Miracle-dz/UniFAR-FTUs huggingface dataset:
A Hierarchical Bayesian Fusion Method of Infrared and Visible Images for Temperature Monitoring of High-Speed Direct-Drive Blower

The high-speed direct-drive blower is a high-efficiency, energy-saving, and environmentally friendly blower, and it is widely applied in industrial fields. The temperature changes significantly affect the performance of the high-speed direct-drive blower, and it is crucial to monitor its temperature. Infrared and visible light cameras are simultaneously used to measure and characterize temperature information. The measurement method can have both the temperature information of the infrared image and the contrast information of the structure and contour of the visible light image. This article establishes an image fusion representation and probabilistic generation model of infrared and visible images. Then, the information of the infrared and visible images is fused under the Bayesian framework. A hierarchical prior model using the Haar wavelet transform is proposed. The joint maximum a posteriori criterion is chosen, and an appropriate alternate optimization algorithm is designed to achieve information fusion. The proposed method is validated in industrial scenarios of high-speed direct-drive blowers. The experimental results demonstrate the robustness and effectiveness of the proposed method.
Recovery of Lithium Carbonate from Dilute Li-Rich Brine via Homogenous and Heterogeneous Precipitation

An extensive experimental campaign on Li recovery from relatively dilute LiCl solutions (i.e., Li+ ∼ 4000 ppm) is presented to identify the best operating conditions for a Li2CO3 crystallization unit. Lithium is currently mainly produced via solar evaporation, purification, and precipitation from highly concentrated Li brines located in a few world areas. The process requires large surfaces and long times (18–24 months) to concentrate Li+ up to 20,000 ppm. The present work investigates two separation routes to extract Li+ from synthetic solutions, mimicking those obtained from low-content Li+ sources through selective Li+ separation and further concentration steps: (i) addition of Na2CO3 solution and (ii) addition of NaOH solution + CO2 insufflation. A Li recovery up to 80% and purities up to 99% at 80 °C and with high-ionic strength solutions was achieved employing NaOH solution + CO2 insufflation and an ethanol washing step.
Image compression and classification using vector quantization

Vector quantization is a lossy compression technique based on principles from statistical clustering. In this thesis, we present several vector quantization methods for compression and combined compression and classification of images. After a review of the basic ideas of image compression and vector quantization, we describe an image compression technique involving product vector quantization that uses three tree-structured codebooks to encode the mean, gain and shape features of vectors. Joint pruning of the codebooks is shown to provide optimal bit allocation among the features. The method provides low encoding complexity and reduced memory requirements while producing good coding performance. Next, the application of vector quantization to image classification is discussed. Vector quantization can perform block-based classification and compression simultaneously by associating a class label with each codeword. We present two methods of modifying traditional vector quantizer design algorithms to improve the classification ability of the quantizer. One approach modifies the tree-growing algorithm used for constructing tree-structured codebooks by incorporating classification information into the splitting criterion. The second approach explicitly incorporates a Bayes risk component into the distortion measure used for quantizer design, permitting a flexible trade-off between compression and classification priorities. These approaches are used to analyze simulated data, identify tumors in computerized tomography (CT) lung images, and identify man-made regions in aerial images.
Antisense Morpholino-Based In Vitro Correction of a Pseudoexon-Generating Variant in the SGCB Gene

