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With the continued deployment of the Internet of Things (IoT) , increasing volumes of devices are being deployed that emit massive spatially referenced data. Due in part to the dynamic, decentralized, and heterogeneous architecture of the IoT, the varying and often low quality of spatial IoT data (SID) presents challenges to applications built on top of this data. This survey aims to provide unique insight to practitioners who intend to develop IoT-enabled applications and to researchers who wish to conduct research that relates to data quality in the IoT setting. The survey offers an inventory analysis of major data quality dimensions in SID and covers significant data characteristics and associated quality considerations. The survey summarizes data quality related technologies from both task and technique perspectives. Organizing the technologies from the task perspective, it covers recent progress in SID quality management, encompassing location refinement, uncertainty elimination, outlier removal, fault correction, data integration, and data reduction; and it covers low-quality SID exploitation, encompassing querying, analysis, and decision-making techniques. Finally, the survey covers emerging trends and open issues concerning the quality of SID.

Generalist predators that kill and eat other natural enemies can weaken biological control. However, pest suppression can be disrupted even if actual intraguild predation is infrequent, if predators reduce their foraging to lower their risk of being killed. In turn, predator-predator interference might be frequent when few other prey are available, but less common when herbivorous and detritus-feeding prey are plentiful. We used molecular gut-content analysis to track consumption of the predatory bug Geocoris sp. by the larger intraguild predator Nabis sp., in organic and conventional potato (Solanum tuberosum) fields.We found that higher densities of both aphids and thrips, two common herbivores, correlated with higher probability of detecting intraguild predation. Perhaps, Nabis foraging for these herbivores also encountered and ate more Geocoris. Surprisingly, likelihood of intraguild predation was not strongly linked to densities of either Nabis or Geocoris, or farming system, suggesting a greater importance for prey than predator community structure. Intriguingly, we found evidence that Geocoris fed more often on the detritus-feeding fly Scaptomyza pallida with increasing predator evenness. This would be consistent with Geocoris shifting to greater foraging on the ground, where S. pallida would be relatively abundant, in the face of greater risk of intraguild predation.Overall, our findings suggest that while herbivorous prey may heighten intraguild predation of Geocoris in the foliage, detritivores might support a shift to safer foraging on the ground. This provides further evidence that prey abundance and diversity can act to either heighten or relax predator-predator interference, depending on prey species identity and predator behavior. © 2022 Society of Chemical Industry.

BACKGROUND: Surgical extraction of testicular spermatozoa is needed in men with nonobstructive azoospermia (NOA) who wish to become biological fathers. Based on available uncontrolled studies with unspecific patient selection, microdissection testicular sperm extraction (mTESE), having a sperm retrieval rate (SRR) of 50%, is considered the most efficient sperm retrieval procedure. However, no randomized clinical trials for comparison of different sperm retrieval procedures exist. Testicular sperm aspiration (TESA) is simple and commonly used, and we hypothesized that this technique using multiple needle passes would give similar SRRs to mTESE.OBJECTIVE: To compare mTESE and multiple needle-pass TESA in men with NOA.DESIGN, SETTING, AND PARTICIPANTS: A randomized clinical trial was performed between June 2017 and April 2021, with inclusion of 100 men with NOA from four centers in Denmark and Sweden. All participants received treatment at the same institution.INTERVENTION: Participants were randomized to mTESE (n = 49) or multiple needle-pass TESA (n = 51). Patients with failed multiple needle-pass TESA proceeded directly to salvage mTESE.OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: The primary outcome was SRR. Secondary outcomes included complications and changes in reproductive hormones after surgery.RESULTS AND LIMITATIONS: Spermatozoa were retrieved in 21/49 (43%) men after mTESE and in 11/51 (22%) men after multiple needle-pass TESA (rate difference -0.21; 95% confidence interval -0.39 to -0.03; p = 0.02). The combined SRR for multiple needle-pass TESA + salvage mTESE was 15/51 (29%). No complications occurred after multiple needle-pass TESA only, while 5/89 (6%) men having mTESE experienced a complication requiring surgical intervention. Overall, no statistically significant differences in reproductive hormones were observed between groups after 6 mo. Limitations include the low number of patients in secondary outcome data.CONCLUSIONS: In direct comparison, SRR was higher in mTESE than in multiple needle-pass TESA.PATIENT SUMMARY: Men with azoospermia need surgical extraction of spermatozoa to become biological fathers. In this randomized trial, we compared two surgeries (microdissection testicular sperm extraction [mTESE] and testicular sperm aspiration [TESA]) and found that mTESE gives a higher sperm retrieval rate than multiple needle-pass TESA.

