Miracle-dz/UniFAR-FTUs huggingface dataset:
Water-saving aftertreatment of reactive dyed cotton fabrics in D5 medium

In order to match the non-aqueous reactive dyeing process of cotton fabric in decamethyl cyclopentasiloxane (D5), the water-saving aftertreatment process in D5 was projected and investigated. Taking the dye residual concentration of water-extracting solution of soaped sample as the evaluating index, the parameters such as the type and dosage of soaping agent, the amount of water in bath, soaping temperature, and duration of the novel soaping process were optimized by single-factor tests. The optimal soaping process was figured out as: 2.2 g L−1 hexadecyl trimethyl ammonium bromide dissolved in water (300% o.w.f), then mixed with D5 (bath ratio 1:30), and soaping the dyed fabric in the mixed solution for 10 min at 95 °C. The rinse procedure can be omitted by adopting the second soaping procedure. The color fastness of soaped samples was satisfactory.
KNIME4NGS: a comprehensive toolbox for next generation sequencing analysis

Summary Analysis of Next Generation Sequencing (NGS) data requires the processing of large datasets by chaining various tools with complex input and output formats. In order to automate data analysis, we propose to standardize NGS tasks into modular workflows. This simplifies reliable handling and processing of NGS data, and corresponding solutions become substantially more reproducible and easier to maintain. Here, we present a documented, linux-based, toolbox of 42 processing modules that are combined to construct workflows facilitating a variety of tasks such as DNAseq and RNAseq analysis. We also describe important technical extensions. The high throughput executor (HTE) helps to increase the reliability and to reduce manual interventions when processing complex datasets. We also provide a dedicated binary manager that assists users in obtaining the modules' executables and keeping them up to date. As basis for this actively developed toolbox we use the workflow management software KNIME. Availability and Implementation See http://ibisngs.github. io/knime4ngs for nodes and user manual (GPLv3 license). Contact robert.kueffner@helmholtz-muenchen.de. Supplementary information Supplementary data are available at Bioinformatics online.
Medical data mining: A case study of a Paracoccidioidomycosis patient's database

Data mining applied to medical databases is a challenging process. The unavailability of large sources of data and data complexity are some of the difficulties encountered. This is especially true for rare and neglected diseases. Those databases are, in general, relatively small, wide and sparse, making them very challenging to analyze. There are also ethical, legal and social issues regarding privacy and clinical validation of the findings. This work proposes a way of dealing with this challenge with a case study of data mining applied in a Paracoccidioidomycosis (PCM) patients database. Paracoccidioidomycosis (PCM) is a typical Brazilian disease, caused by the yeast Paracoccidioides brasiliensis. This disease represents an important Public Health issue, due to its high incapacitating potential and the amount of premature deaths it causes if untreated. This paper discusses methods for the analysis of this complex dataset, to help increase the understanding of both the disease and this type of data. Despite the challenges of the dataset, some interesting findings were made being: flaws in form filling protocols, notably the lack of chest X-ray in 40% of the records; the discovery of a possible new relation between smoking habits and PCM evolution time. The average evolution time for smoking patients was 2.8 times longer; the successful classification/prediction of the cutaneous form of the disease with a 93% precision rate are some of the discoveries made.
High-throughput trapping of secretory pathway genes in mouse embryonic stem cells

High-throughput gene trapping is a random approach for inducing insertional mutations across the mouse genome. This approach uses gene trap vectors that simultaneously inactivate and report the expression of the trapped gene at the insertion site, and provide a DNA tag for the rapid identification of the disrupted gene. Gene trapping has been used by both public and private institutions to produce libraries of embryonic stem (ES) cells harboring mutations in single genes. Presently, ∼66% of the protein coding genes in the mouse genome have been disrupted by gene trap insertions. Among these, however, genes encoding signal peptides or transmembrane domains (secretory genes) are underrepresented because they are not susceptible to conventional trapping methods. Here, we describe a high-throughput gene trapping strategy that effectively targets secretory genes. We used this strategy to assemble a library of ES cells harboring mutations in 716 unique secretory genes, of which 61% were not trapped by conventional trapping, indicating that the two strategies are complementary. The trapped ES cell lines, which can be ordered from the International Gene Trap Consortium (), are freely available to the scientific community.
Mild traumatic brain injury in soldiers returning from combat

