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A bstract The Coherent Neutrino-Nucleus Interaction Experiment (CONNIE) is taking data at the Angra 2 nuclear reactor with the aim of detecting the coherent elastic scattering of reactor antineutrinos with silicon nuclei using charge-coupled devices (CCDs). In 2019 the experiment operated with a hardware binning applied to the readout stage, leading to lower levels of readout noise and improving the detection threshold down to 50 eV. The results of the analysis of 2019 data are reported here, corresponding to the detector array of 8 CCDs with a fiducial mass of 36.2 g and a total exposure of 2.2 kg-days. The difference between the reactor-on and reactor-off spectra shows no excess at low energies and yields upper limits at 95% confidence level for the neutrino interaction rates. In the lowest-energy range, 50 − 180 eV, the expected limit stands at 34 (39) times the standard model prediction, while the observed limit is 66 (75) times the standard model prediction with Sarkis (Chavarria) quenching factors.

The Neutrinos Angra Experiment, a water-based Cherenkov detector, is located at the Angra dos Reis nuclear power plant in Brazil. Designed to detect electron antineutrinos produced in the nuclear reactor, the primary objective of the experiment is to demonstrate the feasibility of monitoring reactor activity using an antineutrino detector. This effort aligns with the International Atomic Energy Agency (IAEA) program to identify potential and novel technologies applicable to nonproliferation safeguards. Operating on the surface presents challenges such as high noise rates, necessitating the development of very sensitive, yet small-scale detectors. These conditions make the Angra experiment an excellent platform for both developing the application and gaining expertise in new technologies and analysis methods. The detector employs a water-based target doped with gadolinium to enhance its sensitivity to antineutrinos. In this work, we describe the main features of the detector and the electronics chain, including front-end and data acquisition components. We detail the data acquisition strategies and the methodologies applied for signal processing and event selection. Preliminary physics results suggest that the detector can reliably monitor reactor operations by detecting the inverse beta decay induced by electron antineutrinos from the reactor.

The Coherent Neutrino-Nucleus Interaction Experiment (CONNIE) is taking data at the Angra 2 nuclear reactor with the aim of detecting the coherent elastic scattering of reactor antineutrinos with silicon nuclei using charge-coupled devices (CCDs). In 2019 the experiment operated with a hardware binning applied to the readout stage, leading to lower levels of readout noise and improving the detection threshold down to 50 eV. The results of the analysis of 2019 data are reported here, corresponding to the detector array of 8 CCDs with a fiducial mass of 36.2 g and a total exposure of 2.2 kg-days. The difference between the reactor-on and reactor-off spectra shows no excess at low energies and yields upper limits at 95% confidence level for the neutrino interaction rates. In the lowest-energy range, 50-180 eV, the expected limit stands at 34 (39) times the standard model prediction, while the observed limit is 66 (75) times the standard model prediction with Sarkis (Chavarria) quenching factors.

Millicharged particles, proposed by various extensions of the standard model, can be created in pairs by high-energy photons within nuclear reactors and can interact electromagnetically with electrons in matter. Recently, the existence of a plasmon peak in the interaction cross-section with silicon in the eV range was highlighted as a promising approach to enhance low-energy sensitivities. The CONNIE and Atucha-II reactor neutrino experiments utilize Skipper-CCD sensors, which enable the detection of interactions in the eV range. We present world-leading limits on the charge of millicharged particles within a mass range spanning six orders of magnitude, derived through a comprehensive analysis and the combination of data from both experiments.

