bluuebunny/crossref_metadata_2025 huggingface dataset:
Automated Detection of Cannabis-Induced Alteration in Cardiac Autonomic Regulation of the Indian Paddy-Field Workers Using Empirical Mode Decomposition, Discrete Wavelet Transform and Wavelet Packet Decomposition Techniques with HRV Signals
Authors: Nayak Suraj Kumar , Jarzębski Maciej , Gramza-Michałowska Anna , Pal Kunal
Published: October 2022

Early detection of the dysfunction of the cardiac autonomic regulation (CAR) may help in reducing cannabis-related cardiovascular morbidities. The current study examined the occurrence of changes in the CAR activity that is associated with the consumption of bhang, a cannabis-based product. For this purpose, the heart rate variability (HRV) signals of 200 Indian male volunteers, who were categorized into cannabis consumers and non-consumers, were decomposed by Empirical Mode Decomposition (EMD), Discrete Wavelet transform (DWT), and Wavelet Packet Decomposition (WPD) at different levels. The entropy-based parameters were computed from all the decomposed signals. The statistical significance of the parameters was examined using the Mann–Whitney test and t-test. The results revealed a significant variation in the HRV signals among the two groups. Herein, we proposed the development of machine learning (ML) models for the automatic classification of cannabis consumers and non-consumers. The selection of suitable input parameters for the ML models was performed by employing weight-based parameter ranking and dimension reduction methods. The performance indices of the ML models were compared. The results recommended the Naïve Bayes (NB) model developed from WPD processing (level 8, db02 mother wavelet) of the HRV signals as the most suitable ML model for automatic identification of cannabis users.
Evaluation of Stress Distribution of Maxillary Anterior Segment during en Masse Retraction Using Posterior Mini Screw: A Finite Element Study
Authors: Ali Meer Juned , Bhardwaj Amit , Khan Mohammad Shoyab , Alwadei Farhan , Gufran Khalid , Alqahtani Abdullah Saad , Alqhtani Nasser Raqe , Alasqah Mohammed , Alsakr Abdulaziz Mohammad , Alghabban Rawda Omar
Published: October 2022

The current study aimed to perceive and estimate the distribution of stress generated by the forces on the maxillary anterior teeth during orthodontic retraction using the bilateral mini screw implant. Finite element models were generated from the three-dimensional (3D) reconstruction of the maxillary arch via cone–beam computed tomography (CBCT). These models imitate the retraction of maxillary anterior teeth with the mini screw placed as the skeletal anchorage. The titanium mini screw of 1.3 mm × 8 mm dimension was placed at a height of 9 mm between the first molar and second premolar on both sides of the maxilla. A nickel titanium (NiTi) coil spring of 9 mm length was attached from the mini screw implant to the power arm which generated a force of 250 gm/side. Two different power arms were placed between the lateral incisor and canine at a height of 4 mm (group 1) and 8 mm (group 2), respectively. There were no significant differences observed when the stress values were compared to the left side and the right side in group 1 with a power arm of 4 mm. In group 2, the stresses around the lateral incisors were found to be on the higher side when compared with the central incisors and canines. The length of the power arm shows no significant difference in stress distribution pattern on the left and right sides except for stresses moving from the canine region to the lateral incisor region with the increase in power arm height.
Mechanical Properties and Torque/Force Generation of XP-Endo Shaper, Trunatomy, Spring Endo File, and Spring Endo Heated Finish File, Part 1
Authors: Oh Soram , Jeon Bong-Ki , Chang Seok Woo
Published: October 2022

We evaluated the mechanical properties and torque/force generated during canal shaping by four NiTi files with innovative designs. Each of the 52 TruNatomy Prime, XP-endo Shaper, Spring Endo files with unheated finish (Spring Endo), and Spring Endo files with heated finish (Spring H) were subjected to bending, buckling, cyclic fatigue, and torsional resistance tests (n = 10 per NiTi file type). Canal shaping was simulated with J-shaped resin blocks (n = 10). Phase transformation behavior was investigated using differential scanning calorimetry (n = 2). Statistical analysis was performed by one-way ANOVA and the Games-Howell test. Spring Endo and Spring H files showed higher bending and buckling resistances, ultimate torsional strength, and elastic modulus than TruNatomy and XP-endo Shaper (p < 0.05). XP-endo Shaper demonstrated the highest cyclic fatigue resistance and angle of rotation to fracture (p < 0.05). The elastic modulus increased in the order of XP-endo Shaper, TruNatomy Prime, Spring H, and Spring Endo. During simulated canal shaping, XP-endo Shaper generated greater clockwise torque and less screw-in force compared to Spring Endo files, with superior cutting ability. TruNatomy Prime generated the least clockwise torque and screw-in force. At room temperature, TruNatomy and XP-endo Shaper files consisted of mixed phases of austenite, martensite, and R-phase; Spring H files consisted of martensite; and Spring Endo files consisted of austenite.
Adaptive Markov IMM Based Multiple Fading Factors Strong Tracking CKF for Maneuvering Hypersonic-Target Tracking
Authors: Luo Yalun , Li Zhaoming , Liao Yurong , Wang Haining , Ni Shuyan
Published: October 2022

