Miracle-dz/UniFAR-FTUs huggingface dataset:
Observation of s-Channel Single Top Quark Production at the Tevatron

Testing the Standard Model (SM) and looking for new phenomena have been the focus of generations of particle physicists in the last decades. Following this spirit, this thesis presents two searches. The first is the search for single top quark production from the exchange of an s-channel virtual W boson using events with an imbalance in the total transverse energy, b-tagged jets, and no identified leptons. Assuming the electroweak production of top quarks of mass 172.5 GeV/c2 in the s-channel, a cross section of 1.12+0.61 -0.57 (stat+syst) pb, with a significance of 1.9 standard deviations, is measured. This measurement is combined with the result obtained from events with an imbalance in total transverse momentum, b-tagged jets, and exactly one identified lepton, yielding a cross section of 1.36+0.37 -0.322 (stat+syst) pb, with a significance of 4.2 standard deviations. The first observation of single-top-quark production in the s channel through the combination of the CDF and D0 measurements is also reported. The measured cross section is σs = 1.29+0.26 -0.244 pb. The probability of observing a statistical fluctuation of the background to a cross section of the observed size or larger is 1.8 10-10, corresponding to a significance of 6.3 standard deviation.more » The second is the search for W'-like resonances decaying to tb. No significant excess above the SM prediction is found. Using a benchmark W' → tb left-right symmetric model, 95% C.L. mass-dependent upper limits are placed on the W0 boson production cross section times branching ratio to tb. Assuming a W' boson with SM-like couplings and allowed (forbidden) decay to leptons, W' → tb is excluded with 95% C.L. for W' boson masses below 860 (880) GeV/c2. Relaxing the hypothesis on SM-like couplings, we exclude W' boson coupling strength values as a function of the W' boson mass above 10% of the SM coupling strength for MW' = 300 GeV/c2. The constraints obtained with the present analysis are the most stringent for charged resonance masses below 570 GeV/c2 decaying to a top and a bottom quark. « less
Information Frictions and Take-up of Government Credit Programs

Most governments in developing countries offer subsidized credit programs to the agricultural sector. We document that farmers often lack information on how these programs work, their eligibility criteria and loan terms offered. We study the impact of information frictions on credit take-up by exploiting plausibly exogenous variation in the construction of new mobile phone towers in rural areas of India without previous mobile phone coverage. Areas receiving coverage experience higher take-up of agricultural credit. The effects are concentrated in short-term credit to small farms, which have been the target of a major government subsidized credit program, the Kisan credit cards.
Refine control methodology and implementation of capacitor voltage control for improved switched inductor Z‐source inverter

Nowadays, Z‐source inverter (ZSI) has received several attentions compared to other power converters owing to their simplicity and reliability. In this paper, a refine control methodology of capacitor voltage control is presented based on third‐order small signal analysis. The proposed control is applied to the improved switched inductor ZSI (ISL‐ZSI). Proportional, integral, and derivative controller (PID) is adopted due to their capability to operate with large operation levels, reliable operation, and cheaper implementation. In addition, the function of this control can be achieved even with incomplete system data or parameters variations. ISL‐ZSI has been presented because of its advantages such as the high gain of direct current voltage, low voltage stress for both the Z‐network and the inverter bridge switches, and ensuring good soft starting. In addition, the inrush current has been removed based on its configuration. The proposed control is validated by both experimental and simulation results under input voltage change, load change, and steady‐state operations using DSP F28335 and MATLAB SIMULINK Real‐Time Workspace.
Real-Time Global Localization of a Mobile Robot by Exploiting RFID Technology

This work addresses the problem of the global localization of a mobile robot by exploiting RFID technology. The robot is equipped with kinematic sensors capable of measuring the incremental distances covered by each wheel and an RFID reader which measures the phase of the signal that is backscattered by reference RFID tags situated inside the environment at known positions. The motion of the robot with respect to the tags enables the collection of measurements from multiple antenna-locations, in a synthetic-aperture sense. Localization of the mobile robot over time is accomplished by processing short segments of trajectory during each iteration. The odometry-data are exploited to estimate each segment of the vehicle’s trajectory relative to an unknown initial position. The odometry-based estimation, the known positions of the reference tags, the unwrapped phase measurements and a phase-to-distance model represent the input to a data-fit problem, the solution of which reveals the unknown initial position and orientation of the trajectory segment in the absolute frame. Thanks to phase unwrapping, the data-fit problem features convexity-type properties and the solution is rapidly found by non-linear optimization techniques. The influence of different algorithmic features on the performance of the method is investigated in a simulative context. An experimental campaign that employs a prototype robotic agent equipped with two antennas reports a mean absolute localization error of less than 0.1m, while the execution time stays below the measurements’ collection-time such that the real-time capability of the method is preserved.
Correlation between Post-Thaw Spermatozoa Quality of the Endangered Javan Banteng with OPN Gene Expression

