Miracle-dz/UniFAR-FTUs huggingface dataset:
Transcriptional Level of Genes Involved in The Neurotransmitter System of Dicentrarchus labrax in Response to Chronic Exposure to Psychopharmaceuticals

Up to 10% of the human population suffers from depression. SSRIs and SNRIs are prescribed for clinical depression and detected in aquatic ecosystems. The main aim of this study was to explore and evaluate transcriptional levels of neurotransmitter genes in brain of a marine fish species European sea bass. The juveniles were exposed to two PP: (i) FLUX at the concentration of 0.5 μg/L and 50 μg/L; (ii) VEN at the concentration of 0.01 μg/L and 1 μg/L. The chronic exposures were performed for 21 days, and followed by a 7 day of recovery period to assess the reversibility of effects. Transcription levels of genes encoding for proteins involved in the neurotransmitter system, such as 5-ht3a and 5-ht3b, sert, mao, vmat and dopamine d2 and d3 were analyzed using qPCR-RT. One of the main results was that both antidepressants act differentially on the neurotransmitters gene expression. We found strong and unique profile of effects in transcription levels in FLUX and VEN. The FLUX exposure revealed acute induction on day 1 in all targets genes, except mao, where a chronic effect was present at day 21. In contrast to FLUX, VEN exposure at day 21 decreased the mRNA expression of the receptors of serotonin 5-ht3a and 5-ht3b, but only for 5-ht3a with significant differences. In addition, VEN exposure increased Dopamine d2 and d3 receptor mRNA expression at the recovery period at day 28. Analyzed dopaminergic and serotonergic neurotransmission genes from European Sea bass had a high degree of homology with D.rerio, O.latipes, T.rubripes, and H. sapiens, analyzed by multiple alignments and phylogenetic trees. Sequence similarities indicate the possibility of similar gene functions in vertebrates. Modulated genes from this study, are associated in humans with several mental disorders, and are known to control various behavior and food intake in aquatic vertebrates. These results provide new insights into the chronic effects of psychopharmaceutical compounds and indicate different mechanism of toxicity.
Sugar Overcomes Oxygen Inhibition in Photoinitiated Free Radical Polymerization

Faruk Oytun, Muhammet U. Kahveci, Yusuf Yagci Department of Chemistry, Faculty of Science and Letters, Istanbul Technical University, Maslak, Istanbul 34469, Turkey Department of Bioengineering, Faculty of Chemical and Metallurgical Engineering, Yildiz Technical University, Davutpasa, Esenler, Istanbul 34210, Turkey Department of Chemistry, Faculty of Science, King Abdulaziz University, Jeddah 21589, Kingdom of Saudi Arabia Correspondence to: Y. Yagci (E-mail: yusuf@itu.edu.tr)
Joint Bayesian estimation of tensor and lensing B modes in the power spectrum of CMB polarization data

We investigate the performance of a simple Bayesian fitting approach to correct the cosmic microwave background (CMB) B-mode polarization for gravitational lensing effects in the recovered probability distribution of the tensor-to-scalar ratio. We perform a two-dimensional power spectrum fit of the amplitude of the primordial B-modes (tensor-to-scalar ratio, $r$) and the amplitude of the lensing B-modes (parameter $A_{lens}$), jointly with the estimation of the astrophysical foregrounds including both synchrotron and thermal dust emissions. Using this Bayesian framework, we forecast the ability of the proposed CMB space mission LiteBIRD to constrain $r$ in the presence of realistic lensing and foreground contributions. We compute the joint posterior distribution of $r$ and $A_{lens}$, which we improve by adopting a prior on $A_{lens}$ taken from the South Pole Telescope (SPT) measurement. As it applies to the power spectrum, this approach cannot mitigate the uncertainty on $r$ that is due to E-mode cosmic variance transferred to B-modes by lensing, unlike standard delensing techniques that are performed on maps. However, the method allows to correct for the bias on $r$ induced by lensing, at the expense of a larger uncertainty due to the increased volume of the parameter space. We quantify, for different values of the tensor-to-scalar ratio, the trade-off between bias correction and increase of uncertainty on $r$. For LiteBIRD simulations, which include foregrounds and lensing contamination, we find that correcting the foreground-cleaned CMB B-mode power spectrum for the lensing bias, not the lensing cosmic variance, still guarantees a $3\sigma$ detection of $r=5\times 10^{-3}$. The significance of the detection is increased to $6\sigma$ when the current SPT prior on $A_{lens}$ is adopted.
Dynamic resource allocation with a soft handover procedure for application in a broadband system

