Experimental investigation on strengthening of Zea mays root fibres for biodegradable composite materials using potassium permanganate treatment.

Humans are the only species who generate waste materials that cannot be broken down by natural processes. The ideal solution to this waste problem would be to employ only compostable materials. Biodegradable materials play a key role in creating a safer and greener world. Biodegradability is the gift that keeps on giving, in the sense of creating an Earth worth living. The future is thus best served by green energy, sustainability, and renewable resources. To realize such goals, waste should be considered as a valuable resource. In this context, Zea mays (Zm) root fibres, which are normally considered as agricultural waste, can be used as reinforcing substances in polymer matrices to produce structural composite materials. Before being used in composites, such fibres must be analysed for their physical properties. Chemical treatments can be employed to improve the structural quality of fibres, and the changes due to such modification can be analysed. Therefore, the current work examines the effect of permanganate treatment on the surface properties of Zm fibres. The raw and potassium permanganate-treated samples were assayed for various properties. Physical analysis of the fibre samples yielded details concerning the physical aspects of the fibres. The thermal conductivity and moisture absorption behaviour of the samples were analysed. Chemical analysis was employed to characterize the composition of both treated and untreated samples. p-XRD was employed to examine the crystalline nature of the Zm fibres. Numerous functional groups present in each sample were analysed by FTIR. Thermogravimetric analysis was used to determine the thermal stability of Zm fibres. Elemental analysis (CHNS and EDS) was used to determine the elemental concentrations of both raw and treated samples. The surface alterations of Zm fibres brought on by treatment were described using SEM analysis. The characteristics of Zm roots and the changes in quality due to treatment were reviewed, and there were noticeable effects due to the treatment. Both samples would have applications in various fields, and each could be used as a potential reinforcing material in the production of efficient bio-composites.

On-Machine LTS Integration for Layer-Wise Surface Quality Characterization in MEX/P.

Material Extrusion (MEX) currently stands as the most widespread Additive Manufacturing (AM) process, but part quality deficiencies remain a barrier to its generalized industrial adoption. Quality control in MEX is a complex task as extrusion performance impacts the consistency of mechanical properties and the surface finish, dimensional accuracy, and geometric precision of manufactured parts. Recognizing the need for early-stage process monitoring, this study explores the potential of integrating Laser Triangulation Sensors (LTS) into MEX/P manufacturing equipment for layer-wise 3D inspections. Using a double-bridge architecture, an LTS-based sub-micrometric inspection system operates independently from the manufacturing process, enabling comprehensive digitization and autonomous reconstruction of the target layer's topography. Surface texture is then computed using standardized indicators and a new approach that provides insight into layer quality uniformity. A case study evaluating two alternative extruder head designs demonstrates the efficacy of this integrated approach for layer quality characterization. Implementing a generalized layer-wise procedure based on this integration can significantly mitigate quality issues in MEX manufacturing and optimize process parameter configurations for enhanced performance.

Correct Nucleotide Selection Is Confined at the Binding Site of Polymerase Enzymes.

DNA polymerases (Pols) add incoming nucleotides (deoxyribonucleoside triphosphate (dNTPs)) to growing DNA strands, a crucial step for DNA synthesis. The insertion of correct (vs incorrect) nucleotides relates to Pols' fidelity, which defines Pols' ability to faithfully replicate DNA strands in a template-dependent manner. We and others have demonstrated that reactant alignment and correct base pairing at the Pols catalytic site are crucial structural features to fidelity. Here, we first used equilibrium molecular simulations to demonstrate that the local dynamics at the protein-DNA interface in the proximity of the catalytic site is different when correct vs incorrect dNTPs are bound to polymerase ß (Pol ß). Formation and dynamic stability of specific interatomic interactions around the incoming nucleotide influence the overall binding site architecture. This explains why certain Pols' mutants can affect the local catalytic environment and influence the selection of correct vs incorrect nucleotides. In particular, this is here demonstrated by analyzing the interaction network formed by the residue R283, whose mutant R283A has an experimentally measured lower capacity of differentiating correct (G:dCTP) vs incorrect (G:dATP) base pairing in Pol ß. We also used alchemical free-energy calculations to quantify the G:dCTP →G:dATP transformation in Pol ß wild-type and mutant R283A. These results correlate well with the experimental trend, thus corroborating our mechanistic insights. Sequence and structural comparisons with other Pols from the same family suggest that these findings may also be valid in similar enzymes.