The role of ex situ conservation facilities or captivity through captive breeding programs is essential in the conservation of the endangered Javan banteng. The development of semen cryopreservation may assist on one side of the conservation plan. However, the male Javan banteng reproductive capability must be considered as it influences the targeted outputs. Studying the potential biomarker for fertility such as osteopontin gene expression is also expected to help predict male fertility. Therefore, this study aimed to analyze the quality of spermatozoa after thawing to help predict the male reproductive capability of Javan banteng. Furthermore, this study investigated the potential role of osteopontin gene expression in male Javan banteng fertility. A positive reinforcement approach was used to accustom the male and female animals as we focused on establishing a collection procedure using neither sedation nor anaesthesia. Semen samples were collected at Taman Safari Indonesia, Bogor, in accordance with the female banteng receptivity. Semen samples were then evaluated and then cryopreserved under field conditions. Our study showed the different predicted reproductive capability of the Javan banteng based on the post-thaw spermatozoa quality, which showed significant differences. The OPN gene showed positive correlations with the progressive motility (r = 0.711, p = 0.048), viability (r = 0.822, p = 0.012), and acrosomal integrity (r = 0.665, p = 0.072) of Javan banteng spermatozoa after thawing. Our study demonstrated the predicted Javan banteng reproductive capability based on various post-thaw spermatozoa variables. This finding is also the first report on the OPN gene potential to be developed as the assessment tool of post-thaw spermatozoa quality of the male Javan banteng. The findings in our study may help give recommendations for future breeding programs, especially in the ex situ conservation sites.
Formulation and Characteristics of Edible Oil Nanoemulsions Modified with Polymeric Surfactant for Encapsulating Curcumin

Curcumin (Cur) is a beneficial phytochemical with numerous health advantages. However, its limited solubility in oil and poor stability hinder its potential for biomedical applications. In this study, we employed a mixture of food-grade Tween 60, a polymeric surfactant, and Span 60 to adjust the hydrophilic lipophilic balance number (HLBt) and prepared nanoemulsions (NEs) of coconut oil (Cc oil) as carriers for Cur. The effects of HLBt values, surfactant-to-oil ratio, and oil ratio on the physicochemical characteristics of the food-grade oil-NEs were investigated using dynamic light scattering, transmission electron microscopy, differential scanning calorimetry, fluorescence polarization spectroscopy, and viscometry. Increasing the addition ratio of Tween 60 in the NEs, thereby increasing the HLBt, resulted in a reduction in NE size and an improvement in their storage stability. The temperature and size of the phase transition region of the NEs decreased with increasing HLBt. NEs with higher HLBt exhibited a disordering effect on the intra-NE molecular packing of Cc oil. NEs with high HLBt displayed low viscosity and demonstrated nearly Newtonian fluid behavior, while those with lower HLBt exhibited pseudoplastic fluid behavior. Cur was effectively encapsulated into the Cc oil-NEs, with higher encapsulation efficiency observed in NEs with higher HLBt values. Furthermore, the Cur remaining activity was significantly enhanced through encapsulation within stable NEs. The biocompatibility of the Cc oil-NEs was also demonstrated in vitro. In summary, this study highlights the preparation of stable NEs of Cc oil by adjusting the HLBt using Tween 60, facilitating effective encapsulation of Cur. These findings provide valuable insights for the development of Cur carriers with improved solubility, stability, and bioavailability.
Numerical Solutions of a Quadratic Integral Equations by Using Variational Iteration and Homotopy Perturbation Methods

In this paper, the approximate solutions for quadratic integral equations (QIEs) are given by the variational iteration method(VIM) and homotopy perturbation method (HPM). These methods produce the solutions in terms of convergent series without needing to restrictive assumptions, to illustrate the ability and credibility of the methods, we deal with some examples that show simplicity and effectiveness.
3D4DT: AN APPROACH TO EXPLORE DECISION TREES FOR THEMATIC MAP CREATION AS AN INTERACTIVE 3D SCENE

Abstract. Several tools have been proposed to automatically create thematic maps. A common drawback of these tools is that they rarely provide means for users to explore their decision trees. Users may thus create maps or get some maps proposed, but not know why some suggestions of maps were made. To address this gap, this work introduces 3D4DT, an approach to explore decision trees as a three-dimensional interactive scene. The 3D4DT approach uses JSON as a machine-readable format to represent decision trees and maps JSON elements to user interface elements (e.g. radio buttons and cubes). A preliminary evaluation of 3D4DT has shown effectiveness gains in comparison to information displayed as text+picture, for a decision tree with a simple hierarchical structure. The contributions of this work are relevant to the design of more transparent software for automated thematic map creation.
Interactive global illumination of non-deformable massive models = 정적 대용량 모델의 대화형 전역 조명

