Miracle-dz/UniFAR-FTUs huggingface dataset:
Bounds on the capacity region of a class of compound interference channels

—We derive inner and outer bounds on the capacity region of a class of compound interference channels and quantify the gap between these bounds. From this we derive the capacity region of the compound version of El Gamal and Costa’s deterministic interference channel, and characterize to within 2 bits the capacity region of scalar compound Gaussian interference channels. One of our main contributions is a novel achievable scheme for compound interference channels.
Innovating in the Periphery: Firms, Values and Innovation in Southwest Norway

How do peripheral and relatively isolated regions innovate? Recent research has tended to stress the importance of agglomeration economies and geographical proximity as key motors of innovation. According to this research, large core areas have significant advantages with respect to peripheral areas in innovation potential. Yet, despite these trends, some remote areas of the periphery are remarkably innovative even in the absence of critical innovation masses. In this paper, we examine one such case—the region of southwest Norway—which has managed to remain innovative and dynamic, despite having a below average investment in R&D in the Norwegian context. The results of the paper highlight that innovation in southwest Norway does not stem from agglomeration and physical proximity, but from other types of proximity, such as cognitive and organizational proximity, rooted in soft institutional arrangements. This suggests that the formation of regional hubs with strong connections to international innovative networks may be a way to overcome peripherality in order to innovate.
Three essays on agent-based modelling and adaptation to climate change

The integrated environmental, economic and social analysis of climate change calls for a paradigm shift as it is fundamentally a problem of complex, bottom-up and multi-agent human behavior. There is a growing awareness that global environmental change dynamics and the related socio-economic implications involve a degree of complexity that requires an innovative modelling of combined social and ecological systems. Climate change policy can no longer be addressed separately from a broader context of adaptation and sustainability strategies. A vast body of literature on agent-based modelling (ABM) shows its potential to couple social and environmental models, to incorporate the influence of micro-level decision making in the system dynamics and to study the emergence of collective responses to policies. However, there are few publications which concretely apply this methodology to the study of climate change related issues. The analysis of the state of the art reported in this paper supports the idea that today ABM is an appropriate methodology for the bottom-up exploration of climate policies, especially because it can take into account adaptive behavior and heterogeneity of the system's components.
Are improved water supply and sanitation always safe for children? Implications for attaining the MDGs in the Philippines

In 2010, the Philippines appeared to be on track to attain by 2015 its target for Millennium Development Goals 4 (Reduce child mortality), but less so for Goal 7 (Ensure environmental sustainability). In pursuit of the latter, the government expands its provision of water and services to more households. Applying propensity score matching technique on the data from the four rounds of a nationwide survey, such interventions are found to reduce the incidence of child diarrhea, a persistent top cause of child mortality, though not always. The impact of improved sources of drinking water is 1.3% to 2.6% in 1993 and 2.9% to 4.6% in 2003, but none is found in 1998 and 2008. The impact of improved sanitation is 1.2% to 2.1% in 1993 and 3.1% to 4.7% in 2008; but none is found in 1998 and 2003. In addition to health interventions, the regular monitoring of the quality of water and sanitation at the household level is suggested to achieve Goal 4.
Evidence for the chaotic origin of Northern Annular Mode variability

Exponential spectra are found to characterize variability of the Northern Annular Mode (NAM) for periods less than 36 days. This corresponds to the observed rounding of the autocorrelation function at lags of a few days. The characteristic persistence timescales during winter and summer is found to be ∼5 days for these high frequencies. Beyond periods of 36 days the characteristic decorrelation timescale is ∼20 days during winter and ∼6 days in summer. We conclude that the NAM cannot be described by autoregressive models for high frequencies; the spectra are more consistent with low‐order chaos. We also propose that the NAM exhibits regime behaviour, however the nature of this has yet to be identified.
Development of the Precision Link Biobank at Boston Children’s Hospital: Challenges and Opportunities

