Background
Coronal alignment of the tibial component determines functional outcome and survival in total knee arthroplasty (TKA). Innovative techniques for tibial instrumentation have been developed ...to improve accuracy and reduce the rate of outliers.
Methods
In a prospective study, 300 patients were allocated to four different groups using a randomization process (two innovative and two conventional) techniques of tibial instrumentation (conventional: extramedullary, intramedullary; innovative: navigation and patient-specific instrumentation (PSI);
n
= 75 for each group). The aims were to reconstruct the medial proximal tibial angle (MPTA) to 90° and the mechanical tibio-femoral axis (mTFA) to 0°. Both angles were evaluated and compared between all groups three months after the surgery. Patients who presented with a postoperative mTFA > 3° were classified as outliers.
Results
The navigation and intramedullary technique both demonstrated that they were significantly more precise in reconstructing a neutral mTFA and MPTA compared to the other two techniques. The odd’s ratio (OR) for producing outliers was highest for the PSI method (PSI OR = 5.5,
p
< 0.05; extramedullary positioning OR = 3.7,
p
> 0.05; intramedullary positioning OR = 1.7,
p
> 0.05; navigation OR = 0.04,
p
< 0.05). We could only observe significant differences between pre- and postoperative MPTA in the navigation and intramedullary group. The MPTA showed a significant negative correlation with the mTFA in all groups preoperatively and in the extramedullary, intramedullary and PSI postoperatively.
Conclusion
The navigation and intramedullary instrumentation provided the precise positioning of the tibial component. Outliers were most common within the PSI and extramedullary technique. Optimal alignment is dependent on the technique of tibial instrumentation and tibial component positioning determines the accuracy in TKA since mTFA correlated with MPTA pre- and postoperatively.
•441 influenza virus infections from a Swiss Hospital were included.•During 4 influenza seasons, 238 infections due to influenza A virus; 203 due to b.•30-day mortality was 6.0% and independently ...associated with A virus.•qSOFA≥2 points showed a very good accuracy (0.89).•Hospital-acquired infection was a predictor of worst outcome.
Influenza infections have been associated with high morbidity. The aims were to determine predictors of mortality among patients with influenza infections and to ascertain the role of quick Sequential Organ Failure Assessment (qSOFA) in predicting poor outcomes.
All adult patients with influenza infection at the Hospital of Jura, Switzerland during four influenza seasons (2014/15 to 2017/18) were included. Cepheid Xpert Xpress Flu/RSV was used during the first three influenza seasons and Cobas Influenza A/B and RSV during the 2017/18 season.
Among 1684 influenza virus tests performed, 441 patients with influenza infections were included (238 for influenza A virus and 203 for B). The majority of infections were community onset (369; 83.7%). Thirty-day mortality was 6.0% (25 patients). Multivariate analysis revealed that infection due to A virus (P 0.035; OR 7.1; 95% CI 1.1–43.8), malnutrition (P < 0.001; OR 25.0; 95% CI 4.5–138.8), hospital-acquired infection (P 0.003; OR 12.2; 95% CI 2.3–65.1), respiratory insufficiency (PaO2/FiO2 < 300) (P < 0.001; OR 125.8; 95% CI 9.6–1648.7) and pulmonary infiltrate on X-ray (P 0.020; OR 6.0; 95% CI 1.3–27.0) were identified as predictors of mortality. qSOFA showed a very good accuracy (0.89) equivalent to other more specific and burdensome scores such as CURB-65 and Pneumonia Severity Index (PSI).
qSOFA performed similarly to specific severity scores (PSI, CURB-65) in predicting mortality. Infection by influenza A virus, respiratory insufficiency and malnutrition were associated with worse prognosis.
To fill the “green absorption gap”, a green absorbing proteorhodopsin was expressed in a PSI-deletion strain (ΔPSI) of Synechocystis sp. PCC6803. Growth-rate measurements, competition experiments and ...physiological characterization of the proteorhodopsin-expressing strains, relative to the ΔPSI control strain, allow us to conclude that proteorhodopsin can enhance the rate of photoheterotrophic growth of ΔPSI Synechocystis strain. The physiological characterization included measurement of the amount of residual glucose in the spent medium and analysis of oxygen uptake- and production rates. To explore the use of solar radiation beyond the PAR region, a red-shifted variant Proteorhodopsin-D212N/F234S was expressed in a retinal-deficient PSI-deletion strain (ΔPSI/ΔSynACO). Via exogenous addition of retinal analogue an infrared absorbing pigment (maximally at 740 nm) was reconstituted in vivo. However, upon illumination with 746 nm light, it did not significantly stimulate the growth (rate) of this mutant. The inability of the proteorhodopsin-expressing ΔPSI strain to grow photoautotrophically is most likely due to a kinetic rather than a thermodynamic limitation of its NADPH-dehydrogenase in NADP+-reduction.
•Proteorhodopsin expression increases growth rate of a ∆PSI Synechocystis strain with at least 16 %.•Proteorhodopsin contributes to proton motive force generation in vivo in Synechocystis.•A transgenic Synechocystis strain has been generated that can absorb infrared light.•‘Reversed electron transfer’ through NDH-1 could not be demonstrated in Synechocystis.
