Miracle-dz/UniFAR-FTUs huggingface dataset:
Constraints on dark energy from TDCOSMO & SLACS lenses

Problems with the cosmological constant model of dark energy motivate the investigation of alternative scenarios. I make the first measurement of the dark energy equation of state using the hierarchical strong lensing time delay likelihood provided by TDCOSMO. I find that the combination of seven TDCOSMO lenses and 33 SLACS lenses is only able to provide a weak constraint on the dark energy equation of state, w < −1.75 at 68 per cent confidence, which nevertheless implies the presence of a phantom dark energy component. When the strong lensing time delay data is combined with a collection of cosmic microwave background, baryon acoustic oscillation and Type Ia supernova data, I find that the equation of state is w = −1.025 ± 0.029.
Using Experience Classification for Training Non-Markovian Tasks

Unlike the standard Reinforcement Learning (RL) model, many real-world tasks are non-Markovian, whose rewards are predicated on state history rather than solely on the current state. Solving a non-Markovian task, frequently applied in practical applications such as autonomous driving, financial trading, and medical diagnosis, can be quite challenging. We propose a novel RL approach to achieve non-Markovian rewards expressed in temporal logic LTL$_f$ (Linear Temporal Logic over Finite Traces). To this end, an encoding of linear complexity from LTL$_f$ into MDPs (Markov Decision Processes) is introduced to take advantage of advanced RL algorithms. Then, a prioritized experience replay technique based on the automata structure (semantics equivalent to LTL$_f$ specification) is utilized to improve the training process. We empirically evaluate several benchmark problems augmented with non-Markovian tasks to demonstrate the feasibility and effectiveness of our approach.
Aging with GRACE: Lifelong Model Editing with Discrete Key-Value Adapters

Deployed models decay over time due to shifting inputs, changing user needs, or emergent knowledge gaps. When harmful behaviors are identiﬁed, targeted edits are required. However, current model editors, which adjust speciﬁc behaviors of pre-trained models, degrade model performance over multiple edits. We pro-pose GRACE, a Lifelong Model Editing method, which implements spot-ﬁxes on streaming errors of a deployed model, ensuring minimal impact on unrelated inputs. GRACE writes new mappings into a pre-trained model’s latent space, creating a discrete, local codebook of edits without altering model weights. This is the ﬁrst method enabling thousands of sequential edits using only streaming errors. Our experiments on T5, BERT, and GPT models show GRACE’s state-of-the-art performance in making and retaining edits, while generalizing to unseen inputs. Our code is available at github.com/thartvigsen/grace.
Enhancing anatomy education through cooperative learning: harnessing virtual reality for effective gross anatomy learning

ABSTRACT The advent of virtual reality (VR) in education offers unique possibilities for facilitating cooperative learning strategies, particularly in fields demanding intricate spatial understanding, such as gross anatomy. This study investigates the impact of integrating cooperative learning strategies within a VR-based gross anatomy curriculum, focusing on enhancing students’ anatomy knowledge and skills. We analyzed the performance of two cohorts of first-year nursing students across five semesters (2016–2020), where traditional learning methods were used in the first three semesters (2016–2018), and a VR-based cooperative learning approach was adopted in the last two semesters (2019–2020). Our findings suggest that the VR-based cooperative learning group achieved significantly higher scores in their gross anatomy laboratory courses compared to their counterparts learning through traditional methods. This research provides valuable insights into how the integration of VR technology and cooperative learning strategies can not only enhance learning outcomes but also improve the VR learning experience by reducing motion sickness. It accentuates the potential of VR-based cooperative learning as an impactful educational tool in anatomy education. Future research should further explore the optimal integration of VR and cooperative learning strategies in diverse course types and their potential to enhance educational outcomes and the learning experience.
Natural occurrence of entomopathogenic nematodes (Steinernema and Heterorhabditis) and Pristionchus nematodes in black truffle soils from Spain

