ethicalabs/Research-Intent-Collab huggingface dataset:
Natural language processing of Veterans’ electronic health records to confirm diagnoses of monoclonal gammopathy of undetermined significance.

1557  Background: The Veterans Health Administration (VHA) provides extensive electronic health records (EHRs) on Veterans nationwide. Our prior studies utilized VHA data to study the risk of progression from monoclonal gammopathy of undetermined significance (MGUS) to multiple myeloma. These studies relied on International Classification of Disease (ICD) codes and manual abstraction on clinical notes to both identify and verify MGUS patients. Diagnosis confirmation is necessary because many providers place a diagnosis on the clinical notes to order lab tests, which is often left in the EHR despite a negative test result. However, manual abstraction is labor intensive and time consuming. With the advancement in natural language processing (NLP), we developed a model to make MGUS confirmation more efficient. Methods: We randomly selected 700 patients within patients diagnosed with MGUS from 1999-2021 in the VHA identified via ICD codes. A random sample of 500 patients were selected and split into the training (80%) and the testing (20%) sets. The remainder (n = 200) served as the validation set. There were 32,708 unstructured hematology/oncology Text Integration Utility reports and 9,237 lab reports (including 2,322 discrete results and 6,915 unstructured comments). All reports were manually reviewed to confirm MGUS diagnoses and served as the reference standard. We compiled three lists of keywords suggestive of MGUS diagnosis, subtypes of immunoglobulins, and negation modifiers. We trained a symbolic NLP model to identify diagnoses using combinations of the lists along with M-protein levels from lab reports. The optimized combination that gave the highest recall and precision from the training set was used and evaluated on the testing and validation sets. Results: Among patients with ICD codes for MGUS, manual abstraction confirmed 84% MGUS diagnoses in the testing set and 80% in the validation set. Our NLP model in the training set confirmed 75% and achieved recall, precision, accuracy, and F1 score of 88.1, 98.7, 89.0, and 93.1%, respectively; in the validation set, our rule confirmed 76% patients and the recall, precision, accuracy, and F1 score were 89.4, 94.7, 87.5, and 92.0%, respectively. On average data abstraction took five minutes per patient (excluding data loading time), whereas NLP model completed 13 patients per minute. Conclusions: The developed NLP model to confirm MGUS diagnosis improves accuracy in diagnosis, compared to ICD codes alone. While the performance is similar to that of manual abstraction, our NLP model is an efficient and viable method in MGUS diagnosis confirmation. [Table: see text]
Kepler's third law of n-body periodic orbits in a Newtonian gravitation field

This study considers the periodic orbital period of an n-body system from the perspective of dimension analysis. According to characteristics of the n-body system with point masses $(m_1,m_2,...,m_n)$, the gravitational field parameter, $α\sim Gm_im_j$, the n-body system reduction mass $M_n$, and the area, $A_n$, of the periodic orbit are selected as the basic parameters, while the period, $T_n$, and the system energy, $|E_n|$, are expressed as the three basic parameters. Using the Buckingham $π$ theorem, We obtained an epic result, by working with a reduced gravitation parameter $α_n$, then predicting a dimensionless relation $T_n|E_n|^{3/2}=\text{const} \times α_n \sqrt{μ_n}$ ($μ_n$ is reduced mass). The const$=\fracπ{\sqrt{2}}$ is derived by matching with the 2-body Kepler's third law, and then a surprisingly simple relation for Kepler's third law of an n-body system is derived by invoking a symmetry constraint inspired from Newton's gravitational law: $T_n|E_n|^{3/2}=\fracπ{\sqrt{2}} G\left(\frac{\sum_{i=1}^n\sum_{j=i+1}^n(m_im_j)^3}{\sum_{k=1}^n m_k}\right)^{1/2}$. This formulae is, of course, consistent with the Kepler's third law of 2-body system, but yields a non-trivial prediction of the Kepler's third law of 3-body: $T_3|E_3|^{3/2}= \fracπ{\sqrt{2}} G \left[\frac{(m_1m_2)^3+(m_1m_3)^3+(m_2m_3)^3}{m_1+m_2+m_3}\right]^{1/2}$. A numerical validation and comparison study was conducted. This study provides a shortcut in search of the periodic solutions of three-body and n-body problems and has valuable application prospects in space exploration.
“DAM Becky, Look at That Asset”: Digital Asset Management in Cultural Heritage Institutions

