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Accurate prediction of photovoltaic (PV) power generation is the key to daily dispatch management and safe and stable grid operation. In order to improve the accuracy of the prediction, a finite iterative PV power prediction model with long range dependence (LRD) characteristics was developed using fractional Lévy stable motion (fLsm) and applied to a real dataset collected in the DKASC photovoltaic system in Alice Springs, Australia. The LRD prediction model considers the influence of current and past trends in the stochastic series on the future trends. Firstly, the calculation of the maximum steps prediction was introduced based on the maximum Lyapunov. The maximum prediction steps could provide the prediction steps for subsequent prediction models. Secondly, the order stochastic differential equation (FSDE) which describes the fLsm can be obtained. The parameters of the FSDE were estimated by using a novel characteristic function method. The PV power forecasting model with the LRD characteristics was obtained by discretization of FSDE. By comparing statistical performance indicators such as root max error, mean square error with Conv-LSTM, BiLSTM, and GA-LSTM models, the performance of the proposed fLsm model has been demonstrated. The proposed methods can provide better theoretical support for the stable and safe operation of PV grid connection. They have high reference value for grid dispatching department.

BACKGROUND: Few data on the management of acute phase of traumatic spinal cord injury (tSCI) in patients suffering polytrauma are available. As the therapeutic choices in the first hours may have a deep impact on outcome of tSCI patients, we conducted an international survey investigating this topic. METHODS: The survey was composed of 29 items. The main endpoints of the survey were to examine: (1) the hemodynamic and respiratory management, (2) the coagulation management, (3) the timing of magnetic resonance imaging (MRI) and spinal surgery, (4) the use of corticosteroid therapy, (5) the role of intraspinal pressure (ISP)/spinal cord perfusion pressure (SCPP) monitoring and (6) the utilization of therapeutic hypothermia. RESULTS: There were 171 respondents from 139 centers worldwide. A target mean arterial pressure (MAP) target of 80-90 mmHg was chosen in almost half of the cases [n = 84 (49.1%)]. A temporary reduction in the target MAP, for the time strictly necessary to achieve bleeding control in polytrauma, was accepted by most respondents [n = 100 (58.5%)]. Sixty-one respondents (35.7%) considered acceptable a hemoglobin (Hb) level of 7 g/dl in tSCI polytraumatized patients. An arterial partial pressure of oxygen (PaO2) of 80-100 mmHg [n = 94 (55%)] and an arterial partial pressure of carbon dioxide (PaCO2) of 35-40 mmHg [n = 130 (76%)] were chosen in most cases. A little more than half of respondents considered safe a platelet (PLT) count > 100.000/mm3 [n = 99 (57.9%)] and prothrombin time (PT)/activated partial thromboplastin time (aPTT)

Motivated by the recent research about non-integer order derivatives of Dirac delta function, we use a fractional Taylor series to explore a fractional distributional representation of gamma function. It proved significant to develop a novel fractional kinetic equation, which is an essential mathematical model to measure the degree of transformation in the chemical structure of stars (sun) as a key component of our environment. In addition to the classical solution of the formulated fractional kinetic equation, the distributional solution is also attained which is not possible without using fractional derivatives of Dirac delta function. Novel identities involving the gamma function are obtained using several fractional transforms. Convergence of new series is proved using the theory of distributions leading to further new applications.

We investigate the behavior of a complex three-strain model with a generalized incidence rate. The incidence rate is an essential aspect of the model as it determines the number of new infections emerging. The mathematical model comprises thirteen nonlinear ordinary differential equations with susceptible, exposed, symptomatic, asymptomatic and recovered compartments. The model is well-posed and verified through existence, positivity and boundedness. Eight equilibria comprise a disease-free equilibria and seven endemic equilibrium points following the existence of three strains. The basic reproduction numbers $ \mathfrak{R}_{01} $, $ \mathfrak{R}_{02} $ and $ \mathfrak{R}_{03} $ represent the dominance of strain 1, strain 2 and strain 3 in the environment for new strain emergence. The model establishes local stability at a disease-free equilibrium point. Numerical simulations endorse the impact of general incidence rates, including bi-linear, saturated, Beddington DeAngelis, non-monotone and Crowley Martin incidence rates.

