Miracle-dz/UniFAR-FTUs huggingface dataset:
Key Factors to Consider when Predicting the Costs of Forwarding Contracts

Predicting the cost of forwarding contracts is a typical problem that logistics companies need to solve in order to optimize their business for a better profit. This is the challenge defined in the FedCSIS 2022 Competition where a five-year history of contract data and their delivery routes from a large Polish logistics company are provided to train a Machine Learning model. In addition to the contract data, historical wholesale fuel prices and euro exchange rates at the contract time are also provided. To address this challenge, we first designed a basic solution where we focused on feature engineering to find good impact features for the model. After that, the same set of features were used to train two different models: one using XGBoost and the other using LightGBM. The average predictions of the two boosting models were then used as the predictions for the next post-processing step. Finally, in the post-processing step, we designed and trained a simple linear regression model to capture the average monthly changes of the contract cost, given the changes of the fuel prices and euro exchange rates. These captured changes were used to post-process (adjust) the predictions in the previous step to address the issue that tree-based models could not predict the value that they did not see before. While the basic solution with careful feature selection gave us a place in the top-5, our post-processing strategy in the last step helped us win the 3rd prize in the competition.
Weight space structure and analysis using a finite replica number in the Ising perceptron

The weight space of the Ising perceptron, in which a set of random patterns is stored, is examined using the generating function of the partition function ϕ(n) = (1/N)log[Zn] as the dimension of the weight vector N tends to infinity, where Z is the partition function and represents the configurational average. We utilize ϕ(n) for two purposes, depending on the value of the ratio α = M/N, where M is the number of random patterns. For α<αs = 0.833. , we employ ϕ(n), in conjunction with Parisi’s one-step replica symmetry breaking scheme in the limit of , to evaluate the complexity that characterizes the number of disjoint clusters of weights that are compatible with a given set of random patterns, which indicates that, in typical cases, the weight space is equally dominated by a single large cluster of exponentially many weights and exponentially many small clusters of a single weight. For α>αs, on the other hand, ϕ(n) is used to assess the rate function of a small probability that a given set of random patterns is atypically separable by the Ising perceptrons. We show that the analyticity of the rate function changes at α = αGD = 1.245. , which implies that the dominant configuration of the atypically separable patterns exhibits a phase transition at this critical ratio. Extensive numerical experiments are conducted to support the theoretical predictions.
Reliability of Machine Learning in Eliminating Data Redundancy of Radiomics and Reflecting Pathophysiology in COVID-19 Pneumonia: Impact of CT Reconstruction Kernels on Accuracy

Background: Radiomical data are redundant but they might serve as a tool for lung quantitative assessment reflecting disease severity and actual physiological status of COVID-19 patients. Objective: Test the effectiveness of machine learning in eliminating data redundancy of radiomics and reflecting pathophysiologic changes in patients with COVID-19 pneumonia. Methods: We analyzed 605 cases admitted to Al Ain Hospital from 24 February to 1 July, 2020. They met the following inclusion criteria: age<inline-formula> <tex-math notation="LaTeX">$\geq 18$ </tex-math></inline-formula> years; inpatient admission; PCR positive for SARS-CoV-2; lung CT available at PACS. We categorized cases into 4 classes: mild <5% of pulmonary parenchymal involvement, moderate - 5-24%, severe - 25-49%, and critical <inline-formula> <tex-math notation="LaTeX">$\geq50$ </tex-math></inline-formula>%. We used CT scans to build regression models predicting the oxygenation level, respiratory and cardiovascular functioning. Results: Radiomical findings are a reliable source of information to assess the functional status of patients with COVID-19. Machine learning models can predict the oxygenation level, respiratory and
GENETIC ANALYSIS OF SUMATRAN ELEPHANTS IN SEBLAT NATURAL ECOTOURISM PARK BASED ON PARTIAL OF MITOCHONDRIAL CYTOCHROME B GENE

