Miracle-dz/UniFAR-FTUs huggingface dataset:
Meta-Analysis of Environmental Kuznets Curve Studies: Meta-Analysis of Environmental Kuznets Curve Studies: Determining the Cause of the Curve’s Presence Determining the Cause of the Curve’s Presence

This investigation uses meta-analysis to explore the systematic variation across Environmental Kuznets Curve (EKC) studies to better understand the specific factors that affect the relationship between economic growth and environmental quality. Meta-analysis is the statistical synthesis of data from a set of comparable studies yielding a quantitative summary of pooled results. Following the findings of Li et al., (2007) a multinomial logit model is employed to analyze 929 observations from 120 different studies published between 1992 and 2012. Results indicate that seven variables (time, quality, emissions, development, fitness, anthropogenic-related gases, carbon dioxide, and sulfur dioxide) significantly affect the presence of the EKC. There is no statistically significant evidence indicating an increased or decreased probability of finding an EKC from the number of observations, panel data, global aspect, reverse publication date, GDP measures, chemically active gases, biologically related gases, nitrogen oxide, and air pollution.
Extensions for Network-Assisted MPTCP Deployment Models

Because of the lack of Multipath TCP (MPTCP) support at the server side, some service providers now consider a network-assisted model that relies upon the activation of a dedicated function called MPTCP Conversion Point (MCP). Network-Assisted MPTCP deployment models are designed to facilitate the adoption of MPTCP for the establishment of multi-path communications without making any assumption about the support of MPTCP by the communicating peers. MCPs located in the network are responsible for establishing multi-path communications on behalf of endpoints, thereby taking advantage of MPTCP capabilities to achieve different goals that include (but are not limited to) optimization of resource usage (e.g., bandwidth aggregation), of resiliency (e.g., primary/backup communication paths), and traffic offload management. This document specifies extensions for Network- Assisted MPTCP deployment models.
Sex Differences in Distress From Inﬁdelity in Early Adulthood and in Later Life A Replication and Meta-Analysis of Shackelford et al. (2004)

Shackelford and colleagues (2004) found that men, compared to women, are more distressed by sexual than emotional infidelity, and this sex difference continued into older age. We conducted four high-powered replications (total N = 1,952) of this effect and found different results. A meta-analysis of original and replication studies finds the sex difference in younger samples (though with a smaller effect size), and no effect among older samples. Furthermore, we found attitude toward uncommitted sex to be a mediator (although not consistently in the same direction) between participant sex and relative distress between sexual and emotional infidelity. We hypothesize that the discrepancies between the original and replication studies may be due to changing cultural attitudes about sex across time. Confirming this speculative interpretation requires further investigation.
Black Box or Open Science? A study on reproducibility in AI Development Papers

The surge in Artiﬁcial Intelligence (AI) research has spurred signiﬁcant breakthroughs across various ﬁelds. However, AI is known for its Black Box character and reproducing AI outcomes is a challenge. Open Science, emphasizing transparency, reproducibility, and accessibility, is crucial in this context, ensuring research validity and facilitating practical AI adoption. We propose a framework to assess the quality of AI documentation and assess 51 papers. We conclude that despite guidelines, many AI papers fall short on reproducibility due to insuﬃcient documentation. It is crucial to provide comprehensive details on training data, source code, and AI models, and for reviewers and editors to strictly enforce reproducibility guidelines. A dearth of detailed methods or inaccessible source code and models can raise questions about the authenticity of certain AI innovations, potentially impeding their scientiﬁc value and their adoption. Although our sample size inhibits broad generalization, this study nonetheless oﬀers key insights on enhancing AI research reproducibility.
The Development of a Large Scale Geospatial Telecommunications Application Independent from GIS Proprietary Mechanisms

This article presents the evolution of a very large geospatial database and application developed for telecommunications outside plant management. The needs for the construction of this system and the decisions taken during its development and consolidation phases are described. New challenges found in securing and expanding this type of system in today's market will be listed, as will be the need for a solution independent from the geographical information system (GIS) proprietary mechanisms. The alternatives examined and the approaches chosen to address the main points regarding the system evolution have resulted in a guide to similar initiatives in the area.
Formal Veriﬁcation of Developer Tests: a Research Agenda Inspired by Mutation Testing

