Miracle-dz/UniFAR-FTUs huggingface dataset:
Approach to analyzing executable code based on the software architecture recovery

The article discusses a new approach to obtaining additional information about the software module under study based on the preliminary software architecture recovery during the executable code analysis. As a result, it is possible to reduce the requirements for the resources spent by limiting the field of research, rational choice of priorities, and abstraction from secondary elements. The paper demonstrates the feasibility of restoring the software architecture in a two-step process: first, the separate components are isolated, and then their purposes and relationships are determined. An automated method for decomposing a software module is proposed, which allows allocating components corresponding to static libraries, classes, and their groups. This method is based on the functions clustering by the distances between them in the address space and on the call graph. A description of the implementation of the developed method as a plug-in for the IDA disassembler is given.
A Hybrid Deep Learning Model for Dynamic Stock Movement Predictions Based on Supply Chain Networks

An inter-firm relationship of paramount importance is captured by supply chain networks. <br>Embedded in such a network, a firm’s performance is associated with its partners’ and peers’<br>performance. This paper proposes an end-to-end predictive framework named Hybrid and<br>Temporal Graph Neural Network (HT-GNN) to predict the dynamic stock price movement of<br>firms. The model learns time-dependent node embeddings by aggregating network neighbors’<br>features and market trends to provide node classifications over time. Experiments on a real-world<br>supply chain network among over 2,700 publicly traded firms show that HT-GNN can improve<br>dynamic stock movement predictions. We define different types of network neighborhoods by<br>identifying firms that contribute to such predictions in different ways and going even beyond<br>immediate ties. Our results would naturally help investors understand stock price movement and<br>managers identify network neighbors with predictive power over its own stock price movement.
Evaluation of the phytomass source for composite preparation

The properties of lignocellulose materials from the trunk and bark of trees, and from agricultural sources were investigated by thermogravimetry (TG) and pyrolysis–gas chromatography/mass spectrometry (Py-GC/MS). The goal was to learn which of the phytomass sources is the most accessible to dehydration and aldol reactions, and in this way could be considered suitable for composite preparation by the thermal pressing treatment. The bagasse second differential thermal analysis peak in air is at the highest temperature acceptable for intermolecular dehydration/crosslinking, and therefore we consider bagasse to be the most suitable candidate for composite preparation. From the TG results in air at 250°C, it follows that willow wood and bagasse are the most thermally resistant sources. The data obtained by Py-GC/MS analysis showed glycolaldehyde and acetic acid as dominant markers related to adhesion properties via aldol condensation. The detected sum amount of glyceraldehyde and acetic acid decreases in the order: beech wood > bagasse > acacia wood > sugar beet pulp, whereas the remaining species produced much less of it. By comparing results run at above conditions with composite preparation using the pressing thermal treatment at a temperature of 150°C and pressures up to 800 kPa, the suggested evaluation was examined for application on sugar beet residue. © 2012 Wiley Periodicals, Inc. J. Appl. Polym. Sci., 2013
SOLVENT INFLUENCE ON THE ELECTRONIC ABSORPTION SPECTRA OF SOME AZOAROMATIC COMPOUNDS

Solvent-induced effects on the π–π* electronic absorption band frequencies of some azobenzene derivatives are described in terms of dipole–dielectric, solute–solvent, and hydrogen bonding interactions. A multiple linear regression equation for νmax was developed based on polarizability–polarity parameters and Kamlet–Taft solvatochromic parameters. Although the polarizability is a major contributor to the interactions in solutions, parameters related to the solvent polarity, hydrogen bond acidity, and hydrogen bond basicity are also statistically significant in determining the spectral shifts.
Inverse phase transfer catalysis versus interfacial catalysis. Effect of medium stirring in the epoxidation reaction of chalcone by hydrogen peroxide

