Miracle-dz/UniFAR-FTUs huggingface dataset:
H∞ filtering via convex optimization

This paper reformulates the suboptimal (or level-gamma) H filtering problem into a Linear Matrix Inequality (LMI) problem by applying a bounded real lemma to the closed-loop transfer function. This formulation not only provides the condition of solvability but also constructs the suboptimal H filter. This formulation furthermore allows one to solve the 'epsilon-optimal' H filtering problem via convex optimization techniques, where the 'epsilon-optimality' implies that theH-norm of the resulting closed-loop transfer function is greater than or equal to the infimum, say gamma inf of the H-norms of all possible closed-loop transfer functions, but is less than or equal to epsilon gamma for an extremely small positive number epsilon, which will depend on the inf accuracy of the algorithms and the precision of a computer.
Influences of CNT Dispersion Methods, W/C Ratios, and Concrete Constituents on Piezoelectric Properties of CNT-Modified Smart Cementitious Materials

In order to achieve effective monitoring of concrete structures for sound structural health, the addition of carbon nanotubes (CNTs) into cementitious materials offers a promising solution for fabricating CNT-modified smart concrete with self-sensing ability. This study investigated the influences of CNT dispersion method, water/cement (W/C) ratio, and concrete constituents on the piezoelectric properties of CNT-modified cementitious materials. Three CNT dispersion methods (direct mixing, sodium dodecyl benzenesulfonate (NaDDBS) and carboxymethyl cellulose (CMC) surface treatment), three W/C ratios (0.4, 0.5, and 0.6), and three concrete constituent compositions (pure cement, cement/sand, and cement/sand/coarse aggregate) were considered. The experimental results showed that CNT-modified cementitious materials with CMC surface treatment had valid and consistent piezoelectric responses to external loading. The piezoelectric sensitivity improved significantly with increased W/C ratio and reduced progressively with the addition of sand and coarse aggregates.
The Downstream Effects of Body-worn Cameras: A Systematic Review and Meta-analysis

Abstract By virtue of their ability to capture evidence of criminal behavior, body-worn cameras (BWCs) have been associated with enhanced investigations and prosecutions. To date, however, research on these outcomes has been inconsistent, and there has been no attempt to systematically review or synthesize the results of these studies. To address this gap, we conducted a systematic review and meta-analysis of 12 experimental and quasi-experimental studies examining the impact of BWCs on prosecutorial and court-related outcomes. In aggregate, we find no significant effects of BWCs across any reported outcome measure, however, we find that studies focused on domestic violence offenses are associated with significant and large treatment effects across most outcome measures. While these results show promise, extant domestic violence studies are generally quasi-experimental in nature, and thus the effect of crime type cannot currently be separated from that of research design. Policy implications and directions for future research are discussed.
The Synergy between Zinc and Antimicrobial Peptides: An Insight into Unique Bioinorganic Interactions

Antimicrobial peptides (AMPs) are essential components of innate immunity across all species. AMPs have become the focus of attention in recent years, as scientists are addressing antibiotic resistance, a public health crisis that has reached epidemic proportions. This family of peptides represents a promising alternative to current antibiotics due to their broad-spectrum antimicrobial activity and tendency to avoid resistance development. A subfamily of AMPs interacts with metal ions to potentiate antimicrobial effectiveness, and, as such, they have been termed metalloAMPs. In this work, we review the scientific literature on metalloAMPs that enhance their antimicrobial efficacy when combined with the essential metal ion zinc(II). Beyond the role played by Zn(II) as a cofactor in different systems, it is well-known that this metal ion plays an important role in innate immunity. Here, we classify the different types of synergistic interactions between AMPs and Zn(II) into three distinct classes. By better understanding how each class of metalloAMPs uses Zn(II) to potentiate its activity, researchers can begin to exploit these interactions in the development of new antimicrobial agents and accelerate their use as therapeutics.
Human Ear Recognition Using Hybrid Filter and Supervised Locality Preserving Projection

