Large Language Models are In-Context Semantic Reasoners rather than Symbolic Reasoners

The emergent few-shot reasoning capabilities of Large Language Models (LLMs) have excited the natural language and machine learning community over recent years. Despite of numerous successful applications, the underlying mechanism of such in-context capabilities still remains unclear. In this work, we hypothesize that the learned \textit{semantics} of language tokens do the most heavy lifting during the reasoning process. Different from human's symbolic reasoning process, the semantic representations of LLMs could create strong connections among tokens, thus composing a superficial logical chain. To test our hypothesis, we decouple semantics from the language reasoning process and evaluate three kinds of reasoning abilities, i.e., deduction, induction and abduction. Our findings reveal that semantics play a vital role in LLMs' in-context reasoning -- LLMs perform significantly better when semantics are consistent with commonsense but struggle to solve symbolic or counter-commonsense reasoning tasks by leveraging in-context new knowledge. The surprising observations question whether modern LLMs have mastered the inductive, deductive and abductive reasoning abilities as in human intelligence, and motivate research on unveiling the magic existing within the black-box LLMs. On the whole, our analysis provides a novel perspective on the role of semantics in developing and evaluating language models' reasoning abilities. Code is available at {\url{https://github.com/XiaojuanTang/ICSR}}

Baechi: Fast Device Placement of Machine Learning Graphs

Machine Learning graphs (or models) can be challenging or impossible to train when either devices have limited memory, or models are large. To split the model across devices, learning-based approaches are still popular. While these result in model placements that train fast on data (i.e., low step times), learning-based model-parallelism is time-consuming, taking many hours or days to create a placement plan of operators on devices. We present the Baechi system, the first to adopt an algorithmic approach to the placement problem for running machine learning training graphs on small clusters of memory-constrained devices. We integrate our implementation of Baechi into two popular open-source learning frameworks: TensorFlow and PyTorch. Our experimental results using GPUs show that: (i) Baechi generates placement plans 654 X - 206K X faster than state-of-the-art learning-based approaches, and (ii) Baechi-placed model's step (training) time is comparable to expert placements in PyTorch, and only up to 6.2% worse than expert placements in TensorFlow. We prove mathematically that our two algorithms are within a constant factor of the optimal. Our work shows that compared to learning-based approaches, algorithmic approaches can face different challenges for adaptation to Machine learning systems, but also they offer proven bounds, and significant performance benefits.Comment: Extended version of SoCC 2020 paper: https://dl.acm.org/doi/10.1145/3419111.342130

SIK2 inhibition enhances PARP inhibitor activity synergistically in ovarian and triple-negative breast cancers

Poly(ADP-ribose) polymerase inhibitors (PARP inhibitors) have had an increasing role in the treatment of ovarian and breast cancers. PARP inhibitors are selectively active in cells with homologous recombination DNA repair deficiency caused by mutations in BRCA1/2 and other DNA repair pathway genes. Cancers with homologous recombination DNA repair proficiency respond poorly to PARP inhibitors. Cancers that initially respond to PARP inhibitors eventually develop drug resistance. We have identified salt-inducible kinase 2 (SIK2) inhibitors, ARN3236 and ARN3261, which decreased DNA double-strand break (DSB) repair functions and produced synthetic lethality with multiple PARP inhibitors in both homologous recombination DNA repair deficiency and proficiency cancer cells. SIK2 is required for centrosome splitting and PI3K activation and regulates cancer cell proliferation, metastasis, and sensitivity to chemotherapy. Here, we showed that SIK2 inhibitors sensitized ovarian and triple-negative breast cancer (TNBC) cells and xenografts to PARP inhibitors. SIK2 inhibitors decreased PARP enzyme activity and phosphorylation of class-IIa histone deacetylases (HDAC4/5/7). Furthermore, SIK2 inhibitors abolished class-IIa HDAC4/5/7–associated transcriptional activity of myocyte enhancer factor-2D (MEF2D), decreasing MEF2D binding to regulatory regions with high chromatin accessibility in FANCD2, EXO1, and XRCC4 genes, resulting in repression of their functions in the DNA DSB repair pathway. The combination of PARP inhibitors and SIK2 inhibitors provides a therapeutic strategy to enhance PARP inhibitor sensitivity for ovarian cancer and TNBC

Particular distribution and expression pattern of endoglin (CD105) in the liver of patients with hepatocellular carcinoma

