A Novel Hydrated Iron Vanadate Cathode Material for Advanced Aqueous Nickel-Ion Batteries.

Aqueous nickel-ion batteries (ANIBs) as an emerging energy storage device attracted much attention owing to their multielectron redox reaction and dendrite-free Ni anode, yet their development is hindered by the divalent properties of Ni2+ and the lack of suitable cathode materials. Herein, a hydrated iron vanadate (Fe2V3O10.5∙1.5H2O, FOH) with a preferred orientation along the (200) plane is innovatively proposed and used as cathode material for ANIBs. The FOH cathode exhibits a remarkable capacity of 129.3 mAh g-1 at 50 mA g-1 and a super-high capacity retention of 95% at 500 mA g-1 after 700 cycles. The desirable Ni2+ storage capacity of FOH can be attributed to the preferentially oriented and tunnel structures, which offer abundant reaction active planes and a broad Ni2+ diffusion path, the abundant vacancies and high specific surface area further increase ion storage sites and accelerate ion diffusion in the FOH lattice. Furthermore, the Ni2+ storage mechanism and structural evolution in the FOH cathode are explored through ex situ XRD, ex situ Raman, ex situ XPS and other ex situ characteristics. This work opens a new way for designing novel cathode materials to promote the development of ANIBs.

TIMELESS promotes reprogramming of glucose metabolism in oral squamous cell carcinoma.

BACKGROUND: Oral squamous cell carcinoma (OSCC), the predominant malignancy of the oral cavity, is characterized by high incidence and low survival rates. Emerging evidence suggests a link between circadian rhythm disruptions and cancer development. The circadian gene TIMELESS, known for its specific expression in various tumors, has not been extensively studied in the context of OSCC. This study aims to explore the influence of TIMELESS on OSCC, focusing on cell growth and metabolic alterations. METHODS: We analyzed TIMELESS expression in OSCC using western blot, immunohistochemistry, qRT-PCR, and data from The Cancer Genome Atlas (TCGA) and the Cancer Cell Line Encyclopedia (CCLE). The role of TIMELESS in OSCC was examined through clone formation, MTS, cell cycle, and EdU assays, alongside subcutaneous tumor growth experiments in nude mice. We also assessed the metabolic impact of TIMELESS by measuring glucose uptake, lactate production, oxygen consumption, and medium pH, and investigated its effect on key metabolic proteins including silent information regulator 1 (SIRT1), hexokinase 2 (HK2), pyruvate kinase isozyme type M2 (PKM2), recombinant lactate dehydrogenase A (LDHA) and glucose transporter-1 (GLUT1). RESULTS: Elevated TIMELESS expression in OSCC tissues and cell lines was observed, correlating with reduced patient survival. TIMELESS overexpression enhanced OSCC cell proliferation, increased glycolytic activity (glucose uptake and lactate production), and suppressed oxidative phosphorylation (evidenced by reduced oxygen consumption and altered pH levels). Conversely, TIMELESS knockdown inhibited these cellular and metabolic processes, an effect mirrored by manipulating SIRT1 levels. Additionally, SIRT1 was positively associated with TIMELESS expression. The expression of SIRT1, HK2, PKM2, LDHA and GLUT1 increased with the overexpression of TIMELESS levels and decreased with the knockdown of TIMELESS. CONCLUSION: TIMELESS exacerbates OSCC progression by modulating cellular proliferation and metabolic pathways, specifically by enhancing glycolysis and reducing oxidative phosphorylation, largely mediated through the SIRT1 pathway. This highlights TIMELESS as a potential target for OSCC therapeutic strategies.

Robustness of the modified multi-trench fiber design with two gaps.

We investigate the robustness of a modified multi-trench fiber (MTF) design with two gaps numerically. The excellent suppression of high-order modes is demonstrated over a wide range of the gap misalignment and the fundamental mode loss is barely affected even with the 5 dB/m scattering loss in gaps at the modified two-gap MTF for the first time. Therefore, the required fabrication accuracy decreases.

Experimental study of intramodal XPM reduction by intramodal dispersion in weakly coupled FMF.

