Miracle-dz/UniFAR-FTUs huggingface dataset:
Architecture of the brain’s visual system enhances network stability and performance through layers, delays, and feedback

In the visual system of primates, image information propagates across successive cortical areas, and there is also local feedback within an area and long-range feedback across areas. Recent findings suggest that the resulting temporal dynamics of neural activity are crucial in several vision tasks. In contrast, artificial neural network models of vision are typically feedforward and do not capitalize on the benefits of temporal dynamics, partly due to concerns about stability and computational costs. In this study, we focus on recurrent networks with feedback connections for visual tasks with static input corresponding to a single fixation. We demonstrate mathematically that a network’s dynamics can be stabilized by four key features of biological networks: layer-ordered structure, temporal delays between layers, longer distance feedback across layers, and nonlinear neuronal responses. Conversely, when feedback has a fixed distance, one can omit delays in feedforward connections to achieve more efficient artificial implementations. We also evaluated the effect of feedback connections on object detection and classification performance using standard benchmarks, specifically the COCO and CIFAR10 datasets. Our findings indicate that feedback connections improved the detection of small objects, and classification performance became more robust to noise. We found that performance increased with the temporal dynamics, not unlike what is observed in core vision of primates. These results suggest that delays and layered organization are crucial features for stability and performance in both biological and artificial recurrent neural networks.
Finite difference modelling of P-wave scattering in the upper mantle

Summary Scattering within the upper mantle is prominently documented in the so-called high-frequency teleseismic Pn phase, generated by velocity fluctuations in the upper mantle. This phase is seen in many data sets from active and passive seismology. Whenever the source-generated frequencies are high enough (5–10 Hz) to allow their observation at large distances (>2000 km), this phase appears in the recordings of the Russian PNE programme, in other long-range refraction experiments, and in numerous recordings of earthquakes. Using a 2-D finite difference scheme we calculate complete synthetic seismograms in order to relate the scales of the fluctuation of the elastic parameters to wavefield properties. We discuss the influence of critical parameters on the scattering properties of the upper mantle and on the propagation mechanism of the teleseismic Pn: variations in vertical and horizontal correlation lengths, rms velocity fluctuations, thickness of the heterogeneous layer, and cross-correlation of P- and S-wave velocities. A teleseismic Pn phase arises only if the velocity fluctuations are strong enough to cause multiple scattering and if the horizontal correlation length exceeds the vertical by an order of magnitude. Our favourite model for the Russian PNE profiles includes a 100–150-km-thick zone of scatterers below the Moho, containing heterogeneities with a horizontal correlation length of 20 km, a vertical correlation length of 0.5 km and an rms velocity perturbation of 2 per cent, while keeping the P- and S-wave velocities correlated. As the teleseismic Pn is often observed, this scale of velocity fluctuations seems to be characteristic of the uppermost mantle. Anisotropy is likely to contribute to the inferred velocity fluctuations.
Rhomboid protease RHBDL4/RHBDD1 cleaves SREBP-1c at endoplasmic reticulum monitoring and regulating fatty acids

Abstract The endoplasmic reticulum (ER)–embedded transcription factors, sterol regulatory element-binding proteins (SREBPs), master regulators of lipid biosynthesis, are transported to the Golgi for proteolytic activation to tune cellular cholesterol levels and regulate lipogenesis. However, mechanisms by which the cell responds to the levels of saturated or unsaturated fatty acids remain underexplored. Here, we show that RHBDL4/RHBDD1, a rhomboid family protease, directly cleaves SREBP-1c at the ER. The p97/VCP, AAA-ATPase complex then acts as an auxiliary segregase to extract the remaining ER-embedded fragment of SREBP-1c. Importantly, the enzymatic activity of RHBDL4 is enhanced by saturated fatty acids (SFAs) but inhibited by polyunsaturated fatty acids (PUFAs). Genetic deletion of RHBDL4 in mice fed on a Western diet enriched in SFAs and cholesterol prevented SREBP-1c from inducing genes for lipogenesis, particularly for synthesis and incorporation of PUFAs, and secretion of lipoproteins. The RHBDL4-SREBP-1c pathway reveals a regulatory system for monitoring fatty acid composition and maintaining cellular lipid homeostasis.
Molecular phylogeny and taxonomy of the genus Vernaya (Mammalia: Rodentia: Muridae) with the description of two new species

