Miracle-dz/UniFAR-FTUs huggingface dataset:
Physical Spaces in Higher Education as Scenarios of Learning Innovation: Compositional and Formative Synergies among Architecture, Music, and Fashion

Learning innovation is a positive approach on the contemporary higher education international stage. This article stresses the need to devise physical spaces that are also innovative. For that purpose, using a qualitative methodology, we investigated recent trends based on the synergies between certain creative disciplines: architecture, music, and fashion. The comparison was based on compositional features and formative dimension. Using a qualitative methodological comprehensive approach, a set of case studies was analysed. The findings show the usefulness of activating these synergies as effective strategies when enriching educational processes in different ways. Six cases of excellence wherein university physical spaces reached levels of innovation were studied, representing relevant transfers among the three disciplines. The text presents examples that show the educational consequences in the establishment of those synergies, in terms of both composition (music–architecture) and the activation of heritage sites in the city as venues of learning innovation (fashion–architecture). The basic conclusions were based on the fact that the increase in teaching and spatial creativity that emanates from said synergies among the three disciplines can be potentially extrapolated to other areas of knowledge.
Diterpene Sonderianin isolated from Croton blanchetianus exhibits acetylcholinesterase inhibitory action and anxiolytic effect in adult zebrafish (Danio rerio) by 5-HT system

Abstract Croton blanchetianus is known as ‘marmeleiro preto’, a very widespread shrub in Northeast Brazil. Terpenoids, steroids and phenolic compounds are among the reported secondary metabolites of the Croton genus that are a potential source of bioactive compounds. This study evaluated the anxiolytic potential of clerodine-type diterpene, sonderianin (CBWS) isolated from the stem bark of C. blanchetianus and its mechanism of action in adult zebrafish (Danio rerio) (ZFa). The anticonvulsant and anti-acetylcholinesterase effects have also been explored. ZFa (n = 6/group) were treated intraperitoneally (ip; 20 µL) with CBWS (4, 12 and 40 mg/kg) and vehicle (3% DMSO; 20 µL) and subjected to locomotor activity tests, as well as toxicity acute 96 h. CBWS was also administered for analysis in the light/dark test. The involvement of the serotonergic system (5-HT) was investigated using 5-HTR1, 5-HTR2A/2C and 5-HTR3A/3B receptor antagonists. Anxiolytic doses were tested for pentylenetetrazol-induced seizure in ZFa. The inhibitory activity of the enzyme acetylcholinesterase (AChE) was measured. CBWS was not considered toxic and reduced locomotor activity. The results of the present study identified for the first time the interaction of the diterpene sonderianina in the CNS. This study provides evidence that CBWS has an anxiolytic effect mediated by serotonergic (5-HT) involvement and anti-acetylcholinesterase action. The 5-HTR1 and 5-HTR2A/2C receptors may be implicated in the low anticonvulsant effect in CBWS. Communicated by Ramaswamy H. Sarma
Development and criterion validity of the COVID-19 anxiety and fear assessment scale: a cross sectional study

Background: The emergence of the new severe acute respiratory syndrome coronavirus 2, which causes COVID-19 disease, has been a major public health challenge and an increase in the feeling of uncertainty of the population, who is also experiencing an increase in levels of anxiety and fear regarding the COVID-19 disease. Objective: The objective of the study was the construct and criterion validation of the Escala de evaluación de la Ansiedad y MIedo a COVID-19 (AMICO, for its acronym in Spanish) to measure both constructs in the general Spanish population Methods: Descriptive study of psychometric validation. A field study was carried out to execute univariate and bivariate analyses, in addition to the exploratory and confirmatory factorial analysis of the scale. For the criteria validity study, the State-Trait Anxiety Inventory (STAI) and sensitivity and specificity values were calculated. Results: The study sample was composed of 1036 subjects over 18 years of age, who resided in Spain, where 56.3% were women with a mean age of 48.11 years (SD = 15.13). The study of construct validity reported two factors and 16 items, with a Cronbach's alpha value of 0.92. The scale was concurrently valid with the used gold standard and obtained sensitivity values of 90.48% and specificity values of 76%. Conclusions: The AMICO scale is valid and reliable for assessing the level of anxiety and fear of COVID-19 in the adult Spanish population and is highly sensitive.
Sustainable Apple Disease Management in China: Challenges and Future Directions for a Transforming Industry.

