PurposeDigital service innovation (DSI) is a type of technological innovation that is recognized in practice in the innovation structure of companies. Given the breadth of digital technologies that ...enable digital services and the variety of these services, analysis is needed to discern the nature of these services, as well as the process that culminates in co-innovation. The literature on DSI is fragmented and spread across multiple research areas. This fragmentation impedes conceptualization of the elements that constitute DSI. This paper describes the nature of DSI through the process and elements of initiation, adoption and routinization of DSI in the context of digital service platforms (DSPs).Design/methodology/approachThis paper presents a single exploratory case study of a provider of a leading digital solution in customer relations. The data analysis is based on abductive reasoning.FindingsThe paper conceptualizes the nature of DSI and describes the process and elements of DSI (phases, actors, functions and interactions). It contributes to building a common language for DSI research in service management. The analysis shows that DSI in DSPs is synonymous with co-innovation. This paper offers insight into how co-innovation occurs, using hybrid agile methodologies with the coordination of multiple actors and multilateral interactions.Originality/valueThe originality and value of the study reside in its conceptualization and analysis of what is meant by DSI. The components of the service and the technological requirements for not only provision but also ideation and development appear to be inseparable. The study unveils the mechanisms that turn a digital service solution into a co-innovative proposal. This knowledge can facilitate scalability in digital services.
Endocannabinoids play central roles in retrograde signaling at a wide variety of synapses throughout the CNS. Although several molecular components of the endocannabinoid system have been identified ...recently, their precise location and contribution to retrograde synaptic signaling is essentially unknown. Here we show, by using two independent riboprobes, that principal cell populations of the hippocampus express high levels of diacylglycerol lipase alpha (DGL-alpha), the enzyme involved in generation of the endocannabinoid 2-arachidonoyl-glycerol (2-AG). Immunostaining with two independent antibodies against DGL-alpha revealed that this lipase was concentrated in heads of dendritic spines throughout the hippocampal formation. Furthermore, quantification of high-resolution immunoelectron microscopic data showed that this enzyme was highly compartmentalized into a wide perisynaptic annulus around the postsynaptic density of axospinous contacts but did not occur intrasynaptically. On the opposite side of the synapse, the axon terminals forming these excitatory contacts were found to be equipped with presynaptic CB1 cannabinoid receptors. This precise anatomical positioning suggests that 2-AG produced by DGL-alpha on spine heads may be involved in retrograde synaptic signaling at glutamatergic synapses, whereas CB1 receptors located on the afferent terminals are in an ideal position to bind 2-AG and thereby adjust presynaptic glutamate release as a function of postsynaptic activity. We propose that this molecular composition of the endocannabinoid system may be a general feature of most glutamatergic synapses throughout the brain and may contribute to homosynaptic plasticity of excitatory synapses and to heterosynaptic plasticity between excitatory and inhibitory contacts.
In medical imaging, quantitative measurements have shown promise in identifying diseases by classifying normal versus pathological parameters from tissues. The support vector machine (SVM) has shown ...promise as a supervised classification algorithm and has been widely used. However, the classification results typically identify a category of abnormal tissues but do not necessarily differentiate progressive stages of a disease. Moreover, the classification result is typically provided independently as a supplement to medical images, which contributes to an overload of information sources in the clinic. Hence, we propose a new imaging method utilizing the SVM to integrate classification results into medical images. This framework is called disease-specific imaging (DSI) that produces a color overlaid highlight on B-mode ultrasound images indicating the type, location, and severity of pathology from different conditions. In this article, the SVM training was performed to construct hyperplanes that can differentiate normal, fibrosis, steatosis, and pancreatic ductal adenocarcinoma (PDAC) metastases in livers based on ultrasound echoes. Also, cluster centroids for specific diseases define unique disease axes, and the inner product between measured features and any disease axis selected by the SVM quantifies the disease progression. The features were measured from 2794 ultrasound frames using the H-scan analysis, attenuation estimation, and B-mode image analysis. The performance of our proposed DSI method was evaluated for a preclinical model of steatosis (<inline-formula> <tex-math notation="LaTeX">{n} =400 </tex-math></inline-formula> frames). The contribution of each feature was assessed, and the results were compared with ground truth from histology. Moreover, the images generated by our DSI were compared with earlier imaging methods of B-mode, H-scan, and histology. The comparisons demonstrate that DSI images yield higher sensitivity to monitor progressive steatosis than B-mode and H-scan and provide a comparable performance with the histology. For the parameter comparison, DSI and H-scan resulted in similar correlation with histology (<inline-formula> <tex-math notation="LaTeX">{r}_{s} =0.83 </tex-math></inline-formula>) but higher than attenuation (<inline-formula> <tex-math notation="LaTeX">{r}_{s} =0.73 </tex-math></inline-formula>) and B-mode (<inline-formula> <tex-math notation="LaTeX">{r}_{s} =0.47 </tex-math></inline-formula>). Therefore, we conclude that DSI utilizing the SVM applied to steatosis can visually represent the classification results with color highlighting, which can simplify the interpretation of classification compared to the traditional SVM result. We expect that the proposed DSI can be used for any medical imaging modality that can estimate multiple quantitative parameters at high resolution.
