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Objective. Mesenchymal stem cell (MSC) therapy has been explored in Huntington disease (HD) as a potential therapeutic approach; however, a complete synthesis of these results is lacking. We conducted a meta-analysis to evaluate the effects of MSCs on HD. Method. Eligible studies published before November 2022 were screened from Embase, PubMed, Web of Science, Medline, and Cochrane in accordance with PRISMA guidelines. ClinicalTrial.gov and the World Health Organization International Clinical Trials Registry Platform were also searched for registered clinical trials. The outcomes in rodent studies evaluated included morphological changes (striatal volume and ventricular volume), motor function (rotarod test, wire hang test, grip strength test, limb-clasping test, apomorphine-induced rotation test, and neuromuscular electromyography activity), cognition (Morris water maze test), and body weight. Result. The initial search returned 362 records, of which 15 studies incorporating 346 HD rodents were eligible for meta-analysis. Larger striatal and smaller ventricular volumes were observed in MSC-treated animals compared to controls. MSCs transplanted before the occurrence of motor dysfunction rescued the motor incoordination of HD. Among different MSC sources, bone marrow mesenchymal stem cells were the most investigated cells and were effective in improving motor coordination. MSC therapy improved muscle strength, neuromuscular electromyography activity, cortex-related motor function, and striatum-related motor function, while cognition was not changed. The body weight of male HD rodents increased after MSC transplantation, while that of females was not affected. Conclusion. Meta-analysis showed a positive effect of MSCs on HD rodents overall, as reflected in morphological changes, motor coordination, muscle strength, neuromuscular electromyography activity, cortex-related motor function, and striatum-related motor function, while cognition was not changed by MSC therapy.

Alternanthera philoxeroides, an invasive alien malignant weed, competes with rice for water, fertilizer, light, and growth space before seedling closure stages, which commonly stresses the growth of rice. Chemical herbicides are mainly used to control weeds. However, excessive use of chemical herbicides could lead to serious environmental pollution. With the rapid development of artificial intelligence and deep-learning techniques, it is possible to reduce the use of chemical herbicides by spraying herbicides on only precise regions of weeds in rice fields. To improve the accuracy of the model in identifying weed regions, in this study the performance among the you only look once (YOLO) series and single-shot multibox detector (SSD) one-stage target detection models, i.e., YOLOv3, YOLOv4-tiny, YOLOv5-s, and SSD target detection networks, is discussed. The experimental results showed that the SSD-based target detection model for Alternanthera philoxeroides was better than the YOLO series due to its higher recall, mAP (mean average precision), and F1 values, which reached 0.874, 0.942, and 0.881, respectively. Meanwhile, the target detection model based on SSD performed better than the YOLO series when dealing with mutual occlusion images between seedlings and Alternanthera philoxeroides. In conclusion, in this study a high-accuracy method is provided for detecting precise regions of Alternanthera philoxeroides by constructing a model based on SSD, contributing to the reduction of environmental pollution.

Two Cu(i) CPs based on a new heterotopic tripodal ligand were constructed and their visible-light-driven photocatalytic performance were studied.

Metal-organic framework (MOF) glass is a new type of glass material, but it usually lacks sufficient porosity. Thus, regulating the pore structure of MOF glass to improve its adsorption performance is very important. Herein, we found that the porosity of MOF glasses agZIF-62 and agZIF-76 can be regulated via an ammonia-immersion approach. After ammonia immersion, the resulting agZIF-62-NH

Allergic rhinitis (AR) threatens patient survival. CD4

Different from analyzing the time-series directly, the Poincaré cross-section method is employed in the dynamical study of the Rulkov mapping model, more importance is that some new phenomena of the model are reported in this paper. First, it is proved that x=−1 is the Poincaré cross-section for all non-converging-to-fixed-point trajectories based on fast-slow dynamics. Then, some new dynamics are presented by means of the Poincaré cross-section method. In detail, a “ lightning-shaped” periodic divider of the original model is introduced, which is caused by the different selection of the initial value of slow variable. The Period 3 on the Poincaré cross-section is proposed near the chaos region, which may be not reported in other literatures according to our understanding. In some parameter region, it will cause the pseudo chaos phenomenon, here the trajectories spend a lot time converging to a periodic solution. Besides, in the view of mean-field of action potential, the sensitiveness with small parameter’s perturbations is analyzed, which the period changes frequently in the bursts of spikes region, and it has robustness in the normal spikes region.

