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The Blue Hill Meteorological Observatory, located on the 635-foot summit of Great Blue Hill ten miles south of Boston, Massachusetts, has been the site of continuous monitoring of the local weather and climate since its founding in 1885. The meticulous, extensive, and high-quality climate record maintained at this location has included the measurement of wind among many other parameters since its earliest days, and this provides a unique opportunity to examine seasonal and annual wind speed trends at this site over more than 135 years. Although multiple wind sensors have been in use during this time and the height of the anemometers was raised in 1908, the wind records have been made as consistent as possible through careful analysis of these changes and the application of adjustments to ensure consistency. An analysis of wind data homogeneity is being performed to associate statistical change points in monthly mean wind speeds to the documented wind instrument metadata. The running 30-year mean wind speed at Blue Hill Observatory has decreased from 7.0 m s-1 in the middle 20th century to its present value of 5.7 m s-1 with an increase in the rate of the decline beginning around 1980, and these changes persist in all seasons. The annual wind speed time series shows a significant (p < 0.05) downward trend over the entire period of record from 1885-2021 (-0.103 m s-1 decade-1) that is steeper and is also significant for the sub-periods from 1961-2021 (-0.274 m s-1 decade-1) and 1979-2012 (-0.339 m s-1 decade-1; the lowest annual mean wind speed was recorded in 2021). In addition, daily wind data for the last 60-70 years have been digitized including wind speed, peak gust, fastest mile, and prevailing direction, and this detailed data provides further characterization of the wind changes in recent decades at this location. The declining wind speed trend at Blue Hill has significant implications for the efficiency of wind power generation in the area if it reflects a re

Breast cancer (BC) is the second cause of cancer-related deceases in the worldwide female population. Despite the successful treatment advances, 25% of BC develops resistance to current therapeutic regimens, thereby remaining a major hurdle for patient management. Current therapies, targeting the molecular events underpinning the adaptive resistance, still require effort to improve BC treatment. Using BC sphere cells (BCSphCs) as a model, here we showed that BC stem-like cells express high levels of Myc, which requires the presence of the multifunctional DNA/RNA binding protein Sam68 for the DNA-damage repair. Analysis of a cohort of BC patients displayed that Sam68 is an independent negative factor correlated with the progression of the disease. Genetic inhibition of Sam68 caused a defect in PARP-induced PAR chain synthesis upon DNA-damaging insults, resulting in cell death of TNBC cells. In contrast, BC stem-like cells were able to survive due to an upregulation of Rad51. Importantly, the inhibition of Rad51 showed synthetic lethal effect with the silencing of Sam68, hampering the cell viability of patient-derived BCSphCs and stabilizing the growth of tumor xenografts, including those TNBC carrying BRCA mutation. Moreover, the analysis of Myc, Sam68 and Rad51 expression demarcated a signature of a poor outcome in a large cohort of BC patients. Thus, our findings suggest the importance of targeting Sam68-PARP1 axis and Rad51 as potential therapeutic candidates to counteract the expansion of BC cells with an aggressive phenotype.

Despite advances in the curative approach, the survival rate of advanced colorectal cancer (CRC) patients is still poor, which is likely due to the emergence of cancer cell clones resistant to the available therapeutic options. We have already shown that CD44v6-positive CRC stem cells (CR-CSCs) are refractory toward standard anti-tumor therapeutic agents due to the activation of the PI3K pathway together with high HER2 expression levels. Tumor microenvironmental cytokines confer resistance to CR-CSCs against HER2/PI3K targeting by enhancing activation of the MAPK pathway. Here, we show that the CSC compartment, spared by BRAF inhibitor-based targeted therapy, is associated with increased expression levels of CD44v6 and Myc and retains boosted clonogenic activity along with residual tumorigenic potential. Inhibition of Myc transcription, downstream of the MAPK cascade components, and PI3K pathway activity was able to overcome the protective effects of microenvironmental cytokines, affecting the survival and the clonogenic activity of CR-CSCs, regardless of their mutational background. Likewise, the double targeting induced stabilization of mouse tumor avatars. Altogether, these data outline the rationale for dual kinase targeting of CR-CSCs to prevent their adaptive response, which would lead to disease progression.

Obesity is a strong risk factor for cancer progression, posing obesity-related cancer as one of the leading causes of death. Nevertheless, the molecular mechanisms that endow cancer cells with metastatic properties in patients affected by obesity remain unexplored. Here, we show that IL-6 and HGF, secreted by tumor neighboring visceral adipose stromal cells (V-ASCs), expand the metastatic colorectal (CR) cancer cell compartment (CD44v6 +), which in turn secretes neurotrophins such as NGF and NT-3, and recruits adipose stem cells within tumor mass. Visceral adipose-derived factors promote vasculogenesis and the onset of metastatic dissemination by activation of STAT3, which inhibits miR-200a and enhances ZEB2 expression, effectively reprogramming CRC cells into a highly metastatic phenotype. Notably, obesity-associated tumor microenvironment provokes a transition in the transcriptomic expression profile of cells derived from the epithelial consensus molecular subtype (CMS2) CRC patients towards a mesenchymal subtype (CMS4). STAT3 pathway inhibition reduces ZEB2 expression and abrogates the metastatic growth sustained by adipose-released proteins. Together, our data suggest that targeting adipose factors in colorectal cancer patients with obesity may represent a therapeutic strategy for preventing metastatic disease.

