TS Model Research Articles

Cinchona Organocatalyzed Enantioselective Amination for Quaternized Serines as Tertiary Amides.

Herein, we describe a Cinchona-aminocatalyzed enantioselective α-hydrazination of an α-formyl amide for the production of protected quaternized serines as tertiary amides with ee's of generally >98% and ≤99% yields. The proposed TS model supported by density functional theory calculations involves a quinuclidinium ion Brønsted acid-assisted delivery of DtBAD, which occurs from the Re face of an H-bonded enaminone when using a 9S-cinchonamine catalyst, resulting in a hydrazide with the R-configuration as determined by X-ray analysis.

Generation of a mouse model of thyroid storm and preliminary investigation of the therapeutic effects of ghrelin

BackgroundThyroid storm (TS), a life-threatening condition that can damage multiple organs, has limited therapeutic options. Hypercytokinemia is a suggested background, but the pathological condition is unclear and there are no appropriate animal models. We aimed to develop a TS mouse model by administration of triiodothyronine and lipopolysaccharide, and then to examine the effects of ghrelin on this model.MethodsWe evaluated the use of serum IL-6 levels as a representative marker of hypercytokinemia in patients with TS. To establish the mouse model, preliminary experiments were conducted to determine the non-lethal doses of triiodothyronine and lipopolysaccharide when administered individually. As a TS model, C57BL/6 mice were administered with triiodothyronine 1.0 mg/kg (subcutaneously, once daily for seven consecutive days) and lipopolysaccharide 0.5 mg/kg (intraperitoneally, on day 7) to develop a lethal model with approximately 30% survival on day 8. We assessed the survival ratio, mouse sepsis scores and blood biomarkers (IL-6, metanephrine, alanine aminotransferase) and evaluated the effects of ghrelin 300 µg/kg on these parameters in TS model.ResultsSerum IL-6 was increased in patients with TS compared with those with Graves’ disease as the diseased control (18.2 vs. 2.85 pg/mL, P < .05, n = 4 each). The dosage for the murine TS model was triiodothyronine 1.0 mg/kg and lipopolysaccharide 0.5 mg/kg. The TS model group had increased mouse sepsis score, serum IL-6, metanephrine and alanine aminotransferase. In this model, the ghrelin improved the survival rate to 66.7% (P < .01, vs. 0% [saline-treated group]) as well as the mouse sepsis score, and it decreased the serum IL-6 and metanephrine.ConclusionWe established an animal model of TS that exhibits pathophysiological states similar to human TS with induction of serum IL-6 and other biomarkers by administration of T3 and LPS. The results suggest the potential effectiveness of ghrelin for TS in humans.

Model-informed Evidence for Clinical Non-inferiority of Every-2-Weeks Versus Standard Weekly Dosing Schedule of Cetuximab in Metastatic Colorectal Cancer.

Cetuximab was initially developed and approved as a first-line treatment in patients with unresectable metastatic colorectal cancer (mCRC) for weekly administration (250 mg/m2 Q1W with 400 mg/m2 loading dose). An every-2-weeks schedule (500 mg/m2 Q2W) was approved recently by several health authorities. Being synchronized with chemotherapy, Q2W administration should improve patients' convenience and healthcare resource utilization. Herein, we present evidence of non-inferiority of Q2W cetuximab, compared with Q1W dosing using pharmacometrics modeling and clinical trial simulation (CTS). Pooled data from five phase I-III clinical trials in 852 patients with KRAS wild-type mCRC treated with Q1W or Q2W cetuximab were modeled using a population exposure-tumor size (TS) model linked to overall survival (OS); exposure was derived from a previously established population pharmacokinetic model. A semi-mechanistic TS model adapted from the Claret model incorporated killing rate proportional to cetuximab area under the concentration-time curve over 2 weeks (AUC) with Eastern Cooperative Oncology Group (ECOG) status as covariate on baseline TS. The OS was modeled with Weibull hazard using ECOG, baseline TS, primary tumor location, and predicted percent change in TS at 8 weeks as covariates. Model-based simulations revealed indistinguishable early tumor shrinkage and survival between Q2W vs. Q1W cetuximab. CTS evaluated OS non-inferiority (predefined margin of 1.25) in 1,000 trials, each with 2,000 virtual patients receiving Q2W or Q1W cetuximab (1:1), and demonstrated non-inferiority in 94% of cases. Taken together, these analyses provide model-based evidence for clinical non-inferiority of Q2W vs. Q1W cetuximab in mCRC with potential benefits to patients and healthcare providers.

