Miracle-dz/UniFAR-FTUs huggingface dataset:
Optimizing Screening for HIV

Abstract Background The HIV epidemic is unevenly distributed throughout the United States, even within neighborhoods. This study evaluated how effectively current testing approaches reached persons at risk for HIV infection across San Diego (SD) County, California. Methods HIV case and testing data, sexually transmitted infection (STI) data, and sociodemographic data for SD County were collected from the SD Health and Human Services Agency and the “Early Test” community-based HIV screening program between 1998 and 2016. Relationships between HIV diagnoses, HIV prevalence, and STI diagnoses with screening at the ZIP code level were evaluated. Results Overall, 379 074 HIV tests were performed. The numbers of HIV tests performed on persons residing in a ZIP code or region overall strongly correlated with prevalent HIV cases (R2 = .714), new HIV diagnoses (R2 = .798), and STI diagnoses (R2 = .768 [chlamydia], .836 [gonorrhea], .655 [syphilis]) in those regions. ZIP codes with the highest HIV prevalence had the highest number of tests per resident and fewest number of tests per diagnosis. Even though most screening tests occurred at fixed venues located in high-prevalence areas, screening of residents from lower-prevalence areas was mostly proportional to the prevalence of HIV and rates of new HIV and STI diagnoses in those locales. Conclusions This study supported the ability of a small number of standalone testing centers to reach at-risk populations dispersed across SD County. These methods can also be used to highlight geographic areas or demographic segments that may benefit from more intensive screening.
Blockchain Technologies: Opportunities for Solving Real-World Problems in Healthcare and Biomedical Sciences

Introduction: Blockchain technology is associated with the financial industry, but it can be applied to other industries. The supporting architecture of blockchain has the immense potential to transform the delivery of healthcare, medical, clinical, and life sciences, due to the extended functionality and distinct features of its distributed ledger. The potential scale of impact is comparable to that seen with the introduction of TCP/IP. Blockchain technology has captured the interest of healthcare providers and biomedical scientists within various healthcare domains such as longitudinal healthcare records, automated claims, drug development, interoperability in population health, consumer health, patient portals, medical research, data security, and reducing costs with supply chain management. It is not yet clear if blockchain is going to disrupt healthcare, but healthcare organizations are monitoring its potential closely for prospective concepts like secure patient IDs. Realistically, the adoption and implementation of blockchains will be a gradual evolution over time, but now is the time to take a fresh look at its possibilities in healthcare and biomedical sciences. Blockchain technology revolutionary solutions are bringing us closer to the possibility of every patient record being able to send updates to an open-source, community-wide trusted ledger that is accessible and understood across organizations with guaranteed integrity. Aim and Methods: This paper discusses as a review some potential areas of opportunity for blockchain in the health and biomedical sciences fields. Results and Conclusions: This paper describes and synthesizes 20 examples of real-world use-case scenarios for blockchains in healthcare and biomedical practice.
Breastfeeding Self-Efficacy of Early Postpartum Mothers in an Urban Municipality in the Philippines

Abstract Studies on women have identified breastfeeding confidence as an important variable in influencing breastfeeding outcomes. The mother’s breastfeeding self-efficacy in the early postpartum period was a strong predictor of the duration of breastfeeding. This study aims to assess the breastfeeding self-efficacy of the postpartum mothers in urban barangays of San Jose Occidental Mindoro. The respondents of the study were 200 early postpartum mothers distributed equally chosen from four purposively selected urban barangays. The data collection technique was through a survey interview using 14-item Breastfeeding Self-Efficacy Scale-Short Form (BSES-SF) and a demographic questionnaire. Descriptive and inferential statistics were used to analyze the data. The study revealed that postpartum mothers responded in the study were confident and has self-efficacy in breastfeeding their child as measured through technique and intrapersonal thought in breastfeeding. Moreover, the number of prenatal check up was positively correlated with breastfeeding self-efficacy. The result of the study can be used as a baseline assessment tool in the hospital at delivery to assist in identifying women who are at risk for early weaning.
EFFECT OF CONCURRENT EXPOSURE OF LOWER CONCENTRATIONS OF LEAD AND ENDOSULFAN ON HEPATIC DRUG METABOLIZING ENZYMES IN MALE RATS

