Miracle-dz/UniFAR-FTUs huggingface dataset:
Design, Characterization and Pharmacokinetic–Pharmacodynamic Evaluation of Poloxamer and Kappa-Carrageenan-Based Dual-Responsive In Situ Gel of Nebivolol for Treatment of Open-Angle Glaucoma

This study developed a dual-responsive in situ gel of nebivolol (NEB), a selective β-adrenergic antagonist. The gel could achieve sustained concentrations in the aqueous humor to effectively treat glaucoma. The gel was prepared using a combination of poloxamers (Poloxamer-407 (P407) and Poloxamer-188 (P188)) and kappa-carrageenan (κCRG) as thermo-responsive and ion-sensitive polymers, respectively. Box–Behnken design (BBD) was used to optimize the effect of three critical formulation factors (concentration of P407, P188 and κCRG) on two critical response variables (sol-to-gel transition temperature of 33–35 °C and minimum solution state viscosity) of the in situ gel. A desirability function was employed to find the optimal concentrations of P407, P188 and κCRG that yielded a gel with the desired sol-to-gel transition temperature and solution state viscosity. An NEB-loaded gel was prepared using the optimized conditions and evaluated for in vitro drug release properties and ex vivo ocular irritation studies. Furthermore, ocular pharmacokinetic and pharmacodynamics studies were conducted in rabbits for the optimized formulation. The optimized NEB-loaded gel containing P407, P188 and κCRG had a sol-to-gel transition temperature of 34 °C and exhibited minimum viscosity (212 ± 2 cP at 25 °C). The optimized NEB-loaded gel sustained drug release with 86% drug release at the end of 24 h. The optimized formulation was well tolerated in the eye. Ocular pharmacokinetic studies revealed that the optimized in situ gel resulted in higher concentrations of NEB in aqueous humor compared to the NEB suspension. The aqueous humor Cmax of the optimized in situ gel (35.14 ± 2.25 ng/mL) was 1.2 fold higher than that of the NEB suspension (28.2 ± 3.1 ng/mL), while the AUC0–∞ of the optimized in situ gel (381.8 ± 18.32 ng/mL*h) was 2 fold higher than that of the NEB suspension (194.9 ± 12.17 ng/mL*h). The systemic exposure of NEB was significantly reduced for the optimized in situ gel, with a 2.7-fold reduction in the plasma Cmax and a 4.1-fold reduction in the plasma AUC0–∞ compared with the NEB suspension. The optimized gel produced a higher and sustained reduction in the intra-ocular pressure compared with the NEB suspension. The optimized gel was more effective in treating glaucoma than the NEB suspension due to its mucoadhesive properties, sustained drug release and reduced drug loss. Lower systemic exposure of the optimized gel indicates that the systemic side effects can be significantly reduced compared to the NEB suspension, particularly in the long-term management of glaucoma.
Animal sheltering: A scoping literature review grounded in institutional ethnography

A diverse research literature now exists on the animals, staff and organisations involved in animal sheltering. We reviewed this research through the lens of institutional ethnography, a method of inquiry that focuses on the actual work that people do within institutions. The main topics, identified through a larger ethnographic study of animal sheltering, were: (i) research about shelter staff and officers; (ii) the relinquishment of animals to shelters; and (iii) animals’ length of stay in shelters. After reviewing the literature, we held focus groups with shelter personnel to explore how their work experiences are or are not represented in the research. The review showed that stress caused by performing euthanasia has attracted much research, but the decision-making that leads to euthanasia, which may involve multiple staff and potential conflict, has received little attention. Research on ‘compassion fatigue’ has also tended to focus on euthanasia but a granular description about the practical and emotional work that personnel undertake that generates such fatigue is missing. Published research on both relinquishment and length of stay is dominated by metrics (questionnaires) and often relies upon shelter records, despite their limitations. Less research has examined the actual work processes involved in managing relinquishment as well as monitoring and reducing animals’ length of stay. Institutional ethnography’s focus on people’s work activities can provide a different and more nuanced understanding of what is happening in animal sheltering and how it might better serve the needs of the animals and staff.
On the pre-main sequence circularization period

In this paper we present an updated compilation of the currently known pre-main sequence (PMS) spectroscopic binaries (SB) for which orbital elements have been determined. In particular we report our results for and discuss the case of the bona-de PMS system RX J1603.9-3938, which has a circular orbit and a period of 7.56 days. This is the longest orbital period for a circular orbit found among the bona-de PMS spectroscopic binaries so far, and we suggest that this system may be thus considered to now set the PMS circularization period. The longer period is compatible with the circularization periods already known for older binary populations such as the Hyades and Praesepe. When considered in the context of the circularization periods for other binary populations of dierent ages, the new PMS circularization period strongly supports the suggestion of Mathieu et al. (1992) that a hybrid scenario (tidal circularization occurring on both PMS phase and on MS phase) could explain the observed circularization periods as a function of age. The apparently circular orbit observed in another PMS system, RX J1301.0-7654a, with an orbital period of nearly 13 days, may perhaps change this picture when the orbit is improved and the system is better understood.
Information Fusion-Based Fault Diagnosis Method Using Synthetic Indicator

