Miracle-dz/UniFAR-FTUs huggingface dataset:
Research Summary of Convolution Neural Network in Image Recognition

Convolution neural networks is a model of deep learning and it is popular in image recognition, object detection and speech recognition. This paper studied Convolution neural networks in detail. Firstly this paper introduced the generation and development of convolution neural networks and illustrated its advantages in image recognition tasks. Then, it summarized the classic structure of convolution neural networks. Next, this paper stated the study trends and summarized five aspects: appropriately simplified networks, reducing over-fitting, increasing gradient signal, deeper networks and randomization. Finally, this paper discussed the problems existed in convolution neural networks and looked forward to the development trends
Improve the Localization Dependability for Cyber-Physical Applications

Localization for mobile group users is one of the important applications in cyber-physical systems. However, due to the sparse deployment of anchors and the instability of signals in the wireless environment, users cannot receive information from adequate anchors, which leads to the localization quality being undependable and unacceptable. To solve this problem, we propose exploiting the localized users as the mobile anchors for localizing the nonlocalized users. These mobile users cooperate as a whole group to improve the localization accuracy. Moreover, to decrease the communication cost among users, an algorithm for electing mobile anchors is designed, with several provable properties. This electing algorithm is a distributed method, without advanced negotiations among mobile users. In addition, for the scenarios with a crowd of users, we divide the users into different groups according to their distance information, which can ensure that only the dependable anchors are used for the localization. Extensive experimental results demonstrate that the localization dependability can be improved obviously. In terms of localization probability, our method outperforms the traditional fixed anchors-based method by approximately 70% with a small increment of communication cost (about 30%), and outperforms the method in which all the localized users are exploited as mobile anchors by about 50% with about a 70% decrement of communication cost.
Resource-Cost-Aware Fault-Tolerant Design Methodology for End-to-End Functional Safety Computation on Automotive Cyber-Physical Systems

Automotive functional safety standard ISO 26262 aims to avoid unreasonable risks due to systematic failures and random hardware failures caused by malfunctioning behavior. Automotive functions involve distributed end-to-end computation in automotive cyber-physical systems (ACPSs). The automotive industry is highly cost-sensitive to the mass market. This study presents a resource-cost-aware fault-tolerant design methodology for end-to-end functional safety computation on ACPSs. The proposed design methodology involves early functional safety requirement verification and late resource cost design optimization. We first propose the functional safety requirement verification (FSRV) method to verify the functional safety requirement consisting of reliability and response time requirements of the distributed automotive function during the early design phase. We then propose the resource-cost-aware fault-tolerant optimization (RCFO) method to reduce the resource cost while satisfying the functional safety requirement of the function during the late design phase. Finally, we perform experiments with real-life automotive and synthetic automotive functions. Findings reveal that the proposed RCFO and VFSR methods demonstrate satisfactory resource cost reduction compared with other methods while satisfying the functional safety requirement.
ZnO Nanowire Networks as Photoanode Model Systems for Photoelectrochemical Applications

In this work, the fabrication of zinc oxide (ZnO) nanowire networks is presented. By combining ion-track technology, electrochemical deposition, and atomic layer deposition, hierarchical and self-supporting three-dimensional (3D) networks of pure ZnO- and TiO2-coated ZnO nanowires were synthesized. Analysis by means of high-resolution transmission electron microscopy revealed a highly crystalline structure of the electrodeposited ZnO wires and the anatase phase of the TiO2 coating. In photoelectrochemical measurements, the ZnO and ZnO/TiO2 nanowire networks, used as anodes, generated higher photocurrents compared to those produced by their film counterparts. The ZnO/TiO2 nanowire network exhibited the highest photocurrents. However, the protection by the TiO2 coatings against chemical corrosion still needs improvement. The one-dimensionality of the nanowires and the large electrolyte-accessible area make these 3D networks promising photoelectrodes, due to the improved transport properties of photogenerated charge carriers and faster redox reactions at the surface. Moreover, they can find further applications in e.g., sensing, catalytical, and piezoelectric devices.
A comparison of the clinical courses of type 2 diabetic patients whose basal insulin preparation was replaced from insulin glargine 100 units/mL to insulin glargine biosimilar or 300 units/mL: a propensity score-matched observation study

