Miracle-dz/UniFAR-FTUs huggingface dataset:
Gravitational scaling in Beijing Subway Network

Recently, with the availability of various traffic datasets, human mobility has been studied in different contexts. Researchers attempt to understand the collective behaviors of human movement with respect to the spatio-temporal distribution in traffic dynamics, from which a gravitational scaling law characterizing the relation between the traffic flow, population and distance has been found. However, most studies focus on the integrated properties of gravitational scaling, neglecting its dynamical evolution during different hours of a day. Investigating the hourly traffic flow data of Beijing subway network, based on the hop-count distance of passengers, we find that the scaling exponent of the gravitational law is smaller in Beijing subway system compared to that reported in Seoul subway system. This means that traffic demand in Beijing is much stronger and less sensitive to the travel distance. Furthermore, we analyzed the temporal evolution of the scaling exponents in weekdays and weekends. Our findings may help to understand and improve the traffic congestion control in different subway systems.
A music recommendation system with consideration of personal emotion

Emotions evoked by were analyzed. An estimation of the correlation coefficient was applied to determine features of music that evoke an emotion. These features were then used to train two support vector machines (SVMs) for an individual subject to classify music that evokes happiness, anger, sadness, and peacefulness. The proposed approach can be used to classify music that evokes an emotion and to build a personal emotion-cognitive music recommendation system for an individual subject. Experiment results show the effectiveness of the proposed approach.
Therapeutic photography: enhancing patient communication

Using photography with patients to help them express concerns, investigate coping strategies and learn from their peers is known as therapeutic photography. The practice has benefits to both professionals and participants, particularly with ‘hard to reach’ populations who may feel intimidated or disempowered. Neil Gibson explains how this intervention can be structured in the health setting.
ALAR : Anonymous Location-Aided outing in Suspicious A , Ts

In many traditional mobile network scenarios, nodes establish communication on the basis of persistent public identities. However, in some hostile and suspicious MANET settings, node identities must not be exposed and node movements must be untraceable. Instead, nodes need to communicate on the basis of nothing more than their current locations. In this paper, we address some interesting issues arising in such MANETs by designing an anonymous routing framework (ALARM). It uses nodes' current locations to construct a secure MANET map. Based on the current map, each node can decide which other nodes it wants to communicate with. ALARM takes advantage of some advanced cryptographic primitives to achieve node authentication, data integrity, anonymity and untraceability (tracking resistance). It also offers resistance to certain insider attacks.
Finding Similar Texts Using U-WIN

Many researches in foreign country for finding similar texts are in progress using the semantic language resources like WordNet. However, in the domestic situation, the language resources like WordNet are still insufficient and so, researches for finding similar texts methods based on it or the methods for utilizing it are insufficient, too. Most of the previous domestic researches for finding similar texts used only the words that occur in texts. In this paper, we propose the semantic based method of finding similar texts by determining the meaning of the words, using semantic similarity measurement with U-WIN.
A Configurable Multi-Sensor Tripod he Study of Near-Bottom Ocean Processes rch

A cost effective and highl platform, dubbed Norton, has been de study of near-bottom ocean processes collapsible lightweight aluminum transported in the back of a pickaccommodated on most vessels. B form of large ship anodes bolted to t desired sensors are attached to the tr typical deployment might utilize the f · Acoustic Doppler Current Profiler directional wave data. · Marsh McBirney electromagn measurements close to the bottom, orbital burst sampling and average cu · Optical Backscatter sensors concentration. · Sector-scanning sonar to suppl Imagenex variable frequency sca integrated into a self-contained hous module, data logger and power supply Other sensors can be added as des deployed by lowering with a line fro release is used to let go of the tripod customized ‘tilt-pinger’ provides co that the tripod is upright. Recovery and/or a ground-line.
A Brief History of Microwave Cad Early Developments

I n this article we review state-of-the-art concepts of space mapping and place them contextually into the history of design optimization and modeling of microwave circuits. We formulate a generic space-mapping optimization algorithm, explain it step-by-step using a simple microstrip filter example, and then demonstrate its robustness through the fast design of an interdigital filter. Selected topics of space mapping are discussed, including implicit space mapping, gradientbased space mapping, the optimal choice of surrogate model, and tuning space mapping. We consider the application of space mapping to the modeling of microwave structures. We also discuss a software package for automated space-mapping optimization that involves both electromagnetic (EM) and circuit simulators.
Magnetic Fields at the Periphery of Ultracompact H II Regions from Carbon Recombination Line Observations