Context Muscle damage and delayed onset muscle soreness (DOMS) can occur following intense exercise. Various modalities have been studied to improve blood lactate accumulation, which is a primary reason for DOMS. It has been well established that active recovery facilitates blood lactate removal more rapidly that passive recovery due to the pumping action of the muscle. The pedal pump is a manual lymphatic technique used in osteopathic manipulative medicine to increase lymphatic drainage throughout the body. Pedal pump has been shown to increase lymphatic flow and improve immunity. This may improve circulation and improve clearance of metabolites post-exercise. Objective This study compared the use of pedal pump lymphatic technique to passive supine recovery following maximal exercise. Methods 17 subjects (male n = 10, age 23 ± 3.01; female n = 7, age 24 ± 1.8), performed a maximal volume O2 test (VO2 max) using a Bruce protocol, followed by a recovery protocol using either pedal pump technique or supine passive rest for 10 min, followed by sitting for 10 min. Outcome measures included blood lactate concentration (BL), heart rate (HR), systolic blood pressure (SBP) and VO2. Subjects returned on another day to repeat the VO2 max test to perform the other recovery protocol. All outcomes were measured at rest, within 1- minute post-peak exercise, and at minutes 4, 7, 10 and 20 of the recovery protocols. A 2 × 6 repeated measures ANOVA was used to compare outcome measures (p ≤ 0.05). Results No significant differences were found in VO2, HR, or SBP between any of the recovery protocols. There was no significant difference in BL concentrations for recovery at minutes 4, 7, or 10 (p > 0.05). However, the pedal pump recovery displayed significantly lower BL concentrations at minute 20 of recovery (p = 0.04). Conclusion The pedal pump significantly decreased blood lactate concentrations following intense exercise at recovery minute 20. The use of manual lymphatic techniques in exercise recovery should be investigated further.

K+ balance in mammals relies on regulated renal K+ excretion matching unregulated fluctuating K+ intake. Upon a K+ rich meal, rapid and powerful K+ excretion is needed. Renal K+ secretion is stimulated by increased tubular flow. We speculated that high K+ intake acutely increases urinary flow to stimulate K+ excretion.Methods: Mice were K+ challenged through diets or gavage. Post K+ loading urinary output, osmolarity, [K+ ]u , [Na+ ]u , plasma osmolarity, [copeptin]p , [K+ ]p , and [Na+ ]p were measured. To locate the mechanism of K+ -induced diuresis in the glomerular/tubular system we measured creatinine excretion and assessed functional transport in isolated perfused TALs and CDs during an acute [K+ ]bl switch from 3.6 to 6.5 mM. Molecular adaptations of transport proteins involved in water reabsorption were investigated by immunoblotting.Results: 1) Mice switched from a 1% to 2% K+ diet increased diuresis within 12h and reciprocally reduced diuresis when switched from 1% to 0.01% K+ diet. 2) A single K+ gavage load, corresponding to 25-50% of daily K+ intake, induced 100% increase in diuresis within 30 minutes. This occurred despite augmented plasma osmolarity and AVP synthesis. 3) K+ gavage did not change GFR. 4) In isolated perfused TALs, shifting [K+ ]bl from 3.6 to 6.5 mM did not affect AVP-induced NaCl transport. 5) In sharp contrast, in isolated perfused CDs, shifting [K+ ]bl from 3.6 to 6.5 mM markedly reduced CD AVP-sensitivity, i.e. inhibited water absorption.Conclusion: Dietary K+ loading induces a rapidly on-setting diuresis. The mechanism of K+ -induced diuresis involves desensitization of the CD to AVP.

