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Abstract The efficient, reliable, and resilient supply of electricity has become essential for social and economic well‐being of the modern society. However, more frequent occurrence of extreme weather events has exposed inequity in the planning and operation practices of power distribution systems, evidenced in higher vulnerability and longer power interruptions for some parts of the grid as compared to others. This paper proposes an equity‐aware power distribution system restoration model in an effort to ensure a more equitable yet resilient power distribution operation after outages. To this end, the proposed equity‐aware distribution system restoration model balances the efficiency of the restoration operation and the equitable allocation of distributed energy resources among affected customers after an outage, while prioritizing the critical infrastructure (e.g. hospitals). The results demonstrate the effectiveness of the proposed framework to ensure a more equitable restoration process as measured by the proposed fairness and restoration performance indices.

Objetivo: Determinar la efectividad de las incisiones arcuatas asistidas con láser de femtosegundo para el tratamiento del astigmatismo residual posterior a trasplante de córnea. Método: Estudio observacional, descriptivo de serie de casos, de corte transversal. Se evaluaron 18 pacientes con astigmatismo corneal residual a trasplante de córnea. Los parámetros evaluados incluyeron: agudeza visual, valor astigmático, queratometría, paquimetría, pretratamiento, a las 24 horas, 7 días y 30 días posterior a la cirugía y análisis vectorial (método de Alpin). Resultados: los índices de seguridad y eficacia fue de 0,66 D y 0,5 D respectivamente. Un mes postoperatorio, se observó una mejora significativa en la agudeza visual, con una ganancia de visión del 50,1% y una reducción del astigmatismo en un 49,12%. El 75% de los pacientes alcanzaron los resultados visuales esperados. Conclusiones: las incisiones corneales arcuatas son un método efectivo para corregir el astigmatismo residual post-queratoplastia, con mejoras significativas en la visión que se mantuvieron hasta el tercer mes. Sin embargo, las limitaciones incluyeron un pequeño tamaño muestral y un período de seguimiento corto.

Upper extremity true arterial aneurysms are rare and often present as a pulsatile mass with associated pain and paresthesia from peripheral nerve compression, and can lead to acute limb ischemia from thromboembolic sequela. History of arteriovenous dialysis access and immunosuppression after renal transplantation may contribute to the development of true aneurysms.This report describes the management of a patient with end-stage renal disease (ESRD) with multiple left upper extremity dialysis access who presented with an axillary and brachial artery aneurysm.

The goal of this study is to determine the feasibility of a wearable multi-sensor positioning prototype to be used as a training tool to evaluate rowing technique and to determine the positioning accuracy using multiple mathematical models and estimation methods. The wearable device consists of an inertial measurement unit (IMU), an ultra-wideband (UWB) transceiver, and a global navigation satellite system (GNSS) receiver. An experiment on a rowing shell was conducted to evaluate the performance of the system on a rower’s wrist, against a centimeter-level GNSS reference trajectory. This experiment analyzed the rowing motion in multiple navigation frames and with various positioning methods. The results show that the wearable device prototype is a viable option for rowing technique analysis; the system was able to provide the position, velocity, and attitude of a rower’s wrist, with a positioning accuracy ranging between ±0.185 m and ±1.656 m depending on the estimation method.

Abstract Background Enteric neuropathies, which result from abnormalities of the enteric nervous system, are associated with significant morbidity and high health-care costs, but current treatments are unsatisfactory. Cell-based therapy offers an innovative approach to replace the absent or abnormal enteric neurons and thereby restore gut function. Methods Enteric neuronal stem cells (ENSCs) were isolated from the gastrointestinal tract of Wnt1-Cre;R26tdTomato mice and generated neurospheres (NS). NS transplants were performed via injection into the mid-colon mesenchyme of nNOS −/− mouse, a model of colonic dysmotility, using either 1 (n = 12) or 3 (n = 12) injections (30 NS per injection) targeted longitudinally 1–2 mm apart. Functional outcomes were assessed up to 6 weeks later using electromyography (EMG), electrical field stimulation (EFS), optogenetics, and by measuring colorectal motility. Results Transplanted ENSCs formed nitrergic neurons in the nNOS −/− recipient colon. Multiple injections of ENSCs resulted in a significantly larger area of coverage compared to single injection alone and were associated with a marked improvement in colonic function, demonstrated by (1) increased colonic muscle activity by EMG recording, (2) faster rectal bead expulsion, and (3) increased fecal pellet output in vivo. Organ bath studies revealed direct neuromuscular communication by optogenetic stimulation of channelrhodopsin-expressing ENSCs and restoration of smooth muscle relaxation in response to EFS. Conclusions These results demonstrate that transplanted ENSCs can form effective neuromuscular connections and improve colonic motor function in a model of colonic dysmotility, and additionally reveal that multiple sites of cell delivery led to an improved response, paving the way for optimized clinical trial design.