Hypersonic targets have complex motion states and high maneuverability. The traditional interactive multi-model (IMM) has low tracking accuracy and a slow convergence speed. Therefore, this paper proposes a strong tracking cubature Kalman filter (CKF) adaptive interactive multi-model (AIMM) based on multiple fading factors. Firstly, this paper analyzes the structure of the CKF algorithm, introduces the fading factor of the strong tracking algorithm into the covariance matrix of the time update and measurement update, and adjusts the filter gain online and in real time, which can reduce the decline infilter accuracy caused by model mismatch. Secondly, Singer model, “current” statistical (CS) model, and Jerk model are selected in the model set of IMM and introduced singular value decomposition (SVD) decomposition to solve the problem that Cholesky decomposition cannot be performed in the CKF due to the model dimension expansion. Last, an adaptive algorithm for the Markov matrix in the IMM is proposed. The transition probability was adaptively modified by the value of the model likelihood function to enhance the proportion of matching models. The simulation results show that the proposed algorithm enhanced the proportion of matching models in the IMM and improved the tracking accuracy by 16.51% and the convergence speed by 37.5%.
Solar Ultraviolet Irradiance Characterization under All Sky Conditions in Burgos, Spain
Authors: García-Rodríguez Sol , García Ignacio , García-Rodríguez Ana , Díez-Mediavilla Montserrat , Alonso-Tristán Cristina
Published: October 2022

Solar Ultraviolet Radiation (UVR), which is identified as a major environmental health hazard, is responsible for a variety of photochemical reactions with direct effects on urban and aquatic ecosystems, human health, plant growth, and the deterioration of industrial systems. Ground measurements of total solar UVR are scarce, with low spatial and temporal coverage around the world, which is mainly due to measurement equipment maintenance costs and the complexities of equipment calibration routines; however, models designed to estimate ultraviolet rays from global radiation measurements are frequently used alternatives. In an experimental campaign in Burgos, Spain, between September 2020 and June 2022, average values of the ratio between horizontal global ultraviolet irradiance (GHUV) and global horizontal irradiance (GHI) were determined, based on measurements at ten-minute intervals. Sky cloudiness was the most influential factor in the ratio, more so than any daily, monthly, or seasonal pattern. Both the CIE standard sky classification and the clearness index were used to characterize the cloudiness conditions of homogeneous skies. Overcast sky types presented the highest values of the ratio, whereas the clear sky categories presented the lowest and most dispersed values, regardless of the criteria used for sky classification. The main conclusion, for practical purposes, was that the ratio between GHUV and GHI can be used to model GHUV.
Marinating and Grilling as Methods of Sensory Enhancement of Sous Vide Beef from Holstein-Friesian Bulls
Authors: Tkacz Katarzyna , Modzelewska-Kapituła Monika
Published: October 2022

An attempt was made to identify technological solutions that would improve the quality of products from the meat of Holstein-Friesian (HF) bulls, with particular emphasis on standardising the quality of the longissimus lumborum (LL) and semimembranosus (SM) muscles. Marinating (Mar) and grilling (Grill) were used in combination with the sous vide (SV) method. The effects of the type of muscle (LL or SM) and the applied treatments (SV, SVMar, and SVGrill) on the yield, colour, maximum shear force (WBSF), tenderness, juiciness, and aroma intensity of grilled and marinated meat were determined. The applied treatments had a significant influence on the meat yield (p < 0.001), WBSF (p < 0.001), tenderness (p < 0.01), and juiciness (p < 0.05) assessed in sensory evaluation. Additional treatments supported the optimisation of the aroma and taste of LL and SM and reduced the WBSF. The SVMar method optimised the beef’s tenderness, and therefore, it can be recommended for preparing meat from HF bulls for consumption.
Effects of Spray Application of Lactic Acid Solution and Aromatic Vinegar on the Microbial Loads of Wild Boar Carcasses Obtained under Optimal Harvest Conditions
Authors: Roila Rossana , Altissimi Caterina , Branciari Raffaella , Primavilla Sara , Valiani Andrea , Cambiotti Fausto , Cardinali Lorenzo , Cioffi Attilia , Ranucci David
Published: October 2022

Solutions of lactic acid 2% and aromatic vinegar were investigated for microbial load reduction on the surfaces of wild boar carcasses. The animals were hunted and processed according to production specifications to obtain the best hygiene for carcasses. The solutions were sprayed on carcass surfaces after skinning, and sites of 5 × 5 cm were sampled 2 h and 48 h post-treatment, with the carcasses under refrigeration conditions. The values of the microbial loads were lower for lactic-acid-treated sites, compared with control, after both 2 and 48 h. Nonetheless, the differences in the microbial loads were only higher than 1 Log/CFU 25 cm2 for the aerobic colony count. The aromatic vinegar resulted in lower values than in controls only after 48 h for the aerobic colony count, Staphylococcus count, and Lactobacillus count, with values always below 1 Log/CFU 25 cm2. The implementation of a lactic acid solution could represent a valuable strategy to reduce microbial growth on wild boar carcasses, thus becoming a relevant critical control point in this peculiar and niche meat production process.
Suggestion of Practical Application of Discrete Element Method for Long-Term Wear of Metallic Materials
Authors: Lee Sung-Je , Lee Jang-Hyun , Hwang Se-Yun
Published: October 2022

