Miracle-dz/UniFAR-FTUs huggingface dataset:
Spatio‐temporal connectivity: assessing the amount of reachable habitat in dynamic landscapes

Landscape heterogeneity and habitat connectivity affect species movements, playing an important role in determining the likelihood of species persistence. However, landscape connectivity is usually evaluated using static snap‐shots, which do not account for the sequential interactions among habitat patches through time. We developed a network‐based model of landscape dynamics, and corresponding connectivity metrics, to account for the reachable habitat across space and time. We illustrate the behaviour of these metrics, using fragmented forested landscapes in the Atlantic Forest of Brazil. We parametrized the models using the dispersal capacities of selected bird and small mammal species. We found that when considering spatio‐temporal links, connectivity is estimated to be on average 30% higher (with a maximum of 150% higher) than what is estimated from purely spatial models. This higher degree of spatio‐temporal connectivity arises due to connections through temporal stepping‐stone patches that appear (habitat gain) and disappear (habitat loss) over time. Species with short dispersal distances (<1000 m) particularly benefited from the spatio‐temporal connections. The contribution of spatio‐temporal connectivity to habitat reachability increased with higher habitat loss rates. Moreover, it depended on the amount of habitat in the landscape, being higher at intermediate habitat amounts (∼30%). We showed that accounting for spatio‐temporal connectivity is critical for understanding ecological patterns and processes in dynamic landscapes, and that a series of purely spatial connectivity metrics underestimates the actual connectivity patterns across time. The proposed spatio‐temporal connectivity approach and metrics can be applied to evaluate the effective connectivity patterns and trends in a variety of dynamic landscapes, avoiding the potential overestimates of population isolation and extinction probabilities that may result from widely used purely spatial connectivity models.
Modifiable Predictors of Supported Employment Outcomes Among People With Severe Mental Illness.

OBJECTIVE Among people with severe mental illnesses, neuropsychological abilities may contribute to vocational outcomes, such as job attainment, job tenure, and wages earned. The current study aimed to determine the strongest neuropsychological and other modifiable predictors of work outcomes in 153 people with severe mental illness (schizophrenia, 38%; bipolar disorder, 24%; and major depression, 38%) who participated in a 2-year supported employment study. METHODS Assessments of neuropsychological performance, functional capacity, social skills, and psychiatric symptom severity were administered at baseline; work outcomes (job attainment, weeks worked, and wages earned) were collected weekly for 2 years. RESULTS Independent of education, diagnosis, and estimated intellectual functioning, more recent work history and less severe negative symptoms significantly predicted job attainment during the 2-year study. Among the 47% who obtained jobs, better global neuropsychological performance (i.e., lower global deficit score) was a significant predictor of greater weeks worked. Both global neuropsychological performance and more recent work history predicted higher wages earned. CONCLUSIONS Modifiable predictors of supported employment outcomes included cognitive functioning and negative symptom severity; thus, interventions to improve these factors may improve work outcomes and decrease the loss of productivity associated with severe mental illness.
PERFORMANCE COMPARISON OF DRAGONFLY AND FIREFLY ALGORITHM IN THE RFID NETWORK TO IMPROVE THE DATA TRANSMISSION 1

RFID (Radio Frequency Identification) network is used for sensing and tracking the objects. The main flaw in this network is reader collision which leads to redundant data. Consequently, due to dissimilar mobility between a head and its member nodes causes unstable clustering. Hence, the protocol known as Dragonfly based Clustering Protocol (DCP) is proposed to minimize the frequent cluster breakage and to improve the data transmission in the network. The readers with high residual energy level are picked as an eligible cluster head. After picking the eligible head, the distance, speed and neighbor count values are calculated between the head nodes and its neighbors. The values are added and optimum cluster heads are opted if the calculated value is high. Then the other nodes join the cluster based on the movement of the head. The conclusion shows that optimal cluster heads are opted using DCP than LEACH and firefly algorithm in which mobility and neighbor count are not taken into account while picking the cluster head. The simulated result in NS2 shows that DCP protocol selects optimal cluster head and the cluster breakage is low when compared with LEACH protocol and firefly algorithm. The reading efficiency in RFID network is also improved using Dragonfly based clustering.
Side effects from acute myeloid leukemia treatment: results from a national survey