Abstract Hearing loss impacts the quality of life and affects communication resulting in social isolation and reduced well-being. Despite its impact on society and economy, no therapies for age-related hearing loss are available so far. Loss of mechanosensory hair cells of the cochlea is a common event of hearing loss in humans. Studies performed in birds demonstrating that they can be replaced following the proliferation and transdifferentiation of supporting cells, strongly pointed out on HCs regeneration as the main focus of research aimed at hearing regeneration. Neurotrophins are growth factors involved in neuronal survival, development, differentiation, and plasticity. NGF has been involved in the interplay between auditory receptors and efferent innervation in the cochlea during development. During embryo development, both NGF and its receptors are highly expressed in the inner ears. It has been reported that NGF is implicated in the differentiation of auditory gangliar and hair cells. Thus, it has been proposed that NGF administration can decrease neuronal damage and prevent hearing loss. The main obstacle to the development of hearing impairment therapy is that efficient means of delivery for selected drugs to the cochlea are missing. Herein, in this study NGF was administered by the intranasal route. The first part of the study was focused on a biodistribution study, which showed the effective delivery in the cochlea; while the second part was focused on analyzing the potential therapeutic effect of NGF in senescence-accelerated prone strain 8 mice. Interestingly, intranasal administration of NGF resulted protective in counteracting hearing impairment in SAMP8 mice, ameliorating hearing performances (analyzed by auditory brainstem responses and distortion product otoacoustic emission) and hair cells morphology (analyzed by microscopy analysis). The results obtained were encouraging indicating that the neurotrophin NGF was efficiently delivered to the inner ear and that it was effective in counteracting hearing loss.

Computational models lie at the intersection of basic neuroscience and healthcare applications because they allow researchers to test hypotheses in silico and predict the outcome of experiments and interactions that are very hard to test in reality. Yet, what is meant by "computational model" is understood in many different ways by researchers in different fields of neuroscience and psychology, hindering communication and collaboration. In this review, we point out the state of the art of computational modeling in Electroencephalography (EEG) and outline how these models can be used to integrate findings from electrophysiology, network-level models, and behavior. On the one hand, computational models serve to investigate the mechanisms that generate brain activity, for example measured with EEG, such as the transient emergence of oscillations at different frequency bands and/or with different spatial topographies. On the other hand, computational models serve to design experiments and test hypotheses in silico. The final purpose of computational models of EEG is to obtain a comprehensive understanding of the mechanisms that underlie the EEG signal. This is crucial for an accurate interpretation of EEG measurements that may ultimately serve in the development of novel clinical applications.

As the demand for miniaturization of thermal management systems for electronic devices rises, numerous researchers are dedicating their efforts to the study of single-phase forced convective heat transfer (FCHT) within nanoscale channels. However, investigating FCHT in nanochannels (FCHT-NC) using experimental and theoretical methods is challenging. Alternately, molecular dynamics (MD) simulations have emerged as a unique and powerful technique in recent years. This paper presents a comprehensive review of the application of the MD simulation method in the study of FCHT-NC. Firstly, the current paper reviews various simulation techniques and models, along with their associated primary parameters employed in FCHT-NC, through a detailed and systematic literature survey and critical analysis. Evaluating the current methods and discussing their limitations provide helpful guidelines for future studies. Furthermore, based on the existing literature in the MD simulation, this review outlines all influencing parameters on the performance of FCHT-NC, covering their effects and discussing underlying mechanisms. Finally, key challenges and future research directions are summarized in this review, thereby providing essential support for researchers seeking to apply the MD simulation method to investigate FCHT-NC.

For lithium-ion batteries and supercapacitors in hybrid power storage facilities, both steady degradation and random shock contribute to their failure. To this end, in this paper, we propose to introduce the degradation-threshold-shock (DTS) model for their remaining useful life (RUL) prediction. Non-homogeneous compound Poisson process (NHCP) is proposed to simulate the shock effect in the DTS model. Considering the long-range dependence and heavy-tailed characteristics of the degradation process, fractional Weibull process (fWp) is employed in the diffusion term of the stochastic degradation model. Furthermore, the drift and diffusion coefficients are constantly updated to describe the environmental interference. Prior to the model training, steady degradation and shock data must be separated, based on the three-sigma principle. Degradation data for the lithium-ion batteries (LIBs) and ultracapacitors are employed for model verification under different operation protocols in the power system. Recent deep learning models and stochastic process-based methods are utilized for model comparison, and the proposed model shows higher prediction accuracy.

