Miracle-dz/UniFAR-FTUs huggingface dataset:
Dynamical Quantum Phase Transitions from Quantum Optics Perspective

It is shown that dynamical quantum phase transitions observed as singularities in the Loschmidt rate singularities bear close resemblance to standard Rabi oscillations known from dynamics of two-level systems. For some many-body systems this analogy may go even further and the behaviour observed for e.g. transverse Ising chain can be directly mapped to such simple dynamics. It is explained why A simple link between Loschmidt echo singularities and quantum scars is suggested.
Reinforcement Learning with Intrinsic Affinity for Personalized Asset Management

The common purpose of applying reinforcement learning (RL) to asset management is the maximization of proﬁt. The extrinsic reward function used to learn an optimal strategy typically does not take into account any other preferences or constraints. We have developed a regularization method that ensures that strategies have global intrinsic afﬁni-ties, i.e., different personalities may have preferences for certain assets which may change over time. We capitalize on these intrinsic policy afﬁnities to make our RL model inherently interpretable. We demonstrate how RL agents can be trained to orchestrate such individual policies for particular personality proﬁles and still achieve high returns.
Who Benefits from Political Connections in Brazilian Municipalities

A main issue in improving public sector efﬁciency is to understand to what extent public appointments are based on worker capability, instead of being used to reward political supporters (patronage). I contribute to a recent literature documenting patronage in public sector employment by establishing what type of workers beneﬁt the most from political connections. Under the (empirically supported) assumption that in close elections the result of the election is as good as random, I estimate a causal forest to identify heterogeneity in the conditional average treatment effect of being afﬁliated to the party of the winning mayor. Contrary to previous literature, for most positions we ﬁnd positive selection on education, but a negative selection on (estimated) ability. Overall, unemployed workers or low tenure employees that are newly afﬁliated to the winning candidate’s party beneﬁt the most from political connections, suggesting that those are used for patronage.
Generalizing to the Future: Mitigating Entity Bias in Fake News Detection

The wide dissemination of fake news is increasingly threatening both individuals and society. Fake news detection aims to train a model on the past news and detect fake news of the future. Though great efforts have been made, existing fake news detection methods overlooked the unintended entity bias in the real-world data, which seriously influences models' generalization ability to future data. For example, 97% of news pieces in 2010-2017 containing the entity 'Donald Trump' are real in our data, but the percentage falls down to merely 33% in 2018. This would lead the model trained on the former set to hardly generalize to the latter, as it tends to predict news pieces about 'Donald Trump' as real for lower training loss. In this paper, we propose an entity debiasing framework (ENDEF) which generalizes fake news detection models to the future data by mitigating entity bias from a cause-effect perspective. Based on the causal graph among entities, news contents, and news veracity, we separately model the contribution of each cause (entities and contents) during training. In the inference stage, we remove the direct effect of the entities to mitigate entity bias. Extensive offline experiments on the English and Chinese datasets demonstrate that the proposed framework can largely improve the performance of base fake news detectors, and online tests verify its superiority in practice. To the best of our knowledge, this is the first work to explicitly improve the generalization ability of fake news detection models to the future data. The code has been released at https://github.com/ICTMCG/ENDEF-SIGIR2022.
WHEN NATION BUILDING GOES SOUTH: DRAFT EVASION, GOVERNMENT REPRESSION, AND THE ORIGINS OF THE SICILIAN MAFIA

This paper claims that the emergence of the mafia in Sicily in the 19th century was in part caused by the discontent with the central government in the Sicilian society during the Italian unification process. From its establishment in 1861, the Kingdom of Italy’s central government introduced a range of nation building policies, including conscription, to strengthen internal stability. Still, in 1863 a key episode deeply compromised the state’s legitimacy in Sicily: a repressive military campaign ordered by the government to curb widespread draft evasion on the island. Historians like Alatri (1954) have argued that this campaign raised distrust in government and, in turn, helped the Sicilian mafia gain popular support across the region. In this paper I empirically investigate this hypothesis using an instrumental variables approach and show that the Sicilian mafia was more likely to develop in municipalities victimized by the 1863 repression campaign. In the main analysis I use original data from the Borsani-Bonfadini parliamentary enquiry on the conditions of public security in Sicily, held in 1875, to infer mafia presence at the town level. I combine this information with town-level data on the exposure to the 1863 military repression campaign, coded from archival material including military reports and notes written by Giuseppe Govone, the army general in charge of the military operations. Moreover, to generate exogenous variation in military repression, I rely on archival data containing information on the itinerary of the army. Using the pre-existing (1826) road network, I construct least cost paths connecting towns that had military barracks and were in the approximate path of the armies. I then calculate the distance from such optimal paths for each town in the dataset, to predict the respective exposure to repression. Finally, I remove the towns with military barracks from the sample, to identify the effect of repression in municipalities that were only treated incidentally due to their position along the shortest route between two garrison towns, in the spirit of the “inconsequential places” approach described by Redding and Turner (2015). 2019) and are also robust to different estimation techniques, such as propensity score and geographical matching. In a preliminary mechanism analysis, I also find that repression-hit towns experienced on average a lower trust in institutions in the short term, as measured by electoral turnout in 1867, compared to non-repressed towns. I complement these results with other qualitative evidence, taken from Sonnino (1881), Dickie (2004) and Govone’s personal letters, indicating a decrease in state legitimacy following the forceful introduction of conscription in Sicily. Overall, my findings suggest that coercive nation building reforms can unintentionally fuel organized crime and lead to the emergence of mafia-type organizations.
An Empirical Investigation of the Higher Educational Institutions’ Attractiveness as an Employer

