Miracle-dz/UniFAR-FTUs huggingface dataset:
Feeding postural behaviors and food geometric and material properties in bearded capuchin monkeys (Sapajus libidinosus)

Abstract Objectives Foods that are geometrically and mechanically challenging to eat have been associated with specializations in feeding behavior and craniodental morphology across primates, and many of these foods are embedded, requiring a variety of positional behaviors during feeding. However, variation in positional behaviors in response to food properties is not well understood. Here, we examine differences in feeding postural behaviors across feeding events in relation to substrate and food geometric and material properties in a species of extractive foragers, bearded capuchins (Sapajus libidinosus). Methods and materials We coded over 1400 co‐occurring postural and feeding behaviors, their durations, and relative sizes of substrate and food from videos recorded at Fazenda Boa Vista in Gilbués, Piauí, Brazil. Food material properties were measured from foods collected at the time of the video recordings. Results Our results suggest that bearded capuchin feeding postures significantly differ across the feeding sequence, with substrate size, and between foods of high and low toughness and elastic modulus. Feeding postures were less variable for highly mechanically challenging foods. Food size also had a significant effect on postural behaviors. Large foods were more likely to be associated with suspended postures and small foods with sitting and squatting. Feeding postural behaviors were best explained by a combination of substrate and food variables. Conclusions Our results indicate that food geometric and mechanical properties have a significant influence on feeding postural behaviors in bearded capuchins. We posit that feeding postural behaviors reflect a combination of substrate variables and food properties, and large, mechanically challenging foods have a limiting effect on postural variation.
High Power Active Filter using LC Tuned Filter

Usually, to eliminate the harmonics of transmission lines, LC tuned filters are employed to let bypass these harmonic components. But the elimination ability is limited by its damping resistance. Therefore, active filters composed of high frequency PWM converters are desirable. Comparing with the LC tuned filters, the cost would be very high even in high power systems.In this paper, a low cost and high power active filters for a DC transmission system is proposed. It has active filter ability as well as low cost for high power uses. Its main circuit is composed of conventional LC filters in series with square wave voltage inverters. The voltage of the inverter is controlled to cancel the voltage drop of the internal resistance of the LC filter. So the Q factor of the filter can appear infinity. Calculation of the harmonic and the control are done by DSP (TMS 32010). In the experimental system and simulations, two three phase tuned filter 5-th and 7-th are employed. Excellent results under 1% distortion voltage are obtained.
The neuro-inflammation and excitotoxicity in perinatal brain injury: The emerging role of brain mast cells

Perinatal brain injury is a serious neurodevelopmental problem that can be occurred in preterm and term newborn infants. It is well established that neuro-inflammation is implicated in the pathophysiology of perinatal brain injury. The excitotoxicity is considered as a common molecular mechanism of perinatal brain injury. These insults are capable of leading to neuro-inflammation, but however neuro-inflammation is also able to induce the excitotoxicity in the developing brain. Thus, neuro-inflammation is both a cause and a consequence of excitotoxicity resulting in the brain damages during perinatal period. Excessive glutamate accumulation in the synaptic cleft in the brain is a prominent mechanism in the excitotoxicity while vasoactive and pro-inflammatory mediators such as histamine, prostaglandins, interleukin 1 (IL-1) β and tumor necrosis factor (TNF)-α released from brain-resident immune cells play a major role in neuro-inflammation that lead to the brain damages. Although the role of brain-resident microglial cells has been well documented in these neuro-inflammation processes, evidence for the role of brain mast cells (BMCs) has recently begun to emerge. Growing evidence indicates that brain mast cells are first responders of inflammatory insults in the developing brain and their activation is involved in induced brain injury. We have recently demonstrated that ibotenate-induced excitotoxicity leads to the activation of brain mast cells in a model of ibotenate-induced brain injury in newborn rats. Thus, in this review we point out the current knowledge on the bidirectional role of brain mast cells in neuro-inflammation and excitotoxicity underlying perinatal brain injury.
Biological Functions and Applications of Virus-Related Bacterial Nanoparticles: A Review

Accumulating evidence suggests that microorganisms produce various nanoparticles that exhibit a variety of biological functions. The structure of these bacterial nanoparticles ranges from membrane vesicles composed of membrane lipids to multicomponent proteinaceous machines. Of bacterial nanoparticles, bacterial phage tail-like nanoparticles, associated with virus-related genes, are found in bacteria from various environments and have diverse functions. Extracellular contractile injection systems (eCISs), a type of bacterial phage tail-like nanostructure, have diverse biological functions that mediate the interactions between the producer bacteria and target eukaryote. Known gram-negative bacterial eCISs can act as protein translocation systems and inject effector proteins that modulate eukaryotic cellular processes by attaching to the target cells. Further investigation of the functions of eCISs will facilitate the application of these nanomachines as nano-sized syringes in the field of nanomedicine and vaccine development. This review summarises the recent progress in elucidating the structures and biological functions of nanoparticles that resemble the tail components of phages that infect bacteria and discusses directions for future research to improve the clinical applicability of virus-related bacterial nanoparticles.
The generalized sigmoidal quantile function