Sumatran elephant (Elephas maximus sumatranus Temminck, 1847) is one of the Asian elephant sub-species distributed in Sumatera Island and classified as endangered species due to hunting and high habitat fragmentation. This study aimed to analyze the genetic relationship of Sumatran elephants based on the mitochondrial cytochrome b gene (Cyt b). Blood samples were collected from 11 elephants in Seblat Natural Ecotourism Park. Based on mt-DNA Cytochrome b gene analysis, low genetic diversity was found in the Sumatran elephant population, indicated by 99-100% sequence similarity among elephant samples. Phylogenetic analysis showed that all elephants were in the same clade and has a close relationship with Borneo elephants. Additionally, the Median-joining network illustrated only two haplotypes in the Sumatran elephant population. The low genetic diversity of the Sumatran elephant indicates that a strategic breeding program should be seriously taken into account to prevent the Sumatran elephant from extinction.
Cardiac Mitochondria Dysfunction in Dyslipidemic Mice

Dyslipidemia triggers many severe pathologies, including atherosclerosis and chronic inflammation. Several lines of evidence, including our studies, have suggested direct effects of dyslipidemia on cardiac energy metabolism, but details of these effects are not clear. This study aimed to investigate how mild dyslipidemia affects cardiac mitochondria function and vascular nucleotide metabolism. The analyses were performed in 3- and 6-month-old knock-out mice for low-density lipoprotein receptor (Ldlr−/−) and compared to wild-type C57Bl/6J mice (WT). Cardiac isolated mitochondria function was analyzed using Seahorse metabolic flux analyzer. The mechanical function of the heart was measured using echocardiography. The levels of fusion, fission, and mitochondrial biogenesis proteins were determined by ELISA kits, while the cardiac intracellular nucleotide concentration and vascular pattern of nucleotide metabolism ecto-enzymes were analyzed using reverse-phase high-performance liquid chromatography. We revealed the downregulation of mitochondrial complex I, together with a decreased activity of citrate synthase (CS), reduced levels of nuclear respiratory factor 1 and mitochondrial fission 1 protein, as well as lower intracellular adenosine and guanosine triphosphates’ pool in the hearts of 6-month Ldlr−/− mice vs. age-matched WT. The analysis of vascular ecto-enzyme pattern revealed decreased rate of extracellular adenosine monophosphate hydrolysis and increased ecto-adenosine deaminase activity (eADA) in 6-month Ldlr−/− vs. WT mice. No changes were observed in echocardiography parameters in both age groups of Ldlr−/− mice. Younger hyperlipidemic mice revealed no differences in cardiac mitochondria function, CS activity, intracellular nucleotides, mitochondrial biogenesis, and dynamics but exhibited minor changes in vascular eADA activity vs. WT. This study revealed that dysfunction of cardiac mitochondria develops during prolonged mild hyperlipidemia at the time point corresponding to the formation of early vascular alterations.
Neuroscience and Blockchain

s Our brain is made of thousands of neurons that create a chain of different episodes stored in the human brain in a decentralized manner that shapes human conscious experience just like blockchain technology. Although the human brain can voluntarily delete some episodes stored by the mechanism of distributed neurons, this ability is limited. Thus, each episode is open to access and saved securely so that we do not confuse our childhood memories with movie characters same as blocks in a decentralized ledger (Allegri, 2021). In this paper, it is investigated that some properties of the human brain can be to some extent analogical to blockchain and that certain blockchain concepts can be applied to the development of neuroscience as knowledge of the workings of the human brain and memories. At the same time, the latest advancements in blockchain technology can be fruitful in the development of neuroscience. To closely examine the correlation between neuroscience and blockchain, decentralized ledger technology concepts and neuroscience basics are presented [1].
Measurement of the W boson helicity in tt decays

Ziel dieser Dissertation ist die Messung des Anteils an W Bosonen mit positiver Helizitaet aus Top-Antitop Zerfallen. Die Daten fur diese Analyse wurden mit dem D0 Detektor am Fermilab Tevatron in den Jahren 2002-2004 aufgezeichnet. Sie entsprechen einer integrierten Luminositaet von ca. 230 inversen pb. Die Messung benutzt den Zerfallswinkel theta zwischen dem geladenen Lepton und der (negativen) Flugrichtung des b-Quarks im Ruhesystem des W Bosons. Um den Winkel theta zu rekonstruieren, wird das Top-Antitop System mit Hilfe eines kinematischen Fits rekonstruiert, wobei die Masse des W Bosons und des Top Quarks als Nebenbedingungen ausgenutzt werden. Der Vergleich zwischen der erwarteten Verteilung in cos(theta) aus Monte Carlo Simulationen fuer verschiedene Anteile an rechtshaendigen W Bosonen, f+, mit der Verteilung in den Daten ergab das folgende Resultat fuer f+: f+ = -0.10 +- 0.17(stat) +- 0.07 (syst). Dieses Ergebnis schliesst theoretische Modelle die einen sehr grossen V+A Anteil im elektroschwachen geladenen Strom des Top Zerfalls vorhersagen aus.
A −20-dBm Sensitivity RF Energy-Harvesting Rectifier Front End Using a Transformer IMN

