Miracle-dz/UniFAR-FTUs huggingface dataset:
LTCS–Report Inconsistency-and Error-Tolerant Reasoning w.r.t. Optimal Repairs of E L ⊥ Ontologies (Extended Version)

Errors in knowledge bases (KBs) written in a Description Logic (DL) are usually detected when reasoning derives an inconsistency or a consequence that does not hold in the application domain modelled by the KB. Whereas classical repair approaches produce maximal sub-sets of the KB not implying the inconsistency or unwanted consequence, optimal repairs maximize the consequence sets. In this paper, we extend previous results on how to compute optimal repairs from the DL EL to its extension EL ⊥ , which in contrast to EL can express inconsistency. The problem of how to deal with inconsistency in the context of optimal repairs was addressed previously, but in a setting where the (fixed) terminological part of the KB must satisfy a restriction on cyclic dependencies. Here, we consider a setting where this restriction is not required. We also show how the notion of optimal repairs obtained this way can be used in inconsistency-and error-tolerant reasoning.
A study of profile of non-governmental organizations working on women empowerment in Chhattisgarh state

The study evaluates the profile of NGOs working in women empowerment in Chhattisgarh State, targeting 20 NGOs in three districts (Bilaspur, Durg and Raipur) with 40 randomly selected staff members. The study found that NGOs aim to improve the socio-economic status of poor people by providing economic support, raising awareness on health, education, nutrition, and sanitation, and empowering women through SHGs, vocational training
Systematic Literature Review: Teachers' Educational Interaction with Students in Learning in Indonesia

Background: Educative interaction between teachers and students in learning is a definite thing, and if it is not carried out well, it will trigger learning problems at school. Research on educational interactions is trending and has become an important study in education. This research aims to analyze the educational interactions of teachers and students in learning at school. Method :This research uses the SLR (Systematic Literature Review) method. Data was collected by documenting and reviewing previous articles related to interaction and education. Article searches were carried out by searching for articles using the Scopus database. The subjects studied in this research are education, social interaction, interpersonal communication, human relations, interaction, interpersonal relations, students, and teaching. The initial database was 113,234, and then the researchers re-specified it so that it was found to be 475 documents. Results and Dıscussion: The research results show that articles dominate discussions about educational interactions, and there is still very little study of reviews, book chapters, and letters. Social sciences, health, and computer science dominate the subject of discussion. National institutions, especially in the health sector, are more dominant in funding studies on educational interactions. From the Scopus database obtained, publications about educational interactions in learning are still very rare
A Comparison of Three Approaches to Assist Users in Memorizing System-Assigned Passwords

—Users struggle to select strong passwords. System-assigned passwords address this problem, but they can be difficult for users to memorize. While password managers can help store system-assigned passwords, there will always be passwords that a user needs to memorize, such as their password manager’s master password. As such, there is a critical need for research into helping users memorize system-assigned passwords. In this work, we compare three different designs for password memorization aids inspired by the method of loci or memory palace. Design One displays a two-dimensional scene with objects placed inside it in arbitrary (and randomized) positions, with Design Two fixing the objects’ position within the scene, and Design Three displays the scene using a navigable, three-dimensional representation. In an A-B study of these designs, we find that, surprisingly, there is no statistically significant difference between the memorability of these three designs, nor that of assigning users a passphrase to memorize, which we used as the control in this study. However, we find that when perfect recall failed, our designs helped users remember a greater portion of the encoded system-assigned password than did a passphrase, a property we refer to as durability . Our results indicate that there could be room for memorization aids that incorporate fuzzy or error-correcting authentication. Similarly, our results suggest that simple (i.e., cheap to develop) designs of this nature may be just as effective as more complicated, high-fidelity (i.e., expensive to develop) designs.
Forward Scattering of Loaded and Unloaded Antennas

Forward scattering of antennas is related to antenna performance via the forward-scattering sum rule. The forward-scattering sum rule is an integral identity that shows that a weighted integral of the extinction cross section over all spectrum is proportional to the static polarizability of the antenna structure. Here, the forward-scattering sum rule is experimentally verified for loaded, short-circuit, and open-circuit cylindrical dipole antennas. It is also shown that the absorption efficiency cannot be greater than 1/2 for reciprocal linearly polarized lossless matched antennas with a symmetric radiation pattern in the forward and backward directions.
University of Birmingham Live strong and prosper

