Miracle-dz/UniFAR-FTUs huggingface dataset:
Excitation-resolved fluorescence tomography with simplified spherical harmonics equations

Fluorescence tomography (FT) reconstructs the three-dimensional (3D) fluorescent reporter probe distribution inside biological tissue. These probes target molecules of biological function, e.g. cell surface receptors or enzymes, and emit fluorescence light upon illumination with an external light source. The fluorescence light is detected on the tissue surface and a source reconstruction algorithm based on the simplified spherical harmonics (SPN) equations calculates the unknown 3D probe distribution inside tissue. While current FT approaches require multiple external sources at a defined wavelength range, the proposed FT method uses only a white light source with tunable wavelength selection for fluorescence stimulation and further exploits the spectral dependence of tissue absorption for the purpose of 3D tomographic reconstruction. We will show the feasibility of the proposed hyperspectral excitation-resolved fluorescence tomography method with experimental data. In addition, we will demonstrate the performance and limitations of such a method under ideal and controlled conditions by means of a digital mouse model and synthetic measurement data. Moreover, we will address issues regarding the required amount of wavelength intervals for fluorescent source reconstruction. We will explore the impact of assumed spatially uniform and nonuniform optical parameter maps on the accuracy of the fluorescence source reconstruction. Last, we propose a spectral re-scaling method for overcoming the observed limitations in reconstructing accurate source distributions in optically non-uniform tissue when assuming only uniform optical property maps for the source reconstruction process.
Suboptimal maternal nutrition, during early fetal liver development, promotes lipid accumulation in the liver of obese offspring

Maternal nutrition during the period of early organ development can modulate the offspring's ability to metabolise excess fat as young adults when exposed to an obesogenic environment. This study examined the hypothesis that exposing offspring to nutrient restriction coincident with early hepatogenesis would result in endocrine and metabolic adaptations that subsequently lead to increased ectopic lipid accumulation within the liver. Pregnant sheep were fed either 50 or 100% of total metabolisable energy requirements from 30 to 80 days gestation and 100% thereafter. At weaning, offspring were made obese, and at ∼1 year of age livers were sampled. Lipid infiltration and molecular indices of gluconeogenesis, lipid metabolism and mitochondrial function were measured. Although hepatic triglyceride accumulation was not affected by obesity per se, it was nearly doubled in obese offspring born to nutrient-restricted mothers. This adaptation was accompanied by elevated gene expression for peroxisome proliferator-activated receptor γ (PPARG) and its co-activator PGC1α, which may be indicative of changes in the rate of hepatic fatty acid oxidation. In contrast, maternal diet had no influence on the stimulatory effect of obesity on gene expression for a range of proteins involved in glucose metabolism and energy balance including glucokinase, glucocorticoid receptors and uncoupling protein 2. Similarly, although gene expressions for the insulin and IGF1 receptors were suppressed by obesity they were not influenced by the prenatal nutritional environment. In conclusion, excess hepatic lipid accumulation with juvenile obesity is promoted by suboptimal nutrition coincident with early development of the fetal liver.
Efficient and robust sensor data aggregation using linear counting sketches

Sensor networks have received considerable attention in recent years, and are often employed in the applications where data are difficult or expensive to collect. In these applications, in addition to individual sensor readings, statistical aggregates such as Min and Count over the readings of a group of sensor nodes are often needed. To conserve resources for sensor nodes, in-network strategies are adopted to process the aggregates. One primitive in-network aggregation strategy is the tree-based aggregation, where the aggregates are computed along a spanning tree over a sensor network. However, a shortcoming with the tree-based aggregation is that it is not robust against communication failures, which are common in sensor networks. One of the solutions to overcome this shortcoming is to enable multi-path routing, by which each node broadcasts its reading or a partial aggregate to multiple neighbors. However, multi-path routing based aggregation typically suffers from the problem of overcounting sensor readings. In this study, we propose using the linear counting sketches for multi-path routing based in-network aggregation. We claim that the use of the linear counting sketches makes our approach considerably more accurate than previous approaches using the same sketch space. Our approach also enjoys low variances in term of the aggregate accuracy, and low overheads either in computations or sketch space. Through extensive experiments with real-world and synthetic data, we demonstrate the efficiency and effectiveness of using the linear counting sketches as a solution for the in- network aggregation.
A specification invariant technique for operation cost minimisation in flow-graphs