This article proposes a neighbors' similarity-based fuzzy community detection (FCD) method, which we call "NeSiFC." In the proposed NeSiFC approach, we compute the similarity between two neighbors by ...introducing a modified local random walk (mLRW). Basically, in a network, a node and its' neighbors with noticeable similarities among them construct a community. To measure this similarity, we introduce a new metric, called the peripheral similarity index (PSI). This PSI is used to construct the transition probability matrix for the mLRW. The mLRW is applied for each node until it meets a parameter called step coefficient. The mLRW gives better neighbors' similarity for community detection. Finally, a fuzzy membership function is used iteratively to compute the membership degrees for all nodes with reference to existing communities. The proposed NeSiFC has no dependence on the network characteristics, and no adjustment or fine tuning of more than one parameter is needed. To show the efficacy of the proposed NeSiFC approach, we provide a thorough comparative performance analysis considering a set of well-known FCD algorithms viz., the genetic algorithm for fuzzy community detection, membership degree propagation, center-based fuzzy graph clustering, FMM/H2, and FuzAg on a set of popular benchmarks, as well as real-world datasets. For both disjoint and overlapping community structures, results of various accuracy and quality metrics indicate the outstanding performance of our proposed NeSiFC approach. The asymptotic complexity of the proposed NeSiFC is found as O(n 2 ).
Some complete monotonicity results for q-polygamma functions are proved. Our results extend positivity of some functions containing q-polygamma functions to complete monotonicity property. Also, we ...give two new inequalities for q-trigamma function.
Abstract
Then the pixel shape index method is used to extract the pixel shape index features of high spatial resolution remote sensing images and supplement the spectral features.The experimental ...results show that the pixel shape index feature can effectively distinguish the ground objects with similar spectral features but different geometric shapes, and is superior to the spectral feature classification method in accuracy.Compared with the small ripple feature method and the multi-scale region feature method, the pixel shape index method also achieves better results.On the other hand, it is found in the experiment that the method is easily affected by the detailed information in the high spatial resolution remote sensing image, and the classification effect of the region rich in detailed information is not ideal.In this paper, pixel shape index method is used to effectively distinguish ground object targets with similar spectral features but different shapes, and extract pixel shape index features of high-resolution remote sensing images. Compared with spectral features, pixel shape index features have great advantages in accuracy, and it is also conducive to the supplement of spectral features.
Introduction: There is the need of a simple but highly reliable score system for stratifying the risk of mortality and Intensive Care Unit (ICU) transfer in patients with SARS-CoV-2 pneumonia at the ...Emergency Room. Purpose: In this study, the ability of CURB-65, extended CURB-65, PSI and CALL scores and C-Reactive Protein (CRP) to predict intra-hospital mortality and ICU admission in patients with SARS-CoV-2 pneumonia were evaluated. Methods: During March-May 2020, a retrospective, single-center study including all consecutive adult patients with diagnosis of SARS-CoV-2 pneumonia was conducted. Clinical, laboratory and radiological data as well as CURB-65, expanded CURB-65, PSI and CALL scores were calculated based on data recorded at hospital admission. Results: Overall, 224 patients with documented SARS-CoV-2 pneumonia were included in the study. As for intrahospital mortality (24/224, 11%), PSI performed better than all the other tested scores, which showed lower AUC values (AUC=0.890 for PSI
versus
AUC=0.885, AUC=0.858 and AUC=0.743 for expanded CURB-65, CURB-65 and CALL scores, respectively). Of note, the addition of hypoalbuminemia to the CURB-65 score increased the prediction value of intra-hospital mortality (AUC=0.905). All the tested scores were less predictive for the need of ICU transfer (26/224, 12%), with the best AUC for extended CURB-65 score (AUC= 0.708). Conclusion: The addition of albumin level to the easy-to-calculate CURB-65 score at hospital admission is able to improve the quality of prediction of intra-hospital mortality in patients with SARS-CoV-2 pneumonia.
Since its launch in 2007, TerraSAR-X has continuously provided spaceborne synthetic aperture radar (SAR) images of our planet with unprecedented spatial resolution, geodetic, and geometric accuracy. ...This has brought life to the once inscrutable SAR images, which deterred many researchers. Thanks to merits like higher spatial resolution and more precise orbit control, we are now able to indicate individual buildings, even individual floors, to pinpoint targets within centimeter accuracy. As a result, multi-baseline SAR interferometric (InSAR) techniques are flourishing, from point target-based algorithms, to coherent stacking techniques, to absolute positioning of the former techniques. This article reviews the recent advances of multi-baseline InSAR techniques using TerraSAR-X images. Particular focus was put on our own development of persistent scatterer interferometry, SAR tomography, robust estimation in distributed scatterer interferometry and absolute positioning using geodetic InSAR. Furthermore, by introducing the applications associated with these techniques, such as 3D reconstruction and deformation monitoring, this article is also intended to give guidance to wider audiences who would like to resort to SAR data and related techniques for their applications.
Hydro turbine machineries erosion due to silt is a complex issue for the effective practice of hydropower plants. Erosion caused by silt of the Pelton turbine buckets is a compound phenomenon that ...depends on size of silt particles , silt particles concentration , velocity of jet , and working time . This paper deals with the influence of silt erosion for various silt loaded factors and effective parameters. The preference selection index (PSI) and technique for order of preference by similarity to ideal solution (TOPSIS) approaches has been adopted to find optimal set of parameters which offers the highest performance for the Pelton turbine. Based up on the results obtained from both PSI and TOPSIS approaches it is found that optimal performance has been provided by A-1 alternate with geometric and flow parameters as , , and respectively.