Limb-girdle muscular dystrophies (LGMD) are clinically and genetically heterogenous presentations displaying predominantly proximal muscle weakness due to the loss of skeletal muscle fibers. Beta-sarcoglycanopathy (LGMDR4) results from biallelic molecular defects in SGCB and features pediatric onset with limb-girdle involvement, often complicated by respiratory and heart dysfunction. Here we describe a patient who presented at the age of 12 years reporting high creatine kinase levels and onset of cramps after strenuous exercise. Instrumental investigations, including a muscle biopsy, pointed towards a diagnosis of beta-sarcoglycanopathy. NGS panel sequencing identified two variants in the SGCB gene, one of which (c.243+1548T>C) was found to promote the inclusion of a pseudoexon between exons 2 and 3 in the SGCB transcript. Interestingly, we detected the same genotype in a previously reported LGMDR4 patient, deceased more than twenty years ago, who had escaped molecular diagnosis so far. After the delivery of morpholino oligomers targeting the pseudoexon in patient-specific induced pluripotent stem cells, we observed the correction of the physiological splicing and partial restoration of protein levels. Our findings prompt the analysis of the c.243+1548T>C variant in suspected LGMDR4 patients, especially those harbouring monoallelic SGCB variants, and provide a further example of the efficacy of antisense technology for the correction of molecular defects resulting in splicing abnormalities.
Mapping Spiritual Leadership in Today's Organizations: Bibliometrics Analysis 2017-2021

Introduction/Main Objectives: Leadership research tries to find strategies and ways of good leaders in managing organizations throughout history. With the many studies conducted, various theories of leadership were born. Spiritual Leadership is a synthesis of previous leadership, namely ethics, authenticity, stewardship and other theories. SL seeks to fully pay attention to the dimensions in humans so that individuals experience fullness in the organization. Research reveals that SL has fostered intrinsic value in individuals, resolved problems in organizations well and promoted a sustainable workplace. Background Problems: With a variety of studies related to SL, we try to map the number of journals each year, then see what keywords are correlated with SL, and find influential SL authors. Novelty: This study will look at the latest research themes between 2017-2021 and be assisted by Bibliometric analysis. Research Methods: The search was carried out in the Scopus database, on November 8, 2021. In the search terms in all titles, abstracts, and keywords, the word “spiritual leadership” was written. The filter used is the document year range from 2017 to 2021. Then the results of the scopus analysis are mapped using VosViewer. Finding/Results: The results show an average of 36 articles publish each year. The three countries that produce the most writing are America, China, and Indonesia. Authors like Fry, Usman, Ali, and Yang most frequently cited by other authors. Network analysis and density visualization identify keywords related to SL: workplace spirituality, work engagement, spiritual well-being, organizational commitment, employee performance, job satisfaction and organizational citizenship behaviour. Conclusion: SL research can be developed more broadly on the scope of themes that appear little, such as vision, job satisfaction, employee performance, organizational citizenship behavior, and work engagement. Second, SL research whose scope does not yet exist, such as Education, organizational culture and religion.
Characteristics of the urban heat island effect in the coastal Mediterranean city of Kalamata, Greece

ABSTRACT The urban heat island effect for the coastal Mediterranean city of Kalamata is studied, for June to September during two consecutive years, 2019–2020. Temperature data were gathered by fixed temperature stations, placed in representative locations, covering all the major areas (urban, suburban, and rural). Results showed that the urban area is warmer than suburban and rural ones. The maximum heat island intensity was also estimated, usually achieved during nighttime and early in the morning. As there are no such data for Kalamata, this work helps to identify issues of energy consumption and human comfort. Especially for small Mediterranean cities, the work could be useful for a researcher to clarify the UHI Intensity. Detailed data are presented in the work, both for the clarification of UHI and its intensity and for the characteristics of each area, which could be useful for the development of UHI mitigation strategies, in small coastal cities.
Simultaneous ambient air motion and raindrop size distributions retrieved from UHF vertical incident profiler observations

The raindrop size distribution is a fundamental quantity used to describe the characteristics of rain. Vertically pointing Doppler radar profilers are well suited to retrieve the raindrop size distributions because of their operating frequency and data collection methodology. Doppler radar profilers operating at UHF are sensitive to both Bragg scattering from the radio refractive index of turbulence and Rayleigh scattering from distributed targets. During light precipitation, both scattering processes are resolved in the Doppler velocity spectra. During moderate to heavy precipitation the ambient air motion is not resolved in the Doppler velocity spectra. The sans air motion (SAM) model is introduced in this study and uses only the Rayleigh scattering portion of the Doppler velocity spectrum to estimate the ambient vertical air motion, the spectral broadening, and the raindrop size distribution. The SAM model was applied to 915 MHz profiler observations in central Florida. There was good agreement between the SAM‐model‐retrieved rain rate and mass‐weighted mean diameter at an altitude of 300 m with simultaneous surface disdrometer observations. The SAM model was applied to the profile of Doppler velocity spectra to yield estimates of rain rate, mass weighted mean diameter, and ambient vertical air motion from 300 m to just under the melting level at 4 km.
A Post-Pandemic Exploration of International Student-Athlete Personal Branding and Fan Interaction via Social Media