This work investigates the advantages of adopting a soft handover (SHO) procedure with a TDD-TDMA-OFDM access method in a WLAN system, when broadband mobile users are considered. Reference is made to the MEDIAN-ACTS system scenario extended to a multi-cell environment. A particular distributed queue packet reservation multiple access scheme with priorities, called PAMA (priority assignment multiple access) is considered. Simulation results carried out in the present investigation indicate that SHO outperforms hard HO (HHO), in terms of packet loss and time delay, and its performance approaches that of the fixed users case. In fact, SHO exploits the overlapping area between adjacent cells permitting users to be simultaneously served by two base stations (BSs) instead of a single one. As a consequence, the overall offered traffic is better distributed among the BSs of the system, resulting into a more efficient resource allocation.
Liquid atomization and spray drift measurement in a wind tunnel for a twin fluid system with a deflector nozzle

The objectives of this research were to inspect the drop production of a twin fluid system with the Floodjet TK SS 10 042 deflector nozzle and to identify the drift of the droplets produced by the nozzle in a wind tunnel when using the nozzle with the individual settings provided by the company that enlisted our institute to do the described research task. The results of the inspection of drop production, done using a particle sizer, showed that the values of volume diameter Dv10 were low, the percentage of drops smaller than 100 µm in size was considerable, and the drop sizes varied widely in each setting. It was concluded that the risk of drift and, therefore, the risk of placing an unnecessary load on the environment existed when using the nozzle with the given settings. The application of the nozzle that was tested may cause problems in various aspects of practical spraying techniques. Based on the results of the drift measurements performed in a wind tunnel, the material deposition reported as relative coverage decreased significantly only when the recommended settings were changed at wind velocities of 2.0 m s-1 and 4.0 m s-1. At wind velocities of 4.0 m s-1 and 6.0 m s-1, detectable (>=1%) relative coverage values were recorded for each setting, even at the measurement limit. It was concluded that the inspected twin fluid system with the Floodjet TK SS 10 042 deflector nozzle does not provide the expected decrease in drift when using the given settings at wind velocities of 4.0 m s-1 and 6.0 m s-1.
Study on order analysis for condition monitoring wind turbine gearbox

A complex 3-stage gearbox design, in which one planetary gear set at first stage and two sets of parallel gears at second and third stage, is conventionally applied on the large wind turbine configuration with Doubly Fed Induction Generator. In this variable-speed wind turbine, it is hard to directly apply conventional frequency analysis on condition monitoring of the gearbox planetary stage. Proper signal processing and analysis become crucial here for interpreting the conditions of gears and bearings. In this paper, order analysis is studied for condition monitoring the planetary stage of wind turbine gearbox. The approach takes advantage of angular resampling to achieve cyclo-stationary vibration signals and lessen the effects due to speed changes. One key element in the scheme is taking angular information to enable resampling the time-domain signals into angular-domain signals. A vibration signal model for gearbox planetary stage is firstly described, and the scheme is then tested on simulated signals to achieve fine frequency resolution. Time synchronous averaging is applied as a pre-processing technique to enhance the Signal to Noise Ratio (SNR) in order spectrum
Query Answering Approach Based on Document Summarization

