Miracle-dz/UniFAR-FTUs huggingface dataset:
Tropical seagrass Halophila stipulacea shifts thermal tolerance during Mediterranean invasion

Exotic species often face new environmental conditions that are different from those that they are adapted to. The tropical seagrass Halophila stipulacea is a Lessepsian migrant that colonized the Mediterranean Sea around 100 years ago, where at present the minimum seawater temperature is cooler than in its native range in the Red Sea. Here, we tested if the temperature range in which H. stipulacea can exist is conserved within the species or if the exotic populations have shifted their thermal breadth and optimum due to the cooler conditions in the Mediterranean. We did so by comparing the thermal niche (e.g. optimal temperatures, and upper and lower thermal limits) of native (Saudi Arabia in the Red Sea) and exotic (Greece and Cyprus in the Mediterranean Sea) populations of H. stipulacea. We exposed plants to 12 temperature treatments ranging from 8 to 40°C for 7 days. At the end of the incubation period, we measured survival, rhizome elongation, shoot recruitment, net population growth and metabolic rates. Upper and lower lethal thermal thresholds (indicated by 50% plant mortality) were conserved across populations, but minimum and optimal temperatures for growth and oxygen production were lower for Mediterranean populations than for the Red Sea one. The displacement of the thermal niche of exotic populations towards the colder Mediterranean Sea regime could have occurred within 175 clonal generations.
Fabrication and Applications of Polymer Planar Bragg Grating Sensors Based on Cyclic Olefin Copolymers

This contribution reviews recent advancements, current research and possible applications of polymer planar Bragg grating (PPBG) sensors with a focus on the utilization of cyclic olefin copolymer (COC) substrates. COC-PPBGs can be handled and fabricated efficiently by employing a single writing step procedure which features simultaneous generation of waveguide and Bragg grating structure within an injection molded substrate. The resulting photonic structures exhibit an attenuation as low as 1.2 dB cm−1 and a reflectivity up to 99%. The potential of COC-PPBGs for high-temperature applications is proven by demonstrating temperature measurements up to 160°C. Moreover, it is possible to employ single PPBGs for multidimensional stress and strain sensing or even three-dimensional shape reconstruction. Due to their excellent properties, it is feasible to integrate COC-PPBGs into commercial-grade carbon fiber reinforced polymer workpieces for structural health monitoring. Furthermore, utilization of appropriate coatings enables functionalization of PPBGs for refractive index sensing and thus biochemical applications. Beside the fabrication and characterization of COC-based PPBGs, this contribution exemplifies and reviews such applications.
In silico, in vitro, and in vivo Approaches to Identify Molecular Players in Fragile X Tremor and Ataxia Syndrome

Fragile X-associated tremor/ataxia syndrome (FXTAS) is a late-onset neurodegenerative monogenetic disorder affecting carriers of premutation (PM) forms of the FMR1 gene, resulting in a progressive development of tremors, ataxia, and neuropsychological problems. This highly disabling disease is quite common in the general population with an estimation of about 20 million PM carriers worldwide. The chances of developing FXTAS increase dramatically with age, with about 45% of male carriers over the age of 50 being affected. Both the gene and pathogenic trigger, a mutant expansion of CGG RNA, causing FXTAS are known. This makes it an interesting disease to develop targeted therapeutic interventions for. Yet, no such interventions are available at this moment. Here we discuss in silico, in vitro, and in vivo approaches and how they have been used to identify the molecular determinants of FXTAS pathology. These approaches have yielded substantial information about FXTAS pathology and, consequently, many markers have emerged to play a key role in understanding the disease mechanism. Integration of the different approaches is expected to provide crucial information about the value of these markers as either therapeutic target or biomarker, essential to monitor therapeutic interventions in the future.
Modeling the Views of WeChat Articles by Branching Processes

