Belief Evolution Network-based Probability Transformation and Fusion

Smets proposes the Pignistic Probability Transformation (PPT) as the decision layer in the Transferable Belief Model (TBM), which argues when there is no more information, we have to make a decision using a Probability Mass Function (PMF). In this paper, the Belief Evolution Network (BEN) and the full causality function are proposed by introducing causality in Hierarchical Hypothesis Space (HHS). Based on BEN, we interpret the PPT from an information fusion view and propose a new Probability Transformation (PT) method called Full Causality Probability Transformation (FCPT), which has better performance under Bi-Criteria evaluation. Besides, we heuristically propose a new probability fusion method based on FCPT. Compared with Dempster Rule of Combination (DRC), the proposed method has more reasonable result when fusing same evidence

Comparative Component Analysis of Exons with Different Splicing Frequencies

Transcriptional isoforms are not just random combinations of exons. What has caused exons to be differentially spliced and whether exons with different splicing frequencies are subjected to divergent regulation by potential elements or splicing signals? Beyond the conventional classification for alternatively spliced exons (ASEs) and constitutively spliced exons (CSEs), we have classified exons from alternatively spliced human genes and their mouse orthologs (12,314 and 5,464, respectively) into four types based on their splicing frequencies. Analysis has indicated that different groups of exons presented divergent compositional and regulatory properties. Interestingly, with the decrease of splicing frequency, exons tend to have greater lengths, higher GC content, and contain more splicing elements and repetitive elements, which seem to imply that the splicing frequency is influenced by such factors. Comparison of non-alternatively spliced (NAS) mouse genes with alternatively spliced human orthologs also suggested that exons with lower splicing frequencies may be newly evolved ones which gained functions with splicing frequencies altered through the evolution. Our findings have revealed for the first time that certain factors may have critical influence on the splicing frequency, suggesting that exons with lower splicing frequencies may originate from old repetitive sequences, with splicing sites altered by mutation, gaining novel functions and become more frequently spliced

Evaluating the performance of empirical models of total electron density and whistler-mode wave amplitude in the Earth’s inner magnetosphere

Empirical models have been previously developed using the large dataset of satellite observations to obtain the global distributions of total electron density and whistler-mode wave power, which are important in modeling radiation belt dynamics. In this paper, we apply the empirical models to construct the total electron density and the wave amplitudes of chorus and hiss, and compare them with the observations along Van Allen Probes orbits to evaluate the model performance. The empirical models are constructed using the Hp30 and SME (or SML) indices. The total electron density model provides an overall high correlation coefficient with observations, while large deviations are found in the dynamic regions near the plasmapause or in the plumes. The chorus wave model generally agrees with observations when the plasma trough region is correctly modeled and for modest wave amplitudes of 10–100 pT. The model overestimates the wave amplitude when the chorus is not observed or weak, and underestimates the wave amplitude when a large-amplitude chorus is observed. Similarly, the hiss wave model has good performance inside the plasmasphere when modest wave amplitudes are observed. However, when the modeled plasmapause location does not agree with the observation, the model misidentifies the chorus and hiss waves compared to observations, and large modeling errors occur. In addition, strong (>200 pT) hiss waves are observed in the plumes, which are difficult to capture using the empirical model due to their transient nature and relatively poor sampling statistics. We also evaluate four metrics for different empirical models parameterized by different indices. Among the tested models, the empirical model considering a plasmapause and controlled by Hp* (the maximum Hp30 during the previous 24 h) and SME* (the maximum SME during the previous 3 h) or Hp* and SML has the best performance with low errors and high correlation coefficients. Our study indicates that the empirical models are applicable for predicting density and whistler-mode waves with modest power, but large errors could occur, especially near the highly-dynamic plasmapause or in the plumes

Improving Factual Consistency of Text Summarization by Adversarially Decoupling Comprehension and Embellishment Abilities of LLMs

