Miracle-dz/UniFAR-FTUs huggingface dataset:
Learning Tool Morphology for Contact-Rich Manipulation Tasks with Differentiable Simulation

When humans perform contact-rich manipulation tasks, customized tools are often necessary to simplify the task. For instance, we use various utensils for handling food, such as knives, forks and spoons. Similarly, robots may benefit from specialized tools that enable them to more easily complete a variety of tasks. We present an end-to-end framework to automatically learn tool morphology for contact-rich manipulation tasks by leveraging differentiable physics simulators. Previous work relied on manually constructed priors requiring detailed specification of a 3D object model, grasp pose and task description to facilitate the search or optimization process. Our approach only requires defining the objective with respect to task performance and enables learning a robust morphology through randomizing variations of the task. We make this optimization tractable by casting it as a continual learning problem. We demonstrate the effectiveness of our method for designing new tools in several scenarios, such as winding ropes, flipping a box and pushing peas onto a scoop in simulation. Additionally, experiments with real robots show that the tool shapes discovered by our method help them succeed in these scenarios.
Habitual physical activity , peripheral neuropathy , foot deformities and lower limb function : characterising prevalence and interlinks in patients with type 2 diabetes mellitus

Background: Patients with type 2 diabetes mellitus (T2DM) may have diverse foot problems, but how these problems are linked with physical activity is not clear. This study investigated the prevalence of foot problems among patients with T2DM and investigated how the problems were related to physical activity. Methods: Habitual physical activity, peripheral neuropathy, lower limb functions and foot deformities of 246 T2DM patients were respectively assessed with the Baecke Physical Activity Questionnaire, Michigan Neuropathy Screening Instrument, Lower Limb Function Scale, and a self-designed foot deformity audit form. Results: Habitual physical activity index (3.2 ± 0.83) was highest in work-related activities; 69 (26.1 %) patients presented with peripheral neuropathy and 52 (19. 7%) had the lowest limb function. Pes planus was the most prevalent foot deformity (20.1%). Significant differences existed in physical activity indices across deformity groups (p < 0.05) and total activity index was related to neuropathic and lower limb function scores (p < 0.05). Conclusion: A higher work-related but reduced participation in sports and leisure time physical activity among the patients was observed. Habitual physical activity was lowest in patients with a forefoot deformity, higher neuropathic scores and lesser lower limb function scores. Patients with T2DM in these categories may be a target for special physical activity intervention programmes.
Tilburg University On making the right choice

Are difficult decisions best made after a momentary diversion of thought? Previous research addressing this important question has yielded dozens of experiments in which participants were asked to choose the best of several options (e.g., cars or apartments) either after conscious deliberation, or after a momentary diversion of thought induced by an unrelated task. The results of these studies were mixed. Some found that participants who had first performed the unrelated task were more likely to choose the best option, whereas others found no evidence for this so-called unconscious thought advantage (UTA). The current study examined two accounts of this inconsistency in previous findings. According to the reliability account, the UTA does not exist and previous reports of this effect concern nothing but spurious effects obtained with an unreliable paradigm. In contrast, the moderator account proposes that the UTA is a real effect that occurs only when certain conditions are met in the choice task. To test these accounts, we conducted a meta-analysis and a large-scale replication study (N = 399) that met the conditions deemed optimal for replicating the UTA. Consistent with the reliability account, the large-scale replication study yielded no evidence for the UTA, and the meta-analysis showed that previous reports of the UTA were confined to underpowered studies that used relatively small sample sizes. Furthermore, the results of the large-scale study also dispelled the recent suggestion that the UTA might be gender-specific. Accordingly, we conclude that there exists no reliable support for the claim that a momentary diversion of thought leads to better decision making than a period of deliberation.
LoRa based vehicle tracking system

