Miracle-dz/UniFAR-FTUs huggingface dataset:
Genome-Wide Association Study of Erosive Tooth Wear in a Finnish Cohort

Erosive tooth wear is defined as irreversible loss of dental tissues due to intrinsic or extrinsic acids, exacerbated by mechanical forces. Recent studies have suggested a higher prevalence of erosive tooth wear in males, as well as a genetic contribution to susceptibility to erosive tooth wear. Our aim was to examine erosive tooth wear by performing a genome-wide association study (GWAS) in a sample of the Northern Finland Birth Cohort 1966 (n = 1,962). Erosive tooth wear was assessed clinically using the basic erosive wear examination. A GWAS was performed for the whole sample as well as separately for males and females. We identified one genome-wide significant signal (rs11681214) in the GWAS of the whole sample near the genes PXDN and MYT1L. When the sample was stratified by sex, the strongest genome-wide significant signals were observed in or near the genes FGFR1, C8orf86, CDH4, SCD5, F2R, and ING1. Additionally, multiple suggestive association signals were detected in all GWASs performed. Many of the signals were in or near the genes putatively related to oral environment or tooth development, and some were near the regions considered to be associated with dental caries, such as 2p24, 4q21, and 13q33. Replications of these associations in other samples, as well as experimental studies to determine the biological functions of associated genetic variants, are needed.
A comparative study to evaluate the efficacy of lycopene and curcumin in oral submucous fibrosis patients: A randomized clinical trial

Background: Oral submucous fibrosis (OSMF) is a most prevalent potentially malignant disorder associated with betel quid chewing frequently observed in the Indian population. The present study conducted is much of a keen interest because there is much new information, both in the press and the medical literature, about the benefits of fresh fruits and vegetables and antioxidants (such as lycopene and curcumin) for both prevention and treatment of diseases. As clinicians, we often prescribe medications with significant adverse effects, and certainly, if armed with evidence to support using such antioxidants as safer therapeutic alternatives for treatment of OSMF. Aims and Objective: The aim of the study was to compare and evaluate the efficacy of lycopene and curcumin given orally in clinically diagnosed OSMF patients. Materials and Methods: Sixty patients were divided randomly into two groups Group A and Group B. After fulfilling the eligibility criteria, sixty patients were randomly allotted based on fishbowl method into thirty each. This technique eliminated the selection bias arising in the study. Group A individuals were treated with 4 mg of lycopene and Group B individuals were given 300 mg of curcumin thrice daily for 3 months. Both the groups were assessed in terms of mouth opening and burning sensation. The statistical analysis was done using SPSS Version 16.0 statistical Analysis Software. Results: In Group A, the initial burning sensation was 65.83 ± 3.98%, and in Group B, it was 62.33 ± 5.22% (visual analog scale). After 3 months, there was complete cessation of burning sensation in both the groups. Burning sensation between the groups was statistically nonsignificant (P > 0.05). In Group A, mean mouth opening at baseline (1st visit) observed was 3.17 ± 0.08 cm which improved to 3.52 ± 0.07 cm after 3 months of the treatment period. In Group B, mean mouth opening at baseline (1st visit) observed was 3.32 ± 0.07 cm which improved to 3.52 ± 0.08 cm after 3 months of the treatment period. On comparing intergroup, the difference was statistically nonsignificant (P > 0.05). However, on comparing intergroup, average percent change in mean mouth opening from 1st visit to subsequent time intervals across the time period was found to be statistically significant (P < 0.05). Group A showed 11.1 ± 1.0% improvement in mean mouth opening and Group B showed 6.2 ± 0.4% improvement in the mean mouth opening from the 1st visit till the posttreatment period. The change in the mean mouth opening from 1st visit till posttreatment in Group A was 0.35 ± 0.14, and in Group B, it was 0.20 ± 0.09. Conclusion: Lycopene showed better results than curcumin in improving mouth opening; both the drugs were equally effective in decreasing burning sensation in OSMF patients.
A New Construction of EVENODD Codes With Lower Computational Complexity

EVENODD codes are binary array codes for correcting double disk failures in RAID-6 with asymptotically optimal encoding and decoding complexities. However, the update complexity of EVENODD is sub-optimal. We propose a new construction of binary maximum distance separable array codes, namely EVENODD+, such that the encoding, decoding, and update complexities of EVENODD+ are less than those of EVENODD in general. Moreover, EVENODD+ achieves asymptotically optimal update complexity.
Chemical Education Research: Where from Here?

