Analysis of metagenomes in extreme environments

Samo je malen broj bakterija prisutnih u biosferi moguće uzgojiti u laboratorijskim uvjetima, i stoga sve veća količina znanja o raznolikosti genoma prokariota dolaze iz direktne analize DNA iz okoliša pomoću visokoprotočnih metoda skupnog naziva Metagenomika. Metagenomom se naziva skup svih gena nekog mikrobnog okoliša. Poznato je da prokariotski genomi pokazuju značajnu nejednakost u korištenju sinonimnih kodona (CUB) (prema eng. codon usage bias). CUB je izravno povezan s razinom ekspresije gena stoga što su kodoni koje koriste visokoeksprimirani geni komplementarni s najrasprostranjenijim tRNA u organizmu. Dakle, CUB gena se može povezati s razinom ekspresije gena kroz translacijsku optimizaciju. Analizom različitih metagenomskih uzoraka pokazali smo da je moguće primijetiti nejednako iskorištenje kodona unutar pojedinog mikrobnog okoliša, kao i da je takvo svojstvo moguće iskoristiti za predviđanje razine ekspresije gena na razini cjelokupnog mikrobnog ekosustava. Primjena ovog pristupa omogućuje istraživanje genske adaptacije mikrobnih organizama na okoliš.Not all prokaryotes are amenable to cultivation in laboratory conditions, and increasing amounts of knowledge about microbial diversity is gained from direct sampling of DNA from environments. A rapidly developing field that studies whole microbial communities is metagenomics, the culture‐independent genomic study of organisms extracted directly from an ecological niche. Prokaryotic genomes show strong codon usage bias (CUB). CUB is directly correlated with expression levels of genes because codons used by genes expressed at high levels are encoded for by the most abundant tRNAs. Therefore, the CUB of a gene can be linked to its expression level through translational optimization. We show that metagenomes, much like genomes, also show CUB and that this phenomenon can be used to predict the expression level of genes at the level of the entire microbial community. We analyzed adaptation of organisms in metagenomes to their extreme environments through this approach

PARAMETRIC DESIGN OF 3D PRINTED RIBBED SLAB SYSTEM BASED ON NATURE-INSPIRED PATTERNS

The interest in pattern geometry and its application to architecture may be seen throughout history. While some authors were fascinated by pattern aesthetics, others were focused on their effectiveness and underlying principles of pattern formation. In continuing with the work of the second group of authors, this paper reviews opportunities for efficient ways of implementing patterns in the design of architectural elements, supported by recent developments in parametric design and digital fabrication techniques. This paper aims to analyze pattern configurations found in nature in order to determine the underlying generation principles and the potential of their application for 3D printed slab systems. Using case study methodology, selected patterns will be applied in developing a generative parametric design system, which will further be tested in creating and (small-scale) fabricating ribbed slab elements. The result of the research is the generalization of a design approach based on principles of natural pattern formation to produce sustainable design solutions that rely on the transposition of the inherent efficiency of natural systems, such as low energy or material consumption

Analysis of metagenomes in extreme environments

Samo je malen broj bakterija prisutnih u biosferi moguće uzgojiti u laboratorijskim uvjetima, i stoga sve veća količina znanja o raznolikosti genoma prokariota dolaze iz direktne analize DNA iz okoliša pomoću visokoprotočnih metoda skupnog naziva Metagenomika. Metagenomom se naziva skup svih gena nekog mikrobnog okoliša. Poznato je da prokariotski genomi pokazuju značajnu nejednakost u korištenju sinonimnih kodona (CUB) (prema eng. codon usage bias). CUB je izravno povezan s razinom ekspresije gena stoga što su kodoni koje koriste visokoeksprimirani geni komplementarni s najrasprostranjenijim tRNA u organizmu. Dakle, CUB gena se može povezati s razinom ekspresije gena kroz translacijsku optimizaciju. Analizom različitih metagenomskih uzoraka pokazali smo da je moguće primijetiti nejednako iskorištenje kodona unutar pojedinog mikrobnog okoliša, kao i da je takvo svojstvo moguće iskoristiti za predviđanje razine ekspresije gena na razini cjelokupnog mikrobnog ekosustava. Primjena ovog pristupa omogućuje istraživanje genske adaptacije mikrobnih organizama na okoliš.Not all prokaryotes are amenable to cultivation in laboratory conditions, and increasing amounts of knowledge about microbial diversity is gained from direct sampling of DNA from environments. A rapidly developing field that studies whole microbial communities is metagenomics, the culture‐independent genomic study of organisms extracted directly from an ecological niche. Prokaryotic genomes show strong codon usage bias (CUB). CUB is directly correlated with expression levels of genes because codons used by genes expressed at high levels are encoded for by the most abundant tRNAs. Therefore, the CUB of a gene can be linked to its expression level through translational optimization. We show that metagenomes, much like genomes, also show CUB and that this phenomenon can be used to predict the expression level of genes at the level of the entire microbial community. We analyzed adaptation of organisms in metagenomes to their extreme environments through this approach

