Submission ID: 004
Category: Neuroscience & Biology
Everyday Curiosity:
When I was a kid I attacked an ant colony setup inside the seam of a concrete seat wall. I quickly discovered a white grain like substance that I assumed was their food source. The next day I returned to the wall and found that the surviving ants had collected the corpses of all the dead ants and neatly piled them in one area.
When I was a kid I attacked an ant colony setup inside the seam of a concrete seat wall. I quickly discovered a white grain like substance that I assumed was their food source. The next day I returned to the wall and found that the surviving ants had collected the corpses of all the dead ants and neatly piled them in one area.
AI Translated Thesis Title:
Ant Necrophoresis and Corpse Aggregation Responses Following Colony Disturbance in Urban Concrete Nests
Ant Necrophoresis and Corpse Aggregation Responses Following Colony Disturbance in Urban Concrete Nests
Core Academic Problem:
The observation highlights a gap in understanding how ants detect colony disturbance, prioritize corpse retrieval, and coordinate rapid spatial reorganization under attack, raising questions about the cognitive and structural mechanisms underlying collective hygienic behavior and emergency social organization in eusocial insects.
The observation highlights a gap in understanding how ants detect colony disturbance, prioritize corpse retrieval, and coordinate rapid spatial reorganization under attack, raising questions about the cognitive and structural mechanisms underlying collective hygienic behavior and emergency social organization in eusocial insects.
Suggested Research Methodology:
Hypothesis: ant colonies perform rapid necrophoresis and corpse aggregation after disturbance. Method: run controlled colony-perturbation trials on identical wall-seam microhabitats, varying disturbance intensity and mortality rate. Record with time-lapse video; quantify corpse removal latency, pile size, and worker response using behavioral annotation software. Analyze with survival curves and mixed-effects models. Compare to untreated controls and intact colonies. Validate “white grains” via microscopy/spectroscopy to distinguish brood, food, or debris.
Hypothesis: ant colonies perform rapid necrophoresis and corpse aggregation after disturbance. Method: run controlled colony-perturbation trials on identical wall-seam microhabitats, varying disturbance intensity and mortality rate. Record with time-lapse video; quantify corpse removal latency, pile size, and worker response using behavioral annotation software. Analyze with survival curves and mixed-effects models. Compare to untreated controls and intact colonies. Validate “white grains” via microscopy/spectroscopy to distinguish brood, food, or debris.
Associated Literature:
– E.O. Wilson (1971), The Insect Societies — foundational ant social behavior and colony organization. – J. P. Hölldobler & E.O. Wilson (1990), The Ants — classic reference on ant communication and hygiene. – Necrophoresis/colony sanitation research (e.g., Gordon 2010; Hughes et al. 2002) — why ants remove dead nestmates.
– E.O. Wilson (1971), The Insect Societies — foundational ant social behavior and colony organization. – J. P. Hölldobler & E.O. Wilson (1990), The Ants — classic reference on ant communication and hygiene. – Necrophoresis/colony sanitation research (e.g., Gordon 2010; Hughes et al. 2002) — why ants remove dead nestmates.
Submission ID: 003
Category: Neuroscience & Biology
Everyday Curiosity:
Whenever I look at blue-light blocking screens or night-mode settings on my phone, I still can’t sleep if the content I’m reading is stressful news. But if I read a cozy fiction book on a bright screen, I pass right out. I think sleep doctors are blaming the light color when they should be blaming the stress of the actual apps we look at.
Whenever I look at blue-light blocking screens or night-mode settings on my phone, I still can’t sleep if the content I’m reading is stressful news. But if I read a cozy fiction book on a bright screen, I pass right out. I think sleep doctors are blaming the light color when they should be blaming the stress of the actual apps we look at.
AI Translated Thesis Title:
The Relative Contributions of Screen Light Spectrum and Content-Induced Stress to Sleep Onset Latency on Mobile Devices
The Relative Contributions of Screen Light Spectrum and Content-Induced Stress to Sleep Onset Latency on Mobile Devices
Core Academic Problem:
Current sleep guidance may overattribute pre-sleep disruption to screen light characteristics while underexamining content-induced cognitive and affective arousal. The core gap is whether sleep interference is driven primarily by spectral exposure or by the psychological and structural properties of digital media, such as stress-provoking information versus soothing engagement.