In high-level synthesis, optimising area, time, and power in real-time applications are the prime objectives. A new model and technique are proposed, which minimise a weighted operation cost function for data-paths at an early stage in the synthesis process. The main target domain consists of lowly-multiplexed and hard-wired implementations of real-time DSP applications. The behavioral specification of an application is translated into a signal flow-graph, the operation cost (area/power) of which is minimised using algebraic transformations. A minimal set of elementary transformations are combined in a flexible way into composite transformations, which are used in an ascent/steepest descent search algorithm. Experiments show that this approach achieves optimal or close to optimal results with very few transformations. The technique is invariant to changes in the specification, as long as these retain the bit-true input/output behaviour. <<ETX>>
Fixing the broken time machine: Consistency-aware checkpointing for energy harvesting powered non-volatile processor

Energy harvesting has become a favorable alternative to batteries for wearable embedded systems since it is more environmental and user friendly. However, harvested energy is intrinsically unstable, which could frequently interrupt a processor's execution. To tackle this problem, nonvolatile processors have been proposed to checkpoint the whole volatile processor state into attached non-volatile memories periodically. When power resumes, the processor can copy the checkpointed state back to volatile memories and continue execution. However, without careful consideration, the process of checkpointing and resuming could cause inconsistency among different memory addresses and lead to irreversible errors. In this paper, we present a consistency aware checkpointing scheme that ensures correctness for all checkpoints. The proposed technique efficiently identifies all possible inconsistency positions in programs and inserts auxiliary code to ensure correctness. Evaluation results show that the proposed checkpointing technique can successfully eliminate inconsistency errors and greatly reduce the checkpointing overhead.
Your Body Is the Temple

Colorectal cancer (CRC) is third in cancer incidence and mortality, due in part to lack of awareness and low rates of screening. The purpose of the present study was to evaluate the efficacy of a spiritually based CRC educational intervention delivered by trained Community Health Advisors, in Alabama churches. The aim of the intervention was to increase knowledge and awareness of CRC and early detection, and to eventually increase CRC screening rates. Participants age-eligible for screening (N = 122) completed baseline, 6-month, and 12-month surveys by telephone. Increases in CRC knowledge, perceived benefits of CRC screening, and awareness of the screening modalities and decreases in perceived barriers to screening suggested that this type of intervention may be promising for CRC control and should be examined further.
Differential evolution with stochastic fractal search algorithm for global numerical optimization

Evolutionary algorithms are successfully developed to handle the challenges in solving optimization problems with complex landscapes. Differential evolution proves its efficiency as a powerful evolutionary algorithm to solve complex optimization problems with diverse characteristics. In this paper, we aim at designing an enhanced evolutionary algorithm that embeds Differential Evolution in Stochastic Fractal Search. Stochastic Fractal Search is developed recently as a powerful metaheuristic algorithm that imitates the natural phenomenon of growth and uses the diffusion process based on random fractals. In this paper, we introduce a new adjustment to the Diffusion Process of Stochastic Fractal Search. The proposed algorithm namely, SFS-DPDE-GW, uses Differential Evolution in the Diffusion Process along with the Gaussian Walks to enhance the search. To validate the performance of our algorithm, a challenging test suite of 30 benchmark functions from the IEEE CEC2014 real parameter single objective competition is used. The proposed combination clearly enhances the performance of Stochastic Fractal Search and increases the efficiency of the update process which was incorporated after Diffusion process. Comparative studies show that the new algorithm has a superior performance compared to the original Stochastic Fractal Search and other recent state-of-the-art algorithms.
Specific Acquired Resistance in Mice Immunized with Killed Mycobacteria

