Miracle-dz/UniFAR-FTUs huggingface dataset:
Detecting New Points of Interest Using Taxi GPS Data

Nowadays, online mapping services, such as navigation, rely significantly on points of interest (POIs) data to enhance their utility and efficiency. However, maintaining an up-to-date POI dataset is a challenging task. Recognizing this, we observed that taxi pick-up and drop-off locations often align with POIs, like markets, schools, and department stores. This research proposes a method for detecting potential new POIs by using taxi GPS data alongside an existing POI dataset. The process consists of extracting pick-up and drop-off points from taxi GPS data, clustering them using an adaptive DBSCAN algorithm, and finding the representative point for each cluster. Subsequently, these representative points are compared with the nearest POIs in the current dataset to identify new POIs candidates. Experimental analysis using diverse GPS data distributions showed that areas with greater population and density were more effective in identifying POIs than sparser areas. As a result, our proposed method and the developed tool can augment existing POI datasets by recognizing locations poised to emerge as new POIs.
Fading Cognitive Multiple-Access Channels With Confidential Messages

The fading cognitive multiple-access channel with confidential messages (CMAC-CM) is investigated, in which two users (users 1 and 2) wish to transmit a common message to a destination and user 1 also has a confidential message intended for the destination. The two users transmit to the destination via a multiple access channel, and user 2 also receives noisy channel outputs. Such channel outputs potentially help user 2 to learn user 1's confidential information (although they are not exploited by user 2 for channel transmission). Hence, user 1 views user 2 as an eavesdropper and wishes to keep its confidential message as secret as possible from user 2. A parallel CMAC-CM with independent subchannels is first studied. The secrecy capacity region of the parallel CMAC-CM is established, which yields the secrecy capacity regions of the parallel CMAC-CM with degraded subchannels and the parallel Gaussian CMAC-CM. These results are then applied to study the fading CMAC-CM, in which both the user-to-user channel and the user-to-destination channel are corrupted by multiplicative fading gain coefficients in addition to additive white Gaussian noise. The channel state information (CSI) is assumed to be known at both the users and the destination. With the CSI, users can dynamically change their transmission powers with the channel realization to achieve the optimal performance. The closed-form power allocation function that achieves every boundary point of the secrecy capacity region is derived.
Segment-based and Patient-based Segmentation of CTPA Image in Pulmonary Embolism using CBAM ResU-Net

An accurate pulmonary embolism segmentation from computed tomography pulmonary angiography (CTPA) images is very important in pulmonary embolism diagnosis. However, the segmentation process nowadays is done manually by physicians, making the process time-consuming and the accuracy dependent on the physician's ability. Hence, we focused on improving the accuracy of an automatic segmentation method by employing image preprocessing techniques and modifying U-Net architecture in many ways. This paper introduced ResU-Net (residual U-Net) and CBAM ResU-Net (ResU-Net with the addition of CBAM attention modules in the skip connections) models to this framework. Furthermore, we explored two training approaches: segment-based and patient-based. Our experimental results showed that segment-based models performed substantially better than patient-based models. Regardless of training approaches, the most accurate model was CBAM ResU-Net, which achieved up to 0.8719 in Dice score for the segment-based approach and 0.6751 for the patient-based approach.
Prediction, Explanation, and Control: The Use of Mental Models in Dynamic Environments

Abstract The abilities to predict, explain, and control might arise out of operations on a common underlying representation or, conversely, from independent cognitive processes. We developed a novel experimental paradigm to explore how individuals might use probabilistic mental models in these three tasks, under varying levels of complexity and uncertainty. Participants interacted with a simple chatbot defined by a finite-state machine, and were then tested on their ability to predict, explain, and control the chatbot’s responses. When full information was available, performance varied significantly across the tasks, with control proving most robust to increased complexity, and explanation being the most challenging. In the presence of hidden information, however, performance across tasks equalized, and participants demonstrated an alternative neglect bias, i.e., a tendency to ignore less likely possibilities. A second, within-subject experimental design then looked for correlations between abilities. We did not find strong correlations, but the challenges of the task for the subjects limited our statistical power. To understand these effects better, a final experiment investigated the possibility of cross-training, skill transfer, or “zero-shot” performance: how well a participant, explicitly trained on one of the three tasks, could perform on the others without additional training. Here we found strong asymmetries: participants trained to control gained generalizable abilities to both predict and explain, while training on either prediction or explanation did not lead to transfer. This cross-training experiment also revealed correlations in performance; most notably between control and prediction. Our findings highlight the complex role of mental models, in contrast to task-specific heuristics, when information is partially hidden, and suggest new avenues for research into situations where the acquisition of general purpose mental models may provide a unifying explanation for a variety of cognitive abilities.
Placebo effects in mental health disorders: protocol for an umbrella review