The effect of concurrent repeated exposure of lower concentrations of lead and endosulfan were evaluated on hepatic drug metabolizing enzymes in male rats. Alterations were evaluated through changes in the phase I enzymes (viz. cytochrome P450 and cytochrome b5, aminopyrine N – demethylase and aniline phydroxylase) activity and phase II enzymes (viz. microsomal and cytosolic glutathione-S-transferase UDP-glucuronosyl transferase) activity in liver. Lead, when given alone at the dose of 100 ppm in drinking water and endosufan, when given alone at the dose of 10 ppm in feed, and given in combination did not change the activities of cytochrome b5, aminopyrine N – demethylase and aniline phydroxylase. When given in lower dose combination, they significantly inhibited levels of cytochrome 450, microsomal, cytosolic glutathione-S transferase and microsomal protein as compared to control and their single compounds when given alone. This study suggested that activities of xenobiotic drug metabolizing enzymes by repeated exposure to lead and endosulfan at the concentrations used in the study were not modified to produce significant toxicity in case of combined exposure.
Fake People and Sticky Notes: Fostering Communication for Human-Centered Software Design

Products are made or broken by the communication that exists within and between the products’ creative teams. This paper describes a synergistic development process that uses a series of human-centered design artifacts to replace the single, all-inclusive specification document that so often fails to communicate product requirements to the larger development team. The most powerful result that we’ve found as we’ve implemented our process is that communication, between both individuals and entire teams, gets smoother and expectations tend to converge, which results in a better product.
Teaching fractions - visiting the primary school classroom

The most recent guidelines for mathematics in basic education (6-10-years-old) in Portugal preconize an in-depth contact with fractions. These guidelines suggest the approach to quotient, part-whole, measure and operator interpretations of fractions. Thus, it seems pertinent to investigate whether the current teaching practices reflect those guidelines. The research presented here sought to answer the following questions: 1) What role do teachers give to the interpretations of fractions to introduce the concept of fraction to children? 2) How do teachers approach and articulate the different interpretations of fractions? 3) What difficulties do teachers reveal about these issues? A collaborative working program with four teachers was conducted comprising the observation of lessons. The present paper presents the results concerning one of the cases — teacher Inês (fictitious name). A qualitative analysis of the collected data suggests difficulties in selecting examples and introducing the meaning of the fraction when quotient interpretation is involved; difficulties in approaching the ordering and equivalence of fractions; no exploration of the reference unit; unsuitable emphasis on algebraic procedures when operator interpretation is involved. In-service teacher training should be regularly promoted in order to ensure greater convergence between curriculum and teaching practices and improve the quality of the latter.
Higher-Order Rank Functions on Directed Graphs

We introduce a new higher-order rank function with the capability to completely discriminate non-equivalent nodes. We review the partition lattice and rank functions and situate the existing rank functions and higher-order rank functions within the formalization. We propose a new reﬁning operator and a new rank function that are better than the existing ones in some applications. We also show that the entire topology (graph) can be reconstructed from only our higher-order ranks making it possible to compare nodes in different graphs and to update the equivalence of nodes when an edge is added. Finally, we brieﬂy describe the use of our higher-order rank function in analyzing web pages as a possible application in different domains.
Blind Spot Detection for Safe Sim-to-Real Transfer

Agents trained in simulation may make errors when performing actions in the real world due to mismatches between training and execution environments. These mistakes can be dangerous and difficult for the agent to discover because the agent is unable to predict them a priori. In this work, we propose the use of oracle feedback to learn a predictive model of these blind spots in order to reduce costly errors in real-world applications. We focus on blind spots in reinforcement learning (RL) that occur due to incomplete state representation: when the agent lacks necessary features to represent the true state of the world, and thus cannot distinguish between numerous states. We formalize the problem of discovering blind spots in RL as a noisy supervised learning problem with class imbalance. Our system learns models for predicting blind spots within unseen regions of the state space by combining techniques for label aggregation, calibration, and supervised learning. These models take into consideration noise emerging from different forms of oracle feedback, including demonstrations and corrections. We evaluate our approach across two domains and demonstrate that it achieves higher predictive performance than baseline methods, and also that the learned model can be used to selectively query an oracle at execution time to prevent errors. We also empirically analyze the biases of various feedback types and how these biases influence the discovery of blind spots. Further, we include analyses of our approach that incorporate relaxed initial optimality assumptions. (Interestingly, relaxing the assumptions of an optimal oracle and an optimal simulator policy helped our models to perform better.) We also propose extensions to our method that are intended to improve performance when using corrections and demonstrations data.
Quality Control of Crowdsourcing through Workers Expe- rience

Crowdsourcing is applied more widely in many areas. However, the quality control method still needs future improvement. A new quality control method is proposed through worker’s experience in the work which has been divided in to several stages. Workers in each stage are permitted to work on a number of HITs in proportion to their estimated accuracy in previous stages. To test the method, two experiments are conducted on CrowdFlower, and a simulation model is created based on Gaussian distribution and worker quantitative distribution in some existing crowdsourcing result data. The accuracy of result has increased from 76% to 85% in the first experiment, and in the simulation the accuracy of result has increased from 79.75% to 91.5% in simulation program.
Accelerated DPDK in containers for networking nodes