The growing of online information obliged the availability of a thorough research in the domain of automatic text summarization within the Natural Language Processing (NLP) community.The aim of this paper is to propose a novel approach for a language independent automatic summarization approach that combines three main approaches. The Rhetorical Structure Theory (RST), the query processing approach, and the Network Representationapproach (NRA). RST, as a theory of major aspect for the structure of natural text, is used to extract the semantic relation behind the text.Query processing approachclassifies the question type and finds the answer in a way that suits the user's needs. The NRA is used to create a graph representing the extracted semantic relation. The output is an answer, which not only responses to the question, but also gives the user an opportunity to find additional information that is related to the question.We implemented the proposed approach. As a case study, the implemented approachis applied on Arabic text in the agriculture field. The implemented approach succeeded in summarizing extension documents according to user's query. The approach results have been evaluated using Recall, Precision and F-score measures.
Development of Reduced Graphene Oxide/High Density Polyethlene (RGO/HDPE) High Performance Nanocomposites

In this research, graphene oxide (GO) was synthesized from graphite nanofiber (GNF) using the conventional Hummer methods. The reduced graphene oxide (rGO) was successfully reduced using the chemical reduction by formic acid which was a green, metal free and environmentally friendly reduction method. Different loading of rGO; 0.05 wt%, 0.10 wt%, 0.15 wt% and 0.20 wt% respectively was incorporated into the high density polyethylene (HDPE) to produce HDPE/rGO nanocomposite through melt intercalation method. Characterization test such as Fourier Transform Infrared Spectroscopy (FTIR) was conducted on GO and rGO for the confirmation on the removal of oxygen contained functional group in rGO. For HDPE/rGO nanocomposites, FTIR was carried out to determine the presence of rGO in the nanocomposites while preserving the important peaks of HDPE. Further testing such as Differential Scanning Calorimetry (DSC) and Melt Flow Index (MFI) was done on pure HDPE and HDPE/rGO nanocomposites. DSC was conducted to measure the melting point (Tm), recrystallization temperature (Tc) and crystallinity of nanocomposites. The results showed there were increased in the crystallinity. There was slightly increased in thermal stability. MFI was conducted to determine the flow measurement and viscosity of nanocomposite when in molten state. The MFI values increased which indicated the decrease in viscosity as well. Performance test such as Impact and Tensile test was conducted to determine the mechanical properties of nanocomposite. Impact test showed increment in impact strength when there was increased in rGO loading. The tensile test showed that the optimum loadings for rGO incorporated to HDPE was 0.15 wt% which showed increased in both e-modulus and tensile strength and decreased in elongation at break. The overall test showed that there was increased in thermal and mechanical properties of HDPE/rGO
Time-series forecasting of pollutant concentration levels using particle swarm optimization and artificial neural networks

This study evaluates the application of an intelligent hybrid system for time-series forecasting of atmospheric pollutant concentration levels. The proposed method consists of an artificial neural network combined with a particle swarm optimization algorithm. The method not only searches relevant time lags for the correct characterization of the time series, but also determines the best neural network architecture. An experimental analysis is performed using four real time series and the results are shown in terms of six performance measures. The experimental results demonstrate that the proposed methodology achieves a fair prediction of the presented pollutant time series by using compact networks.
Plant biostimulants (Funneliformis mosseae and humic substances) rather than chemical fertilizer improved biochemical responses in peppermint.

Plant biostimulants such as arbuscular mycorrhizal (AM) fungi and humic substances (HS) can be used as an appropriate alternative to chemical fertilizers, as regards to environmental problems of chemicals. The effects of Funneliformis mosseae as an AM fungus, HS (foliar spray and topdressing application), and chemical fertilizer (NK), separately or interacting, on biochemical responses in Mentha piperita L. plants were investigated under field conditions. Results revealed that the mentioned three factors appear as valid practicable method for improving growth and metabolites of peppermints cultivated in the field even when root colonization of AM fungus does not achieve high rates. The triple interaction between mycorrhizal inoculation, HS application (especially foliar spray), and NK fertilizer treatment induced the maximum accumulation of photosynthetic pigments, starch, soluble sugars, total proteins, proline, total phenolics, and the antioxidants in leaves. However, positive effects of F. mosseae and HS were more than those of the chemical fertilizer. We propose that F. mosseae and foliar spray of HS, particularly in combination can be used as suitable plant biostimulants in peppermint plants under field conditions, which in turn will improve soil health and reduce environmental problems.
Estimating the human contribution to groundwater depletion in the Middle East, from GRACE data, land surface models, and well observations