Tubular biomarkers and histology in lupus nephritis.

INTRODUCTION: The relevance of tubulo-interstitial involvement for kidney prognosis has recently been emphasized, but validated biomarkers for predicting histology are still lacking. The aim of our study was to evaluate different serum and urinary markers of tubular damage in patients with lupus nephritis (LN) and to correlate them with kidney histopathology. METHODS: A single-center retrospective study was conducted from January 2016 to December 2021. Serum and urine samples were collected on the same day of kidney biopsy and correlated with histologic data from a cohort of 15 LN patients. We analyzed the following urinary markers, adjusted for urine creatinine: beta 2-microglobulin, alpha 1-microglobulin, NGAL, uKIM-1, MCP-1, uDKK-3, and uUMOD. The serum markers sKIM-1 and sUMOD were also analyzed. RESULTS: A positive and strong correlation was observed between the degree of interstitial fibrosis (rho = 0.785, p = .001) and tubular atrophy (rho = 0.781, p = .001) and the levels of uDKK3. uUMOD also showed an inverse and moderate correlation with interstitial fibrosis (rho = -0.562, p = .037) and tubular atrophy (rho = -0.694, p = .006). Patients with >10% cortical interstitial inflammation had higher levels of uKIM-1 [4.9 (3.9, 5.5) vs. 0.8 (0.6, 1.5) mcg/mg, p = .001], MCP-1 [3.8 (2. 3, 4.2) vs. 0.7 (0.3, 1.2) mcg/mg, p = .001], sKIM-1 [9.2 (5.9, 32.7) vs. 1.4 (0, 3.5) pg/mL, p = .001], and lower sUMOD [8.7 (0, 39.7) vs. 46.1 (35.7, 53) ng/mL, p = .028]. CONCLUSION: The use of specific urinary and serum biomarkers of tubular dysfunction or injury may help to predict certain histologic parameters in LN patients.

Tubular biomarkers in proteinuric kidney disease: histology correlation and kidney prognosis of tubular biomarkers.

Background: Proteinuria is not only a biomarker of chronic kidney disease (CKD) but also a driver of CKD progression. The aim of this study was to evaluate serum and urinary tubular biomarkers in patients with biopsied proteinuric kidney disease and to correlate them with histology and kidney outcomes. Methods: A single-center retrospective study was conducted on a cohort of 156 patients from January 2016 to December 2021. The following urinary and serum biomarkers were analyzed on the day of kidney biopsy: beta 2 microglobulin (ß2-mcg), alpha 1 microglobulin (α1-mcg), neutrophil gelatinase-associated lipocalin (NGAL), urinary kidney injury molecule-1 (uKIM-1), monocyte chemoattractant protein-1 (MCP-1), urinary Dickkopf-3 (uDKK3), uromodulin (urinary uUMOD), serum kidney injury molecule-1 (sKIM-1) and serum uromodulin (sUMOD). A composite outcome of kidney progression or death was recorded during a median follow-up period of 26 months. Results: Multivariate regression analysis identified sUMOD (ß-0.357, P < .001) and uDKK3 (ß 0.483, P < .001) as independent predictors of interstitial fibrosis, adjusted for age, estimated glomerular filtration rate (eGFR) and log proteinuria. Elevated levels of MCP-1 [odds ratio 15.61, 95% confidence interval (CI) 3.52-69.20] were associated with a higher risk of cortical interstitial inflammation >10% adjusted for eGFR, log proteinuria and microhematuria. Upper tertiles of uDKK3 were associated with greater eGFR decline during follow-up. Although not a predictor of the composite outcome, doubling of uDKK3 was a predictor of kidney events (hazard ratio 2.26, 95% CI 1.04-4.94) after adjustment for interstitial fibrosis, eGFR and proteinuria. Conclusions: Tubular markers may have prognostic value in proteinuric kidney disease, correlating with specific histologic parameters and identifying cases at higher risk of CKD progression.

