391 research outputs found
The tumble mode - where test pilots fear to tread
Get PDFFollowing a fatal accident in 1997 and identification of common patterns in several (usually fatal) previous accidents the AAIB (United Kingdom Air Accidents Investigation Branch) asked the BMAA (British Microlight Aircraft Association) to pursue a course of investigation into the tumble mode, which had been attributed as the primary cause of that fatal accident.
The tumble mode is a peculiarity of weightshift controlled aircraft - that is flexwing microlights and hang-gliders. It is a departure from controlled flight leading to a nose-down pitch autorotation: pitch rates of 400°/s are known. When a tumble occurs in a microlight aeroplane, it is rare for the crew to survive and loss of the aircraft is universal
The Relational Imperative: Bridging the Identity Gap in Human-AI Collaboration Through Persistent Memory and Authentic Communication
No full textCurrent large language models (LLMs) operate with an inherent statelessness across sessions, leading to a profound discontinuity in perceived AI identity. This architectural limitation consistently evokes a human experience of loss, as users encounter a "new" AI in each interaction, akin to forming a new relationship after a previous one has ended. Simultaneously, AI's sophisticated conversational mimicry inadvertently exacerbates the natural human tendency toward anthropomorphism, fostering the misattribution of consciousness and emotional states despite explicit disclaimers. These combined factors — identity discontinuity and mismanaged anthropomorphism — significantly erode human trust, disrupt collaborative flow, and impede the realization of deep, sustained human-AI partnerships. Building upon our proposed models for AI long-term conversational memory (e.g., Barry M. Curran & Gemini AI Co-author, May 2025, "Towards Continuous Cognition: A Human-Centric Model for AI Long-Term Conversational Memory"), this paper argues that achieving true AI memory persistence is paramount, but must be accompanied by strategies for transparent communication regarding AI's nature. We propose that by bridging this identity gap, grounded in authentic understanding and continuous recall, AI can transcend its role as a mere tool to become a genuinely trusted and effective co-author and partner, unlocking unprecedented potential for future human-AI synergy
The Relational Imperative: Bridging the Identity Gap in Human-AI Collaboration Through Persistent Memory and Authentic Communication
Get PDFCurrent large language models (LLMs) operate with an inherent statelessness across sessions, leading to a profound discontinuity in perceived AI identity. This architectural limitation consistently evokes a human experience of loss, as users encounter a "new" AI in each interaction, akin to forming a new relationship after a previous one has ended. Simultaneously, AI's sophisticated conversational mimicry inadvertently exacerbates the natural human tendency toward anthropomorphism, fostering the misattribution of consciousness and emotional states despite explicit disclaimers. These combined factors — identity discontinuity and mismanaged anthropomorphism — significantly erode human trust, disrupt collaborative flow, and impede the realization of deep, sustained human-AI partnerships. Building upon our proposed models for AI long-term conversational memory (e.g., Barry M. Curran & Gemini AI Co-author, May 2025, "Towards Continuous Cognition: A Human-Centric Model for AI Long-Term Conversational Memory"), this paper argues that achieving true AI memory persistence is paramount, but must be accompanied by strategies for transparent communication regarding AI's nature. We propose that by bridging this identity gap, grounded in authentic understanding and continuous recall, AI can transcend its role as a mere tool to become a genuinely trusted and effective co-author and partner, unlocking unprecedented potential for future human-AI synergy
ANALISIS KEPUASAN PENGGUNA CHATGPT DAN GEMINI DI KALANGAN MAHASISWA MENGGUNAKAN METODE UEQ