In cyber security, the temporal patterns of information propagation in online social networks is of crucial importance, especially for false information detection and defense. The mechanism of information propagation is the fundamental of online security, such as predicting and suppressing false information dissemination. The dynamics of information popularity in online social networks open the possibilities for understanding the mechanisms of information spreading. In this paper, we study the temporal patterns associated with online contents generated by WeChat subscription accounts. In order to reveal the popularity dynamics of WeChat articles, we formulate a probabilistic model using branching process to reveal the mechanism of views of WeChat articles. Specifically, a non-Markovian age-dependent branching process is introduced for the purpose of considering the heterogeneousness of human behavior and the tree-like dissemination structures. Different from the Markovian case with exponentially distributed lifetime of particles in the branching system, the heavy-tailed power law distributed inter event time is one of the key ingredients for our model. Moreover, the limitation of users' attention span, and the attractiveness of articles are also considered in our model. We demonstrate our approach on the real data of WeChat articles' popularity time series. The branching model is successful in presenting the temporal patterns of the real evolution. Our findings offer insights into the temporal patterns of information popularity in online social networks, which provides references for further prediction and control of information propagation concerning cyber security.
Performance Analysis of Short Analog Fountain Codes

Analog fountain codes are a class of rateless codes that have been demonstrated to achieve near-capacity performance for asymptotically long blocks, without any channel state information at the transmitter side. Recently, a new design for these codes has been proposed aimed at improving its performance in the finite block length regime, dubbed short analog fountain codes (S-AFC). S-AFC was shown to score error rates orders of magnitude smaller than AFC for blocks of a few hundred bits long. S-AFC was also shown to achieve average block lengths close to the Polyanskiy-Poor and Verdu bound for high SNR and exhibits no error floors down to 10^-7. In this paper, we derive lower and upper bounds on the block error rate (BLER) of S-AFC. We verify these bounds through Monte Carlo simulations and provide all the proofs in the appendix.
GSC Based Speech Enhancement with Generative Adversarial Network

At present, the technology of using microphone arrays for speech enhancement has been widely concerned, and the enhancement effect is excellent. The widely used Generalized Sidelobe Canceller (GSC) method can achieve good noise reduction for noisy speech in the additive noise acoustic environment, and achieve better intelligibility improvement. But there are also areas for improvement. In the lower branch of GSC, signal leakage caused by the estimation of the incident angle or the slight change of the position of the microphone array may cause the self-cancellation of target speech signal, thereby the severe speech distortion is caused. In this paper, the Generative Adversarial Network (GAN), which has broad application prospects in deep learning technology, replaces the lower branch of the traditional GSC structure, thus the self-cancellation of speech signals is avoided and improving the anti-error ability of the enhancement system is improved effectively.
Resource-Constrained Machine Learning for ADAS: A Systematic Review

The advent of machine learning (ML) methods for the industry has opened new possibilities in the automotive domain, especially for Advanced Driver Assistance Systems (ADAS). These methods mainly focus on specific problems ranging from traffic sign and light recognition to pedestrian detection. In most cases, the computational resources and power budget found in ADAS systems are constrained while most machine learning methods are computationally intensive. The usual solution consists in adapting the ML models to comply with the memory and real-time (RT) requirements for inference. Some models are easily adapted to resource-constrained hardware, such as Support Vector Machines, while others, like Neural Networks, need more complex processes to fit into the desired hardware. The ADAS hardware (HW platforms) are diverse, from complex MPSoC CPUs down to classical MCUs, DPSs and application-specific FPGAs and ASICs or specific GPU platforms (such as the NVIDIA families Tegra or Jetson). Therefore, there is a tradeoff between the complexity of the ML model implemented and the selected platform that impacts the performance metrics: function results, energy consumption and speed (latency and throughput). In this paper, a survey in the form of systematic review is conducted to analyze the scope of the published research works that embed ML models into resource-constrained implementations for ADAS applications and what are the achievements regarding the ML performance, energy and speed trade-off.
Segment-Based Joint Caching and Recommendation Optimization for Mobile Video Transmission