Colorectal cancer (CRC) mortality is mainly caused by patient refractoriness to common anti-cancer therapies and consequent metastasis formation. Besides, the notorious toxic side effects of chemotherapy are a concurrent obstacle to be tackled. Thus, new treatment approaches are needed to effectively improve patient outcomes. Compelling evidence demonstrated that cancer stem cells (CSCs) are responsible for treatment failure and relapse. New natural treatment approaches showed capabilities to selectively target the CSC subpopulation by rendering them targetable by standard cytotoxic compounds. Herein we show the anti-cancer properties of the polymethoxyflavones and prenylflavonoids extracted from Citrus sinensis and Humulus lupulus, respectively. The natural biofunctional fractions, singularly and in combination, reduced the cell viability of CRC stem cells (CR-CSCs) and synergized with 5-fluorouracil and oxaliplatin (FOX) chemotherapy. These phenomena were accompanied by a reduced S and G2/M phase of the cell cycle and upregulation of cell death-related genes. Notably, both phytoextracts in combination with FOX thwarted stemness features in CR-CSCs as demonstrated by the impaired clonogenic potential and decreased Wnt pathway activation. Extracts lowered the expression of CD44v6 and affected the expansion of metastatic CR-CSCs in patients refractory to chemotherapy. Together, this study highlights the importance of polymethoxyflavones and prenylflavonoids as natural remedies to aid oncological therapies.

Limited therapeutic options are available for advanced colorectal cancer (CRC). Herein, we report that exposure to a neo-synthetic bis(indolyl)thiazole alkaloid analog, nortopsentin 234 (NORA234), leads to an initial reduction of proliferative and clonogenic potential of CRC sphere cells (CR-CSphCs), followed by an adaptive response selecting the CR-CSphC-resistant compartment. Cells spared by the treatment with NORA234 express high levels of CD44v6, associated with a constitutive activation of Wnt pathway. In CR-CSphC-based organoids, NORA234 causes a genotoxic stress paralleled by G2-M cell cycle arrest and activation of CHK1, driving the DNA damage repair of CR-CSphCs, regardless of the mutational background, microsatellite stability, and consensus molecular subtype. Synergistic combination of NORA234 and CHK1 (rabusertib) targeting is synthetic lethal inducing death of both CD44v6-negative and CD44v6-positive CRC stem cell fractions, aside from Wnt pathway activity. These data could provide a rational basis to develop an effective strategy for the treatment of patients with CRC.

Different paradigms have been used to model the behaviour of pedestrians in a crowd. While some approaches analyze the modelization of crowd motion from a physical perspective, other techniques prefer to focus on similar abstractions following classic paradigms, such as mobile agents or cellular automata, or even from the point of view of social forces interaction. Particular interest has emerged around the topic of crowd behaviour under condition of stress caused by a dramatic event, such as an earthquake, a terrorist attack or a fire. This paper presents a novel approach including a GSPN to describe the behaviour of an individual, which is subsequently translated into a set of Markovian Agents. The model under study reproduces a scenario where a fire, developed in a closed environment, triggers erratic crowd behaviour. It is possible to perceive that a panic situation can be mitigated by enforcing certain measures involving human leaders or small embedded systems (such as Internet-of-things enabled devices), reducing the level of risk related to safety.

Cloud Computing has made possible flexible resources provisioning from an almost unlimited pool. This has created the opportunity to broaden the horizon of data that can be analyzed, allowing to support the so called Big Data Analytics applications. New programming paradigms, such as NoSQL queries and Map-Reduce applications, have emerged within frameworks such as Microsoft Azure, Hadoop and Apache Spark. In many cases, applications execute jobs that are split into stages, each one composed of tasks that can be run in parallel on many computational nodes. Directed acyclic graphs describe the precedence between stages, defining the execution rules and controlling the degree of parallelism. This work presents a Process Algebra dialect aimed at describing both jobs and execution environments. The proposed framework is then used to model and study standard parallel programming benchmarks, to demonstrate its applicability.

