Miracle-dz/UniFAR-FTUs huggingface dataset:
MEASURING PEER EFFECTS IN ACADEMIC OUTCOMES

Title of dissertation: MEASURING PEER EFFECTS IN ACADEMIC OUTCOMES Ying Zeng, Doctor of Philosophy, 2017 Dissertation directed by: Professors Guido Kuersteiner and Ingmar Prucha Department of Economics There is wide belief that a student’s behavior and academic outcome are affected by her/his fellow students. This peer effect lies at the center of the debate about education policy. My dissertation focuses on measuring peer effects in academic outcomes. It consists of a theoretical part and an empirical part. In the theoretical part, I study a peer effects model with group-wise equal interactions and random group effects. Identifying peer effects is notoriously challenging due to the reflection problem. Common shocks to the groups also generate spurious peer effects. My model, therefore, controls for the common shocks to the whole group with random group effects. My estimation strategy overcomes the identification problem with spatial econometrics techniques. I develop a quasi-maximum likelihood estimator of the model. Monte-Carlo simulations show that the bias of the estimator decreases with the number of groups and the variation in group size, and increases with group size. Finally, I prove the consistency and asymptotic normality of the estimator under standard assumptions. In the empirical part, I apply the model to Project STAR data to study the peer effects among kindergarten students. Peers constitute an important context for children’s academic development. This empirical study measures peer effects on math and reading scores of kindergarten children using data from Project STAR, an experiment in Tennessee that randomly assigned both children and teachers to classrooms of different sizes. It estimates the impact of peers’ scores and characteristics on children’s individual scores, controlling among other things for random class effects. In contrast to most existing studies, the estimated peer effects in the empirical part are small and insignificant. The results are robust when allowing peer effects to be heterogeneous by gender, using data from higher grades or considering alternative specifications. The findings of the empirical study cast doubt on the effectiveness of programs that manipulate peer groups for better educational outcomes. MEASURING PEER EFFECTS IN ACADEMIC OUTCOMES
Survey of Consensus Protocols

Distributed ledger technology has gained wide popularity and adoption since the emergence of bitcoin in 2008 which is based on proof of work (PoW). It is a distributed, transparent and immutable database of records of all the transactions or events that have been shared and executed among the participants. All the transactions are verified and maintained by multiple nodes across a network without a central authority through a distributed cryptographic mechanism, a consensus protocol. It forms the core of this technology that not only validates the information appended to the ledger but also ensures the order in which it is appended across all the nodes. It is the foundation of its security, accountability and trust. While many researchers are working on improving the current protocol to be quantum resistant, fault-tolerant, and energy-efficient. Others are focused on developing different variants of the protocol, best suited for specific use cases. In this paper, we shall review different consensus protocols of distributed ledger technologies and their implementations. We shall also review their properties, concept and similar-work followed by a brief analysis.
Protective effects of omega‐3 fatty acids against Alzheimer's disease in rat brain endothelial cells

Omega‐3 fatty acids are well‐known unsaturated fatty acids that are essential for growth and development in animals. They primarily participate in the development of intelligence, the nervous system, and vision, and the metabolism of neurotransmitters. Omega‐3 fatty acids have been widely studied in the treatment of Alzheimer's disease (AD). Omega‐3 fatty acids are known to have neuroprotective effects due to their antioxidant capacity. Rotenone has been shown to induce neurotoxicity in vitro.
Entity-Relationship Search over the Web