This study presents a simulation procedure for the wear of metallic materials exposed to long-term cumulative contact forces and introduces a numerical analysis procedure using the discrete element method (DEM) to predict the wear damage. Since the DEM can calculate the motion and contact load of each particle and the interaction between particles for each dynamic collision of particles, it was possible to analyze the motion of the particles causing metal wear. A method to reflect particle size, material properties, and long-term cumulative friction distance required by the DEM was proposed so that the collision and friction load between particles can be predicted practically. Considering the feature of wear suggested by Archard, it was shown that the wear amount can be predicted efficiently by converting the long-term load into an equivalent material constant. In addition, it was suggested that it is reasonable to determine the size of the particles in consideration of the size of the surface mesh of the metal surface. The accuracy of the analysis results obtained using the procedure proposed in this study was compared with that of the wear test results of metal material specimens presented by former studies. The numerical analysis was also performed in the reference study, but inaccurate results were derived compared to the analysis results. The reason for the inaccuracy of the numerical model performed in the previous study was found to be environmental factors that cannot be considered in a numerical analysis. In this study, it was determined that it was because the behavior of particles and the load transferred to the specimen were not well simulated, which remains a problem for future research. As a result, it was confirmed that it is possible to compute a worn shape similar to the measured shape of experiments. Thereafter, the change in the contact load predicted by simulation is discussed in terms of wear shape and cross-sectional area loss ratio.
Toward Sustainability of the Aqueous Phase Reforming of Wastewater: Heat Recovery and Integration
Authors: Heras Francisco , de Oliveira Adriana S. , Baeza José A. , Calvo Luisa , Ferro Víctor R. , Gilarranz Miguel A.
Published: October 2022

Aqueous-phase reforming has been revealed as a novel, interesting and efficient process for the treatment of wastewater containing organic pollutants. However, due to the relatively severe operating conditions (above 15 bar and 200 °C), this process could become economically competitive if any solution for energy or material valorization is implemented. Most research has been devoted to direct the process to H2 production as an alternative to reach economic sustainability, but the results obtained were not competitive in the current market of hydrogen and syngas. In this work, a preliminary simulation study (using Aspen HYSYS software) of the process heat balance in different conditions was implemented to induce a heat integration that would allow the auto-sustainability of the process, even generating in some cases an excess of energy that could constitute an opportunity for a positive economic balance. The results showed that this approach would only be possible by maximizing the methane production to the detriment of hydrogen production.
A Reinforcement Learning Model of Multiple UAVs for Transporting Emergency Relief Supplies
Authors: Hachiya Daiki , Mas Erick , Koshimura Shunichi
Published: October 2022

In large-scale disasters, such as earthquakes and tsunamis, quick and sufficient transportation of emergency relief supplies is required. Logistics activities conducted to quickly provide appropriate aid supplies (relief goods) to people affected by disasters are known as humanitarian logistics (HL), and play an important role in terms of saving the lives of those affected. In the previous last-mile distribution of HL, supplies are transported by trucks and helicopters, but these transport methods are sometimes not feasible. Therefore, the use of unmanned aerial vehicles (UAVs) to transport supplies is attracting attention due to their convenience regardless of the disaster conditions. However, existing transportation planning that utilizes UAVs may not meet some of the requirements for post-disaster transport of supplies. Equitable distribution of supplies among affected shelters is particularly important in a crisis situation, but it has not been a major consideration in the logistics of UAVs in the existing study. Therefore, this study proposes transportation planning by introducing three crucial performance metrics: (1) the rapidity of supplies, (2) the urgency of supplies, and (3) the equity of supply amounts. We formulated the routing problem of UAVs as the multi-objective, multi-trip, multi-item, and multi-UAV problem, and optimize the problem with Q-learning (QL), one of the reinforcement learning methods. We performed reinforcement learning for multiple cases with different rewards and quantitatively evaluated the transportation of each countermeasure by comparing them. The results suggest that the model improved the stability of the supply of emergency relief supplies to all evacuation centers when compared to other models.
A Model-Based Investigation of the Performance Robustness of the Deflector Jet Servo Valve
Authors: Ren Yukai , Yan Hao , Mao Qiyuan , Zuo Zheqing , Hao He
Published: October 2022

Although it possesses the capabilities of both anti-contamination and rapid response, the deflector jet servo valve is still confronted with the issue of weak performance robustness, usually manifesting as considerable uncertainty of the product pressure indices. To elaborate on the complex internal mechanism of deflector jet valves and figure out the origins of performance fluctuations, a three-dimensional mathematical model of the deflector jet pilot valve is constructed, in which a series of assumptions are presented to apply specific theorems to different regions of the flow field. Numerical simulations and experiments show that this theoretical system can provide a distinct and logical explanation for both the internal flow distribution and the external performance of the servo valve. On this basis, the causes of performance fluctuations are discussed, concerning the installation error of the deflector and the machining error of the shunt wedge. Calculations show that the latter can bring about remarkable performance variation. Quantificationally, a 10 micron width error of the shunt wedge will induce 7.4% and 3.6% drifts of the receiver pressure and the pressure gain, respectively. However, further analyses confirm that a decrease in the deflector jet distance will lead to dramatic deterioration of the valve’s susceptibility to errors. Hence, it is concluded that to enhance the performance robustness of servo valve products, the machining accuracy of the shunt wedge and non-negative errors of the deflector jet distance should both be guaranteed.
Discretization of the Urban and Non-Urban Shape: Unsupervised Machine Learning Techniques for Territorial Planning
Authors: Fiorini Lorena , Falasca Federico , Marucci Alessandro , Saganeiti Lucia
Published: October 2022