Abstract The climbing mouse is a rare, small mammal listed as an endangered species on the China species red list. Molecular phylogenetic analyses and the evolutionary history of the genus remain unexplored because of the extreme difficulty in capturing individuals and their narrow distribution. Here, we collected 44 specimens, sequenced one mitochondrial and eight nuclear genes, and integrated morphological approaches to estimate phylogenetic relationships, delimit species boundaries, and explore evolutionary history. Molecular analyses and morphological results supported the validity of these four species. Here, we describe two new species, Vernaya meiguites sp. nov. and Vernaya nushanensis sp. nov., and recognize Vernaya foramena, previously considered a subspecies of Vernaya fulva, as a valid species. The estimated divergence time suggests that the climbing mouse began to diversify during the Pliocene (3.36 Ma).
Promoting patient self-management following cardiac rehabilitation using a web-based application: A pilot study

Background The use of health-related mobile apps has become an important component of healthcare. Patients can use a range of tools to strengthen their health literacy and promote disease management. The aim of the project was to develop a web-based application for use on smartphones, tablets and computers for patients with cardiovascular diseases (cardio-app). Methods A semi-standardized written survey was conducted among rehabilitation patients with cardiovascular diseases (n = 158). The usability of the cardio-app was assessed using the System Usability Scale (SUS). The usage behaviour was conducted with a self-developed questionnaire. Results The study enrolled 158 eligible rehabilitation patients. The SUS of the cardio-app determined was 74.4 (SD ± 17.4). For 86%, the menu navigation was self-explanatory and logical. The visual presentation appealed to 92% of respondents. The content of the texts used in the app was understandable for 95%, and 93% found the technical terms used in the glossary well explained. For 57%, the app was helpful in planning their physical activities. 83% of the rehabilitation patients would recommend the app to others. The main criticisms of the app were the lack of synchronization options with other apps. Of those who did not use the app, the following reasons for non-use were most frequently cited: too much effort (43%), lack of time (29%) and pandemic-related reasons (29%). Conclusions The cardio-app revealed high agreement values. Whether the use of the app is associated with improved clinical state and outcome would have to be verified in further studies.
Point prevalence mapping reveals hotspot for onchocerciasis transmission in the Ndikinimeki Health District (Centre Region, Cameroon)

Background Ivermectin-based preventive chemotherapy is distributed annually to all at risk eligible individuals to �ght onchocerciasis. Data reporting the impact of mass ivermectin administration on onchocerciasis transmission are scanty, and it is tricky to appreciate the progress towards elimination and engage adapted corrective measures. To �ll that gap in the Centre Region in Cameroon, this study aimed at assessing onchocerciasis endemicity level in the Ndikinimeki Health District after almost three decades of mass treatments.
Structural alterations in a rumination-related network in patients with major depressive disorder

Rumination is a common symptom in major depressive disorder (MDD) and has been linked to risk for that disorder, its prognosis, and relapse likelihood. Previous work has linked individual differences in rumination to structural properties in a variety of brain regions. Some of these regions, such as the dorsolateral prefrontal cortex (dlPFC), have also been highlighted as being altered in MDD, suggesting a connection between structural changes and ruminative symptoms. Although informative, such localised relations have some limitations in the context of a network view of the brain. To further investigate rumination-related structural changes in depression and to situate these within potential functional networks, we acquired structural data from patients with MDD (n = 32) and controls (n = 69). Analysis of cortical grey-matter identified group differences in the dlPFC that were, however, not related to rumination. Instead, rumination was correlated with grey-matter properties in the right precuneus. Using normative functional connectivity analysis on a large independent sample, we show that these two regions are interconnected. It was further shown that the rumination-related precuneus region is highly connected with networks associated with processes such as executive function, autobiographical memory, and visual perception. Notably, each of these processes has been connected to rumination. These results suggest that rumination in depression may be linked to focal structural changes that disrupt a distributed functional network.
Multi-voxel neuro-reinforcement changes resting-state functional connectivity: A pilot study

