Miracle-dz/UniFAR-FTUs huggingface dataset:
Effect of Red, Blue, Green LEDs on the Germination and Seedling Growth of Rice

The present investigations attempted to study the effects of red, blue and green LEDs effect on seed germination, first leaf length, first leaf blade length, root length, seedling fresh and dry weight. Seeds of five rice varieties were germinated and seedlings were grown under dark and red, blue, green LEDs lighting system (6 h photoperiod and 18 h dark) set at 20 to 24± 2 °C for day and night respectively and 70 ± 2 % relative humidity in a control chamber for 14 days (starting 3 days after plated for germination). The result showed that germination percent increased significantly in BRRIdhan52 and BRRIdhan75 under red-blue-green LEDs than dark. First leaf length increased in dark than LEDs treatment. Longest leaf (10.42 cm) was recorded in BRRIdhan86 in dark and under LEDs in BRRIdhan75 (5.70 cm). First leaf blade length was highest in BRRIdhan52 (2.56 cm) under LEDs treatment and in dark BRRIdhan67 had the longest (2.48 cm). Root length was also increased significantly in studied rice varieties. Though, longest root was found in dark in BRRIdhan71 (6.69 cm) and under LEDs, BRRIdhan71 had the longest root (6.35 cm). Seedling fresh and dry weight were highest under red-blue-dark LEDs treatment. BRRIdhan86 had the highest and BRRIdhan67 had the lowest seedling fresh and dry weight with a range of 0.323g to 0.451g and 0.037g to 0.052g respectively than dark condition. Root length showed positive significant correlation with seedling fresh weight (r = 0.876) and seedling dry weight (r = 0.873). Whereas seedling fresh weight showed complete correlation (r = 1) with seedling dry weight. Response index was negative for first leaf length in the studied rice varieties. Highest response index (35.93) was observed for seedling fresh and dry weight in BRRIdhan75 and BRRIdhan86. Environ. Sci. & Natural Resources, 13(1&2): 63-69, 2020
Conflict-Directed Diverse Planning for Logic-Geometric Programming

Robots operating in the real world must combine task planning for reasoning about what to do with motion planning for reasoning about how to do it -- this is known as task and motion planning. One promising approach for task and motion planning is Logic Geometric Programming (LGP) which integrates a logical layer and a geometric layer in an optimization formulation. The logical layer describes feasible high-level actions at an abstract symbolic level, while the geometric layer uses continuous optimization methods to reason about motion trajectories with geometric constraints. In this paper we propose a new approach for solving task and motion planning problems in the LGP formulation, that leverages state-of-the-art diverse planning at the logical layer to explore the space of feasible logical plans, and minimizes the number of optimization problems to be solved on the continuous geometric layer. To this end, geometric infeasibility is fed back into planning by identifying prefix conflicts and incorporating this back into the planner through a novel multi-prefix forbidding compilation. We further leverage diverse planning with a new novelty criteria for selecting candidate plans based on the prefix novelty, and a metareasoning approach which attempts to extract only useful conflicts by leveraging the information that is gathered in the course of solving the given problem.
The role of public procurement in the framework of the 2030 Agenda: the approach of institutions and civil society

Public administration is a key agent for achieving development goals, and this is recognised in the 2030 Agenda and its Sustainable Development Goals. This international consensus requires the involvement of a large number of agents, and the mainstreaming of these global challenges into public policies. However, a practice that could be key in this regard, such as public procurement, does not receive sufficient attention within this framework. Faced with a broad range of goals and targets that cover environmental, economic and social issues, the 2030 Agenda lacks an adequate framework and tools to address the solution to these challenges, and public procurement could have greater prominence as a driver of progress for a number of these goals. The paper studies the role and potential of public procurement as an instrument of policy to contribute to the international development agenda. Therefore, the paper analyses documentation and reports of the main institutions that have worked on these issues to date: United Nations, the Sustainable Development Solutions Network, and the Reflection Group on the 2030 Agenda for Sustainable Development. Despite having been considered in the design of the Agenda, subsequent reports by the United Nations give little importance to the role of public procurement, which contrasts with that expressed by civil society.
Role of Family Support, Spirituality and Self-efficacy in Type 2 Diabetes Self-care in Greater Accra Region, Ghana

