Miracle-dz/UniFAR-FTUs huggingface dataset:
The Research on Multi-Dimensional Evaluation Index System of Distribution Network Loss

At present, the evaluation of regional distribution network loss usually uses a single line loss rate index as the evaluation standard. Comprehensively considering factors such as the distribution grid structure, equipment status, power consumption structure and other factors, this paper establishes a multi-dimensional evaluation index system of the distribution network line loss from three aspects as line loss rate, power grid operation and planning, line and transformer equipment. Taking the line loss situation of the distribution network in two regions of a province as an example, the evaluation index system and corresponding evaluation method are used for evaluation. The calculation example shows that the constructed index system can comprehensively and effectively evaluate the overall situation and weak links of the regional distribution network line loss, thus guiding the direction of regional distribution network loss reduction.
Semantic Segmentation With Light Field Imaging and Convolutional Neural Networks

Semantic segmentation is of great importance and a challenge in computer vision. One of its main problems is how to efficiently obtain rich information (geometric structure) and identify useful features from higher dimensions. A light field camera, due to its special microlens array structure, can completely record the angular-spatial information of scenes, which is attractive and has great potential to improve the performance of semantic segmentation tasks. Inspired by this, we propose an end-to-end semantic segmentation network that can process light field macropixel images robustly and extract their features. In addition, this network can flexibly and efficiently load the different popular deep learning backbones. Furthermore, we propose an efficient angular model, which, to learn the angular features between the different viewpoints of the macropixel image, improves the nonlinearity of angular-spatial features and enhances multichannel semantic correlations. To evaluate the network, we construct a new real scene light field dataset comprising 800 high-quality samples. The quantitative and qualitative results show that the highest mean intersection over union (mIoU) based on our algorithm is greater than 57%. Our algorithm achieves a 10.30% increase compared with state-of-the-art semantic segmentation algorithms. In combination with different backbones or multiscale light field macropixel images, the network can also achieve comparable results. This preliminary work demonstrates that the combination of light field imaging and deep learning technology has potential applications in the future study of semantic segmentation.
Software Implementation of Optimal Pairings on Elliptic Curves with Odd Prime Embedding Degrees

Pairing computations on elliptic curves with odd prime degrees are rarely studied as low eﬃciency. Recently, Clarisse, Duquesne and Sanders proposed two new curves with odd prime embedding degrees: BW13-P310 and BW19-P286 , which are suitable for some special cryptographic schemes. In this paper, we propose eﬃcient methods to compute the optimal ate pairing on this types of curves, instantiated by the BW13-P310 curve. We ﬁrst extend the technique of lazy reduction into the ﬁnite ﬁeld arithmetic. Then, we present a new method to execute Miller’s algorithm. Compared with the standard Miller iteration formulas, the new ones provide a more eﬃcient software implementation of pairing computations. At last, we also give a fast formula to perform the ﬁnal exponentiation. Our implementation results indicate that it can be computed eﬃ-ciently, while it is slower than that over the BLS-446 curve at the same security level.
Distributed ∆-coloring plays hide-and-seek

We prove several new tight or near-tight distributed lower bounds for classic symmetry breaking problems in graphs. As a basic tool, we first provide a new insightful proof that any deterministic distributed algorithm that computes a Δ-coloring on Δ-regular trees requires Ω(logΔn) rounds and any randomized such algorithm requires Ω(logΔlogn) rounds. We prove this by showing that a natural relaxation of the Δ-coloring problem is a fixed point in the round elimination framework. As a first application, we show that our Δ-coloring lower bound proof directly extends to arbdefective colorings. An arbdefective c-coloring of a graph G=(V,E) is given by a c-coloring of V and an orientation of E, where the arbdefect of a color i is the maximum number of monochromatic outgoing edges of any node of color i. We exactly characterize which variants of the arbdefective coloring problem can be solved in O(f(Δ) + log*n) rounds, for some function f, and which of them instead require Ω(logΔn) rounds for deterministic algorithms and Ω(logΔlogn) rounds for randomized ones. As a second application, which we see as our main contribution, we use the structure of the fixed point as a building block to prove lower bounds as a function of Δ for problems that, in some sense, are much easier than Δ-coloring, as they can be solved in O(log* n) deterministic rounds in bounded-degree graphs. More specifically, we prove lower bounds as a function of Δ for a large class of distributed symmetry breaking problems, which can all be solved by a simple sequential greedy algorithm. For example, we obtain novel results for the fundamental problem of computing a (2,β)-ruling set, i.e., for computing an independent set S⊆ V such that every node v∈ V is within distance ≤ β of some node in S. We in particular show that Ω(βΔ1/β) rounds are needed even if initially an O(Δ)-coloring of the graph is given. With an initial O(Δ)-coloring, this lower bound is tight and without, it still nearly matches the existing O(βΔ2/(β+1)+log* n) upper bound. The new (2,β)-ruling set lower bound is an exponential improvement over the best existing lower bound for the problem, which was proven in [FOCS ’20]. As a special case of the lower bound, we also obtain a tight linear-in-Δ lower bound for computing a maximal independent set (MIS) in trees. While such an MIS lower bound was known for general graphs, the best previous MIS lower bounds for trees was Ω(logΔ). Our lower bound even applies to a much more general family of problems that allows for almost arbitrary combinations of natural constraints from coloring problems, orientation problems, and independent set problems, and provides a single unified proof for known and new lower bound results for these types of problems. All of our lower bounds as a function of Δ also imply substantial lower bounds as a function of n. For instance, we obtain that the maximal independent set problem, on trees, requires Ω(logn / loglogn) rounds for deterministic algorithms, which is tight.
A Practical Verifiable Delay Function and Delay Encryption Scheme

