Miracle-dz/UniFAR-FTUs huggingface dataset:
The Logic of Vulnerability and Civilian Victimization: Shifting Front Lines in Italy (1943–1945)

abstract:What causes civilian victimization in conventional civil wars and in conventional wars that experience insurgencies? The authors argue that a key driver of civilian victimization is the vulnerability of the incumbent forces, specifically when the conflict's front line is shifting. Vulnerability is a function of informational and logistical challenges: when the front line is moving, incumbents face increased informational uncertainty and unstable supply chains that augment their vulnerability. Thus, incumbents will increase the use of civilian victimization in response to a scarcity of high-quality information on the location and identity of insurgents, to limit possible information leaks, and to contain supply disruption and logistics support to adversaries. The authors support their argument using matched difference-in-differences analyses of original subnational data on Nazi-Fascist violence in World War II Italy (1943–1945) and qualitative evidence.
Metabolic reprogramming of donor T cells enhances graft-versus-leukemia effects in mice and humans

Bicarbonate boosts metabolic fitness of T cells challenged with leukemia-derived lactic acid. A basic treatment for leukemia For patients with acute myeloid leukemia, hematopoietic stem cell transplant offers a chance of curing the underlying cancer, in part because of the graft-versus-leukemia effect, or anticancer activity of transplanted T cells. Unfortunately, this does not always work, and engrafted T cells often fail to control the leukemia. By studying patients with acute myeloid leukemia who relapsed after hematopoietic stem cell transplant, Uhl et al. found that lactic acid produced by leukemic cells specifically interfered with T cell activity. The detrimental effects of lactic acid could be overcome with sodium bicarbonate, which improved T cell metabolic fitness in both mouse models and human patients. Acute myeloid leukemia (AML) relapse after allogeneic hematopoietic cell transplantation (allo-HCT) has a dismal prognosis. We found that T cells of patients relapsing with AML after allo-HCT exhibited reduced glycolysis and interferon-γ production. Functional studies in multiple mouse models of leukemia showed that leukemia-derived lactic acid (LA) interfered with T cell glycolysis and proliferation. Mechanistically, LA reduced intracellular pH in T cells, led to lower transcription of glycolysis-related enzymes, and decreased activity of essential metabolic pathways. Metabolic reprogramming by sodium bicarbonate (NaBi) reversed the LA-induced low intracellular pH, restored metabolite concentrations, led to incorporation of LA into the tricarboxylic acid cycle as an additional energy source, and enhanced graft-versus-leukemia activity of murine and human T cells. NaBi treatment of post–allo-HCT patients with relapsed AML improved metabolic fitness and interferon-γ production in T cells. Overall, we show that metabolic reprogramming of donor T cells is a pharmacological strategy for patients with relapsed AML after allo-HCT.
Gaming Tasks as a Method for Studying the Impact of Warning Messages on Information Behavior

Abstract:New and nontraditional approaches are required to effectively tackle the global problem of cybercrime. Online warning messages offer the unique potential to influence information behavior at the exact point of user decision-making. This research assessed the prevention effect of differing components of warning messages. Thirty-five male participants, aged 18–43, participated in a behavioral-compliance task comprising messages received when visiting websites likely to contain malware. Participants also rated messages on believability, severity, and effects on intention to comply. The components of messages tested were as follows: three "signal words" (warning, hazard, and stop), two levels of message explicitness (high, low), and two imagery conditions (eyes, no eyes). Contrary to expectations, explicitness was the only message component to yield a significant preventative effect on self-rated and behavioral responses. Participants not only perceived the explicit messages as more believable, severe, and likely to increase intention to comply but also demonstrated, through their behavioral-compliance data, a preventative effect from more explicit messages. The implications of these findings for designing messages to prevent cybercrimes are explored.
Feature extraction based on deep‐convolutional neural network for face recognition