Data from the Gravity Recovery and Climate Experiment (GRACE) satellite mission are used to estimate monthly changes in total water storage across the Middle East during February 2003 to December 2012. The results show a large negative trend in total water storage centered over western Iran and eastern Iraq. Subtracting contributions from the Caspian Sea and two large lakes, Tharthar and Urmiah, and using output from a version of the CLM4.5 land surface model to remove contributions from soil moisture, snow, canopy storage, and river storage, we conclude that most of the long‐term water loss is due to a decline in groundwater storage. By dividing the region into seven mascons outlined along national boundaries and fitting them to the data, we find that the largest groundwater depletion is occurring in Iran, with a mass loss rate of 25 ± 3 Gt/yr during the study period. The conclusion of significant Iranian groundwater loss is further supported by in situ well data from across the country. Anthropogenic contributions to the groundwater loss are estimated by removing the natural variations in groundwater predicted by CLM4.5. These results indicate that over half of the groundwater loss in Iran (14 ± 3 Gt/yr) may be attributed to human withdrawals.
An investigation of the income smoothing behavior of growth and value firms (case study: Tehran Stock Exchange Market)

The major objective of this study is to investigate the income smoothing behaviour of two different types of firms value and growth - in the Tehran Stock Exchange (TSE) Market. All firms listed in the TSE between 2003 and 2007 were examined using the Jones Model to investigate their income smoothing behaviours. Using the Jones model, the discretionary part of accruals was investigated. The results of this study revealed that growth firms tend to apply discretionary accruals more intensively than value firms. In order to support the robustness of the findings, the Eckel model, was also applied. The same result was found for the Eckel model as for the Jones model. The results indicated that growth firms achieved a higher degree of income smoothing than value firms. The effects of various confounding factors which are different between these two types of firms, such as size of the company, standard deviation of earnings, market capitalization and consecutive trend of earnings, were also investigated. The results indicated that income smoothing in growth firms is larger than in value firms, and also that other items, which are known as representatives of the risk, are larger for growth firms than for value firms.
A HIDDEN MARKOV MODEL FOR JOINT ESTIMATION OF GENOTYPE AND COPY NUMBER IN HIGH-THROUGHPUT SNP CHIPS

Amplifications and deletions of chromosomal DNA, as well as copy-neutral loss of heterozygosity have been associated with diseases processes. High-throughput single nucleotide polymorphism (SNP) arrays are useful for making genome-wide estimates of copy number and genotype calls. Because neighboring SNPs in high throughput SNP arrays are likely to have dependent copy number and genotype due to the underlying haplotype structure and linkage disequilibrium, hidden Markov models (HMM) may be useful for improving genotype calls and copy number estimates that do not incorporate information from nearby SNPs. We improve previous approaches that utilize a HMM framework for inference in high throughput SNP arrays by integrating copy number, genotype calls, and the corresponding confidence scores when available. Using simulated data, we demonstrate how confidence scores control smoothing in a probabilistic framework. Software for fitting HMMs to SNP array data is available in the R package ICE.
Meeting the Challenges for Wireless Sensor Network Deployment in Buildings

Wireless sensor networks (WSNs) in buildings are faced with transmission issues, much more severe than those of outdoor applications. Next to the transmission effective range, battery lifetime is also of a high importance, as it can sig- nificantly affect network performance and maintenance requirements. In this paper we present an architectural concept, in fact a dynamic routing protocol, for the setup of a building WSN. Three key goals have underpinned the protocol design; ability to cost efficiently address transmission distance within buildings, acceptable battery longevity, typically up to a year, and no data loss. Experimental data have been collected over a period of several months and have demonstrated the much enhanced performance of the network, when compared to the performance before the protocol implementation.
Selecting of Monorail projects with analytic hierarchy process and 0-1 goal programming methods in Ankara

