Miracle-dz/UniFAR-FTUs huggingface dataset:
Effective fine-tuning training of deep Boltzmann machine based on spatial Monte Carlo integration

: A deep Boltzmann machine (DBM) is a probabilistic deep learning model; DBM learning consists pretraining and ﬁne-tuning stages. This study focuses on the ﬁne-tuning stage, and it develops a new and eﬀective ﬁne-tuning method based on spatial Monte Carlo integration (SMCI), which is an extension of the standard Monte Carlo integration (MCI). It has been proved that SMCI is statistically more accurate than the standard MCI. Fine-tuning methods based on ﬁrst-order and semi-second-order SMCI methods are formulated. The numerical experiments demonstrate that the proposed ﬁne-tuning methods are superior to the conventional method in terms of both training and generalization errors.
Studying the drying mechanism of microalgae Chlorella vulgaris and the optimum drying temperature to preserve quality characteristics

ABSTRACT Drying harvested microalgae from an average moisture content of 80% wet basis to a safe moisture content of 10% is challenging. Removing this high amount of water from microalgal biomass is time-consuming and is not as easy as agricultural crop dehydration. The long drying time results in large drying costs. Although drying is a suitable technique for algal-based fuel production, it has not been commercialized due to its associated challenges. This study was performed to fulfill the knowledge gap in the microalgae drying mechanism and to understand the reason for long drying times. For this purpose, the thin-layer drying of microalgae Chlorella vulgaris at the temperature range of 40 to 140°C was studied in a convective oven. The effect of drying air temperature on Chlorella elemental and chemical composition, surface color, and surface structure in the aforementioned temperature range was also analyzed. The results revealed that the dominant mechanism in Chlorella drying is diffusion, which is attributed to the collapse of microalgal cells structure with increased drying temperature. In fact, moisture is entrapped in the Chlorella cells and it takes a long time for them to reach the biomass surface and evaporate. The result was that both low and high drying temperatures have adverse effects on Chlorella surface color, structure, and carbohydrate and lipid composition. This suggests that microalgae should be dried at an optimum medium (60–80°C) temperature.
Linking the Determinants of Online Shopping Behavior, Full Nest Consumers, and Behavioral Intentions - A Conceptual Review and Framework

Consumer shopping behavior is a complex process, and several factors affect purchase decisions. In recent times, there is a drastic shift in consumer buying behavior due to technological advancements and mobile shopping applications, and consumers are very much concerned about their purchase decisions of what, where, and how to buy. Online shopping outlets use both push and pull marketing strategies for a wide range of products. Hence, online sellers redefined the business model by making consumers actively visit their online stores even though they do not intend to buy anything. Most of the time, the sellers create the demand traffic; also, impulsive purchases are made by the consumers due to the 'online deals' or 'deal of the day. ' Several studies have reported that the family life cycle's role is vital in understanding the consumer market for devising marketing strategies to satisfy various consumer groups' needs. The consumer needs want, and preferences change when they move on to the next stage of the family life cycle. Thus, this study aims to draw a theoretical link between the full nest consumers, online shopping behavior determinants, and online shopping behavioral intentions by proposing a conceptual framework with research propositions. The study identified the key determinants that affect the online shopping behavioral intentions, and the appropriate theoretical linkages were provided with respect to the full nest consumers.
Simultaneous Electrocatalytic CO2 Reduction and Enhanced Electrochromic Effect at WO3 Nanostructured Electrodes in Acetonitrile

Serious concerns about climate change make the reutilization of CO2 particularly attractive; one option for reutilization is the electroreduction of CO2 in acetonitrile solutions on a range of electrode materials. Among them, transition-metal oxides stand out as cost-effective alternatives. In this context, the electrocatalytic activity of nanostructured WO3 electrodes for carbon dioxide reduction in both humid and dry acetonitrile media has been addressed by using electrochemical and spectroelectrochemical measurements. Importantly the cathodic faradaic process starts at potentials as high as −0.16 V vs SHE. Gas chromatography measurements show CO as being the main product in both dry and humid acetonitrile, together with formate in the presence of humidity. Interestingly, purging with CO2 causes not only the appearance of cathodic faradaic currents but also an increase in capacitive currents, which are directly associated with an enhanced electrochromic effect. The ICP-MS determination of tungsten upon .
Effect of pruning and spraying with N , Ca and GA3 on some characters of fruits and percentage of cracking offig cv. Asowd Diala .

