Miracle-dz/UniFAR-FTUs huggingface dataset:
Non-invasive monitoring of cardiac function through Ballistocardiogram: an algorithm integrating short-time Fourier transform and ensemble empirical mode decomposition

The Ballistocardiogram (BCG) is a vibration signal that is generated by the displacement of the entire body due to the injection of blood during each heartbeat. It has been extensively utilized to monitor heart rate. The morphological features of the BCG signal serve as effective indicators for the identification of atrial fibrillation and heart failure, holding great significance for BCG signal analysis. The IJK-complex identification allows for the estimation of inter-beat intervals (IBI) and enables a more detailed analysis of BCG amplitude and interval waves. This study presents a novel algorithm for identifying the IJK-complex in BCG signals, which is an improvement over most existing algorithms that only perform IBI estimation. The proposed algorithm employs a short-time Fourier transform and summation across frequencies to initially estimate the occurrence of the J wave using peak finding, followed by Ensemble Empirical Mode Decomposition and a regional search to precisely identify the J wave. The algorithm’s ability to detect the morphological features of BCG signals and estimate heart rates was validated through experiments conducted on 10 healthy subjects and 2 patients with coronary heart disease. In comparison to commonly used methods, the presented scheme ensures accurate heart rate estimation and exhibits superior capability in detecting BCG morphological features. This advancement holds significant value for future applications involving BCG signals.
Logarithmic Regret for Online Gradient Descent Beyond Strong Convexity

Hoffman's classical result gives a bound on the distance of a point from a convex and compact polytope in terms of the magnitude of violation of the constraints. Recently, several results showed that Hoffman's bound can be used to derive strongly-convex-like rates for first-order methods for \textit{offline} convex optimization of curved, though not strongly convex, functions, over polyhedral sets. In this work, we use this classical result for the first time to obtain faster rates for \textit{online convex optimization} over polyhedral sets with curved convex, though not strongly convex, loss functions. We show that under several reasonable assumptions on the data, the standard \textit{Online Gradient Descent} algorithm guarantees logarithmic regret. To the best of our knowledge, the only previous algorithm to achieve logarithmic regret in the considered settings is the \textit{Online Newton Step} algorithm which requires quadratic (in the dimension) memory and at least quadratic runtime per iteration, which greatly limits its applicability to large-scale problems. In particular, our results hold for \textit{semi-adversarial} settings in which the data is a combination of an arbitrary (adversarial) sequence and a stochastic sequence, which might provide reasonable approximation for many real-world sequences, or under a natural assumption that the data is low-rank. We demonstrate via experiments that the regret of OGD is indeed comparable to that of ONS (and even far better) on curved though not strongly-convex losses.
Association between Urinary AGEs and Circulating miRNAs in Children and Adolescents with Overweight and Obesity from the Italian I.Family Cohort: A Pilot Study

Modern dietary habits are linked to high exposure to Advanced Glycation End products (AGEs) mainly due to the dramatic increase in the consumption of highly processed foods in recent years. Body levels of these compounds vary with food intake and are almost interconnected with age and health status, formally embodying indicators of oxidative stress and inflammation in adults. However, the relationship between AGEs and health issues has not been definitively understood in children, and several pediatric investigations have produced conflicting evidence. Besides, despite extensive research, there are no universally accepted analytical techniques for measuring AGE levels in the human body, with several approaches available, each with its advantages and disadvantages. This pilot study aimed to investigate the association between urinary AGEs, measured using spectrofluorimetry-based assays, and circulating microRNAs (c-miRNAs) in a subsample (n = 22) of Italian children participating in the I.Family Study. Anthropometric measurements, biochemical markers, and miRNA profiles were assessed. The first indication of a relationship between urinary AGEs and c-miRNAs in the context of obesity was found. Specifically, four miRNAs, hsa-miR-10b-5p, hsa-miR-501-5p, hsa-miR-874-3p, and hsa-miR-2355-5p were significantly associated with levels of urinary AGEs. The association between AGEs, obesity, inflammation markers, and specific miRNAs highlights the complex interplay between these factors and their potential impact on cellular and tissue homeostasis. The discovery of altered c-miRNAs profiling has the potential to offer innovative methods for assessing early changes in the body’s AGE pool and allow recognition of an increased risk of disease susceptibility, routinely undetected until metabolic complications are identified.
Convergence Rates for the Constrained Sampling via Langevin Monte Carlo

