Miracle-dz/UniFAR-FTUs huggingface dataset:
Information resilience through user-assisted caching in disruptive Content-Centric Networks

We investigate an information-resilience scheme in the context of Content-Centric Networks (CCN) for the retrieval of content in disruptive, fragmented networks cases. To resolve and fetch content when the origin is not available due to fragmentation, we exploit content cached both in in-network caches and in end-users' devices. Initially, we present the required modifications in the CCN architecture to support the proposed resilience scheme. We also present the family of policies that enable the retrieval of cached content and we derive an analytical expression/lower bound of the probability that an information item will disappear from the network (be absorbed) and the time to absorption when the origin of the item is not reachable. Extensive simulations indicate that the proposed resilience scheme is a valid tool for the retrieval of cached content in disruptive scenarios, since it allows the retrieval of content for a long period after the fragmentation of the network and the “disappearance” of the content origin.
Increasing cognitive dissonance by a fait accompli.

A RECENT theory by Festinger (1957) attempts to state the conditions under which discrepancies between cognitions produce "cognitive dissonance," a state of tension that motivates the individual to reduce or eliminate the discrepancies. One of the conditions that may be necessary for the creation of cognitive dissonance is that there be some element of volition. The theory states, for example, that a person who is completely forced to behave in a manner he would avoid if possible, experiences no dissonance. On the other hand, a, fait accompli—i.e., an event outside of the person's control—might conceivably create dissonance if that same event would have led to the opposite behavior had it been predictable at a prior choice point. The purpose of this paper, then, is to report an experiment in which a fait accompli does appear to have increased cognitive dissonance. The theoretical expectations may be stated succinctly. If a person is induced by the promise of a small prize to eat a disliked food, he should experience dissonance. If other things are held constant, the amount of dissonance can be increased by increasing the amount of the disliked food to be eaten. A person who is experiencing such dissonance should try, in proportion to its magnitude, to reduce it by convincing himself that he likes the food more than he originally thought. If, then, the amount of expected eating is increased by a fait accompli after the initial decision to eat has occurred, and this is accompanied by increased liking, it may be concluded that a, fail accompli can affect the magnitude of dissonance.
‘Looking for a More Modern Life…’: the Role of Italian Television in the Albanian Migration to Italy

When the communist regime collapsed in early March 2001, 25,700 Albanians tried to escape a situation of violent political confrontation and extreme economic deprivation by trying to reach Italy in a flotilla of boats and rafts of every type. This was to be the first act of a very dramatic migratory flow, which has its roots in the prolonged economic and political instability of Albania. Throughout the 1990s, the restrictive visa polices implemented by the Italian state forced many Albanians to smuggle themselves into Italy by risking their lives on dangerous rides on speedboats across the Adriatic Sea to the Apulia shores. Whereas during communism emigration was forbidden, nowadays more than one in five of the current Albanian population lives abroad and migrants’ remittances are a key strategy of economic survival for Albanian households and society more in general. In fact, about 200,000 Albanians currently live and work in Italy, out of a total population of 3,800,000 in Albania (Barjaba 2000, 69).
DPEP1 Inhibits Tumor Cell Invasiveness, Enhances Chemosensitivity and Predicts Clinical Outcome in Pancreatic Ductal Adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal cancers worldwide. To identify biologically relevant genes with prognostic and therapeutic significance in PDAC, we first performed the microarray gene-expression profiling in 45 matching pairs of tumor and adjacent non-tumor tissues from resected PDAC cases. We identified 36 genes that were associated with patient outcome and also differentially expressed in tumors as compared with adjacent non-tumor tissues in microarray analysis. Further evaluation in an independent validation cohort (N = 27) confirmed that DPEP1 (dipeptidase 1) expression was decreased (T: N ratio ∼0.1, P<0.01) in tumors as compared with non-tumor tissues. DPEP1 gene expression was negatively correlated with histological grade (Spearman correlation coefficient = −0.35, P = 0.004). Lower expression of DPEP1 in tumors was associated with poor survival (Kaplan Meier log rank) in both test cohort (P = 0.035) and validation cohort (P = 0.016). DPEP1 expression was independently associated with cancer-specific mortality when adjusted for tumor stage and resection margin status in both univariate (hazard ratio = 0.43, 95%CI = 0.24–0.76, P = 0.004) and multivariate analyses (hazard ratio = 0.51, 95%CI = 0.27–0.94, P = 0.032). We further demonstrated that overexpression of DPEP1 suppressed tumor cells invasiveness and increased sensitivity to chemotherapeutic agent Gemcitabine. Our data also showed that growth factor EGF treatment decreased DPEP1 expression and MEK1/2 inhibitor AZD6244 increased DPEP1 expression in vitro, indicating a potential mechanism for DPEP1 gene regulation. Therefore, we provide evidence that DPEP1 plays a role in pancreatic cancer aggressiveness and predicts outcome in patients with resected PDAC. In view of these findings, we propose that DPEP1 may be a candidate target in PDAC for designing improved treatments.
Use of ibandronate in the prevention of skeletal events in metastatic breast cancer

