Miracle-dz/UniFAR-FTUs huggingface dataset:
Outcome of Decompression Alone Versus Decompression Plus Transpedicular Screw Fixation in the Treatment of Degenerative Lumbar Spine Stenosis

Background: Degenerative lumbar spinal stenosis (DLSS) is a condition where degenerative and arthritic state of the disc and facet joints respectively results in the displacement of the vertebra resulting in lower back pain in association with radiculopathy. In patients with degenerative lumbar spine, the rate of fixation has increased . Aim: To identify the difference in outcome of decompression alone versus decompression with spinal fixation in DLSS. Place and duration of study: Department of Orthopaedic & Spine Surgery, Ghurki Trust Teaching Hospital, Lahore from 1 st January 2017 to 31 st December 2019. Methodology : All the discharged patients with primary diagnosis of DLSS were identified. Two subgroups were studied i.e. Decompression only and Decompression with TranspedicularScrew Fixation . Primary outcome among patients was assessed using Swiss Spinal Stenosis Score (SSS). All the data were entered and analyzed using SPSS software and p-value≤0.05 considered to be significant. Results: Total number of patients included in study was 87.out of the total,34(39%) patients had underwent decompression alone, whereas in 53(60.9%) patients decompression with transpedicular fixation were done. Significant difference was not observed among cases with respect to mean score on SSS based on two different types of surgical interventions. In decompression with fixation group, the average length of stay of patients in hospital was 6.4 days as compared to decompression only group as 4.4 days. Conclusion: Both surgical procedures decompression plus transpedicular fixation and decompression alone produce similar outcome at 2 years follow-up.
The co-evolution of rock physics and seismic inversion

The history of the exploration seismic method can be divided into four distinct phases. In the first phase, prior to 1970, seismic data was used primarily as a structural interpretation tool, where stacked seismic data was interpreted to map structures, such as anticlines, that could potentially be hydrocarbon traps. In the next phase, from roughly 1970 to 1985, geophysicists used the amplitude information in seismic data to infer stratigraphic features, first using the concept of “bright-spots” for gas identification and then by performing post-stack seismic inversion to derive P-impedance, the product of P-wave velocity and density. Since P-impedance is linearly related to porosity, this led to the first attempts to predict rock properties from seismic data. In the third phase, from roughly 1985 to the end of the millennium, geophysicists started utilizing pre-stack amplitude information, first with the AVO technique and then with full bandwidth pre-stack seismic inversion. This allowed them to extract both P-impedance and S-impedance (and hence VP/VS ratio) as well as density information from the seismic data. Geophysicists could now produce twodimensional cross-plots of their results, something that petrophysicists and rock physicists had been doing for decades. This also meant that geophysicists could now estimate more complex petrophysical and rock physics parameters from their seismic data, utilizing these cross-plots. In the fourth phase, which we are currently in, we started using neural networks and machine learning, to directly estimate rock physics parameters from the pre-stack seismic data and its attributes. This talk will summarize the co-evolution of rock physics/petrophysics with seismic methods such as AVO and inversion and show how inter-related all these disciplines have become.
An Efficient Acceleration of Solving Heat and Mass Transfer Equations with the Second Kind of Boundary Conditions in Solid and Hollow Cylinder Using Programmable Graphics Hardware

Recently, heat and mass transfer simulation is more and more important in various engineering fields. In order to analyse how heat and mass transfer in a thermal environment, heat and mass transfer simulation is needed. However, it is too much time-consuming to obtain numerical solutions to heat and mass transfer equations. Therefore, in this paper, one of acceleration techniques developed in the graphics community that exploits a graphics processing unit (GPU) is applied to the numerical solutions of heat and mass transfer equations. The nVidia Compute
Visual Reasoning for Design by Analogy: Fuse Visual and Semantic Knowledge

