Comparing Rough Set Theory with Multiple Regression Analysis as Automated Valuation Methodologies

This paper focuses on the problem of applying rough set theory to mass appraisal. This methodology was first introduced by a Polish mathematician, and has been applied recently as an automated valuation methodology by the author. The method allows the appraiser to estimate a property without defining econometric modeling, although it does not give any quantitative estimation of marginal prices. In a previous paper by the author, data were organized into classes prior to the valuation process, allowing for the if-then, or right “rule” for each property class to be defined. In that work, the relationship between property and class of valued was said to be dichotomic.mass appraisal; property valuation; rough set theory; valued tolerance relation

Income approach and property market cycle

This paper is focused on a proposed valuation method including real estate market cycle analysis in real estate valuation process. Starting from early works on this field (d'Amato 2003) the work highlight the dangerous gap between academic research on property market cycles and professional practice of property valuation. The danger of this gap comes from the fact that in spite it is well documented that the property market has a “natural” cyclical behaviour, the opinions of value based on income approaches still relies on assumption of a stable or perpetually growing (or decreasing) income. This may be one generating factors of the real estate bubble and the subsequent financial markets crisis experienced recently. This paper offers a general introduction on cyclical capitalization as a further family of valuation methodologies based on income approach. This method includes in the traditional Dividend Discount Model more than one g-factor in order to plot property market cycle. An empirical application of Cyclical Capitalization is offered to the office market of the Eastern London

La formazione di Giovanni Battista Antonelli: note storiche e contesto sociale prima del suo arrivo in Spagna

[EN] Giovanni Battista Antonelli before his arrival in Spain in 1559, being in his thirties, had spent the first part of his life in his native country, Italy. The present research concentrates on this territory and those years: a context of wars, captains, architects, theorists and treatises, many known and less known personalities who influenced Antonelli military engineering education. More detailed information appear in Italian archives about Giovan Francesco Guidi di Bagno and Antonelli: the first, Count of Montebello, was an important mercenary captain for the more powerful personalities, while the second was, at that time, at his service. Fiduciary and family relationships interlinked around the Count Guidi and others eminent personalities such as Giovanni Battista Belluzzi called “Sanmarino”, Cosimo I Medici up to Juan Manrique de Lara and Vespasiano Gonzaga Colonna, to mention the main ones. This investigation tries to shed light on the first part of Antonelli learning, as he took part to the War between Florence and Siena and in the Naples Kingdom. He subsequently left for Flanders with the Spanish army and reaching eventually Spain. During Felipe II Reign, after having written the Epitomi, he started the well known career of Antonelli family as military engineers. It was especially Battista, the younger brother, one of the main representatives in the history of military engineering, especially between the 16th and 17th centuries.Useli, G.; D’amato, M. (2015). La formazione di Giovanni Battista Antonelli: note storiche e contesto sociale prima del suo arrivo in Spagna. En Defensive architecture of the mediterranean: XV to XVIII centuries. Vol. I. Editorial Universitat Politècnica de València. 183-190. https://doi.org/10.4995/FORTMED2015.2015.1692OCS18319

Mass Appraisal Modelling in Minsk: Testing different Models Location sensitive

Mass Appraisal is the valuation of large quantity of properties. This automatic valuation procedure gave the opportunity to reach a single point estimate (The Appraisal of Real Estate, 13th Edition). The work test different location sensitive methodologies on a sample of 600 residential properties in the city of Minsk in Belarus. This is the first application of mass appraisal modelling in Belarus. Empirical application compares a location blind model with two Location Value Response Surface models (O Connor, 1982), the former based on the detection of value influence centers the latter based on error surface modelling

Diabetes mellitus and ischemic heart disease. the role of ion channels

Diabetes mellitus is one the strongest risk factors for cardiovascular disease and, in particular, for ischemic heart disease (IHD). The pathophysiology of myocardial ischemia in diabetic patients is complex and not fully understood: some diabetic patients have mainly coronary stenosis obstructing blood flow to the myocardium; others present with coronary microvascular disease with an absence of plaques in the epicardial vessels. Ion channels acting in the cross-talk between the myocardial energy state and coronary blood flow may play a role in the pathophysiology of IHD in diabetic patients. In particular, some genetic variants for ATP-dependent potassium channels seem to be involved in the determinism of IH