Entity-Relationship (E-R) Search is a complex case of Entity Search where the goal is to search for multiple unknown entities and relationships connecting them. We assume that a E-R query can be decomposed as a sequence of sub-queries each containing keywords related to a specific entity or relationship. We adopt a probabilistic formulation of the E-R search problem. When creating specific representations for entities (e.g. context terms) and for pairs of entities (i.e. relationships) it is possible to create a graph of probabilistic dependencies between sub-queries and entity plus relationship representations. To the best of our knowledge this represents the first probabilistic model of E-R search. We propose and develop a novel supervised Early Fusion-based model for E-R search, the Entity-Relationship Dependence Model (ERDM). It uses Markov Random Field to model term dependencies of E-R sub-queries and entity/relationship documents. We performed experiments with more than 800M entities and relationships extractions from ClueWeb-09-B with FACC1 entity linking. We obtained promising results using 3 different query collections comprising 469 E-R queries, with results showing that it is possible to perform E-R search without using fix and pre-defined entity and relationship types, enabling a wide range of queries to be addressed.
Comparison of Nitrate and Perchlorate in Controlling Sulfidogenesis in Heavy Oil-Containing Bioreactors

Control of microbial reduction of sulfate to sulfide in oil reservoirs (a process referred to as souring) with nitrate has been researched extensively. Nitrate is reduced to nitrite, which is a strong inhibitor of sulfate-reducing bacteria (SRB). Perchlorate has been proposed as an alternative souring control agent. It is reduced to chlorate (ClO3-) and chlorite (ClO2-), which is dismutated to chloride and O2. These can react with sulfide to form sulfur. Chlorite is also highly biocidal. Here we compared the effectiveness of perchlorate and nitrate in inhibiting SRB activity in medium containing heavy oil from the Medicine Hat Glauconitic C (MHGC) field, which has a low reservoir temperature and is injected with nitrate to control souring. Using acetate, propionate and butyrate as electron donors, perchlorate-reducing bacteria (PRB) were obtained in enrichment culture and perchlorate-reducing Magnetospirillum spp. were isolated from MHGC produced waters. In batch experiments with MHGC oil as the electron donor, nitrate was reduced to nitrite and inhibited sulfate reduction. However, perchlorate was not reduced and did not inhibit sulfate reduction in these incubations. Bioreactor experiments were conducted with sand-packed glass columns, containing MHGC oil and inoculated with an oil-grown mesophilic SRB enrichment. Once active souring (reduction of 2 mM sulfate to sulfide) was observed, these were treated with nitrate and/or perchlorate. As in the batch experiments, 4 mM nitrate completely inhibited sulfide production, while partial inhibition occurred with 1 and 2 mM nitrate, but injection of 4 mM perchlorate did not inhibit sulfate reduction and perchlorate was not reduced. The enriched and isolated PRB were unable to use heavy oil components, like alkylbenzenes, which were readily used by nitrate-reducing bacteria. Hence perchlorate, injected into a low temperature heavy oil reservoir like the MHGC, may not be reduced to toxic intermediates making nitrate a preferable souring control agent.
Joint Tumor Segmentation in PET-CT Images Using Co-Clustering and Fusion Based on Belief Functions

Precise delineation of target tumor is a key factor to ensure the effectiveness of radiation therapy. While hybrid positron emission tomography-computed tomography (PET-CT) has become a standard imaging tool in the practice of radiation oncology, many existing automatic/semi-automatic methods still perform tumor segmentation on mono-modal images. In this paper, a co-clustering algorithm is proposed to concurrently segment 3D tumors in PET-CT images, considering that the two complementary imaging modalities can combine functional and anatomical information to improve segmentation performance. The theory of belief functions is adopted in the proposed method to model, fuse, and reason with uncertain and imprecise knowledge from noisy and blurry PET-CT images. To ensure reliable segmentation for each modality, the distance metric for the quantification of clustering distortions and spatial smoothness is iteratively adapted during the clustering procedure. On the other hand, to encourage consistent segmentation between different modalities, a specific context term is proposed in the clustering objective function. Moreover, during the iterative optimization process, clustering results for the two distinct modalities are further adjusted via a belief-functions-based information fusion strategy. The proposed method has been evaluated on a data set consisting of 21 paired PET-CT images for non-small cell lung cancer patients. The quantitative and qualitative evaluations show that our proposed method performs well compared with the state-of-the-art methods.
Changes in temperature alter the relationship between biodiversity and ecosystem functioning

