We introduce ChillsDB the first validated database of audiovisual stimuli eliciting aesthetic chills  in a US population. To discover chills stimuli “in the wild”, we devised a bottom-up, ecologically-valid method consisting in searching for mentions of the emotion’ somatic markers in user comments throughout social media platforms (YouTube and Reddit). We successfully captured 204 chills-eliciting videos of three categories: music, film, and speech. We then tested the top 50 videos in the database on 600+ participants and validated a gold standard of 10 stimuli with a 0.9 probability of generating chills. All ChillsDB tools and data are fully available on GitHub for researchers to be able to contribute and perform further analysis. Best characterized as the feeling of cold down the spine or goosebumps while engaging with music or film, chills are the sensation associated to shivers: short thermogenic tremors of skeletal muscles. Though ordinarily involved in the regulation of temperature (or as an immune response during fever), chills can also be triggered by information-related processes , independently of changes in temperature .Aesthetic chills are a universal marker of human peak experiences across the arts, sciences and world religions5. However, no validated database of stimuli exists to elicit aesthetic chills. In psychology and neuroscience, using audiovisual stimuli is a standard procedure for generating and studying emotional reactions, both in humans and primates. Emotional stimulation includes images6, audio7, video13, or text14 and provides a reliable way to elicit emotion in controlled laboratory settings.As a conscious, measurable, and universal emotion, with clear delineated correlates and a wide range of behavioural consequences, chills are a promising field of study for affective and social neuroscience2. As a predictor for the personality trait Openness to Experience2, chills can be generated from a wide range of media: music, films, paintings, poetry, science, mathematics, religion, rituals1. Studies report a number of behavioural effects such as increased altruism15, pleasure1 and reward1. More recently, chills have been related to learning and meaning-making1, and demonstrated effects on cognitive functions such as attention and memory16. As an emotional peak, chills also have downstream effects on valence and arousal17, and physiologic factors such as heart rate18, pupil dilatation19, skin conductance19, and muscle contractions20.Chills seem to be a universal emotional phenomenon found across human culture and languages22, and researchers usually ask participants to bring their own chills-eliciting music to the laboratory15. Some databases exist for emotional labels that include chills as a signature , but none strictly focused on chills. To fill this gap, we introduce ChillsDB, a validated database of chill-eliciting stimuli for a US population. The database consists of 204 chill eliciting audiovisual stimuli collected from social media platforms (YouTube and Reddit) by counting mentions of keywords of somatic markers of aesthetic chills in the user comments. In a subsequent study, we validated 50 stimuli videos (t < 10 minutes duration) in their propensity to elicit chills. The goal was to capture 10 videos with a probability to generate chills higher than 0.7 .However, most research focuses solely on music as a stimulus23. The tool uses a seed video as a starting point to search for related videos using the social media platforms’s recommendation system. For determining if the video qualifies as stimulus, the tool uses a predefined dictionary to find word occurrences in the user comments of the video. The tool then traverses in the network of the seed video and checks if the video qualifies as a stimulus. If the video qualifies, the tool traverses in the network of the qualified video to find more videos and repeats the process. Else if the video does not qualify, the algorithm continues searching in the network of the seed video.We used online social media platforms, YouTube and Reddit, as sources to gather stimulus which elicits chills. For data collection, we developed a Python-based tool to find stimuli distributed across social media platform using breadth-first search algorithmFor the video to qualify as a chills eliciting stimulus, we use mentions of somatic markers of the shiver in user comments as a way to determine the propensity of video to elicit chills. Based on the existing literature, we used a somatic marker dictionary containing: ‘frisson’, ‘chill’, ‘goosebump’, ‘gooseflesh’ as the keywords for somatic reference to define aesthetic chills. Based on the number of cumulative occurrences of the keyword in the user comment section, the stimulus was selected to be part of the database. For the video to be selected as stimulus, we used the criterion of having at least 10 occurrences of the somatic marker dictionary in the stimulus comments, with a total amount of comments greater than 100.All the qualified videos were saved in a Comma Separated Values (.csv) file and videos with high mentions of somatic markers were reused as seed videos to find newer videos. We collected the total comments, likes count, dislike count and somatic marker occurrences from the qualified video. We used a similar process to gather stimulus from the Reddit platform, searching for the dictionnary in the Reddit comments. We found stimulus in Reddit from forums ‘r/Frisson’, ‘r/inspiring’ and ‘r/inspiration’. Since Reddit posts had significantly lower comment counts than YouTube, we did not use minimum somatic marker occurrence criteria to select the stimulus. From YouTube and Reddit we collected 204 stimulus samples (100 in YouTube and 104 in Reddit). From the 204 stimulus samples, we selected the top 50 stimulus that mentioned the dictionary keywords with the highest frequency, to evaluate their propensity in generating chills.24, one before and one after the study so as to ensure high quality data.To validate the database stimulus, we used the Prolific online platform to recruit participants. We also set up an online website to present the stimuli and collect user data. Participants from Prolific were redirected to the online platform and completed the survey after watching the stimulus. Our online platform comprised two attention checks660 subjects participated in our experiment . We removed 100 participants who reported an aberrant proportion of chills as compared to the rest of the sample (N > 10) and did not fulfil the two attention checks. Participants were recruited on an online platform and were screened for psychiatric conditions or neurologic disorders. All the participants reside in the United States of America and practised English as their first language. 75% White, 7.9% Multiracial, 8.4% Asian, 3.6% African American, 3.9% Hispanic, and 2% Middle Eastern. An additional sample of 130 participants  rated the top 6 stimuli, we removed 4 participants who did not fulfil the attention check. The participants were paid proportional to their time in the study at approx hourly rate of USD 11.79.To validate the gold standard, we conducted an online study on Prolific crowdsourcing platform to evaluate the emotional effect of chill-inducing videos. Participants were first screened for neurologic disorders and randomly assigned to one of ChillsDB top 50 videos. Before the video, they were given a definition of “the feeling of emotional chills and shivers” as “the feeling of cold down your spine that are NOT related to temperature or sickness but that are caused by some strong emotions”. Participants were asked to report their age, gender, ethnicity, frequency of daily chills , NEO item 188 score  . Participants were then exposed to the audiovisual stimulus from the database and asked to report whenever they experienced chills by pressing a large button on the right side of the screen. Only once the stimulus is over are they allowed to continue to the next part of the study. After the exposure they were asked to report the intensity of the chills, and rate their experience in terms of valence and arousal all on a 5 point Likert scale.et al., 2009). The attention checks constituted selecting the correct response to a described question, e.g. “Please select ‘strongly agree’ for this question”. Participants were compensated based on time spent in the study at an approximately hourly rate of USD 11.72. Each experiment lasted approximately 10 minutes and was well-received by the participant. Some of the participants even wrote to the authors a personal email to thank them for the experience .To ensure the quality of data we implemented two attention checks, one before the stimulus and one after, to determine if participants were paying attention to questions  and receive appropriate answers. All participants reacted positively to the experiment and were thankful for the opportunity to learn about the phenomenon.25. A simple user interfaces allows anyone to see the YouTube videos (www.chillsdb.com). One can also explore the database based on 1) the platform parsed (YouTube or Reddit) these sheets include the comments from the users, 2) the validated stimuli , 3) the type of stimuli , and finally 4) the participant data .YouTube: 93 English videos captured during the YouTube breadth-first search. This file includes YouTube Video ID, Title of the video, Total number of comments, Total number of Likes, Total Number of Dislikes, the results from the sentiment analysis , the count of each dictionary terms  and the comments from users.Reddit: 104 videos captured during the Reddit search. This file includes YouTube Video ID, the SubReddit where it was found, the title of the video, the number of upvotes and