The understanding of nonlinear propagation effects in low-crosstalk few-mode fiber is crucial for a weakly coupled mode-division multiplexed system. In this Letter, we report the first, to the best of our knowledge, experimental verification of the advantage of intramodal dispersion on mitigating intramodal cross-phase modulation in a weakly coupled few-mode fiber transmission. The experimental system is established over a 70-km multiple-ring-core few-mode fiber accommodating 6 linearly polarized modes, based on which the influences of intramodal cross-phase modulation on transmission performances of each linearly polarized mode are evaluated. Experimental results show that the intramodal cross-phase modulation of degenerate linearly polarized modes with much larger intramodal dispersion values are significantly weaker than those of non-degenerate linearly polarized modes, in which the maximum suppression of intramodal cross-phase modulation noise is up to 9.7 dB. We believe that this work would be beneficial to practical applications of weakly coupled mode-division multiplexing technologies.

Quantum Light Generation Based on GaN Microring toward Fully On-Chip Source.

An integrated quantum light source is increasingly desirable in large-scale quantum information processing. Despite recent remarkable advances, a new material platform is constantly being explored for the fully on-chip integration of quantum light generation, active and passive manipulation, and detection. Here, for the first time, we demonstrate a gallium nitride (GaN) microring based quantum light generation in the telecom C-band, which has potential toward the monolithic integration of quantum light source. In our demonstration, the GaN microring has a free spectral range of 330 GHz and a near-zero anomalous dispersion region of over 100 nm. The generation of energy-time entangled photon pair is demonstrated with a typical raw two-photon interference visibility of 95.5±6.5%, which is further configured to generate a heralded single photon with a typical heralded second-order autocorrelation g_{H}^{(2)}(0) of 0.045±0.001. Our results pave the way for developing a chip-scale quantum photonic circuit.

In Situ Growth of Gold Nanofilms with Branched Structures in the Presence of Organosulfur for High-Performance Flexible Electronics.

Herein, a novel method is presented for the in situ growth of gold nanofilms with branched structures in the presence of organosulfur. The key feature in this approach is the Rayleigh instability of ultrathin gold nanowires (AuNWs) without oleylamine (OAm), which allows the ultrathin AuNWs to decompose into gold nanoparticles (AuNPs) and the AuNPs to in situ grow into branched structures for high-performance stability and electrical conductivity. The sheet resistance of the gold nanofilms initially sharply decreased, whereas it subsequently slightly increased with the concentration of CS(NH2)2 until it exceeded the optimal range. After undergoing a 10 min heat treatment at 150 °C, the sheet resistance of the nanofilms was further reduced to 18 Ω/sq, which could be maintained for more than five months. The internal structure becomes fully grown and denser, forming a branched structure after heat treatment. Only certain organosulfurs can improve the electrical properties of the gold nanofilms, and the mechanism of organosulfur in the in situ growth of gold nanofilms with branched structures has also been presented. Overall, this novel method provides a straightforward and convenient approach to obtaining gold nanomaterials with branched structures, holding great potential promise for applications in flexible electronics, catalysis, and energy fields.

Hydroxyl-Binding Induced Hydrogen Bond Network Connectivity on Ru-based Catalysts for Efficient Alkaline Hydrogen Oxidation Electrocatalysis.

Understanding the role of adsorbed intermediates at the polarized catalyst-electrolyte interface on the structure of electrical double layer (EDL) is essential for developing highly efficient electrocatalysts. Here, we prepared a series of unconventional face-centered-cubic (fcc) phase Ru-based catalysts (i.e. fcc-Ru, fcc-RuCr, and fcc-RuCrW) by rational tuning the binding energetics of hydroxyl intermediate to engineer the electrochemical interface and boost the performance of alkaline hydrogen oxidation reaction (HOR). The introduction of oxyphilic metals Cr and W can regulate the orbital occupation of Ru, promote the adsorption of hydroxyl species, resulting in an anomalous behavior that HOR performance under alkaline media exceeds acidic media. Experimental results and theoretical calculations unravel that the modulated adsorption of hydroxyl species on the electrode surface are responsible for the reconstruction of interfacial water structure and dynamic evolution of free water molecules from nearest to the electrode surface to above the gap region in the EDL, thereby leading to significantly increased water connectivity and hydrogen bond network. Our work reveals a new understanding of the surface intermediates in controlling the dynamic process of interfacial water and hydrogen bonding network in HOR electrocatalysis, and will guide rational design of advanced electrocatalysts through electrochemical interfacial engineering.

