Miracle-dz/UniFAR-FTUs huggingface dataset:
Commentary: From global campaign to global commitment

The article titled “From global campaign to global commitment,” in this issue, describes faithfully two great events promoted during the last two decades by the International Bureau for Epilepsy (IBE), the International League Against Epilepsy (ILAE), some member states of the World Health Organization (WHO), and other civil organizations. These events were initiated by the Global Campaign against Epilepsy (GCAE) in 1996 and the WHA68.20 Resolution approved by the 68th World Health Assembly (WHA) in 2015. These two events are true milestones of great significance in promoting epilepsy control throughout the world, especially in lowand middle-income countries. We all know that epilepsy is a common serious neurologic disease, and also a widespread public health problem. This is because people with epilepsy (PWE) experience not only from the medical consequences of the disease, but also a heavy psychological and economic burden. This burden also affects the family, the community, and society as a whole. PWE can encounter major difficulties in education, employment, marriage, and reproduction, and in other aspects of social life. The core aim of the GCAE and of the WHA68.20 Resolution is precisely to emphasize these public health aspects of epilepsy. To promote prevention and control of epilepsy, we need coordinated actions at the national level to strengthen effective leadership and governance. These actions, as recommended by the WHA68.20 Resolution, should consider the specific needs of people with epilepsy; introduce and implement national health care plans for epilepsy; integrate epilepsy management into health and social care, particularly with respect to community-based services; support the establishment and implementation of strategies for the management of epilepsy, including access to safe, effective, and quality-assured antiepileptic medicines; promote public awareness and education about epilepsy; develop interventions to prevent the causes of epilepsy; improve investment into epilepsy research; and increase research capacity. To accomplish these actions, political commitments by governments are vitally important, as shown by previous successful GCAE projects in a number of lowand middle-income nations. The GCAE Demonstration Project in China, followed by an extensive “epilepsy prevention and control management project in rural area” in the same country (rural project), was one of the most successful interventions. From 2005 to China Association Against Epilepsy (CAAE), Xicheng District, Beijing, China Address correspondence to Dr. Li, Shichuo, Rm. 5102, Building 2, Beijing Exhibition Center Hotel, 135 Xizhimenwai Avenue, Xicheng District, Beijing, P.R. China, Post code 100044. E-mail: shichuoli@163.com
Interactions between soil structure and fungi

The spatial organisation of soils is crucially important in affecting belowground function, and the associated delivery of ecosystem services. Fungi constitute an important part of the soil biomass. As well as playing key roles in nutrient cycling and biotic interactions, they are also intimately involved in soil structural dynamics. Fungi mediate the formation of soil structure at a variety of spatial scales via charge, adhesive and enmeshment mechanisms. They also produce large quantities of hydrophobic compounds that affect water infiltration properties of soils. Fungi can also destroy soil structure via decomposition of organic matter that affects soil aggregation. In turn, soil structure affects fungi. The filamentous growth-form of fungi is a very efficient space-filling structure well adapted for life in a spatially heterogeneous environment such as soil, but the labyrinthine pore network ultimately regulates how fungal mycelia grow through and function within the soil. The distribution of water within soils plays a crucial role in governing fungal development and activity, as does the spatial distribution of nutrient resources. This article reviews the continual interplay that occurs between soil structure and fungi, and discusses how self-organisation mechanisms may operate in the soil system.
A requirements monitoring model for systems of systems

