Miracle-dz/UniFAR-FTUs huggingface dataset:
Determinants of Viscoelasticity and Flow Activation Energy in Biomolecular Condensates

The form and function of biomolecular condensates, which are phase-separated intracellular granules of proteins and RNAs, are regulated by their material and dynamical properties. Emerging reports suggest that biomolecular condensates are viscoelastic network fluids, and the primary sequence and structure of the constituent biopolymers govern their bulk fluid phase properties. Here, we employ a multi-parametric approach to dissect the molecular determinants of condensate viscoelasticity by studying a series of condensates formed by engineered multivalent arginine-rich polypeptides and single-stranded DNA. By measuring the terminal relaxation time of the condensate network through optical tweezer-based microrheology and the activation energy of viscous flow through temperature-controlled video particle tracking, we show that condensate viscoelasticity is controlled by two distinct factors − sequence-encoded inter-chain interactions of associative polymers and entropic factors emerging from their intrinsic polymer properties such as the chain length. The biomolecular diffusion in the dense phase shows a strong dependence on the flow activation energy, indicating that the intra-condensate transport properties are primarily reaction-dominant. These results provide a glimpse of the multifaceted control of viscoelasticity and transport properties within biomolecular condensates. Flow activation energy measurement of single and multicomponent condensates by thermo-rheology provides a direct route to quantify inter-chain interactions in the dense phase and dissect the roles of chain entropy and valence in dictating the viscoelastic behavior of biomolecular condensates.
Researching Artificial Intelligence Applications in Evangelical and Pentecostal/Charismatic Churches: Purity, Bible, and Mission as Driving Forces

We explore in this article how Evangelical and Pentecostal/Charismatic Churches (EPCCs) view Artificial Intelligence (AI), and how they use it, either intentionally or indirectly. Considering first the digital habitus in which EPCCs are immersed, we have documented and analyzed three sample cases showing how EPCCs use advanced AI tools to improve the sanctification process for believers; how the Bible can be translated, distributed, and its reading can be fostered around the world, using machine intelligence; and how a spiritual revival among EPCCs can spread rapidly through AI-mediated algorithms. We discuss the implications of these developments and conclude finally with some ideas about how EPCCs should engage AI applications in the future.
Online Learning for Offroad Robots: Using Spatial Label Propagation to Learn Long-Range Traversability

We present a solution to the problem of long-range obstacle/path recognition in autonomous robots. The system uses sparse traversability information from a stereo module to train a classifier online. The trained classifier can then predict the traversability of the entire scene. A distance-normalized image pyramid makes it possible to efficiently train on each frame seen by the robot, using large windows that contain contextual information as well as shape, color, and texture. Traversability labels are initially obtained for each target using a stereo module, then propagated to other views of the same target using temporal and spatial concurrences, thus training the classifier to be viewinvariant. A ring buffer simulates short-term memory and ensures that the discriminative learning is balanced and consistent. This long-range obstacle detection system sees obstacles and paths at 30–40 meters, far beyond the maximum stereo range of 12 meters, and adapts very quickly to new environments. Experiments were run on the LAGR robot platform.
Fully Automated Annotation of Seismocardiogram for Noninvasive Vital Sign Measurements

