Miracle-dz/UniFAR-FTUs huggingface dataset:
Mechanical Modelling and Analysis of CMOS Image Sensor Package

The growth of automotive industry not only focus on power efficiency and carbon emission reduction, it also has makes further progress in the areas of advanced driver assistance systems (ADAS) and autonomous driving (AD) technologies. With the progressive technology breakthrough and heavily studies in these two areas, the demand for imaging cameras is steadily increasing to support applications such as lane detection, traffic sign detection, pedestrian/vehicle recognition and driver monitoring. Consequently, this drives higher demand for image sensor packages to meet stringent automotive reliability requirements. In the past, high reliability image sensor packages are typically with ceramic based packages, these tend to have considerably higher costs and longer development cycles than laminate-based packages which are normally used in high speed, RF or MEMS market segment. Therefore, it is important to ensure a high reliability for the laminate-based packages by studying the package design. This can be done by finite element analysis (FEA) which is a fast and cost-efficient method in analyzing the stress experienced by the package. This paper discusses the effects of different package designs on the package stress using the FEA simulation method.
A hybrid analog/digital Spike-Timing Dependent Plasticity learning circuit for neuromorphic VLSI multi-neuron architectures

To endow large scale VLSI networks of spiking neurons with learning abilities it is important to develop compact and low power circuits that implement synaptic plasticity mechanisms. In this paper we present an analog/digital Spike-Timing Dependent Plasticity (STDP) circuit that changes its internal state in a continuous analog way on short biologically plausible time scales and drives its weight to one of two possible bi-stable states on long time scales. We highlight the differences and improvements over previously proposed circuits and demonstrate the performance of the new circuit using data measured from a chip fabricated using a standard 180nm CMOS process. Finally we discuss the use of stochastic learning methods that can best exploit the properties of this circuit for implementing robust machine-learning algorithms.
The Malyugin Pupil Expander in Vitreoretinal Surgery

The Malyugin Pupil Expander in Vitreoretinal Surgery Safe and efficacious vitreoretinal surgery requires adequate visualization of the retina and vitreous. Poor visualization may result from inadequate mydriasis, for example secondary to posterior synechiae. Patients with diabetes and pseudoexfoliation are known to have iris atrophy.1,2 Surgical miosis related to prostaglandin production after iris manipulation is well recognized in cataract surgery, and it is likely to be relevant when there is manipulation of iris tissue, for example when intraocular lens explantation is performed. Solutions to deal with inadequate pupil size are broadly divided into pharmacologic and mechanical strategies. Preoperative nonsteroidal antiinflammatory agents can minimize surgically induced miosis.3 Subconjunctival and intracameral mydriatics, such as adrenaline, phenylephrine, and unpreserved lignocaine, may also be considered.3–7 Mechanical strategies include dividing posterior synechiae, sphincterotomy, pupil stretch, and the use of high-viscosity ophthalmic viscoelastic devices.8–12 The pupil may also be dilated using iris hooks or ring pupil dilators.8,13–16 We report a pilot study on the use of a new device for maintaining a large pupil in vitreoretinal surgery. This device is known as the Malyugin pupil expander, and it has been used for cataract surgery.17
Machine learning prediction of multiple anthelmintic resistance and gastrointestinal nematode control in sheep flocks

Abstract The high prevalence of Haemonchus contortus and its anthelmintic resistance have affected sheep production worldwide. Machine learning approaches are able to investigate the complex relationships among the factors involved in resistance. Classification trees were built to predict multidrug resistance from 36 management practices in 27 sheep flocks. Resistance to five anthelmintics was assessed using a fecal egg count reduction test (FECRT), and 20 flocks with FECRT < 80% for four or five anthelmintics were considered resistant. The data were randomly split into training (75%) and test (25%) sets, resampled 1,000 times, and the classification trees were generated for the training data. Of the 1,000 trees, 24 (2.4%) showed 100% accuracy, sensitivity, and specificity in predicting a flock as resistant or susceptible for the test data. Forage species was a split common to all 24 trees, and the most frequent trees (12/24) were split by forage species, grazing pasture area, and fecal examination. The farming system, Suffolk sheep breed, and anthelmintic choice criteria were practices highlighted in the other trees. These management practices can be used to predict the anthelmintic resistance status and guide measures for gastrointestinal nematode control in sheep flocks.
MR angiography of normal pelvic arteries: comparison of signal intensity and contrast-to-noise ratio for three different inflow techniques.

