Miracle-dz/UniFAR-FTUs huggingface dataset:
Serum Glial Fibrillary Acidic Protein and Cranial Computed Tomography in Neonates with Hypoxic Ischemic Encephalopathy

Hypoxic-ischemic encephalopathy (HIE) is a serious birth complication, while numerous potential biomarkers of the brain damage can exist but Glial Fibrillary Acidic Protein (GFAP) hold a significant promise in this group, as it is a key protein in astrocytes that its expression is induced by brain damage, CT show characteristic patterns of brain injury which correlate with the level of brain maturity at the time of an insult, therefore we can exclude other causes of encephalopathy in addition limiting the diagnosis to HIE. Assessment of serum GFAP in neonate with HIE and its relation to grading and to evaluate the role of cranial CT in diagnosis of HIE and its relation to GFAP finding. A case control study was carried out on 30 full term neonates with HIE classified according to Sarnat and Sarnat classification and 20 full term healthy neonates, selected from Rashid General Hospital in Alexandria, Egypt. Samples for GFAP were obtained at two-points time (0-6 & 48-72) hours postnatal in cases, and for control within hours from birth, Cranial Computed Tomography (CT) were obtained at the 4th day age for cases group. The laboratory tests are done in the Immunogenetics Lab, National Research Centre, Dokki, Giza, Egypt. In our study there was statistically significant serial increase in GFAP level in cases of HIE than control from birth to 48-72 hours age and positive correlation between its level and severity of the disease, 26.7% of cases of HIE had a picture of brain edema in cranial CT and this finding also correlated with the level of GFAP. There is serial increase in serum GFAP level from birth to 48-72 hours postnatal in HIE and that increase is correlated with its severity, also brain edema is the most common finding in cranial CT in these cases and it is correlated with the severity and GFAP level.
ffects of admission and treatment strategies of DWI courts on offender outcomes rank

Purpose: The purpose of this study is to classify DWI courts on the basis of the mix of difficult cases participating in the court (casemix severity) and the amount of involvement between the court and participant (service intensity). Using our classification typology, we assessed how casemix severity and service intensity are associated with program outcomes. We expected that holding other factors constant, greater service intensity would improve program outcomes while a relatively severe casemix would result in worse program outcomes. Methods: The study used data from 8 DWI courts, 7 from Michigan and 1 from North Carolina. Using a 2way classification system based on court casemix severity and program intensity, we selected participants in 1 of the courts, and alternatively 2 courts as reference groups. Reference group courts had relatively severe casemixes and high service intensity. We used propensity score matching to match participants in the other courts to participants in the reference group court programs. Program outcome measures were the probabilities of participants’: failing to complete the court’s program; increasing educational attainment; participants improving employment from time of program enrollment; and re-arrest. Results: For most outcomes, our main finding was that higher service intensity is associated with better outcomes for court participants, as anticipated, but a court’s casemix severity was unrelated to study outcomes. Conclusions: Our results imply that devoting more resources to increasing duration of treatment is productive in terms of better outcomes, irrespective of the mix of participants in the court’s program.
LOSSES COMPARISON FOR INVERTERS WITH Si AND SiC DEVICES FROM PUMPED STORAGE SYSTEMS

The pumped storage is a well-established technology, capable of enhancing the integration of renewable energy sources. The power electronics block is a key component of the pumped storage systems (PSS). It enables the control, and interfaces the PSS with the energy source. The technological progress in manufacturing power devices has led to the development of new devices based on wide band gap materials, such as silicon carbide (SiC). A comparison of the losses on the inverter that controls the PSS is realized in this paper, considering the new SiC and the classic silicon (Si) technology for the power devices in the inverter’s structure. The Simulation platform for Power Electronics Systems (Plecs) is used.
FRP in C + + and Its Application

Functional Reactive Programming (FRP) is a framework for constructing interactive applications in a declarative manner. FRP augments a host programming language to express time flow in a simple, semantically uniform manner. FRP has been demonstrated in domains such as animation, vision, robotics and other control systems. In this paper we present an implementation of the FRP programming style using C++ as a host language. There are two primary technical challenges: the implementation of signals in a manner faithful to the FRP semantic model and the use of the C++ type system, the template mechanism and operator overloading in particular, to achieve the same degree of type safety operator re-use that the Haskell type system provides. The resulting FRP implementation thus retains the essential “look and feel” of previous FRP implementations while also offering seamless interoperation with C++ code. We demonstrate FRP/C++ in a complete human-guided robot navigation system that integrates vision, control, and human-machine interfaces. This system shows that the highlevel semantic model expressed by FRP can be captured conveniently in C++ and provide the same declarative programming style found in the Haskell based implementations of FRP without compromising type safety.
The Transfer Dilemma

