Evaluating and Enhancing Large Language Models for Conversational Reasoning on Knowledge Graphs

The development of large language models (LLMs) has been catalyzed by advancements in pre-training techniques. These models have demonstrated robust reasoning capabilities through manually designed prompts. In this work, we evaluate the conversational reasoning capabilities of the current state-of-the-art LLM (GPT-4) on knowledge graphs (KGs). However, the performance of LLMs is constrained due to a lack of KG environment awareness and the difficulties in developing effective optimization mechanisms for intermediary reasoning stages. We further introduce LLM-ARK, a LLM grounded KG reasoning agent designed to deliver precise and adaptable predictions on KG paths. LLM-ARK leverages Full Textual Environment (FTE) prompt to assimilate state information within each reasoning step. We reframe the challenge of multi-hop reasoning on the KG as a sequential decision-making task. Utilizing the Proximal Policy Optimization (PPO) online policy gradient reinforcement learning algorithm, our model is optimized to learn from rich reward signals. Additionally, we conduct an evaluation of our model and GPT-4 on the OpenDialKG dataset. The experimental results reveal that LLaMA-2-7B-ARK outperforms the current state-of-the-art model by 5.28 percentage points, with a performance rate of 36.39% on the target@1 evaluation metric. Meanwhile, GPT-4 scored 14.91%, further demonstrating the effectiveness of our method. Our code is available on GitHub (https://github.com/Aipura/LLM-ARK) for further access

Research on characteristics of removing particles in ship exhaust gas by charged droplet

A traditional water scrubber is able to remove particles with a size over 200 μm in ship engine exhaust effectively. However, as the size of the particles decreases, the removal efficiency of the particles is gradually reduced, especially when the particle size is less than 50 μm, the method almost has little effect. This paper presents a study of charging particles in exhaust gas and water droplets to improve water scrubber’s efficiency in removing fine particles. The charging of the particles is mainly achieved through corona discharge, while the water droplets are charged by passing the high-voltage electricity to the nozzle. However, the feasibility and economics of these two methods have not been verified in other researches, so they are numerically simulated by Comsol Multiphysics software in this paper. The simulation results show that both particles and droplets can be charged steadily by the two methods. The numerical simulation results also indicate that the removal efficiency of particles in ship exhaust gas can be greatly improved by adding charges to droplets and particles at the same time. And a line chart of particle capture efficiency map under different particle sizes and change of droplets is obtained

Alteration of Innate Immunity by Donor IL-6 Deficiency in a Presensitized Heart Transplant Model

Engraftment of IL-6 deficient donor into wild-type recipient could significantly improve allograft survival through T cell lineage particularly regulatory T cells (Tregs) in non-sensitized transplant host. However, its effect on innate immune responses remains uncertain. Our data revealed that donor IL-6 deficiency significantly increased infiltration of two subsets of MDSCs (CD11b+Gr1+myeloid-derived suppressor cells), CD11b+Gr1-low and CD11b+Gr1-int with strong immunosuppression activity in the transplanted graft. It resulted in a dramatic increase of CD11b+Gr1-low frequency and a significant decrease of the frequency of CD11b+Gr1-high and CD4-CD8-NK1.1+ cells in the recipient’s spleen. Unexpectedly, donor IL-6 deficiency could not significantly reduce macrophage frequency irrespective of in the host’s spleen or graft. Taken together, suppression of innate immune effector cells and enhanced activity of regulatory MDSCs contributed to tolerance induction by blockade of IL-6 signaling pathway. The unveiled novel mechanism of targeting IL-6 might shed light on clinical therapeutic application in preventing accelerated allograft rejection for those pre-sensitized transplant recipients

Comparison of bladder carcinogenesis biomarkers in the urine of traditional cigarette users and e-cigarette users

