Miracle-dz/UniFAR-FTUs huggingface dataset:
SD-DefSLAM: Semi-Direct Monocular SLAM for Deformable and Intracorporeal Scenes

Conventional SLAM techniques strongly rely on scene rigidity to solve data association, ignoring dynamic parts of the scene. In this work we present Semi-Direct DefSLAM (SD-DefSLAM), a novel monocular deformable SLAM method able to map highly deforming environments, built on top of DefSLAM [1]. To robustly solve data association in challenging deforming scenes, SD-DefSLAM combines direct and indirect methods: an enhanced illumination-invariant Lucas-Kanade tracker for data association, geometric Bundle Adjustment for pose and deformable map estimation, and bag-of-words based on feature descriptors for camera relocalization. Dynamic objects are detected and segmented-out using a CNN trained for the specific application domain.We thoroughly evaluate our system in two public datasets. The mandala dataset is a SLAM benchmark with increasingly aggressive deformations. The Hamlyn dataset contains intracorporeal sequences that pose serious real-life challenges beyond deformation like weak texture, specular reflections, surgical tools and occlusions. Our results show that SD-DefSLAM outperforms DefSLAM in point tracking, reconstruction accuracy and scale drift thanks to the improvement in all the data association steps, being the first system able to robustly perform SLAM inside the human body.
Incorporating Terminology Constraints in Automatic Post-Editing

Users of machine translation (MT) may want to ensure the use of specific lexical terminologies. While there exist techniques for incorporating terminology constraints during inference for MT, current APE approaches cannot ensure that they will appear in the final translation. In this paper, we present both autoregressive and non-autoregressive models for lexically constrained APE, demonstrating that our approach enables preservation of 95% of the terminologies and also improves translation quality on English-German benchmarks. Even when applied to lexically constrained MT output, our approach is able to improve preservation of the terminologies. However, we show that our models do not learn to copy constraints systematically and suggest a simple data augmentation technique that leads to improved performance and robustness.
Faster Convergence of Stochastic Gradient Langevin Dynamics for Non-Log-Concave Sampling

We provide a new convergence analysis of stochastic gradient Langevin dynamics (SGLD) for sampling from a class of distributions that can be non-log-concave. At the core of our approach is a novel conductance analysis of SGLD using an auxiliary time-reversible Markov Chain. Under certain conditions on the target distribution, we prove that $\tilde O(d^4\epsilon^{-2})$ stochastic gradient evaluations suffice to guarantee $\epsilon$-sampling error in terms of the total variation distance, where $d$ is the problem dimension. This improves existing results on the convergence rate of SGLD (Raginsky et al., 2017; Xu et al., 2018). We further show that provided an additional Hessian Lipschitz condition on the log-density function, SGLD is guaranteed to achieve $\epsilon$-sampling error within $\tilde O(d^{15/4}\epsilon^{-3/2})$ stochastic gradient evaluations. Our proof technique provides a new way to study the convergence of Langevin-based algorithms and sheds some light on the design of fast stochastic gradient-based sampling algorithms.
Explaining and Improving Model Behavior with k Nearest Neighbor Representations

Interpretability techniques in NLP have mainly focused on understanding individual predictions using attention visualization or gradient-based saliency maps over tokens. We propose using k nearest neighbor (kNN) representations to identify training examples responsible for a model's predictions and obtain a corpus-level understanding of the model's behavior. Apart from interpretability, we show that kNN representations are effective at uncovering learned spurious associations, identifying mislabeled examples, and improving the fine-tuned model's performance. We focus on Natural Language Inference (NLI) as a case study and experiment with multiple datasets. Our method deploys backoff to kNN for BERT and RoBERTa on examples with low model confidence without any update to the model parameters. Our results indicate that the kNN approach makes the finetuned model more robust to adversarial inputs.
i-Mix: A Strategy for Regularizing Contrastive Representation Learning

Contrastive representation learning has shown to be an effective way of learning representations from unlabeled data. However, much progress has been made in vision domains relying on data augmentations carefully designed using domain knowledge. In this work, we propose i-Mix, a simple yet effective regularization strategy for improving contrastive representation learning in both vision and non-vision domains. We cast contrastive learning as training a non-parametric classifier by assigning a unique virtual class to each data in a batch. Then, data instances are mixed in both the input and virtual label spaces, providing more augmented data during training. In experiments, we demonstrate that i-Mix consistently improves the quality of self-supervised representations across domains, resulting in significant performance gains on downstream tasks. Furthermore, we confirm its regularization effect via extensive ablation studies across model and dataset sizes.
Extensive Literature Search on the ‘Effects of Copper intake levels in the gut microbiota profile of target animals, in particular piglets’