Current sleep guidance may overattribute pre-sleep disruption to screen light characteristics while underexamining content-induced cognitive and affective arousal. The core gap is whether sleep interference is driven primarily by spectral exposure or by the psychological and structural properties of digital media, such as stress-provoking information versus soothing engagement.
Suggested Research Methodology:
Use a randomized crossover sleep study (n≈60) comparing four pre-bed conditions: stressful news vs cozy fiction × blue-light filter on/off. Measure sleep onset latency, awakenings, and next-morning alertness via actigraphy, EEG, and sleep diaries. Collect pre-sleep arousal/anxiety scales and screen-time logs. Analyze with mixed-effects models, testing content effects, light effects, and interaction. Optionally add eye-tracking and heart-rate variability to quantify cognitive/emotional activation.
Use a randomized crossover sleep study (n≈60) comparing four pre-bed conditions: stressful news vs cozy fiction × blue-light filter on/off. Measure sleep onset latency, awakenings, and next-morning alertness via actigraphy, EEG, and sleep diaries. Collect pre-sleep arousal/anxiety scales and screen-time logs. Analyze with mixed-effects models, testing content effects, light effects, and interaction. Optionally add eye-tracking and heart-rate variability to quantify cognitive/emotional activation.
Associated Literature:
– Chang et al. (2015), “Evening use of light-emitting eReaders negatively affects sleep…” – Cajochen et al. (2011), evening LED-backlit screen exposure and melatonin suppression – Ongoing area: cognitive/emotional arousal from media content, not just light wavelength, and sleep onset (e.g., screen content vs. bedtime use)
– Chang et al. (2015), “Evening use of light-emitting eReaders negatively affects sleep…” – Cajochen et al. (2011), evening LED-backlit screen exposure and melatonin suppression – Ongoing area: cognitive/emotional arousal from media content, not just light wavelength, and sleep onset (e.g., screen content vs. bedtime use)
Submission ID: 002
Category: Technology & Artificial Intelligence
Everyday Curiosity:
We are using AI tools to write all our corporate emails and reports, but now everyone sounds identical. It’s like standard corporate culture is wiping out personal writing voices entirely. Someone should study if AI assistant software is making human business writing completely sterile and killing unique company branding.
We are using AI tools to write all our corporate emails and reports, but now everyone sounds identical. It’s like standard corporate culture is wiping out personal writing voices entirely. Someone should study if AI assistant software is making human business writing completely sterile and killing unique company branding.
AI Translated Thesis Title:
The Homogenization of Corporate Communication: Effects of AI Writing Assistants on Voice, Authenticity, and Brand Distinctiveness
The Homogenization of Corporate Communication: Effects of AI Writing Assistants on Voice, Authenticity, and Brand Distinctiveness
Core Academic Problem:
Theoretical and empirical understanding is limited regarding how widespread reliance on AI writing assistants homogenizes corporate communication, suppresses individual and organizational voice, and potentially erodes brand distinctiveness. This gap concerns whether AI-mediated writing produces structural standardization that diminishes expressive authenticity, psychological ownership, and perceived uniqueness in business discourse.
Theoretical and empirical understanding is limited regarding how widespread reliance on AI writing assistants homogenizes corporate communication, suppresses individual and organizational voice, and potentially erodes brand distinctiveness. This gap concerns whether AI-mediated writing produces structural standardization that diminishes expressive authenticity, psychological ownership, and perceived uniqueness in business discourse.
Suggested Research Methodology:
Use a mixed-methods longitudinal study: collect pre/post AI adoption corpora of internal emails/reports from multiple firms plus employee surveys and writing tasks. Measure lexical diversity, stylistic variance, sentiment, and brand-voice alignment using NLP models (e.g., embeddings + stylometry classifiers, topic modeling). Add blind human raters for perceived distinctiveness and professionalism. Compare across AI-use intensity via regression or difference-in-differences; validate with interviews on writing behavior and editing practices.