The population of international student-athletes (ISAs) at the collegiate level has dramatically impacted the sporting landscape in North America. Whereas a passionate group of fans is vital to the success of a sports team, the development of that athlete–fan relationship has grown due to the increased media attention on athlete personal branding and social media presence. The present study explores ISAs’ perceptions of social media use for personal branding, the challenges they face, and the extent to which they interact with fans through social media in a post-pandemic context. Athletes have pivoted more recently from personal appearances and other face-to-face interactions to more virtual means of interacting with fans. Ten semi-structured interviews were conducted with ISAs from various sports within Divisions I and II of the National Collegiate Athletic Association. Four main themes emerged: (1) social media consumption versus content creation, (2) effects of name, image, and likeness regulations, (3) personal brand building on social media, and (4) fan interaction on social media for ISAs. The study aims to inform various collegiate athletics stakeholders on the potential value of ISAs’ personal branding for fan interaction and how this has been impacted by current name, image, and likeness restrictions.
Speed Estimation of Multiphase Induction Motor Using Rotor Slot Harmonics With Limited SNR and Dynamic Load Conditions

Accurate and reliable speed feedback is vital for closed-loop control of multiphase induction motors (IMs), especially in harsh operating scenes, such as ship propulsion. High-performance speed estimation is effective in getting rid of usual sensor failures, through the rotor slot harmonic (RSH) based method that featured for parameter mismatch robustness. However, the accurate and real-time low speed estimation through RSHs under limited signal noise ratio (SNR) and dynamic load conditions is still a challenge, mainly due to the extremely weak and nonstationary amplitude and closely distributed frequency properties of RSHs. In this article, we investigate the performance limitations of low speed estimation using primary rotor slot harmonics (PSHs) of multiphase IMs, whose detectability is ensured through an improved interior detection coil, under limited SNR and dynamic load conditions. A frequency shifting and an amplitude limiting zero-crossing detection algorithm are proposed for efficient extraction and processing of PSHs in full speed range, which effectively improve the estimation accuracy with reduced complexity. Finally, the proposed method is investigated on a nine-phase IM experimental platform within the whole speed range, limiting the steady and transient error, respectively, under 4 and 20 r/min for closed-loop control.
Solid Mechanics in Engineering

Preface. PART A: BASIC CONCEPTS. 1 Introductory Concepts of Solid Mechanics. 2 Internal Forces and Stress. 3 Deformation and Strain. 4 Behaviour of Materials: Constitutive Equations. 5 Summary of Basic Results and Further Idealisations: Solutions using the "Mechanics--of--Materials" Approach. PART B: APPLICATIONS TO SIMPLE ELEMENTS. 6 Axial Loadings. 7 Torsion of Circular Cylindrical Rods: Coulomb Torsion. 8 Symmetric Bending of Beams -- Basic Relations and Stresses. 9 Symmetric Bending of Beams: Deflections, Fundamental Solutions and Superposition. 10 Thin--Wall Pressure Vessels: Thin Shells Under Pressure. 11 Stability and Instability of Rods under Axial Compression: Beam--Columns and Tie--Rods. 12 Torsion of Elastic Members of Arbitrary Cross--Section: de Saint Venant Torsion. 13 General Bending Theory of Beams. PART C: ENERGY METHODS AND VIRTUAL WORK. 14 Basic Energy Theorems, Principles of Virtual Work and their Application to Structural Mechanics. 15 Stability of Mechanical Systems by Energy Considerations: Approximate Methods. Appendix A: Properties of Areas. Appendix B: Some Mathematical Relations. Appendix C: The Membrane Equation. Appendix D: Material Properties. Appendix E: Table of Structural Properties. Appendix F: Reactions, Deflections and Slopes of Selected Beams. Answers to Selected Problems. Index.
Green Chemistry Based Gold Nanoparticles Synthesis Using the Marine Bacterium Lysinibacillus odysseyi PBCW2 and Their Multitudinous Activities

