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In the metaverse the physical space and the virtual space co-exist, and interact simultaneously. While the physical space is virtually enhanced with information, the virtual space is continuously refreshed with real-time, real-world information. To allow users to process and manipulate information seamlessly between the real and digital spaces, novel technologies must be developed. These include smart interfaces, new augmented realities, and efficient data storage, management, and dissemination techniques. In this paper, we first discuss some promising co-space applications. These applications offer opportunities that neither of the spaces can realize on its own. Then, we further discuss several emerging technologies that empower the construction of metaverse. After that, we discuss comprehensively the data centric challenges. Finally, we discuss and envision what are likely to be required from the database and system perspectives.

Linear extended state observer (LESO) plays a critical role in ADRC's control performance. However, there exists a tradeoff between disturbance rejection and noise immunity for traditional linear ESO (TLESO). Compared to TLESO with similar bandwidth, phase-locking loop observer (PLLO) exhibits a better output tracking performance but weaker noise suppression capability. By combining the advantages of TLESO and PLLO, an adaptive LESO (ALESO) is proposed in this article, which utilizes TLESO in steady state and PLLO during transient state. The dynamic and noise-suppression performances of different observers are analyzed and compared systematically. The proposed ALESO inherits good dynamic response of PLLO and noise-suppression performance of TLESO, without using high bandwidth. It also possesses the advantages of simple structure, requiring few tuning parameters and ease of parameter tuning. To verify the feasibility and effectiveness of the proposed ALESO design, it is employed to a 500 W dual-active-bridge dc–dc converter for pulsed power applications. Experiments results show that, in comparison with TLESO, the proposed ALESO has resulted in 33.3%/37% and 60%/73.3% reductions in output voltage undershoot/overshoot and setting time, respectively, under load step-up/down. For steady-state performance, a noise level reduction of 76.3% is achieved compared to that resulting from PLLO.

Background: Data regarding North-American incidental (cT1a/b) prostate cancer (PCa) patients is scarce. To address this, incidental PCa characteristics (age, PSA values at diagnosis, Gleason score [GS]), subsequent treatment and cancer-specific survival (CSS) rates were explored. Methods: Incidental PCa patients were identified within the Surveillance, Epidemiology, and End Results (SEER) database (2004-2015). Descriptive statistics, annual percentage changes (EAPC), Kaplan-Meier estimates, as well as Cox regression models were used. Bootstrapping technique was used to generate 95% confidence intervals for CSS at 6 years. Results: Of all 344,031 newly diagnosed non metastatic PCa patients, 5155 harbored incidental PCa. Annual rates of incidental PCa increased from 1.9% (2004) to 2.5 % (2015; p= 0.02). PSA values at diagnosis were 0–4 ng/ml in 48% vs. 4–10 ng/ml in 31% vs. > 10 ng/ml in 21%. Of all incidental PCa patients, 64% harbored GS 6 vs. 25% GS 7 vs. 11% GS ≥ 8. Of all incidental PCa patients, 47% were aged < 70, 35% were between 70 and 79 and 18% were ≥ 80 years. Subsequently, 71% underwent no local treatment (NLT) vs. 16% radical prostatectomy (RP) vs. 14% radiotherapy (RT). Proportions of patients with NLT increased from 65 to 81% (p= 0.0001) over the study period (2004–2015). CSS at six years ranged from 58% in GS ≥ 8 patients with NLT to 100% in patients who harbored GS 6 and underwent either RP or RT. Conclusion: Incidental PCa in the United States is rare. Most incidental PCa patients are diagnosed in men aged less than 80 years of age. The majority of incidental PCa patients undergo NLT and enjoy excellent CSS.

The characteristics of HGI fractions of the blend coal were investigated. One rejected coal (A) with three imported coals, Indonesian coal (B), Russian coal (G) and Australian coal (H), and their blends were tested for their grindability indices as per standard ASTM D 409. The fractions obtained from HGI tests were further assessed for its quality using their proximate, ultimate and α-quartz analysis. The reactivity of these fractions was measured with the TGA. The results showed that after pulverization process the blend coals were not of the same blend ratio. The ash content and α-quartz analysis of the fractions reveal disproportionation happening during pulverization of coal. This was supported by the ultimate carbon values of the same parent/blend coals which showed the higher carbon percentage in plus 75 fractions of HGI tests. Thereby, before blending two different coals the characteristics of parent coals needed to be studied and assessed for the optimum blend proportion that can be used for that particular coal.

