Miracle-dz/UniFAR-FTUs huggingface dataset:
Development of surface micromachining technologies for microfluidics and bioMEMS

In the last decade, examples of devices manufactured with SUMMiT(TM) technology have demonstrated the capabilities of polysilicon surface micromachining. Currently we are working on enhancements to this technology that utilize additional structural layers of silicon nitride to enable Microfluidics and BioMEMS applications. The addition of the silicon nitride layers allows the fabrication of microfluidic flow channels that are transparent (allowing observation of cellular motion) and insulating (allowing the placement of polysilicon electrodes at arbitrary locations in the flow channels). The goal of this technology development effort is to ultimately provide functionality that is not feasible with other microfabrication technologies. The enhancements build on the key features of surface micromachining: manufacturability and compatibility with CMOS processing, which allow us to leverage the investment already made in the microelectronics processing technology. In this paper we will present examples of devices fabricated using this new enhanced surface micromachining technology. These devices include pumps, valves, and a cell manipulator.
Towards a classification model for component-based software engineering research

Accurate and timely information is a key motivator in the widespread adoption of CBSE technology in Europe. Although there are overlaps and informal communications between researchers and adopters of CBSE technology in Europe, there is no systematic mechanism for information interchange between the two. CBSEnet is a European Union initiative to create an Internet-based forum for the exchange of information between researchers and adopters of CBSE. We describe a proposed classification model for CBSE research that will form the basis for structuring the CBSEnet knowledge base.
Graph Distances in the Data-Stream Model

We explore problems related to computing graph distances in the data-stream model. The goal is to design algorithms that can process the edges of a graph in an arbitrary order given only a limited amount of working memory. We are motivated by both the practical challenge of processing massive graphs such as the web graph and the desire for a better theoretical understanding of the data-stream model. In particular, we are interested in the trade-offs between model parameters such as per-data-item processing time, total space, and the number of passes that may be taken over the stream. These trade-offs are more apparent when considering graph problems than they were in previous streaming work that solved problems of a statistical nature. Our results include the following: (1) Spanner construction: There exists a single-pass, $\tilde{O}(tn^{1+1/t})$-space, $\tilde{O}(t^2n^{1/t})$-time-per-edge algorithm that constructs a $(2t+1)$-spanner. For $t=\Omega(\log n/{\log\log n})$, the algorithm satisfies the semistreaming space restriction of $O(n\operatorname{polylog}n)$ and has per-edge processing time $O(\operatorname{polylog}n)$. This resolves an open question from [J. Feigenbaum et al., Theoret. Comput. Sci., 348 (2005), pp. 207-216]. (2) Breadth-first-search (BFS) trees: For any even constant $k$, we show that any algorithm that computes the first $k$ layers of a BFS tree from a prescribed node with probability at least $2/3$ requires either greater than $k/2$ passes or $\tilde{\Omega}(n^{1+1/k})$ space. Since constructing BFS trees is an important subroutine in many traditional graph algorithms, this demonstrates the need for new algorithmic techniques when processing graphs in the data-stream model. (3) Graph-distance lower bounds: Any $t$-approximation of the distance between two nodes requires $\Omega(n^{1+1/t})$ space. We also prove lower bounds for determining the length of the shortest cycle and other graph properties. (4) Techniques for decreasing per-edge processing: We discuss two general techniques for speeding up the per-edge computation time of streaming algorithms while increasing the space by only a small factor.
Towards a Theory of Simplicity in Agile Software Development: A Qualitative Study

Context: Several research works emphasise that the concept of simplicity is, in itself, by far not a simple concept, mainly because there are many perspectives on the perception of simplicity. Purpose: To understand how project managers and software engineers interpret their experiences in agile software projects considering the simplicity issues in agile software development. Method: Semi-structured interviews were carried out with practitioners within a software development company. The data was analysed using grounded theory techniques. Results: A set of categories (lightweight process, knowledge acquisition, personal communication, time-consuming, and product with value) that affect the simplicity in agile software development were extracted. Finally, the categories and propositions with higher explanatory power were used to create a provisional theory about simplicity in agile software projects. Conclusion: The results show that a better understanding of the implications of simplicity on agile software development may contribute to the projects' successes.
Pioneering Applications of Two-Photon Microscopy to Mammalian Neurophysiology

