Miracle-dz/UniFAR-FTUs huggingface dataset:
Toward efficient resource utilization at edge nodes in federated learning

Federated learning (FL) enables edge nodes to collaboratively contribute to constructing a global model without sharing their data. This is accomplished by devices computing local, private model updates that are then aggregated by a server. However, computational resource constraints and network communication can become a severe bottleneck for larger model sizes typical for deep learning applications. Edge nodes tend to have limited hardware resources (RAM, CPU), and the network bandwidth and reliability at the edge is a concern for scaling federated fleet applications. In this paper, we propose and evaluate a FL strategy inspired by transfer learning in order to reduce resource utilization on devices, as well as the load on the server and network in each global training round. For each local model update, we randomly select layers to train, freezing the remaining part of the model. In doing so, we can reduce both server load and communication costs per round by excluding all untrained layer weights from being transferred to the server. The goal of this study is to empirically explore the potential trade-off between resource utilization on devices and global model convergence under the proposed strategy. We implement the approach using the federated learning framework FEDn. A number of experiments were carried out over different datasets (CIFAR-10, CASA, and IMDB), performing different tasks using different deep-learning model architectures. Our results show that training the model partially can accelerate the training process, efficiently utilizes resources on-device, and reduce the data transmission by around 75% and 53% when we train 25%, and 50% of the model layers, respectively, without harming the resulting global model accuracy.
Multimodal Modeling For Spoken Language Identification

Spoken language identification refers to the task of automatically predicting the spoken language in a given utterance. Conventionally, it is modeled as a speech-based language identification task. Prior techniques have been constrained to a single modality; however in the case of video data there is a wealth of other metadata that may be beneficial for this task. In this work, we propose MuSeLI, a Multimodal Spoken Language Identification method, which delves into the use of various metadata sources to enhance language identification. Our study reveals that metadata such as video title, description and geographic location provide substantial information to identify the spoken language of the multimedia recording. We conduct experiments using two diverse public datasets of YouTube videos, and obtain state-of-the-art results on the language identification task. We additionally conduct an ablation study that describes the distinct contribution of each modality for language recognition.
Visible and NIR Image Fusion Algorithm Based on Information Complementarity

Visible and near-infrared(NIR) band sensors provide images that capture complementary spectral radiations from a scene. And the fusion of the visible and NIR image aims at utilizing their spectrum properties to enhance image quality. However, currently visible and NIR fusion algorithms cannot well take advantage of spectrum properties, as well as lack information complementarity, which results in color distortion and artifacts. Therefore, this paper designs a complementary fusion model from the level of physical signals. First, in order to distinguish between noise and useful information, we use two layers of the weight-guided filter and guided filter to obtain texture and edge layers, respectively. Second, to generate the initial visible-NIR complementarity weight map, the difference maps of visible and NIR are filtered by the extend-DoG filter. After that, the significant region of NIR night-time compensation guides the initial complementarity weight map by the arctanI function. Finally, the fusion images can be generated by the complementarity weight maps of visible and NIR images, respectively. The experimental results demonstrate that the proposed algorithm can not only well take advantage of the spectrum properties and the information complementarity, but also avoid color unnatural while maintaining naturalness, which outperforms the state-of-the-art.
Disorder and diffuse scattering in single-chirality (TaSe$_4$)$_2$I crystals

