Miracle-dz/UniFAR-FTUs huggingface dataset:
Sommerfeld effect in freeze-in dark matter

If two annihilation products of dark matter (DM) particles are non-relativistic and coupled to a light force mediator, their plane wave functions are modified due to multiple exchanges of the force mediators. This gives rise to the Sommerfeld effect (SE). We consider the attractive and repulsive force SE on the relic density in different phases of freeze-in DM. We find that in the pure freeze-in region, the attractive/repulsive force SE slightly increases/decreases DM relic density by less than $20\%$ for TeV-scale DM. In the reannihilation region, if the portal coupling $\kappa$ is sufficiently large (by comparing the portal reaction rate to the Hubble rate), DM density will reach its equilibrium, and subsequently freeze out. Compared to the case without the SE, the presence of the attractive SE leads to an enlarged cross-section. As a result, a higher equilibrium value of DM density is reached, and a lower relic density is obtained after the subsequent freeze-out. However, the repulsive SE has the opposite influence. In the dark sector (DS) freeze-out region, also known as the middle flat plateau or ``mesa'' in the phase diagram, the SE has a significant impact on DM relic abundance. In this region, the attractive SE suppresses DM relic density by simultaneously enlarging the cross-section of the portal and DS internal interaction. In contrast, the repulsive SE will have the opposite effect. Finally, in the usual freeze-out region, DM relic density is suppressed or enhanced by an enlarged or reduced cross-section of the portal, respectively, due to the presence of the attractive or repulsive SE. In summary, when considering the constraint of producing correct DM relic abundance, the inclusion of SE in the portal reaction or DS internal reaction will modify the model parameters, resulting in a band-like possible parameter space.
Strong-disorder approach for the Anderson localization transition

We implement an efficient strong-disorder renormalization-group (SDRG) procedure to study disordered tight-binding models in any dimension and on the Erdos-Renyi random graphs, which represent an appropriate infinite dimensional limit. Our SDRG algorithm is based on a judicious elimination of most (irrelevant) new bonds generated under RG. It yields excellent agreement with exact numerical results for universal properties at the critical point without significant increase of computer time, and confirm that, for Anderson localization, the upper critical dimension duc = infinite. We find excellent convergence of the relevant 1/d expansion down to d=2, in contrast to the conventional 2+epsilon expansion, which has little to say about what happens in any d>3. We show that the mysterious mirror symmetry of the conductance scaling function is a genuine strong-coupling effect, as speculated in early work. This opens an efficient avenue to explore the critical properties of Anderson transition in the strong-coupling limit in high dimensions.
Implications of existing local (mal)adaptations for ecological forecasting under environmental change

Standing genetic variation represents a genetic load on population fitness but can also support a rapid response to short‐term environmental change, and the greatest potential source of such standing genetic variation typically exists among locally adapted populations living along an environmental gradient. Here, we develop a spatially explicit simulation model to quantify the contribution of existing genetic variation arising from migration–mutation–selection–drift balance to time to extinction under environmental change. Simulations reveal that local adaptation across a species range associated with an underlying environmental gradient could extend time to extinction by nearly threefold irrespective of the rate of environmental change. The potential for preadapted alleles to increase the rate of adaptation changes the relative importance of established extinction risk factors; in particular, it reduced the importance of the breadth of environmental tolerance and it increased the relative importance of fecundity. Although migration of preadapted alleles generally increased persistence time, it decreased it at rates of environmental change close to the critical rate of change by creating a population bottleneck, which ultimately limited the rate at which de novo mutations could arise. An analysis of the extinction dynamics further revealed that one consequence of gene flow is the potential to maximize population growth rate in at least part of the species range, which is likely to have consequences for forecasting the consequences of ecological interactions. Our study shows that predictions of persistence time change fundamentally when existing local adaptations are explicitly taken into account, underscoring the need to preserve and manage genetic diversity.
Probabilistic Methods in Dependency Grammar Parsing

Authentic text as found in corpora cannot be described completely by a formal system, such as a set of grammar rules. As robust parsing is a prerequisite for any practical natural language processing system, there is certainly a need for techniques that go beyond merely formal approaches. Various possibilities, such as the use of simulated annealing, have been proposed recently and we have looked at their suitability for the parse process of the DLT machine translation system, which will use a large structured bilingual corpus as its main linguistic knowledge source. Our findings are that parsing is not the type of task that should be tackled solely through simulated annealing or similar stochastic optimization techniques but that a controlled application of probabilistic methods is essential for the performance of a corpus-based parser. On the basis of our explorative research we have planned a number of small-scale implementations in the near future.
Bounded Latency with RoCE