Behavioral, neuromorphological, and neurobiochemical effects induced by omega-3 fatty acids following basal forebrain cholinergic depletion in aged mice

Background: In recent years, mechanistic, epidemiologic, and interventional studies have indicated beneficial effects of omega-3 polyunsaturated fatty acids (n-3 PUFA) against brain aging and age-related cognitive decline, with the most consistent effects against Alzheimer’s disease (AD) confined especially in the early or prodromal stages of the pathology. In the present study, we investigated the action of n-3 PUFA supplementation on behavioral performances and hippocampal neurogenesis, volume, and astrogliosis in aged mice subjected to a selective depletion of basal forebrain cholinergic neurons. Such a lesion represents a valuable model to mimic one of the most reliable hallmarks of early AD neuropathology. Methods: Aged mice first underwent mu-p75-saporin immunotoxin intraventricular lesions to obtain a massive cholinergic depletion and then were orally supplemented with n-3 PUFA or olive oil (as isocaloric control) for 8 weeks. Four weeks after the beginning of the dietary supplementation, anxiety levels as well as mnesic, social, and depressive-like behaviors were evaluated. Subsequently, hippocampal morphological and biochemical analyses and n-3 PUFA brain quantification were carried out. Results: The n-3 PUFA treatment regulated the anxiety alterations and reverted the novelty recognition memory impairment induced by the cholinergic depletion in aged mice. Moreover, n-3 PUFA preserved hippocampal volume, enhanced neurogenesis in the dentate gyrus, and reduced astrogliosis in the hippocampus. Brain levels of n-3 PUFA were positively related to mnesic abilities. Conclusions: The demonstration that n-3 PUFA are able to counteract behavioral deficits and hippocampal neurodegeneration in cholinergically depleted aged mice promotes their use as a low-cost, safe nutraceutical tool to improve life quality at old age, even in the presence of first stages of AD

A location value response surface model for mass appraising: An “iterative” location adjustment factor in Bari, Italy

The work is focused on a new model of mass appraising including location variable. A location adjustment factor derived from a mathematical iteration was compared to the location adjustment factor based on geostatistical techniques. The work compares three different linear MRA models. The first one uses the location blind linear MRA. The second integrates the linear MRA with a location adjustment factor calculated using spatial interpolation. The second alternative is an application of Location Value Response Surface Models (O'Connor, 1982). It represents the first application of these models for mass appraising in Italy. The third approach introduces the Iterative Location Adjustment Factor. This is a factor which measure the influence of location derived from a mathematical iteration. Empirical results seem to prove the validity of Iterative Location Adjustment Factors in specific context with few observations. Santruka Darbe nagrinejamas naujas masinio turto vertinimo modelis, apimantis geografines padeties kintamaji. Iteraciniu būdu apskaičiuotas geografines padeties korekcijos veiksnys palygintas su geografines padeties korekcijos veiksniu, gautu taikant geostatistinius metodus. darbe lyginami trys skirtingi tiesiniai mrA modeliai. Pirmajame naudojamas geografines padeties nevertinantis tiesinis MRA. Antrajame tiesinis MRA sujungiamas su geografines padeties korekcijos veiksniu, apskaičiuotu pasitelkus erdvine interpoliacija. Antrojoje alternatyvoje pritaikomi geografines padeties vertes stebimojo paviršiaus (angl. Location Value Response Surface) modeliai (O'Connor 1982). Italijoje šie modeliai masiniam turto vertinimui naudojami pirma karta. Trečiojoje alternatyvoje taikomas iteracinis geografines padeties korekcijos veiksnys. Jis ivertina geografines padeties itaka, nustatyta iteraciniu būdu. Empiriniai rezultatai, regis, irodo iteraciniu geografines padeties korekcijos veiksniu pagristuma konkrečiame kontekste, kai stebejimu yra mažai. First Published Online: 09 Jun 201

Detailed stratified GWAS analysis for severe COVID-19 in four European populations

