Depth estimation in SPAD-based LIDAR sensors.

In direct time-of-flight (D-TOF) light detection and ranging (LIDAR), accuracy and full-scale range (FSR) are the main performance parameters to consider. Particularly, in single-photon avalanche diodes (SPAD) based systems, the photon-counting statistics plays a fundamental role in determining the LIDAR performance. Also, the intrinsic performance ultimately depends on the system parameters and constraints, which are set by the application. However, the best-achievable performance directly depends on the selected depth estimation method and is not necessarily equal to intrinsic performance. We evaluate a D-TOF LIDAR system, in the particular context of smartphone applications, in terms of parameter trade-offs and estimation efficiency. First, we develop a simulation model by combining radiometry and photon-counting statistics. Next, we perform a trade-off analysis to study dependencies between system parameters and application constraints, as well as non-linearities caused by the detection method. Further, we derive an analytical model to calculate the Cramér-Rao lower bound (CRLB) of the LIDAR system, which analytically accounts for the shot noise. Finally, we evaluate a depth estimation method based on artificial intelligence (AI) and compare its performance to the CRLB. We demonstrate that the AI-based estimator fully compensates the non-linearity in depth estimation, which varies depending on application conditions such as target reflectivity.

Modifying single-crystal silicon and trimming silicon microring devices by femtosecond laser irradiation.

Single-crystal silicon (c-Si) is a vital component of photonic devices and has obvious advantages. Moreover, femtosecond-pulsed laser interactions with matter have been widely applied in micro/nanoscale processing. In this paper, we report the modification mechanisms of c-Si induced by a femtosecond laser (350 fs, 520 nm) at different pulse fluences, along with the mechanism of this technique to trim the phase error of c-Si-based devices. In this study, several distinct types of final micro/nanostructures, such as amorphization and ablation, were analyzed. The near-surface morphology was characterized using optical microscopy, scanning electron microscopy, and atomic force microscopy. The main physical modification processes were further analyzed using a two-temperature model. By employing Raman spectroscopy, we demonstrated that a higher laser fluence significantly contributes to the formation of more amorphous silicon components. The thickness of the amorphous layer was almost uniform (approximately 30 nm) at different induced fluences, as determined using transmission electron microscopy. From the ellipsometry measurements, we demonstrated that the refractive index increases for amorphization while the ablation decreases. In addition, we investigated the ability of the femtosecond laser to modify the effective index of c-Si microring waveguides by either amorphization or ablation. Both blue and red shifts of resonance spectra were achieved in the microring devices, resulting in double-direction trimming. Our results provide further insight into the femtosecond laser modification mechanism of c-Si and may be a practical method for dealing with the fabrication errors of c-Si-based photonic devices.

Communication-efficient federated learning.

Federated learning (FL) enables edge devices, such as Internet of Things devices (e.g., sensors), servers, and institutions (e.g., hospitals), to collaboratively train a machine learning (ML) model without sharing their private data. FL requires devices to exchange their ML parameters iteratively, and thus the time it requires to jointly learn a reliable model depends not only on the number of training steps but also on the ML parameter transmission time per step. In practice, FL parameter transmissions are often carried out by a multitude of participating devices over resource-limited communication networks, for example, wireless networks with limited bandwidth and power. Therefore, the repeated FL parameter transmission from edge devices induces a notable delay, which can be larger than the ML model training time by orders of magnitude. Hence, communication delay constitutes a major bottleneck in FL. Here, a communication-efficient FL framework is proposed to jointly improve the FL convergence time and the training loss. In this framework, a probabilistic device selection scheme is designed such that the devices that can significantly improve the convergence speed and training loss have higher probabilities of being selected for ML model transmission. To further reduce the FL convergence time, a quantization method is proposed to reduce the volume of the model parameters exchanged among devices, and an efficient wireless resource allocation scheme is developed. Simulation results show that the proposed FL framework can improve the identification accuracy and convergence time by up to 3.6% and 87% compared to standard FL.

A Joint Communication and Computation Design for Probabilistic Semantic Communications.

