Miracle-dz/UniFAR-FTUs huggingface dataset:
Facile external treatment for efficient nanoscale morphology control of polymer solar cells using a gas-assisted spray method

A facile and effective treatment method for controlling the morphology of bulk heterojunction (BHJ) structured polymer-based solar cells (PSCs) using a gas-assisted spray (g-spray) technique was demonstrated. High-efficiency BHJ-PSCs were fabricated using a g-spray method that can be adapted to large-scale high-throughput continuous production, and the bulk film morphology and internal nanomorphology of the active layers were well manipulated using a sprayed solvent overlayer (SSO) treatment. The efficient nanomorphology evolution, which is a prerequisite for obtaining high performance BHJ-PSCs, was confirmed by X-ray diffraction, UV-Vis, photoluminescence, and transmission electron microscopy analysis. The SSO treatment was a simple and rapid process that could be carried out at room temperature, unlike conventional external treatment (ET) methods such as solvent- or thermal-assisted treatment, which typically require a prolonged time (>1 h) or relatively high temperature (>110 °C). After SSO treatment, the PSC performance was enhanced remarkably. The power conversion efficiency (PCE) of the g-sprayed PSCs after SSO treatment was 2.99%, which is higher than that of a solvent vapor treated device (2.42%) and thermally annealed devices (2.61%). Further optimization of the nanomorphology was achieved by sequentially developing P3HT and PCBM. By combining thermal annealing with the SSO treatment, the P3HT/PCBM interfacial area could be enhanced; this enhancement was induced by the PCBM diffusion into the space among pre-assembled P3HT nanofibrils, which in turn promoted their bi-continuity. This means of sequential nanomorphology development further enhanced the PCE (3.35%), which was higher than the other reported values for PSCs using spray methods. Considering that the SSO treatment is a facile room temperature process that requires a short time, these results suggest that the g-spray method can be successfully applied to the continuous production of PSCs.
Human mobility and predictability enriched by social phenomena information

The massive amounts of geolocation data collected from mobile phone records has sparked an ongoing effort to understand and predict the mobility patterns of human beings. In this work, we study the extent to which social phenomena are reflected in mobile phone data, focusing in particular in the cases of urban commute and major sports events. We illustrate how these events are reflected in the data, and show how information about the events can be used to improve predictability in a simple model for a mobile phone user's location.
Multicapillary electrophoresis disposable cartridge for bioseparations

We have successfully demonstrated the development of a compact and cost-effective parallel multi-channel capillary electrophoresis system for bio-molecules analysis. The automated process includes a buffer/gel replenishment mechanism, high voltage control of fluidics and an automated sample tray transport capability. The bio-separation/analysis occurs in a disposable cartridge containing multi-column capillaries with integrated excitation optical fibers, detection micro-optics and a buffer reservoir common to all separation channels. Tests of this fully integrated system indicate, that large quantities of biological samples can be analyzed automatically in a short period with highly sensitive fluorescence detection.
Objective Assessment of Physical Activity: Classifiers for Public Health.

PURPOSE Walking for health is recommended by health agencies, partly based on epidemiological studies of self-reported behaviors. Accelerometers are now replacing survey data, but it is not clear that intensity-based cut points reflect the behaviors previously reported. New computational techniques can help classify raw accelerometer data into behaviors meaningful for public health. METHODS Five hundred twenty days of triaxial 30-Hz accelerometer data from three studies (n = 78) were employed as training data. Study 1 included prescribed activities completed in natural settings. The other two studies included multiple days of free-living data with SenseCam-annotated ground truth. The two populations in the free-living data sets were demographically and physical different. Random forest classifiers were trained on each data set, and the classification accuracy on the training data set and that applied to the other available data sets were assessed. Accelerometer cut points were also compared with the ground truth from the three data sets. RESULTS The random forest classified all behaviors with over 80% accuracy. Classifiers developed on the prescribed data performed with higher accuracy than the free-living data classifier, but these did not perform as well on the free-living data sets. Many of the observed behaviors occurred at different intensities compared with those identified by existing cut points. CONCLUSIONS New machine learning classifiers developed from prescribed activities (study 1) were considerably less accurate when applied to free-living populations or to a functionally different population (studies 2 and 3). These classifiers, developed on free-living data, may have value when applied to large cohort studies with existing hip accelerometer data.
Adaptive Robust Expansion Planning for a Distribution Network With DERs

