Miracle-dz/UniFAR-FTUs huggingface dataset:
A Continuous Actor-Critic Reinforcement Learning Approach to Flocking with Fixed-Wing UAVs

Controlling a squad of ﬁxed-wing UAVs is challenging due to the kinematics complexity and the environmental dynamics. In this paper, we develop a novel actor-critic reinforcement learning approach to solve the leader-follower ﬂocking problem in continuous state and action spaces. Speciﬁcally, we propose a CACER algorithm that uses multilayer perceptron to represent both the actor and the critic, which has a deeper structure and provides a better function approximator than the original continuous actor-critic learning automation (CACLA) algorithm. Besides, we propose a double prioritized experience replay (DPER) mechanism to further improve the training eﬃciency. Speciﬁcally, the state transition samples are saved into two diﬀerent experience replay buﬀers for updating the actor and the critic separately, based on the calculation of sample priority using the temporal diﬀerence errors. We have not only compared CACER with CACLA and a benchmark deep reinforcement learning algorithm DDPG in numerical simulation, but also demonstrated the performance of CACER in semi-physical simulation by transferring the learned policy in the numerical simulation without parameter tuning.
Formalizing and Verifying Generations of AKA Protocols Master Thesis

Mobile networks are connecting the world. More and more mobile network subscribers rely on a secure connection for their communication. The Authentication and Key Agreement (AKA) protocol variants used in mobile networks are crucial to ensure integrity and confidentiality of communication. In this thesis, we analyze different AKA protocol variants currently deployed by leveraging formal models and the Tamarin security protocol verification tool. Specifically, we first formally model individual AKA protocol variants and present the necessary requirements, i.e., minimal assumptions, to satisfy certain security properties. Second, we provide a comparison of the resulting security guarantees of individual AKA protocol variants. Finally, we formally analyze combinations of AKA protocol variants to model the co-existence of multiple mobile network generations. The analysis shows that newer AKA protocol variants improve security guarantees compared to older variants. However, the newest standard is still unable to satisfy certain security properties without extra assumptions that are not part of the actual protocol specification. When combining multiple AKA protocol variants, as happens in the real world, stronger assumptions must be made to satisfy the same security properties.
Supply–Demand Coupling Mechanisms for Policy Design

Ecosystem services are important for sustaining human survival and sustainable socio-economic development. For the past two decades, ecosystem services studies have greatly promoted the application of ecosystem services science in conservation. As a scientific method to integrate multi-regional and multi-scale ecosystem service providers and beneficiaries, ecosystem service supply and demand coupling mechanisms and payments for ecosystem services programs are closely linked. In this paper, we first provide an overview of the payments for ecosystem services concept and an evaluation of its effectiveness in implementation. We then analyze the correlation between payments for ecosystem services and supply–demand coupling mechanisms and propose a framework to link these two ideas. China’s practice in implementing ecological redline policy and institutional reforms for protected area management will provide a good experimental platform for comprehensive payments for ecosystem service design and effectiveness evaluation within China and beyond.
WAVENUMBER-FREQUENCY SPECTRA OF ATMOSPHERIC TEMPERATURE , ZONAL AND MERIDIONAL WINDS IN LOW LATITUDES ON MARS

Introduction: Atmospheric waves in the Martian atmosphere have been studied since Zurek (1976; 1980; 1981) started theoretical studies on atmospheric thermal tides embedded in observations by the Viking Landers. In 1990’s, Wilson and Hamilton (1996) analyzed Viking/IRTM data to clarify thermal tides and simulated them. Hollingsworth et al. (1997) suggested the existence of “storm zone” such as storm tracks in the terrestrial atmosphere by numerical simulations of baroclinic waves. Since 2000’s, various atmospheric waves have been detected in atmospheric temperature data observed by Thermal Emission Spectrometer onboard Mars Global Surveyor (MGS/TES). However, what has been well investigated are relatively large scale waves with wavenumber 1-3 such as baroclinic wave in the winter hemisphere and planetary wave in middle and high latitudes. Atmospheric waves except for migrating and non-migrating thermal tides have not been reported in low latitudes, although atmospheric waves excited by diabatic heating associated with dust events and water ice clouds are expected to exist. In this study, we calculate wavenumber-frequency spectrum of atmospheric temperature T, zonal and meridional winds U and V, and detect all of resolvable atmospheric waves in low latitudes on Mars.
CASC 2 / miR ‐ 18 a ‐ 5 p axis regulates the malignant potential of nasopharyngeal carcinoma by targeting RBBP 8