This article describes a fully integrated CMOS radio frequency energy-harvesting (RFEH) front end. It features an on-chip stacked step-up transformer integrated with a cross-coupled differential drive (CCDD) rectifier to enhance the input sensitivity. The transformer also serves as an on-chip balun for the CCDD rectifier. The CCDD rectifier innovates a gate-biasing technique and realizes coupling capacitors at the end of each stage to increase the subsequent stage biasing. Here, our RFEH front end operating at 900 MHz achieves an improved sensitivity of −20 and −19.2 dBm at the 1-V output for no-load and a 1- $\text{M}\Omega $ load, respectively.
Study of Open Charm Production in p+p Collisions at $\sqrt(s)$ = 200 GeV

The dissertation presents the measurement of electrons from heavy flavor decays in proton + proton collisions at RHIC at collision energy $\sqrt(s) = 200$ GeV. Two independent analysis techniques of signal extraction were performed. This is the first measurement of the Open Charm crossection at this collision energy and it is an important baseline measurement for comparison with nucleus + nucleus collisions. The modification of Open Charm production in heavy ion collisions compared to the presented p+p result can be used to study the final state interaction of the heavy quarks with hot dense matter inside the collisions. The results of the Open Charm measurements are compared to current pQCD predictions both in Leading Order (LO) $O(\alpha_s^2)$ and Next-to-Leading Order (NLO) $O(\alpha_s^3)$. The final result for the total Open Charm crossection is $\sigma_{c\bar{c}}= (0.920 \pm 0.148(stat)\pm 0.524(sys))$ mb.
Qualitative - Binary, Nominal and Ordinal Data Analysis in Medical Science

The outcome of any medical research is belonged to the human beings. The correct application of statistical test has its paramount importance. This article provides the details of categorical data analysis test with example and with its interpretation. It is included when to use Chi-square test (2*2 & R*C), Yate`s Correction, Fisher Exact test, Mc Nemartest manually as well as using Open Epi and R codes.
Using gradient boosting trees to predict the costs of forwarding contracts

When selling goods abroad or bringing them into the country from foreign partners, we face the problem of delivery. The division of responsibilities related to this between the manufacturer and the recipient sometimes varies. In such a situation, it is reasonable to use the services of a forwarding company. Then a forwarding contract is concluded, which specifies the details of the service, but the most important issue remains the selection of its price. In this paper, we present results obtained using the LightGBM method on the forwarding contracts pricing challenge held as part of the FedCSIS 2022 conference.
Duality in massive spin 2 theories in 2+1 dimensions (In spanish)

The equations of motion that must be satisfied by fields that constitute realizations of the Poincare group algebra, for integral spin, and mass m, are obtained. For the case of massive spin 2 these equations are satisfied by the selfdual, intermediate and the linear topologically massive models, whose actions are connected by duality transformations. These duality transformations incorporate the gauge invariances that distinguish one action from the other. The relation between their partition functions is briefly discussed.
The Boulware-Deser mode in 3D first-order massive gravity

Massive gravity in three dimensions accepts several different formulations. Recently, the 3-dimensional bigravity dRGT model in first order form, Zwei-Dreibein gravity, was considered by Bergshoeff {\it et al.} and it was argued that the Boulware-Deser mode is killed by extra constraints. We revisit this assertion and conclude that there are sectors on the space of initial conditions, or subsets of the most general such model, where this mode is absent. But, generically, the theory does carry 3 degrees of freedom and thus the Boulware-Deser mode is still active. Our results also sheds light on the equivalence between metric and vierbein formulations of dRGT model.
Stable High-Gain Linearly and Circularly Polarized Dielectric Resonator Antennas Based on Multiple High-Order Modes

