Miracle-dz/UniFAR-FTUs huggingface dataset:
Benchmark problems for transcranial ultrasound simulation: Intercomparison of compressional wave models

Computational models of acoustic wave propagation are frequently used in transcranial ultrasound therapy, for example, to calculate the intracranial pressure field or to calculate phase delays to correct for skull distortions. To allow intercomparison between the different modeling tools and techniques used by the community, an international working group was convened to formulate a set of numerical benchmarks. Here, these benchmarks are presented, along with intercomparison results. Nine different benchmarks of increasing geometric complexity are defined. These include a single-layer planar bone immersed in water, a multi-layer bone, and a whole skull. Two transducer configurations are considered (a focused bowl and a plane piston operating at 500 kHz), giving a total of 18 permutations of the benchmarks. Eleven different modeling tools are used to compute the benchmark results. The models span a wide range of numerical techniques, including the finite-difference time-domain method, angular spectrum method, pseudospectral method, boundary-element method, and spectral-element method. Good agreement is found between the models, particularly for the position, size, and magnitude of the acoustic focus within the skull. When comparing results for each model with every other model in a cross-comparison, the median values for each benchmark for the difference in focal pressure and position are less than 10% and 1 mm, respectively. The benchmark definitions, model results, and intercomparison codes are freely available to facilitate further comparisons.
The decision problem for perfect matchings in dense hypergraphs

Given 1 ≤ ℓ < k and δ ≥ 0, let PM ( k, ℓ, δ ) be the decision problem for the existence of perfect matchings in n -vertex k -uniform hypergraphs with minimum ℓ -degree at least δ (cid:0) n − ℓ k − ℓ (cid:1) . For k ≥ 3, the decision problem in general k -uniform hypergraphs, equivalently PM ( k, ℓ, 0), is one of Karp’s 21 NP-complete problems. Moreover, for k ≥ 3, a reduction of Szyma´nska showed that PM ( k, ℓ, δ ) is NP-complete for δ < 1 − (1 − 1 /k ) k − ℓ . A breakthrough by Keevash, Knox and Mycroft [STOC ’13] resolved this problem for ℓ = k − 1 by showing that PM ( k, k − 1 , δ ) is in P for δ > 1 /k . Based on their result for ℓ = k − 1, Keevash, Knox and Mycroft conjectured that PM ( k, ℓ, δ ) is in P for every δ > 1 − (1 − 1 /k ) k − ℓ . In this paper it is shown that this decision problem for perfect matchings can be reduced to the study of the minimum ℓ -degree condition forcing the existence of fractional perfect matchings. That is, we hopefully solve the “computational complexity” aspect of the problem by reducing it to a well-known extremal problem in hypergraph theory. In particular, together with existing results on fractional perfect matchings, this solves the conjecture of Keevash, Knox and Mycroft for ℓ ≥ 0 . 4 k .
CFD simulation of particle-fluid two-phase flow in fluidized beds

Advanced CFD simulation has been regarded as one of important tools for dealing with the complicated non-linear fluid dynamics in the fluidized beds.Different momentum balances of particles and fluid phases in Eulerian-Eulerian models have been proposed due to different opinions on fluid-particle and particle-particle interactions.Particle viscous force,solid pressure force and inter-phase drag force are discussed in this paper.Then,authors provided a simple hydrodynamic model based on the two-fluid theory,which considered the effect of discrete particles on both the fluid-and solid-phase momentum equations under a quasi-equilibrium state.One of its main features is that the characteristic length in the model is of the order of the particle diameter.Numerical simulations were conducted in the platform of a commercial software package,CFX 4.4,by adding user-defined Fortran subroutines.After the independence of grid size,time step and the maximum solid volume fraction were explored,case studies including homogeneous fluidization of liquid-solid system,homogenous/aggregative fluidization of Geldart A particle and bubbling/collapsing/jetting fluidization of Geldart B/D particle for gas-solid system were conducted in 2D/3D fluidized beds.The majority of results were compared with classic theories,experimental data and simulations in the literature and good agreements were obtained,which indicates that this model can be used to predict the fluid dynamics of the dense particle-fluid two-phase flow in the fluidized beds.
The New Advancement and Trend of Inertial Navigation Technology

