Miracle-dz/UniFAR-FTUs huggingface dataset:
Professional development of physics teachers through long-term in-service programs: the Israeli experience

New approaches to the teaching of physics, influenced by insights of research on learning and teaching, require teachers to extend their existing practices as well as undergo fundamental changes in their views about learning goals, teaching/learning methods, and their role in the classroom. Teachers need not only a thorough understanding of the subject matter, but also knowledge about learning processes and students’ reasoning; how to relate to students’ ideas in their teaching and how to create student-centered learning environments. Since learning is a slow process, it is essential to allow time for teachers to learn in a meaningful way. The real context of teaching and on-going guidance are important ingredients in programs that would allow teachers to change their existing practices. These conditions are not met neither by short-term in service courses, nor by pre-service programs. Long-terms in-service programs as a part of an on-going long-life professional development, are necessary. We outline a f.
Local model interpolation for stable haptic interaction

Haptic, or force, interaction in virtual environments can support the development of physical manipulation skills if users feel realistic forces in response to their motion in the virtual environment. The realism of the forces felt by users depends on: (i) how accurately the virtual environment simulates a real life situation such as surgery; and (ii) how faithfully the haptic controller renders the simulated interactions to users. Accurate simulations of real life situations such as surgery run at variable frequencies of the order of 20 − 100 Hz. However, the haptic controller needs updated stiffness and direction of contact at 1000 Hz to faithfully convey the shape and hardness of the virtual objects to the user. This thesis proposes to bridge the gap between the required fast haptic control rate and the slower virtual environment updates through a passive local model of interaction. This model comprises an approximation of the shape and stiffness of the virtual world in the area near the point of interaction. It also monitors its exchange of energy with the user to ensure its own passivity and thus, the stability of the haptic system. Lastly, the local model eliminates the spurious discontinuities that arise in contact direction at model updates by interpolating the contact normal before rendering it to the user.
Paper de la placofilina-2 en la miocardiopatia aritmogènica de ventricle dret: bases genètiques i mecanismes moleculars

La mort sobtada cardiaca (MSC) es defineix com una mort natural, repentina i d’origen cardiac que succeeix durant la primera hora des de l’inici dels simptomes fins el seu desenllac final. La MSC es la manifestacio mes temuda dins de les malalties cardiaques ja que frequentment es el primer simptoma de la patologia. La MSC presenta una incidencia d’entre 50-100 en 100.000 individus en la poblacio general, i es consequencia de diferents tipus de cardiopaties. Dins del gran ventall de cardiopaties trobem la Miocardiopatia Aritmogenica de Ventricle Dret (MAVD). La MAVD es una cardiopatia que es caracteritza per la substitucio de part del muscul cardiac del ventricle dret, esquerra o d’ambdos per de teixit fibros i/o greixos que indueix una alteracio de la transmissio electrica a traves de les fibres del cor. Aixo provoca aritmies i un registre caracteristic en l’ electrocardiograma. Aquesta miocardiopatia afecta especialment als joves esportistes, i s’estima que es responsable d’un 5% del total de les MSC. La causa es genetica, i sol ser deguda principalment a alteracions del gen PKP2 el qual codifica per una proteina del desmosoma del miocit, la placofilina-2. Al ser una patologia genetica, cal fer estudis clinics i genetics als familiars ja que tambe poden estar a risc de patir una MSC. Tot i els gran avencos que s’han produit en els darrers anys, el diagnostic clinic es encara complex i els mecanismes que la desencadenen son encara molt desconeguts. Aquesta tesi es planteja com a objectiu aprofundir en el coneixement de les bases genetiques i dels mecanismes moleculars implicats de la MAVD. Els resultats aporten nous coneixements en tres ambits: la predisposicio genetica, les alteracions que es produeixen en el teixit afectat i els mecanismes moleculars que n’estan implicats. Concretament, es determina que les variants genetiques mes comunes son les que afecten al gen de la placofilina-2 i, a mes, que les variants d’aturada que indueixen el truncament d’aquesta proteina estan associades a una edat de diagnostic major. D’altra banda, tambe s’han identificat la deficiencia d’una altra proteina del desmosoma cardiac (placoglobina) en el teixit afectat, suggerint-ho com a eina diagnostica. Tots els resultats obtinguts permeten millorar el coneixement de la MAVD, aixi com ajudar a la millora dels actuals protocols de diagnostic i tractament de les families afectades per la patologia.
Benchmarking the suitability of key-value stores for distributed scientific data