This paper presents a fully automated procedure for acquiring and analyzing seismocardiographic (SCG) traces from an inertial measurement unit (IMU) placed over a subject’s sternum. An automated calibration procedure allows for straightforward adaption to different subjects. Calibration is performed once per subject, exploiting electrocardiogram (ECG) markers; relevant patterns and parameters are automatically extracted and used for successive SCG processing, which does not require concurrent ECG information any longer. Annotation of SCG traces is performed in two steps: in the first one, a suitably engineered signal is derived from SCG and used as coarse heartbeat detector; then, the annotation can be performed by comparing the prototype extracted at calibration time with segments of SCG data, near to the detected beats. The proposed methodology is validated by direct comparison with ECG, adopted as gold standard. In particular, three main metrics are taken into account: sensitivity (i.e., the percentage of correctly identified heartbeats, compared to ECG), precision (i.e., impact of false positives on truly detected beats), and <inline-formula> <tex-math notation="LaTeX">$ {R^{2}}$ </tex-math></inline-formula> (i.e., linearity between beat-to-beat measurements as computed by ECG and SCG). Results show satisfactory performance, more than adequate to continuous, long-term monitoring: overall, approximately 90% of heartbeats are correctly detected, on average, with minimal false positives (<inline-formula> <tex-math notation="LaTeX">${\approx 1}$ </tex-math></inline-formula>%). Linearity between ECG- and SCG-computed beat-to-beat intervals is extremely high (<inline-formula> <tex-math notation="LaTeX">$ {R^{2}>0.95}$ </tex-math></inline-formula>, on average), indicating good agreement between the two measurement methods. These results suggest that SCG can be used as a reliable, contactless measure of heart-related parameters.
Linear Exponential Quadratic Control for Mean Field Stochastic Systems

In this technical note, we consider linear exponential quadratic (LEQ) control for mean field stochastic differential equations (MFSDEs). The MFSDE includes the expectation value of state and control, and the objective functional is exponential of a quadratic functional in state, control, and their expectations. We obtain the explicit optimal solution as well as the optimal cost. The corresponding optimal solution is linear in state and its expectation, which is characterized by the Riccati differential equations (RDEs). The results are obtained by showing that after applying the completion of squares method, the remaining exponentiated stochastic integral and additional RDE terms can be eliminated together by taking expectation since they constitute the associated Radon–Nikodym derivative. As an extension of the problem, the LEQ zero-sum differential game is considered, for which we obtain the explicit optimal solution (saddle-point equilibrium) as well as the optimal cost.
Advances in understanding of dendritic cell in the pathogenesis of acute kidney injury

Acute kidney injury (AKI) is characterized by a rapid decline in renal function and is associated with a high morbidity and mortality rate. At present, the underlying mechanisms of AKI remain incompletely understood. Immune disorder is a prominent feature of AKI, and dendritic cells (DCs) play a pivotal role in orchestrating both innate and adaptive immune responses, including the induction of protective proinflammatory and tolerogenic immune reactions. Emerging evidence suggests that DCs play a critical role in the initiation and development of AKI. This paper aimed to conduct a comprehensive review and analysis of the role of DCs in the progression of AKI and elucidate the underlying molecular mechanism. The ultimate objective was to offer valuable insights and guidance for the treatment of AKI.
Terrorist violence and the fuzzy frontier: national and supranational identities in Britain

We explore the effect of terrorism on individuals’ perceptions about national identity in the context of Great Britain, where national and supranational identities overlap. We find that exposure to terrorist attacks strengthens identification with Britain but has no effect on identification with its constituent nations. The estimated effects last for about 45 days, but subside over time as the threat fades away. We also find that exposure to terrorism leads to more positive attitudes toward the European Union, providing further support for the emergence of a supranational-unity effect. Overall, our results differ from numerous previous studies on how violence reinforces “hardline beliefs,” exacerbating nativism and “narrow” forms of solidarity (JEL D70; F50; Z10).
Simulating Vegetation Migration in Response to Climate Change in a Dynamic Vegetation-climate Model

