Miracle-dz/UniFAR-FTUs huggingface dataset:
Ionization Collection in Detectors of the Cryogenic Dark Matter Search

Author(s): Phipps, Arran Thomas James | Advisor(s): Sadoulet, Bernard | Abstract: Determining the composition of dark matter is at the forefront of modern scientific research. There is compelling evidence for the existence of vast quantities of dark matter throughout the universe, however it has so-far eluded all direct detection efforts and its identity remains a mystery. Weakly interacting massive particles (WIMPs) are a favored dark matter candidate and have been the primary focus of direct detection for several decades. The Cryogenic Dark Matter Search (CDMS) has developed the Z-dependent Ionization and Phonon (ZIP) detector to search for such particles. Typically made from germanium, these detectors are capable of distinguishing between electromagnetic background and a putative WIMP signal through the simultaneous measurement of ionization and phonons produced by scattering events. CDMS has operated several arrays of these detectors at the Soudan Underground Laboratory (Soudan, MN, USA) resulting in many competitive (often world-leading) WIMP exclusion limits. This dissertation focuses on ionization collection in these detectors under the sub-Kelvin, low electric field, and high crystal purity conditions unique to CDMS. The design and performance of a fully cryogenic HEMT-based amplifier capable of achieving the SuperCDMS SNOLAB ionization energy resolution goal of 100 eVee is presented. The experimental apparatus which has been used to record electron and hole properties under CDMS conditions is described. Measurements of charge transport, trapping, and impact ionization as a function of electric field in two CDMS detectors are shown, and the ionization collection efficiency is determined. The data is used to predict the error in the nuclear recoil energy scale under both CDMSlite and iZIP operating modes. A two species, two state model is developed to describe how ionization collection and space charge generation in CDMS detectors are controlled by the presence of ``overcharged'' $D^-$ donor and $A^+$ acceptor impurity states. The thermal stability of these states is exclusive to sub-Kelvin operation, explaining why ionization collection in CDMS detectors differs from similar semiconductor detectors operating at higher temperature. This work represents a solid foundation for the understanding ionization collection in CDMS detectors.
Parts of adjoint weighted shifts

We characterize the parts of a vector-valued adjoint shift operator using operator inequalities and a stability condition. The characterization applies in a class of weighted shifts containing the classical Hardy shift operator as well as the full scale of standard weighted Bergman shift operators on the unit disc. Related operator models form an integral part in recent work on generalized mathematical systems theory and Bergman inner functions. 0. Introduction Let E be an auxiliary Hilbert space and let w = {wk}k≥0 be a positive weight sequence such that w0 = 1 and lim infk→∞ w 1/k k = 1. We consider the space Aw(E) of all E-valued analytic functions (0.1) f(z) = ∑
Baseline Findings of PreventE4: A Double-Blind Placebo Controlled Clinical Trial Testing High Dose DHA in APOE4 Carriers before the Onset of Dementia

Introduction Lower blood levels of the omega-3 polyunsaturated fatty acid docosahexaenoic acid (DHA) are correlated with worse cognitive functions, particularly among APOE ε4 carriers. Whether DHA supplementation in APOE ε4 carriers with limited DHA consumption and dementia risk factors can delay or slow down disease progression when started before the onset of clinical dementia is not known. Methods PreventE4 is a double-blind, single site, randomized, placebo-controlled trial in cognitively unimpaired individuals with limited omega-3 consumption and dementia risk factors (n=368). Its objectives are to determine (1) whether carrying the APOE ε4 allele is associated with lower delivery of DHA to the brain; and (2) whether high dose DHA supplementation affects brain imaging biomarkers of AD and cognitive function. Results 365 cognitively unimpaired individuals between 55 and 80 (mean age 66) were randomized to 2 grams of DHA per day or identically appearing placebo for a period of 2 years. Half the participants were asked to complete lumbar punctures at baseline and 6-month visits to obtain cerebrospinal fluid (CSF). The primary trial outcome measure is the change in CSF DHA to arachidonic acid ratio after 6 months of the intervention (n=181). Secondary trial outcomes include the change in functional and structural connectivity using resting state functional MRI at 24 months (n=365). Exploratory outcomes include the change in Repeatable Battery of the Assessment of Neuropsychological Status at 24 months (n=365). Conclusions Findings from PreventE4 will clarify the brain delivery of DHA in individuals carrying the APOE ε4 allele with implications for dementia prevention strategies. Trial was registered as NCT03613844.
IDENTIFICATION OF SOIL-CULTURABLE MICROMYCETES IN AVOCADO ORCHARDS IN NORTHEASTERN MEXICO

