nils-herrmann/clean_scirepeval huggingface dataset:
Ai BCS: A GPU cluster scheduling optimization based on SKE model
Venue: Microprocess. Microsystems

SKE is more accurate than the other models.SKE can help us to choose the best solution of parallel program and optimize the thread block configurations for the different types of GPU.SKE can help the scheduling algorithm of GPU cluster to reduce the subtask migration of balance according to the current load. A GPGPU is very important technology and a research hotspot for cloud computing. We pay close attention to its energy consumption and performance. In this paper, a static performance analysis model of GPU, SKE (Single Kernel Estimate) is set up to analyze the completion time of the kernel function on a GPU to find the optimal parallel solution to different tasks in a specific GPU device and the granularity size of the thread block division, thus enabling the fastest execution speed of the kernel function. The deviation between the completion time calculated by SKE and the real execution time of the kernel is no more than 13% On this basis, we calculate the completion time for each sub GPU task and seek the critical path of the GPU cluster, and propose a GPU cluster scheduling algorithm, BCS (Based on Critical path Scheduling) The algorithm regulates the frequency of non critical nodes, mainly through dynamic voltage and frequency scaling (DVFS) technology, and achieves the goal of reducing the energy consumption of GPU nodes without affecting the final completion time of the cluster. The evaluation results show that BCS reduces energy consumption by a maximum of 9.4% compared to DRS.
Wood Composite as an Energy Efficient Building Material: Guided Sunlight Transmittance and Effective Thermal Insulation

Among many other requirements, energy efficient building materials require effective daylight harvesting and thermal insulation to reduce electricity usage and weatherization cost. The most commonly used daylight harvesting material, glass, has limited light management capability and poor thermal insulation. For the first time, transparent wood is introduced as a building material with the following advantages compared with glass: (1) high optical transparency over the visible wavelength range >85% (2) broadband optical haze >95% which can create a uniform and consistent daylight distribution over the day without glare effect; (3) unique light guiding effect with a large forward to back scattering ratio of 9 for a 0.5 cm thick transparent wood; (4) excellent thermal insulation with a thermal conductivity around 0.32 W m 1 K 1 along the wood growth direction and 0.15 W m 1 K 1 in the cross plane, much lower than that of glass (1 W m 1 K 1) (5) high impact energy absorption that eliminates the safety issues often presented by glass; and (6) simple, scalable fabrication with reliable performance. The demonstrated transparent wood composite exhibits great promise as a future building material, especially as a replacement of glass toward energy efficient building with sustainable materials.
Determining shear modulus of thin wood composite materials using a cantilever beam vibration method

Shear modulus (G) of thin wood composite materials is one of several important indicators that characterizes mechanical properties. However, there is not an easy method to obtain this value. This study presents the use of a newly developed cantilever beam free vibration test apparatus to detect in plane G of thin wood composite materials by measuring the first order free vibration cantilever specimens and its logarithmic decrement of vibration. Six sets of commercially purchased thin wood composite materials having three different fiber types were tested. A significant linear correlation was found between in plane G and bending modulus of elasticity (MOE) from cantilever beam free vibration test and MOE was shown to be approximately two times of in plane G. This was in full agreement with previous findings by other researchers. The study demonstrated that the cantilever beam free vibration method could be widely used to obtain in plane G easily for thin wood composite materials.
Distributed Air Indexing Scheme for Full Text Search on Multiple Wireless Channel

Wireless data broadcast is the most popular method to disseminate frequently requested data efficiently to a large number of mobile devices. Full text search is a popular query type, for retrieving the documents. Many research efforts have been made which focuses how to apply full text search on wireless broadcast. By increasing the numbers of broadcast channels is a logical way to minimize the energy consumption and access latency. In this paper, we further extend the problem of generating a broadcast sequence of data items to facilitate energy efficient full text search on multiple wireless channels. To support our proposed indexing scheme, we propose a data access algorithm and a data broadcast model for full text search indexing scheme on multi channel. Since the energy of portable devices is limited, minimization of energy consumption and access latency for broadcasting are the important issues. The performance of the proposed scheme is further analyzed and compared with existing full text search indexing schemes. The results show the efficiency of our approach with respect to energy consumption and access latency.
Ultrathin, Skin Like Devices for Precise, Continuous Thermal Property Mapping of Human Skin and Soft Tissues