Given the highly variable clinical phenotype of Coronavirus disease 2019 (COVID-19), a deeper analysis of the host genetic contribution to severe COVID-19 is important to improve our understanding of underlying disease mechanisms. Here, we describe an extended genome-wide association meta-analysis of a well-characterized cohort of 3255 COVID-19 patients with respiratory failure and 12 488 population controls from Italy, Spain, Norway and Germany/Austria, including stratified analyses based on age, sex and disease severity, as well as targeted analyses of chromosome Y haplotypes, the human leukocyte antigen region and the SARS-CoV-2 peptidome. By inversion imputation, we traced a reported association at 17q21.31 to a ~0.9-Mb inversion polymorphism that creates two highly differentiated haplotypes and characterized the potential effects of the inversion in detail. Our data, together with the 5th release of summary statistics from the COVID-19 Host Genetics Initiative including non-Caucasian individuals, also identified a new locus at 19q13.33, including NAPSA, a gene which is expressed primarily in alveolar cells responsible for gas exchange in the lung.S.E.H. and C.A.S. partially supported genotyping through a philanthropic donation. A.F. and D.E. were supported by a grant from the German Federal Ministry of Education and COVID-19 grant Research (BMBF; ID:01KI20197); A.F., D.E. and F.D. were supported by the Deutsche Forschungsgemeinschaft Cluster of Excellence ‘Precision Medicine in Chronic Inflammation’ (EXC2167). D.E. was supported by the German Federal Ministry of Education and Research (BMBF) within the framework of the Computational Life Sciences funding concept (CompLS grant 031L0165). D.E., K.B. and S.B. acknowledge the Novo Nordisk Foundation (NNF14CC0001 and NNF17OC0027594). T.L.L., A.T. and O.Ö. were funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation), project numbers 279645989; 433116033; 437857095. M.W. and H.E. are supported by the German Research Foundation (DFG) through the Research Training Group 1743, ‘Genes, Environment and Inflammation’. L.V. received funding from: Ricerca Finalizzata Ministero della Salute (RF-2016-02364358), Italian Ministry of Health ‘CV PREVITAL’—strategie di prevenzione primaria cardiovascolare primaria nella popolazione italiana; The European Union (EU) Programme Horizon 2020 (under grant agreement No. 777377) for the project LITMUS- and for the project ‘REVEAL’; Fondazione IRCCS Ca’ Granda ‘Ricerca corrente’, Fondazione Sviluppo Ca’ Granda ‘Liver-BIBLE’ (PR-0391), Fondazione IRCCS Ca’ Granda ‘5permille’ ‘COVID-19 Biobank’ (RC100017A). A.B. was supported by a grant from Fondazione Cariplo to Fondazione Tettamanti: ‘Bio-banking of Covid-19 patient samples to support national and international research (Covid-Bank). This research was partly funded by an MIUR grant to the Department of Medical Sciences, under the program ‘Dipartimenti di Eccellenza 2018–2022’. This study makes use of data generated by the GCAT-Genomes for Life. Cohort study of the Genomes of Catalonia, Fundació IGTP (The Institute for Health Science Research Germans Trias i Pujol) IGTP is part of the CERCA Program/Generalitat de Catalunya. GCAT is supported by Acción de Dinamización del ISCIII-MINECO and the Ministry of Health of the Generalitat of Catalunya (ADE 10/00026); the Agència de Gestió d’Ajuts Universitaris i de Recerca (AGAUR) (2017-SGR 529). M.M. received research funding from grant PI19/00335 Acción Estratégica en Salud, integrated in the Spanish National RDI Plan and financed by ISCIII-Subdirección General de Evaluación and the Fondo Europeo de Desarrollo Regional (European Regional Development Fund (FEDER)-Una manera de hacer Europa’). B.C. is supported by national grants PI18/01512. X.F. is supported by the VEIS project (001-P-001647) (co-funded by the European Regional Development Fund (ERDF), ‘A way to build