Miracle-dz/UniFAR-FTUs huggingface dataset:
GPR19 Coordinates Multiple Molecular Aspects of Stress Responses Associated with the Aging Process

G protein-coupled receptors (GPCRs) play a significant role in controlling biological paradigms such as aging and aging-related disease. We have previously identified receptor signaling systems that are specifically associated with controlling molecular pathologies associated with the aging process. Here, we have identified a pseudo-orphan GPCR, G protein-coupled receptor 19 (GPR19), that is sensitive to many molecular aspects of the aging process. Through an in-depth molecular investigation process that involved proteomic, molecular biological, and advanced informatic experimentation, this study found that the functionality of GPR19 is specifically linked to sensory, protective, and remedial signaling systems associated with aging-related pathology. This study suggests that the activity of this receptor may play a role in mitigating the effects of aging-related pathology by promoting protective and remedial signaling systems. GPR19 expression variation demonstrates variability in the molecular activity in this larger process. At low expression levels in HEK293 cells, GPR19 expression regulates signaling paradigms linked with stress responses and metabolic responses to these. At higher expression levels, GPR19 expression co-regulates systems involved in sensing and repairing DNA damage, while at the highest levels of GPR19 expression, a functional link to processes of cellular senescence is seen. In this manner, GPR19 may function as a coordinator of aging-associated metabolic dysfunction, stress response, DNA integrity management, and eventual senescence.
Design of RNGCC for Uncertain Large-Scale Interconnected Systems 1

In this paper, the robust nonfragile guaranteed cost control (RNGCC) problem is studied for a class of linear large-scale systems with uncertainties and a given quadratic cost functions. The uncertainty in the system is assumed to be norm-bounded and time-varying. Also, the state-feedback gains for subsystems of the large-scale system are assumed to have norm-bounded controller gain variations. The problem is to design a state feedback control laws such that the closed-loop system is asymptotically stable and the closed-loop cost function value is not more than a specified upper bound for all admissible uncertainties and controller gain variations. Sufficient conditions for the existence of such controllers are derived based on the linear matrix inequality (LMI) approach combined with the Lyapunov method. A parameterized characterization of the robust non-fragile guaranteed cost controllers is given in terms of the feasible solutions to a certain LMI. A numerical example is given to illustrate the proposed method. c 2006 IIC. All rights reserved.
Approaches for Memristive Structures Using Scratching Probe Nanolithography: Towards Neuromorphic Applications

This paper proposes two different approaches to studying resistive switching of oxide thin films using scratching probe nanolithography of atomic force microscopy (AFM). These approaches allow us to assess the effects of memristor size and top-contact thickness on resistive switching. For that purpose, we investigated scratching probe nanolithography regimes using the Taguchi method, which is known as a reliable method for improving the reliability of the result. The AFM parameters, including normal load, scratch distance, probe speed, and probe direction, are optimized on the photoresist thin film by the Taguchi method. As a result, the pinholes with diameter ranged from 25.4 ± 2.2 nm to 85.1 ± 6.3 nm, and the groove array with a depth of 40.5 ± 3.7 nm and a roughness at the bottom of less than a few nanometers was formed. Then, based on the Si/TiN/ZnO/photoresist structures, we fabricated and investigated memristors with different spot sizes and TiN top contact thickness. As a result, the HRS/LRS ratio, USET, and ILRS are well controlled for a memristor size from 27 nm to 83 nm and ranged from ~8 to ~128, from 1.4 ± 0.1 V to 1.8 ± 0.2 V, and from (1.7 ± 0.2) × 10−10 A to (4.2 ± 0.6) × 10−9 A, respectively. Furthermore, the HRS/LRS ratio and USET are well controlled at a TiN top contact thickness from 8.3 ± 1.1 nm to 32.4 ± 4.2 nm and ranged from ~22 to ~188 and from 1.15 ± 0.05 V to 1.62 ± 0.06 V, respectively. The results can be used in the engineering and manufacturing of memristive structures for neuromorphic applications of brain-inspired artificial intelligence systems.
Secondary Students’ Knowledge on Birds and Attitudes towards Conservation: Evaluation of an Environmental Education Program