Increasingly, biobanks are being developed to support organized collections of biological specimens and associated clinical information on broadly consented, diverse patient populations. We describe the implementation of a pediatric biobank, comprised of a fully-informed patient cohort linking specimens to phenotypic data derived from electronic health records (EHR). The Biobank was launched after multiple stakeholders’ input and implemented initially in a pilot phase before hospital-wide expansion in 2016. In-person informed consent is obtained from all participants enrolling in the Biobank and provides permission to: (1) access EHR data for research; (2) collect and use residual specimens produced as by-products of routine care; and (3) share de-identified data and specimens outside of the institution. Participants are recruited throughout the hospital, across diverse clinical settings. We have enrolled 4900 patients to date, and 41% of these have an associated blood sample for DNA processing. Current efforts are focused on aligning the Biobank with other ongoing research efforts at our institution and extending our electronic consenting system to support remote enrollment. A number of pediatric-specific challenges and opportunities is reviewed, including the need to re-consent patients when they reach 18 years of age, the ability to enroll family members accompanying patients and alignment with disease-specific research efforts at our institution and other pediatric centers to increase cohort sizes, particularly for rare diseases.
Averting the legacy of kidney disease - focus on childhood

World Kidney Day 2016 focuses on kidney disease in childhood and the antecedents of adult kidney disease that can begin in earliest childhood. Chronic kidney disease (CKD) in childhood differs from that in adults, in that the largest diagnostic group among children includes congenital anomalies and inherited disorders, with glomerulopathies and kidney disease as a consequence of diabetes being relatively uncommon. In addition, many children with acute kidney injury will ultimately develop sequelae that may lead to hypertension and CKD in later childhood or in adult life. Children born early or who are small-for-date newborns have relatively increased risk for the development of CKD later in life. Persons with a high-risk birth and early childhood history should be watched closely in order to help detect early signs of kidney disease in time to provide effective prevention or treatment. Successful therapy is feasible for advanced CKD in childhood; there is evidence that children fare better than adults, if they receive kidney replacement therapy including dialysis and transplantation, although only a minority of children may require this ultimate intervention. Because there are disparities in access to care, effort is needed so that children with kidney disease, wherever they live, may be treated effectively, irrespective of their geographic or economic circumstances. Our hope is that the World Kidney Day will inform the general public, policy makers and caregivers about the needs and possibilities surrounding kidney disease in childhood.
Permanent fore‐arc extension and seismic segmentation: Insights from the 2010 Maule earthquake, Chile

Geologists have long known that young normal faults are an important structural element of the Andean Coastal Cordillera, but their relationship to the subduction seismic cycle is still unclear. Some of the largest aftershocks of the 2010 Mw 8.8 Maule earthquake in central Chile were nucleated on upper plate normal faults, including the Mw 6.9 and 7.0 events of the Pichilemu earthquake sequence. We use the available coseismic GPS displacements, moment tensor sums, and slip distribution models for the Maule earthquake to compute the static strain and stress fields imposed on the upper plate by slip on the subduction interface. The extensional strains calculated from coseismic GPS and from a moment tensor sum of the Pichilemu events have similar orientations and orders of magnitude. The normal Coulomb stress increment (CSI) on the Pichilemu fault has maximum positive stresses as high as 4.9 MPa. Regionally, the Maule event produced a semi‐elliptical, radial pattern of static extension and deviatoric tension (CSI > 1.5 MPa) along the Coastal Cordillera enclosing the rupture area. This elliptical pattern mimics the trends of the major upper‐crustal structures. The static deformation field produced by a great subduction earthquake is an effective mechanism for generating permanent extension above the seismogenic zone, reactivating suitably oriented, long‐lived normal faults. We suggest that the semi‐elliptical outline of the first‐order structures along the Coastal Cordillera may define the location of a characteristic, long‐lived megathrust segment. This observation implies a persistence at least over the Quaternary of great subduction ruptures along the Maule segment.
Combination Therapy With Telaprevir for Chronic Hepatitis C Virus Genotype 1 Infection in Patients With HIV

