Heidari Golnaz , Afruzi Fereshte Hassanzadeh , Zare Ehsan Nazarzadeh
Published: January 2023

Broad-spectrum antibiotics from the fluoroquinolone family have emerged as prominent water contaminants, among other pharmaceutical pollutants. In the present study, an antibacterial magnetic molecularly imprinted polymer (MMIP) composite was successfully fabricated using carboxy methyl dextrin grafted to poly(aniline-co-meta-phenylenediamine) in the presence of Fe3O4/CuO nanoparticles and ciprofloxacin antibiotic. The characteristics of obtained materials were investigated using FTIR, XRD, VSM, TGA, EDX, FE-SEM, zeta potential, and BETanalyses. Afterward, the MMIP’s antibacterial activity and adsorption effectiveness for removing ciprofloxacin from aqueous solutions were explored. The results of the antibacterial tests showed that MMIP had an antibacterial effect against Escherichia coli, a Gram-negative pathogen (16 mm), and Staphylococcus aureus, a Gram-positive pathogen (22 mm). Adsorption efficacy was evaluated under a variety of experimental conditions, including solution pH, adsorbent dosage, contact time, and initial concentration. The maximum adsorption capacity (Qmax) of the MMIP for ciprofloxacin was determined to be 1111.1 mg/g using 3 mg of MMIP, with an initial concentration of 400 mg/L of ciprofloxacin at pH 7, within 15 min, and agitated at 25 °C, and the experimental adsorption results were well-described by the Freundlich isotherm model. The adsorption kinetic data were well represented by the pseudo-second-order model. Electrostatic interaction, cation exchange, π-π interactions, and hydrogen bonding were mostly able to adsorb the majority of the ciprofloxacin onto the MMIP. Adsorption–desorption experiments revealed that the MMIP could be retrieved and reused with no noticeable reduction in adsorption efficacy after three consecutive cycles.
Prevalence of Iron Deficiency Anemia Indicated for Intravenous Iron Treatment in the Korean Population
Authors: Choi Rihwa , Chun Gayoung , Park Mi-Jung , Lee Sang Gon , Lee Eun Hee
Published: January 2023

We aimed to investigate the number and prevalence of patients indicated for intravenous iron treatment in a large Korean population using criteria based on laboratory test results in an effort to extract indirect information on the need for intravenous iron treatment. Between 1 January 2019 and 31 December 2021, a total of 83,994 Korean patients (30,499 men and 53,495 women) with a median age of 46 years (interquartile range, 30–61) were evaluated using iron deficiency anemia–associated laboratory tests and serum creatinine tests of estimated glomerular filtration rates. The overall prevalence of anemia (Hb ≤ 11 g/dL) was 16.5%, and the proportion of patients with possible chronic kidney disease who had an estimated glomerular filtration rate < 60 mL/min/1.73 m2 was 11.4%. The number of patients indicated for reimbursable intravenous iron treatment was higher in women than in men, higher in older patients, and higher in 2021 than in 2019 (all p < 0.001). The prevalence of patients indicated for reimbursable intravenous iron treatment was up to 30.0% in those ≥ 80 years of age in 2019. The results of this study provide basic knowledge about the use of iron deficiency anemia-associated laboratory tests in planning nutritional support programs using an intravenous iron formulation in Korea.
Infantile Colic and Long-Term Outcomes in Childhood: A Narrative Synthesis of the Evidence
Authors: Indrio Flavia , Dargenio Vanessa Nadia , Francavilla Ruggiero , Szajewska Hania , Vandenplas Yvan
Published: January 2023

About 1 in 4 infants comes forward with prolonged crying, agitation, or infant colic (IC) during the first three months of life and is referred for medical evaluation. The pathogenesis remains poorly understood, as do its implications for future health. The aim of this narrative review was to critically examine and discuss the available literature on long-term consequences of excessive crying and/or colic. Most studies display an association between IC and the onset of functional gastrointestinal disorders (FGIDs) years later, probably related to the presence of common etiopathogenetic factors (environmental, dietary, intestinal dysmotility, visceral hypersensitivity). Although allergic disease in first-degree relatives may be a risk factor for IC, the latter does not appear to be a risk factor for subsequent atopic disease in the individual. Overall, there seems to be a relationship between IC and subsequent headaches, of the migraine type. Similarly, behavioral problems in children with a history of IC appear to be associated with higher parental stress scores. However, the current evidence is based on associations, and currently, a causal relationship between excessive crying and IC and long-term consequences remains not documented.
Neurobehavioral Mechanisms of Sodium Appetite
Authors: Rowland Neil E.
Published: January 2023