U N I V E R S I T Y C H E M I S T R Y E D U C A T I O N 2 0 0 0 , 4 ( 1 ) research’ approach. In this approach, a small-scale curriculum development is linked to in-depth research on social, content and context specific teaching and learning processes. The structure of the research activities involves repeated cycles (a spiral) of activities, in which each cycle includes the following stages • an evaluation of a current educational situations; • formulation of research questions in conjunction with reflection on chemistry and chemistry education; • development and implementation of new teaching strategies and materials; • investigation of teaching and learning processes during classroom and laboratory sessions (important research instruments are audio/video-tapes for producing records of laboratory /classroom discussions); • repetition of the cycle. The cyclical approach is crucial to the individual teacher and can be used by professional research teams. It allows practitioners to link small-scale curriculum development to more in-depth research. Furthermore, if developmental research is carried out and published by practitioners at secondary level as well as at university level, the results can also help to bridge the gap between chemical education at this interface. References
Replacing Locks by Higher-Level Primitives

ReplacingLo cksbyHigher-LevelPrimitivesSaritaV.Adve,lanL.Cox,SandhyaDwarkadas,andWil lyZwaenepoelDepartment of Electricaland Computer EngineeringDepartment of Computer ScienceRice UniversityHouston, TX 77251-1892ComputerScience Technical Report#TR94-237,Rice University, 1994Presented at the4thWorkshopon Scalable Shared-Memory Multiprocessors,Chicago, May 1994.AbstractLo cks are used in shared memory parallel programs to achieve a variety of synchroniza-tion ob jectives.They may providemutual exclusionfor a criticalsection, or they mayprovide synchronized access to a task queue.In the former case, no ordering is impliedb etweendataop erationsoutsideofthecriticalsections,whileinlattercaseop erations precedingthe enqueue of a task are ordered b efore the op erations followinga dequeue of that task.In this pap er we argue that many uses of lo cks can b e replaced by higher-level primitivesthat directly express the intended b ehavior, such as, for example, enqueue and dequeueop erations on a task queue.This approach not only simpli es the programming mo del,but alsoallowsa more ecientimplementation.By makingtheintendeduseexplicit,wecantailortheimplementationofeachprimitivaccordingly,therebyachievingre-ductionsinlatencyandcommunicationoverhead.Synchronizationhasb eenshown to b eoneof thema jor imp edimentsforachievinghighp erformance,esp eciallyon software distributedshared memory systems.Wedemonstratetheb ene tsofourapproachbycomparingp erformanceonTreadMarks distributedsharedmemorysystem oflo ck-basedimplementationsoffourapplications(TSP,Quicksort,Water,andILINK)tonewimplementationsusingthehigher-levelprimitives.For each of the four applications, the high-levesleadto simplerprograms with b etter p erformance.This work is supp orted in part by NSF Grants No. CCR-91163343 , CCR-9211004 , CDA-9222911 , and CDA-9310073 ,and by Texas ATP Grant No. 0036404013 .
Mobile Phone Messaging to Husbands to Improve Maternal and Child Health Behavior in India