Feature extraction is a critical technology that affects the accuracy of face recognition. However, certain features are highly related to changes in face are difficult to extract because of the influences of individual differences and illumination. Therefore, features can accurately describe the changes in face are urgently required. For this reason, this article proposes a feature extraction method based on deep learning. This method combines the features extracted by Local Binary Patterns and by Convolutional Neural Network convolutional layer in the network connection layer, thus obtaining classification features with high representation ability and solving the problem of single feature extraction. The VGG‐16 network proposed in this article has been improved by changing the framework structure. Some experiments based on the Labeled Faces in the Wild dataset are performed, and results show that, in terms of accuracy and the sensitivity to light, the proposed method reaches 99.56% and 80.35% respectively. The recognition results obtained from fused features are superior to which of single feature recognition. Simulation results show that the method is more robust to changes in the illumination condition and more efficient than the existing methods.
A novel data partitioning algorithm for dynamic energy optimization on heterogeneous high‐performance computing platforms

Energy is one of the most important objectives for optimization on modern heterogeneous high‐performance computing (HPC) platforms. The tight integration of multicore CPUs with accelerators such as graphical processing units (GPUs) and Xeon Phi coprocessors in these platforms presents several challenges to the optimization of multithreaded data‐parallel applications for energy. In this work, the problem of optimization of data‐parallel applications on heterogeneous HPC platforms for dynamic energy through workload distribution is formulated. We propose a workload partitioning algorithm to solve this problem. It employs load‐imbalancing technique to determine the workload distribution minimizing the dynamic energy consumption of the parallel execution of an application. The inputs to the algorithm are discrete dynamic energy profiles of individual computing devices. The profiles are practically constructed using an approach that accurately models the energy consumption by execution of a hybrid scientific data‐parallel application on a heterogeneous platform containing different computing devices such as CPU, GPU, and Xeon Phi. The proposed algorithm is experimentally analyzed using two multithreaded data‐parallel applications, matrix multiplication and 2D fast Fourier transform. The load‐imbalanced solutions provided by the algorithm achieve significant dynamic energy reductions for the two applications (in average by 130% and 44%, respectively) compared with the load‐balanced solutions.
Logic-based Machine Learning for Transparent Ethical Agents

Autonomous intelligent agents are increasingly engaging in human communities. Thus, they must be expected to follow social and ethical norms of the community in which they are deployed in. In this work we present an approach for developing such ethical agents which are able to develop ethical decision making and judgment capabilities by learning from interactions with the users. Our approach is a logic-based approach and the resulting ethical agents are transparent by design.
Re-analysis of Genetic Risks for Chronic Fatigue Syndrome From 23andMe Data Finds Few Remain

It is tempting to mine the abundance of DNA data that is now available from direct-to-consumer genetic tests, but this approach has its pitfalls A recent study put forth a list of 50 single nucleotide polymorphisms (SNPs) that predispose to Chronic Fatigue Syndrome (CFS), a potentially major advance in understanding this still mysterious disease. However, only the patient cohort data came from a commercial company (23andMe) while the control was a genetic database. The extent to which 23andMe data agree with genetic reference databases is unknown. We reanalyzed the 50 purported CFS SNPs by comparing to control data from 23andMe which are available through public platform OpenSNP. In addition, large high-quality database ALFA was used as an additional control. The analysis lead to dramatic change with the top of the leaderboard for CFS risk reduced and reversed from an astronomical 129,000 times to 0.8. Errors were found both within 23andMe data and the original study-reported Kaviar database control. Only 3 of 50 SNPs survived initial study criterion of at least twice as prevalent in patients, EFCAB4B involving calcium ion channel, LINC01171, and MORN2 genes. We conclude the reported top-50 deleterious polymorphisms for Chronic Fatigue Syndrome were more likely the top-50 errors in the 23andMe and Kaviar databases. In general, however, correlation of 23andMe control with ALFA was a respectable 0.93, suggesting an overall usefulness of 23andMe results for research purposes but only if caution is taken with chips and SNPs.
Sur la nomenclature de quelques Theileria (Sporozoa, Babesioidea) des ruminants domestiques

