Miracle-dz/UniFAR-FTUs huggingface dataset:
Energy dependence of jet transport parameter and parton saturation in quark-gluon plasma

We study the evolution and saturation of the gluon distribution function in the quark-gluon plasma as probed by a propagating parton and its effect on the computation of jet quenching or transport parameter $\hat q $. For thermal partons, the saturation scale $Q2_s$ is found to be proportional to the Debye screening mass $\mu_D2$. For hard probes, evolution at small $x=Q2_s/6ET$ leads to jet energy dependence of hat q. We study this dependence for both a conformal gauge theory in weak and strong coupling limit and for (pure gluon) QCD. The energy dependence can be used to extract the shear viscosity $\eta$ of the medium since $\eta$ can be related to the transport parameter for thermal partons in a transport description. We also derive upper bounds on the transport parameter for both energetic and thermal partons. The later leads to a lower bound on shear viscosity-to-entropy density ratio which is consistent with the conjectured lower bound $\eta/s\geq 1/4\pi$. Implications on the study of jet quenching at RHIC and LHC and the bulk properties of the dense matter are discussed.
Understanding Account Deletion and Relevant Dark Patterns on Social Media

Social media users may wish to delete their accounts, but it is unclear if this process is easy to complete or if users understand what happens to their account data after deletion. Furthermore, since platforms profit from users' data and activity, they have incentives to maintain active users, possibly affecting what account deletion options are offered. To investigate these issues, we conducted a two-part study. In Study Part 1, we created and deleted accounts on the top 20 social media platforms in the United States and performed an analysis of 490 deletion-related screens across these platforms. In Study Part 2, informed by our interface analysis, we surveyed 200 social media users to understand how users perceive and experience social media account deletion. From these studies, we have four main findings. First, account deletion options vary considerably across platforms and the language used to describe these options is not always clear. Most platforms offer account deletion on desktop browsers but not all allow account deletion from mobile apps or browsers. Second, we found evidence of several dark patterns present in the account deletion interfaces and platform policies. Third, most participants had tried to delete at least one social media account, yet over one-third of deletion attempts were never completed. Fourth, users mostly agreed that they did not want platforms to have access to deleted account data. Based on these results, we recommend that platforms improve the terminology used in account deletion interfaces so the outcomes of account deletion are more clear to users. Additionally, we recommend that platforms allow users to delete their social media accounts from any device they use to access the platform. Finally, future work is needed to assess how users are affected by account deletion related dark patterns.
CalixBoost: A Stock Market Index Predictor using Gradient Boosting Machines Ensemble

The potential of machine learning has sustained the interest of both academia and industry in stock market prediction over the past decade. This paper aims to integrate modern techniques such as Gradient Boosting Machines (GBMs) into a novel ensemble called CalixBoost which is a resource-efficient and accurate stock index predictor. Data comprising macro-economic metrics and technical financial indicators, as well as sentiment analysis of social media using a simple and fast but effective rule-based model are used in this paper. Other techniques include model tuning with Bayesian Optimization, temporal consistency analysis for invariant feature selection over random trial-and-error, feature importance and inter-feature relationships analysis using a unified game theory approach using Shapley values. Lastly, the model will be evaluated using a novel holdout method, viz. on two separate test datasets whose datapoints are collected under (i) normal economic activity and (ii) during a black swan (financial downturn). The experimental results show that our model outperforms previous methods and can achieve a good prediction performance with 84.88% accuracy, 0.0956 RMSE, 0.0573 MAE and 4.19% MAPE.
Forming Parameters on Friction during Single Point Incremental Forming