Inorganic salts usually demonstrate simple phasal behaviors in dilute aqueous solution mainly involving soluble (homogeneous) and insoluble (macrophase separation) scenarios. Herein, we report the discovery of complex phase behavior involving multiple phase transitions of clear solution – macrophase separation – gelation – solution – macrophase separation in the dilute aqueous solutions of a structurally well-defined molecular cluster [Mo7O24]6− macroanions with the continuous addition of Fe3+. No chemical reaction was involved. The transitions are closely related to the strong electrostatic interaction between [Mo7O24]6− and their Fe3+ counterions, the counterion-mediated attraction and the consequent charge inversion, leading to the formation of linear/branched supramolecular structures, as confirmed by experimental results and molecular dynamics simulations. The rich phase behavior demonstrated by the inorganic cluster [Mo7O24]6− expands our understanding of nanoscale ions in solution.

Introduction. Thoracoscopic minimally invasive surgery is the main method for the treatment of lung cancer. The reduction of surgical trauma can effectively reduce the intraoperative and postoperative inflammatory reaction. The aim of the study is to compare the intraoperative and postoperative inflammatory reactions in patients with non-small-cell lung cancer (NSCLC) treated by single-port thoracoscopic surgery and three-port thoracoscopic surgery. Methods. A total of 68 NSCLC patients (stages I and II) of thoracoscopic surgery were selected and randomly divided into two groups where they received either single-port thoracoscopic surgery or three-port thoracoscopic surgery. Intraoperative and postoperative serum inflammatory markers (C-reactive protein, CRP; serum amyloid A protein, SAA; and interleukin 6, IL-6) were detected using the enzyme-linked immunosorbent assay. Results. The CRP level of the single-port group was significantly lower than that of the three-port group during surgery, the first day after surgery, and third day after surgery ( P < 0.05 ). The level of IL-6 in the single-port group was significantly lower than that in the three-port group during surgery on the first and third days after surgery ( P < 0.05 ). The level of SAA in the single-port group was also significantly lower than that in the three-port group on the first and third days after surgery ( P < 0.05 ). Conclusion. Compared with three-port thoracoscopic surgery, single-port thoracoscopic surgery could reduce the inflammatory response and improve the recovery of NSCLC patients. Single-port thoracoscopic surgery is worthy of further promotion in the current treatment field of NSCLC in terms of reducing intraoperative and postoperative inflammatory reactions.

An AlGaInAs multiple-quantum-well (MQW) polarization mode controller (PMC) using a stepped height ridge waveguide is presented, which is monolithically integrated with a sidewall grating distributed feedback laser using quantum well intermixing (QWI). QWI is used to create a 100 nm blueshift in the PMC and to eliminate the anisotropy and birefringence of the MQW structure. The PMC structure is modelled and optimized using a 3D full-vectorial Finite-Element Method package. The maximum polarization conversion efficiency (PCE) is around 96% for a 537-μm-long PMC operating a wavelength of 1550 nm. To maintain a PCE of ≥90%, the fabrication tolerances of the dry-etch corner and ridge waveguide widths are ± 0.05 μm and ± 0.03 μm respectively. The main advantages of the proposed design are that only a single step of MOPVE and two steps of dry etching are required for the whole integrated device, significantly reducing complexity and cost.

