Miracle-dz/UniFAR-FTUs huggingface dataset:
Exploring the Role of Estrogens in Lizard Spermatogenesis through the Study of Clomiphene and FSH Effects

Spermatogenesis is a fascinating biological process aiming to generate haploid spermatozoa from diploid spermatogonia through a specific hormonal network between gonadotropins and steroids. Increasing evidence suggests that the primary female sex hormone estrogen plays an active role in this process. This research points out on the role of estrogen during lizard spermatogenesis by using three experimental approaches: (1) exposure to an analogue of nonsteroidal estrogen as Clomiphene citrate that acts both as estrogen agonist and antagonist; (2) exposure to the gonadotropin FSH; and (3) exposures to FSH followed by Clomiphene. Histological and immunohistochemical results demonstrate that in the lizard Podarcis sicula during the mating period, Clomiphene as well as FSH determines the breakdown of spermatogenesis and the epididymal regression, presumably through estrogens input as indirectly demonstrated by the appearance of ERα and vitellogenin in the liver. The ability of Clomiphene to restore the gonadal natural condition after FSH treatment is also demonstrated. Finally, data indicate that lizard testis and epididymis control their morphophysiology regulating the intracellular presence of ERα.
Exploring the Ecology of Deep-Sea Hydrothermal Vents in a Metacommunity Framework

Species inhabiting deep-sea hydrothermal vents are strongly influenced by the geological setting, as it provides the chemical-rich fluids supporting the food web, creates the patchwork of seafloor habitat, and generates catastrophic disturbances that can eradicate entire communities. The patches of vent habitat host a network of communities (a metacommunity) connected by dispersal of planktonic larvae. The dynamics of the metacommunity are influenced not only by birth rates, death rates and interactions of populations at the local site, but also by regional influences on dispersal from different sites. The connections to other communities provide a mechanism for dynamics at a local site to affect features of the regional biota. In this paper, we explore the challenges and potential benefits of applying metacommunity theory to vent communities, with a particular focus on effects of disturbance. We synthesize field observations to inform models and identify data gaps that need to be addressed to answer key questions including: 1) what is the influence of the magnitude and rate of disturbance on ecological attributes such as time to extinction or resilience in a metacommunity; 2) what interactions between local and regional processes control species diversity, and 3) which communities are 'hot spots' of key ecological significance. We conclude by assessing our ability to evaluate resilience of vent metacommunities to human disturbance (e.g., deep-sea mining). Although the resilience of a few highly disturbed vent systems in the eastern Pacific has been quantified, these values cannot be generalized to remote locales in the western Pacific or mid Atlantic where disturbance rates are different and information on local controls is missing.
Income Distribution , Market Size , and Foreign Direct Investment ∗

This paper studies the role of the host country’s market size in the determination of foreign direct investment (FDI) and trade flows in a general equilibrium model. We propose a simple model with non-homothetic consumer behavior where the distribution of income in the host country implies market segmentation. Facing a proximity-concentration trade-off, in equilibrium ex-ante identical firms choose different foreign market entry modes depending on the market segment they serve. Firms supplying the mass market in the foreign country engage in FDI whereas those catering to a few rich consumers abroad export. For firms serving the mass market the cost reduction due to the saving of transportation costs on a large number of units sold, outweighs the cost increase due to the higher fixed cost associated with setting up a foreign production facility. The model predicts a positive relationship between average income of the middle class in the host country and FDI activity in the host country. As an illustration, we use data on outward FDI positions of OECD countries between 1997-2007. We estimate a positive relationship between average income of the host country’s middle class and FDI positions in the host country held by OECD countries. JEL classification: F12, F21, F23, F6, D31
EmoLiTe — A database for emotion detection during literary text reading

Observing an individual while reading a text reveals a complex interplay of contextual features. The features are an important part of understanding why a reader reacted in a certain way to a given text, e.g. by expressing an emotion, showing interest or demonstrating dislike. Capturing all these aspects in one database is thus a challenging task. In this paper the context based EmoLiTe database is introduced, which brings together literary text reading experiments using aligned video and eye-tracking data with post-experiment reader annotations. EmoLiTe is released for free and thus contributes to both the emotion and reading research community by providing them with a novel context based corpora.
Age, criterion flexibility, and item recognition

ABSTRACT We examined young and older adults' ability to flexibly adapt response criterion on a recognition test when the probability that a test item had been studied was cued by test color. One word color signaled that the probability of the test item being old was 70% and a second color signaled that the probability of the test item being new was 70%. Young and older adults demonstrated similar levels of criterion shifting in response to color cues. Moreover, although both young and older adults were slowed when test-item color incorrectly predicted test-item status, the extent of slowing did not differ across age group. Putative measures of cognitive control predicted recognition accuracy but not the degree to which criterion changed with test-item color. These results suggest that adaptive criterion shifting does not tax cognitive control or, if it does require effort, may be no more onerous for older than for young adults.
Unsupervised cost sensitive predictions with side information