Aims: The purpose of this study was to examine the relationship between family support, spirituality and self-care in Type 2 Diabetes patients in the Greater Accra Region, Ghana. It also aimed at determining whether self-efficacy would moderate the relationship between spirituality, family support and self-care. Study Design: A cross sectional study was adopted and 270 diabetes patients living in Greater Accra region were conveniently sampled. The data was collected using questionnaire such as FACIT-sp, DSMQ, SDS and S4-Mad. The IBM SPSS version 2020 was used in analysing the data. The Pearson Product Moment Correlation test and Hierarchical Multiple Regression were used respectively to test for the correlation between variables and moderation role of self-efficacy. Results: Spirituality correlated with self-care (r = .151, p < .05). Also, family support correlated with self-care among T2DM patients (r = .237, p < .01). Self-efficacy moderated the relationship between family support and self-care (ΔR2 = .031, β = .254, p < .05). However, self-efficacy did not moderate the relationship between spirituality and self-care (ΔR2 = .002, β = -.358, p > .05). Conclusion: More spirituality and more social support received by patients are associated with greater self-care. Again, self-efficacy moderates the relationship between family support and self-care but fails to influence the association between spirituality and self-care. Self-efficacy, spirituality and family support are critical in diabetes self-care. It is therefore beneficial that health care providers incorporate psychosocial interventions into health care delivery.
Translational Medicine: Towards Gene Therapy of Marfan Syndrome

Marfan syndrome (MFS) is one of the most common inherited disorders of connective tissue caused by mutations of the fibrillin-1 gene (FBN1). Vascular abnormalities, such as the enlargement of the aorta with the risk of life-threatening rupture are frequently observed. However, current treatment is limited and therapeutic options focus solely on symptomatic therapy. Gene therapy focuses on genetically modifying cells to produce a therapeutic effect and may be a promising treatment option for MFS. Here, we first provide an overview of the historical background and characterization of MFS. Subsequently, we summarise current gene therapy options and possible translational concepts for this inherited disorder that affects connective tissue.
A Heartbeat Classifier for Continuous Prediction Using a Wearable Device

Heartbeat monitoring may play an essential role in the early detection of cardiovascular disease. When using a traditional monitoring system, an abnormal heartbeat may not appear during a recording in a healthcare facility due to the limited time. Thus, continuous and long-term monitoring is needed. Moreover, the conventional equipment may not be portable and cannot be used at arbitrary times and locations. A wearable sensor device such as Polar H10 offers the same capability as an alternative. It has gold-standard heartbeat recording and communication ability but still lacks analytical processing of the recorded data. An automatic heartbeat classification system can play as an analyzer and is still an open problem in the development stage. This paper proposes a heartbeat classifier based on RR interval data for real-time and continuous heartbeat monitoring using the Polar H10 wearable device. Several machine learning and deep learning methods were used to train the classifier. In the training process, we also compare intra-patient and inter-patient paradigms on the original and oversampling datasets to achieve higher classification accuracy and the fastest computation speed. As a result, with a constrain in RR interval data as the feature, the random forest-based classifier implemented in the system achieved up to 99.67% for accuracy, precision, recall, and F1-score. We are also conducting experiments involving healthy people to evaluate the classifier in a real-time monitoring system.
Optimizing patient flow, capacity, and performance of COVID-19 vaccination clinics