Green chemistry has paved an ‘avant-garde avenue’ in the production and fabrication of eco-friendly stable nanoparticles employing the utilization of biological agents. In the present study we present the first report on the potential of the marine bacterium Lysinibacillus odysseyi PBCW2 for the extracellular production of gold nanoparticles (AuNPs). Utilizing a variety of methods, AuNPs in the cell-free supernatant of L. odysseyi (CFS-LBOE) were identified and their antioxidant, antibacterial, and dye-degrading properties were examined. The visual coloring of the reaction mixture to a ruby red hue showed the production of LBOE-AuNPs; validated by means of XRD, TEM, SEM, XRD, DLS, TGA, and FT-IR analysis. Additionally, the 2,2-diphenyl-1-picrylhydrazyl technique and the well diffusion assay were used to examine their dose-dependent antioxidant and antibacterial activity. These biogenic LBOE-AuNPs showed 91% dye degradation efficiency during catalytic reduction activity on BTB dye, demonstrating their versatility as options for heterogeneous catalysis.
Inequitable Housing Practices and Youth Internalizing Symptoms: Mediation Via Perceptions of Neighborhood Cohesion

Disordered urban environments negatively impact mental health symptoms and disorders. While many aspects of the built environment have been studied, one influence may come from inequitable, discriminatory housing practices such as redlining, blockbusting, and gentrification. The patterns of disinvestment and reinvestment that follow may be an underlying mechanism predicting poor mental health. In this study, we examine pathways between such practices and internalizing symptoms (i.e., anxiety and depression) among a sample of African American youth in Baltimore, Maryland, considering moderation and mediation pathways including neighborhood social cohesion and sex. In our direct models, the inequitable housing practices were not significant predictors of social cohesion. In our sex moderation model, however, we find negative influences on social cohesion: for girls from gentrification, and for boys from blockbusting. Our moderated mediation model shows that girls in gentrifying neighborhoods who experience lower social cohesion have higher levels of internalizing symptoms. Likewise for boys, living in a formerly blockbusted neighborhood generates poorer social cohesion, which in turn drives higher rates of internalizing symptoms. A key implication of this work is that, in addition to standard measures of the contemporary built environment, considering other invisible patterns related to discriminatory and inequitable housing practices is important in understanding the types of neighborhoods where anxiety and depression are more prevalent. And while some recent work has discussed the importance of considering phenomena like redlining in considering long-term trajectories of neighborhoods, other patterns such as blockbusting and gentrification may be equally important.
Highly Thermal Conductive and Electrically Insulating Epoxy Composites Based on Zinc-Oxide-Coated Silver Nanowires

Nano-ZnO particles were deposited on the surface of silver nanowires (AgNWs) by the precipitation method, and the obtained AgNW@ZnO filler with core-shell structure was added to epoxy resin to prepare AgNW@ZnO/EP thermally conductive composites. The ZnO coating on the surface of AgNWs effectively improves the thermal conductivity of the composites. When 8 wt% AgNW@ZnO filler was added to the epoxy resin, the thermal conductivity of the AgNW@ZnO/EP composite increased to 0.77 W/(m·K). The enhancement of the thermal conductivity is attributed to the fact that ZnO effectively improves the interface bonding between AgNWs and the epoxy matrix, thus strengthening the contact between AgNWs. In addition, the electrical insulation of the AgNW@ZnO/EP composites was improved upon the introduction of the ZnO coating over AgNWs. For the filler content of 8 wt%, the volume resistivity of the AgNW@ZnO/EP composites was found to be higher than 1013 Ω·cm. AgNW@ZnO/EP composites have also exhibited low dielectric constant and good thermal stability.
Simultaneous sodium profile estimation and LGS WFS pixel processing optimization using Shack-Hartmann subaperture images