Dielectric resonator antennas (DRAs) under high-order multiple-modes resonator (MMR) for stable high gain are proposed in this communication. The approach is to implement slot cuts on the surface of DR for reconstructing the electric field distribution of high-order resonance modes. In this way, the sidelobes are reduced and two high-order modes are reallocated to construct a continuous wide band. Various MMR configurations were proposed in this work. First, a DRA operating in TE<inline-formula> <tex-math notation="LaTeX">$^{\mathrm {x}}_{031}$ </tex-math></inline-formula> and TE<inline-formula> <tex-math notation="LaTeX">$^{\mathrm {x}}_{051}$ </tex-math></inline-formula> modes is proposed with a pair of loaded slots to realize a fractional bandwidth (FBW) of 26% and a stable gain as high as 8.3 dBi within the desired passband. Second, a DRA with TE<inline-formula> <tex-math notation="LaTeX">$^{\mathrm {x}}_{051}$ </tex-math></inline-formula> and TE<inline-formula> <tex-math notation="LaTeX">$^{\mathrm {x}}_{071}$ </tex-math></inline-formula> modes is developed by introducing two pairs of slots, and an impedance FBW of 12.8% and a stable gain as high as 11 dBi are achieved. Third, three pairs of slots are introduced to the DRA with TE<inline-formula> <tex-math notation="LaTeX">$^{\mathrm {x}}_{091}$ </tex-math></inline-formula> and TE<inline-formula> <tex-math notation="LaTeX">$^{\mathrm {x}}_{0,11,1}$ </tex-math></inline-formula>modes, and an impedance FBW of 6.4% and a stable antenna gain as high as 12.3 dBi are obtained. At last, a circularly polarized (CP) DRA array with four proposed linearly polarized (LP) DRA elements is designed with an impedance bandwidth of 51.8%, a 3 dB axial-ratio (AR) FBW of 32%, a peak gain of 13.89 dBic, and a 1 dB gain bandwidth of 19.9%.
The risk of suicide in patients with critical illness: A population-based study in Taiwan

The authors investigated retrospectively the association between critical illness and risk of suicide attempts. The data are from Taiwan’s National Health Insurance Research Database. Propensity score matching, multivariable models, Kaplan–Meier analysis, and competing risk analysis were used to explore this association. The authors found that patients having an critical illness were associated with increased risk of suicide attempts after adjusting for risk factors (adjusted hazard ratio = 2.98; 95% confidence interval = 1.46–6.08). Among different subtypes of critical illness, patients with sepsis/septic shock exhibited the highest risk of suicide attempts (adjusted hazard ratio = 3.43, 95% confidence interval = 1.52–7.74). An association between critical illness and suicide attempts was shown. Sepsis/septic shock was found to confer the highest risk in these specific population.
Cuminaldehyde ameliorates hyperglycemia in diabetic mice.

BACKGROUND Animal-fats are rich in long-chain saturated fatty-acids, well known to induct diabetic distress among ingested insulin-insensitive individuals. In the current-study, bovine-fat was fed to selective mice breeds highly sensitized to heavy dietary lipid load. METHODS The later high fat diet (HFD) group indeed undergone diabetic-onset within weeks with a drastically altered feed-behavior pattern. It consumed more food, gained body mass, elevated homeostatic model assessment value and extensively glycosylated Hb transporters. RESULTS However, the hypothetical test drug (Cuminaldehyde or CA) with known therapeutic-potential worked-well to balance food efficiency-ratio and Hb- counts closer to control. The fat-soluble phytochemical mono-terpenoid (CA) promoted constitutive mono-hexose (glucose) consuming catabolic-cycles via mono-glycoprotein (insulin) signal-transduction. It resolved diabetogenic-upsurge of gluconeogenic-enzymes, reduced non-sugar (amino/fatty acids) utilization by restricting transamination/dephosphorylation and restored liver-glycogen reserves near to normal-group effectively at 10 mg/kg b.w dose. CONCLUSIONS Hence, the nutraceutical-potential (anti-diabetes/transaminitis ability) of administered exogenous redox-active agent CA can be entertained for evoking therapeutic-heath in diabetic human-community.
XMM-Newton Archival Study of the Ultraluminous X-Ray Population in Nearby Galaxies

