Miracle-dz/UniFAR-FTUs huggingface dataset:
A blended distance to define"people-like-me"

Curve matching is a prediction technique that relies on predictive mean matching, which matches donors that are most similar to a target based on the predictive distance. Even though this approach leads to high prediction accuracy, the predictive distance may make matches look unconvincing, as the profiles of the matched donors can substantially differ from the profile of the target. To counterbalance this, similarity between the curves of the donors and the target can be taken into account by combining the predictive distance with the Mahalanobis distance into a `blended distance' measure. The properties of this measure are evaluated in two simulation studies. Simulation study I evaluates the performance of the blended distance under different data-generating conditions. The results show that blending towards the Mahalanobis distance leads to worse performance in terms of bias, coverage, and predictive power. Simulation study II evaluates the blended metric in a setting where a single value is imputed. The results show that a property of blending is the bias-variance trade off. Giving more weight to the Mahalanobis distance leads to less variance in the imputations, but less accuracy as well. The main conclusion is that the high prediction accuracy achieved with the predictive distance necessitates the variability in the profiles of donors.
Documenting Data Production Processes

The opacity of machine learning data is a significant threat to ethical data work and intelligible systems. Previous research has addressed this issue by proposing standardized checklists to document datasets. This paper expands that field of inquiry by proposing a shift of perspective: from documenting datasets towards documenting data production. We draw on participatory design and collaborate with data workers at two companies located in Bulgaria and Argentina, where the collection and annotation of data for machine learning are outsourced. Our investigation comprises 2.5 years of research, including 33 semi-structured interviews, five co-design workshops, the development of prototypes, and several feedback instances with participants. We identify key challenges and requirements related to the integration of documentation practices in real-world data production scenarios. Our findings comprise important design considerations and highlight the value of designing data documentation based on the needs of data workers. We argue that a view of documentation as a boundary object, i.e., an object that can be used differently across organizations and teams but holds enough immutable content to maintain integrity, can be useful when designing documentation to retrieve heterogeneous, often distributed, contexts of data production.
Evaluating the Performance of LSTM in Traffic Flow Prediction at Different Time Scales

— Traffic congestion in smart and major cities has been one of the main problems in traffic management and system guidance. Due to the fast economic growth and the highly increasing number of vehicles, the first challenge is to successfully predict accurate traffic flow information to minimize traffic congestion and traffic accidents. Not long ago, many researchers have started to focus more and more concentration on deep learning techniques, including Recurrent Neural Networks (RNN), especially due to their capacity to learn long-term dependencies of sequence data and capture the nonlinearity nature of traffic flow. This paper has applied three different kinds of recurrent neural network architecture such as simple RNN, Long Short Term Memory (LSTM) and Gated Recurrent Unit (GRU) by considering different time intervals. The dataset collected from the California department of transportation in the year 2018 and 2019 have been used; however, few missing values have been discovered due to incorrect measurement and equipment errors. In this study, to ensure the data quality to be trained in our models and increase the model performance, the mean method on the same hours has been used to calculate and substitute the missing values. LSTM model is proposed in this study on both short and long time intervals. Two popular metrics, including Mean Absolute Percentage Errors (MAPE) and Root Mean Squared Error (RMSE), have been used to evaluate the prediction efficiency.
Comparison of Guy’s Stone Score and S.T.O.N.E Nephrolithometry Score for Predicting Outcome of Percutaneous Nephrolithotomy

