Miracle-dz/UniFAR-FTUs huggingface dataset:
Highly Conductive PEDOT:PSS Electrode with Optimized Solvent and Thermal Post‐Treatment for ITO‐Free Organic Solar Cells

Highly conductive poly(3,4‐ethylenedioxythiophene):poly(styrenesulfonate) (PEDOT:PSS) films as stand‐alone electrodes for organic solar cells have been optimized using a solvent post‐treatment method. The treated PEDOT:PSS films show enhanced conductivities up to 1418 S cm−1, accompanied by structural and chemical changes. The effect of the solvent treatment on PEDOT:PSS has been investigated in detail and is shown to cause a reduction of insulating PSS in the conductive polymer layer. Using these optimized electrodes, ITO‐free, small molecule organic solar cells with a zinc phthalocyanine (ZnPc):fullerene C60 bulk heterojunction have been produced on glass and PET substrates. The system was further improved by pre‐heating the PEDOT:PSS electrodes, which enhanced the power conversion efficiency to the values obtained for solar cells on ITO electrodes. The results show that optimized PEDOT:PSS with solvent and thermal post‐treatment can be a very promising electrode material for highly efficient flexible ITO‐free organic solar cells.
Trends, Rhythms, and Aberrations in Global Climate 65 Ma to Present

Since 65 million years ago (Ma), Earth's climate has undergone a significant and complex evolution, the finer details of which are now coming to light through investigations of deep-sea sediment cores. This evolution includes gradual trends of warming and cooling driven by tectonic processes on time scales of 105to 107 years, rhythmic or periodic cycles driven by orbital processes with 104- to 106-year cyclicity, and rare rapid aberrant shifts and extreme climate transients with durations of 103 to 105 years. Here, recent progress in defining the evolution of global climate over the Cenozoic Era is reviewed. We focus primarily on the periodic and anomalous components of variability over the early portion of this era, as constrained by the latest generation of deep-sea isotope records. We also consider how this improved perspective has led to the recognition of previously unforeseen mechanisms for altering climate.
Analysis of Argonaute Complex Bound mRNAs in DU145 Prostate Carcinoma Cells Reveals New miRNA Target Genes

Posttranscriptional gene regulation by microRNAs (miRNAs) contributes to the induction and maintenance of prostate carcinoma (PCa). To identify mRNAs enriched or removed from Ago2-containing RISC complexes, these complexes were immunoprecipitated from normal prostate fibroblasts (PNFs) and the PCa line DU145 and the bound mRNAs were quantified by microarray. The analysis of Ago complexes derived from PNFs or DU145 confirmed the enrichment or depletion of a variety of mRNAs already known from the literature to be deregulated. Novel potential targets were analyzed by luciferase assays with miRNAs known to be deregulated in PCa. We demonstrate that the mRNAs of the death effector domain-containing protein (DEDD), the tumor necrosis factor receptor superfamily, member 10b protein (TNFRSF10B), the tumor protein p53 inducible nuclear protein 1 (TP53INP1), and the secreted protein, acidic, cysteine-rich (SPARC; osteonectin) are regulated by miRNAs miR-148a, miR-20a, miR-24, and miR-29a/b, respectively. Therefore, these miRNAs represent potential targets for therapy. Surprisingly, overexpression of miR-24 induced focus formation and proliferation of DU145 cells, while miR-29b reduced proliferation. The study confirms genes deregulated in PCa by virtue of their presence/absence in the Ago2-complex. In conjunction with the already published miRNA profiles of PCa, the data can be used to identify miRNA-regulated mRNAs.
Health Misinformation in Search and Social Media

People regularly use web search and social media to investigate health related issues. This type of Internet data might contain misinformation i.e incorrect information which contradicts current established medical understanding. If people are influenced by the presented misinformation in these sources, they can make harmful decisions about their health. Our research goal is to investigate the affect of Internet data on people's health. Our current findings suggest that people can be potentially harmed by search engine results. Furthermore, we successfully built a high precision approach to track misinformation in social media. In this paper, we briefly discuss our ongoing work results. Thereafter, we propose a research plan to understand possible mechanisms of misinformation's effect on people and possible impacts of these misinformation on public health.
When Can Antibiotic Treatments for Trachoma Be Discontinued? Graduating Communities in Three African Countries

