Miracle-dz/UniFAR-FTUs huggingface dataset:
Acid Free Oxidation and Simple Dispersion Method of MWCNT for High-Performance CFRP

Carbon nanotubes (CNT) provide an outstanding property spectrum which can be used to improve a wide range of materials. However, the transfer of properties from the nanoscale to a macroscopic material is a limiting factor. Different approaches of functionalizing the surface of a CNT can improve the interaction with the surrounding matrix but is connected to difficult and expensive treatments, which are usually inconvenient for industrial applications. Here, a simple and eco-friendly method is presented for the oxidation of CNT, where hydrogen peroxide (H2O2) is the only chemical needed and no toxic emissions are released. Also, the extensive step of the incorporation of CNT to an epoxy matrix is simplified to an ultrasonic dispersion in the liquid hardener component. The effectiveness is proven by mechanical tests of produced CNT/CFRP and compared to a conventional processing route. The combination of those simple and cost efficient strategies can be utilized to produce multiscale composites with improved mechanical performance in an ecological and economical way.
Introduction to the 1st Place Winning Model of OpenImages Relationship Detection Challenge

This article describes the model we built that achieved 1st place in the OpenImage Visual Relationship Detection Challenge on Kaggle. Three key factors contribute the most to our success: 1) language bias is a powerful baseline for this task. We build the empirical distribution $P(predicate|subject,object)$ in the training set and directly use that in testing. This baseline achieved the 2nd place when submitted; 2) spatial features are as important as visual features, especially for spatial relationships such as "under" and "inside of"; 3) It is a very effective way to fuse different features by first building separate modules for each of them, then adding their output logits before the final softmax layer. We show in ablation study that each factor can improve the performance to a non-trivial extent, and the model reaches optimal when all of them are combined.
Genome Instability Induced by Low Levels of Replicative DNA Polymerases in Yeast

Most cells of solid tumors have very high levels of genome instability of several different types, including deletions, duplications, translocations, and aneuploidy. Much of this instability appears induced by DNA replication stress. As a model for understanding this type of instability, we have examined genome instability in yeast strains that have low levels of two of the replicative DNA polymerases: DNA polymerase α and DNA polymerase δ (Polα and Polδ). We show that low levels of either of these DNA polymerases results in greatly elevated levels of mitotic recombination, chromosome rearrangements, and deletions/duplications. The spectrum of events in the two types of strains, however, differs in a variety of ways. For example, a reduced level of Polδ elevates single-base alterations and small deletions considerably more than a reduced level of Polα. In this review, we will summarize the methods used to monitor genome instability in yeast, and how this analysis contributes to understanding the linkage between genome instability and DNA replication stress.
BPDS: A Blockchain Based Privacy-Preserving Data Sharing for Electronic Medical Records

Electronic medical record (EMR) is a crucial form of healthcare data, currently drawing a lot of attention. Sharing health data is considered to be a critical approach to improve the quality of healthcare service and reduce medical costs. However, EMRs are fragmented across decentralized hospitals, which hinders data sharing and puts patients' privacy at risks. To address these issues, we propose a blockchain based privacy-preserving data sharing for EMRs, called BPDS. In BPDS, the original EMRs are stored securely in the cloud and the indexes are reserved in a tamper-proof consortium blockchain. By this means, the risk of the medical data leakage could be greatly reduced, and at the same time, the indexes in blockchain ensure that the EMRs can not be modified arbitrarily. Secure data sharing can be accomplished automatically according to the predefined access permissions of patients through the smart contracts of blockchain. Besides, the joint-design of the CP-ABE-based access control mechanism and the content extraction signature scheme provides strong privacy preservation in data sharing. Security analysis shows that BPDS is a secure and effective way to realize data sharing for EMRs.
Pre-service and In-service Teachers’ Metacognitive Knowledge of Learning Strategies

Research in cognitive psychology has suggested that difficulties are often desirable for learning: learning strategies that create difficulties for learners during practice often produce durable learning. Prominent examples of effective learning strategies that introduce desirable difficulties are testing as a means of learning, spacing study sessions over time, and interleaving practice of different topics. Previous research has suggested that, generally, undergraduates’ metacognitive knowledge about the effectiveness of these learning strategies is inaccurate. The goal of the current study was to extend the examination of metacognitive knowledge of learning strategies to pre-service and in-service teachers, and further examine whether teachers’ metacognitive knowledge is related to their teaching experience. Pre-service teachers enrolled in a university teacher training program (N = 83) and in-service elementary, junior-high, and high school teachers (N = 82) were presented with learning scenarios and predicted which of two learning strategies would yield the better outcome. Results suggested that, overall, both pre-service and in-service teachers failed to predict the advantages of testing, spacing, and interleaving as learning strategies. Furthermore, their knowledge of learning strategies failed to increase with teaching experience. It is, therefore, recommended that explicit instruction about the benefits of empirically supported learning strategies should be included in teacher training and development programs.
Calibration Wizard: A Guidance System for Camera Calibration Based on Modelling Geometric and Corner Uncertainty

