Miracle-dz/UniFAR-FTUs huggingface dataset:
Mitigating NDN-Based Fake Content Dissemination in Opportunistic Mobile Networks

In this work, we address the problem of Named Data Networking (NDN)-based fake content dissemination in Opportunistic Mobile Networks (OMNs), where nodes have intermittent connectivity and typically lack in end-to-end communication paths. It is important to mitigate the dissemination of such fake contents not only because they waste bandwidth for legitimate communication, but also because such files can be harmful for devices. However, the inherent characteristics of OMNs make such mitigation a challenging task. In this context, we consider a group of nodes, Fake Content Providers (FCPs), who, on receiving content requests, respond with fake contents, rather than the real version. In particular, we consider four different behaviors of the FCPs—referred to as threat scenarios—depending on whether or not they always respond to all requests with fake contents. We analyze these distinct threat scenarios, and characterize the relative performance degradation arising because of them. To mitigate the adverse effects of FCPs, we propose two schemes, wherein the identified FCPs are blacklisted permanently or temporarily, and communication with them is restricted. Results of simulation-based experiments using real-life connection traces show that, compared to the normal scenario with no FCP, the percentage of content requests satisfied decreases by 20–40 percent in the presence of 40 percent FCPs in the OMN. Moreover, in the same scenario, the average latency of content satisfaction relatively increases by up to 176 percent with respect to the normal scenario. However, on using the proposed mitigation schemes, the latency can be reduced by about 13–36 percent together with up to 9 percent improvement in the number of interests satisfied.
Journal of Human Resource Management -- HR Advances and Developments Factors of job satisfaction and its effects on employee performance: A Case Study of Ghazni University employees

Purpose - This study delves into the factors impacting job satisfaction and their subsequent effects on employee performance within the context of Ghazni University. Aims - In addition, the research also strives to assess the extent of job satisfaction and pinpoint the factors that might lead to job attrition. Design/methodology/approach - To achieve the stated goals; the participant combine comprised 110 university employees’ staff, selected through the Yamane sampling method. Employing an applied research approach, the study adopted a survey-based descriptive methodology, using a questionnaire for data collection. For analysing data using SPSS software, involving calculations of Pearson's correlation coefficient and regression analysis. Findings - The study's outcomes uncover a discernible and moderate connection (correlation coefficient of 0.589) between job satisfaction and the performance of employees. Notably, organizational factors have the most impact performance (correlation coefficient of 0.697). Group factors, demonstrate the coefficient of (0.524) with performance. And collaborative management factors exhibit a coefficient of (0.314) in correlation with performance. A more in-depth analysis of the individual components within the aforementioned factors underscores that compensation and benefits exert the most pronounced effect on both job satisfaction and employee performance. Limitations of the study - The main limitation and challenge in conducting this research was the lack of cooperation in sharing information, Still, due to the specialization of the subject, it required more understanding. Originality/value - This study offers significant insights into the essential nexus between job satisfaction and employee performance. The outcomes emphasize the pivotal role of organizational factors in nurturing both job satisfaction and overall job performance. These findings hold the potential to guide university administrators and policymakers in devising strategies aimed at elevating employee contentment, involvement, and output, thereby playing a pivotal role in bolstering the university's accomplishments and operational efficiency.
scientific statement: intravenous thrombolysis in acute ischaemic stroke

The most effective medical treatment for acute ischaemic stroke (AIS) is to offer intravenous thrombolysis during the ultra-early period of time after the onset. Even based on the Consensus of Chinese Experts on Intravenous Thrombolysis for AIS in 2012 and 2014 Chinese Guidelines on the Diagnosis and Treatment of AIS, the rate of thrombolysis for AIS in China remained around 2.4%, and the rate of intravenous tissue plasminogen activator usage was only about 1.6% in real world. The indication of thrombolysis for AIS has been expanded, and contraindications have been reduced with recently published studies. In order to facilitate the standardisation of treating AIS, improve the rate of thrombolysis and benefit patients who had a stroke, Chinese Stroke Association has organised and developed this scientific statement.
Binomial Series-Conﬂuent Hypergeometric Distribution and Its Applications on Subclasses of Multivalent Functions

: Over the past ten years, analytical functions’ reputation in the literature and their application have grown. We study some practical issues pertaining to multivalent functions with bounded boundary rotation that associate with the combination of conﬂuent hypergeometric functions and binomial series in this research. A novel subset of multivalent functions is established through the use of convolution products and speciﬁc inclusion properties are examined through the application of second order differential inequalities in the complex plane. Furthermore, for multivalent functions, we examined inclusion ﬁndings using Bernardi integral operators. Moreover, we will demonstrate how the class proposed in this study, in conjunction with the acquired results, generalizes other well-known (or recently discovered) works that are called out as exceptions in the literature.
Skin Cancer Detection and Tracking