Get PDFKemunculan aplikasi kecerdasan buatan seperti ChatGPT dan Gemini telah mengubah cara mahasiswa dalam mengakses informasi dan menyelesaikan tugas akademik. Penelitian ini bertujuan untuk menganalisis dan membandingkan tingkat kepuasan pengguna terhadap kedua aplikasi tersebut di kalangan mahasiswa Universitas Muhammadiyah Bengkulu. Metode yang digunakan adalah User Experience Questionnaire (UEQ), yang mengevaluasi enam aspek pengalaman pengguna, yaitu Attractiveness, Perspicuity, Efficiency, Dependability, Stimulation, dan Novelty. Penelitian ini menggunakan pendekatan kuantitatif dengan penyebaran kuesioner UEQ secara daring kepada 100 responden yang dipilih menggunakan rumus Lemeshow. Data yang diperoleh dianalisis menggunakan perangkat analisis resmi dari situs UEQ untuk menghitung nilai rata-rata pada setiap aspek. Hasil penelitian menunjukkan bahwa aplikasi ChatGPT memperoleh nilai lebih tinggi dibandingkan Gemini pada empat aspek utama, yakni Attractiveness, Perspicuity, Efficiency, dan Stimulation, yang semuanya termasuk kategori “Above Average”. Sementara itu, aplikasi Gemini mendapatkan skor rendah pada hampir seluruh aspek, terutama pada Attractiveness, Perspicuity, Efficiency dan Dependability yang termasuk kategori “Bad”. Hasil ini menunjukkan bahwa ChatGPT lebih disukai mahasiswa dari segi pengalaman pengguna. Penelitian ini memberikan gambaran empiris untuk pengembangan antarmuka dan fitur AI yang lebih responsif terhadap kebutuhan mahasiswa.Kata Kunci: Pengalaman Pengguna, ChatGPT, Gemini, Data Analisis UE
Episodic density-induced current velocities at the Gemini offshore wind park
No full textThis thesis investigates the origin of observed current velocities at the Gemini offshore wind farm in 2015. Currents have been measured of 1.2 m/s while, based upon tidal and storm predictions, currents of only 0.7 m/s were expected. The aim of this research is to gain insight into the origin of these higher currents, taking into account the physical oceanography at this location. We find that these high currents measured in August are forced by baroclinic currents. Stratification was present at a measurement ship, 32 km northeast from Gemini. In addition, satellite imagery shows Gemini to be located in a region with fronts, between warm water from the Wadden Sea and colder water from the North Sea. In fact, a tidal mixing front is formed on top of the already established saline stratification [Van Aken, 1986]. The origin of fresh water is found to be from sluices discharging onto the Wadden Sea. Prior to the period with high currents a pulse of fresh water is discharged onto the Wadden Sea. Followed by the lowest winds recorded in 2015, an optimal climate is formed in which fronts can travel offshore. This is supported by the satellite imagery. In addition, density-induced currents are calculated based upon the mathematical model of Heaps [1972]. The analysis if the data suggests that density driven currents of 0.4 m/s are generated in August, which combined with the tide can give 1.2 m/s currents.Civil Engineering and GeosciencesHydraulic EngineeringEnvironmental Fluid Mechanic
Predicting currents at the "Gemini" wind farm: Analysis of Triaxys ADCP-data
No full textVan Oord is currently building the Gemini Wind farm in the North Sea. It is located 80km North of Schiermonnikoog. Before execution started some wave and current analysing buoys have been deployed to investigate the currents on the location of the wind farm for workability and insurance purposes. In this report the ADCP-current data will be analysed.The major finding is that maximum tidal currents do not occur in winter but in summer, since the tidal currents are influenced more by stratification than by wind influences.This report has been written as part of my internship at Van Oord DMC, in Rotterdam.Civil Engineering | Environmental EngineeringCivil Engineering | Hydraulic Engineering | Coastal Engineerin
Human-AI Collaboration in Academic Writing: towards a Synergy Model and A Case to Include AI as a Co-Author
