Miracle-dz/UniFAR-FTUs huggingface dataset:
Dynamic emergence of domino effects in systems of interacting tipping elements in ecology and climate

In ecology, climate and other fields, systems have been identified that can transition into a qualitatively different state when a critical threshold or tipping point in a driving process is crossed. An understanding of those tipping elements is of great interest given the increasing influence of humans on the biophysical Earth system. Tipping elements are not independent from each other as there exist complex interactions, e.g. through physical mechanisms that connect subsystems of the climate system. Based on earlier work on such coupled nonlinear systems, we systematically assessed the qualitative asymptotic behavior of interacting tipping elements. We developed an understanding of the consequences of interactions on the tipping behavior allowing for domino effects and tipping cascades to emerge under certain conditions. The application of these qualitative results to real-world examples of interacting tipping elements shows that domino effects with profound consequences can occur: the interacting Greenland ice sheet and thermohaline ocean circulation might tip before the tipping points of the isolated subsystems are crossed. The eutrophication of the first lake in a lake chain might propagate through the following lakes without a crossing of their individual critical nutrient input levels. The possibility of emerging domino effects calls for the development of a unified theory of interacting tipping elements and the quantitative analysis of interacting real-world tipping elements.
On the limits of experimental knowledge

To demarcate the limits of experimental knowledge, we probe the limits of what might be called an experiment. By appeal to examples of scientific practice from astrophysics and analogue gravity, we demonstrate that the reliability of knowledge regarding certain phenomena gained from an experiment is not circumscribed by the manipulability or accessibility of the target phenomena. Rather, the limits of experimental knowledge are set by the extent to which strategies for what we call ‘inductive triangulation’ are available: that is, the validation of the mode of inductive reasoning involved in the source-target inference via appeal to one or more distinct and independent modes of inductive reasoning. When such strategies are able to partially mitigate reasonable doubt, we can take a theory regarding the phenomena to be well supported by experiment. When such strategies are able to fully mitigate reasonable doubt, we can take a theory regarding the phenomena to be established by experiment. There are good reasons to expect the next generation of analogue experiments to provide genuine knowledge of unmanipulable and inaccessible phenomena such that the relevant theories can be understood as well supported. This article is part of a discussion meeting issue ‘The next generation of analogue gravity experiments’.
Use of a Capsule Network to Detect Fake Images and Videos

The revolution in computer hardware, especially in graphics processing units and tensor processing units, has enabled significant advances in computer graphics and artificial intelligence algorithms. In addition to their many beneficial applications in daily life and business, computer-generated/manipulated images and videos can be used for malicious purposes that violate security systems, privacy, and social trust. The deepfake phenomenon and its variations enable a normal user to use his or her personal computer to easily create fake videos of anybody from a short real online video. Several countermeasures have been introduced to deal with attacks using such videos. However, most of them are targeted at certain domains and are ineffective when applied to other domains or new attacks. In this paper, we introduce a capsule network that can detect various kinds of attacks, from presentation attacks using printed images and replayed videos to attacks using fake videos created using deep learning. It uses many fewer parameters than traditional convolutional neural networks with similar performance. Moreover, we explain, for the first time ever in the literature, the theory behind the application of capsule networks to the forensics problem through detailed analysis and visualization.
Thieves on Sesame Street! Model Extraction of BERT-based APIs

We study the problem of model extraction in natural language processing, in which an adversary with only query access to a victim model attempts to reconstruct a local copy of that model. Assuming that both the adversary and victim model fine-tune a large pretrained language model such as BERT (Devlin et al. 2019), we show that the adversary does not need any real training data to successfully mount the attack. In fact, the attacker need not even use grammatical or semantically meaningful queries: we show that random sequences of words coupled with task-specific heuristics form effective queries for model extraction on a diverse set of NLP tasks, including natural language inference and question answering. Our work thus highlights an exploit only made feasible by the shift towards transfer learning methods within the NLP community: for a query budget of a few hundred dollars, an attacker can extract a model that performs only slightly worse than the victim model. Finally, we study two defense strategies against model extraction---membership classification and API watermarking---which while successful against naive adversaries, are ineffective against more sophisticated ones.
Using braids to quantify interface growth and coherence in a rotor-oscillator flow