The objectives of this paper are to first present physiological and ecological aspects of the unique motivational state of sodium appetite, then to focus on systemic physiology and brain mechanisms. I describe how laboratory protocols have been developed to allow the study of sodium appetite under controlled conditions, and focus on two such conditions specifically. The first of these is the presentation a sodium-deficient diet (SDD) for at least one week, and the second is accelerated sodium loss using SDD for 1–2 days coupled with the diuretic furosemide. The modality of consumption is also considered, ranging from a free intake of high concentration of sodium solution, to sodium-rich food or gels, and to operant protocols. I describe the pivotal role of angiotensin and aldosterone in these appetites and discuss whether the intakes or appetite are matched to the physiological need state. Several brain systems have been identified, most recently and microscopically using molecular biological methods. These include clusters in both the hindbrain and the forebrain. Satiation of sodium appetite is often studied using concentrated sodium solutions, but these can be consumed in apparent excess, and I suggest that future studies of satiation might emulate natural conditions in which excess consumption does not occur, using either SDD only as a stimulus, offering a sodium-rich food for the assessment of appetite, or a simple operant task.
The Current State of Knowledge about the Biological Activity of Different Parts of Capers
Authors: Olas Beata
Published: January 2023

The caper, from the Latin capra, meaning goat, is the common name for the salt-fermented floral buds of the perennial shrubs of the Capparis genus (Capparacea family). This genus is represented by about 250 species, including the very popular C. spinosa L. While the whole plant is edible, the aromatic floral buds are most widely consumed, being collected by hand prior to blooming, dried in the sun and pickled. Capers are usually served marinated in vinegar, brine or oil. They have a significant potential as dietary supplements due to their low calorie content and richness in bioactive phytochemicals. Numerous in vitro and in vivo studies have demonstrated that C. spinosa have various nutritional and biological properties, including antioxidant activity resulting from the presence of phenolic compounds. The present paper reviews the current literature concerning the biological properties of the fruits, buds, seeds, roots and leaves of C. spinosa, including their toxicity.
Synthesis and Biological Evaluation of 3-Amidoquinuclidine Quaternary Ammonium Compounds as New Soft Antibacterial Agents
Authors: Odžak Renata , Crnčević Doris , Sabljić Antonio , Primožič Ines , Šprung Matilda
Published: January 2023

Quaternary ammonium compounds (QACs) are among the most effective antimicrobial agents that have been used for more than a century. However, due to the growing trend of bacterial resistance and high toxicity of QACs, research in this field remains a pressing matter. Recent studies of the structure–activity relationship suggest that the introduction of the amide functional group into QAC structures results in soft variants that retain their antimicrobial properties while opening the possibility of fine-tuned activity regulation. Here, we report the synthesis and structure-function study of three structurally distinct series of naturally derived soft QACs. The obtained 3-amidoquinuclidine QACs showed a broad range of antibacterial activities related to the hydrophobic-hydrophilic balance of the QAC structures. All three series yielded candidates with minimal inhibitory concentrations (MIC) in the single-digit μM range. Time-resolved growth analysis revealed subtle differences in the antibacterial activity of the selected candidates. The versatile MIC values were recorded in different nutrient media, suggesting that the media composition may have a dramatic impact on the antibacterial potential. The new QACs were found to have excellent potential to suppress bacterial biofilm formation while exhibiting low ability to induce bacterial resistance. In addition, the selected candidates were found to be less toxic than commercially available QACs and proved to be potential substrates for protease degradation. These data suggest that 3-amidoquinuclidine QACs could be considered as novel antimicrobial agents that pose a low threat to ecosystems and human health.
Nanostructured Lipid Carriers for Enhanced Transscleral Delivery of Dexamethasone Acetate: Development, Ex Vivo Characterization and Multiphoton Microscopy Studies
Authors: González-Fernández Felipe M. , Delledonne Andrea , Nicoli Sara , Gasco Paolo , Padula Cristina , Santi Patrizia , Sissa Cristina , Pescina Silvia
Published: January 2023