During times of war, advances in civilian medical practice often occur from lessons learned treating battlefield injuries, especially true for the field of traumatic brain injury (TBI). September 11, 2001, is a sentinel date, after which over 2 million US military service members were deployed to Afghanistan and Iraq (Operation Enduring Freedom [OEF] and Operation Iraqi Freedom [OIF]). Estimates (dvbic.dcoe.mil) indicate that more than 350,000 US service members have sustained a TBI, 82.3% mild TBI (mTBI; synonymous with concussion). Prior to 2001, there were few military mTBI cohort studies (figure). With the high prevalence of mTBI in OEF/OIF, the dramatic increase in mTBI research is obvious, with military-sponsored studies addressing many important questions, including how to assess, train, treat, and track service members with such injuries, including documenting duration of persisting symptoms.
Monitoring of minimal residual disease in adult acute myeloid leukemia using peripheral blood as an alternative source to bone marrow.

BACKGROUND AND OBJECTIVES To date, bone marrow (BM) is the most common source of cells to use in order to assess minimal residual disease (MRD) in acute myeloid leukemia (AML). In the present study, we investigated whether peripheral blood (PB) could be an alternative source of cells for monitoring MRD in AML. DESIGN AND METHODS Fifty patients with AML were monitored for MRD after the achievement of complete remission. Using multiparametric flow cytometry we compared the levels of MRD in 50 and 48 pairs of BM and PB after induction and consolidation, respectively. RESULTS After induction and consolidation therapy, the findings in BM and PB were significantly concordant (r=0.86 and 0.82, respectively, p<0.001 for both comparisons). The cut-off value of residual leukemic cells in PB which correlated with outcome was 1.5x10 (-4). Thirty-three of 43 (77%) patients with >1.5x10 (-4)residual leukemic cells in PB after induction had a relapse, whereas the seven patients with lower levels did not (p=0.0002). After consolidation, 38 patients had a level of MRD >1.5x10 (-4)and 31 (82%) had a relapse; nine out of the remaining ten patients, whose levels of MRD were below 1.5x10 (-4), are still relapse-free (p=0.00006). In multivariate analysis, PB MRD status at the end of consolidation was found to have a significant effect on relapse-free survival (p=0.036). INTERPRETATION AND CONCLUSIONS These preliminary results indicate that: (i) PB evaluation can integrate BM assessment for MRD detection in patients with AML; (ii) PB MRD status at the end of consolidation therapy may provide useful prognostic information.
Torque ripple minimization of PMSM using PI type iterative learning control

Torque ripples due to cogging torque, current measurement errors and non-sinusoidal flux distribution restrict application of PMSM in direct drive system. In this paper, a method based on PI type iterative learning control (ILC) is presented to suppress the ripple. Tuning method of the controller is given in detail, which ensures stability and convergence of the system. Effect of controller parameters on its performance is discussed. Compared with the existing ILC compensatory strategy, the proposed method needs no estimation or close loop control of the electromagnetic torque, which simplifies structure of the controller. Simulating and experimental results verify that ripple of q axis current is reduced obviously, which consequently leads to desired torque ripple restriction performance.
AGEM: Adaptive Greedy-Compass Energy-Aware Multipath Routing Protocol for WMSNs

This paper presents an Adaptive Greedy-compass Energy-aware Multipath protocol (AGEM), a novel routing protocol for wireless multimedia sensors networks (WMSNs). AGEM uses sensors node positions to make packet forwarding decisions. These decisions are made online, at each forwarding node, in such a way that there is no need for global network topology knowledge and maintenance. AGEM routing protocol performs load-balancing to minimize energy consumption among nodes using twofold policy: (1) smart greedy forwarding, based on adaptive compass and (2) walking back forwarding to avoid holes. Performance evaluations of AGEM compared to GPSR (Greedy Perimeter Stateless Routing) show that AGEM can: (a) maximize the network lifetime, (b) guarantee quality of service for video stream transmission, and (c) scale better on densely deployed wireless sensors network.
Perturbed iron distribution in Alzheimer's disease serum, cerebrospinal fluid, and selected brain regions: a systematic review and meta-analysis.

