nils-herrmann/clean_scirepeval huggingface dataset:
Professional Competencies for Real? A Question about Identity!
Venue: ITiCSE

How students develop professional competencies has been an interest for me for decades. There are several aspects to this issue that I have addressed, e.g. what are professional competencies, how can their development of them be supported in educational settings, what motivates a student to put in an effort towards developing a competency, how can they be assessed, how can progression of professional competencies be handled in education curricula, and how can development of professional competencies be specified in a course description. These are among the more prominent issues that have been on my mind. In this work I have noticed a huge "gap" between how professional competencies are expressed as important learning outcomes of degree programs and the almost zero link to how this development should be done at the course instance level. This "gap" is frustrating for me and a source for thoughts regarding how to bridge that "gap" Work in our research group UpCERG (Uppsala Computing Education Research Group, www.it.uu.se/research/group/upcerg) has lately included studying issues related to identity, initially mostly the identity of different student cohorts, but now also that of teachers and education leaders. This research provides valuable insights towards causes for the "gap" That is, the slow closing of the "gap" can be understood by placing this in the context of the identity of the teachers (especially) and the students. It is how professional competencies are valued in relation to "pure" subject knowledge among these identities that provides severe obstacles to inclusion of development of professional competencies in a meaningful way at the course instance level. This is despite much of the previous work regarding issues related to developing professional competencies in educational settings, as those mentioned above. I will address how I view the identities of teachers and students interfering with integration of development of professional competencies in degree programs. I will give examples from our research and my experience that illustrates the difficulties and outline some potential interventions that might lead to changes. My hope is that this talk will result in many fruitful discussions, both at the talk and afterwards.
Event triggered sliding mode control for delta operator systems
Venue: IECON 2016 42nd Annual Conference of the IEEE Industrial Electronics Society

The paper presents an event triggering based sliding mode control law for delta operator systems with disturbance. The discrete domain representation of a system using shift operator becomes numerically ill conditioned at very high sampling rates. To circumvent this problem, the system is represented using delta operator. The delta operator creates a rapprochement between continuous time and discrete time system model at very high sampling rates. A discrete time sliding mode (DTSM) control law is developed to achieve robustness against external disturbances. Further to reduce the resource utilization, an event triggered DTSM control law is proposed such that the closed loop system is stable. Due to the inherent discrete nature of the control there is no accumulation of triggering instants at any instant of time. Hence the zeno free execution of the control updating instants is always guaranteed. Simulation results are also shown to illustrate the effectiveness of the proposed method.
Output Feedback Based Sliding Mode Control for Fuzzy Systems With Actuator Saturation
Venue: IEEE Transactions on Fuzzy Systems

In this paper, a novel adaptive sliding mode controller is designed for Takagi Sugeno (T S) fuzzy systems with actuator saturation and system uncertainty. By the delta operator approach, the discrete time nonlinear system is described by a T S fuzzy model with unmeasurable state. By singular value decomposition of system input matrix, a reduced order system is obtained for the design of sliding mode surface. A new adaptive sliding mode controller based on system output is presented to guarantee that the closed loop system is uniformly ultimately bounded. Four examples are provided to illustrate the effectiveness and applicability of the proposed control scheme.
Discrete event triggered sliding mode control with fast output sampling feedback
Venue: 2016 14th International Workshop on Variable Structure Systems (VSS)

This paper deals with event triggering based design of discrete time sliding mode (DTSM) control for linear systems. Multirate output feedback based DTSM is designed with event triggering strategy such that the system trajectories remain bounded in the vicinity of sliding manifold. An event triggering rule is developed for DTSM which is evaluated only at periodic time intervals. The control is updated whenever the triggering instant is generated at these discrete time instants. It is shown that with this technique the system trajectories remain bounded. Also, in this triggering scheme there is always guaranteed Zeno free execution of triggering sequences as it is inherently discrete. Simulation results are shown to demonstrate the theoretical treatments of this paper.
5G Ultra Dense Cellular Networks
Venue: IEEE Wireless Communications

Traditional ultra dense wireless networks are recommended as a complement for cellular networks and are deployed in partial areas, such as hotspot and indoor scenarios. Based on the massive multiple input multi output antennas and the millimeter wave communication technologies, the 5G ultra dense cellular network is proposed to deploy in overall cellular scenarios. Moreover, a distribution network architecture is presented for 5G ultra dense cellular networks. Furthermore, the backhaul network capacity and the backhaul energy efficiency of ultra dense cellular networks are investigated to answer an important question, that is, how much densification can be deployed for 5G ultra dense cellular networks. Simulation results reveal that there exist densification limits for 5G ultra dense cellular networks with backhaul network capacity and backhaul energy efficiency constraints.
Mobility Aware Caching and Computation Offloading in 5G Ultra Dense Cellular Networks
Venue: Sensors