Background Repeated mass azithromycin distributions are effective in controlling the ocular strains of chlamydia that cause trachoma. However, it is unclear when treatments can be discontinued. Investigators have proposed graduating communities when the prevalence of infection identified in children decreases below a threshold. While this can be tested empirically, results will not be available for years. Here we use a mathematical model to predict results with different graduation strategies in three African countries. Methods A stochastic model of trachoma transmission was constructed, using the parameters with the maximum likelihood of obtaining results observed from studies in Tanzania (with 16% infection in children pre-treatment), The Gambia (9%), and Ethiopia (64%). The expected prevalence of infection at 3 years was obtained, given different thresholds for graduation and varying the characteristics of the diagnostic test. Results The model projects that three annual treatments at 80% coverage would reduce the mean prevalence of infection to 0.03% in Tanzanian, 2.4% in Gambian, and 12.9% in the Ethiopian communities. If communities graduate when the prevalence of infection falls below 5%, then the mean prevalence at 3 years with the new strategy would be 0.3%, 3.9%, and 14.4%, respectively. Graduations reduced antibiotic usage by 63% in Tanzania, 56% in The Gambia, and 11% in Ethiopia. Conclusion Models suggest that graduating communities from a program when the infection is reduced to 5% is a reasonable strategy and could reduce the amount of antibiotic distributed in some areas by more than 2-fold.
Analysis of Tanzanian Biomass Consumption Using Artificial Neural Network

The growing biomass consumption in developing countries context is being driven by a mixture of concerns over energy security, sustainable development and the climate change mitigation. The development of the comprehensive, sustainable and efficient biomass energy sector policies, strategies and investments requires proper biomass utilization and planning which in fact has not yet received the attention it deserves in the developing countries policies. This paper aims are twofold; one being to demonstrate the practicability of the application of artificial neural network multilayer perceptron (ANN-MLP) in the analysis of the biomass energy consumption and two, to identify the demographic and economic indicators which works better in the analysis and prediction of biomass consumption in Tanzania. Three models made up of Tanzania rural, Tanzania urban and Tanzania population with the addition of economic indicators were formulated for the analysis. The ANN-MLP has shown promising results with the statistical correlation coefficient of 0.9972 indicating that it can be used for practical analysis and prediction of biomass energy consumption. Furthermore the results show the use of Tanzania population model in the analysis and prediction of biomass consumption gives better results in comparison to the Tanzania rural and Tanzania urban population models individually.
Nano-Micro Geometric Modeling Using Microscopic Image

In recent years, there are a lot of active researches on nano-micro manufacturing and metrology, since not only industrial fields but also medical fields require higher accuracy with respect to miniaturizing size of the target. However, we cannot make an effective use of three dimensional measurement data for the nano-micro design and manufacturing due to a wide variety of instruments, resolutions, and noises. In fact, the nano-micro geometric modeling is at an early stage of development in spite of its importance for the next generation. In order to find a solution to this problem, we propose to combine the multi-resolution processing with the microscopic images for high speed and non-destructive geometric modeling as well as for the homogeneous modeling from micro features to macro ones. This research includes measurement data tiling between different instruments, high resolution optical microscopic imaging, focus judgment of three dimensional microscopic data, and large scale point crowd processing. These built models are potentially applied to in-line inspections and numerical simulations. Therefore, the nano-micro geometric modeling contribute to further developments of ultra precise manufacturing and the biotechnology.
Coevolution at protein complex interfaces can be detected by the complementarity trace with important impact for predictive docking

