Formation of robust bound states of interacting microwave photons.

Systems of correlated particles appear in many fields of modern science and represent some of the most intractable computational problems in nature. The computational challenge in these systems arises when interactions become comparable to other energy scales, which makes the state of each particle depend on all other particles1. The lack of general solutions for the three-body problem and acceptable theory for strongly correlated electrons shows that our understanding of correlated systems fades when the particle number or the interaction strength increases. One of the hallmarks of interacting systems is the formation of multiparticle bound states2-9. Here we develop a high-fidelity parameterizable fSim gate and implement the periodic quantum circuit of the spin-½ XXZ model in a ring of 24 superconducting qubits. We study the propagation of these excitations and observe their bound nature for up to five photons. We devise a phase-sensitive method for constructing the few-body spectrum of the bound states and extract their pseudo-charge by introducing a synthetic flux. By introducing interactions between the ring and additional qubits, we observe an unexpected resilience of the bound states to integrability breaking. This finding goes against the idea that bound states in non-integrable systems are unstable when their energies overlap with the continuum spectrum. Our work provides experimental evidence for bound states of interacting photons and discovers their stability beyond the integrability limit.

Accurately computing the electronic properties of a quantum ring.

A promising approach to study condensed-matter systems is to simulate them on an engineered quantum platform1-4. However, the accuracy needed to outperform classical methods has not been achieved so far. Here, using 18 superconducting qubits, we provide an experimental blueprint for an accurate condensed-matter simulator and demonstrate how to investigate fundamental electronic properties. We benchmark the underlying method by reconstructing the single-particle band structure of a one-dimensional wire. We demonstrate nearly complete mitigation of decoherence and readout errors, and measure the energy eigenvalues of this wire with an error of approximately 0.01 rad, whereas typical energy scales are of the order of 1 rad. Insight into the fidelity of this algorithm is gained by highlighting the robust properties of a Fourier transform, including the ability to resolve eigenenergies with a statistical uncertainty of 10-4 rad. We also synthesize magnetic flux and disordered local potentials, which are two key tenets of a condensed-matter system. When sweeping the magnetic flux we observe avoided level crossings in the spectrum, providing a detailed fingerprint of the spatial distribution of local disorder. By combining these methods we reconstruct electronic properties of the eigenstates, observing persistent currents and a strong suppression of conductance with added disorder. Our work describes an accurate method for quantum simulation5,6 and paves the way to study new quantum materials with superconducting qubits.

Interaction of sugar stabilised silver nanoparticles with Momordica charantia seed lectin, a type II ribosome inactivating protein.

Sugar-stabilised nanomaterials have received a lot of attention in cancer therapy in recent years due to their pronounced application as specific targeting agents and maximizing their therapeutic potential while bypassing off-target effects. Lectins, the carbohydrate-binding proteins, are capable of binding to receptors present on the target cell/tissue and interact with transformed glycans better than normal cells. Besides some of the lectins exhibit anticancer activity. Conjugating sugar-stabilised NPs with lectins there for is expected to multiply the potential for the early diagnosis of cancer cells and the specific release of drugs into the tumor site. Because of the prospective applications of lectin-sugar-stabilised nanoparticle conjugates, it is important to understand their molecular interaction and physicochemical properties. Momordica charantia Seed Lectin (MCL) is a type II RIP and has been known as an anti-tumor agent. Investigation of the interaction between sugar-stabilised silver nanoparticles and MCL has been performed by fluorescence spectroscopy to explore the possibility of creating an effective biocompatible drug delivery system against cancer cells. In this regard interaction between lectin and NPs should be well-preserved, while recognizing the specific cell surface sugar. Therefore experiments were carried out in the presence and absence of specific sugar galactose. Protein intrinsic fluorescence emission is quenched at ~ 20% at saturation during the interaction without any significant shift in fluorescence emission maximum. Binding experiments reveal a good affinity. Tetrameric MCL binds to a single nanoparticle. Stern-Volmer analysis of the quenching data suggests that the interaction is via static quenching leading to complex formation. Hemagglutination experiments together with interaction studies in the presence of specific sugar show that the sugar-binding site of the lectin is distinct from the nanoparticle-binding site and cell recognition is very much intact even after binding to AgNPs. Our results propose the possibility of developing MCL-silver nanoparticle conjugate with high stability and multiple properties in the diagnosis and treatment of cancer.

