Miracle-dz/UniFAR-FTUs huggingface dataset:
Subjective Ratings of Sentences in Clear and Conversational Speech

To determine the feasibility of using subjective ratings of clarity to identify perceptual differences between clear and conversational speech and among different talkers, sentences produced by 8 talkers selected from the Ferguson Clear Speech Database (Ferguson, 2004) were presented to listeners with normal hearing. Listeners rated the clarity of each sentence on a scale of 1 to 7 (1 = lowest possible clarity; 7 = highest possible clarity ). Clarity ratings were significantly higher for clear than conversational speech and differed significantly among the talkers. Rated clarity was significantly correlated with vowel intelligibility and vowel space measures, but not with speaking rate. The results suggest that subjective clarity ratings are a useful and valid measure of perceptual differences between speaking styles and among talkers.
A Multimodal Fusion Model for Depression Detection Assisted by Stacking DNNs

Depression is a severe psychosocial pathology that causes mood changes, characterized by a strong feeling of hopelessness and deep sadness. In advanced stages, it can predispose patients to suicidal thoughts, highlighting the importance of ﬁnding methods that provide more accurate diagnoses. Traditional diagnosis relies on semi-structured interviews and complementary questionnaires. Combining these methods with careful data analysis that incorporates audiovisual and textual characteristics can obtain valuable clues about the presence of depression in individuals. Therefore, this study proposes a multimodal Ensemble Stacking Deep Neural Network model based on the analysis of facial expression characteristics, audio signals
Using deep neural networks and similarity metrics to predict and control brain responses

In the last ten years there has been an increase in using artificial neural networks to model brain mechanisms, giving rise to a deep learning revolution in neuroscience. This chapter focuses on the ways convolutional deep neural networks (DCNNs) have been used in visual neuroscience. A particular challenge in this developing field is the measurement of similarity between DCNNs and the brain. We survey similarity measures neuroscientists use, and analyse their merit for the goals of causal explanation, prediction and control. In particular, we focus on two recent intervention-based methods of comparing DCNNs and the brain that are based on linear mapping (Bashivan et al., 2019, Sexton and Love, 2022), and analyse whether this is an improvement. While we conclude explanation has not been reached for reasons of underdetermination, progress has been made with regards to prediction and control.
Towards ﬂexibility and robustness of LSM trees

Log-structured merge trees (LSM trees) are increasingly used as part of the storage engine behind several data systems, and are frequently deployed in the cloud. As the number of applications relying on LSM-based storage backends increases, the problem of performance tuning of LSM trees receives increasing attention. We consider both nominal tunings—where workload and execution environment are accurately known a priori—and robust tunings—which consider uncertainty in the workload knowledge. This type of workload uncertainty is common in modern applications, notably in shared infrastructure environments like the public cloud. To address this problem, we introduce Endure , a new paradigm for tuning LSM trees in the presence of workload uncertainty. Speciﬁcally, we focus on the impact of the choice of compaction policy, size ratio, and memory allocation on the overall performance. Endure considers a robust formulation of the throughput maximization problem and recommends a tuning that offers near-optimal throughput when the executed workload is not the same, instead in a neighborhood of the expected workload. Additionally, we explore the robustness of ﬂexible LSM designs by proposing a new uniﬁed design called K-LSM that encompasses existing designs. We deploy our robust tuning system, Endure , on a state-of-the-art key-value store, RocksDB, and demonstrate throughput improvements of up to 5 × in the presence of uncertainty. Our results indicate that the tunings obtained by Endure are more robust than tunings obtained under our expanded LSM design space. This indicates that robustness may not be inherent to a design, instead, it is an outcome of a tuning process that explicitly accounts for uncertainty.
An Analysis of the Environmental Matrix in the Adriatic Sea – Past and Future Projections