In this note we introduce a new smooth nonparametric quantile function estimator based on a newly defined generalized expectile function and termed the sigmoidal quantile function estimator. We also introduce a hybrid quantile function estimator, which combines the optimal properties of the classic kernel quantile function estimator with our new generalized sigmoidal quantile function estimator. The generalized sigmoidal quantile function can estimate quantiles beyond the range of the data, which is important for certain applications given smaller sample sizes. This property of extrapolation is illustrated in order to improve standard bootstrap smoothing resampling methods.
Intrathecal Fentanyl With a Paracervical Block Is Safe and Effective for Elective Termination of Pregnancy in a Patient With Primary Pulmonary Hypertension

Pulmonary hypertension (PH) in pregnancy, irrespective of etiology, is associated with significant maternal morbidity and mortality. This case describes a novel approach to providing anesthesia for a hemodynamically fragile patient. It demonstrates the careful planning and weighted decision-making that is required when approaching a parturient with severe pulmonary hypertension. The patient's previous pulmonary artery catheterization showed right ventricular systolic pressure of 78 mmHg and pulmonary artery pressure of 78/20 mmHg. The patient presented with worsening dyspnea and a decision was made to proceed with the termination of pregnancy via dilatation and curettage (D&C). Anesthesia was conducted with combined intrathecal fentanyl with a paracervical block using lidocaine 2%. The patient had a complication of post-procedure hemorrhage secondary to uterine atony that required careful monitoring and judicious use of uterotonic medications. A decision was made to use oxytocin due to its favorable effect profile compared to other uterotonic medications. We hope this anesthesia technique will aid in the future management of these challenging cases.
Measurements of three-dimensional flow field at exit of a turbine rotor passage in different tip clearances

The time-resolved flow field downstream of a turbine rotor with different tip clearances was measured using a fast-response four-hole pressure probe.The results show that the flow is obviously periodic due to the rotor.It also indicates that the tip leakage flow has profound effects on the flow field.With bigger tip clearance,the leakage flow is relatively stronger and the secondary flow near the casing wall is weaker.When the tip gap is smaller,the secondary flow near the casing wall becomes stronger.The velocity in the leakage flow region is very low and the loss is high,which leads to substantial flow blockage.The flow under-turning due to the leakage flow is also clearly seen in the measurements.The static pressure in the leakage flow is higher than that in the main flow.The work done by the rotor with bigger tip clearance is lower than that with smaller tip clearance.
Nanocomposites of Fe(II)-Based Metallo-Supramolecular Polymer and a Layered Inorganic–Organic Hybrid for Improved Electrochromic Materials

Fe-based metallo-supramolecular polymer (polyFe), composed of Fe(II) ions and bis(terpyridyl)benzene, is known as a good electrochromic (EC) material. For the first time, to improve the EC properties, we prepared nanocomposites comprising polyFe and a layered inorganic–imidazoline covalently bonded hybrid (LIIm) by simply mixing them in methanol and then examined the effect of the nanocomposition on EC properties. The obtained blue/purple-colored composites (polyFe/LIIm composites) were demonstrated by scanning electron microscopy (SEM) to comprise a structure of LIIm nanoparticles coated with amorphous polyFe. Interestingly, X-ray diffraction (XRD) measurements suggested that there was no intercalation of polyFe in the interlayer space of LIIm. Ultraviolet-visible (UV-vis) spectroscopy measurements demonstrated that light absorption close to 600 nm was attributed to metal-to-ligand charge transfer (MLCT) from the Fe(II) ion to the bisterpyridine ligand and was influenced by LIIm in the composites. The composites exhibited a pair of redox waves, assigned to the redox between Fe(II) and Fe(III), in the cyclic voltammograms; moreover, the composites were estimated to be diffusion controlled. Thin composite films demonstrated reversible EC changes, triggered by the redox reaction of the metal. Furthermore, the results show that the nano-scale composition of the metallo-supramolecular polymers with LIIm can effectively improve the memory properties without reducing the contrast in transmittance (ΔT) of 70–76% in EC changes after applying 1.2 V vs. Ag/Ag+. The EC properties varied with varying ratios (3/0.1, 0.5, 1, and 5) of the polyFe/LIIm, and the ratio of 3/1 exhibited the longest memory and largest MLCT absorption peak among composites. The results show that the polyFe/LIIm composites are useful EC materials for dimming glass applications, such as smart windows.
Criticality Analysis Method for the Failure Mode Effects of Railway Freight Car

