Default Settings Research Articles

An investigation of optimum control of injection timing/injection pressure for a multicylinder common rail direct injection engine fueled with AB20 blend

A multicylinder turbocharged common rail direct injection engine was tested at part load (62.4 Nm) and high load (156 Nm) to determine the optimum combination of injection pressure (IP) and injection timing (IT) for AB20 blended fuel. IP and IT were varied from default settings, that is, 9.2° before top dead center (BTDC), 45 MPa at part load; 9.8° BTDC, 95 MPa at high load, as specified in the calibration map of the engine. As a result of the experimental results, brake thermal efficiency (BTE) increased up to 5.36% when IP increased from 35 MPa to 45 MPa and 0.72% when IP increased from 45 MPa to 55 MPa under the part load condition. At high load, the maximum BTE of 38.22% was attained at 105 MPa IP and 9.8° BTDC IT. At this condition, nitrogen oxide (NOx) emission was noted as 1353 ppm, which is 12.28% higher than the NOx noted for diesel fuel at the default IP and IT conditions. When IP increases from 35 to 55 MPa at part load and 85–105 MPa at high load, cylinder pressure, heat release rate, and rate of pressure rise increase at all tested ITs. At high load, the condition of retarded IT (8.8° BTDC) and default IP (95 MPa) shows (a) 2.35% higher BTE and (b) almost similar NOx and improved HC, CO, and smoke emissions for the AB20 blend. Moreover, at the same experimental conditions, premixed heat release for the AB20 blend was noted to be 70.16 J/Deg./C.A, with heat release rate peak at 6° ATDC.

Development of Custom Sound® Pro software utilising big data and its clinical evaluation

Objectives To inform and optimise a cochlear implant (CI) fitting software design through an analysis of big data to define array-specific comfort (C) level profiles, frequently-used MAP parameters, and the minimum number of Neural Response Telemetry thresholds (tNRT) needed to create an accurate profile. To evaluate the software’s ease of use and completion time for AutoNRT®s. Design MAPs analysis. Clinical study evaluating software use in creating MAPs, addressing sound-quality issues and setting patient goals. Study sample MAPs (N = 39,885); CI recipients (N = 47) and clinicians (N = 19). Results Distinct C-level profiles were observed for lateral-wall, contour, and slim-modiolar electrode arrays. Default settings were used for most MAP parameters (13/16) except for Pulse Width, Rate, and Maxima. Nine tNRT measurements were required for an accurate C-level profile. Measurement-time of nine tNRTs via the new algorithm was comparable to five tNRTs using the previous algorithm. Nearly all (99%) clinical tasks were completed by clinicians with the first use of the software. Most CI recipients (79.5%) rated goal-setting as valuable. Conclusion Custom Sound Pro fitting software developed based on big data analysis incorporates a guided fitting workflow and expected fitting ranges. It helps to improve clinical efficiency, is easy to use and supports patient-centred care.

Evaluating Cognitive Privacy Heuristics that Influence Facebook Users Data Disclosure

Privacy protection has been a challenging issue in online social networks, such as Facebook, Instagram, and Snapchat. The General Data Protection Regulation (GDPR), which protects the privacy and security of individuals, entered into force on May, 2018. This regulation intends to enhance individuals’ control and rights over their own data, guided by lawfulness, loyalty, transparency, adequacy, purpose limitation, need, or minimization. However, despite regulatory efforts to protect personal data online, users are prone to consent to disclose more personal information than they intend and tend to reveal more than they know. With this in mind, the main goal of this study is to carry out a heuristic evaluation of the online social network Facebook to identify the factors that influence the disclosure of user information and verify informed consent. For this, we carried out a survey of cognitive heuristics that influence individuals’ decisions to protect or renounce their privacy. Then, using these heuristics, we conducted a heuristic evaluation on Facebook to explore a significant presence of cue triggers for a specific cognitive heuristic that helps users make their decisions. We found on Facebook a notable amount of heuristics that increase information disclosure, such as modality and narrative. However, the intrusiveness heuristic was also detected, violating the Privacy by Design (PbD) principle of "Privacy as the Default Setting". Accordingly, understanding the number and diversity of suggestions (heuristics) to which users are susceptible allows the creation of explicit guidelines addressing privacy concerns.