Field trial of concurrent co-cable and co-trench optical fiber online identification based on ensemble learning.

The co-route optical fibers, comprising both co-cable and co-trench fibers, pose a significant potential risk to network service quality assurance by operators. They are incapable of achieving high-precision recognition and visual state management. In this study, we gathered both static and dynamic optical fiber data using a linewidth tunable light source (LTLS) and introduced a multimodal detection architecture that applies ensemble learning to the collected data. This constitutes what we believe to be the first field trial of concurrent recognition of optical fibers found both in co-cables and co-trenches. To identify co-cable fibers, we employed a double-layer cascaded Random Forest (DLC-RF) model based on the static features of fibers. For co-trench fiber, the dynamic characteristics of fiber vibrations are utilized in combination with multiple independent curve similarity contrast learners for classifying tasks. The proposed architecture is capable of automatically detecting the condition of the optical fiber and actively identifying the same routing segment within the network, eliminating the need for human intervention and enabling the visualization of passive optical fiber resources. Finally, after rigorous testing and validation across 11 sites in a typical urban area, including aggregation and backbone scenarios within the operator's live network environments, we have confirmed that the solution's ability to identify co-routes is accurate, exceeding 95%. This provides strong empirical evidence of its effectiveness.

Mitigating nonlinear penalty induced from a low-speed optical supervisory channel on coherent signals.

With the increasing signal rates of a long-haul backbone dense-wavelength-division-multiplexing (DWDM) transmission system, e.g., from 100 Gb/s to 400 Gb/s and even to 800 Gb/s, optical path impairments simultaneously become more severe. Harmful factors being formerly insignificant become noticeable, e.g., nonlinear phase noise (NPN) on main DWDM channels induced by the cross-phase modulation (XPM) from the low-speed optical supervisory channel (OSC). Field trials show that a greater than 5.13-dB penalty can be observed on the shortest channel of 400G DP-16QAM-PCS over G.654.E links, which greatly degrades the overall transmission performance and limits the maximum reach. In this paper, we propose a dual-OSC structure with opposite signals to compensate for performance degradation caused by OSC-induced NPN. This method involves no extra digital signal processing (DSP), which is not only simple but also applicable for universal signal rates. By experimental demonstration, a 1.32-dB gain in Q (dB) for 200G DP-16QAM transmission over 1618-km G.652.D can be done, almost achieving the same performance as the no OSC case.

Abnormal cerebral metabolism and metabolic connectivity in individuals with heroin dependence: an integrated resting-state PET/fMRI study in large-scale networks.

BACKGROUND: Increasing evidence suggests that heroin addiction may be related to the dysfunction among the triple brain network (default mode network [DMN], salience network [SN] and executive control network [ECN]). However, the characteristics of glucose metabolism and metabolic connectivity among core regions of the triple brain network remain unknown. Therefore, we hypothesized that individuals with heroin dependence would show abnormal glucose metabolism and accompanied abnormal metabolic connectivity within the triple brain network. METHODS: Individuals with heroin dependence and healthy controls matched for age and sex underwent integrated positron emission tomography/magnetic resonance imaging (PET/MRI). Differences in glucose metabolism and metabolic connectivity among the DMN, SN and ECN were analyzed based on 18F-fluorodeoxyglucose PET and resting-state fMRI data. RESULTS: We included 36 individuals with heroin dependence and 30 matched healthy controls in our study. The heroin dependence group showed a significant reduction of glucose metabolism in the bilateral anterior insula (AI) and inferior parietal lobule (IPL), and a significantly decreased metabolic connectivity between the right AI and the left dorsolateral prefrontal cortex (DLPFC). The daily dose of methadone was negatively correlated with glucose metabolism of the right AI and right IPL. LIMITATIONS: The results revealed the glucose metabolism alterations and metabolic connectivity only within the triple brain network in individuals with heroin dependence; additional brain networks should be investigated in future studies. Although methadone is an opioid with a similar neurophysiological mechanism as heroin, the specific chronic effects of methadone on cerebral metabolism and metabolic connectivity should also be investigated in future studies. CONCLUSION: Our findings suggest that long-term opioid use might, to some extent, be associated with reduced synergistic ability between the SN and ECN, which may be associated with the dysfunction of cognitive control. In particular, the right AI, which showed hypometabolism and related reduction in SN-ECN metabolic connectivity, should receive increasing attention in future studies.

