Miracle-dz/UniFAR-FTUs huggingface dataset:
Characterization of a Novel Intracellularly Activated Gene from Salmonella enterica Serovar Typhi

ABSTRACT A Salmonella enterica serovar Typhi gene that is selectively up-regulated upon bacterial invasion of eukaryotic cells was characterized. The open reading frame encodes a 298-amino-acid hydrophobic polypeptide (30.8 kDa), which is predicted to be an integral membrane protein with nine membrane-spanning domains. The protein is closely related (87 to 94% reliability) to different transport and permease systems. Gene expression under laboratory conditions was relatively weak; however, sevenfold induction was observed in a high-osmolarity medium (300 mM NaCl). The growth pattern in a laboratory medium of a serovar Typhi strain Ty2 derivative containing a 735-bp in-frame deletion in this gene, named gaiA (for gene activated intracellularly), was not affected. In contrast, the mutant was partially impaired in intracellular survival in murine peritoneal macrophages, as well as in human monocyte-derived macrophages. However, in the case of human macrophages, this survival defect was modest and evident only at late infection times (24 h). Despite the distinct intracellular survival kinetics displayed in macrophages of different species, the gaiA null mutant was significantly affected in its potential to trigger apoptosis in both murine and human macrophages. Provision of the gaiA gene in trans resulted in complementation of these phenotypes. Interestingly, the absence of a functional gaiA gene caused a marked attenuation in the mouse mucin model, as shown by the increase (3 orders of magnitude) in the 50% lethal dose of the mutant strain over that of the parental strain Ty2 (P ≤ 0.05). Altogether, these data indicate that the product encoded by the gaiA gene is required for triggering apoptosis and bacterial survival within murine macrophages, which is consistent with the in vivo results obtained in the mouse mucin model. However, gaiA was not required for initial intracellular survival in human cells, indicating that its role in the natural host might be more complex than is suggested by the studies performed in the murine system.
Sparse adaptive L2LP algorithms with mixture norm constraint for multi-path channel estimation

An improved sparse l2 and lp norm error criterion algorithm (L2LP) is carried out by incorporating a p-norm like penalty into the cost function of the L2LP algorithm to fully utilize the prior information of the multi-path fading selective channel. The p-norm-like penalty is split into l0- and l1-norm constraints for large and small channel response coefficients for constructing the l0- and l1-norm constrained L2LP (L0L1-L2LP) algorithm. Two different zero attractors are exerted on the large and small coefficients, respectively. Furthermore, a reweighting factor is incorporated into the L0L1-L2LP algorithm to construct an enhanced algorithm named as reweighted L0L1-L2LP (RL0L1-L2LP) algorithm. The derivations of both sparse L2LP algorithms are introduced in detail. Numerical simulation samples are set up to discuss the channel estimation performance of our proposed L0L1-L2LP and RL0L1-L2LP algorithms. The obtained results give a confirmation that the proposed L0L1-L2LP and RL0L1-L2LP algorithms outperform the L2LP and the related L2LP algorithms in light of the convergence and steady-state performance for handling sparse channel estimation.
SEDEX: Scalable Entity Preserving Data Exchange

Data exchange is the process of generating an instance of a target schema from an instance of a source schema such that source data is reflected in the target. The prevailing approach for data exchange is based on schema mappings, which are high level expressions that describe relationships between database schemas [1]. However, schema-mapping based data exchange techniques suffer from two problems: (1) entity fragmentation, in which information about a single entity is spread across several tuples in the target schema, and (2) ambiguity in generalization, in which incorrect mappings result from using different methods to represent entity type generalization in source and target schemas. In this paper, we propose the Scalable Entity Preserving Data Exchange (SEDEX) method, which combines schema-level and datalevel information to address these problems. We also provide extensive evaluation to demonstrate the benefits and scalability of the approach.
Self‐incompatibilty in gamete recognition: Single self‐recognizing determinants and multiple, non‐self‐recognizing ones function in the same individual

