Miracle-dz/UniFAR-FTUs huggingface dataset:
Federated Learning: Strategies for Improving Communication Efficiency

Federated Learning is a machine learning setting where the goal is to train a high-quality centralized model while training data remains distributed over a large number of clients each with unreliable and relatively slow network connections. We consider learning algorithms for this setting where on each round, each client independently computes an update to the current model based on its local data, and communicates this update to a central server, where the client-side updates are aggregated to compute a new global model. The typical clients in this setting are mobile phones, and communication efficiency is of the utmost importance. In this paper, we propose two ways to reduce the uplink communication costs: structured updates, where we directly learn an update from a restricted space parametrized using a smaller number of variables, e.g. either low-rank or a random mask; and sketched updates, where we learn a full model update and then compress it using a combination of quantization, random rotations, and subsampling before sending it to the server. Experiments on both convolutional and recurrent networks show that the proposed methods can reduce the communication cost by two orders of magnitude.
Some Aspects of the Spline Smoothing Approach to Non‐Parametric Regression Curve Fitting

Non-parametric regression using cubic splines is an attractive, flexible and widely-applicable approach to curve estimation. Although the basic idea was formulated many years ago, the method is not as widely known or adopted as perhaps it should be. The topics and examples discussed in this paper are intended to promote the understanding and extend the practicability of the spline smoothing methodology. Particular subjects covered include the basic principles of the method; the relation with moving average and other smoothing methods; the automatic choice of the amount of smoothing; and the use of residuals for diagnostic checking and model adaptation. The question of providing inference regions for curves-and for relevant properties of curves--is approached via a finite-dimensional Bayesian formulation.
Microbial Response to the MC-252 Oil and Corexit 9500 in the Gulf of Mexico

The Deepwater Horizon spill released over 4.1 million barrels of crude oil into the Gulf of Mexico. In an effort to mitigate large oil slicks, the dispersant Corexit 9500 was sprayed onto surface slicks and injected directly at the wellhead at water depth of 1,500 m. Several research groups were involved in investigating the fate of the MC-252 oil using newly advanced molecular tools to elucidate microbial interactions with oil, gases, and dispersant. Microbial community analysis by different research groups revealed that hydrocarbon degrading bacteria belonging to Oceanospirillales, Colwellia, Cycloclasticus, Rhodobacterales, Pseudoalteromonas, and methylotrophs were found enriched in the contaminated water column. Presented here is a comprehensive overview of the ecogenomics of microbial degradation of MC-252 oil and gases in the water column and shorelines. We also present some insight into the fate of the dispersant Corexit 9500 that was added to aid in oil dispersion process. Our results show the dispersant was not toxic to the indigenous microbes at concentrations added, and different bacterial species isolated in the aftermath of the spill were able to degrade the various components of Corexit 9500 that included hydrocarbons, glycols, and dioctyl sulfosuccinate.
Inherited Neuronal Ion Channelopathies: New Windows on Complex Neurological Diseases

Studies of genetic forms of epilepsy, chronic pain, and migraine caused by mutations in ion channels have given crucial insights into molecular mechanisms, pathogenesis, and therapeutic approaches to complex neurological disorders. Gain-of-function missense mutations in the brain type-I sodium channel NaV1.1 are a primary cause of generalized epilepsy with febrile seizures plus. Loss-of-function mutations in NaV1.1 channels cause severe myoclonic epilepsy of infancy, an intractable childhood epilepsy. Studies of a mouse model show that this disease is caused by selective loss of sodium current and excitability of GABAergic inhibitory interneurons, which leads to hyperexcitability, epilepsy, and ataxia. Mutations in the peripheral sodium channel NaV1.7 cause familial pain syndromes. Gain-of-function mutations cause erythromelalgia and paroxysmal extreme pain disorder as a result of hyperexcitability of sensory neurons, whereas loss-of-function mutations cause congenital indifference to pain because of attenuation of action potential firing. These experiments have defined correlations between genotype and phenotype in chronic pain diseases and focused attention on NaV1.7 as a therapeutic target. Familial hemiplegic migraine is caused by mutations in the calcium channel, CaV2.1, which conducts P/Q-type calcium currents that initiate neurotransmitter release. These mutations increase activation at negative membrane potentials and increase evoked neurotransmitter release at cortical glutamatergic synapses. Studies of a mouse genetic model show that these gain-of-function effects lead to cortical spreading depression, aura, and potentially migraine. Overall, these experiments indicate that imbalance in the activity of excitatory and inhibitory neurons is an important underlying cause of these diseases.
Emotion and decision making explained

