Content Streams Research Articles

EduLive: Re-Creating Cues for Instructor-Learners Interaction in Educational Live Streams with Learners' Transcript-Based Annotations

Educational live streaming has become a complement to in-person teaching. While synchronous instructor-learner communication is useful, the technology-mediated nature of live streaming can obscure many interaction cues (e.g., learners' facial expressions and body language), which dampens the instructors' ability to respond to remote learners' needs. We explore the opportunity of leveraging real-time transcripts generated from instructors' audio as a basis for re-creating interaction cues. Transcripts can be leveraged to reveal the content of live streams in a form that learners can trace back and annotate, and such annotations can be further aggregated and presented to instructors as signals to assist them in tracking learners' engagement. By designing and evaluating our proof-of-concept prototype system, EduLive, we show that instructors benefited from the summative information extracted from learners' annotations, and the context provided by the transcript enhanced their ability to answer learners' questions. Our system contributes to the design space of social annotations in CSCW by employing social annotations in educational live streaming scenarios.

The Impact of Live E-commerce on Consumers' Willingness to Shop: Beauty and Food Areas

Numerous academics have been researching live e-commerce as its form and content continue to diversify and as more platforms become engaged. This article synthesises the results of research on the impact of food and beauty live streaming e-commerce content and the performance of its anchors on consumer purchase intentions. Research has shown that both the content of the live stream and the performance of the anchor have a positive effect on consumer purchase intentions. For food live streaming e-commerce, the credibility of the anchor, social interaction and immersive experience all have a positive impact on consumer purchase intention. For beauty live broadcasts, the provision of free trial samples and the anchors rewarding sales language have a positive impact on consumers purchase intention. In addition, this paper also find that the same stimuli in beauty and food live streaming e-commerce have different impacts on consumers purchase intention. Audiences of beauty products are more inclined to get effective product information and rewards in a short period of time, while audiences of food products are more inclined to a sense of experience and inspiration. Finally, this study suggests directions in which future research could be conducted on the impact of technological developments in the live streaming e-commerce room on consumer purchase intentions.

The Impact of E-commerce Live Streaming on Consumer Purchasing Behavior in the Influencer Economy

This study investigates the impact of e-commerce live streaming on consumer purchasing behavior, focusing on the current market size, the promotion efforts of mainstream media and businesses, and conversion rates. The results show that the market for live streaming is expanding rapidly, with businesses and media viewing it as a key traffic source and marketing tool. The conversion rate of live stream content is also higher than traditional e-commerce marketing methods. However, the influence of live streaming is not entirely positive, highlighting the need for increased regulation and more rigorous market standards. E-commerce platforms and influencers must also deepen their understanding of consumer needs to build trust and optimize their content to suit purchasing behavior.

Controls on the stable Mo isotopic composition of inner-continental precipitation

The molybdenum (Mo) isotope budget of the surface environment has been well characterized in recent decades, facilitating accurate mass balance modeling of the ancient redox-driven Mo cycle. One yet unresolved component is the range of possible processes and sources that result in isotopically heavy river waters relative to continental sources. Following a recent hypothesis that isotopically heavy δ98Mo of precipitation may control the final δ98Mo of river water relative to its continental source bedrock, we investigated the δ98Mo composition of 19 snow samples from three locations in Central Europe: the Swiss Alps (“Alpine” samples) from the Hochalpine Forschungsstation Jungfraujoch (HFSJ) in both summer and winter, the Swiss Jura Mountains in winter and the French Vosges Mountains in winter. Stream waters from two snowmelt-fed streams were additionally collected from the Alpine site. Snow sample δ98Mo compositions were highly variable, ranging from −0.03 to +1.93 ‰, with no clear mixing trends indicating complex sources, source pathways, or post-depositional processing. Only the winter snow samples from the high-altitude HFSJ site had δ98Mo values consistently heavier than typical continental crust. The δ98Mo results were coupled with radiogenic Sr isotopic, major ion, and trace element compositions as tracers for three major sources of airborne ion inputs: sea salt, mineral dust, and anthropogenic aerosols. We found that the most likely source of Mo to precipitation in the lower elevation Vosges and Jura Mountains samples was isotopically light soil mineral dust, which reflected the underlying bedrock sources, with a likely additional anthropogenic component. The isotopically heavy winter snow samples at the elevated HFSJ site were attributed to a higher input of carbonate mineral dust from long-distance transport of carbonate-rich Saharan dust, which was overwritten in the summer by an influx of low elevation sources transported upwards during higher vertical thermal mixing. Finally, we concluded that precipitation has a negligible direct effect on the overall Mo content and isotopic composition of inner continental European streams and rivers relative to other sources, such as bedrock weathering. Future time-series studies may augment these conclusions to show possible heterogeneity of precipitation as well as the addition of sample sites closer to marine sources, where a larger flux of isotopically heavy marine aerosols to streams might be expected.