According to the complexity and fuzzy uncertainty of many factors affecting the failure modes of railway freight car,the comprehensive evaluation method of combining fuzzy theory with analytic hierarchy process is proposed.Based on this method,failure probability,criticality degrees,difficult degrees of failure detection and maintenance are considered.The quantitative criticality analysis of railway freight car′s failure modes is carried out in the case of incomplete failure data information.In the comprehensive evaluation method,criticality degrees of failure modes with lots of fuzzy factors are calculated by applying fuzzy theory,and weights of all influencing factors are determined by using analytic hierarchy process.The application result indicates that this method can not only process quantitatively qualitative questions and obtain reasonable analysis results,but also identify key factors of reliability analysis in accordance with the obtained criticality priority orders,and provide valuable references for ameliorating design and improving reliability of product.
Blended Therapies and Mobile Phones for Improving the Health of Female Victims of Gender Violence

We carried out a case study with a group of female victims of gender violence (n = 39) with the objective of evaluating a blended psychotherapeutic intervention. The results show that blended therapies with mobile text messages combined with face-to-face group therapies significantly improved the health of these women. Mood states and the symptoms of depression were measured with a PHQ-9 personal health questionnaire and evolved positively. In the group of women (n = 39) the scores improved from an initial 13.5 (SD = 7.2, range 3–34) to 6.0 at the end of the period of messages (SD = 5.2, range 0–18), which was a significant difference (t (39) = 2.02; p = 0.000). Most of the women stated that the messages had helped them improve their mood (91.6%) and their general health (83.3%), which made them feel more connected to their social environment (80.6%). We observed that adherence to medication for each woman improved. With mixed therapies and mobile phones, social service professionals can incorporate technology into daily practices and offer personalized attention and daily counseling to victims of gender-based violence.
Influences of Environmental Perception on Individual Cognitive Engagement in Online Learning: The Mediating Effect of Self-Efficacy

During online learning, complicated environmental perception factors influence the cognitive engagement of students, which is an influencing variable of learning motivation, learning outcomes, and other classroom effect indicators. In this study, the research hypotheses on the influences of the environmental perception of online learning (including students’ self-factors, teacher factors, peer factors, and technological factors) on individual cognitive engagement (deep engagement and superficial engagement) were proposed. The mediating effect of the influences of self-efficacy on individual cognitive engagement under the online learning model was estimated. Results demonstrate that the Cronbach’s α of the questionnaire used in the study is 0.891 and the KMO is 0.841. These outcomes reflect that this questionnaire has very good reliability and validity. In the online learning environment, students’ self-factors, peer factors, and technological factors can promote individual cognitive engagement significantly. Furthermore, self-efficacy develops a mediating effect in the significantly positive promotion of environmental perception on individual cognitive engagement. Cognitive engagement also changes with the duration of online learning (F=4.530, p=0.005). Moreover, the influences of majors on cognitive engagement are significant at the 0.05 level (F=2.188, p=0.047). Conclusions have important references to comprehend the influences of different environmental perception factors on individual cognitive engagement in the process of online learning and disclose how self-efficacy influences individual cognitive engagement.
Multi-Aspect Based Approach to Attack Detection in IoT Clouds

This article covers the issues of constructing tools for detecting network attacks targeting devices in IoT clouds. The detection is performed within the framework of cloud infrastructure, which receives data flows that are limited in size and content, and characterize the current network interaction of the analyzed IoT devices. The detection is based on the construction of training models and uses machine learning methods, such as AdaBoostClassifier, RandomForestClassifier, MultinomialNB, etc. The proposed combined multi-aspect approach to attack detection relies on session-based spaces, host-based spaces, and other spaces of features extracted from incoming traffic. An attack-specific ensemble of various machine learning methods is applied to improve the detection quality indicators. The performed experiments have confirmed the correctness of the constructed models and their effectiveness, expressed in terms of the precision, recall, and f1-measure indicators for each analyzed type of attack, using a series of existing samples of benign and attacking traffic.
Investigating the use of social media in intimate social relationships

ABSTRACT Research Question: Is social media activity related to layers of intimacy in social relationships? Study design: Mixed methods, survey on social relationships with 30 participants who identified up to 20 best/close friends and their use of social media. The same 30 participants were interviewed to gather details of how they communicated with close and best friends, and how they used social media/CMC to maintain their social relationships. Analysis: communication frequency, content and rationale were classified according to the intimacy of relationships between the ego and recipients as best or close friends. Results: Communication with best friends was either face to face or by conversational media (phone, text) in both normal use and emergencies. Emotional support and intimate topics dominated these exchanges. Communication with close friends used broadcast social media (Facebook), text and phone. Face to Face (FtF), phone and text were preferred by the majority of participants for social relationship maintenance. Implications: Dyadic (person to person) communication face to face and via social media, phone and text are vital to provide social and emotional support in intimate social relationships. Social media in particular Facebook broadcast functions play a role in supporting awareness of both intimate and less intimate social relationships.
How the Strength of Monsoon Winds Shape Forest Dynamics

