Miracle-dz/UniFAR-FTUs huggingface dataset:
An Information-Theoretic Framework for Non-linear Canonical Correlation Analysis

Canonical Correlation Analysis (CCA) is a linear representation learning method that seeks maximally correlated variables in multi-view data. Non-linear CCA extends this notion to a broader family of transformations, which are more powerful for many real-world applications. Given the joint probability, the Alternating Conditional Expectation (ACE) provides an optimal solution to the non-linear CCA problem. However, it suffers from limited performance and an increasing computational burden when only a finite number of observations is available. In this work we introduce an information-theoretic framework for the non-linear CCA problem (ITCCA), which extends the classical ACE approach. Our suggested framework seeks compressed representations of the data that allow a maximal level of correlation. This way we control the trade-off between the flexibility and the complexity of the representation. Our approach demonstrates favorable performance at a reduced computational burden, compared to non-linear alternatives, in a finite sample size regime. Further, ITCCA provides theoretical bounds and optimality conditions, as we establish fundamental connections to rate-distortion theory, the information bottleneck and remote source coding. In addition, it implies a "soft" dimensionality reduction, as the compression level is measured (and governed) by the mutual information between the original noisy data and the signals that we extract.
The plant alkaloid conophylline inhibits matrix formation of fibroblasts

Conophylline is a Vinca alkaloid from leaves of the tropical plant Ervatamia microphylla and has been shown to mimic the effect of the growth and differentiation factor activin A on pancreatic progenitor cells. However, activin A stimulates fibrosis of pancreatic stellate cells, whereas conophylline inhibits it, suggesting that this compound may serve as an antifibrotic drug. Here we investigated the effects of conophylline on human foreskin fibroblasts, especially focusing on extracellular matrix (ECM) proteins. A gene microarray analysis revealed that conophylline remarkably suppressed expression of the gene for hyaluronan synthase 2 (HAS2) and of its antisense RNA, whereas the expression of collagen genes was unaffected. Of note, immunostaining experiments revealed that conophylline substantially inhibits incorporation of versican and collagens into the ECM in cells treated with transforming growth factor β (TGFβ), which promotes collagen synthesis, but not in cells not treated with TGFβ. Moreover, a protein biosynthesis assay disclosed that conophylline decreases collagen biosynthesis, concomitant with a decrease in total protein biosynthesis, indicating that conophylline-mediated inhibition of fibrosis is not specific to collagen synthesis. Conophylline affected neither TGFβ-induced nuclear translocation of SMAD family member 2/3 (SMAD2/3) nor phosphorylation of SMAD2. However, conophylline substantially inhibited phosphorylation of extracellular signal–regulated kinase 1/2 (ERK1/2), suggesting that conophylline inhibits HAS2 expression via TGFβ-mediated activation of the ERK1/2 pathway. Taken together, our results indicate that conophylline may be a useful inhibitor of ECM formation in fibrosis.
The distribution, number, and certain neurochemical identities of infracortical white matter neurons in a lar gibbon (Hylobates lar) brain

We examined the number, distribution, and immunoreactivity of the infracortical white matter neuronal population, also termed white matter interstitial cells (WMICs), in the brain of a lesser ape, the lar gibbon. Staining for neuronal nuclear marker (NeuN) revealed WMICs throughout the infracortical white matter, these cells being most numerous and dense close to cortical layer VI, decreasing significantly in density with depth in the white matter. Stereological analysis of NeuN‐immunopositive cells revealed a global estimate of ~67.5 million WMICs within the infracortical white matter of the gibbon brain, indicating that the WMICs are a numerically significant population, ~2.5% of the total cortical gray matter neurons that would be estimated for a primate brain the mass of that of the lar gibbon. Immunostaining revealed subpopulations of WMICs containing neuronal nitric oxide synthase (nNOS, ~7 million in number, with both small and large soma volumes), calretinin (~8.6 million in number, all of similar soma volume), very few WMICs containing parvalbumin, and no calbindin‐immunopositive neurons. These nNOS, calretinin, and parvalbumin immunopositive WMICs, presumably all inhibitory neurons, represent ~23.1% of the total WMIC population. As the white matter is affected in many cognitive conditions, such as schizophrenia, autism and also in neurodegenerative diseases, understanding these neurons across species is important for the translation of findings of neural dysfunction in animal models to humans. Furthermore, studies of WMICs in species such as apes provide a crucial phylogenetic context for understanding the evolution of these cell types in the human brain.
Assessment methods and resource requirements for milestone reporting by an emergency medicine clinical competency committee

