Miracle-dz/UniFAR-FTUs huggingface dataset:
Anaphora Resolution for Improving Spatial Relation Extraction from Text

Spatial relation extraction from generic text is a challenging problem due to the ambiguity of the prepositions spatial meaning as well as the nesting structure of the spatial descriptions. In this work, we highlight the difficulties that the anaphora can make in the extraction of spatial relations. We use external multi-modal (here visual) resources to find the most probable candidates for resolving the anaphoras that refer to the landmarks of the spatial relations. We then use global inference to decide jointly on resolving the anaphora and extraction of the spatial relations. Our preliminary results show that resolving anaphora improves the state-of-the-art results on spatial relation extraction.
Effects of Social Bots in the Iran-Debate on Twitter

2018 started with massive protests in Iran, bringing back the impressions of the so called "Arab Spring" and it's revolutionary impact for the Maghreb states, Syria and Egypt. Many reports and scientific examinations considered online social networks (OSN's) such as Twitter or Facebook to play a critical role in the opinion making of people behind those protests. Beside that, there is also evidence for directed manipulation of opinion with the help of social bots and fake accounts. So, it is obvious to ask, if there is an attempt to manipulate the opinion-making process related to the Iranian protest in OSN by employing social bots, and how such manipulations will affect the discourse as a whole. Based on a sample of ca. 900,000 Tweets relating to the topic "Iran" we show, that there are Twitter profiles, that have to be considered as social bot accounts. By using text mining methods, we show that these social bots are responsible for negative sentiment in the debate. Thereby, we would like to illustrate a detectable effect of social bots on political discussions on Twitter.
Spectral–Spatial Weighted Sparse Regression for Hyperspectral Image Unmixing

Spectral unmixing aims at estimating the fractional abundances of a set of pure spectral materials (endmembers) in each pixel of a hyperspectral image. The wide availability of large spectral libraries has fostered the role of sparse regression techniques in the task of characterizing mixed pixels in remotely sensed hyperspectral images. A general solution for sparse unmixing methods consists of using the $\ell _{1}$ regularizer to control the sparsity, resulting in a very promising performance but also suffering from sensitivity to large and small sparse coefficients. A recent trend to address this issue is to introduce weighting factors to penalize the nonzero coefficients in the unmixing solution. While most methods for this purpose focus on analyzing the hyperspectral data by considering the pixels as independent entities, it is known that there exists a strong spatial correlation among features in hyperspectral images. This information can be naturally exploited in order to improve the representation of pixels in the scene. In order to take advantage of the spatial information for hyperspectral unmixing, in this paper, we develop a new spectral–spatial weighted sparse unmixing (S2WSU) framework, which uses both spectral and spatial weighting factors, further imposing sparsity on the solution. Our experimental results, conducted using both simulated and real hyperspectral data sets, illustrate the good potential of the proposed S2WSU, which can greatly improve the abundance estimation results when compared with other advanced spectral unmixing methods.
PCCA: Position Confidentiality Conserving Algorithm for Content-Protection in e-Governance Services and Applications

E-Governance or electronic governance is a procedure of public sector regulation and is a significant step in the transformation of municipal administration, with the intention of confiding and smoothing collaboration among the population and civic establishments through Information and Communications Technology-based applications. Content Confidentiality has become a serious anxiety for modern Information Societies. The sensitive nature of much of the private personal data that are exchanged or released to untrusted parties necessitates that liable administrations should embark on suitable content confidentiality protection mechanisms. Nowadays, many of these data are texts (e.g., emails, messages posted in social media, healthcare outcomes, etc.) that, because of their unstructured and semantic nature, constitutes a challenge for automatic data protection methods. In this paper, we present a solution for position confidentiality conserving content protection in e-Governance services through computational intelligence. We propose PCCA, a novel position confidentiality conserving algorithm for content protection in e-Governance. The proposed algorithm applies computational intelligence in e-Governance for content protection by means of rule-based approach from computational intelligence and users current position information. A simulation model has been implemented on a desktop PC and evaluation using roaming users real-time position-based information demonstrates that PCCA can efficiently conserve roaming users position confidentiality while accomplishing better performance, guaranteed position confidentiality, and better quality of service in e-Governance.
Data-driven analysis of biomedical literature suggests broad-spectrum benefits of culinary herbs and spices

