Miracle-dz/UniFAR-FTUs huggingface dataset:
Evaluation of Bacteria from Soil and Rhizosphere as Herbicidal Candidates of Some Broadleaf Weeds

The use of bacteria in biological weed control is an alternative ecofriendly way to tackle weed problems and reduce the risk of herbicide resistance. In this study, we obtained four main active bacterial isolates under the genera Pseudomonas, Bacillus and Xanthomonas from Wadi El Natroun region. All the tested bacterial isolates caused high significant reductionsin seed germination and seedling growth of Convolvulus arvensis and Portulaca oleracea. Bioassaying ethyl acetate crude extracts of these isolates showed that Pseudomonas sp. (isolate 1) was the most active against seedling stage of Portulaca oleracea. The cultural filtrate of the same isolate caused 100% reduction when assayed on seed germination, shoot and root length of Convolvulus arvensis and Portulaca oleracea. At the highest concentration (40mg/ml) of the crude ethyl acetate extract, the reduction percentage in total biomass fresh weights of Portulaca oleracea and Convolvulus arvensis seedlings reached 71.27 and 39.37%, respectively. The EC50 values (concentration that inhibited growth by 50%) were 1.3 and 1.64mg/ml for Portulaca oleracea and Convolvulus arvensis, respectively. Comparative 16S rRNA gene sequencing analysis and biochemical characterization demonstrated that isolate FS15 was member of the genus Pseudomonas and belongs to the Pseudomonas aeruginosa group with Pseudomonas aeruginosa strain NR 113599.1 as the closest relative (99.5% sequence similarity). In conclusion, Pseudomonas aeruginosa has high potential to be developed as natural bacterial herbicide and may be used in broadleaf weed control.
Purinergic signalling in human adipose-derived mesenchymal stromal cells and in vitro differentiated adipocytes

Obesity is now a global epidemic, which represents a significant health problem. Obesity is defined as an excessive accumulation of adipose tissue mass, thus understanding adipose biology has become imperative to uncovering novel drug targets in the fight against obesity. Purinergic signalling has been implicated in a wide variety of physiological functions, however very little is currently known about the role of purinergic signalling in human adipocytes and their progenitor cells. This project aimed to characterise the P2 receptor profiles in both primary human adipose-derived mesenchymal stromal cells (AD-MSCs) and in vitro differentiated adipocytes and then determine the functional roles of these receptors in each cell type. AD-MSCs and in vitro differentiated adipocytes express almost all of the known subtypes of P2 receptors and transient elevations of intracellular calcium levels are observed in both cell types in response to exogenous application of ATP, ADP and UTP. However subtype-selective antagonism revealed that only P2Y2 and P2Y6 receptors are functionally active in AD-MSCs, and P2Y1, P2Y2 and P2Y12 receptors mediate nucleotide-evoked calcium responses in adipocytes. It is unclear what physiological functions P2Y2 and P2Y6 receptors mediate in AD-MSCs, but in adipocytes, P2Y2 receptors appear to regulate basal lipolysis. Selective antagonism and shRNA-mediated knockdown of P2Y2 receptors resulted in an increase in basal glycerol release. In this study, it was determined that continuous P2Y2 activation suppresses basal lipolysis by maintaining calcium tone within adipocytes to tonicly inhibit calcium-sensitive isoforms of adenylate cyclase. This prevents the cytoplasmic accumulation of cAMP, thus inhibiting the activation of protein kinase A-mediated stimulated lipolytic pathways. These findings imply that P2Y2 receptors may be a novel and interesting drug target for modulating adipose tissue expansion. Further research is required to fully investigate the physiological roles of all of the P2 receptor subtypes expressed in these cells.
AWARD NUMBER: W81XWH-12-1-0194 TITLE: Targeting the Ron-Dek Signaling Axis in Breast Cancer PRINCIPAL INVESTIGATOR: Susan Waltz CONTRACTING ORGANIZATION: University of Cincinnati

The Ron receptor is overexpressed in human breast cancers and is associated with heightened metastasis and poor survival. Ron overexpression in the mammary epithelium of mice is sufficient to induce aggressive mammary tumors with a high degree of metastasis. Despite the well-documented role of Ron in breast cancer, few studies have examined the necessity of the endogenous Ron ligand, hepatocyte growth factor-like protein (HGFL) in mammary tumorigenesis. Herein, mammary tumor growth and metastasis were examined in mice overexpressing Ron in the mammary epithelium with or without HGFL. HGFL ablation decreased oncogenic Ron activation and delayed mammary tumor initiation. HGFL was important for tumor cell proliferation and survival. HGFL loss resulted in increased numbers of macrophages and T-cells within the tumor. T-cell proliferation and cytotoxicity dramatically increased in HGFL deficient mice. Biochemical analysis of HGFL proficient tumors showed increased local HGFL production, with HGFL loss decreasing β-catenin expression and NF-κB activation. Re-expression of HGFL in HGFL deficient tumor cells stimulated cell migration and invasion with coordinate activation of NF-κB and reduced apoptosis. Together, these results demonstrate critical in vivo functions for HGFL in promoting breast tumorigenesis and suggest that targeting HGFL may inhibit tumor growth and reactivate anti-tumor immune responses.
Embedded System Design Processor using GAA