OBJECTIVE Two-dimensional (2D) time-of-flight (TOF) MR angiography has been the standard technique for evaluating arteries of the lower extremity. However, this technique is limited by artifacts resulting from vessel pulsation, as well as by relatively poor vessel-to-background contrast. The purpose of this study was to evaluate two cardiac-gated inflow techniques to determine whether they exhibited better contrast and signal performance than the standard technique of 2D TOF MR angiography of the iliac arteries. SUBJECTS AND METHODS Fourteen subjects who had no clinical evidence of vascular disease had standard 2D TOF, gated 2D TOF, and gated 2D turbo field-echo MR angiography. Images were evaluated for signal-intensity ratio, signal-to-noise ratio, and contrast-to-noise ratio, in addition to qualitative evaluation. RESULTS Turbo field-echo MR angiography exhibited significantly higher signal-intensity, signal-to-noise, and contrast-to-noise ratios than did either gated or standard MR angiography for all vessel segments. We found no significant difference between gated and standard 2D TOF techniques for any vessel segment. Qualitative features of turbo field-echo MR angiography included improved visualization of horizontal vessel segments compared with the standard 2D TOF technique, less effective venous saturation compared with either the gated or standard 2D TOF technique, and increased ghosting artifacts compared with the gated 2D TOF technique. CONCLUSION Two-dimensional turbo field-echo MR angiography exhibits improved signal and contrast for evaluation of normal iliac segments compared with standard or gated 2D TOF MR angiography. This technique should replace standard 2D TOF MR angiography for evaluation of the iliac arteries.
Formal grammars for estimating partition functions of double-stranded chain molecules

This paper looks at an algorithm due to Chen and Dill for estimating the partition functions of a restricted subclass of double-stranded polymers, and shows how it can be translated into a context-free grammar, so that their algorithm reduces to a variant of the CKY parsing algorithm. Our formulation clarifies the structure of Chen and Dill's algorithm, leading to revised complexity analyses and an optimization in one case, and lays a formal foundation for generalizing this method to more complex cases by the use of grammars beyond context-free power such as tree adjoining grammars.
Fluid Computing in the Internet of Things: A Digital Twin Approach

The concept of Fluid Computing entails a dynamic resource allocation approach, enabling seamless task migration between computing nodes. This paper investigates the fusion of Fluid Computing principles with the Internet of Things (IoT) and introduces the concept of Fluid Digital Twins (FDTs) i.e. cyber-physical entities that bridge the complexities of this integration. FDTs serve as intermediaries, overseeing fluid task migration, optimizing resource use, and simplifying interactions for external digital applications. The paper delves into challenges arising from this fusion, including limited IoT device capabilities, fragmentation, and the necessity of an intelligent intermediary layer. This research article models and presents FDT mechanics, features a prototype with experimental evaluation and concludes by discussing findings and potential future research directions.
Prevalence, severity and etiology of dental wear in patients with eating disorders