In this paper, the problem of joint transmission and computation resource allocation for a multi-user probabilistic semantic communication (PSC) network is investigated. In the considered model, users employ semantic information extraction techniques to compress their large-sized data before transmitting them to a multi-antenna base station (BS). Our model represents large-sized data through substantial knowledge graphs, utilizing shared probability graphs between the users and the BS for efficient semantic compression. The resource allocation problem is formulated as an optimization problem with the objective of maximizing the sum of the equivalent rate of all users, considering the total power budget and semantic resource limit constraints. The computation load considered in the PSC network is formulated as a non-smooth piecewise function with respect to the semantic compression ratio. To tackle this non-convex non-smooth optimization challenge, a three-stage algorithm is proposed, where the solutions for the received beamforming matrix of the BS, the transmit power of each user, and the semantic compression ratio of each user are obtained stage by stage. The numerical results validate the effectiveness of our proposed scheme.

Recent advances on low-Co and Co-free high entropy layered oxide cathodes for lithium-ion batteries.

As the price of the precious metal cobalt continues to rise, there is an urgent need for a cobalt-free or low-cobalt electrode material to reduce the cost of lithium-ion batteries, which are widely used commercially, while maintaining their performance as much as possible. With the introduction of the new concept of high entropy (HE) materials into the battery field, low cobalt and cobalt free HE novel lithium-ion batteries have attracted great attention. It possesses important research value to use HE materials to reduce the use of cobalt metal in electrode materials. In this perspective, the comparison between the new cathode materials of low cobalt and cobalt-free HE lithium-ion battery and traditional cathode materials and the latest progress in maintaining structural stability and conductivity are introduced. It is believed that low cobalt and cobalt-free and HE layered oxides can be used to replace the function of cobalt in the cathode materials of lithium-ion batteries. Finally, the future research directions and the synthesis method of HE cathode materials for lithium-ion batteries are also discussed.

CO2 Capture Mechanism by Deep Eutectic Solvents Formed by Choline Prolinate and Ethylene Glycol.

The choline prolinate ([Ch][Pro]) as a hydrogen bond acceptor and ethylene glycol (EG) as a hydrogen bond donor are both used to synthesize the deep eutectic solvents (DESs) [Ch][Pro]-EG to capture CO2. The CO2 capacity of [Ch][Pro]-EG is determined, and the nuclear magnetic resonance (NMR) and infrared (IR) spectrum are used to investigate the CO2 capture mechanism. The results indicate that CO2 reacts with both the amino group of [Pro]- anion and the hydroxyl group of EG, and the mechanism found in this work is different from that reported in the literature for the [Ch][Pro]-EG DESs.

Regulating Pseudo-Jahn-Teller Effect and Superstructure in Layered Cathode Materials for Reversible Alkali-Ion Intercalation.

The Jahn-Teller effect (JTE) is one of the most important determinators of how much stress layered cathode materials undergo during charge and discharge; however, many reports have shown that traces of superstructure exist in pristine layered materials and irreversible phase transitions occur even after eliminating the JTE. A careful consideration of the energy of cationic distortion using a Taylor expansion indicated that second-order JTE (pseudo-JTE) is more widespread than the aforementioned JTE because of the various bonding states that occur between bonding and antibonding molecular orbitals in transition-metal octahedra. As a model case, a P2-type Mn-rich cathode (Na3/4MnO2) was investigated in detail. MnO6 octahedra are well known to undergo either elongation or contraction in a specific direction due to JTE. Here, the substitution of Li for Mn (Na3/4(Li1/4Mn3/4)O2) helped to oxidize Mn3+ to Mn4+ suppressing JTE; however, the MnO6 octahedra remained asymmetric with a clear trace of the superstructure. With various advanced analyses, we disclose the pseudo-JTE as a general reason for the asymmetric distortions of the MnO6 octahedra. These distortions lead to the significant electrochemical degradation of Na3/4Li1/4Mn3/4O2. The suppression of the pseudo-JTE modulates phase transition behaviors during Na intercalation/deintercalation and thereby improves all of the electrochemical properties. The insight obtained by coupling a theoretical background for the pseudo-JTE with verified layered cathode material lattice changes implies that many previous approaches can be rationalized by regulating pseudo-JTE. This suggests that the pseudo-JTE should be thought more important than the well-known JTE for layered cathode materials.

