Miracle-dz/UniFAR-FTUs huggingface dataset:
Rigorous Approach to Polarimetric Radar Modeling of Hydrometeor Orientation Distributions

Abstract A Muceller-matrix-based approach is described for calculating polarimetric radar parameters such as reflectivity, differential reflectivity, linear depolarization ratio, propagation differential phase, and backscatter differential phase. Particle scattering is calculated using the T matrix, which is ideally suited for spheroids in the Mie region. The T matrix, is calculated once for a given wavelength, particle size, shape, and dielectric constant, making full use of symmetry through use of a body coordinate system attached to the particle. For various orientations of the particle symmetry axis and for various radar elevation angles, a separate laboratory coordinate system is used. The scattering amplitudes and polarization basis vectors are transformed between the two coordinate systems using geometrical transformations. Two particle orientation distributions, which are two-dimensional in θ, ϕ, are considered. These are the Gaussian and simple harmonic in θ with random ϕ. Sample calculations are.
Overexpression of MrEsa1 accelerated growth, increased ascospores yield, and the polyketide production in Monascus ruber

Esa1 has been proven to be an important histone acetyltransferase involved in the regulation of growth and metabolism. Monascus spp. with nearly 2000 years of edible history in East Asian countries can produce a variety of polyketides. It is unknown whether Esa1 plays a regulatory role in Monascus spp. In this study, we isolated the homology of histone acetyltransferase Esa1 (named MrEsa1) and constructed a mresa1‐overexpressed strain. Western blot experiments showed that MrEsa1 hyperacetylated at K4 and K9 of the H3 subunit in Monascus ruber. Overexpression of mresa1 led to the larger colony diameter and increased dry cell mass; meanwhile, the conidia germination rate was significantly accelerated in the mresa1‐overexpressed strain before 4 h, and the number of ascospores in the mresa1‐overexpressed strain was significantly higher than that in WT. In addition, the Monascus azaphilone pigments (MonAzPs) and citrinin production of the mresa1‐overexpressed strain were 1.7 and 2.4 times more than those of WT, respectively. Reverse transcription‐quantitative polymerase chain reaction experiment suggested that mrpigB, mrpigH, mrpigJ, and mrpigK, involved in MonAzPs synthesis, and pksCT, mrl3, and mrl7, involved in citrinin synthesis, were upregulated in mresa1‐overexpressed strain. This study provides important insights into the effect of MrEsa1 on the developmental process and the production of secondary metabolites in Monascus spp.
Inhibition of NKCC1 in spinal dorsal horn and dorsal root ganglion results in alleviation of neuropathic pain in rats with spinal cord contusion

Previous studies have confirmed the relationship between chloride homeostasis and pain. However, the role of sodium potassium chloride co-transporter isoform 1 (NKCC1) in dorsal horn and dorsal root ganglion neurons (DRGs) in spinal cord injury (SCI)-induced neuropathic pain (NP) remains inconclusive. Therefore, we aimed to explore whether suppression of NKCC1 in the spinal cord and DRGs alleviate the NP of adult rats with thoracic spinal cord contusion. Thirty adult female Sprague-Dawley rats (8 week-old, weighing 250–280 g) were randomly divided into three groups with ten animals in each group (sham, SCI, and bumetanide groups). The paw withdrawal mechanical threshold and paw withdrawal thermal latency were recorded before injury (baseline) and on post-injury days 14, 21, 28, and 35. At the end of experiment, western blotting (WB) analysis, quantitative real-time Polymerase Chain Reaction (PCR) and immunofluorescence were performed to quantify NKCC1 expression. Our results revealed that NKCC1 protein expression in the spinal cord and DRGs was significantly up-regulated in rats with SCI. Intraperitoneal treatment of bumetanide (an NKCC1 inhibitor) reversed the expression of NKCC1 in the dorsal horn and DRGs and ameliorated mechanical ectopic pain and thermal hypersensitivities in the SCI rats. Our study demonstrated the occurrence of NKCC1 overexpression in the spinal cord and DRGs in a rodent model of NP and indicated that changes in the peripheral nervous system also play a major role in promoting pain sensitization after SCI.
Research progress of ophthalmic preparations of immunosuppressants

