Miracle-dz/UniFAR-FTUs huggingface dataset:
Pseudo gray platelet syndrome: the first case report in Korea

TO THE EDITOR: Currently, the most common blood test in hospitals, complete blood count (CBC), is typically performed by automated hematology analyzers. However, pseudothrombocytopenia caused by pseudo gray platelet syndrome (PGPS) might cause errors in CBC test results. Here we report what we believe to be the first reported case of PGPS in Korea.
Ecology of Lactobacilli in the Oral Cavity: A Review of Literature

Lactobacilli appear in the oral cavity during the first years of a child’s life. Their presence depends on numerous factors such as the presence of ecological niches e.g. natural anfractuosities of the teeth. A strong correlation has been established between the saliva Lactobacillus count and dental caries, the higher the DMF index, the higher the number of children harbouring a high Lactobacillus count. Among children, the presence of lactobacilli in coronal caries is incontestable. Among adults, lactobacilli are found in root caries. Since 1999, taxonomical revisions make it difficult to interpret the results obtained in the numerous previous studies carried out on the identification of oral lactobacilli, but whatever the sampling method or the identification technique, the carious site or the age of sampled subjects, most species belong to the Lactobacillus casei group. This is important because if a specific correlation can be found between few species of lactobacilli and caries a better understanding of their properties could allow the development of new tools for prevention.
Incremental indexing and distributed image search using shared randomized vocabularies

We present a cooperative framework for content-based image retrieval for the realistic setting where images are distributed across multiple cooperating servers. The proposed method is in line with bag-of-features approaches but uses fully data-independent, randomized structures, shared by the cooperating servers, to map image features to common visual words. A coherent, global image similarity measure (which is a kernel) is computed in a distributed fashion over visual words, by only requiring a small amount of data transfers between nodes. Our experiments on various image types show that this framework is a very promising step towards large-scale, distributed content-based image retrieval.
Simultaneous training of negatively correlated neural networks in an ensemble

This paper presents a new cooperative ensemble learning system (CELS) for designing neural network ensembles. The idea behind CELS is to encourage different individual networks in an ensemble to learn different parts or aspects of a training data so that the ensemble can learn the whole training data better. In CELS, the individual networks are trained simultaneously rather than independently or sequentially. This provides an opportunity for the individual networks to interact with each other and to specialize. CELS can create negatively correlated neural networks using a correlation penalty term in the error function to encourage such specialization. This paper analyzes CELS in terms of bias-variance-covariance tradeoff. CELS has also been tested on the Mackey-Glass time series prediction problem and the Australian credit card assessment problem. The experimental results show that CELS can produce neural network ensembles with good generalization ability.
Mining coherent dense subgraphs across massive biological networks for functional discovery

MOTIVATION The rapid accumulation of biological network data translates into an urgent need for computational methods for graph pattern mining. One important problem is to identify recurrent patterns across multiple networks to discover biological modules. However, existing algorithms for frequent pattern mining become very costly in time and space as the pattern sizes and network numbers increase. Currently, no efficient algorithm is available for mining recurrent patterns across large collections of genome-wide networks. RESULTS We developed a novel algorithm, CODENSE, to efficiently mine frequent coherent dense subgraphs across large numbers of massive graphs. Compared with previous methods, our approach is scalable in the number and size of the input graphs and adjustable in terms of exact or approximate pattern mining. Applying CODENSE to 39 co-expression networks derived from microarray datasets, we discovered a large number of functionally homogeneous clusters and made functional predictions for 169 uncharacterized yeast genes. AVAILABILITY http://zhoulab.usc. edu/CODENSE/
Oropharyngeal Dysphagia and Gross Motor Skills in Children With Cerebral Palsy

OBJECTIVES: To determine the prevalence of oropharyngeal dysphagia (OPD) and its subtypes (oral phase, pharyngeal phase, saliva control), and their relationship to gross motor functional skills in preschool children with cerebral palsy (CP). It was hypothesized that OPD would be present across all gross motor severity levels, and children with more severe gross motor function would have increased prevalence and severity of OPD. METHODS: Children with a confirmed diagnosis of CP, 18 to 36 months corrected age, born in Queensland between 2006 and 2009, participated. Children with neurodegenerative conditions were excluded. This was a cross-sectional population-based study. Children were assessed by using 2 direct OPD measures (Schedule for Oral Motor Assessment; Dysphagia Disorders Survey), and observations of signs suggestive of pharyngeal phase impairment and impaired saliva control. Gross motor skills were described by using the Gross Motor Function Measure, Gross Motor Function Classification System (GMFCS), Manual Ability Classification System, and motor type/ distribution. RESULTS: OPD was prevalent in 85% of children with CP, and there was a stepwise relationship between OPD and GMFCS level. There was a significant increase in odds of having OPD, or a subtype, for children who were nonambulant (GMFCS V) compared with those who were ambulant (GMFCS I) (odds ratio = 17.9, P = .036). CONCLUSIONS: OPD was present across all levels of gross motor severity using direct assessments. This highlights the need for proactive screening of all young children with CP, even those with mild impairments, to improve growth and nutritional outcomes and respiratory health.
Extractive Summarization using Inter- and Intra- Event Relevance