Significance Empirical evidence for the response of ecosystem functioning to the combined effects of warming and biodiversity loss is scarce. We show that warming and biodiversity loss interact synergistically, impairing the functioning of microbial communities. We found that as temperatures departed from ambient conditions more species were required to maintain ecosystem functioning. Our results suggest interspecific complementarity increased under thermal stress and high-diversity communities that seemed functionally redundant at ambient temperature became more functionally unique as temperatures changed. Biodiversity may therefore be even more important than previously anticipated when considering the impacts of multiple facets of environmental change. Global warming and the loss of biodiversity through human activities (e.g., land-use change, pollution, invasive species) are two of the most profound threats to the functional integrity of the Earth’s ecosystems. These factors are, however, most frequently investigated separately, ignoring the potential for synergistic effects of biodiversity loss and environmental warming on ecosystem functioning. Here we use high-throughput experiments with microbial communities to investigate how changes in temperature affect the relationship between biodiversity and ecosystem functioning. We found that changes in temperature systematically altered the relationship between biodiversity and ecosystem functioning. As temperatures departed from ambient conditions the exponent of the diversity-functioning relationship increased, meaning that more species were required to maintain ecosystem functioning under thermal stress. This key result was driven by two processes linked to variability in the thermal tolerance curves of taxa. First, more diverse communities had a greater chance of including species with thermal traits that enabled them to maintain productivity as temperatures shifted from ambient conditions. Second, we found a pronounced increase in the contribution of complementarity to the net biodiversity effect at high and low temperatures, indicating that changes in species interactions played a critical role in mediating the impacts of temperature change on the relationship between biodiversity and ecosystem functioning. Our results highlight that if biodiversity loss occurs independently of species’ thermal tolerance traits, then the additional impacts of environmental warming will result in sharp declines in ecosystem function.
Recent Strategies for the Diagnosis of Early Lyme Disease

Lyme disease (LD) is the most common tick-borne disease in the Northern Hemisphere. As the most prevalent vector-borne disease in the USA, LD affects 300,000 human cases each year. LD is caused by inoculation of the bacterial spirochete, Borrelia burgdorferi sensu lato, from an infected tick. If not treated quickly and completely, the bacteria disseminate from the tick's biting site into multiple organs including the joints, heart, and brain. Thus, the best outcome from medical intervention can be expected with early detection and treatment with antibiotics, prior to multi-organ dissemination. In the absence of a characteristic rash, LD is diagnosed using serological testing involving enzyme-linked immunosorbent assay (ELISA) followed by western blotting, which is collectively known as the two-tier algorithm. These assays detect host antibodies against the bacteria, but are hampered by low sensitivity, which can miss early LD cases. This review discusses the application of some current assays for diagnosing LD clinically, thus providing a foundation for exploring newer techniques being developed in the laboratory for more sensitive detection of early LD.
Control of uniflagellar soft robots at low Reynolds number using buckling instability

In this paper, we analyze the inverse dynamics and control of a bacteria-inspired uniflagellar robot in a fluid medium at low Reynolds number. Inspired by the mechanism behind the locomotion of flagellated bacteria, we consider a robot comprising a flagellum—a flexible helical filament—connected to a spherical head. The flagellum rotates about the head at a controlled angular velocity and generates a propulsive force that moves the robot forward. When the angular velocity exceeds a threshold value, the hydrodynamic force exerted by the fluid can cause the soft flagellum to buckle, characterized by a dramatic change in its shape. In this computational study, a fluid–structure interaction model that combines Discrete Elastic Rods algorithm with Lighthill's Slender Body Theory is employed to simulate the locomotion and deformation of the robot. We demonstrate that the robot can follow a prescribed path in three-dimensional space by exploiting buckling of the flagellum. The control scheme involves only a single (binary) scalar input—the angular velocity of the flagellum. By triggering the buckling instability at the right moment, the robot can follow the path in three-dimensional space. We also show that the complexity of the dynamics of the helical filament can be captured using a deep neural network, from which we identify the input–output functional relationship between the control input and the trajectory of the robot. Furthermore, our study underscores the potential role of buckling in the locomotion of natural bacteria.
Automatic Music Playlist Continuation via Neighbor-based Collaborative Filtering and Discriminative Reweighting/Reranking

