Miracle-dz/UniFAR-FTUs huggingface dataset:
Globalization and the Ladder of Development: Pushed to the Top or Held at the Bottom?

We study the relationship between international trade and development in a model where countries differ in their capability, goods differ in their complexity, and capability growth is a function of a country’s pattern of specialization. Theoretically, we show that it is possible for international trade to increase capability growth in all countries and, in turn, to push all countries up the development ladder. This occurs when specialization in the more complex sectors, which face less foreign competition in all countries, also tends to create positive dynamic spillovers. Empirically, we propose to estimate these dynamic spillovers using the entry of countries into the World Trade Organization as an instrumental variable for other countries’ patterns of specialization. Our results suggest that sectors facing less foreign competition tend to create negative spillovers. Through the lens of our model, this implies dynamic welfare losses from trade that are small for the median country, but pervasive and large among a few developing countries. ∗We thank Dave Donaldson and Elhanan Helpman as well as seminar participants at MIT, WIEN conference, Johns Hopkins, and Dartmouth for very helpful comments.
Recent trends in global greenhouse gas emissions:regional trends 1970–2000 and spatial distributionof key sources in 2000

Abstract In 2004, the Joint Research Centre (JRC) of the European Commission, the Netherlands Environmental Assessment Agency (MNP) and the Max Plank Institute for Chemistry (MPIC) started a project to create fast (bi-)annual updates of the EDGAR global emission inventory system, based on the more detailed previous version 3.2. Here, the key features of the Emission Database for Global Atmospheric Research, EDGAR 3 are first summarized, and then the compilation of recent global trends having a major influence on variables and the new ‘Fast Track’ approach to estimate recent emissions of greenhouse gases and air pollutants in 2000 at a country-specific level are described. Also provided is an overview of the approaches and data sources used for this EDGAR 3.2 Fast Track 2000 dataset, the different source sectors and the accuracies achieved, with a focus on anthropogenic sources of methane and nitrous oxide. Results of global emission trends for four air pollutants are also briefly addressed. Results for various sources and greenhouse gases at regional and national scales and on 1×1 degree grid have been made available on the EDGAR website.
Efficiency in the Treatment of Landfill Leachate Using Natural Coagulants From the Seeds of Moringa Oleifera Lam and Abelmoschus Esculentus (L.)

Landfill leachate is considered to be highly damaging to the environment and to human health. The treatment of leachate is seen as a great challenge, and one of the alternatives for these issues can be the use of the seeds of Moringa oleifera Lam as a natural coagulant agent. This research aims to promote the removal of colour, turbidity, conductivity, coliforms, pH, COD, BOD5 of leachate by coagulation/flocculation/sedimentation/filtration processes using natural coagulants: Moringa oleífera Lam and Abelmoschus esculentus (L.) Moench (Okra), in the pre-treatment of landfill leachate under laboratory conditions. The Moringa extracts favours the increase of the COD and BOD5, with the filtration of the Moringa extract (LBMS 37.5 g/L) it presented excellent results in the removal of colour, turbidity, conductivity, solids, COD and BOD5: 92%, 85%, 64%, 90%, 82% and 89.85%, respectively. The treatment of leachate with Okra (LBQ 37.5 g/L) did not result in change of pH but in the removal of the parameters such as: colour, turbidity, solids, conductivity, COD and BOD5 (72%, 35%, 87%, 20%, 78% and 72%, respectively). The combination of Okra and Moringa (LBEMQ 37gL+20gL) obtained 22%, 78%, 42%, 46%, 52% and 88%, respectively, of removal, with both coagulants being efficient in the removal of the parameters evaluated. The natural coagulant from the seeds of Moringa oleífera Lam has however proved to be a promising alternative in the treatment of leachate.
Tiny RespNet: A Scalable Multimodal TinyCNN Processor for Automatic Detection of Respiratory Symptoms

