Effective Mobile Marketing : eine empirische Untersuchung

Mit jährlich mehr als 20 Mrd. versendeten SMS-Nachrichten und fast 35 Mrd. Telefonminuten hat sich das Mobiltelefon zum Kommunikationsmedium Nummer eins in Deutschland entwickelt. Aufgrund des herausragenden Erfolges der Mobiltelefonie steigt das Interesse werbetreibender Unternehmen an der Verwendung dieses Mediums zum Zwecke der werblichen Kommunikation. Nach Ansicht von Branchenspezialisten hat Mobile Marketing das Potenzial, eine neue Epoche der Kommunikationspolitik einzuleiten. Das Handy ist das erste interaktive und zugleich persönlichste Massenmedium unserer Zeit. Mit keinem anderen Medium lassen sich mehr Menschen in kürzerer Zeit und mit minimalen Streuverlusten erreichen. Wenn Mobile Marketing-Kampagnen funktionieren sollen, muss man die Möglichkeiten des Mediums kennen und entsprechend den Marketingzielen des Kunden ausnutzen. Das Management-Know-How-Papier beleuchtet daher zunächst die Grundlagen des Mobile Marketing und zeigt anhand von drei Mobile Marketing-Kampagnen beispielhaft, welche Faktoren den Einsatz des Werbemediums Handy zum Erfolg werden lassen. Abschließend wird ein Kriterienkatalog zur erfolgreichen Implementierung von Mobile Marketing-Kampagnen abgeleitet

Screening of COPD patients for abdominal aortic aneurysm

Purpose: Screening for abdominal aortic aneurysm (AAA) in “men aged over 65 years who have ever smoked” is a recommended policy. To reduce the number of screenings, it may be of value to define subgroups with a higher prevalence of AAA. Since chronic obstructive pulmonary disease (COPD) and AAA are associated with several common risk factors, this study investigates the prevalence of AAA in COPD patients. Patients and methods: Patients with COPD were identified via the hospital information system. Inclusion criteria were: COPD stage I–IV, ability to give full consent, and age >18 years; exclusion criteria were: patient too obese for an ultrasound check, previously diagnosed AAA, prior surgery for AAA, or ethical grounds such as concomitant advanced malignant or end-stage disease. The primary endpoint of the study was an aortic diameter measured by ultrasound of ≥30 mm. Defined secondary endpoints were evaluated on the basis of medical records and interviews. Results: Of the 1,180 identified COPD patients, 589 were included in this prospective study. In 22 patients (3.70%), the aortic diameter was ≥30 mm, representing an AAA prevalence of 6.72% among males aged >65 years. The risk of AAA increased with the following comorbidities/risk factors: male sex (odds ratio [OR] 2.98), coronary heart disease (OR 2.81), peripheral arterial occlusive disease (OR 2.47), hyperlipoproteinemia (OR 2.77), AAA in the family history (OR 3.95), and COPD stage I/II versus IV (OR 1.81). Conclusion: The overall AAA prevalence of 3.7% in our group of COPD patients is similar to that of the general population aged >65 years. However, the frequency of AAA in male COPD patients aged >65 years is considerably higher (6.72%) and increased further still in those individuals with additional comorbidities/risk factors. Defining subgroups with a higher risk of AAA may increase the efficiency of screening

Using natural language processing to support peer‐feedback in the age of artificial intelligence: a cross‐disciplinary framework and a research agenda