We present the results of an archival XMM-Newton study of the bright X-ray point sources (LX > 1038 ergs s-1) in 32 nearby galaxies. From our list of approximately 100 point sources, we attempt to determine if there is a low-state counterpart to the ultraluminous X-ray (ULX) population, searching for a soft-hard state dichotomy similar to that known for Galactic X-ray binaries and testing the specific predictions of the intermediate-mass black hole (IMBH) hypothesis. To this end, we searched for "low-state" objects, which we defined as objects within our sample that had a spectrum well fitted by a simple absorbed power law, and "high-state" objects, which we defined as objects better fitted by a combined blackbody and a power law. Assuming that low-state objects accrete at approximately 10% of the Eddington luminosity (as found by Done & Gierlinski) and that high-state objects accrete near the Eddington luminosity, we further divided our sample of sources into low- and high-state ULX sources. We classify 16 sources as low-state ULXs and 26 objects as high-state ULXs. As in Galactic BH systems, the spectral indices, Γ, of the low-state objects, as well as the luminosities, tend to be lower than those of the high-state objects. The observed range of blackbody temperatures for the high state is 0.1-1 keV, with the most luminous systems tending toward the lowest temperatures. We therefore divide our high-state ULXs into candidate IMBHs (with blackbody temperatures of approximately 0.1 keV) and candidate stellar mass BHs (with blackbody temperatures of approximately 1.0 keV). A subset of the candidate stellar mass BHs have spectra that are well fitted by a Comptonization model, a property similar to Galactic BHs radiating in the "very high" state near the Eddington limit.
The fine structure of 321 avoiding involutions

We study the involutions belonging to the class of 321 avoiding permutations. We calculate the algebraic generating functions of the set containing the involutions avoiding 321 and of some of its subsets. Precisely we determine the algebraic generating functions of the involutions that are expansions of 12, of those expansions of 21, of the simple ones and of their expansions. The graphics of the simple involutions are caracterized. Being the simple involutions avoiding 321 counted by Riordan's numbers, a combinatoric interpretation of the results is illustrated through a class of Motzkin paths. Another interpretation is given through Dyck paths.
Supervised learning and systems with excess degrees of freedom

WHEN DISTINCT OUTPUTS OF AN ADAPTIVE SYSTEM HAVE EQUIVALENT EFFECTS ON THE ENVIRONMENT, THE PROBLEM OF FINDING APPROPRIATE ACTIONS GIVEN DESIRED RESULTS IS ILL-POSED. FOR SUPERVISED LEARNING ALGORITHMS, THE ILL-POSEDNESS OF SUCH "INVERSE LEARNING PROBLEMS" IMPLIES A CERTAIN FLEXIBILITY---DURING TRAINING, THERE ARE IN GENERAL MANY POSSIBLE TARGET VECTORS CORRESPONDING TO EACH INPUT VECTOR. TO ALLOW SUPERVISED LEARNING ALGORITHMS TO MAKE USE OF THIS FLEXIBILITY, THE CURRENT PAPER CONSIDERS HOW TO SPECIFY TARGETS BY SETS OF CONSTRAINTS, RATHER THAN AS PARTICULAR VECTORS. TWO CLASSES OF CONSTRAINTS ARE DISTINGUISHED---`CONFIGURATIONAL'' CONSTRAINTS, WHICH DEFINE REGIONS OF OUTPUT SPACE IN WHICH AN OUTPUT VECTOR MUST LIE, AND `TEMPORAL'' CONSTRAINTS, WHICH DEFINE RELATIONSHIPS BETWEEN OUTPUTS PRODUCED AT DIFFER- ENT POINTS IN TIME. LEARNING ALGORITHMS MINIMIZE A COST FUNCTION THAT CON- TAINS TERMS FOR BOTH KINDS OF CONSTRAINTS. THIS APPROACH TO INVERSE LEARN- ING IS ILLUSTRATED BY A ROBOTICS APPLICATION IN WHICH A NETWORK FINDS TRA- JECTORIES OF INVERSE KINEMATIC SOLUTIONS FOR MANIPULATORS WITH EXCESS DEGREES OF FREEDOM.
Finite‐level uniformly quantized learning control with random data dropouts

In this study, a quantized iterative learning control method with an encoding–decoding mechanism is investigated for networked control systems with constrained transmission bandwidths and random data dropouts at both the measurement and actuator sides. The intermittent update principle is used to address the problem of data asynchronism caused by two‐sided data dropouts. Then, a new “process” concept is introduced for the convergence analysis. The input sequence is guaranteed to achieve asymptotic zero‐error convergence to the unknown desired input for the given reference through an appropriate selection of scaling sequences. Furthermore, the quantization errors are shown bounded, where the upper bounds of the quantization level are precisely determined for selecting a finite‐level uniform quantizer. To verify the proposed scheme, an example of a permanent magnet linear motor is simulated.