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Cracking in hydraulic buried engineering can cause localized damage or complete structural failure, potentially resulting in catastrophic project outcomes. Traditional methods for detecting cracks in hydraulic concrete buried engineering are often insufficient in terms of reliability and accuracy. With the development and application of particle-based technology, it has been widely used in the field of crack detection. This research investigates the support pier of the Yingxiuwan Hydropower Plant and the lock pier of the Yuzixi Hydropower Plant. Employing principles from quantum physics, quantum particle non-destructive detection technology is introduced to identify crack locations. A three-dimensional simulation model is constructed and verified accurately through integration with CT scanning techniques. The results demonstrate that particle detection technology effectively detects cracks in hydraulic concrete buried engineering, exhibiting minimal susceptibility to external interference. The particle detection data enable 3D visualization of cracks, accurately reflecting the conditions within embedded concrete components. This method provides a reliable and advanced technical solution for precise crack detection in concrete-embedded engineering and offers critical data for exploring crack propagation mechanisms. [ABSTRACT FROM AUTHOR]

The objective of this study is to understand the customer journey in technology product adoption by exploring the experiences and perspectives of individuals who have recently adopted new technology products. This research aims to identify key themes and factors influencing the customer journey from initial awareness to ongoing engagement and retention, providing insights to enhance customer experiences and inform marketing strategies. This qualitative study employed semi-structured interviews with 20 participants selected through purposive sampling to ensure diverse representation. Participants included individuals who had recently adopted technology products within the past six months. Data collection continued until theoretical saturation was reached. The interview transcripts were analyzed using NVivo software, following an inductive approach to identify patterns and themes. The analysis revealed three main themes: Awareness and Decision-Making, First-Time Use and Learning, and Ongoing Engagement and Retention. Initial awareness was driven by advertising, social media, and word-of-mouth, while decision-making was influenced by peer recommendations, brand reputation, and price sensitivity. The first-time use phase highlighted the importance of intuitive design and support resources. Regular updates, community engagement, and product reliability emerged as critical factors in ongoing engagement and retention. Participants valued seamless omnichannel experiences, personalized marketing efforts, and robust support systems. The study underscores the significance of personalized, seamless customer journeys in technology product adoption. Businesses should focus on integrating physical and digital touchpoints, leveraging AI for personalized experiences, and maintaining active user communities to enhance customer satisfaction and loyalty. Addressing cultural nuances in global markets and managing digital signals effectively can further optimize the customer journey. These insights provide valuable guidance for businesses aiming to improve customer experiences and foster long-term engagement in the competitive technology market. [ABSTRACT FROM AUTHOR]

In this article, we explore multi-material additive manufacturing (MMAM) for conductive trace printing using molten metal microdroplets on polymer substrates to enhance digital signal transmission. Investigating microdroplet spread informs design rules for adjacent trace printing. We studied the effects of print distance on trace morphology and resolution, noting that printing distance showed almost no change in the printed trace pitch. Crosstalk interference between adjacent signal traces was analyzed across frequencies and validated both experimentally and through simulation; no crosstalk was visible for printed traces at input frequencies below 600 kHz. Moreover, we demonstrate printed trace reliability against thermal shock, whereby no discontinuation in conductive traces was observed. Our findings establish design guidelines for MMAM electronics, advancing digital signal transmission capabilities. [ABSTRACT FROM AUTHOR]

The proliferation of integrated sensing techniques in Sixth Generation (6G) networks is an increasingly significant aspect in facilitating efficient end-to-end communication for all users. The suggested methodology employs a digital signal processed with terahertz bandwidth to assess the impact of 6G networks. The primary focus lies in the design of 6G networks, emphasizing key parameters such interference, loss, signal strength, signal-to-noise ratio, and dual band channels. The aforementioned factors are combined with two machine learning algorithms in order to determine the extent of spectrum sharing among all available resources. Thus suggested approach for detecting signals in the terahertz communication spectrum is evaluated using 10 devices across four situations, which involve interference, signal loss, strength, and time margins for integrated sensing. Also the assumptions are based on signal processing devices operating within millimeter waves ranging from 5 to 10 terahertz. Interference and losses in the specified spectrum are seen to be less than 1%, but the time margin for integrated sensing with 99% maximized signal intensity remains at 85%. [ABSTRACT FROM AUTHOR]

Nowadays, there is an increasing demand for complex behavioral models on the market, as simulation has become the main verification approach used for both analog and digital functionalities. One of the most popular mixed-signal simulators nowadays is Simulation Program for Integrated Circuits Emphasis (SPICE). Over the last decade, the digital part in circuits has become predominant, but this poses big challenges when developing SPICE simulation models, as the circuits are synchronized upon internal or external clock signals, where the frequency accuracy is mandatory. The existing SPICE based simulators have built-in options to measure the signal frequency and duty cycle, but only after the simulation has completed, and in this way the frequency information can not be used during the simulation to synchronize the clock signals. There is a lot of research on frequency measurement techniques in the literature, but this topic has not been translated and covered in SPICE until now. Implementing the physical frequency measurement circuits proposed previously in the literature would increase the models’ complexity and the simulation time, without benefitting the final user. For this reason, in this article, a novel frequency measurement methodology for clock synchronization in SPICE based simulators is proposed, which aims to provide accurate measured frequency and duty cycle values for the digital clock signals with a fast simulation time. The performance evaluation of this methodology is done using OrCAD Capture, which is the most popular SPICE-based simulation environment.

