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Watson transform in quantum scattering
Abstract The scattering of high-energy quantum particles by nanoinclusions into crystalline lattices is studied. Since the typical size of the grid impurity is much larger compared to the wavelength of the produced matter waves, the canonical solutions for the wave functions given as series of spatial harmonics, converge very poorly. Therefore, Watson transform is employed to provide equivalent series that involve complex-ordered Hankel functions and possess a hugely better convergence rate. In this way, the use of a versatile tool is demonstrated allowing for rigorously solving and understanding particle interactions that occur within various research domains: from quantum emission and interference to molecular fluctuations and quantum signal processing.
Elucidating the activation mechanism of botulinum neurotoxin a: role of α-clostripain and NTNH
Tectorigenin induces vasorelaxation in porcine coronary arteries through activation of Kv channels and oestrogen receptor modulation
Enhanced SWIR photodetection in Te0.7Se0.3 alloy based phototransistors with spectral range of 1300 nm via dual-gate engineering
Dissecting lncRNA-mRNA regulatory network in type 2 diabetes as the risk factor of pancreatic cancer
PS3N: leveraging protein sequence-structure similarity for novel drug-drug interaction discovery
Combining antigenic data from public sources gives an early indication of the immune escape of emerging virus variants
Abstract The rapid spread of the Omicron BA.1 (B.1.1.529.1) SARS-CoV-2 (Severe Acute Respiratory Syndrome Coronavirus 2) variant in 2021 resulted in international efforts to quickly assess its escape from immunity generated by vaccines and previous infections. Numerous laboratories published BA.1 neutralization data as preprints and reports. We collated this data in real time and regularly presented updates of the aggregated results in US, European and WHO research and advisory settings. Here, we retrospectively analyzed the accuracy of these aggregations from 85 different sources published during a time period from 2021/12/08 up to 2022/08/14. We found that the mean titer fold change from wild type-like variants to BA.1, a standard measure of a variant’s immune escape, remained stable after the first 15 days of data reporting in people who were twice vaccinated, and incoming data increased the confidence in this quantity. Further, it is possible to build reliable, stable antigenic maps from this collated data already after one month of incoming data. We here demonstrate that combining early reports from variable, independent sources can rapidly indicate a new virus variant’s immune escape and can therefore be of immense benefit for public health.
Space-time spatial channel modulation with multiple constellations
Abstract In this paper, a new schematic of spatial channel modulation aided space-time block code (STBC-SCM), which is to exploit more additional information with both the hybrid constellations group indexes (CGI) and the channel state indexes, is proposed to achieve the higher spectral efficiency and the improvement of the bit error rate (BER) performance. Specifically, four groups of mixing two signal constellations are designed for the selection of two CGI bits and encoded into one STBC codeword. Then, it is modulated on two active transmit antennas (TAs) using the antenna index (AI) bits. Furthermore, its two symbols on each active TAs are transmitted over the specified channel states with two independent parts of channel index (CI) bits, respectively. Finally, the minimum Euclidean distances with each time-slot, the detection complexity and the bit error probability are analyzed. Simulation results are shown that the performance improvement for the STBC-SCM is obviously achieved over other traditional schemes such as space-time channel modulation (STCM) and quadrature spatial modulation aided media based modulation (QSM-MBM).
Biological applications of yttrium oxide nanocomposites synthesized from Aspergillus penicillioides and their potential role in environmental remediation
Abstract Industrial effluent contains hazardous metals, such as lead and nickel, which must be removed to prevent serious illnesses. The biological production of nanocomposites, which utilizes a range of biological resources, including microbes and plant extracts, as reducing and stabilizing agents, has garnered considerable attention in recent years. The goal of the current study is to generate Y 2 O 3 nanocomposites in a unique, feasible, and biodegradable manner by using biological substances for the remediation of lead and nickel in the wastewater. The characterization outcomes demonstrated that Aspergillus penicillioides was capable of extracellular synthesis of Y 2 O 3 nanocomposites with a spherical shape, and their size ranges from 31.4 to 61.9 nm. Furtherly, FTIR reveals that the existence of fungal biomolecules plays a vital role in the synthesis of the nanocomposite. The Y 2 O 3 nanocomposites exhibited an excellent adsorption rate of 60% for lead and nickel at concentrations of 4 µg/mL and 2 µg/mL, respectively, under a pH of 6, thus demonstrating their efficacy as a catalyst in the photocatalytic reduction of these metals. The Freundlich adsorption isotherm validated multilayer adsorption on a heterogeneous surface with changing adsorption energies, whereas the constant parameter in the reaction was identified by pseudo-first-order kinetics. AAS is employed to determine the concentrations of desired metal ions. The biological applications, which include antibiotic activity, bacterial protein leakage, and antioxidant activity, were demonstrated. Biocompatibility of the Y 2 O 3 nanocomposite was determined by the hemolytic assay. Ultimately, our study exhibits the novel bio-based Aspergillus penicillioides -arbitrated Y 2 O 3 nanocomposites that work well as a bioremediating agent.
Heterotrophic denitrification for the simultaneous reduction of nitrates using acorn cups as an energy source
Seismic stability analysis of cracked compound slopes considering soil heterogeneity
Predicting student academic achievement using stacked ensemble learning with deep neural networks and fuzzy-based feature selection
Localization and persistent currents in a quasiperiodic disordered helical lattice
Long-term exposure to ambient air pollution and cardiometabolic multimorbidity in Chinese adults over 45 years
Cold atmospheric plasma restores fulvestrant sensitivity by inhibiting CCND3 in the drug-resistant breast cancer cells
Analytical and clinical comparison of four SLE-associated autoantibodies in different autoimmune diseases
AI-powered prediction of hybrid nanofluid dynamics over a cylinder via LM optimized neural network approach
Association of dietary omega-3 fatty acids intake with all-cause and cardiovascular disease-specific mortality among individuals with cardiovascular disease
Comparative analysis of milk bacteria by two MALDI-MS systems
Abstract This study presents a comparative analysis of bacterial strains isolated from raw milk using two. MALDI-TOF MS systems: the Bruker Microflex LT Biotyper and the newer Zybio EXS2600 Ex-Accuspec. A total of 1,130 isolates were identified using the in-tube extraction method. The aim of the study was to assess identification accuracy at the genus and species levels. Both systems demonstrated high performance: the Bruker system identified 94.6% of the isolates to at least the genus level, and the Zybio system identified 91.3%. Both MALDI systems showed a high level of agreement at the species level - approximately 75% of Bruker identifications matched those obtained with the Zybio system. In the remaining ~ 25% of cases, discrepancies were observed at both the species and genus levels. The results indicate that both systems offer a comparable level of effectiveness for routine use. in microbiological diagnostics.