Miracle-dz/UniFAR-FTUs huggingface dataset:
Timing Estimation and Limits in TOF-PET Detectors Producing Prompt Photons

The production of prompt photons providing high photon time densities is a promising avenue to reach ultrahigh coincidence time resolution (CTR) in time-of-flight positron emission tomography. Detectors producing prompt photons are receiving high interest experimentally, ignited by past exploratory theoretical studies that have anchored some guiding principles. Here, we aim to consolidate and extend the foundations for the analytical modeling of prompt generating detectors. We extend the current models to a larger range of prompt emission kinetics where more stringent requirements on the prompt photon yield rapidly emerge as a limiting factor. Lower bound and estimator evaluations are investigated with different underlying models, notably by merging or keeping separate the prompt and scintillation photon populations. We further show the potential benefits of knowing the proportion of prompt photons within a detection set to improve the CTR by mitigating the detrimental effect of population (prompt versus scintillation) mixing. Taking into account the fluctuations on the average number of detected prompt photons in the model reveals a limited influence when prompt photons are accompanied by fast scintillation (e.g., LSO:Ce:Ca) but a more significant effect when accompanied by slower scintillation (e.g., bismuth germanate). Establishing performance characteristics and limitations of prompt generating detectors is paramount to gauging and targeting the best possible timing capabilities they can offer.
Distributed Dynamic Event-Triggered Cooperative Control of Multiple TCLs and HESS for Improving Frequency Regulation

The volatility and randomness of the source-load sides increase the difficulty for system frequency regulation, while flexible loads like thermostatically controlled loads (TCLs) and hydrogen energy storage system (HESS) can be used to provide frequency auxiliary services. In this article, a hierarchical frequency control framework is established, with TCLs and HESS interacting in a distributed cooperative way to track unmatched power. Then, power allocation principles are proposed, which realizes the rational utilization of various resources and ensures the close tracking of the upper-level power targets. Further, a leader–follower distributed dynamic event-triggered control strategy is designed to guarantee fast convergence speed and synchronization accuracy, where power transmission on demand is realized to save limited network resources. Moreover, sufficient conditions are derived to ensure the stability of the distributed TCLs and HESS system by combining the Lyapunov theory. Finally, case studies assess that the proposed strategy guarantees the effectiveness and rapidity of the frequency control, meanwhile reducing the communication burden.
Speech-Visual Emotion Recognition by Fusing Shared and Specific Features

With the development of artificial intelligence, it has become a mainstream approach for speech-visual emotion recognition by utilizing neural networks to directly fuse the features of each modality. However, this approach is hard to obtain the shared and specific features of speech-visual modalities, which seriously affects the performance of emotion recognition. To this end, this paper proposes an emotion recognition method by fusing the shared and specific features of speech-visual modalities. In particular, the three-dimensional convolutional neural networks (3D-CNNs) and siamese networks are applied as the feature extraction backbone networks of speech-visual modalities, and the loss function is specially designed to ensure that the proposed method effectively obtains the shared and specific features of speech-visual modalities. Experimental results on the RML, BAUM-1s, eNTERFACE05 datasets show that the proposed method achieves a better result.
Tests of Stochastic Dominance for Time Series Data: Theory and Empirical Application

The present thesis investigates the problem of testing for stochastic dominance which is a basic concept of decision theory. We focus on stochastic dominance of first and of second degree which are the most important stochastic dominance decision rules. These decision rules are applied in various branches of economics, e.g. finance and social welfare theory. Statistical tests for stochastic dominance are based on the difference of the empirical distribution or quantile functions. For the determination of the critical region we need the distribution of the test statistic under the null hypothesis. In many tests contemporaneous and serial independence are assumed. However, in many applications the observations do not satisfy these constraints. In particular, financial data usually feature positive correlation between the observations of different samples at the same time and conditional heteroskedasticity within each sample. We confine ourselves to bivariate GARCH (1,1) which has good fit and forecast properties for financial data. In order to get an idea about the impact of conditional heteroskedasticity on statistical tests we analyze its effect on common statistical procedures for means and variances. It turns out that the effect on procedures for variances is tremendous. The main issue of this thesis is the development of tests for stochastic dominance which are robust to these time series properties. Two kinds of tests are considered: on the one hand tests in which dominance is the hypothesis, on the other hand tests with the alternative of dominance. Most of the tests known from literature are not robust to conditional heteroskedasticity. We develop two tests for the first test problem and one test for the second test problem which can be used under the assumption that the underlying processes are strongly mixing. Theoretical analysis and simulations show that the tests using circular subsampling, block permutation and truncation, respectively, have good size and power properties even if conditional heteroskedasticity is prevalent in the data. The developed tests are applied to the daily returns of the stocks of the German stock index DAX.
Detecting urban vegetation categories based on object-oriented method from IKONOS data

