Miracle-dz/UniFAR-FTUs huggingface dataset:
Some Zero Sum Problems in combinatorial number theory

This thesis comprises of three results each of which dealt in separate chapters. First chapter is of introductory nature, as the title suggest. And the other three chapters are devoted to three different problems. Following is a brief introduction to our results. 1. Let G be any finite abelian group of rank r with invariants n1, n2, · · · , nr. In other words, G = Zn1 ⊕Zn2 ⊕· · ·⊕Znr where ni’s are integers satisfying 1 < n1|n2| · · · |nr. The Davenport constant of a group G is defined as the smallest positive integer t such that every sequence of length t of elements of G has a non-empty zero-sum subsequence. It has been conjectured by Śliwa that, D(G) ≤ ∑i=1 ni. Thinking in the direction of this conjecture we have obtained the following upper bound on Davenport constant D(G), of G, D(G) ≤ nr+nr−1+(c(3)−1)nr−2+(c(4)−1)nr−3+· · ·+(c(r)−1)n1+1, where c(i)’s are Alon-Dubiner constants [10] for respective i’s. Also we shall give an application of Davenport’s constant to Quadratic sieve. 2. LetG be a finite abelian group with exp(G) = e. Let s(G) (respectively, η(G)) be the minimal positive integer t with the property that any sequence S of length t of elements ofG contains an e-term subsequence (respectively, a non-empty subsequence of length at most e) of S with sum zero. For the group of rank at most two this constant has been determined completely (see [45]). Looking at the problem for groups of rank greater that 2 gave rise to this result. Our problem is to determine value of s(C nm) under some constraints on n,m, and r. Let n,m and r be positive integers andm ≥ 3. Furthermore, η(C m) = ar(m− 1) + 1, for some constant ar depending on r and n is a fixed integer greater than or equal to, mr(c(r)m− ar(m− r) +m− 3)(m− 1)− (m+ 1) + (m+ 1)(ar + 1) m(m+ 1)(ar + 1) and s(C n) = (ar +1)(n− 1) + 1. In the above lower bound on n, c(r) is the Alon-Dubiner constant. Then s(C nm) = (ar + 1)(nm− 1) + 1. 3. Given an abelian group G of order n, and a finite non-empty subset A of integers, the Davenport constant of G with weight A, denoted by DA(G), is defined to be the least positive integer t such that every sequence (x1, · · · , xt) with xi ∈ G has a non-empty subsequence (xj1 , · · · , xjl) and ai ∈ A such that ∑l i=1 aixji = 0. Similarly, EA(G) is defined to be the least positive integer t such that every sequence (x1, · · · , xt) of length t of elements ofG has a subsequence (xj1 , · · · , xjn) such that ∑n i=1 aixji = 0, for some ai ∈ A. When G is of order n, one considers A to be a non-empty subset of {1, · · · , n− 1}. If G is the cyclic group Z/nZ we denote EA(G) and DA(G) by EA(n) and DA(n) respectively. Here we extend some results in an article of Adhikari et al. [5] and determine bounds for DRn(n) and ERn(n), where Rn = {x2 : x ∈ (Z/nZ)∗} and (Z/nZ) is a group of units modulo n. We follow some line of arguments in [5] and use a recent result of Yuan and Zeng [79], a theorem due to I. Chowla [24] and Kneser’s theorem [52].
Learning to Compose Representations of Different Encoder Layers towards Improving Compositional Generalization