As lithium-ion batteries increasingly become a cornerstone of the automotive sector, the importance of efficient and cost-effective battery production has become paramount. Even though electric vehicle battery cells are produced in three different geometries—cylindrical, prismatic, and pouch—no specific model exists to compare the manufacturing costs of producing cells with different geometries but similar performances. In this paper, we present a process-based cost model with a cell design functionality which enables design and manufacturing cost prediction of user-defined battery cells.

Self-similarity is a common feature among mathematical fractals and various objects of our natural environment. Therefore, escape criteria are used to determine the dynamics of fractal patterns through various iterative techniques. Taking motivation from this fact, we generate and analyze fractals as an application of the proposed Mann iterative technique with h-convexity. By doing so, we develop an escape criterion for it. Using this established criterion, we set the algorithm for fractal generation. We use the complex function f(x)=xn+ct, with n≥2,c∈C and t∈R to generate and compare fractals using both the Mann iteration and Mann iteration with h-convexity. We generalize the Mann iterative scheme using the convexity parameter h(α)=α2 and provide the detailed representations of quadratic and cubic fractals. Our comparative analysis consistently proved that the Mann iteration with h-convexity significantly outperforms the standard Mann iteration scheme regarding speed and efficiency. It is noticeable that the average number of iterations required to perform the task using Mann iteration with h-convexity is significantly less than the classical Mann iteration scheme. Moreover, the relationship between the fractal patterns and the input parameters of the proposed iteration is extremely intricate.

Purpose or Objective—The aim of the study is to evaluate the efficacy and safety of SBRT on detectable prostate bed recurrence in RT-naïve prostate cancer patients. Materials and methods: Eighty-six patients who underwent SBRT for macroscopic bed recurrence after prostatectomy were retrospectively included. Patients were treated based on mpMRI or choline/PSMA PET. Results: The median time to biochemical relapse (BCR) after RP was 46 months, with a median PSA at restaging of 1.04 ng/mL. Forty-six patients were staged with mpMRI and choline/PSMA PET, while ten and thirty were treated based on PET and MRI only, respectively. Only one late G ≥ 2 GI toxicity was observed. With a median BCR follow-up of 14 months, twenty-nine patients experienced a BCR with a median PSA at recurrence of 1.66 ng/mL and a median survival free from the event of 40.1 months. The median time to BCR was 17.9 months. Twenty-seven patients had clinical relapse (CR), with a median CR follow-up of 16.27 months and a median time to CR of 23.0 months. Biochemical recurrence-free survival at one and two years was 88% and 66%, respectively, while clinical recurrence-free survival at one and two years was 92% and 82%, respectively. Regarding local relapses, seven were in the field of treatment, while eight of them were outside the field of treatment. Conclusions: Data showed that SBRT targeting only the macroscopic bed recurrence instead of the whole prostate bed is safe and effective. Additional data and longer follow-ups will provide a clearer indication of the appropriate treatment and staging methodology for these patients.

The primary objective pursued in this research is the creation and thorough evaluation of an inventive cooling system designed to uphold optimal temperatures within the batteries employed in electric vehicles. Nowadays, the prevailing equipment underpinning electrical motion hinges on Lithium-Ion cells. These cells frequently necessitate the expeditious delivery of substantial power, thereby giving rise to a consequential generation of heat. Consequently, there is an emergence of elevated operational temperatures, potentially causing noteworthy declines in battery performance, or, in extreme cases, operational failures. Furthermore, deviating from the recommended temperature range (20–40 °C) significantly expedites the aging process of the battery and elevates the probability of premature malfunction. In response to these crucial challenges, the implementation of a battery thermal management system assumes a pivotal role in maximizing battery efficiency. Within the framework of this investigation, we propose the adoption of a cooling system founded on a three-dimensional pulsating heat pipe as the designated thermal management technology for a battery pack. The preliminary phase of our study involved the assessment of the suggested pulsating heat pipe’s performance. Following this, the efficacy of the pulsating heat pipe is subjected to rigorous scrutiny through practical experimentation on an authentic electric battery. The empirical findings conclusively highlight the substantial cooling capacity of the proposed system, thereby presenting a robust and efficacious solution for the thermal management challenges faced by electric vehicle batteries.