Objective: To compare Guy’s Stone Score and S.T. O.N. E Nephrolithometry Score for predicting stone-free status and complication after Percutaneous Nephrolithotomy (PCNL). Materials and methods: A prospectively maintained database of 104 cases, who underwent PCNL from January to October 2016 in Tribhuvan University Teaching Hospital, was analyzed. Guy’s Stone Score and S.T. O.N. E Nephrolithometry Score were calculated based on preoperative computerized tomography images and their correlation with stone clearance and complications was determined statistically using Spearman’s Rank Correlation. Stone clearance was evaluated with X-ray or ultrasound of the kidneys, ureters and bladder up to three months after PCNL and perioperative complications within one month were recorded as modified Clavien-Dindo classification for PCNL. Result: Mean Guy’s Stone Score in stone-free group and stone-residue group were 1.7 and 2.9 respectively. Similarly, mean S.T. O.N. E Nephrolithometry Score in stone-free group and stone-residue group were 7.2 and 9.8 respectively. Both scores were significantly associated with postoperative stone-free status (p<0.001). In addition, both Guy’s Stone Score and S.T. O.N. E Nephrolithometry Score correlated with complications graded by modified Clavien-Dindo classification for PCNL (p=0.004 and 0.001 respectively) and length of hospital stay(p=0.001 and 0.001 respectively). Conclusion: Guy’s Stone Score and S.T. O.N. E Nephrolithometry Score equally predicted the stone-free status and complications after PCNL. Both of these scoring systems can be used to stratify the complexity of renal stone preoperatively.
Rough Terrain Beetle Robot

: Normally some of the risky and various tasks cannot be done by human. Thus there is need for change in present era. So, robot can be a good and effective option for risky purposes. Robot plays various roles in different fields of industries, medical, colleges, home appliances and military and defense. The proposed work is to design and develop a rough terrain beetle robot. Now a day’s robot’s comes in the market works on a simple terrain while we are on a project which works on plain surface as well as rough surface such as forest, hilly and rocky areas. In this paper we are focusing on the use of rough terrain robots instead of using other simple robots. This paper also presents an automatic robot which uses different technologies like Infrared sensor, PIR sensor etc. and this paper proposed a low voltage power supply, low cost and wireless robot which is controlled using AVR microcontroller.
Interleukin-6 Levels in Patients of Angina Pectoris

Objective; To determine the frequency of raised Interleukin-6 level in patients presenting with angina pectoris. Methodology; This was a cross sectional study, conducted at Services Hospital, Lahore during July to December 2017. The cases of both gender and age more than 30 years were included. Angina pectoris was described with central crushing chest pain lasting for less than half hour along with normal cardiac enzymes with or without ECG changes of ST segment depression or T wave inversion. The cases with electrolyte imbalance, raised cardiac enzymes and end stage renal or liver disease were excluded from the study. The value of IL-6 more than 5 ng/ml was considered as raised. Results; There were 100 cases of angina pectoris in the present study with mean age of 54.11±9.23 years. The mean IL-6 level were 21.45±10.03. There were 63 (63%) males in this study. There were 48 cases of smoking, 36 cases of HTN, 26 cases of DM in this study. Raised IL-6 level were seen in 66 (66%) out of 100 cases. Raised IL-6 levels were observed in 27 (75%) cases with HTN with p= 0.02. Raised IL-6 was also significantly high in cases that had DM where it was seen in 19 (73.08%) and in smoker where it was observed in 36 (75%) of cases out of their respective groups with p values of 0.03 and 0.01 respectively. Conclusion; Interleukin-6 level common and seen in every 2/3 rd of the cases in AP and these are significantly
Valence-dependent disruption in processing of facial expressions of emotion in early visual cortex ̶ a TMS study

Our visual inputs are often entangled with affective meanings in natural vision, implying the existence of extensive interaction between visual and emotional processing. However, little is known about the neural mechanism underlying such interaction. This exploratory transcranial magnetic stimulation (TMS) study examined the possible involvement of the early visual cortex (EVC, area V1/V2/V3) in perceiving facial expressions of different emotional valences. Across three experiments, single-pulse TMS were delivered at different time windows (50˗150 ms) after brief 10 ms onset of face images, and participants reported the visibility and perceived emotional valence of faces. Interestingly earlier TMS at ~90 ms only reduced the face visibility irrespective of displayed expressions, but later TMS at ~120 ms selectively disrupted the recognition of negative facial expressions, indicating the involvement of EVC in the processing of negative expressions at a later time window, possibly beyond the initial processing of fed-forward facial structure information. The observed TMS effect was further modulated by individuals’ anxiety level. TMS at ~110-120 ms disrupted the recognition of anger significantly more for those scoring relatively low in Trait anxiety than the high-scorers, suggesting cognitive bias influences the processing of facial expressions in EVC. Taken together, it seems that EVC is involved in structural encoding of (at least) negative facial emotional valence, such as fear and anger, possibly under modulation from higher cortical areas.
Gene Therapy for Metabolic Diseases 1

