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Rīgas apgabaltiesā, Civilnodaļā apsardzības kārtībā iztiesājamās lietas
1933
Rīgas apgabaltiesā, III Civilnodaļā apsardzības kārtībā iztiesājamās lietas no Nr. 1.-181. ieskaitot, 1933. g. no 11. janvāra līdz 2. februārim un no 16.-17. februārim, I Civilnodaļā apsardzības kārtībā iztiesājamās lietas no Nr. 182.-184. ieskaitot, I Civilnodaļā prasības kārtībā iztiesājamās lietas no Nr. 185.-198.
Elektroniskie pierādīšanas līdzekļi.
2017
Elektroniskie pierādījumi ir salīdzinoši jauns pierādījuma veids, un to izmantošanu civilprocesā nosaka tiesa likuma noteiktajā kārtībā. 21. gadsimts ir tehnoloģiju laikmets, līdz ar tehnoloģiju attīstīšanos būtiski mainās arī elektronisko pierādījumu nozīme tiesu procesos. Pierādījumu avoti mainās un attīstās ik dienu. Elektroniskos pierādījumus civilprocess pieskaita pie rakstveida pierādīšana līdzekļiem, kuri ir vieni no svarīgākajiem pierādīšanas līdzekļu veidiem civilprocesā. Rakstveida pierādījumi ikdienā tiek pielietoti dažādās dzīves jomās t.sk. gan privātajā sfēra, gan biznesa sfērā. 21.gs. ietvaros rakstiskie dokumenti tiek nomainīti uz elektroniskajiem dokumentiem, kas dod iespēj…
Professional vision of Grade 1 teachers experiencing different levels of work-related stress
2022
This study explored teachers' professional vision by examining how teachers experiencing low, moderate and high work-related stress reason their eye-tracking recordings in terms of description, explanation and prediction. A qualitative analysis of retrospective think-aloud interviews with 24 Grade 1 teachers showed that teachers predominantly used description in their reasoning, while explanation and prediction were less frequent. The description mainly focused on teacher information/elaboration and classroom management/behaviour. Teachers with moderate stress utilised self-reflection most frequently, whereas teachers with high stress utilised it the least. The results suggest that the leve…
Decreased temperature increases the expression of a disordered bacterial late embryogenesis abundant (LEA) protein that enhances natural transformati…
2021
Late embryogenesis abundant (LEA) proteins are important players in the management of responses to stressful conditions, such as drought, high salinity, and changes in temperature. Many LEA proteins do not have defined three-dimensional structures, so they are intrinsically disordered proteins (IDPs) and are often highly hydrophilic. Although LEA-like sequences have been identified in bacterial genomes, the functions of bacterial LEA proteins have been studied only recently. Sequence analysis of outer membrane interleukin receptor I (BilRI) from the oral pathogen Aggregatibacter actinomycetemcomitans indicated that it shared sequence similarity with group 3/3b/4 LEA proteins. Comprehensive …
Adiabatic versus non-adiabatic electron transfer at 2D electrode materials
2021
2D electrode materials are often deployed on conductive supports for electrochemistry and there is a great need to understand fundamental electrochemical processes in this electrode configuration. Here, an integrated experimental-theoretical approach is used to resolve the key electronic interactions in outer-sphere electron transfer (OS-ET), a cornerstone elementary electrochemical reaction, at graphene as-grown on a copper electrode. Using scanning electrochemical cell microscopy, and co-located structural microscopy, the classical hexaamineruthenium (III/II) couple shows the ET kinetics trend: monolayer > bilayer > multilayer graphene. This trend is rationalized quantitatively through th…
A Survey on Particle Swarm Optimization for Association Rule Mining
2022
Association rule mining (ARM) is one of the core techniques of data mining to discover potentially valuable association relationships from mixed datasets. In the current research, various heuristic algorithms have been introduced into ARM to address the high computation time of traditional ARM. Although a more detailed review of the heuristic algorithms based on ARM is available, this paper differs from the existing reviews in that we expected it to provide a more comprehensive and multi-faceted survey of emerging research, which could provide a reference for researchers in the field to help them understand the state-of-the-art PSO-based ARM algorithms. In this paper, we review the existing…
Detection of developmental dyslexia with machine learning using eye movement data
2021
Dyslexia is a common neurocognitive learning disorder that can seriously hinder individuals’ aspirations if not detected and treated early. Instead of costly diagnostic assessment made by experts, in the near future dyslexia might be identified with ease by automated analysis of eye movements during reading provided by embedded eye tracking technology. However, the diagnostic machine learning methods need to be optimized first. Previous studies with machine learning have been quite successful in identifying dyslexic readers, however, using contrasting groups with large performance differences between diagnosed and good readers. A practical challenge is to identify also individuals with bord…
GROMEX: A Scalable and Versatile Fast Multipole Method for Biomolecular Simulation
2020
Atomistic simulations of large biomolecular systems with chemical variability such as constant pH dynamic protonation offer multiple challenges in high performance computing. One of them is the correct treatment of the involved electrostatics in an efficient and highly scalable way. Here we review and assess two of the main building blocks that will permit such simulations: (1) An electrostatics library based on the Fast Multipole Method (FMM) that treats local alternative charge distributions with minimal overhead, and (2) A $λ$-dynamics module working in tandem with the FMM that enables various types of chemical transitions during the simulation. Our $λ$-dynamics and FMM implementations d…
Computational Offloading in Mobile Edge with Comprehensive and Energy Efficient Cost Function: A Deep Learning Approach
2021
In mobile edge computing (MEC), partial computational offloading can be intelligently investigated to reduce the energy consumption and service delay of user equipment (UE) by dividing a single task into different components. Some of the components execute locally on the UE while the remaining are offloaded to a mobile edge server (MES). In this paper, we investigate the partial offloading technique in MEC using a supervised deep learning approach. The proposed technique, comprehensive and energy efficient deep learning-based offloading technique (CEDOT), intelligently selects the partial offloading policy and also the size of each component of a task to reduce the service delay and energy …
Introducing a sensemaking perspective to the service experience
2021
PurposeMost recent service experience research considers customers as sensemakers and sensemaking as a focal process in experience construction. Despite this, the sensemaking theory engendered in organization studies has not been applied in the quest for an in-depth understanding of the service experience. This study introduces a sensemaking perspective to the service experience and develops a conceptualization of how customers construct their experiences cognitively through sensemaking.Design/methodology/approachThe service experience literature is dominated by a focus on firms implementing service experiences for customers. This study, in contrast, investigates service experience and its …