downvotes, the ID of the video, the URL, the total number of comments and the comments from users.Top 100: videos from the YouTube and Reddit batch with the most chills comments as a function of total number of comments. The criteria used for YouTube were the highest mentions of the somatic dictionary. We chose the top 15 Reddit videos and images with the highest amount of upvotes and which were not in the YouTube results.Top 10: videos with the highest chills ratio  validated on 10 participants each.Top 6: Chills gold standard of validated videos with the highest chills ratio  validated on 30 participants each.ChillsDB consists in 5 .csv sheets available under a CC0 1.0 license on the associated Harvard Dataversewww.chillsdb.com). As mentioned in the previous subsection, the stimuli can be explored together with their associated data in the corresponding sheet based on 1) stimuli type  or 2) their platform of origin. For each stimulus, the timing of when the chills is most likely to occur is also included. To access the stimuli from the database, enter the listed video ID after the following:A simple website was installed to access the stimuli . Given the disparity in group sizes for each video, we calculated the ratio of chills report divided by the number of participants for each video (Chills Ratio). The average Chills Ratio in our sample is 0.7 . Each video has on average 2.5 chills .et al. study .We then proceed to evaluate the top 10 videos of the batch  on an additional sample of 130 participants, bringing the total of participants per videos to N = 30. The results confirmed the prior analysis with all videos eliciting chills in more than 80% of the participants with two videos (“Jurassic Park” and “Miserere”) eliciting chills in 90% of the participants.We introduce ChillsDB, the first validated dataset for research on aesthetic chills. It includes a mix of films, music, and speeches, which generate chills in a US population Fig. . We conc26.ChillsDB videos can be used to map susceptibility of various psychiatric disorders to reward and allow “stress” test for diagnosing various mood disorders in the form described inChillsDB can be used as material for affective neuroscience research to drive affective response in a controlled reliable way. Furthermore, it provides a rich set of stimuli for emotion-centered psychotherapy, to improve emotional regulation and interoceptive awareness in Emotion Focused Therapy.Finally, ChillsDB also offers valuable materials for intercultural studies in the social and human sciences to study psychosocial similarities and differences in terms of music, speech, and films in fields such as musicology, aesthetics, linguistics, and narratology.We envision that ChillsDB will allow for at least 3 types of future research otherwise impossible:Future research should enrich the database with new content, further classify and analyse the dataset, and test the gold standard with new populations . Indeed, a limitation of the present study is the fact that we had to rely on subjective reports of chills due to the online nature of the experiment. Future studies should therefore include physiological measures  to validate the degree to which chilling experiences are actually induced by these stimuli and confirm the present findings.27. Sarasso and colleagues went further to suggest that they may inhibit motor action for the purpose of knowledge-acquisition28. With the exception of NEO PI-R and despite a promising biomarker for peak experiences, chills are still largely exempt from psychometric questionnaires29. We hope that this validated gold standard will help advance this promising research area.Chills is a promising research field. Several hypotheses have been suggested to account for chills but they remain a challenge to operationalize. Schoeller and Perlovsky have suggested that chills relate to learning rate and that they correspond to a satiation of a vital need for information or knowledge


An ultrahigh molecular weight PMMA with a number-average molecular weight of 1.68 × 106 Da and a weight-average molecular weight of 5.38 × 106 Da has been synthesized at the optimal formulation of [MMA]:[Pd(CF3COO)2]:[1-octanethiol] = 94,300:8:23 at 70 °C. A kinetic study showed that the reaction orders with respect to Pd(CF3COO)2, 1-octanethiol, and MMA are 0.64, 1.26, and 1.46, respectively. A variety of techniques such as proton nuclear magnetic resonance spectroscopy (1H NMR), electrospray ionization mass spectroscopy (ESI-MS), size exclusion chromatography (SEC), X-ray photoelectron spectroscopy (XPS), transmission electron microscopy (TEM), and electron paramagnetic resonance spectroscopy (EPR) were employed to characterize the produced PMMA and palladium nanoparticles (Pd NPs). The results revealed that Pd(CF3COO)2 was firstly reduced by the excess of 1-octanethiol to form Pd NPs at the early stage of the polymerization, followed by the adsorption of 1-octanethiol on the surface of nanoparticles and subsequent generation of corresponding thiyl radicals to initiate the polymerization of MMA.A novel synthesis of ultrahigh molecular weight poly(methyl methacrylate) (PMMA) using organosulfur compounds combined with a catalytical amount of transition metal carboxylates as an initiator has been developed. The combination of 1-octanethiol with palladium trifluoroacetate (Pd(CF Poly(methyl methacrylate) (PMMA), one of the best colorless and transparent thermoplastic resins, is obtained via the polymerization of methyl methacrylate (MMA). PMMA has excellent comprehensive properties such as strong mechanical strength, clear light transmission, superior electrical insulation, extraordinary weather resistance, good heat resistance, etc. ,2. There6 Da, while the maximum tensile strength for fractionated PMMA sample increased linearly with molecular weight up to about 1.0 × 106 Da and began to level off at higher molecular weight regions :[Pd(CF3COO)2]:[1-octanethiol] = 94,300:8:23, entry 15) accelerated the polymerization of MMA to a 92.60% conversion in 48 h and generated an ultrahigh molecular weight PMMA with a number-average molecular weight of 1.68 × 106 Da and a weight-average molecular weight of 5.38 × 106 Da, as measured by SEC (3COO)2 could be employed as an efficient initiator for the polymerization of MMA to synthesize ultrahigh molecular weight PMMA.Thiols are generally recognized as chain transfer agents and often used in free radical polymerizations to control polymer molecular weights. Interestingly, in this work, a trace amount of 1-octanethiol or 1-butanethiol (less than 0.05 wt%) combined with catalytical amount of copper, silver, iron, or palladium carboxylate was found to facilitate the polymerization of MMA (entry 9–15). Specifically, the combination of 1-octanethiol with Pd2 based on the optimal formulation was investigated, and the results are shown in The polymerization kinetics initiated by the combination of 1-octanethiol with Pd(CF3COO)2 concentration, 1-octanethiol concentration, and MMA concentration, and also increased with the increase in temperature. The reaction orders with respect to Pd(CF3COO)2, 1-octanethiol, and MMA were calculated to be 0.64, 1.26, and 1.46, respectively, according to the initial reaction rates measured at the initial stage of the polymerization (conversion < 10%) in R = -d[M]/dt = k[Pd(CF3COO)2]0.64[1-octanethiol]1.26[MMA]1.46. Based on Ea of the polymerization was determined to be 40.0 kJ/mol, according to Arrhenius equation.Clearly, the rate of the polymerization increased with the increase in Pd(CF3COO)2 is not a typical conventional free radical polymerization.It has been well documented that the reaction orders with respect to the initiators and monomers in traditional free radical polymerization are 0.5 and 1, respectively; therefore, the above kinetic results imply that the polymerization of MMA initiated by the combination of 1-octanethiol with a catalytical amount of Pd(CF3COO)2 did not follow a traditional free radical polymerization mechanism, it is necessary to investigate the nature of the polymerization reaction. Inspired by our previous research in which Pd nanoparticles functioned as a catalyst to promote the formation of organic radicals  immediately adjacent to the sulfide atom of 1-octanethiol residue, and the other methylene groups in 1-octanethiol residue [CH3(HC2)6CH2S-] show resonances at peak e (δ = 1.1~1.6 ppm). The methyl peak of 1-octanethiol residue [HC3(CH2)6CH2S-] is supposed to overlap with the methyl peak of the PMMA chain. According to the peak integration areas of a and d, the molecular mass of PMMA is thus calculated to be 1045 Da, which is close to the molecular weight measured by SEC.As can be seen in terature ,50, the m/z = 769.4, 869.5, 969.5, 1069.6, 1169.6, 1269.7, 1369.7, 1469.8) can be observed, and the mass difference between two neighboring major peaks remains 100, which corresponds to the molecular weight of PMMA structural unit (C5H8O2). The peak, for example, at m/z = 769.4 is consistent with the Na+ adduct of the PMMA macromolecular chain with six structural units and an initiator (1-octanethiol), indicating that the end-group structure proposed in the inset in The end-group structure of PMMA was further verified by ESI-MS, as shown in 1H NMR, EPR, and ESI-MS, a plausible mechanism is postulated as follows 2 is firstly reduced by 1-octanethiol to produce Pd clusters and further grow to Pd NPs at the early stage of the polymerization, as there is a higher abundance of 1-octanethiol compared to Pd(CF3COO)2. 1-Octanethiol is then adsorbed on the surface of Pd NPs to form a C8H17S-Pd bond, which is activated at relatively high temperatures in the polymerization conditions to release thiyl radicals around Pd NPs. The thiyl radical could immediately initiate MMA monomer :[Pd(CF3COO)2]:[1-octanethiol] = 94,300:8:23 reached 92.6% conversion in 48 h at 70 °C in the atmosphere of N2, producing an ultrahigh molecular weight PMMA with a number-average molecular weight of 1.68 × 106 Da, a weight-average molecular weight of 5.38 × 106 Da, and a Đ of 3.20. The reaction orders with respect to Pd(CF3COO)2, 1-octanethiol, and MMA were determined to be 0.64, 1.26, and 1.46, respectively; thus, the polymerization rate R could be written as R = -d[M]/dt = k[Pd(CF3COO)2]0.64[1-octanethiol]1.26[MMA]1.46 (k is the reaction rate constant). A mechanism investigation revealed that Pd(CF3COO)2 is firstly reduced by 1-octanethiol to form Pd NPs in situ, followed by the adsorption of 1-octanethiol on the surface of nanoparticles and subsequent release of thiyl radicals to initiate the polymerization of MMA.In this work, a novel synthesis of ultrahigh molecular weight PMMA using organosulfur compounds combined with a catalytical amount of transition metal carboxylates as an initiator has been developed. The bulk polymerization of MMA initiated by the combination of 1-octanethiol with Pd(CF


