Miracle-dz/UniFAR-FTUs huggingface dataset:
Role of Probiotics in Preventing Carbapenem-Resistant Enterobacteriaceae Colonization in the Intensive Care Unit: Risk Factors and Microbiome Analysis Study

Older patients with multiple comorbidities often necessitate prolonged hospital stays and antibiotic treatment in the intensive care unit (ICU), leading to a rise in multidrug-resistant organisms like carbapenem-resistant Enterobacteriaceae (CRE). This study examined risk factors for carbapenem-resistant Enterobacteriaceae colonization in the ICU and assessed probiotics’ preventive role. In this single-center, retrospective study, 9099 ICU patients were tested for stool CRE culture from March 2017 to April 2022. We excluded 136 patients with CRE colonization within one week post-admission and 26 who received probiotics before CRE colonization. Ultimately, 8937 CRE-negative patients were selected. Logistic analysis identified CRE colonization risk factors and evaluated probiotics’ influence, including Saccharomyces boulardii or Lactobacillus rhamnosus, used by 474 patients (5.3%) in the ICU. Compared with data on initial admission, 157 patients (1.7%) had newly discovered CRE colonization before discharge. In a multivariate analysis, coronavirus disease 2019, the ICU, tube feeding, antibiotics such as aminoglycoside, extended-spectrum penicillin, stool vancomycin-resistance enterococci colonization, and chronic kidney disease were significantly associated with de novo CRE infection. However, probiotic use was negatively correlated with CRE infection. Managing risk factors and administering probiotics in the ICU may help prevent CRE colonization; large randomized prospective studies are needed.
Wetlands reserve program: a partnership to restore wetlands and associated habitat

The 1990 Farm Bill created the Wetlands Reserve Program (WRP) to restore and protect wetland, which as of 2002 has enrolled over 1.4 million acres of wetland and upland habitat in 49 states and Puerto Rico. The program is administered by the U. S. Department of Agriculture Natural Resource Conservation Service and delivered in cooperation with many partners from the private and government sector. The program targets converted or degraded wetlands, primarily cropland, with a high probability of successful restoration. It authorizes permanent and 30-year easements as well as 10-year agreements. Restoration costs from 75% to 100% are provided, depending on the length of the easement. Most of the acreage is enrolled with permanent easements, and the remaining are 30- year easements or 10-year contracts.
Plate-curving cell culture as a model for assessing curvature-induced cellular responses during neural tube morphogenesis

ABSTRACT Neurulation is an important shape-transforming event during embryonic development where a flat neural plate is converted into a neural tube. Failure in this morphogenetic process accounts for one of the most common birth defects. Mechanical biology has provided key insights into neural tube formation and curvature among many physical properties that are eliciting attention. However, the lack of a proper model to study the effect of curvature has limited the potential to reveal its role in neurulation. In this study, we introduce a novel cell culture method called plate-curving cell culture where a polydimethylsiloxane (PDMS) plate of desired physical properties is curved in either a concave or convex form while the human pluripotent stem cell culture induced to have early neural plate identity is placed on top of its surface. With this method, we observed the elongation of cell colony morphology, as well as the perpendicular alignment of the cell division axis in the concave surface; the oriented cell division does not seem to explain the colony elongation. Transcriptome comparison in search of alternate possibilities suggested selectively altered pathways in the concave surface culture. Our new method is widely available, easy-to-use and culture-friendly, facilitating future mechanobiological studies of neurulation.
HUMAN AGE -GROUP ESTIMATION BASED ON ANFIS USING THE HOG AND LBP FEATURES

In this paper, a new age-group estimation method is proposed based on fuzzy inference system. Using this method, the facial images could be classified in four groups with more accuracy for classification of marginal ages. The proposed algorithm is divided into 3 stages. At first stage, the images are preprocessed. Then, the image features are extracted using histograms of oriented gradients (HOG) and local binary patterns (LBP). Finally, by using neural networks and adaptive neuro-fuzzy inference system (ANFIS) the age-groups are classified. Experimental results show that by using this method, the agegroup classification is done with better performance and the accuracy of age estimation is improved.
The influence of workload on performance of teachers in public primary schools in Kombewa division, Kisumu West district, Kenya

