Miracle-dz/UniFAR-FTUs huggingface dataset:
T regulatory cell therapy in transplantation: stability, localization and functional specialization

Purpose of reviewThere is great hope that cellular therapy with regulatory T cells (Tregs) will be an effective way to induce alloantigen specific tolerance, ultimately allowing for reduction or elimination of nonspecific immunosuppression. In the past, considerable effort was focused on defining the optimal ways to isolate and expand Tregs from peripheral or cord blood. Now that expansion of therapeutically relevant numbers of Tregs is feasible, we need to consider what is going to happen to the cells when they are transferred in vivo. Recent findingsFor optimal function, Tregs must be able to traffic to the correct location(s) and, despite the presence of immunosuppressive therapy, live long enough to transfer their regulatory function to recipient T cells. Within the Treg pool, there are also functionally specialized subsets, identified by chemokine receptor expression and/or cytokine production, which control their trafficking and relative ability to suppress different types of T helper cells, respectively. Recent findings imply that the plasticity of appropriately obtained populations of Tregs may not be of as great concern as previously suggested. Experimental data have also provided evidence as to how one might design adjunctive treatment that best supports the viability and function of Tregs after transfer. SummaryKnowledge of how Tregs work in transplantation comes from studies that do not recapitulate how these cells will be used in humans. There is a need to develop better preclinical models to study how the in-vivo function of human Tregs can be optimized to ensure they can meet the challenge of inducing transplantation tolerance.
Network performance in virtualized environments

Virtualization is increasingly used for emulating computer networks in areas such as, e. g. , education, testing, forensics and research. In this paper, we experimentally study the performance characteristics of virtualized networks for different virtualization technologies and compare them with real, physical networks. Our results indicate that the performance characteristics of virtualized networks are highly implementation dependent and do not necessarily resemble the performance characteristics of real networks in many cases. Therefore, results obtained in virtualized setups must be carefully checked before drawing conclusions about real networks. Moreover, our results indicate that the performance of virtualized networks may even impact the “common” operation of IT and network infrastructures, e. g. , server-to-server-communication. To the best of our knowledge, this question has not been investigated before.
Disturbance of semantic processing in temporal lobe epilepsy demonstrated with scalp ERPs

We investigated event-related potentials (N400, LPC and CNV) elicited in temporal lobe epilepsy (TLE) patients and control subjects from scalp electrodes, using a word-pair category matching paradigm. Each prime consisted of a Japanese noun (constructed from 2-4 characters of the Hiragana) followed by a Chinese character (Kanji) as the target, the latter representing one of five semantic categories. There were two equally probable target conditions: match or mismatch. Each target was preceded by a prime, either belonging to, or not belonging to, the same semantic category. The subjects were required to respond with a specified button press to the given target, according to the condition. We found RTs to be longer under the mismatch condition in both subject groups. The N400 amplitude was reduced in TLE subjects under both conditions, although LPC and CNV amplitudes showed no significant differences. These results suggest that scalp N400 is capable of demonstrating disturbance of semantic processing in TLE non-invasively.
Biodiesel production from microalgae : Production of biodiesel from algae

Biodiesel production from algae is a promising technique. Microalgae have the potential to produce 5,000-15,000 gallons of biodiesel/(acre-year). However, there are challenges; these include high yield of algae biomass with high lipid content and the effective technique to harvest the grown algae, extract the algal oil and transesterify the oil to biodiesel. In this project Tubular PhotoBioReactor (TPBR) was designed and achieved a ten times increase in algae concentration. It produced 1g of dry algal biomass per liter of medium within 12 days, with a lipid content of 12% approximately. Healthy algal culture grew well in the TPBR reaching 56x10 cells/mL of culture medium. The 10 fold increase is higher than those reported for open ponds and helical photobioreactor.
Propagation Engine Prototyping with a DSL

Constraint propagation is at the heart of constraint solvers. Two main trends co-exist: variable-oriented propagation engines and constraint-oriented propagation engines. Those two approaches ensure the same consistency level, generally arc-consistency, but their efficiency (computation time) can be quite different depending on the instance solved. It is usually accepted that there is no best approach in general, and modern constraint solvers implement only one. In this paper, we would like to go a step further providing a solver independent language at the modeling stage to enable the design of propagation engine prototypes. We validate our proposal with a reference implementation based on Choco and the MiniZinc modeling language.
Causal consistency: beyond memory