Abstract Immune ophthalmopathy is a collection of autoimmune eye diseases. Immunosuppressants are drugs that can inhibit the body’s immune response. Considering drug side effects such as hepatorenal toxicity and the unique structure of the eye, incorporating immunosuppressants into ophthalmic nanodrug delivery systems, such as microparticles, nanoparticles, liposomes, micelles, implants, and in situ gels, has the advantages of improving solubility, increasing bioavailability, high eye-target specificity, and reducing side effects. This study reviews recent research and applications of this aspect to provide a reference for the development of an ophthalmic drug delivery system.
Quantum Repeaters: The Role of Imperfect Local Operations in Quantum Communication

In quantum communication via noisy channels, the error probability scales exponentially with the length of the channel. We present a scheme of a quantum repeater that overcomes this limitation. The central idea is to connect a string of (imperfect) entangled pairs of particles by using a novel nested purification protocol, thereby creating a single distant pair of high fidelity. Our scheme tolerates general errors on the percent level, it works with a polynomial overhead in time and a logarithmic overhead in the number of particles that need to be controlled locally.
Thin ferroelectric liquid crystal layers: mechanical stability and fast electro-optical response, connection between molecule design and surface properties

The storage of information after mechanical stimuli even without applied electrical field is based on the elastic properties of the ferroelectric liquid crystal (FLC) material and the anchoring energy. It is favourable for chiral molecules with extended length, such as 4,4′-di-substituted quaterphenyls and 4,4′-di-substituted quinquephenyls, which have in series-connected benzene rings, but not separated by bridging fragments. To obtain the required stability with a reasonable switching speed of about 50 μs 4,4′-di-substituted chiral quaterphenyls with two chiral centres on the same wing has been synthesised. Here, the switching is much faster compared to compounds with same quaterphenyl fragment, but only with one chiral centre.
A UVR-sensor wearable device intervention to reduce sun exposure in melanoma survivors: Results from a randomized controlled trial

Background Melanoma survivors are at increased risk of developing a second primary melanoma; however, some report sub-optimal sun behaviors and sunburns. We tested the effectiveness of a wearable device with ultraviolet radiation (UVR)-sensing technology to improve sun behaviors and reduce sunburns in cutaneous melanoma survivors. Materials and methods We conducted a randomized controlled trial using Shade 2, a commercially available wrist device that measures UVR. The intervention group received the device and mobile application notifications about their exposure and prompts to use sunscreen. The control group received the device and a separate research mobile application without information about their exposure or notifications. Participants wore the device for 12 weeks and self-reported sun behaviors before, during, and after the intervention. The primary outcome was a composite score of sun protection behaviors at week 12. Results 386 participants were randomized (186 control, 182 intervention). Most were female and 5+ years past their first melanoma diagnosis. The average age was 56 years. Most (93%) completed the study, though 40% experienced device issues. No meaningful differences were observed in self-reported sun protection behaviors at week 12 (controls 3.0±0.5 vs. intervention 2.9±0.5, p = 0.06), any sunburn during the intervention period (controls 14.4% vs. intervention 12.7%, p = 0.75), or average daily objective UVR exposure (controls median 87 vs. intervention 83 J/m2, p = 0.43). Conclusion Wearing a device that measured and alerted melanoma survivors to UVR exposure did not result in different sun behaviors, exposure, or sunburns relative to controls. The technology needs refinement before further attempts to assess the effectiveness of self-monitoring UVR exposure. Clinical trials registration NCT03927742.
Star Formation in Disk Galaxies

Abstract We present results, some preliminary, from a major new study of the star formation properties of a sample of nearby disk galaxies (Ferguson 1997). Our emphasis is on the faint outer regions of disks. Hα images, combined with broad-band images and spectroscopy of HII regions, constrain the present and past star formation rates and chemical enrichment. These data also allow study of faint diffuse ionised gas, which traces the influence of massive stars on their environment, and the structure of the interstellar medium.
Transcutaneous carbon dioxide monitoring during prolonged apnoea with high‐flow nasal oxygen