With the current emphasis on DevOps, automated software tests become a necessary ingredient for continuously evolving, high-quality software systems. This implies that the test code takes a signiﬁcant portion of the complete code base—test to code ratios ranging from 3:1 to 2:1 are quite common. We argue that “testware” provides interesting opportunities for formal veriﬁcation, especially because the system under test may serve as an oracle to focus the analysis. As an example we describe ﬁve common problems (mainly from the subﬁeld of mutation testing) and how formal veriﬁcation may contribute. We deduce a research agenda as an open invitation for fellow researchers to investigate the peculiarities of formally verifying testware.
W&M ScholarWorks W&M ScholarWorks

Micro instances ( t1.micro ) are the class of Amazon EC2 virtual machines (VMs) oﬀering the lowest operational costs for applications with short bursts in their CPU requirements. As processing proceeds, EC2 throttles CPU capacity of micro instances in a complex, unpredictable, manner. This thesis aims at making micro instances more predictable and eﬃcient to use. First, we present a characterization of EC2 micro instances that evaluates the complex interactions between cost, performance, idleness and CPU throttling. Next, we deﬁne adaptive algorithms to manage CPU consumption by learning the workload characteristics at runtime and by injecting idleness to diminish host-level throttling. Experimental results show that a gradient-hill strategy leads to favorable results. For CPU bound workloads, we observe that a signiﬁcant portion of jobs (up to 65%) can have end-to-end times that are even four times shorter than those of the more expensive m1.small class. Our algorithms drastically reduce the long tails of job execution times on the micro instances, resulting to favorable comparisons against even small instances.
A uni ﬁ ed DNN approach to speaker-dependent simultaneous speech enhancement and speech separation in low SNR environments

We propose a uni ﬁ ed speech enhancement framework to jointly handle both background noise and interfering speech in a speaker-dependent scenario based on deep neural networks (DNNs). We ﬁ rst explore speaker-dependent speech enhancement that can signi ﬁ cantly improve system performance over speaker-independent systems. Next, we consider interfering speech as one noise type, thus a speaker-dependent DNN system can be adopted for both speech enhancement and separation. Experimental results demonstrate that the proposed uni ﬁ ed system can achieve comparable performances to speci ﬁ c systems where only noise or speech interference is present. Furthermore, much better results can be obtained over individual enhancement or separation systems in mixed background noise and interfering speech scenarios. The training data for the two speci ﬁ c tasks are also found to be complementary. Finally, an ensemble learning-based framework is employed to further improve the system performance in low signal-to-noise ratio (SNR) environments. A voice activity detection (VAD) DNN and an ideal ratio mask (IRM) DNN are investigated to provide prior information to integrate two sub-modules at frame level and time-frequency level, respectively. The results demonstrate the e ﬀ ectiveness of the ensemble method in low SNR environments.
Movements and habitat selection of a marsupial carnivore in a modified landscape

Landscape modification is a major threat to carnivores worldwide, but modified landscapes can also provide important habitat for these species, as protected areas alone are insufficient. Understanding how carnivores use modified landscapes, such as production forests, can inform management strategies to improve the value of these landscapes to carnivores. Little is known about habitat selection by marsupial carnivores in production forests, where they occupy a similar ecological niche to their more well-studied eutherian counterparts. We used GPS tracking, Hidden Markov Models, and Manly’s selection ratios to identify the habitat selected in 3 behavioral states by the largest marsupial carnivore, the Tasmanian devil (Sarcophilus harrisii), in a timber plantation-dominated landscape. Behavioral states were approximated as: state 1, resting or feeding at a carcass; state 2, foraging; and state 3, travel. Devils did not show preferences for any of native forest, native grassland, and plantation in any behavioral state. Within plantations, devils preferred a plantation age of 4–7 years (selection ratio [wi] = 1.52). Devils preferred roads (state 1: wi = 2.71, state 2: wi = 2.48, state 3: wi = 2.97) and plantation edges (state 1: wi = 2.38, state 2: wi = 2.24, state 3: wi = 2.78) in all behavioral states, and moved faster on roads and edges than away from them. Together, our results indicate devils use road and edges for foraging (scavenging and hunting) and travel. No measured habitat variables influenced devil home range size. To support devils in plantation landscapes, we recommend maintaining a heterogeneous landscape of different plantation ages and native remnants and reducing the risk of vehicle collisions by minimizing forestry traffic at night. Tasmanian devils share similar adaptable traits to generalist eutherian carnivore species in their use of modified landscapes. Plantations can provide valuable habitat for this and other threatened predator species.
Marine Heatwaves in the Chesapeake Bay Marine Heatwaves in the Chesapeake Bay

