Miracle-dz/UniFAR-FTUs huggingface dataset:
Disorder and granular media

Preface (P.G. de Gennes). Foreword (D. Bideau and A. Hansen). Introduction (E. Guyon). 1. Some geometrical properties of two-dimensional hard disk packings (A. Gervois, D. Bideau). 2. Local structure of disordered hard sphere packings (J.L. Finney). 3. Order and disorder in packings and froths (N. Rivier). 4. Growth of packings (R. Jullien, P. Meakin, A. Pavlovitch). 5. Global geometrical description of homogeneous hard sphere packings (J.P. Troadec, J.A. Dodds). 6. Different methods to analyze the structure of granular media (L. Oger, J.P. Jernot). 7. Transport properties of the porous space of grain packings: heterogeneity effects (J.P. Hulin et al.). 8. Properties of the grain space of packings: effects of heterogeneities (S. Roux, D. Bideau, A. Hansen). 9. Disorder, diffusion and structure formation in granular flows (S.B. Savage). 10. Dense suspensions and loose packings (R. Blanc, E.J. Hinch). 11. Computer simulations of granular media (H.J. Herrmann). Subject index.
Estimating NDVI from Sentinel-1 Sar Data Using Deep Learning

Monitoring vegetation is of great importance for many applications, for example agriculture or forestry. Commonly, the normalized difference vegetation index (NDVI) of spaceborn sensor is utilized for this task. However, as the NDVI is derived from multispectral optical data, cloud coverage prevents the acquisition of useful values. This results in data and monitoring gaps. Generally, this can be avoided using cloud penetrating radar sensors but the different sensing method and different image characteristics hamper the easy usage of the data. Therefore, in this paper a method is presented to allow global cloud-independent vegetation monitoring by estimating the NDVI from radar data using a deep learning model. The used U-Net architecture is trained on a newly created dataset called SEN12TP of globally distributed radar and optical imagery with a small difference in acquisition time. The resulting performance is evaluated and different input modalities are compared. Additionally, the ability of this approach to densify NDVI time series is demonstrated.
Personalized quantitative models of NAD metabolism in hepatocellular carcinoma identify a subgroup with poor prognosis

Cancer cells are known to undergo metabolic adaptation to cater to their enhanced energy demand. Nicotinamide adenine dinucleotide (NAD) is an essential metabolite regulating many cellular processes within the cell. The enzymes required for NAD synthesis, starting from the base precursor - tryptophan, are expressed in the liver and the kidney, while all other tissues convert NAD from intermediate precursors. The liver, being an active metabolic organ, is a primary contributor to NAD biosynthesis. Inhibition of key enzymes in the NAD biosynthetic pathways is proposed as a strategy for designing anti-cancer drugs. On the other hand, NAD supplementation has also been reported to be beneficial in cancer in some cases. As metabolic adaptation that occurs in cancer cells can lead to perturbations to the pathways, it is important to understand the exact nature of the perturbation in each individual patient. To investigate this, we use a mathematical modelling approach integrated with transcriptomes of patient samples from the TCGA-LIHC cohort. Quantitative profiling of the NAD biosynthesis pathway helps us understand the NAD biosynthetic status and changes in the controlling steps of the pathway. Our results indicate that NAD biosynthesis is heterogeneous among liver cancer patients, and that Nicotinate phosphoribosyl transferase (NAPRT) levels are indicative of the NAD biosynthetic status. Further, we find that reduced NAPRT levels combined with reduced Nicotinamide phosphoribosyl transferase (NAMPT) levels contribute to poor prognosis. Identification of the precise subgroup who may benefit from NAD supplementation in subgroup with low levels of NAPRT and NAMPT could be explored to improve patient outcome.
BINARITY AND THE ABUNDANCE DISCREPANCY PROBLEM IN PLANETARY NEBULAE