It is commonly assumed, although insufficiently acknowledged, that major advances in neuroscience are spurred bymethodological innovations. Novel techniquesmay appear quite daunting at first, but their successful application not only places them among mainstream methods, but also stimulates further developments in new directions. Such is the case for two-photon laser scanning microscopy (TPLSM) (Denk et al., 1990), which was introduced in neuroscience in the early 1990s (Denk et al., 1994). Since that time, the impact of TPLSM in neurobiology has been nothing short of remarkable. Several excellent reviews on TPLSM have already covered the general aspects of this technique (Denk et al., 1995; Denk & Svoboda, 1997; Stutzmann and Parker, 2005; Zipfel et al., 2003), details of the instrumentation (Tsai et al., 2002), and recent advances (Brecht et al., 2004). The object of this chapter is to showcase seminal applications of TPLSM in neuroscience, with a particular emphasis on mammalian neurobiology. The seven case studies presented here not only expound the broad range of applications of TPLSM but also show that TPLSM has been used to resolve significant issues in mammalian neurobiology thatwere previously unanswereddue to lackof an appropriate technique.
An Object Shape Completion Using the Shape Boltzmann Machine Mr

An object shape plays a crucial role in many computer vision applications such as segmentation, object detection, inpainting and graphics. An object shape mainly depends upon local and global variables. Local variables on the shape such as smoothness and continuity can help provide correct segmentations where the object boundary is noisy, unclear or lost in shadow. Global variables on the shape such as ensuring the correct number of parts (legs, wheels, wings etc) can resolve ambiguities where background clutter looks similar to part of the object. In this paper, we present a new learning algorithm for Boltzmann machines that contain two layers of hidden units that we call a Shape Boltzmann Machine (ShapeBM) for the task of modeling foreground/background (binary) and parts-based (categorical) shape images. We show that the ShapeBM can generate more realistic and generalized samples and ability to do shape completion suggests applications in a computer
Fraud, Anonymization, and Privacy in the Internet: A Database Perspective

Data is everywhere, and manifests itself in various formats. Data can be publicly available and can be privately owned. Data can be persistent on a server or ephemeral in a data stream. Society depends on data and hence the security, privacy and reliability of the data are critical in diverse ways. In this talk I will touch on various security aspects of data in different contexts that arise in diverse internet applications.
Competitive Factors of the Agro-Food E-Commerce

In the new economy small and medium enterprises face new challenges in their business-to-consumers transactions, such as the use of new information and communication technologies. Electronic commerce may represent a competitive strategy to make enterprises of the agro-food sector more visible to consumers, if usability is adequately taken into account. The main barrier to the development of successful e-commerce business is represented by websites not meeting basic accessibility and usability features. To tackle this issue, heuristic evaluation and the gap analysis approach was adopted. The parameters taken into account stemmed from international Web recommendations and from previous surveys in the literature. Web site usability issues have been measured by a panel of consumers assessing a selected Web site each. Potential e-consumers simulated an online purchase, thereby allowing them to acquire insights on the importance and satisfaction on each of the usability issues taken into consideration. The success factors for e-commerce mainly involve efficiency of navigation (useful navigation tools or sequence of navigation), accuracy in content and supplied information. Consumers are more conduced to purchase by easy structure of Web sites than design and style. Additional information underlining the connection of producers to their territory enhances end-consumers' feel in supply chain identification. The adoption of e-commerce, as an innovative communication challenge in rural development and in regional identity is a crucial issue of dynamic food chains.
Emergence of stable and fast folding protein structures

The number of protein structures is far less than the number of sequences. By imposing simple generic features of proteins (low energy and compaction) on all possible sequences we show that the structure space is sparse compared to the sequence space. Even though the sequence space grows exponentially with N (the number of amino acid residues) we conjecture that the number of low energy compact structures only scales as lnN. This implies that many sequences must map onto countable number of basins in the structure space. The number of sequences for which a given fold emerges as a native structure is further reduced by the dual requirements of stability and kinetic accessibility. The factor that determines the dual requirement is related to the sequence dependent temperatures, Tθ (collapse transition temperature) and TF (folding transition temperature). Sequences, for which σ=(Tθ−TF)/Tθ is small, typically fold fast by generically collapsing to the native-like structures and then rapidly assembling to the .
The Ergodic Capacity of Interference Networks

Author(s): Jafar, Syed A | Abstract: We identify the role of equal strength interference links as bottlenecks on the ergodic sum capacity of a K user interference network with the fading process restricted primarily to inde- pendent and uniform phase variations while the channel magnitudes are held ﬁxed across time. It is shown that even though there are K(K − 1) cross-links, only about K/2 disjoint and equal strength interference links suﬃce to determine the capacity of the network regardless of the strengths of the rest of the cross channels. This scenario is called a minimal bottleneck state. It is shown that ergodic interference alignment is capacity optimal for a network in a minimal bottleneck state. The results are applied to large networks. It is shown that large networks are close to bottleneck states with a high probability, so that ergodic interference alignment is close to optimal for large networks. Limitations of the notion of bottleneck states are also high- lighted for channels where both the phase and the magnitudes are allowed to vary with time. It is shown through an example that for these channels, joint coding across diﬀerent bottleneck states makes it possible to circumvent the capacity bottlenecks.
Candida guilliermondii continuous ambulatory peritoneal dialysis peritonitis confirmed by 16s rRNA sequencing

