Miracle-dz/UniFAR-FTUs huggingface dataset:
Understanding the impact of host networking elements on traffic bursts

Conventional host networking features various traffic shaping layers (e.g., buffers, schedulers, and pacers) with complex interactions and wide implications for performance metrics. These interactions can lead to large bursts at various time scales. Understanding the nature of traffic bursts is important for optimal resource provisioning, congestion control, buffer sizing, and traffic prediction but is challenging due to the complexity and feature velocity in host networking. We develop Valinor, a traffic measurement framework that consists of eBPF hooks and measurement modules in a programmable network. Valinor offers visibility into traffic burstiness over a wide span of timescales (nanosecond-to second-scale) at multiple vantage points. We deploy Valinor to analyze the burstiness of various classes of congestion control algorithms, qdiscs, Linux process scheduling, NIC packet scheduling, and hardware offloading. Our analysis counters the assumption that burstiness is primarily a function of the application layer and preserved by protocol stacks, and highlights the pronounced role of lower layers in the formation and suppression of bursts. We also show the limitations of canonical burst countermeasures (e.g., TCP pacing and qdisc scheduling) due to the intervening nature of segmentation offloading and fixed-function NIC scheduling. Finally, we demonstrate that, far from a universal invariant, burstiness varies significantly across host stacks. Our findings under-score the need for a measurement framework such as Valinor for regular burst analysis.
Raga Classification From Vocal Performances Using Multimodal Analysis

Work on musical gesture and embodied cognition suggests a rich complementarity between audio and movement information in musical performance. Pose estimation algorithms now make it possible (in contrast to traditional Motion Capture) to collect rich movement information from unconstrained performances of indefinite length. Vocal performances of Indian art music offer the opportunity to carry out multimodal analysis using this information, combining musician’s body movements (i.e. pose and gesture data) with audio features. In this work we investigate raga identification from 12 s excerpts from a dataset of 3 singers and 9 ragas using the combination of audio and visual representations that are each semantically salient on their own. While gesture based classification is relatively weak by itself, we show that combining latent representations from the pre-trained unimodal networks can surpass the already high performance obtained by audio features.
The power of deep without going deep? A study of HDPGMM music representation learning

In the previous decade, Deep Learning (DL) has proven to be one of the most effective machine learning methods to tackle a wide range of Music Information Retrieval (MIR) tasks. It offers highly expressive learning capacity that can fit any music representation needed for MIR-relevant downstream tasks. However, it has been criticized for sacrificing interpretability. On the other hand, the Bayesian nonparametric (BN) approach promises similar positive properties as DL, such as high flexibility, while being robust to overfitting and preserving interpretability. Therefore, the primary motivation of this work is to explore the potential of Bayesian nonparametric models in comparison to DL models for music representation learning. More specifically, we assess the music representation learned from the Hierarchical Dirichlet Process Gaussian Mixture Model (HDPGMM), an infinite mixture model based on the Bayesian nonparametric approach, to MIR tasks, including classification, auto-tagging, and recommendation. The experimental result suggests that the HDPGMM music representation can outperform DL representations in certain scenarios, and overall comparable.
Latent feature augmentation for chorus detection

In this paper, we introduce LA-Chorus, a chorus detection model based on L atent feature A ugmentation and ResNet-FPN architecture. We make three contributions. Firstly, we propose a method for implicitly augmenting chorus data in the latent space during the training stage. Compared to augmentations on audio surfaces such as time stretching and pitch shifting, latent augmentations indicate changes at a higher level in original audio, thereby increasing the diversity and sufficiency in training. Second, we apply Feature Pyramid Network (FPN) to generate additional embeddings from low dimension to high dimension, consequently achieving a multi-scale training paradigm. Lastly, we release Di-Chorus, a new diversified dataset of 13 gen-res and 14 languages for the community of music structure analysis. In conjunction with other public datasets, we conduct comprehensive experiments to evaluate the performance of our proposed method compared to other state-of-the-art models, where LA-Chorus outperforms other SO-TAs by a considerable margin, meanwhile the proposed latent audio augmentation shows dominant advantages over traditional augmentation methods.
This paper is included in the Proceedings of the 20th USENIX Symposium on Networked Systems Design and Implementation.