The main objective of the proposed work is to assess the environmental matrix in the Adriatic Sea and its expected dynamics in the near future. The attention is focused on the analysis of the wind and wave climate in this basin and to perform a joint evaluation of the wind and wave power resources. The analysis is structured in two-time intervals, each one covering a 30-year time slice. The first time interval represents the past and covers the historical reference period 1976-2005, while the second comprises the near future from 2041 to 2070, under the Representative Concentration Pathway scenario 4.5. For the same two periods, the wave climate and the wave power were evaluated based on the simulation results carried out with the Simulating WAves Nearshore spectral phase averaged model. An analysis of the past and future expected extreme events is carried out. A comprehensive picture of the expected wind and wave power dynamics in the Adriatic Sea is provided by the comparison between the results obtained in the past with those from the near future. The synergy between the wind and wave power is also evaluated for future development of joint wind–wave projects. This option represents a viable direction for the near future to balance wind and wave power.
Opinion: Stratospheric ozone – depletion, recovery and new challenges

Abstract. We summarise current important and well-established open issues related to the depletion of stratospheric ozone and discuss some newly emerging challenges. The ozone layer is recovering from the effects of halogenated source gases due to the continued success of the Montreal Protocol despite recent renewed production of controlled substances and the impact of uncontrolled very short-lived substances. The increasing atmospheric concentrations of greenhouse gases, such as carbon dioxide, methane (CH4) and nitrous oxide (N2O), have large potential to perturb stratospheric ozone in different ways, but their future evolutions, and hence impacts, are uncertain. Ozone depletion through injection of smoke particles has been observed following recent Australian wildfires. Further perturbations to the ozone layer are currently occurring through the unexpected injection of massive amounts of water vapour from the Hunga Tonga–Hunga Ha'apai volcano in 2022. Open research questions emphasise the critical need to maintain, if not expand, the observational network and to address the impending “satellite data gap” in global, height-resolved observations of stratospheric trace gases and aerosols. We will, in effect, be largely blind to the stratospheric effects of similar wildfire and volcanic events in the near future. Complex Earth system models (ESMs) being developed for climate projections have the stratosphere as an important component. However, the huge computational requirement of these models must not result in an oversimplification of the many processes affecting the ozone layer. Regardless, a hierarchy of simpler process models will continue to be important for testing our evolving understanding of the ozone layer and for providing policy-relevant information.
On Hierarchical Trafﬁc Grooming in WDM Networks

— The trafﬁc grooming problem is of high practical importance in emerging wide-area wavelength division multiplexing (WDM) optical networks, yet it is intractable for any but trivial network topologies. In this work, we present an effective and efﬁcient hierarchical trafﬁc grooming framework for WDM networks of general topology, with the objective of minimizing the total number of electronic ports. At the ﬁrst level of hierarchy, we decompose the network into clusters and designate one node in each cluster as the hub for grooming trafﬁc. At the second level, the hubs form another cluster for grooming intercluster trafﬁc. We view each (ﬁrst-or second-level) cluster as a virtual star , and we present an efﬁ-cient near-optimal algorithm for determining the logical topology of lightpaths to carry the trafﬁc within each cluster. Routing and wavelength assignment is then performed directly on the underlying physical topology. We demonstrate the effectiveness of our approach by applying it to two networks of realistic size, a 32-node, 53-link topology and a 47-node, 96-link network. Comparisons to lower bounds indicate that hierarchical grooming is efﬁcient in its use of the network resources of interest, namely, electronic ports and wavelengths. In addition to scaling to large network sizes, our hierarchical approach also facilitates the control and management of multigranular networks.
Digital commons

The number of scholarly documents available on the web is estimated using capture/recapture methods by studying the coverage of two major academic search engines: Google Scholar and Microsoft Academic Search. Our estimates show that at least 114 million English-language scholarly documents are accessible on the web, of which Google Scholar has nearly 100 million. Of these, we estimate that at least 27 million (24%) are freely available since they do not require a subscription or payment of any kind. In addition, at a finer scale, we also estimate the number of scholarly documents on the web for fifteen fields: Agricultural Science, Arts and Humanities, Biology, Chemistry, Computer Science, Economics and Business, Engineering, Environmental Sciences, Geosciences, Material Science, Mathematics, Medicine, Physics, Social Sciences, and Multidisciplinary, as defined by Microsoft Academic Search. In addition, we show that among these fields the percentage of documents defined as freely available varies significantly, i.e., from 12 to 50%.
Practical Papers, Articles and Application Notes