Corticosteroids, although highly effective for the treatment of both anterior and posterior ocular segment inflammation, still nowadays struggle for effective drug delivery due to their poor solubilization capabilities in water. This research work aims to develop nanostructured lipid carriers (NLC) intended for periocular administration of dexamethasone acetate to the posterior segment of the eye. Pre-formulation studies were initially performed to find solid and liquid lipid mixtures for dexamethasone acetate solubilization. Pseudoternary diagrams at 65 °C were constructed to select the best surfactant based on the macroscopic transparency and microscopic isotropy of the systems. The resulting NLC, obtained following an organic solvent-free methodology, was composed of triacetin, Imwitor® 491 (glycerol monostearate >90%) and tyloxapol with Z-average = 106.9 ± 1.2 nm, PDI = 0.104 ± 0.019 and zeta potential = −6.51 ± 0.575 mV. Ex vivo porcine sclera and choroid permeation studies revealed a considerable metabolism in the sclera of dexamethasone acetate into free dexamethasone, which demonstrated higher permeation capabilities across both tissues. In addition, the NLC behavior once applied onto the sclera was further studied by means of multiphoton microscopy by loading the NLC with the fluorescent probe Nile red.
Determination of Polycyclic Aromatic Hydrocarbon Content in Garden Herbal Plants Using Liquid Chromatographic Analysis (HPLC-FL)
Authors: Woźniak Magdalena , Hoppe Karolina , Drzewiecka Kinga
Published: January 2023

Polycyclic aromatic hydrocarbons (PAHs) are a group of chemical compounds generated as a result of the incomplete combustion of fossil fuels or wood. PAHs are known for their negative effect on living organisms, including teratogenic, carcinogenic and mutagenic activity. The objective of this study is to determine the contamination of three popular herbal species showing pro-health properties, i.e., lavender, parsley and mint, with polycyclic aromatic hydrocarbons, collected from three different backyard gardens in Poland. The concentration of PAHs in plant material was determined by high-performance liquid chromatography with a fluorescence detector (HPLC-FL). The concentration of eleven PAHs in plant material was determined with high-pressure liquid chromatography after extraction using the QuEChERS purification technique. Mint collected within an area of a mining and energy production complex (the city of Konin) was characterized by the highest Σ of 11 PAHs, equaled to 902.35 µg/g FW, with anthracene being the most abundant compound. However, it contained the lowest sum of PAHs, among all tested plants, with high carcinogenicity. Parsley from the city of Poznań showed the highest content of benzo[a]pyrene (BaP), showing the strongest carcinogenicity, while the highest value of BaP equivalent was calculated for mint collected in Konin. The obtained results suggest that the level and profile of plant contamination with PAHs depend on the species and the location of herb cultivation. In particular, mining and energy industry facilities are sources of PAHs, which contaminate plant material for further direct use or as bioactive herbal extracts.
The Joint Evolution of Herbivory Defense and Mating System in Plants: A Simulation Approach
Authors: Sandoval-Castellanos Edson , Núñez-Farfán Juan
Published: January 2023

Agricultural losses brought about by insect herbivores can be reduced by understanding the strategies that plants use against insect herbivores. The two main strategies that plants use against herbivory are resistance and tolerance. They are, however, predicted to be mutually exclusive, yet numerous populations have them both (hence a mixed defense strategy). This has been explained, among other alternatives, by the non-linear behavior of the costs and benefits of resistance and tolerance and their interaction with plants’ mating system. Here, we studied how non-linearity and mating system affect the evolutionary stability of mixed defense strategies by means of agent-based model simulations. The simulations work on a novel model that was built upon previous ones. It incorporates resistance and tolerance costs and benefits, inbreeding depression, and a continuously scalable non-linearity. The factors that promoted the evolutionary stability of mixed defense strategies include a multiplicative allocation of costs and benefits of resistance and tolerance, a concave non-linearity, non-heritable selfing, and high tolerance costs. We also found new mechanisms, enabled by the mating system, that are worth considering for empirical studies. One was a double trade-off between resistance and tolerance, predicted as a consequence of costs duplication and the inducibility of tolerance, and the other was named the resistance-cost-of-selfing, a term coined by us, and was derived from the duplication of costs that homozygous individuals conveyed when a single resistance allele provided full protection.
Warming Scenarios and Phytophthora cinnamomi Infection in Chestnut (Castanea sativa Mill.)
Authors: Dorado F. Javier , Alías Juan Carlos , Chaves Natividad , Solla Alejandro
Published: January 2023

