Miracle-dz/UniFAR-FTUs huggingface dataset:
Why cannot long-term cascade be predicted? Exploring temporal dynamics in information diffusion processes

Predicting information cascade plays a crucial role in various applications such as advertising campaigns, emergency management and infodemic controlling. However, predicting the scale of an information cascade in the long-term could be difficult. In this study, we take Weibo, a Twitter-like online social platform, as an example, exhaustively extract predictive features from the data, and use a conventional machine learning algorithm to predict the information cascade scales. Specifically, we compare the predictive power (and the loss of it) of different categories of features in short-term and long-term prediction tasks. Among the features that describe the user following network, retweeting network, tweet content and early diffusion dynamics, we find that early diffusion dynamics are the most predictive ones in short-term prediction tasks but lose most of their predictive power in long-term tasks. In-depth analyses reveal two possible causes of such failure: the bursty nature of information diffusion and feature temporal drift over time. Our findings further enhance the comprehension of the information diffusion process and may assist in the control of such a process.
Evaluation of the relationship between window use and physical environmental variables: consistency, seasonality and diversity

Most of the window use models developed for building energy simulations include physical environmental variables as drivers. Even though it is a common approach to include these variables, the validity of this approach can be questioned based on observations in the literature regarding the consistency and seasonality of the relationship between these variables and the window use. Additionally, it was questioned whether this approach could capture the inter-occupant diversity. To assess the extent of the uncertainties, modelling methods from the literature were applied to a case study. The results revealed that a large share of the variance in window use can be attributed to the season and the household-ID. This indicates that the window use varied across the year but was stable within one season, and that these behaviours differed significantly between households. Thus occupants interacted with windows according to seasonal habits, more so then according to momentaneous environmental conditions.
Tightly-coupled inhibitory and excitatory functional networks in the early visual cortex

Intracortical inhibition plays a critical role in shaping activity patterns in the mature cortex. However, little is known about the structure of inhibition in early development prior to the onset of sensory experience, a time when spontaneous activity exhibits long-range correlations predictive of mature functional networks. Here, using calcium imaging of GABAergic neurons in the early ferret visual cortex, we show that spontaneous activity in inhibitory neurons is already highly organized into distributed modular networks before visual experience. Inhibitory neurons exhibit spatially modular activity with long-range correlations and precise local organization that is in quantitative agreement with excitatory networks. Furthermore, excitatory and inhibitory networks are strongly co-aligned at both millimeter and cellular scales. These results demonstrate a remarkable degree of organization in inhibitory networks early in the developing cortex, providing support for computational models of self-organizing networks and suggesting a mechanism for the emergence of distributed functional networks during development.
“This barbaric terrorist organization”: Orientalism and Barack Obama’s language on ISIS

ABSTRACT This article explores US foreign policy discourse surrounding the rise of ISIS, from 2014 to 2016. Specifically, it asks how Obama constructed ISIS as a threatening Other at this time. This research responds to a gap in the literature concerning official Western discourses on ISIS violence, and partially fills this by tracing the formation of US foreign policy narratives and exploring how this drew from existing discourses and older Orientalist tropes. Conducting a discourse analysis of official statements, this paper shows how Obama modified his language to elevate the level of the threat in official discourse. It argues that he achieved this by drawing upon longstanding racialised and Orientalist archives of knowledge, effectively resituating the terrorist Other within a more markedly Orientalist discourse. Finally, the article concludes that by (re)producing the traditional Orientalist character of the barbarian as an existential threat to a Eurocentric idea of Western civilisation, Obama made possible an approach to intervention that prioritised air power, targeted assassinations and international cooperation to defend the “civilised” world. This had the effect of stigmatising Muslim communities who were left occupying a discursive space between the civilised West and the barbaric ISIS.
Flood Forecasting of Malaysia Kelantan River using Support Vector Regression Technique

The rainstorm is believed to contribute flood disasters in upstream catchments, resulting in further consequences in downstream area due to rise of river water levels. Forecasting for flood water level has been challenging, presenting complex task due to its nonlinearities and dependencies. This study proposes a support vector machine regression model, regarded as a powerful machine learningbased technique to forecast flood water levels in downstream area for different lead times. As a case study, Kelantan River in Malaysia has been selected to validate the proposed model. Four water level stations in river basin upstream were identified as input variables. A river water level in downstream area was selected as output of flood forecasting model. A comparison with several benchmarking models, including radial basis function (RBF) and nonlinear autoregressive with exogenous input (NARX) neural network was performed. The results demonstrated that in terms of RMSE error, NARX model was better for the proposed models. However, support vector regression (SVR) demonstrated a more consistent performance, indicated by the highest coefficient of determination value in twelve-hour period ahead of forecasting time. The findings of this study signified that SVR was more capable of addressing the long-term flood forecasting problems.
An indigenous African framework for counterterrorism: decolonising Kenya’s approach to countering “Al-Shabaab-ism”

