Miracle-dz/UniFAR-FTUs huggingface dataset:
Homeostasis drives intense microbial trace metal processing on marine particles

As marine microorganisms and environmental conditions coevolved over geological timescales, metals have been incorporated into all essential metabolic processes. In the modern ocean, metals are present from trace amounts limiting microbial growth to toxic concentrations. Dissolved trace metals are a major bioavailable reservoir. However, the acquisition of metals from marine particles remains largely unexplored. Here, we combined chemical characterization and a comparative metatranscriptomics approach to investigate the availability of nine metals of biological importance on particles collected in the region of Heard Island (Indian sector of the Southern Ocean). Elemental ratios identified particulate matter as a potential source of metals for prokaryotes. The expression of genes for the uptake of metals through various mechanisms demonstrated that particles are a bioavailable reservoir. But genes involved in the control of resistance to metal toxicity, storage, sensing, and regulation were also highly expressed. Our observations suggest that homeostasis associated with a diverse prokaryotic community is the overarching mechanism that enhances the trace element processing on particles. These results provide clues that microbial activity on particles is critical in the redistribution of trace elements between different fractions and chemical forms in the ocean.
Effect of Intensification Practices, Lambing Period and Environmental Parameters on Animal Health, and Milk Yield and Quality in Dairy Sheep Production Systems on Crete

Due to increasing demand, many traditional, grazing-based Mediterranean sheep production systems have introduced intensified feeding regimes, increased investments in infrastructure and drug use to increase milk yields. However, compared to bovine milk production systems, there is limited knowledge about the impact of these intensification practices on animal welfare and health and on the quality of dairy products. The aim of this study was therefore to quantify the effects of management practices and environmental conditions background on udder health, parasitism and milk quantity and quality in Cretan traditional production systems. Milk yields were higher in semi-intensive production systems while concentrations of several nutritionally desirable compounds such as omega-3 fatty acids were found to be higher in milk from extensive systems. Antibiotic and anthelmintic use was relatively low in both extensive and semi-intensive production systems. There was no substantial difference in parasitic burden, somatic cell counts, and microbiological parameters assessed in milk. Recording of flock health parameters showed that animal health and welfare was high in both extensive and semi-intensively managed flocks, and that overall, the health status of extensively managed ewes was slightly better. In contrast, environmental conditions (temperature and rainfall) had a substantial effect on parasitism and milk quality.
The Model for The Classification of The Ripeness Stage of Pomegranate Fruits In Orchards Using

In agriculture, a timely and accurate estimate of ripeness in the orchard improves the post-harvest process. Choosing fruits based on their maturity stages can reduce storage costs and increase market results. In addition, the estimation of the ripeness of the fruit based on the detection of input and output indicators has brought about practical effects in the harvesting process, as well as determining the amount of water needed for irrigation. pepper, the amount of fertilizer for the end of the season appropriate. In this paper, propose a technical solution for a model to detect persimmon green grapefruit fruit at agricultural farms, Vietnam. Aggregation model and transfer learning method are used. The proposed model contains two object detection sub models and the decision model is the pre-processed model, the transfer model and the corresponding aggregation model. Improving the YOLO algorithm is trained with more than one hundred object types, the total proposed processing is 500,000 images, from the COCO image data set used as a preprocessing model. Aggregation model and transfer learning method are also used as an initial step to train the model transferred by the transfer learning technique. Only images are used for transfer model training. Finally, the aggregation model with the techniques used to make decisions selects the best results from the pre-trained model and the transfer model. Using our proposed model, it has improved and reduced the time when analyzing the maximum number of training data sets and training time. The accuracy of model union is 98.20%. The test results of the classifier are proposed through a data set of 10000 images of each layer for sensitivity of 98.2%, specificity 97.2% with accuracy of 96.5% and 0, 98 in training for all grades.
Tracking Control of Autonomous Underwater Vehicles with Acoustic Localization and Extended Kalman Filter

The absence of global positioning system (GPS) signals and the influence of ocean currents are two of the main challenges facing the autonomy of autonomous underwater vehicles (AUVs). This paper proposes an acoustic localization-based tracking control method for AUVs. Particularly, three buoys that emit acoustic signals periodically are deployed over the surface. Times of arrivals of these acoustic signals at the AUV are then obtained and used to calculate an estimated position of the AUV. Moreover, the uncertainties involved in the localization and ocean currents are handled together in the framework of the extended Kalman filter. To deal with system physical constraints, model predictive control relying on online repetitive optimizations is applied in the tracking controller design. Furthermore, due to the different sampling times between localization and control, the dead-reckoning technique is utilized considering detailed AUV dynamics. To avoid using the highly nonlinear and complicated AUV dynamics in the online optimizations, successive linearizations are employed to achieve a trade-off between computational complexity and control performance. Simulation results show that the proposed algorithms are effective and can achieve the AUV tracking control goals.
TalkNet: Non-Autoregressive Depth-Wise Separable Convolutional Model for Speech Synthesis

