Miracle-dz/UniFAR-FTUs huggingface dataset:
A criterion for detecting m-regularity

Lei S = /([*! , .,xj be a polynomial ring over an infinite field /c, and let / be a homogeneous ideal of S. An algorithm for computing the (first) syzygies of / is due independently to Spear [Spe77] and Schreyer [SchSO]: One chooses an ordering on the monomials of S, and then constructs a monomial ideal in (7) generated by the lead terms of all elements of 7. in (7) can be viewed as the limit of / under the action of a 1-parameter subgroup of GL(n) on the Hilbert scheme [Bay 82], so in (7) occurs as the special fiber of a flat family whose general fiber is isomorphic to 7. It follows from a well-known criterion for flatness [Art 76] that each syzygy of in (I) can be lifted to a syzygy of /; the set of syzygies thus obtained can be trimmed to give a complete set of minimal syzygies of /. The monomial ideal in (7) was first studied by Macaulay [Mac 27]; an algorithm for its construction was first given by Buchberger [Buc65], [Buc76]. in (7) is studied in [Hir64], [Bri73], [Gal 74], [Gal 79] as part of an analogous division process for power series rings. The following problem arises in using this syzygy algorithm in practice: in (7) can have minimal generators and syzygies in degrees higher than any minimal generator or syzygy of 7. In this situation, computations in these higher degrees are unnecessary; one should compute the generators and syzygies of in (7) in only those degrees necessary to find all minimal syzygies of 7. In order to modify the syzygy algorithm to take advantage of this observation, one would like a criterion for determining when all minimal syzygies of 7 have been found. This problem appears to be intractable at present. However, the question of bounding the degrees of the minimal / syzygies of 7, for all ;", is tractable. Recall that 7 is defined to be 7? -regular if the / syzygy module of 7 is generated in degrees ^7? i-fj, for all j^O ([Mum66], [EiGo 84]). The regularity of 7, reg(7), is defined to be the least m for which 7 is m-regular. We have reg(in(7))^reg(7), because regularity is upper-semicontinuous in flat families. When reg(in(7))>reg(7), computations in degrees >reg(7) + l are un-
Seismic Time-lapse Approach to Monitor Temporal Changes in the Supercritical Water Reservoir

Junzo Kasahara, Yoko Hasada, Haruyasu Kuzume, Yoshihiro Fujise, Takashi Yamaguchi, Hitoshi Mikada ENAA, Toranomon Marine Building 10th, 3-18-19, Toranomon, Minato-ku, Tokyo 105-0001, Japan Daiwa Exploration and Consulting Co. Ltd., 5-10-4 Toyo, Koto-ku, Tokyo 135-0016, Japan WELMA Co. Ltd., 2-3-3, Watanabe street, Chuo-ku Fukuoka 810-0004, Japan Kyoto Univ., Department of Earth Resources Engineering, Katsura, Nishikyo-ku, Kyoto 615-8530, Japan Shizuoka Univ., Center for Integrated Research and Education of Natural Hazard, 836 Ohya, Shizuoka, Japan
8.1 A New Approach for GaN Normally-Off Power Transistors: Lateral Recess for Positive Threshold Voltage Shift

We present a new approach for normally-off transistors based on a recess leading to a laterally induced positive threshold voltage. The fabrication process is demonstrated to yield devices with positive threshold voltage. The breakdown voltage of these devices compares well with that of equivalent normallyon devices. Future work is directed towards passivation of the devices in order to reduce the impact of surface traps on device properties.
Time Sequence Learning for Electrical Impedance Tomography Using Bayesian Spatiotemporal Priors