In this paper, the history of inertial navigation technology is introduced and advancement and present development status of the up-to-date inertial sensors are described as well as some state-of-the-art inertial measurement units and their superior specifications are presented. Meanwhile, the application fields of inertial navigation technology are explained, with emphasizing that the nautical applications and development of shipborne inertial navigation systems are expounded. In conclusion, as new inertial sensors springing up and maturing, the hybrid navigation system based on inertial navigation system would be one important orientation of navigation technology in the near future.
PGMax: Factor Graphs for Discrete Probabilistic Graphical Models and Loopy Belief Propagation in JAX

PGMax is an open-source Python package for (a) easily specifying discrete Probabilistic Graphical Models (PGMs) as factor graphs; and (b) automatically running efficient and scalable loopy belief propagation (LBP) in JAX. PGMax supports general factor graphs with tractable factors, and leverages modern accelerators like GPUs for inference. Compared with existing alternatives, PGMax obtains higher-quality inference results with up to three orders-of-magnitude inference time speedups. PGMax additionally interacts seamlessly with the rapidly growing JAX ecosystem, opening up new research possibilities. Our source code, examples and documentation are available at https://github.com/deepmind/PGMax.
A Multi-Task Recurrent Neural Network for End-to-End Dynamic Occupancy Grid Mapping

A common approach for modeling the environment of an autonomous vehicle are dynamic occupancy grid maps, in which the surrounding is divided into cells, each containing the occupancy and velocity state of its location. Despite the advantage of modeling arbitrary shaped objects, the used algorithms rely on hand-designed inverse sensor models and semantic information is missing. Therefore, we introduce a multi-task recurrent neural network to predict grid maps providing occupancies, velocity estimates, semantic information and the driveable area. During training, our network architecture, which is a combination of convolutional and recurrent layers, processes sequences of raw lidar data, that is represented as bird’s eye view images with several height channels. The multi-task network is trained in an end-to-end fashion to predict occupancy grid maps without the usual preprocessing steps consisting of removing ground points and applying an inverse sensor model. In our evaluations, we show that our learned inverse sensor model is able to overcome some limitations of a geometric inverse sensor model in terms of representing object shapes and modeling freespace. Moreover, we report a better runtime performance and more accurate semantic predictions for our end-to-end approach, compared to our network relying on measurement grid maps as input data.
The crowding effect on the melting of short DNA: Comparison with experiments

Abstract We study the effect of crowders on the melting profile of homogeneous and heterogeneous DNA molecules. We find out the melting profile of short DNA molecules and compare our findings with the experiments. We consider some random distribution of crowders along the chain, and by finding out the best match with the experiments, we attempt to identify the location of crowders in the experimental findings of Ghosh [1]. We also study the melting of homogeneous DNA molecules of different lengths (25, 50, 75) in the presence of only one crowder in the chain. By varying the location of the crowder from one end to the other, we find that the melting temperature is susceptible to the location of the crowder at the ends. At the same time, there is minimal effect on the melting temperature due to the location of the crowder. In vivo, the strength of a crowders may vary along the chain. We study the melting of long heterogeneous chain in presence of five crowders of different strength. We find that there is a significant variation in the melting process of DNA in presence of crowders of variable strength.
A.I. and Data-Driven Mobility at Volkswagen Financial Services AG

Machine learning is being widely adapted in industrial applications owing to the capabilities of commercially available hardware and rapidly advancing research. Volkswagen Financial Services (VWFS), as a market leader in vehicle leasing services, aims to leverage existing proprietary data and the latest research to enhance existing and derive new business processes. The collaboration between Information Systems and Machine Learning Lab (ISMLL) and VWFS serves to realize this goal. In this paper, we propose methods in the fields of recommender systems, object detection, and forecasting that enable data-driven decisions for the vehicle life-cycle at VWFS.
Fermionic vacuum polarization induced by a non-Abelian vortex

