Miracle-dz/UniFAR-FTUs huggingface dataset:
Etude des interactions hôte/parasite chez l’huître plate Ostrea edulis et son parasite Bonamia ostreae

L’histoire de l’ostreiculture francaise met en evidence la fragilite de cette production face a la surexploitation des stocks et l’apparition de maladies. En particulier, la production d’huitre plate, Ostrea edulis, a fortement diminue suite a l’apparition de deux maladies parasitaires dont la bonamiose. Les moyens de lutte contre la bonamiose sont relativement restreints. Ils sont essentiellement bases sur la surveillance de la sante des huitres afin de limiter la dissemination et la propagation de la maladie. Cependant l’utilisation de modeles predictifs de l’evolution de la maladie en zone infectee permettrait d’optimiser la gestion des stocks et minimiser l’impact des agents pathogenes. De plus, le developpement d’animaux resistants a l’infection pourrait permettre de relancer cette production. Ces differentes approches necessitent des outils diagnostiques adaptes, une bonne connaissance du cycle de vie de l’agent pathogene, et, plus particulierement des interactions du parasite avec son hote. Dans ce contexte, l’objectif principal du travail de these propose est de comprendre les interactions entre l’huitre plate Ostrea edulis et son parasite Bonamia ostreae, et, plus particulierement les bases moleculaires de la resistance au parasite. Dans un premier temps, la realisation d’une banque soustractive d’ADNc a permis d’identifier des ESTs differentiellement exprimees chez des hemocytes en reponse au parasite. L’expression de certains genes dont une galectine a ete mesuree en PCR en temps reel dans le contexte d’infections in vitro. En complement, la reponse cellulaire a ete etudiee par cytometrie en flux et l’infection controlee en microscopie. Ces experiences ont montre une multiplication parasitaire dans les hemocytes au cours du temps associee a une diminution de la production d’EOR et d’esterases. Dans un second temps, il a ete entrepris une etude comparative entre une population d’huitres plates resistantes a la bonamiose et une population naturelle. Les resultats obtenus tendent a montrer qu’une modulation de l’apoptose et une diminution de la phagocytose seraient impliquees dans les mecanismes lies a la resistance a la bonamiose. Ce travail est le premier a etudier la reponse des hemocytes d’huitres plates a une infection par le parasite Bonamia ostreae au niveau cellulaire et moleculaire.
On the Use of a Virtualized 5G Core for Time Critical Communication in Smart Grid

Protection and automation in a smart grid environment often have stringent real-time communication requirements between devices within a substation, as well as between distantly located substations. The Generic Object Oriented Substation Event (GOOSE) protocol has been proposed to achieve this goal as it allows to transfer time-critical information within a few milliseconds. However, the transmission of GOOSE messages is often limited to a small Local Area Network (LAN). An earlier work has proposed to use the fifth generation of mobile networks (5G) as a means to transport IP-based GOOSE messages in a large-scale smart grid environment. On the basis of this work, this paper designs and implements an alternative solution for Ethernet-based GOOSE communication over a virtualized 5G core network that does not require any modification of the existing network protocol stack and thus is much easier to deploy. Our experimental results show that the delay introduced by the core network is in the order of sub milliseconds, while the one-way delay without a real radio access network, and without background traffic, is less than 1 ms. Moreover, these delays can be significantly reduced with a container-based deployment rather than a virtual machine-based one. Assuming a 1-ms delay budget for a 5G radio access network, our evaluation confirms that it is indeed feasible to use 5G for GOOSE transmission in IEC 61850 substation automation systems.
Correction for the misidentification of a shrew in Sakhalin by Abe et al. (1997), by analysis of the full nucleotide sequence of the mitochondrial cytochrome b gene

