Miracle-dz/UniFAR-FTUs huggingface dataset:
Probabilistic Graphical Models 1.1 Introduction 1.1.1 Problem 1.1.2 Examples

1.1. 1 Problem To model complex data, one is confronted with two main questions: • How to manage the complexity of the data to be processed? • How to infer global properties from local models? These questions lead to 3 types of problems: the representation of data (or how to obtain a global model from a local model), the inference of the distributions (how to use the model), and the learning of the models (what are the parameters of the models? ).
Did the great influenza of 1918–1920 trigger a reversal of the first era of globalization?*

I revisit the 1918–20 pandemic and ask whether it led to a reversal in the rise of trade and financial globalization that preceded it. Using annual data for 17 countries for the 1870–1928 period, a variety of tests and techniques are used to draw some robust conclusions. Overall, the pandemic a century ago interrupted, but did not put an end, to the first globalization of the twentieth century. However, two blocs consisting of combatant and non-combatant countries, experienced significantly different consequences. Globalization was sharply curtailed for the combatant countries while there were few, if any, consequences for globalization in the non-combatant group of countries. That said, there was considerable resilience especially in trade openness among several of the combatant economies. Perhaps changes in the make-up of economic blocs, post-pandemic, is a fallout from shocks of this kind. While there are lessons for the ongoing COVID pandemics differences between the 1920s and today also play a role.
SCIE 3500 Final Report: Bitcoin Trading Agent with Deep Q-Learning Algorithms

This is the ﬁrst half of my capstone project which is a continuation of the RIPS-HK 2018 group project. In this project, I focus on trying diﬀerent ways to implement the deep Q-learning algorithm of the Bitcoin trading agent. Two kinds of neural networks are used: ResNet and recurrent neural network (RNN). I tried two approaches to implement the Q-network: the ﬁrst one is to use the Q-network to map the state to the Q-values of all actions, the other one is to use the Q-network to map both the state and a speciﬁc action to a single Q-value. It turns out that the latter scheme has a better performance in this project. And instead of using the past experience to do memory reply, I tried to use the pre-known optimal policy which turned out to have a much better performance.
A critical review on PCR, its types and applications

The invention of polymerase chain reaction (PCR) has been a milestone in the history of biological and medical sciences. The applications of PCR have not only completely revolutionised the research in the field of molecular genetics as well as animal and plant biotechnology, but the technique has also proved its relevance and ingenious utility in other fields of forensic sciences, molecular systematics, molecular epidemiology, archaeology, anthropology, evolutionary genetics, etc. as well. The conventional PCR led to the emergence of RT-PCR, qPCR and combined RT-PCR/q-PCR. PCR has also enabled the successful completion of the ‘human genome project’ by enabling the amplification and sequencing of the human genes, which has further laid the foundation of genetic engineering and has now even made it possible to make useful changes in the genome of an organism. The variants of PCR are now being successfully used in most of the recent advances made in the sciences of modern era.
Topological expansion in isomorphism theorems between matrix-valued fields and random walks

We consider Gaussian fields of real symmetric, complex Hermitian or quaternionic Hermitian matrices over an electrical network, and describe how the isomorphisms between these fields and random walks give rise to topological expansions encoded by ribbon graphs. We further consider matrix-valued Gaussian fields twisted by an orthogonal, unitary or symplectic connection. In this case the isomorphisms involve traces of holonomies of the connection along random walk loops parametrized by boundary cycles of ribbon graphs.
Preventive Effect of Shenduning Prescription Combined with Hydration Therapy on Contrast Induced Nephronpathy after Elective Percutaneous Coronary Intervention

