Simultaneous Collection Research Articles

Three-dimensional measurements of scapular kinematics: Interrater reliability and validation of a skin marker-based model against an intracortical pin model

A skin marker-based motion capture model providing measures of scapular rotations was recently developed. The aim of this study was to investigate the concurrent validity and the interrater reliability of the model. Shoulder range of motion (RoM) and activities of daily living (ADL) were tested in healthy volunteers with reflective markers on the scapula and thorax. To investigate the validity, the model was compared to simultaneous data collection from markers on a scapular intracortical pin. The interrater reliability was tested by comparing the skin marker-based protocol performed by two investigators. The mean root mean square error (RMSE) and the intraclass correlation coefficient (ICC(2,1)) were calculated to determine the validity and the interrater reliability, respectively. Eight subjects were included in the validity test: female/male = 2/6, mean (SD) age 35.0 (3.0) and BMI 23.4 (3.3). The mean RMSE of all scapular rotations ranged 2.3–6.7° during shoulder RoM and 2.4–7.6° during ADL. The highest errors were seen during sagittal and scapular plane flexions, hair combing and eating. The reliability test included twenty subjects: female/male = 8/12, mean (SD) age 31.4 (4.9) and BMI 22.9 (1.7). The ICC(2,1) for measuring protraction ranged 0.07–0.60 during RoM and 0.27–0.69 for ADL, for upward rotation the corresponding ICC(2,1) ranged 0.01–0.64 and 0.38–0.60, and anterior tilt 0.25–0.83 and 0.25–0.62. The validity and interrater reliability of the model are task dependent, and interpretation should be made with caution. The model provides quantitative measurements for objective assessment of scapular movements and can potentially supplement the clinical examination in certain motion tasks.

Characterizing Water Composition with an Autonomous Robotic Team Employing Comprehensive In Situ Sensing, Hyperspectral Imaging, Machine Learning, and Conformal Prediction

Inland waters pose a unique challenge for water quality monitoring by remote sensing techniques due to their complicated spectral features and small-scale variability. At the same time, collecting the reference data needed to calibrate remote sensing data products is both time consuming and expensive. In this study, we present the further development of a robotic team composed of an uncrewed surface vessel (USV) providing in situ reference measurements and an unmanned aerial vehicle (UAV) equipped with a hyperspectral imager. Together, this team is able to address the limitations of existing approaches by enabling the simultaneous collection of hyperspectral imagery with precisely collocated in situ data. We showcase the capabilities of this team using data collected in a northern Texas pond across three days in 2020. Machine learning models for 13 variables are trained using the dataset of paired in situ measurements and coincident reflectance spectra. These models successfully estimate physical variables including temperature, conductivity, pH, and turbidity as well as the concentrations of blue–green algae, colored dissolved organic matter (CDOM), chlorophyll-a, crude oil, optical brighteners, and the ions Ca2+, Cl−, and Na+. We extend the training procedure to utilize conformal prediction to estimate 90% confidence intervals for the output of each trained model. Maps generated by applying the models to the collected images reveal small-scale spatial variability within the pond. This study highlights the value of combining real-time, in situ measurements together with hyperspectral imaging for the rapid characterization of water composition.

