Analyzing the accuracy of variable returns to scale data envelopment analysis models

The data envelopment analysis (DEA) model is extensively used to estimate efficiency, but no study has determined the DEA model that delivers the most precise estimates. To address this issue, we advance the Monte Carlo simulation-based data generation process proposed by Kohl and Brunner (2020). The developed process generates an artificial dataset using the Translog production function (instead of the commonly used Cobb Douglas) to construct well-behaved scenarios under variable returns to scale (VRS). Using different VRS DEA models, we compute DEA efficiency scores with artificially generated decision-making units (DMUs). We employ five performance indicators followed by a benchmark value and ranking as well as statistical hypothesis tests to evaluate the quality of the efficiency estimates. The procedure allows us to determine which parameters negatively or positively influence the quality of the DEA estimates. It also enables us to identify which DEA model performs the most efficiently over a wide range of scenarios. In contrast to the widely applied BCC (Banker-Charnes-Cooper) model, we find that the Assurance Region (AR) and Slacks-Based Measurement (SBM) DEA models perform better. Thus, we endorse the use of AR and SBM models for DEA applications under the VRS regime

Stable annual scheduling of medical residents using prioritized multiple training schedules to combat operational uncertainty

For educational purposes, medical residents often have to pass through many departments, which place different requirements on them. They are informed about the upcoming departments by an annual training schedule which keeps the individual departments’ service level as constant as possible. Due to poor planning and uncertain events, deviations in the schedule can occur. These deviations affect the service level in the departments, as well as the training progress and satisfaction of the residents. This article analyzes the impact of priorities on residents’ annual planning based on department assignments to combat uncertainty that might result in departmental changes. We present a novel two-stage formulation that combines residents’ tactical planning with duty and daily scheduling’s operational level. We determine an analytical bound for the problem that is superior to the LP bound. Additionally, we approximate a bound based on the solution approach using the objective value of the deterministic solution of an instance and the absences in each scenario. In a computational study, we analyze the performance of various bounds, our solution approach, and the effects of additional priorities in residents’ annual planning. We show that additional priorities can significantly reduce the number of unexpected department assignments. Finally, we derive a practical number of priorities from the results

Metallkomplex-funktionalisierte Oligonucleotide und Peptidnucleinsäuren für die DNA-Sequenzerkennung

Die Arbeit umfasst die Synthese Metallkomplex-funktionalisierter Oligonucleotide und Peptidnucleinsäuren und deren Anwendung als Sonden für den sequenzspezifischen DNA-Nachweis. Die Ligation chemisch modifizierter Oligonucleotide (bzw. deren Analoga) am Nucleinsäure-Templat ist ein etabliertes Detektionsverfahren mit hoher Sequenzselektivität, aber geringer Sensitivität aufgrund starker Produkthemmung. Durch Entwicklung einer katalytischen Variante der templatgesteuerten Reaktion konnte die Sensitivität des Verfahrens durch Signalamplifikation gesteigert werden. Dazu wurden terminale Esterkonjugate (Substrate) und Metallkomplexkonjugate (Katalysatoren) von Peptidnucleinsäuren (PNAs) synthetisiert. Die Ester-PNA und die Metallkomplex-PNA wurden am komplementären DNA-Templat in räumliche Nähe gebracht, wodurch die metallkatalysierte Spaltung des Esters stark beschleunigt wurde. Durch den Templateffekt wurde eine Reaktionsbeschleunigung um den Faktor 150 gegenüber der Hintergrundreaktion erzielt. Bei 100fachem Esterkonjugat-Überschuss konnten 35 Umsätze erreicht werden. Eine Fehlbasenpaarung der komplementären DNA erniedrigte die Reaktionsgeschwindigkeit bis zu 15fach. �Molecular Beacons� (Molekulare Leuchtfeuer) sind Oligonucleotid-Sonden mit Haarnadelstruktur, die bei Hybridisierung fluoreszieren, da eine intramolekulare Fluorophor-Quencher-Wechselwirkung unterbunden wird. Im Rahmen der Arbeit wurden �Molecular Beacons� entwickelt, in denen ein Metallkomplex durch koordinative Bindung an den Fluorophor als fluoreszenzlöschende Komponente wirkt. Dazu wurden 3´-Fluorescein und 5´-Ligand modifizierte DNA-Oligonucleotide mit Haarnadelstruktur synthetisiert. Im nicht-hybridisierten Zustand ist die Fluoreszenz der Kupfer(II)-komplexierten Oligonucleotid-Sonden effektiv gelöscht. Durch Hybridisierung mit komplementärer DNA wurde der Metallkomplex vom Farbstoff räumlich getrennt. Dadurch konnte eine 14fache Erhöhung der Fluoreszenz und eine Diskriminierung einer einzelnen Fehlbase um den Faktor 40 erzielt werden. Das Potential dieses neuen Sondentyps liegt in der Möglichkeit, die Stärke der Fluorophor-Quencher-Wechselwirkung abzustimmen, und damit die Hintergrundfluoreszenz zu minimieren und unspezifische, störende Wechselwirkungen zu blockieren