BACKGROUND Telaprevir (TVR) plus peginterferon-α2a (PEG-IFN-α2a) and ribavirin substantially increases treatment efficacy for genotype 1 chronic hepatitis C virus (HCV) infection versus PEG-IFN-α2a-ribavirin alone. Its safety and efficacy in patients with HCV and HIV-1 are unknown. OBJECTIVE To assess the safety and efficacy of TVR plus PEG-IFN-α2a-ribavirin in patients with genotype 1 HCV and HIV-1 and to evaluate pharmacokinetics of TVR and antiretrovirals during coadministration. DESIGN Phase 2a, randomized, double-blind, placebo-controlled study. (ClinicalTrials.gov: NCT00983853). SETTING 16 international multicenter sites. PATIENTS 62 patients with HCV genotype 1 and HIV-1 who were HCV treatment-naive and receiving 0 or 1 of 2 antiretroviral regimens were randomly assigned to TVR plus PEG-IFN-α2a-ribavirin or placebo plus PEG-IFN-α2a-ribavirin for 12 weeks, plus 36 weeks of PEG-IFN-α2a-ribavirin. MEASUREMENTS HCV RNA concentrations. RESULTS Pruritus, headache, nausea, rash, and dizziness were higher with TVR plus PEG-IFN-α2a-ribavirin during the first 12 weeks. During this period, serious adverse events occurred in 5% (2 in 38) of those receiving TVR plus PEG-IFN-α2a-ribavirin and 0% (0 in 22) of those receiving placebo plus PEG-IFN-α2a-ribavirin; the same number in both groups discontinued treatment due to adverse events. Sustained virologic response occurred in 74% (28 in 38) of patients receiving TVR plus PEG-IFN-α2a-ribavirin and 45% (10 in 22) of patients receiving placebo plus PEG-IFN-α2a-ribavirin. Rapid HCV suppression was seen with TVR plus PEG-IFN-α2a-ribavirin (68% [26 in 38 patients] vs. 0% [0 in 22 patients] undetectable HCV RNA levels by week 4). Two patients had on-treatment HCV breakthrough with TVR-resistant variants. Patients treated with antiretroviral drugs had no HIV breakthroughs; antiretroviral exposure was not substantially modified by TVR. LIMITATION Small sample size and appreciable dropout rate. CONCLUSION In patients with HCV and HIV-1, more adverse events occurred with TVR versus placebo plus PEG-IFN-α2a-ribavirin; these were similar in nature and severity to those in patients with HCV treated with TVR. With or without concomitant antiretrovirals, sustained virologic response rates were higher in patients treated with TVR versus placebo plus PEG-IFN-α2a-ribavirin.
Valuing Air Quality Impacts of Transportation: A Review of Literature

The monetary valuation of air quality impacts of transportation is increasingly being adopted when undertaking cost-benefit analysis of projects or strategies aimed at reducing the negative effects of transport on the environment. This paper provides a review of the evidence available on the most appropriate methodologies to be used for such air quality impact valuations. The paper deals with the main issues in identifying and categorising air quality impacts; the methodologies adopted to quantify mortality and morbidity effects of air pollution on health; and the valuations put forward by studies in Europe, the US and in Australia. Unit monetised values by pollutant are summarised in the paper. The valuations for each pollutant currently being proposed for Australian conditions have been derived using in some cases European values corrected for local conditions. There is considerable uncertainty in some of the estimates to warrant further research. There is little research or evidence available on non-health impacts of air quality deterioration, such as local and regional economic activity and employment effects due to loss of tourism revenues.
HE4 immunostaining of malignant ascites differentiates cancer of Mullerian origin from gastrointestinal cancer

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Neural differential equations enable early-stage prediction of preterm birth using vaginal microbiota

