Miracle-dz/UniFAR-FTUs huggingface dataset:
Study on Unsupervised Statistical Machine Translation for Backtranslation

Machine Translation systems have drastically improved over the years for several language pairs. Monolingual data is often used to generate synthetic sentences to augment the training data which has shown to improve the performance of machine translation models. In our paper, we make use of an Unsupervised Statistical Machine Translation (USMT) to generate synthetic sentences. Our study compares the performance improvements in Neural Machine Translation model when using synthetic sentences from supervised and unsupervised Machine Translation models. Our approach of using USMT for backtranslation shows promise in low resource conditions and achieves an improvement of 3.2 BLEU score over the Neural Machine Translation model.
Multidimensional Relevance in Microblog Search

In Information Retrieval, the assessment of relevance is affected by multiple criteria. This doctoral research aims to understand which relevance criteria or dimensions can aﬀect the eﬀectiveness of Mi-croblog search systems. The research is based on the hypotheses that depending on the search intention, the user will consider diﬀerent criteria and give diﬀerent importance to the various relevance dimensions.
Multilingual Dynamic Topic Model

Dynamic topic models (DTMs) capture the evolution of topics and trends in time series data.Current DTMs are applicable only to monolingual datasets. In this paper we present the multilingual dynamic topic model (ML-DTM), a novel topic model that combines DTM with an existing multilingual topic modeling method to capture cross-lingual topics that evolve across time. We present results of this model on a parallel German-English corpus of news articles and a comparable corpus of Finnish and Swedish news articles. We demonstrate the capability of ML-DTM to track significant events related to a topic and show that it finds distinct topics and performs as well as existing multilingual topic models in aligning cross-lingual topics.
Health Detection of Wheat Crop Using Pattern Recognition and Image Processing

Agriculture plays a vital role in India's economy. 44% of the employment in India is engaged in agriculture and allied activities and it also contributes 17% of the gross value added. As most of the country's people are in the agricultural sector and out of them only a few are literate about how to protect their cultivation ultimately gives rise to severe problems like a low economy in the sector and starvation for the nation. The job of this research is to help the farmers to save crops from disease. The authors came with the thought of combining a pattern recognition method and an image processing technique. The system allows a farmer to follow a particular pattern of growing crops so that threats will be analyzed earlier. Combining this with the power of Internet of Things, the authors can automate the process without the need for human resources. This research can ultimately make the agriculture process faster and farmers can cultivate more in a less amount of time.
Relationship between Herbs with Hepatotoxicity and its Property

Objective:Studied the relation between the hepatotoxicity(HTX) and four characters(FC),five tastes(FT) and channel distributions of herbs.Methods:Applying literature statistic method,add up,classified and analyzed 144 herbs with HTX.Results:Herbs mainly occurs among the herbs that are cold or warm in property,bitter or acrid or sweet in taste,distribute to 1iver,lung channel.HTX Herbs trend it too.Conclusion:There are no relation between herbs property and HTX according to 144 kinds herbs.
Contingent Weighing of Past and Future Decision Outcomes

Juliusson, Á, Karlsson, N. , and Gärling, T. , Contingent Weighing of Past and Future Decision Outcomes. Göteborg Psychological Reports, 2001, 31, No. 5. This research investigated the weighing of past and future outcomes in investment decisions. Building on previous research demonstrating that both past and future outcomes determine choices to continue or discontinue investments, two experiments were conducted with the aim of investigating contingencies of how prior investments and returns are weighed relative to current investments and expected future returns. Experiment 1 tested the hypothesis that a gain-maximizing goal would make participants place less weight on sunk outcomes (prior returns minus prior investments) than would a lossminimizing goal do. Sunk outcomes influenced the decisions but only a main effect of decision goal was observed irrespectively of whether the investments were personal or business. In Experiment 2 the results showed a main effect of bonus although no evidence of an contingent effect for ignoring losses. The main findings of both experiments are that both the past and the future and both past losses and gains influence investment decisions.
Exploiting Frame-Semantics and Frame-Semantic Parsing for Automatic Extraction of Typological Information from Descriptive Grammars of Natural Languages

