Miracle-dz/UniFAR-FTUs huggingface dataset:
The Effectiveness of New Inspection Regime on Port State Control Inspection

Port state control (PSC) inspection is an important measure to improve ship safety and reduce ship accident rate. To improve the effectiveness of PSC inspections, some MoUs have begun to implement new inspection regime (NIR). However, the effectiveness of NIR remains to be studied. Then this study aims to verify the effectiveness of NIR and improve shipping safety. In this study, Bayesian Network model is used to establish the relationship between NIR, ship deficiencies, detention and ship accident to explore the impact of NIR on maritime safety. The data in this study are from PSC inspection data in the Tokyo Memorandum of Understanding (MoU) and accident data in the International Maritime Organization (IMO). By analyzing the changes of the number of ship deficiency, detention rate and accident rate before and after NIR implementation, the effectiveness of NIR can be verified. The results show that the implementation of NIR does not effectively reduce the number of substandard ships, but the number of ships with serious deficiencies is significantly reduced. However, ship accident rate has not declined. Therefore, it is believed that Tokyo MoU needs to further improve the effectiveness of NIR and strengthen supervision of defective ships.
The Potential Role of Probiotics (nutraceuticals) in Gut Health of Domestic Animals; an Alternative to Antibiotic Growth Promoters

The term gut health is currently becoming more important for domestic animals including poultry. Gut health refers to the fundamental organ system which covers multiple positive functions like effective digestion, stabilizing intestinal microbiota, gut pH and modulation of effective immune response. Gut health depends on proper balance of microbial population. A wide range of feed and pathogen associated factors influence this balance, and adversely affect the animal health status and production performance. Antibiotic stimulators have been used in farm animals to achieve maximum production. But drug resistance and residual effects of antibiotics in animal products (milk, meat and egg etc.) have raised serious issues in human life. Therefore, The European Union (EU) has strictly banned the application of antibiotic stimulators in livestock nutrition in several others countries including China. As a result, an alternative to antibiotic growth promoters are required to support the profitable and sustainable animal production system. Probiotics as nutraceuticals has been categorized as an alternative natural feed supplement for commercial utilization. Such products have been recognized as safe feed additives in animal industry. Very few studies have comparatively described the effect of probiotics on gut health of domestic animals. Therefore, the aim of this review is not only to explore the beneficial effects of probiotics in improving gut health of domestic animals as an alternative to antibiotic growth promoters, but also to evaluate the probiotics associated health and risk factors, and to provide comprehensive scientific information for researchers, scientists and commercial producers.
Deep Learning Methods in Communication Systems: A Review

With the rapid development of modern communication systems, the amount of data has exploded, the system structure has become increasingly complex, and existing communication theories and technologies are facing huge challenges. The successful application of deep learning technology in the fields of images, speech, natural language processing, and games provides a possible solution for the theory and technology of communication systems that goes beyond traditional ideas and performance. This article mainly summarizes the application cases of deep learning methods in channel estimation, signal detection, and modulation recognition, and shows their outstanding performance compared to traditional communication theory and technology. Finally, we analyze the opportunities and challenges faced by deep learning-based communication technologies.
Sleep-related breathing disorders and pulmonary hypertension

