Miracle-dz/UniFAR-FTUs huggingface dataset:
Intention-based Behavioral Anomaly Detection

In this work we consider the problem of detecting anomalous deviations from expected behavioral trajectories generated by a multi-agent system. Common methods for time series anomaly detection do not explicitly consider the goal-directed nature of rational agents. This work proposes a method for detection of anomalous behaviors based on agent intent formulated using agent-based Lagrangian Mechanics. We pro-pose an anomaly detection method that simultaneously learns to 1) predict the intended goals of agents from their trajectories, and 2) detect anomalies based on the predictions. The method uses a structured one-class support vector machine (structured OC-SVM), where latent variables represent the intentions (goals) of agents, and SVM weights represent the attraction or repulsion strength of potential goals and obstructions. Model parameters are learned in an unsupervised way. We conduct experiments in a marine surveillance setting, where we monitor high-trafﬁc ports and detect anomalous vessels. Experimental results show that our algorithm shows promise for detecting anomalous behaviors in systems of goal-directed agents.
ON THE CLASS OF ARRAY-BASED APM-LDPC CODES

We construct an explicit class of affine permutation matrix low-density parity-check (APM-LDPC) codes based on the array parity-check matrix by using two affine maps f (x) = x-1 and g(x) = 2x-1 on Z_m, where m is an odd prime number, with girth 6 and flexible row (column)-weights. Simulation results justify well performance, minimum-distances and cycle distribution of these codes in comparison the array-LDPC , structured QC-LDPC and APM-LDPC.
Relations between spectrum curves of discrete Sturm-Liouville problem with nonlocal boundary conditions and graph theory

Sturm-Liouville problem with nonlocal boundary conditions arises in many scientific fields such as chemistry, physics, or biology. There could be found some references to graph theory in a discrete Sturm-Liouville problem, especially in investigation of spectrum curves. In this paper, relations between discrete Sturm-Liouville problem with nonlocal boundary conditions characteristics (poles, critical points, spectrum curves) and graphs characteristics (vertices, edges and faces) were found.
A Markov-Switching Model of Inflation in Bolivia

The Bolivian inflation process is analyzed utilizing a time-varying univariate and multivariate Markov-switching model (TMS). With monthly data and, beginning in the late 1930s, inflation is accurately described by a univariate TMS. The intercept for the high-inflation regime is significantly higher than for the low-inflation regime and the actual inflation rate mirrors the smoothing probabilities of the Markov process. Additionally, the predicted duration of each regime closely fits the periods when the country experienced low and inordinate high inflation rates. From a long-run perspective and utilizing a multivariate TMS, the results generally fall in line with what the quantity theory of money predicts. In the high-inflation regime, money growth increases inflation (almost) one-for-one, as classical economics contends. From a short-run perspective and in the high-inflation regime, inflation is almost exclusively explained by a negative output gap. In the low-inflation regime, lagged inflation is the most important determinant of inflation, in line with price stickiness expectations. Partitioning the sources of inflation demonstrate that, from a long-run perspective and in the high inflation regime, differences in inflation are mostly explained by GDP growth; in the low-inflation regime, money growth and velocity growth are the principal factors explaining the variance of inflation. From a short-run perspective, the output gap explains almost all regression variance in the high-inflation regime, and past inflation does the same during times of low inflation, though in both cases the R2 is low which precludes making definite statements about the sources of variability in inflation.
EFFECT OF FOLIAR FERTILIZATION FOR OLIVE TREES ON THE BIOACTIVE COMPOUNDS, PURITY AND ORGANOLEPTIC ATTRIBUTES OF OLIVE OILS