Recent studies have shown that sequence-to-sequence (seq2seq) models struggle with compositional generalization (CG), i.e., the ability to systematically generalize to unseen compositions of seen components. There is mounting evidence that one of the reasons hindering CG is the representation of the encoder uppermost layer is entangled, i.e., the syntactic and semantic representations of sequences are entangled. However, we consider that the previously identified representation entanglement problem is not comprehensive enough. Additionally, we hypothesize that the source keys and values representations passing into different decoder layers are also entangled. Starting from this intuition, we propose \textsc{CompoSition} (\textbf{Compo}se \textbf{S}yntactic and Semant\textbf{i}c Representa\textbf{tion}s), an extension to seq2seq models which learns to compose representations of different encoder layers dynamically for different tasks, since recent studies reveal that the bottom layers of the Transformer encoder contain more syntactic information and the top ones contain more semantic information. Specifically, we introduce a \textit{composed layer} between the encoder and decoder to compose different encoder layers' representations to generate specific keys and values passing into different decoder layers. \textsc{CompoSition} achieves competitive results on two comprehensive and realistic benchmarks, which empirically demonstrates the effectiveness of our proposal. Codes are available at~\url{https://github.com/thinkaboutzero/COMPOSITION}.
Deep Omni-supervised Learning for Rib Fracture Detection from Chest Radiology Images

Deep learning (DL)-based rib fracture detection has shown promise of playing an important role in preventing mortality and improving patient outcome. Normally, developing DL-based object detection models requires a huge amount of bounding box annotation. However, annotating medical data is time-consuming and expertise-demanding, making obtaining a large amount of fine-grained annotations extremely infeasible. This poses a pressing need for developing label-efficient detection models to alleviate radiologists' labeling burden. To tackle this challenge, the literature on object detection has witnessed an increase of weakly-supervised and semi-supervised approaches, yet still lacks a unified framework that leverages various forms of fully-labeled, weakly-labeled, and unlabeled data. In this paper, we present a novel omni-supervised object detection network, ORF-Netv2, to leverage as much available supervision as possible. Specifically, a multi-branch omni-supervised detection head is introduced with each branch trained with a specific type of supervision. A co-training-based dynamic label assignment strategy is then proposed to enable flexible and robust learning from the weakly-labeled and unlabeled data. Extensive evaluation was conducted for the proposed framework with three rib fracture datasets on both chest CT and X-ray. By leveraging all forms of supervision, ORF-Netv2 achieves mAPs of 34.7, 44.7, and 19.4 on the three datasets, respectively, surpassing the baseline detector which uses only box annotations by mAP gains of 3.8, 4.8, and 5.0, respectively. Furthermore, ORF-Netv2 consistently outperforms other competitive label-efficient methods over various scenarios, showing a promising framework for label-efficient fracture detection. The code is available at: https://github.com/zhizhongchai/ORF-Net/tree/main.
Steepest Descent Neural Architecture Optimization: Escaping Local Optimum with Signed Neural Splitting

Developing efficient and principled neural architecture optimization methods is a critical challenge of modern deep learning. Recently, Liu et al.[19] proposed a splitting steepest descent (S2D) method that jointly optimizes the neural parameters and architectures based on progressively growing network structures by splitting neurons into multiple copies in a steepest descent fashion. However, S2D suffers from a local optimality issue when all the neurons become "splitting stable", a concept akin to local stability in parametric optimization. In this work, we develop a significant and surprising extension of the splitting descent framework that addresses the local optimality issue. The idea is to observe that the original S2D is unnecessarily restricted to splitting neurons into positive weighted copies. By simply allowing both positive and negative weights during splitting, we can eliminate the appearance of splitting stability in S2D and hence escape the local optima to obtain better performance. By incorporating signed splittings, we significantly extend the optimization power of splitting steepest descent both theoretically and empirically. We verify our method on various challenging benchmarks such as CIFAR-100, ImageNet and ModelNet40, on which we outperform S2D and other advanced methods on learning accurate and energy-efficient neural networks.
Understanding the Software of the Mind, Self and Culture: The Scientific Foundation of Indigenous and Cultural Psychology

