Miracle-dz/UniFAR-FTUs huggingface dataset:
Evaluation of the Effect of Investment on Future Performance Considering the Level of Firm Financial Constraint

The effects of investment on firm performance depends on several factors. One of the most important factors is firm financial constraint. This study aimed to investigate the effect of investment on firms’ future profitability and buy-and-hold market adjusted returns considering the level of firm financial constraint. For statistical analysis in this study, multiple regression models were used. The firm financial constraint was measured using ordered logit regression. This research has been conducted on 120 listed companies in Tehran Stock Exchange based on data mentioned in financial annual reports between2008–2014. Results indicated different effects of investment on future profitability in constraint firms in comparison to non-constraint firms. These findings largely concur with theoretical background. However, no evidence could be found for different effects of investment on future buy-and-hold market adjusted stock return in constraint and non-constraint
Numerical suppression of the twin image in in-line holography of a volume of micro-objects

We address the twin-image problem that arises in holography due to the lack of phase information in intensity measurements. This problem is of great importance in in-line holography where spatial elimination of the twin image cannot be carried out as in off-axis holography. A unifying description of existing digital suppression methods is given in the light of deconvolution techniques. Holograms of objects spread in 3D cannot be processed through available approaches. We suggest an iterative algorithm and demonstrate its efficacy on both simulated and real data. This method is suitable to enhance the reconstructed images from a digital hologram of small objects.
Genetic Analysis Of Specialized Tumor Associated Macrophages And Tumor Associated Fibroblast

ii Tumor associated macrophages (TAMs) perform various task that are essential for tumor growth, angiogenesis, metastasis, and tumor invasion. Growth factors, chemokines, cytokines and the extra cellular matrix in the tumor microenvironments signal the TAMs to perform these tasks. The tumor microenvironment is not homogeneous and can be classified into several distinct regions such as sites of tumor invasion, perivascular, hypoxic and stromal regions. Each of these sites likely has different cytokines and signaling molecules in their microenvironment that might signal and direct the function of TAMs. The purpose of this project is to isolate and analyze TAMs from distinct tumor regions to gain a better understanding of the mechanism behind the specialized role of these TAMs. As a first step towards this goal, micro array analysis was conducted on flow sorted TAMs and developmental macrophages expressing yellow fluorescence protein (YFP). Micro array data from age matched developmental macrophages was compared to TAMS from early, premalignant stage of breast cancer, and late stage metastatic breast cancer to find the genes which were upregulated in TAMs versus developmental macrophages, and in late stage TAMs versus TAMs from the earlier premalignant stage of breast cancer. From this list of genes upregulated in TAMs, candidate cell surface macrophage markers that could be used to classify TAMs based on there association with one of the distinct tumor microenvironments was selected. These candidate markers will be used to visualize macrophages associated with different regions within the tumor microenvironment using immuno-staining of tumor sections. In preliminary work, CD16 was selected as one potential candidate gene that was upregulated late in tumor development compared to earlier stages. Immunostaining indicated CD16 was expressed on a set of macrophages near blood vessels near the tumors, but not in macrophages located within tumors. Further evaluation of these markers would facilitate isolation of different subsets of macrophages within tumor and understanding the function of these macrophages in tumor microenvironment. Another major cell group involved in all the changes in the tumor microenvironment discussed is the fibroblast. Originally the fibroblast inhibits the growth of the tumor. However through natural selection tumors evolve to change the microenvironment and like wise the function the fibroblast are performing to aid in tumor progression rather than suppress tumor progression. These fibroblast reprogrammed by the tumor cells are called tumor associated fibroblast TAFs. TAFs aid in tumor progression by angiogenesis, immune suppression, and matrix remodeling, providing growth and anti apoptotic factors and aid in metastasis by recruiting TAMs. A key gene involved with this is IKK. It is our hypothesis that ablating IKK in the fibroblast will lead to a reduction of tumor growth.
Human-Machine Real-Virtual Haptic Interaction Systems