Event-based summarization attempts to select and organize the sentences in a summary with respect to the events or the sub-events that the sentences describe. Each event has its own internal structure, and meanwhile often relates to other events semantically, temporally, spatially, causally or conditionally. In this paper, we define an event as one or more event terms along with the named entities associated, and present a novel approach to derive intra- and inter- event relevance using the information of internal association, semantic relatedness, distributional similarity and named entity clustering. We then apply PageRank ranking algorithm to estimate the significance of an event for inclusion in a summary from the event relevance derived. Experiments on the DUC 2001 test data shows that the relevance of the named entities involved in events achieves better result when their relevance is derived from the event terms they associate. It also reveals that the topic-specific relevance from documents themselves outperforms the semantic relevance from a general purpose knowledge base like Word-Net.
The role of climate and tectonics in aggradation and incision of the Indus River in the Ladakh Himalaya during the late Quaternary

Abstract The geomorphic evolution of the upper Indus River that traverses across the southwest (SW) edge of Tibet, and the Ladakh and Zanskar ranges, was examined along a ~350-km-long stretch of its reaches. Based on the longitudinal river profile, stream length gradient index, and river/strath terraces, this stretch of the river is divided into four segments. Valley fill river terraces are ubiquitous, and strath terraces occur in the lower reaches where the Indus River cuts through deformed Indus Molasse. Optically stimulated luminescence ages of river/strath terraces suggest that valley aggradation occurred in three pulses, at ~52, ~28, and ~16 ka, and that these broadly coincide with periods of stronger SW Indian summer monsoon. Reconstructed longitudinal river profiles using strath terraces provide an upper limit on the bedrock and provide incision rates ranging from 1.0±0.3 to 2.2±0.9 mm/a. These results suggested that rapid uplift of the western syntaxes aided by uplift along the local faults led to the formation of strath terraces and increased fluvial incision rates along this stretch of the river.
Large‐scale analysis reveals populational contributions of cortical spike rate and synchrony to behavioural functions

There have been few systematic population‐wide analyses of relationships between spike synchrony within a period of several milliseconds and behavioural functions. In this study, we obtained a large amount of spike data from > 23,000 neuron pairs by multiple single‐unit recording from deep layer neurons in motor cortical areas in rats performing a forelimb movement task. The temporal changes of spike synchrony in the whole neuron pairs were statistically independent of behavioural changes during the task performance, although some neuron pairs exhibited correlated changes in spike synchrony. Mutual information analyses revealed that spike synchrony made a smaller contribution than spike rate to behavioural functions. The strength of spike synchrony between two neurons was statistically independent of the spike rate‐based preferences of the pair for behavioural functions.
A species-specific nematocide that results in terminal embryogenesis

ABSTRACT Nematode–insect interactions are ubiquitous, complex and constantly changing as the host and nematode coevolve. The entomophilic nematode Pristionchus pacificus is found on a myriad beetle species worldwide, although the molecular dynamics of this relationship are largely unknown. To better understand how host cues affect P. pacificus embryogenesis, we characterized the threshold of sensitivity to the pheromone (Z)-7-tetradecen-2-one (ZTDO) by determining the minimum exposure duration and developmental window that results in P. pacificus embryonic lethality. We found early-stage embryos exposed to volatile ZTDO for as few as 4 h all display terminal embryogenesis, characterized by punctuated development up to 48 h later, with abnormal morphology and limited cavity formation. To determine if the pheromone arrests pre-hatching development by suffocating or permeabilizing the eggshells, we raised embryos under anoxic conditions and also examined eggshell permeability using the lipophilic dye FM4-64. We found that asphyxiating the embryos arrested embryogenesis in a reversible manner but did not phenocopy the effects of ZTDO exposure, whereas the ZTDO-induced disruption of embryogenesis did correlate with increased eggshell permeability. The effects of ZTDO are also highly specific, as other lipid insect compounds do not produce any detectable embryocidal effect. The high specificity and unusual teratogenic effect of ZTDO may be important in mediating the host–nematode relationship by regulating P. pacificus development. Summary: Insect-associated nematodes coordinate their development using host cues to ‘walk the line’ between mutualism and pathogenesis. A host pheromone causes terminal embryogenesis by permeabilizing the nematode eggshell.
Radiation Dose Reduction in 4D Cerebral CT Angiography by Individualized Estimation of Cerebral Circulation Time