In many security and healthcare systems, a sequence of sensors/tests is used for detection and diagnosis. Each test outputs a prediction of the latent state, and carries with it inherent costs. Our objective is to learn strategies for selecting a test that gives the best trade-off between accuracy & costs. Unfortunately, it is often impossible to acquire ground truth annotations and we are left with the problem of unsupervised sensor selection (USS). Hanawal et al. [9] reduces USS to a special case of multi-armed bandit problem with side information and develop polynomial time algorithms that achieve sub-linear regret. In this paper, we extend earlier analysis with contextual information, propose an algorithm having sub-linear regret and verify our results on synthetic & real datasets.
An Enhanced Boundary Scan Architecture for Inter-Die Interconnect Leakage Measurement in 2.5D and 3D Packages

3D-IC is a solution to achieve lower cost and higher performance as the transistor density doubles every 18 months following Moore's law. In recent years, Integrated Fan-Out Wafer-Level Chip-Scale Packaging (InFO WLCSP) is one of the most promising packaging technologies for 3D-IC. In InFO WLCSP, there are some inter-die interconnects. We cannot access these interconnects directly. Therefore, it causes 1-2% test coverage loss. As a result, a built-in self-test (BIST) or other design-for-test (DFT) methodology is necessary to test these interconnects. It is easy to detect open defects and short defects leading to large leakage currents with conventional test methods. However, defects leading to small leakage currents are hard to detect, so we focus on these defects in this work. In this paper, we propose a scheme to measure the small leakage current of these inter-die interconnects. The scheme uses IEEE 1149.1 boundary scan interface. Because boundary scan is a well-adopted standard, the scheme can be integrated into any electronic product easily. Beside four mandatory terminals, we add a reference current input. Users can apply current to compare it with the leakage current. For the input EBSC, two OR gates, a MUX, and a current digitizer are added and it is compared with the conventional BSC. A test chip is implemented to verify our design, which uses the one-polynine-metal (1P9M) 90nm CMOS technology. Measurement results show that the proposed scheme is able to measure the leakage current of the interconnect. In addition, with the dynamic range of 128nA, the current digitizer has 6-bit resolution.
To the problem of "The Instrumental complex for ontological engineering purpose" software system design

The given work describes methodological principles of design instrumental complex of ontological purpose. Instrumental complex intends for the implementation of the integrated information technologies automated build of domain ontologies. Results focus on enhancing the effectiveness of the automatic analysis and understanding of natural-language texts, building of knowledge description of subject areas (primarily in the area of science and technology) and for interdisciplinary research in conjunction with the solution of complex problems.
Weighted fast iterative shrinkage thresholding for 3D massive MIMO channel estimation

Fitting the huge number of pilots needed for massive multiple inputs multiple outputs antennas (MIMO) channel estimation within the available time and frequency resources is a challenging problem. Generally, compressed sensing (CS) channel estimation algorithms face the dilemma of trading off the estimation accuracy and the computational complexity. In this paper, we propose a weighted fast iterative shrinkage thresholding algorithm (W-FISTA). The proposed algorithm provides higher estimation efficiency with the same complexity as the original FISTA. With low computational complexity, multiple measurement vectors (MMV) version of the W-FISTA is proposed to estimate the 3D massive MIMO channel. The proposed MMV-WFISTA estimate the channel coefficients by exploiting its joint sparsity structure in the angle-delay sparse domain. The complexity analysis and the simulation results indicate a clear improvement in the performance of the proposed MMV-WFISTA over joint estimation algorithms.
A novel animal model for subcutaneous soft tissue infection using temporally neutropenic lys-EGFP mice

Neutrophils play an important role against bacterial infection, mainly methicillin resistant Staphylococcus aureus (MRSA). Therefore, we developed an animal model to simultaneously monitor bacterial colonization and neutrophil migration in vivo. Using lys-EGFP C57BL/6 mice, we initially rendered the mice temporally neutropenic using cyclophosphamide (CPM) treatment (300mg/kg or 375mg/kg). Later, bioluminescent MRSA (Xen31, PerkinElmer) were subcutaneously injected (1.0×107 CFU) into the dorsal skin of the neutropenic lys-EGFP mice. The mice were then administered either saline (control group), or vancomycin (66mg/kg, treated group) consecutively for three days. For the evaluation of MRSA activity and neutrophil accumulation, an in vivo imaging system (LAS-4000, GE) was performed. Our results demonstrated that vancomycin is capable of killing bacterial cells and it also promotes inflammation. In addition, the rate of neutrophil regeneration after being suppressed by CPM is dependent on the dose of CPM. We could conclude that vancomycin is capable of inducing inflammation but the effects of the drug could only be observed if the immune system is adequately suppressed.
Bulk immunoassays for analysis of extracellular vesicles

