Miracle-dz/UniFAR-FTUs huggingface dataset:
Life stage affects prey use with �tness consequences in a zoophytophagous mirid bug

Omnivorous insects make foraging decisions between plant and prey resources depending on their accessibility, availability, and nutritional value. This shapes the stability and complexity of foodwebs, but also pest control services in agroecosystems. The mirid bug Lygus pratensis is a common cotton pest in China, but it also feeds on a variety of prey species. However, little is known about how different types of available resources affect its �tness and foraging behaviour. In laboratory experiments, we measured the �tness (survival, longevity and fecundity) of L. pratensis fed with bean pod only, bean + Aphis gossypii nymphs, or bean + Helicoverpa armigera eggs, and we also conducted focal observations of its foraging behaviour when provided the latter two. Adding H. armigera to its diet increased its �tness (both survival and fecundity), while adding A. gossypii was marginally detrimental. The different diets did not affect the time spent walking (searching for food resources) or preying, but signi�cantly affected the time spent sapping bean tissue depending on L. pratensis life stage. Nymphs spent more time sapping plant when provided with H. armigera than A. gossypii (possibly through higher e�ciency of handling prey). In addition, adults spent less time sapping plant than did nymphs (possibly through good e�ciency of handling A. gossypii mobile prey and due to higher protein requirements). This special case of life-history omnivory highlights the complexity of natural foodwebs, where a major pest at the juvenile stage may reduce pest damage by preying on other pests species at the adult stage.
AN EXPERIMENTAL INVESTIGATION BASED ON SERVICES OF VIDEO STREAMING USING DEEP NEURAL NETWORK FOR CONTINUOUS QOE PREDICTION

Now-a-days Global Internet traffic is created by video streaming which is a primary source of platform, this may create and contact with the worldwide audience. The user the contents high quality streaming to delivering a crucial role play with quality of experiences the continuous user predicting with video streaming services. By the temporal dependencies that can cause the complexity in data QoE and the factor influence QoE among non-linear relationship that can introduced challenge to prediction QoE continuous. To effectively capture Gated Recurrent Unit (GRU) that utilized the existing studies this can be deal, accuracy QoE prediction excellent resulting. Even-through, GRU complexity is high computational, architecture with characteristic processing sequential with it, power computational with limited devices it’s performance about the serious question which has been raised. Meanwhile, Deep neural network with variation of Temporal convolutional network (TCN), for modelling task with sequences which has been proposed, computational complexity and accuracy prediction with terms GRU based on the method of baseline over the performances prediction supervisor has been provided. In this paper, based on the model TCN with improved, namely DNN-QOE, the QoE proposed is predictive continuous, sequential data with characteristic pose, to overcome the complexity computation based on the advantage of TCN leverage from drawback model of GRU based QoE, to improve the accuracy of the QoE prediction they improved the architecture that has been introduced at the certain time. The performances of the DNN-QoE are highly competitive.
Engine Performance and Exhaust Emissions of a Diesel Engine From Various Biodiesel Feedstock

Engine Performance and Exhaust Emissions of a Diesel Engine from Various Biodiesel Feedstock. (December 2009) Bjorn Sanchez Santos, B.S., University of the Philippines at Los Baños Chair of Advisory Committee: Dr. Sergio C. Capareda Increasing fuel prices, stricter government policies, and technological developments made it possible to seek for renewable alternatives, called biofuels, to petroleum fuel. Biodiesel, a biofuel that is produced from chemically mixing animal fat, vegetable oils, or recycled restaurant grease with alcohol and catalyst, is gaining popularity in recent years as a substitute for petroleum diesel. Ninety percent (90%) of U.S. biodiesel industry makes use of soybean oil as its feedstock. However, soybean oil alone cannot meet such a huge demand on biofuel production. Hence, it is important to identify and get more information about other feedstocks, specifically on its effects on the performance and exhaust emissions of diesel engines. The purpose of this study is to investigate the performance and emissions of two diesel engines operating on different biodiesel fuels (i.e. canola oil, sunflower oil, safflower oil, peanut oil, and chicken fat) and compare them to the performance and emissions when the engine is operated on soybean oil-based biodiesel and petroleumbased diesel.
Factors Influences the Use of Cost Accounting Systems in Libyan Agricultural Firms

