The Higher Cicho\'n Diagram

For a strongly inacessible cardinal $\kappa$, we investigate the relationships between the following ideals: - the ideal of meager sets in the ${<}\kappa$-box product topology - the ideal of "null" sets in the sense of [Sh:1004] (arXiv:1202.5799) - the ideal of nowhere stationary subsets of a (naturally defined) stationary set $S_{\rm pr}^\kappa \subseteq \kappa$. In particular, we analyse the provable inequalities between the cardinal characteristics for these ideals, and we give consistency results showing that certain inequalities are unprovable. While some results from the classical case ($\kappa=\omega$) can be easily generalized to our setting, some key results (such as a Fubini property for the ideal of null sets) do not hold; this leads to the surprising inequality cov(null)$\le$non(null). Also, concepts that did not exist in the classical case (in particular, the notion of stationary sets) will turn out to be relevant. We construct several models to distinguish the various cardinal characteristics; the main tools are iterations with $\mathord<\kappa$-support (and a strong "Knaster" version of $\kappa^+$-cc) and one iteration with ${\le}\kappa$-support (and a version of $\kappa$-properness).Comment: 84 page

Reading the Future: Predicting Who Will Benefit from Bunion Surgery

Introduction/Purpose: Hallux valgus is a common condition of the foot with 4.4 million patients seeking care yearly for this condition. A previous study suggested specific pre-operative cut-off scores based on Patient Reported Outcomes Measurement Information System (PROMIS) physical function (PF), pain interference (PI), and depression (D) values could predict post-operative outcomes in foot and ankle surgery. Though hallux valgus correction, among other procedures, were identified as one of the most common surgeries in the previous study, specific conditions were not considered separately. The purpose of this study was to evaluate the validity of applying a published comprehensive pre-surgical PROMIS profile of PF, PI and D to patients undergoing bunionectomy surgery

Correlation between layer thickness and periodicity of long polytypes in silicon carbide

The layer widths and repeat spacing of long-period polytypes (LPPs) have been determined using synchrotron radiation source (SRS) X-ray diffraction topography (XRDT). This method has proved to be a powerful tool in investigating the spatial extent of one-dimensional disorder (1DD), long-period polytypes (LPPs) and the boundaries of polytype layers in silicon carbide (SiC). The resulting neighbourhood coalescence models have confirmed the validity of the sandwich rule even in the limit of two arbitrarily long LPPs, as well as the unique nature of the 6H polytype. A significant empirical trend is reported here that relates the thickness of LPP layers to the periodicity of the repeat stacking sequence measured on the topographs. A good correlation between the data suggests that this behaviour is governed by a simple mathematical expression t = kNn. Values for k and n have been determined that relate the polytype thickness (t in microns) to the number of hexagonal layers (N) in the polytype stacking repeat. These values can be used to prompt questions about the limits of polytypism and disorder in SiC

Can Patient Reported Outcomes Guide Therapy Needs in Foot and Ankle Patients?

Introduction/Purpose: The patient acceptable symptom state (PASS) is a validated question establishing if patients activity and symptoms are at a satisfactory low level for pain and function. Surprisingly, ~20% of foot and ankle patients at their initial visit present for care with an acceptable symptom state (i.e. PASS yes). These patients are important to identify to prevent over treatment and avoid excessive cost. It is also unclear what health domains (Pain Interference (PI), Physical Function (PF), or Depression (Dep)) influence a patients judgement of their PASS state (i.e. why they are seeking treatment). The purpose of this analysis is to document the prevalance of PASS state and determine the health domains that discriminate PASS patients and predict PASS state at the initiation of rehabilitation

Does Identifying Provider Expectations Improve Adoption of Patient Reported Outcomes?

Introduction/Purpose: New instruments like the Patient Reported Outcome Information System (PROMIS) minimize the burden to patients and providers addressing significant barriers to adoption. Despite these advances provider adoption remains lackluster. Models of technology adoption suggest adoption is more likely to occur when PRO’s directly improve patient care (performance expectancy) and it’s easy to implement (effort expectancy). Problems with effort expectancy are dealt with by training and improving logistics (i.e. eHR presentation, alerts), where performance expectancy is addressed through research (i.e. validation of thresholds). The purposes of this study were to: 1) evaluate the proportion of orthopedic rehabilitation providers who use PRO’s and how they use them; And, 2) to determine if performance expectancy, effort expectancy or provider burnout are related to provider use

Increasing the Reliability and Performance through Automatization and Parallel Working

Re-examination of the behaviour of structures can be necessary due to deterioration or changes in the traffic situation during their lifetime. The Finite Element Method (FEM) is widely used in order to accomplish numerical analysis. Considering the development of computer performance, more detailed FEM models can be analyzed, even on site, with mobile computers. To compensate the increasing amount of data needed for the model input, measures need to be taken to save time, by distributing the work. In order to provide consistency to the model, fedback data must be checked upon reception. A local wireless computer network of ultra-portable devices linked together with a computer can provide the coordination necessary for efficient parallel working. Based on a digital model consisting of all data gathered, structural modelling and numerical analysis are performed automatically. Thus, the user is released from the work that can be automatized and the time needed for the overall analysis of a structure is decreased

Critical Success Factors for the Implementation and Adoption of Cloud Services in SMEs

Cloud computing (CC) is a fast-growing technology and one of the most important technological drivers of the digitalization of enterprises. The implementation and adoption of a suitable cloud service is challenging and knowledge-intensive and requires strong participation and ownership of business managers and IT units. However, even if the awareness of critical success factors (CSFs) for cloud implementation projects strongly supports avoiding failures within the projects, this field has rarely been researched, especially with a focus on small and medium-sized enterprises (SMEs). Therefore, our paper’s contribution to research and practice is the identification of 26 CSFs through a rigorous literature review in combination with an interview study among German SMEs. As a result, we derive a comprehensive model as a starting point for cloud implementation projects in which we assign the CSFs to the respective parties involved in those projects

The Road to Recovery for Bunion Surgery: Data Analytic Plots to Target Patient Progress

Introduction/Purpose: Patient reported outcomes (PROs) can provide information on individual patient’s progress throughout a treatment course and additionally, with common surgeries, powerful numbers can be generated to provide data analytic curves to provide a recovery road map for patients and surgeons. Those who deviate negatively from the predicted path may have a complication and early intervention can be initiated. Those who deviate positively have the potential to need less physical therapy, early return to sports or work. Hallux valgus (HV) is a common condition of the foot with 4.4 million patients seeking care yearly and surgery is equally common. The purpose of this study was to determine if PROMIS PROs can be used to construct data analytic curves for HV surgery