ABSTRACT Background: The Accreditation Council for Graduate Medical Education (ACGME) introduced milestones for Emergency Medicine (EM) in 2012. Clinical Competency Committees (CCC) are tasked with assessing residents on milestones and reporting them to the ACGME. Appropriate workflows for CCCs are not well defined. Objective: Our objective was to compare different approaches to milestone assessment by a CCC, quantify resource requirements for each and to identify the most efficient workflow. Design: Three distinct processes for rendering milestone assessments were compared: Full milestone assessments (FMA) utilizing all available resident assessment data, Ad-hoc milestone assessments (AMA) created by multiple expert educators using their personal assessment of resident performance, Self-assessments (SMA) completed by residents. FMA were selected as the theoretical gold standard. Intraclass correlation coefficients were used to analyze for agreement between different assessment methods. Kendall’s coefficient was used to assess the inter-rater agreement for the AMA. Results: All 13 second-year residents and 7 educational faculty of an urban EM Residency Program participated in the study in 2013. Substantial or better agreement between FMA and AMA was seen for 8 of the 23 total subcompetencies (PC4, PC8, PC9, PC11, MK, PROF2, ICS2, SBP2), and for 1 subcompetency (SBP1) between FMA and SMA. Multiple AMA for individual residents demonstrated substantial or better interobserver agreement in 3 subcompetencies (PC1, PC2, and PROF2). FMA took longer to complete compared to AMA (80.9 vs. 5.3 min, p < 0.001). Conclusions: Using AMA to evaluate residents on the milestones takes significantly less time than FMA. However, AMA and SMA agree with FMA on only 8 and 1 subcompetencies, respectively. An estimated 23.5 h of faculty time are required each month to fulfill the requirement for semiannual reporting for a residency with 42 trainees.
Retinal explant culture: A platform to investigate human neuro‐retina

The retina is the tissue responsible for light detection, in which retinal neurons convert light energy into electrical signals to be transported towards the visual cortex. Damage of retinal neurons leads to neuronal cell death and retinal pathologies, compromising visual acuity and eventually leading to irreversible blindness. Models of retinal neurodegeneration include 2D systems like cell lines, disassociated cultures and co‐cultures, and 3D models like organoids, organotypic retinal cultures and animal models. Of these, ex vivo human retinal cultures are arguably the most suitable models for translational research as they retain complex inter‐cellular interactions of the retina and precisely mimic in‐situ responses. In this review, we summarize the distinguishing features of the human retina which are important to preserve in experimental culture, the historical development of human retinal culture systems, the factors affecting ex vivo human retinal culture and the applications and challenges associated with current methods of human retinal explant culture.
Towards End-to-End Code-Switching Speech Recognition

Code-switching speech recognition has attracted an increasing interest recently, but the need for expert linguistic knowledge has always been a big issue. End-to-end automatic speech recognition (ASR) simplifies the building of ASR systems considerably by predicting graphemes or characters directly from acoustic input. In the mean time, the need of expert linguistic knowledge is also eliminated, which makes it an attractive choice for code-switching ASR. This paper presents a hybrid CTC-Attention based end-to-end Mandarin-English code-switching (CS) speech recognition system and studies the effect of hybrid CTC-Attention based models, different modeling units, the inclusion of language identification and different decoding strategies on the task of code-switching ASR. On the SEAME corpus, our system achieves a mixed error rate (MER) of 34.24%.
Practical Backward-Secure Searchable Encryption from Symmetric Puncturable Encryption

