Miracle-dz/UniFAR-FTUs huggingface dataset:
Assessing the Effect of Sequencing Depth and Sample Size in Population Genetics Inferences

Next-Generation Sequencing (NGS) technologies have dramatically revolutionised research in many fields of genetics. The ability to sequence many individuals from one or multiple populations at a genomic scale has greatly enhanced population genetics studies and made it a data-driven discipline. Recently, researchers have proposed statistical modelling to address genotyping uncertainty associated with NGS data. However, an ongoing debate is whether it is more beneficial to increase the number of sequenced individuals or the per-sample sequencing depth for estimating genetic variation. Through extensive simulations, I assessed the accuracy of estimating nucleotide diversity, detecting polymorphic sites, and predicting population structure under different experimental scenarios. Results show that the greatest accuracy for estimating population genetics parameters is achieved by employing a large sample size, despite single individuals being sequenced at low depth. Under some circumstances, the minimum sequencing depth for obtaining accurate estimates of allele frequencies and to identify polymorphic sites is , where both alleles are more likely to have been sequenced. On the other hand, inferences of population structure are more accurate at very large sample sizes, even with extremely low sequencing depth. This all points to the conclusion that under various experimental scenarios, in cost-limited population genetics studies, large sample sizes at low sequencing depth are desirable to achieve high accuracy. These findings will help researchers design their experimental set-ups and guide further investigation on the effect of protocol design for genetic research.
Analysis and Fabrication of Microfluidic Systems by Excimer Laser Micromachining and Its Applications for Microfluidic and Bio-Medical Devices.

KIM, EUI SEOK. Analysis and Fabrication of Microfluidic Systems by Excimer Laser Micromachining and Its Applications for Microfluidic and Bio-Medical Devices. (Under the direction of Yuan-Shin Lee and Roger J. Narayan.) This study primary focuses on identifying the relationship between laser micromachining parameters and the functionality of micro bio-device design. Micro biodevices such as Lab-on-a-chip (LOC) and microarrays are an emerging technology that recently attracts a lot of attention. For successful applications in the area, the fabrication methods and the system functionality should be addressed. Excimer laser machining is a good candidate to apply to the micro bio-devices manufacturing because different materials can be machined and the process can be easily controlled compared to other fabrication methods. In the thesis, a parametric study of laser micro machining on different materials are conducted: efforts were focused on identifying the relationship between the laser micromachining parameters and micro bio-device functionality. Experimental study and analytical modeling for the parametric study of excimer laser machining were performed to analyze the machined surface quality and the material removal rate of polyethylene, PMMA and silicon. Microfluidic experiments were carried out to verify liquid flow on laser machined microchannels. In this study, a novel geometrical model is presented to calculate a contact angle of liquid on the solid substrate to apply for micro bio-device manufacturing. The contact angle can be used to optimize designs of microarrays and microfluidic devices on development state. Based on a simplified geometry of a droplet, the wetting distance was derived as the function of liquid volume, a contact angle and material properties. To verify our method, the contact angles of a few materials were measured with goniometer, and the results were compared with the contact angle identified by our model. This method can be simplified the current method and the result can be used for design estimation of micro bio-device. Examples of the proposed technique were presented in the fabrication of inkwells for Dip-Pen Nanolithography (DPN) applications. This study verified that the channel fabricated by laser micromachining allows well-developed liquid flow through the microchannels. The presented methods can be used for laser micro/nano machining of micro bio-devices development and biomedical application. Analysis and Fabrication of Microfluidic Systems by Excimer Laser Micromachining and Its Applications for Microfluidic and Bio-Medical Devices
A Longitudinal Investigation of Willingness to Pay for Health Insurance in Germany

