Miracle-dz/UniFAR-FTUs huggingface dataset:
On the Solution of the Optimal Power Flow for Three-Phase Radial Distribution Networks With Energy Storage

We study a multiperiod optimal power flow (OPF) problem in unbalanced three-phase radial distribution networks with batteries. To address this problem, we first take the resistance-line battery model that treats lossy batteries by adding resistive lines and virtual buses. Then, we derive a linearization for the power flow equations, called generalized three-phase simplified DistFlow, which accounts for shunt elements. Also, it is exact at a freely chosen point while having globally good performance. Using it, we extend the heuristic iterative OPF algorithm, CoDistFlow, to unbalanced three-phase networks. At convergence, three-phase CoDistFlow gives a solution that satisfies the exact nonlinear power-flow equations and the exact security constraints. To theoretically guarantee the convergence of three-phase CoDistFlow, we develop the forced convergent three-phase CoDistFlow. Moreover, we show how to adapt the three-phase CoDistFlow to solve a scenario-based OPF in the presence of uncertainties, whereas other existing OPF solution methods may not offer this possibility. Finally, we perform evaluations on the IEEE 123-bus test feeder and comparisons with Ipopt.
New Heuristics for Scheduling and Distributing Jobs under Hybrid Dew Computing Environments

Mobile grid computing has been a popular topic for researchers due to mobile and IoT devices’ ubiquity and their evergrowing processing potential. While many scheduling algorithms for harnessing these resources exist in the literature for standard grid computing scenarios, surprisingly, there is little insight into this matter in the context of hybrid-powered computing resources, typically found in Dew and Edge computing environments. This paper proposes new algorithms aware of devices’ power source for scheduling tasks in hybrid environments, i.e., where the battery- and non-battery-powered devices cooperate. We simulated hybrid Dew/Edge environments by extending DewSim, a simulator that models battery-driven devices’ battery behavior using battery traces profiled from real mobile devices. We compared the throughput and job completion achieved by algorithms proposed in this paper using as a baseline a previously developed algorithm that considers computing resources but only from battery-dependent devices called Enhanced Simple Energy-Aware Schedule (E-SEAS). The obtained results in the simulation reveal that our proposed algorithms can obtain up to a 90% increment in overall throughput and around 95% of completed jobs in hybrid environments compared to E-SEAS. Finally, we show that incorporating these characteristics gives more awareness of the type of resources present and can enable the algorithms to manage resources more efficiently in more hybrid environments than other algorithms found in the literature.
Performance Improvements of AODV by Black Hole Attack Detection Using IDS and Digital Signature

Department of Information and Communication Technology (ICT), Comilla University, Cumilla, Bangladesh Centre for Cyber Security, Faculty of Information Science and Technology, Universiti Kebangsaan Malaysia (UKM), 43600 UKM Bangi, Selangor, Malaysia Department of Computer Science and Information Technology, Maulana Azad National Urdu University, Hyderabad, India Computing Department, Engineering Faculty, Global College of Engineering and Technology, Oman
Semantic Models for Network Intrusion Detection

The presented paper describes the design and validation of the hierarchical intrusion detection system (IDS), which combines machine learning approach with the knowledgebased methods. As the knowledge model, we have proposed the ontology of network attacks, which allow to us decompose detection and classification of the existing types of attacks or formalize detection rules for the new types. Designed IDS was evaluated on a widely used KDD 99 dataset and compared to similar approaches. Keywords—ontologies, network security incidents, machine learning
HEAVY METAL TOLERANCE OF THREE DIFFERENT BACTERIA ISOLATED FROM INDUSTRIAL EFFLUENT