Background While 5% of 247 million global malaria cases are reported in Uganda, it is also a top refugee hosting country in Africa, with over 1.36 million refugees. Despite malaria being an emerging challenge for humanitarian response in refugee settlements, little is known about its risk factors. This study aimed to investigate the risk factors for malaria infections among children under 5 years of age in refugee settlements in Uganda. Methods We utilized data from Uganda’s Malaria Indicator Survey which was conducted between December 2018 and February 2019 at the peak of malaria season. In this national survey, household level information was obtained using standardized questionnaires and a total of 7787 children under 5 years of age were tested for malaria using mainly the rapid diagnostic test. We focused on 675 malaria tested children under five in refugee settlements located in Yumbe, Arua, Adjumani, Moyo, Lamwo, Kiryadongo, Kyegegwa, Kamwenge and Isingiro districts. The extracted variables included prevalence of malaria, demographic, social-economic and environmental information. Multivariable logistic regression was used to identify and define the malaria associated risk factors. Results Overall, malaria prevalence in all refugee settlements across the nine hosting districts was 36.6%. Malaria infections were higher in refugee settlements located in Isingiro (98.7%), Kyegegwa (58.6%) and Arua (57.4%) districts. Several risk factors were significantly associated with acquisition of malaria including fetching water from open water sources [adjusted odds ratio (aOR) = 1.22, 95% CI: 0.08–0.59, P = 0.002], boreholes (aOR = 2.11, 95% CI: 0.91–4.89, P = 0.018) and water tanks (aOR = 4.47, 95% CI: 1.67–11.9, P = 0.002). Other factors included pit-latrines (aOR = 1.48, 95% CI: 1.03–2.13, P = 0.033), open defecation (aOR = 3.29, 95% CI: 1.54–7.05, P = 0.002), lack of insecticide treated bed nets (aOR = 1.15, 95% CI: 0.43–3.13, P = 0.003) and knowledge on the causes of malaria (aOR = 1.09, 95% CI: 0.79–1.51, P = 0.005). Conclusions The persistence of the malaria infections were mainly due to open water sources, poor hygiene, and lack of preventive measures that enhanced mosquito survival and infection. Malaria elimination in refugee settlements requires an integrated control approach that combines environmental management with other complementary measures like insecticide treated bed nets, indoor residual spraying and awareness. Graphical Abstract

Transcranial ultrasound stimulation is a neurostimulation technique that has gradually attracted the attention of researchers, especially as a potential therapy for neurological disorders, because of its high spatial resolution, its good penetration depth, and its non-invasiveness. Ultrasound can be categorized as high-intensity and low-intensity based on the intensity of its acoustic wave. High-intensity ultrasound can be used for thermal ablation by taking advantage of its high-energy characteristics. Low-intensity ultrasound, which produces low energy, can be used as a means to regulate the nervous system. The present review describes the current status of research on low-intensity transcranial ultrasound stimulation (LITUS) in the treatment of neurological disorders, such as epilepsy, essential tremor, depression, Parkinson's disease (PD), and Alzheimer's disease (AD). This review summarizes preclinical and clinical studies using LITUS to treat the aforementioned neurological disorders and discusses their underlying mechanisms.

Photodiodes (PDs) which convert optical signals to electrical signals have been widely used in many fields. In contrast to pin PDs, in uni-traveling carrier (UTC) PDs, the absorption layer is p type doped and only photo-generated electrons are transported, which results in several superior characteristics including super high speed operation, high saturation current and low voltage operation. In this work, high speed InP based waveguide UTC-PDs have been fabricated by Zn diffusion doping for the first time to our knowledge, in contrast to the in situ doping of previous UTC-PDs. Diffusion doping will make it much easier for the UTC-PDs to be integrated with high quality passive waveguide and multi-quantum well (MQW) based active devices for photonic integrated circuit (PIC) applications. UTC-PDs with 3 × 15, 3 × 25 and 3 × 50 µm2 absorption areas are fabricated, all having over 50 GHz bandwidth at -1V bias voltage. At -3 V bias, the RF power at 40 GHz shows no saturation at up to 17 mA photocurrent for the 3 × 25 µm2 PD.

A nitrogen-rich mesoporous multi-walled carbon nanotube-dispersed Fe and Zn site oxygen reduction electrocatalyst was designed and fabricated by a secondary coordination chemistry strategy and molten-salt route.