The release of cultivars of two perennial grains is a milestone in perennial grain and oilseed development. Agronomic studies can progress by having stable genetics upon which to conduct research. Agriculture has generally committed to enhancing soil health, with perennial grains and oilseeds offering potentially non-animal-related alternatives to our current choices. Utilizing perennial grains and oilseeds offers potential to small-grain producers to improve, or at least maintain, their soil quality as perennial grains generally have little soil disturbance post-seeding. Understanding perennial grain and oilseed development and how they interact with their growth environment will provide us with baselines upon which to gauge agronomic interventions as we attempt to increase productivity without negative environmental impacts.

While recent studies have proven an unexpected liquid–vapor phase transition of adsorbed liquid films, a comprehensive description of the mechanisms of different types of phase change regimes over realistic representations of random rough surfaces is absent in the literature. The current comprehensive study investigates the effects of a gold random rough surface, liquid film thickness, and substrate temperature on the liquid–vapor phase change regime of an adsorbed sodium liquid film, considering the evaporator section of a wicked heat pipe (WHP) using a molecular dynamics (MD) simulation. At first, to generate a realistic random rough surface, a new and promising method is proposed that is entirely based on MD simulations. Then, to simulate the evaporator section of a WHP, a unique configuration for eliminating the vapor domain is developed. The simulation results reveal that three distinct regimes, namely, normal evaporation, cluster boiling, and film boiling, could be identified, which are presented on two-dimensional diagrams with the substrate temperature and liquid film thickness as coordinates for the ideally smooth and random rough surfaces. The results also manifest that even though using the random rough surface could lead to different phase transition regimes, the type of regime depends mainly on the substrate temperature and liquid film thickness. Furthermore, this study displays two different modes for normal evaporation. Also, it is shown that the impacts of the liquid film thickness and substrate temperature on the mode of normal evaporation are much more significant than the surface roughness.

In this technical development report, we present the strategic placement of fiducial markers within the prostate under the guidance of computed tomography (CT) and electromagnetic navigation (EMN) for the delivery of ultra-hypofractionated cyberknife (CK) therapy in a patient with localized prostate cancer (PCa) who had previously undergone chemo-radiotherapy for rectal cancer and subsequent abdominoperineal resection due to local recurrence. The patient was positioned in a prone position with a pillow under the pelvis to facilitate access, and an electromagnetic fiducial marker was placed on the patient’s skin to establish a stable position. CT scans were performed to plan the procedure, mark virtual points, and simulate the needle trajectory using the navigation system. Local anesthesia was administered, and a 21G needle was used to place the fiducial markers according to the navigation system information. A confirmatory CT scan was obtained to ensure proper positioning. The implantation procedure was safe, without any acute side effects such as pain, hematuria, dysuria, or hematospermia. Our report highlights the ability to use EMN systems to virtually navigate within a pre-acquired imaging dataset in the interventional room, allowing for non-conventional approaches and potentially revolutionizing fiducial marker positioning, offering new perspectives for PCa treatment in selected cases.

Background: The magnitude of short/medium-term air pollution exposure on atopic dermatitis (AD) flare has not been fully investigated. The aim of the study was to investigate the association of short/medium-term exposure to airborne pollution on AD flares in patients treated with dupilumab. Methods: Observational case-crossover study. Patients with moderate-to-severe AD under treatment with dupilumab were included. The exposure of interest was the mean concentrations of coarse and fine particulate matter (PM10, PM2.5), nitrogen dioxide, and oxides (NO2, NOx). Different intervals were considered at 1 to 60 days before the AD flare and control visit, defined as the visit with the highest Eczema Area and Severity Index scores >8 and ≤7, respectively. A conditional logistic regression analysis adjusted for systemic treatments was employed to estimate the incremental odds (%) of flare every 10 μg/m3 pollutant concentration. Results: Data on 169 of 528 patients with AD having 1130 follow-up visits and 5840 air pollutant concentration measurements were retrieved. The mean age was 41.4 ± 20.3 years; 94 (55%) men. The incremental odds curve indicated a significant positive trend of AD flare for all pollutants in all time windows. At 60 days, every 10 μg/m3 PM10, PM2.5, NOx, and NO2 increase concentration was associated with 82%, 67%, 28%, and 113% odds of flare, respectively. Conclusions: In patients treated with dupilumab, acute air pollution exposure is associated with an increased risk for AD flare with a dose-response relationship.

