Miracle-dz/UniFAR-FTUs huggingface dataset:
In Vitro Anatomical Models for Nasal Drug Delivery

Nasal drug delivery has been utilized for locally acting diseases for decades. The nose is also a portal to the systemic circulation and central nervous system (CNS). In the age of SARS-CoV2, the development of nasal sprays for vaccination and prophylaxis of respiratory diseases is increasing. As the number of nasal drug delivery applications continue to grow, the role of targeted regional deposition in the nose has become a factor is nasal drug development. In vitro tools such as nasal casts help facilitate formulation and product development. Nasal deposition has been shown to be linked to pharmacokinetic outcomes. Developing an understanding of the complex nasal anatomy and intersubject variability can lead to a better understanding of where the drug will deposit. Nasal casts, which are replicas of the human nasal cavity, have evolved from models made from cadavers to complex 3D printed replicas. They can be segmented into regions of interest for quantification of deposition and different techniques have been utilized to quantify deposition. Incorporating a nasal cast program into development can help differentiate formulations or physical forms such as nasal powder versus a liquid. Nasal casts can also help develop instructions for patient use to ensure deposition in the target deposition site. However, regardless of the technique used, this in vitro tool should be validated to ensure the results reflect the in vivo situation. In silico, CFD simulation or other new developments may in future, with suitable validation, present additional approaches to current modelling, although the complexity and wide degree of variability in nasal anatomy will remain a challenge. Nonetheless, nasal anatomical models will serve as effective tools for improving the understanding of nasal drug delivery.
Inverse Design of Local Solar Flux Distribution for a Solar Methanol Reforming Reactor Based on Shape Optimization

In this work, an inverse design method that couples the multi-physics model for a solar trough thermochemical reactor (SPTR) and shape optimization model is proposed to find out optimal solar flux distribution for maximizing overall reactor performance. The gradient-based segmentation method is applied to convert the continuous solar flux into step-like flux to guide the concentrator system design. Performance comparisons among uniform flux, linear decreasing flux, and the optimized non-linear flux are also conducted to discuss the reliability of SPTR performance improvement. The results show that the optimized non-linear solar flux can improve the methanol conversion, solar thermochemical conversion, and hydrogen yield of SPTR by 2.5, 3.3, and 2.4%, respectively, compared with the uniform flux. This is attributed to the fact that the optimized non-uniform flux distribution enhances the synergy between temperature and reaction fields, and achieves a better match between spatial solar flux supply and local energy demand by reactions. Also, it is shown that the optimized step-like flux, achieved by regressing the optimized non-linear flux, can perfectly maintain SPTR performance and is effective in boosting SPTR performance under different operating conditions.
Lateral predictive coding revisited: internal model, symmetry breaking, and response time

Predictive coding is a promising theoretical framework in neuroscience for understanding information transmission and perception. It posits that the brain perceives the external world through internal models and updates these models under the guidance of prediction errors. Previous studies on predictive coding emphasized top-down feedback interactions in hierarchical multilayered networks but largely ignored lateral recurrent interactions. We perform analytical and numerical investigations in this work on the effects of single-layer lateral interactions. We consider a simple predictive response dynamics and run it on the MNIST dataset of hand-written digits. We find that learning will generally break the interaction symmetry between peer neurons, and that high input correlation between two neurons does not necessarily bring strong direct interactions between them. The optimized network responds to familiar input signals much faster than to novel or random inputs, and it significantly reduces the correlations between the output states of pairs of neurons.
An Integrative Analysis Revealing ZFHX4-AS1 as a Novel Prognostic Biomarker Correlated with Immune Infiltrates in Ovarian Cancer

Ovarian cancer (OC) is the main cause of deaths worldwide in female reproductive system malignancies. Growing studies have indicated that eRNAs could regulate cellular activities in various tumors. Yet the potential roles of eRNAs in OC progression have not been elucidated. Thus, comprehensive assays were needed to screen the critical eRNAs and to explore their possible function in OC. We used Kaplan–Meier methods to identify survival-associated eRNAs in OC based on TCGA datasets. The levels of ZFHX4-AS1 were examined using TCGA datasets. Further exploration was carried out based on the following assays: clinical and survival assays, GO terms, and KEGG assays. TIMER was applied to delve into the relationships between ZFHX4-AS1 and tumor immune infiltration. In this research, we observed 71 survival-related eRNAs in OC patients. ZFHX4-AS1 was highly expressed in OC specimens and predicted a poor prognosis of OC patients. In addition, high ZFHX4-AS1 expression was positively related to the advanced stages of OC specimens. Multivariate assays revealed that ZFHX4-AS1 was an independent prognostic factor for overall survival of OC patients. KEGG analysis indicated that ZFHX4-AS1 may play a regulatory effect on TGF-beta signaling, PI3K-Akt signaling, and proteoglycans in cancer. The pan-cancer validation indicated that ZFHX4-AS1 was related to survival in eight tumors, namely, UCEC, STAD, SARC, OV, ACC, KICH, KIRC, and BLCA. The expression of ZFHX4-AS1 was correlated with the levels of B cells, T cell CD8+, neutrophil, macrophage, and myeloid dendritic cells. Simultaneously, ZFHX4-AS1 may be a prognostic biomarker and a distinctly immunotherapy-related eRNA in OC.
Extending Sniper with Support to Access Operand Values: A Case Study on Reusability Measurement