We describe a novel system for automatic extraction of typological linguistic information from descriptive grammars of natural languages, applying the theory of frame semantics in the form of frame-semantic parsing. The current proof-of-concept system covers a few selected linguistic features, but the methodology is general and can be extended not only to other typological features but also to descriptive grammars written in languages other than English. Such a system is expected to be a useful assistance for automatic curation of typological databases which otherwise are built manually, a very labor and time consuming as well as cognitively taxing enterprise.
Multi-level analysis and recognition of the text sentiment on the example of consumer opinions

In this article, we present a novel multi-domain dataset of Polish text reviews, annotated with sentiment on different levels: sentences and the whole documents. The annotation was made by linguists in a 2+1 scheme (with inter-annotator agreement analysis). We present a preliminary approach to the classification of labelled data using logistic regression, bidirectional long short-term memory recurrent neural networks (BiLSTM) and bidirectional encoder representations from transformers (BERT).
Evaluation of vector embedding models in clustering of text documents

The paper presents an evaluation of word embedding models in clustering of texts in the Polish language. Authors verified six different embedding models, starting from widely used word2vec, across fastText with character n-grams embedding, to deep learning-based ELMo and BERT. Moreover, four standardisation methods, three distance measures and four clustering methods were evaluated. The analysis was performed on two corpora of texts in Polish classified into subjects. The Adjusted Mutual Information (AMI) metric was used to verify the quality of clustering results. The performed experiments show that Skipgram models with n-grams character embedding, built on KGR10 corpus and provided by Clarin-PL, outperforms other publicly available models for Polish. Moreover, presented results suggest that Yeo–Johnson transformation for document vectors standardisation and Agglomerative Clustering with a cosine distance should be used for grouping of text documents.
Specific Energy, Lorentz Factor & WIMP Annihilation

The time dilation formulas of both the Special Relativity and General Relativity could be studied using a factor dependent on specific energy. Should such factor be used to define the relativistic mass, the equation that arises is an approximation of the mass and energy relation. This mathematical definition of mass is finally compared to the equations that define Dark Matter Annihilation into charged states via loop-level processes.
INFLUENCE OF FLY ASH FINENESS AND HIGH REPLACEMENT RATIOS ON CONCRETE PROPERTIES

The influence of fly ash (FA) fineness and a high cement replacement ratio on concrete properties was investigated. Class F FA with an original fineness of 3,150 cm/g (3F) and a high fineness of 5,690 cm/g (5F) was used; high cement replacement ratios of 30%, 40%, 50%, and 60% by FA with different levels of fineness (two groups: 3F30, 3F40, 3F50, 3F60, and 5F30, 5F40, 5F50, 5F60 by weight of cement) were selected to produce the blended cement concrete. Tests regarding the heat of hydration, compressive strength, water absorption, rapid chloride penetration, and Mercury intrusion porosimetry were performed. The FA with fineness of 5,690 cm/g improved concrete properties more effectively than did the FA with fineness of 3,150 cm/g. The compressive strengths of concretes with FA of 40% or less (3F30, 5F30, 5F40) were higher than that of ordinary Portland cement at 91 days. This indicates that the cement replacement ratio by FA should not exceed 40%. The incorporation of FA reduced the maximum heat of hydration, total charge passed, and capillary pores of concrete. Based on the results, FA concrete with fineness of 5,690 cm/g and a cement replacement ratio of 40% had the most influential properties.
Social Learning in General Information Environments

I study a social learning model in which agents make decisions sequentially and learn about an unknown payoff-relevant state through two sources – a signal about the state itself (a state-signal) and a signal about the actions taken by previous agents (an action-signal). Our objective is to provide general conditions on the action-signals that lead the agents to eventually behave as if they know the state, i.e., that lead to information aggregation. When the agents’ action-signals are what I call weakly separating, it is shown that information aggregation occurs when the agents’ state-signals are unboundedly informative in the sense of Smith and Sorensen (2000). This result provides a unifying criterion to evaluate when information aggregation occurs, and shows that it can occur even in very opaque environments. The theory is illustrated with applications to privacy protection on digital platforms, regulation of third-party information provision in social learning environments, and the design of social learning environments when agents suffer “source amnesia”. I also provide sufficient conditions for information aggregation when the state-signals are boundedly informative, and necessary conditions for information aggregation.
Damping Power System Oscillations with Controller using STATCOM