Sampling from constrained distributions has posed significant challenges in terms of algorithmic design and non-asymptotic analysis, which are frequently encountered in statistical and machine-learning models. In this study, we propose three sampling algorithms based on Langevin Monte Carlo with the Metropolis–Hastings steps to handle the distribution constrained within some convex body. We present a rigorous analysis of the corresponding Markov chains and derive non-asymptotic upper bounds on the convergence rates of these algorithms in total variation distance. Our results demonstrate that the sampling algorithm, enhanced with the Metropolis–Hastings steps, offers an effective solution for tackling some constrained sampling problems. The numerical experiments are conducted to compare our methods with several competing algorithms without the Metropolis–Hastings steps, and the results further support our theoretical findings.
Classifying the Fire Regime Condition Class for Upland Oak-Hickory Forests

ABSTRACT i ACKNOWLEDGEMENTS iii TABLE OF CONTENTS iv LIST OF TABLES vii LIST OF FIGURES x CHAPTER 1 INTRODUCTION 1 Oak-Hickory Ecosystems 1 Study Justification 2 Study Objectives 4 CHAPTER 2 LITERATURE REVIEW 7 Successional Theory and Disturbance Ecology 7 Fire as a Disturbance 8 Oak-Hickory Ecosystems 11 Xerophyte Ecophysiology 12 Fire Regimes of Oak-Hickory Forests 13 Historic Landscapes and Disturbance History of Southern Illinois. 15 Threats to the Persistence of Oak-Hickory Forests 20
The Application of a Topology Optimization Algorithm Based on the Kriging Surrogate Model in the Mirror Design and Optimization of an Aerial Camera

In a Cassegrain optical system, the surface precision of the primary mirror is an important factor in the quality of the image. The design of a lightweight primary mirror with a high-quality optical surface is crucial. In this thesis, an integrated mirror light engine design optimization process is proposed for an aviation optoelectronic device. It is based on the Kriging surrogate model and nests the topology optimization algorithm, which constructs the mirror RMS value response surface and obtains the dominant relationship between mirror structure and surface accuracy. The optimal surface figure lightweight structure of the mirror is obtained by optimizing the surrogate model with an additive criterion and multi-objective optimization analysis. The root mean square value (RMS) of the corresponding primary mirror is 10.41 nm, which is better than 1/40 λ (λ = 632.8 nm). This meets the optical design specifications. The optimal primary mirror structure is analyzed by using the finite element method, which verifies the precision of the Kriging surrogate model. It has an error of 0.28%. The kinetic analysis of the primary mirror shows that the primary mirror does not yield to plastic deformation or even failure under a three-way 20 g acceleration load. This meets the environmental suitability requirements.
Coxiellosis in Livestock: Epidemiology, Public Health Significance, and Prevalence of Coxiella burnetii Infection in Ethiopia