Ammonia inhibition in anaerobic digestion of organic waste: a review

AbstractAnaerobic digestion (AD) has become the technology of choice for organic waste treatment as an environmentally beneficial and sustainable waste treatment technology. However, the nitrogen content of these organic waste streams is generally high. Ammonia is produced in the biodegradation of nitrogenous organic matter. Low concentrations of ammonia favour AD, but high concentrations can lead to digestive system failure. To address the issue of ammonia inhibition and ensure the stability of the digestive system, numerous physical, chemical, and biologicalmethods aimed at controlling ammonia levels and/or strengthening the biological processes have been proposedand developed. Literature evidence suggests that differences in AD reaction conditions and microbial sources result in different tolerances of the digestive system to ammonia and nitrogen. This paper summarises and compares the inhibitory effects of ammonia nitrogen under different conditions and the existing regulatory measures to alleviate ammonia nitrogen inhibition. In addition, since the core of the digestive system is microorganisms, this paper explains the mechanism of ammonia stress especially at the microbial level, and in this way, it explores the future direction of research using biofortification. This review provides a theoretical reference for solving the problem of ammonia nitrogen inhibition.

An autonucleolytic suspension HEK293F host cell line for high-titer serum-free AAV5 and AAV9 production with reduced levels of DNA impurity

We sought to engineer mammalian cells to secrete nuclease activity as a step toward removing the need to purchase commercial nucleases as process additions in bioprocessing of AAV5 and AAV9 as gene therapy vectors. Engineering HeLa cells with a serratial nuclease transgene did not bring about nuclease activity in surrounding media whereas engineering serum-free, suspension-adapted HEK293F cells with a staphylococcal nuclease transgene did result in detectable nuclease activity in surrounding media of the resultant stable transfectant cell line, "NuPro-1S." When cultivated in serum-free media, NuPro-1S cells yielded 3.06×1010 AAV5 viral genomes (vg)/mL via transient transfection, compared with 3.85×109 vg/mL from the parental HEK293F cell line. AAV9 production, followed by purification by ultracentrifugation, yielded 1.8×1013 vg/mL from NuPro-1S cells compared with 7.35×1012 vg/mL from HEK293F cells. AAV9 from both HEK293F and NuPro-1S showed almost identical ability to transduce cells embedded in a scaffold tissue mimic or cells of mouse neonate brain tissue invivo. Comparison of agarose gel data indicated that the DNA content of AAV5 and AAV9 process streams from NuPro-1S cells was reduced by approximately 60% compared with HEK293F cells. A similar reduction in HEK293F cells was only achievable with a 50U/mL Benzonase treatment.

Sentiment Analysis on Twitter through Machine Learning: A Comprehensive Approach with User-Centric Visualisations

Sentiment analysis is a crucial field that deals with the intricate task of identifying and systematically categorizing the various perspectives and opinions expressed within the original text. In today's digital age, social media platforms serve as a prolific source of data, inundated with a relentless stream of status updates, tweets, and content imbued with sentiments. Analysing the sentiments conveyed by users in this vast reservoir of data holds a pivotal role in comprehending the collective sentiments of the user community, dissecting dialogues, and aggregating viewpoints. This, in turn, can be instrumental in shaping strategies for commerce, conducting insightful political research, and gauging the pulse of communal activities. Examining sentiments on Twitter presents an increased difficulty because of the frequency of spelling errors, casual language, icons, and emojis. This research focuses on Twitter sentiment analysis, with a specific emphasis on a particular user account. The approach involves a combination of Python programming and Machine Learning techniques. By embarking on a comprehensive sentiment analysis journey within a specific domain, the aim is to discern the profound impact of that domain's data on sentiment categorization. Furthermore, this paper introduces a novel feature that enhances the organization of a user's most recent tweets and their presentation through visual aids such as graphs, charts, and word clouds. This visualization approach empowers a more intuitive and insightful exploration of the sentiments and trends embedded within the user's Twitter activity, facilitating a deeper understanding of their thoughts and emotions as expressed through their digital interactions.

