Miracle-dz/UniFAR-FTUs huggingface dataset:
Development of methods for evaluating options for improving the air quality in Santiago, Chile and its environs

Officials from both the Santiago metropolitan air quality commission (La Comision Especial de Descontaminacion de le Region Metropolitana) and a government-owned copper development company (La Empresa Nacional de Mineria (ENAMI)) have asked assistance to deal with the air quality problems in Santiago and associated with smelter emissions. Two smelter sites are examined. One smelter, Ventanas, is located on the Pacific coast to the northwest of Santiago, while the other, Paipote, is located several hundred kilometers to the north. The Ventanas emissions may potentially affect Santiago air quality. Several advantages of working with the smelters in the early phases of the project are: (1) the meteorological and air quality monitoring in the vicinity of the smelters allows for model validation; (2) the development of a useful emission inventory is easier, (3) the smelters pose a simpler problem, which when resolved, will provide an early benefit to our Chilean colleagues, and (4) important experience is gained in preparation to delve deeper into Santiago`s air pollution problems. Our goals for this phase of the project include: determining the smelters impact on air quality in surrounding communities; evaluating whether air pollution from the smelters reaches Santiago; and helping Chilean scientists meet a national decreemore » to have air quality models for smelters. « less
A Geometric Structure Based Non Local Mean Image Denoising Algorithm

With the widespread application of image recognition technology, the commercial application value of image denoising is gradually increasing. To optimize the performance of non local mean image denoising algorithms, the similarity of image blocks in this algorithm is now integrated into the evaluation calculation steps of image block direction similarity and geometric information similarity. A neural network structure is used to optimize the mapping function between image blocks, assisting the NLM algorithm in finding the similarity of image blocks. The denoising experimental results for the improved algorithm show that when the noise variance is 25, the normalized peak signal-to-noise ratios of the improved algorithm are 0.58, 0.62, and 0.43, respectively. The improved non local mean image denoising algorithm outperforms other comparative algorithms in terms of information entropy, peak signal-to-noise ratio, and average gradient, which represent the denoising effect. When the noise variance is 45, the normalized structural similarity, mutual information, root mean square error, and absolute error of the algorithm are 0.88, 0.78, 8.2, and 9.7, respectively. The improved non local mean image denoising algorithm performs better than other algorithms in terms of evaluation indicators such as structural similarity, mutual information, root mean square error, and absolute error in preserving original information. It can be seen that the improved algorithm designed in this study has better denoising performance than common methods, and can retain the core information of the original image. It can provide higher quality image denoising services for meteorological prediction, agricultural planting, and other fields.
CRISPR/Cas9-Mediated HY5 Gene Editing Reduces Growth Inhibition in Chinese Cabbage (Brassica rapa) under ER Stress

Various stresses can affect the quality and yield of crops, including vegetables. In this study, CRISPR/Cas9 technology was employed to examine the role of the ELONGATED HYPOCOTYL 5 (HY5) gene in influencing the growth of Chinese cabbage (Brassica rapa). Single guide RNAs (sgRNAs) were designed to target the HY5 gene, and deep-sequencing analysis confirmed the induction of mutations in the bZIP domain of the gene. To investigate the response of Chinese cabbage to endoplasmic reticulum (ER) stress, plants were treated with tunicamycin (TM). Both wild-type and hy5 mutant plants showed increased growth inhibition with increasing TM concentration. However, the hy5 mutant plants displayed less severe growth inhibition compared to the wild type. Using nitroblue tetrazolium (NBT) and 3,3′-diaminobenzidine (DAB) staining methods, we determined the amount of reactive oxygen species (ROS) produced under ER stress conditions, and found that the hy5 mutant plants generated lower levels of ROS compared to the wild type. Under ER stress conditions, the hy5 mutant plants exhibited lower expression levels of UPR- and cell death-related genes than the wild type. These results indicate that CRISPR/Cas9-mediated editing of the HY5 gene can mitigate growth inhibition in Chinese cabbage under stresses, improving the quality and yield of crops.
Spatial analysis and modeling in geographical transformation process : GIS-based applications

