Miracle-dz/UniFAR-FTUs huggingface dataset:
Towards Multi-Hop Homomorphic Identity-Based Proxy Re-Encryption via Branching Program

Identity-based proxy re-encryption (<inline-formula> <tex-math notation="LaTeX">$ \mathsf {IBPRE}$ </tex-math></inline-formula>) is a powerful cryptographic tool for various applications, such as access control system, secure data sharing, and secure e-mail forwarding. Most of the existing efficient <inline-formula> <tex-math notation="LaTeX">$ \mathsf {IBPRE}$ </tex-math></inline-formula> schemes are based on the Diffie–Hellman assumption, and they only focus on the single-hop construction. Based on the work of Chandran <italic>et al.</italic>’s lattice-based proxy re-encryption (<inline-formula> <tex-math notation="LaTeX">$ \mathsf {PRE}$ </tex-math></inline-formula>) scheme (PKC’14) and Yamada’s lattice-based identity-based encryption (<inline-formula> <tex-math notation="LaTeX">$ \mathsf {IBE}$ </tex-math></inline-formula>) scheme (EUROCRYPT’16), in this paper, we first show the possibility of assembling lattice-based <inline-formula> <tex-math notation="LaTeX">$ \mathsf {IBE}$ </tex-math></inline-formula> into lattice-based <inline-formula> <tex-math notation="LaTeX">$ \mathsf {PRE}$ </tex-math></inline-formula>. Then, we present the construction of a new efficient single-hop homomorphic <inline-formula> <tex-math notation="LaTeX">$ \mathsf {IBPRE}$ </tex-math></inline-formula> from learning with errors (<inline-formula> <tex-math notation="LaTeX">$ \mathsf {LWE}\text{s}$ </tex-math></inline-formula>) via key homomorphic computation. Furthermore, using branching program (<inline-formula> <tex-math notation="LaTeX">$ \mathsf {BP}$ </tex-math></inline-formula>), we obtain an efficient multi-hop <inline-formula> <tex-math notation="LaTeX">$ \mathsf {IBPRE}$ </tex-math></inline-formula> scheme. To the best of our knowledge, our scheme is the first multi-hop homomorphic <inline-formula> <tex-math notation="LaTeX">$ \mathsf {IBPRE}$ </tex-math></inline-formula> scheme via <inline-formula> <tex-math notation="LaTeX">$ \mathsf {BP}$ </tex-math></inline-formula>. Our scheme supports homomorphic evaluation and is proved secure under the decisional <inline-formula> <tex-math notation="LaTeX">$ \mathsf {LWE}$ </tex-math></inline-formula> assumption.
Learning solar flare forecasting model from magnetograms

Solar flare is one type of violent eruptions from the Sun. Its effects almost immediately arrive to the near-Earth environment, so it is crucial to forecast solar flares in space weather. So far, the physical mechanisms of solar flares are not yet clear, hence we learn a solar flare forecasting model from the historical observational magnetograms by using the deep learning method. Instead of designing the feature extractor by the solar physicist in the traditional solar flare forecasting model, the proposed forecasting model can automatically learn features from input raw data, and followed by a classifier for foretasting from the learned features. The experimental results demonstrate that the proposed model can achieve better performance of solar flare forecasting comparing to traditional solar flare forecasting models.
Training Clinicians to Deliver Group CBT to Manage Anxiety in Youth With ASD: Results of a Multisite Trial