Many software systems today can be characterized as systems of systems (SoS) comprising interrelated and heterogeneous systems developed by diverse teams over many years. Due to their scale, complexity, and heterogeneity engineers face significant challenges when determining the compliance of SoS with their requirements. Requirements monitoring approaches are a viable solution for checking system properties at runtime. However, existing approaches do not adequately consider the characteristics of SoS: different types of requirements exist at different levels and across different systems; requirements are maintained by different stakeholders; and systems are implemented using diverse technologies. This paper describes a three-dimensional requirements monitoring model (RMM) for SoS providing the following contributions: (i) our approach allows modeling the monitoring scopes of requirements with respect to the SoS architecture; (ii) it employs event models to abstract from different technologies and systems to be monitored; and (iii) it supports instantiating the RMM at runtime depending on the actual SoS configuration. To evaluate the feasibility of our approach we created a RMM for a real-world SoS from the automation software domain. We evaluated the model by instantiating it using an existing monitoring framework and a simulator running parts of this SoS. The results indicate that the model is sufficiently expressive to support monitoring SoS requirements of a directed SoS. It further facilitates diagnosis by discovering violations of requirements across different levels and systems in realistic monitoring scenarios.
KDSNP: A kernel-based approach to detecting high-order SNP interactions

Despite the accumulation of quantitative trait loci (QTL) data in many complex human diseases, most of current approaches that have attempted to relate genotype to phenotype have achieved limited success, and genetic factors of many common diseases are yet remained to be elucidated. One of the reasons that makes this problem complex is the existence of single nucleotide polymorphism (SNP) interaction, or epistasis. Due to excessive amount of computation for searching the combinatorial space, existing approaches cannot fully incorporate high-order SNP interactions into their models, but limit themselves to detecting only lower-order SNP interactions. We present an empirical approach based on ridge regression with polynomial kernels and model selection technique for determining the true degree of epistasis among SNPs. Computer experiments in simulated data show the ability of the proposed method to correctly predict the number of interacting SNPs provided that the number of samples is large enough relative to the number of SNPs. For cases in which the number of the available samples is limited, we propose to perform sliding window approach to ensure sufficiently large sample/SNP ratio in each window. In computational experiments using heterogeneous stock mice data, our approach has successfully detected subregions that harbor known causal SNPs. Our analysis further suggests the existence of additional candidate causal SNPs interacting to each other in the neighborhood of the known causal gene. Software is available from https://github.com/HirotoSaigo/KDSNP .
Recent Advances and Evidence Gaps in Persistent Diarrhea

Department of Pediatrics and Child Health, the Aga Khan University and Hospital, Karachi, Pakistan, {Department of Paediatrics, the Chinese University of Hong Kong, Hong Kong Special Administrative Region, China, {Department of Paediatrics, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia, §Department of Pediatrics, Washington University School of Medicine, St Louis, MO, USA, Department of Gastroenterology, Hospital de Niños ‘‘Benjamin Bloom’’ San Salvador, El Salvador, Journal of Pediatric Gastroenterology and Nutrition 47:260–265 # 2008 by European Society for Pediatric Gastroenterology, Hepatology, and Nutrition and North American Society for Pediatric Gastroenterology, Hepatology, and Nutrition
Drosophila insulin release is triggered by adipose Stunted ligand to brain Methuselah receptor

Animals adapt their growth rate and body size to available nutrients by a general modulation of insulin–insulin-like growth factor signaling. In Drosophila, dietary amino acids promote the release in the hemolymph of brain insulin-like peptides (Dilps), which in turn activate systemic organ growth. Dilp secretion by insulin-producing cells involves a relay through unknown cytokines produced by fat cells. Here, we identify Methuselah (Mth) as a secretin-incretin receptor subfamily member required in the insulin-producing cells for proper nutrient coupling. We further show, using genetic and ex vivo organ culture experiments, that the Mth ligand Stunted (Sun) is a circulating insulinotropic peptide produced by fat cells. Therefore, Sun and Mth define a new cross-organ circuitry that modulates physiological insulin levels in response to nutrients.
Delayed attentional disengagement from sad face: A study of alpha rhythm by event-related desynchronization

