Miracle-dz/UniFAR-FTUs huggingface dataset:
Click-Pixel Cognition Fusion Network With Balanced Cut for Interactive Image Segmentation

Interactive image segmentation (IIS) has been widely used in various fields, such as medicine, industry, etc. However, some core issues, such as pixel imbalance, remain unresolved so far. Different from existing methods based on pre-processing or post-processing, we analyze the cause of pixel imbalance in depth from the two perspectives of pixel number and pixel difficulty. Based on this, a novel and unified Click-pixel Cognition Fusion network with Balanced Cut (CCF-BC) is proposed in this paper. On the one hand, the Click-pixel Cognition Fusion (CCF) module, inspired by the human cognition mechanism, is designed to increase the number of click-related pixels (namely, positive pixels) being correctly segmented, where the click and visual information are fully fused by using a progressive three-tier interaction strategy. On the other hand, a general loss, Balanced Normalized Focal Loss (BNFL), is proposed. Its core is to use a group of control coefficients related to sample gradients and forces the network to pay more attention to positive and hard-to-segment pixels during training. As a result, BNFL always tends to obtain a balanced cut of positive and negative samples in the decision space. Theoretical analysis shows that the commonly used Focal and BCE losses can be regarded as special cases of BNFL. Experiment results of five well-recognized datasets have shown the superiority of the proposed CCF-BC method compared to other state-of-the-art methods. The source code is publicly available at https://github.com/lab206/CCF-BC.
Recognition and segmentation of apple fruits in natural environments

By improving the Mask R-CNN model, the performance of the model is improved for recognizing and segmenting apples in the orchard that are in natural environments such as different light, different weather and overlapping occlusion. Firstly, the dual-channel SE module is introduced into the feature extraction network, secondly, the anchor frames are modified according to the actual exposed proportion and area of the apples, and finally, the NMS is improved to Soft-NMS to enhance the model's recognition ability for apple identification and segmentation in natural environments. The results of the experiments using apple images from real orchard environments: Pixel Acc was 98.4%, mean intersection and Mean IoU was 78.8%, class intersection and Class IoU was 59.4%, and Class Mean Acc was 84.8%. The results show that the improved model in this paper gives better results than the original Mask R-CNN model for apple recognition and segmentation, as well as some other models that are widely used.
A single-phonon directional coupler

Integrated photonics has enabled countless technologies in telecommunications, spectroscopy, metrology, quantum optics, and quantum information processing. Using highly confined guided optical modes is the key that has made integrated circuits possible and has lead to scaling of complex designs, benefiting from their small footprint. At the same time, the field of quantum acoustics has recently gained significant attention due to its various potential advantages over its photonic counterparts, including smaller mode volume, lower energy, and orders of magnitude slower propagation speeds, as well as the potential for interconnecting distinct quantum systems. Developing analogous integrated phononic technology is critical for realizing the full potential of phonons and could lead to groundbreaking new applications, such as scalable quantum computing and hybrid quantum devices. In this work, we demonstrate for the first time a 4-port directional coupler for quantum mechanical excitations - a crucial component for integrated phononic circuits. Adjusting the length of the coupling region allows to realize phononic beam splitters with varying splitting ratios. By sending a single-phonon Fock state onto one of these phononic splitters, we demonstrate the capability of using the directional coupler directly in the quantum regime. Our work provides an essential step towards an integrated phononic platform for both classical and quantum technologies applications.
An adaptive local refinement algorithm for quadrilateral mesh

Based on the adaptive finite element algorithm of the numerical model, the mesh is automatically coarsened by element merging for the grid structure of the quadrilateral, which aims to simplify the simulation model and improve the simulation calculation speed. First, the fine mesh is directly converted into pure geometric elements according to the element nodes, and then the mesh elements are redivided according to the boundary hard points and internal geometric hard lines and mesh scale. Extract the geometric boundaries of each different attribute subregion that needs to be coarsened, and then smooth the geometric boundaries and select the key boundary nodes to form the shape boundaries of the coarse mesh. The polygon area formed by these boundary nodes is remeshed to make the mesh size meet the coarsening requirements. According to the above ideas, this paper finally gives the specific program flow of coarsening on the quadrilateral grid.
An Improved Masking Strategy for Self-supervised Masked Reconstruction in Human Activity Recognition