Friction in the single point incremental forming (SPIF) process is the main factor affecting the surface quality and forming performance of the workpiece. In order to study the effect of process parameters on friction in SPIF, the contact area between the forming tool and the metal sheet was taken as the analysis object according to the principle of SPIF and the characteristics of friction in the forming process. The force status was analytically expressed under the condition of considering friction, and a correlation expression between the forming force and the friction coefficient was given. On this basis, the friction coefficient values under different process parameters were calculated through experimental force measurement, and the accuracy and validity of the obtained friction coefficient were verified by finite element simulation. Finally, the influence of the forming parameters on the friction coefficient and the prediction model of the friction coefficient were analyzed using the surface response method. The research results revealed that the increase of tool diameter or spindle speed helped to reduce the friction coefficient between the contact surfaces, while the increase of layer feed, feed rate, or forming angle increased the friction coefficient to different degrees. The results obtained in this work may provide a reference in theory and technology for improving the surface quality and formability of parts.
Serum levels of α1-antitrypsin, interleukin-1β and interleukin-6 in Iraqi COVID-19 patients: A cross-sectional study

Background: More than half of the individuals diagnosed with coronavirus disease 2019 (COVID-19) have been found to have high levels of interleukin (IL)-6. A recent report showed that more elevated serum IL-6 level predicts COVID-19 disease severity and patients’ clinical outcomes. Therefore, this study aimed to compare the serum levels of α1-antitrypsin (AAT), IL-1β, and IL-6 between COVID-19 patients and healthy individuals. Methods: During the data collection phase, 90 individuals were enrolled, 45 healthy controls, and 45 patients confirmed with COVID-19 using reverse transcription-quantitative PCR (RT-qPCR) at a specialized isolation hospital in Baghdad between November 2021 and March 2022. In this cross-sectional research, venous blood samples were taken, and serum was isolated and stored for quantitative ELISA measurements of AAT, IL-1β, and IL-6 (ELISA). IBM SPSS version 24 was used to analyze the data. Results: This study revealed a significant increase in the serum levels of AAT, IL-1β, and IL-6 in the COVID-19 patients' group compared to the healthy control group with p-values < 0.001 for each of these markers. Conclusions: AAT concentrations were higher during COVID-19; this elevation is essential during infection. IL-1β and IL-6 levels were also elevated during the infection period; however, dysregulated high levels may lead to cytokine release syndrome. Therefore, these three biomarkers can be regarded as diagnostically crucial parameters.
Semantic Segmentation of Panoramic Images for Real-Time Parking Slot Detection

Autonomous parking is an active field of automatic driving in both industry and academia. Parking slot detection (PSD) based on a panoramic image can effectively improve the perception of a parking space and the surrounding environment, which enhances the convenience and safety of parking. The challenge of PSD implementation is identifying the parking slot in real-time based on images obtained from the around view monitoring (AVM) system, while maintaining high recognition accuracy. This paper proposes a real-time parking slot detection (RPSD) network based on semantic segmentation, which implements real-time parking slot detection on the panoramic surround view (PSV) dataset and avoids the constraint conditions of parking slots. The structural advantages of the proposed network achieve real-time semantic segmentation while effectively improving the detection accuracy of the PSV dataset. The cascade structure reduces the operating parameters of the whole network, ensuring real-time performance, and the fusion of coarse and detailed features extracted from the upper and lower layers improves segmentation accuracy. The experimental results show that the final mIoU of this work is 67.97% and the speed is up to 32.69 fps, which achieves state-of-the-art performance with the PSV dataset.
Diet Shift May Trigger LuxS/AI-2 Quorum Sensing in Rumen Bacteria

