Miracle-dz/UniFAR-FTUs huggingface dataset:
Complexation between darunavir ethanolate and beta cyclodextrin: experimental and theoretical studies

Darunavir (DRV) is a protease inhibitor used in the treatment of HIV infection, which constitutes a keystone in the therapy of patients infected with this virus. Unfortunately, DRV has low solubility in water and poor bioavailability, therefore it requires administration in relatively high doses in order to exhibit therapeutic efficacy. A commonly applied approach to increase the solubility of drugs is the formation of complexes with macromolecules, of which molecular encapsulation with β-cyclodextrin (βCD) constitutes an alternative for the development of new pharmaceutical dosage forms. Therefore, it was to evaluate by theoretical (molecular modelling) and experimental (spectroscopic) approaches the possibility of obtaining an inclusion complex between DRV and βCD. From the results obtained by the docking procedures, we found three clusters of conformations for the DRV:β-CD complex, corresponding to conformations in which the ligand moieties were buried into the β-CD hydrophobic cavities. Molecular modelling results were compared with spectroscopic studies, with H NMR studies evidencing that DRV and βCD proton resonances were modified upon complexation, thus confirming the formation of the inclusion complex. The combination of theoretical and experimental techniques confirmed the formation of the inclusion complex between DRV and βCD. WORLD JOURNAL OF PHARMACY AND PHARMACEUTICAL SCIENCES SJIF Impact Factor 2.786 Volume 3, Issue 6, 298-309. Research Article ISSN 2278 – 4357 Article Received on 10 April 2014, Revised on 22 April 2014, Accepted on 20 May 2014 *Correspondence for Author Ana Carolina Kogawa Department of Drugs and Pharmaceutics, School of Pharmaceutical Sciences, Universidade Estadual Paulista “Júlio de Mesquita Filho” UNESP, Araraquara, São Paulo, Brazil
Physical Education in the COVID Era: Considerations for Online Program Delivery Using the Comprehensive School Physical Activity Program Framework

In the wake of COVID-19, online physical education (OLPE) has become essential to the sustainability of school physical education programs. The purpose of this article is to consider factors that may be influential in efforts to deliver OLPE to students. The comprehensive school physical activity program model is used to frame a multicomponent conceptualization of OLPE and its goals and outcomes. Central to this framing is the intersectionality of school physical education, the family, and the community. This article provides a platform for physical education teacher educators and researchers to advance OLPE in its support of both the educational and public health benefits of high-quality physical education programs.
End‐to‐End Multi‐Domain and Multi‐Step Jamming Prediction in Wireless Communications

In this letter, the problem of jamming data prediction in wireless communications is investigated. Both time and frequency domains are considered to construct the multi-domain historical jamming data tensor. Besides, due to the perceiver’s limited ability, false alarm data and missing detection data are considered. Two neural network prediction models are proposed to predict the jammers’ future actions based on deep learning techniques. One is the multi-variate long-short-term-memory (multi-variate LSTM) model, and the other is the 2-D convolutional long-short-term-memory model. Simulation results show that the proposed models have better prediction accuracy and robustness than the benchmark method.
Exploring Network Measures of Social Capital: Toward More Relational Measurement

Although social capital is a relational concept, existing studies have focused less on measuring social relations. This article fills the gap by reviewing recent studies that used network measures grouped into three types according to the measurement level. The first group defined social capital as an individual asset and used node-level measures to explain personal benefits. The second group defined social capital as a collective asset and used graph-level measures to describe collective properties. The third group used subgraph-level measures to explain the development of social capital. This article offers a link between the concepts and measures of social capital.
Treatment of Posterolateral Tibial Plateau Fractures With a Rotational Support Plate and Special Pressurizer: a Technical Note and 12 Cases 