Low-dose fluoroscopy technique drastically decreases patient radiation exposure during percutaneous nephrolithotomy.

Fluoroscopy is essential in percutaneous nephrolithotomy (PCNL) but exposes patients and operating room staff to radiation. We investigated whether a low-dose (LD) protocol could reduce radiation exposure during fluoroscopy-guided access without compromising clinical outcomes. Patients undergoing PCNL with fluoroscopy-guided access at a tertiary care stone center between January 2019 and July 2021 were identified. Prior to September 3, 2020, the Philips Veradius C-arm's default settings were used: standard per-frame dose, 15 pulses per second (PPS) frame rate. After this date, a low-dose protocol was used: reduced per-frame dose, reduced frame rate of 8 PPS for needle puncture and 4 PPS for all other steps. Clinical and radiographical data were retrospectively collected. The primary outcome was cumulative radiation dose. Secondary outcomes were stone-free status (SFS; defined as no fragments ≥ 2mm) and complications. Multivariate regression analysis was performed. 100 patients were identified; 31 were in the LD group. The LD cohort was exposed to a significantly lower mean cumulative radiation dose of 11.68mGy compared to 48.88mGy (p < 0.0001). There were no differences in operative time, fluoroscopy time, stone burden, SFS, or complications. In a multivariable regression model adjusting for several variables, LD protocol was associated with lower radiation dose while skin-to-calyx-distance (STCD) was positively associated with cumulative radiation dose. Low-dose fluoroscopy and decreased frame rate during PCNL decreased radiation exposure fourfold without affecting SFS or complication rates.

Quality of Information for Post-Prostatectomy Incontinence Treatments on YouTube

ObjectiveTo assess the quality of information on YouTube regarding post-prostatectomy incontinence treatments. The 2019 American Urological Association(AUA)/(SUFU) Society of Urodynamics, Female Pelvic Medicine & Urogenital Reconstruction guidelines recommend the placement of a male sling or artificial urinary sphincter. Patient education is essential for appropriate expectations and patient satisfaction. MethodsThe top 100 most relevant (default setting) YouTube videos searched with terms “post-prostatectomy incontinence” and “male stress incontinence” were assessed using the validated DISCERN instrument, Patient Education Materials Assessment Tool for Audiovisual Materials, and a misinformation Likert Scale. Videos with poor video/audio quality, duplicates, and non-English videos were excluded. Four independent raters were randomly assigned such that each video had 2 raters. Data was analyzed using multivariate linear regression, and inter-rater reliability was measured using Cohen's kappa. ResultsThe median DISCERN score was 2.5 with 71% of videos scoring <=3. The median PEMAT Actionability and Understandability scores were 64.6 (range 0-100) and 79.9 (range 52-100), respectively. The median misinformation Likert score was 1 range (1-4). Less than half of the videos discussed realistic treatment outcomes or the risks (39% and 24%, respectively). PEMAT Actionability and risk discussion significantly predicted average DISCERN score (p < .001). There were no significant disagreements between raters. ConclusionOur study shows most videos on post-prostatectomy incontinence had moderate to low quality information and were published by medical professionals. The majority did not sufficiently discuss realistic outcomes and risks, which are hallmarks of informed decision making. This provides an opportunity for the urologic community to create educational materials that adequately supplement shared-decision making for patients treated for post-prostatectomy incontinence.

Retentive design of a small surgical guide for implant surgery: An in-vitro study

