Organic Photovoltaic Cells Based on PbPc Nanocolumns Prepared by Glancing Angle Deposition

Organic small material lead phthalocyanine (PbPc) nanocolumns were prepared via glancing angle deposition (GLAD) on indium tin oxide (ITO) coated glass substrates. Organic electron acceptor materials fullerene (C60) was evaporated onto the nanocolumn PbPc thin films to prepare heterojunction structure ITO/PbPc/C60/Bphen/Al organic photovoltaic cells (OPVs). It is worthwhile to mention that C60 molecules firstly fill the voids between PbPc nanocolumns and then form impact C60 layer. The interpenetrating electron donor/acceptor structure effectively enhances interface between electron donor and electron acceptor, which is beneficial to exciton dissociation. The short circuit current density (Jsc) of organic photovoltaic devices (OPVs) based on PbPc nanocolumn was increased from 1.19 mA/cm2 to 1.74 mA/cm2, which should be attributed to the increase of interface between donor and acceptor. The effect of illumination intensity on the performance of OPVs was investigated by controlling the distance between light source and sample, and the Jsc of two kind of OPVs was increased along with the increase of illumination intensity

Dimeth­yl(2-oxo-2-phenyl­eth­yl)sulfanium bromide

Single crystals of the title compound, C10H13OS+·Br−, were obtained from ethyl acetate/ethyl ether after reaction of acetophenone with hydro­bromic acid and dimethyl­sulfoxide. The carbonyl group is almost coplanar with the neighbouring phenyl ring [O—C—C—C = 178.9 (2)°]. The sulfanium group shows a trigonal–pyramidal geometry at the S atom. The crystal structure is stabil­ized by C—H⋯Br hydrogen-bonding inter­actions. Weak π–π inter­actions link adjacent phenyl rings [centroid–centroid distance = 3.946 (2) Å]

Distributed Coordination of Fractional Dynamical Systems with Exogenous Disturbances

Distributed coordination of fractional multiagent systems with external disturbances is studied. The state observer of fractional dynamical system is presented, and an adaptive pinning controller is designed for a little part of agents in multiagent systems without disturbances. This adaptive pinning controller with the state observer can ensure multiple agents' states reaching an expected reference tracking. Based on disturbance observers, the controllers are composited with the pinning controller and the state observer. By applying the stability theory of fractional order dynamical systems, the distributed coordination of fractional multiagent systems with external disturbances can be reached asymptotically

HGT: A Hierarchical GCN-Based Transformer for Multimodal Periprosthetic Joint Infection Diagnosis Using CT Images and Text

Prosthetic Joint Infection (PJI) is a prevalent and severe complication characterized by high diagnostic challenges. Currently, a unified diagnostic standard incorporating both computed tomography (CT) images and numerical text data for PJI remains unestablished, owing to the substantial noise in CT images and the disparity in data volume between CT images and text data. This study introduces a diagnostic method, HGT, based on deep learning and multimodal techniques. It effectively merges features from CT scan images and patients' numerical text data via a Unidirectional Selective Attention (USA) mechanism and a graph convolutional network (GCN)-based feature fusion network. We evaluated the proposed method on a custom-built multimodal PJI dataset, assessing its performance through ablation experiments and interpretability evaluations. Our method achieved an accuracy (ACC) of 91.4\% and an area under the curve (AUC) of 95.9\%, outperforming recent multimodal approaches by 2.9\% in ACC and 2.2\% in AUC, with a parameter count of only 68M. Notably, the interpretability results highlighted our model's strong focus and localization capabilities at lesion sites. This proposed method could provide clinicians with additional diagnostic tools to enhance accuracy and efficiency in clinical practice

Modelling and analyses of helical milling process

A comparison between the geometry of the helical milling specialized tool and conventional end mill was firstly introduced. Furthermore, a mathematical model, in which the cutting area was divided into different cutting zones, was established to simulate the cutting depths and volume of the different cutting edges (three kinds) on specialized tool. Accordingly, a specific ratio between the volume removed by different edges and the total hole volume was derived mathematically and modeled using 3D modeling software SolidWorks. Based on the established models, the cutting depths and cutting volume ratio variation trends under different cutting parameters were analyzed. The results showed that the change rules of cutting depths were different in every cutting zone and influenced greatly by the cutting parameters. In addition, the cutting volume ratio changes with different cutting parameters, but it can only vary in certain range due to the structure of the helical milling specialized tool. The cutting volume ratio obtained from the established model shows a good agreement with the data modeled using SolidWorks, proving that the established model is appropriate. Moreover, the undeformed chip geometry was modeled and observed using SolidWorks. The undeformed chip showed a varying geometry with different cutting parameters and it can be optimized to obtain a good cutting condition during helical milling process