This study estimates the health-related and public expenditure impacts of the solid waste services provided by public consortia in Brazilian Municipalities from the enactment of Public Consortia law (2005) to 2019. To conduct the analysis, we applied the econometric method of staggered difference-in-differences to publicly available datasets at the municipality level. The results show that the operation of solid waste services by public consortia had statistically significant effects in reducing hospitalizations caused by Schistosomiasis, Diarrhea/gastroenteritis (up to 5 years age) and other intestinal diseases. The results also indicate a positive impact on the reduction of environmental expenses in treated municipalities, supporting the idea that a Solid Waste Consortium can serve as a local coordinator and improve health and fiscal indicators simultaneously. The findings provide quantitative evidence that policymakers at the local and regional level can use to better understand the benefits of adhering to public consortia when preparing new investments and operation developments for this sector. This paper contributes to the literature of applied research in solid waste by shedding light on the underexplored theme of the intergovernmental cooperative arrangements, which can be instrumental in accelerating and enhancing the development of solid waste services.

High-resolution biological tissue slice images provide opportunities for more precise observation and analysis of histopathological features. These images typically consist of enclosed contours, and Bendlets transform is an effective means to approximate such structures. In this study, we leverage Bendlet transform to incorporate multi-level image data, thereby establishing a multi-scale pyramid feature set. This approach aids in achieving a sparser representation of image textures and structures. We apply Bendlets transform to extract multi-frequency wavelet subband features and formulate structured dictionaries for both high and low resolutions based on these features. After creating these dictionaries, we compute sparse representation coefficients using the low-resolution dictionary and subsequently integrate them with the high-resolution dictionary to generate high-resolution subbands. Ultimately, through the process of inverse wavelet transformation, we completed the reconstruction of high-resolution images. This method not only significantly enhances the restoration of image details and clarity but also effectively preserves the overall structural characteristics of the original images.

O presente ensaio apresenta experiências cênicas realizadas pela autora marcadas por tensões entre sexualidade, violência, desejo e poder, no intuito de problematizar o juízo de valor sobre a expressão da sexualidade feminina e as diversas consequências que derivam de um machismo estrutural. Articulando aspectos do pensamento da escritora feminista Despentes, do sociólogo e antropólogo Wacquant e da artista Bandarra, são apontadas algumas das motivações da performer ao escolher o caminho da dita "mulher vulgar", mais desejante do que desejada, e o modo como o burlesco vem lhe proporcionando um espaço de expressão capaz de acolher esse seu desejo de provocação e questionamento.

Objective To estimate the prevalence of overweight at 12 months in an Italian birth cohort and to identify factors related to an increased likelihood of being overweight.Methods The Italian NASCITA birth cohort was analysed. Infants were classified as underweight (

Abstract Vaginal birth causes pelvic floor injury which may lead to urinary incontinence. Cell therapy has been proposed to assist in functional recovery. We aim to assess if intra-arterial injection of rat mesoangioblasts (MABs) and stable Vascular Endothelial Growth Factor (VEGF)-expressing MABs, improve recovery of urethral and vaginal function following simulated vaginal delivery (SVD). Female rats (n = 86) were assigned to either injection of saline (control), allogeneic-MABs (MABsallo), autologous-MABs (MABsauto) or allogeneic-MABs transduced to stably expressed VEGF (MABsallo-VEGF). One hour after SVD, 0.5 × 106 MABs or saline were injected into the aorta. Primary outcome was urethral (7d and 14d) and vaginal (14d) function; others were bioluminescent imaging for cell tracking (1, 3 and 7d), morphometry (7, 14 and 60d) and mRNAseq (3 and 7d). All MABs injected rats had external urethral sphincter and vaginal function recovery within 14d, as compared to only half of saline controls. Functional recovery was paralleled by improved muscle regeneration and microvascularization. Recovery rate was not different between MABsallo and MABsauto. MABsallo-VEGF accelerated functional recovery and increased GAP-43 expression at 7d. At 3d we detected major transcriptional changes in the urethra of both MABsallo and MABsallo-VEGF-injected animals, with upregulation of Rho/GTPase activity, epigenetic factors and dendrite development. MABSallo also upregulated transcripts that encode proteins involved in myogenesis and downregulated pro-inflammatory processes. MABsallo-VEGF also upregulated transcripts that encode proteins involved in neuron development and downregulated genes involved in hypoxia and oxidative stress. At 7d, urethras of MABsallo-VEGF-injected rats showed downregulation of oxidative and inflammatory response compared to MABSallo. Intra-arterial injection of MABsallo-VEGF enhances neuromuscular regeneration induced by untransduced MABs and accelerates the functional urethral and vaginal recovery after SVD.