Urdaibai Biosphere Reserve holds a diversity of habitats and resources that are essential for migratory bird species’ conservation, and at the same time provides a rich milieu for the development of environmental education programs. This study evaluates the impact of a daylong and place-based environmental education program, performed at the Urdaibai Bird Center (UBC), on secondary education students’ environmental attitudes and knowledge. Students (n = 908) completed a written questionnaire where their perceptions on the Urdaibai Biosphere Reserve and marshes, together with their interest in biodiversity, knowledge about bird migration and bird species identification skills, and attitudes towards conservation were assessed. Results show that students’ knowledge regarding Biosphere Reserves, marshes, and bird migration is limited, and that their bird identification skills are scarce. Although they scored high on environmental attitudes, a significant number of them feel that conservation efforts are excessive and hinder economic development. Students living within the Biosphere Reserve, as well as from rural milieus or who underwent primary education through a bird-centered curriculum hold a better knowledge of the local biodiversity. To adapt the environmental education program at the UBC, its integration in formal teaching/learning contexts via meaningful hands-on and/or project-based activities could be considered, together with the systematic evaluation of the outcomes.
Laws and regulations enabling and restricting Africa’s vegetable seed sector

ABSTRACT Farmers in sub-Saharan Africa do not have much choice of quality seed of vegetable cultivars adapted to local growing conditions and consumer demand. Only a handful of vegetable seed companies invest in local breeding research, while nearly all rely on seed imports. Our objective was to analyse to what extent existing seed laws and regulations enable or restrict the development of a research-based vegetable seed sector in Africa. Using a regulatory value chain approach, we analysed written laws and regulations for 13 countries and interviewed private and public sector stakeholders. We generally find that countries have taken a government-centred approach to seed quality control without recognizing that government agencies have little capacity to do this properly for vegetable crops. Mandatory Value for Cultivation and Use (VCU) trials and state-controlled seed certification are the two examples of regulatory approaches that may work for cereals but are not well suited for vegetables. No country has vegetable breeding as a goal in their national seed policy, and only four set out specific objectives for the vegetable seed sector. Tailoring seed policies, laws and regulations more specifically to vegetables could stimulate local variety development and seed production and benefit smallholder farmers and consumers at large.
Galectin-3 and Epithelial MUC1 Mucin—Interactions Supporting Cancer Development

Simple Summary MUC1 mucin with T antigen and galectin-3 with high affinity to T disaccharide are both overexpressed in a variety of human cancers. Their mutual interactions support cancer development, attenuate anoikis, promote cancer cells proliferation, invasiveness and metastasis. The inhibition of MUC1/T antigen—galectin-3 interactions may be a potential strategy to reduce tumor progression and metastasis. The aim of this review is to summarize the current knowledge about the relationship between MUC1 and galectin-3. Abstract Aberrant glycosylation of cell surface proteins is a very common feature of many cancers. One of the glycoproteins, which undergoes specific alterations in the glycosylation of tumor cells is epithelial MUC1 mucin, which is highly overexpressed in the malignant state. Such changes lead to the appearance of tumor associated carbohydrate antigens (TACAs) on MUC1, which are rarely seen in healthy cells. One of these structures is the Thomsen-Friedenreich disaccharide Galβ1-3GalNAc (T or TF antigen), which is typical for about 90% of cancers. It was revealed that increased expression of the T antigen has a big impact on promoting cancer progression and metastasis, among others, due to the interaction of this antigen with the β-galactose binding protein galectin-3 (Gal-3). In this review, we summarize current information about the interactions between the T antigen on MUC1 mucin and Gal-3, and their impact on cancer progression and metastasis.
H2S Crosstalk in Rhizobia Modulates Essential Nutrient Allocation and Transport in Soybean

