Miracle-dz/UniFAR-FTUs huggingface dataset:
Robust shape approximation and mapping between surfaces

This thesis is divided into two independent parts.In the first part, we introduce a method that, given an input tolerance volume, generates a surface triangle mesh guaranteed to be within the tolerance, intersection free and topologically correct. A pliant meshing algorithm is used to capture the topology and discover the anisotropy in the input tolerance volume in order to generate a concise output. We first refine a 3D Delaunay triangulation over the tolerance volume while maintaining a piecewise-linear function on this triangulation, until an isosurface of this function matches the topology sought after. We then embed the isosurface into the 3D triangulation via mutual tessellation, and simplify it while preserving the topology. Our approach extends toDepot de theseDonnees complementairessurfaces with boundaries and to non-manifold surfaces. We demonstrate the versatility and efficacy of our approach on a variety of data sets and tolerance volumes.In the second part we introduce a new approach for creating a homeomorphic map between two discrete surfaces. While most previous approaches compose maps over intermediate domains which result in suboptimal inter-surface mapping, we directly optimize a map by computing a variance-minimizing mass transport plan between two surfaces. This non-linear problem, which amounts to minimizing the Dirichlet energy of both the map and its inverse, is solved using two alternating convex optimization problems in a coarse-to-fine fashion. Computational efficiency is further improved through the use of Sinkhorn iterations (modified to handle minimal regularization and unbalanced transport plans) and diffusion distances. The resulting inter-surface mapping algorithm applies to arbitrary shapes robustly and efficiently, with little to no user interaction.
Voltage Sensitivity-Related Hybrid Coordinated Power Control for Voltage Regulation in ADNs

Voltage is a key operation index for active distribution networks. Coordinated power compensation of distributed energy resources (DERs) has shown promising results in alleviating voltage violation. Most methods use global optimization to obtain the optimal use of network-wide available resources, which becomes unfair when solving the same voltage issue of regional buses. Refined coordination of DERs on regional buses has not been formed as well. Therefore, this paper proposes a voltage sensitivity-related hybrid coordination algorithm. In order to fully tap into surplus reactive power of DESs, Volt/VAr control is considered in a higher priority than Volt/Watt control. For the selected crucial bus, a hybrid coordinated power compensation of regional DERs is designed in descending order of sensitivity or in proportion to available capacity under the same sensitivity value, which prioritizes using local and adjacent DERs to improve regulation effect and reduce changes in power flow. Due to the fact that voltage information is updated through association, the crucial bus needs to be reselected based on voltage assessment as a result, and the algorithm process will continue until the updated bus voltages become acceptable. Finally, the case study results in MATLAB indicate the effectiveness.
Examining High-Risk Behaviors and Behavioral Disorders in Adolescents with Addicted and Non-Addicted Fathers in Public School of Zabol in the Academic Year 2016–2017

Adolescence is considered an important period for the prevalence of risky behaviors due to adolescents’ self-centeredness and wrong understanding of their own behaviors. This period is followed by widespread physical, psychological, and social changes. The present study aims to examine high-risk behaviors and behavioral disorders in adolescents with addicted and non-addicted fathers at public school of Zabol in the academic year 2016–2017. The present study is a descriptive research that falls within the category of scientific comparative research. Iranian Adolescents Risk-taking Scale, Rutter Behavioral Disorder Questionnaire, and a demographic questionnaire were used for data collection purposes. The statistical data were analyzed using SPSS Version18. A total of 310 students were placed in two 155-participant groups, namely the case and control groups. The mean value of participants’ age equaled 15.48 years. The highest and lowest rates of risky behaviors pertained to smoking and sexual relations. The results of independent t-test indicated no significant difference between the two groups in terms of drug abuse, violence, and risky driving (P<0.005). The findings of this study suggest the need for the development of prevention programs and treatment interventions in children with addicted fathers. Hence, it is suggested that prevention programs be developed and implemented in order to prevent the incidence of behavioral disorders and highrisk behaviors.
Turbulence in high-beta ASDEX upgrade advanced scenarios

Recent experiments at ASDEX Upgrade achieve non-inductive operation in full tungsten wall conditions by applying electron cyclotron and neutral beam current drive. These discharges are characterised by a well-measured safety factor profile, which does not drop below one, and a good energy confinement. By reproducing the experimental heat fluxes, nonlinear gyrokinetic simulations suggest that the observed strong peaking of the ion temperature in the core is caused by the stabilising impact of a significant beam ion content, as well as strong electromagnetic effects on turbulent transport. Quasilinear transport models are not yet applicable in this interesting and reactor relevant parameter regime, but available simulation data may serve as a testbed for improvements. As the present plasma is close to the kinetic ballooning (KBM) threshold, elevating the safety factor profile under otherwise identical conditions is proposed to clarify, whether profiles are ultimately limited by KBM turbulence, or by global stability constraints.
Insight into lipid-based nanoplatform-mediated drug and gene delivery in neuro-oncology and their clinical prospects

