Miracle-dz/UniFAR-FTUs huggingface dataset:
Deep Room Recognition Using Inaudible Echos

Recent years have seen the increasing need of location awareness by mobile applications. This paper presents a room-level indoor localization approach based on the measured room's echos in response to a two-millisecond single-tone inaudible chirp emitted by a smartphone's loudspeaker. Different from other acoustics-based room recognition systems that record full-spectrum audio for up to ten seconds, our approach records audio in a narrow inaudible band for 0.1 seconds only to preserve the user's privacy. However, the short-time and narrowband audio signal carries limited information about the room's characteristics, presenting challenges to accurate room recognition. This paper applies deep learning to effectively capture the subtle fingerprints in the rooms' acoustic responses. Our extensive experiments show that a two-layer convolutional neural network fed with the spectrogram of the inaudible echos achieve the best performance, compared with alternative designs using other raw data formats and deep models. Based on this result, we design a RoomRecognize cloud service and its mobile client library that enable the mobile application developers to readily implement the room recognition functionality without resorting to any existing infrastructures and add-on hardware. Extensive evaluation shows that RoomRecognize achieves 99.7%, 97.7%, 99%, and 89% accuracy in differentiating 22 and 50 residential/office rooms, 19 spots in a quiet museum, and 15 spots in a crowded museum, respectively. Compared with the state-of-the-art approaches based on support vector machine, RoomRecognize significantly improves the Pareto frontier of recognition accuracy versus robustness against interfering sounds (e.g., ambient music).
Clinical Outcome and Management for Geriatric Traumatic Injury: Analysis of 2688 Cases in the Emergency Department of a Teaching Hospital in Taiwan

Geriatric traumatic injuries in emergency departments are frequent and associated with higher mortality rates and catastrophic functional outcomes. Several prediction scores have been established to manage traumatic patients, including the shock index (SI), revised trauma score (RTS), injury severity score (ISS), trauma injury severity score (TRISS), and new injury severity score (NISS). However, it was necessary to investigate the effectiveness and efficiency of care for the geriatric traumatic population. In addition, image studies such as computed tomography and magnetic resonance imaging play an important role in early diagnosis and timely intervention. However, few studies focus on this aspect. The association between the benefit of carrying out more image studies and clinical outcomes remains unclear. In this study, we included a total of 2688 traumatic patients and analyzed the clinical outcomes and predicting factors in terms of geriatric trauma via pre-hospital and in-hospital analysis. Our evaluation revealed that a shock index ≥1 may be not a strong predictor of geriatric trauma due to the poor physical response in the aging population. This should be modified in geriatric patients. Other systems, like RTS, ISS, TRISS, and NISS, were significant in terms of predicting the clinical outcome.
Structure of graphene and its disorders: a review

ABSTRACT Monolayer graphene exhibits extraordinary properties owing to the unique, regular arrangement of atoms in it. However, graphene is usually modified for specific applications, which introduces disorder. This article presents details of graphene structure, including sp2 hybridization, critical parameters of the unit cell, formation of σ and π bonds, electronic band structure, edge orientations, and the number and stacking order of graphene layers. We also discuss topics related to the creation and configuration of disorders in graphene, such as corrugations, topological defects, vacancies, adatoms and sp3-defects. The effects of these disorders on the electrical, thermal, chemical and mechanical properties of graphene are analyzed subsequently. Finally, we review previous work on the modulation of structural defects in graphene for specific applications. Graphical Abstract
Mammalian STT3A/B oligosaccharyltransferases segregate N-glycosylation at the translocon from lipid-linked oligosaccharide hydrolysis