The focus of RecSys Challenge 2018 is automatic playlist continuation (APC), which refers to the task of adding one or more tracks to a playlist in a manner that does not alter the intended characteristics of the original playlist. This paper presents our approach to this challenge. We adopted neighbor-based collaborative filtering approaches since they are able to deal with large datasets in an efficient and effective way, and have previously been shown to perform well on recommendation problems with similar characteristics. We show that by choosing an appropriate similarity function that properly accounts for the list-song similarities, simple neighbor-based methods can still achieve highly competitive performance on the MPD data, meanwhile, by using a set of techniques that discriminantly finetune the recommendation lists produced by neighbor-based methods, the overall recommendation accuracy can be improved significantly. By using the proposed approach, our team HAIR was able to attain the 6th place in the competition. We have open-sourced our implementation on https://github.com/LauraBowenHe/Recsys-Spotify-2018-challenge.
Message scheduling to reduce AFDX jitter in a mixed NoC/AFDX architecture

Current avionics architecture are based on an avionics full duplex switched Ethernet network (AFDX) that interconnects end systems. Avionics functions exchange data through Virtual Links (VLs), which are static flows with bounded bandwidth. The jitter for each VL at AFDX entrance has to be less than 500 μs. This constraint is met, thanks to end system scheduling. The interconnection of many-cores by an AFDX backbone is envisioned for future avionics architecture. The principle is to distribute avionics functions on these many-cores. Many-cores are based on simple cores interconnected by a Network-on-Chip (NoC). The allocation of functions on the available cores as well as the transmission of flows on the NoC has to be performed in such a way that the jitter for each VL at AFDX entrance is still less than 500 μs. A first solution has been proposed, where each function manages the transmission of its VLs. The idea of this solution is to distribute functions on each many-core in order to minimize contentions for VLs which concern functions allocated on different many-cores. In this paper, we consider that VL transmissions are managed by a single task in each many-core. We propose to construct a scheduling table executed by this task using an Integer Linear Program. The access to the Ethernet interface is then only allowed to one VL leading to a significant reduction of the jitter.
An empirical study of design discussions in code review

Background: Code review is a well-established software quality practice where developers critique each others' changes. A shift towards automated detection of low-level issues (e.g., integration with linters) has, in theory, freed reviewers up to focus on higher level issues, such as software design. Yet in practice, little is known about the extent to which design is discussed during code review. Aim: To bridge this gap, in this paper, we set out to study the frequency and nature of design discussions in code reviews. Method: We perform an empirical study on the code reviews of the OpenStack Nova (provisioning management) and Neutron (networking abstraction) projects. We manually classify 2,817 review comments from a randomly selected sample of 220 code reviews. We then train and evaluate classifiers to automatically label review comments as design related or not. Finally, we apply the classifiers to a larger sample of 2,506,308 review comments to study the characteristics of reviews that include design discussions. Results: Our manual analysis indicates that (1) design discussions are still quite rare, with only 9% and 14% of Nova and Neutron review comments being related to software design, respectively; and (2) design feedback is often constructive, with 73% of the design-related comments also providing suggestions to address the concerns. Furthermore, our classifiers achieve a precision of 59%-66% and a recall of 70%-78%, outperforming baselines like zeroR by 43 percentage points in terms of F1-score. Finally, code changes that have design-related feedback have a statistically significantly increased rate of abandonment (Pearson χ2 test, DF=1, p < 0.001). Conclusion: Design-related discussion during code review is still rare. Since design discussion is a primary motivation for conducting code review, more may need to be done to encourage such discussions among contributors.
The role of cellular contact and TGF-beta signaling in the activation of the epithelial mesenchymal transition (EMT)