ABSTRACT There is increasing clinical interest in extracellular vesicles (EV) for diagnostic and treatment purposes. This review provides an overview of bulk immunoassays to analyse EV. Western blot and enzyme-linked immunosorbent assay are still the two predominant bulk immunoassays. Recently, new assays have become available that can detect exposure to EV concentrations that are up to 10,000-fold lower. This is advantageous for applications that detect rare EV. Other important parameters are the detectable concentration range, the required sample volume, whether simultaneous presence of different antigens on a single EV can be detected, size selectivity of each assay and practical considerations. In this review, we will explain the working principles of the traditional and novel assays together with their performance parameters. The most sensitive assays are micro-nuclear magnetic resonance, surface plasmon resonance, and time-resolved fluorescent immunoassay.
Synchronization of rigid body dynamics in SE(3) without velocity measurement

In this paper, we first propose a control law for synchronization of multi-agent systems in Special Euclidean group SE(3). Then, as an extension of the proposed synchronization algorithm, we propose another control algorithm for the same task without using velocity measurement. It will be shown that the synchronization can be enabled on the basis of an auxiliary dynamic system and double integrated consensus algorithm. Additionally, to overcome the disadvantage of the Euler angles, we use a quaternion. Using the Lyapunov stability analysis, we can verify that the proposed algorithms could ensure the synchronization in the attitude and position as well as in angular and linear velocities. Simulation results demonstrate the effectiveness of theoretical results.
Spanning Tree Congestion and Computation of Generalized Győri-Lov{á}sz Partition

We study a natural problem in graph sparsification, the Spanning Tree Congestion (\STC) problem. Informally, the \STC problem seeks a spanning tree with no tree-edge \emph{routing} too many of the original edges. The root of this problem dates back to at least 30 years ago, motivated by applications in network design, parallel computing and circuit design. Variants of the problem have also seen algorithmic applications as a preprocessing step of several important graph algorithms. For any general connected graph with $n$ vertices and $m$ edges, we show that its STC is at most $\mathcal{O}(\sqrt{mn})$, which is asymptotically optimal since we also demonstrate graphs with STC at least $\Omega(\sqrt{mn})$. We present a polynomial-time algorithm which computes a spanning tree with congestion $\mathcal{O}(\sqrt{mn}\cdot \log n)$. We also present another algorithm for computing a spanning tree with congestion $\mathcal{O}(\sqrt{mn})$; this algorithm runs in sub-exponential time when $m = \omega(n \log^2 n)$. For achieving the above results, an important intermediate theorem is \emph{generalized Gy\H{o}ri-Lov{\'{a}}sz theorem}, for which Chen et al. gave a non-constructive proof. We give the first elementary and constructive proof by providing a local search algorithm with running time $\mathcal{O}^*\left( 4^n \right)$, which is a key ingredient of the above-mentioned sub-exponential time algorithm. We discuss a few consequences of the theorem concerning graph partitioning, which might be of independent interest. We also show that for any graph which satisfies certain \emph{expanding properties}, its STC is at most $\mathcal{O}(n)$, and a corresponding spanning tree can be computed in polynomial time. We then use this to show that a random graph has STC $\Theta(n)$ with high probability.
U-DBMS: A Database System for Managing Constantly-Evolving Data

In many systems, sensors are used to acquire information from external environments such as temperature, pressure and locations. Due to continuous changes in these values, and limited resources (e.g., network bandwidth and battery power), it is often infeasible for the database to store the exact values at all times. Queries that uses these old values can produce invalid results. In order to manage the uncertainty between the actual sensor value and the database value, we propose a system called U-DBMS. U-DBMS extends the database system with uncertainty management functionalities. In particular, each data value is represented as an interval and a probability distribution function, and it can be processed with probabilistic query operators to produce imprecise (but correct) answers. This demonstration presents a PostgreSQL-based system that handles uncertainty and probabilistic queries for constantly-evolving data.
Non‐genomic activities of retinoic acid receptor alpha control actin cytoskeletal events in human platelets

Essentials Platelets employ proteins/signaling pathways traditionally thought reserved for nuclear niche. We determined retinoic‐acid‐receptor alpha (RARα) expression and function in human platelets. RARα/actin‐related protein‐2/3 complex (Arp2/3) interact via non‐genomic signaling in platelets. RARα regulates Arp2/3‐mediated actin cytoskeletal dynamics and platelet spreading.
Speech Emotion Recognition based on Optimized Support Vector Machine