The pollution of the environment with toxic heavy metals is spreading throughout the world along with industrial progress. Microorganisms and Microbial products can be highly efficient bioaccumulations of soluble and particulate forms of metals especially dilute external solutions. Microbes related technologies may provide an alternative or addition to conventional method of metal removal or metal recovery. The present paper deals with t he isolation and characterization of heavy metal tolerant bacteria from Industrial effluents and determination of Minimum Inhibitory Concentration (MIC) of the heavy metal resistant bacteria isolates. Among various outcomes of the study, important aspect i s the metal accumulating ability of these isolates which can be applied in removal and recovery of metals. Minimum inhibitory concentration (MIC) values for were 450 µg/ml, for B. subtilis were 400 µg/ml and for E. coli chl oride salts of cadmium. Minimum inhibitory concentration (MIC) values for were resistant to 450 µg/ml, for B. subtilis were 300 µg/ml for the chloride salts of Nickel. Minimum inhibitory concentration (MIC) values f aureus were 300 µg/ml for B. subtilis were 400 µg/ml the Lead nitrate. These three strains of bacteria that were resistant to heavy metals were chosen for further investigations. Heavy-metal chloride salt of cadmium at varying concentrations (50 µg/ml, 100 µg/ml, 150 µg/ml, 200 µg/ml, 250 µg/ml, 300 µg/ml, 350 µg/ml, 400 µg/ml, 450 µg/ml, 500 µg/ml) were taken for study. The three isolates, all with significant metal up taking ability can be either u as a mixed consortium to act efficiently in lesser time. The metal accumulation and nanoparticle generation by the cell can be further explored at a molecular level. This can further help in genetic manipulation for more efficiency
Family and occupational functioning following military trauma exposure and moral injury

Introduction Evidence is growing regarding the impact of potentially morally injurious events (PMIEs) on mental health; yet how moral injury may affect an individual’s occupational and familial functioning remains poorly understood. Method Thirty male veterans who reported exposure to either traumatic or morally injurious events and 15 clinicians were recruited for semi-structured qualitative interviews. Results While many veterans experienced psychological distress postevent, those who experienced PMIEs especially reported social withdrawal and engagement in aggressive, risk-taking behaviours. This was highly distressing for family members and created a tense, volatile home and workplace environment that was difficult for others to navigate. Following PMIEs, employment could be used as a cognitive avoidance strategy or as a means to atone for transgressive acts. In cases of moral injury, clinicians considered that targeted support for spouses and accessible guidance to help children to better understand how their military parent may be feeling would be beneficial. Conclusions This study provides some of the first evidence of the pervasive negative impact of PMIEs on veterans’ familial and occupational functioning. These findings highlight the need to comprehensively screen for the impact of moral injury on daily functioning in future studies that goes beyond just an assessment of psychological symptoms.
Charge Carrier Transport in Poly(N-vinylcarbazole):CdS Quantum Dot Hybrid Nanocomposite

Hybrid organic:inorganic materials have emerged as a novel class of electronic and optoelectronic media for a number of potential technological applications. However, very little fundamental understanding of charge carrier transport in such hybrid materials exists. A knowledge of the influence of nanoparticle doping on charge carrier mobility in nano composites becomes important in order to optimize properties for photorefractive and photovoltaic operations. We report here a study of the mobility of holes in a model nanoparticle-sensitized hybrid organic:inorganic system consisting of poly(N-vinylcarbazole) (PVK) doped with quantum dots of cadmium sulfide. The mobility of holes (dominant carriers in the PVK host materials) was measured using the conventional time-of-flight technique with injection of holes from a selenium layer. Though photocurrent transients exhibit features typical of dispersive transport in an amorphous semiconductor, certain deviations from the original Scher-Montroll theory are obser.
Development and testing of a cobalt dicarbollide based solvent extraction process for the separation of cesium and strontium from acidic tank waste