A53-year-oldmanundergoing continuous ambulatory peritoneal dialysis (CAPD) presented with abdominal pain and cloudy dialysate. The white blood cell (WBC) count of dialysate effluent was 495/mm. Serum C-reactive protein (CRP) level was 6.7 mg/dL. The patient was initially treated with intraperitoneal administration of cefazolin and ceftazidime. However, his abdominal pain was aggravated.WBC count of dialysate effluent and serum CRP level increased to 1,494/mm and 16.98 mg/dL, respectively. Yeast forming fungi were detected in the dialysate effluent fluid. The peritoneal catheter was removed, and hemodialysis was initiated. Intravenous administration of fluconazole was empirically performed. Candida guilliermondii was confirmed by 16S ribosomal RNA (rRNA) sequencing. The genomic DNAwas extracted from the cultivated microorganism. The 16S rRNA gene was amplified with universal primers (forward, 5’-AGTTTGATCCTGGCTCAG-3’; reverse, 5’-GTATTGCCGCGGCTGCTG-3’), and sequenced. C. guilliermondii was verified with 99–100% similarity (GeneBank accession number: KF913531.1). After 5 weeks of treatment with fluconazole, the patient’s symptoms completely subsided and the serum CRP levels were maintained within the normal range. Fungal peritonitis is associated with significant mortality and catheter loss in patients undergoing CAPD. Diagnosis of fungal peritonitis can be difficult and delayed because of the nonspecific symptoms and slow growth rates. The most common fungi identified in fungal peritonitis are Candida species, especially C. albicans and C. parapsilosis. C. guilliermondii is an
ORFeus: detection of distant homology using sequence profiles and predicted secondary structure

ORFeus is a fully automated, sensitive protein sequence similarity search server available to the academic community via the Structure Prediction Meta Server (http://BioInfo.PL/Meta/). The goal of the development of ORFeus was to increase the sensitivity of the detection of distantly related protein families. Predicted secondary structure information was added to the information about sequence conservation and variability, a technique known from hybrid threading approaches. The accuracy of the meta profiles created this way is compared with profiles containing only sequence information and with the standard approach of aligning a single sequence with a profile. Additionally, the alignment of meta profiles is more sensitive in detecting remote homology between protein families than if aligning two sequence-only profiles or if aligning a profile with a sequence. The specificity of the alignment score is improved in the lower specificity range compared with the robust sequence-only profiles.
Sparse and Greedy: Sparsifying Submodular Facility Location Problems

Submodular facility location functions are widely used for summarizing large datasets and have found applications ranging from sensor placement, image retrieval, and clustering. A significant problem is that evaluating such functions typically requires the calculation of pairwise benefits for all items, which is computationally unmanageable for large problems. In this paper we propose a sparsification method that only computes nearest-neighbor benefits and can dramatically accelerate submodular greedy optimization. We show that the optimal solution of the sparsified problem will be at most a factor of a half from optimal, under minimal assumptions.
Metric Learning for Kernel Regression

Kernel regression is a well-established method for nonlinear regression in which the target value for a test point is estimated using a weighted average of the surrounding training samples. The weights are typically obtained by applying a distance-based kernel function to each of the samples, which presumes the existence of a well-defined distance metric. In this paper, we construct a novel algorithm for supervised metric learning, which learns a distance function by directly minimizing the leave-one-out regression error. We show that our algorithm makes kernel regression comparable with the state of the art on several benchmark datasets, and we provide efficient implementation details enabling application to datasets with ∼O(10k) instances. Further, we show that our algorithm can be viewed as a supervised variation of PCA and can be used for dimensionality reduction and high dimensional data visualization.
Automatic 3D scene generation based on Maya

Generating 3D virtual scene is a very important task in the computer graphics and virtual reality community. Manual scene generation often achieves very good visual effects but is a time-consuming and intensive process. Automatic scene generation speeds up the whole generating process but often pays less attention to the graphics engine. In this paper, we present a new system for automatically generating 3D scenes from text descriptions based on Autodesk Maya. We combine the advantages of both automatic 3D scene generation and excellent graphics tools in Maya, to achieve fast and efficient generation of 3D scene and good visual effects as well as convenience for the subsequent operations.
A Context Sensitive Experience Feeder for Computer Aided Engineering