The discrepancy between abundances computed using optical recombination lines and collisionally excited lines is a major unresolved problem in nebular astrophysics. Here, we show that the largest abundance discrepancies are reached in planetary nebulae with close binary central stars. We illustrate this using deep spectroscopy of three nebulae with a post common-envelope (CE) binary star. Abell 46 and Ou 5 have O2+/H+ abundance discrepancy factors larger than 50, and as high as 300 in the inner regions of Abell 46. Abell 63 has a smaller discrepancy factor around 10, which is still above the typical values in ionized nebulae. Our spectroscopic analysis supports previous conclusions that, in addition to “standard” hot ( T e ? > ∼ 104 K) gas, there exists a colder ( T e ? > ∼ 103 K), ionized component that is highly enriched in heavy elements. These nebulae have low ionized masses, between 10−3 and 10−1 M⊙ depending on the adopted electron densities and temperatures. Since the much more massive red giant envelope is expected to be entirely ejected in the CE phase, the currently observed nebulae would be produced much later, during post-CE mass loss episodes when the envelope has already dispersed. These observations add constraints to the abundance discrepancy problem. We revise possible explanations. Some explanations are naturally linked to binarity such as, for instance, high-metallicity nova ejecta, but it is difficult at this stage to depict an evolutionary scenario consistent with all of the observed properties. We also introduce the hypothesis that these nebulae are the result of tidal destruction, accretion, and ejection of Jupiter-like planets.
Open Surgical Excision of Intracranial Arachnoid Cysts after Initial Procedure Failure in Children

: Background: Intracranial arachnoid cysts are pathological conditions that occur in 2.6% of children. Different surgical procedures had significant failure rate. Objective: A trial to evaluate the effectiveness of open surgical excision in failed first-other surgery. Methods: Twenty-three patients with symptomatic arachnoid cysts with radiological evidence who had had one previous failed surgical intervention, shunting or endoscopic fenestration, underwent open surgical excision of the arachnoid cyst at the Neurosurgery Department of Benha University and Benha Children Hospitals through the period from January 2018 to January 2022. Results: Twenty-three children with intracranial arachnoid cysts (IAC) underwent open surgical excision, totaling nine cases (39.1%) and partial in fourteen cases (60.9%). In thirteen cases, associated microscopic fenestration to basal arachnoid cisterns was done. The mean follow-up period is 28.36±3.97 months with 77.3% success and 22.7% failure with subsequent treatment by cystoperitoneal shunting. Total excision success is 100%, but partial excision is 64.3%, with 88.9% of them being associated with microscopic fenestration. Mild early transient complications were reported in only three cases and were conservatively treated, but late complications occurred in two cases. Conclusion: Open surgical excision of IAC has a very good success rate in the treatment of intracranial arachnoid cysts after initial procedure failure; complete excision should be the main aim whenever possible for optimum results that force us to ask: "Could it be the first line of surgical treatment in symptomatic untreated cases? "
Adjusted Pearson residuals in exponential family nonlinear models

In this paper, we give matrix formulae of order 𝒪(n −1), where n is the sample size, for the first two moments of Pearson residuals in exponential family nonlinear regression models [G.M. Cordeiro and G.A. Paula, Improved likelihood ratio statistic for exponential family nonlinear models, Biometrika 76 (1989), pp. 93–100. ]. The formulae are applicable to many regression models in common use and generalize the results by Cordeiro [G.M. Cordeiro, On Pearson's residuals in generalized linear models, Statist. Prob. Lett. 66 (2004), pp. 213–219. ] and Cook and Tsai [R.D. Cook and C.L. Tsai, Residuals in nonlinear regression, Biometrika 72(1985), pp. 23–29. ]. We suggest adjusted Pearson residuals for these models having, to this order, the expected value zero and variance one. We show that the adjusted Pearson residuals can be easily computed by weighted linear regressions. Some numerical results from simulations indicate that the adjusted Pearson residuals are better approximated by the standard normal distribution than the Pearson residuals.
Laser–Microwave synchronisation for ultrafast electron diffraction