One of the goals of the scientific community is to equip the discipline of spatial planning with efficient tools to handle huge amounts of data. In this sense, unsupervised machine learning techniques (UMLT) can help overcome this obstacle to further the study of spatial dynamics. New machine-learning-based technologies make it possible to simulate the development of urban spatial dynamics and how they may interact with ecosystem services provided by nature. Modeling information derived from various land cover datasets, satellite earth observation and open resources such as Volunteered Geographic Information (VGI) represent a key structural step for geospatial support for land use planning. Sustainability is certainly one of the paradigms on which planning and the study of past, present and future spatial dynamics must be based. Topics such as Urban Ecosystem Services have assumed such importance that they have become a prerogative on which to guide the administration in the difficult process of transformation, taking place not only in the urban context, but also in the peri-urban one. In this paper, we present an approach aimed at analyzing the performance of clustering methods to define a standardized system for spatial planning analysis and the study of associated dynamics. The methodology built ad hoc in this research was tested in the spatial context of the city of L’Aquila (Abruzzo, Italy) to identify the urbanized and non-urbanized area with a standardized and automatic method.
Water Retention Curve of Biocemented Sands Using MIP Results
Authors: Cardoso Rafaela , Vieira Joana , Borges Inês
Published: October 2022

Biocementation is a soil treatment technique wherein bacteria living in soil pores promote the precipitation of calcium carbonate. One of the most recent applications of this treatment is to provide resistance against the erosion of slopes by creating a resistant cover but still allowing infiltration to avoid water runoff. For modeling infiltration, it is fundamental to know the water retention curve of the treated material. This may not be an easy task because the soils most suitable for biocementation treatment are sands, due to their large pore sizes and consequent high permeability. The water retention curves (WRCs) of such types of soil are characterized for having a very small air entry value, followed by an almost-horizontal zone, which cannot be measured by using the vapor equilibrium, most of the existing sensors, or a water dewpoint potentiometer. Data from mercury intrusion porosimetry (MIP) tests can be used as an alternative to find the WRC, and this is explored in this paper. The model for the water retention curve presented considers the deformability of the soil during the MIP test, assuming an isotropic elastic behavior. The WRC derived from the MIP tests is well-fitted to the points measured by using a water dewpoint psychrometer (only for suctions above 1 MPa) and vapor equilibrium.
On the Universally Optimal Activation Function for a Class of Residual Neural Networks
Authors: Zhao Feng , Huang Shao-Lun
Published: October 2022

While non-linear activation functions play vital roles in artificial neural networks, it is generally unclear how the non-linearity can improve the quality of function approximations. In this paper, we present a theoretical framework to rigorously analyze the performance gain of using non-linear activation functions for a class of residual neural networks (ResNets). In particular, we show that when the input features for the ResNet are uniformly chosen and orthogonal to each other, using non-linear activation functions to generate the ResNet output averagely outperforms using linear activation functions, and the performance gain can be explicitly computed. Moreover, we show that when the activation functions are chosen as polynomials with the degree much less than the dimension of the input features, the optimal activation functions can be precisely expressed in the form of Hermite polynomials. This demonstrates the role of Hermite polynomials in function approximations of ResNets.
Is Portugal Starting to Burn All Year Long? The Transboundary Fire in January 2022
Authors: Couto Flavio T. , Santos Filippe L. M. , Campos Cátia , Andrade Nuno , Purificação Carolina , Salgado Rui
Published: October 2022

Changes in the large fire seasons induced by climate variability may have implications in several sectors of modern society. This communication aims to investigate possible changes in the behaviour of active fires during the wintertime and document an event that occurred in the transboundary mountainous region in the north-western Iberian Peninsula between Portugal and Spain on 28 January 2022. The VIIRS active fire data, a satellite product, were analysed for the period between December 2012 and February 2022. The Meso-NH model was used to explore the atmospheric conditions during the event that burned almost 2400 ha. It was configured in a single domain with a horizontal resolution of 1500 m (300 × 300 grid points). The study highlights an increase in fire occurrence during the winter of 2021/22 and indicates that climate variability may create atmospheric conditions propitious for fire development even during the winter. The mild temperatures, dry air, and easterly flow affecting northern Portugal played an important role in the fire that occurred on 28 January 2022. Local orographic effects associated with downslope flow favoured fire propagation. Given the lack of knowledge about large winter fires, this study can be a starting point for future research on this subject.
Analytical Study on the Steady-State Thermal Blooming of Incoherent Combining Beam
Authors: Zhang Ke , Sun Quan , Chu Xiuxiang
Published: October 2022

