Analyzing scheduling in the food-processing industry:Structure and tasks

Production scheduling has been widely studied in several research areas, resulting in a large number of methods, prescriptions, and approaches. However, the impact on scheduling practice seems relatively low. This is also the case in the food-processing industry, where industry-specific characteristics induce specific and complex scheduling problems. Based on ideas about decomposition of the scheduling task and the production process, we develop an analysis methodology for scheduling problems in food processing. This combines an analysis of structural (technological) elements of the production process with an analysis of the tasks of the scheduler. This helps to understand, describe, and structure scheduling problems in food processing, and forms a basis for improving scheduling and applying methods developed in literature. It also helps in evaluating the organisational structures and information flows related to scheduling.</p

Metal–Organic Frameworks as A Tunable Platform for Designing Functional Molecular Materials

Metal-organic frameworks (MOFs), also known as coordination polymers, represent an interesting class of crystalline molecular materials that are synthesized by combining metal-connecting points and bridging ligands. The modular nature of and mild conditions for MOF synthesis have permitted the rational structural design of numerous MOFs and the incorporation of various functionalities via constituent building blocks. The resulting designer MOFs have shown promise for applications in a number of areas, including gas storage/separation, nonlinear optics/ferroelectricity, catalysis, energy conversion/storage, chemical sensing, biomedical imaging, and drug delivery. The structure-property relationships of MOFs can also be readily established by taking advantage of the knowledge of their detailed atomic structures, which enables fine-tuning of their functionalities for desired applications. Through the combination of molecular synthesis and crystal engineering MOFs thus present an unprecedented opportunity for the rational and precise design of functional materials

Reproducibility in the absence of selective reporting: An illustration from large‐scale brain asymmetry research

The problem of poor reproducibility of scientific findings has received much attention over recent years, in a variety of fields including psychology and neuroscience. The problem has been partly attributed to publication bias and unwanted practices such as p-hacking. Low statistical power in individual studies is also understood to be an important factor. In a recent multisite collaborative study, we mapped brain anatomical left-right asymmetries for regional measures of surface area and cortical thickness, in 99 MRI datasets from around the world, for a total of over 17,000 participants. In the present study, we revisited these hemispheric effects from the perspective of reproducibility. Within each dataset, we considered that an effect had been reproduced when it matched the meta-analytic effect from the 98 other datasets, in terms of effect direction and significance threshold. In this sense, the results within each dataset were viewed as coming from separate studies in an "ideal publishing environment," that is, free from selective reporting and p hacking. We found an average reproducibility rate of 63.2% (SD&nbsp;=&nbsp;22.9%, min&nbsp;=&nbsp;22.2%, max&nbsp;=&nbsp;97.0%). As expected, reproducibility was higher for larger effects and in larger datasets. Reproducibility was not obviously related to the age of participants, scanner field strength, FreeSurfer software version, cortical regional measurement reliability, or regional size. These findings constitute an empirical illustration of reproducibility in the absence of publication bias or p hacking, when assessing realistic biological effects in heterogeneous neuroscience data, and given typically-used sample sizes