Spectra Of Complexes Research Articles

Discovery of 226 [formula omitted] Scuti and [formula omitted] Doradus Stars near NGC 6871 with TESS

We present the discovery of 269 pulsating variable stars of δ Scuti, γ Doradus, and Maia types in the vicinity of the open cluster NGC 6871, using data from the Transiting Exoplanet Survey Satellite (TESS). Our small-scale regional survey centered on the δ Scuti star V1821 Cyg in the open cluster NGC 6871, covering a radius of one degree. The results include a remarkable total of 1512 newly classified variable stars, comprising the following categories: 105 δ Scuti stars, 121 γ Doradus stars, 50 Maia variables, 198 eclipsing binary systems, with 12 exhibiting pulsating or rotating components, 500+ rotating variable stars, and dozens of other types. Out of 1512 newly discovered variable stars, 108 are confirmed members of NGC 6871 with a membership probability exceeding 50%. Notably, dedicated Fourier analyses were applied to eight representative stars from the newly discovered variables. Among these, one star exhibits a rich and complex pulsation spectrum characterized by amplitude variations in dominant pulsations. To contextualize the new pulsators, we plotted them in the Hertzsprung–Russell diagrams alongside the largest known group of class member stars. Surprisingly, both δ Scuti and γ Doradus stars occupy nearly the same region in the diagrams, hinting at a potential unified pulsation mechanism. This study contributes valuable insights into the variability census of NGC 6871 and sheds light on the pulsation behavior of different stellar types. Further investigations into the physical properties and evolutionary status of these stars are warranted.

Eco-friendly chemometric analysis: Sustainable quantification of five pharmaceutical compounds in bulk, tablets, and spiked human plasma

The development of sustainable chemometric methodologies is crucial in pharmaceutical analysis to ensure accurate chemical quantification with little environmental effect. This study introduces novel chemometric techniques for the simultaneous measurement of Rabeprazole (RAB), Lansoprazole (LAN), Levofloxacin (LEV), Amoxicillin (AMO), and Paracetamol (PAR) in various samples, including lab-prepared mixtures, tablets, and spiked human plasma. Taguchi L25 (5^5) orthogonal array design to construct the calibration and validation sets was employed, the techniques used named Principal Component Regression (PCR), Partial Least Squares (PLS-2), Artificial Neural Networks (ANNs), and Multivariate Curve Resolution-Alternating Least Squares (MCR-ALS). The models were validated for their effectiveness in resolving complex spectra from overlapping components, the models achieving high correlation coefficients (R≥0.9997) and the relative error of prediction (REP) and root mean square error of prediction (RMSEP), were (0.2221 to 0.8022) and (0.0352 to 0.1767), respectively. The bias-corrected mean square error of prediction (BCMSEP) was (−0.00065 to 0.00166). The application of various assessment tools for evaluating greenness, blueness, and whiteness offered valuable insights into the environmental impact and sustainability of the developed methods compared to the reported ones. According to the Need Quality Sustainability (NQS) index, the developed methods align with sustainable analytical practices and support the United Nations Sustainable Development Goals (UN-SDGs).

New Infrared Spectra of Acetylene-Water Dimers: First Determination of the A Rotational Constant and Another K-Dependent Anomaly.

Infrared spectra of acetylene-water complexes are studied in the regions of the H2O ν2 bend (1600 cm-1) and the D2O ν1/ν3 stretches (2670-2808 cm-1), using tunable infrared sources to probe a pulsed supersonic slit jet expansion. In the H2O bend region, there is a puzzling absence of Ka = 0 transitions for C2H2-H2O, while both Ka = 0 and 1 are observed for C2D2-H2O. This continues a pattern of "missing" Ka states noted in previous infrared studies of acetylene-water. Noticeable line broadening gives estimates of upper state predissociation lifetimes of about 1.6 ns for C2D2-H2O with Ka' = 1, 0.8 ns for C2H2-H2O with Ka' = 1, and 0.8 ns for C2D2-H2O with Ka' = 0. The lifetime for C2H2-H2O Ka' = 0 must be much shorter (<0.05 ns) since rapid predissociation seems to be the only explanation for its absence in the spectrum. In the D2O ν3 region, clear sub-bands with Ka = 0 ← 1, 1 ← 0, and 2 ← 1 are observed which enable a good determination of the A rotational constant of C2H2-D2O (7.313 ± 0.007 cm-1), a first for acetylene-water dimer and larger than previously expected.