It is well known that the accuracy of a calibration depends strongly on the choice of camera poses from which images of a calibration object are acquired. We present a system -- Calibration Wizard -- that interactively guides a user towards taking optimal calibration images. For each new image to be taken, the system computes, from all previously acquired images, the pose that leads to the globally maximum reduction of expected uncertainty on intrinsic parameters and then guides the user towards that pose. We also show how to incorporate uncertainty in corner point position in a novel principled manner, for both, calibration and computation of the next best pose. Synthetic and real-world experiments are performed to demonstrate the effectiveness of Calibration Wizard.
The RLLChatbot: a solution to the ConvAI challenge

Current conversational systems can follow simple commands and answer basic questions, but they have difficulty maintaining coherent and open-ended conversations about specific topics. Competitions like the Conversational Intelligence (ConvAI) challenge are being organized to push the research development towards that goal. This article presents in detail the RLLChatbot that participated in the 2017 ConvAI challenge. The goal of this research is to better understand how current deep learning and reinforcement learning tools can be used to build a robust yet flexible open domain conversational agent. We provide a thorough description of how a dialog system can be built and trained from mostly public-domain datasets using an ensemble model. The first contribution of this work is a detailed description and analysis of different text generation models in addition to novel message ranking and selection methods. Moreover, a new open-source conversational dataset is presented. Training on this data significantly improves the Recall@k score of the ranking and selection mechanisms compared to our baseline model responsible for selecting the message returned at each interaction.
Lesions Mimicking Melanoma at Dermoscopy Confirmed Basal Cell Carcinoma: Evaluation with Reflectance Confocal Microscopy

Background: Atypical basal cell carcinoma (BCC), characterized by equivocal dermoscopic features typical of malignant melanoma (MM), can be difficult to diagnose. Reflectance confocal microscopy (RCM) enables in vivo imaging at nearly histological resolution. Objectives: To evaluate with RCM atypical melanocytic lesions identified in dermoscopy, according to common RCM criteria for the differential diagnosis of BCC, and to identify representative RCM parameters for superficial (sBCCs) and nonsuperficial (nsBCCs) basal cell carcinomas (BCCs). Methods: A retrospective analysis of consecutive patients evaluated with RCM, selecting excised lesions classified at dermoscopy with ≥1 score from the re visited 7-point checklist, mimicking melanoma, registered between 2010 and 2016. Cluster analysis identified BCC subclassifications. Results: Of 178 atypical lesions, 34 lesions were diagnosed as BCCs with RCM. Lesions were confirmed BCCs with histopathology. Dermoscopic features included atypical network (55.9%) and regression structures (35.5%) associated with sBCCs, and an atypical vascular pattern (58.8%) and irregular blotches (58.8%) with nsBCCs. Hierarchical cluster analysis identified 2 clusters: cluster 1 (100% sBCCs) was characterized by the presence of cords connected to the epidermis (90%, p < 0.001), tumor islands located in the epidermis (100%, p < 0.001), smaller vascular diameter (100%, p < 0.001) and solar elastosis (90%, p = 0.017), and cluster 2 (nsBCCs 85%) was defined by the dermic location of tumor islands (87.5%, p < 0.001) with branch-like structures (70.8%, p = 0.007) and surrounding collagen (83.3%, p = 0.012), peripheral palisading (83.3%, p = 0.012) and coiled vascular morphology (79.2%, p < 0.001) with a larger vascular diameter (50%, p < 0.001). Conclusions: RCM is able to diagnose BCCs mimicking melanoma at dermoscopy and seems able to identify sBCCs and nsBCCs.
Perpetrator Risk Markers for Intimate Terrorism and Situational Couple Violence: A Meta-Analysis

Johnson developed a typology of intimate partner violence (IPV) which includes two different categories of violence: situational couple violence (SCV) and intimate terrorism (IT). Johnson proposed that IT is more likely to be found in clinical samples (e.g., batterer intervention programs or domestic violence shelters) compared to nonclinical (general population) samples. This meta-analysis (n = 149 studies; k = 216 effect sizes) examines differences in the strengths of IPV risk markers in clinical and nonclinical samples of male perpetrators and female victims. All variables (communication and conflict resolution, demand–withdraw patterns, relationship dissatisfaction, controlling behaviors, jealousy, patriarchal beliefs, power in the relationship, and stalking) were expected to be significantly related to IPV for both clinical and nonclinical populations. However, specific variables indicative of IT (control, jealousy, patriarchal beliefs, power, and stalking) were expected to be more strongly associated with clinical samples compared to nonclinical samples. As expected, most variables were significant for clinical and nonclinical populations, and IT risk markers (control, power, jealousy, and patriarchal beliefs) were significantly stronger risk markers for IPV in clinical samples. These results indicate that Johnson’s typology may be conceptualized as representing a continuum of violence, with IT being more severe due to the controlling nature of the violence. Sample type needs to be considered when research about IPV is disseminated, as different degrees of IPV (IT vs. SCV) may be present depending on sample type. Implications from this study include the need to differentiate the level of violence and to tailor intervention for IPV appropriately.
Design of Frequency Selective Surface-Based Hybrid Nanocomposite Absorber for Stealth Applications