BackgroundDuring the use of electronic cigarettes (e-cigarettes), users are still exposed to carcinogens similar to those found in tobacco products. Since these carcinogens are metabolized and excreted in urine, they may have carcinogenic effects on the bladder urinary tract epithelium. This meta-analysis aimed to compare bladder cancer carcinogens in the urine of tobacco users and e-cigarette users using a large number of samples.MethodsA systematic meta-analysis was performed using data obtained from several scientific databases (up to November 2023). This cumulative analysis was performed following the Preferred Reporting Items for Systematic Evaluation and Meta-Analysis (PRISMA) and Assessing the Methodological Quality of Systematic Evaluations (AMSTAR) guidelines, according to a protocol registered with PROSPERO. This study was registered on PROSPERO and obtained the unique number: CRD42023455600.ResultsThe analysis included 10 high-quality studies that considered polycyclic aromatic hydrocarbons (PAHs), volatile organic compounds (VOCs) and tobacco-specific nitrosamines (TSNAs). Statistical indicators show that there is a difference between the tobacco user group and the e-cigarette user group in terms of 1-Hydroxynaphthalene (1-NAP) [weighted mean difference (WMD)10.14, 95% confidence interval (CI) (8.41 to 11.88), p < 0.05], 1-Hydroxyphenanthrene (1-PHE) [WMD 0.08, 95% CI (−0.14 to 0.31), p > 0.05], 1-Hydroxypyrene (1-PYR) [WMD 0.16, 95% CI (0.12 to 0.20), p < 0.05], 2-Hydroxyfluorene (2-FLU) [WMD 0.69, 95% CI (0.58 to 0.80), p < 0.05], 2-Hydroxynaphthalene (2-NAP) [WMD 7.48, 95% CI (4.15 to 10.80), p < 0.05], 3-Hydroxyfluorene (3-FLU) [WMD 0.57, 95% CI (0.48 to 0.66), p < 0.05], 2-Carbamoylethylmercapturic acid (AAMA) [WMD 66.47, 95% CI (27.49 to 105.46), p < 0.05], 4-Hydroxy-2-buten-1-yl-mercapturic acid (MHBMA) [WMD 287.79, 95% CI (−54.47 to 630.04), p > 0.05], 4-(Methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNAL) [WMD 189.37, 95% CI (78.45 to 300.29), p < 0.05], or N0-nitrosonornicotine (NNN) [WMD 11.66, 95% CI (7.32 to 16.00), p < 0.05].ConclusionUrinary bladder cancer markers were significantly higher in traditional tobacco users than in e-cigarette users.Systematic review registration: PROSPERO (CRD42023455600: https://www.crd.york.ac.uk/PROSPERO/)

Can Large Language Models Understand Real-World Complex Instructions?

Large language models (LLMs) can understand human instructions, showing their potential for pragmatic applications beyond traditional NLP tasks. However, they still struggle with complex instructions, which can be either complex task descriptions that require multiple tasks and constraints, or complex input that contains long context, noise, heterogeneous information and multi-turn format. Due to these features, LLMs often ignore semantic constraints from task descriptions, generate incorrect formats, violate length or sample count constraints, and be unfaithful to the input text. Existing benchmarks are insufficient to assess LLMs' ability to understand complex instructions, as they are close-ended and simple. To bridge this gap, we propose CELLO, a benchmark for evaluating LLMs' ability to follow complex instructions systematically. We design eight features for complex instructions and construct a comprehensive evaluation dataset from real-world scenarios. We also establish four criteria and develop corresponding metrics, as current ones are inadequate, biased or too strict and coarse-grained. We compare the performance of representative Chinese-oriented and English-oriented models in following complex instructions through extensive experiments. Resources of CELLO are publicly available at https://github.com/Abbey4799/CELLO

Engineering brown fat into skeletal muscle using ultrasound-targeted microbubble destruction gene delivery in obese Zucker rats: Proof of concept design

plasmid cDNA contructs encoding a gene cocktail with BMP7/ PRDM16/PPARGC1A incorporated within microbubbles and intravenously delivered into their left thigh. Controls received UTMD with plasmids driving a DsRed reporter gene. An ultrasound transducer was directed to the thigh to disrupt the microbubbles within the microcirculation. Blood samples were drawn at baseline, and after treatment to measure glucose, insulin, and free fatty acids level

Mechanical properties of AlSi10Mg alloy fabricated by laser melting deposition and improvements via heat treatment

Process optimization and heat treatment of AlSi10Mg aluminum alloy parts fabricated by laser melting deposition (LMD) based on coaxial powder feeding are conducted in this paper to improve manufacturing quality. The microstructures and mechanical properties of the LMD-built AlSi10Mg alloy parts are systematically investigated. Experimental results show the relative density of the block samples increase to 99.2% without larger pores and cracks after process optimization. The sample microstructures are found to display directional rapid solidification characteristics, with the Al-Si eutectic microstructure containing three microstructures being cellular, columnar dendrites and divergent dendrites. With solution and artificial aging heat treatments, Si atoms are rejected from the supersaturated Al matrix to form small Si granular particles. The heat treated samples display a uniform microstructure without heterogeneities and the microhardness remains stable at 118 HV. When the as-built sample is heat treated for solution time 2h, tensile strength increases from 292 MPa to 342 MPa due to the formation of strengthening phase Mg2Si