Over 90% of households in rural Uttar Pradesh, the most populous state of India, have at least one mobile phone. However, ownership of mobile phone among women is quite low. Implementation research was conducted in Uttar Pradesh to examine (a) whether providing information on selected maternal and child health (MCH) behaviors to a husband’s mobile phone would enhance the man’s knowledge and lead to discussions in their family, and (b) whether such discussions would help in the adoption of healthy practices. The m-Health intervention included biweekly voice messages in local language (Hindi) on MCH topics to the mobile phone of pregnant women’s husbands. Using a quasi-experimental design, after four months of the m-Health intervention, in 2014, 881 husbands and 956 women from the study area were interviewed. Husbands’ knowledge, controlling for their socio-demographic characteristics, were significantly higher among the listeners of the messages than the non-listeners. Multivariate logistic regression analysis showed that if husbands discussed the messages with family members, the odds of wives’ practicing health behaviors improved significantly for three behaviors. These include one antenatal checkup in last trimester of pregnancy (odds ratio 1.72, p < 0.05), receiving a postnatal checkup within 7 days of delivery (odds ratio 3.02, p < 0.05), and delayed bathing of newborn (odds ratio 1.93, p < 0.05). Thus, communicating messages using m-Health was found to be an effective intervention for behavior change. The study demonstrated that mobile phones can be used effectively to reach men with MCH information and encourage them to promote healthy behavior in their family.
Photochemistry beyond the red limit in chlorophyll f–containing photosystems

Lower-energy photons do the work, too Plants and cyanobacteria use chlorophyll-rich photosystem complexes to convert light energy into chemical energy. Some organisms have developed adaptations to take advantage of longer-wavelength photons. Nürnberg et al. studied photosystem complexes from cyanobacteria grown in the presence of far-red light. The authors identified the primary donor chlorophyll as one of a few chlorophyll molecules in the far-red light–adapted enzymes that were chemically altered to shift their absorption spectrum. Kinetic measurements demonstrated that far-red light is capable of directly driving water oxidation, despite having less energy than the red light used by most photosynthetic organisms. Science, this issue p. 1210 A chlorophyll variant with far-red absorption is involved in photosynthesis in cyanobacteria adapted to far red light. Photosystems I and II convert solar energy into the chemical energy that powers life. Chlorophyll a photochemistry, using red light (680 to 700 nm), is near universal and is considered to define the energy “red limit” of oxygenic photosynthesis. We present biophysical studies on the photosystems from a cyanobacterium grown in far-red light (750 nm). The few long-wavelength chlorophylls present are well resolved from each other and from the majority pigment, chlorophyll a. Charge separation in photosystem I and II uses chlorophyll f at 745 nm and chlorophyll f (or d) at 727 nm, respectively. Each photosystem has a few even longer-wavelength chlorophylls f that collect light and pass excitation energy uphill to the photochemically active pigments. These photosystems function beyond the red limit using far-red pigments in only a few key positions.
Extracting Parallel Sentences with Bidirectional Recurrent Neural Networks to Improve Machine Translation

Parallel sentence extraction is a task addressing the data sparsity problem found in multilingual natural language processing applications. We propose a bidirectional recurrent neural network based approach to extract parallel sentences from collections of multilingual texts. Our experiments with noisy parallel corpora show that we can achieve promising results against a competitive baseline by removing the need of specific feature engineering or additional external resources. To justify the utility of our approach, we extract sentence pairs from Wikipedia articles to train machine translation systems and show significant improvements in translation performance.
Anterior distal femoral hemiepiphysiodesis can reduce fixed flexion deformity of the knee: a retrospective study of 83 knees