Objective: Few guidelines are available regarding optimal training models for practitioners delivering cognitive–behavioral therapy (CBT) for anxiety in youth with autism spectrum disorder (ASD). The present study systematically compared 3 instructional conditions for delivering the Facing Your Fears program (FYF) to children with ASD and anxiety. Method: Thirty-four clinicians (Mage = 34 years; 94% women, 88% Caucasian) and an intent-to-treat sample of 91 children with ASD and anxiety (Mage = 11; 84% male 53% Caucasian) met eligibility criteria across 4 sites. A 3-group parallel design via a Latin square procedure was used to randomize 9 teams of clinicians to 1 of 3 training conditions: Manual, Workshop, Workshop-Plus. The effectiveness of instructional condition was assessed via implementation (CBT knowledge, treatment fidelity) and treatment outcomes (reductions in anxiety as measured by the Anxiety Disorders Interview Schedule-Parent (ADIS-P). Results: Clinicians in both Workshop conditions significantly increased CBT knowledge postworkshop, F(1, 18) = 19.8, p < . 001. Excellent treatment fidelity was obtained across conditions (above 89%), although clinicians in the Workshop conditions obtained significantly higher fidelity ratings and delivered FYF with greater quality than the Manual condition. Children with ASD demonstrated significant reductions in anxiety symptoms for three of the four anxiety diagnoses, with no differences noted across instructional condition. Rates of improvement were lower than those obtained in a previous controlled trial. Conclusions: Results suggest that although there may be some advantage to participating in a Workshop, clinicians in all conditions could deliver FYF with excellent fidelity and yield positive treatment outcomes. Lack of a no-treatment comparison group limits interpretation of findings.
Leukocyte telomere length-related genetic variants in ACYP2 contribute to the risk of esophageal carcinoma in Chinese Han population

Background Short leukocyte telomere length has been associated with significantly increased risk of esophageal carcinoma. A previous genome-wide association study demonstrated that ACYP2 was associated with leukocyte telomere length. However, the role of ACYP2 genetic variants on esophageal carcinoma susceptibility is still unknown. Therefore, we investigated whether ACYP2 polymorphisms have impact on the risk of esophageal carcinoma in Chinese. Materials and Methods We conducted a case-control study among 386 cases and 495 healthy controls from northwest China. 14 SNPs in ACYP2 were selected and genotyped using Sequenom MassARRAY technology. Odds ratios (OR) and 95% confidence intervals (CIs) were calculated by unconditional logistic regression adjusting for age and gender. RESULTS We found that 1.34-fold increased risk of esophageal carcinoma is associated with the rs11125529 A allele compared with the rs11125529 C allele (OR=1.29, 95%CI: 1.02-1.62, p=0.030) under the additive model, after adjusted by age and gender. We also found rs11896604 and rs17045754 loci increased the esophageal carcinoma risk under the additive model (rs11896604: OR=1.34, 95%CI: 1.03-1.76, p=0.032; rs17045754: OR=1.36, 95%CI: 1.03-1.80, p=0.028). One main linkage block was observed across the locus. This block was comprised of seven closely linked SNPs: rs1682111, rs843752, rs10439478, rs843645, rs11125529, rs843711 and rs11896604. The haplotype analysis detected that haplotype “TTCTATG” increased the risk of esophageal carcinoma (OR=1.38, 95%CI: 1.04-1.82, p=0.025). Conclusion In conclusion, ACYP2 gene may be associated with an increased risk of esophageal carcinoma in Chinese Han populations. Future studies to address the biological function of this polymorphism in the development of esophageal carcinoma are warranted.
Developmental origin of the clavicle, and its implications for the evolution of the neck and the paired appendages in vertebrates

In fish, the pectoral appendage is adjacent to the head, but during vertebrate evolution a long neck region emerged via caudal relocation of the pectoral appendage. The pectoral appendage is comprised of endochondral portions, such as the humerus and the scapula, and a dermal portion, such as the clavicle, that contributes to the shoulder girdle. In the search for clues to the mechanism of the caudal relocation of the pectoral appendage, the cell lineage of the rostral lateral plate mesoderm was analyzed in chickens. It was found that, despite the long neck region in chickens, the origin of the clavicle attached to the head mesoderm ranged between 1 and 14 somite levels. Because the pectoral limb bud and the endochondral pectoral appendage developed on 15–20 and 15–24 somite levels, respectively, the clavicle‐forming region corresponds to the embryonic neck, which suggests that the relocation would have been executed by the expansion of the source of the clavicle. The rostral portion of the clavicle‐forming region overlaps the source of the cucullaris muscle, embraces the pharyngeal arches caudally, and can be experimentally replaced with the head mesoderm to form the cucullaris muscle, which implies that the mesodermal portion could have been the head mesoderm and that the clavicle would have developed at the head/trunk boundary. The link between the head mesoderm and the presumptive clavicle appears to have been the developmental constraint needed to create the evolutionarily conserved musculoskeletal connectivities characterizing the gnathostome neck. In this sense, the dermal girdle of the ganathostomes would represent the wall of the branchial chamber into which the endochondral pectoral appendage appears to have attached since its appearance in evolution.
Persistently low lymphocyte counts after FCR therapy for chronic lymphocytic leukemia are associated with longer overall survival