Fluorinated‐Thiolate Osmium(III) and Osmium(IV) Complexes Bearing N,N‐diethyldithiocarbamate and Substituted Phosphines. Synthesis, Crystal Structures and DFT‐Studies

AbstractThe paramagnetic osmium(III) [Os(SRF)(S2CNEt2)2(P(C6H4X‐4)3)] (RF=C6F4H−4, C6F5; X=OCH3, CH3, F) (1–6) along with diamagnetic osmium(IV) [Os(SRF)2(S2CNEt2)2] (7–8) complexes were obtained from [Os(SRF)4(P(C6H4‐X)3)] and NaS2CNEt2, which were characterized by FAB mass spectrometry, IR spectroscopy, single crystal X‐ray diffraction, and for the diamagnetic 7 also by NMR. TD‐DFT calculations were performed to simulate the absorption spectra of complexes. In the visible region, LMCT transitions contribute to the calculated intensities, which are somewhat related to the color of the synthesized compounds. In the ultraviolet region, the phosphine ligand plays a significant role in MLCT transitions, which results in Os(III) complexes exhibiting an intense band in that region. Topological analysis and electron localization function (ELF) maps calculated for 6 and 7 confirm the strong ionic character of the Os−S coordination bonds formed by the thiophenolate and dithiocarbamate ligands. This comprehensive study provides information on the structure, bonding, and electronic properties of osmium complexes, for potential applications in catalysis, materials science, and biological systems.

Redox conditions influence the chemical composition of iron-associated organic carbon in boreal lake sediments: A synchrotron-based NEXAFS study

The global carbon and iron cycles are intimately linked as redox-sensitive iron oxides readily bind organic carbon in a variety of environmental settings, including marine and lacustrine sediments. While these iron-organic carbon complexes sequester vast quantities of organic carbon, the composition of the organic matter within them remains unknown for lacustrine environments. Here we present C K1s and Fe L3,2 edge Near Edge X-ray Absorption Fine Structure (NEXAFS) spectra of surface sediments and authigenic iron complexes from adjacent basins of a pristine boreal lake located in Québec, Canada, with contrasting oxygen exposure regimes. We demonstrate differences in organic carbon speciation in sediments from both basins, as well as co-localization of organic carbon and iron on a sub-micron scale in 100 nm thick samples. Differences in redox cycling across these two basins allow for a direct comparison of the effect of oscillating redox conditions on the composition of organic carbon sequestered by iron. Our results suggest that reactive organic molecules, which may be polysaccharides, were found preferentially associated with iron in the perennially oxic sediments compared to more phenol rich organics in the seasonally anoxic sediments, highlighting the importance of iron oxides in the protection and preservation of labile organic compounds. Traces of aliphatic carbon were observed in sediments from the anoxic basin, alongside carboxyl and aromatic functionalities. This carboxyl-rich aliphatic material could possibly interact with the sediment mineral matrix either through a ligand exchange mechanism between the mineral phases and the carboxyl functionalities, or via non-specific hydrophobic interactions involving the aliphatic moieties. Finally, our work also shows that OC:Fe ratios should be used with caution when inferring a binding mechanism between OC and iron oxides.

Interpretation of complex x-ray photoelectron peak shapes. I. Case study of Fe 2p3/2 spectra

Analyzing transition metal XPS peaks is widely used to determine surface composition and chemistry. However, these peaks have a complex structure, which is still the subject of investigation. Fe 2p analysis is a case in point where the multiplet structure and many-electron-effects lead to peak shapes that cannot be analyzed using standard approaches. Examination of the literature reveals that one of the most widely used approaches to data reduction when processing Fe 2p3/2 spectra involves using symmetric two- or three-component peak fitting with each peak effectively acting to capture a single chemical species (chemistry fit) in the complex spectra. Herein, this approach is compared to an envelope fit approach using Biesinger multiplet components of known iron oxides to determine how effective these methods are in reproducing iron oxide composition. Mixed oxide and metal XPS Fe 2p spectra were synthesized using reference spectra collected experimentally. For the first time, the accuracy and differences between the two approaches are reported. It is demonstrated that no meaningful conclusions can be drawn using single symmetric peaks to analyze complex Fe 2p3/2 spectra, implying that a large portion of the literature is flawed. The envelope fit approach, however, is shown to provide useful information regarding oxide ratios in mixed iron oxide materials, though limitations do exist. A methodology for evaluating the quality of XPS analysis of Fe 2p3/2 spectra is proposed for benchmarking new submissions so that reviewers, authors, and editors can assess these submissions.