The potential effect of the copper intake on the microbiota profile of pigs, chickens and cows was reviewed through an extensive literature search. A total of 28 (out of 229), 17 (out of 106) and 0 (out of 114) references were considered relevant for pigs, chickens and cows, respectively. The overall conclusion from the studies with piglets and growing pigs is that copper, even at low concentrations (<50 mg/kg feed), may affect the microbiota in the gastrointestinal tract. Especially, the population of clostridia and coliform bacteria seems to be affected by low copper concentrations. At higher concentrations (>170 mg/kg feed) Cu as CuSO4 reduces the population of lactobacilli in piglets as well as growing pigs. In slaughter pigs, the addition of Cu as CuSO4 reduces the population of streptococci in colonic and fecal samples, the population of ureolytic bacteria in the colon of which streptococci make up 74%, the urease activity in the colon, and decarboxylation and deamination of amino acids in the small intestine. No effect of Cu as CuSO4 on the population of streptococci and on urease activity is seen in piglets. Supplementing piglet diets with 100 to 250 mg/kg Cu as CuSO4 significantly change the community structure of the microbiota in the gastrointestinal tract by reducing the number of bacterial species and reducing the similarity of the microbiota. The overall conclusion from the studies with broilers is that copper, even at low concentrations (<50 mg/kg feed), may affect the microbiota in the gastrointestinal tract. Especially the population of clostridia seems to be affected by low copper concentrations. In particular, copper bound clay minerals seem to have an effect. At higher concentrations (>200 mg/kg feed) inorganic or organic bound copper also seems to affect the population of lactobacilli and coliform bacteria, to reduce the pH in gizzard content and to produce severe gizzard erosion. © European Food Safety Authority, 2016
Continuum limit of p-Laplacian evolution problems on graphs: Lq graphons and sparse graphs

In this paper we study continuum limits of the discretized p-Laplacian evolution problem on sparse graphs with homogeneous Neumann boundary conditions. This extends the results of [24] to a far more general class of kernels, possibly singular, and graph sequences whose limit are the so-called L q-graphons. More precisely, we derive a bound on the distance between two continuous-in-time trajectories defined by two different evolution systems (i.e. with different kernels, second member and initial data). Similarly, we provide a bound in the case that one of the trajectories is discrete-in-time and the other is continuous. In turn, these results lead us to establish error estimates of the full discretization of the p-Laplacian problem on sparse random graphs. In particular, we provide rate of convergence of solutions for the discrete models to the solution of the continuous problem as the number of vertices grows.
An updated detailed characterization of planes of satellites in the MW and M31

We present a detailed characterization of planes of satellite galaxies in the Milky Way (MW) and M31. For a positional analysis, we introduce an extension to the `4-galaxy-normal density plot' method \citep[][P13]{Pawlowski13}. It finds the normal directions to the predominant planar configurations of satellites of a system, yielding for each a \textit{collection} of planes of increasing member satellites. This allows to quantify the quality of planes in terms of population ($N_{\rm sat}$) and spatial flattening ($c/a$). We apply this method to the latest data for confirmed MW and M31 satellite samples, with 46 and 34 satellites, respectively. New MW satellites form part of planes previously identified from the sample with $N_{\rm sat}=27$ studied in P13: we identify a new plane with $N_{\rm sat}=39$ as thin as the VPOS-3 ($c/a\sim 0.2$), and with roughly the same normal direction; so far the most populated plane that thin reported in the Local Group. We introduce a new method to determine, using kinematic data, the axis of maximum co-orbitation of MW satellites. Interestingly, this axis approximately coincides with the normal to the former plane: $\geq45\pm5\%$ of satellites co-orbit. In M31 we discover a plane with $N_{\rm sat}=18$ and $c/a\sim0.15$, i.e., quality comparable to the GPoA, and perpendicular to it. This structure is viewed face-on from the Sun making it susceptible to M31 satellite distance uncertainties. An estimation of the perpendicular velocity dispersion suggests it is dynamically unstable. Finally we find that mass is not a property determining a satellite's membership to good quality planes.
Advertisement calls of Guenther’s frog Hylarana guentheri (Anura: Ranidae) during the breeding season