This study investigated the influence of different emotional facial cues on the detection of subsequent visual digit targets presented after various cue-target intervals (CTIs). Behavioral results indicated that, compared to neutral faces, happy faces facilitated the response to subsequent tasks only after a short CTI (17 ms), while sad faces would slow or inhibit the processing of following tasks after different CTIs (17, 350, 1000, and 1500 ms). Event-related desynchronization of alpha rhythm (α-ERD) showed that the left frontal and parietal cortical areas were more prominently activated by emotional faces than by neutral ones. In particular, happy faces induced more activity in left frontal lobes, starting from the beginning of CTI (post-cue 0~400 ms), while sad faces induced stronger and longer activation during the middle of CTI (post-cue 400~800 ms). Such a later a-ERD in left frontal area suggested that the attentional disengagement was slowed by sad faces.
A follow‐up study of post partum illness, 1946‐1978

Abstract Eighty‐two patients, who were treated for post partum illness between 1946 and 1971, were identified and followed up. Diagnostically, the sample comprised unipolar depression (52%), bipolar disorder (18%), schizophrenia (16 %), abnormal personality with depression (8 %), organic disorder (2%), and obsessional state with depression and paranoid disorder (1% each). The overall prognosis was good, except for schizophrenia, in which more than 50 % of patients had chronic disability. Further childbirth intensified, and caused deterioration of, the underlying schizophrenia process. Following an initial illness in the puerperium, the probability of a recurrent affective illness was 43 % for unipolar and 66 % for bipolar disorder. The risk of developing another post partum illness varied from 1 in 3 to 1 in 5 pregnancies. Five percent of the sample ultimately committed suicide, and the probable incidence of infanticide was 4 %.
Live Migration of Stateful Processes across Edge Servers

Edge Computing facilitates low-latency for realtime applications. It can be achieved by installing computing infrastructure at the network edge or bringing cloud benefits closer to the user. In Edge Computing, computing resources are not more than one hop away from the user equipment. The mobility of a user in such a case can cause problems. If a user continues to move, maintaining low-latency becomes challenging. So, service is migrated between edge servers as the user moves. This migration can lead to a time duration for which the service is not available, called Downtime. While migrating, to leverage low- latency, Downtime must be kept to a minimum. In this paper, we introduced an approach to migrate service so that the minimum amount of data is transferred during Downtime. We have also discussed some existing techniques for migrating service and compared them based on how they reduce data to be transferred to lessen the Downtime. Our approach transfers lesser data that causes less Downtime than one of the existing techniques.
FORTY-FIVE Personalized Medicine and Nonmotor Symptoms in Parkinson ’ s Disease

Parkinson’s disease (PD) is a multineurotransmitter dysfunction related disorder resulting in a range of motor and nonmotor symptoms. Phenotypic heterogeneity is pronounced in PD and nonmotor symptoms dominant subtypes have been described. These endophenotypes may be underpinned by considerable nondopaminergic dysfunction; however, conventional treatment of PD continues to be mostly reliant on dopamine replacement strategy or manipulation of brain dopaminergic pathways. Consequently, treatment of many nondopaminergic nonmotor and some motor symptoms remains a key unmet need. It is also recognized that treatment strategies for PD are influenced by a number of nondrug-related issues. These include factors such as age, personality, and preferences for treatment, cultural beliefs, lifestyle, pharmacoeconomics, pharmacogenetics as well as comorbidity. Therefore, the success International Review of Neurobiology, Volume 134 # 2017 Elsevier Inc. ISSN 0074-7742 All rights reserved. http://dx.doi. org/10.1016/bs.irn. 2017.05. 015 1257 of clinical therapy will rest on how much these factors are considered to develop a truly holistic treatment plan. Personalized medicine is the modern way of delivering this holistic strategy for treatment of PD. Personalized medicine thus encompasses several strands of treatment. From the pharmaceutical point of view, it should involve dopaminergic and nondopaminergic strategies. In addition, there are substrategies involving precision and tailored medicine to suit the needs and requirements of individual patients. Precision medicine would be relevant for patients who may be at risk of developing the clinical syndrome of Parkinson’s as identified by specific gene mutations. Precision medicine in this scenario will attempt to be preventive. Tailored medicine would address the “single multifactorial” complex nature of PD and address symptoms as well subtype-specific strategies. Personalized medicine is now practiced for other conditions such as oncology as well as diabetes. In this chapter, we discuss the rationale and the need to develop strategies for personalized medicine for PD.
Some fundamental limits on frequency synchronization in massive MIMO