Symmetric Searchable Encryption (SSE) has received wide attention due to its practical application in searching on encrypted data. Beyond search, data addition and deletion are also supported in dynamic SSE schemes. Unfortunately, these update operations leak some information of updated data. To address this issue, forward-secure SSE is actively explored to protect the relations of newly updated data and previously searched keywords. On the contrary, little work has been done in backward security, which enforces that search should not reveal information of deleted data. In this paper, we propose the first practical and non-interactive backward-secure SSE scheme. In particular, we introduce a new form of symmetric encryption, named symmetric puncturable encryption (SPE), and construct a generic primitive from simple cryptographic tools. Based on this primitive, we then present a backward-secure SSE scheme that can revoke a server's searching ability on deleted data. We instantiate our scheme with a practical puncturable pseudorandom function and implement it on a large dataset. The experimental results demonstrate its efficiency and scalability. Compared to the state-of-the-art, our scheme achieves a speedup of almost 50x in search latency, and a saving of 62% in server storage consumption.
Designing Informative Rating Systems for Online Platforms: Evidence from Two Experiments

Platforms critically rely on rating systems to learn the quality of market participants. In practice, however, these ratings are often highly inflated, drastically reducing the signal available to distinguish quality. We consider two questions: First, can rating systems better discriminate quality by altering the meaning and relative importance of the levels in the rating system? And second, if so, how should the platform optimize these choices in the design of the rating system? We first analyze the results of a randomized controlled trial on an online labor market in which an additional question was added to the feedback form. Between treatment conditions, we vary the question phrasing and answer choices. We further run an experiment on Amazon Mechanical Turk with similar structure, to confirm the labor market findings. Our tests reveal that current inflationary norms can in fact be countered by re-anchoring the meaning of the levels of the rating system. In particular, scales that are positive-skewed and provide specific interpretations for what each label means yield rating distributions that are much more informative about quality. Second, we develop a theoretical framework to optimize the design of a rating system by choosing answer labels and their numeric interpretations in a manner that maximizes the rate of convergence to the true underlying quality distribution. Finally, we run simulations with an empirically calibrated model and use these to study the implications for optimal rating system design. Our simulations demonstrate that our modeling and optimization approach can substantially improve the quality of information obtained over baseline designs. Overall, our study illustrates that rating systems that are informative in practice can be designed, and demonstrates how to design them in a principled manner.
Secure Communication over Interference Channel: To Jam or Not to Jam?

We consider a secure communication over a two-user Gaussian interference channel, where each transmitter sends a confidential message to its legitimate receiver. For this setting, we identify a regime where the simple scheme of using Gaussian wiretap codebook at each transmitter (without cooperative jamming) and treating interference as noise at each intended receiver (in short, GWC-TIN scheme) achieves the optimal secure sum capacity to within a constant gap. For the symmetric case, this simple scheme is optimal when the interference-to-signal ratio (all link strengths in decibel scale) is no more than 2/3. However, when the ratio is more than 2/3, we show that this simple scheme is not optimal anymore and a scheme with cooperative jamming is proposed to achieve the optimal secure sum generalized degrees-of-freedom (GDoF). Specifically, for the symmetric case, we complete the optimal secure sum GDoF characterization for any interference regimes.
Relationship Between Near-Infrared Spectroscopy-Derived Cerebral Oxygenation and Delirium in Critically Ill Patients: A Systematic Review

