Miracle-dz/UniFAR-FTUs huggingface dataset:
A Study and analysis of attacks by exploiting the source code against computer systems

An avalanche of threats from malicious used information and communication technologies (ICT) ‎in political, military, economic and social affairs led to a deep awareness of the fact that new ‎technologies may pose additional risks to international peace and safety. Thus, the problem of ‎international information security, that is, the state of the spread of information among the ‎countries of the world, with which excludes the possibility of violation of the rights of the ‎individual and users in various state agencies and in all fields of knowledge. In the field of ‎knowledge, as well as destructive and illegal impact on elements of the national critical ‎information infrastructure, became an integral part of international security as a system of ‎international relations based on the observance by all states of generally recognized principles and ‎norms of international law and excluding the solution of controversial questions and ‎disagreements between them through force or threat of force, in general. Thus, the principles of ‎international security providing for promoting peaceful coexistence, being ensuring equal security ‎for all states, the creation of effective guarantees in the military, political, economic and ‎humanitarian spheres, preventing the race of nuclear and space weapons, respect for the sovereign ‎rights of every people, fair political settlement of international crises and regional conflicts ‎certainly include the creation of a system of international information security. At the same time, ‎under the IIB system, designed for countering threats to strategic stability and ensuring equal ‎partnership in the global digital environment, we understand the totality international and ‎national norms and institutions, chief among which are the UN Regulated activities of various ‎actors worldwide. ‎
ON NEURAL NETWORK GENERALIZATION VIA PROMOTING WITHIN - LAYER ACTIVATION DIVERSITY

During the last decade, neural networks have been intensively used to tackle various problems and they have often led to state-of-the-art results. These networks are composed of multiple jointly optimized layers arranged in a hierarchical structure. At each layer, the aim is to learn to extract hidden patterns needed to solve the problem at hand and forward it to the next layers. In the standard form, a neural network is trained with gradient-based optimization, where the errors are back-propagated from the last layer back to the first one. Thus at each optimization step, neurons at a given layer receive feedback from neurons belonging to higher layers of the hierarchy. In this paper, we propose to complement this traditional ’between-layer’ feedback with additional ’within-layer’ feedback to encourage diversity of the activations within the same layer. To this end, we measure the pairwise similarity between the outputs of the neurons and use it to model the layer’s overall diversity. By penalizing similarities and promoting diversity, we encourage each neuron to learn a distinctive representation and, thus, to enrich the data representation learned within the layer and to increase the total capacity of the model. We theoretically study how the within-layer activation diversity affects the generalization performance of a neural network in a supervised context and we prove that increasing the diversity of hidden activations reduces the estimation error. In addition to the theoretical guarantees, we present an empirical study confirming that the proposed approach enhances the performance of neural networks.
Spatio-temporal patterns and drivers of terrestrial Dissolved 1 Organic Carbon (DOC) leaching to the European river 2 network.

Leaching of dissolved organic carbon (DOC) from soils to the river network is an important 15 component of the land carbon (C) budget. At regional to global scales, its significance has been estimated 16 through simple mass budgets, often using multi-year averages of observed fluvial DOC fluxes as proxy of DOC 17 leaching due to the limited availability of observations of the leaching flux itself. This procedure leads to a 18 systematic underestimation of the leaching flux because of the decay of DOC during fluvial transport. Moreover, 19 this procedure does not allow revealing spatio-temporal variability in DOC leaching from soils, which is vital to 20 better understand the drivers of DOC leaching and its impact on the local soil C budget. In this study, we use the 21 land surface model ORCHILEAK to simulate the terrestrial C budget including leaching of DOC from the soil 22 and its subsequent reactive transport through the river network of Europe. The model performance is evaluated 23 not only against the sparse observations of soil DOC leaching rate, but also against the more abundant 24 observations of fluxes and reactivity of DOC in rivers, providing further evidence that our simulated
Eosinophilic Dermatosis of Hematologic Malignancy (EDHA): An Obscure Dermatologic Diagnosis Effectively Treated with Rituximab