The frameworks (key mechanisms) of the self/non‐self‐discrimination systems that are found in various organisms have not been actively selected for, but have evolved by genetic drift such that the genetic frequency of random, advantageous mutations has increased within the genomes of these species by natural selection. The passive nature of this process leads to an important conclusion: in the self/non‐self‐discrimination system, the number of self‐recognizing determinants becomes one compared to multiple non‐self‐recognizing determinants. Thus, the number of determinants is defined not by the character of the determinant, but by the system framework. Mol. Reprod. Dev. 80: 2–7, 2013. © 2012 Wiley Periodicals, Inc.
Noninvasive assessment of hepatic lipid composition: Advancing understanding and management of fatty liver disorders

Nonalcoholic fatty liver is frequently observed in obese individuals, yet the factors that predict its development and progression to liver disease are poorly understood. We proposed that proton magnetic resonance spectroscopy (1H‐MRS) might allow noninvasive assessment of hepatic lipid composition. Lipid saturation (SI) and polyunsaturation (PUI) indices measured by 1H‐MRS were in agreement with those expected in oils of known composition. Hepatic triglyceride concentration (HTGC) and composition were then measured in healthy lean (LEAN) men, obese men with normal HTGC (OB), and obese men with hepatic steatosis (OB+HS). The effect of marked changes in dietary fat consumption on hepatic lipids were also compared in lean men after 67 hours of a normal mixed (NM) diet versus a low‐carbohydrate, high‐saturated‐fat (LCHF) diet. SI was significantly higher in OB+HS (0.970 ± 0.004) and OB (0.944 ± 0.008) versus LEAN (0.818 ± 0.025) (P < 0.01 for both). PUI was significantly lower in OB+HS (0.003 ± 0.001) and OB (0.022 ± 0.005) versus LEAN (0.120 ± 0.021) (P < 0.01), and significantly lower in OB+HS versus OB (P < 0.05). LCHF diet did not alter HTGC, SI, or PUI (P > 0.05). The 1H‐MRS method provides for rapid, qualitative assessment of lipid composition. Application of this technique in the liver produces results that are consistent with biopsy‐based approaches demonstrating that relative hepatic lipid saturation increases and polyunsaturation decreases with obesity. Obesity‐related hepatic steatosis is characterized by further depletion of polyunsaturated hepatic lipids. Conclusion: This readily available and noninvasive approach should promote further study into interactions between hepatic and whole‐body lipid metabolism and help to elucidate the pathogenesis of disorders characterized by lipid accumulation within the liver. (HEPATOLOGY 2008.)
Multiple Proteases to Localize Oxidation Sites

Proteins present in cellular environments with high levels of reactive oxygen and nitrogen species and/or low levels of antioxidants are highly susceptible to oxidative post-translational modification (PTM). Irreversible oxidative PTMs can generate a complex distribution of modified protein molecules, recently termed as proteoforms. Using ubiquitin as a model system, we mapped oxidative modification sites using trypsin, Lys-C, and Glu-C peptides. Several M+16 Da proteoforms were detected as well as proteoforms that include other previously unidentified oxidative modifications. This work highlights the use of multiple protease digestions to give insights to the complexity of oxidative modifications possible in bottom-up analyses.
SymbiosisSketch: Combining 2D & 3D Sketching for Designing Detailed 3D Objects in Situ

We present SymbiosisSketch, a hybrid sketching system that combines drawing in air (3D) and on a drawing surface (2D) to create detailed 3D designs of arbitrary scale in an augmented reality (AR) setting. SymbiosisSketch leverages the complementary affordances of 3D (immersive, unconstrained, life-sized) and 2D (precise, constrained, ergonomic) interactions for in situ 3D conceptual design. A defining aspect of our system is the ongoing creation of surfaces from unorganized collections of 3D curves. These surfaces serve a dual purpose: as 3D canvases to map strokes drawn on a 2D tablet, and as shape proxies to occlude the physical environment and hidden curves in a 3D sketch. SymbiosisSketch users draw interchangeably on a 2D tablet or in 3D within an ergonomically comfortable canonical volume, mapped to arbitrary scale in AR. Our evaluation study shows this hybrid technique to be easy to use in situ and effective in transcending the creative potential of either traditional sketching or drawing in air.
Research on surface plasmon resonance sensor based on wavelength and angular combined modulations