Sleep-related breathing disorders (SBDs) include obstructive apnoea, central apnoea and sleep-related hypoventilation. These nocturnal events have the potential to increase pulmonary arterial pressure (PAP) during sleep but also in the waking state. “Pure” obstructive sleep apnoea syndrome (OSAS) is responsible for a small increase in PAP whose clinical impact has not been demonstrated. By contrast, in obesity hypoventilation syndrome (OHS) or overlap syndrome (the association of chronic obstructive pulmonary disease (COPD) with obstructive sleep apnoea (OSA)), nocturnal respiratory events contribute to the development of pulmonary hypertension (PH), which is often severe. In the latter circumstances, treatment of SBDs is essential in order to improve pulmonary haemodynamics. Patients with pulmonary arterial hypertension (PAH) or chronic thromboembolic pulmonary hypertension (CTEPH) are at risk of developing SBDs. Obstructive and central apnoea, as well as a worsening of ventilation–perfusion mismatch, can be observed during sleep. There should be a strong suspicion of SBDs in such a patient population; however, the precise indications for sleep studies and the type of recording remain to be specified. The diagnosis of OSAS in patients with PAH or CTEPH should encourage treatment with continuous positive airway pressure (CPAP). The presence of isolated nocturnal hypoxaemia should also prompt the initiation of long-term oxygen therapy. These treatments are likely to avoid worsening of PH; however, it is prudent not to treat central apnoea and Cheyne–Stokes respiration (CSR) with adaptive servo-ventilation in patients with chronic right-heart failure because of a potential risk of serious adverse effects from such treatment. In this review we will consider the current knowledge of the consequences of SBDs on pulmonary haemodynamics in patients with and without chronic respiratory disease (group 3 of the clinical classification of PH) and the effect of treatments of respiratory events during sleep on PH. The prevalence and consequences of SBDs in PAH and CTEPH (groups 1 and 4 of the clinical classification of PH, respectively), as well as therapeutic options, will also be discussed. In some clinical situations, important to identify, sleep-related breathing disorders can be responsible for severe pulmonary haemodynamic consequences. In these situations, it is important to treat apnoeas, hypopnoeas and nocturnal oxygen desaturations. https://bit.ly/30akkoM
A Configurable Noise-Shaping Band-Pass SAR ADC With Two-Stage Clock-Controlled Amplifier

This article presents an $8\times $ -oversampling successive approximation register (SAR) analog-to-digital converter (ADC) with configurable center frequency of noise shaping (NS), which permits the signal passband being configured to any one of the 8 equally divided sub-bands in the first Nyquist band. The configurable noise shaping is realized by an error-feedback (EF) structure with an adjustable 2-tap switched-capacitor (SC) FIR filter. Taking advantage of the sub-bands’ symmetry, the selection of the 8 sub-bands are determined by only a 2-bit controlled variable capacitor in the FIR filter in addition to one bit indicating which half-band the target sub-band is in. As a result, the configuration circuit is area efficient and introduces very little parasitic into the critical EF path. A 2-stage clock-controlled amplifier (CAMP) is proposed for the EF path, which can ensure gain and speed simultaneously through allocating reasonable currents into the gain stage and the driving stage separately. Implemented in 65-nm CMOS process, measurement results under a sampling rate of 10 MSPS show that the prototype achieves signal-to-noise-and-distortion (SNDR) of 71.9~74.6 dB in the 8 sub-bands with 625-KHz bandwidth, corresponding to a Scherier FoM of 171.4 -174 dB. The ADC prototype occupies 0.03-mm2 core area and consumes 70- $\mu \text{W}$ average power at 1-V supply voltage.
Ballroom Dancing for Community-dwelling Older Adults: A 12-month Study of the Effect on Well-being, Balance and Falls Risk

ABSTRACT Physical activities that involve muscle strengthening, balance and coordination skills such as ballroom dancing are encouraged for older adults to assist with the maintenance of functional autonomy and prevention of falls. Twenty-three community-dwelling older adults engaged in regular ballroom dancing completed a 12-month study assessing well-being, falls risk and balance using a set of clinical outcome measures. Those attending ballroom dancing classes were more likely to be active older adults, with lower levels of BMI and obesity compared to the general population. Participants scored lower in the falls risk tests than normative values. Some of the results suggest a possible substantive finding for clinical practice and indicate ballroom dancing is an activity with good attrition and adherence rates among community-dwelling older adults that can improve well-being, balance and reduce falls risk as part of an active lifestyle.
Coordination in Coupled Arrays of Stiff Filaments—Modelling and Simulation