his investigation was carried out during two seasons 2014 and 2015 at farm located EL -Nobarya, EL-Behera governorate, Egypt, to study the influence of foliar fertilization with soluation of potassium and magnesium sulphate at ratios of 3 and 5% and 0.5 and 1.5%, respectively, on the organolyptic attributes, purity, overall quality index, stability, bioactive compounds (tocopherols, pigments, polyphenols and diortho phenols) and phenolic compounds of Koronaki olive oil under the environmental condition. The results were as follows : the spraying with potassium and magnesium sulphate at ratios of 5% and 1.5% foliar fertilization, respectively, gave the highest positive attribute (fruity) of olive oil, follwed by 3 and 0.5%, respectively compared with the control samples in seasons 2014 and 2015, while the defect properties of olive oil were equal to zero in both treated (foliar fertilized) and untreated (control) samples during two seasons under study. Results showed that the lowest parameters for K232 and K270 nm. of olive oil were obtained when olive trees were foliar fertilization by potassium and magnesium sulphate at different concentrations in two seasons compared with control samples, while Δk recorded slight increase as a result of all previous treatments. Oleuropein, ellagic and E-vanillic phenolic compounds recorded high content compared to other phenolic compounds in the control samples while ellagic compound decreased compared with the control samples during two seasons. Commonly, most phenolic compounds increased as a result of all folair fertilization under study. Foliar fertilization with solution of potassium and magnesium sulphate at all concentrations caused a high increment in Epi-catechin and cinamic compounds in season 2015, whilst these compounds decreased in seasons 2014 compared to control samples . But it caused decrease in carotonoids content in two seasons and also in chlorophylls content in season 2014 only. On the other hand, it caused increase in total tocopherol in two seasons with a higher value (5%) for foliar fertilization. Therefore, folair fertilization by potassium and magnesium sulphate at different concentrations caused increment in di-o-phenols of olive oil compared to the control samples during two seasons. Kaywords: Olive oil, organolyptic attributes, purity, polyphenols, tocophenols, pigments, di-O-phenols, overall quality index and phenolic compounds. T EFFECT OF FOLIAR FERTILIZATION FOR OLIVE TREES ON THE BIOACTIVE COMPOUNDS, PURITY AND ORGANOLEPTIC ATTRIBUTES OF OLIVE OILS 770
OP-MOLB200192 1..13

Novel phenotypes are commonly associated with gene duplications and neofunctionalization, less documented are the cases of phenotypic maintenance through the recruitment of novel genes. Proteolysis is the primary toxic character of many snake venoms, and ADAM metalloproteinases, named snake venom metalloproteinases (SVMPs), are largely recognized as the major effectors of this phenotype. However, by investigating original transcriptomes from 58 species of advanced snakes (Caenophidia) across their phylogeny, we discovered that a different enzyme, matrix metalloproteinase (MMP), is actually the dominant venom component in three tribes (Tachymenini, Xenodontini, and Conophiini) of rear-fanged snakes (Dipsadidae). Proteomic and functional analyses of these venoms further indicate that MMPs are likely playing an “SVMP-like” function in the proteolytic phenotype. A detailed look into the venom-specific sequences revealed a new highly expressed MMP subtype, named snake venom MMP (svMMP), which originated independently on at least three occasions from an endogenous MMP-9. We further show that by losing ancillary noncatalytic domains present in its ancestors, svMMPs followed an evolutionary path toward a simplified structure during their expansion in the genomes, thus paralleling what has been proposed for the evolution of their Viperidae counterparts, the SVMPs. Moreover, we inferred an inverse relationship between the expression of svMMPs and SVMPs along the evolutionary history of Xenodontinae, pointing out that one type of enzyme may be substituting for the other, whereas the general (metallo)proteolytic phenotype is maintained. These results provide rare evidence on how relevant phenotypic traits can be optimized via natural selection on nonhomologous genes, yielding alternate biochemical components.
Analytical Calculation of the Equivalent Circuit Parameters of Non-Salient Pole Large Synchronous Generators

Optimal Design of electrical machines using population-based optimization algorithms needs computationally fast model for evaluating the performance characteristics from design data, i.e. geometric dimensions, winding layouts, material properties. The Electric Equivalent Circuit (EEC) is a simple and appropriate model with acceptable accuracy to be incorporated in the design procedure. In this paper, an analytical approach is presented for calculating the EEC parameters of large non-salient pole synchronous generator based on winding-function method. Although the synchronous generator is well recognized, calculation of its dynamic EEC parameters is not reported in previous studies. Special issues of high-rated industrial synchronous generators are considered such as rotor slots with different dimensions, rotor sub-slots, the damper winding which is created from rotor wedges and retaining rings, saturation of magnetic flux routes in d-q-axis and stator core stacking. The connections of damper windings in d-q-axis and definitions of turn-ratios to refer the parameters to the stator-winding side are of novelties of the research. The calculated parameters for a 200MVA power-plant generator are compared with the experimentally obtained parameters. The results of EEC analysis of the studied machine have acceptable coincidence with the experimental and 2D finite-element simulation results, which proves the validity of the proposed method.
Proposal: Framework for Snarky Ceremonies

