Miracle-dz/UniFAR-FTUs huggingface dataset:
Drug Delivery Strategies for Poorly Water-Soluble Silymarin

Silymarin, a mixture of flavonolignan and flavonoid polyphenolic compounds extractable from milk thistle (Silybum marianum) seeds, is gaining an increasingly widespread clinical consensus as a natural remedy in the treatment of numerous chronic liver diseases such as cirrhosis and hepatocellular carcinoma due to its antioxidant, anti-inflammatory, anticancer and antiviral activities. Silymarin is able also to increase the stability of cell membrane, is active in the regeneration of tissues and prevents cardiac diseases through numerous mechanisms that include the action of chelating promoters of metals and scavenging free radicals. Equally promising are the effects of silymarin in protecting the brain from the inflammatory and oxidative stress effects by which metabolic syndrome contributes to neurodegenerative diseases. However, although clinical trials have proved that silymarin is safe at high doses (>1500 mg/day) in humans, it suffers limiting factors such as low solubility in water (<50 μg/mL) and low bioavailability. Furthermore, despite its poor solubility in water, silymarin does not retain lipophilic properties and this leads to poor intestinal permeability and rapid excretion in bile and urine. To potentiate the therapeutic action and promote sustained release of silymarin, numerous strategies have been proposed to tackle the low solubility in water and provide a prolonged drug release at the site of absorption. The purpose of this study is to review the different types of microand nanocarriers available in literature as delivery strategies to improve the intestinal absorption and bioavailability of silymarin.
Resource Allocation and 3-D Placement for UAV-Enabled Energy-Efficient IoT Communications

As the commercial launch of the fifth-generation (5G) wireless communications gets near, the trend from the Internet of Things (IoT) to the Internet of Everything (IoE) is emerging. Due to the advantages of the high mobility, high Line-of-Sight (LoS) probability and low labor cost, unmanned aerial vehicles (UAVs) may play an important role in the future IoT communication networks, e.g., data collection in remote areas. In this article, we study the 3-D placement and resource allocation of multiple UAV-mounted base stations (BSs) in an uplink IoT network, where the balanced task for the UAV-BSs, the limited channel resource, and the signal interference are taken into consideration. In the considered system, the total transmission power of IoT devices is minimized, subject to a signal-to-interference-and-noise ratio (SINR) threshold for each device. First, aiming to balance the task of each UAV, we propose a clustering algorithm based on an improved $K$ -means method to divide IoT devices into several groups so that the number of devices in each group is roughly the same. Then, based on matching theory, a modified-Hungarian-based dynamic many–many matching (HD4M) algorithm is designed for assigning subchannels to IoT devices, which can efficiently mitigate the interference. Finally, we jointly optimize the transmission power of IoT devices and the altitudes of UAVs via an alternating iterative method. The simulation results show that the total transmission power decreases significantly after applying the proposed algorithms.
PolSAR Ship Detection Based on Neighborhood Polarimetric Covariance Matrix

The detection of small ships in polarimetric synthetic aperture radar (PolSAR) images is still a topic for further investigation. Recently, patch detection techniques, such as superpixel-level detection, have stimulated wide interest because they can use the information contained in similarities among neighboring pixels. In this article, we propose a novel neighborhood polarimetric covariance matrix (NPCM) to detect the small ships in PolSAR images, leading to a significant improvement in the separability between ship targets and sea clutter. The NPCM utilizes the spatial correlation between neighborhood pixels and maps the representation for a given pixel into a high-dimensional covariance matrix by embedding spatial and polarization information. Using the NPCM formalism, we apply a standard whitening filter, similar to the polarimetric whitening filter (PWF). We show how the inclusion of neighborhood information improves the performance compared with the traditional polarimetric covariance matrix. However, this is at the expense of a higher computation cost. The theory is validated via the simulated and measured data under different sea states and using different radar platforms.
Cafeteria Perspectives of a Southern Farm to School Program: Happy Harvests and Room for New Growth.

