Spectral Changes Research Articles

Characterization of carbon dioxide on Ganymede and Europa supported by experiments: Effects of temperature, porosity, and mixing with water

The surfaces of icy moons are primarily composed of water ice that can be mixed with other compounds, such as carbon dioxide. The carbon dioxide (CO$_2)$ stretching fundamental band observed on Europa and Ganymede appears to be a combination of several bands that are shifting location from one moon to another. We investigate the cause of the observed shift in the CO$_2$ stretching absorption band experimentally. We also explore the spectral behaviour of CO$_2$ ice by varying the temperature and concentration. We analyzed pure CO$_2$ ice and ice mixtures deposited at 10 K under ultra-high vacuum conditions using Fourier-transform infrared (FTIR) spectroscopy and temperature programmed desorption (TPD) experiments. Laboratory ice spectra were compared to JWST observation of Europa's and Ganymede's leading hemispheres. The simulated IR spectra were calculated using density functional theory (DFT) methods, exploring the effect of porosity in CO$_2$ ice. Pure CO$_2$ and CO$_2$-water ice show distinct spectral changes and desorption behaviours at different temperatures, revealing intricate CO$_2$ and H$_2$O interactions. The number of discernible peaks increases from two in pure CO$_2$ to three in CO$_2$-water mixtures. The different CO$_2$ bands were assigned to $ nu $ (2351 cm$^ $, 4.25 mu m) caused by CO$_2$ dangling bonds (CO$_2$ found in pores or cracks) and $ nu $ (2345 cm$^ $, 4.26 mu m) due to CO$_2$ segregated in water ice, whereas $ nu $ (2341 cm$^ $, 4.27 mu m) is due to CO$_2$ molecules embedded in water ice. The JWST NIRSpec CO$_2$ spectra for Ganymede and for Europa can be fitted with two Gaussians attributed to $ nu $ and $ nu $. For Europa, $ nu $ is located at lower wavelengths due to a lower temperature. The Ganymede data reveal latitudinal variations in CO$_2$ bands, with $ nu $ dominating in the pole and $ nu $ prevalent in other regions. This shows that CO$_2$ is embedded in water ice at the poles and it is present in pores or cracks in other regions. Ganymede longitudinal spectra reveal an increase of the CO$_2$ $ nu $ band throughout the day, possibly due to ice cracks or pores caused by large temperature fluctuations.

Spectral and mass characterization of kinetic conversion from retinoids to retinoic acid in an in vitro 3-D human skin equivalent model

To investigate the effect of retinoids, such as retinol (ROL), retinal (RAL), and retinyl palmitate (RP), on epidermal integrity, skin deposition, and bioconversion to retinoic acid (RA). 3-D human skin equivalent model (EpiDermFT™) was used. Epidermal cellular integrity measured by TEER values was significantly higher for a topical treatment of ROL and RAL than RP (p < 0.05). The skin deposition (μM) of ROL and RAL was approximately 269.54 ± 73.94 and 211.35 ± 20.96, respectively, greater than that of RP (63.70 ± 37.97) over 2 h incubation. Spectral changes were revealed that the CO maximum absorbance occurred between 1600∼1800 cm−1 and was greater from ROL than that from RAL and RP, indicating conjugation of R–OH to R-CHO or R-COOH could strongly occur after ROL treatment. Subsequently, a metabolite from the bioconversion of ROL and RAL was identified as RA, which has a product ion of m/z 283.06, by using liquid a chromatography-mass spectrometry (LC-MS) - total ion chromatogram (TIC). The amount of bioconversion from ROL and RAL to RA in artificial skin was 0.68 ± 0.13 and 0.70 ± 0.10 μM at 2 h and 0.60 ± 0.04 and 0.57 ± 0.06 μM at 24 h, respectively. RA was not detected in the skin and the receiver compartment after RP treatment. ROL could be a useful dermatological ingredient to maintain epidermal integrity more effectively, more stably deposit on the skin, and more steadily metabolize to RA than other retinoids such as RAL and RP.

Detecting Moisture in Building Materials and Commercial Food adducts by 2-Hydroxy-naphthaldehyde Derived Chromo-Fluorogenic Chemosensor.