Spices and herbs are key dietary ingredients used across cultures worldwide. Beyond their use as flavoring and coloring agents, the popularity of these aromatic plant products in culinary preparations has been attributed to their antimicrobial properties. Last few decades have witnessed an exponential growth of biomedical literature investigating the impact of spices and herbs on health, presenting an opportunity to mine for patterns from empirical evidence. Systematic investigation of empirical evidence to enumerate the health consequences of culinary herbs and spices can provide valuable insights into their therapeutic utility. We implemented a text mining protocol to assess the health impact of spices by assimilating, both, their positive and negative effects. We conclude that spices show broad-spectrum benevolence across a range of disease categories in contrast to negative effects that are comparatively narrow-spectrum. We also implement a strategy for disease-specific culinary recommendations of spices based on their therapeutic tradeoff against adverse effects. Further by integrating spice-phytochemical-disease associations, we identify bioactive spice phytochemicals potentially involved in their therapeutic effects. Our study provides a systems perspective on health effects of culinary spices and herbs with applications for dietary recommendations as well as identification of phytochemicals potentially involved in underlying molecular mechanisms.
ALANIS at SemEval-2018 Task 3: A Feature Engineering Approach to Irony Detection in English Tweets

This paper describes the ALANIS system that participated in Task 3 of SemEval-2018. We develop a system for detection of irony, as well as the detection of three types of irony: verbal polar irony, other verbal irony, and situational irony. The system uses a logistic regression model in subtask A and a voted classifier system with manually developed features to identify ironic tweets. This model improves on a naive bayes baseline by about 8 percent on training set.
A Study in Using Neural Networks for Anomaly and Misuse Detection

Current intrusion detection systems lack the ability to generalize from previously observed attacks to detect even slight variations of known attacks. This paper describes new process-based intrusion detection approaches that provide the ability to generalize from previously observed behavior to recognize future unseen behavior. The approach employs artificial neural networks (ANNs), and can be used for both anomaly detection in order to detect novel attacks and misuse detection in order to detect known attacks and even variations of known attacks. These techniques were applied to a large corpus of data collected by Lincoln Labs at MIT for an intrusion detection system evaluation sponsored by the U.S. Defense Advanced Research Projects Agency (DARPA). Results from applying these techniques for both anomaly and misuse detection against the DARPA evaluation data are presented.
Pattern-Aware Reliable Virtual Network Function Chain Deployment

Network function virtualization enables network middlebox running as virtual network function (VNF) on general servers, and further be chained in a certain order to provide specific services. In order to meet reliability requirement, the VNFs need certain backups against both nodes (servers) and links failures. Previous backup strategies for VNF focuses on node failures based on an unreasonable assumption that VNFs do not share any server. In this paper, we focus on the reliable virtual network function chain (VNFC) deployment problem taking both node and link failure into consideration, with the objective to minimize loss of profit due to server energy consumption and requests rejection. We formulate reliable VNFC problem with an Integer Linear Programming model, and prove the NP-hardness. We propose an efficient pattern-aware reliable VNFC deployment strategy considering link insurance as well as node backups, which can save resources by finding patterns. Extensive simulation experiments show that, under availability constraint of each VNFC request, our strategies can reduce 18% energy consumption and increase 54.7% request accept ratio compared with greedy strategies.
Atg9 establishes Atg2-dependent contact sites between the endoplasmic reticulum and phagophores