Apples are grown worldwide, and consuming fresh apple fruit is associated with many health benefits. China produces about half of the world's apple supply. However, apple growing in China differs sharply from that in western countries in terms of the prevalent diseases and corresponding management strategies. For instance, family-owned small-scale orchards dominate China's apple industry, and manual bagging of fruit has been a long-standing practice for controlling fruit diseases. In recent years, rural labor shortages have been increasingly challenging the traditional production system, and China's apple industry is experiencing a rapid transition to much larger-scale enterprises featuring high-density orchards with advanced automation and mechanization. Associated with this transition are new challenges and grower demands that are changing the face of apple disease management. This Feature Article summarizes the ongoing transformation of China's apple industry in the context of sustainable disease management.
Statistics of two-point correlation and network topology for Ly α emitters at z ≈ 2 . 67

We investigate the spatial distribution of Ly α-emitting galaxies (LAEs) at z ≈ 2.67, selected from the NOAO Deep Wide-Field Survey, using two-point statistics and topological diagnostics adopted from network science. We measure the clustering length, r0 ≈ 4 h−1 Mpc, and the bias, bLAE = 2.2+0.2 −0.1. Fitting the clustering with halo occupation distribution (HOD) models results in two disparate possibilities: (1) where the fraction of central galaxies is <1 per cent in haloes of mass >1012 M and (2) where the fraction is ≈20 per cent. We refer to these two scenarios as the ‘Dusty Core Scenario’ for Model#1, since most of the central galaxies in massive haloes are dead in Ly α emission, and the ‘Pristine Core Scenario’ for Model#2, since the central galaxies are bright in Ly α emission. Traditional two-point statistics cannot distinguish between these disparate models given the current data sets. To overcome this degeneracy, we generate mock catalogues for each HOD model using a high-resolution N-body simulation and adopt a network statistics approach, which provides excellent topological diagnostics for galaxy point distributions. We find three topological anomalies from the spatial distribution of observed LAEs, which are not reproduced by the HOD mocks. We find that Model#2 matches better all network statistics than Model#1, suggesting that the central galaxies in >1012 h−1 M haloes at z ≈ 2.67 need to be less dusty to be bright as LAEs, potentially implying some replenishing channels of pristine gas such as the cold mode accretion.
A sequence to sequence transformer data logic experiment

In this paper we present experiments to evaluate how a T5 model behaves with regard to input data ﬁdelity. The rationale behind these experiments is to evaluate if a sequence to sequence transformer can be constrained into generating the speciﬁcs of a ﬁnancial report, and more generally whether it can trustfully re-produce a semantic logic, and to what extent.
Emergence and radiation of distemper viruses in terrestrial and marine mammals

Canine distemper virus (CDV) and phocine distemper virus (PDV) are major pathogens to terrestrial and marine mammals. Yet little is known about the timing and geographical origin of distemper viruses and to what extent it was influenced by environmental change and human activities. To address this, we (i) performed the first comprehensive time-calibrated phylogenetic analysis of the two distemper viruses, (ii) mapped distemper antibody and virus detection data from marine mammals collected between 1972 and 2018, and (iii) compiled historical reports on distemper dating back to the eighteenth century. We find that CDV and PDV diverged in the early seventeenth century. Modern CDV strains last shared a common ancestor in the nineteenth century with a marked radiation during the 1930s–1950s. Modern PDV strains are of more recent origin, diverging in the 1970s–1980s. Based on the compiled information on distemper distribution, the diverse host range of CDV and basal phylogenetic placement of terrestrial morbilliviruses, we hypothesize a terrestrial CDV-like ancestor giving rise to PDV in the North Atlantic. Moreover, given the estimated timing of distemper origin and radiation, we hypothesize a prominent role of environmental change such as the Little Ice Age, and human activities like globalization and war in distemper virus evolution.
Families with fetal alcohol spectrum disorders: Exploring adoptive parents’ experiences of family well-being