The growth rate of material interfaces is an important proxy for mixing and reaction rates in fluid dynamics, and can also be used to identify regions of coherence. Estimating such growth rates can be difficult, since they depend on detailed properties of the velocity field, such as its derivatives, that are hard to measure directly. When an experiment gives only sparse trajectory data, it is natural to encode planar trajectories as mathematical braids, which are topological objects that contain information on the mixing characteristics of the flow, in particular through their action on topological loops. We test such braid methods on an experimental system, the rotor-oscillator flow, which is well-described by a theoretical model. We conduct a series of laboratory experiments to collect particle tracking and particle image velocimetry data, and use the particle tracks to identify regions of coherence within the flow that match the results obtained from the model velocity field. We then use the data to estimate growth rates of material interface, using both the braid approach and numerical simulations. The interface growth rates follow similar qualitative trends in both the experiment and model, but have significant quantitative differences, suggesting that the two are not as similar as first seems. Our results shows that there are challenges in using the braid approach to analyze data, in particular the need for long trajectories, but that these are not insurmountable.
Sequence-to-Sequence Automatic Speech Recognition with Word Embedding Regularization and Fused Decoding

In this paper, we investigate the benefit that off-the-shelf word embedding can bring to the sequence-to-sequence (seq-to-seq) automatic speech recognition (ASR). We first introduced the word embedding regularization by maximizing the cosine similarity between a transformed decoder feature and the target word embedding. Based on the regularized decoder, we further proposed the fused decoding mechanism. This allows the decoder to consider the semantic consistency during decoding by absorbing the information carried by the transformed decoder feature, which is learned to be close to the target word embedding. Initial results on LibriSpeech demonstrated that pre-trained word embedding can signifi-cantly lower ASR recognition error with a negligible cost, and the choice of word embedding algorithms among Skip-gram, CBOW and BERT is important.
Lithium in red giant stars: Constraining non-standard mixing with large surveys in the Gaia era

Context. Li is extensively known to be a good tracer of non-standard mixing processes occurring in stellar interiors. Aims. We present the results of a new large Li survey in red giant stars and combine it with surveys from the literature to probe the impact of rotation-induced mixing and thermohaline double-diffusive instability along stellar evolution. Methods. We determined the surface Li abundance for a sample of 829 giant stars with accurate Gaia parallaxes for a large sub-sample (810 stars) complemented with accurate HIPPARCOS parallaxes (19 stars). The spectra of our sample of northern and southern giant stars were obtained in three ground-based observatories (Observatoire de Haute-Provence, ESO-La Silla, and the Mc Donald Observatory). We determined the atmospheric parameters (Teff, log(g) and [Fe/H]), and the Li abundance. We used Gaia parallaxes and photometry to determine the luminosity of our objects and we estimated the mass and evolution status of each sample star with a maximum-likelihood technique using stellar evolution models computed with the STAREVOL code. We compared the observed Li behaviour with predictions from stellar models, including rotation and thermohaline mixing. The same approach was used for stars from selected Li surveys from the literature. Results. Rotation-induced mixing accounts nicely for the Li behaviour in stars warmer than about 4200 K, independently of the mass domain. For stars with masses lower than 2 M⊙ thermohaline mixing leads to further Li depletion below the Teff of the RGB bump (about 4000 K), and on the early asymptotic giant branch, as observed. Depending on the definition we adopt, we find between 0.8 and 2.2% of Li-rich giants in our new sample. Conclusions.Gaia puts a new spin on the understanding of mixing processes in stars, and our study confirms the importance of rotation-induced processes and of thermohaline mixing. However asteroseismology is required to definitively pinpoint the actual evolution status of Li-rich giants.
Quantized Graphs and Quantum Error Correction