Decreased absolute lymphocyte counts (ALCs) following frontline therapy for chronic lymphocytic leukemia may be associated with disease control, even in patients without evidence of minimal residual disease. We studied the prognostic significance of ALCs during the first year following treatment with fludarabine, cyclophosphamide, and rituximab (FCR).
Visualization of coronary artery calcium in dual energy chest radiography using automatic rib suppression

Coronary artery calcification (CAC) as assessed with CT calcium score is the best biomarker for predicting future cardiac events. Dual energy (DE) chest radiography offers an inexpensive, low radiation-dose alternative to CT. We have shown CAC can be visualized using non-gated, 2-shot, DE chest x-ray imaging. However, calcium signal from the ribs, superimposed on the CAC signal, can interfere with both image registration and reader detection of CAC. To improve the registration algorithm and the detectability of CAC, we created an enhanced CAC visualization algorithm with automatic rib segmentation and suppression. In this paper, we trained an active appearance model to detect the spatial location of rib in the DE bone images. Then, we suppressed the rib signal in the single kVp images using a kernel-filter based method. After the rib suppression, we used affine and non-rigid registration to align the CAC in low and high kVp image. 1800 dual energy cases were used in our experiment after data augmentation on 60 cases. We evaluated the segmentation from the rib AAM using six-fold cross validation. The average dice coefficient of the rib segmentation in the heart region is 0.92. The reduction of CAC mis-registration by the enhanced CAC registration algorithm is evaluated using both simulated and clinical images. Adding rib suppression improves the image registration significantly. Our results show that in both simulated synthetic images and clinical images, the CAC overlap improves from 0% to > 50% after rib suppression. Results suggest that CAC visualization and registration can be significantly improved using the rib suppression when rib signal confounds CAC signal in DE chest radiography.
Programmable Switch as a Parallel Computing Device

Modern switches have packet processing capacity of up to multi-tera bits per second, and they are also becoming more and more programmable. We seek to understand whether the programmability can translate packet processing capacity to computational power for parallel computing applications. In this paper, we first develop a simple mathematical model to understand the costs and overheads of data plane computation. Then we validate the the performance benefits of offloading computation to network. Using experiments on real data center network, we finnd that offloading computation to the data plane results in up to 20x speed-up for a simple Map-Reduce application. Motivated by this, we propose a parallel programming framework, p4mr, to help users efficiently program multiple switches. We successfully build and test a prototype of p4mr on a simulated testbed.
Comparison of non-negative matrix factorization and convolution kernel compensation in surface electromyograms of forearm muscles

This contribution compares performances of nonnegative matrix factorization and high-density surface electromyogram (EMG) decomposition on EMG signals recoded from forearm muscles of young healthy subjects. During the EMG measurements, subjects performed dynamic wrist extensions and flexions and universal haptic device robot was used to oppose their movements and to measure wrist kinematics and excreted muscle forces. Recoded EMG signals were independently decomposed by Convolution Kernel Compensation technique and by alternating least squares non-negative matrix factorization. The identified motor unit discharge patterns were summed into cumulative spike trains and compared with non-negative components in each measurement. The results demonstrated good match (average correlation coefficient of 0.92 ± 0.06), but several discrepancies between the identified components have also been observed. In particular, when limiting the time support of identified components to active EMG signal portions only, the average correlation coefficient dropped to 0.72 ±0.20.
Dynamic IoT management system using K-means machine learning for precision agriculture applications