In this article we provide an overview of research on transfer, highlighting its main tenets. Then we look at interviews of two 5th-grade students learning about mathematical concepts regarding operations on positive and negative quantities. We attempt to focus on how their learning is influenced by their prior knowledge and experience. We take the position that transfer is a theory of learning and we attempt to show that it cannot provide a solid foundation for explaining such examples of learning.
Optimizing UDP for content delivery: GSO, pacing and zerocopy

UDP is a popular basis for the experimentation with and rapid deployment of new protocols. Experience shows a large gap in cycle efficiency compared to in-kernel TCP. This talk presents recent optimizations to the UDP stack that narrow this gap. At the core are optimizations long available to TCP: segmentation offload, pacing and zerocopy. We present the recently merged UDP GSO and SO_TXTIME interfaces and discuss select implementation details. We also review partial GSO as it fits in this context and discuss optimizations that are in submission: UDP zerocopy transmit with MSG_ZEROCOPY and UDP GRO.
HYDROPHILIC ORGANOSILICONE RUBBER: THE NEW ORGANIC-INORGANIC HYBRID CONSOLIDANT FOR ANCIENT EARTHEN ARCHITECTURES

Organic-inorganic hybrid material used as consolidant for earthen relics was synthesized by adding silica nano particles into polysiloxane with the presence of surfactant. This composite material is less hydrophobic than other polymer consolidant, which can avoid the preservation damage caused by the incompatibility between the hydrophobic consolidant and the hydrophilic soil. The tensile strength of the synthesized consolidant is close to other rubbers, which can relieve the stress between consolidant and soil within the expansion-shrinkage process when environmental conditions change. The product was applied on ancient Liangzhu city wall and its effectiveness was examined.
Application Level Resource Scheduling with Optimal Schedule Interval Filling ( RS-OSIF ) for Distributed Cloud Computing Environments

Application level resource scheduling in distributed cloud computing is a significant research objective that grabbed the attention of many researchers in recent literature. Minimal resource scheduling failures, robust task completion and fair resource usage are the critical factors of the resource scheduling strategies. Hence, this manuscript proposed a scalable resource-scheduling model for distributed cloud computing environments that aimed to achieve the scheduling metrics. The proposed model called "Application Level Resource Scheduling with Optimal Schedule Interval Filling (RS-OSIF)" schedules the resource to respective task such that the optimal utilization of resource idle time achieved. The proposed model performs the scheduling in hierarchical order and they are optimal idle resource allocation, if no individual resource is found to allocate then it allocates optimal multiple idle resources with considerable schedule intervals filling. This manuscript explores (i) requirement of resource scheduling strategies, (ii) recent scheduling models found in contemporary literature, (iii) methods and materials used and approach of the proposed resource scheduling strategy (iv)and its advantage over other benchmarking models. The performance analysis of the proposal done through cross validation of the metrics like load (window of tasks) versus loss (no of tasks failed to accomplish), task completion optimality and process overhead in resource scheduling. The experimental results evincing that the proposed model is scalable and robust under the adapted metrics.
A Comparative Analysis between Homodyne and Heterodyne Receiver Architecture

Two available choices for receiver architecture in wireless communications are Homodyne and Heterodyne receivers. Among them, heterodyne receiver was the leading choice in the past compared to homodyne receiver regarding facing challenges in suppressing interference and noise. However, Direct Conversion is becoming popular for wireless communications due to its lower cost. The goal of this paper is to discuss the key problems and tradeoffs in the design of Heterodyne and Homodyne receiver.
Semantic parsing with a domain ontology 領域オントロジーを用いた セマンティックパージング *

Using restricted domains in question answering (QA) allows to build an ontology of the domain that can be used with by a semantic parser to improve the performance of a QA system. However, building an ontology and a semantic parser can be costly and usually require a large amount of annotated data that may not be available for specific domains. Our work is a case study on how to build a semantic parser and a domain ontology with very low resource for the video game Minecraft. We show that the creation of a semantic parser and the ontology it is based on can be done with a very low amount of expert manual annotations, facilitated by the use of automatically collected data from the web, and that fairly good performance can be obtained. Thus, as a contribution, this case study is a first step in solving the common problem of building a QA system in a restricted domain from very low resource and low manual effort.
Analysis of dynamic radiation level changes using surface networks

The Fukushima nuclear accident reminds us of severe risk of radioactive substances. Citizen scientists voluntarily collect and share radiation data using geotagged sensors for radiation preparedness. However, radiation levels are affected by a number of factors including for example weather conditions, naturally occurring radioactive materials (NORM), and large marble structures. It is therefore difficult to determine whether a higher radiation level comes from a normal variation in background or not. This research analyzes the radiation changes using surface networks that can be used to characterize complex surfaces. A new algorithm has been developed to identify salient peaks and their hills by merging insignificant peaks recursively. Salient peaks and their hills are converted into graphs. The structural similarities of graphs were compared over time. The radiation measurements in the city of Koriyama, Japan were analyzed as a case study. The results demonstrated that structural analysis of dynamic radiation levels revealed stable changes, while numeric analysis of radiation levels presented statistically significant differences. This method is able to detect radiation level changes irrespective of background variations.
USING AN ECOSYSTEM MODELING APPROACH TO ASSESS THE MANAGEMENT OF A MEXICAN COASTAL LAGOON SYSTEM