Despite the recent progress in text summarization made by large language models (LLMs), they often generate summaries that are factually inconsistent with original articles, known as "hallucinations" in text generation. Unlike previous small models (e.g., BART, T5), current LLMs make fewer silly mistakes but more sophisticated ones, such as imposing cause and effect, adding false details, overgeneralizing, etc. These hallucinations are challenging to detect through traditional methods, which poses great challenges for improving the factual consistency of text summarization. In this paper, we propose an adversarially DEcoupling method to disentangle the Comprehension and EmbellishmeNT abilities of LLMs (DECENT). Furthermore, we adopt a probing-based efficient training to cover the shortage of sensitivity for true and false in the training process of LLMs. In this way, LLMs are less confused about embellishing and understanding; thus, they can execute the instructions more accurately and have enhanced abilities to distinguish hallucinations. Experimental results show that DECENT significantly improves the reliability of text summarization based on LLMs

Deep learning model of hiss waves in the plasmasphere and plumes and their effects on radiation belt electrons

Hiss waves play an important role in removing energetic electrons from Earth’s radiation belts by precipitating them into the upper atmosphere. Compared to plasmaspheric hiss that has been studied extensively, the evolution and effects of plume hiss are less understood due to the challenge of obtaining their global observations at high cadence. In this study, we use a neural network approach to model the global evolution of both the total electron density and the hiss wave amplitudes in the plasmasphere and plume. After describing the model development, we apply the model to a storm event that occurred on 14 May 2019 and find that the hiss wave amplitude first increased at dawn and then shifted towards dusk, where it was further excited within a narrow region of high density, namely, a plasmaspheric plume. During the recovery phase of the storm, the plume rotated and wrapped around Earth, while the hiss wave amplitude decayed quickly over the nightside. Moreover, we simulated the overall energetic electron evolution during this storm event, and the simulated flux decay rate agrees well with the observations. By separating the modeled plasmaspheric and plume hiss waves, we quantified the effect of plume hiss on energetic electron dynamics. Our simulation demonstrates that, under relatively quiet geomagnetic conditions, the region with plume hiss can vary from L = 4 to 6 and can account for up to an 80% decrease in electron fluxes at hundreds of keV at L > 4 over 3 days. This study highlights the importance of including the dynamic hiss distribution in future simulations of radiation belt electron dynamics

Rubidium Chloride Targets Jnk/p38-Mediated NF-κB Activation to Attenuate Osteoclastogenesis and Facilitate Osteoblastogenesis

The unbalanced crosstalk between osteoclasts and osteoblasts could lead to disruptive bone homeostasis. Herein, we investigated the therapeutic effects of rubidium chloride (RbCl) on ovariectomized (OVX) and titanium (Ti) particle-induced calvaria osteolysis mouse models, showing that non-toxic RbCl attenuated RANKL-stimulated osteoclast formation and functionality while significantly enhancing osteogenesis in vitro. The expressions of osteoclast-specific genes were downregulated considerably by RbCl. Despite the direct inhibition of RANKL-induced activation of MAPK signaling, RbCl was able to target NF-κB directly and indirectly. We found that after the co-stimulation of the c-Jun N-terminal kinase (Jnk)/p38 activator and RANKL, RbCl inhibited the elevated expression of p-IKKα and the degradation of IκBα in osteoclast precursors, indicating indirect NF-κB inhibition via MAPK suppression. Furthermore, the two animal models demonstrated that RbCl attenuated tartrate-resistant acid phosphate (TRAP)-positive osteoclastogenesis and rescued bone loss caused by the hormonal dysfunction and wear particle in vivo. Altogether, these findings suggest that RbCl can target Jnk/p38-mediated NF-κB activation to attenuate osteoclastogenesis, while facilitating osteoblastogenesis both in vivo and in vitro, suggesting the possible future use of RbCl for surface coating of orthopedic implant biomaterials to protect against osteoporosis

The effect of compressive strain on the Raman modes of the dry and hydrated BaCe0.8Y0.2O3 proton conductor