OBJECTIVE To investigate factors affecting willingness to pay (WTP) for health insurance of older adults in a longitudinal setting in Germany. DATA SOURCES Survey data from a cohort study in Saarland, Germany, from 2008-2010 and 2011-2014 (n1 = 3,124; n2 = 2,761) were used. STUDY DESIGN Panel data were taken at two points from an observational, prospective cohort study. DATA COLLECTION WTP estimates were derived using a contingent valuation method with a payment card. Participants provided data on sociodemographics, lifestyle factors, morbidity, and health care utilization. PRINCIPAL FINDINGS Fixed effects regression models showed higher individual health care costs to increase WTP, which in particular could be found for members of private health insurance. Changes in income and morbidity did not affect WTP among members of social health insurance, whereas these predictors affected WTP among members of private health insurance. CONCLUSIONS The fact that individual health care costs affected WTP positively might indicate that demanding (expensive) health care services raises the awareness of the benefits of health insurance. Thus, measures to increase WTP in old age should target at improving transparency of the value of health insurances at the moment when individual health care utilization and corresponding costs are still relatively low.
Visualising large-scale neural network models in real-time

As models of neural networks scale in concert with increasing computational performance, gaining insight into their operation becomes increasingly important. This paper proposes an efficient and generalised method to access simulation data via in-system aggregation, providing visualised representation at all layers of the network in real-time. Enabling neural networks for real-time visualisation allows a user to gain insight into the network dynamics of their systems as they operate over time. This visibility also permits users (or a computational agent) to determine whether early intervention is required to adjust parameters, or even to terminate operation of experimental networks that are not operating correctly. Conventionally the determination of correctness would occur post-simulation, so with sufficient `in-flight' insight, a significant advantage may be obtained, and compute time minimised. For this paper we apply the real-time visualisation platform to the SpiNNaker programmable neuromimetic system and a variety of neural network models. The visualisation platform is shown to be capable across a range of diverse simulations, and at supporting differing layers of network abstraction, requiring minimal configuration to represent each model. The resulting general-purpose visualisation platform for neural networks, is effective at presenting data to users in order to aid their comprehension of the network dynamics during operation, and scales from small to biologically-significant network sizes.
Multivariate Fine-Grained Complexity of Longest Common Subsequence

We revisit the classic combinatorial pattern matching problem of finding a longest common subsequence (LCS). For strings $x$ and $y$ of length $n$, a textbook algorithm solves LCS in time $O(n^2)$, but although much effort has been spent, no $O(n^{2-\varepsilon})$-time algorithm is known. Recent work indeed shows that such an algorithm would refute the Strong Exponential Time Hypothesis (SETH) [Abboud, Backurs, Vassilevska Williams + Bringmann, K\"unnemann FOCS'15]. Despite the quadratic-time barrier, for over 40 years an enduring scientific interest continued to produce fast algorithms for LCS and its variations. Particular attention was put into identifying and exploiting input parameters that yield strongly subquadratic time algorithms for special cases of interest, e.g., differential file comparison. This line of research was successfully pursued until 1990, at which time significant improvements came to a halt. In this paper, using the lens of fine-grained complexity, our goal is to (1) justify the lack of further improvements and (2) determine whether some special cases of LCS admit faster algorithms than currently known. To this end, we provide a systematic study of the multivariate complexity of LCS, taking into account all parameters previously discussed in the literature: the input size $n:=\max\{|x|,|y|\}$, the length of the shorter string $m:=\min\{|x|,|y|\}$, the length $L$ of an LCS of $x$ and $y$, the numbers of deletions $\delta := m-L$ and $\Delta := n-L$, the alphabet size, as well as the numbers of matching pairs $M$ and dominant pairs $d$. For any class of instances defined by fixing each parameter individually to a polynomial in terms of the input size, we prove a SETH-based lower bound matching one of three known algorithms. Specifically, we determine the optimal running time for LCS under SETH as $(n+\min\{d, \delta \Delta, \delta m\})^{1\pm o(1)}$. [. ]
A new formulation of model predictive direct torque control for a sensorless IM drive

This paper is concerned with developing an applicable model predictive direct torque control (MP DTC) for an induction motor (IM) drive. The novelty in this paper is viewed through regulating the reactive power (measured) instead of stator flux (estimated), which gives a more compact control structure. The robustness of the system is enhanced through a sensorless drive operation that is achieved by exploiting the predictive nature of proposed strategy. The paper is organized as follows; firstly, it introduces the theoretical analysis for the proposed control approach. Then the implementation steps are presented. For testing the dynamic performance of the IM drive, experimental tests are carried out by the help of fast control prototyping dSpace1104 board. Obtained results demonstrate the feasibility of the proposed control procedure, obtaining fast and precise dynamic response over the required speed range without involving switching tables similar to that used in classic DTC configurations.
Topological study of diverse hydrogen-bonded patterns found in a system of a nickel(II) complex and the sulfate anion.

