Using Large Language Models to Enhance the Reusability of Sensor Data.

The Internet of Things generates vast data volumes via diverse sensors, yet its potential remains unexploited for innovative data-driven products and services. Limitations arise from sensor-dependent data handling by manufacturers and user companies, hindering third-party access and comprehension. Initiatives like the European Data Act aim to enable high-quality access to sensor-generated data by regulating accuracy, completeness, and relevance while respecting intellectual property rights. Despite data availability, interoperability challenges impede sensor data reusability. For instance, sensor data shared in HTML formats requires an intricate, time-consuming processing to attain reusable formats like JSON or XML. This study introduces a methodology aimed at converting raw sensor data extracted from web portals into structured formats, thereby enhancing data reusability. The approach utilises large language models to derive structured formats from sensor data initially presented in non-interoperable formats. The effectiveness of these language models was assessed through quantitative and qualitative evaluations in a use case involving meteorological data. In the proposed experiments, GPT-4, the best performing LLM tested, demonstrated the feasibility of this methodology, achieving a precision of 93.51% and a recall of 85.33% in converting HTML to JSON/XML, thus confirming its potential in obtaining reusable sensor data.

Automated Generation of Clinical Reports Using Sensing Technologies with Deep Learning Techniques.

This study presents a pioneering approach that leverages advanced sensing technologies and data processing techniques to enhance the process of clinical documentation generation during medical consultations. By employing sophisticated sensors to capture and interpret various cues such as speech patterns, intonations, or pauses, the system aims to accurately perceive and understand patient-doctor interactions in real time. This sensing capability allows for the automation of transcription and summarization tasks, facilitating the creation of concise and informative clinical documents. Through the integration of automatic speech recognition sensors, spoken dialogue is seamlessly converted into text, enabling efficient data capture. Additionally, deep models such as Transformer models are utilized to extract and analyze crucial information from the dialogue, ensuring that the generated summaries encapsulate the essence of the consultations accurately. Despite encountering challenges during development, experimentation with these sensing technologies has yielded promising results. The system achieved a maximum ROUGE-1 metric score of 0.57, demonstrating its effectiveness in summarizing complex medical discussions. This sensor-based approach aims to alleviate the administrative burden on healthcare professionals by automating documentation tasks and safeguarding important patient information. Ultimately, by enhancing the efficiency and reliability of clinical documentation, this innovative method contributes to improving overall healthcare outcomes.

The Latarjet Procedure Without Remplissage Is Effective to Restore Stability in Athletes With Glenoid Bone Defects Greater Than 25% and Off-Track Hill-Sachs Lesions.

PURPOSE: There were 2 main purposes in this study: (1) to report on clinical outcomes of the Latarjet procedure without remplissage in athletes with glenoid bone defects greater than 25% and off-track Hill-Sachs lesions and (2) to determine whether the isolated Latarjet procedure converted off-track Hill-Sachs lesions to on-track Hill-Sachs lesions as measured on computed tomography (CT). METHODS: During the study period, a total of 29 athletes who had anterior glenohumeral instability with glenoid bone defects greater than 25% and off-track Hill-Sachs lesions, who underwent Latarjet surgery, and who had a minimum follow-up period of 24 months were included in this study. The glenoid track was analyzed before and 3 months after the procedure using 3-dimensional CT. Return to sport and range of motion, as well as the Rowe score, visual analog scale score for pain during sports activity, and Athletic Shoulder Outcome Scoring System score, were used to assess functional outcomes. Recurrences were also evaluated. RESULTS: The mean follow-up period was 35 months (standard deviation [SD], 6 months), and the mean age was 30 years (SD, 2 years). Of the patients, 27 (93%) were able to return to sports and 25 (86%) returned to the same level as before their injury. No significant difference in shoulder range of motion was found between preoperative and postoperative results. The Rowe, visual analog scale, and Athletic Shoulder Outcome Scoring System scores showed statistically significant improvements after surgery (P < .001). The mean width of the glenoid pathway changed significantly from 21.5 mm (SD, 2.54 mm) in the preoperative period to 35.1 mm (SD, 5.46 mm) at 3 months' follow-up. All the Hill-Sachs lesions remained on track, and no patient had recurrence of instability at the end of follow-up. No complications occurred in this series. CONCLUSIONS: The Latarjet procedure was effective to restore stability in athletes with recurrent glenohumeral instability with glenoid bone defects greater than 25% and off-track Hill-Sachs lesions, avoiding recurrence in all patients after an average follow-up period of 35 months. Moreover, the Latarjet procedure converted all off-track Hill-Sachs lesions to on-track Hill-Sachs lesions as measured on CT. LEVEL OF EVIDENCE: Level IV, retrospective case series.

