Miracle-dz/UniFAR-FTUs huggingface dataset:
Tunneling magnetoresistance materials and devices for neuromorphic computing

Artificial intelligence has become indispensable in modern life, but its energy consumption has become a significant concern due to its huge storage and computational demands. Artificial intelligence algorithms are mainly based on deep learning algorithms, relying on the backpropagation of convolutional neural networks or binary neural networks. While these algorithms aim to simulate the learning process of the human brain, their low bio-fidelity and the separation of storage and computing units lead to significant energy consumption. The human brain is a remarkable computing machine with extraordinary capabilities for recognizing and processing complex information while consuming very low power. Tunneling magnetoresistance (TMR)-based devices, namely magnetic tunnel junctions (MTJs), have great advantages in simulating the behavior of biological synapses and neurons. This is not only because MTJs can simulate biological behavior such as spike-timing dependence plasticity and leaky integrate-fire, but also because MTJs have intrinsic stochastic and oscillatory properties. These characteristics improve MTJs’ bio-fidelity and reduce their power consumption. MTJs also possess advantages such as ultrafast dynamics and non-volatile properties, making them widely utilized in the field of neuromorphic computing in recent years. We conducted a comprehensive review of the development history and underlying principles of TMR, including a detailed introduction to the material and magnetic properties of MTJs and their temperature dependence. We also explored various writing methods of MTJs and their potential applications. Furthermore, we provided a thorough analysis of the characteristics and potential applications of different types of MTJs for neuromorphic computing. TMR-based devices have demonstrated promising potential for broad application in neuromorphic computing, particularly in the development of spiking neural networks. Their ability to perform on-chip learning with ultra-low power consumption makes them an exciting prospect for future advances in the era of the internet of things.
Structuring the Individual Plan of Professional Development (IPPD) For Teachers in the Advancement of Career Demand Growth

This research assessed the implementation of the Individual Plan of Professional Development (IPPD) towards career demand growth for secondary public-school teachers in South District 7 at Cebu City Division, Cebu City school year 2021-2022 as bases for a developmental action plan. Findings of this study reveal that the school heads and teacher-respondents belong to the age group of 31-40 years old, female, married, obtained units in their master’s degree, have been linked with the institution for more than 6 years, have a performance rating of very satisfactory, and attended national trainings, seminars, and workshops. Looking into the extent of implementation of the individual plan of professional development (IPPD) which is divided into five indicators – professional development in school; learning through professional development; participation experience in IPPD; impact on learners; and attitude and beliefs, accumulated an overall grand mean of 4.27, which means that the respondents strongly agree that the extent of implementation of the IPPD across all indicators increases their career demand growth
Liquid Crystalline Blue Phases and Swimmer Hydrodynamics

Soft condensed matter is concerned with the wide variety of materials, ranging from polymers to foams, that are neither crystalline, nor gaseous, but lie somewhere in between. In this thesis, we shall describe two such “soft” systems: liquid crystalline blue phases and the hydrodynamics of microscopic swimming creatures. Blue phases epitomise the term liquid crystal, possessing three-dimensional crystalline orientational order whilst maintaining full fluidity. We describe some of their unique properties and the subtle balance between local order and topology that is responsible for their stability. The application of an electric field leads to both a distortion of the blue phase and to textural transitions, both of which we simulate numerically in good agreement with experiments, reproducing the blue phase X transition observed in the 1980s, but not identified theoretically. Finally, we show that blue phases extend beyond their traditional chiral setting and also occur in achiral nematics under strong flexoelectric coupling. At the small length scales relevant to microscopic bacteria viscous stresses dominates over the effects of inertia and propulsion is achieved by quite different means to macroscopic organisms. We describe in detail the hydrodynamics of a simple model linked-sphere swimmer, with an emphasis on the interactions between swimmers. Time reversal symmetry is important, constraining both the locomotion of individuals and the nature of their interactions. We take this up with two examples: the hydrodynamic scattering of two swimmers, related to each other by time reversal, is shown to itself be time reversal covariant; the initial configuration being recovered exactly in the final state. Finally, a model of simple dumb-bells is described. Each swimmer is time reversal invariant and does not swim, but collective locomotion is still possible through hydrodynamic interactions, leading to a minimal description of active apolar fluids.
Psychological Resilience and Suicidal Thoughts in Bipolar Disorders Patients