REFERENCES Friedmann, T. 1994. Gene therapy for neurological disorders. Trends in Genetics 10:210-214. Gilboa, E. and C. Smith. 1994. Gene therapy for infectious diseases: The AIDS model. Trends in Genetics 10:139-144. Gordon, J. 1991. Strategies for human germ-line gene therapy. Pp. 221229 in Preimplantation Genetics, Y. Verlinsky and A. Kuliev, eds. New York: Plenum Press. Kolberg, R. 1995. RAC tiptoes into new territory: In utero gene therapy. J. NIH Res. 7:37-39.
ANALYSIS OF THE PM MOTOR WITH EXTERNAL ROTOR FOR DIRECT DRIVE OF ELECTRIC WHEELCHAIR

The paper deals with analysis of properties of synchronous motor with external permanent magnets rotor. The mathematical analysis and equivalent circuit of permanent magnet synchronous motor (SMPM) is presented. In the parts of the paper the electromagnetic design, construction design and FEM Simulation of a SMPM is described and its properties are analysed. In the paper the results of simulation in Matlab/Simulink of torque, speed and current on the base mathematical model are shown.
ELASTIC ROUTE MAPPING OVERLIES HELPFUL COMBINATION IN WNSS

Within this area, the cycle is predicted to garner sustained by coordinated bag forwarding. However, some read has designed around relief in discrete WSNs, most of them veto hold the collection in the choices of everybody WSN balk abuse resource, handle launch procedure, the size of nodes, nodes locations, energy reduction, capsule size and/or data standard transmission calculate, in this way. Inside the odd touch, ignorant life development with aid may not be fair. In this disclose, we praise a fair responsive routing scheme of variant overlapped WSNs. It introduces a certain pool to help stifle the way of a person's discharge by integrated forwarding. The concentration pool plays contracting of speculator absolutely aid. As fundamental sensor systems (WSNs) are mostly instill, numerous beetling WSNs bet on one area be common.
DOSAGE OF CISPLATIN AND RELATED TOXICITY OF CANCER PATIENTS BASED ON BODY FAT AND MUSCLE MASS

In oncology practice, the human body surface area (BSA) is used for the calculation of the dose of chemotherapy. The human BSA is determined by derived formulas, but it is not directly linked to the pharmacokinetics of the drugs. Obesity alters the disposition of drugs pharmacokinetics, which should be considered when prescribing medications in this patient population. Failure to adjust doses in obesity may result in increased toxicity. The aim of this study was to assess predictors of an increase in the level of trygliceride considered to be among the cardiovascular risk factors. Method. The study involved 118 oncology patients with various tumor localizations. The patients underwent anthropometric measurements (height, weight, circumference, fat fold thickness, the distance between the epicondyls above the joint), and the BSA (according to the Mosteller formula). Patients who received cisplatin chemotherapy were analyzed in serum triglyceride levels before and after the treatment. Results. A comparison of female and male subsamples revealed no significant in variance between sexes and no significant differences in initial triglyceride, triglyceride change, and in the age between groups. Body fat mass was relatively higher in females, while body muscle mass and bone mass were relatively higher in males. There was a difference in the cisplatin dose, with a higher dose for males than for females. The results demonstrate that the higher cisplatin dose and higher body fat mass are significant predictors of an increase in triglyceride for both sexes.
Novel Rate-Jitter Control Algorithms Modeling and Analysis