Objective — To explore the preventive effect of Shenduning prescription combined with hydration therapy on contrast induced nephronpathy (CIN) after elective percutaneous coronary intervention. Methods — 159 patients undergoing selective coronary intervention were divided into simple hydration group, intensive statin group and Shenduning prescription group randomly, with 53 cases in each group. The simple hydration group received conventional drugs for coronary heart disease and preoperative routine hydration therapy. The intensive statin group received intensive treatment with atorvastatin calcium tablets on the basis of the simple hydration group, and the Shenduning prescription group received Shenduning prescription treatment on the basis of the hydration group. Serum creatinine (Scr), malondialdehyde (MDA), superoxide dismutase (SOD) and glomerular filtration rate (eGFR) were detected by blood samples at 24h before and after operation, as well as 72h after operation respectively. The primary endpoint event was the occurrence of CI-AKI. Results — The Scr level of the intensive statin group and the Shenduning prescription group was significantly lower than that of the simple hydration group, while the eGFR level was significantly higher than that of the simple hydration group, which is of statistical significance (P<0.05). The incidence of CI-AKI was 15.1% in simple hydration group, 5.7% in intensive statin group and 3.8% in Shenduning prescription group respectively after operation (x = 5.194, P=0.075), of which there was significant statistical difference between simple hydration group and Shenduning prescription group (x = 3.975, P=0.046). After 72h of the operation, MDA level in Shenduning prescription group was significantly lower than that in simple hydration group and intensive statin group, while its SOD level was significantly higher than that in simple hydration group and intensive statin group, which is of statistical significance (P<0.05). The proportion of abnormal liver function in intensive statin group and the Shenduning prescription group was 13.1% and 3.8%, respectively, and the difference was statistically significant (x = 4.867, P=0.027). Conclusion — The combination treatment of Shenduning prescription with hydration therapy may protect the patient’s renal function after elective coronary interventional therapy, while reducing the incidence of CIN and the oxidative stress reaction caused by contrast agent, thus effectively reducing adverse reactions.
Real-Time Hand Gesture Recognition Using Deep Learning

— With the impetuous advancement of informatics, human knowledge is unable to bridge the boundaries and human computer interaction is paving the way for new eras. Here, a real-time human gesture recognition using an automated technology called Computer Vision is demonstrated. This is a type of noncognitive computer user interface, having the endowment to perceive gestures and execute commands based on that. The design is implemented on a Linux system but can be implemented by installing modules for python on a windows system also. OpenCV and KERAS are the platforms used for the identification. Gesture displayed in the screen is recognized by the vision-based algorithms. Using background removal technique, an assortment of skin color masks was trained by Lenet architecture in KERAS for the recognition. The users have tested and produced over 5000 masks with KERAS to generate 96% more accurate results.
Existence of three-phase interlines on a cerium dioxide surface

The three-phase interline described by a statistical continuum limit (i.e. quasi-boundary) has been postulated to gain a deeper insight into the reduction of CeO2 to CeO1.940 in a LiCl-KCl eutectic melt. Fabrication of a CeO2 superstructure by a condensed-phase method provided a CeO2 (111) surface at the nanoscale, which allowed the three-phase interline to be identified given previously reported quantum confinement effects in quasi-stoichiometric CeO2 nanoparticles. Also, the CeO2 superstructure displays the same crystal lattice planes as a bulk CeO2 grain but the triply degenerate Raman-active peak of the grain is higher by a factor of ~ 2.5 with a wider full width at half maximum.
Synchrotron-Based In Situ Characterization of Carbon-Supported Platinum and Platinum Monolayer Electrocatalysts

A detailed understanding of oxidation/dissolution mechanisms of Pt is critical in designing durable catalysts for the oxygen reduction reaction (ORR), but exact mechanisms remain unclear. The present work explores the oxidation/dissolution of Pt and Pt monolayer (ML) electrocatalysts over a wide range of applied potentials using cells that facilitate in situ measurements by combining X-ray absorption spectroscopy (XAS) and X-ray diffraction (XRD) measurements. The X-ray absorption near edge structure (XANES) measurement demonstrated that Pt nanoparticle surfaces were oxidized from metallic Pt to α-PtO2-type oxide during the potential sweep from 0.41 to 1.5 V, and the transition state of O or OH adsorption on Pt and the onset of the place exchange process were revealed by the delta mu (Δμ) method. Only the top layers of Pt nanoparticles were oxidized, while the inner Pt atoms remained intact. At a higher potential over 1.9 V, α-PtO2-type surface oxides dissolve due to local acidification caused by the oxyg.
Restricted access to a conical intersection to explain aggregation induced emission in dimethyl tetraphenylsilole