This research project reports findings on the influence of workload on the performance of teachers in public primary schools in Kombewa Division, Kisumu West District, Kenya. The objective of the study was to establish the influence of workload on the performance of teachers in public primary schools in Kombewa Division, Kisumu West District, Kenya. A survey design was used to gather data by means of questionnaires. Secondary data was obtained from the Divisional Education Office. The responses of 130 teachers out of a sample of 162 teachers revealed that workload influences performance of teachers. Using Pearson's correlation technique, the study shows that the independent variable (workload) and the dependent variable (performance of teachers) have a weak positive relationship (r = 0.03). The study also established that there is a shortage of teachers in public primary schools in Kombewa Division. Another key finding of the study is that job overload negatively influences performance of teachers. Most of the teachers in the division admit that job overload contributes to low performance. Since it is clear that employee performance is influenced by the workload, this study recommends that the employees be given enough loads to improve in performance. The study further recommends that more teachers should be employed to help curb understaffing. Further studies can also be done on motivation and effect of stress on employee performance.
A Study on Mobile Crowd Sensing Systems for Healthcare Scenarios

Due to the growing capabilities of mobile phones and devices, mobile crowd sensing (MCS) is rapidly gaining popularity among researchers in different fields, given its ability to collect data at scale and low cost. MCS is particularly important in the healthcare domain since it provides opportunities to collect health, wellness, and Quality of Life information from a large and diverse population. For example, MCS can be used to detect early signs of emerging health conditions, track the spread of infectious diseases, and assess the effectiveness of interventions without the need for frequent clinical visits. Consequently, MCS can also reduce healthcare costs and help overcome barriers to healthcare access. This article takes a closer look at MCS systems that have been used to collect data for research in the medical and healthcare domains. We provide a thorough analysis of selected systems based on their different health-related objectives, such as monitoring physical activity, detecting and preventing disorders, and providing medical treatment. We also adopt a three-layered architecture to structure health-centric MCS frameworks, consisting of application, data, and sensing layers. In the application layer, we analyze participant recruitment, incentive mechanisms, and task allocation strategies. In the data layer, we analyze the types of data collected and how they are stored and processed for future use. The sensing layer specifies the sensing methods and explains the fundamental requirements at a lower level. Additionally, we explore the significant challenges faced by existing MCS systems and domains that offer promising avenues for future research, which are user privacy, resource utilization, data quality, and user compliance. This work provides insights into some practical applications of MCS, highlights challenges faced by existing MCS solutions, and how they can be addressed, all of which can help catalyze future research in MCS development.
Lake level reconstruction of Huangqihai Lake in northern China since MIS 3 based on pulsed optically stimulated luminescence dating

Lake sediments provide rich information about past climatic variations in the drainage area. Five outcrops from Huangqihai Lake in northern China were investigated to reconstruct the lake level fluctuations during the late Pleistocene and Holocene. A chronological framework ranging from ∼34 to ∼8 ka was established by pulsed optically stimulated luminescence dating using sand‐sized quartz and by radiocarbon dating techniques. The chronological and geological evidence demonstrates that the lake level of Huangqihai reached a peak elevation of ∼1340 m [>77 m above the present lake level (a.p.l.l)] during the early Holocene. Such highstand was sustained from ∼10 to ∼8 ka and retreated towards the middle and late Holocene. Between ∼50 and ∼11 ka, aeolian and fluvial deposition prevailed around the lake basin and no lake sediment was found above 1277 m (∼14 m a.p.l.l.), demonstrating a low lake level during this interval compared with that of the early Holocene.
Cluster and Conquer: Malicious Traffic Classification at the Edge

