How Secure And Private Is My Data On Boundless?

My take is that if a lawyer is asking for private messages, it's usually because they think those messages prove something important — a timeline, admissions, promises about money, or evidence of misconduct. In practical terms, discovery in family court can be broad: if something in the messages is relevant to custody, support, or property division, opposing counsel will want them. That doesn't automatically mean every single personal chat is fair game, though. From experience watching friends go through this, the safer first move is preservation: don't delete anything and tell your lawyer exactly what exists. There are nuances too — messages to a lawyer or ones that are explicitly confidential may be protected, and metadata can reveal more than the text. Your lawyer may ask you to produce messages voluntarily to show cooperation, or they might be preparing to fight a subpoena if the other side demands them. Personally, I find it calming to treat texts like documents: keep them organized, ask about redaction for irrelevant private details, and remember there are procedural ways to push back if something feels invasive.

This is a brutal violation and, yes, in many places you can sue — but the best path depends on where you live and what exactly happened. If your boyfriend auctioned off private photos without your consent, that's often treated as a civil wrong: claims like public disclosure of private facts, invasion of privacy, or intentional infliction of emotional distress are commonly used. Some states and countries also have specific laws that criminalize the non-consensual distribution of intimate images, sometimes called 'revenge porn' statutes, and those statutes frequently create a civil cause of action too, allowing victims to seek damages and injunctions. Collect everything: screenshots, URLs, auction listings, messages, bank or crypto transactions, and witnesses. Preserve metadata where possible and don’t delete original messages; copies should be saved in multiple places. Request takedowns from the platforms hosting the content and file a police report — criminal charges can run alongside civil suits. A lawyer can seek an injunction so the images stop circulating and try for monetary damages, punitive damages, and attorney fees if the law allows. Emotionally it’s wrenching — reach out to someone you trust or a local support group while you sort the legal side. I’ve seen people regain control by acting fast and getting both legal and emotional support, and that helped me feel less powerless.

Yep — I use SpecialChem regularly and, in my experience, most product pages include safety data sheets (SDS) and technical data sheets (TDS) uploaded by the suppliers. On a practical level, I usually click into a product, look for a ‘Downloads’ or ‘Documents’ section, and there will often be PDF links for SDS and TDS. That said, availability is supplier-dependent: some manufacturers post full, up-to-date SDS/TDS right away, while others require you to register or contact them for the files. I make a habit of checking the document date and the region (EU, US, etc.), because hazard classifications and regulatory language can differ depending on jurisdiction. If a sheet isn’t visible, I message the supplier through SpecialChem’s contact options or email the manufacturer directly. For compliance work I’m cautious — I always cross-check the downloaded SDS/TDS against the manufacturer’s own site to be absolutely sure I have the latest version.

Zaskakująco często dostaję to pytanie od znajomych z Polski — więc krótko i na temat: finał sezonu 7, czyli odcinek 16 'Outlander', miał swoją polską premierę 30 września 2023 roku. Emisja była zsynchronizowana z międzynarodową dystrybucją — po amerykańskiej premierze odcinek trafił na platformę streamingową dla widzów w Polsce (z napisami i/dubbingiem zależnie od oferty platformy). Dla wielu oznaczało to możliwość obejrzenia dokładnie tego samego odcinka, co widzowie za oceanem, tylko z lekkim przesunięciem wynikającym ze stref czasowych i polityki wydawniczej serwisu. Jeżeli szukasz konkretnego sposobu na obejrzenie teraz: sprawdzałem wtedy oferty największych usług streamingowych dostępnych w Polsce i to właśnie tam pojawiła się legalna emisja. Osobiście miałem mieszane uczucia wobec tego finału — emocje, piłowanie relacji i kilka scen, które długo mi nie schodziły z głowy.

Se a tua pergunta é sobre quando a sétima temporada de 'Outlander' ia aparecer na Netflix em Portugal, deixo aqui um panorama honesto e prático do que acompanhei: a transmissão original da temporada 7 estreou na Starz em duas partes — a Parte 1 começou a 16 de junho de 2023 e a Parte 2 estreou a 25 de maio de 2024. Tradicionalmente, a Netflix em Portugal costuma adicionar temporadas estrangeiras com algum atraso face à transmissão original nos EUA, porque os direitos de streaming são negociados e sincronizados de forma diferente em cada mercado. Até à minha última verificação em meados de 2024, a temporada 7 completa ainda não estava disponível na Netflix Portugal; isso não é incomum. Muitas séries chegam à Netflix local só depois do término da exibição na emissora original, ou então aos poucos (às vezes primeiro uma parte, depois a outra). Se tiveres paciência, o padrão recente tem sido a Netflix lançar a temporada completa algumas semanas a alguns meses após a última emissão na Starz — portanto, o mais provável era que a temporada 7 ficasse disponível em Portugal no verão ou início do outono de 2024. Para fãs impacientes, vale também ficar de olho em serviços ou comunicados oficiais, porque há sempre exceções e acordos específicos por país. Eu fiquei na expectativa como muitos: ver Jamie e Claire traduzidos para o catálogo português traz uma sensação especial de maratonas com amigos e memórias de leituras dos livros de Diana Gabaldon. Entretanto, enquanto a Netflix não anuncia a data exata para Portugal, a melhor referência continua a ser a própria janela das estreias na Starz — a 25 de maio de 2024 marca o fim da saga televisiva da temporada 7, o que normalmente abre caminho para que a Netflix a adicione pouco depois. De qualquer forma, a espera costuma valer a pena; gosto de rever certas cenas com legendas em português para apanhar nuances de diálogo que me escaparam nas legendas originais. Estou curioso para saber como te parece a adaptação da última parte, quando a vires.

