Miracle-dz/UniFAR-FTUs huggingface dataset:
Enhancing Neonatal Pain Assessment Transparency via Explanatory Training Examples Identification

Deep Learning (DL)-based solutions have shown promising performance in assessing neonatal pain. However, the occlusion of the visual modality (face and body) is common in clinical settings due to several factors, including a prone sleeping position, low light, or swaddling. In such scenarios, other pain signals, such as audio signals, can be used as the major behavioral signs of pain. Although DL-based methods are proposed to assess pain from audio, these methods lack transparency and explainability (black box), which can decrease the user's trust in the automated decision. In this work, we visualize the neonate's audio signal as a spectrogram image to classify it as pain or no pain and present an instance-based approach for explaining the decision of the black-box model. Further, this work provides an analysis of the most helpful and harmful training instances using an influence score followed by assessing their impact on pain prediction. Experimental results demonstrate that the proposed approach can detect and remove harmful instances, eventually leading to a compressed dataset. Our results also show that the proposed work can add explainability to the current DL-based pain detection methods, which can enhance users' trust and provide a viable approach toward pain assessment in clinical settings.
Perspective: A review on memristive hardware for neuromorphic computation

Neuromorphic computation is one of the axes of parallel distributed processing, and memristor-based synaptic weight is considered as a key component of this type of computation. However, the material properties of memristors, including material related physics, are not yet matured. In parallel with memristors, CMOS based Graphics Processing Unit, Field Programmable Gate Array, and Application Specific Integrated Circuit are also being developed as dedicated artificial intelligence (AI) chips for fast computation. Therefore, it is necessary to analyze the competitiveness of the memristor-based neuromorphic device in order to position the memristor in the appropriate position of the future AI ecosystem. In this article, the status of memristor-based neuromorphic computation was analyzed on the basis of papers and patents to identify the competitiveness of the memristor properties by reviewing industrial trends and academic pursuits. In addition, material issues and challenges are discussed for implementing the memristor-based neural processor.
Vehicle-Borne Multi-Sensor Temporal–Spatial Pose Globalization via Cross-Domain Data Association

Large-scale urban scene 3D mapping has urgent demands and wide applications in many areas, where sensor pose globalization remains its fundamental problem and critical step. As the street-view images and vehicle-borne Light Detection And Ranging (LiDAR) points contain complementary advantages in urban scene 3D mapping, it is desirable to make the most of both to facilitate this task. Most existing methods make strong assumptions of strict synchronization, and even further, exact calibration between the vehicle-borne cameras and LiDARs, which are hard to guarantee in practice. To deal with this, we propose a novel pipeline for vehicle-borne camera and LiDAR temporal and spatial pose globalization with the guidance of Global Navigation Satellite System/Inertial Measurement Unit (GNSS/IMU), where both of the assumptions on strict synchronization and exact calibration are loosened. Specifically, the global poses of both cameras and LiDARs are first initialized by leveraging GNSS/IMU signals and multi-sensor pre-calibrations, and then refined by a global optimization scheme. To perform the global pose optimization, image-based, LiDAR-based, and cross-domain data association and constraint construction are conducted. Among them, the cross-domain ones, which are achieved by LiDAR point projection, image feature back-projection, and spatial point association, provide key clues for associating these two kinds of data with significant differences. Comprehensive experiments on both of a self-collected and the KITTI Odometry datasets demonstrate the effectiveness of our proposed method on multi-sensor pose globalization for large-scale urban scene 3D mapping.
Newer Modalities in Psychopharmacology in Children and Adolescents: A Selective Narrative Review of the Literature