INTELLIGENT CONTROL SYSTEM OF MULTI-MOTION MOBILE ROBOT

Technical devices with irregular motion are described by complex non-linear differential equations, as they have an uncertain environment. Due to interactions and simplifications in these types of control objects, their mathematical models may have certain errors. For this reason, by known methods, for example, the linear matrix inequality method, Lyapunov's quadratic function, etc. The synthesized automatic control systems (ACS) for dynamic objects written by nonlinear mathematical models based on the quadratic matrix determined by The synthesis of regulators for the management of dynamic objects described in nonlinear and uncertain conditions is based on fuzzy logic theory. Since the controllers synthesized by fuzzy logic are based on knowledge, their application to other objects (robots) is limited. In such systems, it is difficult or not at all to determine the dependencies between ACS quality indicators, stability and object parameters. Taking into account the above, a method of analytically parametric synthesis of regulators that ensures the degree of stability and accuracy in ACS’s designed for fuzzy TS-type dynamic objects is proposed. In the article, the solution to the problem of the synthesis of the control system of the mobile robot was considered, and it was successfully applied in the multi-motion mobile robot system. Modeling and experimental results confirm that the operation and stability of the obtained system fully meet the technical requirements. The proposed method has led to an increase in both tracking and control accuracy during high-speed movements. Keywords: multi-motion mobile robot, mathematical model, mechatronic modules, fuzzy TS model, robust controller, fuzzy logic.

Temperature and moisture sensitivities of soil respiration vary along elevation gradients: An analysis from long-term field observations

Based on long-term field observation data over 11 years at 23 sites in two mountainous areas (TS1 and TS2) at elevations from 829 to 2700 m, where the dominant vegetation type of TS1 and TS2 was temperate mixed broadleaf-coniferous forest and cold temperate coniferous forest, respectively, we analyzed the correlations between soil respiration (Rs) and abiotic and biotic factors to explore the response patterns of Rs to environmental factors within and between the sites along the elevation gradient. We found that soil moisture (θ) and its combinations (Ts × θ and θ/Ts) with soil temperature (Ts) increased significantly with increasing elevation, while Ts, soil bulk density (SBD), C/N ratio, and pH decreased significantly with increasing elevation. Within each site, both exponential- Ts (ET) and Gaussian-Ts (GT) models could be used for predicting the Rs seasonal variation, except for two sites in the area of TS1, where θ was a better predictor than Ts. The integrated ET–θ and GT–θ models could be applied to all sites except for 22S, and both were superior to the ET and GT models. The mean Rs of each site over the measurement period ranged from 3.07 to 6.94 μmol CO2 m−2 s−1 and showed a quadratic increase along the elevation gradient. Among the 23 sites, Q10 ranged from 1.15 to 3.79, and it increased with elevation, reaching a maximum at an elevation of 2366 m; the θ sensitivity parameter (d) decreased significantly with elevation and reached a minimum at an elevation of 1975 m. Both the d and Ts sensitivity parameter (b) of Rs were complementary to each other along the elevation gradient. Among the sites, Ts, θ, and combinations of the two were more important drivers for both Rs and Q10 variations than microbial and physicochemical indicators.

Comparison of Density-Functional Theory Dispersion Corrections for the DES15K Database.