We present the mechanical model of an array of elastic filaments and simulate the response with different mechanical couplings. This class of systems is inspired by robust and elegant solutions for locomotion mechanics that have emerged in several small-scale biological entities in the form of beating protrusions, such as cellular cilia and eukaryotic flagella. The collective dynamics of cilia arrays reveals important features such as array alignments, two-phase asymmetric beating of individual filaments, and the emergence of metachronal coordination, which make them suitable for bio-inspired terrestrial and aquatic locomotion. The model presented here is the basis for further developments towards the design of terrestrial and aquatic locomotion systems for general purpose robotic devices.
Greening and Browning Trends of Vegetation in India and Their Responses to Climatic and Non-Climatic Drivers

It is imperative to know the spatial distribution of vegetation trends in India and its responses to both climatic and non-climatic drivers because many ecoregions are vulnerable to global climate change. Here we employed the NDVI3g satellite data over the span of 35 years (1981/82–2015) to estimate vegetation trends and corresponding climatic variables trends (i.e., precipitation, temperature, solar radiation and soil moisture) by using the Mann–Kendall test (τ) and the Theil–Sen median trend. Analysis was performed separately for the two focal periods—(i) the earlier period (1981/82–2000) and (ii) later period (2000–2015)—because many ecoregions experienced more warming after 2000 than the 1980s and 1990s. Our results revealed that a prominent large-scale greening trend (47% of area) of vegetation continued from the earlier period to the later period (80% of area) across the northwestern Plain and Central India. Despite climatologically drier regions, the stronger greening trend was also evident over croplands which was attributed to moisture-induced greening combined with cooling trends of temperature. However, greening trends of vegetation and croplands diminished (i.e., from 84% to 40% of area in kharif season), especially over the southern peninsula, including the west-central area. Such changes were mostly attributed to warming trends and declined soil moisture trends, a phenomenon known as temperature-induced moisture stress. This effect has an adverse impact on vegetation growth in the Himalayas, Northeast India, the Western Ghats and the southern peninsula, which was further exaggerated by human-induced land-use change. Therefore, it can be concluded that vegetation trend analysis from NDVI3g data provides vital information on two mechanisms (i.e., temperature-induced moisture stress and moisture-induced greening) operating in India. In particular, the temperature-induced moisture stress is alarming, and may be exacerbated in the future under accelerated warming as it may have potential implications on forest and agriculture ecosystems, including societal impacts (e.g., food security, employment, wealth). These findings are very valuable to policymakers and climate change awareness-raising campaigns at the national level.
Conservative confidence intervals on multiple correlation coefficient for high-dimensional elliptical data using random projection methodology

ABSTRACT So called multiple correlation coefficient (MCC) is a measure of linear relationship between a given variable and set of covariates. In the multiple correlation and regression analysis, it is common practice to construct a confidence interval for the population MCC. In high-dimensional data settings, by which the data dimension p is much larger than the sample size n, due to the singularity of the sample covariance matrix, the classical confidence intervals for the MCC are no longer useable. For high-dimensional elliptical data, some (conservative) confidence intervals for the population MCC are presented using the random projection methodology. To evaluate and compare the performance of the proposed confidence intervals, some simulations are conducted in terms of the coverage probability and average interval length. Experimental validation of the proposed intervals is carried out on two real gene expression datasets.
Optical properties of small silver particles embedded in soda-lime silica glasses

The optical characteristics of silver nanoparticles embedded in a surface layer of commercial soda lime silica glass have been analysed. Additional results were obtained by the transmission electron microscopy observations and the selective area electron diffraction patterns. In this report, we have shown the effect of deviation from the spherical shape and non-homogeneous distribution on the optical characteristics of the Ag nanocrystals embedded in the dielectric matrix under study.
Mapping the Intertidal Microphytobenthos Gross Primary Production Part I: Coupling Multispectral Remote Sensing and Physical Modeling