Abstract Coxiellosis is a zoonotic disease that is prevalent globally and can pose significant challenges, especially in less developed countries like Ethiopia. Coxiella burnetii is responsible for causing an infection called Q fever in humans and coxiellosis in ruminants. Pneumonia and endocarditis are the only signs that characterize the acute and chronic forms of Q fever, respectively. Ruminants exhibit symptoms such as abortion during the later stages of pregnancy, impaired fertility, perinatal death, premature delivery, and reduced birth weight. C. burnetii infection typically spreads among healthy cattle via tick bites and exposure to infected cattle or their bodily secretions. The primary source of human infection is through the ingestion of contaminated milk and milk products, but transmission through aerosols and dust generated during livestock operations is also common. Cattle, sheep, camels and goats are the primary sources of human infection, and the bacterium can be found in various bodily fluids of infected animals. Several factors, including host characteristics, environmental conditions, and management practices, can potentially affect the occurrence of C. burnetii infection in livestock, such as cattle, camels, sheep, and goats. Coxiellosis is prevalent in Ethiopia’s pastoral and mixed cattle management systems, as individuals frequently interact with cattle and are therefore more prone to exposure to the C. burnetii bacterium. Vaccination and biosecurity measures are effective techniques for managing C. burnetii infection. Therefore, it is crucial to implement appropriate mitigation strategies, raise awareness about the spread of C. burnetii infection, and conduct further studies on C. burnetii infection in high-risk groups.
Science Achievement in Finland, Slovenia, Kazakhstan and Turkey with Respect to TIMSS 2011 Results

In order to obtain an adequate amount of information on what the students have achieved and how students can improve their learning, it is necessary to understand the educational contexts where the learning takes place. In this study, the structural relation between students’ science achievement and educational context variables were examined among four countries, including Finland, Slovenia, Kazakhstan and Turkey using TIMSS 2011 data. The educational contextual variables were selected from the questionnaires for teachers and students to analyse the intended curriculum of each country. Having science achievement score as an indicator of attained curriculum, this study tries to model the school effectiveness and examine which factors mostly affect science achievement. A 2-level model of student and teacher were analysed. In result, this study found out the educational contextual characteristics of high performance and reasons why these countries outperformed other countries well in spite of many involved factors, and the social and cultural differences between countries.
Domain adaptive networks with limited data for rotating machinery fault diagnosis: a case of study of gears

Rotating machinery is one of the most common components in the industry. Therefore, timely and accurate fault diagnosis of rotating machinery is essential for the regular operation of equipment. At present, some achievements have been made in rotating machinery fault diagnosis based on a large number of marked fault data. However, most of the machines are in a normal state in actuality. Especially, the machines run under different loads, so it is costly to collect a large number of labeled fault data under different load distributions. To solve rotating machinery fault diagnosis in different load conditions with limited samples, a domain adaptive group convolutional neural network is proposed. Firstly, the least squares generative adversarial networks were used to expand the limited target sample data. By changing the objective function, the two defects of the low quality of the vibration signal generated by the traditional generative adversarial networks and the unstable training process are optimized. Secondly, the raw vibration signals in the source domain are pre-trained by the group convolutional neural network, and the group training network effectively reduces network parameters. Finally, the source domain signals and target domain signals were trained in domain adversarial networks to diagnose different distributed data in target domains. The proposed method is validated by collecting the raw vibration signals of gears under different loads and different health states, and the effectiveness of the proposed method is proved. Experimental validation shows that the method proposed in this paper achieves an average accuracy improvement of more than 12% compared to other existing methods.
Anemia, Iron Deficiency, and Iron Regulators in Pancreatic Ductal Adenocarcinoma Patients: A Comprehensive Analysis