Fibromyalgia (FM) is a chronic central sensitivity syndrome characterized by augmented pain processing at diffuse body sites and presents as a multimorbid clinical condition. Long COVID (LC) is a heterogenous clinical syndrome that affects 10–20% of individuals following COVID-19 infection. FM and LC share similarities with regard to the pain and other clinical symptoms experienced, thereby posing a challenge for accurate diagnosis. This research explores the feasibility of using surface-enhanced Raman spectroscopy (SERS) combined with soft independent modelling of class analogies (SIMCAs) to develop classification models differentiating LC and FM. Venous blood samples were collected using two supports, dried bloodspot cards (DBS, n = 48 FM and n = 46 LC) and volumetric absorptive micro-sampling tips (VAMS, n = 39 FM and n = 39 LC). A semi-permeable membrane (10 kDa) was used to extract low molecular fraction (LMF) from the blood samples, and Raman spectra were acquired using SERS with gold nanoparticles (AuNPs). Soft independent modelling of class analogy (SIMCA) models developed with spectral data of blood samples collected in VAMS tips showed superior performance with a validation performance of 100% accuracy, sensitivity, and specificity, achieving an excellent classification accuracy of 0.86 area under the curve (AUC). Amide groups, aromatic and acidic amino acids were responsible for the discrimination patterns among FM and LC syndromes, emphasizing the findings from our previous studies. Overall, our results demonstrate the ability of AuNP SERS to identify unique metabolites that can be potentially used as spectral biomarkers to differentiate FM and LC.

The enteric nervous system (ENS) is an extensive network of neurons and glia within the wall of the gastrointestinal (GI) tract that regulates many essential GI functions. Consequently, disorders of the ENS due to developmental defects, inflammation, infection, or age-associated neurodegeneration lead to serious neurointestinal diseases. Despite the prevalence and severity of these diseases, effective treatments are lacking as they fail to directly address the underlying pathology. Neuronal stem cell therapy represents a promising approach to treating diseases of the ENS by replacing the absent or injured neurons, and an autologous source of stem cells would be optimal by obviating the need for immunosuppression. We utilized the swine model to address key questions concerning cell isolation, delivery, engraftment, and fate in a large animal relevant to human therapy. We successfully isolated neural stem cells from a segment of small intestine resected from 1-month-old swine. Enteric neuronal stem cells (ENSCs) were expanded as neurospheres that grew optimally in low-oxygen (5%) culture conditions. Enteric neuronal stem cells were labeled by lentiviral green fluorescent protein (GFP) transduction, then transplanted into the same swine from which they had been harvested. Endoscopic ultrasound was then utilized to deliver the ENSCs (10,000–30,000 neurospheres per animal) into the rectal wall. At 10 and 28 days following injection, autologously derived ENSCs were found to have engrafted within rectal wall, with neuroglial differentiation and no evidence of ectopic spreading. These findings strongly support the feasibility of autologous cell isolation and delivery using a clinically useful and minimally invasive technique, bringing us closer to first-in-human ENSC therapy for neurointestinal diseases.