Nasopharyngeal carcinoma (NPC) is a prevalent head and neck tumor which has a high mortality rate in Southeast Asia, especially in Southern China. Cancer susceptibility candidate 2 (CASC2) is a newly identified long non‐coding RNA (lncRNA) that has been found to play a suppressive role in several types of tumors. However, the expression and functional role of CASC2 in NPC are still unclear. In the present study, using NPC tissues, cells and transplanted mice, we investigated the mechanism of CASC2-mediated regulation of NPC. We showed that the CASC2 level is reduced in NPC tissues and cells. CASC2 downregulation promoted proliferation and inhibited apoptotic cell death in NPC cells. In contrast, CASC2 upregulation inhibited proliferation and increased apoptosis. There were putative binding sites of microRNA (miR)-18a-5p in the promoter of CASC2. The level of miR-18a-5p was upregulated in NPC tissues and cells. We further confirmed that CASC2 could directly bind with miR-18a-5p and inhibit miR-18a-5p expression, using reporter gene and RNA immunoprecipitation assays. miR-18a-5p suppressed CASC2 upregulation-mediated decrease in proliferation and increase in apoptotic cell death. Bioinformatics predicted the putative binding site of miR-18a-5p in the 3' untranslated region of C-terminal binding protein interacting protein (CtIP)/RBBP8. It was further confirmed that miR‐18a‐5p could directly bind with RBBP8 and inhibit RBBP8 expression. Downregulation of RBBP8 inhibited the anti-miR-18a-5p-mediated increase in apoptosis and decrease in proliferation. Downregulation of CASC2 increased tumor growth, increased the level of miR-18a-5p and decreased RBBP8 expression in vivo. In summary, CASC2 regulates NPC malignancy through modulation of RBBP8 via sponging miR‐18a‐5p. Our findings highlight the CASC2/miR-18a-5p/RBBP8 axis in NPC pathogenesis and provide new biomarkers and potential targets for the therapy of NPC.
N-nitrosamine formationduringchlorination/chloramination of bromide-containingwater

Z. Chen (corresponding author) L. Yang X. Zhai S. Zhao A. Li J. Shen State Key Laboratory of Urban Water Resources and Environment, School of Municipal & Environmental Engineering, Harbin Institute of Technology, The Second Campus, Harbin Institute of Technology, P.O. Box 2606, Harbin 150090, China E-mail: zhonglinchen@263.net; zhonglinchen@hit.edu. cn This study investigated the impact of bromide on the formation of N-nitrosamines during chlorination and chloramination, and tried to identify the reactive intermediates responsible for variations in the yield of N-nitrosamines. As an intermediate of the reaction between bromide and HOCl, bromine chloride (BrCl) may improve the yield of N-nitrosodimethylamine (NDMA) formation. But increasing the amount of bromide added would result in BrCl being converted into HOBr, which is a weaker oxidant than HOCl. This would result in less nitrite being formed, leading to a decreased yield of NDMA via the nitrosation pathway. When NH4 , was present with the bromide during chlorination, both the rate of formation and yield of N-nitrosamines were improved markedly by highly reactive bromamines. Interestingly, bromide had an inhibitory effect on NDMA formation during the chloramination process when tertiary alkylamines, such as 3-(Dimethylaminomethyl) indole (DMAI) and trimethylamine (TMA), were used as precursors. This phenomenon provides indirect evidence for the hypothesis that the pathway of NDMA formation using tertiary amines with DMA groups is different from that of NDMA formation using secondary alkylamines.
PPAR gamma Regulates Mitochondrial Structure and Function and Human Pulmonary Artery Smooth Muscle Cell Proliferation

