Miracle-dz/UniFAR-FTUs huggingface dataset:
Methodology for Estimating Landslides Susceptibility Using Artificial Neural Networks

In this study, the susceptibility to landslides at Sevilla township, Valle del Cauca, located at southwest of Colombia was evaluated. The conditioning factors that involve the generation of landslides were evaluated using Geographic Information Systems (GIS) and Remote Sensing (RS) techniques. For the estimating susceptibility, an Artificial Neural Network (ANN) was implemented by applying the “Backpropagation” method to extract the synoptic weights of the conditioning variables (slopes, flow length, curvature, geology, fracture density, and land cover) on an automatic way with a data training module. The data for the analysis of the conditioning factors were carried out through a Digital Elevation Model (DEM) obtained through Radar Interferometry techniques, with Sentinel-lB satellite images for the year 2018. The results showed that Sevilla’s township has areas with high susceptibility, high slopes, and that it’s crossed by an active geological fault which implies that the earth’s dynamics will condition the terrain stability.
Feasibility and Acceptability of Two Complementary and Alternative Therapies for Perceived Insufficient Milk in Mothers of Late Preterm and Early Term Infants.

Background: Complementary and alternative medicine (CAM) could be one option to address perceived insufficient milk (PIM), but there are few data comparing the effectiveness, acceptability, and safety of various CAM therapies. The purpose of this study was to describe and compare, among women delivering at 34-376/7 weeks, the feasibility and acceptability of two CAM interventions for treatment of PIM: (1) a meditation/relaxation intervention via an MP3 (Apple iPod Shuffle©) player and (2) a commercially available combination-blend herbal supplement (Motherlove: More Milk Plus Alcohol Free®). Materials and Methods: After randomization, over 9 days, women received three home visits from a lactation consultant, recorded pre/post intervention test weights and expressed milk volume, tracked daily breastfeeding behavior, and completed an end-of-study interview about the interventions. Women in each group were offered the other group's intervention on study day 9. Breastfeeding status and intervention continuation were assessed at 2 months. Results: Of 183 women screened, 11 were eligible, enrolled into, and completed the 9-day trial. Six women were randomized to the herbal supplement and 5 to meditation. One participant (meditation) stopped breastfeeding on study day 8. At 2 months, 3 of 6 women assigned to the herbal supplement and 3 of 5 women assigned to meditation were still breastfeeding; 1 (herbal supplement) was exclusively breastfeeding. Most participants were adherent to the prescribed protocols for both interventions. Interventions were generally perceived as safe, with benefits not necessarily related to increased milk supply. Conclusion: Mothers of late preterm and early term infants who had PIM found the CAM interventions acceptable and safe. The effect of CAM therapies on breastfeeding outcomes, with and without in-home lactation assistance, requires further investigation.
A Dynamic Resource Allocation Scheme in Vehicular Communications

A switched-beam based multiple-input-multiple output (MIMO) vehicle-to-infrastructure (V2I) system can grant better system reliability as the signal-to-interference-plus-noise ratio (SINR) can be significantly optimized. In order to maximize the number of served vehicles by the simple switched-beam based V2I system, it is crucial to additionally introduce vehicle-to-vehicle (V2V) communication because (i) more than one vehicle might occupy a beam coverage, and (ii) vehicles may be out of the coverage region of a beam. In this paper, we proposed a cooperative infrastructure-beam allocation (IBA) and location-estimation (LE) scheme to optimize system coverage and reliability. IBA is an SINR optimization algorithm, and LE is a location-based proximity service for V2I and V2V communications respectively. Our simulation results show that a reliable beam coverage region in switched-beam V2I can be achieved with flexible value of SINR threshold. Also, the outage probability and average rates are directly dependent on set SINR thresholds. Finally, cooperation between V2I and V2V communication significantly improves the utility ratio which is further used as a metric for reliability.
Peak Your Frequency: Advanced Search of 3D CAD Files in the Fourier Domain