Masked reconstruction serves as a fundamental pretext task for self-supervised learning, enabling the model to enhance its feature extraction capabilities by reconstructing the masked segments from extensive unlabeled data. In human activity recognition, this pretext task employed a masking strategy centered on the time dimension. However, this masking strategy fails to fully exploit the inherent characteristics of wearable sensor data and overlooks the inter-channel information coupling, thereby limiting its potential as a powerful pretext task. To address these limitations, we propose a novel masking strategy called Channel Masking. It involves masking the sensor data along the channel dimension, thereby compelling the encoder to extract channel-related features while performing the masked reconstruction task. Moreover, Channel Masking can be seamlessly integrated with masking strategies along the time dimension, thereby motivating the self-supervised model to undertake the masked reconstruction task in both the time and channel dimensions. Integrated masking strategies are named Time-Channel Masking and Span-Channel Masking. Finally, we optimize the reconstruction loss function to incorporate the reconstruction loss in both the time and channel dimensions. We evaluate proposed masking strategies on three public datasets, and experimental results show that the proposed strategies outperform prior strategies in both self-supervised and semi-supervised scenarios.
Sentiment Analysis of Twitter Posts on Global Conflicts

Sentiment analysis of social media data is an emerging field with vast applications in various domains. In this study, we developed a sentiment analysis model to analyze social media sentiment, especially tweets, during global conflicting scenarios. To establish our research experiment, we identified a recent global dispute incident on Twitter and collected around 31,000 filtered Tweets for several months to analyze human sentiment worldwide.
Short-term wind speed prediction model based on parallel integration of multiple networks

Wind speed prediction is of great importance for the control of wind power generation. For the problem of insufficient accuracy in wind speed prediction, this paper proposes a Multi-Network Parallel Integration Model (MNPIM), which is a combination of LSTM, GRU, RNN, ANN and a differential evolution algorithm to assign weights to the output of each sub-model in order to improve the accuracy of wind speed prediction. algorithm is used to assign weights to the output of each sub-model in order to improve the accuracy of wind speed prediction. The modelling and prediction of wind speed of a wind farm in Gansu Province is taken as an example, and the cross-validation method is introduced to partition the data set and compare with the existing LSTM, GRU, RNN, LR and GPR prediction methods.
Are Adakites Slab Melts or High-pressure Fractionated Mantle Melts?

Adakites are unusual felsic igneous rocks commonly associated with asthenospheric slab window opening or fast subduction of a young ( < 25 Ma) oceanic plate that may allow slab melting at shallow depths. Their genesis has been extensively debated, as they are also observed in other geodynamic settings where thermal models do not predict slab melting in the fore-arc region. Here, we present a new approach that provides new constraints on adakite petrogenesis in hot subduction zones (e.g. the Philippines) and above an asthenospheric window (e.g. Baja California, Mexico). We use amphibole compositions to estimate magma storage depths and the composition of the host melts to test the hypothesis that adakites are pristine slab melts. We ﬁnd that adakites from the Philippines and Baja California fore-arcs formed in two distinct petrogenetic scenarios: in the Philippines, water-rich mantle melts stalled and crystallized within lower and upper crustal magma storage regions to produce silica-rich melts with an adakitic signature; in Baja California, slab melts that percolated through the mantle wedge mixed or mingled with water-rich mantle melts within a lower crustal ( (cid:2) 30 km depth) magma storage region before stalling in the upper arc crust ( (cid:2) 7–15 km depth). Alternatively, the Baja California adakites may represent mixing products between high-pressure differentiated mantle melts and mantle melts in a lower crustal magma reservoir, periodically reﬂuxed by mantle melts. Thus, slab melting is not necessarily required to produce an adakitic geochemical ﬁngerprint in hot subduction zones. The hot downgoing plate may cross the ‘adakitic window’ and melt in speciﬁc geodynamic settings such as the opening of a slab tear, as beneath Baja California.
The absence of yeast Pex23 and Pex29 results in a mitochondrial fusion defect

Pex23 family proteins are membrane proteins of the endoplasmic reticulum that play a role in peroxisome and lipid body formation. The yeast Hansenula polymorpha contains four members: Pex23, Pex24, Pex29 and Pex32. We previously showed that the loss of Pex24 or Pex32 results in severe peroxisomal defects, caused by reduced peroxisome-endoplasmic reticulum membrane contact sites. We now analyzed whether the absence of Pex23 proteins affects other organelles. Vacuoles were normal in all deletion strains. The number of lipid droplets was reduced in pex23 and pex29, but not in pex24 and pex32, indicating that peroxisome and lipid droplet formation require different Pex23 proteins. In pex23 and pex29 cells, mitochondria were fragmented and clustered. This phenotype was not suppressed by an artificial mitochondria-endoplasmic reticulum tether, indicating that the abnormalities were not caused by reduced membrane contact sites. Deletion of DNM1 in pex23 cells partially suppressed the phenotype. Also, the level of the mitochondrial fusion protein Fzo1 was reduced in pex23 and pex29 cells. These observations indicate that certain Pex23 family proteins are required for normal mitochondrial fusion.
A Multi-Scale Study of Thalamic State-Dependent Responsiveness