Transitions in the cryptocurrency market during the COVID-19 pandemic: A network analysis.

In this letter, we identify the transitions of the cryptocurrency market during the pandemic by means of a network analysis. This method allows us to observe that COVID-19 significantly affected cryptocurrencies during a short period of financial panic, from 12 March 2020 to 1 April 2020, giving rise to a remarkable increase of market synchronisation. However, since April 2020, the cryptocurrency market progressively recovered its initial state, since the strong synchronisation, observed as a consequence of COVID-19, continuously disappeared. Therefore, our analysis highlights different market phases, which can be related to some of the phenomena reported in the existing literature.

Who raised from the abyss? A comparison between cryptocurrency and stock market dynamics during the COVID-19 pandemic.

This research examines the behaviour of cryptocurrencies and stock markets during the COVID-19 pandemic through the wavelet coherence approach and Markov switching autoregressive model. Our results show a financial contagion in March, since both cryptocurrency and stock prices fell steeply. Despite this turn-down, cryptocurrencies promptly rebounded, while stock markets are trapped in the bear phase. In other words, we observe that the price dynamics during the pandemic depends on the type of the market. These findings are relevant for investors since some hedging properties can be found in the cryptocurrency response to such a drastic event.

Use of biochemical miniaturized galleries, rRNA based lateral flow assay and Real Time PCR for Cronobacter spp. confirmation.

Identification of Cronobacter represent a major challenge for laboratories testing powdered infant formula (PIF). In the present study, two biochemical galleries and three molecular methods have been applied to confirm 276 Cronobacter spp. and non-Cronobacter isolates from different sources. Using the latest database of API 20 E and ID 32 E biochemical miniaturized kits, 53% and 78% of the isolates were identified respectively. From the available results, total accuracy for Cronobacter detection was in 97% (API 20 E) and 99% (ID 32 E). The three molecular methods were based on rRNA based lateral flow, Real Time PCR combined with either a hybridization or hydrolysis probe. For all three methods total accuracy was more than 99%. A pilot trial using Next Generation Sequencing (NGS) correctly identified 58 out of 66 isolates (88%) in DNA mixtures. The results indicate that the commercially available approaches such as ID 32 E, rRNA based lateral flow and Real Time PCR are all suitable for Cronobacter identification at the genus level. The NGS method may become a suitable alternative in the future, provided that the sequence database is improved.

Real-world clinical efficacy of tofacitinib in moderate-to-severe ulcerative colitis.

Tofacitinib is an oral small-molecule Janus kinase (JAK) inhibitor that preferentially inhibits JAK1 and JAK3. Its efficacy in inducing and maintaining remission in ulcerative colitis (UC) as well as its safety profile has been demonstrated in multicenter, randomized, double-blind, placebo-controlled trials. Additionally, real-world studies evaluating the effectiveness and adverse effects of tofacitinib have been conducted, affirming its clinical efficacy in moderate-to-severe UC.

Leukocyte-Poor Platelet-Rich Plasma as an Adjuvant to Arthroscopic Rotator Cuff Repair Reduces the Retear Rate But Does Not Improve Functional Outcomes: A Double-Blind Randomized Controlled Trial.