Significance Specialized sugar polymers (oligosaccharides) are necessary for life at the protein, organelle, cell, and organism levels. Processes for degrading oligosaccharides enhance their repertoire of functions, but a potential problem is short circuiting between degradation and synthesis. With the endoplasmic reticulum of mammalian cells, we show how lipid-linked oligosaccharides (LLOs) meant for attachment to proteins are segregated from an immunogenic process that involves their degradation to free oligosaccharides. Specifically, the STT3A isoform of oligosaccharyltransferase only transfers oligosaccharides, while the STT3B isoform can hydrolyze LLOs when not preoccupied with attachment of oligosaccharides to protein. This allows cells to perform both important processes in concert, without problems due to competition. Oligosaccharyltransferases (OSTs) N-glycosylate proteins by transferring oligosaccharides from lipid-linked oligosaccharides (LLOs) to asparaginyl residues of Asn-Xaa-Ser/Thr acceptor sequons. Mammals have OST isoforms with STT3A or STT3B catalytic subunits for cotranslational or posttranslational N-glycosylation, respectively. OSTs also hydrolyze LLOs, forming free oligosaccharides (fOSs). It has been unclear whether hydrolysis is due to one or both OSTs, segregated from N-glycosylation, and/or regulated. Transfer and hydrolysis were assayed in permeabilized HEK293 kidney and Huh7.5. 1 liver cells lacking STT3A or STT3B. Transfer by both STT3A-OST and STT3B-OST with synthetic acceptors was robust. LLO hydrolysis by STT3B-OST was readily detected and surprisingly modulated: Without acceptors, STT3B-OST hydrolyzed Glc3Man9GlcNAc2-LLO but not Man9GlcNAc2-LLO, yet it hydrolyzed both LLOs with acceptors present. In contrast, LLO hydrolysis by STT3A-OST was negligible. STT3A-OST however may be regulatory, because it suppressed STT3B-OST–dependent fOSs. TREX1, a negative innate immunity factor that diminishes immunogenic fOSs derived from LLOs, acted through STT3B-OST as well. In summary, only STT3B-OST hydrolyzes LLOs, depending upon LLO quality and acceptor site occupancy. TREX1 and STT3A suppress STT3B-OST–dependent fOSs. Without strict kinetic limitations during posttranslational N-glycosylation, STT3B-OST can thus moonlight for LLO hydrolysis. In contrast, the STT3A-OST/translocon complex preserves LLOs for temporally fastidious cotranslational N-glycosylation.
The Effect of Intraradicular Multiple Fiber and Cast Posts on the Fracture Resistance of Endodontically Treated Teeth with Wide Root Canals

Introduction The endodontically treated teeth (ETT) with thin remaining radicular dentin thickness are predisposed to fracture; hence it requires the diligent selection and the execution of endodontic post treatment. The objective of the study was to evaluate the reinforcing effect of both multiple fiber reinforced composite (FRC) and Ni-Cr cast metal posts at anterior and posterior regions. Material and Methods Forty recently extracted root canal treated canine and single rooted premolar teeth were used for the study. They were randomly divided into four groups (n=10) as: Group 1, single FRC post; Group 2, multiple FRC posts; Group 3, single Ni-Cr metal post, Group 4, multiple Ni-Cr posts. The posts were cemented with self-adhesive resin cement and subsequently restored with full veneer metal crown. The compressive static load at 1300 for canine and 450 for premolar was applied with the cross-head speed of 0.5mm/minute until the fracture. The obtained data was analyzed using the Kruskal–Wallis and Pairwise comparison tests with SPSS. Results The results indicate that multiple FRC post restored canine had the maximum fracture load (1843.80±7.13 N), followed by cast multiple posts (1648.99±26.84 N), single fiber post (1623±40.31 N), and cast metal single post (1493±27.33 N). A similar trend was observed in premolar with higher max fracture load with multiple FRC posts at 1920.86±20.61 N and multiple cast metal posts at 1735.43±6.05 N. Conclusion The restoration of ETT with larger canals by multiple FRC and metal posts provides substantially higher fracture resistance in comparison to wider single post.
Learning Saliency Prediction From Sparse Fixation Pixel Map