Multisensor information fusion technology plays an essential role in fault diagnosis. Uncertain reasoning is the core of information fusion, and the DS evidence theory (DSE) has founded a general and popular framework for uncertainty reasoning. Under this framework, a novel information fusion method is developed in this article, to solve the problems of counterintuitive results, poor robustness, and “one-vote veto” when fusing highly conflicting evidence using DSE. We proposed a new synthetic indicator, which can effectively eliminate the conflicts between evidences. This synthetic indicator is composed of two indexes: measurement index of indirect conflicts and that of the evidence’s information itself. First, the divergence is used to measure the degree of conflict between bodies of evidence, and the Decision-Making Trial and Evaluation Laboratory (DEMATEL) model is employed to deal with indirect conflicts. Second, the Deng entropy is utilized to quantitatively measure the uncertainty of evidences, and the relative credibility preference of the evidence is expressed by the fuzzy preference relation. Finally, the initial body of evidence frame is weighted and revised by synthetic indicator before adopting the Dempster Shafer (DS) fusion rule. The superiority of the developed method is illustrated by numerical examples and application cases. The results show that fault diagnosis using the developed information fusion method can have a higher diagnostic accuracy.
Environmental sound classification of western black-crowned gibbon habitat based on subspace method and DenseNet121

The performance of ambient sound classification has substantially improved with the development of neural networks. The presence of noise in the classification of ambient sound remains a significant difficulty, nevertheless. In this research, we offer a method for classifying ambient noises under noise interference, with the main goal of increasing the classification accuracy of the model in the presence of noise interference, for the scenario where noise affects the classification effect. Prior to extracting the Mel frequency cepstrum parameter features and feeding them into the calibrated DenseNet121 model for classification training, the input ambient audio is first noise-reduced using the subspace approach. The more common five sound kinds were categorised using the experimental data to determine the environmental sounds gathered by the western black-crowned gibbon's acoustic monitoring system in the Mourning Mountains. The proposed method improves the accuracy of the training and test sets by 3.3% and 3.2%, respectively, and achieves a classification accuracy of 98.7%.
Crosshatched surface morphology in strained III‐V semiconductor films

The correlation between the surface crosshatched morphology and the interfacial misfit dislocations in strained III‐V semiconductor heteroepitaxy has been studied. The surface pattern is clearly seen on samples grown at high temperature (520 °C) and those with small lattice‐mismatched (f<2%) systems. A poorly defined crosshatched morphology was found on layers grown at relatively low temperature (400 °C). As the lattice mismatch of the strained layer becomes larger than 2%, a roughly textured surface morphology is commonly observed in place of actual cross‐hatching. Few threading dislocations are observed in the strained layer when the crosshatched pattern develops. It is also noted that the surface crosshatched pattern develops after the majority of the interfacial misfit dislocations are generated. The result suggests that the surface crosshatch pattern is directly related to the generation of interfacial misfit dislocations through glide processes.
Scalar-flat Kähler and hyper-Kähler metrics from Painlevé-III

Motivated by the Bianchi-type-IX scalar-flat Kahler metric of Pedersen and Poon, an ansatz is presented which reduces the -Toda field equation to special cases of the Painleve-III differential equation. This leads to new four-dimensional, scalar-flat, Kahler and hyper-Kahler metrics based on Painleve transcendents. By considering the relation between Einstein--Weyl spaces and the -Toda field equation, we classify separable solutions of the latter equation and then characterize those Einstein--Weyl spaces which arise from it.
Simulation of the break-up of a diphasic jet in a microchannel

In this paper, diphasic flows driven by pressure gradient in channels of a few hundred of micrometres square sections are studied. At this scale, the interfacial effects are dominating and the instabilities processes are generally studied from the experimental point of view. The instability is a well-known hydrodynamic instability due to surface tension namely the Plateau-Rayleigh instability. In this work, tridimensional numerical simulations are presented to understand this phenomenon and more generally to study the behaviour of diphasic fluids evolving in square microchannels.
Nanofabrication of TiO2 nanowires: I-V characteristic and improvement of metal oxides gas sensing properties