This study explores the role of the Digital Asset Management system within Cultural Heritage Institutions, and acts as a needs assessment for institutions with DAM systems in place. The study was conducted to understand how Digital Asset Management systems are being used in institutions and what the potential roadblocks are for implementation at smaller institutions.    Before delving into research, the paper outlines both the history of Digital Asset Management systems in museums, as well as its potential futures. The research is based on a survey and telephone interviews of industry professionals that occurred in the Spring of 2019. Despite a growing interest in DAM systems, Cultural Heritage Institutions are still in need of more nuanced features specific to their workflows.
The Perspective of Originality: Research on the Legal Attribute of Content Generated by Artificial Intelligence

With the strong rise of generative AI represented by ChatGPT, the issue of copyrightability of AI-generated content has become the focus of controversy in both theoretical and practical circles. The pivotal aspect in determining the legal status of AI-generated content lies in establishing a standard for originality. The current discourse within the theoretical community regarding the copyrightability of such content often revolves around the contrasting viewpoints of the "Dialectics of Negation" and the "Dialectics of Affirmation." By refining the criteria for assessing the originality of AI-generated content and evaluating their attributes through objective measures like "independent creation" and "modicum of creativity", demarcating the boundaries of creative expression, streamlining the creative process, and driving forward the expansion of the artificial intelligence industry. This endeavor is essential for enhancing legal clarity, fostering innovation, and navigating the dynamic landscape where technology and creativity intersect.
A Case Study of Using Inventory Turnover as a Key Measure for Restructuring Supply Chain and Logistics Management

วารสารวิชาชีพบัญชี JAP, 14, 42 (มิถุนายน 61), 69
ALZHEIMER’S DEMENTIA EARLY DIAGNOSIS, CHARACTERIZATION, PROGNOSIS AND TREATMENT DECISION VIA A SOFTWARE‐AS‐MEDICAL DEVICE WITH AN ARTIFICIAL INTELLIGENT AGENT

AbstractBackgroundTRACE4AD (DeepTrace Technologies s.r.l, Italy) is a machine learning‐based software‐as‐medical device able to predict the conversion to Alzheimer’s disease (AD) dementia of subjects at risk within 24‐months exploiting automatic processing of T1‐weighted MPRAGE brain MRI study and neuropsychological tests. TRACE4AD provides a report with the predicted individual risk of conversion to AD dementia, specific cognitive deficits, and suggestions supporting neurologists in diagnosis and characterization, prognosis, and decision‐making. We tested TRACE4AD in the clinical setting in its ability, at baseline, to: a) predict amnestic Mild Cognitive Impairment (MCI) conversion to AD dementia within 24‐months; b) characterize cognitive deficits; c) support neurologists' decision‐making.MethodWe retrospectively included 92 subjects (mean age 73.12±7.6, 46% female): 32 patients from two Italian centers where TRACE4AD was implemented after user training; and 60 subjects from the ADNI dataset. All patients had a brain MPRAGE study at baseline, 77/92 patients (83.7%) also performed a neuropsychological assessment at baseline, 75/92 patients (81.5%) had a stable clinical diagnosis at 24‐month. TRACE4AD extracted the gray matter map from MPRAGE and used it (combined with cognitive measures when available) to make inferences. Reference standards were: a) the neurologist’s clinical diagnosis at 24‐months, b) the neuropsychological assessment at the baseline, c) the agreement with the neuro exam and intervention decision time and type defined by neurologists at the baseline.ResultTRACE4AD accurately predicted conversion to AD dementia in 93.3% of patients based on the MRI, and in 96.6% based on MRI and cognitive measures. Cognitive deficits were found in agreement with the neuropsychological assessment for all patients except one who presented with major depression. We found disagreement between the neurologist’s decision at baseline and the tool in only two patients, defined with normal cognition by the neurologist and predicted at high risk of AD dementia conversion by the tool. TRACE4AD supported neurologists' decision by 12 months in 15/17 patients for the prompt decision at baseline.ConclusionTRACE4AD is promising, safe, and effective in supporting neurologists in the clinical practice of MCI across different centers.
Airway basal stem cell therapy for lung diseases: an emerging regenerative medicine strategy