An ever-increasing number of industries are adopting additive manufacturing (AM), also known as 3D printing, to their production lifecycles for manufacturing parts. A computer aided design (CAD) model is used to manufacture the part. The capability for efficient search and retrieval of the CAD models from the database has become an essential need for designers and users. However, traditional search techniques perform poorly in the context of searching CAD designs. In this paper, we propose Fourier Fingerprint Search (FFS), a retrieval framework for 3D models that deduces and leverages critical shape characteristics for search. FFS introduces a novel search methodology that incorporates these characteristics and uses two advanced matching techniques that operate at different granularities and take into account unique patterns associated with each design. In addition, FFS supports both exact and partial matching in order to provide helpful and robust search results for any scenario. We investigate a diverse set of features and enhancements for search that allows for high adaptability in all situations, such as dividing shapes into smaller parts, surface interpolation, and two different types of rotation. We evaluate FFS using the FabWave CAD dataset with approximately 3000 manufacturing models with different configurations. Our experimental results demonstrate the efficiency and high accuracy of our approach for both exact and partial matching, rendering FFS a powerful framework for CAD model search.
Excessive Production of Nitric Oxide by Macrophages From DP-BB Rats Is Secondary to the T-Lymphopenic State of These Animals

Activated macrophages are the first mononuclear cells to migrate to the pancreas of DP-BB rats at the initiation of insulitis. These cells produce an excess of NO, which has been implicated as a mediator of both (β-cell damage and inhibition of T-cell proliferation in this rat strain. Genetic studies have shown that the impaired proliferative response of T-cells segregates with one of the diabetes-susceptibility genes of the DP-BB rat, lyp, which is responsible for a peripheral T-lymphopenia. This observation suggests that the dysregulated expression of inducible NO synthase (iNOS) is under the control of lyp itself or a gene in linkage disequilibrium with lyp. Using two models of hemopoietic chimeras—DP-BB rats reconstituted with isocongenic Tcells and irradiated (WF × DP-BB)F1 animals reconstituted with bone marrow of both parental strains—we demonstrated that the production of NO by DP-BB macrophages is normal when these cells originate from a non–T-lymphopenic environment. Consequently, these macrophages no longer inhibit the stimulation of DNA synthesis in activated T-cells. Macrophages of young WF rats were found to produce high levels of NO, which inhibited T-cell proliferation in vitro. This observation strongly suggests that upregulation of NO synthesis in DP-BB macrophages represents the abnormal persistence of a phenomenon restricted to the first few weeks of life in non-diabetes-prone rats. Taken together, these results demonstrate that the elevated production of NO by DP-BB macrophages results from the lyp mutation and represents a crucial mechanism through which T-lymphopenia contributes to the development of diabetes.
Is Deception Emotional? An Emotion-Driven Predictive Approach

In this paper, we propose a method for automatically detecting deceptive speech by relying on predicted scores derived from emotion dimensions such as arousal, valence, regulation, and emotion categories. The scores are derived from task-dependent models trained on the GEMEP emotional speech database. Inputs from the INTERSPEECH 2016 Computational Paralinguistics Deception sub-challenge are processed to obtain predictions of emotion attributes and associated scores that are then used as features in detecting deception. We show that using the new emotion-related features, it is possible to improve upon the challenge baseline.
Decentralized and Distributed Machine Learning Model Training with Actors