Electronics system design is the evolutionary task which is concentrating on the system design for various things like processor, SoC for real time system, embedded systems, reconfigurable system design and more where the Processor design is one of them; it may be a single core, or more than one cores depends on the requirement Specification. There are various hardware description languages used to design and fabricate the processor, among them Verilog, VHDL, SystemVerilog and Bluespec System Verilog are few of them. Bluespec is the one of the modern hardware synthesizable language with guarded atomic action(GAA), which has many advantages over the others. This paper presents the design and implementation of pipeline based 64-bit processor using bluespec, also presents the analysis of number of clock cycles per instructions, implementation of RISC V instruction sets and working principle of pipeline processor using bluespec.
Chemical profile οf Greek Arbutus unedo honey: biological properties

Nowadays there is an increasing interest in the use of honey in the traditional Mediterranean diet, due to its high quality of sugar content as well as its strong antioxidant and antibacterial properties. Thus, the detailed knowledge of the chemical composition and bioactivities of honey is of great importance. In this study, the chemical characterization and the authentication of the aromatic profile, the total phenolic content, the antimicrobial evaluation, and the pollinic spectrum of Greek strawberry-tree (Arbutus unedo L.) honey were studied. Typification of Arbutus honey sample was based on its pollinic spectrum exerted an approx. 23% on Ericaceae pollen (expressed to Arbutus unedo pollen). The studied sample was analysed through GC-MS and among the volatile substances: benzene derivatives (dimethyl, trimethyl, and tetramethyl), β-isophorone, α-isophorone, 4-oxoisophorone, dihydrooxophorone, and 2-Hydroxy-4-oxoisophorone were detected, together with homogentistic acid (HGA) and 5-hydroxymethylfurfural (HMF), known as an essential parameter of freshness and of good quality of commercial honeys. The chemical markers of such European honeys, unedone and 2-cis-4-trans-abscisic acid (c-t-ABA), have been isolated and structurally determined by spectral means. Furthermore, the sample exhibited a high total phenolic content and an interesting antimicrobial activity against human pathogenic microorganisms, suggesting that the consumption of Greek strawberry tree honey could have beneficial effects.
Knee Muscle Torque and H:Q Ratio Changes before ACL Surgery and after Rehabilitation

Research background and hypothesis. Anterior cruciate ligament (ACL) of the knee joint is often quite a fragile structure of the knee. After the rupture of ACL neuromuscular control worsens and sensorimotor system breaks down (Risberg et al., 2007), muscle activation is poor and muscle strength decreases (Croce, Miller, 2006). Some authors have reported greater strength loss in quadriceps femoris than in hamstring femoris muscle (Busch-Joseph et al., 2001; Neeter et al., 2006), therefore we hypothesized that strength loss in knee extensors may affect hamstring/quadriceps torque (H:Q) ratio. Research aim of this study was to investigate knee extensors and ﬂ exors isometric and dynamic torque and H:Q ratio alterations before ACL surgery and after rehabilitation.Research methods. Ten volunteers with ACL ruptured knee where tested before surgery and after rehabilitation. Isokinetic dynamometer was used for this testing. Maximal isometric torque was performed during ﬂ exion and extension at 90°, 60º knee angles. Dynamic torque was performed at 30, 180, 300º/s angular velocities.Research results. Results of this study show that after rehabilitation isometric and dynamic torque of the involved leg decreased. Isometric ﬂ exion and extension torque of the uninjured leg was greater than that of the injured leg, but after rehabilitation the extension torque of the injured leg was lower than that before surgery. Discussion and conclusions. Before ACL surgery and after rehabilitation quadriceps femoris muscle torque of the uninjured leg was more affected than hamstring femoris muscle torque. After rehabilitation H:Q ratio of the injured leg was not dependent on angular velocity and knee joint angle.Keywords: maximal voluntary torque, muscle balance, muscle contraction.
The performance of dairy supply chain in Indonesia: a system dynamics approach