Efficacy of the magnetic stimulation of sacral nerve roots combined with Tui-na on neurogenic bladder after spinal cord injury: preliminary short-term results.

OBJECTIVE: Neurogenic bladder (NGB) is a serious complication after spinal cord injury (SCI), a destructive neurological disease. This study focused on exploring the efficacy of the magnetic stimulation of sacral nerve roots combined with Tui-na in treating NGB after SCI. METHODS: One hundred patients with NGB after SCI were studied, and intermittent clean catheterization was performed with a water intake program, and patients were grouped into four groups by the random number table method: general treatment group, Tui-na group, magnetic stimulation group, and combined treatment group. A series of relevant factors (voiding diary, urodynamics, and quality of life scores) and clinical efficacy of patients in the four groups before and after treatment were observed. RESULTS: The magnetic stimulation of sacral nerve roots alone, Tui-na alone, and the combination of both were all effective in improving bladder function and quality of life in patients with NGB after SCI, including improvements in voiding frequency, single urine output, maximum urine output, residual urine output, bladder volume and quality of life scores in patients with NGB after SCI. The efficacy of the magnetic stimulation of sacral nerve roots combined with Tui-na was better than that of the magnetic stimulation of sacral nerve roots alone and the Tui-na alone. CONCLUSION: This research demonstrates that the magnetic stimulation of sacral nerve roots combined with Tui-na treatment could effectively improve the urinary system and the quality of life of patients with NGB after SCI, which is worthy of clinical promotion and application.

Electronic Modulation of Ru Nanosheet by d-d Orbital Coupling for Enhanced Hydrogen Oxidation Reaction in Alkaline Electrolytes.

The alkaline polymer electrolyte fuel cells (APEFCs) hold great promise for using nonnoble metal-based electrocatalysts toward the cathodic oxygen reduction reaction (ORR), but are hindered by the sluggish anodic hydrogen oxidation reaction (HOR) in alkaline electrolytes. Here, a strategy is reported to promote the alkaline HOR performance of Ru by incorporating 3d-transition metals (V, Fe, Co, and Ni), where the conduction band minimum (CBM) level of Ru can be rationally tailored through strong d-d orbital coupling. As expected, the obtained RuFe nanosheet exhibits outstanding HOR performance with the mass activity of 233.46 A gPGM -1 and 23-fold higher than the Ru catalyst, even threefold higher than the commercial Pt/C. APEFC employing this RuFe as anodic catalyst gives a peak power density of 1.2 W cm-2 , outperforming the documented Pt-free anodic catalyst-based APEFCs. Experimental results and density functional theory calculations suggest the enhanced OH-binding energy and reduced formation energy of water derived from the downshifted CBM level of Ru contribute to the enhanced HOR activity.

Single-incision plus one-port laparoscopic gastrectomy versus conventional multi-port laparoscopy-assisted gastrectomy for gastric cancer: a retrospective study.

BACKGROUND: We compared short-term perioperative outcomes after single-incision plus one-port laparoscopic gastrectomy (SILG+1) and conventional multi-port laparoscopy-assisted gastrectomy (C-LAG) for gastric cancer. METHODS: The work was conducted between August 2017 and October 2019. A total of 90 patients with early or advanced gastric cancer were retrospectively analyzed: 43 patients of which underwent SILG+1, and 47 of which underwent C-LAG, respectively. These were divided into two groups: the total gastrectomy group (SILT+1 and C-LATG) and the distal gastrectomy group (SILD + 1 and C-LADG). The demographics, tumor characteristics, postoperative outcomes, and short-term complications of all enrolled patients were summarized and statistically analyzed. RESULTS: The mean incision length in SILT+1 group was 5.40 cm shorter than that in C-LATG group (3.15 ± 0.43 vs. 8.55 ± 2.72, P < 0.001). This comparison between the SILD + 1 and the C-LADG group produced comparable results. The SILT+1 group underwent a 56.32 min longer operation than the C-LATG group (273.03 ± 66.80 vs. 216.71 ± 82.61, P = 0.0205). SILG+1 group had better postoperative visual analog scale (VAS) and cosmetic score than those of the C-LATG group (P < 0.05). There were no significant differences in preoperative demographics or 30-day postoperative complication rates between the SILG+1 and C-LAG groups. Tumor-related index, including mass size, histological type, number of retrieved lymph nodes, pathological tumor-node-metastasis (TNM) stage, and proximal and distal edges were all equivalent between the SILG+1 and the C-LAG group. CONCLUSIONS: This retrospective study demonstrates the safety and feasibility of SILG+1 with D1+ or D2 lymphadenectomy for the treatment of early and advanced gastric cancers, compared with C-LAG.