Distribution expansion planning (DEP) is used to determine the best expansion plan of a distribution system. Considering the uncertainties of loads and of power productions of wind distributed energy resources (DERs) and incorporating AC power flow equations make the DEP problem increasingly challenging. In this context, this paper presents a new adaptive robust distribution expansion planning model to identify the timing of feeder reinforcements in addition to the location, capacity, and installation time of dispatchable and wind DERs. The proposed approach characterizes the uncertain nature of loads and power productions of wind DERs through polyhedral uncertainty sets and the robustness of the solution can be controlled by means of a budget of uncertainty. Since AC power flow equations rather than DC ones are considered, the proposed model is a nonlinear and non-convex min–max–min optimization problem, which cannot be solved directly by commercial optimization packages. Hence, a tri-level decomposition algorithm using both primal and dual cutting planes is introduced to solve the problem. Additionally, to attain a smoother optimization problem, the non-convex AC power flow equations are convexified. The working of the proposed model is illustrated using 33-bus and 123-bus distribution networks.
Rendering of unfalsified PID gain sets for parameter space control design

In this paper, a new approach to the data-driven PID control design in parameter space is proposed. Namely, first, volume data of the PID gains that are falsified by a necessary condition for the maximum sensitivity constraint is calculated, and next it is visualized by volume rendering. Because of the recent development of parallel computation and GPU(graphics processing unit), rendering can be easily applied, and our main issue is how fast the volume data can be calculated by the parallel computation. We give an estimation method of the £2 gain using a filter bank from a finite length response data, and this method is used for the volume data calculation at ten-thousand grid points. Efficiency and accuracy of our algorithm are examined by numerical experiments.
MSCs seeded on bioengineered scaffolds improve skin wound healing in rats

Growing evidence has shown the promise of mesenchymal stromal cells (MSCs) for the treatment of cutaneous wound healing. We have previously demonstrated that MSCs seeded on an artificial dermal matrix, Integra (Integra Lifesciences Corp., Plainsboro, NJ) enriched with platelet‐rich plasma (Ematrix) have enhanced proliferative potential in vitro as compared with those cultured on the scaffold alone. In this study, we extended the experimentation by evaluating the efficacy of the MSCs seeded scaffolds in the healing of skin wounds in an animal model in vivo. It was found that the presence of MSCs within the scaffolds greatly ameliorated the quality of regenerated skin, reduced collagen deposition, enhanced reepithelization, increased neo‐angiogenesis, and promoted a greater return of hair follicles and sebaceous glands. The mechanisms involved in these beneficial effects were likely related to the ability of MSCs to release paracrine factors modulating the wound healing response. MSC‐seeded scaffolds, in fact, up‐regulated matrix metalloproteinase 9 expression in the extracellular matrix and enhanced the recruitment of endogenous progenitors during tissue repair. In conclusion, the results of this study provide evidence that the treatment with MSC‐seeded scaffolds of cutaneous wounds contributes to the recreation of a suitable microenvironment for promoting tissue repair/regeneration at the implantation sites.
Effect of Exercise on Pregnancy Outcome

The purpose of this review was to critically evaluate the scientific literature for the effects of exercise on pregnancy outcome. Evidenced-based studies were reviewed. Maternal outcomes analyzed in this review were gestational diabetes mellitus, preeclampsia, and weight gain, fetal outcomes evaluated were birth weight, time of delivery, and mode of delivery. Despite methodological pitfalls in the studies published, the evidence suggests a benefit of exercise in pregnancy. Exercise in pregnancy could prevent and limit adverse maternal and fetal morbidities and provide a long-term benefit through reduction of maternal weight gain during pregnancy, and improvement in cardiovascular fitness. Pregnancy emerges as a unique time for behavior modification.
Pulmonary perfusion quantification with flow‐sensitive inversion recovery (FAIR) UTE MRI in small animal imaging

Blood perfusion in lung parenchyma is an important property for assessing lung function. In small animals, its quantitation is limited even with radioactive isotopes or dynamic contrast‐enhanced MRI techniques. In this study, the feasibility flow‐sensitive alternating inversion recovery (FAIR) for the quantification of blood flow in lung parenchyma in free breathing rats at 7 T has been investigated. In order to obtain sufficient signal from the short T2* lung parenchyma, a 2D ultra‐short echo time (UTE) Look‐Locker read‐out has been implemented. Acquisitions were segmented to maintain acquisition time within an acceptable range. A method to perform retrospective respiratory gating (DC‐SG) has been applied to investigate the impact of respiratory movement. Reproducibilities within and between sessions were estimated, and the ability of FAIR‐UTE to identify the decrease of lung perfusion under hyperoxic conditions was tested. The implemented technique allowed for the visualization of lung parenchyma with excellent SNR and no respiratory artifact even in ungated acquisitions. Lung parenchyma perfusion was obtained as 32.54 ± 2.26 mL/g/min in the left lung, and 34.09 ± 2.75 mL/g/min in the right lung. Application of retrospective gating significantly but minimally changes the perfusion values, implying that respiratory gating may not be necessary with this center‐our acquisition method. A decrease of 10% in lung perfusion was found between normoxic and hyperoxic conditions, proving the feasibility of the FAIR‐UTE approach to quantify lung perfusion changes.
DeepThin: A Self-Compressing Library for Deep Neural Networks

