Analytical Solution of Poisson's Equation with Application to VLSI Global Placement

Poisson's equation has been used in VLSI global placement for describing the potential field caused by a given charge density distribution. Unlike previous global placement methods that solve Poisson's equation numerically, in this paper, we provide an analytical solution of the equation to calculate the potential energy of an electrostatic system. The analytical solution is derived based on the separation of variables method and an exact density function to model the block distribution in the placement region, which is an infinite series and converges absolutely. Using the analytical solution, we give a fast computation scheme of Poisson's equation and develop an effective and efficient global placement algorithm called Pplace. Experimental results show that our Pplace achieves smaller placement wirelength than ePlace and NTUplace3. With the pervasive applications of Poisson's equation in scientific fields, in particular, our effective, efficient, and robust computation scheme for its analytical solution can provide substantial impacts on these fields

Associations between polygenic risk, negative symptoms, and functional connectome topology during a working memory task in early-onset schizophrenia

Working memory (WM) deficit in schizophrenia is thought to arise from a widespread neural inefficiency. However, we do not know if this deficit results from the illness-related genetic risk and influence the symptom burden in various domains, especially in patients who have an early onset illness. We used graph theory to examine the topology of the functional connectome in 99 subjects (27 early-onset schizophrenia (EOS), 24 asymptomatic siblings, and 48 healthy subjects) during an n-back task, and calculated their polygenic risk score (PRS) for susceptibility to schizophrenia. Linear regression analysis was used to test associations of the PRS, clinical symptoms, altered connectomic properties, and WM accuracy in EOS. Indices of small-worldness and segregation were elevated in EOS during the WM task compared with the other two groups; these connectomic aberrations correlated with increased PRS and negative symptoms. In patients with higher polygenic risk, WM performance was lower only when both the connectomic aberrations and the burden of negative symptoms were higher. Negative symptoms had a stronger moderating role in this relationship. Our findings suggest that the aberrant connectomic topology is a feature of WM task performance in schizophrenia; this relates to higher polygenic risk score as well as higher burden of negative symptoms. The deleterious effects of polygenic risk on cognition are played out via its effects on the functional connectome, as well as negative symptoms

Alleviating the Long-Tail Problem in Conversational Recommender Systems

Conversational recommender systems (CRS) aim to provide the recommendation service via natural language conversations. To develop an effective CRS, high-quality CRS datasets are very crucial. However, existing CRS datasets suffer from the long-tail issue, \ie a large proportion of items are rarely (or even never) mentioned in the conversations, which are called long-tail items. As a result, the CRSs trained on these datasets tend to recommend frequent items, and the diversity of the recommended items would be largely reduced, making users easier to get bored. To address this issue, this paper presents \textbf{LOT-CRS}, a novel framework that focuses on simulating and utilizing a balanced CRS dataset (\ie covering all the items evenly) for improving \textbf{LO}ng-\textbf{T}ail recommendation performance of CRSs. In our approach, we design two pre-training tasks to enhance the understanding of simulated conversation for long-tail items, and adopt retrieval-augmented fine-tuning with label smoothness strategy to further improve the recommendation of long-tail items. Extensive experiments on two public CRS datasets have demonstrated the effectiveness and extensibility of our approach, especially on long-tail recommendation.Comment: work in progres

Phenylboronic ester-modified polymeric nanoparticles for promoting TRP2 peptide antigen delivery in cancer immunotherapy

The tremendous development of peptide-based cancer vaccine has attracted incremental interest as a powerful approach in cancer management, prevention and treatment. As successful as tumor vaccine has been, major challenges associated with achieving efficient immune response against cancer are (1) drainage to and retention in lymph nodes; (2) uptake by dendritic cells (DCs); (3) activation of DCs. In order to overcome these barriers, here we construct PBE-modified TRP2 nanovaccine, which comprises TRP2 peptide tumor antigen and diblock copolymer PEG-b-PAsp grafted with phenylboronic ester (PBE). We confirmed that this TRP2 nanovaccine can be effectively trapped into lymph node, uptake by dendritic cells and induce DC maturation, relying on increased negative charge, ROS response and pH response. Consistently, this vehicle loaded with TRP2 peptide could boost the strongest T cell immune response against melanoma in vivo and potentiate antitumor efficacy both in tumor prevention and tumor treatment without any exogenous adjuvant. Furthermore, the TRP2 nanovaccine can suppress the tumor growth and prolong animal survival time, which may result from its synergistic effect of inhibiting tumor immunosuppression and increasing cytotoxic lymphocyte (CTL) response. Hence this type of PBE-modified nanovaccine would be widely used as a simple, safe and robust platform to deliver other antigen in cancer immunotherapy