Tumors of the Central nervous System (CNS) are a spectrum of neoplasms that range from benign lesions to highly malignant and aggressive lesions. Despite aggressive multimodal treatment approaches, the morbidity and mortality are high with dismal survival outcomes in these malignant tumors. Moreover, the non-specificity of conventional treatments substantiates the rationale for precise therapeutic strategies that selectively target infiltrating tumor cells within the brain, and minimize systemic and collateral damage. With the recent advancement of nanoplatforms for biomaterials applications, lipid-based nanoparticulate systems present an attractive and breakthrough impact on CNS tumor management. Lipid nanoparticles centered immunotherapeutic agents treating malignant CNS tumors could convene the clear need for precise treatment strategies. Immunotherapeutic agents can selectively induce specific immune responses by active or innate immune responses at the local site within the brain. In this review, we discuss the therapeutic applications of lipid-based nanoplatforms for CNS tumors with an emphasis on revolutionary approaches in brain targeting, imaging, and drug and gene delivery with immunotherapy. Lipid-based nanoparticle platforms represent one of the most promising colloidal carriers for chemotherapeutic, and immunotherapeutic drugs. Their current application in oncology especially in brain tumors has brought about a paradigm shift in cancer treatment by improving the antitumor activity of several agents that could be used to selectively target brain tumors. Subsequently, the lab-to-clinic transformation and challenges towards translational feasibility of lipid-based nanoplatforms for drug and gene/immunotherapy delivery in the context of CNS tumor management is addressed.
An adaptive optimization method toward batch-wise variable set point of outlet moisture content for the tobacco drying process

Abstract The tobacco drying process in the cigarette production has an important effect on the final product quality. Therefore, the intelligent control methods have been widely investigated to ensure the stability of tobacco’s outlet moisture content. The existing work mostly uses a relatively fixed set point of the outlet moisture content for different tobacco batches, which can lead to unforeseen product quality after several processes following the drying process and inaccessible amount of dehydration for the rotary dryer. Some tobacco moisture prediction methods have been studied recently while the relationship with the intelligent control methods remain largely unexplored. To deal with these issues, a novel method is proposed in this paper to identify the optimal set point of the drying outlet moisture content for each tobacco batch. An encoder-decoder model is first developed to forecast the post-drying moisture trajectory. Then, an adaptive filter with specially designed mechanisms and a confidence interval of the dehydration level are constructed to obtain the design constraints. Based on all above, a constrained optimization problem is formulated and solved by the genetic algorithm. Extensive experiments on 895 tobacco batches from a large cigarette factory are carried out, which involves both algorithmic evaluation and field test. It turns out that the proposed method achieves the superior performance and leads to an improvement of the product quality in real production.
ASTRI SST-2M: the design evolution from the prototype to the array telescope

The Cherenkov Telescope Array (CTA) observatory will represent the new frontier of imaging atmospheric Cherenkov Telescope. The simultaneous use of large, medium and small telescopes (respectively LST, MST and SST) will allow to explore the astronomy related to the very high energy domain, typical of Gamma rays, with a sensitivity, angular resolution and image quality never seen before. Within this project, ASTRI, the Italian 2 mirrors Schwarzshild-Couder configuration Small SST led by Italian National Institute of Astronomy (INAF), has moved quickly developing a 4m class telescope prototype which has been tested with results which demonstrates excellent performance as well as wide margins for further improvements. On the basis of the experiences made on the prototype, this paper focus on the design enhancements carried out for the telescope which will be part of the Cherenkov Telescope Array.
Emotion detection on social media status in Myanmar language

Many social media emerged and provided services during these years. Most people, especially in Myanmar, use them to express their emotions or moods, learn subjects, sell products, read up-to-date news, and communicate with each other. Emotion detection on social users makes critical tasks in the opinion mining and sentiment analysis. This paper presents the emotion detection system on social media (Facebook) user status or post written in Myanmar (Burmese) language. Before the emotion detection process, the user posts are pre-processed under segmentation, stemming, part-of-speech (POS) tagging, and stop word removal. The system then uses our preconstructed Myanmar word-emotion Lexicon, M-Lexicon, to extract the emotion words from the segmented POS post. The system provides six types of emotion such as surprise, disgust, fear, anger, sadness, and happiness. The system applies naïve Bayes (NB) emotion classifier to examine the emotion in the case of more than two words with different emotion values are extracted. The classifiers also classify the emotion of the users on their posts. The experiment shows that the system can detect 85% accuracy in NB based emotion detection while 86% in recurrent neural network (RNN).
Overexpression of Sly-miR398b Compromises Disease Resistance against Botrytis cinerea through Regulating ROS Homeostasis and JA-Related Defense Genes in Tomato

