The electric network frequency (ENF), often referred to as the industrial heartbeat, plays a crucial role in the power system. In recent years, it has found applications in multimedia evidence identification for court proceedings and audio-visual temporal source identification. This paper introduces a ENF region classification model named UniTS-SinSpec within the UniTS framework. The model integrates the si-nusoidal activation function and spectral attention mechanism while also redesigning the model frame-work. Training is conducted using a public dataset on the open science framework platform (OSF), with final experimental results demonstrating that after parameter optimization, the UniTS-SinSpec model achieves an average validation accuracy of 97.47%, surpassing current state-of-the-art and baseline models. Accurate classification can significantly aid in ENF temporal source identification. Future re-search will focus on expanding dataset coverage and diversity to verify the model's generality and ro-bustness across different regions, time spans, and data sources. Additionally, it aims to explore extensive application potential of ENF region classification in preventing crimes such as telecommunications fraud, terrorism, and child pornography.

The reactive nature of traditional frequency stability methods can lead to delayed corrective actions and unnecessary loss-of-load. This work presents a distributed model predictive control method for proactive power system frequency stability. Dynamic state estimation model is derived through a particle filter. By being able to estimate the future state of frequency, corrective actions can be taken before the system reaches a critical condition. Proactive approach makes it possible to optimize the response to a disturbance, which results in a decrease of the amount of compensation utilized. The method is tested via Matlab simulations based on Kundur's Two-Area System, and the IEEE 14-Bus system. Performance metrics are provided and evaluated against other contemporary solutions found in literature. Easy-to-derive model, without hard-to-design parameters, indicate potential towards real-life applications.

Proteins are the workhorses of the cell that perform biological functions by interacting with other proteins. Many statistical methods for protein-protein interaction (PPI) have been studied without considering time-dependent changes in networks and the functionalities. I introduced a novel method that models PPI networks as being dynamic in nature and evolving time-varying multivariate distribution with Conditional Random Fields (CRF). This research is directed towards implementing this new combinatorial algorithm on massively parallel architectures such as Graphics Processing Units (GPUs) for efficient computations for large scale bioinformatics datasets. I compared Conditional Random Fields (CRF) and the proposed novel method using CRF combined with the Block Coordinate Descent algorithm for human protein-protein interaction data set. Both are implemented on GPU-Accelerated Computing Architecture and the proposed novel method showed the advantages in predicting protein-protein interaction sites. I also show that the proposed approach is more efficient in 6.13% than standalone CRF++ in predicting protein-protein interaction sites.

Structural Units (SU) is a novel unit system, proposed as compatible to the International System of Units (SI), rooted in Spacetime Structure. Unlike SI, which evolved over history without a fixed reference frame, SU defines one Structural Unit as the space and time between two vertices in the Spacetime Structure. This perspective offers a unique viewpoint, where space and time units are proportionate. This correlation results in Natural constants being expressible through algebraic relationships involving the pure numbers π, φ (the Golden ratio), and α (the Fine Structure constant), not only simplifying Fundamental constants but also introducing a harmonious integration of geometric concepts. In contrast, SI currently relies on fixed values for seven constants derived from CODATA. It's crucial for Structural Units to seamlessly integrate with the existing International System of Units, proposing a theoretical framework, hitherto nonexistent, for the values of the various Fundamental Constants that have been experimentally obtained in our scientific endeavor. To ensure compatibility, the four Planck Units, (length, mass, time, and temperature), introduced by Max Planck in 1899, will be recalculated in SU and then converted back to SI using dimensional analysis. Additionally, to further validate this compatibility, we will examine the Schwarzschild radius from Relativity, the photon energy from Quantum Mechanics, and propose a new interpretation of the Uncertainty Principle under the SU framework. This potential harmonization of geometry and Natural constants in SU could offer a deeper understanding of the inherent order in the fabric of the Universe.

The gravitational constant is equivalent to natural units in its six unit dimensions. Evaluating the classical formulas in each unit dimension shows how inputs of mass and radius are transformed into the correct unit dimensions and magnitude of gravitational potential. Mass and radial distance are equivalent proportions of the Planck scale as the potentials they produce. Gravitational potentials of velocity, acceleration, energy, and force are proportional to a radial density limit of one Planck mass per Planck length of radial distance.

The natural units of measure lauded by Max Planck more than 100 years ago are rarely used today. But many physical constants, including Planck's constant, the gravitational constant, the speed of light, vacuum permittivity, and vacuum permeability, consist of natural units in their unit dimensions. The natural units are present in all formulas containing these constants. The defining characteristic of the natural units is an alignment of unit values at the Planck scale. This alignment gives a computational basis of proportionality from which the correlated properties and dynamics of elementary particles, including wavelength, period, mass, momentum, and energy, manifest in equal or inversely proportional ratios of the Planck scale. These correlations explain many of the defining equations of quantum mechanics, classical gravity, and electromagnetism.

n this article a first attempt at formalizing a new approach to the grand unified theory is introduced. This theory named NUVO is based primarily on considering two aspects of inertia. The first aspect is how a mass couples to space, introducing definitions to distinguish massive particles from massless particles. The second aspect is space’s availability to couple to massive particles. In essence these are the two contributions of inertia; mass and space. Postulates, clarifications, and a mathematical structure are introduced. Part 1 covers the physics of the very large (cos- mic), laying ground work for part two which applies the structure to the very small (quantum). The cosmic application of the theory will show a strong correlation to empirical data and correspondence to General Rela- tivity, including; time dilation, length contraction, and orbital advances. Departing from the canonical findings of General Relativity by predicting a quantization of physical units under the effect of acceleration and or gravity.

Planck’s constant and the gravitational constant are comprised of more fundamental quantities of length, mass, and time. Reformulating traditional equations in terms of these fundamental units offers a more granular view of the physical transformations encoded in the equations of physics. The composite structure of h and G conceals a simple model in which maximum unit potentials are reduced by dimensionless proportionality operators. Natural symmetries correlate the three unit dimensions, yielding predictable quantities of physical dynamics. Insights are organized into a New Foundations Model of physics that reformulates traditional constants and equations in elementary form. The New Foundations Model offers a common language for describing quantum mechanical, gravitational, and electromagnetic phenomena.

Integrating systems acquired from third parties and legacies has become of great necessity in companies. This is mainly due to the need to exchange information between entities, such as banks, suppliers, customers, allies, etc. Therefore, it is essential to guarantee the integrity of the data and keep the integration up to date with the changes that can occur. Furthermore, reducing the transaction risk and avoiding losing information is necessary. Implementing this complex task involving technological and business challenges requires appropriate architecture implementation. This article presents an architecture named Dynamic Canonical Data Model through agnostic messages. The contribution involves treating the low link in integrating software units, also called the integration of loosely coupled software units. In particular, it focuses on internal data and external data integration. The proposal reduces their integration, maintenance time, and cost, maximizing their scalability and promoting reuse. To illustrate their components, a case study undertaken at the Mexican Logistics Company Paquetexpress is presented. The company has evaluated different enterprise application integration systems over 26 years to achieve a standardized integration. The article describes an architecture designed and implemented for this delivery company in a real-world case. The implementation’s source code was registered in the National Registry of Copyrights of Mexico.

Synergistic control of emissions of air pollutants and CO2 is critical to the dual challenges of air quality improvement and climate change in China. Based on the emission inventories of thermal power units in Beijing, Tianjin, and Hebei, this study analyzes the CO2 and NOX emission characteristics of these units, identifies and quantifies the synergistic drivers affecting these emission trends. Inventory data show that between 2010 and 2020, NOX emissions were reduced by 86.1%, while CO2 emissions were reduced by only 29.8%. Although significant progress has been made in reducing NOX emissions through measures such as end-of-pipe treatment, controlling CO2 emissions remains a difficult task. The index decomposition analysis reveals that economic growth is the main driver of CO2 and NOx emission growth, energy intensity reduction is the main driver of CO2 emission reduction, and end-of-pipe treatment is the main driver of NOX emission reduction. Currently, coal occupies about 87% of the energy consumption of thermal power units in the Beijing-Tianjin-Hebei, and remains the main type of energy for synergistic emissions, and the potential for emission reduction in the energy structure remains huge. For NOX emissions, it is expected that 90% of the reduction potential can be achieved through energy restructuring and end-of-pipe treatment. In conclusion, the high-precision unit-by-unit emission study confirms the effectiveness of the control policy for thermal power units in the region and provides some scientific reference for future policy formulation.

Background: Recent years have seen chaos in the neonatology use of antibiotics with diverse opinions and recommendations in international guidelines and societies. This has created great uncertainty in which cases to use, for how long, and which tests apply to make these decisions. We conducted a retrospective cohort study about the use of antibiotics in the EpicLatino neonatal units and a Latin American network database, after noting these variations in the 2019 report. Methods: For the year 2019 using the EpicLatino database, we included cases (only first admission) ≤32 weeks gestational age at birth, excluding one unit that did not accept to participate. The number of cases and days receiving antibiotics were recorded as well as the progression for each unit. Inappropriate use of antibiotics was defined as greater than 3 days in patients with negative cultures (blood/CSF cultures) excluding: major malformations, urinary tract infections, necrotizing enterocolitis (NEC) and cases with suspected chorioamnionitis in the mother (the latter two only during the course of diagnosis of NEC or chorioamnionitis). This study was approved by the EpicLatino board of directors and by the participating units. Results: A total of 6,543 days of antibiotics were observed, 49.5% of cases had at least one positive blood/CSF culture. A total of595 days of antibiotics without justification were found in 72 courses in 61 cases; 14/72(19.4%) had no diagnosis of infection in the database, 7/72(9.7%) did not document any culture throughout their stay, and 37/72(51,4%) obtained only one blood/CSF culture during their entire stay. Most diagnosis were clinical sepsis and in 24/58(41%) curses, a diagnosis of pneumonia with a poor positive culture correlation was found. Furthermore, 74% of the units didn´t use pneumonia as a justification to use antibiotics. Other diagnosis found: Conjunctivitis, NEC 1A and rotavirus NEC. Conclusions: Although the method of reviewing the use of antibiotics in a database has a number of limitations, especially the cause that motivated the use of antibiotics and other tools used for diagnosis of infections, the notable differences between units is striking. Although it is difficult to make recommendations to all units, it is important to control infections in some units and in others to reduce the excessive use of antibiotics, especially with diagnosis of pneumonia in neonates and negative blood/CSF cultures.