Protein surfaces are under significant selection pressure to maintain interactions with their partners throughout evolution. Capturing how selection pressure acts at the interfaces of protein–protein complexes is a fundamental issue with high interest for the structural prediction of macromolecular assemblies. We tackled this issue under the assumption that, throughout evolution, mutations should minimally disrupt the physicochemical compatibility between specific clusters of interacting residues. This constraint drove the development of the so-called Surface COmplementarity Trace in Complex History score (SCOTCH), which was found to discriminate with high efficiency the structure of biological complexes. SCOTCH performances were assessed not only with respect to other evolution-based approaches, such as conservation and coevolution analyses, but also with respect to statistically based scoring methods. Validated on a set of 129 complexes of known structure exhibiting both permanent and transient intermolecular interactions, SCOTCH appears as a robust strategy to guide the prediction of protein–protein complex structures. Of particular interest, it also provides a basic framework to efficiently track how protein surfaces could evolve while keeping their partners in contact.
Verifikation von UML-Statecharts unter besonderer Berücksichtigung von Speicherverbrauch und Laufzeit des Model Checkers

Ein Model Checker verifiziert, ob ein Modell bestimmte Anforderungen erfullt. Eine Moglichkeit, das Verhalten von Softwaresystemen zu modellieren, sind endliche Automaten. Diese finden Einzug in die Unified Modelling Language in Form von Statecharts. UML-Statecharts konnen ein hohes Mas an Komplexitat erreichen, so dass sich ihr Zustandsraum nicht mehr komplett in den Hauptspeicher abbilden lasst. Dies fuhrt dazu, dass eine vollstandige Verifikation mit einem Model Checker nicht mehr moglich ist, da der gesamte Zustandsraum nicht mehr untersucht werden kann. Um diesem Problem zu begegnen, stellt diese Arbeit die domanenspezifische Sprache UDL (UML-Statechart Description Language), sowie eine Transformation von UDL in die Model Checker Eingabesprache Promela vor. Der Schwerpunkt der Sprache UDL und des Ubersetzungsprozesses liegt dabei auf der Generierung von effizientem Promelacode, der beim Verifizieren einen moglichst kleinen Zustandsraum belegt. Der Vorteil ist, dass durch diesen Ansatz auch grosere Modelle wieder verifizierbar werden. Die Machbarkeit des Ansatzes und die daraus entstehenden Vorteile werden anhand einer Fallstudie mit dem 3DBewegungstrackingsystem AssyControl demonstriert.
Long lasting underwater wireless sensors network for water quality monitoring in fish farms

This paper concerns the implementation of an efficient underwater acoustic network suitable for long lasting environmental monitoring in fish farming. Several hardware and software solutions have been designed and implemented to extend the network lifetime and to make the system autonomous and suitable for such an application scenario. The proposed system is composed of different components. The SUNSET Software Defined Communication Stack (SDCS) is used to provide networking capabilities to underwater nodes communicating acoustically through AppliCon SeaModem modems. The Hydrolab Series 5 probes are used to monitor the water quality. Lifetime of underwater nodes is extended through the use of a novel device that allows to harvest energy from underwater water currents via suitable propellers. In addition, novel sleep and wake up mechanisms have been designed and implemented into the underwater nodes to minimize the energy consumption of the system during the idle periods. The performance of the proposed system has been extensively evaluated in field by monitoring the water quality in three fish farming cages located in the Mediterranean Sea, Italy. The system has been connected to the Internet infrastructure allowing the users to easy interact with the underwater system in real-time. Our results confirm that the proposed system is suitable for long term monitoring providing a reliable and robust data collection scheme with an extended network life time.
A MATHEMATICAL DESCRIPTION OF THE FUNCTIONALITY OF CORRECTION FACTORS USED IN ALLOMETRY FOR PREDICTING HUMAN DRUG CLEARANCE