Abstract Mass vaccination plays an important role in increasing immunization against COVID-19 and decreasing morbidity. Drive-through and traditional walk-through centers have been set up in most cities in the United States and other countries to vaccinate large numbers of people in a short period of time. This article focuses on a pair of mass vaccination clinics conducted on a mid-sized, public university campus. Applying tools from Industrial Engineering, including time study, flow charts, and Queuing Theory, the team identified improvements that resulted in a 40% reduction in the duration of the second clinic while vaccinating almost the same number of patients with no increases in overall staffing. The work resulted in a model for designing mass vaccination clinics in the future and demonstrates that engineers have the ability to support healthcare personnel to increase the performance of the vaccination centers. The inclusion of engineering in the planning and execution of these vaccination clinics can help maximize clinic capacity, reduce the staff and resources needed, and reduce the patients’ waiting time.
Reputation Detection for Information Diffusion in Social Network Systems

Reputation detection in traditional distributed systems (e.g., electronic commerce systems and peer-to-peer systems) relies heavily on the factor of interaction reputation, which can be derived from direct interactions between agents through bidirectional relationships. However, in the current information diffusion in social network systems (SNS) (e.g., Twitter), the characteristic of the unidirectional relationship between agents and the decay property of diffusion will result in lacking direct interactions; therefore, interaction reputations will be difficult to be obtained by agents in a distributed manner. To solve this problem, a novel distributed reputation detection model following the pattern “from path to individual” (FPTI) is proposed, which can provide a new reputation factor as an alternative to interaction reputation in such environments. The main idea is that the positive (or negative) observation of an information diffusion process increases (or decreases) the belief of the corresponding diffusion path, which further increases (or decreases) the reputation of each involved agent. Thus, the reputation of a target agent can be assessed by the superimposition of reputations of multiple paths on which this agent has participated in past information diffusion processes. Furthermore, being aware of agent’s limited capacity for reputation detection in SNS, we then propose the enhanced FPTI model (eFPTI), which simplifies the detection source to reduce detection costs and achieve the approximate performance as FPTI. Theoretical analyses and experimental evaluations validate the efficiency and effectiveness of our models and also show several properties of the models, for example, the robustness for dynamic environments.
The input/output constrained control for v/stol aircraft dynamics under a descriptor system formulation

This paper investigates the input/output constrained control for the planar vertical/short takeoff and landing aircraft. The controller construction is based on a descriptor system formulation. The resulting nonlinear matrix inequality in addressing the invariant ellipsoid for given initial state conditions is reformulated as an objective optimization problem and tackled by iteratively optimization with relaxed linear objective. This dilated LMI scheme does not contain the multiplication of the system matrix and Lyapunov matrix variable, and thus relieves the imposed structure constraint on the Lyapunov Matrix. Also, the additional design matrix variable can help to achieve a better design performance. The design results show that the proposed approach can deliver better performances compared to the standard LMIs in terms of the achieved largest relative stability under the same control efforts and attitude constraints. The merits of this approach are demonstrated by various numerical controller constructions with different specifications regarding the certain level of relative stability and parasitic uncertain coupling. The time-response simulations are given for verification.
Dual targeting inhibitors for HIV-1 capsid and cyclophilin A: molecular docking, molecular dynamics, and quantum mechanics

ABSTRACT The acquired immunodeficiency syndrome (AIDS), a progressive failure of the immune system that leads to death if left untreated, is caused by a member of a family of retroviruses known as human immunodeficiency virus type 1 (HIV-1). Virus capsid (CA) and human cyclophilin A (cyPA) are two important HIV-1 targets that are known for their primary role in the life cycle of the virus, making them attractive targets for HIV-1 drug discovery. This study used a dual targeting approach to inhibit these two targets utilising different in silico techniques. A library of 672 antiviral agents from the ChEMBL database was docked into the CA crystal structure. The obtained 10 best docking scores were used as queries in the PubChem database to search for similar structures. These analogs were then docked into CA and cyPA, resulting in 220 compounds with good docking scores on both targets, which were filtered by calculating MM-GBSA free binding energy and in silico pharmacokinetic properties. This led to the identification of 10 compounds with better docking scores and free binding energies with respect to CA and cyPA compared to the references. The best 3 compounds were further validated by molecular dynamics (MD) and density functional theory (DFT) calculations, which proved to have stable binding interactions and high reactivity. These compounds can be considered as potential double inhibitors of CA and cyPA, which are expected to achieve promising results in an experimental study.
Long-core experimental study of different displacement modes on fractured-vuggy carbonate reservoirs