The study aimed to assess the prevalence of the frailty syndrome in older patients hospitalized in the geriatric ward depending on the diagnostic criteria used, the feasibility of particular diagnostic scales in hospitalized patients, and their compatibility. Material and methods: Patients admitted to the Department of Geriatrics of Hospital of the Ministry of the Interior and Administration in Bialystok within eight months were included in the study. Four diagnostic scales were used to identify the frailty syndrome: Fried criteria, 7-point Clinical Frailty Scale (CFS), 40-item Frailty Index (FI), and FRAIL Scale. The compatibility of the scales was determined using Cohen's Kappa statistics. Results: 416 patients (mean age 81.2 ± 6.91 years, 77.4% women) were included in the study. Depending on the scale, the prevalence of frailty syndrome varied from 26.8% ( FRAIL Scale), 52.3% (Clinical Frailty Scale), and 58.1% (Fried criteria) up to 62.9% (Frailty Index). We observed the highest feasibility for CFS (100%), intermediate for Frailty Index (95.2%), FRAIL Scale (89.7%), and the lowest for Fried scale (79.8%). The highest level of agreement was found between the CFS and Fried scale, with 70.2% consistent ratings (Cohen Kappa 0.49). Conclusions: Patients in the geriatric ward are characterized by a high prevalence of frailty, although it differs depending on the criteria. The Frailty Index found the highest prevalence and the lowest in the case of the FRAIL scale. The feasibility of scales and their comparability differed; the most difficult to use in daily practice was the Fried scale, while the Clinical Frailty Scale was determined feasible in all patients. The highest agreement was observed between the Fried criteria and the Clinical Frailty Scale and the lowest between the FRAIL scale and the remaining ones.

Objectives To develop and validate a prediction model for 28-day in-hospital mortality among adult patients critically ill with COVID-19 in the UK. Design Observational cohort study. Setting 287 adult critical care units in England, Wales and Northern Ireland, of which 260 admitted at least one eligible patient. Participants 10,933 patients with confirmed COVID-19 of whom 10,401 were eligible (excluding 532 patients with a duration of critical care less than 24 hours and 1 patient with unknown 28-day outcome): 8,666 development (March-April 2020) and 1,735 temporal validation (May-August 2020). Main outcome measures 28-day in-hospital mortality from start of critical care. Results Two models were developed using 14 patient level predictors selected from 30 candidate predictors, with and without adjustment for calendar time. In the temporal validation data, the model discrimination was maintained (c index 0.78) but calibration was poor, particularly for the model not adjusted for calendar time (ratio of observed to predicted mortality 0.74 versus 0.88 for the model adjusted for calendar time). Conclusions We developed and validated a prediction model for 28-day in-hospital mortality for patients critically ill with COVID-19. Although absolute predictions were inaccurate due to changing outcomes, the models will support risk-adjustment in analyses and monitoring changes in risk-adjusted outcome over time.

This study examines the Soil Organic Carbon (SOC) within Greek croplands, offering a comprehensive understanding of its dynamics. SOC, a cornerstone in soil health, nutrient cycling, and global carbon dynamics, assumes critical significance in sustainable agriculture and climate change mitigation. Drawing on diverse soil properties, including pH, soil texture as well as different drainage and slope categories, the research explores the nuanced relationships shaping SOC dynamics in the diverse agroecological landscape of Greece. The investigation transcends local boundaries, emphasizing SOC's global role in climate change mitigation by sequestering carbon dioxide. Two maps were used as data sources: 1) SOC stock baseline map (2010) by JRC, 2) SOC stock map (2021) by the Institute of Soil and Water Resources, Hellenic Agricultural Organization – DIMITRA in collaboration with FAO. Greek croplands emerge as a mosaic of agroecological diversity, where anthropogenic activities wield transformative influences on SOC stock, demanding a delicate balance between agricultural productivity and soil health. The study unveils the influence of Soil Order, weaving a tapestry of SOC variability. Microscopic factors, from soil texture to cation exchange capacity, further shape SOC dynamics, emphasizing the role of clayey soils and coarse materials in carbon retention. Although soil organic carbon decreased from 2010 to 2021 the degree of carbon loss varied. This scientific endeavor synthesizes existing knowledge and unveils novel insights, offering a narrative woven from diverse soil properties. The findings contribute valuable insights for sustainable land management practices and climate change mitigation strategies, underscoring the importance of region-specific approaches in addressing global challenges.

In Burkina Faso, the infant flours produced are intended for weaning-age and malnourished children. This study was to evaluate the management of infant flour production in Ouagadougou. A survey was conducted among the production units to determine the raw materials used in the production of infant flours, the production processes, the methods of conservation of raw materials and infant flours, the types of infant flours produced as well as their packaging. The results showed that 45.45% of the production units surveyed were of the semi-industrial type against 54.54% from the artisanal and CREN types. Among the raw materials, the most used cereals were millet, sorghum and maize. As for legumes, peanuts and soybeans were the most used at respectively 35% and 31%. For the conservation of raw materials, 85.71% of infant flour producers had storage warehouses and 66% used storage pesticides. These flours produced were intended for children of wean age (37.14%) and children in nutritional recovery (62.86%). Flours were stored in an airy (94.29%), dry area/environment (88.57%) and in the presence of light (91.43%). All the results of this survey reflect that efforts are still expected to further improve the nutritional and sanitary quality of the infant flours produced.

Gait analysis has historically been implemented in laboratory settings with expensive instruments; however, recently, wearable sensors have allowed the integration into clinical applications and use in daily activities. Previous studies have shown poor validity of ankle joints using inertial measurement units (IMUs), especially for small movement ranges. The purpose of this study was to validate the ability of commercially available IMUs to accurately measure the ankle joint angles during running. Ten healthy subjects participated in the study. Validation was performed by comparing the ankle joint angles measured using the wearable device with those obtained using the gold standard motion capture system during running. Reliability was evaluated using the intraclass correlation coefficient and standard error of measurement, whereas validity was evaluated using Pearson coefficient correlation method. Day-to-day reliability was excellent in the two planes for ankle joints. Validity was good in both sagittal and frontal planes for ankle joints. The results suggested that the developed device might be used as an alternative tool to the 3D motion capture system.

The use of antibiotics in neonatal units worldwide varies significantly. We included data from 2015-2022 from the EpicLatino database, which comprises a network of 32 units in Latin America and the Caribbean with gestational age at birth (GA) of ≤ 32 weeks. A questionnaire was sent to the EpicLatino units, to correlate practice with outcomes. Negative binomial regression with standard errors and confidence intervals computed for incidence-rate ratios (IRRs) was used for comparative statistics on antibiotic days per 1000 patient-days between units. All units that responded had 1-6 differences with the reference unit (Unit 2) with the best results, but there was no clear association with the IRR. Each EpicLatino unit should review its statistics to explore possibilities for reducing antibiotic usage.

Although, central venous pressure (CVP) is among the most frequent estimated hemodynamic parameters in the critically ill setting, extremely little is known on how intensive care unit (ICU) nurses use this index in their decision-making process. The purpose of the study was to develop a new questionnaire for accessing how ICU nurses use CVP measurements to address patients’ he-modynamics investigating its validity and reliability. A cross-sectional study was conducted among 120 ICU nurses from four ICUs of Greece. Based on a comprehensive literature review and the evaluation of a five-experts panel a new questionnaire, named “CVP-Score”, was created having 8 items. The construct validity and the reliability of the questionnaire were examined. The half of the study participants’ (51.7%) was working at a specialized ICU, and they had a mean [±Standard Deviation (SD)] ICU experience of 13(±7.1) years. The estimated construct validity of the new-developed tool was acceptable, while the internal consistency reliability as measured by Cronbach alpha was excellent (0.901). CVP Score had acceptable test-retest reliability (r=0.996, p<0.001) and split-half reliability (0.855). CVP Score is a valid and reliable instrument for measuring how critical care nurses use CVP measurements in their decision-making process.

Aim: The aim of this study was to estimate the number of nurses who independently care for pa-tients with severe respiratory failure receiving mechanical ventilation (MV) or veno-venous ex-tracorporeal membrane oxygenation (VV-ECMO). Additionally, the study analyzed the actual role of nurses in the treatment of patients with MV and VV-ECMO. Methods: We conducted a cross-sectional study using postal surveys. The study included 725 Japanese intensive care units (ICUs). Descriptive statistics were conducted. Results: Among the 725 ICUs, we obtained 302 re-sponses (41.7%) and analyzed 282 responses. The median number of nurses per bed was 3.25. The median proportion of nurses who independently cared for patients with MV was 60% [IQR: 42.3-77.3]. The median proportion of nurses who independently cared for patients with VV-ECMO was 46.9 (35.7-63.3%) in the ICU experiencing VV-ECMO use. Concerning task-sharing, 33.8% of ICUs and nurses did not facilitate weaning from MV. Nurses always ti-trated sedatives in 44.5% of ICUs. Conclusion: Nurse staffing might be inadequate in all ICUs, es-pecially for severe respiratory failure. The proportion of competent nurses for caring for severe respiratory failure in ICUs should be considered when determining the work force of nurses.

In the coming years, the Anthropocene Working Group (AWG) will submit its proposal on the ‘Anthropocene’ as a new geological epoch to the International Commission on Stratigraphy (ICS) for approval. If approved, the proposal will be send to the International Union of Geological Sciences (IUGS) for ratification. If the proposal is approved and ratified, the ‘Anthropocene’ will be formalised and the Holocene Series/Epoch will be officially terminated. Currently, the ‘Anthropocene’ is a broadly used term and concept in a wide range of scientific and non-scientific situations and, for many, the official acceptance of this term is only a matter of time. However, the AWG proposal, in its present state, seems to not fully meet the ICS requirements for a new geological epoch. This paper asks what could happen if the current ‘Anthropocene’ proposal is not formalised by the ICS/IUGS. The possible stratigraphic alternatives are evaluated on the basis of the more recent literature and the personal opinions of distinguished AWG and ICS members. The eventual impact on environmental sciences and on non-scientific sectors, where the ‘Anthropocene’ seems already firmly rooted and de facto accepted as a new geological epoch, are also discussed.