In distributed systems where strong consistency is costly when not impossible, causal consistency provides a valuable abstraction to represent program executions as partial orders. In addition to the sequential program order of each computing entity, causal order also contains the semantic links between the events that affect the shared objects -- messages emission and reception in a communication channel, reads and writes on a shared register. Usual approaches based on semantic links are very difficult to adapt to other data types such as queues or counters because they require a specific analysis of causal dependencies for each data type. This paper presents a new approach to define causal consistency for any abstract data type based on sequential specifications. It explores, formalizes and studies the differences between three variations of causal consistency and highlights them in the light of PRAM, eventual consistency and sequential consistency: weak causal consistency, that captures the notion of causality preservation when focusing on convergence; causal convergence that mixes weak causal consistency and convergence; and causal consistency, that coincides with causal memory when applied to shared memory.
The B . subtilis sin Operon : An Evolvable Network Motif

The strategy of combining a regulatory protein and its antagonist onto same operon, but controlling their activities differentially, can lead to diverse regulatory functions. This protein-antagonist motif is ubiquitous and present in evolutionarily unrelated regulatory pathways. Using the sin operon from the B. subtilis sporulation pathway as a model system, we build a theoretical model, parameterize it using data from the literature, and use bifurcation analyses to determine the circuit functions it could encode. The model demonstrates that this motif can generate a bistable switch with tunable control over the switching threshold and the degree of population heterogeneity. Further, we show that a small perturbation of a single critical parameter can bias this architecture into functioning like a graded response, a bistable switch, an oscillator, or a pulse generator. By mapping the parameters of the model to specific DNA regions and comparing the genomic sequences of Bacillus species, we show that phylogenetic variation tends to occur in those regions that tune the switch threshold without disturbing the circuit function. Due to the dynamical plasticity of the protein-antagonist operon motif, we propose that it is an evolutionarily convergent design selected not only for particular immediate function but also for its evolvability.
Techniques in High Pressure Neutron Scattering

Basic Concepts Basic elements of material strength The cylindrical pressure vessel Construction Materials I: Nonferrous Alloys Copper beryllium Titanium-zirconium (TiZr) High tensile titanium alloys High tensile aluminium alloys Construction Materials II: Steels and Super-Alloys General The iron-carbon phase diagram Other alloy elements Designation (naming) of steels High tensile steels Stainless steels Superalloys Hydrogen compatibility Construction Materials III: Sinter Materials Tungsten carbide (TC) Sintered cubic boron nitride (cBN) Sintered diamond (SD) Perspective: Nano-polycrystalline diamond (NPD) Ceramics Liquid/Gas and Clamp Pressure Cells Liquid/gas pressure cells Clamp cells McWhan-Type Cells General Conclusion Sapphire, Moissanite and Diamond Anvil Cells Sapphire cells Moissanite anvil cells (MACs) Diamond anvil cells (DACs) Special Designs SANS high pressure cells Single-crystal sapphire gas cells Uniaxial Pressure Cells General Clamp devices Remotely operated devices Paris-Edinburgh Cells I General Load-frames Anvils and gaskets General remarks and observations Paris-Edinburgh Cells II: Low and High Temperatures General Low temperatures High temperatures Paris-Edinburgh Cells III: Ancillary Equipment Oil and gas compressors Loading clamps High pressure gas loading Anvil rotor Pressure Determination and Pressure Transmitting Media Equations-of-state (EoS) Pressure markers Useful empirical rules Pressure transmitting media (PTM) General comments and recommendations Applications General Diffraction Inelastic scattering Small angle neutron scattering (SANS) Quasi-elastic neutron scattering (QENS) Appendices Bibliography Index
Global Free Energy Scoring Functions Based on Distance-Dependent Atom-Type Pair Descriptors

Scoring functions for protein-ligand docking have received much attention in the past two decades. In many cases, remarkable success has been demonstrated in predicting the correct geometry of interaction. On independent test sets, however, the predicted binding energies or scores correlate only slightly with the observed free energies of binding. In this study, we analyze how well free energies of binding can be predicted on the basis of crystal structures using traditional QSAR techniques in a proteochemometric approach. We introduce a new set of protein-ligand interaction descriptors on the basis of distance-binned Crippen-like atom type pairs. A subset of the publicly available PDBbind09-CN refined set (MW < 900 g/mol, #P < 2, ndon + nacc < 20; N = 1387) is being used as data set. It is demonstrated how simple, yet surprisingly good, scoring functions can be generated for the whole diverse database (R(2)(out-of-bag) = 0.48, R(p) = 0.69, RMSE = 1.44, MUE = 1.14) and individual protein family subsets. This performance is significantly better than the performance of almost all other scoring functions published that have been validated on a test set as large and diverse as the PDBbind refined set. We also find that on some protein families surprisingly good scoring functions can be obtained using simple ligand-only descriptors like logS, logP, and molecular weight. The ligand-descriptor based scoring function equals or even outperforms commonly used scoring functions, highlighting the need for better scoring functions. We demonstrate how the observed performance depends on the validation strategy, and we outline a general validation protocol for future free energy scoring functions.
Tractable locomotion planning for RoboSimian