The quasi-one-dimensional chiral compound (TaSe$_4$)$_2$I has been extensively studied as a prime example of a topological Weyl semimetal. Upon crossing its phase transition temperature $T_\textrm{CDW}$ $\approx$ 263 K, (TaSe$_4$)$_2$I exhibits incommensurate charge density wave (CDW) modulations described by the well-defined propagation vector $\sim$(0.05, 0.05, 0.11), oblique to the TaSe$_4$ chains. Although optical and transport properties greatly depend on chirality, there is no systematic report about chiral domain size for (TaSe$_4$)$_2$I. In this study, our single-crystal scattering refinements reveal a bulk iodine deficiency, and Flack parameter measurements on multiple crystals demonstrate that separate (TaSe$_4$)$_2$I crystals have uniform handedness, supported by direct imaging and helicity dependent THz emission spectroscopy. Our single-crystal X-ray scattering and calculated diffraction patterns identify multiple diffuse features and create a real-space picture of the temperature-dependent (TaSe$_4$)$_2$I crystal structure. The short-range diffuse features are present at room temperature and decrease in intensity as the CDW modulation develops. These transverse displacements, along with electron pinning from the iodine deficiency, help explain why (TaSe$_4$)$_2$I behaves as an electronic semiconductor at temperatures above and below $T_\textrm{CDW}$, despite a metallic band structure calculated from density functional theory of the ideal structure.
Bialgebra cohomology and exact sequences

We show how the bialgebra cohomologies of two Hopf algebras involved in an exact sequence are related, when the third factor is finite-dimensional cosemisimple. As an application, we provide a short proof of the computation of the bialgebra cohomology of the universal cosovereign Hopf algebras in the generic (cosemisimple) case, done recently by Baraquin, Franz, Gerhold, Kula and Tobolski.
Pharmacokinetics of Oral Minor Cannabinoids in Blood and Brain.

Introduction: Minor cannabinoids are increasingly being consumed in oral formulations (i.e., edibles, tinctures) for medical and nonmedical purposes. This study examined the pharmacokinetics (PKs) of cannabinoids tetrahydrocannabivarin (THCV), cannabichromene (CBC), cannabinol (CBN), and delta-8-tetrahydrocannabinol (D8-THC) after the first and last oral dose during a 14-day administration period. Materials and Methods: Sprague-Dawley rats (N=6 animals/dose, 50% female) were given an assigned dose of one of four cannabinoids (THCV=3.2-100 mg/kg, CBC=3.2-100 mg/kg, CBN=1-100 mg/kg, or D8-THC=0.32-10 mg/kg) or vehicle (medium-chain triglyceride oil) through oral gavage once daily for 14 days. Blood was collected 45 min and 1.5, 3, and 24 h following the first dose (day 1) and the last dose (day 14) of repeated oral cannabinoid treatment for PK analysis. Outcomes of interest included time to maximum concentration (Tmax), maximum concentration (Cmax), and area under the concentration versus time curve (AUClast). Dose-normalized (DN) Cmax and DN AUClast were also calculated. Brain tissue was collected 24 h post-administration of the first (day 1) and the last (day 14) dose of each cannabinoid to determine concentrations in brain. Results: All cannabinoids tested were detectable in plasma after single and 14-day repeated dosing. DN Cmax and DN AUClast were highest for D8-THC, followed by CBC, CBN, and THCV. There was no sex difference observed in cannabinoid kinetics. Accumulation of D8-THC in plasma was observed after 14 days of administration. THCV levels in plasma were lower on day 14 compared to day 1, indicating potential adaptation of metabolic pathways and increased drug elimination. Cannabinoids were detected in brain tissue 24 h post-administration of the first and the last dose of 17-100 mg/kg THCV, 3.2-100 mg/kg CBC, 10-100 mg/kg CBN, and 10 mg/kg D8-THC. Conclusions: THCV, CBC, CBN, and D8-THC produced detectable levels in plasma and translocated to brain tissue after the first dose (day 1) and the last dose (day 14) of repeated oral dosing. Examination of PKs of these minor cannabinoids in blood and brain provides a critical step for informing target dose ranges and dosing schedules in future studies that evaluate the potential effects of these compounds.
Lamas und Alpakas – der neurologische Patient

Was tun, wenn Neuweltkameliden mit neurologischen Symptomen und einer sehr vielseitigen klinischen Symptomatik vorgestellt werden? Wir zeigen Ihnen passende diagnostische Möglichkeiten und führen Sie durch das Spektrum neurologischer Erkrankungen bei dieser besonderen Tierart.
NegesAPI: An API for Negation Cue Detection and Scope Identification in Spanish

