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Abstract Rice is one of the major food crops grown globally. However, during the wet season, rice suffers significant yield loss due to reduced light intensity caused by overcast clouds when the light intensity is only around 450–500 µmol/m2/s, compared to 1400–1800 µmol/m2/s in summer. This reduction in light intensity leads to a decrease in seed yield, mainly by limiting tiller or panicle numbers. Yield and its attributing parameters were recorded in one hundred thirty RILs for four consecutive wet seasons in ambient light (AL) and low light (LL, 35% light-cut using white shade net). QTL analysis was performed using Inclusive Composite Interval Mapping (ICIM) with all the phenotypic data and 927 polymorphic SNPs identified by the 7 K Infinium chip. The study identified a large QTL influencing panicle numbers and yield exclusively in lowlight on chromosome 1 (qPNLL1.1, qGYLL1.1) in four consecutive seasons with LOD > 10 and PVE > 30%. The favourable alleles are from the tolerant parent, Swarnaprabha. Another grain yield improving QTL was identified on chromosome 6 (qGYLL6.1), with LOD > 3 in three consecutive seasons. In a diverse rice panel of one hundred seventeen genotypes with five different models, association analysis identified the associated marker for panicle numbers and grain yield in LL, which is also the left marker of the newly identified QTLs for the traits under LL condition. A shade-responsive gene, monoculm 2 (MOC2, LOC_Os01g64660) inside the QTL on chromosome 1, upregulated in the tolerant parent and its QTL-carrying RILs, whereas repressed in the susceptible one. Therefore, due to its significant additive effect and validation across various genotypes, the yield-improving QTL on chromosome 1 can be directly utilised in marker-assisted selection (MAS) for developing shade-tolerant rice. This can also help reduce the yield gap between wet and dry-season rice.

Abstract Cd(II) is a potentially toxic heavy metal having carcinogenic activity. It is becoming widespread in the soil and groundwater by various natural and anthropological activities. This is inviting its immediate removal. The present study is aimed at developing a Cd(II) resistant strain isolated from contaminated water body and testing its potency in biological remediation of Cd(II) from aqueous environment. The developed resistant strain was characterized by SEM, FESEM, TEM, EDAX, FT-IR, Raman Spectral, XRD and XPS analysis. The results depict considerable morphological changes had taken place on the cell surface and interaction of Cd(II) with the surface exposed functional groups along with intracellular accumulation. Molecular contribution of critical cell wall component has been evaluated. The developed resistant strain had undergone Cd(II) biosorption study by employing adsorption isotherms and kinetic modeling. Langmuir model best fitted the Cd(II) biosorption data compared to the Freundlich one. Cd(II) biosorption by the strain followed a pseudo second order kinetics. The physical parameters affecting biosorption were also optimized by employing response surface methodology using central composite design. The results depict remarkable removal capacity 75.682 ± 0.002% of Cd(II) by the developed resistant strain from contaminated aqueous medium using 500 ppm of Cd(II). Quantitatively, biosorption for Cd(II) by the newly developed resistant strain has been increased significantly (p

The study was aimed to evaluate the performance of a newly developed spectroscopy-based non-invasive and noncontact device (SAMIRA) for the simultaneous measurement of hemoglobin, bilirubin and oxygen saturation as an alternative to the invasive biochemical method of blood sampling. The accuracy of the device was assessed in 4318 neonates having incidences of either anemia, jaundice, or hypoxia. Transcutaneous bilirubin, hemoglobin and blood saturation values were obtained by the newly developed instrument which was corroborated with the biochemical blood tests by expert clinicians. The instrument is trained using Artificial Neural Network Analysis to increase the acceptability of the data. The artificial intelligence incorporated within the instrument determines the disease condition of the neonate. The Pearson's correlation coefficient, r was found to be 0.987 for hemoglobin estimation and 0.988 for bilirubin and blood gas saturation respectively. The bias and the limits of agreement for the measurement of all the three parameters were within the clinically acceptance limit.