As an emerging technology for continuous monitoring of a bounded domain, electrical impedance tomography (EIT) gains increasing popularity in various applications. Despite unprecedented progress, the EIT inverse solvers at the present stage are incompetent to guarantee sufficient fidelity as well as efficient investigation of the internal impedance dynamics. In this context, this article introduces a spatiotemporal structure-aware sparse Bayesian learning (SA-SBL) framework for solving the time-continuous EIT inverse problems. Specifically, in the process of reconstructing the EIT time sequence, both intraframe spatial clustering and interframe temporal continuity are explored and exploited in an unsupervised manner by using the hierarchical Bayesian model and structure-aware priors. A multiple measurement vector model is established to capture the spatiotemporal correlations and describe the underlying multidimensional reconstruction problem. The resultant large-scale inversion is efficiently solved by applying the approximate message passing to the expectation updating. A speedup ratio of ${\mathcal{ O}}\left({\frac {N^{2}}{M}}\right)$ is achieved compared with original SA-SBL. Simulation results indicate that the proposed algorithm exhibits superior reconstruction performance to the existing methods, where the scores evaluated by the quantitative metrics are improved by at least 17%. The presented algorithm is envisioned to offer broader applicability since it yields improved image quality and recovery efficiency.
Program Development Using Dissolved Gas Analysis Method for an Analysis of Power Transformer Oil Testing Results

23 Abstract— This paper presents a program development for an an alysis of power transformer oil testing results. Th e Dissolved Gas Analysis (DGA) method is applied. Thi s method is generally used to determine transformer condition and failure causes by analyzing quantities of combu sti le gases in oil. The DGA method consists of thr ee well known methods as the key gases method, the total combusti ble gases method, and the ratios method. In additio n, he failure pattern and reliability of transformer components a re analyzed by applying statistic methods as Weibul l distribution and Normal distribution methods. Different cases of p wer transformers were examined in this paper by taking the historical data of power transformers into consider ation. Finally, the failure rate and reliability of power transformer components are determined. This program development is designed to be a tool for systematic database m anagement and failure analysis program on web-application to determine the criticality of power transformer comp onents. The strategy and process for preventive maintenance can be built up from causes of failure to improve powe r transformer as well as system reliabilities.
A Complex Adaptive System Approach to Predictive Data Insertion for Missing Student Data

: Educational Data Mining techniques generally rely on complete sets of student data for analysis. In order to limit the number of students that have to be removed due to missing data, various methods have often been used to fill in these missing data points. We propose a novel method utilizing a Complex Adaptive System to predicatively insert these missing data. This system compares very favorably to other commonly used algorithms, and it is generally more flexible and scalable in approach. What’s more, the CAS can output results in real-time, and can quickly adapt to newly added data. We present our results of comparison between a CAS and other common methods of Predictive Data Insertion on a set of real student data, and discuss some of the considerations when implementing a CAS.
EFFECTS OF CUTTING PRACTICES ON MICROENVIRONMENT IN RELATION TO HARDWOOD REGENERATION

Regeneration cutting results in significant changes in the microenvironment of the forest floor and soil. For example, light intensity, surface soil temperature, and soil moisture increase with removal of the forest canopy. These changes influence regeneration success directly through their impact on photosynthesis, heat and frost damage, and available soil moisture. Changes in the microenvironment also influence available nutrients because decomposition and nutrient cycling processes are strongly regulated by soil temperature arid moisture. Nutrient availability is further influenced by changes in dry deposition and leaching through the logging slash. The degree of changes in the physical, chemical, and biological properties of the forest floor and soil is dependent upon cutting intensity. Thus, silvicultural prescriptions should consider the microenvironmental requirements of the desired regenerating species.
A Review of the Relationship between the Endocannabinoid System and the Reduction of Depression and Anxiety