Speech emotion recognition is a very important speech technology. In this paper, Mel Frequency Cepstral Coefficients (MFCC) has been used to represent speech signal as emotional features. MFCCs plus energy of an utterance are used as the input for Support Vector Machine. Support Vector Machine (SVM) has been profoundly successful in the area of pattern recognition. In the recent years there has been use of SVM for speech recognition. Many kinds of kernel functions are available for SVM to map an input space problem to high dimensional spaces. We lack guidelines on choosing a better kernel with optimized parameters of SVM. Some kernels are better for some questions, but worse for other questions. Which is better is unknown for speech emotion recognition, thus the thesis studies the SVM classifier and proposes methods used to select a better kernel with optimized parameters. The new method we proposed in this paper can more efficiently gain optimized parameters than common methods. In order to improve recognition accuracy rate of the speech emotion recognition system, a speech emotion recognition based on optimized support vector machine is proposed. Experimental studies are performed over the HIT Emotional Speech Database established by Speech Processing Lab in School of Computer Science and Technology at HIT. The experiment result shows that the speech emotion recognition based on optimized SVM can improve the performance of the emotion recognition system effectively.
Time‐dependent effect of phytocannabinoid treatments in fat cells

The objectives of this paper is to investigate, demonstrate, and compare the mechanism of action of phytocannabinoids as antidiabetic and anti‐obesity agents in preadipocytes and adipocytes, relative to rosiglitazone and metformin. Briefly, cannabis extract, Δ9‐tetrahydrocannabinol and cannabidiol (in very low dosages) were shown to promote glucose uptake higher or to equivalent levels, reduce fat accumulation, and reverse the insulin‐resistant state of 3T3‐L1 cells more effectively, relative to rosiglitazone and metformin. The phytocannabinoids had a more pronounced effect in preadipocytes undifferentiated model rather than the differentiated model. They induced a protective effect at the mitochondrial level by preventing overactivity of the succinate dehydrogenase pathway (p < .01), unlike rosiglitazone, through activation of the glycerol‐3‐phosphate dehydrogenase shuttling system. An increase in oxygen consumption and an increased expression of beta to alpha adrenoceptors (p < .05) in treated cells were noted. These findings contribute toward understanding the mechanism of action of phytocannabinoids in fat cells and highlight the antidiabetic and anti‐obesity properties of various phytocannabinoids that could potentially support the treatment of obesity‐related insulin resistance.
Identification of G0S2 as a gene frequently methylated in squamous lung cancer by combination of in silico and experimental approaches

Epigenetic changes can lead to abnormal expression of genes in cancer, and several genes have been reported to have aberrant promoter DNA methylation in non‐small‐cell lung cancer (NSCLC). We identified aberrantly methylated genes in NSCLC by combination of in silico and experimental approaches. We first applied bioinformatics, and from microarray datasets, we selected genes with low expression and having functions related to cancer. Next, combined bisulfite restriction analysis was carried out in 10 pooled resected lung cancer tissues to screen for genes that were aberrantly methylated, and the methylation ratio (the fraction of methylated DNA in extracted DNA from a cancer tissue sample) was quantified using quantitative analysis of methylated alleles. We identified 8 methylated genes (ARPC1B, DNAH9, FLRT2, G0S2, IRS2, PKP1, SPOCK1 and UCHL1) previously unreported in NSCLC. Analyses of methylation profiles of 101 resected lung cancer tissue samples revealed quantitatively low methylation in whole, methylation ratios were almost less than 30% even in the methylated samples, and no significant correlation to prognosis after 2 years of follow‐up using hierarchical clustering. DNA methylation of G0S2 gene was significantly more frequent in squamous lung cancer (n = 18, mean of methylation ratios: 15%) compared with nonsquamous lung cancer (n = 83, mean of methylation ratios: 2.6%) (Mann‐Whitney U test, p < 0.001). DNA methylation of G0S2 can be an important biomarker for squamous lung cancer.
Further Explorations in State-Space Search for Optimal Task Scheduling

The problem of task scheduling with communication delays is NP-hard. State-space search algorithms such as A* have been shown to be a promising approach to solving this problem optimally. A recently proposed state-space model for task scheduling, known as Allocation-Ordering (AO), allows state-space search methods to be applied to the problem of optimal task scheduling without the need for duplicate avoidance mechanisms. This paper examines the performance of two parallel search algorithms when applied to both the AO model and the older ELS state-space model. This suggests that its use may provide an advantage with many different variations on state-space search. This paper explores the application of AO to some of these variants, namely depth-first branch-and-bound (DFBnB) and parallel search. We also present an update to the formulation of AO that prevents invalid states from being considered during a search. An evaluation shows that AO gives a clear advantage to DFBnB and allows greater scalability for parallel search algorithms. The update to AO's formulation has no significant impact on performance either way.