Abstract Acoustic signalling is the most important form of communication in anuran amphibians. Here we recorded and analysed the calls of 18 male Guenther’s frogs (Hylarana guentheri) from the wild during the breeding season. The advertisement calls of H. guentheri were composed of from a single note to five notes, with three-note calls the most recorded. All individuals produced calls around 600 Hz but calls ranged from 470 to 2600 Hz. Comparing the differences between individuals calls, we found within-male coefficients of variation (CVw) of call intensity, the fundamental frequency, the first formant, the second formant, the third formant and the fourth formant were static (less than 5% variation), whereas those of note duration, call duration, call interval, numbers of pulses and dominant frequency were dynamic (larger than 15% variation). Comparisons of the call characteristics of H. guentheri in this study with other studies from China, Singapore and Vietnam found call characteristics varied greatly between the five different locations.
Revisiting the genetic diversity and population structure of the critically endangered leatherback turtles in the South-west Atlantic Ocean: insights for species conservation

The worldwide population of the leatherback turtle (Dermochelys coriacea) encompasses seven subpopulations among the Pacific, Atlantic and Indian Oceans. It has experienced declines across parts of its distribution, with the subpopulation of the South-west Atlantic listed as critically endangered by the IUCN Red List. The main threats to this subpopulation include its interaction with fisheries, coastal development, pollution and climate change. In this study, we sequenced mitochondrial DNA from 52 leatherback turtles in Brazil and combined these with published data from other Atlantic Ocean rookeries. The haplotype diversities of the Atlantic population rookeries ranged from 0.112 to 0.533 and are not directly proportional to current rookery sizes. The Brazilian rookery, despite recording low nest numbers per year, had the second-highest haplotype diversity among all Atlantic rookeries (h = 0.532). A mixed-stock analysis revealed that the South American pelagic aggregate is primarily composed of individuals from West Africa (84%), with contributions from the North Atlantic rookeries (14%). Leatherback turtles appear to have a complex phylogeographic pattern, showing evidence of multiple colonization events and a lack of isolation by distance. Our novel dataset, based on DNA sequences of 695 base pairs, will provide baseline data needed to understand population dynamics in the region, building comprehensive population assessments to support and develop management strategies. Having both the only known regular rookery in the South-west Atlantic, and a mixed-origin foraging area for the species along its coast, Brazil has a key role in the conservation of the leatherback turtle.
Antioxidative and biological activity of extracts from Orostachys japonicus

와송에 함유된 phenol성 물질은 50% ethanol을 용매로 하여 추출하였을 때 10.56±0.32 mg/g의 함량을 나타내었다. 와송 추출물의 항산화력을 측정한 결과 전자공여능은 200 μg/mL phenolic농도에서 열수 추출물과 50% ethanol 추출물 모두 80.0% 이상으로 높은 효과가 확인되었다. ABTS radical cation decolorization을 측정한 결과에서 와송 열수와 50% ethanol 추출물 모두 95.0% 이상의 높은 항산화 활성이 측정되었다. Antioxidant protection factor (PF)는 열수 추출물이 50% ethanol 추출물에 비해 높은 PF값을 나타내었으며, thiobarbituric acid reactive substance (TBARs) 저해효과는 50% ethanol 추출물이 열수 추출물 보다 높은 항산화력을 나타내었다. 와송 추출물의 항고혈압 효과를 살펴보기 위하여 angiotensin converting enzyme 저해활성을 측정한 결과 200 μg/mL phenolic의 처리농도에서 열수와 50% ethanol 추출물이 각각 6.67%과 7.98%로 낮게 나타났다. 와송 추출물의 XOase 저해활성은 50% ethanol 추출물200 μg/mL phenolic 농도에서 60.85%의 저해율을 나타내었으며, tyrosinase 억제활성은 50% ethanol 추출물 200 μg/mL phenolic 농도에서 64.59%로 나타나 대조구인 kojic acid 보다 미백 효과가 더 우수함을 입증하였다. 주름 생성과 관련된 collagenase 억제효과는 50% ethanol 추출물의 50200 μg/mL phenolic 농도에서 75.9585. 02%로 매우 우수하였으며, 대조구인 epigallocatechin-gallate의 68.9176. 64% 보다 다소 높았다. Elastase저해활성도 50% ethanol 추출물 200 μg/mL phenolic 농도에서 최대 63.65%의 저해효과를 나타내어 와송 50% ethanol 추출물의 주름개선 효과가 매우 우수함을 확인하였다. 이상의 결과를 통해 와송 추출물의 항산화 활성, 통풍 억제효능, 미백 및 주름개선 등의 기능성 검증을 위한 기초 연구 자료로 활용이 가능할 것으로 예상되며, 향후 추가적인 연구를 통해 와송 추출물을 기능성 식품 및 화장품, 의약품 소재로 적용이 가능할 것으로 판단되었다.
Modern human origins: multiregional evolution of autosomes and East Asia origin of Y and mtDNA