Prolonged events of anomalously warm sea water temperature, or marine heatwaves (MHWs), have major detrimental effects to marine ecosystems and the world’s economy. While frequency, duration and intensity of MHWs have been observed to increase in the global oceans, little is known about their potential occurrence and variability in estuarine systems due to limited data in these environments. In the present study we analyzed a novel data set with over three decades of continuous in situ temperature records to investigate MHWs in the largest and most productive estuary in the US: the Chesapeake Bay. MHWs occurred on average twice per year and lasted 11 days
On a new pelycosaur from the lower Permian of Oklahoma, and on the origin of the family Caseidae

Colobomycter, n. gen., a small pelycosaur known from a skull from the lower Permian fissure deposits near Fort Sill, Oklahoma, is closely related to Eo- thyris and shows signs of relationship to the caseids, thus supporting the opinion that the latter are derived from among the eothyridids.
Antecedents and Consequences of The Role of Trust in Mediation of Perceived Ease of Use, Risk and E-Service Quality on Online Purchase Intention

: This research aims to find out the direct influence perceived ease of use, risk perception and E-Service Quality on buying trust and interest, and also to find out the indirect influence perceive ease of use, risk perception and E-Service. Quality of trust-mediated buying interests. The population in this study was all shopee users in the Jakarta region. In this study differs from previous research by using different variables and models in this study. The methods used in this research are quantitative analysis with SEM analysis tools and SmartPLS 3.3 tools. The findings in this study are: (1) Perceived easy of use has a significant positive effect on the purchase intention of Shopee users in Jakarta. (2) Perceived easy of use has a significant positive effect on shopee user trust in Jakarta. (3) Risk perception has a significant negative effect on the purchase intention of Shopee users in Jakarta. (4) Risk perception has a significant negative effect on shopee user trust in Jakarta. (5) Service quality has a significant positive effect on the purchase intention of Shopee users in Jakarta. (6) Service quality has a significant positive effect on shopee user trust in Jakarta. (7) Trust has a significant positive effect on the buying interest of Shopee users in Jakarta. (8) Trust is not a mediation variable in influencing risk perception of purchase intention in Shopee Users in Jakarta.
Alpha-tACS e ﬀ ect on inhibitory control and feasibility of administration in community outpatient substance use treatment

Background: De ﬁ cits in inhibitory control (IC) and distress tolerance (DT) are associated with substance use disorders (SUD) and post-treatment return to substance use. Transcranial alternating current stimulation (tACS) modulates the neural oscillations that are associated with the cognitive and a ﬀ ective mechanisms contributing to IC and DT. The aims of the current study were to examine the feasibility and acceptability of administering tACS in a community-based SUD treatment setting, and to test the e ﬀ ect of alpha-tACS on IC and DT. Method: A double-blind, randomized, active sham-controlled trial of treatment-seeking adults with a SUD ( N = 30, Mean age = 43.2 years, 70.0% male). Participants attended two sessions and completed computerized inhibitory control and distress tolerance tasks while receiving tACS targeting the bilateral dorsolateral prefrontal cortex (DLPFC). Participants received sham-tACS and were then randomized to receive sham, alpha-, or gamma-tACS within 2 – 3 days. Results: Treatment retention was 87%. Participant self-reported belief of having received tACS and mean side e ﬀ ect intensity ratings did not di ﬀ er across conditions, with all side e ﬀ ect ratings in the absent to mild range. There was a large ( d = 0.83) and signi ﬁ cant e ﬀ ect of alpha-tACS on inhibitory control compared to sham-tACS ( β = 1.78, SE = 0.65, 95 % CI: 0.41, 3.14, p <0.01). There were no signi ﬁ cant e ﬀ ects of condition on distress tolerance. Conclusions: To our knowledge, this is the ﬁ rst study of tACS in adults with a SUD. Our ﬁ ndings provide pre-liminary evidence for recruitment, retention, and administration feasibility of tACS in a community-based substance use treatment program and a bene ﬁ cial e ﬀ ect of alpha-tACS on inhibitory control.
Evaluation of Site Effects in a Wide Frequency Band at Ashigara Valley, Japan, Using Strong Motion Records from Remote and Large Events