Physiological and antioxidant responses associated with Sub1 gene introgressed rice (Oryza sativa L.) lines under complete submergence.

Rice is the only crop which is well adapted to aquatic environment but, it is unable to survive if completely submerged for several weeks. Breeding rice varieties with submergence tolerance is one of the best approaches to alleviate the adverse effect of submergence which requires the introgression of Sub1 gene into elite rice varieties. Hence, the study was undertaken to introgress submergence tolerant gene into the rice variety Jaya through Marker-Assisted Backcross Breeding. Also the physiological and biochemical responses like survival percentage, underwater shoot elongation, total carbohydrate content and superoxide dismutase activity were also studied in Sub1 introgressed lines. We could develop twenty Sub1 introgressed lines with Sub1 region of 3.1-5.1mb and with 80.0- 95.3% recurrent parent genome recovery. Sub1 introgressed Jaya lines and the tolerant checks FR13A and Swarna Sub1 had lower shoot elongation under water, higher superoxide dismutase activity (about 5 times) upto 4 h after de-submergence which resulted in higher survival percentage. The reduced shoot elongation of tolerant varieties reduced the utilization of stored carbohydrate. Through our research we introgressed Sub1 gene into rice variety Jaya through Marker-Assisted Backcross Breeding and could study the physiological responses under submergence by which we confirmed the presence of Sub1 gene in these lines. These lines could be field evaluated and could be released as a new variety thus helping the farmers of flood prone areas of Kerala.

Phosphorus cycling from a coastal upwelling zone in the Southeastern Arabian Sea.

The present study examined the seasonal cycling of phosphorous (P) along the southwest coast of India (SWCI) based on two cruises during the southwest monsoon (SWM) and northeast monsoon (NEM) of 2018. During SWM, the entire SWCI experienced intense upwelling manifested by the incursion of cold, nutrient-rich, and hypoxic waters. During NEM, the region was transformed into a warm, well-oxygenated and nutrient-deplete environment. Dissolved inorganic phosphorus (DIP) was significantly high in the subsurface during SWM due to its release from sediments. The sediment P was high and showed an increasing trend towards the south, principally dependent on the sediment texture, organic carbon, and Fe concentrations. Bioavailable P, the sum of exchangeable (PEx) and reducible (PFe) fractions, was almost consistent (5-20%) over seasons, though PFe showed a marked reduction during SWM. Authigenic fraction (PAut) was the most dominant (46%), followed by detrital (PDet 41%) and residual (PRes 8%) fractions. Principal component analysis (PCA) of geochemical parameters for SWM was indicative of the high dissolution of Fe (oxy)hydroxides under hypoxia releasing P and its complexation with organic matter and Fe. PCA results for the NEM were different, as it indicated increased preservation of P-associated organic matter and Fe, alternately favouring the formation of PAut in sediments. The study's significance is the observation that the bottom water oxygen concentration can significantly influence sedimentary P cycling in tropical coastal upwelling zones.

Demonstrating a Continuous Set of Two-Qubit Gates for Near-Term Quantum Algorithms.

Quantum algorithms offer a dramatic speedup for computational problems in material science and chemistry. However, any near-term realizations of these algorithms will need to be optimized to fit within the finite resources offered by existing noisy hardware. Here, taking advantage of the adjustable coupling of gmon qubits, we demonstrate a continuous two-qubit gate set that can provide a threefold reduction in circuit depth as compared to a standard decomposition. We implement two gate families: an imaginary swap-like (iSWAP-like) gate to attain an arbitrary swap angle, θ, and a controlled-phase gate that generates an arbitrary conditional phase, ϕ. Using one of each of these gates, we can perform an arbitrary two-qubit gate within the excitation-preserving subspace allowing for a complete implementation of the so-called Fermionic simulation (fSim) gate set. We benchmark the fidelity of the iSWAP-like and controlled-phase gate families as well as 525 other fSim gates spread evenly across the entire fSim(θ,ϕ) parameter space, achieving a purity-limited average two-qubit Pauli error of 3.8×10^{-3} per fSim gate.