The Coherent Neutrino-Nucleus Interaction Experiment (CONNIE) aims to detect the coherent scattering (CE\\(\\nu\\)NS) of reactor antineutrinos off silicon nuclei using thick fully-depleted high-resistivity silicon CCDs. Two Skipper-CCD sensors with sub-electron readout noise capability were installed at the experiment next to the Angra-2 reactor in 2021, making CONNIE the first experiment to employ Skipper-CCDs for reactor neutrino detection. We report on the performance of the Skipper-CCDs, the new data processing and data quality selection techniques and the event selection for CE\\(\\nu\\)NS interactions, which enable CONNIE to reach a record low detection threshold of 15 eV. The data were collected over 300 days in 2021-2022 and correspond to exposures of 14.9 g-days with the reactor-on and 3.5 g-days with the reactor-off. The difference between the reactor-on and off event rates shows no excess and yields upper limits at 95% confidence level for the neutrino interaction rates comparable with previous CONNIE limits from standard CCDs and higher exposures. Searches for new neutrino interactions beyond the Standard Model were performed, yielding an improvement on the previous CONNIE limit on a simplified model with light vector mediators. A first dark matter (DM) search by diurnal modulation was performed by CONNIE and the results represent the best limits on the DM-electron scattering cross-section, obtained by a surface-level experiment. These promising results, obtained using a very small-mass sensor, illustrate the potential of Skipper-CCDs to probe rare neutrino interactions and motivate the plans to increase the detector mass in the near future.

The v-Angra experiment aims to estimate the flux of antineutrino particles coming out from the Angra II nuclear reactor. Such flux is proportional to the thermal power released in the fission process and therefore can be used to infer the quantity of fuel that has been burned during a certain period. To do so, the v-Angra Collaboration has developed an antineutrino detector and a complete acquisition system to readout and store the signals generated by its sensors. The entire detection system has been installed inside a container laboratory placed beside the dome of the nuclear reactor, in a restricted zone of the Angra II site. The system is supposed to work standalone for a few years in order to collect enough data so that the experiment can be validated. The detector's readout electronics and its environmental conditions are crucial parts of the experiment and they should work autonomously and be controlled and monitored remotely. Additionally, threshold configuration is a central issue of the experiment since antineutrino particles produce low energy signals in the detector, being necessary to carefully adjust it for all the detector channels in order to make the system capable of detecting signals as low as those generated by single photons. To this end, an embedded system was developed and integrated to the detection apparatus installed in the container at the Angra II site and is now operational and accessible to the v-Angra Collaboration. This article aims at describing the proposed embedded system and presenting the results obtained during its commissioning phase.

Diabetic foot ulcers (DFUs) are considered one of the most severe chronic complications of diabetes and can lead to amputation in severe cases. In addition, bacterial infections in diabetic chronic wounds aggravate this scenario by threatening human health. Wound dressings made of polymer matrices with embedded metal nanoparticles can inhibit microorganism growth and promote wound healing, although the current clinical treatments for diabetic chronic wounds remain unsatisfactory. In this view, this research reports the synthesis and characterization of innovative hybrid hydrogels made of carboxymethyl cellulose (CMC) and poly(vinyl alcohol) (PVA) chemically crosslinked by citric acid (CA) functionalized with silver nanoparticles (AgNPs) generated in situ using an eco-friendly aqueous process. The results assessed through comprehensive in vitro and in vivo assays demonstrated that these hybrid polymer hydrogels functionalized with AgNPs possess physicochemical properties, cytocompatibility, hemocompatibility, bioadhesion, antibacterial activity, and biocompatibility suitable for wound dressings to support chronic wound healing process as well as preventing and treating bacterial infections. Hence, it can be envisioned that, with further research and development, these polymer-based hybrid nanoplatforms hold great potential as an important tool for creating a new generation of smart dressings for treating chronic diabetic wounds and opportunistic bacterial infections.