2 Number of spot samples required when using the GreenFeed System in grazing beef cows

Abstract Methane (CH4) production from beef cattle occurs through a natural digestive process called enteric fermentation. This has increasingly become an area of focus due to environmental and efficiency concerns. There are several techniques to quantify gas fluxes from beef cattle such as an open circuit gas quantification system (OCGQS). The GreenFeed (C-Lock, Inc.) is an OCGQS, which has been validated in previous literature, that is capable of quantifying CH4, carbon dioxide (CO2), and oxygen (O2) from grazing beef cattle. However, few studies have reported the minimum number of spot samples to quantify gas fluxes from an individual animal, particularly in a grazing environment. No recommendations have been made to evaluate the number of spot samples for the calculation of metabolic heat production, using the gas fluxes quantified by an OCGQS. A minimum of 100 spot samples each were collected from 17 grazing animals using an OCGQS. The mean gas fluxes were computed starting from the first 10 visits (forward) and increasing by increments of 10 until 100 visits was reached and also from visit 100 moving back in time in increments of 10 (reverse). Mean gas fluxes were used to calculate individual animal metabolic heat production for each interval with both the forward and reverse approach. Pearson and Spearman correlations were computed between the full 100 visits and each shortened visit interval. Mean forward and reverse gas fluxes and metabolic heat production were also computed starting at 30 visits and increasing by 2 until 40 visits and vice versa. The minimum number of spot samples was determined when correlations with the full 100 visits were greater than 0.95. The minimum number of spot samples needed for accurate quantification of CH4, CO2, O2, and metabolic heat production were 38, 40, 40, and 36, respectively. Simultaneous collection of gas fluxes for the calculation of metabolic heat production would require at least 40 spot samples given the recommendations for gas flux components. Animals had an average of 1.2 visits/day to the OCGQS in this study. Therefore, animals met the required number of spot samples for quantification of metabolic heat production, CH4, CO2, and O2 in 29.5 ± 8.7, 30.5 ± 9.1, 31.8 ± 9.2, and 31.8 ± 9.2 d, respectively. There was large variation in the number of days needed to achieve the recommended number of spot samples. For this reason, protocols for the OCGQS should be based on the total number of spot samples, rather than a test duration. These recommendations can be applied to grazing cattle that typically have more infrequent visits. More research is needed to establish if the minimum number of spot samples would be fewer if animals have more frequent visits, although this is difficult in grazing settings.

Adsorption of heavy metals from aqueous solutions by magnetic barium hydroxyapatite nanoparticles

ABSTRACT Magnetic barium hydroxyapatite (Fe3O4@BaHAP) nanoparticles were synthesised and used as a sorbent for the removal of several heavy metal ions from aqueous solutions. The sorbent characterisation was performed by scanning electron microscopy (SEM), X-ray diffraction (XRD), Brunauer–Emmett–Teller (BET), vibrating-sample magnetometer (VSM) and Fourier transform infrared spectroscopy (FTIR) techniques. A homemade device, named continuous collection of magnetic sorbent (CCMS), was designed for efficient removal of heavy metal ions from aqueous solutions and simultaneous collection of the sorbent by a permanent magnet at the end of the process. Results of BET analysis show that average pore diameter, average pore width, pore volume and specific surface area of the Fe3O4@BaHAP NPs were 10.9 nm, 11.6 nm, 0.16 cm3/g and 55.7 m2/g, respectively. Influential parameters on the removal efficiency were investigated and optimised using a central composite design method. The optimised values for solution pH, sorbent amount, stirring and circulating times were 6.2, 150 mg, 13 and 25 min, respectively. Magnetic BaHAP nanoparticles were shown to have higher removal efficiency than BaHAP or Fe3O4 alone. Under optimised conditions, adsorption capacities for Pb2+, Cr3+, Cd2+ and Cu2+ were 99.0, 66.5, 91.2 and 92.1 mg/g, respectively. The results demonstrated that the synthesised magnetic BaHAP nanoparticles can effectively remove several metal ions from contaminated water sources.

Probing the Reactive Intermediates in CO2 Hydrogenation on Ni/Al2O3 Catalysts with Modulation Excitation Spectroscopy

AbstractIn‐situ infrared spectroscopy is one of the most effective methods to study the surface species on solid catalysts. Still, it is sometimes difficult to identify the reactive intermediates because spectator species, the catalyst support, and experimental noise also contribute to the total spectra. In this study, we prepared three archetypical Ni/Al2O3 catalysts that showed significantly different catalytic activity and selectivity for CO2 hydrogenation, depending on the calcination and reduction temperature. After detailed characterization, we used a combination of Modulation Excitation‐Phase Sensitive Detection‐Diffuse Reflectance Infrared Fourier Transform Spectroscopy (ME‐PSD‐DRIFTS) and Steady State Isotopic Kinetic Analysis (SSITKA) to show that bicarbonates and formates are key reactive intermediates. Furthermore, we also observe carbonyls on the catalyst with the most metallic character and highest selectivity towards CH4. These results confirm that the hydrogenation of CO2 occurs in an associative and consecutive reaction pathway that is highly structure‐sensitive. In this way, we also demonstrate how the simultaneous collection of spectroscopic and kinetic data during modulated or transient experiments is a powerful tool for investigating solid catalysts under realistic operation conditions.