Received Mar 27, 2019 Revised May 6, 2019 Accepted May 29, 2019 This work describes an open source tracking system that determines the location and speed of a vehicle in real-time. The system was inspired by the need to track tourist boats in UNESCO Kilim Karst Geoforest Park, Malaysia. Boats that travel too fast generate wakes that are suspected to cause ecological damage. In this work, geolocation information is provided by Arduino based transponders with Global Positioning System (GPS). Transponders periodically transmit location and speed data using LoRa through a gateway to a cloud server. On the server, open source software components implement a Geographical Information System (GIS) to manage the location and speed data for display and further analysis. The resulting prototype performed the required functions as expected.
Rescuing the End-user systems from Vulnerable Applications using Virtualization Techniques

In systems owned by normal end-users, many times security attacks are mounted by sneaking in malicious applications or exploiting existing software vulnerabilities through security non-conforming actions of users. Virtualization approaches can address this problem by providing a quarantine environment for applications, malicious devices, and device drivers, which are mostly used as entry points for security attacks. However, the existing methods to provide quarantine environments using virtualization are not transparent to the user, both in terms of application interface transparency and file system transparency. Further, software configuration level solutions like remote desktops and remote application access mechanisms combined with shared file systems do not meet the user transparency and security requirements. We propose qOS, a VM-based solution combined with certain OS extensions to meet the security requirements of end-point systems owned by normal users, in a transparent and efficient manner. We demonstrate the efficacy of qOS by empirically evaluating the prototype implementation in the Linux+KVM system in terms of efficiency, security, and user transparency.
PRICE OF ANARCHY IN ATOMIC CONGESTION GAMES WITH STOCHASTIC DEMANDS AND AFFINE COSTS

We consider atomic congestion games with stochastic demands. The game captures the fact that players may end up not being able to participate. Participation happens independently and with exogenous probabilities pi ∈ [0, 1] that are common knowledge. Conversely, exclusion happens with probability 1−pi , in which case players incur no cost. We prove that this is a potential game, and that the price of anarchy parameterized by the probabilities is a nondecreasing function of p = maxi pi . The worst case is attained for players with the same probabilities pi ≡ p. In the case of a ne costs we provide an analytic expression for the parameterized price of anarchy as a function of p. This function is continuous on (0, 1], it is equal to 4/3 for 0 < p ≤ 1/4, and increases towards the known atomic bound of 5/2 when p → 1. The result follows using the (λ, μ)smoothness framework and optimizing the parameters to get sharp bounds. We show that these bounds are tight and are attained on routing games with purely linear costs (i.e., without constant terms). Additionally, we derive tight bounds for the price of stability for all values of p ∈ [0, 1].
Poset Ramsey number $R(P,Q_n)$. II. N-shaped poset

Given partially ordered sets (posets) $(P, \leq_P)$ and $(P', \leq_{P'})$, we say that $P'$ contains a copy of $P$ if for some injective function $f\colon P\rightarrow P'$ and for any $A, B\in P$, $A\leq _P B$ if and only if $f(A)\leq_{P'} f(B)$. For any posets $P$ and $Q$, the poset Ramsey number $R(P,Q)$ is the least positive integer $N$ such that no matter how the elements of an $N$-dimensional Boolean lattice are colored in blue and red, there is either a copy of $P$ with all blue elements or a copy of $Q$ with all red elements. We focus on the poset Ramsey number $R(P, Q_n)$ for a fixed poset $P$ and an $n$-dimensional Boolean lattice $Q_n$, as $n$ grows large. It is known that $n+c_1(P) \leq R(P,Q_n) \leq c_2(P) n$, for positive constants $c_1$ and $c_2$. However, there is no poset $P$ known, for which $R(P, Q_n)>(1+\epsilon)n$, for $\epsilon>0$. This paper is devoted to a new method for finding upper bounds on $R(P, Q_n)$ using a duality between copies of $Q_n$ and sets of elements that cover them, referred to as blockers. We prove several properties of blockers and their direct relation to the Ramsey numbers. Using these properties we show that $R(\mathcal{N},Q_n)=n+\Theta(n/\log n)$, for a poset $\mathcal{N}$ with four elements $A, B, C, $ and $D$, such that $A
Hypolipidemic effects of Olax subscorpioidea Oliv. root extract in experimental rat model