Virtual Network Functions (VNFs) provisioned in the cloud require deterministic and reliable services. Networking has a major impact on cloud based services, thus we focus on RDMA over Converged Ethernet (RoCE), as a combination of Ethernet, the ubiquitous networking technology, and RDMA, which provides extremely low latency. RoCE significantly outperforms socket communication, confirmed by our measurements, but we also show that maximum latencies are orders of magnitude larger than the average. We provide methods how to keep even maximum latencies low while concurrent network traffic is also present in the infrastructure.
Emotion recognition based on contours of features

Facial gesture recognition is one of the important components of natural human-machine interfaces; it may also be used in behavioural science, security systems and inClinical practice. Automatic analysis of facial gestures is rapidly becoming an area of intense interest in computer science and human-computer interaction design communities. However, the basic goal of this area of research – translating detected facial changes into a human-like description of shown facial expression – is yet to be achieved. One of the main impediments to achieving this aim is the fact that human interpretations of a facial expression differ depending upon whether the observed person is speaking or not. A first step in tackling this problem is to achieve automatic detection of facial gestures that are typical for speech articulation. Although humans recognise facial expressions virtually without effort or delay, reliable expression recognition by machine is still a challenge. The face expression recognition problem is challenging because different individuals display the same expression differently. This paper presents an overview of gesture recognition in real time using the concepts of correlations. Our approach to seizing this step in the research on automatic facial expression analysis. We consider the six universal emotional categories namely joy, anger, fear, disgust, sadness and surprise.The applications of gesture recognition are manifold, ranging from sign language through medicalrehabilitation to virtual reality. In this paper, various algorithms for gesture recognition have been investigated. Firststep in any gesture recognition process is face detection. We investigated algorithms like color segmentation,morphological Image Processing etc. for face detection, and Eigen faces for gesture recognition.
The Neural Correlates of Time: A Meta-analysis of Neuroimaging Studies

During the last two decades, our inner sense of time has been repeatedly studied with the help of neuroimaging techniques. These investigations have suggested the specific involvement of different brain areas in temporal processing. At least two distinct neural systems are likely to play a role in measuring time: One is mainly constituted of subcortical structures and is supposed to be more related to the estimation of time intervals below the 1-sec range (subsecond timing tasks), and the other is mainly constituted of cortical areas and is supposed to be more related to the estimation of time intervals above the 1-sec range (suprasecond timing tasks). Tasks can then be performed in motor or nonmotor (perceptual) conditions, thus providing four different categories of time processing. Our meta-analytical investigation partly confirms the findings of previous meta-analytical works. Both sub- and suprasecond tasks recruit cortical and subcortical areas, but subcortical areas are more intensely activated in subsecond tasks than in suprasecond tasks, which instead receive more contributions from cortical activations. All the conditions, however, show strong activations in the SMA, whose rostral and caudal parts have an important role not only in the discrimination of different time intervals but also in relation to the nature of the task conditions. This area, along with the striatum (especially the putamen) and the claustrum, is supposed to be an essential node in the different networks engaged when the brain creates our sense of time.
Neural Mechanisms for Monitoring and Halting of Spoken Word Production

During conversation, speakers monitor their own and others' output so they can alter their production adaptively, including halting it if needed. We investigated the neural mechanisms of monitoring and halting in spoken word production by employing a modified stop signal task during fMRI. Healthy participants named target pictures and withheld their naming response when presented with infrequent auditory words as stop signals. We also investigated whether the speech comprehension system monitors inner (i.e., prearticulatory) speech via the output of phonological word form encoding as proposed by the perceptual loop theory [Levelt, W. J. M. Speaking: From intention to articulation. Cambridge, MA: MIT Press, 1989] by presenting stop signals phonologically similar to the target picture name (e.g., cabbage–CAMEL). The contrast of successful halting versus naming revealed extensive BOLD signal responses in bilateral inferior frontal gyrus, preSMA, and superior temporal gyrus. Successful versus unsuccessful halting of speech was associated with increased BOLD signal bilaterally in the posterior middle temporal, frontal, and parietal lobes and decreases bilaterally in the posterior and left anterior superior temporal gyrus and right inferior frontal gyrus. These results show, for the first time, the neural mechanisms engaged during both monitoring and interrupting speech production. However, we failed to observe any differential effects of phonological similarity in either the behavioral or neural data, indicating monitoring of inner versus external speech might involve different mechanisms.
KolmoLD: Data Modeling for the Modern Internet

KolmoLD is a framework for content-addressable networking with a programmable layer: the data objects distributed across the network can contain program code to decode the data that is specified to be executed in a sandboxed environment and references other data objects based on a cryptographic hash function naming scheme. Traditionally, the algorithms to access given data are delivered via a channel that is separate from the one used to deliver the data itself, and usually involves installing custom software that could introduce security risks. In contrast, KolmoLD enables the delivery of the algorithms and the data along the same channel and ensures security. The KolmoLD approach unlocks the promise of the information-centered networks: enabling true data deduplication, data reuse and optimal data delivery.
NetBOA: Self-Driving Network Benchmarking