Europe’). Additional data included in this study were obtained in part by the COVICAT Study Group (Cohort Covid de Catalunya) supported by IsGlobal and IGTP, European Institute of Innovation & Technology (EIT), a body of the European Union, COVID-19 Rapid Response activity 73A and SR20-01024 La Caixa Foundation. A.J. and S.M. were supported by the Spanish Ministry of Economy and Competitiveness (grant numbers: PSE-010000-2006-6 and IPT-010000-2010-36). A.J. was also supported by national grant PI17/00019 from the Acción Estratégica en Salud (ISCIII) and the European Regional Development Fund (FEDER). The Basque Biobank, a hospital-related platform that also involves all Osakidetza health centres, the Basque government’s Department of Health and Onkologikoa, is operated by the Basque Foundation for Health Innovation and Research-BIOEF. M.C. received Grants BFU2016-77244-R and PID2019-107836RB-I00 funded by the Agencia Estatal de Investigación (AEI, Spain) and the European Regional Development Fund (FEDER, EU). M.R.G., J.A.H., R.G.D. and D.M.M. are supported by the ‘Spanish Ministry of Economy, Innovation and Competition, the Instituto de Salud Carlos III’ (PI19/01404, PI16/01842, PI19/00589, PI17/00535 and GLD19/00100) and by the Andalussian government (Proyectos Estratégicos-Fondos Feder PE-0451-2018, COVID-Premed, COVID GWAs). The position held by Itziar de Rojas Salarich is funded by grant FI20/00215, PFIS Contratos Predoctorales de Formación en Investigación en Salud. Enrique Calderón’s team is supported by CIBER of Epidemiology and Public Health (CIBERESP), ‘Instituto de Salud Carlos III’. J.C.H. reports grants from Research Council of Norway grant no 312780 during the conduct of the study. E.S. reports grants from Research Council of Norway grant no. 312769. The BioMaterialBank Nord is supported by the German Center for Lung Research (DZL), Airway Research Center North (ARCN). The BioMaterialBank Nord is member of popgen 2.0 network (P2N). P.K. Bergisch Gladbach, Germany and the Cologne Excellence Cluster on Cellular Stress Responses in Aging-Associated Diseases, University of Cologne, Cologne, Germany. He is supported by the German Federal Ministry of Education and Research (BMBF). O.A.C. is supported by the German Federal Ministry of Research and Education and is funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany’s Excellence Strategy—CECAD, EXC 2030–390661388. The COMRI cohort is funded by Technical University of Munich, Munich, Germany. This work was supported by grants of the Rolf M. Schwiete Stiftung, the Saarland University, BMBF and The States of Saarland and Lower Saxony. K.U.L. is supported by the German Research Foundation (DFG, LU-1944/3-1). Genotyping for the BoSCO study is funded by the Institute of Human Genetics, University Hospital Bonn. F.H. was supported by the Bavarian State Ministry for Science and Arts. Part of the genotyping was supported by a grant to A.R. from the German Federal Ministry of Education and Research (BMBF, grant: 01ED1619A, European Alzheimer DNA BioBank, EADB) within the context of the EU Joint Programme—Neurodegenerative Disease Research (JPND). Additional funding was derived from the German Research Foundation (DFG) grant: RA 1971/6-1 to A.R. P.R. is supported by the DFG (CCGA Sequencing Centre and DFG ExC2167 PMI and by SH state funds for COVID19 research). F.T. is supported by the Clinician Scientist Program of the Deutsche Forschungsgemeinschaft Cluster of Excellence ‘Precision Medicine in Chronic Inflammation’ (EXC2167). C.L. and J.H. are supported by the German Center for Infection Research (DZIF). T.B., M.M.B., O.W. und A.H. are supported by the Stiftung Universitätsmedizin Essen. M.A.-H. was supported by Juan de la Cierva Incorporacion program, grant IJC2018-035131-I funded by MCIN/AEI/10.13039/501100011033. E.C.S. is supported by the Deutsche Forschungsgemeinschaft (DFG; SCHU 2419/2-1).Peer reviewe

