Computational Mechanisms of Face Perception

The intertwined history of artificial intelligence and neuroscience has significantly impacted their development, with AI arising from and evolving alongside neuroscience. The remarkable performance of deep learning has inspired neuroscientists to investigate and utilize artificial neural networks as computational models to address biological issues. Studying the brain and its operational mechanisms can greatly enhance our understanding of neural networks, which has crucial implications for developing efficient AI algorithms. Many of the advanced perceptual and cognitive skills of biological systems are now possible to achieve through artificial intelligence systems, which is transforming our knowledge of brain function. Thus, the need for collaboration between the two disciplines demands emphasis. It\u27s both intriguing and challenging to study the brain using computer science approaches, and this dissertation centers on exploring computational mechanisms related to face perception. Face recognition, being the most active artificial intelligence research area, offers a wealth of data resources as well as a mature algorithm framework. From the perspective of neuroscience, face recognition is an important indicator of social cognitive formation and neural development. The ability to recognize faces is one of the most important cognitive functions. We first discuss the problem of how the brain encodes different face identities. By using DNNs to extract features from complex natural face images and project them into the feature space constructed by dimension reduction, we reveal a new face code in the human medial temporal lobe (MTL), where neurons encode visually similar identities. On this basis, we discover a subset of DNN units that are selective for facial identity. These identity-selective units exhibit a general ability to discriminate novel faces. By establishing coding similarities with real primate neurons, our study provides an important approach to understanding primate facial coding. Lastly, we discuss the impact of face learning during the critical period. We identify a critical period during DNN training and systematically discuss the use of facial information by the neural network both inside and outside the critical period. We further provide a computational explanation for the critical period influencing face learning through learning rate changes. In addition, we show an alternative method to partially recover the model outside the critical period by knowledge refinement and attention shifting. Our current research not only highlights the importance of training orientation and visual experience in shaping neural responses to face features and reveals potential mechanisms for face recognition but also provides a practical set of ideas to test hypotheses and reconcile previous findings in neuroscience using computer methods

Genetic and Molecular Mechanisms Underlying Symbiotic Specificity in Legume-Rhizobium Interactions

Legumes are able to form a symbiotic relationship with nitrogen-fixing soil bacteria called rhizobia. The result of this symbiosis is to form nodules on the plant root, within which the bacteria can convert atmospheric nitrogen into ammonia that can be used by the plant. Establishment of a successful symbiosis requires the two symbiotic partners to be compatible with each other throughout the process of symbiotic development. However, incompatibility frequently occurs, such that a bacterial strain is unable to nodulate a particular host plant or forms nodules that are incapable of fixing nitrogen. Genetic and molecular mechanisms that regulate symbiotic specificity are diverse, involving a wide range of host and bacterial genes/signals with various modes of action. In this review, we will provide an update on our current knowledge of how the recognition specificity has evolved in the context of symbiosis signaling and plant immunity

Simulating landslide-induced tsunamis in the Yangtze River at the Three Gorges in China

Landslide-induced tsunamis may cause fatalities, damages and financial losses. In the Three Gorges Reservoir Area of China, several large landslides are still unstable and persistently creeping toward the Yangtze River. In this paper, we investigate the impacts of landslide-induced tsunamis in the Three Gorges Reservoir by using a hybrid numerical approach. One of the largest unstable mass in this area, the Huangtupo landslide, is chosen as the study object. First, the landslide deformation and initiating velocities are obtained by using the finite-discrete element method. The landslide-induced tsunamis and their impacts on shipping on the Yangtze River are then investigated through smooth particle hydrodynamics modelling. Our results reveal that an approximately 80% reduction in shear strength of the tip in the landslide will lead to catastrophic failure of the landslide, with sliding velocities of up to 8 m/s. Subsequently, such a collapse may initiate a river tsunami, propagating up to 9 m on the nearby reservoir banks within 3 km. The impacts on surrounding floating objects, such as surges and sways, heaves and rolls, are up to 110 m, 8 m and 6°, respectively. The simulations indicate that although the likelihood of a catastrophic failure of the whole landslide is low, the partial sliding still poses severe threat to the nearby reservoir banks and shipping on the Yangtze River. Thus, we recommend continuous monitoring as well as landslide early warning systems at this and also other hazardous sites in this area

Airfoil Optimization using Design-by-Morphing

We present Design-by-Morphing (DbM), a novel design methodology applicable to creating a search space for topology optimization of 2D airfoils. Most design techniques impose geometric constraints and sometimes designers' bias on the design space itself, thus restricting the novelty of the designs created, and only allowing for small local changes. We show that DbM methodology does not impose any such restrictions on the design space and allows for extrapolation from the search space, thus granting truly radical and large search space with a few design parameters. In comparison to other shape design methodologies, we apply DbM to create a search space for 2D airfoils. We optimize this airfoil shape design space for maximizing the lift-over-drag ratio, $CLD_{max}$, and stall angle tolerance, $\Delta \alpha$. Using a bi-objective genetic algorithm to optimize the DbM space, it is found that we create a Pareto-front of radical airfoils exhibiting remarkable properties for both objectives

An Efficient Process for Co-Production of γ-Aminobutyric Acid and Probiotic \u3ci\u3eBacillus subtilis\u3c/i\u3e Cells

