Miracle-dz/UniFAR-FTUs huggingface dataset:
Tarbela reservoir, Pakistan: A region of compressional tectonics with reduced seismicity upon initial reservoir filling

The Tarbela reservoir is located on the Indus River in the lesser Himalayas of northern Pakistan, a region of considerable natural seismicity. A microseismic survey conducted prior to impounding has indicated that crustal shortening under horizontal north-south compression dominates present-day tectonics, resulting in thrusting and strike-slip motion along numerous faults. The reservoir was first partially filled for a few weeks in 1974 and then completely filled in 1975. In both cases, the microseismic activity decreased slightly during the impounding period and recovered quickly upon commencement of drainage or establishment of a constant reservoir level. In tectonic environments where the maximum principal stress is horizontal and the tectonic system is compressive, a vertical surface load can move the crustal stresses away from a Navier-Coulomb failure criterion, and hence can temporarily decrease seismicity. The observed rapid recovery of seismicity may alternately be explained by: (1) high rates of tectonic strain accumulation which, in turn, increase horizontal stresses at crustal depths; they may quickly overcome the stabilizing effects of the small vertical stress changes and increased friction across faults from reservoir loading and, hence, may return the crustal stress system to one of failure; or (2) high diffusivity of the basement rock results in a pore pressue increase after a few weeks of raised reservoir head; the raised pore pressure equally reduces the effective horizontal and vertical stresses and brings the crustal system back to failure. Since direct monitoring of pore pressure at crustal depths is not available at Trabela, it is presently not possible to distinguish between the two alternatives. Indirect observations, such as long-term monitoring of space-time changes in seismicity, may aid in the resolution of this ambiguity. A few reservoirs, located in regions with preferentially extensional or pure strike-slip tectonics, have triggered or induced seismic activity, whereas Tarbela reservoir, in a region of convergent tectonics, has (to present) only slightly modified the natural seismicity. Here, in a region of active Himalayan tectonics, it is likely that any severe earthquake to occur in the near future would occur sooner or later, regardless of the presence of the reservoir. Within hundreds of years a major earthquake near Tarbela appears tectonically inevitable. Yet the presence of the reservoir may strongly affect, say, the time of occurrence, exact location, and the details of rupture of an earthquake. The time most likely for inducing a tectonic stress release (if any) would be during or shortly after a rapid draw-down of the reservoir, when the decrease in pore pressure from its high level at crustal depths lags behind the instantaneous stress decrease from reservoir unloading.
Exploring the Utilization of Program Semantics in Extreme Code Summarization: An Experimental Study Based on Acceptability Evaluation

—With the rise of deep learning methods, neural network architecture adopted from neural machine translation has been widely studied in code summarization by learning the sequential content of code. Given the inherent nature of programming languages, learning the representation of source code from the parsed structural information is also a typical way for constructing code summarization models. Recent studies show that the overall performance of the neural models for code summarization can be improved by utilizing sequential and structural information in a hybrid manner. However, both of these two kinds of information fed to the neural models for code summarization fail to embrace the semantics of source code snippets in an explicit way. Is it really a good way to just leave the semantics as hidden things in the source code and have the neural models capture whatever they can get? To observe the utilization of program semantics in automatic code summarization, we conducted an experimental study by analyzing the acceptability of the extreme code summaries generated from neural models. To make the models aligned in the same context for this experimental study and to focus on the observation of the semantics, we re-implement the neural models from three selected studies as extreme code summarization solutions. After an intuitive observation and exploration of the generated summaries with the models trained from a Java dataset, we identify five acceptability aspects: (1) function name format; (2) function naming style; (3) semantic level similarity; (4) the differences in hitting rate of representative words; and (5) the correlation between extreme code summaries with function body. Based on the false negative and false positive phenomena in the results, ablation experiments have shown that the use of program semantics has a positive effect on generating high-quality abstracts in neural models. Our work proves the potential of utilizing the program semantics explicitly in code summarization, and the possible directions
RAMC: Reverse-Auction-Based Multilevel Cooperation for Large Size Data Download in VANETs