A nickel(II) coordination complex, bis[2,6-bis(1H-benzimidazol-2-yl-κN3)pyridine-κN]nickel(II) sulfate, [Ni(C19H13N5)2]SO4 or [Ni(H2L)2]SO4, having four peripheral tetrahedrally oriented N-H donor units, combines with sulfate bridges to create hydrogen-bonded structures of varied dimensionality. The three crystal structures reported herein in the space groups P212121, I-4 and Pccn are defined solely by strong charge-assisted N-H.O hydrogen bonds and contain disordered guests (water and dimethylformamide) that vary in size, shape and degree of hydrophilicity. Two of the compounds are channelled solids with three-dimensional structures, while the third is one-dimensional in nature. In spite of their differences, all three present a striking resemblance to the previously reported anhydrous relative [Guo et al. (2011). Chin. J. Inorg. Chem. 27, 1517-1520], which is considered as the reference framework from which all three title compounds are derived. The hydrogen-bonded frameworks are described and compared using crystallographic and topological approaches.
Viability and neuronal differentiation of neural stem cells encapsulated in silk fibroin hydrogel functionalized with an IKVAV peptide

Three‐dimensional (3D) porous scaffolds combined with therapeutic stem cells play vital roles in tissue engineering. The adult brain has very limited regeneration ability after injuries such as trauma and stroke. In this study, injectable 3D silk fibroin‐based hydrogel scaffolds with encapsulated neural stem cells were developed, aiming at supporting brain regeneration. To improve the function of the hydrogel towards neural stem cells, silk fibroin was modified by an IKVAV peptide through covalent binding. Both unmodified and modified silk fibroin hydrogels were obtained, through sonication, with mechanical stiffness comparable to that of brain tissue. Human neural stem cells were encapsulated in both hydrogels and the effects of IKVAV peptide conjugation on cell viability and neural differentiation were assessed. The silk fibroin hydrogel modified by IKVAV peptide showed increased cell viability and an enhanced neuronal differentiation capability, which contributed to understanding the effects of IKVAV peptide on the behaviour of neural stem cells. For these reasons, IKVAV‐modified silk fibroin is a promising material for brain tissue engineering. Copyright © 2015 John Wiley & Sons, Ltd.
How important is diversity for capturing environmental-change responses in ecosystem models?

Marine ecosystem models used to investigate how global change affects ocean ecosystems and their functioning typically omit pelagic plankton diversity. Diversity, however, may affect functions such as primary production and their sensitivity to environmental changes. Here we use a global ocean ecosystem model that explicitly resolves phytoplankton diversity by defining subtypes within four phytoplankton functional types (PFTs). We investigate the model's ability to capture diversity effects on primary production under environmental change. An idealized scenario with a sudden reduction in vertical mixing causes diversity and primary-production changes that turn out to be largely independent of the number of coexisting phytoplankton subtypes. The way diversity is represented in the model provides a small number of niches with respect to nutrient use in accordance with the PFTs defined in the model. Increasing the number of phytoplankton subtypes increases the resolution within the niches. Diversity effects such as niche complementarity operate between, but not within PFTs, and are constrained by the variety of traits and trade-offs resolved in the model. The number and nature of the niches formulated in the model, for example via trade-offs or different PFTs, thus determines the diversity effects on ecosystem functioning captured in ocean ecosystem models.
HuR promotes the molecular signature and phenotype of activated microglia: Implications for amyotrophic lateral sclerosis and other neurodegenerative diseases