Recent trends show that Internet traffic is increasingly dominated by content, which is accompanied by the exponential growth of traffic. To cope with this phenomena, network caching is introduced to utilize the storage capacity of diverse network devices. In this paper, we first summarize four basic caching placement strategies, i.e. local caching, Device to Device (D2D) caching, Small cell Base Station (SBS) caching and Macrocell Base Station (MBS) caching. However, studies show that so far, much of the research has ignored the impact of user mobility. Therefore, taking the effect of the user mobility into consideration, we proposes a joint mobility aware caching and SBS density placement scheme (MS caching) In addition, differences and relationships between caching and computation offloading are discussed. We present a design of a hybrid computation offloading and support it with experimental results, which demonstrate improved performance in terms of energy cost. Finally, we discuss the design of an incentive mechanism by considering network dynamics, differentiated user's quality of experience (QoE) and the heterogeneity of mobile terminals in terms of caching and computing capabilities.
Wireless Backhaul Capacity of 5G Ultra Dense Cellular Networks
Venue: 2016 IEEE 84th Vehicular Technology Conference (VTC Fall)

With the growth of wireless transmission rate on user terminals, the backhaul network capacity becomes a bottleneck for improving the performance of future 5G ultra dense cellular networks. Based on the wireless multi hop relay technology, the backhaul network capacity of 5G ultra dense cellular networks with multi gateways is analyzed in this paper. Moreover, a minimum average hop number (MAN) algorithm is developed to improve the backhaul network capacity and energy efficiency of wireless backhaul networks for 5G ultra dense cellular networks. Simulation results indicate there exist a stationary backhaul network capacity and a maximum energy efficiency of wireless backhaul networks when the density of small cell BSs is larger than the specified threshold.
Annual Report to the Nation on the Status of Cancer, 1975 2012, featuring the increasing incidence of liver cancer
Venue: Cancer

Annual updates on cancer occurrence and trends in the United States are provided through an ongoing collaboration among the American Cancer Society (ACS) the Centers for Disease Control and Prevention (CDC) the National Cancer Institute (NCI) and the North American Association of Central Cancer Registries (NAACCR) This annual report highlights the increasing burden of liver and intrahepatic bile duct (liver) cancers.
Adaptive Sex Specific Cognitive Bias in Predation Behaviours of Japanese Pygmy Squid

Errors in decision making in animals can be partially explained by adaptive evolution, and error management theory explains that cognitive biases result from the asymmetric costs of false positive and false negative errors. Error rates that result from the cognitive bias may differ between sexes. In addition, females are expected to have higher feeding rates than males because of the high energy requirements of gamete production. Thus, females may suffer relatively larger costs from false negative errors (i.e. non feeding) than males, and female decisions would be biased to reduce these costs if the costs of false positive errors are not as high. Females would consequently overestimate their capacity in relation to the probability of predation success. We tested this hypothesis using the Japanese pygmy squid Idiosepius paradoxus. Our results show that size differences between the squid and prey shrimp affected predatory attacks, and that predatory attacks succeeded more often when the predator was relatively larger than the prey. Nevertheless, compared to male predatory attacks, female squid frequently attacked even if their size was relatively small compared to the prey, suggesting that the females overestimated their probability of success. However, if the females failed in the first attack, they subsequently adjusted their attack threshold: squid did not attack again if the prey size was relatively larger. These results suggest a sex specific cognitive bias, that is females skewed judgment in decision making for the first predation attack, but they also show that squid can modify their threshold to determine whether they should attack in subsequent encounters.
Adaptive features of natural killer cells, lymphocytes of innate immunity
Venue: Russian Journal of Bioorganic Chemistry

Natural killer cells (NK cells) are traditionally attributed to the innate immune system. It is considered that previously received stimuli have little effect on the functioning of these immune cells. Indeed, NK cells even without prior sensitization provide a rapid effector response against tumor, virus infected, or otherwise damaged cells. They have a limited repertoire of receptors, the expression of which does not require somatic recombination. However, recent data indicate that NK cells may acquire the properties specific to adaptive immune cells. In particular, NK cells have been shown to possess the features of immunological memory, namely, the ability to more quickly and effectively respond to a repeated stimulus. The mechanisms of memory acquisition in NK cells differ from those implemented in T and B lymphocytes and are still rather vague. Presumably, some of these mechanisms underlie the significant phenotypic and functional NK cell diversity emerging during their differentiation. The recent data accumulated in this area considerably change the existing immunology paradigm, which postulates a clear delineation of the adaptive and innate immune cells. The published data on phenotypic and functional characteristics of NK cells and particular changes in these characteristics during NK cell differentiation and generation of memory like NK cells are reviewed.
PENGARUH PENERAPAN SISTEM INFORMASI AKUNTANSI TERHADAP KINERJA INDIVIDUAL DENGAN BUDAYA ORGANISASI SEBAGAI PEMODERASI

