Miracle-dz/UniFAR-FTUs huggingface dataset:
Investigating process stresses on Saccharomyces cerevisiae using isothermal microcalorimetry

04 June 2017 ii The slow cold shock (0.13 °C/minute) had no impact on cell viability but did cause a slight decrease in cell vitality. As expected, the rapid cold shock (18 °C/minute) had no impact on cell viability but a significant negative effect on cell vitality. Ethanol shock – the sudden suspension of yeast cultures in ethanol and subsequent removal of the ethanol in the range 4% to 8% (v/v) – had no observable impact on cell viability or cell vitality and the growth thermogram. The growth of cells in the presence of ethanol, known for product inhibition, had a significant effect on the growth thermograms, which is in line with previous literature findings. The combination of a rapid cold shock and growth in ethanol had no significant cumulative effect on the growth thermogram. The results show that yeast is more susceptible to a rapid cold shock than a gradual cooling and that yeast is largely resistant to rapid ethanol exposure however, continual ethanol exposure severely retards growth. The method developed has been shown to be repeatable and accurate for assessing yeast viability and vitality. Further, it is sufficiently sensitive to determine both stress response and inhibition trends. Matthew Myers Acknowledgements iii Acknowledgements I would like to thank the entire CeBER cohort, not to mention the CeBER academic staff, lab staff and administrative staff for their support and guidance. A special thank you to my supervisors; Siew Tai, Rob, Marijke Fagan-Endres and Sue Harrison for their invaluable input. I also would like to thank my siblings, grandparents and especially my three parents, Peter, Michelle and Candace who have supported and encouraged me through all my endeavours.
Causes of multimodal size distributions in 1 spatially-structured populations 2

16 Plant sizes within populations often exhibit multimodal distributions, even when 17 all individuals are the same age and have experienced identical conditions. To 18 establish the causes of this we created an individual-based model simulating the 19 growth of trees in a spatially-explicit framework, parameterised using data from 20 a long-term study of forest stands in New Zealand. First we demonstrate that 21 asymmetric resource competition is a necessary condition for the formation of 22 multimodal size distributions within cohorts. In contrast, the legacy of small-scale 23 clustering during recruitment is transient and quickly overwhelmed by density24 dependent mortality. Complex multi-layered size distributions are generated when 25 established individuals are restricted in the spatial domain within which they can 26 capture resources. The number of modes reveals the effective number of direct 27 competitors, while the separation and spread of modes are influenced by distances 28 among established individuals. An unexpected emergent outcome was the produc29 tion of U-shaped size-mortality relationships, an enigmatic pattern often observed 30 in natural forests. This occurred in the simulations because of the high mainten31 tance costs of large individuals, which made them sensitive to even minor compet32 itive effects. Asymmetric competition within local neighbourhoods can therefore 33 generate a range of complex size distributions. 34
ADJUVANLA ARTRİT OLUŞTURULMUŞ SIÇAN MODELİNDE İZOLE AORT PREPARATININ REAKTİF YANITLARI VE ALLOPÜRİNOL’ÜN GEVŞEME YANITLARINA ETKİSİ REACTIVE RESPONSES OF ISOLATED AORTA PREPERATIONS AND THE RELA- XING EFFECT OF ALLOPURİNOL IN ADJUVANT İNDUCED ARTHRITIS MODEL IN RATS