NFV is fast moving towards containers for software virtualization and thereby imposing stringent requirements on container networking. The current status of networking in containers is quite limited especially for fast packet processing and needs further exploration. The thesis is a comprehensive study on container networking for fast packet processing in standalone and orchestrated environments. Existing technologies such as DPDK and SR-IOV are utilized along with OvS and OVN to build different topologies and measure network latency. Utilizing these results and taking into account the hardware features supported by different nodes in an orchestrated environment, the thesis further proposes a latency based scheduler that can meet the network latency requirements of container applications being deployed.
Human milk oligosaccharide 2’-fucosyllactose links feedings at 1 month to cognitive development at 24 months in infants of normal and overweight mothers

Background Infant cognitive development is influenced by maternal factors that range from obesity to early feeding and breast milk composition. Animal studies suggest a role for human milk oligosaccharide (HMO), 2’-fucosyllactose (2’FL), on learning and memory, yet no human studies have examined its impact on infant cognitive development relative to other HMOs and maternal factors. Objective To determine the impact of 2’FL from breast milk feeding on infant cognitive development at 24 months of age relative to maternal obesity and breast milk feeding frequency. Methods and materials Hispanic mother-infant pairs (N = 50) were recruited across the spectrum of pre-pregnancy BMI. Breast milk was collected at 1 and 6 months, and feedings/day were reported. Nineteen HMOs were analyzed using high-performance liquid chromatography, with initial interest in 2’FL. Infant cognitive development score was assessed with the Bayley-III Scale at 24 months. Linear regressions were used for prediction, and bootstrapping to determine mediation by 2’FL. Results Maternal pre-pregnancy BMI was not related to feedings/day or HMOs, but predicted poorer infant cognitive development (β = -0.31, P = 0.03). Feedings/day (β = 0.34) and 2’FL (β = 0.59) at 1 month predicted better infant cognitive development (both P≤ 0.01). The association of feedings/day with infant cognitive development was no longer significant after further adjustment for 2’FL (estimated mediation effect = 0.13, P = 0.04). There were no associations of feedings/day and 2’FL at 6 months with infant cognitive development. Conclusions Our findings suggest that maternal factors influence infant cognitive development through multiple means. Though maternal obesity may be a separate negative influence, greater frequency of breast milk feeding at 1 month contributed to infant cognitive development through greater exposure to 2’FL relative to other HMOs. The influence of 2’FL was not significant at 6 months, indicating that early exposure to 2’FL may be a critical temporal window for positively influencing infant cognitive development.
A catastrophic tropical drought kills hydraulically vulnerable tree species

Drought‐related tree mortality is now a widespread phenomenon predicted to increase in magnitude with climate change. However, the patterns of which species and trees are most vulnerable to drought, and the underlying mechanisms have remained elusive, in part due to the lack of relevant data and difficulty of predicting the location of catastrophic drought years in advance. We used long‐term demographic records and extensive databases of functional traits and distribution patterns to understand the responses of 20–53 species to an extreme drought in a seasonally dry tropical forest in Costa Rica, which occurred during the 2015 El Niño Southern Oscillation event. Overall, species‐specific mortality rates during the drought ranged from 0% to 34%, and varied little as a function of tree size. By contrast, hydraulic safety margins correlated well with probability of mortality among species, while morphological or leaf economics spectrum traits did not. This firmly suggests hydraulic traits as targets for future research.
Thy1 promoter activity in the Rosa26 locus in mice: lessons from Dre-rox conditional expression system

The pronuclear injection (PI)-based targeted transgenesis (PITT) method allows the generation of targeted transgenic (Tg) mice wherein a single copy of a transgene is integrated into the Rosa26 locus following PI. The Rosa26 locus allows unbiased ubiquitous expression of integrated transgenes; however, it remains little known whether tissue-specific promoters retain their functional properties when placed at the Rosa26 locus. We evaluated tissue-specific activity and reproducibility of exogenous tissue-specific promoters targeted to the Rosa26 locus by generating Thy1-Dre/Dre reporter mice using PITT and assessed spatial expression patterns of the transgenes. The Thy1 promoter targeted to the Rosa26 locus appeared active in virtually all Purkinje cells in the cerebellum and hippocampus. However, mosaic expression of the transgene under the Thy1 promoter was observed in many other organs. This phenomenon was consistent in all the Tg lines generated by PITT, indicating a high degree of reproducibility for this experiment.
Can Karst Conduit Models Be Calibrated? A Dual Approach Using Dye Tracing and Temperature