In step with the digitalization of transportation, we are witnessing a growing range of path-based smart-city applications, e.g., travel-time estimation and travel path ranking. A temporal path (TP) that includes temporal information, e.g., departure time, into the path is of fundamental to enable such applications. In this setting, it is essential to learn generic temporal path representations (TPRs) that consider spatial and temporal correlations simultaneously and that can be used in different applications, i.e., downstream tasks. Existing methods fail to achieve the goal since (i) supervised methods require large amounts of task-specific labels when training and thus fail to generalize the obtained TPRs to other tasks; (ii) though unsupervised methods can learn generic representations, they disregard the temporal aspect, leading to sub-optimal results. To contend with the limitations of existing solutions, we propose a Weakly-Supervised Contrastive learning model. We first propose a temporal path encoder that encodes both the spatial and temporal information of a temporal path into a TPR. To train the encoder, we introduce weak labels that are easy and inexpensive to obtain, and are relevant to different tasks, e.g., temporal labels indicating peak vs. off-peak hour from departure times. Based on the weak labels, we construct meaningful positive and negative temporal path samples by considering both spatial and temporal information, which facilities training the encoder using contrastive learning by pulling closer the positive samples' representations while pushing away the negative samples' representations. To better guide the contrastive learning, we propose a learning strategy based on Curriculum Learning such that the learning performs from easy to hard training instances. Experimental studies involving three downstream tasks, i.e., travel time estimation, path ranking, and path recommendation, on three road networks offer strong evidence that the proposal is superior to state-of-the-art unsupervised and supervised methods and that it can be used as a pre-training approach to enhance supervised TPR learning.

The ongoing, sweeping digitalization of societal processes generates massive volumes of data that capture the underlying processes at an unprecedented level of detail, in turn enabling us to better understand and improve those processes. Put differently, if harnessed properly, data holds the potential to enable value creation throughout society.Considering primarily vehicle trajectory data, this talk put focus on the important process of transportation: While we all depend on it for mobility, transportation has adverse effects on (i) our productivity due to lack of predictability and congestion, (ii) the climate due to greenhouse gas emissions, and (iii) our health and safety due to air and noise pollution and accidents. Thus, it makes good sense to invent techniques capable of leveraging big data for the improvement of transportation.The talk describes how the availability of massive trajectory data renders the traditional routing paradigm, where a road network is modeled as an edge-weighted graph, inadequate. Instead, new paradigms that thrive on massive trajectory data are called for. The talk covers several such paradigms, including path-centric, on-the-fly, and cost-oblivious routing [2, 3, 4, 10, 11, 12]. As even massive volumes of trajectory data are sparse in these settings, the talk also covers means of making good use of available data [6, 7, 13]. Finally, trajectory data has many uses beyond routing—the talk covers several such uses [1, 5, 8, 9].

Before introducing combination antiretroviral therapy (cART), a higher prevalence of emphysema in people living with HIV (PLWH) than in the background population was reported. This systematic literature review aimed to investigate the prevalence of emphysema in PLWH and to compare the prevalence between PLWH and controls in the current cART era. A systematic literature search was conducted in PubMed, EMBASE, Scopus, and Web of Science (WOS), searching for “human immunodeficiency virus (HIV)” and “emphysema” from January 1, 2000 to March 10, 2021. Eligible studies were published after the introduction of cART, included PLWH, and reported the prevalence of emphysema. A total of 17 studies were included, and nine studies also included controls. The weighted average prevalence of emphysema in PLWH was 23% (95% CI: 16–30). In studies including both PLWH and controls the weighted average prevalence were 22% (95% CI: 10–33) and 9.7% (95% CI: 2.3–17), respectively (p = 0.052). The prevalence of emphysema in never-smoking PLWH and controls was just reported in one study and was 18 and 4%, respectively (p < 0.01). Thirteen of the studies had a moderate risk of bias, mainly due to selection of patients. A tendency to higher prevalence of emphysema was found in PLWH in comparison to controls in the current cART era. However, in the included studies, the definition of emphysema varied largely. Thus, to have a clear overview of the prevalence, further studies with well-designed cohorts of PLWH and controls are warranted.

