Contrary to predictions, motivated investor framing did not suppress AI fraud warnings; if anything, it marginally increased them.
这一发现挑战了传统观点,表明在投资者动机的影响下,AI系统在欺诈检测方面表现更佳,甚至可能略微提高了警告的频率。
Contrary to predictions, motivated investor framing did not suppress AI fraud warnings; if anything, it marginally increased them.
这一发现挑战了传统观点,表明在投资者动机的影响下,AI系统在欺诈检测方面表现更佳,甚至可能略微提高了警告的频率。
This ultimately also leads to false positives, but my manual QA run verified it's maybe 5-10%.
大多数人认为AI检测系统应该追求零错误,但作者接受5-10%的误报率,这挑战了技术检测的完美主义标准。这种务实态度暗示在AI识别领域,准确率和实用性之间需要权衡,而非盲目追求完美。
Socket, an a16z portfolio company, detected the malicious dependency in the Axios attack within 6 minutes of its publication. That's roughly 63,000 times faster than the industry average.
令人惊讶的是:Socket公司在Axios攻击发布后仅6分钟就检测到恶意依赖,这比行业平均水平快约63,000倍。这种速度差异凸显了传统安全工具与新型行为检测方法之间的巨大鸿沟,也展示了早期检测在防止供应链攻击中的关键作用。
The industry average time to detect a supply chain breach is 267 days. SolarWinds went undetected for 14 months. XZ Utils took two years to surface.
令人惊讶的是:软件供应链漏洞的平均检测时间长达267天,有些攻击如XZ Utils甚至需要两年才被发现。这意味着攻击者有充足的时间在系统中潜伏并造成广泛损害,而组织往往在损害发生后才意识到问题。
The industry average time to detect a supply chain breach is 267 days. SolarWinds went undetected for 14 months. XZ Utils took two years to surface. Socket, an a16z portfolio company, detected the malicious dependency in the Axios attack within 6 minutes of its publication.
检测时间的巨大差异(267天与6分钟)展示了安全检测领域的革命性变化。传统方法依赖已知漏洞数据库,而新型行为分析系统能够在攻击发生时立即检测到异常行为,这种能力差异决定了安全事件的严重程度。
Socket, an a16z portfolio company, detected the malicious dependency in the Axios attack within 6 minutes of its publication. That's roughly 63,000 times faster than the industry average.
令人惊讶的是:安全公司Socket能在恶意包发布后6分钟内检测到问题,比行业平均水平快约63,000倍。更令人震惊的是,他们在第一个受损的Axios版本发布前16分钟就发现了问题,因为他们直接检测到了可疑的依赖包本身。
Socket, an a16z portfolio company, detected the malicious dependency in the Axios attack within 6 minutes of its publication. That's roughly 63,000 times faster than the industry average.
大多数人认为供应链攻击需要数月甚至数年才能被发现,但作者展示了新型安全工具可以在几分钟内检测到攻击,比行业平均水平快63000倍。这表明安全检测范式正在从基于CVE的静态检查转向基于行为的实时分析。
Real-time monitoring of agent actions with a 12-category anomaly detection system derived from frontier model safety evaluations. Three-level alert system: PROHIBITED (immediate block), HIGH_RISK_DUAL_USE (human review), DUAL_USE (log and track).
这种三级警报系统展示了AI安全监控的精细化程度,将代理行为分为不同风险级别,从完全禁止到仅记录跟踪。这种分类方法反映了AI安全中'双重用途'挑战的复杂性,即同一技术既可用于防御也可用于攻击。
Legacy platforms rely on brittle, hand-written rules. An engineer writes a detection rule : 'if events A, B, & C happen in sequence, fire an alert.' It works for a couple months.
这一描述揭示了传统安全检测系统的根本局限性:规则脆弱且需要持续维护。'works for a couple months'这一表述特别有洞察力,暗示了传统方法在快速变化的IT环境中根本不可持续,这为Artemis的自主检测系统提供了强有力的合理性。
On these tasks, our Gemini Robotics-ER models improve over baseline Gemini 3.0 Flash performance (+6% in text, +10% in video) in perceiving injury risks accurately.
这一数据展示了AI在安全风险识别方面的具体进步,特别是在视频理解上的显著提升(+10%)。这表明机器人系统正在更好地理解人类环境中的潜在危险,这一能力对于实现人机协作至关重要。然而,这也引发了一个深刻问题:当AI能够识别风险时,它是否应该被赋予干预决策的权力?这涉及到AI自主性与人类监督之间的平衡问题。
It also discovered a 16-year-old vulnerability in FFmpeg—which is used by innumerable pieces of software to encode and decode video—in a line of code that automated testing tools had hit five million times without ever catching the problem.
令人惊讶的是:Claude Mythos Preview在FFmpeg中发现了一个存在16年的漏洞,而这个漏洞在被自动化测试工具执行了500万次后仍未被发现。这揭示了AI在代码分析方面具有传统自动化工具无法比拟的独特洞察力。
For example, people who themselves use AI writing tools heavily have been shown to accurately detect AI-written text. A panel of human evaluators can even outperform automated tools in a controlled setting
This statement alone is very interesting to me because in my personal opinion I believe that AI is either a great tool for learning but at the same time it can hinder our abilities to learn.
H. Ma, B. Ghojogh, M. N. Samad, D. Zheng and M. Crowley, "Isolation Mondrian Forest for Batch and Online Anomaly Detection," 2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC), Toronto, ON, Canada, 2020, pp. 3051-3058, doi: 10.1109/SMC42975.2020.9283073.
The algorithm fuses two ideas, "isolation" from ensemble trees methods for anomaly detection and "Mondrian forests" which can learn flexible regression models from streaming data.