ABSTRACT The terrorism discourse in the Kenyan context dates back to the colonial and post-colonial years with the country having suffered its most devastating terrorist attacks in the period since 1998. Despite a series of dreadful experiences, it was not until 9/11 that the country’s counterterrorism discourse took a serious upward trajectory. This was after Kenya’s elevation by her Western allies as an “anchor” state in the Global War on Terror (GWOT). This development illustrates how Kenya’s security architecture is hugely dependent on Western counterterrorism frameworks, strategies, and at times, security priorities. In this regard, the existing counterterrorism frameworks not only perpetuate colonial continuities but also neglect the national contextual peculiarities. This article, thus, explores how Western constructions of terrorism permeate Kenya’s counterterrorism, and deny subaltern actors the opportunity to participate in developing intervention priorities and owning the strategies. Our analysis of the explicit knowledge predispositions between Western and the local constructions of counterterrorism, consequently, suggest some parallels between colonial continuities and the state-owned interventions. We, therefore, seek to deconstruct the universality of knowledge on counterterrorism, and argue for increased recognition and inclusion of indigenous African counterterrorism approaches which have been obscured from mainstream knowledge systems.
A Twitter analysis of World Pharmacists Day 2020 images: Sending the wrong messages

Background: Pharmacists are often depicted as dispensers of medication as opposed to health professionals who provide patient care. Our objective was to identify how pharmacists’ roles were portrayed in images on Twitter for World Pharmacists Day (WPD) 2020. Methods: A qualitative content analysis was undertaken to evaluate the images of pharmacists on WPD. Tweets were included that had a photo or image, used 1 of 5 WPD hashtags and were posted between September 24 and 26, 2020. Thematic analysis was performed independently by 2 investigators. Tweets were categorized into 5 groups: 1) drug distribution roles, 2) patient care roles, 3) no described roles, 4) not professional/unprofessional roles and 5) not relevant. Subgroup analysis was performed for the users who posted the tweets. Results: Of the 970 tweets analyzed, only 11% of the overall tweets portrayed the patient care roles of pharmacists, whereas 51% portrayed drug distribution roles and 29% did not describe any particular roles of pharmacists. These proportions were similar between subgroups of tweeters. Discussion: WPD is intended to promote and advocate for the pharmacy profession. The results of our study show poor messaging of pharmacists’ roles and reflect a missed opportunity to showcase the full scope of pharmacy practice. Conclusion: Based on the images tweeted on WPD 2020, the diversity of pharmacists’ practice as skilled health care practitioners was lost in a sea of tweets portraying pharmacists’ roles in drug distribution. We hope that pharmacists and pharmacy organizations will awaken to this self-induced problem for WPD 2021. Can Pharm J (Ott) 2021;154(5):xx-xx.
The STAT5-IRF4-BATF pathway drives heightened epigenetic remodeling in naïve CD4+ T cell responses of older adults

T cell aging is a complex process combining the emergence of cellular defects with activation of adaptive mechanisms. Generation of T cell memory is impaired, while a low-inflammatory state is induced, in part due to effector T cells. To determine whether age-associated changes in T cell fate decisions occur early after T cell activation, we profiled the longitudinal transcriptional and epigenetic landscape induced by TCR stimulation comparing naïve CD4+ T cells from young and older adults. In spite of attenuated TCR signaling, activation-induced remodeling of the epigenome increased with age, culminating in heightened BATF and BLIMP1 activity. Single cell studies, integrating ATAC-seq and RNA-seq data, identified increases in dysfunctional and in effector T cells and a decrease in BACH2-expressing memory cell precursors. STAT5 activation, in part due to a decline in HELIOS and aberrant IL-2 receptor expression, accounted for the induction of transcription factor networks favoring effector cell differentiation.
MS‐Driven Metabolic Alterations Are Recapitulated in iPSC‐Derived Astrocytes

