Miracle-dz/UniFAR-FTUs huggingface dataset:
FESDIA (v1.0): exploring temporal variations of sediment biogeochemistry under the influence of flood events using numerical modelling

Abstract. Episodic events of flood deposit in coastal environments are characterized by deposition of large quantities of sediment containing reactive organic matter within short periods of time. While steady-state modelling is common in sediment biogeochemical modelling, the inclusion of these events in current early diagenesis models has yet to be demonstrated. We adapted an existing model of early diagenetic processes to include the ability to mimic an immediate organic carbon deposition. The new model version (FESDIA) written in Fortran and R programming language was able to reproduce the basic trends from field sediment porewater data affected by the November 2008 flood event in the Rhône River prodelta. Simulation experiments on two end-member scenarios of sediment characteristics dictated by field observation (1–high thickness deposit, with low TOC (total organic carbon) and 2–low thickness, with high TOC), reveal contrasting evolutions of post-depositional profiles. A first-order approximation of the differences between subsequent profiles was used to characterize the timing of recovery (i.e. relaxation time) from this alteration. Our results indicate a longer relaxation time of approximately 4 months for SO42- and 5 months for DIC (dissolved inorganic carbon) in the first scenario, and less than 3 months for the second scenario which agreed with timescale observed in the field. A sensitivity analysis across a spectrum of these end-member cases for the organic carbon content (described as the enrichment factor α) and for sediment thickness indicates that the relaxation time for oxygen, sulfate, and DIC decreases with increasing organic enrichment for a sediment deposition that is less than 5 cm. However, for larger deposits (>14 cm), the relaxation time for oxygen, sulfate, and DIC increases with α. This can be related to the depth-dependent availability of oxidant and the diffusion of species. This study emphasizes the significance of these sediment characteristics in determining the sediment's short-term response in the presence of an episodic event. Furthermore, the model described here provides a useful tool to better understand the magnitude and dynamics of flooding event on biogeochemical reactions on the seafloor.
Focusing range image in VCO based FMCW radar

This paper presents a simple method for focusing images in VCO based cheap FMCW radar. Image defocusing is caused by non-linear distortions in the voltage controlled oscillator (VCO, very often YIG type). To obtain good quality FMCW radar images, a linear frequency modulated (LMF) signal is required. Even small changes in voltage-frequency VCO characteristics cause range defocusing, and therefore decrease of radar sensitivity and resolution. The method, derived from the polynomial model of non-linear LFM signal phase, is based on a generalized chirp transform of the video (intermediate frequency IF) signal obtained by mixing the transmitted LFM signal with the received (delayed) signal. To avoid complicated laboratory equipment (such as optical delay lines) the whole procedure is performed on live radar signals, using a maximum contrast approach.
A Concurrent Language for Re(cid:12)nement

We present a combination of the well-established formal speci(cid:12)cation languages Z and CSP; our objective is to provide support for the speci(cid:12)cation of both data and behaviour aspects of concurrent systems, and a development technique. The resulting language, Circus , distinguishes itself in that it is aimed at the calculational re(cid:12)nement of speci(cid:12)cations to programs written in a language similar to occam and Handel-C . In this paper, we present Circus , the rationale for its design, and a case study in its use.
Experimental Validation of Change of Volume in Pneumatic Artificial Muscle during Excitation

Abstract The majority of pneumatic artificial muscles (PAMs) models for calculating generated force with virtual work are good approximations. These models usually do nottake into account the edge deformations of the muscle orthe elastic deformations of the muscle bladder as a function of different internal pressure of the muscle, but only the contraction of the muscle. This paper presents the method that enables us to accurately measure the change in pneumatic muscle volume. Experimental results are compared with the standard Chou model. Also, further improvement of the PAM model is suggested. Key words: pneumatic artificial muscle, machine vision, volume calculation, camera calibration. 1. INTRODUCTION PAM actuator is a mechanical actuator that contracts when air pressure is applied. As the pressure in the bladder increases through the valve air supply the muscle contracts (Figure 1) [1]. Figure 1. PAM generating force and contraction with an increase of internal pressure p [1]
A Deep Architecture for Log-Linear Models