This paper presents the design, fabrication, and electromagnetic testing of a frequency selective surface (FSS)-based novel hybrid nanocomposite absorber for enhanced electromagnetic absorption. The proposed hybrid absorber consists of an FSS pattern printed over a dielectric substrate backed by aluminum foil, which is integrated together with a customized dielectric nanocomposite sheet. The dielectric sheet comprises the conducting carbon black (CB) nanopowders embedded into the epoxy matrix. The fabricated nanocomposite sheet is first characterized for the effective complex permittivity using the free-space measurement technique, and the measured electromagnetic properties are then used for the design of a hybrid absorber. The proposed hybrid absorber having overall thickness of 2.6 mm shows enhanced −10-dB absorption bandwidth of 3.5 GHz, which is much higher than that of the FSS and CB nanocomposite samples measured individually. The proposed work provides an effective way to combine the absorption properties of FSS with that of a customized dielectric absorber sheet in order to design an efficient hybrid absorber having reduced thickness with enhanced absorption bandwidth for stealth technology and various strategic applications.
Towards Fluent Translations From Disfluent Speech

When translating from speech, special consideration for conversational speech phenomena such as disfluencies is necessary. Most machine translation training data consists of well-formed written texts, causing issues when translating spontaneous speech. Previous work has introduced an intermediate step between speech recognition (ASR) and machine translation (MT) to remove disfluencies, making the data better-matched to typical translation text and significantly improving performance. However, with the rise of end-to-end speech translation systems, this intermediate step must be incorporated into the sequence-to-sequence architecture. Further, though translated speech datasets exist, they are typically news or rehearsed speech without many disfluencies (e.g. TED), or the disfluencies are translated into the references (e.g. Fisher). To generate clean translations from disfluent speech, cleaned references are necessary for evaluation. We introduce a corpus of cleaned target data for the Fisher Spanish-English dataset for this task. We compare how different architectures handle disfluencies and provide a baseline for removing disfluencies in end-to-end translation.
Trends and drivers of change in the prevalence of anaemia among 1 million women and children in India, 2006 to 2016

Introduction India carries the largest burden of anaemia globally. Progress to reduce anaemia has been slow despite substantial economic growth and 50 years of programmatic efforts. Identification of the factors that contribute to anaemia reductions is needed to accelerate progress. We examined changes in haemoglobin (Hb) and anaemia among women and children in India from 2006 to 2016 and identified drivers of changes in these outcomes over time. Methods We used two rounds of National Family Health Survey data collected in 2005–2006 and 2015–2016 (n=245 346 children 6–59 months; 37 165 pregnant women (PW) 15–49 years; 760 460 non-pregnant women (NPW) 15–49 years). We first examined trends in Hb and anaemia, and changes in 30 selected variables (including immediate and underlying determinants, and nutrition and health interventions (NHIs)). We identified drivers of Hb and anaemia using multivariate regression and estimated their contribution to changes in these outcomes over time using regression-based decomposition. Results Hb and anaemia improved significantly between 2006 and 2016 in children (4.5 g/L and 11 percentage points (pp), respectively) and PW (3.2 g/L and 7.6 pp), but not in NPW. Despite these changes, anaemia is still very high (>50%) and progress varied considerably by state (−33 pp to +16 pp). Most immediate and underlying determinants, and NHIs improved significantly over time. Changes among a set of drivers common to children and PW accounted for the changes in Hb; these included maternal schooling (children, 10%; PW, 24%), coverage of NHIs (children, 18%; PW, 7%), socioeconomic status (children, 7%; PW, 17%), sanitation (children, 3%; PW, 9%), and meat and fish consumption (children, 3%; PW, 1%). The decomposition models moderately explained Hb changes over time (children, 49%; PW, 66%). Conclusions Multiple common drivers have contributed to the anaemia changes among children and pregnant women in India. Further improvements in these drivers can have population-level effects by simultaneously influencing both maternal and child anaemia.
Multiport In-Phase/Antiphase Power Dividing Network With Bandpass Response Based on Dielectric Resonator