Past attempts to raise resistance against Mycobacterium tuberculosis using various preparations of killed mycobacteria have questioned the specificity of the generated immune response. In the present study, we have focused on the protective efficacy of experimental vaccines based on killed mycobacteria. We demonstrate that killed mycobacteria can confer high levels of protection, which can be adoptively transferred to recipient T‐cell‐deficient mice. Moreover, protective antigens can be found in the cell wall, membrane and cytosol of the mycobacterial cell, and hence emphasize the importance of searching for protective antigens in various compartments of the mycobacterial cell.
Exposure-Dependent Control of Malaria-Induced Inflammation in Children

In malaria-naïve individuals, Plasmodium falciparum infection results in high levels of parasite-infected red blood cells (iRBCs) that trigger systemic inflammation and fever. Conversely, individuals in endemic areas who are repeatedly infected are often asymptomatic and have low levels of iRBCs, even young children. We hypothesized that febrile malaria alters the immune system such that P. falciparum re-exposure results in reduced production of pro-inflammatory cytokines/chemokines and enhanced anti-parasite effector responses compared to responses induced before malaria. To test this hypothesis we used a systems biology approach to analyze PBMCs sampled from healthy children before the six-month malaria season and the same children seven days after treatment of their first febrile malaria episode of the ensuing season. PBMCs were stimulated with iRBC in vitro and various immune parameters were measured. Before the malaria season, children's immune cells responded to iRBCs by producing pro-inflammatory mediators such as IL-1β, IL-6 and IL-8. Following malaria there was a marked shift in the response to iRBCs with the same children's immune cells producing lower levels of pro-inflammatory cytokines and higher levels of anti-inflammatory cytokines (IL-10, TGF-β). In addition, molecules involved in phagocytosis and activation of adaptive immunity were upregulated after malaria as compared to before. This shift was accompanied by an increase in P. falciparum-specific CD4+Foxp3− T cells that co-produce IL-10, IFN-γ and TNF; however, after the subsequent six-month dry season, a period of markedly reduced malaria transmission, P. falciparum–inducible IL-10 production remained partially upregulated only in children with persistent asymptomatic infections. These findings suggest that in the face of P. falciparum re-exposure, children acquire exposure-dependent P. falciparum–specific immunoregulatory responses that dampen pathogenic inflammation while enhancing anti-parasite effector mechanisms. These data provide mechanistic insight into the observation that P. falciparum–infected children in endemic areas are often afebrile and tend to control parasite replication.
Maturation, Activation, and Protection of Dendritic Cells Induced by Double-stranded RNA

The initiation of an immune response is critically dependent on the activation of dendritic cells (DCs). This process is triggered by surface receptors specific for inflammatory cytokines or for conserved patterns characteristic of infectious agents. Here we show that human DCs are activated by influenza virus infection and by double-stranded (ds)RNA. This activation results not only in increased antigen presentation and T cell stimulatory capacity, but also in resistance to the cytopathic effect of the virus, mediated by the production of type I interferon, and upregulation of MxA. Because dsRNA stimulates both maturation and resistance, DCs can serve as altruistic antigen-presenting cells capable of sustaining viral antigen production while acquiring the capacity to trigger naive T cells and drive polarized T helper cell type 1 responses.
Analysis of Blog Spams and Collaborative Blog Spam Filtering Using Adaptive Percolation Search Analysis of Blog Spams and Collaborative Blog Spam Filtering Using Adaptive Percolation Search

We provide basic analysis on blog spams, which little is known about before. Then, we propose a novel collaborative filtering method for link spams on blogs. The key idea is to rely on manual identification of spams and share this information about spams through a network of trust. The blogger who has identified a spam tells a small number of fellow bloggers (content implantation), and those who have not heard about it start a search using an adaptive percolation search, combined with content implantation, they contract the information about identified spam in only a fraction of the query period time without producing large volume of traffic.
Compositional representations of language structures in multilingual joint-vector space