Slope failures pose a substantial threat to mining activity due to their destructive potential and high probability of occurrence on steep slopes close to limit equilibrium conditions, often found both in open pits and in waste and tailing disposal facilities. The development of slope monitoring and modeling programs usually entails the exploitation of in situ and remote sensing data together with the application of numerical modeling, and it plays an important role in the definition of prevention and mitigation measures aimed at minimizing the impact of slope failures in mining areas. Here we present a new methodology combining satellite radar interferometry and 2D finite element modeling for slope stability analysis at a regional scale, applied within slope unit polygons. We studied a former mining area in southeast Spain, and the method proved useful in detecting and characterizing a considerably large number of unstable slopes. Out of 1,959 slope units used for the spatial analysis of the radar interferometry data, 43 were unstable, with varying values of safety factor and landslide size. Out of the 43 active slope units, 21 exhibited line of sight velocities greater than the maximum error obtained through the validation analysis (2.5 cm/year). Eventually, this work discusses the possibility of using the results of the proposed approach to devise a proxy for landslide hazard. The proposed methodology can help to provide non-expert final users with intelligible, clear and easily comparable information to analyze slope instabilities in different settings, not limited to mining areas.

Two-dimensional ultrasound (2D US) is commonly used in clinical settings for its cost-effectiveness and non-invasiveness, but it is limited by spatial orientation and operator dependency. Three-dimensional ultrasound (3D US) overcomes these limitations by adding a third dimension and enhancing integration with other imaging modalities. Advances in deep learning (DL) have further propelled the viability of freehand image-based 3D reconstruction, broadening clinical applications in intraoperative and point-of-care (POC) settings. This review evaluates state-of-the-art freehand 3D US reconstruction methods that eliminate the need for external tracking devices, focusing on experimental setups, data acquisition strategies, and reconstruction methodologies. PubMed, Scopus, and IEEE Xplore were searched for studies since 2014 following PRISMA guidelines, excluding those using additional imaging or tracking systems other than inertial measurement units (IMUs). Fourteen eligible studies were analyzed, showing a shift from traditional speckle decorrelation towards DL-based methods, particularly Convolutional Neural Networks (CNNs). Variability in datasets and evaluation methods hindered a comprehensive quantitative comparison, but notable accuracy improvements were observed with IMUs and integration of contextual and temporal information within CNNs. These advancements enhance freehand 3D US reconstruction feasibility, though variability limits definitive conclusions about the most effective methods. Future research should focus on improving precision in complex trajectories and adaptability across clinical scenarios.

Objectives: Imaging exams are requested in intensive care units as a diagnostic, evaluation, and clinical monitoring method. While Chest Computed Tomography is the gold standard, Chest X-ray is the exam usually performed in routine care. Lung ultrasound has been gaining ground as it is a reliable exam performed at the bedside without exposure to radiation and at a low cost. This study aimed to evaluate the accuracy of bedside lung ultrasounds performed by pediatric intensivists as a diagnostic method. Methods: A prospective, diagnostic test-type study comparing bedside lung ultrasound performed by a pediatric intensivist with the evaluation of chest X-ray and lung ultrasound performed by a radiologist. Result: 48 patients on mechanical ventilation, aged from 1 month to 14 years, were analyzed, corresponding to 95 chest X-ray exams and 95 lung ultrasound exams. The Kappa agreement coefficients between the pediatric intensivist and the radiologist, both analyzing the lung ultrasound, were: normal report (1.0), atelectasis (1.0), pneumothorax (1.0), consolidation (0.97), pleural effusion (0.95), and pulmonary edema (0.90). Sensitivity, specificity, and accuracy of lung ultrasound were, respectively, normal report (50%; 91.8%; 82.1%), consolidation (88.3%; 57.1%; 76.8%), atelectasis (11.1%; 90.7%; 83.2%), edema (0; 70.2%; 70.5%), pneumothorax (83.3%; 94.4%; 93.7%), and pleural effusion (71.4%; 73%; 72.6%). Conclusion: The pediatric intensivist was skilled in examining and diagnosing lung injuries. Lung ultrasound showed good sensitivity, specificity, and accuracy when the pediatric intensivist performed when diagnosing consolidation, pleural effusion, and pneumothorax. Furthermore, lung ultrasound demonstrated better accuracy in evaluating pulmonary edema when compared with chest X-ray.

The architectural configuration of the space plays a crucial role in the acoustics of Neonatal Intensive Care Units (NICUs). The design of the environment, the materials used in construction, and the organisation of noise sources within the room significantly influence the noise levels present in these critical areas. For this research, noise levels found in two hospitals, with different architectural configurations and sizes but similar construction materials, have been analyzed. Data were recorded at 1-second intervals over a period of more than 24 hours. The data collected in these hospitals confirm the magnitude of the noise problem in NICUs, highlighting the urgent need to address it effectively to ensure an appropriate and safe environment for the recovery of neonates. Good architectural planning can help mitigate noise, while poor configuration can exacerbate acoustic problems, negatively affecting both patients and healthcare staff. It is crucial to involve architects, acoustic engineers, and healthcare staff in the design and renovation of NICUs to create spaces that not only meet medical needs but also consider the auditory well-being of neonates.

The remote monitoring of clinical parameters plays a fundamental role in different situations, like pandemic health emergencies and post-surgery conditions. In these situations, the patients might be impeded in their movements and it could be difficult to have a specific health monitoring. In recent years, technological advancements in smartphones have opened up new possibilities in this landscape. The present work aims to propose a new method for respiratory kinematics monitoring via smartphone sensors. In particular, a specific application was developed to register Inertial Movement Unit (IMU) sensors data from the smartphone for respiratory kinematics measurement and to guide the user through a specific acquisition session. The session was defined to allow for the monitoring of the respiratory movement in five prescribed positions. The application and the sequence were successfully tested on a given population of 77 healthy volunteers. The resulting accelerometers and gyroscope signals were processed to evaluate the significance of differences according to participants sex, vector components and smartphone positioning and, finally, to estimate the respiratory rate. The emerged statistical differences revealed the significance of information in the different acquisition positions.

Trypanosoma cruzi, the protozoan causative of Chagas disease (ChD), exhibits striking genetic and phenotypic intraspecific diversity, along with ecoepidemiological complexity. Human-pathogen interactions lead to distinct clinical presentations of ChD. In 2009, an international consensus classified T. cruzi strains into six discrete typing units (DTUs), TcI to TcVI, later including TcBat, and proposed reproducible genotyping schemes for DTU identification. This article aims to review the impact of classifying T. cruzi strains into DTUs on our understanding of biological, ecoepidemio-logical, and pathogenic aspects of T. cruzi. We will explore the likely origin of DTUs and the intrinsic characteristics of each group of strains concerning genome organization, genomics, and suscepti-bility to drugs used in ChD treatment. We will also provide an overview of the association of DTUs with mammalian reservoirs, and summarize the geographic distribution, and the clinical implica-tions, of prevalent specific DTUs in ChD patients. Throughout this review, we will emphasize the crucial roles of both parasite and human genetics in defining ChD pathogenesis and chemotherapy outcome.

Infrared thermography has already been proven to be a significant method in non-destructive evaluation since it gives information with immediacy, rapidity and low cost. However, the thorniest issue for wider application of IRT is the quantification. In this work, we proposed a specific depth quantifying technique by employing the Gated Recurrent Units (GRU) in composite material samples via pulsed thermography (PT). Carbon Fiber Reinforced Polymer(CFRP) embedded with flat bottom holes were designed via Finite Element Method (FEM) modeling in order to precisely control the depth and geometrics of the defects. The GRU model automatically quantified the depth of defects presented in the CFRP material. The proposed method evaluated the accuracy and performance of synthetic CFRP data from FEM for defect depth predictions.

Florida geologic units and soils contain a wide range in concentrations of naturally-occurring arsenic. The average range of bulk rock concentrations is 1 to 13.1 mg/kg with concentrations in accessary minerals being over 1,000 mg/kg. Soils contain natural arsenic concentrations of between 0.18 and 2.06 mg/kg with organic-rich soils having the highest concentrations. Anthropogenic sources of arsenic have added about 610,000 metric tons of arsenic into the Florida environment since 1970, thereby increasing background concentrations in soils. The anthropogenic sources of arsenic in soils include: pesticides (used in Florida beginning in the 1890’s), fertilizers, chromated copper arsenate (CCA)-treated wood, soil amendments, cattle-dipping vats, chicken litter, sludges from water treatment plants, and others. The default Soil Cleanup Target Level (SCTL) in Florida for arsenic in residential soils is 2.1 mg/kg which is below some naturally-occurring background concentrations in soils and anthropogenic concentrations in agricultural soils. A review of risk considerations shows that adverse health impacts associated with exposure to arsenic is dependent on many factors and that the Florida cleanup levels are very conservative. Exposure to arsenic in soils at concentrations that exceed the Florida residential cleanup level in residential environments does not necessarily pose a meaningful public health risk.

This study was undertaken to investigate and analyze noise pollution in a large Chinese governmental hospital’s medical intensive care unit and compare to the WHO guidelines.This cross-sectional study was conducted in a MICU at a public governmental teaching hospital in Fujian province between July and August of 2017. A WENSN® WS1361 Integrated Sound Level Meter (China) was used for continuous every five seconds one week noise levels recording. After this measurement, the decibel meter was used for recording different location of isolation rooms and open bays, including occupied and unoccupied patient, and recording sound events occurs in the ICU to identify sources of noise. Peak and average noise levels were obtained from the meter, and data were downloaded from the WS1361 into a laptop computer. The measured mean equivalent sound pressure levels (L) and standard Aeq deviation over one week period were 66.64±7.57 dB(A), with acute spikes reaching 119.7 dB(A), the average sound level for a 24 hour period in a work day was 68.03±5.07 dB(A). These are higher than the current daytime environmental noise limit of 40-45 decibels in China and WHO. Mean work day noise was significantly louder than weekend time, there was a significant difference in work days and weekend (t=16.85;P=0.000).There was a statistical difference between the day time and night time shifts (t=34.67;P=0.000). The isolation rooms were significantly quieter than the open-bay rooms(t=46.15; p=0.00), sound levels in the occupied and unoccupied rooms also had significant difference(t=17.26; P=0.000).Two types of noise resources, including twenty kinds sources were identified and measured, mean noise levels ranged from of 61.33 to 79.21 dB(A). This study shows noise levels in intensive care units were exceeded the recommended. The study of the influence of noise on patient and staff is needed, and noise reduction strategies must be conduct in ICU.