Abstract Overexpression of Glycine max disease resistant 1 (GmDR1) exhibits broad-spectrum resistance against Fusarium virguliforme, Heterodera glycines (soybean cyst nematode), Tetranychus urticae (Koch) (spider mites), and Aphis glycines Matsumura (soybean aphids) in soybean. To understand the mechanisms of broad-spectrum immunity mediated by GmDR1, the transcriptomes of a strong and a weak GmDR1-overexpressor following treatment with chitin, a pathogen- and pest-associated molecular pattern (PAMP) common to these organisms, were investigated. The strong and weak GmDR1-overexpressors exhibited altered expression of 6098 and 992 genes, respectively, as compared to the nontransgenic control following chitin treatment. However, only 192 chitin- and 115 buffer-responsive genes exhibited over two-fold changes in expression levels in both strong and weak GmDR1-overexpressors as compared to the control. MapMan analysis of the 192 chitin-responsive genes revealed 64 biotic stress-related genes, of which 53 were induced and 11 repressed as compared to the control. The 53 chitin-induced genes include nine genes that encode receptor kinases, 13 encode nucleotide-binding leucine-rich repeat (NLR) receptor proteins, seven encode WRKY transcription factors, four ethylene response factors, and three MYB-like transcription factors. Investigation of a subset of these genes revealed three receptor protein kinases, seven NLR proteins, and one WRKY transcription factor genes that are induced following F. virguliforme and H. glycines infection. The integral plasma membrane GmDR1 protein most likely recognizes PAMPs including chitin and activates transcription of genes encoding receptor kinases, NLR proteins and defense-related genes. GmDR1 could be a pattern recognition receptor that regulates the expression of several NLRs for expression of PAMP-triggered immunity and/or priming the effector triggered immunity.

Abstract In the era of social media, the use of emojis and code-mixed language has become essential in online communication. However, selecting the appropriate emoji that matches a particular sentiment or emotion in the code-mixed text can be difficult. This paper presents a novel task of predicting multiple emojis in English-Hindi code-mixed sentences and proposes a new dataset called SENTIMOJI, which extends the SemEval 2020 Task 9 SentiMix dataset. Our approach is based on exploiting the relationship between emotion, sentiment, and emojis to build an end-to-end framework. We replace the self-attention sublayers in the transformer encoder with simple linear transformations and use the RMS-layer norm instead of the normal layer norm. Moreover, we employ Gated Linear Unit and Fully Connected layers to predict emojis and identify the emotion and sentiment of a tweet. Our experimental results on the SENTIMOJI dataset demonstrate that the proposed multi-task framework outperforms the single-task framework. We also show that emojis are strongly linked to sentiment and emotion and that identifying sentiment and emotion can aid in accurately predicting the most suitable emoji. Our work contributes to the field of natural language processing and can help in the development of more effective tools for sentiment analysis and emotion recognition in code-mixed languages. The codes and data will be available at https://www.iitp.ac.in/~ai-nlp-ml/resources.html#SENTIMOJI to facilitate research.

Abstract Carbon fibre-reinforced polyetheretherketone (CF-PEEK) composites have gained significant usage across diverse industries like automotive and aerospace due to their desirable characteristics. These properties encompass recyclability, low density, high strength, wear resistance and thermal stability. The components made from CF-PEEK composites for space applications will be subjected to a high radiation environment due to the incoming cosmic rays, comprising protons, α particles, electrons, γ rays, etc., once they escape the Earth’s atmosphere. The ion irradiation of CF-PEEK is accompanied by radiation-induced effects, which drastically change the structure and properties of irradiated material. Since the resistance of CF-PEEK to radiation damage has not been studied extensively, this study aims to understand the effect of high-energy He2+ ions on the microstructure and properties of CF-PEEK composites manufactured using automated fibre placement (AFP) under different processing conditions. The samples have been radiated with 5 MeV He2+ ions using an energy degrader wheel to create a layer with relatively uniform damage. Then, were characterized using optical and scanning electron microscopy and their hardness was evaluated using nanoindentation. It was observed that, irradiation increases the hardness of the fibres in all cases. Also, fibre orientation affects the hardness in a statistically significant manner in both unirradiated and irradiated conditions.