Hızla artan nüfus, plansız kentleşme ve özel araç sayısındaki artış kentsel alanlarda trafik sorununu ortaya çıkarmıştır. Bu durum ulaşım planlarının yeniden şekillenmesine ve öneminin artmasına sebep olmuştur. Bu sebeple, toplu ulaşım sistemini daha verimli hale getirmek için yoğun çalışmalar yapılmaktadır. Bunun sonucunda alternatif ulaşım türlerine eğilim başlamıştır. Bu noktada hızlı, emniyetli ve konforlu ulaşım sistemi olarak monoray teknolojisi öne çıkmaktadır. Bu çalışmada çok ölçütlü karar verme yöntemlerinden Analitik Hiyerarşi Prosesi (AHP) ve 0-1 Hedef Programlama yöntemleri kullanılarak Ankara Büyükşehir Belediyesi’nde belirlenen güzergâhlara en uygun ulaştırma projelerinin seçimi yapılmıştır. Uncontrolled increasing population, unplanned urbanization and enhancement in private vehicles number have revealed the of congestion traffic problem in urban area. These conditions have led to increase the need to remodeling the transportation plans. For this reason, a huge number of intensive studies were carried out in order to insure more efficiency to the public transport system by their different modes. One of these studies concerns the monorail service in Ankara, one of the most safe, fast and comfortable transport modes. Indeed, we made selection from several transport projects in Ankara Metropolitan Municipality using Analytic Hierarchy Process (AHP) and 0-1 Goal Programming methods.
Meteorological hazards - visualization system for national protection against extreme hazards for Poland

Meteorological hazard maps are one of the components of the IT System for Country Protection against extreme hazards (ISOK) created by a consortium of Polish institutions, including the Institute of Meteorology and Water Management – National Research Institute. These maps present meteorological phenomena such as: temperature extremes, heavy and flood-producing rainfall, strong winds, intensive snowfall, fogs, glaze, rime and thunderstorms with hail. These elements were chosen arbitrarily due to recorded or estimated losses. The main aim of the maps is to present visualization methods of hazard forecast with consideration of climatological (historical) background. To identify areas especially exposed to the above meteorological hazards, extensive climatological analyses were performed, based on long-term daily data (mainly the 1951-2010 period). The main component of the warning system is a set of prediction maps created automatically on the basis of scientific algorithms that provide the probability of the occurrence of particular phenomena, or the conditions favourable for them. The algorithms’ structure, based on information about physical processes in the atmosphere, as well as detailed climatological analysis, enables the reclassification of the forecast values – predicted by the ALADIN mesoscale atmospheric model – into four groups of any hazard at the gridded points. Finally, the information will be interpolated and will result in the production of maps of spatial distribution presenting the objective probability of a particular hazard, i.e. its actual risk. Results of historical analysis are to be presented for the public by a number of climatological maps, and accompanied by additional fact sheets to provide society with an actual view of the spatial distribution of the distinguished weather phenomena, and the interrelated risks.
Theories of Gold Price Movements: Common Wisdom or Myths?; Pension Incentives and Premature Retirement

This paper examines several of the explanations commonly provided regarding gold and its price movements. We consider the safe haven, inflation hedge, and dollar destruction hypotheses. The results are mixed. Our data does not support the theories that gold is a safe haven or an inflation hedge. We find that gold is a zerobeta asset and there is a strong negative correlation between gold and the value of the US dollar in the post Bretton-Woods era. The decomposition of gold prices under a semi-structural model finds the aggregate demand shock, monetary policy shock, and precautionary demand shock of gold all only have modest influence on the price movement of gold.
Characterization of Corrosion Products on Carbon Steel Exposed to Natural Weathering and to Accelerated Corrosion Tests

The aim of this work was to compare the corrosion products formed on carbon steel plates submitted to atmospheric corrosion in urban and industrial atmospheres with those formed after accelerated corrosion tests. The corrosion products were characterized by X-ray diffraction, Mossbauer spectroscopy, and Raman spectroscopy. The specimens were exposed to natural weathering in both atmospheres for nine months. The morphologies of the corrosion products were evaluated using scanning electron microscopy. The main product found was lepidocrocite. Goethite and magnetite were also found on the corroded specimens but in lower concentrations. The results showed that the accelerated test based on the ASTM B117 procedure presented poor correlation with the atmospheric corrosion tests whereas an alternated fog/dry cycle combined with UV radiation exposure provided better correlation.