Analysis of LazLive Utilization in Mobile Applications Lazada at Sahoor Time

Live streaming is becoming a global trend that is popularly used in many sectors, including e-commerce. Lazada, as one of the largest app-based e-commerce in Southeast Asia, also utilizes the use of live streaming by initiating LazLive (Lazada Live Streaming) as one of the featured features in their mobile application. Unlike most e-commerce such as Tokopedia and Shopee, Lazada as a brand also creates official live stream content from the company through a series of special programs, which are actual features as well as customized marketing messages. This study aims to examine Lazada's strategy of creating a new live streaming method in its mobile application (LazLive). Based on the view of the social construction theory of technology, this study analyzed 23 Lazada live streams held from March 23 to April 24, 2023, during sahoor time. Using a descriptive qualitative approach, this study used content analysis techniques. The results found that (1) Lazada personalized several of its live streaming features to match the feel of the program, and (2) Lazada continues to update its features according to customer needs and feedback. (3) LazLive received a positive response from Lazada app users and contributed to the number of reviews received by the Lazada mobile app in the Google Play Store. All the innovations that Lazada provides through LazLive are expected to increase application consumers and the welfare of sellers.

Biogas upgrading by intensified methanation (SESaR): Reaction plus water adsorption - desorption cycles with Ni-Fe/Al2O3 catalyst and LTA 5A zeolite

This work is conducted within the framework of the Power to Gas (PtG) technologies, focusing on the topic of “biogas upgrading”. The objective is to enhance the CH4 content of biogas streams by utilizing the CO2 present in these streams through the Sabatier reaction, thereby producing a renewable alternative to natural (fossil) gas. Referred to as “SESaR”(Sorption Enhanced Sabatier Reaction), this process employs a catalytic fixed-bed reactor, featuring selective water adsorption using LTA 5A zeolites, as an innovative approach to traditional methanation reactors. The catalyst used comprises Ni-Fe (7.5:2.5 wt/wt) as the active metallic phase supported on γ-Al2O3. Experimental work has been divided in two sets of trials. The first set focuses on the hydrogenation of CO2 as single reactant (H2 also supplied in the inlet with 4:1 = H2:CO2 molar ratio). The second set of experiments was carried out with a synthetic gas mixture representative of a sweetened biogas stream (molar ratio CH4:CO2 = 7:3). Maximum intensification behavior for CO2 conversion was found at 350 °C, also showing that CH4 presence in the inlet gas has negligible influence on the conversion of CO2. Selectivity to CO is minimized at temperatures exceeding 300 °C and remains constant after three consecutive cycles of methanation, water adsorption, and desorption. The Fe-Ni catalyst has demonstrated sustained performance throughout the experimental cycles, exhibiting no significant loss of activity.

Content Filtering with Inattentive Information Consumers

We develop a model of content filtering as a game between the filter and the content consumer, where the latter incurs information costs for examining the content. Motivating examples include censoring misinformation, spam/phish filtering, and recommender systems acting on a stream of content. When the attacker is exogenous, we show that improving the filter’s quality is weakly Pareto improving, but has no impact on equilibrium payoffs until the filter becomes sufficiently accurate. Further, if the filter does not internalize the consumer’s information costs, its lack of commitment power may render it useless and lead to inefficient outcomes. When the attacker is also strategic, improvements in filter quality may decrease equilibrium payoffs.