The autophagy-related (Atg) proteins play a key role in the formation of autophagosomes, the hallmark of autophagy. The function of the cluster composed by Atg2, Atg18, and transmembrane Atg9 is completely unknown despite their importance in autophagy. In this study, we provide insights into the molecular role of these proteins by identifying and characterizing Atg2 point mutants impaired in Atg9 binding. We show that Atg2 associates to autophagosomal membranes through lipid binding and independently from Atg9. Its interaction with Atg9, however, is key for Atg2 confinement to the growing phagophore extremities and subsequent association of Atg18. Assembly of the Atg9–Atg2–Atg18 complex is important to establish phagophore–endoplasmic reticulum (ER) contact sites. In turn, disruption of the Atg2–Atg9 interaction leads to an aberrant topological distribution of both Atg2 and ER contact sites on forming phagophores, which severely impairs autophagy. Altogether, our data shed light in the interrelationship between Atg9, Atg2, and Atg18 and highlight the possible functional relevance of the phagophore–ER contact sites in phagophore expansion.
Comparison of the effects of the three major tyrosine kinase inhibitors as first-line therapy for non-small-cell lung cancer harboring epidermal growth factor receptor mutations

Introduction Patients with advanced lung adenocarcinoma harboring epidermal growth factor receptor (EGFR)-activating mutations have good response rate and longer progression-free survival (PFS) when treated with the tyrosine kinase inhibitors (TKI) compared with platinum-based chemotherapy. However, studies comparing the effectiveness of these drugs as first-line therapy in such patients are limited. Results We analyzed 422 patients with EGFR-mutated advanced lung adenocarcinoma receiving first-line gefitinib (n = 195, 46.2%), erlotinib (n = 123, 29.1%), or afatinib (n = 104, 24.6%). The PFS of the afatinib group was longer (12.2 months) than that of the gefitinib group (9.8 months) (p = 0.035) but similar to that of the erlotinib group (11.4 months) (p = 0.38). In patients without brain metastasis (BM), subgroup analysis showed that the afatinib group had significantly longer PFS (13.1 months) than erlotinib (11.7 months) and gefitinib (9.8 months) groups (p = 0.010). Patients with exon 19 deletions in the afatinib and erlotinib groups had potentially long PFS (p = 0.073). Efficacy of afatinib was similar between the 30 mg and 40 mg arms (median PFS 16.1 months vs. 10.3 months; p = 0.923). Conclusions Afatinib may be the optimal EGFR-TKI for advanced lung adenocarcinoma harboring EGFR-activating mutations, particularly in the absence of BM. Patients with exon 19 deletions taking afatinib had potentially long PFS. An afatinib dose of 30 and 40 mg has similar effect. Methods We conducted this retrospective study at a single medical center from January 2013 to March 2017 and used PFS to evaluate the effectiveness of gefitinib, erlotinib, and afatinib in patients with advanced lung adenocarcinoma harboring EGFR mutations.
GAN Q-learning

Distributional reinforcement learning (distributional RL) has seen empirical success in complex Markov Decision Processes (MDPs) in the setting of nonlinear function approximation. However, there are many different ways in which one can leverage the distributional approach to reinforcement learning. In this paper, we propose GAN Q-learning, a novel distributional RL method based on generative adversarial networks (GANs) and analyze its performance in simple tabular environments, as well as OpenAI Gym. We empirically show that our algorithm leverages the flexibility and blackbox approach of deep learning models while providing a viable alternative to traditional methods.
Effect of starch substitution with crude glycerol on growing rabbit and lactating doe performance.

