Miracle-dz/UniFAR-FTUs huggingface dataset:
Exploring the Interplay of Intrinsic Fluctuation and Complexity in Intracellular Calcium Dynamics

The concentration of intracellular calcium ion (Ca$^{2+}$) exhibits complex oscillations, including bursting and chaos, as observed experimentally. These dynamics are influenced by inherent fluctuations within cells, which serve as crucial determinants in cellular decision-making processes and fate determination. In this study, we systematically explore the interplay between intrinsic fluctuation and the complexity of intracellular cytosolic Ca$^{2+}$ dynamics using complexity measures such as permutation entropy (PE) and statistical complexity (SC). Using the chemical Langevin equation, we simulate the stochastic dynamics of cytosolic Ca$^{2+}$. Our findings reveal that PE and SC effectively characterize the diverse, dynamic states of cytosolic Ca$^{2+}$ and illustrate their interactions with intrinsic fluctuation. PE analysis elucidates that the chaotic state is more sensitive to intrinsic fluctuation than the other periodic states. Furthermore, we identify distinct states of cytosolic Ca$^{2+}$ occupying specific locations within the theoretical bounds of the complexity-entropy causality plane. These locations indicate varying complexity and information content as intrinsic fluctuation varies. When adjusting the permutation order, the SC for the different states exhibits peaks in an intermediate range of intrinsic fluctuation values. Additionally, we identify scale-free or self-similar patterns in this intermediate range, which are further corroborated by multifractal detrended fluctuation analysis. These high-complexity states likely correspond to optimal Ca$^{2+}$ dynamics with biological significance, revealing rich and complex dynamics shaped by the interplay of intrinsic fluctuation and complexity. Our investigation enhances our understanding of how intrinsic fluctuation modulates the complexity of intracellular Ca$^{2+}$ dynamics that play crucial roles in biological cells.
HeadEvolver: Text to Head Avatars via Locally Learnable Mesh Deformation

We present HeadEvolver, a novel framework to generate stylized head avatars from text guidance. HeadEvolver uses locally learnable mesh deformation from a template head mesh, producing high-quality digital assets for detail-preserving editing and animation. To tackle the challenges of lacking fine-grained and semantic-aware local shape control in global deformation through Jacobians, we introduce a trainable parameter as a weighting factor for the Jacobian at each triangle to adaptively change local shapes while maintaining global correspondences and facial features. Moreover, to ensure the coherence of the resulting shape and appearance from different viewpoints, we use pretrained image diffusion models for differentiable rendering with regularization terms to refine the deformation under text guidance. Extensive experiments demonstrate that our method can generate diverse head avatars with an articulated mesh that can be edited seamlessly in 3D graphics software, facilitating downstream applications such as more efficient animation with inherited blend shapes and semantic consistency.
The Use of Magnetometry Techniques to Characterise the Size Distribution of Magnetic Nanoparticles

The Use of Magnetometry Techniques to Characterise the Size Distribution of Magnetic Nanoparticles by Jason Heeris Supervisors: Dr. R. Woodward and Dr. T. G. St Pierre T he use of SQuID magnetometry to characterise the particle size distribution of magnetic nanoparticles was investigated using a variety of techniques and compared to results from transmission electron microscopy (TEM) and small angle neutron scattering (SANS). In particular, temperature dependent magnetic viscosity measurements were compared with other magnetometry techniques, and variations on typical experimental parameters were explored in order to gain a better picture of the size distribution and the effectiveness of various measurement techniques. Magnetic viscosity experiments on a sample of magnetite nanoparticles using an initial field of 100Oe were found to give a moment-weighted energy barrier distribution consistent with a log-normal distribution of particle diameters with a mean of 5.9nm and a standard deviation of 1.6nm, compared to values obtained from TEM of 3.7nm and 0.9nm, and SANS values of 3.2nm and 0.6nm.
The Size-Linewidth Relation and Signatures of Feedback from Quiescent to Active Star Forming Regions in the LMC