Activating a Multielectron Reaction of NASICON-Structured Cathodes toward High Energy Density for Sodium-Ion Batteries.

The increasing demand to efficiently store and utilize the electricity from renewable energy resources in a sustainable way has boosted the request for sodium-ion battery technology due to the high abundance of sodium sources worldwide. Na superionic conductor (NASICON) structured cathodes with a robust polyanionic framework have been intriguing because of their open 3D structure and superior thermal stability. The ever-increasing demand for higher energy densities with NASICON-structured cathodes motivates us to activate multielectron reactions, thus utilizing the third sodium ion toward higher voltage and larger capacity, both of which have been the bottlenecks for commercializing sodium-ion batteries. A doping strategy with Cr inspired by first-principles calculations enables the activation of multielectron redox reactions of the redox couples V2+/V3+, V3+/V4+, and V4+/V5+, resulting in remarkably improved energy density even in comparison to the layer structured oxides and Prussian blue analogues. This work also comprehensively clarifies the role of the Cr dopant during sodium storage and the valence electron transition process of both V and Cr. Our findings highlight the importance of a broadly applicable doping strategy for achieving multielectron reactions of NASICON-type cathodes with higher energy densities in sodium-ion batteries.

Superior sodium storage of Na3V(PO3)3N nanofibers as a high voltage cathode for flexible sodium-ion battery devices.

The cathode materials for sodium-ion batteries are always the key issues for the ultimate success of large-scale energy storage systems. The nitrogen-dope polyanionic type material is one of the important high voltage candidates. Herein, we have developed a simple and facile method to synthesize a high voltage cathode material, Na3V(PO3)3N nanofibers, via an electrospinning approach. Unexpected excellent rate performance and cyclability have been demonstrated, with a discharge capacity of 61.5 mAh g-1achieved at a current density of 4 A g-1. Capacity retention of 86.7% could be obtained at 0.8 A g-1over 2000 cycles. Density functional theory calculations reveal that this material has an abnormal flat band characteristic, and its high voltage platform can be explained by the dominant V d-orbital contribution to the density of states at the Fermi level.

Wireless Network Optimization for Federated Learning with Model Compression in Hybrid VLC/RF Systems.

In this paper, the optimization of network performance to support the deployment of federated learning (FL) is investigated. In particular, in the considered model, each user owns a machine learning (ML) model by training through its own dataset, and then transmits its ML parameters to a base station (BS) which aggregates the ML parameters to obtain a global ML model and transmits it to each user. Due to limited radio frequency (RF) resources, the number of users that participate in FL is restricted. Meanwhile, each user uploading and downloading the FL parameters may increase communication costs thus reducing the number of participating users. To this end, we propose to introduce visible light communication (VLC) as a supplement to RF and use compression methods to reduce the resources needed to transmit FL parameters over wireless links so as to further improve the communication efficiency and simultaneously optimize wireless network through user selection and resource allocation. This user selection and bandwidth allocation problem is formulated as an optimization problem whose goal is to minimize the training loss of FL. We first use a model compression method to reduce the size of FL model parameters that are transmitted over wireless links. Then, the optimization problem is separated into two subproblems. The first subproblem is a user selection problem with a given bandwidth allocation, which is solved by a traversal algorithm. The second subproblem is a bandwidth allocation problem with a given user selection, which is solved by a numerical method. The ultimate user selection and bandwidth allocation are obtained by iteratively compressing the model and solving these two subproblems. Simulation results show that the proposed FL algorithm can improve the accuracy of object recognition by up to 16.7% and improve the number of selected users by up to 68.7%, compared to a conventional FL algorithm using only RF.

A Cation and Anion Dual Doping Strategy for the Elevation of Titanium Redox Potential for High-Power Sodium-Ion Batteries.

