Miracle-dz/UniFAR-FTUs huggingface dataset:
Visualizing Neural Network Developing Perturbation Theory

Motivated by the question whether the empirical fitting of data by neural networks can yield the same structure of physical laws, we apply neural networks to a quantum-mechanical two-body scattering problem with short-range potentials---a problem that by itself plays an important role in many branches of physics. After training, the neural network can accurately predict $s$-wave scattering length, which governs the low-energy scattering physics. By visualizing the neural network, we show that it develops perturbation theory order by order when the potential depth increases, without solving the Schr\"odinger equation or obtaining the wave function explicitly. The result provides an important benchmark to the machine-assisted physics research or even automated machine learning physics laws.
A fiber-coupled diamond quantum nanophotonic interface

Color centers in diamond provide a promising platform for quantum optics in the solid state, with coherent optical transitions and long-lived electron and nuclear spins. Building upon recent demonstrations of nanophotonic waveguides and optical cavities in single-crystal diamond, we now demonstrate on-chip diamond nanophotonics with a high efficiency fiber-optical interface, achieving > 90% power coupling at visible wavelengths. We use this approach to demonstrate a bright source of narrowband single photons, based on a silicon-vacancy color center embedded within a waveguide-coupled diamond photonic crystal cavity. Our fiber-coupled diamond quantum nanophotonic interface results in a high flux of coherent single photons into a single mode fiber, enabling new possibilities for realizing quantum networks that interface multiple emitters, both on-chip and separated by long distances.
"Thinking Quantum": Lectures on Quantum Theory for High-School Students

We present a conceptually clear introduction to quantum theory at a level suitable for high-school students attending the International Summer School for Young Physicists (ISSYP) at Perimeter Institute. It is entirely self-contained and no university-level background knowledge is required. The lectures we given over four days, four hours each day. On the first day the students were given all the relevant mathematical background from linear algebra and probability theory. On the second day, we used the acquired mathematical tools to define the full quantum theory in the case of a finite Hilbert space and discuss some consequences such as entanglement, Bell's theorem and the uncertainty principle. Finally, in days three and four we presented an overview of advanced topics related to infinite-dimensional Hilbert spaces, including canonical and path integral quantization, the quantum harmonic oscillator, quantum field theory, the Standard Model, and quantum gravity.
Topic mining of tourist attractions based on a seasonal context aware LDA model

With the rise of personalized travel recommendation in recent years, automatic analysis and summary of the tourist attraction is of great importance in decision making for both tourists and tour operators. To this end, many probabilistic topic models have been proposed for feature extraction of tourist attraction. However, existing state-of-the-art probabilistic topic models overlook the fact that tourist attractions tend to have distinct characteristics with respect to specific seasonal context. In this article, we contribute the innovative idea of using seasonal contextual information to refine the characteristics of tourist attractions. Along this line, we first propose STLDA, a season topic model based on latent Dirichlet allocation which can capture meaningful topics corresponding to various seasonal contexts for each attraction. Then, an inference algorithm using Gibbs sampling is put forward to learn the model parameters of our proposed model. In order to verify the effectiveness of STLDA model, we present a detailed experimental study using collected real-world textual data of tourist attractions. The experimental analysis results show that the superiority of STLDA over the basic LDA model in providing a representative and comprehensive summarization related to each tourist attraction. More importantly, it has great significance for improving the level of personalized attraction recommendation.
High Tolerance of the Pacific Oyster (Crassostrea gigas, Thunberg) to Low Temperatures

ABSTRACT As an intertidal species, the Pacific oyster (Crassostrea gigas, Thunberg) is very tolerant to varying abiotic conditions. The temperature range for survival has, however, not been fully evaluated. Most notably, information about cold tolerance of the species is missing. As a first step toward acquiring a better understanding of the species' cold tolerance, the aim of this study was to measure mortality of groups of Pacific oysters after exposure to simulated winter conditions (-22°C) for 24, 48, and 72 h. Such conditions are not very different from what can be experienced in nature during wintertime in Scandinavia. The Pacific oyster was found to be very tolerant to low temperatures with, in general, 50% survival after 24 h. Thermal acclimatization and premature adjustment to winter conditions allowing for improved survival after cold treatment were also observed.
An examination of the heterogeneity in the pattern and association between rates of change in grip strength and global cognition in late life. A multivariate growth mixture modelling approach

