Miracle-dz/UniFAR-FTUs huggingface dataset:
Explainable Non-Contact Sleep Apnea Syndrome Detection Based on Comparison of Random Forests

This paper focuses on Sleep Apnea Syndrome (SAS) and proposes the novel eXplainable AI (XAI) method that extracts characteristics of SAS by comparing the datasets of the SAS patients and the non-SAS subjects. For this issue, this paper (i) employs “two” Random Forests (RFs) to respectively learn the models for the SAS patients and the non-SAS subjects to classify the WAKE/non-WAKE stage, (ii) compares the two learned RFs to find their difference as the physiological characteristic of SAS, and (iii) proposes the SAS detection method based on the difference between the two learned RFs. Through the human subject experiment of the SAS detection based on the biological vibration data acquired from the mattress sensor during sleep, the following implications have been revealed: 1) RF learned from the SAS patient data classifies the WAKE/non-WAKE stage from the viewpoint of the “low” frequencies of the biological vibration data, while RF learned from the non-SAS subject data classifies it from the viewpoint of its “high” frequencies; and 2) the SAS patients have the WAKE stage with the low frequencies of the biological vibration data caused by disturbances in the autonomic nervous system due to apnea/hypopnea, while the non-SAS subjects do not have it but have the usual WAKE stage with the high frequencies caused by large body movements, which has a potential of the new characteristic of SAS instead of respiration as a traditional characteristic of SAS.
Application of a combination of lactated Ringer's solution and ulinastatin for early resuscitation in sepsis

Purpose: To investigate the effect of early resuscitation using a combination of lactated Ringer's solution and ulinastatin on the survival rate of patients with sepsis. Methods: 82 patients with septic shock admitted to Xi'an People's Hospital, China from June 2017 to December 2020 were enrolled and randomly divided into control and study groups (n = 41 each). Patients in control group were given conventional fluid resuscitation and anti-infective therapy, while patients in study group were additionally given ulinastatin. Acute physiology and chronic health evaluation (APACHE II) score, sequential organ failure assessment (SOFA) score, and tissue perfusion were determined. Also, mechanical ventilation time, intensive care unit (ICU) stay time, and 28-day mortality rates were recorded. Results: Both groups presented no significant difference in clinical characteristics before treatment. After treatment, APACHE II score, SOFA score, and lactic acid level of the study group significantly decreased (p < 0.05), and the patients’ condition improved. Moreover, inflammation-related indices, viz, procalcitonin (PCT), white blood cells (WBC), and C reactive protein (CRP) were significantly reduced in the study group (p < 0.05). Renal function-related indices which include creatinine, and blood urea nitrogen (BUN) significantly decreased in study group (p < 0.05). Mechanical ventilation time, and ICU stay time were significantly shortened (p < 0.0001), while short-term survival rate significantly improved (p < 0.05). Conclusion: Lactated Ringer's solution in combination with ulinastatin expedites tissue perfusion and recovery, suppresses inflammation, enhances renal function, and significantly enhances the survival rate of septic patients. These findings provide valuable information for exploring new therapeutic approaches to sepsis.
An Alternating Proximal Method for Sea Clutter Suppression in Over-the-Horizon Radar Systems

The over-the-horizon (OTH) radar systems are seriously affected by sea clutter. The precise estimation of sea clutter covariance (SCC) plays an important role in suppressing the sea clutter, especially in the case of limited samples. Toward this end, this letter proposes a robust dictionary learning (DL) based on the SCC reconstruction method to suppress sea clutter with a single observation sample. The DL procedure is formulated as a nonconvex optimization problem, which is known to be NP-hard. To address this problem and reconstruct the SCC effectively, we propose a novel alternating proximal (AltProx) method designed for solving $\ell _{0}$ -norm-based problems. Extensive analyses demonstrate that our proposed algorithm exhibits global convergence with a sublinear convergence rate. Through simulation results, we verify the effectiveness of our proposed algorithm, demonstrating a notable performance improvement compared with conventional methods using single samples. In addition, we conduct experiments using real sea clutter datasets, further demonstrating the practical applicability of our method.
Ecological condition and biodiversity value of urban riparian and non-riparian bushland environments: Ku-ring-gai, Sydney

