Miracle-dz/UniFAR-FTUs huggingface dataset:
Neuronal CXCL10/CXCR3 Axis Mediates the Induction of Cerebral Hyperexcitability by Peripheral Viral Challenge

Peripheral infections can potently exacerbate neuropathological conditions, though the underlying mechanisms are poorly understood. We have previously demonstrated that intraperitoneal (i.p.) injection of a viral mimetic, polyinosinic-polycytidylic acid (PIC) induces a robust generation of CXCL10 chemokine in the hippocampus. The hippocampus also features hyperexcitability of neuronal circuits following PIC challenge. The present study was undertaken to determine the role of CXCL10 in mediating the development of hyperexcitability in response to PIC challenge. Briefly, young female C57BL/6 mice were i.p. injected with PIC, and after 24 h, the brains were analyzed by confocal microscopy. CXCL10 staining of neuronal perikarya and a less intense staining of the neuropil was observed in the hippocampus and cortex. CXCL10 staining was also evident in a subpopulation of astrocytes, whereas microglia were CXCL10 negative. CXCR3, the cognate receptor of CXCL10 was present exclusively on neurons, indicating that the CXCL10/CXCR3 axis operates through an autocrine/paracrine neuronal signaling. Blocking cerebral CXCR3 through intracerebroventricular injection of a specific inhibitor, AMG487, abrogated PIC challenge-induced increase in basal synaptic transmission and long-term potentiation (LTP), as well as the reduction of paired-pulse facilitation (PPF), in the hippocampus. The PIC-mediated abolishment of hippocampal long-term depression (LTD) was also restored after administration of AMG487. Moreover, CXCR3 inhibition attenuated seizure hypersensitivity induced by PIC challenge. The efficacy of AMG487 strongly strengthens the notion that CXCL10/CXCR3 axis mediates the induction of cerebral hyperexcitability by PIC challenge.
Acute Effect of Kinesiology Taping on Postural Stability in Individuals With Unilateral Chronic Ankle Instability

Background Chronic ankle instability (CAI), which is characterized by deficient postural control, could be improved through kinesiology taping (KT). However, the effect of KT on postural control in CAI individuals is controversial. Therefore, this study aimed to investigate the acute effect of KT on postural control through computerized dynamic posturography (CDP) and self-perceived sensation in CAI individuals. Methods Participants with CAI received four different ankle treatments randomly, including KT, athletic taping (AT), sham taping (ST), and no taping (NT). A series of postural stability measurements was performed using CDP subsequently. The measurements included sensory organization test (SOT), unilateral stance (US), limit of stability (LOS), motor control test (MCT), and adaption test (ADT). In addition, self-perceived sensation was measured through visual analog scaling. Repeated measures analysis of variance was conducted to determine whether the difference among KT, AT, ST, and NT was significant; Bonferroni test was used for post hoc analysis. Results No significant difference was observed for parameters in SOT, US, and LOS in four different taping treatments. In MCT, the amplitude scaling scores of KT were 35.87% significantly lower than that of NT [p < 0.001, 95% confidence interval (CI) = 0.548–1.795] in forward-small slip and 21.58% significantly lower than that of ST (p = 0.035, 95% CI = 0.089–3.683) in backward-large slip. In ADT, sway energy scores were 7.59% significantly greater in ST than in AT (p = 0.028, 95% CI = −8.343 to −0.320). For perceived stability, KT was significantly greater than ST (p < 0.001, 95% CI = 0.552–1.899) and NT (p < 0.001, 95% CI = 0.797–2.534), and AT was significantly greater than ST (p = 0.001, 95% CI = 0.423–2.246) and NT (p < 0.001, 95% CI = 0.696–2.852). For perceived comfort, KT was significantly greater than AT (p = 0.001, 95% CI = 0.666–3.196) and NT (p = 0.031, 95% CI = 0.074–2.332), and ST was significantly greater than AT (p = 0.007, 95% CI = 0.349–2.931). Conclusion KT and AT have limited effect to facilitate postural control for CAI individuals during SOT, US, and LOS. However, KT and AT could provide effective support to cope with sudden perturbation in MCT and ADT. Moreover, KT provided excellent perceived stability and comfort, whereas AT provided excellent perceived stability but least comfort.
Seeking the Roles for Fungal Small-Secreted Proteins in Affecting Saprophytic Lifestyles