What produces emotions? Why do we have emotions? How do we have emotions? Why do emotional states feel like something? What is the relation between emotion, and reward value, and subjective feelings of pleasure? How is the value of a good represented in the brain? Will neuroeconomics replace classical microeconomics? How does the brain implement decision-making? Are gene-defined rewards and emotions in the interests of the genes, and does rational multistep planning enable us to go beyond selfish genes to long-term plans and social contracts in the interests of the individual? This book seeks explanations of emotion and decision-making by considering these questions. The topics covered include: The nature of emotion, and a theory of emotion The functions of emotion, including a Darwinian theory of the adaptive value of emotion, which helps to illuminate many aspects of brain design and behaviour The brain mechanisms of emotion Affective states and motivated behaviour: hunger and sexual behaviour The pharmacology of emotion, and brain mechanisms for action Neuroeconomics, and the foundation of economic value Decision-making Emotional feelings, and consciousness Neural networks involved in emotion The book will be valuable for those in the fields of neuroscience and neurology, psychology, psychiatry, and philosophy
A New Algorithm for Finding Minimum-Weight Words in a Linear Code: Application to McEliece’s Cryptosystem and to Narrow-Sense BCH Codes of Length

— An algorithm for ﬁnding minimum-weight words in large linear codes is developed. It improves all previous attacks on the public-key cryptosystems based on codes and it notably points out some weaknesses in McEliece’s cipher. We also determine with it the minimum distance of some BCH codes of length 511 .
Long-Term Follow-Up of Proteinuria and Estimated Glomerular Filtration Rate in HIV-Infected Patients with Tubular Proteinuria

Objective The objective of this prospective observational study was to describe the evolution of tubular proteinuria detected in HIV-infected patients, and to evaluate the impact of tenofovir disoproxil fumarate (TDF) discontinuation. Methods Proteinuria and estimated glomerular filtration rate (eGFR) were followed during a median duration of 32 months, in 81 HIV-infected patients with tubular proteinuria and eGFR ≥ 60 ml/min/1.73 m2 (determined using the Chronic Kidney Disease Epidemiology (CKD-EPI) Collaboration equation). Tubular proteinuria was defined by urine protein to creatinine ratio (uPCR) ≥200 mg/g and albumin to protein ratio (uAPR) <0.4. Results Twenty per cent of patients had persistence of tubular proteinuria: TDF continuation was the main factor associated with this persistence [OR 9.0; 95%CI: 1.9–41.4; p = 0.01]. Among the 23 patients who discontinued TDF, uPCR returned below the threshold of 200 mg/g in 11 patients. Overall, eGFR decreased with a mean rate of decline of 3.8 ml/min/1.73m2/year. The decline in eGFR was lesser after discontinuation of TDF (5.8 ml/min/1.73m2/year during TDF exposure versus 3 ml/min/1.73m2/year after TDF discontinuation; p = 0.01). Conclusions The continuation of TDF was the main factor associated with the persistence of proteinuria. Moreover, proteinuria was normalized in only half of the patients who discontinued TDF. The clinical significance of TDF-related low level of proteinuria as a factor associated with renal disease progression and bone loss remains poorly understood.
Heritabilities and Genetic Correlations for Egg Weight Traits in Iranian Fowl by Multi Trait and Random Regression Models