We propose TalkNet, a non-autoregressive convolutional neural model for speech synthesis with explicit pitch and duration prediction. The model consists of three feed-forward convolutional networks. The ﬁrst network predicts grapheme durations. An input text is then expanded by repeating each symbol according to the predicted duration. The second network predicts pitch value for every mel frame. The third network generates a mel-spectrogram from the expanded text conditioned on predicted pitch. All networks are based on 1D depth-wise separable convolutional architecture. The explicit duration prediction eliminates word skipping and repeating. The quality of the generated speech nearly matches the best auto-regressive models – TalkNet trained on the LJSpeech dataset got a MOS of 4 . 08 . The model has only 13.2M parameters, almost 2 x less than the present state-of-the-art text-to-speech models. The non-autoregressive architecture allows for fast training and inference. The small model size and fast inference make TalkNet an attractive candidate for embedded speech synthesis.
An Automatic, Simple Ultrasound Biofeedback Parameter for Distinguishing Accurate and Misarticulated Rhotic Syllables

Characterizing accurate vs. misarticulated patterns of tongue movement using ultrasound can be challenging in real time because of the fast, independent movement of tongue regions. The usefulness of ultrasound for biofeedback speech therapy is limited because speakers must mentally track and compare differences between their tongue movement and available models. It is desirable to automate this interpretive task using a single parameter representing deviation from known accurate tongue movements. In this study, displacements recorded automatically by ultrasound image tracking were transformed into a single biofeedback parameter (time-dependent difference between blade and dorsum displacements). Receiver operating characteristic (ROC) curve analysis was used to evaluate this parameter as a predictor of production accuracy over a range of different vowel contexts with initial and final /r/ in American English. Areas under ROC curves were 0.8 or above, indicating that this simple parameter may provide useful real-time biofeedback on /r/ accuracy within a range of rhotic contexts.
Southern Italian Peripheries at the Ballot Box. Continuity and Innovation in Electoral Behaviours in Three Southern Italian Cities during Post-Crisis Decade (2008–2019)

ABSTRACT The article explores the social and political geography of three southern Italian cities – Bari, Napoli and Reggio Calabria – and investigates inside their centre–periphery cleavage, highlighting whether and how peripheral conditions affect electoral behaviours. It provides a multidimensional statistical analysis based on I.S. T.A. T. data on Italian cities and suburbs and on the results of the political and European elections during the post-economic crisis decade (2008–2019). The study highlights a growing predictive power, after the 2008 crisis, of the peripheral condition on the electoral behaviour, the weakening of the centre-left parties and the specular political success of 5-Star Movement (M.5.S.) in deprived urban areas.
Dialogue Situation Recognition for Everyday Conversation Using Multimodal Information

In recent years, dialogue systems have been applied to daily living. Such systems should be able to associate conversations with dialogue situations, such as a place where a dialogue occurs and the relationship between participants. In this study, we propose a dialogue situation recognition method that under-stands the perspective of dialogue scenes. The target dialogue situations contain dialogue styles, places, activities, and relations between participants. We used the Corpus of Everyday Japanese Conversation (CEJC), which records natural everyday conversations in various situations for experiments. We experimentally veriﬁed the effectiveness of our proposed method us-ing multimodal information for situation recognition.
Failure Mode and Effect Analysis for a Programmable Logic Controller-Based Control Unit for a Miniature Neutron Source Reactor Pneumatic Transfer System