One shrew specimen which is identified as Sorex unguiculatus in Abe et al. (1997) was reexamined. Accerding to morphological characters and nucleotide sequences of the mitochondrial cytochreme b gene, {t is reidentified as Sorex isodon. METHODS AND RESUI;TS Abe et al. (1997) published a list of small rnammals inhabiting southern Sakha]in in PPfldtijle Conservation Japan, vol. 2, no. 1. , where they listed a ]ongclawed shrew from Trudovoe Village (location 9) as Sorex unguicutatus Dobson. Later, I, one of the authors of the former report, reexamined the specimen (specimen code, 94saklO) and found that it had gradually reducing tooth height from the fiTst to fifth unicuspids, much shoTter forefoot claws, and a greater value of"unicuspid Tow ]engthfupper tooth row length" (3.02 mmf8.75 mm) than ordinary S unguiculatus. According to Dolgov (1985), such characteristics are those for Sorex sinalis Thomas, and it is now widely accepted that S. sinalis in Sakhalin as described by Dolgov (1985) is known as dusky shrewl Sbrex isodon Turov (Hutterer, 1993). Moreover, to confirm the identification of 94saklO as S, isodon, I cempared the mitochondrial cytochrome b gene (1140 bases) full'nucleotide sequ nce of unambiguous S. unguicutatus specimens. First, the region which covers the who]e cytochrome b region was amplified by PCR, using a forward primer 5'AAAAACCMCGTTGITA[I'I'CAACT-3' (L14734) and a reverse primer 5'-[lldLGAATGTCAGCTTTGG GTGCT-3' (H15985). Primer codes in parentheses indicate the 3' end position of the equivalent human mitochondrial DNA (L, light strande and H, heavy strand). Next, the region was sequenced by an autosequencer (ABI Prism 377) using the dye-terminatormethod. Sequencing was conducted foT 94saklO and 30 S. unguiculatus from Hokkaido, Sakhalin, and Primorski territory. The sequence of 94saklO was easily distinguished from those of S. unguiculatus by dendrograms drawn by the neighborjoining and maximum parsimony mcthods (figures not shown). Forexarnple, the bootstrap value of the monophy]y of the 30 S. unguiculatus analyzed was 100% (1000 replications), indicating that the identified S. isodon is clustered out of S, unguiculatus, in the neighbor joining method with multiple substitution correction (Thompson et al., 1994) when a pig (Randi et al., 1996) is an outgroup. Sequences of 94saklO and two S. unguicutatus specimens from Hokkaido and Sakhalin are shown in Fig. 1. Based on the morphological and molecular characteristics mentioned above, 94saklO in Trudovoe Village in Abe et al. (1996) identified as S. unguiculatus must be changed to S. isodon, Sorex isodon has been previous]y recorded in southern Sakhalin (e.g,, Nbronov, 1974; Dolgov, 1985), but was not recorded by Abe et al. (1997) due to misidentification, I would like to thank R. Masuda, M, Ashida, and
The complete mitochondrial genome of chlorella sp. Dachan (Chlorellaceae: Chlorella)

Abstract The Chlorella sp. Dachan belongs to the genus Chlorella. Chlorella sp is widely distributed in the fresh water area with the largest number of species. It is easy to cultivate and propagate and it can use photosynthesis with high application value. In this study, the complete nucleotide sequence of the circular mitochondrial (mt) DNA of the chlorophyte alga C. sp. Dachan has been determined (55,450 base-pairs, A + T content 71.69%). The genes identified encode three subunits of the cytochome oxidase, apocytochrome b, seven subunits of the NADH dehydrogenase complex (nad1 3 4 5 7 9 and 4 L), three ATPase subunits (atp1, atp6, atp9), two ribosomal RNAs small subunit (srn) and large subunit (lrn) RNA), 27 tRNAs, 2 ribosome proteins. The complete mitochondrial genome sequence will provide new molecular biology information to further understand the genetic diversity of the Chlorella sp. Dachan and to protect this population.
The effect of host–guest interaction in tourist co-creation in public services: evidence from Hangzhou

ABSTRACT This study focuses on tourist co-creation in the public service context, an area that has received limited attention in tourism studies. By utilizing a survey with a sample of 458 responses from on-site tourists in Hangzhou, China, this study explored how host–guest interactions at the destination motivate tourists’ intention to participate in public service co-creation. The empirical analysis shows that different types of host–guest interaction in the public service context lead tourists to feel different dimensions of experiential value. Emotional and social experiential value play a full mediating role between host–guest interaction and co-creation intention.
Divergent male and female mate preferences do not explain incipient speciation between lizard lineages