In March 2013, a novel avian influenza A H7N9 virus was emerged in China, which cause rapidly progressive pneumonia and with a high fatality rate. Serologic studies to evaluate neutralizing antibodies of infected patients and birds are invaluable tools for immunogenicity research of H7N9 and epidemiological investigation. Conventional neutralization assays are laborious and time-consuming which also hampered by biosafety requirement. In this study, We construct and produce pseudovirus bearing the full-length hemagglutinin (HA) of H7N9 virus in the Env-defective, luciferase-expressing HIV-1 backbone. The production of lentiviral pseudovirus was analysed by HA gene specific real-time reverse-transcription PCR, transmission electron microscopy (TEM), and Western Blot assay to prove the nucleic acid replication, the morphology of virus, and the expression of HA protein in pseudovirus. After that pseudovirus based inhibition assay was established to detect neutralizing antibodies of a panel of serum samples. Our results demonstrated that H7N9 pseudovirus which had single-cycle infection was generated. By comparing the neutralization antibody titers, pseudovirus based neutralization test could be recognized as an alternative of conventional microneutralization (MN). Hence, we conclude that it is possible to use pseudovirus inhibition assay to screen sera samples, as well as evaluate vaccine-induced neutralizing antibodies against H7N9 virus.

Segregating one space from another is a rudimentary act of architecture and the basic principle of this act is creating differentiation between outside and inside. Thresholds, in their expanded or summed form, also produce spaces. They establish the staging for threshold areas in conjunction with space-defining elements. Threshold spaces are typically complicated spatial formations that serve as transition points. They pose a challenge to the interacting human senses in terms of perception. In this research threshold areas have been studied under a specific typology of architecture i.e the traditional housing in historic cities of India. The traditional dwelling settlements have evolved and grown over multiple layers of history, influenced by the culture, society, economy, climate and topography. The purpose of this research is to examine the characteristics of these transition spaces of the traditional dwelling units in relation to the symbolic reference and social meanings assigned to them that influence the architectural and urban spaces attached to them. It seeks to describe transition space in terms of its nature, character, morphology, and social significance. Transparency and material articulation, as well as hierarchy and enclosure, will be investigated. The importance and quality of the nature of "transition" will be examined from the inside to the outside. The research reveals that the space has great functional and socio-cultural importance. It allows multiple activities, provides protection from sun and rain, defines boundaries, connects people within the neighborhood, enhances security and gives an identity to the owner. The contributions made by this research have the potential to improve design considerations for transition areas between the dwelling units and the street.

The calculation of the global shear capacity of steel-concrete composite downstand cellular beams with precast hollow-core units is important as it affects the span to depth ratios and the amount of material used, hence affects the embodied CO2 calculation when designers are deciding on the floor grids. This paper presents a reliable tool that can be used by designers to alter and optimise grip options during the preliminary design stages, without the need to run onerous calculations. The global shear capacity prediction formula is developed using five machine learning models. First, a finite element model database is developed. The influence of the opening diameter, web opening spacing, tee-section height, concrete topping thickness, the interaction degree, and the number of shear studs above the web opening are investigated. Reliability analysis is conducted to assess the design method and propose new partial safety factors. The Catboost Regressor algorithm presented better accuracy compared to the other algorithms. An equation to predict the shear capacity of composite cellular beams with hollow-core units is proposed by Gene Expression Programming. In general, the partial safety factor for resistance, according to the reliability analysis, varied between 1.25 and 1.26.

The purpose of this study was to investigate the relationship between clinical outcomes and lateral thrust before and after unicompartmental knee arthroplasty (UKA) using inertial measurement sensor units. Eleven knees were evaluated with gait analysis. The varus angular velocity was used to evaluate lateral thrust. The femoro-tibial angle (FTA) and hip-knee-ankle angle (HKA) were used to evaluate lower limb alignment, and Oxford Knee Score (OKS) and Japanese Orthopaedic Association Score (JOA) were used to evaluate clinical outcomes. The mean pre-UKA peak varus velocity was 37.1 ± 9.8°/sec, and that of post-UKA was 28.8 ± 9.1°/sec (p=0.00003). Assuming the definition of lateral thrust is when varus angular velocity is more than 28.1°/sec, 81.8% of patients had lateral thrust preoperatively, but this decreased to 55.6% postoperatively. Both OKS and JOA improved after surgery. In addition, HKA was -7.9° preoperatively and -5.8° postoperatively (p=0.024), and FTA was 181.4° preoperatively and 178.4° postoperatively (p=0.012). There was a positive correlation between postoperative JOA and FTA, indicating that changes in postoperative alignment affected clinical outcomes. This study quantitatively evaluated the disappearance of lateral thrust by UKA, and it found that the stability can be achieved by UKA for unstable knees with lateral thrust.

In horses, quantitative assessment of gait parameters, as the use of inertial measurement units system (IMUs), might help in the decision-making process. However, it requires financial investment, is time-consuming, and lacks accuracy if displaced. An innovative Artificial Intelligence marker-less Motion Tracking System (AI-MTS) may overcome these limitations in the field. Our aim was to compare the level of agreement and accuracy between both systems and visual clinical assessment. Twenty horses underwent locomotion analysis by visual assessment, IMUs and AI- MTS systems, in the following conditions: straight hard (SH), straight soft (SS), left and right circle hard (LCH, RCH) and soft (LCS, RCS). A greater number of horses were considered sound by clinical examination, compared to those identified as symmetric by the two gait analysis systems. More limbs were considered asymmetric by the AI-MTS compared to IMUs, suggesting its greater sensitivity. The greatest agreement between the two systems was found for the difference between two minima in vertical head position in SH, while the lowest for the difference between two minima in vertical pelvis position in SS, reflecting the difficulties in assessing asymmetry of hindlimbs. Some degree of asymmetry may be clinically relevant, suggesting its regular use in training horses.

Imaginary dimensions in physics require an imaginary set of base Planck units and some negative parameter $c_n$ corresponding to the speed of light in vacuum $c$. The second, negative fine-structure constant $\alpha_2^{-1} \approx -140.178$ present in Fresnel coefficients for the normal incidence of electromagnetic radiation on monolayer graphene leads to the imaginary Planck units. Furthermore, it sets $c_n \approx -3.06 \times 10^8~\text{[m/s]}$. It follows that electric charges are the same in real and imaginary dimensions. Neutron stars and white dwarfs, objects emitting perfect black-body radiation, need energy exceeding their mass-energy equivalence ratios. Complex energies are defined in terms of real and imaginary Planck units. Their imaginary parts, inaccessible for direct observation, store the excess of these energies. It follows that black holes are fundamentally uncharged, charged micro neutron stars and white dwarfs with masses lower than $5.7275 \times 10^{-10}~[\text{kg}]$ are unphysical, and the radii of white dwarfs' cores are limited to $R_{\text{WD}} < 6.7933~G M_{\text{WD}}/c^2$. It is conjectured that the maximum atomic number $Z=238$. A black-body object is in the equilibrium of complex energies of masses, charges, and wavelengths if its radius $R_\text{eq} \approx 2.7665~G M_{\text{BBO}}/c^2$, which corrects the value of the photon sphere radius $R_{\text{ps}}=3G M/c^2$, taking into account the value(s) of the fine-structure constant(s), which is otherwise neglected in general relativity.

Background: Identifying a specific threshold level of SARS-CoV-2 antibodies that confers protection in immunocompromised patients has been very challenging. The aim was to assess the threshold of 264 binding antibody units (BAU)/ml using four different SARS-CoV-2 antibody assays (Abbott, Beckman, Roche, and Siemens) and to establish a new optimal threshold of protection for each of the four antibody assays. Methods: This study was performed on data retrieved from 69 individuals, who received at least one dose of the Pfizer/BioNTech BNT162b2 or Moderna COVID-19 vaccine (Spikevax) at the Alphabio Laboratory in Marseille, France (European Hospital, Alphabio – Biogroup). The results were compared to the percent inhibition calculated using a functional surrogate of a standardized virus neutralization test (Genscript). Results: Samples from 69 patients were analyzed. For a reference cutoff of 264 BAU/ml, assays showed moderate to good overall concordance with Genscript: 87% concordance for Abbott, 78% for Beckman, 75% for Roche, and 88% for Siemens. Overall concordance increased consistently after applying new thresholds, i.e., 148 BAU/ml (Abbott), 48 (Beckman), 559 (Roche), and 270 (Siemens). Conclusion: We suggest specific adjusted thresholds (BAU/ml) for the four commercial antibody assays that are used to assess pre-exposure prophylaxis in immunocompromised patients.

According to observations leptons are always produced in pairs. Both particles can be electrically charged, or just one, in which case the charged particle is accompanied by a particle specific neutrino. The period doubling process in nonlinear dynamical systems creates stable pair structures from the Planck units. The electron-positron pair is one of the stable structures, and the rest mass, electric charge and magnetic moment can be accurately calculated by the period doubling process. That the pair structure is stable means, that e.g., an electron and a positron are always born together. In the muon decay one of the pair is charged, while the other remains chargeless because there is only one charge available. It is suggested in this article that neutrino is the chargeless part of the lepton pair.