Repetitive transcranial magnetic stimulation modulates coupling among large-scale brain networks in heroin-dependent individuals: A randomized resting-state functional magnetic resonance imaging study.

The abnormal interactions of three key large-scale brain networks (default mode [DMN], salience and executive control [ECN]) were showed underlie dysfunctions in heroin addiction. Repetitive transcranial magnetic stimulation (rTMS) targeting the left dorsolateral prefrontal cortex (DLPFC) is a potential treatment for heroin addiction. It is unclear whether impaired coupling among the large-scale brain networks would be improved by rTMS in treated heroin-dependent individuals. Thirty-five heroin-dependent individuals were included in this sham-controlled, randomized study. The patients received either active or sham rTMS for 1 week. The craving for heroin and resting-state functional magnetic resonance imaging data were collected before and after 1-week rTMS. Twenty-two healthy subjects were included as controls not receiving rTMS. After 1-week rTMS, only the active rTMS group showed a significant decrease in spontaneous and heroin cue-induced craving. The coupling between left DLPFC (a key node of left ECN) and left parahippocampal gyrus (PHG, included in DMN) significantly increased for the active group with a tendency towards that of controls. The coupling between the right precentral gyrus and three key regions included in DMN (posterior cingulate cortex/precuneus and bilateral inferior parietal cortex) significantly decreased for the active group with a tendency towards that of healthy controls. For the active rTMS individuals, the left DLPFC-PHG coupling negatively correlated with the spontaneous craving and the drug cue-induced craving. It suggested that the rTMS could reduce heroin craving, which might be related to the modulation of ECN-DMN coupling. This finding might shed light on the mechanism of rTMS for heroin addiction treatment.

Meta-Knowledge and Multi-Task Learning-Based Multi-Scene Adaptive Crowd Counting.

In this paper, we propose a multi-scene adaptive crowd counting method based on meta-knowledge and multi-task learning. In practice, surveillance cameras are stationarily deployed in various scenes. Considering the extensibility of a surveillance system, the ideal crowd counting method should have a strong generalization capability to be deployed in unknown scenes. On the other hand, given the diversity of scenes, it should also effectively suit each scene for better performance. These two objectives are contradictory, so we propose a coarse-to-fine pipeline including meta-knowledge network and multi-task learning. Specifically, at the coarse-grained stage, we propose a generic two-stream network for all existing scenes to encode meta-knowledge especially inter-frame temporal knowledge. At the fine-grained stage, the regression of the crowd density map to the overall number of people in each scene is considered a homogeneous subtask in a multi-task framework. A robust multi-task learning algorithm is applied to effectively learn scene-specific regression parameters for existing and new scenes, which further improve the accuracy of each specific scenes. Taking advantage of multi-task learning, the proposed method can be deployed to multiple new scenes without duplicated model training. Compared with two representative methods, namely AMSNet and MAML-counting, the proposed method reduces the MAE by 10.29% and 13.48%, respectively.

Deep Reinforcement Learning-Based Resource Allocation for Satellite Internet of Things with Diverse QoS Guarantee.

Large-scale terminals' various QoS requirements are key challenges confronting the resource allocation of Satellite Internet of Things (S-IoT). This paper presents a deep reinforcement learning-based online channel allocation and power control algorithm in an S-IoT uplink scenario. The intelligent agent determines the transmission channel and power simultaneously based on contextual information. Furthermore, the weighted normalized reward concerning success rate, power efficiency, and QoS requirement is adopted to balance the performance between increasing resource efficiency and meeting QoS requirements. Finally, a practical deployment mechanism based on transfer learning is proposed to promote onboard training efficiency and to reduce computation consumption of the training process. The simulation demonstrates that the proposed method can balance the success rate and power efficiency with QoS requirement guaranteed. For S-IoT's normal operation condition, the proposed method can improve the power efficiency by 60.91% and 144.44% compared with GA and DRL_RA, while its power efficiency is only 4.55% lower than that of DRL-EERA. In addition, this method can be transferred and deployed to a space environment by merely 100 onboard training steps.