To wavelength modulation SPR sensor, the measuring sensitivity of refractive index increases with wavelength. A broadband light source (700 nm~900 nm) with relative narrow bandwidth at long wavelength is selected, to measure the refractive index of surrounding medium by using SPR reflection power spectrums, in order to obtain relatively higher sensitivity and resolution. But the measuring range of refractive index is decreased by the reduction in bandwidth of light source. We propose a surface plasmon resonance sensor based on wavelength and angular combined modulations, in order to solve the mutual restriction of measuring range and sensitivity/ resolution, sectional measurement method is adopted, i.e. different incident angles are selected respectively, which will detect different measuring ranges of refractive index. Wavelength and angular combined SPR modulations can cover the whole measuring range of refractive index, and improve the measuring sensitivity and resolution simultaneously.
Linkage map of Salmonella typhimurium, Edition VI

We present the sixth edition of the linkage map of Salmonella typhimurium, comprising 532 genes. The first edition of the map contained 133 genes (383), and subsequent editions were in 1967 (380), 1970 (381), 1972 (382), and 1978 (385). All genes presently known to us are included on the linkage map (Fig. 1) and are listed in Table 1, but references presented in earlier editions of the map are not normally included. Alternative gene symbols are listed in Table 2. In addition, we review some new methods and materials for genetic analysis which are presently available for use in S. typhimurium.
Centralized and distributed approximation algorithms for routing and weighted max-min fair bandwidth allocation

Given a set of demands between pairs of nodes, we examine the traffic engineering problem of maximal flow routing and fair bandwidth allocation where flows can be split to multiple paths (e.g., MPLS tunnels). In the past we presented a polynomial solution for this problem but its complexity makes it hard to implement for large problem sizes. Thus, this paper presents a fully polynomial epsilon-approximation (FPTAS) algorithm for the max-min fair allocation problem which is based on a primal-dual alternation technique. In addition we present a fast and novel distributed algorithm where each source router can find the routing and the fair rate allocation for its commodities. We implemented the centralized algorithm to demonstrate its correctness, efficiency, and accuracy.
Evaluation Strategies for HCI Toolkit Research

Toolkit research plays an important role in the field of HCI, as it can heavily influence both the design and implementation of interactive systems. For publication, the HCI community typically expects toolkit research to include an evaluation component. The problem is that toolkit evaluation is challenging, as it is often unclear what 'evaluating' a toolkit means and what methods are appropriate. To address this problem, we analyzed 68 published toolkit papers. From our analysis, we provide an overview of, reflection on, and discussion of evaluation methods for toolkit contributions. We identify and discuss the value of four toolkit evaluation strategies, including the associated techniques that each employs. We offer a categorization of evaluation strategies for toolkit researchers, along with a discussion of the value, potential limitations, and trade-offs associated with each strategy.
Practical Considerations for Using Pooled Lentiviral CRISPR Libraries

CRISPR/Cas9 technology is ideally suited for genome‐wide screening applications due to the ease of generating guide RNAs (gRNAs) and the versatility of Cas9 or Cas9 derivatives to knockout, repress, or activate expression of target genes. Several pooled lentiviral CRISPR libraries have been developed and are now publicly available, but while using CRISPR/Cas9 for genetic experiments has become widely adopted, genome‐wide screening experiments remain technically challenging. This review covers the basics of CRISPR/Cas9, describes several publicly available CRISPR libraries, and provides a general protocol for conducting genome‐wide screening experiments using CRISPR/Cas9. © 2016 by John Wiley & Sons, Inc.
LPSPS: A New Linear Programming Program