The functionality of the correction factors, maximum life-span potential (MLP), and brain weight (BrW) used in allometry is mathematically described. Correction by MLP or BrW is equivalent to a multiplication of some constants by the predicted values in humans from simple allometry, but they have no relationship to measured pharmacokinetic parameters in the animal species. The values of these constants (FMLP or FBrW) were calculated for some commonly used combinations of animal species. For all combinations of animal species, the value of FBrW is always greater than that of FMLP with a fold-increase of about 1.3 to 1.9. Different combinations of species give different values of FBrW and FMLP. In addition, the role of correction factors (MLP and BrW) or the “rule of exponents” (ROE) was evaluated. An intrinsic defect in using correction factors or ROE was revealed; different study designs will produce significantly different prediction results. However, ROE may still serve as a useful practical approach in predicting human CL since it was derived from real observations and has been applied to many examples.
Effects of environmental estrogens on tumor necrosis factor α-mediated apoptosis in MCF-7 cells

Environmental estrogens represent a class of compounds which have been shown to mimic the effects or activity of the naturally occurring ovarian hormone 17beta-estradiol. Given the role of 17beta-estradiol in cell survival in a number of systems, we wished to determine if environmental estrogens protect MCF-7 cells from apoptosis. Here we demonstrate that the organochlorine pesticides o, p' DDT and alachlor, like 17beta-estradiol, have the ability to suppress tumor necrosis factor alpha (TNF)-induced apoptosis in estrogen receptor (ER)-positive MCF-7 breast carcinoma cells. These compounds, however, did not affect TNF-induced apoptosis of the ER-negative MDA-MB-231 cell line. The ability of these compounds to suppress apoptosis in MCF-7 cells was correlated with an ER-dependent increase in Bcl-2 expression. Taken together these results demonstrate that estrogenic organochlorine pesticides like o, p' DDT and alachlor may partially mimic the primary endogenous estrogen, 17beta-estradiol, and function to suppress apoptosis in ER-responsive cells.
Tuning Approximate Computations with Constraint-Based Type Inference

Unreliable hardware can lead to great gains in energy efficiency, but it can be difficult to reason about how unreliable each operation in a computation may feasibly be. To make approximate computing viable, we need tools that can help programmers derive precision‐energy trade-offs for individual fine-grained operations while reasoning about the collective impact on the result quality. We formulate the problem of precision tuning as type inference over a system of types parameterized on their accuracy. Our type inference system generates numerical constraints and uses an SMT solver to produce parameters for unspecified types. Programmers can choose to provide explicit types where they make sense and depend on inference where the appropriate accuracy parameter is unclear. Remaining research challenges are discussed.
A Tighter Bound for Graphical Models

We present a method to bound the partition function of a Boltzmann machine neural network with any odd-order polynomial. This is a direct extension of the mean-field bound, which is first order. We show that the third-order bound is strictly better than mean field. Additionally, we derive a third-order bound for the likelihood of sigmoid belief networks. Numerical experiments indicate that an error reduction of a factor of two is easily reached in the region where expansion-based approximations are useful.
Organization and Evolution of Subtelomeric Satellite Repeats in the Potato Genome

Subtelomeric domains immediately adjacent to telomeres represent one of the most dynamic and rapidly evolving regions in eukaryotic genomes. A common feature associated with subtelomeric regions in different eukaryotes is the presence of long arrays of tandemly repeated satellite sequences. However, studies on molecular organization and evolution of subtelomeric repeats are rare. We isolated two subtelomeric repeats, CL14 and CL34, from potato (Solanum tuberosum). The CL14 and CL34 repeats are organized as independent long arrays, up to 1-3 Mb, of 182 bp and 339 bp monomers, respectively. The CL14 and CL34 repeat arrays are directly connected with the telomeric repeats at some chromosomal ends. The CL14 repeat was detected at the subtelomeric regions among highly diverged Solanum species, including tomato (Solanum lycopersicum). In contrast, CL34 was only found in potato and its closely related species. Interestingly, the CL34 repeat array was always proximal to the telomeres when both CL14 and CL34 were found at the same chromosomal end. In addition, the CL34 repeat family showed more sequence variability among monomers compared with the CL14 repeat family. We conclude that the CL34 repeat family emerged recently from the subtelomeric regions of potato chromosomes and is rapidly evolving. These results provide further evidence that subtelomeric domains are among the most dynamic regions in eukaryotic genomes.
Improving Information Extraction by Modeling Errors in Speech Recognizer Output