The growing acceptance of cannabis use for medical and recreational purposes across the world has sparked interest in evaluation of the therapeutic potential of the drug. While the beneficial effects of cannabis use to treat physical pain are well-known, its efficacy as a treatment for mental health disorders has not been as extensively investigated. As the most prominent and widespread of these disorders, depression and anxiety have been diagnosed in individuals across the world. Despite the wide range of severity for these disorders, tricyclic antidepressants and selective serotonin reuptake inhibitors are predominately prescribed to treat any case. However, these compounds are not always effective treatments, which leaves a need to investigate alternative treatment options for depression and anxiety. This review article aims to identify prominent research studies focused on evaluating the potential of the human endocannabinoid system, which consists of two main cannabinoid receptor subtypes (CB1 and CB2). Prior studies have focused on the use of exogenous cannabinoids such as oleamide or phytocannabinoids such as delta-9THC, but this review gives more consideration to endocannabinoids that are produced by the human body. In addition to experiments testing the independent capacity of endocannabinoid receptor ligands as antidepressants, the additive and synergistic potentials of these ligands have been examined in conjunction with cholinergic receptor ligands through the use of mice FST. Recent studies have also indicated that certain genetic variants within the endocannabinoid system such as the CB1 rs1049353 G allele have been linked to increased prevalence of mental health disorders and provide a rationale for gender discrepancies in disorder incidence. Although current research into the prospective use of endocannabinoids as antidepressants is limited, this review details the field’s most salient advancements toward potential clinical applications.
Where should I comment my code? A dataset and model for predicting locations that need comments

Programmers should write code comments, but not on every line of code. We have created a machine learning model that suggests locations where a programmer should write a code comment. We trained it on existing commented code to learn locations that are chosen by developers. Once trained, the model can predict locations in new code. Our models achieved precision of 74% and recall of 13% in identifying comment-worthy locations. This first success opens the door to future work, both in the new where-to-comment problem and in guiding comment generation. Our code and data is available at http://groups.inf. ed.ac. uk/cup/comment-locator/. CCS CONCEPTS • Software and its engineering $\rightarrow$ Maintaining software; • Computing methodologies $\rightarrow$ Neural networks; Natural language processing.
Compositely modulated structures of phosphor materials SrxLi2+xAl2-xO4:Eu2.

Composite crystals SrxLi2+xAl2-xO4:Eu2+ were synthesized and their structures were determined using single-crystal X-ray diffraction. The commensurate structure with a modulation wavevector q = 5c*/6 was analyzed in a conventional manner in 3D space, while a structure model in (3+1)-dimensional superspace was used for the other two crystals with modulation wavevectors slightly differing from 5c*/6. The superstructure of the commensurate phase was described using the space group P4/n and a common superspace group I4/m(00γ)00 was used for the (3+1)D structures of all three crystals. The whole structure of each crystal consists of two substructures. Basis vectors a and b are common, but c is different for the two substructures. The first substructure is a host framework constructed by (Li/Al)O4 tetrahedra sharing edges. A linear connection of cavities is seen to be channel-like, in which Sr ions locate as guest cations forming the second substructure. The crystal of q = 5c*/6 contains five Sr ions per six cavities in a channel. Sr ions are distributed at seven sites, some of which are partially occupied. Statistical disorder of local structure models for the location of Sr ions in the channel was assumed to explain the results. Such a partially disordered character was also seen in the incommensurate phases and properly embodied by a (3+1)D model containing an atomic domain of the Sr ion with occupational modulation. Plots of the occupation factor, interatomic distances and the bond valence sum at each metal site as functions of t (= x4 - q·r) are roughly identical in the three crystals, which are considered as members of the same series of composite crystals.
E-WASTE MANAGEMENT STRATEGY IN ORGANIZATIONS - A CONCEPTUAL FRAMEWORK

Existing studies on consumer response to e-waste management mainly focus on the household consumers and little attention has been given to study the role of bulk consumers, despite the fact that they create majority of e-waste. The aim of the present study is to build a proposed conceptual framework of the key factors shaping the organizational e-waste strategy as well as the organizational challenges related to its implementation through a review of the current literature. The proposed model takes into consideration studies previously carried out by the authors in the areas of e-waste and environmental management in general. An extensive literature survey has been carried out to derive the constructs of the conceptual framework as a basis for further empirical research. Based on the review of existing literature, a conceptual framework of determinants of e-waste strategy and organizational challenges related to strategy implementation are identified. The model depicts that various internal and external factors served as key strategic drivers for e-waste management in the organizations and the hurdles faced to implement it. The proposed conceptual framework for organizational e-waste management strategy developed through literature review is yet to be empirically tested and validated using appropriate tools and techniques. Future research can be carried out to test the applicability of the proposed framework to a wider spectrum of organizations in varying contexts. The study proposes a novel framework of strategy for e-waste management in the organizational context
Bilateral Carotid Artery Occlusion Induces Cochlear Oxidative Stress And Hearing Loss In Rat