The mechanism behind aggregation induced emission (AIE) in the prototypical dimethyl tetraphenylsilole (DMTPS) molecule is investigated with ab initio calculations combining the CASSCF and CASPT2 methods with time-dependent DFT. DMTPS is AIE-active because it is strongly fluorescent in the aggregate phase but only weakly in solution. Based on the results, we introduce a restricted access to a conical intersection (RACI) model to explain AIE in DMTPS. According to the RACI model, excited DMTPS in solution can decay to the ground state because there is an energetically available conical intersection, and this explains the weak fluorescence observed experimentally. The reaction coordinate to the intersection involves mainly a twist of the silole ring and a flapping motion of the phenyl substituents. The behaviour in the aggregate phase is simulated by carrying out calculations of one excited DMTPS molecule embedded in a crystal. Because of steric effects, the conical intersection in the crystal is not accessible energetically, and the molecule fluoresces. Thus, the different energy required to access the conical intersection with the ground state in solution and in the crystal explains the AIE phenomenon. Our results are in good agreement with the experimental photophysical properties (absorption and emission wavelength) of DMTPS. They are also in line with recent experimental results for a phosphole analogue of DMTPS showing that fusion of a benzene ring to the phosphole ring increases the lifetime of the excited state in solution (F. Bu, E. Wang, Q. Peng, R. Hu, A. Qin, Z. Zhao and B. Z. Tang, Chem. – Eur. J., 2015, 21, 4440). The present work, together with our previous study on diphenyl dibenzofulvene (Q. Li and L. Blancafort, Chem. Commun., 2013, 49, 5966), suggests that RACI must be quite a general model to explain AIE in medium sized molecules. It is also consistent with the restriction of intramolecular motion (RIM) mechanism introduced recently to explain AIE, since the intramolecular motions responsible for AIE are those leading to the intersection. Knowledge of the reaction coordinate to access the intersection provides useful guidelines for the design of more efficient luminescent compounds.
Heterogeneous IoT Sensor Data Classiﬁcation for Emergency Detection using Machine Learning

—Inertial Measurement Unit (IMU) and Ultra Wide Band (UWB) sensors were integrated to collect heterogeneous data in a smart factory scenario. In this paper, various machine learning algorithms were used to classify the data with a view to detect normal and anomaly situations based on threshold values of the sensor data. System was simulated using keras with GPU 1xTesla K80, 2496 CUDA cores and 12GB GDDR5 VRAM on top of Google colaboratory. Training and testing data were split into 75% and 25% respectively. Classiﬁcation of the vibration data from the IMU gave Logistic regression (75.9% ), KNN1 (73.37%) and KNN2 (78.4%). In the case of the UWB sensor, KNN1 (100% for movement and respiration), KNN2 (98.60% for movement and 100% for respiration) and Logistic regression gave 100% accuracy both for movement and respiration data. Therefore, it is recommended that based on trade-off, KNN-2 outperformed other machine learning algorithms.
Smart Parking System Based on Internet of Things