ObjectivesInstability of the surgical guide is an overlooked factor that can result in a difference between the planned and the actual positions of an implant. Our aim was to compare the stability of the retentive surgical guide (RSG) with a conventional surgical guide (CSG) in an in-vitro experiment. MethodsA platform to evaluate the stability of the surgical guide was designed using 3D-modelling software (Meshmixer 3.5, Autodesk). Imaging data from 15 patients with a single missing tooth were used to plan the virtual implant. Two surgical guides were designed (Blue Sky Plan 4.8, Blue Sky Bio) and 3D printed (Form2, Dental SG resin, Formlabs) for each case: the CSG with the default, predetermined software settings, and the RSG, designed on a dental model with a 0.1-mm undercut and altered production parameters (reduced guide-to-teeth offset of 0.07 mm, reduced guide thickness of 2.3 mm and a retentive clasp in a marginal area). The dental models were reproducibly secured on the testing platform using a digital force gauge, and the surgical guides were positioned. An increasing force of 0.1 N, 1 N, 2.5 N, and 5 N was sequentially applied from the buccal and the oral directions to the surgical guide via a drill handle. For each force, either the magnitude of the guide's displacement was captured with an intra-oral scanner (CEREC Omnicam AC, Dentsply Sirona; software version: SW 4.5.2) or the dislodgement of the guide was recorded. Scans were imported for analysis (GOM Inspect 2018, GOM GmbH), and library files of the surgical guides and implants were superimposed as a joined complex. The deviation of the implant's position was calculated from the displacement of the guide's position ResultsThree-way repeated measures using ANOVA revealed a more significant guide displacement and virtually projected implant deviation in the CSG group than the RSG group and with increasing force in all the deviation parameters. Both groups showed greater resistance to the displacement with the force applied from the oral direction than the buccal direction. The application of the force in the buccal direction resulted in guide dislodgements of 13% and 0% for the CSG and RSG, respectively. In the oral direction, the dislodgement rates were 33% and 7% for the CSG and RSG, respectively. ConclusionsWithin the limitations of this study, the retentive design increased the stability of the surgical guide and, consequently, the accuracy of the virtually projected implants in comparison to the conventional surgical guide designed using the default settings. Clinical trials are needed to confirm its advantages in clinical use. Clinical SignificanceWith a simple modification to the design, the surgical guide retention provided greater stability, with smaller deviations under loading; this resulted in improved implant precision parameters without requiring additional materials or software. Further studies are needed to assess the clinical feasibility of this surgical guide with improved retention and function.

Composition of Mars's Dayside Ionosphere Under Changing Solar Irradiance Conditions

AbstractThe response of the Mars ionosphere to changes in solar irradiance is an important aspect of how conditions on Mars are shaped by our dynamic Sun. Changes in the composition of ionospheric plasma with changes in solar irradiance will affect how the ionosphere mediates the interaction of the neutral atmosphere with the surrounding space environment. Here we use MAVEN ion and neutral density measurements acquired at low (Deep Dip 8) and high (Deep Dip 2) solar irradiance conditions to determine how ion and neutral densities change when the ionizing solar irradiance doubles. We find that the neutral composition does not change significantly when examined at fixed total neutral number density. Furthermore, we find that and O+ densities increase by a factor of 2, but densities increase by a factor of 1.5. The relative abundance of decreases as solar irradiance increases. These results are explained by straightforward theoretical considerations of changes in ion production and loss rates. However, a photochemical model fails to reproduce these results with its default set of inputs. Consistent with previous modeling efforts, densities are over‐predicted. Acceptable model–data agreement requires significant adjustments to important model inputs, such as reduction in irradiance by 15%, reduction in CO2 density by a factor of 2, and increase in O density by a factor of 2. These large adjustments are suggestive of the need for improvements to the state of Mars ionosphere models based on MAVEN inputs rather than issues with the underlying data.

Zurich Trading Simulator (ZTS) — A dynamic trading experimental tool for oTree

Recent literature on the intersection of economics, finance and psychology indicates the benefits of simulated experience in tools measuring decision making. Here, we present the Zurich Trading Simulator (ZTS) first used by Andraszewicz et al. (2022) to test the impact of upward social comparison on trading activity. ZTS is a free application for oTree designed to create dynamic investment experiments suitable for measuring trading activity and risk taking. The software is ready-to-use applying the default settings. It can also be freely adapted in the source code depending on the experimenter’s needs. Price paths developed for experiments with the ZTS are freely available online. We also outline recommendations and possibilities for future studies and extensions.