How to Best Convey Information About Intensive/Comfort Care to the Family Members of Premature Infants to Enable Unbiased Perinatal Decisions

Background: As the infant's best interests are determined through the perinatal decisions of family members and physicians, it is important to understand the factors that affect such decisions. This paper investigated the separate and combined effects of various factors related to perinatal decision making and sought to determine the best way to convey information in an unbiased manner to family members.Methods: In total, 613 participants were consecutively recruited. Each participant completed a series of surveys. All responses to four items were examined via a latent class analysis (LCA) to identify subgroups of participants with similar preferences for intensive care (IC) and comfort care (CC) regarding their potentially premature infant. Multiple logistic regression analyses were applied to identify the sociodemographic predictors for the classification of participants into different subgroups.Results: χ2-tests indicated that perinatal decision making for Item 2 was influenced by framing information, whereas decision making wasn't affected by presentation modes. Furthermore, the endorsement rates of IC significantly decreased with the information increased from brief to detailed, regardless of framing or presentation mode. The LCA indicated that a 3-subgroup model, which included the IC, CC, and variation subgroups, was optimal. Logistic regression analyses demonstrated that, compared with the IC subgroup, negative framing, higher education, parenthood, and poor numeracy predicted participants' preferences for CC. Meanwhile, worrying about physical or mental disabilities predicted preferences for CC and sensitivity to the amount of information provided regarding treatment options (variation subgroup).Conclusions: Perinatal decision making is affected by many factors, suggesting that more detailed information, improved understandability of numerical data, and a neutral tone of voice regarding therapeutic outcomes would be helpful for the families of premature infants to make unbiased decisions. Our findings should be replicated in future research

Variants at multiple loci implicated in both innate and adaptive immune responses are associated with Sjögren’s syndrome

Sjögren’s syndrome is a common autoimmune disease (~0.7% of European Americans) typically presenting as keratoconjunctivitis sicca and xerostomia. In addition to strong association within the HLA region at 6p21 (Pmeta=7.65×10−114), we establish associations with IRF5-TNPO3 (Pmeta=2.73×10−19), STAT4 (Pmeta=6.80×10−15), IL12A (Pmeta =1.17×10−10), FAM167A-BLK (Pmeta=4.97×10−10), DDX6-CXCR5 (Pmeta=1.10×10−8), and TNIP1 (Pmeta=3.30×10−8). Suggestive associations with Pmeta<5×10−5 were observed with 29 regions including TNFAIP3, PTTG1, PRDM1, DGKQ, FCGR2A, IRAK1BP1, ITSN2, and PHIP amongst others. These results highlight the importance of genes involved in both innate and adaptive immunity in Sjögren’s syndrome

The LifeCycle Project-EU Child Cohort Network : a federated analysis infrastructure and harmonized data of more than 250,000 children and parents

Early life is an important window of opportunity to improve health across the full lifecycle. An accumulating body of evidence suggests that exposure to adverse stressors during early life leads to developmental adaptations, which subsequently affect disease risk in later life. Also, geographical, socio-economic, and ethnic differences are related to health inequalities from early life onwards. To address these important public health challenges, many European pregnancy and childhood cohorts have been established over the last 30 years. The enormous wealth of data of these cohorts has led to important new biological insights and important impact for health from early life onwards. The impact of these cohorts and their data could be further increased by combining data from different cohorts. Combining data will lead to the possibility of identifying smaller effect estimates, and the opportunity to better identify risk groups and risk factors leading to disease across the lifecycle across countries. Also, it enables research on better causal understanding and modelling of life course health trajectories. The EU Child Cohort Network, established by the Horizon2020-funded LifeCycle Project, brings together nineteen pregnancy and childhood cohorts, together including more than 250,000 children and their parents. A large set of variables has been harmonised and standardized across these cohorts. The harmonized data are kept within each institution and can be accessed by external researchers through a shared federated data analysis platform using the R-based platform DataSHIELD, which takes relevant national and international data regulations into account. The EU Child Cohort Network has an open character. All protocols for data harmonization and setting up the data analysis platform are available online. The EU Child Cohort Network creates great opportunities for researchers to use data from different cohorts, during and beyond the LifeCycle Project duration. It also provides a novel model for collaborative research in large research infrastructures with individual-level data. The LifeCycle Project will translate results from research using the EU Child Cohort Network into recommendations for targeted prevention strategies to improve health trajectories for current and future generations by optimizing their earliest phases of life.Peer reviewe