Allentown High School

Shared micromobility systems, such as electric scooters and bikes, have gained widespread popularity as sustainable alternatives to traditional transportation modes. However, these systems face persistent challenges due to spatio-temporal demand fluctuations, often resulting in a mismatch between vehicle supply and user demand. Existing shared micromobility vehicle scheduling methods typically redistribute vehicles once or twice per day, which makes them vulnerable to performance degradation under atypical conditions. In this work, we design to augment existing micromobility scheduling methods by integrating a small number of autonomous shared micromobility vehicles (ASMVs), which possess self-rebalancing capabilities to dynamically adapt to real-time demand. Specifically, we introduce SMART, a hierarchical reinforcement learning framework that jointly optimizes high-level initial deployment and low-level real-time rebalancing for ASMVs. We evaluate our framework based on real-world e-scooter usage data from Chicago. Our experiment results show that our framework is highly effective and possesses strong generalization capability, allowing it to seamlessly integrate with existing vehicle scheduling methods and significantly enhance overall micromobility service performance.

Timely and accurate two-way communication between the school nurse and the families and school communities they work with is essential in supporting student health and success. Modern technology has allowed for virtual communication beyond the use of a telephone or email. Real-time messages can be sent to individual family members or specific groups using school-focused communication applications. This article will provide an overview of the basic features of popular school communication apps that the school nurse can use. Best practices when using these apps will also be discussed.

The RAS pathway, known as the Ras/Raf/MAPK pathway, is a crucial signal transduction cascade that regulates essential cellular processes, including growth, differentiation, and survival. Central to this pathway is the RAS protein, a small GTPase that acts as a molecular switch, alternating between inactive GDP-bound and active GTP-bound states. Activation of RAS is initiated by extracellular signals, primarily through the binding of ligands to receptor tyrosine kinases (RTKs), which subsequently activate guanine nucleotide exchange factors (GEFs) and the conversion of GDP to GTP. Notably, mutations in the RAS gene, especially the KRAS G12C mutation, are implicated in various cancers, particularly non-small cell lung cancer (NSCLC) and colorectal cancer (CRC), where they lead to uncontrolled cell proliferation and tumorigenesis. This study examines the intricate roles of KRAS, including its domains, isoforms, and mutation profiles, and discusses emerging therapeutic approaches targeting KRAS mutations, such as specific inhibitors like Adagrasib. A comprehensive understanding of the RAS pathways complexities and its oncogenic potential is essential for advancing targeted therapies and enhancing cancer treatment outcomes.

Clinical documentation of patient visits has changed over the last 20 years, with the increasing use of electronic records causing a seismic shift in how notes are taken. Electronic note-taking aims at reducing the time taken to document a visit, and the introduction of dot phrases, or DotPhrases, in electronic medical records is a step toward reducing the time required to update patients’ charts, which might allow doctors to spend more time with their patients. DotPhrases, abbreviated phrases used in the electronic medical record, help in the simplification of note-taking and the standardization of notes. They also allow for a more comprehensive note from physicians and ensure that no information is undocumented. On the contrary, however, excessive usage of DotPhrases can lead to an excessively long and cumbersome note. This can overwhelm physicians and lead to them missing crucial information that is buried somewhere in the notes. Although there is ample research studying the benefits of DotPhrases, adequate research must also be carried out to understand their shortcomings and disadvantages. This article aims to shed some light on use of DotPhrases and to outline their advantages and disadvantages affecting patient management and care.

Aging is a scary part of life, and sarcopenia can make it much scarier. This is a condition that directly affects your skeletal muscle mass, and has the ability to greatly affect your life for the worse. Some pre-requisites of sarcopenia cannot be affected by you, but some can be changed. This affects many elderly people and causes many hardships in the later stages of life. In most cases sarcopenia isn’t alone as it commonly occurs with other muscle mass related conditions like cachexia. The best way to aid a sarcopenic person or discover sarcopenia is to know your body and make sure that something isn't wrong. Many sarcopenic patients assume that the weakness and fatigue isn’t a “big deal” and this mindset causes them to learn about their condition too late to do anything about it. The main reason for this is that they simply don’t know, and even if they tried to learn about it many articles are very hard to comprehend and digest. So, I created the opposite of these articles, a digestible and easily understandable article on sarcopenia, an article that highlights many aspects of it, specifically what it is, what it does, who it affects, and how we can prevent or delay it.

Fake news has had a significant effect on society and politics. To aid in combating the spread of misinformation, we worked to develop a machine learning algorithm that could detect fake news based on textual data. We used a count vectorizer to vectorize our text which we then inputted into Logistic Regression, Support Vector Machine (SVM), and Linear Support Vector Classifier (SVC) models. The greatest accuracy score achieved was 99.97% with the Linear SVC. We discovered however that there was a significant difference in how the real and fake news datasets were constructed that would not translate into real life: the true news articles contained quotation marks, apostrophes, and dashes while these characters were not present in the fake news articles. Because of this, we also developed a more applicable Logistic Regression model removing these specific characters from the dataset all together with an accuracy score of 98.4%.

We have previously demonstrated that observers in multielement tracking tasks can successfully track objects when they become invisible for up to 400 ms (Alvarez, Wolfe, Horowitz, & Arsenio (VSS 01)). Is this an extension of the ability to track occluded items, or a different mechanism that allows us to divert our attention from the tracking task in order to do something else for a moment? We hypothesized that if the ability to track invisible items is a way to cope with the disappearance of items in the world, then tracking should be easier if only one item disappears at a time. Furthermore, the presence of occluders at the time of disappearance/reappearance should improve performance, because occlusion is the most likely cause of disappearance of an item that remains present in the visual field. We measured tracking performance at 3 gap durations (?100, 300, & 500 ms). In Experiment 1, items disappeared and reappeared either all at once (synchronous) or one by one (asynchronous). There were two stimulus cue conditions: 1) items simply vanished and reappeared or 2) items were deleted by and accreted from modal surfaces. Contrary to the disappearing object hypothesis, synchronous disappearance yielded superior performance compared to asynchronous (F(1, 14) = 14.3, p < .005), and occlusion cues provided no advantage (F(1, 14) < 1). In Experiment 2, we used only synchronous disappearance, and found that occlusion cues actually harmed performance (F(1, 10) = 27.5, p < .0005). These results suggest that the ability to track invisible objects serves to allow the observer to set aside the tracking task for brief periods in order to direct attention to other priorities (e.g. an interpolated search task, c.f. Alvarez et al. '01). The ability does not appear to be due to a mechanism which merely copes with the periodic disappearance of objects from the field of view.

Abstract Curriculum‐based assessment (CBA) strategies have been suggested as an alternative model to traditional norm‐referenced assessment for decision making in special education. The application of CBA procedures across all decision making areas (i.e., screening and referring; determining eligibility and classifying; planning programs; monitoring progress and modifying programs; and evaluating programs) is presented. Implementation of a CBA model in applied settings indicates that this model may be feasible, efficient, accurate, and effective for all levels of decision making in special education. Suggestions for further research are offered.