Based on urban vegetation characteristics of spectrum,texture,geometry and location,the object-oriented method was used to identify urban vegetation categories from IKONOS imagery.Firstly,vegetated area and non-vegetated area were separated by the threshold of NDVI and digital number(DN)value of blue band,and further,region growing method was adopted to segment the vegetated area into "objects",which represent the aggregation of pixels adjacent in location and in DN value.Secondly,9 features of form index,bright,maximum spectral difference of green band,mean spectral value of red band,ratio of near-infrared band,the standard deviation of near-infrared band,x,y and Homogeneity,were selected to construct feature space.Thirdly,objects were classified into five vegetation categories using maximum likelihood methods and expert knowledge,within the feature space.The overall accuracy of 87.37% and the Kappa coefficient of 0.8267 of the classification results showed the object-oriented method is useful to classify urban vegetation.
A Methodology of Sensor Fault-Tolerant Control on a Hierarchical Control for Hybrid Microgrids

This study develops a new Sensor Fault-Tolerant methodology for two-level Centralized Hierarchical Control of isolated microgrids based on a modified Kalman filter algorithm. The main objective is to increase the reliability and safety margins of isolated smart microgrids in the presence of different sensor faults on the secondary control. Consequently, Sensor Fault-Tolerant control reduces the costs because costly redundant hardware is not required. Because of its low computing effort, speed, ease of implementation, and tuning, this method can be used in more complex control configurations, multiple sensor faults, and different hierarchical control levels. The designed Sensor Fault-Tolerant Hierarchical Control System was initially proposed for a grid-forming topology of single-phase BESSs systems connected in cascade to the microgrid. The implemented fault tolerance methodology can maintain control objectives with sensor faults. Consequently, the MG’s voltage at the time of the fault does not exceed 5%, and the voltage unbalance at the common coupling point or on the critical bus is compensated to a quality reference value of less than 2%. The performance of the proposed algorithm is tested using the MATLAB/Simulink simulation platform.
General spatial correlation model in von Mises angle of arrival distribution environment

Abstract Analytical expressions are derived for the envelope correlation of the signals measured with two closely spaced antennas in an urban multipath environment. The angles-of-arrival (АоА) of the multipath waves are assumed to be von Mises distributed. It are closed-form expressions and therefore easier to implement in for instance MIMO-capacity calculations than previously published formulas that include infinite summations. Moreover, the new expressions are not restricted to an array of isotropic radiators but also hold for an array of dipole antennas.
Some Physical and Chemical Properties of the Arctic Winter Aerosol in Northeastern Canada

Abstract Measurements spanning much of the particle size spectrum were made on the surface aerosol arriving at Igloolik, Northwest Territories, Canada during late February 1982. Vertical profiles of aerosol particle concentration were obtained during one day of the study period. Concentrations of Aitken nuclei and cloud condensation nuclei as well as the aerosol light-scattering coefficient were measured instrumentally several times a day. Inertial impaction systems were used to separate and collect particles for microscopic sizing and chemical analysis. Suspended and precipitating ice crystals were inertially collected on microscope slides. The aerosol observations were accompanied by observations of temperature, wind speed and direction, visibility and cloud type. An upper-air station at Hall Beach, <100 km from Igloolik, provided radiosonde data. Diurnal variations in the Aitken nucleus concentrations were observed on several clear days. The concentrations were frequently seen to follow the diurnal tem.
A maximum projection and particle filtering algorithm for space debris detection

An algorithm was proposed to detect the space debris in the optical astronomical images. maximum projection was induced to reduce the data amount in the three dimensional space. when the space debris was detected, it was tracked by the particle filter thus the precise location information can be got at any time. the simulation results show that the method can perfectly meet the requirement of the space debris detection with a high accuracy (rms error less than 1 pixel) and detection probability, and a low false alarm rejection.
A regularized k-means and multiphase scale segmentation