MicroRNAs (miRNAs) have been shown to be critical components in plant immunity. MicroRNA398 (miR398) is a highly conserved miRNA in all land plants and plays crucial roles in diverse biotic stress responses. However, the role of miR398 has not yet been characterized in tomato resistance against Botrytis cinerea. In this report, the transcript levels of sly-miR398b were strongly decreased in B. cinerea-infected leaves and the overexpression of sly-miR398b resulted in enhanced susceptibility. The attenuated expression of cytosol Cu/Zn-SOD (CSD1), chloroplast Cu/Zn-SOD (CSD2), and guaiacol peroxidase (GPOD), as well as the decreased activities of superoxide dismutase (SOD) and GPOD, collectively led to increased hydrogen peroxide (H2O2) accumulation in sly-miR398b overexpressing plants. Furthermore, sly-miR398b was induced by methyl jasmonate (MeJA) treatment. The overexpression of sly-miR398b suppressed the expression of TomLoxD, LapA, and PR-STH2 in response to B. cinerea and MeJA treatment. Our data demonstrate that sly-miR398b overexpression negatively regulates the resistance to B. cinerea in tomato by inducing the accumulation of reactive oxygen species (ROS) and downregulating the expression of MeJA-responsive defense genes.
Effect van voersamenstelling op bijtgedrag bij varkens

Op Varkens Innovatie Centrum Sterksel is onderzocht of bijtgedrag (staart-, oor- en flankbijten) en staart- en oorschade bij dieren met intacte (niet gecoupeerde) staarten verminderd kunnen worden door de dieren vanaf enkele dagen na geboorte tot afleveren naar het slachthuis voer met extra vezels (verzadigend voer) en/of voer met extra aminozuren (tryptofaan, threonine en methionine) te geven. De resultaten van het onderzoek zijn beschreven in dit rapport.
QUANTUM NETWORKS WITH SINGLE ATOMS, PHOTONS AND PHONONS

Abstract : The NSSEFF research program has been directed to create new paradigms for the strong interaction oflight and matter. In general terms, the research has laid foundations for building complex quantum systemsfrom 'simple' components of single atoms and photons. Theoretical investigations have predicted surprisingquantum phenomena that have not heretofore existed in Nature. More specifically, the researchinvestigated new quantum phases of matter with photon-mediated atom-atom interactions in one and twodimensionalnano-photonic lattices (e.g., self-organization of free-space atoms into crystals bound by light). In a complimentary fashion, exotic quantum phases for photons become possible by way of strong photonphotoninteractions created by an underlying lattice of atoms (e.g., two propagating photons bonded tobecome a 'molecule').
Performance of a circular cylinder piezoelectric wind energy harvester fitted with a splitter plate

This study examines effects of the splitter plate placed in the near wake of a circular cylinder on the performance of a piezoelectric wind energy harvester through wind tunnel experiments. The kinetic energy of the harvester is gained by wind-induced vibrations of the circular cylinder. The splitter plate is attached to the leeward side of the cylinder. The ratio of the splitter plate length to the diameter of the circular cylinder (Lsp/D) ranges from 0.25 to 2.00. After attaching the splitter plate with an appropriate length, the harvester is able to sustain large amplitude vibrations beyond the wind speed range corresponding to vortex-induced vibrations. Thus, the upper bound of the wind speed range for the harvester to harness wind energy is eliminated, which significantly increases the efficiency of the harvester. Compared to the different lengths of the splitter plate, 0.65D has been found to be the optimal length for maximizing the harvested power.
Biology of the southern giant hornet, Vespa soror: nest architecture, morphological differences among castes, and the genetic structure of colonies

Giant hornets in the genus Vespa are apex predators that are known throughout Asia for their exceptional size and devastating group attacks on social insect colonies. The giant hornets include Vespa mandarinia, a well-studied and widespread temperate species, and Vespa soror, a poorly known sister species that is limited to subtropical and tropical regions of Southeast Asia. Both species have been recently documented on the west coast of North America, raising urgent questions about their potential impact in novel ecosystems. To better understand the biology of V. soror, we describe the nest architecture, caste morphology, and genetic structure of colonies collected in Vietnam. Comparisons of colony metrics between the two giant hornet species suggest important differences that are likely a consequence of the relatively warmer climate in which V. soror occurs. Like V. mandarinia, V. soror constructs large, underground nests of partially enveloped horizontal combs. However, compared to temperate V. mandarinia colonies, the longer nesting period of subtropical V. soror colonies likely resulted in relatively larger colony sizes and nests by the end of their annual cycle. Vespa soror workers and gynes were larger than males, distinguishable based on wing shape and body size (total length and measures of six body parts), and equivalent in size to female castes of V. mandarinia. We genotyped colony members from three mature nests, which revealed that males and females were offspring of singly mated queens. Two colonies were monogynous, but one colony was comprised of two unrelated matrilines. Polygyny has not been observed for V. mandarinia, but is more common in tropical hornet species. Our study sheds light on essential details about the biology of an understudied species of giant hornet, whose populous colonies and long nesting period suggest the potential for substantial ecological impact wherever they occur.
Applying Deep Learning Model to Predict Diagnosis Code of Medical Records

