Miracle-dz/UniFAR-FTUs huggingface dataset:
Characterization of Bacterial Community Structure in a Drinking Water Distribution System during an Occurrence of Red Water

ABSTRACT The role of bacteria in the occasional emergence of red water, which has been documented worldwide, has yet to be determined. To better understand the mechanisms that drive occurrences of red water, the bacterial community composition and the relative abundance of several functional bacterial groups in a water distribution system of Beijing during a large-scale red water event were determined using several molecular methods. Individual clone libraries of the 16S rRNA gene were constructed for three red water samples and one sample of normal water. Beta-, Alpha-, and Gammaproteobacteria comprised the major bacterial communities in both red water and normal water samples, in agreement with previous reports. A high percentage of red water clones (25.2 to 57.1%) were affiliated with or closely related to a diverse array of iron-oxidizing bacteria, including the neutrophilic microaerobic genera Gallionella and Sideroxydans, the acidophilic species Acidothiobacillus ferrooxidans, and the anaerobic denitrifying Thermomonas bacteria. The genus Gallionella comprised 18.7 to 28.6% of all clones in the three red water libraries. Quantitative real-time PCR analysis showed that the 16S rRNA gene copy concentration of Gallionella spp. was between (4.1 ± 0.9) × 107 (mean ± standard deviation) and (1.6 ± 0.3) × 108 per liter in red water, accounting for 13.1% ± 2.9% to 17.2% ± 3.6% of the total Bacteria spp. in these samples. By comparison, the percentages of Gallionella spp. in the normal water samples were 0.1% or lower (below the limit of detection), suggesting an important role of Gallionella spp. in the formation of red water.
A Single Chip Parallel Multiplier by MOS Technology

A parallel multiplier design based on the five-counter cell is discussed. A design optimization for the performance in speed is proposed at the logic design level which is developed into an MOS circuit design. The comparison of the five-counter cell design and the full adder cell design reveals that the proposed design is most useful with pass gate logic and results in high-speed multiplication (approximately twice as fast as that of the full adder design) with a moderate increase in hardware complexity. With the five-counter design, an improvement in the hardware complexity of a squarer can be expected. >
Gait Synthesis and Sensory Control of Stair Climbing for a Humanoid Robot

Stable and robust walking in various environments is one of the most important abilities for a humanoid robot. This paper addresses walking pattern synthesis and sensory feedback control for humanoid stair climbing. The proposed stair-climbing gait is formulated to satisfy the environmental constraint, the kinematic constraint, and the stability constraint; the selection of the gait parameters is formulated as a constrained nonlinear optimization problem. The sensory feedback controller is phase dependent and consists of the torso attitude controller, zero moment point compensator, and impact reducer. The online learning scheme of the proposed feedback controller is based on a policy gradient reinforcement learning method, and the learned controller is robust against external disturbance. The effectiveness of our proposed method was confirmed by walking experiments on a 32-degree-of-freedom humanoid robot.
Atomic-level observation of macromolecular crowding effects: Escape of a protein from the GroEL cage

Experimental work has demonstrated that the efficient operation of the GroEL-GroES chaperonin machinery is sensitive to the presence of macromolecular crowding agents. Here, I describe atomically detailed computer simulations that provide a microscopic view of how crowding effects are exerted. Simulations were performed to compute the free energy required to extract the protein rhodanese from the central cavity of GroEL into solutions containing a range of crowder concentrations. The computed energetics allow the total yield of folded protein to be predicted; the calculated yields show a nonlinear dependence on the concentration of crowding agent identical to that observed experimentally. The close correspondence between simulation and experiment prompts the use of the former in a truly predictive setting: simulations are used to suggest that more effective crowding agents might be designed by exploiting an “agoraphobic effect. ”
The Helical Ventricular Myocardial Band during Standard Echocardiography: A Structure–Function Relationship

The current issue contains a very important report by Hayabuchi and associates entitled “Assessment of the Helical Ventricular Myocardial Band Using Standard Echocardiography” whereby they identify a line of bright-enhanced echogenicity in the middle of the ventricular septum, running from apex to base, and indicate that it defines the boundary line between the ascending and descending segments as described within the Torrent Guasp Helical Ventricular Myocardial Band Model. Most importantly, the functional counterpart is analyzed by employing two-dimensional speckle tracking recordings of longitudinal and circumferential strain to confirm the sequential contraction of first the descending segment and then the ascending segment that were previously recorded by sonomicrometer crystals. Furthermore, the report emphasizes that this readily observed bright line within the septum is identifiable by echocardiographic images obtained in routine clinical practice, so that the underlying functional components now give insight into a deeper understanding of the form function relationship.
High fat diet attenuates glucose‐dependent facilitation of 5‐HT3‐mediated responses in rat gastric vagal afferents

