Miracle-dz/UniFAR-FTUs huggingface dataset:
Performance Evaluation of MindSpore and PyTorch Based on Ascend NPU

The development of deep learning depends on the support of deep learning processing units and frameworks. HUAWEI's Ascend Neural Processing Unit (Ascend NPU), as a chip designed specifically for neural network computation acceleration, not only provides support for its self-developed framework MindSpore, but also provides adaptation for PyTorch. However, there is a lack of comparative evaluation research on MindSpore and other frameworks on Ascend NPU, making it difficult to understand their actual performance. Therefore, comprehensive evaluation experiments in both model level and operator level on MindSpore and PyTorch based on Ascend NPU are conducted in this paper, analyzing and comparing the performance of the two frameworks. With the conclusions analyzed on the model evaluation experiments and operator evaluation experiments, we provide references and suggestions for deep learning researchers and practitioners in terms of framework selection and optimization strategies for Ascend NPU.
A Review of the DC-AC Inverters Used in Photovoltaic Systems

To cope with the perpetually growing energy demand and save the remaining valuable natural resources, a swift transition to utilizing renewable energy sources (RES) has become vital. Solar power stands out among the other RES due to its abundance, availability, cost-effectiveness, etc. Solar energy, also called photovoltaic (PV), still has limitations in terms of efficiency, stability, power output capacity, costs, etc. The need for research and development into improving the utilization techniques and transfer efficiency of RES is intensifying. Various systems and components are imperative to the methods of generating electricity from solar energy, a significant one being DC-AC inverters. The optimum performance of PV can be achieved by using inverters with minimal structural complexity, appropriate size, good lifetime, and reasonable cost. An investigation of numerous types of DC-AC inverters used in photovoltaic systems, along with their specifications, working principles, advantages, and disadvantages, are addressed in this review work, as well as a comparative analysis of some recently proposed topologies.
The algorithmic turn: photosynth, augmented reality and the changing implications of the image

The digital turn, and with it increased use of location-aware technologies, has yielded innovative image applications and posed new questions about the status and value of the image. These applications rely on algorithmically defined relations between the viewing subject and the world viewed, offering robust alternatives to the visual economies of the past. If we take seriously Heidegger's insights regarding the Welt-bild as a metaphor for the modern era, the algorithmic reconfiguration of subject-object relations in this emerging visual regime potentially offers insights through which we can reflect upon the current era – and a metaphoric alternative. This article uses two entry points to explore this possible reconfiguration and, with it, the question of value. Downloadable applications such as Photosynth aggregate location-tagged photographs into a near-seamless whole, and offer a way to consider such issues as collaborative authorship of the image, unstable points of view and the repositioning of subject-object relationships – all elements that fundamentally challenge western representational norms dominant in the modern era. In this new regime, the spatial referents of greatest value are points of uniqueness sought out and built upon by the program's algorithms – and not those perceived by the viewer. The viewer is in turn free to explore an extensive and dynamic image space unconstrained by (and, indeed, without access to) an authorised or ‘correct’ viewing position. A second case, built upon certain augmented reality applications, works by ‘recognising’ particular spaces and, through the use of computationally enhanced viewing screens, superimposing new images over real space. In this case, a system of virtual spatial annotation depends upon the ‘correct’ positioning of the viewer (and portable computing device) in the world. The two cases stand in a roughly reciprocal relationship, turning on different notions of algorithmic intermediation and subject-object relations and dynamics for the generation of meaning and value.
Fusion Hidden Markov Model with Latent Dirichlet Allocation Model in Heterogeneous Domains

To deal with the diversity of feature space in multiple heterogeneous domains, we describe a fusion multi-domain semantic topics and syntax classes model to extract latent long-range topics and short-range classes in multi-domain. The model fuses the information from multiple heterogeneous domains. There are two layers in the fusion model. Firstly, in every sub-domain, the model uses the hidden Markov model with latent dirichlet allocation (HMM-LDA) to extract sub-domain topic and class features. Secondly, the fusion model combines the multiple sub-domain models to extract the whole heterogeneous domain features. The experiments use the international universal recommendation datasets. The results show that our method outperforms three typical recommendation algorithms, and reduces the Mean Absolute Error by an average of 0.313 and 0.182 on MovieLens and Book-Crossing dataset separately. According to the method that extracting single domain features, our proposed method reduces the Mean Absolute Error by an average of 0.065 and 0.099 on MovieLens and Book-Crossing dataset separately. The result also exhibits that our method outperforms other method in the sparse data.
THE COGNITIVE PERSPECTIVE ON STRATEGIC DECISION MAKING