In this paper we describe a technique for improving the performance of an information extraction system for speech data by explicitly modeling the errors in the recognizer output. The approach combines a statistical model of named entity states with a lattice representation of hypothesized words and errors annotated with recognition confidence scores. Additional refinements include the use of multiple error types, improved confidence estimation, and multipass processing. In combination, these techniques improve named entity recognition performance over a text-based baseline by 28%.
Melanization and Pathogenicity in the Insect, Tenebrio molitor, and the Crustacean, Pacifastacus leniusculus, by Aeromonas hydrophila AH-3

Aeromonas hydrophila is the most common Aeromonas species causing infections in human and other animals such as amphibians, reptiles, fish and crustaceans. Pathogenesis of Aeromonas species have been reported to be associated with virulence factors such as lipopolysaccharides (LPS), bacterial toxins, bacterial secretion systems, flagella, and other surface molecules. Several mutant strains of A. hydrophila AH-3 were initially used to study their virulence in two animal species, Pacifastacus leniusculus (crayfish) and Tenebrio molitor larvae (mealworm). The AH-3 strains used in this study have mutations in genes involving the synthesis of flagella, LPS structures, secretion systems, and some other factors, which have been reported to be involved in A. hydrophila pathogenicity. Our study shows that the LPS (O-antigen and external core) is the most determinant A. hydrophila AH-3 virulence factor in both animals. Furthermore, we studied the immune responses of these hosts to infection of virulent or non-virulent strains of A. hydrophila AH-3. The AH-3 wild type (WT) containing the complete LPS core is highly virulent and this bacterium strongly stimulated the prophenoloxidase activating system resulting in melanization in both crayfish and mealworm. In contrast, the ΔwaaE mutant which has LPS without O-antigen and external core was non-virulent and lost ability to stimulate this system and melanization in these two animals. The high phenoloxidase activity found in WT infected crayfish appears to result from a low expression of pacifastin, a prophenoloxidase activating enzyme inhibitor, and this gene expression was not changed in the ΔwaaE mutant infected animal and consequently phenoloxidase activity was not altered as compared to non-infected animals. Therefore we show that the virulence factors of A. hydrophila are the same regardless whether an insect or a crustacean is infected and the O-antigen and external core is essential for activation of the proPO system and as virulence factors for this bacterium.
DNA Segmentation Through the Bayesian Approach

We present a new approach to DNA segmentation into compositionally homogeneous blocks. The Bayesian estimator, which is applicable for both short and long segments, is used to obtain the measure of homogeneity. An exact optimal segmentation is found via the dynamic programming technique. After completion of the segmentation procedure, the sequence composition on different scales can be analyzed with filtration of boundaries via the partition function approach.
Respiratory Syncytial Virus Fusion Glycoprotein Expressed in Insect Cells Form Protein Nanoparticles That Induce Protective Immunity in Cotton Rats

Respiratory Syncytial Virus (RSV) is an important viral agent causing severe respiratory tract disease in infants and children as well as in the elderly and immunocompromised individuals. The lack of a safe and effective RSV vaccine represents a major unmet medical need. RSV fusion (F) surface glycoprotein was modified and cloned into a baculovirus vector for efficient expression in Sf9 insect cells. Recombinant RSV F was glycosylated and cleaved into covalently linked F2 and F1 polypeptides that formed homotrimers. RSV F extracted and purified from insect cell membranes assembled into 40 nm protein nanoparticles composed of multiple RSV F oligomers arranged in the form of rosettes. The immunogenicity and protective efficacy of purified RSV F nanoparticles was compared to live and formalin inactivated RSV in cotton rats. Immunized animals induced neutralizing serum antibodies, inhibited virus replication in the lungs, and had no signs of disease enhancement in the respiratory track of challenged animals. RSV F nanoparticles also induced IgG competitive for binding of palivizumab neutralizing monoclonal antibody to RSV F antigenic site II. Antibodies to this epitope are known to protect against RSV when passively administered in high risk infants. Together these data provide a rational for continued development a recombinant RSV F nanoparticle vaccine candidate.