Introduction Given the high prevalence of mental health disorders and their significant socioeconomic burden, there is a need to develop improved treatments, and to evaluate them through placebo-controlled trials. However, the magnitude of the placebo response in randomised controlled trials to test medications may be substantial, affecting their interpretation. Therefore, improved understanding of the patient, trial and mental disorder factors that influence placebo responses would inform clinical trial design to better detect active treatment effects. There is a growing literature exploring the placebo response within specific mental health disorders, but no overarching synthesis of this research has been produced to date. We present a protocol for an umbrella review of systematic reviews and/or meta-analyses in which we aim to understand the effect size and potential predictors of placebo response within, and across, mental health disorders. Methods and analysis We will systematically search databases (Medline, PsycINFO, EMBASE+EMBASE Classic, Web of Knowledge) for systematic reviews and/or meta-analyses that report placebo effect size in clinical trials in patients with mental health disorders (initial search date 23 October 2022). Screening of abstracts and full texts will be done in pairs. We will extract data to qualitatively examine how placebo effect size varies across mental health disorders. We also plan to qualitatively summarise predictors of increased placebo response identified either quantitatively (eg, through meta-regression) or qualitatively. Risk of bias will be assessed using the AMSTAR-2 tool. We aim to not only summarise the current literature but also to identify gaps in knowledge and generate further hypotheses. Ethics and dissemination We do not believe there are any specific ethical considerations relevant to this study. We will publish the results in a peer-reviewed journal.
‘What we lacked was the courage to take decisions that differed from the rest of the world’: expert perspectives on the role of evidence in COVID-19 policymaking in Iraq

Introduction Iraq reported its first COVID-19 case on 24 February 2020 and formed a national committee and advisory committees to support its response. While global experts have suggested that the COVID-19 pandemic provided an exceptional opportunity for advancing evidence-informed policymaking (EIPM), no research has examined this in Iraq. Therefore, this study aimed to examine evidence use in COVID-19 policymaking in Iraq. Methods This qualitative study employed semi-structured interviews with 20 Iraqi policymakers and researchers. Data were analysed thematically in Arabic using inductive coding. Findings Participants described COVID-19 policy in Iraq as based on research conducted in other countries, with poor access and quality of routine data and lack of national research priorities and academic freedom as barriers to national research production. Most researchers influenced policy individually, with universities and other research bodies not seen as contributing to policy development. Public non-compliance could be traced to mistrust in both political and healthcare systems and became particularly problematic during the pandemic. Proposed strategies to increase national research production included dedicated funding, establishing communication and collaboration for research priority setting, and protection of academic freedom. Conclusion Sociopolitical and economic realities in Iraq were unsupportive of national or subnational evidence generation even before the COVID-19 pandemic, and government relied on international evidence and policy transfer rather than contextually informed EIPM. Strengthening evidence-informed infectious disease policymaking and policy transfer would thus require governmental focus on improving the quality and relevance of Iraqi research, engagement between researchers and policymakers, and processes of evidence use and policy transfer.
Connecting pathogen transmission and healthcare worker cognition: a cognitive task analysis of infection prevention and control practices during simulated patient care

Background Relatively little is known about the cognitive processes of healthcare workers that mediate between performance-shaping factors (eg, workload, time pressure) and adherence to infection prevention and control (IPC) practices. We taxonomised the cognitive work involved in IPC practices and assessed its role in how pathogens spread. Methods Forty-two registered nurses performed patient care tasks in a standardised high-fidelity simulation. Afterwards, participants watched a video of their simulation and described what they were thinking, which we analysed to obtain frequencies of macrocognitive functions (MCFs) in the context of different IPC practices. Performance in the simulation was the frequency at which participants spread harmless surrogates for pathogens (bacteriophages). Using a tertiary split, participants were categorised into a performance group: high, medium or low. To identify associations between the three variables—performance groups, MCFs and IPC practices—we used multiblock discriminant correspondence analysis (MUDICA). Results MUDICA extracted two factors discriminating between performance groups. Factor 1 captured differences between high and medium performers. High performers monitored the situation for contamination events and mitigated risks by applying formal and informal rules or managing their uncertainty, particularly for sterile technique and cleaning. Medium performers engaged more in future-oriented cognition, anticipating contamination events and planning their workflow, across many IPC practices. Factor 2 distinguished the low performers from the medium and high performers who mitigated risks with informal rules and sacrificed IPC practices when managing tradeoffs, all in the context of minimising cross-contamination from physical touch. Conclusions To reduce pathogen transmission, new approaches to training IPC (eg, cognitive skills training) and system design are needed. Interventions should help nurses apply their knowledge of IPC fluidly during patient care, prioritising and monitoring situations for risks and deciding how to mitigate risks. Planning IPC into one’s workflow is beneficial but may not account for the unpredictability of patient care.
Total Joint Arthroplasty In Patients With Liver Cirrhosis: A Systematic Review