Radiologist’s Role in Artificial Intelligence Era

Artificial intelligence (AI) in radiology is recently a rapidly growing subject. Much literature about AI in radiology has been launched within 5 years, as well as commercial AI companies. This phenomenon makes some old radiologists feel worried about losing their jobs, and junior doctors hesitate to choose radiology as a specialty. Currently, implementations of proprietary AIs in clinical practice are limited, with a default setting for a convenient human overwrite. The AIs in clinical imaging largely remain either investigational as part of clinical/pre-clinical trials or being developed for commercialized purposes. Radiologists have an important role in all AI processes from the beginning to the end and vital in training the machine, as well as to validate its added benefit for outcome prediction/prognostication. This article will discuss the importance for radiologists to develop, implement, and monitor AI in clinical imaging, together with some ethical considerations. We would like to encourage radiologists to use AI as an adjunct tool, to save time and have better performance.

Quality and accuracy of gastric cancer related videos in social media videos platforms

BackgroundGastric cancer is a major public health problem worldwide. Social media has affected public’s daily lives in ways no one ever thought possible. Both TikoTok and its Chinese version Douyin are the most popular short video posting platform. This study aimed to evaluate the quality, accuracy, and completeness of videos for gastric cancer on TikTok and Douyin.MethodsThe terms “gastric cancer” was searched on TikTok in both English and Japanese, and on Douyin in Chinese. The first 100 videos in three languages (website’s default setting) were checked. QUality Evaluation Scoring Tool (QUEST) and DISCERN as the instrument for assessing the quality of the information in each video. Content was analysed under six categories (aetiology, anatomy, symptoms, preventions, treatments, and prognosis). The educational value and completeness were evaluated with a checklist developed by the researchers.ResultsA total of 78 videos in English, 63 in Japanese, and 99 in Chinese were analyzed. The types of sources were as follows: 6.4% in English, 4.8% in Japanese, and 57.6% in Chinese for health professionals; 93.6% in English, 95.2% in Japanese, and 3.0% in Chinese for private users; none in English and Japanese, but 39.4% in Chinese for other sources. In all, 20.5% in English, 17.5% in Japanese, and 93.9% in Chinese of videos had useful information about gastric cancer. Among the useful videos, the videos published in Chinese had the highest QUEST(p < 0.05) and DISCERN scores(p < 0.05), followed by those published in Japanese. Among the educational videos, prognosis in English (37.5%), symptoms in Japanese (54.5%), and prevention in Chinese (47.3%) were the most frequently covered topic.ConclusionsTikTok in English and Japanese might not fully meet the gastric cancer information needs of public, but Douyin in Chinese was the opposite.

Gli Archivi Digitali e l'Antropologia Virtuale. Ricostruzione 3D di un cranio umano mediante la moderna tecnica della Fotogrammetria

Modern digital archives mainly thanks to recent developments in 3D modelling by TAC, Laser Scanner and Photogrammetry are highy useful for easily storing and exchanging large amounts of data for both qualitative and quantitative studies. Photogrammetry is a versatile and inexpensive technique that starting from one or more sets of 2D digital images allows for high-resolution 3D models to be built. The protocol reported here allows users with different backgrounds to easily and quickly built accurate models of human skulls using minimal and inexpensive equipment by simply modifying only some of the default settings of the Agisoft-Metashape software. The photo acquisition and the workflow of the software (fundamental steps of photogrammetry) are treated separately to provide a systematic method. The main advantages of this method are: the low number of images needed for a total coverage of the skull, the processing speed and the model accuracy by using only four markers positioned on the skull, as a reference to join the two sets of photos.

Assessment of the z∼ Time‐Filtered Arbitrary Lagrangian‐Eulerian Coordinate in a Global Eddy‐Permitting Ocean Model

AbstractA recognized deficiency of ocean models with a constant‐depth vertical coordinate is for truncation errors in the vertical advection scheme to result in spurious numerical mixing of tracers, which can be substantially stronger than that prescribed by the model's mixing scheme. The z∼ vertical coordinate allows vertical levels to displace in a Lagrangian fashion on time scales shorter than a few days, but reverts to fixed levels on longer timescales, and is intended to reduce numerical mixing from transient vertical motions such as internal waves and tides. An assessment of z∼ in a 1/4° global implementation of the Nucleus for European Modeling of the Ocean model is presented. It is shown that, in the presence of near‐inertial gravity waves in the North Atlantic, z∼ significantly reduces Eulerian vertical velocities with respect to those in a simulation with the default z* vertical coordinate; that the vertical coordinate approaches an isopycnal, or adiabatic, surface on short timescales; and that both tendencies are enhanced when the z∼ timescale parameters are lengthened with respect to the default settings. Analysis based on density transformation rates shows that numerical mixing is consistently reduced by of order 10% as the z∼ timescales are lengthened. The realism of the model simulation with different timescale parameters is assessed in the global domain, and it is shown that drifts in temperature and salinity, and the spindown in z* of the Antarctic Circumpolar Current, are reduced with z∼, without incurring significant drawbacks in other metrics such as the strength of the overturning circulation or sea ice cover.