In neurodegenerative diseases such as amyotrophic lateral sclerosis (ALS), chronic activation of microglia contributes to disease progression. Activated microglia produce cytokines, chemokines, and other factors that normally serve to clear infection or damaged tissue either directly or through the recruitment of other immune cells. The molecular program driving this phenotype is classically linked to the transcription factor NF‐κB and characterized by the upregulation of proinflammatory factors such as IL‐1β, TNF‐α, and IL‐6. Here, we investigated the role of HuR, an RNA‐binding protein that regulates gene expression through posttranscriptional pathways, on the molecular and cellular phenotypes of activated microglia. We performed RNA sequencing of HuR‐silenced microglia and found significant attenuation of lipopolysaccharide‐induced IL‐1β and TNF‐α inflammatory pathways and other factors that promote microglial migration and invasion. RNA kinetics and luciferase reporter studies suggested that the attenuation was related to altered promoter activity rather than a change in RNA stability. HuR‐silenced microglia showed reduced migration, invasion, and chemotactic properties but maintained viability. MMP‐12, a target exquisitely sensitive to HuR knockdown, participates in the migration/invasion phenotype. HuR is abundantly detected in the cytoplasmic compartment of activated microglia from ALS spinal cords consistent with its increased activity. Microglia from ALS‐associated mutant SOD1 mice demonstrated higher migration/invasion properties which can be blocked with HuR inhibition. These findings underscore an important role for HuR in sculpting the molecular signature and phenotype of activated microglia, and as a possible therapeutic target in ALS and other neurodegenerative diseases.
Rules of engagement in mobile health: what does mobile health bring to research and theory?

Background: The effectiveness of mobile health (mHealth) is a controversial issue. For its wide-scale adoption and successful integration to the healthcare system, theoretical, methodological, and practical issues of mHealth should be well understood. Objectives: The purpose of the study was to review the essential characteristics of mHealth and discuss what mHealth presents to research and theory. Method: This review synthesized the studies focused on the adoption, design, and implementation of mHealth. The search strategy included reviewing electronic databases, key journals, web-based research and knowledge centers, and manual searching reference lists of the main studies. Results: mHealth's core characteristics were specified as accessibility, inclusivity, patient's autonomy, customizability, increasing the accuracy of diagnostics and treatment, improvement in service quality, and testability. Opportunities and challenges in regards to theory and research were discussed. Conclusions and implications: Using an integrated approach, this study identified and summarized the key issues to understand mHealth. Implications and recommendations for research and practice were provided.
How the Brain May Have Shaped Muscle Anatomy and Physiology: A Preliminary Study

Skeletal muscle fibers are often used to evaluate functional differences in locomotion. However, because there are energetic differences among muscle fiber cells, muscle fiber composition could be used to address evolutionary questions about energetics. Skeletal muscle is composed of two main types of fibers: Type I and II. The difference between the two can be reduced to how these muscle cells use oxygen and glucose. Type I fibers convert glucose to ATP using oxygen, while Type II fibers rely primarily on anaerobic metabolic processes. The expensive tissue hypothesis (ETH) proposes that the energetic demands imposed on the body by the brain result in a reduction in other expensive tissues (e.g., gastrointestinal tract). The original ETH dismisses the energetic demands of skeletal muscle, despite skeletal muscle being (1) an expensive tissue when active and (2) in direct competition for glucose with the brain. Based on these observations we hypothesize that larger brained primates will have relatively less muscle mass and a decrease in Type I fibers. As part of a larger study to test this hypothesis, we present data from 10 species of primates. We collected body mass, muscle mass, and biopsied four muscles from each specimen for histological procedures. We collected endocranial volumes from the literature. Using immunohistochemistry, a muscle fiber composition profile was created for each species sampled. Results show that larger brained primates have less muscle and fewer Type I fibers than primates with smaller brains. Results clarify the relationship between muscle mass and brain mass and illustrate how muscle mass could be used to address energetic questions. Anat Rec, 301:528–537, 2018. © 2018 Wiley Periodicals, Inc.
Weight Loss Through Living Well