With the widespread application of 5G technology, there has been a significant surge in wireless video service demand and video traffic due to the proliferation of smart terminal devices and multimedia applications. However, the complexity of terminal devices, heterogeneous transmission channels, and the rapid growth of video traffic present new challenges for wireless network-based video applications. Although scalable video coding technology effectively improves video transmission efficiency in complex networks, traditional cellular base stations may struggle to handle video transmissions for all users simultaneously, particularly in large-scale networks. To tackle this issue, we propose a scalable video multicast scheme based on user demand perception and Device-to-Device (D2D) communication, aiming to enhance the D2D multicast network transmission performance of scalable videos in cellular D2D hybrid networks. Firstly, we analyze user interests by considering their video viewing history and factors like video popularity to determine their willingness for video pushing, thereby increasing the number of users receiving multicast clusters. Secondly, we design a cluster head selection algorithm that considers users’ channel quality, social parameters, and video quality requirements. Performance results demonstrate that the proposed scheme effectively attracts potential request users to join multicast clusters, increases the number of users in the clusters, and meets diverse user demands for video quality. With the remarkable advancement of wireless communication technology and the rapid evolution of online media content, intelligent wireless communication devices have achieved widespread proliferation, inducing a substantial metamorphosis in wireless network traffic patterns. The transition from voice-centric activities to the dominance of social media platforms, such as Weibo, WeChat, and QQ, alongside the emergence of network live streaming and short video content, has instigated an unprecedented upsurge in wireless data consumption. According to Cisco’s projections, the global data traffic is poised to escalate to 396EB per month by 2022, surpassing the cumulative data traffic from the inception of the internet until the close of 2016. Notably, the proliferation of voluminous data traffic is principally fueled by the realm of network video streaming, which is anticipated to encompass 17% of the total internet video traffic, significantly escalating from the previous 5%. Furthermore, the consumption of network live-streaming data is forecasted to undergo a fifteen-fold surge by 2022 [In order to address the elevated demands for high bandwidth and low latency within wireless networks while simultaneously alleviating the strain on base stations, the fifth generation (5G) networks have introduced transformative objectives, namely Enhanced Mobile BroadBand (eMBB) and Ultra-Reliable Low Latency Connection (URLLC). Moreover, the significance of Device-to-Device (D2D) technology has been acknowledged as a pivotal approach for mitigating latency and reducing base station burdens. Particularly in contexts involving extensive data transmission and processing, such as those encountered in smart cities, D2D communication offers distinct advantages, encompassing elevated transmission rates and minimized latency. This renders it particularly suitable for transmitting substantial data payloads, including video content necessitating robust throughput . FurtherIn the domain of mobile communication networks, the scarcity of wireless spectrum and computing resources presents significant hurdles. Scalable video coding (SVC) technology emerges as a promising solution. SVC partitions a video into distinct constituents, including a fundamental base layer and multiple augmentation layers. These augmentation layers can be dynamically chosen in response to fluctuating channel conditions, thereby optimizing the judicious employment of precious channel resources. Prioritizing the transmission of the base layer ensures that fundamental communication requisites are fulfilled, even amid suboptimal channel circumstances, albeit with a compromise on video quality. Conversely, during favorable channel conditions, the selection of supplementary enhancement layers becomes viable, ushering in heightened frame rates and resolutions, consequently elevating the comprehensive video quality. By amalgamating video recommendation principles with the adaptive capabilities of scalable video transmission, we can effectively harness available resources, affording users an optimal viewing encounter meticulously tailored to their distinct preferences and the prevalent network conditions.In summary, within the domain of scalable video transmission on the Internet of Things (IoT) facilitated by D2D communication, the utilization of intelligent methodologies for a comprehensive analysis encompassing user historical data, social parameters, channel quality, and other pertinent aspects of big data, offers substantial academic merit in augmenting the quality of diversified communication services. This undertaking assumes paramount importance in proficiently harnessing spectrum resources, mitigating base station burdens, and satisfying users’ requisites for elevated bandwidth and minimized latency.Investigation of D2D Multicast for Scalable Videos: This research introduces a scalable video multicast approach centered around user demand perception for video dissemination. Leveraging insights from users’ historical video consumption patterns and capturing their preferences, this study offers intelligent video recommendations to potential requestors. Additionally, an innovative clustering algorithm is devised, which augments the user count within D2D multicast clusters.Cluster Head Selection: A cluster head selection algorithm is formulated, taking into account inter-user channel quality, social parameters, and users’ preferences for video quality. This algorithm establishes a holistic metric aimed at optimizing multicast effectiveness, thereby achieving the highest possible efficiency in D2D multicast operations.Validation through Simulation Experiments: Through a series of simulation experiments, the efficacy of the proposed scheme is substantiated. The results reveal that the scheme adeptly incorporates potential requestors into multicast clusters, amplifies the user count within said clusters, and adeptly addresses diverse user preferences for video quality. Consequently, this substantiates a notable enhancement in service quality.This paper predominantly centers on investigating the matter of scalable video transmission within cellular D2D hybrid networks. The principal contributions of this study are outlined below:The subsequent sections of this paper are structured as follows: The adept deployment of D2D communication technology holds the potential to substantially enhance spectrum efficiency, alleviate the workload on base stations, and expand the communication scope for users. This culminates in the establishment of more supple and efficacious mobile communication networks. Nonetheless, owing to the finite availability of channel resources, instances arise where cellular users have fully utilized all accessible spectrums. Consequently, D2D users are compelled to engage in communication by repurposing the spectrum already utilized by cellular users.In tackling the challenges presented by extensive data transmission scenarios, current research predominantly revolves around methodologies pertaining to resource allocation and computation offloading . These sCai et al.  delve inAll the previously cited studies concentrate on centralized resource allocation algorithms, which yield favorable outcomes in resource allocation. However, these algorithms necessitate the base station to possess comprehensive user information, consequently engendering resource contention among users . This, iNevertheless, D2D multicast encounters distinct challenges when juxtaposed with unicast transmission. The determinants influencing multicast group throughput encompass not solely channel resource allocation and power distribution  but alsoDiverse factors, encompassing physical locations, preferences, and social attributes, wield significant influence over the realms of edge computing and content caching . In the In the domain of enhancing D2D relayed multicast data packet reliability, network coding principles were harnessed, as evidenced by the literature . ReinforCurrently, the majority of research in the realm of D2D