While density-functional theory (DFT) remains one of the most widely used tools in computational chemistry, most functionals fail to properly account for the effects of London dispersion. Hence, there are many popular post-self-consistent methods to add a dispersion correction to the DFT energy. Until now, the most popular methods have never been compared on equal footing due to not being implemented in the same electronic structure packages. In this work, we performed a large-scale benchmarking study, directly comparing the accuracy of the exchange-hole dipole moment (XDM), D3BJ, D4, TS, MBD, and MBD-NL dispersion models when applied to the recent DES15K database of nearly 15,000 molecular complexes at both expanded and compressed geometries. Our study showed similarly good performance for all dispersion methods (except TS) when applied to neutral complexes. However, they all performed worse for ionic complexes, particularly those involving dications of alkaline earth metals, due to systematic overbinding by the base PBE0 density functional. Investigation of the largest outliers also revealed that only the MBD and MBD-NL methods demonstrate surprising errors for complexes involving alkali metal cations at compressed geometries where they tended to significantly overbind. As we would expect minimal dispersion binding for such complexes, we further investigated the origins of these errors for the potential energy curve of a model cation-π complex. Overall, there is little choice between the XDM, D3BJ, D4, MBD, and MBD-NL dispersion methods for most systems. However, the MBD-based methods are not recommended for complexes involving organic species and alkali or alkaline earth metal cations, for example when modeling Li+ intercalation into graphite.

Interactions and conformational changes of annexin A2/p11 heterotetramer models on a membrane: a molecular dynamics study

Ca2+-dependent membrane-binding by the Annexin A2/p11 heterotetramer (A2t) plays an important role in various biological processes including fibrinogen activation and exocytosis in neuroendocrine cells. Two models where A2t associates with a single membrane surface were generated and used to perform molecular dynamics simulations. The first model mimics initial A2t-membrane binding through both Annexin A2 (A2) subunits of A2t (TS model) while the second model mimics A2t-binding through a single A2 subunit (OS model). Conformational changes were summarized using principal component analysis (PCA), simulation snapshots, and distance plots from the simulations. The full TS model, including the p11 dimer, fully associates with the membrane adopting a stable structure with little conformational variation as evidence by PCA. The unassociated subunits of the OS model moved toward the membrane. The molecular mechanics/Generalized-Born surface area (MMGBSA) method was applied to investigate the energetics of the models. The MMGBSA results demonstrated that R63 of p11 was the primary contributor to the p11-membrane interaction. The TS model results were both consistent with those found in the literature and provide novel insights about the specific residues driving the A2t-membrane interaction. Additionally, it represents the most complete model of A2t on the membrane surface available. Communicated by Ramaswamy H. Sarma

Acoustic Target Strength According to Different Growth Stages of Japanese Anchovy (Engraulis japonicus): A Comparison of Juvenile and Adult Fish

Japanese anchovy (Engraulis japonicus) is an economically important species found in the coastal waters of the northwestern Pacific Ocean. To conduct effective acoustic surveys on the spawning or fishing grounds of this species, the target strength (TS, dB re 1 m2) during its growth stages must be understood. However, knowledge regarding the TS of juvenile Japanese anchovies is limited. To address this knowledge gap, we measured the TS and proposed equation models for juvenile Japanese anchovies while describing the TS differences between young and adult anchovies. We evaluated 21 live anchovies using 38, 120, and 200 kHz transducers. TS models were fitted for the juvenile stage of anchovies, considering different frequencies. The mean TS values of young and adult anchovies were similar to those reported in previous TS studies, whereas the TS values of juvenile anchovies were significantly lower. Thus, applying the same TS equation based on the acoustic characteristics of anchovies at different growth stages, especially for juvenile anchovies, may not be appropriate. These findings underscore the importance of adopting a suitable TS equation specific to the growth stages of Japanese anchovies for accurate data analysis in acoustic surveys conducted on spawning and fishing grounds.

