Miracle-dz/UniFAR-FTUs huggingface dataset:
Plankton: Reconciling Binary Code and Debug Information

Static analysis has been widely used in large-scale software defect detection. Despite recent advances, it is still not practical enough because it requires compilation interference to obtain analyzable code. Directly translating the binary code using a binary lifter mitigates this practicality problem by being non-intrusive to the building system. However, existing binary lifters cannot produce precise enough code for rigorous static analysis even in the presence of the de-bug information. In this paper, we propose a new binary lifter Plankton together with two new algorithms that can fill the gaps between the low-and high-level code to produce high-quality LLVM intermediate representations (IRs) from binaries with debug information, enabling full-fledged static analysis with minor precision loss. Plankton shows comparable static analysis results with traditional compilation interference solutions, producing only 17.2% differences while being much more practical, outperforming existing lifters by 76.9% on average.
More than words: Advancements and challenges in speech recognition for singing

This paper addresses the challenges and advancements in speech recognition for singing, a domain distinctly different from standard speech recognition. Singing encompasses unique challenges, including extensive pitch variations, diverse vocal styles, and background music interference. We explore key areas such as phoneme recognition, language identification in songs, keyword spotting, and full lyrics transcription. I will describe some of my own experiences when performing research on these tasks just as they were starting to gain traction, but will also show how recent developments in deep learning and large-scale datasets have propelled progress in this field. My goal is to illuminate the complexities of applying speech recognition to singing, evaluate current capabilities, and outline future research directions.
Jupiter Lightning‐Induced Whistler and Sferic Events With Waves and MWR During Juno Perijoves

During the Juno perijove explorations from 27 August 2016 through 1 September 2017, strong electromagnetic impulses induced by Jupiter lightning were detected by the Microwave Radiometer (MWR) instrument in the form of 600‐MHz sferics and recorded by the Waves instrument in the form of Jovian low‐dispersion whistlers discovered in waveform snapshots below 20 kHz. We found 71 overlapping events including sferics, while Waves waveforms were available. Eleven of these also included whistler detections by Waves. By measuring the separation distances between the MWR boresight and the whistler exit point, we estimated the distance whistlers propagate below the ionosphere before exiting to the magnetosphere, called the coupling distance, to be typically one to several thousand of kilometers with a possibility of no subionospheric propagation, which gives a new constraint on the atmospheric whistler propagation.
A new multi‐proxy investigation of Late Quaternary palaeoenvironments along the north‐western Barents Sea (Storfjorden Trough Mouth Fan)

A new integrated micropalaeontological study on planktonic and benthic foraminifera, calcareous nannofossils and diatoms was performed on three sediment cores from the Storfjorden Trough Mouth Fan to reconstruct the Late Quaternary palaeoenvironmental and climatic history. Two main intervals were discussed: the last deglaciation (16.2–11.7 ka BP) and the Holocene. The age model relies on palaeomagnetic parameters together with 10 radiocarbon dates. Deglacial sediments had largely diluted the biogenic content which was scarce and poorly preserved. The first occurrence of Cibicidoides wuellerstorfi (benthic foraminifer), together with Turborotalita quinqueloba (planktonic foraminifer) and Coscinodiscus spp. (diatoms) at 11.3 ka BP followed the end of the Younger Dryas cold event and marked the beginning of the early Holocene warm period. Diatoms and planktonic foraminifers indicated a warming of the surface water from 10.5 to 9.2 ka BP, identifying the Holocene Thermal Maximum event. Bottom water fauna registered these warming conditions less clearly. Cooling events were identified during the Holocene, in particular the 8.2 ka BP event and the Neoglacial between 3.2 and 2 ka BP, as shown by the presence of cold‐water taxa such as Gephyrocapsa muellerae (nannoplankton) and Neogloboquadrina pachyderma (planktonic foraminifer). These events were influenced by sea ice extent, cold or relatively warm current influxes.
An Eﬃcient Sub-Gigawatt Level X-band BWO at Low Guiding Magnetic Field