communication tends to emphasize the impact of physical proximity, often allocating comparatively less attention to the inherent social attributes of users. Furthermore, investigations that seamlessly integrate D2D communication with video transmission and encoding are conspicuously lacking.D2D communication is marked by a diverse array of user terminal devices and channels, thereby posing challenges for conventional video coding methodologies to effectively accommodate the constantly evolving and intricate network milieu. Nevertheless, scalable video coding has emerged as a propitious remedy, showcasing notable versatility across network terminals and channels. This approach has garnered considerable attention in recent times, particularly within the ambit of D2D communication. Notably, in scenarios demanding substantial data computation and offloading, the role of scalable video coding technology is paramount.Scalable video coding attains its adaptability by partitioning the video bitstream into multiple layers with distinct truncation points. A contemporary area of concentrated research revolves around the judicious selection of suitable bitstreams for video transmission, with the ultimate goal of furnishing users with elevated service quality. Present investigations concerning bitstream selection frequently center on prioritizing the transmission of the foundational video layer, underscoring the significance of these bitstream segments.Furthermore, within the domain of D2D communication, scholars have delved into the intricacies of resource allocation pertaining to data transmission. This realm of inquiry encompasses an array of topics, including wireless channel allocation , the selDespite the potential advantages, research on D2D transmission with scalable video in the IoT remains somewhat limited. The user access rate has yet to attain its maximal capacity, thereby indicating that certain extant algorithms may fall short of adequately fulfilling the rigorous demands inherent in scalable video transmission within the IoT settings. Confronting these challenges and devising innovative remedies assumes paramount significance in order to fully unleash the inherent potential of scalable video coding within the domain of IoT applications.In conventional cellular communication systems, multiple users with similar demands within a shared cell are compelled to access desired content independently via cellular links originating from the base station. Consequently, when multiple users initiate service requests, the base station is obligated to transmit identical content through distinct links. This transmission methodology is manifestly inefficient, resulting in a substantial redundancy in the transmission workload for the base station. Moreover, as the popularity of the transmitted content escalates, the redundancy amplifies correspondingly. To ameliorate redundant transmissions and enhance the efficiency in utilizing system resources, D2D communication presents significant potential for facilitating multicast transmissions. As a result, the exploration of D2D multicast communication has garnered extensive attention in recent years.Nonetheless, owing to the substantial user influx accessing videos across distinct time segments, prevailing D2D multicast communication technologies can still engender pronounced instances of redundant transmissions, particularly concerning widely popular video content within smart cities or intelligent transportation contexts. Within the confines of the same geographical region, identical video content may be repetitively transmitted during various instances, thereby fostering considerable redundancy across the system. In an endeavor to further mitigate data redundancy and elevate the resource utilization efficiency inherent in D2D multicast communication systems, this research introduces a novel scalable video multicast scheme predicated upon video pushing. This scheme not only dispenses videos to users making specific requests but also proactively delivers videos to potential recipients, thereby augmenting the cohort of multicast recipients. This augmentation culminates in heightened throughput, ultimately leading to enhancements in spectrum utilization and energy efficiency.Within a cellular small cell context, an array of IoT devices coexist, each harboring its distinctive video preferences. Furthermore, owing to device constraints and user inclinations, dissimilar individuals manifest varying expectations concerning video quality. When multiple users express a desire to partake in the viewing of identical video content, an opportunity emerges for the establishment of a potential D2D multicast cluster. Within this configuration, a cluster head is designated to take delivery of the video content from the base station, subsequently diffusing the multicast-shared video content to the remaining users within the cluster via D2D links. This procedure engenders a solitary cellular link at the base station while concurrently satiating the multimedia needs of multiple users, thereby considerably alleviating the operational burden imposed upon the base station.However, owing to the divergent video requisites exhibited by individual users, the application of scalable video coding comes to the fore. The video content is consequently disseminated through the mechanism of layered multicast. This approach empowers users to selectively receive distinct video layers commensurate with their personalized preferences. The strategic utilization of scalable video coding, in conjunction with layered multicast methodologies, adeptly attends to the heterogeneous user requirements, culminating in an optimization of resource allocation within the expansive milieu of IoT big data analysis.D2D users communicate by sharing spectrum resources with cellular users, which leads to co-channel interference. To ensure that all users within a multicast cluster can receive multicast data properly, it is necessary to guarantee that the user with the worst channel quality can receive multicast data successfully. Let us denote the multicast-receiving user with the worst channel quality. According to Shannon’s formula, the channel capacity, which represents the upper limit of the multicast transmission rate for the multicast group, is given by:In the network, when transmitting scalable videos, different numbers of video layers require different bitrates, represented by the set In prevailing configurations of D2D multicast video delivery systems, a predominant majority of them employ non-scalable video coding techniques, and they neglect to address the variability in video quality requisites among distinct users. Consequently, these systems are constrained to providing a uniform video quality level for all users. Furthermore, certain investigations have not fully accommodated the temporal disparities inherent in users’ video requests; this pertains to scenarios where users soliciting the same video content might do so at disparate time instances. In the context of popular videos, it is noteworthy that video requests originating from users within the same geographical vicinity may transpire across multiple time intervals. This phenomenon necessitates repeated retrieval of the video content from the base station and potentially gives rise to numerous instances of D2D multicast clusters. Evidently, the current state of traditional D2D multicast video delivery systems exhibits appreciable scope for refinement, with the potential to significantly augment transmission efficiency.In this investigation, users expressing a demand for video content are classified into two distinct categories. The first category encompasses users who instigate video requests in the present moment, and they are termed “service request users.” The second category comprises users who, although not initiating video requests in the current timeframe, share an identical video demand; these are denoted as “potential request users”. As delineated in The entire cellular expanse is partitioned into multiple grids using the approach expounded in Reference . In thesIf videos could be multicast concurrently to both service request users and potential request users who express a willingness to receive them, the aggregate count of multicast recipients would witness a substantial augmentation. This, in turn, would yield a pronounced enhancement in the energy and spectrum efficiency of the entire system. While a judicious video push service undoubtedly contributes to an elevated user experience, a caveat emerges—frequent dissemination of undesired videos to users may impede their overall experience.Given the enigma posed by the elusive nature of potential request users, a universal video service push to all users is rendered unfeasible. Consequently, the imperative to winnow out potential request users assumes prominence. This filtration process engenders the selective delivery of videos solely to the identified, filtered potential request users. These filtered potential request users, alongside the service request users who consent to the video push, collectively constitute the pivotal constituents constituting the D2D multicast cluster. Subsequently, the subsequent phase entails the meticulous appointment of an apt cluster head tasked with the retrieval of the video content from the base station. This cluster head subsequently orchestrates the distribution of the video content among the remaining users encompassed within the multicast cluster. Within this research endeavor, our focus is twofold: firstly, the precision prediction of potential request users to participate within the multicast cluster, and secondly, the discerning selection of an optimal cluster head. This