In this paper, we analyze the fermionic condensate (FC) and the vacuum expectation value (VEV) of the energy-momentum tensor associated with an isospin-$1/2$ charged massive fermionic field induced by the presence of a $SU(2)$ vortex, taking into account the effect of the conical geometry produced by this object. We consider the vortex as an idealized topological defect, i.e., very thin, straight and carrying a magnetic flux running along its core. Besides the direct coupling of the fermionic field with the iso-vector gauge field, we also admit the coupling with the scalar sector of the non-Abelian vortex system, expressed as a vector in the three-dimensional isospace. Due to this interaction, the FC is expressed as the sum of two contributions associated with the two different effective masses for the $\pm 1/2$ fermionic components of the isospin operator, $\tau^3/2$. The VEV of the energy-tensor also presents a similar structure. The vacuum energy density is equal to the radial and axial stresses. As to the azimuthal one, it is expressed in terms of the radial derivative of energy-density. Regarding to the magnetic flux, both, the FC and the VEV of the energy-momentum tensor, can be positive or negative. Another interesting consequence of the interaction with the bosonic sector, the FC and VEV of the energy-momentum tensor, present different intensity for different values of the ratio between the scalar coupling constant and the mass of the fermionic field. This is a new feature that the system presents.
Conditional generative data-free knowledge distillation

Knowledge distillation has made remarkable achievements in model compression. However, most existing methods require the original training data, which is usually unavailable due to privacy and security issues. In this paper, we propose a conditional generative data-free knowledge distillation (CGDD) framework for training lightweight networks without any training data. This method realizes efficient knowledge distillation based on conditional image generation. Specifically, we treat the preset labels as ground truth to train a conditional generator in a semi-supervised manner. The trained generator can produce specified classes of training images. For training the student network, we force it to extract the knowledge hidden in teacher feature maps, which provide crucial cues for the learning process. Moreover, an adversarial training framework for promoting distillation performance is constructed by designing several loss functions. This framework helps the student model to explore larger data space. To demonstrate the effectiveness of the proposed method, we conduct extensive experiments on different datasets. Compared with other data-free works, our work obtains state-of-the-art results on CIFAR100, Caltech101, and different versions of ImageNet datasets. The codes will be released.
The prevalence of loneliness across 113 countries: systematic review and meta-analysis

Abstract Objectives To identify data availability, gaps, and patterns for population level prevalence of loneliness globally, to summarise prevalence estimates within World Health Organization regions when feasible through meta-analysis, and to examine temporal trends of loneliness in countries where data exist. Design Systematic review and meta-analysis. Data sources Embase, Medline, PsycINFO, and Scopus for peer reviewed literature, and Google Scholar and Open Grey for grey literature, supplemented by backward reference searching (to 1 September 2021) Eligibility criteria for selecting studies Observational studies based on nationally representative samples (n≥292), validated instruments, and prevalence data for 2000-19. Two researchers independently extracted data and assessed the risk of bias using the Joanna Briggs Institute checklist. Random effects meta-analysis was conducted in the subset of studies with relatively homogeneous research methods by measurement instrument, age group, and WHO region. Results Prevalence data were available for 113 countries or territories, according to official WHO nomenclature for regions, from 57 studies. Data were available for adolescents (12-17 years) in 77 countries or territories, young adults (18-29 years) in 30 countries, middle aged adults (30-59 years) in 32 countries, and older adults (≥60 years) in 40 countries. Data for all age groups except adolescents were lacking outside of Europe. Overall, 212 estimates for 106 countries from 24 studies were included in meta-analyses. The pooled prevalence of loneliness for adolescents ranged from 9.2% (95% confidence interval 6.8% to 12.4%) in South-East Asia to 14.4% (12.2% to 17.1%) in the Eastern Mediterranean region. For adults, meta-analysis was conducted for the European region only, and a consistent geographical pattern was shown for all adult age groups. The lowest prevalence of loneliness was consistently observed in northern European countries (2.9%, 1.8% to 4.5% for young adults; 2.7%, 2.4% to 3.0% for middle aged adults; and 5.2%, 4.2% to 6.5% for older adults) and the highest in eastern European countries (7.5%, 5.9% to 9.4% for young adults; 9.6%, 7.7% to 12.0% for middle aged adults; and 21.3%, 18.7% to 24.2% for older adults). Conclusion Problematic levels of loneliness are experienced by a substantial proportion of the population in many countries. The substantial difference in data coverage between high income countries (particularly Europe) and low and middle income countries raised an important equity issue. Evidence on the temporal trends of loneliness is insufficient. The findings of this meta-analysis are limited by data scarcity and methodological heterogeneity. Loneliness should be incorporated into general health surveillance with broader geographical and age coverage, using standardised and validated measurement tools. Systematic review registration PROSPERO CRD42019131448.
Antiphospholipid syndrome–mediated acute cerebrovascular diseases and long-term outcomes

