A regional GIS-based model for reconstructing natural monthly streamflow series at ungauged sites

Several hydrologic applications require reliable estimates of monthly runoff in river basins to face the widespread lack of data, both in time and in space. The main aim of this work is to propose a regional model for the estimation of monthly natural runoff series at ungauged sites, analyzing its applicability, reliability and limitations. A GIS (Geographic Information System) based model is here developed and applied to the entire region of Sicily (Italy). The core of this tool is a regional model for the estimation of monthly natural runoff series, based on a simple modelling structure, consisting of a regression based rainfall-runoff model with only four parameters. The monthly runoff is obtained as a function of precipitation and mean temperature at the same month and runoff at the previous month. For a given basin, the four model parameters are assessed by specific regional equations as a function of some easily measurable geomorphic and climate basins’ descriptors. The model is calibrated by a “two-step” procedure applied to a number of gauged basins over the region. The first step is aimed at the identification of a set of parameters optimizing model performances at the level of single basin. Such “optimal” parameters sets, derived for each calibration basin, are successively used inside a regional regression analysis, performed at the second step, by which the regional equations for model parameters assessment are defined and calibrated. All the gauged watersheds across the Sicily have been analyzed, selecting 53 basins for model calibration and using other 6 basins exclusively for validation purposes. Model performances, quantitatively evaluated considering different statistical indexes, demonstrate a relevant model ability in capturing the observed hydrological response at both the monthly level and higher time scales (seasonal and annual). One of the key features related to the proposed methodology is its easy transferability to other arid and semiarid Mediterranean areas; thus, the application here shown may be considered as a benchmark for similar studies. The calibrated model is implemented by a GIS software (i.e. Quantum GIS 2.10), automatizing data retrieving and processing procedures and creating a prompt and reliable tool for filling/reconstructing precipitation, temperature or streamflow time series at any gauged or ungauged Sicilian basin. The proposed GIS plug-in can, in fact, be applied at any point of the hydrographical network of the region, assessing the precipitation, temperature and natural streamflow series (at the monthly or higher time scales) for a desired time-window

Improving Password Guessing via Representation Learning

Learning useful representations from unstructured data is one of the core challenges, as well as a driving force, of modern data-driven approaches. Deep learning has demonstrated the broad advantages of learning and harnessing such representations. In this paper, we introduce a deep generative model representation learning approach for password guessing. We show that an abstract password representation naturally offers compelling and versatile properties that can be used to open new directions in the extensively studied, and yet presently active, password guessing field. These properties can establish novel password generation techniques that are neither feasible nor practical with the existing probabilistic and non-probabilistic approaches. Based on these properties, we introduce:(1) A general framework for conditional password guessing that can generate passwords with arbitrary biases; and (2) an Expectation Maximization-inspired framework that can dynamically adapt the estimated password distribution to match the distribution of the attacked password set.Comment: This paper appears in the proceedings of the 42nd IEEE Symposium on Security and Privacy (Oakland) S&P 202

A weather monitoring system for the study of precipitation fields, weather, and climate in an urban area

The possibility to study the precipitation dynamics with advanced and specific tools is an important task of the research activity addressing the understanding, the modeling, and the managing of rainfall events. Over the last years, the hydrology laboratory of the Department of Civil, Environmental, Aerospace Engineering, and Materials (DICAM) at the University of Palermo, has installed several instruments for the monitoring and the study of precipitation within the urban area of Palermo (Italy). The main instrument of this system is the X-band weather radar, which allows monitoring the precipitation fields with high resolution in space and time. This instrument is supported by a rain gauges network of 18 tipping bucket gauges spread over the observed area, a weight rain gauge, an optical disdrometer, and a weather station. The information provided by different devices can be combined in order to integrate different data and correct errors. In particular, the disdrometer is able to provide the drop size distribution (DSD) that is directly linked to the parameters used to transform radar reflectivity to precipitation estimates. Moreover, disdrometer observations can be used to classify the precipitation events. The rain gauges network data is used to apply a ground correction to the radar precipitation maps. Such an operation is useful to constrain the radar estimate to the observed ground precipitation value. Results obtained from a prototypal version of the system, that considers only the main applications designed, are discussed for a study event. Finally, all of the above instruments are embedded in an integrated early warning system able to provide warnings related to possible flood in the urban area of Palermo

Altered expression of mitochondrial and extracellular matrix genes in the heart of human fetuses with chromosome 21 trisomy

<p>Abstract</p> <p>Background</p> <p>The Down syndrome phenotype has been attributed to overexpression of chromosome 21 (Hsa21) genes. However, the expression profile of Hsa21 genes in trisomic human subjects as well as their effects on genes located on different chromosomes are largely unknown. Using oligonucleotide microarrays we compared the gene expression profiles of hearts of human fetuses with and without Hsa21 trisomy.</p> <p>Results</p> <p>Approximately half of the 15,000 genes examined (87 of the 168 genes on Hsa21) were expressed in the heart at 18–22 weeks of gestation. Hsa21 gene expression was globally upregulated 1.5 fold in trisomic samples. However, not all genes were equally dysregulated and 25 genes were not upregulated at all. Genes located on other chromosomes were also significantly dysregulated. Functional class scoring and gene set enrichment analyses of 473 genes, differentially expressed between trisomic and non-trisomic hearts, revealed downregulation of genes encoding mitochondrial enzymes and upregulation of genes encoding extracellular matrix proteins. There were no significant differences between trisomic fetuses with and without heart defects.</p> <p>Conclusion</p> <p>We conclude that dosage-dependent upregulation of Hsa21 genes causes dysregulation of the genes responsible for mitochondrial function and for the extracellular matrix organization in the fetal heart of trisomic subjects. These alterations might be harbingers of the heart defects associated with Hsa21 trisomy, which could be based on elusive mechanisms involving genetic variability, environmental factors and/or stochastic events.</p