Mexico is the world's leading producer and exporter of avocado ( Persea americana Miller). There are few studies on soil microorganisms associated with this crop, which are important to establish the role they can play in the production system and their use in different areas of interest. In this re-search, the biodiversity of cultivable micromycetes in the soil of five avocado orchards located in two municipalities of the state of Nuevo León was determined. The isolates obtained were grouped into morphotypes and identified to genus level or grouped by common morphological characteristics. Shannon-Wiener, Simpson, and Margalef diversity indices were determined for morphotypes, as well as for and genera and groups of micromycetes with common characteristics in each orchard. The Hutcheson's test (p= 0.05) was performed to determine significant differences between Shannon-Wiener diversity index of genera and micromycetes with common characteristics between orchards. A total of 518 isolates were obtained and classified into 291 morphotypes that were grouped into 44 genera and 7 groups with common characteristics. Hutcheson's test showed that the Shannon-Wiener index of genera and groups of a single orchard is different to the others. The sterile mycelium group was the most abundant in four of the five orchards. Genera reported as phytopathogens ( Fusarium , Verticillium ), entomopathogens ( Beauveria , Paecilomyces , Metarhizium ) and mycoparasites ( Trichoderma , Gliocladium ) were identified. In addition, 28 new genera associated with avocado orchard soil are reported in this research.
University of Birmingham Profile of neratinib and its potential in the treatment of breast cancer

: The HER (ErbB) receptor tyrosine kinase receptors are implicated in many cancers and several anti-HER treatments are now approved. In recent years, a new group of compounds that bind irreversibly to the adenosine triphosphate binding pocket of HER receptors have been developed. One of these compounds, neratinib, has passed preclinical phases and is currently undergoing various clinical trials. This manuscript reviews the preclinical as well as clinical data on neratinib. As a pan-HER inhibitor, this irreversible tyrosine kinase inhibitor binds and inhibits the tyrosine kinase activity of epidermal growth factor receptors, EGFR (or HER1), HER2 and HER4, which leads to reduced phosphorylation and activation of downstream signaling pathways. Neratinib has been shown to be effective against HER2-overexpressing or mutant tumors in vitro and in vivo. Neratinib is currently being investigated in various clinical trials in breast cancers and other solid tumors, including those with HER2 mutation. Earlier studies have already shown promising clinical activity for neratinib. However, more translational research is required to investigate biomarkers that could help to predict response and resistance for selection of appropriate patients for treatment with neratinib, either as monotherapy or in combination with other drug(s).
In vitro Studies on the Neuroprotective Potential of Rhododendron arboreum Flower

Rhododendron arboreum (Buransh) is the national flower of Nepal and is predominantly found in the Himalayan belt. Since ancient times, the bright red flowers have been utilised in various medicinal practices. Floral extracts have been used in ethnomedicine to treat a wide spectrum of health conditions like gout, rheumatism, diarrhoea, blood dysentery, and high-altitude sickness. Studies have elucidated that the floral parts of the plant are rich in phenols, alkaloids, and other bioactives, making it an elixir of life. Although the plant has established medicinal value among the locals, due to the ephemeral blooming phase of the flower and meagre availability, the neuroprotective potential of Rhododendron arboreum flowers is yet to be confirmed by scientific studies. In this study, we aim to establish the therapeutic role of the flower extracts in oxidative stress-based neurodegeneration. There have been predictions about a colossal surge in the prevalence of neurodegenerative diseases in the upcoming decades. Furthermore, we are yet to develop a potential cure. Here, we aim to impart preliminary information about Rhododendron arboreum flower (RAF) potency, including antioxidant potential as well as its impact on oxidative stress markers in a neurodegenerative disease model, essential for further clinical development of novel therapeutic drugs
Testing Efficiency in NHL Betting Markets Testing Efficiency in NHL Betting Markets