Background: Bipolar disorder is a serious mental illness associated with an increased risk of suicidal thoughts and behaviour. Resilience, or the ability to adapt and manage stress and adversity, maybe a major factor in lowering this risk and improving outcomes for people with bipolar disorder. Aim: The current study aimed to assess the relationship between psychological resilience and suicidal thoughts in bipolar disorder patients. Design: A descriptive correlational design was adopted in the present study. setting: The research was carried out in the "Psychiatric Medicine and Addiction Prevention Hospital—Cairo University Hospitals" inpatient and outpatient departments. Sample: A purposive sample of 50 male and female bipolar illness patients selected for this investigation. Tools : A structured interview sheet collecting socio-demographic and medical information, the Connor-Davidson Resilience Scale, and the Morey Suicidal Ideation Scale were used to collect data. Results : The results showed that (46.60%) of the bipolar patients tested had a low degree of resilience, (42.20%) had a moderate level of resilience, and only a small fraction (11.2%) had a high level of resilience. Suicidal thoughts were present in 66.60% and 33.40% of studied bipolar patients, respectively. In bipolar disorder patients, there is no statistically significant relationship between psychological resilience and suicidal thoughts. In order to build resilience and reduce the risk of suicide thoughts and behaviours in bipolar patients, a complete approach that treats both the medical and emotional elements of the condition is required. Recommendation : A patient education programme is necessary: Nurses can educate patients on the value of resilience and self-care in the management of bipolar disease, as well as providing information on coping techniques and self-care practises that patients can use to improve their well-being.
Water absorption, thickness swelling and mechanical properties of cement bonded wood composite treated with water repellent

In this study, the purpose was to improve outdoor performance of cement bonded wood composite due to their biodegradation and sensitivity to moisture especially in warm and humid climates. Cement bonded wood composites were treated with different concentrations (10 %, 25 %, 50 %, 75 % and 100 %) of water repe - llent. Water repellent used was an organo-silicon based, nano-sized, eco-friendly, water-based agents. Dipping and pressure systems were applied for composite treatment. Water absorption, thickness swelling, accelerated weathering, color changes and mechanical properties after accelerated weathering were determined for treated and untreated cement-bonded composites. Results showed that treatment of composites with water repellent provided a transparent layer on composite surface. Thus, lower water absorption and thickness swelling results in the beginning of immersion in water. Treated and untreated composites were exposed to an accelerated weathering test for 350 h. Their mechanical strength including modulus of rupture, modulus of elasticity and internal bonding properties were decreased after 350 h of weathering. However, overall results after weathe-ring test showed that all panels’ mechanical properties provided minimum modulus of rupture, modulus of elasticity and internal bonding requirements of the EN standards.
Oxygen Availability on the Application of Antimicrobial Photodynamic Therapy against Multi-Species Biofilms

Methylene blue (MB)- or Curcumin (Cur)-based photodynamic therapy (PDT) has been used as an adjunctive treatment for periodontitis. Its actual clinical efficacy is still in question because the lack of oxygen in a deep periodontal pocket might reduce the PDT efficacy. We aim to investigate the effect of oxygen on PDT efficacy and to examine if the addition of hydrogen peroxide (HP) could improve PDT performance anaerobically. To this end, we cultured 48 h saliva-derived multi-species biofilms and treated the biofilms with 25 µM MB or 40 µM Cur, HP (0.001%, 0.01% and 0.1%), light (L-450 nm or L-660 nm), or combinations thereof under ambient air or strictly anaerobic conditions. MB- and Cur-PDTs significantly reduced biofilm viability in air but not under anaerobic conditions. HP at 0.1% significantly enhanced the killing efficacies of both MB- and Cur-PDTs anaerobically. The killing efficacy of Cur-PDT combined with 0.1% HP was higher anaerobically than in air. However, this was not the case for MB-PDT combined with 0.1% HP. In conclusion, this study demonstrated that the biofilm killing efficacies of MB- and Cur-PDTs diminished when there was no oxygen. HP at 0.1% can enhance the efficacy of PDT performed anaerobically, but the level of enhancement is photosensitizer-dependent.
On multipartite invariant states

We propose a natural generalization of bipartite Werner and isotropic states to multipartite systems consisting of an arbitrary even number of d-dimensional subsystems (qudits). These generalized states are invariant under the action of local unitary operations. We study basic properties of multipartite invariant states: separability criteria and multi-PPT conditions.
Sustainable socio-ecological transformations in agriculture: cases from South Asia

ABSTRACT Climate change is becoming a defining factor for communities in South Asia. Forming one-fifth of the world population, the region increasingly faces climate-induced disasters such as floods, droughts, heatwaves, cyclones etc. This region also has one of the world’s poorest people who struggle to cope with the rapidly changing climatic conditions. Agriculture still employs many people in the region, one of the worst-hit sectors. Agriculture will become untenable in some parts of the region due to climate change. Monsoon patterns have changed, and agriculture does not guarantee sustainable income for the vast majority. Many climate change adaptations have been initiated in the region in response to the threat of climate change. Scholars and practitioners feel that these adaptations must be transformative to be effective. In this paper, we examine eight such adaptations from three South Asian Countries – Bangladesh, India, and Nepal, from the lens of transformative adaptation. We found that no single adaptation initiative meets all the criteria for sustainable socio-ecological transformations. However, there is a significant overlap between different typologies of transformation as envisaged in the paper and literature. We conclude that the concept of socio-ecological transformation is new for South Asia, so integrating it into the programmes and policies is the need of the hour.
Poseidon-NDP: Practical Fully Homomorphic Encryption Accelerator Based on Near Data Processing Architecture

