Miracle-dz/UniFAR-FTUs huggingface dataset:
A Dynamic Resource-Aware Routing Protocol in Resource-Constrained Opportunistic Networks

: Recently, Opportunistic Networks (OppNets) are considered to be one of the most attractive developments of Mobile Ad Hoc Networks that have arisen thanks to the development of intelligent devices. OppNets are characterized by a rough and dynamic topology as well as unpredictable contacts and contact times. Data is forwarded and stored in intermediate nodes until the next opportunity occurs. Therefore, achieving a high delivery ratio in OppNets is a challenging issue. It is imperative that any routing protocol use network resources, as far as they are available, in order to achieve higher network performance. In this article, we introduce the Resource-Aware Routing (ReAR) protocol which dynamically controls the buffer usage with the aim of balancing the load in resource-constrained, stateless and non-social OppNets. The ReAR protocol invokes our recently introduced mutual information-based weighting approach to estimate the impact of the buffer size on the network performance and ultimately to regulate the buffer consumption in real time. The proposed routing protocol is proofed conceptually and simu-lated using the Opportunistic Network Environment simulator. Experiments show that the ReAR protocol outperforms a set of well-known routing protocols such as EBR, Epidemic MaxProp, energy-aware Spray and Wait and energy-aware PRoPHET in terms of message delivery ratio and overhead ratio.
Abiotic and Biotic Damage of Microalgae Generate Different Volatile Organic Compounds (VOCs) for Early Diagnosis of Algal Cultures for Biofuel Production

Open microalgal ponds used in industrial biomass production are susceptible to a number of biotic and abiotic environmental stressors (e.g., grazers, pathogens, pH, temperature, etc.) resulting in pond crashes with high economic costs. Identification of signature chemicals to aid in rapid, non-invasive, and accurate identification of the stressors would facilitate targeted and effective treatment to save the algal crop from a catastrophic crash. Specifically, we were interested in identifying volatile organic compounds (VOCs) that can be used to as an early diagnostic for algal crop damage. Cultures of Microchloropsis gaditana were subjected to two forms of algal crop damage: (1) active grazing by the marine rotifer, Brachionus plicatilis, or (2) repeated freeze–thaw cycles. VOCs emitted above the headspace of these algal cultures were collected using fieldable solid phase microextraction (SPME) fibers. An untargeted analysis and identification of VOCs was conducted using gas chromatography-mass spectrometry (GC-MS). Diagnostic VOCs unique to each algal crop damage mechanism were identified. Active rotifer grazing of M. gaditana was characterized by the appearance of carotenoid degradation products, including β-cyclocitral and various alkenes. Freeze–thaw algae produced a different set of VOCs, including palmitoleic acid. Both rotifer grazing and freeze–thawed algae produced β-ionone as a VOC, possibly suggesting a common stress-induced cellular mechanism. Importantly, these identified VOCs were all absent from healthy algal cultures of M. gaditana. Early detection of biotic or abiotic environmental stressors will facilitate early diagnosis and application of targeted treatments to prevent algal pond crashes. Thus, our work further supports the use of VOCs for monitoring the health of algal ponds to ultimately enhance algal crop yields for production of biofuel.
Business Intelligence and Business Value in Organisations: A Systematic Literature Review

Organisations must derive adequate business value (BV) from Business Intelligence (BI) adoption to retain their profitability and long-term sustainability. Yet, the nuances that define the realisation of BV from BI are still not understood by many organisations that have adopted BI. This paper aims to foster a deeper understanding of the relationship between Business Intelligence (BI) and business value (BV) by focusing on the theories that have been used, the critical factors of BV derivation, the inhibitors of BV, and the different forms of BV. To do this, a systematic literature review (SLR) methodology was adopted. Articles were retrieved from three scholarly databases, namely Google Scholar, Scopus, and Science Direct, based on relevant search strings. Inclusion and exclusion criteria were applied to select ninety-three (93) papers as the primary studies. We found that the most used theoretical frameworks in studies on BI and BV are the Resource-Based View (RBV), Dynamic Capabilities Theory (DCT), Technology-Organisation-Environment (TOE), and Contingency Theory (CON). The most acknowledged critical factors of BV are skilled human capital, BI Infrastructure, data quality, BI application and usage/data culture, BI alignment with organisational goals, and top management support. The most acclaimed inhibitors of BV are data quality and handling, data security and protection, lack of BI Infrastructure, and lack of skilled human resource capital, while customer intelligence is the most acknowledged form of BV. So far, many theories that are relevant to BI and BV, critical factors, inhibitors, and forms of BV were marginally mentioned in the literature, requiring more investigations. The study reveals opportunities for future research that can be explored to gain a deeper understanding of the issues of BV derivation from BI. It also offers useful insights for adopters of BI, BI researchers, and BI practitioners.
A Generic Process Model for Sociocultural Data Collection and Decision Making in Facility Programming