Title: Bilateral Carotid Artery Occlusion Induces Cochlear Oxidative Stress and Hearing Loss in Rat Authors: Hamed Fanaei1, Akram Pourbakht2, Sadegh Jafarzadeh3* 1 Assistant prof Pregnancy Health Research Center, Zahedan University of Medical Sciences, Zahedan, Iran. 2 Associate prof Department of Audiology, Rehabilitation Research Center, Faculty of Rehabilitation Sciences, Iran University of Medical Sciences, Tehran, Iran. 3 Assistant prof Department of Audiology, School of Paramedical Sciences, Mashhad University of Medical Sciences, Mashhad, Iran.
Profiling Potential Land Redistribution Beneficiaries In South Africa: Implications For Agricultural Extension And Policy Design

There is a general agreement that land reform has fallen short in achieving its intended objectives. One of the most commonly cited reasons for the slow progress in the land redistribution programme is lack of clear criteria in beneficiary selection. The State Land Lease and Disposal Policy, which is one of the current land redistribution policies, has identified commercial-oriented smallholders in the communal land as one of the land redistribution beneficiaries. However, there is little detailed empirical evidence on their constituents. Such information is crucial for policy-makers including the agricultural extension personnel, as this will enhance effective policy design and appropriate design of extension advisory service which will contribute to the success of land redistribution. The objective of this article is to fill this gap by profiling commercial-oriented small-scale farmers in three provinces that have the highest number of smallholders in South Africa. A survey of 833 farmers from these three provinces was conducted. Descriptive statistics and Binary Logistic Regression were used to analyse the data with the use of STATA software. The results show that a potential emerging farmer is a 55 years old male with primary education. Furthermore, 57% of the farmers are willing to relocate to commercial farms if there is government support and require an average farm of 152 hectares where they want to plant maize. The article concludes with some recommendations and implications for agricultural extension.
Master Data Management Planning: A Case Study of Flight Information System at PT Angkasa Pura I (Persero)

The flight information system used for flight data management at PT Angkasa Pura I (Persero) uses several applications that have different features. This results in inconsistent values that affect data quality due to absence of single master data source. Therefore, this study aims to provide recommendations to PT Angkasa Pura I (Persero) regarding the planning of master data management for flight information system according to its business processes. Master data management planning is carried out using the key user interview method, analyzing the database schema of each application, analyzing IT policy documents, and using the framework of the Data Management Body of Knowledge (DMBOK). The research succeeded in producing the needs of master data management at PT Angkasa Pura I (Persero) using collaborative methods and transaction hub architecture patterns. The results of this master data management plan are expected to help PT Angkasa Pura I (Persero) in managing and managing flight data so that there are no more inconsistent data between applications and can improve data quality.
The Axis “Human Papillomavirus - Anal Squamous Cell Carcinoma”: A Review

Background: Anal Squamous Cell Carcinoma (ASCC) is an infrequent neoplasia that represents 2% of the digestive tumors and it has a growing incidence. Objective: This investigation (i) studies the pathogenesis of an increasingly prevalent disease, (ii) its treatment and prognosis along with (iii) a bibliographical review of the main characteristics of the Human Papillomavirus (HPV) as well as its effects on humans. Methods: A literature review is performed, comprising articles up to 2019 and cross-research manuscripts with the initial research. Results: Several studies demonstrate the HPV role as a significant risk factor to the development of ASCC, as well as its higher incidence in HIV-positive individuals and in those who engage in receptive anal intercourse. Future trends in theragnostic using information technology are examined. Conclusions: ASCC is a neoplasm mostly associated with HPV. Many studies are needed to improve the treatment as well as in the evaluation of the tumor characteristics.
On the Discrepancies of Graphs