The thalamus is the brain’s central relay station, orchestrating sensory processing and cognitive functions. However, how thalamic function depends on internal and external states, is not well understood. A comprehensive understanding would necessitate the integration of single cell dynamics with their collective behaviour at population level. For this we propose a biologically realistic mean-field model of the thalamus, describing the dynamics of thalamocortical relay neurons (TC) and thalamic reticular neurons (RE). With this we perform a multi-scale study of thalamic responsiveness and its dependence on cell, synaptic, and brain states. Based on existing single-cell experiments we show that: The transition between tonic and burst states of TC cells acts as a linear-nonlinear switch in the thalamic response to stimuli. In the awake state, sensory stimuli generate a linear thalamic response while cortical input to the thalamus generates a nonlinear response. And that stimulus response and information transfer are controlled by cortical input and synaptic noise, which both suppress responsiveness. In addition, synaptic noise acts as an equalizer between thalamic response at different states and diffuses state transitions between tonic-bursting and awake-sleep states. Finally, the model replicates spindles within a sleep-like state, reducing its responsiveness. This study results in new insight on the brain-state dependent function of the thalamus. In addition, the development of a novel thalamic mean-field model provides a new a tool for incorporating detailed thalamic dynamics in large scale brain simulations. This will help to bridge the gap between computational neuroscience, behavioral experiments, and the study of brain diseases.
When is gene expression noise advantageous?

The variability of gene expression levels, also known as gene expression noise, is an evolvable trait subject to selection. While gene expression noise is detrimental in constant environments where the expression level is under stabilizing selection, it may be beneficial in changing environments when the phenotype is far from the optimum. However, expression noise propagates along the gene network, making the evolution of connected genes interdependent. Here, we explore how their position in the gene network constrains the evolution of genes under selection using an in silico evolution experiment. We simulate the evolution of populations of model gene regulatory networks under directional and fluctuating selection on the gene expression level while allowing the basal expression level and expression noise level to mutate. We find that expression noise is only transiently favoured under directional selection, but high levels of noise can be maintained in a fluctuating selection regime. Furthermore, target genes, regulated by other genes, were more likely to increase their gene-specific expression noise than regulator genes. These findings suggest that both the mean and variance of gene expression levels respond to selection due to changing environments – and do so in a network-dependent manner. They further point at gene expression noise as a putative mechanism for populations to escape extinction when facing environmental changes.
Longitudinal Effects of Trapped Homs in Shanghai Coherent Light Facility

Shanghai Coherent Light Facility (SCLF), a superconducting accelerated structure-baesd FEL device, is now under development at Shanghai Institute of Applied Physics, Chinese Academy of Sciences. We investigate effects of cryogenic losses caused by trapped longitudinal high order modes (HOM). Results of calculations are presented for losses caused by HOMs excitation in the acceleration RF system of the continues-wave (CW) linac of SCLF.
Picturesque atmosphere: in-between the past and present

Abstract The picturesque refers to an influential genre as well as a critical period during which the aesthetic culture of the Enlightenment was blended to form the Romanticist face of the age. Though it means ‘picture-like’ etymologically, the picturesque goes beyond being an eye-based scene and covers the other senses while aiming to provide a scenario with multi-sensory experiences for ramblers on site. Regarding this disposition, the picturesque atmosphere denotes a bridge in-between the past and present with its role in the theories of aesthetics. In this framework, this article aims to read the eighteenth- and nineteenth-century picturesque by referring to the phenomenological theories of the spatial atmosphere of the twentieth and twenty-first centuries. Our research demonstrated that the atmosphere of picturesque landscape designs can be conveyed strongly through spatial representations in different art forms. In doing this, the paper proposes the concept of the picturesque atmosphere as a tool to read the spatiality, especially in art branches, mainly including painting. Therefore, a reading model to examine the spatiality in the picturesque paintings was proposed at the end of the paper, by drawing from the theories of both the picturesque and spatial atmosphere.
Factors influencing Agrobacterium-mediated genetic transformation efficiency in wheat