Tectonics and geological environments in and around Ashigara valley are very complex, especially surrounding rock outcrop sites are not on the same geology. Therefore, it is our concern to find the best reference site and to determine the seismic response at a site in the valley. We had an opportunity to use the ground motion data sets from the very far (>700 km) and large (>M 7) events to compare the rock sites motion as well as the response of sediments site. Advantages of using far and large events are that the source and path effects will be common with a sufficient approximation and that the ground motions of wide frequency band content are expected. Selecting one rock site, seismic responses of the sediment sites and rock sites were determined in terms of frequency as well as time domain amplitudes applying band-pass filtering techniques. Results are as follows; (1) Spatial distribution of seismic responses as a function of frequency in the valley are displayed. The spatial distribution of amplitude in low frequency range under 0.2 Hz is relatively simple and similar to Bouguer anomaly map. The characteristics of spatial distribution in high frequency are more complex. (2) Deviations of spectral amplitude at rock sites were determined by taking the spectral ratio of the site to the average spectra of 6 rock sites. Only lower frequency motion than 0.07 Hz are the same and the deviations of spectral ratio are a factor of 2 in the frequency range of 0.1-10 Hz. (3) The level of spectral ratios of very far earthquakes are more stable than that of near earthquakes in 0.1-10 Hz.
Evaluation of OntoLearn, a Methodology for Automatic Learning of Domain Ontologies

Ontology evaluation is a critical task, even more so when the ontology is the output of an automatic system, rather than the result of a conceptualization effort produced by a team of domain specialists and knowledge engineers. This paper provides an evaluation of the OntoLearn ontology learning system. The proposed evaluation strategy is twofold: first, we provide a detailed quantitative analysis of the ontology learning algorithms. Second, we automatically generate natural language descriptions of formal concept specifications in order to facilitate per-concept qualitative analysis by domain specialists.
Improve Visualization? Can an Iterative Reconstruction Technique CT Metal Artifact Reduction in the Spine:

BACKGROUND AND PURPOSE: Metal-related artifacts from spine instrumentation can obscure relevant anatomy and pathology. We evaluated the ability of CT images reconstructed with and without iterative metal artifact reduction to visualize critical anatomic structures in postoperative spines and assessed the potential for implementation into clinical practice. MATERIALS AND METHODS: We archived CT projection data in patients with instrumented spinal fusion. CT images were reconstructed by using weighted ﬁltered back-projection and iterative metal artifact reduction. Two neuroradiologists evaluated images in the region of spinal hardware and assigned a score for the visualization of critical anatomic structures by using soft-tissue and bone windows (critical structures totally obscured, n (cid:2) 0; anatomic recognition with high diagnostic conﬁdence, n (cid:2) 5). Using bone windows, we measured the length of the most pronounced linear artifacts. For each patient, neuroradiologists made recommendations regarding the optimal use of iterative metal artifact reduction and its impact on diagnostic conﬁdence. RESULTS: Sixty-eightpatientsmettheinclusioncriteria.Visualizationofcriticalsoft-tissueanatomicstructureswassigniﬁcantlyimproved by using iterative metal artifact reduction compared with weighted ﬁltered back-projection (median, 1 (cid:3) 1.5 versus 3 (cid:3) 1.3, P (cid:4) . 001), with improvement in the worst visualized anatomic structure in 88%(60/68) of patients. There was not signiﬁcant improvement in visualization of critical osseous structures. Linear metal artifacts were reduced from 29 to 11 mm ( P (cid:4) . 001). In 87% of patients, neuroradiologists recommended reconstructing iterative metal artifact reduction images instead of weighted ﬁltered back-projection images, with deﬁnite improvement in diagnostic conﬁdence in 32% (22/68). CONCLUSIONS: Iterativemetalartifactreductionimprovesvisualizationofcriticalsoft-tissuestructuresinpatientswithspinalhardware. Routine generation of these images in addition to routine weighted ﬁltered back-projection is recommended.
Annals of Clinical Case Reports