A Ni(ii) MOF based on a imidazole–tetrazole heterotopic tripodal ligand was constructed. It exhibits abilities for the stable capture of iodine molecules present in cyclohexane, water, and vapor, via amorphization induced by guest exchange.

Background Globally, 5% of 247 million global malaria cases are reported Uganda which is also one of the top refugee hosting countries in Africa, with 1.36 million refugees currently. Although malaria is an emerging challenge for humanitarian response in refugee settlements, little is known about its risk factors. The study analysed data from the 2018-19 Uganda Malaria Indicator Survey (UMIS) to determine the factors associated with malaria infections among refugee children under five years of age. Methods The analysis was run using the ‘Individual dataset’ of UMIS. The independent variables related to the demographic, social-economic and environmental information on 3,481 refugees spreading across the country. The rapid diagnostics test results was the outcome variable. Multivariate logistic regression was performed to identify predictors of the malaria infections. Results Overall, the prevalence of malaria infections in all refugee settlements across the nine hosting districts was 36.6%. Malaria infections were higher in refugee settlements located in Isingiro (98.7%), Kyegegwa (58.6%) and Arua (57.4%) districts. The odds of contracting malaria were higher in refugee households whose children were aged 31–45 months (AOR = 2.14, 95% CI = 1.32–3.47) and above 45 months (AOR = 2.01, 95% CI = 1.22–3.32). Households whose main sources of domestic water were open water sources, boreholes and water tanks, were 1.22 (AOR = 1.22, 95% CI = 0.08–0.59), 2.11(AOR = 2.11, 95% CI = 0.91–4.89) and 4.47(AOR = 4.47, 95% CI = 1.67–11.9) times more likely to have their children contracting malaria. Households which used pit latrines and those without any toilet facility or used open defecation methods were 1.48 (AOR = 1.48, 95% CI = 1.03–2.13) and 3.29 (AOR = 3.29, 95% CI = 1.54–7.05) times more likely to have their children contracting malaria. Households which did not have insecticide treated bed nets or sprayed their households were 1.15 (AOD = 1.15, 95% CI = 0.43–3.13) and 8.04 (AOD = 8.04, 95% CI = 2.47–26.2) times more likely to have their children contracting malaria. Households which did not know that mosquito bites caused malaria, were 1.09 (AOD = 1.09, 95%=0.79–1.51) times more likely to have their children getting malaria. Conclusions These findings suggest that humanitarian responses and investments that reduce survival, biting, feeding, parasite development and breeding of mosquitoes will provide malaria health benefits in refugee settlements in Uganda.

Video Anomaly Detection (VAD) is an essential yet challenging task in signal processing. Since certain anomalies cannot be detected by isolated analysis of either temporal or spatial information, the interaction between these two types of data is considered crucial for VAD. However, current dual-stream architectures either confine this integral interaction to the bottleneck of the autoencoder or introduce anomaly-irrelevant background pixels into the interactive process, hindering the accuracy of VAD. To address these deficiencies, we propose a Multi-scale Spatial-Temporal Interaction Network (MSTI-Net) for VAD. First, to prioritize the detection of moving objects in the scene and harmonize the substantial semantic discrepancies between the two types of data, we propose an Attention-based Spatial-Temporal Fusion Module (ASTFM) as a substitute for the conventional direct fusion. Furthermore, we inject multi-ASTFM-based connections that bridge the appearance and motion streams of the dual-stream network, thus fostering multi-scale spatial-temporal interaction. Finally, to bolster the delineation between normal and abnormal activities, our system records the regular information in a memory module. Experimental results on three benchmark datasets validate the effectiveness of our approach, which achieves AUCs of 96.8%, 87.6%, and 73.9% on the UCSD Ped2, CUHK Avenue, and ShanghaiTech datasets, respectively.

The Ru@TiO2 sandwich structure of TiO2|Ru|TiO2 is developed by a novel synthesis by etching from two dimensional K2Ti2O5 in a salicylic acid solution and further inserting Ru nanodots between anatase...