The aim of this work was to study the effect of dietary inclusion of 2.5 or 5.0% of glycerol in substitution for starch on performance of lactating does and fattening rabbits. Over four consecutive reproductive cycles, a total of 81 New Zealand ´ Californian rabbit does and 813 young rabbits weaned at 25 (fattening trial 1) or 35 (fattening trial 2) days of age were allocated at random to the experimental treatments. Inclusion of glycerol in the diet up to 5% did not influence total feed consumption of does and suckling rabbits, body weight and bioelectrical impedance of does at parturition or at day 21 of lactation and litter weight at weaning, or reproductive efficiency. Substitution of starch with glycerol did not affect feed intake, weight gain or mortality during fattening. The results of the current study indicate that crude glycerol from the biofuel industry can be used at levels up to 5% in rabbit diets without any detrimental or beneficial effect on performance.
Salvianolic acid B reverses multidrug resistance in nude mice bearing human colon cancer stem cells

Salvianolic acid B (SalB) is a water-soluble phenolic compound, extractable from Salvia miltiorrhiza, and has previously been demonstrated to reverse tumor multidrug resistance (MDR) in colon cancer cells. Cancer stem cells (CSCs) are closely associated with drug resistance. Therefore, establishing a nude mouse model bearing human colon CSCs is important for the study of the mechanisms underlying colon cancer drug resistance as well as the reversal of drug resistance. The present study aimed to establish a nude mouse model bearing human colon CSCs and to investigate the effects of SalB on the drug resistance exhibited by the nude mouse model as well as determine its underlying mechanism. Cells from two colon cancer cell lines (LoVo and HCT-116) were cultured in serum-free medium to obtain CSCs-enriched spheroid cells. Following this, nude mice were transplanted with LoVo and HCT-116 colon CSCs to establish the CSC nude mouse model, which was subsequently demonstrated to exhibit MDR. The results of the present study revealed that following treatment with SalB, the chemotherapeutic drug resistance of xenografts was reversed to a certain extent. Western blot analysis was performed to investigate the expression levels of cluster of differentiation (CD)44, CD133, transcription factor sox-2 (SOX2) and ATP-binding cassette sub-family G member 2 (ABCG2) proteins, and the results demonstrated that treatment with SalB downregulated the expression of CD44, SOX2 and ABCG2 proteins in both LoVo and HCT-116 colon CSCs xenografts. In conclusion, the results of the present study revealed that a serum-free suspension method can be performed to successfully isolate colon CSCs. In addition, a nude mice bearing colon CSCs animal model was successfully established, and associated tumors were confirmed to exhibit MDR. Furthermore, SalB was demonstrated to successfully reverse MDR in nude mice bearing LoVo and HCT-116 colon CSCs, as well as suppress the expression of CD44, SOX2 and ABCG2 proteins.
Rapid Learning in Early Attentional Processing: Bayesian Estimation of Trial-by-Trial Updating

All agents must constantly learn from dynamic environments to optimize their behaviors. For instance, it is necessary in new environments to learn how to distribute attention – i.e., which stimuli are relevant, and thus should be selected for greater processing, and which are irrelevant, and should be suppressed. Despite this, many experiments implicitly assume that attentional control is a static process (by averaging performance over large blocks of trials). By developing and utilizing new statistical tools, here we demonstrate that the effect of flanking items on response times to a central item (often utilized as an index of attentional control) is systematically and continuously influenced through time by the statistics of the flanking items. We discuss the implications of this finding from the perspective of examining individual differences – where traditional data analysis approaches may confound the rate at which attentional filtering changes through time with the asymptotic ability to filter.
Alternative Corrective Measures Used in Managing Student Behavior Problems in Secondary Schools in Bondo Sub County, Kenya