In this study, we investigated the alteration of isolated aorta responses and the relevant relaxing effects of allopurinol in primary and secondary phases of rat’s adjuvant arthritis model. The arthritis was evaluated by scoring prior to and 6 (primary phase) and 15 days (secondary phase) after induction of arthritis by intradermal Freund’s complete adjuvant. Moreover, the relaxation and contraction responses of thoracic aorta rings were also recorded in both phases of arthritis. The contractile response to phenylephrine in secondary phase was higher than the control and primary phase. The reduction of the relaxing effect of acetylcholine in all arthritis groups indicates profound endothelial disturbance. No difference was found among the groups with regard to the effects of sodium nitroprusside in the aorta with intact endothelium. Allopurinol alone relaxed the aortic preparation. However, the effect of allopurinol in secondary phase aorts, both with and without endothelium, was decreased compared to that obtained in control and primary phase . The relaxing effect of acetylcholine in presence of allopurinol in aortic preparation with intact endothelium was decreased in control and primary phase, but the effect was not changed in secondary phase. L-NAME altered the effect of allopurinol on acetylcholine. In conclusion, the effect of allopurinol in inflammatory arthritis is partly via an effect on xanthine oxidase and partly on nitric oxide. (Pam Med J 2009;2(3):107-17).
Left Colon Cancer Metastatic to the Gallbladder: A Case Report

Case Report Gallbladder metastases (GBM) may be rare, but they are not exceptional. An autopsy series has found that up to 6% of cancer patients presented with GBM [1]. Different types of cancer can spread to the gallbladder. The most common primary cancer to is malignant melanoma, which may do so in up to 20% of cases [2]. Other tumors that show clinically significant metastasis to the gallbladder include renal cell carcinoma, adenocarcinoma of the breast, gastric cancer. Only a few cases of GBM were reported in patients with colon cancer. Here we present a case of a 62 years old female patient, admitted for a tumor in the left (descending) cancer, with a mild tenderness in the right hypochondrium. CT scan showed a stage II colon cancer, with gallbladder lithiasis. The case was managed with a laparoscopic colectomy along with a cholecystectomy. Histological examination of the gallbladder revealed an adenocarcinoma of colon origin. Only few cases of colon cancer metastasizing to the gallbladder were reported in English literature [3, 4].
Decentralized Internet Archive using the Cothority framework

Since the 1990s, Internet takes more and more importance in the everyday life. People use it to store any data from holidays pictures to government’s communications. They also use it as a reliable source of informations and knowledge. Nevertheless, we observe a centralization of the providers of services and a fragility of the long-term sustainability of the data. Because of that, the latter are very vulnerable to censorship either by deletion, modification, or access denial. In this report, we present the definition and the implementation of a consensus-based system to create a decentralized internet archive. The particularity of this protocol is that the servers involved in it will first agree on the biggest common subset of the website using a tree comparison based approach. Then they will only store that common subset on a blockchain. The implementation is done inside the Cothority[1] framework. Once a website is archived, our solution makes it impossible for a single entity to remove or modify its content. The consensus algorithm is considered efficient since it grows polynomially with the size of the website and linearly with the number of machine involved in the consensus. Furthermore, our simulations shows that it can save a news web page in under 40 seconds. Finally, from a security point of view, if the leader of the consensus protocol and the majority of the machines involved in the archiving protocol are honest, the latter will store a honest, immutable snapshot of the web page that can later be securely retrieved by any user of the system.
Semantic-aware Active Perception for UAVs using Deep Reinforcement Learning

This work presents a semantic-aware path-planning pipeline for Unmanned Aerial Vehicles (UAVs) using deep reinforcement learning for vision-based navigation in challenging environments. Driven by the maturity of works in semantic segmentation, the proposed path-planning architecture uses reinforcement learning to distinguish the parts of the scene that are perceptually more informative using semantic cues, in effect guiding more robust, repeatable, and accurate navigation of the UAV to the predefined goal destination. Assuming that the UAV performs vision-based state estimation, such as keyframe-based visual odometry, and semantic segmentation onboard, the proposed deep policy network continuously evaluates the optimal relative perceptual informativeness of each semantic class in view. A perception-aware path planner uses these informativeness values to perform trajectory optimization in order to generate the next best action with respect to the current state and the perception quality of the surroundings, essentially guiding the UAV to avoid flying over perceptually degraded regions. Thanks to the use of semantic cues, the policy can be trained in a large number of non-photorealistic randomly-generated scenes, and results to an architecture that is generalizable to environments with the same semantic classes, independently of their visual appearance. Extensive evaluations on challenging, photorealistic simulations reveal a remarkable improvement in robustness and success rate with the proposed approach over the state of the art in active perception. Video – https://youtu.be/RaO3whUBVnc
An efficient and scalable synthesis of potent TLR2 agonistic PAM2CSK4