Water Quality and Dissolved Organic Carbon Content in Agricultural Streams: Northern Nile Delta Region, Egypt

Sustainable development goals (SDGs) 2 (zero hunger), 6 (clean water and sanitation), and 15 (life on land) are related to the human-water-soil nexus. Soil organic carbon and nutrients can be removed and transported to waterways through runoff and drainage. The main goals of this study are to quantify the water quality for irrigation and assess the dissolved organic carbon (DOC) contents in streams in the northern Nile Delta, Egypt. A 4-year water quality monitoring program is accomplished by collecting 35 irrigation and drainage water samples per year from the study area. The measured water quality parameters are as follows: salinity, pH, Na, SAR, Cl, and NO3–N. In addition, the DOC content is accessed. The salinity hazard ranged from moderate, for most irrigation samples, to high and very high for drainage samples. All collected water samples have low to medium sodium hazards. Results indicate that average DOC contents in irrigation canals are 2.32 and 2.93 mg L−1 for the summer and winter, respectively. The respective means of DOC concentration in drainage canals for the summer and winter seasons are around 3.96 and 5.09 mg L−1. This study revealed significant differences in EC, pH, Na, Cl, and SAR, as water quality parameters, between irrigation and drainage canals. Additionally, the studied agroecosystem has seasonal variability in DOC concentration in irrigation and drainage canals between summer and winter. Overall, reusing drainage water for irrigation in the study area requires the selection of suitable crops and site-specific management.

Glass Fibre Composites Recycling Using the Fluidised Bed: A Comparative Study into the Carbon Footprint in the UK

The UK has no established process for recycling waste glass fibre-reinforced thermosets that are widely used within wind blade structures. Consequently, these materials are typically disposed of in landfills or undergo energy recovery in waste facilities. This study investigates the carbon footprint of the fluidised bed process for recycling glass fibre composite waste, considering the present and future scenarios of composite waste management in the UK. The impact was compared to conventional disposal routes and other prominent recycling technologies, such as cement kiln co-processing and mechanical recycling, by developing energy and material flow models for each waste treatment strategy. Variables, such as the type of waste, the quantity of recycling facilities in the UK, and waste haulage distance, were examined to inform the lowest impact deployment of recycling technologies. Cement kiln co-processing, mechanical, and fluidised bed recycling technologies reduced the global warming potential of processing wind blade waste compared with conventional disposal routes, with impacts of −0.25, −1.25, and −0.57 kg CO2e/kg GRP waste, respectively. Mechanical recycling had the lowest global warming potential resulting from low greenhouse gas emissions associated with the process itself and potentially high offsets by replacing glass fibre in the production of moulding compound. Composite wind turbine blade waste was found to be a particularly promising feedstock for the fluidised bed process due to relatively low resin content diminishing direct greenhouse gas emissions during thermal decomposition, as well as high material recovery offsets due to the high glass fibre content of this waste stream.

Sensitivity analysis of heat flow of heat exchangers in ethanol-water distillation column

In this study sensitivity analysis was made with Unisim Design process simulator software for ethanol-water mixture. The effect of the reflux ratio and the number of trays on the heat flow of the heat exchangers was investigated in case of different purification of bottom product. The results of the sensitivity analysis showed that the heat flow of the reboiler averagely 1.94 times higher than the heat flow of the condenser. Afterwards, the effect of the thermal state of the feed stream was investigated on the heat flow of the condenser and the reboiler. In each cases the mass flow and ethanol content of the distillate stream were also investigated. The results showed that in the studied cases the liquid volume percent of the ethanol varies between 65% and 87%. A simplified cost estimation was calculated with the determination of mass flow of cooling water and low-pressure steam. From the results it was concluded that higher number of trays, higher temperature of the feed stream and higher ethanol content in the bottom product resulted lower costs of the utility streams.

Iron ore tailings valorization through separate characterization and upgradation of different tailings streams of an Iranian iron ore processing plant.