Background: Posterolateral tibial plateau fractures are uncommon fractures and challenging to treat. Although there are many surgical approaches and fixation methods for the treatment of these fractures, all of these methods have limitations. We designed a new rotational support plate (RSP) and a special pressurizer that can fix the fracture directly via the anterolateral approach. This method is advantageous because it leads to little trauma, involves a simple operation and has a reliable fixation effect. This study details the technique of treating these fractures with the RSP and special pressurizer and provides the outcomes.Methods: From May 2016 to January 2019, the data of 12 patients with posterolateral tibial plateau fractures treated with the RSP and special pressurizer in our hospital were retrospectively analysed. Postoperative rehabilitation was advised, knee X-rays were taken at follow-ups, and fracture healing, complications, and knee range of motion were assessed. The Hospital for Special Surgery (HSS) knee score was used to evaluate knee function at the last follow-up.Results: The average follow-up time of all patients was 16.5 months (range, 12-25 months). The average bony union time was 3.2 months (range, 3-4.5 months). At the last follow-up, the average knee range of motion was 138° (range, 107°-145°). The average HSS score was 91 (range, 64-98). Skin necrosis, incision infections, and fixation failure did not occur during the follow-up period.Conclusions: With our newly designed RSP and special pressurizer, posterolateral tibial plateau fractures can be easily and effectively reduced and fixed through the anterolateral approach, which serves as a novel treatment for posterolateral tibial plateau fractures.
Crowding and Factor Returns

This paper documents that crowding by market participants affects the expected return to popular factor strategies such as value, momentum, and carry. Using data published by the CFTC for commodity futures markets, we construct a direct measure of factor strategy crowding that is based on the aggregate positioning of market participants. We show that this crowding measure has a strong negative predictive impact on expected factor strategy returns. Historical factor strategy returns are accumulated primarily during periods of low crowding. We link variation in our crowding measure to macroeconomic fundamentals and suggest that the reduction of factor strategy returns is related to variation in the cost of arbitrage capital.
Effects of Different Contents of Each Component on the Structural Stability and Mechanical Properties of Co-Cr-Fe-Ni High-Entropy Alloys

The structural stability of high-entropy alloys (HEAs) is closely related to their mechanical properties. The precise control of the component content is a key step toward understanding their structural stability and further determining their mechanical properties. In this study, first-principle calculations were performed to investigate the effects of different contents of each component on the structural stability and mechanical properties of Co-Cr-Fe-Ni HEAs based on the supercell model. Co-Cr-Fe-Ni HEAs were constructed based on a single face-centered cubic (FCC) solid solution. Elemental components have a clear effect on their structure and performance; the Cr and Fe elements have an obvious effect on the structural stability and equilibrium lattice constant, respectively. The Ni elements have an obvious effect on stiffness. The Pugh ratios indicate that Cr and Ni addition may increase ductility, whereas Co and Fe addition may decrease it. With increasing Co and Fe contents or decreasing Cr and Ni contents, the structural stability and stiffness of Co-Cr-Fe-Ni HEAs are improved. The structural stability and mechanical properties may be related to the strength of the metallic bonding and covalent bonding inside Co-Cr-Fe-Ni HEAs, which, in turn, is determined by the change in element content. Our results provide the underlying insights needed to guide the optimization of Co-Cr-Fe-Ni HEAs with excellent mechanical properties.
Missing the missing values: The ugly duckling of fairness in machine learning

Nowadays, there is an increasing concern in machine learning about the causes underlying unfair decision making, that is, algorithmic decisions discriminating some groups over others, especially with groups that are defined over protected attributes, such as gender, race and nationality. Missing values are one frequent manifestation of all these latent causes: protected groups are more reluctant to give information that could be used against them, sensitive information for some groups can be erased by human operators, or data acquisition may simply be less complete and systematic for minority groups. However, most recent techniques, libraries and experimental results dealing with fairness in machine learning have simply ignored missing data. In this paper, we present the first comprehensive analysis of the relation between missing values and algorithmic fairness for machine learning: (1) we analyse the sources of missing data and bias, mapping the common causes, (2) we find that rows containing missing values are usually fairer than the rest, which should discourage the consideration of missing values as the uncomfortable ugly data that different techniques and libraries for handling algorithmic bias get rid of at the first occasion, (3) we study the trade‐off between performance and fairness when the rows with missing values are used (either because the technique deals with them directly or by imputation methods), and (4) we show that the sensitivity of six different machine‐learning techniques to missing values is usually low, which reinforces the view that the rows with missing data contribute more to fairness through the other, nonmissing, attributes. We end the paper with a series of recommended procedures about what to do with missing data when aiming for fair decision making.
Non-UN Peacekeeping Effectiveness: Further Analysis

