Miracle-dz/UniFAR-FTUs huggingface dataset:
Intranasal Cerium Oxide Nanoparticles Ameliorate Cognitive Function in Rats with Alzheimer’s via Anti-Oxidative Pathway

Cerium oxide nanoparticles (CNPs), owing to their antioxidant property, have recently emerged as therapeutic candidate for Alzheimer’s disease (AD). However, intravenous CNPs are limited due to their poor physicochemical properties, rapid blood clearance and poor blood–brain penetration. Thus, we developed intranasal CNPs and evaluated its potential in experimental AD. CNPs were synthesized using homogenous precipitation method and optimized through Box–Behnken Design. The formation of CNPs was confirmed by UV spectroscopy and FTIR. The optimized CNP were spherical, small (134.0 ± 3.35 nm), uniform (PDI, 0.158 ± 0.0019) and stable (ZP, −21.8 ± 4.94 mV). The presence of Ce in CNPs was confirmed by energy-dispersive X-ray analysis. Further, the X-ray diffraction spectra revealed that the CNPs were nano-crystalline. The DPPH assay showed that at concentration of 50 µg/mL, the percentage radical scavenging was 95.40 ± 0.006%. Results of the in vivo behavioral studies in the scopolamine-induced Alzheimer rat model showed that intranasal CNPs dose dependently reversed cognitive ability. At dose of 6 mg/kg the morris water maze results (escape latency, path length and dwell time) and passive avoidance results (retention latency) were significantly different from untreated group but not significantly different from positive control group (rivastigmine patch, 13.3 mg/24 h). Further, biochemical estimation showed that intranasal CNP upregulated the levels of SOD and GSH in brain. In conclusion, intranasal CNPs, through its antioxidant effect, could be a prospective therapeutics for the treatment of cognitive impairment in AD.
Effect of Ginger Powder on Production Performance, Antioxidant Status, Hematological Parameters, Digestibility, and Plasma Cholesterol Content in Broiler Chickens

Simple Summary Chicken meat is a popular food item all over the wrld. Improving the nutrition of broilers is important for producing high-quality broiler meat. The inclusion of natural effective ingredients, such as ginger, in the diet of broilers did not adversely affect the palatability of the diet, nor did it cause anemia in the broilers. Rather, ginger enhanced the oxidative status and growth rate of broiler chickens. Abstract The effect of dietary ginger powder on the production performance, digestibility, hematological parameters, antioxidant status, dietary oxidation stability, and plasma cholesterol content of broiler chickens was investigated. Ginger powder was included in the diet at 0, 5, 10, or 15 g/kg. Total antioxidant capacity and malondialdehyde in sera samples, superoxide dismutase activity, glutathione peroxidase, catalase, and malondialdehyde in liver samples, and the peroxide value and acid value of the stored diets were evaluated. The results showed that ginger inclusion significantly improved antioxidation indices in broiler sera and liver. Total body weight gain in ginger-supplemented birds was higher than that of control birds (p < 0.048). Supplementing the broiler chickens with ginger powder reduced total feed consumption (p < 0.031). White blood cell counts and the percentage of heterophils in the blood were increased in birds that received ginger supplementation (p < 0.001). The inclusion of ginger in the diet improved dry matter digestibility, crude protein utilization, crude fiber utilization, and ether extract utilization. In addition, blood cholesterol, triglyceride, and very low-density lipoprotein levels were decreased (p < 0.001), and high-density lipoprotein and levels were increased, following the inclusion of ginger in the diet (p < 0.001).
Multi-stage investigation of deep neural networks for COVID-19 B-line feature detection in simulated and in vivo ultrasound images