Small secreted proteins (SSPs) comprise 40–60% of the total fungal secretome and are present in fungi of all phylogenetic groups, representing the entire spectrum of lifestyles. They are characteristically shorter than 300 amino acids in length and have a signal peptide. The majority of SSPs are coded by orphan genes, which lack known domains or similarities to known protein sequences. Effectors are a group of SSPs that have been investigated extensively in fungi that interact with living hosts, either pathogens or mutualistic systems. They are involved in suppressing the host defense response and altering its physiology. Here, we aim to delineate some of the potential roles of SSPs in saprotrophic fungi, that have been bioinformatically predicted as effectors, and termed in this mini-review as “effector-like” proteins. The effector-like Ssp1 from the white-rot fungus Pleurotus ostreatus is presented as a case study, and its potential role in regulating the ligninolytic system, secondary metabolism, development, and fruiting body initiation are discussed. We propose that deciphering the nature of effector-like SSPs will contribute to our understanding of development and communication in saprophytic fungi, as well as help, to elucidate the origin, regulation, and mechanisms of fungal-host, fungal-fungal, and fungal-bacterial interactions.
Micro Analysis to Enable Energy-Efficient Database Systems

CPU has been identified as the energy bottleneck for database systems and existing approaches only allow database systems to trade the performance for energy. However, our work show that cutting down the energy cost of database systems without losing the CPU performance is feasible. We first develop a measurement methodology to accurately evaluate the energy cost of different CPU micro-operations. Then three popular data-base systems with different setups and data sizes are used as benchmarks to explore the energy distribution on CPU micro-operations. Our experimental results show that L1 data cache (L1D cache) consumes 39%-67% of total CPU energy and it is definitely the energy bottleneck of database systems. This finding inspires us a novel idea on building energy-efficient database systems with customized CPU architecture that features low L1D cache energy cost. A proof-of-concept system is developed to evaluate this idea and the experimental results show that our solution can not only achieve 60% of peak energy saving but also gain further performance improvement.
Tracing nested data with structural provenance for big data analytics

Big data analytics systems such as Apache Spark natively support nested data formats since they offer operators to manipulate nested lists and complex types. Compared to flat data, nested data introduces further complexity and sources of error, e.g., when developing data processing pipelines, performing auditing tasks, or performance tuning. To ease such tasks, we propose a provenance-based solution tailored to nested data processing in big data analytics systems. Unlike previous solutions, it combines (i) tracing provenance of nested data with (ii) efficient and scalable provenance processing, leveraging a newly proposed structural provenance that traces structural manipulations through data processing pipelines in addition to data. We provide a formal definition of structural provenance, as well as methods to efficiently capture and succinctly backtrace it. We implement them in our Pebble system in Apache Spark and validate its performance and usefulness on up to 500GB of real-world data.
skyex: an R Package for Entity Linkage

As the data is becoming bigger, more heterogeneous, and originating from different sources, the availability of the same information in different forms leads to various entity linkage problems. We demonstrate our skyex package, an R package that supports all three steps of entity linkage: blocking, pairwise comparison, and labeling. Thus, the user can solve the whole process using skyex , but not necessarily; the skyex modules are independent, meaning that the user can easily integrate them with other packages or even other environments. Additionally, we are the first to provide the implementation of two skyline-based algorithms ( SkyEx-F and SkyEx-D ) that can label the compared pairs without the need for weights, scoring functions, etc. skyex supports the typical workflow of entity linkage, using minimalist, user-friendly function calls.
Data Curation with Deep Learning

Data curation – the process of discovering, integrating, and cleaning data – is one of the oldest, hardest, yet inevitable data management problems. Despite decades of efforts from both researchers and practitioners, it is still one of the most time consuming and least enjoyable work of data scientists. In most organizations, data curation plays an important role so as to fully unlock the value of big data. Unfortunately, the current solutions are not keeping up with the ever-changing data ecosystem, because they often require substantially high human cost. Meanwhile, deep learning is making strides in achieving remarkable successes in multiple areas, such as image recognition, natural language processing, and speech recognition. In this vision paper, we explore how some of the fundamental innovations in deep learning could be leveraged to improve existing data curation solutions and to help build new ones. We identify interesting research opportunities and dispel common myths. We hope that the synthesis of these important domains will unleash a series of research activities that will lead to significantly improved solutions for many data curation tasks.
Entity Matching with Transformer Architectures - A Step Forward in Data Integration

Transformer architectures have proven to be very effective and provide state-of-the-art results in many natural language tasks. Theattention-basedarchitectureincombinationwith pre-training on large amounts of text lead to the recent breakthrough and a variety of slightly different implementations. In this paper we analyze how well four of the most recent attention-based transformer architectures (BERT[6], XLNet[33], RoBERTa[17] and DistilBERT [23]) perform on the task of entity matching - a crucial part of data integration. Entity matching (EM) is the task of finding data instances that refer to the same real-world entity. It is a challenging task if the data instances consist of long textual data or if the data instances are "dirty" due to misplaced values. To evaluate the capability of transformer architectures and transfer-learning on the task of EM, we empirically compare the four approaches on inherently difficult data sets. We show that transformer architectures outperform classical deep learning methods in EM[7, 20] by an average margin of 27.5%.
Highly Secure Privacy-Preserving Outsourced k-Means Clustering under Multiple Keys in Cloud Computing