The duration of apnoeic oxygenation with high‐flow nasal oxygen is limited by hypercapnia and acidosis and monitoring of arterial carbon dioxide level is therefore essential. We have performed a study in patients undergoing prolonged apnoeic oxygenation where we monitored the progressive hypercapnia with transcutaneous carbon dioxide. In this paper, we compared the transcutaneous carbon dioxide level with arterial carbon dioxide tension.
Protein interactomes for plant lipid biosynthesis and their biotechnological applications

Summary Plant lipids have essential biological roles in plant development and stress responses through their functions in cell membrane formation, energy storage and signalling. Vegetable oil, which is composed mainly of the storage lipid triacylglycerol, also has important applications in food, biofuel and oleochemical industries. Lipid biosynthesis occurs in multiple subcellular compartments and involves the coordinated action of various pathways. Although biochemical and molecular biology research over the last few decades has identified many proteins associated with lipid metabolism, our current understanding of the dynamic protein interactomes involved in lipid biosynthesis, modification and channelling is limited. This review examines advances in the identification and characterization of protein interactomes involved in plant lipid biosynthesis, with a focus on protein complexes consisting of different subunits for sequential reactions such as those in fatty acid biosynthesis and modification, as well as transient or dynamic interactomes formed from enzymes in cooperative pathways such as assemblies of membrane‐bound enzymes for triacylglycerol biosynthesis. We also showcase a selection of representative protein interactome structures predicted using AlphaFold2, and discuss current and prospective strategies involving the use of interactome knowledge in plant lipid biotechnology. Finally, unresolved questions in this research area and possible approaches to address them are also discussed.
Comparison of Person-Centered and Cumulative Risk Approaches in Explaining the Relationship Between Adverse Childhood Experiences and Behavioral and Emotional Problems

Adverse childhood experiences (ACEs) commonly co-occur, and researchers often estimate their impact using a cumulative risk approach. The person-centered approach offers another approach to operationalize the co-occurrence of ACEs. This study aims to estimate latent classes of ACEs in a sample of U.K. children, examine their relationship with emotional and behavioral problems, and compare the explanatory value of the latent classes to cumulative risk scores. Data were collected among a general population sample of British 10-year-old children extracted from the U.K. Household Longitudinal Study (N = 601). Seven items characterized ACEs, comprising parent-report physical discipline, emotional abuse, supervisory neglect, maternal psychological distress, child-report parental educational disinterest, bullying victimization, and adverse neighborhood. Outcome measures were derived from the self-report Strengths and Difficulties Questionnaire including total difficulties, emotional symptoms, conduct problems, hyperactivity, peer problems, and prosocial behavior. Latent class analysis resulted in a three-class solution: low ACEs, household challenges, and community challenges. Compared to the other classes, the community challenges class scored substantially worse on total difficulties, emotional symptoms, and peer subscales. The cumulative risk score was associated with all outcomes except prosocial behavior. Cumulative risk models accounted for a larger proportion of variance compared with the latent class models, except for peer problems which the person-centered model explained better. This study confirms that ACEs are associated with impairment in child functioning, and that both person-centered and cumulative risk approaches can capture this relationship well. Specifically, the person-centered approach demonstrated how co-occurring risk factors in the community challenges class produced particularly poor internalizing outcomes.
Current advances in endovascular treatment

Purpose of review Endovascular thrombectomy (EVT) is the most beneficial reperfusion therapy for acute ischemic stroke. Currently, much effort is done to promote trials examining EVT efficacy and safety in various conditions not included in the main randomized controlled trials established the superiority of EVT. This review summarizes the current advances of EVT patients’ selection and periprocedural management. Recent findings Recent evidence points to beneficial effect of EVT among patients with relatively large ischemic core, premorbid independent nonagenarians and basilar artery occlusion, and suggest that intravenous thrombolysis bridging treatment is associated with better reperfusion rates. Ongoing trials currently examine EVT efficacy and safety in distal vessel occlusions and in large vessel occlusion with low NIHSS. Current evidence also support use of general anaesthesia and avoid postprocedural extremely low or high blood pressure as well as haemodynamic instability. Summary The field of EVT is rapidly evolving. The results of recent trials have dramatically increased the indications for EVT, with many ongoing trials examining further indications.
Rounding non-binary categorical variables following multivariate normal imputation: evaluation of simple methods and implications for practice