Fetal alcohol spectrum disorder (FASD) is the leading non-genetic cause of developmental disability in Canada. It poses many challenges at the individual, family and societal levels. This study explores adoptive parents’ experiences of having a child with FASD in their family and how these experiences impact family well-being and, specifically, parenting, family dynamics, sources of support and coping strategies. Using an Interpretive Phenomenological Analysis (IPA) approach, in-depth semi-structured interviews were conducted with eight adoptive parents of children with FASD. Four main themes emerged, each with several subthemes: (1) managing individuals with FASD; (2) navigating family cohesion; (3) psychological warfare; and (4) experiences of supports. Findings showed how FASD affects all aspects of family life and has a constant and cumulative effect on the family’s well-being. Hope, community and parents feeling successful in their efforts were found to have strong connections to well-being.
Online Spectral Classification for Long-Term Spike Sorting

In this paper, we explore online spike sorting for chronic extracellular recording. A challenge is to track drifts of clusters across time. In our proposed approach, time-series data of neural spikes are batched into sliding time frames, and a Laplacian eigenproblem corresponding to each time frame is efficiently solved using iterative methods with an initial guess provided by the previous time frame. The labels are obtained by comparing the eigenvectors of successive time frames. This approach is capable of classifying data points from time-varying but locally stationary distributions.
Building Reliable Cloud Services Using Coyote Actors

Cloud services must typically be distributed across a large number of machines in order to make use of multiple compute and storage resources. This opens the programmer to several sources of complexity such as concurrency, order of message delivery, lossy network, timeouts and failures, all of which impose a high cognitive burden. This paper presents evidence that technology inspired by formal-methods, delivered as part of a programming framework, can help address these challenges. In particular, we describe the experience of several engineering teams in Microsoft Azure that used the open-source Coyote Actor programming framework to build multiple reliable cloud services. Coyote Actors impose a principled design pattern that allows writing formal specifications alongside production code that can be systematically tested, without deviating from routine engineering practices. Engineering teams that have been using Coyote have reported dramatically increased productivity (in time taken to push new features to production) as well as services that have been running live for months without any issues in features developed and tested with Coyote.
Provisioning Differentiated Last-Level Cache Allocations to VMs in Public Clouds

Public cloud providers offer access to hardware resources and users rent resources by choosing among many VM sizes. While users choose the CPU core count and main memory size per VM, they cannot specify last-level cache (LLC) requirements. LLC is typically shared among all cores of a modern CPU causing cache contention and performance interference among co-located VMs. Consequently, a user's only way to avoid this interference is purchasing a full-server VM to prevent co-tenants. Although researchers have studied LLC partitioning and despite its availability in commodity processors, LLC QoS has not been offered to public cloud users today. Existing techniques rely mostly on performance profiling, which is not feasible in public cloud settings with opaque VMs. Moreover, prior work does not address how to deliver differentiated LLC allocations at scale. In this work, we develop CacheSlicer, the first system that provides cluster-level support for LLC management in a public cloud. We show how to provide LLC allocations in a major public cloud provider to enable differentiated VM categories, from which users select VMs that match their workloads. We integrate it into the Azure VM scheduler and show its effectiveness through extensive evaluations.
A Systematic Review on Extracting Predictors for Forecasting Complications of Diabetes Mellitus