Let $X$ be a metric space with doubling measure, and $L$ be a nonnegative self-adjoint operator on $L^2(X)$ whose heat kernel satisfies the Gaussian upper bound. Let $f$ be in the space $ {\rm BMO}_L(X)$ associated with the operator $L$ and we define its distance from the subspace $L^{\infty}(X)$ under the $ {\rm BMO}_L(X)$ norm as follows: $$ {\rm dist} (f, L^{\infty}):= \inf_{g\in L^{\infty}} \|f -g\|_{{\rm BMO}_L(X)}. $$ In this paper we prove that ${\rm dist} (f, L^{\infty})$ is equivalent to the infimum of the constant $\varepsilon$ in the John-Nirenberg inequality for the space ${\rm BMO}_L(X)$: $$ \sup_B { \mu\big(\{ x\in B: |f(x)-e^{-{r_B^2}L}f(x)|>\lambda\}\big) \over \mu(B)} \leq e^{-\lambda/\varepsilon}\ \ \ \ {\rm for\ large\ } \lambda. $$ This extends the well-known result of Garnett and Jones \cite{GJ1} for the classical ${\rm BMO}$ space (introduced by John and Nirenberg). As an application, we show that a ${\rm BMO}_L(X)$ function with compact support can be decomposed as the summation of an $L^\infty$-function and the integral of the heat kernel (associated with $L$) against a finite Carleson measure on $X\times[0,\infty)$. The key new technique is a geometric construction involving the semigroup $e^{-tL}$. We also resort to several fundamental tools including the stopping time argument and the random dyadic lattice.

Amine-functionalized covalent organic frameworks (COFs) hold great potential in diversified applications. However, the synthesis is dominated by postsynthetic modification, while the de novo synthesis allowing for direct installation of amine groups remains a formidable challenge. Herein, we develop a site-selective synthetic strategy for the facile preparation of amine-functionalized hydrazone-linked COF for the first time. A new monomer 2-aminoterephthalohydrazide (NH

Background Annexin A1 might be neuroprotective and serum annexin A1 concentrations were markedly declined after severe traumatic brain injury. We determine dthe ability of serum annexin A1 to assess severity and predict prognosis after aneurysmal subarachnoid hemorrhage (aSAH). Methods We included 157 aSAH patients and 157 healthy subjects. Serum annexin A1 measurements were measured. A poor outcome was designated as Glasgow outcome scale score of 1–3. Multivariate logistic regression analysis was applied to identify predictors of a poor 6-month outcome. Results Serum annexin A1 concentrations were significantly lower in patients than in controls. Annexin A1 concentrations were strongly correlated with the World Federation of Neurological Surgeons scale (WFNS) score, Hunt-Hess score, Glasgow coma scale score and modified Fisher score. A total of 59 patients (37.6%) experienced a poor outcome. Serum annexin A1, WFNS score and modified Fisher score emerged as the 3 independent predictors for a poor outcome after aSAH. Under ROC curve analysis, serum annexin A1 had a fair accuracy to predict a poor outcome, AUC of serum annexin A1 concentration was equivalent to those of WFNS score and modified Fisher score and AUC of combination of the 3 factors significantly exceeded that of each one alone. Conclusions Annexin A1 may be involved in the occurrence and progression of secondary brain injury after aSAH. Detection of serum annexin A1 may have certain ability for assessment of severity and prediction of long-term prognosis following aSAH.