According to National Health and Nutrition Examination Survey data from 2007-2010, 60% of children aged 1–18 years did not meet fruit intake recommendations, and 93% did not meet vegetable recommendations (Kim et al., 2014). However, school-based programming can provide opportunities for fruit and vegetable (FV) exposure and consumption (Glickman, Parker, Sim, Del Valle Cook, & Miller, 2012; Korinek, Bartholomew, Jowers, & Latimer, 2015). Farm to School programs are designed to improve FV offerings, and increase local connections by providing programs, staff training, technical assistance, and research (United States Department of Agriculture [USDA] Food and Nutrition Service [FNS], 2018).
Effects of Transcranial Direct Current Stimulation on Gait and Balance Post-Stroke

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A comparative analysis of Listeria monocytogenes plasmids: Presence, contribution to stress and conservation

Listeria monocytogenes is a food-borne pathogen responsible for the disease listeriosis and is commonly isolated from food products and production facilities. Some of these isolates are known to contain plasmids, though previous plasmid studies were conducted with a limited data set of 14 sequenced strains. To determine the presence of plasmids in a variety of L. monocytogenes strains and from various sequence types (ST), a large-scale analysis of 1924 L. monocytogenes genome sequences was conducted to determine the presence of plasmids in different STs, years, countries, and isolation sources. On average, 53% of all L. monocytogenes strains, and up to 92% of the strains within a ST (i.e. ST121), analyzed contained a plasmid. These plasmids ranged in size between 3 kb to 140 kb, with the majority being around 58 kb (± 1kb) and the other around 77 kb (± 1 kb). Plasmid conservation was a minimum of 91.9% nucleotide identity across all plasmids among all STs and the average similarity was 92.3% similarity. Examination of six previously identified plasmid-encoded stress-related genes indicated the genes present in L. monocytogenes plasmids are highly conserved, but their presence in plasmids is highly variable. Analysis of the dataset also identified a novel mercury-resistance operon containing seven genes involved in increasing tolerance in the presence of mercury. Understanding that plasmids often play a role in stress survival, it was necessary to determine the contribution of L. monocytogenes plasmids to stress tolerance when under such conditions. For this aim, we studied three isogenic pairs of L. monocytogenes ST5, ST8, and ST121 strains, isolated from dairy foods and production facilities, and that either contained or were cured of plasmids harboring putative stress
Customer Value Co-Creation Behavior of Higher Education in South Sumatera

This research was conducted in several higher education institutions in South Sumatra, the research questionnaire was distributed as many as 347 respondents and the results showed all hypotheses were positively correlated and accepted, except the influence of subjective norms on customer value co creation behavior there is a negative effect. Based on the results of this study indicate that the services provided at tertiary education must be better and focus on respondent satisfaction, tertiary education must also formulate to improve the brand image of tertiary education through good service. Higher education must be able to create a good academic culture, so that information from word of mouth can be carried out properly. Following the brand experiences, they should formulate branding strategies enabling the customer attitude and behavior. The research contributes to the value of co-creation by considering several variables which influence customer behavior such as brand awareness, perceived quality and also analyze multiple aspects of brand experience and its impact on customer attitude and behavior
A Self-Matching Complementary-Reference Sensing Scheme for High-Speed and Reliable Toggle Spin Torque MRAM

While spintronic memories, for example, spin transfer torque magnetic random access memory (STT-MRAM), have shown huge potential for building next-generation memory due to their attractive characteristics, the relatively large write latency and deficient read mechanism preclude their further application for emerging concepts, such as in-memory-processing and neuromorphic computing. A toggle spin torque (TST) MRAM combining STT and spin orbit torque (SOT) has recently been proposed to alleviate the write issue. However, the sensing featuring a good balance between the reliability and speed has not been addressed. In this paper, we propose a self-matching complementary-reference (SMCR) sensing scheme, which provides not only a maximum sensing margin (SM) but also a high-speed read operation. Through applying it in the TST-MRAM, advantageous performance in terms of both write and read processes can be realized. To validate the functionality of our proposal, we design and evaluate an 8Kb TST-MRAM array, in which a read delay of 1 ns and a read bit error rate (BER) of $1.02\times 10^{-13}$ are achieved. Moreover, when being operated at 0.8 V supply voltage, it can reduce the read access energy by 7.5% and 20%, compared with conventional voltage sensing and dynamic reference sensing schemes, respectively.
Overviewing of weed management practices to reduce weed seed bank and to increase maize yield