Abstract Objective: Acute myeloid leukemia (AML) is experiencing a therapeutic renaissance due to the heightened biomedical understanding of AML and patient-focused drug development (PFDD). Many AML patients now live long-term with the side effects of treatment. This study documents the prevalence and severity of AML treatment-related side effects. Methods: A national cross-sectional survey designed with the Leukemia & Lymphoma Society assessed patients’ experiences with short-term (nausea/vomiting, diarrhea, hair loss, mouth sores, infection, rash) and long-term (organ dysfunction, chemobrain, fatigue, neuropathy) treatment side effects. Patient and caregiver participants rated side effect severity (none–severe). Results: Survey participants (n = 1182) were mostly female (65%), AML patients (76%), and had undergone chemotherapy (94%). Eighty-seven per cent of participants reported severe short-term effects, and 33% reported severe long-term effects of treatment. Only 11% of respondents did not have any severe effects. Hair loss and fatigue were the most common severe short- and long-term side effects (78%, 33%). There was a moderate correlation between having short- and long-term adverse effects (r = 0.41, p < 0.001). Caregivers were more likely than patients to report severe organ dysfunction, fatigue, and neuropathy (p-values < 0.05). Conclusions: Survivors experience a high burden of side effects from AML treatments highlighting the need for the development of less toxic therapies. Differences in patients’ and caregivers’ experiences illustrate the importance of sampling from diverse sources to understand the full burden of AML treatment, and the need for less toxic drugs. This study informs patients, patient-advocacy groups, clinicians, and regulators about AML treatment burdens and provides the community with information to inform PFDD.
OpEn-Tag: a customizable optogenetic toolbox to dissect subcellular signaling.

Subcellular localization of signal molecules is a hallmark in organizing the signal network. OpEn-Tag is a modular optogenetic endomembrane targeting toolbox that allows alteration of the localization and therefore the activity of signaling processes with the spatio-temporal resolution of optogenetics. OpEn-Tag is a two-component system employing 1) a variety of targeting peptides, fused to and thereby dictating the localization of mCherry-labeled cryptochrome 2 binding protein CIBN towards distinct endomembranes and 2) the cytosolic, fluorescence-labeled blue light photoreceptor cryptochrome 2 as customizable building block that can be fused to proteins of interest. The combination of OpEn-Tag with growth factor stimulation or the use of two membrane anchor sequences allows investigation of multilayered signal transduction processes as demonstrated here for the protein kinase AKT.
Cantharidin decreased viable cell number in human osteosarcoma U-2 OS cells through G2/M phase arrest and induction of cell apoptosis

ABSTRACT Cantharidin (CTD), a sesquiterpenoid bioactive substance, has been reported to exhibit anticancer activity against various types of cancer cells. The aim of the present study was to investigate the apoptosis effects and the underlying mechanisms of CTD on osteosarcoma U-2 OS cells. Results showed that CTD induced cell morphologic changes, reduced total viable cells, induced DNA damage, and G2/M phase arrest. CTD increased the production of reactive oxygen species and Ca2+, and elevated the activities of caspase-3 and −9, but decreased the level of mitochondrial membrane potential. Furthermore, CTD increased the ROS- and ER stress-associated protein expressions and increased the levels of pro-apoptosis-associated proteins, but decreased that of anti-apoptosis-associated proteins. Based on these observations, we suggested that CTD decreased cell number through G2/M phase arrest and the induction of cell apoptosis in U-2 OS cells and CTD could be a potential candidate for osteosarcoma treatments. Graphical abstract The possible signaling pathways for CTD induced apoptosis in U-2 OS human osteosarcoma cancer cells
What Makes a Good Location in the Method of Loci: Meaningfulness of Locations and Environmental Segregation Studied with Virtual Reality