The understanding of the nature and the software of the mind has generated immense debate in religion, philosophy, sciences and psychology. Drucker notes that the basic assumption about the reality is the foundation for science, axiom and algorithm adopted for the theory, concept and method. The assumption differentiates what is important from what is noise. In the medieval Europe, the Catholic Church provided a unified theory of the world as a reflection of God’s grand design and purpose. They held the power to define and thus had the power to control people’s lives. Their power was challenged during the Renaissance with the emergence of humanism. The Cartesian duality of separating the mind from body allowed the separation of church and state and science to flourish. In East Asia, Confucius articulated a different set of assumptions. Humans are defined as ingan 人間 (‘human between’) and assume relationship and compassion as the basic foundation. This is the basis of the cultural difference and theory of the mind. The Darwinian Evolutionary Theory replaced the religious definition, Cartesian duality, and empathy with the biological traits, instincts and natural selection. Psychology adopted the biological model to explain human behaviour. Research in paleoanthropology, genetics, and neurobiology outline the limitations of the biological model in explaining the human mind and behaviour. Bandura has documented the importance of human agency, consciousness, and self-efficacy in explaining human behaviour and provided empirical results with greater predictive and explanatory power than the traditional psychological theories. Indigenous and cultural psychology represents the continuation of the assumptions, theory and concepts outlined by Wilhelm Wundt and Albert Bandura. Kim outlines the transactional model of science, where human agency (measured by self-efficacy) can explain a person’s performance and outcome. Empirically, the Harvard Study of Adult Development, the 85-year longitudinal study, found the unexpected results that challenge the previous held assumptions. Waldinger and Schulz have found that maintaining good relationship is the most important predictor of happiness, health and longevity and not high income, success, IQ and personality. Kim and Kim found that for Millennials and Gen Z, happiness is predicted by relational and social efficacy, positive outlook, and receiving social support from family, friends and online communities, replicating previous results found across three generations and for the past 25 years in Korea. These results point to the importance of examining the basic assumptions of the theories in psychology and the scientific foundation of indigenous and cultural psychology.
Efficient Deep Space Filling Curve

Space-filling curves (SFCs) act as a linearization approach to map data in higher dimensional space to lower dimensional space, which is used comprehensively in computer vision, such as image/point cloud compression, hashing and etc. Currently, researchers formulate the problem of searching for an optimal SFC to the problem of finding a single Hamiltonian circuit on the image grid graph. Existing methods adopt graph neural networks (GNN) for SFC search. By modeling the pixel grid as a graph, they first adopt GNN to predict the edge weights and then generate a minimum spanning tree (MST) based on the predictions, which is further used to construct the SFC. However, GNN-based methods suffer from high computational costs and memory footprint usage. Besides, MST generation is un-differentiable, which is infeasible to optimize via gradient descent. To remedy these issues, we propose a GNN-based SFC-search framework with a tailored algorithm that largely reduces computational cost of GNN. Additionally, we propose a siamese network learning scheme to optimize DNN-based models in an end-to-end fashion. Extensive experiments show that our proposed method outperforms both DNN-based methods and traditional SFCs, e.g. Hilbert curve, by a large margin on various benchmarks.
Recovery from radiation anxiety and posttraumatic growth among community dwellers after the nuclear disaster in Fukushima

Abstract Objective This study examined (1) the current status of posttraumatic growth (PTG) and (2) the relationship between recovery from radiation anxiety and PTG among community dwellers five years after the nuclear disaster in Fukushima. Design This was a cross-sectional study with 796 residents of Fukushima Prefecture (367 men and 429 women). A questionnaire survey assessed PTG with one question (“Have you gained anything through the disaster experience? ” [yes/no]), and current and past radiation anxiety on a 5-point Likert-type scale. These two anxiety measures were combined to generate a new item “recovery from radiation anxiety” with three values (“no anxiety,” “recovered,” and “unrecovered”). Results Approximately half of participants experienced PTG (55.4%). Women were more likely to experience PTG than men. Multiple logistic regression showed that individuals who “recovered” from radiation anxiety were more likely to experience PTG (odds ratio (OR) = 1.99, 95% confidence interval (CI): 1.34–2.85), and that higher level of education (OR = 2.12, 95% CI: 1.28–3.49 for secondary education; OR = 3.95, 95% CI: 2.26–6.88 for higher education) and health literacy (OR = 1.34, 95% CI: 1.09–1.63 for one point increase) were also associated with the experience of PTG.Conclusion: Our findings indicate that during the period of recovery from radiation anxiety, a positive psychological adjustment may occur and PTG might emerge as a result; our findings may be practically used to support sufferers of traumatic events in their recovery.
You Can Clone But You Cannot Hide: A Survey of Clone Prevention and Detection for RFID