Mining previous acoustic surveys to improve walleye pollock (Gadus chalcogrammus) target strength estimates

Abstract Acoustic-trawl surveys are widely used to measure the abundance and distribution of pelagic fish. The echo integration method used in these surveys requires estimates of the target strength (TS, dB re 1 m2) of acoustic scatterers. Here, we present a new automated method to estimate TS from a large volume of previously collected acoustic survey data recorded near trawl sites. By applying a series of selection and filtering methods to echosounder data, single echo measurements representative of fish encountered during surveys can be objectively and reliably isolated from existing survey data. We applied this method to 30 surveys of walleye pollock (Gadus chalcogrammus) conducted in Alaska from 2007 to 2019 and estimated a new length-to-TS relationship. The resulting relationship ($TS = 20.0 \cdot {\log _{10}}\,L - 66.0$) was largely consistent with previous in situ estimates made during dedicated, mostly nighttime TS collection events. Analysis of this sizeable data set (n = 142) indicates that increased fish depth, lower ambient temperature, and summer months may increase pollock TS. The application of a new TS model incorporating these environmental covariates to historic surveys resulted in -16 to +21% changes in abundance relative to the model without environmental covariates. This study indicates that useful TS measurements can be uncovered from existing datasets.

Comprehensive Evaluation of Interval Equalization of Power Quality in Active Distribution Network Based on CVAE-TS

AbstractWhen distributed generation is connected to the distribution network, there are many uncertainties and various loads, and the power quality is difficult to judge. Therefore, a comprehensive evaluation method for power quality interval balance of active distribution network based on CVAE-TS (coordination Vocational Academic Education-Takagi–Sugeno) is proposed. The method of change vector analysis (CVA) is adopted to generate power data samples of active distribution network. The category labels of each data are added to the original power data as training sets for CVAE, and the number of samples generated within the interval is increased. TS modeling is adopted, fuzzy set theory is combined with least square method, incomplete electric energy data in data sample is converted into complete electric energy data by filling method, and the applicability of data is enhanced. An interval evaluation model of power quality in active power network is established by using analytic hierarchy process. The experimental results show that this method can effectively realize the sampling and filling of power data in active distribution network, the evaluation results are accurate and reliable, and the horizontal distribution of power quality can be intuitively known.

The inflammatory injury in the striatal microglia-dopaminergic-neuron crosstalk involved in Tourette syndrome development.

Tourette syndrome (TS) is associated with immunological dysfunction. The DA system is closely related to TS development, or behavioral stereotypes. Previous evidence suggested that hyper-M1-polarized microglia may exist in the brains of TS individuals. However, the role of microglia in TS and their interaction with dopaminergic neurons is unclear. In this study, we applied iminodipropionitrile (IDPN) to establish a TS model and focused on the inflammatory injury in the striatal microglia-dopaminergic-neuron crosstalk. Male Sprague-Dawley rats were intraperitoneally injected with IDPN for seven consecutive days. Stereotypic behavior was observed to verify the TS model. Striatal microglia activation was evaluated based on different markers and expressions of inflammatory factors. The striatal dopaminergic neurons were purified and co-cultured with different microglia groups, and dopamine-associated markers were assessed. First, there was pathological damage to striatal dopaminergic neurons in TS rats, as indicated by decreased expression of TH, DAT, and PITX3. Next, the TS group showed a trend of increased Iba-1 positive cells and elevated levels of inflammatory factors TNF-α and IL-6, as well as an enhanced M1-polarization marker (iNOS) and an attenuated M2-polarization marker (Arg-1). Finally, in the co-culture experiment, IL-4-treated microglia could upregulate the expression of TH, DAT, and PITX3 in striatal dopaminergic neurons vs LPS-treated microglia. Similarly, the TS group (microglia from TS rats) caused a decreased expression of TH, DAT, and PITX3 compared with the Sham group (microglia from control rats) in the dopaminergic neurons. In the striatum of TS rats, microglia activation is M1 hyperpolarized, which transmits inflammatory injury to striatal dopaminergic neurons and disrupts normal dopamine signaling.

Estimation performance comparison of machine learning approaches and time series econometric models: evidence from the effect of sector-based energy consumption on CO2 emissions in the USA.