The management, conservation and enhancement of biodiversity and ecological functioning within riparian bushland present significant challenges for many local councils, natural resource managers and agencies. The protection of bushland is particularly important in urban areas where much of the remnant bushland habitat lies along creek systems and is subject to ongoing and significant development pressure.This paper examines the terrestrial invertebrate biodiversity of bushland as an indicator of ecological condition within the Kuring-gai Local Government Area in north Sydney. The results reveal that riparian zones are significantly taxonomically richer than ‘upland’ non-riparian areas and that invertebrate assemblage structures are significantly different between these two habitat patch types. Fire was found to significantly influence the taxonomic structure of invertebrate communities, although further research is required to better understand this relationship. Habitats that had undergone bush regeneration were found to have significant variation in invertebrate faunal structure, particularly within riparian zones. While the results are considered preliminary, they do demonstrate the enhanced ecological value of riparian zones compared to non-riparian areas. The results presented herein are the first attempt to identify the specific ecological value of riparian zones compared to other remnant urban Sydney bushland habitats. The results provide invaluable ecological evidence that can be used to support the protection of riparian bushland patches from future urban development.
How large are present‐day heat flux variations across the surface of Mars?

The first in situ Martian heat flux measurement to be carried out by the InSight Discovery‐class mission will provide an important baseline to constrain the present‐day heat budget of the planet and, in turn, the thermochemical evolution of its interior. In this study, we estimate the magnitude of surface heat flux heterogeneities in order to assess how the heat flux at the InSight landing site relates to the average heat flux of Mars. To this end, we model the thermal evolution of Mars in a 3‐D spherical geometry and investigate the resulting surface spatial variations of heat flux at the present day. Our models assume a fixed crust with a variable thickness as inferred from gravity and topography data and with radiogenic heat sources as obtained from gamma ray measurements of the surface. We test several mantle parameters and show that the present‐day surface heat flux pattern is dominated by the imposed crustal structure. The largest surface heat flux peak‐to peak variations lie between 17.2 and 49.9 mW m−2, with the highest values being associated with the occurrence of prominent mantle plumes. However, strong spatial variations introduced by such plumes remain narrowly confined to a few geographical regions and are unlikely to bias the InSight heat flux measurement. We estimated that the average surface heat flux varies between 23.2 and 27.3 mW m−2, while at the InSight location it lies between 18.8 and 24.2 mW m−2. In most models, elastic lithosphere thickness values exceed 250 km at the north pole, while the south pole values lie well above 110 km.
Ecohydrological transformation in the Dry Chaco and the risk of dryland salinity: Following Australia's footsteps?

During the last century, the massive conversion of Australian dry forests to crops and pastures triggered the massive soil and groundwater degradation process known as dryland salinity. Currently, South American Chaco's dry forests are undergoing a similar transformation, leading global deforestation rates. The goal of this study was to review existing ecohydrological information about natural and cultivated systems in the Chaco to assess the dryland salinity risks. We review deep soil water, salt stocks, and groundwater recharge from agriculture or native dry forests stands located in a precipitation range of 450–1100 mm. We complement this with water table level records and geoelectric profiles together with personal observations. We use data from 15 Australian studies for comparison. Strong salt leaching, especially after 20 years of forest clearance, indicates the onset of deep drainage following forest conversion to agriculture in the Dry Chaco. Water stocks were more than double in the cleared stands compared to their dry forest pairs, and recharge rates were up to two order magnitude higher in agricultural areas. Although lower atmospheric salt deposition, younger sediments, and relatively high water‐consuming agricultural systems in the Dry Chaco attenuate salinization risks compared to Australia, the very flat topography and related shallow water table levels of the South American region could make groundwater recharge and salt mobilization processes more widespread and difficult to manage. The lack of awareness among the general public, farmers, and decision makers about this issue amplifies the problem, making land management plans for the Argentine dry forest territories essential.
A Wearable Sonification System to Improve Movement Awareness: A Feasibility Study

This paper presents the design, development, and feasibility testing of a wearable sonification system for real-time posture monitoring and feedback. The system utilizes inexpensive motion sensors integrated into a compact, wearable package to measure body movements and standing balance continuously. The sensor data is processed through sonification algorithms to generate real-time auditory feedback cues indicating the user’s balance and posture. The system aims to improve movement awareness and physical conditioning, with potential applications in balance rehabilitation and physical therapy. Initial feasibility testing was conducted with a small group of healthy participants performing standing balance tasks with eyes open and closed. Results indicate that the real-time audio feedback improved participants’ ability to maintain balance, especially in the case of closed eyes. This preliminary study demonstrates the potential for wearable sonification systems to provide intuitive real-time feedback on posture and movement to improve motor skills and balance.
Face Recognition for Industrial Shop Floor Access Control