A cheap nanofabrication process for Titania (TiO2) polycristalline nanowire array for gas sensing applications with lateral size ranging from 90 to 180 nm, and gas sensing characterizations are presented. Alternatively to typical pattern transfer techniques for submicron fabrication, authors focused on a standard 365 nm UV photolithographic process able to fabricate sol-gel nanostructured titania nanowires from a solid thin film. Main aim of present work is the experimental validation of enhanced gas sensing response of nanopatterned metal oxide thin film sensors. Two different kind of gas sensor with nanopatterned sensitive area have been realized onto silicon substrates and tested towards different EtOH concentrations; experimental tests have been carried out with a contemporary output signals collection from a nanowires-based gas sensor and a second device with solid sensitive film without patterning, in order to validate effects of nano-machining on sensitive material response.
Nine Questions to Evaluate a Data Science Team’s Process: Exploring a Big Data Science Team Process Evaluation Framework Via a Delphi Study

While the lack of an effective team process is often noted as one of the key drivers for data science project inefficiencies and failures, there has been minimal research on how to evaluate a data science team’s process. Without an evaluation framework, it is difficult for data science teams to understand their team process strengths and weaknesses. To help address this challenge, this exploratory research, via a Delpha study, identified nine key questions a data science team could answer to help evaluate their process. In short, the study identified questions evaluating the team’s communication (within the team and with stakeholders). The study also identified team process questions (e.g., the use of iterations, life cycles and a prioritization process for potential tasks). Future research could explore how data science teams can best improve their process by leveraging and refining these questions as well as defining an overall data science project management evaluation framework.
Technical Report: The Fastest Relativistic Jets from Quasars and Active Galactic Nuclei

Among the major advances in astronomy over the past several decades has been the realization that supermassive black holes (up to of order 109 solar masses) are a ubiquitous feature at the centers of bright galaxies [1], including the center of our own Milky Way. Material from the host galaxy that is drawn close to the central supermassive black hole can form a rotating accretion disk around the central object. This infalling matter can liberate large amounts of gravitational binding energy as radiation, causing the hot accretion disk and surrounding gas to far outshine the host galaxy, and forming an object known as a quasar, or, at lower luminosity, an active galactic nucleus (AGN). Quasars are predominantly seen at large cosmological distances, and therefore at remote times in the past, presumably before they have exhausted the reserves of fuel surrounding the central black hole and become quiescent. Since quasars were first detected in 1963 [2], they have fascinated astronomers with their enormous ene.
Ethical Issues in Automatic Dialogue Generation for Non-Player Characters in Digital Games

In game industry, natural language processing (NLP) has been expected to be applied to digital games, but was impossible for several reasons such as memory limitation, CPU resource limitation, and degree of maturity of NLP. However, with the advent of the Transformer architecture in the late 2010s and the huge amount of text resources in the Internet, NLP technology is rapidly advancing. Large-scale pre-trained language models, or foundation models, are now capable of generating sentences that are comparable to those of humans, and their application to creative use is being explored. The incorporation of NLP, especially conversation generation, into digital games is expected to allow users to communicate more freely with non-player characters (NPCs) in a fictional world. In generating the speech of the inhabitants of the virtual world, it is thought that considerations unique to digital games, apart from the ethical considerations of conversation generation in general, will be necessary. We have created a technical demo of a digital game using single-turn conversation generation and discussed issues for its practical application and commercialization. In this paper, we argue that it is necessary to consider the ethics of characters and the ethics of content as a whole in a hierarchical manner. For example, an entertainment story may include a villain who torments the protagonist. Such a villain character does not have a general sense of ethics. When a user converses with such a character, there is a concern that user will be disappointed if the automatically generated statements of the immoral character are morally correct. Entertainment sometimes requires amorality, and eliminating all ethically incorrect content is not always a good policy. In addition, inhabitants in fictional worlds may live under different ethical standards than those in our real world. The utterances of NPCs in such worlds should be based on their morals, not ours. On the other hand, the entire digital game, including these conversational agents, would naturally be evaluated according to the ethics of our world. Thus, we argue that hierarchical ethical considerations for the automatic generation of character utterances in digital games are essential for designing the digital games in the incoming era.
Random laser-based noninvasive sensor for direct measurements of scattering samples

The invention of the random laser has opened a new frontier in optics, providing also the opportunity to explore new possibilities in the field of sensing. The research in optical sensors has indeed been largely encouraged by the demand for low-cost and non-invasive new detection strategies. The main advantage in exploiting the physical principle of the random laser in optical sensors is due to the presence of the stimulated emission mechanism, which allows amplification and spectral modification of the signal. We present here a step forward in the exploitation of this optical sensor device by an improved revisitation of a previous experimental setup, both in the instrumentation and in the measurement method, to mitigate the instability of the results due to shot-to-shot pump energy fluctuations. The novelties introduced, the use of optical fibers, a reference sensor, and a peristaltic pump have shown to eliminate optical beam alignment issues and the problems linked to variation in pump energy. The implemented sensor allows easy and rapid change of the sensed medium. These results pave the way for a portable device to directly measure the scattering of liquid samples, without resorting to complicated numerical or analytic inversion procedures of the measured data, provided that a suitable calibration of the system is performed.
A Deep Learning Method Using Gender-Specific Features for Emotion Recognition