Diabatic Gates for Frequency-Tunable Superconducting Qubits.

We demonstrate diabatic two-qubit gates with Pauli error rates down to 4.3(2)×10^{-3} in as fast as 18 ns using frequency-tunable superconducting qubits. This is achieved by synchronizing the entangling parameters with minima in the leakage channel. The synchronization shows a landscape in gate parameter space that agrees with model predictions and facilitates robust tune-up. We test both iswap-like and cphase gates with cross-entropy benchmarking. The presented approach can be extended to multibody operations as well.

Fluctuations of Energy-Relaxation Times in Superconducting Qubits.

Superconducting qubits are an attractive platform for quantum computing since they have demonstrated high-fidelity quantum gates and extensibility to modest system sizes. Nonetheless, an outstanding challenge is stabilizing their energy-relaxation times, which can fluctuate unpredictably in frequency and time. Here, we use qubits as spectral and temporal probes of individual two-level-system defects to provide direct evidence that they are responsible for the largest fluctuations. This research lays the foundation for stabilizing qubit performance through calibration, design, and fabrication.

Rapid profiling and structural characterization of bioactive compounds and their distribution in different parts of Berberis petiolaris Wall. ex G. Don applying hyphenated mass spectrometric techniques.

RATIONALE: Berberis petiolaris Wall. is a lesser known medicinal plant, belonging to the family Berberidaceae. The genus Berberis is known for many biological activities such as anti-microbial, anti-inflammatory and anti-diarrheal, etc. There are not many reports of the isolation of components from Berberis petiolaris. This study aims to seek identification, characterization and quantification of components. METHODS: A method was developed for rapid screening of phytochemicals using high-pressure liquid chromatography hyphenated with quadrupole time-of-flight mass spectrometry (HPLC/ESI-QTOF-MS/MS). Suitable collision-induced dissociation mass spectrometry (CID-MS/MS) methods were developed for structural investigation of alkaloids, flavanoids and other classes of compounds using nine reference standards for authentication. Multiple reaction monitoring (MRM) methods were developed for quantitative study of five constituents using triple quadrupole-linear ion trap mass spectrometry (UPLC/QqLIT-MS/MS). RESULTS: On the basis of HPLC retention behavior and fragmentation pathways obtained by high-resolution MS and MS/MS, 32 compounds were identified and characterized in different parts of Berberis petiolaris. Quantitative studies of chlorogenic acid, magnoflorine, jatrorrhizine, palmatine and berberine were also completed successfully. CONCLUSIONS: Rapid and accurate HPLC/ESI-QTOF-MS/MS and UPLC/ESI-QqLIT-MS/MS methods were established for identification, characterization and quantification of phytochemicals in the ethanolic extract of Berberis petiolaris. These methods, therefore, can be used for studies on phytochemical variation in different parts of the plant. Principle components analysis (PCA) may be used for plant part discrimination.

CNN-O-ELMNet: Optimized Lightweight and Generalized Model for Lung Disease Classification and Severity Assessment.

The high burden of lung diseases on healthcare necessitates effective detection methods. Current Computer-aided design (CAD) systems are limited by their focus on specific diseases and computationally demanding deep learning models. To overcome these challenges, we introduce CNN-O-ELMNet, a lightweight classification model designed to efficiently detect various lung diseases, surpassing the limitations of disease-specific CAD systems and the complexity of deep learning models. This model combines a convolutional neural network for deep feature extraction with an optimized extreme learning machine, utilizing the imperialistic competitive algorithm for enhanced predictions. We then evaluated the effectiveness of CNN-O-ELMNet using benchmark datasets for lung diseases: distinguishing pneumothorax vs. non-pneumothorax, tuberculosis vs. normal, and lung cancer vs. healthy cases. Our findings demonstrate that CNN-O-ELMNet significantly outperformed (p < 0.05) state-of-the-art methods in binary classifications for tuberculosis and cancer, achieving accuracies of 97.85% and 97.70%, respectively, while maintaining low computational complexity with only 2481 trainable parameters. We also extended the model to categorize lung disease severity based on Brixia scores. Achieving a 96.20% accuracy in multi-class assessment for mild, moderate, and severe cases, makes it suitable for deployment in lightweight healthcare devices.