Due to improved health care, diet and infrastructure in developed countries, since 1840 life expectancy has increased by approximately 2 years per decade. Accordingly, by 2050, a quarter of Europe’s population will be over 65 years, representing a 10 % rise in half a century. With this rapid rise comes an increased prevalence of diseases of ageing and associated healthcare expenditure. To address the health consequences of global ageing, research in model systems (worms, ﬂies and mice) has indicated that reducing the rate of organ growth, via reductions in protein synthetic rates, has multi-organ health beneﬁts that collectively lead to improvements in lifespan. In contrast, human pre-clinical, clinical and large cohort prospective studies demonstrate that ageing leads to anabolic (i.e. growth) impairments in skeletal muscle, which in turn leads to reductions in muscle mass and strength, factors directly associated with mortality rates in the elderly. As such, increasing muscle protein synthesis via exercise or protein-based nutrition maintains a strong, healthy muscle mass, which in turn leads to improved health, independence and functionality. The aim of this review is to critique current literature relating to the maintenance of muscle mass across lifespan and discuss whether maintaining or reducing protein synthesis is the most logical approach to support musculoskeletal function and by extension healthy human ageing.
The Correlation between Intake of Vitamin C and β-Carotene and Fasting Blood Sugar: A Cross-Sectional Analysis in Diabetic Patients of Fasa Cohort Study

Background: Diet and nutrition are strongly implicated in the etiology of type 2 diabetes. This study has investigated whether low vitamin C and β-carotene intakes were associated with glycemic control in diabetic patients. Methods: In a cross-sectional analysis of diabetic adult patients participating in Fasa Cohort Study, a 24-h dietary recall was used to assess intake of fruits, vegetables, vitamin C and β-carotene. The associations between vitamin C and β-carotene intakes and glycemic control were determined in 3 groups of normal glucose tolerance, pre-diabetes mellitus, and type 2 diabetes mellitus (T2DM) and the relationship between fasting blood glucose (FBS) and vitamin C and β-carotene intakes was investigated. Results: There were no differences between groups for intake of total vitamin C and β-carotene ( p >0.05). An inverse relation was recognized between intake of total vitamin C and β-carotene and FBS ( p <0.05). Conclusion: A negative association was observed between FBS and intake of vitamin C and β-carotene; however more experimental studies are needed to establish whether increase in intake of vitamin C and β-carotene can
PromptAD: Zero-shot Anomaly Detection using Text Prompts

We consider the problem of zero-shot anomaly detection in which a model is pre-trained to detect anomalies in images belonging to seen classes, and expected to detect anomalies from unseen classes at test time. State-of-the-art anomaly detection (AD) methods can often achieve exceptional results when training images are abundant, but they catastrophically fail in zero-shot scenarios with a lack of real examples. However, with the emergence of multi-modal models such as CLIP, it is possible to use knowledge from other modalities (e.g. text) to compensate for the lack of visual information and improve AD performance. In this work, we propose PromptAD, a dual-branch framework which uses prior knowledge about both normal and abnormal behaviours in the form of text prompts to detect anomalies even in unseen classes. More speci ﬁ cally, it uses CLIP as a backbone encoder network and an additional dual-branch vision-language decoding network for both normality and abnormality information. The normality branch establishes a pro ﬁ le of normality, while the abnormality branch models anomalous behaviors, guided by natural language text prompts. As the two branches capture complementary information or ‘views’, we propose a ‘cross-view contrastive learning’ (CCL) component which regularizes each view with additional reference information from the other view. We further propose a cross-view mutual interaction (CMI) strategy to promote the mutual exploration of useful knowledge from each branch. We show that PromptAD outperforms existing baselines in zero-shot anomaly detection on key benchmark datasets and analyse the
University of Birmingham Stream temperature under contrasting riparian forest cover

• We assess stream temperature and energy ﬂ uxes under 3 riparian vegetation types. • Stream temperature varies signi ﬁ cantly between different vegetation types. • Net energy ﬂ uxes are greatest in open grassland and lowest in coniferous woodland. • Results of this study have implications for riparian tree planting schemes.
Lifting the curse of knowing: How feedback improves perspective-taking

People are likely to use their own knowledge as a frame of reference when they try to assess another person’s perspective. Due to this egocentric anchoring, people often overestimate the extent to which others share their point of view. This study investigated which type of feedback (if any) stimulates perceivers to make estimations of another person’s perspective that are less biased by egocentric knowledge. We allocated participants to one of the three feedback conditions (no feedback, accuracy feedback, narrative feedback). Findings showed that participants who were given feedback adjusted their perspective-judgement more than those who did not receive feedback. They also showed less egocentric projection on future assessments. Participants adjusted their perspective within the same trial to the same degree for both feedback types. However, participants’ egocentric bias was only reduced when they received narrative feedback and not when they received accuracy feedback about their performance. Implications of these findings for theories of perspective-taking are discussed.
New Fossil Reptile Records from the Siwalik of North India