Hydrogen sulfide (H2S), a novel gas signaling molecule, plays a crucial role in plant growth and stress response. However, little attention has been devoted to the regulation of H2S on nutrient transport and utilization in legume–rhizobia symbiosis systems. Although we have previously proven that H2S synergized with rhizobia to considerably enhance nitrogen (N) metabolism and remobilization in N-deficient soybeans, it remains uncertain if changes in nutrient absorption, metabolism, and accumulation occur concurrently. Therefore, employing a synergistic treatment of H2S and rhizobia, we examined the dry matter biomass and carbon (C), N, phosphorous (P), and potassium (K) nutrient content in various organs of soybean from blooming to maturity. Firstly, H2S and rhizobia application obviously improved leaf and plant phenotypes and biomass accumulation in different organs during N-deficient soybean development. Second, from flowering to maturity, the contents and stoichiometric ratios of C, N, P, and K in various organs of soybean were changed to variable degrees by H2S and rhizobia. Furthermore, H2S collaborated with rhizobia to significantly affect grain nutrient harvest across soybean growth as well as overall plant nutrient accumulation. Consequently, H2S synergizes with rhizobia to optimize grain harvest quality and nutrient accumulation across the plant by managing the rational allocation and dynamic balance of nutrients in diverse organs, hence boosting soybean development and production.
Modelling Decision Problems Via Birkhoff Polyhedra

A compact formulation of the set of tours neither in a graph nor its complement is presented and illustrates a general methodology proposed for constructing polyhedral models of decision problems based upon permutations, projection and lifting techniques. Directed Hamilton tours on n vertex graphs are interpreted as (n-1)- permutations. Sets of extrema of Birkhoff polyhedra are mapped to tours neither in a graph nor its complement and these sets are embedded into disjoint orthogonal spaces as the solution set of a compact formulation. An orthogonal projection of its solution set into the subspace spanned by the Birkhoff polytope is the convex hull of all tours neither in a graph nor its complement. It’s suggested that these techniques might be adaptable for application to linear programming models of network and path problems.
On certain zeta functions attached to two Hilbert modular forms II. The case of automorphic forms on a quaternion algebra

As to the meaning of the symbols, the reader is referred to the introduction of Part I. We recall here only that F is a totally real algebraic number field of degree n, and w denotes the Fourier coefficients of an elliptic modular form 52(z) = E wQ(a)e2q'iaz. In Part I, we investigated D assuming that EX(a)N(Q) S is an L-function of a CM-field with an algebraic-valued Hecke character. In the present Part II, we treat the case where X( a) can be obtained as eigenvalues of Hecke operators T(a) on a quaternion algebra B over F. Thus we begin our study by recalling the theory of automorphic forms on the product o r of r copies of the upper half plane & with respect to congruence subgroups of B x . Here r is the number of archimedean primes of F unramified in B. Then we introduce in Section 2 the notion of arithmeticity (or Q-rationality) of such automorphic forms and show that the space of automorphic forms can be spanned by the arithmetic ones. Our main theorems will be stated in Section 3 and proved in Section 6; Sections 4 and 5 are preliminaries to the proof. The central result, specialized to the case r = 1, asserts that if g is a Q-rational eigenform such that gj T( a) =X( a )g for all integral ideals a of F, then D(s0) for certain integers so are algebraic numbers times 7Tdg, g), where d is an integer determined by the weight of g, and (*, *) is the Petersson inner product.
CLASSIFICATION OF RANDOM TIMES AND APPLICATIONS

The paper gathers together ideas related to thin random time, i.e., random time whose graph is contained in a thin set. The concept naturally completes the studies of random times and progressive enlargement of filtrations. We develop classification and (*)-decomposition of random times, which is analogous to the decomposition of a stopping time into totally inaccessible and accessible parts, and we show applications to the hypothesis (H ′), honest times and informational drift via entropy.
Stepping back from Data and AI for Good – current trends and ways forward