Bone metastasis from breast cancer often cause significant morbidity including pain, impaired mobility, pathological fracture, and spinal cord compression. Bisphosphonates play an important role in preventing these skeletal related events and are the standard of care for patients with bone metastasis from breast cancer. Ibandronate is a highly potent bisphosphonate available in both intravenous and oral preparations. It has been shown in clinical trials to be effective in reducing skeletal complications and also significantly improve quality of life up to 96 weeks. Unlike other intravenous bisphosphonates, ibandronate has minimal renal toxicity, allowing safe outpatient administration, reducing the need for hospital attendance and safety monitoring. Early trials have shown ibandronate may also be effective in high doses for palliation of opioid-resistant pain from bone metastasis, and as a second-line agent in patients developing a skeletal complication whilst receiving another bisphosphonate.
A Ca. 2.8‐Ga Plume‐Induced Intraoceanic Arc System in the Eastern North China Craton

The conversion of Archean tectonic regimes from mantle plume to plate tectonic and the mechanism of subduction initiation are two crucial issues in the current Earth sciences. A typical komatiite‐tholeiite sequence consisting of ~2,850–2,800‐Ma komatiites and ~2,780–2,710‐Ma basaltic and andesitic to dacitic volcanic rocks is well preserved in the Archean Western Shandong terrane of the eastern North China Craton. These volcanic rocks were derived from the partial melting of a depleted mantle source with subsequent fractional crystallization, a metasomatized subarc mantle wedge, and a descending oceanic slab. Structural and kinematic observations suggest that the Qixingtai‐Yanlinguan‐Panchegou granite‐greenstone belt experienced ~2.85–2.80‐Ga extensional deformation (D1) by upwelling of a mantle plume and NE‐SW‐oriented shortening (D2) during ~2.78–2.71 Ga. The petrogenesis of the Mesoarchean to early Neoarchean metamorphosed volcanic rock series and regional deformation indicate that a plume‐induced self‐sustaining intraoceanic arc system with SW‐dipping subduction polarity operated ~2.8 Ga, followed by the evolution from initial to mature subduction. An increasing pull caused by the descending slab generated gravitational instability in the surrounding oceanic lithosphere and formation of a new initial subduction zone adjacent to the preexisting arc system. Similar to the process in the Western Shandong terrane, plume activity generally culminated in subduction events in many other Archean greenstone belts, revealing that plume‐arc interaction may have been a crucial mechanism for global Archean tectonic regime conversion from mantle plume to initial plate subduction in the crust of the early Earth.
NEGATIVE MATERNAL EFFECT REVISITED: A TEST ON TWO POPULATIONS OF ORCHESELLA CINCTA L. (COLLEMBOLA: ENTOMOBRYIDAE)

A Dutch population of Orchesella cincta had been demonstrated to exhibit a negative maternal effect on age at first reproduction, which caused alternation of short and long generations. The adaptive significance of such a mechanism was assumed to be associated with the bivoltine life cycle of Dutch O. cincta. We expected that it would be absent in a non bivoltine population sampled in Siena, Italy. To test this hypothesis we performed a parent‐offspring regression experiment with both populations simultaneously. The experiment showed that there was no negative maternal effect in both populations. We leave open the question of the cause of the discrepancy between the previous result with the Dutch population and the present result. The results of our experiment were also used to determine heritabilities of the traits age, mass and number of molts at first reproduction, and size of the first clutch. The estimates of heritabilities were often not significantly different from zero, especially in the Italian population which had only one significant heritability.
Evolutionary learning with kernels: a generic solution for large margin problems

In this paper we embed evolutionary computation into statistical learning theory. First, we outline the connection between large margin optimization and statistical learning and see why this paradigm is successful for many pattern recognition problems. We then embed evolutionary computation into the most prominent representative of this class of learning methods, namely into Support Vector Machines (SVM). In contrast to former applications of evolutionary algorithms to SVMs we do not only optimize the method or kernel parameters. We rather use both evolution strategies and particle swarm optimization in order to directly solve the posed constrained optimization problem. Transforming the problem into the Wolfe dual reduces the total runtime and allows the usage of kernel functions. Exploiting the knowledge about this optimization problem leads to a hybrid mutation which further decreases convergence time while classification accuracy is preserved. We will show that evolutionary SVMs are at least as accurate as their quadratic programming counterparts on six real-world benchmark data sets. The evolutionary SVM variants frequently outperform their quadratic programming competitors. Additionally, the proposed algorithm is more generic than existing traditional solutions since it will also work for non-positive semidefinite kernel functions and for several, possibly competing, performance criteria.
Prevalent Involvement of Illegitimate V(D)J Recombination in Chromosome 9p21 Deletions in Lymphoid Leukemia*