Glucose regulates the density and function of 5‐HT3 receptors on gastric vagal afferent neurones. Diet‐induced obesity compromises the excitability and responsiveness of vagal afferents. In this study, we assessed whether exposure to a high fat diet (HFD) compromises the glucose‐dependent modulation of 5‐HT responses in gastric vagal afferents prior to the development of obesity. We show that HFD does not alter the response of gastric vagal afferent nerves and neurones to 5‐HT but attenuates the ability of glucose to amplify 5‐HT3‐induced responses. These results suggest that glucose‐dependent vagal afferent signalling is compromised by relatively short periods of exposure to HFD well in advance of the development of obesity or glycaemic dysregulation.
Association and intrinsic connections of human extrastriate visual cortex

Human extrastriate visual cortex contains several functionally defined visual areas of which four (V2, VP, V4 and V5) can be identified using cyto- and myeloarchitectonic criteria. A case with a small lesion in the superolateral part of cytoarchitectonic area 19, outside the previously defined visual areas, has been studied with the Nauta method for anterogradely degenerating axons. The infarcted part of cortex formed dense intrahemispheric connections in some visual areas (V1, V2, V3 and probably a part of V4) and weaker connections in others (VP, V5). Connections to V1 and to V2 were mainly directed to the representation of the lower paramedian part of the visual field. Intrinsic connections, visualized by the degenerating axon segments in the cortex around the lesion, had a patchy distribution. In conclusion, intrahemispheric corticocortical connections link preferentially some of the visual areas and within these areas certain parts.
Formal modelling and verification approach for improving probabilistic behaviour of Robot Swarms

Robot Swarms (RS) is an approach that leads to the combined functioning of multiple robot systems to achieve a desired collective behaviour. Robot Swarms possess multiple benefits e.g. RS employment in calamity salvage missions: Swarms of robots of various sizes could be sent to the spots where salvage specialists can't reach securely to detect the presence of life. Swarms can be utilized as a part of military to frame a self-governing armed force. Apart from a large number of advantages, the biggest challenge for RS is its non-predictable behaviour. Architectures and protocols for working of swarms of robots have already been designed and implemented, but to improve the non-predictability of swarms either experiments with robots are to be carried out or computational simulations are performed. However, with these approaches, a deep analysis of all the possible behaviours is very difficult. To improve the non-predictability of RS we used a potent technique, formal verification to confirm that it is bug free. Researchers have realized that computer simulations alone are not capable of evaluating a system or protocol against all possible scenarios. This has encouraged us to employ model checker tools like UPAAL to evaluate Path Planning Algorithms and Alive Human Navigation through RS in disastrous situation. After verification of probabilistic behaviour of swarms, finally, we can safely claim that the collective working of a robot swarm will be free of any undesirable behaviour.
Object contour extraction using color and motion

A new approach to the extraction of the contour of a moving object is presented. The method is based on the integration of a motion segmentation technique using image substraction and a color segmentation technique based on the split-and-merge algorithm. The advantages of this method are: it can detect large moving objects and extract their boundaries; the background can be arbitrarily complicated and contain many non-moving objects occluded by the moving object; and it requires only three image frames that need not be consecutive, provided that the object is entirely contained in each of the three frames. The method is applied to a large number of color images of vehicles moving on a road and a highway ramp. The results are promising. The moving object boundaries are correctly extracted in 66 out of 73 test image sequences. The authors describe how this contour can be used as an input to a recognition system that classifies the vehicles into five generic categories. Of the 73 vehicles, 67 are correctly classified. <<ETX>>
A Novel Prior- and Motion-Based Compressed Sensing Method for Small-Animal Respiratory Gated CT