The paper presented here outlines an approach to design a damping controller, which is used for providing the pulses to the gates of the energy storage based type static synchronous compensator (STATCOM). The energy storage type STATCOM is one of the A.C. transmission system devices, which are also known as FACTS devices. It is an advanced flexible device, which controls the injection and absorption of both active and reactive power to the power system. Integrating an energy storage system into a FACTS device helps to provide much-needed flexibility for mitigating transmission-level power flow problems. It also provides a better power oscillations damping. The control strategy is carried out using a proportional-integral controller. The desired model is implemented in MATLAB Simulink using a sim power system toolbox. Power oscillations are introduced in the power system, and their effects on the power system generator’s and load’s current-voltage with and without the use of STATCOM are shown in the Simulink waveform. The simulation results and waveforms are used to verify the effectivity of the proposed control method to provide power oscillation damping.
A Bibliometric Analysis of the HICSS Software Technology Track

The HICSS Software Technology track has a long tradition and many papers have been published as part of its history. Its impact in terms of citations, paper contributions, author share and community impact does not yet seem to have been investigated, though. In particular, software technology has evolved, and as it stands, it is of primary importance for mobile computing, the Internet-of-Things and Cyber-physical Systems. Hence, the development of these topics and the related impact of this track are of particular interest. In this paper, we present a bibliographic analysis as a first step towards such an investigation. We found that the history of the track is indeed noteworthy. Our results include finding a few extremely much cited papers, some curious tendencies, and a generally favourable outlook for HICSS. We found that indeed many papers in the history of this HICSS track addressed mobile technology and are highly cited. Together with providing insight into track, paper and author impact, we also raise questions worth of further investigation to understand the role of the HICSS Software Technology track and its impact on the academic field and society.
EM Identification of Continuous–Time State Space Models from Fast Sampled Data

In this paper we apply the ExpectationMaximization (EM) algorithm to the identification of continuous-time state-space models from fast sampled data. We modify the standard EM formulation, using a parametrization of the sampled-data model in incremental form. This model recovers the underlying continuous-time system when the sampling period goes to zero. Also, the use of the incremental model parametrization shows better numerical behavior for fast sampling rates. We also consider the case of non–uniform sampling and a robust identification procedure that can be applied in the time or frequency domain.
Corruption, Inequality, Poverty and Social Exclusion in Europe

Coruption isa major problem in the world and in the entire Europe. It represents a widespread penomenon and a problem faced by all countries of the world, and the low number of casesin which coruption was eradicated leads to the conclusion that this flagel is a persistent one, once installedbeeinghard to eliminate. Defining and establishing the magnitude of this phenomenon is in the attention of Transparency International, which conducts researches and periodicalsurveys elaboratingreports withcomparative results in order to identify the dynamics of the Corruption PerceptionsIndex in the countries included in the research. In theEuropean Union "coruption continues to be one of the biggest challenges, a phenomenon whichcosts the EUeconomy approximatively 120 billion eurosanually”, is shown in a European Comission release(European Comission, 2014). The paper sought to determinehow theCorruption Perception Index (CPI) has evolved in Europeand to carry out an analisys ofthe corruption level in relation to the development level of a country, and in relation to the level of poverty, inequality and social exclusion recorded in 2010-2016.
The impact of a high-fat diet in mice is dependent on duration and age, and differs between muscles