The incoherent combined beam of lasers has many important applications due to its simple technology and excellent expansibility. Thermal blooming is one factor that will seriously affect the propagation of the combined beam in the atmosphere. Based on the analytical expression of thermal blooming for a Gaussian beam, the thermal blooming of the incoherent combined beam with a basic arrangement was studied and analyzed. From the evolution of thermal blooming for the incoherent combined beam with a basic arrangement, the thermal blooming for the incoherent combined beam with a complex arrangement can be predicted. As an example, incoherent beams with seven channels were studied. Results show that the thermal lens effect will split the beam located at the central path of heat into two parts.
A Closure Study of Secondary Organic Aerosol Estimation at an Urban Site of Yangtze River Delta, China
Authors: Wan Zichao , Song Kai , Zhu Wenfei , Yu Ying , Wang Hui , Shen Ruizhe , Tan Rui , Lv Daqi , Gong Yuanzheng , Yu Xuena , Chen Shiyi , Zeng Limin , Lou Shengrong , Yu Yijun , Guo Song
Published: October 2022

Secondary organic aerosols (SOA) are crucial components of ambient particulate matters. However, their composition and formation mechanisms remain uncertain. To investigate the SOA formation and evaluate various SOA estimation approaches, a comprehensive measurement was conducted at an urban site, Changzhou, in Yangtze River Delta (YRD) region. 98 kinds of volatile organic compounds (VOCs) were measured by an online gas chromatography-mass spectrometer/flame ionization detector (GC-MS/FID). Non-refractory submicron particulate matters (NR-PM1) were measured by an Aerodyne Aerosol Chemical Speciation Monitor (ACSM). Both bottom-up approaches, i.e., VOCs oxidation yield method, and top-down approaches, i.e., elemental carbon (EC) tracer method and ACSM, combined with positive matrix factorization (PMF) method, were utilized to estimate SOA. ACSM-PMF method estimated the highest SOA concentration, followed by EC tracer method. SOA from VOCs oxidation yield method accounted for 43.2 ± 41.9% of that from EC tracer method, suggesting the existence of missing SOA precursors, e.g., semivolatile organic compounds. The influencing factors of SOA formation were investigated and a good correlation of SOA with odd oxygen rather than aerosol liquid water content was found, suggesting the importance of photochemical formation of SOA.
Medicane Ianos: 4D-Var Data Assimilation of Surface and Satellite Observations into the Numerical Weather Prediction Model WRF
Authors: Vourlioti Paraskevi , Mamouka Theano , Agrafiotis Apostolos , Kotsopoulos Stylianos
Published: October 2022

This work investigates extreme weather events such as the onset of medicanes, which can cause severe socioeconomic impacts, along with their predictability. In order to accurately forecast such events, the Weather Research and Forecasting (WRF) model and its state-of-the-art data assimilation modeling framework (WRFDA) were set up to produce high-resolution forecasts for the case study of Medicane Ianos, which affected Greece between 17 and 19 September 2020. Information from weather stations and the satellite precipitation product IMERG was blended with the background model information from the Global Forecast System (GFS) using the 4D variational data assimilation (4D-Var) technique. New fields in an 18 km spatial resolution domain covering Europe were generated and utilized as improved initial conditions for the forecast model. Forecasts were issued based on these improved initial conditions at two nested domains of 6 km and 2 km spatial resolution, with the 2 km domain enclosing Greece. Denial experiments, where no observational data were assimilated in the initial boundary conditions, showed that the temperature fields benefited throughout the forecasting horizon from the assimilation (ranging from a 5 to 10% reduction in the average MAE values), while neutral to slightly positive (ranging from a 0.4 to 2% reduction in the average MAE values) improvement was found for wind, although not throughout the forecast horizon. The increase in spatial resolution did not significantly reduce the forecast error, but was kept at the same small order of magnitude. A tendency of the model to overpredict precipitation regardless of assimilation was observed. The assimilation of the IMERG data improved the precipitation forecasting ability up to the 18th hour of forecast. When compared to assimilation experiments that excluded IMERG data, the assimilation of IMERG data produced a better representation of the spatial distribution of the precipitation fields.
Machine Learning-Based Fog Nowcasting for Aviation with the Aid of Camera Observations
Authors: Bartok Juraj , Šišan Peter , Ivica Lukáš , Bartoková Ivana , Malkin Ondík Irina , Gaál Ladislav
Published: October 2022

In aviation, fog is a severe phenomenon, causing difficulties in airport traffic management; thus, accurate fog forecasting is always appreciated. The current paper presents a fog forecast at the Poprad-Tatry Airport, Slovakia, where various methods of machine learning algorithms (support vector machine, decision trees, k-nearest neighbors) are adopted to predict fog with visibility below 300 m for a lead time of 30 min. The novelty of the study is represented by the fact that beyond the standard meteorological variables as predictors, the forecast models also make use of information on visibility obtained through remote camera observations. Cameras observe visibility using tens of landmarks in various distances and directions from the airport. The best performing model reached a score level of 0.89 (0.23) for the probability of detection (false alarm ratio). One of the most important findings of the study is that the predictor, defined as the minimum camera visibilities from eight cardinal directions, helps improve the performance of the constructed machine learning models in terms of an enhanced ability to forecast the initiation and dissipation of fog, i.e., the moments when a no-fog event turns into fog and vice versa. Camera-based observations help to overcome the drawbacks of the automated sensors (predominantly point character of measurements) and the human observers (complex, but lower frequency observations), and offer a viable solution for certain situations, such as the recent periods of the COVID-19 pandemic.
Rapid Warming in the Australian Alps from Observation and NARCliM Simulations
Authors: Ji Fei , Nishant Nidhi , Evans Jason P. , Di Luca Alejandro , Di Virgilio Giovanni , Cheung Kevin K. W. , Tam Eugene , Beyer Kathleen , Riley Matthew L.
Published: October 2022