A fission product solvent extraction technology for the simultaneous extraction of Cs and Sr from acidic tank waste has been developed as a collaborative effort of the Idaho National Engineering and Environmental Laboratory (INEEL) and the Khlopin Radium Institute in St. Petersburg, Russia. The process is being developed as a potential method for treating the current five million liter inventory of acidic tank waste stored at the INEEL. The fission product extraction process is based on an immiscible organic phase comprised of chlorinated cobalt dicarbollide (CCD, Cs extractant) and polyethylene glycol (PEG, Sr extractant) dissolved in a poly-fluorinated sulfone diluent. Batch contact experiments and preliminary flowsheet testing were used to define potential solvent composition and flowsheet configuration. This information was used to specify an initial flowsheet for countercurrent testing with simulated tank waste using a 3.3-cm diameter centrifugal contactor pilot plant at the INEEL. The initial extractant composition was 0.08 M CCD, 0.6 vol% PEG-400 in a phenyl trifluoromethyl sulfone (FS-13) diluent. Approximately 1.5 L of solvent was used (with continuous recycle) to treat 43 L of simulated tank waste during 75 hr of continuous operation. Greater than 99.992% of the Sr and 97.45% of the Cs were extracted from the simulated tank waste and recovered in the strip product. The matrix components Ba (>99.6%), Pb (99.8%), and Ca (10.6%) were also extracted from the simulated tank waste and recovered in the strip product. Less than 1% of the K, Na, Fe, Zr, and Mo were extracted from the tank waste simulant. Finally, none of the analytically determined waste components were observed to build up in the organic solvent.
Incidence and predictors of surgical site infection after distal femur fractures treated by open reduction and internal �xation: a prospective single-center study

Background: There remain limited data on the epidemiological characteristics and related predictors of surgical site infection (SSI) after open reduction and internal �xation (ORIF) for distal femur fractures. We designed this single-centre prospective study to explore and resolve these clinical problems. Methods (cid:0) From October 2014 to December 2018, 364 patients with distal femur fractures were treated with ORIF and followed for complete data within one year. Receiver operating characteristic (ROC) analyses, univariate Chi-square analyses, and multiple logistic regression analyses were used to screen the adjusted predictors of SSI. Results : The incidence of SSI was 6% (22/364): 2.4% for super�cial SSIs and 3.6% for deep SSIs. Staphylococcus aureus (methicillin-resistant S. aureus in 2 cases) was the most common pathogenic bacteria (7, 36.8%). In multivariate analysis, parameters independently associated with SSI were: Open fracture (OR: 7.27, p = 0.003), drain use (OR: 4.11, p = 0.037), and incision cleanliness (OR: 3.53, p = 0.002). An albumin/globulin (A/G) level ≥ 1.35 (OR: 0.23, p = 0.042) was an adjusted protective factor for SSI. Conclusions : The SSI after ORIF affected approximately one in 15 patients with distal femur fractures. We recommend that maintaining A/G levels higher than 1.35 is introduced during hospitalization and elaborative evaluation of drain use is conducted for reducing the risk of post-operative SSI. Trial 2014. We 2014 study protocol was conducted according to the Declaration Board. ethics committee approved the Data used in this study were obtained from the patients surgeries 2018.
The role of long-lived greenhouse gases as principal LW control knob that governs the global surface temperature for past and future climate change

The climate system of the Earth is endowed with a moderately strong greenhouse effect that is characterised by non-condensing greenhouse gases (GHGs) that provide the core radiative forcing. Of these, the most important is atmospheric CO2. There is a strong feedback contribution to the greenhouse effect by water vapour and clouds that is unique in the solar system, exceeding the core radiative forcing due to the non-condensing GHGs by a factor of three. The significance of the non-condensing GHGs is that once they have been injected into the atmosphere, they remain there virtually indefinitely because they do not condense and precipitate from the atmosphere, their chemical removal time ranging from decades to millennia. Water vapour and clouds have only a short lifespan, with their distribution determined by the locally prevailing meteorological conditions, subject to Clausius–Clapeyron constraint. Although solar irradiance is the ultimate energy source that powers the terrestrial greenhouse effect, there has been no discernable long-term trend in solar irradiance since precise monitoring began in the late 1970s. This leaves atmospheric CO2 as the effective control knob driving the current global warming trend. Over geological time scales, volcanoes are the principal source of atmospheric CO2, and the weathering of rocks is the principal sink, with the biosphere participating as both a source and a sink. The problem at hand is that human industrial activity is causing atmospheric CO2, to increase by 2 ppm yr−1, whereas the interglacial rate has been 0.005 ppm yr−1. This is a geologically unprecedented rate to turn the CO2 climate control knob. This is causing the global warming that threatens the global environment.
Measurement of electron temperature and density in an argon microdischarge by laser Thomson scattering