The cooperative data download in vehicular ad hoc networks (VANETs) is attracting more and more attention since a great number of services and applications, which aim at improving user safety and promoting overall travel experience, are based on the efficient and reliable data download among vehicles. However, the characteristics of VANETs, such as fast-moving vehicles, quick-changing topologies, and unstable channel conditions, put great challenge on the realization of efficient cooperative data download, especially for large size data download in highway environment. In this article, we present an efficient and economical cooperative data download mechanism for large size data in highway environment. A multilevel cooperation strategy is designed to enable progressive cooperation and to allow continuous adding of new cooperative vehicles as needed, so that the resources of candidate cooperative vehicles can be utilized sufficiently. Moreover, a reverse auction-based vehicles selection method is proposed to work closely with the multilevel cooperation strategy, to find the most appropriate cooperative vehicles, which can accomplish the data download task with the lowest cost. In addition, the performance degradation introduced by the communication blind zones between road side units (RSUs) is resolved by a carefully designed data forwarding policy. The proposed mechanism focuses on helping vehicles download large size data not only efficiently but also economically, thus distinct it from existing works. Simulation results prove that the proposed mechanism achieves remarkable performance gain in terms of data download cost, download time, completion ratio and the amount of downloaded data in one download period.
Influence of Generic Strategies on Student Attraction by Church Based Schools in Kenya (A Case Study of CITAM Schools)

Purpose: This study focused on assessing the influence of generic strategies on student attraction by church-based schools in Kenya with a case study of Christ Is the Answer Ministry schools. It is guided by the subsequent definite objectives; to determine the influence of Cost leadership strategy, focus strategy and Differentiation strategy on student attraction by church-based schools in Kenya. Methodology: The study has used descriptive cross-sectional design. The management personnel and teachers were the target population for the exercise which were limited to ten schools owned by CITAM. Primary data was collected using semi-structured questionnaires containing both open ended and close ended questions. The questionnaires were to be administered through a drop and pick method. Qualitative analysis was done on the information collected from the results of the questionnaires. Quantitative analysis includes descriptive statistical technique. Descriptive statistics compliments the use of frequencies, mean and percentages that was summarized and presented using tables, graphs and charts. The data was analysed with the aid of a linear regression model from an SPSS analysis tool. Findings: The study established that differentiation strategy and focus strategy had a positive and influence on student attraction by church based schools in Kenya as shown by beta values of 0.983 and 0.364 and significant values of 0.000 and 0.000 respectively. This bears the implications that increasing aspects either differentiation strategy or focus strategy with one unit results to increase in the levels of on student attraction with respective beta units. Cost leadership strategy on the other hand had a negative influence on student attraction by church based schools in Kenya as shown by a beta value of -0.002. On differentiation strategy, the study recommends prioritizing technological leadership is crucial in creating a modern and innovative learning environment that resonates with the preferences of contemporary students, enhancing customer care should be a central focus for church-based schools to create a supportive and nurturing educational community and expanding market share is essential in reaching a broader audience and establishing the school's unique value proposition within the educational landscape. Unique contribution to theory, practice and policy: On focus strategy, the study recommends, prioritizing targeted market segmentation is essential in catering to the unique needs and preferences of specific student groups, the focus on academic performance should remain a central priority in enhancing student attraction to church-based schools and strategic media advertisements play a crucial role in raising awareness and visibility of the unique educational offerings and values-based learning environment offered by church-based schools.
Stratigraphic interfaces identification based on wavelet transform

The local singularity of signal often carries a lot of important information. Unlike Fourier transform, the wavelet transform has good local property in time and frequency domains, and it is suitable for processing the non-stationary signal. According to the characteristics of impedance data, in this study we proposed a new concept, called impedance basis function, which can indicate discontinuity of impedance data in time and extract information of the stratigraphic interfaces exactly. The analysis based on Marmousiǁimpedance model and real seismic impedance data shows that our method is applicable to stratigraphic interfaces identification. Also, it is helpful to identification and interpretation of thin-bed.
The Holistic Expression Factors of Emotional Motion for Non-humanoid Robots

—The development of technology and the increasing prevalence of solitary living have transformed non-humanoid robots, such as robotic sweepers and mechanical pets, into potential sources of emotional support for individuals. Nevertheless, the majority of non-humanoid robots currently in existence are task-oriented and lack features such as facial expressions and sound. Existing research primarily emphasizes the details of human motion in robot motion design, while devoting less attention to the analysis of universal emotional expression factors and methods rooted in human recognition patterns. In our initial step, a theoretical framework and holistic expression factors were proposed based on Gestalt theory and SOR theory. These factors encompass vertical and horizontal motion direction, stimulation, and vertical repetition. Subsequently, animation simulation tests were conducted to confirm and examine the contributions of each factor to the recognition of emotional expressions. The results indicate that both vertical and horizontal movements can convey emotional valence. However, if both of them exist, there is no leading direction to the valence recognition result. When both vertical and horizontal movements are present, valence recognition is influenced by the combined effects of stimulation, vertical repetition, and movement direction. Simultaneously, non-humanoid robots can display recognizable emotional content when influenced by holistic expression factors. This framework can serve as a universal guide for emotional expression tasks in non-humanoid robots, proving the hypothesis that Gestalt theory is applicable in dynamic emotional recognition tasks. At the same time, these findings propose a new holistic perspective for designing emotional expression methods for robots.
gem5-accel: A Pre-RTL Simulation Toolchain for Accelerator Architecture Validation

