Analyzing Dynamical Disorder for Charge Transport in Organic Semiconductors via Machine Learning

Organic semiconductors are indispensable for today’s display technologies in the form of organic light-emitting diodes (OLEDs) and further optoelectronic applications. However, organic materials do not reach the same charge carrier mobility as inorganic semiconductors, limiting the efficiency of devices. To find or even design new organic semiconductors with higher charge carrier mobility, computational approaches, in particular multiscale models, are becoming increasingly important. However, such models are computationally very costly, especially when large systems and long timescales are required, which is the case to compute static and dynamic energy disorder, i.e., the dominant factor to determine charge transport. Here, we overcome this drawback by integrating machine learning models into multiscale simulations. This allows us to obtain unprecedented insight into relevant microscopic materials properties, in particular static and dynamic disorder contributions for a series of application-relevant molecules. We find that static disorder and thus the distribution of shallow traps are highly asymmetrical for many materials, impacting widely considered Gaussian disorder models. We furthermore analyze characteristic energy level fluctuation times and compare them to typical hopping rates to evaluate the importance of dynamic disorder for charge transport. We hope that our findings will significantly improve the accuracy of computational methods used to predict application-relevant materials properties of organic semiconductors and thus make these methods applicable for virtual materials design

Analyzing dynamical disorder for charge transport in organic semiconductors via machine learning

Organic semiconductors are indispensable for today's display technologies in form of organic light emitting diodes (OLEDs) and further optoelectronic applications. However, organic materials do not reach the same charge carrier mobility as inorganic semiconductors, limiting the efficiency of devices. To find or even design new organic semiconductors with higher charge carrier mobility, computational approaches, in particular multiscale models, are becoming increasingly important. However, such models are computationally very costly, especially when large systems and long time scales are required, which is the case to compute static and dynamic energy disorder, i.e. dominant factor to determine charge transport. Here we overcome this drawback by integrating machine learning models into multiscale simulations. This allows us to obtain unprecedented insight into relevant microscopic materials properties, in particular static and dynamic disorder contributions for a series of application-relevant molecules. We find that static disorder and thus the distribution of shallow traps is highly asymmetrical for many materials, impacting widely considered Gaussian disorder models. We furthermore analyse characteristic energy level fluctuation times and compare them to typical hopping rates to evaluate the importance of dynamic disorder for charge transport. We hope that our findings will significantly improve the accuracy of computational methods used to predict application relevant materials properties of organic semiconductors, and thus make these methods applicable for virtual materials design

Time Series Continuous Modeling for Imputation and Forecasting with Implicit Neural Representations

We introduce a novel modeling approach for time series imputation and forecasting, tailored to address the challenges often encountered in real-world data, such as irregular samples, missing data, or unaligned measurements from multiple sensors. Our method relies on a continuous-time-dependent model of the series' evolution dynamics. It leverages adaptations of conditional, implicit neural representations for sequential data. A modulation mechanism, driven by a meta-learning algorithm, allows adaptation to unseen samples and extrapolation beyond observed time-windows for long-term predictions. The model provides a highly flexible and unified framework for imputation and forecasting tasks across a wide range of challenging scenarios. It achieves state-of-the-art performance on classical benchmarks and outperforms alternative time-continuous models

Importance d’un schéma de vaccination a deux doses dans la lutte contre la rougeole (cas de la zone de santé de Manika)

Objectif: Pour contribuer à la réduction de la morbide mortalité liée à la rougeole, nous avons menés une étude descriptive transversale, au cours de laquelle nous avons analysés,, l’importance de la seconde vaccination, face aux résurgences de l’épidémie de la rougeole dans la zone de santé de Manika, district de Kolwezi, province du Katanga, en République démocratique du Congo, au cours de la période allant de janvier à décembre 2011 .Méthodologie et résultats: ressort de notre travail que, parmi les enfants enquêtés, 46,8% étaient non vaccinés, et parmi eux 38% avaient présenté la rougeole, l’Odds ratio est de 6,34 avec un intervalle de confiance de [4,26 ; 9,43], d’où une différence statistiquement significative qui se dégage entre la survenue de la rougeole et le statut de zéro dose. Pour ce qui est des enfants qui ont reçu une dose, on déduit que la vaccination est un facteur (OR = 0,45 IC95% [0,16 ; 0,87]). Quant aux enfants ayant reçu deux doses, il est a noté que la deuxième vaccination était apparu comme un facteur protecteur, offrant à l’enfant moins de chance à développer la rougeole (OR = 0,03 IC95% [0,01 ; 0,07]).Conclusion et application des résultats: Actuellement, il est admis qu’avec une seule dose de vaccination contre la rougeole, il est peu probable de réduire la morbidité et la mortalité liée à la rougeole dans la Zone de santé Manika, car environ 20,3% d’enfants vaccinés d’une seule dose, ont développé la maladie. La seconde vaccination des enfants demeure un enjeu majeur pour un meilleur contrôle, et élimination de la rougeole, dans notre pays.Mots clés: épidémie rougeole Manika : importance du schéma à deux dosesEnglish AbstractObjective: To contribute to the reduction of the morbid mortality related to measles, we conducted a descriptive transversal study, during which we analyzed, the importance of the second vaccination, in the face of resurgences of the measles epidemic in the Manika Health Zone, Kolwezi District, Katanga Province, Democratic Republic of the Congo, during the period January to December 2011.Methodology and results: Our work shows that among the children surveyed, 46.8% were unvaccinated, and among them 38% had measles, the odds ratio was 6.34 with a confidence interval of [4.26; 9.43], resulting in a statistically significant difference between the occurrence of measles and zero dose status. For children who received a dose, it is deduced that vaccination is a protective factor because its odds ratio is 0.45 (> to 1) and its confidence interval is [0.16; 0.87]. As for the children who received two doses, it was noted that the second vaccination is also a protective factor, giving the child less chance to develop measles, because his odds ratio was 0.03 with a confidence interval of [0.01; 0.07].Conclusion and application of results: Currently, it is recognized that with a single measles vaccination dose, it is unlikely to reduce measles-related morbidity and mortality in the Manika Health Zone, as about 20.3% of children vaccinated against measles are affected by measles. A single dose, developed the disease. The second vaccination of children remains a major challenge for better control and elimination of measles in our countryKeywords: Manika measles epidemic: importance of the two-dose regim