: As of late the idea of smart cities have picked up grind notoriety. On account of the development of Internet of things smart city presently is by all accounts attainable. Steady endeavours are being made in the field of IOT so as to augment the efficiency and dependability of urban foundation. Issues, for example, traffic blockage, constrained vehicle leaving offices and street security are being tended to by IOT. In this paper, an IOT based cloud coordinated smart parking system is presented. The proposed Smart Parking system comprises of an on location sending of an IOT module that is utilized to screen and signalize the condition of accessibility of each single parking spot. A versatile application is additionally given that permits an end client to check the accessibility of parking spot and book a parking space in like manner. The paper likewise depicts an elevated level perspective on the system design. Towards the end, the paper talks about the working of the system in type of a utilization case that demonstrates the rightness of the proposed model.
The Design of a Smart City Sonification System Using a Conceptual Blending and Musical Framework, Web Audio and Deep Learning Techniques

This paper describes an auditory display system for smart city data for Dublin City, Ireland. It introduces and describes the different layers of the system and outlines how they operate individually and interact with one another. The system uses a deep learning model called a variational autoencoder to generate musical content to represent data points. Further data-to-sound mappings are introduced via parameter mapping sonification techniques during sound synthesis and post-processing. Conceptual blending and music theory provide frameworks, which govern the design of the system. The paper ends with a discussion of the design process that contextualizes the contribution, highlighting the interdisciplinary nature of the project, which spans data analytics, music composition and human-computer interaction.
Structural and some physical properties of Sodium Boro-phosphate Glass Containing Mill Scale

Sodium boro-phosphate glasses containing different amounts of mill scale (65% FeO and 35% Fe2O3) [an iron industry waste formed during the rolling process to produce steel plates] were prepared by the melt quenching technique. The structure and some physical properties of the prepared glasses were investigated using different tools. The amorphous phase of the prepared glass samples was confirmed from their X-ray diffraction. The experimental and empirical densities were found to increase, while the experimental and empirical molar volumes were found to decrease, as mill scale content was increased. By comparing both the experimental and empirical values of density and molar volume, the amorphous nature and short range order character of the studied glasses was confirmed. It was found also that all glass samples behave like semiconductor and both electronic and ionic conductivities were present in these glasses. The correlated barrier hopping model is the appropriate conduction mechanism. The conductivity was found to increase as mill scale content was increased from 10 to 25 mol%, then decreased at sample contains 30 mol% of mill scale, The IR analysis indicated that the iron cations occupy the glass network modifier positions, while the iron cations occupies the glass network former positions only in the sample containing 30 mol% of mill scale. It indicated also that phosphorous cations occupy mainly the tetrahedral coordination state. The volume, mass and molar magnetic susceptibility measurements exhibited gradual increase as mill scale content was increased in the sample composition and all the samples exhibit paramagnetic character. © 2020 NIODC. All rights reserved
Institutions and Firms’ Organization: Asymmetric Effects of Trade on Productivity and Welfare∗

Contract enforcement and, more generally, the business environment play an important role in a world where producers of final goods need to source inputs from other suppliers. Weak institutions create uncertainty over the provision of intermediate goods demanded by final producers. Firms adapt the organization of their production to the local institutional environment. Compared to other models, we allow heterogeneous producers to choose their sector of production and we study how trade affects the relocation of final producers and resources across sectors. The quality of institutions and the ex-ante distribution of productivity determine the endogenous organization of firms and, in turn, the sector in which each final producer specializes. The best producers are shown to be relatively better at producing more complex goods and choose to specialize in the most complex sectors. We study how trade liberalization leads to asymmetric effects on the allocation of intermediate suppliers across final producers and across industries, as well as on aggregate productivity and welfare, when countries differ in institutional quality. Consistent with results in the literature, the model finds a positive effect of trade liberalization on aggregate productivity in the country with good institutions. On the other hand, it unveils a negative effect in the country with weak institutions. This asymmetric effect is larger when the difference in institutions is higher. In addition a large difference leads consumers from the country with good institutions that benefit from more varieties to lose in terms of purchasing power and aggregate utility.
Effect of different cooking methods on chemical composition, nutritional values,
and sensory properties of Jack bean (Canavalia ensiformis) tempe