Enhancing reporting through structure: a before and after study on the effectiveness of SPIRIT-based templates to improve the completeness of reporting of randomized controlled trial protocols.

BACKGROUND: Despite the improvements in the completeness of reporting of randomized trial protocols after the publication of the Standard Protocol Items: Recommendations for Interventional Trial (SPIRIT) guidelines, many items remain poorly reported. This study aimed to assess the effectiveness of using SPIRIT-tailored templates for trial protocols to improve the completeness of reporting of the protocols that master's students write as part of their master's theses. METHODS: Before and after experimental study performed at the University Master's Degree in Orthopaedic Manual Physiotherapy of the Universitat Internacional de Catalunya (Barcelona, Spain). While students in the post-intervention period were instructed to use a trial protocol template that was tailored to SPIRIT, students in the pre-intervention period did not use the template. PRIMARY OUTCOME: Difference between the pre- and post-intervention periods in the mean number of adequately reported items (0-10 scale). The outcomes were evaluated independently and in duplicate by two blinded assessors. Students and their supervisors were not aware that they were part of a research project. For the statistical analysis, we used a generalized linear regression model (dependent variable: number of adequately reported items in the protocol; independent variables: intervention period, call, language). RESULTS: Thirty-four trial protocols were included (17, pre-intervention; 17, post-intervention). Protocols produced during the post-intervention period (mean: 8.24; SD: 1.52) were more completely reported than those produced during the pre-intervention period (mean: 6.35; SD: 1.80); adjusted difference: 1.79 (95% CI: 0.58 to 3.00). CONCLUSIONS: SPIRIT-based templates could be used to improve the completeness of reporting of randomized trial protocols.

Comparison of Refractive Index Matching Techniques and PLIF40 Measurements in Annular Flow.

This paper investigates non-invasive techniques for annular two-phase flow analysis, focusing on liquid film characterization to understand the interfacial phenomena that are crucial for heat and mass transfer. Limited methods allow the study of the temporal and spatial evolution of liquid film, such as Planar Laser-Induced Fluorescence (PLIF). However, this method possesses optical challenges, leading to the need for improved techniques to mitigate refraction and reflection, such as Refractive Index Matching (RIM). This study utilizes an experimental annular flow facility to analyze both RIM and non-RIM PLIF over a range of liquid Reynolds numbers from 4200 to 10,400. Three configurations-PLIF RIM90, PLIF RIM40, and PLIF nRIM40-are compared from both qualitative and quantitative perspectives. In the quantitative analysis, key variables of the liquid film are measured, namely mean film thickness, disturbance wave height, and frequency. Variations in the analyzed variables indicate minor deviations, which are not likely to be caused by the technique used. However, all three methodologies exhibited errors that are estimated to be within a maximum of 10%, with a mean value of approximately 8%.

How do sports injury epidemiological outcomes vary depending on athletes' response rates to a weekly online questionnaire? An analysis of 39-week follow-up from 391 athletics (track and field) athletes.

OBJECTIVE: To explore how sports injury epidemiological outcomes (i.e., prevalence, average prevalence, incidence, burden, and time to first injury) vary depending on the response rates to a weekly online self-reported questionnaire for athletes. METHODS: Weekly information on athletics injuries and exposure from 391 athletics (track and field) athletes was prospectively collected over 39 weeks (control group of the PREVATHLE randomized controlled trial) using an online self-reported questionnaire. The data were used to calculate sports injury epidemiological outcomes (i.e., prevalence, average prevalence, incidence, burden, and time to first injury) for sub-groups with different minimum individual athletes' response rates (i.e., from at least 100%, at least 97%, at least 95%, … to at least 0% response rate). We then calculated the relative variation between each sub-group and the sub-group with a 100% response rate as a reference. A substantial variation was considered when the relative variation was greater than one SD or 95% CI of the respective epidemiological outcome calculated in the sub-group with a 100% response rate. RESULTS: Of 15 249 expected weekly questionnaires, 7209 were completed and returned, resulting in an overall response rate of 47.3%. The individual athletes' response rates ranged from 0% (n = 51) to 100% (n = 100). The prevalence, average weekly prevalence, and time to first injury only varied substantially for the sub-groups below a 5%, 10% and 18% minimum individual response rate, respectively. The incidence and injury burden showed substantial variations for all sub-groups with a response rate below 100%. CONCLUSIONS: Epidemiological outcomes varied depending on the minimum individual athletes' response rate, with injury prevalence, average weekly prevalence, and time to first injury varying less than injury incidence and injury burden. This highlights the need to take into account the individual response rate when calculating epidemiological outcomes, and determining the optimal study-specific cut-offs of the minimum individual response rate needed.