ABSTRACT The epithelial mesenchymal transition (EMT) is one step in the process through which carcinoma cells metastasize by gaining the cellular mobility associated with mesenchymal cells. This work examines the dual influence of the TGF-β pathway and intercellular contact on the activation of EMT in colon (SW480) and breast (MCF7) carcinoma cells. While the SW480 population revealed an intermediate state between the epithelial and mesenchymal states, the MC7 cells exhibited highly adhesive behavior. However, for both cell lines, an exogenous TGF-β signal and a reduction in cellular confluence can push a subgroup of the population towards the mesenchymal phenotype. Together, these results highlight that, while EMT is induced by the synergy of multiple signals, this activation varies across cell types.
Measuring human values in software engineering

Background: Human values, such as prestige, social justice, and financial success, influence software production decision-making processes. While their subjectivity makes some values difficult to measure, their impact on software motivates our research. Aim: To contribute to the scientific understanding and the empirical investigation of human values in Software Engineering (SE). Approach: Drawing from social psychology, we consider values as mental representations to be investigated on three levels: at a system (L1), personal (L2), and instantiation level (L3). Method: We design and develop a selection of tools for the investigation of values at each level, and focus on the design, development, and use of the Values Q-Sort. Results: From our study with 12 software practitioners, it is possible to extract three values `prototypes' indicative of an emergent typology of values considerations in SE. Conclusions: The Values Q-Sort generates quantitative values prototypes indicating values relations (L1) as well as rich personal narratives (L2) that reflect specific software practices (L3). It thus offers a systematic, empirical approach to capturing values in SE.
Practical Aspects of LTE Network Design and Deployment

This paper covers the practical aspects of commercial long term evolution (LTE) network design and deployment. The end-to-end architecture of the LTE network and different deployment scenarios are presented. Moreover, the LTE coverage and link budget aspects are discussed in details. Theoretical and practical throughputs of LTE system are analyzed. In addition, capacity dimensioning of LTE system is explained in details and compared with the evolved high-speed packet access (HSPA+) system. Additionally, the quality of service (QoS) of the LTE system and the end-to-end implementation scenarios along with testing results are presented. Finally, the latency of the LTE system is analyzed and compared with the HSPA+ system. This paper can be used as a reference for best practices in LTE network design and deployment.
A high glucose diet induces autophagy in a HLH-30/TFEB-dependent manner and impairs the normal lifespan of C. elegans

A high-glucose diet (HGD) is associated with the development of metabolic diseases that decrease life expectancy, including obesity and type-2 diabetes (T2D); however, the mechanism through which a HGD does so is still unclear. Autophagy, an evolutionarily conserved mechanism, has been shown to promote both cell and organismal survival. The goal of this study was to determine whether exposure of Caenorhabditis elegans to a HGD affects autophagy and thus contributes to the observed lifespan reduction under a HGD. Unexpectedly, nematodes exposed to a HGD showed increased autophagic flux via an HLH-30/TFEB-dependent mechanism because animals with loss of HLH-30/TFEB, even those with high glucose exposure, had an extended lifespan, suggesting that HLH-30/TFEB might have detrimental effects on longevity through autophagy under this stress condition. Interestingly, pharmacological treatment with okadaic acid, an inhibitor of the PP2A and PP1 protein phosphatases, blocked HLH-30 nuclear translocation, but not TAX-6/calcineurin suppression by RNAi, during glucose exposure. Together, our data support the suggested dual role of HLH-30/TFEB and autophagy, which, depending on the cellular context, may promote either organismal survival or death.