An experiment was conducted on private orchard at AlAbbasyia / Nijaf on 15/1/ at 2009 and 2010 respectively to investigate the effects of pruning 50 % and spraying with N , Ca and GA3 at conc. Of 0.3% , 1%, 200 mg/L each ather in single way or combination on the leaf area , total chlorophyll , percentage of carbohydrate , calcium pictate , Firmness , type of crackings and total crackings on ripe Fruits of Fig cv. Aswod Diala . Results indicated that Fruits of treated trees with nitrogen was increased the kinds of crackings , total percentage of crackings and decreased the Calcium pictate and Firmness siginificantly compared with control treatment . Treatmented trees with pruning , Ca and GA3 in single way or combination together with N produced a siginificat increase in leaf area , total chlorophyll and contening Fruits from percentage of carbohydrate , calcium pictate , Firmness and reducing percentage of type of crackings and total crackings compared with control treatment . The treatment of ( P + N + Ca + GA3 ) was siginificantly increased leaf area , total chlorophyll , percentage of carbohydrate , calcium pictate , Firmness , which were (7.54 m 2 /tree , 115.42 mg / 100g .32.42 % ,o.431kg/cm 2 , 3.82 % ) and (8.86 m 2 /tree , 114.17 mg / 100g , 22.31 % , 0.422 kg/cm 2 ,3.66 % ) for the two growing seasons , respectively and , this treatment gave the lowest percentage of lengitudial , tertiary , quaternary , basal cracking's and total cracking which were ( 1.84 , 1.67 . 1.48 , 0.44 , 5.43 ) % and ( 1.79 , 1.72 , 1.76 , 0.50 , 5.77 )% for both seasons respectively .
Multi-Objective Multi-Dimensional Transportation: A Case Study to the Flow of the Commodities of the Main Roads to Main Nodes in the North Western Coastal Strip of Egypt

The distribution of merchandises and commodities from source towns to final destinations is a vital issue. The job of transporter’s decisions can be optimized by reformulating the transportation problem as generalization of the classical transportation problems. Multiobjective multi-dimensional transportation network is considered the extension of conventional two-dimensional transportation network and is convenient for dealing with transportation systems with multiple supply nodes, multiple demand nodes, as well as diverse modes of transportation demands or delivering multiple kinds of merchandises. In this study, we implement an improved Biogeography based optimization IBBO to the flow of the commodities of the main roads to main nodes in the North Western Coastal Strip of Egypt, where there are four main roads and three nodes. The proposed algorithm incorporates the dominance criteria to handle multiple objective functions which enable the decision maker to cover all the Pareto frontier of the problem which have a large-scale size. Numerical results were reported in order to establish the real computational burden of the proposed algorithm and to assess its convergence performances for solving real geographical problem.
Preparation of Ti/CFRTP joint strengthened by carbon fiber cloth

A Ti/CF/CFRTP joint method was suggested for the carbon fiber reinforced thermoplastic ABS polymer (CFRTP), and titanium (Ti) with extremely large friction force induced by broad interface of carbon fiber cloth. The tensile stress-strain curves of Ti/CF/CFRTP joint prepared by lamination method by ABS plates and CF-cloth sheets were obtained. The maximum tensile strength and its strain in Ti/CF/CFRTP joint were extremely higher than those of Ti/ABS joints prepared by wrap-casting and gluing. Developing the joint improved the safety level of tensile strength.
La localisation des écoles primaires et le bruit aérien dans la région métropolitaine
 de Toronto : un diagnostic d’équité environnementale et une analyse des impacts sur la
 réussite scolaire