The purpose of the study was to identify alternative corrective measures used by teachers to manage students’ behavior problems in secondary schools. The study was informed by Assertive Discipline Model and Thorndike’s Behavior Modification Theory. Mixed methods research approach was used and with it, concurrent triangulation design was adopted. Target population of the study was composed of 308 teachers from a total number of 34 schools that had 34 Heads of Guidance and Counseling, 34 Deputy Principals and 240 classroom teachers. Krejcie & Morgan sample size determination table and stratified random sampling technique was used to sample 28 Deputy Principals from a total number of 34 deputy principals, 28 Heads of Guidance and Counseling from a total number of 34 and 152 teachers from a total of 240. Pilot study was done in three schools that didn’t participate in the actual study to determine reliability of the instruments and split half method was used to ascertain a reliability coefficient of 0.871. Face validity of the instruments was ascertained by pilot testing the questionnaires and also by seeking expert judgment by university lecturers. Data was collected using questionnaires, in-depth interviews and document analysis guides. Quantitative data was analyzed using basic descriptive statistics and inferential statistics. Qualitative data from interviews were analyzed using thematic analysis. The study findings revealed that alternative corrective measures like guidance and counseling, manual work, temporary withdrawal from class, withdrawal of privileges and suspension were used in managing student behavior problems. However, it was established that use of rules and detention were not preferred as alternative methods of managing student behavior problems. DOI: 10.5901/mjss.2016. v7n1p527
The Suppression of Medium Acidosis Improves the Maintenance and Differentiation of Human Pluripotent Stem Cells at High Density in Defined Cell Culture Medium

Cell density has profound impacts on the cell culture practices of human pluripotent stem cells. The regulation of cell growth, cell death, pluripotency and differentiation converge at high density, but it is largely unknown how different regulatory mechanisms act at this stage. We use a chemically defined medium to systemically examine cellular activities and the impact of medium components in high-density culture. We show that medium acidosis is the main factor that alters cell cycle, gene expression and cellular metabolism at high cell density. The low medium pH leads to inhibition of glucose consumption, cell cycle arrest, and subsequent cell death. At high cell density, the suppression of medium acidosis with sodium bicarbonate (NaHCO3) significantly increases culture capacity for stem cell survival, derivation, maintenance and differentiation. Our study provides a simple and effective tool to improve stem cell maintenance and applications.
Mandibular Osteitis Fibrosa Cystica as First Sign of Vitamin D Deficiency

Introduction Brown tumors of hyperparathyroidism are locally destructive bone lesions. They are the late clinical consequence of the disease. They can occur in primary, secondary, and rarely tertiary forms. They affect usually long bones and less frequently those of the maxilla. Case Report Our 45-year-old female patient presented with a mandibular tumor next to the first right lower molar. At first, we have chosen tooth extraction and tumor excision. When the histological report showed the giant cell tumor we suspected a metabolic bone disorder. Biochemical tests screened hyperparathyroidism and severe vitamin D deficiency, and parathyroid scintiscan revealed parathyroid adenoma. Discussion The association of hyperparathyroidism and vitamin D deficiency leads to diagnostic uncertainty. First, secondary hyperparathyroidism can be due vitamin D deficiency. Second, data available show that vitamin D deficiency is more prevalent in patients with primary hyperparathyroidism than in general population. Hyperparathyroidism management is based on correct and precise diagnosis. Furthermore, the resolution of brown tumors depends on the cure of hyperparathyroidism. In fact, bone lesions should regress after biological tests' normalization. Conclusion Clinicians should be aware of such rare and complicated presentation. They must consider the diagnosis of the brown tumor to avoid extensive surgical excision and teeth extractions.
Towards the improvement of ADHD children through augmented reality serious games: Preliminary results

Attention Deficit-Hyperactivity Disorder is the most common childhood neurodevelopment disorder that globally affects 3 to 5 percent of children. Several computerized training programs for ADHD have been designed to improve executive functions. With technological advancement, new approaches can be used to develop interactive experiences with visual effects. In this sense, Serious Games have recently shown great potential to be adopted in this psychotherapeutic area. One critical challenge is developing serious games using emerging technologies like Augmented Reality (AR) focus on cognitive-behavioral therapies for children with this disorders in scholar-age. This paper aim is to improve ADHD children's attention and train them using an Augmented Reality Serious Games (ARSG) prototype. It was designed with the help of experts, workshops with designers, the guidance of psychologists and medical doctors specialized on ADHD, by using a methodical game design approach along with natural user interface (Kinect). Findings of this case study showed that player's attention and retention increased, improving their tolerance for frustration and with a significant time reduction in the game activities.