Background: A common neurological complication of critical illness is delirium, defined as an acute change in level of consciousness, with impaired attention and disorganized thinking. Patients with delirium have increased risk of long-term cognitive dysfunction and mortality. The cause is unknown, which limits our ability to design therapeutic interventions. In patients undergoing surgery, low regional cerebral oxygenation (rSO2), as measured by near-infrared spectroscopy (NIRS), is associated with postoperative neurological dysfunction (eg delirium and long-term cognitive impairment). However, the relationship between NIRS-derived rSO2 and neurological outcomes in critically ill patients is unclear. The objective of this study was to assess the utilization of NIRS-derived rSO2 in critically ill patients outside the operating theater. We aimed to examine the relationship between rSO2 and neurological outcomes as well as to report rSO2 values in this population. Methods: The following databases were searched from inception to August 14, 2017: Ovid MedLine, Embase, Cochrane Library, and Web of Science. Results: Of 1410 articles identified by the search strategy, 8 were ultimately selected for final review. Most (7 of 8) were published since 2014. These studies included a total of 213 patients primarily with shock or respiratory failure. A variety of devices were used to measure rSO2, including INVOS and FORESIGHT. The duration of recording varied from 5 minutes to 72 hours. Four of the 8 studies reported on neurological outcomes. In all 4 studies, rSO2 was lower in critically ill patients who were delirious compared to controls, but this was only statistically significant in 2 of the studies. The heterogeneity in devices and duration of recording precluded meta-analysis. Conclusions: There is limited literature describing rSO2 in critically ill patients outside the operating room. Although there may be a slight signal of an association between low rSO2 and delirium, more study is needed to explore this relationship.
Acute otitis externa because of negative pressure wound therapy applied over the head and ear canal for scalping treatment

Scalping is considered a complex wound with difficult treatment, requiring early surgical intervention, reconstructive plastic surgery, and a multidisciplinary team. The reconstruction of the scalp frequently requires a combination of therapies, including temporary coverage, such as negative pressure wound therapy (NPWT). Complications of NPWT, such as bleeding, infection, and pain, have been described. However, there is no report of acute otitis externa (AOE) because of NPWT. In this article, we present an unprecedented clinical case – a female patient who developed AOE after scalping treatment with NPWT applied over the head and ear canal. We consider that it may be a result of the direct physical action of subatmospheric pressure, the presence of dressing covering the external meatus, and alteration of the bacterial population.
Restructuring the built environment to change adult health behaviors: a scoping review integrated with behavior change frameworks

ABSTRACT Built environment restructuring can improve public health through increased opportunity for healthy behaviors. Behavioral science targets individual health behaviors within place, suggesting the potential to integrate these approaches. This scoping review was one of the first to summarise the impact built environment restructuring has on health outcomes and behaviors and integrate these findings with the Capability-Opportunity-Motivation-Behavior model and Theoretical Domains Framework of behavior change. Potential studies were identified from 12 academic databases in urban design, psychology and public health. Search parameters involved 50 environment types, for example green space or healthy cities, combined with both an intervention (e.g. green infrastructure, active transport) and a measurable health outcome (e.g. exercise, wellbeing). Searches were limited to North America, Europe, or Australia/New Zealand. Of 536 potential studies reviewed against defined inclusion/exclusion criteria, 23 contributed to the findings. Evidence supported the positive influence of restructuring on varied health outcomes, many of which were drivers and domains of health behavior. Most studies indicated a clear contribution to increased physical activity. Recommendations include the need for explicit communication of theories guiding restructuring project design, consideration of health outcomes beyond physical activity, and better investigation of unanticipated barriers to health behaviors arising from built environment restructuring projects.
Performance assessment of the deep learning technologies in grading glaucoma severity