In this competitive global market, where organisations struggle to attract the best talent, providing a unique employer value proposition (EVP), educational sector does not lag behind other sectors. In this study, the researchers tried to identify the dimensions of employer brand attractiveness among higher educational institutions’ potential faculty members. Furthermore, this study compares higher educational institutions’ attractiveness dimensions as employers among potential faculty members based on gender. A sample of 250 potential faculty members of higher educational institutions has been drawn from the national capital region (NCR), India. Confirmatory factor analysis and independent-sample t-test has been used to attain the objectives of the study. The study highlighted that economic value, social value, developmental value, interest value and application value significantly contribute to higher educational intuitions’ employer attractiveness. Furthermore, the independent sample t-test showed a significant difference among male and female potential employees of higher education institutions based on application value. The remaining dimensions, namely economic, social, developmental and interest, do not significantly differ. The study will help the management of higher educational institutions frame their unique EVP to attract quality academic talent.
Exploring constant speed with a visually impaired student by using a smartphone

Abstract Assistive technologies are frequently used to help disabled students to access core and expanded core curricula and to improve their functional, communication and literacy skills. Non-optical low vision devices and optical and tactile graphics technologies are some of the assistive technologies used by visually impaired students in today’s classrooms. In this study, we used a smartphone app, a Braille printer, and the Braille Spotdot embosser to design and develop a science activity to teach the concept of constant speed to a visually impaired student and two non-impaired peers using the 5E instructional model. The goal of the activity was to help students develop such skills as defining a problem, designing an experiment, and drawing graphs as well as to learn to compute unit rates and comprehend proportional relationships among variables.
Portal vein reconstruction with cryopreserved vascular grafts: A two‐edged sword

Portal vein anastomotic complications related to size discrepancy are important causes of morbidity and mortality in pediatric liver transplantation. Interposed vascular grafts in portal vein anastomosis can solve this problem. The aim of this study is to evaluate the results of pediatric liver transplantations performed using cryopreserved interposed vascular grafts between graft portal vein and superior mesenteric vein (SMV)‐splenic vein (SpV) confluence.
A dysmorphic mouse model reveals developmental interactions of chondrocranium and dermatocranium

The cranial endo- and dermal skeletons, which comprise the vertebrate skull, evolved independently over 470 million years ago and form separately during embryogenesis. In mammals, much of the cartilaginous chondrocranium is transient, undergoing endochondral ossification or disappearing, so its role in skull morphogenesis is not well studied and it remains an enigmatic structure. We provide complete three-dimensional (3D) reconstructions of the laboratory mouse chondrocranium from embryonic day 13.5 through 17.5 using a novel methodology of uncertainty-guided segmentation of phosphotungstic enhanced 3D microcomputed tomography images with sparse annotation. We evaluate the embryonic mouse chondrocranium and dermatocranium in 3D and delineate the effects of a Fgfr2 variant on embryonic chondrocranial cartilages and on the association with forming dermal bones using the Fgfr2cC342Y/+ Crouzon syndrome mouse. We show that the dermatocranium develops outside of and in shapes that conform to the chondrocranium. Results reveal direct effects of the Fgfr2 variant on embryonic cartilage, on chondrocranium morphology, and on the association between chondrocranium and dermatocranium development. Histologically we observe a trend of relatively more chondrocytes, larger chondrocytes, and/or more matrix in the Fgfr2cC342Y/+ embryos at all timepoints before the chondrocranium begins to disintegrate at E16.5. The chondrocrania and forming dermatocrania of Fgfr2cC342Y/+ embryos are relatively large, but a contrasting trend begins at E16.5 and continues into early postnatal (P0 and P2) timepoints, with the skulls of older Fgfr2cC342Y/+ mice reduced in most dimensions compared to Fgfr2c+/+ littermates. Our findings have implications for the study and treatment of human craniofacial disease, for understanding the impact of chondrocranial morphology on skull growth, and potentially on the evolution of skull morphology.
WFA-GPU: Gap-affine pairwise alignment using GPUs