After the recent developments in Artificial Neural Networks and deep learning techniques, representation learning has become the focus of many research interests. In the field of Natural Language Processing, representation learning techniques have gained many implementation advances and improved different tasks compared to any other method. One of the primary research topics in this area is to construct compositional representations of discrete language structures in multilingual joint-vector space. In this thesis study, several techniques from deep learning and NLP are combined to investigate their potential impact on NLP tasks. For this purpose, four different composition vector models (CVM) by using tokens and morphemes as basic language structures are studied. To construct tokens and morphemes, first, a parallel corpus is segmented into discrete objects via tokenization and morphological analysis. Several hierarchical composition methods via bilingual method are employed to construct the embeddings of these structures. Bilingual models are trained by using sentence-aligned corpora for four languages. The models learn how to employ compositional vector models and construct embeddings of sentence constituents as well. Two different test scenarios are performed to evaluate different CVMs. The first one is paraphrase test. In this case, the bilingual models using CVMs are trained with each language pair L1-L2 ( English, Turkish, German and French) parallel corpus. Then the models are tested by evaluating their performance in finding the corresponding pairs correctly from 100 randomly selected sentences from each L1-L2 pair. The other test scenario is cross-lingual document classification. In this case, the trained models are employed by a document classifier model to evaluate their performance in classification task by first training in L1 documents and then testing with L2 documents.
Identification of two essential aspartates for polymerase activity in parainfluenza virus L protein by a minireplicon system expressing secretory luciferase

Gene expression of nonsegmented negative‐strand RNA viruses (nsNSVs) such as parainfluenza viruses requires the RNA synthesis activity of their polymerase L protein; however, the detailed mechanism of this process is poorly understood. In this study, a parainfluenza minireplicon assay expressing secretory Gaussia luciferase (Gluc) was established to analyze large protein (L) activity. Measurement of Gluc expression in the culture medium of cells transfected with the minigenome and viral polymerase components enabled quick and concise calculation of L activity. By comparing the amino acid sequences in conserved region III (CRIII), a putative polymerase‐active domain of the L protein, two strictly conserved aspartates were identified in all families of nsNSV. A series of L mutants from human parainfluenza virus type 2 and parainfluenza virus type 5 showed that these aspartates are necessary for reporter gene expression. It was also confirmed that these aspartates are important for the production of viral mRNA and antigenome cRNA, but not for a polymerase‐complex formation. These findings suggest that these two aspartates are key players in the nucleotidyl transfer reaction using two metal ions.
Trägerung lasergenerierter Goldnanopartikel in flüssigen und überkritischen Medien

Die vorliegende Arbeit („Tragerung lasergenerierter Goldnanopartikel in flussigen und uberkritischen Medien“) behandelt die Herstellung von porosen und unporosen Nanostrukturen basierend auf der lasergestutzten Synthese von Nanopartikeln sowie deren Tragerung auf oxidischen Materialien unter Anwendung flussiger und uberkritischer Fluide. Die Arbeit ist dabei in zwei Teile unterteilt worden. Im ersten Abschnitt werden am Beispiel der laserbasierten Herstellung von Goldnanopartikeln (AuNP) kostenneutrale Methoden zur Steigerung der Produktivitat sowohl fur die Laserablation als auch Laserfragmentierung erarbeitet. Zusatzlich werden fur die Laserfragmentierung anhand experimenteller Methoden in Kombination mit einer Simulation Bedingungen ermittelt bzw. postuliert, um zukunftig Massendurchsatze bei der Laserfragmentierung im Gramm pro Stunde Masstab zu realisieren. Anschliesend wird der Einfluss von Sauerstofffehlstellen auf die Tragerungseffizienz von AuNP auf unporosen TiO2 Strukturen bei elektrostatisch inhibierten Bedingungen, unter Berucksichtigung von Ergebnissen der DLVO-Theorie, evaluiert. Abschliesend dazu wird die katalytische Aktivitat und Stabilitat der hergestellten Katalysatoren basierend auf einer selektiven Oxidationsreaktion bei unterschiedlichen AuNP Beladungen untersucht, mit einem kommerziellen Referenzkatalysator verglichen und durch eine auf der Wechselwirkung von Sauerstofffehlstellen und AuNP basierenden Wirkhypothese diskutiert. Im zweiten Teil der Arbeit ist erstmalig unter Anwendung von uberkritischem (sc.) CO2 der diffusionsgetriebene Eintrag von lasergenerierten AuNP (hergestellt in primaren Alkoholen bzw. Aceton) in die Porenstruktur von mesoporosem SiO2 umgesetzt worden. Im Falle von wassrigen AuNP wurde jedoch kein Phasentransfer der AuNP in die sc. CO2 Phase beobachtet. Dennoch konnte fur AuNP in Wasser eine kontrollierbare Agglomeration und deren Einflussgrosen beschrieben werden. Bei der Tragerung der AuNP (hergestellt in primaren Alkoholen bzw. Aceton) unter uberkritischen Bedingungen konnte die mittlere freie Weglange der CO2 Molekule als wesentlicher Einflussfaktor auf die Tragerungseffizienz identifiziert werden. Eine hohe Depositionseffizienz wird dabei durch eine moglichst grose mittlere freie Weglange der CO2 Molekule erreicht (erhohte Temperatur und geringe Drucke oberhalb des kritischen Punktes von CO2). Bezuglich der Eindringtiefe konnten erste Ergebnisse in Verbindung mit der Literatur zeigen, dass eine effektive Porendiffusion nur bei einem mindestens um den Faktor drei hoheren Porendurchmesser verglichen zum Durchmesser der Nanopartikel moglich ist. Die vorliegende Arbeit erweitert damit das Prinzip der lasergestutzten Herstellung von nicht porosen (Modell-) Katalysatoren auf porose (Modell-) Katalysatoren und vergrosert somit das Anwendungsgebiet der lasergestutzten Materialsynthese innerhalb der Katalysatorforschung und Katalysatorentwicklung.
The State of Coral Reef Ecosystems of the Northwestern Hawaiian Islands