Abstract A balanced ecosystem with coexisting constituent species is often perturbed by different natural events that persist only for a finite duration of time. What becomes important is whether, in the aftermath, the ecosystem recovers its balance or not. Here we study the fate of an ecosystem by monitoring the dynamics of a particular species that encounters a sudden increase in death rate. For exploration of the fate of the species, we use Monte-Carlo simulation on a three-species cyclic rock-paper-scissor model. The density of the affected (by perturbation) species is found to drop exponentially immediately after the pulse is applied. In spite of showing this exponential decay as a short-time behavior, there exists a region in parameter space where this species surprisingly remains as a single survivor, wiping out the other two which had not been directly affected by the perturbation. Numerical simulations using stochastic differential equations of the species give consistency to our results.

Abstract Healthcare delivery during the initial days of outbreak of COVID-19 pandemic was badly impacted due to large number of severely infected patients posing an unprecedented global challenge. Although the importance of Chest X-rays (CXRs) in meeting this challenge has now been widely recognized, speedy diagnosis of CXRs remains an outstanding challenge because of fewer Radiologists. The exponential increase in Smart Phone ownership globally, including LMICs, provides an opportunity for exploring AI-driven diagnostic tools when provided with large volumes of CXRs transmitted through Smart Phones. However, the challenges associated with such systems have not been studied to the best of our knowledge. In this paper, we show that the predictions of AI-driven models on CXR images transmitted through Smart Phones via applications, such as WhatsApp, suffer both in terms of Predictability and Explainability, two key aspects of any automated Medical Diagnosis system. We find that several existing Deep learning based models exhibit prediction instability–disagreement between the prediction outcome of the original image and the transmitted image. Concomitantly we find that the explainability of the models deteriorate substantially, prediction on the transmitted CXR is often driven by features present outside the lung region, clearly a manifestation of Spurious Correlations. Our study reveals that there is significant compression of high-resolution CXR images, sometimes as high as 95%, and this could be the reason behind these two problems. Apart from demonstrating these problems, our main contribution is to show that Multi-Task learning (MTL) can serve as an effective bulwark against the aforementioned problems. We show that MTL models exhibit substantially more robustness, 40% over existing baselines. Explainability of such models, when measured by a saliency score dependent on out-of-lung features, also show a 35% improvement. The study is conducted on WaCXR dataset, a curated dataset of 6562 image pairs corresponding to original uncompressed and WhatsApp compressed CXR images. Keeping in mind that there are no previous datasets to study such problems, we open-source this data along with all implementations.

Abstract The use of neurofeedback is an important aspect of effective motor rehabilitation as it offers real-time sensory information to promote neuroplasticity. However, there is still limited knowledge about how the brain’s functional networks reorganize in response to such feedback. To address this gap, this study investigates the reorganization of the brain network during motor imagery tasks when subject to visual stimulation or visual-electrotactile stimulation feedback. This study can provide healthcare professionals with a deeper understanding of the changes in the brain network and help develop successful treatment approaches for brain–computer interface-based motor rehabilitation applications. We examine individual edges, nodes, and the entire network, and use the minimum spanning tree algorithm to construct a brain network representation using a functional connectivity matrix. Furthermore, graph analysis is used to detect significant features in the brain network that might arise in response to the feedback. Additionally, we investigate the power distribution of brain activation patterns using power spectral analysis and evaluate the motor imagery performance based on the classification accuracy. The results showed that the visual and visual-electrotactile stimulation feedback induced subject-specific changes in brain activation patterns and network reorganization in the $$\alpha$$ α band. Thus, the visual-electrotactile stimulation feedback significantly improved the integration of information flow between brain regions associated with motor-related commands and higher-level cognitive functions, while reducing cognitive workload in the sensory areas of the brain and promoting positive emotions. Despite these promising results, neither neurofeedback modality resulted in a significant improvement in classification accuracy, compared with the absence of feedback. These findings indicate that multimodal neurofeedback can modulate imagery-mediated rehabilitation by enhancing motor-cognitive communication and reducing cognitive effort. In future interventions, incorporating this technique to ease cognitive demands for participants could be crucial for maintaining their motivation to engage in rehabilitation.