Several indirect evidences indicate a magnetic origin for the nonthermal width of spectral lines observed toward molecular clouds. In this Letter, I suggest that the origin of the nonthermal width of carbon recombination lines (CRLs) observed from photodissociation regions (PDRs) near ultracompact H II regions is magnetic and that the magnitude of the line width is an estimate of the Alfvén speed. The magnetic field strengths estimated based on this suggestion compare well with those measured toward molecular clouds with densities similar to PDR densities. I conclude that multifrequency CRL observations have the potential to form a new tool to determine the field strength near star-forming regions.
ANG Promotes Proliferation and Invasion of the Cell of Lung Squamous Carcinoma by Directly Up-Regulating HMGA2

Objective: To determine the mechanism of Angiogenin(ANG) function involved in the carcinogenesis of lung squamous cell carcinoma. Methods: 12 patients' normal tissue and cancerous tissue were collected. ANG expression in the squamous cell carcinoma of the lung was evaluated by qRT-PCR and western-blot. The regulation of ANG on proliferation, migration, invasion, and apoptosis of SK-MES-1 cells were analyzed by Cell Counting Kit-8, Transwell migration chamber, Transwell invasion chamber, and Annexin V-FITC assay, respectively. PCR array was utilized for screening potential target genes of ANG. Chromatin immunoprecipitation(ChIP) assays and luciferase assay were adopted for investigation of ANG's direct regulation on HMGA2. Results: ANG expression is increased in the squamous cell carcinoma of the lung tissue. In vitro experiments results indicated that overexpression of ANG promotes proliferation and invasion capability of SK-MES-1 cells. The candidate proliferation, migration, and invasion related ANG target gene found was HMGA2, expression levels of which were also enhanced in lung squamous cell carcinoma tissue. The direct regulation of ANG on HMGA2 was verified by ChIP and luciferase assay results. Furthermore, down-regulating HMGA2 significantly alleviated the suppression effects of ANG on proliferation, migration, and invasion of SK-MES-1 cells. Conclusions: Our data illustrated the mechanisms that ANG promoted the cell of SQCLC proliferation, migration, and invasion capacity via directly up-regulating HMGA2.
Tensor Space Model for Hypertext Representation

We investigate the basics of tensor based hypertext representation and perform experiments this novel hypertext representation model. Most documents have an inherent hierarchical structure that render the desirable use of multidimensional representations such as those offered by tensor objects. We focus on the advantages of Tensor Space Model, in which documents are represented using second-order tensors. We exploit the local-structure and neighborhood recommendation encapsulated by the proposed representation. We define the distance metric on tensor space of hypertext documents, which is a generalization of distance metric defined on vector space model. Our results provide evidence that tensor based model is very efficient for clustering and classification of hypertext documents compared to traditional vector based model.
Chloroplast DNA Haplotype Variation within and among Populations of Coreopsis grandiflora (Asteraceae)

An intraspecific chloroplast DNA (cpDNA) restriction site survey within Coreopsis grandzjlora was used to evaluate the correspondence of genetic variation with patterns of morphological differentiation and geographical separation. Eight frequent-cutting restriction enzymes were used with a sample of 273 individuals representing 14 populations from two geographical regions. Thirteen distinct cpDNA haplotypes were detected, differing by as many as 22 restriction site changes, or an estimated 0.674% nucleotide sequence divergence. The survey detected sufficient cpDNA variation for analyses of intraspecific and intrapopulational genetic structure and yielded evidence for interpopulational gene flow, a cpDNA polymorphism that transcends the species boundary, and possible cpDNA introgression. Patterns of genetic diversity do not strictly correspond to either morphological variation or geographical distribution; this may be a result of either cpDNA introgression or the maintenance of a cpDNA polymorphism through the speciation event that gave rise to C. grandiflora.
A low-offset low-voltage CMOS op amp with rail-to-rail input and output ranges

A low voltage CMOS op amp is presented. The circuit uses complementary input pairs to achieve a rail-to-rail common mode input voltage range. Special attention has been given to the reduction of the op amp's systematic offset voltage. Gain boost amplifiers are connected in a special way to provide not only an increase of the low-frequency open-loop gain but also a significant reduction of the systematic offset voltage.
vINT: Hardware-Assisted Virtual Interrupt Remapping for SMP VM with Scheduling Awareness

Symmetric Multi-Processing (SMP) virtual machine (VM), or virtual SMP for short, enables a single virtual machine to span multiple processors, thereby supporting the virtual machine to run resource-intensive applications. In addition to offering higher computing capacity, virtual SMP also offers the opportunity to alleviate the problem of unpredictable I/O responsiveness. To this end, we propose vINT (scheduling status based virtual INterrupt remapping adapTer), a scheme that leverages hardware-assisted interrupt mapping. vINT obtains high efficiency and flexibility by adding a lightweight module in virtual machine monitor (VMM) with no need of changing VMM scheduler and is transparent to guest OS. We implement the prototype in XEN 4.3. 0 and conduct evaluations with both micro-benchmarks and macro-benchmarks. The experimental results show that vINT can increase the networking throughput by 5x and can reduce the required execute time of disk I/O by 17.5%, while introducing only a light overhead.
Learning 3D Scene Synthesis from Annotated RGB‐D Images