COVID-19 is a highly infectious disease with high morbidity and mortality, requiring tools to support rapid triage and risk stratification. In response, deep learning has demonstrated great potential to quicklyand autonomously detect COVID-19 features in lung ultrasound B-mode images. However, no previous work considers the application of these deep learning models to signal processing stages that occur prior to traditional ultrasound B-mode image formation. Considering the multiple signal processing stages required to achieve ultrasound B-mode images, our research objective is to investigate the most appropriate stage for our deep learning approach to COVID-19 B-line feature detection, starting with raw channel data received by an ultrasound transducer. Results demonstrate that for our given training and testing configuration, the maximum Dice similarity coefficient (DSC) was produced by B-mode images (DSC = 0.996) when compared with three alternative image formation stages that can serve as network inputs: (1) raw in-phase and quadrature (IQ) data before beamforming, (2) beamformed IQ data, (3) envelope detected IQ data. The best-performing simulation-trained network was tested on in vivo B-mode images of COVID-19 patients, ultimately achieving 76% accuracy to detect the same (82% of cases) or more (18% of cases) B-line features when compared to B-line feature detection by human observers interpreting B-mode images. Results are promising to proceed with future COVID-19 B-line feature detection using ultrasound B-mode images as the input to deep learning models.
Short‐Term Outcomes Following Left Atrial Appendage Closure in the Very Elderly: A Population‐Based Analysis

Background Data on percutaneous left atrial appendage closure (LAAC) outcomes in the very elderly with atrial fibrillation are limited. We aimed to investigate the clinical characteristics and short‐term outcomes of patients 80 years or older following percutaneous LAAC in a large nationwide database. Methods and Results Using the Nationwide Readmissions Database, we identified patients who underwent percutaneous LAAC between January 2016 and December 2018. Patients were categorized based on age (≥80 and <80 years old). The primary outcome was in‐hospital mortality. Secondary outcomes were in‐hospital end points including periprocedural complications, 30‐day outcomes, and all‐cause 30‐day readmissions. A propensity score–matched model (1:1) was used to adjust for baseline characteristics among the study groups. A total of 13 208 patients were included in this study (43% women, median age in years [interquartile range] 79.5 [73–84]) and matched one‐to‐one (6604 and 6604 patients were ≥80 and <80 years old, respectively). In‐hospital mortality was not statistically different between the study groups and occurred in 21 patients ≥80 years old (0.32%) and in 14 patients <80 years old (0.21%); P=0.236. Rates of in‐hospital stroke/transient ischemic attack were higher in patients ≥80 years old compared with those <80 years old (1.22% versus 0.77%; P=0.009). In‐hospital bleeding requiring transfusion, vascular complications, systemic embolization, and pericardial effusion/tamponade requiring pericardiocentesis or surgical intervention occurred more frequently in patients ≥80 years old. Furthermore, the elderly group was more likely to be readmitted within 30 days compared with those <80 years old (9.91% versus 8.4%; P=0.004); however, rates of 30‐day complications were not statistically different between the study groups. Conclusions In a large nationwide database, patients ≥80 years old undergoing percutaneous LAAC were found to have similar in‐hospital mortality but an increased risk of periprocedural complications and 30‐day readmission compared with younger patients. Our data suggest that LAAC should be considered on a case‐by‐case basis in the very elderly, taking into consideration the risks and benefits of this intervention. Further studies are needed to assess long‐term LAAC outcomes in this high‐risk population.
Contribution‐based Federated Learning client selection

Federated Learning (FL), as a privacy‐preserving machine learning paradigm, has been thrusted into the limelight. As a result of the physical bandwidth constraint, only a small number of clients are selected for each round of FL training. However, existing client selection solutions (e.g., the vanilla random selection) typically ignore the heterogeneous data value of the clients. In this paper, we propose the contribution‐based selection algorithm (Contribution‐Based Exponential‐weight algorithm for Exploration and Exploitation, CBE3), which dynamically updates the selection weights according to the impact of clients' data. As a novel component of CBE3, a scaling factor, which helps maintain a good balance between global model accuracy and convergence speed, is proposed to improve the algorithm's adaptability. Theoretically, we proved the regret bound of the proposed CBE3 algorithm, which demonstrates performance gaps between the CBE3 and the optimal choice. Empirically, extensive experiments conducted on Non‐Independent Identically Distributed data demonstrate the superior performance of CBE3—with up to 10% accuracy improvement compared with K‐Center and Greedy and up to 100% faster convergence compared with the Random algorithm.
Individualized and generalized learner models for predicting missed hepatic metastases