— The EMC area was once born due to radio interference problems. It is likely to assume that wireless issues will once again cause a strong development of the EMC area. The rapid development within multimedia and wireless systems has lead to a large need in development activities in order to make the current EMC product standards relevant for these emerging technologies. The complexity of these development issues is, however, large and includes several challenging research activities to be carried out. In this paper, examples of such research activities are presented to give an overview of future needs within some technical areas.
On the Nature of Higher‐Order Ambient Seismic Field Correlations

We find that higher‐order ambient seismic field correlations, specifically C3 (correlation of the coda of correlations) of long‐duration data sets from Southern California are symmetric despite the fact that the background wavefield is strongly directional. We demonstrate that this symmetry arises primarily from the structure of the C3 time series analysis rather than the diffuse character of the coda. For that reason, the resulting ambient‐field Green's function symmetry may not be diagnostic of correlation quality. We propose an alternative prestack processing scheme that constructs C3 correlations from each C1 (cross correlation) coda time window, but stacks the results only at the final step of processing. Prestack C3 leads to faster convergence and extracts arrivals at higher frequencies than standard poststack processing.
Forecasting the Environmental Parameters of Water Resources Using Machine Learning Methods

Careful monitoring of the quality and quantity of water resources plays a signiﬁcant role in modern environmental management. Thus, to achieve this aim, the quantitative and qualitative parameters of water resources should be measured and controlled with a desirable accuracy. However, it is not always possible to measure these parameters with easy, inexpensive, precise, and quick experimental methods. Therefore, today to solve this type of problems, new methods including smart methods are used which have a great potential in many computational areas. Considering the variety of the studies and absence of a comprehensive review paper, this research should be conducted. The aim of this paper is to comprehensively review application of the smart methods of artiﬁcial neural network and support vector machine in the area of water resources and to develop a comprehensive study source for the researchers interested in this ﬁeld. The results of these studies all show that these advanced smart methods are more eﬃcient, accurate, economical, and faster than other computational methods to predict quantitative and qualitative parameters of water resources.
Potential of soil moisture estimation using C-band polarimetric SAR data in arid regions

ABSTRACT Soil moisture plays an important role in various applications such as hydrology, agronomy, climatology and ecology. Over the past few decades, images acquired by PolSAR (Polarimetric Synthetic Aperture Radar) systems have raised much interest in the remote sensing community. However, only a few studies have analysed the potential use of polarimetric parameters for the estimation of soil moisture. Taking Juyanze as the study area, two feature extraction methods, the simple polarimetric intensity and phase processing, and the polarimetric decomposition were used to extract different polarimetric parameters. The response of single, multiple, and combined polarimetric parameters to bare surface soil moisture was investigated based on linear and non-linear regression strategies in using fully polarimetric RADARSAT-2 SAR (Synthetic Aperture Radar) imagery and field measurements. The results indicate that each individual polarimetric parameter at C-band is not very sensitive to surface soil moisture under this investigation. However, with the increasing number of polarimetric parameters, the correlation between soil moisture and polarimetric parameters improves steadily and the root mean square error (RMSE) and mean absolute error (MAE) decreased gradually. Combined polarimetric parameters have little improvement on the correlation between soil moisture and polarimetric parameters. The non-linear regression method can improve the correlation to some extent. However, the preliminary results so far still do not satisfy the accuracy of using the polarimetric parameters to inverse soil moisture. Further investigations are required in the direction of a better characterization and exploitation of polarimetric SAR data for the retrieval of soil moisture in arid regions.
Efficient Recovery of Phosphate from Water Media by Iron-Magnesium Functionalized Lignite: Adsorption Evaluation, Mechanism Revelation and Potential Application Exploration