MvP : "Direct Multi-view Multi-person 3D Pose Estimation" Tao Wang, Jianfeng Zhang, Yujun Cai, Shuicheng Yan, Jiashi Feng
Influential paper on learning consistent skeletal models of human pose from multiview images
Really interesting and innovative method for using multiview perspective data to learn human pose and pedestrian detection.
However, sinceevery block in GSN is signed, when one breaches privacy within the protocol the breach carriestheir signature so the culprit can be identified.
What stops a culprit to send off-group a message that is not his own? We can only achieve the "culprit detection" by addressing and signing every message we send to A. This is a lot of re-signing. And we won't have a convergent DAG.
Résumé de la vidéo [00:00:00][^1^][1] - [00:12:53][^2^][2]:
Cette vidéo présente le rôle crucial du psychologue scolaire dans le soutien des élèves en difficulté, en évaluant leur intelligence et en proposant des solutions adaptées pour améliorer leur parcours éducatif.
Points forts: + [00:00:00][^3^][3] Le rôle du psychologue scolaire * Évalue l'intelligence des élèves * Propose des solutions éducatives + [00:01:36][^4^][4] L'intervention du psychologue * Réalise un bilan intellectuel et psychologique * Suggère des orientations ou des redoublements + [00:06:07][^5^][5] Formation et rémunération * Détails sur la formation requise * Salaire de débutant à fin de carrière + [00:07:12][^6^][6] Cas pratiques d'intervention * Exemples d'accompagnement d'élèves * Discussion sur les défis en zone rurale + [00:10:00][^7^][7] Rencontres avec les parents * Diagnostic et solutions pour les élèves * Importance de l'acceptation parentale
les négligences sont bien perçues dans la petite enfance mais pas très bien perçu à l'adolescence
Résumé de la vidéo [00:00:07][^1^][1] - [00:21:14][^2^][2]:
La vidéo aborde l'impact des négligences sur le parcours des enfants, soulignant la difficulté de les repérer et de les mesurer, ainsi que les défis associés à leur diagnostic et à leur traitement dans le système de santé.
Points forts: + [00:00:07][^3^][3] Introduction au sujet * Importance de l'expression sur les négligences + [00:01:07][^4^][4] Définition des négligences * Absence de réponse aux besoins fondamentaux + [00:02:06][^5^][5] Problèmes de diagnostic * Manque de données et difficulté d'évaluation + [00:03:08][^6^][6] Facteurs de risque * Confusion entre facteurs de risque et prédictifs + [00:06:09][^7^][7] Diagnostic médical * Complexité et absence de standardisation + [00:07:00][^8^][8] Codage des négligences * Limitations du système de codage actuel + [00:09:03][^9^][9] Caractérisation judiciaire * Défis dans l'identification et la caractérisation des dommages + [00:11:13][^10^][10] Collecte de données * Obstacles au croisement des données de recherche + [00:13:27][^11^][11] Cas clinique * Exemple réel illustrant les défis de la négligence + [00:17:02][^12^][12] Expérimentation nationale * Initiative pour améliorer les soins et la coordination Résumé de la vidéo [00:21:16][^1^][1] - [00:36:04][^2^][2] : La vidéo aborde l'impact des négligences sur les enfants en protection de l'enfance, en mettant l'accent sur l'importance d'une coordination médicale adaptée et sur les défis liés aux systèmes d'information et à la recherche.
Points forts : + [00:21:16][^3^][3] Coordination médicale * Plus de 300 médecins pour les bilans annuels * Importance de la coordination sur-mesure + [00:23:22][^4^][4] Recherche et données * Difficultés liées à la collecte de données pour la recherche * Importance des bilans standardisés + [00:25:00][^5^][5] Systèmes d'information * Problèmes avec les systèmes informatiques * Différences entre les systèmes des ARS + [00:27:27][^6^][6] Collecte de données * Entraves à la collecte et à l'utilisation des données * Complexité des interactions entre soins et recherche + [00:30:17][^7^][7] Avancées malgré les obstacles * Réalisation des bilans annuels pour les enfants * Importance de la vue externe des professionnels de ville + [00:31:18][^8^][8] Négligences et violences * Exemples concrets de négligences et de violences intriquées * Difficultés de prise en charge et d'identification des violences
Résumé de la vidéo [00:00:00][^1^][1] - [00:30:24][^2^][2]:
La vidéo traite de l'application des principes de la théorie de l'attachement dans l'évaluation des capacités parentales, en particulier dans le contexte de la protection de l'enfance au Québec. Elle souligne l'augmentation significative des signalements traités par la DPJ et l'importance d'une évaluation précise pour le placement des enfants.
Points clés: + [00:00:00][^3^][3] Introduction à la théorie de l'attachement * Application dans l'évaluation des capacités parentales + [00:00:58][^4^][4] Statistiques sur la maltraitance * Augmentation des signalements au Québec + [00:03:01][^5^][5] Importance de l'évaluation * Impact sur les décisions de placement des enfants + [00:06:41][^6^][6] Définition des capacités parentales * Large vision par la DPJ + [00:07:45][^7^][7] Facteurs influençant les capacités parentales * Risques et protections issus de l'environnement écologique + [00:11:07][^8^][8] Défis de l'évaluation des capacités parentales * Manque de consensus et méthodes d'évaluation + [00:15:58][^9^][9] Principes pour évaluer les capacités parentales * Évaluation des forces et limites, qualité des interactions, et potentiel de changement + [00:22:03][^10^][10] Rôle de la théorie de l'attachement * Interventions de courte durée pour améliorer la sensibilité parentale + [00:25:11][^11^][11] Attachement désorganisé chez les enfants maltraités * Comportements contradictoires et besoin d'évaluation précise Résumé de la vidéo [00:30:27][^1^][1] - [00:59:54][^2^][2]:
La vidéo présente une conférence sur l'évaluation des capacités parentales et l'importance d'intégrer la théorie de l'attachement dans ce processus. Elle souligne l'efficacité des interventions basées sur l'attachement pour améliorer les relations parent-enfant et les comportements des enfants.