This paper describes preliminary versions of two human-machine real-virtual haptic interaction systems: a unilateral real-virtual teleoperation system, and a simple bilateral haptic game. Both applications were designed and implemented by computer engineering undergraduate students in collaboration with their teachers. The main objective of this work was to create a basis system that permits to evaluate the effects of force feedback in applications involving interaction between human operators and virtual environments.
Comparison of Hamstring Flexibility between Patients with Chronic Lower Back Pain and the Healthy Individuals at the National Hospital of Sri Lanka

Introduction & Objectives: A back pain lasting more than 12 weeks has been defined as a chronic low back pain. It is one of the leading causes for functional limitations in adult population. Due to the anatomical origin and insertion of hamstring; the lack of hamstrings flexibility decreases pelvic mobility which may lead to development of low back pain. The main aim of this study was to compare hamstrings flexibility between the patients with chronic lower back pain and healthy individuals at the National Hospital of Sri Lanka. Methodology: Hospital based cross-sectional descriptive study was carried out with 100 participants; 50 patients with chronic low back pain and 50 age and gender matched healthy subjects with age between 40-60 years from National hospital of Srilanka. Active knee extension test was used to measure hamstrings flexibility. Results: Each group consisted of 50 subjects and 66% were females. Mean age of the patients with chronic low back pain was 50.08 ±5.18 years and mean age of the healthy people was 49.44 ±5.66 years. The mean hamstrings flexibility for all subjects with chronic low back pain was 152.630 ±3.74 for the right and 152.150 ±3.81 for the left. Mean values for right and left hamstrings flexibility of healthy group were 159.480 ±3.42, 159.330 ±3.07 respectively. Hamstrings flexibility of the patients with chronic low back pain were significantly lower than the hamstrings flexibility of healthy people (p<0.05). Conclusion: Hamstrings flexibility was significantly reduced among the patient chronic low back pain when compared to healthy individuals of same age and gender.
The usefulness of phonological information for the acquisition of grammatical structure in child language development

During the process of language development, one of the most important tasks that children must face is that of identifying the grammatical category to which words in their language belong. This is essential in order to be able to form grammatically correct utterances. How do children proceed in order to classify words in their language and assign them to their corresponding grammatical category? The present study investigates the usefulness of phonological information for the categorization of nouns in English, given the fact that it is phonology the first source of information that might be available to prelinguistic infants who lack access to semantic information or complex morphosyntactic information. We analyse four different corpora containing linguistic samples of English speaking mothers addressing their children in order to explore the reliability with which words are represented in mothers’ speech based on several phonological criteria. The results of the analysis confirm the prediction that most of the words to which English learning infants are exposed during
A physically based numerical approach for modeling fracture-matrix interaction in fractured reservoirs

Modeling fracture-matrix interaction within a multiple-phase flow system is a key issue for fractured reservoir simulation. Commonly used mathematical models for dealing with such interactions employ dual- or multiple-continuum concepts, in which fractures and matrix are represented as overlapping, different, but interconnected continua, described by parallel sets of conservation equations. The conventional single-point upstream weighting scheme is most commonly used to estimate flow mobility for fracture-matrix flow. However, such a scheme may have serious limitations or flaws, which lead to unphysical solutions or significant numerical errors. To overcome the limitations of the conventional upstream weighting scheme, this paper presents a physically based modeling approach for estimating physically correct relative permeability in calculating multiphase flow between fractures and the matrix, using continuity of capillary pressure at the fracture-matrix interface. The proposed approach has been implemented into two multiphase reservoir simulators and verified using analytical solutions and laboratory experimental data. The new method is demonstrated to be accurate, numerically efficient, and easy to implement in dual- or multiple-continuum reservoir simulators.
Acute toxicity of copper and chromium oxide nanoparticles to Daphnia similis