Background: Total hip arthroplaties (THAs) and total knee arthroplasties (TKAs) have proven themselves as effective surgical procedures. As a result, the number of such procedures performed is increasing. It is also likely that more cirrhotic patients will undergo THA or TKA. Purpose: We performed a systematic review to assess periprosthetic joint complications, infections, mortality, and the outcome of total joint arthroplasties in patients diagnosed with cirrhosis. Material and Methods: We researched Medline, EMBASE, and Cochrane databases to identify eligible prospective studies. This yielded 346 unique articles. 27 of these articles fit the inclusion criteria, and 7 articles remained eligible after in-depth reading. Demographic characteristics, adverse events, and clinical outcomes were manually extracted from the selected studies. Results: The 7 studies included a total of 2724 TJA of which 1276 were THA and 1448 were THK. 3 studies provided data on the severity of cirrhosis using Child-Turcotte-Pugh. 4.7 % of perioperative complications occurred in class A, 50% in class B, and 100% in class C with a mortality rate of 66.6%. 5 studies provided data on short term (30 days) mortality after TJA. Therefore, these studies showed that mortality in patients with cirrhosis, undergoing TJA, is greater than in noncirrhotic patients (1.13% vs 0.17%). The rate of infection varied from 3.1% to 22% in cirrhotic patients and 0.7% to 1.4% in non-cirrhotic patients. Conclusion: This present systematic review shows that total joint arthroplasty surgery of patients with cirrhosis results in increased postoperative morbidity and mortality compared to similar surgeries for noncirrhotic patients.
Rationalizing the Design of Pluronics − Surfactant Mixed Micelles through Molecular Simulations and Experiments

: Aqueous systems comprising polymers and surfactants are technologically important complex fluids with tunable features dependent on the chemical nature of each constituent, overall composition in mixed systems, and solution conditions. The phase behavior and self-assembly of amphiphilic polymers can be changed drastically in the presence of conventional ionic surfactants and need to be clearly understood. Here, the self-aggregation dynamics of a triblock copolymer (Pluronics L81, EO 3 PO 43 EO 3 ) in the presence of three cationic surfactants (with a 12C long alkyl chain but with different structural features), viz., dodecyltrimethylammonium bromide (DTAB), didodecyldimethylammonium bromide (DDAB), and ethanediyl-1,2-bis-(dimethyldodecylammonium bromide) (12-2-12), were investigated in an aqueous solution environment. The nanoscale micellar size expressed as hydrodynamic diameter ( D h ) of copolymer − surfactant mixed aggregates was evaluated using dynamic light scattering, while the presence of a varied micellar geometry of L81 − cationic surfactant mixed micelles were probed using small-angle neutron scattering. The obtained findings were further validated from molecular dynamics (MD) simulations, employing a simple and transferable coarse-grained molecular model based on the MARTINI force field. L81 remained molecularly dissolved up to ∼ 20 ° C but phase separated, forming turbid/translucent dispersion, close to its cloud point (CP) and existed as unstable vesicles. However, it exhibited interesting solution behavior expressed in terms of the blue point (BP) and the double CP in the presence of different surfactants, leading to mixed micellar systems with a triggered morphology transition from unstable vesicles to polymer-rich micelles and cationic surfactant-rich micelles. Such an amendment in the morphology of copolymer nanoaggregates in the presence of cationic surfactants has been well observed from scattering data. This is further rationalized employing the MD approach, which validated the effective interactions between Pluronics − cationic surfactant mixed micelles. Thus, our experimental results integrated with MD yield a deep insight into the nanoscale interactions controlling the micellar aggregation (Pluronics-rich micelles and surfactant-rich micelles) in the investigated mixed system
DOCUMENTATION OF VALIDITY FOR THE AT-SAT COMPUTERIZED TEST BATTERY. VOLUME 2

Abstract : This document is a comprehensive report on a large-scale research project to develop and validate a computerized selection battery to hire Air Traffic Control Specialists (ATCSs) for the Federal Aviation Administration (FAA). The purpose of this report is to document the validity of the Air Traffic Selection and Training (AT-SAT) battery according to legal and professional guidelines. An overview of the project is provided, followed by a history of the various job analyses efforts. Development of predictors and criterion measures are given in detail. The document concludes with the presentation of the validation of predictors and analyses of archival data.
STUDY ON RADON EMANATION FROM SELECTED BUILDING MATERIALS IN Iraqi Kurdistan Region