Points forts: + [00:30:27][^3^][3] L'importance de l'attachement * Nécessité d'intégrer l'attachement dans l'évaluation des capacités parentales + [00:33:04][^4^][4] Efficacité des interventions * Les interventions fondées sur l'attachement améliorent l'adaptation sociale et émotionnelle des enfants + [00:34:11][^5^][5] Intervention relationnelle * Utilisation de la rétroaction vidéo pour valoriser les comportements sensibles des parents + [00:41:22][^6^][6] Recherche sur l'évaluation * Étude des bénéfices d'un protocole d'évaluation intégrant une intervention sur l'attachement + [00:45:43][^7^][7] Décisions de placement * Impact de l'intervention relationnelle sur les décisions de placement et la récurrence de maltraitance + [00:57:52][^8^][8] Prédiction de la récurrence * L'évaluation basée sur l'intervention relationnelle prédit mieux la récurrence de maltraitance Résumé de la vidéo [00:59:58][^1^][1] - [01:22:22][^2^][2]:
La vidéo aborde l'évaluation des capacités parentales et l'impact des traumatismes vécus dans l'enfance sur la capacité à prendre soin des enfants. Elle souligne l'importance de la théorie de l'attachement et de la formation des évaluateurs pour améliorer les jugements et les interventions.
Points forts: + [01:00:34][^3^][3] Analyse des évaluations * Importance des antécédents de maltraitance * Influence des traumatismes sur les propositions + [01:02:02][^4^][4] Formation des évaluateurs * Impact de la théorie de l'attachement * Développement des habiletés d'observation + [01:03:18][^5^][5] Mesures dans les protocoles d'évaluation * Nécessité d'observer l'interaction parent-enfant * Importance de la sensibilité et du potentiel de changement + [01:04:35][^6^][6] Supervision et rétroaction vidéo * Utilisation des vidéos pour la supervision * Effet positif sur la réduction des défenses des parents + [01:06:02][^7^][7] Recommandations pour les protocoles d'évaluation * Formation continue en théorie de l'attachement * Création d'équipes spécialisées en intervention relationnelle + [01:07:26][^8^][8] Importance de la supervision continue * Supervision basée sur les vidéos des familles * Maintien et développement de l'expertise des intervenants
As long as money hasexisted, the problem of counterfeit currency has too, but it became aparticular problem once printed notes went into general circulation. Ineighteenth-century North America, Benjamin Franklin – who owned a firmthat printed money for several of the colonies – hit on the idea of misspellingPennsylvania on official currency, on the grounds that forgers would spell it
correctly and the notes could easily be spotted as counterfeit, but that only went so far.
revenir un peu sur les représentation qui sont trop communément admises que les enfants maltraités les enfants en grande difficultés seraient en échec 00:42:41 scolaire déjà l'équipe de Koffman d 94 relevait que les enfants victimes de maltraitance étaient de tiers avoir de bons résultats à l'école donc en plus ce qui est intéressant c'est que ces 00:42:54 enfantsl ils passent sous les radars parce que comme ils surinvestissent l'école au moins l'école ils arrivent à y vivre ils sont pas repérés à l'école on va avoir plutôt tendance à repérer ceux qui sont remarqués ceux qui sont en échec scolaire
A second, complementary, approach relies on post-hoc machine learning and forensic anal-ysis to passively identify statistical and physical artifacts left behind by media manipulation.For example, learning-based forensic analysis techniques use machine learning to automati-cally detect manipulated visual and auditory content (see e.g. [94]). However, these learning-based approaches have been shown to be vulnerable to adversarial attacks [95] and contextshift [96]. Artifact-based techniques exploit low-level pixel artifacts introduced during synthe-sis. But these techniques are vulnerable to counter-measures like recompression or additivenoise. Other approaches involve biometric features of an individual (e.g., the unique motionproduced by the ears in synchrony with speech [97]) or behavioral mannerisms [98]). Biomet-ric and behavioral approaches are robust to compression changes and do not rely on assump-tions about the moment of media capture, but they do not scale well. However, they may bevulnerable to future generative-AI systems that may adapt and synthesize individual biometricsignals.
Ernest Hemingway’s idea of the ‘crap detector’
source?
Google has had the ability to harden SafetyNet checks using hardware-backed key attestation for several years now. The fact that they refrained to do so for 3 years has allowed users to enjoy root and Magisk Modules without sacrificing the ability to use banking apps. However, it seems that Magisk's ability to effectively hide the bootloader unlock status is soon coming to an end. It's a change that we've expected for years, but we're sad to see it finally go into effect.
https://docs.google.com/document/d/163G79vq-mFWjIqMb9AzYGbr5Y8YMGcpbSzJRutO8tpw/edit
Howard Rheingold, et al. A Guide to Crap Detection Resources
Summarization of Methods for DeFi Optimization
squashed resource table of methods for DeFi Optimization.