This work presents the augmentation of Sniper, a state-of-the-art multi/many-core simulator, with access to the operand values of a specific group of instructions. Our motivation for accessing the operand values is given because computer programs, in particular graphic and multimedia applications, are characterized by a high degree of redundancy which can be exploited by dynamic instruction reuse techniques. This paper falls into the category of "open architectures" starting from the open-source concept, as it provides researchers with a methodology for reading the values of instruction operands. The most important added value is a technical one, comprising details about the simulator’s architecture and our modifications. Furthermore, we propose a simulation methodology to study the potential reusability of specific types of dynamic instructions. The experimental study is done on the SPLASH-II benchmark suite under different parameters using the modified simulator. Among parameters we vary the number of cores, the compiler optimization method and the operand history length (depth of different operand values stored for each instruction). Our results are indicating a promising potential of reusability, on average varying from 84% to 87%, on selected types of dynamic instructions and lead to the idea of implementing a 4-way associative reuse buffer in a multi/many-core system. The level of optimization of the compiler influences the degree of reusability and overall performance. A rough estimation of potential gain in performance (speedup) is also calculated, reaching a maximum of 17.5% and 3.6% on average.
Online Dynamic Security Assessment Using Phasor Measurement Unit and Forecasted Load

On-line dynamic security assessment (DSA) analysis has been developed and applied in several power dispatching control centers. Existing applications of DSA systems are limited by the assumption of the present system operating conditions and computational speeds. To overcome these obstacles, this research developed a novel two-stage DSA system to provide periodic security prediction in real time. The major contribution of this research is to develop an open source on-line DSA system incorporated with Phasor Measurement Unit (PMU) data and forecast load. The pre-fault prediction of the system can provide more accurate assessment of the system and minimize the disadvantage of a low computational speed of time domain simulation. This Thesis describes the development of the novel two-stage on-line DSA scheme using phasor measurement and load forecasting data. The computational scheme of the new system determines the steady state stability and identifies endangerments in a small time frame near real time. The new on-line DSA system will periodically examine system status and predict system endangerments in the near future every 30 minutes. System real-time operating conditions will be determined by state estimation using phasor measurement data. The assessment of transient stability is carried out by running the time-domain simulation using a forecast working point as the initial condition. The forecast operating point is calculated by DC optimal power flow based on forecast load.
Plant-Based Foods and Vascular Function: A Systematic Review of Dietary Intervention Trials in Older Subjects and Hypothesized Mechanisms of Action

Cardiovascular diseases, still the leading cause of mortality in the world, are closely related to vascular function. Older subjects are more susceptible to endothelial dysfunction and therefore it is important to define possible preventive or support strategies, such as consumption of foods with health-promoting effects. This systematic review aims to summarize the currently available evidence on acute or chronic trials testing the effect of selected plant-based foods on vascular function parameters in older subjects, and consider plausible mechanisms that may support the main findings. A total of 15 trials were included and analyzed, testing the effects of beetroot, plum, blueberry, and vegetable oils. We found some interesting results regarding markers of vascular reactivity, in particular for beetroot, while no effects were found for markers of arterial stiffness. The amelioration of vascular function seems to be more related to the restoration of a condition of nitric oxide impairment, exacerbated by diseases or hypoxic condition, rather than the enhancement of a physiological situation, as indicated by the limited effects on healthy older subjects or in control groups with young subjects. However, the overall set of selected studies is, in any case, rather limited and heterogeneous in terms of characteristics of the studies, indicating the need for additional high-quality intervention trials to better clarify the role of vegetable foods in restoring and/or improving vascular function in order to better elucidate the mechanisms through which these foods may exert their vascular health benefits in older subjects.
Carbon Dioxide and Methane Dynamics in a Peatland Headwater Stream: Origins, Processes and Implications