We propose a data clustering model reduced from variational approach. This new clustering model, a regularized k-means, is an extension from the classical k-means model. It uses the sum-of-squares error for assessing fidelity, and the number of data in each cluster is used as a regularizer. The model automatically gives a reasonable number of clusters by a choice of a parameter. We explore various properties of this classification model and present different numerical results. This model is motivated by an application to scale segmentation. A typical Mumford-Shah-based image segmentation is driven by the intensity of objects in a given image, and we consider image segmentation using additional scale information in this paper. Using the scale of objects, one can further classify objects in a given image from using only the intensity value. The scale of an object is not a local value, therefore the procedure for scale segmentation needs to be separated into two steps: multiphase segmentation and scale clustering. The first step requires a reliable multiphase segmentation where we applied unsupervised model, and apply a regularized k-means for a fast automatic data clustering for the second step. Various numerical results are presented to validate the model.
Multiple Intramolecular Hydrogen Bonding in Large Biomolecules: DFT Calculations and Deuterium Isotope Effects on 13C Chemical Shifts as a Tool in Structural Studies

Large biomolecules often have multiple intramolecular hydrogen bonds. In the cases where these interact, it requires special tools to disentangle the patterns. Such a tool could be deuterium isotope effects on chemical shifts. The use of theoretical calculations is an indispensable tool in such studies. The present paper illustrates how DFT calculations of chemical shifts and deuterium isotope effects on chemical shifts in combination with measurements of these effects can establish the complex intramolecular hydrogen bond patterns of rifampicin as an example) The structures were calculated using DFT theoretical calculations, performed with the Gaussian 16 software. The geometries were optimized using the B3LYP functional and the Pople basis set 6-31G(d) and the solvent (DMSO) was taken into account in the PCM approach. Besides the 6-31G(d) basis set, the 6-31 G(d,p) and the 6-3111G(d,p) basis sets were also tested. The nuclear shieldings were calculated using the GIAO approach. Deuteriation was simulated by shortening the X-H bond lengths by 0.01 Å.
Linear Programming Model For Optimal Cropping Pattern For Economic Benefits Of Mrbc Command Area

Optimal cropping pattern optimization model is formulated in which the surface and ground water as decision variables. Linear programming is used for multiple crop models and dynamic programming for single crop model. In irrigated agriculture, where various crops are competing for a limited quantity of land and water resources, linear programming is one of the best tools for optimal allocation of land and water resources (smith, 1973; mAji and heady, 1980; loucks et al., 1981. Salman et al (2001) present a linear programming model to derive regional water demands based on optimized regional cropping pattern with variable water prices based on quality.
Bridging Gaps in Peripheral Nerves: From Current Strategies to Future Perspectives in Conduit Design

In peripheral nerve injuries (PNI) with substance loss, where tensionless end-to-end suture is not achievable, the positioning of a graft is required. Available options include autografts (e.g., sural nerve, medial and lateral antebrachial cutaneous nerves, superficial branch of the radial nerve), allografts (Avance®; human origin), and hollow nerve conduits. There are eleven commercial hollow conduits approved for clinical, and they consist of devices made of a non-biodegradable synthetic polymer (polyvinyl alcohol), biodegradable synthetic polymers (poly(DL-lactide-ε-caprolactone); polyglycolic acid), and biodegradable natural polymers (collagen type I with/without glycosaminoglycan; chitosan; porcine small intestinal submucosa); different resorption times are available for resorbable guides, ranging from three months to four years. Unfortunately, anatomical/functional nerve regeneration requirements are not satisfied by any of the possible alternatives; to date, focusing on wall and/or inner lumen organization/functionalization seems to be the most promising strategy for next-generation device fabrication. Porous or grooved walls as well as multichannel lumens and luminal fillers are the most intriguing options, eventually also including the addition of cells (Schwann cells, bone marrow-derived, and adipose tissue derived stem cells) to support nerve regeneration. This review aims to describe common alternatives for severe PNI recovery with a highlight of future conduits.
The European freshwater landscape and hotspot areas of mass effects and regional connectivity

The maintenance of broad‐scale connectivity patterns is suggested as a sustainable strategy for biodiversity preservation. However, explicit approaches for quantifying the functional role of different areas in biogeographic connectivity have been elusive. Freshwaters are spatially structured ecosystems critically endangered because of human activities and global change, demanding connectivity‐based approaches for their conservation. Mass effects—the increase in local diversity by immigration—and corridor effects—the connections with distant communities—are basic and relevant mechanisms connecting diversity with landscape configuration. Here, we identified freshwater hotspots areas for mass and corridor effects across Europe.
Spatio-Temporal Characterization of Stochastic Dynamic Transportation Networks