Background: Weeds are unwanted and undesirable plants which deteriorate the quality of agricultural products and interfere with farming activities. Most of the weeds (indigenous and invasive) seeds get preserved in soil horizons as weed seed bank which ensure their survival leading to the spoilage of quantitative and qualitative functioning of agricultural farms. Objective: To keep weeds below threshold level, elimination of weeds seed before germination can be a viable and pro-ecological approach. To achieve this objective, weed seeds reserved in the soil which serve as an effective pool to ensure their survival necessitate weed-seed bank management. Thus the ultimate goal was to synthesize and analyze research findings on weed seed bank management leading to formulating the most effective strategy encompassing viable control of weeds in maize. Methods: This study reviewed and analyzed the characteristics which impart botanical superiority to weeds and impact of all prevalent weed control strategies on weed seed bank, weeds density and maize yield. The research findings pertaining to different agronomic practices and technological packages were critically analyzed to sort out the most effective and eco-friendly approach to control weed-seed bank and weeds density in maize crop. Results: The synthesis and critical evaluation of research findings pertaining to weed control methods revealed that manual and mechanical methods were eco-friendly but involved expensive labor, while the chemical approach involving the use of herbicides led to serious deterioration of agro-environmental resources. Two or more techniques used in coherence which encompassed deep tillage to burry weeds seed and prevented their germination through mulches of biotic and synthetic materials along with optimizing sowing method especially raised bed technique reduced weed seed bank and weeds density in maize. SBCPD | Planta Daninha Maqsood Q, et al. Weed-seed bank management in maize Planta Daninha 2020;38:e020199716 https://doi.org/10.1590/S0100-83582020380100075 2/10 Conclusions: It is inferred that integrated approach entailing cultural, manual, mechanical and chemical control can be developed as a proenvironmental and farmer friendly approach for weed control by reducing weed seed reserves which can potentially lead to higher economic returns through higher maize yield.
Comparison of Bishop score and cervical length measurement through transvaginal ultrasound as prediction against labor induction

Objective: To compare the Bishop score and cervical length measured by transvaginal ultrasound concerned with prediction over the success of labor induction. Methods: This cross-sectional observational analytical study was conducted from May 2017 to October 2017 at several teaching hospitals of Obstetrics and Gynecology Department, Faculty of Medicine Hasanuddin University of Makassar, India. There were 110 samples of pregnant women undergoing labor induction process including 79 samples of successful induction and 31 samples of induction failure. The data analysis used Pearson Chi-square test and multivariate logistic regression to see the effect of Bishop score and measurement of cervical length with successful induction of labor. Results: Number of samples with successful labor induction with Bishop score ⩾3 was 25 (31.6%) and Bishop score was 54 (68.4%), with rate ratio=3.714 and P=0.000. With measurement of cervical length (cut-off point 2.98 cm), number of samples with successful labor induction with cervical length ⩽2.98 cm was 12 (15.2%) and cervical length >2.98 cm was 67 (84.8%), with rate ratio=3.124 and P=0.000. Multivahate analysis of logistic regression was found to be more influential in the predicted success of labor induction (P=0.014 with Bishop score <3, odds ratio=1.000 and Bishop score ⩾3, odds ratio=3.779. Conclusions: Bishop score is better in predicting the success of labor induction compared to the measurement of cervical length through transvaginal ultrasound.
Unsupervised Detection of Non-Technical Losses via Recursive Transform Learning