Changes in renal blood flow after surgically induced weight loss: can bariatric surgery halt the progression of chronic kidney disease?

BACKGROUND: We previously demonstrated how kidney injury in patients with morbid obesity can be reversed by bariatric surgery (BaS). OBJECTIVE(S): Based on previous experience, we hypothesize patients' potentially reversible kidney injury might be secondary to reduction in renal blood flow (RBF), which improves following BaS. SETTING: Academic Hospital. METHODS: We conducted a retrospective analysis of patients who underwent BaS at our institution from 2002 to 2019. We identified patients with chronic kidney disease (CKD) using the estimated glomerular filtration rate (eGFR) from the CKD Epidemiology Collaboration Study (CKD-EPI) classification system. We used the BUN/Creatinine (Cr) ratio pre- and postoperatively to determine a prerenal (decreased RBF) versus intrinsic component as the responsible cause of CKD in this patient population. Decreased RBF was defined as BUN/Cr > 20 preoperatively. RESULTS: Our analysis included n = 2924 patients, of which 11% (n = 325) presented decreased RBF. From our original sample, only n = 228 patients had the complete data necessary to assess both eGFR and RBF (BUN/Cr). Patients with baseline CKD stage 2 demonstrated preoperative BUN/Cr 20.85 ± 10.23 decreasing to 14.99 ± 9.10 at 12-month follow-up (P < .01). Patients with baseline CKD stage 3 presented with preoperative BUN/Cr 23.88 ± 8.75; after 12-month follow-up, BUN/Cr ratio decreased to 16.38 ± 9.27 (P < .01). Patients with CKD stage 4 and ESRD (eGFR < 30) did not demonstrate a difference for pre- and postoperative BUN/Cr 21.71 ± 9.28 and 19.21 ± 14.58, respectively. CONCLUSION(S): According to our findings, patients with CKD stages 1-3 present improvement of their kidney function after BaS. This amelioration could be secondary to improvement of the RBF, an unstudied reversible mechanism of kidney injury in the bariatric population.

Risk factors for injury complaints leading to restricted participation in Athletics (Track and Field): a secondary analysis of data from 320 athletes over one season.

Objective: To investigate if several potential risk factors were associated with time to injury complaints leading to participation restriction in Athletics (ICPR). Methods: We performed a secondary analysis of data collected during 39 weeks of the 2017-2018 Athletics season in a cluster-randomised controlled trial ('PREVATHLE'). Univariate and multivariable analyses using Cox regression models were performed to analyse the association between the time to first ICPR and potential risk factors collected (1) at baseline: sex, age, height, body mass, discipline, the usual duration of Athletics training and non-specific sports training, ICPR in the preceding season (yes/no), ICPR at baseline (yes/no); (2) weekly during the season: duration and intensity of Athletics training and competition, and non-specific sports training, fitness subjective state, sleep duration and illness (yes/no); and (3) combined. Results: Data from 320 athletes were included; 138 (43.1%) athletes reported at least one ICPR during the study follow-up. The combined multivariable analyses revealed that the risk of ICPR at any given time was significantly higher in athletes with a pre-existing ICPR (hazard rate ratio, HRR 1.90, 95% CI 1.15 to 3.15; p=0.012) and lower in athletes with a higher fitness subjective state (HRR 0.63, 95% CI 0.55 to 0.73; p<0.001) and who had had at least one illness during the season (HRR 0.42, 95% CI 0.29 to 0.62; p<0.001). Conclusions: Our results provide new insights into injury risk factors in Athletics that could help with potential injury risk reduction strategies. These could be to explore the pre-existing injury presence at the season's beginning and to monitor the fitness subjective state and illnesses occurrence during the season. Trial registration: ClinicalTrials.gov Identifier: NCT03307434.