Commissioning of an Artificial Intelligence (AI) Tool for Automated Head and Neck Intensity Modulated Radiation Therapy (IMRT) Treatment Planning

<h3>Purpose/Objective(s)</h3> Radiation treatment planning for head and neck (HN) cancers is challenging due to complex anatomy and labor-intensive inverse optimization. Recently we developed an Artificial Intelligence (AI) tool to generate IMRT plans for bilateral planning target volumes (PTVs) with promising results in both plan quality and efficiency. In this study, we describe the clinical commissioning process of this tool. <h3>Materials/Methods</h3> The AI tool was interfaced to the commercial treatment planning system (TPS) in the clinical environment. Essential information about patient anatomy was collected through vendor-supported scripts and transmitted to a designated workstation. This workstation was configured to perform AI core functions to avoid modification and burden on TPS workstations. The AI-generated optimal fluence maps were then imported into TPS for leaf sequencing, dose calculation, and optional fine-tuning. Planners could examine the plan dose and make further adjustments as clinically needed. The workflow and performance were evaluated and validated by experienced physicians and physicists specializing in HN treatment. Training, validation, and testing datasets of the AI tool consisted of 200, 16, and 15 retrospective cases. The commissioning dataset of the AI tool used 36 recent cases of various disease sites in HN. The commissioning AI plans were evaluated based on the corresponding clinical plans regarding critical dose-volume endpoints and 3D dose distributions. All plans were normalized to 44Gy covering 95% of PTV. Wilcoxon signed-rank tests were performed with a significance level of 0.05. <h3>Results</h3> The average AI planning time was 10 to 15min per case with default settings from start to finish. The dose distributions were comparable to clinical plans with slightly better dose conformity and slightly worse but acceptable dose heterogeneity and maximum dose. OAR sparing was comparable. <h3>Conclusion</h3> The AI planning tool for HN was commissioned in our clinic. The commissioning process demonstrates outstanding performance and robustness of the AI tool and provides sufficient validation and confidence for clinical use. Table. Statistics of dosimetric endpoints (median ± std) of the 36 commissioning cases.

An analytical pipeline to support robust research on the ecology, evolution, and function of floral volatiles

Research on floral volatiles has grown substantially in the last 20 years, which has generated insights into their diversity and prevalence. These studies have paved the way for new research that explores the evolutionary origins and ecological consequences of different types of variation in floral scent, including community-level, functional, and environmentally induced variation. However, to address these types of questions, novel approaches are needed that can handle large sample sizes, provide quality control measures, and make volatile research more transparent and accessible, particularly for scientists without prior experience in this field. Drawing upon a literature review and our own experiences, we present a set of best practices for next-generation research in floral scent. We outline methods for data collection (experimental designs, methods for conducting field collections, analytical chemistry, compound identification) and data analysis (statistical analysis, database integration) that will facilitate the generation and interpretation of quality data. For the intermediate step of data processing, we created the R package bouquet, which provides a data analysis pipeline. The package contains functions that enable users to convert chromatographic peak integrations to a filtered data table that can be used in subsequent statistical analyses. This package includes default settings for filtering out non-floral compounds, including background contamination, based on our best-practice guidelines, but functions and workflows can be easily customized as necessary. Next-generation research into the ecology and evolution of floral scent has the potential to generate broadly relevant insights into how complex traits evolve, their genomic architecture, and their consequences for ecological interactions. In order to fulfill this potential, the methodology of floral scent studies needs to become more transparent and reproducible. By outlining best practices throughout the lifecycle of a project, from experimental design to statistical analysis, and providing an R package that standardizes the data processing pipeline, we provide a resource for new and seasoned researchers in this field and in adjacent fields, where high-throughput and multi-dimensional datasets are common.