<p>Abstract</p> <p>Background</p> <p>Endoglin (CD105) has been considered a prognostic marker for hepatocellular carcinoma (HCC), and widely used as an appropriate targeting for antiangenesis therapy in some cancers. Our aim was to evaluate the distribution and expression of CD105 in the liver of patients with HCC, and to discuss whether CD105 may be used as an appropriate targeting for antiangenesis therapy in HCC.</p> <p>Methods</p> <p>Three parts of liver tissues from each of 64 patients with HCC were collected: tumor tissues (TT), adjacent non-tumor (AT) liver tissues within 2 cm, and tumor free tissues (TF) 5 cm far from the tumor edge. Liver samples from 8 patients without liver diseases served as healthy controls (HC). The distribution and expression of CD105 in tissues were evaluated by immunohistochemistry, Western blotting analysis, and real-time PCR. HIF-1alpha and VEGF₁₆₅protein levels in tissues were analyzed by Immunohistochemistry and Western blotting analysis or ELISA.</p> <p>Results</p> <p>CD105 was positively stained mostly in a subset of microvessels 'endothelial sprouts' in TT of all patients while CD105 showed diffuse positive staining, predominantly on hepatic sinus endothelial cells in the surrounding of draining veins in TF and AT. The mean score of MVD-CD105 (mean ± SD/0.74 mm²) was 19.00 ± 9.08 in HC, 153.12 ± 53.26 in TF, 191.12 ± 59.17 in AT, and 85.43 ± 44.71 in TT, respectively. Using a paired <it>t </it>test, the expression of CD105 in AT and TF was higher than in TT at protein (MVD, <it>p </it>= 0.012 and <it>p </it>= 0.007, respectively) and mRNA levels (<it>p </it>< 0.001 and <it>p </it>= 0.009, respectively). Moreover, distribution and expression of CD105 protein were consistent with those of HIF-1alpha and VEGF₁₆₅protein in liver of patients with HCC. The level of <it>CD105 </it>mRNA correlated with VEGF₁₆₅level in TF (r = 0.790, <it>p </it>= 0.002), AT (r = 0.723, <it>p </it>< 0.001), and TT (r = 0.473, <it>p </it>= 0.048), respectively.</p> <p>Conclusion</p> <p>It is demonstrated that CD105 was not only present in neovessels in tumor tissues, but also more abundant in hepatic sinus endothelium in non-tumor tissues with cirrhosis. Therefore, CD105 may not be an appropriate targeting for antiangenesis therapy in HCC, especially with cirrhosis.</p

Low genetic diversity in a critically endangered primate: shallow evolutionary history or recent population bottleneck?

Abstract Background Current patterns of population genetic variation may have been shaped by long-term evolutionary history and contemporary demographic processes. Understanding the underlying mechanisms that yield those patterns is crucial for informed conservation of endangered species. The critically endangered white-headed langur, Trachypithecus leucocephalus, is endemic to a narrow range in southwest China. This species shows very low genetic diversity in its 2 main relict populations, Fusui and Chongzuo. Whether this has been caused by a short evolutionary history or recent population declines is unknown. Therefore, we investigated the contributions of historical and recent population demographic changes to population genetic diversity by using 15 nuclear microsatellite markers and mitochondrial DNA (mtDNA) control region sequences. Results Using genetic data from 214 individuals we found a total of 9 mtDNA haplotypes in the Fusui population but only 1 haplotype in the Chongzuo population, and we found an overall low genetic diversity (haplotype and nucleotide diversities: h = 0.486 ± 0.036; π = 0.0028 ± 0.0003). The demographic history inferred from mtDNA and microsatellite markers revealed no evidence for historical population size fluctuations or recent population bottlenecks. Simulations of possible population divergence histories inferred by DIYABC analysis supported a recent divergence of the Chongzuo population from the Fusui population and no population bottlenecks. Conclusions Despite severe population declines caused by anthropogenic activities in the last century, the low genetic diversity of the extant white-headed langur populations is most likely primarily due to the species’ shallow evolutionary history and to a recent, local population founder event

Acoustic emission precursor information of rock failure under true triaxial loading and unloading conditions

Rock failure generally leads to serious consequences, and it is significant to obtain the precursor information prior to failure using associated techniques. Acoustic emission (AE) is one of the indispensable methods for disaster warning of hard and brittle rock. Acoustic emission detection technology can effectively monitor real-time information about changes in the rock interior and predict the process of rock damage failure. To probe the relationship among the AE precursor information of red sandstone under different intermediate principal stresses, an experimental study was conducted by us to examine the alterations in AE parameters during the failure of red sandstone under both loading and unloading circumstances. The study shows that the ringing count rate and absolute energy versus time curves are divided into four stages, namely, quiet, frequent, sudden increase and decline periods. The cumulative count curve is also divided into four phases: pre-unloading period, post-unloading period, sharp increase period, and decrease period. With the rise of the intermediate principal stress, the ringing count rate and energy exhibited during the frequent period of AE demonstrate a consistent increase, with a larger increase in the maximum value and a smaller increase in the average value. In addition, the peak value of AE signals during failure also increases accordingly. The occurrence moment and clarity of the frequent period determine the reliability and priority of the information related to the rock’s failure precursor; moreover, the reliability and priority of the AE precursor information will increase with the increase of the intermediate principal stress. After comparison, it is found that the AE precursor information occurs prior to the thermal infrared precursor information