Optofluidic flow cytometer with in-plane spherical mirror for signals enhancement

Statistical analysis of properties of single microparticles, such as cells, bacteria or plastic slivers, has attracted increasing interest in recent years. In this field flow cytometry is considered the gold standard technique, but commercially available instruments are bulky, expensive, and not suitable for use in Point-of-Care (PoC) testing. Microfluidic flow cytometers, on the other hand, are small, cheap and can be used for on-site analysis. However, in order to detect small particles, they require complex geometries and the aid of external optical components. To overcome these limitations here we present an opto-fluidic flow cytometer with an integrated 3D in-plane spherical mirror for enhanced optical signal collection. As result the signal-to-noise ratio is increased by a factor of 6, enabling the detection of particle sizes down to 1.5μm. The proposed optofluidic detection scheme allows the simultaneous collection of particles fluorescence and scattering - using a single optical fiber - which is crucial to easily distinguish particle populations with different optical properties. The devices have been fully characterized using fluorescent polystyrene beads of different sizes. As a proof of concept for potential real-world applications, signals from fluorescent HEK cells and Escherichia coli bacteria were analyzed.

The Relationship between Personality and Academic Burnout: Exploring the Influence of Psychological Well-Being and Demographic Factors

The results of previous research have found that academic burnout occurs at all levels of education, including universities. Academic burnout is a syndrome characterized by emotional exhaustion, depersonalization, and a lack of confidence in students' abilities. It can be influenced by various variables, such as personality, well-being, and demographic factors. This research aims to examine the relationship between personality and academic burnout among college students while also exploring the role of psychological well-being as a mediator and demographic factors as a moderator, using a correlational design. This design allows for the simultaneous collection of data from many individuals. We recruited 522 undergraduate students to participate in an online survey and used the Maslach-Student Burnout Inventory (MSBI), NEO Five-Factor Inventory (FFI), and Psychological Well-being Questionnaire for measurement. For data analysis, we used SPSS version 25 and IBM SPSS AMOS version 24 to determine the mediation-moderation effect and tested the factor analysis of the proposed model. This research found a relationship between personality and academic burnout, with extraversion, agreeableness, conscientiousness, and openness to experience being associated with low academic burnout, while neuroticism was associated with high academic burnout. Furthermore, the level of student psychological well-being was found to mediate the correlation between personality and academic burnout. Therefore, this study recommends that students, teachers, and parents pay attention to the importance of psychological well-being.

Understanding Suicidal Behaviour and Distress in Young Muslim Canadians: A Qualitative Study

