Miracle-dz/UniFAR-FTUs huggingface dataset:
Risk Analysis Frameworks Used in Biological Control and Introduction of a Novel Bayesian Network Tool

Classical biological control, the introduction of natural enemies to new environments to control unwanted pests or weeds, is, despite numerous successful examples, associated with rising concerns about unwanted environmental impacts such as population decline of nontarget species. Recognition of these biosafety risks is globally increasing, and prerelease assessments of biological control agents (BCAs) have become more rigorous in many countries. We review the current approaches to risk assessment for BCAs as used in Australasia, Europe, and North America. Traditionally, these assessments focus on providing assurance about the specificity of a proposed BCA, generally via a list of suitable versus nonsuitable hosts determined through laboratory specificity tests (i.e., by determining the BCA's physiological host range). The outcome of interactions of proposed agents in the natural environment can differ from laboratory‐based predictions. Potential nontarget host testing may be incomplete, additional ecological barriers under field conditions may limit encounters between BCA and nontargets or reduce attack levels, and BCAs could disperse to habitats beyond those used by the target species and adversely affect nontarget species. We advocate for the adoption of more comprehensive, ecologically‐based, probabilistic risk assessment approaches to BCA introductions. An example is provided using a Bayesian network that can integrate information on probabilities and uncertainties of a BCA to spread and establish in new habitats, interact with nontarget species in these habitats, and eventually negatively impact the populations of these nontarget species. Our new model, Biocontrol Adverse Impact Probability Assessment, aims to be incorporated into a structured decision‐making framework to support national regulatory authorities.
Ocean Regime Shift is Driving Collapse of the North Atlantic Right Whale Population

C. FINMARCHICUS ABUNDANCE Figure S1 shows the time series of the annual C. finmarchicus Abundance Index for the Gulf of Maine. It should be noted that NOAA funding cuts resulted in the Gulf of Maine Continuous Plankton Recorder (CPR) survey being discontinued in 2017. In addition, the survey route was changed in 2009, shifting its departure port from Boston, Massachusetts, to Portland, Maine. Therefore, coverage of Massachusetts Bay was discontinued, and coverage of the western Gulf of Maine was markedly different after 2009. Coverages of the eastern Gulf of Maine and western Scotian Shelf remained comparable. Results from a spatially and temporally resolved right whale reproduction model (Meyer-Gutbrod et al., 2015) demonstrated that when the summertime (third quarter–July, August, September) C. finmarchicus Abundance Index in the eastern Gulf of Maine falls below a certain threshold value, prenatal or neonatal calf mortality is triggered, presumably due to inadequate prey availability and poor maternal nutrition. This threshold value is shown in Figure S2, the time series of the summertime C. finmarchicus Abundance Index in the eastern Gulf of Maine. Due to the previously mentioned limitations in the availability of CPR survey data in the western Gulf of Maine during recent years, this threshold value could only be estimated, with the model using data through 2009. Because of this constraint, it was decided to show the threshold value in Figure S2 rather than in Figure 2c.
SCHIZOPHRENIA AND EPILEPSY: WHAT LINKS BETWEEN? ARRAZI HOSPITAL EXPERIENCE ABOUT 56 CASES