Mobile edge caching is able to reduce transmission latency and relieve the traffic load of backhaul links in the delivery of mobile video contents. However, the content caching remains a challenging problem considering the relatively limited cache capacity and the heterogeneous user demand. Recommendation system, with the ability to shape users' demand, can be leveraged to improve the performance of mobile edge caching efficiency. In this paper, the caching policies and recommendation strategies are designed for the cache-enabled wireless networks. Considering popularity difference among segments in a single video content, a more fine-grained segment-based proactive caching policy is introduced, which is different from the existing works that focus on content-level caching. Besides, the impact of recommendation system on usersâ€™ request patterns is taken into account. In order to effectively reduce the content transmission latency, a joint caching and recommendation optimization problem is formulated. Due to the NP-hard nature, the problem is divided into two convex subproblems and a heuristic iterative algorithm is proposed. Numerical simulation results show that the proposed algorithm outperforms the existing algorithms in terms of both average transmission latency and cache hit ratio.
Voice Activity Detection Based on Time-Delay Neural Networks

Voice activity detection (VAD) is an important preprocessing part of many speech applications. Context information is important for VAD. Time-delay neural networks (TDNNs) capture long context information with a few parameters. This paper investigates a TDNN based VAD framework. A simple chunk based decision method is proposed to smooth raw posteriors and decide border points of utterances. To evaluate decision performance, a metric intersection-over-union (IoU) is introduced from image object detection. The experiment results are evaluated on Wall Street Journal (WSJ0) corpus. Frame classification performance is measured by area under the curve (AUC) and equal error rate (EER). Compared with long short-term memory baseline, the TDNN based system achieves a 41.26% EER relative reduction on average in matched noise condition, and relative improvement of average AUC is 3.82%. Proposed decision method achieves an 18.74% IoU relative improvement on average compared with moving average method on average.
Paranoia, sensitization and social inference: findings from two large-scale, multi-round behavioural experiments

The sensitization model suggests that paranoia is explained by over-sensitivity to social threat. However, this has been difficult to test experimentally. We report two preregistered social interaction studies that tested (i) whether paranoia predicted overall attribution and peak attribution of harmful intent and (ii) whether anxiety, interpersonal sensitivity and worry predicted the attribution of harmful intent. In Study 1, we recruited a large general population sample (N = 987) who serially interacted with other participants in multi-round dictator games and matched to fair, partially fair or unfair partners. Participants rated attributions of harmful intent and self-interest after each interaction. In Study 2 (N = 1011), a new sample of participants completed the same procedure and additionally completed measures of anxiety, worry and interpersonal sensitivity. As predicted, prior paranoid ideation was associated with higher and faster overall harmful intent attributions, whereas attributions of self-interest were unaffected, supporting the sensitization model. Contrary to predictions, neither worry, interpersonal sensitivity nor anxiety was associated with harmful intent attributions. In a third exploratory internal meta-analysis, we combined datasets to examine the effect of paranoia on trial-by-trial attributional changes when playing fair and unfair dictators. Paranoia was associated with a greater reduction in harmful intent attributions when playing a fair but not unfair dictator, suggesting that paranoia may also exaggerate the volatility of beliefs about the harmful intent of others.
Die Arbeitsmarktintegration von Migrantinnen und Migranten in Österreich

Dieser Beitrag bietet anhand der Ergebnisse des Ad-hoc-Moduls der Arbeitskrafteerhebung zur Arbeits- und Lebenssituation von Migrantinnen und Migranten im II. Quartal 2008 einen Uberblick uber die Arbeitsmarktlage der ersten und zweiten Generation und der im Ausland Geborenen in Osterreich. Demnach zeigen sich erhebliche Unterschiede zwischen der ersten und zweiten Generation, zwischen Mannern und Frauen, zwischen Personen, die ursprunglich als Asylantinnen bzw. Asylanten zuwanderten und anderen Gruppen und zwischen im Ausland Geborenen, deren formale Qualifikation in Osterreich anerkannt wurde, und Personen, fur die dies nicht der Fall ist. In den Schlussfolgerungen werden die aus diesen Ergebnissen ableitbaren Forschungsfragen diskutiert.
Autocatalytic chemical networks at the origin of metabolism