: Computer aided engineering (CAE) tries to map properties and interactions of real world entities with symbols and values readable to the machine. Modern CAE software packages are powerful in function, but users usually need a lot of knowledge and experience to manipulate them. As a kind of tacit knowledge, experiences require gauged context in order to be fully understood and applied. To better exploit the freely written, hard-to-encode experiences on the web, we propose in this paper a context sensitive experience feeding mechanism which is able to recommend experiences matching the context of a given CAE task. Our method makes use of information extraction and natural language processing techniques to find experience valuable to engineer’s trouble shooting. Empirical evaluation of a prototypical feeder suggests that our method is effective.
Signalling crosstalk in light stress and immune reactions in plants

The evolutionary history of plants is tightly connected with the evolution of microbial pathogens and herbivores, which use photosynthetic end products as a source of life. In these interactions, plants, as the stationary party, have evolved sophisticated mechanisms to sense, signal and respond to the presence of external stress agents. Chloroplasts are metabolically versatile organelles that carry out fundamental functions in determining appropriate immune reactions in plants. Besides photosynthesis, chloroplasts host key steps in the biosynthesis of amino acids, stress hormones and secondary metabolites, which have a great impact on resistance against pathogens and insect herbivores. Changes in chloroplast redox signalling pathways and reactive oxygen species metabolism also mediate local and systemic signals, which modulate plant resistance to light stress and disease. Moreover, interplay among chloroplastic signalling networks and plasma membrane receptor kinases is emerging as a key mechanism that modulates stress responses in plants. This review highlights the central role of chloroplasts in the signalling crosstalk that essentially determines the outcome of plant–pathogen interactions in plants.
Distinct signatures of diversifying selection revealed by genome analysis of respiratory tract and invasive bacterial populations

Many pathogens colonize different anatomical sites, but the selective pressures contributing to survival in the diverse niches are poorly understood. Group A Streptococcus (GAS) is a human-adapted bacterium that causes a range of infections. Much effort has been expended to dissect the molecular basis of invasive (sterile-site) infections, but little is known about the genomes of strains causing pharyngitis (streptococcal “sore throat”). Additionally, there is essentially nothing known about the genetic relationships between populations of invasive and pharyngitis strains. In particular, it is unclear if invasive strains represent a distinct genetic subpopulation of strains that cause pharyngitis. We compared the genomes of 86 serotype M3 GAS pharyngitis strains with those of 215 invasive M3 strains from the same geographical location. The pharyngitis and invasive groups were highly related to each other and had virtually identical phylogenetic structures, indicating they belong to the same genetic pool. Despite the overall high degree of genetic similarity, we discovered that strains from different host environments (i.e., throat, normally sterile sites) have distinct patterns of diversifying selection at the nucleotide level. In particular, the pattern of polymorphisms in the hyaluronic acid capsule synthesis operon was especially different between the two strain populations. This finding was mirrored by data obtained from full-genome analysis of strains sequentially cultured from nonhuman primates. Our results answer the long-standing question of the genetic relationship between GAS pharyngitis and invasive strains. The data provide previously undescribed information about the evolutionary history of pathogenic microbes that cause disease in different anatomical sites.
Prevalence of malnutrition in patients admitted to a major urban tertiary care hospital in Hanoi, Vietnam.

OBJECTIVES To determine the prevalence of malnutrition using anthropometric measures among hospitalized pediatric and adult patients admitted at Bach Mai Hospital, Hanoi, Vietnam. METHODS A one-day cross-sectional survey was used in selected wards (Pediatrics, Surgery, Intensive Care Unit, Renal Diseases, Gastroenterology Diseases, Respiratory Diseases, and Endocrinology). Unavailable patients and those discharged within 24 hours were excluded. Anthropometric data included body weight, height (or length), and mid-upper arm circumference. The type, severity, and prevalence rate of malnutrition were defined based on World Health Organization (WHO) criteria. RESULTS The sample was hospitalized children and adults: 108 and 571 were children aged 6 months to 18.9 years old and adult patients, respectively. The overall rate of pediatric wasting (weight-for-height ≤ -2 SD or BMI ≤ -2 SD, kg/m²) was 19.0% (n= 19/100) and that of stunting (height-for-age ≤ -2 SD) was 13.9% (n=14/101). Using either the mid-upper arm circumference <11.5 cm or the weight-for-height and weight-for-length ≤ -3 SD, the rate of severe wasting among children aged 6-59 months old was 7.0% (n=3/43). None of the children were obese based on weight-for-length, weight-for-height, or BMI. In adults, the prevalence of under-nutrition (BMI<18.5 kg/m²) was 33.3% (n=141/423) while that of obesity (BMI ≥ 30 kg/m²) was 0.9% (n=4/423). Adults admitted to the Respiratory Diseases ward had the highest prevalence of under-nutrition, 40.9% (n=38/93). CONCLUSIONS The prevalence of malnutrition was high in this cohort of hospitalized patients, particularly in adults, but comparable to other published reports. Obesity was nearly nonexistent in both children and adults.