Background: Given the higher incidence of psychotic disorders in patients with epilepsy, several neurologists and psychiatrists have attempted to explain this controversial comorbidity. Thus, several hypotheses have been put forward but no link has been established with certainty until today. Objectives: The aim of our work is to draw up a socio-demographic and psychopathological profile of patients with schizophrenia-epilepsy comorbidity as well as to assess the risk of suicide, the management, the reasons for admission and the length of hospitalization. Methodology: we conducted a retrospective cross-sectional study on medical records of patients with schizophrenia and epilepsy who were hospitalized at the Ar-Razi University Psychiatric Hospital in SalÃ© between January 01, 2017 and March 31, 2021. Results: Our study included 56 patients. The average age was 33 + / - 9.83, 55% male. 50% of patients had attempted suicide in the past and 25% had a history of depressive episode, 41.1% had substance use disorder and 26.8% had a family history of psychosis. 85.7% of our patients developed schizophrenia from pre-existing epilepsy the time to onset of schizophrenia compared to epilepsy was 11.08 years +/- 7.71. The mean age of onset of schizophrenia is 23.3 years with a mean duration of progression of 9.18 years, 55.4% of patients were on monotherapy and 8.9% had resistant schizophrenia on clozapine. The average age of onset of epilepsy is 14.73 years, with generalized epilepsy in 84% of cases. The average length of stay is 42 days. The reasons for admission were as follows: hetero-aggression 78.6%, delusional verbalization 85.7% and suicide attempt 23.2%. The majority of our patients have been treated with atypical antipsychotics: Risperidone 30.4%, Amisulpride 21.4% and Aripiprazole 12.5%. Conclusion: The co-occurrence of schizophrenia epilepsy suggests the existence of possible common etiopathogenic factors. The management of this comorbidity requires a multidisciplinary collaboration between neurologist and psychiatrist, in order to confirm the diagnosis, establish a good therapeutic approach and propose a management algorithm taking into account the two pathologies.
Testing the area–altitude balance ratio (AABR) and accumulation–area ratio (AAR) methods of calculating glacier equilibrium-line altitudes

Abstract In this study, we compare equilibrium-line altitudes (ELAs) calculated using the area–altitude balance ratio (AABR) and the accumulation–area ratio (AAR) methods, with measured ELAs derived from direct field observations. We utilise a GIS toolbox to calculate the ELA for 64 extant glaciers by applying the AABR and AAR methods to DEMs and polygons of their geometry. The calculated ELAs (c-ELAs) are then compared to measured zero-net balance ELAs (znb-ELAs) obtained from mass-balance time series held by the WGMS for the same glaciers. The correlation between znb-ELAs and AABR (1.56)/AAR (0.58) c-ELAs is very strong, with an r2 = 0.99. The smallest median difference between znb-ELAs and c-ELAs (i.e. 65.5 m) is obtained when a globally representative AABR of 1.56 is used. When applied to palaeoglacier-climate applications, this difference translates to ~0.42°C, well within the uncertainty of palaeotemperature proxies used to determine mean summer temperature at the ELA. The more widely used mean AABR of 1.75 is shown to be statistically invalid due to the skewness of the dataset. On this basis, when calculating glacier ELAs, we recommend the use of a global AABR value of 1.56.
Vegetation Type and Soil Moisture Drive Variations in Leaf Litter Decomposition Following Secondary Forest Succession

Soil moisture was an important factor affecting litter decomposition. However, less attention has been given to the complete succession ecosystem after farmland abandonment. To better understand the effect of moisture on leaf litter decomposition after farmland abandonment, in this study, we used three water gradients (10%, 25% and 50%) of field moisture capacity for succession vegetation. Furthermore, we used the typical species leaf litter decomposition of four succession stages—grassland (GL), shrubland (SL), pioneer forest (PF), and climax forest (CF) from the Loess Plateau of China. The results showed that leaves decomposition rate exhibited an increasing pattern with increasing moisture contents. The decomposition trend was shown as GL > SL > PF > CF. During the decomposition process, the leaf carbon concentration (LC) and leaf nitrogen concentration (LN) changed, but non-significantly. The effects of LC, LN, and LC: LN on leaf decomposition varied with vegetation type. Soil properties such as NH4+, NO3−, dissolved organic nitrogen (DON), and leaf quality parameters such as leaf cellulose, lignin, lignin: LN, and lignin: LC played an important role in driving leaf litter decomposition. Overall, the results provide evidence that litter decomposition in secondary forest succession system was linked to leaf and soil nutrient dynamics, and was limited by soil moisture.
A Review on Five Membered Nitrogen Containing Heterocyclic Compounds with Various Biological Activities

Heterocyclic compounds are a highly valuable and unique class of compounds. Different heterocyclic analogues have been evaluated for their diverse biological activities. Five membered heterocyclic compounds possess various pharmacological activities. Among them Nitrogen containing five membered heterocyclic compounds have crucial place in medicinal chemistry. This paper aims to review on the pharmacological activities of five membered nitrogen containing heterocyclic compounds.
Numerical Analyses of Transcritical Evaporation using Diffuse-Interface Method