The effect of frequency offsets on the uplink sum-rate performance of massive MIMO systems is studied in the case of flat fading with pilot assisted estimation. Both collocated and distributed antenna architectures are studied to determine if there is a fundamental preference for collocated or distributed architectures from the perspective of frequency synchronization and its effect on the rate performance in a high mobility environment.
Towards Software Development For Social Robotics Systems

In this paper we introduce the core results of the project on software development for social robotics systems. The usability of maintenance and control features is crucial for many kinds of systems, but in the case of social robotics we also have to take into account that (1) the humanoid robot physically interacts with humans, (2) the conversation with children might have different requirements in comparison to the conversation with adults. The results of our work were implement for the humanoid PAL REEM robot, but their core ideas can be applied for other types of humanoid robots. We developed a web-based solution that supports the management of robot-guided tours, provides recommendations for the users as well as allows for a visual analysis of the data on previous tours.
Bolt : Uncovering and Reducing the Security Vulnerabilities of Shared Clouds

Cloud providers routinely schedule multiple applications per physical host to increase cost efficiency. The resulting interference in shared resources leads to performance degradation and, more importantly, security vulnerabilities. Interference can leak important information ranging from the placement of a service to confidential data, like private keys. We present Bolt, a practical system that accurately detects the type and characteristics of applications sharing a cloud platform, based on the interference an adversary sees on shared resources. Bolt leverages practical data mining techniques for detection that operate online and require 2-5 seconds. In a 40-server shared cluster, Bolt correctly detects 81% out of 108 diverse batch and interactive workloads. Extracting this information enables a wide spectrum of previouslyimpractical cloud attacks, including denial of service (DoS), resource freeing (RFA) and co-residency attacks. For example, Bolt can successfully launch difficult to detect, host-based DoS attacks, with only a fraction of the resources and time needed by a conventional distributed DoS that cause the tail latency of the victim to increase by up to 140x. Finally, we show that, while advanced isolation techniques, such as cache partitioning, lower detection accuracy, they are insufficient to eliminate these vulnerabilities. To do so, one must either disallow core sharing, or only allow it between threads of the same application, leading to significant inefficiencies and performance penalties respectively.
The activity of a tumor factor in Drosophila development.

1. The inductive activity of the tu-e tumor factor was first demonstrated at the 36th hour of tu-e development. No tumor factor was actively present at or after 144 hours of tu-e development. 2. Six donor age extracts induced tumor formation in eight of the wild 51–52 host age groups. One induced tumors in seven, while another donor age extract induced tumor formation (high incidences) in all host age groups. 3. Dilution and concentration experiments indicate that the variations in induced tumor incidences may be due in part to differences in tumor factor concentration. 4. The tumor factor was extracted from the wild 51–52 hosts after a specific period of time subsequent to the injection of the tu-e donor extracts. Incubation in the proper age hosts for specific periods increased the inductivity of the tumor factors.
A 10.3 Gb/s Burst-Mode CDR Using a ΔΣ DAC

A burst-mode clock and data recovery circuit (CDR) for 10 G-EPON systems is described. We propose a new architecture with a single gated voltage-controlled oscillator (GVCO), a digital frequency detector, and a ΔΣ digital-to-analog converter (DAC). The single GVCO and detector reduce frequency error to less than 2 MHz. The ΔΣ DAC eliminates external devices. Moreover, the simulation results show the DAC is more tolerant to process, voltage, and temperature (PVT) variations than a conventional charge pump. We fabricated a test CDR with this architecture using the 0.25 μm SiGe BiCMOS process. The measurement results show root-mean-square (rms) and total jitter of the recovered data of 2.4 and 14.7 ps, respectively, instantaneous locking in 1 bit, tolerance to a 160-bit sequence without transition in the data, and jitter tolerance of over 0.27 UIpp.
Advances in methods for estimating stopover duration for migratory species using capture-recapture data.

