Miracle-dz/UniFAR-FTUs huggingface dataset:
Bayesian Matrix Co-Factorization: Variational Algorithm and Cram´er-Rao Bound a

Matrix factorization is a popular method for collaborative prediction, where unknown ratings are predicted by user and item factor matrices which are determined to approximate a user-item matrix as their product. Bayesian matrix factorization is preferred over other methods for collaborative ﬁltering, since Bayesian approach alleviates overﬁtting, integrating out all model parameters using variational inference or sampling methods. However, Bayesian matrix factorization still suﬀers from the cold-start problem where predictions of ratings for new items or of new users’ preferences are required. In this paper we present Bayesian matrix co-factorization as an approach to exploiting side information such as content information and demographic user data, where multiple data matrices are jointly decomposed, i.e., each Bayesian decomposition is coupled by sharing some factor matrices. We derive variational inference algorithm for Bayesian matrix co-factorization. In addition, we compute Bayesian Cram´er-Rao bound in the case of Gaussian likelihood, showing that Bayesian matrix co-factorization indeed improves the reconstruction over Bayesian factorization of single data matrix. Numerical experiments demonstrate the useful behavior of Bayesian matrix co-factorization in the case of cold-start problems.
Adaptive Hyperparameter Selection for Differentially Private Gradient Descent

We present an adaptive mechanism for hyperparameter selection in differentially private optimization that addresses the inherent trade-off between utility and privacy. The mechanism eliminates the often unstructured and time-consuming manual effort of selecting hyperpa-rameters and avoids the additional privacy costs that hyperparameter selection otherwise incurs on top of that of the actual algorithm. We instantiate our mechanism for noisy gradient descent on non-convex, convex and strongly convex loss functions, respectively, to derive schedules for the noise variance and step size. These schedules account for the properties of the loss function and adapt to convergence metrics such as the gradient norm. When using these schedules, we show that noisy gradient descent converges at essentially the same rate as its noise-free counterpart. Numerical experiments show that the schedules consistently perform well across a range of datasets without manual tuning.
Erratum: Diffusion models and steady-state approximations for exponentially ergodic Markovian queues

Motivated by queues with many servers, we study Brownian steady-state approximations for continuous time Markov chains (CTMCs). Our approximations are based on diffusion models (rather than a diffusion limit) whose steady-state, we prove, approximates that of the Markov chain with notable precision. Strong approximations provide such “limitless” approximations for process dynamics. Our focus here is on steady-state distributions, and the diffusion model that we propose is tractable relative to strong approximations. Within an asymptotic framework, in which a scale parameter n is taken large, a uniform (in the scale parameter) Lyapunov condition imposed on the sequence of diffusion models guarantees that the gap between the steady-state moments of the diffusion and those of the properly centered and scaled CTMCs shrinks at a rate of n 12 − ϵ for any ϵ > 0 . Our proofs build on gradient estimates for solutions of the Poisson equations associated with the (sequence of) diffusion models and on elementary martingale arguments. As a by-product of our analysis, we explore connections between Lyapunov functions for the fluid Model, the Diffusion Model and the CTMC.
Administration of Linoleoylethanolamide Reduced Weight Gain, Dyslipidemia, and Inflammation Associated with High-Fat-Diet-Induced Obesity

