Implementing fault tolerant applications using reflective object-oriented programming

Abstract: Shows how reflection and object-oriented programming can be used to ease the implementation of classical fault tolerance mechanisms in distributed applications. When the underlying runtime system does not provide fault tolerance transparently, classical approaches to implementing fault tolerance mechanisms often imply mixing functional programming with non-functional programming (e.g. error processing mechanisms). The use of reflection improves the transparency of fault tolerance mechanisms to the programmer and more generally provides a clearer separation between functional and non-functional programming. The implementations of some classical replication techniques using a reflective approach are presented in detail and illustrated by several examples, which have been prototyped on a network of Unix workstations. Lessons learnt from our experiments are drawn and future work is discussed

The History and Outlook of Animal Drugs Treating Asthma, Chronic Bronchitis, and Haze Episode-induced Respiratory Diseases

Animal drugs have been historically applied in Chinese remedies for more than two thousands. It was reported that Chinese medical animals consisting of 1,590 species took up 12.5% of the total number of all TCM resources. Those animal drugs such as, earthworm, gecko, periostracum cicadae, and scorpios, of commonly used in China, are very remarkable and traditional for the treatment of asthma or chronic bronchitis. This review presents research advance of animal drugs possessing significant implications for the development of novel anti-asthma or chronic bronchitis drugs. The experimental studies and clinical efficacies against asthma and chronic bronchitis of animal drugs were summarized herein. Moreover, the potential utilization of animal drugs on inhibiting haze/fog induced respiratory diseases was also discusse

Whole-lesion histogram analysis of multiple diffusion metrics for differentiating lung cancer from inflammatory lesions

BackgroundWhole-lesion histogram analysis can provide comprehensive assessment of tissues by calculating additional quantitative metrics such as skewness and kurtosis; however, few studies have evaluated its value in the differential diagnosis of lung lesions.PurposeTo compare the diagnostic performance of conventional diffusion-weighted imaging (DWI), intravoxel incoherent motion (IVIM) magnetic resonance imaging (MRI) and diffusion kurtosis imaging (DKI) in differentiating lung cancer from focal inflammatory lesions, based on whole-lesion volume histogram analysis.MethodsFifty-nine patients with solitary pulmonary lesions underwent multiple b-values DWIs, which were then postprocessed using mono-exponential, bi-exponential and DKI models. Histogram parameters of the apparent diffusion coefficient (ADC), true diffusivity (D), pseudo-diffusion coefficient (D*), and perfusion fraction (f), apparent diffusional kurtosis (Kapp) and kurtosis-corrected diffusion coefficient (Dapp) were calculated and compared between the lung cancer and inflammatory lesion groups. Receiver operating characteristic (ROC) curves were constructed to evaluate the diagnostic performance.ResultsThe ADCmean, ADCmedian, Dmean and Dmedian values of lung cancer were significantly lower than those of inflammatory lesions, while the ADCskewness, Kappmean, Kappmedian, KappSD, Kappkurtosis and Dappskewness values of lung cancer were significantly higher than those of inflammatory lesions (all p < 0.05). ADCskewness (p = 0.019) and Dmedian (p = 0.031) were identified as independent predictors of lung cancer. Dmedian showed the best performance for differentiating lung cancer from inflammatory lesions, with an area under the ROC curve of 0.777. Using a Dmedian of 1.091 × 10-3 mm2/s as the optimal cut-off value, the sensitivity, specificity, positive predictive value and negative predictive value were 69.23%, 85.00%, 90.00% and 58.62%, respectively.ConclusionsWhole-lesion histogram analysis of DWI, IVIM and DKI parameters is a promising approach for differentiating lung cancer from inflammatory lesions, and Dmedian shows the best performance in the differential diagnosis of solitary pulmonary lesions

ChatRadio-Valuer: A Chat Large Language Model for Generalizable Radiology Report Generation Based on Multi-institution and Multi-system Data

Radiology report generation, as a key step in medical image analysis, is critical to the quantitative analysis of clinically informed decision-making levels. However, complex and diverse radiology reports with cross-source heterogeneity pose a huge generalizability challenge to the current methods under massive data volume, mainly because the style and normativity of radiology reports are obviously distinctive among institutions, body regions inspected and radiologists. Recently, the advent of large language models (LLM) offers great potential for recognizing signs of health conditions. To resolve the above problem, we collaborate with the Second Xiangya Hospital in China and propose ChatRadio-Valuer based on the LLM, a tailored model for automatic radiology report generation that learns generalizable representations and provides a basis pattern for model adaptation in sophisticated analysts' cases. Specifically, ChatRadio-Valuer is trained based on the radiology reports from a single institution by means of supervised fine-tuning, and then adapted to disease diagnosis tasks for human multi-system evaluation (i.e., chest, abdomen, muscle-skeleton, head, and maxillofacial $\&$ neck) from six different institutions in clinical-level events. The clinical dataset utilized in this study encompasses a remarkable total of \textbf{332,673} observations. From the comprehensive results on engineering indicators, clinical efficacy and deployment cost metrics, it can be shown that ChatRadio-Valuer consistently outperforms state-of-the-art models, especially ChatGPT (GPT-3.5-Turbo) and GPT-4 et al., in terms of the diseases diagnosis from radiology reports. ChatRadio-Valuer provides an effective avenue to boost model generalization performance and alleviate the annotation workload of experts to enable the promotion of clinical AI applications in radiology reports

Selective applications of excisional surgical treatments of cervical precancers

Cervical precancers encompass high-grade squamous intraepithelial lesion and adenocarcinoma in situ. Treatment of precancerous lesions can reduce cervical cancer mortality and prevent the development of invasive cervical cancer. The choice of treatment regimen needs to follow the principle of individualization and should be based on a combination of factors, including the patient's age, fertility requirements, pregnancy status, pathological type, type of colposcopic transformation zone, patient's follow-up conditions, and the experience of the treating provider. This article presents an opinion regarding the appropriate indications for excisional surgery and total hysterectomy in the management of precancerous lesions of the cervix, with the aim of establishing standardized therapeutic approaches for the treatment of precancerous lesions of the cervix

Using Metaobject Protocols to Separate Functional and Non-Functional Concerns: An Example

: One of the key ideas underlying the DeVa conceptual framework is the notion of using reflection as a general approach to implementing non-functional requirements such as dependability and distribution transparency in a way that is transparent to application programmers [Stroud 1993]. In this paper, we use the example of atomic data types to explain why we believe that reflection is an appropriate way of implementing these kinds of non-functional requirements transparently by contrasting a conventional implementation of atomic data types with a reflective implementation [Stroud & Wu 1995]. We also discuss the kind of support that needs to be provided by reflective language systems for this kind of programming. 1. Introduction We are interested in using reflection as a general approach to implementing nonfunctional requirements such as dependability and distribution transparency in a way that is transparent to application programmers [Stroud 1993]. In this paper, we use the example of..