Abstract It is difficult to utilize real fractured–vuggy carbonate cores to conduct long-core displacement experiments due to the special structures of fractured and vuggy. Aiming to not affect the porosity and permeability of the original core structure, a special filling method on the sunken space of the core surface was created to meet the requirements of long-core experiments. Long-core experiments of depletion drive, water flooding, gas drive, and water alternating gas (WAG) drive were performed to simulate the actual conditions of one-dimension oil reservoir and systematically study the influence of different development approaches on the recovery of vuggy carbonate reservoirs. Results show that the optimal conversion pressure of water flooding is between 80% bubble point and bubble point pressure. In the high-pressure and high water-cut stage, the development effect of gas–water alternative drive becomes significant, it can effectively reduce water cut and improve oil recovery. The most suitable and effective displacement mode is adopted depletion drive first and converts water flooding when the pressure decreases between 80% bubble point and bubble point pressure. When the water cut approximately reaches 80%, then WAG flooding is performed. The experiments provide data and technical support for the rational development of vuggy carbonate reservoirs.
An MILP Method for Design of Distributed Energy Resource System Considering Stochastic Energy Supply and Demand

A distributed energy resource (DER) system, which can be defined as a medium or small energy conversion and utilization system with various functions for meeting multiple targets, is directly oriented towards users and achieves on-site production and energy supply according to users’ demands. Optimization research on system construction has recently become an important issue. In this paper, simple stochastic mathematical equations were used to interpret the optimal design problem of a DER system, and based on this, a novel method for solving the optimization problem, which has multi-dimensional stochastic uncertainties (involving the price of input-energy and energy supply and demand), was put forward. A mixed-integer linear programming (MILP) model was established for the optimal design of the DER system by combining the ideas of mean value and variance, aiming to minimize the total costs, including facility costs, energy purchase costs, and loss caused by energy supply shortage, and considering the energy balance and facility performance constraints. In the end, a DER system design for an office building district in Xuzhou, China, was taken as an example to verify the model. The influences of uncertainty on the selection of system facilities and the economic evaluation were analyzed. The result indicated that uncertainty of energy demand played a significant role in optimal design, whereas energy price played a negligible role. With respect to economy, if uncertainties are not considered in system design, it will result in a short supply, and therefore the total cost will increase considerably. The calculation convergence was compared with previous work. The implementation results showed the practicality and efficiency of the proposed method.
Quality of Life and Associated Factors of International Students in South Korea: A Cross-Sectional Study Using the WHOQOL-BREF Instrument

The quality of life (QoL) of an individual is affected in a complex way by the person’s physical health, psychological state, social relationships, and their relationship to their environment. We assessed the QoL of international university students using the World Health Organization Quality of Life (WHOQOL-BREF) tool and explored the QoL-associated factors. We conducted a cross-sectional study between January and March 2021. The WHOQOL-BREF was summarized as a four-domain construct following the WHO guidelines and QoL scores for each domain were compared through a t-test and chi-squared test. To determine the factors associated with international students’ QoL we used multiple linear regression models, with each of the domains serving as the outcome variable. In total, 261 students participated, with 52.5% being males. We reported predicted means (PM) along with 95% confidence intervals (CI). Cronbach’s alpha for the overall WHOQOL-BREF tool was 0.88. Students’ self-reported QoL mean score was 3.67 ± 0.71 and the mean score of their overall satisfaction with health was 3.61 ± 0.83. The social relationships domain had the highest mean score at 56.88 ± 19.55 and was significantly associated with age (>25 years: PM: 59.7; 95% CI: 56.2–63.2, p = 0.033) and region of origin (Asia: PM: 54.4; 95% CI: 42.5–64.8, p = 0.027). Students above 25 years had significantly higher scores in all domains (p < 0.05). Our results showed that the social relationships and psychological health domains have more positive impact on international students’ QoL compared to the physical and environmental health domains. To cope with factors influencing international students’ QoL, universities should develop and provide efficient support systems for foreign students in South Korea.
Cerebrospinal Fluid Cortisol and Dehydroepiandrosterone Sulfate, Alzheimer’s Disease Pathology, and Cognitive Decline

