Rethink Baseline of Integrated Gradients from the Perspective of Shapley Value

Numerous approaches have attempted to interpret deep neural networks (DNNs) by attributing the prediction of DNN to its input features. One of the well-studied attribution methods is Integrated Gradients (IG). Specifically, the choice of baselines for IG is a critical consideration for generating meaningful and unbiased explanations for model predictions in different scenarios. However, current practice of exploiting a single baseline fails to fulfill this ambition, thus demanding multiple baselines. Fortunately, the inherent connection between IG and Aumann-Shapley Value forms a unique perspective to rethink the design of baselines. Under certain hypothesis, we theoretically analyse that a set of baseline aligns with the coalitions in Shapley Value. Thus, we propose a novel baseline construction method called Shapley Integrated Gradients (SIG) that searches for a set of baselines by proportional sampling to partly simulate the computation path of Shapley Value. Simulations on GridWorld show that SIG approximates the proportion of Shapley Values. Furthermore, experiments conducted on various image tasks demonstrate that compared to IG using other baseline methods, SIG exhibits an improved estimation of feature's contribution, offers more consistent explanations across diverse applications, and is generic to distinct data types or instances with insignificant computational overhead.Comment: 12 page

Fast and Robust Face-to-Parameter Translation for Game Character Auto-Creation

With the rapid development of Role-Playing Games (RPGs), players are now allowed to edit the facial appearance of their in-game characters with their preferences rather than using default templates. This paper proposes a game character auto-creation framework that generates in-game characters according to a player's input face photo. Different from the previous methods that are designed based on neural style transfer or monocular 3D face reconstruction, we re-formulate the character auto-creation process in a different point of view: by predicting a large set of physically meaningful facial parameters under a self-supervised learning paradigm. Instead of updating facial parameters iteratively at the input end of the renderer as suggested by previous methods, which are time-consuming, we introduce a facial parameter translator so that the creation can be done efficiently through a single forward propagation from the face embeddings to parameters, with a considerable 1000x computational speedup. Despite its high efficiency, the interactivity is preserved in our method where users are allowed to optionally fine-tune the facial parameters on our creation according to their needs. Our approach also shows better robustness than previous methods, especially for those photos with head-pose variance. Comparison results and ablation analysis on seven public face verification datasets suggest the effectiveness of our method

Genome-Wide Analysis of Sorbitol Dehydrogenase (SDH) Genes and Their Differential Expression in Two Sand Pear (Pyrus pyrifolia) Fruits

Through RNA-seq of a mixed fruit sample, fourteen expressed sorbitol dehydrogenase (SDH) genes have been identified from sand pear (Pyrus pyrifolia Nakai). Comparative phylogenetic analysis of these PpySDHs with those from other plants supported the closest relationship of sand pear with Chinese white pear (P. bretschneideri). The expression levels varied greatly among members, and the strongest six (PpySDH2, PpySDH4, PpySDH8, PpySDH12, PpySDH13 and PpySDH14) accounted for 96% of total transcript abundance of PpySDHs. Tissue-specific expression of these six members was observed in nine tissues or organs of sand pear, with the greatest abundance found in functional leaf petioles, followed by the flesh of young fruit. Expression patterns of these six PpySDH genes during fruit development were analyzed in two sand pear cultivars, “Cuiguan” and “Cuiyu”. Overall, expression of PpySDHs peaked twice, first at the fruitlet stage and again at or near harvest. The transcript abundance of PpySDHs was higher in “Cuiguan” than in “Cuiyu”, accompanied by a higher content of sugars and higher ratio of fructose to sorbitol maintained in the former cultivar at harvest. In conclusion, it was suggested that multiple members of the SDH gene family are possibly involved in sand pear fruit development and sugar accumulation and may affect both the sugar amount and sugar composition

The Design and Experimentation of a Corn Moisture Detection Device Based on Double Capacitors

Detecting the moisture content of grain accurately and rapidly has important significance for harvesting, transport, storage, processing, and precision agriculture. There are some problems with the slow detection speeds, unstable detection, and low detection accuracy of moisture contents in corn harvesters. In that case, an online moisture detection device was designed, which is based on double capacitors. A new method of capacitance complementation and integration was proposed to eliminate the limitation of single data. The device is composed of a sampling mechanism and a double-capacitor sensor consisting of a flatbed capacitor and a cylindrical capacitor. The optimum structure size of the capacitor plates was determined by simulation optimization. In addition to this, the detection system with software and hardware was developed to estimate the moisture content. Indoor dynamic measurement tests were carried out to analyze the influence of temperature and porosity. Based on the influencing factors and capacitance, a model was established to estimate the moisture content. Finally, the support vector machine (SVM) regressions between the capacitance and moisture content were built up so that the R2 values were more than 0.91. In the stability test, the standard deviation of the stability test was 1.09%, and the maximum relative error of the measurement accuracy test was 1.22%. In the dynamic verification test, the maximum error of the measurement was 4.62%, less than 5%. It provides a measurement method for the accurate, rapid, and stable detection of the moisture content of corn and other grains

Fe-biochar as a safe and efficient catalyst to activate peracetic acid for the removal of the acid orange dye from water

International audiencePollution of wastewater and natural waters by organic contaminants is a major health issue, yet actual remediation methods are limited by incomplete removal of recalcitrant contaminants and by secondary pollution by chlorinated contaminants and catalytic metals. To attempt to solve these issues, we tested the removal of acid orange by peracetic acid (PAA), a safe oxidant, activated by Fe-biochar that iron anchored on biochar to prevent secondary pollution by iron. Fe-biochar was synthesized using a simple, one-step pyrolysis method. We investigated the effects of PAA concentration, pH, humic acids, chloride, bicarbonate on the reaction. Radical quenching and electron paramagnetic resonance were used to identify reacting species. Results showed that the granulous structure of Fe-biochar and the presence of Fe, Fe3O4, Fe2O3, and Fe3C on Fe-biochar surface. The highest removal of acid orange of 99.9% was obtained with 1.144 mM PAA and 0.3 g/L Fe-biochar at pH 7. Acid orange removal increases with Fe-biochar dose, decreases with pH, is slightly inhibited by humic acids and bicarbonate, and is not modified by chloride. Our experimental results suggested that CH3C(O)OO⋅ and CH3C(O)O⋅ are the main radical species, but there may also be non-radical effects in Fe-biochar/PAA process. Fe-biochar displayed high re-usability, with 92.8% removal after five uses

Preparation and Characterization of Textile-Grade Long Cellulose Fibers and Their Yarns from Windmill Palm

Windmill palm fiber (WPF) is an abundant source of cellulose fiber that can be used in textile manufacturing. In this study, acid-alkali palm fiber and acid-alkali-enzyme palm fiber were prepared to create blended yarns. The morphology, chemical composition, physical structural parameters, and tensile properties of the WPF samples and yarns were studied. The results indicated that both the acid-alkali and acid-alkali-enzyme treatments can be used as degumming methods to prepare windmill palm textile-grade long fibers with spinning ability. After chemical treatment, the cellulose content of WPF increased to more than 60%, up from 34%. However, the line densities of the acid-alkali and acid-alkali-enzyme textile-grade long fibers decreased to 5.29 ± 1.00 tex and 4.52 ± 0.82 tex, respectively. For the enzyme-treated fiber, a stratification phenomenon of the fiber cell walls and a decrease in the modulus were observed. The palm/cotton yarn had a high tensile strength and strip uniformity