ABSTRACT This paper examines the effectiveness of non-UN-led peacekeeping operations (PKOs) from two alternative perspectives. First, the four kinds of regional and international (out of region) PKOs are investigated based on their ability to curtail one-sided violence (OSV) against civilians by host governments or rebels. That analysis is further bolstered by propensity-score matching to ameliorate potential selection bias stemming from non-UN PKOs. For the matched sample, we find that non-UN peacebuilding and peace enforcement missions limit rebel caused OSV, which is a novel result. Second, the ability of non-UN PKOs’ troops and police to end conflict or to maintain peace are ascertained based on survival analysis. Non-UN troops, but not police, curtail the transition from peace, regardless of matching. Generally, non-UN PKOs display effectiveness in limiting OSV or maintaining peace, but not in ending conflict.
Femtosecond Optical Trap-Assisted Nanopatterning through Microspheres by a Single Ti:Sapphire Oscillator

A new approach for fabricating a range of patterns using femtosecond optical trap-assisted nanopatterning is presented. We report how a single Gaussian laser beam from a 55 fs, 80 MHz, 780 nm Ti:sapphire oscillator trapping dielectric microspheres near surfaces can be used to enable near-field, direct-write, subwavelength ∼λ/6 (∼130 nm), two-dimensional nanopatterning of a polymer surface. We discuss the stability conditions for effective manipulation of the particle by the pulsed beam. Klein–Kramers and Brownian motion models were used to analyze the positional accuracy of femtosecond tweezers. We studied effects of the microsphere size, pulsed laser energy and light polarization, and spacing between objective focal plane and polymer surface on the pattern size experimentally and theoretically. Microspheres with a diameter of about 1 μm provide the smallest patterns. The experimental results are reasonably matched by generalized Lorentz–Mie theory.
Wearable Exercise Technology and the Impact on College Women’s Physical Activity

ABSTRACT Increased exercise correlates with positive health outcomes in college women. Many women do not get the recommended physical activity during college. The purpose of this study was to analyze whether regular use of wearable exercise technology (i.e., smartphones, dedicated devices) during exercise was associated with increased exercise behaviors. The theoretical framework was Transtheoretical Model of Behavior Change. The participants were 289 undergraduate students, all women. The research design was a survey method using an online platform. The survey questionnaire was administered to identify motivational readiness (from never to regularly) for exercise and exercise technology use. Descriptive and inferential statistics (analysis of variance and Chi-Square) were used in analyzing the data. Of the 289 women participants, 80 were identified as meeting exercise recommendations, and 27 were regular users (6 months or longer) of exercise technology; of these 27, 23 were also regular exercisers. Chi-square tests identified a strong association between the most motivated group for regular exercise and for regular device use, suggesting that women who regularly used an exercise technology device were significantly more likely to be regularly exercising (Χ 2 (4) = 9.41, p = 0.05. ).
A Comparative Study of Deep Learning Models for Network Intrusion Detection

With the advancement of digital technologies, cybersecurity is attracting more attention as cyber-attacks are becoming more frequent and threatening. A marked upturn has been noticed in the volume and creativity of hacks and cyberattacks. Artificial Intelligence (AI) and Deep Learning (DL) can help address these concerns by contributing to threat detection. They can recognize patterns in data, enabling security systems to learn from former experience. This paper concerns the comparative evaluation of the several techniques of deep learning employed for network intrusion detection.
Forecasting Abrupt Depletion of Dissolved Oxygen in Urban Streams Using Discontinuously Measured Hourly Time‐Series Data