Acylethanolamides (NAEs) are bioactive lipids derived from diet fatty acids that modulate important homeostatic functions, including appetite, fatty acid synthesis, mitochondrial respiration, inflammation, and nociception. Among the naturally circulating NAEs, the pharmacology of those derived from either arachidonic acid (Anandamide), oleic acid (OEA), and palmitic acid (PEA) have been extensively characterized in diet-induced obesity. For the present work, we extended those studies to linoleoylethanolamide (LEA), one of the most abundant NAEs found not only in plasma and body tissues but also in foods such as cereals. In our initial study, circulating concentrations of LEA were found to be elevated in overweight humans (body mass index (BMI, Kg/m2) > 25) recruited from a representative population from the south of Spain, together with AEA and the endocannabinoid 2-Arachidonoyl glycerol (2-AG). In this population, LEA concentrations correlated with the circulating levels of cholesterol and triglycerides. In order to gain insight into the pharmacology of LEA, we administered it for 14 days (10 mg/kg i.p. daily) to obese male Sprague Dawley rats receiving a cafeteria diet or a standard chow diet for 12 consecutive weeks. LEA treatment resulted in weight loss and a reduction in circulating triglycerides, cholesterol, and inflammatory markers such as Il-6 and Tnf-alpha. In addition, LEA reduced plasma transaminases and enhanced acetyl-CoA-oxidase (Acox) and Uncoupling protein-2 (Ucp2) expression in the liver of the HFD-fed animals. Although the liver steatosis induced by the HFD was not reversed by LEA, the overall data suggest that LEA contributes to the homeostatic signals set in place in response to diet-induced obesity, potentially contributing with OEA to improve lipid metabolism after high fat intake. The anti-inflammatory response associated with its administration suggests its potential for use as a nutrient supplement in non-alcoholic steatohepatitis.
Improved algorithms for finding fixed-degree isogenies between supersingular elliptic curves

Finding isogenies between supersingular elliptic curves is a natural algorithmic problem which is known to be equivalent to computing the curves’ endomorphism rings. When the isogeny is additionally required to have a specific known degree d , the problem appears to be somewhat different in nature, yet its hardness is also required in isogeny-based cryptography. Let E 1 , E 2 be supersingular elliptic curves over F p 2 . We present improved classical and quantum algorithms that compute an isogeny of degree d between E 1 and E 2 if it exists. Let d ≈ p 1 / 2+ ϵ for some ϵ > 0 . Our essentially memory-free algorithms have better time complexity than meet-in-the-middle algorithms, which require exponential memory storage, in the range 1 / 2 ≤ ϵ ≤ 3 / 4 on a classical computer. For quantum computers, we improve the time complexity in the range 0 < ϵ < 5 / 2 . Our strategy is to compute the endomorphism rings of both curves, compute the reduced norm form associated to Hom( E 1 , E 2 ) and try to represent the integer d as a solution of this form. We present multiple approaches to solving this problem which combine guessing certain variables exhaustively (or use Grover’s search in the quantum case) with methods for solving quadratic Diophantine equations such as Cornac-chia’s algorithm and multivariate variants of Coppersmith’s method. For the different approaches, we provide implementations and experimental results. A solution to the norm form can be then be efficiently translated to recover the sought-after isogeny using well-known techniques. As a consequence of our results we show that a recently introduced signature scheme from [3] does not reach NIST level I security.
Molecular Analysis of Microbial Communities in Endotracheal Molecular Analysis of Microbial Communities in Endotracheal Tube Biofilms Tube Biofilms

Background: Ventilator-associated pneumonia is the most prevalent acquired infection of patients on intensive care units and is associated with considerable morbidity and mortality. Evidence suggests that an improved understanding of the composition of the biofilm communities that form on endotracheal tubes may result in the development of improved preventative strategies for ventilator-associated pneumonia. Methodology/PrincipalFindings: The aim of this study was to characterise microbial biofilms on the inner luminal surface of extubated endotracheal tubes from ICU patients using PCR and molecular profiling. Twenty-four endotracheal tubes were obtained from twenty mechanically ventilated patients. Denaturing gradient gel electrophoresis (DGGE) profiling of 16S rRNA gene amplicons was used to assess the diversity of the bacterial population, together with species specific PCR of key marker oral microorganisms and a quantitative assessment of culturable aerobic bacteria. Analysis of culturable aerobic bacteria revealed a range of colonisation from no growth to 2.1 6 10 8 colony forming units (cfu)/cm 2 of endotracheal tube (mean 1.4 6 10 7 cfu/cm 2 ). PCR targeting of specific bacterial species detected the oral bacteria Streptococcus mutans (n=5) and Porphyromonas gingivalis (n=5). DGGE profiling of the endotracheal biofilms revealed complex banding patterns containing between 3 and 22 (mean 6) bands per tube, thus demonstrating the marked complexity of the constituent biofilms. Significant inter-patient diversity was evident. The number of DGGE bands detected was not related to total viable microbial counts or the duration of intubation. Conclusions/Significance: Molecular profiling using DGGE demonstrated considerable biofilm compositional complexity and inter-patient diversity and provides a rapid method for the further study of biofilm composition in longitudinal and interventional studies. The presence of oral microorganisms in endotracheal tube biofilms suggests that these may be important in biofilm development and may provide a therapeutic target for the prevention of ventilator-associated pneumonia.
Edinburgh Research Explorer Low cell number proteomic analysis using in-cell protease digests reveals a robust signature for cell cycle state classification