In this chapter, we report the organizational, technological, and individual information technology (IT) issues of Italian IT workers. The participants of our survey are mostly IT professionals, working full time in non-managerial positions. IT strategic planning, IT service management, knowledge management, alignment between IT and business were among the most pressing organizational issues. Top technology concerns include enterprise application integration, business intelligence/analytics, collaborative and workflow tools, and networks/telecommunications. Italian IT employees seem to be satisfied with their work and perceived their workloads to be meaningful. They exhibited low levels of turnover intention and felt quite secure in their jobs.

The faithful reproduction and accurate prediction of the phe-notypes and emergent behaviors of complex cellular systems are among the most challenging goals in Systems Biology. Although mathematical models that describe the interactions among all biochemical processes in a cell are theoretically feasible, their simulation is generally hard because of a variety of reasons. For instance, many quantitative data (e.g., kinetic rates) are usually not available, a problem that hinders the execution of simulation algorithms as long as some parameter estimation methods are used. Though, even with a candidate parameterization, the simulation of mechanistic models could be challenging due to the extreme computational effort required. In this context, model reduction techniques and High-Performance Computing infrastructures could be leveraged to mitigate these issues. In addition, as cellular processes are characterized by multiple scales of temporal and spatial organization, novel hybrid simulators able to harmonize different modeling approaches (e.g., logic-based, constraint-based, continuous deterministic, discrete stochastic, spatial) should be designed. This chapter describes a putative unified approach to tackle these challenging tasks, hopefully paving the way to the definition of large-scale comprehensive models that aim at the comprehension of the cell behavior by means of computational tools.

As many real world systems evolve according to phenomena characterized by a continuous time dependency, literature studied several approaches to correctly capture all their aspects. Since their analysis is not trivial, different high level approaches have been proposed, such as classical pure mathematical analysis or tool-oriented frameworks like Fluid Stochastic Petri Nets. Each approach has its specific purposes and naturally addresses some application field. This paper instead focuses on the simulation of models written in a custom Hybrid Systems (HS) formalism. The key aspect of this work is focused on the use within a framework called SIMTHESys of a function describing how the fluid variables evolve, providing more efficient simulation with respect to traditional approaches.

Starting with the birth of Web 2.0, the quantity of data managed by large-scale web services has grown exponentially, posing new challenges and infrastructure requirements. This has led to new programming paradigms and architectural choices, such as map-reduce and NoSQL databases, which constitute two of the main peculiarities of the specialized massively distributed systems referred to as Big Data architectures. The underlying computer infrastructures usually face complexity requirements, resulting from the need for efficiency and speed in computing over huge evolving data sets. This is achieved by taking advantage from the features of new technologies, such as the automatic scaling and replica provisioning of Cloud environments. Although performances are a key issue for the considered applications, few performance evaluation results are currently available in this field. In this work we focus on investigating how a Big Data application designer can evaluate the performances of applications exploiting the Apache Hive query language for NoSQL databases, built over a Apache Hadoop map-reduce infrastructure. This paper presents a dedicated modeling language and an application, showing first how it is possible to ease the modeling process and second how the semantic gap between modeling logic and the domain can be reduced, by means of vertical multiformalism modeling. © 2014 Elsevier B.V. All rights reserved.

Outsourcing is a managerial procedure whose success needs clarification regarding the long-term relationship between customer and supplier. The authors’ aim is to examine simultaneously the client’s and supplier’s perspectives through the psychological contract that, by assimilating the contents of the legal contract, focuses on (1) the implicit (not formalized) and reciprocal (mutual) duties between the two parties, (2) the equivalence of psychological obligations and contractual values and (3) the importance of the individual commitment level. While the legal contract is managed and based on an organizational level, the psychological contract is individual and perceived as such: from the authors’ point of view, all workers, regardless of whether they work inside or outside the company, are part of the psychological contract. The authors employ a case study represented by an outsourcing centre belonging to a group of Italian banks, using the “qualitative and quantitative” mixed method. In the first phase, a series of interviews will help identify the key variables to develop a questionnaire for both customers and suppliers. The second phase will comprise the interviews and questionnaire formalization. The two themes, the psychological contract on the one hand and the outsourcing governance on the other hand, represent a highly relevant matter that has received scant attention in the literature.

Performance prediction for Big Data applications is a powerful tool supporting designers and administrators in achieving a better exploitation of their computing resources. Big Data architectures are complex, continuously evolving and adaptive, thus a rapid design and verification modeling approach can be fit to the needs. As a result, a minimal semantic gap between models and applications would enable a wider number of designers to directly benefit from the results. The paper presents a multiformalism modeling approach based on a one-to-one mapping of Apache Hive querying primitives to modeling primitives. This approach exploits a combination of proper Big Data specific submodels and Petri nets to enable modeling of conventional application logic.