Diacylated PAM2CSK4, a highly expensive lipopeptide with desirable aqueous solubility and a broad spectrum of cytokine/chemokine induction is a most potent dual (human and murine) Toll-Like Receptor-2 (TLR2) agonist. Besides such thrilling characteristics, its synthetic process is not reported in the literature. The present report describes an efficient and scalable 20 step synthesis of PAM2CSK4 in good yield (all steps > 60%) along with a clear description of the hindrances and easy solutions adopted in each step. Overall, a convergent synthetic approach was adopted involving synthesis of appropriately protected starting materials, synthesis of a key backbone skeleton PAM2CS, synthesis of a tetralysine fragment and the final coupling to yield PAM2CSK4. Tedious column chromatography was avoided on a large scale in many steps.
A Review on Fact Extraction and Verification

We study the fact-checking problem, which aims to identify the veracity of a given claim. Specifically, we focus on the task of Fact Extraction and VERification (FEVER) and its accompanied dataset. The task consists of the subtasks of retrieving the relevant documents (and sentences) from Wikipedia and validating whether the information in the documents supports or refutes a given claim. This task is essential and can be the building block of applications such as fake news detection and medical claim verification. In this article, we aim at a better understanding of the challenges of the task by presenting the literature in a structured and comprehensive way. We describe the proposed methods by analyzing the technical perspectives of the different approaches and discussing the performance results on the FEVER dataset, which is the most well-studied and formally structured dataset on the fact extraction and verification task. We also conduct the largest experimental study to date on identifying beneficial loss functions for the sentence retrieval component. Our analysis indicates that sampling negative sentences is important for improving the performance and decreasing the computational complexity. Finally, we describe open issues and future challenges, and we motivate future research in the task.
Chinese economic performance in the long run

This book is unique in its depth of perspective. It uses a comparative approach to explain why China’s role in the world economy has changed so dramatically in the last thousand years. It concludes that China is likely to resume its natural role as the world’s largest economy by the year 2015, thus regaining the position it had held until the end of the nineteenth century. The study provides a major reassessment of the scale and scope of China’s resurgence over the past half century, employing quantitative measurement techniques which are standard practice in OECD countries, but which have not hitherto been available for China. Written by the author of many studies on comparative economic history, including two best sellers for the OECD Development Centre, this book is essential reading for all those who seek to understand the role of China in the world economy, in the past, as well as in the present and the future.
Optimal and Suboptimal MMSE Precoding for Multiuser MIMO Systems Using Constant Envelope Signals with Phase Quantization at the Transmitter and PSK

We propose an optimal MMSE precoding technique using quantized signals with constant envelope and PSK modulation. Unlike the existing MMSE design for 1-bit resolution, the proposed method employs uniform phase quantization and the bounding step in the branch-and-bound method is different in terms of considering the most restrictive relaxation of the nonconvex problem, which is then utilized for a suboptimal design also. Numerical simulations show that using the MMSE criterion instead of the established maximum distance to decision threshold yields a lower BER in many scenarios and a smaller average number of bound evaluations for low and medium SNR.
Assessing the impact of Cyber-Physical Attacks on Critical Infrastructures: A Semantic-Based Approach

This paper proposes an integrated approach to study impact propagation of cyber and physical incidents within critical health-care infrastructures. This approach is based on a semantic modeling and reasoning engine which takes into account assets and input/output incident types while running propagation through a network graph. Besides, it calculates impact scores based on assets availability and protection degree upon incident reception.
Using Attraction Models for Competitive Optimization: Pitfalls to avoid and Conditions to check