To investigate the effects of stellar feedback on the gravitational state of giant molecular clouds (GMCs), we study $^{12}$CO and $^{13}$CO ALMA maps of nine GMCs distributed throughout the Large Magellanic Cloud (LMC), the nearest star-forming galaxy to our own. We perform noise and resolution matching on the sample, working at a common resolution of 3.5 arcseconds (0.85 pc at the LMC distance of 50 kpc), and use the \textit{SCIMES} clustering algorithm to identify discrete substructure, or"clumps. "We supplement these data with three tracers of recent star formation: $8\mu$m surface brightness, continuum-subtracted H$\alpha$ flux, and interstellar radiation field energy density inferred from dust emission. The $^{12}$CO clumps identified cover a range of 3.6 dex in luminosity-based mass and 2.4 dex in average $8\mu$m surface brightness, representative of the wide range of conditions of the interstellar medium in the LMC. Our observations suggest evidence for increased turbulence in these clouds. While the turbulent linewidths are correlated with clump surface density, in agreement with previous observations, we find even better correlation with the three star formation activity tracers considered, suggesting stellar energy injection plays a significant role in the dynamical state of the clumps. The excess linewidths we measure do not appear to result from opacity broadening. $^{12}$CO clumps are found to be typically less gravitationally bound than $^{13}$CO clumps, with some evidence of the kinetic-to-gravitational potential energy ratio increasing with star-formation tracers. Further multi-line analysis may better constrain the assumptions made in these calculations.
Life Cycle of Atmospheric Rivers: Identification and Climatological Characteristics

An atmospheric river (AR) event is a strong poleward moisture transport that is composed of a series of spatiotemporally connected instantaneous AR objects. A new object‐based tracking algorithm is developed in this study, which aims to identify an AR event and investigate its life cycle from origin to termination. The algorithm identifies duration, intensity, propagation speed and direction, and the traveled distance throughout the life cycle of the AR event. The tracking algorithm is applied to 6‐hourly column‐integrated water vapor flux from November to March during the period of 1979–2017, with a focus on the North Pacific. Most North Pacific AR events originate in the subtropics over the Northwest Pacific and terminate at higher latitudes over the Northeast Pacific including western North America. On average, long AR events that last more than 72 hrs travel 7 times longer in distance and have stronger intensity than short AR events that last less than 24 hrs. Finally, a new accumulated AR intensity index is developed, which summarizes the overall impact of AR events over a given domain during a certain period by incorporating number, lifetime, and intensities of AR events.
Adaptivity is not helpful for Pauli channel learning

This note shows that adaptive strategies do not offer additional advantages for learning and testing Pauli channels with entangled input. First, the tight query complexity of learning Pauli channels with entangled input is established for the general norm $l_p$. In particular, the complexities for the $l_{1}$, $l_2$ and $l_\infty$ norms are improved or matched compared to previous results using entanglement in the literature. We also settle the query complexity to test if Pauli channels are white noise sources across $l_p$. Additionally, we demonstrate that the query complexity of estimating the noise level of a Pauli channel, characterized by the entropy of its error distribution and the count of non-zero probabilities, is $\Theta(4^n/n)$. Further, $\Theta(4^n/n)$ queries are sufficient to estimate the diamond norm between two Pauli channels.
Confidence-Aware Safe and Stable Control of Control-Affine Systems

Designing control inputs that satisfy safety requirements is crucial in safety-critical nonlinear control, and this task becomes particularly challenging when full-state measurements are unavailable. In this work, we address the problem of synthesizing safe and stable control for control-affine systems via output feedback (using an observer) while reducing the estimation error of the observer. To achieve this, we adapt control Lyapunov function (CLF) and control barrier function (CBF) techniques to the output feedback setting. Building upon the existing CLF-CBF-QP (Quadratic Program) and CBF-QP frameworks, we formulate two confidence-aware optimization problems and establish the Lipschitz continuity of the obtained solutions. To validate our approach, we conduct simulation studies on two illustrative examples. The simulation studies indicate both improvements in the observer's estimation accuracy and the fulfillment of safety and control requirements.
Effect of Viscosity-Enhancing Admixtures on Formwork Pressure and Thixotropy of Self-Consolidating Concrete