Contributing authors Preface 1. Spatial Analysis: Evolution, methods, and applications By Yuji Murayama and Rajesh Bahadur Thapa Part I: Spatial Scale, Autocorrelation and Neighborhood Analysis 2. Field-based fuzzy spatial reasoning model for constraint satisfaction problem. By Yaolong Zhao, Yumin Zhang, and Yuji Murayama 3. Testing local spatial autocorrelation using k-order neighbours. By Changping Zhang and Yuji Murayama 4. Effect of spatial scale on urban land-use pattern analysis. By Yaolong Zhao and Yuji Murayama 5. Modeling neighborhood interaction in Cellular Automata-based urban geosimulation. By Yaolong Zhao and Yuji Murayama Part II: Urban Analysis: Zonation and Population Structure 6. Estimation of building population from LIDAR derived digital volume model. By Ko Ko Lwin and Yuji Murayama 7. Accuracy assessment of GIS based building population estimation algorithm. By Ko Ko Lwin and Yuji Murayama 8. The application of GIS in education administration. By Fatemeh Ahmadi Nejad Masouleh, Yuji Murayama, and Todd Wendell Rho'Dess Part III: Land Use and Land Cover Change 9. Accuracy of land use and land cover mapping methods. By Rajesh Bahadur Thapa and Yuji Murayama 10. Urban dynamics analysis using spatial metrics geosimulation. By Yaolong Zhao and Yuji Murayama 11. Modeling deforestation using a neural network-Markov model. By Duong Dang Khoi and Yuji Murayama Part IV: Multi-criteria GIS Analysis 12. Land suitability analysis for peri-urban agriculture. By Rajesh Bahadur Thapa, Federic Borne, and Yuji Murayama 13. Suitability analysis for beekeeping sites integrating GIS & MCE Techniques. By Ronald C. Estoque and Yuji Murayama 14. Spatial allocation of the best shipping canal in South Thailand. By Rajesh Bahadur Thapa, Michiro Kusanagi, Akira Kitazumi, and Yuji Murayama Part V: Socio-environmental Applications 15. Spatiotemporal patterns of urbanization: Mapping, measurements, and analysis. By Rajesh Bahadur Thapa and Yuji Murayama 16. Spatial determinants of poverty using GIS-based mapping. By Brandon M. Vista and Yuji Murayama Index
A cultural training for the improvement of cognitive and affective Theory of Mind in people with Multiple Sclerosis: a pilot randomized controlled study

Theory of Mind (ToM), the ability to understand and attribute mental states to ourselves and others, could be impaired in Multiple Sclerosis (MS), a neurodegenerative disease affecting young adults. Considering that ToM is strictly connected to Quality of Life (QoL) in MS and that could enhance the social support network -which is particularly important for this population-, we aimed to design and implement a novel ToM rehabilitation training. To make the training as much ecological as possible, we have devised a protocol enhancing ToM through stimuli depicting real-world conditions (video-clips taken from cinema movies, literary fictions, and audio voices). We test training’s effect on both cognitive and affective components of ToM in a sample of 13 subjects, randomly assigned to the ToM training Group and to the Control Group. The following ToM tasks were administered: the Reading the Mind in the Eyes (RMET), the Strange Stories task, the Faux Pas Task and the False Belief First- and Second - Order Task (FB II and III order). We also administered a psycho-behavioral assessment through the Toronto Alexithymia Scale (TAS-20). Results show that our novel ToM training is useful in enhancing ToM abilities measured by the following tasks: the RMET (affective task, p = 0.015) and the FB II-order task (FB, cognitive task, p = 0.032). Our ToM training had also a significant effect on the total score of the TAS-20 Scale (p = 0.018) and on its “Difficulty Describing Feelings subscale” (p = 0.018), indicating a reduction of the alexithymia traits. Future works with larger samples could investigate the ToM training effectiveness in a more representative MS populations.
On Lengths of Singleton-Optimal Locally Repairable Codes