This paper used quantitative approach to examine the relationship between six contingent factors that influence the Libyan agricultural firms to practice cost accounting systems. The available literature focused on the practice of cost accounting systems in manufacturing and servicing firms, this study filled the gap in the literature in term of studying the factors that influence the cost accounting practices in the agricultural firms. A questionnaire survey was used to collect data from 227 respondents, and the response rate was 81% (184). It was found that there is a positive relationship between the size, competition, legal obligation, and importance of cost information and practice of cost accounting systems, while the relationship between product diversity, cost structure and practice of cost accounting systems was found to be not significant.
AKADEMİK MOTİVASYONUN YORDANMASINDA AKADEMİK YETKİNLİK VE AKADEMİK SORUMLULUK

The main purpose of this study is to determine the relationship between academic motivation and academic self-efficacy and academic responsibility levels of university students through correlational and regression analysis. This study’s other purpose is to determine whether the academic motivation, academic self-efficacy and academic responsibilities of university students differ according to their gender. For this purpose, data were collected face-to-face from a total of 370 university students, 196 of whom were women and 174 of whom were men, in central of Mugla City. The average age of these students is 21.09 (ss= 2.19), and the age range is between 17 and 31. Academic Motivation Scale, Academic Responsibility Scale and Academic Self-efficacy Scale were used as data collection tools. According to the findings, positively meaningful relationships were obtained between academic motivation and academic self-efficacy and academic responsibility. Similarly, there is a positively meaningful relationship between the belief in academic self-efficacy and academic responsibility. It has been observed that the level of academic self-efficacy predicts academic motivation, on the other hand, academic responsibilities in graduates predict academic motivation. Together, these two variables predict 48% of the variance on academic motivation. According to another finding, there was no significant difference between academic self-efficacy and academic motivation levels and gender. However, it was found to be significantly different in favor of female students according to the level of academic responsibility. The findings have been discussed and interpreted.
A HYBRID APPROACH FOR TEXT CLASSIFICATION

On the internet, a huge amount of text data is collected, and segregating it based on a particular category is a crucial task. The data collected can be structured or unstructured. In the proposed method, machine learning algorithms and ensemble technique is used to handle the unstructured text data for classifying the text. The paper aims to evaluate the performance of the machine and deep ensemble classifiers. Ensemble classifiers provide solutions to numerous problems. There are various methods for the ensemble. General ensemble techniques are bagging, boosting, and stacking. In this paper, the bagging and boosting techniques are used to evaluate the performance of the models. Different voting schemes are available in the bagging method. The ensemble learner used in this paper makes predictions based on voting techniques.
Aggregate Wage Flexibility in Selected New Eu Member States Nontechnical Summary

A fixed exchange rate regime eliminates one degree of freedom in absorbing macroeconomic shocks. Therefore, there is a call for higher labor market flexibility in countries which are members of the monetary union or those which intend to join the monetary union. Focusing on the crosscountry analysis of labor markets in the enlarged European Union, this paper aims to assess empirically the role of aggregate wages as a correction mechanism for dealing with economic disturbances. A comparable quarterly data-set is constructed covering 1995–2004 for four central European states (CE-4), four new EU members already participating in the Exchange Rate Mechanism-II (ERM-II participants), and three peripheral members of the euro area (EMU-3). We apply classical time series/panel, Bayesian, and cointegration techniques to determine the extent to which aggregate wages can accommodate shocks in the economy. The macroeconomic data does not seem to support the argument that real wages are flexible in the CE-4, the ERM-II participants, and the EMU-3. and seminar participants at the CNB and the IMF for discussion and helpful comments. A fixed exchange rate regime eliminates one degree of freedom in absorbing macroeconomic shocks. Therefore, there is a call for higher labor market flexibility in countries which are members of the monetary union or those which intend to join the monetary union. Focusing on the crosscountry analysis of labor markets in the enlarged European Union, this paper aims to assess empirically whether steps towards the European Monetary Union (EMU) indeed go hand in hand with higher wage flexibility in reality. Due to limited and even declining mobility of workers within the new member states, and given the formal restrictions on the free movement of labor for new EU members, it is unlikely that migration can be considered an efficient tool for coping with adverse shocks. This paper, therefore, focuses on aggregate wage adjustment. A comparable quarterly data-set is constructed covering 1995–2004 for four central European states (CE-4), four new EU members already participating in the Exchange Rate Mechanism-II (ERM-II participants), and three peripheral members of the euro area (EMU-3). We apply alternative econometric techniques to determine the extent to which aggregate wages can accommodate shocks in the economy. The macroeconomic data does not seem to support the argument that the degree of wage adjustment is significantly higher for countries which already participate in the ERM-II. Nor is wage flexibility higher in the three EMU members selected. In addition, …
How to Construct Double-block-length Hash Functions *