The high global prevalence, irreversible health burden, and expenditures of diabetes mellitus lead to a proliferative research area of prognosis and diagnosis of diabetes and its complications through machine learning techniques. Although the risk scoring and prediction models have been proposed for decades, challenges still persist. Feature selection is one challenging problem that is still remains when building accurate models. Since each risk factor's contribution in predicting complications of diabetes vary with the recognition of novel risk factors, it is a requirement to make an up-to-date standard feature subset that can predict the risk of complications of diabetes mellitus. This research in progress paper proposes a systematic review study that aims to extract frequent feature subsets for predicting complications of diabetes. Diabetic retinopathy, neuropathy, nephropathy, and cardiovascular diseases have been considered as the most common complications of diabetes. PRISMA guidelines will be used to conduct the systematic review. Further, the proposed study will be strengthened by selecting credible journal repositories, optimising the search query, utilising inclusion and exclusion criteria, and determining top-ranked journals. The paper presents data analysis design with feature subsets to predict the aforementioned four complications of diabetes, which is directly beneficial for clinicians, researchers, and model developers to assist their clinical decisions, research purposes, and feature selection phase in model designing respectively.
Characterizing Microservice Dependency and Performance: Alibaba Trace Analysis

Loosely-coupled and light-weight microservices running in containers are replacing monolithic applications gradually. Understanding the characteristics of microservices is critical to make good use of microservice architectures. However, there is no comprehensive study about microservice and its related systems in production environments so far. In this paper, we present a solid analysis of large-scale deployments of microservices at Alibaba clusters. Our study focuses on the characterization of microservice dependency as well as its runtime performance. We conduct an in-depth anatomy of microservice call graphs to quantify the difference between them and traditional DAGs of data-parallel jobs. In particular, we observe that microservice call graphs are heavy-tail distributed and their topology is similar to a tree and moreover, many microservices are hot-spots. We reveal three types of meaningful call dependency that can be utilized to optimize microservice designs. Our investigation on microservice runtime performance indicates most microservices are much more sensitive to CPU interference than memory interference. To synthesize more representative microservice traces, we build a mathematical model to simulate call graphs. Experimental results demonstrate our model can well preserve those graph properties observed from Alibaba traces.
Secure Namespaced Kernel Audit for Containers

Despite the wide usage of container-based cloud computing, container auditing for security analysis relies mostly on built-in host audit systems, which often lack the ability to capture high-fidelity container logs. State-of-the-art reference-monitor-based audit techniques greatly improve the quality of audit logs, but their system-wide architecture is too costly to be adapted for individual containers. Moreover, these techniques typically require extensive kernel modifications, making it difficult to deploy in practical settings. In this paper, we present saBPF (secure audit BPF), an extension of the eBPF framework capable of deploying secure system-level audit mechanisms at the container granularity. We demonstrate the practicality of saBPF in Kubernetes by designing an audit framework, an intrusion detection system, and a lightweight access control mechanism. We evaluate saBPF and show that it is comparable in performance and security guarantees to audit systems from the literature that are implemented directly in the kernel.
On reciprocity: expanding the dialogue between disciplines

Lately, I have been thinking a great deal about reciprocity: about the need for mutual exchange and for increased conversation, as a gesture towards greater understanding. The world has experienced a divisive turn in the form of a resurgent xenophobia, increased economic stratification, political division, bellicosity and entrenched hatreds. The migrant and climate crises, along with the COVID-19 pandemic, have tested civility and shaken the public trust. But reciprocity is about the practice of exchange for mutual benefit, and the sharing of privileges, ideas, and hopefully solutions; it therefore holds the potential to bring us together in the service of common goals. Within academe, the interaction between disciplines and fields can be minimal, if not also antagonistic. Notions of methodological purity and the policing of disciplinary standards are often a means of preserving time-tested standards. But in this time of increased division, scholars and cultural producers have a unique opportunity to foster a renewed culture of collectivity and a vibrant form of exchange, as we all navigate the complexities and challenges of the twentyfirst century.
Design of a Partial Resonant Inverter for solar photovoltaic applications