Succinct non-interactive arguments of knowledge (SNARKs) have found wide-scale adoption in recent years. The most eﬃcient SNARKs require a distributed ceremony protocol to generate public parameters, also known as a structured reference string (SRS). We propose a general security framework for non-interactive zero-knowledge (NIZK) arguments with a ceremony protocol. In particular, our framework generalizes the notion of updatable reference strings, proposed by Groth, Kohlweiss, Maller, Meiklejohn, and Miers [Crypto, 2018], to multiple independent update phases. Importantly, this allows us to also capture existing setup ceremonies as performed for Groth16 SNARKs.
ACCURATE AIR QUALITY PREDICTION: A PHYSICAL- TEMPORAL COLLECTION MODEL CONFERENCE SUBMISSIONS

Air quality is closely related to public health. Several known health issues such as cardiovascular and respiratory diseases are in connection with long exposure in highly polluted environment. Accurate air quality forecast becomes extremely important, particularly for people living in less developed countries. To estimate the variation and growth of several air pollution concentrations, previous researchers proposed either model-based or data-driven approaches, such as Community Multiscale Air Quality model (CMAQ) and neural networks. These methods either require manual adjustment based on experience or purely learn from existing data and thus struggle to catch the dynamics of air pollutants. This paper proposes a physical-temporal collection (PTC) model to integrate both the model-based and data-driven strategies, aiming to reduce the systematic error and improve forecast accuracy. To validate the proposed method, we collected over two years of air pollutants record in Chengdu, one of the most polluted cities in China, covering a period from January 1st, 2016 to December 31st, 2017. Experiment results show that the proposed PTC achieves excellent performance with the average accuracy improved by 6.9% comparing with the baseline CMAQ model. Furthermore, the model can learn the long and short term effects from historical data, and thus facilitate deployment in the areas that lack trained experts and help vulnerable people to make informed planning for upcoming air pollution.
RELATIONSHIP BETWEEN LEADERSHIP STYLES AND NURSES’ TURNOVER INTENTION IN PUBLIC HOSPITALS: THE CASE OF PUBLIC HOSPITALS IN ADDIS ABABA, ETHIOPIA BY

CHAPTER 1: INTRODUCTION . 1 1.1. Background of the Study.1 1.2. Statement of the Problem.2 1.3. Research Questions.4 1.4. Objectives of the study.4 1.4. 1. General objective . 4 1.4. 2. Specific Objectives . 4 1.5. Research Hypothesis.4 1.6. Definitions of Terms.5 1.7. Significance of the Study.5 1.8. Scope and Limitations of the study.6 1.9. Organization of the Study.6 CHAPTER 2: REVIEW OF RELATED LITERATURE . 7 2.1. Theoretical Literature Review.7 2.1.1. Basic concepts and Definitions . 7 2.1.1.1. Concept of Leadership.7 2.1.1.2. Leadership style.7 2.1.2. Leadership Theories . 8 2.1.2.1. Great-Man Theory.8 2.1.2.2. Trait Theory.9 2.1.2.3. Contingency Theories (Situational). 9 2.1.2.4. Style and Behavior Theory.10 2.1.2.5. Process Leadership Theory.11 2.1.2.6. Transactional Theory.11 2.1.2.7. Transformational Theory.12 2.1.3. Leadership Styles . 12 2.1.4. Turnover Intention . 16
Nanoscale quantitative mechanical mapping of poly dimethylsiloxane in a time dependent fashion

