Miracle-dz/UniFAR-FTUs huggingface dataset:
Annexin II regulates multivesicular endosome biogenesis in the degradation pathway of animal cells

Proteins of the annexin family are believed to be involved in membrane‐related processes, but their precise functions remain unclear. Here, we have made use of several experimental approaches, including pathological conditions, RNA interference and in vitro transport assays, to study the function of annexin II in the endocytic pathway. We find that annexin II is required for the biogenesis of multivesicular transport intermediates destined for late endosomes, by regulating budding from early endosomes—but not the membrane invagination process. Hence, the protein appears to be a necessary component of the machinery controlling endosomal membrane dynamics and multivesicular endosome biogenesis. We also find that annexin II interacts with cholesterol and that its subcellular distribution is modulated by the subcellular distribution of cholesterol, including in cells from patients with the cholesterol‐storage disorder Niemann‐Pick C. We conclude that annexin II forms cholesterol‐containing platforms on early endosomal membranes, and that these platforms regulate the onset of the degradation pathway in animal cells.
Tidying and cleaning rooms using a daily assistive robot

This paper describes a system integration of daily assistive robots. Several tasks related to cleaning and tidying up rooms are focused on. Recognition and motion generation functions were integrated onto the robot, and these provided failure detection and in some cases, its recovery. Experiments of several daily tasks handling daily tools showed the effectiveness of our system.
Electrocardiographic abnormalities among dialysis naïve chronic kidney disease patients in Ilorin Nigeria.

BACKGROUND Chronic kidney disease (CKD) has an increased risk of not only end-stage renal disease (ESRD), but majority of moderate CKD patients do die from cardiovascular disease (CVD) before reaching ESRD. The prognosis of these patients is very poor in most developing countries because of late presentation, inadequate diagnostic facilities, and inability to pay for treatment. Knowledge about CVD in CKD is crucial because of unpredictable progressive nature of the disease and increased risk of premature death from cardiovascular events. We sought to determine prevalence and pattern of electrocardiographic abnormalities in dialysis naïve CKD patients. MATERIALS AND METHODS This is a 10-year prospective cross-sectional study carried out at the University of Ilorin Teaching Hospital, Ilorin. Patients were recruited from the nephrology clinic and renal wards and all who met diagnostic criteria for stages 4 and 5 CKD were included. All had their standard 12-lead electrocardiogram (ECG) recorded and various findings were critically studied and interpreted independently by two consultant physician including a cardiologist. Data analysis was done using SPSS version 16. RESULTS Overall, 86% of the patients had at least one form of ECG abnormality, with hypertension (HTN) and anemia being the main contributory factors. These include left ventricular hypertrophy (LVH) (27.6%), left atrial enlargement (LAE) (21.6%), combination of LVH and LAE (17.2%), and ventricular premature contractions (6%). Etiology of CKD appears to have influence on ECG changes as prevalence of LVH and LAE were high among hypertensive renal disease, chronic glomerulonephritis (CGN), and diabetic nephropathy patients. CONCLUSION LVH and LAE were very common ECG abnormalities in our dialysis naïve CKD patients. HTN, CGN, anemia, late presentation, and male gender appear to be the main risk factors for the ECG abnormalities. There is need for gender-specific intervention strategies directed at early detection and treatment of HTN, anemia, and underlying kidney disease, especially in resource poor nations where the burden of CKD is assuming epidemic proportion.
Assessment of budget sustainability in Sarawak

This study reexamines the sustainability of budget stance of Sarawak state, 1970-2008. Using the intertemporal borrowing constraint as a framework, the study tests the long-run relationship between government revenue and expenditure. Empirical results demonstrate a long-run equilibrium relationship among the variables. The cointegration test result suggests that Sarawak state’s fiscal stance satisfies the weak sustainability condition. In addition, the Granger causality test result reveals a bi-directional relationship between government revenue and expenditure. This means that fiscal authorities made simultaneous decisions on expenditure and revenue. Government revenue and expenditure will mutually reinforce each other.
Inadequate record keeping by dental practitioners.