Advancements in artificial intelligence are rapidly increasing. The new-generation large language models, such as ChatGPT and GPT-4, bear the potential to transform educational approaches, such as peer-feedback. To investigate peer-feedback at the intersection of natural language processing (NLP) and educational research, this paper suggests a cross-disciplinary framework that aims to facilitate the development of NLP-based adaptive measures for supporting peer-feedback processes in digital learning environments. To conceptualize this process, we introduce a peer-feedback process model, which describes learners' activities and textual products. Further, we introduce a terminological and procedural scheme that facilitates systematically deriving measures to foster the peer-feedback process and how NLP may enhance the adaptivity of such learning support. Building on prior research on education and NLP, we apply this scheme to all learner activities of the peer-feedback process model to exemplify a range of NLP-based adaptive support measures. We also discuss the current challenges and suggest directions for future cross-disciplinary research on the effectiveness and other dimensions of NLP-based adaptive support for peer-feedback. Building on our suggested framework, future research and collaborations at the intersection of education and NLP can innovate peer-feedback in digital learning environments

Using natural language processing to support peer‐feedback in the age of artificial intelligence: A cross‐disciplinary framework and a research agenda

Advancements in artificial intelligence are rapidly increasing. The new-generation large language models, such as ChatGPT and GPT-4, bear the potential to transform educational approaches, such as peer-feedback. To investigate peer-feedback at the intersection of natural language processing (NLP) and educational research, this paper suggests a cross-disciplinary framework that aims to facilitate the development of NLP-based adaptive measures for supporting peer-feedback processes in digital learning environments. To conceptualize this process, we introduce a peer-feedback process model, which describes learners' activities and textual products. Further, we introduce a terminological and procedural scheme that facilitates systematically deriving measures to foster the peer-feedback process and how NLP may enhance the adaptivity of such learning support. Building on prior research on education and NLP, we apply this scheme to all learner activities of the peer-feedback process model to exemplify a range of NLP-based adaptive support measures. We also discuss the current challenges and suggest directions for future cross-disciplinary research on the effectiveness and other dimensions of NLP-based adaptive support for peer-feedback. Building on our suggested framework, future research and collaborations at the intersection of education and NLP can innovate peer-feedback in digital learning environments

A Class 1 Histone Deacetylase as Major Regulator of Secondary Metabolite Production in Aspergillus nidulans

An outstanding feature of filamentous fungi is their ability to produce a wide variety of small bioactive molecules that contribute to their survival, fitness, and pathogenicity. The vast collection of these so-called secondary metabolites (SMs) includes molecules that play a role in virulence, protect fungi from environmental damage, act as toxins or antibiotics that harm host tissues, or hinder microbial competitors for food sources. Many of these compounds are used in medical treatment; however, biosynthetic genes for the production of these natural products are arranged in compact clusters that are commonly silent under growth conditions routinely used in laboratories. Consequently, a wide arsenal of yet unknown fungal metabolites is waiting to be discovered. Here, we describe the effects of deletion of hosA, one of four classical histone deacetylase (HDAC) genes in Aspergillus nidulans; we show that HosA acts as a major regulator of SMs in Aspergillus with converse regulatory effects depending on the metabolite gene cluster examined. Co-inhibition of all classical enzymes by the pan HDAC inhibitor trichostatin A and the analysis of HDAC double mutants indicate that HosA is able to override known regulatory effects of other HDACs such as the class 2 type enzyme HdaA. Chromatin immunoprecipitation analysis revealed a direct correlation between hosA deletion, the acetylation status of H4 and the regulation of SM cluster genes, whereas H3 hyper-acetylation could not be detected in all the upregulated SM clusters examined. Our data suggest that HosA has inductive effects on SM production in addition to its classical role as a repressor via deacetylation of histones. Moreover, a genome wide transcriptome analysis revealed that in addition to SMs, expression of several other important protein categories such as enzymes of the carbohydrate metabolism or proteins involved in disease, virulence, and defense are significantly affected by the deletion of HosA