Modern cells embody metabolic networks containing thousands of elements and form autocatalytic sets of molecules that produce copies of themselves. How the first self-sustaining metabolic networks arose at life's origin is a major open question. Autocatalytic sets smaller than metabolic networks were proposed as transitory intermediates at the origin of life, but evidence for their role in prebiotic evolution is lacking. Here, we identify reflexively autocatalytic food-generated networks (RAFs)—self-sustaining networks that collectively catalyse all their reactions—embedded within microbial metabolism. RAFs in the metabolism of ancient anaerobic autotrophs that live from H2 and CO2 provided with small-molecule catalysts generate acetyl-CoA as well as amino acids and bases, the monomeric components of protein and RNA, but amino acids and bases without organic catalysts do not generate metabolic RAFs. This suggests that RAFs identify attributes of biochemical origins conserved in metabolic networks. RAFs are consistent with an autotrophic origin of metabolism and furthermore indicate that autocatalytic chemical networks preceded proteins and RNA in evolution. RAFs uncover intermediate stages in the emergence of metabolic networks, narrowing the gaps between early Earth chemistry and life.
Pathogenicity and Immune Responses of Aspergillus fumigatus Infection in Chickens

Aspergillus fumigatus is a ubiquitous pathogen in poultry farms, causing aspergillosis in chickens. To study the pathogenicity of A. fumigatus, 14-days-old chickens were infected with fungal conidia (2 × 107 CFU/mL) via thoracic intra-air sacs inoculation. The clinical symptoms, gross and histopathological lesions, and fungal load in the lungs were examined. Additionally, the mRNAs of Toll like receptors (TLR) and pro-inflammatory cytokines were evaluated by quantitative PCR to explore the immune responses induced by A. fumigatus. The results showed that overt depression, ruffled feathers, and dyspnea were observed in the infected chickens as early as 3 days post infection (dpi). Eleven out of 25 infected chickens died from 5 to 9 dpi, and A. fumigatus could also be reisolated from the infected lung. Histopathological examination revealed obvious airsacculitis and pneumonia, characterized by inflammatory cell infiltration (heterophils and macrophages), and granulomatous lesions in the lung. The mRNA expressions of TLR1 and TLR2 were upregulated in the lung and spleen, and most pro-inflammatory cytokines including IL-1β, Cxcl-8, TNF-α, IL-12, and IFN-γ were increased in both the lung and spleen during the tested period, suggesting that the innate immune responses were triggered by A. fumigatus infection, and these cytokines participated in the inflammatory responses against A. fumigatus. These results indicate that A. fumigatus infection by thoracic intra-air sacs inoculation can cause severe respiratory damage in chickens, activate TLR1 and TLR2 mediated immune responses, and elicit large expression of pro-inflammatory cytokines such as IL-1β, Cxcl-8, and IFN-γ. These data will help further understanding of the pathogenesis and immune responses of A. fumigatus infection in the chicken.
Evaluation of Thyroid function Status in Hemodialysis Patients