Ultrafast electron diffraction is a pump--probe technique that allows the visualisation of molecular dynamics with atomic scale resolution. However, the fastest electronic and atomic dynamics in light-driven matter transformations are, as yet, unmeasureable with this technique. This is because the temporal resolution in ultrafast electron diffraction is limited by difficulties in producing the shortest electron pulses, caused by the electron charge, via Coulomb repulsion (space charge), and rest mass, via vacuum dispersion of the electron wavefunction. Space charge effects and a finite energy bandwidth both lead to temporal broadening of electron pulses. Methods to compress such pulses in microwave fields have been developed, but these are fundamentally limited by the achievable temporal synchronisation of the employed microwave with the excitation laser pulses. This work is aimed at breaking this limitation and thereby advancing ultrafast electron diffraction towards the ultimate temporal resolution of any realistic light--matter interaction. Firstly, a high-resolution optical-microwave phase detector based on optical interferometry is designed for operation around the 800-nm wavelength of Ti:sapphire lasers best suited for sample excitation. The phase detector provides a resolution of 3 fs and the capability of functioning as an integral component in a phase-locked loop for synchronising a low-noise dielectric resonator oscillator with the Ti:sapphire laser. Furthermore, we demonstrate a separate, novel, passive synchronisation technique through direct microwave extraction of a harmonic of the laser repetition rate by photodetection. A record-low residual phase noise over nine frequency decades (mHz--MHz) is achieved through implementation of an optical-mode filter which circumvents thermal noise problems at low pulses energies to simultaneously reduce detrimental amplitude-to-phase noise conversion in the photodetection process. An amplification chain is designed to achieve a microwave power suitable for electron compression while preserving this excellent phase noise. Rigorous out-of-loop characterisation of the synchronisation with the optical-microwave phase detector shows a root-mean-square (rms) timing stability of 4.8 fs. This superior synchronisation has allowed the generation of 12 fs (rms) electron pulses, the shortest to our knowledge. Lastly, stability of the laser--electron synchronisation over many hours is also demonstrated on a sub-five-femtosecond scale through in-situ measurement and subsequent compensation for the entire range of possible long-term drifts. This shows that incorporating these techniques can allow ultrafast electron diffraction experiments to observe the fastest reversible atomic-scale light--matter interaction dynamics.
Diffused Redundancy in Pre-trained Representations

Representations learned by pre-training a neural network on a large dataset are increasingly used successfully to perform a variety of downstream tasks. In this work, we take a closer look at how features are encoded in such pre-trained representations. We find that learned representations in a given layer exhibit a degree of diffuse redundancy, ie, any randomly chosen subset of neurons in the layer that is larger than a threshold size shares a large degree of similarity with the full layer and is able to perform similarly as the whole layer on a variety of downstream tasks. For example, a linear probe trained on $20\%$ of randomly picked neurons from the penultimate layer of a ResNet50 pre-trained on ImageNet1k achieves an accuracy within $5\%$ of a linear probe trained on the full layer of neurons for downstream CIFAR10 classification. We conduct experiments on different neural architectures (including CNNs and Transformers) pre-trained on both ImageNet1k and ImageNet21k and evaluate a variety of downstream tasks taken from the VTAB benchmark. We find that the loss and dataset used during pre-training largely govern the degree of diffuse redundancy and the"critical mass"of neurons needed often depends on the downstream task, suggesting that there is a task-inherent redundancy-performance Pareto frontier. Our findings shed light on the nature of representations learned by pre-trained deep neural networks and suggest that entire layers might not be necessary to perform many downstream tasks. We investigate the potential for exploiting this redundancy to achieve efficient generalization for downstream tasks and also draw caution to certain possible unintended consequences. Our code is available at \url{https://github.com/nvedant07/diffused-redundancy}.
Qualitative and quantitative DNA metabarcoding assessment of Neotropical ichthyoplankton communities is marker-dependent