Grupo de investigación MOTUS. Proyecto de Investigación asociado: Prevent4Work Actions to improve occupational health and safety arose from the need to protect employees working in European industries, such as nuclear power plants or large-scale chemical industries, from accidents. Today, the field has evolved in many directions, with the prevention and management of musculoskeletal disorders (MSDs) being one of its main lines of action. MSDs are the main reason for workers to take time off work. Specifically, the prevalence of MSDs represents more than 1.3 billion people and a loss of more than 100 million years of life due to disability; they are a common cause of disability and sick leave. Historically, the workplace approach to MSDs has focused on adopting ergonomic measures, which has been positive in some cases. However, despite ergonomic and biomechanical measures being widely implemented in the workplace, the increasing prevalence of MSDs globally indicates that they are not sufficient measures on their own. Therefore, new holistic approaches that take biological, psychological, and social aspects are needed to address them. The European Prevent4Work Alliance for innovative measures to prevent MSDs in the workplace has developed this document as a guide based on the most recent and relevant scientific knowledge. Both companies and their employees can benefit from the recommendations of this guide

Crowdsourcing aims to enable the assignment of available resources to the completion of tasks at scale. The continued digitization of societal processes translates into increased opportunities for crowdsourcing. For example, crowdsourcing enables the assignment of computational resources of humans, called workers, to tasks that are notoriously hard for computers. In settings faced with malicious actors, detection of such actors holds the potential to increase the robustness of crowdsourcing platform. We propose a framework called Outlier Detection for Streaming Task Assignment that aims to improve robustness by detecting malicious actors. In particular, we model the arrival of workers and the submission of tasks as evolving time series and provide means of detecting malicious actors by means of outlier detection. We propose a novel socially aware Generative Adversarial Network (GAN) based architecture that is capable of contending with the complex distributions found in time series. The architecture includes two GANs that are designed to adversarially train an autoencoder to learn the patterns of distributions in worker and task time series, thus enabling outlier detection based on reconstruction errors. A GAN structure encompasses a game between a generator and a discriminator, where it is desirable that the two can learn to coordinate towards socially optimal outcomes, while avoiding being exploited by selfish opponents. To this end, we propose a novel training approach that incorporates social awareness into the loss functions of the two GANs. Additionally, to improve task assignment efficiency, we propose an efficient greedy algorithm based on degree reduction that transforms task assignment into a bipartite graph matching. Extensive experiments offer insight into the effectiveness and efficiency of the proposed framework.

13 pags., 4 figs., Continuum structures of three short-range interacting particles in a deformed external one-body field are investigated. We use the equivalent d method employing noninteger dimension, d, in a spherical calculation with a dimension-dependent angular momentum barrier. We focus on dimensions close to the critical dimension, d=dE, between 2 and 3, defined by zero two-body energies, where the Efimov effect can occur. We design for this dimension region a schematic, long-distance realistic, square-well based, three-body spherical model, which is used to derive analytic expressions for the wave functions, scattering lengths, phase shifts, and elastic-scattering cross sections. The procedure and the results are universal, valid for all short-range potentials, and for large scattering lengths. We discuss the properties and validity of the derived expressions by means of the simplest system of three identical bosons. The derived expressions are particularly useful for very small energies, where full numerical calculations are often not feasible. For energies where the numerical calculations can be performed, a good agreement with the analytic results is found. These model results may be tested by scattering experiments for three particles in an equivalent external deformed oscillator potential. The cross sections all vanish in the zero-energy limit for d, This work has been partially supported by the Ministerio de Ciencia e Innovación MCI/AEI/FEDER,UE (Spain) under Grant No. PGC2018-093636-B-I00.