From the Siwalik Group of Haryana and Himachal Pradesh, new fossil reptile records are described. The Siwalik fauna from Haryana and Himachal is recorded from the pre-Pinjor and Pinjor beds (Upper Siwalik Subgroup: Pliocene—Lower Pleistocene). The reptile fauna includes Crocodylus aff. palustris, Gavialis cf. gangeticus, Rhamphosuchus crassidens, Batagur sp. , Geoclemys hamiltoni and Hardella thurjii. The findings are significant as fossil reptiles from the Siwalik Group are scanty as compared to the richer mammalian fauna.
Tear lipid layer thickness with eye drops in meibomian gland dysfunction

Purpose: The aim of this study was to evaluate the efficacy of a lipid containing emollient eye drop, Soothe XP, which was reformulated in 2014 with a more stable preservative and buffer system, compared to a control, non-emollient, eye drop (Systane Ultra) in improving lipid layer thickness (LLT) in subjects with dry eye due to meibomian gland dysfunction (MGD). Patients and methods: This prospective single-center, open-label, cross-over, examiner masked-study enrolled subjects aged 30–75 years with lipid-deficient dry eye and a clinical diagnosis of MGD as determined by a slit lamp examination, an evaluation of meibomian gland drop out with meibography, and a standard patient evaluation of eye dryness questionnaire of . 5. Eligibility was then determined by a LLT of , 75 nm at baseline and the inability to increase LLT $ 15 nm with three blinks, as determined by interferometric methods. Subjects were randomized to receive a single emollient or non-emollient eye drop at Visit 1 and were crossed over for the alternate treatment at Visit 2. At each visit, LLT was measured prior to and 15 minutes following the instillation of the assigned eye drop. The primary endpoint was the change in LLT from baseline. Results: Subjects (n = 40) were enrolled and 35 completed the two study arms. Mean ( ± SD) patient age was 55.7 years (10.9) and 69% were female. Mean ( ± SD) LLT at baseline was 49.5 nm (9.2). Instillation of Soothe XP resulted in an increase in LLT to 77.5 nm (29.3) 15 minutes following drop instillation, which is an increase of 28.0 nm (27.4) ( P , 0.001). In contrast, LLT 15 minutes after the instillation of Systane Ultra was 50.8 nm (14.1), which was not statistically significant when compared to the baseline LLT. Conclusion: In this study of subjects with MGD, the emollient, or lipid containing eye drop, increased the LLT of tears when measured 15 minutes after instilling a single eye drop.
STIM: Predicting Memory Uncorrectable Errors with Spatio-Temporal Transformer

Memory Uncorrectable Errors (UEs) have been identified as a leading cause of server crashes in Microsoft Azure datacenters. To mitigate this, leveraging machine learning methods to predict UEs before undertaking preventive maintenance has become an effective measurement to decrease server downtime in large-scale clusters. However, the prediction of UEs presents several challenges: (1) anomaly UEs are exceedingly rare in memory events. This rarity renders machine learning methods highly vulnerable to imbalanced data, leading to high false positives and low recall rates. (2) memory data is inherently noisy and heterogeneous because memory hardware comes from a range of manufacturers (e.g., Samsung, SK-Hynix) and is deployed in diverse operational environments. This necessitates the need for robust machine learning models. (3) Predicting UEs demands the handling of intricate spatial and temporal variability in the memory framework, given the hardware degradation over its lifecycle and the iterative introduction of new software and hardware configurations. To address these issues, we proposed a Spatial-temporal Transformer in Memory (STIM) model that learns spatial and temporal features with self-attention mechanisms across memory cells. Comparative evaluations on our developed Azure Memory Error Dataset (AMED) reveal that our proposed STIM model outperforms existing machine learning methods and strong baselines, which marks the significant application of Language Models (LMs) to address complex UE prediction tasks.
Quality of Root Canal Filling in Curved Canals Utilizing Warm Vertical Compaction and Two Different Single Cone Techniques: A Three-Dimensional Micro-Computed Tomography Study

Statement of the Problem: Successful endodontic treatment depends on three-dimensional (3D) root canal filling to prevent the leakage of residual bacteria. Different obturation techniques with different sealers should be compared by employing advanced assessment tools. Purpose: This study compared the obturation quality of warm vertical compaction (WVC) and two different single-cone (SC) techniques using micro-computed tomography (micro-CT). Materials and Method: Thirty-three extracted maxillary molars with mesial root canal curvature of 20‒40º were prepared in vitro with One-Curve files and randomly assigned to three groups (n=11) for root canal obturation with WVC, SC technique with AH Plus sealer (SC-AH), or SC technique with SureSeal bioceramic (BC) sealer (SC-Su). The root canals underwent micro-CT examinations before and after obturation to determine the volume percentages (VPs) of voids and gaps at different distances from the apex (coronal, middle, and apical thirds). Data were analyzed by Kruskal-Wallis and Mann-Whitney U tests. Results: The highest VP of voids and gaps was recorded in the SC-Su group, with no significant difference from other groups ( p > 0.05). There were significant differences in VP of gaps at different distances from the apex ( p <0.05). The VPs of gaps in the apical third of all the samples were significantly higher than in the coronal and middle thirds. However, the difference in VP of voids was not significant at different distances from the apex ( p >0.05). Conclusion: None of the tested techniques could provide a void-free and gap-free filling. The apical third of the canals showed the highest VP of gaps in all obturation techniques.
Hope College Digital Commons Hope College Digital Commons