Abstract Diversification in sexual signals is often taken as evidence for the importance of sexual selection in speciation. However, in order for sexual selection to generate reproductive isolation between populations, both signals and mate preferences must diverge together. Furthermore, assortative mating may result from multiple behavioral mechanisms, including female mate preferences, male mate preferences, and male–male competition; yet their relative contributions are rarely evaluated. Here, we explored the role of mate preferences and male competitive ability as potential barriers to gene flow between 2 divergent lineages of the tawny dragon lizard, Ctenophorus decresii, which differ in male throat coloration. We found stronger behavioral barriers to pairings between southern lineage males and northern lineage females than between northern males and southern females, indicating incomplete and asymmetric behavioral isolating barriers. These results were driven by both male and female mate preferences rather than lineage differences in male competitive ability. Intrasexual selection is therefore unlikely to drive the outcome of secondary contact in C. decresii, despite its widely acknowledged importance in lizards. Our results are consistent with the emerging view that although both male and female mate preferences can diverge alongside sexual signals, speciation is rarely driven by divergent sexual selection alone.
Shed+: Optimal Dynamic Speculation to Meet Application Deadlines in Cloud

With the growing deadline-sensitivity of cloud applications, adherence to specific deadlines is becoming increasingly crucial, particularly in shared clusters. A few slow tasks called stragglers can potentially adversely affect job execution times. Equally, inadequate slotting of data analytics applications could result in inappropriate resource deployment, ultimately damaging system performance. Against this backdrop, one effective way of tackling stragglers is by making extra attempts (or clones)<xref ref-type="fn" rid="fn1"><sup>1</sup></xref> for every single straggler after the submission of a job. This paper proposes Shed<inline-formula> <tex-math notation="LaTeX">$\pmb {+}$ </tex-math></inline-formula>, which is an optimization framework utilizing dynamic speculation that aims to maximize the jobs’ PoCD (Probability of Completion before Deadline) by making full use of available resources. Notably, our work encompasses a new online scheduler that dynamically recomputes and reallocates resources during the course of a job’s execution. According to our findings, Shed<inline-formula> <tex-math notation="LaTeX">$\pmb {+}$ </tex-math></inline-formula> successfully leverages cloud resources and maximizes the percentage of jobs meeting their deadlines. In our experiments, we have seen this percentage for heavy load going up to 98% for Shed<inline-formula> <tex-math notation="LaTeX">$\pmb {+}$ </tex-math></inline-formula> as opposed to nearly 68%, 40%, 35% and 37% for Shed, Dolly, Hopper and Hadoop with speculation enabled, respectively. <fn id="fn1"><label><sup>1</sup></label><p>Cloning or extra attempts means task duplication. </p></fn>
ViMo: Vital Sign Monitoring Using Commodity Millimeter Wave Radio

Accurate monitoring of human vital signs (e.g. breathing and heart rates) is crucial in detecting medical problems. In this paper, we propose ViMo, a calibration-free remote Vital sign Monitoring system that can simultaneously monitor multiple users by leveraging the channel impulse response (CIR) of 60GHz WiFi. By exploiting the periodicity introduced by respiration, we first propose a human detection algorithm which does not require any prior calibration. Then, we apply the auto-correlation function (ACF) of the CIR phase to estimate the breathing rate. Lastly, to mitigate the impact of the breathing signal on the weak heartbeat signal, the cubic spline interpolation is used to eliminate the breathing signal before the estimation of the heart rate. Extensive experiments show that ViMo can achieve a median accuracy of 0.19 BPM for breathing rate estimation and 1 BPM for heart rate estimation, out-performing the existing non-contact solutions that are purely based on frequency analysis.
Personality Traits and Self-Compassion in Relation to Psychological Well-Being in Farhangian University Students: A Cross-Cultural Study