LPSPS is a new linear programming program based on the saddle point algorithm which can solve largescale,sparse linear programming problems. The saddle point algorithm is a new fast iterative method for linear programming. It has been widely used in many fields and shows better performance than other public domain simplex-based programs. Several aspects in the development of the program are described in this article such as the saddle point algorithm, pre-solving, post-solving and the data scaling. At the end of the paper, we compare LPSPS with CPLEX on the NETLIB test set.
Study of Thermoelectric Properties of Cuprous Selenide with High Figure-of-merit

3 ACKNOWLEDGEMENTS . 7 LIST OF FIGURES AND CHARTS . 11 Chapter 1: Introduction to Thermoelectric Materials . 20 1.1 Background . 20 1.2 Thermoelectric Effects . 22 1.3 Thermoelectric Parameters . 26 1.4 Application of Thermoelectric Devices . 41 1.5 Design and Optimization of Thermoelectric Materials . 46 1.6 Different Models of Thermoelectric Materials . 61 1.7 Cu-based Thermoelectric Materials . 69 References . 76 Chapter 2: Experimental and Characterization . 83 2.1 Materials Fabrication . 83 2.2 Materials Characterization . 85
Long-term outcome of L86 and L97 protocols for adult acute lymphoblastic leukemia

We analysed the long-term outcome of the L86 protocol using l-asparaginase (l-asp), vincristine (VCR) and prednisolone (PSL), collectively known as LVP or L97 protocol using LVP along with pirarubicin hydrochloride (THP-ADR) for 97 patients with acute lymphoblastic leukemia (ALL) diagnosed between 1986 and 2002. No significant differences were seen in the two protocols regarding the complete remission (CR) rate or survival. Seventy-five of the 97 patients (77%) achieved a CR. The overall survival (OS) and disease-free survival (DFS) rates were 32.1% and 30.4% at 10 years, respectively. By univariate analysis, we identified seven adverse factors for DFS which included the L2 subtype by French-American-British classification, hepatosplenomegaly, a white blood cell count of more than 30 × 109/L, a blast cell count of more than 10 × 109/L in the peripheral blood, hemoglobin concentration greater than 10 g/dL, a serum lactate dehydrogenase value greater than twice the upper limit of normal and the presence of the Philadelphia chromosome (Ph). According to multivariate analysis, only the presence of Ph was a significant unfavourable factor for DFS and OS. In the 30 patients under 35 years of age without Ph, the OS in the 20 patients treated with L86 and in the 10 patients treated with L97 were 48 and 86%, respectively (P = 0.011). These results indicate that intensified chemotherapy, such as the L97 protocol that includes an anthracycline, might be beneficial for younger patients who are Ph-negative.
Hybrid Intelligent Model Fusing Brain Imaging and Cognition Scale Information for AD Diagnosis

At present, most of the data-driven image medical analysis methods in the diagnosis of brain diseases are difficult to utilize the existing medical expert knowledge, which is unconducive to improve the robustness of model. The cognition scale naturally contains expert knowledge of related brain diseases, but the hybrid-driven method fusing brain imaging and cognition scales to predict brain diseases has challenges in data heterogeneity and information interaction among different analysis tasks. To address the problem above, we propose a contrastive multitask self-supervised pretraining model by effectively fusing brain imaging and cognition scales. First, we simultaneously establish the brain image feature reconstruction and the cognitive score regression prediction model in uniform framework, which can extract the complementary information between brain imaging feature and cognitive scale. Second, we introduce the mask automatic encoder, a self-supervised learning method, to above model to make full use of the rich feature information of sMRI. Then, we adopt contrastive learning to alleviate the problem of negative transfer between the brain reconstruction and cognition score regression prediction tasks. Finally, the loss functions of the two tasks are jointly used to train the backbone network alternately, and the model is applied to the downstream AD diagnosis task as a pre-training model. The experimental results demonstrate that our proposed method is superior to other common AD diagnosis methods, and the proposed model has a certain generalization ability.
Learning More Robust Features with Adversarial Training