—Time Division Multiplexing over Internet Protocol (TDMoIP) is a transport technology that extends the voice, video and data trafﬁc transparently over IP. When TDM trafﬁc is packetized and injected into a packet switched network (PSN) for transportation, packets arrive at the destination with different inter-arrival times, due to variable delay (jitter) introduced by PSN. This network induced jitter should be minimized, because TDM devices operate at constant bit rate. Problem of jitter from theoretical (competitive and statistical analysis) to more practical view point had been well studied. In this paper, we have proposed two on-line algorithms, algorithm-A and algorithm-B to minimize rate-jitter. We have shown both analytically and by simulation that the rate-jitter achieved by algorithm-A is strictly less than the rate-jitter of an on-line algorithm proposed in a previous work. The simulation results shows that algorithm-B also achieves less rate-jitter than the reference algorithm. We also undertake the statistical analysis of above algorithms, in particular, we have modeled jitter buffer as an MMPP / (cid:101) D / 1 / B on queue by making two assumptions on Markov modulated Poisson process (MMPP) and steady state queue length distribution is calculated. The correctness of the analytical results corresponding to our proposed algorithms is veriﬁed with simulation results. From the simulation results, it is also shown that the mean waiting time of a packet in the buffer is less for both proposed algorithms compared with the reference algorithm.
STAPHYLOCOCCUS AUREUS DSBA DOES NOT HAVE A DESTABILISING DISULFIDE: A NEW PARADIGM FOR BACTERIAL OXIDATIVE FOLDING

(  ), 10 µ M SaDsbA (  ), 10 µ M SaDsbA T153V (  ), 10 µ M SaDsbA E96Q (  )). Reactions were started by adding DTT to a final concentration of 0.35 mM and the aggregation of reduced insulin was followed 650 nm every 30 s. B. Refolding of scrambled RNase. Reshuffling of scRNase was carried out by incubating the scrambled enzyme (40 µ M) in 100 mM sodium phosphate/NaOH, pH 7.0, 1 mM EDTA, 10 µ M DTT and in the presence of 10 µ M EcDsbC (  ) or SaDsbA (  ). Folded RNase was used as a positive control (  ). The cleavage of cCMP by native RNase A was followed spectroscopically at 296 nm.
Effect of Pressure on Essential Oil Yield of Chromolaena Odorata Leaves Extract using Supercritical Fluid Carbon Dioxide

Most of the previous researchers used conventional extraction technique such as steam distillation and solvent extraction method in Chromolaena Odorata extraction. Therefore, in this study a clean extraction method that is Supercritical Fluid Extraction (SFE) technology using supercritical carbon dioxide as a solvent (SC-CO2) was introduced for Chromolaena Odorata leaves extraction to produce oil of bioactive components. The objective of this research was to find the optimum pressure for the highest oil yield extracted. The extraction was conducted within a range of temperature (40, 45 and 50°C) and pressure (3000, 3500, 4000, 4500 and 5000psi), at a constant flowrate (24 ml/min) for 10, 20, 30, 40, 50 and 60 minutes of extraction time. From the studies, it was found that extraction pressure is an important factor that can affect the extraction yield where the oil yield increased as the pressure increased due to the increasing amount of CO2 consumed where it boost the density of the solvent to interact with the solute. The highest oil yield is 51.20% at pressure of 4000psi and temperature 50°C. Whereas at the highest pressure of 5000psi, the oil yield is the lowest. This shows that the extraction is not suitable at pressure 5000psi.
Comparative Study of One Dimensional and Two Dimensional Dynamic Time Warping

Today’s trend in Speech recognition applications include automatic answering machines, dictation systems, command control applications, speaker identification system etc. In this paper, early Patten matching technique DTW is studied used to find the similarity of speech data using MFCC and LPCC features. A small vocabulary containing command words used to test the already existing method in two ways. One-dimensional raw speech data of command words are considered as input the algorithm. In the second method, two-dimensional features of the same set of data were considered. Finally, these two methods were compared in terms of efficiency.
A Decision Support Approach for Quality Management Based on Artificial Intelligence Applications