Purpose First, the purpose of this paper is to develop some policies as an alternative scenario to increase the performance of the Indonesian dairy milk supply chain so it can fulfil the target of the government. Second, this study aims to find the best alternative scenario based on the performance resulted from the simulation. Design/methodology/approach The paper develops a system dynamics-based model by using six approaches, i.e. “population and consumption of dairy milk”, “national milk production”, “dairy cattle feed”, “dairy cattle population”, “profit gained by the dairy farmer”, and “government policy”. Findings There is no best scenario; however, the combined scenario can give the better condition to achieve the targets set by the government. Research limitations/implications The limitations of this study include: the relationship between the levels of welfare of farmers and the desire being a dairy farmer is not modelled; the quality of milk is only determined by the content of fat and protein in one litre of milk, and the level of milk consumption per capita increases naturally without any intervention or policy from the government. Practical implications This study provides essential insights into the context of implementing the policies in the Indonesian dairy supply chain. Social implications The research revealed that good policies scenario could be built after simulating and analysing the effect of each scenario on the performance of a dairy supply chain carefully. Originality/value This study does not test one policy in isolation. It simultaneously tests various combinations of policy that related to dairy cattle import, operational assistance for dairy cooperative and dairy farmer that may help maximise the performance of the Indonesian dairy milk supply chain.
Attitude towards sustainable agriculture: future farmers and agronomist perspectives in Brazil

This study aims to identify the attitude of the future farmers regarding sustainable agriculture, based on the understanding of sustainable agriculture concept, its current and future importance and the fact that agronomy students will be future managers of rural enterprises, public managers and companies of the sector. The research was conducted with 288 students of agronomy from the best Brazilian universities. Through information analysis obtained from the application of the attitude scale toward sustainable agriculture it was possible to notice that the students associate aspects of this concept to the balance of environment and natural resources, and that through these practices agriculture can have both environmental and economic gains. It is expected that the next farmers generation favorable attitude that was found in this research generate greater implementation of the practices of sustainable agriculture in the long term. Keywords: Future farmers, Sustainable agriculture, Agronomist, Brazil, Agriculture.
Collaborative Clustering Selection Algorithm Based on T-LEACH

In order to solve the problem of WSN data collection in smart greenhouse under step terrain, factors such as energy consumption, distance and node density are considered in the clustering process, and the LEACH algorithm is improved to achieve energy saving and energy balance. The terrace model of multi-layer stochastic distributed WSN system is established, and the terraced CMIMO hierarchical clustering algorithm, namely T-LEACH algorithm, is proposed. The rationality and effectiveness of the algorithm are verified by simulation. Introduction In WSN, energy can be saved through CMIMO technology. With MIMO technology, capacity and transmission speed can be increased under multi-antenna transmission, and at the same speed, energy consumption can be saved compared to SISO. In CMIMO transmission mode, this paper analyzes the energy consumption, distance and density between each node, and selects the cooperative node CN (CN, Cooperative node) to improve the coverage of WSN and extend the life cycle of the network. The literature[2] proposed a distributed clustering routing algorithm, which proposed a CH competition algorithm, which depends on the residual energy of the candidate CH and the residual energy of its GN in the life cycle. This document also considers the problem that the geometrical dimensions formed by candidate CHs close to the BS are also small. In [3], a new dynamic clustering DCREDT selection algorithm is proposed. The algorithm uses residual energy and distance threshold to cluster. Under the premise of saving energy, the node with larger residual energy is preferentially CH, and CH is realized. Energy balance with other nodes, but does not consider the transmission distance in complex environments and the variation of transmission signal attenuation. After analyzing the WSN data acquisition in the topography of the terraced fields, the terraced hierarchical clustering algorithm is proposed, namely T-LEACH. The basic idea of the algorithm is to manually distribute the nodes according to the area of the trapezoids in each layer of the network, so that the nodes with high density, close distance and high energy become the working nodes of the current round, and the other nodes enter the sleep state. Thereby better balancing the energy consumption of the entire network and extending the life cycle of the entire network. This provides an important reference value for the later stepped terrain.
Sensitivity of tetracene layer as an effect of entanglement

Application of the method of quantum-mechanical calculations allowed for studies of variability of interactions between molecules of ethanol and tetracene. Entanglement of quantum states is seen during calculations in two ways: as a change of electric dipole moment and as an increase of the basis set superposition error (BSSE) with decreasing distance between molecules under study. There are observed the dependences of the total energy of the system due to the mutual arrangement of the long axes of the molecules and due to the orientation of the bond of the oxygen atom to the carbon atom with respect to the plane of benzene skeleton of tetracene molecule.
MORINGA OLEIFERA FLOUR PROTEIN FRACTIONS AS FOOD INGREDIENTS WITH ANTIOXIDANT PROPERTIES