Due to advances of modeling techniques, massive models are easily generated these days. Such massive models can consist of hundreds of millions of primitives and thus use more than tens of gigabytes. This high memory requirement is likely to cause serious performance issues on visualization and rendering because of the heavy loads of data accesses. Moreover, it is not trivial to make the data access pattern of global illumination be coherent which aggravates the performance degradation. In this thesis, three directions to address the issues are proposed. To reduce the expensive data transmission from external drives, we propose two kinds of compressed representations of massive models as in-core and out-of-core representations. The proposed representations show significant performance benefits of various application requiring random access. We further accelerate the performance by fully utilizing heterogeneous computing resources, CPU and GPU. We propose a novel framework which drastically reduces data transmission overhead between the heterogeneous resources. By using the framework, an interactive performance of rendering massive models with global illumination effects is achieved. Finally, we propose an optimization method which maximizes both rendering throughput and responsiveness. The rendering framework with the optimization robustly works with running machines of different performances. A user study is performed to show the benefit of the optimization.
Synthesis of Solar Light Active Reduced Graphene Oxide-ZnS Nanomaterial for Photocatalytic Degradation and Antibacterial Applications

Good water quality is essential for life; therefore, decolorizing and detoxifying organic dye wastes (textile effluents) have gained immense environmental importance in recent years. Thus, the degradation of wastewater has become a potential need for our environment. This research aims to synthesize and investigate a ceramic-based nanomaterial catalyst for the degradation of dye solution under exposure to sunlight. A reduced graphene oxide-ZnS (rGO-ZnS) nanomaterial was qualitatively synthesized using a solvothermal method. The prepared nanomaterial was characterized using XRD, SEM, HR-TEM, EDX, XPS, and FT-IR techniques. The photocatalytic activity of the rGO-ZnS nanomaterial was checked using oxidative photocatalytic degradation of naphthol blue black dye (NBB) under direct sunlight irradiation. Here, the rGO/ZnS composite showed a significant photocatalytic performance to degraded NBB (93.7%) under direct solar light. Chemical Oxygen Demand (COD) measurements confirmed the mineralization of the dye. The influence of different radical scavengers on NBB degradation was studied. Optimum conditions for efficient degradation were determined. The antibacterial property of the prepared catalyst was studied.
Towards Optimal Application Offloading in Heterogeneous Edge-Cloud Computing

Application offloading plays a crucial role in application deployment in edge-cloud computing. However, finding the optimal solution for application offloading is challenging due to the heterogeneous resources, computing dependency of tasks, and complex network. Existing research on application offloading problems often assumes that the communication delay between the edge and the cloud (inter-side) is symmetrical or that within the cloud or edge (intra-side) can be omitted. However, this assumption is not practical considering the distinct features of the clouds and the edge clusters. Therefore, we study application offloading in the heterogeneous edge-cloud environment by considering both intra-side communication delay between tasks assigned to the same side and asymmetry inter-side communication delay between edge and cloud sides. We first focus on the specific circumstances with a boundary condition that lead to an optimal offloading solution in a heterogeneous edge-cloud environment. Then we study the general case by designing an iterative algorithm with maximum gain technique to solve it. Furthermore, considering various bandwidths within each side and resource capacities of physical nodes, we develop two efficient algorithms by combining minimum cut and maximum gain approaches. Both simulations and real trace-based evaluations are conducted to validate that the proposed algorithms outperform existing solutions.
Categories for the working modal logician

We attempt to build a ladder connecting the heavens of Category Theory to the interests of modal logicians, in particular those concerned with modelling tasks and therefore involved with specific models and languages. The body of work presented in this theses witnesses two possible modes of interaction. The first is the study of hybrid models, namely structures that are on one hand significant from a category-theoretic perspective and on the other hand lend themselves to a treatment with modal languages. We show how presheaf models can be seen as particular relational structures and develop a hierarchy of modal languages to express their properties. To argue in favor of the flexibility of this framework we review several applications; we especially dive into the details of a modal logic for social choice functions. Furthermore, we highlight how in this setting some of the traditional issues of Modal Logic, e.g. completeness, expressivity and decidability, receive an original twist and can be resolved with alternative solutions. A second mode, more heuristic in nature, consists of regarding a given class of models as a category. The benefit of this stance is the cluster of questions that come with it. The right notion of morphism for these models, its closure under composition, the functoriality of some uniform constructions, these are some of the basic issues that get raised in this context. In the second half of the thesis we explicate how they can shape research in Modal Logic and how they are intertwined with existing problems.
Toward Human-in-the-Loop Shared Control for Upper-Limb Prostheses: A Systematic Analysis of State-of-the-Art Technologies