We present a novel perspective on deep learning architectures using a partial order structure, which is naturally incorporated into the information geometric formulation of the log-linear model. Our formulation provides a different perspective of deep learning by realizing the bias and weights as different layers on our partial order structure. This formulation of the neural network does not require any gradients and can efﬁciently estimate the parameters using the EM algorithm
How Do the Financial Markets Respond to Emerging Economies’ Asset Purchase Program? Evidence from the COVID-19 Crisis

This study examines the impacts of unconventional monetary policy on the exchange rate, stock market, and bond market during the COVID-19 economic crisis in an emerging economy. It focuses particularly on the asset purchase program conducted by the Central Bank of India. The Central Bank announced an asset purchase program four times during the pandemic. By applying the EGARCH methodology, this study finds that: (1) the asset purchase program effectively reduced the yield rate in the bond market and its volatility; (2) the first two announcements did not exert any impact on the financial market, but the third and fourth announcements helped to compress the yield and its volatility; (3) the program helped to restrain the exchange rate depreciation and volatility in the foreign exchange market; and (4) the impact of the announcements on stock returns, however, was weak.
Sniper GMMs: Structured Gaussian mixtures poison ML on large n small p data with high efﬁcacy

We propose a method for structured learning of Gaussian mixtures with low KL-divergence from target mixture models that in turn model the raw data. We show that samples from these structured distributions are highly effective and evasive in poisoning training datasets of popular machine learning training pipelines such as neural networks, XGBoost and random forests. Such attacks are especially destructive given the current uptrends towards distributed machine learning with several untrusted client devices that provide their data to servers and cloud service providers for privacy preserving distributed machine learning. In current day and age of machine learning, Gaussian mixtures are perceived to be an older/classical technique in practice, although they are still actively studied from a theoretical perspective. Therefore it is quite interesting to see that they can be highly effective in performing data poisoning attacks on complex ML pipelines if learned with the right structural constraints.
Epistemic advantage on the margin: A Network Standpoint Epistemology

I use network models to simulate social learning situations in which the dominant group ignores or devalues testimony from the marginalized group. I find that the marginalized group ends up with several epistemic advantages due to testimonial ignoration and devaluation. The results provide one possible explanation for a key claim of standpoint epistemology, the inversion thesis, by casting it as a consequence of another key claim of the theory, the unidirectional failure of testimonial reciprocity. Moreover, the results complicate the understanding and application of previously discovered network epistemology effects, notably the Zollman effect (Zollman, 2007, 2010).
Polygalactolipids in Spinach Chloroplasts1

Two polygalactolipids, designated as components A and B, were isolated from spinach chloroplasts and were also obtained from glycolipid products synthesized with chloroplast enzymes using uridine diphosphate galactose as a galactose donor. These lipids were purified by column and thin layer chromatography. Chemical analysis of component A indicates that the lipid is trigalaotosyl diglyceride, whereas component B behaves like tetragalaOtosyl di- glyceride on a thin layer plate. The major fatty acid in trigalactosyl diglyceride was a. -linolenic acid. Relative amount (molar ratio) of galactolipids in spinach chloroplasts was monogalac- tosyl diglyceride :digalactosyl diglyceride :trigalactosyl diglyceride: (tetragalactosyl diglyceride) = 60:30:5:1.
SUAVE: An Open-Source Environment Enabling Unconventional Vehicle Designs through Higher Fidelity