Polydimethylsiloxane (PDMS) is one of the most widely adopted silicon-based organic polymeric elastomers. Elastomeric nanostructures are normally required to accomplish an explicit mechanical role and correspondingly their mechanical properties are crucial to affect device and material performance. Despite its wide application, the mechanical properties of PDMS are yet fully understood. In particular, the time dependent mechanical response of PDMS has not been fully elucidated. Here, utilizing state-of-the-art PeakForce Quantitative Nanomechanical Mapping (PFQNM) together with Force Volume (FV) and Fast Force Volume (FFV), the elastic moduli of PDMS samples were assessed in a time-dependent fashion. Specifically, the acquisition frequency was discretely changed four orders of magnitude from 0.1 Hz up to 2 kHz. Careful calibrations were done. Force data were fitted with a linearized DMT contact mechanics model considering surface adhesion force. Increased Young's modulus was discovered with increasing acquisition frequency. It was measured 878+-274 kPa at 0.1 Hz and increased to 4586+-758 kPa at 2 kHz. The robust local probing of mechanical measurement as well as unprecedented high-resolution topography imaging open new avenues for quantitative nanomechanical mapping of soft polymers, and can be extended to soft biological systems.
A BUSINESS MODEL FOR NURSERY PRODUCTION OF CACTI FROM THE CHIHUAHUAN DESERT A conservation strategy under the administrative process review

With the presence of about 52 genus and 850 species, Mexico is considered as the biggest center of diversity for the Cactaceae family. About 84% of these species are only found in our country and in no other part of the world, consider themselves an endemic family of México. Unfortunately over 75% of all species of cacti are in decline, due to anthropogenic activity. The work performed in nurseries to produce high-quality native and traditional plants helps perpetuate these species. Nursery-grown native plants overcome barriers to natural recolonization, such as weed competition, animal predation and lack of a natural seed bank. There are several steps that need to be completed in order to stablish a plant nursery. Several factors need to be considered, such as the quality of the water, the location, the specific areas of plant production, among others. Planning, organizing, leading and controlling are very important stages of the administrative process that need to be determined for the project to work the best way possible. As a result of this work, a proposal for a CANVAS business model for the production of cactaceae is presented. The documentary analysis carried out shows a potential viability for the development of a project that allows the production of cacti in nurseries for its distribution or commercialization.
Optimum NaHCO3-to-vinasse ratio for Chlorella pyrenoidosa cultivation and poly-b-hydroxybutyrate (PHB) production

Chlorella pyrenoidosa is a microalga that grows best under mixotrophic conditions. The lag phase reflects how long C. pyrenoidosa takes to adapt and grow well in a cultivation medium and also affects the performance of C. pyrenoidosa in the next phase. NaHCO3 is used as an alternative inorganic carbon source during C. pyrenoidosa cultivation. In addition, vinasse is wastewater with potential as an organic carbon source during C. pyrenoidosa cultivation. To determine the optimum NaHCO3to-vinasse ratio, we performed an experiment over 10 d in batch mode with the following six cultivation medium ratio variations: 100% NaHCO3, 80% NaHCO3 and 20% vinasse, 60% NaHCO3 and 40% vinasse, 100% vinasse, 80% vinasse and 20% NaHCO3, and 60% vinasse and 40% NaHCO3. The lag phase of C. pyrenoidosa cultivation was determined using nonlinear logistic, modified Gompertz, and Richard equations. The chemical oxygen demand (COD), dry mass, and poly-β-hydroxybutyrate (PHB) content were measured every day. The ratio of 60% vinasse and 40% NaHCO3 showed the best C. pyrenoidosa growth, the highest biomass productivity, and the shortest lag phase during C. pyrenoidosa cultivation. The lowest and highest COD efficiency was observed with 100% NaHCO3 and 100% vinasse, respectively. In addition, to obtain PHB, the optimum ratio is 20% NaHCO3 and 80% vinasse. A NaHCO3 and vinasse combination is economically feasible and recommended.
A Novel Index Based Search Algorithm on Large Datasets

– As the dimension increases, the complexity to find the nearest neighbor also increases. In one dimension we can find the nearest point very efficiently. But when the dimension increases, the search efficiency depends on how many points we have to search. In this thesis, we propose a simple and efficient technique on how to organize the points in the high dimensional space which also allows searching the nearest point efficiently. We have used a memory efficient database organization of the points in the high dimension, and the searching algorithm is based on limiting the search within some particular indexes of the database. A comparative analysis reveals that our database organization is faster than K-d tree, R-tree , and the searching algorithm is also very efficient.
Anion exchange membranes by bromination of tetramethylbiphenol-based poly(sulfone)s