Objective: The main objective of this research was estimation of genetic parameters for five consecutive measurements of egg weights in Isfahan fowl using multi trait model and random regression models. Methods: The statistical models included generation-hatch as a fixed effect, weeks of age as a covariate and additive genetic and individual permanent environmental effects as random effects. The date set included records of egg weight measured from 21 weeks to 84 weeks of age that collected during 15 generations from 1986 to 2011. For acquiring of best accuracy of variance components and determining appropriate model, used heterogeneous residual variances with 5 classes and considering different orders of Legendre polynomial and accordingly eight different models were compared. Finally, the model with fourth order for additive genetic effect and third order for individual permanent environmental effect was selected as best model. Results: Results showed high genetic correlations of the 32 weeks of age with all other ages also its heritability indicated that it could be the optimum period for breeding.
The genetic basis of seasonal affective disorder

Family and twin studies have shown a heritable component to seasonal affective disorder (SAD). While a few studies have examined individual genetic variants in SAD, many methodological issues exist in the current literature. First, most studies combined major depression (MDD) and bipolar (BD) cases in the genetic analysis of SAD. This makes it difficult to differentiate the effect from MDD and BD. Second, most studies adopted a candidate gene approach and used fairly small sample sizes. This does not allow for testing across a wide variety of genes, and it yields less robust P-values. Third, healthy controls have been used, but not case comparisons, which makes it difficult to differentiate the effects of seasonality from that of the primary illness (MDD and BD). To overcome these issues, seasonal MDD and BD cases were separated into two different studies in this thesis; sample sizes for both studies are the largest in the current SAD molecular genetics literature; GWAS was used to test for potential risk loci in a hypothesis-free fashion; case comparisons were incorporated to exclude potential genetic contributions related generally to the primary diseases themselves (MDD and BD). For MDD, we performed a GWAS with 562 seasonal MDD cases and 1,225 comparison cases with non-seasonal MDD. Subjects were drawn from two iterations of the Genetics of Recurrent Early Onset Depression (GenRED) study. Seasonal cases were those whose depressive episodes typically started in fall or winter. A mega-analysis of the two GWAS datasets was done using SNPTEST. We found that two single nucleotide polymorphisms (SNPs), rs149882931 and rs77073398, on chromosome 16p12.1 were associated with seasonal depression, at a genome-wide significant level (OR= 1.66, P= 3.59 x 10-8 and OR=1.62, 4.76 x 10-8, respectively). Since SAD is more prevalent in females, a female-specific analysis was carried out. The two variants were more significant in this analysis: P=2.18x10-9 (OR=1.89) and P=2.79x10-9 (OR=1.82), respectively, and a significant sex-by-SNP interaction was observed. These SNPs are
Strong winter monsoon wind causes surface cooling over India and China in the Late Miocene

Abstract. Modern Asian winter monsoon characterised by the strong northwesterly wind in East Asia and northeasterly wind in South Asia, has a great impact on the surface temperature of the Asian continent. Its outbreak can result in significant cooling of the monsoon region. However, it is still unclear whether such an impact existed and is detectable in the deep past. In this study, we use temperature reconstructions from plant and mammal fossil data together with climate model results to examine the co-evolution of surface temperature and winter monsoon in the Late Miocene (11–5 Ma), when a significant change of the Asian monsoon system occurred. We find that a stronger-than-present winter monsoon wind might have existed in the Late Miocene due to the lower Asian orography, particularly the northern Tibetan Plateau and the mountains north of it. This can lead to a pronounced cooling in southern China and northern India, which counteracts the generally warmer conditions in the Late Miocene compared to present. The Late Miocene strong winter monsoon was characterised by a marked westerly component and primarily caused by a pressure anomaly between the Tibetan Plateau and Northern Eurasia, rather than by the gradient between the Siberian High and the Aleutian Low. As a result, the close association of surface temperature with winter monsoon strength on inter-annual scale as observed at present may not have established in the Late Miocene.
Methodological approach for assessing the economic impact of forest fires using MODIS remote sensing images