Preterm births (PTBs), i.e., births before 37 weeks of gestation are completed, are one of the leading issues concerning infant health, and is a problem that plagues all parts of the world. Millions of infants are born preterm globally each year, resulting in developmental disorders in infants and increase in neonatal mortality. Although there are known risk factors for PTB, the current procedures used to assess PTB risk are effective only at the later stages of pregnancy, which reduces the impact of currently possible interventions administered to prevent PTB or mitigate its ill-effects. Vaginal microbial communities have recently garnered attention in the context of PTB, with the notion that a highly diverse microbiome is detrimental as far as PTB is concerned. Increased abundance or scarcity of certain microbial species belonging to specific genera has also been linked to PTB risk. Consequently, attempts have been made towards establishing a correlation between alpha-diversity indices associated with vaginal microbial communities, and PTB. However, the vaginal microbiome varies greatly from individual to individual, and this variation is more pronounced in racially, ethnically and geographically diverse populations, which diversity indices may not be able to overcome. Machine learning (ML)-based approaches have also previously been explored, however, the success of these approaches reported thus far has been limited. Additionally, microbial communities have been reported to evolve during the duration of the pregnancy, and capturing such a signature may require higher, more complex modeling paradigms. Thus, alternative approaches are necessary to identify signatures in these microbial communities that are capable of distinguishing PTB from a full-term pregnancy. In this study, we have highlighted the limitations of diversity indices for prediction of PTB in racially diverse cohorts. We applied Deep Learning (DL)-based methods to vaginal microbial abundance profiles obtained at various stages of pregnancy, and Neural Controlled Differential Equations (CDEs) are able to identify a signature in the temporally-evolving vaginal microbiome during trimester 2 and can predict incidences of PTB (mean test set ROC-AUC = 0.81, accuracy = 75%, F1-score = 0.71) significantly better than traditional ML classifiers such as Random Forests (mean test set ROC-AUC = 0.65, accuracy = 66%, F1-score = 0.42) and Decision Trees (mean test set ROC-AUC = 0.48, accuracy = 46%, F1-score = 0.40), thus enabling effective early-stage PTB risk assessment. Graphical Abstract
Long-read genome assembly of the Japanese parasitic wasp Copidosoma floridanum (Hymenoptera: Encyrtidae)

Copidosoma floridanum is a cosmopolitan species and an egg-larval parasitoid of the Plusiine moth. C. floridanum has a unique development mode called polyembryony, in which thousands of genetically identical embryos are produced from a single egg. Some embryos develop into sterile soldier larvae, and their developmental patterns differ between the US and Japanese C. floridanum strains. Genome sequencing can accelerate our understanding of the molecular bases underlying polyembryony, including the production of soldier castes. However, only the genome sequence of the US strain has been reported. In the present study, we determined the genome sequence of the Japanese strain using Pacific Biosciences high-fidelity reads and generating a highly contiguous assembly (552.7 Mb, N50: 17.9 Mb). Gene prediction and annotation identified 13,886 transcripts derived from 10,786 gene models. We searched the genomic differences between US and Japanese strains. Among gene models predicted in this study, 100 gene loci in the Japanese strain had extremely different gene structure from those in the US strain. This was accomplished through the functional annotation (GGSEARCH) and long-read sequencing. Genomic differences between strains were also reflected to amino acid sequences of vasa that plays a central role in caste determination in this species. The genome assemblies constructed in this study will facilitate the genomic comparisons between Japanese and US strains, leading to our understanding of detail genomic regions responsible for the ecological and physiological characters of C. floridanum.
Projected land‐cover change effects on East African rainfall under climate change