—The uptake of digital services and IoT technology gives rise to increasingly diverse cyber attacks, with which commonly-used rule-based Network Intrusion Detection Systems (NIDSs) struggle to cope. Therefore, Artificial Intelligence (AI) supports a second line of defense, since this methodology helps in extracting non-obvious patterns from network traffic and subsequently in detecting more confidently new types of threats. Cybersecurity is however an arms race and intelligent solutions face renewed challenges as attacks evolve while network traffic volumes surge. We propose Adaptive Clustering-based Intrusion Detection (A CID ), a novel approach to malicious traffic classification and a valid candidate for deployment at the network edge. A CID addresses the critical challenge of sensitivity to subtle changes in traffic features, which routinely leads to misclassification. We circumvent this problem by relying on low-dimensional embeddings learned with a lightweight neural model comprising multiple kernel networks that we introduce, which optimally separates samples of different classes. Extensive experiments with datasets spanning 20 years demonstrate A CID attains 100% accuracy and F1-score, and 0% false alarm rate, significantly outperforming state-of-the-art clustering methods and NIDSs. Furthermore, our results show that A CID offers a high degree of robustness to input perturbations, while intrinsically providing a framework for continual learning.
Eye tracking vyšetření predilekce očních pohybů u pacientů po cévní mozkové příhodě

Vizuospacialni vnimani nam umožňuje fungovat ve vizualnim světě. Poruchy vizuospacialniho vnimani u pacientů po cevni mozkove přihodě mohou mimo jine narusit kvalitu průběhu rehabilitace. Cilem teto prace je zjistit, zda se u pacientů po prodělane cevni mozkove přihodě vyskytuji poruchy vizuospacialniho vnimani, a dochazi tak k urcite stranove prostorove predilekci. Měřeni probihalo pomoci eye trackingu, což je metoda snimajici a zaznamenavajici pohyb lidskeho oka. Před samotným vysetřenim bylo zjistěno pomoci klinických testů (zejmena pen and paper testů), jestli proband nema klinicky významný neglect syndrom. Lide s klinicky průkazným neglect syndromem byli ze studie vyřazeni. Měřena byla skupina 20 pacientů s CMP (10 s pravostrannou hemiparezou, 10 s levostrannou hemiparezou), ve srovnani s 10 zdravými probandy. Vysetřeni pomoci eye trackingu bylo provaděno pomoci 19 interaktivnich ukolů se zaměřenim na prostorove vnimani promitaných na obrazovku. Ac výsledky nebyly statisticky významne, přesto se u některých jednotlivců výraznějsi stranova prostorova predilekce projevila.
Exploring the impact of diagenesis on (isotope) geochemical and microstructural alteration features in biogenic aragonite

For the Quaternary and Neogene, aragonitic biogenic and abiogenic carbonates are frequently exploited as archives of their environment. Conversely, pre‐Neogene aragonite is often diagenetically altered and calcite archives are studied instead. Nevertheless, the exact sequence of diagenetic processes and products is difficult to disclose from naturally altered material. Here, experiments were performed to understand biogenic aragonite alteration processes and products. Shell subsamples of the bivalve Arctica islandica were exposed to hydrothermal alteration. Thermal boundary conditions were set at 100°C, 175°C and 200°C. These comparably high temperatures were chosen to shorten experimental durations. Subsamples were exposed to different 18O‐depleted fluids for durations between two and twenty weeks. Alteration was documented using X‐ray diffraction, cathodoluminescence, fluorescence and scanning electron microscopy, as well as conventional and clumped isotope analyses. Experiments performed at 100°C show redistribution and darkening of organic matter, but lack evidence for diagenetic alteration, except in Δ47 which show the effects of annealing processes. At 175°C, valves undergo significant aragonite to calcite transformation and neomorphism. The δ18O signature supports transformation via dissolution and reprecipitation, but isotopic exchange is limited by fluid migration through the subsamples. Individual growth increments in these subsamples exhibit bright orange luminescence. At 200°C, valves are fully transformed to calcite and exhibit purple‐blue luminescence with orange bands. The δ18O and Δ47 signatures reveal exchange with the aqueous fluid, whereas δ13C remains unaltered in all experiments, indicating a carbonate‐buffered system. Clumped isotope temperatures in high‐temperature experiments show compositions in broad agreement with the measured temperature. Experimentally induced alteration patterns are comparable with individual features present in Pleistocene shells. This study represents a significant step towards sequential analysis of diagenetic features in biogenic aragonites and sheds light on reaction times and threshold limits. The limitations of a study restricted to a single test organism are acknowledged and call for refined follow‐up experiments.
The Rating of Perceived Exertion—Pediatric (RPE-P) Scale: Preliminary Validation