Eosinophilic dermatoses are a heterogeneous group of diseases, characterized by an eosinophil-rich infiltrate and/or degranulation of eosinophils. Eosinophilic dermatoses encompass a broad spectrum of diseases of different etiologies hallmarked by eosinophilic infiltration of the skin and/or mucous membranes, with or without associated blood
In vitro free radical scavenging activity of aonla (Emblica offi cinalis) varieties at various stages of fruit development

An investigation was undertaken to assess the free radical scavenging activity of aonla (Emblica offi cinalis) varieties viz., BSR-1, Chakaiya, Krishna and NA-7 at various stages of fruit development viz., initial stage, one-fourth maturity stage, half maturity stage, three-fourth maturity stage and full maturity stage using DPPH assay to identify the variety and stage of fruit development for maximum antioxidant activity. The experimental DPPH assay revealed that the free radical scavenging activity was signifi cantly different among the aonla varieties and also at various stages of fruit development in each variety. It was also found that the DPPH free radical scavenging activities of fresh aonla fruit extracts were found to be signifi cantly higher (P<0.05) than the radical scavenging activity of the standard ascorbic acid at varying concentrations. The pattern of total soluble sugars accumulation and free radical scavenging activity at various stages of fruit development in each aonla variety studied were discussed in detail.
EFFICIENT UTILIZATION OF CORN STALK AND POPLAR

In this study, particleboards were manufactured using a mixture of corn stalks and poplar wood particles at different ratios utilizing 10 % urea-formaldehyde adhesive. Panels with a density of 0,70 g/cm3 were manufactured using various amount of corn stalks and poplar wood from 100 to 25 %. Manufactured panels were tested the mechanical properties including modulus of rupture, modulus of elasticity and internal bond and the water absorption and thickness swelling. In addition, the chemical properties and fiber dimensions of poplar wood and corn stalks were also evaluated. Some properties of the manufactured panels increased with the content of poplar particles. The addition of wood poplar particles resulted in a significant increase of some properties of particleboards. From this study, it can be concluded that the combination of poplar particles and corn stalks resulted in particleboards acceptable for interior applications due to low water absorption and thickness swelling. The internal bond strength, the most serious deficiency of stalks, was upgraded sufficiently by increasing the content of wood poplar particles. This study demonstrate that corn stalks may be considered as a charger for wood poplar particleboards manufacturer in region where wood is not abundant. unusual to wood material in the production of particleboards.
Enhancement of Speech to Text Synthesis

:A real time speech to text conversion system converts the spoken words into text exactly as pronounced . We created a real time speech recognition system that was tested in real time noiseous environment. We used the design of a Extended Kalman filter with the dual channel microphone to enhance the ability of this Real time speech recognition system. Extended Kalman filter has been proved the best noise estimator in non-stationary noiseous environment. The purpose of this project was to introduce a new speech recognition system that is computationally simple and more robust to noise than the HMM based speech recognition system. MFCC features of speech sample were calculated and words were distinguished according to the feature matching of each sampled word. This paper deals with speech enhancement in dual-microphone devices using beam forming along with post filtering techniques. The performance of these algorithms relies on a good estimation of the acoustic channel and speech and noise statistics. In this work we present a speech enhancement system that combines the estimation of the relative transfer function (RTF) between microphones using an extended Kalman filter framework with a novel speech presence probability estimator intended to track the noise statistics ’ variability. The available dual-channel information is exploited to obtain more reliable estimates of clean speech statistics. Noise reduction is further improved by means of postfiltering techniques that take advantage of the speech presence estimation. Our proposal is evaluated in different reverberant and noisy environments when the system is used in both close-talk and far-talk positions. The experimental results show that our system achieves improvements in terms of noise reduction, low speech distortion and better speech intelligibility compared to other state-of-the-art approaches
Analysis of Commutation Torque Ripple Suppression Strategy for Brushless DC Motor using NIBFE with SEPIC