Chronic pulmonary diseases pose a prominent health threat globally owing to their intricate pathogenesis and lack of effective reversal therapies. Nowadays, lung transplantation stands out as a feasible treatment option for patients with end-stage lung disease. Unfortunately, the use of this this option is limited by donor organ shortage and severe immunological rejection reactions. Recently, airway basal stem cells (BSCs) have emerged as a novel therapeutic strategy in pulmonary regenerative medicine because of their substantial potential in repairing lung structure and function. Airway BSCs, which are strongly capable of self-renewal and multi-lineage differentiation, can effectively attenuate airway epithelial injury caused by environmental factors or genetic disorders, such as cystic fibrosis. This review comprehensively explores the efficacy and action mechanisms of airway BSCs across various lung disease models and describes potential strategies for inducing pluripotent stem cells to differentiate into pulmonary epithelial lineages on the basis of the original research findings. Additionally, the review also discusses the technical and biological challenges in translating these research findings into clinical applications and offers prospective views on future research directions, therefore broadening the landscape of pulmonary regenerative medicine.
Observability of secondary Doppler peaks in the cosmic microwave background radiation power spectrum by experiments with small fields

We investigate the effects of finite sky coverage on the spectral resolution $\Delta\ell$ in the estimation of the CMBR angular power spectrum $C^{\ell}$. A method is developed for obtaining quasi-independent estimates of the power spectrum, and the cosmic/sample variance of these estimates is calculated. The effect of instrumental noise is also considered for prototype interferometer and single-dish experiments. By proposing a statistic for the detection of secondary (Doppler) peaks in the CMBR power spectrum, we then compute the significance level at which such peaks may be detected for a large range of model CMBR experiments. In particular, we investigate experimental design features required to distinguish between competing cosmological theories, such as cosmic strings and inflation, by establishing whether or not secondary peaks are present in the CMBR power spectrum.
Predicting surface phase transitions from<i>ab initio</i>based statistical mechanics and thermodynamics

The atomic structure and stoichiometry of a solid surface dictates its physical and chemical properties, and hence plays a crucial role in the performance of a material in technological applications. Indeed, in the field of surface science, a significant proportion of studies address the determination of surface atomic geometries and associated phase transitions. From the theoretical side, the desire is to obtain a first-principles based description that can accurately predict arbitrary surface structures and phase transitions under various conditions, such as temperature, partial pressure, and adparticle coverage. In the present paper, we discuss recent theoretical approaches through various examples, which address this goal. In particular, ab initio atomistic thermodynamics, which affords determination of the surface free energy as a function of relevant atom chemical potentials, and varying pressure and temperature conditions, as well as more powerful schemes that combine first-principles quantum mecha...
Measurement of a Peak in the Cosmic Microwave Background Power Spectrum from the North American Test Flight of Boomerang

We describe a measurement of the angular power spectrum of anisotropies in the Cosmic Microwave Background (CMB) from 0.3 degrees to ~10 degrees from the North American test flight of the BOOMERANG experiment. BOOMERANG is a balloon-borne telescope with a bolometric receiver designed to map CMB anisotropies on a Long Duration Balloon flight. During a 6-hour test flight of a prototype system in 1997, we mapped &gt; 200 square degrees at high galactic latitudes in two bands centered at 90 and 150 GHz with a resolution of 26 and 16.6 arcmin FWHM respectively. Analysis of the maps gives a power spectrum with a peak at angular scales of ~1 degree with an amplitude ~70 uK.
VIIRS on-orbit optical anomaly: investigation, analysis, root cause determination and lessons learned