Liquid fuel placed in a supercritical environment (with respect to the fuel’s critical properties) can undergo different evaporation processes that is determined by the droplet’s surface temperature T s in comparison with the critical mixing temperature T c . In the transcritical regime, the ambient condition is such that at initial time, T s < T c , a sharp liquid-vapor interface exists, and evaporation occurs at subcritical condition. Eventually, the surface temperature approaches the critical mixing temperature, and the evaporation process becomes supercritical, with no distinct liquid-vapor interface. Traditional methods for simulating this complex evaporation behavior employ separate formulations for the liquid and vapor phases during subcritical evaporation and a continuous formulation during supercritical evaporation. Here, we developed a holistic formulation for the simulation of transcritical evaporation that is valid for both sub- and super-critical evaporation regimes using a diffuse-interface method derived from Linear Gradient Theory. The formulation allows for direct modeling of surface tension and interface thickness during the process of interface thickening as T s → T c . The diffuse-interface model was employed in simulations of a nanoscale transcritical planar evaporation conﬁguration. Furthermore, the ability of the diffuse-interface model to resolve both macroscale ﬂuid behavior and nanoscale liquid-vapor interface structure was demonstrated.
Dynamically Adaptive Machine Speech Chain Inference for TTS in Noisy Environment: Listen and Speak Louder

Although machine speech chains were originally proposed to mimic a closed-loop human speech chain mechanism with auditory feedback, the existing machine speech chains are only utilized as a semi-supervised learning method that allows automatic speech recognition (ASR) and text-to-speech synthesis systems (TTS) to support each other given unpaired data. During inference, however, ASR and TTS are still performed separately. This paper focuses on machine speech chain inferences in a noisy environment. In human communication, speakers tend to talk more loudly in noisy environments, a phenomenon known as the Lombard effect. Simulating the Lombard effect, we implement a machine speech chain that enables TTS to speak louder in a noisy condition given auditory feedback. The auditory feedback includes speech-to-noise ratio prediction and ASR loss as a speech intelligibility measurement. To the best of our knowledge, this is the ﬁrst deep learning framework that mimics human speech perception and production behaviors in a noisy environment.
A Study on Structural Behaviour of RC Buildings Pre-Designed According to TBSC Design Principles

Despite the changes and updates made in the Seismic Codes, it is obvious that the loss of life and property in the occurring earthquakes did not decrease to the desired extent. One of the most important reasons for this is that adequate and quality engineering services cannot be provided in the design of buildings. This is mostly due to complex calculation methods of the Seismic Codes. In this respect, some limit conditions are specified for the design of the cross-sectional dimensions of the structural system elements of regular buildings with shear walled-framed in Turkish Building Seismic Code (TBSC). In these relations, the smallest cross-sectional dimensions are obtained to provide sufficient axial pressure and shear force resistance of the load-carrier system and its elements. However, seismic performance of buildings are not mentioned in these design rules. In this study, the seismic performance and structural behaviour of the buildings were evaluated by considering the column and shear wall cross-section dimensions. The compatibility of the buildings designed according to the proposed design rules with seismic performance has been investigated. When the analytical results obtained are evaluated, it can be stated that the design rules specified in TBSC can be generally sufficient for the building performance and structural behaviour.
Soil Erosion Monitoring in Quarry Restoration Using Drones

Mining is an essential activity that supports the provision of raw materials. However, the extraction process of mining has deep environmental impacts. For this reason, restoration actions are mandatory, and monitoring is a key step in ensuring the renaturalization of affected areas. Erosion processes are one of the main problems that affect restored areas in extractive activities due to the frequently steep slopes and the difficulty of revegetating the technosols constructed using mining debris. This research aims to develop a method for determining soil losses due to water erosion in mine-restored areas by using Geographic Information Systems (GIS) and Remote Sensing (RS) tools. For the study, images obtained using Unmanned Aerial Systems (UAS) in an open pit mine in the process of restoration are used, from which the Digital Elevation Model (DEM) of the current state of the slopes is obtained (0.10 m spatial resolution). With GIS techniques, ridges of the rills and gullies generated in the slopes are detected, whereby an estimation of a first DEM before the erosive process and a second DEM after the erosive process can be constructed. Each of these DEMs are evaluated individually in order to determine the height differences and estimate the volumetric loss. At the same time, the results are validated with the DEM derived from official mapping agencies’ airborne Lidar data (1.00 m spatial resolution), which yield consistent data in the volumetric quantification of the erosion despite the difference in spatial resolution. In conclusion, the high spatial resolution of drone images facilitated a detailed monitoring of erosive processes, obtaining data from vast and inaccessible slopes that are usually immeasurable with traditional field techniques, and altogether improving the monitoring process of mine restoration.
FK506-loaded PLGA nanoparticles improve long-term survival of a vascularized composite allograft in a murine model