Dense object detection and temporal tracking are needed across applications domains ranging from people-tracking to analysis of satellite imagery over time. The detection and tracking of malignant skin cancers and benign moles poses a particularly challenging problem due to the general uni-formity of large skin patches, the fact that skin lesions vary little in their appearance, and the relatively small amount of data available. Here we introduce a novel data synthesis technique that merges images of individual skin lesions with full-body images and heavily augments them to generate significant amounts of data. We build a convolutional neural network (CNN) based system, trained on this synthetic data, and demonstrate superior performance to traditional detection and tracking techniques. Additionally, we compare our system to humans trained with simple criteria. Our system is intended for potential clinical use to augment the capabilities of health-care providers. While domain-speciﬁc, we believe the meth-ods invoked in this work will be useful in applying CNNs across domains that suffer from limited data availability.
On the Inﬂuence of Data Imbalance on Supervised Gaussian Mixture Models

: Imbalanced data present a pervasive challenge in many real-world applications of statistical and machine learning, where the instances of one class signiﬁcantly outnumber those of the other. This paper examines the impact of class imbalance on the performance of Gaussian mixture models in classiﬁcation tasks and establishes the need for a strategy to reduce the adverse effects of imbalanced data on the accuracy and reliability of classiﬁcation outcomes. We explore various strategies to address this problem, including cost-sensitive learning, threshold adjustments, and sampling-based techniques. Through extensive experiments on synthetic and real-world datasets, we evaluate the effectiveness of these methods. Our ﬁndings emphasize the need for effective mitigation strategies for class imbalance in supervised Gaussian mixtures, offering valuable insights for practitioners and researchers in improving classiﬁcation outcomes.
fac-Acid or erythromycin stress significantly improves transformation efficiency through regulating expression of DNA binding proteins in Lactococcus lactis F44

Lactococcus lactis is a gram-positive bacterium used extensively in the dairy industry and food fermentation, and its biological characteristics are usually improved through genetic manipulation. However, poor transformation efficiency was the main restriction factor for the construction of engineered strains. In this study, the transformation efficiency of L. lactis F44 showed a 56.1-fold increase in acid condition (pH 5.0); mean-while, erythromycin stress (0.04 µg/mL) promoted the transformation efficiency more significantly (76.9-fold). Notably, the transformation efficiency of F44e ( L. lactis F44 harboring empty pLEB124) increased up to 149.1-fold under the synergistic stresses of acid and erythromycin. In addition, the gene expression of some DNA binding proteins (DprA, RadA, RadC, RecA, RecQ, and SsbA) changed correspondingly. Especially for radA , 25.1-fold improvement was detected when F44e was exposed to pH 5.0. Overexpression of some DNA binding proteins could improve the transformation efficiency. The results suggested that acid or erythromycin stress could improve the transformation efficiency of L. lactis through regulating gene expression of DNA binding proteins. We have proposed a simple but promising strategy for improving the transformation efficiency of L. lactis and other hard-transformed microorganisms.
Quality of Experience in Video Streaming: Status Quo, Pitfalls, and Guidelines

Quality of experience (QoE) becomes both the holy grail and a free-for-all in adaptive bitrate (ABR) video streaming. On the one hand, the design, operation, and evaluation of ABR algorithms increasingly rely on QoE. On the other hand, QoE frequently receives only cursory attention in this supporting role, with many of its important aspects treated with insufficient care. As a complex subjective notion, QoE is directly measurable through subjective tests, which incur evident overhead. While an objective QoE model represents a scalable automated means for QoE assessment, QoE models proliferate without consensus on their goodness due to numerous influence factors, construction methods, and usages. The model proliferation creates a false impression that proposing a new QoE model without a proper validation is acceptable. Because the multifaceted QoE problem involves separable and often separated tasks of test conducting, model building, and model using, this separation of concerns causes additional complications. By leveraging two large real datasets of individual QoE perception, this paper reviews the status quo in QoE, identifies various pitfalls, and offers guidelines for test conducting, model building, and model using, so as to foster high standards in future work on QoE in ABR video streaming.
Effectiveness of Insulation Layers for Fire Protection of FRP Reinforced Concrete Flexural Members