The efficiency of markets is a prominent topic in the field of finance. Market efficiency has been thoroughly examined across many subsectors of finance; however thus far, existing research has sparsely covered the increasingly prominent sports betting market. This market is currently valued at roughly $10B per year (Grandview). In this article, we evaluate the efficiency of sports betting markets, using NHL betting lines and results from 2015-2020 to create a multivariate probit model which tests the market’s efficiency. Using a multivariate probit model to identify NHL money line bets with a relatively high probability of success compared to their implied probability, we generate significant profit and beat betting markets, generating an 8.5% ROI when tested against the 20-21 NHL season.
CHARACTERIZATION OF CHALCONE ISOMERASE 4A ( CHI4A ) GENE IN Pueraria mirifica

Pueraria mirifica is a popular medicinal plant and is rich in phytoestrogens, especially isoflavonoids. The chalcone isomerase ( CHI ) gene is well-known as a key factor in biosynthetic pathways such as flavonoid, isoflavonoid, and anthocyanin biosynthesis. Among four CHI subfamilies, group IV remained largely uncharacterized in P. mirifica . By isolation and gene cloning, the CHI4A gene was amplified and sequenced. A dataset that included CHI4A genes from isolation, transcriptome, and Glycine max CHI4A was constructed for analysis. A total of 31 single nucleotide polymorphism (SNPs) was detected among sequences and 14 SNPs were found in P. mirifica subgroups. Thirteen SNPs changed the amino acid sequences of CHI4A genes; however, they do not affect core active residues in the protein structure. Two active sites typical for group 4 CHI in the Fabaceae family: Ile50 and Tyr106; and one conserved site Asn113, were found in this study, which is similar to the result of the previous study on CHI4 . A three-dimensional protein model of isolated P. mirifica CHI4A enzyme was constructed with a high confidence level. The result provides more information about the variation and protein profile of the CHI4A gene for further experiments.
Role of Emerging Risk Markers in Cardiometabolic Syndrome

Cardiometabolic syndrome (CMS), also known as metabolic syndrome (MetS) is a common and silent epidemic, which is linked to type 2 diabetes mellitus, abdominal obesity, and a higher risk of cardiovascular disease. Comprehensive demographic, physiological, genetic, and clinical data were collected from 199 subjects suffering from varying degrees of Metabolic syndrome (MetS) and 100 healthy control subjects. Mutagen induced chromosome sensitivity analysis for DNA repair proficiency and the extent of somatic DNA damages by Cytokinesis-Block Micronuclei (CBMN) assay were also performed among the study subjects. The study found that individuals with CMS showed an elevated concentration of Lp-PLA2, MA and hsCRP. The study also showed an association between DNA damage and DNA repair among the test subjects. Microalbumin and Lp-PLA2 can be considered good markers for the early prediction of coronary artery disease (CAD) and several other cardiovascular diseases. In addition, the rising frequency of somatic DNA damage points to the varied degrees of MetS progression. Thus, novel biomarkers can identify patients who are at risk beyond traditional ones, thereby alleviating the possible CMS events and also other disorders related to CMS by following healthy lifestyle habits and proper medication.
Discovering Hierarchy for Reinforcement Learning Using Data Mining

Reinforcement Learning has the limitation that problems become too large very quickly. Dividing the problem into a hierarchy of subtasks allows for a strategy of divide and conquer, which is what makes Hierarchical Reinforcement Learning (HRL) algorithms often more efﬁcient at ﬁnding solutions quicker than more na¨ıve approaches. One of the biggest challenges with HRL is the construction of a hierarchy to be used by the algorithm. Hierarchies are often designed by a human author using their own knowledge of the problem. We pro-pose a method for automatically discovering task hierarchies based on a data mining technique, Association Rule Learning (ARL). These hierarchies can then be applied to Semi-Markov Decision Process (SMDP) problems using the options technique.
Recommending for a Multi-Sided Marketplace: A Multi-Objective Hierarchical Approach