Speech reflects people’s mental state and using a microphone sensor is a potential method for human–computer interaction. Speech recognition using this sensor is conducive to the diagnosis of mental illnesses. The gender difference of speakers affects the process of speech emotion recognition based on specific acoustic features, resulting in the decline of emotion recognition accuracy. Therefore, we believe that the accuracy of speech emotion recognition can be effectively improved by selecting different features of speech for emotion recognition based on the speech representations of different genders. In this paper, we propose a speech emotion recognition method based on gender classification. First, we use MLP to classify the original speech by gender. Second, based on the different acoustic features of male and female speech, we analyze the influence weights of multiple speech emotion features in male and female speech, and establish the optimal feature sets for male and female emotion recognition, respectively. Finally, we train and test CNN and BiLSTM, respectively, by using the male and the female speech emotion feature sets. The results show that the proposed emotion recognition models have an advantage in terms of average recognition accuracy compared with gender-mixed recognition models.
The neutral carbon distribution in a bipolar outflow/molecular disc source configuration: G35.2−0.74N

Maps are presented of P-3(1)-->P-3(0) [C I] and J=2-->1 (CO)-O-18 line emission from the interstellar molecular cloud G35.2-0.74N. The maps are interpreted with reference to a previous model for the structure of the cloud in which opposing jets from a central object, embedded in a rotating interstellar disc, precess and drive a bipolar molecular outflow. The (CO)-O-18 emission traces the rotating interstellar disc, but the [C I]] emission shows several features. An unresolved component is observed which probably results from dissociation of CO in the centre of the disc by UV radiation from the central source. Background [C I] emission is also observed which shares the rotation of the disc on larger scales. The C I/CO ratio in these components is typically a few per cent. High-velocity [C I] emission, where C I/CO is high (> 0.1-0.4), is observed between the CO molecular outflow and the cavity exacavated by the jet. This material has probably been accelerated by the jet but dissociated by far-UV radiation propagating through the cavity. The C I/CO ratio falls as the shocked outflow later sweeps up CO.
An Adaptive ORB-SLAM3 System for Outdoor Dynamic Environments

Recent developments in robotics have heightened the need for visual SLAM. Dynamic objects are a major problem in visual SLAM which reduces the accuracy of localization due to the wrong epipolar geometry. This study set out to find a new method to address the low accuracy of visual SLAM in outdoor dynamic environments. We propose an adaptive feature point selection system for outdoor dynamic environments. Initially, we utilize YOLOv5s with the attention mechanism to obtain a priori dynamic objects in the scene. Then, feature points are selected using an adaptive feature point selector based on the number of a priori dynamic objects and the percentage of a priori dynamic objects occupied in the frame. Finally, dynamic regions are determined using a geometric method based on Lucas-Kanade optical flow and the RANSAC algorithm. We evaluate the accuracy of our system using the KITTI dataset, comparing it to various dynamic feature point selection strategies and DynaSLAM. Experiments show that our proposed system demonstrates a reduction in both absolute trajectory error and relative trajectory error, with a maximum reduction of 39% and 30%, respectively, compared to other systems.
PostMe: Unsupervised Dynamic Microtask Posting For Efficient and Reliable Crowdsourcing

Even after over a decade of many crowdsourcing researches, we have no standard framework for low-cost quality assurance in crowdsourced data annotation. This paper proposes an unsupervised learning method for dynamic microtask posting which allows each microtask to adjust their own number of collected responses based on the data difficulty. Since crowdsourced data labels are likely to contain errors, researchers often employ majority voting that aggregates responses from multiple workers to calculate a final l abel. T his t echnique, h owever, i nvolves a trade-off between label accuracy and cost. This paper presents a dynamic microtask posting model that reduces the total number of collected responses while maintaining the labeling accuracy; we also aim to obtain the model with an “unsupervised” approach, which does not require training through experience of microtask posting for data labeled with ground-truths. Our simulation in annotating livestock surveillance images demonstrated that our approach achieved i) comparable learning performance to that of the supervised approach that required model training with labeled data, and ii) a significant c ost r eduction without degrading accuracy in comparison to simple majority voting.
Coupled-cavity resonant photodetectors for high-performance wavelength demultiplexing applications

A new coupled-cavity resonant photodetector structure is studied to provide a flat-topped passband with steep skirts in the photoresponse. The idea is to add a low-loss cavity that is optically coupled to the absorptive cavity via an intermediate mirror. Experimental reflection spectra confirm this coupling effect. Modeling for an InGaAs/GaAs/AlGaAs design reveals that this new coupled-cavity structure will be able to show a 22 dB channel rejection ratio even when the optical channel spacing is as narrow as 2 nm. In addition, the design and processing tolerances for cavity-mode adjustment are also addressed.