Strategic management researchers are showing increased interest in the cognitions of strategic decision‐makers. In this article, the importance of strategic cognitions is discussed and research on a number of major topics within the cognitive perspective is summarized. the paper concludes with an integrative model of cognitions in strategic decision making. This model provides the basis for questions for future research.
Virulence and the Role of Iron in Pseudomonas aeruginosa Infection

The virulence of Pseudomonas aeruginosa can be enhanced by passage in mice or rabbits. Enhanced virulence has some specificity for the host in which the passage is done. Experimental infection in the peritoneal cavity of cannulated rabbits has shown that the injection of iron compounds can lead to a rapid and fatal growth of an otherwise nonlethal dose of bacteria. In vitro the unsaturated iron-binding proteins present in the peritoneal fluid can halve the growth rate of P. aeruginosa. The restricted rate of growth is restored to normal if the iron-binding proteins are saturated with iron. Exactly the same results are achieved with purified transferrin. Both fatal and nonfatal infections with P. aeruginosa cause a sharp fall in the percentage of saturation with Fe of the plasma and peritoneal fluid. In both normal and infected animals the peritoneal fluid is invariably less saturated than the plasma. Specific antiserum not only protects against death but also against the fall in iron saturation of the plasma and peritoneal fluid. In both fatal and nonfatal infections a high proportion of viable bacteria are unphagocytized in the peritoneal cavity.
Multi-Deep-Model Ensemble Technique for Aircraft Detection in Remote Sensing Images

Aircraft detection in remote sensing images is a challenging problem due to the small and densely distributed nature of objects. In this work, an ensemble-based multi-deep learning model is proposed which exploits the properties of both attention-based ResNet34 and YOLO V5 models for accurate aircraft object detection. Convolutional Block Attention Module (CBAM) is incorporated into ResNet34 to enhance the informative regions in the feature maps and suppress irrelevant information. To accurately locate the position of the object, a Multilevel fusion module is incorporated to fuse the output of shallow and deep class activation maps extracted from different layers of ResNet-CBAM. The pre-trained YOLO V5 model, utilizing fully labeled data, is used as the second model for ensembling. To integrate the results from both models, a non-maximum suppression ensemble technique is used. The performance of the proposed work is evaluated on the WSADD dataset in terms of different quantitative metrics such as Precision, Recall, and F1 score, and it has been found that the proposed methods yield better performance compared to the state-of-the-art methods.
A Validation System for Object Oriented Specifications of Information Systems

In this paper, we present a set of software tools for developing and validating object oriented conceptual models specified in TROLL. TROLL is a formal object-oriented language for modelling information systems on a high level of abstraction. The tools include editors, syntax and consistency checkers as well as an animator which generates executable prototypes from the models on the same level of abstraction. In this way, the model behaviour can be observed and checked against the informal user requirements. After a short introduction in some validation techniques and research questions, we describe briefly the TROLL language as well as its graphical version OMTROLL. We then explain the system architecture and show its functionalities by a simplified example of an industrial application which is called CATC (ComputerAided Testing and Certifying).
Evolution of epidemiological estimates of attributable fraction

Background and aim of the work: Lung cancer is the leading cause of cancer death world-wide. Among the possible causes, occupational risk factors play a major role and are potentially preventable. We reviewed the scientific evidence about lung cancer burden due to occupation. Methods: We reviewed the literature and selected population case-control and cohort studies which provided estimates of the proportion of lung cancers attributable to occupational carcinogens (population attributable fraction, PAF). Different methods were used to evaluate occupational exposure to suspected/known lung carcinogens: lists of high-risk occupations, job-exposure matrix ( JEM), expert assessment. Only studies which adjusted for tobacco smoking were included. Results: The PAFs reported by the 32 selected Italian and international studies among men vary greatly in time and space: they ranged between 0 to 40% according to different geographical prevalence of hazardous industries (e.g., basic metal industries, shipbuilding and railroad equipment manufacturing). The PAFs estimated using JEM and expert assessment were on average higher. Data for women were usually few and insufficient to calculate stable estimates. Conclusions: A significant proportion of lung cancers is attributable to occupational carcinogens. The estimates are extremely variable in time and place and mainly depend on the industrial setting of the area under study; caution is therefore required in generalizing these results to the whole country. Alternative approaches to evaluate occupational lung cancer burden among women are necessary. (www.actabiomedica.it)
A Comparison of University Students' Approaches to Learning Across Taiwan and Turkey