This dissertation is going to explore the suitability for a key-value store to be utilized in a scientific environment. In the dissertation, we present a benchmark approach to evaluate the performance of a key-value store based on CAP (consistency, availability and partition tolerance) theorem, then explore the suitability when a scientific application needs to use a key-value store. With development of Internet technology, there is a trend that more and more data is generated for scientific research which leads to the demand of partitioning data across multiply nodes. However, the performance of relational database drops because of its data complexity. As a result, this dissertation will investigate the suitability of two key-value stores, Redis and Voldemort, by benchmarking it consistency and availability with different configuration (node number/dataset size). The result of benchmarking shows that Redis scales with the size of datasets but not number of nodes while Voldemort scales with the number of nodes but not size of datasets regarding consistency. The availability of Redis is better than Voldemort but both and Redis and Voldemort reduce its availability with more datasets. In addition, Voldemort shows a possibility that adding more nodes to Voldemort system may increase its availability. Furthermore, due to the client issues for both two data stores partition tolerance may not be evaluated currently. Finally, with an analysis of demanding scientific application, we conclude that both Voldemort and Redis could be suitable for a scientific application with dependence on the requirement of scientific application.
Gender Transition Services for Hijras and Other Male-to-Female Transgender People in India: Availability and Barriers to Access and Use

ABSTRACT. This qualitative investigation explored access to and use of gender transition services by hijras and other male-to-female transgender people in the public and private hospitals in 7 Indian cities. We conducted 7 focus groups (n = 42 participants) and 30 in-depth interviews with a purposive sample of hijras/transpeople and 22 key informant interviews with service providers. Findings reveal a near-absence of gender transition services in public hospitals. Lack of free sex reassignment surgery (SRS) in public hospitals and the prohibitive cost of SRS in private hospitals seem to be the key reasons behind why some hijras/transpeople go to unqualified medical practitioners for surgery or undergo Dai Nirvan, a traditional but risky method of removing male genitalia practiced within the hijra communities. Similarly, unwillingness among qualified medical practitioners to prescribe hormone therapy compels many hijras/transpeople to self-administer hormones. The lack of national guidelines on gender transition services and ambiguous legal status of SRS mean that even qualified medical practitioners are hesitant to perform SRS. Findings highlight the need to provide free or affordable gender transition services in public hospitals, to develop national guidelines on gender transition, and to equip health care providers to provide technically and culturally competent gender transition services.
Binary Code Reuse Detection for Reverse Engineering and Malware Analysis

Code reuse detection is a key technique in reverse engineering. However, existing source code similarity comparison techniques are not applicable to binary code. Moreover, compilers have made this problem even more difficult due to the fact that different assembly code and control flow structures can be generated by the compilers even when implementing the same functionality. To address this problem, we present a fuzzy matching approach to compare two functions. We first obtain our initial mapping between basic blocks by leveraging the concept of longest common subsequence on the basic block level and execution path level. Then, we extend the achieved mapping using neighborhood exploration. To make our approach applicable to large data sets, we designed an effective filtering process using Minhashing and locality-sensitive hashing. Based on the approach proposed in this thesis, we implemented a tool named BinSequence. We conducted extensive experiments to test BinSequence in terms of performance, accuracy, and scalability. Our results suggest that, given a large assembly code repository with millions of functions, BinSequence is efficient and can attain high quality similarity ranking of assembly functions with an accuracy above 90% within seconds. We also present several practical use cases including patch analysis, malware analysis, and bug search. In the use case for patch analysis, we utilized BinSequence to compare the unpatched and patched versions of the same binary, to reveal the vulnerability information and the details of the patch. For this use case, a Windows system driver (HTTP.sys) which contains a recently published critical vulnerability is used. For the malware analysis use case, we utilized BinSequence to identify reused components or already analyzed parts in malware so that the human analyst can focus on those new functionality to save time and effort. In this use case, two infamous malware, Zeus and Citadel, are analyzed. Finally, in the bug search use case, we utilized BinSequence to identify vulnerable functions in software caused by copying and pasting or sharing buggy source code. In this case, we succeeded in using BinSequence to identify a bug from Firefox. Together, these use cases demonstrate that our tool is both efficient and effective when applied to real-world scenarios. We also compared BinSequence with three state of the art tools: Diaphora, PatchDiff2 and BinDiff. Experiment results show that BinSequence can achieve the best accuracy when compared with these tools.
Face Inpainting with Dilated Skip Architecture and Multi-Scale Adversarial Networks

Recent researches in neural network models have shown great potential in image inpainting task, which focus on finding reasonable area from known content to predict missing pixel values of incomplete image and generate new images. However they still create distorted structures and textures that are inconsistent with surrounding areas and require further post processing to optimize the results. Especially for face repair problems, it is often necessary to generate semantically new images that contain a large number of appearance. In addition, many recent approaches limited their applications in the field center region inpainting, which have difficulties to repair border regions or large missing area. Motivated by these observations, we introduce dilated skip architecture, which combines the advantages of dilated convolution and U-net. With this combination, our proposed network can enlarge the perception area for better repairing, as well as preserve the completeness of the original image features during the repairing process. Experiments on CelebA show that our approach can effectively deal with image inpainting problems and obtain images with higher qualities than previous ones.
Transformation through visual art: a case study in an African village living with HIV/AIDS