This paper presents a solar-powered Partial Resonant Inverter (PRI) interfaced with an asymmetrical cascaded nine-level inverter. The DC input of the proposed system is obtained using Solar Photovoltaic (SPV) panel. The input DC sources fed to the asymmetrical cascaded nine-level inverter are in the ratio of 1:3. The step modulated nine-level inverter works with a precalculated switching angle for a fixed modulation of 0.7. Compared to the conventional 50 Hz inverter and the multi-output transformer design, the proposed system is more compact because of the high-frequency AC link. The PRI ensures Zero Voltage Switching (ZVS) and reduces the switching losses. The proposed scheme has been validated in the MATLAB/ SIMULINK environment and an experimental prototype is built in the laboratory. Based on the investigations the Selective Harmonic Elimination (SHE) method gives superior performance when compared to the Optimal Harmonic Stepped Modulation (OHSM) method. From the results and comparative analysis, the proposed system uses fewer switches to obtain the nine-level output, uses the PRI setup with the multioutput transformer to make the design compact and improves the power quality of the system.
Questionnaire: visual studies now

In the present moment of the twenty-first century we need to engage with the visual in such a way that enables us to productively and interventionally address the crisis points of our times – in relation to climate change, public health, politics and emerging technologies. To achieve this our work needs to be theoretically, methodologically and practically astute, strategic and humble. My starting point proposes that we should engage with the visual and similarly with people, other species and organisms, materialities, processes, environments (and more) as things we research with and through, rather than as things we do research about. Seeing the visual – or anything else for that matter – as an object that is separate from us as researchers and the environment makes visual research a mere intellectual exercise. Alone, analysis that separates its object from the environment in which it is constituted and participates has little value for how we understand meaning in the world, or for our capacity to participate in shaping possible futures.
High Risk Percutaneous Coronary Intervention of Left Main Bifurcation Stenosis in a Peritoneal Dialysis Patient

Abstract Complex coronary artery disease is the leading cause of death in patients with end-stage renal disease. We report a case of a patient on peritoneal dialysis, preloaded with Prasugrel and acetylsalicylic acid as а potent dual antiplatelet therapy (DAPT). The patient underwent a high-risk percutaneous coronary intervention (PCI) due to bifurcation stenosis of the left main stem branch. A “double kiss crush” bifurcation stenting technique was performed. This case provides additional data about the treatment of this group of patients, a group that is often excluded from randomized control trials, but is frequently encountered in cardiovascular practice. Furthermore, it helps to advance PCI treatment along with exploring the safety of potent DAPT in a group that is susceptible to both ischemia and bleeding, thus presenting a great challenge in the decision for treatment.
Fetuin-A as a Marker of Insulin Resistance

Abstract Fetuin-A is a glycoprotein which helps in the regulation of metabolism. It is an early marker of insulin resistance (IR). The aim of this study was to evaluate the role of Fetuin-A as a predictive biomarker in cases of newly detected type 2 diabetes (NDD). The study involved 60 NDD and 60 Normal Healthy Controls (NHC). All the demographics and anthropological characteristics were noted. Fasting blood samples were drawn and various biochemical parameters were analyzed. The homeostatic model assessment of insulin resistance (HOMA-IR) and the quantitative insulin sensitivity check index (QUICKI) score was calculated. Chisquare, student T-test and Mann Whitney U tests were employed to associate and compare the mean and median between the NDD and NHC groups. Pearson's and Spearman’s correlation analysis were employed to examine the relationship of Fetuin-A levels with parametric and nonparametric variables. The independent predictors of Fetuin-A was determined by employing multiple forward linear regression. Fetuin-A was significantly high in NDD compared to NHC (1323 vs. 306.98 mcg/mL; p<0.001). Majority of NDD patients demonstrated IR based on the HOMA-IR (88.33% vs. 66.67%) and QUICKI score (96.67% vs. 85%). The multiple linear regression analysis showed that systolic blood pressure, age and QUICKI score were independently associated with Fetuin-A (p value <0.01). Fetuin-A may be used as a biomarker to detect NDD. Therefore, early detection of Fetuin-A levels in NDD gives an opportunity for suitable patient management.