To solve the difficult problem of human ear recognition caused by variety of ear angle, a novel method which combines hybrid filter with supervised locality preserving projection (SLPP) is proposed. The ear image is firstly filtered by Log-Gabor filter which is constructed with 5 scales and 8 orientations. The important parameters of Log-Gabor filter are selected through experiments. To form effective and discriminative feature too many Log-Gabor coefficients are reduced by discrete cosine transform. Lastly feature is constructed by SLPP to discovery geometrical rules. Experimental results show that compared with the traditional methods, the proposed method obtains higher recognition rate, and is robust to multi-pose of ear recognition.
Analysis of Musical Instrument Tones

A technique is presented for the analysis of musical instrument tones. The end result is a mathematical representation for the tone being investigated. Since no assumptions are made about the frequencies of the partial tones, inharmonic frequencies can be detected and accounted for in the representation. An analog‐digital converter was used to present the signals to the ILLIAC II digital computer for analysis. Five tones were analyzed, resynthesized, and subjected to listening tests. The trumpet tone was characterized by a frequency change which, if omitted during synthesis, made the tone sound mechanical. The saxophone tone had a short‐duration, inharmonic component which gave it the “bite” characteristic of a jazz tone. The other tones analyzed were produced by a violin, bassoon, and clarinet; and each, when resynthesized, still retained the tonal quality of the original; as examples, the wind tones sounded breathy and the violin sounded bowed. It was thus concluded that this analysis technique can be s.
Formative assessment for hybrid course in smart classroom: A cognitive presence perspective

This study investigated formative assessment for hybrid course. The participants were 379 students who took the "college Physics" hybrid course in the fall of 2022 in a university of China. Most students were learning with face-to-face teaching, while a few students were learning remotely in smart classrooms. Data were collected from the cognitive presence survey within community of inquiry framework and online self-regulatory learning questionnaire during the middle term. The result indicated that remote students’ cognitive presence were lower than students with face-to-face teaching in the smart classroom, and there were strong positive correlation between students’ online self-regulatory learning and cognitive presence. It was suggested that cognitive presence were measured again at the end of the semester to examine whether the cognitive presence of remote students in the final semester is better than that of the middle semester after intervention.
Use of Informational Brochures on Knowledge of Cataracts in Rural Ecuador

Background Cataracts are the leading global cause of preventable blindness. Despite the high prevalence of cataracts in rural Ecuadorian communities, no community-wide educational efforts on the impact of cataract-related blindness have been attempted. This study used an educational brochure to assess individual knowledge of cataract blindness before and after the distribution of the brochure. Methods We conducted electronic surveys with 100 patients over the age of 18 who visited the Fundacion Internacional Buen Samaritano Paul Martel (FIBUSPAM) clinic serving the Chimborazo region of Ecuador. Participation in the study included an introduction and written consent followed by a pre-survey. Every patient was given a brochure. After reviewing the brochure, patients were then asked to complete the same survey again. Each survey question received one mark. Knowledge was considered "good" if the subject correctly answered four out of seven questions and "poor" if they scored ≤3. Results Of the 100 patients, 21 had poor knowledge surrounding cataracts. Cataract awareness was lowest in the group without formal education (50%). In addition, 17 participants demonstrated poor knowledge before the informational brochure was distributed, and all improved to "good" knowledge after. Following brochure distribution, there was an improved knowledge of cataract anatomy (correct answer: 32.9% to 94.6%), treatment of cataracts (80% to 95.9%), cataract symptoms (36.7% to 95.9%), age at risk (88.8% to 97.3%), and relationship to blindness (93.5% to 98.6%). In contrast, overall knowledge of the risk factors for cataracts (46.8% to 37%) and prevention of the onset of the cataract (81.3% to 77%) slightly decreased after the brochure was given. Overall, the increase in the number of correct answers after the brochure was not significant (p = 0.25). Conclusions To our knowledge, this is a rare study to assess the effect of informational brochures on cataract knowledge in rural Ecuador. This study was limited by selection bias and did not look at the long-term recall of knowledge. The results of this study suggest that brochures can improve health awareness; however, brochures alone may not be enough. Additional assessments on the use of oral and visual aids are needed. Health education efforts should go beyond simple brochures and focus on innovative strategies to improve health education and communication efforts.
Perception of Torque is Impacted by a Subset of Features Related to the Motor Command