Objective: The purpose of this study was to evaluate the prevalence, distribution and associated factors of dental wear among patients with eating disorders (EDs). Materials and Methods: An epidemiological cross-sectional survey was conducted by trained, calibrated examiners, using the dental wear index. The sample was composed of 30 patients with EDs (experimental group - G1) and 30 control patients without current or previous history of EDs (G2). A questionnaire was used to assess the etiological factors of dental wear. The univariate analyses using the Chi-square (χ2 ) test were used to compare the tooth wear prevalence between groups according to the surface and tooth (P > 0.05). Results: The dental wear was similar for both group; however, the G1 presented more moderate wear in molars when compared with G2 (P = 0.048). The majority of EDs patients related have one or more oral habits (n = 26; 86.6%) and only 13.4% (n = 4) affirmed did not have oral habits. The etiological factors of tooth wear related with dental wear were biting objects (P = 0.04) and pain in temporomandibular disorders (P = 0.03). Conclusion: The highest prevalence of dental wear was observed in the molars teeth. Differences in the extent and pattern of dental wear were found in an individual, emphasized the relevance of clinical parameter.
Using Item Response Theory To Rate (Not Only) Programmers

We show how Item Response Theory (IRT) can be used to define a new type of rating system, one that is especially suitable for programming competitions (and other types of competitions where difficulty of competitions varies between rounds). We show some useful theoretical properties of this rating system, including the ability to argue about hardness of past competition tasks, and about the precision of contestants’ skill estimates. We also define an objective method of comparing different rating systems. In the final section of the paper we apply our methods on real competition data.
Cracking in spot welding aluminum alloy AA5754

The phenomenon of cracking was observed during resistance spot welding a commercial aluminum alloy AA5754, and mechanisms of cracking and healing are discussed in this paper Metallographic study of welded coupons revealed cracks located on only one side of a weldment in the heat-affected zone (HAZ), with respect to the welding sequence. Cracks are visible from longitudinal cross sections only. Some of them are partially or fully filled. Crack appearance and orientation are fairly repeatable and their intergranular characteristics and dendritic fracture surface morphology prove they were formed at elevated temperatures in the presence of liquid metal. The discussion of metallurgical factors considering the Al-Mg equilibrium phase diagram and the possible temperature histories of various zones in a weldment during spot welding elucidated the approximate conditions for cracking during spot welding and for mending the structure. A thermomechanical analysis revealed a high possibility for tensile stress huildup on the cracked side of the weldments as a result of material flow, thermal stress development and localized straining.
High Accuracy Attack Provenance via Binary-based Execution Partition

An important aspect of cyber attack forensics is to understand the provenance of suspicious events, as it discloses the root cause and ramifications of cyber attacks. Traditionally, this is done by analyzing audit log. However, the presence of long running programs makes a live process receiving a large volume of inputs and produce many outputs and each output may be causally related to all the preceding inputs, leading to dependence explosion and making attack investigations almost infeasible. We observe that a long running execution can be partitioned into individual units by monitoring the execution of the program’s event-handling loops, with each iteration corresponding to the processing of an independent input/request. We reverse engineer such loops from application binaries. We also reverse engineer instructions that could cause workflows between units. Detecting such a workflow is critical to disclosing causality between units. We then perform selective logging for unit boundaries and unit dependences. Our experiments show that our technique, called BEEP, has negligible runtime overhead (< 1.4%) and low space overhead (12.28% on average). It is effective in capturing the minimal causal graph for every attack case we have studied, without any dependence explosion.
Theoretical and numerical study of seismic tsunami dynamics