To evaluate the incidence of severe ocular injury requiring emergent ophthalmic evaluation in visually asymptomatic patients presenting with orbital fractures. We performed a retrospective chart review of all adult and pediatric orbital fractures between 2012–2022 at a level 1 trauma center. Ocular injuries were categorized into severe, moderate, and mild. We evaluated symptoms, mechanism of injury, visual acuity (VA), and severity of injuries using the Cochran-Armitage and linear-by-linear tests. Of the 2495 cases, 1534 had ophthalmology evaluation. The mean ± standard deviation age was 40.4 ± 20.4 years. Most patients were male (73.1%) and Caucasian (75.9%). The mean time to evaluation was 0.6 ± 2.5 days. 486 (31.7%) were visually symptomatic, 760 (49.5%) were asymptomatic, and 288 (18.8%) were unknown. Of the symptomatic, 135 (27.8%) had severe injuries, 108 (22.2%) had moderate injuries, 216 (44.4%) had mild injuries, and 27 (5.6%) had no injuries. Of the asymptomatic, 67 (8.8%) had severe injuries, 183 (24.1%) had moderate injuries, 468 (61.6%) had mild injuries, and 42 (5.5%) had no injuries. Symptoms correlated with injury severity (p-value

We propose variational quasi-recurrent autoencoders (VQRAEs) to enable robust and efficient anomaly detection in time series in unsupervised settings. The proposed VQRAEs employs a judiciously designed objective function based on robust divergences, including a, ß, and, -divergence, making it possible to separate anomalies from normal data without the reliance on anomaly labels, thus achieving robustness and fully unsupervised training. To better capture temporal dependencies in time series data, VQRAEs are built upon quasi-recurrent neural networks, which employ convolution and gating mechanisms to avoid the inefficient recursive computations used by classic recurrent neural networks. Further, VQRAEs can be extended to bi-directional Bi VQRAEs that utilize bi-directional information to further improve the accuracy. The above design choices make VQRAEs not only robust and thus accurate, but also efficient at detecting anomalies in streaming settings. Experiments on five real-world time series offer insight into the design properties of VQRAEs and demonstrate that VQRAEs are capable of outperforming state-of-the-art methods.

We all depend on mobility, and vehicular transportation affects the daily lives of most of us. Thus, the ability to forecast the state of traffic in a road network is an important functionality and a challenging task. Traffic data is often obtained from sensors deployed in a road network. Recent proposals on spatial-temporal graph neural networks have achieved great progress at modeling complex spatial-temporal correlations in traffic data, by modeling traffic data as a diffusion process. However, intuitively, traffic data encompasses two different kinds of hidden time series signals, namely the diffusion signals and inherent signals. Unfortunately, nearly all previous works coarsely consider traffic signals entirely as the outcome of the diffusion, while neglecting the inherent signals, which impacts model performance negatively. To improve modeling performance, we propose a novel Decoupled Spatial-Temporal Framework (DSTF) that separates the diffusion and inherent traffic information in a data-driven manner, which encompasses a unique estimation gate and a residual decomposition mechanism. The separated signals can be handled subsequently by the diffusion and inherent modules separately. Further, we propose an instantiation of DSTF, Decoupled Dynamic Spatial-Temporal Graph Neural Network (D2STGNN), that captures spatial-temporal correlations and also features a dynamic graph learning module that targets the learning of the dynamic characteristics of traffic networks. Extensive experiments with four real-world traffic datasets demonstrate that the framework is capable of advancing the state-of-the-art., Comment: Accepted by VLDB 2022