With the development of the important solution for privacy computing—fully homomorphic encryption (FHE), the explosion of data size, and computing intensity in FHE applications brings enormous challenges to the hardware design. In this article, we propose a novel co-design scheme for FHE acceleration named “Poseidon-NDP,” which focuses on improving the efficiency of the hardware resource and the bandwidth. Specifically, we investigate the special implications of the hardware imposed by the FHE applications. It empirically shows that the FHE performance is suffered from both the intractable data movement and the computation bottleneck. Besides, we also introduce the opportunity and the challenges of accelerating FHE on near data processing (NDP) architecture. Based on such analysis, we propose an optimized technique called “NTT-fusion” to simplify the FHE operator and reduce its hardware overhead. Then, we design the accelerator based on the simplified operator to achieve maximized data and computation parallelism with limited hardware resources. Additionally, we evaluate Poseidon-NDP with 4 domain-specific FHE applications on the SmartSSD, which is a practical NDP device. The empirical studies show that the efficient co-design enables Poseidon-NDP vastly superior to the state-of-the-art FHE acceleration techniques: 1) up to <inline-formula> <tex-math notation="LaTeX">$217\times /84\times $ </tex-math></inline-formula> speedup over CPU and high-performance GPUs for the number theoretic transform; 2) up to <inline-formula> <tex-math notation="LaTeX">$3.7\times /29\times $ </tex-math></inline-formula> higher-speedup/energy delay product (EDP) over the SOTA FPGA accelerator for the FHE applications; and 3) up to <inline-formula> <tex-math notation="LaTeX">$4.9\times $ </tex-math></inline-formula> higher-bandwidth utilization over CPU due to the NDP-based architecture.
A new approach for the optimal control of time-varying delay systems with external persistent matched disturbances

The aim of this study is to develop an efficient iterative approach for solving a class of time-delay optimal control problems with time-varying delay and external persistent disturbances. By using the internal model principle, the original time-delay model with disturbance is first converted into an augmented system without any disturbance. Then, we select a quadratic performance index for the augmented system to form an undisturbed time-delay optimal control problem. The necessary optimality conditions are then derived in terms of a two-point boundary value problem involving advance and delay arguments. Finally, a fast iterative algorithm is designed for the latter advance-delay boundary value problem. The convergence of the new iterative technique is also investigated. Numerical simulations verify that the proposed approach is efficient and provides satisfactory results.
Trusted Execution Environment TEE: Research and Prospect

Trusted Execution Environment (TEE) technologies are widely developed in the current computer systems along with the user’s serious concerns about privacy protection, secure computing, etc. in network services. Generally, TEEs provide an isolated execution environment for the managers and users for privacy and confidential computing even if the underlying OSes are compromised. To build the TEEs, the device manufacturers like Intel, Arm update the hardware foundation by adding the external Processor Mode, memory control, cryptography engine, etc. In addition, they provide corresponding interfaces in the system following the application requirements. Except that, researchers further design compatible TEE models for various goals with the above hardware or firmware assistance. This paper comprehensively analyzes the technical characteristics of TEE technology in mainstream system architecture (including x86, Arm, RISC-V, Heterogeneous computing unit), including infrastructure and hardware facilities design, software interface definition, security boundary, etc., and explores the feasible application scenarios of TEE technology. At the same time, we analyze the challenges of current TEE technologies and discuss the limitations and the security risks, e
Knowledge, Belief, Probabilities, Updates, Model Checking

The talk will present epistemic probability models with probabilistic updates, and will discuss an implementation that allows model checking the results of updates in a multi-agent setting. I will also try to convey the attractions of functional programming. How are Logic and Probability Theory Related? • Logic = Reasoning about Certainty • Probability Theory = Reasoning about Uncertainty • Wikipedia defines Epistemic or Bayesian probability as “. an extension of propositional logic that enables reasoning with hypotheses, i.e., the propositions whose truth or falsity is uncertain. ” • But logic has something to say, too, about reasoning under uncertainty: epistemic logic, doxastic logic, default logic, . • How are all these enterprises related? The Usefulness of Probability Theory
of Telemedicine Diabestie Application Usage Attitude on Ease of Use