The Pneumatic Transfer System (PTS) is an auxiliary system of Ghana Research Reactor-1 (GHARR-1) used to transfer the sample capsule in and out of the reactor irradiation sites. The PTS′ controller unit design and construction was carried out because the original transfer system was not designed to operate in Cyclic Neutron Activation Analysis (CNAA). To address these situations, a Programmable Logic Controller (PLC) has been used to design and construct a control unit to facilitate a CNAA application for GHARR-1. The design has been simulated successfully using LOGO! Soft Comfort software, version 8. A Failure Mode and Effect Analysis (FMEA) was conducted on the PTS Control Unit (PTSCU) to evaluate and document, by item failure mode analysis, the potential impact of each functional or hardware failure of the control unit, personnel and system safety, system performance, maintainability, and maintenance requirements. Each potential failure is ranked by the severity of its effect so that appropriate corrective actions can be taken to eliminate or control the high-risk items. The result obtained upon the analysis shows that the likelihood of occurrence of failures, detection, and severity on the control unit is low per the risk priority number. The paper outlines the severity classification and description used in FMEA, the likelihood of detecting various failures of components, and failure causes and effect.
A Comparison of Acoustic Correlates of Voice Quality Across Different Recording Devices: A Cautionary Tale

There has been a recent increase in speech research utilizing data recorded with participants' personal devices, particularly in light of the COVID-19 pandemic and restrictions on face-toface interactions. This raises important questions about whether these recordings are comparable to those made in traditional lab-based settings. Some previous studies have compared the viability of recordings made with personal devices for the clinical evaluation of voice quality. However, these studies rely on simple statistical analyses and do not examine acoustic correlates of voice quality typically examined in the (socio-) phonetic literature (e.g. H1-H2). In this study, we compare recordings from a set of smartphones/laptops and a solid-state recorder to assess the reliability of a range of acoustic correlates of voice quality. The results show significant differences for many acoustic measures of voice quality across devices. Further exploratory analyses demonstrate that these differences are not simple offsets, but rather that their magnitude depends on the value of the measurement of interest. We therefore urge researchers to exercise caution when examining voice quality based on recordings made with participants' devices, particularly when interested in small effect sizes. We also call on the speech research community to investigate these issues more thoroughly. Copyright © 2021 ISCA.
Investigating Speech Reconstruction for Laryngectomees for Silent Speech Interfaces

Silent speech interfaces (SSIs) are devices that convert non-audio bio-signals to speech, which hold the potential of recovering quality speech for laryngectomees (people who have undergone laryngectomy). Although signiﬁcant progress has been made, most of the recent SSI works focused on data collected from healthy speakers. SSIs for laryngectomees have rarely been investigated. In this study, we investigated the reconstruction of speech for two laryngectomees who either use tra-cheoesophageal puncture (TEP) or electro-larynx (EL) speech as their post-surgery communication mode. We reconstructed their speech using two SSI designs (1) real-time recognition-and-synthesis and (2) directly articulation-to-speech synthesis (ATS). The reconstructed speech samples were measured in subjective evaluation by 20 listeners in terms of naturalness and intelligibility. The results indicated that both designs increased the naturalness of alaryngeal speech. The real-time recognition-and-synthesis design obtained higher intelligibility in electro-larynx speech as well, while the ATS did not. These prelimi-nary results suggest the real-time recognition-and-synthesis design may have a better potential for clinical applications (for laryngectomees) than ATS.
Interseismic deformation in the Gulf of Aqaba from GPS measurements

Although the Dead Sea Transform (DST) fault system has been extensively studied in the past, little has been known about the present-day kinematics of its southernmost portion that is offshore in the Gulf of Aqaba. Here, we present a new GPS velocity field based on three surveys conducted between 2015 and 2019 at 30 campaign sites, complemented by 11 permanent stations operating near the gulf coast. Interseismic models of strain accumulation indicate a slip rate of $4.9^{+0.9}_{-0.6}~\mathrm{ mm}\,\mathrm{ yr}^{-1}$ and a locking depth of $6.8^{+3.5}_{-3.1}~\mathrm{ km}$ in the gulf’s northern region. Our results further indicate an apparent reduction of the locking depth from the inland portion of the DST towards its southern junction with the Red Sea rift. Our modelling results reveal a small systematic left-lateral residual motion that we postulate is caused by, at least in part, late post-seismic transient motion from the 1995 MW 7.2 Nuweiba earthquake. Estimates of the moment accumulation rate on the main faults in the gulf, other than the one that ruptured in 1995, suggest that they might be near the end of their current interseismic period, implying elevated seismic hazard in the gulf area.
URLLC Performance Under Outdated Channel State Information and Generalised-Rician Fading

Under ultra-reliable and low-latency communications (URLLC) for modern and future wireless networks, this work studies block-length-error probability (BLE) over an outdated-channel-state-information (oCSI) relay network deploying maximal ratio combining. Impact of finite-blocklength regimes on hybrid-automatic-repeat-request protocols with a finite pilot length is also studied. The network is operating under a generalised-Rician fading environment, which covers both line-of-sight (LoS) and non-LoS. The BLE is computed as a function of a bandwidth, payload, an oCSI coefficient, a diversity order and LoS power. Reliability-latency trade-off and effects of other parameters to URLLC performance are examined and discussed. Impact of system incoherence on URLLC performance will also be studied.
Genetic evidence for the invasion of Cymbella janischii (A. Schmidt) De Toni in Japan

