How to choose the frozen density in Frozen-Density Embedding Theory-based numerical simulations of local excitations?

According to Frozen-Density Embedding Theory, any observable evaluated for the embedded species is a functional of the frozen density (ρ B —the density associated with the environment). The environment-induced shifts in the energies of local excitations in organic chromophores embedded in hydrogen-bonded environments are analyzed. The excitation energies obtained for ρ B , which is derived from ground-state calculations for the whole environment applying medium quality basis sets (STO-DZP) or larger, vary in a narrow range (about 0.02eV which is at least one order of magnitude less than the magnitude of the shift). At the same time, the ground-state dipole moment of the environment varies significantly. The lack of correlation between the calculated shift and the dipole moment of the environment reflects the fact that, in Frozen-Density Embedding Theory, the partitioning of the total density is not unique. As a consequence, such concepts as "environment polarization” are not well defined within Frozen-Density Embedding Theory. Other strategies to generate ρ B (superposition of densities of atoms/molecules in the environment) are shown to be less robust for simulating excitation energy shifts for chromophores in environments comprising hydrogen-bonded molecules

Analisis Kebutuhan Parkir Pada Rumah Sakit Umum Kelas B Di Kota Semarang

Parking is one of the important elements of urban transportation, such, it has various long and short-term impacts on individuals, societies, and transportation systems. It affects to the transportation mode selection. People tend to drive private car when the representative parking area is available. This research is focused at the determination of the parameters that affect the use of parking area. The parameters are expected to be useful in estimating the parking area demand of the hospital class B in Semarang. There are six major parameters describing the parking slot, i.e.: accumulation, parking volume, total spaces available (capacity), parking turnover, peak time, duration of occupancy and occupancy. Three hospitals are selected as object of the study; there are RS Telogorejo, RS Elisabeth and RS dr Kariadi. The survey is carried out by direct investigation and questionnaire. Statistical analysis by using linear regression, logarithmic, quadratic, and exponential, indicated that the amount of bed used has a very high correlation with the parking demand. The next highest correlation is observed between medical specialist and parking demand. The average duration in RS Telogorejo is 15 – 30 minutes, RS Elisabeth is 30 minutes – 2 hours, and RS dr Kariadi is 15 – 30 minutes for car. For motorcycle, the average duration in RS Telogorejo is 30 minutes – 1 hour, RS Elisabeth is 30 minutes – 2 hours, and RS dr Kariadi is above 4 hours. From the study, it was found that the ratio between parking demand for vehicle and the number of bed being used is 0.89, meanwhile the ratio between parking demand for motorcycle and the number of bed being used is 1.29. Other alternative of parking facility like special parking building area is recommended to be considered for the hospital with limited area

Computing excited state properties of chromophores: a challenge for the computational chemist

This thesis introduces the basic principles of quantum chemistry, photochemistry and the computation of molecular properties. The results of original research are divided in three parts. Each part is constructed around a common feature of those projects, including a specific theoretical introduction. The first part approaches the problem of modelling solvent effects for property calculations. It approaches more specifically the use of continuum models and frozen density embedding methods. The second part highlights the problem of computing charge transfer excitations. It starts with a short presentation of the failure of linear-response time-dependent density functional theory and is followed by the results of two projects involving the computation of charge-transfer like excitations. Finally, the last part approaches the case where multireference methods are necessary to compute properly the features of different potential energy surfaces

Fluorescence quantum yield rationalized by the magnitude of the charge transfer in π-conjugated terpyridine derivatives

Terpyridine derivatives are of great interest due to their unique photophysical properties when used as antennas in metallic complexes. Several experimental and theoretical studies indicate strong charge-transfer character of the lowest electronic excited state, which could be exploited for predicting fluorescence quantum yields from the magnitude of the charge separation induced by electronic transitions. Focusing on substituted 4′-phenyl-2,2′:6′2′′-terpyridyl, we report on two measures of the charge separation obtained from high-level calculations in ground and excited states (length of the change of the dipole moment and the electron–hole distance). Our refined model confirms that the fluorescence quantum yield shows a global S-shape dependence on the magnitude of the charge separation, which can be quantified either by the change in dipole moments between the ground and excited states or by the associated charge–hole distances. This approach provides a remarkable tool for the molecular design of a fluorescent polyaromatic antenna

SCOPE: predicting future diagnoses in office visits using electronic health records