Data clustering is the unsupervised classification of data records into groups. As one of the steps in data analysis, it has been widely researched and applied in practical life, such as pattern recognition, image processing, information retrieval, geography, and marketing. In addition, the rapid increase of data volume in recent years poses a huge challenge for resource-constrained data owners to perform computation on their data. This leads to a trend that users authorize the cloud to perform computation on stored data, such as keyword search, equality test, and outsourced data clustering. In outsourced data clustering, the cloud classifies users’ data into groups according to their similarities. Considering the sensitive information in outsourced data and multiple data owners in practical application, it is necessary to develop a privacy-preserving outsourced clustering scheme under multiple keys. Recently, Rong et al. proposed a privacy-preserving outsourced k-means clustering scheme under multiple keys. However, in their scheme, the assistant server (AS) is able to extract the ratio of two underlying data records, and key management server (KMS) can decrypt the ciphertexts of owners’ data records, which break the privacy security. AS can even reduce all data records if it knows one of the data records. To solve the aforementioned problem, we propose a highly secure privacy-preserving outsourced k-means clustering scheme under multiple keys in cloud computing. In this paper, noncolluded cloud computing service (CCS) and KMS jointly perform clustering over the encrypted data records without exposing data privacy. Specifically, we use BCP encryption which has additive homomorphic property and AES encryption to double encrypt data records, where the former cryptosystem prevents CCS from obtaining any useful information from received ciphertexts and the latter one protects data records from being decrypted by KMS. We first define five protocols to realize different functions and then present our scheme based on these protocols. Finally, we give the security and performance analyses which show that our scheme is comparable with the existing schemes on functionality and security.
Differentially-Private Next-Location Prediction with Neural Networks

The emergence of mobile apps (e.g., location-based services, geo-social networks, ride-sharing) led to the collection of vast amounts of trajectory data that greatly benefit the understanding of individual mobility. One problem of particular interest is next-location prediction, which facilitates location-based advertising, point-of-interest recommendation, traffic optimization, etc. However, using individual trajectories to build prediction models introduces serious privacy concerns, since exact where-abouts of users can disclose sensitive information such as their health status or lifestyle choices. Several research efforts focused on privacy-preserving next-location prediction, but they have serious limitations: some use outdated privacy models (e.g., k-anonymity), while others employ learning models with limited expressivity (e.g., matrix factorization). More recent approaches (e.g., DP-SGD) integrate the powerful differential privacy model with neural networks, but they provide only generic and difficult-to-tune methods that do not perform well on location data, which is inherently skewed and sparse. We propose a technique that builds upon DP-SGD, but adapts it for the requirements of next-location prediction. We focus on user-level privacy, a strong privacy guarantee that protects users regardless of how much data they contribute. Central to our approach is the use of the skip-gram model, and its negative sampling technique. Our work is the first to propose differentially-private learning with skip-grams. In addition, we devise data grouping techniques within the skip-gram framework that pool together trajectories from multiple users in order to accelerate learning and improve model accuracy. Experiments conducted on real datasets demonstrate that our approach significantly boosts prediction accuracy compared to existing DP-SGD techniques.
Enhancement of Energy Yield for Ozone Production via Packed-Bed Reactors

The present work aims to enhance the energy yield of ozone production via packed-bed reactors. It has been experimentally demonstrated that ozone concentration and corresponding energy yield achieved by packed-bed reactors are significantly higher than that achieved by DBD only. The so-called packed-bed reactor is constructed by packing granular dielectric pellets within a DBD reactor. Two kinds of dielectric materials including glass beads and Al2O3 pellets are tested. Experimental results indicate that an ozone generator packed with Al2O3 pellets results in a higher ozone production compared with one packed with glass beads. The maximum ozone production takes place when Al2O3 pellets with diameter of 2 mm are packed. The maximum ozone concentration, ozone production rate, and energy yield achieved in this study are 61 gO3/m3, 3.7 gO3/hr, and 173 gO3/kWh, respectively. The highest ozone concentration and energy yield achieved with the packed-bed reactor are about 8 and 12 times high as those with DBD reactor, respectively. Although the packed-bed reactors have a shortcoming of high temperature, it can be solved by adding a cooling system and the ozone generation can be improved thereof. As a result, the packed-bed reactor is a promising and state-of-the-art technology for ozone generation based on this study.
Production of Australian English language-specific variability