Abstract Disposal of significant tonnages of rice straw is expensive, but using it to mobilise phosphorus (P) from inorganically fixed pools in the soil may add value. This study was carried out to determine whether the use of rice straw mixed with phosphorus-solubilizing microbes could solubilize a sizable portion fixed soil P and affect P transformation, silicon (Si) concentration, organic acid concentrations, and enzyme activity to increase plant growth. Depending on the soil temperature, the application of rice straw at 12 Mg ha−1 with phosphorus-solubilizing microbes could solubilize 3.4–3.6% of inorganic P, and minimised the hysteresis impact by 6–8%. At plant maturity, application of rice straw at 12 Mg ha−1 with phosphorus-solubilizing microbes and 75% of recommended P application raised the activity of dehydrogenase, alkaline phosphatase activity, cellulase, and peroxidase by 77, 65, 87, and 82% in soil, respectively. It also boosted Si concentration in the soil by 58%. Wheat grain yield was 40% and 18% higher under rice straw at 12 Mg ha−1 with phosphorus-solubilizing microbes with 75% of recommended P application than under no and 100% P application, respectively. Rice grain yield also increased significantly with the same treatment. Additionally, it increased root volume, length, and P uptake by 2.38, 1.74 and 1.62-times above control for wheat and 1.98, 1.67, and 2.06-times above control for rice, respectively. According to path analysis, P solubilisation by Si and organic acids considerably increased (18–32%) P availability in the rhizosphere. Therefore, cultivators could be advised to use rice straw at 12 Mg ha−1 with phosphorus-solubilizing microbes with 75% P of mineral P fertiliser to save 25% P fertiliser without reducing wheat and rice yield.

Abstract The recent prediction of diabetes to be a global pandemic invites a detection strategy preferably non-invasive, and bloodless to manage the disease and the associated complications. Here, we have synthesized chitosan polymer functionalized, organic–inorganic bio-compatible nano-hybrids of Mn3O4 nanoparticles, and characterized it by utilizing several optical methodologies for the structural characterization which shows the Michaelis Menten (MM) kinetics for glucose and alpha-amylase protein (well-known diabetes biomarkers). We have also studied the potentiality for the detection of alpha-amylase in human salivary secretion which is reported to be strongly correlated with uncontrolled hyperglycemia. Finally, we have developed a prototype for the measurement of glucose (LOD of 0.38 mg/dL, LOQ of 1.15 mg/dL) and HbA1c (LOD of 0.15% and LOQ of 0.45%) utilizing the basic knowledge in the study for the detection of uncontrolled hyperglycemia at the point-of-care. With the limited number of clinical trials, we have explored the potential of our work in combating the diabetic pandemic across the globe in near future.

The traditionally held assumption that photo-dependent processes are the predominant source of H2O2 in natural waters has been recently questioned by an increrasing body of evidence showing the ubiquitiousness of H2O2 in dark water bodies and in groundwater. In this study, we conducted field measurement of H2O2 in an intra-meander hyporheic zone and in surface water at East River, CO. On-site detection using a sensitive chemiluminescence method suggests H2O2 concentrations in groundwater ranging from 6 nM (at the most reduced region) to ~ 80 nM (in a locally oxygen-rich area) along the intra-meander transect with a maxima of 186 nM detected in the surface water in an early afternoon, lagging the maximum solar irradiance by ∼ 1.5 h. Our results suggest that the dark profile of H2O2 in the hyporheic zone is closely correlated to local redox gradients, indicating that interactions between various redox sensitive elements could play an essential role. Due to its transient nature, the widespread presence of H2O2 in the hyporheic zone indicates the existence of a sustained balance between H2O2 production and consumption, which potentially involves a relatively rapid succession of various biogeochemically important processes (such as organic matter turnover, metal cycling and contaminant mobilization). More importantly, this study confirmed the occurrence of reactive oxygen species at a subsurface redox transition zone and further support our understanding of redox boundaries on reactive oxygen species generation and as key locations of biogeochemical activity.