A gradual, but persistent, decrease in the optical throughput was detected during the early commissioning phase for the Suomi National Polar-Orbiting Partnership (SNPP) Visible Infrared Imager Radiometer Suite (VIIRS) Near Infrared (NIR) bands. Its initial rate and unknown cause were coincidently coupled with a decrease in sensitivity in the same spectral wavelength of the Solar Diffuser Stability Monitor (SDSM) raising concerns about contamination or the possibility of a system-level satellite problem. An anomaly team was formed to investigate and provide recommendations before commissioning could resume. With few hard facts in hand, there was much speculation about possible causes and consequences of the degradation. Two different causes were determined as will be explained in this paper. This paper will describe the build and test history of VIIRS, why there were no indicators, even with hindsight, of an on-orbit problem, the appearance of the on-orbit anomaly, the initial work attempting to understand and determine the cause, the discovery of the root cause and what Test-As-You-Fly (TAYF) activities, can be done in the future to greatly reduce the likelihood of similar optical anomalies. These TAYF activities are captured in the lessons learned section of this paper.
Protecting ‘Cybersecurity &amp;amp; Resiliency’ of Nation’s Critical Infrastructure – Energy, Oil &amp;amp; Gas

Cyber and sophistication of cyber adversaries grow, so too must the US power system’s defenses, situational awareness, and response and recovery strategies. Traditionally power dedicated communication channels to large generators and utility-owned assets but network connectivity in today’s industrial entities, including electrical utilities, has exposed many digital communication and control aspects to the threat of cyber-attacks.When forward-looking improvements including smart grid, smart meters and other advancements are considered, security is of foremost concern. In fact, governments around the world have recognized the existing vulnerability and need to protect the grid infrastructure. To solve the problem, regulations and standards are being developed to ensure that the proper security steps are taken. In addition, cyber attackers have targeted crude oil and natural gas (O&G) companies, with attacks growing in frequency, sophistication and impact as the industry employs ever more connected technology. But the industry’s cyber maturity is relatively low, and O&G boards show generally limited strategic appreciation of cyber issues. research paper documents the current spread throughout US, highlights required security enhancements and recommendations to foster Cyber-secure, resilient energy is paramount to the prosperity of the United States. As the experience additionally, power systems were operated with control aspects to the threat of cyber companies, with attacks growing in frequency, sophistication, and Cyber security gaps across Energy, Oil & Gas sector systems Security & Resiliency of our Critical Infrastructure.
System Level simulation framework for the ASICs development of a novel particle physics detector

The simulation of the passage of particles through matter using Monte Carlo methods is broadly used in the development of particle detectors for high energy physics experiments. To develop the readout electronics for the Compact Muon Solenoid (CMS) experiment at CERN, and to assist the design of the on-detector ASICs, a simulation framework was build capable to link the physics Monte Carlo simulations platforms with an industry standard EDA simulation tools. This contribution focuses on the implementation of the simulation framework based on the System Verilog language and the Universal Verification Methodology (UVM). The simulation results that guided the development of the ASICs and the choice of the final architecture are presented.
Promoting the Values of Integrity, Transparency, and Accountability and Their Role in Combating Corruption

Corruption has been a widespread global phenomenon since ancient times and has no limited time, and there is hardly a society without modern and old societies from it, and corruption has become the biggest challenge facing all governments and societies. Therefore, our goal in this research is to identify the concept of corruption as well as to define the concept of integrity, transparency and accountability and the role of promoting their values in combating and eliminating corruption by promoting the higher values that are honesty, honesty and sincerity at work, and complete clarity in decision-making, drawing plans and policies, and providing those responsible for jobs with periodic reports on their work, policy and success in implementing them.
The International Criminal Tribunal for the Former Yugoslavia: paving the way for modern international humanitarian law enforcement

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Investigating the Influence of AI Attitudes on Visual Literacy for AI-Generated Images Through AI-Specific Creative Self-Efficacy Among Chinese Art Students