Supplemental Digital Content is Available in the Text.Temporal internal limiting membrane flap without gas endotamponade is effective in closing complex macular hole (MH), including large MH and MH associated with high myopia. Retinal surgeons may consider using this technique for complex MH, particularly in patients with only-seeing eye, preexisting glaucoma, or noncompliant to posturing.

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Statins are the cornerstone treatment for patients with heterozygous familial hypercholesterolaemia but research suggests it could increase the risk of type 2 diabetes in the general population. A low prevalence of type 2 diabetes was reported in some familial hypercholesterolaemia cohorts, raising the question of whether these patients are protected against type 2 diabetes. Obesity is a well known risk factor for the development of type 2 diabetes. We aimed to investigate the associations of known key determinants of type 2 diabetes with its prevalence in people with heterozygous familial hypercholesterolaemia.

This paper describes the beam dynamic simulation with transfer matrix method for four sector cyclotron. Starting from a description on the equation of motion in the cyclotron, lattice functions were determined from transfer matrix method and the solutions for the 2nd-order nonlinear Hamiltonian were introduced and used in phase space particle tracking. Based on the description of beam dynamics in the cyclotron, simulation code was also developed for cyclotron design.

Nanocrystalline ZnxCu1 – xO (0.0 ≤ x≤ 1.0) samples were synthesized through phytochemical (chrysin) mediated chemical reduction method. The samples were annealed at 600 °C for 4 h with the aim of aging and further studied the crystallographic characteristics, structure, morphology and optical properties using measurements such as X-ray diffraction, FESEM, UV–Visible spectroscopy and photoluminescence spectra. The crystallographic plane reflections analogous to the formation of monoclinic end-centered phase of copper (II) oxide (CuO) under the space group C2/c (15) and hexagonal primitive lattice of zinc (II) oxide (ZnO) phase under the space group P63mc (186) were obtained, respectively, for x= 0.0 and x= 1.0 samples. Gradual phase changes were observed in the intermediate compositions from x= 0.3 to 0.7. The strain separated effective crystallite size of the samples was estimated using Halder–Wagner method. The parameter, micro-strain, was calculated and used to study the defect structure and to analyze the effect of zinc substitution in the copper (II) oxide lattice in arbitrating the conducting nature of lattices. The optical direct band gaps were estimated through Tauc plot employing Kubelka–Munk function and UV-reflection data. Using PL spectra, CIE chromaticity diagram was drawn, from which photometric properties like chromaticity coordinates, correlated color temperature, color rendering index (CRI), color purity and luminaire efficacy of radiation were calculated. The CRI value for x= 0.0 and 0.3 samples is above 95, which signifies their perfect color appearance and the efficacy as the pertinent material for applications in white light-emitting sources. A prototype sketch for electroluminescent double heterojunction device structure is also discussed.

In a fragment-based approach using NMR spectroscopy, benzyloxyacetohydroxamic acid-derived inhibitors of the bacterial deacetylase LpxC bearing a substituent to target the uridine diphosphate-binding site of the enzyme were developed. By appending privileged fragments via a suitable linker, potent LpxC inhibitors with promising antibacterial activities could be obtained, like the one-digit nanomolar LpxC inhibitor (S)-13j[Ki(EcLpxC C63A) = 9.5 nM; Ki(PaLpxC): 5.6 nM]. To rationalize the observed structure–activity relationships, molecular docking and molecular dynamics studies were performed. Initial in vitro absorption–distribution–metabolism–excretion–toxicity (ADMET) studies of the most potent compounds have paved the way for multiparameter optimization of our newly developed isoserine-based amides.

The methyl-d-erythritol phosphate (MEP) pathway has emerged as an interesting target in the fight against antimicrobial resistance. The pathway is essential in many human pathogens, including Plasmodium falciparum(Pf), but is absent in human cells. In the present study, we report on the discovery of a new chemical class targeting IspD, the third enzyme in the pathway. Exploration of the structure–activity relationship yielded inhibitors with potency in the low-nanomolar range. Moreover, we investigated the whole-cell activity, mode of inhibition, metabolic, and plasma stability of this compound class, and conducted in vivopharmacokinetic profiling on selected compounds. Lastly, we disclosed a new mass spectrometry (MS)-based enzymatic assay for direct IspD activity determination, circumventing the need for auxiliary enzymes. In summary, we have identified a readily synthesizable compound class, demonstrating excellent activity and a promising profile, positioning it as a valuable tool compound for advancing research on IspD.