Graph theory is important in information theory. We introduce a quantization process on graphs and apply the quantized graphs in quantum information. The quon language provides a mathematical theory to study such quantized graphs in a general framework. We give a new method to construct graphical quantum error correcting codes on quantized graphs and characterize all optimal ones. We establish a further connection to geometric group theory and construct quantum low-density parity-check stabilizer codes on the Cayley graphs of groups. Their logical qubits can be encoded by the ground states of newly constructed exactly solvable models with translation-invariant local Hamiltonians. Moreover, the Hamiltonian is gapped in the large limit when the underlying group is infinite.
HUBERT Untangles BERT to Improve Transfer across NLP Tasks

We introduce HUBERT which combines the structured-representational power of Tensor-Product Representations (TPRs) and BERT, a pre-trained bidirectional Transformer language model. We show that there is shared structure between different NLP datasets that HUBERT, but not BERT, is able to learn and leverage. We validate the effectiveness of our model on the GLUE benchmark and HANS dataset. Our experiment results show that untangling data-specific semantics from general language structure is key for better transfer among NLP tasks.
Increase in Ty Lymphocytes in B‐Cell Chronic Lymphocytic Leukaemia

Summary. The proportion of Tγ and Tμ lymphocytes was studied in 40 cases of B‐chronic lymphocytic leukaemia (B‐CLL) and six of B‐prolymphocytic leukaemia (B‐PLL). The significant increase in Ty cells, previously reported in two small B‐CLL series, was confirmed and shown to be directly correlated with the clinical stages of the disease (P < 0.01 to < 0.001). The normal Tμ: Tγ ratio (2.3:1) was reversed in B‐CLL (1:1.4) and B‐PLL (1:1.9). The proportion of Tμ cells was decreased but was not related to stage.
ZPD Teaching Strategies for Deep Reinforcement Learning from Demonstrations

Learning from demonstrations is a popular tool for accelerating and reducing the exploration requirements of reinforcement learning. When providing expert demonstrations to human students, we know that the demonstrations must fall within a particular range of difficulties called the "Zone of Proximal Development (ZPD)". If they are too easy the student learns nothing, but if they are too difficult the student is unable to follow along. This raises the question: Given a set of potential demonstrators, which among them is best suited for teaching any particular learner? Prior work, such as the popular Deep Q-learning from Demonstrations (DQfD) algorithm has generally focused on single demonstrators. In this work we consider the problem of choosing among multiple demonstrators of varying skill levels. Our results align with intuition from human learners: it is not always the best policy to draw demonstrations from the best performing demonstrator (in terms of reward). We show that careful selection of teaching strategies can result in sample efficiency gains in the learner's environment across nine Atari games
Okulöncesi Öğretmenliği Lisans Programı Derslerinin Öğretim Elemanları Tarafından Genel Bir Bakış Açısıyla Değerlendirilmesi

Okuloncesi egitim bireysel ve toplumsal gelisim icin cok onemlidir Bu nedenle okuloncesi ogretmenligi egitiminin nitelikli olmasi gerekmektedir Bu calisma 2006 ogretim yilinda uygulanmaya baslanan Okuloncesi Ogretmenligi Lisans Programini OOLP ogretim elemanlarinin goruslerine dayali olarak degerlendirmektedir Calismanin verileri Turkiye? deki 26 universitenin Okuloncesi Egitimi Ogretmenligi Anabilim Dali? nda gorevli 65 ogretim elemanindan bir anket ile toplanmistir Calismada ogretim elemanlarinin cogu programdaki derslerin uygun oldugunu belirtmistir Bunun yaninda programa 70 dersin daha eklenmesi ve 30 dersin adinin degistirilmesini onermislerdir Onerilen ders adlarinda ? okuloncesi egitim? sozcuklerini kullanma egilimleri vardir Calismanin sonuclari Okuloncesi Ogretmenligi Lisans Programi uzerinde yonetsel ve uygulama acisindan ayrintili olarak dusunulmesini saglayabilir; ileride uygulanacak programlar ve bu programlarin degerlendirilmesi icin kaynak olusturabilir
Teacher Certification in Indonesia: A Confusion of Means and Ends