Occurrence, sources and risk assessment of polycyclic aromatic hydrocarbons in the coral reef waters of the Lakshadweep Archipelago, Arabian Sea.

The compound effects of anthropogenic disturbances on global and local scales threaten coral reef ecosystems of the Arabian Sea. The impacts of organic pollutants on the coral reefs and associated organisms have received less attention and are consequently less understood. This study examines the background levels, sources, and ecological implications of polycyclic aromatic hydrocarbons (PAHs) in the coral reef ecosystems of Lakshadweep Archipelago. Water and particulate matter were collected from four coral Islands (Kavaratti, Agatti, Bangaram and Perumal Par) of Lakshadweep Archipelago during January and December 2022 and analysed for 15 PAHs priority pollutants. The 15 PAHs congeners generally ranged from 2.77 to 250.47 ng/L in the dissolved form and 0.44 to 6469.86 ng/g in the particulate form. A comparison of available data among the coral reef ecosystems worldwide revealed relatively lower PAHs concentrations in the Lakshadweep coral ecosystems. The isomeric ratios of individual PAH congeners and principal component analysis (PCA) indicate mixed sources of PAHs in the water column derived from pyrogenic, low-temperature combustion and petrogenic. The risk quotient (RQ) values in the dissolved form indicate moderate risk to the aquatic organisms, while they indicate moderate to severe risk in the particulate form.

Distribution and sea-to-air fluxes of nitrous oxide and methane from a seasonally hypoxic coastal zone in the southeastern Arabian Sea.

The seasonal variability, pathways, and sea-to-air fluxes of nitrous oxide (N2O) and methane (CH4) in the coastal environment, where coastal upwelling and mudbanks co-exist are presented based on the monthly time-series measurements from November 2021 to December 2022. Upwelling-driven hypoxic water's shoreward propagation and persistence were the major factors controlling the N2O concentrations, while the freshwater influx and sedimentary fluxes modulate CH4 concentrations. The N2O concentrations were high during the southwest monsoon (up to 35 nM; 19 ± 8 nM)), followed by spring inter-monsoon (up to 19 nM; 10 ± 5 nM), and lowest during the northeast monsoon (up to 13 nM; 8 ± 2 nM), whereas the CH4 levels were high during the spring inter-monsoon (8.4 to 65 nM), followed by southwest monsoon (6.8 to 53.1 nM) and relatively lower concentrations during the northeast monsoon (3.3 to 32.6 nM). The positive correlations of excess N2O with Apparent Oxygen Utilisation (AOU) and the sum of nitrate and nitrite (NOx) indicate that nitrification is the primary source of N2O in the mudbank regime. The negative correlation of CH4 concentrations with salinity indicates considerable input of CH4 through freshwater influx. CH4 exhibited a highly significant positive correlation with Chlorophyll-a throughout the study period. Furthermore, it displayed a statistically significant positive correlation with phosphate (PO43-) during the northeast monsoon while a strong negative correlation with PO43- during the spring inter-monsoon, pointing towards the role of aerobic CH4 production pathways in the mudbank regime. N2O and CH4 exhibited a contrasting seasonal pattern of sea-to-air fluxes, characterised by the highest N2O fluxes during the southwest monsoon (hypoxia) (13 ± 10 µM m-2 d-1), followed by spring inter-monsoon (12 ± 16 µM m-2 d-1), and the lowest during the northeast monsoon (0.6 ± 3 µM m-2 d-1). Conversely, the highest sea-to-air fluxes of CH4 were noticed during the spring inter-monsoon (74 ± 56 µM m-2 d-1), followed by the southwest monsoon (45 ± 35 µM m-2 d-1), and the lowest values during the northeast monsoon (19 ± 16 µM m-2d-1). Long-term time-series measurements will be invaluable in understanding the longer-term impacts of climate-driven variability on marine biogeochemical cycles in dynamic nearshore systems.

Dynamics of magnetization at infinite temperature in a Heisenberg spin chain.