In recent years, it has been found that neural networks can be easily fooled by adversarial examples, which is a potential safety hazard in some safety-critical applications. Many researchers have proposed various method to make neural networks more robust to white-box adversarial attacks, but an effective method have not been found so far. In this short paper, we focus on the robustness of the features learned by neural networks. We show that the features learned by neural networks are not robust, and find that the robustness of the learned features is closely related to the resistance against adversarial examples of neural networks. We also find that adversarial training against fast gradients sign method (FGSM) does not make the leaned features very robust, even if it can make the trained networks very resistant to FGSM attack. Then we propose a method, which can be seen as an extension of adversarial training, to train neural networks to learn more robust features. We perform experiments on MNIST and CIFAR-10 to evaluate our method, and the experiment results show that this method greatly improves the robustness of the learned features and the resistance to adversarial attacks.
Double-Level Binary Tree Bayesian compressed sensing for block sparse image

Based on the fact that some image signals possess the block sparsity in practical application environment, a novel Compressed Sensing (CS) algorithm for block sparse image is proposed in this paper. Namely, a Double-level Binary Tree (DBT) Bayesian model is proposed for the block sparse image at the same time the relationship of the root node and the leaf node of this DBT structure is defined as “genetic characteristic”. Then, the block clustering for the block sparse image can be executed successfully and effectively by utilizing Markov Chain Monte Carlo (MCMC) method. The simulation results prove that, our proposed method for the block sparse image signal can get better recovery results with less computation time.
Early Evaluation of the Fetal Heart

Evaluation of the fetal heart at 11-13 + 6 weeks of gestation is indicated for women with a family history of congenital heart defects (CHD), a previous child with CDH, or an ultrasound finding associated with cardiac anomalies. The accuracy for early detection of CHD is highly related to the experience of the operator. The 4-chamber view and outflow tracts are the most important planes for identification of an abnormal heart, and can be obtained in the majority of fetuses from 11 weeks of gestation onward. Transvaginal ultrasound is the preferred route for fetal cardiac examination prior to 12 weeks of gestation, whereas, after 12 weeks, the fetal heart can be reliably evaluated by transabdominal ultrasound. Cardiac defects, such as ventricular septal defects, tetralogy of Fallot, Ebstein's anomaly, or cardiac tumors, are unlikely to be identified at ≤14 weeks of gestation. Additional ultrasound techniques such as spatiotemporal image correlation and the evaluation of volumes by a fetal-heart expert can improve the detection of congenital heart disease. The evaluation of the fetal cardiac function at 11-13 + 6 weeks of gestation can be useful for early identification of fetuses at risk of anemia due to hemoglobinopathies, such as hemoglobin Bart's disease.
Agile 3D Sketching with Air Scaffolding

Hand motion and pen drawing can be intuitive and expressive inputs for professional digital 3D authoring. However, their inherent limitations have hampered wider adoption. 3D sketching using hand motion is rapid but rough, and 3D sketching using pen drawing is delicate but tedious. Our new 3D sketching workflow combines these two in a complementary manner. The user makes quick hand motions in the air to generate approximate 3D shapes, and uses them as scaffolds on which to add details via pen-based 3D sketching on a tablet device. Our air scaffolding technique and corresponding algorithm extract only the intended shapes from unconstrained hand motions. Then, the user sketches 3D ideas by defining sketching planes on these scaffolds while appending new scaffolds, as needed. A user study shows that our progressive and iterative workflow enables more agile 3D sketching compared to ones using either hand motion or pen drawing alone.
Unified logging system for monitoring multiple cloud storage providers in cloud storage broker

With the increasing demand for personal and enterprise data storage service, Cloud Storage Broker (CSB) provides cloud storage service using multiple Cloud Service Providers (CSPs) with guaranteed Quality of Service (QoS), such as data availability and security. However monitoring cloud storage usage in multiple CSPs has become a challenge for CSB due to lack of standardized logging format for cloud services that causes each CSP to implement its own format. In this paper we propose a unified logging system that can be used by CSB to monitor cloud storage usage across multiple CSPs. We gather cloud storage log files from three different CSPs and normalise these into our proposed log format that can be used for further analysis process. We show that our work enables a coherent view suitable for data navigation, monitoring, and analytics.