Detection of respiratory symptoms has long been an area of extensive research to expedite the process of machine aided diagnosis for various respiratory conditions. This paper attempts to address the early diagnosis of respiratory conditions using low power scalable software and hardware involving end-to-end convolutional neural networks (CNNs). We propose Tiny RespNet, a scalable multimodal CNN software hardware architecture that can take audio recordings, speech information, and other sensor modalities belonging to patient demographic or symptom information as input to classify different respiratory symptoms. We analyze four different publicly available datasets and use them as case studies as part of our experiment to classify respiratory symptoms. With regards to fitting the network architecture to the hardware framework, we perform windowing, low bit-width quantization, and hyperparameter optimization on the software side. As per our analysis, detection accuracy goes up by 5% when patient demographic information is included in the network architecture. The hardware prototype is designed using Verilog HDL on Xilinx Artix-7 100t FPGA with hardware scalability extending to accommodate different numbers of processing engines for parallel processing. The proposed hardware implementation has a low power consumption of only 245 mW and achieves an energy efficiency of 7.3 GOPS/W which is 4.3 × better than the state-of the-art accelerator implementations. In addition, Tiny RespNet TensorFlow model is implemented on NVIDIA Jetson TX2 SoC (CPU + GPU) and compared to TX2 single-core CPU and GPU implementations to provide scalability in terms of off-the-shelf platform implementations.
Ozonation of azo dyes

Ozone pretreatment studies of wastewater containing a specific azo dye - Orange II - were conducted in order to assess the kinetics of ozone oxidation and to evaluate the effect of ozonation on the biodegradability of the wastewater. Batch experiments were performed at different initial concentrations of the dye, showing that ozone is capable of a rapid disruption of the dye molecule. Moreover, the production of biodegradable compounds is apparent from the evolution of COD and BOD5 measurements. A mathematical model which describes the dye elimination, the COD and BOD5 variation, and the amount of ozone reacted has been developed.
Nonsymmetric Palladium Complexes of Partly Fluorinated Bisphosphine Ligands: Efficient Catalysts for Flexible Propene/CO Copolymer Materials of Ultrahigh Molecular Weight

Five new nonsymmetric 1-diphenylphosphino-3-{bis[aryl]phosphino}propane ligands 1b−f [aryl: b = 3,5-bis(trifluoromethyl)phenyl, c = 3,5-dimethylphenyl, d = 3,5-difluorophenyl, e = 2-(trifluoromethyl)phenyl, f = 2,4,6-trifluorophenyl] and their corresponding neutral dichloro palladium(II) 2b−f, diiodo palladium(II) 3d,e, and dicationic diacetonitrile palladium(II) ditetrafluoroborate complexes 4b−f were synthesized. The symmetric ligand 1,3-bis{bis[3,5-bis(trifluoromethyl)phenyl]phosphino}propane (1a) and the related palladium(II) complexes 2a and 4a were prepared for comparison. Solid state structures of new ligands were determined by X-ray structure analysis in the form of the dichloro (2a−c,f) and diiodo (3d,e) compounds. The properties of the symmetric (4a) and nonsymmetric catalysts (4b−f) were tested in propene/CO copolymerization experiments. A clear correlation between primarily steric effects of these ligands and the catalyst activity as well as the molecular weight of the resulting polyketone ma.
Sum Frequency Generation Study of the Interfacial Layer in Liquid-Phase Heterogeneously Catalyzed Oxidation of 2-Propanol on Platinum: Effect of the Concentrations of Water and 2-Propanol at the Interface

Sum frequency generation (SFG) vibrational spectroscopy was applied to study the solid–liquid interface in the heterogeneously catalyzed oxidation of 2-propanol to acetone by dissolved dioxygen in aqueous solution on platinum. The mole fraction of alcohol was varied from 0 to 1. At 2-propanol mole fractions less than 0.14 and above 0.23, the TOF for acetone is approximately 20 h–1. A 3-fold increase in the reaction rate is seen when 2-propanol is present with concentrations in this intermediate range (0.14–0.23). SFG spectra indicate that in aqueous mixtures of 2-propanol the solid–liquid interface is dominated by the alcohol, even at low mole fractions of alcohol, but resonant features from molecular 2-propanol not bound to the platinum surface appear only above 0.14 mole fraction. At 2-propanol concentrations where the highest reaction rates are observed, SFG shows the presence of water and alcohol at the catalyst interface, whereas, above and below these concentrations, either water or 2-propanol is no.
On the increased climate sensitivity in the EC-Earth model from CMIP 5 to CMIP 6 ” by