Design by analogy is a design ideation strategy to find inspiration from source domains to generate design concepts in target domains. Recently, many computational methods were proposed to measure similarities between source domains and target domains to build connections between them. However, most existing methods only explore either visual or semantic cues of the concepts in source and target domains but ignore the integration of both modalities. In fact, humans have remarkable visual reasoning ability to transfer knowledge learned from objects in familiar categories (source domains) to recognize objects from unfamiliar categories (target domains). In this paper, we propose a visual reasoning framework to support design by visual analogy. The challenge of this research is how computation methods can mimic the process of humans’ visual reasoning, which fuses visual and semantic knowledge. In the framework, the convolutional neural network (CNN) is applied to learn visual knowledge from objects in familiar categories. The hierarchy-based graph convolutional network (HGCN) is proposed to transfer learned visual knowledge from familiar categories to unfamiliar categories by their semantic distances. Finally, the unfamiliar objects can be reasoned and recognized based on the transferred visual knowledge. Extensive experimental results on one mechanical component benchmark dataset demonstrate the favorable performance of our proposed methods.
Drift diffusion simulation of organic semiconducting devices

This report contains the results of the implementation of a charge injection model and the generalized Einstein relation in a drift-diffusion simulation program for organic semiconductor devices. Charge injection through low energy pathways and image charge barrier lowering showed to have some effect on the current. A non realistic current at zero voltage occurred when the generalized Einstein relation was used. Increasing the number of grid points and decreasing the used tolerance for the numerical integration method were found not to be a solution for this problem. It was discussed that while the used Scharfetter-Gummel discretization scheme is based on Boltzmann statistics, the generalized Einstein relation depends on Fermi-Dirac statistics. It was therefore proposed to generalize the Scharfetter-Gummel discretization scheme.
Self-supervised anomaly detection in static attributed graphs

In this work, we consider the task of detecting anomalous nodes in static attributed graphs in the absence of labeled samples. Anomaly (or outlier) detection is generally a diﬃcult problem to solve. This is due to the absence of a concrete deﬁnition of what constitutes an anomaly, but also because anomalies themselves occur very rarely and ﬁnding enough samples to learn from is often impossible. In this work, we pro-pose two methods that combine Graph Neural Networks (GNNs) with a self-supervised training scheme to learn a representation of normal (non-anomalous) nodes in the graph, and identify anomalies using these learned representations. Both models, called HideGNN and MaskGNN , use a mask-based self-supervision approach, whereby the algorithm is set up to predict the masked or hidden features of nodes at train time. We show experimentally that our approach outperforms known baselines on real-world datasets and we explore the power of the methods in detecting speciﬁc types of anomalies with synthetic data.
Commentary on ‘Income and Happiness: A Philippines Context’

The commentary discusses five items pertinent to Palanca-Tan (2021), namely: Easterlin Paradox, Easterlin Hypothesis, happiness-income model, happiness survey question, and happy poor. The goal is to offer clarification and to help enrich the understanding of readers of Palanca-Tan. “A person who is ill-fed, undernourished, unsheltered and ill can still be high up in the scale of happiness or desire-fulfillment if he or she has learned to have ‘realistic’ desires and to take pleasure in small mercies. The physical conditions of a person do not enter the view of well-being seen entirely in terms of happiness or desire-fulfillment, except insofar as they are indirectly covered by the mental attitude of happiness or desire. ”
Networked Musical XR: where’s the limit? A preliminary investigation on the joint use of point clouds and low-latency audio communication

As of today, the field of networked musical XR is in its infancy. While the next generation networks keep pushing the available bandwidth towards new frontiers, promoting the deployment of new services and applications, a limited amount of residual latency still hinders the possibility for musicians to seamlessly interact over the Internet. In fact, while audiovisual (and audio in particular) streaming has reached high performances, allowing for smooth interaction in many application scenarios such as video calls and dialogues, the study of tools to ensure a flawless immersive interplay experience among musicians is a rather unexplored area. This paper reports a preliminary investigation on a technical setup that couples a networked music performance system with an XR system, conceived to interconnect geographically displaced musicians. The setup we have envisaged has allowed us to identify the existing technical issues in current technologies used for networked musical XR. We discuss such issues and reason about possible future research directions in this area that should be covered to advance the current state of the art.
FReD: Identifying File Re-Delegation in Android System Services

