On operators which are adjoint to each other

Given two linear operators $S$ and $T$ acting between Hilbert spaces $\mathscr{H}$ and $\mathscr{K}$, respectively $\mathscr{K}$ and $\mathscr{H}$ which satisfy the relation \begin{equation*} \langle Sh, k\rangle=\langle h, Tk\rangle, \quad h\in\dom S, \ k\in\dom T, \end{equation*} i.e., according to the classical terminology of M.H. Stone, which are adjoint to each other, we provide necessary and sufficient conditions in order to ensure the equality between the closure of $S$ and the adjoint of $T.$ A central role in our approach is played by the range of the operator matrix M_{S, T}=\begin{pmatrix} 1_{\dom S} & -T S & 1_{\dom T} \end{pmatrix}. We obtain, as consequences, several results characterizing skewadjointness, selfadjointness and essential selfadjointness. We improve, in particular, the celebrated selfadjointness criterion of J. von Neumann

Ranking Projects in Multi-Criteria Environment

In the construction industry, the way the company manages its projects is a fundamental issue. IT tools supporting project portfolio management have become widely available and widely used, however, some of their processes still significantly need to be refined and made more accurate. Choosing the right project is a vital element of their way to success or failure. This also means that when a building project becomes value-destroying, it has to be suspended, or even stopped. Making such decisions is vitally important for the company. The paper presents an integrated project prioritization model, which includes both financial and non-financial criteria. The conceptual idea is to integrate the financial element with the most widely used non-financial points of view that are already applied, tested and published in the relevant literature separately. The authors go over the steps of PPM one by one and in addition to the ranking of the outlined projects, also briefly summarize the basics of monitoring

Raman Spectral Signatures of Serum-Derived Extracellular Vesicle-Enriched Isolates May Support the Diagnosis of CNS Tumors

Investigating the molecular composition of small extracellular vesicles (sEVs) for tumor diagnostic purposes is becoming increasingly popular, especially for diseases for which diagnosis is challenging, such as central nervous system (CNS) malignancies. Thorough examination of the molecular content of sEVs by Raman spectroscopy is a promising but hitherto barely explored approach for these tumor types. We attempt to reveal the potential role of serum-derived sEVs in diagnosing CNS tumors through Raman spectroscopic analyses using a relevant number of clinical samples. A total of 138 serum samples were obtained from four patient groups (glioblastoma multiforme, non-small-cell lung cancer brain metastasis, meningioma and lumbar disc herniation as control). After isolation, characterization and Raman spectroscopic assessment of sEVs, the Principal Component Analysis–Support Vector Machine (PCA–SVM) algorithm was performed on the Raman spectra for pairwise classifications. Classification accuracy (CA), sensitivity, specificity and the Area Under the Curve (AUC) value derived from Receiver Operating Characteristic (ROC) analyses were used to evaluate the performance of classification. The groups compared were distinguishable with 82.9–92.5% CA, 80–95% sensitivity and 80–90% specificity. AUC scores in the range of 0.82–0.9 suggest excellent and outstanding classification performance. Our results support that Raman spectroscopic analysis of sEV-enriched isolates from serum is a promising method that could be further developed in order to be applicable in the diagnosis of CNS tumors

Time-varying Risks of Construction Projects

AbstractAlthough risk management has become an integral part of project management generally insomuch that its application is required even by standards, it is usually left to project managers to define the required processes in detail and only little relevant methodological literature is available to provide further theoretical content. Known practices can still be developed in many parts, since in current approaches it is especially difficult to reflect on e.g. a phenomenon that individual risks typically decline and then disappear as construction progresses.This article focuses on declining and disappearing risk changing with time, based on value-based risk monitoring. For providing the mathematical background of time-varying risks, it is important to detect and monitor risks related to the added value of the project. Consequently, if necessary, it is possible to start action plans to avoid losses. In a construction project, in order to maintain a value-based risk management process, a continuous valuation method is necessary which is able to capture the value of the building in its current state.Our aim is twofold: to develop an evaluation method, which is able to determine the current market value of a project in the construction phase, and to provide a risk monitoring tool, which reflects the phenomenon of time-varying risks

Advanced Techniques for Monitoring and Management of Urban Water Infrastructures—An Overview

Water supply systems are essential for a modern society. This article presents an overview of the latest research related to information and communication technology systems for water resource monitoring, control and management. The main objective of our review is to show how emerging technologies offer support for smart administration of water infrastructures. The paper covers research results related to smart cities, smart water monitoring, big data, data analysis and decision support. Our evaluation reveals that there are many possible solutions generated through combinations of advanced methods. Emerging technologies open new possibilities for including new functionalities such as social involvement in water resource management. This review offers support for researchers in the area of water monitoring and management to identify useful models and technologies for designing better solutions