: This paper presents NegesAPI, an API for negation detection in Spanish. This API receives as input a text, analyzes it and automatically annotated it with the negation cues present in the text and their respective scopes of inﬂuence for their subsequent incorporation in Natural Language Processing systems. For the development of it, the SFU Review SP-NEG corpus and the negation model of Jim´enez-Zafra et al. (2020a) have been updated. Moreover, it has been created a web application with the API documentation, a tutorial and a user management system to monitor the API usage.
Collective randomized measurements in quantum information processing

The concept of randomized measurements on individual particles has proven to be useful for analyzing quantum systems and is central for methods like shadow tomography of quantum states. We introduce $\textit{collective}$ randomized measurements as a tool in quantum information processing. Our idea is to perform measurements of collective angular momentum on a quantum system and actively rotate the directions using simultaneous multilateral unitaries. Based on the moments of the resulting probability distribution, we propose systematic approaches to characterize quantum entanglement in a collective-reference-frame-independent manner. First, we show that existing spin-squeezing inequalities can be accessible in this scenario. Next, we present an entanglement criterion based on three-body correlations, going beyond spin-squeezing inequalities with two-body correlations. Finally, we apply our method to characterize entanglement between spatially-separated two ensembles.
SHOWMe: Benchmarking Object-agnostic Hand-Object 3D Reconstruction

Recent hand-object interaction datasets show limited real object variability and rely on fitting the MANO parametric model to obtain groundtruth hand shapes. To go beyond these limitations and spur further research, we introduce the SHOWMe dataset which consists of 96 videos, annotated with real and detailed hand-object 3D textured meshes. Following recent work, we consider a rigid hand-object scenario, in which the pose of the hand with respect to the object remains constant during the whole video sequence. This assumption allows us to register sub-millimeter-precise groundtruth 3D scans to the image sequences in SHOWMe. Although simpler, this hypothesis makes sense in terms of applications where the required accuracy and level of detail is important e.g., object hand-over in human-robot collaboration, object scanning, or manipulation and contact point analysis. Importantly, the rigidity of the hand-object systems allows to tackle video-based 3D reconstruction of unknown handheld objects using a 2-stage pipeline consisting of a rigid registration step followed by a multi-view reconstruction (MVR) part. We carefully evaluate a set of non-trivial baselines for these two stages and show that it is possible to achieve promising object-agnostic 3D hand-object reconstructions employing an SfM toolbox or a hand pose estimator to recover the rigid transforms, and off-the-shelf MVR algorithms. However, these methods remain sensitive to the initial camera pose estimates which might be imprecise due to lack of textures on the objects or heavy occlusions of the hands, leaving room for improvements in the reconstruction. Code and dataset are available at https://europe.naverlabs. com/research/showme/.
Inducer of CBF Expression 1 (ICE1) Promotes Cold-enhanced Immunity by Directly Activating Salicylic Acid Signaling

Cold stress affects plant immune responses, and this process may involve the salicylic acid (SA) signaling pathway. However, the underlying mechanism by which low temperature signals coordinate with SA signaling to regulate plant immunity remains not fully understood. Here, we found that low temperatures enhanced the disease resistance of Arabidopsis against Pseudomonas syringae pv. tomato (Pst) DC3000. This process required Inducer of CBF expression 1 (ICE1), the core transcription factor in cold-signal cascades. ICE1 physically interacted with Non-expresser of PR genes 1 (NPR1), the master regulator of the SA signaling pathway. Enrichment of ICE1 on the PR1 promoter and its ability to transcriptionally activate PR1 were enhanced by NPR1. Further analyses revealed that cold stress signals cooperate with SA signals to facilitate plant immunity against pathogen attack in an ICE1-dependent manner. Cold treatment promoted interactions of NPR1 and TGA3 with ICE1, and increased the ability of the ICE1–TGA3 complex to transcriptionally activate PR1. Together, our results characterize a previously unrecognized role of ICE1 as an indispensable regulatory node linking low temperature activated- and SA-regulated immunity. Discovery of a crucial role of ICE1 in coordinating multiple signals associated with immunity broadens our understanding of plant–pathogen interactions.
Polarization mapping of a dual-wavelength passively mode-locked fiber ring laser