We introduce a streamlined sample processing method for bottom – up proteomics called the “ in-cell digest. ” Fixed cells are directly digested by trypsin to peptides for LC – MS/MS. Combined with AMPL, we analyze the proteomes of 16 unperturbed cell cycle populations using 2500 cells for each. We identify a 119-protein cell cycle signature. Using this signature, we show unbiased classi ﬁ cation of proteomes in proteomeHD into speci ﬁ c cell cycle phases. Precise cell cycle classi ﬁ cation will be important in dissecting single-cell proteome heterogeneity
Opleiding Informatica Ground State approximation with Product States using Graph Theory

Ground states of one-dimensional quantum systems can be approximated efficiently (i.e. in polynomial time) as product states. Finding the ground state efficiently can be mapped to a graph problem in which we find the k shortest paths. We present two methods to improve the run time of finding the k shortest paths for this specific application. In this application the problem instances are comprised of directed acyclic graphs (DAGs). The first method aims to improve the run time by slightly modifying the graph whilst maintaining the ability to perform general graph algorithms on it, with an expected quadratic speedup. The second method is the implementation of Eppstein’s algorithm, which has a better theoretical time complexity than the algorithms that have been used so far.
Evaluation of Water Quality Pollution Indices for part of Bokaro District, Jharkhand

Bokaro is a hub of mining, industries, wholesale trade and commerce. Due to rapid industrialization and mining activity many environmental problems like air pollution, subsidence, damage to the aquifer, accelerated soil erosion and destruction of soil structure are rising. Therefore, degrading both the ground water and surface water quality, on which most of the population is dependent for drinking and other domestic purpose. 20 groundwater samples were collected from different locations in Bokaro district, Jharkhand. The dug-wells samples were analysed for various physiochemical parameters and 6 heavy metals including Copper, Iron, Manganese, Lead, Cadmium and Zinc. The contamination levels of 20 locations were evaluated using Contamination Index (Cd) and Heavy Metal Pollution Index (HPI). The result shows that the major heavy metal pollutants exceeding Bureau of Indian Standards (BIS) permissible limits are Copper, Manganese and Iron at various locations. The study recommends proper treatment and maintenance for the affected sites.
Δ -coloring

We present a randomized distributed algorithm that computes a (cid:2) -coloring in any non-complete graph with maximum degree (cid:2) ≥ 4 in O ( log (cid:2)) + 2 O ( √ loglog n ) rounds, as well as a randomized algorithm that computes a (cid:2) -coloring in O (( log log n ) 2 ) rounds when (cid:2) ∈ [ 3 , O ( 1 ) ] . Both these algorithms improve on an O ( log 3 n / log (cid:2)) -round algorithm of Panconesi and Srinivasan (STOC’93), which has remained the state of the art for the past 25years. Moreover, the latter algorithm gets (exponentially) closer to an (cid:3)( log log n ) round lower bound of Brandt et al. (STOC’16).
Sensory cortical dynamics during optical microstimulation training