Training a machine learning model with terabytes to petabytes of data using very deep neural networks doesn’t scale well within a single machine. A significant amount of work in recent years has gone into distributing the training of such neural networks across a cluster of machines, by partitioning on both the data and the model itself. The most well-established form of distributed training uses a centralized parameter server to manage the shared state of neural network weights used across all partitions of the data, but this introduces a bottleneck and single-point of failure during training. In this paper, we explore a more experimental form of decentralized training that removes this bottleneck. Finally, we show that by taking advantage of sparse updates to the shared parameter matrix, decentralized training can be tuned to make tradeoffs between training speed and model accuracy.
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One morning in April, we each directed our browsers to Amazon.com's website. Not only did the site greet us by name, the home page opened with a host of suggested purchases. It directed Joe to Barry Greenstein's Ace on the River: An Advanced Poker Guide, Jonah Lehrer's Imagine: How Creativity Works, and Michael Lewis's Boomerang: Travels in the New Third World. For John it selected Dave Barry's Only Travel Guide You'll Ever Need, the spy novel Mission to Paris, by Alan Furst, and the banking exposé The Big Short: Inside the Doomsday Machine, also by Michael Lewis. By now, online shoppers are accustomed to getting these personalized suggestions. Netflix suggests videos to watch. TiVo records programs on its own, just in case we're interested. And Pandora builds personalized music streams by predicting what we'll want to listen to.
REMD Simulations Reveal the Dynamic Profile and Mechanism of Action of Deleterious, Rescuing, and Stabilizing Perturbations to NBD1 from CFTR

Cystic Fibrosis (CF) is a lethal, genetic disease caused by mutations to the CFTR chloride channel. The most common CF causing mutation is the deletion of F508 from the first Nucleotide Binding Domain (F508del-NBD1). This mutation leads to a thermally unstable domain and a misfolded, nonfunctioning CFTR. Replica Exchange MD simulations were used to simulate seven NBD1 constructs including wt and F508del-NBD1 both alone and in the presence of known rescuing mutations as well as F508del-NBD1 in complex with a known small (ligand) stabilizer. Analyzing the resulting trajectories suggests that differences in the biochemical properties of the constructs result from local and coupled differences in their dynamic profiles. A comparative analysis of these profiles as well as of the resulting trajectories reveals how the different perturbations exert their deleterious, rescuing, and stabilizing effects on NBD1. These simulations may therefore be useful for the design and mechanism-of-action analysis of new NBD1 stabilizers.
Characterization of Helicobacter pylori dapE and construction of a conditionally lethal dapE mutant

Helicobacter pylori colonizes the human gastric mucosa and causes gastritis, ulceration, or gastric cancer. A previously uncharacterized region of the H. pylori genome was identified and sequenced. This region includes a putative operon containing three open reading frames termed gidA (1,866 bp), dapE (1,167 bp), and orf2 (753 bp); the gidA and dapE products are highly homologous to other bacterial proteins. In E. coli, dapE encodes N-succinyl-L-diaminopimelic acid desuccinylase, which catalyzes the hydrolysis of N-succinyl-L-diaminopimelic acid to L-diaminopimelic acid (L-DAP) and succinate. When wild-type H. pylori strains were transformed to select for dapE mutagenesis, mutants were present when plates were supplemented with DAP but not with lysine; orf2 mutants were selected without DAP supplementation. Consistent with the finding that GidA is essential in Escherichia coli, we were unable to obtain a gidA mutant in H. pylori despite evidence that insertional mutagenesis had occurred. The positions of gidA, dapE, and orf2 suggest that they form an operon, which was supported by slot blot RNA hybridization and reverse transcriptase PCR studies. The data imply that the H. pylori dapE mutant may be useful as a conditionally lethal vaccine.
Robust H∞ performance using lifted polynomial parameter-dependent Lyapunov functions

This paper investigates the robust H ∞ performance of time-invariant linear uncertain systems where the uncertainty is in polytopic domains. Robust H ∞ is checked by constructing a quadratic parameter-dependent Lyapunov function. The matrix associated with this quadratic Lyapunov function is a polynomial function of the uncertain parameters, expressed as a particular polynomial matrix involving κ powers of the dynamic matrix of the system and one symmetric matrix to be determined. The degree of this polynomial matrix function is arbitrary. Finsler's Lemma is used to lift the obtained stability conditions into a larger space in which sufficient stability tests can be developed in the form of linear matrix inequalities. As κ increases, less conservative H ∞ evaluations are obtained. Both continuous and discrete-time systems are investigated. Numerical examples illustrate the method and compare the present results with similar works in the literature.
Toward gene therapy of uterine fibroids: targeting modified adenovirus to human leiomyoma cells.