The Australian Alps are the highest mountain range in Australia, which are important for biodiversity, energy generation and winter tourism. Significant increases in temperature in the past decades has had a huge impact on biodiversity and ecosystem in this region. In this study, observed temperature is used to assess how temperature changed over the Australian Alps and surrounding areas. We also use outputs from two generations of NARCliM (NSW and Australian Regional Climate Modelling) to investigate spatial and temporal variation of future changes in temperature and its extremes. The results show temperature increases faster for the Australian Alps than the surrounding areas, with clear spatial and temporal variation. The changes in temperature and its extremes are found to be strongly correlated with changes in albedo, which suggests faster warming in cool season might be dominated by decrease in albedo resulting from future changes in natural snowfall and snowpack. The warming induced reduction in future snow cover in the Australian Alps will have a significant impact on this region.
Modeling of Atmospheric Dispersion of Jarosite Particles from Tailing Waste in Mitrovica, Kosovo
Authors: Kerolli Mustafa Mihone , Djokic Jelena , Ćurković Lidija
Published: October 2022

Most of the zinc producers in the world use the jarosite process to improve zinc recovery and to remove iron as an undesirable constituent of zinc ores. Jarosite waste released from the zinc extraction process in Mitrovica, Kosovo has led to severe environmental problems due to toxic heavy metals. This industrial waste from the Zn hydrometallurgy process was abandoned on an open field, being exposed to meteorological conditions and aging. The chemical composition and grain size distribution of the jarosite waste deposit was determined. Microwave digestion procedures were used on whole jarosite samples for use in inductively coupled plasma optical emission spectrometry trace metal analysis (ICP-OES). In addition, different weathering conditions were considered for testing the emission rate of the particles in the laboratory, including relative humidity, wind speed, and temperature. Terrain properties, urban infrastructure, source formation, and location were used for modeling with the AERMOD View-Gaussian air dispersion model. The modeling results showed a range of pollution exceeding the maximum limits in an area of 3 km in the conditions of southeast wind direction and wind speed exceeding 10 m s−1, heavily polluting the city of Mitrovica.
Development and Application of the SmartAQ High-Resolution Air Quality and Source Apportionment Forecasting System for European Urban Areas
Authors: Siouti Evangelia , Skyllakou Ksakousti , Kioutsioukis Ioannis , Patoulias David , Fouskas George , Pandis Spyros N.
Published: October 2022

Air pollution forecasting systems are useful tools for the reduction in human health risks and the eventual improvement of atmospheric quality on regional or urban scales. The SmartAQ (Smart Air Quality) forecasting system combines state-of-the-art meteorological and chemical transport models to provide detailed air pollutant concentration predictions at a resolution of 1 × 1 km2 for the urban area of interest for the next few days. The Weather Research and Forecasting (WRF) mesoscale numerical weather prediction model is used to produce meteorological fields and the PMCAMx (Particulate Matter Comprehensive Air quality Model with extensions) chemical transport model for the simulation of air pollution. SmartAQ operates automatically in real time and provides, in its current configuration, a three-day forecast of the concentration of tens of gas-phase air pollutants (NOx, SO2, CO, O3, volatile organic compounds, etc.), the complete aerosol size/composition distribution, and the source contributions for all primary and secondary pollutants. The system simulates the regional air quality in Europe at medium spatial resolution and can focus, using high resolution, on any urban area of the continent. The city of Patras in Greece is used for the first SmartAQ application, taking advantage of the available Patras’ dense low-cost sensor network for PM2.5 (particles smaller than 2.5 μm) concentration measurements. Advantages of SmartAQ include (a) a high horizontal spatial resolution of 1 × 1 km2 for the simulated urban area; (b) advanced treatment of the organic aerosol volatility and chemistry; (c) use of an updated emission inventory that includes not only the traditional sources (industry, transport, agriculture, etc.), but also biomass burning from domestic heating and cooking; (d) forecasting of not only the pollutant concentrations, but also of the sources contributions for each one of them using the Particulate matter Source Apportionment Technology (PSAT) algorithm.
“Flower Power”: Controlled Inhalation of THC-Predominant Cannabis Flos Improves Health-Related Quality of Life and Symptoms of Chronic Pain and Anxiety in Eligible UK Patients
Authors: Moreno-Sanz Guillermo , Madiedo Alvaro , Lynskey Michael , Brown Matthew R. D.
Published: October 2022

