FairEdge: A Fairness-Oriented Task Offloading Scheme for Iot Applications in Mobile Cloudlet Networks

Mobile cloud computing has emerged as a promising paradigm to facilitate computation-intensive and delay-sensitive mobile applications. Computation offloading services at the edge mobile cloud environment are provided by small-scale cloud infrastructures such as cloudlets. While offloading tasks to in-proximity cloudlets enjoys benefits of lower latency and smaller energy consumption, new issues related to the cloudlets are rising. For instance, unbalanced task distribution and huge load gaps among heterogeneous mobile cloudlets are becoming challenging with respect to network dynamics and distributed task offloading. In this paper, we propose 'FairEdge', a Fairness-oriented computation offloading scheme to enable balanced task distribution for mobile Edge cloudlet networks. By integrating the balls-and-bins theory with fairness index, our solution promotes effective load balancing with limited information at low computation cost. The evaluation results from extensive simulations and experiments with real-world datasets show that FairEdge outperforms conventional task offloading methods, it can achieve a network fairness up to 0.85 and reduce the unbalanced task offload by 50%

Autologous Skin Fibroblast-Based PLGA Nanoparticles for Treating Multiorgan Fibrosis

Fibrotic diseases remain a substantial health burden with few therapeutic approaches. A hallmark of fibrosis is the aberrant activation and accumulation of myofibroblasts, which is caused by excessive profibrotic cytokines. Conventional anticytokine therapies fail to undergo clinical trials, as simply blocking a single or several antifibrotic cytokines cannot abrogate the profibrotic microenvironment. Here, biomimetic nanoparticles based on autologous skin fibroblasts are customized as decoys to neutralize multiple fibroblast-targeted cytokines. By fusing the skin fibroblast membrane onto poly(lactic-co-glycolic) acid cores, these nanoparticles, termed fibroblast membrane-camouflaged nanoparticles (FNPs), are shown to effectively scavenge various profibrotic cytokines, including transforming growth factor-beta, interleukin (IL)-11, IL-13, and IL-17, thereby modulating the profibrotic microenvironment. FNPs are sequentially prepared into multiple formulations for different administration routines. As a proof-of-concept, in three independent animal models with various organ fibrosis (lung fibrosis, liver fibrosis, and heart fibrosis), FNPs effectively reduce the accumulation of myofibroblasts, and the formation of fibrotic tissue, concomitantly restoring organ function and indicating that FNPs are a potential broad-spectrum therapy for fibrosis management.Peer reviewe

Role of perioperative nutritional status and enteral nutrition in predicting and preventing post-operative complications in patients with Crohn’s disease

BackgroundPerioperative immune-nutritional status is correlated with post-operative outcomes. This study aimed to evaluate whether pre-operative nutritional status could predict post-operative complications in patients with Crohn’s disease (CD) and whether pre-operative enteral nutrition (EN) can prevent post-operative complications.MethodsThis retrospective cohort study analyzed the electronic health records of 173 patients diagnosed with CD in Ruijin Hospital, Shanghai, China, between August 2015 and May 2021: 122 patients had pre-operative nutritional support while 51 patients underwent surgery without pre-operative nutritional support. The pre-operative nutritional status, disease activity index, disease-related data, frequency of multiple surgery, operative data, and post-operative characters in each group were compared to determine whether the nutritional support and status could significantly affect post-operative outcome. One-to-one propensity score matching (PSM) was performed to limit demographic inequalities between the two groups.ResultsAfter PSM, no statistically significant differences were found in pre-operative patient basic characteristics between the two groups of 47 patients (98 patients in all) included in this study. Overall, 21 patients developed 26 post-operative complications. In terms of pre-operative nutritional status, the level of serum albumin (ALB), pre-albumin (pre-ALB), and hemoglobin (Hb) in the nutrition group were statistically higher than that in the control group. We also observed a statistically significant decrease in post-operative complications, need for emergency surgery, and staged operations, while the rate of laparoscopic surgery was higher in the nutrition group compared to the non-nutritional group. Post-operative complications were related to pre-operative nutritional condition, which indicated that EN may improve the nutritional status and reduced the rate of post-operative complications.ConclusionPre-operative nutritional status is correlated with post-operative outcomes while EN plays a positive role in preventing the post-operative complications. EN is useful for improving the pre-operative nutritional status and reducing the post-operative adverse events for CD patients undergoing surgery

Einfluss der multikriteriellen Kalibrierung bei der Modellierung der hydrologischen Prozesse und der Stickstoffbelastung in Wassereinzugsgebieten