ackground The interactions between kidney and thyroid functions are known for years. Thyroid hormones (TH) are necessary for growth and development of the kidney and for the maintenance of water and electrolytes homeostasis. On the other hand, kidney is involved in the metabolism and elimination of TH. Chronic renal failure (CRF) affects thyroid function in many ways, including low circulating thyroid hormone levels, altered peripheral hormone metabolism, insufficient binding to carrier proteins, possible reduction in tissue hormone content and altered iodide storage in the thyroid gland. Thus, patients with renal failure may have various abnormalities of thyroid function; nevertheless, they are typically clinically euthyroid. Objectives: the aim of the present study is to evaluate thyroid function status in patients with hemodialysis in Karbala province, and to determine the benefit of thyroid function test as a routine test requested in hemodialysed patients. Methods: Forty-two hemodialysed patients who attend hemodialysis unit in Al_Hussien teaching hospital in Karbala province with mean age of (44.4±15.9), another 32 apparently healthy subjects with mean age (41.4±12.5) took part in the current study as a control group. An early morning fasting sample of venous blood from each, total trioiodothyronine (TT3), total thyroxine (TT4) and thyroid stimulating hormone TSH were estimated by Enzyme Linked ImmuoSorbent Assay( ELISA). Result: The (TT3) level in haemodialysed patients was significantly lower than the level TT3 in control group (P< 0.001). T-student test reveals no significant difference in the total thyroxine (TT4) level between haemodialysed patients and control group. Also There was no significant difference in the mean level of TSH between hemodialysis and control group. About 41% of haemodialysed patients have TT3 level in the lower tertile of the reference range another 26% have TT3 level below the reference value. There was no correlation between TT3 level in hemodialysis group and duration of hemodialysis (in months). Conclusion: Abnormalities in thyroid function test in hemodialysis patient are more common than that in general population, and low T3 syndrome is considered the main disorder that affect the thyroid function test in hemodialysis patients. So this disorder should be investigated in those patients routinely as, its presence in hemodialysis patients indicates a bad prognosis for them . ﺔﺻﻼﺨﻟا
Régime DASH et risque de cancer colorectal chez les adultes canadiens

Introduction : Le cancer colorectal (CCR) est un cancer à taux d’incidence élevé qui touche de nombreux adultes canadiens chaque année. L’alimentation joue un rôle important dans l’étiologie du CCR et de nombreuses composantes alimentaires sont considérées comme des facteurs de risque potentiels. L’utilisation du profil DASH (Dietary Approaches to Stop Hypertension, régime alimentaire qui vise à lutter contre l’hypertension) est un moyen efficace de caractériser l’alimentation générale des individus. L’objectif de cette étude a été de déterminer un profil DASH en contexte canadien et de vérifier ses liens avec le risque de CCR chez les adultes canadiens.
Validation of the 3D reconstructed human skin Comet assay, an animal-free alternative for following-up positive results from standard in vitro genotoxicity assays

Abstract As part of the safety assessment process, all industrial sectors employ genotoxicity test batteries, starting with well-established in vitro assays. However, these batteries have limited predictive capacity for the in vivo situation, which may result in unnecessary follow-up in vivo testing or the loss of promising substances where animal tests are prohibited or not desired. To address this, a project involving regulators, academia and industry was established to develop and validate in vitro human skin-based genotoxicity assays for topically exposed substances, such as cosmetics ingredients. Here, we describe the validation of the 3D reconstructed skin (RS) Comet assay. In this multicenter study, chemicals were applied topically three times to the skin over 48 h. Isolated keratinocytes and fibroblasts were transferred to slides before electrophoresis and the resulting comet formation was recorded as % tail DNA. Before decoding, results of the validation exercise for 32 substances were evaluated by an independent statistician. There was a high predictive capacity of this assay when compared to in vivo outcomes, with a sensitivity of 77 (80)%, a specificity of 88 (97)% and an overall accuracy of 83 (92)%. The numbers reflect the calls of the performing laboratories in the coded phase, whereas those in parenthesis reflect calls according to the agreed evaluation criteria. Intra- and inter-laboratory reproducibility was also very good, with a concordance of 93 and 88%, respectively. These results generated with the Phenion® Full-Thickness skin model demonstrate its suitability for this assay, with reproducibly low background DNA damage and sufficient metabolic capacity to activate pro-mutagens. The validation outcome supports the use of the RS Comet assay to follow up positive results from standard in vitro genotoxicity assays when the expected route of exposure is dermal. Based on the available data, the assay was accepted recently into the OECD test guideline development program.