Research in psychopharmacology in children and adolescents is an area of growing interest with numerous newer modalities becoming available in recent years. Nevertheless, it still lags significantly behind research in adult psychopharmacology although, in the last decade, the gap is beginning to be bridged with FDA approval for newer agents for the paediatric age group. The purpose of this selective narrative review is to examine the latest advances in psychopharmacology in the last decade and their safety, tolerability and applicability in children and adolescents. In methodology, we identified 4 main areas of recent advances in psychopharmacology, viz. Ketamine, Nitrous Oxide, Cannabidiol and cannabis derivates and the area of pharmacogenomics. We then conducted a comprehensive search of the literature using PubMed, Embase and Ovid databases to identify the most recent updates in these areas, especially focussed on the paediatric population. The search was limited to English language studies and focussed on recent updates in these four areas. In the results, it was seen that all the four identified areas have potential applicability in children and adolescents with some studies evaluating their safety and tolerability in the paediatric population. However, literature on the long-term safety and efficacy of these newer modalities in the paediatric population is limited and none of the identified agents are currently recommended for routine clinical use in children and adolescents. Overall, it could be concluded that the results of this selective narrative review suggest that newer modalities in psychopharmacology offer promising treatments for psychiatric disorders in children and adolescents. However, further research is needed to fully understand the long-term safety and efficacy of these treatments as well as optimal dosing and monitoring strategies to ensure their safe and effective use in the paediatric population.
Nonlinear maps preserving the pseudo spectral radius of skew semi-triple products of operators

Let H be a complex Hilbert space of dimension greater than 2,and denote by ℒ( H ) the algebra of all bounded linear operators on H . For ε > 0 and T 2 L( H ), let r _ε( T ) denote the ε-pseudo spectral radius of T . Let G _1and G _2 be subsets of ℒ( H ) which contain all rank one operators and the identity. A characterization is obtained for surjective maps ϕ: G_1 → G _2 satisfying r _ε(ϕ( T )ϕ( S ) ϕ( T )) = r _ϕ( T, S ∈ G _1) (T, S 2 S1). An analogous description is also obtained for the pseudo spectrum of operators.
Apolipoprotein E deficiency potentiates macrophage against Staphylococcus aureus in mice with osteomyelitis via regulating cholesterol metabolism

Introduction Staphylococcus aureus (S. aureus) osteomyelitis causes a variety of metabolism disorders in microenvironment and cells. Defining the changes in cholesterol metabolism and identifying key factors involved in cholesterol metabolism disorders during S. aureus osteomyelitis is crucial to understanding the mechanisms of S. aureus osteomyelitis and is important in designing host-directed therapeutic strategies. Methods In this study, we conducted in vitro and in vivo experiments to define the effects of S. aureus osteomyelitis on cholesterol metabolism, as well as the role of Apolipoprotein E (ApoE) in regulating cholesterol metabolism by macrophages during S. aureus osteomyelitis. Results The data from GSE166522 showed that cholesterol metabolism disorder was induced by S. aureus osteomyelitis. Loss of cholesterol from macrophage obtained from mice with S. aureus osteomyelitis was detected by liquid chromatography-tandem mass spectrometry(LC-MS/MS), which is consistent with Filipin III staining results. Changes in intracellular cholesterol content influenced bactericidal capacity of macrophage. Subsequently, it was proven by gene set enrichment analysis and qPCR, that ApoE played a key role in developing cholesterol metabolism disorder in S. aureus osteomyelitis. ApoE deficiency in macrophages resulted in increased resistance to S. aureus. ApoE-deficient mice manifested abated bone destruction and decreased bacteria load. Moreover, the combination of transcriptional analysis, qPCR, and killing assay showed that ApoE deficiency led to enhanced cholesterol biosynthesis in macrophage, ameliorating anti-infection ability. Conclusion We identified a previously unrecognized role of ApoE in S. aureus osteomyelitis from the perspective of metabolic reprogramming. Hence, during treating S. aureus osteomyelitis, considering cholesterol metabolism as a potential therapeutic target presents a new research direction.
Drop-DIP: A single-image denoising method based on deep image prior