Attaining the performance and efficiency levels required by modern applications often requires the use of application-specific accelerators. However, writing synthesizable Register-Transfer Level code for such accelerators is a complex, expensive, and time-consuming process, which is cumbersome for early architecture development phases. To tackle this issue, a pre-synthesis simulation toolchain is herein proposed that facilitates the early architectural evaluation of complex accelerators aggregated to multi-level memory hierarchies. To demonstrate its usefulness, the proposed gem5-accel is used to model a tensor accelerator based on Gemmini, showing that it can successfully anticipate the results of complex hardware accelerators executing deep Neural Networks.
Energy Cycle in the Ocean: Powering the Microbial World

Energy is the most important requirement for life. It can be acquired by harvesting electrons flowing naturally from reduced to oxidized inorganic compounds (lithotrophy) or organic compounds (organotrophy), or by lightmediated processes such as photosynthesis. Patterns of energy utilization have played a dominant role in the evolution of life and its diversification into intricately rich and complex ecosystems. A supply of reduced chemical species on the ocean floor supports chemoautotrophic life that is confined to the ocean abyss, whereas light at the surface propels the flow of photosynthetically produced electrons throughout most of the
HOW LEADERS CAN BUILD COMMON UNDERSTANDING, PSYCHOLOGICAL SAFETY, AND PROSOCIAL PURPOSE

The author, an “organizational psychologist by training, and now a writer and keynote speaker who helps organizations understand and apply evidence‐based leadership insights,” discusses the importance of teams and especially team cultures. He notes that “creating high‐performing teams through culture is the goal, but many of us are uncertain about the approach. ” He explains common or shared understanding, illustrated with an example from Chris Hadfield’s leadership during Expedition 35 on the International Space Station (ISS). He builds on Amy Edmondson’s psychological safety construct, with an example from Maggie Wilderotter, who turned around Frontier Communications in 2004. Another construct is prosocial purpose, building on the research of Wharton professor Adam Grant. Within this example the author explores KPMG and two of its highly successful internal campaigns, the “10,000 Stories Challenge,” and “We Shape History. ” One positive result from the campaigns: “KPMG ascended seventeen places on Fortune magazine’s list of the 100 Best Companies To Work For, surpassing all other “big four” accounting firms. ” Regarding leadership behavior within teamwork, the author cautions that “leaders who advocate for teamwork but fail to acknowledge their own imperfections (and thus the team’s growth opportunities) quickly lose credibility and the trust of their team. ”
The stability of a rapid mode II shear crack with finite cohesive traction

It has been found in numerical simulations by Andrews [1976] that a growing mode II shear crack may at first rapidly accelerate toward the Rayleigh wave speed vR and then after a short period of readjustment start running at a speed slightly greater than (2)½vS, where vS is the shear wave speed. In order to throw some light on this phenomenon we study in detail the steady motion of a semi-infinite crack which is driven by a following point load which remains at constant distance d from the crack tip. A cohesive traction which is a function of relative displacement acts in the Dugdale type tip region [Dugdale, 1960] which is small in comparison with d. We consider crack speeds vC in the range vC < vP, the P wave speed, and find that for vC < vR and for vS < vC < (2)½vS the load is a decreasing function of vC, while for (2)½vS < vC < vP the load increases with vC. The former situation is interpreted as instability, and the latter as stability. The range vR < vC < vS appears to be forbidden. This is in agreement with, and partially explains, Andrews's results. It also agrees with an earlier analytic solution obtained by Craggs [1960] for vC < vR. We find that for vC < vR the displacement in the tip region has a shape independent of vC but suffers a contraction analogous to a Lorentz contraction so that the length goes to zero as vC ↑ vR.
Assessing the relationship between tumor proliferation and prognosis in breast cancer patients: A pathological analysis