Intermediate filament accumulation can stabilize microtubules in Caenorhabditis elegans motor neurons.

Neural circuits utilize a coordinated cellular machinery to form and eliminate synaptic connections, with the neuronal cytoskeleton playing a prominent role. During larval development of Caenorhabditis elegans, synapses of motor neurons are stereotypically rewired through a process facilitated by dynamic microtubules (MTs). Through a genetic suppressor screen on mutant animals that fail to rewire synapses, and in combination with live imaging and ultrastructural studies, we find that intermediate filaments (IFs) stabilize MTs to prevent synapse rewiring. Genetic ablation of IFs or pharmacological disruption of IF networks restores MT growth and rescues synapse rewiring defects in the mutant animals, indicating that IF accumulation directly alters MT stability. Our work sheds light on the impact of IFs on MT dynamics and axonal transport, which is relevant to the mechanistic understanding of several human motor neuron diseases characterized by IF accumulation in axonal swellings.

Time-moduated nonreciprocal metasurface absorber for surface waves.

We have investigated a magnet-free, nonreciprocal surface wave absorber based on high impedance surfaces (HISs) using a spatial-temporal modulation approach. By controlling embedded switches with a travelling wave, the HIS metasurface is modulated to break the time and spatial symmetry, which enables surface waves to propagate in one direction but be absorbed when propagating in the reverse direction. The nonreciprocity has been demonstrated by an EM-circuit co-simulation. We envision that this could be possibly applied in future communication systems that preferably transmit unidirectionally but absorb interference from the reverse direction caused by reflections or other devices.

Construction of a novel Chinese normal brain database using 18F-FDG PET images and MIMneuro software, the initial application in epilepsy.

PURPOSE: To create a standard Western Chinese normal functional brain database for quantitative analysis using 2-deoxy-2-[18F] fluoro-d-glucose (18F-FDG) positron emission tomography (PET) images and MIMneuro software. METHODS: 78 healthy right-handed Chinese volunteers from Tangdu Hospital were scanned using 18F-FDG PET to evaluate brain metabolism between March and October 2016. All PET images were processed using MIMneuro software to create a normal database platform. The platform included anatomical optimization to facilitate spatial localization of abnormalities and a statistical comparison with normal cases utilizing the Z-scores, which represent the number of standard deviations from the mean of the normal controls in the database. RESULTS: The novel Chinese brain metabolism database platform including 78 healthy volunteers (male: female 40:38; age 3-78 years, mean age, 45 years) was constructed based on the MIMneuro software, which increased the diagnostic confidence in the test patient by quantifying and emphasizing the abnormality. The BrainAlignTM deformation algorithm of MIMneuro matched the size, shape, and orientation of the patient's brain scan to a template brain for comparison against a database of normal controls. The quantitative analysis performed on a voxel and regional level was useful in assessing the areas of abnormalities. CONCLUSIONS: A novel Chinese 18F-FDG PET-based normal brain function database was created to highlight the local regions of abnormal metabolic activity through quantitative comparisons against the normal database. The Z-scores obtained by MIMneuro potentially aid in visualizing and quantifying the subtle lesions on 18FDG-PET scan images as observed in a patient diagnosed with epilepsy.

Pedestal-free 25-GHz subpicosecond optical pulse source for 16 × 25-Gb/s OTDM based on phase modulation and dual-stage nonlinear compression.

An optical pulse generation scheme based on an ultra-short chirped seed pulse generator followed by a dual-stage fiber-based nonlinear pulse processing stage is proposed and demonstrated experimentally. After phase modulation and linear-chirp compensation, optical seed pulse with a duty cycle of 9.8% and an obvious pedestal is obtained. By soliton compression and Mamyshev reshaping, a pedestal-free optical pulse with a duty cycle of 2% and an extinction ratio of 27 dB is achieved. The optical pulse source is further applied in a 16×25-Gb/s on-off keying optical time-division multiplexing transmitter.