As the industry deploys increasingly large and complex neural networks to mobile devices, more pressure is put on the memory and compute resources of those devices. Deep compression, or compression of deep neural network weight matrices, is a technique to stretch resources for such scenarios. Existing compression methods cannot effectively compress models smaller than 1-2% of their original size. We develop a new compression technique, DeepThin, building on existing research in the area of low rank factorization. We identify and break artificial constraints imposed by low rank approximations by combining rank factorization with a reshaping process that adds nonlinearity to the approximation function. We deploy DeepThin as a plug-gable library integrated with TensorFlow that enables users to seamlessly compress models at different granularities. We evaluate DeepThin on two state-of-the-art acoustic models, TFKaldi and DeepSpeech, comparing it to previous compression work (Pruning, HashNet, and Rank Factorization), empirical limit study approaches, and hand-tuned models. For TFKaldi, our DeepThin networks show better word error rates (WER) than competing methods at practically all tested compression rates, achieving an average of 60% relative improvement over rank factorization, 57% over pruning, 23% over hand-tuned same-size networks, and 6% over the computationally expensive HashedNets. For DeepSpeech, DeepThin-compressed networks achieve better test loss than all other compression methods, reaching a 28% better result than rank factorization, 27% better than pruning, 20% better than hand-tuned same-size networks, and 12% better than HashedNets. DeepThin also provide inference performance benefits ranging from 2X to 14X speedups, depending on the compression ratio and platform cache sizes.
Modeling trust for service e-marketplaces: case study in the manufacturing domain

Industrial countries are subject to structural change toward a service society, but trading industrial services using web applications remains highly restricted. Service offers are more difficult to assess than product offers, the value co-creation process of the service provision causes certain unpredictability of its outcome. Consumers perceive increased risks at service purchasing. This risk and the lack of trust in service stakeholders are main reasons that industrial procurement does not utilize possible benefits given by the use of electronic marketplaces at sourcing of services. The industrial service buyer evaluates the trustiness of the service provider as main process step at service discovery. This trust evaluation process needs to be supported by e-markets for services. This article discovers the information that must be described at e-markets, so that the industrial buyer can decide whether to trust the service provider's offer or not. An explorative case study in the automotive domain is conducted to explore factors that influence the confidence in services and the trust in a provider. A literature study is used to generalize the findings of the case study, to develop a conceptual model of trust factors. This research describes information that has to be represented at B2B e-markets for services, so that industrial buyers can evaluate the trustworthiness of an offer.
Design and Research of Camera Calibration System in Binocular Stereo Vision

Aiming at the camera calibration of binocular stereo vision system, based on Zhang’s calibration method, the specified points in the calibration template obtained by the Harris operator, a set of camera calibration system combined with VC++ and Matlab was developed. The results of the calibration system, comparing with those of four-step calibration method, was analyzed and showed that: the error of calibration data in this system was within 0~5 mm, which had a high precision calibration, providing a new reference measure for the camera calibration.
Contextual Insight in Search: Enabling Technologies and Applications

When the fields of efficient and scalable search, data aggregation, XML search and information extraction come together, we get a powerful and exciting mix. Taken together, these are enabling technologies that make it possible to search for information in new ways and that make new types of search applications possible. Using a state-of-the-art enterprise search platform as an example, this tutorial outlines the workings of these technologies and presents some applications of their intersection.Search engines differ from traditional databases in several ways, yet they both address the issue of organizing information and making it retrievable. The anatomy of a modern search engine will be presented. Although search engines are typically associated with web search, some are now equipped with features usually associated with databases and structured data, e.g., the ability to do aggregation of meta data across a full result set.Most search engines are built around a flat document model: A document is seen as a collection of typed fields, but the fields themselves have no particular structure. As such, queries tend to focus on document content, with little or no constraints on document structure. Recently, however, scalable and efficient search engines have appeared that support indexing and retrieval of complex XML. Queries that are posed to a search engine can thus combine content and structure in ways that enable extreme search precision. Furthermore, data aggregation can be restricted to take place on the level of the matching document fragments instead of on the document level, thus providing more contextually relevant statistics.Given XML capabilities, applying text mining and information extraction techniques to the content becomes particularly interesting: By automatically detecting semantic entities, and possibly also relations between these, this information can be searched for in different ways and, e.g., enable applications that have a strong element of discovery to them.
A novel information diffusion model for online social networks