Laser Thomson scattering in a novel, backscattered configuration was employed to measure the electron temperature (Te) and electron density (ne) in argon dc microdischarges, with an interelectrode gap of 600μm. Measurements were performed at the center of the gap that corresponds to the positive column. For 50mA microdischarge current and over the pressure range of 300–700Torr, the plasma parameters were found to be Te=0.9±0.3eV and ne=(6±3)×1013cm−3, in reasonable agreement with the predictions of a mathematical model.
Influence of grain size, surface energy, and deviatoric stress on the pressure-induced phase transition of ZnO and AlN

The high pressure behavior of aluminum nitride (AlN) and zinc oxide (ZnO) nanocrystals was studied up to 30 GPa using second harmonic generation. ZnO (10 nm) crystals transform to the high pressure B1 phase at 16.6 GPa, ≈5 GPa higher than the corresponding value for a bulk sample. The transition of AlN (20 nm) and AlN (100 nm) occurred at 14 and 21.5 GPa at lower values than for bulk samples. Under non-hydrostatic pressure conditions, the transition pressures of ZnO (10 nm) and AlN (100 nm) decrease to 12.5 and 18 GPa, respectively. We determined the surface energy ( and ) of the B1 polymorphs. We show that the main reason for the size-dependent decrease of the transition pressure of AlN nanocrystals is due to the higher surface energy of the B4 phase relative to the surface energy of the B1 phase. We predict that it is possible to quench or synthesize pure B1 AlN to ambient conditions if the grain size is less than 8.5 nm.
Synthesis of trans-4-Methylaminorex from Norephedrine and Potassium Cyanate

An unusual and previously undocumented synthesis for trans-4-methylaminorex was determined to be in use at a clandestine laboratory. Conventional references unanimously describe the use of norephedrine (phenylpropanolamine, 2-amino-1-phenylpropan-1-ol) and cyanogen bromide to synthesize cis-4-methyl- aminorex. In this case, use of norephedrine and potassium cyanate gave predominantly trans-4-methylaminorex. This new synthesis is explored, and its intermediates and byproducts are characterized.
HIGH-PRESSURE GAS FROM LITHIUM HYDRIDE AND SEA WATER

Abstract : Tests were made to determine the quantity and rate of gas produced from the lithium hydride-sea water reaction. The effects of particle size, pressure, temperature, water composition, water-lithium hydride ratio, and additives to the lithium hydride were investigated. In addition, a gas inflation system for torpedo recovery using lithium hydride was designed and tested in the ocean. Lithium hydride and water were found to react completely at a ratio of 25 (or more) parts water: 1.0 part lithium hydride, by weight. The effects of other variables on the reaction were minor. The lithium hydride torpedo-recovery system successfully raised 50 pounds from a depth of 2,600 feet.
Shapley Explanation Networks

Shapley values have become one of the most popular feature attribution explanation methods. However, most prior work has focused on post-hoc Shapley explanations, which can be computationally demanding due to its exponential time complexity and preclude model regularization based on Shapley explanations during training. Thus, we propose to incorporate Shapley values themselves as latent representations in deep models thereby making Shapley explanations first-class citizens in the modeling paradigm. This intrinsic explanation approach enables layer-wise explanations, explanation regularization of the model during training, and fast explanation computation at test time. We define the Shapley transform that transforms the input into a Shapley representation given a specific function. We operationalize the Shapley transform as a neural network module and construct both shallow and deep networks, called ShapNets, by composing Shapley modules. We prove that our Shallow ShapNets compute the exact Shapley values and our Deep ShapNets maintain the missingness and accuracy properties of Shapley values. We demonstrate on synthetic and real-world datasets that our ShapNets enable layer-wise Shapley explanations, novel Shapley regularizations during training, and fast computation while maintaining reasonable performance. Code is available at https://github.com/inouye-lab/ShapleyExplanationNetworks.
How does supervision aid cognitive behaviour therapy skill development? Perspectives of CBT trainees: a thematic analysis