Given the wide adoption of disaggregated storage in public clouds, networking is the key to enabling high performance and high reliability in a cloud storage service. In Azure, we choose Remote Direct Memory Access (RDMA) as our transport and aim to enable it for both storage frontend traffic (between compute virtual machines and storage clusters) and backend traffic (within a storage cluster) to fully realize its benefits. As compute and storage clusters may be located in different datacenters within an Azure region, we need to support RDMA at regional scale. This work presents our experience in deploying intra-region RDMA to support storage workloads in Azure. The high complexity
A Theoretical Study of Mountain Barrier Jets over Sloping Valleys

Abstract A shallow-water model is developed to examine the dynamics of mountain-barrier jets over a mesoscale sloping valley between two mountain ridges. In this model, the cold air trapped in the valley is represented by a shallow-water layer that is coupled with the upper-layer flow through a free-slip interface. The pressure gradient exerted from the upper layer plus the pressure gradient generated by the sloping cold layer itself drive the cold air down the valley forming a jet against the surface friction. In the cross-valley direction, the jet-induced Coriolis force is balanced by the pressure gradient force. For a given cross-valley terrain profile, the solution is controlled by eight dimensional environmental parameters. In the nondimensional space, the solution is controlled only by three parameters: the Froude number modified by the ratio between the valley width and the Rossby radius of deformation, the surface drag coefficient normalized by the ratio between the valley depth and the inertial r.
POWER SPECTRAL DENSITY OF FLUCTUATIONS OF BULK AND THERMAL SPEEDS IN THE SOLAR WIND

This paper analyzes solar wind power spectra of bulk and thermal speed fluctuations that are computed with a time resolution of 32 ms in the frequency range of 0.001–2 Hz. The analysis uses measurements of the Bright Monitor of the Solar Wind on board the Spektr-R spacecraft that are limited to 570 km s−1 bulk speed. The statistics, based on more than 42,000 individual spectra, show that: (1) the spectra of bulk and thermal speeds can be fitted by two power-law segments; (2) despite their large variations, the parameters characterizing frequency spectrum fits computed on each particular time interval are very similar for both quantities; (3) the median slopes of the bulk and thermal speeds of the segment attributed to the MHD scale are −1.43 and −1.38, respectively, whereas they are −3.08 and −2.43 in the kinetic range; (4) the kinetic range slopes of bulk and thermal speed spectra become equal when either the ion density or magnetic field strength are high; (5) the break between MHD and kinetic scales seems to be controlled by the ion β parameter; (6) the best scaling parameter for bulk and thermal speed variations is a sum of the inertial length and proton thermal gyroradius; and (7) the above conclusions can be applied to the density variations if the background magnetic field is very low.
Deficiency of Wdr60 and Wdr34 cause distinct neural tube malformation phenotypes in early embryos

Cilia are specialized organelles that extend from plasma membrane, functioning as antennas for signal transduction and are involved in embryonic morphogenesis. Dysfunction of cilia lead to many developmental defects, including neural tube defects (NTDs). Heterodimer WDR60-WDR34 (WD repeat domain 60 and 34) are intermediate chains of motor protein dynein-2, which play important roles in ciliary retrograde transport. It has been reported that disruption of Wdr34 in mouse model results in NTDs and defects of Sonic Hedgehog (SHH) signaling. However, no Wdr60 deficiency mouse model has been reported yet. In this study, piggyBac (PB) transposon is used to interfere Wdr60 and Wdr34 expression respectively to establish Wdr60 PB/PB and Wdr34 PB/PB mouse models. We found that the expression of Wdr60 or Wdr34 is significantly decreased in the homozygote mice. Wdr60 homozygote mice die around E13.5 to E14.5, while Wdr34 homozygote mice die around E10.5 to E11.5. WDR60 is highly expressed in the head region at E10.5 and Wdr60 PB/PB embryos have head malformation. RNAseq and qRT-PCR experiments revealed that Sonic Hedgehog signaling is also downregulated in Wdr60 PB/PB head tissue, demonstrating that WDR60 is also required for promoting SHH signaling. Further experiments on mouse embryos also revealed that the expression levels of planar cell polarity (PCP) components such as CELSR1 and downstream signal molecule c-Jun were downregulated in WDR34 homozygotes compared to wildtype littermates. Coincidently, we observed much higher ratio of open cranial and caudal neural tube in Wdr34 PB/PB mice. CO-IP experiment showed that WDR60 and WDR34 both interact with IFT88, but only WDR34 interacts with IFT140. Taken together, WDR60 and WDR34 play overlapped and distinct functions in modulating neural tube development.
Classification, identification, and reservoir characteristics of intermediate mafic lava flows: a case study in Dongling area, Songliao Basin