This paper investigates practical solutions for low-bandwidth, teleoperated mobility for RoboSimian in complex environments. Locomotion planning for this robot is challenging due to kinematic redundancy. We present an end-to-end planning method that exploits a reduced-dimension rapidly-exploring random tree search, constraining a subset of limbs to an inverse kinematics table. Then, we evaluate the performance of this approach through simulations in randomized environments and in the style of the Defense Advanced Research Projects Agency Robotics Challenges terrain both in simulation and with hardware. We also illustrate the importance of allowing for significant body motion during swing leg motions on extreme terrain and quantify the trade-offs between computation time and execution time, subject to velocity and acceleration limits of the joints. These results lead us to hypothesize that appropriate statistical “investment” of parallel computing resources between competing formulations or flavors of random planning algorithms can improve motion planning performance significantly. Motivated by the need to improve the speed of limbed mobility for the Defense Advanced Research Projects Agency Robotics Challenge, we introduce one formulation of this resource allocation problem as a toy example and discuss advantages and implications of such trajectory planning for tractable locomotion on complex terrain.
DETC 2002 / MECH-34281 PROJECTIVE CONVEXITY IN COMPUTATIONAL KINEMATIC GEOMETRY

In recent years, there is an increasing interest in developing geometric algorithms for kinematic computations. The aim of this paper is to present the notion of projective convexity as a key element for a new framework for kinematic geometry, that allows for the development of more elegant and efficient algorithms for geometric computations with kinematic applications. The resulting framework, called computational kinematic geometry, is developed by combining the oriented projective geometry with the kinematic geometry of rigid body motions.
Tracheo‐oesophageal compression due to rapid thyroid enlargement after radioiodine treatment

In reply: Beattie's letter raises an interesting issue about the methodology of case-control studies of vaccine effectiveness. In such studies, it is preferable to include subjects with prior histories of the disease in question, particularly when the validity of these histories is unknown.t-' This approach will tend to underestimate vaccine effectiveness because those who have previously had the disease are likely to be unvaccinated, but are not susceptible to infection. Thus, their inclusion (as controls) in a case-control study will mean that unvaccinated subjects appear relatively less susceptible to disease than vaccinated subjects. ' Although not stated in our article," we did seek information on prior measles history. Parents of 6% of cases and 9% of controls reported that their child had had measles before the study period. Controls were no more likely than cases to have had measles (X2 =0.6; P= 0.4), casting doubt on the accuracy of these reports. Mathematical modelling has shown that the inclusion of subjects with a history of prior disease in case-control studies may lead to an underestimation of vaccine effectiveness by up to 10%. This conservative approach seems to have had little effect in our study, given our very high vaccine effectiveness estimate (94% for those with verified vaccination records).
Plasma Membrane Redox System in the Erythrocytes of Rowers: Pilot Study

Dear Editor-in-ChiefThe oxidative stress results from a change in the physiological balance between oxidant and anti-oxidant species. This type of stress is a chemical change in the redox state of cells.The increased production of reactive species is related to an excessive metabolic activation, for example, from an intense physical exercise or an excessive caloric intake (1). In physiological con-ditions, muscle fibers are provided with an anti-oxidant system able to keep under control the ex-cessive production of Reactive Oxygen Species (ROS). Endogenous and exogenous antioxidants are in-volved in countering the damage caused by reac-tive chemical species on muscle skeletal system. High-intensity training is associated with in-creased oxidative stress, because of the muscular effort required and the activation of all the meta-bolic pathways for ATP synthesis. Rowing is very demanding of high power maintained over time, mostly produced from aerobic metabolism (2). The aim of this study was to evaluate the reduc-ing activity in plasma and in erythrocytes in a group of rowers compared to a group of sedenta-ry subjects, and then to evaluate the efficiency of the trans-plasma membrane electron transport (TPMET), also known as PMRS, in the erythro-cytes of rowers as a compensatory mechanism of cellular redox homeostasis. Twenty-six healthy volunteers who did not practice physical activity at a competitive level (control subjects group) (26.6±2.2 yr) and twenty-two professional rowers were recruited (18.6±3.1 yr). Venous blood sam-ples were collected from rowers and control group after overnight fast. After centrifugation at 3000 rpm for 10 min at 4 °C, plasma was separated from red blood cells. The resultant plasma was transferred to micro centrifuge tubes and used at least in part for ferric-reducing activi-ty power (FRAP) assay. Red blood cells, after removal of buffy coat and upper 15% of the packed red blood cells, were washed two times with cold PBS (3). The ferric reducing activity in plasma and erythrocytes (FRAP) assay was per-formed (4). The PMRS activity was evaluated by reduction of 1 mM-ferricyanide (FIC) solution in PBS (pH 7.4) in ferrocyanide (FOC), using 1, 10-phenanthroline as an indicator and measuring ab-sorption at 510 nm. All analyses were performed using GraphPad Prism 5 (GraphPad Software Inc., Chicago, IL, USA). The statistical signific-ance level was set at PThe main finding of this study concern the activi-ty of plasma membrane redox system (PMRS): it has been elevated of 35% in RBCs from rowers than in RBCs from untrained group. The PMRS operated to maintain the ascorbate level in plas-ma, concerning the compensatory/protective mechanism. …
A new method in simultaneous estimation of Kinect-V2 sensor calibration using shuffled frog leaping algorithm