Strength-based Video-feedback to improve maternal sensitivity in mother-infant dyads with maternal depressive symptoms: Study protocol for a randomized controlled feasibility trial // Video-retroalimentación Focalizado en los Recursos para mejorar la sensibilidad en díadas madre-infante con síntomas depresivos: protocolo de un ensayo clínico aleatorizado piloto

Introduction Maternal sensitivity and mentalization are fundamental for children’s mental health development. These skills have been negatively associated with maternal postpartum depressive symptomatology. Moreover, its prevalence increases in low socioeconomic and psychosocial risk contexts, where the access to treatment is scarce. Even though Attachment Based Interventios, such as Video-Feedback has been internationally recognized as an effective intervention. Its cost, as well as the need for language translation and cultural adaptation makes it difficult to implement in Latinamerican countries. Aim The present study aims to assess the feasibility and acceptability of an online Video-Feedback intervention informed n mentalization aimed at mother-infant dyads with depressive symptomatology who attend Chilean public health centers. Method This is a pilot randomized clinical trial with two groups of 60 mother-infant dyads between 4 and 12 months of age. Participants will be randomly assigned to control and experimental groups in a 1:1 ratio. Even though both groups will receive usual treatment, the experimental group will also receive the present video-intervention. At the end of the study, feasibility will be assessed based on focus groups aimed at interveners and quantitative outcomes such as recruitment rate, questionnaire completion rate and intervention completeness. Acceptability will be assessed from in-depth interviews with participants. In addition, effect sizes of primary and secondary outcomes will be calculated. Expected results Results are expected to generate parameters to design a larger-scale clinical trial and to preliminary assess the effect of the reported mentalization-informed intervention on maternal sensitivity. Additionally, it seeks to contribute with a mental health intervention for low-income mother-infant dyads, which can be implemented remotely, at a low cost, and that would be suitable for implementation at a mental health care system policy. The protocol of this trial’s design was registered at Clinical Trials (NCT04748731)

Relations between Au / Sn-W mineralizations and late hercynian granite: Preliminary results from the Schistose Domain of Galicia-Trás-os-Montes Zone, Spain

International audienceAu and W-Sn mineralization of the Schistose Domain of Galicia-Trás-os-Montes are spatially related to late hercynian granites. The Bruès (Au) and the Mina Soriana W-(Sn) deposits are studied. Both show some similarities and are assumed to form in the same tectonic and metamorphic context, on top of the granites. The role of the granite as a source for mineralizing fluids and rheological control for vein emplacement is re-adressed and discussed

β-catenin tyrosine 654 phosphorylation increases Wnt signalling and intestinal tumorigenesis

Objective: Deregulation of the Wnt signalling pathway by mutations in the Apc or β-catenin genes underlies colorectal carcinogenesis. As a result, β-catenin stabilises, translocates t

Mapping Cosmic Dawn and Reionization: Challenges and Synergies

Cosmic dawn and the Epoch of Reionization (EoR) are among the least explored observational eras in cosmology: a time at which the first galaxies and supermassive black holes formed and reionized the cold, neutral Universe of the post-recombination era. With current instruments, only a handful of the brightest galaxies and quasars from that time are detectable as individual objects, due to their extreme distances. Fortunately, a multitude of multi-wavelength intensity mapping measurements, ranging from the redshifted 21 cm background in the radio to the unresolved X-ray background, contain a plethora of synergistic information about this elusive era. The coming decade will likely see direct detections of inhomogenous reionization with CMB and 21 cm observations, and a slew of other probes covering overlapping areas and complementary physical processes will provide crucial additional information and cross-validation. To maximize scientific discovery and return on investment, coordinated survey planning and joint data analysis should be a high priority, closely coupled to computational models and theoretical predictions.Comment: 5 pages, 1 figure, submitted to the Astro2020 Decadal Survey Science White Paper cal

Quantime - A miniature cesium atomic clock using CPT technique for telecom application

The Quantime project aims at developing a miniature atomic clock suited for the telecom market, requiring a wide operating temperature range (from -40 to +85°C), and a low production cost. The CPT (Coherent Population Trapping) technique for atomic interrogation is used for miniaturization and low power consumption. In the first phase of the project, the clock architecture was chosen, and the main sub-systems were developed. A clock breadboarding demonstrator was assembled and the measured Allan deviation of 1E-11 at 400 s confirms the operation of all the sub-systems