Objectives The antiphospholipid syndrome (APS) is an autoimmune disease associated with thrombotic and non-thrombotic neurologic manifestations. APS is classified as primary (PAPS) or secondary (SAPS) when it co-exists with another autoimmune disease. We aim to describe the spectrum of acute cerebrovascular disease among patients with APS, their differences between stroke subtypes, and long-term functional outcomes. Methods Retrospective cohort study including adult (≥18 years) patients with APS followed in the stroke clinic of a tertiary-care reference center for autoimmune diseases in Mexico from 2009 to 2019. Results We studied 120 cases; 99 (82.5%) women; median age 43 years (interquartile range 35–52); 63.3% with SAPS. Demographics, comorbidities, and antiphospholipid antibodies (aPL) positivity were similar between APS type and stroke subtypes. Amongst index events, we observed 84 (70%) acute ischemic strokes (AIS), 19 (15.8%) cerebral venous thromboses (CVT), 11 (9.2%) intracerebral hemorrhages (ICH), and six (5%) subarachnoid hemorrhages (SAH). Sixty-seven (55.8%) were known patients with APS; the median time from APS diagnosis to index stroke was 46 months (interquartile range 12–96); 64.7% of intracranial hemorrhages (ICH or SAH) occurred ≥4 years after APS was diagnosed (23.5% anticoagulation-related); 63.2% of CVT cases developed before APS was diagnosed or simultaneously. Recurrences occurred in 26 (22.8%) patients, AIS, in 18 (69.2%); intracranial hemorrhage, in eight (30.8%). Long-term functional outcomes were good (modified Rankin Scale ≤2) in 63.2% of cases, during follow-up, the all-cause mortality rate was 19.2%. Conclusion We found no differences between stroke subtypes and APS types. aPL profiles were not associated with any of the acute cerebrovascular diseases described in this cohort. CVT may be an initial thrombotic manifestation of APS with low mortality and good long-term functional outcome.
Multilingualism in Education: The Lived Experience of the Marginalised Language Learner

Abstract This study explored how minority language speaking learners experience language use in a multilingual classroom. The study was conducted in Binga District, Zimbabwe, where Tonga, a formerly marginalised language, is predominant. This qualitative study is grounded in the multilingual education framework. A sample of 40 learners was drawn from four primary schools. Data were gathered mainly through semi-structured interviews. Findings indicate that the majority of teachers at these schools are either Ndebele or Shona first language speakers, with some having almost no communicative competence in Tonga, the language of the community. This has led to the adoption of English and Ndebele or Shona as the language of teaching and learning (LOTL) in the classroom. Adopting these languages has resulted in the isolation and marginalisation of Tonga learners, who are thereby denied the right to education in the classroom context, leading to negative attitudes towards school and high failure and dropout rates.
Shifting sands: navigating being academic in an evolving sector