INTRODUCTION AND SETTING The Northwestern Hawaiian Islands (NWHI) consist of small islands, atolls, submerged banks, and reefs, and stretch for more than 2,000 km northwest of the high windward main Hawaiian Islands (MHI; Figures 10.1 and 10.2). From Nihoa and Necker Island (~7 and 10 million years old respectively) to Midway and Kure Atolls (~28 million years old), the NWHI represent the older portion of the emergent archipelago (Juvik and Juvik, 1998). The majority of the islets and shoals remain uninhabited, although Midway, Kure, Laysan Island, and French Frigate Shoals have all been occupied for extended periods over the last century by various government agencies.
Effect of Maturation on Hemodynamic and Autonomic Control Recovery Following Maximal Running Exercise in Highly Trained Young Soccer Players

The purpose of this study was to examine the effect of maturation on post-exercise hemodynamic and autonomic responses. Fifty-five highly trained young male soccer players (12–18 years) classified as pre-, circum-, or post-peak height velocity (PHV) performed a graded running test to exhaustion on a treadmill. Before (Pre) and after (5th–10th min, Post) exercise, heart rate (HR), stroke volume (SV), cardiac output (CO), arterial pressure (AP), and total peripheral resistance (TPR) were monitored. Parasympathetic (high frequency [HFRR] of HR variability (HRV) and baroreflex sensitivity [Ln BRS]) and sympathetic activity (low frequency [LFSAP] of systolic AP variability) were estimated. Post-exercise blood lactate [La]b, the HR recovery (HRR) time constant, and parasympathetic reactivation (time-varying HRV analysis) were assessed. In all three groups, exercise resulted in increased HR, CO, AP, and LFSAP (P < 0.001), decreased SV, HFRR, and Ln BRS (all P < 0.001), and no change in TPR (P = 0.98). There was no “maturation × time” interaction for any of the hemodynamic or autonomic variables (all P > 0.22). After exercise, pre-PHV players displayed lower SV, CO, and [La]b, faster HRR and greater parasympathetic reactivation compared with circum- and post-PHV players. Multiple regression analysis showed that lean muscle mass, [La]b, and Pre parasympathetic activity were the strongest predictors of HRR (r2 = 0.62, P < 0.001). While pre-PHV players displayed a faster HRR and greater post-exercise parasympathetic reactivation, maturation had little influence on the hemodynamic and autonomic responses following maximal running exercise. HRR relates to lean muscle mass, blood acidosis, and intrinsic parasympathetic function, with less evident impact of post-exercise autonomic function.