(1) Background: To estimate resistance, reactance and phase angle values among moderate preterm infants and their variation according to neonatal and maternal characteristics and nutritional intake. (2) Methods: This was a cohort that evaluated 43 moderate preterm infants using bioelectrical impedance analysis. The study variables included resistance, reactance and PA measurements, in addition to classification of nutritional intake. (3) Results: The mean resistance was 602.0+118.2 Ω, reactance was 57.2 Ω (IIQ = 42.6-65.2) and phase angle was 522° (IIQ = 4.1-6.6). Lower resistance values were found in the presence of risky pregnancy (532.2+111.9 Ω vs 650.9+97.9 Ω, p&lt;0.001) and lower reactance values, in the presence of harmful maternal lifestyle habits at both the first (p=0.01) and second assessments (p=0.01). Eight preterm infants were considered to have insufficient nutritional intake (23.5%); 17, sufficient (50.0%) and 9, partially sufficient (26.5%). There was less reactance among preterm infants with insufficient nutritional intake (p &lt; 0.001). (4) Conclusions: The bioelectrical impedance analysis measurements were within the range of values reported in other studies. There was an association between full diet and adequate nutritional intake with higher resistance values, and a lower reactance value was associated with the presence of risky pregnancy and harmful maternal lifestyle.

This paper addresses the issue of the automatic identification of river reaches and their planform type, given the (observed) set of geomorphic elements and units. It introduces further advances with respect to the original proposal by Nardini and Brierley. And it explores explicitly the ability of the algorithm and associated tools to work properly on significantly different rivers while adopting a given same parametrization. This was indeed an envisaged ability speculated as a challenging conclusion of the previous work. The Duqueco, Laja and Biobío rivers (Chile) are analyzed for this purpose. The conclusion is definitely positive, what opens future promising application horizons.

The use of inertial measurement units (IMUs) to compute gait outputs such as the 3D lower limb kinematics is of huge potential, but no consensus on the procedures and algorithms exists. This study aimed at evaluating the validity of a 7-IMUs system against the optoelectronic system. Ten asymptomatic subjects were included. They wore IMUs on their feet, shanks, thighs and pelvis. The IMUs were embedded in clusters with reflective markers. Reference kinematics was computed from anatomical markers. Gait kinematics was obtained from accelerometer and gyroscope data after sensor orientation estimation and sensor-to-segment (S2S) calibration steps. The S2S calibration steps were also applied to the cluster data. IMU-based and cluster-based kinematics were compared to the reference through root mean square errors (RMSEs), centered RMSEs (after mean removal), correlation coefficients (CCs) and differences of amplitude. The mean RMSE and centered RMSE were respectively 7.5° and 4.0° for IMU-kinematics, and 7.9° and 3.8° for cluster-kinematics. Very good CCs were found in the sagittal plane for both IMUs and cluster-based kinematics at the hip, knee and ankle levels (CCs&gt;0.85). The overall mean amplitude difference was about 7°. These results reflected good accordance of our system with the reference, especially in the sagittal plane, but the presence of offsets requires caution for clinical use.

This study aims to explore the possibility of estimating a multitude of kinematic and dynamic quantities using subject-specific musculoskeletal models in real-time. The framework was designed to operate with marker-based and inertial measurement units enabling extensions far beyond dedicated motion capture laboratories. We present the technical details for calculating the kinematics, generalized forces, muscle forces, joint reaction loads, and predicting ground reaction wrenches during walking. Emphasis was given to reduce computational latency while maintaining accuracy as compared to the offline counterpart. Notably, we highlight the influence of adequate filtering and differentiation under noisy conditions and its importance for consequent dynamic calculations. Real-time estimates of the joint moments, muscle forces, and reaction loads closely resemble OpenSim's offline analyses. Model-based estimation of ground reaction wrenches demonstrates that even a small error can negatively affect other estimated quantities. An application of the developed system is demonstrated in the context of rehabilitation and gait retraining. We expect that such a system will find numerous applications in laboratory settings and outdoor conditions with the advent of predicting or sensing environment interactions. Therefore, we hope that this open-source framework will be a significant milestone for solving this grand challenge.

This study proposes a novel flexible bus dispatching system where a fleet of fully automated modular bus units, together with conventional buses, serves the passenger demand. These modular bus units can either operate individually or combined (forming larger modular buses with a higher passenger capacity). This provides enormous flexibility to manage the service frequencies and vehicle allocation, reducing thereby the operating cost and improving passenger mobility. We develop an optimization model used to determine the optimal composition of bus units and the optimal service frequency at which the buses (both conventional and modular) are dispatched across each bus line. We explicitly account for the dynamics of traffic congestion and complex interactions between the modes at the network level based on the recently proposed three-dimensional macroscopic fundamental diagram (3D-MFD). To the best of our knowledge, this is the first application of the 3D-MFD and modular bus units for the frequency setting problem in the domain of bus operations. Numerical results show the improvements in the total system cost made by adapting the number of combined modular bus units and their dispatched frequencies to the evolution of both, the car and the passenger demand. A comparison with the commonly used approach that considers only the bus system (neglecting the complex multimodal interactions and congestion propagation) reveals the value of the proposed modeling framework.

In an attempt to improve the quality of the agricultural drain in Egypt for its reuse again in the irrigation, low cost solution such as sand filter along with/ without other filtration media have been used in this research, As a result of that, pilot plant of sand filter mixed with other filtration media was tested for its ability to improve the sand performance in removing the suspended solids and organic matters from agricultural drain water of the Belbeis drain (in Sharkia governorate in Egypt). Only sand compared with sand with sponge and sand with Liyan Nanfang activated carbon (L.N.A.C) have been tested to find the optimum mixing sand/ medium ratio &optimum infiltration rate. The work has been done on four runs. It was found that sand mixed with sponge gave the best removal efficiency compared to that of the sand only and the sand mixed with L.N.A.C. The results presented that the concentration of CODt, CODsol and TSS was reduced from 125, 47 and 162 mg/l to 44, 34 and 28 mg/l respectively at optimum infiltration rate of 2 m³/m²/d for sand mixed with sponge.

The livestock sector can be a major contributor to the mitigation of greenhouse (GHG) emissions. Within the sector, beef production produces the largest proportion of the livestock sector’s direct emissions. The objective of this study was to assess the on-farm GHG emissions in semi-arid rangelands in Argentina and to identify the relationships between emissions and current farm management practices. A survey recorded detailed information on farm management and characteristics. Assessments of GHG emissions were based on the IPCC Tier 2 protocols [1]. The relationships between farm management and GHG emissions were identified using General Linear Models. Cluster analysis was used to identify groups of farms that differed from others in emissions and farm characteristics. Emissions per product sold were low on farms that had improved livestock care management, rotational grazing, received technical advice, and had high animal and land productivities. Emissions per hectare of farmland were low on farms that had low stocking rates, low number of grazing paddocks, little or no land dedicated to improved pastures and forage crops, and low land productivity. Our results suggest that the implementation of realistic, relatively easy-to-adopt farming management practices has considerable potential for mitigating GHG emissions in semi-arid rangelands of central Argentina.

The area of Central and Eastern Europe, and thus Poland, is not exposed to effects of seismic actions. Any possible tremors can be caused by coal or copper mining. Wind, rheological effects, the impact of other objects or a non-uniform substrate are the predominant types of loading included in calculations for stiffening walls. The majority of buildings in Poland, as in most other European countries, are low, medium-high brick buildings. Some traditional materials, like solid brick (>10% of construction materials market) are still used. But autoclaved aerated concrete (AAC) and cement-sand calcium-silicate (Ca-Si) elements with thin joints are prevailing (>70% of the market) on the Polish market. Adding reinforcement only to bed joints in a wall is a satisfactory solution (in addition to confining) for seismic actions occurring in Poland that improves ULS and SLS. This paper presents results from our own tests on testing horizontal shear walls without reinforcement and with different types of reinforcement. This discussion includes 51 walls made of solid brick (CB) reinforced with steel bars and steel trusses, results from tests on 15 walls made of calcium-silicate (Ca-Si) and AAC masonry units reinforced with steel trusses and plastic meshes. Taking into account our own tests and those conducted by other authors, empirical relationships were determined on the basis of more than 90 walls. They are applicable to design and construction phase to determine the likely effect of reinforcement on cracking stress that damage shear deformation and wall stiffness.

The national-scale evaluation and modelling of the impact of agricultural management and cli-mate change on soils, crop growth, and the environment require soil information at a spatial res-olution addressing individual agricultural fields. This manuscript presents a data science ap-proach which agglomerates the soil parameter space into a limited number of functional soil pro-cess units (SPUs) which may be used to run agricultural process models. In fact, two unsupervised classification methods were developed to generate a multivariate 3D data product consisting of SPUs, each being defined by a multivariate parameter distribution along the depth profile from 0 to 100 cm. The two methods account for differences in variable types and distributions and in-volve genetic algorithm optimization to identify those SPUs with the lowest internal variability and maximum inter-unit difference with regards to both, their soil characteristics and landscape setting. The high potential of the methods was demonstrated by applying them to the agricultural German soil landscape. The resulting data product consists of twenty SPUs. It has a 100 m raster resolution in the 2D mapping space, and its resolution along the depth profile is 1 cm. It includes the soil properties texture, stone content, bulk density, hydromorphic properties, total organic carbon content, and pH.

Measured values of the electron mass and Compton wavelength produce a value of Planck's constant with a relative standard uncertainty of 3 x 10^-10. This is only slightly larger than the 1.3 x 10^-10 relative standard uncertainty in measurements performed using the Kibble balance. Compton scattering represents an alternative pathway to improving the value of Planck's constant in the future. Natural units of length, mass, and time offer new pathways to improving the values of physical constants. While extensive values of the Planck units lie beyond the reach of present-day instrumentation, certain product and quotient pairs of Planck units such as the speed of light can be measured with relatively high precision. Better measurements of certain unit pairs will improve the value of the gravitational constant.

