What determines the Czech land market prices? Some regional findings

The paper deals with the analysis of market land prices that were collected from land purchased contracts in the Czech Republic. Regression model was used to identify determinants explaining variability of market prices between 2008 and 2009. It was found out that type of plantation, region, type of buyers, plot size, distance to regional city or number of parcels play significant role. These factors explain more than a half of variance in land price. Quality of land that was expressed through administrative price has significant effect on market price. Yet, such effect became less import in regions nearby cities (e.g. Prague and Olomouc), where the market land price is significantly influenced by the distance to the district city. Land reform, however has not been confirmed to stimulate higher prices for sellers. It is reasonable to expect that part of the remaining variation could still be accounted for by non-random variables.Land, market price, administrative price, regression model, region., Land Economics/Use, GA, IN,

Template-based verification of heap-manipulating programs

We propose a shape analysis suitable for analysis engines that perform automatic invariant inference using an SMT solver. The proposed solution includes an abstract template domain that encodes the shape of a program heap based on logical formulae over bit-vectors. It is based on a points-to relation between pointers and symbolic addresses of abstract memory objects. Our abstract heap domain can be combined with value domains in a straight-forward manner, which particularly allows us to reason about shapes and contents of heap structures at the same time. The information obtained from the analysis can be used to prove reachability and memory safety properties of programs manipulating dynamic data structures, mainly linked lists. The solution has been implemented in 2LS and compared against state-of-the-art tools that perform the best in heap-related categories of the well-known Software Verification Competition (SV-COMP). Results show that 2LS outperforms these tools on benchmarks requiring combined reasoning about unbounded data structures and their numerical contents

Automatic C Compiler Generation from Architecture Description Language ISAC

This paper deals with retargetable compiler generation. After an introduction to application-specific instruction set processor design and a review of code generation in compiler backends, ISAC architecture description language is introduced. Automatic approach to instruction semantics extraction from ISAC models which result is usable for backend generation is presented. This approach was successfully tested on three models of MIPS, ARM and TI MSP430 architectures. Further backend generation process that uses extracted instruction is semantics presented. This process was currently tested on the MIPS architecture and some preliminary results are shown

Instructor Selector Generation from Architecture Description

We describe an automated way to generate data for a practical LLVM instruction selector based on machine-generated description of the target architecture at register transfer level. The generated instruction selector can handle arbitrarily complex machine instructions with no internal control flow, and can automatically find and take advantage of arithmetic properties of an instructions, specialized pseudo-registers and special cases of immediate operands

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2–4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2,3,4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease

Comparison of Categorical Foundations of Object-Oriented Database Model

. The present development in the database area is highly influenced by the object-oriented principles of data modeling. On the contrary to the previously successful relational approach, it lacks rigorous theoretical support. This problem is mainly due to the fact that the semantics description of such features as generalization, specialization, encapsulation, and inheritance is not trivial by using just the means of the set theory. Therefore, many researchers focused on finding suitable theoretical means for the modeling of complex objects. This paper is concerned with the comparison of categorical modeling in the database area and proposes a limit data model that enables to represent the objects, relationships, multiple inheritance, class polymorphism and virtual methods in the categorical setting. The aim to formalize these notions arose from the actual need. We would like to use it to support the development of an object-oriented database model closely following the standard ODMG'93..

The assessment of the effects of investment support measures of the Rural Development Programmes: the case of the Czech Republic

The investment support has been considered as a principal vehicle for enhancing competitiveness of the Czech agriculture since the early days of the economic transition. However so far, little attention has been paid to the evaluation of actual effects of the corresponding support programmes. The objective of this paper is to assess economic and other effects of the measure 121 “Modernisation of Agricultural Holdings” of the RDP 2007-2013 on the Czech farms. The counterfactual approach is adopted investigating what would have happened if the supported producers did not participate in the programme and then comparing the result indicators. The quantitative analysis of programme effects is complemented by a qualitative survey on 20 farms which received the investment support between 2008 and 2010. The quantitative assessment showed significant benefits of the investment support in terms of business expansion (GVA) and productivity (GVA/labour costs) improvements. These results were confirmed by the qualitative survey. It showed that production expansion and productivity increase were primary objectives of the investment strategies on most of the farms. The public support enabled farms to achieve these strategic objectives. The respondents of the survey declared that the supported investment was important for their prosperity however, we could not prove it in the quantitative assessment in terms of profit and cost/revenue ratio. Finally, the issue of deadweight of the investment support is discussed: the figures on very low net investment relatively to the provided public support at the sector level and answers of respondents indicate possible significant deadweight, however, the insight is incomplete, since it does not take into account post accession restructuring of the sector and multiannual and multi-enterprise character of investment at the farm level