Interview mit Hans-Christian Boos zum Thema „Unternehmertum in der IT-Branche“

Ohne Zusammenfassung     

Teaching severely self-abusive and aggressive autistic residents to exit to fire alarms

Fifty-two case-hardened, severely self-abusive and aggressive autistic and retarded students, living in six different community residences, were trained to exit their residences, without the presence or assistance of staff, when a fire alarm sounded at night. On a pretest, prior to an 11-week period of intensive environmental and behavioral interventions, only 25% of the students exited within 2 1/2 minutes and independent of staff assistance. At posttest, 100% exited successfully, in a mean evacuation time of 60 seconds. The study was conducted at the Behavior Research Institute (BRI).     

Seminar planning guidelines. As I see it

Small local chapter groups can present quality cost effective regional seminars. Key components are dedication of members, teamwork, and a sense of direction. The following guidelines and information can provide a framework for planning and coordinating a seminar.     

Thermolysis of poly(diaryl diazosulfide)s

Poly(diaryl diazosulfide)s and model diaryl diazosulfides of the general structure aryl-N?N? S-aryl' are tested for their thermostability. Thermolysis in solution is followed by means of UV spectroscopy. At the beginning of the decay most model diazosulfides follow first-order kinetics, but show an acceleration of the decay rate in the further course of the thermolysis. In contrast to the models the decomposition of the corresponding polymers cannot be described by first-order kinetics, except one example ( P 1 ). Thermogravimetry studies show weight losses of 8–12% in the range between 80 and 150°C depending on the structure of the models and polymeric diazosulfides. These values correspond with the content of azo function in these compounds, therefore it is assumed that nitrogen is split off under these reaction conditions.     

Excretion of a radiolabelled anticancer biodegradable polymeric implant from the rabbit brain

The elimination of a clinically used anticancer biodegradable polymer implant (Gliadel) in the rabbit brain was studied. The implant is composed of N,N-bis(2-chloroethyl)-N-nitrosourea (BCNU) (1.6 wt%) dispersed in a copolyanhydride matrix of 1,3-bis(p-carboxyphenoxypropane) (CPP) and sebacic acid (SA) in a 20:80 molar ratio. Four groups of rabbits were implanted with wafers loaded with BCNU, one in a 14C-SA-labelled polymer, another in a 14C-CPP-labelled polymer and two groups with 14C-BCNU in a non-labelled polymer, one for BCNU disposition study and one for residual drug study. In the rabbits implanted with the 14C-SA-labelled polymer, approximately 10% of the radioactivity was found in the urine and 2% in the faeces, and about 10% remained in the device 7 d after implantation. In contrast, only 4% of the radioactivity of the 14C-CPP-labelled polymer was found in urine and faeces during this period. However, a drastic increase in the CPP excretion was found after 9 d, and at 21 d, 64% of the implanted 14C-CPP was found in the urine and faeces, and 29% was still in the recovered wafers. Approximately 50% of the BCNU in the wafers was released in 3 d, and over 95% was released after 6 d in the rabbit brain. This study demonstrates that BCNU-loaded polyanhydride is biodegradable and is excreted from the body primarily through the renal system. The water-soluble components SA and BCNU were rapidly excreted, while the insoluble CPP was gradually eliminated after a lag time of 9 d.     

Structure-Activity Relationships of Benzamides and Isoindolines Designed as SARS-CoV Protease Inhibitors Effective against SARS-CoV-2

Inhibition of coronavirus (CoV)-encoded papain-like cysteine proteases (PL^pro) represents an attractive strategy to treat infections by these important human pathogens. Herein we report on structure-activity relationships (SAR) of the noncovalent active-site directed inhibitor (R)-5-amino-2-methyl-N-(1-(naphthalen-1-yl)ethyl) benzamide ( 2 b ), which is known to bind into the S3 and S4 pockets of the SARS-CoV PL^pro. Moreover, we report the discovery of isoindolines as a new class of potent PL^pro inhibitors. The studies also provide a deeper understanding of the binding modes of this inhibitor class. Importantly, the inhibitors were also confirmed to inhibit SARS-CoV-2 replication in cell culture suggesting that, due to the high structural similarities of the target proteases, inhibitors identified against SARS-CoV PL^pro are valuable starting points for the development of new pan-coronaviral inhibitors.     

Regional mass flux balancing for controlling gentle soil remediation operations

Extraction of heavy metals by accumulating plants is a method which is currently in development for the "gentle" remediation of contaminated agricultural soils (phytoremediation, see [2]). Areal contaminant mass flux balances are basic criteria for the design of such remediations and their control. A framework for the integration of contaminant balances relating the field scale of remediation with the regional scale of soil monitoring networks is provided by the recently developed method PROTERRA [3]. The objective of the study presented in this paper was to test the suitability of PROTERRA for planning and monitoring gentle soil remediations. For this purpose we applied the PROTERRA method to the contaminated agricultural land in and around Dornach, Switzerland, to assess copper flux balances.The calculations showed that atmospheric deposition and the application of pesticides and manure are important pathways for the inputs of copper. The copper export with a special maize cultivar accumulating heavy metals would be about three times higher than the average metal export with crops. A moderate increase of sewage sludge application would lead to a substantial increase of the copper input. Decisions to remediate the soil should take the uncertainty of mass flux balances both on field scale as well as on regional scale into account. Therefore, an important need of further development of the PROTERRA method is the integration of uncertainty analysis on both scales.     

Predicting roadheader performance by using artificial neural network

With growing use of roadheaders in the world and its significant role in the successful accomplishment of a tunneling project, it is a necessity to accurately predict performance of this machine in different ground conditions. On the other hand, the existence of some shortcomings in the prediction models has made it necessary to perform more research on the development of the new models. This paper makes an attempt to model the rate of roadheader performance based on the geotechnical and geological site conditions. For achieving the aim, an artificial neural network (ANN), a powerful tool for modeling and recognizing the sophisticated structures involved in data, is employed to model the relationship between the roadheader performance and the parameters influencing the tunneling operations with a high correlation. The database used in modeling is compiled from laboratory studies conducted at Azad University at Science and Research Branch, Tehran, Iran. A model with architecture 4-10-1 trained by back-propagation algorithm is found to be optimum. A multiple variable regression (MVR) analysis is also applied to compare performance of the neural network. The results demonstrate that predictive capability of the ANN model is better than that of the MVR model. It is concluded that roadheader performance could be accurately predicted as a function of unconfined compressive strength, Brazilian tensile strength, rock quality designation, and alpha angle R ² = 0.987. Sensitivity analysis reveals that the most effective parameter on roadheader performance is the unconfined compressive strength.