Precision thermal measurements of skin and soft tissue can provide clinically relevant information about cardiovascular health, cognitive state, hydration levels, heterogeneous vasculature changes, and many other important aspects of human physiology. In this chapter we discuss recent advances in ultrathin, compliant skin like sensor/actuator technologies that enable forms of continuous thermal mapping, of temperature as well as transport properties, that are unavailable with other methods. We review the key mechanical and thermal properties that are fundamental to the operation of this class of devices. Further discussion of devices configured for mapping temperature, monitoring local thermal transport and skin hydration, and mapping thermal transport for blood flow analysis provides a few examples of the types of capabilities that are enabled with these technologies.
Effects of Pre Service Information Technologies (IT) Teachers' Thinking Styles on Their Use of Information and Communication Technology (ICT)

Thinking styles are considered as approaches and tendencies of individuals toward various problems, incidents, phenomenon and variables which they face through their thinking processes. Preservice teachers are expected to be capable of using information and communication technologies (ICT) in intra and extra curricular activities and be a role model to their students. In this regard, it is important to investigate the relationship between thinking styles of preservice teachers from the Department of Computer Education and Instructional Technology (CEIT) department who are expected to utilize from the ICT and their attitudes toward ICT. The present study aims to investigate thinking styles of preservice teachers from the CEIT department and their attitudes toward the ICT and the relationship between these two variables. According to the present study's results, preservice teachers at most prefer innovative and visionary "Innovative thinking style" which deals with indetermined indefinite works; at least prefer "Traditionalist thinking style" which is subject to certain codes and more realists. Whereas gender and grade level variables have no any effect on thinking style preferences; academic success level has statistically significant difference. It was observed that attitudes of participants regarding utilization from the ICT in education was rather high; gender and grade variables have no effect on their attitude toward the ICT; there is positive and proportional relationship between academic success levels and their attitude toward the ICT. Moreover, as perception levels of preservice teachers regarding innovative thinking style increases, their attitude toward the ICT enhances. On the contrary, their perception levels regarding traditionalist thinking style increases, their attitude toward the ICT is affected adversely.  Thinking styles, information and communication technologies, education technologies, computer usage in education, Computer Education and Instructional Technology (CEIT)
Impact of Training and Development of Employees on Employee Performance through Job Satisfaction: A Study of Telecom Sector of Pakistan

Training and development of employees and job satisfaction of employees are two crucial components for the performance of employee. In this study the influence of training and development on employee performance through job satisfaction is studied. 115 questionnaires were distributed among employees i.e. executives and managers of Telecom companies in Abbottabad, Haripur and Mansehra of which 105 were returned. Convenience sampling technique was used for data collection. The response rate was 91% The finding of our study showed positive impact of training and development and job satisfaction with employee performance. Training and development will lead to higher job satisfaction level in employees and they will fulfill their duties with a great deal of responsibility with best performance.
Microsoft Academic (Search) a Phoenix arisen from the ashes?
Venue: Scientometrics

In comparison to the many dozens of articles reviewing and comparing (coverage of) the Web of Science, Scopus, and Google Scholar, the bibliometric research community has paid very little attention to Microsoft Academic Search (MAS) An important reason for the bibliometric community's lack of enthusiasm might have been that MAS coverage was fairly limited, and that almost no new coverage had been added since 2012. Recently, however, Microsoft introduced a new service Microsoft Academic built on content that search engine Bing crawls from the web. This article assesses Microsoft Academic coverage through a detailed comparison of the publication and citation record of a single academic for each the four main citation databases: Google Scholar, Microsoft Academic, the Web of Science, and Scopus. Overall, this first small scale case study suggests that the new incarnation of Microsoft Academic presents us with an excellent alternative for citation analysis. If our findings can be confirmed by larger scale studies, Microsoft Academic might well turn out to combine the advantages of broader coverage, as displayed by Google Scholar, with the advantages of a more structured approach to data presentation, typical of Scopus and the Web of Science. If so, the new Microsoft Academic service would truly be a Phoenix arisen from the ashes.
Inferring annotations for device drivers from verification histories
Venue: 2016 31st IEEE/ACM International Conference on Automated Software Engineering (ASE)