—Efficiency enhancement in Backward Wave Oscillator (BWO) device at low magnetic field is a matter of concern. With decrease in guiding magnetic field, the quality of beam gets reduced along with increase in transverse motion of electrons. The transverse motion of electrons extracts energy from the RF field and undergo multipacting with the Slow Wave Structure (SWS) surface under influence of periodic accelerating electric field of microwaves. Hence, electron beam to microwave conversion efficiency gets reduced. Lowering magnetic field can also lead to two types of cyclotron absorptions i) Forward cyclotron absorption & ii) Backward cyclotron absorption. The simulation results of High-Power Microwave (HPM) generation from a non-uniform X-band BWO device having circular profiled SWS have been presented in this paper. Output power of 810 MW has been observed at 9.8 GHz with 27% efficiency, guided by 0.6T magnetic field. Also, overbunching & backstreaming of electron beam was observed in PIC simulation using CST studio. These phenomena restrict the device efficiency.
Characteristic Eigenvalues and their Interpretation using Power Quantities

For a ﬁxed frequency and an arbitrarily shaped lossless object, characteristic mode (CM) analysis yields a set of characteristic eigenvalues and their corresponding characteristic eigencurrents. The ﬁelds radiated by the characteristic currents are orthogonal and the eigenvalues measure how well each mode radiates. In this presentation, we discuss how the characteristic eigenvalues can be interpreted in terms of power quantities when the object is either perfectly electrically conducting (PEC) or a homogeneous lossless dielectric
Eﬃciently Learning the Preferences of People

This paper presents a framework for optimizing the preference learning process. In many real-world applications in which preference learning is involved the available training data is scarce and obtaining labeled training data is expensive. Luckily in many of the preference learning situations data is available from multiple subjects. We use the multi-task formalism to enhance the individual training data by making use of the preference information learned from other subjects. Furthermore, since obtaining labels is expensive, we optimally choose which data to ask a subject for labelling to obtain maximum of information about her/his preferences. This paradigm —called active learning— has hardly been studied in a multi-task formalism. We propose an alternative for the standard criteria in active learning which actively chooses queries by making use of the available preference data from other subjects. The advantage of this alternative is the reduced computation costs and reduced time subjects are involved. We validate empirically our approach on two real-world data sets involving the preferences of people: an audiological data set and an art image data set.
Attribute-Based Signatures with Advanced Delegation, and Tracing

Attribute-based cryptography allows fine-grained control on the use of the private key. In particular, attribute-based signature ( ABS ) specifies the capabilities of the signer, which can only sign messages associated to a policy that is authorized by his set of attributes. Furthermore, we can expect signature to not leak any information about the identity of the signer. ABS is a useful tool for identity-preserving authentication process which requires granular access-control, and can furthermore be enhanced with additional properties, for example delegation where users are able to manage a set of keys derived from their original one. In this paper, we address delegation of signing keys. Our first delegation works for any subset of the original attributes, which is the intuitive approach of delegation. Furthermore, we also provide another kind of delegation where the delegator can choose a policy at delegation time to produce keys that can sign any message under this specific policy. This last approach to delegation is a direct application of a new version of the indexing technique, which was first introduced by Okamoto and Takashima in order to prove adaptive security in ABS and its counterpart for encryption, ABE . On top of that, we prove that our scheme is compatible with a well studied feature of ABS , traceability, by using an approach based on Linearly-Homomorphic signatures. All our schemes also guarantee the anonymity of the real signer. The unforgeability of our schemes is proven using the SXDH assumption, and our constructions use the Dual Pairing Vector Spaces (DPVS) framework developed by Okamoto and Takashima, which has been widely used for all kind of attribute and functional cryptography mechanisms.
NeuroImage: Clinical