PASSIVE CONTACTLESS MONITORING OF NIGHTTIME RESPIRATORY SYMPTOMS AND ITS APPLICATION IN DISEASE MANAGEMENT

PASSIVE CONTACTLESS MONITORING OF NIGHTTIME RESPIRATORY SYMPTOMS AND ITS APPLICATION IN DISEASE MANAGEMENT

S1585 Combining Surgical Pyloroplasty and Gastric Electrical Stimulation in Gastroparetic Patients Is Superior to Pyloroplasty Alone: A Randomized Double Blind Placebo Control Trial

Introduction: Pathophysiology of gastroparesis (GP) is related to the depletion of interstitial cells of Cajal in the stomach and suspected pathology of the pyloric smooth muscle. Pyloroplasty (PP) accelerates gastric emptying (GE), while gastric electrical stimulation (GES) improves GP symptoms. Our double-blind randomized clinical trial investigated if combining surgical PP and GES is more effective than PP alone. Methods: Drug refractory GP patients underwent simultaneous surgical implantation of the GES system with PP. Scintigraphic GE was performed at baseline (all participants were delayed at 4 h with >10 % retention), and 3 months after surgery. Patients were randomized to 3 months of active GES stimulation (ON group with default setting of GES parameters), or no stimulation (OFF group). All patients then had GES turned ON for another 3 months. GP Cardinal Symptom Index (GCSI) with 6-points scale (0- none; 5-very severe) was recorded at baseline, 3 and 6 months after the surgery. Delta changes of GCSI and individual GP symptoms in ON and OFF groups at 3 and 6 months versus their baseline were calculated and compared using 2-way ANOVA followed by Tukey’s post-hoc analysis. Results: 30 GP patients (18F; mean age 46 (21-72); 6 idiopathics; 24 diabetics with mean duration of DM 24 years (3-50); mean duration of GP 5.6 (1-18) years met criteria for the trial. The mean baseline 4 h GE retention was not different in GES-OFF and -ON group. GE was significantly accelerated at 3 months in GES-OFF (46%) and GES-ON (62%) groups (*P< 0.05), and 39% patients normalized their 4h GE. Patients were randomized to GES-OFF or ON (15 patients per group). GP etiologies were similar in both groups. Baseline GCSI in GES-OFF (3.5±0.2) was comparable to GES-ON (3.7±0.2) group, and significantly improved in 3 months compared to baseline (P< 0.01) in both groups. However, mean GCSI score was significantly better (P< 0.05) in GES-ON than GES-OFF group (Figure). When GES was turned ON in GES-OFF group at 3 months their GSCI significantly improved at 6 months. The frequency of hospitalizations due to vomiting was significantly reduced in GES-ON vs OFF group (P=0.02). There were no post-surgical complications or technical dysfunctions recorded during this trial. Conclusion: Our randomized, double-blind study has revealed for the first time that combining GES with pyloroplasty is statistically more effective than PP alone in controlling GP symptoms and GE is similarly accelerated following PP in both groups.Figure 1.: Changes of Gastroparesis Cardinal Symptom Index (GCSI) at 3 and 6 months in GES-ON versus GES-OFF group compared to baseline. **P<0.01

A Comparative Study of RNA-Seq Aligners Reveals Novoalign’s Default Setting as an Optimal Setting for the Alignment of HeLa RNA-Seq Reads

The introduction of RNA-sequencing (RNA-Seq) technology into biological research has encouraged bioinformatics developers to build various analysis pipelines. The chosen bioinformatics pipeline mostly depends on the research goals and organisms of interest because a single pipeline may not be optimal for all cases. As the first step in most pipelines, alignment has become a crucial step that will affect the downstream analysis. Each alignment tool has its default and parameter settings to maximise the output. However, this poses great challenges for the researchers as they need to determine the alignment tool most compatible with the correct settings to analyse their samples accurately and efficiently. Therefore, in this study, the duplication of real data of the HeLa RNA-seq was used to evaluate the effects of data qualities on four commonly used RNA-Seq tools: HISAT2, Novoalign, TopHat and Subread. Furthermore, these data were also used to evaluate the optimal settings of each aligner for our sample. These tools’ performances, precision, recall, F-measure, false discovery rate, error tolerance, parameter stability, runtime and memory requirements were measured. Our results showed significant differences between the settings of each alignment tool tested. Subread and TopHat exhibited the best performance when using optimised parameters setting. In contrast, the most reliable performance was observed for HISAT2 and Novoalign when the default setting was used. Although HISAT2 was the fastest alignment tool, the highest accuracy was achieved using Novoalign with the default setting.