BACKGROUND: Suicide is a major public health concern worldwide, including in Canada. The onset of major mental illnesses occurs during adolescence and young adulthood. Among this group, young Muslims in Canada may be particularly vulnerable due to unique stressors and emerging evidence indicating that Muslims in the U.S. report more suicide attempts than other religious groups. To our knowledge, no prior study has undertaken an in-depth exploration of the lived experiences of Muslim young adults who have attempted suicide. This study aims to broaden our understanding of how Muslim young adults experience and understand suicidal behavior by exploring narratives of distress and help-seeking, the meanings of suicidal behavior, the impact of immigration/resettlement, discrimination, Islamophobia, and the role of negotiating multiple religious, cultural, and gender identities. METHODS: This study is currently in progress. We are recruiting approximately 25-30 Muslim youth between the ages of 15-24 who have experienced suicidal behavior with any intent to die, as reported by the participants themselves, within the Greater Toronto Area (GTA). Exclusion criteria include (1) active substance intoxication or withdrawal, (2) current admission to a psychiatric facility, and (3) low levels of intellectual functioning or a history of neurological impairment. We are conducting heterogeneous purposive sampling to ensure that our sample includes diversity in terms of gender, age, countries of origin, and first and second-generation youth. Recruitment will end when data saturation is reached. Each participant will take part in a semi-structured qualitative interview. The interview explores family and social contacts, immigration/acculturation experiences, gender and cultural roles, and views on religion. Data is being transcribed and analyzed in N-Vivo 12 software using constructivist grounded principles entailing simultaneous collection and analysis, inductive construction of abstract categories explaining social processes, sampling and categorical refinement through iterative analysis, and integration of categories into a theoretical framework. RESULTS: Preliminary data analysis is in progress based on participants (n=15) recruited thus far. Emerging themes in relation to the causes of suicidality include isolation and an inability to cope with multiple stressors, such as family conflict and physical illness. Religion has a varied effect on suicidality, ranging from minimal to strong influence and from being protective to triggering suicidality. Regarding barriers to care, emerging themes included fear of invalidation, Islamophobia, and the lack of cultural safety within the healthcare system. Notably, youth appear to have a different explanatory model for mental illness compared to their family/community. CONCLUSION: This is the first qualitative study examining the experiences of Canadian Muslim youth who have experienced suicidal behavior. Our findings will help elucidate the unique stressors and protective factors that influence suicide and suicidal behavior for Canadian Muslim youth. Understanding patterns of distress and barriers to care through qualitative analysis will provide critical context to ultimately develop appropriate and effective screening, service provision, and suicide prevention strategies.

Simultaneous passive acoustic monitoring uncovers evidence of potentially overlooked temporal variation in an Amazonian bird community

The vocal activity and detectability of tropical birds are subject to high levels of temporal heterogeneity, but quantifying patterns of diel and day‐to‐day variation in complex systems is challenging with traditional point count methods. As a result, research concerning stochastic temporal effects on tropical bird assemblages is limited, typically offering only broad conclusions, such as that overall activity is highest in the first few hours of the morning and some species are active at different times of the day. Passive acoustic monitoring introduces several advantages for studying temporal variation, particularly by enabling simultaneous and continuous data collection across adjacent sites. Here, we employed autonomous recording units to quantify temporal variation in bird vocal activity and observed species richness at an Amazonian reserve in Madre de Dios, Peru, a region featuring some of Earth's richest, most complex bird assemblages. We manually annotated 18 dawn hour recordings, collected simultaneously from three separate days at the same six sites, which represent various microhabitats and bird community compositions. We documented significant and consistent temporal variation in avian vocal activity levels and observed species richness within the dawn hour and across days. We found that temporal effects were stronger for vocal activity than for observed species richness and that vocal activity patterns over the course of the dawn hour varied between species. Our results indicate that overlooked temporal variation in Amazonian soundscapes may obfuscate the results of surveys that do not sufficiently account for temporal variables with simultaneous monitoring. While manual analysis of large volumes of soundscape data remains challenging, such data should be collected to supplement traditional surveys whenever possible. Rapid advances in the automated processing of acoustic data could lead to more efficient methods for reducing temporal bias and improving the calibration and accuracy of tropical bird surveys.

Development of an Automated Ultrasound Signal Indicator of Lung Interstitial Syndrome.

The number and distribution of lung ultrasound (LUS) imaging artifacts termed B-lines correlate with the presence of acute lung disease such as infection, acute respiratory distress syndrome (ARDS), and pulmonary edema. Detection and interpretation of B-lines require dedicated training and is machine and operator-dependent. The goal of this study was to identify radio frequency (RF) signal features associated with B-lines in a cohort of patients with cardiogenic pulmonary edema. A quantitative signal indicator could then be used in a single-element, non-imaging, wearable, automated lung ultrasound sensor (LUSS) for continuous hands-free monitoring of lung fluid. In this prospective study a 10-zone LUS exam was performed in 16 participants, including 12 patients admitted with acute cardiogenic pulmonary edema (mean age 60 ± 12 years) and 4 healthy controls (mean age 44 ± 21). Overall,160 individual LUS video clips were recorded. The LUS exams were performed with a phased array probe driven by an open-platform ultrasound system with simultaneous RF signal collection. RF data were analyzed offline for candidate B-line indicators based on signal amplitude, temporal variability, and frequency spectrum; blinded independent review of LUS images for the presence or absence of B-lines served as ground truth. Predictive performance of the signal indicators was determined with receiving operator characteristic (ROC) analysis with k-fold cross-validation. Two RF signal features-temporal variability of signal amplitude at large depths and at the pleural line-were strongly associated with B-line presence. The sensitivity and specificity of a combinatorial indicator were 93.2 and 58.5%, respectively, with cross-validated area under the ROC curve (AUC) of 0.91 (95% CI = 0.80-0.94). A combinatorial signal indicator for use with single-element non-imaging LUSS was developed to facilitate continuous monitoring of lung fluid in patients with respiratory illness.