selection process aims to establish an expanded, more steadfast multicast cluster characterized by heightened capacity.Users sharing the same video demand often exhibit disparate temporal patterns in initiating service requests. Propagating videos to potential request users offers the potential to facilitate simultaneous video reception for a greater number of users, thereby amplifying multicast efficiency. However, an overabundance of video pushes may introduce a degradation in user experience. Several scenarios can hinder successful video pushes, encompassing instances where a device is marred by insufficient battery power or storage capacity to accommodate video reception. Furthermore, user preferences must be heeded, as certain users may opt not to receive video pushes to avoid disruptions.Furthermore, the success of a video push hinges upon a confluence of factors. Even if a user and their device satisfy the prerequisites for video reception, the pertinence of the pushed video content to the user’s interests remains pivotal. Indeed, a video push can adversely affect the quality of a user’s service experience if the pushed video content lacks relevance, thus rendering the entire video push service inconsequential. In light of these considerations, this section undertakes a comprehensive analysis of potential request users’ demands. The objective is to gauge their inclination to embrace video pushes and, by extension, ensure the attainment of a satisfactory user experience.The likelihood of a user soliciting a specific video hinges on two pivotal factors: the video’s overall popularity and the user’s distinct personal interests. Consequently, in the computation of the video request probability, it becomes imperative to account for both the aggregate attributes characterizing videos within the IoT context and the idiosyncratic predilections of individual users. This holistic approach is essential to engender outcomes that faithfully encapsulate the true video request probability.User InterestThe user’s past video-viewing behavior serves as a reflection of their individual interests. If a user has engaged with a specific genre of video content on numerous occasions within a recent timeframe, it serves as an indicative manifestation of their affinity toward that particular video genre. The frequency with which a distinct video genre is accessed and viewed by a user can be deemed a reliable gauge of their degree of interest. As such, the proportion of video content consumption attributed to a specific genre by an individual user can be mathematically expressed as follows:In the formula, 2.Video Popularityi in a video A significant body of research has demonstrated that while the specific video content may differ across regions, user requests for video content within the same region adhere strongly to the Zipf distribution. Therefore, the popularity of videos is commonly computed using the Zipf distribution. Let set “The prior calculation of the probability of users accepting push notifications did not encompass the current status and device conditions of the users. Within a given user’s context, their receptiveness to video push notifications exhibits temporal fluctuations. To elucidate, users might refrain from disturbances during work or study periods, while embracing such notifications during leisure or relaxation intervals. Moreover, the state of users’ devices also assumes significance, with the reception of videos necessitating specific physical prerequisites. Initially, the establishment of a reliable link between the user receiving the video and the cluster head is imperative. Furthermore, the act of video content reception entails an expenditure of energy.As a result, users have two distinct states: the state of accepting push notifications and the state of rejecting push notifications. Users can actively set these two states. They set the state to accept push notifications when it is appropriate for them to receive videos, and they set the state to reject push notifications during time periods when it is not suitable to receive videos. The device can perceive its current state and automatically determine if it meets the physical conditions for receiving video push notifications. For example, it checks if the current battery level is sufficient to fulfill the requirements for receiving videos and if there are physical conditions to establish a stable D2D link. When users set the state of accepting push notifications, if the device senses that its current state is insufficient to receive video push notifications, the device automatically modifies its current state. Let In the preceding section, this paper computed the likelihood of users in the “accepting push notifications” state embracing a specific video push. This computation considered both the user’s viewing history and the video’s popularity. The objective of the video push service is to elevate user experience quality while refraining from pushing videos to users who have opted to reject push notifications. In scenarios involving users who are amenable to video push notifications, a judicious approach is employed, wherein video pushes are administered selectively. This strategic selection aims to curtail superfluous resource consumption and minimize potential disturbances. For any given user subjected to a push notification, their predisposition to accept video pushes must conform to the following criterion:Given the limited scope of D2D communication and the dynamic movement patterns of D2D users, ensuring the persistence of the wireless channel state for seamless D2D communication presents a notable challenge. This challenge inherently raises the prospect of potential disruptions in D2D links. The efficacy of a D2D communication system is intrinsically tied to the stability of its D2D links. Extensive research has substantiated the intrinsic correlation between D2D communication stability and users’ social interactions.Several attributes serve as indicative markers of user social relationships, including trust, mobility congruence, and shared interests. As depicted in Extensive research has been conducted in the domain of social relationships. In this study, a user preference analysis approach is adopted to gauge the intensity of social connections between two users situated within the same grid. As previously elucidated, users’ receptiveness to widely favored videos serves as a credible proxy for gauging their preferences. The formulation presented in Equation (6) facilitates the comprehension of a user’s proclivity toward various video categories, thereby enabling the derivation of the user’s interest preference vector. Specifically, for a given user denoted as Next, the social relationship strength between two users is calculated using cosine similarity. The social relationship strength between user Formula (12) enables the computation of the social relationship strength between any two users.In the preceding section, the inclination of users in the state of accepting push notifications to embrace a specific video push was deduced through an amalgamation of their viewing history and video popularity. Following this, the act of video pushing transpired based on users’ proclivity, with these recipients being amalgamated alongside service request users to forge cohesive D2D multicast clusters. Within the context of D2D multicast transmission, the meticulous curation of cluster heads emerges as a pivotal determinant, wielding pronounced influence over multicast cluster performance. In light of this, the formulation of a cluster head selection framework becomes imperative and is aimed at discerning an apt cluster head and configuring a multicast infrastructure characterized by elevated transmission capacity and steadfast stability.A multicast cluster is preemptively established through proactive video broadcasting, with the designated user ensemble of the multicast cluster delineated as In this representation, The efficacy of multicast transmission is influenced not solely by the physical characteristics of users but also by their social attributes. A more robust social connection between two users tends to correlate with improved stability of the D2D link. To provide an accurate gauge of the transmission performance within the D2D multicast system, the utility metric The proposed approach outlined in this paper is validated through extensive simulations carried out on the MATLAB platform. The purpose of these simulations is to provide a comprehensive evaluation of the clustering and cluster head selection methodology put forth in this study. The performance of the algorithm is rigorously assessed across various communication scenarios to ensure a robust analysis.In order to evaluate the effectiveness of the proposed clustering and cluster head selection scheme, a series of simulation experiments are conducted. These experiments involve comparing the algorithm’s performance against alternative schemes operating within the same communication environments. The benchmarked schemes encompass social-aware strategies, interference-aware methodologies, and random selection approaches. The social-aware scheme is designed to establish D2D multicast clusters by taking into account nearby service request users, with the cluster head chosen based on the user possessing the highest number of stable social relationship links. Similarly, the interference-aware scheme constructs D2D multicast clusters considering nearby service request users, and the cluster head selection is based on the user with the most stable links. By conducting these simulation experiments and comprehensive comparisons, the efficacy of the proposed scheme is thoroughly assessed, ensuring