Method of Loci (MoL) is an efficient mnemonic strategy especially good for enhancing serial recall of auditorily presented material. MoL is traditionally used by imagining oneself on a familiar journey and associating to-be-remembered words or ideas with distinct locations on that journey. However, previous research has established that newly learned virtual environments are just as good as highly familiar environments. But much less is known about what makes a good location or an environment for the use of MoL. Immersive virtual reality (VR) headset was used in the experiment to study the characteristics of environments that affect the effectiveness of MoL. Two within-subject factors were varied: meaningfulness of locations (low paint on the floor, high furniture), environmental segregation (no segregation – 1 big room, with segregation – 6 small rooms). Results show that using furniture to mark locations improved memory performance. No effect of environmental segregation was found. Also, females did better than males in lenient scoring which is in line with previous research showing better objectlocation memory for females. Further research is required to see if the locations marked with paint on the floor are still better than controls without mnemonic training.
User Preference for SharpView-Enhanced Virtual Text During Non-Fixated Viewing

For optical see-through head-mounted displays, the mismatch between a display's focal length and the real world scene inadvertently prevents users from simultaneously focusing on the presented virtual content and the scene. It has been shown that it is possible to ameliorate the out-of-focus blur for images with a known focus distance, by applying an algorithm called Sharp View. However, it remains unclear if Sharp View also improves the readability and clarity of text rendered on the display. In this study, we investigate whether users reported increased text clarity when Sharp View was applied to a text label, and how the focal demand of the display, the focal distance to real world content, and gaze condition affect the result. Our results indicate that, in non-fixated viewing, there is a significant user preference for Sharp View-enhanced text strings.
Explaining Repaired Data with CFDs

Many popular data cleaning approaches are rule-based: Constraints are formulated in a logical framework, and data is considered dirty if constraints are violated. These constraints are often discovered from data, but to ascertain their validity, user verification is necessary. Since the full set of discovered constraints is typically too large for manual inspection, recent research integrates user feedback into the discovery process. We propose a different approach that employs user interaction only at the start of the algorithm: a user manually cleans a small set of dirty tuples, and we infer the constraint underlying those repairs, called an explanation . We make use of conditional functional dependencies (CFDs) as the constraint formalism. We introduce XP lode , an on-demand algorithm which discovers the best explanation for a given repair. Guided by this explanation, data can then be cleaned using state-of-the-art CFD-based cleaning algorithms. Experiments on synthetic and real-world datasets show that the best explanation can typically be inferred using a limited number of modifications. Moreover, XP lode is substantially faster than discovering all CFDs that hold on a dataset, and is robust to noise in the modifications.
Relating photosynthetic pigments and in vivo optical density spectra to irradiance for the Florida red-tide dinoflagellate Gymnodinium breve