An experimental program was undertaken to determine the influence of the type and concentration of viscosity-enhancing admixture (VEA) on formwork pressure that can be exerted by self-consolidating concrete (SCC). A liquid polysaccharide, powder polysaccharide, and a cellulose-based VEA were used in this study. Both naphthalene-and polycarboxylate-based high-range water-reducing admixtures (HRWRAs) were employed. Thixotropy of the concrete was evaluated and correlated to the initial lateral pressure and its variations in time. Test results show that the type, combination, and dosage rate of VEA-HRWRA have a marked effect on thixotropy and formwork pressure. SCC made with cellulose-based VEA and polycarboxylate-based HRWRA are shown to yield a greater degree of thixotropy compared to similar concrete prepared with polysaccharide-based VEA and naphthalene-based HRWRA. SCC made with cellulose-based VEA, however, exhibited a lower rate of increase in thixotropy with time. This is associated with the greater degree of fluidity retention when using polycarboxylate-based HRWRA. Irrespective of the VEA type and combination with HRWRA, results indicate that the incorporation of VEA at relatively low concentrations could result in lower formwork pressure compared to reference mixtures made without any VEA and those containing medium or high concentrations of VEA. SCC made with a low VEA concentration necessitated lower HRWRA demand to secure the targeted slump flow. This results in a sharper loss in fluidity, enabling the concrete to develop enough cohesiveness to resist some of the applied vertical stress. A good relationship was established between formwork pressure and thixotropy determined for SCC mixtures containing low concentrations of VEA with mixtures of greater degree of thixotropy exerting lower lateral pressure on the formwork. The increase of VEA concentration, however, necessitated a greater HRWRA dosage, thus leading to higher lateral pressure measured initially and over time, despite the increase in thixotropy.
To Label or Not to Label: Hybrid Active Learning for Neural Machine Translation

Active learning (AL) techniques reduce labeling costs for training neural machine translation (NMT) models by selecting smaller representative subsets from unlabeled data for annotation. Diversity sampling techniques select heterogeneous instances, while uncertainty sampling methods select instances with the highest model uncertainty. Both approaches have limitations - diversity methods may extract varied but trivial examples, while uncertainty sampling can yield repetitive, uninformative instances. To bridge this gap, we propose HUDS, a hybrid AL strategy for domain adaptation in NMT that combines uncertainty and diversity for sentence selection. HUDS computes uncertainty scores for unlabeled sentences and subsequently stratifies them. It then clusters sentence embeddings within each stratum using k-MEANS and computes diversity scores by distance to the centroid. A weighted hybrid score that combines uncertainty and diversity is then used to select the top instances for annotation in each AL iteration. Experiments on multi-domain German-English datasets demonstrate the better performance of HUDS over other strong AL baselines. We analyze the sentence selection with HUDS and show that it prioritizes diverse instances having high model uncertainty for annotation in early AL iterations.
Microstructures and Mechanical Properties of High‐Strength Fe‐Mn‐Al‐C Light‐Weight TRIPLEX Steels