ABSTRACT The evolution of the higher education sector has included a strong focus on academic performance despite increasing workloads and employment precarity, with COVID-19 further disrupting traditional university expectations. Drawing on HERD’s author voices from 2010 to 2020, this reflective review examines the changing nature of academe, mapping the shifts in role and identity that occur through an academic’s career life cycle. The mechanisms to support these developmental journeys are examined, highlighting the role that development agencies and university leaders need to play in supporting the holistic development of academics (and researchers), particularly as expectations evolve. Implications for a post-COVID sector are explored, suggesting this disruptive phase will require more responsive support from universities, developers and university leaders. The paper identifies gaps in research and commentary that warrant further exploration by scholars in the future.
Optimal Control of Energy Storage Based on Fuzzy Correlated-chance Programming

In order to maximize the match between the output of the hybrid wind/photovoltaic/energy storage system and the scheduling curve,the energy storage device is optimized and controlled one day ahead.Owing to the fuzziness of the wind and photovoltaic output,an optimal control method of energy storage is proposed based on a fuzzy correlated-chance programming theory.This method considers the constraints of the energy storage device including the power output and energy constraints,and the matching degree of each time is represented by the credibility value.So the final goal is to maximize the mean value of the total credibility within a day of 96periods.By using the fuzzy simulation based genetic algorithm,the different periods of energy storage charge and discharge power corresponding to the credibility of the maximum mean value can be obtained.Numerical results analysis shows that the proposed optimal control strategy is valid for maximizing the match between the output of the hybrid wind/photovoltaic/energy storage system and the scheduling curve.
Domestic Advanced Manufacturing Equipments Helping the Technical Progress of Power Capacitor in China

This article summarizes the development and application of the homemade advanced manufacturing equipments for power capacitor in China.Important role of the equipments in technical progress of our power capacitor industry is stressed.The technical characteristics of the homemade advanced equipments used for power capacitor key technologies are introduced.At last,some demands and expectations of the homemade advanced equipments are proposed,and it is hoped that play further important roles for the homemade advanced equipment achieve the international advanced level.
Motor memory consolidation in children: The role of awareness and sleep on offline general and sequence-specific learning

Abstract Study aim: The purpose of this study was to investigate the role of sleep and awareness on consolidation of general and Sequence-Specific learning in children. Material and methods: Male participants (n = 48, 10 to 12 years old) were assigned to one of four groups based on awareness and sleep. Acquisition phase took place in the morning (wake groups, 8 ± am) or in the evening (sleep groups, 8 ± pm) followed by a 12 hours retention interval and a subsequent delayed retention test (1 week). Children in the explicit groups were informed about the presence of the sequence, while in the implicit groups were not informed about it. For data analysis in consolidation of general sequence learning and Sequence-Specific Consolidation phases, 2 × 2 × 2 and 2 × 2 × 3 ANOVA with repeated measures on block tests were used respectively. Results: The data provides evidence of offline enhancement of general motor learning after 12 hours which was dependent on sleep and awareness. Moreover, the information persistence after 1-week was significant only in sleep groups. The results also indicated that consolidation of sequence-specific learning was only observed after 12 hours in element duration and it was related to sleep and awareness. Conclusions: The results revealed that sleep wasn’t only an essential factor in enhancement of off-line sequence learning task after 12 hours in children, but performance of the children was dependent on awareness and sleep.
Assessing Human Genome-wide Variation in the Massim Region of Papua New Guinea and Implications for the Kula Trading Tradition

The Massim, a cultural region encompassing the southeastern tip of mainland Papua New Guinea (PNG) and nearby islands, is famous for the Kula trading network, in which different valuables circulate in different directions among the islands. To explore Massim genetic history, we generated genome-wide data from across the region and found variable levels of Papuan-related (indigenous) ancestry, including a novel ancestry associated with Rossel Island, and Austronesian-related ancestry that arrived later. We find genetic evidence for different patterns of contact across PNG, the Massim, and the Bismarck and Solomon Archipelagoes for Austronesian-related vs. Papuan-related ancestry, with more geographic restriction for the latter. Moreover, Kula-practicing groups share more genetic similarity than do other groups, and this likely predates the origin of Kula, suggesting that high between-group contact facilitated the formation of Kula. Our study provides the first comprehensive genome-wide assessment of Massim inhabitants and new insights into the fascinating Kula system.