Intermediate mafic lava is a special oil and gas reservoir. While its internal structure is an important factor affecting the reservoir properties, the identification of facies and understanding of the relationship between facies architecture and reservoir are limited. This study evaluated the intermediate mafic lava flows of the Yingcheng Formation in the Dongling area of Songliao Basin by analyzing drilling cores, corresponding thin sections, and scanning electron microscope (SEM) images, as well as well-logging and seismic attributes. We also performed helium gas experiments and high-pressure mercury intrusion (HPMI) analysis to assess the physical properties and pore structure of the reservoir, respectively. The results showed that intermediate mafic lava flows develop tabular lava flow, compound lava flow, and hyaloclastite. Three facies showed present diverse well-logging and seismic responses. The intermediate mafic lava facies architecture was divided into crater-proximal facies (CF-PF), medial facies (MF), and distal facies (DF), which were characterized by their vesicles and joints and could be identified through their seismic attributes. The reservoir spaces including vesicles, amygdale inner pores, joint fissures, and dissolution pores predominantly showed oil and gas accumulation. The results of the tests of the reservoir’s physical properties showed that the reservoir quality was best in the CF-PF, which is the main target of oil and gas exploration.
A cytokine-induced spheroid-based in vitro model for studying osteoarthritis pathogenesis

Given the lack of in vitro models faithfully reproducing the osteoarthritis (OA) disease on-set, this work aimed at manufacturing a reliable and predictive in vitro cytokine-based Articular Cartilage (AC) model to study OA progression. Cell spheroids of primary human fetal chondrocytes (FCs) and h-TERT mesenchymal stem cells differentiated chondrocytes (Y201-C) were analysed in terms of growth kinetics, cells proliferation and apoptosis over 10 days of culture, in healthy condition or in presence of cytokines (interleukin-1ß, −6 and TNF-α). Then, the spheroids were assembled into chondrospheres using a bottom-up strategy, to obtain an in vitro cytokines-induced OA model. The resulting chondrospheres were evaluated for gene expression and anabolic ECM proteins. Compared to the healthy environment, the simulated OA environment induced chondrocyte hyperproliferation and apoptotic pathway, decreased expression of anabolic ECM proteins, and diminished biosynthetic activity, resembling features of early-stage OA. These characteristics were observed for both Y201-C and HC at high and low concentrations of cytokines. Both HC and Y201-C demonstrated the suitability for the manufacturing of a scaffold-free in vitro OA model to facilitate studies into OA pathogenesis and therapeutic strategies. Our approach provides a faithful reproduction of early-stage osteoarthritis, demonstrating the ability of obtaining different disease severity by tuning the concentration of OA-related cytokines. Given the advantages in easy access and more reproducible performance, Y201-C may represent a more favourable source of chondrocytes for establishing more standardized protocols to obtain OA models.
“Huoling Shengji granule” for amyotrophic lateral sclerosis: protocol for a multicenter, randomized, double-blind, riluzole parallel controlled clinical trial