Many modelling groups that contribute to CMIP6 (Coupled Model Intercomparison Project phase 6) have found a larger equilibrium climate sensitivity (ECS) with their latest model versions compared to the values obtained with earlier versions for CMIP5. This is also the case for the EC-Earth model, and in this study we investigate what developments since the CMIP5 era could have caused the increase in the ECS in this model. Apart from increases in horizontal and vertical resolution, the EC-Earth model also has substantially changed the representation of aerosols, and in particular it has introduced a more sophisticated description of aerosol indirect effects. After testing the model with some of the recent updates switched off, we find that the ECS increase can be attributed to the more advanced treatment of aerosols, with the largest contribution coming from the effect of aerosols on cloud microphysics (cloud lifetime or second indirect effect). The increase in climate sensitivity is unrelated to model tuning as all experiments have been performed with the same tuning parameters and only the representation of the aerosol effects has been changing. These results cannot be easily generalised to other models as their CMIP5 and CMIP6 versions may differ in other aspects than the aerosol-cloud interaction, but the results highlights the strong sensitivity of ECS to the details of the aerosol forcing.
Effect of water absorption and desorption on the interfacial degradation in a model composite of an aramid fibre and unsaturated polyester evaluated by Raman and FT infra-red microspectroscopy

The interfacial degradation in a model composite of an aramid fibre (Kevlar 49) and unsaturated polyester (UP) followed by absorption and desorption of hot water at 90 °C was monitored by measuring the variations in residual stress in the embedded fibre by means of the micro-Raman technique. The Fourier transform infra-red (FTIR) microspectroscopic analyses were also conducted to study the structure and the quantity of absorbed water causing interfacial degradation. Copyright © 1999 John Wiley & Sons, Ltd.
A six-long noncoding RNA model predicts prognosis in lung adenocarcinoma

Background The incidence and mortality of lung cancer rank first among various malignant tumors. The lack of clear molecular classification and effective individualized treatment greatly limits the treatment benefits of patients. Long non-coding RNAs (lncRNAs) have been demonstrated widely involve in tumor progressing, and been proved easy to detect for occupying majority in transcriptome. However, less work focuses on studying the potency of lncRNAs as molecular typing and prognostic indicator in lung cancer. Methods Based on the 448 lung adenocarcinoma (LUAD) samples and the expression of 14,127 lncRNAs from the Cancer Genome Atlas (TCGA) database, we constructed a co-expression network using weighted gene co-expression network analysis. Then based on the feature module and the overall survival of patients, we constructed a risk score model through Cox proportional hazards regression and verified it with a validation cohort. Finally, according to the median of risk score, the function of this model was enriched. Results We identified a module containing 123 lncRNAs that is related with the prognosis of LUAD. Using univariate and multivariate Cox proportional hazards regression with lasso regression, six lncRNAs were identified to construct a risk score model. The calculation formula shown as follows: risk score = (−0.3057 × EXPVIM-AS1) + (0.9678 × EXPAC092811.1) + (1.0829 × EXPNFIA-AS1) + (−0.3505 × EXPAL035701.1) + (3.9378 × EXPAC079336.4) + (−0.2810 × EXPAL121790.2). Six-lncRNA model can be used as an independent prognostic indicator in LUAD (P<0.001) and the area under the 5-year receiver operating characteristic (ROC) curve is 0.715. Conclusions We developed a six-lncRNA model, which could be used for predicting prognosis and guiding medical treatment in LUAD patients.
Enemy at the Gate: Evolution of Twitter User's Polarization During National Crisis