A great deal of effort has been put into developing a novel and cost-effective molecular probe for selective and sensitive recognition of trace amounts of water in organic solvents due to their tremendous advantages in industrial, pharmaceutical, and laboratory-scale chemistry. Herein, a cost-effective chemosensor L has been designed and studied for the detection of trace amounts of water. The addition of water to the DMSO solution of L exhibited an enhancement of fluorescence emission at 460nm along with a color change from green to colorless. The spectral and color changes occurred due to the self-aggregation of L. The interaction between water and L was performed by dynamic light scattering (DLS), scanning electron microscope (SEM) and finally complemented by quantum mechanical calculation. The detection limit was found to be 0.0093 wt% in DMSO. The L also exhibits a fast visual response and is effectively applied to detect trace amounts of moisture in various food materials (salt, sugar, wheat and honey) and building materials (cement, fly ash, limestone and sand).

A turn-off fluorescent sensor based on Schiff base incorporating diformyl phenol moiety for the detection of Cu2+ in aqueous solution at nanomolar level and its application in living cells

Given the critical role of trace copper ion in human health, its sensitive detection in environmental and biological samples is crucial. We, herein, designed and synthesized a diformyl phenol-based turn-off fluorescent sensor ((5-(tert-butyl)-2-hydroxy-1,3-phenylene)bis (methanylylidene)) bis (azanylylidene)) bis(4-hydroxy-2H-chromen-2-one) (MH-4)) for the spectrofluorometric detection of Cu2+ ion, which has sensitive and selective fluorescence quenching over other competitive metal ions. The efficiency and fast response of the sensor were confirmed by UV–Visible, fluorescence spectral changes, which may be due to the formation of coordination bond between MH-4 and Cu2+ ions. The binding stoichiometry of MH-4 with Cu2+ was examined with the help of UV–Vis and fluorescence titrations, and Job’s plot, which gives a 1:1 coordination stoichiometry; this is further confirmed through MS studies. The binding constant of the complex was found to be 9.4 x 107 M−1. Then, the absorbance and fluorescence-based detection limits were calculated to define the sensitivity range of the proposed sensor and were found to be 69.30 nM and 37.40 nM, respectively. Finally, a live cell image study of MH-4 in L929 (murine aneuploid fibrosarcoma) cells was also performed to test the cell permeability of MH-4 and its effectiveness for selective detection of Cu2+ in living cells.

Caffeic acid phenethyl ester (CAPE) Chitosan capped ZnO nanoparticles: Preparation, characterization, and its potential for the treatment of Prostate Cancer

The synthesis of zinc oxide nanoparticles/chitosan (ZnONPs/CS) formulation loaded with Caffeic acid phenethyl ester (CAPE) was performed to evaluate its prostate cancer treatment efficiency within the scope of this research. It has been hypothesized that a dual active materials delivery system containing ZnO and CAPE loaded Chitosan (CS) nanoparticles has better bioavailability compared to single one against to cancer cells. ZnONPs were synthesized between 45-60 nm particle sizes and then they were capped with CS biodegradable polymer prior to load with CAPE bioactive molecule. ZnONPs/CS-CAPE system was characterized by using Fourier Transform Infrared (FTIR) for structural elucidation, Scanning Electron Microscope (SEM) for particle size determination, High Performance Liquid Chromatography (HPLC) system for determination of CAPE amount. 131I CAPE and 131I ZnONPs/CS-CAPE labeled by the Iodogen method with 131I were used in in-vitro cell culture experiments. Cell viabilities (%) of CAPE and ZnONPs/CS-CAPE were examined using Cell Counting Kit-8 assay on PC-3 (human adenocarcinoma prostate), LnCaP (human carcinoma prostate), and RWPE-1 (human normal prostate). IC50 values of ZnONPs /CS -CAPE on all cells were found 2-fold lower than neat CAPE. Based on the FTIR data, the most significant spectral changes (lipid, protein, nucleic acids, glycogen) were monitored for the PC-3 and LnCaP cancer cells incubated with ZnONPs/CS-CAPE samples while being exposed to neat CAPE molecules caused small cellular changes when compared to RWPE-1 healthy cell lines.