Various ‘Data for Good’ and ‘AI for Good’ initiatives have emerged in recent years to promote and organise efforts to use new computational techniques to solve societal problems. The initiatives exercise ongoing influence on how the capabilities of computational techniques are understood as vehicles of social and political change. This paper analyses the development of the initiatives from a rhetorical slogan into a research program that understands itself as a ‘field’ of applications. It discusses recent academic literature on the topic to show a problematic entanglement between the promotion of initiatives and prescriptions of what ‘good’ ought to be. In contrast, we call researchers to take a practical and analytical step back. The paper provides a framework for future research by calling for descriptive research on the composition of the initiatives and critical research that draws from broader social science debates on computational techniques. The empirical part of the paper provides first steps towards this direction by positioning Data and AI for Good initiatives as part of a single continuum and situating it within a historical trajectory that has its immediate precursor in ICT for Development initiatives.
Correlation coefficient analysis: centrality vs. maximal clique size for complex real-world network graphs

The high-level contribution of this paper is correlation analysis between the centrality values observed for nodes (a computationally lightweight metric) and the maximal clique size (a computationally hard metric) that each node is part of in complex real-world network graphs. The real-world network graphs studied range from regular random network graphs to scale-free network graphs. The maximal clique size for a node is the size of the largest clique (in terms of the number of constituent nodes) the node is part of. We observe the degree-based centrality metrics such as the degree centrality and eigenvector centrality to be relatively better correlated with the maximal clique size compared to the shortest path-based centrality metrics such as the closeness centrality and betweenness centrality. As the real-world networks get increasingly scale-free, we observe the correlation between the centrality value and the maximal clique size to increase.
Observability Analysis of SINS/GPS Tightly Coupled System

The observation equations of the tightly coupled SINS/GPS system based on pseudo-range and pseudo-range rate were presented through constellation-selecting algorithm of G matrix,and the tightly coupled SINS/GPS system mentioned above was proved to satisfy the condition of piece-wise constant system(PWCS)theorem.The ob-servability and observable degrees of the system were analyzed with the striped observability matrix(SOM)of respec-tive discrete system instead of the total observability matrix(TOM)of the corresponding continuous system.And then the results of the observability analysis of the system on condition that the number of the visible satellites were not more than 4 and equal to 6 was presented using the theory of singular value decomposition(SVD). The results of simulation show that the more the visible satellites are,the better the observability and the observable degrees of the system are.
Effects of Selected Essential Oils on Listeria monocytogenes in Biofilms and in a Model Food System

The composition of 18 essential oils was determined using gas chromatography–mass spectrometry, and their antilisterial activity was evaluated by the disk diffusion method, followed by the determination of the minimum inhibitory and minimum bactericidal concentrations. The most active essential oils were oregano, thyme, cinnamon, winter savory, and clove, with MIC values ranging from 0.09 to 1.78 µL/mL. We investigated the biofilm-forming potential of Listeria monocytogenes on polystyrene at 5 °C, 15 °C, and 37 °C in three different media. The formation of biofilm was found to be dependent on the temperature and the availability of nutrients. After treatment with selected essential oils, the reduction in biofilm biomass was in the range of 32.61% and 78.62%. Micromorphological changes in the L. monocytogenes treated by oregano and thyme essential oils were observed in the form of impaired cell integrity and cell lyses by using scanning electron microscope. Oregano and thyme essential oils (MIC and 2MIC) significantly (p < 0.05) reduced the population of L. monocytogenes in minced pork meat during storage at 4 °C. In conclusion, the obtained results indicated the good activity of some selected essential oils on L. monocytogenes, with bacteriostatic, bactericidal, and antibiofilm effects at very low concentrations.
Chatbot In The Selection Of Outpatient Ward In Hospital Using C4.5 Algorithm