Background previous research has demonstrated how older adults exhibit different patterns of change in cognitive and physical functioning, suggesting differences in the underlying causal processes. Objective to (i) identify subgroups of older adults that best account for different patterns of longitudinal change in performance on global cognition and grip strength, (ii) examine the interrelationship between global cognition and grip strength trajectories within these subgroups and (iii) identify demographic and health-related markers of class membership. Methods multivariate growth mixture models (GMM) were used to identify groups of individuals with similar developmental trajectories of muscle strength measured by grip strength, and global cognition measured by Mini Mental State Examination (MMSE). Results GMM analyses indicated high, moderate and low functioning groups. Individuals in the high and moderate classes demonstrated better cognitive and physical functioning at the start of the study and less decline than those in the low functioning group. Notably, cognitive performance was related to physical functioning at study entry only among individuals in the low functioning group. Conclusion the study demonstrates the applicability of the multivariate GMM to achieve a better understanding of the heterogeneity of various aging related processes.
Phylogenetic Status of the Turkish Red Fox (Vulpes vulpes) based on Partial Sequences of the Mitochondrial Cytochrome b Gene

Genetic diversity and multiple mitochondrial phylogroups of the red fox have been revealed from scattered locations in previous studies. There is a still lack of information about the genetic diversity and phylogeographic structure of the red fox in Asia Minor. We investigated the genetic diversity in the Turkish red fox using a part of the cytochrome b mitochondrial gene (375 bp), and attempted to evaluate the phylogeographic structure in various geographic ranges of the species with the use of sequences available from the GenBank from various geographic origins and our data. Bayesian and Network analyses of the cytochrome b sequences from Turkey and GenBank suggested that the red fox is divided into four main phylogroups. They are grouped accordingly: Group 1 (SW Anatolia, Turkey and Hokkaido, Japan), Group 2 (Eurasia and North America), Group 3 (only North America), and Group 4 (Vietnam). The majority of Turkish haplotypes grouped with those of Eurasia. Despite the great distance between the localities, two haplotypes from SW Anatolia, Turkey grouped with previously reported haplotypes from Hokkaido, Japan. The present study shows that the Turkish red fox is nested within two main phylogroups and exhibits a high genetic diversity.
Genetic unrelatedness of co-occurring pancreatic adenocarcinomas and IPMNs challenges current views of clinical management

Intraductal papillary mucinous neoplasms (IPMNs) represent the most common cystic preinvasive lesion in the pancreas, which can progress to invasive pancreatic ductal adenocarcinoma (PDAC). Patients with radiological findings consistent with IPMN are strictly monitored with imaging techniques, and surgical resection is recommended in case of clinical and/or radiological ‘high-risk stigmata’ or ‘worrisome features’. 1 2 Recent research has suggested the potential role of molecular analysis of cyst fluid to discriminate IPMNs from other types of pancreatic cysts and from invasive lesions.3–6 Notably, recent evidences pointed out the presence of a so-called ‘field effect’ of pancreatic carcinogenesis. This concept indicates the occurrence of seemingly unrelated patches of non-neoplastic cells that may be partly shared with a tumour lesion.7 Therefore, within the pancreas not only a preinvasive lesion is at risk of progression to malignancy but independent preinvasive and invasive lesions may develop as well. In other words, the ‘field effect’ might separately predispose to both preinvasive and invasive lesions. Along this line, Pea and colleagues, sequenced DNA from a cohort of IPMNs and PDAC from the same patients, showing that a significant proportion of the recurrent cancers was likely independent from the primary resected IPMNs.8 The existence of a field-effect carcinogenesis in the pancreas has also been suggested by the work of Shindo and colleagues, who reported that germ line mutations in PDAC susceptibility genes are commonly identified in patients with pancreatic cancer, even when a family history of cancer is lacking.9 Some of these mutations …
Biological and physico-chemical properties of new root canal sealers