Fruit juices (FJ) have gained widespread global consumption, driven by their perceived health benefits. The accuracy of nutrition information is essential for consumers assessing FJ quality, especially with increasing concerns about added sugars and obesity risk. Conversely, ascorbic acid (Vitamin C), found in nature in many fruits and vegetables, is often lost due to its susceptibility to light, air, and heat, and it undergoes fortification during FJ production. Current analytical methods for determining FJ components are time-consuming and labor-intensive, prompting the need for rapid analytical tools. This study employed a field-deployable portable FT-IR device, requiring no sample preparation, to simultaneously predict multiple quality traits in 68 FJ samples from US markets. Using partial least square regression (PLSR) models, a strong correlation (RCV ≥ 0.93) between FT-IR predictions and reference values was obtained, with a low standard error of prediction. Remarkably, 21% and 37% of FJs deviated from nutrition label values for sugars and ascorbic acid, respectively. Portable FT-IR devices offer non-destructive, simultaneous, simple, and high-throughput approaches for chemical profiling and real-time prediction of sugars and acid levels in FJs. Their handiness and ruggedness can provide food processors with a valuable “out-of-the-laboratory” analytical tool.

The natural variation in estrogen secretion throughout the female menstrual cycle impacts various organs, including estrogen receptor (ER)-expressed skeletal muscle. Many women commonly experience increased fatigue or reduced energy levels in the days leading up to and during menstruation, when blood estrogen levels decline. Yet, it remains unclear whether endogenous 17β-estradiol, a major estrogen component, directly affects the energy metabolism in skeletal muscle due to the intricate and fluctuating nature of female hormones. In this study, we employed 2D 31P FID-MRSI at 7T to investigate phosphoryl metabolites in the soleus muscle of a cohort of young females (average age: 28 ± 6 years, n = 7) during the early follicular (EF) and peri-ovulation (PO) phases, when their blood 17β-estradiol levels differ significantly (EF: 28 ± 18 pg/mL vs. PO: 71 ± 30 pg/mL, p < 0.05), while the levels of other potentially interfering hormones remain relatively invariant. Our findings reveal a reduction in ATP-referenced phosphocreatine (PCr) levels in the EF phase compared to the PO phase for all participants (5.4 ± 4.3%). Furthermore, we observe a linear correlation between muscle PCr levels and blood 17β-estradiol concentrations (r = 0.64, p = 0.014). Conversely, inorganic phosphate Pi and phospholipid metabolite GPC levels remain independent of 17β-estradiol but display a high correlation between the EF and PO phases (p = 0.015 for Pi and p = 0.0008 for GPC). The robust association we have identified between ATP-referenced PCr and 17β-estradiol suggests that 17β-estradiol plays a modulatory role in the energy metabolism of skeletal muscle.

The diagnostic criteria for fibromyalgia (FM) have relied heavily on subjective reports of experienced symptoms coupled with examination-based evidence of diffuse tenderness due to the lack of reliable biomarkers. Rheumatic disorders that are common causes of chronic pain such as rheumatoid arthritis, systemic lupus erythematosus, osteoarthritis, and chronic low back pain are frequently found to be comorbid with FM. As a result, this can make the diagnosis of FM more challenging. We aim to develop a reliable classification algorithm using unique spectral profiles of portable FT-MIR that can be used as a real-time point-of-care device for the screening of FM. A novel volumetric absorptive microsampling (VAMS) technique ensured sample volume accuracies and minimized the variation introduced due to hematocrit-based bias. Blood samples from 337 subjects with different disorders (179 FM, 158 non-FM) collected with VAMS were analyzed. A semi-permeable membrane filtration approach was used to extract the blood samples, and spectral data were collected using a portable FT-MIR spectrometer. The OPLS-DA algorithm enabled the classification of the spectra into their corresponding classes with 84% accuracy, 83% sensitivity, and 85% specificity. The OPLS-DA regression plot indicated that spectral regions associated with amide bands and amino acids were responsible for discrimination patterns and can be potentially used as spectral biomarkers to differentiate FM and other rheumatic diseases.