This is the third paper in a trilogy of papers that started with developing the philosophical and theoretical foundations for the study of sociospatial interactions. In the second paper, we created a guiding framework for facilities programming information collection and decision making. In this paper, we use that guiding framework and develop a process model for the programming process. Our methodology involves systems theory, activity theory, and task analysis. We present a generic model of the data collection process in facilities programming. This model delineates process steps, their sequence, and their content. The intent of this model is to provide structure and content suggestions for developing project-specific facilities programing research designs for information collection, processing, and programmatic decision-making. It is a plan for action, articulated and explicated so that professional programmers can use it as a template for organizing their work. This process model is tentative and general, intended as a guide for creating customized process designs for each programming project, considering the specifics of the building type and the programming situation.
Energy Efficient Cluster-Based Optimal Resource Management in IoT Environment

: Internet of Things (IoT) is a technological revolution that redefined communication and computation of modern era. IoT generally refers to a network of gadgets linked via wireless network and communicates via internet. Resource management, especially energy management, is a critical issue when designing IoT devices. Several studies reported that clustering and routing are energy efficient solutions for optimal management of resources in IoT environment. In this point of view, the current study devises a new Energy-Efficient Clustering-based Routing technique for Resource Management i.e., EECBRM in IoT environment. The proposed EECBRM model has three stages namely, fuzzy logic-based clustering, Lion Whale Optimization with Tumbling (LWOT)-based routing and cluster maintenance phase. The proposed EECBRM model was validated through a series of experiments and the results were verified under several aspects. EECBRM model was compared with existing methods in terms of energy efficiency, delay, number of data transmission, and network lifetime. When simulated, in comparison with other methods, EECBRM model yielded excellent results in a significant manner. Thus, the efficiency of the proposed model is established.
Effectiveness of Seed priming with Polyamines in Decreasing Drought Stress Adversities in Two Wheat Cultivars

Two cultivars of bread Wheat (Triticum aestivum), Miser2 and Sakha 94 (Differ in their drought tolerance) were selected for drought and Polyamines (PAs) treatment. Seeds of both cultivars were presoaked in water or 100 μM solutions of either putrescine (put) spermines (spm) separately or in mixture for 10 h. Thereafter, all seedlings (OR) germinated seeds were restricted to drought by withholding water beginning from the seventh day after sowing (DAS) for a total experimental period of 21days. The results revealed that drought caused significant decrease in growth parameters, pigments, total protein contents, total insoluble sugars, antioxidant enzymes activities and membrane stability index in both cultivars. The decrease was more pronounced in Sakha94.The level of proline, total soluble sugars, H2O2 and lipid peroxidation increased under drought stress in Misr2 more than in Sakha 94 confirming thatMisr2 is more tolerant. Presoaking seeds in putrescine solutions accumulated pigments, proline, soluble and insoluble sugars and total protein however; it decreased H2O2 content and lipid peroxidation in Sakha 94, but soaking in spermine increased catalase activity while pretreatment with the mixture increased guaiacol peroxidase activity in Sakha94 only. The little effect of presoaking with polyamines was most detected in Misr2. In conclusion, presoaking with spm and/ or put play to some extent a protective role against drought stress through improving plant tolerance. This response differs according to the cultivar but more future research will be carried about PAs application as foliar spray.
An Efficient Energy Aware Routing Mechanism for Wireless Body Area Networks

The accelerated development of wireless network technology has resulted in the emergence of Wireless Body Area Network (WBAN), which is a technology commonly used in the medical field. WBAN consists of tiny sensor nodes that interconnect with each other and set in the human body to collect and transmit the patient data to the physician, to monitor the patients remotely. These nodes typically have limited battery energy that led to a shortage of network lifetime. Therefore, energy efficiency is considered one of the most demanding challenges in routing design for WBAN. Many proposed routing mechanisms inWBAN did not cover the source node energy and energy harvesting techniques. Therefore, this study proposes an Efficient Energy Aware Routing (EEAR) mechanism. This paper constructs a path cost function that considers three parameters: residual energy, number of hops to the sink, and the distance between the nodes. Besides, data aggregationwith filtration and hybrid energy harvesting technique are used to extend the network lifetime, reduce the network traffic load, and maintain the source node energy. Extensive simulations using MATLAB have been performed to evaluate the performance of the proposed mechanism. EEAR is contrasted with the two latest schemes, called Priority-based Congestion-avoidance Routing Protocol (PCRP) and Energy Efficient Routing Protocol (EERP). The results show the significant performance of the EEARmechanism in terms of network lifetime, residual energy, network stability, and throughput.
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Design and Implementation of Asymmetric Cascaded Multilevel Inverter with Optimal Components