To understand molecular pathways underlying 9p21 deletions, which lead to inactivation of the p16/CDKN2A, p14/ARF, and/or p15/CDKN2B genes, in lymphoid leukemia, 30 breakpoints were cloned from 15 lymphoid leukemia cell lines. Seventeen (57%) breakpoints were mapped at five breakpoint cluster sites, BCS-LL1 to LL5, each of <15 bp. Two breakpoint cluster sites were located within the ARF and CDKN2Bloci, respectively, whereas the remaining three were located >100 kb distal to the CDKN2A, ARF, andCDKN2B loci. The sequences of breakpoint junctions indicated that deletions in the 11 (73%) cell lines were mediated by illegitimate V(D)J recombination targeted at the five BCS-LL and six other sites, which contain sequences similar to recombination signal sequences for V(D)J recombination. An extrachromosomal V(D)J recombination assay indicated that BCS-LL3, at which the largest number of breakpoints (i.e. five breakpoints) was clustered, has a V(D)J recombination potential 150-fold less than the consensus recombination signal sequence. Three other BCS-LLs tested also showed V(D)J recombination potential, although it was lower than that of BCS-LL3. These results indicated that illegitimate V(D)J recombination, which was targeted at several ectopic recombination signal sequences widely distributed in 9p21, caused a large fraction of 9p21 deletions in lymphoid leukemia.
Pluralist action research: a review of the information systems literature *

Action research (AR) has for many years been promoted and practised as one way to conduct field studies within the information systems (IS) discipline. Based on a review of articles published in leading journals, we explore how IS researchers practise AR. Our review suggests that AR lends itself strongly towards pluralist approaches which facilitate the production of both theoretical and practical knowledge. First, on the level of each study we analyse how research and problem‐solving activities are mixed, in three ways: the research dominant, the problem‐solving dominant and the interactive approaches. Second, in the context of the wider research programme in which the study is situated, we analyse how AR is mixed with other research methods, in two ways: the dominant and the sequential approaches. We argue that these pluralist practices of mixing types of research activities and types of research methods provide IS action researchers with a rich portfolio of approaches to knowledge production. This portfolio helps them address the risks involved in AR to ensure their efforts contribute to the literature as well as to practical problem‐solving.
Beyond the Cortical Column: Abundance and Physiology of Horizontal Connections Imply a Strong Role for Inputs from the Surround

Current concepts of cortical information processing and most cortical network models largely rest on the assumption that well-studied properties of local synaptic connectivity are sufficient to understand the generic properties of cortical networks. This view seems to be justified by the observation that the vertical connectivity within local volumes is strong, whereas horizontally, the connection probability between pairs of neurons drops sharply with distance. Recent neuroanatomical studies, however, have emphasized that a substantial fraction of synapses onto neocortical pyramidal neurons stems from cells outside the local volume. Here, we discuss recent findings on the signal integration from horizontal inputs, showing that they could serve as a substrate for reliable and temporally precise signal propagation. Quantification of connection probabilities and parameters of synaptic physiology as a function of lateral distance indicates that horizontal projections constitute a considerable fraction, if not the majority, of inputs from within the cortical network. Taking these non-local horizontal inputs into account may dramatically change our current view on cortical information processing.
SEALDH-II—An Autonomous, Holistically Controlled, First Principles TDLAS Hygrometer for Field and Airborne Applications: Design–Setup–Accuracy/Stability Stress Test

Instrument operation in harsh environments often significantly impacts the trust level of measurement data. While commercial instrument manufacturers clearly define the deployment conditions to achieve trustworthy data in typical standard applications, it is frequently unavoidable in scientific field applications to operate instruments outside these commercial standard application specifications. Scientific instrumentation, however, is employing cutting-edge technology and often highly optimized but also lacks long-term field tests to assess the field vs. laboratory performance. Recently, we developed the Selective Extractive Laser Diode Hygrometer (SEALDH-II), which addresses field and especially airborne applications as well as metrological laboratory validations. SEALDH-II targets reducing deviations between airborne hygrometers (currently up to 20% between the most advanced hygrometers) with a new holistic, internal control and validation concept, which guarantees the transfer of the laboratory performance into a field scenario by capturing more than 80 instrument internal “housekeeping” data to nearly perfectly control SEALDH-II’s health status. SEALDH-II uses a calibration-free, first principles based, direct Tuneable Diode Laser Absorption Spectroscopy (dTDLAS) approach, to cover the entire atmospheric humidity measurement range from about 3 to 40,000 ppmv with a calculated maximum uncertainty of 4.3% ± 3 ppmv. This is achieved not only by innovations in internal instrument monitoring and design, but also by active control algorithms such as a high resolution spectral stabilization. This paper describes the setup, working principles, and instrument stabilization, as well as its precision validation and long-term stress tests in an environmental chamber over an environmental temperature and humidity range of ΔT = 50 K and ΔRH = 80% RH, respectively.
Neurostimulation for Drug-Resistant Epilepsy