This paper addresses the problem of modeling stochastic dynamic transportation networks, where travel times are random variables with time-varying distributions and spatio-temporal dependencies. It presents a taxonomy of modeling approaches used in the literature and defines extended taxonomic categories to better capture the characteristics of transportation networks. A two-part approach is presented to characterize transportation networks spatially and temporally based on the network structure and observed travel time data. The first part implements a community detection approach from network science modified for the application to transportation networks. The community detection approach is further adapted to use dynamic time warping distance to measure the dissimilarity between time series of link travel times. The second part implements a change point detection approach that identifies points in time when there are changes in the underlying link travel time distributions generating the observed time series. The proposed approach is tested via sensitivity analysis using the large-scale Chicago network and its corresponding travel time data. Sensitivity analysis with varying model parameters demonstrates the robustness of the network characterization and helps determine the most suitable parameter values. The sensitivity analysis with respect to varying weather conditions and demand patterns in the network demonstrates that the spatial and temporal characteristics are robust with respect to changing exogenous and endogenous conditions.
Protective effect of mussel polysaccharide on cyclophosphamide‐induced intestinal oxidative stress injury via Nrf2‐Keap1 signaling pathway

Abstract The hard‐shelled mussel (Mytilus coruscus) has been used as a traditional Chinese medicine and health food in China for centuries. Polysaccharides from mussel has been reported to have multiple biological functions, however, it remains unclear whether mussel polysaccharide (MP) exerts protective effects in intestinal functions, and the underlying mechanisms of action remain unclear. The aim of this study was to investigate the protective effects and mechanism of MP on intestinal oxidative injury in mice. In this study, 40 male BALB/C mice were used, with 30 utilized to produce an animal model of intestinal oxidative injury with intraperitoneal injection of cyclophosphamide (Cy) for four consecutive days. The protective effects of two different doses of MP (300 and 600 mg/kg) were assessed by investigating the change in body weight, visceral index, and observing colon histomorphology. Moreover, the underlying molecular mechanisms were investigated by measuring the antioxidant enzymes and related signaling molecules through ELISA, real‐time PCR, and western blot methods. The results showed that MP pretreatment effectively protected the intestinal from Cy‐induced injury: improved the colon tissue morphology and villus structure, increased superoxide dismutase (SOD), catalase (CAT), and glutathione peroxidase (GSH‐Px) activities, and reduced malondialdehyde (MDA) content in serum and colon tissues. Meanwhile, MP also significantly increased the expression levels of SOD, GSH‐Px, heme oxygenase‐1 (HO‐1), and nuclear factor E2‐related factor 2 (Nrf2) mRNA in colon tissues. Further, western blot results showed that the expression of Nrf2 protein was significantly upregulated while kelch‐like ECH‐associated protein 1 (Keap1) was significantly downregulated by MP in the colonic tissues. This study indicates that MP can ameliorate Cy‐induced oxidative stress injury in mice, and Nrf2‐Keap1 signaling pathway may mediate these protective effects.
Evaluation of Morphological and Quality Parameters in Adult Male Red King Crabs (Paralithodes camtschaticus) Raised to Commercial Weight from Juveniles

Red king crab (RKC) has become a valuable resource, and most of this fishery operates in a quota-regulated area (QRA) east of 26°E. West of the QRA, a free fishery area (FFA) is established to limit further migration. Today, juvenile RKCs from the FFA are not utilized. This study investigated morphological and quality parameters in adult RKCs (≥800 g) after live holding (LH) of 23 months starting from juveniles (on average 500 g). During the LH, the RKCs were kept in two separate tanks, one at ambient seawater temperature (AST) and one at elevated seawater temperature (AST-E). The RKCs were fed ad libitum. Both tanks were divided into two sections, one with a sand tray. After 23 months, the RKCs were processed and analyzed. The hepatosomatic index, abdomen index, meat content, cluster yield, moisture, whiteness index, and instrumental chewiness differed significantly ( P < 0.05 ) between the wild RKCs and the RKCs from one or both LH groups. The availability of sand indicated improved habitat conditions as several parameters were positively affected. Also, lower variation in morphology and quality parameters of the processed muscle was observed in RKCs from the subgroups with access to sand than those without sand.
Determining the Influencing Factors of Purchase Intention of the Class 2021 Students of Bina Nusantara University Alam Sutera

This paper examined the relationship between E-WOM and Social Media Marketing on purchase intention mediated by brand equity. This paper used SPSS 2.6 version to analyze 130 respondents. This paper confirms the influence of social media marketing on brand equity and concludes the significant impact of brand equity on e-WOM, which ultimately provides the answer to the question of why strong brands can persuade their consumers to spread e-WOM messages and influence and motivate others to buy or the same products. The main limitation in this paper is the sample used only Binus University students, so it is less relevant to generalize the research findings to the entire population of social media users. To deeply understand the role of social media marketing activities, further research is needed on social media users in other regions and platforms such as Facebook, Twitter, and YouTube.