The epoxidation of chalcone by H2O2 has been investigated in a water–heptane two-phase system in the presence of a surfactant (dodecyltrimethylammonium bromide; DTAB) in order to analyse the role played by the rate and the type of stirring (magnetic and sonication). Under these conditions two catalytic processes have been proved to intervene: an inverse phase transfer catalysis (IPTC) or an interfacial catalysis (IC). This latter process appears to be very sensitive to stirring efficiency.
The Influence of the Alkyl Chain Length and Steric Effect on Stability Constants and Extractability of Co(II) Complexes with 1‐Alkyl‐4(5)‐methylimidazoles

Abstract Extraction of Co(II) complexes has been studied with nine derivatives of 1‐alkyl‐4(5)‐methylimidazoles (with R=C2H3 to C10H21) from aqueous solution [I=0.5(KNO3) at 25°C] with toluene, trichloromethane, and 2‐ethyl‐1‐hexanol. Stability constants of the complexes formed in the aqueous phase (β c ) as well as partition constants (P c ) of the extracted species were determined. It was demonstrated that both the stability constants and partition constants of the complexes increase with an increasing of the 1‐alkyl chain length. The tetrahedral together with octahedral complexes were formed beginning from the second step of complexation. Furthermore, the influence of the bulkiness of the 1‐alkyl group on separation process of Co(II) from Zn(II) for extractions with toluene and 2‐ethyl‐1‐hexanol were determined.
Supplement to “ The discretization filter : A simple way to estimate nonlinear state space models ”

In this section, I detail intermediate and auxiliary theoretical results used in the proofs of the main theorems stated in Section 5. Following Douc, Moulines, and Ryden (2004), I first establish that the distribution of Xt M given a history of observations Y r is itself a uniformly ergodic (inhomogeneous) Markov chain with minorizing constant independent of the parameter θ ∈ Θ and the number of discrete points M ∈ Z+. This is the analogous result to Lemma 1 in their paper. Note that a Markov chain with transition kernel Pθ is said to satisfy a uniform minorization condition if there exist a probability measure μQ, a positive integer n, and > 0 such that P θ (x A)≥ μQ(A) for all x ∈ X andA ∈ B(X ), where P θ is the n-step ahead transition kernel of the Markov chain. Define Q− M ≡ infm m′ Pθ M(m m′) and Q+ M ≡ supm m′ Pθ M(m m′) for M ∈ Z+. I now state the first lemma.
Focusing Gentzen’s LK proof system

Gentzen’s sequent calculi LK and LJ are landmark proof systems. They identify the structural rules of weakening and contraction as notable inference rules, and they allow for an elegant statement and proof of both cut elimination and consistency for classical and intuitionistic logics. Among the undesirable features of those sequent calculi is that their inferences rules are low-level and frequently permute over each other. As a result, large-scale structures within sequent calculus proofs are hard to identify. In this paper, we present a diﬀerent approach to designing a sequent calculus for classical logic. Starting with Gentzen’s LK proof system, we examine the proof search meaning of his inference rules and classify those rules as involving either don’t care nondeterminism or don’t know nondeterminism . Based on that classiﬁcation, we design the focused proof system LKF in which inference rules belong to one of two phases of proof construction depending on which ﬂavor of nondeterminism they involve. We then prove that the cut rule and the general form of the initial rule are admissible in LKF . Finally, by showing that the inference rules for LK are all admissible in LKF , we can give a relative completeness proof for LKF provability with respect to LK provability. We shall also apply these properties of the LKF proof system to establish other meta-theoretic properties of classical logic, including Herbrand’s theorem.
ALMAJIRI ISLAMIC PRACTICES AND THE COVID-19 PANDEMIC IN NIGERIA: MATTERS ARISING Amanambu, Uchenna Ebony, PhD

There has been an age long struggle between the rich and the poor in any given society. Many intellectuals and critics have taken some swipes at this phenomenon. Karl Marx in his criticism of religion opines that the rich created religion so as to opiate the poor and by extension subjugate them. This study objectively seeks to analyze the history of Islam, its impacts and Almajiri Islamic practices in Nigeria. Apart from the historical developments, the study tries to survey the detailed, overt and covert planned manipulations of this practice for some paranoid aims. Moreso, it also analyses the inhuman treatments meted out to them because of the dreaded coronavirus pandemic popularly referred to as covid-19.
Impact of natural zeolite in agriculture with special reference to field crops