Many species are migratory, resulting in a life cycle divided into periodic stages occurring in different habitats occupied for a limited amount of time. Estimating the time spent in each habitat is crucial to understanding how individuals modulate their activities and thus to evolutionary ecology and conservation biology. Several methods, including some recent promising advances, can be used to estimate stopover duration as well as arrival and departure probabilities at sites where individuals are monitored using capture-recapture sampling. Our objectives in this study were to (1) describe the available models to estimate stopover duration, (2) illustrate with an original data set what kinds of questions can be addressed using the most recent methods, and (3) to provide in a detailed appendix a practical guide for implementing these methods in E-SURGE software. To illustrate the potential of these models for testing biological hypotheses, we used a capture-recapture data set on marbled newts (Triturus marmoratus). We used time-dependent and time-elapsed-since-arrival effects (using both Markovian and semi-Markov processes for the latter) to model stopover duration and the probability of arriving in and departing from a breeding pond for this species and compared the relative performance of the resulting models. Our findings showed a strong sex effect on stopover duration: females stayed on average 5.63 weeks in a breeding pond whereas males stayed only 3.03 weeks. In both sexes, the retention probability was mainly influenced by the time already spent there. Consequently, individuals of the same sex stayed a similar amount of time in a pond, although they did not arrive simultaneously but successively. The selected data set demonstrated the flexibility of these methods and their potential relevance for applications in evolutionary ecology and conservation.
Economic and Clinical Outcomes Resulting From the Stage 4 Chronic Kidney Disease Case Management Quality Improvement Initiative

Purpose of Study: Chronic kidney disease (CKD) is a costly and burdensome public health concern. The goal of this study was to evaluate the impact on outcomes and utilization of a pilot program to identify and engage beneficiaries with CKD at risk for progression from Stage 4 to Stage 5. Primary Practice Settings: A quality improvement initiative was conducted to assess the impact of case management on costs and outcomes among 7,720 Cigna commercial medical beneficiaries with Stage 4 CKD enrolled in the United States between January 2012 and October 2012. Methodology and Sample: Claims data were analyzed to compare 3,861 beneficiaries randomized to receive condition-focused case management with 3,859 controls, with follow-up through July 2013. After using an algorithm to identify beneficiaries at highest risk of progression, a case management team implemented, among those assigned to the intervention, an evidence-based assessment tool, provided education and follow-up, engaged nephrologists and other providers, and conducted weekly rounds. Primary outcome measures were hospital admissions, emergency department visits, nephrologist visits, dialysis, arteriovenous (AV) fistula creation, and total medical costs. Analysis of variance techniques were used to test group differences. Results: As compared with controls, intervention beneficiaries were 12% more likely to have fistula creation (p = .004). Intervention beneficiaries were observed to have savings of $199 per member per month (PMPM), F = 23.05, p = . 04. This difference equated to 6% lower total medical costs in the intervention group. Savings observed were derived half from improved in-network utilization and half from reduced hospital costs. Implications for Case Management Practice:The observed 12% increased rate of creation of AV fistulas and $199 (6%) decrease in PMPM cost between the intervention and control groups corresponded to a savings of more than $18 million in 2015 U.S. dollars (USD). On the basis of observation of substantial improvements in outcomes and cost savings, health plan administrators could better serve those at highest risk of progression by implementing focused case management.Our findings support the value of care coordination between nephrologists, providers, and health plan case managers in improving outcomes and reducing total medical costs among beneficiaries at risk for CKD progression from Stage 4 to Stage 5.