The Huizache-Caimanero coastal lagoon system supports an economically important artisanal shrimp fishery and a less valuable finfish fishery. We analyze the response of the fisheries and the ecosystem to changes in fishing effort. To do this we use Ecosini-a dynamic version of Ecopath, which is a steady-state model emphasizing natural rates of growth and consumption of marine populations. We examine changes in each group's biomass and determine which fishing strategies optiniize yields on the basis of economic, social, and ecological criteria. We find that two of the four exploited fish groups, centroponiids and gerreids, are underutilized; the other two, ariids and mugilids, are near the maxinium sustainable yield. We find that the shrimp resource is overexploited. Our simulations suggest that the optimal management strategy occurs with a small increase in effort in the finfish fishery (1.24 times) combined with a sniall reduction of effort (0.8 times) in the shrimp fishery. This strategy enhances fishery yields of centropoinids and gerreids, thereby decreasing the biomass of finfish and resulting in fewer (lower biomass 00 shrimp predators. Simulations suggest that applying the optimal fishing strategy increases economic profits by ten percent. INTRODUCTION The shrimp resources of the Huizache-Caimanero lagoon systeni are important ecologically, economically, and socially. This lagoon complex is a nursery area for penaeid shrimp. The area has supported an important shrimp fishery since ancient times. Nearly 90% of the total shrimp catch in this lagoon is made up of one species, Litopenacus vannamei Boone 1931. Three other minor species of shrimp are also caught in the fishery: L. stylirostvis Stimpson 1874, Farfdntepenneus cal~fiirniewis Holmes 1900, and E brcvivostvis Kingsley 1878. Shrimp catches in the Huizache-Caimanero lagoon system reached 1,500 nietric tons in the 1980s (de la Lanza and Garcia-Calderbn 1991) and had one of the highest yields per unit area compared with other coastal lagoons (Edwards 1978), but catches have declined in the last decade. A finfish fishery in the area exploits four groups: centropomids, ariids, gerreids, and mugilids. On the basis of economic value and catch volume, however, the finfish fishery is less important than the shrimp fishery. An Ecopath mass balance model (Christensen and Pauly 1992) has been developed by Zetina-Rej6n (2000) using available information for the Huizache-Cainianero lagoon system. This model describes the trophic structure and energy flow among the major functional groups in the ecosystem. In this paper, we use the model to evaluate the status of the current fisheries and to explore optimization of fishing strategies based on ecological, economic, and social criteria. MATERIALS AND METHODS
Machine learning approaches for predicting diabetes and determining risk factors from epidemiological data Work presented in partial fulfillment of the requirements for the degree of Bachelor in Computer

The medical field has an urgent need for new analytical methods that are able to process complex and voluminous data, improving diagnostic tools and the knowledge regarding disease risk factors. In this sense, machine learning (ML) algorithms have become increasingly popular in the analysis of clinical and epidemiological data. The aim of this work is twofold. First, we carry out a systematic literature review (SLR) to investigate recent efforts towards the use of ML algorithms in the study of chronic diseases and summarize, in a comparative way, the performance of distinct methods for training prediction models and detecting risk factors. Second, based on the knowledge derived from the SLR, we apply a ML methodology to analyze data from an epidemiological study that investigated the impact of socioeconomic factors on the occurrence of chronic diseases, including diabetes. We apply multiple ML algorithms and assess their performance for training accurate prediction models and identifying important risk factors for the development of this disease. Our SLR results corroborate the notion that ML technology is growing exponentially in the medical research community, with several ML methods presenting promising results, which are extremely competitive in relation to traditional approaches such as clinical prediction scores derived by experts. Moreover, our experimental results with the diabetes dataset suggest that the Random Forest algorithm have the best predictive capability in the explored scenario, and that ML, in general, has great potential to elucidate new associations among socio-demographic variables and diabetes that may be useful for the development of new public health intervention programs to reduce the incidence of this disease.
1 EX / P 3-32 Results from the Sheared-Flow Stabilized Z-Pinch and Scaling to Fusion Conditions