Communication networks have not only become a critical infrastructure of our digital society, but are also increasingly complex and hence error-prone. This has recently motivated the study of more automated and "self-driving" networks: networks which measure, analyze, and control themselves in an adaptive manner, reacting to changes in the environment. In particular, such networks hence require a mechanism to recognize potential performance issues. This paper presents NetBOA, an adaptive and "data-driven" approach to measure network performance, allowing the network to identify bottlenecks and to perform automated what-if analysis, exploring improved network configurations. As a case study, we demonstrate how the NetBOA approach can be used to bench-mark a popular software switch, Open vSwitch. We report on our implementation and evaluation, and show that NetBOA can find performance issues efficiently, compared to a non-data-driven approach. Our results hence indicate that NetBOA may also be useful to identify algorithmic complexity attacks.
Review of Recent Physical Activity Guidelines During Pregnancy to Facilitate Advice by Health Care Providers.

Importance Physical activity during pregnancy can offer many maternal and fetal health benefits. Objective The aim was to summarize American, Canadian, and international recommendations published recently on physical activity during pregnancy to aid health care providers in their delivery of advice on the topic. Evidence Acquisition A descriptive review of 3 national guidelines and 1 international guideline on physical activity during pregnancy was conducted. The guidelines included the 2019 Canadian recommendations, the 2018 United States' Physical Activity Guidelines for Americans (second edition), the 2015 (reaffirmed in 2017) American College of Obstetrics and Gynecology guideline, and the 2016-2018 International Olympic Committee recommendations for recreational and elite athletes. Results For apparently healthy women, under the guidance of their health care provider, moderate-intensity physical activity using both aerobic and muscle conditioning activities is recommended. The guidelines recommended at least 150 min/wk spread throughout the week (Canada, United States) or at least 20 to 30 min/d (American College of Obstetrics and Gynecology). Conclusions and Relevance This summary of 4 recent guidelines can facilitate use of updated recommendations by health care providers regarding physical activity during pregnancy. More detailed evidence-based guidelines on physical activity during postpartum are needed.
From Extraction to Advanced Analytical Methods: The Challenges of Melanin Analysis

The generic term “melanin“ describes a black pigment of biological origin, although some melanins can be brown or even yellow. The pigment is characterized as a heterogenic polymer of phenolic or indolic nature, and the classification of eu-, pheo- and allo- melanin is broadly accepted. This classification is based on the chemical composition of the monomer subunit structure of the pigment. Due to the high heterogeneity of melanins, their analytical characterization can be a challenging task. In the present work, we synthesized the current information about the analytical methods which can be applied in melanin analysis workflow, from extraction and purification to high-throughput methods, such as matrix-assisted laser desorption/ionization mass-spectrometry or pyrolysis gas chromatography. Our thorough comparative evaluation of analytical data published so far on melanin analysis has proven to be a difficult task in terms of finding equivalent results, even when the same matrix was used. Moreover, we emphasize the importance of prior knowledge of melanin types and properties in order to select a valid experimental design using analytical methods that are able to deliver reliable results and draw consistent conclusions.
RNA-seq reveals disruption of gene regulation when honey bees are caged and deprived of hive conditions

ABSTRACT In this study, we present phenotypic and genetic data characterizing the impact of imidacloprid and caging stress on honey bee Apis mellifera physiological responses and regulation of 45 genes using targeted-RNA seq. The term ‘caging stress’ characterizes the effects of depriving honey bees of all hive aspects and conditions. Two cohorts of 1 day old sister bees were subjected to different conditions. One cohort was caged and fed different imidacloprid-tainted sugar solutions and the second was marked and introduced back to its natal hive. Physiological bee parameters and diet behavior were monitored daily for caged bees over several weeks. Bee samples from both cohorts were sampled weekly for RNA sequencing and oxidative stress analyses. Imidacloprid induced significant protein damage and post-ingestive aversion responses in caged bees, leading to lower tainted syrup consumption and higher water intake compared with the controls. No differentially expressed genes were observed among caged bees in regards to imidacloprid treatment. However, significant upregulation in antioxidant genes was recorded in caged bees as compared with hive bees, with overwhelming downregulation in all gene categories in caged bees at week 4. We identified two sets of genes that were constantly regulated in caged bees, including Rsod with unknown function in insects that could potentially characterize caging stress in honey bees. Summary: Honey bees caged for experimental purposes show significant alteration of their gene regulation and oxidative stress compared with their sister-mates operating under natural hive conditions.
Relationships between Occupational Therapy Practitioner Characteristics and Home Exercise Program Prescription for Clients with Neurological Injuries