Background and purpose — Fixed knee flexion deformity in children is a common problem in various diseases including myelomeningocele and cerebral palsy. Until now, only a few studies focusing on the surgical procedure of anterior distal femoral hemiepiphysiodesis have been published. We analyzed outcome and correction rate in the largest case series to date of patients treated by staples or 8-plates. Patients and methods — We reviewed the medical records of all patients with fixed knee flexion deformity who were treated with anterior distal femoral hemiepiphysiodesis using either staples or 8-plates between the years 2002 and 2017 (73 patients; 130 knees). 49 patients (83 knees) had completed treatment with implant removal at the time of full correction of the deformity or at skeletal maturity and were included. The average age at operation was 12 years (6–20). Patients were assigned to 3 different groups based on their diagnosis: cerebral palsy, myelomeningocele, and the “other” group.d Results — Mean fixed knee flexion deformity improved from 21° (10–60°) to 8° (0–50°) (p < 0.001) with an average correction rate of 0.44° per month (range –2.14° to 1.74°). The correction rate per month was lowest for patients with cerebral palsy (0.20°), followed by the myelomeningocele group (0.50°), and the “other” group (0.58°). Implant loosening occurred in 10% of the treated knees with consecutive re-implantation in 5% of the cases. Interpretation — Anterior distal femoral hemiepiphysiodesis is an effective and safe method for the treatment of fixed knee flexion deformity in children. The optimal timing depends on the remaining individual growth potential, the underlying disease, and the extent of the deformity.
DynaSLAM: Tracking, Mapping, and Inpainting in Dynamic Scenes

The assumption of scene rigidity is typical in SLAM algorithms. Such a strong assumption limits the use of most visual SLAM systems in populated real-world environments, which are the target of several relevant applications like service robotics or autonomous vehicles. In this letter we present DynaSLAM, a visual SLAM system that, building on ORB-SLAM2, adds the capabilities of dynamic object detection and background inpainting. DynaSLAM is robust in dynamic scenarios for monocular, stereo, and RGB-D configurations. We are capable of detecting the moving objects either by multiview geometry, deep learning, or both. Having a static map of the scene allows inpainting the frame background that has been occluded by such dynamic objects. We evaluate our system in public monocular, stereo, and RGB-D datasets. We study the impact of several accuracy/speed trade-offs to assess the limits of the proposed methodology. DynaSLAM outperforms the accuracy of standard visual SLAM baselines in highly dynamic scenarios. And it also estimates a map of the static parts of the scene, which is a must for long-term applications in real-world environments.
Reactivation of recall-induced neurons contributes to remote fear memory attenuation

The mechanisms of fear attenuation Surprisingly little is known about how remote fearful memories are stored and attenuated. Khalaf et al. used independent fear memory attenuation paradigms, engram-based tagging techniques, and chemogenetic tools to alter neuronal activity (see the Perspective by Frankland and Josselyn). They found that a discrete subset of neurons within an ensemble is engaged during recall after memory attenuation, which correlated with fear reduction. Memory updating and extinction mechanisms thus likely coexist to make this happen. These findings support the notion that effective memory attenuation is mediated by a rewriting of the original memory trace of fear toward one of safety. Science, this issue p. 1239; see also p. 1186 During the attenuation of long-lasting fear memories, the original memory trace is reengaged toward safety. Whether fear attenuation is mediated by inhibition of the original memory trace of fear with a new memory trace of safety or by updating of the original fear trace toward safety has been a long-standing question in neuroscience and psychology alike. In particular, which of the two scenarios underlies the attenuation of remote (month-old) fear memories is completely unknown, despite the impetus to better understand this process against the backdrop of enduring traumata. We found—chemogenetically and in an engram-specific manner—that effective remote fear attenuation is accompanied by the reactivation of memory recall–induced neurons in the dentate gyrus and that the continued activity of these neurons is critical for fear reduction. This suggests that the original memory trace of fear actively contributes to remote fear attenuation.
SPNets: Differentiable Fluid Dynamics for Deep Neural Networks

In this paper we introduce Smooth Particle Networks (SPNets), a framework for integrating fluid dynamics with deep networks. SPNets adds two new layers to the neural network toolbox: ConvSP and ConvSDF, which enable computing physical interactions with unordered particle sets. We use these lay- ers in combination with standard neural network layers to directly implement fluid dynamics inside a deep network, where the parameters of the network are the fluid parameters themselves (e.g., viscosity, cohesion, etc.). Because SPNets are imple- mented as a neural network, the resulting fluid dynamics are fully differentiable. We then show how this can be successfully used to learn fluid parameters from data, perform liquid control tasks, and learn policies to manipulate liquids.
Learning Dynamics of Linear Denoising Autoencoders