Olax subscorpioidea (Olacaceae) is a major component of a recipe used traditionally in the management of Obesity. In view of the traditional therapeutic use of the plant, this research screened the ethanol root extract of the plant for hypolipidemic effect in Wistar rats. This was carried out to validate its potential as a lipid lowering agent. The experimental rats were randomly distributed into five groups of 7 animals each. Group 1 (not induced with hyperlipidemia) received distilled water; Group 2 (induced with hyperlipidemia). Group 3 (induced) received 10 mg/kg bw of atorvastatin. Groups 4 and 5 were induced with hyperlipidemia and treated with 200 and 400 mg/kg bw extract of Olax subscorpioidea respectively for 14 days. Olax subscorpioidea root contained saponins (865.00 mg/100 g), alkaloids (963.33 mg/100 g), tannins (863.33 mg/100 g), flavonoids (636.67 mg/100 g), anthraquinones (46.67 mg/100 g) and proanthocyanidins (2.67 mg/g). The extract gave 47.30% inhibition against DPPH+. Significant decrease in TC, TG and LDL was recorded in treated groups with 200 and 400 mg/kg bw of the extract. There was also a significant increase in HDL level of treated groups when compared with induced group. This result suggests that ethanol extract of Olax subscorpioidea at 200 and 400 mg/kg bw possesses hypolipidemic effects on diet induced hyperlipidemic rats. The observed bioactivity could be attributed to phytochemical components, proximate contents as well as antioxidant activity of the plant.
Fungemia with Co-isolation of Candida parapsilosis and Trichosporon asahii Confirmed by MALDI-TOF MS and D 2 rRNA Sequencing

eISSN 2093-6338 patients and patients with serious general clinical status [1]. Candida species are currently a major cause of sepsis acquired in health care institutions [2] and the most common cause of blood stream fungal infections [3, 4]. Among Candida species, the incidence of Candida parapsilosis infection has rapidly increased [1]. This species is the second most common pathogen isolated from blood cultures of patients with candidemia in the USA [5]. Several studies of the worldwide incidence of Candida infections have reported that C. parapsilosis is a more common isolate than Candida albicans in some non-US regions [6]. C. parapsilosis is responsible for many clinical diseases such as fungemia [5, 7], endocarditis [8], meningitis [9], and peritonitis [10]. In addition to Candida, Trichosporon species are associated with diverse clinical symptoms, from mild to fatal [11]. Trichosporon species are widely distributed; they are sometimes present on the human body as INTRODUCTION
Learning to learn: Non-equilibrium design protocols for adaptable materials

Evolution in time-varying environments naturally leads to adaptable biological systems that can easily switch functionalities. Advances in the synthesis of environmentally-responsive materials therefore open up the possibility of creating a wide range of synthetic materials which can also be trained for adaptability. We consider high-dimensional inverse problems for materials where any particular functionality can be realized by numerous equivalent choices of design parameters. By periodically switching targets in a given design algorithm, we can teach a material to perform incompatible functionalities with minimal changes in design parameters. We exhibit this learning strategy for adaptability in two simulated settings: elastic networks that are designed to switch deformation modes with minimal bond changes; and heteropolymers whose folding pathway selections are controlled by a minimal set of monomer affinities. The resulting designs can reveal physical principles, such as nucleation-controlled folding, that enable adaptability.
Transcriptome Complexities Across Eukaryotes