The Effect of Starspots on Spectroscopic Age and Mass Estimates of Nonaccreting T Tauri Stars in the Taurus–Auriga Star-forming Region

Accurate age and mass determinations for young pre-main-sequence stars are made challenging by the presence of large-scale starspots. We present results from a near-infrared spectroscopic survey of 10 T-Tauri Stars in Taurus-Auriga that characterize spot-filling factors and temperatures, the resulting effects on temperature and luminosity determinations, and the consequences for inferred stellar masses and ages. We constructed composite models of spotted stars by combining BTSettl-CIFIST synthetic spectra of atmospheres to represent the spots and the photosphere along with continuum emission from a warm inner disk. Using a Markov Chain Monte Carlo algorithm, we find the best-fit spot and photospheric temperatures, spot-filling factors, as well as disk-filling factors. This methodology allowed us to reproduce the 0.75–2.40 μm stellar spectra and molecular feature strengths for all of our targets, disentangling the complicated multicomponent emission. For a subset of stars with multiepoch observations spanning an entire stellar rotation, we correlate the spectral variability and changes in the filling factors with rotational periods observed in K2 and AAVSO photometry. Combining spot-corrected effective temperatures and Gaia distances, we calculate luminosities and use the Stellar Parameters of Tracks with Starspots models to infer spot-corrected masses and ages for our sample of stars. Our method of accounting for spots results in an average increase of 60% in mass and a doubling in age with respect to traditional methods using optical spectra that do not account for the effect of spots.

Adaptive Shadow Compensation Method in Hyperspectral Images via Multi-Exposure Fusion and Edge Fusion

Shadows in hyperspectral images lead to reduced spectral intensity and changes in spectral characteristics, significantly hindering analysis and applications. However, current shadow compensation methods face the issue of nonlinear attenuation at different wavelengths and unnatural transitions at the shadow boundary. To address these challenges, we propose a two-stage shadow compensation method based on multi-exposure fusion and edge fusion. Initially, shadow regions are identified through color space conversion and an adaptive threshold. The first stage utilizes multi-exposure, generating a series of exposure images through adaptive exposure coefficients that reflect spatial shadow intensity variations. Fusion weights for exposure images are determined based on exposure, contrast, and spectral variance. Then, the exposure sequence and fusion weights are constructed as Laplacian pyramids and Gaussian pyramids, respectively, to obtain a weighted fused exposure sequence. In the second stage, the previously identified shadow regions are smoothly reintegrated into the original image using edge fusion based on the p-Laplacian operator. To further validate the effectiveness and spectral fidelity of our method, we introduce a new hyperspectral image dataset. Experimental results on the public dataset and proposed dataset demonstrate that our method surpasses other mainstream shadow compensation methods.

Chiroptical Properties of a Cryptophane Soluble at Neutral pH

AbstractThis article reports the synthesis of the two enantiomers of a water‐soluble cryptophane 3 enabling cesium and thallium complexation at neutral or basic pH. The two enantiomers of 3 were obtained in a two steps synthesis from cryptophane 4, a molecule decorated with three phenol groups and three other phenol groups protected by benzyl units. The two enantiomers of 4 were isolated from liquid chromatography using chiral stationary phase. The absolute configuration of the two enantiomers of 3 was determined by vibrational circular dichroism combined with theoretical calculations. Contrary to cryptophane 1 that present large spectroscopic changes upon cesium and thallium complexation, the electronic circular dichroism spectra of compound 3 exhibit moderate spectral changes suggesting that this compound cannot change the conformation of its linkers as easily as cryptophane 1.

Large-scale land use/land cover extraction from Landsat imagery using feature relationships matrix based deep-shallow learning

Deep learning has demonstrated its effectiveness in capturing high-level features, with convolutional neural networks (CNNs) excelling in remote sensing classification. However, CNNs encounter challenges when applied to Landsat images with limited multi-spectral bands, as they struggle to learn stable features from the spectral domain and integrate them with spatial features to enhance accuracy. Additionally, most CNN applications focus on learning features directly from the raw image, making them susceptible to spectral environment changes. To overcome these limitations, this paper introduces a novel approach for large-scale Land Use/Land Cover (LULC) extraction from Landsat OLI images. The proposed classification architecture comprises two modules. The first module utilizes a feature relationships matrix to generate an extent feature map (EFM), and a specifically designed CNN structure learns deep features from the EFM and spatial domain. In the second module, a multiple classifiers system (MCS) is employed to obtain shallow learning features, which are further enhanced by another CNN structure through continued learning. The combined features from these modules contribute to improved classification of remote sensing images. Experimental results demonstrate that our proposed method effectively acquires stable features for training deep learning models with strong generalization ability. It exhibits significant advancements in accuracy improvement and large-scale LULC extraction in the Yangtze River Economic Belt (YREB) in China, surpassing comparative approaches based on deep learning and non-deep learning methods.