A colorimetric Ag+ chemosensor based on a cyclometalated ruthenium complex with deprotonated 2-phenylbenzimidazole

A cyclometalated ruthenium complex (1) using 2-phenylbenzimidazole as a C,N-ligand was developed as a colorimetric chemosensor to detect Ag+ ions. Upon the addition of Ag+ ions, the absorption spectra of complex 1 demonstrated no change in CH3CN solution. However, an excellent solution color change from dark-green to purple and absorption spectral change with a blue-shift of 27 nm (from 612 to 585 nm) were clearly observed after Ag+ ions were added to the solution of 1 with 2-fold of fluoride (denoted as 1 + F−). When Ag+ ions were replaced by other common metal ions, the solution color changed from green to red. Therefore, the solution of 1 + F− can be used to distinguish Ag+ from the other common metal ions. The absorption intensity at 612 nm exhibited a good linear correlation for the detection of Ag+ ion from 0 to 4 µM with a detection limit of 0.34 µM. According to the absorption and 1HNMR spectral changes of complex 1, the reaction mechanism is proposed to be as a coordination between silver ion and the deprotonated nitrogen in imidazole. However, the interactions of other metal ions with 1 + F− are related to a proton transfer process.

Wavelength-Dependent Bragg Grating Sensors Cascade an Interferometer Sensor to Enhance Sensing Capacity and Diversification through the Deep Belief Network

Fiber-optic sensors, such as fiber Bragg grating (FBG) sensors and fiber-optic interferometers, have excellent sensing capabilities for industrial, chemical, and biomedical engineering applications. This paper used machine learning to enhance the number of fiber-optic sensing placement points and promote the cost-effectiveness and diversity of fiber-optic sensing applications. In this paper, the framework adopted is the FBG cascading an interferometer, and a deep belief network (DBN) is used to demodulate the wavelength of the sampled complex spectrum. As the capacity of the fiber-optic sensor arrangement is optimized, the peak spectra from FBGs undergoing strain or temperature changes may overlap. In addition, overlapping FBG spectra with interferometer spectra results in periodic modulation of the spectral intensity, making the spectral intensity variation more complex as a function of different strains or temperature levels. Therefore, it may not be possible to analyze the sensed results of FBGs with the naked eye, and it would be ideal to use machine learning to demodulate the sensed results of FBGs and the interferometer. Experimental results show that DBN can successfully interpret the wavelengths of individual FBG peaks, and peaks of the interferometer spectrum, from the overlapping spectrum of peak-overlapping FBGs and the interferometer.

Structural and antibacterial assessment of two distinct dihydroxy biphenyls encapsulated with β-cyclodextrin supramolecular complex

β-Cyclodextrin plays a vital role in biological application because it can enhance the stability and solubility of the guest molecules in the supramolecular inclusion complexes. Moreover, the β-Cyclodextrin inclusion complex has control-releasing behavior and lower toxicity than bare guest molecules. To improve the solubility and stability properties of two structurally different fluorescent guest molecules, namely 2,2′-dihydroxy biphenyl and 3,3′-dihydroxy biphenyls, they involve the β-Cyclodextrin inclusion complex process. Optical measurements clearly described the efficient binding through the changes in the absorbance and emission intensities of guest molecules in the presence of β-Cyclodextrin. The Job's plot from absorbance measurements reveals the 1:1 stochiometric ratio of binding of guests and the β-Cyclodextrin host. The FT-IR spectra of the solid complex show the characteristic stretching and bending vibrations from both the guests and the host molecule. The 1HNMR spectra of the inclusion complex promote downfield shifting of guest molecule protons upon binding with the β-Cyclodextrin host. The solid complex prepared using the solution method exhibits superior antibacterial activity against both gram-positive and gram-negative bacteria compared to the kneading and physical mixing methods.