Strengthening dendrite suppression in lithium metal anode by in-situ construction of Li–Zn alloy layer

Abstract(#br)The lithium metal anode is one of the most attractive candidates for high-energy lithium rechargeable batteries because it has an ultrahigh theoretical specific capacity and the lowest electrode potential. Unfortunately, uncontrollable growth of dendritic Li leads to problems such as safety hazards and low cycling reversibility, which greatly hinder its commercial application. Here, a Li–Zn alloy layer is constructed in situ on Li metal foil by a simple chemical reaction of zinc trifluoromethanesulfonate with Li metal. The modified Li metal anode forms an interface with fast charge transfer kinetics and high chemical resistance to the electrolyte, which enables deposition of Li with a smooth, dense morphology without the growth of dendritic Li. In symmetrical cells, the Li metal anode with the Li–Zn alloy layer can reach a cycling lifetime of more than 500 h under a current density of 2 mA cm −2 . This work provides a simple and effective strategy to suppress the formation of Li dendrites

Comparative metabolomics analysis of milk components between Italian Mediterranean buffaloes and Chinese Holstein cows based on LC-MS/MS technology

Buffalo and cow milk have a very different composition in terms of fat, protein, and total solids. For a better knowledge of such a difference, the milk metabolic profiles and characteristics of metabolites was investigated in Italian Mediterranean buffaloes and Chinese Holstein cows were investigated by liquid chromatography tandem-mass spectrometry (LC-MS/MS) in this study. Totally, 23 differential metabolites were identified to be significantly different in the milk from the two species of which 15 were up-regulated and 8 down-regulated in Italian Mediterranean buffaloes. Metabolic pathway analysis revealed that 4 metabolites (choline, acetylcholine, nicotinamide and uric acid) were significantly enriched in glycerophospholipid metabolism, nicotinate and nicotinamide metabolism, glycine, serine and threonine metabolism, as well as purine metabolism. The results provided further insights for a deep understanding of the potential metabolic mechanisms responsible for the different performance of Italian Mediterranean buffaloes’ and Chinese Holstein cows’ milk. The findings will offer new tools for the improvement and novel directions for the development of dairy industry

Genetic diversity and runs of homozygosity analysis of Hetian sheep populations revealed by Illumina Ovine SNP50K BeadChip

Hetian sheep have a long history and a wide distribution. They are renowned for their carpet-grade wool, which makes them a valuable genetic resource in China. The survey revealed that Hetian sheep primarily inhabit three distinct ecological environments: mountains (MTS), mountain–grasslands (MGTS), and grasslands (GTS). To understand the evolutionary relationships and germplasm characteristics of Hetian sheep in these diverse environments, we randomly selected 84 healthy adult ewes from each of these ecological regions. We obtained the Illumina Ovine SNP50K BeadChip by extracting DNA from Hetian sheep ear tissue using the phenol-chloroform method. Afterward, we conducted a population genetic structure and genetic diversity analysis of Hetian sheep using the Illumina Ovine SNP50K Beadchip. Principal component analysis (PCA) and neighbor-joining (NJ) phylogenetic analysis indicated that Hetian sheep in three different ecological environments exhibit distinct genetic distances. Admixture analysis indicated that MGTS and GTS share a common ancestral origins. Additionally, the linkage disequilibrium (LD) analysis indicated that M had the highest decay rate, while MG had the lowest decay rate. Furthermore, we identified the overlapping homozygous genomic regions of Hetian sheep in the three ecological environments through runs of homozygosity (ROH) analysis. We subsequently performed gene annotation and enrichment analysis on these overlapping genomic regions. In the MTS environment, we identified 31 candidate genes associated with high-altitude environmental adaptation. These genes are involved in bone cell generation, differentiation, and the maintenance of bone homeostasis (WNT6, WNT10A, and CHSY1); tooth and tongue development (LEF1, TP63, and PRDM16); and hearing and visual functions (RBP4, ATF6, and JAG1). In the GTS environment, we identified 22 candidate genes related to economic traits, including those associated with reproduction (PLA2G4F, ACVR1, and ADCY2) and growth (CAPN3, YAP1, and FGF9). Research indicates that Hetian sheep can be divided at the genomic level into three subtypes: MTS, MGTS, and GTS. This enhances the genetic diversity of Hetian sheep germplasm resources and provides guidance for the conservation of Hetian sheep breeds. Additionally, we have identified genes related to multiparous traits in MGTS and GTS, offering insights for the selection and breeding of multiparous Hetian sheep