Indonesia is ranked seventh in the world for the most smartphone users, supported by changes in the modern era where technology is increasingly sophisticated, thus having an impact on daily activities. One of them is the use of telemedicine applications. Diabestie is one of the telemedicine services that provides online health consultations focusing on diabetes, where diabetes in Indonesia is considered a major health problem with more than 10 million people living with diabetes. There are still those who think telemedicine services are difficult to operate, so this research was conducted to find out the influence of ease and usability of use on the attitudes of Diabestie application users. The findings revealed that ease of use and usability of use influence attitudes toward use. In other words, perceived usability and ease of use are important for people to determine their attitude towards Diabestie's telemedicine app services. Furthermore, people will tend to adopt a service when they find that it is useful and easy to use.
Digital forensic techniques for static analysis of NTFS images

Static analysis of the Windows NT File System (NTFS) which is the standard and most commonly used file system could provide useful information for digital forensics. However, since the NTFS disk image records every event in the system, forensic tools need to process an enormous amount of information related to user / kernel environment, buffer overflows, trace conditions, network stack and other related subsystems. This leads to imperfect forensic tools that are practical for implementation but not comprehensive and effective. This research discusses the analysis technique to detect data hidden based on the internal structure of the NTFS file system in the boot sector. Further, it attempts to unearth the vulnerabilities of NTFS disk image and the weaknesses of the current forensic techniques. This paper argues that a comprehensive tool with improved techniques is warranted for a successful forensic analysis.
S UPPLEMENTARY M ATERIAL : N EURAL E PDO S : S PA - TIALLY A DAPTIVE E QUIVARIANT P ARTIAL D IFFEREN - TIAL O PERATOR B ASED N ETWORKS

Regular Representation It is a group representation commonly used for discrete groups. It acts on a vector space R|G| by permuting its axes. If we associate every axis with a group element, then the action ρreg(g) of regular representation permutes the axis associated with g1 to the axis associated with gg1. Specifically, the matrix form of ρreg(g) is ρ G reg(g)gi,gj = δgi,gjg 1, where gi, gj , gjg ∈ G denote the corresponding axes. Feature maps with regular representations as transformation type are called regular fields.
SAR target recognition using parametric supervised t-stochastic neighbor embedding

ABSTRACT This paper proposes a new method for feature extraction of synthetic aperture radar (SAR) image based on parametric supervised t-stochastic neighbor embedding (PS-tSNE). To mitigate the rejection of dissimilar targets from the same class, aspect angles of targets are modeled to supervise and construct the distributional properties of the training data in the original space. Then, an explicit nonlinear mapping using kernel trick is proposed by an extension of non-parametric t-SNE supervised by the information of aspect angles. This method preserves the local structure of the targets of SAR images as well as possible and enables explicit out-of-sample extensions. Experimental results based on moving and stationary target automatic recognition (MSTAR) dataset illustrate the effective performance of the proposed method on visualization and recognition.
Feature Map Variational Auto-Encoders

There have been multiple attempts with variational auto-encoders (VAE) to learn powerful global representations of complex data using a combination of latent stochastic variables and an autoregressive model over the dimensions of the data. However, for the most challenging natural image tasks the purely autoregressive model with stochastic variables still outperform the combined stochastic autoregressive models. In this paper, we present simple additions to the VAE framework that generalize to natural images by embedding spatial information in the stochastic layers. We significantly improve the state-of-the-art results on MNIST, OMNIGLOT, CIFAR10 and ImageNet when the feature map parameterization of the stochastic variables are combined with the autoregressive PixelCNN approach. Interestingly, we also observe close to state-of-the-art results without the autoregressive part. This opens the possibility for high quality image generation with only one forward-pass.
Liquid Vapor Phase Transitions: Modeling, Riemann Solvers and Computation

The numerical approximation of liquid vapor flows within the compressible regime is a challenging task because complex physical effects at the phase interfaces govern the global flow behavior. We develop a sharp interface approach which treats the phase boundary like a shock wave discontinuity and takes capillarity effects into account. The approach relies on the solution of Riemann problems across the interface that separates the liquid and the vapor phase. The Riemann solution accounts for the relevant physics by enforcing appropriate jump conditions at the phase boundary. A wide variety of interface effects can be handled in a thermodynamically consistent way. This includes surface tension, as well as, mass and energy transfer by phase transition. Moreover, the local normal speed of the interface, which is needed to calculate the time evolution of the phase boundary, is given by the Riemann solution. The focus of this work is the development of isothermal and non-isothermal two-phase Riemann solvers for the sharp interface approach. To verify the solvers with respect to numerical and thermodynamic requirements, one-dimensional and radially symmetric problems are studied. Furthermore, the Riemann solvers and the sharp interface approach are successfully validated against shock tube experiments of real fluids (alkanes).