BACKGROUND The homeostasis and physiological role of iron in Alzheimer's disease (AD) has been debated for decades. Overall, it has been difficult to reach a consensus to prove marked disease-associated changes in the iron content of the AD brain, blood, or cerebrospinal fluid (CSF). OBJECTIVES We sought to contribute to resolve this issue by quantifying the iron content in serum, CSF, and sub-regions of the AD brain. METHODS We conducted a comprehensive systematic meta-analysis and review of multiple observational studies till October 2013 that investigated the iron content in AD serum, CSF, or brain tissue. RESULTS 2,556 publications were screened. Forty-three eligible studies with 1,813 AD patients and 2,401 healthy controls were identified. Twenty-one studies investigated the serum iron in AD while seven and nineteen studies investigated the CSF iron and various brain regions iron respectively. Our meta-analysis showed that serum iron was significant lower in AD than healthy controls. CSF iron appeared not to be affected by AD although more studies are required due to the relative small number of CSF studies reported to date. We critically analyzed iron content in twelve selective brain regions by separated meta-analyses using cross-referenced statistical methods. We found that eight specific brain regions had higher iron concentrations that correlated with the clinical diagnosis of AD in a statistically validated manner. CONCLUSIONS These data provided rigorous statistical support for the model that iron homeostasis was changed in AD patients, including the finding of lower iron in their serum and evidence for iron overload in several specific brain regions.
Nonconvex model predictive control for commercial refrigeration

We consider the control of a commercial multi-zone refrigeration system, consisting of several cooling units that share a common compressor, and is used to cool multiple areas or rooms. In each time period we choose cooling capacity to each unit and a common evaporation temperature. The goal is to minimise the total energy cost, using real-time electricity prices, while obeying temperature constraints on the zones. We propose a variation on model predictive control to achieve this goal. When the right variables are used, the dynamics of the system are linear, and the constraints are convex. The cost function, however, is nonconvex due to the temperature dependence of thermodynamic efficiency. To handle this nonconvexity we propose a sequential convex optimisation method, which typically converges in fewer than 5 or so iterations. We employ a fast convex quadratic programming solver to carry out the iterations, which is more than fast enough to run in real time. We demonstrate our method on a realistic model, with a full year simulation and 15-minute time periods, using historical electricity prices and weather data, as well as random variations in thermal load. These simulations show substantial cost savings, on the order of 30%, compared to a standard thermostat-based control system. Perhaps more important, we see that the method exhibits sophisticated response to real-time variations in electricity prices. This demand response is critical to help balance real-time uncertainties in generation capacity associated with large penetration of intermittent renewable energy sources in a future smart grid.
Combustor Exhaust Temperature Nonuniformity Sensing Using Diode Laser Absorption

iii ACKNOWLEDGEMENTS This thesis is the culmination of many years of learning and research at The Georgia Institute of Technology. None of this would have been possible without the help and support of my advisor, Dr. Jerry Seitzman, whom I would like to extend my deepest thanks. He provided me with guidance and mentoring as I developed my academic, research, and communication skills, as well as help me grow my confidence and sense of fulfillment. In addition, I would like to thank my reading committee for taking the time to familiarize themselves with my research and provide useful comments and questions. I would also like to thank the research engineers, especially David Scarborough and John Holthaus, and the many students in the Combustion Lab for helping me find my way around, setting up my experiments and studying for the qualifiers. Thanks also to my many friends who made my stay in Atlanta so enjoyable and memorable. And finally, my thoughts and thanks go to my wonderful wife, Nicol, who gives me the strength and the love that nourishes me, supports me, and makes me be a better person. And to my loving family who has been my model in life and without whom this PhD would have not been possible.
The effects of corticotrophin‐releasing factor and two antagonists on breathing movements in fetal sheep.