What is color for?" And instead of telling you, I'll just show you. What you see here is a jungle scene, 00:02:08 and you see the surfaces according to the amount of light that those surfaces reflect. Now, can any of you see the predator that's about to jump out at you? And if you haven't seen it yet, you're dead, right? (Laughter) Can anyone see it? Anyone? No? Now let's see the surfaces according to the quality of light that they reflect. And now you see it. So, color enables us to see 00:02:32 the similarities and differences between surfaces, according to the full spectrum of light that they reflect. But what you've just done is in many respects mathematically impossible. Why? Because, as Berkeley tells us, we have no direct access to our physical world, other than through our senses. And the light that falls onto our eyes is determined by multiple things in the world, not only the color of objects, 00:02:56 but also the color of their illumination, and the color of the space between us and those objects. You vary any one of those parameters, and you'll change the color of the light that falls onto your eye. This is a huge problem, because it means that the same image could have an infinite number of possible real-world sources
BEing journey 2 pattern detection
Leo Poon. (2022, January 15). @MackayIM @Clin_Chem_AACC HK has another lay of swiss cheese. Testing waste water to identify COVID positive buildings, following by mandatory testing on occupants. It can find some silent spreaders. Https://t.co/2wu6QG6Db1 [Tweet]. @world_epidemic. https://twitter.com/world_epidemic/status/1482189879010217986
Yaniv Erlich on Twitter. (n.d.). Twitter. Retrieved February 8, 2022, from https://twitter.com/erlichya/status/1482847821397176325
Camero, K. (n.d.). If You Think You Have COVID But Your Rapid Test Is Negative, Here’s Why. BuzzFeed News. Retrieved February 4, 2022, from https://www.buzzfeednews.com/article/katiecamero/negative-covid-test
Mrigank Shail, MD. (2022, January 11). Update on Omicron by Dr @mvankerkhove from @WHO’s Q&A https://t.co/NqCOvs59Tl [Tweet]. @mrigankshail. https://twitter.com/mrigankshail/status/1481006646826577925
Scientists try to pinpoint why rapid Covid tests are missing some cases. (2022, January 6). STAT. https://www.statnews.com/2022/01/06/scientists-try-to-pinpoint-why-rapid-covid-tests-are-missing-cases/
Mahase, E. (2021). Covid-19: Do vaccines work against omicron—and other questions answered. BMJ, 375, n3062. https://doi.org/10.1136/bmj.n3062
Omicron cases may be far higher than currently confirmed, variant marker analysis reveals. (2021, December 8). Inews.Co.Uk. https://inews.co.uk/news/health/omicron-covid-cases-may-be-seven-times-higher-than-confirmed-1341156
Lai, J., German, J., Hong, F., Tai, S.-H. S., McPhaul, K. M., Milton, D. K., & Group, for the U. of M. S. R. (2021). Comparison of Saliva and Mid-Turbinate Swabs for Detection of COVID-19 (p. 2021.12.01.21267147). https://doi.org/10.1101/2021.12.01.21267147
Evaluating Omicron and Other COVID Variants to Ensure Test Effectiveness. (n.d.). Abbott. Retrieved December 3, 2021, from https://www.abbott.com/corpnewsroom/diagnostics-testing/monitoring-covid-variants-to-ensure-test-effectiveness.html
Cauchemez, S., & Bosetti, P. (2021). A reconstruction of early cryptic COVID spread. Nature. https://doi.org/10.1038/d41586-021-02989-3
FAKE NEWS DETECTION IN PRACTICE
The article showed the scientific processes that can be used in analyzing information and how they applied it in fact-checking. Technology makes fact-checking easier and faster but humans are still the most accurate. That is why studying information science is important because of its relevance to the society.
Covid: Lateral flow tests more accurate than first thought, study finds—BBC News. (n.d.). Retrieved October 15, 2021, from https://www.bbc.co.uk/news/health-58899612
Shahsavari, S., Holur, P., Wang, T., Tangherlini, T. R., & Roychowdhury, V. (2020). Conspiracy in the time of corona: automatic detection of emerging COVID-19 conspiracy theories in social media and the news. Journal of Computational Social Science, 3(2), 279–317. https://doi.org/10.1007/s42001-020-00086-5
Ministers ‘failed to act on Bedford Covid variant surge for two weeks’ | Coronavirus | The Guardian. (n.d.). Retrieved May 24, 2021, from https://www.theguardian.com/world/2021/may/23/ministers-failed-to-act-on-bedford-covid-variant-surge-for-two-weeks
Armitage, C., Keyworth, C., Leather, J., Byrne-Davis, L., & Epton, T. (2020). Identifying Targets For Interventions To Support Public Adherence To Government COVID-19-Related Instructions. PsyArXiv. https://doi.org/10.31234/osf.io/8gfvb
Mallapaty, S. (2020). The mathematical strategy that could transform coronavirus testing. Nature. https://doi.org/10.1038/d41586-020-02053-6
Peeters, A., Mullins, G., Becker, D., Orellana, L., & Livingston, P. (2020). COVID-19’s impact on Australia’s health research workforce. The Lancet, 396(10249), 461. https://doi.org/10.1016/S0140-6736(20)31533-6
that garbage has ZERO damned business in an e-mail which is why a great many places use HTML only e-mail as a trigger for spam detection! (if you send multipart as both text/html and text/plain, you're fine)
Tan, Steph H., Orchid Allicock, Mari Armstrong-Hough, and Anne L. Wyllie. ‘Saliva as a Gold-Standard Sample for SARS-CoV-2 Detection’. The Lancet Respiratory Medicine 0, no. 0 (19 April 2021). https://doi.org/10.1016/S2213-2600(21)00178-8.