The BaCe0.8Y0.2O3-{\delta} proton conductor under hydration and under compressive strain has been analyzed with high pressure Raman spectroscopy and high pressure x-ray diffraction. The pressure dependent variation of the Ag and B2g bending modes from the O-Ce-O unit is suppressed when the proton conductor is hydrated, affecting directly the proton transfer by locally changing the electron density of the oxygen ions. Compressive strain causes a hardening of the Ce-O stretching bond. The activation barrier for proton conductivity is raised, in line with recent findings using high pressure and high temperature impedance spectroscopy. The increasing Raman frequency of the B1g and B3g modes thus implies that the phonons become hardened and increase the vibration energy in the a-c crystal plane upon compressive strain, whereas phonons are relaxed in the b-axis, and thus reveal softening of the Ag and B2g modes. Lattice toughening in the a-c crystal plane raises therefore a higher activation barrier for proton transfer and thus anisotropic conductivity. The experimental findings of the interaction of protons with the ceramic host lattice under external strain may provide a general guideline for yet to develop epitaxial strained proton conducting thin film systems with high proton mobility and low activation energy

EMIC wave events during the four GEM QARBM challenge intervals

This paper presents observations of EMIC waves from multiple data sources during the four GEM challenge events in 2013 selected by the GEM “Quantitative Assessment of Radiation Belt Modeling” focus group: March 17‐18 (Stormtime Enhancement), May 31‐June 2 (Stormtime Dropout), September 19‐20 (Non‐storm Enhancement), and September 23‐25 (Non‐storm Dropout). Observations include EMIC wave data from the Van Allen Probes, GOES, and THEMIS spacecraft in the near‐equatorial magnetosphere and from several arrays of ground‐based search coil magnetometers worldwide, as well as localized ring current proton precipitation data from low‐altitude POES spacecraft. Each of these data sets provides only limited spatial coverage, but their combination shows consistent occurrence patterns and reveals some events that would not be identified as significant using near‐equatorial spacecraft alone. Relativistic and ultrarelativistic electron flux observations, phase space density data, and pitch angle distributions based on data from the REPT and MagEIS instruments on the Van Allen Probes during these events show two cases during which EMIC waves are likely to have played an important role in causing major flux dropouts of ultrarelativistic electrons, particularly near L* ~ 4.0. In three other cases identifiable smaller and more short‐lived dropouts appeared, and in five other cases these waves evidently had little or no effect

High-Density Transcriptional Initiation Signals Underline Genomic Islands in Bacteria

Genomic islands (GIs), frequently associated with the pathogenicity of bacteria and having a substantial influence on bacterial evolution, are groups of “alien” elements which probably undergo special temporal–spatial regulation in the host genome. Are there particular hallmark transcriptional signals for these “exotic” regions? We here explore the potential transcriptional signals that underline the GIs beyond the conventional views on basic sequence composition, such as codon usage and GC property bias. It showed that there is a significant enrichment of the transcription start positions (TSPs) in the GI regions compared to the whole genome of Salmonella enterica and Escherichia coli. There was up to a four-fold increase for the 70% GIs, implying high-density TSPs profile can potentially differentiate the GI regions. Based on this feature, we developed a new sliding window method GIST, Genomic-island Identification by Signals of Transcription, to identify these regions. Subsequently, we compared the known GI-associated features of the GIs detected by GIST and by the existing method Islandviewer to those of the whole genome. Our method demonstrates high sensitivity in detecting GIs harboring genes with biased GI-like function, preferred subcellular localization, skewed GC property, shorter gene length and biased “non-optimal” codon usage. The special transcriptional signals discovered here may contribute to the coordinate expression regulation of foreign genes. Finally, by using GIST, we detected many interesting GIs in the 2011 German E. coli O104:H4 outbreak strain TY-2482, including the microcin H47 system and gene cluster ycgXEFZ-ymgABC that activates the production of biofilm matrix. The aforesaid findings highlight the power of GIST to predict GIs with distinct intrinsic features to the genome. The heterogeneity of cumulative TSPs profiles may not only be a better identity for “alien” regions, but also provide hints to the special evolutionary course and transcriptional regulation of GI regions