A modal aerosol module (MAM) has been developed for the Community Atmosphere Model version 5 (CAM5), the atmospheric component of the Community Earth System Model version 1 (CESM1). MAM is capable of simulating the aerosol size distribution and both internal and external mixing between aerosol components, treating numerous complicated aerosol processes and aerosol physical, chemical and optical properties in a physically-based manner. Two MAM versions were developed: a more complete version with seven lognormal modes (MAM7), and a version with three lognormal modes (MAM3) for the purpose of long-term (decades to centuries) simulations. In this paper a description and evaluation of the aerosol module and its two representations are provided. Sensitivity of the aerosol lifecycle to simplifications in the representation of aerosol is discussed. Simulated sulfate and secondary organic aerosol (SOA) mass concentrations are remarkably similar between MAM3 and MAM7. Differences in primary organic matter (POM) and black carbon (BC) concentrations between MAM3 and MAM7 are also small (mostly within 10 %). The mineral dust global burden differs by 10 % and sea salt burden by 30-40 % between MAM3 and MAM7, mainly due to the different size ranges for dust and sea salt modes and different standard deviations of the log-normal size distribution for sea salt modes between MAM3 and MAM7. The model is able to qualitatively capture the observed geographical and temporal variations of aerosol mass and number concentrations, size distributions, and aerosol optical properties. However, there are noticeable biases; e.g., simulated BC concentrations are significantly lower than measurements in the Arctic. There is a low bias in modeled aerosol optical depth on the global scale, especially in the developing countries. These biases in aerosol simulations clearly indicate the need for improvements of aerosol processes (e.g., emission fluxes of anthropogenic aerosols and precursor gases in de, AuthorCount:22

The study of software aging and rejuvenation is based on models that conjugate the complexity of architectural models with the problem of time dependence of parameters. Exploiting the metaphors of common performance-oriented modeling formalisms (such as Petri nets or queuing networks) with the support of proper solution techniques can help modelers in approaching the analysis of complex software-based systems. This paper shows how SIMTHESys (a multiformalism modeling framework) can be used to approach the modeling problem by implementing a new user-defined modeling formalisms and the related fluid-based solution engine. © 2012 IEEE.

SIMTHESys is a framework for the design of multiformalism performance evaluation models. The modeler can create new formalisms by specifying both the syntax and the dynamic behavior of their atomic elements. Even if other approaches address the same issue, the proposed methodology relies on fewer assumptions, opening new possibilities that allow to consider new types of composition and interaction between formalisms. In this direction, this paper shows how four formalisms belonging to three different classes can interact together in a single environment. The multiformalism proposed is composed of two standard performance evaluation formalisms, a reliability formalism and a verification formalism. The potential of this approach is demonstrated by analyzing a model of an e-government process. Copyright © 2011 ICST.

Exceptions constitute a widely accepted fault tolerance mechanism, suitable to manage both hardware and software faults. In performability analysis it is a common practice to exploit software tools capable of describing a system using models expressed in various formalisms. Often these tools provide extensibility features that allow augmenting the primitives of a given formalism, but in most cases they lack of exception support. This paper aims at filling this gap, by introducing a general mechanism to add support for exception handling to most of the existing formalisms. The validity of the proposed method is supported by two modelling cases that benefit in clarity and economy. © 2011 Springer-Verlag.

The use of multi-formalism techniques is very appealing in modeling complex systems since they allow for building of complex models by integrating or composing sub-models specified by different formalisms. Hence, the most suitable formalism may be used according to the evaluation goals, the level of abstraction of the sub-models and the nature of the sub-systems. Each formalism is usually coupled with efficient solution methods, thus multi-solution approaches are needed to solve multi-formalism models whose analysis involves different techniques and tools. In this paper the software architecture of the OsMoSys Multi-solution Framework (OMF) is presented. OMF was born to provide the support needed to allow for loosely coupled cooperation among heterogeneous analysis techniques and tools, and automates the tasks that must be performed to solve complex multi-formalism models. OMF does not require that heterogeneous models are translated into a common formalism in order to be solved, nor that the available tools are modified to be integrated in the framework, but it achieves multi-solution by orchestration. Copyright 2007 ICST.

The use of multi-formalism techniques is very appealing in modeling complex systems since they allow for building of complex models by integrating or composing sub-models specified by different formalisms. Hence, the most suitable formalism may be used according to the evaluation goals, the level of abstraction of the sub-models and the nature of the sub-systems. Each formalism is usually coupled with efficient solution methods, thus multi-solution approaches are needed to solve multi-formalism models whose analysis involves different techniques and tools. In this paper the software architecture of the OsMoSys Multi-solution Framework (OMF) is presented. OMF was born to provide the support needed to allow for loosely coupled cooperation among heterogeneous analysis techniques and tools, and automates the tasks that must be performed to solve complex multi-formalism models. OMF does not require that heterogeneous models are translated into a common formalism in order to be solved, nor that the available tools are modified to be integrated in the framework, but it achieves multi-solution by orchestration. Copyright 2007 ICST.