High‐strength TRIPLEX light‐weight steels of the generic composition Fe‐xMn‐yAl‐zC contain 18 ‐ 28 % manganese, 9 ‐ 12 % aluminium, and 0.7 ‐ 1.2 % C (in mass %). The microstructure is composed of an austenitic γ‐Fe(Mn, Al, C) solid solution matrix possessing a fine dispersion of nano size κ‐carbides (Fe,Mn)3 AlC1‐x and α‐Fe(Al, Mn) ferrite of varying volume fractions. The calculated Gibbs free energy of the phase transformation γfcc → ∊hcp amounts to ΔGγ→∊ = 1757 J/mol and the stacking fault energy was determined to ΓSF = 110 mJ/m2. This indicates that the austenite is very stable and no strain induced ∊‐martensite will be formed. Mechanical twinning is almost inhibited during plastic deformation. The TRIPLEX steels exhibit low density of 6.5 to 7 g/cm3 and superior mechanical properties, such as high strength of 700 to 1100 MPa and total elongations up to 60 % and more. The specific energy absorption achieved at high strain rates of 103 s−1 is about 0.43 J/mm3. TEM investigations revealed clearly that homogeneous shear band formation accompanied by dislocation glide occurred in deformed tensile samples. The dominant deformation mechanism of these steels is shear band induced plasticity ‐SIP effect‐ sustained by the uniform arrangement of nano size κ‐carbides coherent to the austenitic matrix. The high flow stresses and tensile strengths are caused by effective solid solution hardening and superimposed dispersion strengthening.
Reservoir property estimation using only dual-sensor seismic data – a case study from the West of Shetlands, UKCS

Marine broadband towed streamer seismic analysis and case studies in recent years have revealed several benefits of extended seismic bandwidth for the reservoir geoscientist – both for structural and quantitative seismic interpretation. Since 2007, dual-sensor towed streamer seismic technology (Tenghamn et al., 2007) has provided industry-wide access to seismic data with a significantly broader range of low and high frequencies. Benefits on the interpretation side include improved vertical resolution, enhanced geological texture, cleaner event continuity and character, sharper fault plane truncations and improved seismic-to-well correlations. The key benefit for quantitative seismic interpretation (QI) is a significant reduction of the low frequency model requirement and this allows seismic inversion to be derived from the seismic data rather than from a model extrapolation of a priori information. In addition, the quality and prediction of the reservoir properties derived from seismic data, without well log information, has significantly improved – resulting in the potential de-risking of prospects and discoveries. This paper describes the data analysis of dual-sensor 3D seismic from the West of Shetlands area and specifically focuses on wavelet extraction and low frequency phase stability. The study explores the relevance of these aspects to the inversion and investigates the estimation of reservoir properties, including porosity prediction, without the direct use of well information. The match of results from seismic only inversion to ‘blind wells’ demonstrates the potential of dual-sensor pre-stack data to reliably estimate elastic and reservoir properties in an exploration setting. Estimating reliable absolute reservoir properties away from wells has been a continuous challenge for reservoir geoscientists. Where it can be achieved, the value of the information can be significant in de-risking an opportunity and/or better characterising a prospect. In addition, in appraisal, development and reservoir optimisation, any reliable elastic information extracted from seismic data can potentially assist in optimising a well location and its trajectory for maximum recovery.
The Development of a Gamebird Research Strategy: Unraveling The Development of a Gamebird Research Strategy: Unraveling the Importance of Arthropod Populations the Importance of Arthropod Populations

This paper describes work conducted in the United Kingdom (UK) on upland gamebirds, primarily gray partridge, that identified the importance of arthropod abundance in determining chick survival and in the overall population dynamics of this declining quarry species. Several sequential steps that were taken to quantify the importance of arthropods in determining levels of chick survival, ranging from laboratory studies with captive chicks, through field-based surveys to computer simulation are described. Next, various field-scale experiments to manipulate vegetation to increase arthropod densities are described. These included the management of cereal crop edges with reduced levels of pesticides.
Charlie, Charlie, Charlie on Industrial Control Systems: PLC Control Logic Attacks by Design, Not by Chance