The main threats to chestnut in Europe are climate change and emerging pathogens. Although many works have separately addressed the impacts on chestnut of elevated temperatures and Phytophthora cinnamomi Rands (Pc) infection, none have studied their combined effect. The objectives of this work were to describe the physiology, secondary metabolism and survival of 6-month-old C. sativa seedlings after plants were exposed to ambient temperature, high ambient temperature and heat wave events, and subsequent infection by Pc. Ten days after the warming scenarios, the biochemistry of plant leaves and roots was quantified and the recovery effect assessed. Plant growth and root biomass under high ambient temperature were significantly higher than in plants under ambient temperature and heat wave event. Seven secondary metabolite compounds in leaves and three in roots were altered significantly with temperature. Phenolic compounds typically decreased in response to increased temperature, whereas ellagic acid in roots was significantly more abundant in plants exposed to ambient and high ambient temperature than in plants subjected to heat waves. At recovery, leaf procyanidin and catechin remained downregulated in plants exposed to high ambient temperature. Mortality by Pc was fastest and highest in plants exposed to ambient temperature and lowest in plants under high ambient temperature. Changes in the secondary metabolite profile of plants in response to Pc were dependent on the warming scenarios plants were exposed to, with five compounds in leaves and three in roots showing a significant ‘warming scenario’ × ‘Pc’ interaction. The group of trees that best survived Pc infection was characterised by increased quercetin 3-O-glucuronide, 3-feruloylquinic acid, gallic acid ethyl ester and ellagic acid. To the best of our knowledge, this is the first study addressing the combined effects of global warming and Pc infection in chestnut.
Effect of Gamma Radiation on the Processability of New and Recycled PA-6 Polymers
Authors: González Niño Carlos , Vidal Julio , Del Cerro Martina , Royo-Pascual Lucía , Murillo-Ciordia Gonzalo , Castell Pere
Published: January 2023

The growing quantities of plastic waste have raised environmental concerns, with almost a quarter of disposed plastics being sent to landfill. This has motivated research efforts into various recycling technologies to ease dependence on fossil resources, increasing circularity. Irradiation of various kinds, such as electron beam, beta and gamma rays, has been studied in the past as a way of revamping end-of-life polymer properties. The present work focuses on the effects of gamma radiation on the processability of new and recycled polymers, which is intimately linked with their rheological properties. In this study, both virgin and recycled polymers were irradiated under different radiation doses and the effects of the radiation on their viscosity assessed and compared. Results were analyzed making use of different theoretical relationships, and the causes of the changes in rheology were investigated by means of various characterization techniques, such as GPC, FTIR, EPR and DSC. Finally, the rheological curves of all samples were fitted to the Ostwald–de Waele relationship and the dependence of its parameters on the absorbed dose fitted to a function.
Macro-Mesoscale Mechanical Properties of Basalt-Polyvinyl Alcohol Hybrid Fiber-Reinforced Low-Heat Portland Cement Concrete
Authors: Zhang Yu , Zheng Yuanxun
Published: January 2023

To investigate the mechanical properties of hybrid basalt fiber (BF) and polyvinyl alcohol fiber (PVAF)-reinforced low-heat Portland cement concrete (LHPCC), two groups of concrete were formulated. The BF and PVAF were equal in the first group, and the total fiber contents were 0–0.4%. The second group was the total fiber content of 0.3% and the occupancy of BF in the hybrid fiber of 0, 25%, 50%, 75%, and 100%. Two groups of concrete were tested for compressive, splitting tensile, and flexural strengths to illustrate the enhanced mechanism of the mechanical properties of LHPCC by hybrid fiber. The best mechanical property enhancement was achieved when BF and PVAF were in equal proportions and the fiber content was 0.3%. Meanwhile, the test results for the mechanical properties were also compared with the predicted values of ACI 318 and Eurocode 2. Moreover, the hybrid BF-PVAF-reinforced concrete was regarded as a three-phase composite material consisting of fiber-reinforced mortar, coarse aggregate, and an interfacial transition zone. The axial compressive and splitting tensile strengths, damage processes, and mechanical strengthening mechanisms of concrete were investigated for different total fiber content at equal ratios of BF and PVAF, and the results were compared with the macroscopic mechanical test findings. The results show that the conclusion of the meso-simulation matches well with the test. Finally, the effect of aggregate and hybrid fiber content on the mechanical properties of LHPCC was predicted by a simulation. The results of this study can provide references for future mechanical modeling, performance studies, and practical engineering applications of LHPCC.
Effect of Surface Polishing on Physical Properties of an Occlusal Splint Material for Additive Manufacturing under Protection Gas Post-Curing Condition
Authors: Wada Junichiro , Wada Kanae , Gibreel Mona , Wakabayashi Noriyuki , Iwamoto Tsutomu , Vallittu Pekka , Lassila Lippo
Published: January 2023

