MA-NeRF: Motion-Assisted Neural Radiance Fields for Face Synthesis from Sparse Images

We address the problem of photorealistic 3D face avatar synthesis from sparse images. Existing Parametric models for face avatar reconstruction struggle to generate details that originate from inputs. Meanwhile, although current NeRF-based avatar methods provide promising results for novel view synthesis, they fail to generalize well for unseen expressions. We improve from NeRF and propose a novel framework that, by leveraging the parametric 3DMM models, can reconstruct a high-fidelity drivable face avatar and successfully handle the unseen expressions. At the core of our implementation are structured displacement feature and semantic-aware learning module. Our structured displacement feature will introduce the motion prior as an additional constraints and help perform better for unseen expressions, by constructing displacement volume. Besides, the semantic-aware learning incorporates multi-level prior, e.g., semantic embedding, learnable latent code, to lift the performance to a higher level. Thorough experiments have been doen both quantitatively and qualitatively to demonstrate the design of our framework, and our method achieves much better results than the current state-of-the-arts

Predictive model for inflammation grades of chronic hepatitis B: Large‐scale analysis of clinical parameters and gene expressions

BackgroundLiver biopsy is the gold standard to assess pathological features (eg inflammation grades) for hepatitis B virus‐infected patients although it is invasive and traumatic; meanwhile, several gene profiles of chronic hepatitis B (CHB) have been separately described in relatively small hepatitis B virus (HBV)‐infected samples. We aimed to analyse correlations among inflammation grades, gene expressions and clinical parameters (serum alanine amino transaminase, aspartate amino transaminase and HBV‐DNA) in large‐scale CHB samples and to predict inflammation grades by using clinical parameters and/or gene expressions.MethodsWe analysed gene expressions with three clinical parameters in 122 CHB samples by an improved regression model. Principal component analysis and machine‐learning methods including Random Forest, K‐nearest neighbour and support vector machine were used for analysis and further diagnosis models. Six normal samples were conducted to validate the predictive model.ResultsSignificant genes related to clinical parameters were found enriching in the immune system, interferon‐stimulated, regulation of cytokine production, anti‐apoptosis, and etc. A panel of these genes with clinical parameters can effectively predict binary classifications of inflammation grade (area under the ROC curve [AUC]: 0.88, 95% confidence interval [CI]: 0.77‐0.93), validated by normal samples. A panel with only clinical parameters was also valuable (AUC: 0.78, 95% CI: 0.65‐0.86), indicating that liquid biopsy method for detecting the pathology of CHB is possible.ConclusionsThis is the first study to systematically elucidate the relationships among gene expressions, clinical parameters and pathological inflammation grades in CHB, and to build models predicting inflammation grades by gene expressions and/or clinical parameters as well.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/139116/1/liv13427.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/139116/2/liv13427_am.pd

Schizophrenia-associated somatic copy-number variants from 12,834 cases reveal recurrent NRXN1 and ABCB11 disruptions

While germline copy-number variants (CNVs) contribute to schizophrenia (SCZ) risk, the contribution of somatic CNVs (sCNVs)—present in some but not all cells—remains unknown. We identified sCNVs using blood-derived genotype arrays from 12,834 SCZ cases and 11,648 controls, filtering sCNVs at loci recurrently mutated in clonal blood disorders. Likely early-developmental sCNVs were more common in cases (0.91%) than controls (0.51%, p = 2.68e−4), with recurrent somatic deletions of exons 1–5 of the NRXN1 gene in five SCZ cases. Hi-C maps revealed ectopic, allele-specific loops forming between a potential cryptic promoter and non-coding cis-regulatory elements upon 5′ deletions in NRXN1. We also observed recurrent intragenic deletions of ABCB11, encoding a transporter implicated in anti-psychotic response, in five treatment-resistant SCZ cases and showed that ABCB11 is specifically enriched in neurons forming mesocortical and mesolimbic dopaminergic projections. Our results indicate potential roles of sCNVs in SCZ risk