While the spread of artificial intelligence (AI)-generated images becomes inevitable, many universities started to pay attention to developing their art students’ visual literacy in this regard. In this case, these students’ visual literacy for AI-generated images becomes an important area of investigation. This study examines whether attitudes of Chinese art students towards AI will affect their visual literacy for AI-generated images and investigates the mediating role of AI-specific creative self-efficacy (AI-Specific CSE) therein. A total of 418 valid self-reported responses were collected from art students at a Chinese university. The results showed that AI attitudes had a directly positive impact on these students’ visual literacy with AI-specific CSE working as a positive mediator. These findings suggest the great importance of psychological factors in art students’ visual literacy development and offer some pedagogical implications for university leaders and teachers. Beyond this study, broader educational suggestions were also given to cultivate the future artists to use AI tools more critically for their creative process.
From Connection to Concern: Understanding Social Media's Influence on Mental Health Among Adolescents in Abuja, Nigeria

Background: Social media has become an integral part of daily life for adolescents but it is influencing their mental well being significantly. This study investigates social media usage patterns among students of a Government Senior Secondary School in Abuja and their effects on mental health. Methods: A cross-sectional study was conducted with a sample of 265 students, selected through systematic random sampling. Data were collected on age, gender, family structure, social media use, experiences of cyberbullying, and mental health indicators via a structured self-administered questionnaire. Analysis utilized IBM-SPSS version 27, employing descriptive statistics for quantitative variables and Chi-square tests for categorical variables (p ≤ 0.05). Results: Findings revealed that 56.9% of respondents were aged 16-18 years, with 60% female. Most (58.5%) used social media for 1-3 hours daily, while 6.9% exceeded 10 hours. Motivations included social connection and entertainment, with 17.3% reporting experiences of cyberbullying. Mental health assessments indicated that 56.5% displayed poor mental health, though 42.3% retained optimism. Notably, family structure significantly affected digital engagement (p = 0.001). Conclusion: This study underscores the prevalent use of social media among adolescents and its substantial impact on mental health, highlighting factors like cyberbullying. The alarming rate of poor mental health emphasizes the need for targeted interventions, including digital literacy education, enhanced mental health support, and community programs to promote responsible social media use.
Lifestyle intervention on psychotherapy and exercise and their effect on physical and psychological health in outpatients with schizophrenia spectrum disorders. A pragmatic clinical trial

IntroductionPatients with Schizophrenia Spectrum Disorders (SSD) often lead unhealthy lifestyles with higher prevalence of obesity and unfavourable cardiometabolic parameters with less life expectancy and often worse quality of life compared with general population.ObjectivesEvaluate the effectiveness of a combined intervention of exercise and psychoeducation in 48 SSD outpatients with metabolic syndrome (MetS), treated with second-generation antipsychotics and also aimed to explore if the effect persisted in a long-term follow-up of 24 months.MethodsThe intervention included a 12-week aerobic exercise program and a session of lifestyle psychoeducation. Effectiveness was measured in terms a wide range of outcomes involving physical and psychological health, functioning, quality of life, physical activity and changes in motivation to exercise in the context of the self-determination theory.ResultsThe active intervention group showed benefits after Bonferroni correction over clinical global impression, identified motivation to exercise and changes of physical activity pattern. Maintenance of effects after 24 months of follow-up was observed for identified regulation to exercise and also for negative symptoms of psychosis (Table). Table. Effects assigned-group/time-over *p≤0.05 **p≤0.01. Variables12weeks24monthsTimeGroupxtimeGroupx timex gender p p p ppHDL (mg/dl)0.021*Negative Syndrome Scale0.044*0.004**BREQ-2- Extrinsic regulation0.008**0.004**-External0.026*-Introyected0.038*-Identified0.018*0.015*0.003**0.002**BREQ-2-Intrinsic regulation0.005**0.004**Pedometer (steps/day)0.001**0.006**ConclusionsA combined intervention on SSD outpatients with MetS showed effectiveness over several clinical parameters and functioning. Therefore, should be considered an essential part of the integral treatment in mental health services for SSD patients.DisclosureNo significant relationships.