Abstract DNA interactions with multivalent ligand(s) have increasingly become the subject of substantial research. For several small molecules with therapeutic potential, nucleic acids serve as their primary molecular target. Such interaction has been shown to affect transcription or replication, ultimately leading to apoptotic cell death. As a result, researchers are becoming increasingly interested in understanding how small molecules interact with DNA making it possible to develop new, DNA-specific drugs. The bioactive indole alkaloid, Yohimbe (Yohimbine; Yh) has been broadly studied in pharmacological properties while its binding mode to DNA has not been explicated so far. This study adopted molecular modelling and multi-spectroscopic methods to investigate the interaction between Yohimbine and herring testes (HT DNA) in physiological conditions. Minor hypochromic and bathochromic shifts of fluorescence intensity were observed, suggesting the binding of Yh to HT DNA. The Scatchard plot analyses using the McGhee-von Hipple method revealed non-cooperative binding and affinities in the range of 105 M−1. The thermodynamic parameters suggested exothermic binding, which was favoured by negative enthalpy and positive entropy changes from temperature-dependent fluorescence experiments. Salt-dependent fluorescence suggested that the interaction between the ligand and DNA was governed by non-polyelectrolytic forces. The results of iodide quenching, urea denaturation assay, dye displacement, and in silico molecular docking, suggested groove binding of Yh to HT DNA. Thus, the groove binding mechanism of interaction was validated by both biophysical and computational techniques. The structural elucidation and energetic profiling of Yh's interaction with naturally occurring polymeric DNA can be useful to the development of DNA-targeted therapeutics.

Abstract Severe Thunderstorms are the extreme weather convective features. It causes local calamities in various ways. Proper prediction with lead time is an important factor to prevent such calamities from saving people. Here, both probabilistic and machine learning techniques are applied to weather data to obtain proper predictions. Traditional methodologies are already available for such prediction purposes. However, Naïve Bayes and RBFN (Radial Basis Function Network) methodology have been introduced here with some specific weather parameters that has not done before remarkably. A comparative study was performed on weather data including Naïve Bayes, Multilayer Perceptron (MLP), K-nearest neighbor (KNN) and Radial Basis Function Network (RBFN). All these data have been procured from Kolkata located in north-east India. The result obtained by applying the Radial Basis Function Network is better among the three methods, yielding a correct prediction of 95% for severe “squall-storms” and 94% for “no storm”. The predictions have a sufficient lead time of 10- 12 h.

Abstract Cadmium is one of the most dreadful heavy metals and is becoming a major toxicant in ground water with increasing concentration above the WHO Guidelines in drinking water (0.003 mg/L). The potential sources of cadmium include sewage sludge, phosphate fertilizers and ingredients like Ni–Cd batteries, pigments, plating and plastics. Cadmium levels are increased in water owing to the use and disposal of cadmium containing ingredients. Water draining from a landfill may contain higher cadmium levels. The authors have tried to evaluate the optimized nutritional conditions for the optimal growth and Cd(II) remediation capacity for a developed Cd(II) resistant yeast strain named Candida tropicalis XTA 1874 isolated from contaminated water-body in West Bengal. By analyzing the optimization conditions, a synthetic medium was developed and the composition has been given in the main text. The strain showed much better Cd(II) adsorption capacity under the optimized nutritional conditions (Mean removal = 88.077 ± 0.097%).