Abstract A novel asymmetrical cascaded one-twenty-five level multilevel inverter is proposed with optimal components. The proposed inverter consists of three sub-cells connected asymmetrical configuration to generate a 125-level output voltage. The sub-cell comprises six power switches and two DC sources to produce five output voltage levels with symmetrical configuration. This paper presents the five, twenty-five, one-twenty five-level inverters with optimal components with very lower harmonics. The results of the proposed inverters are experimentally tested with linear and non-linear loads. During dynamic circumstances, the suggested inverters are extremely stable. The proposed inverters will generate a greater voltage level with nominal harmonics as per IEEE standards. A complete comparison is made with previously published similar MLIs with proposed twenty-five MLI. The Proposed MLI has several merits such as cost factor, optimal components, THD, and TSV. The proposed five, twenty-five, and one-twenty-five level inverters are experimentally implemented with the help of the dSPACE RTI1104 controller. The proposed inverters are well suited for grid-connected and renewable applications.
Metaanalysis of the Influence of Problem-Based Learning Model on Mathematic Problem Solving Ability

This study aims to determine: (1) Analyzing the effect size of the Problem-based Learning model on students' mathematical problem solving abilities; (2) To find out the meta-analysis of the effect of the problem-based learning model on students' mathematical problem solving abilities. Researchers meta-analyze journals about the effect of problem-based learning model on mathematical problem solving abilities with quantitative descriptive methods. The results showed that: (1) Of the 14 studies that met the criteria for a meta-analysis of the problem-based learning model in improving the mathematical problem solving ability of junior high school students, the highest effect size was 0.92; (2) The results of the meta-analysis of learning models on mathematical problem solving abilities are included in the large category with r RE = 0.53.
Public Perception Influence on the Reshaping Urban Heritage: A Case Study of Port Said Historic Quarters

Cultural heritage plays an important role in reshaping cities’ current morphologies, reinforcing public sense of belonging, cultural identity, and place authenticity. Port Said, the research case study, a former colonial city located at the edge of the Mediterranean Sea and the Suez Canal at the north east Egyptian coast, is struggling between new urban sprawl that obliterates its identity and urban heritage preservation. Port Said is an important logistic city distinguished by its unique urban heritage, facing a real threat of heritage obliteration. There is a continuous fight between nostalgic memories, modern life style dreams, and aimed economic benefit. Although there is an international developing agenda for the preservation of tangible urban heritage, the local community can barely interfere with reshaping of urban heritage in the modern society. It is urgent to create public awareness and heritage guardians in developing countries as the economic benefits strongly demolish heritage, ignoring their significance and peculiarity. This research aims to investigate the city’s historical and urban development with special emphasis on buildings’ visual characteristics and architectural features. Visual preference survey research methodology is used to study public perception influence toward reshaping city historical image. The current study employs both qualitative and quantitative tactics in data collection to examine the research hypotheses and to achieve organized and rational local perception about Egyptian building heritage development. Finally, conclusions are drawn about the joining of current public perception of the Port Said heritages, urban identity and city unique reshaping and development.
Real-Time Network Intrusion Prevention System Using Incremental Feature Generation

: Security measures are urgently required to mitigate the recent rapid increase in network security attacks. Although methods employing machine learning have been researched and developed to detect various network attacks effectively, these are passive approaches that cannot protect the network from attacks, but detect them after the end of the session. Since such passive approaches cannot provide fundamental security solutions, we propose an active approach that can prevent further damage by detecting and block-ing attacks in real time before the session ends. The proposed technology uses a two-level classifier structure: the first-stage classifier supports real-time classification, and the second-stage classifier supports accurate classification. Thus, the proposed approach can be used to determine whether an attack has occurred with high accuracy, even under heavy traffic. Through extensive evaluation, we confirm that our approach can provide a high detection rate in real time. Furthermore, because the proposed approach is fast, light, and easy to implement, it can be adopted in most existing network security equipment. Finally, we hope to mitigate the limitations of existing security systems, and expect to keep networks faster and safer from the increasing number of cyber-attacks.
Hindrance stressors, ego depletion and knowledge sharing