An important contribution to understanding competition has been the development of market share models based on the relative attractiveness of brands within a competitive set. These models have been used extensively as statistical tools to analyze and represent demand data. They have also been used for analytical studies of competitive optimization but this entails a number of challenges for the researcher. Preliminary
Towards 3D Mapping of Seagrass Meadows with Topo-Bathymetric Lidar Full Waveform Processing

Topo-bathymetric lidar is a powerful tool to survey coastal ecosystems while ensuring data continuity between land and water regardless of the nature of the terrain, and allowing the collection of information up to several dozens of metres deep. This study analyzes the potential of full waveform lidar data to monitor key ecosystems for climate change mitigation: seagrasses. It proposes an original way of processing topo-bathymetric lidar waveforms to map their spatial repartition and extent in Corsica (France). Waveform statistical and shape parameters are computed and used to produce a map of seagrass meadows that reaches over 86% of overall accuracy. Seagrass height is also extracted, offering perspectives for structural complexity assessment and ecosystem services quantification.
Analysis of Machine Learning Approach for the modemodel in SWC Mapping in Automotive Systems

Automotive technologies are ever-increasinglybecoming digital. Highly autonomous driving togetherwith digital E/E control mechanisms include thousandsof software applications which are called as software components. Together with the industry requirements, and rigorous software development processes, mappingof components as a software pool becomes very difficult.This article analyses and discusses the integration possiblilities of machine learning approaches to our previously introduced concept of mapping of software components through a common software pool.
PRIMARY STUDENTS’ PERFORMANCE OF STEM DOMAIN-SPECIFIC SELF-EFFICACY BELIEF AND EXPECTANCY-VALUE BELIEF

Most studies have concentrated in assessing students’ overall attitudes towards science, mathematics, and engineering/technology or the attitude towards individual STEM domain. The present research aims to explore primary students’ gender and grade differences of their STEM domain-specific attitudes including self-efficacy and expectancy-value beliefs, as well as their correlations. The results showed no detected significant effects among these different STEM domains in the overall attitudes, the overall self-efficacy beliefs, and the overall expectancy-value beliefs for primary students. The correlations between self-efficacy and expectancy-value were much stronger for the science domain and engineering/technology domain than the mathematics domain. No gender difference of the self-efficacy beliefs was detected except in the mathematics domain, and the result that lower primary students performed significantly better than upper primary students in the self-efficacy was also mainly contributed by the grade difference in the mathematics domain. Whereas no different expectancy-value beliefs existed across genders and grade levels in various STEM domains. The present results reported some unique performances by the primary school students compared to the elder group. Keywords: expectancy-value, gender differences, grade levels, self-efficacy, STEM attitudes
Exploring Students’ Perceptions towards Integrating Facebook in EFL Literature Classroom: the Case of the Second Year LMD

: The importance of teaching literature in the department of English has always been a challenge for teachers. Hence, they are seeking innovative strategies to use the new technologies in the classroom settings to obtain better learning outcomes. Therefore, the present study offers concrete insights about the usage of Facebook in teaching literature. It attempts to explore the use of Facebook as an accompanying resource for Second year licence students to learn English Literature at the Department of Literature and English, Dr Tahar Mouley University, Saida. Two research tools were used: classroom observation and questionnaire in order to examine students’ perceptions towards the use of Facebook in learning literature. The results showed that via Facebook students can widen their knowledge about the target language as it can increase their interest in literature class.
Color2Embed: Fast Exemplar-Based Image Colorization using Color Embeddings