BACKGROUND When a dental practitioner is brought before a disciplinary body, a common finding is that dental records were poorly kept and inadequate to establish issues of consent for treatment or the nature of the treatment undertaken. Often this finding may be incidental to the actual issue that brought the practitioner before a regulatory body or the Courts. The aim of this study was to examine recent cases reported in the State of Victoria involving dental practitioners, specifically seeking those cases where the record keeping was found to be inadequate as an incidental finding. METHODS Published rulings of formal complaints and notification cases brought before disciplinary hearings in the State of Victoria for the period January 2000 to June 2014 were analysed with regards to orders made in respect to record keeping. RESULTS Complaints and notifications specific to dental record keeping accounted for less than 2% of formal complaints. And yet up to 75% of cases have made a finding of unprofessional conduct against a dental practitioner on the basis of inadequate record keeping, most often in combination with other breaches of conduct. CONCLUSIONS Adherence to the traditional format of handwriting or typing entries into patient records may contribute to the problem of poor record keeping in a clinical dental setting. Newer technologies such as digital intraoral and extraoral photography and audio-recording of patient interactions may offer a solution to the problems of record keeping.
Type I seesaw mechanism as the common origin of neutrino mass, baryon asymmetry, and the electroweak scale

The type-I seesaw represents one of the most popular extensions of the Standard Model. Previous studies of this model have mostly focused on its ability to explain neutrino oscillations as well as on the generation of the baryon asymmetry via leptogenesis. Recently, it has been pointed out that the type-I seesaw can also account for the origin of the electroweak scale due to heavy-neutrino threshold corrections to the Higgs potential. In this paper, we show for the first time that all of these features of the type-I seesaw are compatible with each other. Integrating out a set of heavy Majorana neutrinos results in small masses for the Standard Model neutrinos; baryogenesis is accomplished by resonant leptogenesis; and the Higgs mass is entirely induced by heavy-neutrino one-loop diagrams, provided that the tree-level Higgs potential satisfies scale-invariant boundary conditions in the ultraviolet. The viable parameter space is characterized by a heavy-neutrino mass scale roughly in the range $10^{6.5\cdots7.0}$ GeV and a mass splitting among the nearly degenerate heavy-neutrino states up to a few TeV. Our findings have interesting implications for high-energy flavor models and low-energy neutrino observables. We conclude that the type-I seesaw sector might be the root cause behind the masses and cosmological abundances of all known particles. This statement might even extend to dark matter in the presence of a keV-scale sterile neutrino.
A 75dB image rejection IF-input quadrature sampling SC /spl Sigma//spl Delta/ modulator

Quadrature sampling of intermediate frequency (IF) signals is subject to the well-known problem of gain and phase mismatches between the in-phase (I) and quadrature (Q) paths of analog circuitry. This paper presents an IF-input quadrature-sampling switched-capacitor (SC) /spl Sigma//spl Delta/ modulator that circumvents the I/Q mismatch problem by time-sharing between the I and Q paths the critical components, namely, the sampling capacitors and the capacitors of the first-stage feedback digital-to-analog converter. Moreover, a clocking scheme insensitive to I/Q phase imbalance is used. A 3rd order lowpass single-loop 1-bit modulator has been designed and fabricated in a 0.35/spl mu/m CMOS process with an active area of 0.57mm/sup 2/. Experimental results show that the modulator achieves an image-rejection ratio (IRR) of greater than 75dB throughout a 100 kHz bandwidth.
Sub-Turing Islands in the Wild

Recently, there has been growing debate as to whether or not static analysis can be truly sound. In spite of this concern, research on techniques seeking to at least partially answer undecidable questions has a long history. However, little attention has been given to the more empirical question of how often an exact solution might be given to a question despite the question being, at least in theory, undecidable. This paper investigates this issue by exploring sub-Turing islands -- regions of code for which a question of interest is decidable. We define such islands and then consider how to identify them. We implemented Cook, a prototype for finding sub-Turing islands and applied it to a corpus of 1100 Android applications, containing over 2 million methods. Results reveal that 55\% of the all methods are sub-Turing. Our results also provide empirical, scientific evidence for the scalability of sub-Turing island identification. Sub-Turing identification has many downstream applications, because islands are so amenable to static analysis. We illustrate two downstream uses of the analysis. In the first, we found that over 37\% of the verification conditions associated with runtime exceptions fell within sub-Turing islands and thus are statically decidable. A second use of our analysis is during code review where it provides guidance to developers. The sub-Turing islands from our study turns out to contain significantly fewer bugs than `theswamp' (non sub-Turing methods). The greater bug density in the swamp is unsurprising; the fact that bugs remain prevalent in islands is, however, surprising: these are bugs whose repair can be fully automated.
On commuting billiards in higher-dimensional spaces of constant curvature

We consider two nested billiards in $\mathbb R^d$, $d\geq3$, with $C^2$-smooth strictly convex boundaries. We prove that if the corresponding actions by reflections on the space of oriented lines commute, then the billiards are confocal ellipsoids. This together with the previous analogous result of the author in two dimensions solves completely the Commuting Billiard Conjecture due to Sergei Tabachnikov. The main result is deduced from the classical theorem due to Marcel Berger saying that in higher dimensions only quadrics may have caustics. We also prove versions of Berger's theorem and the main result for billiards in spaces of constant curvature: space forms.
Accelerating Min-Max Optimization with Application to Minimal Bounding Sphere