SUAVE is a conceptual level aircraft design environment that incorporates multiple information sources to analyze unconventional configurations. This work incorporates higherfidelity tools to build upon previous efforts where SUAVE analyzed and optimized several types of aircraft using low-fidelity methods. This is done in an automated way that incorporates three external programs. The first is OpenVSP, which is used for geometry creation, area calculation, and surface meshing. The second is Gmsh, which uses these surface meshes to create volume meshes. The third is SU2, which is used to run Euler CFD simulations. Wetted areas from OpenVSP and lift from SU2 is used to enhance SUAVE’s aerodynamic analyses. We present results for a verification case with the Onera M6 wing, then present mission results with a conventional narrow-body airliner, a supersonic jet, and a blended wing body.
Sophie van Rijn

Studying Klinefelter syndrome (47,XXY), a genetically defined disorder characterized by the presence of an additional X chromosome, can reveal insights into genotype-phenotype associations. Increased vulnerability to psychiatric disorders characterised by difficulties in social interactions, such as schizophrenia and autism, has been reported for this population. The reported social difficulties in 47,XXY men may arise as a consequence of impairments in the processing of social and emotional information. The present study is the first investigation of social-emotional information processing in this Xchromosomal disorder. 32 Klinefelter men and 26 men from the general population, with the groups matched for age, educational level and I.Q. , participated in the study. Several tasks were included, reflecting aspects of social-emotional information processing on levels of perception, experience and expression: labeling of facial expressions of emotion, emotion-cognition interactions in decision making and emotion regulation, that refers to subjective experience and identification of emotional arousal as well as verbal expression of emotions. A discrepancy between cognitive appraisal of emotions and emotional arousal was observed in Klinefelter syndrome. Taken together, Klinefelter men seem less accurate in perception of socio-emotional cues such as angry facial expressions, they are less able to identify and verbalize their emotions, but experience increased levels of emotional arousal, in comparison to the general population. Besides describing the social-emotional phenotype of this Xchromosomal disorder, the present data may prove to be an important contribution to the development of more general models describing pathways to neuropsychiatric disorders characterized by social cognitive disturbances. 64 | Chapter 4
Optogenetic and chemogenetic manipulation of hippocampal circuitry

Epilepsy comprises a family of neurological disorders characterized by recurrent seizures, which can be highly debilitating. Up to 30% of patients with temporal lobe epilepsy, the most common form of the disorder in adults, arising in the hippocampus, cannot be effectively treated by current pharmaceuticals. Novel treatment strategies are highly needed, as well as increased understanding of the hippocampal components and signaling properties involved in the mechanisms of epileptogenesis and induction of seizures, to guide a rational search for such future treatments. In the present thesis, we have applied optogenetics to study these questions, a technology based on modified microbial membrane channels or pumps that are introduced into target neurons, which can thereafter be activated by light. This is a powerful means of achieving excitatory or inhibitory control over neurons in a target specific manner. In paper I, we have explored the use of inhibitory optogenetics to attenuate seizures (epileptiform bursts) in acute chemical models in vitro and in vivo. GABAergic inhibition was abolished creating a strong excitatory drive among principal neurons in mainly area CA3 of the hippocampus. Under these conditions, we showed that we could inhibit hypersynchronized bursts by activating the inhibitory chloride pump NpHR. Repeated neuronal discharges gradually creating a hyperexcitable state in the hippocampal circuitry and presenting with seizure-like afterdischarges, known as the kindling process, is traditionally induced by electrical stimulation. In paper II & III, we showed that similarly, afterdischarges could be generated by repeated optogenetic train stimulation in anaesthetized transgenic mice expressing the excitatory cation channel ChR2. Additionally, we corroborated the well known role of the dentate gyrus is this type of progressive seizure model. Finally, using the chemogenetic novel hyperpolarizing Gi-DREADD receptor, activated by CNO, we could show that inhibiting the dentate gyrus and CA3 contralateral to optogenetic stimulation effectively halted the afterdischarge progression. The work presented in this thesis reinforces the potential of optogenetic and chemogenetic techniques to explore the mechanistic underpinnings and new treatment options for seizures & epilepsy.
Improved Image Quality Using Joint Image Reconstruction and Non-Local Means Filtering for Multi-Spectral SPECT