Xu, Z., & Guo, H. (2018). Using Text Mining to Compare Online Pro- and Anti-Vaccine Headlines: Word Usage, Sentiments, and Online Popularity. Communication Studies, 69(1), 103–122. https://doi.org/10.1080/10510974.2017.1414068
Carl Bergstrom: “People are using data to bullshit.” (2020, August 1). The Guardian. http://www.theguardian.com/science/2020/aug/01/carl-bergstrom-people-are-using-data-to-bullshit
Silverman, J. D., Hupert, N., & Washburne, A. D. (2020). Using influenza surveillance networks to estimate state-specific prevalence of SARS-CoV-2 in the United States. Science Translational Medicine. https://doi.org/10.1126/scitranslmed.abc1126
López, J. A. M., Arregui-Garcĺa, B., Bentkowski, P., Bioglio, L., Pinotti, F., Boëlle, P.-Y., Barrat, A., Colizza, V., & Poletto, C. (2020). Anatomy of digital contact tracing: Role of age, transmission setting, adoption and case detection. MedRxiv, 2020.07.22.20158352. https://doi.org/10.1101/2020.07.22.20158352
Lang, T. (2020). Plug COVID-19 research gaps in detection, prevention and care. Nature, 583(7816), 333–333. https://doi.org/10.1038/d41586-020-02004-1
But there doesn’t appear to be a simple way to test for :placeholder-shown.
You can’t use @supports for selectors, only property/values (e.g. @supports (display: flex))
first sighting CSS: @supports
McMurtry, C. M. (2020). Managing immunization stress-related response: A contributor to sustaining trust in vaccines. Canada Communicable Disease Report, 46(6), 210–218. https://doi.org/10.4745/ccdr.v46i06a10
image-lidar fusion algorithm
This is quite popular recent two years - hybrid method, multi-modality
KITTI
dataset
But I’m afraid it’s perfectly possible to ship one version of your code to GitHub and a different version to npm.
The point is, just because you don’t see it, doesn’t mean it’s not happening. It’s been more than two years and as far as I know, no one has ever noticed one of my requests. Maybe it’s been in your site this whole time
Also the URL looks a lot like the 300 other requests to ad networks your site makes.
I’d notice the network requests going out!Where would you notice them? My code won’t send anything when the DevTools are open (yes even if un-docked).I call this the Heisenberg Manoeuvre: by trying to observe the behaviour of my code, you change the behaviour of my code.
If you manage to make Svelte aware of what needs to be tracked, chances are that the resulting code will be more performant than if you roll your own with events or whatever. In part because it will use Svelte's runtime code that is already present in your app, in part because Svelte produces seriously optimized change tracking code, that would be hard to hand code all while keeping it human friendly. And in part because your change tracking targets will be more narrow.
This creates an options object with a getter function for the passive property; the getter sets a flag, passiveSupported, to true if it gets called. That means that if the browser checks the value of the passive property on the options object, passiveSupported will be set to true; otherwise, it will remain false. We then call addEventListener() to set up a fake event handler, specifying those options, so that the options will be checked if the browser recognizes an object as the third parameter.
Svelte's advantage here is that it indicates the need for an update at the place where the associated data is updated, instead of at each place the data is used. Then each template expression of reactive statement is able to check very quickly if it needs to rerender or not.
But you can still run into strange race conditions where the browser displays stale data depending on if some other unrelated code has caused a digest update to run after the buggy code or not.
The advantage of ngOnChanges() is that we get all the changes at once if the component has several @Input()s. However, if we have a single @Input() a setter is probably the better approach.
To detect foreign DNA in 5 ml of lake water, 15 ml of lake water must be screened.
Why is this multiplied by 3? Related to statistical error of subsampling - rule of three)
Jaeger, B., Oud, B., Williams, T., Krumhuber, E., Fehr, E., & Engelmann, J. B. (2020, October 20). Trustworthiness detection from faces: Does reliance on facial impressions pay off?. https://doi.org/10.31234/osf.io/ayqeh
Identify your user agents When deploying software that makes requests to other sites, you should set a custom User-Agent header to identify the software and provide a means to contact its maintainers. Many of the automated requests we receive have generic user-agent headers such as Java/1.6.0 or Python-urllib/2.1 which provide no information on the actual software responsible for making the requests.
Perhaps we should detect URLSearchParams objects differently (using duck typing detection instead of instanceof window.URLSearchParams, for example) but the solution isn't adding a specific polyfill to Axios (as it'd increase the bundle size and still won't work with other polyfills).
Sometimes we can’t implement a solution that’s fully spec-compliant, and in those cases using a polyfill might be the wrong answer. A polyfill would translate into telling the rest of the codebase that it’s okay to use the feature, that it’ll work just like in modern browsers, but it might not in edge cases.
AI and control of Covid-19 coronavirus. (n.d.). Artificial Intelligence. Retrieved October 15, 2020, from https://www.coe.int/en/web/artificial-intelligence/ai-and-control-of-covid-19-coronavirus
Abbott, K. R., & Sherratt, T. N. (2013). Optimal sampling and signal detection: Unifying models of attention and speed–accuracy trade-offs. Behavioral Ecology, 24(3), 605–616. https://doi.org/10.1093/beheco/art001
r/BehSciResearch—Review on combatting the COVID misinformation flood. (n.d.). Reddit. Retrieved October 12, 2020, from https://www.reddit.com/r/BehSciResearch/comments/j9mrlp/review_on_combatting_the_covid_misinformation/
Nouri, A. B., Ali. (n.d.). COVID Misinformation Is Killing People. Scientific American. Retrieved October 12, 2020, from https://www.scientificamerican.com/article/covid-misinformation-is-killing-people1/
New tool for the early detection of public health threats from Twitter data: Epitweetr. (2020, October 1). European Centre for Disease Prevention and Control. https://www.ecdc.europa.eu/en/news-events/new-tool-early-detection-public-health-threats-twitter-data-epitweetr
Scientists study whether immune response wards off or worsens Covid. (2020, October 4). The Guardian. http://www.theguardian.com/science/2020/oct/04/scientists-study-whether-immune-response-wards-off-or-worsens-covid
Kaplan, Edward H, Dennis Wang, Mike Wang, Amyn A Malik, Alessandro Zulli, and Jordan H Peccia. ‘Aligning SARS-CoV-2 Indicators via an Epidemic Model: Application to Hospital Admissions and RNA Detection in Sewage Sludge’. Preprint. Infectious Diseases (except HIV/AIDS), 29 June 2020. https://doi.org/10.1101/2020.06.27.20141739.