The International Classification of Diseases (ICD) code is a diagnostic classification standard that is frequently used as a referencing system in healthcare and insurance. However, it takes time and effort to find and use the right diagnosis code based on a patient’s medical records. In response, deep learning (DL) methods have been developed to assist physicians in the ICD coding process. Our findings propose a deep learning model that utilized clinical notes from medical records to predict ICD-10 codes. Our research used text-based medical data from the outpatient department (OPD) of a university hospital from January to December 2016. The dataset used clinical notes from five departments, and a total of 21,953 medical records were collected. Clinical notes consisted of a subjective component, objective component, assessment, plan (SOAP) notes, diagnosis code, and a drug list. The dataset was divided into two groups: 90% for training and 10% for test cases. We applied natural language processing (NLP) technique (word embedding, Word2Vector) to process the data. A deep learning-based convolutional neural network (CNN) model was created based on the information presented above. Three metrics (precision, recall, and F-score) were used to calculate the achievement of the deep learning CNN model. Clinically acceptable results were achieved through the deep learning model for five departments (precision: 0.53–0.96; recall: 0.85–0.99; and F-score: 0.65–0.98). With a precision of 0.95, a recall of 0.99, and an F-score of 0.98, the deep learning model performed the best in the department of cardiology. Our proposed CNN model significantly improved the prediction performance for an automated ICD-10 code prediction system based on prior clinical information. This CNN model could reduce the laborious task of manual coding and could assist physicians in making a better diagnosis.
Quantized H∞ filtering for discrete-time systems over fading channels

This paper addresses the problem of quantized H ∞ filtering for multi-output discrete-time systems over independent identically distributed (i.i.d.) fading channels and Markov fading channels, respectively. The measurement outputs are quantized by a logarithmic quantizer, and then transmitted to the filter over fading channels. For the i.i. d. fading channels, the stochastic multiplicative noise form is used to model the unreliable communication environment. For the Markov fading channels, a set of Markov channel state processes is introduced to model time-varying fading channels, which characterizes various configurations of the physical communication environment and/or different channel fading amplitudes. The sufficient condition for stochastic stability with a prescribed H ∞ performance is obtained by using a Lyapunov method and matrix decoupling technique. The corresponding filter design casts into a convex optimization problem. Finally, simulation results are provided to illustrate the effectiveness of our results.
Lamin A/C Ablation Restricted to Vascular Smooth Muscle Cells, Cardiomyocytes, and Cardiac Fibroblasts Causes Cardiac and Vascular Dysfunction

Mutations in the LMNA gene (encoding lamin A/C proteins) cause several human cardiac diseases, including dilated cardiomyopathies (LMNA-DCM). The main clinical risks in LMNA-DCM patients are sudden cardiac death and progressive left ventricular ejection fraction deterioration, and therefore most human and animal studies have sought to define the mechanisms through which LMNA mutations provoke cardiac alterations, with a particular focus on cardiomyocytes. To investigate if LMNA mutations also cause vascular alterations that might contribute to the etiopathogenesis of LMNA-DCM, we generated and characterized Lmnaflox/floxSM22αCre mice, which constitutively lack lamin A/C in vascular smooth muscle cells (VSMCs), cardiac fibroblasts, and cardiomyocytes. Like mice with whole body or cardiomyocyte-specific lamin A/C ablation, Lmnaflox/floxSM22αCre mice recapitulated the main hallmarks of human LMNA-DCM, including ventricular systolic dysfunction, cardiac conduction defects, cardiac fibrosis, and premature death. These alterations were associated with elevated expression of total and phosphorylated (active) Smad3 and cleaved (active) caspase 3 in the heart. Lmnaflox/floxSM22αCre mice also exhibited perivascular fibrosis in the coronary arteries and a switch of aortic VSMCs from the ‘contractile’ to the ‘synthetic’ phenotype. Ex vivo wire myography in isolated aortic rings revealed impaired maximum contraction capacity and an altered response to vasoconstrictor and vasodilator agents in Lmnaflox/floxSM22αCre mice. To our knowledge, our results provide the first evidence of phenotypic alterations in VSMCs that might contribute significantly to the pathophysiology of some forms of LMNA-DCM. Future work addressing the mechanisms underlying vascular defects in LMNA-DCM may open new therapeutic avenues for these diseases.