Dampened circadian amplitude of EEG power in women after menopause.

Postmenopausal women are at high risk of developing sleep-wake disturbances. We previously reported dampened circadian rhythms of melatonin, alertness and sleep in postmenopausal compared with young women. The present study aims to further explore electroencephalography power spectral changes in the sleep of postmenopausal women. Eight healthy postmenopausal women were compared with 12 healthy, naturally ovulating, young women in their mid-follicular phase. Participants followed a regular 8-hr sleep schedule for ≥ 2 weeks prior to laboratory entry. The laboratory visit included an 8-hr baseline sleep period followed by an ultradian sleep-wake cycle procedure, consisting of alternating 1-hr wake periods and nap opportunities. Electroencephalography power spectral analysis was performed on non-rapid eye movement sleep obtained over a 48-hr period. The baseline nocturnal sleep of postmenopausal women comprised lower power within delta and sigma, and higher power within alpha bands compared with that of younger women. During nighttime naps of the ultradian sleep-wake cycle procedure, lower power within delta and sigma, and higher power within beta bands were observed in postmenopausal women. During the ultradian sleep-wake cycle procedure, postmenopausal women presented lower power of delta, theta and sigma (14-15 Hz), undetectable rhythms of delta and theta, and a dampened or undetectable rhythm of sigma (12-15 Hz) power compared with younger women. Our results support the hypothesis of a dampened circadian variation of sleep microstructure in healthy-sleeping postmenopausal women. Circadian changes with aging are potential mechanisms for increased susceptibility to develop sleep disturbances; however, further research is needed to clarify their clinical implications and contribution to insomnia.

Antibacterial [Zn(nicotinamide)2Cl2] complex for the treatment of skin conditions: An experimental-theoretical study of physicochemical, microbiological and in silico pharmacokinetic properties

A dichlorobis(nicotinamide)zinc(II) complex, [Zn(nicotinamide)2Cl2], was crystallized through the slow evaporation method, and its vibrational, electronic, structural, and thermal properties have been characterized. Density functional theory (DFT) was used for the accurate analysis of intramolecular vibrational modes, obtaining chemical reactivity indices and comparative studies of geometric and electronic parameters, including solvation effects in methanol, ethanol, and water, as well as in vacuum. Additionally, the nature and strength of the bonds associated with the coordination sphere (Cl–Zn and N–Zn) were elucidated from the quantum theory of atoms in molecules and natural bond orbital analyses. Powder X-ray diffraction showed that the coordination compound belongs to a monoclinic symmetry with P21/a (C2h5) space group. Thermal analyses revealed that the material is stable up to 200 °C. From DFT calculations, the complex is chemically more stable in solvents compared to vacuum conditions, with the aqueous medium offering greater stability. The chemical stability was also analyzed by infrared and Raman spectroscopy, with the results showing spectral changes mainly for the vibrational spectra obtained in methanol, ethanol, and water against those obtained in vacuum. Biological experiments showed the complex antibacterial activity against Gram-positive and Gram-negative bacteria, mainly against the Cutibacterium acnes ATCC 6919 strain. A computational study of the absorption, distribution, metabolism, excretion (ADME), and drug-likeness were calculated to support the experimental data.

Structural dynamics of the heme pocket and intersubunit coupling in the dimeric hemoglobin from Scapharca inaequivalvis.

Cooperativity is essential for the proper functioning of numerous proteins by allosteric interactions. Hemoglobin from Scapharca inaequivalvis (HbI) is a homodimeric protein that can serve as a minimal unit for studying cooperativity. We investigated the structural changes in HbI after carbon monoxide dissociation using time-resolved resonance Raman spectroscopy and observed structural rearrangements in the Fe-proximal histidine bond, the position of the heme in the pocket, and the hydrogen bonds between heme and interfacial water upon ligand dissociation. Some of the spectral changes were different from those observed for human adult hemoglobin due to differences in subunit assembly and quaternary changes. The structural rearrangements were similar for the singly and doubly dissociated species but occurred at different rates. The rates of the observed rearrangements indicated that they occurred synchronously with subunit rotation and are influenced by intersubunit coupling, which underlies the positive cooperativity of HbI.