The impact of tsunamis on mankind is well known. During recent years, several events showed us the disasters they can trigger which reiterate the importance of understanding their dynamics. Due to the lack of in-situ data, the generation is the least known aspect of tsunamis. As a result, simplified models of the source are used for numerical tsunami modeling, as for seismic generation for which the traditional approach neglects several phenomena, among which is the kinematic deformation of the sea floor. This motion canbe characterized by two temporal parameters: the rupture velocity vp and a hydraulic rise time tr. The novelty here, is to investigate both parameters simultaneously and to extend the linear theoretical development to a non-linear numerical study. From these works, a resonance zone is identified for small tr and vp close to the long wave celerity. For these particular values, the waves are amplified beside the sea floor deformation and dispersive effects develop. To illustrate this theory, the 1947 New Zealand tsunami is simulatedwith the Non-Linear Shallow Water and Boussinesq models of Telemac2D. This seismic event corresponds to a tsunami earthquake with slow kinematics of deformation. Four generation models, with different values of vp and tr are compared. The impact of vp on the generated wave amplitudes is strong whereas the influence due to tr is significantly smaller. Additionally, it was found that the expected dispersive effects did not develop during the numerical modeling. Meanwhile, in the scope of the TANDEM project, the validation of the Telemac system is performed through test cases, covering: generation, propagation and run-up of tsunamis. Globally, the models from the Telemac system match the validation data, however we note a reliance on numerical parameters for sensitive cases as the propagation of a solitary wave. Finally, the Non-Linear Shallow Water model of Telemac2D is used to simulate the Tohoku-Oki tsunami that hit Japan in 2011. Thenumerical model succeeds in representing this real event incorporating all the stages of tsunami life, from generation to flooded areas. Some limitations in using the method were found, which one discussed in detail within the present manuscript
Outage performance of dual hop full-duplex relaying with Alamouti/MRC over Rayleigh fading channels

In this study, we present a full-duplex (FD) transmission scheme based on conventional Alamouti coding technique and investigate end-to-end (e2e) outage probability (OP) performance over independent identically distributed Rayleigh fading channels in dual-hop relay networks. We assume that direct link is not available due to channel impairments, so that the communication between the source and destination is maintained only via a single relay. In the network, the relay is equipped with one receive and one transmit antennas, and adopts amplify-and-forward (AF) and decode-and-forward (DF) protocols. While Alamouti code is used at the transmitter side, maximal-ratio combining (MRC) technique is employed at the destination in order to provide higher diversity order. OP expressions are derived in single integral and closed forms for AF and DF protocols, respectively. In addition, in order to provide insight into OP, asymptotic OP expressions are also derived. The analytical derivations are verified by the Monte Carlo simulations. Results show that e2e performance of the system is improved at low signal-to-noise ratio (SNR) region by increasing the number of antennas at the destination and DF provides approximately 2 dB SNR gain as compared to AF.
Fingerprinting VPNs with Custom Router Firmware: A New Censorship Threat Model

Virtual Private Networks are effective in bypassing Internet censorship. Extensive research has been done to obfuscate VPN traffic in order to circumvent control filtering. In this paper, we introduce a new threat model in which a censorship body can use home routers running a custom firmware or an embedded OS to identify VPN connections. Monitoring network traffic at home routers enables efficient and accurate fingerprinting of VPN traffic before the traffic is NATed to the Internet. The proposed model leverages a vulnerability in VPN implementations. Experimental results highlight its ability to fingerprint with negligible false positives/negatives. The purpose of the study is to increase awareness of this issue and inspire others to take this threat model as a reasonable risk that needs to be addressed.
A high performing brain–machine interface driven by low-frequency local field potentials alone and together with spikes

Objective. Brain–machine interfaces (BMIs) seek to enable people with movement disabilities to directly control prosthetic systems with their neural activity. Current high performance BMIs are driven by action potentials (spikes), but access to this signal often diminishes as sensors degrade over time. Decoding local field potentials (LFPs) as an alternative or complementary BMI control signal may improve performance when there is a paucity of spike signals. To date only a small handful of LFP decoding methods have been tested online; there remains a need to test different LFP decoding approaches and improve LFP-driven performance. There has also not been a reported demonstration of a hybrid BMI that decodes kinematics from both LFP and spikes. Here we first evaluate a BMI driven by the local motor potential (LMP), a low-pass filtered time-domain LFP amplitude feature. We then combine decoding of both LMP and spikes to implement a hybrid BMI. Approach. Spikes and LFP were recorded from two macaques implanted with multielectrode arrays in primary and premotor cortex while they performed a reaching task. We then evaluated closed-loop BMI control using biomimetic decoders driven by LMP, spikes, or both signals together. Main results. LMP decoding enabled quick and accurate cursor control which surpassed previously reported LFP BMI performance. Hybrid decoding of both spikes and LMP improved performance when spikes signal quality was mediocre to poor. Significance. These findings show that LMP is an effective BMI control signal which requires minimal power to extract and can substitute for or augment impoverished spikes signals. Use of this signal may lengthen the useful lifespan of BMIs and is therefore an important step towards clinically viable BMIs.
3D Communities as Platforms for Developing Social Capital