The security of the Android platform beneﬁts greatly from a privileged middleware that provides indirect access to protected resources. This architecture is further enhanced by privilege separating functionality into many different services and carefully tuning ﬁle access control policy to mitigate the impact of software vulnerabilities. However, these services can become confused deputies if they improperly re-delegate ﬁle access to third-party applications through remote procedure call (RPC) interfaces. In this paper, we propose a static program analysis tool called FR E D, which identiﬁes a mapping between Java-based system service RPC interfaces and the ﬁle paths opened within the Java and C/C++ portions of the service. It then combines the Linux-layer ﬁle access control policy with the Android-layer permission policy to identify potential ﬁle re-delegation. We use FR E D to analyze three devices running Android 10 and identify 12 confused deputies that are accessible from third-party applications. These vulnerabilities include ﬁve CVEs with moderate severity, demonstrating the utility of semi-automated approaches to discover subtle ﬂaws in access control enforcement.
A Lipid-Based In Situ-Forming Hexagonal Phase for Prolonged Retention and Drug Release in the Breast Tissue

In this study, the addition of monoolein to phosphatidylcholine (PC), tricaprylin, and propylene glycol (PG) mixtures was studied to produce fluid precursor formulations (FIPs) that could transform into hexagonal phase (resistant to aqueous dilution) in vitro and in vivo. The overall goal was to obtain FIPs that could incorporate chemopreventive drugs for subcutaneous administration in the mammary tissue to inhibit the development and/or recurrence of breast cancer. Increasing PG content reduced FIP viscosity up to ~ 2.5-fold, while increases in PC (over monoolein) increased the formation of emulsified systems. The hexagonal phase was observed at 20% of water and higher, with the minimum amount of water necessary for this formation increasing with PG content. The selected FIP formed a depot in vivo after ~ 24 h of administration; its structure was compatible with the hexagonal phase and it remained in the mammary tissue for at least 30 days, prolonging the permanence of a fluorescent probe. In vitro, the release of the synthetic retinoid fenretinide was slow, with ~ 9% of the drug released in 72 h. Consistent with this slow release, fenretinide IC50 in breast cancer cells was ~ 100-fold higher in the selected FIP compared to its solution. The FIP reduced cell migration and presented higher cytotoxicity towards tumor compared to non-tumor cells. Given the limited number of options for pharmacological prevention of breast cancer development and recurrences, this formulation could potentially find applicability to reduce the frequency of administration and improve local concentrations of chemopreventive drugs.
A simplified aperiodic cross-correlation model for direct-sequence spread-spectrum multiple-access communication systems

The discrete probability density function (pdf) of the average aperiodic cross-correlation function (ACF) is modeled by a triangular function to simplify the evaluation of the bit-error-rate (BER) performance. Both the pdf of ACF for a random binary sequence and the pdf of the ACF for a Gold sequence were employed to examine the simplified linear model. The pdf of the multiple-access interference (MAI) component obtained from a probabilistic approach was employed to investigate the discrepancy among the approximations. It is shown that the sum of the square error between the average pdf of the MAI component for the Gold sequence and that of the simplified linear model is 0.0683% which is negligible, and thus the simplified linear model can be used to simplify the evaluation of the BER performance of an asynchronous direct-sequence spread-spectrum multiple-access (A-DS/SSMA) communication system. <<ETX>>
Accuracy of a customized volumetric rendering program in linear measurement of cone beam and multi-slice computed tomography derived three-dimensional images