Social networks are effective platforms to study the real-life behavior of users. In this paper, we study users' political polarization during the times of crisis and its relation to nationalism. To this purpose, we focus on the reaction of Indian and Pakistani Twitter users during February 2019 crisis and the ensuing Indian General Elections in 2019. We show that a national crisis affects the polarization and discourse in both countries. Also, we show that user activities increase during a national crisis, and political discourse strengthens while polarization decreases on critical days. Finally, we highlight the links between this crisis and the Indian elections and show how the political parties discussed the crisis in their campaigns.
The Impact of 3G Mobile Internet on Educational Outcomes in Brazil ∗

What is the impact of mobile broadband internet on children’s test scores? We compare standardized test scores before and after the staggered entry of 3G into Brazil’s 5,570 municipalities using a heterogeneity-robust event study design. We ﬁnd no effects of mobile internet on test scores for 5th or 9th grade students, and can reject effect sizes of 0.04 standard deviations in both math and Portuguese. Taken together, our results indicate that the arrival of high-speed mobile internet is not sufﬁcient to improve educational outcomes either through direct take-up by individuals or through broader changes to the economy.
Advances in Brief Expression of the pl6 and pl5 Cyclin-dependent Kinase Inhibitors in Lymphocyte Activation and Neuronal Differentiation1

The cyclin-dependcnt kinase inhibitors pl6INK4/MTSl and pl51NK4l>/ MTS2 have been mapped to a region in chromosome 9 (p21 )that is deleted frequently in acute lymphoblastic leukemias and malignant (Â¡liornas.To gain insight into the functions of these inhibitors in lymphocytes and neuronal cells, we studied the expression of pl5 and pl6 during lympho cyte mitogenesis and neuronal differentiation. Expression of pl5 was extinguished during lymphocyte activation, concomitant with an increase in retinoblastoma kinase activity. The differentiation of the embryonic teralocarcinoma cell line NT2 into postmitotic neurons (hNT) was asso ciated with enhanced expression of pl5 and pl6 proteins. These findings suggest that pl5 and pl6 play a role in maintaining cell quiescence in lymphocytes and neuronal cells, respectively. Deletions of these genes may thus promote unrestrained growth.
Cloning and high level expression of bovine

Ph.D. Student in Biotechnology, Department of Patho biol gy, Faculty of Veterinary Medicine, University of Tehran, Tehran, Iran; Department of Pathobiology, Faculty of Veterinary M edicine, University of Tehran, Tehran, Iran; Fellow Member of Academy of Science of Iran, Tehran , Iran; Department of Basic Sciences, Faculty of Veterinary Medicine, University of Tehra n, Tehran, Iran; Department of Parasitology, Pasteur Institute, Tehran, Iran; Department of Biotechnology, Faculty of Sciences, U niversity of Isfahan, Isfahan, Iran
Programming “ Programming by Example ” by Example a thesis presented by Garrett

Programming by Example (PbE) is an increasingly popular model for writing programs to automate repetitive tasks, such as those common in data wrangling. In this paradigm, the user presents a set of input/output pairs, and an inductive synthesizer responds with a program that satisfies these examples. However, due to performance limitations, these synthesizers must be specialized to the domain at hand. Frameworks like PROSE [10] have been developed to ease the implementation burden when writing synthesizers for domain-specific languages (DSLs), but they remain relatively inaccessible to those who are not experts in programming languages and synthesis. We identify three key challenges facing the users of such tools: designing DSLs, writing deduction rules, and debugging. In order to remove these barriers, we present a new interaction model for developing inductive program synthesizers by example. Rather than write an explicit DSL grammar, the developer communicates their intendeddomain implicitly, by providing a corpus of programs in a general-purpose language. From these examples, a compiler infers an embeddedDSL and outputs an inductive synthesizer for this specialized domain. We demonstrate the viability of this approach with VERSE (VERified Synthesis Engine), a Coq implementationof theProgramming “Programming byExample” byExample (PbE2) interactionmodel. VERSE comprises a toy general-purpose language and its library of operators, the aforementionedDSL compiler, and a synthesis engine that uses top-down deductive search à la PROSE. It is architected to enable an endto-end, mechanically verified proof of correctness—this component is under ongoing development. VERSE’s implementation is publicly available at https://github.com/gtanzer/verse.
Assessing temporal and spatial features in detecting disruptive users on Reddit