This article examines the Russian translation of 'Le leggende sarde' [Sardinian Legends] by Grazia Deledda, which deals with the extremely complex language of the Italian-Sardinian hybrid original text. The aim of this work is to verify the achievement, in the target text, of functional equivalence (f-equivalence). In direct dialogue with the translator, the strategies involve the explanation and application of the theoretical tools dictated by the most recent studies in translation studies.

In the present study, the effects of the strong Allee effect on the dynamics of the modified Leslie-Gower predator-prey model, in the presence of nonlinear prey-harvesting, have been investigated. In our findings, it is seen that the behaviors of the described mathematical model are positive and bounded for all future times. The conditions for the local stability and existence for various distinct equilibrium points have been determined. The present research concludes that system dynamics are vulnerable to initial conditions. In addition, the presence of several types of bifurcations (e.g., saddle-node bifurcation, Hopf bifurcation, Bogdanov-Takens bifurcation, homoclinic bifurcation) has been investigated. The first Lyapunov coefficient has been evaluated to study the stability of the limit cycle that results from Hopf bifurcation. The presence of a homoclinic loop has been demonstrated by numerical simulation. Finally, possible phase drawings and parametric figures have been depicted to validate the outcomes.

The growing demand and market penetration of electric vehicles (EVs) have led to an expansion in the size of the market for used EVs, accompanied by a continuous increase in the return rate of aging battery systems. Consequently, a second-hand market for aged battery systems, known as second-life batteries, is slowly emerging. Understanding this market is crucial for enabling a functioning circular economy for batteries. This paper analyzes the market mechanisms influencing price formation for used goods, drawing parallels to the largest second-hand market, the used car market, and applies them to the second-life battery market. By examining these mechanisms, insights are provided into the dynamics of the second-life battery market, facilitating the development of strategies to optimize resource utilization and sustainability in the EV industry. Finally, the second-life battery price index is introduced, increasing the transparency of prices for lithium-ion batteries and the circular economy.

Wound healing is a dynamic and complex process, characterized by the coordinated activities of multiple cell types, each with distinct roles in the stages of hemostasis, inflammation, proliferation, and remodeling. The cells of the immune system not only act as sentinels to monitor the skin and promote homeostasis, but they also play an important role in the process of skin wound repair. Skin-resident and recruited immune cells release cytokines and growth factors that promote the amplification of the inflammatory process. They also work with non-immune cells to remove invading pathogens and debris, as well as guide the regeneration of damaged host tissues. Dysregulation of the immune system at any stage of the process may lead to a prolongation of the inflammatory phase and the development of a pathological condition, such as a chronic wound. The present review aims to summarize the roles of different immune cells, with special emphasis on the different stages of the wound healing process.

Roller bearing degradation features fractal characteristics such as self-similarity and long-range dependence (LRD). However, the existing remaining useful life (RUL) prediction models are memoryless or short-range dependent. To this end, we propose a RUL prediction model based on fractional Brownian motion (FBM). Bearing faults can happen in different places, and thus their degradation features are difficult to extract accurately. Through variational mode decomposition (VMD), the original degradation feature is decomposed into several components of different frequencies. The monotonicity, robustness and trends of the different components are calculated. The frequency component with the best metric values is selected as the training data. In this way, the performance of the prediction model is hugely improved. The unknown parameters in the degradation model are estimated by the maximum likelihood algorithm. The Monte Carlo method is applied to predict the RUL. A case study of a bearing is presented and the prediction performance is evaluated using multiple indicators.

The paper discusses the energy efficiency of smart working (SW) as a solution to traditional work-approach issues, with a focus on evaluating benefits for both employers and employees. Remote working, while offering environmental advantages such as reduced commuting and office space use, poses challenges in assessing its true impact. The study presents results from a dynamic analysis on a real residential building, typical of an architectural style diffused in northern Italy, revealing a 15% average increase in energy consumption when all work tasks are performed from home. To address concerns about the environmental impact of SW, the research proposes a method and metrics for evaluation. Four novel indices (SWEET, SEE, SSEE, and 4E) are introduced, providing a structured approach to assess the energy efficiency of SW initiatives. The paper outlines a methodology for data gathering and metric application, aiming to acquire quantitative insights and mitigate disparities arising from a transfer of burdens to employees. This contribution not only signifies a ground-breaking methodology but also addresses an unresolved research question concerning the evaluation of the actual energy efficiency of smart working implementations for both employers and employees. The results underscore the importance of understanding the nuances of SW’s impact on household energy usage and its broader implications for sustainability goals.