Objective Astrocytes play a significant role in the pathology of Multiple Sclerosis (MS). Nevertheless, for ethical reasons, most of the studies in these cells were performed on the Experimental Autoimmune Encephalomyelitis model. As there are significant differences between human and mouse cells, we aimed here to better characterize astrocytes from patients with MS (PwMS), focusing mainly on mitochondrial function and cell metabolism. Methods We obtained and characterized induced pluripotent stem cell (iPSC)-derived astrocytes from three PwMS and three unaffected controls and performed functional assays including electron microscopy, flow cytometry, cytokine measurement, gene expression, in situ respiration, and metabolomics. Results We detected several differences in MS astrocytes including: (i) enrichment of genes associated with mitophagy and neurodegeneration, (ii) increased mitochondrial fission and decreased mitochondrial to nuclear DNA ratio, indicating disruption of mitochondrial content, (iii) increased production of superoxide and MS-related proinflammatory chemokines, (iv) increased electron transport capacity and proton leak, in line with the increased oxidative stress, and (v) a distinct metabolic profile, with a deficiency in amino acid catabolism and increased sphingolipid metabolism, which have already been linked to MS. Interpretation To our knowledge, this is the first study thoroughly describing the metabolic profile of iPSC-derived astrocytes from PwMS, and validating this model as a powerful tool to study disease mechanisms and to perform non-invasive drug targeting assays in vitro. Our findings recapitulate several disease features described in patients and provide new mechanistic insights into the metabolic rewiring of astrocytes in MS, which could be targeted in future therapeutic studies.
Intimate relationship among Nigerian university undergraduates: The predictive effects of self-esteem and identity

ABSTRACT This study examined self-esteem and identity as predictors of intimate relationship among Nigerian undergraduates. Two hundred and thirty eight (238) participants drawn from Nnamdi Azikiwe University, Awka participated in the study. A total of 103 (43.3%) were males while 135 (56.7%) were females. They were selected through simple random sampling technique. Their ages ranged from 17 to 30 years, with a mean age of 23.06 and standard deviation of 2.34. The instruments used were Experience in close relationship scale, Self-esteem Scale, and Aspect of Identity Scale. The design adopted was a cross-sectional predictive design. Based on this, Multiple Linear Regression was adopted as the statistical tool for data analysis. Three hypotheses were tested and the results showed that the first hypothesis, which stated that self-esteem would significantly and positively predict intimate relationship among undergraduates was accepted at (B =.138, p <.05). The second hypothesis, which stated that personal identity would negatively predict intimate relationship among undergraduates was accepted at (B = −.060, p <.05). And the third hypothesis, which stated that relational identity would significantly and positively predict intimate relationship among undergraduates was also accepted at (B =.166, p <.05). The researchers therefore recommended that parents and teachers should find a way of encouraging self-esteem development and independence among adolescents and youths and also teach students the various outcomes of intimate relationships and how to build and maintain a healthy relationship.
Decomposition and Interleaving for Variance Reduction of Post-click Metrics

In this study, we propose an efficient method for comparing the post-click metric (e.g., dwell time and conversion rate) of multiple rankings in online experiments. The proposed method involves (1) the decomposition of the post-click metric measurement of a ranking into a click model estimation and a post-click metric measurement of each item in the ranking, and (2) interleaving of multiple rankings to produce a single ranking that preferentially exposes items possessing a high population variance. The decomposition of the post-click metric measurement enables the free layout of items in a ranking and focuses on the measurement of the post-click metric of each item in the multiple rankings. The interleaving of multiple rankings reduces the sample variance of the items possessing a high population variance by optimizing a ranking to be presented to the users so that those items received more samples of the post-click metric. In addition, we provide a proof that the proposed method leads to the minimization of the evaluation error in the ranking comparison and propose two practical techniques to stabilize the online experiment. We performed a comprehensive simulation experiment and a real service setting experiment. The experimental results revealed that (1) the proposed method outperformed existing methods in terms of efficiency and accuracy, and the performance was especially remarkable when the input rankings shared many items, and (2) the two stabilization techniques successfully improved the evaluation accuracy and efficiency. The real service data from our experiments can be used to validate our experiments as well as investigate the user modeling and bandit algorithms.
Modality Effects When Simulating User Querying Tasks