Fibromyalgia (FM) is a chronic muscle pain disorder that shares several clinical features with other related rheumatologic disorders. This study investigates the feasibility of using surface-enhanced Raman spectroscopy (SERS) with gold nanoparticles (AuNPs) as a fingerprinting approach to diagnose FM and other rheumatic diseases such as rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), osteoarthritis (OA), and chronic low back pain (CLBP). Blood samples were obtained on protein saver cards from FM (n = 83), non-FM (n = 54), and healthy (NC, n = 9) subjects. A semi-permeable membrane filtration method was used to obtain low-molecular-weight fraction (LMF) serum of the blood samples. SERS measurement conditions were standardized to enhance the LMF signal. An OPLS-DA algorithm created using the spectral region 750 to 1720 cm−1 enabled the classification of the spectra into their corresponding FM and non-FM classes (Rcv > 0.99) with 100% accuracy, sensitivity, and specificity. The OPLS-DA regression plot indicated that spectral regions associated with amino acids were responsible for discrimination patterns and can be potentially used as spectral biomarkers to differentiate FM and other rheumatic diseases. This exploratory work suggests that the AuNP SERS method in combination with OPLS-DA analysis has great potential for the label-free diagnosis of FM.

In this study, a new wireless electronic circuitry to analyze weight distribution was designed and incorporated into a chair to gather data related to common human postures (sitting and standing up). These common actions have a significant impact on various motor capabilities, including gait parameters, fall risk, and information on sarcopenia. The quality of these actions lacks an absolute measurement, and currently, there is no qualitative and objective metric for it. To address this, the designed analyzer introduces variables like Smoothness and Percussion to provide more information and objectify measurements in the assessment of stand-up/sit-down actions. Both the analyzer and the proposed variables offer additional information that can objectify assessments depending on the clinical eye of the physicians.

Post Acute Sequelae of SARS-CoV-2 infection (PASC or Long COVID) is characterized by lingering symptomatology post-initial COVID-19 illness that is often debilitating. It is seen in up to 30–40% of individuals post-infection. Patients with Long COVID (LC) suffer from dysautonomia, malaise, fatigue, and pain, amongst a multitude of other symptoms. Fibromyalgia (FM) is a chronic musculoskeletal pain disorder that often leads to functional disability and severe impairment of quality of life. LC and FM share several clinical features, including pain that often makes them indistinguishable. The aim of this study is to develop a metabolic fingerprinting approach using portable Fourier-transform mid-infrared (FT-MIR) spectroscopic techniques to diagnose clinically similar LC and FM. Blood samples were obtained from LC (n = 50) and FM (n = 50) patients and stored on conventional bloodspot protein saver cards. A semi-permeable membrane filtration approach was used to extract the blood samples, and spectral data were collected using a portable FT-MIR spectrometer. Through the deconvolution analysis of the spectral data, a distinct spectral marker at 1565 cm−1 was identified based on a statistically significant analysis, only present in FM patients. This IR band has been linked to the presence of side chains of glutamate. An OPLS-DA algorithm created using the spectral region 1500 to 1700 cm−1 enabled the classification of the spectra into their corresponding classes (Rcv > 0.96) with 100% accuracy and specificity. This high-throughput approach allows unique metabolic signatures associated with LC and FM to be identified, allowing these conditions to be distinguished and implemented for in-clinic diagnostics, which is crucial to guide future therapeutic approaches.

Educational remote laboratories, when properly designed, have been demonstrated to be highly effective from a pedagogical point of view. Throughout the years their technology has evolved and they offer great capabilities, that are sometimes even superior to hands on labs. Nonetheless, despite their potential, they are not yet a widespread tool across learning institutions. One of the main reasons is that many remote laboratories have traditionally been research-oriented and have not been able to guarantee a high-enough quality of service (QoS) in a real-world educational environment. Such a QoS requires a relatively high number of students being able to access the labs concurrently, since classes may include dozens of students. Likewise, such a QoS requires reliability: the laboratory must work, be available and provide correct results. This work evaluates whether by applying an architecture oriented towards cost-effective instance replication and a model oriented towards fault-detection, it is possible to create laboratories that can provide a high QoS and that can therefore be used in a real environment, across multiple institutions. The study encompasses a period of 736 days and over 72,377 laboratory sessions, and relies on real data, from multiple institutions, of professors and students using the LabsLand Intel DE1-SoC FPGA remote laboratory, of which many instances are deployed. The results show that the QoS did indeed meet very high standards, and that such an approach can indeed lead to trusted remote laboratories, appropriate for real-world educational usage, and their eventual widespread adoption.