Daley, J. (n.d.). Millions of Rapid COVID-19 Antigen Tests May Help Fill the Testing Gap. Scientific American. Retrieved September 30, 2020, from https://www.scientificamerican.com/article/millions-of-rapid-covid-19-antigen-tests-may-help-fill-the-testing-gap/
the promise specification explicitly does not make a distinction
LOD was defined as <x>bi + ksbi, where <x>bi equals the mean of the no-template controls, sbi is s.d. of no-template controls and k = 2.479 (99% confidence interval)
ddPCR
Chin, A. W. H., Chu, J. T. S., Perera, M. R. A., Hui, K. P. Y., Yen, H.-L., Chan, M. C. W., Peiris, M., & Poon, L. L. M. (2020). Stability of SARS-CoV-2 in different environmental conditions. The Lancet Microbe, 1(1), e10. https://doi.org/10.1016/S2666-5247(20)30003-3
Tybur, J. M., Lieberman, D., Fan, L., Kupfer, T., & de Vries, R. E. (2020). Behavioral immune tradeoffs: Interpersonal value relaxes social pathogen avoidance [Preprint]. PsyArXiv. https://doi.org/10.31234/osf.io/ec8uw
Santosh, R., Guntuku, S. C., Schwartz, H., Eichstaedt, J., & Ungar, L. (2020). Detecting Symptoms using Context-based Twitter Embeddings during COVID-19. https://openreview.net/forum?id=DFJhXXPZrM7
Herper, M. (2020, July 1). Covid-19 vaccine from Pfizer and BioNTech shows positive results. CNBC. https://www.cnbc.com/2020/07/01/coronavirus-vaccine-from-pfizer-and-biontech-shows-positive-results-report-says.html
Shan, B., Broza, Y. Y., Li, W., Wang, Y., Wu, S., Liu, Z., Wang, J., Gui, S., Wang, L., Zhang, Z., Liu, W., Zhou, S., Jin, W., Zhang, Q., Hu, D., Lin, L., Zhang, Q., Li, W., Wang, J., … Haick, H. (2020). Multiplexed Nanomaterial-Based Sensor Array for Detection of COVID-19 in Exhaled Breath. ACS Nano. https://doi.org/10.1021/acsnano.0c05657
Mohammadi, A., Esmaeilzadeh, E., Li, Y., Bosch, R. J., & Li, J. Z. (2020). SARS-CoV-2 detection in different respiratory sites: A systematic review and meta-analysis. EBioMedicine, 0(0). https://doi.org/10.1016/j.ebiom.2020.102903
Cevik, M., Tate, M., Lloyd, O., Maraolo, A. E., Schafers, J., & Ho, A. (2020). SARS-CoV-2, SARS-CoV-1 and MERS-CoV viral load dynamics, duration of viral shedding and infectiousness: A living systematic review and meta-analysis. MedRxiv, 2020.07.25.20162107. https://doi.org/10.1101/2020.07.25.20162107
Identifying social media manipulation with OSoMe tools. (2020, August 11). https://www.youtube.com/watch?v=1BMv0PrdVGs&feature=youtu.be
Tasnim, S., Hossain, M. M., & Mazumder, H. (2020). Impact of rumors or misinformation on coronavirus disease (COVID-19) in social media [Preprint]. SocArXiv. https://doi.org/10.31235/osf.io/uf3zn
Golding, N., Russell, T. W., Abbott, S., Hellewell, J., Pearson, C. A. B., Zandvoort, K. van, Jarvis, C. I., Gibbs, H., Liu, Y., Eggo, R. M., Edmunds, J. W., & Kucharski, A. J. (2020). Reconstructing the global dynamics of under-ascertained COVID-19 cases and infections. MedRxiv, 2020.07.07.20148460. https://doi.org/10.1101/2020.07.07.20148460
LoD = LoB + 1.645(SD low concentration sample)
LoD is the lowest analyte concentration likely to be reliably distinguished from the LoB and at which detection is feasible. LoD is determined by utilising both the measured LoB and test replicates of a sample known to contain a low concentration of analyte.
LoB is the highest apparent analyte concentration expected to be found when replicates of a blank sample containing no analyte are tested.