Monitoring long-term forest dynamics can improve our understanding of how tree species change under varying environmental conditions over time. The Nanjenshan Nature Reserve, located in the southernmost part of Taiwan, is covered by natural tropical forest and affected by the northeast monsoon wind in the winter. To explore how monsoon wind shapes the structure of vegetation, we used the long-term data of the Lanjenchi plot (high wind exposure forest) and Nanjenshan plot I (low wind exposure forest) located in the Nanjenshan Nature Reserve. In these two plots, all free-standing trees with diameter at breast height (DBH) ≥ 1 cm were identified, measured, and mapped five times in thirty years (1989–2019). Temporal changes of tree abundance, dominance, recruitment, and mortality were calculated for all species. We recorded 9694 ± 3924 individual ha−1 belonging to 126 species in the high wind exposure forest and 4019 ± 1791 individual ha−1 belonging to 105 species in the low wind exposure forest in the latest census (census 5). From 1989 to 2019, stem density in the high wind exposure forests decreased (from 12,179 ± 6689 to 9694 ± 3924 individual ha−1), while stem density in the low wind exposure forests increased (from 3253 ± 1208 to 4019 ± 1791 individual ha−1). The stem density of the rare species, which survived only in the high wind exposure forest, decreased over time. However, the basal areas of these two forests barely changed during the study periods. Due to environmental conditions, the two forests have developed different forest structures in spaces and time. Species stem density in the high wind exposure forest and diversity could continually decrease and affect the maintenance of species diversity in the monsoon wind-shaped forest.
Spatial Analysis and Lead‐Risk Assessment of Philadelphia, USA

Childhood lead poisoning is an issue that continues to plague major U.S. cities. Despite efforts by the Philadelphia Department of Public Health to curtail systemic childhood lead poisoning, children continue to be identified with elevated blood lead levels. The persistence of elevated blood lead levels in children is concerning because lead poisoning has been linked to decreases in academic achievement and IQ, with associated repercussions for entire communities. This paper reports the results of an analysis of the spatial distribution of houses with lead paint (i.e., pre‐1978), demolitions, and occurrence of historic smelters, in West and North Philadelphia, relative to elevated blood lead level data, to determine which lead sources act as primary lead‐risk factors. The presence of lead paint in homes and the number of demolitions of older properties were found to have the highest correlations to elevated blood lead levels for children in Philadelphia. Using lead‐risk factors including lead paint, housing code violations, demolitions, and owner‐occupied housing units, a lead‐risk assessment was performed at the census tract level to identify future soil sampling sites and high‐risk neighborhoods in Philadelphia. These sites of high risk for lead exposure, and in particular the census tracts 175 and 172, should be prioritized for lead poisoning prevention initiatives.
Smart Grid Energy Optimization and Scheduling Appliances Priority for Residential Buildings through Meta-Heuristic Hybrid Approaches

Smart grid technology has given users the ability to regulate their home energy use more efficiently and effectively. Home Energy Management (HEM) is a difficult undertaking in this regard, as it necessitates the optimal scheduling of smart appliances to reduce energy usage. In this research, we introduce a metaheuristic-based HEM system which incorporates Earth Worm Algorithm (EWA) and Harmony Search Algorithms (HSA). In addition, a hybridization based on the EWA and HSA operators is used to optimize energy consumption in terms of electricity cost and Peak-to-Average Ratio (PAR) reduction. Hybridization has been demonstrated to be beneficial in achieving many objectives at the same time. Extensive simulations in MATLAB were used to test the performance of the proposed hybrid technique. The simulations were run for multiple homes with multiple appliances, which were categorized according to the usage and nature of the appliance, taking advantage of appliance scheduling in terms of the time-varying retail pricing enabled by the smart grid two-way communication infrastructure algorithms EWA and HSA, along with a Real-Time Price scheme. These techniques helped us to find the best usage pattern for energy consumption to reduce electricity costs. These metaheuristic techniques efficiently reduced and shifted the load from peak hours to off-peak hours and reduced electricity costs. In comparison to HSA, the simulation results suggest that EWA performed better in terms of cost reduction. In comparison to EWA and HSA, HSA was more efficient in terms of PAR. However, the proposed hybrid approach EHSA gave the maximum reduction in cost which was 2.668%, 2.247%, and 2.535% in the case of 10, 30, and 50 homes, respectively, as compared to EWA and HSA.