Determining the local coordination of the active site is a prerequisite for the reliable modeling of single-atom catalysts (SACs). Obtaining such information is difficult on powder-based systems and much emphasis is placed on density functional theory computations based on idealized low-index surfaces of the support. In this work, we investigate how Pt atoms bind to the (11̅02) facet of α-Fe2O3; a common support material in SACs. Using a combination of scanning tunneling microscopy, X-ray photoelectron spectroscopy, and an extensive computational evolutionary search, we find that Pt atoms significantly reconfigure the support lattice to facilitate a pseudolinear coordination to surface oxygen atoms. Despite breaking three surface Fe–O bonds, this geometry is favored by 0.84 eV over the best configuration involving an unperturbed support. We suggest that the linear O–Pt–O configuration is common in reactive Pt-based SAC systems because it balances thermal stability with the ability to adsorb reactants from the gas phase. Moreover, we conclude that extensive structural searches are necessary to determine realistic active site geometries in single-atom catalysis.

The purpose of this study was to evaluate the performance of a bench-scale phase separation ditch system and assess the impact of major operating factors. This assessment also focused on the conversion reactions of nitrogen and phosphorus compounds across consecutive phases within an operational cycle. Phase separation could be achieved by scheduling flow and aeration patterns, and was easily confirmed through observations of the dissolved oxygen (DO) profile and oxidation–reduction potential (ORP) change. As the hydraulic retention time (HRT) became longer, phosphorus (P) release was reduced due to decreased organic loading during the cycle, and the period of P uptake was not related to the quantity of released phosphate. The amount of released phosphate at a shorter solids retention time (SRT) of 20 d was also higher than that at a longer SRT of 30 d. When separate sewer wastewater was used, unlike combined sewer wastewater with low strength, dramatic reaction profiles along consecutive phases were observed, even at a longer HRT of 12 h. When the anoxic–anaerobic phase length was prolonged from 1.5 to 3 h, P release was well maintained during the anaerobic phase, and sufficient P uptake occurred during the aerobic phases.

Primary diabetes care and diabetic retinopathy (DR) screening persist as major public health challenges due to a shortage of trained primary care physicians (PCPs), particularly in low-resource settings. Here, to bridge the gaps, we developed an integrated image–language system (DeepDR-LLM), combining a large language model (LLM module) and image-based deep learning (DeepDR-Transformer), to provide individualized diabetes management recommendations to PCPs. In a retrospective evaluation, the LLM module demonstrated comparable performance to PCPs and endocrinology residents when tested in English and outperformed PCPs and had comparable performance to endocrinology residents in Chinese. For identifying referable DR, the average PCP’s accuracy was 81.0% unassisted and 92.3% assisted by DeepDR-Transformer. Furthermore, we performed a single-center real-world prospective study, deploying DeepDR-LLM. We compared diabetes management adherence of patients under the unassisted PCP arm (n= 397) with those under the PCP+DeepDR-LLM arm (n= 372). Patients with newly diagnosed diabetes in the PCP+DeepDR-LLM arm showed better self-management behaviors throughout follow-up (P< 0.05). For patients with referral DR, those in the PCP+DeepDR-LLM arm were more likely to adhere to DR referrals (P< 0.01). Additionally, DeepDR-LLM deployment improved the quality and empathy level of management recommendations. Given its multifaceted performance, DeepDR-LLM holds promise as a digital solution for enhancing primary diabetes care and DR screening.

Machine learning potentials have become an essential tool for atomistic simulations, yielding results close to ab initio simulations at a fraction of computational cost. With recent improvements on the achievable accuracies, the focus has now shifted on the data set composition itself. The reliable identification of erroneously predicted configurations to extend a given data set is therefore of high priority. Yet, uncertainty estimation techniques have achieved mixed results for machine learning potentials. Consequently, a general and versatile method to correlate energy or atomic force uncertainties with the model error has remained elusive to date. In the current work, we show that epistemic uncertainty cannot correlate with model error by definition but can be aggregated over groups of atoms to yield a strong correlation. We demonstrate that our method correctly estimates prediction errors both globally per structure and locally resolved per atom. The direct correlation of local uncertainty and local error is used to design an active learning framework based on identifying local subregions of a large simulation cell and performing ab initio calculations only for the subregion subsequently. We successfully utilized this method to perform active learning in the low-data regime for liquid water.