: This paper investigates experimentally the efficiency of thermal insulation layers in preserving the flexural capacity of fiber-reinforced polymer (FRP) reinforced concrete beams subjected to elevated temperature. FRP rebars are innovative alternatives to conventional steel reinforcement rebars in reinforced concrete structures. There is a need to identify the performance of those beams under fire scenario. Four concrete beams reinforced by different FRP rebars were investigated under elevated temperature exposure up to 800 o C for two hours. Two of those beams were thermally insulated by a 25 mm thick thermal insulation layer from perlite mortar. Experimental tests showed that the insulation layer enhanced the flexural performance of the concrete beams compared to the uninsulated beams. Moreover, the thermally insulated beams showed that the major failure mode is the crushing concrete at the top substrate of tested beams as recommended by the design guidelines. The thermal progression, failure load, failure mechanism and mid-span deflection of the tested beams are presented and discussed.
A TIME-SERIES ANALYSIS OF TIDAL EFFECTS ON GROUNDWATER SALINITY

A time series approach may also be applied to model tidal intrusion into coastal aquifers. The author s examine the effect of tidal behaviour on groundwater level and salinity intrusion for the coastal Brisbane region using autocorrelation and spectral analyses. The results sho w a close relationship between tidal behaviour, gro undwater depth and salinity levels for the Brisbane coast. The known effect can be quantified and incorporated in new mo dels in order to more accurately map salinity intrusion into coastal groundwater.
Long-Term Prediction from Topic-Level Knowledge and Engagement in Mathematics Learning

During middle school, students’ learning experiences begin to influence their future decisions about college enrollment and career selection. Prior research indicates that both knowledge gained and the disengagement and affect experienced during this period are predictors of these future outcomes. However, this past research has investigated affect, disengagement, and knowledge in an overall fashion – looking at the average manifestation of these constructs across all topics studied across a year of mathematics. It may be that some mathematics topics are more associated with these outcomes than others. In this study, we use data from middle school students interacting with a digital mathematics learning platform, to analyze the interplay of these features across different topic areas. Our findings show that mastering Functions is the most important predictor of both college enrollment and STEM career selection, while the importance of knowing other topic areas varies across the two outcomes. Furthermore, while subject knowledge tends to be the most relevant predictor for general college enrollment, affective states, especially confusion and engaged concentration, become more important for predicting STEM career selection.
MORPHOLOGICAL, GENETIC AND FEEDING HABITS DIVERSITY OF THE COMMON SAND FISH, Scincus scincus IN TWO DIFFERENT HABITATS IN EGYPT

S. scincus is a typically desert-dwelling lizard skink that has evolved the ability to swim in loose sand. The main habitat of S. scincus is loose sand with minimal vegetation such as grass and dry shrubs. Geographic variation in sexual size dimorphism (SSD) and head size dimorphism (HSD) with greater dimensions in Gabal al Maghārah, North Sinai compared with Qariat El Prince, El-Faiyum might be correlated with spatial food availability and abundance or microevolutionary change or phenotypic plasticity. Our study revealed that beetles were found in Gabal al Maghārah, North Sinai with a higher percentage of occurrences than in Qariat El Prince, El-Faiyum which could be correlated with the high activity of Ldh in their liver tissues which reflects the high activity, adaptation and energetics of that population. The higher activity of β-Est in liver tissues of S. scincus inhabiting Gabal al Maghārah, North Sinai, may reflect to some extent, the unsafely of the diet applied to this natural population of skinks and its high ability to accumulate the environmental contaminants in their body tissues than that inhabiting Qariat El Prince, El-Faiyum. The highly polluted environment in Qariat El Prince, El-Faiyum compared with Gabal al Maghārah, North Sinai resulting in elevations in DNA damage level that threatens the persistence of S. scincus inhabiting this habitat. Thus it is recommended to solve the pollution problem to protect ecosystem biodiversity.
Fine-scale spatial genetic structure and intra-specific interactions of Populus nigra within a natural river corridor along the lower Allier River (France)

41 Spatial genetic structure (SGS) studies contribute to our understanding of gene flow and species dispersal. Only a few studies have linked the spatio-temporal pattern of SGS and intra-specific interactions. Black poplar ( Populus 43 nigra L.) is a threatened pioneer riparian tree species along many rivers across Europe. We studied its SGS in 44 cohorts of varying ages at a fine-scale (i.e. at distances including the zone of influence between individuals) to 45 better understand local patterns of dispersal and intra-specific interactions during early life-stages. We genotyped 46 349 P. nigra individuals in three gravel bars along a 1.6 km reach of the Allier River in the Réserve Naturelle du 47 Val d’Allier, central France. We found high genetic diversity values ( H e = 0.860) thus identifying this site as 48 important for the conservation of P. nigra genetic diversity. We also found significantly more clones in locations 49 exposed to the river flow compared with less exposed locations. These clones offer mechanical protection and 50 habitat improvement (through facilitation) to individuals in close proximity. A significant fine-scale SGS was 51 observed in the youngest cohort at the gravel bar scale while none was observed in the older cohorts or at the river 52 reach scale. This pattern was confirmed by a reanalysis of published data on the Garonne River. A shift in intra- 53 specific interactions, from facilitation to competition through self-thinning, could explain the loss of SGS in older 54 cohorts. This highlights the importance of shifts in intraspecific interactions through life and their consequence on 55 population genetic structure. to local of early of P. To do we explored the FSGS a scale or less) of three different cohorts of black poplar over a 1.6 km reach of the Allier River (France) located in a nature reserve. We used microsatellite markers that allowed us to estimate the genetic diversity of the population. As vegetative propagation was identified in the population, we investigated its geographic distribution, in particular in relation to topography using a digital elevation model (DEM) of this reach of the Allier River. The originality of the present study lies in the very fine scale (metric) genetic structure approach combined with the comparison between different cohorts.
The impact of saponin and tannin on performance, blood constituents, and carcass fatty acids in Baluchi lambs