ABSTRACT OBJECTIVE Flattening the curve was the most promoted public health strategy worldwide, during the pandemic, to slow down the spread of the SARS-CoV-2 virus, and, consequently, to avoid overloading the healthcare systems. In Brazil, a relative success of public policies was evidenced. However, the association between public policies and the “flatten the curve” objectives remain unclear, as well as the association of different policies to reach this aim. This study aims to verify if the adoption of different public policies was associated with the flattening of the infection and death curves by covid-19 first wave in 2020. METHODS Data from the Sistema de Informação da Vigilância Epidemiológica da Gripe (Influenza Epidemiological Surveillance Information System – SIVEP-Gripe) and the Instituto Brasileiro de Geografia e Estatística (Brazilian Institute of Geography and Statistics – IBGE) were used to compute standardized incidence and mortality rates. The Oxford Covid-19 Government Response Tracker (OxCGRT) was used to obtain information about governmental responses related to the mitigation of pandemic effects, and the Human Development Index (HDI) was used as a measure of socioeconomic status. A non-linear least-square method was used to estimate parameters of the five-parameter sigmoidal curve, obtaining the time to reach the peak and the incremental rate of the curves. Additionally, ordinary least-square linear models were used to assess the correlation between the curves and the public policies adopted. RESULTS Out of 51 municipalities, 261,326 patients had SARS-CoV-2 infection. Stringency Index was associated with reducing covid-19 incremental incidence and death rates,in addition to delaying the time to reach the peak of both pandemic curves. Considering both parameters, economic support policies did not affect the incidence nor the mortality rate curves. CONCLUSION The evidence highlighted the importance and effectiveness of social distancing policies during the first year of the pandemic in Brazil, flattening the curves of mortality and incidence rates. Other policies, such as those focused on economic support, were not effective in flattening the curves but met humanitarian and social outcomes.

Natural disasters present ongoing risks to human life and the global economy, with climate change and environmental factors exacerbating these threats. This article introduces an innovative approach to earthquake prediction and modeling, utilizing a combination of modern mathematical techniques, data-driven methodologies, and artificial intelligence (AI). By integrating the finite element method and wavelet collocation method, our approach enables the solution of complex partial differential equations involving fractional derivatives. This integration provides a more accurate prediction of earthquake behavior by leveraging AI analysis of the resulting numerical solutions.Our advanced modeling technique enables three-dimensional earthquake modeling, surpassing the limitations of traditional methods and offering unprecedented insights. The comprehensive AI approach shows great potential for improving our understanding of earthquake behavior, facilitating the design of earthquake-resistant structures, and effectively mitigating the devastating impacts of earthquakes.This research significantly contributes to the field of disaster risk reduction and offers practical applications for both researchers and practitioners. By combining mathematical rigor, data-driven insights, and the power of AI, our next-generation approach opens new avenues for enhancing our preparedness and response to seismic events.

Introduction.We performed a single-center, prospective, observational study of newborns born from mothers with microbiologically confirmed SARS-CoV-2 infection in pregnancy or at time of delivery to evaluate acute and mid-term multidisciplinary outcomes.Methods.Infants were offered a multidisciplinary follow-up consisting of nasopharyngeal Polymerase Chain Reaction test at birth and at 48–72 h of life, auxological and ophthalmological assessments, and serologic testing.Results.791 women and their 791 children (52.3% males) were included. Most placentas (94.9%) had abnormal inflammatory findings. 171 (27.3%) and 36 (13.7%) children respectively had pathological TEOAEs in at least one ear and bilaterally, while only four of the 85 children that underwent ABR had pathological findings (4.7%). 64 children underwent fluorescein angiography, which resulted pathological only in 1 case (1.6%). Anti-SARS-CoV-2 IgGs were found in up to 60% of children tested at six months of age. Our findings showed no association between the maternal vaccination status or the presence of maternal symptoms during pregnancy and neonatal outcomes.Conclusions.Our study shows that the large majority of newborns exposed to SARS-CoV-2 infection in utero or during the first hours of life have optimal outcomes. Our previous report of abnormal ophthalmologic findings was not confirmed on a larger cohort, while further studies are needed to better characterize audiological outcomes. Further prospective, case-controlled studies are still needed.