BACKGROUND AND PURPOSE: The novel technique of 4D CTA for dynamic assessment of the intracranial vessels has a greater radiation burden than conventional CTA. Previous descriptions of the technique used a fixed-duration exposure protocol. This study examines the potential for dose reduction by individualizing exposure time to patient physiology by the use of time-enhancement curve techniques as previously applied in CT angiography and venography. MATERIALS AND METHODS: 4D-CTA examinations performed at our institution were retrospectively reviewed. Scan protocols used a test-bolus scan with either a subjective estimate of the main acquisition timing (estimated-duration method) or a quantitative measure (measured-duration method). The estimated-duration method used peak arterial enhancement to determine the start of exposure, with the duration chosen at the radiologist's discretion. The measured-duration method used arterial and venous time-enhancement curves to determine exposure start and duration. Exposure duration, study adequacy, quality score, and maximum venous enhancement were compared among groups. RESULTS: One hundred fifty-one examinations used the estimated-duration method, and 53 used measured-duration. The measured-duration method used a shorter exposure time (10 versus 15.8 seconds; P < .001). There was no statistically significant difference in the study adequacy rate, subjective quality score, or maximum venous enhancement. The radiation dose was reduced by 51% in the measured-duration method (3021 mGy × cm, 6.9 mSv, versus 1473 mGy × cm, 3.4 mSv). Both methods showed good agreement with DSA (κ = 0.88 for estimated-duration, κ = 1.0 for measured duration). CONCLUSIONS: Exposure time in 4D-CTA can be reduced with dual time-enhancement curves to match exposure to physiology without degrading study adequacy or quality.
An Investigation of Driver Distraction Near the Tipping Point of Traffic Flow Stability

Objective: The purpose of this study was to explore the interrelationship between driver distraction and characteristics of driver behavior associated with reduced highway traffic efficiency. Background: Research on the three-phase traffic theory and on behavioral driving suggests that a number of characteristics associated with efficient traffic flow may be affected by driver distraction. Previous studies have been limited, however, by the fact that researchers typically do not allow participants to change lanes, nor do they account for the impact of varying traffic states on driving performance. Methods: Participants drove in three simulated environments with differing traffic congestion while both using and not using a cell phone. Instructed only to obey the speed limit, participants were allowed to vary driving behaviors, such as those involving forward following distance, speed, and lane-changing frequency. Results: Both driver distraction and traffic congestion were found to significantly affect lane change frequency, mean speed, and the likelihood of remaining behind a slower-moving lead vehicle. Conclusions: This research suggests that the behavioral profile of “cell phone drivers,” which is often described as compensatory, may have far-reaching and unexpected consequences for traffic efficiency. Application: By considering the dynamic interplay between characteristics of traffic flow and driver behavior, this research may inform both public policy regarding in-vehicle cell phone use and future investigations of driving behavior.
Camera Height Doesn't Change: Unsupervised Training for Metric Monocular Road-Scene Depth Estimation

In this paper, we introduce a novel training method for making any monocular depth network learn absolute scale and estimate metric road-scene depth just from regular training data, i.e., driving videos. We refer to this training framework as StableCamH. The key idea is to leverage cars found on the road as sources of scale supervision but to incorporate them in the training robustly. StableCamH detects and estimates the sizes of cars in the frame and aggregates scale information extracted from them into a camera height estimate whose consistency across the entire video sequence is enforced as scale supervision. This realizes robust unsupervised training of any, otherwise scale-oblivious, monocular depth network to become not only scale-aware but also metric-accurate without the need for auxiliary sensors and extra supervision. Extensive experiments on the KITTI and Cityscapes datasets show the effectiveness of StableCamH and its state-of-the-art accuracy compared with related methods. We also show that StableCamH enables training on mixed datasets of different camera heights, which leads to larger-scale training and thus higher generalization. Metric depth reconstruction is essential in any road-scene visual modeling, and StableCamH democratizes its deployment by establishing the means to train any model as a metric depth estimator.
Weisfeiler and Leman Go Loopy: A New Hierarchy for Graph Representational Learning

We introduce $r$-loopy Weisfeiler-Leman ($r$-$\ell{}$WL), a novel hierarchy of graph isomorphism tests and a corresponding GNN framework, $r$-$\ell{}$MPNN, that can count cycles up to length $r + 2$. Most notably, we show that $r$-$\ell{}$WL can count homomorphisms of cactus graphs. This strictly extends classical 1-WL, which can only count homomorphisms of trees and, in fact, is incomparable to $k$-WL for any fixed $k$. We empirically validate the expressive and counting power of the proposed $r$-$\ell{}$MPNN on several synthetic datasets and present state-of-the-art predictive performance on various real-world datasets. The code is available at https://github.com/RPaolino/loopy
Social comparison based relaying in device-to-device networks