The aim of this experiment was to study the effect of pure saponin and tannic acid on feed intake, weight gain, immune metabolites, blood lipids, and fatty acid profiles of lamb carcass. In this experiment, 18 lambs with an average weight of 17±1.5 kg were used in a completely randomized design (3 treatments with 6 replications) for 60 days. Treatments consisted of a basal diet consisting of forage (30%) and concentrates (70%), and diets containing saponin (150 mg/kg dry matter) or tannic acid (15 g/kg dry matter). Dry matter intake, weight gain, feed conversion ratio, packed cell volume and blood concentrations of hemoglobin, glucose, urea nitrogen, total proteins, and triglycerides were not affected by the experimental treatments. Concentration of saturated fatty acids and unsaturated fatty acids with a double bond did not show a significant difference between the experimental treatments, but the sum of unsaturated fatty acids with several double bonds was highest in the tannic acid treatment (P<0.05).
Capacity-Aware Undersea Cable System Design

—Undersea cables play a crucial role in enabling 1 global communication and data transfer, significantly affect-2 ing Internet speeds. Without them, global communication 3 would be severely limited. As technology advances and 4 network demands increase, the number and variety of optical 5 fibers within cables are constantly increasing. This growth 6 results in more costly cable networks with the ability to 7 transmit more data and enhances the speed and reliability 8 of data transmission. The construction of an undersea cable 9 system requires careful consideration of the appropriate 10 bandwidth of the cable to meet network bandwidth require-11 ments while minimizing costs. In this paper, we formulate 12 the undersea cable network optimization problem taking 13 account of the bandwidth capacity of each cable edge on the 14 cable network as a weighted edges Steiner minimum tree 15 problem and describe a new algorithm called the weighted 16 edges Steiner minimum tree (WE-SMT) algorithm. For the 17 given locations of the terminal nodes and the bandwidth 18 capacity requirement, the WE-SMT algorithm optimizes the 19 position of Steiner nodes, the bandwidth capacity of each 20 cable edge, and the cable path. We implement our algorithm 21 in a real-world setting, evaluating the benefit gained against 22 the outcomes obtained without accounting for bandwidth 23 optimization, as well as studying the effect of data resolution 24 on the quality of the path planning results. In addition, we 25 assess the performance of our new algorithm in comparison 26 with that of an operational real-world cable system. 27
Genetic Diversity of Ethiopian Durum Wheat (Triticum durum Desf.) Landrace Collections as Reveled by SSR Markers

The genetic diversity of 141 Ethiopian durum wheat (Triticum durum Desf.) landrace collections and 19 improved varieties was analyzed using primers of 12 SSR markers in 2015. The experiment was conducted at the National Agricultural Biotechnology Laboratory, Holetta, Ethiopia. The difference between the longest and shortest amplified fragment size ranged from 100 to 350 bp. The highest variation in fragment size was observed for primer CFD 257 (250-350 bp) and the lowest was for primer CFA2278 (100-180 bp). All the 12 SSR primer pairs were polymorphic and generated a total of 74 alleles. The number of alleles per locus ranged from 4 for primers WMS 375, WMS 493, and CFD257 to 9 for primers WMS53, with a mean of 6 alleles per locus. Some loci were more monomorphic (WMS493, WMS516, and WMS532) with less gene flow than other loci such as WMS269 and WMS234. Based on the analysis of molecular variance (AMOVA), lower level (19%) of variation was observed among populations and higher level (81%) within population. The dendogram of cluster analysis based on neighbor-joining algorithm categorized the 160 durum wheat genotypes into three major clusters. Cluster I consisted 47, Cluster II 64, and Cluster III 49 genotypes. Based on the magnitude of the genetic distance (GD), more differentiations were observed between accessions in populations originated from different geographical regions in Ethiopia.