Abstract Objective: We compared the clinical course of type 2 diabetic patients whose basal insulin preparations were replaced from insulin glargine (IGlar) 100 units/mL (U100) to IGlar biosimilar or IGlar 300 units/mL (U300). Methods: After propensity score matching, 34 patients whose basal insulin preparation was switched from IGlar U100 to IGlar biosimilar and 102 switched to IGlar U300 were observed for 6 months. Results: The HbA1c level and body weight did not change significantly after the replacement in the IGlar biosimilar or IGlar U300 groups. In the IGlar biosimilar group, the frequency of subjects who experienced hypoglycemia after the replacement (12%) was not different from before (12%). However, the frequency was significantly lower after the replacement (2%) than before (13%) in the IGlar U300 group. The change in the HbA1c level after the replacement showed a significant association with the HbA1c level at the baseline but not with the kind of IGlar. Hypoglycemia was frequently observed in subjects who had experienced hypoglycemia before the replacement. Conclusions: IGlar biosimilar and IGlar U300 induced similar HbA1c and body weight changes among type 2 diabetic patients. IGlar biosimilar is a suitable option for patients with a low risk for hypoglycemia.
Comparative In Vitro and In Silico Analysis of the Selectivity of Indirubin as a Human Ah Receptor Agonist

The aryl hydrocarbon receptor (AhR) is a ligand-dependent transcription factor that modulates gene expression following its binding and activation by structurally diverse chemicals. Species differences in AhR functionality have been observed, with the mouse AhR (mAhR) and human AhR (hAhR) exhibiting significant differences in ligand binding, coactivator recruitment, gene expression and response. While the AhR agonist indirubin (IR) is a more potent activator of hAhR-dependent gene expression than the prototypical ligand 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD), it is a significantly less potent activator of the mAhR. DNA binding analysis confirmed the greater potency/efficacy of IR in stimulating transformation/DNA binding of the hAhR in vitro and domain-swapping experiments demonstrated that the enhanced response to IR was primarily due to the hAhR ligand binding domain (LBD). Site-directed mutagenesis and functional analysis studies revealed that mutation of H326 and A349 in the mAhR LBD to the corresponding residues in the hAhR LBD significantly increased the potency of IR. Since these mutations had no significant effect on ligand binding, these residues likely contribute to an enhanced efficiency of transformation/DNA binding by IR-bound hAhR. Molecular docking to mAhR LBD homology models further elucidated the different roles of the A375V mutation in TCDD and IR binding, as revealed by [3H]TCDD competitive binding results. These results demonstrate the differential binding of structurally diverse ligands within the LBD of a given AhR and confirm that amino acid differences within the LBD of AhRs contribute to significant species differences in ligand response.
Presenilin 1 Regulates NF-κB Activation via Association with Breakpoint Cluster Region and Casein Kinase II

We recently reported that NF-κB–mediated inflammation caused by breakpoint cluster region (BCR) is dependent on the α subunit of casein kinase II (CK2α) complex. In the current study, we demonstrate that presenilin 1 (Psen1), which is a catalytic component of the γ-secretase complex and the mutations of which are known to cause familial Alzheimer disease, acts as a scaffold of the BCR–CK2α–p65 complex to induce NF-κB activation. Indeed, Psen1 deficiency in mouse endothelial cells showed a significant reduction of NF-κB p65 recruitment to target gene promoters. Conversely, Psen1 overexpression enhanced reporter activation under NF-κB responsive elements and IL-6 promoter. Furthermore, the transcription of NF-κB target genes was not inhibited by a γ-secretase inhibitor, suggesting that Psen1 regulates NF-κB activation in a manner independent of γ-secretase activity. Mechanistically, Psen1 associated with the BCR–CK2α complex, which is required for phosphorylation of p65 at serine 529. Consistently, TNF-α–induced phosphorylation of p65 at serine 529 was significantly decreased in Psen1-deficient cells. The association of the BCR–CK2α–p65 complex was perturbed in the absence of Psen1. These results suggest that Psen1 functions as a scaffold of the BCR–CK2α–p65 complex and that this signaling cascade could be a novel therapeutic target for various chronic inflammation conditions, including those in Alzheimer disease.
Electrically tunable optical properties of few-layer black arsenic phosphorus