This letter addresses the problem of detecting non-technical losses in an unsupervised fashion. Most prior studies in this area proposed supervised means (assumed the losses to be labeled); getting supervised data for such a problem seems impractical. For a practical scenario, non-technical losses should be detected in an unsupervised fashion. This work proposes a new dynamical model called recursive transform learning for online unsupervised detection of non-technical losses. Results show that our proposed method is better or at par compared to the state-of-the-art.
Emotional Impact for Predicting Student Performance in Intelligent Tutoring Systems (ITS)

Current Intelligent Tutoring Systems (ITS) provide better recommendations for students to improve their learning. These recommendations mainly involve students’ performance prediction, which remains problematic for ITS, despite the significant improvements made by prediction methods such as Matrix Factorization (MF). The present contribution therefore aims to provide a solution to this prediction problem by proposing an approach that combines Multiple Linear Regression (Modelling Emotional Impact) and a Weighted Multi-Relational Matrix Factorization model to take advantage of both student cognitive and emotional faculties. This approach takes into account not only the relationships that exist between students, tasks and skills, but also students’ emotions. Experimental results on a set of pedagogical data collected from 250 students show that our approach significantly improves the results of Student Performance Prediction.
EFFECTS OF EMITTER SPACING AND IRRIGATION RATE ON THE YIELD, QUALITY AND ENERGY REQUIREMENTS OF DRIP-IRRIGATED TOMATOES (SOLANUM LYCOPERSICUM L.)

An experiment with a randomised split plot design was performed to assess the yield, irrigation water use efficiency, energy requirements and quality of tomatoes (Lycopersicon esculentum cv. BT236 F1) grown with drip irrigation on the Alpu Plain in north-western Central Anatolia, Turkey. During a trial period involving three replications from 2009 to 2011, a Class A pan was used to measure the daily evaporation values of treatments in split plots with different emitter spacing (25 cm and 50 cm) and irrigation rates (20%, 30%, 40% and 50% of the evaporation rate of the Class A pan). Among the results, annual evaporation during the trial period ranged from 550.9 mm to 721.4 mm, and whereas higher irrigation rates afforded higher yields, lower ones afforded higher irrigation water use efficiency (IWUE). The average weight, vitamin C content, total soluble solid (TSS) content and pH values for tomatoes, all used in the proposed irrigation ratio, were 149 g, 99.18 mg kg, 6.21% and 4.17, respectively. The energy requirement of irrigation water for diesel and electric consumption changed from 42 to 105 L and 140.6 and 351.4 kWh/ha, on average, respectively.
The Link between Board Structure, Audit, and Performance for Corporate Sustainability

The economic and social transformations, the bankruptcies recorded, and the financial crisis affecting all economies have increased the interest for the corporate governance concept. Our intention in this paper was to study the impact of corporate governance attributes on performance given the information published by the entities listed on five stock exchanges from Europe, namely the main market from Bucharest Stock Exchange (BSE) in Romania, the Athens Stock Exchange(ATHEX) main market in Greece, Financial Times Stock Exchange 100 Index (FTSE 100) from Great Britain, Spanish Stock Exchange 35 Index (IBEX 35) from Spain, and Warsaw Stock Exchange 20 Index (WIG 20) from Poland, between 2016–2018. Through mathematical modeling and multiple linear regression, we aimed to determine the extent to which corporate governance characteristics, firm characteristics, industry and stock market fixed effects, and random effects influence the performance of 226 entities included in our sample. The empirical findings revealed that CEO duality, the number of non-executive directors and women on board, audit committee, and audit opinion influenced performance measured by the Return on Assets (ROA) and Return on Equity (ROE) indicators. The ideas highlighted and the results obtained in this research contribute to the literature that analyzes the extent to which an effective governance determines the increase in performance, needed for a sustainable development.
Towards A Module-based Product Platform For Ship Locks Using DSM Methods