The diagnostic performance of radiologist readers exhibits substantial variation that cannot be explained by CT acquisition protocol differences. Studying reader detectability from CT images may help identify why certain types of lesions are missed by multiple or specific readers. Ten subspecialized abdominal radiologists marked all suspected metastases in a multi-reader-multi-case study of 102 deidentified contrast-enhanced CT liver scans at multiple radiation dose levels. A reference reader marked ground truth metastatic and benign lesions with the aid of histopathology or tumor progression on later scans. Multi-slice image patches and 3D radiomic features were extracted from the CT images. We trained deep convolutional neural networks (CNN) to predict whether an average (generalized) or individual radiologist reader would detect or miss a specific metastasis from an image patch containing it. The individualized CNN showed higher performance with an area under the receiver operating characteristic curve (AUC) of 0.82 compared to a generalized one (AUC = 0.78) in predicting reader-specific detectability. Random forests were used to build the respective versions from radiomic features. Both the individualized (AUC = 0.64) and generalized (AUC = 0.59) predictors from radiomic features showed limited ability to differentiate detected from missed lesions. This shows that CNN can identify and learn automated features that are better predictors of reader detectability of lesions than radiomic features. Individualized prediction of difficult lesions may allow targeted training of idiosyncratic weaknesses but requires substantial training data for each reader.
Distribution of astaxanthin in the spiny lobster Jasus lalandii: trends during biological cycles

ABSTRACT Astaxanthin, the dominant carotenoid pigment in the South African spiny lobster, Jasus lalandii, was quantified in haemolymph and tissue extracts by means of reverse phase-high pressure liquid chromatography and analysed with respect to growth and reproduction cycles of adults. Haemolymph, exoskeleton, muscle, gonads and hepatopancreas from both sexes, as well as egg parcels from berried females were collected within days of removing the animals from the ocean. The astaxanthin profile is, therefore, representative of spiny lobsters in the wild. Astaxanthin is significantly more in exoskeleton, ovaries and egg parcels, and is influenced by the ovarian cycle in females: it accumulated in growing oocytes and remained in the extruded eggs ostensibly for protection as antioxidant. Radioactive inulin was used to determine total haemolymph volume of a spiny lobster and the gravimetric contribution of body organs and various tissues to the total weight of these animals were measured: muscle tissue constitutes 33% of the total wet weight of J. lalandii, while haemolymph (22%) and exoskeleton (20%) are other major contributors. For maximal harvesting of astaxanthin from carcases, it would thus, be best to focus only on the exoskeleton with an emphasis on the carapace, which can be easily removed.
A Course Module on Application Logic Flaws

Software security is extremely important, and even thoroughly tested code may still have exploitable vulnerabilities. Some of these vulnerabilities are caused by logic flaws. Due to the nature of application or business logic, few automated tools can test for these types of security issues. Therefore, it is important for students to learn how to reduce the number of logic flaws when developing software, and how to test for them manually. A course module with a case study was created to teach students about this topic. Case-based teaching methods are used because it allows students to better apply learned skills to real world industrial settings, and there is a lack of case studies available for current software engineering curriculum. The course module includes an introduction, a quiz on the reading, an animated PowerPoint about the case, and a set of discussion questions. The introduction covers what logic flaws are, reducing logic flaws during software development, and how to test for them manually. The case is about eCommerce merchant software Bigcommerce using PayPal Express to collect payment. A flaw lets attackers complete an expensive order using the payment intended for a cheaper order. An animation was created to trace the HTTP interactions and back-end code representing the steps of the exploit from this case, and explain the manual testing method used to discover the exploit. A set of discussion questions has students apply this method to similar code, to find potential vulnerabilities and then fix them. This course module was taught in COMP 727 Secure Software Engineering at North Carolina A&T State University in the Spring 2015 semester. A pre-survey and post-survey on the learning objectives shows students felt they improved their knowledge and skills relating to application logic flaws. A quiz based on the reading shows students understood the material. The quality of student discussions was very high. Discussion question results were graded using a
“Get Two Degrees for the Price of One”: Career Orientations and Choices of Double-Degree Students