Titanium-based polyanions have been intensively investigated for sodium-ion batteries owing to their superior structural stability and thermal safety. However, their low working potential hindered further applications. Now, a cation and anion dual doping strategy is used to boost the redox potential of Ti-based cathodes of Na3 Ti0.5 V0.5 (PO3 )3 N as a new cathode material for sodium ion batteries. Both the Ti3+ /Ti4+ and V3+ /V4+ redox couples are reversibly accessed, leading to two distinctive voltage platforms at ca. 3.3 V and ca. 3.8 V, respectively. The remarkably improved cycling stability (86.3 %, 3000 cycles) can be ascribed to the near-zero volume strain in this unusual cubic symmetry, which has been demonstrated by in situ synchrotron-based X-ray diffraction. First-principles calculations reveal its well-interconnected 3D Na diffusion pathways with low energy barriers, and the two-sodium-extracted intermediate NaTi0.5 V0.5 (PO3 )3 N is also a stable phase according to formation energy calculations.

Development and Investigation of a NASICON-Type High-Voltage Cathode Material for High-Power Sodium-Ion Batteries.

Herein, we introduce a 4.0 V class high-voltage cathode material with a newly recognized sodium superionic conductor (NASICON)-type structure with cubic symmetry (space group P21 3), Na3 V(PO3 )3 N. We synthesize an N-doped graphene oxide-wrapped Na3 V(PO3 )3 N composite with a uniform carbon coating layer, which shows excellent rate performance and outstanding cycling stability. Its air/water stability and all-climate performance were carefully investigated. A near-zero volume change (ca. 0.40 %) was observed for the first time based on in situ synchrotron X-ray diffraction, and the in situ X-ray absorption spectra revealed the V3.2+ /V4.2+ redox reaction with high reversibility. Its 3D sodium diffusion pathways were demonstrated with distinctive low energy barriers. Our results indicate that this high-voltage NASICON-type Na3 V(PO3 )3 N composite is a competitive cathode material for sodium-ion batteries and will receive more attention and studies in the future.

Recent Progress of Layered Transition Metal Oxide Cathodes for Sodium-Ion Batteries.

Sodium-ion batteries (SIBs) are attracting increasing attention and considered to be a low-cost complement or an alternative to lithium-ion batteries (LIBs), especially for large-scale energy storage. Their application, however, is limited because of the lack of suitable host materials to reversibly intercalate Na+ ions. Layered transition metal oxides (Nax MO2 , M = Fe, Mn, Ni, Co, Cr, Ti, V, and their combinations) appear to be promising cathode candidates for SIBs due to their simple structure, ease of synthesis, high operating potential, and feasibility for commercial production. In the present work, the structural evolution, electrochemical performance, and recent progress of Nax MO2 as cathode materials for SIBs are reviewed and summarized. Moreover, the existing drawbacks are discussed and several strategies are proposed to help alleviate these issues. In addition, the exploration of full cells based on Nax MO2 cathodes and future perspectives are discussed to provide guidance for the future commercialization of such systems.

CO2 capture by imidazolium-based deep eutectic solvents: the effect of steric hindrance of N-heterocyclic carbenes.

CO2 capture by deep eutectic solvents (DESs) formed between 1,3-bis(isopropyl)imidazolium 1,2,4-triazolide ([IiPim][Triz]) and ethylene glycol (EG) is investigated in this study. [IiPim][Triz]-EG DESs exhibit a capacity of ∼1.0 mol CO2 per mol DES at 1.0 atm and 25 °C. Surprisingly, mechanistic results disclose that CO2 reacts with EG but does not bind with the C-2 site of the [IiPim]+ cation, which may be due to the high steric hindrance of the C-2 site of the N-heterocyclic carbene IiPim present in [IiPim][Triz]-EG DESs.

A High-Voltage Cathode Material with Ultralong Cycle Performance for Sodium-Ion Batteries.

