Drug use is an ancient practice, but its associated disorders represent a contemporary public health challenge. This study investigates the impact of proximal processes in childhood/adolescence and adulthood on substance use, focusing on the role of Therapeutic Communities (TCs). Using a qualitative methodology, 19 residents of TCs in the state of Rio de Janeiro were interviewed. Instruments included a screening test (ASSIST), a sociodemographic inventory, and semi-structured interviews. Content analysis of the interviews was supported by the Requalify.ai software, which proved to be an efficient tool for categorizing and visualizing qualitative data. Results indicate that factors such as dysfunctional family environments, violence, and early onset of consumption, often mediated by peer influence, are determining risk factors. On the other hand, peer social support within TCs emerges as a crucial protective factor, associated with positive changes reported by participants. The sample revealed an overrepresentation of Black and Brown individuals, highlighting the racial dimension in the history of drug use in Brazil. The study concludes that proximal relationships are decisive in both the etiology and recovery of substance use disorders, and that TCs, although controversial, can offer a supportive environment that favors change, especially through peer support and cohabitation.
This work presents an end-to-end, deployment-aware testing pipeline for IoT-based automotive applications that combines requirement-driven test and code generation with large language model (LLM) and vision-language model (VLM) assistance, and human-in-the-loop curation to reduce manual effort and improve consistency.
A reverse engineering technique is presented for extracting a behavioural model of a deployed chatbot through the automated exploration of its functionality via Large Language Models through the automated exploration of its functionality via Large Language Models.
This case highlights the technical challenges of identifying melioidosis in a non-endemic region and confirms the diagnosis of melioidosis was difficult due to the misreporting of this isolate with a MALDI-TOF high score as B. thailandensis.
Работа посвящена контролю качества данных в многоканальной телеметрии робототехнического манипулятора. Цель исследования – разработать и экспериментально оценить метод, который выявляет и локализует искаженный канал без обучения нейронной сети и без физического стенда. Метод объединяет показатели полноты, временной корректности и стабильности каждого потока с кинематическими и динамическими невязками между энкодерами, токами приводов, инерциальным каналом и внешней оценкой положения рабочего органа. Пороговые значения вычисляются по чистому калибровочному интервалу с использованием медианы и медианного абсолютного отклонения; локализация выполняется по графу межканальных связей. Воспроизводимый программный эксперимент включает 864 сценария, шесть видов искажений, четыре канала, три уровня интенсивности и двенадцать повторов. Предлагаемый метод достиг среднего F1 0,862 при 95-процентном бутстреп-интервале [0,845; 0,879], тогда как фиксированные правила и адаптивный одноканальный контроль дали 0,622 и 0,791 соответственно. Средняя точность локализации составила 0,843, доля ложных срабатываний – 0,0059. Наибольший выигрыш получен для постоянных смещений; для выбросов и замирания одноканальные методы оказались конкурентоспособнее. Результат представляет собой интерпретируемый модуль контроля входной телеметрии, пригодный для встраивания перед хранением и аналитической обработкой данных. The paper addresses data quality control in the multichannel telemetry of a robotic manipulator. The aim of the study is to develop and experimentally evaluate a method that detects and localises a corrupted channel without training a neural network and without a physical test bench. The method combines indicators of completeness, temporal correctness and stability of each stream with kinematic and dynamic residuals between the encoders, the drive currents, the inertial channel and the external estimate of the end-effector position. Threshold values are computed over a clean calibration interval using the median and the median absolute deviation; localisation is performed on a graph of inter-channel relations. The reproducible software experiment covers 864 scenarios, six types of distortion, four channels, three intensity levels and twelve repetitions. The proposed method reached a mean F1 of 0,862 with a 95% bootstrap interval [0,845; 0,879], whereas fixed rules and adaptive single-channel control yielded 0,622 and 0,791 respectively. The mean localisation accuracy was 0,843 and the false positive rate was 0,0059. The largest gain was obtained for constant offsets; for outliers and freezing, single-channel methods proved more competitive. The result is an interpretable module for input telemetry control suitable for embedding before data storage and analytical processing.
Telecommunications base-station towers support services that are indispensable to crisis communication, emergency response, public administration and economic continuity. Their dispersed location, height and lattice geometry make conventional close-access inspection hazardous, time-consuming and difficult to document consistently. This study evaluates the usefulness and limitations of uncrewed aircraft systems for inspecting steel lattice towers that form part of telecommunications critical infrastructure. A retrospective field study was conducted using records from inspections performed in 2022–2023 at 50 towers in three Polish provinces. More than 150 sorties were completed with a DJI Matrice 30T platform using optical zoom, thermal imaging, a laser rangefinder and georeferenced mission telemetry. Manual, column and spiral flight patterns were compared, while image sets were processed with photogrammetric software to support three-dimensional reconstruction and spatial localisation of defects. The observations show that uncrewed inspection is particularly effective for documenting coating damage, local corrosion, fastener deterioration, connection anomalies, snow or ice accretion and equipment requiring thermographic follow-up. Column flights generated the most detailed evidence but also the greatest processing burden; spiral flights were faster and better suited to screening and three-dimensional modelling. The study also identified important constraints: wind, battery endurance, vegetation, airspace restrictions, electromagnetic and navigation disturbances, and the need to protect sensitive infrastructure data. Uncrewed aircraft should therefore be treated as a risk-based screening and documentation tool integrated with engineering judgement and targeted close-contact or non-destructive testing, rather than as an unconditional replacement for statutory structural inspection.
In his latest book, Professor Eugene Fitzgerald examines the forces that turn breakthroughs into value — and why innovation resists simple formulas.
MIT students designed, built, and tested a jet engine with AI copilots, assessing AI’s usefulness in developing high-performance aerospace systems.
Researchers developed an auditing technique to test generative AI models for malicious capabilities, without prompting them for illegal outputs.
A USAF cadet and a Lincoln Laboratory researcher found AI chatbots can help nontechnical service members produce viable software applications for their unique problems.