Denoising autoencoders (DAEs) have proven useful for unsupervised representation learning, but a thorough theoretical understanding is still lacking of how the input noise influences learning. Here we develop theory for how noise influences learning in DAEs. By focusing on linear DAEs, we are able to derive analytic expressions that exactly describe their learning dynamics. We verify our theoretical predictions with simulations as well as experiments on MNIST and CIFAR-10. The theory illustrates how, when tuned correctly, noise allows DAEs to ignore low variance directions in the inputs while learning to reconstruct them. Furthermore, in a comparison of the learning dynamics of DAEs to standard regularised autoencoders, we show that noise has a similar regularisation effect to weight decay, but with faster training dynamics. We also show that our theoretical predictions approximate learning dynamics on real-world data and qualitatively match observed dynamics in nonlinear DAEs.
The Use of Serum Procalcitonin as a Diagnostic and Prognostic Biomarker in Chronic Obstructive Pulmonary Disease Exacerbations: A Literature Review Update

Acute exacerbations of chronic obstructive pulmonary disease (AECOPD) are a major complication in COPD patients which can be triggered by bacterial or viral infections, environmental pollutants and other causes. Procalcitonin (PCT), a peptide that markedly increases in cases of bacterial infection, has been extensively investigated as a biomarker in the diagnosis, prognosis and treatment in patients with AECOPD. A number of studies published in the last decade, tried to investigate whether PCT levels can differentiate between bacterial and other causes of exacerbations, if they can be used as a guide for optimal antibiotic therapy and if they can be a tool in the assessment of the severity and the need for further interventions in the management of those patients. This review aims to gather, summarize and critically present all the available data to date.
From Trailers to Storylines: An Efficient Way to Learn from Movies

The millions of movies produced in the human history are valuable resources for computer vision research. However, learning a vision model from movie data would meet with serious difficulties. A major obstacle is the computational cost -- the length of a movie is often over one hour, which is substantially longer than the short video clips that previous study mostly focuses on. In this paper, we explore an alternative approach to learning vision models from movies. Specifically, we consider a framework comprised of a visual module and a temporal analysis module. Unlike conventional learning methods, the proposed approach learns these modules from different sets of data -- the former from trailers while the latter from movies. This allows distinctive visual features to be learned within a reasonable budget while still preserving long-term temporal structures across an entire movie. We construct a large-scale dataset for this study and define a series of tasks on top. Experiments on this dataset showed that the proposed method can substantially reduce the training time while obtaining highly effective features and coherent temporal structures.
Synapse-specific representation of the identity of overlapping memory engrams

Disentangling specific memories Each memory is stored in a distinct memory trace in the brain, in a specific population of neurons called engram cells. How does the brain store and define the identity of a specific memory when two memories interact and are encoded in a shared engram? Abdou et al. used optogenetic reactivation coupled with manipulations of long-term potentiation to analyze engrams that share neurons in the lateral amygdala (see the Perspective by Ramirez). Synapse-specific plasticity guaranteed the storage and the identity of individual memories in a shared engram. Moreover, synaptic plasticity between specific engram assemblies was necessary and sufficient for memory engram formation. Science, this issue p. 1227; see also p. 1182 Memory identity is defined by plasticity occurring at specific synapses that underlie each memory trace. Memories are integrated into interconnected networks; nevertheless, each memory has its own identity. How the brain defines specific memory identity out of intermingled memories stored in a shared cell ensemble has remained elusive. We found that after complete retrograde amnesia of auditory fear conditioning in mice, optogenetic stimulation of the auditory inputs to the lateral amygdala failed to induce memory recall, implying that the memory engram no longer existed in that circuit. Complete amnesia of a given fear memory did not affect another linked fear memory encoded in the shared ensemble. Optogenetic potentiation or depotentiation of the plasticity at synapses specific to one memory affected the recall of only that memory. Thus, the sharing of engram cells underlies the linkage between memories, whereas synapse-specific plasticity guarantees the identity and storage of individual memories.