Accuracy-Aware Uncertain Stream Databases

Abstract-Previous work has introduced probability distributions as first-class components in uncertain stream database systems. A lacking element is the fact of how accurate these probability distributions are. This indeed has a profound impact on the accuracy of query results presented to end users. While there is some previous work that studies unreliable intermediate query results in the tuple uncertainty model, to the best of our knowledge, we are the first to consider an uncertain stream database in which accuracy is taken into consideration all the way from the learned distributions based on raw data samples to the query results. We perform an initial study of various components in an accuracy-aware uncertain stream database system, including the representation of accuracy information and how to obtain query results' accuracy. In addition, we propose novel predicates based on hypothesis testing for decision-making using data with limited accuracy. We augment our study with a comprehensive set of experimental evaluations. I. INTRODUCTION Recent research has extended stream databases to handle uncertain data in order to meet the requirements from everincreasing applications in sensor networks and ubiquitous computing (e.g., Where do we obtain the probabilities in the first place? In many applications, probability distributions are learned from observations and measurements, a.k.a. samples. Such applications include sensor networks, ubiquitous computing, and scientific databases. Let us look at an example. Example 1 (accuracy of learned probability distributions). A few projects in both academia and industry (e.g., the CarTel project at MIT [24

Modification of wetting property of Inconel 718 surface by nanosecond laser texturing

Topographic and wetting properties of Inconel 718 (IN718) surfaces were modified via nanosecond laser treatment. In order to investigate surface wetting behavior without additional post treatment, three kinds of microstructures were created on IN718 surfaces, including line pattern, grid pattern and spot pattern. From the viewpoint of surface morphology, the results show that laser ablated grooves and debris significantly altered the surface topography as well as surface roughness compared with the non-treated surfaces. The effect of laser parameters (such as laser scanning speed and laser average power) on surface features was also discussed. We have observed the treated surface of IN718 showed very high hydrophilicity just after laser treatment under ambient air condistion.And this hydrophicility property has changed rapidly to the other extreme; very high hydrophobicity over just about 20 days. Further experiments and analyses have been carried out in order to investigate this phenomena. Based on the XPS analysis, the results indicate that the change of wetting property from hydrophilic to hydrophobic over time is due to the surface chemistry modifications, especially carbon content. After the contact angles reached steady state, the maximum water contact angle (WCA) for line-patterned and grid-patterned surfaces increased to 152.3 1.2° and 156.8 1.1° with the corresponding rolling angle (RA) of 8.8 1.1° and 6.5 0.8°, respectively. These treated IN718 surfaces exhibited superhydrophobic property. However, the maximum WCA for the spot-patterned surfaces just increased to 140.8 2.8° with RA above 10°. Therefore, it is deduced that laser-inscribed modification of surface wettability has high sensitivity to surface morphology and surface chemical compositions. This work can be utilized to optimize the laser processing parameters so as to fabricate desired IN718 surfaces with hydrophobic or even superhydrophobic property and thus extend the applications of IN718 material in various fields

Examining ERP Committee Beliefs: A Comparison of Alternative Models

Various models have been proposed to explain information technology (IT) adoption behavior. However, these models are based primarily on logical deliberation. In reality, it is impossible to obtain perfect information for a rational evaluation of new or emerging IT. In this situation, sometimes the “best alternative” is imitation. We believe that two opposing forces influence the beliefs of enterprise resource planning (ERP) committee members: rational and imitative. We propose here an integrated model and examine it together with diffusion of innovation (DOI) and imitation models. The study findings indicate that our integrated model has better explanatory power. In addition, imitative forces are shown to have a consistent direct effect and significant indirect effect on beliefs. Hence, imitative forces play a crucial role in the decision-making process, which opens up a new avenue for research into technology adoption