Calibration of color and infra-red cameras is the fundamental step in almost every 2D or 3D image processing applications and pre-processing of images and videos. This article presents a novel method for estimation of 19 parameters of RGB and depth camera calibration in Kinect sensor, simultaneously. The proposed algorithm is based on applying shuffled frog leaping algorithm (SFLA) for deep optimization and estimation all parameters of intrinsic, extrinsic and lens distortions of cameras. This algorithm does not need the initial estimation for optimization and it can avoid trapping into local minima. Using non-direct estimation, we achieve middle computing matrices such as homography matrix, used in pinhole camera model. Re-projection error criteria is defined as the objective function in this algorithm. The radial lens distortion is estimated using SFLA. Kinect version 2 sensor is used in this research and experimental results show the proposed method is more efficient and accurate in compare with traditional numerical solutions.
The Well-Separated Pair Decomposition and Its Applications

Computational geometry is concerned with the design and analysis of algorithms that solve problems on geometric data in R, where the dimension d is a constant. A large part of the field has been devoted to problems that involve distances determined by pairs of points in a given point set. Given a set S of n points in R, we may wish to compute a pair p, q of distinct points in S whose distance is minimum, the k smallest distances among the ( n 2 ) pairwise distances, the nearest neighbor of each point of S, or the minimum spanning tree of S. Most problems of this type can be rephrased as a graph problem on the complete Euclidean graph on S, in which each edge pq has a weight being the Euclidean distance |pq| between p and q. Since the number of edges in this graph is Θ(n), many problems involving pairwise distances can trivially be solved in O(n) time. Even though the complete Euclidean graph has size Θ(n), it can be represented in Θ(n) space: It is clearly sufficient to only store the points of S, because the weight of any edge can be computed in O(1) time. This leads to the question whether distance problems can be solved in subquadratic time, possibly at the cost of obtaining an approximate solution. For many of these problems, subquadratic algorithms have indeed been designed; see for example the books by Preparata and Shamos [21] and de Berg et al. [11], and the survey papers by Bern and Eppstein [5], Eppstein [12], and
Meanings Over Time of Working as a Nurse in Elderly Care

Background: Although registered nurses (RNs) play a central role in the care of older persons, their work in elderly care has historically been described as “low status” in nursing. This is especially problematic due to the global issue of RN turnover, but there is still little evidence of how to change this trend. Better understanding is needed of the reasons why RNs work in elderly care, as well as knowledge of whether these reasons have changed over time. Aim: The aim was to explore the meaning of working in elderly care, over time, from the perspective of RNs. Method: We interviewed thirteen RNs working in nursing homes, six of them in 2000 and the remaining seven in 2012, and analysed the resulting data using Interpretive Description. Results: The results show similarities and differences over time in the RNs’ reasoning about the meaning of their work with older persons, from a focus on obstacles to a view of opportunities. Conclusion: An RN’s intention to continue working in elderly care might be based on their beliefs; their view of older people, and their experiences of being able to influence the care. Managing this knowledge could be an essential factor in reversing the historical trend of RN work in elderly care being seen as low status, and the increasing turnover in such nurses. Our results could stimulate reflection on daily care and beliefs about caring for older persons.
Visualization for Classification Problems , with Examples Using Support Vector Machines

In the simplest form support vector machines (SVM) define a separating hyperplane between classes generated from a subset of cases, called support vectors. The support vectors “mark” the boundary between two classes. The result is an interpretable classifier, where the importance of the variables to the classification, is identified by the coefficients of the variables defining the hyperplane. This paper describes visual methods that can be used with classifiers to understand cluster structure in data. The study leads to suggestions for adaptations to the SVM algorithm and ways for other classifiers to borrow from the SVM approach to improve the result. The end result for any data problem is a classification rule that is easy to understand with similar accuracy.