First‐order streams flowing through peatlands receive, carry and transform large amounts of organic carbon, methane (CH4) and carbon dioxide (CO2) but remain poorly documented. The objectives of this study were to (a) identify the origins of CO2 and CH4 (thereafter C‐GHG for carbon greenhouse gases) in a peatland headwater stream, (b) determine the environmental factors driving C‐GHG export and emissions, and (c) quantify C‐GHG losses from this system and discuss its implications. Data were collected from eight sampling sites along a 3 km boreal peatland headwater stream (Eastern Canada) over the growing seasons 2019 and 2020. The studied stream was oversaturated in pCO2 [min: 2,044; max: 23,306 μatm] and pCH4 [14; 17,614 μatm]. A mass balance model showed that ∼81% of in‐stream CO2 originated from porewater seepage while the remaining 17% and 2% originated from in‐stream productivity and methane oxidation, respectively. Porewater seepage was concluded to be the primary source of CH4. Seasonal dissolved C‐GHG concentrations were negatively correlated with the peatland water table depth, suggesting an active release of carbon‐rich peat porewater during the base flow. Nevertheless, greater C‐GHG losses occurred during stormflow periods which acted as pulses with most of the C‐GHG being shunted downstream. The sum of C‐GHG export and emissions at our site was 8.08 gC m−2 y−1 with 86% being released to the atmosphere and 14% being exported downstream. Our study demonstrates that peatland headwater streams act as large sources of C‐GHG and that precipitation events and topography control the magnitude of the fluxes.
Trajectory tracking control with convergence time assessment

This paper presents a general procedure for state feedback trajectory tracking control design for a class of nonlinear system that combines smoothness, robustness and convergence time assessment and reduction to a prescribed invariant residual set. In particular, it is well adapted to deal with the trajectory tracking control of a half-car kinematic model since only one simple design condition provides the control law that imposes to the closed-loop system, asymptotic tracking of a given trajectory with a prescribed yaw angle orientation. Norm bounded additive matched disturbances are considered in order to establish a trade-off between robustness and speed of convergence. Two examples and a case study are presented and discussed in order to clearly illustrate and compare the theoretical results.
The Influence of Textbook Visual Quality of Geographical Phenomena on Children’s Conceptions

Abstract The aim of the presented study is to evaluate the influence of the quality of visuals in printed geography textbooks on the character of children’s conceptions using the example of the geographical location concept. Visuals are a graphical representation of a certain phenomenon. A two-tier diagnostic test without and with three types of high and low quality physical-geographical visuals was used to achieve this objective. The research study among elementary school students (n = 434) has shown that students are mostly unable to work effectively with visuals due to their inappropriate properties such as headline quality or factual errors.
Grounding the Analysis of Cognitive Processes in Music Performance: Distributed Cognition in Musical Activity by Linda T. Kaastra

The opening of Grounding the Analysis of Cognitive Processes in Music by Linda T. Kaastra poses a question that implies an ambitious agenda: what is music? As the title of the book suggests, Kaastra addresses this question by locating her work ﬁ rmly in a performance-centered ontology: music as action rather than object. Not so much “ what is music? ” , then, but rather “ where ” , “ how ” , or even “ when is music? ” . In this way, the main concern of the book — the location of (musical) knowledge
RACIAL PROFILING ON POLICE STOP AND SEARCH PRACTICE AS PORTRAYED IN THE GEORGE TILLMAN’S MOVIE THE HATE U GIVE

Racial profiling becomes public spotlight over the past two decades in America that creates right devastation and discrimination. Therefore, this thesis aims to find racial profiling on police stop and search as portrayed in the movie The Hate U Give by Goerge Tillman which the movie tells about the life of Afro-American people who lived discriminated by state institutions. The objectives of this study are to describe the potrayal of racial profiling in Angie Thomas The Hate U Give movie and to find the motive of Racial profiling in Angie Thomas The Hate U Give movie. This study is typical library research with descriptive qualitative method. This study used critical race theory by Delgado and Stefancic (2001), racial profiling theory by Filimon (2015), and also movie theory by Boggs and Petrie. At the end of this study, the writer finds that the racial profiling practice in the movie is portrayed through events and experiences in the form of discrimination in police service and bias in news media. Meanwhile, the motives of racial profiling are police strategy specifically enforcement, prejudice and law bias.
An Improved Immune Genetic Algorithm for Solving the Flexible Job Shop Scheduling Problem with Batch Processing

This paper presents a mathematical model for the flexible job shop scheduling problem (FJSP) with batch processing for manufacturing enterprises with both the flexible job shop scheduling problem and a batch process (BP) problem in actual production. An improved immune genetic algorithm (IGA) based on greedy thought combined with local scheduling rules is used to solve this scheduling problem. In the flexible job shop part, the greedy optimal solution is obtained through the greedy thought. The concept of cross-entropy is then introduced to improve the standard IGA. Calculating the cross-entropy of the individual and greedy optimal solutions for optimization considerably accelerates the optimization speed of the algorithm and enhances the ability of the algorithm to escape the local optimum. In the batching process, effective batching rules are designed to reduce blockage and improve batching efficiency; thus, the job can quickly and effectively pass the batching process and complete the entire production process. In the algorithm verification stage, standard FJSP datasets are used to simulate and verify the proposed algorithm. Considering the specific FJFP with BP problem, we perform simulation experiments with actual production data of a transformer manufacturer. The results show that the proposed method can effectively solve such problems.
Investigation into Mode Localization of Electrostatically Coupled Shallow Microbeams for Potential Sensing Applications