The aim of this study was to evaluate the effect of surface polishing as well as the post-curing atmospheres (air and nitrogen gas) on the physical properties of an occlusal splint material for additive manufacturing. Flexural strength, flexural modulus, Vickers hardness number (VHN), degree of carbon double bond conversion (DC), water sorption (WSP), and water solubility (WSL) were evaluated. Surface polishing significantly affected the evaluated properties. Regardless of the post-curing atmosphere, flexural strength, flexural modulus, VHN, and DC showed significantly higher values for the polished specimens when compared with the unpolished ones, while WSP and WSL were significantly lower for the polished specimens. Unpolished specimens post-cured at nitrogen gas showed significantly higher VHN and DC values. However, the effect of the post-curing at a nitrogen gas atmosphere was non-significant in polished specimens. The current results suggested that surface polishing plays a role in the physical properties of the evaluated occlusal splint material and can enhance all the evaluated properties regardless of the post-curing atmosphere. Meanwhile, the post-curing at a nitrogen gas atmosphere can enhance the VHN and DC but its effect is confined only to the surface layers, which can be removed during surface polishing.
Characteristics and Drivers of Marine Heatwaves in 2021 Summer in East Korea Bay, Japan/East Sea
Authors: Chen Sijie , Yao Yulong , Feng Yuting , Zhang Yongchui , Xia Changshui , Sian Kenny T. C. Lim Kam , Dong Changming
Published: January 2023

Marine heatwaves (MHWs) are persistent, discrete, extreme high-temperature events in the ocean, which can destructively affect marine ecosystems. Using satellite remote sensing data and reanalysis data from 1982 to 2021, we find that six indices characterizing the MHWs are in a remarkable increasing trend in the Japan/East Sea (JES), which shows that the most severe MHW events take place in the East Korean Bay (EKB) in the summer of 2021. Based on this finding, the present study focuses on the characteristics and mechanisms of the MHWs in the EKB and its adjacent areas from June to August 2021. The analysis reveals that the total days and mean intensity of MHWs that occur in the EKB are 1.84 and 1.47 times more than those averaged in the JES, respectively. It is shown that mechanisms for the occurrences of the MHWs in the summer of 2021 are caused by the atmospheric high-pressure system moving to the EKB area. Other reasons also decrease the water cooling: the net positive lateral heat fluxes across open boundaries, and the weak sea surface wind over the EKB area. Other possible reasons which cause the summer MHW events in 2021 need the oceanic numerical models to further investigate the issue.
Can MRI Be Used as a Sensor to Record Neural Activity?
Authors: Roth Bradley J.
Published: January 2023

Magnetic resonance provides exquisite anatomical images and functional MRI monitors physiological activity by recording blood oxygenation. This review attempts to answer the following question: Can MRI be used as a sensor to directly record neural behavior? It considers MRI sensing of electrical activity in the heart and in peripheral nerves before turning to the central topic: recording of brain activity. The primary hypothesis is that bioelectric current produced by a nerve or muscle creates a magnetic field that influences the magnetic resonance signal, although other mechanisms for detection are also considered. Recent studies have provided evidence that using MRI to sense neural activity is possible under ideal conditions. Whether it can be used routinely to provide functional information about brain processes in people remains an open question. The review concludes with a survey of artificial intelligence techniques that have been applied to functional MRI and may be appropriate for MRI sensing of neural activity.
Young Novice Drivers’ Cognitive Distraction Detection: Comparing Support Vector Machines and Random Forest Model of Vehicle Control Behavior
Authors: Xue Qingwan , Wang Xingyue , Li Yinghong , Guo Weiwei
Published: January 2023