We report an extensive experimental study of a dual-wavelength (1530 and 1560 nm) passively mode-locked fiber laser in a ring configuration with strict control of the polarization state. Different types of laser operation are identified, which are classified into ten mode locking regimes (solitons-noise-like pulsing, solitons–solitons, solitons-CW, bound solitons-CW, solitons (1530 nm), CW-solitons, CW-bound solitons, Q-switched-like noise-like pulsing, steady noise-like pulsing at 1530 nm and intermittent mode locking), which are mapped in terms of the polarization settings (ellipticity and azimuth). The resulting map establishes, in a clear and repeatable way, the relation existing between each mode locking regime and the polarization adjustment, which allows controlling at the same time intracavity losses, the gain profile, the cavity spectral transfer function, as well as the nonlinear switching characteristic.
Evaluating the performance portability of SYCL across CPUs and GPUs on bandwidth-bound applications

In this paper, we evaluate the portability of the SYCL programming model on some of the latest CPUs and GPUs from a wide range of vendors, utilizing the two main compilers: DPC++ and hipSYCL/OpenSYCL. Both compilers currently support GPUs from all three major vendors; we evaluate performance on the Intel(R) Data Center GPU Max 1100, the NVIDIA A100 GPU, and the AMD MI250X GPU. Support on CPUs currently is less established, with DPC++ only supporting x86 CPUs through OpenCL, however, OpenSYCL does have an OpenMP backend capable of targeting all modern CPUs; we benchmark the Intel Xeon Platinum 8360Y Processor (Ice Lake), the AMD EPYC 9V33X (Genoa-X), and the Ampere Altra platforms. We study a range of primarily bandwidth-bound applications implemented using the OPS and OP2 DSLs, evaluate different formulations in SYCL, and contrast their performance to “native” programming approaches where available (CUDA/HIP/OpenMP). On GPU architectures SCYL on average even slightly outperforms native approaches, while on CPUs it falls behind - highlighting a continued need for improving CPU performance. While SYCL does not solve all the challenges of performance portability (e.g. needing different algorithms on different hardware), it does provide a single programming model and ecosystem to target most current HPC architectures productively.
Impact of climatic disturbances on the chemical compositions and metabolites of Salvia officinalis

Abstract Aromatic and medicinal plants in ecosystems are subject to various climatic disturbances that impact their morphological and physiological processes. Although plants have mechanisms to adapt to their climatic conditions, such as periods of drought and lack of precipitation, their metabolism is still affected. This study aimed to predict and evaluate the behavior of Salvia officinalis under climatic disturbances. Over a period of 4 years in a controlled environment, three treatments were applied to the plant: Treatment 1 with normal monthly average temperature and precipitation in the first year; Treatment 2 with a temperature increase of 5°C and a 50% reduction in water supply in the second year; and Treatment 3 with a temperature increase of 10°C and a 75% reduction in water supply in the fourth year. The results show that the percentage of primary metabolites, including nutritional values, changed with increasing temperature and decreasing precipitation. Treatment 1 had 7.13% protein, 6.21% carbohydrate, 1.35% lipid, and 4% dietary fiber, while Treatment 2 had 7.05% protein, 5.12% carbohydrate, 1.01% lipid, and 3.01% dietary fiber, and Treatment 3 had 6.86% protein, 3.02% carbohydrate, 0.52% lipid, and 2.34% dietary fiber. The mineral composition of the plant also changed with each treatment, with Mg decreasing from 10.02 to 8.55 to 0.05%, Fe decreasing from 8.18 to 8 to 7.62%, K decreasing from 5.55 to 5.05 to 4.02%, Mn decreasing from 5.54 to 5.11 to 3.48%, Ca decreasing from 4.65 to 2.75 to 1.23%, and P decreasing from 3.37 to 3.05 to 2.25%. Regarding secondary metabolites, the percentage of alkaloids, flavonoids, saponins, coumarins, tannins, and essential oil yield changed as well. Treatment 2 showed an increase in secondary metabolites, while Treatment 3 showed a decrease. Alkaloids increased from 9.56 to 13.68 to 11.3%, flavonoids increased from 7.53 to 13.48 to 10.49%, saponins increased from 5.23 to 7.44 to 6%, coumarins increased from 3.35 to 4.85 to 3.99%, tannins increased from 2.26 to 3.22 to 2.62%, and essential oil yield increased from 0.53 to 0.80 to 0.62%. Gas chromatography analysis revealed that the major compounds of the essential oils of Salvia officinalis, such as α-thujone, manool, β-caryophyllene, α-humulene, viridiflorol, 1,8-cineol, and camphor, were also modified by temperature and water stress.
symbSODA: Configurable and Verifiable Orchestration Automation for Active Malware Deception