Over the past few years, deep learning methods have emerged as powerful image denoising tools. Among them, unsupervised deep learning without external training data is more practical and challenging. Reducing noisy overﬁtting is challenging due to single-image unsupervised learning is prone to overﬁtting. In this paper, we propose a method named drop-DIP combing Deep Image Prior (DIP) with drop-out for the ﬁrst time to solve the above problems. In our method, we construct new network training pairs by performing drop-out training on the Bernoulli sampling of the input and output, and then construct a regularization term by using the corrected bias of the output and the generated prior. Finally, update the parameters through the Alternating Direction Method of Multipliers (ADMM) algorithm. Experiments demonstrate that drop-DIP can alleviate the overﬁtting difﬁculty in DIP, facilitate the early stopping of the network, and is applicable to different noise models. Furthermore, our method has good performance on Peak Signal to Noise Ratio (PSNR), Structural Similarity (SSIM), and Learned Perceptual Image Patch Similarity (LPIPS) metrics validated by two different datasets.
PART TIME WIFE (ESPOSA A MEDIAS) (1930) DE LEO McCAREY: UNA PELÍCULA PRECURSORA DE LAS COMEDIAS REMATRIMONIO DE HOLLYWOOD

Part Time Wife es considerado el primer largometraje de Mc- Carey en el que aparecen sus rasgos más propios. Por su temática y por su relación con The Awful Truth (1937) puede considerarse una comedia de rematrimonio de Hollywood. En ella pueden distinguirse dos núcleos temáticos: el conflicto matrimonial o la amenaza del divorcio y el rematrimonio como retorno al Paraíso.
Asymptotic Analysis of Regularized Zero-Forcing Precoding in MISO Broadcast Channels with Limited Feedback

In this paper we analyse the asymptotic sum-rate of regularized zero-forcing (RZF) precoding in MISO broadcast channels with limited feedback, transmit correlation and path- loss. Our analysis assumes that the ratio of the number of transmit antennas M to the number of users K is bounded as (K; M ) grow large. By applying recent results from random matrix theory we derive a deterministic equivalent of the SINR and compute the sum-rate maximizing regularization term as well as sum-rate bounds for high SNR. Numerical simulations show that the asymptotic results extend well into ﬁnite regimes.
The hyperosculating Points of the Generalized Fermat Curves

Let $(S,H)$ be a generalized Fermat curve of the type $(k,n)$ and let $F\subset S$ be the set of the fixed point by $H$. In this article we will show that $F$ is exactly the set of hyperosculating points of the standard embedding of $S$, and we will give an lower bound (non trivial) for the Weierstrass weight of these points.
Applications of Nonlinear Optical Gain Mechanisms from Phonon and Atomic Vapor Interactions

There are many methods to achieve optical gain for laser applications; such methods have been used to make improved spectroscopy and microscopy apparatus. In particular, gain from acoustic and atomic interactions has attained much interest, as is evident in the literature. In this work, we report the results of several experiments involving nonlinear Brillouin scattering and three-level gain in rubidium vapor. Brillouin scattering, both spontaneous and stimulated, in principle result from the scattering of light off of acoustic waves in a medium. While both spontaneous and stimulated Brillouin scattering have been applied to spectroscopy of various samples, from condensed matter to gases, only spontaneous Brillouin scattering has been used for microscopy purposes. We report our result from several proof-of-principle experiments in which stimulated Brillouin scattering and impulsive stimulated Brillouin scattering were applied to microscopic purposes for the first time. We show the advantages these methods afford over spontaneous Brillouin scattering and make a statistical comparison between them. There are also many ways to achieve gain in atomic vapors. Using a setup similar to the stimulated Brillouin scattering setup we performed gain in a three-level Λ system in warm rubidium vapor. To our knowledge, this is the first time this three-level analog of Mollow’s two-level system with Doppler broadening has been experimentally investigated. Our results show about 0.12% gain in the probe beam. This work, and extensions of it, should provide additional methods of performing spectroscopy and microscopy in various materials from atoms to bulk matter.
Variant identification in human periodontal ligament stem cells associated to proto-oncogenes: A review