The use of mobile phones has become one of the major threats to road safety, especially in young novice drivers. To avoid crashes induced by distraction, adaptive distraction mitigation systems have been developed that can determine how to detect a driver’s distraction state. A driving simulator experiment was conducted in this paper to better explore the relationship between drivers’ cognitive distractions and traffic safety, and to better analyze the mechanism of distracting effects on young drivers during the driving process. A total of 36 participants were recruited and asked to complete an n-back memory task while following the lead vehicle. Drivers’ vehicle control behavior was collected, and an ANOVA was conducted on both lateral driving performance and longitudinal driving performance. Indicators from three aspects, i.e., lateral indicators only, longitudinal indicators only, and combined lateral and longitudinal indicators, were inputted into both SVM and random forest models, respectively. Results demonstrated that the SVM model with parameter optimization outperformed the random forest model in all aspects, among which the genetic algorithm had the best parameter optimization effect. For both lateral and longitudinal indicators, the identification effect of lateral indicators was better than that of longitudinal indicators, probably because drivers are more inclined to control the vehicle in lateral operation when they were cognitively distracted. Overall, the comprehensive model built in this paper can effectively identify the distracted state of drivers and provide theoretical support for control strategies of driving distraction.
Optimal Transducer Placement for Deep Learning-Based Non-Destructive Evaluation
Authors: Kim Ji-Yun , Han Je-Heon
Published: January 2023

In this study, the Convolution Neural Network (CNN) algorithm is applied for non-destructive evaluation of aluminum panels. A method of classifying the locations of defects is proposed by exciting an aluminum panel to generate ultrasonic Lamb waves, measuring data with a sensor array, and then deep learning the characteristics of 2D imaged, reflected waves from defects. For the purpose of a better performance, the optimal excitation location and sensor locations are investigated. To ensure the robustness of the training model and extract the feature effectively, experimental data are collected by slightly changing the excitation frequency and shifting the location of the defect. The high classification accuracy for each defect location can be achieved. It is found that the proposed algorithm is also successfully applied even when a bar is attached to the panel.
Machine-Learning-Based Carbon Dioxide Concentration Prediction for Hybrid Vehicles
Authors: Tena-Gago David , Golcarenarenji Gelayol , Martinez-Alpiste Ignacio , Wang Qi , Alcaraz-Calero Jose M.
Published: January 2023

The current understanding of CO2 emission concentrations in hybrid vehicles (HVs) is limited, due to the complexity of the constant changes in their power-train sources. This study aims to address this problem by examining the accuracy, speed and size of traditional and advanced machine learning (ML) models for predicting CO2 emissions in HVs. A new long short-term memory (LSTM)-based model called UWS-LSTM has been developed to overcome the deficiencies of existing models. The dataset collected includes more than 20 parameters, and an extensive input feature optimization has been conducted to determine the most effective parameters. The results indicate that the UWS-LSTM model outperforms traditional ML and artificial neural network (ANN)-based models by achieving 97.5% accuracy. Furthermore, to demonstrate the efficiency of the proposed model, the CO2-concentration predictor has been implemented in a low-powered IoT device embedded in a commercial HV, resulting in rapid predictions with an average latency of 21.64 ms per prediction. The proposed algorithm is fast, accurate and computationally efficient, and it is anticipated that it will make a significant contribution to the field of smart vehicle applications.
A Machine Learning-Based Applied Prediction Model for Identification of Acute Coronary Syndrome (ACS) Outcomes and Mortality in Patients during the Hospital Stay
Authors: Sherazi Syed Waseem Abbas , Zheng Huilin , Lee Jong Yun
Published: January 2023

Nowadays, machine learning (ML) is a revolutionary and cutting-edge technology widely used in the medical domain and health informatics in the diagnosis and prognosis of cardiovascular diseases especially. Therefore, we propose a ML-based soft-voting ensemble classifier (SVEC) for the predictive modeling of acute coronary syndrome (ACS) outcomes such as STEMI and NSTEMI, discharge reasons for the patients admitted in the hospitals, and death types for the affected patients during the hospital stay. We used the Korea Acute Myocardial Infarction Registry (KAMIR-NIH) dataset, which has 13,104 patients’ data containing 551 features. After data extraction and preprocessing, we used the 125 useful features and applied the SMOTETomek hybrid sampling technique to oversample the data imbalance of minority classes. Our proposed SVEC applied three ML algorithms, such as random forest, extra tree, and the gradient-boosting machine for predictive modeling of our target variables, and compared with the performances of all base classifiers. The experiments showed that the SVEC outperformed other ML-based predictive models in accuracy (99.0733%), precision (99.0742%), recall (99.0734%), F1-score (99.9719%), and the area under the ROC curve (AUC) (99.9702%). Overall, the performance of the SVEC was better than other applied models, but the AUC was slightly lower than the extra tree classifier for the predictive modeling of ACS outcomes. The proposed predictive model outperformed other ML-based models; hence it can be used practically in hospitals for the diagnosis and prediction of heart problems so that timely detection of proper treatments can be chosen, and the occurrence of disease predicted more accurately.
Tele-Assessment of Functional Capacity through the Six-Minute Walk Test in Patients with Diabetes Mellitus Type 2: Validity and Reliability of Repeated Measurements
Authors: Pepera Garyfallia , Karanasiou Evmorfia , Blioumpa Christina , Antoniou Varsamo , Kalatzis Konstantinos , Lanaras Leonidas , Batalik Ladislav
Published: January 2023