Purpose : It has been well established that personality traits and self-compassion are associated with psychological well-being, thus, the current research aimed to investigate the underlying mechanisms in a collectivist culture. Methodology : The present study was a descriptive correlational one in terms of purpose and in terms of data collection. Quantitative research approach was used. Male and female University students of Ahvaz Farhangian University were considered as a studies population. For the purpose of the research, 150 students were selected as a sample using voluntary-available sampling method. for measurement Ryff Psychological Well-Being Scale, the NEO Personality Inventory, and Neff's Self-Compassion Scale. Findings : The results of correlation analysis showed that there were significant relationships between the personality traits (neuroticism, extraversion, agreeableness, and conscientiousness) and self-compassion (self-kindness, isolation, mindfulness, and the total score of self-compassion) with psychological well-being. The regression analysis showed that neuroticism, extraversion, and conscientiousness significantly predicted psychological well-being. Discussion : The current research was one of the first Iranian studies which addressed to the issues with a cultural point of view. Also, this research tried to direct attention to other social factors influencing gender differences (e.g., traditional socialization) as well which are not discussed in other similar studies. The cultural implications and future orientations have been discussed.
HCP: Heterogeneous Computing Platform for Federated Learning Based Collaborative Content Caching Towards 6G Networks

A heterogeneous computing architecture is essential to facilitate intelligent network traffic control for a joint computation, communication, and collaborative caching optimization in 6G networks to provide stringent Quality of Experience (QoE) guarantees. In this paper, we consider a 6G integrated aerial-terrestrial network model where Unmanned Aerial Vehicles (UAVs) and terrestrial Remote Radio Heads (RRHs) jointly serve as heterogeneous Base Stations (hgNBs) of a Cloud Radio Access Network (HCRAN) serving different mobile user (UE) types. We propose a distributed heterogeneous computing platform (HCP) across the UAVs and terrestrial Base Stations (BSs) by utilizing their caching and cooperative communication capabilities. In order to preserve the privacy of the content of the UEs, we propose a 2-stage federated learning algorithm among the UEs, UAVs/BSs, and HCP to collaboratively predict the content caching placement by jointly considering traffic distribution, UE mobility and localized content popularity. An asynchronous weight updating method is adopted to avoid redundant learning transfer in the federated learning. Once the global model is learnt by the HCP, it transfers the learned model to the UEs to facilitate the much desired edge intelligence in the considered 6G tiny cell. The effectiveness of the proposal is evaluated by extensive numerical analysis.
Multifunctional Filtering Leaky-Wave Antenna Exhibiting Simultaneous Rapid Beam-Scanning and Frequency-Selective Characteristics Based on Radiative Bandpass Filter Concept

In this article, the concept of radiative bandpass filter (RBPF) is proposed and investigated for developing a class of multifunctional filtering leaky-wave antennas (LWAs) which exhibit the simultaneous rapid frequency-dependent beam-scanning and frequency-selective characteristics. A substrate-integrated waveguide (SIW) is periodically loaded with closed (nonradiative) discontinuities acting as a bandpass filter, where the lower and higher stopbands are, respectively, stemmed from the SIW natural cutoff and the Bragg effect bandgap or bandstop caused by periodic discontinuities. By adequately adjusting the periodicity of filter unit cells and loading effects of closed discontinuities, filtering and dispersion behaviors of the periodic SIW can be flexibly engineered. Open (radiative) discontinuities are then deliberately introduced into the bandpass filter to generate a controllable radiation leakage, thereby accomplishing the design of the RBPF, i.e., the proposed LWA. With this concept, both filtering/dispersion and radiation tasks can be independently managed by different modules for LWAs. For demonstration purposes, two kinds of closed discontinuities, namely nonradiative longitudinal slot-pair (capacitive) and iris (inductive), are separately exploited for periodic SIWs with bandpass and high dispersion characteristics, whereas transverse slot (open discontinuity) is mainly aimed for radiation leakage. Two RBPF-based LWAs are simulated, fabricated, and measured. The simulated and measured results are in a reasonable agreement, and both demonstrate the rapid beam-scanning and filtering behaviors, thereby validating the proposed concept.
3-D Acoustic Modeling for Far-Field Multi-Channel Speech Recognition