Following the transfer of hospital services to provincial government oversight, it is essential to understand how such changes impact service quality and efficiency. This study aims to identify the factors affecting hospital service quality post-transfer and evaluate the role of professional nurses in maintaining service standards under new governance.We conducted the study at sub-district health-promoting hospitals using a mixed-methods design based on the Global Fund-HSS framework (2012), which categorizes factors into accessibility, processes, productivity, and outcomes. We collected data from 340 nurses and 400 patients using structured questionnaires. We divided the questionnaires into seven sections, which captured a range of metrics such as the personal data of nurses, hospital service activities, and leadership qualities. We employed a Likert scale to gauge perceptions and expectations of service quality. We used paired t-tests to compare performance metrics before and after the administrative transfer, one-way ANOVA to assess variability among different service units, and binary logistic regression to identify key determinants of service quality in our statistical analysis. The analysis revealed a significant correlation between the attitudes and competencies of healthcare teams and the levels of service quality. Notably, service units transferred less than 50% exhibited minimal changes, indicating that the degree of transfer significantly impacts service outcomes. Despite these variations, the fundamental mission of promoting health remained consistent. The study emphasizes the critical role of nurses and recommends further research to identify additional factors that could improve service quality in transferred healthcare facilities. This could contribute to improved healthcare delivery across restructured health systems.

Following the transfer of hospital services to provincial government oversight, it is essential to understand how such changes impact service quality and efficiency. This study, conducted from 1 March 2023 to 31 March 2024 at sub-district health-promoting hospitals in Thailand, aims to identify the factors affecting hospital service quality post-transfer and evaluate the role of profes-sional nurses in maintaining service standards under new governance. Utilizing a mixed-methods design based on the Global Fund-HSS framework (2012), which categorizes factors into accessibility, processes, productivity, and outcomes, we collected data from 340 nurses and 400 patients through structured questionnaires. These questionnaires were divided into seven sec-tions, capturing metrics such as the personal data of nurses, hospital service activities, and lead-ership qualities. We employed a Likert scale to gauge perceptions and expectations of service quality and conducted paired t-tests to compare performance metrics before and after the admin-istrative transfer. One-way ANOVA was used to assess variability among different service units, and binary logistic regression helped identify key determinants of service quality. The analysis revealed a significant correlation between the attitudes and competencies of healthcare teams and the levels of service quality. Notably, service units transferred less than 50% exhibited mini-mal changes, indicating that the degree of transfer significantly impacts service outcomes. Despite these variations, the fundamental mission of promoting health remained consistent. The study emphasizes the critical role of nurses and recommends further research to identify additional factors that could improve service quality in transferred healthcare facilities, potentially contributing to enhanced healthcare delivery across restructured health systems.

.Bacground: Sepsis remains a major health challenge worldwide, characterized by a dysre-gulated host response to infection, leading to high mortality and morbidity in intensive care units (ICUs). The Fibrosis 4 (FIB-4) index, originally developed to assess liver fibrosis in hepatitis C patients, has recently been explored for its potential prognostic value in sepsis patients. Method: This study retrospectively analyzed 309 sepsis patients admitted to the Internal Me-dicine and Anaesthesia ICUs between December 12, 2021, and December 15, 2023, to inves-tigate the relationship between FIB-4 levels, Acute Physiology and Chronic Health Evaluation (APACHE), and Sequential Organ Failure Assessment (SOFA) and clinical outcomes. Results: The study found that higher FIB-4 measurements were statistically significantly asso-ciated with increased 28-day mortality, with a cut-off value of 4.9 providing a sensitivity of 54.92% and specificity of 74.25%. Logistic regression analysis indicated that elevated Conclusion:FIB-4 levels were a significant predictor of early mortality, suggesting that the FIB-4 index could serve as a valuable prognostic tool in assessing the severity and prognosis of sepsis patients.

Although microgrids facilitate the increased penetration of distributed generations (DGs) and improve the security of power supplies, they have some issues that need to be better understood and addressed before realising the full potential of microgrids. This paper presents a comprehensive list of challenges and opportunities supported by a literature review on the evolution of converter-based microgrids. The discussion in this paper presented with a view to establishing microgrids as distinct from the existing distribution systems. This is accomplished by, firstly, describing the challenges and benefits of using DG units in a distribution network and then those of microgrid ones. Also, the definitions, classifications and characteristics of microgrids are summarised to provide a sound basis for novice researchers to undertake ongoing research on microgrids.

Background: Gut-Brain-Axis provides bidirectional communicational route; imbalance of which can have pathophysiological consequences. It is a frontier in autism research, affects 85% of autistic children (NIH report). Their microbiome has few overall microbes and smaller number of health promising microbes than their neurotypical peers. We hypothesize autism gut might play a role in manifestation of autism behaviours and on treatment, can revert back to normal behaviour considerably. The aim is to better understand to what degree gut microbiota of autism subjects differs from controls and identify bacterial species present exclusively in autism. Materials and Methods: 16s-rRNA-sequence of autism-subjects were retrieved from the American Gut Project Archive. Taxonomic assignment was inferred by similarity based methods using Quantitative Insights Into Microbial Ecology (QIIME). Species abundance was characterized and co-occurrence network was built to infer species interaction using measures of diversity. Statistical parameters were considered to validate the findings. Result: A total of 206 (1.8%) of American Gut Project datasets onstituted of autistic samples. Various bacteria such as Akkermansia sp., and Prevotella sp., were harboured in higher abundance in autistic children with statistical significance than in controls. Conclusion: These findings indicate connecting-link between gut-microbiome-brain-axis and autistic behaviour which can result in improved management

Plants significantly shape root-associated microbiota, making rhizosphere microbes useful environmental indicator organisms for safety assessment. Here, we report the pyrosequencing of the bacterial 16S ribosomal RNA in rhizosphere soil samples collected from transgenic cry1Ab/cry1Ac Bt rice Huahui No. 1 (GM crop) and its parental counterpart, Minghui63. We identified a total of 2,579 quantifiable bacterial operational taxonomic units (OTUs). Many treatment-enriched microbial OTUs were identified, including 14 NonGM-enriched OTUs and 10 GM-enriched OTUs. The rhizosphere microbiota communities were influenced more strongly by growth in the field than by rice varieties. Furthermore, Huahui No. 1 transgenic Bt rice had a greater impact on the rhizosphere bacterial communities than Minghui63. Early developmental stages of the transgenic Bt rice had a significant impact on many Bacillaceae communities. While soil chemical properties were not significantly altered by the presence of transgenic Bt rice, we found peak expression level of Bt proteins during the seedling stage, which may be an intriguing factor for bacterial diversity variations. Based on these findings, we conclude that transgenic Bt rice has a significant impact on root-associated bacteria. This information may be leveraged in future environmental safety assessments of transgenic Bt rice varieties.

Running is a basic form of human locomotion and one of the most popular sports worldwide. While the leg biomechanics of running have been studied extensively, few studies have focused on the upper-body movement. However, an effective arm swing and longitudinal rotation of the shoulders play an important role in running efficiency as they must compensate for the longitudinal torques generated by the legs. The aim of this study is to assess the upper-body rotation using wearable inertial sensors and to elucidate its relation to energy expenditure. Eighty-six junior elite middle and long-distance runners (37 female, 49 male) performed an incremental treadmill test with sensors attached on both shoulders, tibiae and the sacrum. Mean and total horizontal shoulder and pelvis rotation per stride were derived while energy costs were determined using respiratory gas analysis and blood sampling. Results show that shoulder and pelvis rotation increase with running speed. While shoulder rotation is more pronounced in female than in male runners, there is no sex difference for pelvis rotation. Energy cost of running and upper trunk rotation prove to be slightly negatively correlated. In conclusion, upper body rotation appears to be an individual characteristic influenced by a sex-specific body mass distribution.

This study aimed to investigate the prevalence, location, and characteristics of new-onset chronic pain by using a new definition in long-term survivors after discharge from a tertiary emergency center. We conducted a single-center ambidirectional cohort study from January to May 2022. A survey of patients was conducted by postal mail 2-2.5 years since their discharge from a tertiary emergency center. We used the Brief Pain Inventory to investigate chronic pain parameters, and the painDETECT questionnaire to investigate neuropathic pain. Patient information during hospitalization was collected retrospectively from medical records. The survey was sent to 78 patients, 63 (81%) of whom responded and were included in the analysis. Nine of the 63 patients (14%) had new-onset chronic pain. Of these, six (67%) had chronic pain of moderate or severe intensity which interfered with daily life. The most frequent location of chronic pain was the ankle/foot (n=4, 44%). Neuropathic pain was present in four (44%) patients with new-onset chronic pain. New-onset chronic pain may occur for up to 2-2.5 years after discharge from a tertiary emergency center, and this may interfere with daily life. Therefore, a follow-up system for chronic pain is warranted.

It is shown that structuring at the microlevel is the intrinsic property of water and aqueous solutions. At room conditions water (including "ultrapure" one) and aqueous solutions are dispersed systems in which microcrystals of NaCl, surrounded by a layer of hydrated water (average diameter - 10-15 microns), are "elementary microparticles", which form the basis of the dispersed phase. Possible ways of formation of these microparticles and their evolution in the process of evaporation of unstructured part of water - dispersion medium - are considered. It is shown, in particular, that they are present in the air as aerosol contaminants. When the ionic strength of the solution increases, the water-salt particles coagulate, forming a new phase - coacervates, remaining on the substrate after evaporation of the liquid part of the water. The aggregates of coacervate structures, formed in a liquid medium, are disordered during heating, which can cause a change in a number of physicochemical properties of water at the temperatures of 50°-60°C range that have not been correctly explained in the framework of atomic-molecular concepts.

Despite soccer popularity, comparatively little scientific information is available concerning the assessment of youth players’ physiological characteristics. The use of medical software integrating wearable sensors to provide accurate and objective data is necessary. In the present study, the objective assessment of physical performance of 128 adolescent soccer players at two timepoints (pre-season and end-season) has been performed. Participants completed a comprehensive test battery including stability, countermovement jumps (CMJ), plyometric jumps (PJ), agility, and quick feet tests. A single Inertial Measurement Unit (IMU) sensor provided quantitative data on various performance metrics. Principal Component Analysis (PCA) reduced the dataset to four principal components (PCs) explaining over 80% of the variance: power (PC1), balance (PC2), speed/agility (PC3), and stiffness (PC4). Paired samples t-test between the two timepoints showed no significant differences in the PCs between the two timepoints, indicating that the training program did not significantly alter the assessed physical attributes. However, subtle individual changes may still inform personalized training adjustments. The study highlights the importance of continuous monitoring and individualized training strategies to optimize athlete performance and reduce injury risk.