ABSTRACT Prolonged high-fat diets (HFDs) can cause intramyocellular lipid (IMCL) accumulation that may negatively affect muscle function. We investigated the duration of a HFD required to instigate these changes, and whether the effects are muscle specific and aggravated in older age. Muscle morphology was determined in the soleus, extensor digitorum longus (EDL) and diaphragm muscles of female CD-1 mice from 5 groups: young fed a HFD for 8 weeks (YS-HFD, n=16), young fed a HFD for 16 weeks (YL-HFD, n=28) and young control (Y-Con, n=28). The young animals were 20 weeks old at the end of the experiment. Old (70 weeks) female CD-1 mice received either a normal diet (O-Con, n=30) or a HFD for 9 weeks (OS-HFD, n=30). Body mass, body mass index and intramyocellular lipid (IMCL) content increased in OS-HFD (P≤0.003). In the young mice, this increase was seen in YL-HFD and not YS-HFD (P≤0.006). The soleus and diaphragm fibre cross-sectional area (FCSA) in YL-HFD was larger than that in Y-Con (P≤0.004) while OS-HFD had a larger soleus FCSA compared with that of O-Con after only 9 weeks on a HFD (P<0.001). The FCSA of the EDL muscle did not differ significantly between groups. The oxidative capacity of fibres increased in young mice only, irrespective of HFD duration (P<0.001). High-fat diet-induced morphological changes occurred earlier in the old animals than in the young, and adaptations to HFD were muscle specific, with the EDL being least responsive. Summary: High-fat diet induces muscle fibre hypertrophy, an increase in oxidative capacity and accumulation of intracellular lipids, earlier in old than in young mice; these adaptations are muscle specific with the EDL being least responsive.
TRIM32 Drives Pathogenesis in Streptococcal Toxic Shock-Like Syndrome and Streptococcus suis Meningitis by Regulating Innate Immune Responses

Streptococcus suis is an emerging zoonotic agent that causes streptococcal toxic shock-like syndrome (STSLS) and meningitis in humans, with high mortality and morbidity. The pathogenesis of both STSLS and central nervous system (CNS) infections caused by S. suis is not well understood. TRIM32, a member of the tripartite motif (TRIM) protein family, has been reported to regulate host inflammatory responses. In this study, we showed that TRIM32 deficiency significantly reduced the level of bacteremia and the production of proinflammatory cytokines following severe S. suis infection, protecting infected mice from STSLS. ABSTRACT Streptococcus suis is an emerging zoonotic agent that causes streptococcal toxic shock-like syndrome (STSLS) and meningitis in humans, with high mortality and morbidity. The pathogenesis of both STSLS and central nervous system (CNS) infections caused by S. suis is not well understood. TRIM32, a member of the tripartite motif (TRIM) protein family, has been reported to regulate host inflammatory responses. In this study, we showed that TRIM32 deficiency significantly reduced the level of bacteremia and the production of proinflammatory cytokines following severe S. suis infection, protecting infected mice from STSLS. The influence of TRIM32 gene deletion on a range of processes known to be involved in S. suis meningitis was also examined. Both levels of bacterial loads and indications of brain hemorrhage were reduced in infected Trim32−/− mice compared with infected wild-type (WT) controls. We also found that TRIM32 deficiency increased the permeability of the blood-brain barrier (BBB) and the recruitment of inflammatory monocytes during the early course of S. suis infection, potentially limiting the development of S. suis meningitis. Our results suggest that TRIM32 sensitizes S. suis-induced infection via innate immune response regulation.
TPGS-1000 exhibits potent anticancer activity for hepatocellular carcinoma in vitro and in vivo

D-alpha-tocopheryl polyethylene glycol 1000 succinate (TPGS1000) is the most active water-soluble derivative of vitamin E and has been widely used as a carrier of solvents, plasticizers, emulsifiers, absorbent agents and refractory drug delivery systems. However, its anti-hepatocellular carcinoma (HCC) properties have not been explored. HCC cells were treated with different concentrations of TPGS1000. Cell survival was tested by CCK8 assay, and cell migration was tested by wound healing and Transwell assay. EdU staining verified cell proliferation, and signalling pathway was assayed by Western blot analysis. The BALB/c-nu mouse xenograft model was established to test HCC cell growth in vivo. In vitro TPGS1000 significantly inhibited the viability and mobility of HCC cells (HepG2, Hep3B and Huh7) in a dose-dependent manner. Cell cycle analysis indicated that TPGS1000 treatment arrested the HCC cell cycle in the G0/G1 phase, and induction of cell apoptosis was confirmed by TUNEL and Annexin V-7-AAD staining. Further pharmacological analysis indicated that collapse of the transmembrane potential of mitochondria, increased ROS generation, PARP-induced cell apoptosis and FoxM1-p21-mediated cell cycle arresting, were involved in the anti-HCC activity of TPGS1000. Moreover, treatment in vivo with TPGS1000 effectively impaired the growth of HCC xenografts in nude mice.
Social Pressure and Self-Selection in Experimental Policy Evaluation