We present a novel construction for a Veriﬁable Delay Function (VDF), in which the prover is challenged to produce the factorisation of a special class of RSA modulus. Our approach produces a VDF with a very e � cient veriﬁcation procedure. The properties of our VDF allow us to establish the design of the ﬁrst practical Delay Encryption scheme, a primitive introduced at EURO-CRYPT 2021. We provide a formal security analysis of our results, as well as an implementation study detailing the practical performance of our VDF.
Electrophysiological features of guillain barre syndrome in Mongolia

The Guillain-Barré syndrome (GBS) is a rare but severe disorder that affects peripheral nerves and is classified into several subtypes based on clinical presentation and electrophysiological abnormalities. Incidence and predominant subtypes of GBS differ geographically. The diagnosis is made upon clinical features and confirmed by nerve conduction studies (NCSs) which can differentiate subtypes such as demyelinated and axonal. Demyelinating subtypes in Europe and North America and axonal subtypes in Asia are predominant. Electrophysiological subtypes have not been determined in Mongolia. Therefore, we aimed to determine common electrophysiological subtypes of Guillain-Barré syndrome in Mongolia. In our study, 75 patients referred to Reflex Neurological Clinic between 2016 and 2019 were retrospectively reviewed. After excluding the cases by the criteria, patients were classified as demyelinating, axonal, normal and equivocal subtypes based on Hadden criteria. We compared the electrophysiological features of axonal and demyelinating subtypes. SPSS-23 was used for statistical analysis. The results are expressed in averages (standard deviations) and percentages (numbers). The difference between the mean and the group of variables was calculated using the T-test and the Chi-square test. Patients were 44% male (33), and the mean age was 46.4±15.1. There was no significant association between seasonal factors and electrophysiological subtypes. Among 75 patients with Guillain-Barré syndrome, a nerve conduction study was performed in the first week on 36% of patients, 33.3% in the 2nd week, and others in the 3rd-4th week after symptom onset. Electrophysiology subtypes were classified as demyelinating (65.3%), axonal (20%), within the normal range (5.4%) and equivocal (9.3%) based on Hadden criteria. The absence of F-waves on electrophysiological examination was higher in patients within 14 days of the disease onset, whereas non-sensory changes were higher in patients after 14 days. We conclude that acute inflammatory demyelinating neuropathy (AIDP) was the most frequent subtype of GBS in Mongolia.
Study on MRI Brain Tumor Recognition and Segmentation Based on an Improved U-Net Network Model

Current malignant tumor is one of the main causes of death in Chinese residents, and the incidence of brain tumor in the population is higher. With the continuous development of modern imaging technology, especially MRI imaging technology, it provides a favorable help for doctors to assess brain tumors and choose treatment options. The accuracy of brain tumor segmentation is the key for doctors to diagnose patients’ medical condition information. Brain tumor’s structure is complex, shape is changeable and grayscale isn’t uniform, showing considerable differences in different patients. Artificial segmentation of MRI brain tumor images is time-consuming, and it is often affected by subjective differences. For the above reasons, researchers are working to develop an MRI brain tumor recognition segmentation method. This paper presents a recognition and segmentation method for MRI brain tumors, based on an improved U-Net network model. The proposed method avoids too large or too small learning rate leading to too fast or too slow convergence, and adds the BatchNormalization module to normalize the input of the input activation function of the network, thus realizing the training length, robustness, and accurately and completely dividing the brain tumor image. This paper performs detection experiments on the Kaggle+LGG Datasets, with the average classification accuracy of 99.8309%, the average IoU is 0.9935, and the average Dice coefficient is 0.9956.
Contrasting interannual impacts of European and Greenland blockings on the winter North Atlantic storm track