This paper studies and optimizes automated program verification. Detailed reasoning about software behavior is often facilitated by program invariants that hold across all program executions. Finding program invariants is in fact an essential step in automated program verification. Automatic discovery of precise invariants, however, can be very difficult in practice. The problem can be simplified if one has access to a candidate set of assertions (or annotations) and the search for invariants is limited over the space defined by these annotations. Then, the main challenge is to automatically generate quality program annotations. We present an approach that infers program annotations automatically by leveraging the history of verifying related programs. Our algorithm extracts high quality annotations from previous verification attempts, and then applies them for verifying new programs. We present a case study where we applied our algorithm to Microsoft's Static Driver Verifier (SDV) SDV is an industrial strength tool for verification of Windows device drivers that uses manually tuned heuristics for obtaining a set of annotations. Our technique inferred program annotations comparable in performance to the existing annotations used in SDV that were devised manually by human experts over years. Additionally, the inferred annotations together with the existing ones improved the performance of SDV overall, proving correct 47% of drivers more while running 22% faster in our experiments.
The EGFR signaling pathway controls gut progenitor differentiation during planarian regeneration and homeostasis
Venue: Development

The planarian Schmidtea mediterranea maintains and regenerates all its adult tissues through the proliferation and differentiation of a single population of pluripotent adult stem cells (ASCs) called neoblasts. Despite recent advances, the mechanisms regulating ASC differentiation into mature cell types are poorly understood. Here, we show that silencing of the planarian EGF receptor egfr 1 by RNA interference (RNAi) impairs gut progenitor differentiation into mature cells, compromising gut regeneration and maintenance. We identify a new putative EGF ligand, nrg 1, the silencing of which phenocopies the defects observed in egfr 1(RNAi) animals. These findings indicate that egfr 1 and nrg 1 promote gut progenitor differentiation, and are thus essential for normal cell turnover and regeneration in the planarian gut. Our study demonstrates that the EGFR signaling pathway is an important regulator of ASC differentiation in planarians.  EGFR signaling promotes the differentiation of stem cell derived progenitors into mature gut cells during both normal homeostasis and regeneration of the planarian Schmidtea mediterranea.
b Elemene enhances the efficacy of gefitinib on glioblastoma multiforme cells through the inhibition of the EGFR signaling pathway.
Venue: International journal of oncology

Glioblastoma multiforme (GBM) is the most common and severe form of primary tumor in the central nervous system of adults which has poor prognosis and limited therapeutic options. Epidermal growth factor receptor (EGFR) inhibitor, such as gefitinib (brand name Iressa, ZD1839) has been approved as a targeted medicine for several types of tumor including glioblastoma multiforme. However, gefitinib exerted very limited effects on some glioblastoma multiforme patients after a period of treatment due to intrinsic and acquired drug resistance. b Elemene, a natural plant drug extracted from Curcuma wenyujin, has shown promising anticancer effects against a broad spectrum of tumors. In the present study, we found that b elemene could enhance the chemosensitivity of glioblastoma multiforme cells to gefitinib. The combination medication of b elemene and gefitinib not only inhibited the survival and proliferation of glioblastoma multiforme cells via inhibition of EGFR signaling pathway but also induced more distinct apoptosis and autophagy in the glioblastoma multiforme cells than the gefitinib monotherapy. These results showed that b elemene might be one potential adjuvant to enhance the effect of EGFR inhibitor and reduce the resistance of gefitinib in glioblastoma multiforme.
Extracellular PKM2 induces cancer proliferation by activating the EGFR signaling pathway.
Venue: American journal of cancer research