The lipophilic pigment content and composition and in vivooptical density (OD) spectra for batch cultures of the Florida (USA) red-tide dinoflagellate Gyn~nodinium breve Davis were analyzed after exposure to irradiance treatments representative of an irradiance gradient that cells might experience in a coastal water column. Decreases in total chlorophyll (chl) content (attributable to decreasesin chls a, c,/c2 and c3) and total carotenoid content (attributable to decreases in total fucoxanthin and 19'-acylofucoxanthins, and gyroxanthin-diester) coincided with exposure to increased irradiance. The relative abundances of chl pigments remained constant whereas decreases in the relative abundances of total fucoxanthin and 19'-acylofucoxanthins, and p-v-carotene and an increase in the relative abundance of diadinoxanthin coincided with exposure to increased irradiance. Because gyroxanthin-diester has been observed only in a lim~ted number of toxic dinoflagellates (of which G. breve is the only warm-water taxon), was consistently quant~f~able throughout various irradiance-lnduced physiological states, and had a distinctive elution pos~tlon and absorption maxima in the chromatographic eluent, this carotenoid may serve as a 'biomarker' for G. breve within Florida coastal waters. An analysis of variance, performed on fourthderivative plots derived from normalized OD spectra, identified portions of the OD spectra which differed among irradiance treatments. Designated wavelengths coincided with wave crests in the fourth-derivative plots representative of absorption maxima for total chl c (460 to 468, 585 to 590 nm) and total fucoxanthin and 19'-acylofucoxanthins, and diadinoxanthin (490 to 496 nm). Stepwise discriminant analysis identified a set of 6 wavelengths (403,541,546,509,673 and 663 nm) which optimally classified OD spectra for populations among irradiance treatments. l k s lack of correspondence between wavelengths identified by the 2 statistical techniques was not unexpected; fourth-derivative analysis identified portions of the OD spectra where differences in the sharpness of curvature (as produced by absorption maxima of component pigments) occurred among treatments whereas discriminant analysis identified portions of the spectra which could be used to classify populations among treatments and did not necessarily have to correspond to absorption maxima. Such detectable differences in the bio-optical 'signatures' of G. breve indicate that previous light history, as manifested in the pigment component, could be incorporated into future pigment-based monitoring applications to allow for the detection and/or physiological characterization of problematic taxa prior to bloom status.
Rare genetic variation is important for survival in extreme low pH conditions

Population persistence through increasingly frequent extreme environmental fluctuations will require selection on standing genetic variation. While some species have shown the capacity to adapt to mean future conditions, the ability to survive and potentially adapt to extreme events is unknown. Here we used pooled capture sequencing to test for adaptive capacity and identify genetic variation responsive to moderate (pH 8.0) and extreme (pH 7.5) low pH conditions using single generation selection experiments on hundreds of thousands of Strongylocentrotus purpuratus sea urchin larvae generated from wild-caught adults. The single generation of selection showed consistent shifts in allele frequencies across replicate cultures and increased linkage disequilibrium around selected loci, revealing selective sweeps from standing variation. We found extreme pH selection targeted alleles at low frequency in the population while variants that responded to both moderate and extreme pH selection started at higher allele frequencies, suggesting maintenance by balancing selection. Variants with the greatest changes in allele frequencies performed functions related to lipid metabolism, pH tolerance, membrane trafficking, and regulation of actin/cytoskeleton dynamics. These results highlight that survival in extreme conditions relies on low frequency standing genetic variation that must be maintained by large population sizes.
Large-scale Dynamic Visualization of Multiple Comparative Genomic Data

A novel visualization technique facilitates the comparative analysis of large-scale genome data. It reveals the relationships among multiple compared genome sequences by combining three traditional and well-established representations of comparative genomic data: the dot plot, the gradient view and the linear representation of inter-genome connections. By integrating them into a single threedimensional structure and offering dynamic exploration, a significantly more powerful visualization is provided. Being able to rotate the axonometric representation of the three-dimensional data freely enables the user to easily link semantics of different representations with each other and therefore getting a deeper understanding of the sequences and their relations.
Gamification in teaching maintenance engineering: a Dutch experience in the rolling stock management learning

The aim of this study is to evaluate the application of an innovative serious game, based on the asset management of rolling stock, in the training of future maintenance engineers within the master course in mechanical engineering at the University of Twente. The Logistic Support Game (LSG) is a serious game developed together with Netherlands Railways (Nederlandse Spoorwegen, NS) and Invocate (design firm) as a tool to simulate the maintenance operations of a fleet of trains. The simulation shows four perspectives: the operations manager, the asset manager, the maintenance manager and the financial manager. The three goals of this innovative training are the improvement of student engagement in the learning process, the increas of active cooperation between students with different roles in a group, and the opportunity to receive feedback on decision making. To indicate achievement of these goals, they are linked to the basic needs of learning: competence, relatedness and autonomy. A total of thirty six students played the serious game in two different sessions. At the end of each session, a survey is collected for game based learning assessment. Results suggest that the serious game has a positive impact on student engagement, cooperation, and helps transfer course contents.
A Computational Approach To Predict A Novel MicroRNA From The Associated Genes Of Cutaneous Lichen Planus: An Initiation Towards The Discovery Of Therapeutic Biomarkers