Genomic complexity is a growing field of evolution, with case studies for comparative evolutionary analyses in model and emerging non-model systems. Understanding complexity and the functional components of the genome is an untapped wealth of knowledge ripe for exploration. With the “remarkable lack of correspondence” between genome size and complexity, there needs to be a way to quantify complexity across organisms. In this study we use a set of complexity metrics that allow for evaluation of changes in complexity using TranD. We ascertain if complexity is increasing or decreasing across transcriptomes and at what structural level, as complexity is varied. We define three metrics – TpG, EpT, and EpG in this study to quantify the complexity of the transcriptome that encapsulate the dynamics of alternative splicing. Here we compare complexity metrics across 1) whole genome annotations, 2) a filtered subset of orthologs, and 3) novel genes to elucidate the impacts of ortholog and novel genes in transcriptome analysis. We also derive a metric from Hong et al., 2006, Effective Exon Number (EEN), to compare the distribution of exon sizes within transcripts against random expectations of uniform exon placement. EEN accounts for differences in exon size, which is important because novel genes differences in complexity for orthologs and whole transcriptome analyses are biased towards low complexity genes with few exons and few alternative transcripts. With our metric analyses, we are able to implement changes in complexity across diverse lineages with greater precision and accuracy than previous cross-species comparisons under ortholog conditioning. These analyses represent a step forward toward whole transcriptome analysis in the emerging field of non-model evolutionary genomics, with key insights for evolutionary inference of complexity changes on deep timescales across the tree of life. We suggest a means to quantify biases generated in ortholog calling and correct complexity analysis for lineage-specific effects. With these metrics, we directly assay the quantitative properties of newly formed lineage-specific genes as they lower complexity in transcriptomes.
A k-additive Choquet integral-based approach to approximate the SHAP values for local interpretability in machine learning

Besides accuracy, recent studies on machine learning models have been addressing the question on how the obtained results can be interpreted. Indeed, while complex machine learning models are able to provide very good results in terms of accuracy even in challenging applications, it is difficult to interpret them. Aiming at providing some interpretability for such models, one of the most famous methods, called SHAP, borrows the Shapley value concept from game theory in order to locally explain the predicted outcome of an instance of interest. As the SHAP values calculation needs previous computations on all possible coalitions of attributes, its computational cost can be very high. Therefore, a SHAP-based method called Kernel SHAP adopts an efficient strategy that approximate such values with less computational effort. In this paper, we also address local interpretability in machine learning based on Shapley values. Firstly, we provide a straightforward formulation of a SHAP-based method for local interpretability by using the Choquet integral, which leads to both Shapley values and Shapley interaction indices. Moreover, we also adopt the concept of $k$-additive games from game theory, which contributes to reduce the computational effort when estimating the SHAP values. The obtained results attest that our proposal needs less computations on coalitions of attributes to approximate the SHAP values.
UvA-DARE ( Digital Academic Repository ) Relativistic jets from stellar black holes

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In-plane local defect resonances for efficient vibrothermography of impacted carbon fiber-reinforced composite ( CFRP )

It is well known that the efficiency of the vibroth ermographic non-destructive testing (NDT) technique can be enhanced by taking advantage of local defect resonance (LDR) frequencies. Recently, the classical out-of-plane l ocal defect resonance was extended towards in-plane LDR for enhanced efficiency of vib rometric NDT. This paper further couples the concept of this in-plane LDR to vibroth ermography, on the basis of the promising potential of in-plane LDRs to enhance the rubbing (tangential) interaction and viscoelastic damping of defects. Carbon fiber-r einforced composites (CFRPs) with barely visible impact damage (BVID) are inspected a n the significant contribution of in-plane LDRs in vibrational heating is demonstrate d. Moreover, it is shown that the defect thermal contrast induced by in-plane LDRs is o high that it allows for easy detection of BVID by live monitoring of infrared th ermal images during a single broadband sweep excitation. Thermal and vibrational spectra of the inspected surface are studied and the dominant contribution of in-pla ne LDR in vibration-induced heating is demonstrated.
A formal framework for generalized reporting methods in parametric settings