Background: Multi-voxel neuro-reinforcement has been shown to selectively reduce amygdala reactivity in response to feared stimuli, but the precise mechanisms supporting these effects are still unknown. The current pilot study seeks to identify potential intermediaries of change using functional brain connectivity at rest. Methods: Individuals (N = 11) diagnosed with at least two animal subtype specific phobias took part in a double-blind multi-voxel neuro-reinforcement clinical trial targeting one of two phobic animals, with the untargeted animal as placebo control. Changes in whole-brain resting state functional connectivity from pre-treatment to post-treatment were measured using group ICA. These changes were tested to see if they predicted the previously observed decreases in amygdala reactivity in response to images of target phobic animals. Results: A common functional connectivity network overlapping with the visual network was identified in resting state data pre-treatment and post-treatment. Significant increases in functional connectivity in this network from pre-treatment to post-treatment were found in higher level visual and cognitive processing regions of the brain. Increases in functional connectivity in these regions also significantly predicted decreases in task-based amygdala reactivity to targeted phobic animals following multi-voxel neuro-reinforcement. Specifically, greater increases of functional connectivity pre-treatment to post-treatment were associated with greater decreases of amygdala reactivity to target phobic stimuli pre-treatment to post-treatment. Conclusions: These findings provide preliminary evidence that multi-voxel neuro-reinforcement can induce persisting functional connectivity changes in the brain. Moreover, these changes in functional connectivity were not limited to the direct area of neuro-reinforcement, suggesting neuro-reinforcement may change how the targeted region interacts with other brain regions. Identification of these brain regions represent a first step towards explaining the underlying mechanisms of change in previous multi-voxel neuro-reinforcement studies. Future research should seek to replicate these effects in a larger sample size to further assess their role in the effects observed from multi-voxel neuro-reinforcement.
Digital Voice-Based Biomarker for Monitoring Respiratory Quality of Life: Findings from the Colive Voice Study

Regular monitoring of respiratory quality of life (RQoL) is essential in respiratory healthcare, facilitating prompt diagnosis and tailored treatment for chronic respiratory diseases. Voice alterations resulting from respiratory conditions create unique audio signatures that can potentially be utilized for disease screening or monitoring. Analyzing data from 1908 participants from the Colive Voice study, which collects standardized voice recordings alongside comprehensive demographic, epidemiological, and patient-reported outcome data, we evaluated various strategies to estimate RQoL from voice, including handcrafted acoustic features, standard acoustic feature sets, and advanced deep audio embeddings derived from pretrained convolutional neural networks. We compared models using clinical features alone, voice features alone, and a combination of both. The multimodal model combining clinical and voice features demonstrated the best performance, achieving an accuracy of 70.34% and an area under the receiver operating characteristic curve (AUROC) of 0.77; an improvement of 5% in terms of accuracy and 7% in terms of AUROC compared to model utilizing voice features alone. Incorporating vocal biomarkers significantly enhanced the predictive capacity of clinical variables across all acoustic feature types, with a net classification improvement (NRI) of up to 0.19. Our digital voice-based biomarker is capable of accurately predicting RQoL, either as an alternative to or in conjunction with clinical measures, and could be used to facilitate rapid screening and remote monitoring of respiratory health status.
Visualizing the Supernova Explosion of a 25-Solar-Mass Star and the Simultaneous Birth of a Neutron-Star