This paper is based on Analysis of Commutation Torque Ripple Suppression Strategy for Brushless DC Motor using NIBFE with SEPIC. BLDC Motor are used by many applications as it has high starting torque, high efficiency, high power density. There are no brushes and commutator present in BLDC motor. Commutation happens every 60 degrees. Commutation is done with help of electronic switches of Inverter. Hall sensors placed in Stator are used to sense position of rotor. In commutation period torque ripple is produced due to phase current which is not undergoing commutation. The commutation torque ripple cause vibration and noise, could reduce high performance operation of BLDC motor. By maintaining noncommutation phase current steady in commutation period torque ripple can be reduced. In this Project work NIBFE fed BLDC motor is compared with SEPIC converter fed BLDC motor using Proposed control strategy. NIBFE called as Non inductive boost front end formed using Diode, MOSFET and capacitor. A Closed loop feedback controller circuit with Switching sequence is used to generate PWM gate pulse for Inverter and converter Switch. By selecting proper Switching Vectors in Noncommutation and Commutation period have reduced Commutation Torque Ripple. The components are simulated in MATLAB 2019b Software and Simulation results of Open and Closed loop of NIBFE compared with SEPIC Converter with Proposed method is presented.
A Review of Visual and Endocrine Outcome Following Surgery for Pituitary Adenoma in a Tertiary Hospital

Background: Pituitary adenomas present with hormone and visual dysfunction requiring surgical treatment. Evaluating benefits of treatment becomes expedient in our emerging tertiary practice. Aims and Objectives: Evaluating benefits of treatment pituitary adenomas in a tertiary hospital, North Central Nigeria. Methods: Retrospective review of cases of surgery for pituitary adenomas (Jan 2013 to Dec 2017). Study parameters were visual and endocrine functions evaluated up to 12 months post-op. Simple descriptive statistics was used for data analysis. Results: Total 28 out of 57 cases (49%) had surgery. M:F 3:1. Mean age of 44 years (range 21 to 72 years). 23/28 (82%) were referred from eye clinics. Commonest presentation was visual impairment (100%). Bitemporal field loss in 12/28 (42.8%) and complete blindness in 10/28 (35.7%). Low cortisol and low thyroid hormone were observed in one case each (3.5%). Of the four functional cases, three were prolactin secreting and one growth hormone secreting. Mean time to presentation was 29 months (Range1 to 108 months). Commonest neuroimaging modalities were contrast enhanced CT and MRI. Commonest pre-op diagnosis was non-functional adenoma 24/29 (85.7%). Commonest surgical approach was transsphenoidal surgery 20/28 (70.1%). CVF at 12 months follow up recorded visual improvement in only 11/28 (39.2%). Hormone profile at 12 months showed improved status from 21/28 (75%) to 25/28 (89%) but residual prolactinemia in 2/28 (7.1%) and persisting GH secreting in 1/28 (3.5%). Check MRI at 12 months revealed no significant residual/ recurrent tumor and no chiasmal pressure in 16/27 (59.2%). Commonest histology report was pituitary adenoma with diffuse FSH/LH expression in 15/28 cases (53.5%). Further treatments were re-do operation and radiotherapy referral in 3/27 (11.1%) each. Conclusion: Following surgery, a marginal improvement in vision was observed but hypocortisolism and low thyroid hormones were restored to normalcy at 12 months. However, despite surgical/ medical interventions GH remained high at 12 months in lone case of acromegaly and prolactinemia persisted in two out of the three cases.
Mindfulness Moderates The Association Between Internalizing Symptomatology And Emotional Eating