In November 2018, the UK’s Home Office established a legal route for eligible patients to be prescribed cannabis-based products for medicinal use in humans (CBPMs) as unlicensed medicines. These include liquid cannabis extracts for oral administration (“oils”) and dried flowers for inhalation (“flos”). Smoking of CBPMs is expressly prohibited. To date, THC-predominant cannabis flowers remain the most prescribed CBPMs in project Twenty21 (T21), the first multi-center, prospective, observational UK cannabis patient registry. This observational, prospective data review analyzes patient-reported outcome measures (PROMS) collected by T21 associated with the inhalation of KHIRON 20/1, the most prescribed CBPM in the project. PROMS collected at baseline and at subsequent 3-month follow-up included health-related quality of life (HRQoL), general mood, and sleep. Condition-specific measures of illness severity were performed with the Brief Pain Inventory Short Form (BPI-SF) and the Generalized Anxiety Disorder 7-Item Scale (GAD-7). Participants (N = 344) were mostly males (77.6%, average age = 38.3) diagnosed mainly with chronic pain (50.9%) and anxiety-related disorders (25.3%). Inhalation of KHIRON 20/1 was associated with a marked increase in self-reported HRQoL, general mood, and sleep (N = 344; p < 0.001). Condition-specific assessments showed significant improvements in pain severity (T = 6.67; p < 0.001) and interference (T = 7.19; p < 0.001) in patients using KHIRON 20/1 for chronic pain (N = 174). Similar results were found for patients diagnosed with anxiety-related disorders (N = 107; T = 12.9; p < 0.001). Our results indicate that controlled inhalation of pharmaceutical grade, THC-predominant cannabis flos is associated with a significant improvement in patient-reported pain scores, mood, anxiety, sleep disturbances and overall HRQoL in a treatment-resistant clinical population.
Medical Records: A Historical Narrative
Authors: Lorkowski Jacek , Pokorski Mieczyslaw
Published: October 2022

The history of medical records is thousand-year-long, with earlier roots in ancient civilizations. Until the 19th century, medical records mainly served educational purposes, later assuming other roles such as in insurance or legal procedures. This article comprehensively describes and reviews the development of medical records from ancient to modern times in Europe and North America, reflecting alterations and adaptations compliant with the mental and technological capabilities of a given period. We searched PubMed and Google Scholar databases to collect pertinent articles. English articles or those having English abstracts were considered. The search terms included “Medical Records,” “Health Records,” “History of Medicine,” and “eHealth” and covered the last hundred years. References were also picked out from the identified articles. Overall, 600 articles were identified, 158 of which were judged thematically relevant. The general conclusion is that medical records undergo a revolutionary change from paper-based to electronic format, which reflects the development of eHealth systems. The migration process to eHealth records involves the use of artificial intelligence (AI) algorithms that streamline medical services by using faster and simpler working methods. AI benefits both patients and providers as it improves patient management and communication among medical centers, spares resources, identifies contamination or infections, and limits health costs. These advantages have become pointedly apparent during the recent COVID-19 scourge.
Soft Gripper with Electro-Thermally Driven Artificial Fingers Made of Tri-Layer Polymers and a Dry Adhesive Surface
Authors: Li Xiangmeng , Shi Qiangshengjie , Wei Huifen , Zhao Xiaodong , Tong Zhe , Zhu Xijing
Published: October 2022

Soft grippers have attracted great interest in the soft robotics research field. Due to their lack of deformability and control over compliance, it can be challenging for them to pick up objects that are too large or too small in size. In particular, compliant objects are vulnerable to the large grasping force. Therefore, it is crucial to be able to adjust the stiffness of the gripper materials. In this study, a soft gripper consisting of three artificial fingers is reported on. Each of the artificial fingers is made of a tri-layer polymer structure. An exterior layer, made of an ecoflex–graphene composite is embedded with electric wires as a heating source, by applying direct-current potential. The Joule heat not only allows for deformation of the exterior layer, but also transfers heat to the middle layer of the thermoplastic polyurethane (TPU) elastomer. As a result, the stiffness of the TPU layer can be adjusted using electro-thermal heating. Meanwhile, the third layer consists of a polydimethylsiloxane replica as a supporting layer with a gecko-inspired dry adhesive structure. By applying voltage through electric wires, the artificial fingers can bend and, thus, the soft gripper can hold the objects, with the help of the dry adhesive layer. Finally, objects like a shuttlecock, tennis ball and a glass beaker, can be picked up by the soft gripper. This research may provide an insight for the design and fabrication of soft robotic manipulators.
Biomechanical Effects of Adding an Ankle Soft Actuation in a Unilateral Exoskeleton
Authors: Otálora Sophia , Ballen-Moreno Felipe , Arciniegas-Mayag Luis , Cifuentes Carlos A. , Múnera Marcela
Published: October 2022

