Miracle-dz/UniFAR-FTUs huggingface dataset:
Using Geo-spatial Agent-Based Models for Studying Cities

The agent-based modelling (ABM) paradigm provides a mechanism for understanding the effects of interactions of individuals and through such interactions emergent structures develop, both in the social and physical environment of cities. This paper explores how through the use of ABM, and its linkage with complexity theory, allows one to create agent-based models for the studying cities from the bottom-up. Specifically the paper focuses on segregation and land-use change. Furthermore, it will highlight the growing interest between geographical information systems (GIS) and ABM. This linkage is allowing modellers to create spatially explicit agent-based models, thus relating agents to actual geographical places. This approach allows one to explore the link between socio-economic geography of the city and its built physical form, and can support decision-making regarding interventions within the social and physical environment.
Desarrollo de sistema de curado por efecto Joule en nanocompuestos de matriz termoestable con aplicaciones en la industria aeronáutica

espanolEn la actualidad, el curado de cualquier material termoestable se lleva a cabo utilizando una fuente de calor que normalmente es un horno de grandes dimensiones, con el consiguiente enorme gasto energetico La idea principal del presente trabajo es la consecucion del curado de un termoestable mediante corriente electrica por efecto Joule, que reduciria en una gran proporcion este enorme gasto. Para conseguir que el termoestable pase de tener conductividades electricas mas altas, se ha introducido en el material bicomponente una concentracion del 3 % de nanotubos de carbono. El seguimiento del curado por efecto Joule se ha realizado mediante reologia. Para ello, se ha utilizado la geometria de platos paralelos en los que a cada plato inferior y superior, ahora considerados los bornes, son soldados a los terminales positivo y negativo de la salida de una fuente de alimentacion en continua. La diferencia de potencial introducida entre dichos platos produce la corriente electrica, la cual produce el aumento de temperatura deseado. Se utilizo la tecnica de la termogravimetria para estudiar la influencia de la presencia de los nanotubos en la degradacion del material. La calorimetria diferencial de barrido nos permitio saber si el grado de curado alcanzado y la transicion vitrea son adecuadas para la aplicacion requerida. Una vez conocido el comportamiento del material durante el curado por efecto Joule, llevado a cabo en el reometro, se implemento el sistema a escala de laboratorio. EnglishNowdays, the curing of any thermoset material is performed using a heat source, that generally is a huge furnace. This furnace tipically needs a lot of energy. The main target of the present work is the achievement of the curing of a thermoset material using the Joule effect. This will reduce the amount of energy needed to achive the curing process. In order to decrease the resistivity of the material, multiwall Carbon Nanotubes have been introduced in the material at a concentration of 3 % over the percolation threshold. The curing of the composite that is driven by the heat produced by the Joule effect has being followed by rheology. In order to do that, we have used aluminium parallel plate geometries where each plate is soldered to the positive and negative terminals of a DC source. The voltage difference between both plates produces the electrical current that gives the commanded increase in temperature. The termogravimetic technique was used to characterize the impact of the Carbon nanotubes on the degradation of the composite. The calorimetric technique allowed us to be sure that the conversion percent reached and the glass transition of material is suitable for the required application. Once the material´s behavior during the curing process is known, a prototype was built.
Experiences regarding Home Care for Older Adults from the Viewpoint of Family, Paid Caregivers, Nurses, and Experts: A Qualitative Study

Home care (HC) is recommended for older adults who want to live at home as long as possible despite life-limiting conditions. It is more convenient and cost-effective than institutionalization and hospitalization. However, HC for older adults in Iran faces many challenges. The purpose of this study was to explore the perspectives of different stakeholders involved in HC for older adults about their experiences and suggestions for HC improvement. This qualitative study was conducted based on the explorative content analysis approach between 2021 and 2022 in Tabriz, Iran. The participants were selected using the purposeful sampling method, and the data were collected through in-depth semistructured personal interviews. A total of 27 individuals who participated in individual interviews were family members, HC workers (including nurses and unqualified paid caregivers), heads of counseling and nursing care at home centers, and experts who had clinical or research experience in the field of geriatric care. Collected data were categorized into three main themes: defects in home care governance, concern about the efficiency of home care, and caregivers’ job security concerns. These themes reflected the problems of HC, such as conflicts between multiple trustees, lack of evaluation and monitoring, inadequate competence and financial barriers of families and caregivers, and poor integration and coordination of services. Therefore, it is recommended to develop a national model for HC for Iranian older adults and allocation of different financial resources for HC, implementing quality improvement and evaluation tools, enhancing the training of caregivers, providing them with adequate compensation and benefits, and ensuring the safety and quality of services. These findings can inform the policymakers and planners of care services about the needs and challenges of this population and facilitate the collaboration among different stakeholders to provide better HC for older adults.
Identifying Languages using Support Vector Machines