3D virtual communities, a particular form of platforms, have gained remarkable attention in theory and practice. Similarly, the well established concept of social capital, which describes resources becoming accessible and available through the connection and interaction between individuals on a platform, has regained prominence with the boom of social media. In this study, we investigate the development of social capital in 3D virtual communities. Adapting the model of Adler and Kwon (2002), we analyze the role of motivation, ability, opportunity, and integration fir constituting social capital in 3D virtual communities. Our empirical investigation conducted in 2008 and 2009 among users of two 3D virtual communities, one networking platform and one online gaming platform, suggests that only motivation and ability are generally important. We conclude that the sources of social capital depend on the specific type and user audience of a 3D virtual community as well as on the sophistication of the available tools in the particular 3D environment and the cultural openness of the network.
Cognitive Benefits of Digital Games for Older Adults - Strategies for Increasing Participation

There is evidence that shows that playing digital games has cognitive benefits for older adults. However, to reap these cognitive benefits, barriers that prevent full participation in gameplay must be overcome. This position paper describes the cognitive benefits of digital gaming for older people, outlines some of the obstacles they may face when playing digital games, and offers strategies that could help reduce these barriers so more older adults could enjoy the benefits of playing digital games.
Prognostic Role of microRNA-155 in Various Carcinomas: Results from a Meta-Analysis

BACKGROUND: Recent studies have shown that microRNAs (miRNA) have prognostic values in cancers. This meta-analysis seeks to summarize the global predicting role of miR-155 for survival in patients with a variety of carcinomas. METHODS: Eligible studies were identified through multiple search strategies. Data were extracted from studies investigating the relationship between miR-155 expression and survival in cancer patients. Combined hazard ratios (HRs) of miR-155 for outcome were analyzed. RESULTS: A total of 16 studies dealing with various carcinomas were included for this meta-analysis. For overall survival, higher miR-155 expression could significantly predict worse outcome with the pooled HR of 2.057 (95% CI: 1.392–3.039). For relapse or progress-free survival, elevated miR-155 was also a significant predictor, with a combined HR of 1.918 (95% CI: 1.311–2.806,). In addition, subgroup analysis showed that higher expression of miR-155 had the trends to predict worse outcome in lung cancer. However, the HRs did not reach the statistical significance. CONCLUSION: Our findings suggest that miR-155 detection has a prognostic value in cancer patients. Regularly measuring miR-155 expression may be useful in clinical practice.
Efficient Algorithms for k-Regret Minimizing Sets

A regret minimizing set Q is a small size representation of a much larger database P so that user queries executed on Q return answers whose scores are not much worse than those on the full dataset. In particular, a k-regret minimizing set has the property that the regret ratio between the score of the top-1 item in Q and the score of the top-k item in P is minimized, where the score of an item is the inner product of the item's attributes with a user's weight (preference) vector. The problem is challenging because we want to find a single representative set Q whose regret ratio is small with respect to all possible user weight vectors. We show that k-regret minimization is NP-Complete for all dimensions d >= 3. This settles an open problem from Chester et al. [VLDB 2014], and resolves the complexity status of the problem for all d: the problem is known to have polynomial-time solution for d <= 2. In addition, we propose two new approximation schemes for regret minimization, both with provable guarantees, one based on coresets and another based on hitting sets. We also carry out extensive experimental evaluation, and show that our schemes compute regret-minimizing sets comparable in size to the greedy algorithm proposed in [VLDB 14] but our schemes are significantly faster and scalable to large data sets.