Regularities and Anomalies in Neon Matrix Shifts of Hydrogen-Bonded O-H Stretching Fundamentals.

O-H bond stretching vibrations in hydrogen-bonded complexes embedded into cryogenic neon matrices are subtly downshifted from cold gas phase reference wavenumbers. To the extent that this shift is systematic, it enables neon matrices as more universally applicable spectroscopic benchmark environments for quantum chemical predictions. Outliers are indicative of either an assignment problem in one of the two cryogenic experiments or they reveal interesting dynamics or structural effects on the complexes as a function of the environment. We compile 6 literature-known pairs of experimental data in jet and neon matrix expansions and realize a 6-fold expansion of that number through targeted matrix isolation and/or slit jet expansion spectroscopy presented in this work. In many cases, the neon matrix shift is less than the uncertainty of the currently best-performing blind quantum chemical predictions for the gas phase, but in specific cases, it may exceed the currently achievable theoretical accuracy. Some evidence for a positive correlation of the matrix shift with the hydrogen bond shift is found, similar to observations for helium nanodroplets. Outliers in particular for water acting as a donor are discussed, and in a few cases they call for a future reinvestigation. Substantial improvement in the correlation of the matrix shift with the hydrogen bond shift is achieved for ketone monohydrates by removing a vibrational resonance. New insights into nitrile hydration isomerism are obtained, and the linear OH stretching spectrum of the jet-cooled ammonia-water complex is presented for the first time. Vibrational spectroscopy in weakly perturbing solid rare gas quantum matrices for the benchmarking of gas phase theory and future explicit theoretical treatments of the quantum matrix environment to better understand the outliers are both encouraged.

Bidirectional Energy Flow in the Photosystem II Supercomplex.

The water-splitting capability of Photosystem II (PSII) of plants and green algae requires the system to balance efficient light harvesting along with effective photoprotection against excitation in excess of the photosynthetic capacity, particularly under the naturally fluctuating sunlight intensity. The comparatively flat energy landscape of the multicomponent structure, inferred from the spectra of the individual pigment-protein complexes and the rather narrow and featureless absorption spectrum, is well known. However, how the combination of the required functions emerges from the interactions among the multiple components of the PSII supercomplex (PSII-SC) cannot be inferred from the individual pigment-protein complexes. In this work, we investigate the energy transfer dynamics of the C2S2-type PSII-SC with a combined spectroscopic and modeling approach. Specifically, two-dimensional electronic-vibrational (2DEV) spectroscopy provides enhanced spectral resolution and the ability to map energy evolution in real space, while the quantum dynamical simulation allows complete kinetic modeling of the 210 chromophores. We demonstrate that additional pathways emerge within the supercomplex. In particular, we show that excitation energy can leave the vicinity of the charge separation components, the reaction center (RC), faster than it can transfer to it. This enables activatable quenching centers in the periphery of the PSII-SC to be effective in removing excessive energy in cases of overexcitation. Overall, we provide a quantitative description of how the seemingly contradictory functions of PSII-SC arise from the combination of its individual components. This provides a fundamental understanding that will allow further improvement of artificial solar energy devices and bioengineering processes for increasing crop yield.

Structures and unimolecular chemistry of alkali metal cation complexes with glutathione in the gas phase

