Ti li畛u tr狸nh by v畛 畛nh lu畉t I Newton v t叩c 畛ng c畛a n坦 trong chuy畛n 畛ng c畛a c叩c v畉t. N坦 bao g畛m c叩c th鱈 nghi畛m l畛ch s畛 畛 minh h畛a qu叩n t鱈nh v kh叩i ni畛m v畉t c担 l畉p. Ngoi ra, ti li畛u c滴ng cung c畉p c叩c li棚n k畉t video v ti nguy棚n h畛 tr畛 li棚n quan 畉n ch畛 畛.
Ti li畛u tr狸nh by 畛nh lu畉t III Newton v 畛nh lu畉t v畉n v畉t h畉p d畉n, k竪m theo c叩c bi畛u th畛c v th鱈 nghi畛m li棚n quan. N坦 c滴ng so s叩nh l畛c c但n b畉ng v l畛c tr畛c 畛i, 畛ng th畛i tr狸nh by v畛 chuy畛n 畛ng c畛a v畉t b畛 n辿m v l畛c n h畛i. C叩c video h動畛ng d畉n v ti li畛u b畛 sung c滴ng 動畛c li畛t k棚 畛 h畛 tr畛 h畛c t畉p.
Ti li畛u tr狸nh by c叩c 畛nh lu畉t chuy畛n 畛ng c畛a Newton, bao g畛m 畛nh lu畉t II v III, c湛ng v畛i c叩c v鱈 d畛 v t狸nh hu畛ng th畛c t畉 li棚n quan 畉n l畛c t叩c d畛ng v ph畉n l畛c. C叩c bi t畉p v th鱈 nghi畛m minh h畛a s畛 t動董ng t叩c gi畛a c叩c v畉t th畛 c滴ng nh動 gi畉i th鱈ch v畛 gia t畛c v l畛c b棚n trong c叩c h畛 th畛ng kh叩c nhau. Ngoi ra, ti li畛u c滴ng cung c畉p c叩c li棚n k畉t 畉n video v ti nguy棚n h畛u 鱈ch cho vi畛c h畛c h畛i v畛 ch畛 畛 ny.
Ee341 dsp1 1_sv_chapter1_hay truy cap vao trang www.mientayvn.com de tai them...www. mientayvn.com
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This document provides an introduction to digital signal processing. It discusses signals, analog versus digital signals, sampling, quantization, coding, and analog-to-digital and digital-to-analog conversion. The key advantages of digital signal processing are also summarized, such as flexibility, reliability, size/power benefits, and suitability for sophisticated applications. Common digital signal processing applications are then outlined, including radar, biomedical processing, speech/audio, communications, image processing, and more.
Ti li畛u tr狸nh by c董 ch畉 bi畛u hi畛n gen trong th畛c v畉t, nh畉n m畉nh vai tr嘆 c畛a protein v c叩c y畉u t畛 i畛u h嘆a trong qu叩 tr狸nh t畛ng h畛p RNA v protein. N坦 c滴ng 畛 c畉p 畉n s畛 a d畉ng c畛a th畛c v畉t v h畛 mi畛n d畛ch 畛 畛ng v畉t c坦 v炭, 畉c bi畛t l c董 ch畉 t畉o ra kh叩ng th畛 qua vi畛c s畉p x畉p l畉i genome trong t畉 bo B. Cu畛i c湛ng, c叩c gi畉 thuy畉t v畛 s畛 a d畉ng c畛a kh叩ng th畛 動畛c n棚u ra, c湛ng v畛i c畉u tr炭c v ch畛c nng c畛a ch炭ng.
Ti li畛u l cu畛n bi t畉p v畛 v畉t l箪 nguy棚n t畛 v h畉t nh但n, ph畛c v畛 cho sinh vi棚n 畉i h畛c s動 ph畉m v gi叩o vi棚n. Cu畛n s叩ch bao g畛m hai ph畉n ch鱈nh: v畉t l箪 nguy棚n t畛 v v畉t l箪 h畉t nh但n, v畛i c叩c ch動董ng t坦m t畉t l箪 thuy畉t, bi t畉p m畉u v bi t畉p t畛 gi畉i. Cu畛i s叩ch c坦 ph畉n 叩p 叩n v h動畛ng d畉n gi炭p ng動畛i h畛c t畛 ki畛m tra v n畉m v畛ng ki畉n th畛c.
Ti li畛u tr狸nh by v畛 畛nh lu畉t I Newton v t叩c 畛ng c畛a n坦 trong chuy畛n 畛ng c畛a c叩c v畉t. N坦 bao g畛m c叩c th鱈 nghi畛m l畛ch s畛 畛 minh h畛a qu叩n t鱈nh v kh叩i ni畛m v畉t c担 l畉p. Ngoi ra, ti li畛u c滴ng cung c畉p c叩c li棚n k畉t video v ti nguy棚n h畛 tr畛 li棚n quan 畉n ch畛 畛.