A locally repairable code is called Singleton-optimal if it achieves the Singleton-type bound. Such codes are of great theoretic interest in the study of locally repairable codes. One of the major problems in this topic is to determine the maximum length of a <inline-formula> <tex-math notation="LaTeX">$q$ </tex-math></inline-formula>-ary Singleton-optimal locally repairable code with fixed locality and minimum distance. Unlike classical MDS codes, the maximum length of Singleton-optimal locally repairable codes is very sensitive to the minimum distance and locality. Thus, determining the maximum length of the Singleton-optimal locally repairable codes is more challenging and complicated. In literature, many efforts are paid to solve this problem especially for small distance and locality regime. Moreover, most of works also requires that <inline-formula> <tex-math notation="LaTeX">$(r+1)|n$ </tex-math></inline-formula> and the recovery sets are disjoint so as to simplify the argument, where <inline-formula> <tex-math notation="LaTeX">$r$ </tex-math></inline-formula> is locality and <inline-formula> <tex-math notation="LaTeX">$n$ </tex-math></inline-formula> is the code length. In this paper, we derive some upper bounds on the maximum length of Singleton-optimal locally repairable codes with minimum distance <inline-formula> <tex-math notation="LaTeX">$5, 6$ </tex-math></inline-formula> and 7 without the constraint that <inline-formula> <tex-math notation="LaTeX">$(r+1)|n$ </tex-math></inline-formula> and the recovery sets are disjoint.It turns out that even without this constraint we still obtain better upper bounds for codes with small locality and distance compared to known results. Furthermore, based on our upper bounds for codes with small distance and locality, we propose the propagation rule to derive some upper bounds for codes with relatively large distance and locality assuming that <inline-formula> <tex-math notation="LaTeX">$(r+1)|n$ </tex-math></inline-formula> and recovery sets are disjoint.
Uncertainty-aware automated assessment of the arm impedance with upper-limb exoskeletons

Providing high degree of personalization to a specific need of each patient is invaluable to improve the utility of robot-driven neurorehabilitation. For the desired customization of treatment strategies, precise and reliable estimation of the patient's state becomes important, as it can be used to continuously monitor the patient during training and to document the rehabilitation progress. Wearable robotics have emerged as a valuable tool for this quantitative assessment as the actuation and sensing are performed on the joint level. However, upper-limb exoskeletons introduce various sources of uncertainty, which primarily result from the complex interaction dynamics at the physical interface between the patient and the robotic device. These sources of uncertainty must be considered to ensure the correctness of estimation results when performing the clinical assessment of the patient state. In this work, we analyze these sources of uncertainty and quantify their influence on the estimation of the human arm impedance. We argue that this mitigates the risk of relying on overconfident estimates and promotes more precise computational approaches in robot-based neurorehabilitation.
Ramsey theory

a temporary collection of stars, we earthlings observe from the edge of an ordinary galaxy. Yet most stargazers agree that the night sky appears to be filled with constellations in the shape of straight lines, rectangles and pentagons. it be that such geometric patterns arise from unknown forces in the cosmos?
Revisiting Schistosoma mansoni Micro-Exon Gene (MEG) Protein Family: A Tour into Conserved Motifs and Annotation

Genome sequencing of the human parasite Schistosoma mansoni revealed an interesting gene superfamily, called micro-exon gene (meg), that encodes secreted MEG proteins. The genes are composed of short exons (3–81 base pairs) regularly interspersed with long introns (up to 5 kbp). This article recollects 35 S. mansoni specific meg genes that are distributed over 7 autosomes and one pair of sex chromosomes and that code for at least 87 verified MEG proteins. We used various bioinformatics tools to produce an optimal alignment and propose a phylogenetic analysis. This work highlighted intriguing conserved patterns/motifs in the sequences of the highly variable MEG proteins. Based on the analyses, we were able to classify the verified MEG proteins into two subfamilies and to hypothesize their duplication and colonization of all the chromosomes. Together with motif identification, we also proposed to revisit MEGs’ common names and annotation in order to avoid duplication, to help the reproducibility of research results and to avoid possible misunderstandings.
LTCC-Based Dual-Polarized AiP Module by Multilayered Cross-Dipole Antennas for 5G Mobile Terminal Applications at 28 GHz Band