“I think the rose-tinted glasses do just sort of slowly come off”: a grounded theory study on the development of empathy towards people with dementia in healthcare student education.

Background:Globally, dementia prevalence is rising. In the UK, over a million people are expected to be impacted by dementia by 2050. One in four hospital beds are occupied by a person with dementia, and it is inevitable that healthcare professionals will work with people with dementia during their career and across a variety of settings. To deliver effective person-centered care, healthcare professionals need to have the capacity and skills to practice with empathy. Greater empathy can lead to better patient relationships, reduced burnout, and enhanced recognition of personhood. However, people with dementia frequently report episodes of care that lack empathetic approaches. To improve the quality of care, high quality dementia education needs to be provided at undergraduate level. To inform the design and delivery of suitable educational resources, this study aimed to understand the major factors that impact the development of empathy towards people with dementia during undergraduate education.Methods:A constructivist, longitudinal grounded theory study (Charmaz, 2014) was conducted. Data were collected in 2019 using semi-structured interviews with undergraduate nursing, physiotherapy, and medical students (n=30). A second interview was completed with students (n=26) eighteen months later. Emergent findings were informed by simultaneous data collection and analysis using constant comparison techniques, and the use of theoretical memo writing.Results:Preliminary findings suggested that the development of empathy towards people with dementia was impacted by social and emotional exposure during undergraduate years. Data centered on four sub-categories. While there were barriers connecting and understanding people with dementia, students experienced conflicting expectations about empathy more widely. Positive and negative cultural experiences during placement led to emotional changes and a shift in ideals.Conclusion:Environments that promote empathetic practice during clinical placement could impact the development of empathy in undergraduate healthcare education more widely. This study highlights a need for educational design that focuses on both the patient and the environment.

A Comparative Study of Minimum Data Set of Speech Therapy: A Systematic Literature Review

Introduction: A minimum data set improves the potential of data standardization and overcoming the problem of low-quality speech therapy data by providing coherent, complete, and uniform data elements. Therefore, this study was conducted to compare speech therapy minimum data set among different countries.Material and Methods: A systematic review was conducted without time limits in PubMed, Scopus, Web of Science, Embase, SID, Magiran, Elmnet databases, and in the Google search engine to retrieve articles, speech therapy forms, and speech therapy registry sites. Keywords related to speech therapy minimum data set including minimum data set, registry, and speech therapy, were used. First, studies were reviewed based on titles and abstracts. Then, the selected studies from the previous stage were examined independently by two researchers. A similar standard checklist was used to extract and compare the findings.Results: A total of 1710 related records were extracted for review, and finally, six main articles and 11 forms were included in this review. The six original articles included two related to speech therapy minimum data set in the United States, two related to Iran, and one related to Australia and Germany. A comparative review of the most important data elements obtained from the articles and input forms in this review, including identity and admission information, referral information, history, assessment of verbal skills, assessment of non-verbal skills, assessment of organs of production, assessment of cognitive skills, assessment of other aspects of speech, and linguistic and cultural considerations, were information elements related to diagnoses, recommendations, and treatment plans.Conclusion: It could be concluded that an agreed classification system is needed to facilitate communication between speech therapists. This potentially enables further testing of diagnostic and therapeutic hypotheses with more coherent and simultaneous data collection. The challenge ahead is to create a comprehensive and universally agreed-upon classification system that meets the needs of professionals and researchers.