Understanding universal aspects of quantum dynamics is an unresolved problem in statistical mechanics. In particular, the spin dynamics of the one-dimensional Heisenberg model were conjectured as to belong to the Kardar-Parisi-Zhang (KPZ) universality class based on the scaling of the infinite-temperature spin-spin correlation function. In a chain of 46 superconducting qubits, we studied the probability distribution of the magnetization transferred across the chain's center, [Formula: see text]. The first two moments of [Formula: see text] show superdiffusive behavior, a hallmark of KPZ universality. However, the third and fourth moments ruled out the KPZ conjecture and allow for evaluating other theories. Our results highlight the importance of studying higher moments in determining dynamic universality classes and provide insights into universal behavior in quantum systems.

Stable quantum-correlated many-body states through engineered dissipation.

Engineered dissipative reservoirs have the potential to steer many-body quantum systems toward correlated steady states useful for quantum simulation of high-temperature superconductivity or quantum magnetism. Using up to 49 superconducting qubits, we prepared low-energy states of the transverse-field Ising model through coupling to dissipative auxiliary qubits. In one dimension, we observed long-range quantum correlations and a ground-state fidelity of 0.86 for 18 qubits at the critical point. In two dimensions, we found mutual information that extends beyond nearest neighbors. Lastly, by coupling the system to auxiliaries emulating reservoirs with different chemical potentials, we explored transport in the quantum Heisenberg model. Our results establish engineered dissipation as a scalable alternative to unitary evolution for preparing entangled many-body states on noisy quantum processors.

Factors influencing nearshore hypoxia in the southeastern Arabian Sea: A sensor-based study.

Seasonal upwelling and the associated incursion of hypoxic waters into the coastal zone is a widely studied topic over different upwelling zones. However, its persistence or variations over short time scales are poorly addressed. The present study, therefore, brings out a first report on hourly variations in the temperature, salinity and dissolved oxygen recorded by an environmental data buoy equipped with sensors, deployed in the nearshore waters of Alappuzha (southeastern Arabian Sea) from April to August 2022. The characteristic feature of the Alappuzha coast is the development of mud banks during the southwest monsoon, providing a tranquil environment suitable for continuous sensor-based measurements when the sea remains turbulent elsewhere. The results showed that despite an advance in the upwelling intensity, there is a significant variation in the oxygen concentration in the study domain on a diurnal scale. In general, the nearshore region was under hypoxia during the first half of the day (00:00 to 12:00 h), which increased steadily to reach normoxic and supersaturated levels during the rest of the day (12:00 to 24:00 h). Statistical analysis showed that winds significantly correlate to the coastal environment's subsurface oxygen concentration. During the morning hours, the wind was weak, and the water column remained stratified over the subsurface hypoxic water layer. The situation changed in the afternoon (12:00 h onwards), as there was a steady increase in the local wind speed (>5 m/s), which was sustained during the rest of the day. A local wind speed >5 m/s can disturb the stratification and enhance the mixing process from 12:00 to 24:00 h. The total kinetic energy of 11.5 J/m3 is the threshold for this oxygen supersaturation. These findings emphasize the role of wind-induced mixing in alleviating coastal hypoxia, highlighting the need for further biogeochemical and ecological investigations into the impacts of alternating oxic-hypoxic conditions in nearshore waters.

To Drill or not to Drill: A Turnabout in Endodontic Practices during Corona Virus Disease -2019- A South India Based Study.

Introduction: The emergence of coronavirus disease-2019 (COVID-19) pandemic poses an immense global health challenge. It also had a profound impact on dentistry with all elective treatment grinding to half initially and a slow phased return to normal services. The aim of the article is to provide an insight into the effect of COVID-19 on endodontic treatment. Materials and Methods: A cross-sectional study among endodontists of various southern states of India was conducted from January 1, 2021 to March 31, 2021, using an online questionnaire. A total of 300 dentists who perform endodontic treatment in daily clinical practice were chosen for the survey. The information was coded, entered, and analyzed utilizing SPSS 20.0 version. Results: A total of 263 questionnaires were answered by the selected group. About 92.01% of endodontists have made changes in infection control including modification in their personal protective equipment and duration of the interval between their appointments. A whopping 74.14% of endodontists faced the economic loss of varying degrees due to the pandemic. In general tremendous changes have been occurred in their daily practice following the pandemic. Conclusion: The pandemic's current and enduring consequences on every part of our lives have been a cause of pain and frustration, but it has also highlighted the human spirit's resilience. Ideally, endodontists must be able to select the best arrangements for safely performing their procedures.