By considering the existence of two separate analysis families and the usage of different data frequencies, this study aims to examine the effect of method choice, data frequency, and sector-based energy consumption on carbon dioxide (CO2) emissions by performing machine learning (ML) algorithms and time series econometric (TS) models simultaneously. In this situation, the study examines the United States (USA), considers sector-based energy consumption indicators as explanatory variables, uses monthly and yearly data between January 1973 and December 2021, estimates CO2 emissions, and compares the estimation performance of the models. The empirical findings reveal that (i) the ML algorithms outperform the TS models based on R2 and goodness of fit criteria; (ii) the estimation performance of the models increases with the high-frequency (i.e., monthly) data; (iii) the ML algorithms perform much better in case of high-frequency usage; (iv) some thresholds identify the effects of the sector-based energy consumption indicators on the CO2 emissions; (v) electric power and transportation sectors are the most important sectors in the estimation of the CO2 emissions for monthly and yearly data, respectively. Hence, the study provides to help the understanding role of method choice, data frequency, and sector-based energy consumption for the estimation of CO2 emissions. Based on the results, this study proposes that US policymakers should consider the ML algorithms, use higher-frequency data, and include sector-based energy consumption indicators to have a better estimation of CO2 emissions.

Covering soft rough sets and its topological properties with application

In this article, we introduce the notion of the complementary soft neighborhood and present three kinds of covering soft rough set (mathcal {CSR}) models. The basic properties of these models are investigated. The relationships among these models are also discussed. Moreover, we establish the topological approach to mathcal {CSR} say, varDelta -topological spaces (i.e., varDelta -TS). Hence, the topological properties for varDelta -TS models such as varDelta -open sets, varDelta -closed sets, varDelta -interior, varDelta -closure, varDelta -boundary, varDelta -neighborhood and varDelta -limit point are studied and the relationships between them are given. Finally, we make use of an algorithm for these proposed models to deal with uncertainties for solving the MGDM problems using the constructed topologies.

TS-GCN: Aspect-level sentiment classification model for consumer reviews

The goal of aspect-level sentiment classification (ASC) task is to obtain the sentiment polarity of aspect words in the text. Most existing methods ignore the implicit aspects, resulting in low classification accuracy. To improve the accuracy, this paper proposes a classification model for consumer reviews, abbreviated as TS-GCN (Truncated history attention and Selective transformation network-Graph Convolutional Networks). TS-GCN can classify sentiment from both explicit and implicit aspects. Firstly, we process the text by the BERT model and the BiLSTM model to obtain the text features. Secondly, the GCN model completes explicit sentiment classification by training text features. Due to the lack of implicit words, the GCN model cannot classify implicit sentiments. Finally, we predict implicit words based on the TS model, which makes up for the deficiency of the GCN model and completes the sentiment classification of implicit words. TS-GCN is proved on several datasets in the consumer reviews field. The results of experiments show that the TS-GCN can improve the accuracy and F1 of ASC.

Takotsubo syndrome-like model in rats with high reproducibility and low mortality