LoB = meanblank + 1.645(SDblank)
Zhong, H., Wang, Y., Shi, Z., Zhang, L., Ren, H., He, W., Zhang, Z., Zhu, A., Zhao, J., Xiao, F., Yang, F., Liang, T., Ye, F., Zhong, B., Ruan, S., Gan, M., Zhu, J., Li, F., Li, F., … Zhao, J. (2020). Characterization of Microbial Co-infections in the Respiratory Tract of hospitalized COVID-19 patients. MedRxiv, 2020.07.02.20143032. https://doi.org/10.1101/2020.07.02.20143032
New Scientist on Twitter: “Thread on #covid19 trends in the US: Coronavirus infections have surged since the start of June from around 20,000 new cases a day to over 60,000. (1/4) https://t.co/wVFwHWczYR” / Twitter. (n.d.). Twitter. Retrieved July 19, 2020, from https://twitter.com/newscientist/status/1283387188391149571
Song, S. (2020). China Experience in Controlling COVID-19. https://doi.org/10.31235/osf.io/gfnep
Hossain, M. M., McKyer, E. L. J., & Ma, P. (2020). Applications of artificial intelligence technologies on mental health research during COVID-19 [Preprint]. SocArXiv. https://doi.org/10.31235/osf.io/w6c9b
Davis, J. T., Chinazzi, M., Perra, N., Mu, K., Piontti, A. P. y, Ajelli, M., Dean, N. E., Gioannini, C., Litvinova, M., Merler, S., Rossi, L., Sun, K., Xiong, X., Halloran, M. E., Longini, I. M., Viboud, C., & Vespignani, A. (2020). Estimating the establishment of local transmission and the cryptic phase of the COVID-19 pandemic in the USA. MedRxiv, 2020.07.06.20140285. https://doi.org/10.1101/2020.07.06.20140285
Fleming, N. (2020). Coronavirus misinformation, and how scientists can help to fight it. Nature. https://doi.org/10.1038/d41586-020-01834-3
The Lancet. (2020). Sustaining containment of COVID-19 in China. The Lancet, 395(10232), 1230. https://doi.org/10.1016/S0140-6736(20)30864-3
Hironori Funabiki on Twitter
Dewa, L. H., Lawrence‐Jones, A., Crandell, C., Jaques, J., Pickles, K., Lavelle, M., Pappa, S., & Aylin, P. (n.d.). Reflections, impact and recommendations of a co-produced qualitative study with young people who have experience of mental health difficulties. Health Expectations, n/a(n/a). https://doi.org/10.1111/hex.13088
Cai, L., Chen, Z., Luo, C., Gui, J., Ni, J., Li, D., & Chen, H. (2020). Structural Temporal Graph Neural Networks for Anomaly Detection in Dynamic Graphs. ArXiv:2005.07427 [Cs, Stat]. http://arxiv.org/abs/2005.07427
Ortiz, E., García-Pérez, G., & Serrano, M. Á. (2020). Geometric detection of hierarchical backbones in real networks. ArXiv:2006.03207 [Physics]. http://arxiv.org/abs/2006.03207
Meyer, A. C. M., Robinson. (2020, May 21). ‘How Could the CDC Make That Mistake?’ The Atlantic. https://www.theatlantic.com/health/archive/2020/05/cdc-and-states-are-misreporting-covid-19-test-data-pennsylvania-georgia-texas/611935/
Yasseri, T. (n.d.). Dominic Cummings: How the internet knows when you’ve updated your blog. The Conversation. Retrieved June 1, 2020, from http://theconversation.com/dominic-cummings-how-the-internet-knows-when-youve-updated-your-blog-139517
Aslak, U., & Alessandretti, L. (2020). Infostop: Scalable stop-location detection in multi-user mobility data. ArXiv:2003.14370 [Physics]. http://arxiv.org/abs/2003.14370
Kim, H. (2020, March 20). South Korea learned its successful Covid-19 strategy from a previous coronavirus outbreak: MERS. Bulletin of the Atomic Scientists. https://thebulletin.org/2020/03/south-korea-learned-its-successful-covid-19-strategy-from-a-previous-coronavirus-outbreak-mers/
Michalak, N. M., Sng, O., Wang, I., & Ackerman, J. (2020, May 14). Sounds of sickness: Can people identify infectious disease using sounds of coughs and sneezes?. https://doi.org/10.1098/rspb.2020.0944
Riolo, M. A., & Newman, M. E. J. (2020). Consistency of community structure in complex networks. Physical Review E, 101(5), 052306. https://doi.org/10.1103/PhysRevE.101.052306
Kaplan, E. H., & Forman, H. P. (2020). Logistics of Aggressive Community Screening for Coronavirus 2019. JAMA Health Forum, 1(5), e200565–e200565. https://doi.org/10.1001/jamahealthforum.2020.0565
Chu, H. Y., Englund, J. A., Starita, L. M., Famulare, M., Brandstetter, E., Nickerson, D. A., Rieder, M. J., Adler, A., Lacombe, K., Kim, A. E., Graham, C., Logue, J., Wolf, C. R., Heimonen, J., McCulloch, D. J., Han, P. D., Sibley, T. R., Lee, J., Ilcisin, M., … Bedford, T. (2020). Early Detection of Covid-19 through a Citywide Pandemic Surveillance Platform. New England Journal of Medicine, NEJMc2008646. https://doi.org/10.1056/NEJMc2008646
Shental, N., Levy, S., Skorniakov, S., Wuvshet, V., Shemer-Avni, Y., Porgador, A., & Hertz, T. (2020). Efficient high throughput SARS-CoV-2 testing to detect asymptomatic carriers. MedRxiv, 2020.04.14.20064618. https://doi.org/10.1101/2020.04.14.20064618
Wurtzer, S., Marechal, V., Mouchel, J.-M., & Moulin, L. (2020). Time course quantitative detection of SARS-CoV-2 in Parisian wastewaters correlates with COVID-19 confirmed cases. MedRxiv, 2020.04.12.20062679. https://doi.org/10.1101/2020.04.12.20062679
Lohse, S., Pfuhl, T., Berkó-Göttel, B., Rissland, J., Geißler, T., Gärtner, B., Becker, S. L., Schneitler, S., & Smola, S. (2020). Pooling of samples for testing for SARS-CoV-2 in asymptomatic people. The Lancet Infectious Diseases, S1473309920303625. https://doi.org/10.1016/S1473-3099(20)30362-5
Adams, E. R., Anand, R., Andersson, M. I., Auckland, K., Baillie, J. K., Barnes, E., Bell, J., Berry, T., Bibi, S., Carroll, M., Chinnakannan, S., Clutterbuck, E., Cornall, R. J., Crook, D. W., Silva, T. D., Dejnirattisai, W., Dingle, K. E., Dold, C., Eyre, D. W., … Sanchez, V. (2020). Evaluation of antibody testing for SARS-Cov-2 using ELISA and lateral flow immunoassays. MedRxiv, 2020.04.15.20066407. https://doi.org/10.1101/2020.04.15.20066407
Wolf, M. G. (2020, April 26). Survey Uses May Influence Survey Responses. https://doi.org/10.31234/osf.io/c4hd6
Third Report. (2020, April 17). COVID-19 Mobility Monitoring Project. https://covid19mm.github.io//in-progress/2020/04/17/third-report.html