Double degrees have been identified in universities around the globe. The Colombian double degree is a local hybrid of the American double major and the local profession-enabling pregrado that universities, particularly elite private ones, marketize in a context of mass higher education, devaluation of first university degrees and a weak economy ensuing from social conflict. Through a narrative approach, we found that students learn to pursue two degrees to maximize their investment in education, seek future job security, reduce their angst about survival given the low value of university credentials, and gain recognition from peers and family members. Choosing two degrees also maximizes their opportunities for preparing themselves to serve others, allows them to pursue intellectual development, and to satisfy their curiosity. The main trend found is that of students led by a consumerist orientation privileged over an educational rationale. We argue that the superimposition of consumerist orientations over self-cultivation motives may occur in the context of implementation of new programs such as double degrees, implemented by universities under a market logic.
Improving correlation of wastewater SARS-CoV-2 gene copy numbers with COVID-19 public health cases using readily available biomarkers

Abstract The COVID-19 (coronavirus disease 2019) pandemic has highlighted the potential role that wastewater-based epidemiology can play in assessing aggregate community health. However, efforts to translate SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) gene copy numbers obtained from wastewater samples into meaningful community health indicators are nascent. In this study, SARS-CoV-2 nucleocapsid (N) genes (N1 and N2) were quantified weekly using reverse transcriptase droplet digital PCR from two municipal wastewater treatment plants for 6 months. Four biomarkers [ammonium, biological oxygen demand (BOD), creatinine and human mitochondrial gene NADH dehydrogenase subunit 5] were quantified and used to normalize SARS-CoV-2 gene copy numbers. These were correlated to daily new case data and 1-, 2- and 3-week cumulative case data. Over the course of the study, the strongest correlations were observed with a 1-day case data lag. However, early measurements were strongly correlated with a 5-day case data lag. This indicates that in the early stages of the pandemic, the wastewater samples may have indicated active COVID-19 cases before clinical indications. Mitochondrial and creatinine normalization methods showed the strongest correlations throughout the study, indicating that human-specific biomarkers were better at normalizing wastewater data than ammonium or BOD. Granger causality tests supported this observation and showed that gene copies in wastewater could be predictive of new cases in a sewershed.
Phase-field microstructure-based effective thermal conductivity calculations in tungsten

Using a phase-field approach with the heat conduction equation, we predict the grain growth behaviors in tungsten (W) and their effects on effective thermal conductivity. Results show that the simulated grain growth kinetics is basically consistent with experimental observations. An empirical correlation is derived, describing the averaged grain area as a function of temperature and time. Further, we study the effect of grain growth, columnar crystal structure, and recrystallization on the effective thermal conductivity of W. It is found that the effective thermal conductivity increases nonlinearly with increasing grain size, and a simple correlation of converting two-dimension into three-dimension effective thermal conductivity is obtained. Interestingly, the effective thermal conductivity of the columnar crystal is relatively high along the elongated direction and higher than that of the isometric crystal. Nevertheless, the effective thermal conductivity decreases with the occurrence of the recrystallization due to the increased grain boundary density. Our results reveal that grain growth and grain structure can affect the capacity of heat transfer at high temperatures, which could be considered in the transient event of the long-time service of W materials in fusion devices.
Investigating the influence of TQM, service quality and market orientation on customer satisfaction and loyalty in the Indian banking sector

Purpose The purpose of this paper is to examine the effect of total quality management (TQM) on service quality (SQ), market orientation (MO) and the subsequent effect on customer satisfaction (CS) and customer loyalty (CL). The research also analyses the direct effect of TQM on CS. Design/methodology/approach Data were collected from middle managers of retail banking sector in India using survey method. Structural equation modeling is used to analyze the data and to test the hypotheses. Findings The results show that TQM is positively associated with SQ, MO and CS. SQ and MO are significantly and positively associated with CS. CS subsequently leads to improved CL. Practical implications Enforcing TQM practices in their organizations as a change management tool, banks can achieve a greater degree of MO, improved SQ and higher CS to gain higher CL. Originality/value This paper empirically demonstrates that, by proper implementation of TQM in banks, the SQ and MO can be improved. Well implemented quality management practices, better customer service and market-focused attitude of banks will elevate the CS level and improve loyalty of customers toward the banks. With a little study has yet focused on India, the paper offers knowledge to banking professionals for increasing CL by effective implementation of TQM practices.
Effects of Harvesting Period on Phytochemicals of Wheatgrass (Triticum aestivum, WK 1204 Variety)