In 2006, Indonesia started implementing a nation-wide program of teacher certification with the aim to certify as many as 2.3 million teachers in 2015 with the budgetary cost of as much as US$460 million. Despite the magnitude and the importance of this program, there has been no quantitative study to evaluate the impact of such program on student’s achievement. In this study, we conducted a teacher survey in the Greater Bandung Area and collected the information on average national exam scores of the students of certified and not-certified teachers. We use two different impact evaluation techniques namely Propensity Score Matching (PSM) and Difference-in-Difference (DD) to evaluate the impact of certification. Both methods suggest that teacher certification has no impact on student’s achievement. The certification program may have improved teacher’s living standard as remuneration increase is an elemental part of it, yet its formally-stated goal to improve the quality of education as should be indicated in better students’ performance may not have been achieved. This program, being the largest in the nation’s history, may have confused means and ends.
Attitudes towards the Diagnosis and Treatment of Depression among South Asian Muslim Americans

Attitudes towards the Diagnosis and Treatment of Depression among South Asian Muslim Americans Sadia Rahman Chaudhury While Muslim Americans are one of the fastest growing communities in the United States, very little is known about their mental health needs or concerns. In an effort to better understand their mental health needs, this study explores the attitudes towards the diagnosis and treatment of depression among South Asian Muslim Americans, specifically examining how acculturation shapes these attitudes. A sample of 427 South Asian Muslim Americans (mean age 30.67 years, 73.8% female) completed an anonymous survey on the internet. Participants answered questions about how strongly they agreed with certain diagnostic and treatment recommendations after reading two clinical vignettes, and completed the Attitudes towards Seeking Professional Psychological Help Scale and the Acculturation Rating Scale for Mexican-Americans II. Participants were also asked about their personal experiences with depression, religious identity; and demographic information. Results indicated that educated participants were more accepting of a clinical diagnosis of depression, while females and educated participants had more positive attitudes towards seeking professional psychological help for depression. Acculturation predicted more positive attitudes toward seeking professional psychological help for depression, but did not predict acceptance of a clinical diagnosis of depression, comfort level talking to people outside the family, likelihood of seeking professional help, or importance of ethnic match with mental health provider. Exploratory analyses were conducted to determine how personal history of depression shapes attitudes; however, this variable was not particularly salient in shaping attitudes in this sample. While the results suggest that acculturation did not play as strong a role in predicting attitudes as initially anticipated, several limitations, including the fact that the instrument used to measure acculturation and enculturation in this study has not been validated in this sample and that the sample may be more acculturated than the general South Asian Muslim American population, must be taken into consideration. The results of this study begin to shed light on the attitudes towards depression and its treatment in this community. Future studies should further explore the roles of acculturation and enculturation, while also collecting more personal qualitative information to more fully understand the experiences and needs of South Asian Muslim Americans.
Effects of preoperative anti-tumour necrosis factor alpha infusion timing on postoperative surgical site infection in inflammatory bowel disease: A systematic review and meta-analysis

Background Anti-tumour necrosis factor alpha agents (anti-TNF-α) have been widely used in patients with inflammatory bowel disease (IBD). However, few published meta-analyses have focused on timing of the last infusion before surgery. We evaluated the relationship between preoperative anti-TNF-α timing and postoperative surgical site infection to provide additional evidence for surgeons to choose appropriate dates for surgery. Methods We searched from inception until January 2019 for studies that documented postoperative complications of adults with IBD who underwent preoperative anti-TNF-α treatment. Primary outcomes of included studies were the odds ratios of preoperative anti-TNF-α time frames (4, 8 and 12 weeks). In addition, surgical site infection and its subtypes (anastomotic leakage, abscesses and wound infection) were analysed. Results Twenty-seven publications were included. No significant difference between anti-TNF-α and control cohorts was observed for most postoperative surgical site infections (or its subtypes) when the preoperative anti-TNF-α infusion time window was within 4, 8 or 12 weeks. Additionally, no significant difference in postoperative complications was observed between preoperative anti-TNF-α windows of within four weeks and more than four weeks. Conclusions In terms of surgical site infection and its subtypes, anti-TNF-α may be safe for ulcerative colitis and Crohn’s disease patients who receive their last infusion of anti-TNF-α more than four weeks before surgery. We also found no evidence that anti-TNF-α was a risk factor when administered within four weeks, with the exception of subgroup results from a single study. Stratified by time window, use of anti-TNF-α until surgery has the potential to become a more considered strategy in clinical practice.
Postpartum Depression in Men