Primary sensory cortex is a key locus of plasticity during learning. Exposure to novel stimuli often alters cortical activity, but isolating cortex-specific dynamics is challenging due to extensive pre-cortical processing. Here, we employ optical microstimulation of pyramidal neurons in layer (L) 2/3 of mouse primary vibrissal somatosensory cortex (vS1) to study cortical dynamics as mice learn to discriminate microstimulation intensity. Tracking activity over weeks using two-photon calcium imaging, we observe a rapid sparsification of the photoresponsive population, with the most responsive neurons exhibiting the largest declines in responsiveness.
Study of Wetlands Landscape Pattern Dynamic Changes Based on 3S——Taking Yinchuan Plain as a Case

Based on the TM images of 1991 and ETM images of 2006,the wetlands types of study area was classified into nature wetland and artificial wetland,and the wetland landscapes of two periods was picked.The landcape pattern was analyzed based on the plot area and number,fragmentation index,diversity index,dominance index,and fractal dimension index.The result indicated that from 1991 to 2006,the plot area and number of the wetland decreased severely.The area of nature wetland was greater than artificial wetland,but the proportion of nature wetland was decreased and that of artificial wetland was increased.For the landscape pattern,the fragmentation and the dominance index were decreased,while the diversity and the fractal dimension were increased a little.
The overseas Taiwanese in Belize: An exploration of a south-south development project in a Belizean context

n In the tourism literature a lot of attention is paid to different approaches towards tourism development, especially when it comes to developing countries. Often it is argued that it is necessary to come to a sustainable approach, whereby it is stressed that attention should be paid to the way tourism organizations influence (and are influenced by) the natural environment as well as the cultural, and economical context in which they are situated. Although the debates on sustainable forms of tourism development are a positive direction for the tourism field, we will argue in this paper that these debates will not really contribute to the progress of the field as long as there is a lack of local accounts of actors in such tourism destinations. By presenting empirical data from Belize and the Dominican Republic, the aim is to move beyond the dominant ‘sus-tainability discourse’ in the field of tourism in which mass-tourism is per definition ‘bad’ and small-scale tourism is ‘good’, and gain an insight into what is actually going on at the micro level.
Effectiveness of ACI-318 and TS-500 Codes on Nonlinear Seismic Analysis of RC structures: Force-Based Approach

Different equations for the material properties of concrete are suggested in several national codes. The effectiveness of these equations on the nonlinear seismic analysis of RC structures for the material properties has been an important research subject. In this study, the effectiveness of ACI-318 and TS 500 design codes is investigated in the numerical modeling of RC structures. For this purpose, the seismic responses of two RC structures experimented in the laboratory are used. The first structure is a two-dimensional three-bay and four-story RC bare frame structure that was tested in European Laboratory for Structural Assessment. The second structure is an RC tall bridge pier that was tested at Pacific Earthquake Engineering Research Center. The numerical solutions are obtained by using the Force-based Fiber Element Approach. The experimental and numerical analysis results are compared in terms of top displacements and damage zones. The concrete material properties which provide the best approximation to the experimental results are investigated for both design codes. It is concluded that the material properties of RC structures determined according to the ACI-318 code can be used for the Force-based Fiber Element Approach with regard to displacement response and damage regions.
A DETAILED SUMMARY OF OPTIMIZATION ALGORITHMS FOR MOBILE-WSN

Mobile wireless sensor networks (MWSN) are a result of recent advancements in wireless telecommunications. The sensor nodes that make up these networks are mobile in addition to being inexpensive and having a short battery life. Numerous applications have been developed for these networks because of their inherent properties. Rescue efforts in the impacted areas, surveillance, and surveillance systems are all possible with it. Traffic signals are transmitted using it. Movable equipment that has energy limits and is energy-conserving is a considerable tool in its design. According to the needs of the aforementioned applications and taking into consideration the wireless sensor nodes. The MWSN allows the sensor nodes to move autonomously and communicate with one another, doing away with the need for centralised control. These networks can outperform static wireless sensor networks due to their longer network lifetime, reduced power consumption, more bandwidth availability, and better targeted capabilities. Given that the sensor nodes in MWSN are resource-constrained, low-cost mobile devices, the routing process is frequently challenging in mobile networks. Many
Inter-decadal climate variability in the Southern Hemisphere: evidence from Tasmanian tree rings over the past three millennia