Effect size measures and visualization techniques aimed at maximizing the interpretability and comparability of results from statistical models have long been of great importance and are recently again receiving increased attention in the literature. However, since the methods proposed in this context originate from a wide variety of disciplines and are more often than not practically motivated, they lack a common theoretical framework and many quantities are narrowly or heuristically defined. In this work, we put forward a common mathematical setting for effect size measures and visualization techniques aimed at the results of parametric regression and define a formal framework for the consistent derivation of both existing and new variants of such quantities. Throughout the presented theory, we utilize probability measures to derive weighted means over areas of interest. While we take a Bayesian approach to quantifying uncertainty in order to derive consistent results for every defined quantity, all proposed methods apply to the results of both frequentist and Bayesian inference. We apply selected specifications derived from the proposed framework to data from a clinical trial and a multi-analyst study to illustrate its versatility and relevance.
A STUDY OF THREE ORIBATID MITE SPECIES IN ORCHARD HABITATS IN EGYPT

This study was done to investigate the relationship between the reproductive potential of oribatid mites (estimated by egg number) and their population density in different orchard habitats. We hypothesized that species with narrow feeding niches would be more susceptible to intraspecific competition and would show a decrease in egg number with increasing density, while general feeders would show egg numbers independent of density. To investigate these predictions, soils were sampled four times a year in orange, mango and date palm orchards at each of three sites in AlGharbia Governorate, Egypt. The number of mites extracted, the total number of eggs contained in their bodies and the gut contents were evaluated. The results show a significant difference between species in the way egg number varies with density. In Scheloribates laevigatus, a positive correlation between population density and egg number per individual is present. For Xylobates lophotrichus, however, a negative correlation was observed, while in the case of Zygoribatula undulata, no significant correlation between population density and egg number could be demonstrated. Gut contents showed that S. laevigatus has the widest trophic breadth, while X. lophotrichus is the most specialized feeder. We argue that the relationship between egg number and population density is shaped by differences in feeding habits: a specialized feeding habit is associated with a negative relationship between egg number and population density, whereas a broad trophic niche seems to be associated with a positive relationship between egg number and population density. This suggests that feeding habits have important population dynamic consequences in these soil-living invertebrates.
A Page Fault Equation for Dynamic Heap Sizing

For garbage-collected applications, dynamically-allocated objects are contained in a heap. Programmer productivity improves significantly if there is a garbage collector to automatically de-allocate objects that are no longer needed by the applications. However, there is a run-time performance overhead in garbage collection, and this cost is sensitive to heap size H: a smaller H will trigger more collection, but a large H can cause page faults, as when H exceeds the size M of main memory allocated to the application. This paper presents a Heap Sizing Rule for how H should vary with M . The Rule can help an application trade less page faults for more garbage collection, thus reducing execution time. It is based on a heap-aware Page Fault Equation that models how the number of page faults depends on H and M . Experiments show that this rule outperforms the default policy used by JikesRVM’s heap size manager. Specifically, the number of faults and the execution time are reduced for both static and dynamically changing M .
Real Analysis, 2nd Edition, G.B.Folland Chapter 6 L Spaces

Proof. (a) For p = 1, since we know the triangle inequality |(f + g)(x)| ≤ |f(x)| + |g(x)| is always true, to characteriz the case when the equality holds in Minkowski’s inequality is equivalent to seeking the condition for the equality |(f + g)(x)| = |f(x)|+ |g(x)| for all x, that is f(x)g(x) ≥ 0 for a.e. x. (We consider the complex-valued functions here.) (b) For 1 < p < ∞, in its proof, we know the equality holds in Minkowski inequality if and only if the ones in triangle and Hölder’s inequalities hold, that is, if and only if f(x)g(x) ≥ 0 for a.e. x, and there are constants α, β ≥ 0 such that |f(x)| = α|f(x) + g(x)| and |g(x)| = β|f(x) + g(x)| for a.e. x. Combining them, we know the equality holds in Minkowski if and only if f(x) = γg(x) for a.e. x, for some γ ≥ 0. (c) For p =∞. Define the set Af = {{xn}} where {xn} is a sequence in X with |f(xn)| → ‖f‖∞. We claim that ‖f + g‖∞ = ‖f‖∞ + ‖g‖∞ iff either one of the functions is 0 a.e. , or Af ∩ Ag is nonempty and for some {xn} ∈ Af ∩ Ag, where f(xn) → a and g(xn) → b, there is a λ > 0 such that b = λa.