Lightweight thermal monitoring in optical networks-on-chip via router reuse

Optical network-on-chip (ONoC) is an emerging communication architecture for manycore systems due to low latency, high bandwidth, and low power dissipation. However, a major concern lies in its thermal susceptibility - under onchip temperature variations, functional nanophotonic devices, especially microring resonator (MR)-based devices, suffer from significant thermal-induced optical power loss, which potentially counteracts the power advantages of ONoCs and even cause functional failures. Considering the fact that temperature gradients are typically found on many-core systems, effective thermal monitoring, performing as the foundation of thermal-aware management, is critical on ONoCs. In this paper, a lightweight thermal monitoring scheme is proposed for ONoCs. We first design a temperature measurement module based on generic optical routers. It introduces trivial overheads in chip area by reusing the components in routers. A major problem with reusing optical routers is that it may potentially interfere with the normal communications in ONoCs. To address it, we then propose a time allocation strategy to schedule thermal sensing operations in the time intervals between communications. Evaluation results show that our scheme exhibits an untrimmed inaccuracy of 1.0070 K with low energy consumption of 656.38 pJ/Sa. It occupies an extremely small area of 0.0020 mm 2 , reducing the area cost by 83.74% on average compared to the state-of-the-art optical thermal sensor design.Ministry of Education (MOE)Published versionThis work is partially supported by MoE AcRF Tier 2 MOE2019-T2-1-071 and Tier 1 MOE2019-T1-1-072, NTU NAP M4082282 and SUG M4082087, Singapore and NSFC 61772094, China

Attack mitigation of hardware trojans for thermal sensing via micro-ring resonator in optical NoCs

As an emerging role in new-generation on-chip communication, optical networks-on-chip (ONoCs) provide ultra-high bandwidth, low latency and low power dissipation for data transfers. However, the thermo-optic effects of the photonic devices have a great impact on the operating performance and reliability of ONoCs, where the thermal-aware control with accurate measurements, e.g., thermal sensing, is typically applied to alleviate it. Besides, the temperature-sensitive ONoCs are prone to be attacked by the hardware Trojans (HTs) covertly embedded in the counterfeit integrated circuits (ICs) from the malicious third-party vendors, leading to performance degradation, denial-of-service (DoS), or even permanent damages. In this paper, we focus on the tampering and snooping attacks during the thermal sensing via micro-ring resonator (MR) in ONoCs. Based on the provided work flow and attack model, a new structure of the anti-HT module is proposed to verify and protect the obtained data from the thermal sensor for attacks in its optical sampling and electronic transmission processes. In addition, we present the detection scheme based on the spiking neural networks (SNNs) to implement an accurate classification of the network security statuses for further high-level control. Evaluation results indicate that, with less than 1% extra area of a tile, our approach can significantly enhance the hardware security of thermal sensing for ONoC with trivial costs of up to 8.73%, 5.32% and 6.14% in average latency, execution time and energy consumption, respectively.Ministry of Education (MOE)Nanyang Technological UniversityAccepted versionThis work is partially supported by the Ministry of Education, Singapore, under its Academic Research Fund Tier 2 (Grant No. MOE2019-T2-001-071) and Tier 1 (Grant No. MOE2019-T1-001-072), and Nanyang Technological University, Singapore, under its NAP (Grant No. M4082282) and SUG (Grant No. M4082087)

Mitigation of tampering attacks for MR-based thermal sensing in optical NoCs

As an emerging role in on-chip communication, the optical networks-on-chip (ONoCs) can provide ultra-high bandwidth, low latency and low power dissipation for the data transfer. However, the thermo-optic effects of the photonic devices have a great impact on the operating performance and reliability of ONoCs, where the thermal-aware control is used to alleviate it. Furthermore, the temperature-sensitive ONoCs are prone to be attacked by the hardware Trojans (HTs) covertly embedded in the integrated circuits (ICs) from the malicious third-party components, leading to performance degradation, denial of service (DoS), or even permanent damages. In this paper, we focus on the tampering attacks on optical sampling during the thermal sensing process in ONoCs. Corresponding approaches are proposed to mitigate the negative impacts from HT attacks. Evaluation results indicate that our approach can significantly enhance the hardware security of thermal sensing for ONoC with trivial overheads of up to 3.06% and 2.6% in average latency and energy consumption, respectively.Ministry of Education (MOE)Accepted versio