With the aid of laboratory typing techniques, infectious disease surveillance networks have the opportunity to obtain powerful information on the emergence, circulation, and evolution of multiple genotypes, serotypes or other subtypes of pathogens, informing understanding of transmission dynamics and strategies for prevention and control. The volume of typing performed on clinical isolates is typically limited by its ability to inform clinical care, cost and logistical constraints, especially in comparison with the capacity to monitor clinical reports of disease occurrence, which remains the most widespread form of public health surveillance. Viewing clinical disease reports as arising from a latent mixture of pathogen subtypes, laboratory typing of a subset of clinical cases can provide inference on the proportion of clinical cases attributable to each subtype (i.e., the mixture components). Optimizing protocols for the selection of isolates for typing by weighting specific subpopulations, locations, time periods, or case characteristics (e.g., disease severity), may improve inference of the frequency and distribution of pathogen subtypes within and between populations. Here, we apply the Disease Surveillance Informatics Optimization and Simulation (DIOS) framework to simulate and optimize hand foot and mouth disease (HFMD) surveillance in a high-burden region of western China. We identify laboratory surveillance designs that significantly outperform the existing network: the optimal network reduced mean absolute error in estimated serotype-specific incidence rates by 14.1%; similarly, the optimal network for monitoring severe cases reduced mean absolute error in serotype-specific incidence rates by 13.3%. In both cases, the optimal network designs achieved improved inference without increasing subtyping effort. We demonstrate how the DIOS framework can be used to optimize surveillance networks by augmenting clinical diagnostic data with limited laboratory typing resources, while adapting to specific, local surveillance objectives and constraints.

We provide a connection between Brownian motion and a classical Newton mechanical system in dimension d ≥ 3 {d\geq 3} . This paper is an extension of [S. Liang, A mechanical model of Brownian motion for one massive particle including slow light particles, J. Stat. Phys. 170 2018, 2, 286–350]. Precisely, we consider a system of one massive particle interacting with an ideal gas, evolved according to non-random Newton mechanical principles, via interaction potentials, without any assumption requiring that the initial energies of the environmental particles should be restricted to be “high enough”. We prove that, as in the high-dimensional case, the position/velocity process of the massive particle converges to a diffusion process when the mass of the environmental particles converges to 0, while the density and the velocities of them go to infinity.

Metal-organic cages (MOCs) that assemble from metal ions or metal clusters and organic ligands have attracted the interest of the scientific community because of their various functional coordination cavities. Unlike metal-organic frameworks (MOFs) with infinite frameworks, MOCs have discrete structures, making them soluble and stable in certain solvents and facilitating their application as starting reagents in the further construction of single components or composite materials. In recent years, increasing progress has been made in this field. In this review, we introduce these works from the perspective of design strategies, and focus on how presynthesized MOCs can be used to construct functional materials. Finally, we discuss the challenges and development prospects in this field.

At present, the treatment of esophageal cancer (EC) is mainly surgical and drug treatment. However, due to drug resistance, these therapies can not effectively improve the prognosis of patients with the EC. Therefore, a multigene prognostic risk scoring system was constructed by bioinformatics analysis method to provide a theoretical basis for the prognosis and treatment decision of EC. The gene expression profiles and clinical data of esophageal cancer patients were gathered from the Cancer Genome Atlas TCGA database, and the differentially expressed genes (DEGs) were screened by R software. Genes with prognostic value were screened by Kaplan Meier analysis, followed by functional enrichment analysis. A cox regression model was used to construct the prognostic risk score model of DEGs. ROC curve and survival curve were utilized to evaluate the performance of the model. Univariate and multivariate Cox regression analysis was used to evaluate whether the model has an independent prognostic value. Network tool mirdip was used to find miRNAs that may regulate risk genes, and Cytoscape software was used to construct gene miRNA regulatory network. GSCA platform is used to analyze the relationship between gene expression and drug sensitivity. 41 DEGs related to prognosis were pre-liminarily screened by survival analysis. A prognostic risk scoring model composed of 8 DEGs (APOA2, COX6A2, CLCNKB, BHLHA15, HIST1H1E, FABP3, UBE2C and ERO1B) was built by Cox regression analysis. In this model, the prognosis of the high-risk score group was poor (P