Trolling, echo chambers and general suspicious behaviour online are a serious cause of concern due to their potential disruptive effects beyond social media. This motivates a better understanding of the characteristics of disruptive behaviour on the internet and methods of detection. In this work we focus on Reddit which provides a rich social media platform for community focused interactions. Using network representations of user activity alongside temporal statistics and other features we assess the behaviour of a sample of potentially disruptive users, based on their assigned comment karma (an aggregate of a user's comment up-votes), relative to the wider population. We explore how these signals contribute to the accurate prediction of disruptive users, and note that this is achieved without requiring any semantic analysis. Our results show that it is possible to detect signs of disruptive behaviour with good accuracy using limited inputs that are primarily based on the reply patterns that users generate. This is of potential value for large-scale detection problems and operation across different languages.
NMR of peptides and proteins in oriented membranes

Solid-state NMR spectroscopy is used to determine the structures of membrane peptides and proteins in lipid bilayers. The methodology for membrane protein structure determination using solid-state NMR of oriented lipid bilayer samples is outlined. Recent developments in recombinant bacterial expression systems for the preparation of isotopically labeled membrane proteins, pulse sequences for high-resolution spectroscopy, and structural indices that guide the structure assembly process greatly extend the capabilities of the technique. © 2002 Wiley Periodicals, Inc. Concepts in Magn Reson 14, 212–224, 2002.
Explorer Proof-of-Burn

Proof-of-burn has been used as a mechanism to destroy cryptocurrency in a verifiable manner. Despite its well known use, the mechanism has not been previously formally studied as a primitive. In this paper, we put forth the first cryptographic definition of what a proofof-burn protocol is. It consists of two functions: First, a function which generates a cryptocurrency address. When a user sends money to this address, the money is irrevocably destroyed. Second, a verification function which checks that an address is really unspendable. We propose the following properties for burn protocols. Unspendability, which mandates that an address which verifies correctly as a burn address cannot be used for spending; binding, which allows associating metadata with a particular burn; and uncensorability, which mandates that a burn address is indistinguishable from a regular cryptocurrency address. Our definition captures all previously known proof-of-burn protocols. Next, we design a novel construction for burning which is simple and flexible, making it compatible with all existing popular cryptocurrencies. We prove our scheme is secure in the Random Oracle model. We explore the application of destroying value in a legacy cryptocurrency to bootstrap a new one. The user burns coins in the source blockchain and subsequently creates a proof-of-burn, a short string proving that the burn took place, which she then submits to the destination blockchain to be rewarded with a corresponding amount. The user can use a standard wallet to conduct the burn without requiring specialized software, making our scheme user friendly. We propose burn verification mechanisms with different security guarantees, noting that the target blockchain miners do not necessarily need to monitor the source blockchain. Finally, we implement the verification of Bitcoin burns as an Ethereum smart contract and experimentally measure that the gas costs needed for verification are as low as standard Bitcoin transaction fees, illustrating that our scheme is practical.
BATCH AND STREAM BIG DATA PROCESSING PLATFORM: CASE OF NETWORK TRAFFIC ANALYSIS

While scientific data is usually processed with specialized software, more and more institutions make use of new developments in Big Data for processing all the ancillary data that accompany experimental research and scientific computing. One common use case is monitoring of the experiments and the IT infrastructure, but a well-realized Big Data platform can be used to extract useful knowledge from many available data streams. This work describes our efforts to lay out and implement a general-purpose Big Data processing framework capable of both batch and stream operation for use in our institute. As the core, we chose Apache Spark running on cluster resources controlled by Apache Mesos. To demonstrate the functionality of the platform in both modes, we chose a sample problem of local network packet analysis. TCP and IP header fields were aggregated by the source IP and converted to the AGgregate and Mode (AGM) form. After encoding into numerical features, clusterization and principal component analysis was performed. Thus, it was shown that the platform works and can be used for batch processing. The same algorithm will be implemented for online network packet analysis to test the stream processing capability of the platform.