Background: The study aimed to verify the accuracy of volumetric rendering software on cone beam computed tomography (CBCT) and multislice computed tomography (MSCT)-derived surface models. Materials and Methods: Gutta Purcha cone tips were fixed on 14 points at the facial surface of five dry mandibles. The mandibles were scanned twice with each scanner on three occasions. 26 distances were measured 10 times, using digital calipers. The surface models rendered by the software were linearly measured thrice and their means recorded. The data sets were subjected to vigorous statistical treatment using analysis of variance and Tukey test. Results: The caliper measurements, the CBCT and MSCT images were comparable, indicated by an F = 0.0003 and a Tukey T value (8.7), larger than the absolute difference between any two means. Thus, confirming the linear accuracy of the software. Conclusions: "SolidPlanner" volumetric rendering program yields a near 1-to-1 ratio with reality. The program enjoys linear accuracy, which remained submillimeter accurate, emphasizing the validity of the program as a measuring tool.
Diversification of User Recommendations Using Entropy Redistribution

—Different users may have different ranges of interests - the preference of a highly focused user might include only few topics, whereas that of the user with broad interests may encompass a wide range of topics. In the recommendation systems most of the algorithms mostly focus on the accuracy and recall of results. The most accurate result according the defined metric may not be in the interest range of the user. The diversity of the result interests users while the diversification must be within the range of interest of the users. In this paper a method for diversification has been proposed which includes both individual and aggregate diversity using the entropy of topics and users who are being recommended by this diversification task. Whenever a particular user will have high entropy, a topic having low entropy should be recommended to him and vice-versa for redistributing entropy and so eventually the diversification of recommendations will be achieved.
In silico Evaluation of the Antimalarial Potential of the Phytoconstituents of the Azadirachta indica Plant

Background and objectives : Malaria, a parasitic protozoan disease caused primarily by Plasmodium falciparum, has killed millions of people in Africa, particularly those with meager or no access to orthodox medical facilities and therapies. Extracts from the Azadirachta indica ( neem) plant is believed to possess antimalaria properties among the locals that rely on herbs. Numerous in - vivo studies have suggested the antimalarial properties of neem extract and phytochemicals. This study employs an in - silico method through molecular docking techniques to provide insight while adding credence to the antimalarial potential of phytochemicals of neem plants as claimed in folkloric medicine. Methods : e The crystal structure of P. falciparum a causative parasite of malaria was retrieved from the Protein Data Bank, and Azadirachta indica phytochemicals were obtained from the PubChem database. Molecular docking through virtual screening was carried out on the characterized phytochemicals. The bioactive compounds from the Azadirachta indica plant were investigated by docking with the crystal structure of P. falciparum receptor and compared with standard antimalarial drugs (lumenfrantrine and artemisinin). Results : Three Azadirachta indica phytochemicals (gedunnin, nimbinene and salanin) shows a competing binding energy and af ﬁ nity when compared to the approved antimalarial drugs (lumefrantrine and artemisinin). While the binding af ﬁ nities for azadirachtin, nimbandiol and quercetin is lower than the af ﬁ nity in artemisinin but comparable with lumefrantrine. Conclusion : This virtual screening veri ﬁ ed and identi ﬁ ed a potential phytochemical component of antimalarial properties against a protein target: 1m7o, P. falciparum triosephosphate isomerase (PfTIM).
Triangle Centrality in Arkouda

—There are a wide number of graph centrality metrics. Further, the performance of each can vary widely depending on the type of implementation. In this work we present our implementation of triangle centrality in Arkouda with several different triangle counting methods. Triangle Centrality is a robust metric that captures the centrality of a vertex through both a vertex’s own connectedness and that of its neighbors. Arkouda is an open-source framework for data science at the scale of terabytes and beyond. These methods are compared against each other and another shared memory implementation.
Multimodality for NLP-Centered Applications: Resources, Advances and Frontiers

With the development of multimodal systems and natural language generation techniques, the resurgence of multimodal datasets has attracted significant research interests, which aims to provide new information to enrich the representation of textual data. However, there remains a lack of a comprehensive survey for this task. To this end, we take the first step and present a thorough review of this research field. This paper provides an overview of a publicly available dataset with different modalities according to the applications. Furthermore, we discuss the new frontier and give our thoughts. We hope this survey of multimodal datasets can provide the community with quick access and a general picture of the multimodal dataset for specific Natural Language Processing (NLP) applications and motivates future researches. In this context, we release the collection of all multimodal datasets easily accessible here: https://github.com/drmuskangarg/Multimodal-datasets
Metacognitive functions of patients with trichotillomania and skin picking disorder