BACKGROUND To circumvent the paucity of the primary adenovirus (Ad5) receptor and the non-specific Ad5 tropism in the context of uterine leiomyoma cells, Ad5 modification strategies would be beneficial. METHODS We screened several modified adenoviruses to identify the most efficient and selective virus toward human leiomyoma cells to be used as candidate for delivering therapeutic genes. We propagated: wild-type Ad5-luc, fiber-modified viruses: ad5 RGD-luc, Ad5-Sigma-luc, Ad5/3-luc and Ad5-CAV2-luc, as well as transcriptional targeted viruses: ad5 survivin-luc, Ad5-heparanase-luc, Ad5-MSLN-CRAD-luc and Ad5-SLPI-luc, on 293 cells and purified them by double CsCL density centrifugation. Then we transfected primary cultures of human leiomyoma cells derived from fibroids of four different patients, telomerase-immortalized human leiomyoma cell line (huLM), telomerase-immortalized normal human myometrial cell line (HM9) and immortalized normal human liver cells (THLE3) with the viruses at 5, 10 and 50 plaque-forming units (PFU)/cell. After 48 h, luciferase activities were measured and normalized to the total cellular protein content. RESULTS Ad5-RGD-luc and Ad5-CAV2-luc, Ad5-SLPI-luc and Ad5-MSLN-CRAD-luc at 5, 10 and 50 pfu/cell showed significantly higher expression levels of luciferase activity in both primary and immortalized human leiomyoma cells when compared with Ad5-Luc. Additionally, these modified viruses demonstrated selectivity toward leiomyoma cells, compared with myometrial cells and exhibited lower liver cell transduction, compared with Ad5-luc, at the same dose levels. CONCLUSIONS Ad5-CAV2-luc, Ad5-RGD-luc, Ad5-SLPI-luc and Ad5-MSLN-CRAD-luc are promising delivery vehicles in the context of leiomyoma gene therapy.
Decision Aiding Rank inclusion in criteria hierarchies

This paper presents a method called Rank Inclusion in Criteria Hierarchies (RICH) for the analysis of incomplete preference information in hierarchical weighting models. In RICH, the decision maker is allowed to specify subsets of attributes which contain the most important attribute or, more generally, to associate a set of rankings with a given set of attributes. Such preference statements lead to possibly non-convex sets of feasible attribute weights, allowing decision recommendations to be obtained through the computation of dominance relations and decision rules. An illustrative example on the selection of a subcontractor is presented, and the computational properties of RICH are
Improvement of Speech Intelligibility of Mobile Devices in Noisy Environments

Multi-channel signal processing has gained popularity due to its practical application (e.g., speech recognition, noise reduction etc.) in a wide range of fields (i.e., military applications, music editing, audio information retrieval, etc.), and to the increased use of mobile and assistive communication devices. Without a doubt, increases in the computational power of these devices have allowed for the use of a wide range of techniques for noise reduction and to increase speech intelligibility. However, many of these are ineffective in many situations and, if not adjusted correctly for the particular environment, often introduce artifacts and distortions to the signal. Furthermore, these devices are often expensive, removing there availability from the general public, and proprietary, making them difficult to replicate and verify. Hence, there is a need for techniques for improving speech intelligibility in noisy environments which are open source, verifiable, and repeatable. Objectives and Importance The overall objective is to create a technique for improving speech intelligibility in noisy environments. To achieve this, the following subtopics must be addressed. Sound Source Separation Source separation problems in Digital Signal Processing (DSP) are those in which several signals have been mixed together into a combined signal and the objective is to recover the original component signals from the combined signal [1], [2]. The classical example of a source separation problem is the cocktail party problem, where a number of people are talking simultaneously in a room (e.g., at a cocktail party), and a listener is trying to follow one of the discussions. The human brain can handle this sort of auditory source separation problem, but it is a difficult problem in DSP. Several approaches have been proposed for the solution of this problem but development is currently still very much in progress. Some of the more successful approaches are Principal Component Analysis (PCA) and Independent Components Analysis (ICA), which work well when there are no delays or echoes present (i.e., the problem is simplified a great deal). The field of computational auditory scene analysis attempts to achieve auditory source separation using an approach that is based on human hearing. The human brain must also solve this problem in real time. In human perception, this ability is commonly referred to as Auditory Scene Analysis (ASA) or the cocktail party effect. These techniques will be investigated for separating an audio mixture and then HeadRelated Transfer Functions (HRTFs) will be used to position the sources in their respective positions in 3D space.
Clustering of banned food additives based on Word2vec