Laboratory diagnosis of measles infection using molecular and serology during 2019–2020 outbreak in Brazil

IntroductionLaboratory diagnosis of measles can be challenging, and the reintroduction of the measles virus in Brazil has brought about new issues. The aim of this study was to analyze the qPCR results of swab and urine samples and compare them with those of immunological methods for the diagnosis of measles. MethodsThis was a cross-sectional study based on a retrospective analysis of 3,451 suspected cases using laboratory test surveillance databases for qPCR (respiratory swabs and urine) and serologic tests for IgM and paired IgG. Sensitivity, specificity, positive predictive value, negative predictive value, accuracy, and agreement through kappa and adjusted kappa coefficients (PABAK) were calculated using different diagnostic strategies. ResultsThe swab and urine samples obtained using real-time qPCR were equivalent. Samples collected simultaneously and the combined samples showed moderate agreement between IgM ELISA and real-time qPCR; however, 48.9 % of the IgM ELISA analyses did not demonstrate detectable qPCR concentrations during simultaneous collections and 43.9 % of combined collections. The paired analysis of IgG showed an accuracy of 67.5 % for IgM and 90.7 % for real-time qPCR. ConclusionsDiagnosis based on IgM presents detection delimitation in samples collected early (1–5 days), suggesting that these individuals satisfy at least two criteria. In addition to qPCR, paired analysis of IgG using ELISA can be used to increase the sensitivity and specificity of laboratory diagnoses.

Spectroscopic pressure investigation of a novel high energy system

AbstractThis work combines a novel multimodal spectroscopic technique, O‐PTIR and Raman spectroscopy, which allows for the simultaneous collection of infrared and Raman spectra, with traditional diamond anvil cell techniques to explore pressure induced phase transitions in a high energy material. Two phase transitions are revealed, with the first transition emerging below 0.23 GPa, to a higher order phase, followed by a broad transition to a lower order phase. Aside from the pressure studies, hyperspectral imaging was performed, confirming the homogeneous nature of the system.

Wireless, battery-free, multifunctional integrated bioelectronics for respiratory pathogens monitoring and severity evaluation

The rapid diagnosis of respiratory virus infection through breath and blow remains challenging. Here we develop a wireless, battery-free, multifunctional pathogenic infection diagnosis system (PIDS) for diagnosing SARS-CoV-2 infection and symptom severity by blow and breath within 110 s and 350 s, respectively. The accuracies reach to 100% and 92% for evaluating the infection and symptom severity of 42 participants, respectively. PIDS realizes simultaneous gaseous sample collection, biomarker identification, abnormal physical signs recording and machine learning analysis. We transform PIDS into other miniaturized wearable or portable electronic platforms that may widen the diagnostic modes at home, outdoors and public places. Collectively, we demonstrate a general-purpose technology for rapidly diagnosing respiratory pathogenic infection by breath and blow, alleviating the technical bottleneck of saliva and nasopharyngeal secretions. PIDS may serve as a complementary diagnostic tool for other point-of-care techniques and guide the symptomatic treatment of viral infections.

Optofluidic Flow Cytometer with In-Plane Spherical Mirror for Signal Enhancement.

Statistical analysis of the properties of single microparticles, such as cells, bacteria or plastic slivers, has attracted increasing interest in recent years. In this regard, field flow cytometry is considered the gold standard technique, but commercially available instruments are bulky, expensive, and not suitable for use in point-of-care (PoC) testing. Microfluidic flow cytometers, on the other hand, are small, cheap and can be used for on-site analyses. However, in order to detect small particles, they require complex geometries and the aid of external optical components. To overcome these limitations, here, we present an opto-fluidic flow cytometer with an integrated 3D in-plane spherical mirror for enhanced optical signal collection. As a result, the signal-to-noise ratio is increased by a factor of six, enabling the detection of particle sizes down to 1.5 µm. The proposed optofluidic detection scheme enables the simultaneous collection of particle fluorescence and scattering using a single optical fiber, which is crucial to easily distinguishing particle populations with different optical properties. The devices have been fully characterized using fluorescent polystyrene beads of different sizes. As a proof of concept for potential real-world applications, signals from fluorescent HEK cells and Escherichia coli bacteria were analyzed.