a robust evaluation of its performance across a variety of communication contexts.Given the central focus of this paper on enhancing the quality of video transmission, the scope of short-range video transmission is confined to small-scale D2D communication scenarios. Within the purview of such small-scale D2D communication contexts, the fundamental objective of D2D communication is the direct exchange of data among devices that are situated in relatively close proximity. This encompasses a spectrum of activities including social interactions, file sharing, and gaming. In these scenarios, the communication range typically spans from several tens to a few hundred meters. For the purpose of our simulations, the maximum D2D communication radius is set at 60 m. Given that specific values for D2D communication simulation parameters are not explicitly defined, we have drawn inspiration from the general parameters for D2D communication simulations, as outlined in Reference . The conThe simulation environment is structured as a single-cell model, with users distributed randomly within a grid. The geographic positions of users adhere to a homogeneous Poisson distribution. Additionally, key factors pertaining to user count in the context of small-scale communication are integrated into the fixed parameters of the simulation environment. The specifics of the communication parameters are outlined as follows: video bitrates ranging from 600 kbps to 3000 kbps are partitioned into five distinct layers, with each layer necessitating a constant bitrate of 600 kbps. Each successive layer corresponds to an increment in bitrate, denoting a varying level of video quality. Unless explicitly indicated otherwise in subsequent simulations, it is assumed that the likelihood of user requests for each level of video quality is as follows: 0.01, 0.02, 0.05, 0.1, and 0.79. Furthermore, users engaged in D2D communication opportunistically share uplink cellular channel resources alongside cellular users. The channel model encompasses factors such as path loss, Rayleigh fading, and Gaussian channel noise. The core configurations of the primary parameters are itemized in Multicast performance is influenced by a range of factors, which can be fundamentally categorized into two main groups: the number of users within the multicast group and the choice of the cluster head. The subsequent sections of this paper will delve into an analysis of the multicast scheme’s performance, specifically focusing on these two facets, through comprehensive simulations.The impact of potential request users is pivotal in assessing the efficacy of the recommendation algorithm proposed in this study. Comparative experiments were meticulously conducted across varying scenarios involving potential request users. This allowed for an exploration of the interplay between the algorithm’s performance and key parameter settings, encompassing factors such as willingness threshold, popularity factor, and fluctuations in video quantity. Notably, distinct configurations of potential service users yielded diverse system performances. Nonetheless, an overarching trend emerged, wherein an augmented count of potential service users correlated with heightened utility values within the D2D multicast system. This utility value serves as a reliable indicator of the average throughput achieved by the D2D multicast transmission system.As shown in In synthesis, an augmented count of potential requesting users aligns with an amplified efficacy of the video recommendation algorithm proffered in this study. Moreover, the manipulation of distinct parameter configurations markedly influences the performance of the system.The aforementioned simulation outcomes underscore the direct correlation between the count of potential requesting users and the population within the multicast cluster, thereby exerting a substantial influence on the multicast utility value. Subsequently, the efficacy of the cluster head selection scheme posited in this study is subjected to validation through ensuing simulation analyses.The impact of distinct parameter configurations on the utility value of the multicast scheme has been deliberated from dual vantage points. Yet, an additional pivotal factor influencing the efficacy of the proposed scheme pertains to the diversity in users’ preferences for video quality. Throughout the simulation, videos have been stratified into five layers, thereby affording five discrete levels of video quality. The likelihood of a user expressing a preference for each quality tier is designated as The wireless network realm is inherently shackled by finite spectrum resources. In the ambit of transmitting copious video data, the pivotal quandary encountered by contemporary video transmission services resides in adroitly modeling and dissecting these confined spectrum assets. This vanguard research embarks upon the precincts of D2D multicast for scalable videos, proffering forth a scalable video multicast blueprint imbued with user demand data acumen. Commencing the journey, user predilections are meticulously cast and scrutinized, harnessing a trove of data encompassing their historical video consumption trajectory and the tapestry of video popularities. This compendium of insights coalesces to fathom users’ proclivity to embrace specific video recommendations, thus engendering an assessment of their amenability. In sequitur, videos are judiciously channeled toward users manifesting a pronounced predisposition, thereby augmenting the retinue of recipients within the multicast constellation. This endeavor is galvanized by an innovative clustering algorithm that ushers in a coterie of latent inquirers. Concomitantly, cognizant of users’ channel fidelity, social dynamics, and video quality predilections, a cluster head selection algorithm is meticulously contrived. This algorithm, in essence, choreographs a clustering architecture calibrated to distill maximal utility from the tapestry of D2D multicast. Culminating in an array of simulation experiments, the proposed paradigm adeptly infuses nascent inquirers into the multicast coterie, augments the phalanx of cluster constituents, resonates with an eclectic gamut of video quality requisites, and amplifies the echelons of service quality governing video transmission within the annals of D2D communication among an assemblage of devices.


Aspergillus oryzae YRA3, isolated from the wild plant Atractylis carduus (Forssk.) C.Chr, was tested for its biocontrol activity against Rhizoctonia root rot of sorghum. The antagonistic potential of A. oryzae YRA3 was tested against Rhizoctonia solani in vitro. A full inhibition in the growth of R. solani was recorded indicating a strong antagonistic potential for this endophyte. To investigate the chemical composition of its metabolites, GC/MS analysis was used and thirty-two compounds in its culture filtrate were identified. Among these metabolites, some compounds with an antifungal background were detected including palmitic acid, 2-heptanone, and 2,3-butanediol. To these antifungal metabolites the antagonistic activity of A. oryzae YRA3 can be attributed. In the greenhouse experiment, treating of the infected sorghum plants with A. oryzae YRA3 significantly reduced severity of the Rhizoctonia root rot by 73.4%. An upregulation of the defensive genes (JERF3), (POD) and (CHI II) was recorded in sorghum roots when were inoculated with A. oryzae YRA3. In addition, an increment in the activity of peroxidase and polyphenol oxidase, as well as the total phenolic content in the sorghum roots was also recorded. Furthermore, the results obtained from the greenhouse experiment revealed a growth-promoting effect for inoculating the sorghum plants with A. oryzae YRA3. It can be concluded that A. oryzae YRA3 can be a probable biological agent to control this disease in sorghum. However, its evaluation under field conditions is highly needed in the future studies.Environmental pollution due to the improper use of the chemical fungicides represents a vital ecological problem, which affects human and animal health, as well as the microbial biodiversity and abundance in the soil. In this study, an endophytic fungus  Sorghum bicolor (L) Moench) is the world's fifth most important cereal grain1. In 2021, the global cultivated area under sorghum was estimated at 40,93 million ha, which produced 61,36 million tons2. The archaeological evidences suggest this crop was initially grown between 5,000 and 8,000 years ago in northeastern Africa, close to the Egyptian-Sudanese border, and it spread throughout the rest of the world via trade routes3. Sorghum has been cultivated as a food crop for humans and as animal feed, for construction materials, or industrial raw materials. In both Africa and Asia, sorghum is an important cereal crop4. However, sorghum production is threatened by various pathogenic fungi that negatively affect the crop yield and growth in spite of the availability of effective chemical fungicides5.After wheat, maize, rice, and barley, sorghum  of this pathogen are known to infect different plant species, at varying degrees7. The disease symptoms include stunting of the plant and appearing of brown to reddish lesions along the root and stem of the plant, which may extend to girdle the stem leading to the plant death8. Due to the wide host range, long-term persistence in soil, and genetic variability of this pathogen, it is considered one of the dangerous plant pathogens, which results in high yield losses9.10, these fungicides are not desired due to some health concerns. One of the most crucial global environmental problems is the incorrect use of the chemical fungicides in agriculture11. Heavy application of these