Multi-media applications for use in Precision Agriculture (PA) and Smart Farming (SM) require Network Management Systems to deliver Quality of Service (QoS) end-to-end guarantees. This paper presents the second phase of the research in providing a network management system capable of delivering end-to-end QoS guarantees for Internet of Things (IOT) networks. The first phase of this work used a wireless test bed to develop a propagation model to incorporate the attenuation due to foliage in dense vegetation typically found in PA environments. The output of this propagation model will influence the decision making process in the network management system. Wireless Multimedia Sensor Networks (WMSN) operate under the umbrella of the Wireless Sensor Network (WSN) IEEE 802.15. 4 Medium Access Control (MAC) and Physical (PHY) protocol to deliver multimedia applications such as voice, video and live streaming. To operate successfully these multi-media applications have high QoS requirements. To enable these QoS requirements to be fulfilled performance metrics such as throughput, end-to-end delay and limited packet loss must be guaranteed. This next phase of the work in developing the intelligent network management system presented in this paper uses an OPNET™ simulation package to implement a modified K-Means algorithm to detect the presence of multi-media traffic. Consequently a signal informs the network management system to adopt pre-configured settings via the Personal Area Network Co-ordinator (PANC). The resulting changes implement service differentiation by manipulating the MAC layer (size of the individual GTS timeslots and duty cycle) to deliver better throughput and end-to-end delay performance. OPNET™ simulation results show that the new algorithm facilitates better performance and meets QoS requirements suitable to multimedia applications. This paper focuses on the derivation and evaluation of the performance of the K-Means algorithm. The sensory nodes are power, memory and computationally restricted. These restrictions coupled with the heterogeneous structure of the wireless network make intelligent network management systems very important if the QoS requirements are to be fulfilled. Upon detection of multimedia traffic with high QoS demands usually triggered in the aftermath of an event of particular interest e.g. security threat etc., a management system must dynamically effect change of the network configuration settings to maintain such guarantees. As real-time applications require an urgent response, the dynamic change must occur during run time automatically. This research work is novel in that it combines the output from the development of the physical layer propagation model to inform a network management system to trigger service differentiation for multimedia traffic in a PA environment.
Contrast enhancement scheme for visual saliency detection

Visual saliency detection becomes more popular research topic in the recent years because the prediction of attention finds application in object detection, object recognition and human computer interface etc. This paper presents the bottom up visual saliency detection with the help of contrast enhancement. Initially the SLIC segmentation is performed as preprocessing step. The global contrast enhancement scheme is adopted in this proposed method. The color distribution and contrast enhancement map is multiplied together to get the final saliency map. The performance metrics of Precision, Recall, f-measure, ROC, AUC are obtained to validate the results. The benchmark dataset of MSRA and ECSSD are used to evaluate the performance metric of the proposed method and state-of-methods. The experimental results demonstrate that the proposed method is computationally efficient.
Different distributions of M1 and M2 macrophages in a mouse model of laser-induced choroidal neovascularization

Choroidal neovascularization (CNV) is a serious complication of age-related macular degeneration. The aim of the present study was to investigate the expression and distribution of M1 and M2 macrophages in a laser-induced CNV adult mouse model. The mRNA expression levels of M1, M2 and pan macrophage markers, and macrophage-associated angiogenic cytokines, were determined by reverse transcription-quantitative polymerase chain reaction. Immunofluorescence studies were performed to determine the location of the macrophages. The expression levels of M1 macrophage markers increased to a greater extent compared with M2 markers in the retinal pigment epithelium (RPE)-choroid complexes following laser photocoagulation. By contrast, the expression levels of M2 macrophage markers increased primarily in the retinas. Immunofluorescence studies revealed that the increased number of cluster of differentiation (CD)206-positive cells were located primarily in the retina, whereas the CD80-positive cells were located around the site of CNVs in the RPE-choroid. In addition, the M1-associated cytokines increased to a greater extent in the RPE-choroid complexes, whereas the M2-associated cytokines were highly expressed in the retinas. These findings indicate that M1 and M2 macrophage numbers increased following CNV; however, the locations were different in this mouse model of laser-induced CNV. The results of the present study suggest that M1 macrophages have a more direct role in inhibiting the development of CNV.
Flocculation in Silica Reinforced Rubber Compounds