Radio-frequency identification (RFID) is one of the driving technologies for Internet of Things. The architecture-succinctness and cost-effectiveness of RFID tags promise their proliferation as well as allure security and privacy breaches. The cloning attack using clone tags to impersonate genuine tags can lead to unimaginable threats because RFID applications equate tag genuineness to the authenticity of tagged objects. Proposed countermeasures, however, keep showing limitations in effectiveness, efficiency, security, privacy, or applicability as new RFID applications emerge. The countermeasures therefore require constant review and improvement to stay at the leading edge. In this paper, we conduct the first comprehensive and systematic survey of RFID clone prevention and detection solutions. We systematically classify existing RFID cloning countermeasures over the period 2003–2016, sketch the main idea and highlight the strengths and weaknesses of each solution type, and summarize the similarity and difference among solution types. We find that RFID cloning countermeasures turn to be much more complex to design than they were thought in the literature. Prevention solutions can hardly thwart RFID cloning completely. Detection solutions may have specific application requirements to take effect. Many open issues further complicate the design of RFID cloning countermeasures. We hope that our survey can provide academic researchers and industrial engineers with useful references to combat RFID cloning and therefore to secure RFID ecosystem.
Cryptographic enforcement of information flow policies without public information via tree partitions

We may enforce an information flow policy by encrypting a protected resource and ensuring that only users authorized by the policy are able to decrypt the resource. In most schemes in the literature that use symmetric cryptographic primitives, each user is assigned a single secret and derives decryption keys using this secret and publicly available information. Recent work has challenged this approach by developing schemes, based on a chain partition of the information flow policy, that do not require public information for key derivation, the trade-off being that a user may need to be assigned more than one secret. In general, many different chain partitions exist for the same policy and, until now, it was not known how to compute an appropriate one. In this paper, we introduce the notion of a tree partition, of which chain partitions are a special case. We show how a tree partition may be used to define a cryptographic enforcement scheme and prove that such schemes can be instantiated in such a way as to preserve the strongest security properties known for cryptographic enforcement schemes. We establish a number of results linking the amount of secret material that needs to be distributed to users with a weighted acyclic graph derived from the tree partition. These results enable us to develop efficient algorithms for deriving tree and chain partitions that minimize the amount of secret material that needs to be distributed.
Preferential Fragmentation of Protonated Gas-Phase Peptide Ions Adjacent to Acidic Amino Acid Residues

Matrix-assisted laser desorptiodionization (MALDI) is an effective method for producing protonated peptide and protein ions in the gas phase. ' Together with electrospray ionization, MALDI has become an ionization method of choice for analyzing peptides and proteins by mass spectrometry (MS). 2 The analyses are usually carried out by measuring the molecular masses of the intact polypeptides or peptide fragments produced by proteolysis or chemical degradation of proteins in solution. An alternative method for obtaining detailed primary structural information uses fragmentation of the protonated peptides in the gas phase followed by MS analysis of the fragment ions. A powerful variation of this approach, called tandem MS, employs mass spectrometric selection of the peptide ion of interest prior to fragmentation, followed by analysis of the fragment ion^. ^^^ Fragmentation of peptide ions produced by MALDI has been studied in time-of-flight (TOF) mass analyzers (fitted with ion mirrors), instrumentation well-suited to the pulsed ionization ~ource. ~*~ Mass analyzers that utilize the principle of ion trapping are also well-suited to the pulsed MALDI ion so~rce. ~ Precursor ion selection can be achieved with high resolution.8 The prolonged time window of the measurement in the quadrupole ion trap to =- 1 s) compared with that in the ion mirror TOF analyzer (< s) enables the observation of fragmentation processes with low rate constants. In the reflecting TOF analyzer, highly preferential peptide bond cleavage has been observed at the bond carboxy (C)-terminal to aspartic acid residues, with Asp-Pro bonds exhibiting particularly high lability.6 In the present study, we investigate the fragmentation of MALDI-produced protonated peptide ions (containing an Arg residue and at least one acidic amino acid residue) in a quadrupole ion trap mass spectrometer and also observe preferential cleavage of the peptide bond adjacent to aspartic acid residues. In addition, we report the first observation of preferential fragmentation adjacent to glutamic acid residues. The investigation was carried out on a MALDI quadrupole ion trap mass spectrometer constructed at Rockefeller University? Ions are generated external to the ion trap using 355 nm laser irradiation,I0 accelerated to 60 eV, focused with an einzel lens, and injected axially into the trap. The trapped ions are (1) Hillenkamp, F. ; Karas, M. ; Beavis, R. C. , Chait, B. T. Anal. Chem.
On the Subexponential Time Complexity of CSP