We examined developmental trajectories of attention-deficit/hyperactivity disorder (ADHD) symptoms, standardized achievement, and school performance for adolescents with and without ADHD who did and did not enroll in postsecondary education (PSE; N = 749; 79% boys; 63% White, 17% non-Hispanic Black, 10% Hispanic, and 10% other ethnicities). In a multisite study (recruitment based in New York, North Carolina, Pennsylvania, California, and Quebec), participants were originally enrolled between 1994 and 1998 at ages 7 to 9.9 and followed up through 2012 (M

Grupo de investigación MOTUS. Proyecto de investigación asociado: Prevent4Work Las acciones dirigidas a la mejora de la seguridad y de la salud laboral surgieron de la necesidad de proteger frente a los accidentes a los empleados que trabajaban en industrias europeas; como en centrales nucleares o en industrias químicas de gran escala. Actualmente, este campo ha evolucionado en multitud de direcciones, siendo la prevención y el manejo de los trastornos musculoesqueléticos (TME) una de sus principales líneas de actuación, debido a que son el principal motivo de baja laboral en los trabajadores. Concretamente, la prevalencia de los TME representa más de 1,3 mil millones de personas y una pérdida de más de 100 millones de años de vida por incapacidad; siendo una causa común de incapacidad y de bajas laborales. Históricamente, el abordaje de los TME desde el lugar de trabajo se ha focalizado en la adopción de medidas ergonómicas, lo que ha sido positivo en algunos casos. Sin embargo, a pesar de las ergonómicas y biomecánicas llevadas de manera generalizada en los puestos de trabajo, el aumento de la prevalencia de los TME a escala global indica que no son medidas suficientes por si solas., Por lo tanto, nuevos enfoques holísticos que tengan en cuenta aspectos biológicos, psicológicos y sociales para su abordaje son necesarios. Desde la Alianza Europea Prevent4Work para la prevención de los TME en el ámbito laboral, se ha elaborado este documento en forma de guía en base al conocimiento científico más reciente y relevante. Tanto las empresas como sus trabajadores se pueden beneficiar de las recomendaciones de esta guía.

The water snowline location in protostellar envelopes provides crucial information about the thermal structure and the mass accretion process as it can inform about the occurrence of recent (≲1000 yr) accretion bursts. In addition, the ability to image water emission makes these sources excellent laboratories to test indirect snowline tracers such as H13CO+. We study the water snowline in five protostellar envelopes in Perseus using a suite of molecular-line observations taken with the Atacama Large Millimeter/submillimeter Array (ALMA) at ∼0.″2−0.″7 (60–210 au) resolution. B1-c provides a textbook example of compact H 2 18 O (31,3−22,0) and HDO (31,2−22,1) emission surrounded by a ring of H13CO+ (J = 2−1) and HC18O+ (J = 3−2). Compact HDO surrounded by H13CO+ is also detected toward B1-bS. The optically thick main isotopologue HCO+ is not suited to trace the snowline, and HC18O+ is a better tracer than H13CO+ due to a lower contribution from the outer envelope. However, because a detailed analysis is needed to derive a snowline location from H13CO+ or HC18O+ emission, their true value as a snowline tracer will lie in the application in sources where water cannot be readily detected. For protostellar envelopes, the most straightforward way to locate the water snowline is through observations of H 2 18 O or HDO. Including all subarcsecond-resolution water observations from the literature, we derive an average burst interval of ∼10,000 yr, but high-resolution water observations of a larger number of protostars are required to better constrain the burst frequency.