An oncogene is a gene that has the potential to cause cancer. Dental caries and periodontitis cause enormous health care costs and morbidity, but their genetic basis remains largely unknown. Clinical laboratories implement a variety of measures to classify somatic and sequence variants identifies clinically relevant variants to facilitate implementation of precision medicine. We developed a semi-automated tool called Variant Interpretation for Periodontal Cancer (VIC) to speed up the interpretation process and minimize individual risk biases. VIC loads pre-annotated files and automatically classifies sequence variants based on multiple criteria, with the ability for users to include additional evidence to streamline interpretation for clinical implications evaluated the VIC using several publicly available databases and compared it to several forecasting programs. Although the VIC cannot replace human examiners, it will speed up the process of interpreting variants. VIC can also be adapted by clinical laboratories into their analytical pipelines to ease the tedious process of variant interpretation.
Research and Practice of Automatic Identification Method for Construction Materials based on Deep Learning

Based on computer vision technology, this paper proposes an automatic identification method for construction materials based on deep learning. For the "artificial counting method", "artificial counting accuracy" and "artificial counting efficiency", the material counting on construction sites is completed by using algorithms instead of the artificial method from the perspective of "the best engineering practice". The engineering practice shows that this technology can greatly improve the material counting efficiency of managers on construction sites comprehensively.
Work-based learning partnerships: mentor-teachers’ perceptions of student teachers’ challenges

ABSTRACT Background For prospective teachers, the school-based learning component of their teacher education programme is a crucial, and often demanding, part of becoming a teacher. During this time, mentor-teachers work in close collaboration with student teachers, who are often teaching in an actual school setting for the first time. As the relationship between mentor-teacher and student teacher is pivotal to the quality of work-based learning and to supporting the professional development of prospective teachers, more needs to be understood about this complex dynamic. Purpose Our study aimed to contribute to this area by investigating, from the viewpoint of mentor-teachers, how student teachers respond to the demands of work-based learning. It had a particular focus on mentor-teachers’ perceptions of student teachers’ emotional challenges associated with teaching and engagement. Methods Data consisted of interviews with 22 experienced mentor -teachers from five different municipalities. Data were analysed qualitatively, using tools aligned with a constructivist grounded theory approach. Findings Describing teaching as a complex practice, the mentor-teachers regarded proactive engagement in developing professionalism, and ability to make appropriately differentiated adjustments to their teaching as important criteria in their evaluation of student teacher progression. The mentor-teachers described student teachers’ emotional challenges in relation to these and discussed support strategies. Conclusions The findings of the study highlight the complex dynamic of work-based learning and the key role that mentor-teachers can play in supporting the development of prospective teachers entering the profession, including the navigation of emotionally challenging situations.
The influence of the COVID-19 pandemic on videolaryngoscopy: a cross-sectional before-and-after survey

Background Guidelines and consensus statements recommend the use of videola-ryngoscopes (VLs) in airway management of patients with COVID-19. However, there is a lack of knowledge about which types of videolaryngoscopes are used, differences of use between countries, and how the COVID-19 pandemic influenced their use. The primary aim of this before-and-after cross-sectional survey study was to assess the frequency of the use of videolaryngoscopy in the operation theatres in different countries. Also, the preferred characteristics of videolaryngoscopes were assessed. Methods With Ethics Committee approval, a questionnaire was distributed among anaes-thesiologists through the European Airway Management Society’s network in 2019 before and in 2021 during the COVID-19 pandemic. Responses to the questions were analysed and presented as descriptive statistics. Results We reached out to 791 anaesthesiologists; 155 (19.5%) returned the first questionnaire, and 91 (11.5%) returned the second survey. Videolaryngoscopes were used in 24.1% of cases before COVID-19 and in 43.1% after the pandemic (P < 0.001). We revealed that the availability of videolaryngoscopes increased to 100% in all centres during the pandemic. Routine use of videolaryngoscopes in all cases increased from 12.5% to 38.9%. The type of videolaryngoscope and the blade preference did not change during this period (P = 1.000). Conclusions This survey reflects that the COVID-19 pandemic significantly increased the availability and use of videolaryngoscopes in operating theatres, and that more anaesthesiologists now use them routinely in all cases. The preferred type of VL or blade did not change during the pandemic.
Time-Optimal Trajectory Planning along Parametric Polynomial Lane-Change Curves with Bounded Velocity and Acceleration: Simulations for a Unicycle Based on Numerical Integration