Accurate perception of one's self-generated torques is integral to sensorimotor control. Here, we examined how features of the motor control task, specifically the variability, duration, muscle activation pattern, and magnitude of torque generation, relate to one's perception of torque. Nineteen participants generated and perceived 25% of their maximum voluntary torque (MVT) in elbow flexion while simultaneously abducting at their shoulder to 10%, 30%, or 50% of their MVT in shoulder abduction (MVT<inline-formula><tex-math notation="LaTeX">$_{\text{SABD}}$</tex-math></inline-formula>). Subsequently, participants matched the elbow torque without feedback and without activating their shoulder. The shoulder abduction magnitude affected the time to stabilize the elbow torque (p<inline-formula><tex-math notation="LaTeX">$\ <$</tex-math></inline-formula>0.001), but did not significantly impact the variability of generating the elbow torque (p <inline-formula><tex-math notation="LaTeX">$=$</tex-math></inline-formula> 0.120) or the co-contraction between the elbow flexor and extensor muscles (p <inline-formula><tex-math notation="LaTeX">$=$</tex-math></inline-formula> 0.265). The shoulder abduction magnitude influenced perception (p <inline-formula><tex-math notation="LaTeX">$=$</tex-math></inline-formula> 0.001) in that the error in matching the elbow torque increased with an increased shoulder abduction torque. However, the torque matching errors neither correlated with the time to stabilize and variability in generating the elbow torque, nor the co-contraction of the elbow muscles. These findings suggest that the total torque generated during a multi-joint task impacts the perception of a torque about a single joint; yet, effective and efficient generation of the torque about a single joint does not impact the torque percept.
Estimation of genetic parameters for pork belly traits

Objective Pork belly is a cut of meat with high worldwide demand. However, although the belly is comprised of multiple muscles and fat, unlike the loin muscle, research on their genetic parameters has yet to focus on a representative cut. To use swine breeding, it is necessary to estimate heritability against pork belly traits. Moreover, estimating genetic correlations is needed to identify genetic relationship among the traditional carcass and meat quality traits. This study sought to estimate the heritability of the carcass, belly, and their component traits, as well as the genetic correlations among them, to confirm whether these traits can be improved. Methods A total of 543 Yorkshire pigs (406 castrated males and 137 females) from 49 sires and 244 dam were used in this study. To estimate genetic parameters, a total of 12 traits such as lean meat production ability, meat quality and pork belly traits were chosen. The heritabilities were estimated by using genome-wide efficient mixed model association software. The statistical model was selected so that farm, carcass weight, sex, and slaughter season were fixed effects. In addition, its genetic parameters were calculated via MTG2 software. Results The heritability estimates for the 7th belly slice along the whole plate and its components were low to moderate (0.07±0.07 to 0.33±0.07). Moreover, the genetic correlations among the carcass and belly traits were moderate to high (0.28±0.20 to 0.99±0.31). Particularly, the rectus abdominis muscle exhibited a high absolute genetic correlation with the belly and meat quality (0.73±52 to 0.93±0.43). Conclusion A moderate to high correlation coefficient was obtained based on the genetic parameters. The belly could be genetically improved to contain a larger proportion of muscle regardless of lean meat production ability.
Hepatoprotective Effect of Kaempferol: A Review of the Dietary Sources, Bioavailability, Mechanisms of Action, and Safety