Spectral features related to the auditory perception of twang-like voices

Background To the best of our knowledge, studies on the relationship between spectral energy distribution and the degree of perceived twang-like voices are still sparse. Through an auditory-perceptual test we aimed to explore the spectral features that may relate with the auditory-perception of twang-like voices. Methods Ten judges who were blind to the test’s tasks and stimuli rated the amount of twang perceived on seventy-six audio samples. The stimuli consisted of twenty voices recorded from eight CCM singers who sustained the vowel [a:] in different pitches, with and without a twang-like voice. Also, forty filtered and sixteen synthesized-manipulated stimuli were included. Results and conclusions Based on the intra-rater reliability scores, four judges were identified as suitable to be included in the analyses. Results showed that the frequency of F1 and F2 correlated strongly with the auditory-perception of twang-like voices (0.90 and 0.74, respectively), whereas F3 showed a moderate negative correlation (–0.52). The frequency difference between F1 and F3 showed a strong negative correlation (–0.82). The mean energy between 1–2 kHz and 2–3 kHz correlated moderately (0.51 and 0.42, respectively). The frequency of F4 and F5, and the energy above 3 kHz showed weak correlations. Since the spectral changes under 2 kHz have been associated with the jaw, lips, and tongue adjustments (i.e. vowel articulation) and a higher vertical laryngeal position might affect the frequency of all formants (including F1 and F2), our results suggest that vowel articulation and the laryngeal height may be relevant when performing twang-like voices.

Continuous Fetal Cardiac Monitoring During Fetoscopic Myelomeningocele Repair and Relationship to Spectral Doppler Changes.

No evidence-based protocols exist for fetal cardiac monitoring during fetoscopic myelomeningocele (fMMC) repair and intraprocedural spectral Doppler data is limited. We determined the feasibility of continuous fetal echocardiography during fMMC repair and correlated Doppler changes with qualitative fetal cardiac function during each phase of fMMC repair. Patients undergoing fMMC repair had continuous fetal echocardiography interpreted in real-time by pediatric cardiology. Fetal data included fetal heart rate (FHR), qualitative cardiac function, mitral and tricuspid valve inflow waveforms, and umbilical artery (UA), umbilical vein (UV), ductus arteriosus (DA) and ductus venosus (DV) Dopplers. UA abnormalities were noted in 14/25 patients, UV abnormalities were observed in two patients, and DV and DA abnormalities were each noted in 4 patients. Qualitative cardiac function was normal for all patients with the exception of one with isolated left ventricular dysfunction during myofascial flap creation, concurrent with an abnormal UA flow pattern. All abnormalities resolved by the first postoperative day. Continuous fetal echocardiography was feasible during all fMMC repairs. Spectral Doppler changes in the UA were common during fMMC procedures but qualitative cardiac dysfunction was rare. Abnormalities in the UV, DV and DA Dopplers, FHR, and cardiac function were less common findings.

Detection of pine wood nematode infestation using hyperspectral drone images

The pine wood nematode (PWN) is one of the most threatening pests of pine forests in China. An essential management response involves felling and removing the infested trees before the PWN can spread over large areas, but this requires early detection. In this study, we analyzed the temporal changes in the spectral signatures of healthy and infested trees throughout the entire growing season (May to October) using unmanned aerial vehicle (UAV) hyperspectral images (HSI). To explore the potential of these seasonal spectral changes in detecting PWN, we investigated the separability of healthy and infested trees using both absolute values and changes in values. A random forest (RF) classifier was applied to separate healthy and infested trees based on reflectances, derivatives, vegetation indices (VIs), and their seasonal change values. We obtained the following results: (1) the seasonal changes of tree crown spectra following a PWN infestation were similar to those observed using absolute spectral values, though the latter performed better in early detection; (2) in the early stage of infestation (June and July), the green and red-edge regions contained the most sensitive bands, whereas the near-infrared portion played a more important role in later stages; (3) derivatives achieved higher overall accuracy (OA) than the reflectance in the early stage of PWN infestation (June and July); (4) in June, the Pigment Specific Simple Ratio (PSSR) had the highest separability (OA = 0.77) for PWN infestation, followed by the Plant Senescence Reflectance Index (PSRI) and the Normalized Difference Red-edge Index (NDRE), both with a OA of 0.70. In July, PSRI, Red Edge Normalized Difference Vegetation Index (RENDVI), and the Modified Red Edge Simple Ratio (MRESR) had the highest OA of 0.77. These VIs were calculated based on the red-edge regions. In August, RENDVI achieved the best accuracy (0.87), followed by the Normalized Difference Vegetation Index (NDVI, OA = 0.83) and the Plant Stress Index (PSI, OA = 0.80). In September and October, PSRI, PSI, the Greenness Index (GI), and RENDVI showed the strongest separability (0.87 to 0.90). Similar results were obtained using change values of VIs. In June, RENDVI, PSI, and NDVI showed the highest accuracy (OA = 0.73). In July, MRESR had the best accuracy (0.77), followed by RENDVI (0.73) and PSI (0.73). In the late stage of PWN infestation, NDVI, PSRI, PSI, RENDVI, GI, and PSSR obtained the highest accuracies (0.83 to 0.93), surpassing the accuracy achieved using absolute spectra; (5) in RF classification model, seasonal variation values derived from reflectances, derivatives, and VIs performed well in the late stages of the PWN infestation (September and October) but were not as good as absolute values in the early and middle stages (June to August). Our study explored the potential of seasonal changes in UAV spectra for early detection of forest pests.