1. The respiratory effects of corticotrophin‐releasing factor (CRF) and the CRF antagonists alpha‐helical CRF 9‐41 (alpha hCRF) and [DPhe 12, Nle 21‐38] rCRF (12‐41) (DPhe CRF) have been studied in unanaesthetized fetal lambs of 125‐140 days gestation. 2. CRF when given as a 10 micrograms bolus followed by a 5 micrograms h‐1 infusion into a lateral cerebral ventricle caused prolonged continuous fetal breathing movements which were stimulated in both amplitude and frequency but which did not persist during hypoxia. 3. Lower doses of CRF (20 ng bolus followed by 10 ng h‐1) increased the amplitude but not the frequency of fetal breathing movements which did not become continuous. 4. At higher doses (20 micrograms bolus followed by 10‐15 micrograms h‐1) CRF induced cerebral convulsions which were also associated with fetal breathing movements of increased amplitude and frequency. 5. The CRF antagonists alpha hCRF and DPhe CRF both inhibited fetal breathing movements and induced a prolonged apnoea which was resistant to the stimulatory effects of 5‐6% hypercapnia. 6. We conclude that CRF stimulates breathing movements in the fetal lamb. The finding that administration of the CRF antagonists alone cause apnoea suggests that CRF may have a tonic role in the regulation of fetal breathing movements.
Increased Angiotensin II Contraction of the Uterine Artery at Early Gestation in a Transgenic Model of Hypertensive Pregnancy Is Reduced by Inhibition of Endocannabinoid Hydrolysis

Increased vascular sensitivity to angiotensin II (Ang II) is a marker of a hypertensive human pregnancy. Recent evidence of interactions between the renin–angiotensin system and the endocannabinoid system suggests that anandamide and 2-arachidonoylglycerol may modulate Ang II contraction. We hypothesized that these interactions may contribute to the enhanced vascular responses in hypertensive pregnancy. We studied Ang II contraction in isolated uterine artery (UA) at early gestation in a rat model that mimics many features of preeclampsia, the transgenic human angiotensinogen×human renin (TgA), and control Sprague–Dawley rats. We determined the role of the cannabinoid receptor 1 by blockade with SR171416A, and the contribution of anandamide and 2-arachidonoylglycerol degradation to Ang II contraction by inhibiting their hydrolyzing enzyme fatty acid amide hydrolase (with URB597) or monoacylglycerol lipase (with JZL184), respectively. TgA UA showed increased maximal contraction and sensitivity to Ang II that was inhibited by indomethacin. Fatty acid amide hydrolase blockade decreased Ang IIMAX in Sprague–Dawley UA, and decreased both Ang IIMAX and sensitivity in TgA UA. Monoacylglycerol lipase blockade had no effect on Sprague–Dawley UA and decreased Ang IIMAX and sensitivity in TgA UA. Blockade of the cannabinoid receptor 1 in TgA UA had no effect. Immunolocalization of fatty acid amide hydrolase and monoacylglycerol lipase showed a similar pattern between groups; fatty acid amide hydrolase predominantly localized in endothelium and monoacylglycerol lipase in smooth muscle cells. We demonstrated an increased Ang II contraction in TgA UA before initiation of the hypertensive phenotype. Anandamide and 2-arachidonoylglycerol reduced Ang II contraction in a cannabinoid receptor 1–independent manner. These renin–angiotensin system-endocannabinoid system interactions may contribute to the enhanced vascular reactivity in early stages of hypertensive pregnancy.
The Use of a Kinematic Hardening Model for Estimating Subgrade Stiffness in Layered-elastic Analyses