Background The purpose of the present study was to compare the biological and the physico-chemical properties of bioceramic-based root canal sealers, calcium hydroxide-based, MTA-based and epoxy resin-based root canal sealers. Material and Methods Two bioceramic-based sealers, one calcium hydroxide-based sealer, one MTA-based sealer and two epoxy resin-based sealers were tested. Results EasySeal and MTA Fillapex showed severe citotoxic activity, AH Plus and SealapexTM moderate cytotoxicity, BioRoot™ RCS and TotalFill BC Sealer were both cytocompatible. Except for TotalFill BC Sealer, all root canal sealers caused inhibition zones when tested with E. faecalis. The highest inhibition zone was observed for EasySeal, followed by AH Plus. BioRoot™ RCS, SealapexTM and MTA Fillapex showed the lowest inhibition zone. All the tested materials showed different degree of antibacterial activity by using direct contact test (DCT). The highest values were observed for BioRoot™ RCS, TotalFill BC Sealer and EasySeal, followed by MTA Fillapex and SealapexTM. Except for BioRoot RCS and TotalFill BC Sealer, all the root canal sealers fulfilled the requirements of the ISO 6876 standard, demonstrating a weight loss less than 3%. Bioroot RCS, TotalFill BC Sealer and SealapexTM exhibited high alkaline pH with an increase both for BioRoot™ RCS and TotalFill BC Sealer after 24 hours. Conclusions The new bioceramic-based sealers showed acceptable physico-chemical properties, but BioRoot™ RCS and TotalFill BC Sealer seems to be too soluble, not respecting ISO 6876 requirements. Key words:Antibacterial activity, cytoxicity, pH, root canal sealers, solubility.
Web Canvas Testing Through Visual Inference

Canvas elements are one of the major web technologies for creating high-performance graphics and visualizations in the browser. The canvas provides APIs for directly painting on the screen, but does not have a DOM state. As such, common web testing techniques that rely on the DOM cannot be applied to canvas elements. Furthermore, there has been little to no research in the literature for testing canvas elements. We propose an automated approach for testing canvas elements and their properties. Our approach performs a visual analysis of the screenshots of canvas elements and infers visual objects, their attributes, and their hierarchical relationships present on the canvas. Each inferred object is then represented as an augmented element inside the canvas element on the DOM tree. Finally, tests are generated from the augmented canvas DOM with assertions that check the inferred objects. We implement this approach in a tool, CanvaSure, and evaluate its accuracy and effectiveness for testing canvas-based applications. Our evaluation results show that CanvaSure has an accuracy of 91% for visually inferring the contents of the canvas, and is capable of correctly detecting 93% of injected visual faults on canvas applications.
An Online Water Army Detection Method Based on Network Hot Events

With the advent of the mobile Internet era, large numbers of online water army active in the network are driven by interests. Spread network rumors and false information against network incidents, seriously disturbing the normal network order and affecting social harmony and stability. We analyzed the rumor publishing, dissemination and trace back process in social platforms. This paper proposes a query algorithm for similarity of text content. Based on the principle of rumor propagation, emotion analysis of texts and the characteristics of network public opinions, this paper studies the evolvement of network hot events over time, and proposes a set of detection methods based on current network events. The results show that the analysis of the rumors of the Online water army can reveal the evolving trend of network events well. Our method can achieve an accuracy of 93% in the Sina Weibo, which is of considerable reference value for realizing the automatic discovery of network public opinion hot spots and follow-up intelligent tracking.
A frugal approach to reduce RCU grace period overhead