A central issue in climate change research is to identify what species will be most affected by variations in temperature, precipitation or CO2 and via which underlying mechanisms. Dynamic global vegetation models (DGVMs) have been used to address questions of habitat shifts, extinctions and changes in carbon and nutrient cycling. However, DGVMs have been criticized for assuming full migration and using the most generic of plant functional types (PFTs) to describe vegetation cover. My doctoral research addresses both of these concerns. In the first study, I added two new tropical PFTs to an existing regional model (LPJ-GUESS) to improve vegetation representation in Central America. Although there was an improvement in the representation of some biomes such as the pine-oak forests, LPJ-GUESS was still unable to capture the distribution of arid ecosystems. The model representations of fire, soil, and processes unique to desert vegetation are discussed as possible explanations. The remaining three chapters deal with the assumption of full migration, where plants can arrive at any location regardless of distance or physical barriers. Using LPJ-GUESS, I imposed migration limitations by using fattailed seed dispersal kernels. I used three temperate tree species with different life history strategies to test the new dispersal functionality. Simulated migration rates for Acer rubrum (141 m year -1 ) and Pinus rigida (76 m year -1 ) correspond well to pollen and genetic reconstructed iii rates. However, migration rates for Tsuga canadensis (85 m year -1 ) were considerably slower than historical rates. A sensitivity analysis showed that maturation age is the most important parameter for determining rates of spread, but it is the dispersal kernel which determines if there is any long distance dispersal or not. The final study demonstrates how northerly refugia populations could have impacted landscape recolonization following the retreat of the last glacier. Using three species with known refugia (Acer rubrum, Fagus grandifolia, Picea glauca), colonization rates were faster with a northerly refugia population present. The number of refugia locations also had a positive effect on landscape recolonization rates, which was most pronounced when populations were separated. The results from this thesis illustrate the improvements made in vegetation-climate models, giving us increasing confidence in the quality of future climate change predictions.
Electroweak-boson measurements from small to large collision systems with ALICE at the LHC

Electroweak bosons, W ± and Z 0 , are massive weakly-interacting particles insensitive to the strong interaction. Therefore, they are unique probes in pp and heavy-ion collisions and provide a medium-blind probe of the initial state of the heavy-ion collision. In the ALICE experiment, the productions of W ± and Z 0 are studied by exploiting theirleptonic decay channels in a wide rapidity region. In this contribution, the differential cross sections for W ± and Z 0 in pp collisions at √ 𝑠 = 13 , p–Pb collisions at √ 𝑠 NN = 8.16 and Pb–Pb collisions at √ 𝑠 NN = 5.02 are reported. The charged particle multiplicity dependence of W bosons and the associated hadrons production in pp collisions at √ 𝑠 = 13 is also shown.
Predicting pharmacodynamic effects through early drug discovery with artificial intelligence-physiologically based pharmacokinetic (AI-PBPK) modelling

A mechanism-based pharmacokinetic/pharmacodynamic (PK/PD) model links the concentration-time profile of a drug with its therapeutic effects based on the underlying biological or physiological processes. Clinical endpoints play a pivotal role in drug development. Despite the substantial time and effort invested in screening drugs for favourable pharmacokinetic (PK) properties, they may not consistently yield optimal clinical outcomes. Furthermore, in the virtual compound screening phase, researchers cannot observe clinical outcomes in humans directly. These uncertainties prolong the process of drug development. As incorporation of Artificial Intelligence (AI) into the physiologically based pharmacokinetic/pharmacodynamic (PBPK) model can assist in forecasting pharmacodynamic (PD) effects within the human body, we introduce a methodology for utilizing the AI-PBPK platform to predict the PK and PD outcomes of target compounds in the early drug discovery stage. In this integrated platform, machine learning is used to predict the parameters for the model, and the mechanism-based PD model is used to predict the PD outcome through the PK results. This platform enables researchers to align the PK profile of a drug with desired PD effects at the early drug discovery stage. Case studies are presented to assess and compare five potassium-competitive acid blocker (P-CAB) compounds, after calibration and verification using vonoprazan and revaprazan.
Enhanced Electrocatalytic Oxygen Reduction Reaction of TiO2 Nanotubes by Combining Surface Oxygen Vacancy Engineering and Zr Doping

