LLM-FuncMapper: Function Identification for Interpreting Complex Clauses in Building Codes via LLM

As a vital stage of automated rule checking (ARC), rule interpretation of regulatory texts requires considerable effort. However, interpreting regulatory clauses with implicit properties or complex computational logic is still challenging due to the lack of domain knowledge and limited expressibility of conventional logic representations. Thus, LLM-FuncMapper, an approach to identifying predefined functions needed to interpret various regulatory clauses based on the large language model (LLM), is proposed. First, by systematically analysis of building codes, a series of atomic functions are defined to capture shared computational logics of implicit properties and complex constraints, creating a database of common blocks for interpreting regulatory clauses. Then, a prompt template with the chain of thought is developed and further enhanced with a classification-based tuning strategy, to enable common LLMs for effective function identification. Finally, the proposed approach is validated with statistical analysis, experiments, and proof of concept. Statistical analysis reveals a long-tail distribution and high expressibility of the developed function database, with which almost 100% of computer-processible clauses can be interpreted and represented as computer-executable codes. Experiments show that LLM-FuncMapper achieve promising results in identifying relevant predefined functions for rule interpretation. Further proof of concept in automated rule interpretation also demonstrates the possibility of LLM-FuncMapper in interpreting complex regulatory clauses. To the best of our knowledge, this study is the first attempt to introduce LLM for understanding and interpreting complex regulatory clauses, which may shed light on further adoption of LLM in the construction domain

Finite volume effects of the Nambu-Jona-Lasinio model with the running coupling constant

With the Schwinger's proper-time formalism of the Nambu-Jona-Lasinio model, we investigate the finite volume effects in the presence of magnetic fields. Since the coupling constant $G$ can be influenced by strong magnetic fields, the model is solved with a running coupling constant $G(B)$ which is fitted by the lattice average $(\Sigma_u+\Sigma_d)/2$ and difference $\Sigma_u-\Sigma_d$. The investigation mainly focuses on the constituent quark mass and the thermal susceptibility depending on the magnetic fields, the temperatures and the finite sizes. For the model in finite or infinite volume, the magnetic fields can increase the constituent quark mass while the temperatures can decrease it inversely. There is a narrow range of the box length that makes the effects of finite volume perform prominently. The model will behave close to infinite volume limit for larger box length. It is shown that the influence of finite volume can be changed by magnetic fields and temperatures. Finally, we discuss the thermal susceptibility depending on the temperature in finite volume in the presence of magnetic fields.Comment: 13 pages, 6 figure

Nanobubbles for enhanced ultrasound imaging of tumors

The fabrication and initial applications of nanobubbles (NBs) have shown promising results in recent years. A small particle size is a basic requirement for ultrasound contrast-enhanced agents that penetrate tumor blood vessel pores to allow for targeted imaging and therapy. However, the nanoscale size of the particles used has the disadvantage of weakening the imaging ability of clinical diagnostic ultrasound. In this work, we fabricated a lipid NBs contrast-enhanced ultrasound agent and evaluated its passive targeting ability in vivo. The results showed that the NBs were small (436.8 ± 5.7 nm), and in vitro ultrasound imaging suggested that the ultrasonic imaging ability is comparable to that of microbubbles (MBs). In vivo experiments confirmed the ability of NBs to passively target tumor tissues. The NBs remained in the tumor area for a longer period because they exhibited enhanced permeability and retention. Direct evidence was obtained by direct observation of red fluorescence-dyed NBs in tumor tissue using confocal laser scanning microscopy. We have demonstrated the ability to fabricate NBs that can be used for the in vivo contrast-enhanced imaging of tumor tissue and that have potential for drug/gene delivery

Effectiveness of laparoscopic sleeve gastrectomy for weight loss and obesity-associated co-morbidities: a 3-year outcome from Mainland Chinese patients

AbstractBackgroundLaparoscopic sleeve gastrectomy (LSG) is becoming a stand-alone bariatric surgery for obesity, but its effectiveness for Mainland Chinese patients remains unclear.ObjectivesTo evaluate the effectiveness and safety of LSG for Mainland Chinese patientsSettingA tertiary hospitalMethodsRetrospective analysis of patients admitted for LSG between January 2011 and February 2012 was performed. Medium-term outcome measures were: total weight loss (%TWL), excess weight loss (%EWL), co-morbidities, improvement, and complications.ResultsSeventy patients (body mass index [BMI] 40.8±5.9 kg/m2) underwent LSG, comprising 40 women and 30 men. The most common co-morbidity was diabetes (n = 29, 41.4%). Lost to follow-up rate for weight loss was 15.7%, 31.4%, and 41% at 1, 2, and 3 years. The %TWL was 34.4±6.1, 34.7±6.2 and 33.7±7.1 at 1, 2, and 3 years. The %EWL increased to 77.1±13.0, 77.9±12.2 and 77.2±13.1 at 1, 2, and 3years. The proportions of patients having successful weight loss were 100% or 85% at 3 years according the definition of %TWL>10% or %EWL>50%. Approximately 79.3%, 51.7%, and 44.8% of patients completed follow-up for glycemic control at each time point, respectively. The proportions of patients with optimal glycemic control (fasting blood glucose [FBG]<5.6 mmol/L; hemoglobin A1C [HbA1C]<6.5%) were 47.9%, 60.0%, and 69.2% at 1, 2, and 3years. The weight loss and glycemic control effect may be greater in the high BMI group (≥40 kg/m2). Early and late complications occurred in 8.6% and 7.1% of patients during follow-up.ConclusionsLSG is effective in weight loss and glycemic control and is safe for Mainland Chinese obese patients, especially for patients with a BMI≥40 kg/m2