Abstract Eleven cognitive behaviour therapy (CBT) trainees in Scotland were interviewed regarding their experiences of clinical supervision and its impact on their skill development. Using thematic analysis, the authors developed four main themes: Linking Theory to Practice, Mirroring CBT in Supervision, The Expert Supervisor, and Trainees’ Reluctance to Give Negative Feedback. Clinical supervision was essential in helping trainees to link theory to practice; particularly through audio recordings, discussing formulations, and modelling and role-play. A CBT-specific approach to supervision and a CBT expert supervisor were also identified as valuable to learning. Trainees were reluctant to give negative feedback to supervisors, fearing negative consequences. The findings inform supervision practice. Key learning aims Readers of this paper will be able to: (1) Describe trainees’ most valued elements of CBT supervision. (2) Determine key learning methods in CBT supervision. (3) Explain the value of modality specific CBT supervision. (4) Articulate the context of supervision in CBT training and consider mutual feedback as a method to address identified challenges.
Effect of dissociation of iron–boron pairs in crystalline silicon on solar cell properties

The effect of dissociation of interstitial iron‐substitutional boron (FeiBs) pairs, as it occurs under illumination in iron‐contaminated silicon solar cells, on the solar cell properties has been studied on the basis of numerical device simulations using reported recombination parameters for Fei and FeiBs. Most cell parameters are found to degrade during FeiBs dissociation. However, the open‐circuit voltage can also increase within certain ranges of the iron concentration. Critical iron concentrations are determined, giving the threshold contamination level above which a significant degradation in the corresponding cell parameter can be observed. The threshold iron contamination level of the open‐circuit voltage degradation is found to be up to two orders of magnitude larger than the threshold iron level of the short‐circuit current degradation. As the behaviour of the cell parameters under illumination is specific to the dissociation of FeiBs pairs, the characteristic changes in the cell parameters due to illumination may be used as a simple way of identifying iron contamination problems in silicon solar cells. Copyright © 2005 John Wiley & Sons, Ltd.
A MODELING STUDY ON HYDROLYSIS OF LACTOSE RECOVERED FROM WHEY AND β-GALACTOSIDASE STABILITY UNDER SONIC TREATMENT

In the present study, the aim was to investigate the effect of ultrasonication on the kinetics of hydrolysis of lactose recovered from whey. The effects of the duty cycle, acoustic power of sonifier, reaction volume, and the hydrolysis products on hydrolysis degree as well as on enzyme stability were studied. The hydrolysis reactions were carried out in 25 mM phosphate buffer solution by using a commercial β-galactosidase produced from Kluyveromyces marxianus lactis under the conditions of 37°C, pH 6.5, and processing time of 30 min. Under ultrasonic treatment, 92% of lactose charged was hydrolyzed and the residual enzyme activity was 77% under the optimum operational conditions: acoustic power of 20 W, duty cycle rate of 10%, and reaction volume of 250 mL. The corresponding values of hydrolysis degree and residual enzyme activity without ultrasonic irradiation were 81% and 68%, respectively. These results show that sonication was beneficial for hydrolysis of lactose recovered from whey. The mathematical models were derived by using the experimental data of residual lactose concentration and residual enzyme activity depending on the operating conditions. In addition, an exponential equation was used for reflecting the ultrasonic energy regarding the hydrolysis and enzyme inactivation. After evaluation of the data, the activation energy required for hydrolysis of lactose recovered from whey (E H ) and the inactivation energy for β-galactosidase enzyme (E D ) were found as 0.0489 and 0.0804 J mL−1, respectively.