Homogeneity and best practice analyses in hospital performance management: an analytical framework

Performance modeling of hospitals using data envelopment analysis (DEA) has received steadily increasing attention in the literature. As part of the traditional DEA framework, hospitals are generally assumed to be functionally similar and therefore homogenous. Accordingly, any identified inefficiency is supposedly due to the inefficient use of inputs to produce outputs. However, the disparities in DEA efficiency scores may be a result of the inherent heterogeneity of hospitals. Additionally, traditional DEA models lack predictive capabilities despite having been frequently used as a benchmarking tool in the literature. To address these concerns, this study proposes a framework for analyzing hospital performance by combining two complementary modeling approaches. Specifically, we employ a self-organizing map artificial neural network (SOM-ANN) to conduct a cluster analysis and a multilayer perceptron ANN (MLP-ANN) to perform a heterogeneity analysis and a best practice analysis. The applicability of the integrated framework is empirically shown by an implementation to a large dataset containing more than 1,100 hospitals in Germany. The framework enables a decision-maker not only to predict the best performance but also to explore whether the differences in relative efficiency scores are ascribable to the heterogeneity of hospitals

Balancing control and autonomy in master surgery scheduling: benefits of ICU quotas for recovery units

When scheduling surgeries in the operating theater, not only the resources within the operating theater have to be considered but also those in downstream units, e.g., the intensive care unit and regular bed wards of each medical specialty. We present an extension to the master surgery schedule, where the capacity for surgeries on ICU patients is controlled by introducing downstream-dependent block types – one for both ICU and ward patients and one where surgeries on ICU patients must not be performed. The goal is to provide better control over post-surgery patient flows through the hospital while preserving each medical specialty’s autonomy over its operational surgery scheduling. We propose a mixed-integer program to determine the allocation of the new block types within either a given or a new master surgery schedule to minimize the maximum workload in downstream units. Using a simulation model supported by seven years of data from the University Hospital Augsburg, we show that the maximum workload in the intensive care unit can be reduced by up to 11.22% with our approach while maintaining the existing master surgery schedule. We also show that our approach can achieve up to 79.85% of the maximum workload reduction in the intensive care unit that would result from a fully centralized approach. We analyze various hospital setting instances to show the generalizability of our results. Furthermore, we provide insights and data analysis from the implementation of a quota system at the University Hospital Augsburg. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s10729-021-09588-8

Pollen allergy and health behavior: patients trivializing their disease

Allergies are increasing in prevalence worldwide, with socioeconomic impacts and effects on quality of life. The aim of this study was to explore the health behavior and the utilization of different treatment options via questionnaires and to investigate for relationships of the above with socioeconomic factors. This cross-sectional survey was carried out among pollen allergic subjects in 2016, using questionnaires. A total of 679 allergics participated in the study (61.2% females). Their average age was 26.8 +/- 8.8years. Their symptom severity was 6.1 +/- 1.9, measured on a 10-step scale and symptoms lasted for 9.0 +/- 6.8weeks during pollen season. Of all allergics, 9.1% were not aware of the causative agent of their allergy and 17.4% had never undergone allergy testing. Symptoms, especially in females, had strong impact on social life, everyday routines and sleep quality. Almost half of the participants treated their allergy without medical supervision, while only 32.3% sought medical support. Nevertheless, three quarters reported self-management of their allergies with oral antihistamines. Compared to males, females sought significantly more medical support, medications and allergen avoidance strategies. Knowledge about allergy increased the likelihood of treatment under supervision of a medical expert than no treatment, as well as symptom severity and interaction between female gender and symptom severity. The attitude of not considering allergy as a serious disease significantly reduced the likelihood of undergoing specific immunotherapy. This survey not only highlights the negative impact of pollen allergies on everyday life of allergics, but also that allergies are often neglected and untreated because of their trivialization by allergic subjects themselves

Efficacy and trade‑offs of an innovative hyperthermia device to control Varroa destructor in honeybee colonies