The conventional approach to automatic speech recognition in multichannel reverberant conditions involves a beamforming based enhancement of the multi-channel speech signal followed by a single channel neural acoustic model. In this paper, we propose to model the multi-channel signal directly using a convolutional neural network (CNN) based architecture which performs the joint acoustic modeling on the three dimensions of time, frequency and channel. The features that are input to the 3-D CNN are extracted by modeling the signal peaks in the spatio-spectral domain using a multivariate autoregressive modeling approach. This AR model is efficient in capturing the channel correlations in the frequency domain of the multi-channel signal. The experiments are conducted on the CHiME-3 and REVERB Challenge dataset using multi-channel reverberant speech. In these experiments, the proposed 3-D feature and acoustic modeling approach provides significant improvements over an ASR system trained with beamformed audio (average relative improvements of 16% and 6% in word error rates for CHiME-3 and REVERB Challenge datasets respectively).
Insulator Recognition and Fault Detection Using Deep Learning Approach

Uninterrupted power supply to electric power consumers has increasingly become a global necessity. Monitoring the health of distribution network is crucial to provide quality service. Traditional monitoring methods based on on-site patrols to detect faults have increasingly become labor-intensive and time-consuming, raising demand for new and more efficient techniques. To address this issue, we propose faster-RCNN by MXNet for both detection and classification tasks. We utilize convolutional neural network (CNN) for detecting and classifying both insulator components and faulty insulator discs from images captured on overhead electric power transmission systems. Using a dataset of images acquired through UAV (unmanned aerial vehicle) captures, detection and classification is dealt with by dividing the picture content of the training set into three classes: background, insulator and the defective part of insulator. We achieve target insulator recognition and positioning with impressive precision compared to other traditional technologies. Our work could have practical integrated implementation solutions for automated inspection of overhead transmission power line insulators. The code used can be found at https://github.com/QgZhan/Insulator-Defect-Detection.
IoT-Enabled Flood Severity Prediction via Ensemble Machine Learning Models

River flooding is a natural phenomenon that can have a devastating effect on human life and economic losses. There have been various approaches in studying river flooding; however, insufficient understanding and limited knowledge about flooding conditions hinder the development of prevention and control measures for this natural phenomenon. This paper entails a new approach for the prediction of water level in association with flood severity using the ensemble model. Our approach leverages the latest developments in the Internet of Things (IoT) and machine learning for the automated analysis of flood data that might be useful to prevent natural disasters. Research outcomes indicate that ensemble learning provides a more reliable tool to predict flood severity levels. The experimental results indicate that the ensemble learning using the Long-Short Term memory model and random forest outperformed individual models with a sensitivity, specificity and accuracy of 71.4%, 85.9%, 81.13%, respectively.
User Acceptance Test for Kaaba Buku Saku Application

As one of the countries with a big Muslim population in the world, opportunity of growing an Islamic business in Indonesia has swiftly gained. It is proved by the growth of 95% market share in manufacture, service, and technology areas. This will give a chance for entrepreneurs to follow the wave. One of the entrepreneurs that utilized the opportunity is the developer of Kaaba Buku Saku application. They are releasing solutions for Muslims in a form of mobile applications. Since the launching of this application, Kaaba Buku Saku generates only 30% active user from the total downloader. By using Binary Logistic Regression, it is known that Facilitating Conditions was a significant variable that means the customer would prefer to adopt the application when they have a sufficient resources and knowledge to adopt it. From the customer journey map, it is known that the improvements that should be made by the developer are equipped the prayer time feature with automatically locate feature, adjust the highlight content to be more understandable, launch live location feature for Hajj and Umrah users, give a step by step guidance for the first use, give notification to calibrate the phone for Qibla feature, and the last is launch their iOS version application. Keywords: Muslim-based mobile application, Kaaba buku saku, binary logistic regression, customer journey map