Based on the daily reanalysis, the present study examines the interannual influences of the European blocking (EB) and Greenland blocking (GB) frequencies on the winter North Atlantic storm track (WNAST) intensity. There are contrasting relationships between the two types of atmospheric blockings and the WNAST. The EB and GB frequencies are significantly positively and negatively related to the WNAST intensity, respectively. Composite analysis shows a meridional dipole of the WNAST anomalies associated with both frequent EB and GB. The area of EB-related positive WNAST anomalies is obviously larger than that of the negative anomalies, which directly results in their in-phase relationship. However, the amplitudes of the GB-related negative WNAST anomalies that are larger than those of the positive anomalies directly lead to their out-of-phase relationship. The EB-related intensified WNAST is dependent on the enhanced baroclinic energy conversion and the strengthened atmospheric baroclinicity induced by the anomalous westerly winds on the northern side of the EB-related anticyclone. In contrast, the GB-related weakened WNAST is determined by the attenuated atmospheric baroclinicity and baroclinic energy conversion on the southern flank of the WNAST climatology.
Faceknow: Facial Expression Recognition by a Global-Local Network with a Sub-Images-Related Contextual Attention Mechanism

Recognizing health status through human faces is a challenging research topic. Among them, facial recognition expressions can indirectly reflect the inner health status, which has very significant commercial and research value. Most research work on facial expression recognition uses traditional methods, and the accuracy of traditional methods highly depends on feature extraction. Deep learning has already promoted the research on facial expression recognition. This paper proposes a dual-branch network that uses global facial information and local information obtained by using the attention mechanism to merge and identify human facial emotional information. Use of shared pre-training module to extract low-level semantic information of global and also local images. The dual-branch network architecture utilizes the attention module to capture the relationship between different sub-images to fuse the local features of the face. Experimental results demonstrate that the accuracy of the CK+ Dataset reaches 95.96%, which is improved compared to other existing methods.
A Review on Transmission Control Strategies in Energy Harvesting Wireless Sensor Networks

Wireless Sensor Networks (WSNs) have to sacrifice part of their performance to save energy in order to prolong the network life with limited capacity of common batteries. In order to break through the limitation of limited energy on the performance of WSNs, Energy Harvesting Wireless Sensor Networks (EH-WSNs) get more attention. Theoretically, unlimited energy provides the basis for the continuous operation of sensor nodes, which makes the design of EH-WSNs more focused on meeting the requirements of data transmission quality and efficiency. Accordingly, the energy harvesting characteristics present more challenges to the design and optimization of Transmission Control Strategies (TCS) for EH-WSNs. We present and introduce the concept of TCS, which includes energy management strategy, routing protocol optimization, Media Access Control (MAC) protocol optimization and cross-layer optimization. Then, we review and evaluate the TCS related research progress of EH-WSNs, and puts forward the future challenges and prospects of related research.
Praseodymium and iron incorporated Alpo 5 molecular sieves for organic Transformations

Homogeneous catalysts such as sulfuric acid, hydrochloric acid, hydrofluoric acid, phosphoric acid, etc., are frequently used in the chemical industry. However, these catalysts are environmentally hazardous, toxic, corrosive and non-recyclable. Porous materials such as zeoloites, zeotypes and mesoporous solids have emerged as an alternative option for the chemical industry due to their non toxicity, non corrosive nature, possibility of reusing and more importantly their ecofriendly nature. The use of heterogeneous catalysts is highly desirable for compliance with the principles of green chemistry, offering low energy routes to products, eliminating the requirement of auxiliary species and facilitating catalyst recovery to minimise waste generation. The use of porous solid acids as heterogeneous catalyst is gained significant importance in organic synthesis due to their environmental compatibility combined with good yield and selectivity. The isomorphously substituted AlPOs found applications in aerial oxidation of linear and cyclic hydrocarbons using molecular oxygen. Compared to zeolites, MeAlPO molecular sieves possess large variety of acid sites and broader acid sites distribution. Because of these valuable properties, metaloaluminophosphates (MeAPOs) become one of the important materials as heterogeneous catalyst for important organic transformations. The present work focused on the synthesis, characterization and catalytic evaluation of PrAlPO-5 and FeAlPO-5. PrAlPO-5 with different (Al+P)/Pr ratios (25, 50, 75, 100, 150 and 200) were successfully synthesized by hydrothermal method in fluoride
L1 use in group interaction in EFL classes