Abstract There are no guidelines for the prescription of home exercise programs (HEPs) for clients with neurological injuries. However, 95% of occupational therapy practitioners prescribe HEPs. Two thousand anonymous surveys were distributed to occupational therapy practitioners. Data from the 352 returned, usable surveys were analyzed to determine trends in HEP prescription across practice settings and provider demographics. Occupational therapy practitioners in community-based settings tended to use more functional activities and the number of years in practice did not influence HEP dosage. These findings suggest a need for clear guidelines for varying practice settings to guide HEP prescription.
The auxiliary ESCRT complexes provide robustness to cold in poikilothermic organisms

ABSTRACT The ESCRT pathway, comprising the in sequence acting ESCRT-0, -I, -II, -III and Vps4 complexes, conducts the abscission of membranes away from the cytosol. Whereas the components of the central ESCRT-III core complex have been thoroughly investigated, the function of the components of the associated two auxiliary ESCRT sub-complexes are not well-understood in metazoans, especially at the organismal level. We here present the developmental analysis of the Drosophila orthologs of the auxiliary ESCRTs Chmp5 and Ist1, DChmp5 and DIst1, which belong to the two auxiliary sub-complexes. While each single null mutant displayed mild defects in development, the Dist1 Dchmp5 double mutant displayed a severe defect, indicating that the two genes act synergistically, but in separate pathways. Moreover, the presented results indicate that the auxiliary ESCRTs provide robustness against cold during development of diverse poikilothermic organisms, probably by preventing the accumulation of the ESCRT-III core component Shrub on the endosomal membrane. Summary: The analysis of Chmp5 and Ist1, which belong to the two ESCRT auxiliary sub-complexes in Drosophila, suggests that these ESCRT proteins provide robustness against cold in diverse poikilothermic organisms.
The Immune Landscape of Thyroid Cancer in the Context of Immune Checkpoint Inhibition

Immune cells play critical roles in tumor prevention as well as initiation and progression. However, immune-resistant cancer cells can evade the immune system and proceed to form tumors. The normal microenvironment (immune cells, fibroblasts, blood and lymphatic vessels, and interstitial extracellular matrix (ECM)) maintains tissue homeostasis and prevents tumor initiation. Inflammatory mediators, reactive oxygen species, cytokines, and chemokines from an altered microenvironment promote tumor growth. During the last decade, thyroid cancer, the most frequent cancer of the endocrine system, has emerged as the fifth most incident cancer in the United States (USA), and its incidence is steadily growing. Inflammation has long been associated with thyroid cancer, raising critical questions about the role of immune cells in its pathogenesis. A plethora of immune cells and their mediators are present in the thyroid cancer ecosystem. Monoclonal antibodies (mAbs) targeting immune checkpoints, such as mAbs anti-cytotoxic T lymphocyte antigen 4 (anti-CTLA-4) and anti-programmed cell death protein-1/programmed cell death ligand-1 (anti-PD-1/PD-L1), have revolutionized the treatment of many malignancies, but they induce thyroid dysfunction in up to 10% of patients, presumably by enhancing autoimmunity. Combination strategies involving immune checkpoint inhibitors (ICIs) with tyrosine kinase (TK) or serine/threonine protein kinase B-raf (BRAF) inhibitors are showing considerable promise in the treatment of advanced thyroid cancer. This review illustrates how different immune cells contribute to thyroid cancer development and the rationale for the antitumor effects of ICIs in combination with BRAF/TK inhibitors.
Early‐life exposure to low levels of permethrin exerts impairments in learning and memory with the effects on neuronal and glial population in adult male mice

Permethrin, a pyrethroid chemical, is widely used as a pesticide because of its rapid insecticidal activity. Although permethrin is considered to exert very low toxicity in mammals, the effects of early, low‐level, chronic exposure on the adult central nervous system are unclear. In this study, we investigated the effects of low‐level, chronic permethrin exposure in early life on the brain functions of adult mice, using environmentally relevant concentrations. We exposed mice to the acceptable daily intake level of permethrin (0.3 ppm) in drinking water during the prenatal and postnatal periods. We then examined the effects on the central nervous system in adult male offspring. In the permethrin group, we detected behavior that displayed incomplete adaptation to a novel environment, as well as an impairment in learning and memory. In addition, immunohistochemical analysis revealed an increase in doublecortin‐ (an immature neuron marker) positive cells in the hippocampal dentate gyrus in the permethrin exposure group compared with the control group. Additionally, in the permethrin exposure group there was a decrease in astrocyte number in the hilus of the dentate gyrus, and remaining astrocytes were often irregularly shaped. These results suggest that exposure to permethrin at low levels in early life affects the formation of the neural circuit base and behavior after maturation. Therefore, in the central nervous system of male mice, low‐level, chronic permethrin exposure during the prenatal and postnatal periods has effects that were not expected based on the known effects of permethrin exposure in mature animals.