—This paper describes the application of a novel domain-independent decision support approach for product quality management. It is based on customer satisfaction research through deep analysis of consumer reviews posted on the Internet in natural language. Artificial Intelligence (AI) techniques, such as Text Mining and Data Mining, are used for realization of consumer reviews analysis. In paper, specific Internet resources (such as yelp.com, tripadvisor.com, tophotels.ru) are used for accumulating customer reviews as a data source is considered. This is performed in accordance with the quality standard ISO 10004 proposed decision support approach, which allows for both qualitative and quantitative customer satisfaction surveys to be carried out. The output of the quantitative survey are values of customer satisfaction by product and each product’s aspect. The output of the qualitative survey are significance values of products aspect for customers and identified latent relations between satisfaction by product and satisfaction by products’ aspects. The proposed approach is performed as a prototype of a Decision Support System. To evaluate the efficacy of the proposed approach, an experiment on hotel’s customer satisfaction has been carried out. The obtained results prove the efficacy of the proposed decision support approach for quality management and the concept of using it instead of classical methods of qualitative and quantitative research of customer satisfaction.
organization and the completion of cytokinesis Tektin 2 is required for central spindle microtubule

associates with the spindle poles throughout mitosis, organizes the spindle midzone microtubules during anaphase, and assembles into the midbody matrix surrounding the compacted midzone microtubules during cytokinesis. Tek2 small interfering RNA (siRNA) disrupts central spindle organization and proper localization of MKLP1, PRC1, and Aurora B to the midzone and prevents the formation of a midbody matrix. Video microscopy revealed that loss of Tek2 results in binucleate cell formation by aberrant fusion of daughter cells after cytokinesis. Although a myosin II inhibitor, blebbistatin, prevents actin-myosin contractility, the microtubules of the central spindle are compacted. Strikingly, Tek2 siRNA abolishes this actin-myosin – independent midzone microtubule compaction. Thus, Tek2-dependent organization of the central spindle during anaphase is essential for proper midbody formation and the segregation of daughter cells after cytokinesis.
A SCENARIO BASED APPROACH ON HOW NON-VESSEL OPERATING COMMON CARRIERS CAN CHALLENGE THE UNCERTAIN ENVIRONMENT OF OCEAN CARRIERS

The aim of this work is in the first step to uncover different possible scenarios Non-Vessel Operating Common Carriers (NVOCCs) might face in the near future. In the second step, early warning signals and strategic implementations have been developed to allow NVOCCs better preparation and proactive actions to master upcoming challenges. Due to the unpredictable Ocean Freight market, the scenario based planning approach is used to allow a broad view on possible future scenarios. Qualitative interviews with industry experts have been conducted to gain insights into major challenges and uncertainties. The two main critical uncertainties - rate volatility and carrier consolidations – form the basis for four different possible future scenarios. Rates might stabilize or remain volatile; carriers might consolidate into fewer players on the market or might join in alliances. Full transparency regarding the carrier’s financial situation is key to foresee critical situations. Stable long-term contracts with carriers and customers allow better planning. Service differentiation and quality lead to customer loyalty, which could lead to secure the business in difficult times. This work summarizes different influence factors of the ocean freight industry and serves as a basis to support future strategic implementations.
Forest Degradation Associated with Logging Frontier Expansion in the Amazon: The BR-163 Region in Southwestern Para´, Brazil

: Forest degradation is the long-term and gradual reduction of canopy cover due to forest ﬁre and unsustainable logging. A critical consequence of this process is increased atmospheric carbon emissions. Although this issue is gaining attention, forest degradation in the Brazilian Amazon has not yet been properly addressed. The claim here is that this process is not constant throughout Amazonia and varies according to colonization frontiers. Moreover, the accurate characterization of degradation requires lengthy observation periods to track gradual forest changes. The forest degradation process, the associated timeframe, spatial patterns, trajectories, and extent were characterized in the context of the Amazon frontiers of the 1990s using 28 years (1984–2011) of annual Landsat images. Given the large database and the characteristic of logging and burning, this study used data mining techniques and cell approach classiﬁcation to analyze the spatial patterns and to construct associated trajectories. Multitemporal analysis indicated that forest degradation in the last two decades has caused as many interannual landscape changes as have clear-cuts. In addition, selective logging, as a major aspect of forest degradation, affected a larger amount of forest land than did forest ﬁre. Although a large proportion of logged forest was deforested in the following years, selective logging did not always precede complete deforestation. Instead, the results indicate that logged forests were abandoned for approximately 4 years before clearance. Throughout the forest degradation process, there were no recurrent forest ﬁres, and loggers did not revisit the forest. Forest degradation mostly occurred as a result of a single selective logging event and was associated with low-intensity forest damage.