Analysis of metagenomes in extreme environments

Samo je malen broj bakterija prisutnih u biosferi moguće uzgojiti u laboratorijskim uvjetima, i stoga sve veća količina znanja o raznolikosti genoma prokariota dolaze iz direktne analize DNA iz okoliša pomoću visokoprotočnih metoda skupnog naziva Metagenomika. Metagenomom se naziva skup svih gena nekog mikrobnog okoliša. Poznato je da prokariotski genomi pokazuju značajnu nejednakost u korištenju sinonimnih kodona (CUB) (prema eng. codon usage bias). CUB je izravno povezan s razinom ekspresije gena stoga što su kodoni koje koriste visokoeksprimirani geni komplementarni s najrasprostranjenijim tRNA u organizmu. Dakle, CUB gena se može povezati s razinom ekspresije gena kroz translacijsku optimizaciju. Analizom različitih metagenomskih uzoraka pokazali smo da je moguće primijetiti nejednako iskorištenje kodona unutar pojedinog mikrobnog okoliša, kao i da je takvo svojstvo moguće iskoristiti za predviđanje razine ekspresije gena na razini cjelokupnog mikrobnog ekosustava. Primjena ovog pristupa omogućuje istraživanje genske adaptacije mikrobnih organizama na okoliš.Not all prokaryotes are amenable to cultivation in laboratory conditions, and increasing amounts of knowledge about microbial diversity is gained from direct sampling of DNA from environments. A rapidly developing field that studies whole microbial communities is metagenomics, the culture‐independent genomic study of organisms extracted directly from an ecological niche. Prokaryotic genomes show strong codon usage bias (CUB). CUB is directly correlated with expression levels of genes because codons used by genes expressed at high levels are encoded for by the most abundant tRNAs. Therefore, the CUB of a gene can be linked to its expression level through translational optimization. We show that metagenomes, much like genomes, also show CUB and that this phenomenon can be used to predict the expression level of genes at the level of the entire microbial community. We analyzed adaptation of organisms in metagenomes to their extreme environments through this approach

Outage minimization of energy-harvesting wireless sensor network supported by UAV

Due to their adaptability, mobility, and capacity to offer an ideal channel, unmanned aerial vehicles (UAVs) have become a potential option for wireless power transfer and data collection in wireless sensor networks (WSNs). This paper examines energy-constrained WSNs, where data transfer to the data center is facilitated by UAV and sensors rely on radio frequency (RF) energy obtained by a Power Beacon (PB). However, due to energy limitations, sensors can only send data using the harvested energy. We consider a WSN in which the nodes are randomly distributed within a circular area, with the PB placed at the center of the WSN. To evaluate the system performance, we consider the dynamic nature of the wireless channel, which includes factors such as signal reflection, scattering, and diffraction. Through numerical analysis and simulations, the main aim is to identify the optimal system parameters that minimize the outage probability. This analysis provides valuable insights for designing more effective and reliable energy-harvesting WSNs with UAV as data collector. By leveraging UAV in WSNs, system performance can be improved, ensuring data transmission to destination nodes placed at a large distance from the WSN

Shift Work, Quality of Life and Work Ability among Croatian Hospital Nurses

This paper is a report of a study of the associations of shift work with work ability and quality of life (QoL) among clinical nurses. A cross-sectional study was conducted in 2007–2008 on 1124 nurses using the Work Ability Index Questionnaire and the Quality of Life Questionnaire (WHOQOL-BREF). Lower education was a predictor for low level of work ability and low physical health domain of QoL. Older age and having no partner were statistically significantly related to lower social interaction. Predictors significantly related to low environment domain of QoL were low education and shift work. Shift workers had higher level of level of work ability, but clinically insignificant. The study provides no evidence of a significant association between shift work and work ability or quality of life. Education has a positive association with nurses’ work ability and quality of life