Stroke disease leads to a partial or complete disability affecting muscle strength and functional mobility. Early rehabilitation sessions might induce neuroplasticity and restore the affected function or structure of the patients. Robotic rehabilitation minimizes the burden on therapists by providing repetitive and regularly monitored therapies. Commercial exoskeletons have been found to assist hip and knee motion. For instance, unilateral exoskeletons have the potential to become an effective training system for patients with hemiparesis. However, these robotic devices leave the ankle joint unassisted, essential in gait for body propulsion and weight-bearing. This article evaluates the effects of the robotic ankle orthosis T-FLEX during cooperative assistance with the AGoRA unilateral lower-limb exoskeleton (hip and knee actuation). This study involves nine subjects, measuring muscle activity and gait parameters such as stance and swing times. The results showed a reduction in muscle activity in the Biceps Femoris of 50%, Lateral Gastrocnemius of 59% and Tibialis Anterior of 35% when adding T-FLEX to the AGoRA unilateral lower-limb exoskeleton. No differences were found in gait parameters. Nevertheless, stability is preserved when comparing the two legs. Future works should focus on evaluating the devices in ground tests in healthy subjects and pathological patients.
Pathogenesis of Huntington’s Disease: An Emphasis on Molecular Pathways and Prevention by Natural Remedies
Authors: Irfan Zainab , Khanam Sofia , Karmakar Varnita , Firdous Sayeed Mohammed , El Khier Bothaina Samih Ismail Abou , Khan Ilyas , Rehman Muneeb U. , Khan Andleeb
Published: October 2022

Background: Huntington’s disease is an inherited autosomal dominant trait neuro-degenerative disorder caused by changes (mutations) of a gene called huntingtin (htt) that is located on the short arm (p) of chromosome 4, CAG expansion mutation. It is characterized by unusual movements, cognitive and psychiatric disorders. Objective: This review was undertaken to apprehend biological pathways of Huntington’s disease (HD) pathogenesis and its management by nature-derived products. Natural products can be lucrative for the management of HD as it shows protection against HD in pre-clinical trials. Advanced research is still required to assess the therapeutic effectiveness of the known organic products and their isolated compounds in HD experimental models. Summary: Degeneration of neurons in Huntington’s disease is distinguished by progressive loss of motor coordination and muscle function. This is due to the expansion of CAG trinucleotide in the first exon of the htt gene responsible for neuronal death and neuronal network degeneration in the brain. It is believed that the factors such as molecular genetics, oxidative stress, excitotoxicity, mitochondrial dysfunction, neuroglia dysfunction, protein aggregation, and altered UPS leads to HD. The defensive effect of the natural product provides therapeutic efficacy against HD. Recent reports on natural drugs have enlightened the protective role against HD via antioxidant, anti-inflammatory, antiapoptotic, and neurofunctional regulation.
Risk Factors Associated with Mental Health Outcomes during the Post-Quarantine Period of the COVID-19 in Saudi Population: A Cross-Sectional Study
Authors: Ennaceur Soukaina
Published: October 2022

Background: The present study aims to evaluate the mental health symptoms in the Saudi population during the COVID-19 post-quarantine period and to identify the risk factors associated with the severity of the symptoms. Methods: Anxiety was measured with the 7-item Generalized Anxiety Disorder questionnaire, depression with the 9-item Patient Health Questionnaire, insomnia with the 7-item Insomnia Severity Index, and distress with the 22-item Impact Event Scale-Revised questionnaire. Results: A total of 885 respondents answered the online questionnaires. The majority were women (72.8%), married (67.4%), have children (59.3%), and with high education levels (93.2%). The results showed that a high number of the respondents experienced mild to severe symptoms of anxiety (533; 60.3%), depression (659; 47.5%), insomnia (510; 57.6%), and distress (645; 72.9%). The multivariable logistic analysis demonstrated severe anxiety and insomnia among women (OR = 1.71; 95% CI 1.07–1.98; p < 0.001 and OR = 2.00; 95% CI 1.78–2.35; p = 0.002); severe depression among those under 35 (OR = 2.06; 95% CI 1.97–2.44; p = 0.001; and severe distress among non-Saudi respondents (OR = 1.71; 95% CI 1.09–1.93; p < 0.001). Conclusions: The results might help in establishing precautionary measures for protecting the mental health of the general population during pandemics.
Exploring the Effects of the COVID-19 Pandemic on Mental Health and Well-Being of Migrant Populations in Europe: An Equity-Focused Scoping Review
Authors: Alarcão Violeta , Virgolino Ana , Stefanovska-Petkovska Miodraga , Neves Júlia
Published: October 2022

The pandemic is aggravating health inequalities, particularly mental health inequalities, while revealing the social determinants of these inequalities, including migration as a social determinant that mediates the interaction of social, economic, cultural, institutional, and structural factors with health indicators. Therefore, it is of most relevance to identify the multiple interconnected factors that influence the mental health and well-being of migrant populations. A scoping review was developed to map the research performed in this area and to identify any gaps in knowledge, following the PRISMA extension for scoping reviews. MEDLINE, Scopus, and WHO Global Health research databases on COVID-19 were searched from January 2020 to October 2021. The review followed the inclusion criteria Population/Concept/Context (PCC): Population-Adult International migrants (including refugees, asylum seekers, and undocumented migrants); Concept-determinants of (and factors influencing) mental health and well-being; Context-COVID-19 anywhere in the world. Of the sixty-five selected studies, eleven were from European countries and were the focus of this review with special attention to health inequalities experienced by migrants in Europe. The results cover a diversity of themes related to the effects of COVID-19 on the mental health of migrants (country-level environmental factors, social determinants of mental health, mental health indicators and outcomes), responses (such as solidarity and resilience), populations, and study methods. The evidence found can inform recommendations and interventions focused on health promotion and mitigation of the inequalities accentuated by the pandemic.