Why and when should organisms elongate their telomeres? Elaborations on the 'excess resources elongation' and 'last resort elongation' hypotheses.

Telomere length and telomere shortening are thought to be critical cellular attributes and processes that are related to an individual's life span and fitness. The general pattern across most taxa is that after birth telomere length gradually decreases with age. Telomere protection and restoration mechanisms are usually assumed to reduce the rate of shortening or at most keep telomere length constant. However, here we have compiled a list of 26 articles showing that there is an increasing number of studies reporting apparent elongation of telomeres (i.e., a net increase in TL from timet to timet+1) often in a considerable proportion of the individuals studied. Moreover, the few studies which have studied telomere elongation in detail show that increases in telomere length are unlikely to be due to measurement error alone. In this article, we argue that episodes of telomere elongation deserve more attention as they could reflect individual strategies to optimise life histories and maximise fitness, which may not be reflected in the overall telomere dynamics patterns. We propose that patterns of telomere (net) elongation may be partly determined by other factors than those causing telomere shortening, and therefore deserve analyses specifically targeted to investigate the occurrence of telomere elongation. We elaborate on two ecological hypotheses that have been proposed to explain patterns of telomere elongation (the 'excess resources elongation' and the 'last resort elongation' hypothesis) and we discuss the current evidence for (or against) these hypotheses and propose ways to test them.

A Novel Traffic Prediction Method Using Machine Learning for Energy Efficiency in Service Provider Networks.

This paper presents a systematic approach for solving complex prediction problems with a focus on energy efficiency. The approach involves using neural networks, specifically recurrent and sequential networks, as the main tool for prediction. In order to test the methodology, a case study was conducted in the telecommunications industry to address the problem of energy efficiency in data centers. The case study involved comparing four recurrent and sequential neural networks, including recurrent neural networks (RNNs), long short-term memory (LSTM), gated recurrent units (GRUs), and online sequential extreme learning machine (OS-ELM), to determine the best network in terms of prediction accuracy and computational time. The results show that OS-ELM outperformed the other networks in both accuracy and computational efficiency. The simulation was applied to real traffic data and showed potential energy savings of up to 12.2% in a single day. This highlights the importance of energy efficiency and the potential for the methodology to be applied to other industries. The methodology can be further developed as technology and data continue to advance, making it a promising solution for a wide range of prediction problems.

Relationship between a daily injury risk estimation feedback (I-REF) based on machine learning techniques and actual injury risk in athletics (track and field): protocol for a prospective cohort study over an athletics season.

INTRODUCTION: Two-thirds of athletes (65%) have at least one injury complaint leading to participation restriction (ICPR) in athletics (track and field) during one season. The emerging practice of medicine and public health supported by electronic processes and communication in sports medicine represents an opportunity for developing new injury risk reduction strategies. Modelling and predicting the risk of injury in real-time through artificial intelligence using machine learning techniques might represent an innovative injury risk reduction strategy. Thus, the primary aim of this study will be to analyse the relationship between the level of Injury Risk Estimation Feedback (I-REF) use (average score of athletes' self-declared level of I-REF consideration for their athletics activity) and the ICPR burden during an athletics season. METHOD AND ANALYSIS: We will conduct a prospective cohort study, called Injury Prediction with Artificial Intelligence (IPredict-AI), over one 38-week athletics season (from September 2022 to July 2023) involving competitive athletics athletes licensed with the French Federation of Athletics. All athletes will be asked to complete daily questionnaires on their athletics activity, their psychological state, their sleep, the level of I-REF use and any ICPR. I-REF will present a daily estimation of the ICPR risk ranging from 0% (no risk for injury) to 100% (maximal risk for injury) for the following day. All athletes will be free to see I-REF and to adapt their athletics activity according to I-REF. The primary outcome will be the ICPR burden over the follow-up (over an athletics season), defined as the number of days lost from training and/or competition due to ICPR per 1000 hours of athletics activity. The relationship between ICPR burden and the level of I-REF use will be explored by using linear regression models. ETHICS AND DISSEMINATION: This prospective cohort study was reviewed and approved by the Saint-Etienne University Hospital Ethical Committee (Institutional Review Board: IORG0007394, IRBN1062022/CHUSTE). Results of the study will be disseminated in peer-reviewed journals and in international scientific congresses, as well as to the included participants.