—Programmable logic controllers (PLCs) in industrial control systems (ICS) run a control logic program to monitor and control critical infrastructures in real-time, such as nuclear plants and power grids. Attackers target PLC control logic remotely to sabotage or disrupt physical processes. Network intrusion detection systems (IDS) are increasingly used to detect malicious control logic. This paper demonstrates that standard IDS features in a protocol message header and payload are not resilient for detecting (control logic) binary programs, such as entropy, n-gram, and decompilation. It identifies and utilizes a PLC design feature, redundant address pins (RAP), unexplored in the literature, to bypass IDS for injecting a small piece of programmable malicious code (PMC) into a PLC’s control logic as an initial attack vector, allowing it to execute with every scan cycle. We propose three unique attack methods (GizmoSplit, Bu ff Warp, and EnigmaFlow) using PMC as a proof of concept that blends control logic with network tra ffi c via payload encoding, small-size payloads, or sparse memory addressing. The GizmoSplit attack divides the control logic into small gadgets and writes them in random memory locations in a PLC; PMC modifies the stack with the location of the gadgets to execute them as return-oriented programming. The Bu ff Warp attack employs a small-size bu ff er where the attacker writes malicious code periodically to bypass stateful inspection at the payload level; PMC, in turn, keeps moving the bu ff er content to consecutive memory locations to execute. The EnigmaFlow attack encodes control logic and sends it to a PLC’s typically unused memory region, which PMC decodes and executes. The evaluation results indicate that these attacks are stealthy and can subvert IDS utilizing standard message header and payload features. This work points to a research gap in intrusion detection that caters to control logic attacks exploiting PLC design features
Agronomic Suitability for Oil Palm Growing in Uganda

The ever-increasing demand for vegetable oils with its products in Uganda, calls for new areas to be put under oil palm cultivation. A study was conducted to investigate the agronomic suitability of oil palm cultivation in six areas located within a 30 km radius off-shore, on the island and more than 30 km radius off-shore on the mainland. The experiment was superimposed on 45 × 45 m plots in oil palm adaptive trial plantations established in 2008 in Bugiri, Mayuge, Buvuma, Mukono, Kibaale and Masaka districts. The experiment was laid out in a randomized complete block design with three replications. Data on number of oil palm bunches, bunch weight and yield was collected while climatic data (rainfall, temperature, relative humidity and radiation) was acquired from meteorological stations near the experimental locations. Rainfall data analyzed and dry season duration suggested that Mayuge, Masaka, Mukono, Buvuma and Kibaale were moderately favorable for oil palm growing, while temperature and radiation data indicated that all study locations were suitable for oil palm growing. Furthermore, based on relative humidity, Buvuma, Mayuge and Bugiri were suitable for oil palm cultivation but Kibaale, Masaka and Mukono were moderately suitable. Oil palm yield varied significantly (P < 0.05) across locations. The yield was much greater in Mukono (17.7 t/ha/yr) followed by Buvuma (13.8 t/ha/yr) and Kibaale (12.9 t/ha/yr) then Mayuge (10.7 t/ha/yr), Bugiri (10.2 t/ha/yr), and Masaka (10.3 t/ha/yr). The significantly high yield of oil palm observed in Mukono was attributed to the high rainfall received in this location. Based on research findings, Mukono, Masaka, Bugiri, Buvuma, Kibaale and areas within the 30 km radius of Lake Victoria are agronomically suitable for oil palm cultivation.
A Path Analysis to Understanding the Epidemiology of Murine Typhus in South Texas

: This study aims to investigate statistically if there is a causality for the murine typhus endemic disease related to precipitation, temperature and the natural cycle of flea development in South Texas. Path analysis was used to determine the mediating and moderating variables that cause murine typhus disease. Three path diagram models were tested. Model 3 shows a clearer path on how the Rickettsia fleas were transmitted to the patients or subject, where rate of flea development is a mediating variable between sources of transmission and disease contraction, whereas precipitation moderates the source of transmission on its effect on rate of flea development with fleas in the environment and temperature average as covariates. The results of the path analysis support this hypothesis. Graphical research indicates that the number of murine typhus cases reaches a maximum during the month of May, when the temperature is between 65-80°F with about 70% humidity for flea development and the precipitation increases the probability that bacteria, fleas and hosts get into contact with humans. The results of this research suggest that the Laredo population should be made aware that the presence of rickettsia-infected Xenopsyllia cheopis and Ctenocephalides felis , the development of environmental conditions that increase the possibility of contact of wild and domestic animals with human beings can also increase the possibilities of the manifestation of the disease.