Background The side effects of life-long administration of FK506 limit the clinical practice of vascularized composite allografts (VCAs). This study aimed to evaluate the feasibility of FK506-loaded poly (lactic-co-glycolic acid) (PLGA) nanoparticles (FK506 NPs) for prolonging the long-term survival of VCAs and reducing the side effects of FK506. Methods PLGA nanoparticles loaded with FK506 were prepared by the solvent evaporation method. The characterization of FK506 NPs was evaluated by electron microscopy. To confirm the function and safety of FK506 NPs, these particles were administrated into rats by intraperitoneal injection. The survival time of the allograft, systemic concentration of FK506, anti-rejection activity, and side-effect of FK506 NPs were evaluated in a Brown Norway (BN)-to-Sprague Dawley (SD) epigastric VCA transplantation model. Results Compared with the nontreatment, PLGA control and FK506 groups, the median survival times (MST) of the FK506 NP groups were significantly prolonged. The FK506 NPs could maintain therapeutic drug concentration for 60 days. Moreover, cytokine concentrations, flow cytometry of regulatory T cells (Tregs) and histopathology of allografts revealed significantly prolonged immunosuppression by FK506 NPs. FK506 NPs also ameliorated FK506 nephrotoxicity. Conclusions FK506 NPs prolong the survival time of VCAs in a murine model with minimal nephrotoxicity, and provide a potential clinical strategy for ameliorating long-term side effects of immunosuppressive therapy.
Comparative Effectiveness Research using Bayesian Adaptive Designs for Rare Diseases: Response Adaptive Randomization Reusing Participants

Abstract Slow accrual rate is a major challenge in clinical trials for rare diseases and is identified as the most frequent reason for clinical trials to fail. This challenge is amplified in comparative effectiveness research where multiple treatments are compared to identify the best treatment. Novel efficient clinical trial designs are in urgent need in these areas. Our proposed response adaptive randomization (RAR) reusing participants trial design mimics the real-world clinical practice that allows patients to switch treatments when desired outcome is not achieved. The proposed design increases efficiency by two strategies: (i) Allowing participants to switch treatments so that each participant can have more than one observation and hence it is possible to control for participant specific variability to increase statistical power; and (ii) Using RAR to allocate more participants to the promising arms such that ethical and efficient studies will be achieved. Extensive simulations were conducted and showed that, compared with trials where each participant receives one treatment, the proposed participants reusing RAR design can achieve comparable power with a smaller sample size and a shorter trial duration, especially when the accrual rate is low. The efficiency gain decreases as the accrual rate increases.
A Speech Emotion Recognition Framework for Better Discrimination of Confusions

Speech emotion recognition (SER) plays an important role in human-machine interaction (HMI). Various methods have been proposed for the SER task. However, a common problem in most of the previous studies is some speciﬁc emotions are grossly misclassiﬁed. In this paper, we propose a novel SER framework aiming at discriminating the confusions by utilizing triplet loss and data augmentation to enforce a CNN-LSTM model to emphasize more on these emotions which are hard to be correctly classiﬁed. Ablation experiments demonstrate the effectiveness of the proposed framework. On Interactive Emotional Dyadic Motion Capture (IEMOCAP) dataset, our framework can achieve 79.52% of Weighted Accuracy (WA) and 78.30% of Unweighted Accuracy (UA). Compared to the other state-of-the-art models, our framework obtains more than 3.34% and 1.94% improvement on WA and UA respectively.
Molecular assessment of dietary niche partitioning in an endemic island radiation of tropical mammals