Speaker Counting Based on a Novel Hive Shaped Nested Microphone Array by WPT and 2D Adaptive SRP Algorithms in Near-Field Scenarios.

Speech processing algorithms, especially sound source localization (SSL), speech enhancement, and speaker tracking are considered to be the main fields in this application. Most speech processing algorithms require knowing the number of speakers for real implementation. In this article, a novel method for estimating the number of speakers is proposed based on the hive shaped nested microphone array (HNMA) by wavelet packet transform (WPT) and 2D sub-band adaptive steered response power (SB-2DASRP) with phase transform (PHAT) and maximum likelihood (ML) filters, and, finally, the agglomerative classification and elbow criteria for obtaining the number of speakers in near-field scenarios. The proposed HNMA is presented for aliasing and imaging elimination and preparing the proper signals for the speaker counting method. In the following, the Blackman-Tukey spectral estimation method is selected for detecting the proper frequency components of the recorded signal. The WPT is considered for smart sub-band processing by focusing on the frequency bins of the speech signal. In addition, the SRP method is implemented in 2D format and adaptively by ML and PHAT filters on the sub-band signals. The SB-2DASRP peak positions are extracted on various time frames based on the standard deviation (SD) criteria, and the final number of speakers is estimated by unsupervised agglomerative clustering and elbow criteria. The proposed HNMA-SB-2DASRP method is compared with the frequency-domain magnitude squared coherence (FD-MSC), i-vector probabilistic linear discriminant analysis (i-vector PLDA), ambisonics features of the correlational recurrent neural network (AF-CRNN), and speaker counting by density-based classification and clustering decision (SC-DCCD) algorithms on noisy and reverberant environments, which represents the superiority of the proposed method for real implementation.

A New COVID-19 Detection Method Based on CSK/QAM Visible Light Communication and Machine Learning.

This article proposes a novel method for detecting coronavirus disease 2019 (COVID-19) in an underground channel using visible light communication (VLC) and machine learning (ML). We present mathematical models of COVID-19 Deoxyribose Nucleic Acid (DNA) gene transfer in regular square constellations using a CSK/QAM-based VLC system. ML algorithms are used to classify the bands present in each electrophoresis sample according to whether the band corresponds to a positive, negative, or ladder sample during the search for the optimal model. Complexity studies reveal that the square constellation N=22i×22i,(i=3) yields a greater profit. Performance studies indicate that, for BER = 10-3, there are gains of -10 [dB], -3 [dB], 3 [dB], and 5 [dB] for N=22i×22i,(i=0,1,2,3), respectively. Based on a total of 630 COVID-19 samples, the best model is shown to be XGBoots, which demonstrated an accuracy of 96.03%, greater than that of the other models, and a recall of 99% for positive values.

A New Internet of Things Hybrid VLC/RF System for m-Health in an Underground Mining Industry.

This paper proposes a new system based on the Industrial Internet of Things (IIoT) for the monitoring of Mobile Health (m-Health) of workers in the underground mining industry. The proposed architecture uses a hybrid model in data transmission. Visible Light Communication (VLC) is used for downlink because of its narrow coverage, which aids in worker positioning. Radio frequency (RF) communication technology is used to send data for primary vital signs in the uplink, which is more efficient in transmission and is a viable solution according to the problem raised. The results obtained in terms of coverage and transmission for the downlink and uplink links show the feasibility of implementing the proposed system.