This paper presents a fusion design approach of multiport (1-to-<inline-formula> <tex-math notation="LaTeX">$N$ </tex-math></inline-formula>) in-phase/antiphase power dividing network with a bandpass response, which can be applied in constructing either the balanced or single-ended filtering power divider. The relationships of external <inline-formula> <tex-math notation="LaTeX">$Q$ </tex-math></inline-formula>-factors (<inline-formula> <tex-math notation="LaTeX">$Q_{e}\text{s}$ </tex-math></inline-formula>) between the in-phase/antiphase ports are constructed, and it is found that their <inline-formula> <tex-math notation="LaTeX">$Q_{e}$ </tex-math></inline-formula> ratio is determined by power allocation regardless of the phase difference. Meanwhile, the two functions of power allocation and bandpass response can be designed independently. Based on the theoretical analysis, two kinds of filtering power dividers using the dielectric resonator (DR) are proposed. One is balanced and the other is single ended. Both of them can be easily built by properly adding feeding probes for the DR without increasing the circuit size, while the phase difference between the ports can be adjusted to be either in-phase or antiphase by altering the direction of the feeding probes. To verify the proposed design concept, the filtering power dividers mentioned earlier are simulated. Some of them are implemented and measured, and their measured results match well with the simulated data, showing good performance, such as low loss and good selectivity.
Modelling and Design of MEMS Piezoresistive Out-of-Plane Shear and Normal Stress Sensors

In this paper, the design of MEMS piezoresistive out-of-plane shear and normal stress sensor is described. To improve the sensor sensitivity, a methodology by the incorporation of stress concentration regions, namely surface trenches in the proximity of sensing elements was explored in detail. The finite element (FE) model, verified by a five-layer analytical model was developed as a tool to model the performance of the sensor and guide the geometric optimization of the surface trenches. Optimum location and dimensions of the surface trenches have been obtained through a comprehensive FE analysis. The microfabrication and packing scheme was introduced to prototype the sensor with optimum geometric characteristics of surface trenches. Signal output from the prototyped sensor was tested and compared with those from FE simulation. Good agreement has been achieved between the simulation and experimental results. Moreover, the results suggest the incorporation of surface trenches can help improve the sensor sensitivity. More specifically, the sum of signal output from the sensor chip with surface trenches are 4.52, 5.06 and 5.72 times higher compared to flat sensor chip for center sensing area, edge sensing areas 1 and 2, respectively.
The ATG5-binding and coiled coil domains of ATG16L1 maintain autophagy and tissue homeostasis in mice independently of the WD domain required for LC3-associated phagocytosis

ABSTRACT Macroautophagy/autophagy delivers damaged proteins and organelles to lysosomes for degradation, and plays important roles in maintaining tissue homeostasis by reducing tissue damage. The translocation of LC3 to the limiting membrane of the phagophore, the precursor to the autophagosome, during autophagy provides a binding site for autophagy cargoes, and facilitates fusion with lysosomes. An autophagy-related pathway called LC3-associated phagocytosis (LAP) targets LC3 to phagosome and endosome membranes during uptake of bacterial and fungal pathogens, and targets LC3 to swollen endosomes containing particulate material or apoptotic cells. We have investigated the roles played by autophagy and LAP in vivo by exploiting the observation that the WD domain of ATG16L1 is required for LAP, but not autophagy. Mice lacking the linker and WD domains, activate autophagy, but are deficient in LAP. The LAP−/- mice survive postnatal starvation, grow at the same rate as littermate controls, and are fertile. The liver, kidney, brain and muscle of these mice maintain levels of autophagy cargoes such as LC3 and SQSTM1/p62 similar to littermate controls, and prevent accumulation of SQSTM1 inclusions and tissue damage associated with loss of autophagy. The results suggest that autophagy maintains tissue homeostasis in mice independently of LC3-associated phagocytosis. Further deletion of glutamate E230 in the coiled-coil domain required for WIPI2 binding produced mice with defective autophagy that survived neonatal starvation. Analysis of brain lysates suggested that interactions between WIPI2 and ATG16L1 were less critical for autophagy in the brain, which may allow a low level of autophagy to overcome neonatal lethality. Abbreviations: CCD: coiled-coil domain; CYBB/NOX2: cytochrome b-245: beta polypeptide; GPT/ALT: glutamic pyruvic transaminase: soluble; LAP: LC3-associated phagocytosis; LC3: microtubule-associated protein 1 light chain 3; MEF: mouse embryonic fibroblast; NOD: nucleotide-binding oligomerization domain; NADPH: nicotinamide adenine dinucleotide phosphate; RUBCN/Rubicon: RUN domain and cysteine-rich domain containing Beclin 1-interacting protein; SLE: systemic lupus erythematosus; SQSTM1/p62: sequestosome 1; TLR: toll-like receptor; TMEM: transmembrane protein; TRIM: tripartite motif-containing protein; UVRAG: UV radiation resistance associated gene; WD: tryptophan-aspartic acid; WIPI: WD 40 repeat domain: phosphoinositide interacting