Modeling flow and transport using both temperature and dye tracing provides constraints that can improve understanding of karst networks. A laminar flow and transport model using the finite element subsurface flow model simulated the conduit connection between a sinking stream and spring in central Pennsylvania to evaluate how conduit morphology might affect dye transport. Single and overly tortuous conduit models resulted in high concentrations as dye flowed back into the conduit from the matrix after dye injections ceased. A forked conduit model diverted flow from the main conduit, reducing falling limb dye concentration. Latin hypercube sampling was performed to evaluate the sensitivity of 52 parameter combinations (conduit hydraulic conductivity, conduit cross‐sectional area, matrix transmissivity, matrix porosity, and dispersivity) for four conduit geometry scenarios. Sensitivity of arrival time for 50% of the dye indicated no parameter combinations which simulate falling limb dye concentrations for tortuous geometries, confirming the importance of the forked geometry regardless of other parameters. Temperature data from high‐resolution loggers were then incorporated into the forked conduit model to reproduce seasonal spring temperature using variable sink inflow. Unlike the dye trace models, the thermal models were sensitive to other model parameters, such as conduit cross‐sectional area and matrix transmissivity. These results showed this dual approach (dye and temperature) to karst network modeling is useful for (1) exploring the role of conduit and matrix interaction for contaminant storage, (2) constraining karst conduit geometries, which are often poorly understood, and (3) quantifying the effect of seasonal trends on karst aquifers.
Multiple Myeloma: Available Therapies and Causes of Drug Resistance

Multiple myeloma (MM) is the second most common blood cancer. Treatments for MM include corticosteroids, alkylating agents, anthracyclines, proteasome inhibitors, immunomodulatory drugs, histone deacetylase inhibitors and monoclonal antibodies. Survival outcomes have improved substantially due to the introduction of many of these drugs allied with their rational use. Nonetheless, MM patients successively relapse after one or more treatment regimens or become refractory, mostly due to drug resistance. This review focuses on the main drugs used in MM treatment and on causes of drug resistance, including cytogenetic, genetic and epigenetic alterations, abnormal drug transport and metabolism, dysregulation of apoptosis, autophagy activation and other intracellular signaling pathways, the presence of cancer stem cells, and the tumor microenvironment. Furthermore, we highlight the areas that need to be further clarified in an attempt to identify novel therapeutic targets to counteract drug resistance in MM patients.
Quantitative Proteomics to Identify Nuclear RNA-Binding Proteins of Malat1

The long non-coding RNA Malat1 has been implicated in several human cancers, while the mechanism of action is not completely understood. As RNAs in cells function together with RNA-binding proteins (RBPs), the composition of their RBP complex can shed light on their functionality. We here performed quantitative interactomics of 14 non-overlapping fragments covering the full length of Malat1 to identify possible nuclear interacting proteins. Overall, we identified 35 candidates including 14 already known binders, which are able to interact with Malat1 in the nucleus. Furthermore, the use of fragments along the full-length RNA allowed us to reveal two hotspots for protein binding, one in the 5′-region and one in the 3′-region of Malat1. Our results provide confirmation on previous RNA-protein interaction studies and suggest new candidates for functional investigations.
Deep Cerebellar Transcranial Direct Current Stimulation of the Dentate Nucleus to Facilitate Standing Balance in Chronic Stroke Survivors—A Pilot Study

Objective: Cerebrovascular accidents are the second leading cause of death and the third leading cause of disability worldwide. We hypothesized that cerebellar transcranial direct current stimulation (ctDCS) of the dentate nuclei and the lower-limb representations in the cerebellum can improve functional reach during standing balance in chronic (>6 months’ post-stroke) stroke survivors. Materials and Methods: Magnetic resonance imaging (MRI) based subject-specific electric field was computed across a convenience sample of 10 male chronic (>6 months) stroke survivors and one healthy MRI template to find an optimal bipolar bilateral ctDCS montage to target dentate nuclei and lower-limb representations (lobules VII–IX). Then, in a repeated-measure crossover study on a subset of 5 stroke survivors, we compared 15 min of 2 mA ctDCS based on the effects on successful functional reach (%) during standing balance task. Three-way ANOVA investigated the factors of interest– brain regions, montages, stroke participants, and their interactions. Results: “One-size-fits-all” bipolar ctDCS montage for the clinical study was found to be PO9h–PO10h for dentate nuclei and Exx7–Exx8 for lobules VII–IX with the contralesional anode. PO9h–PO10h ctDCS performed significantly (alpha = 0.05) better in facilitating successful functional reach (%) when compared to Exx7–Exx8 ctDCS. Furthermore, a linear relationship between successful functional reach (%) and electric field strength was found where PO9h–PO10h montage resulted in a significantly (alpha = 0.05) higher electric field strength when compared to Exx7–Exx8 montage for the same 2 mA current. Conclusion: We presented a rational neuroimaging based approach to optimize deep ctDCS of the dentate nuclei and lower limb representations in the cerebellum for post-stroke balance rehabilitation. However, this promising pilot study was limited by “one-size-fits-all” bipolar ctDCS montage as well as a small sample size.