We study the min-max optimization problem where each function contributing to the max operation is strongly-convex and smooth with bounded gradient in the search domain. By smoothing the max operator, we show the ability to achieve an arbitrarily small positive optimality gap of $\delta$ in $\tilde{O}(1/\sqrt{\delta})$ computational complexity (up to logarithmic factors) as opposed to the state-of-the-art strong-convexity computational requirement of $O(1/\delta)$. We apply this important result to the well-known minimal bounding sphere problem and demonstrate that we can achieve a $(1+\varepsilon)$-approximation of the minimal bounding sphere, i.e. identify an hypersphere enclosing a total of $n$ given points in the $d$ dimensional unbounded space $\mathbb{R}^d$ with a radius at most $(1+\varepsilon)$ times the actual minimal bounding sphere radius for an arbitrarily small positive $\varepsilon$, in $\tilde{O}(n d /\sqrt{\varepsilon})$ computational time as opposed to the state-of-the-art approach of core-set methodology, which needs $O(n d /\varepsilon)$ computational time.
Matrix Completion in the Unit Hypercube via Structured Matrix Factorization

Several complex tasks that arise in organizations can be simplified by mapping them into a matrix completion problem. In this paper, we address a key challenge faced by our company: predicting the efficiency of artists in rendering visual effects (VFX) in film shots. We tackle this challenge by using a two-fold approach: first, we transform this task into a constrained matrix completion problem with entries bounded in the unit interval [0,1]; second, we propose two novel matrix factorization models that leverage our knowledge of the VFX environment. Our first approach, expertise matrix factorization (EMF), is an interpretable method that structures the latent factors as weighted user-item interplay. The second one, survival matrix factorization (SMF), is instead a probabilistic model for the underlying process defining employees' efficiencies. We show the effectiveness of our proposed models by extensive numerical tests on our VFX dataset and two additional datasets with values that are also bounded in the [0,1] interval.
Ultimate Power of Inference Attacks: Privacy Risks of High-Dimensional Models

Models leak information about their training data. This enables attackers to infer sensitive information about their training sets, notably determine if a data sample was part of the model's training set. The existing works empirically show the possibility of these tracing (membership inference) attacks against complex models with a large number of parameters. However, the attack results are dependent on the specific training data, can be obtained only after the tedious process of training the model and performing the attack, and are missing any measure of the confidence and unused potential power of the attack. A model designer is interested in identifying which model structures leak more information, how adding new parameters to the model increases its privacy risk, and what is the gain of adding new data points to decrease the overall information leakage. The privacy analysis should also enable designing the most powerful inference attack. In this paper, we design a theoretical framework to analyze the maximum power of tracing attacks against high-dimensional models, with the focus on probabilistic graphical models. We provide a tight upper-bound on the power (true positive rate) of these attacks, with respect to their error (false positive rate). The bound, as it should be, is independent of the knowledge and algorithm of any specific attack, as well as the values of particular samples in the training set. It provides a measure of the potential leakage of a model given its structure, as a function of the structure complexity and the size of training set.
A Method to Assess the Economic Feasibility of New Commercial Services in the Smart Grid

As more commercial services are offered and provided on-line, tools to analyse their socio-economic impact are also needed. For instance, new services such as Spotify, Uber and AirBnB have been able to disrupt different sectors because they rely on combining new business models together with information and communication technology (ICT). For (traditional) enterprises, however, launching that kind of services is not always easy since they should consider, among other things, the economic impact of those services. Although tools and techniques based on Enterprise Architecture (EA) help during the design of new services by supporting a holistic process to model business and ICT perspectives, they often lack support to perform economic assessments. This paper presents a method to assess the economic feasibility of new services in the smart grid (SG) that combine business models and ICT. Using multilayer networks and the Smart Grid Architecture Model (SGAM), the method allows to calculate investment decision techniques such as net present value (NPV) and internal rate of return (IRR). Finally, we evaluate our method on two innovative services to locally trade renewable energy.
AdGraph: A Graph-Based Approach to Ad and Tracker Blocking