A Convenient Category of Domains

We motivate and define a category of "topological domains", whose objects are certain topological spaces, generalising the usual $omega$-continuous dcppos of domain theory. Our category supports all the standard constructions of domain theory, including the solution of recursive domain equations. It also supports the construction of free algebras for (in)equational theories, provides a model of parametric polymorphism, and can be used as the basis for a theory of computability. This answers a question of Gordon Plotkin, who asked whether it was possible to construct a category of domains combining such properties

pyTFM: A tool for traction force and monolayer stress microscopy

Cellular force generation and force transmission are of fundamental importance for numerous biological processes and can be studied with the methods of Traction Force Microscopy (TFM) and Monolayer Stress Microscopy. Traction Force Microscopy and Monolayer Stress Microscopy solve the inverse problem of reconstructing cell-matrix tractions and inter- and intra-cellular stresses from the measured cell force-induced deformations of an adhesive substrate with known elasticity. Although several laboratories have developed software for Traction Force Microscopy and Monolayer Stress Microscopy computations, there is currently no software package available that allows non-expert users to perform a full evaluation of such experiments. Here we present pyTFM, a tool to perform Traction Force Microscopy and Monolayer Stress Microscopy on cell patches and cell layers grown in a 2-dimensional environment. pyTFM was optimized for ease-of-use; it is open-source and well documented (hosted at https://pytfm.readthedocs.io/) including usage examples and explanations of the theoretical background. pyTFM can be used as a standalone Python package or as an add-on to the image annotation tool ClickPoints. In combination with the ClickPoints environment, pyTFM allows the user to set all necessary analysis parameters, select regions of interest, examine the input data and intermediary results, and calculate a wide range of parameters describing forces, stresses, and their distribution. In this work, we also thoroughly analyze the accuracy and performance of the Traction Force Microscopy and Monolayer Stress Microscopy algorithms of pyTFM using synthetic and experimental data from epithelial cell patches

Hypothermia Improves Oral and Gastric Mucosal Microvascular Oxygenation during Hemorrhagic Shock in Dogs

Hypothermia is known to improve tissue function in different organs during physiological and pathological conditions. The aim of this study was to evaluate the effects of hypothermia on oral and gastric mucosal microvascular oxygenation (μHbO2) and perfusion (μflow) under physiological and hemorrhagic conditions. Five dogs were repeatedly anesthetized. All animals underwent each experimental protocol (randomized cross-over design): hypothermia (34°C), hypothermia during hemorrhage, normothermia, and normothermia during hemorrhage. Microcirculatory and hemodynamic variables were recorded. Systemic (DO2) and oral mucosal (μDO2) oxygen delivery were calculated. Hypothermia increased oral μHbO2 with no effect on gastric μHbO2. Hemorrhage reduced oral and gastric μHbO2 during normothermia (−36 ± 4% and −27 ± 7%); however, this effect was attenuated during additional hypothermia (−15 ± 5% and −11 ± 5%). The improved μHbO2 might be based on an attenuated reduction in μflow during hemorrhage and additional hypothermia (−51 ± 21 aU) compared to hemorrhage and normothermia (−106 ± 19 aU). μDO2 was accordingly attenuated under hypothermia during hemorrhage whereas DO2 did not change. Thus, in this study hypothermia alone improves oral μHbO2 and attenuates the effects of hemorrhage on oral and gastric μHbO2. This effect seems to be mediated by an increased μDO2 on the basis of increased μflow

QCD-based description of one-particle inclusive B decays

We discuss one-particle inclusive B decays in the limit of heavy b and c quarks. Using the large-N_C limit we factorize the non-leptonic matrix elements, and we employ a short distance expansion. Modeling the remaining nonperturbative matrix elements we obtain predictions for various decay channels and compare them with existing data.Comment: LaTeX, 22 pages, 6 figures (eps); analytical and numerical results unchanged, misrepresentation of experimental data in Fig. 5 corrected, final published versio

Wikirate as a pedagogical tool: 2023 best practices report

This report presents five compelling international case studies that highlight the diverse implementation of Wikirate across higher education institutions. Each case study provides insights into the integration of the platform in the curricula, the skills honed by students through their involvement with Wikirate, and the outputs developed by students with the data collected. These case studies were shared during two enlightening webinars held in April and June 2023