Detailed stratified GWAS analysis for severe COVID-19 in four European populations

Given the highly variable clinical phenotype of Coronavirus disease 2019 (COVID-19), a deeper analysis of the host genetic contribution to severe COVID-19 is important to improve our understanding of underlying disease mechanisms. Here, we describe an extended GWAS meta-analysis of a well-characterized cohort of 3,260 COVID-19 patients with respiratory failure and 12,483 population controls from Italy, Spain, Norway and Germany/Austria, including stratified analyses based on age, sex and disease severity, as well as targeted analyses of chromosome Y haplotypes, the human leukocyte antigen (HLA) region and the SARS-CoV-2 peptidome. By inversion imputation, we traced a reported association at 17q21.31 to a highly pleiotropic ∼0.9-Mb inversion polymorphism and characterized the potential effects of the inversion in detail. Our data, together with the 5th release of summary statistics from the COVID-19 Host Genetics Initiative, also identified a new locus at 19q13.33, including NAPSA, a gene which is expressed primarily in alveolar cells responsible for gas exchange in the lung.Andre Franke and David Ellinghaus were supported by a grant from the German Federal Ministry of Education and Research (01KI20197), Andre Franke, David Ellinghaus and Frauke Degenhardt were supported by the Deutsche Forschungsgemeinschaft Cluster of Excellence “Precision Medicine in Chronic Inflammation” (EXC2167). David Ellinghaus was supported by the German Federal Ministry of Education and Research (BMBF) within the framework of the Computational Life Sciences funding concept (CompLS grant 031L0165). David Ellinghaus, Karina Banasik and Søren Brunak acknowledge the Novo Nordisk Foundation (grant NNF14CC0001 and NNF17OC0027594). Tobias L. Lenz, Ana Teles and Onur Özer were funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation), project numbers 279645989; 433116033; 437857095. Mareike Wendorff and Hesham ElAbd are supported by the German Research Foundation (DFG) through the Research Training Group 1743, "Genes, Environment and Inflammation". This project was supported by a Covid-19 grant from the German Federal Ministry of Education and Research (BMBF; ID: 01KI20197). Luca Valenti received funding from: Ricerca Finalizzata Ministero della Salute RF2016-02364358, Italian Ministry of Health ""CV PREVITAL – strategie di prevenzione primaria cardiovascolare primaria nella popolazione italiana; The European Union (EU) Programme Horizon 2020 (under grant agreement No. 777377) for the project LITMUS- and for the project ""REVEAL""; Fondazione IRCCS Ca' Granda ""Ricerca corrente"", Fondazione Sviluppo Ca' Granda ""Liver-BIBLE"" (PR-0391), Fondazione IRCCS Ca' Granda ""5permille"" ""COVID-19 Biobank"" (RC100017A). Andrea Biondi was supported by the grant from Fondazione Cariplo to Fondazione Tettamanti: "Biobanking of Covid-19 patient samples to support national and international research (Covid-Bank). This research was partly funded by a MIUR grant to the Department of Medical Sciences, under the program "Dipartimenti di Eccellenza 2018–2022". This study makes use of data generated by the GCAT-Genomes for Life. Cohort study of the Genomes of Catalonia, Fundació IGTP. IGTP is part of the CERCA Program / Generalitat de Catalunya. GCAT is supported by Acción de Dinamización del ISCIIIMINECO and the Ministry of Health of the Generalitat of Catalunya (ADE 10/00026); the Agència de Gestió d’Ajuts Universitaris i de Recerca (AGAUR) (2017-SGR 529). Marta Marquié received research funding from ant PI19/00335 Acción Estratégica en Salud, integrated in the Spanish National RDI Plan and financed by ISCIIISubdirección General de Evaluación and the Fondo Europeo de Desarrollo Regional (FEDER-Una manera de hacer Europa").Beatriz Cortes is supported by national grants PI18/01512. Xavier Farre is supported by VEIS project (001-P-001647) (cofunded by European Regional Development Fund (ERDF), “A way to build Europe”). Additional data included in this study was obtained in part by the COVICAT Study Group (Cohort Covid de Catalunya) supported by IsGlobal and IGTP, EIT COVID-19 Rapid Response activity 73A and SR20-01024 La Caixa Foundation. Antonio Julià and Sara Marsal were supported by the Spanish Ministry of Economy and Competitiveness (grant numbers: PSE-010000-2006-6 and IPT-010000-2010-36). Antonio Julià was also supported the by national grant PI17/00019 from the Acción Estratégica en Salud (ISCIII) and the FEDER. The Basque Biobank is a hospitalrelated platform that also involves