BACKGROUND: Whether the use of PRP as an adjuvant of rotator cuff repairs leads to improved tendon healing and better functional outcomes remains unclear in clinical evidence. PURPOSE: The main purpose of this study was to assess whether the use of leukocyte-poor platelet-rich plasma (LP-PRP) as an adjuvant to arthroscopic rotator cuff repair (ARCR) decreases the rate of retears compared with a control group. The secondary objective was to analyze whether LP-PRP improves patient-reported outcomes. STUDY DESIGN: Randomized controlled trial; Level of evidence, 1. METHODS: This was a double-blind randomized controlled trial at a single center. A consecutive series of 96 patients with rotator cuff tears <3 cm were enrolled and randomly allocated to the control group (double-row suture-bridge ARCR alone [n = 48]) and the PRP group (double-row suture-bridge repair, followed by 1 LP-PRP injection during surgery [n = 48]). The visual analog scale (VAS) for pain, the American Shoulder and Elbow Surgeons (ASES) score, the Single Assessment Numeric Evaluation (SANE), and the Pittsburgh Sleep Quality Index (PSQI) were administered preoperatively and at 6- and 12-month follow-up. Magnetic resonance imaging (MRI) was performed to evaluate tendon integrity at 6-month follow-up. Both patients and assessors were blinded to the intervention received during surgery. RESULTS: The mean patient age was 56.1 ± 2.98 years. Of the 96 patients, 90 had MRI performed at 6 months after surgery (94% radiological follow-up). The retear rate in the PRP group was 15.2% (7/46 [95% CI, 6%-28%]), which was lower than that in the control group of 34.1% (15/44 [95% CI, 20%-49%]) (P = .037). Therefore, the risk ratio of ruptures in patients exposed to LP-PRP was 0.44 (95% CI, 0.2-0.9; P = .037). Overall, the ASES, VAS, SANE, and PSQI scores showed a statistical improvement after surgery (P < .001). There were no significant differences in functional scores between the groups. Most of the patients exceeded the minimal clinically important difference for the ASES, SANE, and VAS without significant differences between the groups. CONCLUSION: In patients with rotator cuff tears <3 cm undergoing double-row suture-bridge repair, a 5-mL dose of LP-PRP injected at the tendon-bone interface significantly reduced the retear rate. However, the use of LP-PRP in terms of postoperative pain and patient-reported outcomes failed to show clinically meaningful effects. REGISTRATION: NCT04703998 (ClinicalTrials.gov identifier).

Strong Cavity-Optomechanical Transduction of Nanopillar Motion.

Nanomechanical resonators can serve as ultrasensitive, miniaturized force probes. While vertical structures such as nanopillars are ideal for this purpose, transducing their motion is challenging. Pillar-based photonic crystals (PhCs) offer a potential solution by integrating optical transduction within the pillars. However, achieving high-quality PhCs is hindered by inefficient vertical light confinement. Here, we present a full-silicon photonic crystal cavity based on nanopillars as a platform for applications in force sensing and biosensing areas. Its unit cell consists of a silicon pillar with a larger diameter at its top portion than at the bottom, which allows vertical light confinement and an energy band gap in the near-infrared range for transverse-magnetic polarization. We experimentally demonstrate optical cavities with Q factors exceeding 103, constructed by inserting a defect within a periodic arrangement of this type of pillars. Each nanopillar naturally behaves as a nanomechanical cantilever, making the fabricated geometries excellent optomechanical (OM) photonic crystal cavities in which the mechanical motion of each nanopillar composing the cavity can be optically transduced. These geometries display enhanced mechanical properties, cost-effectiveness, integration possibilities, and scalability. They also present an alternative in front of the widely used suspended Si beam OM cavities made on silicon-on-insulator substrates.

Study of image sensors for enhanced face recognition at a distance in the Smart City context.