Malware is commonly used by adversaries to compromise and infiltrate cyber systems in order to steal sensitive information or destroy critical assets. Active Cyber Deception (ACD) has emerged as an effective proactive cyber defense against malware to enable misleading adversaries by presenting fake data and engaging them to learn novel attack techniques. However, real-time malware deception is a complex and challenging task because (1) it requires a comprehensive understanding of the malware behaviors at technical and tactical levels in order to create the appropriate deception ploys and resources that can leverage this behavior and mislead malware, and (2) it requires a configurable yet provably valid deception planning to guarantee effective and safe real-time deception orchestration. This article presents symbSODA, a highly configurable and verifiable cyber deception system that analyzes real-world malware using multipath execution to discover API patterns that represent attack techniques/tactics critical for deception, enables users to create their own customized deception ploys based on the malware type and objectives, allows for constructing conflict-free Deception Playbooks, and finally automates the deception orchestration to execute the malware inside a deceptive environment. symbSODA extracts Malicious Sub-graphs (MSGs) consisting of WinAPIs from real-world malware and maps them to tactics and techniques using the ATT&CK framework to facilitate the construction of meaningful user-defined deception playbooks. We conducted a comprehensive evaluation study on symbSODA using 255 recent malware samples. We demonstrated that the accuracy of the end-to-end malware deception is 95% on average, with negligible overhead using various deception goals and strategies. Furthermore, our approach successfully extracted MSGs with a 97% recall, and our MSG-to-MITRE mapping achieved a top-1 accuracy of 88.75%. Our study suggests that symbSODA can serve as a general-purpose Malware Deception Factory to automatically produce customized deception playbooks against arbitrary malware behavior.
The effect of ACVR1B/TGFBR1/ACVR1C signaling inhibition on oocyte and granulosa cell development during in vitro growth culture

The signals of the transforming growth factor β (TGF-β) superfamily play a critical role in follicular development in mammals. ACVR1B/TGFBR1/ACVR1C receptors mediate the signaling of several TGF-β superfamily ligands in granulosa cells. Although the requirement for ACVR1B/TGFBR1/ACVR1C receptor signaling in follicular development has been confirmed using mutant mouse models, the detailed roles of the signaling in granulosa cell and oocyte development have not been clearly defined. In the present study, we examined the requirement for ACVR1B/TGFBR1/ACVR1C receptor signaling in granulosa cells using an in vitro growth culture of oocyte-granulosa cell complexes (OGCs) and SB431542, a potent inhibitor of the receptor signaling. Although cumulus-oocyte complexes isolated from the control OGCs were able to undergo cumulus expansion, those isolated from OGCs grown with the inhibitor were not competent, even in the presence of in vivo-grown oocytes. The diameter of the oocytes in the SB431542-treated OGCs was comparable with that of the control; however, these oocytes were not competent for complete meiotic maturation or preimplantation development. Therefore, ACVR1B/TGFBR1/ACVR1C receptor signaling is not required for oocytes to increase their volume but is essential for the normal development of cumulus cells and oocyte developmental competence.