Abstract Vesicular stomatitis (VS) is a vector‐borne viral disease that causes lesions in livestock, premises, county and state quarantines, and important economic losses. We investigated vector–habitat characteristics for vectors associated with VS in regions of recurrent disease within the western United States (US) that consistently lead to the environment where vector, host, and pathogen populations intersect to enable pathogen transmission. We analyzed the habitats of previously identified insect vectors, including black flies (BFs) (Simulium vittatum complex), biting midges (BMs) (Culicoides variipennis complex, which includes Culicoides sonorensis), and sand flies (SFs) (Lutzomyia shannoni) in six regions of interest (ROIs) containing hotspots of VS ranging from Texas (TX) to Wyoming. This analysis broadened the understanding of (1) how regions of reoccurring VS differ from the broader western US, (2) how geographically separated regions and hotspots are similar across time, and (3) how vector–environment habitat a priori knowledge relates to observed hotspots. Analysis of watershed factors (livestock densities, land‐cover proportions, stream and lake densities, and irrigation methods) indicated a complex system separating areas with high, recurring VS from the broader western US. Although no single characteristic separated the six ROIs from other areas, we found two distinct emerging groups (northern ROI and TX). Hotspots, estimated from monthly VS concentrations, evolved northward throughout the year and most hotspots were closer to flowing water and agricultural land than the broader ROI. All ROIs contained environmental conditions suitable for multiple vectors at some point in the year, but BFs had the highest suitability scores, whereas BM scores were lower and varied annually with higher suitability in summer. SFs had the lowest suitability score in all ROIs, consistent with their low likelihood of being vectors. BM habitat patches were often orders of magnitude smaller than BF patches, and hotspot patches reinforce the likelihood that BF may be the most critical vector in northern ROI, whereas both BM and BF have similar likelihood in southern ROI. Given limited existing vector data, this analysis provides an alternate pathway for using habitat information to associate likely vectors responsible for transmission. Results could support early warning and mitigation efforts to reduce the incidence of VS.

Background Stem cell therapy holds promise to improve healing and stimulate tissue regeneration after burn injury. Preclinical evidence has supported this; however, clinical studies are lacking. We examined the application of bone marrow-derived mesenchymal stem cells (BM-MSC) to deep second-degree burn injuries using a two-dose escalation protocol. Methods Ten individuals aged 18 years or older with deep second-degree burn wounds were enrolled. The first five patients were administered 2.5 × 10³ BM-MSC/cm 2 to their wounds. After safety of the initial dose level was assessed, a second group of five patients was treated with a higher concentration of 5 × 10³ allogeneic BM-MSC/cm 2 . Safety was assessed clinically and by evaluating cytokine levels in mixed recipient lymphocyte/donor BM-MSC reactions (INFγ, IL-10 and TNFα). At each visit, we performed wound measurements and assessed wounds using a Patient and Observer Scar Assessment Scale (POSAS). Results All patients responded well to treatment, with 100% closure of wounds and minimal clinical evidence of fibrosis. No adverse reactions or evidence of rejection were observed for both dose levels. Patients receiving the first dose concentration had a wound closure rate of 3.64 cm 2 /day. Patients receiving the second dose concentration demonstrated a wound closure rate of 10.47 cm 2 /day. The difference in healing rates between the two groups was not found to be statistically significant ( P = 0.17). Conclusion BM-MSC appear beneficial in optimising wound healing in patients with deep second-degree burn wounds. Adverse outcomes were not observed when administering multiple doses of allogeneic BM-MSC. Lay Summary Thermal injuries are a significant source of morbidity and mortality, constituting 5%–20% of all injuries and 4% of all deaths. Despite overall improvements in the management of acutely burned patients, morbidities associated with deeper burn injuries remain commonplace. Burn patients are too often left with significant tissue loss, scarring and contractions leading to physical loss of function and long-lasting psychological and emotional impacts. In previous studies, we have demonstrated the safety and efficacy of administering bone marrow-derived mesenchymal stem cells (BM-MSC) to chronic wounds with substantial improvement in healing and evidence of tissue regeneration. In this report, we have examined the application of BM-MSC to deep second-degree burn injuries in patients. The aim of the present phase I/II clinical trial was to examine the safety and efficacy of administering allogeneic BM-MSC to deep second-degree burns. We utilised two different dose levels at concentrations 2.5 × 10 3 and 5 × 10 3 cells/cm 2 . Patients with deep second-degree burn wounds up to 20% of the total body surface area were eligible for treatment. Allogeneic BM-MSC were applied to burn wounds topically or by injection under transparent film dressing