Dexterous prosthetic hand is an essential rehabilitation assistant device to improve the life quality of amputee patients. Despite the continuous emergence of commercial prostheses and laboratory prototypes, the rejection rate remains high caused by the poor neural interaction performance and excessive cognitive burden, especially for the usage of upper-arm prostheses controlled by above-the-elbow amputation stump. The progress in artificial perception, bidirectional neural interface and share control indicates a great potential to improve the manipulation efficiency of upper-limb prostheses. In this review, a comprehensive analysis of human-in-the-loop shared control studies is presented to provide researchers with a systematic technical route in upper-limb prostheses control. The latest avenues of research concerning myoelectric control, sensory feedback, perception, autonomous motion planning of multiple degree of freedom elbow-wrist, and share control are overviewed and discussed. The comprehensive assessments show that there remains inadequate technologies to achieve an anthropomorphic and efficient unified elbow-wrist-hand prostheses manipulation. By delineating the current shortcomings, the outcomes of this work highlight future investigation in the field of intuitive motion control, feedback of proprioception/touch and the natural interaction between human intent and machine autonomy.
PUTS: Privacy-Preserving and Utility-Enhancing Framework for Trajectory Synthesization

Vehicle trajectory data is essential for traffic management and location-based services. However, publishing real-life trajectory data has been challenging because vehicle trajectories contain users’ sensitive information. Differential privacy addresses such problems by publishing a synthetic version of the input dataset, but existing works always assume the real-world data is absolutely accurate. This assumption no longer holds in trajectory data because it typically contains errors due to inaccurate positioning services, which leads to poor performance of data synthesized by such trajectories. Even worse, existing works may generate unrealistic trajectories due to their coarse data synthesis methods, resulting in low practical utility or even inability to handle complex tasks. In this paper, we propose a <underline>P</underline>rivacy-preserving and <underline>U</underline>tility-enhancing framework for <underline>T</underline>rajectory <underline>S</underline>ynthesization (<italic>PUTS</italic>). Our framework mitigates the impact of data errors in trajectories on differential privacy mechanisms, by exploiting map-matching techniques and real-world road network structure. In <italic>PUTS</italic>, a two-layer approach from path to trajectory synthesis is proposed to not only guarantee the reality of synthetic trajectories, but also scale up <italic>PUTS</italic> in real-world applications. Extensive experiments on real-world datasets show that <italic>PUTS</italic> significantly outperforms existing methods in terms of utility in a range of real-world applications.
On the Separability of Local SNR Values Represented by Amplitude Modulation Spectrogram Vectors

Evaluating local SNR values in noisy speech is very valuable for many applications. Research in this paper investigates the separability of local SNR values which are represented by amplitude modulation spectrogram (AMS) feature vectors. Deep belief networks (DBN) were employed in previous studies for binary and quarterly classifications of these SNR feature vectors, however with unsatisfactory results. It is difficult to identify which factor, AMS feature vector or DBN configuration should be responsible for the result. Therefore the technique of t-distributed stochastic neighbor embedding (t-SNE) is called in this study to visualize the separability of AMS feature vectors. According to experimental observations with binary and quarterly classifications, AMS feature vector is a good representation of SNR values with fine grain separability. To improve the classification performance of SNR values represented by AMS feature vectors, more attention should be put on DBN‟s training and configuration.
A generalized network evolution model and self-organization theory on community assembly

Community assembly is the process that species grow and interact to establish a community. In present study, a generalized, rule-based network evolution model, CommAssembly, for community assembly was proposed. The model is based on difference equations with different number of species in different stages of evolution. It consists of pioneer rule, invasion and growth rule, extinction rule, connection (flow) rule and termination rule, etc. Species invades, grows in, or quits the community following specific rules. In addition, I proposed the self-organization theory on community assembly. In this theory, I think that community assembly is a self-organization process. In terms of the model proposed, the practical community can spontaneously adjust its A(t), and guarantee itself to evolve in a natural way. Temporal dynamics and species composition of community depend on species composition of species pool, between-species interactions, intrinsic growth of species, environmental capacity (resource availability), and the probability, strength and history of invasions, etc. The invasion, establishment, growth, and extinction of species follow a series of rules. Community assembly can be best described and modeled with self-organization approaches. The model provides the basis to build self-organization models of community assembly.