The current spread of Internet makes it possible to find online information in a great number of languages. Tasks involving automatic processing of this information may require the identification of the language in which it is written. In this work. we explored the use of Support Vector Machines, a relatively new classification technique from · the machine learning field, for generating language classifiers to distinguish English from any other language in written texts. We' have trained and tested Support Vector Machines, representing documenta as feature vectors based on the occurrence of character sequences in texts (N-Grams). Our empirical resulta show that the Support Vector Machines technique is suitable for the language identi fication task, building very accurate linear classifiers.
Computation and Modeling of the Variability in Electron Concentration and Refractive Index for (cid:1780) (cid:2779) Layer at Pakistan Region

: The ionosphere is electrically conducting region of the upper atmosphere, plays an important role in the ionospheric region on electromagnetic waves of 3 MHz to 30 MHz transmitted from ground station to reach to a receiving station. The low-frequency is limited by signals reflected from ionosphere and other range of frequencies are refracted from ionosphere layers depending upon time, height, season, temporal variations due to solar radiations, Sunspots and Earth magnetic field variations. In this communication the (cid:9) (cid:2870) (cid:3) layer data recorded at SUPARCO Islamabad Ionosphere Station (SIIS) for the year 2005 has been used to compute useful ionosphere parameters in respect of ordinary critical frequency (3.04 to 8.29 MHz) at different altitudes of ionosphere with variation in ion composition of (cid:9) (cid:2870) layer. The geographic location of SIIS is latitude 33.75°N and longitude 72.87°E. The critical frequency and height recorded on hourly basis have been used to compute the ionosphere parameters such as electron concentration and refractive index. The temporal estimation of parametric variability is determined, for estimation and modeling purposes standard statistical techniques have been preferred for regression and autocorrelation according to suitability of data trend/pattern. The aspect of study is useful in predicting and forecasting for sky wave communication. The result derived from study is useful for public, governmental and private sector organizations dealing with the business of radio wave communication in the region of Pakistan.
Diagnosis and Treatment of Fabry Disease - A Review

Fabry disease is a rare lysosomal storage disease that is caused by the irregular degradation of a fatty acid. This disease causes a multisystem disorder affecting mainly the heart and kidneys due to the accumulation of the fatty acid Gb3. There is a classical presentation of Fabry, where patients show symptoms in childhood or early adolescence as well as late onset where patients show symptoms later in life in the third or fourth decade. Early diagnosis is imperative for the success of treatment. This review focuses on symptoms, diagnostic steps, treatment, and future research of Fabry disease.
Indonesian Journal of Crop Science

Areca nut is one of Indonesia’s leading export commodities that must adhere to certain phytosanitary requirements, including being pest-free. It is infested by several types of insect pests during the storage process. Therefore, this study aims to determine the diversity of warehouse pests that infest areca nuts. It was conducted using a survey method at three warehouses of large collectors and exporters of areca nut in the Padang city and the Padang Pariaman regency. The purposive sampling method was adopted to collect samples from three traders' warehouses. Furthermore, the nut was taken diagonally in a pile, namely the corner and center of 1 kg each, and repeated 4 times. The identification key was used to identify 15 insect types from 10 families and 3 orders. The Cryptolestes pusillus , C. ferugineus , and Carpophilus sp . were found with the highest number of individuals in each warehouse.The diversity index of the three warehouses is 1.78, 2.14, and 1.90 indicating a moderate level. Additionally, the similarity index between warehouses shows a high and very high level of species similarity.
Oﬀ-line Signature Veriﬁcation: A Circular Grid-Based Feature Extraction Approach

A new technique for feature extraction based on a circular grid is proposed in this paper for oﬀ-line signature veriﬁcation. Grapho-metric features for this new grid geometry are deﬁned by adapting similar features available for rectangular grids. A Support Vector Machines (SVM) based classiﬁer scheme is used for classiﬁcation tasks and a comparison between the rectangular and the circular grid approaches for feature extraction is performed. Experimental results show improvements in the veriﬁcation performance with respect to the case of using rectangular grid based features, especially in the discrimination of simple and skilled forgeries.
Capital Inflows and Domestic Credit Growth: Empirical Evidence from Emerging Market and Developing Economies