La terminologie en usage pour les Theileria du betail devrait etre modifiee sur les points suivants: le nouveau nom de Th. lestoquardi est propose pour designer la theilerie maligne des petits ruminants; l'agent de la theileriose benigne des bovins d'Eurasie et d'Australie doit etre denomme Th. orientalis (Yakimov et Sudachenkov, 1931)
Bridging the gap between an ontology and deep neural models by pattern mining

A domain ontology (DO) is a machine-readable knowledge repository compatible with the popular knowledge graph (KG) format. An intriguing question is how to leverage a DO plus a KG in a neural learning process. We propose to use ontology-rooted graph patterns mined from a DO-compatible graph translation of the raw data as a vector for injecting some domain knowledge into the neural network. Such patterns represent a frequently occurring regularities in the data yet they are expressed in terms of the ontological entities (classes, properties, etc.) and reﬂect additional knowledge from the KG. Using them as an additional input to the learning process seems a promising way to guide it towards improved explain-ability, accuracy and convergence, as well as, in a more general vein, increase the generalization power of the neural models.
Diversity and Structure of Bacterial Communities in the Gut of Spider: Thomisidae and Oxyopidae

The gut microbiomes of insects were known to have great impact on their physiological properties for survival like nutrition, behavior, and health. In nature, spiders are one of the main predators of insects, and yet their gut microbiomes remain unclear. It is important to explore the gut microbiomes of spiders in the wild to gain an insight on the host–bacterial relationship. Here, we studied the diversity and structure of gut bacterial communities of seven spider species belonging to two families, i.e., Thomisidae and Oxyopidae, from different states of India. Our data revealed a total of 16 bacterial phyla with Proteobacteria as the predominant group in Thomisidae and Firmicutes in Oxyopidae. The core bacterial communities in the spider guts include the genera of Acinetobacter, Staphylococcus, Corynebacterium, Cutibacterium, and Pseudomonas. The genus Paraclostridium was observed for the first time and only in one spider species, i.e., Peucetia viridans. Our data also indicated a higher gut bacterial community similarity between spider species belonging to Thomisidae as compared to those belonging to Oxyopidae bacteria. Furthermore, PICRUSt2 analysis predicted the presence of nine active functional metabolic pathways related to the metabolism of fatty acids and sugar, degradation of organic compounds, and biosynthesis of vitamin E.
Updates on pediatric sepsis

Sepsis, defined as an infection with dysregulated host response leading to life‐threatening organ dysfunction, continues to carry a high potential for morbidity and mortality in children. The recognition of sepsis in children in the emergency department (ED) can be challenging, related to the high prevalence of common febrile infections, poor specificity of discriminating features, and the capacity of children to compensate until advanced stages of shock. Sepsis outcomes are strongly dependent on the timeliness of recognition and treatment, which has led to the successful implementation of quality improvement programs, increasing the reliability of sepsis treatment in many US institutions. We review clinical, laboratory, and technical modalities that can be incorporated into ED practice to facilitate the recognition, treatment, and reassessment of children with suspected sepsis. The 2020 updated pediatric sepsis guidelines are reviewed and framed in the context of ED interventions, including guidelines for antibiotic administration, fluid resuscitation, and the use of vasoactive agents. Despite a large body of literature on pediatric sepsis epidemiology in recent years, the evidence base for treatment and management components remains limited, implying an urgent need for large trials in this field. In conclusion, although the burden and impact of pediatric sepsis remains substantial, progress in our understanding of the disease and its management have led to revised guidelines and the available data emphasizes the importance of local quality improvement programs.
Bone-Conducted oVEMP Latency Delays Assist in the Differential Diagnosis of Large Air-Conducted oVEMP Amplitudes