Anemia and iron deficiency (ID) are common complications in patients with pancreatic ductal adenocarcinoma (PDAC), but their underlying causes remain unclear. This study investigated the incidence and characteristics of anemia and micronutrient deficiencies in PDAC patients before initiating chemotherapy. A total of 103 PDAC patients were included, comprising 67 in the palliative and 36 in the adjuvant groups. The overall incidence of anemia was 42.7% (n = 44), with comparable rates in both groups. Normocytic and normochromic anemia were predominant, with mild and moderate cases observed in 32% and 10.7% of the cohort, respectively. ID was evident in 51.4% of patients, with absolute ID more frequent in the adjuvant than in the palliative group (19.4% vs. 13.4%). Functional ID occurred more often in the palliative than in the adjuvant group (41.8% vs. 25%). Vitamin B12 and folate deficiency occurred in <5% (n = 5) of patients. Furthermore, 8.7% (n = 9) of patients had chronic kidney disease and anemia. To elucidate mechanisms of iron deficiency, the study explored the expression of iron regulators (hepcidin (HEP), ferroportin (FPN), and ZIP14 protein) and mitochondrial mass in PDAC tissue with immunohistochemical (IHC) staining and Perl’s Prussian blue to detect iron deposits on available tumor samples (n = 56). ZIP14 expression was significantly higher in less advanced tumors (p = 0.01) and correlated with mitochondrial mass (p < 0.001), potentially indicating its role in local iron homeostasis. However, no significant impact of tissue iron regulators on patient survival was observed. Perl’s Prussian blue staining revealed iron deposits within macrophages, but not in pancreatic duct cells. Furthermore, the GEPIA database was used to compare mRNA expression of iron regulators (HEP, FPN, and ZIP14) and other genes encoding iron transport and storage, including Transferrin Receptor Protein 1 (TfR1) and both ferritin chain subunits (FTH and FTL), in PDAC and normal pancreatic samples. FPN, TfR1, FTH, and FTL showed higher expression in tumor tissues, indicating increased iron usage by cancer. ZIP14 expression was higher in the pancreas than in PDAC and was correlated with FPN expression. The study highlights the importance of baseline iron status assessment in managing PDAC patients due to the high incidence of anemia and iron deficiency. Furthermore, ZIP14, in addition to HEP and FPN, may play a crucial role in local iron homeostasis in PDAC patients, providing valuable insights into the underlying mechanisms of iron dysregulation.
Diversity of Ferns and Lycophytes in the Mt. Malambo, Southern Philippines

This research was carried out to study the diversity and assess the conservation status and endemism of ferns and lycophytes in the Mt. Malambo, Datu Salumay, Southern Philippines. Repeated transect walks were done with 20 sampling plots delineated on the site. Specimens were collected, identified, and assessed for their conservation status and endemism. Data gathered were analyzed employing the Shannon-Weiner Index. The inventory revealed 215 species (202 species of ferns and 13 species of lycophytes) belonging to 74 genera and 23 families. Polypodiaceae, Aspleniaceae, Hymenophyllaceae, and Pteridaceae were the species-rich families collected. Asplenium nidus L. , Pneumatopteris costata (Brackenr.) Holttum, and Asplenium thunbergii Kunze obtained the highest species importance values. Mt. Malambo has a diversity value of H’=1.83 which is higher compared to other mountains in Mindanao. This study reports 20 Philippine endemic and 19 threatened species of ferns and lycophytes in the area. Of these, one is critically endangered, 11 are endangered, five are vulnerable, and two are other threatened species. The presence of many threatened and endemic species in the area implies that high priority should be addressed in protecting and conserving these species of ferns and lycophytes in Mt. Malambo.
SWGO site environment characterisation activities

The Southern Wide-field Gamma-ray Observatory (SWGO) project aims to build an array of air-shower detectors in the Southern hemisphere. Intensive site search activities are ongoing. We developed an Autonomous Environmental and Scientific SWGO Site Characterization Instrument (AEROSITE) to measure environmental characteristics of the proposed sites and deployed four of them in Argentina, Bolivia, Chile and Peru. The instruments are located at very high altitudes of
Just-in-Time, Just-in-Place Virtual Training in the Pediatric Emergency Department: A Novel Approach to Impact the Perfusion Exam