Cet article poursuit deux objectifs. Premierement, il s’agit de verifier si les ecoles primaires accueillant des enfants issus de milieux defavorises sont disproportionnellement localisees a proximite des aeroports, dans la region metropolitaine de Toronto. Deuxiemement, il s’agit de verifier si les ecoles primaires avec des niveaux de bruit aerien eleves presentent des niveaux de reussite scolaire plus faibles. L’etude porte sur 1420 ecoles primaires publiques ou catholiques. Les courbes NEF ont ete utilisees comme indicateur de gene causee par le bruit des avions. Treize variables decrivant les caracteristiques des ecoles et de leur clientele ont ete recueillies au niveau de chaque etablissement pour l’annee scolaire 2017-2018 a partir de donnees du Gouvernement de l’Ontario et du Ministere de l’Education. Des tests de Student ont ete effectues pour realiser le diagnostic d’equite environnementale alors que pour evaluer l’impact du bruit aerien sur la reussite scolaire, douze modeles de regression ont ete construits. Les resultats des tests de Student demontrent que les ecoles primaires avec des niveaux plus eleves de bruit aerien accueillent une clientele plus souvent issue de milieux defavorises et d’une langue maternelle autre que la langue d’enseignement. Concernant la reussite scolaire, les ecoles dans la zone NEF presentent des taux de reussite significativement plus faibles. Par contre, une fois controlees les caracteristiques sociodemographiques, le bruit aerien n’est plus significativement associe a des taux de reussite plus faibles.
The Digital Traces’ Diamond. A Proposal to Put Together a Quantitative Approach, Interpretive Methods, and Computational Tools

The paper aims to suggest a simple model for the interpretation of digital traces as a source of data in Social Science research. Digital traces are very interesting because in the sociological tradition there is no extensive use of traces: the great part of sociological methods prefer direct and indirect strategies of data collections. But today digital traces are important because the technological environment of the Digital Society produces a great number of digital traces that are an important source of data. While in sociology there is a little debate in the use of traces, in the Social Sciences and humanities there are several traditions in the interpretation of trace, and we focus our attention on the most interesting: the ethnomethodology, the school of suspicion, the interpretive anthropology, the evidential paradigm. What these traditions have in common is their interest in abductive reasoning or the way to use partial information to build probabilistic knowledge, a typical strategy of hunters, detectives, and physicians, archetypes of the social theory of traces. Then we propose a model for the interpretation of digital traces that is inspired by the cultural diamond of Wendy Griswold and for this reason we call it the digital traces’ diamond. Then we use a series of case study to describe how the proposed model works and how can be useful for the use of digital traces as a source of data.
A Strategy Tripod Perspective on ISO 9001 Adoption: Evidence From Chinese Manufacturing Firms

This article examined the factors at different levels of ISO 9001 adoption and their interaction effects through the integration of resource-, industry-, and institution-based views (i.e., a strategic tripod perspective) and performance implications of ISO 9001 adoption in the Chinese context. A longitudinal data of manufacturing firms were collected. The results showed that potential and available slack, as well as industrial munificence, have a negative impact, while institutional development has a positive effect on ISO 9001 adoption. ISO 9001 adoption is also affected by the various interacting effects of resource, industry, and institution-based factors. Finally, ISO 9001 adoption affects long-term sustainable growth positively but has no significant effect on short-term performance. Our findings provided new theoretical insights into the antecedents at different levels of ISO 9001 adoption and their interacting effects based on a strategic tripod perspective and expanded the understanding of its performance outcomes.
Genotype environment interaction analysis for fruit yield in okra (Abelmoschus esculentus L.) under alkaline environments

