Learning Baseline Values for Shapley Values

This paper aims to formulate the problem of estimating the optimal baseline values for the Shapley value in game theory. The Shapley value measures the attribution of each input variable of a complex model, which is computed as the marginal benefit from the presence of this variable w.r.t.its absence under different contexts. To this end, people usually set the input variable to its baseline value to represent the absence of this variable (i.e.the no-signal state of this variable). Previous studies usually determine the baseline values in an empirical manner, which hurts the trustworthiness of the Shapley value. In this paper, we revisit the feature representation of a deep model from the perspective of game theory, and define the multi-variate interaction patterns of input variables to define the no-signal state of an input variable. Based on the multi-variate interaction, we learn the optimal baseline value of each input variable. Experimental results have demonstrated the effectiveness of our method

D3Net: A Unified Speaker-Listener Architecture for 3D Dense Captioning and Visual Grounding

Recent studies on dense captioning and visual grounding in 3D have achieved impressive results. Despite developments in both areas, the limited amount of available 3D vision-language data causes overfitting issues for 3D visual grounding and 3D dense captioning methods. Also, how to discriminatively describe objects in complex 3D environments is not fully studied yet. To address these challenges, we present D3Net, an end-to-end neural speaker-listener architecture that can detect, describe and discriminate. Our D3Net unifies dense captioning and visual grounding in 3D in a self-critical manner. This self-critical property of D3Net also introduces discriminability during object caption generation and enables semi-supervised training on ScanNet data with partially annotated descriptions. Our method outperforms SOTA methods in both tasks on the ScanRefer dataset, surpassing the SOTA 3D dense captioning method by a significant margin.Comment: Project website: https://daveredrum.github.io/D3Net

Towards Axiomatic, Hierarchical, and Symbolic Explanation for Deep Models

This paper aims to show that the inference logic of a deep model can be faithfully approximated as a sparse, symbolic causal graph. Such a causal graph potentially bridges the gap between connectionism and symbolism. To this end, the faithfulness of the causal graph is theoretically guaranteed, because we show that the causal graph can well mimic the model's output on an exponential number of different masked samples. Besides, such a causal graph can be further simplified and re-written as an And-Or graph (AOG), which explains the logical relationship between interactive concepts encoded by the deep model, without losing much explanation accuracy

Double band inversion in the topological phase transition of Ge1-xSnx alloys

We use first-principles simulation and virtual crystal approximation to reveal the unique double band inversion and topological phase transition in Ge1-xSnx alloys. Wavefunction parity, spatial charge distribution and surface state spectrum analyses suggest that the band inversion in Ge1-xSnx is relayed by its first valence band. As the system evolves from Ge to {\alpha}-Sn, its conduction band moves down, and inverts with the first and the second valence bands consecutively. The first band inversion makes the system nontrivial, while the second one does not change the topological invariant of the system. Both the band inversions yield surface modes spanning the individual inverted gaps, but only the surface mode in the upper gap associates with the nontrivial nature of tensile-strained {\alpha}-Sn.Comment: 5 pages, 6 figure

Impacts of air pollutants from rural Chinese households under the rapid residential energy transition

Rural residential energy consumption in China is experiencing a rapid transition towards clean energy, nevertheless, solid fuel combustion remains an important emission source. Here we quantitatively evaluate the contribution of rural residential emissions to PM2.5 (particulate matter with an aerodynamic diameter less than 2.5 μm) and the impacts on health and climate. The clean energy transitions result in remarkable reductions in the contributions to ambient PM2.5, avoiding 130,000 (90,000-160,000) premature deaths associated with PM2.5 exposure. The climate forcing associated with this sector declines from 0.057 ± 0.016 W/m2 in 1992 to 0.031 ± 0.008 W/m2 in 2012. Despite this, the large remaining quantities of solid fuels still contributed 14 ± 10 μg/m3 to population-weighted PM2.5 in 2012, which comprises 21 ± 14% of the overall population-weighted PM2.5 from all sources. Rural residential emissions affect not only rural but urban air quality, and the impacts are highly seasonal and location dependent

Freezing of gait in Parkinson’s disease with glucocerebrosidase mutations: prevalence, clinical correlates and effect on quality of life