Today, one of the world’s biggest problems is the assurance of food integrity from farm to fork. Economically motivated food adulteration and food authenticity problems are increasing daily with considerable health and economic effects. Early detection and prevention of food integrity-related problems could be provided by the application of effective on-site food analysis technologies. FTIR spectroscopy coupled with chemometrics can be used for the rapid quality control of a wide variety of food products with fast, high-throughput, accurate and nondestructive analysis advantages. In particular, hand-held and portable FTIR instruments have the potential to surveil food quality and food safety in various critical segments of the food supply chain. In this review, we explore the abilities of hand-held and portable FTIR spectrometers combined with multivariate statistics to conduct a quality evaluation of various food products in terms of food adulteration and authenticity issues. An examination of the literature showed that comparable results were obtained based on detection limits, correlation coefficient (R2) values, standard error values and discrimination power by using both portable/hand-held FTIR spectrometers and benchtop FTIR spectrometers. In conclusion, this review highlights the potential usefulness of portable and hand-held FTIR spectrometers combined with chemometrics for maintaining the food quality through the presentation of various applications that may shed light for on-site food control at any point of the food supply chain.

Objectives: The aim of this study was to assess the cause-specific mortality rate related to COVID-19 (CMR) in patients with rheumatic and musculoskeletal diseases (RMDs) and COVID-19 and to analyze the role of the different RMDs in their mortality risk. Methods: An observational longitudinal study was conducted during the first pandemic wave in our center. Patients with the diagnosis of RMDs and COVID-19 were included. Main outcome is the death related to COVID-19. Independent variable – type of RMDs: autoimmune rheumatic diseases (ARD), such as chronic inflammatory arthritis (CIA) and connective tissue diseases (CTD) and non-autoimmune Rheumatic Diseases (non-ARD). Survival techniques were used to estimate the CMR per 1000 patients-month with a 95% confidence interval (CI), and Cox multivariate regression analysis was run to examine the effect of ARD compared to non-ARD on mortality risk adjusted by confounders. Results were expressed by Hazard Ratio (HR) and CI. Results: Overall, 405 patients were included (642.5 patients-month). During the study period, 44 (10.86%) deaths were recorded. CMR was 68.48 (50.96–92.01). After adjusting for confounders, HR of mortality in ARD compared to non-ARD did not achieve statistical significance [HR: 1.15 (0.64–2.07)], neither CTD versus CIA nor CTD versus non-ARD. Age and certain comorbidities which are being diagnosed in March compared to April or May [HR: 2.43 (1.1–5.55)] increased the mortality risk. Glucocorticoids and disease-modifying antirheumatic drugs (DMARDs) dropped from the final model. Conclusion: In patients with RMDs and COVID-19, CMR was 6.8% patients-month. This study shows that mortality risk is higher in males, older patients, and similar between CTD, CIA, and non-ARD. COVID-19 management improved after the first month of pandemic. Plain Language Summaries Mortality related to the outbreak of COVID-19 in patients with rheumatic and musculoskeletal diseases Why was this study done? - To report the COVID-19-specific mortality rate in patients with a variety of RMDs during the first pandemic peak in a tertiary hospital in Madrid and to analyze the role of specific types of ARD and other possible factors in the risk of death related to COVID-19. What did the researchers do? - We performed a retrospective observational study during the first wave of the COVID-19 pandemic in Madrid, Spain. What did the researchers find? - In this study, neither the different diagnoses of RMDs, including CIA, CTD, or non-ARD disease or its treatment were not implicated as a potential risk of death related to COVID-19 - In consonance with other studies, RMDs patients and COVID-19, older age, male sex, and certain comorbidities implied more mortality risk - Our data reflect COVID-19 severity in a particular context, time, and population. In times of the absence of COVID-19 vaccine, healthcare, social, and political measures taken to contain the coronavirus outbreak have worked properly. What do the findings mean? - The presence of comorbidities in RMDs patients represents a greater risk than the different types of RMDs themselves, in the development of COVID-19 fatal outcome. It is important to integrate the control of comorbidities in the daily management.