This study investigates the unimolecular reactions of glutathione complexes with alkali metal cations in the gas phase through sustained off-resonance irradiation collision-induced dissociation and examines their structures using a combination of infrared multiphoton dissociation spectroscopy and computational techniques. Under soft CID conditions, glutathione complexes with charge-dense cations such as Li⁺, Na⁺, and K⁺ show significant fragmentation of glutathione, while complexes with heavier cations, Rb⁺ and Cs⁺, primarily undergo loss of glutathione. This behavior is attributed to the stronger non-covalent binding between smaller metal cations and glutathione, which competes with the dissociation thresholds of covalent interactions within the peptide complex. Using CREST, a tool for determining trial structures which were submitted to density functional theory calculations, a thorough investigation of the conformational space revealed many possible structures, including pentacoordinated structures for the Na⁺ and K⁺ complexes, as well as tetra-tri-, bi-, and monocoordinated structures along with zwitterionic structures for all metal cation/GSH complexes. For all alkali metal cation complexes, the thermodynamically most stable structures were found to be tetracoordinated A-type structures where the metal cation is bound to the amine nitrogen and three of the carbonyl oxygens—all except O2, the amide between glycine and cysteine. These computed infrared spectra for these lowest energy complexes were also consistent with the experimental vibrational spectra in the fingerprint region. Based on relative energies and the comparison of computed and experimental infrared spectra in the fingerprint region, the tetracoordinate A-type structures are concluded to be the dominant forms of the [M(GSH)]+ complexes in the gas phase.

Improvements in precision and accuracy of complex- relative to real-domain linear combination model spectral fitting not necessarily recovered by zero filling.

Although the information obtained from in vivo proton magnetic resonance spectroscopy (1H MRS) presents a complex-valued spectrum, spectral quantification generally employs linear combination model (LCM) fitting using the real spectrum alone. There is currently no known investigation comparing fit results obtained from LCM fitting over the full complex data versus the real data and how these results might be affected by common spectral preprocessing procedure zero filling. Here, we employ linear combination modeling of simulated and measured spectral data to examine two major ideas: first, whether use of the full complex rather than real-only data can provide improvements in quantification by linear combination modeling and, second, to what extent zero filling might influence these improvements. We examine these questions by evaluating the errors of linear combination model fits in the complex versus real domains against three classes of synthetic data: simulated Lorentzian singlets, simulated metabolite spectra excluding the baseline, and simulated metabolite spectra including measured in vivo baselines. We observed that complex fitting provides consistent improvements in fit accuracy and precision across all three data types. While zero filling obviates the accuracy and precision benefit of complex fitting for Lorentzian singlets and metabolite spectra lacking baselines, it does not necessarily do so for complex spectra including measured in vivo baselines. Overall, performing linear combination modeling in the complex domain can improve metabolite quantification accuracy relative to real fits alone. While this benefit can be similarly achieved via zero filling for some spectra with flat baselines, this is not invariably the case for all baseline types exhibited by measured in vivo data.

Detection of powder samples based on UV Raman-fluorescence spectroscopy

Rapid and accurate analysis of powder samples is crucial for public safety and food security. Raman spectroscopy, noted for its many advantages, traditionally faces issues of low sensitivity and limited detection information when analyzing powder samples. This paper explores a detection method for powder samples using ultraviolet (UV) Raman-fluorescence spectroscopy. By leveraging the principles of Raman and fluorescence spectroscopy, a combined detection optical path was designed. Utilizing a 266 nm laser as the system light source, a UV Raman-fluorescence spectroscopy detection setup was constructed and seven representative powder samples were analyzed. The experimental results demonstrate that the setup effectively detects the Raman spectral features of inorganic powders like baking soda and extracts the fluorescence spectral features of organic powders such as 1,2,4,5-tetramethyltoluene. Additionally, it accurately analyzes the Raman and fluorescence spectral features of amino acids and glyphosate preparation powders. For complex powder samples with issues such as “substances with the same spectrum” and “complex and similar spectra”, UV Raman-fluorescence spectroscopy enhances spectral information dimensions, compensating for the limitations of traditional Raman spectroscopy. Furthermore, a convolutional neural network algorithm was employed to analyze the measured data of the seven powder samples increased the average recognition accuracy (AVG) from 62.53% to 98.41%. This improvement further validates the effectiveness of the proposed method in recognizing the properties of powder samples.