•Exogenous cannabinoid agonist decreases inhibitory inputs from all aPC layers.•DSI is present in the three layers of aPC inhibitory synapses.•iLTD and CCK interneurons are restricted to inhibitory ...synapses located in layer II and III of the aPC.•CCK interneurons might be necessary for iLTD but not for DSI.
In the olfactory system, the endocannabinoid system (ECS) regulates sensory perception and memory. A major structure involved in these processes is the anterior piriform cortex (aPC), but the impact of ECS signaling in aPC circuitry is still scantly characterized. Using ex vivo patch clamp experiments in mice and neuroanatomical approaches, we show that the two major forms of ECS-dependent synaptic plasticity, namely depolarization-dependent suppression of inhibition (DSI) and long-term depression of inhibitory transmission (iLTD) are present in the aPC. Interestingly, iLTD expression depends on layer localization of the inhibitory neurons associated with the expression of the neuropeptide cholecystokinin. Conversely, the decrease of inhibitory transmission induced by exogenous cannabinoid agonists or DSI do not seem to be impacted by these factors. Altogether, these results indicate that CB1 receptors exert an anatomically specific and differential control of inhibitory plasticity in the aPC, likely involved in spatiotemporal regulation of olfactory processes.
We have developed new Gen. 6 exposure tools “MPAsp‐E903T” for 1.2 μm L&S and 1.8 μm hole patterning. Results of various performance tests show that the new tool meets all requirements for stable mass ...production of high quality display panels. Even higher resolution can be obtained with new techniques.
Mobile displays are overcoming bandwidth hurdles of low cost chip‐on‐glass DDIC manufacturing. Using VESA DSC and MIPI C‐PHY achieves over 6x of additional throughput compared to traditional MIPI ...D‐PHY interfaces and is driving the next generation of mobile devices, VR/AR headsets and immersive automotive consoles providing higher resolution and frame rate at lower cost and power. Using FPGA/ASSP bridging devices with VESA DSC and MIPI C‐PHY support overcomes the adoption challenges of D‐PHY and eDP based SoCs along with cabling interfaces such HDMI, DP and A‐PHY will be discussed.
•Drivers assessment of own driving skills is reflected in their aberrant driving.•Heterogeneity across the driver population.•Sub-groups of drivers that differ in potential danger in traffic.•Improve ...attitudes towards safety.
The Driver Behavior Questionnaire and the Driver Skill Inventory are two of the most frequently used measures of self-reported driving style and driving skill. The motivation behind the present study was to identify sub-groups of drivers that potentially act dangerously in traffic (as measured by frequency of aberrant driving behaviors and level of driving skills), as well as to test whether the sub-groups differ in characteristics such as age, gender, annual mileage and accident involvement. Furthermore, the joint analysis of the two instruments was used to test drivers’ assessment of their own self-reported driving skills and whether the reported skill level was reflected in the reported aberrant driving behaviors. 3908 drivers aged 18–84 participated in the survey. K-means cluster analysis revealed four distinct sub-groups that differed in driving skills and frequency of aberrant driving behavior. The sub-groups also differed in individual characteristics and driving related factors such as annual mileage, accident frequency and number of tickets and fines. The differences between the sub-groups suggest heterogeneity across the population, and since two of the sub-groups reported higher frequency of driving aberrations and lower skill level, they seem more unsafe than the two others. The results suggest that drivers’ assessment of their driving skills is reflected in their aberrant driving behaviors, as drivers who report low levels of driving skills, also report high frequency of aberrant driving behaviors, and vice versa. The present findings highlight the need to look into driver’s attitudes towards safety, and to devise differential interventions targeting specific problematic groups of the population in the attempt to improve road safety nationwide.
Purpose
Lymph node metastasis (LNM) is a crucial factor that determines the prognosis of T1 colorectal cancer (CRC) patients. We aimed to develop a practical prediction model for LNM in T1 CRC.
...Methods
We conducted a retrospective analysis of data from 825 patients with T1 CRC who underwent radical resection at a single center in China. All enrolled patients were randomly divided into a training set and a validation set at a ratio of 7:3 using R software. Risk factors for LNM were identified through multivariate logistic regression analyses. Subsequently, a prediction model was developed using the selected variables.
Results
The lymph node metastasis (LNM) rate was 10.1% in the training cohort and 9.3% in the validation cohort. In the training set, risk factors for LNM in T1 CRC were identified, including depressed endoscopic gross appearance, sex, submucosal invasion combined with tumor grade (DSI-TG), lymphovascular invasion (LVI), and tumor budding. LVI emerged as the most potent predictor for LNM. The prediction model based on these factors exhibited good discrimination ability in the validation sets (AUC: 79.3%). Compared to current guidelines, the model could potentially reduce over-surgery by 48.9%. Interestingly, we observed that sex had a differential impact on LNM between early-onset and late-onset CRC patients.
Conclusions
We developed a clinical prediction model for LNM in T1 CRC using five factors that are easily accessible in clinical practice. The model has better predictive performance and practicality than the current guidelines and can assist clinicians in making treatment decisions for T1 CRC patients.
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