Ground truth for saliency prediction datasets consists of two types of map data: fixation pixel map which records the human eye movements on sample images, and fixation blob map generated by performing gaussian blurring on the corresponding fixation pixel map. Current saliency approaches perform prediction by directly pixel-wise regressing the input image into saliency map with fixation blob as ground truth, yet learning saliency from fixation pixel map is not explored. In this work, we propose a first-of-its-kind approach of learning saliency prediction from sparse fixation pixel map, and a novel loss function for training from such sparse fixation. We utilize clustering to extract sparse fixation pixel from the raw fixation pixel map, and add a max-pooling transformation on the output to avoid false penalty between sparse outputs and labels caused by nearby but non-overlapping saliency pixels when calculating loss. This approach provides a novel perspective for achieving saliency prediction. We evaluate our approach over multiple benchmark datasets, and achieve competitive performance in terms of multiple metrics comparing with state-of-the-art saliency methods.
Development and validation of Cognitive Training Intervention for Alzheimer’s disease (CTI-AD): A picture-based interventional program

Introduction Alzheimer’s disease is a gradual and progressive disorder which cripples the person’s functionality due to cognitive decline. Many clinicopathological and pharmacological therapy has the potential to slow down the progression of the disease but has limited efficacy. One complimentary approach that has emerged is cognitive training interventions which have shown synergistic effect with the drug therapy. Nevertheless, many cognitive interventions lack on specificities of the intervention due to which its efficacy gets scrutinized. Objective To describe the foundation, content, and development of Cognitive Training Intervention for Alzheimer’s disease (CTI-AD) along with the treatment feasibility based on a pilot study. Materials and methods A culture-specific picture-based eight weeks cognitive training manual was developed based on extensive review and focused group discussions. It was standardized on 63 older participants (48 healthy controls (HC); 15 early Alzheimer’s disease cases). Results All the tasks were progressive in nature and were found effective in discriminating the cognitive performance of early Alzheimer’s disease and HC throughout the intervention period. Moreover, it also improved early Alzheimer’s disease performance on the memory (HC: 1st week/8th week = 21.6 ± 5.7/57.3 ± 19.0; early Alzheimer’s disease: 1st week/8th week = 48.5 ± 22.9/60.5 ± 21.8); attention (HC: 1st week/8th week = 90.2 ± 18.0/196.9 ± 28.0; early Alzheimer’s disease: 1st week/8th week = 216.6 ± 78.2/286.8 ± 87.0) and language (HC: 1st week/8th week = 29.8 ± 9.4/115.3 ± 31.1; early Alzheimer’s disease: 1st week/8th week = 211.8 ± 68.4/270.4 ± 104.9) domains, respectively, from the baseline level. Conclusion The current manual (CTI-AD) is one of the first promising non-pharmacological program developed nationally with a strong theoretical base to cater to the tertiary needs of the older adults with early Alzheimer’s disease.
Sport Harrassment in the Eyes of Hong Kong Youth Swimmers

In this study, sport harassment is defined as harassment situated in sport. The aims of the study were to identify behaviors considered to be a form of sport harassment in the eyes of Hong Kong youth swimmers and to understand the prevalence of sport harassment sustained by them. Given that some forms of sport harassment are more offensive than others, the study also aims to identify those forms which youth swimmers find more offensive.
Your Actions or Your Associates? Predicting Certification and Dropout in MOOCs with Behavioral and Social Features

The high level of attrition and low rate of certification in Massive Open Online Courses (MOOCs) has prompted a great deal of research. Prior researchers have focused on predicting dropout based upon behavioral features such as student confusion, click-stream patterns, and social interactions. However, few studies have focused on combining student logs with forum data. In this work, we use data from two different offerings of the same MOOC. We conduct a survival analysis to identify likely dropouts. We then examine two classes of features, social and behavioral, and apply a combination of modeling and feature-selection methods to identify the most relevant features to predict both dropout and certification. We examine the utility of three different model types and we consider the impact of different definitions of dropout on the predictors. Finally, we assess the reliability of the models over time by evaluating whether or not models from week 1 can predict dropout in week 2, and so on. The outcomes of this study will help instructors identify students likely to fail or dropout as soon as the first two weeks and provide them with more support.
Modulation of P2X Purinoceptor 3 (P2X3) in Pentylenetetrazole-Induced Kindling Epilepsy in Rats