Physical activity is critical to functional rehabilitation for youth with chronic pain, which may be especially true for those with co-occurring obesity. To facilitate the development of physical activity interventions for youth with chronic pain, the newly developed “Rating of Perceived Exertion—Pediatric” scale was modeled after the widely used pain numeric rating scale-11. This study is an initial evaluation of the scale in a sample of adolescents (n = 157, 13–17 years, 51% female) with four subgroups: (1) healthy controls (healthy weight/no pain); (2) chronic pain/healthy weight; (3) obese (no pain); (4) chronic pain/obese. Participants rated perceived exertion using the new scale and the Borg 6–20 Scale of Perceived Exertion while holding a three-minute yoga pose (Warrior II). In the whole sample, the Perceived Exertion—Pediatric scale showed good concurrent (p < 0.001), convergent (all ps < 0.05), discriminant (p = 0.431), and known-groups validity (all ps < 0.05). The chronic pain subgroup also showed good concurrent (p < 0.001), mixed convergent (ps < 0.001 to 0.315), and good discriminant validity (p = 0.607). Limitations include the restricted age range, lack of diversity, and lack of test-retest reliability. The RPE-P shows promise as an assessment tool for perceived exertion in adolescents with and without chronic pain.
Competencies required by patients and health professionals regarding telerehabilitation: A scoping review

Background Telerehabilitation offers patients alternative access to therapy and has become more prominent during the COVID-19 pandemic. Despite the increasing attractiveness of such programs, there are research gaps regarding the required competencies in the demand-oriented technology use in rehabilitative care. Objective The study aims at collecting evidence on competencies required by patients and health professionals for using telerehabilitation. We analyse tasks and requirements associated with telerehabilitation and derive and systematise relevant competencies. Methods We conducted a scoping review and analysed MEDLINE, Psyndex, EMBASE, Cochrane Library, and Web of Science for empirical studies and grey literature from 2017 to May 2022. Articles had to be in English/German and refer to medical rehabilitation accompanied by health professionals taking place in the patient's home. Results One hundred ten articles were included, covering video conferencing systems, applications with video, audio, or visual therapy content, or wearables. Depending on the program, tasks before, during, and after therapy sessions differ, as do whether these are performed by health professionals, patients, or the technology. Users need digital, health-related, social, personal, and health professionals also professional competencies. This comprises telerehabilitation, technical, health-related, and clinical knowledge, a range of physical, cognitive, social-interactive, technical, and clinical skills, a positive attitude towards telerehabilitation and experience. Whether sociodemographic factors promote successful use is unclear. Conclusions Telerehabilitation requires a variety of different competencies from patients and health professionals — going beyond the sphere of technical skills. This highlights the need for an evaluation of existing programs for promoting competencies in the use of telerehabilitation and refinement of the programs in line with demands.
UNSUPERVISED STATISTICAL APPROACH FOR TREE-LEVEL SEPARATION OF FOLIAGE AND NON-LEAF COMPONENTS FROM POINT CLOUDS

Abstract. Accurately classifying foliage and non-leaf components in point clouds is essential for remote sensing forest applications. Existing methods rely on radiometric attributes or local geometric features, often requiring time-consuming manual labelling. In this paper, we propose a statistical approach using flexible thresholds determined based on tree-level geometric features. Selected features (local anisotropy, curvature, linearity, first principal component, verticality, and sphericity) have shown robustness in earlier studies. Threshold values are identified as points of inflection in the fitted distributions for each tree. Our method requires only two parameters and was tested with manually labelled Terrestrial Laser Scanning (TLS) data and non-labeled data from an oblique and above canopy setup (Permanent LiDAR scanner setup). We tested two boreal tree species, Scots Pine, and silver birch, with 28 trees in total (14 trees for each species) using two data sources. Compared to two alternative methods (namely, fixed thresholding and CANUPO), our approach consistently outperforms in terms of recall. We achieved an average overall accuracy of 85%, recall of 88.5%, precision of 83%, and f1 score of 85%. Visually assessing oblique and above canopy results, our algorithm effectively captures tree structures. Our statistical approach provides an effective solution for foliage and non-leaf separation, with processing times of less than five minutes for individual tree point clouds containing up to 2 million points and no need for extensive manual labelling or parameter adjustments.
Mapping the Cognitive Biases Related to Vaccination: A Scoping Review of the Literature