Recent studies have revealed that LuxS/AI-2 quorum sensing (QS) is the most universal cell-to-cell communication in rumen bacteria; however, it remains unknown how they respond to nutritional stress from a diet shift. This study aimed to explore whether a diet shift could trigger rumen bacterial LuxS/AI-2 QS and its influences on rumen fermentation characteristics and bacterial community diversity and composition. A total of fifteen Hu sheep were selected to undergo a pre-shift diet (Pre, concentrate to forage ratio 75:25) for one month and then abruptly switch to a post-shift diet (Post, concentrate to forage ratio 49:51). Results showed that the serum cortisol and immunoglobulin G concentrations were higher in Post than in Pre (p < 0.05). The microbial density, AI-2 concentration, biofilm formation, and the gene expression of ftsH were higher in Post when compared with Pre (p < 0.05), whilst the gene expression of luxS tended to be lower in Post (p = 0.054). The molar concentration of valerate and fermentation efficiency decreased after the diet shift, while the acetate to propionate ratio and the molar proportion of butyrate were higher in Post compared to Pre (p < 0.05). Moreover, the diet shift increased the richness of ruminal bacteria and the relative abundances of Roseburia, Prevotellaceae UCG-001, and Lachnospira, and decreased the relative abundances of Prevotella, Megasphaera, and Dialister (p < 0.05). A difference in trends was also observed in an analysis of similarity (R = 0.1208 and p = 0.064). This study suggests that a diet shift could trigger rumen bacterial LuxS/AI-2 QS by altering microbial density, AI-2 concentration, biofilm formation, and related gene expression, as well as affect the rumen fermentation pattern and bacterial community diversity and composition. This study may provide insight into a potential strategy for relieving nutritional stress via regulating bacterial communication.
Unlicensed Spectrum Allocation for LTE and Wi-Fi Coexistence with HAP

In order to accommodate the ever-increasing traffic demands, numerous approaches have been developed to improve spectrum utilization. Among others, the coexistence of LTE (Long-Term Evolution) and Wi-Fi, addressed by the 3GPP (3rd Generation Partnership Project) with hyper access points (HAPs) as bridges, is well recognized as a promising candidate solution. Aimed at improving the spectrum utilization of the unlicensed bands by following LTE-Unlicensed (LTE-U), this article contributes to the determination of the optimal time ratio, δ, for the time-division multiplexing of LTE and Wi-Fi over unlicensed bands. Symmetric allocation with a duty cycle of 50% cannot be an optimal option. Asymmetric allocation according to the quality of service (QoS) requirements and traffic demands should be considered. The problem is formulated as an optimization problem optimizing the total throughput. The lower and upper bounds of δ are obtained according to the QoS requirements of Wi-Fi and the admission control requirements of LTE. The detailed procedure for finding an adequate δ is developed and presented. A series of simulations are conducted to demonstrate the feasibility and effectiveness of the proposed approach. Simulation results show that the proposed approach improves the total throughput without compromising the fairness of Wi-Fi, as intended. Ten percent of improvement in throughput compared with LTE-U can be achieved.
Antimicrobial Resistance and Its Spread Is a Global Threat

Antimicrobial resistance (AMR) is a challenge to human wellbeing the world over and is one of the more serious public health concerns. AMR has the potential to emerge as a serious healthcare threat if left unchecked, and could put into motion another pandemic. This establishes the need for the establishment of global health solutions around AMR, taking into account microdata from different parts of the world. The positive influences in this regard could be establishing conducive social norms, charting individual and group behavior practices that favor global human health, and lastly, increasing collective awareness around the need for such action. Apart from being an emerging threat in the clinical space, AMR also increases treatment complexity, posing a real challenge to the existing guidelines around the management of antibiotic resistance. The attribute of resistance development has been linked to many genetic elements, some of which have complex transmission pathways between microbes. Beyond this, new mechanisms underlying the development of AMR are being discovered, making this field an important aspect of medical microbiology. Apart from the genetic aspects of AMR, other practices, including misdiagnosis, exposure to broad-spectrum antibiotics, and lack of rapid diagnosis, add to the creation of resistance. However, upgrades and innovations in DNA sequencing technologies with bioinformatics have revolutionized the diagnostic industry, aiding the real-time detection of causes of AMR and its elements, which are important to delineating control and prevention approaches to fight the threat.
Climate Change SOS: Addressing Climate Impacts within a Climate Change Spiral of Silence