In this study, university students'approaches to studying were investigated across Turkey and Taiwan. Four hundred sixty-four Turkish university students and 546 Taiwanese university students filled out the Approaches to Studying Inventory (ASI). Approaches to studying was treated as a multidimensional scale with the subdimensions of Meaning Orientation, Reproducing Orientation, and Strategic Orientation. This 3-factor model was fitted across the cultures through the use of linear structural modeling and for each dimension mean differences between Turkish and Taiwanese students were evaluated. The 3-factor model gave sufficient fit regarding goodness-of-fit (GFI) and adjusted goodness-of-fit (AGFI) indexes, and moderate fit regarding the root mean square error of approximation (RMSEA) index within each culture and across the cultures. The means of the Turkish students were found to be significantly greater than the Taiwanese students in all the dimensions.
Optimal normalization tests for shoulder muscle activation: An electromyographic study

To accurately compare electromyographic data from different muscles and different subjects, it is necessary to normalize the integrated data obtained from each muscle. The purpose of this study was to identify the manual muscle testing positions that elicit maximal neural activation (integrated electromyography) of three rotator cuff muscles (supraspinatus, infraspinatus, and subscapularis) and five shoulder synergists (pectoralis major, latissimus dorsi, and anterior, middle, and posterior deltoids). The electromyographic activity of these eight muscles was examined in the nondominant shoulders of nine subjects. Indwelling wire electrodes (supraspinatus, infraspinatus, and subscapularis) and surface adhesive electrodes (pectoralis major, latissimus dorsi, and anterior, middle, and posterior deltoids) were placed. Each subject performed a series of 27 isometric contractions, and optimal tests (maximal neural activation) were identified for each muscle. Four tests were identified that resulted in the maximal neural activation of all eight shoulder muscles: 90° of scapular elevation with −45° of humeral rotation for the supraspinatus, anterior deltoid, and middle deltoid; external rotation at 90° of scapular elevation and −45° of humeral rotation for the infraspinatus and posterior deltoid: internal rotation at 90° of scapular elevation and neutral humeral rotation for the subscapularis and latissimus dorsi: and internal rotation at 0° of elevation and neutral rotation for the pectoralis major. These results identify four standard testing positions that will provide reference values for normalization of maximal voluntary contraction for the eight muscles of the shoulder examined in this study. Standardization of these test positions offers normalization guidelines that can be used in future dynamic electromyography studies of the shoulder.
DNA Break Mapping Reveals Topoisomerase II Activity Genome-Wide

Genomic DNA is under constant assault by endogenous and exogenous DNA damaging agents. DNA breakage can represent a major threat to genome integrity but can also be necessary for genome function. Here we present approaches to map DNA double-strand breaks (DSBs) and single-strand breaks (SSBs) at the genome-wide scale by two methods called DSB- and SSB-Seq, respectively. We tested these methods in human colon cancer cells and validated the results using the Topoisomerase II (Top2)-poisoning agent etoposide (ETO). Our results show that the combination of ETO treatment with break-mapping techniques is a powerful method to elaborate the pattern of Top2 enzymatic activity across the genome.
Verifying Propositional Unsatis ability: Pitfalls to Avoid

The importance of producing a certi cate of unsatis ability is increasingly recognized for high performance propositional satis ability solvers. The leading solvers develop a con ict graph as the basis for deriving (or \learning") new clauses. Extracting a resolution derivation from the con ict graph is theoretically straightforward, but it turns out to have some surprising practical pitfalls (as well as the unsurprising problem that resolution proofs can be extremely long). These pitfalls are exposed, solutions are presented, and analyzed for worse cases. Dramatic improvements on industrial benchmarks are demonstrated.
Aqua[4′-(4-chlorophenyl)-2,2′:6′,2′′-terpyridine]nitratocopper(II) nitrate [4′-(4-chlorophenyl)-2,2′:6′,2′′-terpyridine]dinitratocopper(II) monohydrate

The crystal structure of the title compound, [Cu(NO3)(C21H14ClN3)(H2O)]NO3·[Cu(NO3)2(C21H14ClN3)]·H2O, consists of two crystallographically independent CuII complexes, in which each copper cation is pentacoordinated by three N atoms of the chelating ligand and two O atoms of nitrate anions or water molecules. One of the coordinated nitrate anions is disordered over two set of sites in a 0.85:0.15 ratio.
Using Global Behavior Modeling to Improve QoS in Cloud Data Storage Services

The cloud computing model aims to make large-scale data-intensive computing affordable even for users with limited financial resources, that cannot invest into expensive infrastructures necesssary to run them. In this context, MapReduce is emerging as a highly scalable programming paradigm that enables high-throughput data-intensive processing as a cloud service. Its performance is highly dependent on the underlying storage service, responsible to efficiently support massively parallel data accesses by guaranteeing a high throughput under heavy access concurrency. In this context, quality of service plays a crucial role: the storage service needs to sustain a stable throughput for each individual accesss, in addition to achieving a high aggregated throughput under concurrency. In this paper we propose a technique to address this problem using component monitoring, application-side feedback and behavior pattern analysis to automatically infer useful knowledge about the causes of poor quality of service and provide an easy way to reason in about potential improvements. We apply our proposal to Blob Seer, a representative data storage service specifically designed to achieve high aggregated throughputs and show through extensive experimentation substantial improvements in the stability of individual data read accesses under MapReduce workloads.
Cohort Building through Experiential Learning