This study was to establish an integrated process for the co-production of γ-aminobutyric acid (GABA) and live probiotics. Six probiotic bacteria were screened and Bacillus subtilis ATCC 6051 showed the highest GABA-producing capacity. The optimal temperature and initial pH value for GABA production in B. subtilis were found to be 30 °C and 8.0, respectively. A variety of carbon and nitrogen sources were tested, and potato starch and peptone were the preferred carbon and nitrogen sources for GABA production, respectively. The concentrations of carbon source, nitrogen source and substrate (sodium L-glutamate) were then optimized using the response surface methodology. The GABA titer and concentration of viable cells of B. subtilis reached 19.74 g/L and 6.0 × 108 cfu/mL at 120 h. The GABA titer represents the highest production of GABA in B. subtilis. This work thus demonstrates a highly efficient co-production process for GABA and probiotic B. subtilis cells

Mapping Urban Bare Land Automatically from Landsat Imagery with a Simple Index

In recent years, hundreds of Earth observation satellites have been launched to collect massive amounts of remote sensing images. However, the considerable cost and time to process the significant amount of data have become the greatest obstacle between data and knowledge. In order to accelerate the transformation from remote sensing images to urban thematic maps, a strategy to map the bare land automatically from Landsat imagery was developed and assessed in this study. First, a normalized difference bare land index (NBLI) was presented to maximally differentiate bare land from other land types in Wuhan City, China. Then, an unsupervised classifier was employed to extract the bare land from the NBLI image without training samples or self-assigned thresholds. Experimental results showed good performance on overall accuracy (92%), kappa coefficient (0.84), area ratio (1.1321), and match rate (83.96%), respectively. Results in multiple years disclosed that bare lands in the study site gradually moved from inner loops to the outer loops since 2007, in two main directions. This study demonstrated that the proposed method was an accurate and reliable option to extract the bare land, which led to a promising approach to mapping urban land use/land cover (LULC) automatically with simple indices

The Soybean \u3cem\u3eRfg1\u3c/em\u3e Gene Restricts Nodulation by \u3cem\u3eSinorhizobium fredii\u3c/em\u3e USDA193

Sinorhizobium fredii is a fast-growing rhizobial species that can establish a nitrogen-fixing symbiosis with a wide range of legume species including soybeans (Glycine max). In soybeans, this interaction shows a high level of specificity such that particular S. fredii strains nodulate only a limited set of plant genotypes. Here we report the identification of a dominant gene in soybeans that restricts nodulation with S. fredii USDA193. Genetic mapping in an F2 population revealed co-segregation of the underlying locus with the previously cloned Rfg1 gene. The Rfg1 allele encodes a member of the Toll-interleukin receptor/nucleotide-binding site/leucine-rich repeat class of plant resistance proteins that restricts nodulation by S. fredii strains USDA257 and USDA205, and an allelic variant of this gene also restricts nodulation by Bradyrhizobium japonicum USDA122. By means of complementation tests and CRISPR/Cas9-mediated gene knockouts, we demonstrate that the Rfg1 allele also is responsible for resistance to nodulation by S. fredii USDA193. Therefore, the Rfg1 allele likely provides broad-spectrum resistance to nodulation by many S. fredii and B. japonicum strains in soybeans

Feature-based encoding of face identity by single neurons in the human medial temporal lobe

Neurons in the human medial temporal lobe (MTL) that are selective for the identity of specific people are classically thought to encode identity invariant to visual features. However, it remains largely unknown how visual information from higher visual cortex is translated into a semantic representation of an individual person. Here, we show that some MTL neurons are selective to multiple different face identities on the basis of shared features that form clusters in the representation of a deep neural network trained to recognize faces. Contrary to prevailing views, we find that these neurons represent an individual’s face with feature-based encoding, rather than through association with concepts. The response of feature neurons did not depend on face identity nor face familiarity, and the region of feature space to which they are tuned predicted their response to new face stimuli. Our results provide critical evidence bridging the perception-driven representation of facial features in the higher visual cortex and the memory-driven representation of semantics in the MTL, which may form the basis for declarative memory

Identification and Heterologous Reconstitution of a 5-Alk(en)ylresorcinol Synthase from Endophytic Fungus \u3ci\u3eShiraia\u3c/i\u3e sp. Slf14

A new type III polyketide synthase gene (Ssars) was discovered from the genome of Shiraia sp. Slf14, an endophytic fungal strain from Huperzia serrata. The intron-free gene was cloned from the cDNA and ligated to two expression vectors pET28a and YEpADH2p-URA3 for expression in Escherichia coli BL21(DE3) and Saccharomyces cerevisiae BJ5464, respectively. SsARS was efficiently expressed in E. coli BL21(DE3), leading to the synthesis of a series of polyketide products. Six major products were isolated from the engineered E. coli and characterized as 1,3-dihydroxyphenyl-5-undecane, 1,3-dihydroxyphenyl-5-cis-6\u27-tridecene,1,3-dihydroxyphenyl-5-tridecane, 1,3-dihydroxyphenyl-5-cis-8\u27-pentadecene, 1,3-dihydroxyphenyl-5-pentadecane and 1,3-dihydroxyphenyl-5-cis-10\u27-heptadecene, respectively, based on the spectral data and biosynthetic origin. Expression of SsARS in the yeast also led to the synthesis of the same polyketide products, indicating that this enzyme can be reconstituted in both heterologous hosts. Supplementation of soybean oil into the culture of E. coli BL21(DE3)/SsARS increased the production titers of 1-6 and led to the synthesis of an additional product, which was identified as 5-(8\u27Z,11\u27Z-heptadecadienyl)resorcinol. This work thus allowed the identification of SsARS as a 5-alk(en)ylresorcinol synthase with flexible substrate specificity toward endogenous and exogenous fatty acids. Desired resorcinol derivatives may be synthesized by supplying corresponding fatty acids into the culture medium