User demand for blocking advertising and tracking online is large and growing. Existing tools, both deployed and described in research, have proven useful, but lack either the completeness or robustness needed for a general solution. Existing detection approaches generally focus on only one aspect of advertising or tracking (e.g. URL patterns, code structure), making existing approaches susceptible to evasion.In this work we present AdGraph, a novel graph-based machine learning approach for detecting advertising and tracking resources on the web. AdGraph differs from existing approaches by building a graph representation of the HTML structure, network requests, and JavaScript behavior of a webpage, and using this unique representation to train a classifier for identifying advertising and tracking resources. Because AdGraph considers many aspects of the context a network request takes place in, it is less susceptible to the single-factor evasion techniques that flummox existing approaches.We evaluate AdGraph on the Alexa top-10K websites, and find that it is highly accurate, able to replicate the labels of human-generated filter lists with 95.33% accuracy, and can even identify many mistakes in filter lists. We implement AdGraph as a modification to Chromium. AdGraph adds only minor overhead to page loading and execution, and is actually faster than stock Chromium on 42% of websites and AdBlock Plus on 78% of websites. Overall, we conclude that AdGraph is both accurate enough and performant enough for online use, breaking comparable or fewer websites than popular filter list based approaches.
Changes in repeated-sprint performance in relation to change in locomotor profile in highly-trained young soccer players

Abstract The aim of this study was to examine the effects of changes in maximal aerobic (MAS) and sprinting (MSS) speeds and the anaerobic reserve (ASR) on repeated-sprint performance. Two hundred and seventy highly-trained soccer players (14.5 ± 1.6 year) completed three times per season (over 5 years) a maximal incremental running test to approach MAS, a 40-m sprint with 10-m splits to assess MSS and a repeated-sprint test (10 × 30-m sprints), where best (RSb) and mean (RSm) sprint times, and percentage of speed decrement (%Dec) were calculated. ASR was calculated as MSS-MAS. While ∆RSb were related to ∆MSS and ∆body mass (r2 = 0.42, 90%CL[0.34;0.49] for the overall multiple regression, n = 334), ∆RSm was also correlated with ∆MAS and ∆sum of 7 skinfolds (r2 = 0.43 [0.35;0.50], n = 334). There was a small and positive association between ∆%Dec and ∆MAS (r2 = 0.02 [−0.07;0.11], n = 334). Substantial ∆MSS and ∆MAS had a predictive value of 70 and 55% for ∆RSm, respectively. Finally, ∆ASR per se was not predictive of ∆RSm (Cohen’s = +0.8 to −0.3 with increased ASR), but the greater magnitude of ∆RSm improvement was observed when MSS, MAS and ASR increased together (0.8 vs. +0.4 with ASR increased vs. not, additionally to MSS and MAS). Low-cost field tests aimed at assessing maximal sprinting and aerobic speeds can be used to monitor ∆RS performance.
Basin‐scale, integrated observations of the early 21st century multiyear drought in southeast Australia

The Murray‐Darling Basin in southeast Australia is experiencing one of the most severe droughts observed recently in the world, driven by several years of rainfall deficits and record high temperatures. This paper provides new basin‐scale observations of the multiyear drought, integrated to a degree rarely achieved on such a large scale, to assess the response of water resources and the severity of the drought. A combination of Gravity Recovery and Climate Experiment (GRACE) data with in situ and modeled hydrological data shows the propagation of the water deficit through the hydrological cycle and the rise of different types of drought. Our observations show the rapid drying of soil moisture and surface water storages, which reached near‐stationary low levels only ∼2 years after the onset of the drought in 2001, with a loss of ∼80 and ∼12 km3 between January 2001 and January 2003, respectively. The multiyear drought has led to the almost complete drying of surface water resources which account for most of the water used for irrigation and domestic purposes. High correlation between observed groundwater variations and GRACE data substantiates the persistent reduction in groundwater storage, with groundwater levels still declining 6 years after the onset of the drought (groundwater loss of ∼104 km3 between 2001 and 2007). The hydrological drought continues even though the region returned to average annual rainfall during 2007.
Bacterial Community Profiling of Tropical Freshwaters in Bangladesh

Seasonal and spatial variations in the bacterial communities of two tropical freshwater sources in Bangladesh, Lake Dhanmondi in central Dhaka, and a pond in the outskirts of Dhaka, were assessed and compared using PCR-DGGE and deep sequencing of 16S rRNA genes, as well as heterotrophic enrichments using water samples collected at nine different time points during 1 year. Temporal and spatial variations of common aquatic bacterial genera were observed, but no clear seasonal variations could be depicted. The major bacterial genera identified from these two sites were members of the Proteobacteria, Cyanobacteria, Actinobacteria, Bacteroidetes, Chlorobi, Chloroflexi, Verrucomicrobia, and Firmicutes. Among the proteobacterial groups, members of the α-, β-, and γ- Proteobacteria predominated. γ- Proteobacteria belonging to the Escherichia coli/Shigella group even the diarrheagenic pathotypes of E. coli e.g., EPEC and ETEC were detected in most samples throughout the year, with no apparent correlations with other microbial groups. The other pathotypes, EHEC, EAEC, and EIEC/Shigella spp. were also detected occasionally. This study represents the first thorough analysis of the microbial diversity of tropical freshwater systems in Bangladesh.