Online social networks form a central platform for information sharing and influence maximization. Even though the information dissemination within online social networks flows naturally as diffusion process, the dynamics of online social networks make it challenging to model precisely the spreading mechanism and enable concise prediction of information diffusion. In this paper, we propose information diffusion model in online social networks that applies the physical radiation energy transfer phenomena. To our knowledge, this model is the first in domain that adapts the natural radiation transfer as predictive information diffusion model. Physically, the radiation transfers from one surface to another which has similar form of diffusion in online social networks where the contagion transfers from one user to another. Theoretically, the proposed RADiation DIFFusion (RADDIFF) model measures and predicts the density of influenced users at different levels from the source node. The model has validated on a dataset collected from Twitter. RADDIFF model can accurately predict the information diffusion within a community. The results show that the RADDIFF density reaches high number of users in the networks even though the initial set of users relatively small.
Comparison of the Physical and Technical Demands of Cricket Players During Training and Match-Play

Abstract Vickery, W, Duffield, R, Crowther, R, Beakley, D, Blanch, P, and Dascombe, BJ. Comparison of the physical and technical demands of cricket players during training and match-play. J Strength Cond Res 32(3): 821–829, 2018—This study aimed to determine which training method (net-based sessions or center-wicket simulations) currently used in national level and U19 male players cricket provided a more physical and technical match-specific training response. The heart rate, rating of perceived exertion, and movement patterns of 42 male cricket players were measured across the various training and match formats. Video analysis was coded retrospectively to quantify technical loads based on the cricket skills performed. Magnitude-based inferences were based on the standardization of effect and presented with ±90% confidence intervals. Regardless of playing position, differences in physiological demands between training modes and match-play were unclear, with the exception of higher heart rates in fielders during traditional net sessions (mean heart rate: d = −2.7 [−4.7 to −0.7]; 75% of maximum heart rate: d = −1.7 [−3.2 to −0.2]). Typically, the movement demands of center-wicket simulations were similar or greater than match-play, which was most evident in the distance traveled at a high intensity within each playing position (batsmen: d = 6.4 [3.7–9.2]; medium-fast bowlers: d = 1.71 [0.1–3.3]; spin bowlers: d = 6.5 [0.01–13.0]; fielders: d = 0.8 [−0.2 to 1.7]). The technical demands of traditional net cricket training exceeded that of a typical match for each playing position. Specifically, fast bowlers delivered a greater number of balls during net-bowling compared with a match (d = −2.2 [−3.6 to 0.9]). In conclusion, center-wicket simulations more closely matched the physical demands of a One-Day match within batsmen and spin bowlers, whereas traditional cricket training often exceeded match-specific demands.
The coping experiences of spouses of persons with dementia

AIMS AND OBJECTIVES To explore how spouses who are caregivers to persons with dementia experience everyday life 6-12 months after participation in the intervention condition in the Norwegian Cognitive Behavioural Therapy for Early Dementia (N-CORDIAL) study. BACKGROUND There is no current medical curative treatment for cognitive impairment and dementia-associated conditions. These conditions will lead to an increased need for daily assistance and care, as well as greater stress for caregivers. The Norwegian CORDIAL Study is a manual-based randomised controlled trial based on the German CORDIAL study (cognitive rehabilitation and cognitive behavioural treatment for early dementia in Alzheimer's disease), consisting of cognitive rehabilitation, cognitive behavioural therapy and life review methods. DESIGN AND METHODS A descriptive exploratory study with qualitative semi-structured in-depth interviews with six spouses of persons with dementia who had participated in the Norwegian CORDIAL study. The transcribed text was analysed by systematic text condensation. RESULT The main theme identified, "An everyday search for meaning," referred to the stress experienced by the caregivers and their coping strategies in everyday life. CONCLUSION The caregivers had gained increased awareness of coping strategies in everyday life 6-12 months after the intervention. Caregivers who experienced fewer neuropsychiatric symptoms in their spouses with dementia benefitted most from the intervention. RELEVANCE TO CLINICAL PRACTICE The study is relevant to clinical practice as interventions focusing on how to improve coping strategies may reduce caregiver stress and contribute to postponement of nursing home placement.
Perceptions of Cervical Cancer Threat, Benefits, and Barriers of Papanicolaou Smear Screening Programs for Women in Iran

ABSTRACT Objectives: The main purpose was to assess associations between HBM variables and participation in cervical cancer screening programs in a sample of Iranian women. Methods: A total of 333 married women of childbearing age were recruited with cluster sampling. The study was conducted from spring 2002 to spring 2003 and a self-report questionnaire and structured interview were designed to measure the four HBM constructs and Iranian women's knowledge about Pap smear screening. Results: A total of 68.5% reported having undergone at least one Pap test. Women were more likely to participate in Pap smears when they had access to knowledge about cervical cancer and screening programs. Furthermore, the perceived benefit and barrier variables of the Health belief model were two factors related to participation in Pap smear testing. Conclusions: Health care professionals must provide women with more information about cervical cancer and the benefits of participating in cervical cancer screening programs.