Access Control is an essential defensive tool businesses can use to satisfy both the legal requirements for data privacy and modern security concerns. It is intended to stop unauthorized people and systems from accessing protected resources outside their authorization's scope. The current survey seeks to provide an overview of cutting-edge Access Control methods while showcasing current research trends in this field. The proposed approach is to design a system for authorized employee identification via deep learning algorithms. The algorithm detects the person based on different parameters generated while identifying the face. Generating the number of facial features based on the databases provided by concerned organizations. After detecting the authorized person's face, the entry point will give access to that person. If anyone tries to get access above certain limitations the alert will be generated and sent to the concerned authority with the person's face captured with a camera. For the implementation of the proposed system, after working on the various algorithms, we found out that Haar cascade and MTCNN have their drawbacks while we can use DNN for our proposed system. The project's primary goal is to work on a better algorithm using computer vision techniques that will improve the existing efficiency of the system for facial identification.
HORMONAL AND LIPID DISRUPTION BECAUSE OF STRESS AMONG TEACHERS OF THE UNIVERSITY OF EL-OUED, ALGERIA

and a metabolic disturbance of cholesterol, triglycerides, and total lipids, where a very significant increase was noted (p<0.001) by hyperactivation of the hypothalamic-pitui-tary system because of chronic or repeated stress. Conclusions. Improving the working environment for teachers and raising awareness about the importance of regular visits to psychological support centers can mitigate the impact of stress on teachers, enhance their overall well-being, and consequently improve the quality of education they provide.
Two Different Integration Methods for Weather Radar-Based Quantitative Precipitation Estimation

We discuss two different integration methods for radar-based quantitative precipitation estimation (QPE): the echo intensity integral and the rain intensity integral. Theoretical analyses and simulations were used to test differences between these two methods. Cumulative rainfall calculated by the echo intensity integral is usually greater than that from rain intensity integral. The difference of calculated precipitation using these two methods is generally smaller for stable precipitation systems and larger for unstable precipitation systems. If the echo intensity signal is sinusoidal, the discrepancy between the two methods is most significant. For stratiform and convective precipitation, the normalized error ranges from −0.138 to −0.15 and from −0.11 to −0.122, respectively. If the echo intensity signal is linear, the normalized error ranges from 0 to −0.13 and from 0 to −0.11, respectively. If the echo intensity signal is exponential, the normalized error ranges from 0 to −0.35 and from 0 to −0.30, respectively. When both the integration scheme and real radar data were used to estimate cumulative precipitation for one day, their spatial distributions were similar.
CSER: Enhancing Cybersecurity Entity Recognition Through Multidimensional Feature Fusion

In the rapidly evolving landscape of cybersecurity, the accurate identification and classification of cybersecurity-related entities within textual data have gained paramount importance. This paper presents a novel Cybersecurity Entity Recognition (CSER) model that addresses the distinct challenges posed by the cybersecurity domain. Unlike conventional Named Entity Recognition (NER) methods, the cybersecurity context introduces domain-specific features, such as specialized patterns, keywords, and linguistic structures. Moreover, the presence of out-of-vocabulary words and domain-specific symbols further complicates entity recognition. To tackle these challenges, our CSER model integrates contextual, semantic, and morphological features, leveraging recurrent neural networks, convolutional neural networks, and conditional random fields. We investigate various embeddings, model architectures, and configurations, analyzing their influence on benchmark performance metrics. The outcomes of our experiments demonstrate a consistent superiority of our proposed CSER models over existing ones in terms of diverse performance metrics. This underscores the efficacy of our models in precisely recognizing cybersecurity-related entities. This research contributes to the advancement of entity recognition in the cybersecurity domain, shedding light on the pivotal role of domain-specific features and sophisticated architectures in enhancing accuracy and reliability.
High Genetic Diversity in Third-Generation Cephalosporin-Resistant Escherichia coli in Wastewater Systems of Schleswig-Holstein

The spread of multidrug-resistant bacteria from humans or livestock is a critical issue. However, the epidemiology of resistant pathogens across wastewater pathways is poorly understood. Therefore, we performed a detailed comparison of third-generation cephalosporin-resistant Escherichia coli (3GCREC) from wastewater treatment plants (WWTPs) to analyze dissemination pathways. A total of 172 3GCREC isolated from four WWTPs were characterized via whole genome sequencing. Clonal relatedness was determined using multi-locus sequence typing (MLST) and core genome MLST. Resistance genotypes and plasmid replicons were determined. A total of 68 MLST sequence types were observed with 28 closely related clusters. Resistance genes to eight antibiotic classes were detected. In fluoroquinolone-resistant isolates, resistance was associated with three-or-more point mutations in target genes. Typing revealed high genetic diversity with only a few clonal lineages present in all WWTPs. The distribution paths of individual lines could only be traced in exceptional cases with a lack of enrichment of certain lineages. Varying resistance genes and plasmids, as well as fluoroquinolone resistance-associated point mutations in individual isolates, further corroborated the high diversity of 3GCREC in WWTPs. In total, we observed high diversity of 3GCREC inside the tested WWTPs with proof of resistant strains being released into the environment even after treatment processes.
Can a generic patient reported outcome measure substitute a condition specific measure at assessing care effectiveness in low back pain?