In this article, it is discussed how to construct a compression function with 2n-bit output using a component function with n-bit output. The component function is either a smaller compression function or a block cipher. Some constructions are presented which compose collision-resistant hash functions: Any collision-finding attack on them is at most as efficient as the birthday attack in the random oracle model or in the ideal cipher model. A new security notion is also introduced, which we call indis-tinguishability in the iteration, with a construction satisfying the notion.
Over Fences and Into Yards: Privacy Threats and Concerns of Commercial Satellites

Commercial satellite imaging is used for diverse applications in a wide range of sectors, from agriculture to the military. As satellite images continue to become more widely available and detailed in resolution, the potential for individual and population-level monitoring increases and raises new privacy concerns compared to previous Earth observation technologies. We anticipate that these technologies will only continue to improve in the upcoming decade. To better understand privacy threats and concerns of commercial satellite imagery, we conducted a survey of 99 participants from the United States. We found that most respondents were not aware that commercial satellites existed, and once informed about the capabilities of commercial satellites, most are not comfortable with how good the current state-of-the-art satellite imaging capabilities are. Few respondents want satellite imagery cost-free and widely available, which conflicts with current trends in geospatial data. In addition to aiding our understanding of the public's current perception and relationship with remote sensing technologies, we use these results to propose possible new satellite image legislation, regulation, and technological mitigations, both nationally and internationally.
The Role of Human Hepatic Cytochrome P450 Isozymes in the Metabolism of Racemic 3,4-Methylenedioxy-Methamphetamine and Its Enantiomers

The entactogen, 3,4-methylenedioxy-methamphetamine (MDMA), is a chiral drug that is mainly metabolized by N-demethylation and demethylenation. The involvement of cytochrome P450 (P450) isozymes in these metabolic steps has been studied by inhibition assays with human liver microsomes and, in part, with heterologously expressed human P450 isozymes. However, a comprehensive study on the involvement of all relevant human P450s has not been published yet. In addition, the chirality of this drug was not considered in these in vitro studies. The aim of the present work was to study the contribution of human P450 isozymes in the N-demethylation and demethylenation of racemic MDMA and its single enantiomers. MDMA and its enantiomers were incubated using heterologously expressed human P450s, and the metabolites were quantified by gas chromatography-mass spectrometry after derivatization with S-heptafluorobutyrylprolyl chloride. The highest contribution for the N-demethylation as calculated from the enzyme kinetic data, were obtained for CYP2B6 (R,S-MDMA), CYP1A2 (R-MDMA), and CYP2B6 (S-MDMA). In the case of the demethylenation, the isozyme with the highest contribution to net clearance for R,S-MDMA, R-MDMA, and S-MDMA was CYP2D6. For the first time, marked enantioselectivity was observed for N-demethylation and demethylenation by CYP2C19 with a preference for the S-enantiomers. In addition, CYP2D6 showed preference for S-MDMA in the case of demethylenation. None of the other isozymes showed major preferences for certain enantiomers. In conclusion, therefore, the different pharmacokinetic properties of the MDMA enantiomers may be caused by enantioselective metabolism by CYP2C19 and CYP2D6.
An Improved Physics-Informed Neural Network Based on a New Adaptive Gradient Descent Algorithm for Solving Partial Differential Equations of Nonlinear Systems