A thiazole-based colorimetric and photoluminescent chemosensors for As3+ ions detection: Density functional theory, test strips, real samples, and bioimaging applications

A Schiff-base Ethyl (E)-2-(3-((2-carbamothioylhydrazono)methyl)-4-hydroxyphenyl)-4-methylthiazole-5-carboxylate (TZTS) dual functional colorimetric and photoluminescent chemosensor which includes thiazole and thiosemicarbazide has been synthesized to detect arsenic (As3+) ions selectively in DMSO: H2O (7:3, v/v) solvent system. The molecular structure of the probe was characterized via FT-IR, 1H, and 13C NMR & HRMS analysis. Interestingly, the probe exhibits a remarkable and specific colorimetric and photoluminescence response to As3+ ions when exposed to various metal cations. The absorption spectral changes of TZTS were observed upon the addition of As3+ ions, with a naked eye detectable color change from colorless to yellow color. Additionally, the chemosensor (TZTS) exhibited a new absorption band at 412 nm and emission enhancements in photoluminescence at 528 nm after adding As3+ ions. The limit of detection (LOD) for As3+ ions was calculated to be 16.5 and 7.19 × 10−9 M by the UV–visible and photoluminescent titration methods, respectively. The underlying mechanism and experimental observations have been comprehensively elucidated through techniques such as Job’s plot, Benesi-Hildebrand studies, and density functional theory (DFT) calculations. For practical application, the efficient determination of As3+ ions were accomplished using a spike and recovery approach applied to real water samples. In addition, the developed probe was successfully employed in test strip applications, allowing for the naked-eye detection of arsenic ions. Moreover, fluorescence imaging experiments of As3+ ions in the breast cancer cell line (MCF-7) demonstrated their practical applications in biological systems. Consequently, these findings highlight the significant potential of the TZTS sensor for detecting As3+ ions in environmental analysis systems.

Spectral changes in skin blood flow during pressure manipulations or sympathetic stimulation.

Skin blood flow is commonly determined by laser Doppler flowmetry (LDF). It has been suggested that pathophysiological conditions can be assessed by analysis of specific frequency domains of the LDF signals. We tested whether physiological stimuli that activate myogenic and neurogenic mechanisms would affect relevant portions of the laser Doppler spectrum. LDF sensors were placed on the right forearm of 14 healthy volunteers for myogenic (six females) and 13 for neurogenic challenge (five females). Myogenic responses were tested by positioning the arm ∼50° above/below heart level. Neurogenic responses were tested by immersing the left hand into an ice slurry with and without topical application of local anaesthetic. Short-time Fourier analyses were computed over the range of 0.06 to 0.15Hz for myogenic and 0.02 to 0.06Hz for neurogenic. No significant differences in spectral density were observed (P=0.40) in the myogenic range with arm above (7±54×10-4dB) and below heart (7±14×10-4dB). Neurogenic spectral density showed no significant increase from baseline to cold pressor test (0.0017±0.0013 and 0.0038±0.0039dB; P=0.087, effect size 0.47). After application of anaesthetic, neurogenic spectral density was unchanged between the baseline and cold pressor test (0.0014±0.0025 and 0.0006±0.0005dB; P=0.173). These results suggest that changes in the myogenic and neurogenic spectral density of LDF signals did not fully reflect the skin vascular function activated by pressure manipulation and sympathetic stimulation. Therefore, LDF myogenic and neurogenic spectral density data should be interpreted with caution.