This explanatory visualization shows the results of a state-of-the-art 3D simulation of supernova explosion and neutron-star birth. It is a rare instance where the full stellar evolution of an object, including the physics of the convection and the radiation, has been simulated in three dimensions. Among the highlights is the deep core that is shrinking after explosion due to neutrino cooling and deleptonization on its way to becoming a cold, compact neutron star. There is also evidence of inner proto-neutron star convection, perhaps the site of magnetic dynamo action that can turn a pulsar into a magnetar. An exterior view shows the blast wave, which cocoons the newly-birthed neutron star, moving at ∼ 10,000 km/s. Additionally, a reusable pipeline was developed, which leverages state-of-the-art tools for scientific data analysis and visualization resulting in high-quality renderings.
Age-constrained Ear Recognition: The EICZA Dataset and SASE Baseline Model

Using the ear as a biometric identifier, particularly for children in healthcare settings, has an important advantage over using the face - the privacy of the person can be protected better. However, aging and the resulting appearance differences, known to be challenges for face recognition models, have not been addressed for ear recognition yet. To address this limitation, we curated a publicly available dataset, which we call Ears of Infant Cohort in Zambia with Aging (EICZA) 1. The dataset contains 3,330 ear images of 177 subjects, each photographed multiple times between the ages of 6 days and 9 months, when ear growth is most significant. For the task of age-constrained ear recognition, i.e., recognizing a person who has aged since the model was trained, we propose a new ear recognition model, called SASE for Self-Attention-based Sequential Ear image analysis. The model takes a sequence of ear images at early but different ages as input (instead of a single image) and processes them with a feature extraction network and a Transformer encoder. Trained with a large margin cosine loss function, the model is encouraged to learn a feature representation that distinguishes subjects from each other: Our experiments show that accounting for age enables our model to outperform other models that do not in recognizing ears that have grown and look different in later time periods.
STABILITY AND EXACT TUR ´AN NUMBERS FOR MATROIDS

We consider the Tur´an-type problem of bounding the size of a set M ⊆ F n 2 that does not contain a linear copy of a given ﬁxed set N ⊆ F k 2 , where n is large compared to k . An Erd˝os-Stone type theorem [5] in this setting gives a bound that is tight up to a o (2 n ) error term; our ﬁrst main result gives a stability version of this theorem, showing that such an M that is close in size to the upper bound in [5] is close in edit distance to the obvious extremal example. Our second result shows that the error term in [5] is exactly controlled by the solution to one of a class of ‘sparse’ extremal problems, and in many cases eliminates the error term completely to give a sharp upper bound on | M | .
subconjunctival bevacizumab to augment trabeculectomy with mitomycin C in the management of failed glaucoma surgery

Purpose: To provide a feasible solution to the problem of failed glaucoma surgery. The aim was to evaluate the efficacy and safety of the additional effects of a combined surgical approach. This approach augments the application of trabeculectomy with mitomycin C (MMC) by adding subconjunctival bevacizumab injection. The results were compared with those of trabeculectomy with only adjunctive MMC. Methods: A randomized controlled prospective clinical trial included 28 eyes diagnosed with failed scarred bleb of a previous trabeculectomy. The eyes were divided into two equal groups: combined group A, “trabeculectomy with adjunctive MMC and subconjunctival bevacizumab,” and control group B, “trabeculectomy with adjunctive MMC only. ” The main outcome results included the cumulative probability of surgical success, intraocular pressure (IOP) values, and number of IOP-lowering medications needed to achieve the target IOP. Results: Group A achieved a cumulative probability of complete success of 0.769 and of qualified success of 0.231 at the end of the 24 month study period; group B achieved cumulative probabilities of 0.538 and 0.308, respectively. Group A achieved a lower mean IOP value than group B, with fewer antiglaucoma drugs at all postoperative visits, but this lower value did not reach a statistically significant level ( P  0.05). There was no statistically significant difference between both groups regarding best corrected visual acuity, visual field parameters, operative and/or postoperative complications, and additional interventions. No significant adverse effects were caused by this combined approach. Conclusion: Bevacizumab was not found to add much to the favorable long-term outcome of conventional trabeculectomy with MMC as a solution to the problem of scarred failed bleb.
In Search of Negative Moments: Multi-Modal Analysis of Teacher Negativity in Classroom Observation Videos