Fibromyalgia syndrome (FM), one of the most common illnesses that cause chronic widespread pain, continues to present significant diagnostic challenges. The objective of this study was to develop a rapid vibrational biomarker-based method for diagnosing fibromyalgia syndrome and related rheumatologic disorders (systemic lupus erythematosus (SLE), osteoarthritis (OA) and rheumatoid arthritis (RA)) through portable FT-IR techniques. Bloodspot samples were collected from patients diagnosed with FM (n = 122) and related rheumatologic disorders (n = 70), including SLE (n = 17), RA (n = 43), and OA (n = 10), and stored in conventional protein saver bloodspot cards. The blood samples were prepared by four different methods (blood aliquots, protein-precipitated extraction, and non-washed and water-washed semi-permeable membrane filtration extractions), and spectral data were collected with a portable FT-IR spectrometer. Pattern recognition analysis, OPLS-DA, was able to identify the signature profile and classify the spectra into corresponding classes (Rcv > 0.93) with excellent sensitivity and specificity. Peptide backbones and aromatic amino acids were predominant for the differentiation and might serve as candidate biomarkers for syndromes such as FM. This research evaluated the feasibility of portable FT-IR combined with chemometrics as an accurate and high-throughput tool for distinct spectral signatures of biomarkers related to the human syndrome (FM), which could allow for real-time and in-clinic diagnostics of FM.

Technological advances in imaging and data acquisition are leading to the development of petabyte-scale neuroscience image datasets. These large-scale volumetric datasets pose unique challenges since analyses often span the entire volume, requiring a unified platform to access it. In this paper, we describe the Brain Observatory Storage Service and Database (BossDB), a cloud-based solution for storing and accessing petascale image datasets. BossDB provides support for data ingest, storage, visualization, and sharing through a RESTful Application Programming Interface (API). A key feature is the scalable indexing of spatial data and automatic and manual annotations to facilitate data discovery. Our project is open source and can be easily and cost effectively used for a variety of modalities and applications, and has effectively worked with datasets over a petabyte in size.

Resiliency has been studied in the power and water systems separately. Often the resiliency study is not so comprehensive as to understand interdependent, integrated water and power systems. This research outlines the relevant factors necessary to understand and advance quantification of such integrated systems. It also presents a review of integrated water-power systems resiliency. Based on literature survey and identification of challenges, the authors present quantification and computational steps needed to understand integrated water-power systems resiliency. A conceptual framework is proposed to quantify integrated water-power system resiliency. Finally, the authors presented an opportunity for improved water and power system resilience.

Phytoplankton is a crucial component for the correct functioning of different ecosystems, climate regulation and carbon reduction. Being at least a quarter of the biomass of the world’s vegetation, they produce approximately 50% of atmospheric O2 and remove nearly a third of the anthropogenic carbon released into the atmosphere through photosynthesis. In addition, they support directly or indirectly all the animals of the ocean and freshwater ecosystems, being the base of the food web. The importance of their measurement and identification has increased in the last years, becoming an essential consideration for marine management. The gold standard process used to identify and quantify phytoplankton is manual sample collection and microscopy-based identification, which is a tedious and time-consuming task and requires highly trained professionals. Microfluidic Lab-on-a-Chip technology represents a potential technical solution for environmental monitoring, for example, in situ quantifying toxic phytoplankton. Its main advantages are miniaturisation, portability, reduced reagent/sample consumption and cost reduction. In particular, photonic microfluidic chips that rely on optical sensing have emerged as powerful tools that can be used to identify and analyse phytoplankton with high specificity, sensitivity and throughput. In this review, we focus on recent advances in photonic microfluidic technologies for phytoplankton research. Different optical properties of phytoplankton, fabrication and sensing technologies will be reviewed. To conclude, current challenges and possible future directions will be discussed.