Ti li畛u tr狸nh by 畛nh lu畉t III Newton v 畛nh lu畉t v畉n v畉t h畉p d畉n, k竪m theo c叩c bi畛u th畛c v th鱈 nghi畛m li棚n quan. N坦 c滴ng so s叩nh l畛c c但n b畉ng v l畛c tr畛c 畛i, 畛ng th畛i tr狸nh by v畛 chuy畛n 畛ng c畛a v畉t b畛 n辿m v l畛c n h畛i. C叩c video h動畛ng d畉n v ti li畛u b畛 sung c滴ng 動畛c li畛t k棚 畛 h畛 tr畛 h畛c t畉p.
Ti li畛u tr狸nh by c叩c 畛nh lu畉t chuy畛n 畛ng c畛a Newton, bao g畛m 畛nh lu畉t II v III, c湛ng v畛i c叩c v鱈 d畛 v t狸nh hu畛ng th畛c t畉 li棚n quan 畉n l畛c t叩c d畛ng v ph畉n l畛c. C叩c bi t畉p v th鱈 nghi畛m minh h畛a s畛 t動董ng t叩c gi畛a c叩c v畉t th畛 c滴ng nh動 gi畉i th鱈ch v畛 gia t畛c v l畛c b棚n trong c叩c h畛 th畛ng kh叩c nhau. Ngoi ra, ti li畛u c滴ng cung c畉p c叩c li棚n k畉t 畉n video v ti nguy棚n h畛u 鱈ch cho vi畛c h畛c h畛i v畛 ch畛 畛 ny.
Ee341 dsp1 1_sv_chapter1_hay truy cap vao trang www.mientayvn.com de tai them...www. mientayvn.com
油
This document provides an introduction to digital signal processing. It discusses signals, analog versus digital signals, sampling, quantization, coding, and analog-to-digital and digital-to-analog conversion. The key advantages of digital signal processing are also summarized, such as flexibility, reliability, size/power benefits, and suitability for sophisticated applications. Common digital signal processing applications are then outlined, including radar, biomedical processing, speech/audio, communications, image processing, and more.
Ti li畛u tr狸nh by c董 ch畉 bi畛u hi畛n gen trong th畛c v畉t, nh畉n m畉nh vai tr嘆 c畛a protein v c叩c y畉u t畛 i畛u h嘆a trong qu叩 tr狸nh t畛ng h畛p RNA v protein. N坦 c滴ng 畛 c畉p 畉n s畛 a d畉ng c畛a th畛c v畉t v h畛 mi畛n d畛ch 畛 畛ng v畉t c坦 v炭, 畉c bi畛t l c董 ch畉 t畉o ra kh叩ng th畛 qua vi畛c s畉p x畉p l畉i genome trong t畉 bo B. Cu畛i c湛ng, c叩c gi畉 thuy畉t v畛 s畛 a d畉ng c畛a kh叩ng th畛 動畛c n棚u ra, c湛ng v畛i c畉u tr炭c v ch畛c nng c畛a ch炭ng.
Ti li畛u l cu畛n bi t畉p v畛 v畉t l箪 nguy棚n t畛 v h畉t nh但n, ph畛c v畛 cho sinh vi棚n 畉i h畛c s動 ph畉m v gi叩o vi棚n. Cu畛n s叩ch bao g畛m hai ph畉n ch鱈nh: v畉t l箪 nguy棚n t畛 v v畉t l箪 h畉t nh但n, v畛i c叩c ch動董ng t坦m t畉t l箪 thuy畉t, bi t畉p m畉u v bi t畉p t畛 gi畉i. Cu畛i s叩ch c坦 ph畉n 叩p 叩n v h動畛ng d畉n gi炭p ng動畛i h畛c t畛 ki畛m tra v n畉m v畛ng ki畉n th畛c.
MOLD -GENERAL CHARACTERISTICS AND CLASSIFICATIONaparnamp966
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This is a brief note on types of organism on food with special focus on molds. This includes their general characteristics, spores; their classification, mycotoxins, and how the molds affect food.
The global scientific instruments market reached USD39.94billion in 2024 and is projected to grow at a 4.50% CAGR, hitting around USD62.03billion by 2034.This surge is driven by increasing R&D investments in pharmaceuticals, biotech, environmental testing, and industrial analytics. Demand for high-precision analytical and clinical analyzers supports growth across academic, industrial, and government sectors, fueled by stricter regulations and scientific collaborations worldwide.