The study of ichthyoplankton is paramount to understanding fish assemblages’ reproductive dynamics. DNA metabarcoding has been applied as a rapid, cost-effective, and accurate taxonomy tool, allowing the identification of multiple individuals simultaneously. However, there remain significant challenges when using DNA metabarcoding, such as molecular marker choice according to the taxonomic resolution and length of the fragment to be sequenced, primer bias, incomplete reference databases, and qualitative inferences incongruences. Here, 30 ichthyoplankton pools collected from a Neotropical River were identified at a molecular level using DNA metabarcoding to compare the resolution, sensibility, specificity and relative read abundance (RRA) recovery of three molecular markers: the standard COI fragment (650pb, with each strand analyzed individually) and two short 12S rRNA genes markers (? 200bp NeoFish and MiFish markers). The combined use of the three markers increased the genera detection rates by 25% to 87.5%, allowing an increased taxonomic coverage and robust taxonomic identification of complex neotropical ichthyoplankton communities. RRA is marker-dependent, indicating caution is still needed whilst inferring species abundance based on DNA metabarcoding data when using PCR-dependent protocols. Qualitative and quantitative DNA metabarcoding assessment of Neotropical ichthyoplankton communities is marker-dependent Running Title: Qualitative and quantitative DNA metabarcode Daniel Fonseca Teixeira , Heron Oliveira Hilário, Gilmar Bastos Santos, Daniel Cardoso Carvalho 1Post-Graduate Program in Vertebrate Biology, Pontifical Catholic University of Minas Gerais, PUC Minas, Belo Horizonte 30535-610, Brazil; danielcarvalho@pucminas.br (D.C.C.); heronoh@gmail.com (H.O.H); gilmarsantos4@hotmail.com (G.B.S.) 2Post-Graduate Program in Genetics, Federal University of Minas Gerais, Belo Horizonte 31270-901, Brazil; danielfonsecat@gmail.com (D.F.T.); *Corresponding author: Daniel Cardoso Carvalho (danielcarvalho@pucminas.br) Abstract The study of ichthyoplankton is paramount to understanding fish assemblages’ reproductive dynamics. DNA metabarcoding has been applied as a rapid, cost-effective, and accurate taxonomy tool, allowing the identification of multiple individuals simultaneously. However, there remain significant challenges when using DNA metabarcoding, such as molecular marker choice according to the taxonomic resolution and length of the fragment to be sequenced, primer bias, incomplete reference databases, and qualitative inferences
Symmetric derivation of singlet correlations in a quaternionic 3-sphere model

Using the powerful language of geometric algebra, we present an observationally symmetric derivation of the strong correlations predicted by the entangled singlet state in a deterministic and locally causal model, usually also referred to as a local-realistic model, in which the physical space is assumed to be a quaternionic 3-sphere, or $S^3$, available as the spatial part of a solution of Einstein's field equations of general relativity, and compare it in quantitative detail with Bell's local-realistic model for the singlet correlations set within a flat Euclidean space ${\mathrm{I\! R}^3}$. Since the quantitatively detailed expressions of relative-angle-dependent probabilities of observing measurement outcomes for Bell's local model do not seem to have been fully articulated before, our novel analysis exploiting the non-commutative properties of quaternions, in addition to allowing the comparison with the quaternionic 3-sphere model, may also provide useful comparisons for other less compelling local-realistic models, such as those relying on retrocausality or superdeterminism. Apart from the conservation of zero spin angular momentum, the key attribute underlying the strong singlet correlations within $S^3$ in comparison with Bell's local model turns out to be the spinorial sign changes intrinsic to quaternions that constitute the 3-sphere. In addition, we also discuss anew a macroscopic experiment that can, in principle, test our 3-sphere hypothesis.
EVALUATION OF URINARY CD4 T-CELL LEVELS AS A BIO-MARKER FOR LUPUS NEPHRITIS AND ITS CORRELATION WITH DISEASE ACTIVITY.

Mohammad A. Zakaria 1 *, Doaa M. Sharaf 2 , Ibrahim T. Abdelal 2 and Ghada M. Elakad 3 . 1. Rheumatology, Physical Medicine & Rehabilitation Department, Faculty of Medicine, Ain Shams University, Egypt. 2. Rheumatology, Physical Medicine & Rehabilitation Department, Faculty of Medicine, Zagazig University, Egypt. 3. Clinical Pathology Department, Faculty of Medicine, Zagazig University, Egypt. Manuscript Info Abstract . Manuscript History
Driving ecotourism loyalty through destination image, satisfaction and motivation