INTRAPERSONAL AND SOCIAL FACTORS FOR PROBLEMATIC INTERNET USE AMONG STUDENTS DURING THE COVID-19 PANDEMIC

Background: During the lockdown due to COVID-19, Internet use may become more frequent in students, with possible negative consequences on mental health. In this emergency situation, variables such as depression, anxiety and external locus of control could be related to a Problematic Internet Use; on the other hand, self-esteem, internal locus of control, self-efficacy, and social support can play the role of protective factors for Problematic Internet Use. The present survey aims to verify the impact of these intrapersonal and social factors on Problematic Internet Use in college and High School students during the COVID-19 pandemic through a web-based cross-sectional study. Subjects and methods: 191 students from Lombardy, one of the Italian Regions among the most affected by the COVID-19 pandemic, were included in the study. An online questionnaire has been administered during the first Italian period of forced lockdown. A logistic regression analysis was performed to assess intrapersonal and social factors as predictors of Problematic Internet Use. Results: Analysis highlighted a higher risk of Problematic Internet Use (5.77 times more) in males compared to females. Individuals with high external locus of control and severe depression have respectively 6.56 and 2.84 times more the risk of presenting Problematic Internet Use. In contrast, social support, self-efficacy, and self-esteem were negatively related to Problematic Internet Use. In total sample, the percentage of Problematic Internet Use was high (55.5%). Conclusions: An increasing use of the Internet has been observed during lockdown, leading to a progressive increase in the diffusion of Problematic Internet Use. Gender, depression and external locus of control emerge as risk factors for Problematic Internet Use, while social support, self-efficacy and self-esteem represent protective factors. The current research identifies some intrapersonal and social factors in an epidemic context for which the development of effective behavioural, supportive and/or educational interventions would be appropriate

INTRAPERSONAL AND SOCIAL FACTORS FOR PROBLEMATIC INTERNET USE AMONG STUDENTS DURING THE COVID-19 PANDEMIC

Background: During the lockdown due to COVID-19, Internet use may become more frequent in students, with possible negative consequences on mental health. In this emergency situation, variables such as depression, anxiety and external locus of control could be related to a Problematic Internet Use; on the other hand, self-esteem, internal locus of control, self-efficacy, and social support can play the role of protective factors for Problematic Internet Use. The present survey aims to verify the impact of these intrapersonal and social factors on Problematic Internet Use in college and High School students during the COVID-19 pandemic through a web-based cross-sectional study. Subjects and methods: 191 students from Lombardy, one of the Italian Regions among the most affected by the COVID-19 pandemic, were included in the study. An online questionnaire has been administered during the first Italian period of forced lockdown. A logistic regression analysis was performed to assess intrapersonal and social factors as predictors of Problematic Internet Use. Results: Analysis highlighted a higher risk of Problematic Internet Use (5.77 times more) in males compared to females. Individuals with high external locus of control and severe depression have respectively 6.56 and 2.84 times more the risk of presenting Problematic Internet Use. In contrast, social support, self-efficacy, and self-esteem were negatively related to Problematic Internet Use. In total sample, the percentage of Problematic Internet Use was high (55.5%). Conclusions: An increasing use of the Internet has been observed during lockdown, leading to a progressive increase in the diffusion of Problematic Internet Use. Gender, depression and external locus of control emerge as risk factors for Problematic Internet Use, while social support, self-efficacy and self-esteem represent protective factors. The current research identifies some intrapersonal and social factors in an epidemic context for which the development of effective behavioural, supportive and/or educational interventions would be appropriate

Orthodontics Surgical Assistance (Piezosurgery®): Experimental Evidence According to Clinical Results

Orthodontic tooth movement (OTM) is based on intermitted or continuous forces applied to teeth, changing the mechanical loading of the system and arousing a cellular response that leads to bone adaptation. The traditional orthodontic movement causes a remodeling of the alveolar bone and changes in the periodontal structures that lead to tooth movement. The use of a piezoelectric instrument in orthodontic surgery has already shown great advantages. The purpose of this study is to rank the behavior of inflammatory mediators in accelerating orthodontic tooth movement. Ten patients with malocclusion underwent orthodontic surgical treatment, which included a first stage of surgically guided orthodontic movement (monocortical tooth dislocation and ligament distraction, MTDLD) to accelerate orthodontic movements. In all cases, corticotomy was performed by Piezosurgery. Bone and dental biopsy was executed to evaluate changes in the cytokines IL-1beta, TNF-alpha and IL-2 in different time intervals (1, 2, 7, 14 and 28 days). The molecular mediators are IL-1 beta, TNF-alpha and IL-2. Immediately after the surgical procedure there was a mild expression of the three molecular markers, while the assertion of IL-1 beta and TNF-alpha reached the maximum value after 24 h and 48 h, indicating a strong activation of the treated tissues. The Piezosurgery® surgical technique induces an evident stress in short times, within 24–48 h from the treatment, but it decreases significantly during the follow-up. © 2022 by the authors. Licensee MDPI, Basel, Switzerland