Use a mixed-methods longitudinal study: collect pre/post AI adoption corpora of internal emails/reports from multiple firms plus employee surveys and writing tasks. Measure lexical diversity, stylistic variance, sentiment, and brand-voice alignment using NLP models (e.g., embeddings + stylometry classifiers, topic modeling). Add blind human raters for perceived distinctiveness and professionalism. Compare across AI-use intensity via regression or difference-in-differences; validate with interviews on writing behavior and editing practices.
Associated Literature:
– Hovy, B. (2015) — “Demographic factors can predict the quality of language generation” (stylistic variation and authorship). – Crystal, D. (2006) — Language and the Internet (computer-mediated writing and style). – Ongoing: AI-mediated writing, authorship attribution, and workplace communication homogenization studies.
– Hovy, B. (2015) — “Demographic factors can predict the quality of language generation” (stylistic variation and authorship). – Crystal, D. (2006) — Language and the Internet (computer-mediated writing and style). – Ongoing: AI-mediated writing, authorship attribution, and workplace communication homogenization studies.
Submission ID: 001
Category: Psychology & Human Behavior
Everyday Curiosity:
I’ve noticed that people who scroll short-form video clips (like TikTok or Reels) for more than an hour a day seem completely unable to handle long pauses or silence in normal conversations. They constantly interrupt or check their phones if a friend takes a 3-second breath. It feels like their conversational pacing is being rewired.
I’ve noticed that people who scroll short-form video clips (like TikTok or Reels) for more than an hour a day seem completely unable to handle long pauses or silence in normal conversations. They constantly interrupt or check their phones if a friend takes a 3-second breath. It feels like their conversational pacing is being rewired.
AI Translated Thesis Title:
The Effects of Prolonged Short-Form Video Consumption on Conversational Patience and Tolerance for Silence
The Effects of Prolonged Short-Form Video Consumption on Conversational Patience and Tolerance for Silence
Core Academic Problem:
The theoretical gap concerns whether sustained exposure to high-tempo, short-form video content alters conversational tolerance for temporal latency, thereby reducing patience for silence, pauses, and turn-taking in face-to-face interaction. This raises a psychological and structural question about media-induced recalibration of attention and social pacing in everyday communication.
The theoretical gap concerns whether sustained exposure to high-tempo, short-form video content alters conversational tolerance for temporal latency, thereby reducing patience for silence, pauses, and turn-taking in face-to-face interaction. This raises a psychological and structural question about media-induced recalibration of attention and social pacing in everyday communication.
Suggested Research Methodology:
Use a mixed-method, cross-sectional study: recruit 200 adults, split by short-form video use (60 min/day). Record 10-minute dyadic conversations with standardized pause tasks (2–5s silences). Measure interruption rate, phone-check latency, and pause tolerance via coded behavior. Analyze with mixed-effects regression and mediation models controlling for age, ADHD symptoms, and baseline anxiety. Supplement with phone-screen logs and passive app-usage data from Digital Wellbeing/Screen Time APIs.
Use a mixed-method, cross-sectional study: recruit 200 adults, split by short-form video use (60 min/day). Record 10-minute dyadic conversations with standardized pause tasks (2–5s silences). Measure interruption rate, phone-check latency, and pause tolerance via coded behavior. Analyze with mixed-effects regression and mediation models controlling for age, ADHD symptoms, and baseline anxiety. Supplement with phone-screen logs and passive app-usage data from Digital Wellbeing/Screen Time APIs.
Associated Literature:
– Ophir, Nass & Wagner (2009) — Media multitasking and attentional control – Alter (2017) — Irresistible: addictive design, reward loops, and attention capture – Conversation analysis/turn-taking research (Sacks, Schegloff & Jefferson, 1974) — pause timing, interruption, and response latency
– Ophir, Nass & Wagner (2009) — Media multitasking and attentional control – Alter (2017) — Irresistible: addictive design, reward loops, and attention capture – Conversation analysis/turn-taking research (Sacks, Schegloff & Jefferson, 1974) — pause timing, interruption, and response latency