EXTRACT (SEE PDF FOR FULL ABSTRACT): The characterization of inter-decadal climate variability in the Southern Hemisphere is severely constrained by the shortness of the instrumental climate records. To help relieve this constraint, we have developed and analyzed a reconstruction of warm-season (November-April) temperatures from Tasmanian tree rings that now extends back to 800 BC. A detailed analysis of this reconstruction in the time and frequency domains indicates that much of the inter-decadal variability is principally confined to four frequency bands with mean periods of 31, 57, 77, and 200 years. In so doing, we show how a future greenhouse warming signal over Tasmania could be masked by these natural oscillations unless they are taken into account.
Toward Standardization of Phanerozoic Stratigraphic Nomenclature in New Mexico

Nomenclature for Phanerozoic strata in New Mexico has been rapidly evolving, but not all proposed changes have been widely accepted. From a perspective of geologic mapping, we evaluate some recent nomenclatural proposals for Pennsylvanian, Permian, Triassic, Jurassic, and Paleogene units. Because of the long shelf-life of geologic quadrangle maps and the desirability of minimizing nomenclatural diversity among them, we present guidelines with which we argue for a conservative approach to changes in stratigraphic nomenclature.
Landmark Based Bronchoscope Localization for Needle Insertion Under Respiratory Deformation

Bronchoscopy is currently the least invasive method for definitively diagnosing lung cancer, which kills more people in the United States than any other form of cancer. Successfully diagnosing suspicious lung nodules requires accurate localization of the bronchoscope relative to a planned biopsy site in the airways. This task is challenging because the lung deforms intraoperatively due to respiratory motion, the airways lack photometric features, and the anatomy's appearance is repetitive. In this paper, we introduce a real-time camera-based method for accurately localizing a bronchoscope with respect to a planned needle insertion pose. Our approach uses deep learning and accounts for deformations and overcomes limitations of global pose estimation by estimating pose relative to anatomical landmarks. Specifically, our learned model considers airway bifurcations along the airway wall as landmarks because they are distinct geometric features that do not vary significantly with respiratory motion. We evaluate our method in a simulated dataset of lungs undergoing respiratory motion. The results show that our method generalizes across patients and localizes the bronchoscope with accuracy sufficient to access the smallest clinically-relevant nodules across all levels of respiratory deformation, even in challenging distal airways. Our method could enable physicians to perform more accurate biopsies and serve as a key building block toward accurate autonomous robotic bronchoscopy.
Opleiding Informatica &Economie Modelling Gentrification in Dutch Neighbourhoods: Investigating the Role of Neighbourhood Amenities

In a world characterised by rapid urbanisation and growing prosperity, gentrification has emerged as a well-known urban phenomenon affecting cities worldwide. Effectively handling gentrification relies heavily on the capacity of policymakers, planners and researchers to grasp its causes and consequences. This study aims to model gentrification in the Netherlands by using neighbourhood amenities. While gentrification has been extensively studied, limited attention has been given to the influence of amenities on gentrification, particularly through the implementation of machine learning and Explainable Artificial Intelligence (XAI). Investigating the significance of amenities on gentrification fills this research gap and could provide valuable insights for policymakers, planners and researchers. It is important to emphasise that this study operates within a correlation setting rather than a prediction setting, given the absence of a clear direction of causality between gentrification and amenities. Data from Statistics Netherlands covering three time intervals, namely 2013-2018, 2014-2019, and 2015-2020, was used to conduct research. The amenities (features) and the gentrification score (target variable) were derived from the data. Several regression machine learning models were trained, tested and evaluated. The top-performing model achieved an R-squared of 0.4825, an MAE of 0.0479 and an RMSE of 0.0660. Additionally, these results of a black-box model were extensively interpreted using an additive explanation tool. This study potentially opens up the doors to include a broader range of amenities considered and visualising gentrification patterns on the map of the Netherlands.