Smart monitoring and surveillance systems have become one of the fundamental areas in the context of security applications in Smart Cities. In particular, video surveillance for Human Activity Recognition (HAR) applied to the recognition of potential offenders and to the detection and prevention of violent acts is a challenging task that is still undergoing. This paper presents a method based on deep learning for face recognition at a distance for security applications. Due to the absence of available datasets on face recognition at a distance, a methodology to generate a reliable dataset that relates the distance of the individuals from the camera, the focal length of the image sensors and the size in pixels of the target face is introduced. To generate the extended dataset, the Georgia Tech Face and Quality Dataset for Distance Faces databases were chosen. Our method is then tested and applied to a set of commercial image sensors for surveillance cameras using this dataset. The system achieves an average accuracy above 99% for several sensors and allows to calculate the maximum distance for a sensor to get the required accuracy in the recognition, which could be crucial in security applications in smart cities.

Noise correlations in neural ensemble activity limit the accuracy of hippocampal spatial representations.

Neurons in the CA1 area of the mouse hippocampus encode the position of the animal in an environment. However, given the variability in individual neurons responses, the accuracy of this code is still poorly understood. It was proposed that downstream areas could achieve high spatial accuracy by integrating the activity of thousands of neurons, but theoretical studies point to shared fluctuations in the firing rate as a potential limitation. Using high-throughput calcium imaging in freely moving mice, we demonstrated the limiting factors in the accuracy of the CA1 spatial code. We found that noise correlations in the hippocampus bound the estimation error of spatial coding to ~10 cm (the size of a mouse). Maximal accuracy was obtained using approximately [300-1400] neurons, depending on the animal. These findings reveal intrinsic limits in the brain's representations of space and suggest that single neurons downstream of the hippocampus can extract maximal spatial information from several hundred inputs.

The day after tomorrow: financial repercussions of COVID-19 on systemic risk.

In this paper, we study the financial repercussions of COVID-19 and the effect of anti-epidemic measures on financial markets. By using a composite dataset containing stock market indices of 10 countries characterized by heterogeneous levels of contagion, the daily COVID-19 cases and the 108 more restrictive measures implemented to limit the virus from 31/12/2019 to 13/03/2020, we examine the emergence of financial systemic risk, its speed of propagation and the effectiveness of the policies implemented to curb it. On the one hand, the spread of contagion and its transmission on financial markets are investigated via a lagged cross-correlation analysis. Our results show the emergence of systemic risk characterized by a high speed of diffusion. On the other hand, an augmented AR(1)-EGARCH(1,1) model is applied to examine the impact of anti-COVID-19 "policies on financial markets. We show that, regardless of the level of contagion, the restrictive measures are not able to contain the virus-induced investors panic in the first months of the epidemic.

What do biomarkers add: Mapping quantitative imaging biomarkers research.

PURPOSE: To understand the contribution of the concept of "biomarker" to quantitative imaging research. METHOD: The study consists of a bibliometric and a network analysis of quantitative imaging biomarkers research based on publication data retrieved from the Web of Science (WoS) for the period 1976-2017. Co-authorship is used as a proxy for scientific collaboration among research groups. Research groups are disambiguated and assigned to an institutional sector and to a medical specialty or academic discipline. Co-occurrence maps of specialties are built to delineate the collaborative network structure of this emerging field. RESULTS: Two very distinct growth patterns emerged from the 5432 publications retrieved from WoS. Scientific production on «quantitative imaging biomarkers¼ (QIB) began 20 years after the first publications on «quantitative imaging¼ (QI). The field of QIB has exhibited rapid growth becoming the most used term since 2011. Among the 12,882 institutions identified, 56% include the term QIB and 44% include the term QI; among the 14,734 different research groups identified, 60% include the term QIB and 40% the term QI. QIB is characterized by a well-established community of researchers whose largest contributors are in medical specialties (radiology 17%, neurology 16%, mental 10%, oncology 10%), while QI shows a more fragmented and diverse community (radiology 13%, engineering 13%, physics 10%, oncology 9%, neurology 6%, biology 4%, nuclear 3%, computing 3%). This suggests a qualitative difference between QIB and QI networks. CONCLUSIONS: Adding biomarkers to quantitative imaging suggests that medical imaging is rapidly evolving, driven by the efforts to translate quantitative imaging research into clinical practice.