Recent studies have established that genetic diversities are mostly maintained by selection, therefore rendering the present molecular model of human origins untenable. Using improved methods and public data, we have revisited human evolution and derived an age of 1.91-1.96 million years for the first split in modern human autosomes. We found evidence of modern Y and mtDNA originating in East Asia and dispersing via hybridization with archaic humans. Neanderthals and Denisovans were archaic Africans with Eurasian admixtures and ancestors of South Asia Negritos and Aboriginal Australians. Verifying our model, we found more ancestry of Southern Chinese from Hunan in Africans relative to other East Asian groups examined. These results suggest multiregional evolution of autosomes and East Asia origin of Y and mtDNA, thereby leading to a coherent account of modern human origins.
Functions of GluN2D-containing NMDA receptors in dopamine neurons of the substantia nigra pars compacta

Dopamine (DA) neurons of the substantia nigra pars compacta (SNc) have a key role in regulation of voluntary movement control. Their death is a hallmark of Parkinson’s disease (PD), a neurodegenerative illness characterised by inhibited motor control, including muscle rigidity and tremor. Excitatory input to SNc-DA neurons is primarily from the subthalamic nucleus (STN), and in PD these afferents display a higher frequency firing, as well as increased burst firing, which could cause increased excitatory activity in SNc-DA neurons, in turn potentially activating regulatory processes. NMDA receptors (NMDARs) are widely expressed receptors for the excitatory neurotransmitter glutamate, and are essential for learning and memory due to their ability to act as synaptic coincidence detectors. In SNc-DA neurons, NMDARs have a putative triheteromeric subunit arrangement of GluN1 plus GluN2B and/or GluN2D. Wild type (WT) mice, and those lacking the gene for the GluN2D subunit (Grin2D-null), were used to explore the role of the GluN2D subunit in various aspects of DA neuronal function and dysfunction using whole cell patch clamp electrophysiology, viability assaying, and immunofluorescence. Constitutive expression of synaptic NMDARs was assessed in SNc-DA neurons at several ages by recording the ratio of AMPA receptor EPSC to NMDAR-EPSC, which revealed a nonlinear developmental alteration in this ratio but no genotype-related difference, indicating similar overall expression of functional NMDARs at the synapse in Grin2D-null mice. Pharmacological intervention using subunit-specific inhibitors ifenprodil and DQP-1105 on elicited NMDAR-EPSCs was also explored, with results suggesting a developmental shift from primarily GluN2B to GluN2B/D. Activity dependent regulation was then assessed by high frequency burst stimulation of glutamatergic afferents: in comparison to controls, significant downregulation of NMDARs was observed in SNc-DA neurons from WT mice, though no differences were observed based on genotype, indicating that the GluN2D subunit
Analysis of methods to estimate the mean and variance of the willingness to pay: parametric and non-parametric case

Introduccion: La valoracion contingente (MVC) es el metodo directo mas significativo para calcular el valor monetario total de los servicios ecosistemicos. Objetivos: Los metodos parametrico y no parametrico de estimacion de la disposicion a pagar (DAP) se compararon a traves de intervalos de la media, para dar recomendaciones de uso en la valoracion de servicios ecosistemicos. Materiales y metodos: Para proveer soporte a la comparacion de los metodos se utilizaron dos casos de estudio que aplicaron el MVC. Dentro del enfoque no parametrico, los intervalos de la media y varianza obtenidos con las formulas de Boman, Bostedt y Kristrom se compararon con los obtenidos por el metodo de Haab y McConnell. Resultados y discusion: Los metodos parametrico y no parametrico se pueden utilizar indistintamente para obtener la media de la DAP, debido a que no existieron diferencias significativas entre los valores estimados. En los metodos no parametricos, los dos enfoques analizados no difieren en la estimacion de la media, pero si existen diferencias al momento de calcular las varianzas; el metodo de Haab y McConnell genera varianzas de la media relativamente mas grandes. Conclusiones: Se recomienda utilizar el metodo no parametrico como complemento o validacion de los resultados del metodo parametrico, dado que este ultimo incluye variables socioeconomicas explicatorias de la DAP.
Evaluation of Energy Resolution by Changing Angle and Position of Incident Photon in a LYSO Calorimeter