A significant number of ship locks in the Netherlands are due for renovation during the coming decades. To achieve this, Rijkswaterstaat (RWS), the executive branch of the Dutch Ministry of Infrastructure and Water Management, is investigating the options to meet the specific requirements, while allowing the necessary variety in the configuration of locks. This paper presents a method for the development of a module-based product platform for locks, based on component types and their combinations. By combining different design structure matrix (DSM) modeling methods, possible modules of lock components are defined and assessed. These modules consist of lock components that have a high level of commonality and thus influence each other. Together, these modules form the basis for a product platform for locks, supporting RWS with the renovation of their portfolio.
Analysis of Temporal and Structural Characteristics of Jovian Radio Emissions for Passive Radar Sounding of Jupiter’s Icy Moons

Recent studies have proposed that Jovian decametric radiation (DAM) can be effectively exploited for probing the subsurface of Jupiter’s icy moons by using passive radio sounding. However, these studies were based on the assumption that Jovian noise is white and stationary. Therefore, additional investigations into the temporal stability, predictability, and spectral properties of Jovian noise are required to fully assess the potential of passive radar sounding and improve the acquisitions planning. In this article, we investigate these properties of the Jovian DAM to understand their impact on radar sounding performance. This is done by analyzing the recently available radio spectra acquired by the JUNO Waves instrument. Results are also evaluated for the specific case of the Radar for Icy Moon Exploration (RIME) and the Radar for Europa Assessment and Sounding: Ocean to Near-surface (REASON) that have been selected for European Space Agency (ESA) and NASA missions to Ganymede and Europa. Our results show that the Jovian DAM is not perfectly white, but no severe distortions in the range response should be expected. The results on spatiotemporal occurrence show that Jupiter’s DAM has a variable probability of occurrence, which is rather sporadic for some frequency ranges. The results on RIME and REASON flybys show that the Jovian DAM occurrence probability is relatively low for selected sub-Jovian flybys at Europa. For the RIME Ganymede orbital phase, a large number of high occurrence passive acquisition opportunities are expected. The experimental results also show that a large bandwidth receiver would enhance the chance of recording Jovian noise.
A VHDL-Based Modeling Approach for Rapid Functional Simulation and Verification of Adiabatic Circuits

Adiabatic logic is an energy-efficient technique, however, the time required in the design, validation, and debugging increases manifold for large-scale adiabatic system designs. In this endeavor, we present a hardware description language (HDL)-based modeling approach for 4-phase adiabatic logic design. The paper highlights the drawbacks of the existing approaches and proposes a new approach that captures the timing errors and detects the circuit’s invalid operation due to mutually exclusive inputs being violated. We develop a model library containing the function of the four periods used in the trapezoidal power-clock and the adiabatic logic gates. The validation and verification of the proposed approach were done on the ISO-14443 standard benchmark circuit, a 16-bit cyclic redundancy check (CRC) circuit. The system modeled using HDL shows the timing agreement with the transistor-level SPICE simulations. The novel use of the four periods of a power-clock improves the robustness and reliability for the design and verification of large adiabatic systems.
Effect of water stress at different phenological stages of muskmelon (Cucumis melo L)

Field experiments were carried out at Faculty of Agriculture and Natural Resource Management, Ebonyi State University, Abakaliki in 2011 and 2012 dry seasons to study the effect of water stress at different phenological stages of muskmelon. Results revealed that watering intervals of every six days significantly influenced number of leaves, number of branches and days to 50% flowering.During flowering phase, the plots that were watered in every six and nine days flowered late while early flowering were recorded by plots that were watered once a day and every three days. The higest yield of muskmelon was observed in irrigation intervals of six days.Also watering frequency of six days intervals had maximum net income, closely followed by nine days intervals. It can be inferred that watering frequency of every six days intervals significantly affected both growth and yield characters of the crop studied at different phenological stages and it could be recommended for growing the crop in the study area.