Many online systems today are multi-sided platforms. They create value by bringing buyers, sellers and other partners together, reducing search and transaction costs (Evans and Schmalensee 2016). A recommendation system for these platforms faces two main challenges. First, all sides of the marketplace have different and potentially conflicting utilities. Recommending in these contexts therefore entails jointly optimizing multiple conflicting objectives. Second, many platforms today present their recommendations hierarchically, where a recommendation item can be either a single product or a group of products. Off-the-shelf recommendation algorithms are not applicable in these settings. We propose MOHR, a multi-objective hierarchical recommender that tackles these challenges. MOHR combines machine learning with scalable multi-objective optimization for multi-sided recommendation, and incorporates a probabilistic model for hierarchical recommendation which accounts for consumers’ browsing patterns. The hierarchical approach ensures consistent consumer experience across different levels of aggregations of the products, and provides transparency to the restaurant partners. We further develop an efficient optimization solution for serving MOHR in large-scale online platforms in real time. We implement MOHR at one of the largest industrial three-sided food delivery platforms in the world serving millions of consumers, and experiment with objectives including consumer happiness, marketplace fairness and partner earnings. Online experiments show a significant increase in consumer conversion, retention and gross bookings, which combined translate to $1.5 million weekly gain in revenue. Our work has been deployed globally by the industrial food delivery platform as the recommendation algorithm for its homepage.
Unleashing the Power of Language Models in Clinical Settings: A Trailblazing Evaluation Unveiling Novel Test Design

The realm of clinical medicine stands on the brink of a revolutionary break-through as large language models (LLMs) emerge as formidable allies, propelled by the prowess of deep learning and a wealth of clinical data. Yet, amidst the dis-quieting specter of misdiagnoses haunting the halls of medical treatment, LLMs offer a glimmer of hope, poised to reshape the landscape. However, their mettle and medical acumen, particularly in the crucible of real-world professional sce-narios replete with intricate logical interconnections, remain shrouded in uncer-tainty. To illuminate this uncharted territory, we present an audacious quantitative evaluation method, harnessing the ingenuity of thoracic surgery questions as the litmus test for LLMs' medical prowess. These clinical questions covering various diseases were collected, and a test format consisting of multi-choice questions and case analysis was designed based on the Chinese National Senior Health Professional Technical Qualification Examination. Five LLMs of different scales and sources were utilized to answer these questions, and evaluation and feedback were provided by professional thoracic surgeons. Among these models, GPT-4 demonstrated the highest performance with a score of 48.67 out of 100, achieving accuracies of 0.62, 0.27, and 0.63 in single-choice, multi-choice, and case-analysis questions, respectively. However, further improvement is still necessary to meet the passing threshold of the examination. Additionally, this paper analyz-es the performance, advantages, disadvantages, and risks of LLMs, and proposes suggestions for improvement, providing valuable insights into the capabilities and limitations of LLMs in the specialized medical domain.
Drug-Coated versus conventional balloon to improve recanalization of a coronary chronic total occlusion after failed attempt.

Background: Chronic total occlusion (CTO) plaque modification (CTO-PM) is often used for unsuccessful CTO interventions. Methods: Multicenter, prospective study including consecutive patients with failed CTO recanalization. At the end of the failed procedure, patients received either conventional (CB) or drug-coated balloon (DCB) or at the operator? s discretion for CTO-PM and underwent new attempt of CTO recanalization ~3 months later. Results: A total of 55 patients were enrolled (DCB: 22; CB 33), with a median age of 66 years. Median J-score was 3 and CCS angina class III-IV was present in 40% of the patients. After the first CTO-PCI attempt no in hospital cardiac deaths were registered, with 3.6% rates of in-hospital myocardial infarction. The success rate of the second CTP PCI attempt was 86.8%, with periprocedural complication rate of 5.7% and without difference between DCB and CB groups. Compared with CB, in the DCB group, the second CTO-PCI required a shorter median fluoroscopy time (33 vs 60min, p<0.001), lower contrast volume (170 vs 321cc, p<0.001) and lower radiation dose (1.7 vs 3.3Gy, p<0.001). At 1-year follow up outcomes were comparable between the 2 strategies, target lesion failure occurred in 5.7% and major adverse cardiovascular events in 11.2%. Conclusions: PM after CTO recanalization failure is safe and warrants high success rates when 2nd attempt is performed. A DCB strategy for CTO-PM does not seem to ensure higher success or better clinical outcomes, but its use was associated with simpler staged procedures.
Effect of Tai Chi on Pain and Cognitive Function in Elderly Patients with Chronic Neck Pain: A Protocol for Systematic Review and Meta-analysis