: Physics-Informed Neural Networks (PINNs) are becoming more and more popular for solving partial differential equations (PDEs) of nonlinear systems. Due to the advantage of low computational cost, the gradient descent algorithm coupled with the weighted objectives method is usually used to optimize loss functions in the PINN training. However, the interaction mechanisms between the gradients of loss functions are not fully clarified, leading to poor performances in loss functions optimization such as low efficiency and non-convergence. For this, an adaptive gradient descent algorithm (AGDA) is proposed, and then validated by analytical PDEs and Navier-Stokes equations. Firstly, the interaction mechanisms of loss functions gradients in the PINN training based on the traditional Adam optimizer are analyzed. The main factors responsible for the poor performances of the Adam optimizer are identified. Based on the interaction mechanisms, a new AGDA optimizer is developed for the PINN training by two steps: 1) balancing the magnitude difference of loss functions gradients; 2) eliminating the gradient directions conflict. Then, three types of PDEs (elliptic, hyperbolic and parabolic) and three two-dimensional incompressible Navier-Stokes equations are selected to validate the proposed algorithm. It is found that the AGDA optimizer can achieve higher training accuracy with fewer iterations, and can improve the training efficiency of the analytical PDEs by 5~6 times and the multi-parameter Navier-Stokes equations by 1.4 times. Also, the AGDA optimizer is more robust as it performs better than the traditional Adam optimizer in dealing with the parabolic heat conduction equation and the unsteady Navier-Stokes equation.
Chaos–hologram: a novel technique in encryption information

In this work, hologram-chaos technique was used to encrypt information as one of the hologram applications using MATLAB program. The results showed that the information to be transmitted in complete secrecy can be easily identified using computer generated holograms through the process of computer hologram reconstruction, so this technique is not able to guarantee the confidentiality of information transmission. When coupling the hologram technology with the chaotic Lorenz system by performing several arithmetic operations of addition, multiplication and division for the matrices of Fourier transforms of the information to be sent (the Mona Lisa image) and the hologram of the Lorenz system, the results showed a complete encryption of the images to be sent and the disappearance of their features using the division process.
Effect of Mutations in the Mouse Hepatitis Virus 3′(+)42 Protein Binding Element on RNA Replication

ABSTRACT The mouse hepatitis virus (MHV) genome's 3′ untranslated region contains cis-acting sequences necessary for replication. Studies of MHV and other coronaviruses have indicated a role for RNA secondary and tertiary elements in replication. Previous work in our laboratory has identified four proteins which form ribonucleoprotein complexes with the 3′-terminal 42 nucleotides [3′(+)42] of the MHV genome. Defective interfering (DI) RNA replication assays have demonstrated a role for the 3′(+)42 host protein binding element in the MHV life cycle. Using gel mobility shift RNase T1 protection assays and secondary structure modeling, we have characterized a possible role for RNA secondary structure in host protein binding to the 3′-terminal 42-nucleotide element. Additionally we have identified a role for the 3′-terminal 42-nucleotide host protein binding element in RNA replication and transcription using DI RNA replication assays and targeted recombination and by directly constructing mutants in this protein binding element using a recently described MHV reverse genetic system. DI RNA replication assays demonstrated that mutations in the 3′(+)42 host protein binding element had a deleterious effect on the accumulation of DI RNA. When the identical mutations were directly inserted into the MHV genome, most mutant genomes were viable but formed smaller plaques than the wild-type parent virus. One mutant was not viable. This mutant directed the synthesis of genome-sized negative-sense RNA approximately as efficiently as the wild type did but had a defect in subgenomic mRNA synthesis. These results point to a potential role for sequences at the extreme 3′ end of the MHV genome in subgenomic RNA synthesis.
Pico-Light H 2 O: Intercomparison of in situ water vapour measurements during the AsA 2022 campaign.