Abstract Flocculation plays an important role in reinforcement of silica filled rubber compounds, even if coupling agents are applied. It is well known that silica tends to flocculate during the early stages of vulcanization, when no dense rubber network has been formed yet. In the present study, flocculation was monitored by following the change in storage modulus at low strain, the so-called Payne effect, using a RPA2000 dynamic mechanical tester. The kinetic parameters: the rate constant and the activation energy of the silica flocculation were calculated according to the well-known Arrhenius equation. On basis of the value of the activation energy obtained for flocculation, it can be concluded that the silica flocculation is a purely physical phenomenon. Bound rubber measurements were also done in order to estimate the interfacial interaction layer between silica and polymer resulting from the coupling agent. The silica flocculation rate decreases with increasing interfacial interaction layer on the s.
Improving Bug Localization with an Enhanced Convolutional Neural Network

Background: Localizing buggy files automatically speeds up the process of bug fixing so as to improve the efficiency and productivity of software quality teams. There are other useful semantic information available in bug reports and source code, but are mostly underutilized by existing bug localization approaches. Aims: We propose DeepLocator, a novel deep learning based model to improve the performance of bug localization by making full use of semantic information. Method: DeepLocator is composed of an enhanced CNN (Convolutional Neural Network) proposed in this study considering bug-fixing experience, together with a new rTF-IDuF method and pretrained word2vec technique. DeepLocator is then evaluated on over 18,500 bug reports extracted from AspectJ, Eclipse, JDT, SWT and Tomcat projects. Results: The experimental results show that DeepLocator achieves 9.77% to 26.65% higher Fmeasure than the conventional CNN and 3.8% higher MAP than a state-of-the-art method HyLoc using less computation time. Conclusion: DeepLocator is capable of automatically connecting bug reports to the corresponding buggy files and successfully achieves better performance based on a deep understanding of semantics in bug reports and source code.
Identification and Regulation of Genes for Cobalamin Transport in the Cyanobacterium Synechococcus sp. Strain PCC 7002

ABSTRACT The cyanobacterium Synechococcus sp. strain PCC 7002 is a cobalamin auxotroph and utilizes this coenzyme solely for the synthesis of l-methionine by methionine synthase (MetH). Synechococcus sp. strain PCC 7002 is unable to synthesize cobalamin de novo, and because of the large size of this tetrapyrrole, an active-transport system must exist for cobalamin uptake. Surprisingly, no cobalamin transport system was identified in the initial annotation of the genome of this organism. With more sophisticated in silico prediction tools, a btuB-cpdA-btuC-btuF operon encoding components putatively required for a B12 uptake (btu) system was identified. The expression of these genes was predicted to be controlled by a cobalamin riboswitch. Global transcriptional profiling by high-throughput RNA sequencing of a cobalamin-independent form of Synechococcus sp. strain PCC 7002 grown in the absence or presence of cobalamin confirmed regulation of the btu operon by cobalamin. Pérez et al. (A. A. Pérez, Z. Liu, D. A. Rodionov, Z. Li, and D. A. Bryant, J Bacteriol 198:2743–2752, 2016, http://dx.doi.org/10.1128/JB.00475-16) developed a cobalamin-dependent yellow fluorescent protein reporter system in a Synechococcus sp. strain PCC 7002 variant that had been genetically modified to allow cobalamin-independent growth. This reporter system was exploited to validate components of the btu uptake system by assessing the ability of targeted mutants to transport cobalamin. The btuB promoter and a variant counterpart mutated in an essential element of the predicted cobalamin riboswitch were fused to a yfp reporter. The combined data indicate that the btuB-cpdA-btuF-btuC operon in this cyanobacterium is transcriptionally regulated by a cobalamin riboswitch. IMPORTANCE With a cobalamin-regulated reporter system for expression of yellow fluorescent protein, genes previously misidentified as encoding subunits of a siderophore transporter were shown to encode components of cobalamin uptake in the cyanobacterium Synechococcus sp. strain PCC 7002. This study demonstrates the importance of experimental validation of in silico predictions and provides a general scheme for in vivo verification of similar cobalamin transport systems. A putative cobalamin riboswitch was identified in Synechococcus sp. strain PCC 7002. This riboswitch acts as a potential transcriptional attenuator of the btu operon that encodes the components of the cobalamin active-transport system.