Cymbella janischii (A. Schmidt) De Toni, an endemic diatom of the Pacific Northwest, was found in 2006 in Japan, and since then, its distribution has been expanding. It was identified on the basis of morphology in Japan, however, molecular analyses have not yet been performed, with no sequences known of genes derived from the Japanese isolate. Here, we analyzed rbcL, psaB, psbA, 18S rRNA, and 28S rRNA gene sequences (6526 bp in total) of the C. janischii specimens from several locations in Japan and explored their genetic relatedness with C. janischii from its country of origin (the United States) and its closely related species. We showed that all Japanese specimens had the same sequences, regardless of geographical distance, and formed a clade with the US C. janischii. The identities and the pairwise distance between the sequences of the Japanese and the US diatoms were 99.937% and 0.0003, respectively, indicating that these diatoms are extremely similar. These results provide potential genetic evidence of the recent invasion and rapid spread of C. janischii from the US in Japan.
A University Teachers’ Teaching Performance Evaluation Method Based on Type-II Fuzzy Sets

This paper proposes a university teachers’ teaching performance evaluation method based on type-II fuzzy sets (T2 FSs), which solves the problems of fuzziness, complexity and uncertainty in teaching performance evaluation. Firstly, the evaluation indicator system is constructed from the aspects of teaching attitude, teaching contents, teaching professionalism, teaching methods and teaching effects. Then, T2 FSs theory and the perceptual computing method are introduced to model subjective judgments and capture uncertainties, effectively handling higher levels of uncertainty in the evaluation process. Furthermore, the linguistic weighted average operator is applied as the computing with words engine to aggregate scores and weights of indicators, which effectively integrates the uncertain information in the input data into the final evaluation conclusion and guarantees the accuracy of the evaluation results. Finally, the effectiveness of the method of this study is evaluated by simulation experiments. The computational results demonstrate that it can capture more uncertain and complex information, and is more accurate and reliable than the type-I fuzzy sets method.
Flow characteristics and noise reduction effects of air cleaners of automobile intake systems with built-in resonators with space efficiency

In an automobile intake system, Helmholtz resonator is often used to reduce intake noise. But there is a disadvantage in the engine room. Resonator brings low engine room space efficiency, because resonator needs some. In this paper, we propose air cleaner with built-in resonator for a limited space of air cleaner and analyze the pressure drop effect and the transmission loss performance of the resonator through flow analysis. The air cleaner with a built-in resonator had almost no difference in pressure drop with the conventional air cleaner. Some vortex in conventional air cleaner is removed, and also, the built-in resonator has noise reduction effect at 160Hz at 61dB such as same resonator.
Hydrogels in the removal of industrial pollution: Adsorption characteristics for the removal of a toxic dye from aqueous solutions

Pollution of water resources with various organic and inorganic pollutants is one of the biggest challenges of the present age. These infections seriously threaten human health and the lives of plants and animals. To minimize the mischievous effects of polluted water, technology-based smart treatment methods are necessary for sustainable equipping of drinking water. Application of (AAC-co-AM)-g-MCC hydrogels for the percentage removal of dye Methyl volute MV, from aqueous solutions have been studied. The synthesized (AAC-co-AM)-g-MCC hydrogels was described via FTIR, Thermogravimetric analysis (TGA), and UV-visible spectroscopy. The experiments held out in batch method effect of the factor like the solution of pH, initial concentration dye, and solution of temperature on the removal percentage of dye was studied. Contact time was done in 120 min. The data appear that an amount of 0.08 g (AAC-co-AM)-g-MCC hydrogels showed maximum removal percentage capacity of dye (100 mg L-1). Maximum adsorption of MV dye was attained at pH 6.2. It was further proven the adsorption dye onto (AAC-co-AM)-g-MCC hydrogels followed the isotherm Langmuir while the kinetics studies detect that each adsorption method was pseudo-second-order. The thermodynamic factors like enthalpy (∆Ho), change in free energy (∆Go), and entropy (∆So) were determined, and the values negative of ∆Go indicated that the method of removal was spontaneous at wholly values of temperatures. Further, the values of ∆Ho indicated the endothermic nature of the method of removal.