Background There is still a large demand for effective treatments to delay disease deterioration in amyotrophic lateral sclerosis (ALS). Typical symptoms of ALS are considered “flaccidity syndrome” in traditional Chinese medicine (TCM). Huoling Shengji Granule (HLSJ) is a TCM formula used to treat flaccidity syndrome. Results of preclinical tests and a previous clinical study support HLSJ as a novel drug for ALS patients. This trial proposed to examine whether a 48-week course of HLSJ is effective and safe for ALS patients diagnosed with the Chinese medicine syndrome of spleen qi insufficiency and kidney yang deficiency. Methods and analysis In this phase II, multicenter, randomized, double-blind, riluzole parallel-controlled, superiority-design study, eligible participants had the equal opportunity to be assigned to receive either HLSJ or riluzole randomly. Eleven specialized ALS centers in Mainland China will recruit 144 patients for this trial. The primary and secondary outcomes included the change in the ALSFRS-R score and the Rasch-Built Overall Amyotrophic Lateral Sclerosis Disability Scale (ROADS) from baseline to Week 48. Discussion Here, we endeavored to evaluate TCM for ALS using a standard evidence-based approach for the first time. In addition, the ROADS, a self-report linear-weighted questionnaire, was selected as a secondary outcome measure. We expect to offer a new reference for the outcome evaluation of ALS trials. Clinical trial registration:http://www.Chictr. org.cn, identifier ChiCTR2100044085.
Human African Trypanosomiasis (sleeping sickness): Current knowledge and future challenges

According to both definitions of US Centers for Disease Control and Prevention and World Health Organization, Neglected Tropical Diseases (NTDs) are a group of preventable and treatable parasitic, viral, and bacterial diseases that affect more than one billion people globally. They generally afflict the more indigent patients of the world and historically have not received as much attention as other diseases. NTDs tend to thrive in low-income regions, where water quality, sanitation and access to health care are substandard. They are common in several countries of Africa, Asia, and Latin America. In this literature review, we want to focus on Human African Trypanosomiasis (HAT), also known as “sleeping sickness”, one of the most common neglected diseases in Africa. It is caused by infection with the subspecies of the parasitic protozoan Trypanosoma brucei, and it is transmitted by the bite of the tsetse fly. It puts 70 million people at risk throughout sub-Saharan Africa and it is usually fatal if untreated or inadequately treated. This review covers several aspects of the disease. We focused our interests on most recent epidemiological data, novel diagnostic methods with their advantages and limitations, new improved treatment and orphan drugs and eradication programs, including vector control, according to a “One Health” approach, to achieve the new goals recently set by WHO.
Phase I trial outcome of amnion cell therapy in patients with ischemic stroke (I-ACT)

Background We proposed a Phase I dose escalation trial to assess the safety of allogeneic human amniotic epithelial cells (hAECs) in stroke patients with a view to informing the design for a Phase II trial. Methods The design is based on 3 + 3 dose escalation design with additional components for measuring MR signal of efficacy as well as the effect of hAECs (2–8 × 106/kg, i.v.) on preventing immunosuppression after stroke. Results Eight patients (six males) were recruited within 24 h of ischemic stroke onset and were infused with hAECs. We were able to increase the dose of hAECs to 8 × 106 cells/kg (2 × 106/kg, n = 3; 4 × 106/kg, n = 3; 8 × 106/kg, n = 2). The mean age is 68.0 ± 10.9 (mean ± SD). The frequencies of hypertension and hyperlipidemia were 87.5%, diabetes was 37.5%, atrial fibrillation was 50%, ischemic heart disease was 37.5% and ever-smoker was 25%. Overall, baseline NIHSS was 7.5 ± 3.1, 7.8 ± 7.2 at 24 h, and 4.9 ± 5.4 at 1 week (n = 8). The modified Rankin scale at 90 days was 2.1 ± 1.2. Supplemental oxygen was given in five patients during hAEC infusion. Using pre-defined criteria, two serious adverse events occurred. One patient developed recurrent stroke and another developed pulmonary embolism whilst in rehabilitation. For the last four patients, infusion of hAECs was split across separate infusions on subsequent days to reduce the risk for fluid overload. Conclusion Our Phase I trial demonstrates that a maximal dose of 2 × 106/kg hAECs given intravenously each day over 2 days (a total of 4 × 106/kg) is safe and optimal for use in a Phase II trial. Clinical trial registration ClinicalTrials.gov, identifier ACTRN12618000076279P.
Exploring the diversity of virulence genes in the Magnaporthe population infecting millets and rice in India