Farming with natural rocks and minerals is an age-old practice for food production since stone ages. The intensive production practices associated with imbalanced fertilizer management practices has led to declining quality and or quantity of the soil resource base and climate change. To feed the growing population, soil degradation is the key issue which needs urgent attention. In this context, farming with zeolite has drawn attention. Zeolites are natural rocks and gained a momentum in the recent past due to its large number of physico- chemical properties. They can be used both as carriers of nutrients and as a medium to free nutrients (Sangeetha et al., 2016). Combined application of clinoptilolite zeolite, organic and inorganic fertilizers leads to saving of inorganic fertilizers resulted in improving the growth, increasing the dry matter production, yield and N, P and K uptake in Zea mays L. and also conserve agro-ecosystem for sustainable crop production (Ahmed, 2010). The effect of zeolite and its combination with chemical fertilizer and organic fertilizers (Sugarcane filter cake) increase sugarcane yield as compared to without fertilization (Cairo et al., 2017). Amending urea with rice straw compost and clinoptilolite zeolite improved nitrogen use efficiency because of temporary adsorption and desorption of ammonium on the exchange sites of compost and clinoptilolite zeolite and yield of Zea mays L. (Omar et al., 2018). Combined use of 80 kg / ha N as urea + 50 kg / ha composted manure + 21% zeolite result highest CEC (meq /100gm soil), facilitated highest leave nitrogen concentration (%) and quantity and quality sunflower dry matter yield (kg / ha), but the impact of their application was greater in the second year than in the ﬁrst year (Gholamhoseini et al., 2012). Integration of 10 t zeolite / ha with either alternate wetting and drying (AWD) or complete flooding (CF) management reduced NH3 volatilization without increasing N leaching and increased rice grain yield and water productivity, with an increased economic benefit of $126 − 195 / ha, as compared to CF without zeolite (Sun et al., 2019). Although considerable research has been advanced, further research needs to carry out for their efficient utilization in farming.
Action Selection for Composable Modular Deep Reinforcement Learning

In modular reinforcement learning (MRL), a complex decision making problem is decomposed into multiple simpler subproblems each solved by a separatemodule. Often, these subproblems have conflicting goals, and incomparable reward scales. A composable decision making architecture requires that even the modules authored separately with possibly misaligned reward scales can be combined coherently. An arbitrator should consider different module’s action preferences to learn effective global action selection. We present a novel framework called GRACIAS that assigns fine-grained importance to the different modules based on their relevance in a given state, and enables composable decision making based on modern deep RL methods such as deep deterministic policy gradient (DDPG) and deep Q-learning. We provide insights into the convergence properties of GRACIAS and also show that previous MRL algorithms reduce to special cases of our framework. We experimentally demonstrate on several standard MRL domains that our approach works significantly better than the previous MRL methods, and is highly robust to incomparable reward scales. Our framework extends MRL to complex Atari games such as Qbert, and has a better learning curve than the conventional RL algorithms.
Fake News Detection using Passive Aggressive and TF-IDF Vectorizer

: Consuming news from social media is becoming increasingly popular nowadays. Social media brings benefits to users due to the inherent nature of fast dissemination, cheap cost, and easy access. However, the quality of news is considered lower than traditional news outlets, resulting in large amounts of fake news. Detecting fake news becomes very important and is attracting increasing attention due to the detrimental effects on individuals and the society. The performance of detecting fake news only from content is generally not satisfactory, and it is suggested to incorporate user social engagements as auxiliary information to improve fake news detection. Thus it necessitates an in-depth understanding of the correlation between user profiles on social media and fake news. We perform a comparative analysis over explicit and implicit profile features between these user groups, which reveals their potential to differentiate fake news.
ECOLOGICAL IMPLICATIONS OF PHYTASE ADDED TO NORMAL AND DEFICIENT AVAILABLE PHOSPHORUS DIETS OF LAYING HENS MEASURED BY N AND P EXCRETION