The identification of pathological atrophy in MRI scans requires specialized training, which is scarce outside dedicated centers. We sought to investigate the clinical usefulness of computer-generated representations of local grey matter (GM) loss or increased volume of cerebral fluids (CSF) as normalized deviations (z-scores) from healthy aging to either aid human visual readings or directly detect pathological atrophy. Two experienced neuroradiologists rated atrophy in 30 patients with Alzheimer's disease (AD), 30 patients with frontotemporal dementia (FTD), 30 with dementia due to Lewy-body disease (LBD) and 30 healthy controls (HC) on a three-point scale in 10 anatomical regions as reference gold standard. Seven raters, varying in their experience with MRI diagnostics rated all cases on the same scale once with and once without computer-generated volume deviation maps that were overlaid on anatomical slices. In addition, we investigated the predictive value of the computer generated deviation maps on their own for the detection of atrophy as identified by the gold standard raters. Inter and intra-rater agreements of the two gold standard raters were substantial (Cohen's kappa κ > 0.62). The intra-rater agreement of the other raters ranged from fair ( κ =0.37) to substantial ( κ =0.72) and improved on average by 0.13 (0.57 < κ < 0.87) when volume deviation maps were displayed. The seven other raters showed good agreement with the gold standard in regions including the hippocampus but agreement was substantially lower in e.g. the parietal cortex and did not improve with the display of atrophy scores. Rating speed increased over the course of the study and irrespective of the presentation of voxel-wise deviations. Automatically detected large deviations of local volume were consistently associated with gold standard atrophy reading as shown by an area under the receiver operator characteristic of up to 0.95 for the hippocampus region. When applying these test characteristics to prevalences typically found in a memory clinic, we observed a positive or negative predictive value close to or above 0.9 in the hippocampus for almost all of the expected cases. The volume deviation maps derived from CSF volume increase were generally better in detecting atrophy. Our study demonstrates an agreement of visual ratings among non-experts not further increased by displaying, region-specific deviations of volume. The high predictive value of computer generated local deviations independent from human interaction and the consistent advantages of CSF-over GM-based estimations should be considered in the development of diagnostic tools and indicate clinical utility well beyond aiding visual assessments.
Residual feed intake is related to metabolic and inflammatory response during the preweaning period in Italian Simmental calves

Residual Feed Intake (RFI) is defined as the difference between measured and predicted intake. Understanding its biological regulators could benefit farm profit margins. The most-efficient animals (M-Eff) have observed intake smaller than predicted resulting in negative RFI, whereas the least-efficient (L-Eff) animals have positive RFI. Hence, this observational study aimed at retrospectively comparing the blood immunometabolic profile in calves with divergent RFI during the preweaning period. Twenty-two Italian Sim-mental calves were monitored from birth through 60 d of age. Calves received 3 L of colostrum from their respective dams. From 2 to 53 d of age, calves were fed a milk replacer twice daily, whereas from 54 to 60 d (i.e., weaning) calves were stepped down to only one meal in the morning. Calves had ad libitum access to concentrate and intakes were recorded daily. The measurement of BW and blood samples were performed at 0, 1, 7, 14, 21, 28, 35, 45, 54, and 60 d of age. Calves were ranked and categorized as M-Eff or L-Eff according to the median RFI value. Median RFI was −0.06 and 0.04 kg of DMI/d for M-Eff and L-Eff, respectively. No evidence for group differences was noted for colostrum and plasma IgG concentrations. Although growth rate was not different, as expected, (0.67 kg/d [95% CI = 0.57–0.76] for both L-Eff and M-Eff) throughout the entire preweaning period (0–60 d), starter intake was greater in L-Eff compared with M-Eff calves (+36%). Overall, M-Eff calves had a greater gain-to-feed ratio compared with L-Eff calves (+16%). Plasma ceruloplas-min, myeloperoxidase, and reactive oxygen metabolites
Deep learning for RFI mitigation of Nançay data and its impact on pulsar timing