Architectural 3D-Printed Structures Created Using Artificial Intelligence: A Review of Techniques and Applications

Artificial Intelligence (AI) and 3D printing (3DP) play considerable roles in what is known as the Fourth Industrial Revolution, by developing data- and machine-intelligence-based integrated production technologies. In architecture, this shift was induced by increasingly complex design requirements, posing important challenges for real-world design implementation, large-scale structure fabrication, and production quality standardization. The study systematically reviews the application of AI techniques in all stages of creating 3D-printed architectural structures and provides a comprehensive image of the development in the field. The research goals are to (1) offer a comprehensive critical analysis of the body of literature; (2) identify and categorize approaches to integrating AI in the production of 3D-printed structures; (3) identify and discuss challenges and opportunities of AI integration in architectural production of 3D-printed structures; and (4) identify research gaps and provide recommendations for future research. The findings indicate that AI is an emerging addition to the 3DP process, mainly transforming it through the real-time adjustment of the design or printing parameters, enhanced printing quality control, or prediction and optimization of key design features. However, the potential of the application of AI in large-scale architectural 3D printing still needs to be explored. Lastly, the study emphasizes the necessity of redefining traditional field boundaries, opening new opportunities for intelligent architectural production

INTELLIGENT COMPUTER VISION SYSTEM FOR SCORE DETECTION IN BASKETBALL

Development of an intelligent computer vision system for Smart IoT basketball training and entertainment includes the development of a range of various subsystems, where score detection subsystem is playing a crucial role. This paper proposes the architecture of such a score detection subsystem to improve reliability and accuracy of the RFID technology used primarily for verification purposes. Challenges encompass both hardware-software interdependencies, optimal camera selection, and cost-effectiveness considerations. Leveraging machine learning algorithms, the vision-based subsystem aims not only to detect scores but also to facilitate online video streaming. Although the use of multiple cameras offers expanded field coverage and heightened precision, it concurrently introduces technical intricacies and increased costs due to image fusion and escalated processing requirements. This research navigates the intricate balance between achieving precise score detection and pragmatic system development. Through precise camera configuration optimization, the proposed system harmonizes hardware and software components

3D Printing Technologies in Architectural Design and Construction: A Systematic Literature Review

The proliferation of digital technologies considerably changed the field of architecture. Digital fabrication pushes architecture into an unexpected new domain of previously unachievable complexity, detail, and materiality. Understanding these technologies’ impact can help direct future research, innovate design and construction processes, and improve the education of future professionals. However, comprehensive reviews offering a holistic perspective on the effects of 3D printing technologies on architecture are limited. Therefore, this study aims to provide a systematic review of state-of-the-art research on 3D printing technologies in architectural design and construction. The review was performed using three major databases, and selected peer-reviewed journal articles published in the last ten-year period were included in quantitative and qualitative analyses. Using bibliometric analysis, the research progress is summarized through the identified trend of the annual number of articles, prominent authors and co-authorship network, and key topics in the literature organized in three clusters. Further, content analysis of selected articles enabled coding cluster themes. Moreover, the analysis differentiated two categories of 3D printing technologies based on the scale of the system, elaborating their peculiarities in terms of materials, methods, and applications. Finally, challenges and promising directions for future work and research challenges are discussed

Automated compositions: artificial intelligence aided conceptual design explorations in architecture

The paper focuses on the challenges of the relationship between architecture and artificial intelligence (AI), in particular, the potential of this technology to support architects' creative design processes in the form of augmented intelligence. Conceptual architectural design is an intricate process that produces new concepts by using prior knowledge, experience, intuition, and creativity. Artificial intelligence should not be used during the conceptual design stage with the goal of solving a problem in a predefined search space. Instead, potential solutions and design requirements should be explored using this technology. The suggested approach avoids preconceived solutions and psychological inertia attributed to the designer's finite experience. The paper gives a brief critical review of the application of AI in an architectural context, especially in conceptual design. The review emphasizes changes in the design process brought about by cutting-edge strategies, methods, and tools based on AI. Further, research by design is presented to illustrate the possible use of biologically inspired algorithms in producing innovative design proposals. The applied strategy in architectural design production was based on the human-machine interface and interaction (HMI&I). Symbiotic human-machine interaction in the design process facilitates the emergence of automated compositions that display novel and unexpected forms, detail, materiality, structure, functionality, and aesthetics. This study allowed us to explore peculiar architectural design methodologies and the potential of digitally intelligent architecture