Twenty four Okra genotypes were evaluated for marketable fruit yield and its related traits for genotype environment interaction during 2015-16 and 2016-17. The genotypes were exposed to alkaline environment with a pH range of 8.0±0.2, 8.5±0.2, 9.0±0.2 and 9.5±0.2. A significant level of deviation in expression of different traits was observed in all the genotypes with increasing pH. Based on Additive Main Effects and Multiplicative Interaction (AMMI), Genotype and Genotype Environment Interaction (GGE) biplot, Wrick’s ecovalence (Wi2 ), AMMI Stability Value (ASV) and Yield Stability Index (YSi) stable genotypes with high fruit yield were identified over the eight environments. The combined AMMI analysis of variance indicated that genotype main effect, environment and genotype-by-environment interaction effects showed variation of 19.83%, 63.07% and 17.10%, respectively for fruit yield. On the basis of different stability measures, VRO-112, VRO-110, Kashi Kranti, VROB178, AE-70 and VRO-108 were differentiated as high yielding and stable genotypes over the tested environments. This study will be helpful for selecting alkali tolerant okra parents for further breeding programme and recommending the suitable genotypes for alkalinity prone area
Identification method for polynomially parametrized LTI systems based on exhaustive modelling with algebraic elimination

: Realization problems of impulse responses for linear time-invariant (LTI) systems are well-studied. In particular, the realizations with the least order of such systems are said to be minimal. Apart from these problems, parameter estimations of pre-deﬁned LTI models with a speciﬁc parametrization of the system matrices are also important. In this paper, we propose a parameter estimation method for such LTI models by transforming a minimal realization obtained through black-box identiﬁcations. Our approach is based on the minimal realization theory, exhaustive modelling, and algebraic elimination. Contrary to the existing methods, the proposed method allows polynomial parametrizations of the system.
Robust Predictive Control Scheme for Permanent-Magnet Synchronous Generators Based Modern Wind Turbines

In this article, a deadbeat predictive control (DB-PC) strategy for permanent-magnet synchronous generators (PMSGs)-based modern wind turbines is proposed. The main advantages of the DB-PC technique are its excellent dynamics and its constant switching frequency. However, the main idea of DB-PC is obtaining the actuation voltage for the next sample from the mathematical model of the generator. Therefore, the DB-PC is highly sensitive to mismatches in the parameters of the PMSG. In order to obviate this problem, a disturbance estimator (extended Kalman filter (EKF)) is employed in this work to enhance the robustness of the proposed DB-PC scheme by estimating the total disturbance due to parameter mismatches and adding it to the calculation of the actuation voltage. Furthermore, the same EKF observe the rotor speed and position of the PMSG, i.e., mechanical sensors are not required. Moreover, the EKF is able to reduce the harmonic distortion in the stator currents of the PMSG. The proposed DB-PC strategy is implemented in the laboratory. The experimental results proved the superiority of the proposed DB-PC strategy over the traditional DB-PC technique.
Designing and evaluating the profitability of linear trading system based on the technical analysis and correctional property

Traders in the capital market always seek methods to make full use of available information and combine them to find the best buying and selling strategy. The present study uses a linear hybrid system to combine 106 signals from moving averages oscillators and RSI signals in the technical analysis along with two buy and sell bonds. In addition, the system has correctional property and modifies its parameters over time and according to new information. The result of the research on the Tehran Exchange overall index in the period 1380 to 1397 indicates that the system after the optimal training on training data has an average of daily returns of 0/0025, 0/0048 risk, and a daily Sharp ratio of 0/52, which is better than the individual performance of each signal and market performance in daily average return and sharp ratio criterion.
Novel Spectrophotometric Method Development for the Estimation of Boceprevir in Bulk and in Pharmaceutical Formulations

A New, Simple, Rapid and economical extractive spectrophotometric methods were developed for the determination of Boceprevir (anti-retroviral drug). Boceprevir is a direct acting protease inhibitor for the treatment of hepatitis C. It also has two isomers in which the S isomer is more active than the R-isomer. The methods were based on the formation of color chromogens with Bromo cresol green, Bromo thymol blue, Bromo phenol blue and Methyl orange indicator. The extractive spectrophotometry was carried out with phthalate buffer and chloroform. The absorbances of the chromogens were measured at 410 nm and 415 nm against the corresponding reagent blank. The proposed methods have been successfully applied to the bulk drug. The method has been statistically evaluated and was found to be precise and accurate.
Cross refinement network with edge detection for salient object detection