The liver is the body's most critical organ that performs vital functions. Hepatic disorders can affect the physiological and biochemical functions of the body. Hepatic disorder is a condition that describes the damage to cells, tissues, structures, and functions of the liver, which can cause fibrosis and ultimately result in cirrhosis. These diseases include hepatitis, ALD, NAFLD, liver fibrosis, liver cirrhosis, hepatic failure, and HCC. Hepatic diseases are caused by cell membrane rupture, immune response, altered drug metabolism, accumulation of reactive oxygen species, lipid peroxidation, and cell death. Despite the breakthrough in modern medicine, there is no drug that is effective in stimulating the liver function, offering complete protection, and aiding liver cell regeneration. Furthermore, some drugs can create adverse side effects, and natural medicines are carefully selected as new therapeutic strategies for managing liver disease. Kaempferol is a polyphenol contained in many vegetables, fruits, and herbal remedies. We use it to manage various diseases such as diabetes, cardiovascular disorders, and cancers. Kaempferol is a potent antioxidant and has anti-inflammatory effects, which therefore possesses hepatoprotective properties. The previous research has studied the hepatoprotective effect of kaempferol in various hepatotoxicity protocols, including acetaminophen (APAP)-induced hepatotoxicity, ALD, NAFLD, CCl4, HCC, and lipopolysaccharide (LPS)-induced acute liver injury. Therefore, this report aims to provide a recent brief overview of the literature concerning the hepatoprotective effect of kaempferol and its possible molecular mechanism of action. It also provides the most recent literature on kaempferol's chemical structure, natural source, bioavailability, and safety.
A Personalized and Adaptive Insulin Bolus Calculator Based on Double Deep Q- Learning to Improve Type 1 Diabetes Management

Mealtime insulin dosing is a major challenge for people living with type 1 diabetes (T1D). This task is typically performed using a standard formula that, despite containing some patient-specific parameters, often leads to sub-optimal glucose control due to lack of personalization and adaptation. To overcome the previous limitations here we propose an individualized and adaptive mealtime insulin bolus calculator based on double deep Q-learning (DDQ), which is tailored to the patient thanks to a personalization procedure relying on a two-step learning framework. The DDQ-learning bolus calculator was developed and tested using the UVA/Padova T1D simulator modified to reliably mimic real-world scenarios by introducing multiple variability sources impacting glucose metabolism and technology. The learning phase included a long-term training of eight sub-population models, one for each representative subject, selected thanks to a clustering procedure applied to the training set. Then, for each subject of the testing set, a personalization procedure was performed, by initializing the models based on the cluster to which the patient belongs. We evaluated the effectiveness of the proposed bolus calculator on a 60-day simulation, using several metrics representing the goodness of glycemic control, and comparing the results with the standard guidelines for mealtime insulin dosing. The proposed method improved the time in target range from 68.35% to 70.08% and significantly reduced the time in hypoglycemia (from 8.78% to 4.17%). The overall glycemic risk index decreased from 8.2 to 7.3, indicating the benefit of our method when applied for insulin dosing compared to standard guidelines.
A Hybrid Meta-Heuristic Approach for Optimal Meter Allocation in Electric Power Distribution Systems

The number of nodes present in Electric Power Distribution Systems (EPDS) is a complicating factor for carrying out the State Estimation (SE) and the choice of allocation of available meters affects the quality of observability obtained by the SE. Thus, it is necessary to use optimization methods that evaluate the positions of meters in the system that can contribute to an optimal SE. Artificial Neural Networks (ANN) can perform SE, processing the information obtained by the available meters in an agile way. Meta-heuristics techniques apply to the optimal allocation problem but can be slow processing. Thus, the work seeks to evaluate the potential of a hybrid method that associates the meta-heuristic technique, Artificial Immune System (AIS), with ANNs for evaluating several allocation options in an agile way to find an optimal solution for the allocation of meters.
An application of SAW to a tactile display in virtual reality

SAW has great potential for a 'tactile display' in virtual reality which provides a human virtually with varied tactile sensation of roughness, textures, and friction. From an analysis of a sliding motion of a finger on a rough surface, it is shown that the parameters of the grain are directly related to a frequency of a stick-slip vibration of friction. Thus, it is necessary for the tactile display to create dispersed sources of shear stress which can be modulated temporally with the stick-slip frequency. In our tactile display, we explore a LiNbO/sub 3/ 128/spl deg/ Y-cut substrate with a 'slider' which has around 100 steel balls with the diameter of 800[/spl mu/m] on a thin tape. Because friction between the substrate and the slider is reduced by generating SAW on the substrate, a virtual stick-slip can be created by a burst standing SAW with the carrier frequency of 15[MHz]. It is confirmed that the variable grain can be represented by controlling the burst frequency of SAW.
Anticancer Therapeutic Effects of Green Tea Catechins (GTCs) When Integrated with Antioxidant Natural Components