Pixel processing for laser guide star (LGS) Shack-Hartman wavefront sensor (WFS) is often based on center of gravity with thresholding (tCoG) algorithm, which yields close to linear response but with zero point corrupted by the shape of the source (sodium profile). The spot truncation due to the limited field of view of the WFS sub-apertures, as well as non-common path aberration (NCPA) further complicate the problem. Natural guide star (NGS) based truth wavefront sensors (TWFS) are therefore often used to correct the resulting aberrations, and multiple such TWFS are required to control anisoplanatism effects when there are multiple LGS. In this paper, we demonstrate a novel algorithm that reconstructs the sodium profile from time averaged subaperture images of one or multiple LGS WFS using a system imaging model which can then be used to improve the pixel processing by correcting the tCoG reference vector. It forgoes the need for using any NGS based TWFS for sodium profile induced aberrations and a single TWFS would then be sufficient to monitor optics effects. The reconstructed sodium profile can also be used to build constrained matched filters, a novel pixel processing algorithm alternative to tCoG that requires accurate knowledge of the subaperture reference images and their derivatives and has yet to be demonstrated on sky. Consequently, this new sodium profile reconstruction algorithm eliminates the need for dithering LGS spots on sky, which greatly simplifies the implementation of matched filtering, and also provides better performance. All the pixel processing optimizations can be done with a modern CPU at around 0.1 Hz update rate as a background process for the real time controller. The simulations we have done are for center launch LGS, but we are confident the profile estimation algorithm should work equally well if not better for side launch LGS even when there is truncation.
Mapping Local Climate Zones in the Urban Environment: The Optimal Combination of Data Source and Classifier

The novel concept of local climate zones (LCZs) provides a consistent classification framework for studies of the urban thermal environment. However, the development of urban climate science is severely hampered by the lack of high-resolution data to map LCZs. Using Gaofen-6 and Sentinel-1/2 as data sources, this study designed four schemes using convolutional neural network (CNN) and random forest (RF) classifiers, respectively, to demonstrate the potential of high-resolution images in LCZ mapping and evaluate the optimal combination of different data sources and classifiers. The results showed that the combination of GF-6 and CNN (S3) was considered the best LCZ classification scheme for urban areas, with OA and kappa coefficients of 85.9% and 0.842, respectively. The accuracy of urban building categories is above 80%, and the F1 score for each category is the highest, except for LCZ1 and LCZ5, where there is a small amount of confusion. The Sentinel-1/2-based RF classifier (S2) was second only to S3 and superior to the combination of GF-6 and random forest (S1), with OA and kappa coefficients of 64.4% and 0.612, respectively. The Sentinel-1/2 and CNN (S4) combination has the worst classification result, with an OA of only 39.9%. The LCZ classification map based on S3 shows that the urban building categories in Xi’an are mainly distributed within the second ring, while heavy industrial buildings have started to appear in the third ring. The urban periphery is mainly vegetated and bare land. In conclusion, CNN has the best application effect in the LCZ mapping task of high-resolution remote sensing images. In contrast, the random forest algorithm has better robustness in the band-abundant Sentinel data.
Spectral Evolution of Hercules X-1 over Main High State from RXTE/PCA Observations

We test different X-ray spectrum models to find the one that best represents the observed Rossi X-ray Timing Explore/Proportional Counter Array (RXTE /PCA) spectra of Her X-1 during Main High state (MH). We then apply this model to MH observations taken over the lifetime of RXTE. From the results, we obtain patterns in the spectral parameters vs. 35-day phase during MH. The precessing-disc occultation model explains the 35-day cycle by changes in observer view of the emission regions by the accretion disc 35-day precession. Qualitatively, we find that this model can describe the main spectral changes. However, several spectral parameters show detailed changes that the models have not addressed yet. These changes will likely require modifica-tions to the basic precessing-disc model for the 35-day cycle.