Purpose This study aims to use the ego depletion theory to examine the impact of hindrance stressors on knowledge sharing behaviors by investigating the mediating role of ego depletion and the moderating role of self-enhancing humor. Design/methodology/approach Data were obtained from a two-wave sample of 226 dyads, including employees in the manufacturing industry and their direct supervisors. The hypotheses were tested by hierarchical regression analyzes and Hayes’ PROCESS macro. Findings The results demonstrated that employees’ self-enhancing humor style could alleviate the impact of hindrance stressors on employees’ ego depletion state and buffer the negative indirect effect of hindrance stressors on employees’ knowledge-sharing behaviors. Research limitations/implications Although the authors collected mediator and dependent variables from different sources, this study used a cross-sectional research design, making it difficult to draw causal conclusions. Besides, hindrance stressors, ego depletion and self-enhancing humor style were all reported by employees. Originality/value Through the study, the authors highlight the important role of the self-control view in explaining proactive behavior in the workplace and a great awareness of the unforeseeable consequences of ego depletion for employees.
Molecular Advances in Larval Fruit Moth Identification to Facilitate Fruit Export From Western United States Under Systems Approaches

Abstract Molecular advances facilitate fruit export by improving rapid pest diagnosis by polymerase chain reaction (PCR) and advanced sequencing technology. Improved pest detection provides timely certification of the quarantine pest-free status in the commodity being exported, avoiding unnecessary commodity treatment. The U.S.–Japan Systems Approach to export fresh cherries from the Western United States that targets the codling moth, Cydia pomonella (Linnaeus) (Lepidoptera: Tortricidae), is used as an example. Suspect codling moth larvae interdicted at cherry packing houses are distinguished by PCR from other internal fruit moth larvae such as the oriental fruit moth, Grapholita molesta (Busck) (Lepidoptera: Tortricidae); lesser appleworm, G. prunivora (Walsh) (Lepidoptera: Tortricidae); cherry fruitworm, G. packardi (Zeller) (Lepidoptera: Tortricidae); and filbertworm, Cydia latiferreana (Walsingham) (Lepidoptera: Tortricidae). Identification is confirmed by sequencing the amplicon of a 301 bp region of the COI gene produced by PCR of the DNA from a suspect moth and comparing this sequence of COI gene sequences of other internal fruit feeders of pome fruit. This sequence comparison results in unambiguous pest identification. These findings are discussed in the context of systems approach research to meet evolving needs of phytosanitary requirements for global export of fruits.
High-Efficiency Coupled-Inductor Switched-Capacitor Boost Converter With Improved Input Current Ripple

A novel single-switch coupled-inductor switched-capacitor (CISC) high step-up converter is proposed which has a boost-type input structure allowing an improved input current ripple compared to other leading CISC converters. This is important for sustainable energy applications, such as photovoltaic (PV) cells and fuel cells where high current ripple can degrade performance or lifetime. Though large input filters can be added between the energy source and the boost converter to smooth a pulsed converter input current, the proposed converter naturally has a more moderate current ripple, reducing the need for additional filtering. With regards to the coupled inductor, the leakage inductor energy is recycled without using an extra clamped circuit, and core utilization is high. The detailed theoretical operation is presented and an experimental prototype (200 W, 36 V to 48 input, 400 V output) achieves a maximum efficiency of 97.1%.
Application of Combined In Situ Chemical Reduction and Enhanced Bioremediation to Accelerate TCE Treatment in Groundwater

Groundwater at trichloroethylene (TCE)-contaminated sites lacks electron donors, which prolongs TCE’s natural attenuation process and delays treatment. Although adding electron donors, such as emulsified oil, accelerates TCE degradation, it also causes the accumulation of hazardous metabolites such as dichloroethylene (DCE) and vinyl chloride (VC). This study combined in situ chemical reduction using organo-iron compounds with enhanced in situ bioremediation using emulsified oil to accelerate TCE removal and minimize the accumulation of DCE and VC in groundwater. A self-made soybean oil emulsion (SOE) was used as the electron donor and was added to liquid ferrous lactate (FL), the chemical reductant. The combined in situ chemical reduction and enhanced in situ bioremediation achieved favorable results in a laboratory microcosm test and in an in situ biological field pilot test. Both tests revealed that SOE+FL accelerated TCE degradation and minimized the accumulation of DCE and VC to a greater extent than SOE alone after 160 days of observation. When FL was added in the microcosm test, the pH value decreased from 6.0 to 5.5; however, during the in situ biological pilot test, the on-site groundwater pH value did not exhibit obvious changes. Given the geology of the in situ pilot test site, the SOE+FL solution that was injected underground continued to be released for at least 90 days, suggesting that the solution’s radius of influence was at least 5 m.