Assessing areas affected by forest fires requires comprehensive studies covering a wide range of analyzes. From an economic standpoint, assessing the affected area in monetary terms is crucial. Determining the degree of loss in the value of natural resources, both those of a tangible and intangible nature, enables knowing the residual value remaining after a fire, i.e., it enables determining the “net change in the value of the resources. ” While the importance of economic analysis in the planning process for different post-fire rehabilitation actions is indisputable, determining the net change in the value of natural resources becomes complex when the size of the affected area makes gathering the information unfeasible, partly because of the costs involved in obtaining the information and partly because of the time that will elapse before the final assessment is available. Once the set of algorithms that allow the initial assessment and the corresponding depreciation of existing resources due to fire impact have been obtained, the assessment can be made immediately with the help of a geographic information system and the corresponding “fire impact depreciation matrix. ” The ability to incorporate satellite image processing into economic damage assessment allows identifying with greater precision the delimitation of the affected areas based on the “normalized vegetation index. ”Analysis and interpretation of MODIS images, combined with the energy intensity emitted by the spread of fire, can be integrated into econometric models in order to obtain, in a geo-referenced manner, the economic value per hectare resulting from wildfire damage. This paper details the methodology followed and the results obtained and validated in a series of wildfires that occurred in different geographic areas. 1 An abbreviated version of this paper was presented at the Fourth International Symposium on Fire Economics, Planning, and Policy: Climate Change and Wildfires; 5-11 November 2012, Mexico City, Mexico. 2 Professor and Director, Forest Fire Management Laboratory; Forestry Department. School of Agricultural Engineering and Forestry. University of Cordoba, Leonardo da Vinci Building. Rabanales Campus. 14071, Cordoba, Spain. E-mail: ir1rosif@uco.es. 2 Professor, Forest Fire Management Laboratory. Department of Forest Resources Management. Faculty of Forest Sciences. University of Chile. Santiago, Chile. GENERAL TECHNICAL REPORT PSW-GTR-245 282
Induced Sputum Is Safe and Well-Tolerated for TB Diagnosis in a Resource-Poor Primary Healthcare Setting

Improved tuberculosis (TB) diagnostics are required. Induced sputum sampling is superior to spontaneous sputum analysis for diagnosis of pulmonary TB. Therefore, we examined the applicability of induced sputum in primary health centers of the Peruvian TB program and studied the safety and tolerability of this procedure. We show that induced sputum is safe, inexpensive, and well-tolerated in a resource-limited environment. Widespread use of induced sputum at primary health centers can be implemented and may improve TB diagnosis.
A dynamical model for community detection in complex networks

One important feature observed in several complex networks is the structure of communities, or modular structure. Detecting communities is still a big challenge for researchers, specially the development of models to deal with dynamic networks. Here, we propose a new method for detecting communities by using a dynamical model. The first step consists of generating a spatial representation, named particle, for each vertex in the network. With these two representation, network structure and the spatial particles, we define the model's dynamics by means of two interactions types: the first is related to the network structure, or relational, and it is responsible for approaching particles representing neighbor vertices; the second, repulsive, is generated according to the spatial position of each particle and is responsible to make each unrelated particle, according to the network structure, to repel each other. Thus, after a couple of iteration, we observe the formation of groups of particles representing communities. On the other hand, distinct communities are separated according to the spatial positions of their particles. Simulation results show that our model achieves good results on the two benchmark models taken into account and that it can also deal with dynamic networks owing to its intrinsic dynamics.
Tobacco smoking and tuberculosis treatment outcomes: a prospective cohort study in Georgia