Comparison of covalent and physical immobilization of lipase in gigaporous polymeric microspheres

Lipase (EC 3.1.1.3) is a versatile enzyme which has been widely used in ester-reaction industries. We have previously discovered that gigaporous polystyrene (PST) microspheres can be used as a novel immobilization carrier for lipase. In this work, a series of gigaporous microspheres with different densities of epoxy group including poly(glycidyl methacrylate) (PGMA) and poly(styrene-co-glycidyl methacrylate) [P(ST-GMA)] were evaluated as lipase immobilization carriers, which were also compared with gigaporous PST microspheres and the commercial immobilized lipase Novozym 435. Lipase immobilized in gigaporous PGMA microspheres showed the highest activity yield, reusability, and stability as well as the best affinity for the substrate. The characterizations of adsorption curves, the change of epoxy group amounts, and hydrophobic-hydrophilic properties of the microspheres were carried out to investigate the interaction between lipase molecules and carriers. It was found that covalent binding played a key role in improving the properties of lipase immobilized in gigaporous PGMA microspheres

ArSMART : an improved SMART NoC design supporting arbitrary-turn transmission

SMART NoC, which transmits unconflicted flits to distant processing elements (PEs) in one cycle through the express bypass, is a high-performance NoC design proposed recently. However, if contention occurs, flits with low priority would not only be buffered but also could not fully utilize bypass. Although there exist several routing algorithms that decrease contentions by rounding busy routers and links, they cannot be directly applicable to SMART since it lacks the support for arbitrary-turn (i.e. the number and direction of turns are free of constraints) routing. Thus, in this article, to minimize contentions and further utilize bypass, we propose an improved SMART NoC, called ArSMART, in which arbitrary-turn transmission is enabled. Specifically, ArSMART divides the whole NoC into multiple clusters where the route computation is conducted by the cluster controller and the data forwarding is performed by the bufferless reconfigurable router. Since the long-range transmission in SMART NoC needs to bypass the intermediate arbitration, to enable this feature, we directly configure the input and output ports connection rather than apply hop-by-hop table-based arbitration. To further explore the higher communication capabilities, effective adaptive routing algorithms that are compatible with ArSMART are proposed. The route computation overhead, one of the main concerns for adaptive routing algorithms, is hidden by our carefully designed control mechanism. Compared with the state-of-the-art SMART NoC, the experimental results demonstrate an average reduction of 40.7% in application schedule length and 29.7% in energy consumption.Ministry of Education (MOE)Nanyang Technological UniversityThis work is partially supported by the Ministry of Education, Singapore, under its Academic Research Fund Tier 2 (MoE2019-T2-1-071) and Tier 1 (MoE2019-T1-001-072), and Nanyang Technological University, Singapore, under its NAP (M4082282) and SUG (M4082087)

Towards A Deeper Understanding of the Interfacial Adsorption of Enzyme Molecules in Gigaporous Polymeric Microspheres

Compared with the one immobilized in the conventional mesoporous microspheres, the enzyme immobilized in gigaporous microspheres showed much higher activity and better stability. To gain a deeper understanding, we herein selected lipase as a prototype to comparatively analyze the adsorption behavior of lipase at interfaces in gigaporous and mesoporous polystyrene microspheres at very low lipase concentration, and further compared with the adsorption on a completely flat surface (a chip). Owing to the limited space of narrow pores, lipase molecules were inclined to be adsorbed as a monolayer in mesoporous microspheres. During this process, the interaction between lipase molecules and the interface was stronger, which could result in the structural change of lipase molecular and compromised specific activity. In addition to monolayer adsorption, more multilayer adsorption of enzyme molecules also occurred in gigaporous microspheres. Besides the adsorption state, the pore curvature also affected the lipase adsorption. Due to the multilayer adsorption, the excellent mass transfer properties for the substrate and the product in the large pores, and the small pore curvature, lipase immobilized in gigaporous microspheres showed better behaviors