Pulsars are fast-rotating and highly-magnetized stars producing beams of radio emission at their magnetic poles. Because the magnetic axis is not aligned with the spin axis, the beams are swept across the sky during the rotation of the star, thus creating periodic pulses to remote observers. To study pulsars, we record Times of Arrival (TOAs) [1] of periodic radio pulses at a telescope, and use the TOAs to estimate the parameters of the pulsar and its environment with high precision. However, radio observations of pulsars are impacted by different perturbating signals called radio frequency interferences (RFIs), which result from human activities such as telecommunications. These interferences need to be removed from observations to achieve the most precise pulsar timing. In this contribution we present our method to perform RFI excision from pulsar observations using a deep learning "DL" algorithm. The architecture is based on U-net [2], a convolutional neural network to detect RFIs in the dynamic spectrograms of the observations and generate a binary mask. The dataset comprises 45 000 real observations from the Nançay Radio Telescope (France) between 1.2GHz and 3.5GHz, and for the training process we include masks generated by the Coast Guard [3] standard statistical method as the ground truth value. We tested four configurations during the learning process, including weighted classes and adding simulated RFIs to our datasets to select the method with minimal false-negative detections. We apply the best configuration to remove RFIs on 9 specific pulsars
Impact of Beekeeping on the Wild Bee Diversity in Northern Ivory Coast (West Africa)

In Ivory Coast, beekeeping takes an important place among the major economic activities. It contributes to improving the population’s livelihoods thanks to its derived products which are honey, propolis, wax and royal jelly. However, the installation of honey bee hives could put pressure on wild bee species, which often live solitary. However, these wild bees are excellent pollinators of cultivated and wild plants. The study aimed to assess the effect of honey bee hives on the diversity of wild bees. The methodology approach consisted of capturing bees in three different plots inside the forest fragment of the botanical garden located at the University Peleforo Gon Coulibaly. The first plot was chosen approximately from 10 m to an apiary containing ten hives. The two other plots were chosen to be 200 m and 400 m from the apiary, respectively. Bees were captured once a month for three months using pan traps (UV—blue, yellow and white). A total of 17 bee species belonging to three families (Apidae, Megachilidae and Halictidae) were identified. The furthest plot from the apiary was the most diverse (H’ = 2.49) and that near the apiary was the least diverse (H’ = 0.11). Only, two wild bee species, Hypotrigona sp. and Thrinchostoma petersi , persisted inside the plot nearby the apiary where honey bees were most abundant. The furthest plots from the apiary seem to have the highest diversity of wild bees. These findings are very relevant because they can be used for the policies of conservation of wild bees and the management of beekeeping activities.
Spectral Hypergraph Partitioning Revisited

Most state-of-the-art hypergraph partitioning algorithms follow a multilevel approach that constructs a hierarchy of coarser hypergraphs that in turn is used to drive partition reﬁnements. These partitioners are widely accepted as the current standard, as they have proven to be quite eﬀective. On the other hand, spectral partitioners are considered to be less eﬀective in cut quality, and too slow to be used in industrial applications. In this work, we revisit spectral hypergraph partitioning and we demonstrate that the use of appropriate solvers eliminates the running time deﬁciency; in fact, spectral algorithms can compute competing solutions in a fraction of the time needed by standard partitioning algorithms, especially on larger designs. We also introduce several novel modiﬁcations in the common spectral partitioning workﬂow, that enhance signiﬁcantly the quality of the computed solutions. We run our partitioner on FPGA benchmarks generated by an industry leader, generating solutions that are directly competitive both in runtime and quality 1 .
Marine sampling field manual for benthic stereo BRUVS (Baited Remote Underwater Videos). In: Field Manuals for Marine Sampling to Monitor Australian Waters

Stereo-baited remote underwater video (stereo-BRUV) systems consist of two video cameras inside waterproof housings, attached to a base-bar and encased within a frame with some form of baited container in front of the cameras (Figure 5.1, Figure 5.2; Cappo et al. 2007). Benthic stereo-BRUVs are lowered to the seafloor and are left recording for a set duration. The video footage can then be used to assess the recorded fish assemblages and associated habitats. Stereo-BRUVs are becoming widely adopted as a non-extractive technique for sampling the relative abundance and size structure of fish assemblages (Cappo et al. 2004, 2007, Watson et al. 2009, Langlois et al. 2010, 2012, Hill et al. 2014, Whitmarsh et al. 2017).
Virtual Commons - Bridgewater State University Virtual Commons - Bridgewater State University