Objective: To validate and compare the performance of eight available deep learning architectures in grading the severity of glaucoma based on color fundus images. Materials and Methods: We retrospectively collected a dataset of 5978 fundus images and their glaucoma severities were annotated by the consensus of two experienced ophthalmologists. We preprocessed the images to generate global and local regions of interest (ROIs), namely the global field-of-view images and the local disc region images. We then divided the generated images into three independent sub-groups for training, validation, and testing purposes. With the datasets, eight convolutional neural networks (CNNs) (i.e., VGG16, VGG19, ResNet, DenseNet, InceptionV3, InceptionResNet, Xception, and NASNetMobile) were trained separately to grade glaucoma severity, and validated quantitatively using the area under the receiver operating characteristic (ROC) curve and the quadratic kappa score. Results: The CNNs, except VGG16 and VGG19, achieved average kappa scores of 80.36% and 78.22% when trained from scratch on global and local ROIs, and 85.29% and 82.72% when fine-tuned using the pre-trained weights, respectively. VGG16 and VGG19 achieved reasonable accuracy when trained from scratch, but they failed when using pre-trained weights for global and local ROIs. Among these CNNs, the DenseNet had the highest classification accuracy (i.e., 75.50%) based on pre-trained weights when using global ROIs, as compared to 65.50% when using local ROIs. Conclusion: The experiments demonstrated the feasibility of the deep learning technology in grading glaucoma severity. In particular, global field-of-view images contain relatively richer information that may be critical for glaucoma assessment, suggesting that we should use the entire field-of-view of a fundus image for training a deep learning network.
Anterograde and retrograde signaling by an Aplysia neurotrophin forms a transsynaptic functional unit

Significance Intermediate- and long-term synaptic plasticity generally require coordinated pre- and postsynaptic mechanisms. In our companion paper, we found that presynaptic autocrine signaling by an Aplysia neurotrophin (ApNT) forms part of a positive feedback loop during the consolidation of learning-related synaptic plasticity. Here we report that ApNT also acts through both anterograde and retrograde signaling, so that the pre- and postsynaptic compartments act as one functional unit. Whereas short-term synaptic plasticity is often either pre- or postsynaptic, intermediate- and long-term plasticity generally require coordinated pre- and postsynaptic mechanisms. Thus, the transition from presynaptic short-term facilitation (STF) to intermediate-term facilitation (ITF) induced by 5HT at Aplysia sensory-to-motor neuron synapses requires the recruitment of postsynaptic mechanisms and activation of protein synthesis in both neurons. In the companion paper to this report, we found that presynaptic autocrine signaling by an Aplysia neurotrophin (ApNT) forms a positive feedback loop that drives the synapses from STF to ITF. Here we report that ApNT also acts through both anterograde and retrograde signaling to form a transsynaptic positive feedback loop that orchestrates cellular functions in both the presynaptic and postsynaptic neurons during the induction of ITF. These two feedback loops activate protein synthesis in each synaptic compartment, which in both cases depends on signaling from the other synaptic compartment. These results suggest that the pre- and postsynaptic compartments act as one functional unit during the consolidation of learning-related facilitation induced by 5HT.
Multimodal and Spectral Degradation Effects on Speech and Emotion Recognition in Adult Listeners

For cochlear implant (CI) users, degraded spectral input hampers the understanding of prosodic vocal emotion, especially in difficult listening conditions. Using a vocoder simulation of CI hearing, we examined the extent to which informative multimodal cues in a talker’s spoken expressions improve normal hearing (NH) adults’ speech and emotion perception under different levels of spectral degradation (two, three, four, and eight spectral bands). Participants repeated the words verbatim and identified emotions (among four alternative options: happy, sad, angry, and neutral) in meaningful sentences that are semantically congruent with the expression of the intended emotion. Sentences were presented in their natural speech form and in speech sampled through a noise-band vocoder in sound (auditory-only) and video (auditory–visual) recordings of a female talker. Visual information had a more pronounced benefit in enhancing speech recognition in the lower spectral band conditions. Spectral degradation, however, did not interfere with emotion recognition performance when dynamic visual cues in a talker’s expression are provided as participants scored at ceiling levels across all spectral band conditions. Our use of familiar sentences that contained congruent semantic and prosodic information have high ecological validity, which likely optimized listener performance under simulated CI hearing and may better predict CI users’ outcomes in everyday listening contexts.