Kamberi, M. , S. Muji, A. Kryeziu, R. Kastrati and N. Mestani, 2017. Ecological implications of phytase added to normal and defi cient available phosphorus diets of laying hens measured by N and P excretion. Bulg. J. Agric. Sci., 23 (4): 632–638 Nitrogen and phosphorus are two main pollutants responsible for environmental eutrophication, a process of saturation of surface water with nutrients which as a result of oxygen deple on favors overgrowth of algae and grazing bacteria. An experiment was conducted to determine the effects of adding phytase to a corn-soybean meal laying hen diet over 8 weeks with different available phosphorus (AP) levels on total nitrogen (TN) and total phosphorus (TP) in excreta. In the experiment, 144 Hisex Brown hens were fed two levels of AP (0.12% and 0.46%) and two levels of phytase (0, and 600 Phytase Units-FTU)/ kg). In the experiment supplemental phytase resulted in lower total excreta nitrogen (1.50 ± 0.04; 1.23 ± 0.04; 133 ± 0.07; and 1.31 ± 0.04%, for hens fed 0.12% AP–phytase, 0.12% AP + phytase, 0.46% AP phytase, and 0.46% AP + phytase, respectively) and total excreta phosphorus (1.14 ± 0.01; 1.03 ± 0.05; 1.34 ± 0.03; and 1.37 ± 0.01, respectively). Results of this study indicate that 600 FTU added to corn soybean meal based layer diets containing 0.12% AP contributes to signifi cantly lower levels of total excreta nitrogen and phosphorus without any adverse effects on the performance of laying hens.
RECOGNITION TECHNOLOGY OF AGRICULTURAL PICKING ROBOT 
BASED ON IMAGE DETECTION TECHNOLOGY

As a kind of intelligent agricultural equipment, picking robots are of great significance for improving the efficiency of agricultural production. However, the main bottleneck restricting the development of picking robots today is the positioning and control in image recognition. Therefore, an agricultural picking control method based on visual servo technology is proposed. This method can accurately control the picking hand of the picking robot on the basis of building an eye-hand relationship model and an online identification system. With the tomato picking process as the background, the effectiveness of the method was verified. The test results of image feature points show that there is a small error between the stable feature points and the expected image feature points. In addition, the image plane trajectory of the picking robot is relatively smooth, and there is no vibration or overshoot. In addition, from its density distribution characteristics, it can be seen that the picking hand movement is a continuous acceleration stage at the beginning of the control, and at the end of the control, the characteristic points gradually tend to the desired characteristics, and the output of the control system is relatively stable. It can be seen from this that the model has better control performance. This method has certain practical significance for the improvement of agricultural picking efficiency.
Knowledge Organisation in Historical Information Systems

The complexity and diversity of historical information makes the field of Historical Information Systems (HIS) an interesting platform for Knowledge Organisation research. HIS are defined considering their specific aims and their role as a knowledge store and transfer system. Improving such a system requires the development of representational strategies, solutions for common retrieval problems and a classification capable to organise it all. Some suggestions arc made in these directions. Historical Information Systems (HIS): the concept A historical information system (HIS) may be defined as an automated system integrating a set of databases and formal procedures, designed and maintained to store, treat and retrieve historical information. They must be able to store sources -both references and reproductions-, bibliographical references and research work; should they be textual, graphic or procedural. The stress is put in the inter­ face among the different types of information. The I-lIS is considered to be an open evolutionary system, growing towards an ever closer integration of the data. Fi­ nally, the I-lIS must be considered as a part of a scientific network of research and custodial centres, with which it must interchange data and knowledge, and there­ fore pursue co-operative normalisation policies. Despite the growing research in special information systems, c. g. geographical, business, management, archival and library information systems, HIS are advanc­ ing at a lower pace. Perhaps, this is due to the usually individualistic work of historians, who seldom consider giving access to their data to other scientists or doing co-operative research. This is usually so, unless they are tied by very strong institutions, or unless the accumulation of electronic records is the result of the activities of the original organisation. However, historical information is useful for many sciences and activities. Besides it, the field of HIS is nowadays divided among historical archives and archival networks, heritage databases and historical research projects. Advances in these different areas will undoubtedly affect the others, but the fact is that there is insufficient contact among them. This gap is the result of different stresses: historical researches pursue creation of knowledge from historical sources; heritage and archival officers look mainly for control and pres­ ervation of the documentary units in which sources are stored. Anyway, historical work is rapidly changing: it is leaving the craftsmanship stage, and there is a strong trend towards data-processing and database developing]; and, Advances in Knowledge Organization, Vol.4(1994), p. 81-90
VERDICT: A Language and Framework for Engineering Cyber Resilient and Safe System