Pulmonary hypertension (PH) is a progressive disorder that causes significant morbidity and mortality despite existing therapies. PH pathogenesis is characterized by metabolic derangements that increase pulmonary artery smooth muscle cell (PASMC) proliferation and vascular remodeling. PH-associated decreases in peroxisome proliferator-activated receptor g (PPARg) stimulate PASMC proliferation, and PPARg in coordination with PPARg coactivator 1a (PGC1a) regulates mitochondrial gene expression andbiogenesis. To further examine the impact of decreases in PPARg expression on human PASMC (HPASMC) mitochondrial function, we hypothesized that depletion of either PPARg or PGC1a perturbs mitochondrial structure and function to stimulate PASMC proliferation. To test this hypothesis, HPASMCs were exposed to hypoxia and treated pharmacologically with the PPARg antagonist GW9662 or with siRNA against PPARg or PGC1a for 72 hours. HPASMC proliferation (cell counting), target mRNA levels (qRTPCR), target protein levels (Western blotting),mitochondria-derived H2O2 (confocal immunofluorescence), mitochondrial mass and fragmentation, and mitochondrial bioenergetic profiling were determined. Hypoxia or knockdown of either PPARg or PGC1a increased HPASMC proliferation, enhanced mitochondria-derived H2O2, decreased mitochondrial mass, stimulated mitochondrial fragmentation, and impaired mitochondrial bioenergetics. Taken together, these findings provide novel evidence that loss of PPARg diminishes PGC1a and stimulates derangements in mitochondrial structure and function that cause PASMC proliferation. Overexpression of PGC1a reversed hypoxia-induced HPASMC derangements. This study identifies additional mechanistic underpinnings of PH, and provides support for the notion of activating PPARg as a novel therapeutic strategy in PH.
Response assessment in cancer clinical trials

textabstractMost anticancer agents developed over the last four decades are cytotoxic drugs inducing tumor regression, sometimes also resulting in prolongation of survival. Historically, the direct therapeutic efficacy of such treatments has been monitored through successive evaluations of the tumor burden quantified through the measurement of the size of tumor lesions that were clinically or radiologically evaluable. By the end of the 1970’s, a group of breast cancer specialists, under the auspices of International Union Against Cancer (UICC), set the principles under which response to treatment in breast cancer should be evaluated. This work was subsequently adopted and integrated into the recommendations set by the World Health Organisation (WHO) for the evaluation of cancer treatment in solid tumors. After 1981, many new anticancer drugs have been developed, and many researchers have also started to investigate different combinations of treatments. The experience acquired over the years and the lack of details in the WHO recommendations has stimulated the development of modified versions of the WHO criteria. Over the years, the use of the different versions of the original WHO criteria have rendered the accuracy of the relative comparison of the results of investigations based on the same therapy very unreliable. The evolution of cancer imaging, the importance given to “response rate” as an endpoint of early clinical trials and the rapidly increasing number of new anticancer agents to be tested have also justified the initiative to revisit, update the existing response criteria. This thesis focuses on the development and the implementation of a new set of response criteria (RECIST).
Sunset yellow , tartrazine and sodium benzoate in orange juice distributed in Iranian market and subsequent exposure assessment

The usage of coloring agent and preservative including sunset yellow, tartrazine and sodium benzoate in orange juice is forbidden in Iran because of bad effects on public health. The present study included 30 samples of orange juice purchased from local market of Tehran in Iran for simultaneous identification and quantification of sunset yellow, tartrazine and sodium benzoate through high performance liquid chromatography (HPLC) with UV detection and ACE C18, 5μm (4.6 × 250 mm) column. The additives were eluted with a mixture of methanol and ammonium acetate as mobile phase at flow rate of 1.0 ml/min and monitored at 230 nm. Exposure assessment (estimated daily intakes) of consumers calculated through official reports on annual orange juice production in Iran. Among the samples analyzed, at least one additive detected in all orange juices. The amount of sunset yellow, tartrazine and sodium benzoate were ranging from 5.84 ± 0.05 to 23.12 ± 0.19; 0.70 ± 0.01 to 2.32 ± 0.01 and 12.23 ± 1.50 to 56.80 ± 2.13 μg/ml, respectively. Satisfactory repeatability with relative standard deviation < 2.03, excellent sensitivity (Limit of detection: 0.20, 0.25, 0.22 μg/ml; Limit of quantification: 0.70, 0.90, 0.80 μg/ml) with recovery more than 96.3% were obtained. Estimated daily intake of sunset yellow, tartrazine and sodium benzoate were 0.85, 0.96 and 1.11mg/kg body weight through orang juice, respectively which was lower than acceptable daily intakes in society of Iran. We concluded that the level of additives found in orange juice does not affect adversely on consumer’s health.
A flexible compositional approach to word sense disambiguation