Abstract The European truffle beetle Leiodes cinnamomeus is the most important pest in black truffle (Tuber melanosporum) plantations. Current control methods against it are inefficient, so entomopathogenic nematodes (EPNs) could play an important role in their population regulation due to their efficacy against many soil-dwelling insect pests. A survey of EPNs and Pristionchus nematodes was conducted in truffle soils of Spain, considering environmental and physical–chemical soil factors. A total of 164 soil samples were collected from forests, productive plantations and null-low productive plantations, representing three distinct black truffle-growing habitat types. EPNs were isolated from seven soil samples (4.3%); four nematodes were identified as Steinernema feltiae and three as Heterorhabditis bacteriophora. Both species were sampled in three types of soil texture (loam, sandy loam or sandy clay loam), characterized by alkaline pH (7.5 to 8.5) and high organic matter (2.1–11.04%). The presence of these EPNs was influenced by habitat type and organic matter content. Pristionchus nematodes were isolated from truffle soil, around truffle fruit bodies and under the elytra of L. cinnamomeus, with Pristionchus maupasi being the most commonly identified species. No significant associations were found between environmental and soil factors and the occurrence of Pristionchus nematodes. These nematodes were found in alkaline soils (pH 7.75 to 8.7), across all seven sampled soil textures, with variable organic matter content (0.73%–5.92%). The ecological trends and the presence of Pristionchus may affect the occurrence of EPNs and their prospective use as biological control agents against L. cinnamomeus in black truffle plantations.
A Survey on Bid Optimization in Real-Time Bidding Display Advertising

Real-Time Bidding (RTB) is one of the most important forms of online advertising, where an auction is hosted in real time to sell the individual ad impression. How to design an automated bidding strategy in response to the dynamic auction environment is crucial for improving user experience, protecting the interests of advertisers, and promoting the long-term development of the advertising platform. As an exciting topic in the real-world industry, it has attracted great research interest from several disciplines, most notably data science. There have been abundant studies on bidding strategy design which are based on the large volume of historical ad requests. Despite its popularity and significance, few works provide a summary for bid optimization. In this survey, we present the latest overview of the recent works to shed light on the optimization techniques where most of them are validated in practice. We first explore the optimization problem in different works, explaining how these different settings affect the bidding strategy designs. Then, some forms of bidding functions and specific optimization techniques are illustrated. Further, we specifically discuss a new trend about bidding in first-price auctions, which have gradually become popular in recent years. From this survey, both practitioners and researchers can gain insights of the challenges and future prospects of bid optimization in RTB.
Stroke Home Rehabilitation Approach Using Mobile Application Based on PostNet Machine Learning Model

Stroke is a significant cause of mortality and disability globally, with its occurrence in the human brain and motor function being linked to various parts of the human body. Stroke victims often experience disabilities or mobility problems in affected body parts, either on one or both sides of the body. Physiotherapy exercises are the primary treatment and medication for stroke patients, necessitating daily monitoring by a physiotherapist. However, this approach is expensive, and rehabilitation centers and physicians are scarce. Numerous research studies have been conducted to address this issue from various perspectives. This study proposes a Convolutional Neural Network (CNN) based pose net machine learning (ML) model for stroke home rehabilitation using pose detection and classification with a skeleton base model and human pose estimation drawing. We trained our ML model using different human pose images for this model. The tested accuracy of our CNN model is 100% for our exercise pose image test case. Later we build and mobile application for remote rehabilitation. Tested the application with ten different subjects, achieving a 98% for elbow extension, and in the case of elbow flexion and Normal position of balancing both sides, all the persons achieved a 100 % accuracy rate under a laboratory environment.
Effects of coenzyme Q10 in a propofol infusion syndrome model of rabbits