Quality of care assessments beside the provider level should also include the patient perspective, however, there aren't widespread solutions for this approach. One possibility is to apply a generic, thus, widely applicable Patient Reported Outcomes Measure (PROM) to assess care outcomes. Taking this notion into consideration, this study aimed to investigate if a generic questionnaire can reliably substitute a disease-specific questionnaire when measuring care effectiveness with patient-reported outcome measures among patients with low back pain. Between January and December 2019, we conducted a before and after survey in three Hungarian hospitals. Adults with confirmed low back pain expecting spinal surgery were eligible to enter the study. SF-36 Health Survey (SF-36) and Roland‐Morris Disability Questionnaire (RMDQ) were used. Multivariate linear regression analyses were conducted to explore the relationship between the results of the two questionnaires and how service provider, sex, and education level could explain the differences in the calculated PROM-based performance measures. During the pre-intervention survey, 11 individuals decided to either not sign the consent form or complete the questionnaire. As a result, 116 individuals participated in the first – baseline – survey and 86 in the second – follow-up – survey. The drop-out rate varied by providers: the lowest rate was 15%, and the highest 39%. Of the SF-36 subscale-based performance measures, role limitations due to physical health and physical functioning significantly correlated with the RMDQ performance measure. Considering the necessary minimum clinically important difference, the explanatory analysis showed that the SF-36 physical functioning subscale-based and the RMDQ-based performance measures established the same performance rank-order among the participating hospitals. The physical functioning subscale of the SF-36 provided similar results to the RMDQ regarding care effectiveness. Thus, the SF-36 may be able to measure and compare care effectiveness among providers in low-back pain. If future studies investigating other health conditions come to the same conclusion, then the SF-36 could be used by itself to incorporate the patient perspective into health care quality assessments, thereby increasing comparability and lowering administrative costs.
Production of English prominence by native Mandarin Chinese speakers

Native-like production of intonational prominence is important for spoken language competency. Non-native speakers may have trouble producing prosodic variation in a second language (L2) and thus, problems in being understood. By identifying common sources of production error, we will be able to aid in the instruction of L2 speakers. In this paper we present results of a production study designed to test the ability of Mandarin L1 speakers to produce prominence in English. Our results show that there are some consistent differences between the L1 and L2 speakers in the use of pitch to indicate prominence, as well as in the accenting of phrase-initial tokens. We also ﬁnd that we can automatically detect prominence on Mandarin L1 English with 87.23% and an f-measure of 0.866 if we train a classiﬁer with annotated Mandarin L1 English data. Models trained on native English speech can detect prominence in Mandarin L1 English with an accuracy of 74.77% and f-measure of 0.824.
Impact of BESS Frequency Control on Microgrids: the Case Study of the Small Island Lipari

Isolated microgrids (MG) will face significant challenges soon. The progressive penetration of RES mandated by European targets will jeopardize the already precarious stability of the system unless system operators take proper counteractions. Battery energy storage systems (BESS) represent an asset for restoring the balance between supply and demand. This paper evaluates a BESS's impact on the frequency regulation of a real isolated MG. To emulate BESS performances, an empirical model based on an experimental campaign has been implemented in Powerfactory DIgSILENT. Measurements gathered by the local DSO set the reference for the study case. Various regulations exploited the benchmark to evaluate the BESS impact. Results show that the most power-intensive regulation reduces frequency peaks by 40.5%, with 91.66 % of frequency slips lower than 50 mHz. The outcomes confirmed the BESS's capability to support system stability without jeopardizing its limited energy content.
Bilinear Double-Order Filter Designs and Application Examples

A novel kind of non-integer order bilinear filters, named double-order bilinear filters, is introduced in this work. They are based on the employment of two non-integer orders, offering the maximum design flexibility in comparison with their fractional-order and power-law counterparts. An attractive offered benefit is that this is achieved without increasing the circuit complexity, since the proposed structure is capable of realizing all non-integer kinds of filters. Two design examples are provided, where it is shown that lead/lag compensators utilized in control applications and low/high shelving filters employed in acoustic applications are actually bilinear filters with suitably selected pole/zero frequencies. Simulation and experimental results, using the OrCAD PSpice simulator and a Field Programmable Analog Array device, respectively, support the findings of this work.