Black arsenic phosphorus (b-AsP) is a promising two-dimensional material for various optoelectronic applications, bridging the wavelength gap between two-dimensional molybdenum disulfide and graphene. In particular, it has intriguing potential in photodetectors and great advantages in the mid-infrared field. However, its optoelectronic modulation has yet to be elucidated, which requires a fundamental understanding of its field-effect optical modulation. Here, we report the measurements of the lower-energy infrared anisotropic optical response of thin b-AsP under different electrical gating. We reveal that in addition to band edge absorption, amplitude modulation of sub-band absorption up to ten percent is also obtained in reflection extinction. These in-gap absorptions are attributed to spin–orbital coupling and free carrier absorption. Our results suggest the important potential for use of b-AsP in mid-infrared optoelectronic modulator applications.
Countermovement Jump Analysis Using Different Portable Devices: Implications for Field Testing

The aim of this study was to analyze the concurrent validity, test–retest reliability, and capacity to detect changes of four different portable devices used to measure a wide range of neuromuscular parameters derived from countermovement jump (CMJ). An accelerometric device (Myotest), a jump mat (Ergojump), an optical device (Optojump), and a smartphone app (MyJump) were simultaneously examined for concurrent validity against gold-standard measures (motion-capture system and a force platform). Twenty-two CMJ-derived variables were collected from 15 healthy male subjects (n = 60 CMJs). Contraction time (CT) and eccentric duration (EccD) measurements obtained from the Myotest were moderately to largely associated with and not different from force platform measurements (r = 0.31 to 0.64, ES = 0.11 to 0.18) and showed moderate test-retest reliability (intraclass correlation coefficient (ICC) = 0.92 to 0.97, coefficient of variation (CV) = 3.8 to 8.0%). Flight time (FT) and jump height (JH) from Ergojump, Optojump, and MyJump showed moderate to strong associations with gold-standard measurements (r = 0.57 to 0.98) and good test–retest reliability (ICC = 0.54 to 0.97, CV = 1.8 to 4.2). However, all portable devices underestimated JH (ES = 1.25 to 2.75). Independent of the instrument used, the analyzed CMJ variables showed good capacity to detect changes (standard error of measurement (SEM) < smallest worthwhile change (SWC)), with the exception of rate of force and rate of power development parameters, which showed marginal capacity (SEM > SWC). The Myotest is preferable to measure temporal parameters during ground contact, whereas Ergojump, Optojump, and MyJump devices may be preferable to measure FT and JH, with the Optojump being the most accurate.
Saving Lives at Sea with UAV-assisted Wireless Networks

In this paper, we investigate traits and trade-offs of a system combining Unmanned Aerial Vehicle (UAV)s with Base Station (BS) or Cloud Radio Access Networks (C-RAN) for extending the terrestrial wireless coverage over the sea in emergency situations. Results for an over the sea deployment link budget show the trade-off between power consumption and throughput to meet the Search and Rescue targets.
Metabolic Effects of the Intracellular Regulation of Thyroid Hormone: Old Players, New Concepts