One-shot neural band selection for spectral recovery

Band selection has a great impact on the spectral recovery quality. To solve this ill-posed inverse problem, most band selection methods adopt hand-crafted priors or exploit clustering or sparse regularization constraints to find most prominent bands. These methods are either very slow due to the computational cost of repeatedly training with respect to different selection frequencies or different band combinations. Many traditional methods rely on the scene prior and thus are not applicable to other scenarios. In this paper, we present a novel one-shot Neural Band Selection (NBS) framework for spectral recovery. Unlike conventional searching approaches with a discrete search space and a non-differentiable search strategy, our NBS is based on the continuous relaxation of the band selection process, thus allowing efficient band search using gradient descent. To enable the compatibility for se- lecting any number of bands in one-shot, we further exploit the band-wise correlation matrices to progressively suppress similar adjacent bands. Extensive evaluations on the NTIRE 2022 Spectral Reconstruction Challenge demonstrate that our NBS achieves consistent performance gains over competitive baselines when examined with four different spectral recov- ery methods. Our code will be publicly available.Comment: Accepted by ICASSP 2023, any questions contact [email protected]

Differential expression of carotenogenic genes, associated changes on astaxanthin production and photosynthesis features induced by JA in H. pluvialis.

Haematococcus pluvialis is an organism that under certain conditions can produce astaxanthin, an economically important carotenoid. In this study, the transcriptional expression patterns of eight carotenogenic genes of H. pluvialis in response to jasmonic acid (JA) were evaluated using real-time PCR. Astaxanthin accumulation action and photosynthesis flourescence were monitored at the same time. The results showed all eight genes exhibited higher transcriptional expression significantly under JA treatments. JA25 (25 mg/L) induction had greater effect (>10-fold up-regulation) on the transcriptional expression of pds, crtR-B and lyc than on ipi-1, ipi-2, psy, bkt2, and crtO. JA50 (50 mg/L) treatment had greater impact on the transcriptional expression of ipi-1, ipi-2, psy, crtR-B and crtO than on pds, lyc and bkt2. Astaxanthin biosynthesis in the presence of JA appeared to be up-regulated mainly by psy, pds, crtR-B, lyc, bkt2 and crtO at the transcriptional level and ipi-1, ipi-2 at both transcriptional and post-transcriptional levels. Under JA induction, the photosynthetic efficiency [Y (II)] and the maximum quantum efficiency of PS II (Fv/Fm) decreased significantly, but the non-photochemical quenching of chlorophyll fluorescence (NPQ) increased drastically with the accumulation of astaxanthin

Genetically predicted obstructive sleep apnea is causally associated with an increased risk for periodontitis

Abstract Background Although obstructive sleep apnea (OSA) and periodontitis are associated, whether this association is causative is uncertain. Methods We conducted a bidirectional Mendelian randomization (MR) analysis using data from publically accessible genome-wide association studies. The single-nucleotide polymorphisms (SNPs) for OSA were derived from 16,761 cases and 201,194 controls. The pooled data of periodontitis association involved up to 17,353 individuals. Disease-associated single-nucleotide polymorphisms were selected as an instrumental variable at the genome-wide significance level (p < 5.0 × 10− 6). Subsequently, the causal effects were estimated using three different methods: inverse variance weighting (IVW), MR-Egger, and weighted median. Then, these causal estimates were expressed as dominance ratios [odds ratio (OR)]. Results The MR analysis revealed that genetically determined OSA promotes the development of periodontitis [ IVW OR = 1.117, 95% confidence interval (CI) = 1.001–1.246, p = 0.048). Furthermore, no causal effect of genetically predicted periodontitis on OSA was noted in the reverse MR analysis (IVW OR = 1, 95% CI: 0.95–1.06, p = 0.87). The trend in results from the MR-Egger regression and weighted median (WM) was consistent with that in results from the IVW method. The robustness of the results was confirmed by the sensitivity analysis. Conclusions In summary, the results of our MR investigation suggest an association between OSA and periodontitis, proposing that early screening and treatment of OSA is beneficial for the prevention and prognosis of periodontitis