Tourism, especially ecotourism, is a sector that plays a role in contributing to the Indonesian economy, especially finance and foreign exchange. However, the Covid-19 pandemic has affected this sector. Efforts to revive the ecotourism sector continue to be encouraged after the Pandemic. Padang Savana is one of the Ecotourism Sites that was affected by Covid-19 and was closed. Efforts continue to be made so that these ecotourism sites can rise and return to the interest of visitors. Efforts are being made to increase visiting loyalty through enhancing destination image, tourist motivation, travel satisfaction, and experience. The purpose of this study was to examine the effect of destination image, tourist motivation, travel satisfaction, and experience on ecotourism destination loyalty. This research approach uses a quantitative approach. The population and sample of this study were visitors to the Padang Savana ecotourism. Purposive Sampling was used as a sampling technique. Sources of data were obtained through surveys, and the results were processed using SEM PLS. The results of the study show that destination image and motivation have a positive and significant impact on travel satisfaction. Travel motivation and satisfaction affect destination loyalty. The results of this study are expected to be useful for ecotourism management to increase visitor loyalty through trip motivation and satisfaction. For future research research can be re-tested with different ecotourism sites and test hypotheses that have not been supported.
Riemannian Walk for Incremental Learning: Understanding Forgetting and Intransigence Riemannian Walk for Incremental Learning: Understanding Forgetting and Intransigence

We study the incremental learning problem for the classification task, a key component in developing life-long learning systems. The main challenges while learning in an incremental manner are to preserve and update the knowledge of the model. In this work, we propose a generalization of Path Integral [24] and EWC [7] with a theoretically grounded KL-divergence based perspective. We show that, to preserve and update the knowledge, regularizing the model’s likelihood distribution is more intuitive and provides better insights to the problem. To do so, we use KLdivergence as a measure of distance which is equivalent to computing distance in a Riemannian manifold induced by the Fisher information matrix. Furthermore, to enhance the learning flexibility, the regularization is weighted by a parameter importance score that is calculated along the entire training trajectory. Contrary to forgetting, as the algorithm progresses, the regularized loss makes the network intransigent, resulting in its inability to discriminate new tasks from the old ones. We show that this problem of intransigence can be addressed by storing a small subset of representative samples from previous datasets. In addition, in order to evaluate the performance of an incremental learning algorithm, we introduce two novel metrics to evaluate forgetting and intransigence. Experimental evaluation on incremental version of MNIST and CIFAR-100 classification datasets shows that our approach outperforms existing state-of-the-art baselines in all the evaluation metrics.
The Torres Strait

Foreword. Table of Maps and Figures. 1. Geography of the Torres Strait. 2. Historical Background of the Torres Strait. 3. Economic Characteristics of the Strait. 4. The International Law of Straits and the Torres Strait. 5. Legal Regime of the Torres Strait. 6. Environmental Issues in the Torres Strait. 7. Contemporary Issues: Self-Determination and the Islanders. Appendix A. Appendix B. Appendix C. Index.
StrokeUrokinase and Mechanical Thrombolysis in (Tirofiban) followed by Intra-Arterial Intravenous Glycoprotein IIb/IIIa Inhibitor

BACKGROUND AND PURPOSE: The purpose of this study was to evaluate preliminarily the efficacy and safety of intravenous tirofiban combined with intra-arterial pharmacologic and mechanical thrombolysis in patients with stroke. METHODS: Twenty-one consecutive patients with an acute ischemic stroke due to major cerebral arteries occlusion and a National Institutes of Health Stroke Scale [NIHSS] score > 18 were treated with an intravenous bolus of tirofiban and heparin followed by intra-arterial administration of urokinase coupled with mechanical thrombolysis. RESULTS: Thirteen patients had an anterior circulation stroke (T-siphon internal carotid artery [ICA] (cid:1) 7; middle cerebral artery [MCA] (cid:1) 6), 6 patients a posterior circulation stroke, and 2 patients an anterior plus posterior circulation stroke (left ICA or M1 tract of MCA plus basilar artery occlusions). Mean NIHSS score on admission was 21 (range, 18–27). Immediate recanalization was successful (thrombolysis in myocardial infarction [TIMI] 2–3) in 17 of 21 patients. The following day, 14 of 19 patients improved substantially and complete vessel patency (TIMI 3–4) was confirmed by digital subtraction angiography. Intracranial bleeding occurred in 5 of 21 patients (3 symptomatic cerebral hemorrhages and 2 subarachnoid hemorrhages) and was fatal in the case of 3 patients. At discharge, the mean NIHSS was 5.4 (range, 0–25). Overall, at 3-month follow-up the functional outcome was favorable (modified Rankin Scale score (cid:1) 0–2) in 13 of 21 (62%) patients. Death (including all causes) at 90 days occurred in 6 of 21 (28%) cases. CONCLUSIONS: The combination of intravenous tirofiban