We study bias arising from rounding categorical variables following multivariate normal (MVN) imputation. This task has been well studied for binary variables, but not for more general categorical variables. Three methods that assign imputed values to categories based on fixed reference points are compared using 25 specific scenarios covering variables with k=3, …, 7 categories, and five distributional shapes, and for each k=3, …, 7, we examine the distribution of bias arising over 100,000 distributions drawn from a symmetric Dirichlet distribution. We observed, on both empirical and theoretical grounds, that one method (projected-distance-based rounding) is superior to the other two methods, and that the risk of invalid inference with the best method may be too high at sample sizes n≥150 at 50% missingness, n≥250 at 30% missingness and n≥1500 at 10% missingness. Therefore, these methods are generally unsatisfactory for rounding categorical variables (with up to seven categories) following MVN imputation.
A Dataset for Detecting Humor in Arabic Text

Humor detection is a complex and ambiguous task in natural language processing. This has made automatic humor detection challenging, particularly for languages with limited resources such as Arabic. In this paper, we attempt to solve this task by collecting and annotating Arabic humorous tweets in dialects and Modern Standard Arabic (MSA) text then performing automatic humor detection on the collected data. We experimented on the collected dataset by fine-tuning seven Arabic Pre-Trained language models (PLMs) which are: AraBERTv02, Arabertv02-twitter, QARIB, MarBERT, MARBERTv2, CAMeLBERT-DA, and CAMeLBERT-MIX to establish a baseline classification system. We concluded that CAMeLBERT-DA was the best-performing model and it achieved an F1-score and accuracy of 72.11%.
Recent Advances in Long Documents Classification Using Deep-Learning

Long document classification is one of the most challenging linguistic processing tasks. Recently, Recent deep-learning models such as the transformers have proven to perform this task with a high-level of success. Such models typically include the self-attention mechanism, which makes the calculations extremely complex as document length increases. In order to unlock the use of the most accurate document classification tools on a wider range of document types and make the use of methods based on self-attention practically feasible, it’s necessary to introduce some innovations that facilitate better scaling. In this work we provide a quick and concise survey of recent research work in the area of long documents classification using deep-learning techniques. The advantages and disadvantages of these methods have been discussed along with some directions that may be useful in future research.
Semantic Similarity Based Filtering for Turkish Paraphrase Dataset Creation

In this study, we introduce a new method for creating paraphrase datasets from parallel bilingual corpora. We also introduce large para-phrase datasets created using this method. We utilize machine translation to create paraphrase datasets by translating the English phrases in Turkish-English parallel datasets to Turkish. Detailed pre-processing steps are applied to the text pairs. A sample from our translated datasets was annotated by native speakers for semantic similarity, and a model with the same task was chosen based on the correlation with human annotations. We then filtered the pre-processed and translated text pairs by semantic similarity calculated by the chosen model. Two pre-trained encoder-decoder architectures were fine-tuned on the datasets that we created. We present results asserting our data collection and filtering method’s effectiveness.
TuniSER: Toward a Tunisian Speech Emotion Recognition System

Speech Emotion Recognition (SER) has become an important component for Human-Computer interaction. It is generally used in job interviews, caller-agent calls and streaming videos, etc. In the speech emotion recognition literature, many languages have tackled this topic to extract emotions from signals. The purpose of this work is to build a Speech Emotion Recognition model that predicts the emotional state of Tunisian speakers. We explore different pre-trained acoustic models, we detail the process of building the first Tunisian Speech Emotion Recognition dataset (TuniSER) and we describe the training and testing phases. Our experiments’ results show that fine-tuning the pretrained multilingual wav2vec 2.0 model on the Automatic Speech Recognition downstream task then building a classifier on top of fit out-performed all the tested models achieving an Accuracy of 60.6%.
Making Sense of Unstable Convergence in the Problem of Adaptive Observer Design: Case Study