By using high-speed electrical measurements, we evaluate the endurance and retention performance of the Si channel ferroelectric transistor (FeFET) having SiOx interfacial layer (IL) scaled using the oxygen scavenging technique. The interfacial SiOx is scaled from 1 to 0.4 nm by depositing a 2-nm Si capping (Si-cap) layer on the HfO2 ferroelectric layer (FL). Trapping and detrapping processes are monitored using read-disturb-free fast P–V and ${I}_{\text {d}}$ – ${V}_{\text {g}}$ measurements. FeFETs with a thicker (1 nm) SiO2 IL showed a ~2-V shift in threshold voltage ( ${V}_{\text {th}}\text {)}$ postprogramming pulse due to trapping in and around the IL, resulting in ~1-s write-to-read delay. The addition of Si-cap eliminated read-after-write delay in the pristine state, which is attributed to the shorter tunneling distance for the traps in the IL and near the FL-IL interface. The endurance cycling was found to degrade subthreshold swing (SS) and shift ${V}_{\text {th}}$ in the without Si-cap (w/o Si-cap) devices, suggesting the generation of both interface states and bulk defects. The addition of Si-cap was found to help reduce the generation of interface states and the bulk FL defects owing to the lower effective electric field. It was also found that fatigue cycling introduces a read-after-write delay in the Si-cap (w/Si-cap) devices, which points to the generation of defects near the FL:IL interface. Even though the endurance and read-after-write delay performance improved, the tradeoff is higher depolarization due to a partially oxidized paraelectric Si-cap layer in series with the FL in the devices w/Si-cap. Our study shows that avoiding the formation of SiOx IL and improving the quality of the FL are critical for improving both retention and endurance performance in Si channel FeFETs.

Thin-film transistors with ultrathin channels are fabricated and characterized at low temperatures down to 100 K in this study. Relying on a diffusive charge model, interfacial localized-state density and apparent carrier mobility are extracted from the measured data. The extraction is carried out by a numerical procedure based on particle swarm optimization (PSO). All the extracted parameters vary clearly with lowering temperatures ( $300\sim 100$ K), which are explained by phonon suppression, thermally-strained chemical bonds and carrier transport with effective mobility involving hopping mechanisms. This work demonstrates parameter extraction by PSO for the first time and highlights the challenges of non-crystalline transistors working at low temperatures.

We explore the phonon transport properties of defect-laden bilayer PtSTe using equilibrium molecular dynamics simulations based on a neural-network force field. Defects prove very efficient at depressing the thermal conductivity of the structure, and flower defects have a particularly powerful effect, comparable to that of double vacancies. Furthermore, the conductivity of the structure with flower defects exhibits an unusual temperature dependence due to structural instability at high temperatures. We look into the distortion to normal modes around the defect by means of the projected phonon density of states and find diverse phenomena including localized modes and blue shifts.

Safflower (Carthamus tinctoriusL.) is an edible oilseed crop mainly cultivated in marginal lands. This study evaluates safflower crop water requirements to understand its feasibility to cultivate under rainfed ecosystem through a field experiment undertaken at the International Crops Research Institute for the Semiarid Tropics research farm, India. Eight improved and stress‐tolerant safflower cultivars (five spiny and three non‐spiny) were evaluated in Vertisols at three soil depths, that is, shallow: <0.60 m, medium: 0.60–1.20 m, and deep:1.20–1.80 m, over 3 years (2009–2012). Wet, normal, and deficit rainfall years were experienced during 2009/2010, 2010/2011, and 2011/2012, respectively. Soil moisture, crop yield, and growth parameters were measured, and field‐scale hydrology was captured through a calibrated one‐dimensional water balance model. Safflower responded to available residual soil moisture which varied with soil depth and rainfall received in different years. Total crop water use was 300–320 mm during the postrainy season, of which about 70% was extracted in deep Vertisols and 55% in medium Vertisols through residual soil moisture. In addition, 30% of water requirement was met through postrainy season rainfall. Safflower grown in shallow Vertisols could only meet 40% of crop water requirement. Spiny cultivar NARI‐H‐15 grown in deep soil recorded a maximum yield of 1890 kg ha−1in the wet year. Seed yield from spiny cultivars grown in deep and medium soils was nearly similar (1500–1600 kg ha−1) during wet and normal years; a significant reduction in yield (>50%) occurred in shallow soils and also during a rainfall deficit year. Spiny cultivars produced 10%–50% higher seed yield compared to non‐spiny cultivars. Growing safflower in medium and deep Vertisols provides opportunities for crop intensification. Safflower, cultivated during the postrainy season in semiarid tropics, requires 300–320 mm of water.Residual soil moisture contributes about 30%–35%, 50%–60% and 65%–80%, of the crop's water requirement in shallow, medium, and deep Vertisols.Yield potential of safflower grown in shallow Vertisols was low and was constrained due to moisture stress in the rainfed ecology.Spiny safflower cultivars performed better (10%–50% higher yields) compared with non‐spiny cultivars.