National Natural Science Foundation of China China, Grant/Award Number: 62076075 Abstract Salient object detection aims to identify the most attractive objects from images. However, their boundaries are typically of poor quality when predicted using available methods. One or multiple objects may also be left undetected if the image contains multiple objects. To solve these problems, this article proposes the novel cross refinement network, which consists of a Res2Net‐based backbone network; a fusion network equipped with four convolutional block attention modules and four edge‐salient cross units; and a detection network with an edge enhancement unit and a residual refinement network (RNN). For RNN training, the rough salient maps generated using the DUTS‐TR dataset are treated as a special training dataset. Compared to existing methods, the proposed network can effectively detect all objects as well as improve the boundaries of the detected objects by performing experiments on five benchmark datasets. Based on the experimental results, the proposed network outperforms existing methods both objectively and subjectively.
Mass Balance Analysis of Decomposed Refuse in Laboratory Scale Lysimeters

Decomposition of shredded municipal refuse was studied under laboratory conditions with leachate recycle and neutralization. Cellulose and hemicellulose accounted for 91% of the methane potential of refuse and mineralization of 72% of these constituents was measured in a container sampled after 111 days. Carbon recoveries of 64% to 111% were obtained from mass balances on the decomposed refuse. The measured methane yield was between 77 and 107 liters CH 4 /dry kg of refuse. Mass balances showed that the oxygen and nitrate present in fresh refuse were sufficient for oxidation to CO 2 of only 2% of the initial sugar concentration. This imbalance explained an observed accumulation of carboxylic acids. Mass balances are a valid technique for estimation of the methane potential of landfills.
BinDiffNN: Learning Distributed Representation of Assembly for Robust Binary Diffing Against Semantic Differences

Binary diffing is a process to discover the differences and similarities in functionality between two binary programs. Previous research on binary diffing approaches it as a <italic>function matching</italic> problem to formulate an initial 1:1 mapping between functions, and later a sequence matching ratio is computed to classify two functions being an <italic>exact</italic> match, a <italic>partial</italic> match or <italic>no-match</italic>. The accuracy of existing techniques is best only when detecting exact matches and they are not efficient in detecting partially changed functions; especially those with minor patches. These drawbacks are due to two major challenges (i) In the 1:1 mapping phase, using a strict policy to match function features (ii) In the classification phase, considering an assembly snippet as a normal text, and using sequence matching for similarity comparison. Instruction has a unique structure i.e. mnemonics and registers have a specific position in instruction and also have a semantic relationship, which makes assembly code different from general text. Sequence matching performs best for general text but it fails to detect structural and semantic changes at an instruction level thus, its use for classification produces many false results. In this research, we have addressed the aforementioned underlying challenges by proposing a two-fold solution. For the 1:1 mapping phase, we have proposed computationally inexpensive features, which are compared with distance-based selection criteria to map similar functions and filter unmatched functions. For the classification phase, we have proposed a Siamese binary-classification neural network where each branch is an attention-based distributed learning embedding neural network — that learn the semantic similarity among assembly instructions, learn to highlight the changes at an instruction level and a final stage fully connected layer learn to accurately classify two 1:1 mapped function either an <italic>exact</italic> or a partial match. We have used x86 kernel binaries for training and achieved <inline-formula><tex-math notation="LaTeX">$\sim 99\%$</tex-math><alternatives><mml:math><mml:mrow><mml:mo>∼</mml:mo><mml:mn>99</mml:mn><mml:mo>%</mml:mo></mml:mrow></mml:math><inline-graphic xlink:href="oh-ieq1-3093926.gif"/></alternatives></inline-formula> classification accuracy; which is higher than existing binary <italic>diffing</italic> techniques and tools.