High-Throughput Task to Study Memory Recall During Spatial Navigation in Rodents.

Spatial navigation is one of the most frequently used behavioral paradigms to study memory formation in rodents. Commonly used tasks to study memory are labor-intensive, preventing the simultaneous testing of multiple animals with the tendency to yield a low number of trials, curtailing the statistical power. Moreover, they are not tailored to be combined with neurophysiology recordings because they are not based on overt stereotyped behavioral responses that can be precisely timed. Here we present a novel task to study long-term memory formation and recall during spatial navigation. The task consists of learning sessions during which mice need to find the rewarding port that changes from day to day. Hours after learning, there is a recall session during which mice search for the location of the memorized rewarding port. During the recall sessions, the animals repeatedly poke the remembered port over many trials (up to ∼20) without receiving a reward (i.e., no positive feedback) as a readout of memory. In this task, mice show memory of port locations learned on up to three previous days. This eight-port maze task requires minimal human intervention, allowing for simultaneous and unsupervised testing of several mice in parallel, yielding a high number of recall trials per session over many days, and compatible with recordings of neural activity.

[Spanish adaptation and factor structure of the Denison Organizational Culture Survey]. / Adaptación al castellano y estructura factorial del Denison Organizational Culture Survey.

This article presents a Spanish adaptation of the Denison Organizational Culture Survey, a questionnaire designed to evaluate organizational culture. This survey consists of 60 items, grouped in 12 subscales, which identify 4 cultural dimensions. These dimensions have been widely studied and their influence in organizational effectiveness has been accepted. This adaptation was applied to 488 participants, and analysed with confirmatory factor analysis. Results show adequate psychometric properties, so it can be concluded that the Spanish adaptation almost completely replicates the structure of the original version in English.

Validation of standard method EN ISO 22964:2017 - Microbiology of the food chain - Horizontal method for the detection of Cronobacter spp.

The new version of the ISO standard method for detection of Cronobacter spp. (EN ISO 22964:2017) was validated in the frame of the European Commission Mandate M381 to CEN. Seventeen laboratories from nine countries participated in the interlaboratory studies to determine the performance characteristics of the method. The performance of the method was evaluated using matrices for which the presence of Cronobacter spp. is considered to be of serious concern, such as infant formula and its ingredients and representatives of categories cited in the EC Regulation 2073/2005 on microbiological criteria for foodstuffs for Cronobacter spp. The five matrices included in the validation were: two types of powdered infant food formulas (with and without probiotics); lactose; starch and environmental samples (swabs). The samples were each tested at two different levels of contamination, plus a negative control. Inoculation levels ranged from 4 to 95 CFU/sample. Each participant examined eight replicates of each level of inoculation, a total of 24 samples per matrix type. Specificity was calculated for each matrix used in the validation, with results ranging between 99 and 100%. Sensitivity of the method was calculated for samples in which no fractional recovery was expected and the values that were obtained ranged between 65 and 100%, depending on the matrix, the inoculation level and the interfering microbiota present in the samples. LOD50 value was calculated for three food items (the two powdered infant formulas and the starch) with values between 0.8 and 1.1 CFU/sample.

Estimation of Performance Characteristics of Analytical Methods for Mycobacterium avium subsp. paratuberculosis Detection in Dairy Products.