Industry 4.0 in waste management: An integrated IoT-based approach for facility location and green vehicle routing

The increasing production of solid waste rate in urban areas plays a critical role in sustainable development. To mitigate the adverse effects of waste and enhance waste management efficiency, this paper introduces a holistic approach that notably reduces the overall cost while mitigating social and environmental impacts. Central to the system's efficacy is the critical process of waste sorting, which enhances the output value of the waste management system. While previous studies have not extensively addressed simultaneous waste collection and sorting, this paper provides an innovative integrated framework. This approach Integrates waste collection with various bins, followed by their transfer to separation centers. At these centers, waste is categorized into organic and non-organic varieties, which are then dispatched to a recovery center at the second level. In the context of optimizing the routes at both levels, this paper presents a green, multi-objective location-allocation model. This model is designed to optimize the number and location of separation center facilities. Since the routing problem is influenced by the facility location model, it is addressed as a multi-depot green vehicle routing problem, integrating real-time information from IoT-equipped bins. This paper also proposes the vehicle routing problem with a split pickup, aiming to minimize cost, CO2 emissions, and visual pollution. The developed mathematical models formulate the proposed problem and it is solved by the GAMS optimization software, to apply an exact method, while Social Engineering Optimization and Keshtel algorithms are deployed to solve the routing problem for larger sizes. The proposed approach offers a comprehensive and sustainable solution to waste management, filling crucial gaps in current research and practice.

Integrating spectral and image information for prediction of cottonseed vitality.

Cotton plays a significant role in people's lives, and cottonseeds serve as a vital assurance for successful cotton cultivation and production. Premium-quality cottonseeds can significantly enhance the germination rate of cottonseeds, resulting in increased cotton yields. The vitality of cottonseeds is a crucial metric that reflects the quality of the seeds. However, currently, the industry lacks a non-destructive method to directly assess cottonseed vitality without compromising the integrity of the seeds. To address this challenge, this study employed a hyperspectral imaging acquisition system to gather hyperspectral data on cottonseeds. This system enables the simultaneous collection of hyperspectral data from 25 cottonseeds. This study extracted spectral and image information from the hyperspectral data of cottonseeds to predict their vitality. SG, SNV, and MSC methods were utilized to preprocess the spectral data of cottonseeds. Following this preprocessing step, feature wavelength points of the cottonseeds were extracted using SPA and CARS algorithms. Subsequently, GLCM was employed to extract texture features from images corresponding to these feature wavelength points, including attributes such as Contrast, Correlation, Energy, and Entropy. Finally, the vitality of cottonseeds was predicted using PLSR, SVR, and a self-built 1D-CNN model. For spectral data analysis, the 1D-CNN model constructed after MSC+CARS preprocessing demonstrated the highest performance, achieving a test set correlation coefficient of 0.9214 and an RMSE of 0.7017. For image data analysis, the 1D-CNN model constructed after SG+CARS preprocessing outperformed the others, yielding a test set correlation coefficient of 0.8032 and an RMSE of 0.9683. In the case of fused spectral and image data, the 1D-CNN model built after SG+SPA preprocessing displayed the best performance, attaining a test set correlation coefficient of 0.9427 and an RMSE of 0.6872. These findings highlight the effectiveness of the 1D-CNN model and the fusion of spectral and image features for cottonseed vitality prediction. This research contributes significantly to the development of automated detection devices for assessing cottonseed vitality.

Dried blood spots for erythropoietin analysis: Detection of micro-doses, EPO c.577del variant and comparison with in-competition matching urine samples.