In this paper, we investigate the effect on energy resolution from changing the angle and the position of incidence photon for a 5 $\times$ 5 crystal matrix built with (25 $\times$ 25 $\times$ 200) mm$^{3}$ LYSO scintillating crystals. Those crystals have been proposed for the electromagnetic calorimeter of the Turkish Accelerator Center-Particle Factory (TAC-PF) detector. The energy resolution was obtained as $\sigma_{E}/E = 0.42 \% / \sqrt{E/GeV} \oplus 1.60 \%$ at the center of the matrix in the energy range of 50 MeV to 2 GeV. When we examined the dependence of the energy resolution on the incidence angle of the photon, resolution began to deteriorate at angles greater than $2^{\circ}$ on the 5 $\times$ 5 crystal matrix. Moreover, energy resolution at the corners of the central crystal was worse than at the center of the central crystal by a factor of 1.3 at 50 MeV and 1.1 at 2 GeV.
Parameter Norm Growth During Training of Transformers

The capacity of neural networks like the widely adopted transformer is known to be very high. Evidence is emerging that they learn successfully due to inductive bias in the training routine, typically some variant of gradient descent (GD). To better understand this bias, we study the tendency of transformer parameters to grow in magnitude during training. We find, both theoretically and empirically, that, in certain contexts, GD increases the parameter $L_2$ norm up to a threshold that itself increases with training-set accuracy. This means increasing training accuracy over time enables the norm to increase. Empirically, we show that the norm grows continuously over pretraining for T5 (Raffel et al., 2019). We show that pretrained T5 approximates a semi-discretized network with saturated activation functions. Such "saturated" networks are known to have a reduced capacity compared to the original network family that can be described in automata-theoretic terms. This suggests saturation is a new characterization of an inductive bias implicit in GD that is of particular interest for NLP. While our experiments focus on transformers, our theoretical analysis extends to other architectures with similar formal properties, such as feedforward ReLU networks.
Can jets make the radioactively powered emission from neutron star mergers bluer?

Neutron star mergers eject neutron-rich matter in which heavy elements are synthesised. The decay of these freshly synthesised elements powers electromagnetic transients ("macronovae" or "kilonovae") whose luminosity and colour strongly depend on their nuclear composition. If the ejecta are very neutron-rich (electron fraction $Y_\mathrm{e} < 0.25$), they contain fair amounts of lanthanides and actinides which have large opacities and therefore efficiently trap the radiation inside the ejecta so that the emission peaks in the red part of the spectrum. Even small amounts of this high-opacity material can obscure emission from lower lying material and therefore act as a "lanthanide curtain". Here, we investigate how a relativistic jet that punches through the ejecta can potentially push away a significant fraction of the high opacity material before the macronova begins to shine. We use the results of detailed neutrino-driven wind studies as initial conditions and explore with 3D special relativistic hydrodynamic simulations how jets are propagating through these winds. Subsequently, we perform Monte Carlo radiative transfer calculations to explore the resulting macronova emission. We find that the hole punched by the jet makes the macronova brighter and bluer for on-axis observers during the first few days of emission, and that more powerful jets have larger impacts on the macronova.
Twice is enough for dangerous eigenvalues

We analyze the stability of a class of eigensolvers that target interior eigenvalues with rational filters. We show that subspace iteration with a rational filter is stable even when an eigenvalue is located near a pole of the filter. These dangerous eigenvalues contribute to large round-off errors in the first iteration, but are self-correcting in later iterations. In contrast, Krylov methods accelerated by rational filters with fixed poles typically fail to converge to unit round-off accuracy when an eigenvalue is close to a pole. In the context of Arnoldi with shift-and-invert enhancement, we demonstrate a simple restart strategy that recovers full precision in the target eigenpairs.