Selective phosphorus removal from aquatic media has become an ideal strategy to mitigate eutrophication and meet increasingly stringent discharge requirements. To achieve phosphorus control and resource utilization of low-calorific-value lignite, iron and magnesium salts were used to functionalize lignite, and iron–magnesium functionalized lignite (called IM@BC) was prepared for phosphate recovery from water media. The adsorption properties of IM@BC were systematically evaluated, especially the influence of ambient pH and co-existing ions. The kinetic, isothermal, and thermodynamic adsorption behaviors of IM@BC were analyzed. The adsorption mechanism was revealed by microscopic characterization. The potential application of phosphate-containing IM@BC (P-IM@BC) was explored. The results show that IM@BC has a strong phosphate adsorption capacity, and the maximum adsorption capacity is 226.22 mgP/g at pH = 3. Co-existing CO32− inhibits phosphate adsorption, while coexisting Ca2+ and Mg2+ enhance the effect. At the initial adsorption stage, the amount of phosphate adsorbed by IM@BC continues to increase, and the adsorption equilibrium state is gradually reached after 24 h. The adsorption process conforms to the pseudo-second-order kinetic model (PSO) and Langmuir isothermal adsorption model, and the adsorption process is mainly chemical adsorption. The phosphate absorption capacity is positively correlated with temperature (283.15 K~313.15 K), and the adsorption process is spontaneous, endothermic, and entropy-increasing. Its adsorption mechanism includes electrostatic attraction, ion exchange, surface precipitation, and coordination exchange. IM@BC can efficiently recover phosphate from actual phosphorus-containing wastewater with a recovery efficiency of up to 90%. P-IM@BC slowly releases phosphate from pH 3 to 11. Plant growth experiments showed that P-IM@BC could be used as a slow-release fertilizer to promote the root growth of cowpeas. The novelty of this work lies in the development of a highly efficient phosphate recovery adsorbent, which provides a feasible method of phosphorus control in water media and resource utilization of lignite.
Factors influencing in-hospital mortality for salvage percutaneous transjugular intrahepatic portosystemic shunting in cirrhotic patients with recalcitrant variceal bleeding after failed endoscopic intervention.

BACKGROUND Endoscopic therapy is the first-line treatment of choice for control of acute variceal bleeding (AVB). In high-risk patients with persistent AVB despite pharmacological treatment and endoscopic intervention, percutaneous transjugular intrahepatic portosystemic shunting (TIPS) provides a minimally invasive salvage method to reduce portal pressure and control bleeding. OBJECTIVES To evaluate factors influencing in-hospital mortality after salvage TIPS (sTIPS) in patients with exsanguinating variceal bleeding despite medical treatment and endoscopic intervention. METHODS Clinical and laboratory data were analysed in all patients treated with sTIPS following failed endoscopic therapy for AVB between August 1991 and November 2020. Factors associated with and predictors of death were determined using bivariate analysis and univariate logistic regression analysis. RESULTS Thirty-four patients (29 men, 5 women), mean age 52 years (range 31 - 80), received sTIPS for uncontrolled (n=11) or refractory (n=23) AVB. The causes of portal hypertension were alcohol-related (n=24) and non-alcohol-related cirrhosis. Salvage TIPS controlled bleeding in 32 patients, with recurrence in 1. Ten patients died in hospital (mean 4.8 days, range 1 - 10) of liver failure (n=4), multiorgan failure (n=3), alcoholic cardiomyopathy (n=2) and uncontrolled gastric variceal bleeding (n=1). On bivariate analysis, factors associated with death were Child-Pugh (C-P) score ≥10 (p=0.006), sodium Model for End-stage Liver Disease (MELD-Na) score ≥22 (p<0.001), ≥8 units of blood transfused (p<0.001), Sengstaken-Blakemore balloon tube placement (p<0.001), endotracheal intubation (p<0.001), inotropic support (p<0.001) and endoscopically uncontrolled bleeding (p<0.001). Univariate logistic regression analysis showed that the most significant predictors of mortality were inotrope dependency (odds ratio (OR) 134; p<0.001), endotracheal intubation (OR 99; p<0.001), endoscopically uncontrolled bleeding (OR 28; p=0.001), grade 3 ascites (OR 20.9; p=0.012) and C-P grade C (OR 8.8; p=0.011). CONCLUSION Salvage TIPS controlled variceal bleeding in 94% of patients after failed endoscopic therapy with 29% in-hospital mortality. The most significant predictors of mortality were C-P grade C, grade 3 ascites, inotrope requirement, endotracheal intubation and endoscopically uncontrolled bleeding.
Wildlife Volunteer Tourism: Scientific and Educational Contributions in South Africa