Depletion of dissolved oxygen (DO) is a major cause of fish kills in urban streams. Although forecasting short‐term DO concentrations in streams prior to hypoxic events is necessary, such efforts have been rarely made. In this study, 24‐h forecasting models were developed for DO concentrations in three urban streams of South Korea. To forecast the DO concentrations at the outlet sites, which coincide with fish kill hot spot areas, water quality parameters at the lower reaches and hydrometeorological parameters were used as input variables. The monitoring data were measured hourly between 2017 and 2018 and divided into training and test sets at a ratio of 8:2. Tenfold cross validation was performed for hyperparameter optimization. Due to the dynamic characteristics of DO concentrations and the discontinuity in time‐series data, a long short‐term memory (LSTM) neural network modeling approach was selected. Overall, a high degree of accuracy was recorded for all study streams. Although hypoxic events were forecast with lower accuracy, the timing and magnitude of abrupt DO depletion were well captured. Water temperature and DO concentrations at the lower reaches and 24‐h cumulative precipitation were important variables for forecasting DO concentrations at all stream outlets. In particular, the importance of cumulative precipitation across all streams indicated that the effects of nonpoint sources were critical in depleting DO in urban streams. Monitoring of both lower reaches and outlets in conjunction with a variable importance analysis enhanced interpretability of the LSTM model outputs. This study improves our understanding of precursors of hypoxic events in urban streams.
A Study on the Inhibitory Potential of Dpp-Iv Enzyme by Lobeline through In silico and In vivo Approaches

Aims: To evaluate the inhibitory activity of Lobeline natural alkaloid against dipeptidyl peptidase IV (DPP IV) enzyme by in silico and in vivo experiments. Study Design: Evaluation of Antidiabetic Activity of Lobeline alkaloid. Place and Duration of Study: Department of Pharmaceutical Chemistry, Faculty of Pharmacy, Aleppo University, Aleppo, Syria, between March 2020 and December 2020. Methodology: in silico study was carried out using iGEM docking software to predict the binding affinity of lobeline with DPP IV enzyme in comparison with the reference synthetic compound Sitagliptin. Then in vivo experiment was performed on HFD/alloxan induced diabetic mice to evaluate the anti hyperglycemic effect of lobeline. After treatment duration of 21 days, FBG and the inhibitory effect on DPP IV enzyme activity were measured. Results: Lobeline bound efficiently to the active site of DPP IV enzyme and consumed less binding energy than Sitagliptin. This finding was confirmed by the in vivo study. Original Research Article Sabbagh et al.; IRJPAC, 22(1): 79-91, 2021; Article no.IRJPAC. 66476 80 Administration of lobe line at a dose of 25 mg/kg in HFD/alloxan induced diabetic mice produced a significant reduction in blood glucose level and in DPP IV activity compared to the diabetic control group (P value< .01). Conclusion: Lobe line could be a good candidate to be developed as a natural compound for treating diabetes mellitus.
Factors associated with cognitive failure among mothers involved in child care

Abstract Mothers involved in child care may be prone to various cognitive failures (e.g., leaving things behind) as a result of being overburdened with maternal duties, with limited attentional capacity for responding to children’s frequent demands. Therefore, this study aimed to explore factors associated with cognitive failure among mothers involved in child care in Japan. The participants were 310 mothers aged 25–45 (155 full-time workers, 155 housewives). The self-reported questionnaire covered cognitive failure (outcome variable), basic demographic characteristics, sociological factors, health status, and personality. Cognitive failure was assessed using the 15-item Japanese version of the Short Inventory of Minor Lapses. The variables evaluated for potential associations with cognitive failure included mother’s age, youngest child’s age, number of children, employment status, daily sleep duration, time spent on leisure activities, fatigue, social support (instrumental and emotional), use of child care services, and the Big Five personality traits (neuroticism, extraversion, openness, agreeableness, and conscientiousness). Multiple regression analysis showed that number of children, fatigue, emotional support, neuroticism, agreeableness, and conscientiousness were independently and significantly associated with cognitive failure. Our results may help facilitate the development of effective strategies to prevent adverse effects on children’s and parents’ health by preventing cognitive failure among mothers.
Acerola seed meal (Malpighia emarginata) as a source of dietary fibre in starter piglet diets