Low-dose protocols for respiratory gating in cardiothoracic small-animal imaging lead to streak artifacts in the images reconstructed with a Feldkamp-Davis-Kress (FDK) method. We propose a novel prior- and motion-based reconstruction (PRIMOR) method, which improves prior-based reconstruction (PBR) by adding a penalty function that includes a model of motion. The prior image is generated as the average of all the respiratory gates, reconstructed with FDK. Motion between respiratory gates is estimated using a nonrigid registration method based on hierarchical B-splines. We compare PRIMOR with an equivalent PBR method without motion estimation using as reference the reconstruction of high dose data. From these data acquired with a micro-CT scanner, different scenarios were simulated by changing photon flux and number of projections. Methods were evaluated in terms of contrast-to-noise-ratio (CNR), mean square error (MSE), streak artefact indicator (SAI), solution error norm (SEN), and correction of respiratory motion. Also, to evaluate the effect of each method on lung studies quantification, we have computed the Jaccard similarity index of the mask obtained from segmenting each image as compared to those obtained from the high dose reconstruction. Both iterative methods greatly improved FDK reconstruction in all cases. PBR was prone to streak artifacts and presented blurring effects in bone and lung tissues when using both a low number of projections and low dose. Adopting PBR as a reference, PRIMOR increased CNR up to 33% and decreased MSE, SAI and SEN up to 20%, 4% and 13%, respectively. PRIMOR also presented better compensation for respiratory motion and higher Jaccard similarity index. In conclusion, the new method proposed for low-dose respiratory gating in small-animal scanners shows an improvement in image quality and allows a reduction of dose or a reduction of the number of projections between two and three times with respect to previous PBR approaches.
Fitness evaluation for overlapping community detection in complex networks

The discovery of community structures in complex networks is a challenging problem intensively studied in recent years. This paper investigates the performance of evolutionary algorithms for the task of detecting overlapping communities. This task is of great importance as the membership of a node to more than one group is naturally occuring in many real-world networks from fields such as sociology, biology and computer science. One of the major challenges in designing evolutionary algorithms for overlapping community detection is the efficient assessment of the quality of any particular division of nodes into groups. We test four different fitness functions in an evolutionary approach to the problem using the same chromosome representation and search scheme. The performance of the resulting algorithms is tested in a set of computational experiments for some real-world networks. We show that none of the fitness functions used are able to guide the search process towards good partitions based on a measure of the normalized mutual information.
Mesenchymal stem cells: potential for therapy and treatment of chronic non-healing skin wounds

abstract Wound healing is a complex physiological process including overlapping phases (hemostatic/inflammatory, proliferating and remodeling phases). Every alteration in this mechanism might lead to pathological conditions of different medical relevance. Treatments for chronic non-healing wounds are expensive because reiterative treatments are needed. Regenerative medicine and in particular mesenchymal stem cells approach is emerging as new potential clinical application in wound healing. In the past decades, advance in the understanding of molecular mechanisms underlying wound healing process has led to extensive topical administration of growth factors as part of wound care. Currently, no definitive treatment is available and the research on optimal wound care depends upon the efficacy and cost-benefit of emerging therapies. Here we provide an overview on the novel approaches through stem cell therapy to improve cutaneous wound healing, with a focus on diabetic wounds and Systemic Sclerosis-associated ulcers, which are particularly challenging. Current and future treatment approaches are discussed with an emphasis on recent advances.
Gene transcription of pro-inflammatory cytokines and chemokines induced by IL-17A in canine keratinocytes.

BACKGROUND Pro-inflammatory cytokines and chemokines produced by activated keratinocytes play an important role in the pathogenesis of canine atopic dermatitis (AD) as well as human AD. Recent studies suggest that keratinocytes activated by IL-17A are involved in the pathogenesis of human AD. However, the role of IL-17A in canine keratinocytes is poorly understood. HYPOTHESIS/OBJECTIVES Interleukin-17A would induce the transcription of pro-inflammatory cytokines and chemokines in canine keratinocytes. METHODS The transcription levels of pro-inflammatory cytokines and chemokines were quantified in a canine keratinocyte cell line stimulated with recombinant canine (rc) IL-17A. RESULTS The transcription of GM-CSF, S100A8, IL-8 and IL-19 in cultured keratinocytes was significantly enhanced at 24 h after stimulation with rcIL-17A. CONCLUSIONS AND CLINICAL IMPORTANCE Keratinocytes activated by IL-17A have the ability to produce various pro-inflammatory cytokines and chemokines, suggesting that IL-17A may play a central role of the development of Th2-associated inflammation in canine AD.
'Correctable undetected visual acuity deficit' in patients aged 65 and over attending an accident and emergency department.