Abstract Background Coenzyme Q (CoQ) might be the main site of interaction with propofol on the mitochondrial respiratory chain in the propofol infusion syndrome (PRIS) because of the structural similarity between coenzyme Q10 (CoQ10) and propofol. Aim To investigate the effects of CoQ10 on survival and organ injury in a PRIS model in rabbits. Methods Sixteen male New Zealand white rabbits were divided into 4 groups: (1) propofol infusion group, (2) propofol infusion and CoQ10, 100 mg/kg was administered intravenously, (3) sevoflurane inhalation was administered, and (4) sevoflurane inhalation and CoQ10, 100 mg/kg intravenously, was administered. Arterial blood gas and biochemical analyses were repeated every 2 h and every 12 h, respectively. Animals that were alive on the 24th hour after anesthesia induction were euthanized. The organ damages were investigated under light and transmission electron microscopy (TEM). Results The propofol infusion group had the highest troponin T levels when compared with the other three groups at the 12th hour. The propofol + CoQ10 group had lower troponin T levels when compared with the propofol and sevoflurane groups (P < 0.05). Administration of CoQ10 decreased total liver injury scores and total organ injury scores both in the propofol and sevoflurane groups. The propofol and sevoflurane organ toxicities were attenuated with CoQ10 in liver, gallbladder, urinary bladder, and spleen. Conclusion The addition of CoQ10 to propofol and sevoflurane anesthesia prevented the propofol-associated increase in troponin T levels at the 12th hour of infusion and decreased anesthetic-induced total liver and organ injury scores.
Thermo-solutal Marangoni convective Darcy-Forchheimer bio-hybrid nanofluid flow over a permeable disk with activation energy: Analysis of interfacial nanolayer thickness

Abstract The Marangoni convective phenomena have a unique impact on industries and medical tools. These phenomena are more prominent in the presence of dual nanoparticles (NPs) over base fluids such as blood that are surrounded by a thin interfacial nanolayer, an important feature to control the physical and thermal properties of the NP. In this problem, we have analysed the thermo-solutal Marangoni convective Darcy-Forchheimer flow of nanomaterials with the impact of the interfacial nanolayer. The results of the system of an exponential heat source, non-linear radiation, joule heating, and activation energy are discussed. An appropriate transition is applied to rationalise the substantially paired and nonlinear governing equations and then processed by the Galerkin finite element method (G-FEM). The impression of different governing parameters on the governing systems in conjunction with entropy and Bejan number is demonstrated through graphical and tabular form. Graphs are drawn with an evaluation of general and hybrid nanofluids (HNFs) and different nanolayer thicknesses of NPs. Activation energy and chemical reaction parameters restrict the Sherwood number, and the same is observed for the Nusselt number with an increase in the Brinkman and Eckert numbers. The thickness of the interfacial nanolayer of the NPs restricts the entropy generation of the system, while the entropy is higher for the HNF than the nanofluid. An opposite feature was observed for the Bejan number.
Evaluation of cholinergic enzymes and selected biochemical parameters in the serum of patients with a diagnosis of acute subarachnoid hemorrhage

Abstract Background Spontaneous subarachnoid hemorrhage (SAH) is the most severe form of hemorrhagic stroke and accounts for 5–7% of all strokes. Several chemical enzymes and cytokines are thought to cause reactions that may affect the mortality and morbidity of SAH patients. This study aimed to examine the possible relationships between these parameters and the occurrence of SAH and the clinical–radiological parameters in patients with acute SAH. Methods This study evaluated 44 patients, including 20 with SAH and 24 controls. We obtained blood from the patients and control groups, which was stored in heparinized tubes and used in determining tumor necrosis factor alpha (TNF-α), brain-derived neurotrophic factor (BDNF), acetylcholinesterase (AChE), caspase-3, and butyrylcholinesterase (BChE) enzymes. Results TNF-α, BDNF, AChE, and BChE enzyme levels were not related to the Glasgow Coma scale (GCS) score in the patient group (p > 0.05), whereas higher enzyme levels of caspase-3 were associated with lower GCS scores (p < 0.05). The difference between the control and patient groups in terms of mean TNF-α levels was statistically significant (p < 0.01). The BDNF levels were statistically insignificant in the patient groups (p > 0.05). Caspase-3, AChE, and BChE levels were significantly different between the control and patient groups (p < 0.01). Conclusions Our results may be valuable for predicting the prognosis, diagnosis, and follow-up of patients with SAH. However, further studies are required to elucidate the relationship between the clinical and radiological results in patients with SAH and certain enzymes, cytokines, and growth factors.
Unprecedented spike flexibility revealed by BSL3 Cryo-ET of active SARS-CoV-2 virions