This study investigates the extent to which capital inflows and their composition affect domestic credit growth in emerging market and developing economies (EMDEs) and the role of institutional quality in mediating the capital inflows and domestic credit growth nexus. Using a sample of 130 EMDEs from 1991-2015, the study uses generalized method of moments to control for endogeneity issues. The study makes notable contributions to literature and policy discourse. First, this is the first empirical study that documents the persistence of domestic credit growth in EMDEs. Second, the study provides a granular analysis of the capital inflows – domestic credit growth nexus. Whereas gross capital inflows significantly exert a positive impact on domestic credit growth, disaggregated-level analyses showed that only foreign direct investment positively affects domestic credit growth whereas portfolio equity has a negative effect; and portfolio debt and other investment do not. Third, the study adds novel evidence that institutional quality plays a crucial role in mediating the capital inflows – domestic credit growth nexus. Fourth, this study crystallises the lens used to investigate the interactions between capital inflows and institutional quality in analysing the capital inflows – domestic credit growth nexus. Finally, the findings are helpful for designing and implementing macro-financial policy and strengthening institutions, especially in managing capital flows and financial sector.
Automated Novel Heterogeneous Meditation Tradition Classification via Optimized Chi-Squared 1DCNN Method

The realm of human-computer interaction delves deep into understanding how individuals acquire knowledge and integrate technology into their everyday lives. Among the various methods for measuring brain signals, electroencephalography (EEG) stands out for its non-invasive, portable, affordable, and highly time-sensitive capabilities. Some researchers have revealed a consistent correlation between meditation practices and changes in the EEG frequency range, observed across a wide array of meditation techniques. Furthermore, the availability of EEG datasets has facilitated research in this field. This study explores the effectiveness of the One-Dimensional Convolutional Neural Network (CNN-1D) based novel classification method, which impressively achieved an 62% training accuracy, showcasing the robustness of these models in meditation classification tasks. The proposed methodology unveiling a novel method to differentiate neural oscillations in 4 types of meditators and control. This approach analyzes an EEG dataset of highly experienced meditators practicing Vipassana (VIP), Isha Shoonya (SYN), Himalayan Yoga (HYT), and untrained control subjects (CTR) by employing chi-square, CNN, hyperparameter models for data analysis, The outcomes indicate that different meditation types exhibit distinct cognitive features, enabling effective differentiation and classification.
Inference Control in Statistical Databases

Advances in Inference Control in Statistical Databases: An Overview. - Advances in Inference Control in Statistical Databases: An Overview. - Tabular Data Protection. - Cell Suppression: Experience and Theory. - Bounds on Entries in 3-Dimensional Contingency Tables Subject to Given Marginal Totals. - Extending Cell Suppression to Protect Tabular Data against Several Attackers. - Network Flows Heuristics for Complementary Cell Suppression: An Empirical Evaluation and Extensions. - HiTaS: A Heuristic Approach to Cell Suppression in Hierarchical Tables. - Microdata Protection. - Model Based Disclosure Protection. - Microdata Protection through Noise Addition. - Sensitive Micro Data Protection Using Latin Hypercube Sampling Technique. - Integrating File and Record Level Disclosure Risk Assessment. - Disclosure Risk Assessment in Perturbative Microdata Protection. - LHS-Based Hybrid Microdata vs Rank Swapping and Microaggregation for Numeric Microdata Protection. - Post-Masking Optimization of the Tradeoff between Information Loss and Disclosure Risk in Masked Microdata Sets. - Software and User Case Studies. - The CASC Project. - Tools and Strategies to Protect Multiple Tables with the GHQUAR Cell Suppression Engine. - SDC in the 2000 U.S. Decennial Census. - Applications of Statistical Disclosure Control at Statistics Netherlands. - Empirical Evidences on Protecting Population Uniqueness at Idescat.
Evaluation of Extreme Programming Design Approach: A Replicated Study

Evolutionary Design is Extreme Programming’s approach to organize software structure and its relationships, encouraging refactoring, test driven development and the simplest solution for the requirements of a single iteration, thus avoiding a big up-front design activity at the beginning of the project that can cause carrying on a huge structural complexity throughout the whole project. In order to contrast this approach with a planned or traditional design approach, an empirical evaluation of impact on software design quality and process productivity has been designed and conducted in an academic environment with toy size problems. Experimental studies planning details are presented, and two replications with different experimental designs are described. Results suggest that there are no differences in quality between both approaches, and that productivity is better when a planned design is adopted.
Neurobehavior of exploring AI agents