Keeping the bus voltage within acceptable limits depends on dispatching reactive power. Power quality improves as a result of creating an effective power flow system, which also helps to reduce power loss. Therefore, Optimal Reactive Power Dispatch (ORPD) studies aim at designing appropriate system configurations to enable a reliable operation of power systems. Establishment of such a configuration is handled through control variables in power systems. On the other hand, installing Distributed Generation Unit (DGU) into a power system can have an important effect on power quality and power loss minimization. In this paper, Grey Wolf Optimization (GWO method is applied to ORPD problem for the first time, to find optimal placement of newly installed DGUs at the power system. Active power loss and voltage minimization have been minimized by optimizing the control variables while keeping them within their upper and lower bounds, and by finding the optimal placement of a newly installed DGU in power system. On the basis of IEEE 30 bus and IEEE 118 bus systems, performance of the suggested approach is investigated. A comparison is also performed among the proposed method and some other methods. Test results demonstrate that the resulting configuration contributes to growing the rate of renewable integration to a power system. The results also indicate that the suggested optimization approach applied to ORPD problem has improved power system performance in terms of both on power loss and voltage deviation. The promising results highlight the potential of the GWO algorithm to facilitate the integration of renewable power sources, and its role in promoting sustainable energy solutions.

When it comes to air pollution complaints, odours are often the most significant contributor. Sources of odour emissions range from natural to anthropogenic. Mitigation of odour can be challenging, multifaceted, site-specific, and is often confounded by its complexity—defined by existing (or non-existing) environmental laws, public ordinances, and socio-economic considerations. The objective of this paper is to review and summarize odour legislation in selected European countries (France, Germany, Austria, Hungary, United Kingdom, Spain, The Netherlands, Italy, Belgium), North America (USA and Canada), South America (Chile and Colombia), as well as Oceania (Australia and New Zealand) and Asia (Japan, China). Many countries have incorporated odour controls into their legislation. However, odour-related assessment criteria tend to be highly variable between countries, individual states, provinces and even counties and towns. Legislation ranges from (1) no specific mention in environmental legislation that regulates pollutants which are known to have an odour impact to (2) extensive details about odour source testing, odour dispersion modeling, ambient odour monitoring, (3) setback distances, (4) process operations, and (5) odour control technologies and procedures. Agricultural operations are one specific source of odour emissions in rural and suburban areas and a model example of such complexities. Management of agricultural odour emissions is important because of the dense consolidation of animal feeding operations and the advance of housing development into rural areas. Overall, there is a need for continued survey, review, development, and adjustment of odour legislation that considers sustainable development, environmental stewardship, and socio-economic realities, all of which are amenable to a just, site-specific, and sector-specific application.

Molecular dynamics simulation is currently the theoretical technique eligible to simulate a wide range of systems from soft condensed matter to biological systems. However, of the excellent results that the technique has arrogated, this approach remains computationally expensive, but with the emergence of the new supercomputing technologies bases on graphics processing units graphical processing units-based systems GPUs, the perspective has changed. The GPUs allow performing large and complex simulations at a significantly reduced time. In this work, we present recent innovations in the acceleration of molecular dynamics in GPUs to simulate non-Hamiltonian systems. In particular, we show the performance of measure-preserving geometric integrator in the canonical ensemble, that is, at constant temperature. We provide a validation and performance evaluation of the code by calculating the thermodynamic properties of a Lennard-Jones fluid. Our results are in excellent agreement with reported data reported from literature, which were calculated with CPUs. The scope and limitations for performing simulations of high-throughput MD under rigorous statistical thermodynamics in the canonical ensemble are discussed and analyzed.

This research paper presents an enhanced economic load dispatch (ELD) approach using the Teaching-Learning-Based Optimization (TLBO) algorithm for 10 thermal units, examining the impact of Plug-in Electric Vehicles (PEVs) in different charging scenarios. The TLBO algorithm is utilized to optimize the ELD problem, considering the complexities associated with thermal units. The integration of PEVs in the load dispatch optimization is investigated, and different charging profiles and probability distributions are defined for PEVs in various scenarios, including overall charging profile, off-peak charging, peak charging, and stochastic charging. These tables allow for the modeling and analysis of PEV charging behavior and power requirements within the power system. By incorporating PEVs, additional controllable resources are introduced, enabling more effective load management and grid stability. The comparative analysis showcases the advantages of the TLBO-based ELD model with PEVs, demonstrating the potential of coordinated dispatch strategies leveraging PEV storage and controllability. This paper emphasizes the importance of integrating PEVs into the load dispatch optimization process, utilizing the TLBO algorithm, to achieve economic and reliable power system operation while considering different PEV charging scenarios.

Serum albumin (ALB), one of the most important proteins in human physiology, has the main functions of maintaining plasma oncotic pressure and plasma volume, transporting hormones, vitamins, oligominerals and drugs, and exerting a powerful antioxidant-antiinflammatory role. Its prognostic value in liver and malabsorption syndromes is well known. In this narrative review, an analysis of the most important studies evaluating the prognostic significance of low serum ALB levels in hospitalized patients was performed. Specifically, the risk in emergency medicine, cardiovascular diseases, COVID-19 infection, nephrology, oncology and autoimmune rheumatic diseases has been examined to fully explore its clinical value. ALB is a negative acute-phase reactant and the reduction of its serum levels represents a threatening parameter for long-term survival in several clinical settings, and a strong poor prognostic biomarker in most diseases. Therefore, clinicians should consider serum ALB as a valuable tool to assess the efficacy of specific therapies, both in hospitalized patients and in chronic follow-up.

All humans will experience the process of birth, old age, illness, and death. However, when faced with life-sustaining decisions, the families of patients are often faced with medical decisions as surrogates. In recent years, the families of patients have started to value the importance of the right to palliative care, although this often requires lengthy discussions. Therefore, this study explored the predictability of factors that affect the feeling experienced by patients’ families when signing Do-Not-Resuscitate Consent. This study used a cross-sectional study and interviewed 90 family members using a structural questionnaire. The study hypotheses were tested using a t-test, one-way analysis of variance, product–moment correlation, and hierarchical regression analysis. Attribute variables of family members, such as gender and whether they live with the patient, are predictors that affect the family member’s feeling experience when signing Do-Not-Resuscitate Consent. The emotional support from medical professionals to family members helps the family member to express their negative feelings on signing Do-Not-Resuscitate Consent; more informational support information provided to family members by medical professionals can alleviate negative feelings felt by family members when signing Do-Not-Resuscitate Consent. This study identified that family members’ knowledge about Do-Not-Resuscitate acquired from medical professionals is relatively low. It is suggested that critical care units regularly conduct training on hospice palliative care, implement standard care procedures of hospice palliative care at critical care units, and provide detailed medical information about advanced decisions to family members so as to reduce their emotional stress. This will ensure that intensive care units can also achieve the goal of critically ill hospice palliative care.

Hydro generator sets serve as the peak and frequency regulation of the power system,and play a very important role in maintaining system stability and improving power quality.Based on the internal characteristics model of a specific type of hydro generator,this paper constructs a hydroelectric coupling model for hydropower units,studies the influence of the regulation system of hydropower units on low-frequency oscillations under different load conditions,and adopts variable speed reaching law and fuzzy sliding mode control strategy to improve the regulation quality of the system and ensure the stable operation of the units.Results of simulation and water turbine set under different load conditions show that varible speed reaching law can effectively improve the power-angle oscillation behavior of the hydropower set and suppress the occurrence of low-frequency oscillations of the system when the system is subject to power disturbance,which provide a new theoretical basis and solution for the vibration analysis and control optimization of hydraulic turbine units.

Accurate electricity price forecasting has become a substantial requirement since the liberalization of the electricity markets. Due to the challenging nature of the electricity prices, which includes high volatility, sharp price spikes and seasonality, various types of electricity price forecasting models still compete and can not outperform each other consistently. Neural Networks have been successfully used in machine learning problems and Recurrent Neural Networks (RNNs) have been proposed to address time-dependent learning problems. In particular, Long Short Term Memory and Gated Recurrent Units (GRU) are tailor-made for time series price estimation. In this paper, we propose to use Gated Recurrent Units as a new technique for electricity price forecasting. We have trained a variety of algorithms with rolling 3-year window and compared the results with the RNNs. In our experiments, 3-layered GRUs outperformed all other neural network structures and state of the art statistical techniques in a statistically significant manner in the Turkish day-ahead market.

Wearable sensors have become increasingly popular for assessing athletic performance, but the optimal methods for processing and analysing the data remain unclear. This study investigates the efficacy of discrete and continuous feature extraction methods, separately and in combination, for modelling countermovement jump performance using wearable sensor data. We demonstrate that continuous features, particularly those derived from Functional Principal Component Analysis, outperform discrete features in terms of model performance, robustness to variations in data distribution and volume, and consistency across different datasets. Our findings underscore the importance of methodological choices, such as signal type, alignment methods, and model selection, in developing accurate and generalisable predictive models. We also highlight the potential pitfalls of relying solely on domain knowledge for feature selection and the benefits of data-driven approaches. Furthermore, we discuss the implications of our findings for the broader field of sports biomechanics and provide practical recommendations for researchers and practitioners aiming to leverage wearable sensor data for athletic performance assessment. Our results contribute to the development of more reliable and widely applicable predictive models, facilitating the use of wearable technology for optimising training and enhancing athletic outcomes across various sports disciplines.