Understanding the molecular properties of SARS-CoV-2 is crucial to tackle future outbreaks. Current knowledge of the trimeric spike protein relies on truncated recombinant proteins and inactivated full-length forms, which may suffer from overstabilization. Here, we apply cryo-electron tomography (cryo-ET) at a Biosafety level 3 facility to study the virus structure in its native, active state. The virus particles show variable shapes with diffusible spikes, with the majority in typical prefusion conformations. Notably, we also identified unprecedented, atypical open-trimer prefusion states, revealing hidden flexibility. The sub-tomogram averaged structure suggests a loosely packed trimer. The observed dynamics uncover conserved cryptic regions that can be targeted for broadly effective vaccines. Structural analysis of active viruses will have implications on understanding overlooked fusion mechanism and vaccine, antibody/drug design. (124 words) One-Sentence Summary The BSL3 cryo-electron microscopy uncovered significant flexibility of the spike protein on active viruses, which will facilitate the design of broadly effective vaccines and drugs.
Differential kinematic coding in sensorimotor striatum across species-typical and learned behaviors reflects a difference in control

The sensorimotor arm of the basal ganglia is a major part of the mammalian motor control network, yet whether it is essential for generating natural behaviors or specialized for learning and controlling motor skills is unclear. We examine this by contrasting contributions of the sensorimotor striatum (rodent dorsolateral striatum, DLS) to spontaneously expressed species-typical behaviors versus those adapted for a task. In stark contrast to earlier work implicating DLS in the control of acquired skills, bilateral lesions had no discernable effects on the expression or detailed kinematics of species-typical behaviors, such as grooming, rearing, or walking. To probe the neural correlates underlying this dissociation, we compared DLS activity across the behavioral domains. While neural activity reflected the kinematics of both learned and species-typical behaviors, the coding schemes were very different. Taken together, we did not find evidence for the basal ganglia circuit being required for species-typical behaviors; rather, our results suggest that it monitors ongoing movement and learns to alter its output to shape skilled behaviors in adaptive and task-specific ways.
Growth retardation in a mouse model of Kabuki syndrome 2 bears mechanistic similarities to Kabuki syndrome 1

Growth retardation is a characteristic feature of both Kabuki syndrome 1 (KS1) and Kabuki syndrome 2 (KS2), Mendelian disorders of the epigenetic machinery with similar phenotypes but distinct genetic etiologies. We previously described skeletal growth retardation in a mouse model of KS1 and further established that a Kmt2d−/− chondrocyte model of KS1 exhibits precocious differentiation. Here we characterized growth retardation in a mouse model of KS2, Kdm6atm1d/+. We show that Kdm6atm1d/+ mice have decreased femur and tibia length compared to controls and exhibit abnormalities in cortical and trabecular bone structure. Kdm6atm1d/+ growth plates are also shorter, due to decreases in hypertrophic chondrocyte size and hypertrophic zone height. Given these disturbances in the growth plate, we generated Kdm6a−/− chondrogenic cell lines. Similar to our prior in vitro model of KS1, we found that Kdm6a−/− cells undergo premature, enhanced differentiation towards chondrocytes compared to Kdm6a+/+ controls. RNA-seq showed that Kdm6a−/− cells have a distinct transcriptomic profile that indicates dysregulation of cartilage development. Finally, we performed RNA-seq simultaneously on Kmt2d−/−, Kdm6a−/−, and control lines at Days 7 and 14 of differentiation. This revealed surprising resemblance in gene expression between Kmt2d−/− and Kdm6a−/− at both time points and indicates that the similarity in phenotype between KS1 and KS2 also exists at the transcriptional level.
Quantification of membrane fluidity in bacteria using TIR-FCS