Background: A sensitive test for Superior Semicircular Canal Dehiscence (SCD) is the air-conducted, ocular vestibular evoked myogenic potential (AC oVEMP). However, not all patients with large AC oVEMPs have SCD. This retrospective study sought to identify alternate diagnoses also producing enlarged AC oVEMPs and investigated bone-conducted (BC) oVEMP outcome measures that would help differentiate between these, and cases of SCD. Methods: We reviewed the clinical records and BC oVEMP results of 65 patients (86 ears) presenting with dizziness or balance problems who underwent CT imaging to investigate enlarged 105 dB nHL click AC oVEMP amplitudes. All patients were tested with BC oVEMPs using two different stimuli (1 ms square-wave pulse and 8 ms 125 Hz sine wave). Logistic regression and odds ratios were used to determine the efficacy of BC oVEMP amplitudes and latencies in differentiating between enlarged AC oVEMP amplitudes due to dehiscence from those with an alternate diagnosis. Results: Fifty-three ears (61.6%) with enlarged AC oVEMP amplitudes were identified as having frank dehiscence on imaging; 33 (38.4%) had alternate diagnoses that included thinning of the bone covering (near dehiscence, n = 13), vestibular migraine (n = 12 ears of 10 patients), enlarged vestibular aqueduct syndrome (n = 2) and other causes of recurrent episodic vertigo (n = 6). BC oVEMP amplitudes of dehiscent and non-dehiscent ears were not significantly different (p > 0.05); distributions of both groups overlapped with the range of healthy controls. There were significant differences in BC oVEMP latencies between dehiscent and non-dehiscent ears for both stimuli (p < 0.001). A prolonged n1 125 Hz latency (>11.5 ms) was the best predictor of dehiscence (odd ratio = 27.8; 95% CI:7.0-111.4); abnormal n1 latencies were identified in 79.2% of ears with dehiscence compared with 9.1% of ears without dehiscence. Conclusions: A two-step protocol of click AC oVEMP amplitudes and 125 Hz BC oVEMP latency measures optimizes the specificity of VEMP testing in SCD.
Electrochemistry of Graphene Nanoplatelets Printed Electrodes for Cortical Direct Current Stimulation

Possible risks stemming from the employment of novel, micrometer-thin printed electrodes for direct current neural stimulation are discussed. To assess those risks, electrochemical methods are used, including cyclic voltammetry, square-wave voltammetry, and electrochemical impedance spectroscopy. Experiments were conducted in non-deoxidized phosphate-buffered saline to better emulate living organism conditions. Since preliminary results obtained have shown unexpected oxidation peaks in 0–0.4 V potential range, the source of those was further investigated. Hypothesized redox activity of printing paste components was disproven, supporting further development of proposed fabrication technology of stimulating electrodes. Finally, partial permeability and resulting electrochemical activity of underlying silver-based printed layers of the device were pointed as the source of potential tissue irritation or damage. Employing this information, electrodes with corrected design were investigated, yielding no undesired redox processes.
Intratumor Heterogeneity of MYO18A and FBXW7 Variants Impact the Clinical Outcome of Stage III Colorectal Cancer

Many studies failed to demonstrate benefit from the addition of targeted agents to current standard adjuvant FOLFOX chemotherapy in stage III colorectal cancer (CRC) patients. Intratumor heterogeneity may foster the resistant subclones and leads to cancer recurrence. Here, we built a cancer evolution model and applied machine learning analysis to identify potential therapeutic targets. Among 78 CRC cases, whole-genome (WGS) and deep targeted sequencing data generated from paired blood and primary tumor were used for phylogenetic tree reconstruction. Genetic alterations in the PI3K/AKT, and RTK oncogenic signaling pathways were commonly detected in founding clones. The dominant subclones frequently exhibited dysregulations in the TP53, FBXW7/NOTCH1 tumor suppression, and DNA repair pathways. Fourteen genetic mutations were simultaneously selected by random forest and LASSO methods. The logistic regression model had better accuracy (79%), precision (70%), and recall (65%) and area under the curve (AUC) (82%) for cancer recurrence prediction. Three genes, including MYO18A in the founding clone, FBXW7, and ATM in the dominant subclone, affected the prognosis were selected simultaneously by different feature sets. The in vitro studies, HCT-116 cells transfected with MYO18A siRNA demonstrated a significant reduction in cell migration activity by 20–40%. These results indicate that MYO18A plays a crucial role in the migration of human CRC cells. The cancer evolution model revealed the critical mutations in the founding and dominant subclones. They can be used to predict clinical outcomes and the development of novel therapeutic targets for stage III CRC.
Toward a Better Understanding of Bioassays for the Development of Biopharmaceuticals by Exploring the Structure-Antibody-Dependent Cellular Cytotoxicity Relationship in Human Primary Cells