Purpose of Review: The purpose of this review is to provide an evidence-based update on the neurostimulation options available for patients with drug-resistant epilepsy in the United States and in European countries.Recent Findings: The field of neurostimulation for epilepsy has grown dramatically since 1997, when vagus nerve stimulation became the first device to be approved for epilepsy by the US Food and Drug Administration (FDA). New data from recently completed randomized controlled trials are available for deep brain stimulation of the anterior thalamus, responsive neurostimulation, and trigeminal nerve stimulation. Although vagus nerve stimulation is the only device currently approved in the United States, deep brain stimulation and responsive neurostimulation devices are awaiting FDA approval. Deep brain stimulation, trigeminal nerve stimulation, and transcutaneous vagus nerve stimulation are now approved for epilepsy in the European Union. In this article, the mechanisms of action, safety, and efficacy of new neurostimulation devices are reviewed, and the key advantages and disadvantages of each are discussed.Summary: The exponential growth of the field of neuromodulation for epilepsy is an exciting development; these new devices provide physicians with new options for patients with drug-resistant epilepsy.
Bootstrapping the Recognition and Anaphoric Linking of Named Entities in Drosophila Articles

This paper demonstrates how Drosophila gene name recognition and anaphoric linking of gene names and their products can be achieved using existing information in FlyBase and the Sequence Ontology. Extending an extant approach to gene name recognition we achieved a F-score of 0.8559, and we report a preliminary experiment using a baseline anaphora resolution algorithm. We also present guidelines for annotation of gene mentions in texts and outline how the resulting system is used to aid FlyBase curation.
Altered Expression of ZnT10 in Alzheimer's Disease Brain

There is an increasing body of evidence suggesting that metal homeostasis is dysregulated in the pathology of Alzheimer's disease (AD). Although expression levels of several transporters belonging the SLC30 family, which comprises predominantly zinc transporters, have been studied in the AD brain, SLC30A10 (ZnT10) has not been studied in this context. To determine if dysregulated expression of ZnT10, which may transport both Zn and Mn, could be a factor that contributes to AD, we investigated if there were differences in ZnT10 mRNA levels in specimens of frontal cortex from AD patients and controls and also if brain tissue from the APP/PS1 transgenic (Tg) mouse model showed abnormal levels of ZnT10 mRNA expression. Our results show that ZnT10 is significantly (P<0.01) decreased in the frontal cortex in AD. Furthermore, we observed a significant decrease in ZnT10 mRNA levels in the APP/PS1-Tg mice compared with wild-type controls (P<0.01). Our results suggest that this dysregulation in ZnT10 could further contribute to disease progression.
Optimal Policy Replay: A Simple Method to Reduce Catastrophic Forgetting in Target Incremental Visual Navigation

Visual navigation is a critical task in robotics and artificial intelligence. In recent years, reinforcement learning-based approaches have gained popularity for visual navigation. However, existing methods lack flexibility in learning multiple navigation targets and suffer from catastrophic forgetting. To address these challenges, we propose a novel paradigm called “target incremental visual navigation” and introduce a method called Optimal Policy Replay (OPR). Target incremental visual navigation aims to study the performance of visual navigation in continuous learning of navigation targets. OPR enables continuous learning of navigation targets without the need for relearning all targets. Our method divides the learning process into on-policy and off-policy stages and stores only the optimal experiences in memory. Experimental results show that OPR effectively alleviates catastrophic forgetting and achieves good performance with a small memory size.
Combining CNNs for the Detection of Diabetic Retinopathy

Diabetes is a major public health issue that affects approximately forty million individuals in the United States alone. A common side effect of diabetes is vision loss and blindness caused by diabetic retinopathy (DR). The goal of this research is to introduce a robust deep learning approach for the early detection of DR from retinal images into five categories namely No DR, Mild DR, Moderate DR, Severe DR, Non-Proliferative DR. Here, we propose a fusion of CNNs with an optimal weighting scheme to improve classification accuracy. The dataset used is Kaggle APTOS 2019 and for cross dataset validation we used IDRiD dataset. The proposed weighted twin CNN algorithm is implemented using a pair of pre-trained deep networks namely the DenseNet-169 and the InceptionV3. Such a hybrid combination provided a robust and an optimized architecture. A total of 98.43% sensitivity and 88.78% specificity are recorded with a Kappa score and accuracy of 95.8% and 94.3%. Our research has achieved a significant 11.90% improvement as compared to state of the art, showcasing remarkable performance in this field.