A leading technique uses randomized experimentation to evaluate the impact of policy interventions. Applications of this technique often measure the impact of an intervention on a self-selected sample. In this paper, I propose that social pressure from the experimenter is a determinant of these selection decisions. I test this hypothesis in the context of a study on a free LED lighting program. Recruitment takes place door-to-door in the suburbs of Chicago. A day before their recruitment visit, each household is informed about the study with a flyer on their doorknob. I isolate the role of social pressure by varying whether households can select out of the study by checking an opt-out box on their flyer. My main finding is that the LED lighting program causes a 15 percent reduction in evening energy use in the sample recruited with an opt-out flyer, whereas no energy savings are observed amongst households recruited with a baseline flyer. Social pressure appears to be the driver of these disparate effects, as the opt-out flyer causes a 13 percent reduction in households answering their door and, conditional on answering, causes a 52 percent increase in selection into the study. These results have important implications for the way evaluation experiments with self-selected samples are conducted, reported, and modeled. ∗I thank Leonardo Bursztyn, Steven Levitt, and, John List for their support with this project. This paper also benefited from conversations with Dan Alexander, Mirthe Boomsma, Luigi Butera, Chris Clapp, Jonathan Davis, Michael Dinerstein, Justin Holz, Jeff Livingston, Fatemeh Momeni, David Novgorodsky, Gautam Rao, Matthias Rodemeier, Sally Sadoff, Joe Seidel, Karen Ye, and many others. I thank Diego Ruiz for providing excellent research assistance. Rob Zakim and the UtilityAPI team provided invaluable support throughout. The design and analysis of this experiment was pre-registered as trial 4476 on the American Economic Association RCT Registry, available at: https://doi.org/10.1257/rct.4476-2.0.
Self-Expandable Metallic Stent Therapy for a Gastrointestinal Benign Stricture

Background/Aims: It is well known that self-expandable metallic stents are useful for the treatment of malignant strictures. Balloon and bougie dilation have received significant attention as a useful treatments for a gastriointestinal benign stricture, but the use of stents has some complications, including perforation and bleeding. We evaluated the clinical effectiveness and procedure- related complications of the use of self-expandable metallic stent therapy in gastrointestinal benign strictures. Methods: We inserted self-expandable metallic stents in 11 patients with benign strictures during the period from January 2003 to May 2007. Eleven patients were included in this study (six males; mean age, 50.9 years). We observed clinical improvement, as well as complications and restenosis during follow-up. We defined “recurrence” as the return of symptoms. Results: The causes of strictures were peptic ulcers (eight cases), corrosive esophagitis (two cases) and an anastomosis site stricture (one case). Three stents migrated within two weeks after placement. The mean length of time of a stent staying in a stricture was 16.1 days (3∼35 days). After stent dilation, none of the patients had dysphagia to solid food or procedure- related complications. During a mean follow-up period of 12.8 months (3∼35 months), the rate of restenosis was 36.4% (4/11 cases). All restenosis cases (two cases of peptic ulcer and two cases of corrosive esophagitis) occurred within three months after stent placement. Conclusions: We conclude that the use of self-expandable metallic stent therapy can be effective and safe for patients with gastrointestinal benign strictures. Restenosis (36.4%) occurred within three months. Future research on the management of gastrointestinal benign strictures is recommended. (Korean J Gastrointest Endosc 2008;37:1-6)