Colorimetric Silver Ion Detection Based on Silver Metallization of Gold Nanorods

AbstractDespite the use of silver in various industries, this heavy metal can pose serious risks to living organisms and the environment. Therefore, the development of simple measurement strategies for detection of silver ions (Ag+) with high sensitivity is of great importance. In this research, gold nanorods (AuNRs) have been used as indicator element in colorimetric sensor, which provides the possibility of facile and visual detection of silver by forming gold@silver core‐shell nanostructures (Au@Ag NRs). The basis of this sensor is the metallization of silver on AuNRs through ascorbic acid (AA) as a reducing agent, which forms Au@Ag NRs. During this mechanism, Ag+ is converted to silver atom (Ago) in the presence of AA and the surface of AuNRs is coated by inducing metallization. Any changes in composition and dimensions of AuNRs will cause color changes in the detection solution and subsequently spectral changes. The obtained results showed a good correlation between silver concentration and probe response (λo–λ) in the range of 2.5 to 30.0 μmol L−1 with a detection limit of 1.3 μmol L−1. In addition, the evaluation of the sensor in water and soil samples showed that it has acceptable accuracy in detecting silver ions in real conditions.

Thermodynamics of oligomerization and Helix-to-sheet structural transition of amyloid β-protein on anionic phospholipid vesicles

Understanding oligomerization and aggregation of the amyloid-β protein is important to elucidate the pathological mechanisms of Alzheimer's disease, and lipid membranes play critical roles in this process. In addition to studies reported by other groups, our group has also reported that the negatively-charged lipid bilayers with a high positive curvature induced α-helix-to-β-sheet conformational transitions of amyloid-β-(1–40) upon increase in protein density on the membrane surface and promoted amyloid fibril formation of the protein. Herein, we investigated detailed mechanisms of the conformational transition and oligomer formation of the amyloid-β protein on the membrane surface. Changes in the fractions of the three protein conformers (free monomer, membrane-bound α-helix-rich conformation, and β-sheet-rich conformation) were determined from the fluorescent spectral changes of the tryptophan probe in the protein. The helix-to-sheet structural transition on the surface was described by a thermodynamic model of octamer formation driven by entropic forces including hydrophobic interactions. These findings provide useful information for understanding the self-assembly of amyloidogenic proteins on lipid membrane surfaces.

Communication spectrum prediction method based on convolutional gated recurrent unit network

In modern wireless communication systems, the scarcity of spectrum resources poses challenges to the performance and efficiency of the system. Spectrum prediction technology can help systems better plan and schedule resources to respond to the dynamic changes in spectrum. Dynamic change in the spectrum refers to the changes in the radio spectrum in a wireless communication system. It means that the available spectrum resources may change at different times and locations. In response to this current situation, this study first constructs a communication collaborative spectrum sensing model using channel aliasing dense connection networks. Then, combining convolutional neural network and gated cyclic unit network in deep learning technology, a communication spectrum prediction model is built. It aims to achieve accurate perception and prediction of spectrum resources through the aforementioned spectrum sensing and prediction models. The results confirm that the proposed perception model has inconsistent perception accuracy under different number of secondary users, with a maximum of 0.99. It is verified that the proposed spectrum prediction model achieves a high prediction accuracy of 0.95 within 208 s and its performance outperforms current similar models. The results are based on the model's deep learning analysis of massive historical communication data, in which the optimized shuffle dense net model plus convolutional gated recurrent unit model is the key to achieve fast and accurate prediction. On the contrary, the highest spectrum prediction accuracy of Recurrent Neural Network (RNN), Long Short-Term Memory (LSTM), and Convolutional Neural Networks-Long Short-Term Memory (ConvLSTM) models are 0.86, 0.90, and 0.85, respectively. And the model needs to run for a longer period of time, up to 324, for ConvLSTM to reach the prediction accuracy value of 0.95. In summary, the perception and prediction model built by this research has good performance, and its application in the field of wireless communication can assist staff in better monitoring spectral changes, thereby making more efficient use of spectral resources.