Paratuberculosis is a chronic enteric infection, caused by Mycobacterium avium subsp. paratuberculosis (MAP), affecting virtually all ruminants as well as other animals. MAP is also suspected to be involved in the etiology of some human diseases, like Crohn's disease and others. In surveillance studies, different analytical methodologies were employed to detect MAP, showing different results and incidence in dairy products. The aim of this study was to evaluate the performance characteristics of three analytical methods [culture, quantitative PCR (qPCR) and peptide-mediated magnetic separation (PMS) phage-based assay] for MAP detection in raw, heat-treated and powdered milk. The methods were evaluated according to performance characteristics defined for qualitative methods in ISO 16140-2:2016. To estimate sensitivity (including trueness) and LOD, 720, and 900 test portions, respectively, were blind tested by two laboratories. Considering all matrices, different sensitivities, expressed as the percentage of positives from the total of true positive test portions, were obtained for IS900 qPCR (94%), f57 qPCR (76%), culture (83%), and PMS-phage (40%). Trueness, expressed as results correctly assigned (including positive and negative) to the reference value, was 93% for the IS900 qPCR method, 89% for culture and 49% for the PMS-phage. The LODs obtained in this study were similar to the LODs previously published for cultural and qPCR methods. However, for the PMS-phage method, the obtained results showed higher LOD values compared to the limited data available in the scientific literature. Our results highlight that while the PMS-phage assay is workable in pure liquid culture for estimation of MAP counts, its usage for surveillance of dairy matrices should be treated with a lot of caution as performance characteristics obtained were lower than for the two other methods tested. qPCR and culture are the most appropriate methods to detect MAP in milk-based matrices according to ISO 16140 methodology. Cultural techniques are considered the gold standard for detection of viable MAP, but qPCR, which is widely used in analytical and surveillance studies, can be considered a suitable and recommendable alternative to cultural methods for screening, if confirmation of MAP's viability is not requested.

Drug treatment disparities among Hispanic drug-using women in Puerto Rico and New York City.

This paper reports findings on 334 out-of-treatment drug users in Puerto Rico and 617 in New York City, at the 6-month follow-up interview of a Longitudinal Survey. Main outcomes were health care and drug treatment utilization since baseline, assessed by asking participants if they had received physical or mental health services (including HIV medications), and if they had been in methadone maintenance, inpatient or outpatient drug treatment, or drug treatment while incarcerated. Chi-square tests were used to evaluate associations between gender and the various correlates. Logistic regression was used to calculate the contribution of each variable in predicting use of drug treatment. The analysis suggests that women in both sites were likely to suffer from disparities in both health care and drug treatment utilization when compared with men, albeit women in New York utilized more drug treatment resources and were more embedded in the immediate family than their female peers in Puerto Rico. Further research to specify the impact of contextual factors at the organizational and community levels, among members of the same ethnic group residing in different sites, may prove valuable in identifying the health needs and the factors that impede or facilitate drug-using women in obtaining the most appropriate treatment. Findings from these studies can help in developing appropriate public health policy and science-based drug treatment programs to eliminate disparities such as the ones detected in this study.

[Evaluation of an educational intervention in elderly patients with heart failure performed by nurses using a standardized care plan]. / Evaluación de la intervención educativa al paciente anciano con insuficiencia cardíaca, realizada por enfermería a través de un plan de cuidados estandarizado.

OBJECTIVE: To determine the impact of an educational intervention after discharge in patients with heart failure (HF) performed by applying a standardized care plan centered on encouraging self-care and treatment adherence. MATERIAL AND METHODS: We performed a longitudinal study between January, 2006 and May, 2007 in a population of 112 patients selected after being included in a clinical pathway during their hospital stay. Five scheduled visits were made in the first 2 months after hospital discharge; during these visits, an educational care plan was applied to the patients individually and by means of an interview in the HF day hospital. The patients' level of knowledge was quantified by means of a 5-point Likert-like scale. The education was carefully evaluated at each visit. The results were expressed as means. To compare the variables, a repeated measures ANOVA was used. RESULTS: The mean age of the 100 patients who finalized both phases of the study was 78 years (SD: 7). The intervention was effective in evaluating the level of knowledge acquired by the patients about their disease (signs, symptoms, complications, etc.) and statistically significant differences were obtained in the education acquired at each visit and throughout the 60-day intervention. CONCLUSIONS: Health education in these patients and their families (main caregiver) improved their adaptation to their disease and increased autonomy and treatment adherence, thus improving quality of life.