This work examines the cooperative effect between Zr doping and oxygen vacancy engineering in anodized TiO2 nanotubes (TNTs) for enhanced oxygen reduction reactions (ORRs). Zr dopant and annealing conditions significantly affected the electrocatalytic characteristics of grown TNTs. Zr doping results in Zr4+ substituted for Ti4+ species, which indirectly creates oxygen vacancy donors that enhance charge transfer kinetics and reduce carrier recombination in TNT bulk. Moreover, oxygen vacancies promote the creation of unsaturated Ti3+(Zr3+) sites at the surface, which also boosts the ORR interfacial process. Annealing at reductive atmospheres (e.g., H2, vacuum) resulted in a larger increase in oxygen vacancies, which greatly enhanced the ORR activity. In comparison to bare TNTs, Zr doping and vacuum treatment (Zr:TNT–Vac) significantly improved the conductivity and activity of ORRs in alkaline media. The finding also provides selective hydrogen peroxide production by the electrochemical reduction of oxygen.
Relationship between Cooling Methods and Energy Consumption for the Development of Low-Carbon Collective Housing in Indonesia

Indonesian urban population increase has led to increased energy demands and housing inventory shortages. The Ministry of Public Works and Housing (PUPR) supplies collective housing for low-income communities (MBR). The development of low-carbon collective housing has been thought to suppress the abrupt increase in household-sector energy demand and lead to mitigated greenhouse gas (GHG) emissions. In tropical climates, it is essential to reduce the dependence on air conditioners (AC) to suppress energy consumption. Therefore, to investigate the relationship between cooling methods and energy consumption, this study surveyed the energy consumption per household and classified the existing cooling patterns of ACs, fans, and window openings in collective housing with different income groups in Indonesia. The results confirmed that the use of AC increases household energy consumption. Meanwhile, the implementation of natural ventilation (NV) showed significantly lower energy consumption with a high thermal satisfaction of more than 80% during the day and 90% at night; thus, both energy consumption reduction and indoor thermal comfort improvement could be achieved through these methods. The findings of this study serve as a starting point for verifying the energy saving effects of air conditioning habits with the consideration of socio-demographic changes for the purpose of decarbonizing collective housing, including future predictions and energy simulations.
Study on Effect of Particle Size Distribution on Water-Retention Capacity of Coral Sand from Macro and Micro Perspective

The reclamation coral sand (CS) layer is the survival environment for island reef vegetation in the South China Sea. The root system within the CS bed draws water necessary for vegetation growth, implying that the water-retention capacity of CS plays a pivotal role in determining vegetation viability. Particle size distribution (PSD) significantly influences the water-retention capacity of geomaterials. This study examines the impact of PSD on the water-retention capacity of CS from both macro (soil–water characteristic curve, SWCC) and micro (pore water distribution) perspectives using the pressure plate test and nuclear magnetic resonance technique, and an F&X model was used to analyze the SWCC of CS. The findings indicated that the F&X model aptly describes the SWCC of CS with different PSDs. Both the air entry value and residual water content rise with an increased content of fine grains (d < 0.25 mm), suggesting that the presence of fine grains augments the water-retention capacity of CS. It is considered that a size range of d = 0.075–0.25 mm predominantly impacts the water-retention capacity of CS. The PSD primarily influences the water-retention capacity by affecting the pore size distribution of CS. The volume of small pores swells with the surge of fine-grain content, while the maximum pore size contracts with increasing fine-grain content. Limited pore connectivity in CS means macropores can retain water even under high suction, bolstering the water-retention capacity of CS. These findings offer theoretical guidance for selecting gradation parameters for the planting layer on island reefs.
Initialising landslide-generated tsunamis for probabilistic tsunami hazard assessment in Cook Strait

The Cook Strait Canyon is a submarine canyon which lies within 10 km of Wellington, the capital city of New Zealand. The canyon flanks are scarred with the evidence of past landslides that may have caused large local tsunamis. City planning and civil defence management require information on the magnitude and frequency of these tsunamis to adequately plan for them. Submarine-landslide-generated tsunamis are by nature local features. While they may be catastrophic in the near field, they are generally far smaller scales than co-seismic tsunamis and their energy does not travel very far. Including them within a comprehensive tsunami hazard assessment requires accounting for a large number of potential landslide sources. Unless we only use simple rules of thumb to approximate tsunami height, this requires considerable computing power. This article describes a technique for expanding two-dimensional vertical-slice tsunami generation by landslide modelling into a two-dimensional horizontal surface which can be used for tsunami propagation and inundation modelling. As such, it spans the gap between full three-dimensional modelling of the landslide and simple initialisation.
Sleep and Caregiver Burden Among Caregivers of Persons Living With Dementia: A Scoping Review