Motivation Advances in genomics and sequencing technologies demand faster and more scalable analysis methods that can process longer sequences with higher accuracy. However, classical pairwise alignment methods, based on dynamic programming (DP), impose impractical computational requirements to align long and noisy sequences like those produced by PacBio, and Nanopore technologies. The recently proposed WFA algorithm paves the way for more efficient alignment tools, improving time and memory complexity over previous methods. However, high-performance computing (HPC) platforms require efficient parallel algorithms and tools to exploit the computing resources available on modern accelerator-based architectures. Results This paper presents the WFA-GPU, a GPU (Graphics Processing Unit)-accelerated tool to compute exact gap-affine alignments based on the WFA algorithm. We present the algorithmic adaptations and performance optimizations that allow exploiting the massively parallel capabilities of modern GPU devices to accelerate the alignment computations. In particular, we propose a CPU-GPU co-design capable of performing inter-sequence and intra-sequence parallel sequence alignment, combining a succinct WFA-data representation with an efficient GPU implementation. As a result, we demonstrate that our implementation outperforms the original multi-threaded WFA implementation between 1.5-7.7× and up to 17× when using heuristic methods on long and noisy sequences. Compared to other state-of-the-art tools and libraries, the WFA-GPU is up to 29× faster than other GPU implementations and up to four orders of magnitude faster than other CPU implementations. Availability WFA-GPU code and documentation are publicly available at https://github.com/quim0/WFA-GPU. Contact quim.aguado@uab.cat
Organelle-selective click labeling coupled with flow cytometry allows high-throughput CRISPR screening of genes involved in phosphatidylcholine metabolism

Lipids comprise biomembranes and are involved in many crucial cell functions. While cellular lipid synthesis and transport appear to be governed by intricate protein networks, the whole scheme is insufficiently understood. Although functional genome-wide screening should contribute to deciphering the regulatory networks of lipid metabolism, technical challenges remain – especially for high-throughput readouts of lipid phenotypes. Here, we coupled organelle-selective click labeling of phosphatidylcholine (PC) with flow cytometry-based CRISPR screening technologies to convert organellar PC phenotypes into a simple fluorescence readout for genome-wide screening. This technique, named O-ClickFC, was successfully applied in genome-scale CRISPR-knockout screens to identify previously reported genes associated with PC synthesis (PCYT1A, ACACA), vesicular membrane trafficking (SEC23B, RAB5C), and non-vesicular transport (PITPNB, STARD7). Moreover, this work revealed previously uncharacterized roles of FLVCR1 as a new choline transporter; CHEK1 as a post-translational regulator of the PC-synthetic pathway, and TMEM30A as responsible for translocation of PC to the outside of the plasma membrane bilayer. These findings demonstrate the versatility of O-ClickFC as an unprecedented platform for genetic dissection of cellular lipid metabolism.
Using total RNA quality metrics for time since deposition estimates in degrading bloodstains

Determining the time since deposition (TSD) of bloodstains would provide forensic scientists with critical information regarding the timeline of the events involving bloodshed. The physicochemical changes occurring to biomolecules as a bloodstain degrades can be used to approximate the TSD of bloodstains. Our study aims to quantify the timewise degradation trends and temperature dependence found in total RNA from bloodstains without the use of amplification, expanding the scope of the RNA TSD research which has previously targeted mRNA molecules. Whole bovine blood was stored in plastic microcentrifuge tubes at 21°C or 4°C and tested over different timepoints spanning one week. Nine RNA metrics were visually assessed and quantified using linear and mixed models; the RNA Integrity Number equivalent (RINe) and the DV200 demonstrated strong negative trends over time and statistical independence. The RINe model fit was high (R2 = 0.60), and while including the biological replicate as a random effect increased the fit for all RNA metrics, no significant differences were found between biological replicates stored at the same temperature for the RINe and DV200 metrics. Importantly, this suggests that these standardized metrics can likely be directly compared between scenarios and individuals, with DV200 having an inflection point at ∼28 hrs. This study provides a novel approach for blood TSD estimates, producing metrics that are not affected by inter-individual variation and improving our understanding of the rapid degradation occurring in bloodstains. HIGHLIGHTS Amplification-free analysis of total RNA in degrading bloodstains. Short-term RNA degradation assessment using high-resolution size measurements. Total RNA quality and quantity metrics were assessed across a one-week. Total RNA quality metrics demonstrated the strongest timewise trends. Biological replicates produced similar results for RNA quality metrics.
Att-SiamMask: Attention-based Network For Enhanced Visual Object Tracking