Three experiments were carried out to determine the nutritional value and the effect of acerola seed meal (ASM) for starter piglet diets on feed digestibility, nitrogen balance (NB), growth performance and blood metabolites. Twenty-four crossbred entire male piglets (21.07 ± 3.07 kg) were assigned to a digestibility assay (Exp. I) and distributed in a randomised block design (RBD) with two treatments composed of reference diet (RD) or test diet (20% replacement with ASM), 12 replications and with one pig per experimental unit (EU). An NB study (Exp. II) was conducted with four levels of ASM (0, 4, 8 and 12%) and 24 crossbred entire male piglets (20.78 ± 1.84 kg) allocated in an RBD of six replications and one pig per EU. The growth performance study (Exp. III) involved 120 crossbred piglets: 60 entire males and 60 females (13.85 ± 1.49 kg). Treatments consisted of a gender combination and five levels of ASM (0, 3, 6, 9 and 12%), distributed in an RBD with six replications and four animals per EU. The physicochemical composition results indicated 86.12% of dry matter (DM), 8.03% of crude protein (CP) and 4,553 kcal kg-1 of gross energy (GE) as well as apparent digestibility coefficients of 39.04 and 28.21% for CP and GE, respectively. The levels of ASM that provided the maximum estimate for final body weight, daily body weight gain and average daily feed intake were 2.93% (p = 0.037), 3.05% (p = 0.040) and 4.27% (p = 0.043), respectively. ASM can be indicated as a dietary fibre source for starter piglet diets because it contains relevant nutritional and energy values, without affecting the nitrogen balance and blood urea concentration.
Practical security of a chip-based continuous-variable quantum-key-distribution system

A chip-based continous-variable quantum-key-distribution (CVQKD) system with a high practical conﬁdentiality performance is crucial for constructing quantum metropolitan communication networks, but imperfections in the chip-based modulation will threaten the practical security of the chip-based CVQKD system. In this paper, we combine the plasma dispersion eﬀect of free carriers to model the carrier ﬂuctuations and reveal the essential mechanism of carrier ﬂuctuations’ inﬂuence on the system. The simulations show that the chip-based CVQKD system may face potential loophole threats or its performance will dramatically decrease under diﬀerent carrier ﬂuctuations. Moreover, two preliminary defense strategies are proposed to completely solve the practical security problems commonly induced by modulators in general chip-based CVQKD systems. This work proposes a set of modeling and analysis methods for general chip-based CVQKD systems’ modulators, which provides constructive methods to build the chip-based CVQKD system with more rigorous practical security.
Rice Husk Dust and NPK Improve Soil Chemical Properties and Growth Response of Jatropha

The present study investigated the combined effect of rice husk dust (RHD) (0.1.2.3.4 and 5 ton ha ) and NPK 10:10:10 fertilizer (0, 1, 2, 3, 4 and 5 ton ha) arranged factorially in Randomized Complete Block Design(RCBD)on selected soil fertility indices (pH, organic carbon, organic matter, total nitrogen, available phosphorus, exchangeable bases, exchangeable acidity and effective cation exchange capacity) and growth parameters of Jatropha (number of leaves, plant height, number of branches and stem girth) in an ultisol of southeastern Nigeria. Results showed significant (P<0.05) improvement in all soil chemical properties and growth parameters of plant compared to control which had no treatment. However, the effects varied with treatment levels and interactions. While the effects increased with rate of application, interactions consistently showed superior effect on all parameters studied. Thus, combining rice husk dust (RHD) and NPK may increase the soil fertility and growth of Jatropha. Treatments combination of5tonha -1 RHD and 3tonha NPK and 5tonha RHD and 5tonha NPK relatively gave the most appreciable result in soil chemical properties and growth of Jatropha respectively, thus are recommended. Original Research Article Donatus et al.; IJPSS, 33(2): 10-21, 2021; Article no.IJPSS. 66216 11