The air concentrations of radon (Rn-222) emitted to the atmosphere from 7 types of construction materials (sand, gravel, cement, block, gypsum, gypsum board and ceramic tile) used Iraqi Kurdistan, were measured and analyzed using continuous radon monitoring equipment model 1029. Each sample was placed for 84 hours inside 0.118 m 3 sealed container. Of the seven samples examined, the sand showed the highest levels of radon emission 235.45±4.21Bq.m -3 , whereas the ceramic tile showed the lowest level 75.38±5.16 Bq.m -3 . The average radon exhalation rate from the sand and ceramic tile showed approximately the same value, which was higher than that of the ceramic floors by more than 19%.
Numerical Study on Microphysical Processes of Two Different Snowfall Cases in Northern China

In this paper,two snowfall cases under different weather conditions in northern China are simulated by using the meso scale model MM5.Two-way nesting structure of domains is designed for each case.Among the explicit schemes of MM5,the Reisner graupel scheme is selected to describe the microphysical process. The simulated snow-bands of two cases are basically consistent with observations.The simulated results of microphysical processes are mainly discussed.The hydrometeors and their sources and sinks under different weather backgrounds are described.The feedback effects of microphysical processes on the thermal and dynamic processes are also discussed.Method that outputs the accumulative sources and sinks per hour is used to analyze the distribution characteristics of hydrometeors during the strongest snowfall period.Two sensitivity tests (called heat test and drag test) are conducted to examine the effects of microphysical pro- cesses on cloud produced by the latent heat and drag force. Results have shown that the distribution of particles has a close relation with temperature.The tem- perature of Beijing snowfall is under 0℃and there exist vapor and solid phase particles,while Liaoning snowfall has vapor,liquid,and solid phase particles due to the warm temperature.The distribution of these particles is not the same at different development stages.From the analyses of the characteristics of sources and sinks,it is found that snow is mainly produced by the deposition and accretion with ice.Cloud water is crucial to graupel.The melting of ice-phase particles enhances the rain production.The results of heat tests and drag tests reveal that the microphysical processes have interacted with the dynamic and thermal processes.Latent heat release of hydrometeors feeds back positively on snowfall while the drag force not. At last,comparisons of simulated results have been done between the two different kinds of snowfall cases. The microphysical processes of Liaoning snowfall case is more complicated than those of Beijing snowfall case.The values of the cloud variables are larger and the interactions between the microphysical processes and the thermal and dynamic processes of Liaoning snowfall case are stronger than those of Beijing snowfall case.
Impedance inversion based on basis pursuit decomposition and contourlet transform

Matching pursuit can adaptively decompose a seismic trace into a series of wavelets and realize highly precise impedance inversion for underground geological body. However, since traditional matching pursuit is used in single channel, the lateral continuity is lack along the profile. Faced with this problem, we exploit contourlet transform to enhance the lateral stability of reflection section, and then we calculate impedance based on reflection section. Application in some area shows that contourlet transform can enhance the structures in reflection profile and lateral continuity will be great improved in reflection profile and impedance profile.
Monte Carlo simulation of selected binomial similarity coefficients. II: Effect of sparse data

Binary similarity coefficients are applied widely to many types of paleontological data. Unfortunately, many of these paleontological data sets are "sparse" (i. e., contain substantially more than 50% "zeros, " or absences, in the data matrix). We have run a series of Monte Carlo simulations with sparse data (10% "1" s, or p = 0.10) on a series of selected coefficients that have been tested previously using 50% "1 "s, or p = 0.50 (Archer and Maples, in press). In decreasing order of ability to approximate the mean of the sparse-data binomial (0.10) and general utility, we rank the coefficients tested as Dice, Braun-Blanquet, Simpson, Jaccard, Baroni-Urbani and Buser, Simple Matching, and Hamann. This ranking is generally the opposite of thatfor Monte Carlo simulations using 50% "1"s or p = 0.50 (Archer and Maples, in press). Because the mean has such a low value, Dice, Braun-Blanquet, Simpson, Jaccard, and Baroni-Urbani and Buser all truncate the lower zones of significance. Therefore, statistically meaningful comparisons of the differences between any two samples cannot be made using these coefficients. This does not render these particular coefficients as useless, as long as it is realized that significantly similar linkages will occur at what would normally be interpreted as abnormally low values, especially in comparison with data in which a greater percentage of "1 "s is present. In contrast, the Simple Matching and Hamann coefficients greatly overestimate the mean because the mutual absence of a character or taxon is considered to be a trait in common between any two samples. Because of the shifted mean, lower zones of significance are present; however, all linkages are high-even those that are significantly dissimilar. The mutual absence of one or more characters between any two samples is usually meaningless for most paleontological problems; coefficients should therefore be selected with this in mind.