We study intrinsically motivated exploration by artificially intelligent (AI) agents in animal-inspired settings. We construct virtual environments that are 3D, vision-based, physics-simulated, and based on two established animal assays: labyrinth exploration, and novel object interaction. We assess Plan2Explore (P2E), a leading model-based, intrinsically motivated deep reinforcement learning agent, in these environments. We characterize and compare the behavior of the AI agents to animal behavior, using measures devised for animal neuroethology. P2E exhibits some similarities to animal behavior, but is dramatically less efficient than mice at labyrinth exploration. We further characterize the neural dynamics associated with world modeling in the novel-object assay. We identify latent neural population activity axes linearly associated with representing object proximity. These results identify areas of improvement for existing AI agents, and make strides toward understanding the learned neural dynamics that guide their behavior.
Recommended 3D Workﬂow for Digital Heritage Practices

This paper addresses the concerns of the digital heritage ﬁeld by setting out a series of recommendations for establishing a workﬂow for 3D objects, increasingly prevalent but still lacking a standardized process, in terms of long-term preservation and dissemination. We build our approach on interdisciplinary collaborations together with a comprehensive literature review. We provide a set of heuristics consisting of the following six components: data acquisition, data preservation, data description, data curation and processing, data dissemination, as well as data interoperability, analysis and exploration. Each component is supplemented by suggestions for standards and tools, which are either already common in 3D practices or represent a high potential component seeking consensus to formalize a 3D environment ﬁt for the Humanities, such as eﬀorts carried out by the International Image Interoperability Framework (IIIF). We then present a conceptual high-level 3D workﬂow which highly relies on standards adhering to the Linked Open Usable Data (LOUD) design principles.
Trade Effects of Regional Economic Integration in Tajikistan: The Case of EurAsEC

Since URSS was disintegrated, after several years of civil war and with a seriously weakened economy, Tajikistan begins a process of regional integration in the second part of the 1990's, by signing several economic integration agreements with ex-soviet countries and with other neighborhood countries. The most significant regional agreement involving this country and having better prospects for the future is the Eurasian Economic Community (EurAsEC), formed in 2000. The analysis of the different regional integration options followed by Tajikistan, as well as other initiatives of an insert into the global economy is undertaken in chapter two. In this context, the ultimate goal of the research is to analyze the effects of this integration agreement for Tajikistan’s economy and, in particular, for the foreign trade in this country. Before turning to the empirical analysis, chapter one review the economic and empirical literature on economic integration, focusing on the potential effects which the theory of economic integration attributes to a preferential agreement, both the static effects covered by traditional theories and the dynamic effects in which the new economic integration theory is focused, in particular for developing countries. Once the theoretical part is addressed, two chapters are devoted to the empirical analysis of the effects of EurAsEC for Tajikistan. First, in chapter three, by estimating an augmented gravity model using panel data for the period 1995-2013, we analyze static trade creation and trade diversion effects of EurAsEc on the area as a whole and on Tajikistan. Chapter four study the dynamic effects of EurAsEc in Tajikistan, by focusing on the effects on economic growth, and shows evidence on several integration factors influencing the desirability of developing countries to participate in regional integration agreements (such as economic development objective, market-related and trade-related determinant).
Screening Circulating Tumor Cells as a Non-invasive Cancer Test in 1,585 Asymptomatic Adults (ICELLATE1)

Cancer screening is an approach to reduce cancer-related morbidity and mortality rates. Among those screening tests that have been shown to lead to reduction in cancer deaths 2 tissue biomarkers, PSA and CA-125 have shown to contribute to clinical utility. No tumor marker has however been identified to date that is sufficiently sensitive or specific to be used on its own to screen for cancer. Screening for circulation tumor cells as a new biomarker in the blood therefore seems like an attractive possibility. Cancer is known to spread circulating tumor cells before symptoms occur. Therefore, we have screened 1,585 asymptomatic individuals of age 20 to 80 with no known cancer risk factors. 27 individuals showed one or more circulating tumor cell in a 7.5 ml blood sample, which constitutes a positive circulating tumor cell test, based on the iCellate IsoPicTM laboratory test. That number compares favourably with the cancer incidence of 157.1 per 100,000 people per year in Peru, given that the screening results would be expected to correspond to an accumulated incidence of up to 12 years. The present findings therefore identify circulating tumor cells as a promising new cancer screening test.
Lexical Disambiguation MSc Project 2014-2015 - Progress Report

Word Sense Disambiguation is an open problem of Natural Language processing which consists in identifying the sense intended by an ambiguous word used in a sentence. A large number of approaches have been studied to solve the problem, notably the application of machine learning techniques to WSD. This project aims to apply a graph-based technique that consists in performing the Personalized PageRank algorithm (PPR) on WordNet definitions, and to improve it by combining several knowledge resources.