Background: Tumor proliferation is a key prognostic factor in breast cancer, but the relationship between tumor proliferation and prognosis remains unclear. Aims and Objectives: To investigate the association between tumor proliferation and prognosis in breast cancer patients using a pathological analysis. Materials and Methods: A retrospective cohort study was conducted, including 100 breast cancer patients who underwent surgical resection between January 2021 and December 2022.Tumor proliferation was assessed using Ki-67 immunostaining and evaluated patient prognosis based on disease-free survival (DFS) and overall survival (OS). We performed statistical analyses to examine the association between tumor proliferation and prognosis. Results: Our results showed a significant correlation between tumor proliferation and prognosis in breast cancer patients. High Ki-67 expression was associated with shorter DFS and OS, while low Ki-67 expression was associated with longer DFS and OS. The difference in DFS and OS between high and low Ki-67 expression groups was statistically significant. Conclusion: Tumor proliferation is a valuable prognostic marker in breast cancer and could be used to guide treatment decisions. Our findings suggest that patients with high Ki-67 expression may benefit from more aggressive treatment options, while patients with low Ki-67 expression may be able to avoid unnecessary treatment and its associated side effects. The accurate assessment of tumor proliferation using Ki-67 immunostaining could potentially improve patient outcomes and reduce the burden of breast cancer treatment.
Predictability of cortico-cortical connections in the mammalian brain

Abstract Despite a five order of magnitude range in size, the brains of mammals share many anatomical and functional characteristics that translate into cortical network commonalities. Here we develop a machine learning framework to quantify the degree of predictability of the weighted interareal cortical matrix. Partial network connectivity data were obtained with retrograde tract-tracing experiments generated with a consistent methodology, supplemented by projection length measurements in a nonhuman primate (macaque) and a rodent (mouse). We show that there is a significant level of predictability embedded in the interareal cortical networks of both species. At the binary level, links are predictable with an area under the ROC curve of at least 0.8 for the macaque. Weighted medium and strong links are predictable with an 85%–90% accuracy (mouse) and 70%–80% (macaque), whereas weak links are not predictable in either species. These observations reinforce earlier observations that the formation and evolution of the cortical network at the mesoscale is, to a large extent, rule based. Using the methodology presented here, we performed imputations on all area pairs, generating samples for the complete interareal network in both species. These are necessary for comparative studies of the connectome with minimal bias, both within and across species.
Sequence-to-Sequence-Based Beta-VAE Combined With IECA Attention Mechanism for Energy Disaggregation Algorithm

Nonintrusive load monitoring (NILM) is a technology that measures and identifies individual appliances’ energy consumption by analyzing the total power consumption collected by building sensors. Using the energy disaggregation method, the total power consumption can be disaggregated down to the device level. With the emergence of deep learning, energy disaggregation methods have improved in recent years. However, NILM still faces significant challenges in its generalization capabilities for different households and in disaggregating complex multistate devices. To address these issues, on the basis of sequence-to-sequence, this article proposes a beta-variational autoencoder (Beta-VAE) combined with improved efficient channel attention (IECA) mechanism for energy disaggregation algorithm. In this model, Beta-VAE leverages its strong feature learning and disentanglement capabilities to improve the accuracy of multistate device disaggregation by learning the feature representation of the latent space. Meanwhile, a new improved channel attention IECA is also introduced, which is combined with skip connection technology and is applied between the encoder and decoder to capture multiscale features and improve the reconstruction of power signals. Furthermore, we apply the Gaussian error linear unit (GELU) activation function and instance normalization to the feature extraction network to improve the convergence speed and generalization capability of the model. Finally, we tested and compared our method with several state-of-the-art NILM algorithms on the U.K.-DALE and REFIT datasets and obtain significant improvement. The results showed that the mean absolute error (MAE) of all appliances decreased by an average of 46% and the F1 Score increased by 20%.
Socioeconomic Contribution of Oxytenanthera abyssinica (A.Rich) Munro and Determinants of Growing in Homestead Agroforestry System in Northern Ethiopia

Oxytenanthera abyssinica (A.Rich.) Munro is known to be one of the lowland perennial grass species in Ethiopia with tremendous products and ecological services. It is uncommon to find O. abyssinica at the homestead as it was commonly found in the study area as part of an agroforestry system. This study was conducted to assess socioeconomic benefits of O. abyssinica and factors that influence farmers’ decision to use homestead agroforestry systems, based on a survey of 153 households in Serako kebele, Tselemti woreda, Ethiopia. This paper evaluates, using descriptive statistics, propensity score matching and logit regression analysis. The analysis demonstrates that farmers make decisions to grow O. abyssinica as homestead agroforestry systems based on household and field characteristics. The factors that significantly influenced growing decisions include homestead land holding size, total livestock owned, extension advice, and distance to local market. The average treatment effect (ATT) results show that the households with an O. abyssinica grower had significantly higher annual household income, annual expenditure, and number of months with enough food when compared to the control group. Therefore, we conclude that development of infrastructures that link producers with consumers, availability of large homestead land size, and expansion of extension facilities may enhance engagement of domestication of O. abyssinica at the homestead for sustainable livelihood options.