When faced with an information need, different users are likely to issue different queries. A renewed interest in these user query variations has resulted in a number of collections, tasks, and studies which utilize multiple queries for each topic. The most commonly applied technique for generating query variations is to show a short backstory to a pool of crowdworkers, and ask each of them to provide a keyword query that they would expect to provide more information pertaining to the backstory. In this short paper we explore whether the length of the backstory and the mode in which the backstory is conveyed to crowdworkers affect the resulting queries. Our experiments demonstrate that both the length of the backstory and the mode in which the backstory is delivered influence the resultant query variations; and that there is a consequent downstream implication in terms of forming the judgment pools necessary to assess systems in the presence of query variations.
Effective and Privacy-preserving Federated Online Learning to Rank

Online Learning to Rank (OLTR) has been primarily studied in the centralised setting, where a central server is responsible to index the searchable data, collect the users' queries and search interactions, and optimize ranking models. A drawback of such a centralised OLTR paradigm is that it cannot guarantee user's privacy as all data (both the searchable one and the one related to user interactions) is collected by the server. In this paper, we propose a Federated OLTR method, called FPDGD, which leverages the state-of-the-art Pairwise Differentiable Gradient Descent (PDGD) and adapts it to the Federated Averaging framework. For a strong privacy guarantee, we further introduce a noise-adding clipping technique based on the theory of differential privacy to be used in combination with FPDGD. Empirical evaluation shows FPDGD significantly outperforms the only other federated OLTR method. In addition, FPDGD is more robust across different privacy guarantee requirements than the current method: our method is therefore more reliable for real-life applications.
Enhanced recovery after surgery (ERAS) in patients undergoing emergency laparotomy after trauma: a prospective, randomized controlled trial

Background The role of enhanced recovery after surgery (ERAS) has been established in elective operations. However, its role in emergency operations especially in trauma is under-recognized. The aim of this study was to explore the safety and efficacy of ERAS program in patients undergoing emergency laparotomy for trauma. Methods In this single-center study, patients who underwent emergency laparotomy after trauma were randomized to the ERAS protocol or conventional care. The ERAS protocol included early removal of catheters, early initiation of diet, use of postoperative prophylaxis and optimal usage of analgesia. The primary endpoint was duration of hospital stay. The secondary endpoints were recovery of bowel function, pain scores, complications and readmission rate. Results Thirty patients were enrolled in each arm. The ERAS group had significant reduction in duration of hospital stay (3.3±1.3 vs. 5.0±1.7; p<0.01). Time to remove nasogastric tube (1.1±0.1 vs. 2.2±0.9; p<0.01), urinary catheter (1.1±0.1 vs. 3.5±1.6; p<0.01), and drain (1.0±0.2 vs. 3.7±1.6; p<0.01) was shorter in the ERAS group. In ERAS group, there was earlier initiation of liquid diet (1.1±0.1 vs. 2.3±1.0; p<0.01) and solid diet (2.1±0.1 vs. 3.6±1.3; p<0.01). The usage of epidural analgesia (63% vs. 30%; p=0.01), non-steroidal anti-inflammatory drugs (93% vs. 67%; p-0.02) and deep vein thrombosis prophylaxis (100% vs. 70%; p<0.01) was higher in the ERAS group. There was no difference in the recovery of bowel function (2.4±1.0 vs. 2.1±0.9; p=0.15), pain scores (3.2±1.0 vs. 3.1±1.1; p=0.87), complications (27% vs. 23%; p=0.99) and readmission rates (07% vs. 10%; p=0.99) between the two groups. Conclusion ERAS protocol, when implemented in patients undergoing laparotomy for trauma, has decreased duration of hospital stay with no additional complications. Level of evidence Level 1, randomized controlled trial, care management. Trial registration number Clinical Trials Registry of India (CTRI/2019/06/019533).
The Cost of Being ‘Backward’ in India: Socio-religious Discrimination in the Labour Market

Being from backward castes, classes and Muslims in India has an economic cost associated with the nature of institutional discrimination. Using the 2011–2012 National Sample Survey data, this study identifies that caste and religion still rule the modern Indian labour market. We find that discrimination is evident in the socio-religious earnings gaps. While the parametric decompositions suggest that most of these gaps are due to differential human capital endowment, the nonparametric method almost evenly attributes inequality to discrimination and endowment. The results presented in this study suggest that discrimination against Scheduled Castes and Scheduled Tribes, Muslims and Other Backward Classes should be included in policy designs to promote equity in the Indian labour market.