In the literature, the notion of discrepancy is used in several contexts, even in the theory of graphs. Here, for a graph $G$ with each edge labelled $-1$ or $1$, we consider a family $\mathcal{S}_G$ of subgraphs of a certain type, such as spanning trees or Hamiltonian cycles. As usual, we seek for bounds on the sum of the labels that hold for all elements of $\mathcal{S}_G$, for every labeling.
X-ray, UV, and optical time delays in the bright Seyfert galaxy Ark 120 with co-ordinated Swift and ground-based observations

We report on the results of a multiwavelength monitoring campaign of the bright, nearby Seyfert galaxy Ark 120, using a ∼50-d observing programme with Swift and a ∼4-month co-ordinated ground-based observing campaign, pre-dominantly using the Skynet Robotic Telescope Network. We find Ark 120 to be variable at all optical, UV, and X-ray wavelengths, with the variability observed to be well correlated between wavelength bands on short time-scales. We perform cross-correlation analysis across all available wavelength bands, detecting time delays between emission in the X-ray band and the Swift V, B, and UVW1 bands. In each case, we find that the longer wavelength emission is delayed with respect to the shorter wavelength emission. Within our measurement uncertainties, the time delays are consistent with the τ ∼ λ4/3 relation, as predicted by a disc reprocessing scenario. The measured lag centroids are τcent = 11.90 ± 7.33, 10.80 ± 4.08, and 10.60 ± 2.87 d between the X-ray and V, B, and UVW1 bands, respectively. These time delays are longer than those expected from standard accretion theory and, as such, Ark 120 may be another example of an active galaxy whose accretion disc appears to exist on a larger scale than predicted by the standard thin-disc model. Additionally, we detect further inter-band time delays: most notably between the ground-based I and B bands (τcent = 3.46 ± 0.86 d), and between both the Swift XRT and UVW1 bands and the I band (τcent = 12.34 ± 4.83 and 2.69 ± 2.05 d, respectively), highlighting the importance of co-ordinated ground-based optical observations.
Supplementary Material for “Weakly Supervised Discriminative Feature Learning with State Information for Person Identiﬁcation”

We summarize our model in Algorithm 1. The equations in Algorithm 1 are defined in the main manuscript. We used standard data augmentation (random crop and horizontal flip) during training. We used the spherical feature embedding [4, 3], i.e., we enforced ||x||2 = 1 and ||μk||2 = 1, ∀k. To address the gradient saturation in the spherical embedding [4], we followed the method introduced by [4] to scale every inner product xμ up to 30. We updated {p(k)}k=1 every T = 40 iterations, as we found it not sensitive in a broad range. We maintained a buffer for m and σ as a reference, whereas mj and σj were estimated within each batch to obtain the gradient. We updated the buffer with a momentum α = B/N for each batch where B denoted the batch size and N denotes the training set size.
CrossWOZ: A Large-Scale Chinese Cross-Domain Task-Oriented Dialogue Dataset

Abstract To advance multi-domain (cross-domain) dialogue modeling as well as alleviate the shortage of Chinese task-oriented datasets, we propose CrossWOZ, the first large-scale Chinese Cross-Domain Wizard-of-Oz task-oriented dataset. It contains 6K dialogue sessions and 102K utterances for 5 domains, including hotel, restaurant, attraction, metro, and taxi. Moreover, the corpus contains rich annotation of dialogue states and dialogue acts on both user and system sides. About 60% of the dialogues have cross-domain user goals that favor inter-domain dependency and encourage natural transition across domains in conversation. We also provide a user simulator and several benchmark models for pipelined task-oriented dialogue systems, which will facilitate researchers to compare and evaluate their models on this corpus. The large size and rich annotation of CrossWOZ make it suitable to investigate a variety of tasks in cross-domain dialogue modeling, such as dialogue state tracking, policy learning, user simulation, etc.