Copper oxide nanoparticles (CuO NPs) are employed in antifouling paints, and chromium oxide nanoparticles (Cr2O3 NPs) have been used as a green pigment. Their extensive use can contaminate aquatic ecosystems, and the toxicological effects of these NPs to the biota are poorly known. In this study, we evaluated the acute toxicity induced by CuO and Cr2O3 NPs, comparing with CuSO4 and Cr(NO3)3 as Cu2+ and Cr3+ ion source, respectively, using the microcrustacean Daphnia similis. The mean EC50-48h for CuO NPs was 0.064 mg L-1 and for CuSO4 was 0.015 mg L-1. CuO NPs tend to agglomerate, which may have reduced the release of Cu2+ in the test medium in relation to CuSO4.The mean EC50-48h for Cr2O3 NPs was 6.74 mg L-1 and for Cr(NO3)3 was 11.98 mg L-1. The reduced size of the Cr2O3 NPs (15-30 nm) and the higher zeta potential may have contributed to the higher stability in suspension and less potential for agglomeration, partially explaining the higher toxicity of NPs in relation to Cr(NO3)3. After the tests, we observed morphological damages such as increase in fat droplets, internal organ exposure and partially disintegration in organisms exposed to all tested substances, NPs or the salts.
Assembly of Layer-by-Layer Particles and Their Interactions with Biological Systems

Multilayered polymer particles with a wide range of properties can be precisely engineered via the layer-by-layer technique using a multitude of templates and materials. Such multilayered particles are emerging as a powerful platform for biomedical applications. In this short review, we provide an overview of developments in the engineering of multilayered polymer particles, and describe recent progress in their utilization in biological systems. Emphasis is placed on engineering strategies that achieve different biological objectives, ranging from triggered intracellular release of therapeutics to induction of protective immunity in vivo through particle-enabled vaccination. Finally, we provide a critical outlook of the key issues associated with the continued development of multilayered particles for biological applications.
4H‐SiC: a new nonlinear material for midinfrared lasers

Nonlinear optical (NLO) frequency conversion is commonly used for generating midinfrared (MIR) lasers that offer light sources for a variety of applications. However, the low laser damage thresholds of NLO crystals used so far seriously limit the output power of MIR lasers. Here, a new nonlinear material 4H‐SiC is demonstrated for producing MIR laser. Broadband MIR radiation ranging from 3.90 to 5.60 μm is generated in 4H‐SiC by phase‐matched difference‐frequency generation for the first time. The results may open a door to practically utilize wide‐bandgap semiconductors with high laser damage thresholds as NLO materials for high power output of MIR lasers.
Remediating Comprehension Deficits in Hyperlexia: The Scaffolding Interrogative Method

Children with severe reading comprehension deficits with no word recognition issues have traits associated with hyperlexia, which is advanced word recognition ability in children with language disorders. Scaffolding supports have been recommended for affected children they have difficulties in the formation and organization of schemata for processing information. The Scaffolding Interrogative Method (SIM) is a remediation strategy developed based on this recommendation. Post intervention results following six months of remediation indicated significant improvement in reading comprehension with a very large effect size for a sample of thirty-three subjects. Recommendations and limitations of the study are discussed for further research.
Exact stabilization of entangled states in finite time by dissipative quantum circuits