Assessment of the efficiency of Agrobacterium tumefaciens mediated transformation in four bread wheat varieties was focused and upon optimization of experiments done to obtain tangible results. The four varieties namely Fielder, Navojoa, Baj and Kachu/saul were transformed with optimized protocols, subsequently randomly selected from selection medium amalgamated with phosphinothricin (Glufosinate). Initially the variety Fielder was proceeded with 36 different concentrations of synthetic auxins 2,4-D and Picloram as 36 treatments. The treatment 30 (48 μg of 2,4-D and 64 μg of Picloram) has shown higher efficiency and is comparable in terms of the three traits studied. Additionally, antioxidants and growth regulators were adjusted to obtain better result towards reasonable transformation frequency. Based on the optimization for the variety Fielder, additional varieties were also tested and selected against the selectable marker PPT. Selected genotypes were subjected for gusA or Bar gene PCR amplification. The result revealed the frequency of transgenesis with the range of 60-70% with the varieties studied, however the whole experiment needs further repetitions for confirmatory result. Transgenic genotypes of the Fielder variety showed moderate to strong GUS expression in leaves, anthers, seeds, seed coats, roots compare to non-transgenic control plant tissues. PPT leaf painting assay showed the lack of necrosis on painted area of leaves in transgenic genotypes compared to the non-transgenic ones.
Measuring Cultural Relatedness Using Multiple Seriation Ordering Algorithms

Seriation is a long-standing archaeological method for relative dating that has proven effective in probing regional-scale patterns of inheritance, social networks, and cultural contact in their full spatiotemporal context. The orderings produced by seriation are produced by the continuity of class distributions and uni-modality of class frequencies, properties that are related to social learning and transmission models studied by evolutionary archaeologists. Linking seriation to social learning and transmission enables one to consider ordering principles beyond the classic unimodal curve. Unimodality is a highly visible property that can be used to probe and measure the relationships between assemblages, and it was especially useful when seriation was accomplished with simple algorithms and manual effort. With modern algorithms and computing power, multiple ordering principles can be employed to better understand the spatiotemporal relations between assemblages. Ultimately, the expansion of seriation to additional ordering algorithms allows us an ability to more thoroughly explore underlying models of cultural contact, social networks, and modes of social learning. In this paper, we review our progress to date in extending seriation to multiple ordering algorithms, with examples from Eastern North America and Oceania.
Knowledge Graph Datasets for Recommendation

In the era of daily information overload, personalized retrieval applications represent a crucial solution to provide suggestions to users. The research and industrial community have devoted an unprecedented effort to propose approaches and architectures to extract relevant and tailored information from every shred of knowledge. Inspired by the advances in knowledge graph, Graph Convolutional Networks, Link Prediction, and Recommender Systems research, this study aims to meet their cutting-edge research needs of holistic datasets by largely expanding the information available for two well-known recommendation datasets in the book and movie domains, i.e., LibraryThing and MovieLens 25M. We collect the associated knowledge graphs (KGs) for each of them and publish a mapping for each item in the two datasets with the corresponding entities in the original Wikidata, DBpedia, and Freebase KGs. Our work is available at https://github.com/sisinflab/Augmented-and-Linked-Open-Datasets-for-Recommendation.
Linkages between Boundary-Layer Structure and the 1 Development of Nocturnal Low-Level Jets in Central

In the Southern Great Plains, nocturnal low-level jets (LLJs) develop 9 frequently after sunset and play an important role in the transport and dispersion of 10 moisture and atmospheric pollutants. However, our knowledge regarding the LLJ 11 evolution and its feedback on the structure of the nocturnal boundary layer (NBL) is 12 still limited. In the present study, NBL characteristics and their interdependencies 13 with the LLJ evolution are investigated using data sets collected across the 14 Oklahoma City metropolitan area during the Joint Urban field experiment in July 15 2003 and from three-dimensional simulations with the Weather Research and 16 Forecasting (WRF) model. The strength of the LLJs and turbulent mixing in the NBL 17 both increase with the geostrophic forcing. During the nights with the strongest LLJs, 18 turbulent mixing persisted after sunset in the NBL and a strong surface temperature 19 inversion did not develop. However, the strongest increase in LLJ speed relative to 20 the mixed layer wind speed in the daytime convective boundary layer (CBL) 21 occurred when the geostrophic forcing was relatively weak and thermally induced 22 turbulence in the CBL was strong. Under these conditions, turbulent mixing at night 23 was typically much weaker and a strong surface-based inversion developed. 24 Sensitivity tests with the WRF model confirm that weakening of turbulent mixing 25 during the decay of the CBL in the early evening transition is critical for LLJ 26 formation. The cessation of thermally induced CBL turbulence during the early 27