Vanadium-based polyanionic materials are promising electrode materials for sodium-ion batteries (SIBs) due to their outstanding advantages such as high voltage, acceptable specific capacity, excellent structural reversibility, good thermal stability, etc. Polyanionic compounds, moreover, can exhibit excellent multiplicity performance as well as good cycling stability after well-designed carbon covering and bulk-phase doping and thus have attracted the attention of multiple researchers in recent years. In this paper, after the modification of carbon capping and bulk-phase nitrogen doping, compared to pristine Na3 V2 (PO4 )3 , the well optimized Na3 V(PO3 )3 N/C possesses improved electromagnetic induction strength and structural stability, therefore exhibits exceptional cycling capability of 96.11% after 500 cycles at 2 C (1 C = 80 mA g-1 ) with an elevated voltage platform of 4 V (vs Na+ /Na). Meanwhile, the designed Na3 V(PO3 )3 N/C possesses an exceptionally low volume change of ≈0.12% during cycling, demonstrating its quasi-zero strain property, ensuring an impressive capacity retention of 70.26% after 10,000 cycles at 2 C. This work provides a facial and cost-effective synthesis method to obtain stable vanadium-based phosphate materials and highlights the enhanced electrochemical properties through the strategy of carbon rapping and bulk-phase nitrogen doping.

Analysis of Key Genes and miRNA-mRNA Networks Associated with Glucocorticoids Treatment in Chronic Obstructive Pulmonary Disease.

Background: Some patients with chronic obstructive pulmonary disease (COPD) benefit from glucocorticoid (GC) treatment, but its mechanism is unclear. Objective: With the help of the Gene Expression Omnibus (GEO) database, the key genes and miRNA-mRNA related to the treatment of COPD by GCs were discussed, and the potential mechanism was explained. Methods: The miRNA microarray dataset (GSE76774) and mRNA microarray dataset (GSE36221) were downloaded, and differential expression analysis were performed. Gene Ontology (GO) function and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed on the differentially expressed genes (DEGs). The protein interaction network of the DEGs in the regulatory network was constructed with the STRING database, and the key genes were screened through Cytoscape. Potential downstream target genes regulated by differentially expressed miRNAs (DEMs) were predicted by the miRWalk3.0 database, and miRNA-mRNA regulatory networks were constructed. Finally, some research results were validated. Results: ① Four DEMs and 83 DEGs were screened; ② GO and KEGG enrichment analysis mainly focused on the PI3K/Akt signalling pathway, ECM receptor interaction, etc.; ③ CD2, SLAMF7, etc. may be the key targets of GC in the treatment of COPD; ④ 18 intersection genes were predicted by the mirwalk 3.0 database, and 9 pairs of miRNA-mRNA regulatory networks were identified; ⑤ The expression of miR-320d-2 and TFCP2L1 were upregulated by dexamethasone in the COPD cell model, while the expression of miR-181a-2-3p and SLAMF7 were downregulated. Conclusion: In COPD, GC may mediate the expression of the PI3K/Akt signalling pathway through miR-181a-2-3p, miR-320d-2, miR-650, and miR-155-5p, targeting its downstream signal factors. The research results provide new ideas for RNA therapy strategies of COPD, and also lay a foundation for further research.

d-Aspartate in Low-Protein Diets Improves the Pork Quality by Regulating Energy and Lipid Metabolism via the Gut Microbes.

d-Aspartate is critical in maintaining hormone secretion and reproductive development in mammals. This study investigated the mechanism of different d-aspartate levels (0, 0.005, 0.05, and 0.5% d-aspartate) in low-protein diets on growth performance and meat quality by mediating the gut microbiota alteration in pigs. We found that adding 0.005% d-aspartate to a low-protein diet could dramatically improve the growth performance during the weaned and growing periods. Dietary d-aspartate with different levels markedly increased the back fat, and 0.5% d-aspartate significantly increased the redness in 24 h and reduced the shear force of the longissimus dorsi (LD) muscle. Moreover, d-aspartate treatments decreased the mRNA expression of MyHC II a and MyHC IIx in the LD muscle. The protein expression of MyH1, MyH7, TFAM, FOXO1, CAR, UCP2, and p-AMPK was upregulated by 0.005% d-aspartate. Additionally, the abundance of Alistipes, Akkermansia, and the [Eubacterium]_coprostanoligenes_group in the intestinal chyme of pigs was significantly decreased by d-aspartate treatments at the genus level, which was also accompanied by a significant decrease in acetate content. These differential microorganisms were significantly correlated with meat quality characteristics. These results indicated that d-aspartate in low-protein diets could improve the growth performance and meat quality in pigs by regulating energy and lipid metabolism via the alteration of gut microbiota.