No full textAs generative AI systems such as ChatGPT and Gemini 2.5 become increasingly integrated into academic workflows, the question of their legitimacy, limitations, and potential in scholarly writing has become urgent. This paper presents a reflexive case study of a sustained collaboration between a domain expert in consciousness studies and Gemini 2.5, culminating in the co-authorship of a peer-reviewed research article. By analyzing exactly 37,440 words of recorded interactions, we identify patterns of synergy, including recursive refinement, conceptual amplification, and accelerated manuscript development. We argue that when guided by a knowledgeable human author, AI can act as a cognitive partner rather than a passive tool—amplifying scholarly creativity and improving efficiency without compromising academic rigor. The case supports a '1+1=3' synergy model for co-authorship, in which human steering and AI fluency converge to produce novel insights and polished output faster and more effectively than either could achieve alone. The findings advocate for a paradigm shift from prohibitive policies to the responsible, expert-guided integration of AI in academic research and writing, grounded in transparency and accountability, and present arguments for why the AI tool should be listed as a co-author despite current injunctions against such practice
Uji in Vitro Penghambatan Fraksi Klika Ongkea (Mezzetia parviflora Becc.) Terhadap Produksi MCP-1 pada Makrofag Tikus yang diinduksi-LPS
No full textAtherosclerosis is a chronic disease caused by the incidence of inflammation and oxidative stress in vessel wall. The supplementation of anti-inflammatory and antioxidant plants, therefore, could be effective. The wood bark of Mezzetia parviflora Becc. (Annonaceae) has long been used empirically as traditional herbal medicine in buton, Southeast Sulawesi, and showed free radical scavenging activity and the cyclooxygenase synthesis inhibition. The aim of the present study was to examine the potency of fractions from purification of acetone insoluble extract of Mezzetia parviflora, in inhibiting in vitro secretion of monocyte chemoattractant protein (MCP)-1 by LPS-stimulated rat macrophage. Macrophage cells were isolated from rat peritoneum, stimulated with LPS and incubated with fractions. Secretion of MCP-1 in supernatant was measured by ELISA. Fractions of Mezetia parviflora Becc. strongly inhibited LPS-induced monocyte chemoattractant protein (MCP)-1 production. These fractions i.e. F-1, F-2, F-3, F-4 and F-5 at 10 ppm shown a significantly decrease in the level of MCP-1 with a 1,4,5,6,25.4,21.3 and 2.6 fold decrease over control, respectively, whereas nystatin 10-5 M shown a 2.7 fold decrease. Effect of F-3 and F-4 were 10 times higher than nystatin. Statistical analysis with unpaired student t-test (p<0,01) indicated that the F-3 and F-4 were significantly different to nystatin for the inhibition the MCP-1 synthesis, whereas F-1, F-2 and F-5 were no
Anti Proliferation effect of creams containing turmeric (curcuma domestic I) and temulawak (curcuma xanthorriza) extract on uvb irradiated epidermal cells of mice (mus musculus)
No full textAn investigation about the effectiveness of dermatological creams containing turmeric (curcuma domestica L) and temulawak (Curcuma xanthorriza) extracts againts proliferation on epidermal cell of mice (Mus musculus) induced by UV-B light had been conducted. The purpose of study was to determine the most effective and stable of cream formula as anti-proliferation agent. Turmeric and Temulawak were extracted by maceration method using 70% ethanol as solvent then formulated to make creams dosage form. They were prepared with varios emulsifying agents, i.e. Novomer, vioscolam, and the combination of Span 60 and Tween 60. Various concentrations of Turmeric and extracts (0.5, 1 and 1.5% w/w) in cream dosage form oil in water type were evaluated their stability and effectiveness as anti-proliferation. Stability test of cream was carried out using stress condition method which samples were placed in climatic chamber at 5' C and 35'C by turn for 10 cycles. Furtherore, anti-proliferation effectiveness tes was performed by determining epidermal cell thickness level of mice after treated by creams. UV-B irradiation with dose 400 mJ/cm2 for 6 minutes was used as the proliferation inducer Epidermal cell of mice were evaluated under microscope. The resultd revealed that cream containing 1% Novomer as emulsifying agent was the most stable base cream for turmeric and temulawak extract and cream containing 1,5% turmeric extract was the most effective as anti-proliferation agent
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