Deep learning based trajectory similarity computation holds the potential for improved efficiency and adaptability over traditional similarity computation. However, existing learning-based trajectory similarity learning solutions prioritize spatial similarity over temporal similarity, making them suboptimal for time-aware analyses. To this end, we propose ST2Vec, a representation learning based solution that considers fine-grained spatial and temporal relations between trajectories to enable spatio-temporal similarity computation in road networks. Specifically, ST2Vec encompasses two steps: (i) spatial and temporal modeling that encode spatial and temporal information of trajectories, where a generic temporal modeling module is proposed for the first time; and (ii) spatio-temporal co-attention fusion, where two fusion strategies are designed to enable the generation of unified spatio-temporal embeddings of trajectories. Further, under the guidance of triplet loss, ST2Vec employs curriculum learning in model optimization to improve convergence and effectiveness. An experimental study offers evidence that ST2Vec outperforms state-of-the-art competitors substantially in terms of effectiveness and efficiency, while showing low parameter sensitivity and good model robustness. Moreover, similarity involved case studies including top-k querying and DBSCAN clustering offer further insight into the capabilities of ST2Vec.

Computing path queries such as the shortest path in public transport networks is challenging because the path costs between nodes change over time. A reachability query from a node at a given start time on such a network retrieves all points of interest (POIs) that are reachable within a given cost budget. Reachability queries are essential building blocks in many applications, for example, group recommendations, ranking spatial queries, or geomarketing. We propose an efficient solution for reachability queries in public transport networks. Currently, there are two options to solve reachability queries. (1) Execute a modified version of Dijkstra’s algorithm that supports time-dependent edge traversal costs; this solution is slow since it must expand edge by edge and does not use an index. (2) Issue a separate path query for each single POI, i.e., a single reachability query requires answering many path queries. None of these solutions scales to large networks with many POIs. We propose a novel and lightweight reachability index. The key idea is to partition the network into cells. Then, in contrast to other approaches, we expand the network cell by cell. Empirical evaluations on synthetic and real-world networks confirm the efficiency and the effectiveness of our index-based reachability query solution.

Introduction Acute exacerbations of chronic obstructive pulmonary disease are associated with high morbidity and mortality. Telemonitoring may reduce the frequency of hospitalization. The aim of this study was to investigate the effect of telemonitoring on hospitalization rates for acute exacerbations of chronic obstructive pulmonary disease. Methods Patients were recruited during hospitalization and equally randomized to telemonitoring or usual care. Telemonitoring participants recorded symptoms and monitored oxygen saturation, heart rate, peak expiratory flow, and body weight. Alerts were generated if readings breached thresholds. Acute exacerbations of chronic obstructive pulmonary disease hospitalizations during the 6 months intervention were compared using logistic regression, and time to first hospitalization was assessed using Cox proportional hazard modeling. The incidence rates for acute exacerbations of chronic obstructive pulmonary disease hospitalization were compared using a negative binomial regression model with between-group comparisons expressed as incidence rate ratios. The telemonitoring group was used as reference. Results A total of 222 patients were randomized. 37/112 (33%) in the control group and 31/110 (28%) in the telemonitoring group experienced acute exacerbations of chronic obstructive pulmonary disease hospitalization during the intervention period, odds ratio of 1.26, confidence interval 0.71–2.23, p = 0.4. No difference was seen in time to first hospitalization, hazard ratio 1.23, CI 0.77–1.99, p = 0.4. The number of hospitalizations in the intervention period was 66 in the control group and 42 in the telemonitoring group, with incidence rate ratio 1.42, confidence interval 1.04–1.95, p = 0.03. Adjustment for dyspnea score, smoking, and cohabitation status did not change the results, incidence rate ratio 1.44, confidence interval 1.05–1.99, p = 0.02. Discussion Patients who received telemonitoring experienced significantly fewer acute exacerbations of chronic obstructive pulmonary disease hospitalizations, although the overall risk of having at least one hospitalization and the time to first hospitalization was similar between the two groups.

In “Path Dependence and the Roots of Interorganizational Relationship Challenges,” recently published by PPMG, we suggested the utility of path dependency theory in unpacking the developmental dynamics that may feed into contemporary problems of management and governance. Professor Jörg Sydow was moved to submit commentary on our article; we respond to his thoughtful comments in this essay.