Word sense disambiguation e a tarefa de identificar qual o significado de uma palavra e utilizado em uma sentenca quando a palavra possui multiplos sentidos. Metodos supervisionados de aprendizado de maquina em que um classificador e treinado para cada palavra distinta em um corpus com o significados das palavras manualmente anotados tem obtido os melhores resultados. Uma possivel desvantagem destes metodos e a falta de flexibilidade devido a necessidade de exemplos anotados para cada palavra no vocabulario. Em contraste, os metodos baseados em conhecimento nao requerem um classificador para cada palavra distinta e sao frequentemente construidos sobre recursos lexico-semânticos como ontologias ou tesauros. Neste trabalho, propomos um algoritmo composicional flexivel baseado em comparacoes entre contexto e glosa, que compara o contexto local de uma palavra, representada por suas palavras vizinhas, com glosas dos possiveis sentidos que uma palavra pode assumir usando uma medida de distância semântica. O algoritmo possui tres componentes, cada um baseado em uma fonte de informacao diferente: (i) frequencia de sentido, obtida pela contagem do numero de vezes que uma palavra ocorre com cada significado em um corpus anotado, (ii) glosa estendida, expansao da definicao de palavras no dicionario usando palavras relacionadas em uma ontologia (por exemplo, carro e automovel), e (iii) exemplos de uso de sentido, obtidos de dicionarios que fornecem frases com exemplos de uso para os sentidos das palavras. Nossa abordagem composicional e flexivel no sentido de que nao depende de exemplos anotados e funciona bem, mesmo quando algumas ou todas as tres fontes de conhecimento mencionadas acima nao estao disponiveis. Avaliamos o desempenho de nosso algoritmo para todas as combinacoes possiveis dos tres componentes, simulando diferentes cenarios de disponibilidade de fontes de conhecimento. O algoritmo alcanca um F1 score de 67,5 quando todos os componentes estao disponiveis, apresentando um resultado favoravel quando comparado com o estado da arte em sistemas baseado em conhecimento que atinge um F1 score de 66,4.
The Parallel and Distributed Future of Data Series Mining Themis

There is an increasingly pressing need, by several applications in diverse domains, for developing techniques able to index and mine very large collections of sequences, or data series. Examples of such applications come from biology, astronomy, entomology, the web, and other domains. It is not unusual for these applications to involve numbers of data series in the order of hundreds of millions to billions, which are often times not analyzed in their full detail due to their sheer size. In this work, we describe past efforts in designing techniques for indexing and mining truly massive collections of data series, based on indexing techniques for fast similarity search, an operation that lies at the core of many mining algorithms. We show that there are two bottlenecks in mining such massive datasets, namely, the time taken to build the index, and the time required to answer exactly similarity queries. In response to these challenges, we discuss novel techniques that adaptively create data series indexes, allowing users to correctly answer queries before the indexing task is finished. We also show how our methods allow mining on datasets that would otherwise be completely untenable, including the first published experiments using one billion data series. Moreover, we present our vision for the future in big sequence management and mining research: we argue that more efforts should concentrate on parallel (including modern hardware optimization opportunities) and distributed solutions, which have until now been largely unexploited.
Panel Data Model For Tourism Demand