A questionnaire is a basic tool for collecting information in survey research. Often, these questions are measured using a Likert scale. With multiple items on the same broad object, these codes could be summed or averaged to give an indication of each respondent’s overall positive or negative orientation towards that object. This is the basis for Likert scales. Aggregation methods have been widely used in different research areas. Most of them are mathematical methods, such as the arithmetic mean, the weighted arithmetic mean, or the OWA (Ordered Weighted Averaging) operator. The usual presentation of Likert scale derived data are Mean. This paper presents a new approach to compute an aggregate value that represents Likert scale responses as a histogram adequate to treat better than Mean with asymmetric distributions. This method generates a set of partitions using an approach based on successive division. After every division, each partition is evaluated using a consensus measure and the one with the best value is then selected. Once the process of division has finished, the aggregate value is computed using the resulting partitions. Promising results have been obtained. Experiments show that our method is appropriate for distributions with large asymmetry and is not far from the behavior of the arithmetic mean for symmetric distributions. Overall, the article sheds light on the need to consider other presentations of Likert scale derived data beyond Mean more suitable for asymmetric distributions.

Purpose: To present a 22-month-old girl with a complete retinal detachment who was found to have systemic exam findings consistent with neurofibromatosis type 1 during the course of multi-specialty exam under anesthesia. Observations: During examination under anesthesia, ophthalmic exam findings demonstrated retinal detachment with cyst formation, as well as peripheral non-perfusion of the retina in the left eye. Non-ophthalmic findings discovered on difficulty with intubation included a laryngeal plexiform neurofibroma and café-au-lait spots. Conclusions: Pediatric retinal detachments are uncommon compared to those in adults. Pediatric patients with neurofibromatosis type 1 can present with vision loss as the presenting symptom. Systemic signs and symptoms should be carefully screen and monitored.

This work presents a dual-wavelength C-band erbium-doped fiber laser assisted by an artificial backscatter reflector. This fiber-based reflector, inscribed by femtosecond laser direct writing, was fabricated into a single mode fiber with a length of 32 mm. The dual-wavelength laser obtained, centered at 1527.7 nm and 1530.81 nm, showed an optical signal-to-noise ratio over 46 dB when pumped at 150 mW. Another feature of this laser was that the power difference between the two channels was just 0.02 dB, regardless of the pump power, resulting in a dual emission laser with high equalization. On the other hand, an output power level and a central wavelength instability as low as 0.3 dB and 0.01 nm were measured, in this order for both channels. Moreover, the threshold pump power was 40 mW. Finally, the performance of this dual-wavelength fiber laser enhanced with a random reflector for sensing applications was studied, achieving the simultaneous measurement of strain and temperature with sensitivities around 1 pm/με and 9.29 pm/°C, respectively.

The appearance of defects during the manufacture of tanker trucks via arc-welding is a significant problem in the industry. A reliable low-cost and non-destructive on-line method could aid the discovery of solutions to overcome productivity problems. Plasma optical spectroscopy was employed in this study to correlate the presence of several elemental emission lines with certain quality-related events, such as the appearance of porosities. Results obtained through field trials and also during in-line production show that the convenient processing of acquired process signals facilitates not only the detection of defects, but also the identification of their causes. Output monitoring signals have been compared with X-ray inspections of the seam welds performed. It has been demonstrated that the spectroscopic monitoring variables obtained are good indicators for evaluating contamination in the process and therefore the occurrence of welding defects.

The color stability of anthocyanins (ACN) has been shown to be improved by interaction with whey proteins (WP). In this study, we explore the ACN–WP interaction using Fourier transform infrared spectroscopy (IR). ACN from purple corn, grape, and black carrot (50 μM) were evaluated. IR spectra (4000–700 cm−1) were collected for native and preheated (40–80 °C) WP (5 mg/mL) and ACN–WP mixtures at pH 7.4. Soft independent modeling of class analogy was used to analyze the IR data. The WP secondary structure changed after heat treatments and after interaction with ACN. As expected, the WP α-helices decreased, and β-sheet increased after heat treatment. The intensities of the WP amide I and II bands decreased after ACN addition, revealing a decrease in the WP α-helix content. Higher preheating temperatures (70–80 °C) resulted in a more disordered WP structure that favored stronger WP–ACN interactions related to amide III changes. Addition of ACN stabilized WP structure due to heat denaturation, but different ACN structures had different binding affinities with WP. WP structure had less change after interaction with ACN with simpler structures. These results increase our understanding of ACN–WP interactions, providing a potential strategy to extend anthocyanin color stability by WP addition.