Single photon emission computed tomography (SPECT) is one of the major imaging modalities in medical imaging, including quantitative imaging for the evaluation of efficacy and toxicity in radionuclide therapy. Choosing optimal SPECT image reconstruction strategy for radionuclides with wide energy spectrum affects resulting image quality due to energy-dependent attenuation information in forward projection models and energy-dependent scatter information. A post-reconstruction filtering is also important to suppress noise propagated during reconstruction process. Yttrium-90 (Y-90) is a commonly used radionuclide in targeted radionuclide therapy. Recently, bremsstrahlung in Y-90 has been successfully imaged for good quantification of radioactivity to predict therapy response more accurately. However, wide continuous energy spectrum of bremsstrahlung photons is challenging in Y-90 SPECT image reconstruction. Previously, forward projection models with narrow single-energy window were used for image reconstruction from a single acquisition energy window. We propose a new Y-90 SPECT joint image reconstruction method from multiple acquisitions windows, referred to as joint spectral reconstruction (JSR) using multi-energy window forward models. Our proposed method yielded significantly higher recovery coefficient and lower standard deviation than other methods that use a single acquisition window and single energy window for projection model with narrow and wide energy spectra. We also investigated parameter selection methods for non-local mean (NLM) filter with SPECT. Self-weight estimation is an important factor to influence denoising performance of NLM. Recently introduced local James-Stein type center pixel weight method (LJS) outperformed other existing self-weight estimation methods in determining the contribution of the self-weight to NLM. However, the LJS method may result in excessively large self-weight estimates since no upper bound for self-weights was assumed. It also used relatively large local area for estimating self-weights, which may lead to strong bias. We propose novel local minimax self-weight estimation methods with direct bounds (LMM-DB) and re-parametrization (LMM-RP) using Baranchik’s minimax estimator. Our proposed methods yielded better bias-variance trade-off, higher peak signal-to-noise (PSNR) ratio, and less visual artifacts than the classical NLM method and the original LJS method. Our proposed methods also provide a heuristic way of choosing global smoothing parameters of NLM to yield PSNR values that are close to the optimal values without knowing the true image.
Heel Ulcers: Investigating Injurious Tissue Load-Thresholds in Humans, Based on a Patient- Specific Computational Heel Model

Heel ulcer (HU) is the second most common type of ulcer, formed when the skin and fat that envelope the calcaneus are deformed for extended periods between the bone and a support, eventually causing structural damage to the tissues. No specific data exist regarding the in ‐ vivo mechanical stress and strain thresholds for the onset and progression of HUs within clinically ‐ relevant time periods (e.g., while anesthetized in the operation room, bed ‐ bound in nursing homes, etc.). We used an MRI heel scan of a 72 years ‐ old male with a clearly demonstrated deep tissue injury at the right heel, to develop a three ‐ dimensional finite element model of the heel which include the calcaneal bone, subcutaneous fat, insertion and distal region of the Achilles tendon, and the skin. Biomechanical properties of all tissues were adopted from the literature. A pre ‐ injury anatomy was simulated using healthy ‐ tissue mechanical attributes. Thresholds of the mechanical loads which led to the onset and progression of HU were accessed by back ‐ calculating the mechanical conditions in the wound, caused by the foot weight, as it is not expected to significantly change during the injury ‐ relevant time frame. Shear due to support inclination and foot weight were simulated by displacing the superior surface of the calcaneus downward and horizontally. Von ‐ Mises stress and Lagrangian strain injury thresholds were offered, along with compressive to tensile proportions of the total strain. The influence of shear stress, foot weight, and bed ‐ angle on the thresholds was analyzed. Strain energy density was examined as a predictor for ulcer formation.
Three-dimensional nonlinear imaging using a 3D MEMS enabled compact fibre endoscope