fungicides has resulted in an environmental pollution affecting human and animal health. Moreover, the microbial equilibrium and the biodiversity of microorganisms in the soil have also been affected12. Therefore, researches in the recent years have focused on finding safe alternatives for the plant disease management. Biological control using beneficial microorganisms represents an eco-safe and effective solution for this problem14. Biological control of R. solani using different fungi and bacteria has been investigated by many researchers15. Rashad et al.16 reported an overexpression in the polyphenol biosynthesis genes in the sunflower plants that were infected by R. solani when were treated with the mycorrhizal fungus Rhizophagus irregularis.In spite of the availability of some efficient chemical fungicides to control this disease17. Endophytes are known to produce unique bioactive metabolites, which enhance growth and induce tolerance of their hosts against various stresses. Aspergillus oryzae (Ahlb.) Cohn, a non-pathogenic and non-aflatoxigenic fungus that has been widely used in many fermentation industries such as enzymes production for baking. Furthermore, this fungus and its enzymes are accepted by FAO/WHO as food additives (probiotics), as well as in poultry18. Due to its high secreting ability, A. oryzae has been reported as an efficient cell factory for organic acids, industrial enzymes, and secondary metabolites along the past few decades19. It has various roles in the fields of food, therapeutics, forage, and the ecosystems20. Few researches have investigated the biocontrol activity of A. oryzae against various plant pathogens. In this concern, Alshannaq et al.21 reported an inhibitory effect for A. oryzae M2040 against production of aflatoxin B1 and growth of the toxigenic fungus A. flavus in vitro and on peanuts. The study reported also the production of A. oryzae M2040 for some antifungal compounds as a suggested mode of action. Furthermore, the nematicidal activity against Meloidogyne incognita was also reported for A. oryzae22.Endophytic fungi inhabit the plant for a period of their life without causing any injury or symptoms for the plantA. oryzae against R. solani, (2) detecting its antifungal metabolites, and (3) evaluating its biocontrol activity against Rhizoctonia root rot of sorghum.This work was aimed at (1) studying the antifungal activity of the endophyte A. oryzae (MK714921) confirming the identity of the endophytic fungus YRA3 as A. oryzae YRA3. The nucleotide sequence of A. oryzae YRA3 (584 bp) was deposited in the GenBank under the accession No. (OQ916424). The phylogenetic relationship with the closest species in the genus Aspergillus is illustrated in Fig. A. oryzae YRA3 was clustered with A. oryzae (MK714921) in a distinct subcluster with 89% bootstrap support. This subcluster was grouped with 89% bootstrap support with A. flavus (HQ285616). In the same time, A. niger (HM136829) and A. fumigatus (EU664466) were separately grouped in distinct subclusters, while A. sydowii (NR_131259) and A. nidulans (AY373888) were grouped in one subcluster. Aspergillus terreus (OP113794) was clustered as an outgroup taxon.The endophytic fungus YRA3 was molecularly identified using the ITS region of the DNA. Data obtained from the NCBI BLAST based on the ITS sequence revealed that the endophytic fungus YRA3 had 100% similarity with that of A. oryzae YRA3 was assessed against R. solani in vitro , peroxidase (POD), and chitinase II (CHI II) in sorghum roots, which were infected with R. solani and/or treated with A. oryzae YRA3 is presented in Fig. R. solani (P) overexpressed JERF3, while no significant change in its expression level was observed in response to their inoculation with A. oryzae YRA3 (B), compared to the control plants (C). The highest expression level for this gene was recorded for sorghum plants, which were inoculated with R. solani and A. oryzae YRA3, recording 9.7-fold. The results indicated that inoculation of sorghum plants with R. solani and/or A. oryzae YRA3 upregulated POD, at varying extents, compared with the control plants. However, R. solani had more inducing effect than A. oryzae YRA3 in this concern. The highest expression level of POD was recorded for the sorghum plants, which were inoculated with R. solani and A. oryzae YRA3, recording 7-fold. For CHI II, the obtained results showed that inoculation of the sorghum plants with R. solani and/or A. oryzae YRA3 considerably triggered CHI II, at varying degrees, compared to the negative control treatment. However, R. solani was more effective than A. oryzae YRA3 in this regard. The highest expression level of CHI II was recorded for the sorghum plants, which were inoculated with R. solani and A. oryzae YRA3, recording 5.5-fold.The transcriptional expression of jasmonate and ethylene-responsive factor 3 , but not on number of leaves. On the contrary, inoculating the sorghum plants with A. oryzae YRA3 significantly promoted most of the evaluated growth parameters, compared to the control, recording the highest values in this regard. In addition, inoculating of the infected sorghum plants with A. oryzae YRA3 significantly enhanced their growth parameters, except for the number of leaves, compared with that of the infected plants, which were not inoculated with A. oryzae YRA3.Table A. oryzae YRA3 are presented in Table R. solani led to an increment in the total phenols content as well as the activity of POD and PPO. In the same time, inoculating of the sorghum plants with A. oryzae YRA3 led to an increment in these parameters. However, the priming effect due to inoculating with R. solani was higher than that due to A. oryzae YRA3. The highest values in these parametrs were recorded for sorghum plants, which were inoculated with R. solani and A. oryzae YRA3, recording 312.8 ± 3.1 mg.g-1 fresh weight for the total phenols content and 3.59 ± 0.2 ∆A470 min−1 g−1 fresh weight and 2.69 ± 0.1 ∆A420 min−1 g−1 fresh weight for activity of POD and PPO, respectively.Total phenols and activity of the antioxidant enzymes peroxidase (POD) and polyphenol oxidase (PPO) in the infected sorghum plants that were inoculated with 7. Researches in the recent years have indicated that many of the endophytic fungi and bacteria have been recognized as promising biocontrol agents against various phytopathogenic fungi25. In this study, the antagonistic activity of A. oryzae YRA3 was assessed against the mycelial growth of R. solani in vitro. The obtained results showed a very strong antagonistic activity resulting in a complete inhibition of R. solani growth. This result is in agreement with that of Houda Sara et al.26 who reported an antifungal activity of the culture extract of A. oryzae against Candida albicans as well as an antibacterial activity against a wide range of bacteria. This result can be explained in the light of two modes of action: the first is the competition of A. oryzae YRA3 for the space and/or nutrients. The fast growth rate of A. oryzae YRA3 compared to that of R. solani, which was recorded in this study supports this mechanism. The second probable mechanism is the antibiosis via production of hydrolytic enzymes and/or antifungal metabolites. Endophytic fungi are considered an important source of unique bioactive metabolites27. Around 20,000 natural and bioactive products have been described from different endophytic microorganisms28. This ability can be attributed to the variation in the ecological niches in which these endophytes inhabit and the biotic and/or abiotic stresses they face29. To prove this hypothesis, a GC/MS analysis of the culture filtrate of A. oryzae YRA3 was carried out. Among the detected 32 compounds, different bioactive metabolites with antifungal background were identified, to them the antifungal behavior of A. oryzae YRA3 can be attributed. Among them, 2-heptanone, palmitic acid, heneicosane, and 2,3-butanediol are known to have an antifungal activity against different fungi31. In this concern, Wu et al.32 reported the antifungal activity of 2-heptanone against Fusarium oxysporum, the causal of Fusarium wilt of watermelon. Different antifungal mechanisms have been discussed in this regard such as increasing electrolyte leakage of the pathogen cell via disturbance of the cell membrane permeability and suppression of protein synthesis33.Rhizoctonia root rot is a destructive worldwide disease, which affects a wide host range resulting in a high yield lossA. oryzae YRA3, indicating the probable biocontrol activity of this endophyte. To investigate effect of application of this endophyte on the plant immunity, the transcriptional expression of three defense-related genes , that represent different signaling pathways, was studied. qPCR results indicated that JERF3, POD, and CHI II were significantly upregulated due to inoculation with A. oryzae YRA3. This indicates the resistance-inducing effect of A. oryzae YRA3 on the sorghum plants, particularly in case of the infection with R. solani. JERF3 is a responsive factor, which regulates a set of the resistance genes through both jasmonic acid and ethylene signaling pathways resulting in an induction of the plant immunity against the fungal infection34. This means that the recorded overexpression of JERF3 in this study may led to triggering of other defensive genes in the inoculated sorghum plants. This information was supported by the recorded upregulation of POD, and CHI II in this study that was associated with the JERF3 upregulation. CHI II gene encodes for the antifungal chitinase enzyme. This enzyme plays a crucial role in degrading the chitin, the main structural unit in the fungal cell wall35. Degradation of the chitin units in the fungal cell wall leads to