Moringa oleifera meal proteins were extracted by using salt, water and alkaline precipitation to obtain globulins (GLO), albumins (ALB), and iso-electric precipitated (ISO) isolates. All the samples were tested for antioxidant properties using 2, 2diphenyl-1-picrylhydrazyl (DPPH), hydroxyl radical scavenging activity (HRSA), ferric reducing antioxidant power (FRAP) and inhibition of metal ion chelation assays. The amino acid compositions of the samples, though fairly comparable, the albumin fraction in particular showed considerable inhibitory potentials against the DPPH (53.02%) and hydroxyl radical (44.21%). None of the samples however had any significant metal chelating ability since the only sample (globulin) with activity had less than 5% metal chelation activity. With the results obtained in the study, it was concluded that the albumin and the flour possess some level of inhibitory potentials against free radicals which could present them as useful antioxidant
Selective integration during sequential sampling in posterior neural signals

Decisions are typically made after integrating information about multiple attributes of alternatives in a choice set. The computational mechanisms by which this integration occurs have been a focus of extensive research in humans and other animals. Where observers are obliged to consider attributes in turn, a framework known as “selective integration” can capture salient biases in human choices. The model proposes that successive attributes compete for processing resources and integration is biased towards the alternative with the locally preferred attribute. Quantitative analysis shows that this model, although it discards choice-relevant information, is optimal when the observers’ decisions are corrupted by noise that occurs beyond the sensory stage. Here, we used scalp electroencephalographic (EEG) recordings to test a neural prediction of the model: that locally preferred attributes should be encoded with higher gain in neural signals over posterior cortex. Over two sessions, human observers (of either sex) judged which of two simultaneous streams of bars had the higher (or lower) average height. The selective integration model fit the data better than a rival model without bias. Single-trial analysis showed that neural signals contralateral to the preferred attribute covaried more steeply with the decision information conferred by locally preferred attributes. These findings provide neural evidence in support of selective integration, complementing existing behavioural work. Significance Statement We often make choices about stimuli with multiple attributes, such as when deciding which car to buy on the basis of price, performance and fuel economy. A model of the choice process, known as selective integration, proposes that rather than taking all of the decision-relevant information equally into account when making choices, we discard or overlook a portion of it. Although information is discarded, this strategy can lead to better decisions when memory is limited. Here, we test and confirm predictions of the model about the brain signals that occur when different stimulus attributes of stimulus are being evaluated. Our work provides the first neural support for the selective integration model.
Human-help in automated planning under uncertainty

Planning is the sub-area of artificial intelligence that studies the process of selecting actions to lead an agent, e.g. a robot, to a goal state. In many realistic scenarios, any plan of actions can lead the robot into a dead-end state, that is, a state from which the goal cannot be reached. In such cases, the robot can, pro-actively, resort to human help in order to reach the goal, an approach called symbiotic autonomy. In this work, we propose two different strategies to tackle this problem: (I) contingent planning, where the initial state is partially observable, configuring a belief state, and there is non-determinism in the outcomes of the robot actions; and (II) probabilistic planning, where the initial state may be partially or totally observable and the actions have probabilistic outcomes. In both scenarios, the human help is considered a scarce resource that should be used only when necessary. In contingent planning, the problem is to find a policy (a mapping from states to actions) that: (i) guarantees the agent always reaches the goal (strong policy); (ii) guarantees that the agent eventually reaches the goal (strong cyclic policy), or (iii) does not guarantee achieving the goal (weak policy). In this scenario, one of this work contributions is to propose contingent planning systems that consider human help to transform weak policies into strong (cyclic) policies. To do so, two types of human help are included: (i) human actions that modify states and/or belief states; and (ii) human observations that modify belief states. In probabilistic planning, the problem is to find a policy (a mapping from world states to actions) that can be one of these two types: a proper policy, where the agent has a probability 1 of reaching the goal; or an improper policy, in the case of unavoidable dead-ends. In general, the goal of the agent is to find a policy that minimizes the expected accumulated cost of the actions while maximizes the probability of reaching the goal. In this scenario, this work proposes probabilistic planners that consider human help to transform improper policies into proper policies however, considering two new (alternative) criteria: either to minimize the probability of using human actions or to minimize the expected number of human actions. Furthermore, we show that optimal policies under these criteria can be efficiently computed either by increasing human action costs or given a penalty when a human help is used. Solutions proposed in both scenarios, contingent planning and probabilistic planning with human help, were evaluated over a collection of planning problems with dead-ends. The results show that: (i) all generated policies (strong (cyclic) or proper) include human help only when necessary; and (ii) we were able to find policies for contingent planning problems with up to 1015000 belief states and for probabilistic planning problems with more than 3 ∗ 1018 physical states.