Open quantum systems evolving according to discrete-time dynamics are capable, unlike continuous-time counterparts, to converge to a stable equilibrium in finite time with zero error. We consider dissipative quantum circuits consisting of sequences of quantum channels subject to specified quasi-locality constraints, and determine conditions under which stabilization of a pure multipartite entangled state of interest may be exactly achieved in finite time. Special emphasis is devoted to characterizing scenarios where finite-time stabilization may be achieved robustly with respect to the order of the applied quantum maps, as suitable for unsupervised control architectures. We show that if a decomposition of the physical Hilbert space into virtual subsystems is found, which is compatible with the locality constraint and relative to which the target state factorizes, then robust stabilization may be achieved by independently cooling each component. We further show that if the same condition holds for a scalable class of pure states, a continuous-time quasi-local Markov semigroup ensuring rapid mixing can be obtained. Somewhat surprisingly, we find that the commutativity of the canonical parent Hamiltonian one may associate to the target state does not directly relate to its finite-time stabilizability properties, although in all cases where we can guarantee robust stabilization, a (possibly non-canonical) commuting parent Hamiltonian may be found. Beside graph states, quantum states amenable to finite-time robust stabilization include a class of universal resource states displaying two-dimensional symmetry-protected topological order, along with tensor network states obtained by generalizing a construction due to Bravyi and Vyalyi. Extensions to representative classes of mixed graph-product and thermal states are also discussed.
Human Age Estimation Techniques Using Facial Features

This paper summarizes different techniques used for estimating the age of a human being using face detection. There are several facial features that differentiate individuals from one another. These features vary with the growth of a particular person. So using these features we can estimate the age of an individual. Using face recognition and identification of facial features, there are several techniques for age estimation that are briefly described in this paper. so are their financial requirements. This article focuses on customer satisfaction towards the quality of services offered by various banks. A sample of 230 customers is taken for the survey using convenience sampling. A structured questionnaire is used to collect the data. Percentage analysis , chi-square and standard deviation are used to analyse the data. From the analysis it is found that most of the customers are satisfied with the services offered viz. Provision of savings account, ATM facility, different loans offered, online transaction facility, internet banking, sms facility etc. by the banks. However few customers expressed their dissatisfaction towards the credit card facility, too many formalities to issue a credit card, the credit period and credit limit
Livestock and Livestock Products and By-Product Trade in Ethiopia: A Review

In Ethiopia livestock are economic and social importance at household and national level in addition to significant contribution of export earnings. The country has at an advantageous position in production and possessing of different products and by-products due to high and diverse number of livestock as compared to other African countries. Pastoral area of the country is the sole supplier for both formal and informal live animal and meat exports. The livestock are marketed from the major producing areas reaches to the final consumer passing through complex channels along the supply chains involving various actors. Despite fluctuations over years, the formal exports of meat (7,717 to16, 500 tonnes) and live animals (163,000 to 680,000 head) have significantly increased in between 2006/7 and 2012/13. However, all most all live animals (85%) are exported illegally smuggled to neighbouring countries of Djibouti, Somalia, Kenya and the Sudan, using illegal trade routes and re-export to Middle East. Consequently, the Ethiopian government has lost substantial market share and foreign exchange. Lack of exporting routes and ports, illegal live animal trade, shortage of live animals and lack of appropriate breeding policy are some of the major challenges that hinder the smooth livestock trade of Ethiopia. Keywords: live animals, meat, trade
HOPF ALGEBRAS WITH ONE GROUPLIKE ELEMENT

Introduction. We are interested in the coalgebra structure of cocommutative Hopf algebras. Over an algebraically closed field a cocommutative Hopf algebra K with antipode is of the form H 0 r(G) (as a coalgebra) where r(G) is the group algebra of G the group of grouplike elements-elements of K where dg =g 0 g -and H is the unique maximal sub-Hopf algebra of K containing one grouplike element, namely 1. If the characteristic of the field is zero then H is isomorphic to the universal enveloping algebra of its primitive elements-elements where dx= 1 0 x + x 0 1-which form a Lie algebra. These results of Kostant prompt the present study of H when the characteristic is not zero. We do not insist the field be algebraically closed but merely that the unique simple subcoalgebra of our Hopf algebra is the 1-dimensional space spanned by the unit. In this case the subalgebra generated by the primitive elements is a restricted universal enveloping algebra but not necessarily the entire Hopf algebra. A necessary and sufficient condition for H to be primitively generated is that for all a' E H' (the dual to H which has a natural algebra structure) where = 0 then a'P= 0, p the characteristic of the field. When the field is perfect H modulo the left ideal generated by the primitives (the ideal is actually two
Kalman Normalization: Normalizing Internal Representations Across Network Layers