The gross primary production (GPP) of intertidal mudflat microphytobenthos supports important ecosystem services such as shoreline stabilization and food production, and it contributes to blue carbon. However, monitoring microphytobenthos GPP over a long-term and large spatial scale is rendered difficult by its high temporal and spatial variability. To overcome this issue, we developed an algorithm to map microphytobenthos GPP in which the following are coupled: (i) NDVI maps derived from high spatial resolution satellite images (SPOT6 or Pléiades), estimating the horizontal distribution of the microphytobenthos biomass; (ii) emersion time, photosynthetically active radiation (PAR), and mud surface temperature simulated from the physical model MARS-3D; (iii) photophysiological parameters retrieved from Production–irradiance (P–E) curves, obtained under controlled conditions of PAR and temperature, using benthic chambers, and expressing the production rate into mg C h–1 m–2 ndvi–1. The productivity was directly calibrated to NDVI to be consistent with remote-sensing measurements of microphytobenthos biomass and was spatially upscaled using satellite-derived NDVI maps acquired at different seasons. The remotely sensed microphytobenthos GPP reasonably compared with in situ GPP measurements. It was highest in March with a daily production reaching 50.2 mg C m–2 d–1, and lowest in July with a daily production of 22.3 mg C m–2 d–1. Our remote sensing algorithm is a new step in the perspective of mapping microphytobenthos GPP over large mudflats to estimate its actual contribution to ecosystem functions, including blue carbon, from local and global scales.
How Accurately Can Satellite Products (TMPA and IMERG) Detect Precipitation Patterns, Extremities, and Drought Across the Nepalese Himalaya?

This study aims to assess the accuracy of two satellite‐based precipitation products (SBPPs), that is, Tropical Rainfall Measurement Mission (TRMM)‐based Multi‐satellite Precipitation Analysis (TMPA) and its upgraded version Integrated Multi‐Satellite Retrievals for Global Precipitation Measurement (IMERG), in capturing spatial and temporal variation of precipitation and their application for extreme events (high‐intensity precipitation and drought). They were evaluated against 142‐gauge stations from Nepal during 2001–2018. The results show that, in general, both SBPPs show the overall characteristics of precipitation patterns, although underestimated the mean annual precipitation during the study period. It was also noted that IMERG product yields better performance to detect precipitation events (probability of detection) and no‐precipitation events (false alarm ratio) than TMPA. Based on four different extreme precipitation indices: heavy precipitation events (R10mm), extreme precipitation events (R25mm), five consecutive dry days (CDD), and five consecutive wet days (CWD), it was observed that the SBPPs underestimated the frequency of R25mm and CDD spells while overestimated R10mm and CWD spells. Additionally, both SBPPs exhibited considerable capabilities in capturing the drought events during the study period. Overall, the drought event, bias, and frequency show that the IMERG product has slightly better capabilities to capture drought than the TMPA product. In general, IMERG was found to be superior at a daily timescale, while TMPA shows consistent performance on a monthly scale during the study period. Furthermore, there is still space for further improvement of IMERG rainfall retrieval algorithms.
Fibroblast-Like Limbal Stem Cells (F-Lscs) as a Potential Tool to Promote Tolerance Induction in Autoimmunity Diseases

Despite the countless and intensive research efforts, there is an increasing need to reverse the immunological dysfunctions on which any autoimmune disease is based. Recent evidences has shown in mesenchymal stem cells (MSCs) pleiotropic immune regulatory activities both in vitro and in vivo [1]. In particular MSCs seem to be receptive to inflammatory signals and able to mount peculiar tolerogenic immune responses, restoring the immune homeostasis. Unfortunately the immunosuppressive mechanisms mediated by MSCs are only partially understood with sometimes contradictory data available. Several in vitro data have demonstrated that the proliferation of T cells stimulated with either polyclonal mitogens, allogeneic cells or specific antigens is inhibited by MSCs through the arrest of lymphocytes in the G0/G1 phase of the cell cycle [2-4]. This non-classical form of anergy has been indicated as “tolerance arrest” of T cells [5]. In addition, MSCs have also been reported to influence the cytokine secretion profile of different T-cell subsets, causing decreased production of pro-inflammatory cytokines like interferon (IFN)-γ, tumor necrosis factor (TNF)-α and interleukin (IL)6, IL-17, and increased levels of anti-inflammatory cytokines such as IL-4 and IL-10 [6-8]. Taken together, these results could indicate a possible MSC-mediated restoration of Th1/Th2/Th3 unbalance in all those pathologies that require the expansion of Foxp3+ regulatory T cells, polarization of macrophages and T helper subsets and inhibition of antigen-presenting cells.
Pengaruh Net Working Capital Dan Debt To Equity Ratio Terhadap Return On Equity Pada PT Astra International Tbk