Having high protein content, jack bean is a promising resource for making tempe, a traditional fermented food commonly consumed in Indonesia. The current research aimed to investigate the effect of different cooking methods (boiling, steaming, frying, and baking) on a chemical, nutritional, and sensory aspects of jack bean tempe. The results showed that the highest protein content and antioxidant activity of the processed tempe were obtained by steaming method with a value of 380.3 g/kg and 57.8%, respectively. The steaming process could maintain protein and mineral contents as well as the antioxidant activity. The boiled tempe had six time lower of phytic acid compared to that of control. The baking and frying process increased five to six-fold of the fat content, while reduced the protein content by 30%. For the sensory evaluation, the baked tempe obtained the highest score. In conclusion, from a nutritional point of view, steaming is the best method for cooking jack bean tempe, while in term of sensory, baking is recommended.
Land-based wind turbines with flexible rail transportable blades – Part I: Conceptual design and aeroservoelastic performance

Abstract. This work investigates the conceptual design and the aeroservoelastic performance of land-based wind turbines whose blades can be transported on rail via controlled bending. The turbines have a nameplate power of 5 MW and a rotor diameter of 206 m, and they aim to represent the next generation of land-based machines. Three upwind designs and two downwind designs are presented, combining different design goals together with conventional glass and pultruded carbon fiber laminates in the spar caps. The results show that controlled flexing requires a reduction in the flapwise stiffness of the blades, but it represents a promising pathway to increase the size of land-based wind turbine rotors. Given the required stiffness, the rotor can be designed either downwind with standard rotor preconing and nacelle uptilt angles or upwind with higher-than-usual angles. A downwind-specific controller is also presented, featuring a cut-out wind speed reduced to 19 m per second and a pitch-to-stall shutdown strategy to minimize blade-tip deflections toward the tower. The flexible upwind and downwind rotor designs equipped with pultruded carbon fiber spar caps are found to generate the lowest levelized cost of energy, 2.9 % and 1.3 %, respectively, less than the segmented design. The paper concludes with several recommendations for future work in the area of large flexible wind turbine rotors.
Bibliometric study of volatile compounds in commercial fruits of the Solanaceae family

Bibliometric analysis is a discipline that allows us to identify knowledge trends, assesses scientific activity and the impact of research through its volume, evolution, visibility, and structure. The present study aimed to carry out a bibliometric study of scientific research that contributes to the knowledge of Volatile Organic Compounds (VOCs) of edible and commercial fruits of Solanaceae family. The research consisted of extracting the information from papers in the Web of Science database. We analyzed and performed the production, visibility, and impact of these papers, also relationships and collaboration between authors using BibExcel and VOSviewer software. As a result, 178 documents were obtained from 2001 to 2017. Tomato is the fruit with the largest number of related articles that are focused on studying compounds responsible for taste, aroma, and biotic and abiotic relationships, as well as studies for identification of the genes responsible for these organoleptic and ecological traits. Papers analyzed are related to the research studies of 491 authors from 239 different organizations distributed in 45 countries. This bibliometric study allowed to identify trends in the knowledge in VOCs with respect to Solanaceae fruits, as well as recognizing the location of the scientific material in this field.
Thai Digit Recognition on License Plates using YoloV3

Identification of license plate, Thai numerals including logo is proposed using deep learning method. This is done by collecting the Thai character numerals (0-9) from which a dataset is created to identify them and is constructed to train convolutional neural network (CNN). CNN has proved to achieve state-of-the-art results in such tasks such as optical character recognition, generic objects recognition, and real-time face detection and pose estimation, speech recognition, license plate recognition etc. Subsequently, this method involves detection and recognition of all the Thai numeral characters (0-9), using CNN model. With the trained model, character recognition system is designed and implemented. In this thesis we make use of object detection algorithm YOLOV3 with the help of network architecture Darknet. The proposed method includes recognition and character segmentation in a given license plate image. The experimental results indicate that the proposed deep learning algorithm method is efficient in detecting the characters.