Prevalence of insomnia symptoms and their associated factors in patients treated in outpatient clinics of four general hospitals in Guangzhou, China

Background: Data on the prevalence of insomnia symptoms in medical outpatient clinics in China are lacking. This study examined the prevalence of insomnia symptoms and their socio-demographic correlates in patients treated at medical outpatient clinics affiliated with four general hospitals in Guangzhou, a large metropolis in southern China. Method: A total of 4399 patients were consecutively invited to participate in the study. Data on insomnia and its socio-demographic correlates were collected with standardized questionnaires. Results: The prevalence of any type of insomnia symptoms was 22.1% (95% confidence interval (CI): 20.9–23.3%); the prevalence of difficulty initiating sleep was 14.3%, difficulty maintaining sleep was 16.2%, and early morning awakening was 12.4%. Only 17.5% of the patients suffering from insomnia received sleeping pills. Multiple logistic regression analysis revealed that male gender, education level, rural residence, and being unemployed or retired were negatively associated with insomnia symptoms, while lacking health insurance, older age and more severe depressive symptoms were positively associated with insomnia symptoms. Conclusions: Insomnia symptoms are common in patients attending medical outpatient clinics in Guangzhou. Increasing awareness of sleep hygiene measures, regular screening and psychosocial and pharmacological interventions for insomnia are needed in China. Trial registration: ChiCTR-INR-16008066. Registered 8 March 2016

DSHGT: Dual-Supervisors Heterogeneous Graph Transformer -- A pioneer study of using heterogeneous graph learning for detecting software vulnerabilities

Vulnerability detection is a critical problem in software security and attracts growing attention both from academia and industry. Traditionally, software security is safeguarded by designated rule-based detectors that heavily rely on empirical expertise, requiring tremendous effort from software experts to generate rule repositories for large code corpus. Recent advances in deep learning, especially Graph Neural Networks (GNN), have uncovered the feasibility of automatic detection of a wide range of software vulnerabilities. However, prior learning-based works only break programs down into a sequence of word tokens for extracting contextual features of codes, or apply GNN largely on homogeneous graph representation (e.g., AST) without discerning complex types of underlying program entities (e.g., methods, variables). In this work, we are one of the first to explore heterogeneous graph representation in the form of Code Property Graph and adapt a well-known heterogeneous graph network with a dual-supervisor structure for the corresponding graph learning task. Using the prototype built, we have conducted extensive experiments on both synthetic datasets and real-world projects. Compared with the state-of-the-art baselines, the results demonstrate promising effectiveness in this research direction in terms of vulnerability detection performance (average F1 improvements over 10\% in real-world projects) and transferability from C/C++ to other programming languages (average F1 improvements over 11%)

Optimized sample preparation for two-dimensional gel electrophoresis of soluble proteins from chicken bursa of Fabricius

<p>Abstract</p> <p>Background</p> <p>Two-dimensional gel electrophoresis (2-DE) is a powerful method to study protein expression and function in living organisms and diseases. This technique, however, has not been applied to avian bursa of Fabricius (BF), a central immune organ. Here, optimized 2-DE sample preparation methodologies were constructed for the chicken BF tissue. Using the optimized protocol, we performed further 2-DE analysis on a soluble protein extract from the BF of chickens infected with virulent avibirnavirus. To demonstrate the quality of the extracted proteins, several differentially expressed protein spots selected were cut from 2-DE gels and identified by matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS).</p> <p>Results</p> <p>An extraction buffer containing 7 M urea, 2 M thiourea, 2% (w/v) 3-[(3-cholamidopropyl)-dimethylammonio]-1-propanesulfonate (CHAPS), 50 mM dithiothreitol (DTT), 0.2% Bio-Lyte 3/10, 1 mM phenylmethylsulfonyl fluoride (PMSF), 20 U/ml Deoxyribonuclease I (DNase I), and 0.25 mg/ml Ribonuclease A (RNase A), combined with sonication and vortex, yielded the best 2-DE data. Relative to non-frozen immobilized pH gradient (IPG) strips, frozen IPG strips did not result in significant changes in the 2-DE patterns after isoelectric focusing (IEF). When the optimized protocol was used to analyze the spleen and thymus, as well as avibirnavirus-infected bursa, high quality 2-DE protein expression profiles were obtained. 2-DE maps of BF of chickens infected with virulent avibirnavirus were visibly different and many differentially expressed proteins were found.</p> <p>Conclusion</p> <p>These results showed that method C, in concert extraction buffer IV, was the most favorable for preparing samples for IEF and subsequent protein separation and yielded the best quality 2-DE patterns. The optimized protocol is a useful sample preparation method for comparative proteomics analysis of chicken BF tissues.</p