After decades of research and development concerning cancer treatment, cancer is still at large and very much a threat to the global human population. Cancer remedies have been sought from all possible directions, including chemicals, irradiation, nanomaterials, natural compounds, and the like. In this current review, we surveyed the milestones achieved by green tea catechins and what has been accomplished in cancer therapy. Specifically, we have assessed the synergistic anticarcinogenic effects when green tea catechins (GTCs) are combined with other antioxidant-rich natural compounds. Living in an age of inadequacies, combinatorial approaches are gaining momentum, and GTCs have progressed much, yet there are insufficiencies that can be improvised when combined with natural antioxidant compounds. This review highlights that there are not many reports in this specific area and encourages and recommends research attention in this direction. The antioxidant/prooxidant mechanisms of GTCs have also been highlighted. The current scenario and the future of such combinatorial approaches have been addressed, and the lacunae in this aspect have been discussed.
MicroRNA Profiles in Intestinal Epithelial Cells in a Mouse Model of Sepsis

Sepsis is a systemic inflammatory disorder that leads to the dysfunction of multiple organs. In the intestine, the deregulation of the epithelial barrier contributes to the development of sepsis by triggering continuous exposure to harmful factors. However, sepsis-induced epigenetic changes in gene-regulation networks within intestinal epithelial cells (IECs) remain unexplored. In this study, we analyzed the expression profile of microRNAs (miRNAs) in IECs isolated from a mouse model of sepsis generated via cecal slurry injection. Among 239 miRNAs, 14 miRNAs were upregulated, and 9 miRNAs were downregulated in the IECs by sepsis. Upregulated miRNAs in IECs from septic mice, particularly miR-149-5p, miR-466q, miR-495, and miR-511-3p, were seen to exhibit complex and global effects on gene regulation networks. Interestingly, miR-511-3p has emerged as a diagnostic marker in this sepsis model due to its increase in blood in addition to IECs. As expected, mRNAs in the IECs were remarkably altered by sepsis; specifically, 2248 mRNAs were decreased, while 612 mRNAs were increased. This quantitative bias may be possibly derived, at least partly, from the direct effects of the sepsis-increased miRNAs on the comprehensive expression of mRNAs. Thus, current in silico data indicate that there are dynamic regulatory responses of miRNAs to sepsis in IECs. In addition, the miRNAs that were increased with sepsis had enriched downstream pathways including Wnt signaling, which is associated with wound healing, and FGF/FGFR signaling, which has been linked to chronic inflammation and fibrosis. These modifications in miRNA networks in IECs may lead to both pro- and anti-inflammatory effects in sepsis. The four miRNAs discovered above were shown to putatively target LOX, PTCH1, COL22A1, FOXO1, or HMGA2, via in silico analysis, which were associated with Wnt or inflammatory pathways and selected for further study. The expressions of these target genes were downregulated in sepsis IECs, possibly through posttranscriptional modifications of these miRNAs. Taken together, our study suggests that IECs display a distinctive miRNA profile which is capable of comprehensively and functionally reshaping the IEC-specific mRNA landscape in a sepsis model.
Physics-/Model-Based and Data-Driven Methods for Low-Dose Computed Tomography: A survey

Since 2016, deep learning (DL) has advanced tomographic imaging with remarkable successes, especially in low-dose computed tomography (LDCT) imaging. Despite being driven by big data, the LDCT denoising and pure end-to-end reconstruction networks often suffer from the black-box nature and major issues, such as instabilities, which are major barriers to applying DL methods in LDCT applications. An emerging trend is to integrate imaging physics and models into deep networks, enabling a hybridization of physics-/model-based and data-driven elements. In this article, we systematically review the physics-/model-based data-driven methods for LDCT, summarize the loss functions and training strategies, evaluate the performance of different methods, and discuss relevant issues and future directions.