Nanni, M., Andrienko, G., Boldrini, C., Bonchi, F., Cattuto, C., Chiaromonte, F., Comandé, G., Conti, M., Coté, M., Dignum, F., Dignum, V., Domingo-Ferrer, J., Giannotti, F., Guidotti, R., Helbing, D., Kertesz, J., Lehmann, S., Lepri, B., Lukowicz, P., … Vespignani, A. (2020). Give more data, awareness and control to individual citizens, and they will help COVID-19 containment. ArXiv:2004.05222 [Cs]. http://arxiv.org/abs/2004.05222
DFG, German Research Foundation—Call for Multidisciplinary Research into Epidemics and Pandemics in Response to the Outbreak of SARS-CoV-2. (n.d.). Retrieved April 15, 2020, from https://www.dfg.de/en/research_funding/announcements_proposals/2020/info_wissenschaft_20_20/
J.M. Berger Former Brookings Expert
Paying attention to the qualifications of the author(s)/composer(s) is another crucial role in crap detection at it will help discern whether or not to take the piece seriously or to use it for further research.
Markaz
In the Rheinghold text , he explains the importance of pay attention the website layout as well as content. However, in doing so, you must tune your crap detection and remember that not everything with a fancy layout is reliable, and vice versa.
I took a detailed look at how ISIS functions online, breaking it down into a five-part template, which can be implemented in different ways depending on the target’s disposition:
Rather than simply stating information, the author (Berger) explains his source and the way in which he broke his research down into smaller categories. This citation is also apart of crap detection with a reliable source.
detected through social media analysis,
The implementing of this specific link gives important attribution and increases source reliability. The text makes a statement and is able to back it up with an external, secure source.
there are practical and ethical limits to how much we can interdict discovery.
Though Rheinghold stresses the importance of crap detection and researching your sources, he accepts the fact that there a limits that we reach in terms of discernment of validity. This is shown as the ISIS busters reach ethical and practical limits of search. It is important in the way that one mustn't get overwhelmed with finding the true source origin because you can only go so far.
stripping away the mystique and focusing on the mechanics.
Rheinghold stresses the importance of looking at the base of things, rather than simply the makeup and what you see initially, it is important to dig deeper and look at sources from a questionable yet structured angle.
Monday, November 9, 2015
The article ends in 'edu' which, as Rheinghold states, increases estimation of its credibility.
This post originally appeared on VOX-Pol.
Considering that the origin of this post comes from a non-secure site, that appears a tad amateur - also brings forth speculation. It is a blog site, and considering this - I somehow take what is posted 'with a grain of salt'.
How does ISIS acquire new recruits online and convince them to take action? J.M. Berger explains, arguing that efforts to counter terrorists’ online activity can be more effective if the mechanics are clearly understood.
I begin critiquing this article based on Rheinghold's initial conversation with his daughter. In the text Rheinghold suggests using a free internet service - Whois , in order to search for validity in research. After plugging this domain name into the site, I find that the name of the registered owner is 'Educase'. Educase is a nonprofit core data service for research and analysis.
How terrorists recruit online (and how to stop it)
I will be connecting this text through Howard Rheinghold's "Crap Detection 101" from chapter 2 of his book Net Smart - How to Thrive Online. This allows for further critic of this article in terms of this theme.
视频烟雾检测研究进展
how it uses zones
Does anyone have an authoritative link for this concept of zones and how they work? It'd be much appreciated.
Early event detection problems can go here. Two example cases just came to my mind are: 1- in emergency response: detecting a disaster quickly is important. 2- in computational journalism: many locals suddenly start talking about an event means something newsworthy is going on.
Finally, by assuming the non-detection of a species to indicate absence from a given grid cell, we introduced an extra level of error into our models. This error depends on the probability of false absence given imperfect detection (i.e., the probability that a species was present but remained undetected in a given grid cell [73]): the higher this probability, the higher the risk of incorrectly quantifying species-climate relationships [73].
This will be an ongoing challenge for species distribution modeling, because most of the data appropriate for these purposes is not collected in such a way as to allow the straightforward application of standard detection probability/occupancy models. This could potentially be addressed by developing models for detection probability based on species and habitat type. These models could be built on smaller/different datasets that include the required data for estimating detectability.
Presentation summarizing an approach to duplicate web page detection that was developed by a researcher whilst at Google in the early 2000s
Given an LSH familyH, the LSH scheme amplifiesthe gap between the high probabilityP1and the lowprobabilityP2by concatenating several functions
Useful recap of LSH
Recent survey paper for hashing-based approaches to similarity search
This paper has a very useful overview of previous work that is worth reading under section 9.
We used the following publicly available real datasets in the experiment
Datasets used are DBPL, ENRON, UNIREF-4GRAM. All small (<1M records) in web terms and I would guess, all with small document sizes.
Given a lengthy paper, could potentially divide into smaller documents (1 doc === 1 page) and do signature calculation on a per-page basis. This could have the benefit of bounding the search time by limiting the number of pages that need to be rendered to text in order to start the lookup process.