(Digital Presentation) New Earth-Abundant Photoelectrocatalyst and Pathway for CO2 Electroreduction

The rising levels of carbon dioxide (CO2) in the atmosphere is among the most alarming issues in today’s world: harming the environment, health, and economics of all nations on the planet. CO2 capture and its photochemical and/or photoelectrochemical reduction to fuels are promising methodologies to reduce atmospheric CO2. This is a photochemistry, electrochemistry, and catalysis problem. Transition metal complexes that can be tailored to a desired function utilizing a wide range of ligands, play a crucial role in solar fuels chemistry by reducing the activation energy for catalytic CO2 reduction to fuels. In the last decade, Mn-based complexes have sparked a significant interest owing to their abundance in Earth’s crust and lower prices compared to other transition metals. However, a catalyst that operates with high activity and turnover numbers at low overpotential is still required. We report the synthesis, characterization, and activity toward CO2 electrochemical reduction of Mn complexes containing the photoactive, electron-donating 1-imidazole-2,4,6-tri(carbazole-9-yl)-3,5-dicyanobenzene ligand (3CzImIPN). UV-vis and photoluminescence spectra of the Mn complex containing 3CzImIPN will be reported that investigate its photophysical properties under visible light. Cyclic Voltammetry (CV) studies under nitrogen and CO2 will be reported that investigate the electron transfer between the ligand and the Mn centre, as well as the electrochemical reduction of CO2. Evidence will be presented for a new, low overpotential pathway for the electroreduction of CO2 by these types of complexes. Figure 1

Stepping out of the shadows: the legitimacy of the Bahamas’ NCIA

ABSTRACT The Bahamas is a relatively small archipelago challenged by a broad spectrum of diverse, complex, and consequential national security threats that extend to the ‘unknown’ of a global security threat equation. To address the threat spectrum, Bahamian policymakers incorporated the National Crime Intelligence Agency (NCIA) within the national security architecture. For various reasons, Bahamians are sceptical about, scared of, and uncomfortable with the idea or reality of the NCIA. As such, the NCIA has to pass the legitimacy test as it steps out of the shadows. This article provides a preview into the legitimacy test of The Bahamas’ professional secret intelligence service.

Viral methyltransferase inhibitors: berbamine, venetoclax, and ponatinib as efficacious antivirals against chikungunya virus

Chikungunya virus (CHIKV), transmitted by mosquitoes, poses a significant global health threat. Presently, no effective treatment options are available to reduce the disease burden. The lack of approved therapeutics against CHIKV and the complex spectrum of chronic musculoskeletal and neurological manifestations raise significant concerns, and repurposing drugs could offer swift avenues in the development of effective treatment strategies. RNA capping is a crucial step meditated by non-structural protein 1 (nsP1) in CHIKV replication. In this study, FDA-approved antivirals targeting CHIKV nsP1 methyltransferase (MTase) have been identified by structure-based virtual screening. Berbamine Hydrochloride (BH), ABT199/Venetoclax (ABT), and Ponatinib (PT) were the top-hits, which exhibited robust binding energies. Tryptophan fluorescence spectroscopy-based assay confirmed binding of BH-, ABT-, and PT to purified nsP1 with KD values ∼5.45 μM, ∼161.3 μM, and ∼3.83 μM, respectively. In a capillary electrophoresis-based assay, a decrease in CHIKV nsP1 MTase activity was observed in a dose-dependent manner. Treatment with BH, ABT, and PT lead to a dose-dependent reduction in the virus titer with IC50 < 100, ∼6.75, and <3.9 nM, respectively, and reduced viral mRNA levels. The nsP1 MTases are highly conserved among alphaviruses; therefore, BH, ABT, and PT, as expected, inhibited replication machinery in Sindbis virus (SINV) replicon assay with IC50 ∼1.94, ∼0.23, and >1.25 μM, respectively. These results highlight the potential of repurposing drugs as rapid and effective antiviral therapeutics against CHIKV.

Receptors Involved in COVID-19-Related Anosmia: An Update on the Pathophysiology and the Mechanistic Aspects.