This study presents acoustic and articulatory (EMA) data for the high rounded central vowel at different prosodic boundaries. Data are from three speakers of Australian English. Overall, there is very little variability in production of this vowel according to prosodic boundary, with the two female speakers showing slightly more variability than the male speaker. In particular, variability in F2 is limited, suggesting that the vowel is truly central and cannot be considered a back vowel phonologically. The present results are compared with results presented in Tabain & Perrier from three French speakers producing the high back rounded vowel /u/. The differences in articulatory strategies and in acoustic variability are discussed with respect to the vowel inventory of each language. It is speculated that the back vowel /u:/ has become centralized in several dialects of English due to ease of articulation considerations, as part of a strategy to maintain formant cues indicative of a high rounded vowel.
AFFECT

Abstract Somewhere between use and mere whim there is a place for the expressivity of affect as a concept. This paper raises the question of how the concept of affect might be mobilized without reducing its expressions to the logic of work. We suggest that the very attempt to put affect to work in order to solve pressing problems may be symptomatic of an anxiety to master the events of the world. With this in mind, we make a case for the importance of Georges Bataille's critique of an instrumentalist form of thinking, which reduces events to objects of human sensemaking. Bataille's “general economy” opens onto all that the restricted economy of use negates; namely, that which exceeds our efforts as humans to make sense of, and thus appropriate, events. Ultimately, Bataille's antihumanist thought limits the potential of the gift economy, by rendering it the negative of the social order. We argue that a more posthumanist thought can realize the immanent potential of affect and apprehend its gift to thinking.
Using assessment criteria as learning criteria: a case study in psychology

In this paper it is argued that the current trend of making assessment criteria more explicit in higher education may have a deleterious effect on students' learning. Helping students to concentrate on assessment criteria paradoxically means that they may take a strategic approach and end up focusing on the superficial aspects of their assessment tasks, rather than engaging in meaningful learning activity. One solution might be to re‐conceptualize assessment criteria as ‘learning criteria’ using Biggs' principle of constructive alignment in curriculum development and delivery. To illustrate how this can work in practice, a case study is presented detailing the development of a counselling psychology module over several years to progressively incorporate a text‐based adaptation of the problem‐based learning approach. Student evaluations of the approach are presented together with some examples of feedback given on students' work to demonstrate the effects on students' understanding and functioning knowledge
Study of iron deficiency as a risk factor for first episode of simple febrile siezure

Febrile seizures are seizures that occur between the age of 6 month to 60 month with a temperature of 100.4f or higher,that are not the result of central nervous system infection or any metabolic imbalance and that occur in the absence of a history of prior afebrile seizure. Febrile seizures are the commonest cause of seizures in children, occuring in 2-5% of children. Complications like aspiration can occur during each episode of seizures. Febrile seizure episodes are agonizing to the parent and child and can cause psychological trauma to both. The ABSTRACT
Experiences of patients with implantable cardioverter defibrillator in Turkey: A qualitative study

Background. There has been an increase in the number of patients with implantable cardioverter defibrillator (ICD). It is important to understand ICD patients’ experiences with it. Aim. The aim of this study was to describe experiences of patients with implantable cardioverter defibrillator (ICD). Methodology. A qualitative approach was used. Focus group interviews were used to obtain data from 19 patients who were implanted cardioverter defibrillator at two centers in Izmir, Turkey. The patients were assigned into four groups. The data was analyzed using qualitative content analysis. Results. The analysis revealed six main themes: activities of daily living, social life, familial relationships, emotional changes, implantable cardioverter defibrillator shocks and experiences with receiving information and counselling from health care providers. Conclusions. It can be concluded that patients with ICD experience physical and psychological problems and are not offered the education they need. To reduce the fears of the patients and their families and to prepare them for possible life style changes, comprehensive training programs that start in the pre-implantation period and continue into the post-implantation period should be organized.
Cultural identity in teaching across borders: mainland Chinese pre-service teachers in Hong Kong

This study explores transformations in the cultural identities of a group of pre-service teachers from mainland China during their educational experiences in Hong Kong, and how these transformations subsequently impact their professional identity. Individual and focus group interviews were conducted with 16 cross-border pre-service teachers from a teacher education institution. Findings demonstrate that 1) the participants recast their extant ideologies and cultural beliefs in response to multiple influences in their new context, enabling them to move beyond pre-established teaching values to re-construct their teaching identity; and 2) some participants constructed a bicultural and multilingual identity to gain legitimacy in the host context. The findings indicate that a more supportive context that provides more room for cultural awareness should be co-constructed by local and non-local pre-service teachers, institutions and policy makers. The study extends understanding of the interconnected relations between teacher identity and historical and social discourses.