With the constant need for the development of smart devices, Micro-Electro-Mechanical Systems (MEMS) based smart sensors have been developed to detect hazard materials, micro-particles or even toxic substances. Identifying small particles using such micro-engineering technology requires designing sensors with high sensitivity, selectivity and ease of integration with other electronic components. Nevertheless, the available detection mechanism designs are still juvenile and need more innovative ideas to be even more competitive. Therefore, this work aims to introduce a novel, smart and innovative micro-sensor design consisting of two weakly electrostatically coupled microbeams (both serving as sensors) and electrically excited using a stationary electrode assuming a dc/ac electric signal. The sensor design can be tuned from straight to eventually initially curved microbeams. Such an arrangement would develop certain nonlinear phenomena, such as the snap-through motion. This behavior would portray certain mode veering/mode crossing and ultimately mode localization and it would certainly lead in increasing the sensitivity of the mode-localized based sensing mechanism. These can be achieved by tracking the change in the resonance frequencies of the two microbeams as the coupling control parameter is varied. To this extent, a nonlinear model of the design is presented, and then a reduced-order model considering all geometric and electrical nonlinearities is established. A Long-Time Integration (LTI) method is utilized to solve the static and dynamics of the coupled resonators under primary lower-order and higher-order resonances, respectively. It is shown that the system can display veering and mode coupling in the vicinity of the primary resonances of both beams. Such detected modal interactions lead to an increase in the sensitivity of the sensor design. In addition, the use of two different beam’s configurations in one device uncovered a possibility of using this design in detecting two potential substances at the same time using the two interacting resonant peaks.
Equivariant Holomorphic Filters - Theory and Applications

This article presents a new class of nonlinear image filters, which can be used in various application domains in early vision. The filters are equivariant with respect to the Euclidean motion. To obtain equivariance we use the tool of group integration. Group integration offers a constructive way to compute invariant features in various spaces. In this work it is used to define a projection that maps any image transformation on its equivariant part. Applying this concept on an image transformation based on a holomorphic kernel we are able to derive a class of filters which can be computed very efficiently. We show relations of our approach with Volterra filters, steerable filters and complex moments. In the context of object detection the filter may be interpreted as some kind of generalized Hough transform. The proposed algorithm is used for enhancing noisy contours and rapid object detection in microscopical images. The obtained results are compared to stateof-art approaches.
Fragmentation Size Distribution Measurement by GNSS-Aided Photogrammetry at Real Mine Site

In mining operations that employ explosives and mineral processing, one of the important factors for efficient and low-cost operation is the fragmentation size distribution of rock after it has been blasted. Automatic scaling is a critical component of fragmentation size distribution measurement as it will directly determine the accuracy of the size estimation. In this study, we propose a method to create a system for creating a scaled 3D CG model, without the use of ground truth data such as GCPs (Ground Control Points), for the purpose of improving fragmentation size distribution measurement using positional data such as GNSS (Global Navigation Satellite System)-aided photogrammetry. We confirmed the validation of the method through an experimental evaluation of actual muckpiles. The results showed evidence of improving the scaling aspect of 3D fragmentation measurement systems without using GCPs or manual scales, specifically in surface mines where GNSS data are available.
T-Cell Receptor β Chain and B-Cell Receptor Repertoires in Chronic Hepatitis B Patients with Coexisting HBsAg and Anti-HBs

Antibodies in response to antigens are related to the immune repertoire of T- and B-cell receptors. However, some patients with chronic hepatitis B (CHB) have coexisting HBsAg and anti-HBsAg antibodies (anti-HBs) that cannot neutralize HBV. We attempted to investigate the repertoires that produce this response in CHB patients. The T-cell receptor β chain (TRB) and B-cell receptor (BCR) repertoires of peripheral blood genomic DNA were analyzed using MiXCR. T-cell receptor (TCR) cluster analysis was carried out by clusTCR, and motifs prediction was selected by Multiple Em for Motif Elicitation (MEME). A total of 76 subjects were enrolled, including 26 HBsAg and anti-HBs coexisting patients with CHB (DP group), 25 anti-HBs single-positive healthy people (SP group), and 25 CHB patients (CHB group). The clone length of BCR in 39, 90 was significantly different among these groups (p = 0.005, 0.036). The motif “CASSLG” in the DP group was significantly higher than SP and CHB groups and may relate to coexistence, and the motif “GAGPLT” was only shown in the SP group and may relate to anti-HB expression. These provide important insights into vaccine development and CHB treatment.