In iron ore processing plants, different tailing streams are usually transferred to the tailings thickener for partial dewatering and finally transferred to the tailings dam as a single stream. Therefore, the mixing of different tailings streams happens. This way can challenge the process of reprocessing the tailings in the tailings dam since the mixing of different tailings streams causes more complexity in the mineralogical composition as well as the chemical composition of the tailings in the tailings dam. To solve this problem, the idea of separate characterization and separate upgradation of different tailings streams of an iron ore processing plant was carried out and a comparison was made between the results of magnetic upgradation of each tailings streams with the total tailings (i.e., the tailings in the tailings dam, which is a mixture of different tailings streams of the plant). Hence, the different tailings streams of an iron ore processing plant were sampled and characterize for total iron, FeO content, particle size distribution, mineralogical composition by X-ray diffraction (XRD), magnetic behavior by Davis tube tests, and dry solid tonnage rate. The characterization results showed that the iron grade and dominant iron ore mineral vary from one stream to another tailings stream of the iron ore processing plant. For instance, the total iron content of different tailings streams varies in the range of 18.46 to 64.68% and the dominate iron ore mineral in the Cobber tailings was hematite, but in the other tailings streams it was magnetite. The magnetic upgradation of the Cobber and Rougher tailings and also the total tailings were performed separately by the wet magnetic separation at different magnetic field intensities of 2000, 3500, 5000, and 15,000 Gauss. A concentrate with the highest iron grade of 61.79% and yield of 52.15% was produced from magnetic upgradation of the Rougher tailings, but magnetic upgradation of the total tailings produced a concentrate with the iron grade of 37% and yield of 15.2%. A comparison between the magnetic upgradation of the total tailings and the Cobber and Rougher tailings revealed that the upgradation of Rougher tailings results in a concentrate with higher iron grade and yield than the total tailings.

Insights into Circular Economy Potential of Lithium by System Dynamic Modelling of Material Streams

AbstractLithium is a key raw material for producing lithium‐ion batteries. This study applies system dynamics modelling to demonstrate the (1) global lithium demand in specific lithium applications from 2005 to 2050, (2) the adequacy of lithium reserves for future lithium demand, (3) lithium content of waste streams throughout lithium value chain and (4) potential of various circular strategies for answering to the rising lithium demand. According to the modelling results, the main lithium application is battery electric vehicle batteries (almost 60 % in 2023 to 80–90 % by 2050) with current battery chemistries. Without circular strategies, 75–85 % of lithium is wasted throughout the value chain. Circular strategies may reduce the waste considerably (7–47 %), but to maintain sustainable supply of lithium a stacking of multiple complementary circular strategies over the lithium value chain is required.

Using multilinear regressions developed from excitation-emission matrices to estimate the wastewater content in urban streams impacted by sanitary sewer leaks and overflows

Failing sewer infrastructure introduces unknown quantities of raw wastewater into urban streams, raising human and ecological health concerns. To address this problem, we developed multilinear regressions that relate fluorescent dissolved organic matter to wastewater content. The models were constructed with the area-normalized regional volumes of excitation-emission matrices measured for mixtures of deionized water, surface water from a wastewater-impacted stream, wastewater from a sanitary sewer adjacent to the stream, and Suwannee River natural organic matter. The best performing multilinear regression had a standard error of 0.55 % wastewater. A matrix-matched calibration was used to internally validate the approach and confirm the wastewater content of select samples. The multilinear model was externally validated through (i) comparison to concentrations of contaminants of emerging concern in surface water and wastewater and (ii) extension to samples from previous campaigns that employed alternative wastewater indicators. Using the validated model, we estimated an average wastewater content of 2.4 ± 4.0 % in 165 samples collected from 14 locations in the Gwynns Falls watershed (USA) between April 2019 and April 2023. The maximum wastewater content was 35 % at a site where sanitary sewer leaks and overflows have been previously documented. The reported approach represents a cost-effective and scalable technique to estimate wastewater content in urban streams through analysis of fluorescent dissolved organic matter.

Consumer Purchasing Power Prediction of Interest E-Commerce Based on Cost-Sensitive Support Vector Machine

The traditional e-commerce business chain is being reconstructed around the content of short videos and live streams, and the interest e-commerce is thriving as a new trend in the e-commerce industry. Diversified content promotes the rapid development of interest e-commerce. For consumers, their preferences for different content reflect their consumption level to a certain extent. The purpose of this study is to accurately predict the purchasing power level with the consumer content preference, and provide new ideas for interest e-commerce business. In this paper, the new swarm intelligence algorithm is used to find the optimal misclassification cost, and three cost-sensitive models are established. On this basis, the content preference of interest e-commerce consumers is used to predict the level of purchasing power. The results show that the content preference of interest e-commerce consumers, such as “fashion”, “photography” and “interpretation”, have a significant effect on the prediction of purchasing power at the 95% confidence level. The accuracies of the optimized cost-sensitive support vector machine in predicting consumer purchasing power are all above 0.9, and the highest is 0.9792. This study effectively alleviates the problem that the classification results tend to be biased towards negative samples, especially when the imbalanced rate of the sample is high. It not only provides researchers with an efficient parameter optimization method, but also reflects the relationship between consumer content preference and purchasing power, providing data support for interest e-commerce operations.