Wound healing is important for skin after deep injuries or burns, which can lead to hospitalization, long-term morbidity, and mortality. In this field, tissue-engineered skin substitutes have therapy potential to assist in the treatment of acute and chronic skin wounds, where many requirements are still unmet. Hence, in this study, a novel type of biocompatible ternary polymer hybrid hydrogel scaffold was designed and produced through an entirely eco-friendly aqueous process composed of carboxymethyl cellulose, chitosan, and polyvinyl alcohol and chemically cross-linked by citric acid, forming three-dimensional (3D) matrices, which were biofunctionalized with L-arginine (L-Arg) to enhance cellular adhesion. They were applied as bilayer skin biomimetic substitutes based on human-derived cell cultures of fibroblasts and keratinocytes were seeded and grown into their 3D porous structures, producing cell-based bio-responsive hybrid hydrogel scaffolds to assist the wound healing process. The results demonstrated that hydrophilic hybrid cross-linked networks were formed via esterification reactions with the 3D porous microarchitecture promoted by foam templating and freeze-drying. These hybrids presented chemical stability, physicochemical properties, high moisture adsorption capacity, surface properties, and a highly interconnected 3D porous structure well suited for use as a skin substitute in wound healing. Additionally, the surface biofunctionalization of these 3D hydrogel scaffolds with L-arginine through amide bonds had significantly enhanced cellular attachment and proliferation of fibroblast and keratinocyte cultures. Hence, the in vivo results using Hairless mouse models (an immunocompromised strain) confirmed that these responsive bio-hybrid hydrogel scaffolds possess hemocompatibility, bioadhesion, biocompatibility, adhesiveness, biodegradability, and non-inflammatory behavior and are capable of assisting the skin wound healing process.

Chitosan is a polymer from natural source with a wide range of applications, such as in the adsorption of heavy metals. However, it presents limitation in relation to pH, because it is insoluble in neutral and alkaline. Thus, a good alternative has been the use of derivatives of chitosan, as carboxymethyl chitosan (CMC). This chemical modification of chitosan may favor the adsorption process, because it broadens the pH range of solubility and the quantity of chemical groups available for the uptake of ions. This work was carried out the synthesis and characterization of carboxymethyl chitosan. The properties of derivatives synthesized were assessed through the study of solubility at different pHs and using the techniques of potentiometric titration, Fourier transform infrared spectroscopy (FTIR), ultraviolet-visible (UV-vis) spectroscopy and thermal analysis. The results have demonstrated the effective incorporation of carboxylic groups in the structure of chitosan, as well as the dependence of degree of substitution with the concentration of hydroxide during the synthesis. Hence, the chemical functionalization of chitosan for producing carboxymethyl chitosan offers the possibility of applying this new adsorbent for water treatment.

Background Higher plantar pressures play an important role in the development of plantar foot ulceration in diabetic polyneuropathy and earlier studies suggest that higher pressures under the forefoot may be related to a decrease in lower leg muscle strength. Therefore, in this randomised controlled trial we evaluated whether lower-extremity strength training can reduce plantar pressures in diabetic polyneuropathy. Methods This study was embedded in an unblinded randomised controlled trial. Participants had diabetes and polyneuropathy and were randomly assigned to the intervention group (n = 48) receiving strength training during 24 weeks, or the control group (n = 46) receiving no intervention. Plantar pressures were measured in both groups at 0, 12, 24 and 52 weeks. A random intercept model was applied to evaluate the effects of the intervention on peak pressures and pressure–time-integrals, displacement of center-of-pressure and the forefoot to rearfoot pressure–time-integral-ratio. Results Plantar pressure patterns were not affected by the strength training. In both the intervention and control groups the peak pressure and the pressure–time-integral under the forefoot increased by 55.7 kPa (95% CI: 14.7, 96.8) and 2.0 kPa.s (95% CI: 0.9, 3.2) over 52 weeks, respectively. Both groups experienced a high number of drop-outs, mainly due to deterioration of health status and lower-extremity disabilities. Conclusions Plantar pressures under the forefoot increase progressively over time in people with diabetic polyneuropathy, but in this study were not affected by strength training. Future intervention studies should take this increase of plantar pressure into account and alternative interventions should be developed to reduce the progressive lower extremity problems in these patients. Trial registration This study was embedded in a clinical trial with trial number NCT00759265 .