A tele-assessed 6MWT (TL 6MWT) could be an alternative method of evaluating functional capacity in patients with diabetes mellitus type 2 (DM2). This study aimed to assess the validity and reliability of a TL 6MWT. The functional capacity of 28 patients with DM2 (75% men) aged 61 ± 13 years was evaluated twice via an indoor, center-based 6MWT (CB 6MWT) and twice outside each patient’s home via a web-based platform TL 6MWT. The study showed a high statistically significant correlation between the CB and TL 6MWT (Pearson’s r = 0.76, p < 0.001). Reliability testing showed no statistically significant differences in the distance covered (CB1: 492 ± 84 m and CB2: 506 ± 86 m versus TL1: 534 ± 87 m and TL2: 542 ± 93 m, respectively) and in the best distance of the TL 6MWT (545 ± 93 m) compared to the best CB distance (521 ± 83 m). Strong internal reliability for both the CB (intraclass correlation coefficient (ICC) = 0.93) and the TL 6MWT (ICC = 0.98) was found. The results indicate that a TL 6MWT performed outdoors can be a highly valid and reliable tool to assess functional capacity in patients with DM2. No learning effect between the TL and CB assessment was found, minimizing the need for repetition.
A Deep Learning Method Using Gender-Specific Features for Emotion Recognition
Authors: Zhang Li-Min , Li Yang , Zhang Yue-Ting , Ng Giap Weng , Leau Yu-Beng , Yan Hao
Published: January 2023

Speech reflects people’s mental state and using a microphone sensor is a potential method for human–computer interaction. Speech recognition using this sensor is conducive to the diagnosis of mental illnesses. The gender difference of speakers affects the process of speech emotion recognition based on specific acoustic features, resulting in the decline of emotion recognition accuracy. Therefore, we believe that the accuracy of speech emotion recognition can be effectively improved by selecting different features of speech for emotion recognition based on the speech representations of different genders. In this paper, we propose a speech emotion recognition method based on gender classification. First, we use MLP to classify the original speech by gender. Second, based on the different acoustic features of male and female speech, we analyze the influence weights of multiple speech emotion features in male and female speech, and establish the optimal feature sets for male and female emotion recognition, respectively. Finally, we train and test CNN and BiLSTM, respectively, by using the male and the female speech emotion feature sets. The results show that the proposed emotion recognition models have an advantage in terms of average recognition accuracy compared with gender-mixed recognition models.
An Adaptive ORB-SLAM3 System for Outdoor Dynamic Environments
Authors: Zang Qiuyu , Zhang Kehua , Wang Ling , Wu Lintong
Published: January 2023

Recent developments in robotics have heightened the need for visual SLAM. Dynamic objects are a major problem in visual SLAM which reduces the accuracy of localization due to the wrong epipolar geometry. This study set out to find a new method to address the low accuracy of visual SLAM in outdoor dynamic environments. We propose an adaptive feature point selection system for outdoor dynamic environments. Initially, we utilize YOLOv5s with the attention mechanism to obtain a priori dynamic objects in the scene. Then, feature points are selected using an adaptive feature point selector based on the number of a priori dynamic objects and the percentage of a priori dynamic objects occupied in the frame. Finally, dynamic regions are determined using a geometric method based on Lucas-Kanade optical flow and the RANSAC algorithm. We evaluate the accuracy of our system using the KITTI dataset, comparing it to various dynamic feature point selection strategies and DynaSLAM. Experiments show that our proposed system demonstrates a reduction in both absolute trajectory error and relative trajectory error, with a maximum reduction of 39% and 30%, respectively, compared to other systems.
Wearables in Nephrology: Fanciful Gadgetry or Prêt-à-Porter?
Authors: Stauss Madelena , Htay Htay , Kooman Jeroen P. , Lindsay Thomas , Woywodt Alexander
Published: January 2023