We present a data‐driven method for synthesizing 3D indoor scenes by inserting objects progressively into an initial, possibly, empty scene. Instead of relying on few hundreds of hand‐crafted 3D scenes, we take advantage of existing large‐scale annotated RGB‐D datasets, in particular, the SUN RGB‐D database consisting of 10,000+ depth images of real scenes, to form the prior knowledge for our synthesis task. Our object insertion scheme follows a co‐occurrence model and an arrangement model, both learned from the SUN dataset. The former elects a highly probable combination of object categories along with the number of instances per category while a plausible placement is defined by the latter model. Compared to previous works on probabilistic learning for object placement, we make two contributions. First, we learn various classes of higher‐order object‐object relations including symmetry, distinct orientation, and proximity from the database. These relations effectively enable considering objects in semantically formed groups rather than by individuals. Second, while our algorithm inserts objects one at a time, it attains holistic plausibility of the whole current scene while offering controllability through progressive synthesis. We conducted several user studies to compare our scene synthesis performance to results obtained by manual synthesis, state‐of‐the‐art object placement schemes, and variations of parameter settings for the arrangement model.
Functional promoter testing using a modified lentiviral transfer vector

Purpose The importance of retinal glial cells in the maintenance of retinal health and in retinal degenerations has not been fully explored. Several groups have suggested that secretion of neurotrophic proteins from the retina's primary glial cell type, the Müller cell, holds promise for treating retinal degenerations. Tight regulation of transgene expression in Müller cells is likely to be critical to the efficacy of long-term neuroprotective therapies, due to the genetic heterogeneity and progressive nature of retinal disease. To this end, we developed a modified lentiviral (LV) transfer vector (pFTMGW) to accelerate the testing and evaluation of novel transcriptional regulatory elements. This vector facilitates identification and characterization of regulatory elements in terms of size, cell specificity and ability to control transgene expression levels. Methods A synthetic multiple cloning site (MCS) which can accept up to five directionally cloned DNA regulatory elements was inserted immediately upstream of an enhanced green fluorescent protein (eGFP) reporter. A cytomegalovirus (CMV) promoter, required for tat-independent viral packaging, is located around 2 kb upstream of the eGFP reporter and is capable of directing transgene expression. A synthetic transcription blocker (TB) was inserted to insulate the MCS/eGFP from the CMV promoter. We evaluated eGFP expression from pFTMGW and control constructs using flow cytometry and quantitative reverse transcriptase polymerase chain reaction (RT-PCR). We also tested and compared the activity and cell specificity of a computationally identified promoter fragment from the rat vimentin gene (Vim409) in transfection and lentiviral infection experiments using fluorescence microscopy. Results Transfection data, quantitative RT-PCR, and flow cytometry show that around 85% of expression from the CMV promoter was blocked by the TB element, allowing direct evaluation of expression from the Vim409 candidate promoter cloned into the MCS. Lentiviruses generated from this construct containing the Vim409 promoter (without the TB element) drove robust eGFP expression in Müller cells in vitro and in vivo. Conclusions The TB element efficiently prevented eGFP expression by the upstream CMV promoter and the novel MCS facilitated testing of an evolutionarily conserved regulatory element. Additional sites allow for combinatorial testing of additional promoter, enhancer, and/or repressor elements in various configurations. This modified LV transfer vector is an effective tool for expediting functional analysis of gene regulatory elements in Müller glia, and should prove useful for promoter analyses in other cell types and tissues.
Deep hashing learning networks

Hashing-based methods seek compact and efficient binary codes that preserve the similarity between data. For most existing hashing methods, an input (e.g. image) is first encoded as a vector of hand-crafted visual feature, followed by a hash projection and quantization step to obtain the compact binary vector. Most of hand-crafted features only encode low-level information of the input, the feature may not preserve semantic similarities of pairwise inputs. Meanwhile, the hash function learning process is independent with the feature representation, so that the feature may not be optimal for the hash projection. In this paper, we propose a supervised hashing learning method based on a well designed deep convolutional neural network, which tries to learn hashing code and compact representations of data simultaneously. Particularly, the proposed model learns binary codes by adding a compact sigmoid layer before the classifier layer. Experiments on several image data sets show that the proposed model outperforms other state-of-the-art hashing learning approaches.
Past meanings and future horizons of work mobility: Implications for Canadians and occupational science