The abuse of recombinant erythropoietin (rEPO) and other erythropoietin (EPO) receptor agonists (ERAs) in sports prompted the need for sensitive detection methods of these substances. Dried blood spot (DBS) samples offer an easy solution for simultaneous collection of blood and urine during a doping control, but sensitivity issues are often presented as a challenge for routine EPO analysis from DBS. Its potential use for detecting rEPO micro-doses and the EPO gene c.577del variant thus needed further demonstration. Here, capillary blood collected from the arm skin of 111 athletes with Tasso-M20 (17.5μL/spot), collected during professional triathlon competitions, were analysed. Also, venous blood samples from healthy volunteers were used to prepare several spots of 20 μL on Mitra VAMS (from an rEPO micro-dose study) and Whatman filter paper (from an EPO gene variant study). Immunopurification of 2 spots with MAIIA EPO Purification Gel Kit and analysis with sodium N-lauroylsarcosinate polyacrylamide gel electrophoresis (SAR-PAGE)/Western blot resulted in sensitive detection of (1) micro-doses of rEPO from Mitra VAMS, (2) endogenous EPO from Tasso-M20 in all in-competition subjects, and (3) the EPO c.577del variant from Whatman filter paper. Additionally, in-competition endogenous EPO was detected in DBS even when matching urine samples had undetectable EPO. In conclusion, this work demonstrated that DBS can be a useful complementary matrix to urine samples for EPO detection.

Interactions of variously coated gold and silver nanoparticles with a bis(triarylborane) photodyanmic therapy (PDT)-dye; their cellular uptake, cytotoxicity and photo-activity

Background and purpose: Diethynylarene-linked bis(triarylborane) tetracations can be used as probes for fluorimetric and Raman sensing of biomacromolecules, as well as promising theragnostic agents. Among them, bis(triarylborane) fluorophore (TAB3), when bonded to Ag nanoparticles (NP), stood out with specific properties such as Raman signal enhancemen of the TAB3 dye in a cuvette. However, TAB3 dye - nanoparticle composites have not been studied in biological systems. For this reason, questions arose as to whether different types of metal nanoparticles (Au or Ag-based) with different coatings (negatively charged citrate or neutral PVP) could be efficiently stained with the TAB3 dye in a cuvette. The aim of this research was to examine Au and Ag nanoparticles of similar size (20-25 nm) with different stabilizers for their cellular uptake, cytotoxicity in the dark and under visible light radiation, to characterize the interactions of nanoparticles with the TAB3 fluorophore, and to study NP-TAB3 composites in cells, evaluate their intracellular staining, as well as possible photoinduced release and biological activity. Materials and methods: The binding constants of Au- and Ag- based nanoparticles with TAB3 were determined by fluorimetric titrations. The cytotoxic effect of NPs was determined by the survival of A549 cells (MTT assay). Cellular uptake of both NP and NP-TAB3 composites were performed by live cell imaging experiments. Results: The Au- or Ag-based NPs with different coatings bind to the TAB3 with high affinity. These NPs, as well as TAB3-NP complexes, efficiently enter living human cells, accumulating in cytoplasm with no apparent selectivity for a particular organelle. Even prolonged 3-day treatment with the NPs studied did not show any toxic effect on the cells. Bioimaging studies in cells revealed that the TAB3-NP complex does not intracellularly dissociate; the previously reported photo-bioactivity of TAB3 is completely inhibited by binding to NPs. Conclusion: Au- and Ag NPs were non-covalently stained by TAB3, irrespective of the different coatings, with similar binding affinities. Emission from TAB3 is strongly quenched by the NPs, but not completely. Experiments on living human cells revealed that neither free NPs, nor their composites with TAB3, were toxic. Bioimaging studies by confocal microscopy revealed that all NPs efficiently enter living cells within 90 min. Colocalization experiment with simultaneous collection of data in the reflection and fluorescence modes demonstrated that the TAB3 dye remained bound to NPs inside cells. Strong irradiation of TAB3-NP inside cells with a 457 nm laser did not yield any damage to the cells, at variance with our previously shown very strong photo-bioactivity of the TAB3 dye alone. Thus, binding of a chromophore to a nanoparticle can inhibit the chromophore’s ability to undergo photo-induced singlet oxygen production, consequently blocking its photo-bioactivity.