Thyroid hormones (THs) are key determinants of cellular metabolism and regulate a variety of pathways that are involved in the metabolism of carbohydrates, lipids and proteins in several target tissues. Notably, hyperthyroidism induces a hyper-metabolic state characterized by increased resting energy expenditure, reduced cholesterol levels, increased lipolysis and gluconeogenesis followed by weight loss, whereas hypothyroidism induces a hypo-metabolic state characterized by reduced energy expenditure, increased cholesterol levels, reduced lipolysis and gluconeogenesis followed by weight gain. Thyroid hormone is also a key regulator of mitochondria respiration and biogenesis. Besides mirroring systemic TH concentrations, the intracellular availability of TH is potently regulated in target cells by a mechanism of activation/inactivation catalyzed by three seleno-proteins: type 1 and type 2 iodothyronine deiodinase (D1 and D2) that convert the biologically inactive precursor thyroxine T4 into T3, and type 3 iodothyronine deiodinase (D3) that inactivates TH action. Thus, the pleiotropic effects of TH can fluctuate among tissues and strictly depend on the cell-autonomous action of the deiodinases. Here we review the mechanisms of TH action that mediate metabolic regulation. This review traces the critical impact of peripheral regulation of TH by the deiodinases on the pathways that regulate energy metabolism and the balance among energy intake, expenditure and storage in specific target tissues.
Early Fault Diagnosis for Planetary Gearbox Based Wavelet Packet Energy and Modulation Signal Bispectrum Analysis

The planetary gearbox is at the heart of most rotating machinery. The premature failure and subsequent downtime of a planetary gearbox not only seriously affects the reliability and safety of the entire rotating machinery but also results in severe accidents and economic losses in industrial applications. It is an important and challenging task to accurately detect failures in a planetary gearbox at an early stage to ensure the safety and reliability of the mechanical transmission system. In this paper, a novel method based on wavelet packet energy (WPE) and modulation signal bispectrum (MSB) analysis is proposed for planetary gearbox early fault diagnostics. First, the vibration signal is decomposed into different time-frequency subspaces using wavelet packet decomposition (WPD). The WPE is calculated in each time-frequency subspace. Secondly, the relatively high energy vectors are selected from a WPE matrix to obtain a reconstructed signal. The reconstructed signal is then subjected to MSB analysis to obtain the fault characteristic frequency for fault diagnosis of the planetary gearbox. The validity of the proposed method is carried out through analyzing the vibration signals of the test planetary gearbox in two fault cases. One fault is a chipped sun gear tooth and the other is an inner-race fault in the planet gear bearing. The results show that the proposed method is feasible and effective for early fault diagnosis in planetary gearboxes.
Opinion Forming in Erdös-Rényi Random Graph and Expanders

Assume for a graph G=(V,E) and an initial configuration, where each node is blue or red, in each discrete-time round all nodes simultaneously update their color to the most frequent color in their neighborhood and a node keeps its color in case of a tie. We study the behavior of this basic process, which is called majority model, on the Erdos-Renyi random graph G_{n,p} and regular expanders. First we consider the behavior of the majority model on G_{n,p} with an initial random configuration, where each node is blue independently with probability p_b and red otherwise. It is shown that in this setting the process goes through a phase transition at the connectivity threshold, namely (log n)/n. Furthermore, we say a graph G is lambda-expander if the second-largest absolute eigenvalue of its adjacency matrix is lambda. We prove that for a Delta-regular lambda-expander graph if lambda/Delta is sufficiently small, then the majority model by starting from (1/2-delta)n blue nodes (for an arbitrarily small constant delta>0) results in fully red configuration in sub-logarithmically many rounds. Roughly speaking, this means the majority model is an "efficient" and "fast" density classifier on regular expanders. As a by-product of our results, we show regular Ramanujan graphs are asymptotically optimally immune, that is for an n-node Delta-regular Ramanujan graph if the initial number of blue nodes is s 0. This settles an open problem by Peleg [Peleg, 2014].
Mining specifications of malicious behavior

Malware detectors require a specification of malicious behavior. Typically, these specifications are manually constructed by investigating known malware. We present an automatic technique to overcome this laborious manual process. Our technique derives such a specification by comparing the execution behavior of a known malware against the execution behaviors of a set of benign programs. In other words, we mine the malicious behavior present in a known malware that is not present in a set of benign programs. The output of our algorithm can be used by malware detectors to detect malware variants. Since our algorithm provides a succinct description of malicious behavior present in a malware, it can also be used by security analysts for understanding the malware. We have implemented a prototype based on our algorithm and tested it on several malware programs. Experimental results obtained from our prototype indicate that our algorithm is effective in extracting malicious behaviors that can be used to detect malware variants.
An Embedding-Based Approach for Oral Disease Diagnosis Prediction from Electronic Medical Records