Universities are exploring ways to better prepare teachers for the classroom and to keep them there. Building cohorts of pre-service teachers is one of the ways currently under scrutiny. The University of Memphis began a new cohort-based, grant-funded program entitled Recruitment and Retention through Reinvention of Teacher Education (3Rs) to prepare middle-school math and science teachers in the summer of 2006. This article presents the results of a qualitative study on the effects of a four-day experiential learning program on the development of the 3Rs cohort of middle school pre-service teachers. Participants indicated that their experience was an effective way to build a graduate student cohort. Close relationships with each other were developed and support from the faculty was noted. Few pressing concerns were voiced. Getting away for an overnight stay, focus on educational best practices, and demonstrating the need and importance of this experience were listed as essential to the program.
OL-CBBA: An Online Task Allocation Algorithm under Weak Communication Conditions

Multiple unmanned aerial vehicles (UAVs) and multiple tasks allocation problem is difficult to solve. Existing task allocation algorithms assume that the UAVs’ position is static, and cannot assign tasks with the changing UAVs’ position simultaneously during task execution. Those algorithms reduce the efficiency of task allocation. In this paper, we propose an online consensus-based bundle algorithm (OL-CBBA) under weak communication for dynamic task allocation. We consider the situation that the location information of UAVs will constantly change during the dynamic execution of tasks. The algorithm first improves the static CBBA to an online algorithm by updating the task marginal score in task path. Moreover, we specify a flag for the convergence of individual tasks, allowing UAVs to start executing tasks earlier. Extensive comparative experiments prove the highly consistent efficiency of OL-CBBA under weak communication conditions. Specifically, the proposed OL-CBBA attains up to 22% improvement compared with CBBA.
QUICShield: A Rapid Detection Mechanism Against QUIC-Flooding Attacks

QUICis a modern transport layer internet protocol designed to be more efficient and secure than TCP (Transmission control protocol). However, QUIC remains vulnerable to handshake flooding attacks due to its similar design to TCP in the handshaking process. This paper introduces an innovative defence mechanism, QUICShield, which enables rapid detection and protection from QUIC-flooding DDoS attacks across different IP spoofing scenarios. QUICShield is a Bloom filter-based technique that provides rapid change detection to distinguish between incomplete or invalid handshakes and legitimate connections while accounting for common handshake errors. It utilizes the probabilistic data structure of Bloom Filter to detect malicious traffic effectively and incorporates change detection techniques to adapt to evolving attack patterns. Also, it addresses the unique challenges of QUIC-Flooding attacks, which exploit the protocol's stateless nature and the inclusion of cryptographic computations to overwhelm a target's computational resources. Existing defence mechanisms against DDoS attacks primarily focus on TCP SYN-Flooding. Although these approaches are effective in the TCP domain, they are inadequate in addressing the specific vulnerabilities related to the QUIC protocol. Our QUICShield technique fills this gap by offering a customized solution for QUIC-based systems. It neutralizes malicious traffic, maintains legitimate connections, and adapts to IP spoofing in the QUIC protocol networks. Furthermore, QUICShield defends against QUIC-Flooding DDoS attacks, with real attack emulation demonstrating improved detection of previously ineffective invalid packets, boosting network resilience against security threats.
Broadwell: A family of IA 14nm processors

Intel Core™ M and 5th generation of Core™ processors (code named Broadwell) are fabricated on an optimized 14 nm process technology node resulting in a 49% reduction in feature-neutral die area. 14nm created a new optimized process flavor for Core™ M to improve energy efficiency for mobile devices. Techniques and optimizations were implemented to deliver 2.5x TDP reduction coupled with up-to 60% higher graphics performance. New process technology combined with various design techniques reduced the minimum voltage of operation by 50 m V. Broadwell introduces the second generation of Fully Integrated Voltage Regulator with better droop control and parallel boot LVR along with other power-reduction features resulting in 35% reduction in active and standby power over first generation. 3DL inductor technology introduced for the first time in Broadwell, enables 30 % reduction in package thickness and improved low-load efficiency. IO re-partitioning of the SOC and a major re-design of DDR system resulted in 30% reduction in I/O power. Shutting down various parts of the SOC die in various idle states (C* states) resulted in 60% reduction in the idle power. New software controlled co-optimization methods were implemented such as duty-cycle control and dynamic display support to improve the energy efficiency of the graphics and the display subsystem.