Island radiations represent unique evolutionary histories in unique ecological contexts. These radiations provide opportunities to investigate ecological diversification in groups that typically exhibit niche partitioning among their constituents, including partitioning of food resources. DNA metabarcoding produces finer levels of diet identification than traditional methods, allowing us to examine dietary niche partitioning in communities or clades in which species share superficially similar diets. Here, we use DNA metabarcoding to investigate dietary niche partitioning in an endemic radiation of mammals in the Philippines. Our data reveal niche partitioning as well as phylogenetically‐uncorrelated adaptive evolution in this small mammal community. Because 70% of the focal species belong to the tribe Chrotomyini, an endemic Philippine radiation of murid rodents that feed extensively on earthworms, this study sheds light on dietary adaptation and its role in the co‐occurrence of closely related species. Our results reveal fine‐scale resource partitioning within this community; our data provide compelling evidence for niche partitioning of diet that was masked by previous diet categories and will help in further dissecting the model adaptive radiation of endemic small mammals on Luzon. This study reinforces the notion that DNA metabarcoding can be a valuable tool for investigating both ecological relationships and evolutionary ecology at the community and phylogenetic level, respectively.
Polarization, partisanship, and pandemic: The relationship between county‐level support for Donald Trump and the spread of Covid‐19 during the spring and summer of 2020

Abstract Objective Republicans and Democrats have displayed widely divergent beliefs and behaviors related to COVID‐19, creating the possibility that geographic areas with more Donald Trump supporters may be more likely to suffer from the disease. Methods I use 2016 election data, COVID‐19 case and mortality data, and multilevel linear growth models with state fixed effects to estimate the relationship between county‐level support for Donald Trump and the trajectory of cumulative COVID‐19 cases and deaths per 100,000 county residents between March 17, 2020 and August 31, 2020. Results Counties more supportive of Trump had fewer COVID‐19 cases and deaths in the early months of the pandemic. However, as the summer moved into July and August, counties less supportive of Trump stopped growth rates of COVID‐19 cases and deaths, while counties more supportive of Trump saw a trajectory of increased cases and deaths in July and August. This is likely due to the widely divergent beliefs and behaviors displayed by Republicans and Democrats toward COVID‐19. Conclusion This study underscores the power of polarization and partisanship in the public sphere, even when it comes to a public health issue.
DEMUCS-Mobile : On-Device Lightweight Speech Enhancement

As the importance of speech enhancement for real-world application increases, the compactness of the model is also becoming a crucial study. In this paper, we present compression techniques to reduce the model size and applied them to the state-of-the-art real-time speech enhancement system. We successfully reduce the model size by actively applying channel pruning while maintaining performance. In particular, we pro-pose a method to prune more channels of convolutional neural networks (CNN) by utilizing gated linear unit (GLU) activation. In addition, lower-bit-quantization is applied to reduce model size, while minimizing performance degradation caused by quantization. We show the performance of our proposed model on a mobile device where computing resources are limited. In particular, it is implemented to enable streaming, and speech enhancement works in real-time.
Determination of the Content of Impurity Elements in Aluminum Alloy by XRF Analysis

Aluminum alloy is one of the most widely used metal materials in today’s society. Measurement and analysis of its impurity elements can effectively improve the performance of aluminum alloy. Energy dispersive X-ray fluorescence spectrometry (EDXRF) was used to analyze the types and contents of impurity elements in aluminum alloys, and the best working conditions for the EDXRF analyzer to measure impurity elements in aluminum alloys were determined. The absorption and enhancement effect of Al, Zn, Cu on impurity elements in Ti, Cr, Mn, Fe, Cu, Zn in aluminum alloy was discussed, and the empirical coefficient method was used to correct it. The analytical precision of EDXRF was evaluated. The data show that the average relative errors of the impurity elements in the aluminum alloy are Ti: 7.50%, Cr: 2.48%, Mn: 0.99%, Fe: 3.49%, Cu: 0.44%, Zn: 0.14%, respectively. It shows that the XRF measurement method is feasible and the accuracy meets the requirements of engineering design.