How Psychology Can Power Product Decisions: A Human-Centered Blueprint- Shray...ShrayasiRoy2
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In an era where users are bombarded with endless choices, capturing attention and driving meaningful engagement isn't just about building features it's about understanding what drives human behavior at its core. This presentation offers a deep dive into how psychological principles can inform smarter, more intuitive product decisions. Its not just theory its a hands-on blueprint for applying human-centered thinking at every stage of product development.
Grounded in behavioral science, consumer psychology, and cognitive design, this deck unpacks the key psychological drivers behind user motivation, decision-making, emotional engagement, and habit formation. From attention economics and dopamine-driven interactions to trust cues, loss aversion, and the paradox of choice you'll see how to harness what the mind naturally does to build digital products people dont just use they return to, talk about, and even advocate for.
Well explore:
Cognitive biases that shape user perception and choices and how to use them to your advantage without crossing ethical lines.
Emotional design principles that build trust, trigger desire, and turn features into feelings.
User behavior loops that build stickiness, deepen retention, and create emotional investments.
Psychological friction when to reduce it for conversion, and when to add it for intentionality.
Dark patterns vs. ethical persuasion the thin line between influence and manipulation.
A/B testing with a psychological lens learning not just what works, but why it works.
This is more than UX research or product marketing fluff. Its a call to build with empathy, backed by science, and sharpened by real-world product thinking. Whether youre shaping onboarding flows, gamifying engagement, designing pricing models, or rethinking retention strategies this deck will arm you with a new lens: the human mind.
Perfect for product managers, growth strategists, UX designers, behavioral scientists, and anyone serious about building products that resonate, retain, and inspire action.
Because at the heart of every great product is a human.
Lets start building for the brain not just the screen.
Title: Abzymes mimickers in
catalytic reactions at nanoscales
Speaker: Orchidea Maria Lecian
Authors: Orchidea Maria Lecian, Sergey Suchkov
Talk presented at 4th International Conference on
Advanced Nanomaterials and Nanotechnology
12-13 June 2025, Rome, Italy on 12 June 2025.
Thiazole derivatives of N-substituted isatin have attracted significant interest due to their wide-ranging applications in medicinal chemistry, pharmaceuticals, and materials science. These compounds exhibit diverse biological activities, making them promising drug candidates, while their unique chemical structures offer potential in designing advanced functional materials. This presentation focuses on the synthesis and characterization of these derivatives through targeted chemical reactions involving various substituents on the isatin and thiazole cores, enabling the fine-tuning of their biological and physical properties. Characterization techniques such as NMR, FT-IR, Mass Spectrometry, and X-ray crystallography are employed to confirm molecular structures and analyze solid-state properties. These methods provide critical insights into the structureactivity relationships of the synthesized compounds. Our presentation highlights the synthetic pathways, structural elucidation, and potential applications of thiazole-based N-substituted isatin derivatives, aiming to support ongoing advancements in drug discovery and material development.
About Author:
Noor Zulfiqar is an award-winning chemist, Premium member of American Chemical Society (ACS), certified publisher & peer reviewer, and an experienced academic lecturer. As a professional content creator, she offers top-tier presentation design, research writing, and scientific content development services. Her multidisciplinary expertise spans computational science, chemistry, nanotechnology, environmental studies, socio-economics, human resource management, life sciences, engineering management, medical and pharmaceutical sciences, and business, her work ensures clarity, creativity, and academic excellence. Her services are ideal for those seeking impactful, visually compelling content tailored to diverse academic and research needs.
For collaborations or custom-designed academic content, feel free to reach out!
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Impact of Network Topologies on Blockchain Performancevschiavoni
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Best Student Paper Award at ACM DEBS 2025.
Paper here:
https://dl.acm.org/doi/10.1145/3701717.3730540
Since blockchains are increasingly adopted in real-world applications, it is of paramount importance to evaluate their performance across diverse scenarios. Although the network infrastructure plays a fundamental role, its impact on performance remains largely unexplored. Some studies evaluate blockchain in cloud environments, but this approach is costly and difficult to reproduce. We propose a cost-effective and reproducible environment that supports both cluster-based setups and emulation capabilities and allows the underlying network topology to be easily modified. We evaluate five industry-grade blockchains Algorand, Diem, Ethereum, Quorum, and Solana across five network topologies fat-tree, full mesh, hypercube, scale-free, and torus and different realistic workloads smart contract requests and transfer transactions. Our benchmark framework, Lilith, shows that full mesh, hypercube, and torus topologies improve blockchain performance under heavy workloads. Algorand and Diem perform consistently across the considered topologies, while Ethereum remains robust but slower.