Introduction: Gitelman Syndrome (GS) is a hypokalemic metabolic alkalosis with significant hypomagnesemia, and low urinary calcium excretion and is associated with a biallelic inactivating mutations of the SLC12A3 gene. Congenital Chloride-Losing Diarrhea (CCLD) is characterized by watery diarrhea with a high level of fecal Cl − , metabolic alkalosis
Edinburgh Research Explorer Histone H1 regulates non-coding RNA turnover on chromatin in a m6A-dependent manner

Linker histones are highly abundant chromatin-associated proteins with well-established structural roles in chromatin and as general transcriptional repressors. In addition, it has been long proposed that histone H1 exerts context-speciﬁc effects on gene expression. Here, we identify a function of histone H1 in chromatin structure and transcription using a range of genomic approaches. In the absence of histone H1, there is an increase in the transcription of non-coding RNAs, together with reduced levels of m6A modiﬁcation leading to their accumulation on chromatin and causing replication-transcription conﬂicts. This strongly suggests that histone H1 prevents non-coding RNA transcription and regulates non-coding transcript turnover on chromatin. Accordingly, altering the m6A RNA methylation pathway rescues the replicative phenotype of H1 loss. This work unveils unexpected regulatory roles of histone H1 on non-coding RNA turnover and m6A deposition, highlighting the intimate relationship between chromatin conformation, RNA metabolism, and DNA replication to maintain genome performance.
Behind the Screen: A Narrative Review of Advancements in Mobile and Wearable Passive Sensing for Mental Health Assessment

Mental health disorders—including depression, anxiety, trauma-related, and psychotic conditions—are pervasive and impairing, representing considerable challenges for both individual well-being and public health. Often the first challenge to treatment can be financial, geographic, and stigmatic barriers which limit the accessibility of traditional assessment measures. Further, compounded by frequent misdiagnosis or delayed detection, there is a need for effective, accessible, and scalable approaches to identification and management. Leveraging advances in computing and the ubiquitous nature of personal mobile and wearable technology, this narrative review examines the utilization of passive sensor data as a screening and diagnostic tool for mental disorders. As an alternative to traditional screening measures, passive sensing offers a tool to overcome barriers which prevent many from seeking services. We critically assess the literature up to September 2023, exploring the use of passive data—such as heart rate variability, movement patterns, and geolocation—to predict mental health outcomes across a spectrum of disorders. Through a translational perspective, our review explores the state of passive sensing science, with special emphasis on the capacity for the science to be implemented in real world clinical and general populations. To this aim, we consider study designs, including participant demographics, data collection methods, sensor modalities, outcome measures, and analytic modeling approaches. Our findings highlight overarching limitations in the field including 1) the use of smaller, specialized sample populations, and 2) the predominant use of Android operating systems, 3) a reliance on self-reported measures as proxies for mental health outcomes which ultimately limit the potential to provide robust mental health assessment in larger population samples. We suggest that further research incorporate larger and more diverse samples, inclusion of further smartphone operating systems, and additional clinical-related assessments to strengthen predictive models and maintain a clinician in the loop. Despite these limitations, passive sensing technologies like GPS, heart rate monitoring, and actigraphy offer promise for enhancing early detection and improving the diagnostic process for mental disorders. We conclude that careful consideration of translational factors in the design of future research will aid in enhancing the potential and scope of future passive sensing studies, ultimately enhancing mental health outcomes on a broad scale.