Implementation of information systems in the organization will affect the performance of individuals within the organization. This study aimed to examine the effect of the application of accounting information system of individual performance and to determine the moderating influence of organizational culture in the application of accounting information system of individual performance in the savings and credit cooperatives in the district of Tabanan. This research was conducted at 24 savings and credit cooperatives in the district of Tabanan. Sample selection is done by using purposive sampling method. Data collected through questionnaires. The analysis technique used in this study are moderated regession analysis. The study found that the application of the accounting information system with positive impact on the performance of individual, strengthens organizational culture influence the application of accounting information systems on individual performance.
Evaluating a vocational training programme for women refugees at the Zaatari camp in Jordan: women empowerment: a journey and not an output

This study aims at evaluating a vocational training programme entitled 'Women and Girls Oasis' at the Zaatari Refugee Camp in the city of Mafraq, Jordan. The research study was undertaken in 2014/2015, and highlights the impact of such vocational training programmes on the well being of Syrian women refugees. The results show that 'Women and Girls Oasis' Programme enhanced women's confidence and self esteem, improved their occupational business, and entrepreneurship skills, helped them generate income to build a better life for their shattered families; and gave them hope and opportunities after experiencing war firsthand. The study reveals that in a refugee community, patterns are deconstructed and gender roles may be changed; this gender equality and women empowerment are seen as perquisites for sustainable development and achieving the millennium development goal. The study offers recommendations for UN Women, UNHCR and similar NGO's concerned with the well being of refugees in Jordan and neighbouring countries.
Barriers of Reporting Sexual Violence in Syrian Refugee Camps

Barriers in reporting sexual violence have emerged as a common problem for refugee camps hosting women. Approaches to increase reporting among women who have experienced sexual violence have not adequately considered the cultural context and what actions would help or hinder Syrian women from reporting sexual gender based violence. In a qualitative case study, agencies operating in Vancouver, Canada and Zaatari Camp, Jordan found that Syrian women did not report due to shame, lack of trust in helpers, and a strained legal framework which contributed to non reporting of sexual violence. With input from agencies helping refugees and a Syrian Canadian journalist, this study's findings suggest that awareness of sexual violence and its consequences need to be directed towards both men and women, to promote the idea that victims are blameless when they experience sexual violence.
Interacting with Physically Based Character Using Real Time Motion Capture with Kinect Sensor
Venue: 2016 XVIII Symposium on Virtual and Augmented Reality (SVR)

The use of animated characters is one of themain factors of success for games and simulators. Characters that react to the environment around them provide greater immersion to the user. Another way to improve the user's immersion is providing greater control over the character. Inthis work, we create a physically simulated character based onthe characteristics of the user. Thus, the character used in the simulation becomes unique, with their advantages and physical limitations. We use a Kinect Sensor in order to capture theuser's motion, along with the physical simulation library Open Dynamics Engine, responsible for creating the bodies thatcompose the character and considering the necessary torques and forces, calculated through PD (Proportional Derivative) controllers. Once created the character, it is inserted into aninteractive scenario, previously configured to analyse user's interaction.
mTORC2 sustains thermogenesis via Akt induced glucose uptake and glycolysis in brown adipose tissue
Venue: EMBO molecular medicine

Activation of non shivering thermogenesis (NST) in brown adipose tissue (BAT) has been proposed as an anti obesity treatment. Moreover, cold induced glucose uptake could normalize blood glucose levels in insulin resistant patients. It is therefore important to identify novel regulators of NST and cold induced glucose uptake. Mammalian target of rapamycin complex 2 (mTORC2) mediates insulin stimulated glucose uptake in metabolic tissues, but its role in NST is unknown. We show that mTORC2 is activated in brown adipocytes upon b adrenergic stimulation. Furthermore, mice lacking mTORC2 specifically in adipose tissue (AdRiKO mice) are hypothermic, display increased sensitivity to cold, and show impaired cold induced glucose uptake and glycolysis. Restoration of glucose uptake in BAT by overexpression of hexokinase II or activated Akt2 was sufficient to increase body temperature and improve cold tolerance in AdRiKO mice. Thus, mTORC2 in BAT mediates temperature homeostasis via regulation of cold induced glucose uptake. Our findings demonstrate the importance of glucose metabolism in temperature regulation.
Combining learning with fuzzing for software deobfuscation