Background : The incidence of chronic neck pain (CNP) in the elderly is increasing. CNP in the elderly not only affects the physical function of patients, the quality of life, and work but also increases the direct medical cost and indirect social costs. The recent treatment trends of CNP, such as home self-exercise, focused specific training, and research into the underlying neural mechanisms of pain and cognitive improvement in patients with CNP, suggest that Tai Chi may be beneficial for pain and cognitive function in elderly patients with CNP. Method and Methods : We will search 8 databases, including PubMed, Embase, Cochrane Library, Web of Science, China National Knowledge Infrastructure (CNKI), China Biomedical Literature Database (CBM), VIP database, and Wanfang database. Randomized controlled trials (RCTs) of Tai Chi in the treatment of elderly CNP will be included. The search time is from the establishment of the database to May 31, 2023. In this study, data extraction and methodological quality evaluation will be carried out for the included literature, and statistical analysis will be performed using RevMan 5.4 software. The quality of evidence will be assessed using the Grading of Recommendations Assessment, Development and Evaluation system approach(GRADE). Discussion: This review will search and collect RCTs related to Tai Chi for the prevention and treatment of elderly CNP, and aims to systematically evaluate the evidence of the effects of Tai Chi on pain and cognitive function in elderly patients with CNP. The results of this review are expected to provide more accurate and effective guidance for the prevention and treatment of elderly patients with CNP, and also provide evidence-based medicine references for the formulation of exercise prescriptions.
Evaluating Large Language Models in Extracting Cognitive Exam Dates and Scores

Background: Large language models (LLMs) provide powerful natural language processing (NLP) capabilities in medical and clinical tasks. Evaluating LLM performance is crucial due to potential false results. In this study, we assessed ChatGPT, a state-of-the-art LLM, in extracting information from clinical notes, focusing on cognitive tests, specifically the Mini Mental State Exam (MMSE) and the Cognitive Dementia Rating (CDR). We tasked ChatGPT with extracting MMSE and CDR scores and corresponding dates from clinical notes. Methods: Our cohort had 135,307 clinical notes (Jan 12th, 2010 to May 24th, 2023) mentioning MMSE, CDR, or Montreal Cognitive Assessment (MoCA). After applying inclusion criteria and excluding notes with only MoCA, 34,465 notes remained. Among them, 765 were randomly selected and underwent analysis by ChatGPT. 22 medically-trained experts reviewed ChatGPT's responses and provided ground truth. ChatGPT (GPT-4, version "2023-03-15-preview") was used on the 765 notes to extract MMSE and CDR instances with corresponding dates. Inference was successful for 742 notes. We used 20 notes for fine-tuning and training the reviewers. The remaining 722 were assigned to reviewers, with 309 each assigned to two reviewers simultaneously. Inter-rater-agreement (Fleiss' Kappa), precision, recall, true/false negative rates, and accuracy were calculated. Results: For MMSE information extraction, ChatGPT achieved 83% accuracy. It demonstrated high sensitivity with a Macro-recall of 89.7% and outstanding true-negative rates of 96%. The precision for MMSE was also high at 82.7%. In the case of CDR information extraction, ChatGPT achieved 89% accuracy. It showed excellent sensitivity with a Macro-recall of 91.3% and a perfect true-negative rate of 100%. However, the precision for CDR was lower at 57%. Analyzing the ground truth data, it was found that 89.1% of the notes included an MMSE documentation, whereas only 14.3% had a CDR documentation, which affected the precision of CDR extraction. Inter-rater-agreement was substantial, supporting the validity of our findings. Reviewers considered ChatGPT's responses correct (96% for MMSE, 98% for CDR) and complete (84% for MMSE, 83% for CDR). Conclusion: ChatGPT demonstrates overall accuracy in extracting MMSE and CDR scores and dates, potentially benefiting dementia research and clinical care. Prior probability of the information appearing in the text impacted ChatGPT's precision. Rigorous evaluation of LLMs for diverse medical tasks is crucial to understand their capabilities and limitations.