Blast pathogen, Magnaporthe spp. , that infects ancient millet crops such pearl millet, finger millet, foxtail millet, barnyard millet, and rice was isolated from different locations of blast hotspots in India using single spore isolation technique and 136 pure isolates were established. Numerous growth characteristics were captured via morphogenesis analysis. Among the 10 investigated virulent genes, we could amplify MPS1 (TTK Protein Kinase) and Mlc (Myosin Regulatory Light Chain edc4) in majority of tested isolates, regardless of the crop and region where they were collected, indicating that these may be crucial for their virulence. Additionally, among the four avirulence (Avr) genes studied, Avr-Pizt had the highest frequency of occurrence, followed by Avr-Pia. It is noteworthy to mention that Avr-Pik was present in the least number of isolates (9) and was completely absent from the blast isolates from finger millet, foxtail millet, and barnyard millet. A comparison at the molecular level between virulent and avirulent isolates indicated observably large variation both across (44%) and within (56%) them. The 136 Magnaporthe spp isolates were divided into four groups using molecular markers. Regardless of their geographic distribution, host plants, or tissues affected, the data indicate that the prevalence of numerous pathotypes and virulence factors at the field level, which may lead to a high degree of pathogenic variation. This research could be used for the strategic deployment of resistant genes to develop blast disease-resistant cultivars in rice, pearl millet, finger millet, foxtail millet, and barnyard millet.
iTCep: a deep learning framework for identification of T cell epitopes by harnessing fusion features

Neoantigens recognized by cytotoxic T cells are effective targets for tumor-specific immune responses for personalized cancer immunotherapy. Quite a few neoantigen identification pipelines and computational strategies have been developed to improve the accuracy of the peptide selection process. However, these methods mainly consider the neoantigen end and ignore the interaction between peptide-TCR and the preference of each residue in TCRs, resulting in the filtered peptides often fail to truly elicit an immune response. Here, we propose a novel encoding approach for peptide-TCR representation. Subsequently, a deep learning framework, namely iTCep, was developed to predict the interactions between peptides and TCRs using fusion features derived from a feature-level fusion strategy. The iTCep achieved high predictive performance with AUC up to 0.96 on the testing dataset and above 0.86 on independent datasets, presenting better prediction performance compared with other predictors. Our results provided strong evidence that model iTCep can be a reliable and robust method for predicting TCR binding specificities of given antigen peptides. One can access the iTCep through a user-friendly web server at http://biostatistics.online/iTCep/, which supports prediction modes of peptide-TCR pairs and peptide-only. A stand-alone software program for T cell epitope prediction is also available for convenient installing at https://github.com/kbvstmd/iTCep/.
An integrated nitrogen utilization gene network and transcriptome analysis reveal candidate genes in response to nitrogen deficiency in Brassica napus

Nitrogen (N) is an essential factor for crop yield. Here, we characterized 605 genes from 25 gene families that form the complex gene networks of N utilization pathway in Brassica napus. We found unequal gene distribution between the An- and Cn-sub-genomes, and that genes derived from Brassica rapa were more retained. Transcriptome analysis indicated that N utilization pathway gene activity shifted in a spatio-temporal manner in B. napus. A low N (LN) stress RNA-seq of B. napus seedling leaves and roots was generated, which proved that most N utilization related genes were sensitive to LN stress, thereby forming co-expression network modules. Nine candidate genes in N utilization pathway were confirmed to be significantly induced under N deficiency conditions in B. napus roots, indicating their potential roles in LN stress response process. Analyses of 22 representative species confirmed that the N utilization gene networks were widely present in plants ranging from Chlorophyta to angiosperms with a rapid expansion trend. Consistent with B. napus, the genes in this pathway commonly showed a wide and conserved expression profile in response to N stress in other plants. The network, genes, and gene-regulatory modules identified here represent resources that may enhance the N utilization efficiency or the LN tolerance of B. napus.