Penelitian ini bertujuan untuk mengetahui pengaruh antara Net Working Capital dan Debt to Equity Rasio terhadap Return On Equity pada PT. Astra Internasional Tbk. Pengumpulan data yang digunakan adalah teknik dokumentasi, data yang dikumpulkan dianalisis dengan rumus dari masing-masing rasio keuangan kemudian diolah dengan menggunakan uji asumsi klasik, analisis regresi berganda, analisis korelasi berganda, analisis koefisien determinasi, Uji t dan Uji F. Uji asumsi klasik yang diperoleh menunjukkan 1) data dalam penelitian ini berdistribusi normal, 2) antara variabel tidak terjadi masalah multikolineritas didalam hasil regresi tersebut, 3) tidak terjadi masalah heteroskedasitas, 4) tidak terjadi autokorelasi. Hasil analisis regresi berganda menunjukkan persamaan Y = 14,497 - 0,001X 1 + 0,189X 2 + e, maka hasil penelitian dapat disimpulkan bahwa secara parsial Net Working Capital berpengaruh negatif dan signifikan terhadap Return On Equity dengan nilai signifikan sebesar 0,027 dan Debt to Equity Ratio berpengaruh positif dan tidak signifikan terhadap Return On Equity dengan nilai signifikan sebesar 0,273, secara simultan diperoleh Net Working Capital dan Debt to Equity Ratio berpengaruh positif dan signifikan terhadap Return On Equity dengan nilai signifikan sebesar 0,011. Sedangakan hasil Koefisien Determinasi yang diperoleh adalah sebesar 0,721, ini menunjukan bahwa pengaruh Net Working capital dan Debt to Equity Ratio terhadap Return On Equity adalah sebesar 0,721 atau 72,1%. sehingga sebesar 27,9% dipengaruhi oleh faktor lain diluar variabel bebas yang diteliti.
Typage moléculaire des maladies neurodégénératives dues à l’agrégation de la protéine alpha synucléine

Les synucleinopathies regroupent les maladies neurodegeneratives de Parkinson, les demences a corps de Lewy et l'atrophie multi-systematisee. Des etudes suggerent que les synucleinopathies seraient des maladies a prion. Aujourd'hui, certains aspects manquent pour que l'α-synucleine soit reconnue comme un prion. Par exemple, il est a demontrer que chaque synucleinopathie est causee par une souche precise d'α-synucleine. Durant ma these j’ai mis au point une methode d'amplification fiable des depots presents dans le cerveau des patients atteints de synucleinopathies. J’ai aussi documente les procedures de nettoyage a adopter envers des materiels souilles, par diverses fibres amyloides, afin de reduire le risque de contamination. Finalement, j’ai ete associe a une etude montrant les capacites de propagation d'assemblages d'α synucleine, dans un reseau de neurones humains en culture. Ces resultats permettront des etudes structurales, et fonctionnelles, des souches d’α-synucleine dans les synucleinopathies.
Grapevine clonal selection in Portugal: A different approach

The methodology for selection of an ancient grapevine variety conducted by PORVID (Portuguese Association for Grapevine Diversity) and the Portuguese Network for Grapevine Selection, focuses on quantitative genetic tools resulting in an integrated strategy that comprises two types of selected material – clonal and polyclonal – both carrying high genetic and economic gains for relevant agronomic and oenological traits. This work focused on the clonal selection methodology, particularly on the model for communication with users of selected materials (grape growers and winemakers). The approach is innovative, since detailed information of the whole experimental process leading to certified clones is provided, including predicted genetic gains for several traits and information about the clone's environmental stability (G × E interaction). This last analysis, combined with the utilisation of several certified clones (approximately 7), contributes to a better adaptation to environmental changes.