Grace period computation is a core part of the Read-Copy-Update (RCU) synchronization technique that determines the safe time to reclaim the deferred objects' memory. We first show that the eager grace period computation employed in the Linux kernel is appropriate only for enterprise workloads such as web and database servers where a large amount of reclaimable memory awaits the completion of a grace period. However, such memory is negligible in High-Performance Computing (HPC) and mostly idling environments due to limited OS kernel activity. Hence an eager approach is not only futile but also detrimental as the CPU cycles consumed to compute a grace period leads to jitter in HPC and frequent CPU wake-ups in idle environments. We design frugal grace periods, an economical grace period computation for non-enterprise environments that consume fewer CPU cycles. In addition, we reduce the number of grace periods either by using heuristics or by letting the memory allocator to explicitly request for a grace period only when it is running out of free objects. Our implementation in the Linux kernel reduces the number of grace periods by 68% to 99%, reduces the CPU time consumed by grace periods by 39% to 99%, improves the throughput by up to 28% for NAS parallel benchmarks and increases the CPU time spent in low power states by 2.4x when the system is idle.
Awake Craniotomy with Noninvasive Brain Mapping by 3-Tesla Functional Magnetic Resonance Imaging for Excision of Low-grade Glioma: A Case of a Young Patient from Pakistan

The past few years have seen increasing support for gross total resection in the management of low-grade gliomas (LGGs), with a greater extent of resection correlated with better overall survival, progression-free survival, and time to malignant transformation. There is consistent evidence in literature supporting extent of safe resection as a good prognostic indicator as well as positively affecting seizure control, symptomatic relief in pressure symptoms, and longer progression-free and total survival. The operative goal in most LGG cases is to maximize the extent of resection for these benefits while avoiding postoperative neurologic deficits. Several advanced invasive and noninvasive surgical techniques such as intraoperative magnetic resonance imaging (MRI), fluorescence-guided surgery, intraoperative functional pathway mapping, and neuronavigation have been developed in an attempt to better achieve maximal safe resection. We present a case of LGG in a young patient with a 5-year history of refractory seizures and gradual onset walking difficulty. Serial MRI brain scans revealed a progressive increase in right frontal tumor size with substantial edema and parafalcine herniation. Noninvasive brain mapping by functional MRI (fMRI) and sleep-awake-sleep type of anesthesia with endotracheal tube insertion was utilized during an awake craniotomy. Histopathology confirmed a Grade II oligodendroglioma, and genetic analysis revealed no codeletion at 1p/19q. Neurological improvement was remarkable in terms of immediate motor improvement, and the patient remained completely seizure free on a single antiepileptic drug. There is no radiologic or clinical evidence of recurrence 6 months postoperatively. This is the first published report of an awake craniotomy for LGG in Pakistan. The contemporary concept of supratotal resection in LGGs advocates generous functional resection even beyond MRI findings rather than mere excision of oncological boundaries. This relatively aggressive approach is only possible with an awake craniotomy, which ensures preservation of functional status and thus less postoperative morbidity and better outcomes. Noninvasive mapping for intracranial space-occupying lesions, including fMRI and blood-oxygen-level dependent (BOLD) imaging modality, is an essential tool in a resource-limited setting such as Pakistan.
Effect of filler on the bitumen-aggregate adhesion in asphalt mix

ABSTRACT The loss of adhesion is one of the primary mechanisms of physical distress in asphalt mixes since it negatively affects the durability of asphalt mix. The effect of filler on this mechanism was explored by analyzing active and passive adhesions between the aggregates and the bitumen that constitute asphalt mix. As part of the analysis, the measurement of mixing times and Boiling Water Tests were conducted. Five types of fillers of different sources, constituting of conventional (natural stone dust) and waste fillers (glass powder from glass industry, bauxite residue from aluminum industry, Kota stone dust from dimension stone industry and copper tailings from mining industry) were added at variable compositions (4, 5.5, 7 and 8.5% by weight of aggregates) in mixes to generalise the conclusions. The statistical analysis of results confirmed that type of filler and their quantity in asphalt mixes, significantly affect both active and passive adhesion. The results also indicated that use of calcium-based fillers (natural stone dust and Kota stone dust) result in significant improvement in both adhesions. Whereas, use of silica-based glass powder filler results in the worst active and passive adhesions and should be used judiciously.
Optimization Algorithm Improvement of Association Rule Mining Based on Particle Swarm Optimization