An antenna-in-package (AiP) of $4\,\, {}\times {}4$ elements with dual-polarized radiations for high-power radiation at a 28 GHz band was designed and fabricated by low-temperature co-fired ceramic (LTCC) for fifth-generation (5G) applications. The design starts with selecting cross-dipole elements to ensure good polarization purity. The l/4 separation from a ground plane is achieved by considering a proper combination of multilayered substrates’ thicknesses and their dielectric constant, where the feedings are probed by coaxial-type vias from the bottom. The dipole arms’ shapes are optimally tuned to achieve broadband reflection coefficients. This AiP has the advantage of dual-polarizations along +/−45° to avoid harmful interferences from metal-supporting structures, reasonable inter port isolations, and low cross-polarization levels (XPLs). The AiP has a compact profile of $28\,\, {}\times {}28$ mm2. The interport isolation between the polarization excitation ports is larger than 33 dB from HFSS full-wave simulations. The elements’ bandwidth is larger than 6 GHz from the full-wave simulation and broader than 4 GHz from measurements over the antenna prototype. The array has a bandwidth larger than 6 GHz from measurement with a maximum gain of 16.6 dBi and a sidelobe level (SLL) of 13.3 dB, validating the design concept.
Adaptive sliding mode control with gravity compensation: Application to an upper-limb exoskeleton system

This paper presents a robust control algorithm with gravity compensation in presence of parametric uncertainties. The application deals with an upper limb exoskeleton system, aimed for a rehabilitation application. The treated system is an robot with two degrees of freedom acting on the flexion / extension movement of the shoulder and elbow. An adaptive sliding mode algorithm with gravity compensation has been developed to control the upper limb exoskeleton system. A Stability study is realized. Then, a robustness analysis in the presence of parametric uncertainties using Monte Carlo simulation is developed. To prove the performance of the gravity compensation approach, a comparison study is done. Simulation results are presented to highlight the performances and the effectiveness of the proposed controller using gravity compensation.
Active Disturbance Rejection Repetitive Control for Current Harmonic Suppression of PMSM

Current harmonics will deteriorate the performance of permanent magnet synchronous motor drives, and active disturbance rejection control (ADRC) is a promising method to reduce the harmonics. However, determined by the observation and compensation level of extended state observer (ESO), the harmonic suppression ability of the traditional ADRC is limited. To significantly decrease low-frequency current harmonics, this article proposes a novel active disturbance rejection repetitive control scheme used for current loops, in which two improvements for the ESO are presented. One is the introduction of a low-pass filter (LPF) instead of the conventional integrator, and that can enhance the disturbance observation capability. Based on this new LPF-ESO, the other is the increase of a repetitive controller in parallel with the disturbance loop, which can further estimate the periodic disturbances and thus improve the compensation performance at specific periodic frequencies. The parameter design, stability, antidisturbance ability, tracking performance and robustness of the proposed ADRC current loop are analyzed. Compared with the traditional ADRC, the proposed scheme can obviously reduce the current harmonics, moreover, fast dynamic response and strong robustness can be achieved. The simulation and experimental results about a 1.1 KW PMSM are provided to verify the effectiveness of the proposed scheme.
Identification of Plasma Proteins as Biomarkers for Mild Cognitive Impairment and Alzheimer’s Disease Using Liquid Chromatography–Tandem Mass Spectrometry

Blood proteins can be used for biomarkers to monitor the progression of cognitive decline, even in the early stages of disease. In this study, we developed a liquid chromatography–tandem mass spectrometry (LC-MS/MS)-based blood test to identify plasma proteins that can be used to detect mild cognitive impairment (MCI) and Alzheimer’s disease (AD). Using this system, we quantified plasma proteins using isotope-labeled synthetic peptides. A total of 192 patients, including 63 with AD, 71 with MCI, and 58 non-demented controls (NDCs), were analyzed. Multinomial regression and receiver operating characteristic (ROC) analyses were performed to identify specific combinations of plasma protein panels that could differentiate among NDCs, those with MCI, and those with AD. We identified eight plasma protein biomarker candidates that can be used to distinguish between MCI and AD. These biomarkers were associated with coagulation pathways, innate immunity, lipid metabolism, and nutrition. The clinical potential to differentiate cognitive impairment from NDC was assessed using area under the curve values from ROC analysis, which yielded values of 0.83 for males and 0.71 for females. This LC-MS-based plasma protein panel allows the pathophysiology of AD to be followed through detection of cognitive decline and disease progression markers.
An Investigation of Cyber-Attacks and Security Mechanisms for Connected and Autonomous Vehicles