The COVID-19 pandemic still gains the attention of many researchers worldwide. Over the past few months, China faced a new wave of this pandemic which increases the risk of its spread to the rest of the world. Therefore, there has become an urgent demand to know the expected behavior of this pandemic in the coming period. In this regard, there are many mathematical models from which we may obtain accurate predictions about the behavior of this pandemic. Such a target may be achieved via updating the mathematical models taking into account the memory effect in the fractional calculus. This paper generalizes the power-law growth model of the COVID-19. The generalized model is investigated using two different definitions in the fractional calculus, mainly, the Caputo fractional derivative and the conformable derivative. The solution of the first-model is determined in a closed series form and the convergence is addressed. At a specific condition, the series transforms to an exact form. In addition, the solution of the second-model is evaluated exactly. The results are applied on eight European countries to predict the behavior/variation of the infected cases. Moreover, some remarks are given about the validity of the results reported in the literature.

Abstract Objectives Patients with single‐sided deafness (SSD) may experience difficulties with speech perception in noise, sound localization, have tinnitus and experience a reduced quality of life (QoL). contralateral routing of sound hearing aids (CROS) or bone conduction devices (BCD) may partly improve subjective speech communication and QoL in SSD patients. A trial period with these devices can help in making a well‐informed choice of treatment. Our aim was to evaluate factors influencing the choice of treatment made after a BCD and CROS trial period in adult SSD patients. Methods Patients were randomized in the: “first BCD, then CROS” or “first CROS, then BCD” trial period group. After the BCD on headband and CROS were tested for 6 weeks each, patients choose for BCD, CROS or no treatment. Primary outcome was the distribution of choice of treatment. Secondary outcomes included the association between the choice of treatment and patient characteristics, reasons for treatment acceptance or rejection, device usage during the trial periods, and disease‐specific QoL outcomes. Results Of 91 patients randomized, 84 completed both trial periods and made their choice of treatment: 25 (30%) BCD, 34 (40%) CROS, and 25 (30%) no treatment. No characteristics were found to be related to choice of treatment. Top three reasons for acceptance or rejection were: device (dis)comfort, sound quality and (dis)advantage of subjective hearing. Average daily device use during the trial periods was higher for CROS than for BCD. Choice of treatment was significantly related with both duration of device usage and greater improvement of QoL after the corresponding trial period. Conclusion The majority of SSD patients preferred BCD or CROS over no treatment. Evaluating device usage, discussing treatment (dis)advantages and disease‐specific QoL outcomes after trial periods are to be considered during patient counseling and could facilitate whether to choose one of these treatments. Level of evidence 1B.

Abstract Background Contouring of anatomical regions is a crucial step in the medical workflow and is both time-consuming and prone to intra- and inter-observer variability. This study compares different strategies for automatic segmentation of the prostate in T2-weighted MRIs. Methods This study included 100 patients diagnosed with prostate adenocarcinoma who had undergone multi-parametric MRI and prostatectomy. From the T2-weighted MR images, ground truth segmentation masks were established by consensus from two expert radiologists. The prostate was then automatically contoured with six different methods: (1) a multi-atlas algorithm, (2) a proprietary algorithm in the Syngo.Via medical imaging software, and four deep learning models: (3) a V-net trained from scratch, (4) a pre-trained 2D U-net, (5) a GAN extension of the 2D U-net, and (6) a segmentation-adapted EfficientDet architecture. The resulting segmentations were compared and scored against the ground truth masks with one 70/30 and one 50/50 train/test data split. We also analyzed the association between segmentation performance and clinical variables. Results The best performing method was the adapted EfficientDet (model 6), achieving a mean Dice coefficient of 0.914, a mean absolute volume difference of 5.9%, a mean surface distance (MSD) of 1.93 pixels, and a mean 95th percentile Hausdorff distance of 3.77 pixels. The deep learning models were less prone to serious errors (0.854 minimum Dice and 4.02 maximum MSD), and no significant relationship was found between segmentation performance and clinical variables. Conclusions Deep learning-based segmentation techniques can consistently achieve Dice coefficients of 0.9 or above with as few as 50 training patients, regardless of architectural archetype. The atlas-based and Syngo.via methods found in commercial clinical software performed significantly worse (0.855 $$-$$ - 0.887 Dice).