1 Centre for Micro-Photonics, Faculty of Engineering and Industrial Sciences (FEIS) Swinburne University of Technology, H38, John Street, PO Box 218, Hawthorn, VIC, 3122, Australia 2 WiOptix, Inc., 101 SE 2 nd Place, Downtown Technology Centre, Gainesville, FL 32601, America 3 Department of Electrical and Computer Engineering, PO Box 116200, University of Florida, Gainesville, FL 32611-6200, America Email: hkang@groupwise.swin. edu.au
A Quantitative Study Based On Direct Measurement On Embedded Processors Limiting Context Switches For Energy Saving

Priority based preemptive schedulers are preferred over non-preemptive schedulers due to their flexibility to accommodate real time tasks based on criticality. The overhead associated with a preemptive scheduler is high and with increased number of preemptions and the associated context switches, the execution pattern of tasks become highly unpredictable at run time. In this paper, an effort is made to provide an insight into the significance of controlling context switches during real time application development. The system under study consists of an ARM7 LPC2148 microcontroller, whose energy consumption measurement is carried out with the help of MBED NXP 1768 controller. A study is done by analytical verification and a software simulation using embedded C with Keil uVision IDE. The energy consumed by the processor with and without context switches is verified experimentally by direct measurement. The two factors considered for analysis are increased delay and the augmented energy dissipation during a context switch. It is seen that a substantial saving of time and energy is associated with every context switch.
Operationalizing equity in multipurpose water systems

Abstract. Participatory decision-making is a well-established approach to address the increasing pressure on water systems induced by growing multi-sectoral demands and increased competition among different water users. However, most existing approaches search for system-wise efficient solutions and do not quantify their distributional effect among the stakeholders. In this work, we investigate how to operationalize equity principles to design improved water systems operations that better balance efficiency and justice. More specifically, we explore the extent to which the inclusion of equity principles reshapes the space of efficient solutions. Numerical experiments are conducted on the Lake Como system, Italy, operated primarily for flood control and irrigation water supply while also providing recreation and river ecosystem services. Our results show how incorporating equity considerations into the design of water system operations enriches the solution space by generating more compromise solutions than those obtained using a traditional multi-objective optimization. Moreover, we find that including equity in the operating policy design can indirectly improve the performance of marginalized sectors, such as recreation and ecosystem, which are not explicitly considered by the current lake operation. Lastly, we illustrate how the aggregation of multi-sectoral interests into an equity index strongly shapes our results. Thus, eliciting the preference structure of stakeholders and policymakers becomes paramount for the identification of a fair balance across competing interests. This work bridges the gap between multi-objective optimization approaches and equity-informed decision-making for real-world water resources planning and management, providing an effective tool to promote efficient and equitable policies.
Systematic Morphological and Molecular Studies in Genus Lonicera L. (Caprifoliaceae)

Genus Lonicera has members that have opposite, narrowly elliptic to obovate leaves and yellow-white, red, or purple-red corollas together with capitate stigmas and undulated calyxes. According to Wendelbo (1965) in Flora Iranica, the 19 members of Lonicera are classified into two subgenera, i.e . , Lonicera and Chamaecerasus , and three sections, i.e . , Isika , Isoxylosteum, and Coeloxylosteum. The four studied species belong to subgenus Chamaecerasus and sections Isika and Coeloxylosteum . The taxonomy and phylogeny of this genus is highly complicated and controversial. The present study was done by the use of phenetic analyses of morphology together with Bayesian analyses of molecular data (ITS sequences) to illustrate the species relationships, taxonomic classification, and monophyly versus paraphyly of the species in genus Lonicera. We used seven Lonicera species for molecular studies, for which nrDNA-ITS sequences were newly obtained. Successive reweighting with rescaled consistency index was used to conduct the molecular examination, which showed close similarities among the results of maximum likelihood, maximum parsimony, and Bayesian methods based on the ITS dataset were observed. This study showed that in general, it is possible to differentiate the species via morphological features. Phylogenetic relationships within Lonicera were revealed, and ITS-based phylogenetic trees and morphological characters were in agreement.