The ever-increasing complexity of cyber-physical systems is driving the need for assurance of critical infrastructure and embedded systems. However, traditional methods to secure cyber-physical systems—e.g., using cyber best practices, adapting mechanisms from information technology systems, and penetration testing followed by patching—are becoming ineffective. This paper describes, in detail, Verification Evidence and Resilient Design In anticipation of Cybersecurity Threats (VERDICT), a language and framework to address cyber resiliency. When we use the term resiliency, we mean hardening a system such that it anticipates and withstands attacks. VERDICT analyzes a system in the face of cyber threats and recommends design improvements that can be applied early in the system engineering process. This is done in two steps: (1) Analyzing at the system architectural level, with respect to cyber and safety requirements and (2) by analyzing at the component behavioral level, with respect to a set of cyber-resiliency properties. The framework consists of three parts: (1) Model-Based Architectural Analysis and Synthesis (MBAAS); (2) Assurance Case Fragments Generation (ACFG); and (3) Cyber Resiliency Verifier (CRV). The VERDICT language is an Architecture Analysis and Design Language (AADL) annex for modeling the safety and security aspects of a system’s architecture. MBAAS performs probabilistic analyses, suggests defenses to mitigate attacks, and generates attack-defense trees and fault trees as evidence of resiliency and safety. It can also synthesize optimal defense solutions—with respect to implementation costs. In addition, ACFG assembles MBAAS evidence into goal structuring notation for certification purposes. CRV analyzes behavioral aspects of the system (i.e., the design model)—modeled using the Assume-Guarantee Reasoning Environment (AGREE) annex and checked against cyber resiliency properties using the Kind 2 model checker. When a property is proved or disproved, a minimal set of vital system components responsible for the proof/disproof are identified. CRV also provides rich and localized diagnostics so the user can quickly identify problems and fix the design model. This paper describes the VERDICT language and each part of the framework in detail and includes a case study to demonstrate the effectiveness of VERDICT—in this case, a delivery drone.
Using Augmented Reality to Enhance Nursing Education

Augmented and Virtual Reality are proliferating throughout daily life. Everyday utilities, such as Google Maps, deploy Augmented Reality (AR) to improve the user experience and increase its effectiveness. Similarly, Augmented and Virtual Reality have been used in the educational domain, where these applications have been shown to improve the learning curve and retention. In this study, AR is proposed as an innovative method to improve the effectiveness and efficiency of the education of nursing students. We propose to introduce this innovative technology in the education of future nurses. Within this study the researchers use augmented reality (AR) to help nursing students learn about physical assessment techniques for the heart and the lungs. Researchers have demonstrated increased memory retention while using AR [14][15]. In this study, we provide a holographic overlay including the internal organs heart, ribcage, and lungs to increase the understanding of accurate placement of devices required for assessing cardiac and respiratory issues using anatomical landmarks. In addition, the visual aspects are supported with audio sound tracks to enhance learning. The ability to project images accurately placed onto real world physical objects using AR headsets could lead to increased retention and deeper understanding leading to precision performance related to techniques in physical assessment of the patient.