Device-to-device (D2D) communications are recognized as a key component of future wireless networks which will help to improve spectral efficiency and network densification simultaneously. In order to guarantee a quality of service (QoS) to the cellular links, the transmit power of the D2D nodes needs to be restricted, which has lead to a poor link quality over D2D transmission. One viable option to improve the D2D link quality is incorporating cooperative relays into D2D networks. However most of the existing published work in relay assisted D2D networks has assumed that relay nodes cooperate spontaneously. This cannot always be guaranteed and we take this into account by considering a fundamental model on which donation-based cooperation depends. In particular we model relay cooperation as a donation game based on social comparison and characterize cooperation probability in an evolutionary context. When applying this model we evaluate the outage and capacity of relay assisted D2D network using a stochastic geometric framework.
Partitioning the projective plane to two incidence-rich parts

An internal or friendly partition of a vertex set $V(G)$ of a graph $G$ is a partition to two nonempty sets $A\cup B$ such that every vertex has at least as many neighbours in its own class as in the other one. Motivated by Diwan's existence proof on internal partitions of graphs with high girth, we give constructive proofs for the existence of internal partitions in the incidence graph of projective planes and discuss its geometric properties. In addition, we determine exactly the maximum possible difference between the sizes of the neighbor set in its own class and the neighbor set of the other class, that can be attained for all vertices at the same time for the incidence graphs of desarguesian planes of square order.
Anatomy of Vector-Like Bottom-Quark Models in the Alignment Limit of the 2-Higgs Doublet Model Type-II

Expanding upon our ongoing investigation of Vector-Like Quark (VLQ) phenomenology within a 2-Higgs Doublet Model (2HDM) framework, in this paper, we complement a previous one dedicated to Vector-Like Top-quarks (VLTs) by studying Vector-Like Bottom-quarks (VLBs), specifically focusing on their behavior in the alignment limit of a Type-II Yukawa structure. We examine the potential for detecting VLBs at the Large Hadron Collider (LHC) and analyze their decay signatures, encompassing both Standard Model (SM) processes and exotic decays. The objective is to differentiate among singlet, doublet, and triplet configurations of VLBs by identifying distinct decay patterns, thereby providing insights into the structure of Beyond the SM (BSM) physics.
Where Does the Physics of Extreme Gravitational Collapse Reside

The gravitational collapse of massive stars serves to manifest the most severe deviations of general relativity with respect to Newtonian gravity: the formation of horizons and spacetime singularities. Both features have proven to be catalysts of deep physical developments, especially when combined with the principles of quantum mechanics. Nonetheless, it is seldom remarked that it is hardly possible to combine all these developments into a unified theoretical model, while maintaining reasonable prospects for the independent experimental corroboration of its different parts. In this paper we review the current theoretical understanding of the physics of gravitational collapse in order to highlight this tension, stating the position that the standard view on evaporating black holes stands for. This serves as the motivation for the discussion of a recent proposal that offers the opposite perspective, represented by a set of geometries that regularize the classical singular behavior and present modifications of the near-horizon Schwarzschild geometry as the result of the propagation of non-perturbative ultraviolet effects originated in regions of high curvature. We present an extensive exploration of the necessary steps on the explicit construction of these geometries, and discuss how this proposal could change our present understanding of astrophysical black holes and even offer the possibility of detecting genuine ultraviolet effects in gravitational-wave experiments.
An Entropy-based Text Watermarking Detection Method

Currently, text watermarking algorithms for large language models (LLMs) can embed hidden features to texts generated by LLMs to facilitate subsequent detection, thus alleviating the problem of misuse of LLMs. Although the current text watermarking algorithms perform well in most high-entropy scenarios, its performance in low-entropy scenarios still needs to be improved. In this work, we proposed that the influence of token entropy should be fully considered in the watermark detection process, that is, the weight of each token should be adjusted according to its entropy during watermark detection, rather than setting the weight of all tokens to the same value as in previous methods. Specifically, we proposed an Entropy-based Watermark Detection (EWD) that gives higher-entropy tokens higher weights during watermark detection, so as to better reflect the degree of watermarking. Furthermore, the proposed detection process is training-free and fully automated. %In actual detection, we use a proxy-LLM to calculate the entropy of each token, without the need to use the original LLM. In the experiment, we found that our method can achieve better detection performance in low-entropy scenarios, and our method is also general and can be applied to texts with different entropy distributions. Our code and data will be available online.