Emotional eating is defined as the tendency to increase food consumption in order to modify negative emotional states. Although it is counter to the more typical response of decreasing food intake in the face of distress, emotional eating is observed in both eating disordered and healthy populations and is associated with overweight and obesity. Theories on emotional eating attribute its cause to inadequate emotion regulation, specifically an inability to draw awareness to and accept distress. Mindfulness, or the ability to pay attention to one’s internal and external experiences, is negatively associated with both emotional eating and psychological distress. Only one study to date (Pidgeon et al., 2013), however, has examined the moderating role of trait mindfulness in the relationship between psychological distress and emotional eating. Pidgeon and colleagues utilized a mainly undergraduate sample, and a unidimensional measure of mindfulness, which failed to capture the complexity of the construct. The present study replicated and extended the findings of Pidgeon and colleagues with the Five Factor Mindfulness Questionnaire to probe the effects of specific facets of mindfulness on the relationship between internalizing distress and emotional eating in a diverse community sample (N = 248). Results indicated that depression significantly interacted with nonjudging of inner experience. Analysis of the interaction revealed that there were significant differences between low, average, and high levels of nonjudging only at low levels of depression. At low levels of depression, those who were high in nonjudging endorsed less emotional eating than those who were average or low in nonjudging. Anxiety did not significantly interact with any of the five mindfulness facets to predict emotional eating. These findings further delineate the moderating role of specific aspects of trait mindfulness in the association between depressive symptoms and emotional eating and may inform more targeted intervention and prevention efforts.
A Novel Data Aggregated Underwater Pipeline Communication

: Water Pipeline Monitoring Systems have emerged as a reliable solution to maintain the integrity of the water distribution infrastructure. Various emerging technologies such as the Internet of Things, Physical Cyber Systems, and machine to-machine networks are efficiently deployed to build a Structural Health Monitoring of pipeline and invoke the deployment of the Industrial Wireless Sensor Networks (IWSN) technology. Efficient energy consumption is imperatively required to maintain the continuity of the network and to allow an adequate interconnection between sensor nodes deployed in the harsh environment. In this context, to maximize the Lifetime of the WSN underwater Distribution system domain is a primordial objective to ensure its permanently working and to enable a promising solution for hydraulic damage detection according to diverse performance metrics In this context, the data aggregation techniques are well-designed and various smart algorithms are developed to reduce the quantity of transmitted data and to minimize the energy consumption. In this project, we combine between data aggregation and clustering algorithm in order to improve the WSN Lifetime. Data aggregation applied in order to eliminate redundant data either from different sensor nodes at the same time or from the same sensor node at various time steps . NS2 simulator tool has been used to evaluate existing and proposed system performance . Then, efficient data aggregation allowing the redundancy elimination at the cluster and sensor node level improves more the results ans reduces the energy consumption
C ONTEXTUAL I MAGE P ARSING VIA P ANOPTIC S EGMENT S ORTING

Visual context is versatile and hard to describe or label precisely. We aim to leverage the densely labeled task, image parsing, a.k. a panoptic segmentation, to learn a model that encodes and discovers object-centric context. Most existing approaches based on deep learning tackle image parsing via fusion of pixel-wise classification and instance masks from two sub-networks. Such approaches isolate things from stuff and fuse the semantic and instance masks in the later stage. To encode object-centric context inherently, we propose a metric learning framework, Panoptic Segment Sorting, that is directly trained with stuff and things jointly. Our key insight is to make the panoptic embeddings separate every instance so that the model automatically learns to leverage visual context as many instances across different images appear similar. We show that the context of our model’s retrieved instances is more consistent relatively by 13.7%, further demonstrating its ability to discover novel context unsupervisedly. Our overall framework also achieves competitive performance across standard panoptic segmentation metrics amongst the state-of-the-art methods on two large datasets, Cityscapes and PASCAL VOC. These promising results suggest that pixel-wise embeddings can not only inject new understanding into panoptic segmentation but potentially serve for other tasks such as modeling instance relationships.
Regulatory Role Played by the mRNA Binding Protein Tristetraprolin in the Skin and its Involvement in Different Diseases