Abstract This study uncovers the dynamics that exist among key government officials working to address impacts of climate variability and change within a hostile socio-political setting. Through qualitative analysis of interviews with Oklahoma government officials, this study finds evidence of a climate change spiral of silence impacting key government decision-making processes through the suppression of climate change discourse and science. We argue that settings hostile toward climate action (where there is pervasive skepticism/denial of anthropogenic climate change and opposition to climate mitigations/adaptation policies) are primed for normative dynamics that reinforce a climate change spiral of silence.
Isabelle: A Generic Theorem Prover

Foundations. - Getting started with Isabelle. - Advanced methods. - Basic use of Isabelle. - Proof management: The subgoal module. - Tactics. - Tacticals. - Theorems and forward proof. - Theories, terms and types. - Defining logics. - Syntax transformations. - Substitution tactics. - Simplification. - The classical reasoner. - Basic concepts. - First-order logic. - Zermelo-Fraenkel set theory. - Higher-order logic. - First-order sequent calculus. - Constructive Type Theory. - Syntax of Isabelle Theories.
A Reappraisal of Dependency Length Minimization as a Linguistic Universal

Abstract Dependency length minimization is widely regarded as a cross-linguistic universal reflecting syntactic complexity in natural languages. A typical way to operationalize dependency length in corpus-based studies has been to count the number of words between syntactically related words. However, such a formulation ignores the syntactic nature of the linguistic material that intervenes a dependency. In this work, we investigate if the number of syntactic heads (rather than the number of words) that intervene a dependency better captures the syntactic complexity across languages. We demonstrate that the dependency length minimization constraint in terms of the number of words could arise as a consequence of constraints on the intervening heads and the tree properties such as node arity. The current study highlights the importance of syntactic heads as central regions of structure building during processing. The results show that when syntactically related words are nonadjacent, increased structure building in the intervening region is avoided.
Super-resolution fluorescence blinking imaging using compressive sensing

Abstract. Super-resolution optical fluctuation imaging (SOFI) is an extensively used super-resolution (SR) imaging technique. The sample condition and imaging system are simpler than most SR systems, and the cusp-artifacts limit the resolution of high-order SOFI. To improve the resolution of SOFI, an alternative method is to improve the reconstruction algorithm. Here, compressive sensing (CS) is used in SOFI to improve its resolution. The detailed CS reconstruction algorithm is chosen as multiple measurement vector model sparse Bayesian learning (MSBL). We demonstrate that MSBL can achieve higher than threefold resolution improvement in simulation under certain conditions. The SOFI experiment analysis demonstrates that MSBL can improve the resolution about 2.5-fold compared with the diffraction limit. All results prove that MSBL has a higher resolving ability compared with other algorithms. Our results prove that CS is a broad applicability tool for most of the existing SR microscopy techniques and can be applied in 3D and live-cell SR fluorescence microscopy imaging in the future.
A Transcendental Phenomenology into How Teacher Educators Address Social and Psychological Elements of Teachers' Professional Identity

Addressing social and psychological elements of teachers' professional identities is crucially important to develop teachers’ knowledge and practice concerning social and psychological issues in their classes. Thus, this study was an attempt to investigate how Iranian EFL teacher educators addressed social and psychological elements in teacher education programs to develop teachers’ professional identities. To that end, a series of phenomenological interviews were conducted with four EFL teacher educators to delve into their past, current, and future practices. Moreover, the syllabi covered by the EFL teacher educators were analyzed as a verification of the data obtained through phenomenological interviews. Explicitation of data was done through using Moustakas's (1994) systematic approach to analyze the interviews. The thematic analysis of phenomenological interviews indicated that EFL teacher educators addressed the social elements in teacher education programs by introducing sociolinguistics, collaborative activities, social negotiation, social awareness-raising, and social and cultural engagement. Moreover, the findings indicated that teacher educators addressed EFL teachers' psychological elements through action research, critical thinking, autonomy-enhancing aids, and helping teachers understand emotional work values. It can be concluded that Iranian EFL teacher educators address social and psychological elements of EFL teachers’ professional identities through various approaches which have been discussed in the current study. Using approaches that can affect psychological and social elements of professional identity simultaneously is the implication of the current study that should be followed by the EFL teacher educators.
Anterior-Posterior and Inter-Limb Lower Body Strength Asymmetry in Soccer, Basketball, Futsal, and Volleyball Players