Olfactory perception is an important physiological function for human well-being and health. Loss of olfaction, or anosmia, caused by viral infections such as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has received considerable attention, especially in persistent cases that take a long time to recover. This review discusses the integration of different components of the olfactory epithelium to serve as a structural and functional unit and explores how they are affected during viral infections, leading to the development of olfactory dysfunction. The review mainly focused on the role of receptors mediating the disruption of olfactory signal transduction pathways such as angiotensin converting enzyme 2 (ACE2), transmembrane protease serine type 2 (TMPRSS2), neuropilin 1 (NRP1), basigin (CD147), olfactory, transient receptor potential vanilloid 1 (TRPV1), purinergic, and interferon gamma receptors. Furthermore, the compromised function of the epithelial sodium channel (ENaC) induced by SARS-CoV-2 infection and its contribution to olfactory dysfunction are also discussed. Collectively, this review provides fundamental information about the many types of receptors that may modulate olfaction and participate in olfactory dysfunction. It will help to understand the underlying pathophysiology of virus-induced anosmia, which may help in finding and designing effective therapies targeting molecules involved in viral invasion and olfaction. To the best of our knowledge, this is the only review that covered all the receptors potentially involved in, or mediating, the disruption of olfactory signal transduction pathways during COVID-19 infection. This wide and complex spectrum of receptors that mediates the pathophysiology of olfactory dysfunction reflects the many ways in which anosmia can be therapeutically managed.

The CXSFIT spectral fitting code: Past, present and future.

Magnetically confined plasma experiments generate a wealth of spectroscopic data. The first step toward extracting physical parameters is to fit a spectral model to the often complex spectra. The CXSFIT (Charge eXchange Spectroscopy FITting) spectral fitting code was originally developed for fitting charge exchange spectra on JET from the late 1980s onward and has been further developed over decades to keep up with the needs of the users. The primary use is to efficiently fit a large number of spectra with many constrained Gaussian spectral lines of which the physical parameters can be coupled in a user-friendly manner. More recent additions to the code include time-dependent couplings between parameters, flexible background subtraction, and a non-linear coupling scheme between fit parameters. The latter was a pre-requisite for implementing Zeeman and motional Stark effect multiplets in the library of spectral features. The ability to save and replay "fit recipes," even when multiple iterations are required, has ensured the traceability of the results and is one of the keys to the longevity and success of the code. The code is also in use on other tokamaks (AUG, ST-40) and to fit data from other spectroscopic diagnostics on JET. In this paper, we document the current capabilities and philosophy behind the structure of the code, including some of the algorithms used to calculate spectral features numerically efficiently. We also provide an outline of how CXSFIT could be transferred into a framework that would be able to meet the spectral fitting requirements of future devices, such as ITER.

TinyML-Raman: A novel IoT based field-deployable spectra analysis for accurate identification of pharmaceuticals and trace dye-pesticide mixtures from facile SERS method

BackgroundUpcoming inexpensive, compact Internet of Things (IoT) microcontrollers i.e., tiny-machine learning (TinyML) takes the ML driven Raman spectroscopy one step ahead for realization of more affordable and highly compact field deployable instruments. Further, lack of large spectral datasets and need for numerous specialized SERS substrates impede the development of various ML-based surface enhanced Raman spectroscopy (SERS) applications. The aim is to introduce TinyML analysis on wide range of spectra classes using customized dataset obtained with low-cost SERS. In this regard, it is vital to establish an optimum ML model and efficient data handling methodology for low memory TinyML units. ResultsWe introduce a novel TinyML methodology for accurate classification of large spectra classes with smartphone assistance for data communication and results visualization. To generate large customized spectral dataset, we present a facile, micro-drop SERS using Au colloids and reusable grooved Al substrates. The results demonstrated that memory efficient 8-bit data quantization based convolutional neural network is effective for accurate identification of 22 different spectra classes of trace dye-pesticide mixtures and pharmaceuticals. In this novel quantized data analysis on significantly varied intensity and complex variation spectra classes i.e., many individual, binary-mixtures and some with varied compositions, data normalization is shown to be powerful for improving ML classification accuracy from about 55 % to >99.5 %. Its robustness is demonstrated using inter-instrument driven data variations such as spectral shifts, high noise, and abscissa-flip, with five-fold cross validation of model performance. In addition, on-site quantification of analyte through spectral intensity is also demonstrated. SignificanceThis study opens up a new approach of ML analysis towards realization of next generation field deployable analytical instruments maintaining data privacy. It presents a detailed procedure of quantized spectral data analysis and its implementation in TinyML, attractive for various users and instrument manufacturers. The presented innovative computer-free ML analysis can be employed in all types of spectrometers, meeting the common goal of Raman spectroscopy i.e., accurate identification of complex spectra classes.