The mRNA binding protein Tristetraprolin (TTP), encoded by the ZFP36 gene, plays a fundamental regulatory role in a wide variety of cellular processes by means of its widespread expression in different tissues, and of its ability to post transcriptionally regulate the stability, and therefore the expression, of multiple specific target mRNAs. Because of these features, TTP expression and activity are strictly regulated, and malfunctions of such mechanisms underlie different pathologies. Here we recapitulate the role of TTP in the skin, and its involvement in different conditions, with special reference to psoriasis and cancer.
Molecular dynamics (MD) calculation of the real zeta potential of neutral surfaces

Molecular dynamics (MD) simulations of the zeta potential are so poor that it has become common to term their predictions ’apparent’. Here we demonstrate how zeta potentials that agree with measured values can be calculated by: (1) integrating the net average charge in surface-parallel layers from the midpoint of the fluid layer (where the electrostatic potential is zero) to and then into two solid caps, (2) determining the position of slipping plane with separate Couette flow models, and (3) calculating the charge distribution and electrostatic potential under static conditions. The solids we model are charge neutral surfaces composed of atoms with zero charge or charge balanced monovalent or divalent ions. The zeta potentials calculated are within a few millivolts of measured values, and the measured values fall within the simulation error bars. Insights provided by the improved MD simulations into the complex phenomena that affect surface charge and zeta potential are discussed.
Preparation and Characterization of Poly(D,L-lactide-co-glycolide) Micro- spheres for Controlled Release of Human Growth Hormone

INTRODUCTION The purpose of this research was to assess the physicochemical properties of a controlled release formulation of recombinant human growth hormone (rHGH) encapsulated in poly(D,L-lactide-co-glycolide) (PLGA) composite microspheres. rHGH was loaded in poly(acryloyl hydroxyethyl) starch (acHES) microparticles, and then the protein-containing microparticles were encapsulated in the PLGA matrix by a solvent extraction/evaporation method. rHGH-loaded PLGA microspheres were also prepared using mannitol without the starch hydrogel microparticle microspheres for comparison. The detection of secondary structure changes in protein was investigated by using a Fourier Transfer Infrared (FTIR) technique. The composite microspheres were spherical in shape (44.6 ± 2.47 μm), and the PLGA-mannitol microspheres were 39.7 ± 2.50 μm. Drug-loading efficiency varied from 93.2% to 104%. The composite microspheres showed higher overall drug release than the PLGA/mannitol microspheres. FTIR analyses indicated good stability and structural integrity of HGH localized in the microspheres. The PLGA-acHES composite microsphere system could be useful for the controlled delivery of protein drugs. Biodegradable microspheres have been extensively investigated as delivery systems for biologically active peptides and proteins. Sustained-release characteristics of microspheres reduce the need for frequent administrations and enhance patient compliance by maintaining in vivo drug levels in the therapeutic range. Poly(D,L-lactide) (PLA) and poly(D,L-lactide-coglycolide) (PLGA) are the most widely used and well characterized polymers for biodegradable microspheres. Several factors, however, have limited the development of sustained-release formulations of protein therapeutics. One is the need to stabilize the protein for long periods in an aqueous environment at physiological conditions. In contrast to lower molecular weight drugs, proteins often have large globular structure and exhibit secondary, tertiary or, in some cases, quaternary structure that is necessary for biological activity. In addition, protein instability has been observed during the preparation of protein-loaded microspheres. Usually, an aqueous protein solution is dispersed in an organic polymer solution by using a homogenizer or sonicator to create a water-in-oil (w/o) emulsion. The exposure of proteins to organic solvent or aqueous/organic interface might have adverse effects on their stability.
Consciousness and the Laws of Physics

We have a much better understanding of the dynamics and ontology of physics than we do of consciousness. I consider ways in which intrinsically mental aspects of fundamental ontology might induce modifications of the known laws of physics, or whether they could be relevant to accounting for consciousness if no such modifications exist. I suggest that our current knowledge of physics should make us sceptical of hypothetical modifications of the known rules, and that without such modifications it's hard to imagine how intrinsically mental aspects could play a useful explanatory role.