The sheared-flow stabilized Z-pinch has been experimentally demonstrated to produce longlived plasmas that satisfy radial force balance and are stable for thousands of exponential growth times. The sheared-flow stabilized Z-pinch has the potential to lead to a compact plasma confinement device that scales to fusion conditions. The stabilizing effect of a sheared axial flow on the m = 1 kink instability in Z-pinches has been studied using ideal MHD theory to reveal that a sheared axial flow stabilizes the kink mode when the shear exceeds a threshold value. Following these theoretical results, the ZaP Flow Z-Pinch group at the University of Washington has been experimentally investigating the connection between flow shear and gross plasma stability. Plasma stability is diagnosed with azimuthal arrays of magnetic probes that measure the plasma’s magnetic structure. Large magnetic fluctuations occur during pinch assembly, after which the amplitude and frequency of the magnetic fluctuations diminish. This stable behavior continues for an extended quiescent period. Plasma flow profiles are measured from the Doppler shift of plasma impurity lines. The experimental flow shear exceeds the theoretical threshold during the quiescent period. Scaling relations suggest that high energy density plasma and fusion conditions are possible in a compact design. Recent experiments with the upgraded ZaP-HD device have demonstrated the ability to increase the plasma parameters by compressing the plasma radius to smaller values than achieved with the ZaP device. Plasma parameters of ne = 10 18 cm−3, Te = 200 eV, and Ba = 4 T have been experimentally achieved. Based on the successful results of ZaP and ZaP-HD, a new experiment FuZE is designed to scale the plasma parameters to fusion conditions. The project will focus on furthering our understanding of the physics with specific emphasis on the limitations of sheared flow stabilization and on the importance of kinetic effects at large drift speeds.
A CONTROL METHOD OF DISTRIBUTED GENERATORS IN SMART DISTRIBUTION SYSTEM CONSIDERING SYSTEM LOSS AND VOLTAGE

This paper proposes a control method of distributed generators (DGs) in a smart distribution system environment, where the active and reactive power output of DGs can be actively controlled by using the communication infrastructures. In the proposed method, the power output references of DGs are determined to minimize the system loss while maintaining the bus voltages within the limits. In order to solve this nonlinear optimization problem, the sequential linear programming (SLP) method is adopted. The linearized formulation of objective function and constraints are proposed and the sensitivity matrices are modified to be applicable for this problem. The step size adjustment and convergence test method are also briefly explained. The case studies demonstrate the effects of the proposed method. INTRODUCTION Recently, the characteristics of the distribution system, such as the system loss and voltage, have been changed due to the increased installation of distributed generators (DGs) [1]. The DG control method based on the local control system is utilized in the present distribution system, which is a passive and radial system. However, there is a chance to more effective operation of the distribution system using DGs according to the introduction of new distribution system called “smart distribution system”, which is an active and networked system [2]. The status of the distribution system can be measured and calculated more accurately in the smart distribution system. Moreover, the power output of DGs can be controlled using the communication infrastructures. In this paper, active and reactive power output control method for DGs in smart distribution system considering the system loss and voltage is proposed. The effects of the proposed method, i.e., operation cost reduction, stability improvement, and power quality enhancement, are proven by the case studies. DG CONTROL PROPLEM FORMULATION The control variables of the proposed method are active (PDG) and reactive power output (QDG) of DGs. The objectives of the proposed method are to minimize the system loss while maintaining the bus voltages within the limits. Therefore, with the proposed method, it is expected that the operational cost is reduced and the system stability is improved. This DG control problem can be formulated as an optimization problem as follows. Minimize ) , ( DGs DGs loss Q P P (1) Subject to ) , ( max n DG, min max m DG, min max l min
Modeling for the Control of the Laser Aided Manufacturing Process ( LAMP )

ABSTRACT Many state–of–the–art Rapid Prototyping (RP) technologies adopt lasers to fabricate 3–D solid parts by material deposition in layers. The ability of these RP technologies to control the process requires a thorough understanding of the process mechanics. This paper presents the analysis of an analytical, dynamic model explaining the complex phenomenon of Laser Aided Manufacturing Process (LAMP). The equilibrium of the dynamic model is analyzed and dynamic simulations are performed to determine its stability characteristics. This model forms the basis for the real–time control of the LAMP.
Towards IDEs for Physically Challenged Programmers

Programming is one of the activities that need talent and persistence. Physically challenged people avoid programming jobs and related academic degrees due to lack of tools that accommodate their disabilities. Most people think to program for the physically challenged. Our approach is different, we provide tools to make the physically challenged write computer programs in an easy and affordable way. In this paper, we introduce Proviac (Programming Via Voice) which is a software that helps physically challenged programmers to write their programs in a friendly way. Proviac currently supports C# but it could be extended to include other programming languages. Proviac can be considered a step towards providing IDEs tailored for physically challenged programmers.
The Design Thinking method and its stages

The paper presents the most important issues related to the concept of Design Thinking. The purpose of the publication was in particular to analyze the stages used in the implementation of Design Thinking in organizations. The article is focused on a detailed analysis of the five-step approach but also outlined a competitive seven-step approach to the problem. The publication also discusses Design Thinking relationships with innovation