In this paper, we present a fast exemplar-based image colorization approach using color embeddings named Color2Embed. Generally, due to the difficulty of obtaining input and ground truth image pairs, it is hard to train a exemplar-based colorization model with unsupervised and unpaired training manner. Current algorithms usually strive to achieve two procedures: i) retrieving a large number of reference images with high similarity for preparing training dataset, which is inevitably time-consuming and tedious; ii) designing complicated modules to transfer the colors of the reference image to the target image, by calculating and leveraging the deep semantic correspondence between them (e.g., non-local operation), which is computationally expensive during testing. Contrary to the previous methods, we adopt a self-augmented self-reference learning scheme, where the reference image is generated by graphical transformations from the original colorful one whereby the training can be formulated in a paired manner. Second, in order to reduce the process time, our method explicitly extracts the color embeddings and exploits a progressive style feature Transformation network, which injects the color embeddings into the reconstruction of the final image. Such design is much more lightweight and intelligible, achieving appealing performance with fast processing speed.
Biofouling Impacts and Toxicity of Antifouling Agents on Marine Environment: A Qualitative Study.

Biofouling from microorganisms, plants, barnacles, mussels or algae is a major problem for marine structures. Fouling leads to increased fuel costs due to increased frictional resistance on ships, and reduces reserve buoyancy of floating offshore structure, in addition to causing cage deformation and structural fatigue, impacting endurance of materials. The intrusion of invasive aquatic species (IAS) to new environments by ships is identified as a major threat to the world’s oceans. Marine fouling affects most manmade surfaces immersed in the sea, resulting in substantial losses. Anti-fouling paints tackle this problem to a certain extent. Extensive research is in progress in the antifouling technologies in maritime sector, with new products in compliance with International Maritime Organisation (IMO) regulations being developed. The most efficient solution to minimise fouling is to make surfaces unsuitable for settlers, coating them with Antifouling (AF) Paints containing toxic compounds. Most AF agents had Tributyltin (TBT), and has been phased out by IMO since 2008 due to harmful effect on environment. However, use of TBT in AF paints is not prohibited, though has been restricted in several countries. The environmental problems by biofouling and toxicity of existing and alternative Anti-Fouling techniques are reviewed in this paper. Further, various ship hull cleaning technologies commercially available including afloat cleaning are also introduced. Keywords— Biofouling, TBT, Antifouling (AF), IAS, IMO, AFS, Alternatives Sustainability, Agri, Food and Environmental Research, (ISSN: 0719-3726), 10(X), 2022: http://dx.doi. org/
Global trends regarding competence requirements for managers

The article outlines priority directions of modern management, including the need to ensure the stability of companies, the formation of corporate culture, taking into account insights from behavioral economics. The author demonstrates the growing importance of a systemic approach and democratization in management and outlines key global trends in management systems, which include globalization, implementation of the principles of sustainable development, challenges associated with volatility, uncertainty, complexity and ambiguity, rapid technological development, changes in office and managerial work. Against the background of a comparative description of industrial and post-industrial society the author shows that the human capital is currently a key resource and knowledge is the driving force of development. Given these new requirements, key competencies of a modern manager are presented.
Ka Band-pass Filter Based on SIW Technology for Wireless Communications

Abstract—The paper proposes a new third-order Chebyshev bandpass filter based on the substrate integrated waveguide (SIW) manufacturing technology using an inductive iris and a defected ground structure (DGS) station to resonate in the Ka frequency band, intended for wireless communication applications. All steps that are necessary for designing such a filter have been described in detail based on specific analytical equations harnessed to calculate the different synthesizable parameters of the proposed band-pass filter design, such as the coupling matrix, quality coefficients and initial geometric dimensions. The filter’s ideal frequency response is extracted from an equivalent circuit employing localized elements developed with the use of Design Microwave Office Software. Otherwise, HFSS is employed to set the initial parameters of the proposed topology that will not meet the target specifications defined previously. Accordingly, optimization procedures are necessary for different SIW band-pass filter parameters to reach a high frequency response for the proposed design. The detailed results presented show high efficiency of the SIW technology that offers good performance with lower filter volumes. Two topologies have been developed and then optimized to demonstrate the usefulness of EM software.