The rate of occurrence of correctable undetected visual acuity deficit (CUVAD) in a population of patients aged 65 and over was investigated, using a pinhole screening method, to compare the sociodemographic and optical eye care habits of patients with or without a functionally significant CUVAD. Of 136 patients 46 (34%) were found to have a functionally significant CUVAD in one or both eyes which was not significantly associated with optician or general practitioner contact, age, sex, social class, living situation, or number of medications. Half the patients with significant CUVAD had not attended for 2 years mainly because of financial considerations. Three quarters attended of their own volition; only one in seven were prompted by opticians' postal invitations. It was concluded that a significant degree of CUVAD could be detected using a simple procedure which can be carried out by general practitioners as part of their general elderly health screen.
Running head : LEARNING QUASIREGULARITY 1 THEORETICAL NOTE How Do PDP Models Learn Quasiregularity ?

Parallel Distributed Processing (PDP) models have had a profound impact on the study of cognition. One domain in which they have been particularly influential is quasiregular learning, in which mastery requires both learning regularities that capture the majority of the structure in the input plus learning exceptions that violate the regularities. How PDP models learn quasiregularity is still not well understood. Smalland large-scale analyses of a feedforward, three-layer network were carried out to address two fundamental issues about network functioning: how the model can learn both regularities and exceptions without sacrificing generalizability; and the nature of the hidden representation that makes this learning possible. Results show that capacity-limited learning pressures the network to form componential representations, which ensures good generalizability. Small and highly local perturbations of this representational system allow exceptions to be learned while minimally disrupting generalizability. Theoretical and methodological implications of the findings are discussed.
Activation of transcription by PU.1 requires both acidic and glutamine domains

The B-lymphocyte- and macrophage-specific transcription factor PU.1 is a member of the ets family of proteins. To understand how PU.1 functions as a transcription factor, we initiated a series of experiments to define its activation domain. Using deletion analysis, we showed that the activation domain of PU.1 is located in the amino-terminal half of the protein. Within this region, we identified three acidic subdomains and one glutamine-rich subdomain. The deletion of any of these subdomains resulted in a significant loss in the ability of PU.1 to transactivate in cotransfection studies. Amino acid substitution analysis showed that the activation of transcription by PU.1 requires acidic residues between amino acids 7 and 74 and a group of glutamine residues between amino acids 75 and 84. These data show that PU.1 contains two types of known activation domains and that both are required for maximal transactivation.
Capacitive sensing and communication for ubiquitous interaction and environmental perception

During the last decade, the functionalities of electronic devices within a living environment constantly increased. Besides the personal computer, now tablet PCs, smart household appliances, and smartwatches enriched the technology landscape. The trend towards an ever-growing number of computing systems has resulted in many highly heterogeneous human-machine interfaces. Users are forced to adapt to technology instead of having the technology adapt to them. Gathering context information about the user is a key factor for improving the interaction experience. Emerging wearable devices show the benefits of sophisticated sensors which make interaction more efficient, natural, and enjoyable. However, many technologies still lack of these desirable properties, motivating me to work towards new ways of sensing a user's actions and thus enriching the context. In my dissertation I follow a human-centric approach which ranges from sensing hand movements to recognizing whole-body interactions with objects. This goal can be approached with a vast variety of novel and existing sensing approaches. I focused on perceiving the environment with quasi-electrostatic fields by making use of capacitive coupling between devices and objects. Following this approach, it is possible to implement interfaces that are able to recognize gestures, body movements and manipulations of the environment at typical distances up to 50cm. These sensors usually have a limited resolution and can be sensitive to other conductive objects or electrical devices that affect electric fields. The technique allows for designing very energy-efficient and high-speed sensors that can be deployed unobtrusively underneath any kind of non-conductive surface. Compared to other sensing techniques, exploiting capacitive coupling also has a low impact on a user's perceived privacy. In this work, I also aim at enhancing the interaction experience with new perceptional capabilities based on capacitive coupling. I follow a bottom-up methodology and begin by presenting two low-level approaches for environmental perception. In order to perceive a user in detail, I present a rapid prototyping toolkit for capacitive proximity sensing. The prototyping toolkit shows significant advancements in terms of temporal and spatial resolution. Due to some limitations, namely the inability to determine the identity and fine-grained manipulations of objects, I contribute a generic method for communications based on capacitive coupling. The method allows for designing highly interactive systems that can exchange information through air and the human body. I furthermore show how human body parts can be recognized from capacitive proximity sensors. The method is able to extract multiple object parameters and track body parts in real-time. I conclude my thesis with contributions in the domain of context-aware devices and explicit gesture-recognition systems.