Background Early identification of shock is vital in decreasing morbidity and mortality in the pediatric population. Although residents are taught the perfusion portion of the rapid cardiopulmonary assessment at our institution, they perform it at the bedside with 8.4% completing 1 part of the assessment and 9.7% verbalizing their findings. Newer technologies, including virtual reality (VR), offer immersive training to close this clinical gap. Objective To assess senior pediatric residents’ performance of a perfusion exam and verbalization of their perfusion assessment following VR-based Just-in-Time/Just-in-Place (JITP) training compared to video-based JITP training. We hypothesized that JITP media training was feasible, and VR JITP was more effective than video-based training. Methods Residents were randomized to VR or video-based training during shifts in the emergency department. Clinical performance was assessed by review of a video-recorded patient encounter using a standardized assessment tool and by an in-person, two question shock assessment. Residents completed a survey assessing attitudes toward their intervention at the time of training. Results Eighty-five senior pediatric residents were enrolled; 84 completed training. Sixty-four (76%) residents had a patient encounter available for video review (VR 33; Video 31). Fourteen residents in the VR group (42.4%, 95% CI 25.5% to 60.8%) and 13 residents in the video group (41.9%, 95% CI 24.6% to 60.9%) completed a perfusion exam AND verbalized an assessment during their next clinical encounter (X2 p-value 1.00). Fifty-one of 64 residents (79.7%) completed the two-step shock assessment; 50 (98%) agreed with supervising physician’s assessment. VR was rated more effective than reading, low-fidelity manikin, standardized patient encounters, traditional didactic teaching, and online learning. Video was rated more effective than online learning, traditional didactic teaching, and reading. Conclusion Novel video and VR JITP perfusion exam and assessment trainings are impactful and well-received by senior pediatric residents.
You and me versus the rest of the world: the effects of affiliative motivation and ingroup partner status on social tuning

Bandura argues that individuals are more likely to engage in social learning when they identify with a social model and when they are motivated or rewarded. Therefore, in the present work, we investigate how these two key factors, perceived similarity and affiliative motivation, influence the extent to which individuals engage in social tuning or align their views with an interaction partner—especially if their partner’s attitudes differ from the larger social group. Experiment 1 (170 participants) explored the role of perceived similarity through group membership when needing to work collaboratively with a collaboration partner whose climate change beliefs differed from a larger social group. Experiment 2 (115 participants) directly manipulated affiliative motivation (i.e., length of interaction time) along with perceived similarity (i.e., Greek Life membership) to explore if these factors influenced social tuning of drinking attitudes and behaviors. Experiments 3 (69 participants) and 4 (93 participants) replicated Experiment 2 and examined whether tuning occurred for explicit and implicit attitudes towards weight (negative views Experiment 3 and positive views Experiment 4). Results indicate that when individuals experience high affiliative motivation, they are more likely to engage in social tuning of explicit and implicit attitudes when their interaction partner belongs to their ingroup rather than their outgroup. These findings are consistent with the tenets of Social Learning Theory, Shared Reality Theory, and the affiliative social tuning hypothesis.
Tai Ji on Cognitive Function Improvement in Parkinson's Disease: A Meta-Analysis.

BACKGROUND Tai Ji (TJ) can improve cognitive function, which in turn brings life quality to Parkinson's disease (PD) patients. Cognitive function is thus important for PD patients. Analyzing the cognitive function and obtaining precise TJ exercise prescriptions are effective in treating PD patients. OBJECTIVES The purpose of this review was to discuss the current Randomized Controlled Trials (RCTs) of TJ and cognitive function improvement in PD. MATERIALS AND METHODS Databases, including PubMed, Web of Science, Scopus, Cochrane Library, EBSCOhost, Wan Fang, and CNKI, were searched. Cochrane systematic evaluation method was adopted wherein 6 RCTs met the final inclusion criteria. RESULTS Among the 6 included RCTs, 3 were of high quality, and the rest were of medium quality. Quantitative analysis exhibited that TJ intervention improved the cognitive function of PD patients. TJ promoted the global cognitive function (p < 0.05) and the executive function (p = 0.09) compared with the control. However there was no significant improvement in cognitive motor. TJ training intervention doses of two times a week with 45-60 min sessions over ≤12 weeks could improve the cognitive function of PD patients. CONCLUSIONS TJ affects the cognitive function of PD patients. However, this effect may have a reduced or no significant impact as the disease increases. PD patients can choose TJ as an intervention for 45-60 min twice a week for at least 12 weeks to accomplish maximum improvement in cognitive function.