Background Epilepsy is a complex neurologic disorder with abnormal electrical impulses in the brain. A crucial role of purinergic signalling in the proper working of the nervous system has been reported but much less is known about the modulation of P2X3 purinergic receptors in epilepsy. This study investigated the effect of NF110, a potent P2X3 receptor antagonist, in the rat epilepsy model of pentylenetetrazole (PTZ)-induced kindling. Material/Methods The mean kindling score, motor activity, locomotion, emotional tension, anxiety, discrimination ability, learning, memory, serum neuron-specific enolase (sNSE), hippocampal IL-1β and TNF-α, thiobarbituric acid-reactive substance (TBARS), catalase (CAT) and reduced glutathione (GSH), and mitochondrial complex I, II, and IV levels of PTZ-kindling animals were assessed. Results The PTZ-kindling animals have shown impaired motor activity, locomotion, discrimination ability, learning, and memory, along with increased emotional tension, anxiety, neuronal damage (increased sNSE), hippocampal pro-inflammatory mediators (increased IL-1β and TNF-α), oxidative stress (increased TBARS, decreased GSH and CAT), and mitochondrial dysfunction. The administration of NF110 in 3 different doses has significantly and dose-dependently corrected PTZ-kindling-induced impaired behavior, learning, memory, locomotion, motor activity, discrimination ability, neuronal damage, hippocampal inflammation, oxidative stress, and mitochondrial dysfunction. These beneficial effects of NF110 in PTZ-kindling animals were significantly abolished by the administration of the P2X agonist α, β methylene-ATP. Conclusions P2X3 receptors play a very important role in kindling epilepsy and further research should be done to design P2X3 modulators for their possible therapeutic benefits in epileptic disorders.
A Comprehensive Survey of Immune Cytolytic Activity-Associated Gene Co-Expression Networks across 17 Tumor and Normal Tissue Types

Cytolytic immune activity in solid tissue can be quantified by transcript levels of two genes, GZMA and PRF1, which is named the CYT score. A previous study has investigated the molecular and genetic properties of tumors associated CYT, but a systematic exploration of how co-expression networks across different tumors are shaped by anti-tumor immunity is lacking. Here, we examined the connectivity and biological themes of CYT-associated modules in gene co-expression networks of 14 tumor and 3 matched normal tissues constructed from the RNA-Seq data of the “The Cancer Genome Atlas” project. We first found that tumors networks have more diverse CYT-correlated modules than normal networks. We next identified and investigated tissue-specific CYT-associated modules across 14 tumor types. Finally, a common CYT-associated network across 14 tumor types was constructed. Two common modules have mixed signs of correlation with CYT in different tumors. Given the tumors and normal tissues surveyed, our study presents a systematic view of the regulation of cytolytic immune activity across multiple tumor tissues.
Microfluidically Frequency-Reconfigurable Quasi-Yagi Dipole Antenna

In this paper, a frequency reconfigurable quasi-Yagi dipole antenna is proposed by leveraging the properties of microfluidic technology. The proposed antenna comprises a metal-printed driven dipole element and three directors. To tune resonant frequencies, microfluidic channels are integrated into the driven element. To maintain a high gain for all the tuned frequencies, microfluidic channels are also integrated into the directors. Therefore, the length of the driven-element as well as directors can be controlled by injecting liquid metal in the microfluidic channels. The proposed antenna has the capability of tuning the frequency by varying the length of the metal-filled channels, while maintaining a high gain for all the tuned frequencies. The proposed antenna’s performance is experimentally demonstrated after fabrication. The injected amount of liquid metal into the microfluidic channels is controlled using programmable pneumatic micropumps. The prototype exhibits continuous tuning of the resonant frequencies from 1.8 GHz to 2.4 GHz; the measured peak gain of the proposed antenna is varied in the range of 8 dBi to 8.5 dBi. Therefore, continuous tuning with high gain is successfully demonstrated using liquid-metal-filled microfluidic channels.
Ship Classification in High-Resolution SAR Images Using Deep Learning of Small Datasets