Pyruvate kinase is a key enzyme in the glycolytic pathway that converts phosphoenolpyruvate to pyruvate, and the M2 isoform of pyruvate kinase (PKM2) is associated with cancer. PKM2 has been reported to function independently of its pyruvate kinase activity, which is crucial for cancer cell proliferation. Moreover, there is growing evidence indicating that dimeric PKM2 is released from tumor cells into the circulation of cancer patients. However, the role of secreted PKM2 in cancer is not well understood. Here, we found that the phosphorylation level of epidermal growth factor receptor (EGFR) significantly increased upon the exposure of cells to the recombinant PKM2 protein. In addition, secreted PKM2 induces EGFR phosphorylation and activates the EGFR downstream signaling in triple negative breast cancer cells. In contrast, knocking down PKM2 decreased EGFR phosphorylation. Moreover, expression of R399E mutant PKM2, which has been reported to preferentially form a dimer, enhanced EGFR phosphorylation, cellular transformation, and cell proliferation more strongly than the wild type PKM2. Thus, our study revealed a novel function of extracellular PKM2 in the promoting cancer cell proliferation through EGFR activation.
Demystifying Insider Threat: Language Action Cues in Group Dynamics
Venue: 2016 49th Hawaii International Conference on System Sciences (HICSS)

Written language as a symbolic medium of expression plays an important role in communications. In particular, written words communicated online can provide indications of an actor's behavioral intent. This paper describes an ongoing investigation into the interconnectivity between words and actions for a deceptive insider on group dynamics in virtual team collaboration. An experiment using an online game environment was conducted in 2014. Our findings support the hypothesis that language action cues of group interactions will change significantly after an insider has been compromised. Deceptive actors tend to use more cognition, inclusivity and exclusivity words when interacting with group members. Future work will employ finely tuned complex Linguistic Inquiry and Word Count (LIWC) dictionaries to identify additional language action cues for deception in various experimental conditions.
Using recurrence analysis to examine group dynamics.

This article provides an accessible introduction to recurrence analysis an analytical approach that has great promise for helping researchers understand group dynamics. Recurrence analysis is a technique with roots in the systems dynamics literature that was developed to reveal the properties of complex, nonlinear systems. By tracking when a system visits similar states at multiple points in its life and the form or pattern of these recurrences over time recurrence analysis equips researchers with a set of new metrics for assessing the properties of group dynamics, such as recurrence rate (i.e. stability) determinism (i.e. predictability) and entropy (i.e. complexity) Recent work has shown the potential value of recurrence analysis across a number of different disciplines. To extend its use within the domain of group dynamics, the authors present a conceptual overview of the technique and give a step by step tutorial on how to use recurrence analysis to study groups. An exemplar application of recurrence analysis using dialogue based data from 63 three person student groups illustrates the use of recurrence analysis in examining how groups change their focus on different processes over time. This is followed by a discussion of variations of recurrence analysis and implications for research questions within the literature on groups. When group researchers track group processes or emergent states over time, and thus compile a time series dataset, recurrence analysis can be a useful technique for measuring the properties of groups as dynamic systems.
Conceptualizing Emergent States: A Strategy to Advance the Study of Group Dynamics

AbstractIn this review, we aim to advance work on group and team dynamics by examining how important elements of dynamism are embedded in the current literature on emergent states in groups. We use the concept of emergence as an organizing frame, building block, and critical lens, first summarizing key aspects of the extant literature on emergence, and then drawing four core characteristics of emergent phenomena from this literature. We use these characteristics to organize our review and examine how emergent states are portrayed in the past decade of groups literature. We end by exploring challenges to the development of a more dynamic perspective and by offering specific suggestions to guide and advance future work on groups and teams.
The Group Dynamics of Interorganizational Relationships

This paper examines how organizations collaborate with multiple partners, such as when they develop innovative and complex product platforms like smartphones, servers, and MRI machines that rely on technologies developed by organizations in three or more sectors. Research on multipartner alliances often treats them as a collection of independent dyads, neglecting the possibility of third party influence and interference in dyads that can inhibit innovation. Using a multiple case, inductive study of six groups, each composed of three organizations engaged in technology and product development in the computer industry, I examine the collaborative forms and processes that organizations use to innovate with multiple partners in groups. Groups that used the collaborative forms of independent parallel dyads or single unified triads generated mistrust and conflict that stemmed from expectations about third party participation and overlapping roles and thus had low innovation performance and weaker ties. Other groups avoided these problems by using a dynamic collaboration process that I call "group cycling," in which managers viewed their triad as a small group, decomposed innovative activities into a series of interlinked dyads between different pairs of partners, and managed third party interests across time. By temporarily restricting participation to pairs, managers chose which ideas, technologies, and resources to incorporate from third parties into single dyads and ensured that the outputs of multiple dyads were combined into a broader innovative whole.