<p class="MsoNormal"><span style="color: black; mso-themecolor: text1;">Wheatgrass</span> is a plethora of essential phytochemicals considered to exhibit numerous benefits on human health. Therefore, the study of phytochemicals with varying stages of growth is essential. This study aims to determine the optimum harvesting period of wheatgrass based on its phytochemical content. During the growth of wheat seed (WK 1204 variety), the phytochemicals such as chlorophyll, total phenol content, flavonoids and tannins were extracted by 80% acetone and 80% methanol from wheatgrass harvested on days 6, 7, 8, 9 12 and 15, respectively. <span style="background: white;">2,2-diphenyl-1-picrylhydrazyl</span> (DPPH) radical scavenging activity, chlorophyll and flavonoid contents significantly (p<0.05) increased and reached the maximum level on day 9. Total phenol content was found to be increasing significantly (p<0.05), while the tannin content was decreasing considerably (p<0.05) on day 15. The optimum harvesting period was found <span style="mso-ansi-language: IN;" lang="IN">on</span> day 9. The DPPH radical scavenging activity, chlorophyll and flavonoid content significantly (p<0.05) increas<span style="mso-ansi-language: IN;" lang="IN">ed</span> and reached the maximum level, i.e., 92.27±1.92%, 6.63±0.053 mg g<sup><span style="mso-ansi-language: IN;" lang="IN">-1</span></sup> and 183.64±33.49 mg QE g<sup><span style="mso-ansi-language: IN;" lang="IN">-1</span></sup>, respectively, on day 9 of cultivation. The total phenol content was found to be increasing significantly (p<0.05) from 291.67±5.69 mg GAE g<sup><span style="mso-ansi-language: IN;" lang="IN">-1 </span></sup>on day 6 to 446.67±5.77 mg GAE g<sup><span style="mso-ansi-language: IN;" lang="IN">-1</span></sup> on day 15, while the tannin content was declining significantly (p<0.05) from 11.74±0.29 mg GAE g<sup><span style="mso-ansi-language: IN;" lang="IN">-1</span></sup> on days 6, 7 and so on to 3.36±0.47 mg GAE g<sup><span style="mso-ansi-language: IN;" lang="IN">-1</span></sup> on day 15. Therefore, the optimum harvesting period of wheatgrass was found to be day 9 in terms of phytochemical analysis. </p>
Mechanism of Antagonistic Bioagents in Controlling Root-Knot Nematodes (Meloidogyne sp.): A Review

Root-knot nematodes are among the most significant pathogenic organisms due to their global distribution, capacity for destruction, and economic importance. Antagonistic bioagents are more effective alternative to synthetic pesticides in the suppression of root-knot nematodes. Bioagents reduce the use of synthetic chemicals, which are hazardous to both humans and the environment. Despite this, some bioagents, such as fungi and bacteria have unknown mechanisms. This review discusses the nematophagous bacteria and fungi that have been discovered so far, including Pochonia, Trichoderma sp. , Pseudomonas sp. , and Bacillus sp. , with an overview of the current advances in research regarding their molecular and biochemical control mechanisms. Biological control agents (BCAs), as valuable ecological enemies of nematode infestations, use a range of mechanisms, such as parasitism, nutrient competition, toxin production, induce systemic resistance to antibiotics, enzymes, and enhance plant health. They suppress nematodes directly, improve plant growth, and facilitate the colonization and activities of antagonistic microbes in the rhizosphere. Understanding the molecular basis of BCAs suppression mechanisms provides the basis for their future incorporation into phytopathogen or plant disease control management. This study reviews the current threat posed by the root-knot nematode, biological control, antagonistic bioagents, and their mechanisms, and the future perspectives in modern agricultural sustainability to provide basis for the broad control of root-knot nematodes.