With one-third of marriages in the United States beginning online, online dating platforms have become important curators of the modern social fabric. Prior work on online dating has elicited two critical frictions in the heterosexual dating market. Women, governed by age-old social norms of not making the first move, are inhibited in their interactions in that they do not initiate contact with men. On the other side, men send an abundance of messages, the majority of which do not convert to matches. A key distinguishing feature of online dating versus its traditional counterpart is the ability to leave a range of digital signals not replicable in the offline world. These digital signals can impact the nature of online dating platform outcomes. In this paper, we study the impact of a feature that reveals "who likes you" (WLY) on engagement, the number of matches, match efficiency, and match sorting in online dating. This feature reveals the identity of the voters who have rated the focal user with a like. To causally identify the effect of this feature, we conduct a large-scale randomized control trial in collaboration with a major North American dating platform. The treatment causes women to be more proactive, sending 7.4% more messages, which is a highly desirable market improvement given that men send double the number of messages compared with women. Further, we find that the women endowed with this feature increase their matches by 14.4%, whereas men increase their matches by 11.5%. Analyzing the moderating impact of desirability—a key aspect of the WLY feature—provides us with nuanced findings. Depending on the levels of each of the two parties' desirability, we see evidence of sorting, encouragement, and discouragement. This paper was accepted by Anandhi Bharadwaj, information systems. Supplemental Material: The Online Appendix is available at https://doi.org/10.1287/mnsc.2022.4576. [ABSTRACT FROM AUTHOR]

In this article, we explore multi-material additive manufacturing (MMAM) for conductive trace printing using molten metal microdroplets on polymer substrates to enhance digital signal transmission. Investigating microdroplet spread informs design rules for adjacent trace printing. We studied the effects of print distance on trace morphology and resolution, noting that printing distance showed almost no change in the printed trace pitch. Crosstalk interference between adjacent signal traces was analyzed across frequencies and validated both experimentally and through simulation; no crosstalk was visible for printed traces at input frequencies below 600 kHz. Moreover, we demonstrate printed trace reliability against thermal shock, whereby no discontinuation in conductive traces was observed. Our findings establish design guidelines for MMAM electronics, advancing digital signal transmission capabilities.

Background: The symptoms and associated characteristics of attention-deficit/hyperactivity disorder (ADHD) are typically assessed in person at a clinic or in a research lab. Mobile health offers a new approach to obtaining additional passively and continuously measured real-world behavioral data. Using our new ADHD remote technology (ART) system, based on the Remote Assessment of Disease and Relapses (RADAR)-base platform, we explore novel digital markers for their potential to identify behavioral patterns associated with ADHD. The RADAR-base Passive App and wearable device collect sensor data in the background, while the Active App involves participants completing clinical symptom questionnaires., Objective: The main aim of this study was to investigate whether adults and adolescents with ADHD differ from individuals without ADHD on 10 digital signals that we hypothesize capture lapses in attention, restlessness, or impulsive behaviors., Methods: We collected data over 10 weeks from 20 individuals with ADHD and 20 comparison participants without ADHD between the ages of 16 and 39 years. We focus on features derived from (1) Active App (mean and SD of questionnaire notification response latency and of the time interval between questionnaires), (2) Passive App (daily mean and SD of response time to social and communication app notifications, the SD in ambient light during phone use, total phone use time, and total number of new apps added), and (3) a wearable device (Fitbit) (daily steps taken while active on the phone). Linear mixed models and t tests were employed to assess the group differences for repeatedly measured and time-aggregated variables, respectively. Effect sizes (d) convey the magnitude of differences., Results: Group differences were significant for 5 of the 10 variables. The participants with ADHD were (1) slower (P=.047, d=1.05) and more variable (P=.01, d=0.84) in their speed of responding to the notifications to complete the questionnaires, (2) had a higher SD in the time interval between questionnaires (P=.04, d=1.13), (3) had higher daily mean response time to social and communication app notifications (P=.03, d=0.7), and (4) had a greater change in ambient (background) light when they were actively using the smartphone (P=.008, d=0.86). Moderate to high effect sizes with nonsignificant P values were additionally observed for the mean of time intervals between questionnaires (P=.06, d=0.82), daily SD in responding to social and communication app notifications (P=.05, d=0.64), and steps taken while active on the phone (P=.09, d=0.61). The groups did not differ in the total phone use time (P=.11, d=0.54) and the number of new apps downloaded (P=.24, d=0.18)., Conclusions: In a novel exploration of digital markers of ADHD, we identified candidate digital signals of restlessness, inconsistent attention, and difficulties completing tasks. Larger future studies are needed to replicate these findings and to assess the potential of such objective digital signals for tracking ADHD severity or predicting outcomes., (© Heet Sankesara, Hayley Denyer, Shaoxiong Sun, Qigang Deng, Yatharth Ranjan, Pauline Conde, Zulqarnain Rashid, Philip Asherson, Andrea Bilbow, Madeleine J Groom, Chris Hollis, Richard J B Dobson, Amos Folarin, Jonna Kuntsi. Originally published in JMIR Formative Research (https://formative.jmir.org).)

This work presents the cepstral covariance detector for spectrum sensing in cognitive radio. The power cepstral peaks of digitally modulated signals are exploited for spectrum sensing. To enhance the process of signal detection in low signal-to-noise ratio environments and with the knowledge of the data rate of the primary user signal, the cepstral covariance of the received signal is evaluated. The detection test statistic of the proposed detector is evaluated and an expression for the detection threshold is obtained under the null hypothesis. The detection performance of the proposed cepstrum-based detector is compared to covariance-based detectors and the obtained results validate its detection reliability at low signal-to-noise ratio levels with relatively low computational complexity. [ABSTRACT FROM AUTHOR]