The authors present sharp transformation inequalities for the zero-balanced hypergeometric function $${}_2F_1(a,b;a+b;r)$$ created by the transformations $$r\mapsto x=[(1-r)/(1+2r)]^3$$ and $$r\mapsto 1-x$$ , $$r\mapsto u=(1/2)r(3+r)^2(1+r)^{-3}$$ and $$r\mapsto 1-u$$ , $$r\mapsto p=(27/2)r(1+r)^4(1+4r+r^2)^{-3}$$ and $$r\mapsto 1-p$$ , by showing the monotonicity properties of certain combinations in terms of hypergeometric functions and elementary functions, thus extending the transformation identities satisfied by $${}_2F_1(1/3,2/3;1;r)$$ with these three pairs of transformations and substantively improving the related known results. With these results, some properties are obtained for the generalized Grotzsch ring functions and the modular functions appearing in Ramanujan’s modular equations. Some other properties of $${}_2F_1(a,b;c;r)$$ are obtained, too.

Rolling resistance and angle constraint are important factors affecting the control performance and dynamics of Two-Wheeled Inverted Pendulums (TWIPs, for short), but they are usually neglected in previous studies. Taking both factors into account, this paper presents new control designs for the angle control of the pendulum, for the velocity control and the position control of the TWIP system. Firstly, based on dimensionality reduction and the nonlinear dynamics of the inverted pendulum, a controller with simple structure is designed for controlling the pendulum angle when the rolling resistance is precisely known. Then an improved robust controller against the unknown rolling resistance is designed for the pendulum angle. Secondly, by using the dynamics theory of slow-fast systems, velocity and position controllers for the wheels of the TWIP system are proposed with known and unknown rolling resistance. In the position control, the overshoots can be adjusted close enough to zero. Numerical examples are given to verify and demonstrate the theoretical results.

Rational design of bifunctional electrocatalysts to promote the sluggish kinetics of oxygen reduction reaction (ORR) and oxygen evolution reaction (OER) remains a fundamental challenge for the application of zinc-air batteries (ZABs). Herein, we propose a facile and cost-effective strategy to in situ grow N-doped carbon nanotubes with encapsulated FeCo alloy nanoparticles on carbon cloths (FeCo/N-CNTs@CC) as a self-supported air cathode for rechargeable ZABs. The bamboo-like FeCo/N-CNTs@CC catalyst with high nitrogen content (10.5 atom %) exhibits excellent electrocatalytic activities, including a half-wave potential of 0.816 V for ORR and an overpotential of 1.638 V for OER at 10 mA cm–² in alkaline medium. Impressively, the liquid-state ZAB based on the FeCo/N-CNTs@CC cathode demonstrates a remarkable power density of 132.0 mW cm–² and a stable cycling performance over 65 h. Furthermore, the flexible all-solid-state ZAB possesses outstanding performance retention under various bending conditions. The electrocatalyst presented in this work holds great potential as a self-supported air cathode for practical applications.

Wastewater-based epidemiology (WBE) has become a valuable tool for monitoring SARS-CoV-2 infection trends throughout the COVID-19 pandemic. Population biomarkers that measure the relative human fecal contribution to normalize SARS-CoV-2 wastewater concentrations are needed for improved analysis and interpretation of community infection trends. The Centers for Disease Control and Prevention National Wastewater Surveillance System (CDC NWSS) recommends using the wastewater flow rate or human fecal indicators as population normalization factors. However, there is no consensus on which normalization factor performs best. In this study, we provided the first multistate assessment of the effects of flow rate and human fecal indicators (crAssphage, F+ Coliphage, and PMMoV) on the correlation of SARS-CoV-2 wastewater concentrations and COVID-19 cases using the CDC NWSS dataset of 182 communities across six U.S. states. Flow normalized SARS-CoV-2 wastewater concentrations produced the strongest correlation with COVID-19 cases. The correlation from the three human fecal indicators were significantly lower than flow rate. Additionally, using reverse transcription droplet digital polymerase chain reaction (RT-ddPCR) significantly improved correlation values over samples that were analyzed with real-time reverse transcription quantitative polymerase chain reaction (rRT-qPCR). Our assessment shows that utilizing flow normalization with RT-ddPCR generate the strongest correlation between SARS-CoV-2 wastewater concentrations and COVID-19 cases.