Cell membrane fluidity is an important phenotypic feature that regulates the diffusion, function and folding of transmembrane and membrane-associated proteins. It is particularly interesting to study it in bacteria as variations in membrane fluidity are known to affect fundamental cellular processes such as respiration, transport and antibiotic resistance. As such key parameter, membrane fluidity is regulated to adapt to environmental variations and stresses like temperature fluctuations or osmotic shocks. Membrane fluidity has been however scarcely studied quantitatively in bacterial cells, mostly because of the lack of available tools. Here, we developed an assay based on total internal reflection fluorescence correlation spectroscopy (TIR-FCS) to directly measure membrane fluidity in live bacteria via the diffusivity of fluorescent membrane markers. We used this assay to quantify the fluidity of the cytoplasmic membrane of the Gram-positive model bacterium Bacillus subtilis in response to a cold shock, caused by a shift from 37°C to 20°C. In our experimental conditions, steady-state fluidity was recovered within 30 mins, and the steady-state fluidity at 20°C was about half of that at 37°C. Our minimally invasive assay opens up exciting perspectives and could be used to study a wide range of phenomena affecting the bacterial membrane, from disruption by antibiotics, antimicrobial peptides, or osmotic shocks. Significance Using fluorescence correlation spectroscopy (FCS) with total internal reflection fluorescence (TIRF) illumination, we measured the diffusion speed of fluorescent membrane markers as a readout for membrane fluidity of growing B. subtilis cells. Quantification of the effect of cold shock provided unique information about the dynamics of the plasma membrane of B. subtilis. The unprecedented capability of TIR-FCS to quantify membrane fluidity in living bacteria opens the door to a whole set of new studies that will shed light on the bacterial plasma membrane and its interactions with the environment.
Disrupting the interaction between AMBRA1 and DLC1 is a promising therapeutic strategy for neurodegeneration that prevents apoptosis while enhancing autophagy and mitophagy

Activating molecule in Beclin1-regulated autophagy (AMBRA1) has critical roles in autophagy, mitophagy, cell cycle regulation, neurogenesis and apoptosis. Dysregulation of these processes are hallmarks of various neurodegenerative diseases and therefore AMBRA1 represents a potential therapeutic target. The flexibility of its intrinsically disordered regions allows AMBRA1 to undergo conformational changes and thus perform its function as an adaptor protein for various different complexes. Understanding the relevance of these multiple protein-protein interactions will allow us to gain information about which to target pharmacologically. To compare potential AMBRA1 activation strategies we have designed and validated several mutant constructs (ACTA, TAT, WD40 and S1014) in addition to characterising their effects on proliferation, apoptosis, autophagy and mitophagy in SHSY5Y cells. AMBRA1TAT, which is a mutant form of AMBRA1 that can’t interact with dynein light chain (DLC)1 at the microtubules, produced the most promising results. Indeed, overexpression of this mutant protected cells against apoptosis and induced autophagy and mitophagy in SHSY5Y cells in addition to enhancing the switch from quiescence to proliferation in mouse neural stem cells. Future studies should focus on designing compounds that inhibit the protein-protein interaction between AMBRA1 and DLC1 and thus have potential to be used as a drug strategy to treat neurodegeneration.
APPLICATION OF MULTI-AGENT WHALE MODELLING TO AN INTERACTIVE SAXOPHONE AND WHALES DUET

„Fast Travel‟ is named after a Blue Whale call, and is both a scientific experiment in computer-modelling of schools of artificial singing whales and a live performance for saxophone and electronics. The audience hear a live surround sound interaction between a saxophonist and artificial schools of whales. The whales hear the sax as if it is another whale. The audience are surrounded by at least four speakers and a sub-woofer with a saxophonist in the middle. The whale sounds, driven by a computer model, move from speaker to speaker, as the invisible but audible artificial whales move within an invisible sea the audience are "underwater" with the schools in this “sound sea”. The artificially intelligent whale models sing synthesized electronic sounds, evolving new songs live based on hearing each others' performances. The composition title is not just because of the Blue Whale-type song, but because of the way it speeds up the evolution of the whales‟ song-tuning. Decades are compressed down into the 12 minutes as the audience time travel through the evolution of the underwater music. But the song evolution is driven here by the saxophone, rather than solely by other whales or man-made acoustic phenomena. The scored saxophone is audible to the whales, and influences their tunes through imitation. Although the majority of the saxophone music will be pre-scored, the behaviour of the whales is not 100% predictable because of complex interactions, thus the performance will differ each time.