Objective: This study aimed to compare the metacognitive functions of patients diagnosed with trichotillomania (TTM) and skin picking disorder (SPD) with those of healthy controls (HCs). Method: The study was conducted with 125 participants, 32 of whom had TTM, 47 had SPD, and 46 were HCs. A Sociodemographic Data Form, the Metacognition Questionnaire-30 (MCQ-30), Clinical Global Impression (CGI), Beck Depression Inventory (BDI), and Beck Anxiety Inventory (BAI) were administered to the participants. Results: It was determined that the subscale scores of “uncontrollability and danger” and “need to control thoughts” were significantly higher in patients with TTM and SPD compared with the HCs. There was a positive correlation between the patients’ CGI scores and their MCQ-total scores. A positive and significant relationship was found between BDI and “uncontrollability and danger,” “need to control thoughts,” “cognitive self-consciousness,” and MCQ-total scores. There was a positive correlation between the BAI and other subscales except for "positive beliefs" and MCQ-total scores. Conclusion: Our study reveals dysfunctional metacognitions in TTM and SPD patient groups. The subdimensions of “uncontrollability and danger” and “need to control thoughts” are dysfunctional metacognitions that are prominent in both patient groups. These prevent It also
A Semi-Automatic Approach to Create Large Gender- and Age-Balanced Speaker Corpora: Usefulness of Speaker Diarization & Identification.

This paper presents a semi-automatic approach to create a diachronic corpus of voices balanced for speaker’s age, gender, and recording period, according to 32 categories (2 genders, 4 age ranges and 4 recording periods). Corpora were selected at French National Institute of Audiovisual (INA) to obtain at least 30 speakers per category (a total of 960 speakers; only 874 have be found yet). For each speaker, speech excerpts were extracted from audiovisual documents using an automatic pipeline consisting of speech detection, background music and overlapped speech removal and speaker diarization, used to present clean speaker segments to human annotators identifying target speakers. This pipeline proved highly effective, cutting down manual processing by a factor of ten. Evaluation of the quality of the automatic processing and of the final output is provided. It shows the automatic processing compare to up-to-date process, and that the output provides high quality speech for most of the selected excerpts. This method is thus recommendable for creating large corpora of known target speakers.
Summability of formal solution of Cauchy problem for some PDE with variable coefficients (Recent development of micro-local analysis for the theory of asymptotic analysis)

We give a proof of the summability of formal solution for Cauchy problem of linear first order partial differential equations with respect to t and with t dependent coefficients under some global conditions for Cauchy data. §1. Result We consider the following Cauchy problem for linear partial differential equations of first order with respect to t and with t dependent coefficients (1.1) \left\{\begin{array}{l} @u (t; x)=\sum_{(i, $\alpha$)}^{f^{inite}}a_{i $\alpha$}t^{i}\partial_{x}^{ $\alpha$}u(t, x)\\ u(0, x)= $\varphi$(x)\in \mathcal{O}, \end{array}\right. where (t, x)\in \mathbb{C}^{2}, a_{i $\alpha$}\in \mathbb{C} and \mathcal{O} denotes the set of holomorphic functions in a neigh‐ borhood of the origin. The Cauchy problem (1.1) has a unique formal solution of the form (1.2) û (t, x)=\displaystyle \sum_{n\geq 0}u_{n}(x)\frac{t^{n}}{n! }. We have an interest in the case where the formal solution is divergent. We assume that for the operator (1.3) \displaystyle \max $\alpha$>1, Received March 29, 2012, Accepted July 30, 2012. 2010 Mathematics Subject Classication(s): 35\mathrm{C}10, 35\mathrm{F}10