ABSTRACT This lectureship explores how futures research might be used by occupational scientists to open up a dialogue about what people ‘will do’. Futures research offers alternative ways to explore ideas, viewpoints, schools of inquiry and knowledge that might contribute to the prevention of known, yet unsolved, occupational injustices experienced by groups of people in society. One such global injustice is the burgeoning work disparity of under- and unemployment experienced by young people. The goal of futures research methods is to create transformative spaces for thought, through multiple ways of knowing and analysis across paradigms of knowledge, to inform what groups of people or populations might do differently to achieve a better quality of life or circumstances. In this lectureship, the future of employment for young people in Canada is used as an example to introduce the potential of using Causal Layered Analysis (CLA; Inayatullah, 1998, 2004), a futures research method, in transformative thinking and inquiry into future possibilities for complex social or health issues relevant to occupational science. In general, futures research methods have a focus on the past and present. Understanding the past is explored through the meanings of work mobility, as represented in the lyrics of Canadian songs (n=183) from the early 1800s to 2014. The current challenges of work mobility, the present for young people in Canada, is explored through a learning experience of a graduate student in applying transformative thinking methods using CLA. Alternative opportunities generated through identification of a preferred future offered up insights that can be leveraged for action or policy change. The preferred future narrative may be valuable when coupled with other knowledge to support and sustain future work transitions of young Canadians navigating the contemporary world of work. For occupational science, transformative thinking can uncover new understandings about how social problems at the population level come to be and then to generate scenarios that evoke new ways or potential for doing that make ethical, empathic and human occupational sense in Canadian society.
Fold-specific substitution matrices for protein classification

MOTIVATION Methods that focus on secondary structures, such as Position Specific Scoring Matrices and Hidden Markov Models, have proved useful for assigning proteins to families. However, for assigning proteins to an attribute class within a family these methods may introduce more free parameters than are needed. There are fewer members and there is less variability among sequences within a family. We describe a method for organizing proteins in a family that exhibits up to an order of magnitude reduction in the number of parameters. The basis is the log odds ratio commonly used to measure similarity. We adapt this to characterize the sequence dissimilarities that give rise to attribute differentiation. This leads to the definition of Class Attribute Substitution Matrices (CLASSUM), a dual of the BLOSUM. RESULTS The method was applied to classify sequences hierarchically in the lambda and kappa subgroups of the immunoglobulin superfamily. Positions conferring class were identified based on the degree of amino acid variability at a position. The CLASSUM computed for these positions classified better than 90% of test data correctly compared with 35-50% for BLOSUM-62. The expected value for a random matrix is 14%. The results suggest that family-specific data-derived substitution matrices can improve the resolution of automated methods that use generic substitution matrices for searching for and classifying proteins.
Ensemble data assimilation for an eddy‐resolving ocean model of the Australian region

The Bluelink Ocean Data Assimilation System (BODAS) is an ensemble optimal interpolation system applied to a global ocean general‐circulation model with 10 km resolution around Australia. BODAS derives estimates of forecast‐error covariances (FECs) from a stationary 72‐member ensemble of intraseasonal model anomalies. The FECs are localized around each observation to reduce the negative effects of sampling error and to increase the rank of the ensemble. The FECs have characteristics that reflect the length‐scales and the anisotropy of the ocean circulation in different regions. BODAS assimilates in situ and satellite‐derived observations of temperature, salinity and sea‐level anomaly. Results from a 13‐year ocean re‐analysis demonstrate that the reanalysed fields are often in very good agreement with withheld observations, and provide a good synoptic representation of the eddy field around Australia. Copyright © 2005 Royal Meteorological Society
A Multiple Model Filter for Target Tracking with Interrupted Range Measurements

This paper considers target tracking problems where the range measurements are partially interrupted. A multiple model tracking filter is developed for this problem. By using a soft switching mechanism, the proposed filter automatically abandons the erroneous range measurements in the interrupted time intervals, and captures the remaining correct range measurements for tracking estimation. It has a simplified structure compared to the IMM filter and offers simplicity in the design. A numerical example demonstrates that the filter can maintain an effective tracking in random range measurements interruptions as well as in deterministic cases
The use of simulation for pediatric training and assessment

Purpose of review Simulation has been widely adopted as a training and assessment tool in medical education. Conventional teaching methods may be inadequate to properly train healthcare providers for rare but potentially lethal events in pediatrics such as trauma and respiratory arrest. Recent studies suggest pediatric acute care providers have limited exposure to critically ill patients and also lack the skills to manage them. Simulation has the potential to fill this educational void. This review will highlight the role of simulation as an educational and assessment tool, with a particular emphasis on retention of knowledge and skills. Recent findings Simulation is currently used as an assessment tool to provide ongoing feedback during training (formative assessment) and is gaining popularity as an adjunctive method for demonstrating competency (summative assessment). Recent literature demonstrates increased retention of knowledge and skills after simulation-based training in the areas of resuscitation, trauma, airway management, procedural training, team training, and disaster management. Summary Simulation is an effective training tool for pediatric acute care providers. Further research is necessary to develop validated performance assessment tools and demonstrate improvement in clinical outcomes after simulation training.