The C4.5 algorithm is one of many data mining classification techniques. The final result in the classification of this algorithm is the creation of a decision tree . T his tree helps in making predictions and selection . The c4.5 algorithm is widely used in many cases, such as outpatient services, disease prediction, etc . It's just that for the c4.5 algorithm method in the construction of chatbots, only a few apply it. More cases of implementing chatbots using Semantic Web, NLP, etc . This study focuses on the c4.5 algorithm method and its application in chatbots because , in previous studies , it was still rare to implement chatbot services in hospitals using this algorithm. The c4.5 algorithm method in this study will be carried out on a chatbot because in predicting poly hospital services for selection , it is more suitable to use this algorithm. The data used were obtained from the Azra Hospital Bogor , totaling 3,292 data after the data cleaning process with the classification results using the c4.5 algorithm, namely getting the RMSE (Root Mean Square) / Mean value of 12.66%. This number means that the lower the average prediction error, the less. That means that from the total data used, 315 data experienced wrong predictions, and 2,977 other data were predicted correctly. Gradient Boosting was also carried out to reduce the prediction error rate by 0.66% after being tested seven times. In the future, this research is expected to improve the classification test time
Noise Smoothing in Learning Parameters of Bayesian Network

Noise universally exists in discrete data in real life.It is important and difficult how to smooth these noises effectively.At present,the methods of reducing noise influence are to simplify the structure in the parameter learning of Bayesian network.But the regulated structure will lose some useful edges to fall network reliability.The influence of noise can not be decreased or removed from root.And the continuous learning is very difficult.An effective method of smoothing noise was proposed by combining Bayesian network with Gibbs sampling.A variable was taken as a basic unit and its corresponding datum were smoothed by using the information of Markov blanket providing.The problems above can be efficiently avoided.
State of Art of Particle Swarm Optimization Algorithm to Solve the Permutation Flow Shop Scheduling Problem

Particle Swarm Optimization Algorithm is an improved heuristic algorithm basing on swarm,which has been initially used to solve some problems such as neural network training,fuzzy control system and combinational optimization.The theory and method of particle swarm used to solve shop scheduling problem has emerged in an endless stream in the past few years.To promote the further development of Particle Swarm Optimization Algorithm and solve the permutation flow shop scheduling problems and provide reference for designing better algorithm,we introduce Particle Swarm Optimization Algorithm in brief.Focus and difficulty to solve the permutation flow shop scheduling problem are given next,sum up several typical issues of solving permutation flow shop scheduling problems with Particle Swarm Optimization Algorithm of the last few years,from the perspective of several main issues such as approaches of initialization to population,encoding of particle,design for objective function and the formula of particle's velocity and position update which are connected with Particle Swarm Optimization Algorithm.In addition,we analyze the scope of application of each approach.Finally,we probe into several directions and contents about the issue of solving permutation flow shop scheduling problems with Particle Swarm Optimization Algorithm,which are to be further researched.
A flow Cytometry Gating Strategy for Profiling CD4+CD25+/highCD127-/low Regulatory T Cells in the Rheumatoid Arthritis Scenario

Regulatory T cells (Tregs) has been consider as a potential biomarker in rheumatologic clinical trials as this cell population has been shown to be involved in the autoimmune diseases outcome. Human Tregs are defined as CD4 + CD25 +/high CD127 -/low cells; however its accurate identification by flow cytometry has been argued, especially as a result of different gating strategies. A flow cytometry gating strategy was settled to measure human Tregs from PBMC isolated via density gradient using CPT tubes. With this method we performed a standardized procedure for Treg profiling, useful for immunomonitoring in clinicals assessment
Observer Design for Linear Singular Time-delay Systems

Two kinds of observers for linear singular time-delay systems,namely functional ob- servers and full-order observers,are considered in this paper.For the former,observers with and without internal delay are considered.For the latter,observers without internal delay is given.The corresponding design steps for various observers,which are all normal linear time-delay systems,are presented.Numerical examples are given to illustrate the methods.