Visual object tracking finds the correspondence of the target object in consequent video frames given only the target position in the starting frame, which is considered a major challenging task in computer vision. Siamese-based trackers, such as, SiamRPN [1], SiamRPN++ [2], and SiamMask [3], have recently achieved a significant improvement in visual tracking. On large-scale benchmark datasets, the appearance invariant feature embedding is important for Siamese trackers’ success via pair-wise offline training. The object tracking process is treated as an optimization problem in Siamese networks which finds a similarity between the feature representatives corresponding to the target template as well as the learned features of the search area enclosing it. In this paper, a hybrid attention-based Siamese network (Att-SiamMask) for robust single object tracking is proposed that integrates the attention model with the Siamese network to improve its discrimination ability of the tracker at the level of semantic as well as textural features. In the proposed method, the attention weights are first determined in order to enhance the sub-Siamese network similarity matching and then, the attentive segments are located in order to cope with the search problem. Experimental results show the robustness of the proposed Att-SiamMask tracker to reduce the tracking drifts and failure compared with the recent competitive tracking methodologies that either use the Siamese network individually or those that combine Siamese and attention networks. The proposed Att-SiamMask outperforms the baseline SiamMask tracker mostly in the matter of expected average overlap and robustness metrics with significant improvement of 19 . 5% and 27% on publicly standard VOT2016 dataset and by and 21 . 5% and 22 . 5% on VOT2018 dataset.
HoloLogger: Keystroke Inference on Mixed Reality Head Mounted Displays

When using personal computing services in mixed reality (MR) such as online payment and social media, sensitive information and account passwords must be typed in MR. To design secure MR systems and build up user trust, it is imperative to first understand the security threat to the sensitive MR input. Although keystroke inference attacks by analyzing human-computer interaction in videos or via wireless signals have been successful, they require placing extra hardware near the user which is easily noticeable in practice. In this paper, we expose a more dangerous malware-based attack through the vulnerability that no permission is required for accessing MR motion data. We aim to monitor MR headset motion and infer the user input through a benign App. Realizing the attack system requires addressing unique challenges in MR such as six-degree-of-freedom (6DoF) device motion and no explicit motion signal for keystroke identification. To this end, we present HoloLogger, the first malware-based keystroke inference attack system on HoloLens. HoloLogger is empowered by a 6DoF-head-motion-driven key tracking scheme and an air-tap-pattern-based keystroke inference framework. Extensive evaluations with 25 users and 750 inference trials of passwords consisting of 4–8 lowercase English letters demonstrate that HoloLogger successfully achieves a top-5 accuracy of 93%. HoloLogger is also robust in various environments such as different user positions and input categories.
Validating the Benefits of Glanceable and Context-Aware Augmented Reality for Everyday Information Access Tasks

Glanceable Augmented Reality interfaces have the potential to provide fast and efficient information access for the user. However, where to place the virtual content and how to access them depend on the user context. We designed a Context-Aware AR interface that can intelligently adapt for two different contexts: solo and social. We evaluated information access using Context-Aware AR compared to current mobile phones and non-adaptive Glanceable AR interfaces. We found that in a solo scenario, compared to a mobile phone, the Context-Aware AR interface was preferred, easier, and significantly faster; it improved the user experience; and it allowed the user to better focus on their primary task. In the social scenario, we discovered that the mobile phone was slower, more intrusive, and perceived as the most difficult. Meanwhile, Context-Aware AR was faster for responding to information needs triggered by the conversation; it was preferred and perceived as the easiest for resuming conversation after information access; and it improved the user’s awareness of the other person’s facial expressions.
Low Cycle Fatigue of Thin Metal Films on Vibrating Silicon MEMS Cantilevers: Finite Element Modelling Facilitating Experimental Design

Within our reliability assessments, we study low cycle fatigue of thin metal films that are essential for the electrical connection in semiconductor devices. The dedicated test vehicle is a silicon-based micro-cantilever with a thin metal meander on top. Using this test vehicle we are able to perform our experiments under isothermal conditions, and, thus, without the interaction of thermal and mechanical influences. The test vehicle was initially designed to induce periodical compressive and tensile strain by resonant shaking of the cantilever beam. Within this paper, we explore the mechanical impact of deflections on the stress state inside the thin Aluminium layers by Finite Element (FE) simulations. This study aids the fundamental understanding of the material behaviour. The results are an important input for the definition of a specification for an upcoming custom-made, low-cost, tabletop test stand. Results indicate that external forces in the mN-range to the cantilever tip result in sufficiently large deflections up to a few mm. We found a linear relation between the maximum cantilever deflection and the maximum meander deflection. The minimum cantilever deflection needed to address low cycle fatigue (plastic deformation) of the 1-µm-thick Aluminium layer lies at 0.6 mm. In this case, part of the Aluminium meander also stays within the elastic region. Deflections greater than 0.6 mm lead to plastic deformation of the full meander length on top of the cantilever. The peak strain is reached shortly after the transition point from body to cantilever and decreases steadily until the end of the metal line.