This study explained the construction of panel data models, compared the estimation performance of the Fixed Effects model and the Random Effects model. Our novelty model focuses on the 10 best travel destinations according to Tripadvisor award 2018. The most appropriate model is the Fixed Effect model with Individual Effect. The positive effect on Gross Domestic Product (GDP) partially arising from Number of International tourist arrivals, International Tourism Receipts, and International Tourism Expenditures and the negative effect on GDP partially arising from Total Employment in the tourism sector. The International Tourist Arrivals, International Tourism Receipts, International Tourism Expenditures, and Total Employment in the tourism sectors have simultaneous significant influence on GDP and adjusted together can explain changes in GDP by 95.054% from France, UK, Italy, Indonesia, Greece, Spain, Czech Rep., Morocco, Turkey, and the USA while the remaining 4.946% is explained by other variables outside the model.
Measurement of a condition of polarization of optical beams , method Stokes polarimetry , in real time

The technical solution of the method proposed by us relates to the field of optics for the development and creation of the optical devices allowing to measure a condition of polarization of inhomogeneously polarized monochromatic light fields in real time. It can be used and applied in polarimetry to study the structure and properties of substances in the optical industry to improvement the quality and reliability of polarized optical instruments of polarizing optical devices
Effect of Psychological Intervention on Quality of Life of Alcohol Dependents and their Wives

Alcoholism is known to be a cause of widespread misery for the individual and the family causing significant losses for the community and the nation. The purpose of this study was to examine the effect of psychological Intervention on quality of life of alcohol dependents and their wives. The present pre test and post test study involves the 42 alcohol dependents in total, 21 each in the experimental and control group. Initially, “Alcohol Use Disorder Identification Test” was applied on the alcohol dependents. Finally, 42 participants who gave their consent to participate in the study along with their Wives and having age range of 25-35 years were selected for the study. After that 21 each in the experimental and control group were selected randomly. Further, 42 wives 21 each in the experimental and control group of these participants were included in their respective group as the purposively sampling procedure and their quality of life were assessed on WHOQOL‐BREF. Finding the study confirms poor quality of life in alcohol dependents before intervention. The regular follow-up with the family members (wives) in out-patient setting for psychological intervention improving quality of life of alcohol dependents of the experimental group along with their wives than the Control group after intervention.
Topic Modeling Technique for Text Mining Over Biomedical Text Corpora Through Hybrid Inverse Documents Frequency and Fuzzy K-Means Clustering

Text data plays an imperative role in the biomedical domain. As patient’s data comprises of a huge amount of text documents in a non-standardized format. In order to obtain the relevant data, the text documents pose a lot of challenging issues for data processing. Topic modeling is one of the popular techniques for information retrieval based on themes from the biomedical documents. In topic modeling discovering the precise topics from the biomedical documents is a challenging task. Furthermore, in biomedical text documents, the redundancy puts a negative impact on the quality of text mining as well. Therefore, the rapid growth of unstructured documents entails machine learning techniques for topic modeling capable of discovering precise topics. In this paper, we proposed a topic modeling technique for text mining through hybrid inverse document frequency and machine learning fuzzy k-means clustering algorithm. The proposed technique ameliorates the redundancy issue and discovers precise topics from the biomedical text documents. The proposed technique generates local and global term frequencies through the bag-of-words (BOW) model. The global term weighting is calculated through the proposed hybrid inverse documents frequency and Local term weighting is computed with term frequency. The robust principal component analysis is used to remove the negative impact of higher dimensionality on the global term weights. Afterward, the classification and clustering for text mining are performed with a probability of topics in the documents. The classification is performed through discriminant analysis classifier whereas the clustering is done through the k-means clustering. The performance of clustering is evaluated with Calinsiki-Har-abasz (CH) index internal validation method. The proposed toping modeling technique is evaluated on six standard datasets namely Ohsumed, MuchMore Springer Corpus, GENIA corpus, Bioxtext, tweets and WSJ redundant corpus for experimentation. The proposed topic modeling technique exhibits high performance on classification and clustering in text mining compared to baseline topic models like FLSA, LDA, and LSA. Moreover, the execution time of the proposed topic modeling technique remains stable for different numbers of topics.