This paper reports a diagnosis prediction study from electronic medical records (EMRs) of oral diseases. We propose to learn continuous vector representations (embeddings) of symptoms and diagnoses through training neural networks. To the best of our knowledge, this is the first attempt to apply word embedding to predicting diagnoses from stomatologic EMR data. Evaluations on real-world EMR datasets from eleven departments in Peking University School and Hospital Stomatology demonstrate that our model has produced promising results in diagnosis prediction. Compared with classic machine learning algorithms, our model captures the correlation between symptoms and diagnoses, which leads to the best performance in terms of accuracy, precision, recall, F-score, and Cohen's kappa statistic. Visualizations illustrate the quality of the symptom and diagnosis embeddings generated by our approach.
ID4IDS Methodology: Toward Inclusive Design for Individuals with Down Syndrome

Over the last couple of years, our research group has partnered with a local NGO aiming at improving expressive language, and reading and writing skills of children with Down Syndrome (DS) from low-income families in Mexico. Thus far, we have struggled to find an adequate design methodology that can incorporate parents, therapists, and children with DS. In this paper, we present the ID4IDS Methodology, an inclusive design methodology, which we expect will help provide adequate, technology-driven prototypes for supporting children with DS, their parents, and therapists.
Antiproliferative Activity of Non-Calcemic Vitamin D Analogs on Human Melanoma Lines in Relation to VDR and PDIA3 Receptors

Vitamin D is a precursor for secosteroidal hormones, which demonstrate pleiotropic biological activities, including the regulation of growth and the differentiation of normal and malignant cells. Our previous studies have indicated that the inhibition of melanoma proliferation by a short side-chain, low calcemic analog of vitamin D—21(OH)pD is not fully dependent on the expression of vitamin D receptor (VDR). We have examined the effects of classic vitamin D metabolites, 1,25(OH)2D3 and 25(OH)D3, and two low calcemic vitamin D analogs, (21(OH)pD and calcipotriol), on proliferation, mRNA expression and vitamin D receptor (VDR) translocation in three human melanoma cell lines: WM98, A375 and SK-MEL-188b (subline b of SK-MEL-188, which lost responsiveness to 1,25(OH)2D3 and became VDR−/−CYP27B1−/−). All tested compounds efficiently inhibited the proliferation of WM98 and A375 melanoma cells except SK-MEL-188b, in which only the short side-chain vitamin D analog—21(OH)pD was effective. Overall, 21(OH)pD was the most potent compound in all three melanoma cell lines in the study. The lack of responsiveness of SK-MEL-188b to 1,25(OH)2D3, 25(OH)D3 and calcipotriol is explained by a lack of characteristic transcripts for the VDR, its splicing variants as well as for vitamin D-activating enzyme CYP27B1. On the other hand, the expression of VDR and its splicing variants and other vitamin D related genes (RXR, PDIA3, CYP3A4, CYP2R1, CYP27B1, CYP24A1 and CYP11A1) was detected in WM98 and A375 melanomas with the transcript levels being modulated by vitamin D analogs. The expression of VDR isoforms in WM98 cells was stimulated strongly by calcipotriol. The antiproliferative activities of 21(OH)pD appear not to require VDR translocation to the nucleus, which explains the high efficacy of this noncalcemic pregnacalciferol analog in SK-MEL-188b melanoma, that is, VDR−/−. Therefore, we propose that 21(OH)pD is a good candidate for melanoma therapy, although the mechanism of its action remains to be defined.
High-Performance Generalized Tensor Operations

The efficiency of tensor contraction is of great importance. Compilers cannot optimize it well enough to come close to the performance of expert-tuned implementations. All existing approaches that provide competitive performance require optimized external code. We introduce a compiler optimization that reaches the performance of optimized BLAS libraries without the need for an external implementation or automatic tuning. Our approach provides competitive performance across hardware architectures and can be generalized to deliver the same benefits for algebraic path problems. By making fast linear algebra kernels available to everyone, we expect productivity increases when optimized libraries are not available.