If I had to build the friendliest, most secure texting app for buddies, I'd start by making encryption invisible but ironclad. End-to-end encryption with perfect forward secrecy should be the baseline — not a checkbox. Keys need to be device-bound and easy to verify with a QR or short safety code so two people can confirm they’re really talking to each other. I’d also include optional encrypted backups that are client-side only, and a clear way to revoke device sessions when you lose a phone. Beyond raw cryptography, practical privacy features matter. Let users set message timers (from a few seconds to forever), enable a 'burn after reading' option for specific messages or media, and lock individual chats with a PIN or biometrics. Screenshot notifications are useful even if they can’t technically block every capture — at least you get an alert. Metadata minimization is huge: store as little on servers as possible (no location history, no long-term contact lists), and offer username-only sign-up so you don’t need to hand over a phone number or email unless you want to. I’d bake in safety tooling: robust block/report flows, per-group admin controls, rate limits to prevent harassment, and a panic button that quickly hides chats and logs you out of other devices. Make everything auditable and open-source so independent experts can verify it. Finally, nail the onboarding: plain-language explanations of what features do, why they protect you, and simple guides to verify keys — privacy without confusion feels like a true friend.

Nice question — picking books that teach programming while covering data science basics is one of my favorite rabbit holes, and I can geek out about it for ages. If you want a path that builds both programming chops and data-science fundamentals, I'd break it into a few tiers: practical Python for coding fluency, core data-manipulation and statistics texts, and then project-driven machine learning books. For absolute beginners, start light and hands-on with 'Python Crash Course' and 'Automate the Boring Stuff with Python' — both teach real coding habits and give you instant wins (file handling, scraping, simple automation) so you don’t get scared off before you hit the math. Once you’re comfortable with basic syntax and idioms, move to 'Python for Data Analysis' by Wes McKinney so you learn pandas properly; that book is pure gold for real-world data wrangling and I still flip through it when I need a trick with groupby or time series. For the statistics and fundamentals that underpin data science, I can’t recommend 'An Introduction to Statistical Learning' enough, even though it uses R. It’s concept-driven, beautifully paced, and comes with practical labs that translate easily to Python. Pair it with 'Practical Statistics for Data Scientists' if you want a quicker, example-heavy tour of the key tests, distributions, and pitfalls that show up in real datasets. If you prefer learning stats through Python code, 'Think Stats' and 'Bayesian Methods for Hackers' are approachable and practical — the latter is especially fun if you want intuition about Bayesian thinking without getting lost in heavy notation. For those who like learning by building algorithms from scratch, 'Data Science from Scratch' does exactly that and forces you to implement the basic tools yourself, which is a fantastic way to internalize both code and concepts. When you’re ready to step into machine learning and deeper modeling, 'Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow' is my go-to because it ties the algorithms to code and projects — you’ll go from linear models to neural nets with practical scripts and exercises. For the math background (linear algebra and calculus that actually matter), 'Mathematics for Machine Learning' gives compact, focused chapters that I found way more useful than trying to digest a full math textbook. If you want an R-flavored approach (which is excellent for statistics and exploratory work), 'R for Data Science' by Hadley Wickham is indispensable: tidyverse workflows make data cleaning and visualization feel sane. Finally, don’t forget engineering and best practices: 'Fluent Python' or 'Effective Python' are great as you move from hobby projects to reproducible analyses. My recommended reading order: start with a beginner Python book + 'Automate the Boring Stuff', then 'Python for Data Analysis' and 'Data Science from Scratch', weave in 'Think Stats' or 'ISL' for statistics, then progress to 'Hands-On Machine Learning' and the math book. Always pair reading with tiny projects — Kaggle kernels, scraping a site and analyzing it, or automating a task for yourself — that’s where the learning actually sticks. If you want, tell me whether you prefer Python or R, or how much math you already know, and I’ll tailor a tighter reading list and a practice plan for the next few months.

Oh, absolutely — Barry University's library does have private group study rooms, and I use them all the time when I'm trying to wrangle a group project or rehearse a presentation. The rooms are meant for collaborative work, so they tend to have whiteboards, table space, and sometimes a monitor or hookups for a laptop. I usually check the library's website first to see availability, but if I'm in a hurry I swing by the circulation desk and ask; staff are friendly and will point you toward a room or tell you about same-day walk-ins. From experience, booking ahead is a lifesaver during midterms and finals. Reservation windows can vary — typically you can reserve for a couple of hours at a time and renew if no one else has a hold — but policies change each semester, so double-check the library's reservation rules. Also, bring your student ID because some places require it for check-in, and be considerate of the posted capacity limits and noise expectations. A small pack of markers and a charging cable in my bag has saved me more than once. If the rooms are full, don't panic: there are usually communal study spaces, smaller nooks, or campus lounges that work fine for groups of two or three. And if you want a quick tip — book the worst time first, like early morning or late evening; those slots are less popular and often more reliable for quiet focus.