Excellent Response to Anti-PD1 therapy in a Patient with Hepatocellular Carcinoma: Case Report and Review of Literature

Hepatocellular carcinoma (HCC) is an aggressive cancer associated with high mortality worldwide. HCC develops in the setting of underlying cirrhosis due to chronic liver disease. Surgery is usually considered the treatment of choice for early disease; however, most patients have locally advanced or metastatic HCC at diagnosis in which case treatments are limited. Immune checkpoint blockade of programmed death receptor-1 (PD-1) pathway offers a potential treatment strategy based on the encouraging results of the phase I/II trial of nivolumab (Checkmate 040 trial). This has led to the off-label use of nivolumab after failure of treatment with sorafenib either due to intolerance or progression of disease. Although rare (<5%), clinical response to anti-PD-1 antibody may be preceded by "pseudoprogression" -- increase in the size and number of tumor lesions before actual tumor shrinkage. We report a case of pseudoprogression followed by an excellent response in an HCC patient treated with nivolumab and review the literature for ongoing trials of immune checkpoint blockade in HCC. The pseudoprogression in our case is supported by increase in both tumor size and alpha-fetoprotein after four treatments with nivolumab; however, regression of tumor size and normalization of alpha-fetoprotein occurred after subsequent treatments. To our knowledge, there are no reports of pseudoprogression in HCC although pseudoprogression has been well described in melanoma

A Fuzzy Criticality Assessment System of Process Equipment for Optimized Maintenance Management.

yesIn modern chemical plants, it is essential to establish an effective maintenance strategy which will deliver financially driven results at optimised conditions, that is, minimum cost and time, by means of a criticality review of equipment in maintenance. In this article, a fuzzy logic-based criticality assessment system (FCAS) for the management of a local company’s equipment maintenance is introduced. This fuzzy system is shown to improve the conventional crisp criticality assessment system (CCAS). Results from case studies show that not only can the fuzzy logic-based system do what the conventional crisp system does but also it can output more criticality classifications with an improved reliability and a greater number of different ratings that account for fuzziness and individual voice of the decision-makers

Development of a neuro-fuzzy technique for automated parameter optimization of inverse treatment planning

<p>Abstract</p> <p>Background</p> <p>Parameter optimization in the process of inverse treatment planning for intensity modulated radiation therapy (IMRT) is mainly conducted by human planners in order to create a plan with the desired dose distribution. To automate this tedious process, an artificial intelligence (AI) guided system was developed and examined.</p> <p>Methods</p> <p>The AI system can automatically accomplish the optimization process based on prior knowledge operated by several fuzzy inference systems (FIS). Prior knowledge, which was collected from human planners during their routine trial-and-error process of inverse planning, has first to be "translated" to a set of "if-then rules" for driving the FISs. To minimize subjective error which could be costly during this knowledge acquisition process, it is necessary to find a quantitative method to automatically accomplish this task. A well-developed machine learning technique, based on an adaptive neuro fuzzy inference system (ANFIS), was introduced in this study. Based on this approach, prior knowledge of a fuzzy inference system can be quickly collected from observation data (clinically used constraints). The learning capability and the accuracy of such a system were analyzed by generating multiple FIS from data collected from an AI system with known settings and rules.</p> <p>Results</p> <p>Multiple analyses showed good agreements of FIS and ANFIS according to rules (error of the output values of ANFIS based on the training data from FIS of 7.77 ± 0.02%) and membership functions (3.9%), thus suggesting that the "behavior" of an FIS can be propagated to another, based on this process. The initial experimental results on a clinical case showed that ANFIS is an effective way to build FIS from practical data, and analysis of ANFIS and FIS with clinical cases showed good planning results provided by ANFIS. OAR volumes encompassed by characteristic percentages of isodoses were reduced by a mean of between 0 and 28%.</p> <p>Conclusion</p> <p>The study demonstrated a feasible way to automatically perform parameter optimization of inverse treatment planning under guidance of prior knowledge without human intervention other than providing a set of constraints that have proven clinically useful in a given setting.</p

jFuzzyLogic: a Java Library to Design Fuzzy Logic Controllers According to the Standard for Fuzzy Control Programming

Fuzzy Logic Controllers are a specific model of Fuzzy Rule Based Systems suitable for engineering applications for which classic control strategies do not achieve good results or for when it is too difficult to obtain a mathematical model. Recently, the International Electrotechnical Commission has published a standard for fuzzy control programming in part 7 of the IEC 61131 norm in order to offer a well defined common understanding of the basic means with which to integrate fuzzy control applications in control systems. In this paper, we introduce an open source Java library called jFuzzyLogic which offers a fully functional and complete implementation of a fuzzy inference system according to this standard, providing a programming interface and Eclipse plugin to easily write and test code for fuzzy control applications. A case study is given to illustrate the use of jFuzzyLogic.McGill Uninversity, Genome QuebecSpanish Government TIN2011-28488Andalusian Government P10-TIC-685

Fuzzy control of the production environment process parameters

The fuzzy control process for support of given microclimatic production environment process parameters with loss of one from values, regulating regime of process was shown. The structural schematic decisions with algorithm of functioning and oriented to existing apparatus (means of realization) was presented

A Decolonial Critique of the Racialized “Localwashing” of Extraction in Central Africa

Responding to calls for increased attention to actions and reactions “from above” within the extractive industry, we offer a decolonial critique of the ways in which corporate entities and multinational institutions propagate racialized rhetoric of “local” suffering, “local” consultation, and “local” fault for failure in extractive zones. Such rhetoric functions to legitimize extractive intervention within a set of practices that we call localwashing. Drawing from a decade of research on and along the Chad-Cameroon Oil Pipeline, we show how multi-scalar actors converged to assert knowledge of, responsibility for, and collaborations with “local” people within a racialized politics of scale. These corporate representations of the racialized “local” are coded through long-standing colonial tropes. We identify three interrelated and overlapping flexian elite rhetoric(s) and practices of racialized localwashing: (a) anguishing, (b) arrogating, and (c) admonishing. These elite representations of a racialized “local” reveal diversionary efforts “from above” to manage public opinion, displace blame for project failures, and domesticate dissent in a context of persistent scrutiny and criticism from international and regional advocates and activists