This research is an ethnographic case study that asks the questions “what is transformation? ” and “how does art transform individuals and their communities? ” The narrative describes key moments in the researcher’s journey to South Africa in search of answers to these questions. Findings describe the village of Hamburg’s developing art practice, and include the artists’ own voices and views on this topic. Hamburg is a Xhosa village in South Africa that has faced many challenges due to the spread of HIV/AIDS. One response to the impact of HIV/AIDS on family and economic structures has been the development of an extensive community-based art practice, including large communal tapestry work. To engage questions regarding how visual art transforms people, the researcher reviewed existing Western and Eastern literature on transformation, and compared this with the Southern ethnographic interviews conducted whilst living in the village of Hamburg, where she joined the women for two months as they made their art. The interviews, which were informed by feminist thinking and community based action research, are deeply moving, and form the data from which conclusions were drawn. It
A signal power adaptive regularized sphere decoding algorithm based multiuser detection technique for underdetermined OFDM/SDMA uplink system

This work considers a regularized Fincke‐Pohst Sphere Decoder (R‐FSD) to detect the multiuser data of orthogonal frequency division multiplexing/space division multiple access (OFDM/SDMA) uplink system with underdetermined and rank‐deficient channel. Rank‐deficiency of the detected channel coefficients makes error‐free multiuser detection (MUD) a difficult task. In literature, most of the papers deal with either a determined or over‐determined full‐rank system. The method proposed in this work transforms an original ill‐posed least squares (LS) problem to a well‐posed one at the receiver, by using the standard Tikhonov regularization method. This is an efficient, direct, and less complex approach where the channel is modified using a regularization parameter that adapts to the signal power at the receiver. The result obtained is compared with maximum likelihood (ML), zero forcing (ZF), minimum mean squared error (MMSE) and ordered successive interference cancellation (OSIC) based detection techniques.
Ladar data generation fused with virtual targets and visualization for small drone detection system

For detection of a small target using electro-optical systems, multi-band 2D image sensors are used such as visible, NIR, MWIR, and LWIR. However, 2D imaging systems are not capable to detect a very small target and they are also not capable of calculating target 3D position coordinates to develop the strategic counter method. 3D sensors (e.g. Lidar, RGBD and stereo camera) are utilized to control unmanned vehicles for detecting threats and response for specific situations. Conventional Lidar systems are unable to detect small drone threat at distances higher than their maximum detecting range of 100 ∼ 120 meters. To overcome this limitation, laser radar (LADAR) systems are being developed, which allow the detection at distances up to 2 kilometers. In the development of LADAR, it is difficult to acquire datasets that contain cases of long distant targets. In this study, a fusion data generation with virtual targets technique based on minimum real LADAR initial map dataset is proposed, and precise small target detection method using voxel-based clustering and classification are studied. We present the process of data fusion generation and the experimental results for a small target detection. The presented approach also includes effective visualization of high-resolution 3D data and the results of small target detection in real time. This study is expected to contribute to the optimization of a drone threat detection system for various environments and characteristics.
Subcarrier selection for efficient CSI-based indoor localization

Indoor positioning systems have received increasing attention for supporting location-based services. In recent Wi-Fi networks, the rich information in the physical layer, known as channel state information (CSI), has been recognized an effective positioning characteristic rather than traditional received signal strength. However, the positioning performance depends on a very high-dimensional CSI due to all pairs of transceiver antenna, which may incur over-fitting problems. This paper proposes a subcarrier-selection approach based on information theoretic learning to compensate for over-fitting problems in CSI-based localization systems. After equalizing the histogram of CSIs, the proposed algorithm computes the information gain of each subcarrier and forms a new low-dimensional subset of CSIs to reduce the complexity and to decrease possible over-fitting caused by redundant CSIs. We demonstrate the effectiveness of the proposed algorithm through experiments. On-site experimental results demonstrate that the proposed approach outperforms traditional feature selection schemes.
Range Automata for Alphabetic Time Series Dimensionality Reduction

This paper presents a symbolic time series representation technique using range automata model with dimensionality reduction in large datasets. The proposed technique uses automata model to convert the numeric time series into sequence of symbols from which useful information can be extracted. The important task is to define the number of symbols required for time seriesrepresentation; to identify the cutoff value for each symbol and construct range automata for converting the numeric time series into symbolic one dynamically. The present work addresses the above issues by considering the amplitude range of the time series. The proposed method is validated by applyingit on the time series data of ECG, which proves it to be an effective method for time series representation. The performance of RATSR is compared with SAX for elapsed time for conversion and number of samples in reduced dimension.
Estimation of the absorbed dose to patients treated with 177Lu-Dotatate with regards to the long-term retention and radionuclide impurity in the form of 177mLu