Wildlife volunteer tourism has evolved into a popular form of sustainable tourism in South Africa. This form of tourism can exhibit both positive and negative impacts on a host destination. However, limited research has examined the potential contributions of wildlife volunteer tourism in South Africa. This paper focuses on filling this theoretical gap by investigating the scientific and educational contributions of wildlife volunteer tourism in South Africa. An exploratory qualitative approach was followed, where seven managers of volunteer tourism organisations were interviewed in August and September 2022. Thematic analysis was used to analyse the data. From the results, it is clear that wildlife volunteer tourism makes significant scientific and educational contributions. However, funding remains a challenge. The results provided an increased understanding of wildlife volunteer tourism in South Africa, and is valuable to managers, and contributes to the current discourse on volunteer tourism as an emerging market segment.
Characterization of a Straboviridae phage vB_AbaM-SHI and its inhibition effect on biofilms of Acinetobacter baumannii

Acinetobacter baumannii (A. baumannii) is a popular clinical pathogen worldwide. Biofilm-associated antibiotic-resistant A. baumannii infection poses a great threat to human health. Bacteria in biofilms are highly resistant to antibiotics and disinfectants. Furthermore, inhibition or eradication of biofilms in husbandry, the food industry and clinics are almost impossible. Phages can move across the biofilm matrix and promote antibiotic penetration. In the present study, a lytic A. baumannii phage vB_AbaM-SHI, belonging to family Straboviridae, was isolated from sauce chop factory drain outlet in Wuxi, China. The DNA genome consists of 44,180 bp which contain 93 open reading frames, and genes encoding products morphogenesis are located at the end of the genome. The amino acid sequence of vB_AbaM-SHI endolysin is different from those of previously reported A. baumannii phages in NCBI. Phage vB_AbaM-SHI endolysin has two additional β strands due to the replacement of a lysine (K) (in KU510289.1, NC_041857.1, JX976549.1 and MH853786.1) with an arginine (R) (SHI) at position 21 of A. baumannii phage endolysin. Spot test showed that phage vB_AbaM-SHI is able to lyse some antibiotic-resistant bacteria, such as A. baumannii (SL, SL1, and SG strains) and E. coli BL21 strain. Additionally, phage vB_AbaM-SHI independently killed bacteria and inhibited bacterial biofilm formation, and synergistically exerted strong antibacterial effects with antibiotics. This study provided a new perspective into the potential application value of phage vB_AbaM-SHI as an antimicrobial agent.
PNeSM: Arbitrary 3D Scene Stylization via Prompt-Based Neural Style Mapping

3D scene stylization refers to transform the appearance of a 3D scene to match a given style image, ensuring that images rendered from different viewpoints exhibit the same style as the given style image, while maintaining the 3D consistency of the stylized scene. Several existing methods have obtained impressive results in stylizing 3D scenes. However, the mod- els proposed by these methods need to be re-trained when applied to a new scene. In other words, their models are cou- pled with a specific scene and cannot adapt to arbitrary other scenes. To address this issue, we propose a novel 3D scene stylization framework to transfer an arbitrary style to an ar- bitrary scene, without any style-related or scene-related re- training. Concretely, we first map the appearance of the 3D scene into a 2D style pattern space, which realizes complete disentanglement of the geometry and appearance of the 3D scene and makes our model be generalized to arbitrary 3D scenes. Then we stylize the appearance of the 3D scene in the 2D style pattern space via a prompt-based 2D stylization al- gorithm. Experimental results demonstrate that our proposed framework is superior to SOTA methods in both visual qual- ity and generalization.