Anion exchange membranes (AEM) with tunable properties were synthesized via bromination of poly(ether sulfone)s containing tetramethylbiphenol (TMBP) comonomers, followed by bromination, quaternization, and ion exchange. The bromination reactions of poly(ether sulfone)s containing TMBP and tetramethylbisphenol A (TMBA) comonomers were assessed in terms of the composition of the polymers and the molar equivalents of N-bromosuccinimide (NBS). Compared with TMBP-based polymers, TMBA-based poly(sulfone)s were more susceptible to degradation during bromination due to the degradation of the isopropylidene linkage in TMBA under radical conditions, resulting in a weight average molecular weight decrease of 31–43% after bromination. The decrease of molecular weights also became more pronounced when the equivalents of NBS was raised. Polydispersity after bromination increased for both TMBP- and TMBA-based polymers because of side reactions such as branching, crosslinking, and chain scission. For a given ion exchange capacity, the conductivity and water uptake of TMBP-based AEMs were lower than those of the TMBA-based samples, which can be attributed to the relatively rigid TMBP residue. AEMs in this study retained 40–62% of their original conductivity after degradation in 1 M NaOH solution at 90 °C for 500 hours.
1 POPULATION PHARMACOKINETIC / PHARMACOGENETIC MODEL IN 1 CAUCASIAN HIV-INFECTED PATIENTS FOR OPTIMIZATION OF 2 EFAVIRENZ THERAPY 3 4 Running title : POPULATION PHARMACOKINETIC / PHARMACOGENETIC 5 MODEL EFAVIRENZ 6 7

POPULATION PHARMACOKINETIC/PHARMACOGENETIC MODEL IN 1 CAUCASIAN HIV-INFECTED PATIENTS FOR OPTIMIZATION OF 2 EFAVIRENZ THERAPY 3 4 Running title: POPULATION PHARMACOKINETIC/PHARMACOGENETIC 5 MODEL EFAVIRENZ 6 7 Almudena Sánchez, Salvador Cabrera, Dolores Santos, M Paz Valverde, Aurelio 8 Fuertes, Alfonso Domínguez-Gil, María J. García and Tormes Group. 9 10 1 Pharmacy Service, University Hospital of Salamanca, Salamanca, Spain. 11 2 Pharmacy Institute, University Austral of Chile, Valdivia, Chile. 12 3 Departament of Pharmacy and Pharmaceutical Technology, University of Salamanca, 13 Salamanca, Spain. 14 4 Infectious Disease Service, University Hospital of Salamanca, Salamanca, Spain. 15 5 Tormes Group: Miguel Cordero, Alicia Iglesias, Guillermo Luna and Carmen Bustos. 16 17 Correspondence author: 18 Salvador Cabrera Figueroa 19 Servicio de Farmacia. Hospital Universitario de Salamanca 20 Paseo de San Vicente 58 21 37007 Salamanca. España 22 Telephone: +34-923291172 23 Fax: +34-923291174 24 scabrera@uach.cl 25 Copyright © 2011, American Society for Microbiology and/or the Listed Authors/Institutions. All Rights Reserved. Antimicrob. Agents Chemother. doi:10.1128/AAC.00194-11 AAC Accepts, published online ahead of print on 6 September 2011
Super resolution reconstruction of PET images based on deep learning

PET-CT is a high-end medical imaging technology that can detect tumors in the early stage, and has been widely used in clinical practice.Obtaining high-quality images is a prerequisite for doctors to make a correct diagnosis.For PET itself, how to continuously improve its resolution is a challenging problem.In this study, Generative Adversarial Networks (GAN) combined with Wasserstein distance and gradient penalty technology was used to achieve PET image super-resolution reconstruction.The experimental results show that the structural similarity of the final image reaches more than 60%.
Bayesian inference and Internet of Things based plant health care

Advancements in the Internet of things (IoT) enable us to monitor and maintain a variety of devices in various sectors. Based on the literature available, we have found that there are umpteen IoT based methods proposed for plant health care involving hardware interfacing like sensors, micro-controllers, and cameras. The existing solutions also make use of mobile applications, web-servers, data-base for processing of information. This paper presents a novel and simple cost-effective Bayesian theorem based plant-health-care using sensors interfaced with raspberry pi. Our solution also provides users to watch and water the plant remotely, using a smart-phone via web-server. We have considered rose plant ’ s favourable environmental factors for maintaining its health.