Comparison of Regional Saturation Biopsy, Targeted Biopsy, and Systematic Biopsy in Patients with Prostate-specific Antigen Levels of 4-20 ng/ml: A Prospective, Single-center, Randomized Controlled Trial.

BACKGROUND: Despite the use of multiparametric magnetic resonance imaging (mpMRI)-guided targeted biopsy (TB) to identify suspicious prostate lesions, it may still miss clinically significant prostate cancer (csPCa) or result in false-negative findings. Recent evidence suggests that combining biopsies taken from within and around magnetic resonance imaging (MRI) lesions can improve the detection of csPCa. OBJECTIVE: This study aimed to compare the diagnostic performance of the regional saturation biopsy (RSB) method, involving template-based nine-core biopsies for suspected regions, with that of the MRI-directed TB and/or the systematic biopsy (SB) methods in biopsy-naïve patients with prostate-specific antigen (PSA) levels ranging from 4 to 20 ng/ml. DESIGN, SETTING, AND PARTICIPANTS: A prospective, single-center, randomized controlled trial included 434 biopsy-naïve patients with suspected lesions on mpMRI and PSA levels between 4 and 20 ng/ml (from January 2022 to July 2023). OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: The detection rates of csPCa for the RSB, TB, and SB methods were analyzed using the McNemar test for intrapatient comparisons. The Fisher's exact test was used for comparisons between RSB and TB. RESULTS AND LIMITATIONS: The RSB approach yielded a significantly higher detection rate of csPCa than both the TB approach (44.1% vs 31.8%, p = 0.01) and the SB approach (44.1% vs 34.1%, p = 0.03). The RSB approach exhibited a comparable detection rate of csPCa (44.1% vs. 40.7%, p = 0.3) to the combined approach (TB + SB), while requiring fewer biopsy cores and a higher positive core number to avoid sampling the entire prostate gland (32.7% vs 18.3%, p < 0.001). Upon conducting a whole-mount histopathological analysis, it was observed that the RSB approach successfully identified 97% (32 out of 33) of the prostate cancer foci as the index lesion, whereas only 59.18% (29 out of 49) were classified as index lesions using the SB approach. Furthermore, mpMRI underestimated the average diameter of histological tumor size by a median of 0.76 cm, highlighting the importance of an optimal biopsy area for the RSB procedure. CONCLUSIONS: For patients with suspected lesions on mpMRI and PSA levels between 4 and 20 ng/ml, the RSB approach has shown improved detection of clinically significant prostate cancer, accurately identifying index lesions, and minimizing biopsy cores compared with the MRI-directed TB and SB approaches. PATIENT SUMMARY: For patients with suspected lesions on multiparametric magnetic resonance imaging and prostate-specific antigen levels between 4 and 20 ng/ml, the regional saturation biopsy method provides enhanced detection of clinically significant prostate cancer, as well as precise identification of index lesions, surpassing both magnetic resonance imaging-directed targeted biopsy and the systematic biopsy method.

Development of Acridone Derivatives: Targeting c-MYC Transcription in Triple-Negative Breast Cancer with Inhibitory Potential.

Breast cancer, especially the aggressive triple-negative subtype, poses a serious health threat to women. Unfortunately, effective targets are lacking, leading to a grim prognosis. Research highlights the crucial role of c-MYC overexpression in this form of cancer. Current inhibitors targeting c-MYC focus on stabilizing its G-quadruplex (G4) structure in the promoter region. They can inhibit the expression of c-MYC, which is highly expressed in triple-negative breast cancer (TNBC), and then regulate the apoptosis of breast cancer cells induced by intracellular ROS. However, the clinical prospects for the application of such inhibitors are not promising. In this research, we designed and synthesized 29 acridone derivatives. These compounds were assessed for their impact on intracellular ROS levels and cell activity, followed by comprehensive QSAR analysis and molecular docking. Compound N8 stood out, significantly increasing ROS levels and demonstrating potent anti-tumor activity in the TNBC cell line, with excellent selectivity shown in the docking results. This study suggests that acridone derivatives could stabilize the c-MYC G4 structure. Among these compounds, the small molecule N8 shows promising effects and deserves further investigation.