A Novel and Adaptive Angle Diversity-Based Receiver for 6G Underground Mining VLC Systems.

Visible light communication (VLC) is considered an enabling technology for future 6G wireless systems. Among the many applications in which VLC systems are used, one of them is harsh environments such as Underground Mining (UM) tunnels. However, these environments are subject to degrading environmental and intrinsic challenges for optical links. Therefore, current research should focus on solutions to mitigate these problems and improve the performance of Underground Mining Visible Light Communication (UM-VLC) systems. In this context, this article presents a novel solution that involves an improvement to the Angle Diversity Receivers (ADRs) based on the adaptive orientation of the Photo-Diodes (PDs) in terms of the Received Signal Strength Ratio (RSSR) scheme. Specifically, this methodology is implemented in a hemidodecahedral ADR and evaluated in a simulated UM-VLC scenario. The performance of the proposed design is evaluated using metrics such as received power, user data rate, and bit error rate (BER). Furthermore, our approach is compared with state-of-the-art ADRs implemented with fixed PDs and with the Time of Arrival (ToA) reception method. An improvement of at least 60% in terms of the analyzed metrics compared to state-of-the-art solutions is obtained. Therefore, the numerical results demonstrate that the hemidodecahedral ADR, with adaptive orientation PDs, enhances the received optical signal. Furthermore, the proposed scheme improves the performance of the UM-VLC system due to its optimum adaptive angular positioning, which is completed according to the strongest optical received signal power. By improving the performance of the UM-VLC system, this novel method contributes to further consideration of VLC systems as potential and enabling technologies for future 6G deployments.

Recognizing, normalizing and articulating: An approach to highlight plural values of water ecosystem services in Colombia.

The dialectical relationship between ecosystems and society is complex; therefore, holistic approaches are required to address this complexity. This view also stands out in the ecosystem services valuation field, where different scholars and global platforms have drawn attention to the need to incorporate plural valuation initiatives at decision-making. In this sense, through a comprehensive design, we conducted a multi-layered valuation of ecosystem services, and we highlighted multiple values in two areas of the province of Caldas, Colombia. We proposed a three-phase valuation process called Recognizing, Normalizing and Articulating values. Then, in cooperation with the regional environmental authority, we obtained different water-related ecosystem services values. Our results showed some warnings: first, we found mismatches between ecosystem services values; second, people assigned high values to ecosystems but the actual capacity of ecosystems to support ES is low. Finally, monetary values were marginal compared to social and ecological values. We conclude by saying that the more strata are assessed, the more values appear in the valuation scenarios, and those values could be conflicting. Our results have political implications, since they highlight the need to incorporate plural values as a fundamental tool for planning and land use in real scenarios where conflicts of interest and values are evident.

Recycling of Waste Toner Powder as Adsorbent to Remove Aqueous Heavy Metals.

The removal of Cd2+, Zn2+ and Ni2+ from metal solutions onto waste toner power (WTP) was investigated. The influence of parameters such as pH, contact time, initial metal concentration and adsorbent dosage was studied in batch adsorption experiments. Batch equilibrium experiments showed that the highest removal efficiency for Zn2+ and Cd2+ occurs at pH 7, while pH 5 is the most suitable for Ni2+ removal. The amount of metal removed (mg/g) improved when increasing the initial concentration, and sorption of heavy metals reached equilibrium in 24 h. Metals' uptake increased with increasing adsorbent dosage. The adsorption isotherms of Zn2+, Cd2+ and Ni2+ onto WTP fit the Langmuir better than the Freundlich model with correlation coefficient R2 values ranging from 0.998 to 0.968 and 0.989 to 0.881, respectively. The data showed that the maximum adsorption capacity of heavy metals, amax, ranged from 2.42 to 1.61 mg/g, from 6.22 to 2.01 mg/g and from 3.49 to 2.56 mg/g for Ni2+, Zn2+ and Cd2+, respectively, with the three WTPs used in this study. This adsorbent can potentially be used to remove metal ions from wastewater.