Using a within subjects design, three emotion regulation strategies (compassion‐focused reappraisal, benefit‐focused reappraisal, and offense rumination) were tested for their effects on forgiveness, well‐being, and event‐related potentials (ERPs). Participants (N = 37) recalled a recent interpersonal offense as the context for each emotion regulation strategy. Both decisional and emotional forgiveness increased significantly for the two reappraisal strategies compared to offense rumination. Compassion‐focused reappraisal prompted the greatest increase in both decisional and emotional forgiveness. Furthermore, both reappraisal strategies increased positively oriented well‐being measures (e.g., joy, gratitude) compared to offense rumination, with compassion‐focused reappraisal demonstrating the largest effect on empathy. Late positive potential (LPP) amplitudes in response to unpleasant affect words were larger following the benefit‐focused reappraisal strategy, indicating frontal LPP augmentation due to affective incongruence of the unpleasant stimuli with the positive, silver‐lining orientation of the benefit‐focused reappraisal emotion regulation strategy.
Role of IT Specialists in the Information System Integration Process: The Case of Mergers and Acquisitions

Purpose: The purpose of this study is explore the role of IT specialists in systems integration during M&A processes including the issues faced during the process and provide suggestions based on experience from top management staff and IT specialists about improving the merger-IT integration process. Methods: In-depth interviews with open-ended questions were conducted on ten individuals belonging to the senior management of the companies under the study. The collected data were transcribed and analyzed and coded using qualitative thematic analysis to derive categories and themes. Results: The analysis resulted in 5 themes and 14 categories from a total of 39 codes. The analysis revealed the implications of "Underestimating the importance of IT" and analyzed the "Preferred IT integration approach" methods followed by the participants. The coded data also revealed the "Perception of management toward including IT and IT experts" and the “Issues faced in the M&A process due to the delay/non-involvement of IT experts". The results of the analysis conclude with the "Perceptions of managers toward the timing of IT integration" and suggestions from the participants based on their experiences. Conclusion: The five themes obtained from the qualitative thematic analysis from the interviews of ten participants suggest that IT and IT specialists were a necessary and core function of the M&A process. The analysis also recommends senior management responsible for the merger or acquisition engage IT, specialists, during the early stages of the process to enable better IT integration and follow a centralized approach towards merging the IT systems.
be-Comparison of methods for predicting cow composite somatic cell counts

One of the most common and reliable ways of monitoring udder health and milk quality in dairy herds is by monthly cow composite somatic cell counts (CMSCC). However, such sampling can be time consuming, and more automated sampling tools entail extra costs. Machine learning methods for prediction have been widely investigated in mastitis detection research, and CMSCC is normally used as a predictor or gold standard in such models. Predicted CMSCC between samplings could supply important information and be used as an input for udder health decision-support tools. To our knowledge, methods to predict CMSCC are lacking. Our aim was to find a method to predict CMSCC by using regularly recorded quarter milk data such as milk flow or conductivity. The milk data were collected at the quarter level for 8 wk when milking 372 Holstein-Friesian cows, resulting in a data set of 30,734 records with information on 87 variables. The cows were milked in an automatic milking rotary and sampled once weekly to obtain CMSCC values. The machine learning methods chosen for evaluation were the generalized additive model (GAM), random forest, and multilayer perceptron (MLP). For each method, 4 models with different predictor variable setups were evaluated: models based on 7-d lagged or 3-d lagged records before the CMSCC sampling and additionally for each setup but removing cow number as a predictor variable (which captures indirect information regarding cows’ overall level of CMSCC based on previous samplings). The methods were evaluated by a 5-fold cross validation and predictions on future data using models with the 4 different variable setups. The results indicated that GAM was the superior model, although MLP was equally good when fewer data were used. Information regarding the cows’ level of previous CMSCC was shown to be important for prediction, lowering prediction error in both GAM and MLP. We conclude that the use of GAM or MLP for CMSCC prediction is promising.
Auction Design with Data-Driven Misspecifications: Inefficiency in Private Value Auctions with Correlation ∗

We study the existence of efficient auctions in private value settings in which some bidders form their expectations about the distribution of their competitor’s bids based on the accessible data from past similar auctions consisting of bids and ex post values. We consider steady-states in such environments with a mix of rational and data-driven bidders, and we allow for correlation across bidders in the signal distributions about the ex post values. After reviewing the working of the approach in second-price and first-price auctions, we show our main result that there is no efficient auction in such environments.