It is well known that subgrade stiffness is dependent on stress level; it is not a simple function of California bearing ratio (CBR). A procedure for estimating the subgrade stiffness using a constitutive soil model based on critical state soil mechanics is proposed. The procedure uses a kinematic hardening model to establish stress changes in the subgrade due to the application of a wheel load. These stress changes are then applied to simulated triaxial samples of subgrade clay using the same model for a number of cycles to quickly determine appropriate resilient moduli for input to a multi-layered elastic analysis. Comparison of the resilient deformation predicted by the multi-layered elastic analysis with that determined rigorously using the full elastic–plastic analysis for the pavement, shows that the kinematic model can be used to estimate subgrade stiffness from simulated triaxial tests. The kinematic hardening model requires only eight parameters which can be determined from simple laboratory triaxial tests.
Computational Protein Design and Molecular Dynamics Simulations: A Study of Membrane Proteins, Small Peptides and Molecular Systems

Molecular design and modeling can provide stringent assessment of our understanding of the structure and function of proteins. Due to the subtleness of the interactions that largely stabilize proteins, computational methods have been particularly valuable in establishing practical, formal and physically grounded protocols to study the structure and function of these biomolecules. Especifically, computational protein design seeks to identify sequences that fold into a desired structure and have specific structural and functional properties using computational methodologies. Among current techniques, an entropy-based formalism that efficiently determines the number and composition of sequences satisfying a predefined set of constraints seems particularly promising and powerful. Complementary to this methodology are the well-established molecular dynamics simulation techniques that have been extensively used to study structure, function and dynamics of biologically relevant systems. Herein different studies of systems using computational techniques to address particular molecular problems are described. Efforts to redesign membrane proteins to generate water-soluble variants were applied to a widely studied pentameric ligand-gated ion channel, the nicotinic acetylchoilne receptor (nAChR). NMR structures and binding studies demostrated the robustness and applicability of the computational design approach. Toward the creation of water-soluble variants of a G protein–coupled receptor (GPCR), comparative modeling and docking calculations were used to investigate the structure of the human μ opioid receptor and presented in light of previous mutagenesis studies of structure and agonistinduced activation. Candidate peptides for possible therapeutic agents were computationally analyzed. Peptide design, loop modeling and MD simulations were applied to investigate the stromal cell-derived factor-1&a; (SDF-1&a;). SDF-1&a; displays promising therapeutic benefits to treat blood-supply related heart disease and elicit growth of microvasculature. Simplified analogs of SDF-1&a; exhibit enhanced therapeutic properties in cell-based assays. MD simulations provide insights about the molecular features of this enhancement. One simplified peptide offers a potentially clinically translatable neovasculogenic therapy. Lastly, MD simulations were utilized to analyze a molecule with hindered internal rotors, a tribenzylamine hemicryptophane. The molecule was characterized by different experimental and computational techniques. The structural and dynamic features of the hemicryptophane molecule make it an attractive starting point for controlling internal rotation of aromatic rings within molecular systems. Degree Type Dissertation Degree Name Doctor of Philosophy (PhD) Graduate Group Chemistry First Advisor Jeffery G. Saven This dissertation is available at ScholarlyCommons: http://repository.upenn. edu/edissertations/480
Fabrication of three-dimensional honeycomb structure for aeronautical applications using selective laser melting: a preliminary investigation

Purpose – The purpose of this paper was to investigate the feasibility on design and production of a three-dimensional honeycomb based on selective laser melting (SLM) technique for use in aeronautical application. Design/methodology/approach – Various polyhedrons were investigated using their mechanical property, i.e. strain energy density (SED), by means of finite element (FE) analysis for the suitability of use in aerospace application; the highest SED polyhedron was selected as a candidate polyhedron. From the FE analysis, the truncated octahedron (three-dimensional honeycomb) structure was considered to be the potential candidate. Polyhedron size and beam thickness of the open-cellular three-dimensional honeycomb structure were modelled and analysed to observe how the geometric properties influence the stiffness of the structure. One selected model of open-cellular honeycomb (unit cell size: 2.5 mm and beam thickness: 0.15 mm) was fabricated using SLM. The SLM prototypes were assessed by their mechan.