Pharmaceutical manufacturing relies on rigorous methods of quality control of drugs and in particular of the physico-chemical and functional characterizations of monoclonal antibodies. To that end, robust bioassays are very often limited to reporter gene assays and the use of immortalized cell lines that are supposed to mimic immune cells such as natural killer (NK) cells to the detriment of primary materials, which are appreciated for their biological validity but are also difficult to exploit due to the great diversity between individuals. Here, we characterized the phenotype of the peripheral blood circulating cytotoxic cells of 30 healthy donors, in particular the repertoire of cytotoxic markers, using flow cytometry. In parallel, we characterized the antibody-dependent cellular cytotoxicity (ADCC) effector functions of these primary cells by measuring their cytolytic activity against a cancer cell-line expressing HER2 in the presence of trastuzumab and with regards to FCGR3A genotype. We could not establish a correlation or grouping of individuals using the data generated from whole peripheral blood mononuclear cells, however the isolation of the CD56-positive population, which is composed not only of NK cells but also of natural killer T (NKT) and γδ-T cells, as well as subsets of activated cytotoxic T cells, monocytes and dendritic cells, made it possible to standardize the parameters of the ADCC and enhance the overall functional avidity without however eliminating the inter-individual diversity. Finally, the use of primary CD56+ cells in ADCC experiments comparing glycoengineered variants of trastuzumab was conclusive to test the limits of this type of ex vivo system. Although the effector functions of CD56+ cells reflected to some extent the in vitro receptor binding properties and cytolytic activity data using NK92 cells, as previously published, reaching a functional avidity plateau could limit their use in a quality control framework.
Unfavorable Contribution of a Tissue-Engineering Cartilage Graft to Osteochondral Defect Repair in Young Rabbits

A stem cell-based tissue-engineering approach is a promising strategy for treatment of cartilage defects. However, there are conflicting data in the feasibility of using this approach in young recipients. A young rabbit model with an average age of 7.7 months old was used to evaluate the effect of a tissue-engineering approach on the treatment of osteochondral defects. Following in vitro evaluation of proliferation and chondrogenic capacity of infrapatellar fat pad-derived stem cells (IPFSCs) after expansion on either tissue culture plastic (TCP) or decellularized extracellular matrix (dECM), a premature tissue construct engineered from pretreated IPFSCs was used to repair osteochondral defects in young rabbits. We found that dECM expanded IPFSCs exhibited higher proliferation and chondrogenic differentiation compared to TCP expanded cells in both pellet and tissue construct culture systems. Six weeks after creation of bilateral osteochondral defects in the femoral trochlear groove of rabbits, the Empty group (left untreated) had the best cartilage resurfacing with the highest score in Modified O’Driscoll Scale (MODS) than the other groups; however, this score had no significant difference compared to that of 15-week samples, indicating that young rabbits stop growing cartilage once they reach 9 months old. Interestingly, implantation of premature tissue constructs from both dECM and TCP groups exhibited significantly improved cartilage repair at 15 weeks compared to those at six weeks (about 9 months old), indicating that a tissue-engineering approach is able to repair adult cartilage defects. We also found that implanted pre-labeled cells in premature tissue constructs were undetectable in resurfaced cartilage at both time points. This study suggests that young rabbits (less than 9 months old) might respond differently to the classical tissue-engineering approach that is considered as a potential treatment for cartilage defects in adult rabbits.