Abstract Four yeast strains were isolated from the gut of stingless bee, collected in Churdhar, Himachal Pradesh, India. Physiological characterization, morphological examination, and sequence analysis of small subunit ribosomal RNA (18S rRNA) genes, internal transcribed spacer (ITS) region, and D1/D2 domain of the large subunit rRNA gene revealed that the four strains isolated from the gut of stingless bee belonged to the Debaryomyces clade. Strain CIG-23HT showed sequence divergence of 7.5% from Debaryomyces nepalensis JCM 2095T, 7.8% from Debaryomyces udenii JCM 7855T, and Debaryomyces coudertii JCM 2387T in the D1/D2 domain. In the ITS region sequences, strain CIG-23HT showed a 15% sequence divergence from Debaryomyces nepalensis JCM 2095T and Debaryomyces coudertii JCM 2387T. In 18S rRNA gene sequence, the strain CIG-23HT showed 1.14% sequence divergence from Debaryomyces nepalensis JCM 2095 and and Debaryomyces coudertii JCM 2387, and 0.83% sequence divergence from Debaryomyces hansenii NRRL Y-7426. Strain CIG-23HT can utilize more carbon sources than closely related species. The findings suggest that strain CIG-23HT is a novel species of the genus Debaryomyces, and we propose to name it as Debaryomyces apis f.a., sp. nov. The holotype is CBS 16297T, and the isotypes are MTCC 12914T and KCTC 37024T. The MycoBank number of Debaryomyces apis f.a., sp. nov. is MB836065. Additionally, a method using cresol red and Bromothymol blue pH indicator dyes was developed to screen for lipase producers, which is more sensitive and efficient than the currently used phenol red and rhodamine B dye-based screening methods, and avoids the problem of less differentiable zone of hydrolysis.

Abstract The study was aimed to evaluate the performance of a newly developed spectroscopy-based non-invasive and noncontact device (SAMIRA) for the simultaneous measurement of hemoglobin, bilirubin and oxygen saturation as an alternative to the invasive biochemical method of blood sampling. The accuracy of the device was assessed in 4318 neonates having incidences of either anemia, jaundice, or hypoxia. Transcutaneous bilirubin, hemoglobin and blood saturation values were obtained by the newly developed instrument which was corroborated with the biochemical blood tests by expert clinicians. The instrument is trained using Artificial Neural Network Analysis to increase the acceptability of the data. The artificial intelligence incorporated within the instrument determines the disease condition of the neonate. The Pearson’s correlation coefficient, r was found to be 0.987 for hemoglobin estimation and 0.988 for bilirubin and blood gas saturation respectively. The bias and the limits of agreement for the measurement of all the three parameters were within the clinically acceptance limit.

Abstract Uncontrolled human and industrial activities lead to the increase in demand for selective gas sensors for detection of poisonous gases in our environment. Conventional resistive gas sensors suffer from predetermined sensitivity and poor selectivity among gases. This paper demonstrates curcumin reduced graphene oxide-silk field effect transistor for selective and sensitive detection of ammonia in air. The sensing layer was characterized by X-ray diffraction, FESEM and HRTEM to confirm its structural and morphological features. Raman spectroscopy, Fourier transform infrared spectroscopy and X-ray photoelectron spectroscopy was carried out to analyze the functional moieties present in the sensing layer. Curcumin reduced graphene oxide introduces sufficient hydroxyl groups in the sensing layer to provide high degree of selectivity towards ammonia vapors. The performance of the sensor device was evaluated at positive, negative and zero gate voltage. Carrier modulation in the channel through gate electrostatics revealed that the minority carriers (electrons) in p-type reduced graphene oxide plays a pivotal role in enhancement of sensitivity of the sensor device. The sensor response was enhanced to 634% for 50 ppm ammonia at 0.6 V gate voltage compared to 23.2% and 39.3% at 0 V and − 3 V respectively. The sensor exhibited faster response and recovery at 0.6 V owing to higher mobility of electrons and quick charge transfer mechanism. The sensor exhibited satisfactory humidity resistant characteristics and high stability. Hence, curcumin reduced graphene oxide-silk field effect transistor device with proper gate bias elucidates excellent ammonia detection and may be a potential candidate for future room temperature, low power, portable gas detection system.

Abstract This research proposes a data-driven approach to identify possible disparities in a utility’s outage management practices. The approach has been illustrated for an Investor-Owned Utility located in the Midwest region in the U.S. Power outage data for approximately 5 years between March 2017 and January 2022 was collected for 36 ZIP/postal codes located within the utility’s service territory. The collected data was used to calculate the total number of outages, customers affected, and the duration of outages during those 5 years for each ZIP code. Next, each variable was normalized with respect to the population density of the ZIP code. After normalizing, a K-means clustering algorithm was implemented that created five clusters out of those 36 ZIP codes. The difference in the outage parameters was found to be statistically significant. This indicated differential experience with power outages in different ZIP codes. Next, three Generalized Linear Models were developed to test if the presence of critical facilities such as hospitals, 911 centers, and fire stations, as socioeconomic and demographic characteristics of the ZIP codes, can explain their differential experience with the power outage. It was found that the annual duration of outages is lower in the ZIP codes where critical facilities are located. On the other hand, ZIP codes with lower median household income have experienced more power outages, i.e., higher outage counts in those 5 years. Lastly, the ZIP codes with a higher percentage of the White population have experienced more severe outages that have affected more customers.