Telemedicine and digitalised healthcare have recently seen exponential growth, led, in part, by increasing efforts to improve patient flexibility and autonomy, as well as drivers from financial austerity and concerns over climate change. Nephrology is no exception, and daily innovations are underway to provide digitalised alternatives to current models of healthcare provision. Wearable technology already exists commercially, and advances in nanotechnology and miniaturisation mean interest is also garnering clinically. Here, we outline the current existing wearable technology pertaining to the diagnosis and monitoring of patients with a spectrum of kidney disease, give an overview of wearable dialysis technology, and explore wearables that do not yet exist but would be of great interest. Finally, we discuss challenges and potential pitfalls with utilising wearable technology and the factors associated with successful implementation.
Surgical Strategy for the Treatment of Facial Clefts
Authors: Roddi Roberto , Oo Aung , Pepe Ernesto , Naing Ei , Sung Shalom
Published: January 2023

Craniofacial clefts have an incidence of 1/700 [...]
An Effective Precision Afforestation System for UAV
Authors: Liu Haiyang , Chen Zhuo , Wang Zhiliang , Li Jian
Published: January 2023

Much agricultural and forestry land in the world cannot be accessed by ground planting equipment because of traffic, terrain, and other factors. This not only causes low efficiency and waste of resources, but also has a negative impact on the sustainable development of forestry. Therefore, it is significant to develop an accurate, efficient, and energy-saving aerial precision seeding system using unmanned aerial vehicle (UAV) technology to meet the actual needs of forestry planting. In this study, a UAV precision afforestation system with a GUI, afforestation UAV, positioning system, and information interaction system were developed using related approaches such as electronic information technology. The UAV airborne seeding device added a control circuit and electronic chip to control the launching speed of the cylinder and seed loading speed, while the UAV flight speed is jointly controlled to accurately control the UAV seeding depth and seed spacing. The experimental results showed that the maximum seeding depth of the afforestation equipment was 6.7 cm. At the same seed launching speed, the smaller the content of sand and gravel in the soil, the higher the sowing qualification index, and the greater the sowing depth. The average absolute error of dynamic route RTK-automatic control seeding position accuracy was 7.6 cm, and the average error of static position hovering seeding was 7.7 cm. Resulting from the separate sown experiments of three crops, the sowing pitch angle of 75° gave the highest germination rate. The UAV seeding device has a low missing seed index and a qualified seeding index of more than 95% at 120 r/min seeding speed. The seeding device studied in this paper has a good seeding effect, can meet the requirements of afforestation, and provides a new technical means for managing forest and plant resources.
Towards Legislation Responsive to Integrated Watershed Management Approaches and Land Tenure
Authors: Katusiime Juliet , Schütt Brigitta
Published: January 2023

Land tenure affects integrated watershed management approaches in various ways, such as influencing land use and investment in sustainability practices and decisions. However, some land tenure and integrated watershed management relations need more examination, including how the prevailing relevant legislation responds and the needed course of action. In this paper, we provide relevant evidence to support a shift to responsive actions and legislation through (a) examining land tenure scenarios affecting integrated watershed management, including the public–private land tenure co-existence from a watershed perspective; (b) the responsiveness of the prevailing relevant legislation to integrated watershed management and the land tenure scenarios and (c) identifying legislative remedies recommendable for responsiveness. We use qualitative methods to review secondary data sources, including four legislations, and complement them with field survey data. Field experiences are from three sub-catchments in the Lake Victoria basin, each representing a different land tenure system, as case studies. Land tenure links with integrated watershed management in various ways, such as influencing land use decisions. However, underscoring the relationship from the private and public land tenure perspective also indicates a complex and tense spatial relationship. As such, it likely limits adopting sustainable land use and management practices in watersheds as a case. Regardless, the perceptions from the study area indicate the land tenure systems and forms enabling sustainable choices and decisions, despite limitations such as tenure insecurity. The disconnect between integrated watershed management aspirations of ensuring sustainability, the land tenure abilities and the subsequent human practices is mainly institutional, with the relevant legislation indicating a low to moderate level of responsiveness to integrated watershed management approaches and land tenure, thus, abating effectiveness. Therefore, we suggest a shift towards responsive programming and legislation and the adoption of model legislation to support responsiveness replication. We also recommend further studies to assess the legal gaps and feasibility thereof.