Lichen Planus (LP) is an inflammatory mucocutaneous disease with the pathogenesis of autoimmune disorders [1, 2]. Molecular studies on LP suggest that the result of lesions were raised from a cell-mediated autoimmunity and it was directed against the keratinocytes of the basal layer of skin to the form an infiltrate with CD4 and CD8 lympocytes [3]. MicroRNAs (miRNAs) are short noncoding RNAs and it play a vital role in the physiological and pathophysiological states of cellular processes including the development, differentiation, proliferation and apoptosis [4, 5]. Micro RNAs were identified as a key player in certain inflammatory disorders [6–9]. Most of the published studies on miRNA were from the pathogenesis of Oral Lichen Abstract
Toward Autonomous Antibiotic Discovery

Machines hold the potential to replace humans in many societal endeavors, and drug discovery is no exception. Antibiotic innovation has been stalled for decades, which has coincided with an alarming increase in multidrug-resistant bacteria. ABSTRACT Machines hold the potential to replace humans in many societal endeavors, and drug discovery is no exception. Antibiotic innovation has been stalled for decades, which has coincided with an alarming increase in multidrug-resistant bacteria. Since the beginning of the antibiotic era, the natural world has been our greatest innovator, giving rise to nearly all antibiotics available today. As mere observers of the vast molecular diversity produced by Earth’s organisms, we have perfected the art of isolating novel chemistries with life-saving antimicrobial properties. However, today we are at a crossroads, as no new molecular scaffolds have been discovered for decades. We may need to look beyond the natural world into the virtual dimension for solutions and harness present-day computational power to help solve the grand global health challenge of antibiotic resistance. Computer-made drugs may enable the discovery of unprecedented functions in biological systems and help replenish our arsenal of effective antibiotics.
Symmetrical analysis of the defect level splitting in two-dimensional photonic crystals

In this paper doubly degenerate defect states in the band gap of the two-dimensional photonic crystal are studied. These states can be split by a convenient distortion of the lattice. Through analogy with the Jahn–Teller effect in solids, we present a group theoretical analysis of the lifting of the degeneracy of doubly degenerate states in a square lattice by different vibronic modes. The effect is supported by the supercell plane-wave model and by the finite difference time domain technique. We suggest ways for using the effect in photonic switching devices and waveguides.
Anticancer Therapy at the End of Life: Lessons From a Community Cancer Institute

Introduction: Studies have shown aggressive cancer care at the end of life is associated with decreased quality of life, decreased median survival, and increased cost of care. This study describes the patients most likely to receive systemic anticancer therapy at the end of life in a community cancer institute. Materials and Methods: We performed a retrospective cohort study of 201 patients who received systemic anticancer therapy in our institution and died between July 2016 and April 2017. Data collected included primary malignancy, hospice enrollment, healthcare utilization, Oncology Care Model (OCM) enrollment, and clinical assessments at last office visit prior to a treatment decision before death. We defined our outcome variable as the receipt of anticancer treatment in the last 14 days of a patient’s life. We evaluated 20 clinical exposure variables with respect to the outcome classes. Risk ratios along with their associated confidence intervals and P values were calculated. Significance was determined using the Benjamini-Hochberg procedure to account for multiple testing. Results: Of the 201 patients who died of cancer, 36 (17%) received anticancer therapy within the last 14 days of life. Several risk factors were significantly positively associated with receiving anticancer therapy at the end of life including hospitalization within 30 days of end of life, number of hospitalizations per patient (≥2), death in hospital, enrollment in OCM, and a diagnosis of hematologic malignancy. Conclusion: Our findings demonstrate those enrolled in the OCM and those with hematologic malignancies have a higher risk of receiving anticancer therapy in the last 14 days of life. These observations highlight the need for better identifying the needs of high-risk patients and providing good quality care throughout the disease trajectory to better align end-of-life care with patients’ wishes.