Abstract The Rashba spin–orbit coupling induced quantum transport through a quantum dot embedded in a two-arm quantum loop of a quantum dot transistor is studied at finite temperature in the presence of electron–phonon and Hubbard interactions, an external magnetic field and quantum dissipation. The Anderson-Holstein-Caldeira-Leggett-Rashba model is used to describe the system and several unitary transformations are employed to decouple some of the interactions and the transport properties are calculated using the Keldysh technique. It is shown that the Rashba coupling alone separates the spin-up and spin-down currents causing zero-field spin-polarization. The gap between the up and down-spin currents and conductances can be changed by tuning the Rashba strength. In the absence of a field, the spin-up and spin-down currents show an opposite behaviour with respect to spin–orbit interaction phase. The spin-polarization increases with increasing electron–phonon interaction at zero magnetic field. In the presence of a magnetic field, the tunneling conductance and spin-polarization change differently with the polaronic interaction, spin–orbit interaction and dissipation in different temperature regimes. This study predicts that for a given Rashba strength and magnetic field, the maximum spin-polarization in a quantum dot based device occurs at zero temperature.

It is unknown whether indoles, metabolites of tryptophan that are derived entirely from bacterial metabolism in the gut, are associated with symptoms of depression and anxiety. Serum samples (baseline, 12 weeks) were drawn from participants (n = 196) randomized to treatment with cognitive behavioral therapy (CBT), escitalopram, or duloxetine for major depressive disorder. Baseline indoxyl sulfate abundance was positively correlated with severity of psychic anxiety and total anxiety and with resting state functional connectivity to a network that processes aversive stimuli (which includes the subcallosal cingulate cortex (SCC-FC), bilateral anterior insula, right anterior midcingulate cortex, and the right premotor areas). The relation between indoxyl sulfate and psychic anxiety was mediated only through the metabolite's effect on the SCC-FC with the premotor area. Baseline indole abundances were unrelated to post-treatment outcome measures, and changes in symptoms were not correlated with changes in indole concentrations. These results suggest that CBT and antidepressant medications relieve anxiety via mechanisms unrelated to modulation of indoles derived from gut microbiota; it remains possible that treatment-related improvement stems from their impact on other aspects of the gut microbiome. A peripheral gut microbiome-derived metabolite was associated with altered neural processing and with psychiatric symptom (anxiety) in humans, which provides further evidence that gut microbiome disruption can contribute to neuropsychiatric disorders that may require different therapeutic approaches. Given the exploratory nature of this study, findings should be replicated in confirmatory studies.Clinical trial NCT00360399 "Predictors of Antidepressant Treatment Response: The Emory CIDAR" https://clinicaltrials.gov/ct2/show/NCT00360399 .

Abstract We have studied the fragmentation of the brominated cyclic hydrocarbons bromocyclo-propane, bromocyclo-butane, and bromocyclo-pentane upon Br(3d) and C(1s) inner-shell ionization using coincidence ion momentum imaging. We observe a substantial yield of CH3 + fragments, whose formation requires intramolecular hydrogen (or proton) migration, that increases with molecular size, which contrasts with prior observations of hydrogen migration in linear hydrocarbon molecules. Furthermore, by inspecting the fragment ion momentum correlations of three-body fragmentation channels, we conclude that CH x + fragments (with x = 0, …, 3) with an increasing number of hydrogens are more likely to be produced via sequential fragmentation pathways. Overall trends in the molecular-size-dependence of the experimentally observed kinetic energy releases and fragment kinetic energies are explained with the help of classical Coulomb explosion simulations.