Introduction Elevated cortisol levels have been reported in Alzheimer’s disease (AD) and may accelerate the development of brain pathology and cognitive decline. Dehydroepiandrosterone sulfate (DHEAS) has anti-glucocorticoid effects and it may be involved in the AD pathophysiology. Objectives To investigate associations of cerebrospinal fluid (CSF) cortisol and DHEAS levels with (1) cognitive performance at baseline; (2) CSF biomarkers of amyloid pathology (as assessed by CSF Aβ levels), neuronal injury (as assessed by CSF tau), and tau hyperphosphorylation (as assessed by CSF p-tau); (3) regional brain volumes; and (4) clinical disease progression. Materials and Methods Individuals between 49 and 88 years (n = 145) with mild cognitive impairment or dementia or with normal cognition were included. Clinical scores, AD biomarkers, brain MRI volumetry along with CSF cortisol and DHEAS were obtained at baseline. Cognitive and functional performance was re-assessed at 18 and 36 months from baseline. We also assessed the following covariates: apolipoprotein E (APOE) genotype, BMI, and education. We used linear regression and mixed models to address associations of interest. Results Higher CSF cortisol was associated with poorer global cognitive performance and higher disease severity at baseline. Cortisol and cortisol/DHEAS ratio were positively associated with tau and p-tau CSF levels, and negatively associated with the amygdala and insula volumes at baseline. Higher CSF cortisol predicted more pronounced cognitive decline and clinical disease progression over 36 months. Higher CSF DHEAS predicted more pronounced disease progression over 36 months. Conclusion Increased cortisol in the CNS is associated with tau pathology and neurodegeneration, and with decreased insula and amygdala volume. Both CSF cortisol and DHEAS levels predict faster clinical disease progression. These results have implications for the identification of patients at risk of rapid decline as well as for the development of interventions targeting both neurodegeneration and clinical manifestations of AD.
Cyber Security Issues and Challenges - A Review

Cyber security has become essential for information security. Keeping the information safe is one of the major challenges nowadays. Given the unrestricted number of free websites, the Internet has undeniably opened a new way of exploitation known as cybercrime. Governments and private sectors are taking many measures in order to control these cybercrimes. Handling cyber security is still a very huge concern. This research paper focuses on the various problems in cyber security during the current scenario . It also bring on focus on emerging technologies in the field of cyber security , ethics and the trends changing the features of cyber security.
DIPOLE ANTENNA WITH HORN WAVEGUIDE FOR ENERGY HARVESTING IN DTV SYSTEMS

|This article presents a dipole antenna using an I-shape adding technique on both sides of the antenna’s body to widen the frequency range, using a horn waveguide to gain enhancement and harvest energy by matching the circuit which is compatible with the voltage multiplier circuit at the RF frequency (510{790 MHz) in a TV digital system. Having measured the eﬀect of the antenna, it was found that the antenna operates at a frequency range of 60.24% (450{838 MHz), a 67.79% increase from the base dipole antenna, which has again enhancement of 10.23 dB from adding the horn waveguide (60.99%). It has a pattern of energy radiating in a speci(cid:12)c direction, and when the antenna is used with an energy harvesting circuit to get energy or power from the front direction of the TV digital antenna at a distance of 10 km, it is capable of harvesting energy of up to 7.33 (cid:22) W.