With the capability to automatically learn discriminative features, deep learning has experienced great success in natural images but has rarely been explored for ship classification in high-resolution SAR images due to the training bottleneck caused by the small datasets. In this paper, convolutional neural networks (CNNs) are applied to ship classification by using SAR images with the small datasets. First, ship chips are constructed from high-resolution SAR images and split into training and validation datasets. Second, a ship classification model is constructed based on very deep convolutional networks (VGG). Then, VGG is pretrained via ImageNet, and fine tuning is utilized to train our model. Six scenes of COSMO-SkyMed images are used to evaluate our proposed model with regard to the classification accuracy. The experimental results reveal that (1) our proposed ship classification model trained by fine tuning achieves more than 95% average classification accuracy, even with 5-cross validation; (2) compared with other models, the ship classification model based on VGG16 achieves at least 2% higher accuracies for classification. These experimental results reveal the effectiveness of our proposed method.
Secondary Microplastics Generation in the Sea Swash Zone With Coarse Bottom Sediments: Laboratory Experiments

Marine beaches worldwide are nowadays exposed to significant contamination by plastics. On the Baltic beaches, polyethylene, polypropylene, and polystyrene are most abundant. We investigate the generation of microplastics particles (MPs, characteristic size from 0.5 to 5 mm) from larger plastic items in the sea swash zone using a laboratory rotating mixer filled with water and natural coarse beach sediment (marine pebbles). Inclination of the axis of rotation and the volume of the material were adjusted in such a way that mixing resembled a breaking wave in the swash zone. Plastic samples used were of the types most commonly found on the sea beaches. Experimental 2cm×2cm-large plastic items made of low-density polyethylene (LDPE) were manufactured from common new garbage bags (thickness 5 μm); those made of polypropylene (PP) and polystyrene (PS) were produced from single-use tableware; samples of foamed plastics were presented by cubes (with 2-cm sides) cut out of standard building insulator sheets (foamed PS). Four sets of 24-h-long experiments were conducted (for each type of plastic separately), with step-wise (every 3 hours) examination of the generated MPs mass, number of particles and their qualitative characteristics such as shape, quality of the surface, general behaviour while mixing, etc. Statistically significant dependencies are obtained for the increase in mass and in number of MPs with time for all four used kinds of plastics. Brittle solid PS is shown to be the most productive in terms of both mass and number of MPs generated. Anisotropic springing PP is the most resistant. Tensile tearing of LDPE and fragmentation of foamed PS to compounding bubbles/spherules show the variety of mechanisms involved in fragmentation of plastics in the swash zone. Increase in MPs mass and the number of MPs particles with time, as well the link between them, are important for field monitoring and numerical modelling. Potentially shape-selective operation of sieves during sampling and sorting of MPs particles of various shapes is discussed.
Estimation of daily intake of polychlorinated biphenyls not similar to dioxins (NDL-PCB) from fish consumption in Spain in different population groups

Abstract Objective To assess the daily intake of polychlorinated biphenyls not similar to dioxins (NDL-PCB) derived from fish consumption in Spain and compare it with tolerance limits in order to establish a safe threshold so that the nutritional benefits derived from fish consumption may be optimized. Design Analysis of NDL-PCB in fish samples and ecological study of the estimated intake of NDL-PCB from fish consumption in different Spanish population groups. Subjects National representative sample of the Spanish population. Results The intake of NDL-PCB was estimated in two different scenarios: upper bound (UB) and lower bound (LB). Estimating intake using the average concentration of NDL-PCB found in the fish samples, the intake for ‘other children’ is estimated as: 1·80 (UB) and 5·33 (LB) ng/kg per d at the 50th percentile (P50); 7·39 (UB) and 21·94 (LB) ng/kg per d at the 95th percentile (P95) of fish consumption. Estimated NDL-PCB intake shoots up in the toddler group, reaching values of 30·43 (UB) and 90·37 (LB) ng/kg per d at P95. Estimated intake values are lower than those previously estimated in Europe, something expected since in previous studies intake was estimated through total diet. In adults, our estimated values are 1·59 (UB) and 4·72 (LB) ng/kg per d at P50; 4·95 (UB) and 14·72 (LB) ng/kg per d at P95. Conclusions NDL-PCB concentration in fish is under the tolerance limits in most samples. However, daily intake in consumers of large quantities of fish should be monitored and special attention should be given to the youngest age groups due to their special vulnerability and higher exposure.