Abstract We consider the problem of adaptive observer design for systems in which the uncertainties are modelled by ill-conditioned regressors or/and unknown parameters of the model enter the equations nonlinearly. It is shown that both of these critical issues can be overcome in a unified yet simple way, provided that the usual requirement of global asymptotic stability of solutions of model-observer system is replaced with a weaker constraint of mere set-attractivity. The claim is illustrated with a particular adaptive observer design problem.
Improving NL-to-Query Systems through Re-ranking of Semantic Hypothesis

Natural Language-to-Query systems translate a natural language question into a formal query language such as SQL. Typically the translation results in a set of candidate query statements due to the ambiguity of natural language. Hence, an important aspect of NL-to-Query systems is to rank the query statements so that the most relevant query is ranked on top. We pro-pose a novel approach to significantly improve the query ranking and thus the accuracy of such systems . First, we use existing methods to translate the natural language question ( NL in ) into k query statements and rank them. Then we translate each of the k query statements back into a natural language question ( NL gen ) and use the semantic similarity between the original question NL in and each of the k generated questions NL gen to re-rank the output . Our experiments on two standard datasets, OTTA and Spider, show that this technique improves even strong state-of-the-art NL-to-Query systems by up to 9 percentage points. A detailed error analysis shows that our method correctly down-ranks queries with missing relations and wrong query types. While this work is focused on NL-to-Query, our method could be applied to any other semantic parsing problems as long as a text generation method is available.
Second-order Document Similarity Metrics for Transformers

The similarity of documents represented using static word embeddings is best measured us-ing second-order metrics accounting for the co-variance of the embeddings. Transformers provide superior representations for words compared to static embeddings, but document representation and similarity evaluation are currently often done using simple mean pooling. We explain how the second-order metrics can be used also with transformers, and evaluate the value of improved metrics in this context
Concatenative Phonetic Synthesis for the Proto-Indo-European Language

We propose a ﬂexible concatenative text-to-speech system to synthesize hypothesized pro-nunciations of the reconstructed Proto-Indo-European language. To accomplish this, we synthesize speech examples in 100 extant languages and extract individual phones. Using this large database of phonetic sounds, we concatenate individual phonemes together to estimate pronunciations of Proto-Indo-European. Where available, we prioritize consecutive phones from the same source to help increase naturalness and intelligibility of the synthesized speech. Since the language’s precise pro-nunciation is debated, we provide an interface to select the speciﬁc phonetic symbol(s) used for each of the language’s phonemes and diph-thongs. We provide this novel interactive tool to enable researchers and students to aurally explore the different and competing phonological hypotheses debated in the literature.
Exploiting Data Parallelism in Graph-Based Simultaneous Localization and Mapping: A Case Study with GPU Accelerations

Graph-based simultaneous localization and mapping (G-SLAM) is an intuitive SLAM implementation where graphs are used to represent poses, landmarks and sensor measurements when a mobile robot builds a map of the environment and locates itself in it. Being a very important application employed in many realistic scenarios, estimating the whole environment and all trajectories through solving graph problems for SLAM can incur a large amount of computation and consume a significant amount of energy. For the purpose of improving both performance and energy efficiency, we have unveiled the critical path of the G-SLAM algorithm in this paper and implemented a GPU-based solution to aid it. Furthermore, we have attempted to offload performance-critical components (such as matrix inversions when updating the trajectory) in the G-SLAM process into GPUs through CUDA to exploit data parallelism. With our solution, we observe a speed-up of up to 19.7x and an energy saving of up to 83.7% over a modern workstation class x86 CPU; while on a platform dedicated for edge computing (NVIDIA Jetson Nano), we achieve a speed-up of up to 2.5x and an energy saving of up to 6.4% with its integrated GPU, respectively.