Abstract Background/Purpose Takotsubo syndrome (TS) is an acute form of heart failure with similar mortality and clinical presentation as myocardial infarction. The pathophysiology of the potentially life-threatening syndrome is only partially understood. This experimental study aimed to produce a human-like TS model with high reproducibility and low mortality. Rats have been the small-animal model of choice for preclinical studies within the cardiovascular field, successfully translating gained knowledge to humans. A relevant animal model can aid in elucidating mechanisms behind TS and serve as a platform for developing evidence-based treatment guidelines specific for the disease, which are currently missing. Methods 190 Sprague Dawley rats (male, ∼300 g, ∼47 d) were infused i.v. with a single dose of the β-adrenergic agonist isoprenaline. The first study group was randomized by infusion time (ranging from 1 min to 60 min) while maintaining a fixed total dose (6.25 mg/kg), and the second group by total dose (0.1–50 mg/kg) with specified infusion time. The studies were replicated with saline infusion as a control. This study looked at mortality, the incidence of apical akinesia, the extent of apical akinesia, and recovery time. ECG, HR, SpO2, and temperature were monitored during the induction phase (&amp;lt;60 min) and at time points for imaging. High-resolution speckle-tracking echocardiography was used to study heart function for up to 30 days. The study followed the principles of laboratory animal care and was approved by our institution's Animal Ethics Committee. Results Mechanical dyssynchrony preceded global contractile dysfunction and development of transient apical akinesia. LV function and contractility normalised after 1 to 7 days. All surviving rats showed normal behaviour, ECG, and imaging at 30 days. TS-like phenotype was achieved in 92.9% of survivors. Mortality at 30-day was 6.7%. The deceased animals developed complications like TS patients including heart failure, malignant arrhythmias, LV mural thrombus formation, cardiogenic shock. Longer infusion time was associated with increased mortality (p=0.002), but not with the incidence of akinesia (p=0.818). The extent of apical akinesia decreased at the shortest infusion time (1 min) while at 7.5 minutes and above, it did not differ. The replication study validated these findings, although variability in incidence and mortality was seen across the groups. Conclusions This study provides a highly reproducible TS-like model with low mortality and excellent translational potential. High-resolution imaging and the natural course demonstrated the presence of the most critical characteristics of TS-like phenotype as in humans. The model also validates other findings related to TS including variability in the susceptibility to develop TS-like phenotype and complications. Our model provides a solid experimental platform for future preclinical studies of TS. Funding Acknowledgement Type of funding sources: Public grant(s) – National budget only. Main funding source(s): ALF - Swedish Research Council

TS Model-LMI Based Observer for Improving Active Power Filter Performance

To avoid the negative effects of using a control signal with a ripple, which is generated by the feedback of measured active power filter (APF) variables, a nonlinear observer is employed in this paper. The observer design, through the use of exact TS models and Lyapunov-based LMI conditions, is achieved. Both the APF output current and the DC voltage are estimated by the observer, and they are used in the cascade control feedback. In this way, high gains in the inner control loop are employed, giving place to a control signal without undesired harmonic components or overmodulation. This allows an APF performance improvement for compensation tasks and for reducing the undesired components injection to the mains. A simulation and experimental comparison between APF results using observer and APF results without using observer is presented. Better results are achieved for the observer version case, reducing the THD from 47.6% to 4.8% in experimental conditions, satisfying the IEEE Standard 519TM-2014. Also, load change tests are carried out, where the stability of the system is kept. Moreover, by using the observer, a DC voltage sensor was not required, reducing the number of system sensors.

Ground Motion Prediction Equations for the Vertical Ground Motions from Subduction Interface Earthquakes in Japan Using Site Period or VS30 as the Site-Effect Parameters

ABSTRACT Based on our previous study, we developed ground motion prediction equations (GMPEs) with two site proxies, that is, with one GMPE using the site period (TS, four times the travel time of shear waves down to the bedrock) and the other one using a pseudosite period (TVS30, four times the travel time of shear waves down to 30 m depth). We used two reasonably simple site-effect models based on TS or TVS30, and each site model has four parameters with each parameter having a physical meaning and miming the theoretical process in site amplification calculations. We found that only the linear magnitude terms in the site class (SC) model from our previous study need to be modified to accommodate the change in the site response parameters, suggesting that the source effect interacts with the site effect. At short periods up to about 0.3 s, the performances of these site models are largely similar. However, at spectral periods over 0.3 s, the performances of these site models are strikingly different, and the rank of the three models in the site model performance is (from the best to the worst) TS, SC, and TVS30 site models. It is a surprise that the SC model with four classes can be better than the TVS30 site model, which does not account for the effect of the soil or rock layers between the 30 m and the bedrock depth. These results may mean that the inclusion of these deep soil layers is more important than the limitations of using a simple step function for the SC model. The GMPE using TS presented in this study improved the prediction accuracy significantly, especially for sites with TS over 0.3 s at spectral periods over 0.3 s. The GMPE using TS in this study can be used whenever TS is available.