Background and Objectives: The purpose of this study was twofold: (1) to examine strength asymmetries in elite athletes of different sports and (2) to examine the magnitude of asymmetries between elite and u18 athletes. Materials and Methods: A total of 254 athletes participated in this study. For the first purpose of the study, the group consisted of adult professional male basketball players (n = 30), elite male (n = 30) and female soccer players (n = 20), male futsal players (n = 30), elite male goalkeepers (n = 22), and professional female volleyball players (n = 20). For the second purpose, male youth goalkeepers (n = 22), youth female (n = 20) and male soccer players (n = 30), and youth male basketball players (n = 30) were compared to the adult athletes of the same sport. Asymmetries were measured utilizing a Humac Norm and Rehabilitation device. Testing included three maximal concentric flexion and extension repetitions at an angular speed of 60°/s. The differences in asymmetries were assessed using ANOVA followed by an LS means post-hoc analysis. An independent samples t-test was used to identify the differences between adult and youth players. Results: It was indicated that none of the groups demonstrated asymmetries greater than 10%, other than the elite female soccer players and female volleyball players. Significant differences were demonstrated between youth and adult soccer players (males and females), with the adult groups demonstrating increased asymmetries. Conclusions: Special consideration should be given to female soccer players and volleyball players, as soccer and volleyball practice and competition at the professional level may induce greater lower -limb asymmetries. The isokinetic parameters can be useful for planning strength and conditioning interventions in order to reduce or prevent those imbalances. Additional unilateral and bilateral jumping testing is encouraged for the verification of imbalances.
Meso scale flextensional piezoelectric actuators

We present an ultra-thin meso scale piezoelectric actuator consisting of a piezoceramic beam and a carbon fiber displacement-amplification frame. We show that the actuator can be designed to achieve a wide range of force/displacement characteristics on the mN/μm scales. The best performing design achieved a free displacement of 106 μm and a blocked force of 73 mN, yielding a total energy density of 0.51 Jkg − 1 for the 7.6 mg system. We describe a printed circuit MEMS process for fabricating the actuator that incorporates laser micromachining, chemical vapor deposition, and precision carbon fiber lamination. Lastly, we report the incorporation of the actuator into a microgripper and describe other promising application opportunities in micro-optics and micro-laser systems.
Disentangling the Swedish fertility decline of the 2010s

BACKGROUND The downward fertility trend in Western countries during the 2010s is puzzling, not least in the Nordic region. OBJECTIVE In order to better understand its driving forces, we examine whether the decline is driven by differential behavior or compositional changes across sociodemographic population subgroups, for the empirical case of Sweden. METHODS Event-history techniques are applied to register data of the Swedish-born population to provide an in-depth analysis of the sociodemographic profile of the fertility decline.
Photothermal spectroscopy and micro/nanofluidics

Photothermal spectroscopy, a remarkable detection method that can analyze microscale objects in a noninvasive and nondestructive manner, has been successfully coupled with micro/nanofluidic devices. Specifically, methods that employ a thermal lens microscope (TLM), including a photothermal optical phase shift and photothermal optical diffraction, are a powerful tool for the sensitive detection of nonfluorescent or nonlabeled molecules in micro/nanofluidic channels. This review focuses on the family of TLMs in terms of their historical development. Their recent applications, ranging from separation, particle, biomedical, energy, and environmental analyses, are summarized, and future perspectives in nanoscale liquid science, system integration, and biological studies, such as single-cell analyses, are also discussed.