Process-based hydrological models, which simulate nitrogen load from its sources to the receiving waterbody, play an important role in supporting catchment management. The reliability of those models, such as the representative model SWAT used in this study, is determined by a sound calibration and the analysis of the prediction uncertainty. The multi-objective calibration approach prevails the classic single-objective calibration on the spatial parameterization of specific processes. However, the requirement of additional observations and practical procedures limits its application. Moreover, the prediction uncertainty of nitrogen load is inevitable and should also be quantified. This study is a scientific contribution to catchment management by overcoming the challenge with a systematic, well-founded concept of multi-objective calibration and uncertainty analysis for nitrogen load simulation in data-scarce catchments. The concept is tested and proofed by its practical applicability on the Yuan River Catchment (YRC) in China and leads to a generalized, recommended procedure for catchment management application as valuable progress in this field. The study proposed to apply three groups of objectives, multi-site, multi-objective-function, and multi-metric. The applicability and the advantages of two multi-objective calibration approaches, Euclidean Distance and Non-Dominated Sorting Genetic Algorithm-II were analyzed. To quantify the prediction uncertainty, the study proposed to use the simulations with the highest or the lowest percent bias to represent the uncertainty band of the nitrogen load from the critical source areas (CSAs) and to the stream. The data-scarcity of the YRC was overcome by metrics obtained from open-access satellite-based datasets and metrics extracted from the existing discharge observations. Results show that multi-objective calibration has ensured the model’s better performance in terms of the spatial parameterization, the magnitude of the output time-series and the water balance components, in comparison to single-objective calibration. The predicted CSAs showed that 50% of the total nitrogen (TN) loading to the stream was from 26.3% to 37.1% of the area in the YRC. Meanwhile, over 50% of those TN were from the paddy field. Recommendations for application go to the multi-objective calibration considering all three groups of objectives. Approaches to obtain multi-metric objectives in the YRC are also applicable for catchments with data-scarcity. Recommendations for nitrogen management in the YRC is to emphasize the CSAs identified, especially the paddy field.Prozessbasierte hydrologische Modelle zur Simulation des Stickstofftransports und der resultierenden Belastung in Gewässern sind der Unterstützung des Managements von Wassereinzugsgebieten wichtig. Die Zuverlässigkeit dieser Modelle, wie das repräsentative Modell SWAT, wird durch eine sorgfältige Kalibrierung und die Analyse der Vorhersageunsicherheit bestimmt. Eine Kalibrierung auf der Basis von mehrkriteriellen Optimierung hat sich gegenüber der Kalibrierung mit einer Zielfunktion insbesondere zur räumlichen Parametrisierung relevanter Prozesse bewährt. Sie erfordert jedoch umfangreiche zusätzliche Beobachtungs- und Messwerte sowie zielführende Vorgehensweisen/Verfahren. Die Schwierigkeit der Quantifizierung der zugehörigen Vorhersageunsicherheit der Stickstoffbelastung erhöht sich ebenfalls deutlich. Diese Dissertation ist ein wissenschaftlicher Beitrag zum Management von datenarmen Wassereinzugsgebieten, indem sie die gegebene Herausforderung mit einem systematischen, fundierten Konzept der mehrkriteriellen Kalibrierung und zugehörige Unsicherheitsanalyse für die Simulation der Stickstoffbelastung angeht. Das Konzept wird hinsichtlich der praktischen Anwendbarkeit am Beispiel des Yuan River Catchment (YRC) in China entwickelt und getestet. Daraus wird eine allgemeine Vorgehensweise in datenarmen Wassereinzugsgebieten als wissenschaftlicher Beitrag in diesem Bereich abgeleitet. In der Dissertation werden die verschiedenen Zielkriterien bei der Modellkalibrierung in drei Gruppen klassifiziert: multi-site, multi-objective-function und multi-metric. Die Anwendbarkeit und die Vor- und Nachteile von zwei mehrkriteriellen Kalibrierungsverfahren, Euclidean Distance und Non-Dominated Sorting Genetic Algorithm II werden eingesetzt. Um die Vorhersageunsicherheit zu quantifizieren, werden die Simulationen mit der höchsten oder niedrigsten prozentualen Abweichung für die Spezifikation der Unsicherheitsbandbreite verwendet. Die Datenknappheit des Wassereinzugsgebietes YRC wurde durch die Verwendung von Messungen aus mehrerer, verschiedenen Quellen (multi-metric) überwunden: satellitenbasierte Open-Access-Datensätzen und die vorhandenen Abflussmessungen im Gewässer. Die Ergebnisse zeigen, dass die mehrkriteriellen Kalibrierung die Qualität des Simulationsmodells im Vergleich zur Kalibrierung mit einer Zielfunktion signifikant erhöht hat. Die vorhergesagten kritischen Stickstoffeintragsbereiche (critical source areas, CSAs) zeigen, dass 50% der gesamten Stickstoffbelastung des Yuan River 26,3% bis 37,1% der Fläche im YRC ausmachen. Für die praktische Umsetzung beim Management von Wassereinzugsgebieten wird empfohlen, für die mehrkriteriellen Kalibrierung in datenarmen Einzugsgebieten wie dem YRC alle drei Gruppen von Zielkriterien zu verwenden. Spezifisch für das YRC wird empfohlen, bzgl. der Stickstoffbelastung ein besonderes Augenmerk auf die Reisfelder im Bereich der CSAs und deren Bewirtschaftung zu legen