ObjectivesMutations in glucocerebrosidase (GBA1) can change the clinical phenotype of Parkinson’s disease (PD). This study aimed to explore the clinical characteristics of freezing of gait (FOG) in PD patients with GBA1 mutations.MethodsA whole-exome sequencing analysis was used to identify the GBA1 mutations (pathogenic or likely pathogenic) and exclude other PD-related gene mutations. A forward binary logistic regression model was conducted to identify the associated factors of FOG. The stepwise multiple linear regression analysis models were used to explore the effect of FOG on quality of life.ResultsThe prevalence of FOG in patients with GBA1 mutations (30/95, 31.6%) was significantly higher than those in patients without GBA1 mutations (152/760, 20%) (p = 0.009). A higher (i.e., worse) Unified PD Rating Scale part III score (OR = 1.126, 95%CI = 1.061–1.194, p < 0.001) and a lower (i.e., worse) Montreal Cognitive Assessment score (OR = 0.830, 95%CI = 0.713–0.967, p = 0.017) were significantly associated with FOG in PD patients with GBA1 mutations. The presence of FOG was significantly associated with the decreased (i.e., worse) score of PD Questionnaire 39 after adjustment for sex, age, disease duration, motor score, and non-motor score (B = 14.981, p = 0.001).ConclusionFOG is a relatively common disabling symptom in PD patients with GBA1 mutations, which is affected by motor disability and cognitive decline. Quality of life is reduced in patients with FOG and GBA1 mutations

HDAC3 maintains oocyte meiosis arrest by repressing amphiregulin expression before the LH surge.

It is known that granulosa cells (GCs) mediate gonadotropin-induced oocyte meiosis resumption by releasing EGF-like factors in mammals, however, the detailed molecular mechanisms remain unclear. Here, we demonstrate that luteinizing hormone (LH) surge-induced histone deacetylase 3 (HDAC3) downregulation in GCs is essential for oocyte maturation. Before the LH surge, HDAC3 is highly expressed in GCs. Transcription factors, such as FOXO1, mediate recruitment of HDAC3 to the amphiregulin (Areg) promoter, which suppresses AREG expression. With the LH surge, decreased HDAC3 in GCs enables histone H3K14 acetylation and binding of the SP1 transcription factor to the Areg promoter to initiate AREG transcription and oocyte maturation. Conditional knockout of Hdac3 in granulosa cells in vivo or inhibition of HDAC3 activity in vitro promotes the maturation of oocytes independent of LH. Taking together, HDAC3 in GCs within ovarian follicles acts as a negative regulator of EGF-like growth factor expression before the LH surge

Spatial-temporal evolution pattern and optimization path of family education policy: An LDA thematic model approach

Family education policy plays a crucial role in modernizing family education. By examining the temporal and spatial evolution of this policy, its inherent logic, constructs, and optimal pathways can be better understood. The study analyzed local family education policy documents, extracting six major themes using the Latent Dirichlet Allocation (LDA) model, and presented them according to the calculated mean theme probability. The themes include parental ability, school security, institutional environment, government support, social coordination, and high-quality development. Parental ability and government support were found to be particularly prominent, suggesting that many local policies focus on enhancing parents' skills for delivering family education and bolstering the government's role in public affairs. This combines the dual responsibilities of being an educational entity and accountable subject in the joint development of family education. Understanding the characteristics and variations in temporal and spatial distribution can enrich family education policy design, fostering the high-quality development of family education initiatives. Based on the findings, the study proposes three optimization paths for policy design: promotion and empowerment (building a multi-cooperative system), regional interconnection (understanding the current state of local policies and leveraging their strengths), and breaking barriers (simultaneously promoting the inclusiveness of family education and brand development). This study emphasizes the needs of customizing family education policy based on the temporal and spatial features and local requirements for maximum outputs

Data on tumor progression of c-mos deficiency in murine models of KrasG12D lung and ApcMin colorectal cancer

The c-mos proto-oncogene was one of the first proto-oncogenes to be cloned. Apart from its role in meiosis, many efforts have been made to illuminate the mechanisms by which c-mos might acts as an oncogene. Increased Mos expression was found in most human tumor tissues. However, a detailed role of c-mos in tumor progression remains unknown.In this study, we analyzed online databases to find out the correlation between Mos expression and poor survival rates in human cancer patients. Then, we crossed c-mos knockout mice with ApcMin or KrasG12D mice to generate intestinal cancer model and lung cancer model, respectively. Tumor progression was monitored, and the influence of c-mos deficiency on cancer formation was investigated