The frequent itemsets in the presence of large data categories lead to disturbance, accuracy of data mining association rules feature is not good, in order to improve the extraction performance of associated features in data mining, presents an association rule mining algorithm based on particle swarm algorithm, attribute object template data using the constrained concept lattice structure for mining model construction set and the constrained concept lattice structure Hasse diagram design using depth first traversal mechanism of transaction database, with frequent item list for indexing, search data clustering using particle swarm algorithm for association rules of cable, to achieve large data clustering using fuzzy C means clustering algorithm can meet the classification attribute pattern correlation dimension, The minimum support and the minimum confidence are given as the thresholds to find the valuable association rules. The simulation results show that the method of mining the frequent itemsets can accurately reflect the characteristics of big data fusion clustering association rules mining, the convergence process is better, it can effectively extract the user interest all constrained association rules.
Penetration Into Concrete Targets By A Hard Projectile

Two dimensionless numbers, termed impact function I and geometry function N, are introduced as dominant parameters to control the penetration depth into concrete targets subjected to a hard projectile impact [1,2]. A definition of nose shape factor is defined quantitatively to eliminate the vagueness of the nose shape deftitions in empirical formulae. A unified formula on penetration depth into concrete target, proposed based on dimensional analysis and dynamic cavity expansion model in [1,2] is applicable for a wide range of impact velocities, nose shapes and concrete strengths and reinforcements, The validity of the proposed penetration formula is verified through comparison with all major empirical formulae, e.g., modified NDRC, ACE, LJKAEA, and experimental results. There exists an upper limit of the rigid projectile assumption, beyond which, the penetration is dominated by semi-hydrodynamic regime. The proposed formula can also be extended to metallic and earth targets.
Comparing Reentrant Drivers Predicted by Image-Based Computational Modeling and Mapped by Electrocardiographic Imaging in Persistent Atrial Fibrillation

Electrocardiographic mapping (ECGI) detects reentrant drivers (RDs) that perpetuate arrhythmia in persistent AF (PsAF). Patient-specific computational models derived from late gadolinium-enhanced magnetic resonance imaging (LGE-MRI) identify all latent sites in the fibrotic substrate that could potentially sustain RDs, not just those manifested during mapped AF. The objective of this study was to compare RDs from simulations and ECGI (RDsim/RDECGI) and analyze implications for ablation. We considered 12 PsAF patients who underwent RDECGI ablation. For the same cohort, we simulated AF and identified RDsim sites in patient-specific models with geometry and fibrosis distribution from pre-ablation LGE-MRI. RDsim- and RDECGI-harboring regions were compared, and the extent of agreement between macroscopic locations of RDs identified by simulations and ECGI was assessed. Effects of ablating RDECGI/RDsim were analyzed. RDsim were predicted in 28 atrial regions (median [inter-quartile range (IQR)] = 3.0 [1.0; 3.0] per model). ECGI detected 42 RDECGI-harboring regions (4.0 [2.0; 5.0] per patient). The number of regions with RDsim and RDECGI per individual was not significantly correlated (R = 0.46, P = ns). The overall rate of regional agreement was fair (modified Cohen's κ0 statistic = 0.11), as expected, based on the different mechanistic underpinning of RDsim- and RDECGI. nineteen regions were found to harbor both RDsim and RDECGI, suggesting that a subset of clinically observed RDs was fibrosis-mediated. The most frequent source of differences (23/32 regions) between the two modalities was the presence of RDECGI perpetuated by mechanisms other than the fibrotic substrate. In 6/12 patients, there was at least one region where a latent RD was observed in simulations but was not manifested during clinical mapping. Ablation of fibrosis-mediated RDECGI (i.e., targets in regions that also harbored RDsim) trended toward a higher rate of positive response compared to ablation of other RDECGI targets (57 vs. 41%, P = ns). Our analysis suggests that RDs in human PsAF are at least partially fibrosis-mediated. Substrate-based ablation combining simulations with ECGI could improve outcomes.