The analysis of nitrogen load and simulation uncertainty using SWAT in a catchment with paddy field in China

Excessive load of nitrogen from anthropogenic sources is a threat to sustaining a healthy aquatic ecosystem. The difficulty in identifying the critical source areas (CSAs) of nitrogen load and apportioning the in-stream nitrogen to individual sources spatially and seasonally has made the Soil and Water Assessment Tool (SWAT) useful for analyzing nitrogen load at the catchment scale. However, the uncertainty of the nitrogen load simulated by SWAT has rarely been analyzed. The two simulations with the highest or the lowest PBIAS of total nitrogen (TN) load were proposed in this study to represent the range of the prediction uncertainty and therefore were used to generate the uncertainty of CSAs and nitrogen source apportionment. The model was set up for the Yuan River Catchment, which is under threat of extensive nitrogen load. Results indicated the highest nitrogen load was from downstream paddy fields with a denser population and 85% of the load was from fertilizer and feedlots. The relatively high prediction uncertainty was observed on both CSAs and source apportionment, which emphasizes the limitation of calibration only based on certain processes and the necessity to consider parameter uncertainty in the application of nitrogen load simulation

The Effect of Grain Size on the Diffusion Bonding Properties of SP700 Alloy

Superplastic forming and diffusion bonding (SPF/DB) has been recognized as a viable manufacturing technology. However, the basic understanding of grain size and its effects on the quality of diffusion bonds is still limited. In this study, a certain type of SP700 alloy with different grain sizes is bonded at superplastic temperature. The experimental results indicate that the same materials, if coarse-grained, may not readily bond under identical conditions of pressure, temperature, and time. This type of bonding is possible because of the presence of many grain boundaries in fine-grained materials that act as short-circuit paths for diffusion. In addition, grain-boundary migration is also faster in fine-grained than in coarse-grained materials. Fractographic studies show that the dimples on the coarse-grained specimen have large dimensions compared with that in the fine-grained material, indicating that heterogeneous deformation develops in the coarse-grained specimen during tension

Sema3A inactivates the ERK/JNK signalling pathways to alleviate inflammation and oxidative stress in lipopolysaccharide-stimulated rat endothelial cells and lung tissues

Semaphorin 3A (Sema3A) is a secretory member of the semaphorin family of immune response regulators. This research focuses on its effects on inflammation and oxidative stress in acute respiratory distress syndrome (ARDS). By analysing the GEO dataset GSE57011, we obtained Sema3A as the most downregulated gene in ARDS samples. Lipopolysaccharide (LPS) was used to stimulate rat pulmonary microvascular endothelial cells (PMVECs) and rats to induce ARDS-like symptoms in vitro and in vivo, respectively. LPS induced severe damage in rat lung tissues, in which reduced immunohistochemical staining of Sema3A was detected. Sema3A overexpression reduced apoptosis and angiogenesis of LPS-induced PMVECs and alleviated lung injury and pulmonary edoema of rats. Moreover, ELISA results showed that Sema3A overexpression downregulated the levels of inflammatory cytokines and oxidative stress markers both in PMVECs and the rat lung. Activation of ERK/JNK signalling aggravated LPS-induced damage on PMVECs; however, the aggravation was partly blocked by Sema3A, which suppressed phosphorylation of ERK/JNK. Overall, this study demonstrates that Sema3A inactivates the ERK/JNK signalling to ameliorate inflammation and oxidative stress in LPS-induced ARDS models. Sema3A might therefore represent a candidate option for ARDS treatment

The Influence of Surface Processing on the Surface Plasmonic Enhancement of an Al-Nanoparticles-Enhanced ZnO UV Photodectector

Surface Plasmonic Resonance (SPR) induced by metallic nanoparticles can be exploited to enhance the response of photodetectors (PD) to a large degree. Since the interface between metallic nanoparticles and semiconductors plays an important role in SPR, the magnitude of the enhancement is highly dependent on the morphology and roughness of the surface where the nanoparticles are distributed. In this work, we used mechanical polishing to produce different surface roughnesses for the ZnO film. Then, we exploited sputtering to fabricate Al nanoparticles on the ZnO film. The size and spacing of the Al nanoparticles were adjusted by sputtering power and time. Finally, we made a comparison among the PD with surface processing only, the Al-nanoparticles-enhanced PD, and the Al-nanoparticles-enhanced PD with surface processing. The results showed that increasing the surface roughness could enhance the photo response due to the augmentation of light scattering. More interestingly, the SPR induced by the Al nanoparticles could be strengthened by increasing the roughness. The responsivity could be enlarged by three orders of magnitude after we introduced surface roughness to boost the SPR. This work revealed the mechanism behind how surface roughness influences SPR enhancement. This provides new means for improving the photo responses of SPR-enhanced photodetectors