Postpartum depression (PPD) is a form of major depressive disorder (MDD) and has traditionally been defined as occurring in women within three months to a year following childbirth (McCoy, 2011). However, this phenomenon has also been observed in men after their wives or partners give birth. The terminology used to described depression in males following the birth of a child has not yet been standardized. Some phrasing includes “paternal postpartum depression”, and “postpartum psychiatric disorder, depressed mood, and distress” (Schumacher, 2008). For the purposes of this chapter, “paternal PPD” will be used. Although the research in men has been taking place for a much shorter time and with fewer patients than for women, valuable insights have already been gained.
Radical Hysterectomy and Pelvic Lymphadenectomy at a Community Teaching Hospital

Surgical management of cervical carcinoma by radical hysterectomy has been proven a highly effective method in treating early-stage disease. The purpose of this study was to evaluate the efficacy and safety of radical hysterectomy for the treatment of early-stage (I-IIA) cervical carcinoma at our institution. A retrospective analysis of data on 40 patients with cervical cancer undergoing radical hysterectomy over an 8-year period (1994-2002) was performed. The mean age of the patients was 41.5 years. The most common histology was squamous cell carcinoma (67.5%). Adenocarcinoma comprised 17.5% of cases and adenosquamous cancers 15% of cases. The mean blood loss was 442 mL. The average operating time was 3 hours and 36 minutes. The average duration of hospital stay was 6 days. Metastatic carcinoma to the regional lymph nodes was found in 15% of the cases. Overall survival was 92.5%. There were no operative mortalities or fistulae. With proper patient selection and excellent operative technique, survival rat.
Exertional Rhabdomyolysis: A Retrospective Population-based Study.

PURPOSE To evaluate the incidence and characteristics of exertional rhabdomyolysis (ER) in a population-based cohort. METHODS A retrospective cohort study was performed in Olmsted County, Minnesota, from 2003-2015. Incident ER cases were ascertained through the Rochester Epidemiology Project (REP) medical record linkage system through electronic searches of ICD-9 codes and clinical note text. Population incidence rate was calculated using corresponding calendar-year- and sex specific REP census populations. Descriptive statistics were used. RESULTS 431 cases in 430 patients met inclusion criteria for rhabdomyolysis; 4.9% of cases (n= 20; males n=18; Caucasian n=17) were ER, with one recurrence. There were no deaths secondary to ER. The age and sex adjusted incidence rate of ER was 1.06 ± 0.24 (95% CI 0.59-1.52) per 100,000 person-years. Endurance activity (n=7), manual labor (n=5), and weight lifting (n=4) were common causes. Complications included kidney injury (n=5), mild electrolyte abnormalities (n=10), elevated transaminases (n=12), and minor electrocardiographic abnormalities (n=4). A majority of patients were hospitalized (n=16) for a median of two days, had mild abnormalities in renal and liver function, and electrolytes; and were discharged without sequelae. CONCLUSION ER in the civilian population occurs at a much lower incidence than the military population. The most common causes were endurance exercise, manual labor, and weight lifting. The majority of cases were treated conservatively with intravenous fluid resuscitation during a brief hospital stay, and all were discharged without sequela. Only one case of recurrence occurred in this cohort, indicating the recurrence rate was low.