Abstract We propose an interpretable and scalable model to predict likely diagnoses at an encounter based on past diagnoses and lab results. This model is intended to aid physicians in their interaction with the electronic health records (EHR). To accomplish this, we retrospectively collected and de-identified EHR data of 2,701,522 patients at Stanford Healthcare over a time period from January 2008 to December 2016. A population-based sample of patients comprising 524,198 individuals (44% M, 56% F) with multiple encounters with at least one frequently occurring diagnosis codes were chosen. A calibrated model was developed to predict ICD-10 diagnosis codes at an encounter based on the past diagnoses and lab results, using a binary relevance based multi-label modeling strategy. Logistic regression and random forests were tested as the base classifier, and several time windows were tested for aggregating the past diagnoses and labs. This modeling approach was compared to a recurrent neural network based deep learning method. The best model used random forest as the base classifier and integrated demographic features, diagnosis codes, and lab results. The best model was calibrated and its performance was comparable or better than existing methods in terms of various metrics, including a median AUROC of 0.904 (IQR [0.838, 0.954]) over 583 diseases. When predicting the first occurrence of a disease label for a patient, the median AUROC with the best model was 0.796 (IQR [0.737, 0.868]). Our modeling approach performed comparably as the tested deep learning method, outperforming it in terms of AUROC (p < 0.001) but underperforming in terms of AUPRC (p < 0.001). Interpreting the model showed that the model uses meaningful features and highlights many interesting associations among diagnoses and lab results. We conclude that the multi-label model performs comparably with RNN based deep learning model while offering simplicity and potentially superior interpretability. While the model was trained and validated on data obtained from a single institution, its simplicity, interpretability and performance makes it a promising candidate for deployment

How to choose the frozen density in Frozen-Density Embedding Theory-based numerical simulations of local excitations?

According to Frozen-Density Embedding Theory, any observable evaluated for the embedded species is a functional of the frozen density (ρB —the density associated with the environment). The environment-induced shifts in the energies of local excitations in organic chromophores embedded in hydrogen-bonded environments are analyzed. The excitation energies obtained for ρB , which is derived from ground-state calculations for the whole environment applying medium quality basis sets (STO–DZP) or larger, vary in a narrow range (about 0.02 eV which is at least one order of magnitude less than the magnitude of the shift). At the same time, the ground-state dipole moment of the environment varies significantly. The lack of correlation between the calculated shift and the dipole moment of the environment reflects the fact that, in Frozen-Density Embedding Theory, the partitioning of the total density is not unique. As a consequence, such concepts as “environment polarization” are not well defined within Frozen-Density Embedding Theory. Other strategies to generate ρB (superposition of densities of atoms/molecules in the environment) are shown to be less robust for simulating excitation energy shifts for chromophores in environments comprising hydrogen-bonded molecules

Practical Considerations for Developing Clinical Natural Language Processing Systems for Population Health Management and Measurement

Experts have noted a concerning gap between clinical natural language processing (NLP) research and real-world applications, such as clinical decision support. To help address this gap, in this viewpoint, we enumerate a set of practical considerations for developing an NLP system to support real-world clinical needs and improve health outcomes. They include determining (1) the readiness of the data and compute resources for NLP, (2) the organizational incentives to use and maintain the NLP systems, and (3) the feasibility of implementation and continued monitoring. These considerations are intended to benefit the design of future clinical NLP projects and can be applied across a variety of settings, including large health systems or smaller clinical practices that have adopted electronic medical records in the United States and globally

Where does the Raman optical activity of [Rh(en)3]3+come from? Insight from a combined experimental and theoretical approach

Backscattered Raman optical activity (ROA) spectra are measured for Δ- and Λ-tris-(ethylenediamine)rhodium(III) chloride in aqueous solution. In addition, the spectra of the four possible conformers in the Λ configuration are investigated by ab initio calculations. The Λ(δδδ) conformer is in best agreement with experimental spectra and examined in more details. The two most stable conformers according to the calculations are not compatible with the experimental ROA spectrum. Insights into the origin of observed band intensities are obtained by means of group coupling matrices. The influence of the first solvation shell is explored via an ab initio molecular dynamics simulation. Taking explicit solvent molecules into account further improves the agreement between calculation and experiment. Analysis of selected normal modes using group coupling matrices shows that solvent molecules lead to normal mode rotation and thus contribute to the ROA intensity, whereas the contribution of the Rh can be neglected

Ion Pair−π Interactions

We report that anion−π and cation−π interactions can occur on the same aromatic surface. Interactions of this type are referred to as ion pair−π interactions. Their existence, nature, and significance are elaborated in the context of spectral tuning, ion binding in solution, and activation of cell-penetrating peptides. The origin of spectral tuning by ion pair−π interactions is unraveled with energy-minimized excited-state structures: The solvent- and pH-independent red shift of absorption and emission of push–pull fluorophores originates from antiparallel ion pair−π attraction to their polarized excited state. In contrast, the complementary parallel ion pair−π repulsion is spectroscopically irrelevant, in part because of charge neutralization by intriguing proton and electron transfers on excited push–pull surfaces. With time-resolved fluorescence measurements, very important differences between antiparallel and parallel ion pair−π interactions are identified and quantitatively dissected from interference by aggregation and ion pair dissociation. Contributions from hydrogen bonding, proton transfer, π–π interactions, chromophore twisting, ion pairing, and self-assembly are systematically addressed and eliminated by concise structural modifications. Ion-exchange studies in solution, activation of cell-penetrating peptides in vesicles, and computational analysis all imply that the situation in the ground state is complementary to spectral tuning in the excited state; i.e., parallel rather than antiparallel ion pair−π interactions are preferred, despite repulsion from the push–pull dipole. The overall quite complete picture of ion pair−π interactions provided by these remarkably coherent yet complex results is expected to attract attention throughout the multiple disciplines of chemistry involved