G2 lane-change path imposes symmetric conditions on the path geometric properties. This paper presents the comparative study of time-optimal velocities to minimize the time needed for traversal of three planar symmetric parametric polynomial lane-change paths followed by an autonomous vehicle, assuming that the neighboring lane is free. A simulated model based on unicycle that accounts for the acceleration and velocity bounds and is particularly simple for generating the time-optimal path parameterization of each lane-change path is adopted. We base the time-optimal trajectory simulations on numerical integration on a path basis under two different end conditions representing sufficient and restricted steering spaces with remarkable difference in allowable maximum curvature. The rest-to-rest lane-change maneuvering simulations highlight the effect of the most relevant path geometric properties on minimal travel time: a faster lane-change curve such as a quintic Bezier curve followed by a unicycle tends to be shorter in route length and lower in maximum curvature to have achievable highest speed at the maximum curvature points. The results have implications to path selection for parallel parking and allow the design of continuous acceleration profile via time scaling for smooth, faster motion along a given path. This could provide a reference for on-road lane-change trajectory planning along a given path other than parametric polynomials for significantly more complex, complete higher-dimensional highly nonlinear dynamic model of autonomous ground vehicle considering aerodynamic forces, tire and friction forces of tire-ground interaction, and terrain topology in real-world.
Zone defense: Why liberal cities build too few homes

In this article, I investigate a puzzling feature of American urban politics: cities with more liberal residents tend to enact more restrictive zoning policies and permit fewer new housing units each year than similar conservative cities. To help explain this puzzle, I develop a formal model in which local governments regulate the size of their population to balance the benefits of agglomeration with the costs of congestion. To defend against congestion externalities imposed by new residents, cities enact zoning policies that undersupply housing relative to the social optimum. In liberal cities, where residents value the benefits of agglomeration the most, this undersupply of housing is the most severe.
Lipid Based Formulations of Biopharmaceutics Classification System (BCS) Class II Drugs: Strategy, Formulations, Methods and Saturation

Abstract Active ingredients in pharmaceuticals differ by their physico-chemical properties and their bioavailability therefore varies. The most frequently used and most convenient way of administration of medicines is oral, however many drugs are little soluble in water. Thus they are not sufficiently effective and suitable for such administration. For this reason a system of lipid based formulations (LBF) was developed. Series of formulations were prepared and tested in water and biorelevant media. On the basis of selection criteria, there were selected formulations with the best emulsification potential, good dispersion in the environment and physical stability. Samples of structurally different drugs included in the Class II of the Biopharmaceutics classification system (BCS) were obtained, namely Griseofulvin, Glibenclamide, Carbamazepine, Haloperidol, Itraconazol, Triclosan, Praziquantel and Rifaximin, for testing of maximal saturation in formulations prepared from commercially available excipients. Methods were developed for preparation of formulations, observation of emulsification and its description, determination of maximum solubility of drug samples in the respective formulation and subsequent analysis. Saturation of formulations with drugs showed that formulations 80 % XA and 20 % Xh, 35 % XF and 65 % Xh were best able to dissolve the drugs which supports the hypothesis that it is desirable to identify limited series of formulations which could be generally applied for this purpose.