a disturbance in the cell permeability, leakage of the cytoplasmic electrolytes, and finally the cell death36. The recorded upregulation of CHI II in this study due to application of A. oryzae YRA3 revealed the inducing effect of this endophyte on the plant resistance against the penetration of R. solani to the sorghum roots. The antioxidant gene POD encodes the peroxidase enzyme, which has an antioxidant role against the free radicals and the reactive oxygen species (ROS) resulted due to the different biotic or a biotic stresses37. Upregulation of POD was supported also by the recorded increment in the levels of the activity of the antioxidant enzymes (POD and PPO) in the infected sorghum plants that were inoculated with A. oryzae YRA3, compared with the untreated-infected plants. These antioxidant enzymes act as scavengers for the destructive free radicals and ROS that severely destroy the infected plant cells38. The observed overexpression of POD due to application of A. oryzae YRA3 indicated the inducing effect of this endophyte on the resistance of sorghum plants against fungal infection. The recorded overexpression of these defense-related genes indicated another indirect biocontrol mechanism of the endophyte A. oryzae YRA3.Under the greenhouse conditions, a significant suppression in the Rhizoctonia root rot severity was achieved in the infected sorghum plants that were inoculated with A. oryzae YRA3. The phenolic compounds are very fungi-toxic substances that naturally produced in the plants as a defense line against the fungal penetration and to prevent the transfer of the pathogen from cell to cell39. The increment in the phenolic content is usually used as a marker for the induction of the plant resistance40. In the line with this result, El-Sharkawy et al.41 reported an increment in the phenolic compounds in the wheat plants when were inoculated with the endophyte Epicoccum nigrum HE20 against stripe rust. Different mechanisms are known to be involved in priming plant resistance via endophytes such as thickening of the cell walls, phytoalexins secretion and synthesis of PR-proteins, which play a restricting role against the pathogen penetration and development42. Furthermore, a previous study reported that 2,3-butanediol, which detected in this study as a metabolite of A. oryzae YRA3, can induce the production of the root exudates which modulate the growth of the rhizospheric fungi and bacteria43. In addition, our results showed a growth-promoting effect for the application of A. oryzae YRA3 on the sorghum plants. The results showed a production of 2,3-butanediol in the culture filtrate of A. oryzae YRA3 that is known as a growth enhancer in many plant species43. This result is in agreement with that reported by Wu et al.32 who reported the growth-promoting effect of 2,3-butanediol on Arabidopsis thaliana plantlets. Production of this substance may explain the observed growth-promoting effect of A. oryzae YRA3.One of the most interesting results obtained in this study is the increment in the content of the phenolic compounds in the sorghum roots due to the inoculation with A. oryzae YRA3, isolated from the wild plant Atractylis carduus, has an antagonistic potential against R. solani in vitro. In addition, this endophyte showed a biocontrol activity under the greenhouse conditions, which may qualify A. oryzae YRA3 as a promising candidate to control Rhizoctonia root rot of sorghum as well as a plant growth-promotor. However, further investigations are still needed to evaluate its efficacy under the field conditions.These results demonstrated that R. solani (AG-2–2 IIIB) was kindly obtained from Agricultural Research Center, Egypt. The fungus was maintained on potato dextrose agar medium (PDA) at 4 °C. The fungal inoculum was prepared by culturing the phytopathogenic fungus R. solani on a sterilized maize/soil medium  for 15 days at 30 °C.Sorghum grains (cv. Shandaweel-1), obtained from Agricultural Research Center, Egypt, were used during the greenhouse evaluation. A virulent strain of Atractylis carduus (Forssk.) C.Chr., which was collected from a semi desert area in Borg EL-Arab, Alexandria, Egypt. Different pieces of the wild plant  were surface sterilized by immersing in NaOCl (0.5%) for 2 min, followed by immersing in ethanol (70%) for 2 min, then washing in dist. water. The surface sterilized plant pieces were put on PDA plates (4 pieces per plate) and incubated at 30 °C for 72 h. The recovered fungus was purified using the hyphal tip technique and morphologically identified based on its microscopic and cultural properties according to Pitt et al.44. The wild plant was identified by Dr. Ahmed Abd El-gawad, and deposited at the Herbarium of Faculty of Agriculture, Mansoura University under the deposition number (AW 1318/22/102).The endophytic fungus was isolated from the wild plant 23. To identify the endophytic fungus YRA3, the produced sequence was compared with various sequences in NCBI database. Sequence of the endophyte YRA3 and the closest ones from the GenBank database were aligned using the ClustalW algorithm and the phylogeny tree was constructed using the neighbor-joining method via MEGAX-10.2.445.The endophytic fungus YRA3 was molecularly identified by amplifying the internal transcribed spacer (ITS) part in the DNA. Extraction of the total DNA was performed using QiAamp DNA Kit . The universal primers ITS1 (5’TCC GTA GGT GAA CCT TGC GG3’) and ITS4 (5’TCC TCC GCT TAT TGA TAT GC3’) were used to amplify the ITS region (600 bp) according to Madbouly et al.A. oryzae YRA3 was tested against R. solani in vitro using the dual culture method. On a PDA plate, a 7 mm-diameter disc of A. oryzae YRA3, taken from a 5-days-old culture, and another disc from a 5-days-old culture of the pathogen were inoculated (7 cm) in opposite to each other in the plate. Plates singly inoculated with each fungus served as a control treatment. The PDA plates were incubated at 28 °C for a week. The mycelial growth of the growing fungi and the inhibition percentage were measured.The antagonistic potential of A. oryzae YRA3 was analyzed using a GC/MS-QP2010 system . The DB-5HT capillary column  was used. The programed oven temperature was as follows: 50 °C/1 min, 180 °C/1 min, 230 °C/2 min, and then 250 °C. All compounds were identified according to the NIST 11 Spectral Library .The chemical composition of the cultural filtrate of v/v) at 5 grains per pot. To prepare the inoculum of A. oryzae YRA3, the fungus was grown on PDA at 28 °C for a week. A conidial suspension was prepared in sterile water, mixed and adjusted at 106 conidia mL−1. Sorghum grains soaked in the conidial suspension of A. oryzae YRA3 for 2 h were planted in plastic pots at 5 grains per pot. Soil infestation was done 14 days post planting by mixing the pathogen inoculum with the upper layer of the soil at 2.5%. Four replicates of each treatment were applied. The pots were irrigated when necessary, and arranged in a complete randomized design in a greenhouse (31/20 °C day/night and 73% humidity). The treatments in this experiment were as follows: C = untreated control, P: infected with R. solani, B: uninfected-treated with A. oryzae YRA3, and PB: infected and treated with A. oryzae YRA3.Surface sterilized sorghum grains  were planted in plastic pots filled with sterilized sandy-clay soil (sand:clay 2:1 β-actine. The qPCR program was as follows: 1 cycle (95 °C/3 min), 45 cycles .Seven days after infection, sorghum roots of each treatment were sampled. Extraction of the total RNA was done using RNeasy Kit . cDNA of the extracted RNA was synthesized using a SureCycler 8800 thermocycler . The reaction composed of 20 μL containing total RNA (3 μL), buffer (2.5 μL), primer (5 μL), reverse transcriptase (0.2 μL), dNTPs (2.5 μL), and RNase-free water (6.8 μL). The program was performed at 42 °C/1 h, and at 70 °C/10 min. The real-time PCR was done by a Rotor Gene system . The reaction 20 μL composed of 3 μL cDNA, 12.5 μL SYBR Green Master Mix , 1.5 μL of each primer, and 1.5 μL RNase-free water. The used primers are presented in Table 46, where 0: no disease, 1: discoloration without necrosis, 2: discoloration with low necrosis, 3: discoloration with high necrosis, and 4: complete death. The following equation was used to calculate the disease severity47:To evaluate the disease severity, five sorghum roots of each treatment were collected 45 days post infection and rated according to a 5-degrees scale of Carling et al.1: the number of plants with score 1; n2: the number of plants with score 2; etc.; n5: the number of plants with score 5; and N: total number of plants used in the experiment.where; nFor each treatment, five sorghum plants were uprooted, washed under tap water, and evaluated for the growth parameters . The plant samples were dried at 85 °C for 72 h before be weighted.48. Activity of POD was determined according to Maxwell and Bateman49, while activity of PPO was determined as described by Galeazzi et al.50.Total phenols and activity of POD and PPO enzymes were estimated 45 days post infection in the sorghum roots. For extraction, 0.5 g of the sorghum root was homogenized in 5 mL ethanol (80%), then centrifuged at 3000 rpm for 20 min. The supernatant was collected and evaporated to the dryness. The residue was dissolved in 5 mL distilled water and used for estimation of the total phenols according to Malik and Singh51. Comparing of the means were done based on Tukey’s HSD test at p ≤ 0.05.The data were statistically analyzed using the CoStat softwareAuthors confirm that all the methods and experiments in this study, including the collection of plant material, complied with the institutional, national, and international guidelines and legislation.