Dynamic Kinetic Resolution of Azlactones via Phase-Transfer Catalytic Alcoholysis

Phase-transfer catalytic asymmetric alcoholysis of azlactones via dynamic kinetic resolution proceeded for a wide range of alcohols and azlactones, affording the corresponding α-chiral amino acid esters in up to 98% yield and up to 99:1 er. In addition, this catalytic system was also applied to the asymmetric alcoholysis of N-benzoyl amino acid hexafluoroisopropyl ester providing the desired product in good yield with high stereoselectivity (71% yield, 98:2 er). The catalyst loading could be reduced to 0.1 mol % without significant loss of stereoselectivity (turnover number = 411). Furthermore, a gram-scale reaction and transformations of the enantioenriched products involving hydrogenolysis, LAH-reduction, and Suzuki–Miyaura coupling reactions were successfully achieved. Detailed computational studies using a pseudotransition state (pseudo-TS) conformational search with ConFinder and density functional theory (DFT) calculations indicated a TS model that accounted for the origin of the stereoselectivity. In this TS model, water or alcohol molecules activate the azlactone substrate by H-bonding with the nitrogen atom, and concomitant accumulated weak interactions, including H-bonding interactions, C–H−π, and π–π interactions, stabilize the TS, leading to the major enantiomer.

Deep learning approaches for improving prediction of daily stream temperature in data‐scarce, unmonitored, and dammed basins

AbstractBasin‐centric long short‐term memory (LSTM) network models have recently been shown to be an exceptionally powerful tool for stream temperature (Ts) temporal prediction (training in one period and predicting in another period at the same sites). However, spatial extrapolation is a well‐known challenge to modelling Ts and it is uncertain how an LSTM‐based daily Ts model will perform in unmonitored or dammed basins. Here we compiled a new benchmark dataset consisting of &gt;400 basins across the contiguous United States in different data availability groups (DAG, meaning the daily sampling frequency) with and without major dams, and studied how to assemble suitable training datasets for predictions in basins with or without temperature monitoring. For prediction in unmonitored basins (PUB), LSTM produced a root‐mean‐square error (RMSE) of 1.129°C and an R2 of 0.983. While these metrics declined from LSTM's temporal prediction performance, they far surpassed traditional models' PUB values, and were competitive with traditional models' temporal prediction on calibrated sites. Even for unmonitored basins with major reservoirs, we obtained a median RMSE of 1.202°C and an R2 of 0.984. For temporal prediction, the most suitable training set was the matching DAG that the basin could be grouped into (for example, the 60% DAG was most suitable for a basin with 61% data availability). However, for PUB, a training dataset including all basins with data was consistently preferred. An input‐selection ensemble moderately mitigated attribute overfitting. Our results indicate there are influential latent processes not sufficiently described by the inputs (e.g., geology, wetland covers), but temporal fluctuations can still be predicted well, and LSTM appears to be a highly accurate Ts modelling tool even for spatial extrapolation.

Tuning the optical constants and thermal properties of CdS nanocrystals by SHI irradiation: A blended analysis through DFT+U and TS model

Here, chemically synthesized CdS nanocrystals have been irradiated with swift heavy ions (SHI) with an aim to study the changes in its optical constants such as refractive index and dielectric constant along with the bandgap modification. Scanning electron microscopy (SEM) shows spherical morphology of the pristine CdS nanocrystals with an average size of 17 nm, which gets slightly deviated from its spherical morphology after SHI irradiation. X-ray diffraction (XRD) study reveals a change in the lattice structure of CdS nanocrystals from cubic to hexagonal phase due to irradiation. Structural information obtained from the XRD data has been fed as an initial input parameter in the first principles study (DFT + U) using the Quantum Espresso package for determining refractive index, dielectric constant, band gap and thermal properties theoretically. All these theoretically obtained values of optical constants match approximately with the values obtained from the experimental UV–Visible data analysis. Finally, the value of threshold electronic energy loss has been determined from the Thermal spike model.