Connected and autonomous vehicles (CAVs) can fulfill the emerging demand for smart transportation on a global scale. Such innovations for transportation can bring manyfold benefits, from fully autonomous driving services to proactive vehicle monitoring and traffic management. However, given the complexity involved in the deployment of CAVs, zero-tolerance safety, and security measures must be incorporated to avert vehicle immobilization, road accidents, disclosure of sensitive data, or any potential threats. In this article, we conceive a reference architecture for a CAVs ecosystem to derive a common attack taxonomy for the investigation of existing and emerging cyber threats. Subsequently, we discuss security mechanisms for the CAVs ecosystem that can be useful for the safe and secure transportation of passengers from one destination to another based on comprehensive studies of academic literature and industry white papers. Our work can provide valuable insights to security engineers and system architects for investigating security problems using a top-to-bottom approach and can aid in envisioning robust security solutions to ensure seamless CAVs operations.
Comparison of on-Statin Lipid and Lipoprotein Levels for the Prediction of First Cardiovascular Event in Type 2 Diabetes Mellitus

Background A substantial cardiovascular disease risk remains even after optimal statin therapy. Comparative predictiveness of major lipid and lipoprotein parameters for cardiovascular events in patients with type 2 diabetes mellitus (T2DM) who are treated with statins is not well documented. Methods From the Korean Nationwide Cohort, 11,900 patients with T2DM (≥40 years of age) without a history of cardiovascular disease and receiving moderate- or high-intensity statins were included. The primary outcome was the first occurrence of major adverse cardiovascular events (MACE) including ischemic heart disease, ischemic stroke, and cardiovascular death. The risk of MACE was estimated according to on-statin levels of low-density lipoprotein cholesterol (LDL-C), triglyceride (TG), high-density lipoprotein cholesterol (HDL-C), and non-HDL-C. Results MACE occurred in 712 patients during a median follow-up period of 37.9 months (interquartile range, 21.7 to 54.9). Among patients achieving LDL-C levels less than 100 mg/dL, the hazard ratios for MACE per 1-standard deviation change in on-treatment values were 1.25 (95% confidence interval [CI], 1.07 to 1.47) for LDL-C, 1.31 (95% CI, 1.09 to 1.57) for non-HDL-C, 1.05 (95% CI, 0.91 to 1.21) for TG, and 1.16 (95% CI, 0.98 to 1.37) for HDL-C, after adjusting for potential confounders and lipid parameters mutually. The predictive ability of on-statin LDL-C and non-HDL-C for MACE was prominent in patients at high cardiovascular risk or those with LDL-C ≥70 mg/dL. Conclusion On-statin LDL-C and non-HDL-C levels are better predictors of the first cardiovascular event than TG or HDL-C in patients with T2DM.
Proteomic Analysis of Mesenchymal Stromal Cells Secretome in Comparison to Leukocyte- and Platelet-Rich Fibrin

Secretomes of mesenchymal stromal cells (MSCs) are emerging as a novel growth factor (GF)-based strategy for periodontal and bone regeneration. The objective of this study was to compare the secretome of human bone marrow MSC (BMSC) to that of leukocyte- and platelet-rich fibrin (L-PRF), an established GF-based therapy, in the context of wound healing and regeneration. Conditioned media from human BMSCs (BMSC-CM) and L-PRF (LPRF-CM) were subjected to quantitative proteomic analysis using liquid chromatography with tandem mass spectrometry. Global profiles, gene ontology (GO) categories, differentially expressed proteins (DEPs), and gene set enrichment (GSEA) were identified using bioinformatic methods. Concentrations of selected proteins were determined using a multiplex immunoassay. Among the proteins identified in BMSC-CM (2157 proteins) and LPRF-CM (1420 proteins), 1283 proteins were common. GO analysis revealed similarities between the groups in terms of biological processes (cellular organization, protein metabolism) and molecular functions (cellular/protein-binding). Notably, more DEPs were identified in BMSC-CM (n = 550) compared to LPRF-CM (n = 118); these included several key GF, cytokines, and extracellular matrix (ECM) proteins involved in wound healing. GSEA revealed enrichment of ECM (especially bone ECM)-related processes in BMSC-CM and immune-related processes in LPRF-CM. Similar trends for intergroup differences in protein detection were observed in the multiplex analysis. Thus, the secretome of BMSC is enriched for proteins/processes relevant for periodontal and bone regeneration. The in vivo efficacy of this therapy should be evaluated in future studies.