The mid-infrared lightweight stratospheric hygrometer, “Pico-Light H 2 O”, the successor of Pico-SDLA H 2 O, is 15 presented and its performances are evaluated during the AsA 2022 balloon-borne intercomparison campaign conducted at the CNES Aire-sur-l'Adour (AsA) balloon launch facility and the Aeroclub d'Aire-sur-l'Adour. The Pico-Light instrument has primarily been developed for sounding of the upper troposphere and stratosphere. Though, during the AsA 2022 campaign we expand the range of comparison including the lower troposphere additionally. Three different types of hygrometers and two models of radiosonde were flown, operated by the French Space Agency (CNES) and the NOAA 20 Global Monitoring Laboratory
OSMOTIC COMPUTING ENHANCEMENT BASED ON BLOCKCHAIN APPROACH

Osmotic computing is an emerging concept for managing aggressively distributed IoT applications facilitating IoT ecosystem to compensate the limitation of computational, power consumption resources’ capabilities offer the extension for IoT system to use the power of IoT, edge, and cloud resources within a federated environment to grantee utilization and efficiency of these re-sources. In essence, osmotic computing solves end-to-end IoT solution issues related to the orchestration, deployment, and reconfiguration of osmotic abstraction microelements (MELs) that are constructed and federated across cloud, edge and IoT infrastructures. In consequence, while enabling the dynamic orchestration of the osmotic resources, there is opportunity for attacks and security threats resulting from the continuous reconfiguration of the osmotic topology where providing security and privacy is a key issue in which malicious software/hardware injection at-tacks are compromising data security, integrity, and confidentiality. Blockchain is a fundamental technology, as a distributed and decentralized ledger, is a nominated solution to face the security limitations of osmotic computing solution. The objective of this research is to propose a new blockchain based osmotic computing architecture to leverage private permissioned Hyperledger Fabric (HLF) blockchain aiming to present a security guard by tracking MELs operations into the blockchain ledger to offer authorized access control and establish the root of trust for applying the principal features of traceability, immutability, transparency, and auditability. The implemented architecture prototype is tested on both simulated and real-life environments to validate the architecture hypothesis of running a transparent and traceable osmotic IoT ecosystem maintaining the required security levels.
Characteristics of Liquid Film Thickness of Air-Water Annular Two-Phase Flow in a Helically Coiled Tube. Horizontal Coil.

Experimental study has been carried out to clarify the characteristics of the liquid film thickness of air-water two-phase flow in helically coiled tubes of 500 and 1000mm coil diameters and 25mm tube diameter. The wave of liquid film on the outer side of a coil differs from that on the inner side in not only the wave height but also the wave shape. The liquid flow rate does not affect the film thickness at the inner side, whereas at the bottom and the outer side, it makes the film thicker. The center of gravity of liquid film is in the region about 45 degrees inward from the top or the bottom of the tube. The coil diameter has little effect on the characteristics of the liquid film.
Intracranial Subarachnoid Space MR-Guided Catheter Navigation of the

Summary: Percutaneous intraspinal navigation (PIN) is a new minimally invasive approach to the CNS. The authors studied the utility of MR-guided intracranial navigation following access to the subarachnoid compartment via PIN. The passive tracking technique was employed to visualize devices during intracranial navigation. Under steady-state free precession (SSFP) MR-guidance a microcatheter-mi-croguidewire was successfully navigated to multiple brain foci in two cadavers. SSFP MR fluoroscopy possesses adequate contrast and temporal resolution to allow MR-guided intracranial navigation.
MIT Open Access Articles Dynamical zeta functions for Anosov flows via microlocal analysis

The purpose of this paper is to give a short microlocal proof of the meromorphic continuation of the Ruelle zeta function for C ∞ Anosov ﬂows. More general results have been recently proved by Giulietti–Liverani–Pollicott [GiLiPo] but our approach is diﬀerent and is based on the study of the generator of the ﬂow as a semiclassical diﬀerential operator.