Software obfuscation is widely applied to prevent reverse engineering of applications. However, to evaluate security and validate behaviour we are interested in analysis such software. In this thesis, we give an overview of available obfuscation techniques as well as methods to undo this effort through reverse engineering and deobfuscation. We research active learning, which can be used to automatically learn state machine models of obfuscated software. These state machine models give insight into the behaviour of the program. We identify opportunities to improve the quality of existing active learning algorithms through the use of fuzzing to generate test cases. We utilise the AFL fuzzer, which uses a genetic algorithm in combination with test case mutation to create test cases for a target program. By using insight into the program's execution for each test case, it can create more relevant test cases compared to implementations that do not use this information. We use the generated test cases to find counterexamples for learned state machine models; these counterexamples can then be used by the learning algorithm to significantly improve the quality of the learned model. Compared to active learning with the W method for test case generation, our combination of learning and fuzzing learns models of obfuscated programs with up to 343x more states, and consequently incorporates more of the program's behaviour into the learned state machine model.
Understanding the non solvent induced phase separation (NIPS) effect during the fabrication of microporous PVDF membranes via thermally induced phase separation (TIPS)

The thermally induced phase separation (TIPS) method is regaining momentum as a competitive platform to fabricate highly porous microporous membranes. In membrane technology, there has been an active search for more sustainable ways to fabricate polymeric membranes using green solvents. Rhodiasolv PolarClean(r) is a recently identified environmentally friendly TIPS solvent that shows high potential for the preparation of microporous PVDF membranes. Interestingly, its high miscibility with water induces a nonsolvent induced phase separation (NIPS) effect on the membrane surface and this simultaneous NIPS TIPS effect is referred to as the combined NIPS TIPS (N TIPS) method. In this work, a thorough investigation was carried out to understand the underlying phenomena in the membrane formation kinetics during the N TIPS process. It was found that the NIPS and TIPS morphology can be tailored to control the mechanical properties, pore size distribution, and flux of the prepared membranes. For instance, increasing the coagulation bath solvent concentration facilitated the formation of a spherulitic morphology, whereas increasing the bath temperature induced the formation of a bicontinuous morphology free of macrovoids. It was determined that by controlling the phase separation kinetics, the mechanical properties of the prepared PVDF membranes could be remarkably improved from 0.9 MPa to 6.1 MPa. Several pore forming additives including polyvinylpyrrolidone, Pluronics F 127, LiCl, and glycerol were employed to induce surface pores and their effects were thoroughly characterized. The membranes prepared with Pluronic additives exhibited high water permeabilities up to 2800 L m 2 h 1 bar 1 with narrow pore size distributions.
Association between targeted somatic mutation (TSM) signatures and HGS OvCa progression
Venue: Cancer medicine

Evidence already exists that the activation induced cytidine deaminase (AID/APOBEC) and the adenosine deaminase (ADAR) families of enzymes are implicated as powerful mutagens in oncogenic processes in many somatic tissues. Each deaminase is identified by the DNA or RNA nucleotide sequence "motif" surrounding the nucleotide targeted for deamination. The primary objective of this study is to develop an in silico approach to identify nucleotide sequence changes of the target motifs of key deaminases during oncogenesis. If successful, a secondary objective is to investigate if such changes are associated with disease progression indicators that include disease stage and progression free survival time. Using a discovery cohort of 194 high grade serous ovarian adenocarcinoma (HGS OvCa) exomes, the results confirm the ability of the novel in silico approach used to identify changes in the preferred target motifs for AID, APOBEC3G, APOBEC3B, and ADAR1 during oncogenesis. Using this approach, a set of new cancer progression associated signatures (C PASs) were identified. Furthermore, it was found that the C PAS identified can be used to differentiate between the cohort of patients that remained progression free for longer than 60 months, from those in which disease progressed within 60 months (sensitivity 95% specificity 90% The spectrum of outcomes observed here could provide a foundation for future clinical assessment of susceptibility variants in ovarian, and several other cancers as disease progresses. The ability of the in silico methodology used to identify changes in deaminase motifs during oncogenesis also suggests new links between immune system function and tumorigenesis.
Online incremental higher order partial least squares regression for fast reconstruction of motion trajectories from tensor streams
Venue: 2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

The higher order partial least squares (HOPLS) is considered as the state of the art tensor variate regression modeling for predicting a tensor response from a tensor input. However, the standard HOPLS can quickly become computationally prohibitive or merely impossible, especially when huge and time evolving tensorial streams arrive over time in dynamic application environments. In this paper, we present a computationally efficient online tensor regression algorithm, namely incremental higher order partial least squares (IHOPLS) for adapting HOPLS to the setting of infinite time dependent tensor streams. By incrementally clustering the projected latent variables in latent space and summarizing the previous data, IHOPLS is able to recursively update the projection matrices and core tensors over time, resulting in greatly reduced costs in terms of both memory and running time while maintaining high prediction accuracy. To show the effectiveness and scalability of our approach for large databases, we apply IHOPLS to two real life applications as reconstruction of 3D motion trajectories from video and ECoG streaming signals.