Tuning three-dimensional nano-assembly in the mesoscale via bis(imino)pyridine molecular functionalization.

We investigate the effect of bis(imino)pyridine (BIP) ligands in guiding self-assembly of semiconducting CdSe/ZnS quantum dots (QDs) into three-dimensional multi-layered shells with diameters spanning the entire mesoscopic range, from 200 nm to 2 µm. The assembly process is directed by guest-host interactions between the BIP ligands and a thermotropic liquid crystal (LC), with the latter's phase transition driving the process. Characterization of the shell structures, through scanning electron microscopy and dynamic light scattering, demonstrates that the average shell diameter depends on the BIP structure, and that changing one functional group in the chemical scaffold allows systematic tuning of shell sizes across the entire range. Differential scanning calorimetry confirms a relationship between shell sizes and the thermodynamic perturbation of the BIP molecules to the LC phase transition temperature, allowing analytical modeling of shell assembly energetics. This novel mechanism to controllably tune shell sizes over the entire mesoscale via one standard protocol is a significant development for research on in situ cargo/drug delivery platforms using nano-assembled structures.

Noise-resilient edge modes on a chain of superconducting qubits.

Inherent symmetry of a quantum system may protect its otherwise fragile states. Leveraging such protection requires testing its robustness against uncontrolled environmental interactions. Using 47 superconducting qubits, we implement the one-dimensional kicked Ising model, which exhibits nonlocal Majorana edge modes (MEMs) with [Formula: see text] parity symmetry. We find that any multiqubit Pauli operator overlapping with the MEMs exhibits a uniform late-time decay rate comparable to single-qubit relaxation rates, irrespective of its size or composition. This characteristic allows us to accurately reconstruct the exponentially localized spatial profiles of the MEMs. Furthermore, the MEMs are found to be resilient against certain symmetry-breaking noise owing to a prethermalization mechanism. Our work elucidates the complex interplay between noise and symmetry-protected edge modes in a solid-state environment.

Deep Bidirectional Classification Model for COVID-19 Disease Infected Patients.

In December of 2019, a novel coronavirus (COVID-19) appeared in Wuhan city, China and has been reported in many countries with millions of people infected within only four months. Chest computed Tomography (CT) has proven to be a useful supplement to reverse transcription polymerase chain reaction (RT-PCR) and has been shown to have high sensitivity to diagnose this condition. Therefore, radiological examinations are becoming crucial in early examination of COVID-19 infection. Currently, CT findings have already been suggested as an important evidence for scientific examination of COVID-19 in Hubei, China. However, classification of patient from chest CT images is not an easy task. Therefore, in this paper, a deep bidirectional long short-term memory network with mixture density network (DBM) model is proposed. To tune the hyperparameters of the DBM model, a Memetic Adaptive Differential Evolution (MADE) algorithm is used. Extensive experiments are drawn by considering the benchmark chest-Computed Tomography (chest-CT) images datasets. Comparative analysis reveals that the proposed MADE-DBM model outperforms the competitive COVID-19 classification approaches in terms of various performance metrics. Therefore, the proposed MADE-DBM model can be used in real-time COVID-19 classification systems.

Acceptance of COVID-19 Vaccine among Dental Professionals: A Cross-Sectional Study among Practitioners, Residents, and Students.

INTRODUCTION: The COVID-19 pandemic spread rapidly across the world, prompting governments to impose lengthy restrictions on both movement and trade. While lockdowns reduce the prevalence of COVID-19 disease, they may have a negative impact on the economy and job levels. Dental medicine has been one of the most severely impacted industries during this crisis. Dental professionals are exposed to environments with high levels of occupational hazards, additional risks of viral exposure, and transmission. METHODS: We analyzed 705 anonymous questionnaires filled out by dentists, dental students, and postgraduate students about their willingness to consider a new SARS-CoV-2 vaccine. RESULTS: Our findings show a statistically significant relationship between an individual's unemployment rate and their ability to be immunized with a SARS-CoV-2 vaccine. CONCLUSION: As part of the global vaccination program's alertness, these data may be used to forecast patterns in vaccine adoption or denial depending on economic burden during the COVID-19 pandemic by various industries.