Abstract Objective To assess the effect of tobacco smoking on the outcome of tuberculosis treatment in Tbilisi, Georgia. Methods We conducted a prospective cohort study of adults with laboratory-confirmed tuberculosis from May 2011 to November 2013. History of tobacco smoking was collected using a standardized questionnaire adapted from the global adult tobacco survey. We considered tuberculosis therapy to have a poor outcome if participants defaulted, failed treatment or died. We used multivariable regressions to estimate the risk of a poor treatment outcome. Findings Of the 591 tuberculosis patients enrolled, 188 (31.8%) were past smokers and 271 (45.9%) were current smokers. Ninety (33.2%) of the current smokers and 24 (18.2%) of the participants who had never smoked had previously been treated for tuberculosis (P < 0.01). Treatment outcome data were available for 524 of the participants, of whom 128 (24.4%) – including 80 (32.9%) of the 243 current smokers and 21 (17.2%) of the 122 individuals who had never smoked – had a poor treatment outcome. Compared with those who had never smoked, current smokers had an increased risk of poor treatment outcome (adjusted relative risk, aRR: 1.70; 95% confidence interval, CI: 1.00–2.90). Those who had ceased smoking more than two months before enrolment did not have such an increased risk (aRR: 1.01; 95% CI: 0.51–1.99). Conclusion There is a high prevalence of smoking among patients with tuberculosis in Georgia and smoking increases the risk of a poor treatment outcome.
Can training improve eyewitness identification? The effect of internal feature focus on memory for faces

ABSTRACT Evidence suggests that individuals rely on external features such as hair and face shape when processing and recognising unfamiliar faces. This is problematic in a forensic setting because hairstyle can be changed easily. In two studies we examined whether training individuals to focus more on the stable, internal features of the face (e.g. eyes, nose and mouth) and hence less on the changeable external features would improve identification accuracy. In Study 1, participants were instructed to focus on: (1) internal features, (2) external features, or (3) both internal and external features. Participants’ eye movements were monitored while they studied target faces, which they later tried to identify from an array that included the target with a changed appearance. In Study 2, participants were instructed to focus on: (1) internal features, (2) external features, or (3) given no instructions. Participants were required to identify target faces from line-ups, where they were presented either unchanged or with an altered hairstyle. Results suggested that training individuals to attend to internal features of unfamiliar faces may improve identification accuracy in the common situation where external features have changed between presentation and identification. However, internal feature focus may decrease identification accuracy when external features are unchanged.
X-Chromosome Control of Genome-Scale Recombination Rates in House Mice

Sex differences in recombination are widespread in mammals, but the causes of this pattern are poorly understood. Previously, males from two interfertile subspecies of house mice, Mus musculus musculus and M. m. castaneus, were shown to exhibit a ∼30% difference in their global crossover frequencies. Much of this crossover rate divergence is explained by six autosomal loci and a large-effect locus on the X chromosome. Intriguingly, the allelic effects at this X-linked locus are transgressive, with the allele conferring increased crossover rate being transmitted by the low crossover rate M. m. castaneus parent. Despite the pronounced divergence between males, females from these subspecies exhibit similar crossover rates, raising the question of how recombination is genetically controlled in this sex. Here, I analyze publicly available genotype data from early generations of the Collaborative Cross, an eight-way panel of recombinant inbred strains, to estimate crossover frequencies in female mice with sex-chromosome genotypes of diverse subspecific origins. Consistent with the transgressive influence of the X chromosome in males, I show that females inheriting an M. m. castaneus X possess higher average crossover rates than females lacking the M. m. castaneus X chromosome. The differential inheritance of the X chromosome in males and females provides a simple genetic explanation for sex-limited evolution of this trait. Further, the presence of X-linked and autosomal crossover rate modifiers with antagonistic effects hints at an underlying genetic conflict fueled by selection for distinct crossover rate optima in males and females.
A novel empirical model for NBTI recovery with the modulated measurement time frame

Negative bias temperature instability (NBTI) of p-MOSFETs gets recovered immediately when the stress is removed, and hence the electrical measurement will tend to underestimate the NBTI degradation due to its unavoidable measurement time. This measurement-induced additional NBTI recovery must also be taken into account, especially during the NBTI recovery process, because it directly affects the time frames. In this work, by using different measurement time interval during the electrical characterization, this repeatable NBTI recovery phenomenon is used to extract the critical measurement time. Thereafter, with the modulated time interval, a novel empirical model for longer-time NBTI recovery is also proposed here so as to describe the entire NBTI recovery process together with previous short-time limited empirical model