Behavioral economics interventions to improve medical decision-making

In medicine, a wide gap exists between the medical care that ought to be possible in the light of the current state of medical research and the care that is actually provided. Behavioral biases and noise are two major reasons for this. We present the findings of a selective literature review and illustrate how interventions based on behavioral economics can help physicians make better decisions and thereby improve treatment outcomes. A number of behavioral economics interventions, making use of, for example, default settings, active decision rules, social norms, and self-commitments, may improve physicians' clinical decision-making. Evidence on long-term effects is, however, mostly lacking. Despite their apparent potential, the application of behavioral economic interventions to improve medical decisionmaking is still in its infancy, particularly in Germany.

Mask-guided explicit feature modulation for multispectral pedestrian detection

Multi-task learning of object detection and box-level segmentation is commonly formulated as an implicit feature modulation method, which suffers lacking task interaction. In this paper, a novel explicit feature modulation solution with two different mask infusion methods is proposed. The first modulation method is semantic feature enhancement of backbone, which is achieved by a novel mask-guided mutual attention module (MMA). The proposed MMA module can explicitly guide the feature maps towards a more semantic informative direction for focalizing centrality of pedestrian, which can significantly improve the performance. The second modulation method is confidence score enhancement of detection head, which is benefited from our proposed mask-guided score fusion module (MSF). The proposed MSF module collects information from the classification, IOU, centerness feature map and the learned mask, which can discriminate false and true positives more effectively. It is qualitatively validated that the modulated feature maps in both backbone and detection head become more semantically meaningful and robust to scale and occlusion. Our method achieves a considerable gain over the state-of-the-arts on the KAIST, CVC14 and FLIR datasets. Besides, it runs at 22 FPS in default setting, making it favorable in many practical scenarios.

Multiclass classification of breast cancer histopathology images using multilevel features of deep convolutional neural network

Breast cancer is a common malignancy and a leading cause of cancer-related deaths in women worldwide. Its early diagnosis can significantly reduce the morbidity and mortality rates in women. To this end, histopathological diagnosis is usually followed as the gold standard approach. However, this process is tedious, labor-intensive, and may be subject to inter-reader variability. Accordingly, an automatic diagnostic system can assist to improve the quality of diagnosis. This paper presents a deep learning approach to automatically classify hematoxylin-eosin-stained breast cancer microscopy images into normal tissue, benign lesion, in situ carcinoma, and invasive carcinoma using our collected dataset. Our proposed model exploited six intermediate layers of the Xception (Extreme Inception) network to retrieve robust and abstract features from input images. First, we optimized the proposed model on the original (unnormalized) dataset using 5-fold cross-validation. Then, we investigated its performance on four normalized datasets resulting from Reinhard, Ruifrok, Macenko, and Vahadane stain normalization. For original images, our proposed framework yielded an accuracy of 98% along with a kappa score of 0.969. Also, it achieved an average AUC-ROC score of 0.998 as well as a mean AUC-PR value of 0.995. Specifically, for in situ carcinoma and invasive carcinoma, it offered sensitivity of 96% and 99%, respectively. For normalized images, the proposed architecture performed better for Makenko normalization compared to the other three techniques. In this case, the proposed model achieved an accuracy of 97.79% together with a kappa score of 0.965. Also, it attained an average AUC-ROC score of 0.997 and a mean AUC-PR value of 0.991. Especially, for in situ carcinoma and invasive carcinoma, it offered sensitivity of 96% and 99%, respectively. These results demonstrate that our proposed model outperformed the baseline AlexNet as well as state-of-the-art VGG16, VGG19, Inception-v3, and Xception models with their default settings. Furthermore, it can be inferred that although stain normalization techniques offered competitive performance, they could not surpass the results of the original dataset.