For decades, the honeybee, Apis mellifera, has suffered from severe colony losses due to the ectoparasitic mite Varroa destructor. Various strategies based on chemicals fail to adequately control varroa mite populations, and often comprise side-effects on the host, parasite resistance and residues in hive products. Reduced temperature tolerance of V. destructor compared to its host has long been recognised and accordingly, the potential of hyperthermia to disrupt mite reproduction within honeybee brood cells or even kill adult parasites. Yet, earlier studies on hyperthermia remain largely anecdotal, and readily implementable solutions have so far been lacking. This study investigates autonomously controlled interval heating from within brood combs throughout the season compared to control colonies maintained according to good apicultural practice. We documented treatment-dependent colony growth dynamics and honey production at three apiaries, complemented by regular monitoring of varroa mite levels and comprehensive digital assessments of brood development over time. Our one-year field trial suggests the evaluated hyperthermia device efficiently suppresses mite populations below critical thresholds until autumn. Whilst a general winter reference-curing revealed similar mite infestations of colonies previously treated with hyperthermia versus formic acid (control), only the latter imposed substantial overwintering burdens indirectly through frequent late-season queen supersedure. However, relative to targeted pupae, increased mortality particularly of heat-treated non-target brood stages (eggs and larvae) appeared to trigger compensatory colony-level responses, translating into temporarily decreased numbers of adult workers coupled with increased pollen foraging and overall lower honey harvests. Valuable insights into previously unrecognised side-effects of hyperthermia and mitigation thereof may ultimately permit successful routine applications of this chemical-free approach to combat the major threat to honeybees worldwide

Cost-optimal adaptive iterative linearized FEM for semilinear elliptic PDEs

We consider scalar semilinear elliptic PDEs where the nonlinearity is strongly monotone, but only locally Lipschitz continuous. We formulate an adaptive iterative linearized finite element method (AILFEM) which steers the local mesh refinement as well as the iterative linearization of the arising nonlinear discrete equations. To this end, we employ a damped Zarantonello iteration so that, in each step of the algorithm, only a linear Poisson-type equation has to be solved. We prove that the proposed AILFEM strategy guarantees convergence with optimal rates, where rates are understood with respect to the overall computational complexity (i.e., the computational time). Moreover, we formulate and test an adaptive algorithm where also the damping parameter of the Zarantonello iteration is adaptively adjusted. Numerical experiments underline the theoretical findings

Targeting DNA Mismatches with Rhodium Intercalators Functionalized with a Cell-Penetrating Peptide

Cell-penetrating peptides are widely used to deliver cargo molecules into cells. Here we describe the synthesis, characterization, DNA binding, and cellular uptake studies of a series of metal−peptide conjugates containing oligoarginine as a cell-penetrating peptide. d-Octaarginine units are appended onto a rhodium intercalator containing the sterically expansive chrysenequinone diimine (chrysi) ligand to form Rh(chrysi)(phen)(bpy)^(3+)-tethered oligoarginine conjugates, where the peptide is attached to the ancillary bpy ligand; some conjugates also include a fluorescein or thiazole orange tag. These complexes bind and with photoactivation selectively cleave DNA neighboring single-base mismatches. The presence of the oligoarginines is found to increase the nonspecific binding affinity of the complexes for both matched and mismatched DNA, but for these conjugates, photocleavage remains selective for the mismatched site, as assayed using both gel electrophoresis and mass spectrometry experiments. Significantly, the rhodium complex does not interfere with the delivery properties of the cell-penetrating peptide. Confocal microscopy experiments show rapid nuclear localization of the metal−peptide conjugates containing the tethered fluorescein. Mass spectrometry experiments confirm the association of the rhodium with the HeLa cells. These results provide a strategy for targeting mismatch-selective metal complexes inside cell nuclei

Site-Specific DNA Photocleavage by Rhodium Intercalators Analyzed by MALDI-TOF Mass Spectrometry

The DNA photocleavage reaction of mismatch-selective Rh complexes has been analyzed by MALDI-TOF mass spectrometry as well as gel electrophoresis analysis of radioactively tagged oligonucleotides. Analogous results are obtained with these two techniques showing site-specific cleavage neighboring the mismatch to yield primarily 5‘- and 3‘-phosphate termini. Additional intermediates and products are observed, however, using MALDI-TOF analysis. MALDI-TOF mass spectrometry is seen to be particularly powerful in the analysis of DNA cleavage by site-specific molecules. The method requires no radioactive labeling, only little material, and analysis can be accomplished within minutes. Moreover, this mass spectral analysis of DNA cleavage yields direct information regarding products rather than simply the base pair site of cleavage