Background: Pediatric Rapid Response Teams (RRTs) are expected to significantly lower pediatric mortality in healthcare settings. This study evaluates RRTs' effectiveness in decreasing cardiac arrests and unexpected Pediatric Intensive Care Unit (PICU) admissions. Methods: A quasi-experimental study (2014-2017) at King Abdulaziz University Hospital, Jeddah, Saudi Arabia, involved 3,261 pediatric inpatients, split into pre-intervention (1,604) and post-intervention (1,657) groups. The intervention entailed pediatric specialists collaboratively managing acute decompensations following set protocols. Results: RRT was activated 471 times, primarily for respiratory distress (29.30%), sepsis (22.30%), clinical anxiety (13.80%), and hematological abnormalities (6.7%). Family concerns triggered 0.1% of activations. Post-RRT implementation, unplanned PICU admissions significantly reduced (RR = 0.552, 95% CI 0.485-0.628, P < 0.0001), and non-ICU cardiac arrests were eliminated (RR = 0). Patient care improvement was notable, with a -9.61 coefficient for PICU admissions (95% CI: -12.65 to -6.57, P < 0.001) and a -1.641 coefficient for non-ICU cardiac arrests (95% CI: -2.22 to -1.06, P < 0.001). Sensitivity analysis showed mixed results for PICU admissions, while zero-inflation Poisson analysis confirmed a reduction in non-ICU arrests. Conclusions: The deployment of pediatric RRTs is associated with fewer unexpected PICU admissions and non-ICU cardiopulmonary arrests, indicating improved PICU management. Further research using robust scientific methods is necessary to conclusively determine RRTs' clinical benefits.

Over the past few decades, the growth of the urban population has been remarkable. Nowadays, 50% of the population lives in urban areas, and forecasts point that by 2050 this number will reach 70%. Today, 64% of all travel made is within urban environments and the total amount of urban kilometers traveled is expected to triple by 2050. Thus, seeking novel solutions for urban mobility becomes paramount for 21st century society. In this work, we discuss the performance of vehicular networks. We consider the metric Delta Network. The Delta Network characterizes the connectivity of the vehicular network through the percentage of travel time in which vehicles are connected to roadside units. This article reviews the concept of Delta Network and extends its study through the presentation of a general heuristic based on the definition of scores to identify the areas of the road network that should receive coverage. After defining the general heuristic, we show how small changes in the score computation can generate very distinct (and interesting) patterns of coverage, each one suited to a given scenario. In order to exemplify such behavior, we propose three deployment strategies based on simply changing the computation of scores. The results show that the strategies derived from the general heuristic are very interesting, all of them deploying roadside units in a circle pattern around the traffic epicenter.

Background: The COVID-19 pandemic, caused by SARS-CoV-2, has severely impacted children with Type 1 Diabetes (T1D), placing them at high risk for severe outcomes. Despite extensive observational data suggesting a link between T1D and severe COVID-19, there is a lack of understanding regarding the causal effects. This study aims to determine whether Type 1 diabetes (T1D) influences the risk of severe COVID-19 outcomes, particularly respiratory failure, in pediatric ICU patients. Methods: This two-sample Mendelian Randomization (MR) study utilized genetic data from large-scale genome-wide association studies (GWAS). Genetic variants associated with T1D were used as instrumental variables to assess their impact on severe COVID-19 outcomes. The primary datasets included genetic data for T1D from 457,695 individuals (6,447 T1D cases) and severe COVID-19 outcomes from 3,790 individuals (1,610 severe cases). Various MR methods, including Inverse Variance Weighted (IVW), MR-Egger Regression, and Weighted Median, were employed to ensure robust causal inference and eliminate potential biases such as pleiotropy. Results: The MR analysis revealed no causal relationship between T1D and severe COVID-19 outcomes in pediatric patients. Odds ratios (ORs) obtained using MR-Egger, Weighted Median, and IVW methods varied from 0.7648 to 0.9853, with p-values greater than 0.05, indicating no significant causal effect. Sensitivity analyses confirmed the robustness of these findings, showing no evidence of heterogeneity or directional pleiotropy. Conclusion: Our findings indicate no genetic causal link between T1D and severe respiratory failure from COVID-19 in children. These results contrast with numerous observational studies and suggest that metabolic dysfunction and other non-genetic factors should be the focus in managing this susceptible group. The insights gained are crucial for developing targeted interventions and improving clinical management strategies for pediatric ICU patients with T1D during the COVID-19 pandemic.

To address the issue of traditional static evaluation models being unable to comprehensively analyse the performance of ultra-supercritical coal-fired units under varying loads, we propose a dynamic comprehensive evaluation model based on the improved Criteria Importance Through Inter-criteria Correlation (CRITIC) method and Entropy Weight Method (EWM). The comprehensive performance evaluation index system of ultra-supercritical coal fired units is constructed by examining the boiler performance, turbine performance, plant power performance, environmental performance, and flexible performance of coal powered units. The CRITIC and EWM methods are used to calculate the weights of the indicators, which are then combined with the static evaluation results. Using a dynamic comprehensive evaluation model, we analysed ultra-supercritical coal-fired units, taking into account time weight. This allowed us to obtain the comprehensive dynamic real-time evaluation value of the units under different loads. The research indicates that the dynamic comprehensive evaluation model, which uses an improved CRITIC and EWM, has significant advantages in improving evaluation accuracy, weight-balanced distribution, and generality. Provides more accurate, reasonable, and reliable evaluation results for practical decision making.

The field of Cooperative Intelligent Transport Systems and more specifically Pedestrians to Vehicles could be characterized as quite challenging, since there is a broad research area to be studied, with direct positive results to society. Pedestrians to Vehicles is a type of Cooperative Intelligent Transport System, within the group of Early Warning Collision/Safety System. In this article, we examine the research and applications carried out so far within the field of Pedestrians to Vehicles Cooperative Transport Systems by leveraging the information coming from Vulnerable Road Users’, smartphones. Moreover, an extensive literature review has been carried out in the fields of Vulnerable Road Users Outdoor Localisation via smartphones and Vulnerable Road Users Next Step/Movement Prediction, which are closely related to Pedestrian to Vehicle applications and research. We identify gaps that exist in these fields that could be improved/extended/enhanced or newly developed, while we address future research objectives and methodologies that could support the improvement/development of those identified gaps.

As an important follow-up report on the latest study of the first author (H.S.) on an off-shell quantum field causing a dressed photon and dark energy, we further discuss a couple of intriguing subjects based on our new theory. One is the dressed photon constant. If we use it, in addition to h¯ and c, as the third component of natural units, then it is defined as the geometric mean of the smallest and the largest lengths: Planck length and that relating to the cosmological constant. Interestingly, this length (≈ 50 nanometers) seems to give a rough measure of the Heisenberg cut for electromagnetic phenomena. The other is a new perspective on cosmology that combines two original notions, i.e., twin universes and conformal cyclic cosmology, proposed respectively by Petit and Penrose, into one novel picture where universes expand self-similarly. We show the possibility that twin universes having a dual structure of [matter with (dark energy &amp; matter)] vs. corresponding anti-entities, separated by an event horizon embedded in the geometric structure of de Sitter space, undergo endless cyclic processes of birth and death, as in the case of the pair creation and annihilation of elementary particles through the intervention of a conformal light field.

The teaching of mathematics at the Faculty of Military Technology of the University of Defense in the first two years of the five-year Military master’s degree is divided into the teaching of students in four specializations: Military Technologies – Mechanical, Military Technologies – Electrical, Military Geography and Cartography, and Cybersecurity. The article discusses the previous five-year experience in teaching the subjects Mathematics I, Mathematics II, Mathematics III, and Graph theory for the specialization in Cybersecurity, that the author of the paper gained while teaching, as a guarantor of these four subjects. The article provides an overview of the topics that are covered, typical exam assignments, and an evaluation of the results of the semester exams in the five years since the accreditation of the Cybersecurity specialization was granted.

It has been theorized that black holes are surrounded by firewalls, although there is not universal agreement concerning this. We first review basic concepts pertaining to Schwarzschild black holes and Hawking radiation. Then we discuss the anticipation of Hawking radiation—albeit from non-black holes—initially by R. C. Tolman and shortly thereafter with P. Ehrenfest. We compare evaporation into a vacuum at absolute zero (0 K) of black holes with that of non-black holes, and show that not only black holes but also non-black holes evaporate within a finite time. The times required for evaporation of black holes and non-black holes are compared. Next, we show that (i) if firewalls exist, they can originate via Hawking radiation at the minimum possible ruler distance (the Planck length) beyond the Schwarzschild horizon, where it has not suffered any gravitational redshift, or, alternatively, suffered maximal gravitational blueshift and (ii) the firewall temperature is on the order of the Planck temperature, independently of the mass and hence also of the Schwarzschild radius of a Schwarzschild black hole. We then explain the exponential nature of the gravitational frequency shift as a function of the gravitational potential. Next, we consider the firewall-mass problem, and provide an at least prima facie tentative resolution thereto based on: (i) the mass of a firewall being canceled by the negative gravitational mass = (negative gravitational energy)/c² accompanying its formation, (ii) the unchanged observations of a distant observer upon formation of a firewall, and (iii) Birkhoff's Theorem (actually first discovered by Jørg Tofte Jebsen). We then consider one aspect of thermodynamics in gravitational fields, showing that equilibrium relativistic gravitational temperature gradients cannot be exploited to violate the Second Law of Thermodynamics.

Autonomous electronic area, territory, or space protection is getting more important. One of the areas of application of the system is to monitor the quarantine zones created during epidemics. The idea to create a system of mobile sensory units for defending quarantine zones was born during one of the phases of the Covid epidemic in 2020. The paper contains a brief technical description of a mobile sensor units and their network. This network surrounds an area of interest. The work includes a mathematical and data model of the protected area. In addition, the paper presents a method for distributing mobile sensor units in areas of interest.

Stress has emerged as a major concern in modern society, significantly impacting human health and well-being. Statistical evidence underscores the extensive social influence of stress, especially in terms of work-related stress and associated healthcare costs. This work addresses the critical need for accurate stress detection, emphasising its far-reaching effects on health and social dynamics. Focusing on remote stress monitoring, this work proposes an efficient deep learning framework to discern stress from facial videos. In contrast to research on wearable devices, this paper investigates the application of *dl for stress detection based on *rppg. The methodology involves selecting suitable *dl models (*lstm, *gru, *1dcnn), optimising hyperparameters, and investigating augmentation techniques. 1D-CNNv1 model achieved the best performance compared to other approaches, particularly with augmentation techniques such as linear interpolation and white noise, achieving a stress classification accuracy of 95.83% while maintaining excellent computational efficiency. The experimental results demonstrate the use of *dl for stress detection based on *rppg, with the potential to make significant contributions to the international standard in the field.