At present, food safety crimes frequently occur in China, which not only affects social stability and unity, but also affects the health and life safety of the general public. In this study, 3000 food safety crime judgments from the Wusong Cases Network are used as the data samples, and they are divided into corpus. Then the Word2vec algorithm is used to cluster the toxic and harmful additives in the corpus. The research shows that Word2vec algorithm can well complete the clustering of illegal additives in food safety crime cases, and found some unusual illegal additives which have a certain role in the future food safety crime.
Design Optimization of Inductive Power Transfer Systems Considering Bifurcation and Equivalent AC Resistance for Spiral Coils

This paper presents a design optimization algorithm for series-series compensated Inductive Power Transfer (IPT) system based on flat spiral coils, considering bifurcation phenomenon and AC equivalent resistance of the coils. Moreover, it finds the best values in the areas where the IPT system operates in Zero Voltage Switching (ZVS) condition. Equivalent AC resistance of spiral coils is modeled based on eddy currents simulations using Finite Element Method (FEM) and Maxwell simulator. Based on the FEM simulations, a new approximation method using separation of variables is proposed as a function of spiral coil’s main parameters. This paper shows that this model accurately derive equivalent resistance of the coils for a specific strand diameter, with almost 95% accuracy. Based on the proposed algorithm, several IPT systems are optimized in MATLAB software using Genetic Algorithm (GA). Finally, the proposed method has been verified using a laboratory prototype with output power of about 200 watts and operating frequency of about 85 kHz.
Using a Greedy-Based Approach for Solving Data Allocation Problem in a Distributed Environment

Feed bar advance and return driving apparatus for a transfer press. An upper slider is reciprocally vertically movable in the press crown in synchronization with the operation of the press, and a pinion rotatably mounted on the upper slider is rotated alternatingly in opposite directions with the upward and downward vertical movement of the upper slider. A drive rack vertically slidably supported on the upper slider is connected to the pinion at a position on the pinion which is eccentric to the axis of rotation of the pinion and is reciprocally vertically driven by the rotation of the pinion. The lower end of the drive rack extends downwardly and engages a drive pinion for rotating the drive pinion alternatingly in opposite directions during the reciprocal vertical motion of the drive rack. A drive lever connected to the drive pinion at a position eccentric to the axis of rotation of the drive pinion and pivotally mounted on the press is driven in a swinging motion and is connected to a lower slider for supporting feed bars of the press to drive the lower slider in advancing and returning directions.
The Improvement of the Algorithm EG for the Relative Entropy Loss

A long standing idea in online learning is Exponential Gradient (EG) update protocol. Its online weight updating rules is derived from incorporating components of the relative entropy distance and relevant entropy loss as the objective function. In this manuscript, we study the behaviors of the EG algorithm with relative entropy loss in the scene of conjugate of conjugate. More specifically, we propose that a principled solution to circumventing approximation step for the traditional EG algorithm can be found by conjugate of conjugate strategy. Moreover, an upper bound for the error loss is presented to demonstrate the effectiveness of our proposed update strategies. Meanwhile, we give three different protocols for the choice of the parameter and compare the results on noisy data. In addition, we validate the effectiveness of our devised exponential gradient update rules in the classification and regression scenarios on real-world data sets.