Introduction: Human behavior and understanding of the vaccine ecosystem play a critical role in the vaccination decision-making process. The objective of this study was to understand different cognitive biases that may lead to vaccine acceptance or hesitancy. Methods: The eligibility criteria for this scoping review was vaccination-related cognitive bias studies published in the English language from inception to April 2022 and available on PubMed, Embase, and Google Scholar. It included all geographical locations and individuals of all age groups and excluded studies focusing on (i) clinical trials of vaccines, (ii) vaccine research conduct bias, (iii) cognitive delay, or (iv) statistical biases. The search method also included reviewing references in the retrieved articles. Results: Overall, 58 articles were identified, and after screening, 19 were included in this study. Twenty-one cognitive biases with the potential to affect vaccination decision-making were observed. These biases were further grouped into three broad categories: cognitive biases seen while processing vaccine-related information, during vaccination-related decision-making, and due to prior beliefs regarding vaccination. Conclusions: This review identified critical cognitive biases affecting the entire process of vaccination that can influence research and public health efforts both positively and negatively. Recognizing and mitigating these cognitive biases is crucial for maintaining the population’s level of trust in vaccination programs around the world.
Performance deterioration of asphalt mixture exposed to salt-water-temperature-ultraviolet coupling effect

ABSTRACT The intense ultraviolet radiation and large amount of saline-alkali soil in the Golmud region of Province, China, have deteriorated the performance of asphalt pavement. Given the effect of adverse conditions in this area, this paper investigated the collective and interaction effects of salt chemicals, air temperature, and ultraviolet radiation on asphalt and asphalt mixture through laboratory experiments under controlled conditions. In particular, using different concentrations of Na2SO4 and NaCl solutions, simulated salt chemicals for asphalt and asphalt mixture performance impact. The mechanism of performance deterioration of the asphalt mixture suffered from salt attack was explored. The results show that the original asphalt's storage and loss modulus are higher than the modified asphalt at different temperatures with the multi-factors effect. In addition, the modified asphalt's phase angle is 5%∼10% higher than the original asphalt below −2°C. At the same time, strength loss rates of asphalt mixture increase with the cycles and solution concentration, varying from 20%−40%. Wet-dry cycles and the concentration of salt solution are positively correlated with the deterioration of asphalt mixture strength. This research provides the durability prediction and the more reasonable composition design of the asphalt mixture applied in salt enrichment regions.
Study on Spider Diversity Associated with an Apple Orchard, Nainital District, Uttarakhand, India

: The present study aimed to understand the diversity of spiders in and around the Dev Ban apple orchard from October 2021 to September 2022 in Ramgarh, which lies in the Kumaun region of Nainital district, Uttarakhand, India. This is the first investigation to reveal the presence of 246 spider individuals representing 21 species belonging to 16 genera and 10 families from the study area. The spider sampling was carried out by using visual searching and handpicking, ground hand collection, aerial hand collection, the kerchief method, pitfall traps, beating, and the sweep netting method. The most dominant family of spiders was observed to be the Araneidae (29%), followed by Lycosidae (18%), Salticidae (15%), Pholcidae (10%), Sparassidae (09%), Thomisidae (07%), Linyphiidae (05%), Oxyopidae (04%), Philodromidae (03%), and Theridiidae (1%). The most dominant spider species was Alopecosa cursor of family Lycosidae. Also, the Simpson ’ s Diversity Index (SDI) was calculated, which resulted in a value of 0.94, which indicates the presence of high spider species diversity in the study area. This preliminary study gives base line information about the spider ’ s diversity from the unexplored orchard system of the Kumaun region of Uttarakhand.