Both land‐cover/land‐use change (LCLUC) and greenhouse gas (GHG) concentrations have been shown to influence regional climate, albeit at different spatial scales. In East Africa, climate changes due to changing GHG concentrations are broadly projected to be warmer and wetter. LCLUC projections include trends towards both agricultural intensification and agricultural expansion into savannas, which may result in complex climate interactions and impacts. The primary objective of this study was to examine the regional responses to future GHG, LCLUC, and their combined effects in East Africa, and to better understand how hydrometeorological mechanisms might be altered by LCLUC in future scenarios. In this study, we present high‐resolution decadal simulations from a regional climate model that compare the relative and combined effects of projected LCLUC and GHG. This research suggests that taken separately, these two climate forcings may significantly alter regional precipitation patterns both temporally and spatially but in potentially different and independent ways. In combination, some portions of the region exhibit responses dominated by either LCLUC or GHG effects, but certain areas show complex effects resulting from the combined influence of these two forcings. Perhaps most importantly, the results suggest that projected precipitation changes around major population areas may be as strongly influenced by LCLUC as by GHG effects.
Magnesium Isotopes in the Earth, Moon, Mars, and Pallasite Parent Body: High-Precision Analysis of Olivine by Laser-Ablation Multi-Collector ICPMS

Magnesium isotopes potentially offer new insights into a diverse range of processes including evaporation and condensation in the solar nebula, melting and metasomatism in planetary interiors, and hydrothermal alteration [1,2,3,4]. Volatility-related Mg isotopic variations of up to 10 per mil/amu relative to a terrestrial standard have been found in early nebular phases interpreted as evaporation residues [1], and relatively large variations (up to 3 per mil/amu) in the terrestrial mantle have been reported recently [4]. In order to investigate possible differences in the nebular history of material contributing to the terrestrial planets, and to search for evidence of a high-temperature origin of the Moon, we have measured the magnesium isotopic composition of primitive olivines from the Earth, Moon, Mars, and pallasite parent body using laser-ablation multicollector ICPMS.
Geochemistry: Pathways and Processes

The fundamental principles and techniques of geological chemistry are presented in an introductory text for undergraduate students. Topics addressed include the scope and aims of geochemistry, thermodynamic equilibrium, techniques for solutions, the oceans and atmosphere as geochemical systems, kinetic factors in diagenesis, chemical weathering, the use of stable isotopes, temperature and pressure changes, phase diagrams, kinetics and crystallization, the crust and mantle as a geochemical system, using radioactive isotopes, and cosmochemistry. Diagrams, drawings, graphs, photographs, sample problems, and a glossary of terms are provided.
Enhancing In-Vehicle Network Security Through Bitstream Feature Extraction-Based Intrusion Detection

The in-vehicle network (IVN) is highly vulnerable due to its inherent structure, and the continuous introduction of new features in next-generation vehicles only exacerbates this issue. To address this problem, a proposed intrusion detection approach for in-vehicle networks is based on bitstream feature extraction and autocorrelation analysis. This approach aims to overcome the limitations associated with memory utilization and processing overhead vulnerability by comparing payload features using nibble. The Controller Area Network (CAN) data is highly susceptible, and organizations worldwide are working on developing Intrusion Detection Systems (IDSs) to protect vehicles. Nibbles are four-bit units of digital information, and autocorrelation measures the correlation of a variable with itself over time. In the proposed approach, the CAN payload is processed using nibble feature extraction and fed into a deep-learning CNN for attack classification. This approach presents a promising solution for enhancing the security of in-vehicle networks, by utilizing advanced machine-learning techniques to improve the security of vehicle systems.
Deep Learning Technique to Diagnose Depression in Audio

Depression is a prevalent psychiatric condition that has to be identified and treated right away. It may cause suicidal ideation in extreme instances. The requirement for creating an efficient audio-based automated depression identification system has recently piqued the fascination of researchers. The bulk of studies conducted so far incorporates a broad range of expertly created audio elements for a depression diagnosis. This expands feature space and causes a high-dimensionality problem which complicates pattern identification and increases the chance of data imbalance. This paper suggests a deep learning autoencoder-based method to retrieve pertinent and condensed features from speech signals in order to more precisely diagnose mental illness. The performance and efficacy of the suggested approach are evaluated on the DAIC-WoZ dataset and compared the results with other noteworthy machine learning algorithms. According to the findings, this technique works better than existing audio-based depression detection models when used with an SVM classifier resulting in an accuracy of 97% for diagnosing depression.