As an indispensable component, Batch Normalization (BN) has successfully improved the training of deep neural networks (DNNs) with mini-batches, by normalizing the distribution of the internal representation for each hidden layer. However, the effectiveness of BN would diminish with the scenario of micro-batch (e.g. less than 4 samples in a mini-batch), since the estimated statistics in a mini-batch are not reliable with insufficient samples. This limits BN's room in training larger models on segmentation, detection, and video-related problems, which require small batches constrained by memory consumption. In this paper, we present a novel normalization method, called Kalman Normalization (KN), for improving and accelerating the training of DNNs, particularly under the context of micro-batches. Specifically, unlike the existing solutions treating each hidden layer as an isolated system, KN treats all the layers in a network as a whole system, and estimates the statistics of a certain layer by considering the distributions of all its preceding layers, mimicking the merits of Kalman Filtering. On ResNet50 trained in ImageNet, KN has 3.4% lower error than its BN counterpart when using a batch size of 4; Even when using typical batch sizes, KN still maintains an advantage over BN while other BN variants suffer a performance degradation. Moreover, KN can be naturally generalized to many existing normalization variants to obtain gains, e.g. equipping Group Normalization with Group Kalman Normalization (GKN). KN can outperform BN and its variants for large scale object detection and segmentation task in COCO 2017.
Comparison of Collaborative Optimization to Conventional Design Techniques for a Conceptual RLV

Initial results are reported from an ongoing investigation into optimization techniques applicable to multidisciplinary reusable launch vehicle (RLV) design. The test problem chosen for investigation is neither particularly large in scale nor complex in implementation. However, it does have a number of characteristics relevant to more general problems from this class including 1) the use of legacy analysis codes as contributing analyses and 2) non-hierarchical variable coupling between disciplines. Propulsion, trajectory optimization, and mass properties analyses are included in the RLV problem formulation. A commercial design framework is used to assist data exchange and legacy code integration. The need for a formal multidisciplinary design optimization approach is introduced by first investigating two more conventional approaches to solving the sample problem. A rather naive approach using iterative sublevel optimizations is clearly shown to produce non-optimal results for the overall RLV. The second approach using a system-level response surface equation (RSE) constructed from a small number of RLV point designs is shown to produce better results when the independent variables are judiciously chosen. However, the response surface method (RSM) approach cannot produce a truly optimum solution due to the presence of uncoordinated sublevel optimizers in the three contributing analyses. Collaborative optimization (CO) appears to be an attractive multidisciplinary design optimization approach to solving this problem. Initial implementation attempts
Forecasting Volatility Stock Return: Evidence from the Nordic Stock Exchanges

The purpose of this study is to explore the volatility and secondary effects in the four Nordic stock exchanges of Norway: Oslo B? rs Linked all-share index AXLT Denmark: OMX Copenhagen 20, Sweden: OMX Stockholm 30 and Finland: OMX Helsinki 25. Keeping in mind that there is an ARCH effect in the returns of the four stock exchanges, we move on to the evaluation to the evaluation of models ARCH (q), GARCH (p, q) kai GARCH-M (p, q). Evaluating the parameters became possible through the use of the maximum likelihood method using the BHHH algorithm of (Berndt et al., 1974) and the three distributions (normal, t-Student, and the Generalized normal distribution GED). The results of this study indicate model ARMA(0,1)-GARCH-M(1,1) with t-student distribution as the appropriate one to describe the returns of the all Nordic stock exchanges except that of Sweden, where model ARMA(0,3)-GARCH-M(1,1) describes it best. Lastly, for forecasting the models ARMA(0,1)-GARCH-M(1,1) and ARMA(0,3)-GARCH-M(1,1) of the current stock exchanges we use both the dynamic and static process. The results of this study indicate that the static process forecasts better than the corresponding dynamic.