This research paper analyzes the first language (L1) interactions of 14 students, aged between 14 and 15 years, assembled in groups to accomplish 3 different collaborative and interactional tasks, such as writing, reading and grammar-based tasks in an EFL class. The data were gathered in a state secondary school located in an upper-middle class neighborhood of Barcelona, through the use of recorded videos. The L1 interactions employed by the students in group are analyzed to determine the functions of the L1. This paper also examines if the L1 functions observed are beneficial or a potential obstacle to learn the second language. Findings show that using the first language in EFL classes has social and cognitive benefits and it contributes to second language learning.
Managing Forest Disturbances: Effects on Mule Deer and Plant Communities in Montana's Northern Forests

Mule deer (Odocoileus hemionus) are frequently the focus of population and habitat management in the western United States. Land and wildlife managers use disturbance to reset forests to earlier successional stages and improve the quality and quantity of forage available to mule deer. However, the effects of management practices on nutrition and selection vary widely, so the implementation of management practices raises ecological as well as management-related concerns. This work investigated how disturbance from wildfire, prescribed fire, and timber harvest influences the spatial and temporal distribution of nutritional resources in mule deer summer range, and therefore, how the nutritional landscape influences mule deer selection of disturbance. We studied changes in vegetation and habitat selection by mule deer in three areas with differing disturbance regimes during 2017–2019. We found differences in forage nutrition response to disturbance that was specific to study areas, suggesting that targeted forest management within disturbance regimes would provide nutritional benefits to mule deer populations in the northern Rocky Mountains. Other vegetative responses revealed trade-offs specific to forest and disturbance types. Despite substantial variation in selection among individuals and among study areas, we found some common effects of forage nutrition and disturbance type on selection at population scales. As we predicted, deer selection within home ranges was not explained well within these constraints, suggesting that deer selection may be influenced more by other factors, such as security or cover within home ranges. The age and type of disturbance also influence selection at a population scale, but do not predict selection within home ranges, where the availability of disturbances is irregular. In all study areas, we documented similar selection for more recent disturbance and avoidance of open woodland at the population scale, suggesting that these responses can be generalized to deer in other populations in the Rocky Mountains because we observed them in multiple sites under widely differing conditions. Managers accounting for local and regional frequency and availability of disturbance can identify management actions that are accessible and beneficial for mule deer. Furthermore, consideration of the likely outcomes of forest-specific vegetative responses can help managers balance potential tradeoffs of management alternatives.
Survey of Residual Pesticides in Various FreshFruit Crops: A Case Study

An in-vitro study was conducted to estimate the pesticidal residues in five types of fruits; melon, guava, orange, peach, and mango. Organochlorine, organophosphate, carbamates, and pyrethroids, along with other insecticidal residues, were detected. The collection of samples was carried out from farmland located in the indigenous soil of Faisalabad and Toba Tek Singh. The residual pesticides were extracted by single-phase extraction and then purified by the gel permeation chromatographic technique. The extracted residues were isolated and quantified by HPTLC method. The detected residues were in the range of 0.1-0.3 mg kg-1. The study demonstrated a high risk of ongoing contamination posed by uncontrolled applications of pesticides, which are needed to be overcome on the lines of sustainable management measures.
Remineralization potential of varnish containing casein phosphopeptides-amorphous calcium phosphate with fluoride and varnish containing only fluoride: A comparative study

Background: Fluoride varnishes have been the standard of practice for the professional application of fluoride. The primary reason for wide acceptance of fluoride varnish is that the procedure is easy, safe, convenient, and well-accepted by patients. Aim: The aim of this study is to evaluate and compare the remineralizing potential of varnish containing casein phosphopeptides-amorphous calcium phosphate (CPP-ACP) and fluoride (MI Varnish®), with that of varnish containing only fluoride (Fluor Protector®). Materials and Methods: Fifty premolar teeth samples were used for this part of the study. They were divided into two Groups (1 and 2), consisting of 25 samples each. Two windows on the buccal surface of these samples were made and assigned randomly as control and experimental window. Initial depth of carious lesions of both windows was measured in all the samples. No varnish was applied on control windows. On the experimental window of Subgroup 1, varnish containing CPP-ACP with fluoride was applied, and on samples of Group 2, varnish containing only fluoride was applied. After varnish application, all the samples were subjected to pH-cycling. Following, the final depth of carious lesion was calculated using polarized light microscope. The data obtained were tabulated and subjected to statistical analysis. Results: The final depths of artificial carious lesion of experimental window of Group 1 and 2 were 131.26 ± 7.01 μm and 134.11 ± 5.95 μm, respectively. Conclusion: There was no significant difference in the remineralizing potential of varnish containing CPP-ACP and fluoride and varnish containing only fluoride.