The use of radio-labeled somatostatin analogs, such as 177Lu-labelled DOTATATE, in PRRT, has based on the studies performed until now, shown to be promising for RNT disseminated neuroendocrine tumors [1]. In this regard, the aim of treatment is to assure the delivery of the highest possible absorbed dose to the tumor cells, while saving the normal tissues [1], meaning, to achieve a higher activity uptake in tumors with neuroendocrine origin while assuring the lowest possible radio-toxicity in normal organs [2]. The key challenge associated with the absorbed dose distribution in the body upon administration of PRRT using 177Lu-DOTATATE is the absorbed dose to the kidneys, as being the dose limiting organs in PRRT [7]. The main excretion route of 177Lu-DOTATATE is through urine, where >65% of the total administered activity is excreted. This has lead us to investigate the long time retention of 177Lu in the total body, and also to estimate the absorbed dose given by possible radionuclide impurities. According to the declaration from the producer, a sample of 177Lu contains less than 0.05% of 177mLu. In order to investigate whether the 177mLu contribution to the absorbed dose is as low that it can be tolerated or even neglected, spectroscopy measurements have been performed on patients receiving therapy with 177Lu-DOTATATE at Skane University Hospital [15]. Prior to performing these measurements, the spectroscopy equipment has been carefully calibrated. The data obtained from patient measurements have been analyzed using different methods, and have been combined with imaging based data, obtained as part of the routine dosimetry performed at Skane University Hospital.
Designing and Implementing an ESP Course: Revisiting an Experience

This essay pretends to deep on how the process of making decisions in designing an ESP (English for Specific Purposes) course registered by three TESOL graduate students, structured by the author along with participants, a requirement of the Master of English Teaching for Speakers of Other Languages at University of Costa Rica (UCR). During the course the designers should help a group of UCR workers to communicate in English effectively with international students who want to study at UCR or those who were already participating in international programs. This study introduces data about the apprentices who benefit from this academic activity, tasks designed and taught, aswell as the evaluation and assessment used. Finally, it suggests some recommendations for those who may consider the option of designing an ESP course as an effective strategy to promote the use of the target language in a work context.
Using competency-based education to equip the primary health care workforce to manage chronic disease

Australia’s health system is under pressure from challenges posed by an ageing population, the increasing prevalence of chronic disease, increasing consumerism and new technologies. The health workforce itself compounds these challenges as it ages, and there remain shortages in key disciplines. Workforce shortages in the primary health care sector must be addressed for the health system to deliver good outcomes. Education and training are key components of strategies to address workforce shortages and to equip that workforce to meet future needs of chronic disease management in general practice settings.
Rate adaptive multicast video streaming over software defined network

Multicasting has always been a topic of importance when it comes to multiple receiving users. The participants are heterogeneous in terms of their capacity to process the video data and network technology. This capability difference affects the QoS and QoE of multicast video communication. In this work, we have developed a rate adaptive streaming mechanism to stream the video to meet the device and network constraints. The method uses SIP and SDP protocols to learn device constraints and link statistics to estimate the network resources. Later, this information is made available to the adaptation module to decide the video rate for streaming. We have implemented the method in the floodlight controller and streamed multiple rates of video over an SDN enabled network. The objective quality of the video is used for analysing the performance of the proposed adaptation technique
Entwurf und Realisierung eines haptischen Assistenzsystems für Herzkatheteruntersuchungen

Das Ziel dieser Arbeit ist daher der Entwurf und die Realisierung eines haptischen Assistenzsystems zur extrakorporalen Kraftdarstellung der endovaskularen Kontaktkrafte. In dieser Arbeit werden die Systemstrukturen von kraftgesteuerten und –geregelten haptischen Assistenzsystemen mit der Netzwerktheorie beschrieben. Ausgehend von einer kraftgeregelten Systemstruktur werden speziell angepasste Systemkomponenten fur das haptische Assistenzsystem entworfen. Zur Kraftdarstellung wird eine miniaturisierte haptische Bedieneinheit zur Krafteinkopplung auf den Fuhrungsdraht konzipiert und entworfen. Fur die Messung der auf den Kardiologen eingekoppelten haptischen Ruckmeldung wird ein extrakorporaler Kraftsensor entworfen. Die Messergebnisse zeigen, dass das entworfene und aufgebaute haptische Assistenzsystem Krafte bis 1 N mit einer Bandbreite von DC bis 135 Hz haptisch darstellen kann.