Purpose To translate the Diabetes Prevention Program (DPP) lifestyle intervention into a clinical setting and evaluate its effectiveness. Methods The authors implemented a group-based version of the DPP lifestyle curriculum in a large academic medicine practice. It is delivered by a nurse educator over 12 weekly sessions with optional reenrollment, available on a self-pay basis, and implemented using existing clinical resources (eg, electronic medical record referrals, scheduling, conference rooms, communication technology). The program was evaluated using a controlled before-after design, including all patients referred between April 1, 2005, and February 1, 2007. Patients with a body mass index (BMI) ≥25 kg/m2 were eligible if their primary care providers felt the program was medically appropriate and safe. Change in weight (kg) and frequency of achieving ≥7% weight loss were examined. Results Referred patients were primarily female (84%), with an average age of 49.91 years (SE, 1.46) and average BMI of 39.65 kg/m2 (SE, 0.73). Among eligible patients, 93% of enrollees and 80% of nonenrollees had follow-up weights recorded within the evaluation window. Over 1 year, mean weight change was —5.19 kg (95% confidence interval [CI], —7.71 to —2.68) among enrollees and +0.21 kg (CI, —1.0 to 1.93) among nonenrollees (P < .001). A ≥7% loss was found for 27% of enrollees and 6% of nonenrollees ( P = .001). Conclusions An evidence-based lifestyle intervention can be effectively translated into the clinical setting. Use of existing resources may facilitate patient flow and minimize cost. This provider-integrated preventive care approach may provide a model for incorporating knowledge from behavioral science into clinical care.
Multiagent Architecture for Distributed Adaptive Scheduling of Reconfigurable Real-Time Tasks With Energy Harvesting Constraints

This paper presents new challenges for the real-time scheduling of distributed reconfigurable embedded systems powered by a renewable energy. Reconfigurable computing systems have to deal with unpredictable events from the environment, such as activation of new tasks and hardware or software failures, by adapting the task allocation and scheduling in order to maintain the system feasibility and performance. The proposed approach is based on an intelligent multiagent distributed architecture composed of: 1) a global agent “coordinator” associated with the whole distributed system and 2) four local agents, such as supervisor, scheduler, battery manager, and reconfiguration manager, belong to each subsystem. The efficiency and completeness of the reconfiguration adaptative strategy is proved as all possible reconfiguration forms are considered to guarantee a feasible system with a graceful quality of service. Two communication protocols, such as an intra-subsystem communication protocol and an inter-subsystem communication protocol, are proposed to ensure the effectiveness of the proposed reconfiguration strategy. Extensive simulations show the effectiveness of the proposed intelligent multiagent distributed architecture in terms of the number of exchanged messages, deadline success ratio, and the energy consumption.
Carboxylesterase Precursor (EST-1) Mediated the Fungicide Jinggangmycin-Suppressed Reproduction of Sogatella furcifera (Hemiptera: Delphacidae)

Abstract The jinggangmycin (JGM) is a widely used fungicide for controlling the rice sheath blight, Rhizoctonia solani, in China. Previous experiments under lab conditions showed that JGM foliar spray suppressed Sogatella furcifera (Horvath) reproduction. However, the molecular mechanisms of JGM-driven changes in S. furcifera reproduction are unclear. Therefore, we selected carboxylesterase precursor (EST-1) as a target gene for silencing by RNAi based on gene expression profiles. The present results demonstrated that JGM and control + dsSfEST-1 treatments significantly reduced the number of eggs laid (down by 58% and 54%, respectively), oviposition period (down by 57% and 38%, respectively), and longevity (down by 32% and 38%, respectively) in adult females compared with untreated controls, while no pronounced differences in the preoviposition period were observed. Meanwhile, the dietary control + dsSfEST-1 treatment also severely impeded protein synthesis, specifically soluble ovarian protein content (down by 20% and 24%, respectively) and soluble sugar content (down by 42% and 35%, respectively), which led to stunted growth and reduced body weight in adult females. We thereby speculate that downregulated SfEST-1 expression may be one molecular mechanism underlying JGM-driven reproduction in S. furcifera.