We explore multi-modal machine learning-based approaches (facial expression recognition, auditory emotion recognition, and text sentiment analysis) to identify negative moments of teacher-student interaction during classroom teaching. Our analyses on a large (957 videos, each 20min) dataset of classroom observations suggest that: (1) Negative moments occur sparsely and are laborious to find by manually watching videos from start to finish. (2) Contemporary machine perception tools for emotion, speech, and text sentiment analysis show only limited ability to capture the diverse manifestations of classroom negativity in a fully automatic way. (3) Semi-automatic procedures that combine machine perception with human annotation may hold more promise for finding authentic moments of classroom negativity. Finally, (4) even short 10sec negative moments contain rich structure in terms of the actions and behaviors that they comprise.
Your Echos are Heard: Tracking, Profiling, and Ad Targeting in the Amazon Smart Speaker Ecosystem

—Smart speakers collect voice input that can be used to infer sensitive information about users. Given a number of egregious privacy breaches, there is a clear unmet need for greater transparency and control over data collection, sharing, and use by smart speaker platforms as well as third party skills supported on them. To bridge the gap, we build an auditing framework that leverages online advertising to measure data collection, its usage, and its sharing by the smart speaker platforms. We evaluate our framework on the Amazon smart speaker ecosystem. Our results show that Amazon and third parties (including advertising and tracking services) collect smart speaker interaction data. We ﬁnd that Amazon processes voice data to infer user interests and uses it to serve targeted ads on-platform (Echo devices) as well as off-platform (web). Smart speaker interaction leads to as much as 30 × higher ad bids from advertisers. Finally, we ﬁnd that Amazon’s and skills’ operational practices are often not clearly disclosed in their privacy policies.
The Morphological Processes of Balish

--- Balinese English which is in this article called Balish has an important role in the world of tourism, namely as one of the most important capital for workers in the field of tourism, and they use Balish. Tourism workers are classified as lower class such as merchants, masseurs, parking attendants, shop assistants or kiosks, etc. Balish lexicon has gone through morphological processes. These are the proofs that linguistics has been affected, particularly in the field of morphology. Therefore, this article aims to find Balish lexicon along with their morphological processes. The data were taken from tourism workers at Ubud and Tanah Lot. Documentation method and note-taking technique were applied in collecting the data. Yule’s theory of word formation (2020) and morphological processes theory from O’Grady & Archibald (2016) were applied in analyzing the data through descriptive-qualitative method. The results of the research show that there are 12 types of morphological processes found, namely compounding, blending, borrowing, clipping, conversion, initialism, acronym, inflection and derivation, coinage, and multiple processes. The research proves that morphological process is still relevant and has always been the fundamental base in the formation of new lexemes in a constantly advancing world.
Albumin-bound paclitaxel in solid tumors: clinical development and future directions

: Albumin-bound paclitaxel ( nab -paclitaxel) is a solvent-free formulation of paclitaxel that was initially developed more than a decade ago to overcome toxicities associated with the solvents used in the formulation of standard paclitaxel and to potentially improve efficacy. Nab -paclitaxel has demonstrated an advantage over solvent-based paclitaxel by being able to deliver a higher dose of paclitaxel to tumors and decrease the incidence of serious toxicities, including severe allergic reactions. To date, nab -paclitaxel has been indicated for the treatment of three solid tumors in the USA. It was first approved for the treatment of metastatic breast cancer in 2005, followed by locally advanced or metastatic non-small-cell lung cancer in 2012, and most recently for metastatic pancreatic cancer in 2013. Nab -paclitaxel is also under investigation for the treatment of a number of other solid tumors. This review highlights key clinical efficacy and safety outcomes of nab -paclitaxel in the solid tumors for which it is currently indicated, discusses ongoing trials that may provide new data for the expansion of nab -paclitaxel’s indications into other solid tumors, and provides a clinical perspective on the use of nab -paclitaxel in practice.