Abstract Background and Objectives Caregivers of persons with dementia report worse sleep when compared to the general population. The objective of this review was to synthesize evidence regarding the link between caregiver burden and dementia caregivers’ sleep. Research Design and Methods We conducted a scoping review using a systematic search for pertinent literature in PubMed, CINAHL, and Web of Science through March 2022. Keywords included content areas of dementia, caregiver burden, and sleep. Inclusion criteria were informal caregivers of persons living with dementia, a measured relationship between informal dementia caregiver sleep and subjective caregiver burden variables, and original research. Non-English studies were excluded. Extracted data were organized in tables, compared, and synthesized. Results The search yielded 540 nonduplicate articles screened by title and abstract; 118 full-text articles were reviewed; 24 were included. Most studies were cross-sectional, with variable sample sizes. Dementia caregivers had significantly poorer overall perceived sleep than noncaregivers across 4 studies that examined self-reported sleep measures. Eighteen studies investigated the association between caregiver burden and self-reported sleep quality, with 14 reporting a significant positive association between caregiver burden and self-reported sleep quality, and 4 finding null results. Only 2 of the 4 studies reporting the association between caregiver burden and objective sleep parameters (ie, actigraphy and polysomnography) reported a significant positive association for at least one sleep subdomain. Discussion and Implications Although subjective sleep quality is commonly affected by dementia caregiving burden, there is a lack of corresponding evidence on the relationship between burden and objective sleep metrics. Healthcare providers should consider the dementia caregiver burden’s impact on sleep and regularly assess caregivers’ sleep difficulties. Future studies should focus on consistently measuring caregiver burden and sleep to promote dementia caregiver health and well-being.
KERAGAMAN GENETIK BANTENG (Bos javanicus d’Alton) DARI BERBAGAI LEMBAGA KONSERVASI DAN TAMAN NASIONAL MERU BETIRI

Banteng (Bos javanicus d’Alton) dikonservasi serta didomestikasi sebagai sapi bali (Bos taurus Linnaeus) sejak 3.500 SM. Tujuan penelitian ini adalah memperoleh informasi hasil analisis morfometrik banteng dan keragaman genetik populasi banteng di dalam kawasan konservasi dan lembaga konservasi serta hubungan kekerabatan antara populasi banteng dengan sapi bali melalui jarak genetik antar populasi dan jarak genetik antar individu dengan metode multiple alignment sekuen dari program Clustal X 1.83 serta analisis filogenetik menggunakan metode neighbor-joining. Morfometrik banteng di Kebun Binatang Surabaya dan Kebun Binatang Ragunan telah mengalami perubahan secara fisik dan biologis, hal ini terjadi karena jarak genetik di dalam populasi sebesar 0,000. Di kawasan konservasi, morfometrik banteng paling besar dari Taman Nasional Baluran dilihat dari ukuran telapak kaki dan jarak kaki. Hasil multiple alignment 657 urutan basa fragmen D-loop DNA mitokondria, terdiri dari enam haplotipe yaitu banteng 3 macam haplotipe dan sapi bali 5 macam haplotipe, dengan demikian sapi bali memiliki keragaman genetik lebih tinggi. Jarak genetik antar haplotipe sangat kecil (0,000-0,009), sehingga hubungan kekerabatan antara banteng dan sapi bali sangat dekat. Dengan demikian untuk program pemuliaan, sapi bali dapat dilakukan perkawinan silang dengan banteng dari taman nasional.