There is a wide range of applications for non-covalent DNA binding ligands, and optimization of such interactions requires detailed understanding of the binding mechanisms. One important class of these ligands is that of intercalators, which bind DNA by inserting aromatic moieties between adjacent DNA base pairs. Characterizing the dynamic and equilibrium aspects of DNA-intercalator complex assembly may allow optimization of DNA binding for spe-ciﬁc functions. Single-molecule force spectroscopy studies have recently revealed new details about the molecular mechanisms governing DNA intercalation. These studies can provide the binding kinetics and afﬁnity as well as determining the magnitude of the double helix structural deformations during the dynamic assembly of DNA–ligand complexes. These results may in turn guide the rational design of in-tercalators synthesized for DNA-targeted drugs, optical probes, or integrated biological self-assembly processes. Herein, we survey the progress in experimental methods as well as the corresponding analysis framework for understanding single molecule DNA binding mechanisms. We discuss brieﬂy minor and major groove binding ligands, and then focus on intercalators, which have been probed extensively with these methods. Conventional mono-intercalators and bis-intercalators are discussed, followed by unconventional DNA intercalation. We then
The Squared Kemeny Rule for Averaging Rankings

For the problem of aggregating several rankings into one ranking, Kemeny [1959] proposed two methods: the median rule which selects the ranking with the smallest total swap distance to the input rankings, and the mean rule which minimizes the squared swap distances to the input rankings. The median rule has been extensively studied since and is now known simply as Kemeny’s rule . It exhibits majoritarian properties, so for example if more than half of the input rankings are the same, then the output of the rule is the same ranking. We observe that this behavior is undesirable in many rank aggregation settings. For example, when we rank objects by different criteria (quality, price, etc.) and want to aggregate them with specified weights for the criteria, then a criterion with weight 51% should have 51% influence on the output instead of 100%. We show that the Squared Kemeny rule (i.e., the mean rule) behaves this way, by establishing a bound on the distance of the output ranking to any input rankings, as a function of their weights. Furthermore, we give an axiomatic characterization of the Squared Kemeny rule, which mirrors the existing characterization of the Kemeny rule but replaces the majoritarian Condorcet axiom by a proportionality axiom. Finally, we discuss the computation of the rule and show its behavior in a simulation study.
Assessing the E ﬃ cacy of an Accessible Computing Curriculum for Students with Autism Spectrum Disorders

: There is a limited amount of research dedicated to designing and developing computing curricula speci ﬁ cally tailored for students with autism spectrum disorder (ASD), and thus far, no study has examined the e ﬀ ectiveness of an accessible computing curriculum designed speci ﬁ cally for students with ASD. The goal of this study is to evaluate the e ﬀ ectiveness of an accessible curriculum in improving the learning of computational thinking concepts (CTCs) such as sequences, loops, parallelism, conditionals, operators, and data, as well as the development of pro ﬁ ciency in computational thinking practices (CTPs) including experimenting and iterating, testing and debugging, reusing and remixing, and abstracting and modularizing. The study involved two groups, each comprising twenty-four students. One group received instruction using the accessible curriculum, while the other was taught with the original curriculum. Evaluation of students’ CTCs included the analysis of pretest and pos tt est scores for both groups, and their CTPs were assessed through artifact-based interview scores. The results indicated improvement in both groups concerning the learning of CTCs, with no signi ﬁ cant di ﬀ erence between the two curricula. However, the accessible computing curriculum demonstrated signi ﬁ cant enhancements in students’ pro ﬁ ciency in debugging and testing, iterating and experimenting, modularizing and abstracting, as well as remixing and reusing. The ﬁ ndings suggest the e ﬀ ectiveness of accessible computing curricula for students with ASD.