Frequency and content dual stream network for image dehazing

Image dehazing can improve image clarity and visual effect, which plays a pivotal role in many computer vision tasks. Existing dehazing methods are mostly based on a single feature stream and tend to ignore the low-frequency characteristics of haze. In this paper, we propose a dual stream network for image dehazing. To enhance the edge information and texture detail of the image, we construct a frequency stream based on attention octave convolution. We decompose the features into high and low-frequency branches in the frequency stream to obtain different structural information. By adding a residual channel attention block, the attention octave convolution can extract frequency features more efficiently and effectively. Due to the lower resolution of low-frequency features in the frequency stream, the frequency stream features alone are insufficient for recovering the overall content of the image. Therefore, a content stream was added to compensate for the information lost in the frequency stream. By fusing the outputs of two feature streams, the network achieves an enhanced dehazing performance. The results show that our method is superior to other state-of-the-art algorithms in quantitative evaluation and visual impact.

Evaluation of heavy metals, mycotoxins and mineral bioaccessibility through in vitro static digestion models of rainbow trout (Oncorhynchus mykiss) and sole (Dover sole) side stream extracts obtained by pressurized liquid extraction.

The recovery of antioxidants and minerals as well as the content of contaminants of rainbow trout and sole side streams (head, skin and viscera) extracts obtained by pressurized liquid extraction (PLE) were evaluated. Then, the effect of the gastrointestinal digestion was tested. No mycotoxins were detected in the extracts, while heavy metals contents (mg/kg) were up to 2.9 (As), 0.054 (Cd), 0.16 (Hg) and 0.073 (Pb), being below maximum legislated limits. A positive effect of PLE was found for the antioxidant capacity recovery, being the oxygen radical capacity of sole head and skin extracts significantly enhanced after digestion (∼3.8 times). PLE significantly increased Mg, Fe, Zn, Se and P (KPLE>1) contents of rainbow trout side streams, Zn (KPLE5.97) and Fe (KPLE 2.80) of head sole and Mg, Se and P of all samples. Moreover, Mg, Ca and Fe bioaccessibility was lower in all sole extracts compared to rainbow trout.

Anaerobic Digestion of Olive Mill Wastewater and Process Derivatives—Biomethane Potential, Operation of a Continuous Fixed Bed Digester, and Germination Index

Olive mill wastewater (OMW) management is an economic and environmental challenge for olive oil-producing countries. The recovery of components with high added value, such as antioxidants, is a highly researched approach that could help refinance performant wastewater treatment systems. Anaerobic (co-)digestion is a suitable process to valorize the energetic and nutritional content of OMW and OMW-derived waste streams from resource recovery processes. Issues of process stability, operation, and yields discourage industrial application. Deepening the understanding of biomethane potential, continuous anaerobic digester operational parameters, and co-substrates is key to large-scale implementation. The biomethane potential of different OMW-derived samples and organic solid market waste as co-substrate was 106–350 NL methane per kg volatile solids (VS). The highest yields were obtained with the co-substrate and depolyphenolized OMW mixed with retentate from an ultrafiltration pretreatment. Over 150 days, an anaerobic fixed-bed 300 L digester was operated with different OMW-derived substrates, including OMW with selectively reduced polyphenol concentrations. Different combinations of organic loading rate and hydraulic retention time were set. The biogas yields ranged from 0.97 to 0.99 L of biogas per g of volatile solids (VS) eliminated, with an average methane content in the produced biogas of 64%. Potential inhibition of the process due to high polyphenol concentrations or over-acidification through volatile fatty acids was avoided in the continuous process through process and substrate manipulation. High concentrations of potassium and low concentrations of nitrogen and phosphate end up in the digestate. Sulfate reduction results in high H2S concentrations in the biogas. The digestate was tested for phytotoxic properties via the germination index. Diluted digestate samples improved germination by up to 50%.