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The mismatch problem is commonly happened in photovoltaic systems due to partial shading conditions. Distributed maximum power point tracking architectures can be used to solve such problem. Reinforcement learning (RL) method, which is one of the advanced artificial intelligence methods is proposed to improve the tracking speed. However, the drawbacks, such as the lack of limited adaptability and exploration–exploitation tradeoff theory, make the RL method low in efficiency. Therefore, this article combines the Beta method and $\varepsilon$–greedy algorithm with the RL method to address this problem. The simulation and experimental tests have been carried out and the result shows the efficiency of the proposed RL method is up to 96.85%, which verifies the superiority of the proposed scheme.

The authors, part of the International Consortium on Innovation and Quality in Pharmaceutical Development (IQ Consortium), explore and define common industry approaches and practices when applying GMPs in early development. [...]

Potential genotoxic impurities (PGI) are chemical compounds that could potentially damage DNA and lead to mutation. Controlling the occurrence of PGIs in active pharmaceutical ingredients (APIs) poses a big challenge for chemists, as levels of these compounds must be reduced well below the amounts required for other types of less toxic impurities. In situations where formation of PGIs cannot be avoided, an ideal solution would allow the complete removal of PGIs after the synthesis is complete, for example, by recrystallization, preparative chromatography or other downstream processing approaches. Some disadvantages of using these approaches are potential high yield loss, high solvent consumption, and additional time and resources required for process development. In this work, we present a simple and rapid approach to remove electrophilic PGIs from APIs. A selected nucleophilic resin can be added to the final API solution to reduce or totally remove the PGI. Esters of methanesulfonic acid (MSA), benzenesulfonic acid (BSA), and p-toluenesulfonic acid (pTSA) were used as model electrophilic PGIs. Several nucleophilic resins were screened, and the resins with the highest efficiency of PGI removal were chosen. A recommended procedure is presented for the removal of MSA, BSA, and pTSA esters. The kinetics of PGI removal, resin loading capacity, solvent effects, and API matrix effects are demonstrated.

A simple and safe prototype apparatus was designed and adapted for the in situ determination of the moisture content of a cytotoxic compound (9-fluorenylmethyl-protected doxorubicin-peptide conjugate, or Fm-DPC) by near-infrared absorbance spectroscopy during optimization of the chemical isolation procedure. The cytotoxic nature of the compound restricts one's ability to safely sample such drying processes for more traditional means of moisture determination for fear of hazardous solids dusting, hence in situ sampling approaches are of great importance. These concerns also exist for the process development laboratory, where despite the smaller scale of operations, the volume of experiments (hence cytotoxic samples) required to define a chemical process is often more significant. In this application, partial least squares regression was used with Karl Fischer volumetric titration analysis to generate a calibration model. Although pronounced differences in cake density were observed as a function of the buffer selected for the isolation process, the model still achieved a standard error of calibration of 0.63% w/w and a standard error of prediction of 0.99% (w/w). These results demonstrated the versatility of the prototype apparatus/data processing approach to model Fm-DPC drying under extremely variable conditions, as inherently expected during the investigational laboratory development of a chemical process. © 2003 Wiley-Liss Inc. and the American Pharmaeceutical Association J Pharm Sci 92:529–535, 2003

A simple and safe prototype apparatus was designed and adapted for the in situdetermination of the moisture content of a cytotoxic compound (9‐fluorenylmethyl‐protected doxorubicin‐peptide conjugate, or Fm‐DPC) by near‐infrared absorbance spectroscopy during optimization of the chemical isolation procedure. The cytotoxic nature of the compound restricts one's ability to safely sample such drying processes for more traditional means of moisture determination for fear of hazardous solids dusting, hence in situsampling approaches are of great importance. These concerns also exist for the process development laboratory, where despite the smaller scale of operations, the volume of experiments (hence cytotoxic samples) required to define a chemical process is often more significant. In this application, partial least squares regression was used with Karl Fischer volumetric titration analysis to generate a calibration model. Although pronounced differences in cake density were observed as a function of the buffer selected for the isolation process, the model still achieved a standard error of calibration of 0.63% w/w and a standard error of prediction of 0.99% (w/w). These results demonstrated the versatility of the prototype apparatus/data processing approach to model Fm‐DPC drying under extremely variable conditions, as inherently expected during the investigational laboratory development of a chemical process.