A Constraint Satisfaction Problem (CSP) with n variables ranging over a domain of d values can be solved by brute-force in d^n steps (omitting a polynomial factor). With a more careful approach, this trivial upper bound can be improved for certain natural restrictions of the CSP. In this paper we establish theoretical limits to such improvements, and draw a detailed landscape of the subexponential-time complexity of CSP. We first establish relations between the subexponential-time complexity of CSP and that of other problems, including CNF-Sat. We exploit this connection to provide tight characterizations of the subexponential-time complexity of CSP under common assumptions in complexity theory. For several natural CSP parameters, we obtain threshold functions that precisely dictate the subexponential-time complexity of CSP with respect to the parameters under consideration. Our analysis provides fundamental results indicating whether and when one can significantly improve on the brute-force search approach for solving CSP.
Hepatitis B virus clearance rate estimates

macol Toxicol 2005;45:51-88. 3. Agundez JAG, Ladero JM. Glutathione S-transferase GSTT1 and GSTM1 allozymes: beyond null alleles. Pharmacogenomics 2008;9:359-363. 4. Sun F, Chen Y, Xiang Y, Zhan S. Drug metabolising enzyme polymorphisms and predisposition to anti-tuberculosis drug-induced liver injury: a meta-analysis. Int J Tuberc Lung Dis 2008;12:994-1002. 5. Andrade RJ, Lucena MI, Fernández MC, Pelaez G, Pachkoria K, Garcı́aRuiz E, et al. Drug-induced liver injury: an analysis of 461 incidences submitted to the Spanish registry over a 10-year period. Gastroenterology 2005; 129:512-552. This letter was written on behalf of the Spanish Group for the Study of DrugInduced Liver Disease (Grupo de Estudio para las Hepatopatias Asociadas a Medicamentos). M. Isabel Lucena, Raúl J. Andrade, and Eugenia Ulzurrun are associated with the Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas. Carmen Martı́nez, Elena Garcı́a-Martı́n, and José A. G. Agúndez are associated with the Red de Investigación de Reacciones Adversas a Alergenos y Fármacos. Copyright © 2009 by the American Association for the Study of Liver Diseases. Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/hep.22910 Potential conflict of interest: Nothing to report.
Rupture des matériaux composites en compression sens fibre. Analyse de l’effet de l’endommagement.

To design composite structures it is required to access materials properties and to understand mechanisms of failure for different types of load. Shear and tensile tests are quite easy to do. That is why ply properties are well identified for these types of load. Yet in the case of compression, experimental methods are complex and then the knowledge of materials properties remains poor.When the slenderness of the specimen is excessive in compression test, buckling will affect the failure. But when the coupon is smaller, stress concentration generates a failure in the clamped-end. Structural effects are here the reason of the failure. It is then not possible to conclude about the materials properties.That is why an experimental study is proposed. This work is divided in two main parts. The first one talk about the measure of the compressive strength on undamaged samples with different geometries. It is shown that the behavior up to failure is well identified. In a second part it is demonstrated that damage decreases significantly the compressive strength. These results will finally be apply to the global design of laminates for any type of load.