all Osakidetza health centres, the Basque government's Department of Health and Onkologikoa, is operated by the Basque Foundation for Health Innovation and Research-BIOEF. Mario Cáceres received Grants BFU2016-77244-R and PID2019-107836RB-I00 funded by the Agencia Estatal de Investigación (AEI, Spain) and the European Regional Development Fund (FEDER, EU). Manuel Romero Gómez, Javier Ampuero Herrojo, Rocío Gallego Durán and Douglas Maya Miles are supported by the “Spanish Ministry of Economy, Innovation and Competition, the Instituto de Salud Carlos III” (PI19/01404, PI16/01842, PI19/00589, PI17/00535 and GLD19/00100), and by the Andalussian government (Proyectos Estratégicos-Fondos Feder PE-0451-2018, COVID-Premed, COVID GWAs). The position held by Itziar de Rojas Salarich is funded by grant FI20/00215, PFIS Contratos Predoctorales de Formación en Investigación en Salud. Enrique Calderón's team is supported by CIBER of Epidemiology and Public Health (CIBERESP), "Instituto de Salud Carlos III". Jan Cato Holter reports grants from Research Council of Norway grant no 312780 during the conduct of the study. Dr. Solligård: reports grants from Research Council of Norway grant no 312769. The BioMaterialBank Nord is supported by the German Center for Lung Research (DZL), Airway Research Center North (ARCN). The BioMaterialBank Nord is member of popgen 2.0 network (P2N). Philipp Koehler has received non-financial scientific grants from Miltenyi Biotec GmbH, Bergisch Gladbach, Germany, and the Cologne Excellence Cluster on Cellular Stress Responses in Aging-Associated Diseases, University of Cologne, Cologne, Germany. He is supported by the German Federal Ministry of Education and Research (BMBF).Oliver A. Cornely is supported by the German Federal Ministry of Research and Education and is funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany's Excellence Strategy – CECAD, EXC 2030 – 390661388. The COMRI cohort is funded by Technical University of Munich, Munich, Germany. Genotyping was performed by the Genotyping laboratory of Institute for Molecular Medicine Finland FIMM Technology Centre, University of Helsinki. This work was supported by grants of the Rolf M. Schwiete Stiftung, the Saarland University, BMBF and The States of Saarland and Lower Saxony. Kerstin U. Ludwig is supported by the German Research Foundation (DFG, LU-1944/3-1). Genotyping for the BoSCO study is funded by the Institute of Human Genetics, University Hospital Bonn. Frank Hanses was supported by the Bavarian State Ministry for Science and Arts. Part of the genotyping was supported by a grant to Alfredo Ramirez from the German Federal Ministry of Education and Research (BMBF, grant: 01ED1619A, European Alzheimer DNA BioBank, EADB) within the context of the EU Joint Programme – Neurodegenerative Disease Research (JPND). Additional funding was derived from the German Research Foundation (DFG) grant: RA 1971/6-1 to Alfredo Ramirez. Philip Rosenstiel is supported by the DFG (CCGA Sequencing Centre and DFG ExC2167 PMI and by SH state funds for COVID19 research). Florian Tran is supported by the Clinician Scientist Program of the Deutsche Forschungsgemeinschaft Cluster of Excellence “Precision Medicine in Chronic Inflammation” (EXC2167). Christoph Lange and Jan Heyckendorf are supported by the German Center for Infection Research (DZIF). Thorsen Brenner, Marc M Berger, Oliver Witzke und Anke Hinney are supported by the Stiftung Universitätsmedizin Essen. Marialbert Acosta-Herrera was supported by Juan de la Cierva Incorporacion program, grant IJC2018-035131-I funded by MCIN/AEI/10.13039/501100011033. Eva C Schulte is supported by the Deutsche Forschungsgemeinschaft (DFG; SCHU 2419/2-1).N

Regressed DCF, Real Estate Value, Discount Rate and Risk Premium Estimation. A case in Bucharest

Discounted Cash Flow Analysis is a method used for real estate valuation and valuation of worth. The application of DCF requires the selection of an appropriate discount rate. Discount rate estimation is based on the sum between a risk free and a risk premium. A different approach is the selection of an IRR of comparable projects. The work tests the regressed DCF as a model of valuation. The method is based on regressed DCF recently proposed (D’Amato and Kauko, 2011) relies on deriving risk premium in a specific urban context starting from a small sample of DCF used to appraise commercial property in the same urban context.  Therefore it will be used regressed DCF as discount rate and  risk premium estimation. The area interested by the empirical application is near Bucharest